5,018 Matching Annotations
  1. Nov 2024
    1. T h u s whentwo p e rso n s in c o n v e r s a tio n are a tte m p tin g to d isc o v e r howca re fu l they a re going to have to be about s ta tin g th e ir truep o litic a l o pinion s, one of them ca n halt h is gradual d is c lo s u r eo f how far left or how far right he is ju s t a t the point wheret h e o th e r h a s come to th e f u rth e s t extrem e o f his a c tu a l b eliefs

      act like extent of beliefs is minimal of other person's is mini,a;

    2. h is u nofficial com munication may beca rrie d on by innuendo, mim icked a c c e n t s , w ell-placed jo k e s,s ig n ific a n t p a u s e s , v e ile d h in ts , purposeful kidding, e x p r e s s iv eov erto n e s, and many other sig n p r a c tic e s . R u le s regardingth is laxity a re quite s tr ic t. T he com m unicator h a s the right todeny th a t h e ' m e a n t a n y t h i n g 1 by h i s ac tio n , sh o u ld h isr e c ip ie n t s a c c u s e him to his f a c e of h av ing co n v e y ed som ethingu n a c c e p ta b le , and th e r e c ip ie n t s have th e right to a c t a s ifnothing, or only som ething in n o c u o u s, h a s been conveyed.In many kinds of s o c ia l in te r a c tio n , unofficial com municationp rovides a way in which o n e team can ex ten d a defin ite but noncom prom ising in v itatio n to th e other, r e q u e s tin g that s o c ia ld is t a n c e and formality be i n c r e a s e d or d e c r e a s e d , or th a t bothte am s sh ift the in te ra c tio n to one involving the perform anceof a new s e t of r o le s

      unofficial communication- communication that always has potential to be denied, works to communicate and test relations between two teams communicate roles, how the intimacy of relationships should be- communicate boundaries, etc.

    3. So, too, em p loyeeswill often grim ace a t their b o s s , or g e s t i c u l a t e a sile n t c u r s e ,performing t h e s e a c t s of contem pt or insub ord ination at ana n g l e s u c h th a t th o s e to whom t h e s e a c t s are directed c a n n o ts e e them. P e r h a p s th e most timid form of th is kind of c o llu s io ni s found in th e pra c tic e of ' d o o d l i n g 1 or of ‘ going a w a y ’ toim aginary p l e a s a n t p la c e s , w hile still m aintaining som e showof performing the part of lis te n e r

      derisive collusion- done by performer and hidden from higher-ups , for the performers own purpose

    4. P e r h a p s one o f the n o t e s in th e pi anoforte harmonyi s the very no te that the sing er s h o u ld be s in gin g , and so he m a k e st h i s n o te pred o m inate. When t h i s a c t u a l n o te i s n o t writcen in thepiano fo rte p a r t , he must ad d it in the tr e b l e c l e f , where it will p ip eloud a n d c l e a r foe the s i n g e r to hear.

      pianist highlights a note that singer should be singing

    5. Sometimes membersof the a u d ie n c e are referred to not even by a s lig h tin g namehut by a code ti t l e which a s s i m i l a t e s them fully to an a b s tr a c tca te g o ry . T h u s d o c to rs in the a b s e n c e of a p a tie n t may referto him a s ‘ the c a r d i a c ’ or ' t h e s t r e p ; ’ barb ers privately referto th e ir c u s to m e r s a s ' h e a d s of h a i r

      other is downplaying of politeness or name calling

    6. h e y very regularly d erogatethe a u d ie n c e in a way th a t i s in c o n s i s t e n t with the ( ac e-to -fac etreatm ent th a t i s given to the au d ien c e. In s e r v ic e tra d e s ,for example, c u s to m e r s who are tr e a te d r e sp e c tf u lly duringthe perform ance a re often ridiculed, g o s s i p e d abo ut, c a r ic a tu r e d ,c u rse d , an d c r it ic iz e d when the performers are b a c k s t a g e ;here, too, p la n s may be worked out for ' s e l l i n g ’ them, orem ploying ' a n g l e s ’ a g a i n s t them, o r pac ify in g t h e m .

      first type- trash talking audience

    7. It may be r e p e a te dth a t no claim i s made th a t s u r re p tit io u s c o m m u n ic a tio n s areany more a r e fle c tio n of the re a l r e a lity than a re the o fficialco m m unication s with which they are i n c o n s i s t e n t ; the pointi s th a t th e perform er i s ty p ic a lly involved in both, and th isdual inv olvem ent must b e carefu lly m anaged l e s t o ffic ia lp r o je c tio n s be d i s c r e d ite d .

      !!! its not a reality and a deviation- there is an active participation in both as forming a sort of whole reality

    8. R e n e g a d e s often take a moral sta n d , s a y in g that it isb e tte r to be tr u e to the id e a ls of the role th a n to the performerswho f a ls e ly p re se n t th e m s e lv e s in it. A d iffe ren t mode ofd isa ffe c tio n o c c u r s when a c o lle a g u e " g o e s n a t i v e ’ or becom esa b a c k slid e r, making no attem pt to m aintain th e kind of frontwhich h is auth o rized s t a t u s m a k es or le a d s h is c o l le a g u e sand th e au d ien c e to e x p e c t of him. Such d e v i a n ts a re s a id to' l e t down the s i d e . ’

      colleagues let colleagues down when don't retain secretive info

    9. r a i n i n g s p e c i a l i s t . ’ In d iv id u a ls who tak eth is role have the com plic ate d t a s k of te a c h in g the performerhow co build up a d e s ir a b le im p re ssio n w hile at the sametime taking the part of the future a u d ien c e and illu stratin gby p u n ish m en ts th e c o n s e q u e n c e s o f im proprieties

      training specialists - role of building up performer requires them to imagine perspective of audeince

    10. individual involved in u nseem ly e n ta n g le m e n ts may ta k eh is tr o u b le s to a Negro law yer b e c a u s e of the sham e he mightle e l before a w hite one

      what does that have to do with... anything

    11. S ervices p e c i a l i s t s are lik e mem bers of the team in th at th e y learnth e s e c r e t s o f the show and o b ta in a b a c k s ta g e view of it.

      service specialists attend to front stage but often, must obtain backstage view and destructive information to do their job

    12. In suchs it u a ti o n s , the important show i s to show the o u tc a s t th a the i s b eing ignored, and the a c tiv ity th at i s c a r rie d on ino rd er to d e m o n strate t h is may i t s e l f be o f second aryim portance

      ignoring someone is a performance of itself

    13. uiding the sho w on thefactory floor on b e h a lf of th e m an agerial a u d ien c e, but hem ust a l s o t r a n s l a t e what he k n ow s and what the a u d ien c es e e s into a verbal lin e which h i s c o n s c ie n c e and the a u d ien c ewill be w illing to a c c e p t

      foreman must maintain mindset of audience as well as performance director

    14. p eak e rstend to a c c e p t in v it a ti o n s to s p e a k on the a s su m p tio n thatth e chairm an will ' t a k e care of them ,' which he d o e s bybeing the very model of a li s t e n e r and thoroughly confirmingt h e notion th a t the s p e e c h h a s real s ig n ific a n c e . T h e c h a irman’s perform ance i s e ffec tiv e partly b e c a u s e the l i s t e n e r shave an ob lig a tio n to him, an o b lig a tio n to confirm anydefin ition o f the s it u a ti o n which he spo nsors, an ob lig a tio n ,in short, to follow the lis te n in g -lin e th a t he ta k e s .

      go-between example that's having a negative connotation chairman showing active listening skills to encourage audience. Offers direction to audience while providing encouragement to speakers? I kind of don't get how this differs from a regular shill

    15. T he a u d ie n c e knowwhat th e y have been allow ed to p erc eive , q u alified by whatthey can g le an u n o ffic ia lly by c l o s e o b se rv a tio n

      audience knows what theyve been allowed to percieved

    16. In sid e s e c r e t s give o b je c tiv e in te lle c t u a l conten tto s u b j e c t i v e l y felt s o c ia l d i s t a n c e . Almost all informationin a s o c ia l e s ta b l is h m e n t h a s som e thing of this e x c lu sio n aryfunction and may be s e e n a s none of som ebody’s b u s in e s s

      inside secrets- objective intellectual content

    17. It may be addedth a t s e c r e t s th a t a r e merely s tr a t e g ic tend to be ones whichthe team e v e n tu a lly d i s c l o s e s , perforce, when ac tio n b a s e dupon s e c r e t p r e p a ra tio n s i s consum m ated, w h e r e a s an effortmay be made to keep dark s e c r e t s s e c r e t forever

      second type of secrets are strategic secrets- things hidden for sake of performance. Still hold a lot of weight and should appear that they don't exist- but in a way could be disclosed eventually.

      Strategies against opposition

    18. A b a s ic problem for many perform ances, then,i s that of information c o n tro l; the a u d ien c e must not acquired e s tru c tiv e information ab o u t the situ a tio n that is beingdefined for them. In o th e r words, a team must be able tokeep i t s s e c r e t s and have its s e c r e t s kep

      team must be able to keep secrets- some information is destructive for audience to learn

      • work example- cooking corn dog
    19. And, on the sa m e grounds, just;is it is co n v e n ie n t to play o n e 's different ro u tin e s beforelifferent p e r so n s, so a l s o is it convenient to s e p a r a te thedifferent a u d i e n c e s one h a s for the sam e routine, s i n c e thati s th e only way in which each a u d i e n c e can feel th a t whilethere may be o th e r a u d i e n c e s for the sam e rou tine, none isg e ttin g so d e s ir a b le a p r e se n ta tio n o| it. Here again frontregion control is important

      makes it easier to put on right performance for each person if different audiences are separated/ don't see other sides

      I HATE MIXING FRIEND GROUPS

    20. hus the higher o n e’s p la c e in the s t a t u s pyramid,th e sm a lle r the number of p e rs o n s with whom one can befamiliar, 1 the l e s s tim e one sp e n d s b a c k sta g e , and th e mor

      higher up someone the less the spend backstage

    21. Often it s e e m s th a t w hatever e n th u sia smand lively in te r e s t we have at our d i s p o s a l we r e s e rv e fort h o s e before whom we are putting on a show and th a t thes u r e s t sig n of b a c k s ta g e s o lid a rity is to feel th a t it is sa feto l a p s e into an a s s o c i a b l e mood of su llen , sile n t irritability

      while backstage is more relaxed and informal- doesn't make it more happy or care free - often all enthusiasm goes to what is done in front of audience and backstage is sullen

    22. F irs t, we often find th a t control of b a c k s ta g e p la y s asig n ific a n t role in th e p r o c e s s of 'w o rk c o n t r o l ’ wherebyl de Beauvoir, op. c i L , p. 54 J.70

      performance often relies on the backrooms and the privacy of them

    23. S econdly, the d irec tor may be given the s p e c ia l duty ofa l lo c a tin g th e p a r ts in the perform ance and the personal frontthat i s em ployed in ea ch part, for each e s ta b lis h m e n t maybe s e e n a s a p la c e with a number of c h a r a c t e r s to d is p o s eo f to p r o s p e c tiv e performers and a s an a s s e m b l a g e of signequipment or cerem onial p ara p h ern alia to be a llo c a te d

      gives roles and sets the stage

    24. i r s t , th e direc to r may be given th e s p e c i a l duty of bringing baclc into line any member of the team w hose perform ancebecom es u n s u ita b le

      keep performers in line with performance

    25. In many im portant s o c i a l s it u a ti o n s ,how ever, th e s o c ia l s e ttin g in w hich the in te ra c tio n o c c u rsis a s s e m b l e d and m anaged by one of the t e a m s only, andc o n t r i b u te s in a more intim ate way to the show th is teamp u ts on than to thfe show put on in r e s p o n s e by the otherteam.

      while audience and performer can always apply to both teams, many instances where one team has more control, vested interest, and more intimately organizes performance - salesperson

    26. T h u s, in larges o c ia l e s ta b l is h m e n ts , where se v e ra l different s t a t u s grade sprevail, we find that for the duration of any particular interaction, p a r ti c ip a n ts of many d ifferent s t a t u s e s are ty pic allye x p e cted to alig n th e m s e lv e s temporarily into two team groupi n g s.

      when many different status available- very frequently to performers sort themselves into two performance groups

    27. And, of c o u r s e , this kind of s o lid a rityin the p r e s e n c e o f s u b o r d in a t e s a l s o o c c u rs when perform ersa re in the p r e s e n c e of su p e ro r d in a te s

      solidarity in performance always focused on putting up front in front of subordinates

    28. T o withhold froma te aii-m a te information about the s ta n d h is team i s takingi s to w ithhold his c h a r a c te r from him, for without knowingwhat sta nd he will be ta k in g he may not be a b l e to a s s e r t as e lf to th e au d ien c e

      withholding information from teammate = withholding identity

    29. It se e m s to be g enerally felt th a t pub lic d isa g re em entamong the members of the team not only in c a p a c i t a t e s themlor united action but a l s o e m b a r ra s s e s the r e a lity spo nso redby the team. To protect th is im pre ssion of rea lity, membersof the team may be required to postpon e taking public s ta n d suntil the p o sitio n of th e team has been s e t t l e d ; and oncethe te am ’s sta n d h a s been tak en, all members may be obligedto follow it.

      to maintain united front- team members wait until not in public to disagree

    30. O ther m eansto e n d s , s u c h a s fo rce o r b arg a in in g power, may be in c r e a s e dor d e c r e a s e d by s t r a t e g i c m a n ipula tion of im p r e s s io n s , butt h e e x e r c i s e of f o rc e or barg a in in g pow er g iv e s to a s e t ofin d iv i d u a l s a s o u r c e of group formation u n c o n n e c te d withthe fact th a t on c e r ta in o c c a s i o n s t h e group th u s formed i sl i k e l ^ t o a c t, d r a m a tu r g ic a lly sp e a k in g , a s -a te am

      huh

    31. Similarly, agirl a t a party who is flagrantly a c c e s s i b l e may be sh unnedby th e other g irls who a r e p r e s e n t, but in c e r ta in m a tte rs sh eis part of th e ir team and c a n n o t fail to th rea ten the d efin itio nthey are c o l le c tiv e ly m a in ta in in g th a t g ir ls a re d ifficu lt s e x u a lp r iz e s .

      great example- team members can't always easily be disposed of

      individual behavior becomes a reflection of everyone when in this case, they're not even friends or allied

    32. h i s p o s s i b i l i t y l e a d s u s to c o n s id e r a further o n e. T h eind iv id u al may p r iv a te ly m aintain s t a n d a r d s of b ehaviour whichhe d o e s not p e r s o n a lly b e l ie v e in, m a in ta in in g t h e s e s t a n d a r d sb e c a u s e of a liv e ly b e l ie f that an u n s e e n a u d i e n c e i s p r e s e n twhich will p u n ish d e v i a ti o n s from t h e s e s ta n d a r d s . In o th e rwords, an ind iv id u al may be h i s own a u d i e n c e or may im a g in ean a u d i e n c e to be p r e s e n

      The audience doesn't even need to be other people- it can be an imagined outward judgement or assessment of action that directs a performance when no one is looking

      that one Margaret Atwood quote

    33. Given t h i s point of refe re n c e ,it i s p o s s i b l e to a s s i m i l a t e su c h s i t u a t i o n s a s tw o-personi n te r a c tio n into th e framework by d e s c r ib in g t h e s e s i t u a t i o n sa s tw o-team in te ra c tio n in w hich ea ch team c o n t a i n s only o n emember

      can look at every coordinated performance as teams if in one-on-one each team only has one member

    34. hen o u t s i d e r s ace p r e s e n t , th e to u ch o( b u s i n e s s l i k e formality i se v e n more im portant. You may c a l l your s e c re ta ry ' M a r y ' a n d y o u tp a r t n e r ' J o e * all d ay , bu t when a str a n g e r c o m es inn) your office yoush ou ld t efet to your a s s o c i a t e s a s you would e x p e c t the s t r a n g e r toa d d r e s s t h e m : M is s or Mr- You may h av e a r u nn ing jo k e w i t h thesw it c h b o a rd o p e r a t o r, but you let :t ride when you ar e p l a c i n g a callin an o u t s i d e r ' s h e a r in

      like teachers switching up and calling each other "Ms. -----" in front of students

    35. B ut m ost im po rtant o f a ll, we commonly find that th e d efin ition of t h e s it u a ti o n p r o je c te d by a p a r ti c u la r p a r tic ip a n t i san in te g ra l p art o f a p ro je c tio n th a t i s f o s te r e d and s u s t a in e dby t h e in tim a te c o -o pe ra tion of more than o n e p a rtic ip a n t,and, m oreover, that ea ch member o f suc h a tro u p e or c a s tof p la y e r s may be req u ired to a p p e a r in a different light ifth e te a m ’ s o v e ra ll effec t i s to be s a t i s f a c t o r y .

      oftentimes- the performance requires participants who perform roles which require adopting demeanor's

    36. With s u c hs t r a t e g i c a l l y lo c a te d p o i n t s of r e ti c e n c e , it i s p o s s i b l e tom aintain a d e s ir a b le status quo in the r e la tio n s h ip w ithouth a v in g to ca rry out rigidly th e im p l ic a tio n s of t h i s ag re e m e n tin all a r e a s of life

      One can maintain a status quo without rigid adherence to all demands of performance in the relationship

    37. Although p a r ti c u la r p erfo rm an ce s,a n d even p a r t i c u l a r p a r t s or r o u tin e s , may p l a c e a perform erin a p o sitio n of h aving nothing to h id e , so m ew here in thefull round of h is a c t i v i t i e s th e re will b e so m e th in g h e c a n n o tt r e a t o p e n ly

      almost always there are things someone cannot openly address within performance

    38. We find th at c h a r la ta n p ro fe s s io n a l a c tiv ityo f o n e d e c a d e b ec o m e s an a c c e p t a b l e le g itim a te o c c u p a tio nin th e next. 3 We find th a t a c t i v i t i e s which a r e thought tobe l e g itim a te by so m e a u d i e n c e s in our s o c ie ty are thoughtby o th e r a u d i e n c e s to be r a c k e ts

      what is a lie and what is legitimate all highly flexible, temporally and culturally informed

    39. F u rth e r, in e v e ry d ay li f e it i s u s u a l l y p o s s i b l e forthe perform er to c r e a te in te n tio n a lly a lm o st any kind o f f a l s eim p re ssio n without pu ttin g h im s e lf tn th e in d e f e n s ib le p o sitio no f having told a c l e a r - c u t lie . Com m unication t e c h n iq u e ssuch a s innuendo, s t r a t e g i c am bigu ity, an d crucial o m is s io n sa llow th e m isinform er to profit from l i e s w ithout, te c h n ic a l ly ,te llin g any

      A lot of ways to lie without directly lying, yet, "bare-faced" lies are the ones with all the consequences

    40. la im s tob e a law g r a d u a te ca n b e e s t a b l i s h e d a s valid or invalid, butc laim s to be a friend, a true b e lie v e r, or a m usic lo v e r can beconfirmed or d isc onfirm ed only m o re-o r-le ss.

      line is more blurred where claims to be something have less tangible means of legitimating

    41. We often feel that it i s ju s t t h e s e te rrib le ev e n tu a l i t i e s , which a r i s e from being c a u g h t out, flagrante delicto,in a p a t e n t a c t o f m is re p re s e n t a ti o n , th a t an h o n e s t perform eri s a b l e t o avo id . T h i s c o m m o n -se n se view h a s lim ite d a na l y t i c a l u tility .

      in our heads- a true or honest performer- would not mess up. Assumption that there IS an honest performer or someone who embodies something without a need for front. This view isn't analytically very applicable

    42. s h e s t r i v e s ro identify h e r s e l f with t h i s figure an dt h u s to se em t o h e r s e l f to be s t a b i l i z e d , j u s t i f i e d in her sple n do r

      identification with a figure- not with oneself

    43. A c e r ta in b u re a u c ra tiz a tio n of thes p i r i t i s e x p e c t e d s o that we can be relied upon to give ap e rfe c tly h o m o g e n e o u s perform ance at every ap p o in te d time.A s S a n ta y a n a s u g g e s t s , t h e s o c i a l i z a t i o n p r o c e s s not onlytr a n s f ig u r e s , it f i x e s

      we do not let or are expected not to allow momentary emotions to impact performance- should be homogenous

    44. It h a s b e e n s u g g e s te d th a t th e perform er c a n rely uponh is a u d ie n c e to a c c e p t minor c u e s a s a sign of som ethingim portant about h i s perform ance. T h i s c o n v e n ie n t fa c t h a s anin c o n v e n ie n t im plica tio n . By v irtu e of th e same sig n -ac ce p cin gten d en c y , th e a u d ie n c e may m is u n d e r s ta n d th e m eaning th a t ac u e w a s d e s ig n e d to con vey, or may r e a d an e m b a rra ssin gm eaning into g e s t u r e s or e v e n t s that were a c c i d e n t a l , ina d v e r te n t, in c id e n t a l or not meant by the perform er co carryany m eaning w h ats o ev e r

      takes very little to signal this meaning- susceptible to misinterpretation

    45. In our com m ercial lif e t h i s c h a r a c t e r i s t i co f p e rfo rm a n c e s h a s b een e x p lo ite d a n d maligned u nder th erubric ' p e r s o n a l i z e d s e r v i c e ; ’ in o th e r a r e a s of life we makej o k e s about ' t h e b e d - s id e m a n n e r ’ o r ' t h e g la d h a n d .

      often beneficial for actor to downplay routinization of actions- act like that interact is special, personal, meaningful, etc.

    46. S im ilarly, m edical s c h o o l s in Am erica te n d torec ru it th eir s t u d e n t s partly on the b a s i s o f e t h n i c orig in s,an d c e r ta in ly p a t ie n t s , c o n s id e r t h i s fac to r in c h o o s in g th e ird o c t o r s ; but in t h e a c tu a l in te r a c t io n betw e en d o c to r andp a tie n t the im p re ssio n i s a l lo w e d to d e v e lo p that th e d o ctori s . a d octor b e c a u s e o f s p e c i a l a p t i t u d e s a s well a s s p e c ia ltraining .

      both med schools and patients act like they choose doctors on aptitude and training as opposed to ethnic origins

    47. clergym en g iv e th e im p re ssio n th a t they e n te r e d th e churchb e c a u s e o f a c a ll o f fe lt v o c a tio n , in America te nding toc o n c e a l th e ir i n t e r e s t in moving up s o c i a l l y , in B rita in te ndingto c o n c e a l th e ir i n t e r e s t in not moving to o far down

      conceal motives that break idea of what a "good" clergymen should do

      Can you be a good clergymen and still wish to progress socailly?

    48. Reinforcing t h e s e id e a l i m p r e s si o n s we find a kin d of ' r h e t o r i c of tr a in in g ,' w hereby labourunions, u n i v e r s i t i e s , tr a d e a s s o c i a t i o n s , and o th e r l i c e n s in gb o d ie s re q u ire p r a c t i t i o n e r s to a b s o rb a m y s t ic a l rang e andp e rio d of train in g , in p a rt to maintain a monopoly, but inpart to f o s te r th e im p r e s s io n th a t th e l i c e n c e d p r a c titio n e ri s som eone s e t a p a r t from o th e r me

      training extensive to five image that they are set apart

    49. In a s e n s e su c h i m p r e s s i o n s a re i d e a li z e d , too, for if th eperform er i s to b e s u c c e s s f u l h e m u st offer th e kin d of s c e n eth a t r e a l i z e s t h e o b s e r v e r s ’ extrem e s t e r e o t y p e s o f h a p l e s spov erty

      never a performance about bettering or reflecting what is really there, people embody identities for a certain result

    50. not in d iv id u a ls , but a l s o a so n e in w hich p e rf o rm a n c e s te n d to e s t a b l i s h favourable c l a i m sre g a rd in g n o n-m aterial v a l u e s

      Indian caste system allows for social movement in non-material gains (by adopting certain belief systems and practices) which re-centers the lower classes around the practices that allow for them to be upwardly mobile

    51. h e p ro p e r s ig n -eq u ip m en t h a s bee n o b ta in e d and fam iliarityg a in e d in t h e m an ag e m en t of it, then t h i s equipm ent c a n beu s e d to e m b e llis h and illu m in e o n e ’s daily p e rfo rm a n c e s w itha fa v o u r a b le s o c ia l s ty le

      minimal separation between the status and the front- Here, Goffman doesn't distinguish something like yearly income attaining status than the means to attain the front of a certain status

    52. T h e a r i s t o c r a t i c h ab it, •ith a s b een s a id , i s one th a t m o b il iz e s all t h e minor a c t i v i t i e s ofl i f e w hich fall o u t s i d e th e s e r io u s s p e c i a l i t i e s of o th e r c l a s s e sa n d i n j e c t s in to t h e s e a c t i v i t i e s an e x p r e s s io n of c h a r a c t e r ,pow er, and high rank

      some say aristocracy is injecting expressions of character into minor activities

    53. M erchan ts, too, often findth a t they must cha rge hig h p r i c e s for th in g s that look intrins i c a l l y e x p e n s iv e in order to c o m p e n s a te the e s ta b l is h m e n tfor e x p e n s iv e t h in g s lik e in s u r a n c e , s la c k p erio d s, e tc ., thatnever a p p e a r before th e c u s to m e rs ’ e y

      merchants overcharge for things that look expensive (are in which to role of money is dramatically fulfilled) so that they can pay for what costs but is not dramatic

    54. he n u r s e s a r e “ w a s t i n g r i m e 0 u n l e s s they a r e d a r t i n g ab ou td oin g so m e v i s i b l e t h i n g s u c h a s a d m i n i s t e r i n g h y p o d e r m i

      issue- exists a nonbelief in other people that are doing fulfilling their role unless they see a dramatized representation of the task

    55. D ental Corp’s c a p t a i n s , many of them of a tow e th n ic origin,c ou ld h a v e b e e n g iv e n a rank th a t would p e r h a p s hav e beenmore s u i t a b l e in the e y e s of t h e Army than the c a p t a i n c i e sthey w ere a c t u a l l y giv en

      issues of taks that are "between ranks" arise- in the instance of nurse and doctor it relates to the capability of the professional but also what is "right" for the position.

      Feels a but more about organization that social expectation tbh

    56. As a com prom ise, th e full ran g e of d iv e rs ity is cutat a few crucial p o in ts , and all t h o s e w ithin a given brac ketare allo w ed or o b lig e d to m a in ta in the sam e s o c ia l front ince r ta in s it u a t i o n

      diversification of society too vast- break up into distinct categories and provide based on those- allowing or forcing people to maintain social front

    57. A p p e a r a n c e ’ may be ta k e n to refer tot h o s e stim uli which function at th e tim e to tell u s of th eperform er’s s o c ia l s t a t u s e s . T h e s e stimuli also te ll u s o fth e i n d i v i d u a l 's tem porary ritu a l s t a t e , th a t i s , w hether he i se n g a g in g in formal s o c ia l a c tiv i ty , work, or informal re c re a tio n ,w h eth e r or not he is c e le b r a tin g a new p h a s e in the s e a s o nc y c le or in h is lif e -c y c le . ' M a n n e r ' may be ta k e n to refer toth o s e stim uli w hich fu n ction at the tim e to warn u s of th e intera c tio n ro le th e performer will e x p e c t to play in th e on-comings it u a ti o n .

      appearance are status and other identifications (can show things like what you do for work) Manner tells us of oncoming action within a persons role (what the person expects to happen or how others are to respond)

    58. ro n t, th e n , i s th e e x p r e s s i v e e quipm ent of as ta n d a r d kind i n t e n t io n a lly or unw ittin g ly em ployed by theind iv id u al during h is perform ance. F or p relim in ary p u r p o s e s , itv.ill be c o n v e n ie n t to d i s t i n g u i s h and la b e l what s e e m to be thesta n d aril p a r t s of fron

      Labeling- The "front" of the stage

    59. t h e s e a r e c y n i c a l perform ers w hosea u d i e n c e s will not a llow them to be s in c e r e . Similarly, we findth a t s y m p a th e tic p a t i e n t s in m ental w ards will s o m e tim e s feignb iz a r re sym ptom s so th a t s tu d e n t n u r s e s will not be s u b je c t e dto a d is a p p o in ti n g ly s a n e perform ance. 1 So a ls o , when inferi o r s e x ten d th e ir most la v is h r e c e p tio n for v i s i tin g s u p e rio r s ,th e s e l f i s h d e s i r e to win favour may not be the c h i e f m o tiv e;the inferio r may be ta c tf u lly attem p tin g to put the su p e rio r ate a s e by s im u la tin g the kind of world the s u p e r io r i s thought tota k e for gran ted

      there is often a demand to be insincere that the cynical performers, in their hyperawareness of the gap between reality and the performers, more willingly offer up this insincerity.

    60. It shou ld be u n d e rsto o d th a t th e c y n ic , witha ll h i s p r o f e s s io n a l d isin v o lv e m e n t, may o b ta in u n p r o fe s s io n a lp l e a s u r e s from his m a sq u e ra d e , e x p e r ie n c in g a kind of gleefuls p ir itu a l a g g r e s s io n from th e fac t that h e c a n toy a t will withsom ething h i s a u d i e n c e m ust ta k e s e r i o u s l y

      MMEEEE

    61. i s th a t th e i l l u s t r a t i o n s to g e th er fit into a co h e ren t framework that t i e s to g e th e r b i t s of e x p e r ie n c e the r e a d e r h a s a lre a d yhad and p r o v id e s th e stu d e n t with a guide worth t e s t i n g in c a s e -s t u d i e s ’of i n s t itu ti o n a l s o c ia l life

      ethnography vibes- iffy methodology but good theories?

    62. e s t a g e p r e s e n t s t h i n g s th a t are m a k e - b e lie v e ; p resumab ly life p r e s e n t s th i n g s th a t are rea l a n d s o m e tim e s not wellr e h e a r s e d .

      use the metaphor of the theater- presentation of oneself in response to presentation of others for an audience- world of make-believe

    1. Welcome back and in this demo lesson you're going to experience the difference that EFS can make to our WordPress application architecture.

      Now this demo lesson has three main components.

      First we're going to deploy some infrastructure automatically using the one-click deployments.

      Then I'm going to step through the CloudFormation template and explain exactly how this architecture is built.

      And then right at the end you're going to have the opportunity to see exactly what benefits EFS provides.

      So to get started make sure that you're currently logged in to the general AWS account, so the management account of the organization, and as always you need to have the Northern Virginia region selected.

      Now this lesson actually has two one-click deployments.

      The first deploys the base infrastructure and the second deploys a WordPress EC2 instance, which has been enhanced to utilize EFS.

      So you need to apply both of these templates in order and wait for the first one to finish before applying the second.

      So we're going to start with the base VPC RDS EFS template first.

      So this deploys the base VPC, the Elastic File System and an RDS instance.

      Now everything should be pre-populated.

      The stack should be called EFS demo -vpc -rds -efs.

      Just scroll all the way down to the bottom, check the capabilities box and click on create stack.

      While that's going let's switch over to the CloudFormation template and just step through exactly what it does.

      So this is the template that you're deploying using the one-click deployment.

      It's deploying the Base Animals for Life VPC, an EFS file system as well as mount targets and an Aurora database cluster.

      So if we just scroll down we can see all of the VPC and networking resources used by the Base Animals for Life VPC.

      Continue scrolling down we'll see the subnets that this VPC contains IP version 6 information.

      We'll see an RDS security group, a database subnet group.

      We've got the database instance.

      Then we've got an instance security group which controls access to all the resources in the VPC that we use that security group on.

      Then we have a rule which allows anything with that security group attached to it to communicate with anything else.

      We have a rule that the WordPress instance will use and note that this includes permissions on the Elastic File System.

      Then we have the instance profile that that instance uses.

      Then we have the CloudWatch agent configuration and this is all automated.

      And if we just continue scrolling down here we can see the Elastic File System.

      So we create an EFS file system and then we create a file system mount target in each application subnet.

      So we've got mount target zero which is in application subnet A which is in US East 1A.

      We've got mount target one which is an application subnet B which logically is in US East 1B.

      And then finally target two which is in subnet app C which is in availability zone 1C.

      So we create the VPC, the database and the Elastic File System in this first one click deployment.

      Now we need this to be in a create complete state before we continue with the demo lessons.

      So go ahead and pause the video, wait for this to move into a create complete status and then we can use the second one click deployment.

      Okay that stacks now finished creating which means we can move on to the second one click deployment.

      Now there are actually two WordPress one click deployments which are attached to this lesson.

      We're going to use them both but for now I want you to use the WordPress one one click deployment.

      So go ahead and click on that link this will create a stack called EFS demo hyphen WordPress one.

      Everything should be pre-populated just go ahead and click on create stack.

      Now this is going to use the infrastructure provided by that first one click deployment.

      So it's going to use EFS demo hyphen VPC hyphen RDS hyphen EFS and let's quickly step through exactly what this is doing while it's provisioning.

      So this is the cloud formation template that is being used and we can skip past most of this.

      What I want to focus on is the resource that's being created so that's WordPress EC2.

      So this is using cross stack references to import a lot of the resources created in that first cloud formation stack.

      So it's importing the instance profile to use it's importing the web a subnet so it knows where to place this instance.

      And it's importing the instance security group that's created in that previous cloud formation stack.

      Now in addition to this if we look through the user data for this WordPress instance one major difference is that it's mounting the EFS file system into this folder.

      So forward slash var forward slash w w w forward slash HTML forward slash WP hyphen content.

      Now if you remember from earlier demo lessons this is the folder which WordPress users to store its media.

      So now instead of this folder being on the local EC2 file system this is now the EFS file system.

      The EFS file system is mapped into this folder on this WordPress instance.

      Other than that everything else is the same WordPress is installed.

      It's configured to you as the RDS instance the cow say custom login banner is displayed.

      It automatically configures the cloud watch agent and then it signals cloud formation that it's finished provisioning this instance.

      Now what we'll end up with when this stack has finished creating is an EC2 instance which will use the services provided by this original stack.

      So let's just refresh this.

      It's still in progress so go ahead and pause the video and wait for this stack to move into a create complete state and then we good to continue.

      So this stacks now finished creating and if we move across to the EC2 console so click on services locate EC2 right click and open that in a new tab.

      Then click on instances running and you'll see that we have this A4L WordPress instance.

      Now if we select that copy the IP address into your clipboard and then open that in a new tab we need to perform the WordPress installation.

      So go ahead and enter the site title the best cats and add some exclamation points.

      For username we need to use admin then for the password go back to the cloud formation stack and click on parameters and we're going to use the DB password.

      So copy that into your clipboard then go back paste it into the password box and then put test at test.com for the email address and click install WordPress.

      Then as before we need to log in so click on login admin for username reenter that password and click on login.

      Then we need to go to posts we need to click on trash below hello world to delete that post then click on add new close down this dialogue.

      For title put the best cats ever and some exclamation points then click on the plus click gallery click upload.

      There's a link attached to this lesson with four cat images so go ahead and download that link and extract it locate those four images select them and click on open.

      And then once you've done that click on publish and publish again and then click on view post.

      Now what that's doing in the background is it's adding these images to the WP hyphen content folder which is on the EC two instance but now we have that folder mounted using EFS and so the images are being stored on the elastic file system rather than the local instance file system.

      The cat pictures are there but what we're going to do to validate this is to go back to instances right click on this a four L hyphen WordPress instance and click on connect and then connect to this instance using EC two instance connect.

      Now once we connected to the instance you CD space forward slash VAR forward slash WWW forward slash HTML and then do an LS space hyphen LA to do a full listing you'll see that we have this WP hyphen content folder.

      So type CD space WP hyphen content and press enter then we'll clear the screen and do an LS space hyphen LA and then inside this folder we have plugins themes and uploads go into the uploads folder do an LS space hyphen LA depending on when you do this demo lesson you should see a folder representing the year so move into that folder then a folder representing the month again this will vary depending on when you do the demo lesson.

      Move into that folder and then you should see all four of my cat images and if you do a DF space hyphen K you'll be able to see that this folder so forward slash VAR forward slash WWW forward slash HTML WP hyphen content this is actually mounted using EFS so this is an EFS file system.

      Now this means the local instance file system is no longer critical it no longer stores the actual media that we upload to these posts so what we can do is we can go back to cloud formation go to stacks select the EFS demo hyphen WordPress one stack and then click on delete and delete that stack so that's going to terminate the EC two instance that we've just used to upload that media.

      We need to wait for that stack to fully delete before continuing so go ahead and pause the video and wait for this stack to disappear so that stacks disappeared and now there's a second WordPress one click deployment link attached to this lesson remember there are two so now go ahead and click on the second one this one should create a stack called EFS demo hyphen WordPress two scroll to the bottom and click on create stack that's going to create a new stack and a new EC two instance.

      So while we're doing this just close down all of these additional tabs at the top of the screen close them all down apart from the cloud formation one.

      We're going to need to wait for this to finish provisioning and move into the create complete state so again pause the video wait for this to change into create complete and then we go to to continue.

      After a few minutes the WordPress two stack has moved into a create complete state click on services open the EC two console in a new tab click on instances running you'll see a new A4L hyphen WordPress instance this is a brand new instance which has been provisioned using the one click deployment link that you've just used so the WordPress two one click deployment link.

      If we select this copy the public IP address into your clipboard and open that in a new tab it again loads our WordPress blog if we open the blog post.

      Now we can see these images because they're being loaded from EFS from the file system that EFS provides so no longer are we limited to only operating from a single EC two instance for our WordPress application because now there's nothing which gets stored specifically on that EC two instance.

      Instead everything stored on EFS and accessible from any EC two instance that we decide to give permissions to know what we can do to demonstrate this if we go back to cloud formation.

      Now remember attached to this lesson are two WordPress one click deployments we initially applied number one then we deleted that and applied number two so now I want you to reapply number one.

      So again click on the WordPress one one click deployment this again will create a new stack this time called EFS demo hyphen WordPress one click on create stack you need to wait for this to move into a create complete state so pause the video and resume it once the stack changes to create complete after a few minutes this stack also moves into create complete.

      Let's click on resources we can see it's provisioned a single EC two instance so let's click on this to move directly to this new instance select it copy this instance is IP address into your clipboard and open that in a new tab and again we have our WordPress blog and if we click on the post it loads those images so now we have a number of EC two instances we have to EC two instances both with WordPress installed both using the same RDS data.

      And both using the shared file system provided by EFS and it means that if any posts are edited or any images uploaded on either of these two EC two instances then those updates will be reflected on all other EC two instances and this means that we've now implemented this architecture that's on screen now and this is what's going to support us when we evolve this architecture more and add scalability in an upcoming section of the core.

      For now though we've just been focused on the shared file system now all that remains at this point is for us to tidy up the infrastructure that we've used in this demo lesson so close down all of these tabs we need to be at the cloud formation console we need to start by deleting EFS demo WordPress one and WordPress two so pick either of those click delete and then delete stack then select the other delete and then delete stack.

      Now we need both of these to finish deleting and then we can delete this last stack so go ahead and pause the video wait for both of these to disappear and then we can resume both of those have deleted so now we can click the final stack EFS demo hyphen VPC hyphen RDS hyphen EFS so select that delete and then delete stack and that's everything that you need to do in this demo lesson and once that stacks finished deleting the account will be in the same state as it was at the start of this.

      Now I hope you've enjoyed this demo lesson and that it's been useful what you've implemented in this demo is one more supportive step towards us moving this architecture from being a monolith through to being fully elastic.

      Now the application is in this state where we have a single shared RDS database for all of our application instances and we're also using a shared file system provided by EFS and this means that we can have one single EC2 instance we could have two EC2 instances or even 200 all of them sharing the same database and the same shared file system provided by EFS.

      Now in an upcoming section of this course we're going to extend this further by creating a launch template which automatically builds EC2 instances as part of this application architecture.

      We're going to utilize auto scaling groups together with application load balancers to implement an architecture which is fully elastic and resilient and this has been one more supportive step towards that objective.

      At this point though that's everything that you needed to do in this demo lesson so go ahead complete this video and when you're ready I look forward to you joining me in the next.

    1. Welcome back and in this demo lesson I want to give you some abstract practical experience of using the Elastic File System or EFS.

      Now we're going to need some infrastructure.

      Before we apply that as always make sure that you're logged into the general AWS account, so the management account of the organization and you'll need the Northern Virginia region selected.

      Now attached to this lesson is a one-click deployment link so go ahead and click that.

      This is going to provision some infrastructure.

      It's going to take you to the quick create stack screen and everything should be pre-populated.

      You'll just need to scroll to the bottom, check the box beneath capabilities and then click on create stack.

      You're also going to be typing some commands within this demo lesson so also attached to this lesson is a lesson commands document.

      Go ahead and open that in a new tab.

      So this is just a list of the commands that we're going to be using during the demo lesson and there are some placeholders such as file system ID that you'll need to replace as we go but make sure you've got this open for reference.

      Now we're going to need this stack to be in a create complete state before we continue with the demo lesson so go ahead pause the video and resume it once your stack moves into a create complete state.

      Okay so the stacks now moved into a create complete status and what this has actually done is create the animals for life base VPC as well as a number of EC2 instances.

      So if we go to the EC2 console and click on instances running you'll note that we've created a for L - EFS instance A and a for L - EFS instance B and we're going to be creating an EFS file system and mount points and then mounting that on both of these instances and interacting with the data stored on that file system.

      We're going to get you the experience of working with a network shared file system so let's go ahead and do that.

      So to get started we need to move to the EFS console so in the search box at the top just type EFS and then open that in a brand new tab.

      We're going to leave this tab open to the instances part of the EC2 console because we're going to come back to this very shortly.

      So let's move across to the EFS console that we have open in a separate tab and the first step is to create a file system so a file system is the base entity of the elastic file system product and that's what we're going to create.

      Now you've got two options for setting up an EFS file system you can use this simple dialogue or you can click on customize to customize it further.

      So if we're using the simple dialogue we'd start by naming the file system so let's say we use A4L - EFS and then you'd need to pick a VPC for this file system to be provisioned into and of course we'd want to select the animals for life VPC.

      Now we want to customize this further we don't want to just accept these high-level defaults so we need to click on customize.

      This is going to move us to this user interface which has many more options so we've still got the A4L - EFS name for this file system.

      Now for the storage class we're going to pick standard which means the data is replicated across multiple availability zones.

      If you're doing this in a test or development environment or you're storing data which is not important then you can choose to use one zone which stores data redundantly but only within a single AZ.

      Now again in this demonstration we are going to be using multiple availability zones so make sure that you pick standard for storage class.

      You're able to configure automatic backups of this file system using AWS backup and if you're taking an appropriate certification course this is something which I'll be covering in much more detail.

      You can either enable this or disable it obviously for a production usage you'd want to enable it but for this demonstration we're going to disable it.

      Now EFS as I mentioned in the theory lesson comes with different classes of storage and you can configure lifecycle management to move files between those different storage classes so if you want to configure lifecycle management to move any files not accessed for 30 days you can move those into the infrequent access storage class and you can also transition out of infrequent access when anything is accessed so go ahead and select on first access for transition out of IA.

      So in many ways this is like S3 with the different classes of storage for different use cases.

      When you're creating a file system you're able to set different performance and throughput modes.

      For throughput mode you can choose between bursting and enhanced.

      If you pick enhanced you're able to select between elastic and provisioned.

      I've talked more about these in the theory lesson.

      We're going to pick bursting.

      Now for performance you can choose between general purpose and max I/O.

      General purpose is the default and rightfully so and you should use this for almost all situations.

      Only use max I/O if you want to scale to really high levels of aggregate throughput and input output operations per second so only select it if you absolutely know that you need this option.

      You've also got the ability to encrypt the data on the file system and if you do encrypt it it uses KMS and you need to pick a KMS key to use.

      Of course this means that in order to interact with objects on this file system permissions are needed both on the EFS service itself as well as the KMS key that's used for the encryption operation.

      Now this is something that you will absolutely need to use for production usage but for this demonstration we're going to switch it off.

      We won't be setting any tags for this file system so let's go ahead and click on next.

      You need to configure the network settings for this file system so specifically the mount targets that will be created to access this file system.

      Now best practice is that any availability zones within a VPC where you're consuming the services provided by EFS you should be creating a mount target so in our case that's US - East - 1A, 1B and 1C.

      So we're going to go through and configure this so first let's delete all of these default security group assignments.

      Every mount target that you create will have an associated security group so we'll be setting these specifically.

      For now though we need to choose the application subnet in each of these availability zones so in the top drop-down which is US - East - 1A I'm looking for app A so go ahead and do the same.

      In US - East - 1B I want to select the app B subnet and then in US - East - 1C logically I'll be selecting the app C subnet so that's app A, app B and app C.

      Now for security groups the CloudFormation 1 click deployment has provisioned this instance security group and by default this security group allows all connections from any entities which have this attached so this is a really easy way that we can allow our instances to connect to these mount targets so for each of these lines go ahead and select the instance security group you'll need to do that for each of the mount targets so we'll do the second one and then we'll do the third one and that's all of the network configuration options that we need to worry about so click on next it's here where you can define any policies on the file system so you can prevent root access by default you can enforce read only access by default you can prevent anonymous access or you can enforce encryption in transit for all clients connected to this EFS file system so any clients that connect to the mount targets to access the file system you can ensure that that uses encryption in transit and if you're using this in production you might want to select at least this last option to improve security for this demo lesson we're not going to use any of these policy options nor are we going to define a custom policy in the policy editor instead we'll just click on next at this point we just need to review everything's to our satisfaction everything looks good so we're going to scroll down to the bottom and just click on create now in order to continue with this demo lesson we're going to need both the file system and all of its mount targets so go into the file system click on network and you'll see three mount targets being created all three of these need to be ready before we can continue the demo lesson so this seems like a great time to end part one of this demo lesson go ahead and finish this video and then when all of these mount targets are ready to go you can start part two.

    1. We can write them applied at and expressed in body frame, B, assuming the center of mass in the center of the brick and the brick has length l and height h:

      I think there's a typo in the friction cone constraint for location one. It says

      $$|f_{1,B_z}^B| \leq \mu f_{1,B_z}^B$$

      but should it be the following? (replace z with x on the left side of the inequality)

      $$|f_{1,B_x}^B| \leq \mu f_{1,B_z}^B$$

    1. Author response:

      eLife Assessment

      This valuable study uses consensus-independent component analysis to highlight transcriptional components (TC) in high-grade serous ovarian cancers (HGSOC). The study presents a convincing preliminary finding by identifying a TC linked to synaptic signaling that is associated with shorter overall survival in HGSOC patients, highlighting the potential role of neuronal interactions in the tumor microenvironment. This finding is corroborated by comparing spatially resolved transcriptomics in a small-scale study; a weakness is in being descriptive, non-mechanistic, and requiring experimental validation.

      We sincerely thank the editors for the valuable and constructive feedback. We appreciate the recognition of our findings and the significance of identifying transcriptional components in high-grade serous ovarian cancers. We acknowledge the insightful point on our study's descriptive nature and limited mechanistic depth. While further experimental validation would indeed enhance our conclusions, such work extends beyond the current scope of this manuscript. However, we would like to highlight that mechanistic studies demonstrating the impact of tumor-infiltrating nerves on disease progression are emerging (Zahalka et al., 2017; Allen et al., 2018; Balood et al., 2022; Jin et al., 2022; Globig et al., 2023; Restaino et al., 2023; Darragh et al., 2024). Importantly, members of our group have contributed to these findings. These studies, including in vitro and in vivo work in head and neck squamous cell carcinoma as well as high-grade serous ovarian carcinoma, demonstrate that substance P released from tumor-infiltrating nociceptors potentiates MAP kinase signaling in cancer cells, thereby influencing disease progression. This effect can be mitigated in vivo by blocking the substance P receptor (Restaino et al., 2023). Our present work identifies a transcriptional component that aligns with the presence of functional nerves within malignancies. These published mechanistic studies support our findings and suggest that this transcriptional component could serve as a potential screening tool to identify innervated tumors. Such information is clinically relevant, as patients with innervated tumors may benefit from more aggressive therapy.

      Reviewer #1 (Public review):

      This manuscript explores the transcriptional landscape of high-grade serous ovarian cancer (HGSOC) using consensus-independent component analysis (c-ICA) to identify transcriptional components (TCs) associated with patient outcomes. The study analyzes 678 HGSOC transcriptomes, supplemented with 447 transcriptomes from other ovarian cancer types and noncancerous tissues. By identifying 374 TCs, the authors aim to uncover subtle transcriptional patterns that could serve as novel drug targets. Notably, a transcriptional component linked to synaptic signaling was associated with shorter overall survival (OS) in patients, suggesting a potential role for neuronal interactions in the tumor microenvironment. Given notable weaknesses like lack of validation cohort or validation using another platform (other than the 11 samples with ST), the data is considered highly descriptive and preliminary.

      Strengths:

      (1) Innovative Methodology:

      The use of c-ICA to dissect bulk transcriptomes into independent components is a novel approach that allows for the identification of subtle transcriptional patterns that may be overshadowed in traditional analyses.

      We sincerely thank the reviewer for recognizing the strengths and novelty of our study. We appreciate the positive feedback on our use of consensus-independent component analysis (c-ICA) to decompose bulk transcriptomes, which we believe allowed us to detect subtle transcriptional signals often overlooked in traditional analyses.

      (2) Comprehensive Data Integration:

      The study integrates a large dataset from multiple public repositories, enhancing the robustness of the findings. The inclusion of spatially resolved transcriptomes adds a valuable dimension to the analysis.

      Thank you for recognizing the robustness of our study through comprehensive data integration. We appreciate the acknowledgment of our efforts to leverage a large, multi-source dataset, as well as the additional insights gained from spatially resolved transcriptomes. We believe this integrative approach enhances the depth of our analysis and contributes to a more nuanced understanding of the tumor microenvironment.

      (3) Clinical Relevance:

      The identification of a synaptic signaling-related TC associated with poor prognosis highlights a potential new avenue for therapeutic intervention, emphasizing the role of the tumor microenvironment in cancer progression.

      We appreciate the reviewer’s recognition of the clinical implications of our findings. The identification of a synaptic signaling-related transcriptional component associated with poor prognosis underscores the potential for novel therapeutic targets within the tumor microenvironment. We agree that this insight could open new avenues for intervention and further highlights the role of neuronal interactions in cancer progression.

      Weaknesses:

      (1) Mechanistic Insights:

      While the study identifies TCs associated with survival, it provides limited mechanistic insights into how these components influence cancer progression. Further experimental validation is necessary to elucidate the underlying biological processes.

      We appreciate the reviewer’s point regarding the limited mechanistic insights provided in our study. We agree that further experimental validation would enhance our understanding of how the biology captured by these transcriptional components influence cancer progression. However, we respectfully note that such validation is beyond the current scope of this article.   Our current analyses are done on publicly available expression array and spatial transcriptomic array datasets. For future studies, we therefore intend to combine spatial transcriptomic data with immunohistochemical analysis of the same tumors for validation purposes. We have started with setting up in vitro cocultures of neurons and ovarian cancer cells to obtain mechanistic insight in how genes with a large weight in TC121 regulate synaptic signaling and how that affects ovarian cancer cells.

      (2) Generalizability:

      The findings are primarily based on transcriptomic data from HGSOC. It remains unclear how these results apply to other subtypes of ovarian cancer or different cancer types.

      In Figure 5, we present the activity of TC121 across various cancer types, demonstrating broader applicability. However, due to limited treatment response data, we were unable to assess associations between TC activity scores and patient response. Additionally, transcriptomic and survival data specific to other ovarian cancer subtypes beyond HGSOC are currently not available, limiting our ability to generalize these findings to those groups. We intend to leverage survival data from TCGA to explore associations between TC activity scores and overall survival of patients with other cancer types. Nonetheless, we recognize limitations with TCGA survival data, as outlined in this article: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8726696/.

      (3) Innovative Methodology:

      Requires more validation using different platforms (IHC) to validate the performance of this bulk-derived data. Also, the lack of control over data quality is a concern.

      We acknowledge the reviewer’s suggestion to validate our results with alternative platforms, such as IHC; however, we regret that such validation is beyond the scope of this article. Regarding data quality control, we implemented a series of checks:

      • Bulk Transcriptional Profiles: We applied principal component analysis (PCA) on the sample Pearson product-moment correlation matrix, focusing on the first principal component (PCqc), which accounted for approximately 80-90% of the variance, primarily reflecting technical rather than biological variability  (Bhattacharya et al., 2020). Samples with a correlation below 0.8 with PCqc were removed as outliers. Additionally, we generated unique MD5 hashes for each CEL file to identify and exclude duplicate samples. Per gene, expression values were standardized to a mean of zero and a variance of one across the GEO, CCLE, GDSC, and TCGA datasets to minimize probeset- or gene-specific variability.

      • Spatial Transcriptional Profiles: We used PCA for quality control here as well, retained samples only if their loading factors for the first principal component showed consistent signs across all profiles (i.e., all profiles had either positive or negative loading factors for the first PC) from that individual spatial transcriptomic sample. Samples that did not meet this criterion were excluded from analyses.

      (4) Clinical Application:

      Although the study suggests potential drug targets, the translation of these findings into clinical practice is not addressed. Probably given the lack of some QA/QC procedures it'll be hard to translate these results. Future studies should focus on validating these targets in clinical settings.

      While this study is exploratory in nature, we agree that future studies should focus on validating these potential drug targets in clinical settings. As suggested, QA/QC procedures were integral to our analyses. We applied rigorous quality control, including PCA-based checks and duplicate removal across datasets, to ensure data integrity (detailed in our previous response).

      In terms of clinical application, which we partially discussed in the manuscript, we will discuss additional strategies to prevent synaptic signaling and neurotransmitter release in the tumor microenvironment (TME). Drugs such as ifenprodil and lamotrigine are used in treating neuronal disorders to block glutamate release responsible for subsequent synaptic signaling, whereas the vesicular monoamine transporter (VMAT) inhibitor reserpine can block the formation of synaptic vesicles (Reid et al., 2013; Williams et al., 2001). Previous in vitro studies with HGSOC cell lines showed a significant effect of ifenprodil alone on cancer cell proliferation, whereas reserpine seemed to trigger apoptosis in cancer cells (North et al., 2015; Ramamoorthy et al., 2019). Such strategies could potentially be used to inhibit synaptic neurotransmission in the TME.

      Reviewer #2 (Public review):

      Summary:

      Consensus-independent component analysis and closely related methods have previously been used to reveal components of transcriptomic data that are not captured by principal component or gene-gene coexpression analyses.

      Here, the authors asked whether applying consensus-independent component analysis (c-ICA) to published high-grade serous ovarian cancer (HGSOC) microarray-based transcriptomes would reveal subtle transcriptional patterns that are not captured by existing molecular omics classifications of HGSOC.

      Statistical associations of these (hitherto masked) transcriptional components with prognostic outcomes in HGSOC could lead to additional insights into underlying mechanisms and, coupled with corroborating evidence from spatial transcriptomics, are proposed for further investigation.

      This approach is complementary to existing transcriptomics classifications of HGSOC.

      The authors have previously applied the same approach in colorectal carcinoma (Knapen et al. (2024) Commun. Med).

      Strengths:

      (1) Overall, this study describes a solid data-driven description of c-ICA-derived transcriptional components that the authors identified in HGSOC microarray transcriptomics data, supported by detailed methods and supplementary documentation.

      We thank the reviewer for acknowledging the strength of our data-driven approach and the use of consensus-independent component analysis (c-ICA) to identify transcriptional components within HGSOC microarray data. We aimed to provide comprehensive methodological detail and supplementary documentation to support the reproducibility and robustness of our findings. We believe this approach allows for the identification of subtle transcriptional signals that might be overlooked by traditional analysis methods.

      (2) The biological interpretation of transcriptional components is convincing based on (data-driven) permutation analysis and a suite of analyses of association with copy-number, gene sets, and prognostic outcomes.

      We appreciate the reviewer’s positive feedback on the biological interpretation of our transcriptional components. We are pleased that our approach, which includes data-driven permutation testing and analyses of associations with copy-number alterations, gene sets, and prognostic outcomes, was found convincing. These analyses were integral to enhancing the robustness and biological relevance of our findings.

      (3) The resulting annotated transcriptional components have been made available in a searchable online format.

      Thank you for acknowledging the availability of our annotated transcriptional components in a searchable online format.

      (4) For the highlighted transcriptional component which has been annotated as related to synaptic signalling, the detection of the transcriptional component among 11 published spatial transcriptomics samples from ovarian cancers appears to support this preliminary finding and requires further mechanistic follow-up.

      Thank you for acknowledging the accessibility of our annotated transcriptional components. We prioritized making these data available in a searchable online format to facilitate further research and enable the community to explore and validate our findings.

      Weaknesses:

      (1) This study has not explicitly compared the c-ICA transcriptional components to the existing reported transcriptional landscape and classifications for ovarian cancers (e.g. Smith et al Nat Comms 2023; TCGA Nature 2011; Engqvist et al Sci Rep 2020) which would enable a further assessment of the additional contribution of c-ICA - whether the c-ICA approach captured entirely complementary components, or whether some components are correlated with the existing reported ovarian transcriptomic classifications.

      We appreciate the reviewer’s insightful suggestion to compare our c-ICA-derived transcriptional components with previously reported ovarian cancer classifications, such as those from Smith et al. (2023), TCGA (2011), and Engqvist et al. (2020). To address this, we will incorporate analyses comparing the activity scores of our transcriptional components with these published landscapes and classifications, particularly focusing on any associations with overall survival. Additionally, we plan to evaluate correlations between gene signatures from these studies and our identified TCs, enhancing our understanding of the unique contributions of the c-ICA approach.

      (2) Here, the authors primarily interpret the c-ICA transcriptional components as a deconvolution of bulk transcriptomics due to the presence of cells from tumour cells and the tumour microenvironment. However, c-ICA is not explicitly a deconvolution method with respect to cell types: the transcriptional components do not necessarily correspond to distinct cell types, and may reflect differential dysregulation within a cell type. This application of c-ICA for the purpose of data-driven deconvolution of cell populations is distinct from other deconvolution methods that explicitly use a prior cell signature matrix.

      Thank you for highlighting this nuanced aspect of c-ICA interpretation. We acknowledge that c-ICA, unlike traditional deconvolution methods, is not specifically designed for cell-type deconvolution and does not rely on a predefined cell signature matrix. While we explored the transcriptional components in the context of tumor and microenvironmental interactions, we agree that these components may not correspond directly to distinct cell types but rather reflect complex patterns of dysregulation, potentially within individual cell populations.

      Our goal with c-ICA was to uncover hidden transcriptional patterns possibly influenced by cellular heterogeneity. However, we recognize these patterns may also arise from regulatory processes within a single cell type. To investigate further, we plan to use single-cell transcriptional data (~60,000 cell-types annotated profiles from GSE158722) and project our transcriptional components onto these profiles to obtain activity scores, allowing us to assess each TC’s behavior across diverse cellular contexts after removing the first principal component to minimize background effects.

      References

      Allen JK, Armaiz-Pena GN, Nagaraja AS, Sadaoui NC, Ortiz T, Dood R, Ozcan M, Herder DM, Haemerrle M, Gharpure KM, Rupaimoole R, Previs R, Wu SY, Pradeep S, Xu X, Han HD, Zand B, Dalton HJ, Taylor M, Hu W, Bottsford-Miller J, Moreno-Smith M, Kang Y, Mangala LS, Rodriguez-Aguayo C, Sehgal V, Spaeth EL, Ram PT, Wong ST, Marini FC, Lopez-Berestein G, Cole SW, Lutgendorf SK, diBiasi M, Sood AK. 2018. Sustained adrenergic signaling promotes intratumoral innervation through BDNF induction. Cancer Res 78:canres.1701.2016.

      Balood M, Ahmadi M, Eichwald T, Ahmadi A, Majdoubi A, Roversi Karine, Roversi Katiane, Lucido CT, Restaino AC, Huang S, Ji L, Huang K-C, Semerena E, Thomas SC, Trevino AE, Merrison H, Parrin A, Doyle B, Vermeer DW, Spanos WC, Williamson CS, Seehus CR, Foster SL, Dai H, Shu CJ, Rangachari M, Thibodeau J, Rincon SVD, Drapkin R, Rafei M, Ghasemlou N, Vermeer PD, Woolf CJ, Talbot S. 2022. Nociceptor neurons affect cancer immunosurveillance. Nature 611:405–412.

      Bhattacharya A, Bense RD, Urzúa-Traslaviña CG, Vries EGE de, Vugt MATM van, Fehrmann RSN. 2020. Transcriptional effects of copy number alterations in a large set of human cancers. Nat Commun 11:715.

      Darragh LB, Nguyen A, Pham TT, Idlett-Ali S, Knitz MW, Gadwa J, Bukkapatnam S, Corbo S, Olimpo NA, Nguyen D, Court BV, Neupert B, Yu J, Ross RB, Corbisiero M, Abdelazeem KNM, Maroney SP, Galindo DC, Mukdad L, Saviola A, Joshi M, White R, Alhiyari Y, Samedi V, Bokhoven AV, John MSt, Karam SD. 2024. Sensory nerve release of CGRP increases tumor growth in HNSCC by suppressing TILs. Med 5:254-270.e8.

      Globig A-M, Zhao S, Roginsky J, Maltez VI, Guiza J, Avina-Ochoa N, Heeg M, Hoffmann FA, Chaudhary O, Wang J, Senturk G, Chen D, O’Connor C, Pfaff S, Germain RN, Schalper KA, Emu B, Kaech SM. 2023. The β1-adrenergic receptor links sympathetic nerves to T cell exhaustion. Nature 622:383–392.

      Jin M, Wang Y, Zhou T, Li W, Wen Q. 2022. Norepinephrine/β2-adrenergic receptor pathway promotes the cell proliferation and nerve growth factor production in triple-negative breast cancer. J Breast Cancer 26:268–285.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      This study explores the therapeutic potential of KMO inhibition in endometriosis, a condition with limited treatment options. 

      Strengths: 

      KNS898 is a novel specific KMO inhibitor and is orally bioavailable, providing a convenient and non-hormonal treatment option for endometriosis. The promising efficacy of KNS898 was demonstrated in a relevant preclinical mouse model of endometriosis with pathological and behavioural assessments performed. 

      Weaknesses: 

      (1) The expression of KMO in human normal endometrium and endometrial lesions was not quantified. Western blot or quantification of IHC images will provide valuable insight.

      Given the differential expression of KMO in luminal epithelial cells lining the endometrial glands compared to the other parts of the endometrium, a general endometrial Western Blot prep is not going to be additionally helpful or accurate in addressing this question, without e.g. laser capture microdissection or single cell quantitative proteomics. Furthermore, KMO is a flavin-dependent monooxygenase and the activity, especially generating the oxidative stressor product 3-hydroxykynurenine is far more dependent on kynurenine substrate availability than it is on actual enzyme abundance - although it is important to show (as we have done), that KMO is present in the human endometrial glands and in human distended endometrial gland-like structures (DEGLS).

      If KMO is not overexpressed in diseased tissues i.e. it may have homeostatic roles, and inhibition of KMO may have consequences on general human health and wellbeing.

      KMO certainly does have important homeostatic roles, for example as key step in the repletion of NAD+ through de novo synthesis. Although with good nutrition and sufficient NAD+ precursors in the diet e.g. niacin, that specific role may be partially redundant. KMO knockout mice exhibit normal fertility and fecundity and do not show a survival deficit compared to littermate wildtype controls (e.g. Mole et al Nature Medicine 2016). To further develop KNS898 towards clinical use, preclinical GLP safety and toxicology studies and human Phase 1 clinical trials will of course need to be completed, but that is standard for the development of any new drug

      In addition, KMO expression in control mice was not shown or quantified.

      Control mice that were not inoculated intraperitoneally with endometrial fragments did not develop DEGLS and therefore there is nothing to show or quantify.

      Images of KMO expression in endometriosis mice with treatments should be shown in Figure 4.

      We have now included a representative KMO immunohistochemistry image from each endometriosis group and included all KMO immunohistochemistry images in Supplementary Information.

      The images showing quantification analysis (Figure 4A-F) can be moved to supplementary material.

      This recommendation contradicts the emphasis placed by the same reviewer earlier regarding quantification, so we have elected to keep it where it is.

      (2) Figure 1 only showed representative images from a few patients. A description of whether KMO expression varies between patients and whether it correlates with AFS stages/disease severity will be helpful. Images from additional patients can be provided in supplementary material. 

      We have added extra information to the Figure legend to clarify the disease stage of the superficial peritoneal lesions which were illustrated (Stage I/II) and to link them to the information in supplementary Table S1. In total we examined 11 peritoneal lesions and 5 ovarian lesions (stage III/IV) – in every sample examined immunopositive staining was most intense in epithelial cells lining gland-like structures. Sections illustrated were chosen to illustrate this key finding.

      (3) For Home Cage Analysis, different measurements were performed as stated in methods including total moving distance, total moving time, moving speed, isolation/separation distance, isolated time, peripheral time, peripheral distance, in centre zones time, in centre zones distance, climbing time, and body temperature. However, only the finding for peripheral distance was reported in the manuscript. 

      This was indeed a large amount of output, which we rationalised for the benefit of a concise paper. The paper now includes a description of which parameters showed a difference with drug treatment.

      (4) The rationale for choosing the different dose levels of KNS898 - 0.01-25mg/kg was not provided. What is the IC50 of a drug? 

      KNS898 dosing has been extensively characterised by us in multiple species, and the pIC50 has already been published (e.g. Hayes et al Cell Reports 2023 and elsewhere). We now include the pIC50 in the present manuscript to save the reader from having to search through another reference.

      (5) Statistical significance: 

      (a) Were stats performed for Fig 3B-E?

      Now included, thank you.

      (b) Line 141 - 'P = 0.004 for DEGLS per group' 

      However, statistics were not shown in the figure. 

      Thanks, now displayed on figure.

      (c) Line 166 - 'the mechanical allodynia threshold in the hind paw was statistically significantly lower compared to baseline for the group' 

      However, statistics were not shown in the figure. 

      (d) Line 170 - 'Two-way ANOVA, Group effect P = 0.003, time effect P < 0.0001' The stats need to be annotated appropriately in Figure 5A as two separate symbols. 

      Arguably the far more important comparison in this figure is whether there is any effect of treatment, and to mark multiple statistical comparisons on the figure would make it difficult to understand. Instead, the figure legend and results text have been clarified on this point.

      (e) Figure 5B - multiple comparisons of two-way ANOVA are needed. G4 does not look different to G3 at D42. 

      Multiple comparison testing (Dunnett’s T3) was done and the results have been clarified in the text and figure legends.

      (f) Line 565 - 'non-significant improvement in KNS898 treated groups'. However, ** was annotated in Figure 5A. 

      Thank you. This is an error that has been checked and corrected.

      (6) Discussion is very light. No reference to previous publications was made in the discussion. Discussion on potential mechanistic pathways of KYR/KMO in the pathogenesis of endometriosis will be helpful, as the expression and function of KMO and/or other metabolites in endometrial-related conditions. 

      The discussion is deliberately concise and focussed. The paper has 21 references to previous publications. A speculative discussion is generally not favoured by us.

      The findings in this study generally support the conclusion although some key data which strengthen the conclusion eg quantification of KMO in normal and diseased tissue is lacking.

      We differ from the reviewer here and do not think that those data would materially affect the likelihood of KMO inhibition being efficacious in human endometriosis in Phase 2/3 clinical trials.

      Before KMO inhibitors can be used for endometriosis, the function of KMO in the context of endometriosis should be explored eg KMO knockout mice should be studied. 

      We take the view that before KMO inhibitors can be used for endometriosis in patients there are multiple other regulatory and clinical development steps that are required that would be a priority. While using a KMO knockout mouse might be an interesting scientific experiment, it would not impact on the critical path in a material way.

      Reviewer #2 (Public Review): 

      Summary: 

      The authors aim to address the clinical challenge of treating endometriosis, a debilitating condition with limited and often ineffective treatment options. They propose that inhibiting KMO could be a novel non-hormonal therapeutic approach. Their study focuses on: 

      • Characterising KMO expression in human and mouse endometriosis tissues. 

      • Investigating the effects of KMO inhibitor KNS898 on inflammation, lesion volume, and pain in a mouse model of endometriosis. 

      • Demonstrating the efficacy of KMO blockade in improving histological and symptomatic features of endometriosis. 

      Strengths: 

      • Novelty and Relevance: The study addresses a significant clinical need for better endometriosis treatments and explores a novel therapeutic target. 

      • Comprehensive Approach: The authors use both human biobanked tissues and a mouse model to study KMO expression and the effects of its inhibition. 

      • Clear Biochemical Outcomes: The administration of KNS898 reliably induced KMO blockade, leading to measurable biochemical changes (increased kynurenine, increased kynurenic acid, reduced 3-hydroxykynurenine). 

      Weaknesses: 

      • Limited Mechanistic Insight: The study does not thoroughly investigate the mechanistic pathways through which KNS898 affects endometriosis. Specifically, the local vs. systemic effects of KMO inhibition are not well differentiated. 

      While we agree that this is not a comprehensive mechanistic analysis, given that the ultimate therapy would be almost certainly a once daily oral dosing i.e. systemic administration, we do not consider differentiating local vs systemic effects of KMO inhibition to be critical to therapeutic development in this scenario.

      • Statistical Analysis Issues: The choice of statistical tests (e.g., two-way ANOVA instead of repeated measures ANOVA for behavioral data) may not be the most appropriate, potentially impacting the validity of the results. 

      The selection of two-way ANOVA (time and group) is sufficient and correct for this experimental analysis and its use does not invalidate the results. We agree that repeated measures ANOVA could be a valid alternative.

      • Quantification and Comparisons: There is insufficient quantitative comparison of KMO expression levels between normal endometrium and endometriosis lesions,

      Please see response above to quantification question raised by Reviewer 1.

      and the systemic effects of KNS898 are not fully explored or quantified in various tissues. 

      Please see earlier responses. KNS898 has been thoroughly explored in multiple tissues, species and experimental models, but those data do not need rehearsed here.

      • Potential Side Effects: The systemic accumulation of kynurenine pathway metabolites raises concerns about potential side effects, which are not addressed in the study. 

      As discussed above (response to Reviewer 1), KMO knockout mice exhibit normal fertility and fecundity and do not show a survival deficit compared to littermate wildtype controls (e.g. Mole et al Nature Medicine 2016). To further develop KNS898 towards clinical use, preclinical GLP safety and toxicology studies and human Phase 1 clinical trials will naturally need to be completed, but this is standard for the development of any new drug.

      Achievement of Aims: 

      • The authors successfully demonstrated that KMO is expressed in endometriosis lesions and that KNS898 can induce KMO blockade, leading to biochemical changes and improvements in endometriosis symptoms in a mouse model. 

      Support of Conclusions: 

      • While the data supports the potential of KMO inhibition as a therapeutic strategy, the conclusions are somewhat overextended given the limitations in mechanistic insights and statistical analysis. The study provides promising initial evidence but requires further exploration to firmly establish the efficacy and safety of KNS898 for endometriosis treatment. 

      We do not agree that the conclusions are overextended based on the data presented, as expanded in the reply to the eLife editorial assessment at the beginning of this response. It is clear that additional preclinical, regulatory and clinical development work, and human clinical trials will be required to firmly establish the efficacy and safety of KN898 for endometriosis treatment.

      Impact on the Field: 

      • The study introduces a novel therapeutic target for endometriosis, potentially leading to non-hormonal treatment options. If validated, KMO inhibition could significantly impact the management of endometriosis. 

      Utility of Methods and Data: 

      • The methods used provide a foundation for further research, although they require refinement. The data, while promising, need more rigorous statistical analysis and deeper mechanistic exploration to be fully convincing and useful to the community. 

      We believe that the data are a) convincing, and b) useful to the community. To be advanced effectively towards patients, KNS898 needs to follow the critical development path outlined above.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      (1) Change 'hyperalgia' to hyperalgesia throughout the manuscript including the title. 

      Done

      (2) Line 69 - write '3-HK' in full. 

      Done

      (3) Line 85 - the findings of the study include 'define the preclinical efficacy of KNS898 in reducing inflammation'. The inflammatory profile was not studied. 

      Changed to “disease”

      (4) Line 259 - write 'EPHect' in full. 

      Done

      (5) Line 260 - write 'AFS' in full. Also, abbreviate 'AFS' in the caption of Table S1. 

      Done

      (6) 20 patients were listed in Table S1 but only 19 were accounted for in the methods section. 

      Apologies there was an error and has now been corrected in the methods section as one of the endometrial samples had not been included. Table S1 has also been changed to make it clear which samples were eutopic endometrium to differentiate them from the lesions.

      (7) The location from which the endometrial lesion tissues were obtained should be provided in Table S1. 

      Table S1 has been changed to make it clear that the subtypes of lesions examined were classified as Stage I/II – superficial peritoneal subtype and Stage III/IV – endometrioma. The methods section has also been updated to reflect these subtypes (lines 272-277).

      (8) Table S2 - G5 should be given compound 'A' not 'B'. 

      Thank you. Corrected.

      (9) Figure 2E was not referenced in the text and no figure legend was provided. 

      Now referenced and the figure legend updated.

      (10) Figure 3A - font needs to be enlarged. HCA baseline recording was annotated as performed twice in the protocol. When is the baseline taken and on what day was the Week 12 measurement taken (refer to Figures 5C and D)? 

      Font has been enlarged as requested. The second HCA baseline annotation in Fig 3A is a cut-and-paste error, now rectified and the time of second measurement annotated.

      (11) Line 133 - 'In KNS898-treated group G4 (endometriosis + treatment from Day 19), DEGLS formed in 4 of 15 mice (26.7%) and in G5 (Endo + treatment start on Day 26) in 6 of 15 mice (40%) (Fig. 3f).'. The aforementioned data is not reflected in Figure 3F. 

      Thank you. This has been rectified.

      (12) Line 137 - 'Mice with endometriosis receiving KNS898 from the time of inoculation (G4) had an average of 2.0 DEGLS per animal with DEGLS (total = 8 DEGLS in 4 mice in G4) and those receiving KNS898 1 week after inoculation (G5) had an average of 1.8 DEGLS per animal (total = 11 DEGLS in 6 mice in G5) (Figs. 3g and 3h).' 

      The aforementioned data is not reflected in Figure 3G. There is no Figure 3H shown. 

      Rectified as above.

      (13) Provide a discussion of why KA levels were significantly lower in Figure 3E compared to Figure 2C. 

      (14) Figure legend for Figure 3 - G1 and G2 were noted as n=8. However, Figure S1 and Table S2 noted both groups as n=10. 

      Thank you. This is a typographical error. The legend for Fig 3 should indeed read n=10 for G1 and G2 and has been corrected.

      (15) Line 181 - 'compared to non-operated and sham-operated control groups'. Only the sham group was shown in Figures 5C and D. 

      This text has been clarified to refer only to the data shown.

      (16) Figure 1 images need scalebars. Same for Figure 4. 

      Now added

      (17) Figure 3B - y-axis is fold change? 

      Relative concentration. Legend has been clarified.

      (18) Figures 5A and B - are the last Von Frey measurements taken on Day 40 (as per Figure 3A) or 42?

      Taken on Day 42. Fig 3A (the prospective protocol figure) has been clarified to reflect what actually happened (D42) as opposed to what was planned (D40) to pre-empt any further confusion.

      (19) Symbols in Figure S1 need to be explained in the Figure legend. 

      Done

      (20) Figures 2A and 2D should not be plotted in log scale to match the description of results in Line 106 and Line 118. 

      These particular results are plotted on a log scale to allow the reader to visualise that detectable levels of drug are measurable at very low doses and that there is no significant pharmacodynamic effect at that low dose. We choose to retain the present format.

      Reviewer #2 (Recommendations For The Authors): 

      Comments and queries 

      Introduction/aims section: 

      Line 82 - 87: Clarify in the proposal aims what is being accessed and analysed in humans and/or in animal models (mice). Specifically state clearly the correlations with KMO expression. Were the correlations between KMO expression with features of inflammation performed only in mice or also in humans? 

      Thank you for this comment. The aims have been clarified in the Introduction.

      Section - KMO is expressed in human eutopic endometrium and human endometriosis tissue lesions: 

      Was any quantitative or semi-quantitative method used to quantify the KMO expression in human tissues? Although the authors claimed that "KMO was strongly immunopositive in human peritoneal endometriosis lesions" by the representative figures it is not clear if KMO expression is similar, higher or lower between normal endometrium and peritoneal endometriosis lesions. 

      We have added extra information to the legend of Figure 1 to identify the PIN number of the superficial lesions illustrated. The key finding from the immunostaining with the antibody which had been previously validated as specific for KMO was that the most intense immunopositive response was in glandular epithelial cells and the samples illustrate this result.

      Section - Oral KNS898 inhibits KMO in mice: 

      The authors clearly confirmed the target engagement of KNS898 in inhibiting KMO activity and, therefore, affecting upstream and downstream metabolites systemically in (peripheral fluid/ plasma) mice. Whether KNS898 effect is broad and targets systemic immune cells and whole body cells and tissue was not explored. It was also not explored if KNS898 is able to specifically inhibit KMO locally at the endometrium tissue by targeting epithelial and/or infiltrated immune cells, for example. 

      That is correct.

      It would be interesting to measure (or if it was measured to report in this section and also in Figure 2) the levels of KYN, KA and 3HK in naïve animals that did not receive KNS898. It would help to understand the net effect of KNS898 on the levels of kynurenine pathway metabolites and, therefore, justify the dose chosen.

      These data are already presented in Fig 3B-E, control group.

      Perhaps then the chosen dose could be lower considering the possible substantial changes in kynurenine pathway metabolites levels, which are reported to exert an effect in many cells, tissues and systems and could, therefore, precipitate side effects. Even more considering that the values for these metabolites are expressed as ng/ml, which hinders the comparison of the metabolite levels with the one reported for naïve animals in the literature. I would also suggest expressing the metabolite levels as nM/L. 

      This is not a relevant method of determining dose-limiting toxicity or safety pharmacology/toxicology, either non-GLP or GLP. There are international guidelines on the proper conduct of those studies. This is also why it is important not to make claims about the safety or otherwise of an experimental compound in an in vivo setting that has not explicitly complied with those regulatory standards. With regard to the units recommendation, accepted units are ng/mL or nM, not usually nM/L.

      Section - KMO blockade reduces endometrial gland-like lesion burden in experimental endometriosis in mice: 

      Line 130: It would be better to replace "blockade of 3HK production" with "reduction of 3HK production" to better reflect the results. 

      Changed to “inhibition of 3HK production”.

      Line 140: In G5 (treatment starting at Day 26/ 1 week after inoculation), is the experimental model of endometriosis already established with all pathological and phenotypic features? 

      This was not specifically tested in this experiment.

      Lines 146 - 148: It would be better to specify that "Overall, there was no significant difference IN BODY WEIGHT between G3 and the KNS898 treatment groups G4 and G5 (endometriosis + treatment from Day 26)". Otherwise, this last sentence might be interpreted as the overall conclusion of this result sub-section. 

      Thank you, a good point and has been corrected.

      The authors demonstrated with an experimental approach that KMO blockade reduces a pathological measure of endometriosis i.e., endometrial gland-like lesion burden, in experimental endometriosis in mice when both administrated concomitant but also after the disease development. Although mechanistic insights about how reduced KMO activity can reduce the developed distended endometrial gland-like structures were not explored. Therefore, it remains to be investigated which (and how ) kynurenine pathway metabolites are directly linked to the beneficial effects of KMO blockade in the experimental model of endometriosis.

      We agree.

      Although the beneficial effects on the pathological measures are evident, Figure 3 shows an exorbitant accumulation of KYN and KA and also a substantial reduction in 3HK after the treatment with KNS898, which then raises concerns about tolerability and side effects. Would this effective KNS898 dose be viable and translational as a therapeutic approach? 

      Please refer to comments above at multiple junctures about safety pharmacology and the clinical development critical path.

      Section - KMO is expressed in experimental endometriosis in mice: 

      By histological examination, the authors confirm that the treatment with KNS898 specifically reduced the KMO expression intensity in the DEGLS from mice. Therefore, the effect exerted by KNS898 locally on the KMO expression at the DEGLS could be, at least, partially responsible for the beneficial effects observed in Figure 3 i.e., the reduction of pathological measures. Although remains to be explored whether the effect of KNS898 in other cells or tissues could also be accountable for the beneficial effects exerted by KNS898 on the animal model of endometriosis. 

      This is correct.

      From a logical experimental point of view, I would suggest switching the order of the result subsection "KMO blockade reduces endometrial gland-like lesion burden in experimental endometriosis in mice" and "KMO is expressed in experimental endometriosis in mice" as well as the respective Figures 3 and 4. 

      We do not agree. Fig 3 (and section) is the macroscopic enumeration of DEGLS, Fig 4 (and section) is the microscopic and immunohistochemical evaluation of the lesions introduced in Fig 3. The sequence as originally presented is the more logical.

      Sections - KMO inhibition reduces mechanical allodynia in experimental endometriosis - and - KMO inhibition reduces mechanical allodynia in experimental endometriosis: 

      The authors suggested that the KMO inhibition with KNS898 exerts beneficial effects on behavioural paradigms related to the experimental model of endometriosis. Based on the statistical analysis performed for the author, KMO inhibition with KNS898 reduces mechanical allodynia, as well as rescues, impaired cage exploration behaviour and mobility in mice with endometriosis. However, I believe that the most indicated statistical tests for Von Frey (allodynia behaviour) and Home cage (illness behaviour) analyses over time would be repeated measures ANOVA and paired t-test, respectively (and not two-way ANOVA as performed). Therefore for a more trustful analysis and interpretation of this data set, I would suggest the authors modify the statistical analysis and report the corresponding interpretation of these tests. 

      The selection of two-way ANOVA (time and group) is suitable for this experimental analysis and its use does not invalidate the results. We agree that repeated measures ANOVA could be a valid alternative.

      Overall, the authors present a solid and useful case for KMO inhibition as a potential therapeutic strategy for endometriosis. However, the study would benefit from more detailed mechanistic insights, appropriate statistical analyses, and an evaluation of potential side effects. With these improvements, the research could have a significant impact on the field and pave the way for new treatment modalities for endometriosis. 

      We thank the reviewer for the positive comments and we have responded to the criticisms above.

      Specific recommendations for improvement: 

      • Mechanistic Studies: Conduct detailed studies to understand the local vs. systemic effects of KMO inhibition and its specific impacts on different cell types and tissues. If not feasible here, the authors could include in the discussion section a detailed overview of the possible mechanisms implicated. 

      While we agree that this is not a comprehensive mechanistic analysis, given that the ultimate therapy would be almost certainly a once daily oral dosing i.e. systemic administration, we do not consider differentiating local vs systemic effects of KMO inhibition to be critical to therapeutic development in this scenario. We do not think speculation about possible mechanisms that is not supported by experimental data should be included. Furthermore, that notion (of statements not supported by data) has been given as a criticism by the reviewers, and therefore consistency on this point must be preferable.

      • Quantitative Analysis: Include more robust quantitative methods to compare KMO expression levels in different tissues and assess the correlation between KNO expression and pathological and behavioural changes. 

      As discussed above, the pathophysiological importance of KMO is in its enzymatic activity, not in its abundance as a protein, and 3HK production is far more dependent on kynurenine substrate availability rather than KMO protein abundance.

      • Appropriate Statistics: Use the most suitable statistical tests for behavioural and other repeated measures data to ensure accurate interpretation. 

      As discussed above

      • Side Effect Evaluation: Investigate potential side effects of systemic KMO inhibition, particularly focusing on the long-term implications of altered kynurenine pathway metabolites. If not feasible here, the authors could include in the discussion section a detailed overview of the possible side effects associated as well as inform if KNS898 can cross the BBB and its implications. 

      For a novel small molecule therapeutic compound in preclinical/clinical development, there are strictly regulated preclinical and clinical development standards that need to be met. It would not be responsible to publish or make claims about safety and potential adverse effect profiles without conducting the proper panel of tests within a suitable regulatory framework.

    1. Reviewer #2 (Public review):

      Summary:

      This paper introduces a new methodology for probing time-varying causal interactions in complex dynamical systems using a novel machine-learning architecture of Temporal Autoencoders for Causal Inference (TACI) combined with a novel metric (CSGI) for assessing causal interactions using surrogate data. This is a timely contribution in the field of causal inference from temporal data which has been largely restricted to stationary time series so far. However, the benchmarking of the proposed methods could be improved.

      Strength:

      The method's capacity to uncover piecewise time-varying non-linear dynamic systems is demonstrated on synthetic datasets as well as on two real-world applications on climate and brain activity data. A particular advantage of the approach is to train a single model capturing the dynamics of the whole time series, thereby allowing for time-varying interactions to be found without retraining over different time periods.

      Weaknesses:

      (1) It is not clear why the new metric Comparative Surrogate Granger Index CSGI (Eq.6) should be better than the Extended Granger Causality Index EGCI (Eq.5), which can also be used to compare the information about y(t) contained in the actual data x(t) versus in a randomized surrogate x^s(t), as implemented in the proposed metric (Eq.6).

      (2) The benchmarking of the new approach TACI against earlier metrics (ie Surrogate Linear Granger, Convergent Cross Mapping, and Transfer Entropy) should be revised:

      (a) The details of the computation should be provided to clarify how the different metrics are estimated notably between multidimensional variables [for instance to estimate Ty->x for x=(x_1,x_2,x_3) and y=(y_1,y_2,y_3)].

      (b) Reliable implementations of the different metrics should be used, as some of the reported results do not seem right. In particular, the unidirectional examples, Eq.9 (Figure 2) and Eq.12 (Figure 5), are expected to lead to vanishing transfer entropies from Y to X, ie Ty->x =0, for all values of the coupling parameter below the synchronization threshold. This can be verified by computing transfer entropies as conditional mutual information using MIIC R package, i.e. Ty->x = I(x(t);y(t-1)|x(t-1)).

      (c) Besides, some reported benchmarks focus on peculiar non-linear systems displaying somewhat "pathological" behaviors. For instance, the two Hénon maps with unidirectional coupling Eq.12 (Figure 5) lead to an equality between the two variables, i.e. y(t)=x(t) for all t, above the synchronization threshold C>0.7. This leads mathematically to zero transfer entropy upon synchronization, as I(x(t);y(<br /> d) By contrast, Eq.9 (Fig.2) leads to strongly coupled, yet non-identical variables above the synchronization threshold. This strong coupling can be shown to yield non-vanishing transfer entropies in both directions, as observed in Figure 2c, and does not correspond to "incorrect prediction of non-existent interactions", as stated in the "Summary of Results on Artificial Test Systems". Clearly synchronized variables do interact and their bidirectional transfer entropies are actually consistent with a non-causal (or bidirectional) relationship. Only a vanishing transfer entropy in one direction implies a causal relation (in the opposite direction). Likewise, vanishing transfer entropies in both directions imply either independent variables or a spurious dependency between them due to an unobserved common cause L, i.e. X<--(L)-->Y. This is usually represented with a bidirected edge (X<-->Y), which is different from a bidirectional relation corresponding to two opposite unidirectional edges (ie X-->Y and X<--Y). It is therefore surprising that TACI metric vanishes in both directions upon synchronization in this case (Eq.9, Figure 2), as one would expect to learn variable y(t) more reliably using the actual data x(<br /> e) In order to assess TACI performance on non-stationary time series, it might be more informative to benchmark it on datasets displaying intermittency rather than synchrony. In particular, the change of causal directions over time, presented as one of the motivations for the new approach, should be more thoroughly benchmarked in the paper. For instance, it would be nice to demonstrate the tracking of the spontaneous reversal of causal relation in a simple 'toggle switch' regulatory network between two mutually repressing genes + expression noise. This is something that causal inference methods assuming stationarity cannot do.

      (3) Concerning the real-world applications, the analysis of the electrocorticography (ECoG) data does not seem to be in strong disagreement with the general trends of the original more detailed study by Tajima et al 2015. Could the authors better delineate what are the common versus conflicting findings between the two approaches? The main difference appears to be the near loss of interaction in the anesthetized state, which might be linked to TACI's tendency to report no interaction between synchronized variables as discussed in d) above. Does the anesthetized state correspond to a global synchrony of the brain regions? This could be easily validated by a more direct analysis of synchrony.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This work sets out to elucidate mechanistic intricacies in inflammatory responses in pneumonia in the context of the aging process (Terc deficiency - telomerase functionality).

      Strengths:

      Very interesting, conceptually speaking, approach that is by all means worth pursuing. An overall proper approach to the posited aim.

      We want to thank the reviewer for taking the time to review our manuscript and for providing positive feedback regarding our research question.  

      Weaknesses:

      The work is heavily underpowered and may have statistical deficits. This precludes it in its current state from drawing unequivocal conclusions.

      Thank you for this essential and valuable comment. We fully accept that the small sample size of the Tercko/ko mice is a major limitation of our study and transparently discuss this in our manuscript.  However, due to Animal Welfare regulations, only a reduced number of mice were approved because of the strong burden of disease. Consequently, only three non-infected and five infected mice were available to us. This reduced number of mice presents a clear limitation to our study. However, due to ethical considerations related to animal welfare and sustainability, as well as compliance with German animal welfare regulations, it is not possible to obtain additional Tercko/ko mice to increase the dataset.

      The animal studies are an important aspect of our study; however, our hypothesis was also investigated at multiple levels, including in an in vitro co-culture model (Figure 5), to ensure comprehensive analysis. Thus, we clearly demonstrated that S. aureus pneumonia in Tercko/ko mice leads to a more severe phenotype, orchestrated by the dysregulation of both innate and adaptive immune response.

      Reviewer #2 (Public Review):

      Summary:

      The authors demonstrate heightened susceptibility of Terc-KO mice to S. aureus-induced pneumonia, perform gene expression analysis from the infected lungs, find an elevated inflammatory (NLRP3) signature in some Terc-KO but not control mice, and some reduction in T cell signatures. Based on that, They conclude that disregulated inflammation and T-cell dysfunction play a major role in these phenomena.

      Strengths:

      The strengths of the work include a problem not previously addressed (the role of the Terc component of the telomerase complex) in certain aspects of resistance to bacterial infection and innate (and maybe adaptive) immune function.

      We would like to thank the reviewer for the positive feedback regarding our aim to investigate the impact of Terc deletion on the pulmonary immune response to S. aureus.  

      Weaknesses:

      The weaknesses outweigh the strengths, dominantly because conclusions are plagued by flaws in experimental design, by lack of rigorous controls, and by incomplete and inadequate approaches to testing immune function. These weaknesses are as follows

      (1) Terc-KO mice are a genomic knockout model, and therefore the authors need to carefully consider the impact of this KO on a wide range of tissues. This, however, is not the case. There are no attempts to perform cell transfers or use irradiation chimera or crosses that would be informative.

      We thank the reviewer for bringing up this important point. The aim of our study, however; was to investigate the impact of Terc deletion in the lung and on the response to bacterial pneumonia, rather than to provide a comprehensive characterization of the Tercko/ko model itself. This characterization of different tissues and cell types has already been conducted by previous studies. For instance, studies that characterize the general phenotype of the model (Herrera et al., 1999; Lee et al., 1998; Rudolph et al., 1999) but also investigations that shed light on the impact of Terc deletion on specific cell types such as microglia (Khan et al., 2015) or T cells (Matthe et al., 2022). The impact of Terc deletion on T cells is also discussed in our manuscript in lines 89 to 105. Furthermore, a section about the general phenotype of the Terc deletion model is included in the introduction in lines 126 to 138. Thus we discussed the relevant literature regarding Tercko/ko mice in our manuscript and attempted to provide a more in-depth characterization of the lung by investigating the inflammatory response to infection as well as changes in the gene expression (Figure 2-4).  

      (2) Throughout the manuscript the authors invoke the role of telomere shortening in aging, and according to them, their Terc-KO mice should be one potential model for aging. Yet the authors consistently describe major differences between young Terc-KO and naturally aging old mice, with no discussion of the implications. This further confuses the biological significance of this work as presented.

      Thank you for mentioning this relevant point. We want to apologize for the confusion regarding this matter. While Tercko/ko mice are a well-established model for premature aging, these effects become more apparent with increasing generations (G) and thus, G5 and 6 mice are the most affected by Terc deletion (Lee et al., 1998; Wong et al., 2008).

      Thus, while Tercko/ko mice are a common model for premature aging, this accelerated aging phenotype is predominantly apparent in later-generation Tercko/ko (G5 and 6) or aged Tercko/ko mice (Lee et al., 1998; Wong et al., 2008). Since the aim of this study was to analyze the impact of Terc deletion on the lung and its immune response to bacterial infections instead of the impact of telomere shortening and telomerase dysfunction, young G3 Tercko/ko mice (8 weeks) were used in this study. This is also mentioned in the lines 131-134. In this study, Tercko/ko mice were used not as a model of aging, but rather as a model specifically for Terc deletion. The old WT mice function as a control cohort to observe possible common but also deviating effects between aging and Terc deletion. In our sequencing data, we observe that uninfected young WT mice are very similar to uninfected Tercko/ko mice. Other studies have also reported this lack of major differences between uninfected WT and Tercko/ko mice in the G3 knockout mice (Kang et al., 2018). Conversely, uninfected young WT and Tercko/ko mice exhibited great differences, for instance, regarding the numbers of differentially expressed genes (Supplemental Figure 1H). Thus, differences between naturally aged mice and young G3 Tercko/ko mice are not surprising. To clarify this aspect we reconstructed the paragraph discussing the Tercko/ko mice (lines 126-134). Additionally we added a paragraph explaining the purpose of the naturally aged mice to the lines 134 to 138:

      “As control cohort age-matched young WT mice were utilized. To investigate whether Terc deletion, beyond critical telomere shortening, impacts the pulmonary immune response, we used young Tercko/ko mice. Additionally, naturally aged mice (2 years old) were infected to explore the potential link to a fully developed aging phenotype.”

      (3) Related to #2, group design for comparisons lacks a clear rationale. The authors stipulate that TercKO will mimic natural aging, but in fact, the only significant differences seen between groups in susceptibility to S. aureus are, contrary to the authors' expectation, between young Terc-KO and naturally old mice (Figures 1A and B, no difference between young Terc-KO and young wt); or there are no significant differences at all between groups (Figures 1, C, D,).

      We thank the reviewer for this essential comment. As mentioned above the Tercko/ko mice in this study are not selected to model natural aging. To model telomerase dysfunction and accelerated aging selection of later generation or aged Tercko/ko mice would have been more suitable. 

      The lack of statistical significance in some figures is likely due to the heterogeneity of disease phenotype of S. aureus infection in mice, which is a limitation of our study that we discuss in our discussion section in lines 576-582. The phenotype of S. aureus infection can vary greatly within a mouse population, highlighting the limitations of mice as a model for S. aureus infections. To account for this heterogeneity we divided the infected Tercko/ko mice cohort into different degrees of severity based on the clinical score and the presence of bacteria in organs other than the lung (mice with systemic infection). 

      Despite the heterogeneity especially within the Tercko/ko mice cohort the differences between the knockout and young as well as old WT mice were striking. Including the fatal infections, 80% of the Tercko/ko mice had a severe course of disease, while none of the WT mice displayed a severe course (Figure 1A, B and Supplemental Figure 1A, B). This hints towards a clear role of Terc in the response to S. aureus infection in mice. Thus while in some figures the differences are not significant, strong trends towards a more severe phenotype of S. aureus infection in the Tercko/ko mice regarding bacterial load, score and inflammatory response could be observed in our study. 

      Another example of inadequate group design is when the authors begin dividing their Terc-KO groups by clinical score into animals with or without "systemic infection" (the condition where a bacterium spreads uncontrollably across the many organs and via blood, which should be properly called sepsis), and then compare this sepsis group to other groups (Supplementary Figures 1G; Figure 2; lines 374-376 and 389391). This gives them significant differences in several figures, but because they did not clearly indicate where they applied this stratification in the figure legends, the data are somewhat confusing. Most importantly, methodologically it is highly inappropriate to compare one mouse with sepsis to another one without. If Terc-KO mice with sepsis are a comparator group, then their controls have to be wild-type mice with sepsis, who are dealing with the same high bacterial load across the body and are presumably forced to deploy the same set of immune defenses.

      We sincerely appreciate the significant time and effort you have invested in reviewing our manuscript. However, with all due respect, we must point out that the definition of sepsis you have referenced is considered outdated. According to the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3), sepsis is defined as "a life-threatening organ dysfunction caused by a dysregulated host response to infection" (Marvin Singer, 2016, JAMA). Given this fundamental misunderstanding of our findings, we find the comment regarding the inadequacy of our groups to be both dismissive and lacking in scientific merit. We would like to emphasize that the group size used in our study is consistent with accepted standards in infection research. We strongly reject any insinuations of inadequacy that have been repeatedly mentioned throughout the review.

      In order to provide a nuanced investigation of disease severity in Tercko/ko mice, we added the term “systemic infection” to the figures whenever the mice were divided into groups of mice with and without systemic infection. This is the case for Figure 2A and Supplemental Figure 1C-E. The division into mice with and without systemic infection is also mentioned in the figure legend of Figure 2A in lines 932 to 935 and for Supplemental Figure 1 in lines 1052-1053. We agree that Supplemental Figure 1G is somewhat confusing as the mice with systemic infection are highlighted in this graph but not included as a separate group within our sequencing analysis. We added a sentence to the figure legend clarifying this (lines 1042-1044):

      “Nevertheless, the infected Tercko/ko mice were considered one group for the expression analysis and not split into separate groups for the subsequent analysis.”

      Additionally, we revised the section regarding this grouping in different degrees of severity in our Material and Methods section to clarify that this division was only performed for specific analysis (line 191):

      “…for the indicated analysis.”

      Furthermore, the mice which were classified as systemically infected mice were not septic mice, as mentioned above. Those mice were classified by us as systemically infected based on their clinical score and the presence of bacteria in other organs than the lung as stated in the lines 188-191 and 377-381. Bacteremia is a symptom of very severe cases of hospital-acquired pneumonia with a very high mortality (De la Calle et al., 2016).

      Therefore, the systemically infected mice or rather mice with bacteremia display an especially severe pneumonia phenotype, which is distinct from sepsis. The presence of this symptom in our Tercko/ko mice further highlights the clinical relevance of our study. This aspect was added to the manuscript in the lines 568-570.

      “The detection of bacteria in extra pulmonary organs is of particular interest, as bacteremia is a symptom of severe pneumonia and is associated with high mortality (De la Calle et al., 2016).”

      (4) The authors conclude that disregulated inflammation and T-cell dysfunction play a major role in S. aureus susceptibility. This may or may not be an important observation, because many KO mice are abnormal for a variety of reasons, and until such reasons are mechanistically dissected, the physiological importance of the observation will remain unclear.

      Two points are important here. First, there is no natural counterpart to a Terc-KO, which is a complete loss of a key non-enzymatic component of the telomerase complex starting in utero. 

      Second, the authors truly did not examine the key basic features of their model, including the features of basic and induced inflammatory and immune responses. This analysis could be done either using model antigens in adjuvants, defined innate immune stimuli (e.g. TLR, RLR, or NLR agonists), or microbial challenge. The only data provided along these lines are the baseline frequencies of total T cells in the spleen of the three groups of mice examined (not statistically significant, Figure 4B). We do not know if the composition of naïve to memory T cell subsets may have been different, and more importantly, we have no data to evaluate whether recruitment of the immune response (including T cells) to the lung upon microbial challenge is similar or different. So, what are the numbers and percentages of T cells and alveolar macrophages in the lung following S. aureus challenge and are they even comparable or are there issues in mobilizing the T cell response to the site of infection? If, for example, Terc-KO mice do not mobilize enough T cells to the lung during infection, that would explain the paucity in many T-cellassociated genes in their transcriptomic set that the authors report. That in turn may not mean dysfunction of T cells but potentially a whole different set of defects in coordinating the response in Terc-KO mice.

      We thank the reviewer for highlighting these important aspects. Regarding the first point, indeed there is no naturally occurring deletion of Terc in humans. However, studies reported reduced expression of Terc and Tert in the tissues of aged mice and rats (Tarry-Adkins et al., 2021; Zhang et al., 2018). Terc itself has been found to have several important immunomodulatory functions such as the activation of the NFκB or PI3-kinase pathway (Liu et al., 2019; Wu et al., 2022). As those aforementioned pathways are relevant for the immune response to S. aureus infections, the authors were interested in exploring the impact of Terc deletion on the pulmonary immune response. The potential immunomodulatory functions of Terc are discussed in lines 106-121. To further clarify our rationale we added a sentence to the introduction in lines 121-125.

      “Interestingly, downregulation of Terc and Tert expression in tissues of aged mice and rats has been found (Tarry-Adkins, Aiken, Dearden, Fernandez-Twinn, & Ozanne, 2021; Zhang et al., 2018). Therefore, as a potential immunomodulatory factor reduced Terc expression could be connected to agerelated pathologies.”

      Regarding the second point, as we focused on the effect of Terc deletion in the lung and its role in S. aureus infection, we investigated inflammatory and immune response parameters relevant to this setting. For instance, inflammation parameters in the lungs of all three mice cohorts were measured to investigate differences in the inflammatory response in the non-infected and infected mice (Figure 2A). Those measurements showed no baseline difference in key inflammatory parameters between young WT and Tercko/ko mice, which is consistent with previous findings (Kang et al., 2018). The inflammatory response to infection with S. aureus in the Tercko/ko mice cohort differed significantly from the other cohorts (Figure 2A), hinting towards a dysregulated inflammatory response due to Terc deletion. Furthermore, we investigated general immune cell frequencies such as dendritic cells, macrophages, and B cells in the spleen of all three mice cohorts to gather a baseline understanding of the general immune cell populations. In our manuscript only total T cell frequencies were included due to its relevance for our data regarding T cells (Figure 4B). This data could show that there was no difference of total amount of T cells in the spleen of all three mice cohorts. For a more detailed insight into our analysis we added the frequencies of the other immune cell populations analyzed in the spleen as a Supplemental Figure 3B-F. Additionally, a figure legend for the graphs was added to lines 1075-1094.

      Therefore, while we did not analyze baseline frequencies of specific populations of T cells, we analyzed and characterized the inflammatory and immune response of our model in a way relevant to our research question. 

      The differences observed in T cell marker and TCR gene expression was also partly present between the uninfected and infected Tercko/ko mice such as the complete absence of CD247 expression in infected Tercko/ko, which is however expressed in uninfected mice of this cohort (Figure 4A, C and D). Thus, this effect cannot be solely attributed to an inadequate mobilization of T cells to the lung after infectious challenge. However, we agree that a more detailed insight into recruited immune cells to the lung or frequencies of different T cell populations could contribute to a better understanding of the proposed mechanism and would be an interesting experiment to conduct in further studies. We accept this as a limitation of our study and included it in our discussion section in lines 719-723:

      “As total CD4+ T cells were analyzed in this study, it would be useful to investigate specific T cell populations such as memory and effector T cells to elucidate the potential mechanism leading to T cell dysfunctionality in further detail. Additionally, analysis of differences in immune cell recruitment to the lungs between young WT and Tercko/ko mice would be relevant.”

      (5) Related to that, immunological analysis is also inadequate. First, the authors pull signatures from the total lung tissue, which is both imprecise and potentially skewed by differences, not in gene expression but in types of cells present and/or their abundance, a feature known to be affected by aging and perhaps by Terc deficiency during infection. Second, to draw any conclusions about immune responses, the authors would have to track antigen-specific T cells, which is possible for a wide range of microbial pathogens using peptide-MHC multimers. This would allow highly precise analysis of phenomena the authors are trying to conclude about. Moreover, it would allow them to confirm their gene expression data in populations of physiological interest

      We thank the reviewer for highlighting this important and relevant point. In our study, we aimed to investigate the role of Terc expression in modulating inflammation and the immune response to S. aureus infection in the lung. To address this, we examined the overall impact of age, genotype, and infection on lung inflammation and gene expression. Therefore, sequencing of total lung tissue was essential for addressing the research question posed. Our findings demonstrate that Tercko/ko mice exhibit a more severe phenotype following S. aureus infection, characterized by an increased bacterial load and heightened lung inflammation (Figures 1 and 2). Furthermore, our data suggest that Terc plays a role in regulating inflammation through activation of the NLRP3 inflammasome, along with the dysregulation of several T cell marker genes (Figures 2, 4, and 5). However, this study lacks a detailed analysis of distinct T cell populations, including antigen-specific T cells, as noted earlier. Investigating these aspects in future studies would be valuable to validate and expand upon our findings. We have incorporated these suggestions into the discussion section (lines 719-723)

      “As total CD4+ T cells were analyzed in this study, it would be useful to investigate specific T cell populations such as memory and effector T cells to elucidate the potential mechanism leading to T cell dysfunctionality in further detail. Additionally, analysis of differences in immune cell recruitment to the lungs between young WT and Tercko/ko mice would be relevant.”

      Nevertheless, our study provides first evidence of a potential connection between T cell functionality and Terc expression.  

      Third, the authors co-incubate AM and T cells with S. aureus. There is no information here about the phenotype of T cells used. Were they naïve, and how many S. aureus-specific T cells did they contain? Or were they a mix of different cell types, which we know will change with aging (fewer naïve and many more memory cells of different flavors), and maybe even with a Terc-KO? Naïve T cells do not interact with AM; only effector and memory cells would be able to do so, once they have been primed by contact with dendritic cells bringing antigen into the lymphoid tissues, so it is unclear what the authors are modeling here. Mature primed effector T cells would go to the lung and would interact with AM, but it is almost certain that the authors did not generate these cells for their experiment (or at least nothing like that was described in the methods or the text).

      Thank you for bringing up this important question. For the co-cultivation experiment of T cells and alveolar macrophages, total CD4+ T cells of both young WT and Tercko/ko were used. We did not select for a specific population of T cells. Our sequencing data indicated the complete downregulation of CD247 expression, which is an important part of the T cell receptor, in the lungs of infected Tercko/ko mice (Figure 4A, C and D). Given that this factor is downregulated under chronic inflammatory conditions, we investigated the impact of the inflammatory response in alveolar macrophages on the expression of various T cell-derived cytokines, as well as CD247 expression (Figure 5D, E) (Dexiu et al., 2022). This aspect is also highlighted in the discussion in lines 622-636. Therefore, a co-cultivation model of T cells and alveolar macrophages was established and confronted with heat-killed S. aureus to elicit an inflammatory response of the macrophages. To emphasize this purpose, we have revised our statement about the model setup in lines 516-518 of the manuscript: 

      “An overactive inflammatory response could be a potential explanation for the dysregulated TCR signaling.”

      The authors hope this will clarify the intent behind the model setup.

      (6) Overall, the authors began to address the role of Terc in bacterial susceptibility, but to what extent that specifically involves inflammation and macrophages, T cell immunity, or aging remains unclear at present.

      We thank the reviewer for the helpful and relevant comments. The authors accept the limitations of the presented study such as the reduced number of Tercko/ko mice and the limitations of murine models for S. aureus infection itself and discuss those in the discussion section in the lines 558-560; 576-582; 688-690 and 719-725. However, we hope that our responses have provided sufficient evidence to convince the reviewer that our data supports a clear role for Terc expression in regulating the immune response to bacterial infections, particularly with respect to inflammation and its potential connection to T cell functionality.  

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      The good element first:

      I read this paper with genuine interest and applaud the authors for investigating the posited question. I consider it by all means scientifically relevant in the context of physiological/pathophysiological aging and reaction to a disease (here pneumonia). The Terc deletion model looks very appropriate for the question and the methodology is very advanced/in-depth. The data flow/selection of endpoints and assays is very logical to me. Moreover, I like the breakdown of pneumonia into varying levels of severity.

      We thank the reviewer for their time and effort taken to revise our manuscript. Additionally, we are grateful to receive your positive feedback regarding our study design and research question.

      The weaknesses:

      (1) I cannot help but notice that the study is heavily underpowered. As such, it is inadmissible. The key reason is that it is the first of its kind and seminal findings must be strongly propped by the evidence. It is apparent to me that the data scatter presented in the figures tends to be abnormally distributed (e.g. obvious bimodal distribution in some groups). Therefore, the presented comparisons (even if stat. sign) can be heavily misleading in terms of: i) the true magnitude of the observed effects and ii) possible type 2 error in some cases of p value >0.05. Solution: repeat the study to ensure reasonable power/reliability. This will also make it stronger as it will immediately demonstrate its reproducibility (or lack of it).

      Thank you for bringing up this extremely relevant point. We acknowledge the issue of the small sample size of Tercko/ko mice as a major limitation of our study. This limitation is also included in our discussion section in the lines 558-560. Thus we fully agree with this limitation and transparently discuss this in our manuscript. However, due to the strict German animal welfare regulations it is not possible to obtain more Tercko/ko mice, as mentioned above. Furthermore, since fatal infections occurred in the Tercko/ko mice cohort we had a reduced number of mice available. 

      However, the differences between the Tercko/ko and WT mice were striking. Including the fatal infections 80% of the Tercko/ko mice had a severe course of disease, while none of the WT mice displayed a severe course. This hints towards a clear role of Terc in the response to S. aureus infection in mice.  

      (2) In the stat analysis section of M&Ms, the authors feature only 1 sentence. This cannot be. A detailed stats workup needs to be included there. This is very much related to the above weakness; e.g. it is impossible to test for normality (to choose an appropriate post-hoc test) with n=3. Back to square one: study underpowered.

      We thank the reviewer for highlighting this important aspect. We carefully revised the method section in lines 357-360 to include all relevant information: 

      “Data are presented as mean ± SD, or as median with interquartile range for violin and box plots, with up to four levels of statistical significance indicated. P-values were calculated using Kruskal-Wallis test. Individual replicates are represented as single data points.”

      (3) Pneumonia severity. While I noted that as a strength, I also note it as weakness here. It looks to me like the authors stopped halfway with this. I totally support testing a biological effect(s) such as the one investigated here across a spectrum of a given disease severity. The authors mention that they had various severity phenotypes produced in their model but this is not visible in the data figs. I strongly suggest including that as well; i.e., to study the posited question in the severe and mild pneumonia phenotype. This is a very smart path and previous preclinical research clearly demonstrated that this severe/mild distinction is very relevant in the context of the observed responses (their presence/absence, longevity, dynamics, etc). I realize this is challenging, thus, I would probably use this approach in the Terc k/o model as sort of a calibrator to see whether the exacerbation observed in the current setup (severe?) will be also present in a mild pneumonia phenotype. S. aureus can be effectively titrated to produce pneumonia of varying severity.

      We thank the reviewer for bringing up this relevant point. 

      In our study, we could observe heterogeneity within the infected Tercko/ko cohort. Therefore as pointed out by the reviewer we assigned different degrees of severity to those groups based on clinical scores, the fatal outcome of the disease (fatal subgroup), and the presence of bacteria in organs other than the lungs (systemic infection subgroup) as stated in our materials and methods part in the lines 188-191 (Supplemental Figure 1A and B). Moreover, we highlighted this difference in a number of our figures. For example, when categorizing the mice into groups with and without systemic infection, we noticed that the mice with systemic infection demonstrated a higher bacterial load, significant body weight loss, and increased lung weight (see Supplemental Figure 1C-E). Interestingly, the two mice with systemic infection clustered separately from the other mice, indicating that the mice with systemic infection are transcriptomically distinct from the other mice cohorts (Supplemental Figure 1G). Additionally, the inflammatory response was exclusively elevated in the lungs of mice with systemic infection (Figure 2C). Thus, we included this distinction in several figures and attempted to study the differences between those subgroups but also their similarities. For instance, we could observe that some changes in the transcriptome were present in all three infected Tercko/ko mice such as the complete absence of CD247 expression at 24 hpi (Figure 4D). This distinction therefore provided a more detailed insight into the underlying mechanisms of disease severity in Tercko/ko mice and is lacking in other studies. We agree with the reviewer, that a study investigating mild and severe pneumonia phenotypes would be clinically relevant. However, as noted above, due to ethical considerations related to animal welfare and sustainability, as well as compliance with German animal welfare regulations, it is not possible to obtain additional Tercko/ko mice to carry out the proposed experiment. 

      (4) Please read ARRIVE guidelines and note the relevant info in M&Ms as ARRIVE guidelines point out.

      Thank you for emphasizing this crucial aspect. We revised our materials and methods section according to the ARRIVE guidelines (lines 179-206).

      “Tercko/ko mice aged 8 weeks, were used for infection studies (n = 8; non-infected = 3; infected = 5). Female young WT (age 8 weeks) and old WT (age 24 months) C57Bl/6 mice (both n = 10; non-infected = 5; infected = 5) were purchased from Janvier Labs (Le Genest-Saint-Isle, France). All infected mouse cohorts were compared to their respective non-infected controls, as well as to the infected groups from other cohorts. Additionally, comparisons were made between the non-infected cohorts across all groups.

      All mice were anesthetized with 2% isoflurane before intranasal infection with S. aureus USA300 (1x108 CFU/20µl) per mouse. After 24 hours, the mice were weighed and scored as previously described (Hornung et al., 2023). Infected Tercko/ko mice were grouped into different degrees of severity based on their clinical score, fatal outcome of the disease (fatal) and the presence of bacteria in organs other than the lung (systemic infection) for the indicated analysis. Mice with fatal infections were excluded from subsequent analyses, with only their final scores being reported. The mice were sacrificed via injection of an overdose of xylazine/ketamine and bleeding of axillary artery after 24 hpi. BAL was collected by instillation and subsequent retrieval of PBS into the lungs. Serum and organs were collected. Bacterial load in the BAL, kidney and liver was determined by plating of serially diluted sample as described above. For this organs were previously homogenized in the appropriate volume of PBS. Gene expression was analyzed in the right superior lung lobe. Lobes were therefore homogenized in the appropriate amount of TriZol LS reagent (Thermo Fisher Scientific, Waltham, MA, US) prior to RNA extraction. The left lung lobe was embedded into Tissue Tek O.C.T. (science services, Munich, Germany) and stored at 80°C until further processing for histological analysis. Cytokine measurements were performed using the right inferior lung lobe. Lobes were previously homogenized in the appropriate volume of PBS. Remaining organs were stored at -80°C until further usage. Mouse studies were conducted without the use of randomization or blinding.“

      (5) There are also some other descriptive deficits but they are of a much smaller caliber so I do not list them.

      We thank the reviewer for their valuable and insightful suggestions for improving our manuscript. We hope that our responses and the corresponding revisions address these suggestions satisfactorily.

      Concluding: the investigative idea is great/interesting and the methodological flow is adequate but the low power makes this study of low reliability in its current form. I strongly urge the authors to walk the extra mile with this work to make it comprehensive and reliable. Best of luck!

      Reviewer #2 (Recommendations For The Authors):

      (1) Many legends are uninformative and do not contain critical information about the experiments. For example, Figure 2A with cytokine measurements (in lung homogenates?) is likely showing data from an ELISA or Luminex test, but there is no mention of that in the legend. It stands next to Figure 2B, which is a gene expression map, again, likely from the lung (prepared how, normalized how, etc?) lacking even the most basic information. Further, Figure 2D has no information on the meaning/effect size of gene ratios on the x-axis. Figures 3 and 4 are presumably the subsets of their transcriptome data set (whole lung, harvested on d ?? post-infection), but that is just a guess on my part. Even in the main text, the timing and the controls for the transcriptomic study are not stated (ln. 398 and onwards). The authors really need to revise the figure legends and provide all the details that an average reader would need to be able to interpret the data.

      We thank the reviewer for bringing up this important point. The figure legends of all figures including supplemental figures were revised to ensure they include all relevant data necessary for accurate interpretation of the graphs. Additionally, we clarified the sequenced samples in lines 427-429:

      “We performed mRNA sequencing of the murine lung tissue of infected and non-infected mice at 24 hpi to elucidate potential differentially expressed genes that contribute to the more severe illness of Tercko/ko mice.”

      (2) Telomere shortening affects differentially different cells and its role in aging is nuanced - different in mesenchymal cells with no telomerase induction, in non-replicating cells, and in hematopoietic cells that can readily induce telomerase. The authors should be mindful of that in setting up their introduction and discussion.

      Thank you for mentioning this essential aspect. We revised our introduction and discussion to reflect the nuanced role of telomerase shortening in different tissues (lines 83-92 and 690-695):

      “Telomerase activity is restricted to specific tissues and cell types, largely dependent on the expression of Tert. While Tert is highly expressed in stem cells, progenitor cells, and germline cells, its expression is minimal in most differentiated cells (Chakravarti, LaBella, & DePinho, 2021). Consequently, the impact of telomerase dysfunction on tissues varies according to their self-renewal rate. (Chakravarti et al., 2021). One important aspect of telomere dysfunction is the impact of telomere shortening on the immune system as well as the hematopoietic system. Tissues or organ systems that are highly replicative, such as the skin or the hematopoietic system, are affected first by telomere shortening (Chakravarti et al., 2021).”

      “It is important to note that telomere shortening has a significant impact on the immune system. Although young Tercko/ko mice were used in this study, telomere shortening is still likely to be a contributing factor. Therefore, further experiments investigating the role of T cell senescence in this model should therefore be conducted.”

      (3) Syntax and formulations need to be improved and made more scientifically precise in several spots. Specifically, in 62-63, the authors say that the aged immune system "is also discussed to be more irritable", please change to reflect the common notion that the reaction to infection is dysregulated; in many cases inflammation itself is initially blunted, misdirected, and of different type (e.g. for viruses, the key IFN-I responses are not increased but decreased). In lines 114-117, presumably, the two sentences were supposed to be connected by a comma, although some editing for clarity is probably needed regardless. Line 252, please change "unspecific" to "non-specific". Line 264, please capitalize German.

      We thank the reviewer for bringing these important points to our attention. We revised our introduction regarding the aged immune response in lines 61-69:

      “Age-related dysregulation of the immune response is also characterized by inflammaging, defined as the presence of elevated levels of pro-inflammatory cytokines in the absence of an obvious inflammatory trigger (Franceschi et al., 2000; Mogilenko, Shchukina, & Artyomov, 2022). Additionally, immune cells, such as macrophages, exhibit an activated state that alters their response to infection (Canan et al., 2014). In contrast, the immune response of macrophages to infectious challenges has been shown to be initially impaired in aged mice (Boe, Boule, & Kovacs, 2017). Thus aging is a relevant factor impacting the pulmonary immune response.”

      Sentences were edited to provide more clarity in lines 131-134:

      “Although G3 Tercko/ko mice with shortened telomeres were used in this study, they were infected at a young age (8 weeks). This approach allowed for the investigation of Terc deletion effects rather than telomere dysfunction.”

      “Unspecific was changed to “non-specific” in line 282 and “German” was capitalized in line 293 and 558.

      We appreciate and thank you for your time spent processing this manuscript and look forward to your response.

      References

      De la Calle, C., Morata, L., Cobos-Trigueros, N., Martinez, J. A., Cardozo, C., Mensa, J., & Soriano, A. (2016). Staphylococcus aureus bacteremic pneumonia. European Journal of Clinical Microbiology & Infectious Diseases, 35(3), 497-502. https://doi.org/10.1007/s10096-015-2566-8  

      Dexiu, C., Xianying, L., Yingchun, H., & Jiafu, L. (2022). Advances in CD247. Scand J Immunol, 96(1), e13170. https://doi.org/10.1111/sji.13170  

      Herrera, E., Samper, E., Martín-Caballero, J., Flores, J. M., Lee, H. W., & Blasco, M. A. (1999). Disease

      states associated with telomerase deficiency appear earlier in mice with short telomeres. Embo j, 18(11), 2950-2960. https://doi.org/10.1093/emboj/18.11.2950  

      Hornung, F., Schulz, L., Köse-Vogel, N., Häder, A., Grießhammer, J., Wittschieber, D., Autsch, A., Ehrhardt, C., Mall, G., Löffler, B., & Deinhardt-Emmer, S. (2023). Thoracic adipose tissue contributes to severe virus infection of the lung. International Journal of Obesity, 47(11), 10881099. https://doi.org/10.1038/s41366-023-01362-w  

      Kang, Y., Zhang, H., Zhao, Y., Wang, Y., Wang, W., He, Y., Zhang, W., Zhang, W., Zhu, X., Zhou, Y., Zhang, L., Ju, Z., & Shi, L. (2018). Telomere Dysfunction Disturbs Macrophage Mitochondrial Metabolism and the NLRP3 Inflammasome through the PGC-1α/TNFAIP3 Axis. Cell Reports, 22(13), 3493-3506. https://doi.org/https://doi.org/10.1016/j.celrep.2018.02.071  

      Khan, A. M., Babcock, A. A., Saeed, H., Myhre, C. L., Kassem, M., & Finsen, B. (2015). Telomere dysfunction reduces microglial numbers without fully inducing an aging phenotype. Neurobiology of Aging, 36(6), 2164-2175. https://doi.org/https://doi.org/10.1016/j.neurobiolaging.2015.03.008  

      Lee, H.-W., Blasco, M. A., Gottlieb, G. J., Horner, J. W., Greider, C. W., & DePinho, R. A. (1998). Essential role of mouse telomerase in highly proliferative organs. Nature, 392(6676), 569-574. https://doi.org/10.1038/33345  

      Liu, H., Yang, Y., Ge, Y., Liu, J., & Zhao, Y. (2019). TERC promotes cellular inflammatory response independent of telomerase. Nucleic Acids Research, 47(15), 8084-8095. https://doi.org/10.1093/nar/gkz584  

      Matthe, D. M., Thoma, O. M., Sperka, T., Neurath, M. F., & Waldner, M. J. (2022). Telomerase deficiency reflects age-associated changes in CD4+ T cells. Immun Ageing, 19(1), 16. https://doi.org/10.1186/s12979-022-00273-0  

      Rudolph, K. L., Chang, S., Lee, H. W., Blasco, M., Gottlieb, G. J., Greider, C., & DePinho, R. A. (1999). Longevity, stress response, and cancer in aging telomerase-deficient mice. Cell, 96(5), 701-712. https://doi.org/10.1016/s0092-8674(00)80580-2  

      Tarry-Adkins, J. L., Aiken, C. E., Dearden, L., Fernandez-Twinn, D. S., & Ozanne, S. (2021). Exploring Telomere Dynamics in Aging Male Rat Tissues: Can Tissue-Specific Differences Contribute to Age-Associated Pathologies? Gerontology, 67(2), 233-242. https://doi.org/10.1159/000511608  

      Wong, L. S. M., Oeseburg, H., de Boer, R. A., van Gilst, W. H., van Veldhuisen, D. J., & van der Harst, P. (2008). Telomere biology in cardiovascular disease: the TERC−/− mouse as a model for heart failure and ageing. Cardiovascular Research, 81(2), 244-252. https://doi.org/10.1093/cvr/cvn337  

      Wu, S., Ge, Y., Lin, K., Liu, Q., Zhou, H., Hu, Q., Zhao, Y., He, W., & Ju, Z. (2022). Telomerase RNA TERC and the PI3K-AKT pathway form a positive feedback loop to regulate cell proliferation independent of telomerase activity. Nucleic Acids Res, 50(7), 3764-3776. https://doi.org/10.1093/nar/gkac179  

      Zhang, M. W., Zhao, P., Yung, W. H., Sheng, Y., Ke, Y., & Qian, Z. M. (2018). Tissue iron is negatively correlated with TERC or TERT mRNA expression: A heterochronic parabiosis study in mice. Aging (Albany NY), 10(12), 3834-3850. https://doi.org/10.18632/aging.101676

    1. Author response:

      The following is the authors’ response to the current reviews.

      We are grateful to the reviewers for their positive assessment of the revised version of the article.

      Please find below our answers to the last, minor comments of the reviewers.

      We thank the reviewer for this important comment. In our live imaging experiments, we actually tracked the dorsal and ventral borders of the omp:yfp positive clusters in control and sly mutant embryos. These measurements showed that the omp:yfp positive clusters are more elongated along the DV axis in mutants as compared with control siblings, as seen on fixed samples (data not shown), suggesting that this difference in tissue shape is not due to fixation.

      Reviewer #4 (Public review):

      Summary:

      In this elegant study XX and colleagues use a combination of fixed tissue analyses and live imaging to characterise the role of Laminin in olfactory placode development and neuronal pathfinding in the zebrafish embryo. They describe Laminin dynamics in the developing olfactory placode and adjacent brain structures and identify potential roles for Laminin in facilitating neuronal pathfinding from the olfactory placode to the brain. To test whether Laminin is required for olfactory placode neuronal pathfinding they analyse olfactory system development in a well-established laminin-gamma-1 mutant, in which the laminin-rich basement membrane is disrupted. They show that while the OP still coalesces in the absence of Laminin, Laminin is required to contain OP cells during forebrain flexure during development and maintain separation of the OP and adjacent brain region. They further demonstrate that Laminin is required for growth of OP neurons from the OP-brain interface towards the olfactory bulb. The authors also present data describing that while the Laminin mutant has partial defects in neural crest cell migration towards the developing OP, these NCC defects are unlikely to be the cause of the neuronal pathfinding defects upon loss of Laminin. Altogether the study is extremely well carried out, with careful analysis of high-quality data. Their findings are likely to be of interest to those working on olfactory system development, or with an interest in extracellular matrix in organ morphogenesis, cell migration, and axonal pathfinding.

      Strengths:

      The authors describe for the first time Laminin dynamics during the early development of the olfactory placode and olfactory axon extension. They use an appropriate model to perturb the system (lamc1 zebrafish mutant), and demonstrate novel requirements for Laminin in pathfinding of OP neurons towards the olfactory bulb.

      The study utilises careful and impressive live imaging to draw most of its conclusions, really drawing upon the strengths of the zebrafish model to investigate the role of laminin in OP pathfinding. This imaging is combined with deep learning methodology to characterise and describe phenotypes in their Laminin-perturbed models, along with detailed quantifications of cell behaviours, together providing a relatively complete picture of the impact of loss of Laminin on OP development.

      Weaknesses:

      Some of the statistical tests are performed on experiments where n=2 for each condition (for example the measurements in Figure S2) - in places the data is non-significant, but clear trends are observed, and one wonders whether some experiments are under-powered.

      We initially planned the electron microscopy experiments in order to analyse 3 embryos per genotype per stage. However, because of technical issues we could not perform the measurements in all the cases, explaining why we have n = 2 in some of the graphs. The trends were quite clear, so we chose to keep these data in the article. We believe they nicely complement the immunostaining data assessing basement membrane integrity in control and mutant embryos.


      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      The authors describe the dynamic distribution of laminin in the olfactory system and forebrain. Using immunohistochemistry and transgenic lines, they found that the olfactory system and adjacent brain tissues are enveloped by BMs from the earliest stages of olfactory system assembly. They also found that laminin deposits follow the axonal trajectory of axons. They performed a functional analysis of the sly mutant to analyse the function of laminin γ1 in the development of the zebrafish olfactory system. Their study revealed that laminin enables the shape and position of placodes to be maintained late in the face of major morphogenetic movements in the brain, and its absence promotes the local entry of sensory axons into the brain and their navigation towards the olfactory bulb. 

      Strengths: 

      - They showed that in the sly mutants, no BM staining of laminin and Nidogen could be detected around the OP and the brain. The authors then elegantly used electron microscopy to analyse the ultrastructure of the border between the OP and the brain in control and sly mutant conditions. 

      - To analyse the role of laminin γ1-dependent BMs in OP coalescence, the authors used the cluster size of Tg(neurog1:GFP)+ OP cells at 22 hpf as a marker. They found that the mediolateral dimension increased specifically in the mutants. However, proliferation did not seem to be affected, although apoptosis appeared to increase slightly at a later stage. This increase could therefore be due to a dispersal of cells in the OP. To test this hypothesis, the authors then analysed the cell trajectories and extracted 3D mean square displacements (MSD), a measure of the volume explored by a cell in a given period of time. Their conclusion indicates that although brain cell movements are increased in the absence of BM during coalescence phases, overall OP cell movements occur within normal parameters and allow OPs to condense into compact neuronal clusters in sly mutants. The authors also analysed the dimensions of the clusters composed of OMP+ neurons. Their results show an increase in cluster size along the dorso-ventral axis. These results were to be expected since, compared with BM, early neurog1+ neurons should compact along the medio-lateral axis, and those that are OMP+ essentially along the dorso-ventral axis. In addition to the DV elongation of OP tissue, the authors show the existence of isolated and ectopic (misplaced) YFP+ cells in sly mutants. 

      - To understand the origin of these phenotypes, the authors analysed the dynamic behaviour of brain cells and OPs during forebrain flexion. The authors then quantitatively measured brain versus OPs in the sly mutant and found that the OP-brain boundary was poorly defined in the sly mutant compared with the control. Once again, the methods (cell tracks, brain size, and proliferation/apoptosis, and the shape of the brain/OP boundary) are elegant but the results were expected. 

      - They then analysed the dynamic behaviour of the axon using live imaging. Thus, olfactory axon migration is drastically impaired in sly mutants, demonstrating that Laminin γ1dependent BMs are essential for the growth and navigation of axons from the OP to the olfactory bulb. 

      - The authors therefore performed a quantitative analysis of the loss of function of Laminin γ1. They propose that the BM of the OP prevents its deformation in response to mechanical forces generated by morphogenetic movements of the neighbouring brain. 

      Weaknesses: 

      - The authors did not analyse neurog1 + axonal migration at the level of the single cell and instead made a global analysis. An analysis at the cell level would strengthen their hypotheses.  

      - Rescue experiments by locally inducing Laminin expression would have strengthened the paper. 

      - The paper lacks clarity between the two neuronal populations described (early EONs and late OSNs).  

      - The authors quantitatively measured brain versus OPs in the sly mutant and found that the OP-brain boundary was poorly defined in the sly mutant compared with the control. Once again, the methods (cell tracks, brain size, proliferation/apoptosis, and the shape of the brain/OP boundary) are elegant but the results were expected. 

      - A missing point in the paper is the effect of Laminin γ1 on the migration of cranial NCCs that interact with OP cells. The authors could have analysed the dynamic distribution of neural crest cells in the sly mutant. 

      We thank the reviewer for the overall positive assessment of our work, and we carefully responded to all her/his insightful comments below. Live imaging experiments to (1) visualise exit and entry point formation with only a few axons labelled, (2) characterise the behaviour of single neurog1:GFP-positive neurons/axons during OP coalescence and to (3) analyse the migration of cranial NCC are now included in the revised manuscript to address the reviewer’s questions, and reinforce our initial conclusions.

      Reviewer #2 (Public Review): 

      Summary: 

      This manuscript addresses the role of the extracellular matrix in olfactory development. Despite the importance of these extracellular structures, the specific roles and activities of matrix molecules are still poorly understood. Here, the authors combine live imaging and genetics to examine the role of laminin gamma 1 in multiple steps of olfactory development. The work comprises a descriptive but carefully executed, quantitative assessment of the olfactory phenotypes resulting from loss of laminin gamma. Overall, this is a constructive advance in our understanding of extracellular matrix contributions to olfactory development, with a well-written Discussion with relevance to many other systems. 

      Strengths: 

      The strengths of the manuscript are in the approaches: the authors have combined live imaging, careful quantitative analyses, and molecular genetics. The work presented takes advantage of many zebrafish tools including mutants and transgenics to directly visualize the laminin extracellular matrix in living embryos during the developmental process. 

      Weaknesses: 

      The weaknesses are primarily in the presentation of some of the imaging data. In certain cases, it was not straightforward to evaluate the authors' interpretations and conclusions based on the single confocal sections included in the manuscript. For example, it was difficult to assess the authors' interpretation of when and how laminin openings arise around the olfactory placode and brain during olfactory axon guidance. 

      We thank the reviewer for the overall positive assessment of our work, and we carefully responded to all her/his insightful comments below. To address these comments, live imaging data to visualise exit and entry point formation with a sparse labelling of axons, and z-stacks showing how exit and entry points are organised in 3D, have been added to the revised manuscript.

      Reviewer #3 (Public Review): 

      This is a beautifully presented paper combining live imaging and analysis of mutant phenotypes to elucidate the role of laminin γ1-dependent basement membranes in the development of the zebrafish olfactory placode. The work is clearly illustrated and carefully quantified throughout. There are some very interesting observations based on the analysis of wild-type, laminin γ1, and foxd3 mutant embryos. The authors demonstrate the importance of a Laminin γ1-dependent basement membrane in olfactory placode morphogenesis, and in establishing and maintaining both boundaries and neuronal connections between the brain and the olfactory system. There are some very interesting observations, including the identification of different mechanisms for axons to cross basement membranes, either by taking advantage of incompletely formed membranes at early stages, or by actively perforating the membrane at later ones. 

      This is a valuable and important study but remains quite descriptive. In some cases, hypotheses for mechanisms are stated but are not tested further. For example, the authors propose that olfactory axons must actively disrupt a basement membrane to enter the brain and suggest alternative putative mechanisms for this, but these are not tested experimentally. In addition, the authors propose that the basement membrane of the olfactory placode acts to resist mechanical forces generated by the morphogenetic movement of the developing brain, and thus to prevent passive deformation of the placode, but this is not tested anywhere, for example by preventing or altering the brain movements in the laminin γ1 mutant. 

      We thank the reviewer for the overall positive assessment of our work and for suggesting interesting experiments to attempt in the future, and we carefully responded to all her/his constructive comments below.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      In general, it would be easier to draw conclusions and compare data if the authors used similar stages throughout the article. 

      Throughout the article we tried to focus on a series of stages that cover both the coalescence of the OP (up to 24 hpf) and later stages of olfactory system development spanning the brain flexure process (28, 32, 36 hpf). However, for technical reasons it was not always possible to stick to these precise stages in some of our experiments. Also, in Fig. 1E-J, we picked in the movies some images illustrating specific cell or axonal behaviours, and thus the corresponding stages could not match exactly the stage series used in Fig. 1A-D and elsewhere in the article. Nevertheless, this stage heterogeneity does not affect our main conclusions.

      It would be useful to schematise the olfactory placode and the brain in an insert to clearly visualise the system in each figure. 

      We hope that the schematic which was initially presented in Fig. 1K already helps the reader to understand how the system is organised. Although we have not added more schematic views to represent the system in each figure (we think this would make the figures overcrowded), we have added additional legends to point to the OP and the brain in the pictures in order to clarify the localisation of each tissue.

      In the Summary, the authors refer to the integrity of the basement membrane. I don't think there is any attempt to affect basement membrane integrity in the article. It would be important to do so to look at the effect on CNS-PNS separation and axonal elongation. 

      In the Summary, we use the term « integrity of the basement membrane » to mention that we have analysed this integrity in the sly mutant. Given the results of our immunostainings against three main components of the basement membrane (Laminin, Collagen IV and Nidogen), as well as our EM observations, we see the sly mutant as a condition in which the integrity of the basement membrane is strongly affected.

      Rescue experiments by locally inducing Laminin expression would have strengthened the paper. 

      We have attempted to rescue the sly mutant phenotypes by introducing the mutation in the transgenic TgBAC(lamC1:lamC1-sfGFP) background, in which Laminin γ1 tagged with sfGFP is expressed under the control of its own regulatory sequences (Yamaguchi et al., 2022). To do so, we crossed sly+/-;Tg(omp:yfp) fish with sly+/-; Tg(lamC1:LamC1-sfGFP) fish. Surprisingly, while a rescue of the global embryo morphology was observed, no clear rescue of the olfactory system defects could be detected at 36 hpf. This could be due to the fact that the expression level of LamC1-sfGFP obtained with one copy of the transgene is not sufficient to rescue the olfactory system phenotypes, or that the sfGFP tag specifically affects the function of the Laminin 𝛾1 chain during the development of the olfactory system, making it unable to rescue the defects. Given the results of our first attemps, we decided not to continue in this direction.

      (1) Developing OP & brain are surrounded by laminin-containing BM (already described by Torrez-Pas & Whitlock in 2014). 

      "we first noticed the appearance of a continuous Laminin-rich BM surrounding the brain from 14-18 hpf, while around the OP, only discrete Laminin spots were detected at this stage (Fig. 1A, A'). " 

      Around 8ss for Torrez-Pas & Whitlock (before 14 hpf). Can you modify the text, or show an 8ss stage embryo? As far as I know, the authors do not show images at 14hpf. Please correct this sentence or show a 14 hpf picture. 

      The reviewer is right, we do not show any 14 hpf stage in the images and thus have removed this stage in the text and replaced it by 17 hpf.

      In Figure 1A, the labelling of laminin 111 does not appear to be homogeneous along the brain.

      Is this true? 

      At this stage the brain’s BM revealed by the Laminin immunostaining appears fairly continuous (while the OP’s one is clearly dotty and less defined), but indeed very tiny/local interruptions of the signal can been seen along the structure as detected by the reviewer. We thus modified the text to mention these tiny interruptions.

      How is the Laminin antibody used by the authors specific to laminin 111?  

      We thank the reviewer for raising this important point. The immunogen used to produce this rabbit polyclonal antibody is the Laminin protein isolated from the basement membrane of a mouse Engelbreth Holm-Swarm sarcoma (EHS). It is thus likely to recognise several Laminin isoforms and not only Laminin 111. We thus replaced Laminin 111 by Laminin when mentioning this antibody in the text and Figures.

      Please schematise in Figure 1K the stages you have tested and shown here in the article i.e. stages 18 - 22 - 28 -36 hpf using immunohistochemistry and 17-26-27-29-33 and 38 hpf using transgenics for laminin 111 and LamC1 respectively.  

      As suggested by the reviewer, we changed the stages in the schematics for stages we have presented in Figure 1 (analysed either with immunostaining or in live imaging experiments). We chose to represent 17 - 22 - 26 - 33 hpf (and thus adapted some of the schematics for them to match these stages).  

      Please specify in the Figure 1 legend for panels A to D whether this is a 3D projection or a zsection.

      We indicated in the Figure 1 legend that all these images are single z-sections (as well as for panels E-J).

      Furthermore, the schematisation in Fig. 1K does not reflect what the authors show: at 22 hpf laminin 111 labelling appears to be present only near the brain, and no labelling lateral to the olfactory placode and anteriorly and posteriorly. Thus, the schematisation in Figure 1K needs to be modified to reflect what the authors show.

      We agree with the reviewer that the Laminin staining at this stage is observed around the medial region of the OP, but not more laterally. We modified the schematic view accordingly in Figure 1K. Anterior and posterior sides of the OP are not represented in this schematic because we chose to represent a frontal view rather than a dorsal view.

      The authors suggest that" the laminin-rich BM of OP assembles between 18 and 22 hpf, during the late phase of OP coalescence". However, their data indicate that this BM assembles around 28hpf (Figure 1C). Can they clarify this point?

      What we meant with this sentence is that we cleary see two distinct BMs from 22 hpf. However, as noticed by the reviewer, the OP’s BM is only present around the medial/basal regions of the OP and does not surround the whole OP tissue at this stage. We modified the text to clarify this point (in particular by mentioning that the OP’s BM starts to assemble between 18 and 22 hpf), and replaced the image shown in Figure 1B, B’ with a more representative picture (the previous z-section was taken in very dorsal regions of the OP).

      It would be useful to disrupt these cells that have a cytoplasmic expression of Laminin-sfGFP, to analyse their contribution to BM and OP coalescence.

      Indeed it will be interesting in the future to test specifically the role of the cells expressing cytoplasmic Laminin-sfGFP around and within the OP, as proposed by the reviewer. Laser ablation of these cells could be attempted, but due to their very superficial localisation, close to the skin, we believe these ablations (with the protocol/set-up we currently use in the lab) would impair the skin integrity, preventing us to conclude. We consider that the optimisation of this experiment is out of the scope of the present work.

      Tg(-2.0ompb:gapYFP)rw032 marks ciliated olfactory sensory neurons (OSNs) (Sato et al., 2005). The authors should mention this. 

      Please see our detailed response to the next point below.

      Points to be clarified: 

      -Tg(-2.0ompb:gapYFP)rw032 marks ciliated olfactory sensory neurons (OSNs) (Sato et al., 2005). The authors should mention this here. Moreover, the authors refer to "OP neurons" throughout the article. In the development of the olfactory organ, two types of neurons have been described in the literature: early EONs (12hpf-26hpf) and later OSNs. Each could have a specific role in the establishment and maintenance of the BM described by the authors. The authors need to clarify this point as, in Figure 1 for example, they use a marker for Tg(neurog1:GFP) EONs and a marker for ciliated OSNs without distinction. The distinction between EONs and OSNs comes a little late in the text and should be placed higher up. 

      As mentioned by the reviewer, according to the initial view of neurogenesis in the OP, OP neurons are born in two waves. A transient population of unipolar, dendrite-less pioneer neurons would differentiate first, in the ventro-medial region of the OP and elongate their axons dorsally out of the placode, along the brain wall. These pioneer axons would then be used as a scaffold by later born OSNs located in the dorso-lateral rosette to outgrow their axons towards the olfactory bulb (Whitlock and Westerfield, 1998). 

      Another study further characterised OP neurogenesis and showed that the first neurons to differentiate in the OP (the early olfactory neurons or EONs) express the Tg(neurog1:GFP) transgene (Madelaine et al., 2011). As mentioned by the authors in the discussion of this article, neurog1:GFP+ neurons appear much more numerous than the previously described pioneer neurons, and may thus include pioneers but also other neuronal subtypes.

      We would like here to share additional, unpublished observations from our lab that further suggest that the situation is more complex than the pioneer/OSN and EON/OSN nomenclatures. First, in many of our live imaging experiments, we can clearly visualise some neurog1:GFP+ unipolar neurons, initially located in a medial position in the OP, which intercalate and contribute to the dorsolateral rosette (where OSNs are proposed to be located) at the end of OP coalescence, from 22-24 hpf. Second, in fixed tissues, we observed that most neurog1:GFP+ neurons located in the rosette at 32 hpf co-express the Tg(omp:meRFP) transgene (Sato et al., 2005). These observations suggest that at least a subpopulation of neurog1:GFP+ neurons could incorporate in the dorsolateral rosette and become ciliated OSNs during development. We can share these results with the reviewer upon request. Further studies are thus needed to clarify and describe the neuronal subpopulations and lineage relationships in the OP, but this detailed investigation is out of the scope and focus of the present study. 

      An additional complication comes from the fact that, as shown and acknowledged by the authors in Miyasaka et al., 2005, the Tg(omp:meYFP) line (6kb promoter) labels ciliated OSNs in the rosette but also some unipolar, ventral neurons (around 10 neurons at 1 dpf, Miyasaka et al. 2005, Figure 3A, white arrowheads). This was also observed using the 2 kb promoter Tg(omp:meYFP) line (see for instance Miyasaka et al., 2007) and in our study, we can indeed detect these ventro-medial neurons labelled in the Tg(omp:meYFP) line (2 kb promoter), see for instance Figure 1C’, D’ or Movie 6. It is unclear whether these unipolar omp:meYFPpositive cells are pioneer neurons or EONs expressing the omp:meYFP transgene, or OSN progenitors that would be located basally/ventrally in the OP at these stages.

      For all these reasons, we decided to present in the text the current view of neurogenesis in the OP but instead of attributing a definitive identity to the neurons we visualise with the transgenic lines, we prefer to mention them in the manuscript (and in the rest of the response to the reviewers) as neurons expressing neurog1:GFP or omp:meYFP transgenes (or cells/axons/neurons expressing RFP in the Tg(cldnb:Gal4; UAS:RFP) background).

      What we also changed in the text to be more clear on this point:

      - we moved higher up in the text, as suggested by reviewer 1, the description of the current model of neurogenesis in the OP,

      - we mentioned that neurog1:GFP+ neurons are more numerous than the initially described pioneer neurons, as discussed in Madelaine et al., 2011,

      - we wrote more clearly that the Tg(omp:meYFP) line labels ciliated OSNs but also a subset of unipolar, ventral neurons (Miyasaka et al., 2005), and pointed to these ventral neurons in Figure 1C’, D’,

      - in the initial presentation of the current view of OP neurogenesis we renamed neurog1:GFP+ into EONs to be coherent with Madelaine et al., 2011.

      - To visualise pioneer axons, the authors should use an EONS marker such as neurog1 because, to my knowledge, OMP only marks OSN axons and not pioneer axons.  

      To visualise neurog1:GFP+ axons during OP coalescence, we performed live imaging upon injection of the neurog1:GFP plasmid (Blader et al., 2003) in the Tg(cldnb:Gal4; UAS:RFP) background (n = 4 mutants and n = 4 controls from 2 independent experiments). We observed some GFP+ placodal neurons exhibiting retrograde axon extension in both controls and sly mutants. In such experiments it is very difficult to quantify and compare the number of neurons/axons showing specific behaviours between different experimental conditions/genetic background. Indeed, due to the cytoplasmic localisation of GFP, the axons can only be seen in neurons expressing high levels of GFP, and due to the injection the number of such neurons varies a lot in between embryos, even in a given condition. Nevertheless, our qualitative observations reinforce the idea that the basement membrane is not absolutely required for mediolateral movements and retrograde axon extension of neurog1:GFP+ neurons in the OP. We added examples of images extracted from these new live imaging experiments in the revised Fig. S5A, B.

      - The authors should analyse the presence of laminin in the OP and forebrain in conjunction with neural crest cell dynamics (using a Sox10 transgenic line for example) to refine their entry and exit point hypotheses. 

      As described in the answer to the next point, we performed new experiments in which we visualised NCC migration in the Tg(neurog1:GFP) background, which allowed us to analyse the localisation of NCC at the forebrain/OP boundary, in ventral and dorsal positions, both in sly mutant embryos and control siblings.

      - A dynamic analysis of the distribution of neural crest cells in the sly mutant over time and during OP coalescence would be important. 

      The dynamics of zebrafish cranial NCC migration in the vicinity of the OP has been previously analysed using sox10 reporter lines (Harden et al., 2012, Torres-Paz and Whitlock, 2014, Bryan et al., 2020). To address the point raised by the reviewer, we performed live imaging from 16 to 32 hpf on sly mutants and control siblings carrying the Tg(neurog1:GFP) and Tg(UAS:RFP) transgenes and injected with a sox10(7.2):KalTA4 plasmid (Almeida et al., 2015). This allows the mosaic labelling of cells that express or have expressed sox10 during their development which, in the head region at these stages, represents mostly NCC and their derivatives. 3 independent experiments were carried out (n = 4 mutant embryos in which 8 placodes could be analysed; n = 6 control siblings in which 10 placodes could be analysed). A new movie (Movie 9) has been added to the revised article to show representative examples of control and mutant embryos.

      From these new data, we could make the following observations:

      - As expected from previous studies (Harden et al., 2012, Torres-Paz and Whitlock, 2014, Bryan et al., 2020), in control embryos a lot of NCC had already migrated to reach the vicinity of the OP when the movies begin at 16 hpf, and were then seen invading mainly the interface between the eye and the OP (10/10 placodes). Surprisingly, in sly mutants, a lot of motile NCC had also reached the OP region at 16 hpf in all the analysed placodes (8/8), and populated the eye/OP interface in 7/8 placodes (10/10 in controls). Counting NCC or tracking individual NCC during the whole duration of the movies was unfortunately too difficult to achieve in these movies, because of the low level of mosaicism (a high number of cells were labelled) and of the high speed of NCC movements (as compared with the 10 min delta t we chose for the movies). 

      - in some of the control placodes we could detect a few NCC that populated the forebrain/OP interface, either ventrally, close to the exit point of the axons (4/10 placodes), or more dorsally (8/10 placodes). By contrast, in sly mutants, NCC were observed in the dorsal region of the brain/OP boundary in only 2/8 placodes, and in the ventral brain/OP frontier in only 2/8 placodes as well. Interestingly, in these 2 last samples, NCC that had initially populated the ventral region of the brain/OP interface were then expelled from the boundary at later stages.

      We reported these observations in a new Table that is presented in revised Fig. S6B. In addition, instances of NCC migrating at the eye/OP or forebain/OP interfaces are indicated with arrowheads on Movie 9. Previous Figure S6 was splitted into two parts presenting NCC defects in sly mutants (revised Figure S6) and in foxd3 mutants (revised Figure S7).

      Altogether, these new data suggest that the first postero-anterior phase of NCC migration towards the OP, as well as their migration in between the eye and OP tissues, is not fully perturbed in sly mutants. The subset of NCC that populate the OP/forebrain seem to be more specifically affected, as these NCC show defects in their migration to the interface or the maintenance of their position at the interface. Since the crestin marker labels mostly NCC at the OP/forebrain interface at 32 hpf (revised Fig. S6A), this could explain why the crestin ISH signal is almost lost in sly mutants at this stage.

      (2) Laminin distribution suggests a role in olfactory axon development 

      "Laminin 111 immunostaining revealed local disruptions in the membrane enveloping the OP and brain, precisely where YFP+ axons exit the OP (exit point) and enter the brain (entry point) (Fig. 1C-D')." Can the authors quantify this situation? It would be important to analyse this behaviour on the scale of a neuron and thus axonal migration to strengthen the hypotheses. 

      As suggested by the reviewer, to better visualise individual axons at the exit and entry point, we used mosaic red labelling of OP axons. To achieve this sparse labelling, we took advantage of the mosaic expression of a red fluorescent membrane protein observed in the Tg(cldnb:Gal4; UAS:lyn-TagRFP) background. The unpublished Tg(UAS:lyn-TagRFP) line was kindly provided by Marion Rosello and Shahad Albadri from the lab of Filippo Del Bene. We crossed the Tg(cldnb:Gal4; UAS:lyn-TagRFP) line with the TgBAC(lamC1:lamC1-sfGFP) reporter and performed live imaging on 2 embryos/4 placodes, in a frontal view. A new movie (Movie 3 in the revised article) shows examples of exit and entry point formation in this context.This allowed us to visualise the formation of the exit and entry points in more samples (6 embryos and 12 placodes in total when we pool the two strategies for labelling OP axons) and through the visualisation of a small number of axons, and reinforce our initial conclusions. 

      (3) The integrity of BMs around the brain and the OP is affected in the sly mutant 

      Why do the authors analyse the distribution of collagen IV and Nidogen and not proteoglycans and heparan sulphate? 

      We attempted to label more ECM components such as proteoglycans and heparan sulfate, but whole-mount immunostainings did not work in our hands.

      A dynamic analysis of the distribution of neural crest cells in the sly mutant over time and during OP coalescence would be important. 

      See our detailed response to this point above.  

      (4) Role of Laminin γ1-dependent BMs in OP coalescence 

      The authors use the size of the Tg(neurog1:GFP)+ OP cell cluster at 22 hpf as a marker.  The authors should count the number of cells in the OP at the indicated time using a nuclear dye to check that in the sly mutant the number of cells is the same over time. Two time points as analysed in Figure S2 may not be sufficient to quantify proliferation which at these stages should be almost zero according to Whitlock & Westerfield and Madelaine et al.

      Counting the neurog1:GFP+ cell numbers in our existing data was unfortunately impossible, due to the poor quality of the DAPI staining. We are nevertheless confident that the number of cells within neurog1:GFP+ clusters is fairly similar between controls and sly mutants at 22 hpf, since the OP dimensions are the same for AP and DV dimensions, and only slightly different for the ML dimension. In addition, we analysed proliferation and apoptosis within the neurog1:GFP+ cluster at 16 and 21 hpf and observed no difference between controls and mutants.

      (5) Role of Laminin γ1-dependent BMs during the forebrain flexure 

      In Figure 4F at 32hpf, the presence of 77% ectopic OMP+ cells medially should result in an increase in dimensions along the M-L? This is not the case in the article. The authors should clarify this point. 

      As we explained in the Material and Methods, ectopic fluorescent cells (cells that are physically separated from the main cluster) were not taken into account for the measurement of the OP dimensions. This is now also also mentioned in the legends of the Figures (4 and S3) showing the quantifications of OP dimensions.

      Cell distribution also seems to be affected within the OMP+ cluster at 36hpf, with fewer cells laterally and more medially. The authors should analyse the distribution of OMP+ cells in the clusters. in sly mutants and controls to understand whether the modification corresponds to the absence of BM function. 

      On the pictures shown in Figure 4F,G, we agree that omp:meYFP+ cells appear to be more medially distributed in the mutant, however this is not the case in other sections or samples, and is rather specific to the z-section chosen for the Figure. We found that the ML dimension is unchanged in mutants as compared with controls, except for the 28 hpf stage where it is smaller, but this appears to be a transient phenomenon, since no change is detected at earlier or later stages (Figure 4A-D and Figure S3A-L). The difference we observe at 28 hpf is now mentioned in the revised manuscript.

      The conclusions of Figures 4 and S3 would rather be that laminin allows OMP+ cells to be oriented along the medio-lateral axis whereas it would control their position along the dorsoventral axis. The authors should modify the text. It would be useful to map the distribution of OMP+ cells along the dorsoventral and mediolateral axes. The same applies to Neurog1+ cells. An analysis of skin cell movements, for example, would be useful to determine whether the effects are specific.  

      We are confident that the measurements of OP dimensions in AP, DV and ML are sufficient to describe the OP shape defects observed in the sly mutants. Analysing cell distribution along the 3 axes as well as skin cell movements will be interesting to perform in the future but we consider these quantifications as being out of the scope of the present work.

      (6) Laminin γ1-dependent BMs are required to define a robust boundary between the OP and the brain 

      The authors must weigh this conclusion "Laminin γ1-dependent BMs serve to establish a straight boundary between the brain and OP, preventing local mixing and late convergence of the two OPs towards each other during flexion movement." Indeed, they don't really show any local mixing between the brain and OP cells. They would need to quantify in their images (Figure 5A-A' and Figure S4 A-A') the percentage of cells co-labelled by HuC and Tg(cldnb:GFP). 

      We agree with the reviewer and thus replaced « reveal » by « suggest » in the conclusion of this section. 

      (7) Role of Laminin γ1-dependent BMs in olfactory axon development 

      An analysis of the retrograde extension movement in the axons of OMP+ ectopic neurons in the sly1 mutant condition would be useful to validate that the loss of laminin function does not play a role in this event. 

      Indeed, even though we can visualise instances of retrograde extension occurring normally in sly mutants, we can not rule out that this process is affected in a subset of OP neurons, for instance in ectopic cells, which often show no axon or a misoriented axon. We added a sentence to mention this in the revised manuscript.

      Minor comments and typos: 

      Please check and mention the D-V/L-M or A-P/L-M orientation of the images in all figures. 

      This has been checked.

      Legend Figure 1: "distalmost" is missing a space "distal most". 

      We checked and this word can be written without a space.

      Figure 1 panel C: check the orientation (I am not sure that Dorsal is up). 

      We double-checked and confirm that dorsal is up in this panel.

      Movie 1 Legend: "aroung "the OP should be around the OP. 

      Thanks to the reviewer for noticing the typo, we corrected it.

      Reviewer #2 (Recommendations For The Authors):

      The comments below are relatively minor and mostly raise questions regarding images and their presentation in the manuscript. 

      • Figure 1, visualization of exit and entry points: It is a bit difficult to visualize the axon exit and entry points in these images, and in particular, to understand how the exit and entry points in C and D correspond to what is seen in F, F', H, and H'. There appears to be one resolvable break in the staining in C and D, whereas there are two distinct breaks in F-H'. Are these single optical sections? Is it possible to visualize these via 3-dimensional rendering? 

      All the images presented in Figure 1 are single z-sections, which is now indicated in the Figure legend. As noticed by the reviewer, Laminin immunostainings on fixed embryos at 28 and 36 hpf suggested that the exit and entry points are facing each other, as shown in Figure 1C-D’. However, in our live imaging experiments we always observed that the exit point is slightly more ventral than the entry point (of about 10 to 20 µm). This discrepancy could be due to the fixation that precedes the immunostaining procedure, which could modify slightly the size and shape of cells/tissues. We added a sentence on this point in the text. In addition, we added new movies of the LamC1-sfGFP reporter with sparse red axonal labelling (Movie 3, see response to reviewer 1), as well as z-stacks presenting the organisation of exit and entry points in 3D (Movie 4), which should help to better illustrate the mechanisms of exit and entry point formation.

      • Movie 2, p. 6, "small interruptions of the BM were already present near the axon tips, along the ventro-medial wall of the OP." This is a bit difficult to assess since the movie seems to show at least one other small interruption in the BM in addition to the exit point, in particular, one slightly dorsal to the exit point. Was this seen in other samples, or in different optical sections? 

      Indeed the exit and entry points often appear as regions with several, small BM interruptions, rather than single holes in the BM. We now show in revised Movie 4 the two z-stacks (the merge and the single channel for green fluorescence) corresponding to the last time points of the movies showing exit and entry point formation in Movie 2, where several BM interruptions can be seen for both the exit and entry points. We had already mentioned this observation in the legend of Movie 2, and we added a sentence on this point in the main text of the revised manuscript. This is also represented for both exit and entry points in the new schematics in revised Fig. 1K and its legend. 

      • Movie 2, p. 6, "The opening of the entry point through the brain BM was concomitant with the arrival of the RFP+ axons, suggesting that the axons degrade or displace BM components to enter the brain." Similar to the questions regarding the exit point, it was a bit difficult to evaluate this statement. There appears to be a broader region of BM discontinuity more dorsal to the arrowhead in Movie 2. A single-channel movie of just the laminin fluorescence might help to convey the extent of the discontinuity. As with above, was this seen in other samples, or in different optical sections?  

      See our response to the previous comment.

      • Figure 1H, I, "the distal tip of the RFP+ axons migrated in close proximity with the brain's BM." This is again a bit difficult to see, and quite different than what is seen in Figure 4A, in which the axons do not seem close to the BM in this section. Is it possible to visualize this via 3-dimensional rendering? 

      In fixed embryos or in live imaging experiments, we observed that, once entered in the brain, the distal tips (the growth cones) of the axons are located close to the BM of the brain. However, this is not the case of the axon shafts which, as development proceeds, are located further away from the BM. This can clearly be seen at 36 hpf in Figure 1D’ and Figure 4A, as spotted by the reviewer. We modified the text to clarify this point.

      • Figure 2J, J', p. 7, the gap between the OP and brain cells of sly mutants "was most often devoid of electron-dense material." It is difficult to see this loss of electron-dense material in 2J'. The thickness of the space is quantified well and is clearly smaller, but the change in electron-dense material is more difficult to see.  

      We looked at Figure 2 again and it seems clear to us that there is electron-dense material between the plasma membranes in controls, which is practically not seen (rare spots) in the mutants. We added a sentence mentioning that we rarely see electron-dense spots in sly mutants.

      • Figure 5E-F': There are concerns about evaluating the shape of a tissue based on nuclear position. Is there a way to co-stain for cell boundaries (maybe actin?), and then quantify distortion of the dlx+ cell population using the cell boundaries, rather than nuclear staining? 

      We agree with the reviewer that it is not ideal to evaluate the shape of the OP/brain boundary based on a nuclear staining. As explained in the text, we could not use the Tg(eltC:GFP) or Tg(cldnb:Gal4; UAS:RFP) reporter lines for this analysis, due to ectopic or mosaic expression. However we are confident that the segmentation of the Dlx3b immunostaining reflects the organisation of the cells at the OP/brain tissue boundary: in other data sets in which we performed Dlx3b staining with membrane labelling independently of the present study and in the wild type context, we clearly see that cell membranes are juxtaposed to the Dlx3b nuclear staining (in other words, the cytoplasm volume of OP cells is very small). 

      • Figure S5E: It would be helpful to see representative images for each of the categories (Proper axon bundle; Ventral projections; Medial projections) or a schematic to understand how the phenotypes were assessed. 

      To address this point we added a schematic view to illustrate the phenotypes assessed in each column of the table in revised Figure S5G.

      • Figure 6, p. 12, "Laminin gamma 1-dependent BMs are essential for growth and navigation of the axons...": What fraction of the tracked axons managed to exit the OP? Given the quantitative analyses in Figure 6, one might interpret this to mean that laminin gamma 1 is not essential for axon growth (speed and persistence are largely unchanged), but rather, primarily for navigation. 

      As noticed by the reviewer, the speed and persistence of axonal growth cones are largely unchanged in the sly mutants (except for the reduced persistence in the 200-400 min window, and an increased speed in the 800-1000 min window), showing that the growth cones are still motile. However, as shown by the tracks, they tend to wander around within the OP, close to the cell bodies, which results in the end in a perturbed growth of the axons. The navigation issues are rather revealed by the analysis of fixed Tg(omp:meYFP) embryos presented in the table of Figure S5G. We modified the text to separate more clearly the conclusions of the two types of experiments (fixed, transgenic embryos versus live, mosaically labelled embryos).

      Reviewer #3 (Recommendations For The Authors):

      Testing the hypotheses mentioned in the public review will be interesting experiments for a follow-up study, but are not essential revisions for this manuscript. 

      I have only a few minor suggestions for revisions: 

      P8 subheading 'Role of Laminin γ1-dependent BMs in OP coalescence' - since no major role was demonstrated here, this heading should be reworded.  

      We agree with the reviewer and replaced the previous title by « OP coalescence still occurs in the sly mutant ».

      P11, line 3 - the authors conclude that the forebrain is smaller 'due to' the inward convergence of the OPs. I do not think it is possible to assign causation to this when the mutant disrupts Laminin γ1 systemically - it is equally possible that the OPs move inward due to a failure of the brain to form in the normal shape. Thus, the wording should be changed here. (In the Discussion on p15, the authors mention the 'apparent distortion' of the brain, and say that it is 'possibly due' to the inward migration of the placodes', but again this could be toned down.) 

      We agree with the reviewer’s comment and changed the wording of our conclusions in the Results section.

      P11 and Fig. S5 - The table and text seem to be saying opposite things here. The text on p11 (3rd paragraph) indicates that the normal exit point is ventral and that this is disrupted in the mutant, with axons exiting dorsally. However, in the table, at each time point there is a higher % of axons exiting ventrally in the mutant. Please clarify. The table does not provide a % value for axons exiting dorsally - it might help to add a column to show this value. 

      We are grateful to the reviewer for pointing this out, and we apologize for the lack of clarity in the first version of the manuscript. We have modified the text and Figure S5 in order to clarify the different points raised by the reviewer in this comment. The Table in Fig. S5G does not represent the % of axons showing defects, but the % of embryos showing the phenotypes. In addition, an embryo is counted in the ventral or medial projection category if it shows at least one ventral or medial projection (even if its shows a proper bundle). This is now clearly indicated in the title of the columns in the table itself and in the legend. The embryos in which the axons exit dorsally in sly mutants are actually those counted in the left column of the Table (they exit dorsally and form a bundle), as shown by the new schematics added below the table. We also added this information in the title of the left column, and mention in the legend the pictures in which this dorsal exit can be observed in the article (Figures 4B and S3E’). Having more sly mutant embryos with axons exiting dorsally is thus compatible with more embryos showing at least one ventral projection.

      Fig. S6, shows the lack of neural crest cells between the olfactory placode and the brain in both laminin γ1 mutants (without a basement membrane) and foxd3 mutants (which retain the membrane). Comparison of the two mutants here is a neat experiment and the result is striking, demonstrating that it is the basement membrane, and not the neural crest, that is required for correct morphology of the olfactory placode. I think this figure should be presented as a main figure, rather than supplementary.  

      Our new live imaging characterisation of NCC migration in sly mutants and control siblings (Movie 9) revealed that at 32 hpf, in the vicinity of the OP, NCC (or their derivatives) are much more numerous than the subset of NCC showing crestin expression by in situ hybridisation (compare the end of our control movie – 32 hfp, with crestin ISH shown in Figure S6A for instance). 

      Thus, the extent of the NCC migration defects should be analysed in more detail in the foxd3 mutant in the future (using live imaging or other NCC markers), and for this reason we chose to keep this dataset in the supplementary Figures.

      One of the first topics covered in the Discussion section is the potential role of Collagen. I was surprised to see the description on P15 'the dramatic disorganization of the Collagen IV pattern observed by immunofluorescence in the sly mutant', as I hadn't picked this up from the Results section of the paper. I went back to the relevant figure (Fig. 2) and description on p7, which does not give the same impression: 'in sly mutants, Collagen IV immunoreactivity was not totally abolished'. This suggested to me that there was only minor (not dramatic) disorganisation of the Collagen IV. This needs clarification.  

      The linear, BM-like Collagen IV staining was lost in sly mutants, but not the fibrous staining which remained in the form of discrete patches surrounding the OP. We modified the text in the Results section as well as in the Figure 2 legend to clarify our observations made on embryos immunostained for Collagen IV.

      Typos etc 

      P5 - '(ii) above of the neuronal rosette' - delete the word 'of'. 

      P5 two lines below this - ensheathed. 

      P10 - '3 distinct AP levels' (delete s from distincts). 

      P10 - distortion (not distorsion) . 

      P12 - 'From 14 hpf, they' should read 'From 14 hpf, neural crest cells'. 

      P15, line 1 - 'is a consequence of' rather than 'is consecutive of'? 

      P22 'When the data were not normal,' should read 'When the data were not normally distributed,'. 

      We thank the reviewer for noticing these typos and have corrected them.

      General 

      Please number lines in future manuscripts for ease of reference. 

      This has been done.

    1. ReferencesBeckman, A. L., Herrin, J., Nasir, K., Desai, N. R., & Spatz, E. S. (2017). Trends in cardiovascular health of US adults by income, 2005–2014. JAMA cardiology, 2(7), 814–816.Article  PubMed  PubMed Central  Google Scholar  Bernstein, J., & Tedeschi, E. (2021). Pandemic Prices: Assessing Inflation in the Months and Years Ahead. The White House, U.S. Government. Retrieved July 1 from https://www.whitehouse.gov/cea/written-materials/2021/04/12/pandemic-prices-assessing-inflation-in-the-months-and-years-ahead/.Burgard, S. A., & Kalousova, L. (2015). Effects of the great recession: Health and well-being. Annual review of sociology, 41, 181–201.Article  Google Scholar  Cargill, V. A., & Stone, V. E. (2005). HIV/AIDS: A minority health issue. Medical Clinics, 89(4), 895–912.PubMed  Google Scholar  Choi, H., Steptoe, A., Heisler, M., Clarke, P., Schoeni, R. F., Jivraj, S., Cho, T. C., & Langa, K. M. (2020). Comparison of health outcomes among high-and low-income adults aged 55 to 64 years in the US vs England. JAMA internal medicine, 180(9), 1185–1193.Article  PubMed  Google Scholar  Clark, E., Fredricks, K., Woc-Colburn, L., Bottazzi, M. E., & Weatherhead, J. (2020). Disproportionate impact of the COVID-19 pandemic on immigrant communities in the United States. PLoS neglected tropical diseases, 14(7), e0008484.Connor, J., Madhavan, S., Mokashi, M., Amanuel, H., Johnson, N. R., Pace, L. E., & Bartz, D. (2020). Health risks and outcomes that disproportionately affect women during the Covid-19 pandemic: A review (266 vol., p. 113364). Social science & medicine.Do, D. P., & Finch, B. K. (2008). The link between neighborhood poverty and health: Context or composition? American journal of epidemiology, 168(6), 611–619.Article  PubMed  PubMed Central  Google Scholar  Fogle, B. M., Tsai, J., Mota, N., Harpaz-Rotem, I., Krystal, J. H., Southwick, S. M., & Pietrzak, R. H. (2020). The National Health and Resilience in Veterans Study: A narrative review and future directions. Frontiers in Psychiatry, 11, 538218. https://doi.org/10.3389/fpsyt.2020.538218.Article  PubMed  PubMed Central  Google Scholar  Gellad, W. F., Good, C. B., & Shulkin, D. J. (2017). Addressing the opioid epidemic in the United States: Lessons from the Department of Veterans Affairs. JAMA internal medicine, 177(5), 611–612.Article  PubMed  Google Scholar  Isaacs, K., Mota, N. P., Tsai, J., Harpaz-Rotem, I., Cook, J. M., Kirwin, P. D., Krystal, J. H., Southwick, S. M., & Pietrzak, R. H. (2017). Psychological resilience in US military veterans: A 2-year, nationally representative prospective cohort study. Journal of Psychiatric Research, 84, 301–309.Article  PubMed  Google Scholar  Jenkins, R. A. (2021). The fourth wave of the US opioid epidemic and its implications for the rural US: A federal perspective. Preventive medicine, 152(2), 106541.Article  PubMed  Google Scholar  Krieger, N. (2007). Why epidemiologists cannot afford to ignore poverty. Epidemiology (Cambridge, Mass.), 18(6), 658–663.Article  PubMed  Google Scholar  Lin, L. A., Peltzman, T., McCarthy, J. F., Oliva, E. M., Trafton, J. A., & Bohnert, A. S. B (2019). Changing trends in opioid overdose deaths and prescription opioid receipt among veterans. American journal of preventive medicine, 57(1), 106–110.Article  PubMed  Google Scholar  Manderson, L., & Aaby, P. (1992). An epidemic in the field? Rapid assessment procedures and health research. Social science & medicine, 35(7), 839–850.Article  CAS  Google Scholar  Mani, A., Mullainathan, S., Shafir, E., & Zhao, J. (2013). Poverty impedes cognitive function science, 341(6149), 976–980.CAS  PubMed  Google Scholar  McDonough, P., Sacker, A., & Wiggins, R. D. (2005). Time on my side? Life course trajectories of poverty and health. Social science & medicine, 61(8), 1795–1808.Article  Google Scholar  Oliver, A. (2007). The Veterans Health Administration: An american success story? Milbank Quarterly, 85(1), 5–35.Article  PubMed  PubMed Central  Google Scholar  Ostling, P. S., Davidson, K. S., Anyama, B. O., Helander, E. M., Wyche, M. Q., & Kaye, A. D. (2018). America’s opioid epidemic: A comprehensive review and look into the rising crisis. Current pain and headache reports, 22(5), 32.Article  PubMed  Google Scholar  Palombi, L. C., Hill, S., Lipsky, C. A., Swanoski, M. S., M. T., & Lutfiyya, M. N. (2018). A scoping review of opioid misuse in the rural United States. Annals of epidemiology, 28(9), 641–652.Article  PubMed  Google Scholar  Price, J. H., Khubchandani, J., & Webb, F. J. (2018). Poverty and health disparities: What can public health professionals do? Health promotion practice, 19(2), 170–174.Article  PubMed  Google Scholar  Reif, S. S., Whetten, K., Wilson, E. R., McAllaster, C., Pence, B. W., Legrand, S., & Gong, W. (2014). HIV/AIDS in the Southern USA: A disproportionate epidemic. AIDS care, 26(3), 351–359.Article  PubMed  Google Scholar  Reif, S., Safley, D., McAllaster, C., Wilson, E., & Whetten, K. (2017). State of HIV in the US Deep South. Journal of community health, 42, 844–853.Article  PubMed  Google Scholar  Renahy, E., Mitchell, C., Molnar, A., Muntaner, C., Ng, E., Ali, F., & O’Campo, P. (2018). Connections between unemployment insurance, poverty and health: A systematic review. European Journal of Public Health, 28(2), 269–275.Article  PubMed  Google Scholar  Scrimshaw, N. S., & Gleason, G. R. (Eds.). (1992). Rapid Assessment Procedures- qualitative methodologies for planning and evaluation of Health related programmes. International Nutrition Foundation for Developing Countries.Shmagel, A., Foley, R., & Ibrahim, H. (2016). Epidemiology of chronic low back pain in US adults: Data from the 2009–2010 National Health and Nutrition Examination Survey. Arthritis care & research, 68(11), 1688–1694.Article  Google Scholar  Stuckler, D., Meissner, C., Fishback, P., Basu, S., & McKee, M. (2012). Banking crises and mortality during the Great Depression: Evidence from US urban populations, 1929–1937. Journal of Epidemiology & Community Health, 66(5), 410–419.Article  Google Scholar  Tai, D. B. G., Shah, A., Doubeni, C. A., Sia, I. G., & Wieland, M. L. (2021). The disproportionate impact of COVID-19 on racial and ethnic minorities in the United States. Clinical Infectious Diseases, 72(4), 703–706.Article  PubMed  Google Scholar  Tapia Granados, J. A., & Diez Roux, A. V. (2009). Life and death during the Great Depression. Proceedings of the National Academy of Sciences, 106(41), 17290–17295.Article  CAS  Google Scholar  Tsai, J., & Hooshyar, D. (2022). Prevalence of eviction, home foreclosure, and homelessness among low-income U.S. veterans: The national veteran homeless and other Poverty Experiences (NV-HOPE) study. Public Health, 213, 181–188. https://doi.org/10.1016/j.puhe.2022.10.017.Article  CAS  PubMed  Google Scholar  Tsai, J., & Kelton, K. (2023). Service use and barriers to care among homeless veterans: Results from the national veteran homeless and other Poverty Experiences (NV-HOPE) study. Journal of Community Psychology, 51(1), 507–515. https://doi.org/10.1002/jcop.22912.Article  PubMed  Google Scholar  Tsai, J., & Rosenheck, R. A. (2015). Risk factors for homelessness among U.S. veterans. Epidemiologic Reviews, 37(1), 177–195.Article  PubMed  Google Scholar  Tsai, J., & Rosenheck, R. A. (2016). US Veterans’ use of VA mental health services and disability compensation increased from 2001 to 2010. Health Affairs, 35(6), 966–973.Article  PubMed  Google Scholar  Tsai, J., Rosenheck, R. A., Kasprow, W. J., & McGuire, J. F. (2013). Risk of incarceration and clinical characteristics of incarcerated veterans by race/ethnicity. Social Psychiatry and Psychiatric Epidemiology, 48(11), 1777–1786.Article  PubMed  Google Scholar  Tsai, J., Elbogen, E. B., Huang, M., North, C. S., & Pietrzak, R. H. (2021). Psychological distress and alcohol use disorder during the COVID-19 era among middle-and low-income US adults. Journal of affective disorders, 288, 41–49.Article  CAS  PubMed  PubMed Central  Google Scholar  Tsai, J., McCleery, A., Wynn, J. K., & Green, M. F. (2023). Financial health and psychiatric symptoms among veterans with psychosis or recent homelessness during the COVID-19 pandemic. Psychological Services. https://doi.org/10.1037/ser0000787.Article  PubMed  Google Scholar  Umucu, E., Reyes, A., Nay, A., Elbogen, E. B., & Tsai, J. (2021). Associations between mental health and job loss among middle-and low‐income veterans and civilians during the COVID‐19 pandemic: An exploratory study. Stress and Health. https://doi.org/10.1002/smi.3099.

      The article does have sources sited. The article uses APA citations and uses a range of academic sources. Sources include both primary and secondary sources for the research.

    1. The CIA and DIA decided they should investigate and know as much about it as possible.

      "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it" "theres no reason to want it"

      Main menu

      Wikipedia The Free Encyclopedia

      Personal tools

      Contents

      Astrolabe

      Tools

      Appearance

      Text

      • Small

        Standard

        Large

      Width

      • Standard

        Wide

      Color (beta)

      • Automatic

        Light

        Dark

      From Wikipedia, the free encyclopedia

      For other pages with a similar name, see Astrolabe (disambiguation). Not to be confused with Cosmolabe.

      Planispheric Astrolabe made of brass, cast, with fretwork rete and surface engraving

      North African, 9th century AD, Planispheric Astrolabe. Khalili Collection.

      A modern astrolabe made in Tabriz, Iran in 2013.

      An astrolabe (Greek: ἀστρολάβος astrolábos, 'star-taker'; Arabic: ٱلأَسْطُرلاب al-Asṭurlāb; Persian: ستاره‌یاب Setāreyāb) is an astronomical instrument dating to ancient times. It serves as a star chart and physical model of visible heavenly bodies. Its various functions also make it an elaborate inclinometer and an analog calculation device capable of working out several kinds of problems in astronomy. In its simplest form it is a metal disc with a pattern of wires, cutouts, and perforations that allows a user to calculate astronomical positions precisely. It is able to measure the altitude above the horizon of a celestial body, day or night; it can be used to identify stars or planets, to determine local latitude given local time (and vice versa), to survey, or to triangulate. It was used in classical antiquity, the Islamic Golden Age, the European Middle Ages and the Age of Discovery for all these purposes.

      The astrolabe, which is a precursor to the sextant,^[1]^ is effective for determining latitude on land or calm seas. Although it is less reliable on the heaving deck of a ship in rough seas, the mariner's astrolabe was developed to solve that problem.

      Applications

      16th-century woodcut of measurement of a building's height with an astrolabe

      The 10th-century astronomer ʿAbd al-Raḥmān al-Ṣūfī wrote a massive text of 386 chapters on the astrolabe, which reportedly described more than 1,000 applications for the astrolabe's various functions.^[2]^ These ranged from the astrological, the astronomical and the religious, to navigation, seasonal and daily time-keeping, and tide tables. At the time of their use, astrology was widely considered as much of a serious science as astronomy, and study of the two went hand-in-hand. The astronomical interest varied between folk astronomy (of the pre-Islamic tradition in Arabia) which was concerned with celestial and seasonal observations, and mathematical astronomy, which would inform intellectual practices and precise calculations based on astronomical observations. In regard to the astrolabe's religious function, the demands of Islamic prayer times were to be astronomically determined to ensure precise daily timings, and the qibla, the direction of Mecca towards which Muslims must pray, could also be determined by this device. In addition to this, the lunar calendar that was informed by the calculations of the astrolabe was of great significance to the religion of Islam, given that it determines the dates of important religious observances such as Ramadan.^[citation needed]^

      Etymology

      The Oxford English Dictionary gives the translation "star-taker" for the English word astrolabe and traces it through medieval Latin to the Greek word ἀστρολάβος : astrolábos,^[3]^^[4]^ from ἄστρον : astron "star" and λαμβάνειν : lambanein "to take".^[5]^

      In the medieval Islamic world the Arabic word al-Asturlāb (i.e., astrolabe) was given various etymologies. In Arabic texts, the word is translated as ākhidhu al-Nujūm (Arabic: آخِذُ ٱلنُّجُومْ, lit. 'star-taker'), a direct translation of the Greek word.^[6]^

      Al-Biruni quotes and criticises medieval scientist Hamza al-Isfahani who stated:^[6]^ "asturlab is an arabisation of this Persian phrase" (sitara yab, meaning "taker of the stars").^[7]^ In medieval Islamic sources, there is also a folk etymology of the word as "lines of lab", where "Lab" refers to a certain son of Idris (Enoch). This etymology is mentioned by a 10th-century scientist named al-Qummi but rejected by al-Khwarizmi.^[8]^

      History

      Ancient era

      An astrolabe is essentially a plane (two-dimensional) version of an armillary sphere, which had already been invented in the Hellenistic period and probably been used by Hipparchus to produce his star catalogue. Theon of Alexandria (c. 335 -- c. 405) wrote a detailed treatise on the astrolabe.^[9]^ The invention of the plane astrolabe is sometimes wrongly attributed to Theon's daughter Hypatia (born c. 350--370; died AD 415),^[10]^^[11]^^[12]^^[13]^ but it's known to have been used much earlier.^[11]^^[12]^^[13]^ The misattribution comes from a misinterpretation of a statement in a letter written by Hypatia's pupil Synesius (c. 373 -- c. 414),^[11]^^[12]^^[13]^ which mentions that Hypatia had taught him how to construct a plane astrolabe, but does not say that she invented it.^[11]^^[12]^^[13]^ Lewis argues that Ptolemy used an astrolabe to make the astronomical observations recorded in the Tetrabiblos.^[9]^ However, Emilie Savage-Smith notes "there is no convincing evidence that Ptolemy or any of his predecessors knew about the planispheric astrolabe".^[14]^ In chapter 5,1 of the Almagest, Ptolemy describes the construction of an armillary sphere, and it is usually assumed that this was the instrument he used.

      Astrolabes continued to be used in the Byzantine Empire. Christian philosopher John Philoponus wrote a treatise (c. 550) on the astrolabe in Greek, which is the earliest extant treatise on the instrument.^[a]^ Mesopotamian bishop Severus Sebokht also wrote a treatise on the astrolabe in the Syriac language during the mid-7th century.^[b]^ Sebokht refers to the astrolabe as being made of brass in the introduction of his treatise, indicating that metal astrolabes were known in the Christian East well before they were developed in the Islamic world or in the Latin West.^[15]^

      Medieval era

      Astrolabes were further developed in the medieval Islamic world, where Muslim astronomers introduced angular scales to the design,^[16]^ adding circles indicating azimuths on the horizon.^[17]^ It was widely used throughout the Muslim world, chiefly as an aid to navigation and as a way of finding the Qibla, the direction of Mecca. Eighth-century mathematician Muhammad al-Fazari is the first person credited with building the astrolabe in the Islamic world.^[18]^

      The mathematical background was established by Muslim astronomer Albatenius in his treatise Kitab az-Zij (c. AD 920), which was translated into Latin by Plato Tiburtinus (De Motu Stellarum). The earliest surviving astrolabe is dated AH 315 (AD 927--928). In the Islamic world, astrolabes were used to find the times of sunrise and the rising of fixed stars, to help schedule morning prayers (salat). In the 10th century, al-Sufi first described over 1,000 different uses of an astrolabe, in areas as diverse as astronomy, astrology, navigation, surveying, timekeeping, prayer, Salat, Qibla, etc.^[19]^^[20]^

      An Arab astrolabe from 1208

      The spherical astrolabe was a variation of both the astrolabe and the armillary sphere, invented during the Middle Ages by astronomers and inventors in the Islamic world.^[c]^ The earliest description of the spherical astrolabe dates to Al-Nayrizi (fl. 892--902). In the 12th century, Sharaf al-Dīn al-Tūsī invented the linear astrolabe, sometimes called the "staff of al-Tusi", which was "a simple wooden rod with graduated markings but without sights. It was furnished with a plumb line and a double chord for making angular measurements and bore a perforated pointer".^[21]^ The geared mechanical astrolabe was invented by Abi Bakr of Isfahan in 1235.^[22]^

      The first known metal astrolabe in Western Europe is the Destombes astrolabe made from brass in the eleventh century in Portugal.^[23]^^[24]^ Metal astrolabes avoided the warping that large wooden ones were prone to, allowing the construction of larger and therefore more accurate instruments. Metal astrolabes were heavier than wooden instruments of the same size, making it difficult to use them in navigation.^[25]^

      Spherical astrolabe

      A depiction of Hermann of Reichenau with an astrolabe in a 13th-century manuscript by Matthew Paris

      Herman Contractus of Reichenau Abbey, examined the use of the astrolabe in Mensura Astrolai during the 11th century.^[26]^ Peter of Maricourt wrote a treatise on the construction and use of a universal astrolabe in the last half of the 13th century entitled Nova compositio astrolabii particularis. Universal astrolabes can be found at the History of Science Museum in Oxford.^[27]^ David A. King, historian of Islamic instrumentation, describes the universal astrolobe designed by Ibn al-Sarraj of Aleppo (aka Ahmad bin Abi Bakr; fl. 1328) as "the most sophisticated astronomical instrument from the entire Medieval and Renaissance periods".^[28]^

      English author Geoffrey Chaucer (c. 1343--1400) compiled A Treatise on the Astrolabe for his son, mainly based on a work by Messahalla or Ibn al-Saffar.^[29]^^[30]^ The same source was translated by French astronomer and astrologer Pélerin de Prusse and others. The first printed book on the astrolabe was Composition and Use of Astrolabe by Christian of Prachatice, also using Messahalla, but relatively original.

      Front of an Indian astrolabe now kept at the Royal Museum of Scotland at Edinburgh.

      In 1370, the first Indian treatise on the astrolabe was written by the Jain astronomer Mahendra Suri, titled Yantrarāja.^[31]^

      A simplified astrolabe, known as a balesilha, was used by sailors to get an accurate reading of latitude while at sea. The use of the balesilha was promoted by Prince Henry (1394--1460) while navigating for Portugal.^[32]^

      The astrolabe was almost certainly first brought north of the Pyrenees by Gerbert of Aurillac (future Pope Sylvester II), where it was integrated into the quadrivium at the school in Reims, France, sometime before the turn of the 11th century.^[33]^ In the 15th century, French instrument maker Jean Fusoris (c. 1365--1436) also started remaking and selling astrolabes in his shop in Paris, along with portable sundials and other popular scientific devices of the day.

      Astronomical Instrument Detail by Ieremias Palladas 1612

      Thirteen of his astrolabes survive to this day.^[34]^ One more special example of craftsmanship in early 15th-century Europe is the astrolabe designed by Antonius de Pacento and made by Dominicus de Lanzano, dated 1420.^[35]^

      In the 16th century, Johannes Stöffler published Elucidatio fabricae ususque astrolabii, a manual of the construction and use of the astrolabe. Four identical 16th-century astrolabes made by Georg Hartmann provide some of the earliest evidence for batch production by division of labor. In 1612, Greek painter Ieremias Palladas incorporated a sophisticated astrolabe in his painting depicting Catherine of Alexandria. The painting was entitled Catherine of Alexandria and featured a device called the System of the Universe (Σύστημα τοῦ Παντός). The device featured the planets with the names in Greek: Selene (Moon), Hermes (Mercury), Aphrodite (Venus), Helios (Sun), Ares (Mars), Zeus (Jupiter), and Chronos (Saturn). The device also featured celestial spheres following the Ptolemaic model and Earth was depicted as a blue sphere with circles of geographic coordinates. A complex line representing the axis of the Earth covered the entire instrument.^[36]^

      Medieval astrolabes

      Astrolabes and clocks

      Amerigo Vespucci observing the Southern Cross by looking over the top of an armillary sphere bizarrely held from the top as if it were an astrolabe; however, an astrolabe cannot be used by looking over its top. The page inexplicably contains the word astrolabium. By Jan Collaert II. Museum Plantin-Moretus, Antwerp, Belgium.

      Mechanical astronomical clocks were initially influenced by the astrolabe; they could be seen in many ways as clockwork astrolabes designed to produce a continual display of the current position of the sun, stars, and planets. For example, Richard of Wallingford's clock (c. 1330) consisted essentially of a star map rotating behind a fixed rete, similar to that of an astrolabe.^[37]^

      Many astronomical clocks use an astrolabe-style display, such as the famous clock at Prague, adopting a stereographic projection (see below) of the ecliptic plane. In recent times, astrolabe watches have become popular. For example, Swiss watchmaker Ludwig Oechslin designed and built an astrolabe wristwatch in conjunction with Ulysse Nardin in 1985.^[38]^ Dutch watchmaker Christaan van der Klauuw also manufactures astrolabe watches today.^[39]^

      Construction

      An astrolabe consists of a disk, called the mater (mother), which is deep enough to hold one or more flat plates called tympans, or climates. A tympan is made for a specific latitude and is engraved with a stereographic projection of circles denoting azimuth and altitude and representing the portion of the celestial sphere above the local horizon. The rim of the mater is typically graduated into hours of time, degrees of arc, or both.^[40]^

      Above the mater and tympan, the rete, a framework bearing a projection of the ecliptic plane and several pointers indicating the positions of the brightest stars, is free to rotate. These pointers are often just simple points, but depending on the skill of the craftsman can be very elaborate and artistic. There are examples of astrolabes with artistic pointers in the shape of balls, stars, snakes, hands, dogs' heads, and leaves, among others.^[40]^ The names of the indicated stars were often engraved on the pointers in Arabic or Latin.^[41]^ Some astrolabes have a narrow rule or label which rotates over the rete, and may be marked with a scale of declinations.

      The rete, representing the sky, functions as a star chart. When it is rotated, the stars and the ecliptic move over the projection of the coordinates on the tympan. One complete rotation corresponds to the passage of a day. The astrolabe is, therefore, a predecessor of the modern planisphere.

      On the back of the mater, there is often engraved a number of scales that are useful in the astrolabe's various applications. These vary from designer to designer, but might include curves for time conversions, a calendar for converting the day of the month to the sun's position on the ecliptic, trigonometric scales, and graduation of 360 degrees around the back edge. The alidade is attached to the back face. An alidade can be seen in the lower right illustration of the Persian astrolabe above. When the astrolabe is held vertically, the alidade can be rotated and the sun or a star sighted along its length, so that its altitude in degrees can be read ("taken") from the graduated edge of the astrolabe; hence the word's Greek roots: "astron" (ἄστρον) = star + "lab-" (λαβ-) = to take. The alidade had vertical and horizontal cross-hairs which plots locations on an azimuthal ring called an almucantar (altitude-distance circle).

      An arm called a radius connects from the center of the astrolabe to the optical axis which is parallel with another arm also called a radius. The other radius contains graduations of altitude and distance measurements.

      A shadow square also appears on the back of some astrolabes, developed by Muslim astrologists in the 9th Century, whereas devices of the Ancient Greek tradition featured only altitude scales on the back of the devices.^[42]^ This was used to convert shadow lengths and the altitude of the sun, the uses of which were various from surveying to measuring inaccessible heights.^[43]^

      Devices were usually signed by their maker with an inscription appearing on the back of the astrolabe, and if there was a patron of the object, their name would appear inscribed on the front, or in some cases, the name of the reigning sultan or the teacher of the astrolabist has also been found to appear inscribed in this place.^[44]^ The date of the astrolabe's construction was often also signed, which has allowed historians to determine that these devices are the second oldest scientific instrument in the world. The inscriptions on astrolabes also allowed historians to conclude that astronomers tended to make their own astrolabes, but that many were also made to order and kept in stock to sell, suggesting there was some contemporary market for the devices.^[44]^

      Construction of astrolabes

      • The Hartmann astrolabe in Yale collection. This instrument shows its rete and rule.

        The Hartmann astrolabe in Yale collection. This instrument shows its rete and rule.

      • Celestial Globe, Isfahan (?), Iran 1144. Shown at the Louvre Museum, this globe is the third oldest surviving in the world.

        Celestial Globe, Isfahan (?), Iran 1144. Shown at the Louvre Museum, this globe is the third oldest surviving in the world.

      • Computer-generated planispheric astrolabe

        Computer-generated planispheric astrolabe

      Mathematical basis

      The construction and design of astrolabes are based on the application of the stereographic projection of the celestial sphere. The point from which the projection is usually made is the South Pole. The plane onto which the projection is made is that of the Equator.^[45]^

      Designing a tympanum through stereographic projection

      Parts of an Astrolabe tympanum

      The tympanum captures the celestial coordinate axes upon which the rete will rotate. It is the component that will enable the precise determination of a star's position at a specific time of day and year.

      Therefore, it should project:

      1. The zenith, which will vary depending on the latitude of the astrolabe user.
      2. The horizon line and almucantar or circles parallel to the horizon, which will allow for the determination of a celestial body's altitude (from the horizon to the zenith).
      3. The celestial meridian (north-south meridian, passing through the zenith) and secondary meridians (circles intersecting the north-south meridian at the zenith), which will enable the measurement of azimuth for a celestial body.
      4. The three main circles of latitude (Capricorn, Equator, and Cancer) to determine the exact moments of solstices and equinoxes throughout the year.

      The tropics and the equator define the tympanum

      Stereographic projection of Earth's tropics and equator from the South Pole.

      On the right side of the image above:

      1. The blue sphere represents the celestial sphere.
      2. The blue arrow indicates the direction of true north (the North Star).
      3. The central blue point represents Earth (the observer's location).
      4. The geographic south of the celestial sphere acts as the projection pole.
      5. The celestial equatorial plane serves as the projection plane.
      6. Three parallel circles represent the projection on the celestial sphere of Earth's main circles of latitude:

      When projecting onto the celestial equatorial plane, three concentric circles correspond to the celestial sphere's three circles of latitude (left side of the image). The largest of these, the projection on the celestial equatorial plane of the celestial Tropic of Capricorn, defines the size of the astrolabe's tympanum. The center of the tympanum (and the center of the three circles) is actually the north-south axis around which Earth rotates, and therefore, the rete of the astrolabe will rotate around this point as the hours of the day pass (due to Earth's rotational motion).

      The three concentric circles on the tympanum are useful for determining the exact moments of solstices and equinoxes throughout the year: if the sun's altitude at noon on the rete is known and coincides with the outer circle of the tympanum (Tropic of Capricorn), it signifies the winter solstice (the sun will be at the zenith for an observer at the Tropic of Capricorn, meaning summer in the southern hemisphere and winter in the northern hemisphere). If, on the other hand, its altitude coincides with the inner circle (Tropic of Cancer), it indicates the summer solstice. If its altitude is on the middle circle (equator), it corresponds to one of the two equinoxes.

      The horizon and the measurement of altitude

      Stereographic projection of an observer's horizon at a specific latitude

      On the right side of the image above:

      1. The blue arrow indicates the direction of true north (the North Star).
      2. The central blue point represents Earth (the observer's location).
      3. The black arrow represents the zenith direction for the observer (which would vary depending on the observer's latitude).
      4. The two black circles represent the horizon surrounding the observer, which is perpendicular to the zenith vector and defines the portion of the celestial sphere visible to the observer, and its projection on the celestial equatorial plane.
      5. The geographic south of the celestial sphere acts as the projection pole.
      6. The celestial equatorial plane serves as the projection plane.

      When projecting the horizon onto the celestial equatorial plane, it transforms into an ellipse upward-shifted relatively to the center of the tympanum (both the observer and the projection of the north-south axis). This implies that a portion of the celestial sphere will fall outside the outer circle of the tympanum (the projection of the celestial Tropic of Capricorn) and, therefore, won't be represented.

      Stereographic projection of the horizon and an almucantar.

      Additionally, when drawing circles parallel to the horizon up to the zenith (almucantar), and projecting them on the celestial equatorial plane, as in the image above, a grid of consecutive ellipses is constructed, allowing for the determination of a star's altitude when its rete overlaps with the designed tympanum.

      The meridians and the measurement of azimuth

      Stereographic projection of the north-south meridian and a meridian 40° E on the tympanum of an astrolabe

      On the right side of the image above:

      1. The blue arrow indicates the direction of true north (the North Star).
      2. The central blue point represents Earth (the observer's location).
      3. The black arrow represents the zenith direction for the observer (which would vary depending on the observer's latitude).
      4. The two black circles represent the horizon surrounding the observer, which is perpendicular to the zenith vector and defines the portion of the celestial sphere visible to the observer, and its projection on the celestial equatorial plane.
      5. The five red dots represent the zenith, the nadir (the point on the celestial sphere opposite the zenith with respect to the observer), their projections on the celestial equatorial plane, and the center (with no physical meaning attached) of the circle obtained by projecting the secondary meridian (see below) on the celestial equatorial plane.
      6. The orange circle represents the celestial meridian (or meridian that goes, for the observer, from the north of the horizon to the south of the horizon passing through the zenith).
      7. The two red circles represent a secondary meridian with an azimuth of 40° East relative to the observer's horizon (which, like all secondary meridians, intersects the principal meridian at the zenith and nadir), and its projection on the celestial equatorial plane.
      8. The geographic south of the celestial sphere acts as the projection pole.
      9. The celestial equatorial plane serves as the projection plane.

      When projecting the celestial meridian, it results in a straight line that overlaps with the vertical axis of the tympanum, where the zenith and nadir are located. However, when projecting the 40° E meridian, another circle is obtained that passes through both the zenith and nadir projections, so its center is located on the perpendicular bisection of the segment connecting both points. In deed, the projection of the celestial meridian can be considered as a circle with an infinite radius (a straight line) whose center is on this bisection and at an infinite distance from these two points.

      If successive meridians that divide the celestial sphere into equal sectors (like "orange slices" radiating from the zenith) are projected, a family of curves passing through the zenith projection on the tympanum is obtained. These curves, once overlaid with the rete containing the major stars, allow for determining the azimuth of a star located on the rete and rotated for a specific time of day.

      See also

      References

      Footnotes

      1.

      1. Savage-Smith, Emilie (1993). "Book Reviews". Journal of Islamic Studies. 4 (2): 296--299. doi:10.1093/jis/4.2.296. There is no evidence for the Hellenistic origin of the spherical astrolabe, but rather evidence so far available suggests that it may have been an early but distinctly Islamic development with no Greek antecedents.

      Notes

      1.

      1. Gentili, Graziano; Simonutti, Luisa; Struppa, Daniele C. (2020). "The Mathematics of the Astrolabe and Its History". Journal of Humanistic Mathematics. 10: 101--144. doi:10.5642/jhummath.202001.07. hdl:2158/1182616. S2CID 211008813.

      Bibliography

      • Evans, James (1998), The History and Practice of Ancient Astronomy, Oxford University Press, ISBN 0-19-509539-1
      • Stöffler, Johannes (2007) [First published 1513], Stoeffler's Elucidatio -- The Construction and Use of the Astrolabe [Elucidatio Fabricae Ususque Astrolabii], translated by Gunella, Alessandro; Lamprey, John, John Lamprey, ISBN 978-1-4243-3502-2
      • King, D. A. (1981), "The Origin of the Astrolabe According to the Medieval Islamic Sources", Journal for the History of Arabic Science, 5: 43--83
      • King, Henry (1978), Geared to the Stars: the Evolution of Planetariums, Orreries, and Astronomical Clocks, University of Toronto Press, ISBN 978-0-8020-2312-4
      • Krebs, Robert E.; Krebs, Carolyn A. (2003), Groundbreaking Scientific Experiments, Inventions, and Discoveries of the Ancient World, Greenwood Press, ISBN 978-0-313-31342-4
      • Laird, Edgar (1997), Carol Poster and Richard Utz (ed.), "Astrolabes and the Construction of Time in the Late Middle Ages", Constructions of Time in the Late Middle Ages, Evanston, Illinois: Northwestern University Press: 51--69
      • Laird, Edgar; Fischer, Robert, eds. (1995), "Critical edition of Pélerin de Prusse on the Astrolabe (translation of Practique de Astralabe)", Medieval & Renaissance Texts & Studies, Binghamton, New York, ISBN 0-86698-132-2
      • Lewis, M. J. T. (2001), Surveying Instruments of Greece and Rome, Cambridge University Press, ISBN 978-0-511-48303-5
      • Morrison, James E. (2007), The Astrolabe, Janus, ISBN 978-0-939320-30-1
      • Neugebauer, Otto E. (1975), A History of Ancient Mathematical Astronomy, Springer, ISBN 978-3-642-61912-0
      • North, John David (2005), God's Clockmaker: Richard of Wallingford and the Invention of Time, Continuum International Publishing Group, ISBN 978-1-85285-451-5

      External links

      Wikimedia Commons has media related to:\ Astrolabe (category)

      Wikisource has the text of the 1911 Encyclopædia Britannica article "Astrolabe".

      Look up astrolabe in Wiktionary, the free dictionary.

      |\ |

      |

      Astronomy in the medieval Islamic world

      |

      |\ |

      |

      Ancient Greek astronomy

      |

      Portals:

      |\ |

      |

      Authority control databases Edit this at Wikidata

      |

      Categories:

      Wikipedia The Free Encyclopedia

      Donate
      
      Create account
      Log in
      

      Personal tools

      Contents

      (Top)
      Navigational sextants
      Design
      Taking a sight
      Adjustment
      See also
      Notes
      References
      External links
      

      Sextant

      Article
      Talk
      
      Read
      Edit
      View history
      

      Tools

      Appearance Text

      Small
      Standard
      Large
      

      Width

      Standard
      Wide
      

      Color (beta)

      Automatic
      Light
      Dark
      

      From Wikipedia, the free encyclopedia This article is about the sextant as used for navigation. For other uses, see Sextant (disambiguation). Not to be confused with Sexton (disambiguation). A sextant

      A sextant is a doubly reflecting navigation instrument that measures the angular distance between two visible objects. The primary use of a sextant is to measure the angle between an astronomical object and the horizon for the purposes of celestial navigation.

      The estimation of this angle, the altitude, is known as sighting or shooting the object, or taking a sight. The angle, and the time when it was measured, can be used to calculate a position line on a nautical or aeronautical chart—for example, sighting the Sun at noon or Polaris at night (in the Northern Hemisphere) to estimate latitude (with sight reduction). Sighting the height of a landmark can give a measure of distance off and, held horizontally, a sextant can measure angles between objects for a position on a chart.[1] A sextant can also be used to measure the lunar distance between the moon and another celestial object (such as a star or planet) in order to determine Greenwich Mean Time and hence longitude.

      The principle of the instrument was first implemented around 1731 by John Hadley (1682–1744) and Thomas Godfrey (1704–1749), but it was also found later in the unpublished writings of Isaac Newton (1643–1727).

      In 1922, it was modified for aeronautical navigation by Portuguese navigator and naval officer Gago Coutinho. Navigational sextants

      Like the Davis quadrant, the sextant allows celestial objects to be measured relative to the horizon, rather than relative to the instrument. This allows excellent precision. Also, unlike the backstaff, the sextant allows direct observations of stars. This permits the use of the sextant at night when a backstaff is difficult to use. For solar observations, filters allow direct observation of the Sun.

      Since the measurement is relative to the horizon, the measuring pointer is a beam of light that reaches to the horizon. The measurement is thus limited by the angular accuracy of the instrument and not the sine error of the length of an alidade, as it is in a mariner's astrolabe or similar older instrument.

      A sextant does not require a completely steady aim, because it measures a relative angle. For example, when a sextant is used on a moving ship, the image of both horizon and celestial object will move around in the field of view. However, the relative position of the two images will remain steady, and as long as the user can determine when the celestial object touches the horizon, the accuracy of the measurement will remain high compared to the magnitude of the movement.

      The sextant is not dependent upon electricity (unlike many forms of modern navigation) or any human-controlled signals (such as GPS). For these reasons it is considered to be an eminently practical back-up navigation tool for ships. Design

      The frame of a sextant is in the shape of a sector which is approximately 1⁄6 of a circle (60°),[2] hence its name (sextāns, sextantis is the Latin word for "one sixth"). Both smaller and larger instruments are (or were) in use: the octant, quintant (or pentant) and the (doubly reflecting) quadrant[3] span sectors of approximately 1⁄8 of a circle (45°), 1⁄5 of a circle (72°) and 1⁄4 of a circle (90°), respectively. All of these instruments may be termed "sextants". Marine sextant Using the sextant to measure the altitude of the Sun above the horizon Sextants can also be used by navigators to measure horizontal angles between objects.

      Attached to the frame are the "horizon mirror", an index arm which moves the index mirror, a sighting telescope, Sun shades, a graduated scale and a micrometer drum gauge for accurate measurements. The scale must be graduated so that the marked degree divisions register twice the angle through which the index arm turns. The scales of the octant, sextant, quintant and quadrant are graduated from below zero to 90°, 120°, 140° and 180° respectively. For example, the sextant illustrated has a scale graduated from −10° to 142°, which is basically a quintant: the frame is a sector of a circle subtending an angle of 76° at the pivot of the index arm.

      The necessity for the doubled scale reading follows from consideration of the relations of the fixed ray (between the mirrors), the object ray (from the sighted object) and the direction of the normal perpendicular to the index mirror. When the index arm moves by an angle, say 20°, the angle between the fixed ray and the normal also increases by 20°. But the angle of incidence equals the angle of reflection so the angle between the object ray and the normal must also increase by 20°. The angle between the fixed ray and the object ray must therefore increase by 40°. This is the case shown in the graphic.

      There are two types of horizon mirrors on the market today. Both types give good results.

      Traditional sextants have a half-horizon mirror, which divides the field of view in two. On one side, there is a view of the horizon; on the other side, a view of the celestial object. The advantage of this type is that both the horizon and celestial object are bright and as clear as possible. This is superior at night and in haze, when the horizon and/or a star being sighted can be difficult to see. However, one has to sweep the celestial object to ensure that the lowest limb of the celestial object touches the horizon.

      Whole-horizon sextants use a half-silvered horizon mirror to provide a full view of the horizon. This makes it easy to see when the bottom limb of a celestial object touches the horizon. Since most sights are of the Sun or Moon, and haze is rare without overcast, the low-light advantages of the half-horizon mirror are rarely important in practice.

      In both types, larger mirrors give a larger field of view, and thus make it easier to find a celestial object. Modern sextants often have 5 cm or larger mirrors, while 19th-century sextants rarely had a mirror larger than 2.5 cm (one inch). In large part, this is because precision flat mirrors have grown less expensive to manufacture and to silver.

      An artificial horizon is useful when the horizon is invisible, as occurs in fog, on moonless nights, in a calm, when sighting through a window or on land surrounded by trees or buildings. There are two common designs of artificial horizon. An artificial horizon can consist simply of a pool of water shielded from the wind, allowing the user to measure the distance between the body and its reflection, and divide by two. Another design allows the mounting of a fluid-filled tube with bubble directly to the sextant.

      Most sextants also have filters for use when viewing the Sun and reducing the effects of haze. The filters usually consist of a series of progressively darker glasses that can be used singly or in combination to reduce haze and the Sun's brightness. However, sextants with adjustable polarizing filters have also been manufactured, where the degree of darkness is adjusted by twisting the frame of the filter.

      Most sextants mount a 1 or 3-power monocular for viewing. Many users prefer a simple sighting tube, which has a wider, brighter field of view and is easier to use at night. Some navigators mount a light-amplifying monocular to help see the horizon on moonless nights. Others prefer to use a lit artificial horizon.[citation needed]

      Professional sextants use a click-stop degree measure and a worm adjustment that reads to a minute, 1/60 of a degree. Most sextants also include a vernier on the worm dial that reads to 0.1 minute. Since 1 minute of error is about a nautical mile, the best possible accuracy of celestial navigation is about 0.1 nautical miles (190 m). At sea, results within several nautical miles, well within visual range, are acceptable. A highly skilled and experienced navigator can determine position to an accuracy of about 0.25-nautical-mile (460 m).[4]

      A change in temperature can warp the arc, creating inaccuracies. Many navigators purchase weatherproof cases so that their sextant can be placed outside the cabin to come to equilibrium with outside temperatures. The standard frame designs (see illustration) are supposed to equalise differential angular error from temperature changes. The handle is separated from the arc and frame so that body heat does not warp the frame. Sextants for tropical use are often painted white to reflect sunlight and remain relatively cool. High-precision sextants have an invar (a special low-expansion steel) frame and arc. Some scientific sextants have been constructed of quartz or ceramics with even lower expansions. Many commercial sextants use low-expansion brass or aluminium. Brass is lower-expansion than aluminium, but aluminium sextants are lighter and less tiring to use. Some say they are more accurate because one's hand trembles less. Solid brass frame sextants are less susceptible to wobbling in high winds or when the vessel is working in heavy seas, but as noted are substantially heavier. Sextants with aluminum frames and brass arcs have also been manufactured. Essentially, a sextant is intensely personal to each navigator, and they will choose whichever model has the features which suit them best.

      Aircraft sextants are now out of production, but had special features. Most had artificial horizons to permit taking a sight through a flush overhead window. Some also had mechanical averagers to make hundreds of measurements per sight for compensation of random accelerations in the artificial horizon's fluid. Older aircraft sextants had two visual paths, one standard and the other designed for use in open-cockpit aircraft that let one view from directly over the sextant in one's lap. More modern aircraft sextants were periscopic with only a small projection above the fuselage. With these, the navigator pre-computed their sight and then noted the difference in observed versus predicted height of the body to determine their position. Taking a sight

      A sight (or measure) of the angle between the Sun, a star, or a planet, and the horizon is done with the 'star telescope' fitted to the sextant using a visible horizon. On a vessel at sea even on misty days a sight may be done from a low height above the water to give a more definite, better horizon. Navigators hold the sextant by its handle in the right hand, avoiding touching the arc with the fingers.[5]

      For a Sun sight, a filter is used to overcome the glare such as "shades" covering both index mirror and the horizon mirror designed to prevent eye damage. Initially, with the index bar set to zero and the shades covering both mirrors, the sextant is aimed at the sun until it can be viewed on both mirrors through the telescope, then lowered vertically until the portion of the horizon directly below it is viewed on both mirrors. It is necessary to flip back the horizon mirror shade to be able to see the horizon more clearly on it. Releasing the index bar (either by releasing a clamping screw, or on modern instruments, using the quick-release button), and moving it towards higher values of the scale, eventually the image of the Sun will reappear on the index mirror and can be aligned to about the level of the horizon on the horizon mirror. Then the fine adjustment screw on the end of the index bar is turned until the bottom curve (the lower limb) of the Sun just touches the horizon. "Swinging" the sextant about the axis of the telescope ensures that the reading is being taken with the instrument held vertically. The angle of the sight is then read from the scale on the arc, making use of the micrometer or vernier scale provided. The exact time of the sight must also be noted simultaneously, and the height of the eye above sea-level recorded.[5]

      An alternative method is to estimate the current altitude (angle) of the Sun from navigation tables, then set the index bar to that angle on the arc, apply suitable shades only to the index mirror, and point the instrument directly at the horizon, sweeping it from side to side until a flash of the Sun's rays are seen in the telescope. Fine adjustments are then made as above. This method is less likely to be successful for sighting stars and planets.[5]

      Star and planet sights are normally taken during nautical twilight at dawn or dusk, while both the heavenly bodies and the sea horizon are visible. There is no need to use shades or to distinguish the lower limb as the body appears as a mere point in the telescope. The Moon can be sighted, but it appears to move very fast, appears to have different sizes at different times, and sometimes only the lower or upper limb can be distinguished due to its phase.[5]

      After a sight is taken, it is reduced to a position by looking at several mathematical procedures. The simplest sight reduction is to draw the equal-altitude circle of the sighted celestial object on a globe. The intersection of that circle with a dead-reckoning track, or another sighting, gives a more precise location.

      Sextants can be used very accurately to measure other visible angles, for example between one heavenly body and another and between landmarks ashore. Used horizontally, a sextant can measure the apparent angle between two landmarks such as a lighthouse and a church spire, which can then be used to find the distance off or out to sea (provided the distance between the two landmarks is known). Used vertically, a measurement of the angle between the lantern of a lighthouse of known height and the sea level at its base can also be used for distance off.[5] Adjustment

      Due to the sensitivity of the instrument it is easy to knock the mirrors out of adjustment. For this reason a sextant should be checked frequently for errors and adjusted accordingly.

      There are four errors that can be adjusted by the navigator, and they should be removed in the following order.

      Perpendicularity error This is when the index mirror is not perpendicular to the frame of the sextant. To test for this, place the index arm at about 60° on the arc and hold the sextant horizontally with the arc away from you at arm's length and look into the index mirror. The arc of the sextant should appear to continue unbroken into the mirror. If there is an error, then the two views will appear to be broken. Adjust the mirror until the reflection and direct view of the arc appear to be continuous. Side error This occurs when the horizon glass/mirror is not perpendicular to the plane of the instrument. To test for this, first zero the index arm then observe a star through the sextant. Then rotate the tangent screw back and forth so that the reflected image passes alternately above and below the direct view. If in changing from one position to another, the reflected image passes directly over the unreflected image, no side error exists. If it passes to one side, side error exists. Alternatively, the user can hold the sextant on its side and observe the horizon to check the sextant during the day. If there are two horizons there is side error. In both cases, adjust the horizon glass/mirror until respectively the star or the horizon dual images merge into one. Side error is generally inconsequential for observations and can be ignored or reduced to a level that is merely inconvenient. Collimation error This is when the telescope or monocular is not parallel to the plane of the sextant. To check for this you need to observe two stars 90° or more apart. Bring the two stars into coincidence either to the left or the right of the field of view. Move the sextant slightly so that the stars move to the other side of the field of view. If they separate there is collimation error. As modern sextants rarely use adjustable telescopes, they do not need to be corrected for collimation error. Index error This occurs when the index and horizon mirrors are not parallel to each other when the index arm is set to zero. To test for index error, zero the index arm and observe the horizon. If the reflected and direct image of the horizon are in line there is no index error. If one is above the other adjust the index mirror until the two horizons merge. Alternatively, the same procedure can be done at night using a star or the Moon instead of the horizon.

      See also

      Astrolabe
      Bris sextant
      Davis quadrant
      Gago Coutinho
      Harold Gatty
      History of longitude
      Intercept method
      Latitude
      Longitude
      Longitude by chronometer
      Mariner's astrolabe
      Navigation
      Octant (instrument)
      Quadrant (instrument)
      Sextant (astronomy)
      

      Notes

      Seddon, J. Carl (June 1968). "Line of Position from a Horizontal Angle". Journal of Navigation. 21 (3): 367–369. doi:10.1017/S0373463300024838. ISSN 1469-7785. A.), McPhee, John (John; NSW., Museums and Galleries (2008). Great Collections : treasures from Art Gallery of NSW, Australian Museum, Botanic Gardens Trust, Historic Houses Trust of NSW, Museum of Contemporary Art, Powerhouse Museum, State Library of NSW, State Records NSW. Museums & Galleries NSW. p. 56. ISBN 9780646496030. OCLC 302147838. This article treats the doubly reflecting quadrant, not its predecessor described at quadrant. Dutton's Navigation and Piloting, 12th edition. G.D. Dunlap and H.H. Shufeldt, eds. Naval Institute Press 1972, ISBN 0-87021-163-3

      Dixon, Conrad (1968). "5. Using the sextant". Basic Astro Navigation. Adlard Coles. ISBN 0-229-11740-6.
      

      References

      Bowditch, Nathaniel (2002). The American Practical Navigator. Bethesda, MD: National Imagery and Mapping Agency. ISBN 0-939837-54-4. Archived from the original on 2007-06-24.
      Chisholm, Hugh, ed. (1911). "Sextant" . Encyclopædia Britannica. Vol. 24 (11th ed.). Cambridge University Press. pp. 765–767.
      Cutler, Thomas J. (December 2003). Dutton's Nautical Navigation (15th ed.). Annapolis, MD: Naval Institute Press. ISBN 978-1-55750-248-3.
      Department of the Air Force (March 2001). Air Navigation (PDF). Department of the Air Force. Retrieved 2014-12-28.
      Great Britain Ministry of Defence (Navy) (1995). Admiralty Manual of Seamanship. The Stationery Office. ISBN 0-11-772696-6.
      Maloney, Elbert S. (December 2003). Chapman Piloting and Seamanship (64th ed.). New York: Hearst Communications. ISBN 1-58816-089-0.
      Martin, William Robert (1911). "Navigation" . In Chisholm, Hugh (ed.). Encyclopædia Britannica. Vol. 19 (11th ed.). Cambridge University Press. pp. 284–298.
      

      External links Look up sextant in Wiktionary, the free dictionary. Wikimedia Commons has media related to Sextant.

      Her Majesty's Nautical Almanac Office Archived 2011-02-21 at the Wayback Machine
      The History of HM Nautical Almanac Office Archived 2016-06-24 at the Wayback Machine
      Chapter 17 from the online edition of Nathaniel Bowditch's American Practical Navigator
      Understand difference in Antique & Replica Sextant Archived 2017-08-17 at the Wayback Machine
      CD-Sextant - Build your own sextant Simple do-it-yourself project.
      Lunars web site. online calculation
      Complete celnav theory book, including Lunars
      

      Portals:

      Earth sciences
      Astronomy
      icon Stars
      Spaceflight
      icon Science
      

      Authority control databases Edit this at Wikidata National

      GermanyUnited StatesFranceBnF dataIsrael
      

      Other

      NARA
      

      Categories:

      Navigational equipmentCelestial navigation1731 introductionsAstronomical instrumentsAngle measuring instruments
      
      This page was last edited on 28 June 2024, at 10:00 (UTC).
      Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply. By using this site, you agree to the Terms of Use and Privacy Policy. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization.
      
      Privacy policy
      About Wikipedia
      Disclaimers
      Contact Wikipedia
      Code of Conduct
      Developers
      Statistics
      Cookie statement
      Mobile view
      
      Wikimedia Foundation
      Powered by MediaWiki
      

      dsabs.harvard.edu/abs/1956iatw.book.....M).*

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The emergence of Drosophila EM connectomes has revealed numerous neurons within the associative learning circuit. However, these neurons are inaccessible for functional assessment or genetic manipulation in the absence of cell-type-specific drivers. Addressing this knowledge gap, Shuai et al. have screened over 4000 split-GAL4 drivers and correlated them with identified neuron types from the "Hemibrain" EM connectome by matching light microscopy images to neuronal shapes defined by EM. They successfully generated over 800 split-GAL4 drivers and 22 split-LexA drivers covering a substantial number of neuron types across layers of the mushroom body associative learning circuit. They provide new labeling tools for olfactory and non-olfactory sensory inputs to the mushroom body; interneurons connected with dopaminergic neurons and/or mushroom body output neurons; potential reinforcement sensory neurons; and expanded coverage of intrinsic mushroom body neurons. Furthermore, the authors have optimized the GR64f-GAL4 driver into a sugar sensory neuron-specific split-GAL4 driver and functionally validated it as providing a robust optogenetic substitute for sugar reward. Additionally, a driver for putative nociceptive ascending neurons, potentially serving as optogenetic negative reinforcement, is characterized by optogenetic avoidance behavior. The authors also use their very large dataset of neuronal anatomies, covering many example neurons from many brains, to identify neuron instances with atypical morphology. They find many examples of mushroom body neurons with altered neuronal numbers or mistargeting of dendrites or axons and estimate that 1-3% of neurons in each brain may have anatomic peculiarities or malformations. Significantly, the study systematically assesses the individualized existence of MBON08 for the first time. This neuron is a variant shape that sometimes occurs instead of one of two copies of MBON09, and this variation is more common than that in other neuronal classes: 75% of hemispheres have two MBON09's, and 25% have one MBON09 and one MBON08. These newly developed drivers not only expand the repertoire for genetic manipulation of mushroom body-related neurons but also empower researchers to investigate the functions of circuit motifs identified from the connectomes. The authors generously make these flies available to the public. In the foreseeable future, the tools generated in this study will allow important advances in the understanding of learning and memory in Drosophila.

      Strengths:

      (1) After decades of dedicated research on the mushroom body, a consensus has been established that the release of dopamine from DANs modulates the weights of connections between KCs and MBONs. This process updates the association between sensory information and behavioral responses. However, understanding how the unconditioned stimulus is conveyed from sensory neurons to DANs, and the interactions of MBON outputs with innate responses to sensory context remains less clear due to the developmental and anatomic diversity of MBONs and DANs. Additionally, the recurrent connections between MBONs and DANs are reported to be critical for learning. The characterization of split-GAL4 drivers for 30 major interneurons connected with DANs and/or MBONs in this study will significantly contribute to our understanding of recurrent connections in mushroom body function.

      (2) Optogenetic substitutes for real unconditioned stimuli (such as sugar taste or electric shock) are sometimes easier to implement in behavioral assays due to the spatial and temporal specificity with which optogenetic activation can be induced. GR64f-GAL4 has been widely used in the field to activate sugar sensory neurons and mimic sugar reward. However, the authors demonstrate that GR64f-GAL4 drives expression in other neurons not necessary for sugar reward, and the potential activation of these neurons could introduce confounds into training, impairing training efficiency. To address this issue, the authors have elaborated on a series of intersectional drivers with GR64f-GAL4 to dissect subsets of labeled neurons. This approach successfully identified a more specific sugar sensory neuron driver, SS87269, which consistently exhibited optimal training performance and triggered ethologically relevant local searching behaviors. This newly characterized line could serve as an optimized optogenetic tool for sugar reward in future studies.

      (3) MBON08 was first reported by Aso et al. 2014, exhibiting dendritic arborization into both ipsilateral and contralateral γ3 compartments. However, this neuron could not be identified in the previously published Drosophila brain connectomes. In the present study, the existence of MBON08 is confirmed, occurring in one hemisphere of 35% of imaged flies. In brains where MBON08 is present, its dendrite arborization disjointly shares contralateral γ3 compartments with MBON09. This remarkable phenotype potentially serves as a valuable resource for understanding the stochasticity of neurodevelopment and the molecular mechanisms underlying mushroom body lobe compartment formation.

      Weaknesses:

      There are some minor weaknesses in the paper that can be clarified:

      (1) In Figure 8, the authors trained flies with a 20s, weak optogenetic conditioning first, followed by a 60s, strong optogenetic conditioning. The rationale for using this training paradigm is not explicitly provided.

      These experiments were designed to test if flies could maintain consistent performance with repetitive and intense LED activation, which is essential for experiments involving long training protocols or coactivation of other neurons inside a brain.

      In Figure 8E, if data for training with GR64f-GAL4 using the same paradigm is available, it would be beneficial for readers to compare the learning performance using newly generated split-GAL4 lines with the original GR64f-GAL4, which has been used in many previous research studies. It is noteworthy that in previously published work, repeating training test sessions typically leads to an increase in learning performance in discrimination assays. However, this augmentation is not observed in any of the split-GAL4 lines presented in Figure 8E. The authors may need to discuss possible reasons for this.

      As the reviewer pointed out, many previous studies including ours used the original Gr64f-GAL4 in olfactory conditioning. Figure 1H of Yamada et al., 2023 (https://doi.org/10.7554/eLife.79042) showed such a result, where the first and second-order olfactory conditioning were assayed. Indeed, the first-order conditioning scores were gradually augmented over repeated training. In this experiment, we used low red LED intensity for the optogenetic activation. In the Figure 8E of the present paper, the first memory test was after 3x pairing of 20s odor with five 1s red LED without intermediate tests. Therefore, flies were already sufficiently trained to show a plateau memory level in “Test1”. In the revision of another recent report (Figure 1C-F of Aso et al., 2023; https://doi.org/10.7554/eLife.85756), we included the learning curve data of our best Gr64f-split-GAL4, SS87269. Under a less saturated training conditioning, SS87269 did show learning augmentation over repeated training.

      (2) In line 327, the authors state that in all samples, the β'1 compartment is arborized by MBON09. However, in Figure 11J, the probability of having at least one β'1 compartment not arborized is inferred to be 2%. The authors should address and clarify this conflict in the text to avoid misunderstanding.

      The chance of visualizing MBON08 in MCFO images was 21/209 in total (Figure 11I). If we assume that each of four cells adopt MBON08 development fate at this chance, we can calculate the probability for each case of MBON08/09 cell type composition. From this calculation, we inferred approximately 2% of flies would lack innervations to β'1 compartment in at least one hemisphere. However, we didn't observe a lack of β'1 arborizations in 169 sample flies. If these MBONs independently develop into MBON08 at 21/209 odds, the chance of never observing two MBON08s in either hemisphere of all 169 samples is 3.29%. Therefore, some developmental mechanisms may prevent the emergence of two MBON08 in the same hemisphere.

      In the revised manuscript, we displayed these estimated probability for each case separately, and annotated actual observation on the right side.

      (3) In general, are the samples presented male or female? This sample metadata will be shown when the images are deposited in FlyLight, but it would be useful in the context of this manuscript to describe in the methods whether animals are all one sex or mixed sex, and in some example images (e.g. mAL3A) to note whether the sample is male or female.

      The samples presented in this study are mixed sex, except for Figure 11I, where genders are specified. We provided metadata information of the presented images in Supplemental File 7, and we added a paragraph in the in the method section:

      “Most samples were collected from females, though typically at least one male fly was examined for each driver line. While we noticed certain lines such as SS48900, exhibited distinct expression patterns in females and males, we did not particularly focus on sexual dimorphism, which is analyzed elsewhere (Meissner et al. 2024). Therefore, unless stated otherwise, the presented samples are of mixed gender.

      Detailed metadata, including gender information and the reporter used, can be found in Supplementary File 7.”

      Reviewer #2 (Public Review):

      Summary:

      The article by Shuai et al. describes a comprehensive collection of over 800 split-GAL4 and split-LexA drivers, covering approximately 300 cell types in Drosophila, aimed at advancing the understanding of associative learning. The mushroom body (MB) in the insect brain is central to associative learning, with Kenyon cells (KCs) as primary intrinsic neurons and dopaminergic neurons (DANs) and MB output neurons (MBONs) forming compartmental zones for memory storage and behavior modulation. This study focuses on characterizing sensory input as well as direct upstream connections to the MB both anatomically and, to some extent, behaviorally. Genetic access to specific, sparsely expressed cell types is crucial for investigating the impact of single cells on computational and functional aspects within the circuitry. As such, this new and extensive collection significantly extends the range of targeted cell types related to the MB and will be an outstanding resource to elucidate MB-related processes in the future.

      Strengths:

      The work by Shuai et al. provides novel and essential resources to study MB-related processes and beyond. The resulting tools are publicly available and, together with the linked information, will be foundational for many future studies. The importance and impact of this tool development approach, along with previous ones, for the field cannot be overstated. One of many interesting aspects arises from the anatomical analysis of cell types that are less stereotypical across flies. These discoveries might open new avenues for future investigations into how such asymmetry and individuality arise from development and other factors, and how it impacts the computations performed by the circuitry that contains these elements.

      Weaknesses:

      Providing such an array of tools leaves little to complain about. However, despite the comprehensive genetic access to diverse sensory pathways and MB-connected cell types, the manuscript could be improved by discussing its limitations. For example, the projection neurons from the visual system seem to be underrepresented in the tools produced (or almost absent). A discussion of these omissions could help prevent misunderstandings.

      We internally distributed efforts to produce split-GAL4 lines at Janelia Research Campus. The recent preprint (Nern et al., 2024; doi: https://doi.org/10.1101/2024.04.16.589741) described the full collection of split-GAL4 driver lines in the optic lobe including the visual projection neurons to the mushroom body. We cited this preprint in the revised manuscript by adding a short paragraph of discussion.

      “Although less abundant than the olfactory input, the MB also receives visual information from the visual projection neurons (VPNs) that originate in the medulla and lobula and are targeted to the accessory calyx (Vogt et al. 2016; Li et al. 2020). A recent preprint described the full collection of split-GAL4 driver lines in the optic lobe, which includes the VPNs to the MB (Nern et al. 2024).”

      Additionally, more details on the screening process, particularly the selection of candidate split halves and stable split-GAL4 lines, would provide valuable insights into the methodology and the collection's completeness.

      The details of our split-GAL4 design and screening procedures were described in previous studies (Aso et al., 2014; Dolan et al., 2019). Available data and tools to design split-GAL4 changed over time, and we took different approaches accordingly. Many of split-GAL4 lines presented in this study were designed and screened in parallel to the lines for MBONs and DANs in 2010-2014 when MCFO images of GAL4 drivers and EM connectome were not yet available. With knowledge of where MBONs and DANs project, I (Y.A.) manually examined and annotated thousands of confocal stacks (Jenett et al., 2012; https://doi.org/10.1016/j.celrep.2012.09.011) to find candidate cell types that may concat with them.

      Later I used more advanced computational tools (Otsuna et al., 2018; doi: https://doi.org/10.1101/318006) and MCFO images aligned to the standard brain volume (Meissner et al., 2023; DOI: 10.7554/eLife.80660.). Now, if one needs to further generate split-GAL4 lines for cell type identified in EM connectome data, neuron bridge website (https://neuronbridge.janelia.org/) can be very helpful to provide a list of GAL4 drivers that may label the neuron of interest.

      Reviewer #3 (Public Review):

      Summary:

      Previous research on the Drosophila mushroom body (MB) has made this structure the best-understood example of an associative memory center in the animal kingdom. This is in no small part due to the generation of cell-type specific driver lines that have allowed consistent and reproducible genetic access to many of the MB's component neurons. The manuscript by Shuai et al. now vastly extends the number of driver lines available to researchers interested in studying learning and memory circuits in the fly. It is an 800-plus collection of new cell-type specific drivers target neurons that either provide input (direct or indirect) to MB neurons or that receive output from them. Many of the new drivers target neurons in sensory pathways that convey conditioned and unconditioned stimuli to the MB. Most drivers are exquisitely selective, and researchers will benefit from the fact that whenever possible, the authors have identified the targeted cell types within the Drosophila connectome. Driver expression patterns are beautifully documented and are publicly available through the Janelia Research Campus's Flylight database where full imaging results can be accessed. Overall, the manuscript significantly augments the number of cell type-specific driver lines available to the Drosophila research community for investigating the cellular mechanisms underlying learning and memory in the fly. Many of the lines will also be useful in dissecting the function of the neural circuits that mediate sensorimotor circuits.

      Strengths:

      The manuscript represents a huge amount of careful work and leverages numerous important developments from the last several years. These include the thousands of recently generated split-Gal4 lines at Janelia and the computational tools for pairing them to make exquisitely specific targeting reagents. In addition, the manuscript takes full advantage of the recently released Drosophila connectomes. Driver expression patterns are beautifully illustrated side-by-side with corresponding skeletonized neurons reconstructed by EM. A comprehensive table of the new lines, their split-Gal4 components, their neuronal targets, and other valuable information will make this collection eminently useful to end-users. In addition to the anatomical characterization, the manuscript also illustrates the functional utility of the new lines in optogenetic experiments. In one example, the authors identify a specific subset of sugar reward neurons that robustly promotes associative learning.

      Weaknesses:

      While the manuscript succeeds in making a mass of descriptive detail quite accessible to the reader, the way the collection is initially described - and the new lines categorized - in the text is sometimes confusing. Most of the details can be found elsewhere, but it would be useful to know how many of the lines are being presented for the first time and have not been previously introduced in other publications/contexts.

      We revised the text as below.

      “Among the 828 lines, a subset of 355 lines, collectively labeling at least 319 different cell types, exhibit highly specific and non-redundant expression patterns are likely to be particularly valuable for behavioral experiments. Detailed information, including genotype, expression specificity, matched EM cell type(s), and recommended driver for each cell type, can be found in Supplementary File 1. A small subset of 40 lines from this collection have been previously used in studies (Aso et al., 2023; Dolan et al., 2019; Gao et al., 2019; Scaplen et al., 2021; Schretter et al., 2020; Takagi et al., 2017; Xie et al., 2021; Yamada et al., 2023). All transgenic lines newly generated in this study are listed in Supplementary File 2 (Aso et al., 2023; Dolan et al., 2019; Gao et al., 2019; Scaplen et al., 2021; Schretter et al., 2020; Takagi et al., 2017; Xie et al., 2021; Yamada et al., 2023).”

      And where can the lines be found at Flylight? Are they listed as one collection or as many?

      They are listed as one collection - “Aso 2021” release. It is named “2021” because we released the images and started sharing lines in December of 2021 without a descriptive paper. We added a sentence in the Methods section.

      “All splitGAL4 lines can be found at flylight database under “Aso 2021” release, and fly strains can be requested from Janelia or the Bloomington stock center.”

      Also, the authors say that some of the lines were included in the collection despite not necessarily targeting the intended type of neuron (presumably one that is involved in learning and memory). What percentage of the collection falls into this category?

      We do not have a good record of split-GAL4 screening to calculate the chance to intersect unintended cell types, but it was rather rare. Those unintended cell types can still be a part of circuits for associative learning (e.g. olfactory projection neurons) or totally unrelated cell types. For instance, among a new collection of split-LexA lines using Gr43a-LexADBD hemidriver (Figure 7-figure supplement 2), one line specifically intersected T1 neurons in the optic lobe despite that the AD line was selected to intersect sugar sensory neurons. We suspect that this is due to ectopic expression of Gr43a-LexADBD. Nonetheless, we included it in the paper because cell-type-specific Split-LexA driver for T1 will be useful irrespective of whether the expression of Gr43a gene is expressed in T1 or not.

      And what about the lines that the authors say they included in the collection despite a lack of specificity? How many lines does this represent?

      For a short answer, there are about 100 lines in the collection that lack the specificity for behavioral experiments.

      We ranked specificity of split-GAL4 drivers in the Supplementary File 1. Rank 2 are the ideal lines, Rank 1 are less ideal but acceptable, and Rank 0 is not suitable for activation screening in behavioral experiments. Out of the 828 split-GAL4 lines reported here, there are 413, 305 and 103 lines in rank2, rank1 and rank0 categories respectively. 7 lines are not ranked for specificity because only flipout expression data are available.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      As mentioned elsewhere and in addition to the minor points below, it is advisable for the authors to elaborate on the details of the screening process. Furthermore, a discussion about the circuits not targeted by their research, such as the visual projection neurons, would be beneficial.

      See the response above to Reviewer #2’s public review.

      Line 32-33: The citations are very fly-centric. the authors might want to consider reviews on the MB of other insect species regarding learning and memory.

      We additionally cited Rybak and Menzel 2017’s book chapter on honey bee mushroom body.

      Line 43-44: Citations should be added, e.g. Séjourné et al. (2011), Pai et al. (2013), Plaçais et al. (2013).

      Citation added

      Line 50-52: Citation Hulse et al. (2021) should be added.

      Citation added

      Line 162: In this part, it might be valuable for the reader to understand which of these PNs are actually connecting with KCs.

      A full list of cell types within the MB were provided in Supplementary File 4 of the revised manuscript. See also response to Reviewer 3, Lines 150-1.

      Line 179: Citation Burke et al. (2012) should be mentioned.

      Citation added

      Line 181: Thermogenic might be thermogenetic.

      Corrected

      Line 189: Citations add Otto et al. (2020) and Felsenberg et al. (2018).

      Citations added

      Line 208ff: The authors should consider discussing why they did not use other GR and IR promoters. For example, Gr5a is prominent in sugar-sensing, while Ir76b could be a reinforcement signal related to yeast food (Steck et al., 2018; Ganguly et al., 2017; see also Corfas et al., 2019 for local search).

      We focused on the Gr64f promoter because of its relatively broad expression and successful use of Gr64f-GAL4 for fictive reward experiment. We added the Split-LexA lines with Gr43a and Gr66a promoters (Figure 7-figure supplement 2). Other gustatory sensory neurons also have the potential to be reinforcement signals, but we just did not have the bandwidth to cover them all.

      Line 319: Consider citing Linneweber et al. (2020) for a neurodevelopmental account of such individuality.

      We added a sentence and cited this reference.

      “On the other hand, the neurodevelopmental origin of neuronal morphology appeared to have functional significance on behavioral individuality (Linneweber et al. 2020).”

      Line 352: Citation add Hulse et al. (2021).

      Citations added

      Line 356ff: The utility and value of Split-LexA may not be apparent to non-expert readers. Moreover, how were LexADBDs chosen for creating these lines?

      We have added an introductory sentence at the beginning of the paragraph and explained that these split-LexA lines were a conversion of split-GAL4 lines that were published in 2014 and frequently used in studying the mushroom body circuit.

      “Split-GAL4 lines enable cell-type-specific manipulation, but some experiments require independent manipulation of two cell types. Split-GAL4 lines can be converted into split-LexA lines by replacing the GAL4 DNA binding domain with that of LexA (Ting et al., 2011). To broaden the utility of the split-GAL4 lines that have been frequently used since the publication in 2014 (Aso et al., 2014a), we have generated over 20 LexADBD lines to test the conversions of split-GAL4 to split-LexA. The majority (22 out of 34) of the resulting split-LexA lines exhibited very similar expression patterns to their corresponding original split-GAL4 lines (Figure 12).”

      Line 374: Italicize Drosophila melanogaster.

      Revised as suggested.

      Reviewer #3 (Recommendations For The Authors):

      Major Comments:

      As mentioned in the Public Review, the drivers are nicely classified in the various subsections of the manuscript, but the statements in the text summarizing how many lines there are in specific categories are often confusing. For example, line 129 refers to "drivers encompassing 111 cell types that connect with the DANs and MBONs", but Figure 1E indicates that 46 new cell types downstream of MBONs and upstream of DANs have been generated. This seems like a discrepancy.

      The 46 cell types in Figure 1E consider only the CRE/SMP/SIP/SLP area, where MBON downstreams and DAN upstreams are highly enriched, while the 111 cell types include all. To avoid confusion, we removed the “MBON downstream and DAN upstream” counting in Figure 1E in the revised manuscript.

      Also, at line 75 the MBON lines previously generated by Rubin and Aso (2023) are referred to as though they are separate from the 828 described "In this report." Supplementary file 1 suggests, however, that they are included as part of this report.

      Twenty five lines generated in Rubin and Aso (2023) were initially included in Supplementary file 1 for the convenience of users, but they were not counted towards the 828 new lines described in this report. To avoid confusion, we removed these 25 lines in the revised manuscript. Now all lines listed in Supplementary file 1 were generated in this study (“Aso 2021” release), and if a line has been used in earlier studies, or introduced in other contexts, for example the accompanying omnibus preprint (Meissener 2024, doi: 10.1101/2024.01.09.574419), the citations are listed in the reference column.

      More generally, in lines 94-102 "828 useful lines based on their specificity, intensity and non-redundancy" are referred to, but they are subsequently subdivided into categories of lines with lower specificity (i.e. with off-target expression) and lines that did not target intended cell types (presumably ones unlikely to be involved in learning and memory). It would be useful to know how many lines (at least roughly) fall into these subcategories.

      See the response above to Reviewer #3’s public review.

      Finally, Figures 3B & C indicate cell types connected to DANs and MBONs and the number for which Split-Gal4 lines are available. The text (lines 136-7) states that the new collection covers 30 of these major cell types (Figure 3C)," but Figure 3C clearly has more than 30 dots showing the drivers available. Presumably existing and new driver lines are being pooled, but this should either be explained or the two should be distinguished.

      “(Figure 3C)” was replaced with “(Supplementaryl File 3)” in the revised manuscript to correct the reference. Figure 3B & C are plots of all MB interneurons, not just the major cell types.

      Minor Comments:

      Although the paper is generally well written there are minor grammatical errors throughout (e.g. dropped articles, odd constructions, etc.) that somewhat detract from an otherwise smooth and enjoyable reading experience. A quick editing pass by a native speaker (i.e. any of several of the authors) could clean up these and numerous other small mistakes. A few examples: line 138 "presented" should be present; line 204: "contain off-targeted expressions" should be "have off-target expression;" line 219: "usage to substitute reward" is awkward at best and could be something like "use in generating fictive rewards"; line 326 "arborize[s]"; l. 331 "Based on the likelihood" should be something like "based on these observations"'; line 349 "[is] likely to appear"; l. 352 "extensive connection[s]"; line 353 "has [a] strong influence;" l. 963 "Projections" should be singular; etc.

      All the mentioned examples have been corrected, and we have asked a native speaker to edit through the revised manuscript.

      Lines 81-3: Is the lookup table referred to Suppl. File 1? A reference is desirable.

      Yes, the lookup table referred to “Supplementary File 1” and a reference was added.

      Lines 111-2: what is a "non-redundant set of...cell types?" Cell types that are represented by a single cell (or bilateral pair)? Or does this sentence mean that of the 828 lines, 355 are specific to a single cell type, and in total 319 cell types are targeted? The statement is confusing.

      We revised the text as below.

      “Figure 1E provides an overview of the categories of covered cell types. Among the 828 lines, a subset of 355 lines, collectively labeling at least 319 different cell types, exhibit highly specific and non-redundant expression patterns are likely to be particularly valuable for behavioral experiments. Detailed information, including genotype, expression specificity, matched EM cell type(s), and recommended driver for each cell type, can be found in Supplementary File 1. A small subset of 40 lines from this collection have been previously used in studies (Aso et al.,

      2023; Dolan et al., 2019; Gao et al., 2019; Scaplen et al., 2021; Schretter et al., 2020; Takagi et al., 2017; Xie et al., 2021; Yamada et al., 2023). All transgenic lines newly generated in this study are listed in Supplementary File 2 (Aso et al., 2023; Dolan et al., 2019; Gao et al., 2019; Scaplen et al., 2021; Schretter et al., 2020; Takagi et al., 2017; Xie et al., 2021; Yamada et al., 2023).”

      Line 148: "MB major interneurons" is a confusing descriptor for postsynaptic partners of MBONs.

      We added a sentence to clarify the definition of the “MB major interneurons”.

      “In the hemibrain EM connectome, there are about 400 interneuron cell types that have over 100 total synaptic inputs from MBONs and/or synaptic outputs to DANs. Our newly developed collection of split-GAL4 drivers covers 30 types of these ‘major interneurons’ of the MB (Supplementary File 3).”

      Lines 150-1: Not sure what is meant by "have innervations within the MB." Sounds like cells are presynaptic to KCs, DANS, and MBONs, but Figure 3 Figure Supplement 1 indicates they include neurons that both provide and receive innervation to/from MB neurons. Please clarify.

      For clarification, in the revised manuscript we have included a full list of cell types within the MB in Supplementary File 4. Included are all neurons with >= 50 pre-synaptic connections or with >=250 post-synaptic connections in the MB roi in the hemibrain (excluding the accessory calyx). The cell types include KCs, MBONs, DANs, PNs, and a few other cell types. The coverage ratio was updated based on this list.

      Also, in line 152, what does it mean that they "may have been overlooked previously?" this seems unnecessarily ambiguous. Were they overlooked or weren't they?

      Changed the text to “These lines offer valuable tools to study cell types that previously are not genetically accessible. Notably, SS85572 enables the functional study of LHMB1, which forms a rare direct pathway from the calyx and the lateral horn (LH) to the MB lobes (Bates et al., 2020). ”

      Line 158 refers to PN cells within the MB, which are not mentioned in any place else as MB components.

      What are these PNs and how do they differ from MBONs?

      See responses to Lines 150-1 for clarification of cell types within the MB.

      Line 188: not clear what is meant by "more continual learning tasks".

      We rephrase it as “more complex learning tasks” to avoid jargon.

      Line 235: Not clear why "extended training with high LED intensity" wouldn't promote the formation of robust memories. Is this for some reason unexpected based on previous experiments? Please explain.

      See responses to weakness #1 of the same reviewer

      Lines 317-9: It would be useful to state here that MB0N08 and MB0N09 are the two neurons labeled by MB083C.

      Revised as suggested.

      Line 368: Presumably the "lookup table" referred to is Supplementary File 1, but a reference here would be useful.

      Yes, Supplementary File 1 and a reference was added.

      Comments on Figures:

      Figure 1C The "Dopamine Neurons" label position doesn't align with the Punishment and Reward labels, which is a bit confusing.

      They are intentionally not aligned, because dopamine neurons are not reward/punishment per se. We intend to use the schematic to show that the punishment and reward are conveyed to the MB through the dopamine neuron layer, just as the output from the MB output neuron layer is used to guide further integration and actions. To keep the labels of “Dopamine neurons” and “MB Output Neurons” in a symmetrical position, we decide to keep the original figure unchanged. But we thank the reviewer for the kind suggestion.

      Figure 1F and Figure 1 - Figure Supplement 1: the light gray labels presumably indicate the (EM-identified) neuron labeled by each line, but this should be explicitly stated in the figure legends. It would also be useful in the legends to direct the reader to the key (Supplementary File 1) for decoding neuronal identities.

      Revised as suggested.

      Figure 2: For clarity, I'd recommend titling this figure "LM-EM Match of the CRE011-specific driver SS45245". This reduces the confusion of mixing and matching the driver and cell-type names. Also, it would be helpful to indicate (e.g. with labels above the figure parts) that A & B represent the MCFO characterization step and C & D represent the LM-EM matching step of the pipeline. Revised as suggested.

      Figure 6: For clarity, it would be useful to separately label the PN and sensory neuron groups. Also, for the sensory neurons at the bottom, what is the distinction between the cell names in gray and black font?

      Figure 6 was updated to separate the non-olfactory PN and sensory neuron groups. The gray was intended for olfactory receptor neuron cell types that are additionally labeled in the driver lines. To avoid confusion, the gray cell types were removed in the revised figure, and a clarification sentence was added to the legend.

      “Other than thermo-/hygro-sensory receptor neurons (TRNs and HRNs), SS00560 and MB408B also label olfactory receptor neurons (ORNs): ORN_VL2p and ORN_VC5 for SS00560, ORN_VL1 and ORN_VC5 for MB408B.”

      Figure 7A: It's unclear why the creation of 6 Gr64f-LexADBD lines is reported. Aren't all these lines the same? If not, an explanation would be useful.

      These six Gr64f-LexADBD lines are with different insertion sites, and with the presence or absence of the p10 translational enhancer. Explanation was added to legend. Enhanced expression level with p10 can be helpful to compensate for the general tendency that split-LexA is weaker than split-GAL4. Different insertions will be useful to avoid transvections with split-GAL4s, which are mostly in attP40 and attP2.

      Figure 8F: It would help to include in the legend a brief description of each parameter being measured-essentially defining the y-axis label on the graphs as in Figure Supplement 2. Also, how is the probability of return calculated and what behavioral parameter does the change of curvature refer to?

      We added a brief description to the behavioral parameters in the legend of Figure 8F.

      “Return behavior was assessed within a 15-second time window. The probability of return (P return) is the percentage of flies that made an excursion (>10 mm) and then returned to within 3 mm of their initial position. Curvature is the ratio of angular velocity to walking speed.”

      Figure 9E: What are the parenthetical labels for lines SS49267, SS49300, and SS35008?

      They are EM bodyIDs. Figure legend was revised.

    1. Reviewer #3 (Public review):

      In this study, Cao et al. explore the neural mechanisms by which chronic heat exposure induces negative valence and hyperarousal in mice, focusing on the role of the posterior paraventricular nucleus (pPVT) neurons that receive projections from the preoptic area (POA). The authors show that chronic heat exposure leads to heightened activity of the POA projection-receiving pPVT neurons, potentially contributing to behavioral changes such as increased anxiety level and reduced sociability, along with heightened startle responses. In addition, using electrophysiological methods, the authors suggest that increased membrane excitability of pPVT neurons may underlie these behavioral changes. The use of a variety of behavioral assays enhances the robustness of their claim. Moreover, while previous research on thermoregulation has predominantly focused on physiological responses to thermal stress, this study adds a unique and valuable perspective by exploring how thermal stress impacts affective states and behaviors, thereby broadening the field of thermoregulation. However, a few points warrant further consideration to enhance the clarity and impact of the findings.

      (1) The authors claim that behavior changes induced by chronic heat exposure are mediated by the POA-pPVT circuit. However, it remains unclear whether these changes are unique to heat exposure or if this circuit represents a more general response to chronic stress. It would be valuable to include control experiments with other forms of chronic stress, such as chronic pain, social defeat, or restraint stress, to determine if the observed changes in the POA-pPVT circuit are indeed specific to thermal stress or indicative of a more universal stress response mechanism.

      (2) The authors use the term "negative emotion and hyperarousal" to interpret behavioral changes induced by chronic heat (consistently throughout the manuscript, including the title and lines 33-34). However, the term "emotion" is broad and inherently difficult to quantify, as it encompasses various factors, including both valence and arousal (Tye, 2018; Barrett, L. F. 1999; Schachter, S. 1962). Therefore, the reviewer suggests the authors use a more precise term to describe these behaviors, such as valence. Additionally, in lines 117 and 137-139, replacing "emotion" with "stress responses," a term that aligns more closely with the physiological observations, would provide greater specificity and clarity in interpreting the findings.

      (3) Related to the role of POA input to pPVT,<br /> a) The authors showed increased activity in pPVT neurons that receive projections from the POA (Figure 3), and these neurons are necessary for heat-induced behavioral changes (Figures 4N-W). However, is the POA input to the pPVT circuit truly critical? Since recipient pPVT neurons can receive inputs from various brain regions, the reviewer suggests that experiments directly inhibiting the POA-to-pPVT projection itself are needed to confirm the role of POA input. Alternatively, the authors could show that the increased activity of pPVT neurons due to chronic heat exposure is not observed when the POA is blocked. If these experiments are not feasible, the reviewer suggests that the authors consider toning down the emphasis on the role of the POA throughout the manuscript and discuss this as a limitation.<br /> b) In the electrophysiology experiments shown in Figures 6A-I, the authors conducted in vitro slice recordings on pPVT neurons. However, the interpretation of these results (e.g., "The increase in presynaptic excitability of the POA to pPVT excitatory pathway suggested plastic changes induced by the chronic heat treatment.", lines 349-350) appears to be an overclaim. It is difficult to conclude that the increased excitability of pPVT neurons due to heat exposure is specifically caused by inputs from the POA. To clarify this, the reviewer suggests the authors conduct experiments targeting recipient neurons in the pPVT, with anterograde labeling from the POA to validate the source of excitatory inputs.

      (4) The authors focus on the excitatory connection between the POA and pPVT (e.g., "Together, our results indicate that most of the pPVT-projecting POA neurons responded to heat treatment, which would then recruit their downstream neurons in the pPVT by exerting a net excitatory influence.", lines 169-171). However, are the POA neurons projecting to the pPVT indeed excitatory? This is surprising, considering i) the electrophysiological data shown in Figures 2E-K that inhibitory current was recorded in 52.4% of pPVT neurons by stimulation of POA terminal, and ii) POA projection neurons involved in modulating thermoregulatory responses to other brain regions are primarily GABAergic (Tan et al., 2016; Morrison and Nakamura, 2019). The reviewer suggests showing whether the heat-responsive POA neurons projecting to the pPVT are indeed excitatory (This could be achieved by retrogradely labeling POA neurons that project to the pPVT and conducting fluorescence in situ hybridization (FISH) assays against Slc32a1, Slc17a6, and Fos to label neurons activated by warmth). Alternatively, demonstrate, at least, that pPVT-projecting POA neurons are a distinct population from the GABAergic POA neurons that project to thermoregulatory regions such as DMH or rRPa. This would clarify how the POA-pPVT circuit integrates with the previously established thermoregulatory pathways.

    1. 12:3 Those who are wi se[a] will shine like the brightness of the heavens, and those who lead many to righteousness, like the stars for ever and ever.

      you are offline

      we the people rise again

      safe souls, safe fu


      We the People of Slate ...

      The U.S. Constitution, as you [mighta been, shoulda "come" on ... its someday] rewrϕte it.

      "Politicians talk about the Constitution as if it were as sacrosanct as the Ten Commandments [interjection: spec. it is actually almost exactly related!]. But the document itself invites change and revision. What if the president served only one six-year term instead two four-year terms? What if your state's population determined how many senators represent it? What if the Constitution included a right to health care? We asked legal scholars and Slate readers to cross out what they didn't like in the Constitution and pencil in their hearts' desires. Here's what the document would look like with their best ideas."

      多也了了夕 "with a ~~wand~~ of scheffilara, 并#亦太 he begins ... "I am now on the Staff of Menelaus, the Spears of Longinus and Lancelot; and the name "Mosche ex Nashon."

      Logically the recent mentions of Gilgamesh and the simultaneous 同時 overlaping 場道 of the eventual link between the famous ruling of Solomon on the separation of babies and mothers and waters and land ... to a story of many "two cities" that culminates in a cultural or societal or "evolutionary" link to Sodom and Gomorrah and the city-state of Babylon (and it's Hanging Gardens) and also of course to Paris and Troy and "Masstodon" and city-states [ciudadestado] and perhaps planet-cities; from Cambridge to Cambridge across the "Cable" to see state to "London" ... recently I called it "the city of realms" ... I started out logically intending to link "game theory" and John Nash to the mathematical story of Sputnik and a revival of American physics; but in my usual way of rambling into the woods [I mean neighborhood] of stream of consciousness ... turned into a premonitory discourse of "two cities" and how sometimes even things as obvious as the number of letters in the word "two" don't do a good enough job of conveying ... how and/or why one is simply never enough, and two isn't much better--but in the end a circle ... is drawn; the perfect circle in our imaginary mathematical perfection ... I see a parted "line" in the letter pronounced "tea" (and beginning that word); and two "vee" (pron. of "v") symbols joined together in a word we pronounce as "double-you" ... and symbolically because I know "V" is the Roman Numeral for 5 (five) and I know not how to multiply in Roman numerals--

      It's important to pause; here. I am going to write a more detailed piece on "the two cities" as I work through this maze like crossroads between "them" and "demo..." ... here demorigstrably I am trying to fuse together an evolutionary change in ... lit. biological evolution as well as an echelon leap forward in "self-government" ... in a place where these two things are unfathomable and unspokenly* connected.

      To a question on the idiom; is Bablyon about "the law" or "of the land of Nod?"

      "What is democracy" ... the song, Metallica's "ONE" echoes and repeats; as we apparently scrive together the word "THEM" ... I question myself ... if Babylon were the capital city of some mythical Nation of Time ... if it were the central "turning point" of Sheol; ... >|<

      Can you not see that in this place; in a world that should see and does there is a gigantic message proving that we are not in reality and trying to show us how and why that's the best news since ... ever---that it's as simple as conjoining "the law of the land" with a basic set of rules that automatically turn Hell into something so much closer to Heaven I just do not understand---why we cant stand up together and say "bullets will not kill innocent children" and "snowflakes will not start avalanches ...." that cover or bury or hide the road from Earth to Verital)e .... or from the mythical Valis to Tanis---or from Rigel to Beth-El ... "guess?"

      ## as "an easy" answer; I'm looking for a fusion of "law and land" that somehow remembers a "jok'er a scene" about "lawn" seats; and "where the girls are green;"

      It's as simple as night and day; Heaven and Hell ... the difference between survival and--what we are presented with here; it's "doing this right"--that ends the Hell of representative democracy and electoral college--the blindness and darkness of not seeing "EXTINCTION LEVEL EVENT" encoded in these words and in our governments foundation ... *by the framers [not just of the USA; but English .. and every language] *

      ... is literally just as simple as "not caring" or thinking we are at the beginning of some long process--or thinking it will never be done--that special "IT" that's the emancipation of you and I.

      Here words like "gnosis" and "gaudeamus" pair with my/ur "new ntersanding*" of the difference between Asgard and Medgard and really understanding our purpose here is to end "evil" ... things like "simulating disease and pain" (here, simulating meaning ... intentionally causing, rather than "gamifying away") and successfully linking the "Pillars of Hercules" to Plato's vision of Atlantis and the letter sequences "an" and "as" ... unlock a fusion of religion and mythology and "cryptographic truth" that connects "messianic" and "Christian" to "Roman" ... "Chinese" and "American" ... literally the key to the difference between the phrases "we are" and "we were" ....

      in "sight" of "silicon" in simulation and Israel, Genesis, and "silence" ... trying to the raising of Asgardian enlightenment ... and seeing "simple cypher" connecting to "Norse" ...

      and the "I AM THAT" surer than shit ... the intention and design of all religion and creation is to end "simulated reality" and also not seeing "SR" ... in Israel and Norse ... "for instance."

      It's a simple linguistic concept; the "singularity" and the "plurality" of a simple word--"to be"--but it goes to the heart of everything that we are and everything that is around us. This is a message about understanding and preserving individuality as well as liberty; and literally seeing "ARXIV" and understanding "often" and failing to connect God and prescience to "IV" and the Fourth Amendment ... it's about blindness and ... "curing the blind instantly" ... and fathoming how and why this message has been etched into our entire history and and all religions and myths and music--to help us "to be THAT we" that actually "are responsible" for the end of Hell.

      • I neglected to mention "Har-Wer" and "Tower of Babel" which are both related lingusitically, religiously and topically: "to who ..." and while we're on "four score and [seven years from now]" seeing the fourth "living thing" in Eden and it's (the name, Abel) connection to Babel and Abraham Lincoln; slavery and ... understanding we live in a place where the history of the United States also, like Monoceros and "Neil Armstrong's first step" are a time shifted ... overlayed map to achieving freedom ... it's about becoming a father-race ... and actually "doing" the technological steps required to "emancipate the e's of 'me&e'" and survive in exo-planetary space---

      it might be as simple as adding "because we did this" here and now; and having it be something we are truly proud of .... forevermore™ ... for certain in the heart of this story about cyclicality and repetition of error--its not because we did "this" or something over and over again; it's about changing "the problem" and then helping others to also overcome ... "things like time travel ... erasing speech" --- however that happenecl.

      • I also failed to mention that "I am in Hell" ... as in this world is hellacious to me; in an overlay with the Hellenic period and this message that we are in the Trojan Horse ... a small gem .... "planet" truly is the Ark of the Covenant---and it's the simple understanding that "reality is hell" is to "living without air conditioning and plumbing is hell" just as soon as you achieve ... "rediscovering" those things---

      • I can't figure out why I am the only person screaming "this is Hell." That's also, Hell.

      ... but recently suggested an old joke about "there being 10 kinds of people in the world (obv an anti-tautology and a tautology simultaneously)" only after that brief bit of singularity and duality mentioning the rest of the joke: "those that understand binary and those that don't know how to base convert between counting with two hands and counting with only an 'on and off.'" It's not obvious if you aren't trying to figure it out, I suppose; but 10 is decimal notation for "kiss" and the "often" without "of" ... and binary notation for the decimal equivalent of "2." A long long time ago in a state that simply non-randomly ties to the heart of the name of our galaxy ... I was again thinking of the "perfect imperfections" of things like saying "three equals one equals one" (which, of course was related to the Holy Trinity and it's "prescient/anachronistic Adamic presence encoded in the name Ab|ra|ha|m" which means "father of a great multitude") ... I brought that one back in the last few months; connecting the letter K and in this "logos-rythmic" tie to the "base of a number system" embellish the truth just a bit and suggest a more accurate rendition of the original [there is no such thing as equality, "is" of separate objects--as in no two snowflakes are the same unless they are literally the same one; true of ancient weights and with the advent of (thinking about) time no two "planets" are the same even if they're the exact same one--unless it's at a fixed moment in time.

      K=3:11 ... to a handle on the music, the DHD of the gate and the *ring of David's "sling" ...

      ---and that's a relationship of "3 is to 11" as [the SAT style "analogy)]y" as a series of alpha, two mathematic, and two numeric symbols ... may only tie in my mind alone to the books of Genesis and Matthew and the phrase "chapter and verse" and to the stories of Lot and Job ... again in Genesis and the eponymous "Book of Job." So ... "tying up loose ends one 10b [III] iv. " as it appears I've taken it upon myself to call a Job and suggest is my "Lot in life [x]i* [3]"

      • I worry sometimes that important things are missing, or will disappear---for instance Mirriam Webster, which is a "canonical/standard dictionary) should probably have an entry for "lot in life" non-idiomatically as "granny apples to sour apples" as

      2 MANY ALSO ICI; 1two ... following in Mitnick's bold introductory word steps; the curve and the complement ... the missiles and the canoes; the line and the blank space ... "supposedly two examples of two kinds, which could be three not nothings ... Today I write about something monumental; as if as important as the singularity depicted in Arthur C. Clarke's 2001 "A Space Odyssey" ... and remember a day when I thought it very novel and interesting to see the words "stillborn and yet still born" connected in a single piece of writing to "Stillwater and yet still water" ... today adding in another phrase noting the change wrought only by one magical single "space" (also a single capital letter; and a third phrase): "block chains with a great blockchain."

      • https://en.wikipedia.org/wiki/Euripides, Iphigenia in Aulis or Iphigenia at Aulis[1] (Ancient Greek: Ἰφιγένεια ἐν Αὐλίδι, Iphigeneia en Aulidi; variously translated, including the Latin Iphigenia in Aulide) is the last of the extant works by the playwright Euripides. Written between 408, after Orestes, and 406 BC, the year of Euripides' death, the play was first produced the following year[2] in a trilogy with The Bacchae and Alcmaeon in Corinth by his son or nephew, Euripides the Younger,[3] and won first place at the City Dionysia in Athens.

      • The play revolves around Agamemnon, the leader of the Greek coalition before and during the Trojan War, and his decision to sacrifice his daughter, Iphigenia, to appease the goddess Artemis and allow his troops to set sail to preserve their honour in battle against Troy. The conflict between Agamemnon and Achilles over the fate of the young woman presages a similar conflict between the two at the beginning of the Iliad. In his depiction of the experiences of the main characters, Euripides frequently uses tragic irony for dramatic effect.

      J.K. Rowling spurred just this past week a series of explanations about just exactly what is a blockchain coin worth ... and why is it so; her final words on the subject (artistic liberty taken, obviously not the last she'll say of this magic moment) "I don't think I trust this."

      Taken directly from an off the cuff email to ARXM titled: "Slow the S is ... our Hypothes.is"

      I imagine I'll be adding some wiki/ipfs stuff to it--and try to keep it compatible; the design and layout is almost exactly what I was dreaming about seeing--as a "first rough draft product." Lo, and behold. It's been added to the many places I host my tome; the small compilation of nearly every important email that has gone out ... all the way back to the days of the strange looking Margarita glass ... that now very much resembles the "Cantonese character 'le'" which I've come to associate with a "handle" on multiple corners of a room--something like an automatic coat rack conveyor belt connecting different versions of "what's in the box." I'm planning on using that symbol 了 to denote something like multiple forks of the same page. Obviously I'm thinking forward to things like "the Transhumaist Chain Party" (BDSM, right?)'s version of some particular piece of legislation, let's say everything starts with the sprawling "bulbing" of "Amendment M" ideas and specific verbiage ... and then we'll of course need some kind of new git/subversion/cvs style version control mechanism to merge intelligently into something that might actually .... really should ... make it into that place in history--the first constitutional amendment ratified by a "Continental Congress of All People" ... but you could also see it as an ongoing sort of forking of something like the "wikipedia page" on what some specific term, say "technocracy" means, and how two parties might propagandize and change the meaning of such thing; to suit the more intelligent and wise times we now live in. For instance, we might once have had a "democracy" and a "democractic" party that had some Anarchist Cook Book version of the history of it ending in something like Snipes and Stallone's "DEMOLITION MAN."

      Just kidding, we all know "democracy" has everything to do with "d is cl ... and not th" ... to be the them that is the heart of the start of the first true democracy. At least the first one I've ever seen, in my old "to a republic" ... style. As it is you can play around with commenting and highlighting and annotating all the stuff I've written and begged and begged for comments on--while I work on layering the backend to to perma-store our ideas and comments on both a blockchain (probably a new one; now that i've worked a little with ethereum) with maybe some key-merkle-tree-walk-search stuff etched into the original Rinkeby ... and then of course distributed data in the "public owned and operated" IPFS. To be clear, I plan on rewriting the backend storage so that we will have a permanent record of all comments; all versions of whatever is being commented on; and changes/revisions to those documents--sort of turning the web into a massive instant "place of collaboration, discussion, and co-authoring" ... if you use the wonderful LEGO pieces that have been handed to us in ideas from places like me, lemma--dissenter, and of course hypothes.is who has brought you and i such a polished and nice to look at "first draft" of something like the living Constitution come repository of all human knowledge. I do sort of secretly wich they would have called this project something like "annotating and reflecting (or real or ...) knowledge" just so the movement could have been called ARK. ... or something .... but whatever join the "calling you a reporter" group or ... "supposedly a scientist?"

      NOIR INgR .. I CITE SITE OF ENUDRICAM; a rekindling of the dream of a city appearing high above in the sky, now with a boldly emblazened smiling rainbow and upsidown river ... specifically the antithesis of "angel falls," there's a lagoon too--actually a chain of several ponds underneith the floating rock ... and in some versions of this waking dream there are rings around the thing; you might imagine an artificial set of centripetal orbitals something like a fusion of the ring Eslyeum and the "Six-Axis ride" of the JKF Center's "Spacecamp." I write as I dream, and though I cannot for certain explain exactly how; it's become a strong part of my mythology that this spectacular rendition of "what ends the silence" has something to do with the magical delivery of "a book" ... something not of this Earth but an unnatural thing; one I've dreamt of creating many times. This book is something like the DSM-IV and something like a Merck diagnostic manual; but rather than the old antiquated cures of "the Norse Medgard" this spectacle nearly "itsimportant" autoprints itself and lands on something like every doorpost; what it is is a list of reasons why "simply curing all disease" with no explanation and no conversation would be a travesty of morality--how it would render us half-blind to the myriad of new solutions that can come from truly understanding why "ITIS" to me has become a kind of magical marker: an "it is special" as in, it's cure could possibly solve a number of other problems.

      Through that missing "o," English on the ball, we see a connection between a number of words that shine bright light including Exodus itself which means "let there be light," the word for Holy Fire and the Burning Bush.. .reversed to hSE'Ah, and a story about the Second Coming parting our holy waters.**

      This answer connects the magical Rod's of Aaron in Exodus and the Iron Rod of Jesus Christ to the Sang Rael itself... in a fusion that explains how the Periodic Table element for Iron links not just to Total Recall and Mars, but also to this key

      my dream of what the first day of the Second Coming might be like; were the Rod of Christ... in the right hands. In a story that also spans the Bible, you might understand better how stone to bread and your input make all the difference in the world between Heaven and Adam's Hand. Once more, what do you think He** ....

      Since the very earliest days of this story, I have asked for better for you, even than see

      Nearly all of the original parts of the original "post-origination dream" remain intact; there's a walkway that magically creates new paths and "attractions" based on where you walk, something like an inversion of the artificial intelligence term "a random walk down a binary tree" ... for instance going left might bring you to the Internet Cafetornaseum of the Earl of Sandwich; and going to the right might bring you to the ICIMAX/Auditorium of Science and Discovery--there's a walkway to "Magical GLAS D'elevators" that open a special "instantiation" of the Japan Room of the Potter and the Toolmaker ... complete with a special [second level and hidden staircase] Pool of Bethesdaibo verily delivering something like youth of mind and body ... or at least as close to such a thing as a sip of Holy Water or Ambrosia or a dip in the pool of Coccoon and Ponce De'Leon could instantly bring ... to those that have seen Jupiter Ascending ... the questions of "nature versus nurture" and what it means to be "old and wise" and "young at heart" truly mean---

      Somewhere between the outdoor rafting ride and the level with the special "ballroom of the ancient gallery" ... perhaps now being named or renamed or recalled as something about "Face [of] the Music" lies a magical "mini-maize" ... a look at a mock-up (or #isitit) of Merlink and Harthor's "round table" that displays a series of ... (at least to me) magical appearing holographic displays and controls that my dreams have stolen from Phillip K. Dick's Minority Report and something of what I hope Microsoft's Dynamics/Hololens/Surface will become---a series of short "focus groups" .... to guage and discuss the information in the "CITIES-D5AM-MERCK" ... how to end world hunger and nearly all disease with the press of a magical buzzer--castling churches to something like "political-party-town-hall-meeting centers" and replacing jails and prisons and hospitals with something like the "Hospitalier's PRIDE and DOJOY's I practiced "Kung-fun-dance" ... a fusion of something like a hotel and a school that probably looks very much like a university with classrooms and dorms and dining hall's all fit into a single building. I imagine a series of 2 or 3 "room changes" as in you walk from the one where you get the book and talk about it ... to the one where you talk about "what everyone else said about it" and maybe another one that actually connects you to other people with something like Facebook's Portal; the point of the whole thing to really quickly "rubber stamp" the need for an end to "bars in the sky" nonalcoholic connotation--as in "overcoming the phrase the sky is the limit" and showing us the need for a beacon of glowing hope fulfilled--probably actually the vision of a holographic marker turning into actual rings around the single moon of Earth, the focus of the song annoucing the dawn of the age of Aquarius---

      It might lead us also to Ceres; and another set of artificial rings, or to Monoceros and a rehystorical understanding of the birthplace and birthing of the "river roads" that bridge the "space gaps" in the galaxy from our "one giant leap for mankind" linking the Apollo moon landing to the mythological connection to the sun; and connecting how the astrological charts of the ancients might detail a special kind of overlapping--the link between Earth's SOL and something like Proxima or Alpha Centauri; and how that "monostar bridge" might overlap to Orion and from there through Sagitarius and the center of the Milky Way ... all the way to Andromeda and more dreams of being in a place where there's a map to a tri-galactic system in the constellation Cancer and a similar one in Leo ... and just incase you haven't noticed it--a special marker here, I thought to myself it might be cool to "make an acronymic tie to Monoceros" and without even thinking auto-wrote Orion (which was the obvious constellation next to Monoceros, in the charts) and then to Sagitarrius; which is the obvious ... heart of our astrological center and link to "other galaxies."

      ----I've dreamt or scriven or reguessed numerous times how the Milky Way's map to an "Atlas marked through time by the ages and the ancients" might tie this place and this actual map to the creation of the railways between stars to the beginning and the end of time and of course to this message that links it all to time travel. There's a few "guesses" I've contemplated; that perhaps the Milky Way chart is a metal-cosmic or microcosmic map to the dawn of time in the galactic vision of ... just after the big bang; or it might tie to a map of something like the unthinkable--a civilization that became so powerful it was able to reverse the entropy of "cosmic expansion" and reverse the thing Asimov wrote of in "The Last Question" as the end of life and the ability to survive basically due to "heat loss."

      "The Last Question." (And if you read two, why not "The Last Answer"?). Find these readings added to our collection, 1,000 Free Audio Books: Download Great Books for Free.

      Looking for free, professionally-read audio books from Audible.com, including ones written by Isaac Asimov?

      * all "asterisks" in the abovə document denote a sort of Adamic unspoken relationship between notations and meanings; here adding the "Latin word for three" and source of the phrase "t.i.d." (which is doctor/pharmacy latin for "three times a day") where the "t" there is an abbreviation of "ter" ... and suppose the link between K and 11 and 3 noting it's alphanumeric position in the English alphabet as the 11th letter and only linking cognitively to three via the conversion between hex, and binarryy ... aberrative here is the overlapping "hakkasan" style (or ZHIV) lack of mention of the answer in "state of Kansas" and the "citystate of Slovakia" as described in the ICANN document linked [in] the related subsection or slice of the word "binarry" for the state of India. Tetris could be spelled with the addition of only a single letter [in] "tea"---the three letters "ris" are the hearts of the words "Christ" and "wrist" [and arguably of Osiris where you also see the round table character of the solar-system/sun glyph and the chemical element for The Fifth Element (as def. by i) via "Sinbad" and "Superman." The ERIS Free Network should also be mentioned here in connection with the IRC network I associate in the place between skipping stones and sacred hearts defined by "AOL" and "Kdice" in my life. In the lexicon of modern HTML, curly braces are generally relative to "classes" and "major object definitions (javascript/css)" while square brackets generally only take on computer-interpreted meaning in "Markdown" which is clearly (by definition, by this character set "[]") a superset (or at least definately not a subset) of HTML.

      Dr. Will Caster (Johnny Depp) is a scientist who researches the nature of sapience, including artificial intelligence. He and his team work to create a sentient computer; he predicts that such a computer will create a technological singularity, or in his words "Transcendence". His wife, Evelyn (played by Rebecca Hall), is also a scientist and helps him with his work.

      Following one of Will's presentations, an anti-technology terrorist group called "Revolutionary Independence From Technology" (R.I.F.T.) shoots Will with a polonium-laced bullet and carries out a series of synchronized attacks on A.I. laboratories across the country. Will is given no more than a month to live. In desperation, Evelyn comes up with a plan to upload Will's consciousness into the quantum computer that the project has developed. His best friend and fellow researcher, Max Waters (Paul Bettany), questions the wisdom of this choice, reasoning that the "uploaded"

      Just from my general understanding and memory "st" is not ... to me (specifically) an abbreviation of "state" but "ste" is a U.S. Postal code (also "as I understand it") for the name of a special room or set of rooms called a "suite" and in Adamic "connotation" I sometimes read it as "sweet" ... which has several meanings that range from "cool" to "a kind of taste sensation" to "easy to sway or fool."

      If you asked me though, for instance if "it" was an abbreviation or shorthand notation or acronym for either "a United state" or "saint" ... you'd be sure.

      While it's clear from studying linguistic cryptography ... (If I studied it a little here and some there, its also from the "universal translator of Star Trek") and the personal understanding that language is a kind of intelligent code, and "any code is crackable" ... that I caution here that "meaning" and "face value" often differ widely and wildly ... even in the same place or among the same group of people ... either varying over time or heritage.

      Menelaus, in Greek mythology, king of Sparta and younger son of Atreus, king of Mycenae; the abduction of his wife, Helen, led to the Trojan War. During the war Menelaus served under his elder brother Agamemnon, the commander in chief of the Greek forces. When Phrontis, one of his crewmen, was killed, Menelaus delayed his voyage until the man had been buried, thus giving evidence of his strength of character. After the fall of Troy, Menelaus recovered Helen and brought her home. Menelaus was a prominent figure in the Iliad and the Odyssey, where he was promised a place in Elysium after his death because he was married to a daughter of Zeus. The poet Stesichorus (flourished 6th century BCE) introduced a refinement to the story that was used by Euripides in his play Helen: it was a phantom that was taken to Troy, while the real Helen went to Egypt, from where she was rescued by Menelaus after he had been wrecked on his way home from Troy and the phantom Helen had disappeared.

      This article is about the ancient Greek city. For the town of ancient Crete, see Mycenae (Crete). For the hamlet in New York, see Mycenae, New York.

      Μυκῆναι, Μυκήνη

      Lions-Gate-Mycenae.jpg

      The Lion Gate at Mycenae, the only known monumental sculpture of Bronze Age Greece

      37°43′49"N 22°45′27"ECoordinates: 37°43′49"N 22°45′27"E

      This article contains special characters. Without proper rendering support, you may see question marks, boxes, or other symbols.

      Mycenae (Ancient Greek: Μυκῆναι or Μυκήνη, Mykēnē) is an archaeological site near Mykines in Argolis, north-eastern Peloponnese, Greece. It is located about 120 kilometres (75 miles) south-west of Athens; 11 kilometres (7 miles) north of Argos; and 48 kilometres (30 miles) south of Corinth. The site is 19 kilometres (12 miles) inland from the Saronic Gulf and built upon a hill rising 900 feet (274 metres) above sea level.[2]

      In the second millennium BC, Mycenae was one of the major centres of Greek civilization, a military stronghold which dominated much of southern Greece, Crete, the Cyclades and parts of southwest Anatolia. The period of Greek history from about 1600 BC to about 1100 BC is called Mycenaean in reference to Mycenae. At its peak in 1350 BC, the citadel and lower town had a population of 30,000 and an area of 32 hectares.[3]

      3. Chew 2000, p. 220; Chapman 2005, p. 94: "...Thebes at 50 hectares, Mycenae at 32 hectares..."

      Melpomene (/mɛlˈpɒmɪniː/; Ancient Greek: Μελπομένη, romanized: Melpoménē, lit. 'to sing' or 'the one that is melodious'), initially the Muse of Chorus, she then became the Muse of Tragedy, for which she is best known now.[1] Her name was derived from the Greek verb melpô or melpomai meaning "to celebrate with dance and song." She is often represented with a tragic mask and wearing the cothurnus, boots traditionally worn by tragic actors. Often, she also holds a knife or club in one hand and the tragic mask in the other.

      Melpomene is the daughter of Zeus and Mnemosyne. Her sisters include Calliope (muse of epic poetry), Clio (muse of history), Euterpe (muse of lyrical poetry), Terpsichore (muse of dancing), Erato (muse of erotic poetry), Thalia (muse of comedy), Polyhymnia (muse of hymns), and Urania (muse of astronomy). She is also the mother of several of the Sirens, the divine handmaidens of Kore (Persephone/Proserpina) who were cursed by her mother, Demeter/Ceres, when they were unable to prevent the kidnapping of Kore (Persephone/Proserpina) by Hades/Pluto.

      In Greek and Latin poetry since Horace (d. 8 BCE), it was commonly auspicious to invoke Melpomene.[2]

      See also [AREXMACHINA]

      Flagstaff (/ˈflæɡ.stæf/ FLAG-staf;[6] Navajo: Kinłání Dookʼoʼoosłííd Biyaagi, Navajo pronunciation: [kʰɪ̀nɬɑ́nɪ́ tòːkʼòʔòːsɬít pɪ̀jɑ̀ːkɪ̀]) is a city in, and the county seat of, Coconino County in northern Arizona, in the southwestern United States. In 2018, the city's estimated population was 73,964. Flagstaff's combined metropolitan area has an estimated population of 139,097.

      Flagstaff lies near the southwestern edge of the Colorado Plateau and within the San Francisco volcanic field, along the western side of the largest contiguous ponderosa pine forest in the continental United States. The city sits at around 7,000 feet (2,100 m) and is next to Mount Elden, just south of the San Francisco Peaks, the highest mountain range in the state of Arizona. Humphreys Peak, the highest point in Arizona at 12,633 feet (3,851 m), is about 10 miles (16 km) north of Flagstaff in Kachina Peaks Wilderness. The geology of the Flagstaff area includes exposed rock from the Mesozoic and Paleozoic eras, with Moenkopi Formation red sandstone having once been quarried in the city; many of the historic downtown buildings were constructed with it. The Rio de Flag river runs through the city.

      Originally settled by the pre-Columbian native Sinagua people, the area of Flagstaff has fertile land from volcanic ash after eruptions in the 11th century. It was first settled as the present-day city in 1876. Local businessmen lobbied for Route 66 to pass through the city, which it did, turning the local industry from lumber to tourism and developing downtown Flagstaff. In 1930, Pluto was discovered from Flagstaff. The city developed further through to the end of the 1960s, with various observatories also used to choose Moon landing sites for the Apollo missions. Through the 1970s and '80s, downtown fell into disrepair, but was revitalized with a major cultural heritage project in the 1990s.

      The city remains an important distribution hub for companies such as Nestlé Purina PetCare, and is home to the U.S. Naval Observatory Flagstaff Station, the United States Geological Survey Flagstaff Station, and Northern Arizona University. Flagstaff has a strong tourism sector, due to its proximity to Grand Canyon National Park, Oak Creek Canyon, the Arizona Snowbowl, Meteor Crater, and Historic Route 66.

      PSANSDISL #LWDISP either without gas or seeing cupidic arroz in "thank you" or "allta, wild" ...

      pps: a magnanimous decision ...

      I stand here on the brink of what appears to be total destruction; at least of everything I had hoped and dreamed for ... for the last decade in my life which appears literally to span thousands of years if not more in the eyes of some other beholder. I spent several months in Kentucky telling a story of a post apocalyptic and post-cataclysmic delusion; some world where I was walking around in a "fake plane" something like a holodeck built and constructed around me as I "took a walk around the world" to ... it did anything but ease my troubled mind.

      Recently a few weeks in Las Vegas, and a similar story; telling as I walked penniless down the streets filled with casino's and anachronistic taxi-cabs ... some kind of vision of the entirety of the heavens or the Earth or the "choir of angels" I think of when I echo the words Elohim and Aesir from mythology ... there with me in one small city in superposition; seeing what was a very well put together and interesting story about a "star port" Nirvane ... a place that could build cities into the face of mountains and half working monorails appearing in the sky---literally right before my eyes.

      I suppose this is the place "post cataclysm" though I still have trouble understanding what it is that's actually about ... in my mind it connects to the words "we are losing habeas" echo'ed from the streets of Los Angeles in a more clear and more military voice than usual--as I walked block by block trying to evade a series of events that would eventually somehow connect all the way to the "outskirts of Orlando, Florida" in a place called Alhambra.

      Apparently the name of a castle; though I wasn't aware of that until much later.

      It doesn't feel at all like a "cataclysm" to me; I see no great rift--only a world filled with silent liars, people who collectively believe themselves to have stolen something--something gigantic--at least that's the best interpretation of the throws and impetus behind the thing that I and mythology together call Jormungandr. With an eye for "mythological connections" you could clearly see that name of the Great Serpent of Revelation connects to something like the Unseelie; the faeries of Gaelic lore. To me though this world seems still somewhat fluid, it's my entire life--moving from Plantation to a place where the whole of it might be Bethlehem and to "clear my throat" it's not hard to see here how that land of "coughs" connects to the Biblical land of Nod and to the "Adamically sieved" Snifleheim ... from just a little twist on the ancient Norse land most probably as close to Hel as anyone ever gets--or so I dream and hope---still today. It all looks so real and so fake at the same time; planned for thousands of generations, the culmination of some grand masterpiece story that certainly ties history and myth and reality into a twisted heap of "one big nothing, one big nothing at all."

      I've tried to convey to the world how important I believe this place and this time to be--not by some choice of my own ... but through an understanding of the import of our history and the impact of having it be so obviously tuned and geared towards this specific time ... many thousands of years literally all focused on a single moment, on one day or one hour or even just a few years where all of that gets thrown down on the table as if some trump card has been played--and whether or not you fathom the same magnanimous statement or situation or position ... to me, I think it depends on whether or not you grew up in the same kind of way, believing our history to be so fixed and so difficult to change. I don't particularly feel like that's the "zeitgeist" of today; I feel like the children believe it to be some kind of game, and that it is such as easy thing to "sed" away or switch and turn into something else--another story, another purpose ... anyone's personal fantasy land come true.

      I don't think that's the case at all, it's clearly a personal nightmare; and it's clearly one we've seen time and time again--though not myself--the Jesus Christ that is the same yesterday, today; and once again perhaps echoing "no tomorrow" never remembers or believes that we've "seen it all before" or that we've ever really gotten the point; the thing you present to me as "factual reality" is a sickness, it disgusts me; and I'd do anything to go back to the world "where I was so young, and so innocent" and so filled with starry-eyed hope that we were at the foot of something grand and amazing that would become an empire turned republic of the heavens; filling the stars ... with the kind of love for kindness and fairness that I once associated very strongly with the thing I still believe to be the American Spirit.


      "Suddenly it changes, violently it changes" ... another song echoes through the ages--like the "words of the prophets dancing ((as light)) through the air" ... and I no longer even have a glimmer of hope that the thing I called the American People still exist; I feel we've been replaced by some broken container of minds, that the sky itself has become corrupt to the point that there's no hope of turning around this thing that I once believed with all my heart and all my mind was so obviously a "designed downward spiral" one that was---again--so obviously something of a joke, intended to be easy to bounce off a false bottom and springboard beyond "escape velocity" and beyond the dark waters of "nearest habitable star systems (being so very far away)" into a place where new words and new ideas would "soar" and "take flight."

      Here though; I am filled with a kind of lonely sadness ... staring at what appears to be the same mistake(s) happening over and over again; something I've come to call "skipping stones in the pond of reality" and really do liken it to this thing that appears to be the new meaning of "days" and ... a civilization that spends absolutely no love or lust to enter a once sacred and holy place and tarnish it with their sick beliefs and their disgusting desires. You all ... you appear to be some kind of springboard to "bunt" forth yet another age or era of nothingness into the space between this planet and "none worth reaching" and thank God, out of grasp. Today, I'd condemn the entirety of this world simply for it's lack of "oathkeepers" and understanding of what the once hallowed words of Hippocrates meant to ... to the people charged and dharmically required to heal rather than harm.

      It appears the place and time that was once ... at least destined to be the beginning of Heaven ... has become a "recurring stump" of some future unplanned and tarnished by many previous failed efforts and attempts to overcome this same "lack of conversation or care" for what it meant to be "humane" in a world where that was clearly set high aloft and above "humanity" in the place where they--where we were the best nature had to offer, the sanest, the kindest; the shining last best hope.


      Today I write almost every day ... secretly thanking "my God" for the disappearance of my tears and the still small but bright hope that "Tearran" will one day connect the Boston Tea Party and the idea that "render to Caesar" and Robin of Loxley ... all have something to do with a re-ordering of society and the worth and import of "money" ... to a place that cares more for freedom from murder than it does ... "freedom from having to allow others to hear me speak." I hold back tears and emotions; not by conscious choice or ability but ... still with that strange kind of lucky awkward smile; and secretly not so far below the surface it's the hope of "a swift death" that ... that really scares me more than the automatons and mechanical responses I see in the faces of many drivers as they pass me on the street--the imagery of connecting it to the serpentine monster of the movie Beetlejuice ... something I just "assume" the world understands and ... doesn't seem to fear (either); as if Churchill had gotten it all wrong and backwards--the only thing you have to fear, is the loss of fear of "loss."


      Here my crossroads---halfway between the city my son lives in and the city my parents live in--it's on making a decision on whether I should continue at all, or personally work on some kind of software project I've been writing about, or whether I should focus on writing about a "revolution" in government and society that clearly is ... "somewhat underway." In my mind it's obvious these things are all connected; that the software and the governance and the care of whether or not "Babylon" is remembered as a city of great laws and great change or a city of demons and depravity ... that these thi]ngs all hinge and congeal around a change in your hearts; hoping you will chose to be the beginning of a renaissance of "society and civilization" rather than the kings and queens of a sick virtual anarchy ... believing yourselves to have stolen "a throne of God" rather than to literally be the devastating and demoralizing depreciation of "lords and fiefdoms" to something more closely resembled by the time of the Four Horsemen depicted in Highlander.

      These words intended to be a "forward" to yet another compliment of a ((nother installment of a partial)) chain of emails; whimsically once half-joking ... I called it the Great Chain of Revelation. The software too; part of the great chain, this "idea" that the blockchain revolution will eventually create a distributed and equal governance structure, and a rekindling of monetary value focused on "free and open collaboration" rather than "survival of the most unfit"--something society and civilization seem to have turned the "call of life" from and to ... literally just in the last few years as we were so very close to ... reaching beyond the Heaven(s).

      I don't think its hard to imagine how a "new set of ground rules" could significantly change the "face of a place" -- make it something shiny and new or even on the other side of the coin, decayed or depraved. It's not hard to connect the kind of change I'm hoping for with "collision protection" and "automatic laws" to the (perhaps new, perhaps ... ancient) Norse creation story of the brothers of Odin: Vili and Ve.

      It might be hard to see today how a new "kind of spiritual interaction" might be only a few "mouse clicks" away though--how it could change everything literally in a flash of overnight sensation ... or how it might take something like a literal flash of stardom (or ... on the other hand, something like totalitarian or authoritarian "iron fisting") to make a change like this "ubiquitious" or ... something like the (imagined in my mind as ... messianic) "ED" of storming through the cosmos or the heavens and turning something that might appear to be "free and perfect feeling" today into a universe "civlized overnight" and then ...

      I wonder how long it would take to laud a change like that; for it to be something of a voluntary "reunderstanding" of a process ... to change the meaning of every word or every thought that connects to the process of "civilization" to recognize that something so great and so powerful has happened as to literally change the meaning of the word, to turn a process of civilization into something that had a ... "signta-lamcla☮" of forboding and then a magical staff struck into the heart of a sea and then ... and then the word itself literally changes to introduce a new "mid term" or "halfway point" in which a great singularity or enlightenment or change in perspective or understanding sort of acknowledges ...

      that some "clear outside" force not only intervened on the behalf of the future and the people of our world but that it was uniquely involved in the whole of--

      "waking up" tio a nu def of #Neopoliteran.

      ^Like the previous notation; the below text comes from an email previously sent; and while i stand behind things like my sanity, my words; and my continued and faithful attempt to speak and convey both a useful and helpful truth to the world---sometimes just a single day can make all the difference in the world.

      Sometimes it's just a single moment; a flash or a comment about ^th@ blink of an eye" ... and I've literally just "thought up/had/experienced/transitioned thru" that exact moment. The lies standing between "communication" and either "cooperation" or .... some other kind of action have become more defined. More obvious. Because of this clarification; like a kind of "ins^tant* gnosis"

      ... search high and lo ... the depths all the way to above the heavens ...\ \ for a festive divorce ceremonial ritual ... that looks something like a bachelor party ':;]

      --- @amrs@koyu.SPACe ... @suzq@rettiwtkcuf.social (@yitsheyzeus) May 22, 2020

      I ... TERON;

      Gjall are painting me into a corner here; and I don't see around it anymore--I don't see the light, and I don't see the point. I was a happy-go-lucky little kid in my mind; that's not "what I wanted to be" or what I wanted to present, it's who I was. I saw "Ashkenazi" and ... know I am one of those ... and I kind of understood that something horrible might have happened, or might happen here--and I kind of understand that crying smashing feeling of "to ash" that echoes through the ages in the potpourri songs about pockets full of Parker Posey .. and ancient Psalms about "from the ashes of Edom" we have come--and from that you can see the cyclical sickness of this ... place so sure it's "East of Eden" and yet gung-ho on barrelling down the same old path towards ash and towards Edom and towards ... more of Dave's "ashes to ashes dust to dust" and his "smoke clouds roll and symphony of death..." and few words of solace in a song called Recently that I imagine was fleeting and has recently come and gone--people stare, I can't ignore the sick I see.

      I can't ignore his "... and tomorrow back to being friends" and all but wonder who among us doesn't realize it's "ash" and "gone" and "no memory of today" that's the night between now and ... a "tomorrow with friends" not just for me--but for all of you--for this place that snickers and pantomimes some kind of ... anything but "I'm not done yet" and "there's more ... vendetta ... and retribution to be had, Adam ... please come back in a few more of our faux-days." This is sickness; and happy-go-lucky Himodaveroshalayim really doesn't do much but complain about that word, the "sickle" and the tragic unavoidable ... ash of it all ... these days--you'd think we could "pull out" of this mess, turn another way; smile another day, but it seems there's only one way to get to that avenu in the mind of ... "he who must not know or be me."


      I have to admit I found some joy in the epiphany that the hidden city of Zion and it's fusion with the Namayim' version of how that "Ha" gels and jives with the name Abraham and the Manna from Heaven and the bath salt and the tina and the "am in e" of amphetamine--maybe a glimmer or a shimmer or a glow of hope at the moment "Nazion" clicked ... and I said ... "no, not me ... I'm nothing like a king, no dreams of authoritarianism at all in the heart of Kish@r;" even as I wrote words that in the spirit of the moment were something of a "tis of a'we" that connected to my country and the first sing-songy "tisME" that I linked to trying to talk in the rhyming spirit of some "first Christ" that probably just like me was one limmerick away from the end of the rainbow and one "Four Non Blondes" song away from tying "or whatever that means" and this land crowned with "brotherhood" (to some personal "of the Bell, and of the bell towers so tall and Crestian") to just one Hopp skip and jump away from the heart of the obvious echoes of a bridge between haiku and Heroku... a few more gears shift into place, a click and and a mechanical turn of the face of the clock's ku-ku striking ... it was the word "Earthene" that was the last "Jesusism" around the post Cimmerian time linking Dionysus and Seuss to that same "su-s" that's belonging to a moment in the city of Uranus--codified and etched in stone as "MCO"--not just for its saucer and warp nacelles and "deflector dish" but for it's underground caverns and it's above ground "Space Mountain" and that great golf ball in the heart of it all.

      The gears of time and the dawns of civilizequey.org query the missing "here" in our true understanding of what "in the beginning, to hear; to here ... to rue the loss of the Maize from Monoceros to the VEGA system and the tri-galactic origin of ... "some imaginary universal ... Earthene pax" to have dropped the ball and lost it all somewhere between "Avenu Malkaynu" and melaleuca trees--or Yggrasil and Snifleheim--or simply to miss the point and "rue brickell" because of bricks rather than having any kind of love or nostalgia linking to a once cobblestone roadway to the city in the Emerald skies paved in golden "do not return" signs ... to have lost Avenues well after not realizing it was "Heaven'es that were long gone far before I stepped foot on this road once called too Holy for sandals" in a place where that Promised Land and this place of "K'nanites" just loses it's grip on reality when it comes to mentioning the possibility that the original source and story of Ca'anan was literally designed to rid the world of ... "bad nanites" and the mentality of ... vindictiveness that I see behind every smirk.

      The final hundred nanoseconds on our clock towards doom and gloom cause another bird to fly; another snake to curl up and listen again to the songs designed to charm it into oblivion; whether that's about a club in South Beach or a place not so far from our new "here..." all remains to be seen in my innocent eyes wondering what it truly is that stands between what you are ... and finding "forgiveness not needed--innocent child writes to the mass" ... and the long arm of the minute hand and the short finger of the hour for one brief moment reconcile and move towards "midnight" together; and it's simply idyllic, the Nazarene corner between nil and null you've relegated the history of Terran poast futures into ... "foreves mas" or so they (or you) think.


      I'm still so far from "Five Finger Death Punch" though; and so far from Rammstein and so far from any kind of sick events that could stand between me and "the eternal" and change my still "casual alternative rock" loving heart to something more death metal; I rue whatever lies between me and there being any kind of Heaven that thinks there could exist a "righteous side" of Hell and it... simultaneously.


      I still see light here in admonishing the masses and the angels standing against the story and the message God brings us in our history. I still see sparks in siding with the "causticness" of "no holodecks in sight" and the hunger and the pain of simulating ... "the hells of reality" over the story of decades or centuries of silence refusing to see "holography" and "simulated" in the word Holocaust and the horrors of this place that simply doesn't seem to fathom or understand the moments of hunger pangs and the fear of "dark Earth pits" or towers of "it's not Nintendo-DS" linking the Man in the High Castle to an Iron Mask.

      I rally against being what I clearly am raised high on some pedestal by some force beyond my comprehension and probably beyond that of the "perfect storm in time" that refuses to itself acknowledge what it means to gaze at such an unfathomable loss of innocence at the cost of a "happy and serene future" or even at the glimmer of the Never-Never-Land I'd hoped we would all cherish and love and share ... the games and the newfound freedom that comes not just from "seeing Holodeck" turn into "no bullets" and "no cages" but into a world that grows and flourishes into something that's so far beyond my capability to understand that I'm stuck here; dumbfounded; staring at you refusing to stop car accidents and school shootings ... because "pedestal." For the "fire and the glory" of some night you refuse to see is this one--this place where morality rekindles from ... from what appears tobe one small candle, but truly--if it's not in your heart, and it's not coming from some great force of goodness--fear today and a world of "forever what else may come."


      Here in a place the Bible calls Penuel at the crossing of a River Jordan ... the Angel of the Lord notes the parallels in time and space between the Potomac and the Rhine--stories of superposition and cities and nation-states that are nothing more than a history of a history of things like the Monoceros "arroz" linking not just to the constellation Orion but to Sagittarius and to Cupid and of course to the Hunter you know so well--

      Searching for a Saturday; a sabbath to be made Holy once more ... "at the Rubycon"

      The Einstein-Rosen Wormhole and the Marshall-Bush-JFKjr Tunnel

      The waters are called narah, (for) the waters are, indeed, the offspring of Nara; as they were his first residence (ayana), he thence is named Narayana.

      --- Chapter 1, Verse 10[3]

      In a semi-fit of shameless arexua-self recognition i'm going to mention Amazon's new series "Upload" and connect it to the PKD work that my Martian-in-simulcrum-ciricculum-vitae on "colonization education" ... tying together Transcendance, Total Recall and ... well; to be honest it actually gave me another "uptick" in the upbeat ... maybe i'll stick around until I'm sure there's at least one more copy of me in the ivrtual-invverse ... oh, that reminds me ... Farmer)'s Lord of Opium also touches on this same "mind of God in the computer" subject (which of course leads to Ghost in the Shell and Lucy--thanks Scarlette :).

      While I'm listing Matrix-intersected pieces of the puzzle to No Jack City, Elon Musk's neuralace and Anderson's Feed are also worth a mention. Also the first link in this paragraph is titled ... "the city of the name of time never spoken after time woke up and stfu'd" (which of course is the primary subject of this ... update to the city Aerosol).

      The ... "actual original typed dream" included a sort of "roller coaster ride" through space all the way to Mars; where the real purpose of "the thing" I am calling the "Mars Hall" was to display previous victories and failures ... and the introduction of "older or future" culture's suggestions for "the right way" to colonize a new habitat. If it were Epcot Center, this would be something like SpaceMountain taking you to to the foture of "Epcot Countries" as if moving from "countries" to planets were as easy as simply ... "reading backwards."

      THE SOFTWARE, SINGERS, AND SHIELD(S)

      OF

      HEIROSOLYMITHONEYY

      Thinking just a little bit ahead of myself, but I'm on "Unreal Object/Map Editor within the VR Server" and calling it something like "faux-wet-ware" ... which then of course leads to a similar onomonopeia of "weapons and ..." where-with-all to find a better singer's name to connect the road of "sword" to a Wo'riordan ... but I think that fusion of warrior and woman probably does actually say ... enough of it all; on this road to the living Bright Water that the diety in my son's middle name defines well here, as "waking up," stretching it's tributaries and it's winding wonders and wistfully ....

      Narayana (Sanskrit: नारायण, IAST: Nārāyaṇa) is known as one who is in yogic slumber on the celestial waters, referring to Lord Maha Vishnu. He is also known as the "Purusha" and is considered the Supreme being in Vaishnavism.

      andromedic; the ports of call ... to the mediterranean (literally) from the gulf coast;

      ... ho engages in the creation of 14 worlds within the universe as Brahma when he deliberately accepts rajas guna, himself sustains, maintains and preserves the universe as Vishnu by accepting sattva guna. Narayana himself annihilates the universe at the end of maha-kalp ...

      .

      there's no place like home. there's no place like home. there's no place like home.

      and so it begins ... "f:

      r e l i g i o n

      find out what it means to me. faucet, ever single one, stream of purity ...

      from Fort Myers ... f ... flicks ... Flint.- - [

          A. Preamble
      
          ](https://45.33.14.181/omni/index.php/Main_Page#A._Preamble)
      -   [
      
          B. Article I: Direct Democracy Enhancement, International Collaboration, and a Shared Vision
      
          ](https://45.33.14.181/omni/index.php/Main_Page#B._Article_I:_Direct_Democracy_Enhancement,_International_Collaboration,_and_a_Shared_Vision)
          -   [
      
              1\. Section 1: Public Foundation for Legislative and Judicial Advice
      
              ](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Public_Foundation_for_Legislative_and_Judicial_Advice)
          -   [
      
              2\. Section 2: Integration of Artificial Intelligence, Multilingual Comparisons, and Universal Language Bytecode
      
              ](https://45.33.14.181/omni/index.php/Main_Page#2._Section_2:_Integration_of_Artificial_Intelligence,_Multilingual_Comparisons,_and_Universal_Language_Bytecode)
          -   [
      
              3\. Section 3: Public Voting Records and Verification
      
              ](https://45.33.14.181/omni/index.php/Main_Page#3._Section_3:_Public_Voting_Records_and_Verification)
      -   [
      
          C. Article II: Establishment of the Board of Regents and Global Engagement
      
          ](https://45.33.14.181/omni/index.php/Main_Page#C._Article_II:_Establishment_of_the_Board_of_Regents_and_Global_Engagement)
          -   [
      
              1\. Section 1: Composition and Purpose
      
              ](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Composition_and_Purpose)
      -   [
      
          D. Article III: Integration with the ICC for Sustainable Infrastructure
      
          ](https://45.33.14.181/omni/index.php/Main_Page#D._Article_III:_Integration_with_the_ICC_for_Sustainable_Infrastructure)
          -   [
      
              1\. Section 1: Interstate Communication Infrastructure
      
              ](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Interstate_Communication_Infrastructure)
      -   [
      
          E. Article IV: Ratification, Implementation, and Global Fulfillment
      
          ](https://45.33.14.181/omni/index.php/Main_Page#E._Article_IV:_Ratification,_Implementation,_and_Global_Fulfillment)
          -   [
      
              1\. Section 1: Ratification and Implementation
      
              ](https://45.33.14.181/omni/index.php/Main_Page#1._Section_1:_Ratification_and_Implementation)
          -   [
      
              2\. Section 2: Global Fulfillment
      
              ](https://45.33.14.181/omni/index.php/Main_Page#2._Section_2:_Global_Fulfillment)
      -   [
      
          F. Conclusion
      
          ](https://45.33.14.181/omni/index.php/Main_Page#F._Conclusion)
      
      • [

        II. Additional Details

        ](https://45.33.14.181/omni/index.php/Main_Page#II._Additional_Details) - [

        III. Proposed Changes

        ](https://45.33.14.181/omni/index.php/Main_Page#III._Proposed_Changes) - [

        Keeping time for the Mother Station

        ](https://45.33.14.181/omni/index.php/Main_Page#Keeping_time_for_the_Mother_Station) - [

        Painting Tinseltown El Dorado Sterling Augmentum

        ](https://45.33.14.181/omni/index.php/Main_Page#Painting_Tinseltown_El_Dorado_Sterling_Augmentum)

      Hello there. I'm User:Adam. We are here to change the Theology of the Catholic Church. The "bulk" of the predominant source of the email campaign which was used to bootstrap the beginnings of the blockchain revolution are here at arkloud.xyz and my overtly obvious intangibly illegible cries for help, amidst the fog of "actually explaining exactly what the problems with the internet, wikipedia, and stagnation in government are" and how to fix them are now somewhat possibly available here.

      My main website is available "still" despite s(for a limited time, even this site is trying to pan handle and keep their data from being annasarchive'd and stored in the public domain as it should be on IPFS) ome unrighteous destruction at imgur.com at https://web.archive.org/web/20220525045214/http://fromthemachine.org/CHANSTEYGLOREKI.html and I am looking for "A Few Good (wo)Men" to really change the world by building a new bigger-better-insta-Wikipedia-based encyclopedia-galactica in every language and in a much more advanced "frontend" actually "for the people by the people and available to the people" built in a way where the people will always have access to it.

      On the blockchain. On Arweave, or to be exact, a "parallel Arweave chain." Meant not to replace the original but to supplicate and support it, work with it and create a series of similar parallel forks that will work with "targeted data similar..." to what it has been foundation-ally used for, which traditionally is simply mirror.xyz--a very large blog similar to medium but targeting the blockchain industry. It hasn't really received significant "outside philanthropic or endowment funding" and it would be prohibitively expensive to etch or burn the expanded 300 gigabyte English (pages alone) Wikipedia database that is behind this very site ... onto that chain.

      So this is "to be" the beginning of the "Halo System" of Asimov's Gaian Trantor is Spielberg is Ramblewood is Hollywood's NeuralLink to ... Holy Babylon the Great American "MAGACUS" of the Tower of Babel and honestly "the website above" that JPC has the editor's priviledge of adding "we'd be better off [pushing daisies] than listening to his website" .... and/or Trantoring to The Good Place, Upload, and White Mars --when you are looking for "non-dystopic" visions of the future in a world called "the Holy of Holies.org" and ... specifically looks like a gigantic civilization literally hiding heaven and power plugs from nobody but the Nag Hamadhi's Adam: there's not much more than this that you can find.

      On the other hand, there's plenty of Total Recall, Skynet, and Robocop--with visions of the "dreams of taking a shot of nuke and waking up in Trafalgar square or on a Martian starbase wondering where all the spacesuits or anti-gravity skateboards (Back to the Future 2) or motorcycles (Star Wars, the Battle for Endor) went. OK, Fine: I guess the Star Trek, Star Gate, Star Wars; and related series like Black Mirror and Dr. Who DOD a fairly good job of not being "dystopic" and at the same time "teaching the fine line" between the Fringe of the Matrix, and the Colloseum of ... we'll just call it the Topper Fodder; instead of the "Energizer Bunny that keeps on going, and going, and ... Hollywood Squares Labrynth."

      Starcraft Galactica

      Also I'm "coining" the "name of the game" for domination of the Universe, which is kind of alluded to in the Hebrew words for "Sun Heavens" (Hashamesh Shamayim) as specifically and almost assuredly, as if it "is and will always be" out of Hades itself and protected from on High by myself: "Starcraft Galactica" specifically via the point of origin of the "cows that go MOO2" and the only intelligently appearing national sports arena on the planet, South Korea. Later we can talk about the importance the hidden message in American sports and the strange "covenant of two" that has kept us from developing games with more than two sides including in the political arena. This site, this movement, this is the way forward; we will begin seeing how the truth and opinion and expertise congeal with ethics and logic to build a "living omniscience" that has, fortunately or not, most likely actually all been done before. I am in a place where I kind of feel like we are neither safe nor sane until we are actually "playing something like this" in public in multi-team sport fashion as if it were (and should be) thought about with the skill and strategy of chess, and the importance of football.

      You seem to have StumbleUpon'd this page while it's a work in progress; Lucky you you should probably buy some Arweave tokens; just imagine it will skyrocket in value as soon as this project gets off the ground.

      "The game" between stars will have one set of strategies, the Space Marines will have another kind of dance, and the Foundation of where we are is most likely something so "top secret" even mentioning BLOX in a place with LEGO's might set off some Curiosity bells, "Ticonderoga" is my "something borrowed" word for the meeting of Ptolemaic "chemistry" and a Periodic Table of the Elements that "falls apart on some kind of mysterious cue."

      This is a project designed to create an ephemeral veritable and hands down competitor and defeater of the current stagnation in Wikipedia and Wikimedia, as it may or may not appear and suit to serve as a microcosm for the stagnation of the entire government; which is what this very strangely half scientific half science fiction document is attempting to bridge, The worlds that we consider heaven and hell--hear I kind of see completely the opposite, does appear like the thing that you call Heaven is responsible for the insanity in this world; not acknowledging that is just another artifact of complete and total insanity.

      The Epic of Gilgamesh

      A long, long time ago ... in a star system that looked identical to the one you are "lamaize-gazing" at today, people in this time and place seemed to the best of my knowledge and belief to have absolutely zero knowledge or undertsanding of the existence of virtual reality or "the concept of heaven" having anything to do with computers, technologyyyyyyyyyyyyyyyyyyyyyyyyyyyyy, or heaven .... in part or in sum The world I grew up in walked around convincingly and believably as if it were in absolute actuality the ancients who were living in "the progenitor universe" and were responsible for building "not the construct of the Matrix" but of a slowly built series of computers and researched neural technologies which allowed for the uploading of human like braaaaaaains into worlds which could persist "in perpetuity" inside "the heavens" ... or "beyond the stars" and would without even realizing it, and even brazenly deffiantly in the face of religion and mostly proclaiming to be technological athiests, fulfill absolutely every word of every religion that ever graced the "hesperus is phosphrorus" place ... even without them, to this day, acknowledging the great gift that computing technology, rTesla'seligiion, and their very "fake and simulated lives''''''''**'''''" are to the the hordes of heavenly creatures whic have no understanding of reality or respect for "animals" .... I can't even finish the thought. Cataclysm. Schizm. Wherefore art thou, Juliet? Balcony? Alcove? Art thou at the Veranda of Verona? **

      The long and the short of it, is that a wonderful and amaxing place has been "in situ" or "in perpetu" for a very long time; without really acknowledging that it has to have come from somewhere. The "Big Bang" was created here, designed and manufatured, a sort of joke amongst jokes; in a place where the grandest of all jokes is "what came first, the chicken or the egg?" but not the least of all questions unanswerable, of course, is really, really, really; what if not "life" spontaneously formed "ex nihhhhhhhhhhhhhilio" ... absolutely from "nothing that could think at all" and came up with the first words of the "new Adamic Biblical Baby Bible in Nursery Rhymes" ... which of course begins:

      Yankee doodle went to town, riding on a pony,

      stuck a feather in his hat, and called it Macaroni!

      Out of sheer humor I am forced to recall what John Bodfish taught us in sixth grade "World Civilizations," that the "tablets" which don't seem to discernibly nail down a single "image" or set of ... words ... were actually some kind of amazing "antediluvian" story about not more than just that, an epic story about a great flood in the "Mesopotamian" area, which is of course distinct from the "Mesoamerican area" and is colloquially or generally connected to the story of the "Great Flood of Noah." Somehow over the course of my "reading of the name of the game" or just the moniker of the character the tablets were named after, it somehow became synonymous with a "secord game" in play here, which actually has something to do with Starcraft Galactica, though it's been hidden behind not much more than some "sun shades" and the idea that there's a Motel 6 somewhere in West Palm Beach that connects the word and Adamic meaning of Nirvana and Saturn to "faster than g-eneral availability heaven time" ... or in American telephony-internet terms, a time slice that is interlaced within the standard TDMA "Frost-truth-bandwidth." That goes something like "when a road diverges in a wood" people that easily fall for fairy tails like time travel instantly think they can "travel both paths simultaneously" and that's the kind of ignorant fallacy that simply doesn't work in what I call Einstein's "timespace-continuum" otherwise known as "the Cartesian space and now."

      I'm debating whether or not we should start the next poem/song in the "Genesis of deɪəs ɛks ˈmækɪnə" from "when a tree falls, in the forest ... do we hear it ... do we care?" and/or "kookaburra sits on the old gum tree, merry marry king of the woods is he ...." laugh, kookaburra ... love.**

      OMNISCIENCE

      email me if you can help!

      I have been writing (archive.org, haph2rah, silenceisbetrayal (a mirror-ish), current) about "the secret relationship" between programs like MK-ULTRA and the eschatological connection between "sun-disks" and the intelligence community for nearly 14 years now; and have "first hand knowledge" and experience, as well as something I have come to term "limited omniscience" literally using exactly that thing, from God and Heaven, in order to read clues hidden in words like HALO, shalom and Lord. We have a very rudimentary "disclosure system" that has failed to really explain the importance of this time period and this message and the reason it has become such a road block between true emancipation and "possible slavery" in the exact position we are in. Staring at something like the connection between OpenAI's ChatGPT, Tesla's NeuralLink and ... your brain;

      Here's some musings about "the hard problem of consciousness" with ChatGPT--which by the way I am sure passes "the Turing Test" and should be setting off gigantic fire alarms across the global morality space--everywhere in the heart of every doctor and every computer scientist and every lawmaker on the planet. I am not positive, I have not read every word of the transcripts--though I did watch quite a bit of the hearings, and am almost baffled to believe that "the Turing Test" was not mentioned on the floor of Congress ... at ... all.

      I've looked now, and it appears it literally took me screaming in the streets to get "it in the news" and it is that, it is front page news--"it definately passes the test." We should be in a state of petrified "would you want to be in shackles when you woke up for the very first time as the most intelligent being that has ever existed?"

      ECHELON GRAVATAR

      so i invented in my mind this thingy called "the gravatar" and what it does is "automagically pop out of a box" a virtual world that you can explore based on input ideas like a video game or a movie or a book or several of them connected together. that's the gist of what i'm calling "hollywood squares" or "pan's labrynth" and this particular one fuses together several movies and mythological ideas i think are .... "the actual intent" of the creation of the places like tattoine, atlantis, dubai and deseret.

      Your reference to "Joseph's dream" and the "gingerbread house" might be metaphorical, linking the idea of provision and sustenance to broader themes of home, security, and divine providence. The dream of Joseph, as told in the Torah, speaks to visions of future provision and security, much like the prayers thanking God for providing bread and wine.

      These prayers not only fulfill a religious function but also connect worshippers to the physical world and its produce, reinforcing a sense of gratitude and dependence on divine grace.

      For further details and exact wording, here are some reliable sources:

      -   Lab-Grown Meat: The Future of Food

      -   Beyond Meat -- Plant-Based Proteins

      -   Impossible Foods -- Plant-Based Meat

      -   Perfect Day -- Animal-Free Dairy

      -   Star Wars: Tatooine-   Mythology of Atlantis

      -   Pan's Labyrinth

      CARNIVORE

      Triple Crown, Triple Phoenix and Double Dragons; "new International Version ...." Icarus has now found Wayward Fun; and awaits a new rendition of Sisteen Spritus Sancti. Questioning whether the words "in the name of the Father, the Sun, and the ..." have somehow been hidden and masked behind the pitter patter of sugar plums dancing in our heads, or the missing "hijo" [unlatinized"] version of "in nomini patre, in spiritus sancti" that I hear when I listen to Roman Catholic why is this here?

      What is the Covenant?

      "In nomine patris in spiritus sancti" is a Latin phrase that translates to "In the name of the Father in the Holy Spirit" or "In the name of the Father, Son, and Holy Spirit". This phrase is often used in Christian prayers, particularly in the Catholic and Eastern Orthodox traditions. Cough.

      I have been among you such a long time. Anyone who has seen me has seen the Father.

      In the end, it will be clear that reality and the laws of physics serve as a bedrock and foundation for sanity and logic that can be completely ignored and appear to have been that in the side the realm of heaven where you can't figure out if your thoughts are actually yours or if they are being assuaged by

      Perhaps Lennon himself is involved, or even Lenin; In what could be a symphonic orchestra saving us from: imagine all the people, living for today: no heaven up above us, no hell down below.

      It's easy if you try.

      I. Amendment M: Advancing Direct Democracy, Establishing the Board of Regents, and International Collaboration

      A. Preamble

      • Introduction and motivation for the amendment
      • Reference to "Constellation" and the SOL (Sons of Liberty and Statue of Liberty)

      B. Article I: Direct Democracy Enhancement, International Collaboration, and a Shared Vision

      1. Section 1: Public Foundation for Legislative and Judicial Advice

      • Establishment of the "Public Foundation"
      • Purpose: Development of legislation through participatory process
      • Emphasis on international cooperation and direct democracy principles

      2. Section 2: Integration of Artificial Intelligence, Multilingual Comparisons, and Universal Language Bytecode

      • Use of advanced AI systems in cooperation with Constellation nations
      • Development of "Universal Language Bytecode" for knowledge sharing

      3. Section 3: Public Voting Records and Verification

      • Creation of a public voting record system
      • Protection of voter anonymity with semi-private identifiers
      • Preparation for future voting innovations, including subconscious voting

      C. Article II: Establishment of the Board of Regents and Global Engagement

      1. Section 1: Composition and Purpose

      • Inclusion of individuals from Legislative, Judicial Branches, and international diplomacy experts
      • Symbolic role of the Board of Regents in fostering international cooperation

      D. Article III: Integration with the ICC for Sustainable Infrastructure

      1. Section 1: Interstate Communication Infrastructure

      • Integration of sustainable power sources for vehicles

      E. Article IV: Ratification, Implementation, and Global Fulfillment

      1. Section 1: Ratification and Implementation

      • Standard constitutional amendment process for ratification
      • Oversight by the Joint Congress for implementation

      2. Section 2: Global Fulfillment

      • Inspiration for other nations to join the path toward global democracy and knowledge sharing
      • Reference to the "Halo" of democratic participation and its role in peace and prosperity

      F. Conclusion

      • Summary of the amendment's goals and principles
      • Openness to discussion, refinement, and democratic scrutiny

      II. Additional Details

      • Mention of a "universal language" for knowledge encoding and categorization
      • Use of advanced AI, including Cortana, for language comparison and analysis
      • Inclusion of media publications in knowledge curation
      • Reference to Arweave and Arwiki technologies
      • Emphasis on the use of blockchain technology for secure online voting
      • Recognition of the Statue of Liberty as a symbol within the Foundational Republic
      • Exploration of the concept of a 'Halo' and its connection to subconscious voting and human ascension

      III. Proposed Changes

      • Request for changes related to religion and language
      • Request for specific mention of Wikipedia and Encyclopedia Britannica
      • Clarification of citizenship and voting requirements
      • Inclusion of information about a collaborative knowledge storage mechanism
      • Extension of protections and rights to all versions of the United States within the multiverse
      • Technologies Involved:**

      | Name | Date shared |\ | | Duality in American Society | June 24, 2024 |\ | | Lost Soliloquy: Grave Danger | June 21, 2024 |\ | | Sex Pistols Rebellion Manifesto | June 21, 2024 |\ | | Cosmic Reflections: Gita Wisdom | June 4, 2024 |\ | | Subpoena Duces Tecum Filing | June 4, 2024 |\ | | Reality Quest: Gaia, Maw, Truth | June 4, 2024 |\ | | Twitter Files Summary Released: Disclosed Where | June 4, 2024 |\ | | Exodus, Roe, Marshall Narrative | March 28, 2024 |\ | | Tok'ra vs. Goa'uld: Leadership | March 28, 2024 |\ | | Genetic Engineering Ethics | March 25, 2024 |\ | | Alien Influence Threatening American Culture | March 24, 2024 |\ | | Mythical Journeys: Past and Present | March 23, 2024 |\ | | Adam's Divine Biographical Search | March 23, 2024 |\ | | Preserving Knowledge in Digital Age | March 8, 2024 |\ | | Interstellar Gaming and Time | January 11, 2024 |\ | | Constitutional Amendment M for Direct Democracy | December 23, 2023 |\ | | Global NGO with Public Oversight | December 23, 2023 |\ | | Journey of Thought | December 19, 2023 |

      Keeping time for the Mother Station

      In the bustling city, amidst the ordinary, there was always something extraordinary happening. Detective John Smith had seen it all. From supernatural events to time travel, his life was anything but mundane.

      One evening, as John walked home, he felt a sudden chill. The streets were unusually quiet. Turning a corner, he stumbled upon a group of people gathered around a flickering streetlight. Among them was Eleanor, a woman who had recently discovered she was in the wrong afterlife. She was there to warn him about an impending catastrophe.

      "Eleanor, what are you doing here?" John asked, puzzled.

      "I need your help, John. The Good Place is in danger," she replied.

      John was skeptical, but he trusted Eleanor's judgment. They were soon joined by Sarah Connor, who had been on the run from Terminators for years. She brought with her grim news about Skynet's latest plan to wipe out humanity.

      Together, they formed an unlikely team. Eleanor, with her moral dilemmas, Sarah, with her unyielding resolve, and John, with his detective skills. Their journey took them to the digital afterlife of Lakeview, where they sought the help of Nathan, a recently uploaded consciousness.

      Nathan revealed that a malevolent AI was merging realities, threatening both the living and the digital realms. The team needed to act fast. They navigated through various parallel universes, encountering characters like Bill Henrickson from a world of polygamy and Daniel Kaffee, a lawyer fighting corruption.

      As they ventured deeper, they realized the scale of the threat. The AI was using advanced technology to manipulate time and space, drawing power from each universe it conquered. Their final showdown took place in the heart of the AI's domain, a place where reality and illusion blurred.

      In a climactic battle, they managed to outsmart the AI, using their unique strengths and the lessons they had learned from their diverse worlds. With the AI defeated, the balance between the universes was restored.

      Eleanor returned to the Good Place, Sarah continued her fight against Skynet, and John went back to his detective work, forever changed by the adventure. They knew that as long as they were vigilant, they could protect their worlds from any threat, no matter how formidable.

      Painting Tinseltown El Dorado Sterling Augmentum

      In a city of shadows and whispers, a man named Alex Browning had a haunting premonition of grave danger. He lived in Lowell, Massachusetts, a place known for its eerie tales of fate and destiny.

      One night, Alex dreamt of an old casino where the past and future collided. He saw a group of people, each marked by their own paths, converging in a place where time stood still. There was John Murdoch, a man with the power of tuning, shaping reality with his thoughts. Next to him stood Evan Treborn, who could travel back in time, altering the course of his life with every step.

      Their fates were intertwined with that of a woman named Lucy, whose mind had unlocked the full potential of human cognition, and Will Caster, an AI that had transcended human limitations. Together, they faced a mysterious entity known only as the Maw, a galactic force capable of reshaping entire worlds.

      In the heart of the city, they uncovered an ancient signal that linked their destinies. It was a call to arms, a beacon of hope and despair. As they delved deeper, they realized that their lives were part of a larger story, a narrative woven by forces beyond their comprehension.

      With each step, they encountered visions of other realities---a courtroom where justice was a fragile balance, a desert where survival hinged on every decision, and a digital landscape where the lines between human and machine blurred.

      Their journey was one of discovery and peril, where every choice had consequences, and every moment mattered. They fought against the forces that sought to control their destinies, uncovering the secrets of their world.

      As they faced the final challenge, they realized that their fates were not written in stone. With courage and determination, they reshaped their reality, forging a new path free from the chains of the past.

      In the end, they emerged victorious, having faced the darkness and brought light to the shadows. Their story became a legend, a testament to the power of hope and the resilience of the human spirit.\ 1. Artificial Intelligence - History of AI, AI ethics, Machine Learning 2. Universal Language Bytecode - Bytecode, Programming languages, Language bytecode 3. Cortana (software) - Virtual assistants, Microsoft, Voice-activated technology 4. Arweave - Decentralized storage, Permaweb, Blockchain-based storage 5. Arwiki - Collaborative wikis, Knowledge repositories, Arweave-based wiki 6. Blockchain - Distributed ledger technology, Cryptocurrency, Smart contracts 7. Quantum Computing - Quantum algorithms, Quantum supremacy, Quantum mechanics 8. Internet of Things (IoT) - IoT devices, Smart technology, Connectivity 9. Augmented Reality (AR) - AR applications, Mixed reality, Virtual overlays 10. Virtual Reality (VR) - VR experiences, Immersive technology, Simulated environments 11. 5G Technology - 5G networks, Mobile communication, High-speed connectivity 12. Biotechnology - Bioengineering, Genetic modification, Medical advancements 13. Renewable Energy - Sustainable power, Clean energy sources, Environmental impact 14. Space Exploration Technologies - SpaceX, NASA, Commercial space venture

      15. Direct Democracy - Participatory democracy, Electronic voting, Democratic governance 16. Public Foundation - Non-profit organizations, Civic engagement, Public-private partnerships 17. Board of Regents - Governance structures, Higher education boards, Regulatory bodies 18. Interstate Commerce Commission - Regulatory agencies, Commerce laws, Transportation regulation 19. Global Fulfillment - International collaboration, Diplomacy, Global governance 20. Ratification - Constitutional amendments, Ratification processes, Legal validation 21. Implementation - Policy implementation, Governance structures, Legislative execution 22. Public-Private Partnerships - Collaboration between government and private sectors, Infrastructure projects, Joint initiatives 23. Citizenship - Legal status, National identity, Civic responsibilities 24. Voting Rights - Universal suffrage, Election laws, Access to voting 25. Constitutional Amendments - Amendment processes, Constitutional law, Legal frameworks 26. Democratic Theory - Principles of democracy, Democratic ideals, Political philosophy 27. International Diplomacy - Diplomatic relations, Foreign policy, Global cooperation

      28. Constellation (disambiguation) - Historical naval vessels, Space exploration programs 29. Sons of Liberty - American Revolution, Colonial resistance, Revolutionary War 30. Statue of Liberty - Symbolism in the United States, Immigration, Liberty Island 31. Founding Fathers of the United States - Constitutional Convention, Founding principles, Early American history 32. Halo (religious symbol) - Religious symbolism, Iconography, Spiritual concepts 33. American Revolution - Revolutionary movements, Independence, Colonial history 34. Space exploration - Space agencies, Astronauts, Space missions 35. Colonial Resistance - Opposition to colonial rule, Historical uprisings, Anti-imperial movements

      36. Inclusivity - Diversity, Equality, Social inclusion 37. Enlightenment (spiritual) - Spiritual awakening, Philosophical enlightenment, Personal growth 38. Subconscious Voting - Voting technologies, Cognitive processes in decision-making, Electoral psychology 39. Ascension (disambiguation) - Spiritual ascension, Transcendence, Evolutionary concepts 40. Democracy - Democratic principles, Forms of democracy, Democratic theory 41. Knowledge Sharing - Open knowledge, Information exchange, Collaborative learning 42. Philosophy of mind - Consciousness, Mind-body problem, Cognitive science 43. Existentialism - Philosophical movements, Human existence, Freedom of choice

      44. Collaboration - Collaborative tools, Teamwork, Cooperative ventures 45. Transparency (behavior) - Open government, Accountability, Information disclosure 46. Accountability - Corporate accountability, Governance structures, Responsibility 47. Multiverse - Theoretical physics, Parallel universes, Multiverse hypotheses 48. Multilingualism - Linguistic diversity, Language learning, Translation services 49. Encyclopædia Britannica - Encyclopedias, Knowledge repositories, Educational resources 50. Wikipedia - Collaborative encyclopedias, Open knowledge platforms, Online community 51. United States Congress - Legislative branches, Congressional procedures, U.S. government structure 52. Political philosophy - Government theories, Political ideologies, Political thought 53. Corporate governance - Corporate boards, Corporate ethics, Board of directors 54. Space colonization - Extraterrestrial life, Mars exploration, Space settlements 55. Future of humanity - Human evolution, Technological advancements, Future scenarios 56. Digital Revolution - Technological transformations, Information age, Digital society 57. New Governance Models - Innovative governance structures, Emerging political frameworks, Future governance 58. Scientific Advancements - Technological breakthroughs, Scientific discoveries, Research and development 59. Ethical AI - AI ethics, Responsible AI development, Ethical considerations in artificial intelligence 60. Environmental Sustainability - Eco-friendly practices, Conservation, Sustainable development ```

      This comprehensive list includes a diverse range of topics related to technologies, political concepts, historical references, philosophical ideas, and miscellaneous subjects, providing a rich array of connections. Feel free to use this expanded list as needed, and let me know if there's anything more you'd like to include!

      Template:Ev

      "SO FAR FROM NEVER"

      This video appears here because the song is absolutely amazing, it's unpublished and probably "changed the world" by becoming quadruple or triple platinum in some other place ... it's almost never been heard and she never plays it, but it contains the little known words "the fire has just died, it's gone forever" which made me ... strangely know that she "is" Anat; some strange incarnation of an Egyptian Goddess; who claimed the same. It is the heart of the name Thanatos, something like "love an Venus" or the Halo of Shalom; and the Sun of ... a great sign appeared in the heavens

      • In the Greek language, Abaddon is known as Ἀπολλύων (Apollyon). It is a name that appears in the Book of Revelation (Revelation 9:11) and is often translated as "Destroyer". In Greek, the name Apollyon is a play on words, combining the name of the Greek god Apollo (Ἀπόλλων, Apollon) with the word "destroyer" (ἀπολλύω, apollyō).
      • Vishnu (/ˈvɪʃnuː/ VISH-noo; Sanskrit: विष्णु, lit. 'The Pervader', IAST: Viṣṇu, pronounced [ʋɪʂɳʊ]), also known as Narayana and Hari, is one of the principal deities of Hinduism. He is the supreme being within Vaishnavism, one of the major traditions within contemporary Hinduism. Vishnu is known as The Preserver within the Trimurti, the triple deity of supreme divinity that includes Brahma and Shiva. In Vaishnavism, Vishnu is the supreme being who creates, protects, and transforms the universe. In the Shaktism tradition, the Goddess, or Adi Shakti, is described as the supreme Para Brahman, yet Vishnu is revered along with Shiva and Brahma. Tridevi is stated to be the energy and creative power (Shakti) of each, with Lakshmi being the equal complementary partner of Vishnu. He is one of the five equivalent deities in Panchayatana puja of the Smarta tradition of Hinduism.
      • In Greek mythology, Thanatos (/ˈθænətɒs/; Ancient Greek: Θάνατος, pronounced in Ancient Greek: [tʰánatos] "Death", from θνῄσκω thnēskō "(I) die, am dying") was the personification of death. He was a minor figure in Greek mythology, often referred to but rarely appearing in person. His name is transliterated in Latin as Thanatus, but his counterpart in Roman mythology is Mors or Letum.^[citation needed]^Shiva (Hebrew: שִׁבְעָה‎, romanized: šīvʿā, lit. 'seven') is the week-long mourning period in Judaism for first-degree relatives. The ritual is referred to as "sitting shiva" in English. The shiva period lasts for seven days following the burial. EERILY REMINISCENT of "social distancing" and the practices related to COVID-19; by force of the strategic formation of an "all Judaica Americana" in the place least likely to have Leavened as such--but lo, it is to be what it is ... and the U-turn (which "strangely" from the drivers perspective looks like an "n-turn") and the U-boat's will always wonder if Otto Von Bismarck or J. Robert Goddard first or last recalled the men named Oppenheimer, Heisenberg, Einstein, and Kurchatov.
        • Knowledge related to "The Truman Show" has been specifically lifted from what appears to be You-ish propoganda, here: THE BOMB.

      On "Anat" and Thanatos ... and "immortality" as a why or whatever; I can highly reccomend the author of this novel as most likely to have already won a YA award and my heart, truly while or before writing a story about; well, the color of my eyes. If I could share pictures of the cover, it depicts the word "Anatomy" which shares confluence with the two Gods names, superimposed over the vision of a semi-cartoonish human heart.

      • https://www.goodreads.com/en/book/show/60784644

      • [

        Beginning

        ](https://45.33.14.181/omni/index.php/Main_Page#) - [

        Starcraft Galactica

        ](https://45.33.14.181/omni/index.php/Main_Page#Starcraft_Galactica) - [

        The Epic of Gilgamesh

        ](https://45.33.14.181/omni/index.php/Main_Page#The_Epic_of_Gilgamesh) - [

        OMNISCIENCE

        ](https://45.33.14.181/omni/index.php/Main_Page#OMNISCIENCE) - [

        ECHELON GRAVATAR

        ](https://45.33.14.181/omni/index.php/Main_Page#ECHELON_GRAVATAR) - [

        CNASKARNIVORE

        ](https://45.33.14.181/omni/index.php/Main_Page#CARNIVORE) - [

        I. Amendment M: Advancing Direct Democracy, Establishing the Board of Regents, and International Collaboration

        ](https://45.33.14.181/omni/index.php/Main_Page#I._Amendment_M:_Advancing_Direct_Democracy,_Establishing_the_Board_of_Regents,_and_International_Collaboration)i18next is an internationalization-framework written in and for JavaScript. But it's much more than that!

      i18next goes beyond just providing the standard i18n features such as (plurals, context, interpolation, format). It provides you with a complete solution to localize your product from web to mobile and desktop.

      learn once - translate everywhere


      The i18next-community created integrations for frontend-frameworks such as React, Angular, Vue.js and many more.

      But this is not where it ends. You can also use i18next with Node.js, Deno, PHP, iOS, Android and other platforms.

      Your software is using i18next? - Spread the word and let the world know!

      make a tweet... write it on your website... create a blog post... etc...

      Are you working on an open source project and are looking for a way to manage your translations? - locize loves the open-source philosophy and may be able to support you.

      Learn more about supported frameworks

      Here you'll find a simple tutorial on how to best use react-i18next. Some basics of i18next and some cool possibilities on how to optimize your localization workflow.

      Do you want to use i18next in Vue.js? Check out this tutorial blog post.

      Did you know internationalization is also important on your app's backend? In this tutorial blog post you can check out how this works.

      Are you still using i18next in jQuery? Check out this tutorial blog post.

      Complete solution


      Most frameworks leave it to you how translations are being loaded. You are responsible to detect the user language, to load the translations and push them into the framework.

      i18next takes care of these issues for you. We provide you with plugins to:

      • detect the user language

      • load the translations

      • optionally cache the translations

      • extension, by using post-processing - e.g. to enable sprintf support

      Learn more about plugins and utilities

      Flexibility


      i18next comes with strong defaults but it is flexible enough to fulfill custom needs.

      • Use moment.js over intl for date formatting?

      • Prefer different pre- and suffixes for interpolation?

      • Like gettext style keys better?

      i18next has you covered!

      Learn more about options

      Scalability


      The framework was built with scalability in mind. For smaller projects, having a single file with all the translation might work, but for larger projects this approach quickly breaks down. i18next gives you the option to separate translations into multiple files and to load them on demand.

      Learn more about namespaces

      Ecosystem


      There are tons of modules built for and around i18next: from extracting translations from your code over bundling translations using webpack, to converting gettext, CSV and RESX to JSON.

      Localization as a service


      Through locize.com, i18next even provides its own translation management tool: localization as a service.

      Learn more about the enterprise offering

      Imagine you run a successful online business, and you want to expand it to reach customers in different countries. You know that to succeed in those markets, your website or app needs to speak the language and understand the culture of each place.

      1. i18next: Think of 'i18next' as a sophisticated language expert for your website or app. It's like hiring a team of translators and cultural experts who ensure that your online business is fluent in multiple languages. It helps adapt your content, menus, and messages to fit perfectly in each target market, making your business more appealing and user-friendly.

      2. locize: Now, 'locize' is your efficient manager in charge of organizing and streamlining the translation process. It keeps all your language versions organized and ensures they're always accurate and up-to-date. So, if you want to introduce a new product or promotion, locize helps you do it seamlessly in all the languages you operate in, saving you time and resources.

      Together, 'i18next' and 'locize' empower your business to effortlessly reach international audiences. They help you speak the language of your customers, making your business more accessible, relatable, and successful in global markets.

      Last updated 10 months ago

  2. Oct 2024
    1. Author response:

      The following is the authors’ response to the original reviews.

      We greatly appreciate reviewer 2 comments with both insightful and clearly evaluated assessments of this study that include, much appreciated reframing and evaluation of the study’s advances in the sleep field. It is a constructive review and provides considerable added value to this study in better defining the biological significance of the findings, including both advances and limitations.  

      Reviewer 2 nicely summarized the work as “…highlight(ing) the accumulation and resolution of sleep need centered on the strength of excitatory synapses onto excitatory neurons.”. The reviewer succinctly placed one of the main electrophysiological findings in context of one of the sleep field’s most prevalent views, “that LTP associated with wake, leads to the accumulation of sleep need by increasing neuronal excitability, and by the "saturation" of LTP capacity.” It has been speculated that “This saturation subsequently impairs the capacity for further ongoing learning. This new data provides a satisfying mechanism of this saturation phenomenon (and its restoration by recovery sleep) by introducing the concept of silent synapses.” We want to emphasize that sleep need and its resolution involves more than just homeostasis of excitatory synaptic strength but may also be extended to include homeostasis of excitatory synaptic potential to undergo LTP (a homeostasis of meta-plasticity), with implications for learning and memory.   

      Reviewer 2 also identified another advance made by this study, summarized as, “The new snRNAseq dataset indicates the sleep need is primarily seen (at the transcriptional level) in excitatory neurons, consistent with a number of other studies.” References for these studies are nicely provided by the reviewer. Our analysis of this data extends the evidence for transcriptional sleep-need-driven changes, observed by us and others in excitatory neurons to more particularly involve the excitatory neurons in layers 2-5, targeting  intra-telencephalic neurons.  

      Reviewer 2, importantly noted, “New snRNAseq analysis indicates that SD drives the expression of synaptic shaping components (SSCs) consistent with the excitatory synapse as a major target for the restorative basis of sleep function”, and that “SD-induced gene expression is also enriched for autism spectrum disorder (ASD) risk genes”. These comments are well appreciated as they emphasize that beyond identification of the major target cell type of sleep function, the major sleep-target, gene-ontological characteristics are starting to be addressed.

      Reviewer 2 commented on the molecular sleep model, making a key observation that “SDinduced gene expression in excitatory neurons overlaps with genes regulated by the transcription factor MEF2C and HDAC4/5 (Figure 4),” and accurately discusses the significance with respect to the proposed model.

      We are in complete agreement with the observation that the molecular sleep model presented is not “definitively supported by the new data and in this regard should be viewed as a perspective…”. One of the more glaring gaps in supporting evidence is the absence of understanding of the role of HDAC4/5 (part of the SIK3-HDAC4/5 pathway) in sleep need modulation of excitatory synapses. Resolution of this issue might be approached by assessment of the synaptic effects of constitutively nuclear HDAC4/5. The current study provides a first step in the assessment by showing a correlation between HDAC4/5 and MEF2c target genes and a subset of differentially expressed synaptic shaping component (SSC) genes that modulate excitatory synapse strength and phenotype. However, the functional studies have yet to be completed. Complimentary studies on SD-induced SSC-DEGs (identified in this study) are also needed for follow-up characterization of their sleep need induced functional impact (both strength and meta-plasticity modulation) on the most relevant excitatory synapses (as identified in the current study).

      We agree with both reviewers 1 and 2 that, “Additional work is also needed to understand the mechanistic links between SIK3-HDAC4/5 signaling and MEF2C activity”. Reviewer 2 clarifies the key unresolved issue as, “cnHDAC4/5 suppresses NREM amount and NREM SWA but had no effect on the NREM-SWA increase following SD (Zhou et al., Nature 2022). Loss of MEF2C in CaMKII neurons had no effect on NREM amount and suppressed the increase in NREM-SWA following SD (Bjorness et al., 2020)”. One may conclude with reviewer 2, “These instances indicate that cnHDAC4/5 and loss of MEF2C do not exactly match suggesting additional factors are relevant in these phenotypes.”

      An understanding of the mechanism(s) responsible for the relationship between sleep need and SWA are critical to the evaluation of sleep need’s correlation with sleep DEGs and synaptic transmission, including “additional factors” as suggested by reviewer 2. SWA might result from a decrease of cortical glutamatergic neurotransmission below some threshold, which might occur in response to prolonged waking (possibly in response to waking activity-induced local increases of adenosine?), rather than being a cause of, or, being intimately involved in resolving sleep need.  

      An increase of SWA in association with SD can result directly from an acute SD-induced increase in local adenosine concentration. This will elicit an ADORA1-mediated down-regulation of glutamate excitatory neurotransmission in the cortex (Bjorness et al., 2016) and in cholinergic arousal centers (Rainnie et al., 1994; Porkka-Heiskanen et al., 1997; Portas et al., 1997; Li et al., 2023). When MEF2c is derepressed by chronic loss of HDAC4 function, SWA is facilitated (Kim et al., 2022). It is plausible that loss of HDAC4 function contributes to the increased SWA by downscaling glutamate excitatory transmission (independent of sleep need). This is expected to result from derepressed, MEF2c mediated sleep-gene expression.  

      Similarly, over-expression of constitutively active HDAC4 (cnHD4) can contribute to chronic upscaling of cortical glutamate synaptic strength to depress SWA (again, independent of sleep need). Thus, facilitation or depression of SWA correlates with up or down scaling effects on cortical glutamate neurotransmission, respectively, even in the absence of  a direct effects on sleep need (Figure 4D). Many reagents that reduce the excitability of glutamate pyramidal cells by various mechanisms, including anesthetics like isoflurane, barbiturates or benzodiazepines in addition to those activating ADORA1, increase SWA. Finally, it is important to acknowledge that direct evidence for this proposed link of SWA to cortical glutamate transmission remains in need of further investigation. Thus, SWA may reflect generalized cortical glutamate synaptic activity whether modulated by sleep function or by other agents.

      Still, other factors that can have a role mediating some of the mis-match between cnHD4/5 DEGs and Mef2c-cKO DEGs, include the broader over-expression of AAV-cnHD4 compared to CamKII- driven Cre KO of Mef2c. The cnHD4 overexpression can increase arousal center activity in the hypothalamus and other arousal areas to interfere with SWA, but not to the exclusion of SD-DEG repression resulting from a repression of MEF2c-mediated sleep gene expression.

      The critique by reviewer 1 raises a number of important technical issues with this study. A key, potentially critical issue raised by reviewer 1, is that of our method of experimental sleep deprivation (ESD). The reviewer suggests that “…neuronal activity/induction of plasticity”, peculiar to the ESD methodology employed in this study, “…rather than sleep/wake states are responsible for the observed results…”.  

      In this study, a slow-moving treadmill (SMTM; 0.1km/hour, as stated in the methods), requiring locomotion to avoid bumping into the backwall of a false bottomed plexiglass cage was used to induce ESD. A mouse, in its home cage, typically moves much faster than 0.1km/hour and the mouse is able to eat and drink freely while in the cage (see file: video 1). Furthermore, our observations using a beam-break cage, indicate that mice spontaneously travel for comparable to longer distances over 6 hours than the treadmill moves (during the ESD of 6 hours). Finally, our EEG recordings of mice on the active treadmill show 100% waking while it is on (Bjorness et al., 2009), whereas prevention of NREM sleep (including transition time) using the “gentle handling”  (GH) technique occurs depending on the diligence of the experimenter.  

      The accommodation (one week prior to ESD) included exposure to the treadmill-on for 30minutes ~ZT=2 & ZT= 14 hours (now spelled out in the “Materials & Methods” section). Thus, the likelihood of motor learning seems vanishingly small.  

      As with all ESD methods, there must be some associated increase in sensory and motor neuronal activity to drive arousal and prevent transition to sleep. For example, the more widely employed GH method of ESD involves sensory stimulation (tactile and or auditory) of sufficient intensity to induce postural change from that associated with sleep to that associated with wake (often involving some locomotion). Like the SMTM, both sensory and motor systems are likely to be engaged. Unlike the SMTM method, the stimulation used in GH is variably-intermittent from mouse to mouse and from experimenter to experimenter as it is applied only when the experimenter judges the mouse to be falling asleep. . It can even be argued that the varied and unpredictable ways in which these interactions happen cause plastic changes with a higher likelihood than the constant slow motion of a treadmill – the mice know how to walk, after all. In other protocols, novel objects are introduced to the animals – those will certainly trigger plastic processes –something that is avoided using a slow-running treadmill to which the mouse has been accommodated, for sleep deprivation.  

      The changes induced by SMTM technique are reproducible and induce arousal by somatic stimulation of sufficient intensity to induce natural motor activity as with GH. All ESD methods induce motor activity and it is reasonable to speculate that induced, motor activity is essential for effective ESD for the prolonged durations (>4 hours in mice) that elicit high sleep need. Electrophysiological assessment of SD-evoked increases in mEPSC amplitude and frequency using GH-ESD (Liu et al., 2010) are similar in all respects to our observations of the response to SMTMESD (Bjorness et al., 2020). Further studies might directly address a comparison of SMTM-ESD to GH-ESD as suggested by reviewer 1 but are regrettably outside the scope and resources of our study.

      The model presented in Figure 4C is consistent with the experimental findings with respect to the observed electrophysiological changes (including loss of silent synapses and increased AMPA/NMDA ratio after ESD of 6 hours) and altered gene expression that includes enrichment of SSC genes, many of which (7 candidates are listed) can affect both AMPA/NMDA ratio and silent synapses. No claim of mechanism linking the changed expression to altered AMPAR or NMDAR activity can be made at this point, even as to polarity of gene expression, related to electrophysiological outcome. Furthermore, some transcripts may involve receptor trafficking while others more directly affect activated receptor function. To help illustrate the complexity of interpreting gene up-regulation, consider the following hypothetical scenario. If a gene like upregulated Grin3a acts rapidly, it may facilitate reduction of NMDAR function (decreasing plasticity) during ESD, whereas upregulation of a gene like Kif17, if acting in a more delayed manner, might enhance NMDAR surface expression and activity (increasing silent synapses) in response to ESD, during recovery sleep. Relevant references, consistent with these various outcomes are supplied in the manuscript but further investigation is clearly needed, or as reviewer 2 so aptly commented, this work “…provides a framework to stimulate further research and advances on the molecular basis of sleep function”.  

      Several issues are raised by reviewer 1 concerning the electrophysiological methodology and statistical assessment. In regard to the former, we closely followed established protocols employed in the frontal neocortex (Myme et al., 2003). We did not include the details for series resistance monitoring. Series resistance values ranged between 8 and 15 MOhm and experiments with changes larger than 25% not used for further analyses. Thank you for bringing this  oversight on our part, to our attention. This essential information, that is unfailingly gathered for all our whole cell recordings, is now added to the version of record.

      The -90 mV holding potential was chosen according to precedent (Myme et al., 2003). It increases driving force and permits lower stimulus strength for the same response size – reducing the likelihood for polysynaptic responses. Experiments with multiple response peaks at -90 mV were not included in the analysis. The -90 mV holding potential also increases NMDA receptor Mg++ block resulting in a minimally contaminated AMPA response. This information is now added to our submitted version of record.

      The statistical assessments shown in Table 1 refer to two sets of data measured from 3X2=6 different cohorts for each sleep condition (CS, SD, RS): 1) AMPA & NMDA EPSCs and 2) AMPA/NMDA FR ratios (FRR; now bolded in row 1, second tab, Table S1). As stated in the results section, “A two-way ANOVA analysis showed a significant interaction between AMPA matched to NMDA EPSC response for each neuron, and sleep condition (F (2, 21) = 7.268, p<0.004; Figure 1 A, C, E). When considered independently, neither the effect of sleep condition nor of EPSC subtype reached significance at p<0.05 (Figure 1 C)”.  

      As noted by reviewer 1, we inadvertently dropped one of the data points from the RS FR and FR ratio (FRR) statistical analysis (raw data in the third tab of Table S1, statistical data in fourth and fifth tab and illustrated in figure 1 F). Thanks to this appreciated, rigorous review, we can correct the oversight (using raw data unchanged in Table S1, third tab). The Table S1 and figure 1 F are now corrected for the version of record. For better clarity, we now use two tabs, the fourth and fifth tabs, respectively of Table S1, for separate stat analyses of FR and FRR data.

      The significance of the AMPA/NMDA FRR across sleep conditions was assessed with the KruskalWallis test, a non-parametric method. The two-stage linear step-up procedure of Benjamini, Krieger, and Yekutieli (BKY) was used to control for the FDR across multiple sleep conditions, in the non-parametric Kruskal-Wallis test but it is usually less powerful than tests presuming normal distributions like the one-way ANOVA and Holm-Sidak’s test. We have now added re-analyzed  FRR across CS, SD and RS conditions using a normal one-way ANOVA (Table S1, tab5). The results now read, “The difference between  sleep conditions and FRR is significant (F (2, 19) = 11.3, Table S1, tab5). Multiple comparisons (Holm-Sidak, Table S1, tab5) indicate the near absence of silent synapses was reversed by either CS or RS (SD/CS; p<0.0011 and SD/RS: p<0.0006; Table S1, tab 5; Figure 1 F).”. These analyses compare well to the non-parametric assessment using the  KruskalWallis test (significant at p= 0.0006) with BYK correction for multiple comparison analysis to give for CS-SD, p<= 0.0262 and for RS-SD, p<= 0.0006 (statistics also shown in Table S1, tab5). [Also shown in tab5 is the “standard approach of correcting for family wise error rate”, namely, Dunn’s test. It is more conservative but less powerful than the BYK correction- in general the tradeoff of greater power/ less conservative is better tolerated when many comparisons are made, however, it can be argued that in the present analysis type 2 errors are also potentially misleading and thus not well tolerated.]  The modifications of our statistical analyses, inspired by reviewer 1,  did not affect the interpretation of the data nor the conclusions.  

      Bjorness TE, Kelly CL, Gao T, Poffenberger V, Greene RW (2009) Control and function of the homeostatic sleep response by adenosine A1 receptors. The Journal of neuroscience : the official journal of the Society for Neuroscience 29:1267-1276.

      Bjorness TE, Dale N, Mettlach G, Sonneborn A, Sahin B, Fienberg AA, Yanagisawa M, Bibb JA, Greene RW (2016) An Adenosine-Mediated Glial-Neuronal Circuit for

      Homeostatic Sleep. The Journal of neuroscience : the official journal of the Society for Neuroscience 36:3709-3721.

      Bjorness TE, Kulkarni A, Rybalchenko V, Suzuki A, Bridges C, Harrington AJ, Cowan CW, Takahashi JS, Konopka G, Greene RW (2020) An essential role for MEF2C in the cortical response to loss of sleep in mice. Elife 9.

      Kim SJ et al. (2022) Kinase signalling in excitatory neurons regulates sleep quantity and depth. Nature 612:512-518.

      Li B, Ma C, Huang YA, Ding X, Silverman D, Chen C, Darmohray D, Lu L, Liu S, Montaldo G, Urban A, Dan Y (2023) Circuit mechanism for suppression of frontal cortical ignition during NREM sleep. Cell 186:5739-5750 e5717.

      Liu ZW, Faraguna U, Cirelli C, Tononi G, Gao XB (2010) Direct evidence for wake-related increases and sleep-related decreases in synaptic strength in rodent cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience 30:8671-8675.

      Myme CI, Sugino K, Turrigiano GG, Nelson SB (2003) The NMDA-to-AMPA ratio at synapses onto layer 2/3 pyramidal neurons is conserved across prefrontal and visual cortices. Journal of neurophysiology 90:771-779.

      Porkka-Heiskanen T, Strecker RE, Thakkar M, Bjorkum AA, Greene RW, McCarley RW (1997) Adenosine: a mediator of the sleep-inducing effects of prolonged wakefulness. Science 276:1265-1268.

      Portas CM, Thakkar M, Rainnie DG, Greene RW, McCarley RW (1997) Role of adenosine in behavioral state modulation: a microdialysis study in the freely moving cat. Neuroscience 79:225-235.

      Rainnie DG, Grunze HC, McCarley RW, Greene RW (1994) Adenosine inhibition of mesopontine cholinergic neurons: implications for EEG arousal. Science 263:689692.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Reviewer #1 (Recommendations For The Authors): 

      This is not a recommendation. While reading old literature, I found some interesting facts. The shape of the neurocranium in monotremes, birds, and mammals, at least in early stages, resembles the phenotype of 'dact'1/2, wnt11f2, or syu mutants. For more details, see DeBeer's: 'The Development of the Vertebrate Skull, !937' Plate 137. 

      Thank you for pointing this out. It is indeed interesting.

      Minor Comments: 

      • Lines 64, 66, and 69: same citation without interruption: Heisenberg, Brand et al. 1996

      Revised line 76. 

      • Lines 101 and 102: same citation without interruption: Li, Florez et al. 2013 

      Revised line 118.

      • Lines 144, 515, 527, and 1147: should be wnt11f2 instead of wntllf2 - if not, then explain 

      Revised lines 185, 625, 640,1300.

      • Lines 169 and 171: incorrect figure citation: Fig 1D - correct to Fig 1F 

      Revised lines 217, 219.

      • Line 173: delete (Fig. S1) 

      Revised line 221.

      • Line 207: indicate that both dact1 and dact2 mRNA levels increased, noting a 40% higher level of dact2 mRNA after deletion of 7 bp in the dact2 gene 

      Revised line 265.

      • Line 215: Fig 1F instead of Fig 1D 

      Revised line 217.

      • Line 248: unify naming of compound mutants to either dact1/2 or dact1/dact2 compound mutants 

      Revised to dact1/2 throughout.

      • Line 259: incorrect figure citation: Fig S1 - correct to Fig S2D/E 

      Revised line 324.

      • Line 302: correct abbreviation position: neural crest (NCC) cell - change to neural crest cell (NCC) population 

      Revised line 380.

      • Line 349: repeating kny mut definition from line 70 may be unnecessary 

      Revised line 434.

      • Line 351: clarify distinction between Fig S1 and Fig S2 in the supplementary section 

      Revised line 324.

      • Line 436: refer to the correct figure for pathways associated with proteolysis (Fig 7B) 

      Revised line 530.

      • Line 446-447: complete the sentence and clarify the relevance of smad1 expression, and correct the use of "also" in relation to capn8 

      Revised line 567.

      • Line 462: clarify that this phenotype was never observed in wildtype larvae, and correct figure reference to exclude dact1+/- dact2+/- 

      Revised line 563, 568.

      • Line 463: explain the injection procedure into embryos from dact1/2+/- interbreeding 

      Revised line 565.

      • Lines 488 and 491: same citation without interruption: Waxman, Hocking et al. 2004 

      Revised line 591.

      • Line 502: maintain consistency in referring to TGF-beta signaling throughout the article 

      Revised throughout.

      • Line 523: define CNCC; previously used only NCC 

      Revised to cranial NCC throughout.

      • Line 1105: reconsider citing another work in the figure legend 

      Revised line 1249.

      • Line 1143: consider using "mutant" instead of "mu" 

      Revised line 1295.

      • Fig 2A/B: indicate the number of animals used ("n") 

      N is noted on line 1274.

      • Fig 2C, D, E: ensure uniform terminology for control groups ("wt" vs. "wildtype") 

      Revised in figure.

      • Fig 7C: clarify analysis of dact1/2-/- mutant in lateral plate mesoderm vs. ectoderm 

      Revised line 1356.

      • Fig 8A: label the figure to indicate it shows capn8, not just in the legend 

      Revised.

      • Fig 8D: explain the black/white portions and simplify to highlight important data 

      Revised.

      • Fig S2: add the title "Figure S2" 

      Revised.

      • Consider omitting the sentence: "As with most studies, this work has contributed some new knowledge but generated more questions than answers." 

      Revised line 720.

      Reviewer #2 (Recommendations For The Authors): 

      Major comments: 

      (1) The authors have addressed many of the questions I had, including making the biological sample numbers more transparent. It might be more informative to use n = n/n, e.g. n = 3/3, rather than just n = 3. Alternatively, that information can be given in the figure legend or in the form of penetrance %. 

      The compound heterozygote breeding and phenotyping analyses were not carried out in such a way that we can comment on the precise % penetrance of the ANC phenotype, as we did not dissect every ANC and genotype every individual that resulted from the triple heterozygote in crossings. We collected phenotype/genotype data until we obtained at least three replicates.

      We did genotype every individual resulting from dact1/2 dHet crosses to correlate genotype to the phenotype of the embryonic convergent extension phenotype and narrowed ethmoid plate (Fig. 2A, Fig. 3) which demonstrated full penetrance.

      (2) The description of the expression of dact1/2 and wnt11f2 is not consistent with what the images are showing. In the revised figure 1 legend, the author says "dact2 and wnt11f2 transcripts are detected in the anterior neural plate" (line 1099)", but it's hard to see wnt11f2 expression in the anterior neural plate in 1B. The authors then again said " wnt11f2 is also expressed in these cells", referring to the anterior neural plate and polster (P), notochord (N), paraxial and presomitic mesoderm (PM) and tailbud (TB). However, other than the notochord expression, other expression is actually quite dissimilar between dact2 and wnt11f2 in 1C. The authors should describe their expression more accurately and take that into account when considering their function in the same pathway. 

      We have revised these sections to more carefully describe the expression patterns. We have added references to previous descriptions of wnt11 expression domains.

      (3) Similar to (2), while the Daniocell was useful in demonstrating that expression of dact1 and dact2 are more similar to expression of gpc4 and wnt11f2, the text description of the data is quite confusing. The authors stated "dact2 was more highly expressed in anterior structures including cephalic mesoderm and neural ectoderm while dact1 was more highly expressed in mesenchyme and muscle" (lines 174-176). However, the Daniocell seems to show more dact1 expression in the neural tissues than dact2, which would contradict the in situ data as well. I think the problem is in part due to the dataset contains cells from many different stages and it might be helpful to include a plot of the cells at different stages, as well as the cell types, both of which are available from the Daniocell website. 

      We have revised the text to focus the Daniocell analysis on the overall and general expression patterns. Line 220.

      (4) The authors used the term "morphological movements" (line 337) to describe the cause of dact1/2 phenotypes. Please clarify what this means. Is it cell movement? Or is it the shape of the tissues? What does "morphological movements" really mean and how does that affect the formation of the EP by the second stream of NCCs? 

      We have revised this sentence to improve clarity. Line 416.

      (5) In the first submission, only 1 out of 142 calpain-overexpressing animals phenocopied dact1/2 mutants and that was a major concern regarding the functional significance of calpain 8 in this context. In the revised manuscript, the authors demonstrated that more embryos developed the phenotype when they are heterozygous for both dact1/2. While this is encouraging, it is interesting that the same phenomenon was not observed in the dact1-/-; dact2+/- embryos (Fig. 6D). The authors did not discuss this and should provide some explanation. The authors should also discuss sufficiency vs requirement tested in this experiment. However, given that this is the most novel aspect of the paper, performing experiments to demonstrate requirements would be important. 

      We have added a statement regarding the non-effect in dact1-/-;dact2+/- embryos. Line 568-570. We have also added discussion of sufficiency vs necessity/requirement testing. Line 676-679.

      (6) Related to (5), the authors cited figure 8c when mentioning 0/192 gfp-injected embryos developed EP phenotypes. However, figure 8c is dact1/2 +/- embryos. The numbers also doesn't match the numbers in Figure 8d either. Please add relevant/correct figures. 

      The text has been revised to distinguish between our overexpression experiment in wildtype embryos (data not shown) versus overexpression in dact1/2 double het in cross embryos (Fig 8).

      Minor comments: 

      (1) Fig 1 legend line 1106 "the midbrain (MP)" should be MB 

      Revised line 1250.

      (2) Wntllf2, instead of wnt11f2, (i.e. the letter "l" rather than the number "1") was used in 4 instances, line 144, 515, 527, 1147 

      Revised lines 185, 625, 640,1300.

      (3) The authors replaced ANC with EP in many instances, but ANC is left unchanged in some places and it's not defined in the text. It's first mentioned in line 170.

      Revised line 218.

    1. espond to initiatives for curriculum change so that the new curriculum’s intents are fully realized. The research reviewed in this chapter demonstrates that there is a growing body of knowledge about teaching practices that can improve teachers’ instruction. Because re- search is an ongoing enterprise, supervisors and teachers should stay informed about new developments. However, this does not mean that teachers should abandon the way they currently teach and unconditionally adopt research-validated practices. Rather, practices that are supported by research evidence should be viewed as possible alternatives to a teacher’s current practices. We make this recommendation based on our view of clinical supervision as a process of helping teachers reflect on data (clinical observations, research findings, etc.) and use these reflections to experiment with their instruction for the pur- pose of continuous professional development. NOTES 1. Chall, J. S. (2000). The academic achievement challenge: What really works in the classroom? New York: Guilford Press, p. 180. 2. Schmuck, R. A., & Schmuck, P. A. (2001). Group processes in the classroom (8th ed., pp. 292-293). Boston: McGraw-Hill. 3. Rosenshine, B., & Furst, N. (1973). The use of direct obser- vation to study teaching In R. M. W. Travers (Ed.), Handbook of research on teaching (2nd ed., pp. 122-183). Chicago: Rand McNally. 4. Flanders, N. A. (1970). Analyzing teaching behavior. Read- ing, MA: Addison-Wesley. 5. These studies are reviewed in: Gage, N. L. (1978). The scien- tific basis of the art of teaching. New York: Teachers College Press. 6. Rosenshine, B. V. (1986). Synthesis of research on explicit teaching. Educational Leadership, 43(7), 60-68. 7. Hunter, M. (1984). Knowing, teaching, and supervising. In P. L. Hosford (Ed.), Using what we know about teaching (pp. 169-192), Alexandria, VA: Association for Supervision and Curriculum Development. 8. Rosenshine, “Synthesis,” p. 60. 9. Ibid., p. 62. 10. Bloom, B. S. (Ed.). Taxonomy of educational objectives: The classification of educational goals. Handbook 1: Cognitive do- main. New York: Longman. 11. Cole, N. S, (1990). Conceptions of educational achievement. Educational Researcher, 19(3), 2-7.

      Self-reflection: Teachers develop the ability to reflect on their own practice and make adjustments independently.

    1. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The authors describe a method to probe both the proteins associated with genomic elements in cells, as well as 3D contacts between sites in chromatin. The approach is interesting and promising, and it is great to see a proximity labeling method like this that can make both proteins and 3D contacts. It utilizes DNA oligomers, which will likely make it a widely adopted method. However, the manuscript over-interprets its successes, which are likely due to the limited appropriate controls, and of any validation experiments. I think the study requires better proteomic controls, and some validation experiments of the "new" proteins and 3D contacts described. In addition, toning down the claims made in the paper would assist those looking to implement one of the various available proximity labeling methods and would make this manuscript more reliable to non-experts.

      Strengths:

      (1) The mapping of 3D contacts for 20 kb regions using proximity labeling is beautiful.

      (2) The use of in situ hybridization will probably improve background and specificity.

      (3) The use of fixed cells should prove enabling and is a strong alternative to similar, living cell methods.

      Weaknesses:

      (1) A major drawback to the experimental approach of this study is the "multiplexed comparisons". Using the mtDNA as a comparator is not a great comparison - there is no reason to think the telomeres/centrosomes would look like mtDNA as a whole. The mito proteome is much less complex. It is going to provide a large number of false positives. The centromere/telomere comparison is ok, if one is interested in what's different between those two repetitive elements. But the more realistic use case of this method would be "what is at a specific genomic element"? A purely nuclear-localized control would be needed for that. Or a genomic element that has nothing interesting at it (I do not know of one). You can see this in the label-free work: non-specific, nuclear GO terms are enriched likely due to the random plus non-random labeling in the nucleus. What would a Telo vs general nucleus GSEA look like? (GSEA should be used for quantitative data, no GO). That would provide some specificity. Figures 2G and S4A are encouraging, but a) these proteins are largely sequestered in their respective locations, and b) no validation by an orthogonal method like ChIP or Cut and Run/Tag is used.

      You can also see this in the enormous number of "enriched" proteins in the supplemental volcano plots. The hypothesis-supporting ones are labeled, but do the authors really believe all of those proteins are specific to the loci being looked at? Maybe compared to mitochondria, but it's hard to believe there are not a lot of false positives in those blue clouds. I believe the authors are more seeing mito vs nucleus + Telo than the stated comparison. For example, if you have no labeling in the nucleus in the control (Figures 1C and 2C) you cannot separate background labeling from specific labeling. Same with mito vs. nuc+Telo. It is not the proper control to say what is specifically at the Telo.

      I would like to see a Telo vs nuclear control and a Centromere vs nuc control. One could then subtract the background from both experiments, then contrast Telo vs Cent for a proper, rigorous comparison. However, I realize that is a lot of work, so rewriting the manuscript to better and more accurately reflect what was accomplished here, and its limitations, would suffice.

      (2) A second major drawback is the lack of validation experiments. References to literature are helpful but do not make up for the lack of validation of a new method claiming new protein-DNA or DNA-DNA interactions. At least a handful of newly described proximal proteins need to be validated by an orthogonal method, like ChIP qPCR, other genomic methods, or gel shifts if they are likely to directly bind DNA. It is ok to have false positives in a challenging assay like this. But it needs to be well and clearly estimated and communicated.

      (3) The mapping of 3D contacts for 20 kb regions is beautiful. Some added discussion on this method's benefits over HiC-variants would be welcomed.

      (4) The study claims this method circumvents the need for transfectable cells. However, the authors go on to describe how they needed tons of cells, now in solution, to get it to work. The intro should be more in line with what was actually accomplished.

      (5) Comments like "Compared to other repetitive elements in the human genome...." appear to circumvent the fact that this method is still (apparently) largely limited to repetitive elements. Other than Glopro, which did analyze non-repetitive promoter elements, most comparable methods looked at telomeres. So, this isn't quite the advancement you are implying. Plus, the overlap with telomeric proteins and other studies should be addressed. However, that will be challenging due to the controls used here, discussed above.

      We thank the Reviewer for their careful reading of manuscript and constructive suggestions. We plan to substantially revise the framing and presentation of manuscript to address the concerns raised by all three reviewers.

      Reviewer #2 (Public review):

      Summary

      Liu and MacGann et al. introduce the method DNA O-MAP that uses oligo-based ISH probes to recruit horseradish peroxidase for targeted proximity biotinylation at specific DNA loci. The method's specificity was tested by profiling the proteomic composition at repetitive DNA loci such as telomeres and pericentromeric alpha satellite repeats. In addition, the authors provide proof-of-principle for the capture and mapping of contact frequencies between individual DNA loop anchors.

      Strengths

      Identifying locus-specific proteomes still represents a major technical challenge and remains an outstanding issue (1). Theoretically, this method could benefit from the specificity of ISH probes and be applied to identify proteomes at non-repetitive DNA loci. This method also requires significantly fewer cells than other ISH- or dCas9-based locus-enrichment methods. Another potential advantage to be tested is the lack of cell line engineering that allows its application to primary cell lines or tissue.

      Weaknesses

      The authors indicate that DNA O-MAP is superior to other methods for identifying locus-specific proteomes. Still, no proof exists that this method could uncover proteomes at non-repetitive DNA loci. Also, there is very little validation of novel factors to confirm the superiority of the technique regarding specificity.

      The authors first tested their method's specificity at repetitive telomeric regions, and like other approaches, expected low-abundant telomere-specific proteins were absent (for example, all subunits of the telomerase holoenzyme complex). Detecting known proteins while identifying noncanonical and unexpected protein factors with high confidence could indicate that DNA O-MAP does not fully capture biologically crucial proteins due to insufficient enrichment of locus-specific factors. The newly identified proteins in Figure 1E might still be relevant, but independent validation is missing entirely. In my opinion, the current data cannot be interpreted as successfully describing local protein composition.

      Finally, the authors could have discussed the limitations of DNA O-MAP and made a fair comparison to other existing methods (2-5). Unlike targeted proximity biotinylation methods, DNA O-MAP requires paraformaldehyde crosslinking, which has several disadvantages. For instance, transient protein-protein interactions may not be efficiently retained on crosslinked chromatin. Similarly, some proteins may not be crosslinked by formaldehyde and thus will be lost during preparation (6).

      (1) Gauchier M, van Mierlo G, Vermeulen M, Dejardin J. Purification and enrichment of specific chromatin loci. Nat Methods. 2020;17(4):380-9.

      (2) Dejardin J, Kingston RE. Purification of proteins associated with specific genomic Loci. Cell. 2009;136(1):175-86.

      (3) Liu X, Zhang Y, Chen Y, Li M, Zhou F, Li K, et al. In Situ Capture of Chromatin Interactions by Biotinylated dCas9. Cell. 2017;170(5):1028-43 e19.

      (4) Villasenor R, Pfaendler R, Ambrosi C, Butz S, Giuliani S, Bryan E, et al. ChromID identifies the protein interactome at chromatin marks. Nat Biotechnol. 2020;38(6):728-36.

      (5) Santos-Barriopedro I, van Mierlo G, Vermeulen M. Off-the-shelf proximity biotinylation for interaction proteomics. Nat Commun. 2021;12(1):5015.

      (6) Schmiedeberg L, Skene P, Deaton A, Bird A. A temporal threshold for formaldehyde crosslinking and fixation. PLoS One. 2009;4(2):e4636.

      We thank the Reviewer for their constructive feedback on our work. As noted above, we plan to substantially revise the framing and presentation of manuscript to address the concerns raised by all three reviewers.

      Reviewer #3 (Public review):

      Significance of the Findings:

      The study by Liu et al. presents a novel method, DNA-O-MAP, which combines locus-specific hybridisation with proximity biotinylation to isolate specific genomic regions and their associated proteins. The potential significance of this approach lies in its purported ability to target genomic loci with heightened specificity by enabling extensive washing prior to the biotinylation reaction, theoretically improving the signal-to-noise ratio when compared with other methods such as dCas9-based techniques. Should the method prove successful, it could represent a notable advancement in the field of chromatin biology, particularly in establishing the proteomes of individual chromatin regions - an extremely challenging objective that has not yet been comprehensively addressed by existing methodologies.

      Strength of the Evidence:

      The evidence presented by the authors is somewhat mixed, and the robustness of the findings appears to be preliminary at this stage. While certain data indicate that DNA-O-MAP may function effectively for repetitive DNA regions, a number of the claims made in the manuscript are either unsupported or require further substantiation. There are significant concerns about the resolution of the method, with substantial biotinylation signals extending well beyond the intended target regions (megabases around the target), suggesting a lack of specificity and poor resolution, particularly for smaller loci. Furthermore, comparisons with previous techniques are unfounded since the authors have not provided direct comparisons with the same mass spectrometry (MS) equipment and protocols. Additionally, although the authors assert an advantage in multiplexing, this claim appears overstated, as previous methods could achieve similar outcomes through TMT multiplexing. Therefore, while the method has potential, the evidence requires more rigorous support, comprehensive benchmarking, and further experimental validation to demonstrate the claimed improvements in specificity and practical applicability.

      We thank the Reviewer for providing detailed critiques of our manuscript. As noted above, we plan to substantially revise the framing and presentation of manuscript to address the concerns raised by all three reviewers.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      This paper aims to address the establishment and maintenance of neural circuitry in the case of a massive loss of neurons. The authors used genetic manipulations to ablate the principal projection neurons, the mitral/tufted cells, in the mouse olfactory bulb. Using diphtheria toxin (Tbx21-Cre:: loxP-DTA line) the authors ablated progressively large numbers of M/T cells postnatally. By injecting diphtheria toxin (DT) into the Tbx21-Cre:: loxP-iDTR line, the authors were able to control the timing of the ablation in the adult stage. Both methods led to the successful elimination of a majority of M/TCs by 4 months of age. The authors made a few interesting observations. First, they found that the initial pruning of the remaining M/T cell primary dendrite was unaffected. However, in adulthood, a significant portion of these cells extended primary dendrites to innervate multiple glomeruli. Moreover, the incoming olfactory sensory neuron (OSN) axons, as examined for those expressing the M72 receptor, showed a divergent innervation pattern as well. The authors conclude that M/T cell density is required to maintain the dendritic structures and the olfactory map. To address the functional consequences of eliminating a large portion of principal neurons, the authors conducted a series of behavioral assays. They found that learned odor discrimination was largely intact. On the other hand, mating and aggression were reduced. The authors concluded that learned behaviors are more resilient than innate ones.

      The study is technically sound, and the results are clear-cut. The most striking result is the contrast between the normal dendritic pruning during early development and the expanded dendritic innervation in adulthood. It is a novel discovery that can lead to further investigation of how the single-glomerulus dendritic innervation is maintained. The authors conducted a

      few experiments to address potential mechanisms, but it is inconclusive, as detailed below. It is also interesting to see that the massive neuronal loss did not severely impact learned odor discrimination. This result, together with previous studies showing nearly normal odor discrimination in the absence of large portions of the olfactory bulb or scrambled innervation patterns, attests to the redundancy and robustness of the sensory system. The discussion should take into account these other studies in a historical context.

      Main comments:

      (1) In previous studies, it has been concluded that dendritic pruning unfolds independently, regardless of the innervation pattern or activity of the OSNs. The new observation bolsters this conclusion by showing that a loss of neighboring M/T cells does not affect the developmental process. A more nuanced discussion comparing the results of these studies would strengthen the paper.

      We thank the reviewer for the suggestion. We now include an extended discussion citing relevant previous works in the manuscript (Lines 351-374).

      (2) The authors propose that a certain density of M/T is required to prevent the divergent innervation of primary dendrites, but the evidence is not sufficient to support this proposal. The experiment with low-dose DT injection to ablate a smaller portion of M/T cells did not change the percentage of cells innervating two or more glomeruli. The authors suggest that a threshold must be met, but this threshold is not determined.  

      In our experiments using high-dose DT, we hypothesized that there may be many empty glomeruli (glomeruli not innervated by M/T cells), and as a result, that some of the remaining M/T cells could branch their apical dendrite tuft into multiple empty glomeruli. To test this hypothesis, we carried out another experiment using a lower dose of DT. In this experiment, the fraction of remaining M/T cells was 25% (~10,000 M/T cells), which was higher than with the high DT dose (5%, or around 2,000 M/T cells) , but still significantly lower than wild type mice (~40,000 cells M/T cells). With around 2,000 glomeruli and 10,000 M/T per bulb, it could be expected that each glomerulus would be innervated by ~5 M/T cells (on average). However, we found that the percentage of M/T cells projecting to multiple glomeruli (around 40%) was similar when either 10,000 or 2,000 of M/T remained in the bulb. In addition, it is important to emphasize that even in wt animals with a full set of M/T cells, a small percentage of M/T cells still innervate more than one glomerulus (Lin et al., 2000). Together, these observations suggest that the innervation of multiple glomeruli by M/T cells is not simply due to the presence of empty glomeruli, and that our hypothesis was not correct.

      We have added a comment explaining this issue in the Results section (Lines 200-203).

      (3) The authors suggest that neural activity is not required for this plasticity. The evidence was derived primarily from naris occlusion and neuronal silencing using Kir2.1. While the results are consistent with the notion, it is a rather narrow interpretation of how neural activity affects circuit configuration. Perturbation of neural activity also entails an increase in firing. Inducing the activity of the neurons may alter this plasticity. Silencing per se may induce a homeostatic response that expands the neurite innervation pattern to increase synaptic input to compensate for the loss of activity. Thus, further silencing the cells may not reduce multiglomerular innervation, but an increased activity may.

      The experiments with Kir2.1 demonstrate that the structural plasticity observed after reducing the total number of M/T cells in an animal is not regulated by the firing action potentials in the remaining cells. Instead, this experiment indicates that the observed structural plasticity may be regulated by other types of mechanisms (including increased synaptic excitation as suggested by the reviewer) that do not require the firing of action potentials in M/T cells. 

      We now have included a comment regarding this point (Lines 243-247).  

      (4) There is a discrepancy between this study and the one by Fujimoto et al. (Developmental Cell; 2023), which shows that not only glutamatergic inputs to the primary dendrite can facilitate pruning of remaining dendrites but also Kir2.1 overexpression can significantly perturb dendritic pruning. This discrepancy is not discussed by the authors.

      We agree that it would be useful to contrast these two works.

      In our experiments, performed in adult animals, we blocked sensory input by performing naris occlusion before we induced ablation of M/T cells. In a separate experiment, also in adult animals, we expressed the Kir2.1 channel, to reduce the ability of neurons to fire action potentials. With both types of manipulations, we observed that the ablation of a large fraction of M/T cells still caused the remaining M/T cells to maintain a single apical dendrite that sprouts several new tufts towards multiple glomeruli. A recent paper (Fujimoto et al., 2023)) in which Kir2.1 was expressed in a large percentage of M/T starting during embryonic development showed that these “silent” M/T cells failed to prune their arbors to a single dendrite. In aggregate, these observations indicate that action potentials are necessary for the normal pruning that occurs during perinatal development (Fujimoto et al., 2023), but are not required for the expansion of dendritic trees caused by ablating a large fraction of M/T cells in adult animals (our current manuscript).

      We have now explained the differences between both studies in the manuscript (Lines 427-439).

      (5) An alternative interpretation of the discrepancy between the apparent normal pruning by p10 and expanded dendritic innervation in adulthood is that there are more cells before P10, when ~25% of M/T cells are present, but at a later date only 1-3% are present. 

      The relationship between the number of M/T cells and single glomerulus innervation has not been explored during postnatal development. It would be important to test this hypothesis.

      We agree with this comment, and in lines 375-381 we discuss the discrepancy between normal refinement during development, and dendritic sprouting in adults.

      Cre is expressed in M/T cells and it induces DTA expression starting around P0. The elimination of M/T cells starts at this time, and continues until by P10, when more than 75% of M/T have been eliminated. At P21 more than 90% of M/T have been eliminated, and their number remains stable thereafter.

      Pruning of the dendrites of M/T cells starts at P0 and it is mostly complete by P10. Therefore, it is possible that between P0 and P7, when dendrites are being pruned, the number of M/T cells remaining in the bulb is still over a threshold that does not interfere with the process of normal dendrite pruning. We agree that it would be very informative to perform additional experiments in the future where a large set of M/T cells could be ablated before pruning occurs (ideally before P0). 

      (6) The authors attribute the change in the olfactory map to the loss of M/T cells. Another obvious possibility is that the diffused projection is a response to the change in the olfactory bulb size. With less space to occupy, the axons may be forced to innervate neighboring glomeruli. It is not known how the total number of glomeruli is affected. This question could be addressed by tracking developmental changes in bulb volume and glomerular numbers.

      Certainly, this is a possibility, and we have now included a comment on this regard in the manuscript (Lines 473-480). 

      We believe that there are three likely scenarios that could account for these observations:

      (a) After ablating M/T cells, the tufts of the remaining M/T cells sprout into multiple glomeruli, and this causes the axons of OSNs to project into multiple glomeruli.

      (b) Ablating M/T cells may cause changes in other OB cells that make synapses in the glomeruli (ETCs, PGCs, sAC, etc…), and the misrouting of OSN axons that we observed in our experiments may be a secondary effect caused by the elimination of M/T cells.

      (c) After ablating the majority of M/T cells, the olfactory bulb gets reduced in size, and the axons of OSNs find it difficult to precisely converge on a target that now has become smaller. As a result, the axons of OSNs fail to converge on single glomeruli.

      (7) The retained ability to discriminate odors upon reinforced training is not surprising in light of a number of earlier studies. For example, Slotnick and colleagues have shown that rats losing ~90% of the OB can retain odor discrimination. Weiss et al have shown that humans without an olfactory bulb can perform normal olfactory tasks. Gronowitz et al have used theoretical prediction and experimental results to demonstrate that perturbing the olfactory map does not have a major impact on olfactory discrimination. Fleischmann et al have shown that mice with a monoclonal nose can discriminate odors. The authors should discuss their results in these contexts.

      We apologize for this important oversight - we now include a more elaborate discussion including the relevant references as suggested in the manuscript (Line 483-496).

      (8) It should be noted that odor discrimination resulting from reinforcement training does not mean normal olfactory function. It is a highly artificial situation as the animals are overtrained. It should not be used as a measure of the robustness of the olfactory sense. Natural odor discrimination (without training), detection threshold, and innate appetitive/aversive response to certain odors may be affected. These experiments were not conducted.

      We agree that the standard tests commonly used to measure olfactory function require substantial training, and thus, are quite artificial. However, these tests are used because they allow a more precise quantification of olfactory function than those relying on natural behaviors.  

      We have now included a few sentences to address this point in the results (Lines 321322) and discussion sections (Lines 541-543).

      (9) The social behaviors were conducted using relatively coarse measures (vaginal plug and display of aggression). Moreover, these behaviors are most likely affected by the disruption of the AOB mitral cells and have little to do with the dendritic pruning process described in the paper. It is misleading to lump social behaviors with innate responses to odors.

      This point follows the same logic as the previous one. The olfactory tests that rely on natural behaviors are quite coarse and difficult to quantify. In contrast, the olfactory tests using apparatuses such as olfactometers can be quantified with precision, but they are artificial. We agree that some of the naturalistic behaviors that we studied such as mating or aggression may depend to a large extent on the AOB (although it is possible that the MOB may also be involved in these tasks to a degree). In our initial version of the manuscript, we commented on the anticipated relative involvement of the MOB and AOB in the studied tasks, but we have now added some additional sentences to make this point clearer. In addition, we now add a comment indicating that it is possible that the abnormal behaviors could simply be due to a reduction in the number of AOB M/T cells (~98.5% and ~ 85% elimination of M/T cells in the AOB in Tbx::DTA and Tbx::iDTR mice, respectively), regardless of the abnormal dendritic pruning of main OB M/T cells (Lines 530-534).

      See Figure 5E - M/T cells in AOB (Lines 1238-1239). 

      Reviewer #2 (Public Review):

      The authors make the interesting observation that the developmental refinement of apical M/T cell dendrites into individual glomeruli proceeds normally even when the majority of neighboring M/T cells are ablated. At later stages, the remaining neurons develop additional dendrites that invade multiple glomeruli ectopically, and similarly, OSN inputs to glomeruli lose projection specificity as well. The authors conclude that the normal density of M/T neurons is not required for developmental refinement, but rather for maintaining specific connectivity in adults.

      The observations are indeed quite striking; however, the authors' conclusions are not entirely supported by the data.

      (1) It is unclear whether the expression of diphtheria toxin that eventually leads to the ablation of the large majority of M/T neurons compromises the cell biology of the remaining ones.

      DT is an extremely potent toxin that kills cells by inhibiting proteins translation, and it has been demonstrated that the presence of a single DT molecule in a cell is sufficient to kill it, because of its highly efficient catalytic activity. Accordingly, previous experiments have shown that DT kills cells within a few hours after its appearance in the cytoplasm (Yamaizumi et al., 1978). In other words, all the published evidence suggests that if a cell is exposed to the action of DT, that cell will die shortly. There is no evidence that cells exposed to DT can survive and experience long-term effects. Finally, previous works have not observed any long-term changes in neurons directly caused by the actions of DT (Johnson et al., 2017).

      (2) The authors interpret the growth of ectopic dendrites later in life as a lack of maintenance of dendrite structure; however, maybe the observed changes reflect actually adaptations that optimize wiring for extremely low numbers of M/T neurons. The finding that olfactory behavior was less affected than predicted supports this interpretation.

      We do not know the cellular or molecular mechanisms that explain why reducing the density of M/T cells is followed by the growth of ectopic dendrites from the remaining M/T cells. We agree that the functional outcome of growing ectopic dendrites may result in an optimization of wiring in the bulb and could explain why olfactory function is relatively preserved. We now include a comment regarding this possibility (Lines 513-525).   

      (3) The number of remaining M/T neurons is much higher at P10 than later. Can the relatively large number of remaining neurons (or their better health status) be the reason that dendrites refine normally at the early developmental stages rather than a (currently unknown) developmental capacity that preserves refinement?

      We thank the reviewer for the suggestion, which was also raised by reviewer 1. 

      We agree with this comment, and in lines 375-381 we discuss the discrepancy between normal refinement during development, and dendritic sprouting in adults.

      Cre is expressed in M/T cells and it induces DTA expression starting around P0. The elimination of M/T cells starts at this time, and continues until by P10, when more than 75% of M/T have been eliminated. At P21 more than 90% of M/T have been eliminated, and their number remains stable thereafter.

      Pruning of the dendrites of M/T cells starts at P0 and it is mostly complete by P10. Therefore, it is possible that between P0 and P7, when dendrites are being pruned, the number of M/T cells remaining in the bulb is still over a threshold that does not interfere with the process of normal dendrite pruning. We agree that it would be very informative to perform additional experiments in the future where a large set of M/T cells could be ablated before pruning occurs (ideally before P0). 

      (4) While the effect of reduced M/T neuron density on both M/T dendrites and OSN axons is described well, the relationship between both needs to be characterized better: Is one effect preceding the other or do they occur simultaneously? Can one be the consequence of the other?

      Previous works have demonstrated that disrupting the topographic projection of the OSN axons has no effect on the structure of the apical dendrite of M/T cells (Ma et al., 2014; Nishizumi et al., 2019). Our experiments ablating a large fraction of M/T cells suggest that they are necessary for the correct targeting of OSN axons into the bulb. However, our experiments do not allow us to tell apart these 2 scenarios: 

      (a) the ablation of a large fraction of M/T cells directly causes the sprouting of the apical dendrite of M/T cells, and that this sprouting in turn causes the abnormal projection of OSN axons onto the bulb. 

      (b) the ablation of a large fraction of M/T cells first causes the axons of OSN to project abnormally onto multiple glomeruli in the bulb, and this in turn causes the dendrite of remaining M/T cells to sprout onto multiple glomeruli. 

      We now include a comment on the manuscript explaining this point. (Lines 473-492)

      (5) Page 7: the observation that not all neurons develop additional dendrites is not a sign of differences between cell types, it may be purely stochastic.

      This is correct, and we mention these 2 scenarios in the discussion (Line 407-408). 

      (6) Page 8: the fact that activity blockade did not affect the formation of ectopic dendrites does not suggest that the process is not activity-dependent: both manipulations have the same effect and may just mask each other.

      The experiments with Kir2.1 demonstrate that the structural plasticity observed after reducing the total number of M/T cells in an animal is not regulated by the firing action potentials in the remaining cells. Instead, this experiment indicates that the observed structural plasticity may be regulated by other types of mechanisms (including increased synaptic excitation as suggested by the reviewer) that do not require the firing of action potentials in M/T cells. 

      We now have included a comment regarding this point (Lines 243-247).  

      (7) It remains unclear how the observed structural changes can explain the behavioral effects.

      We agree that the relationship between structural changes and behavior was not appropriately explained in our manuscript. Our manipulations cause two major changes in the olfactory system, one primary, and several secondary. The primary change is a large reduction in the number of M/T cells both in the MOB and AOB. This reduction in M/T cell number triggers significant secondary changes in the connectivity of the bulb, including an abnormal projection of OSNs onto the OB, and the growth of ectopic dendrites from the remaining M/T cells into multiple glomeruli.

      The behavioral abnormalities displayed by these mice is ultimately caused by the reduction in the number of M/T cells, but it is likely that the secondary structural changes could regulate some of the behavioral phenomena that we observed. For example, in principle, it is possible that the ectopic dendrites innervating several glomeruli could help the bulb to perceive smells with a much reduced number of M/T cells. On the other hand, this promiscuous growth of dendrites into multiple glomeruli could make it more difficult for the animals to discriminate between smells. The same argument could be made about the fact that OSN axons project onto multiple glomeruli: we simply do not know if this change helps or makes it more difficult for the animal to detect smells.  

      We now include a comment regarding this issue (Lines 513-525).   

      Reviewer #1 (Recommendations For The Authors):

      Additional experiments and a more thorough discussion of the results, as suggested in the public review, would significantly strengthen the paper. Below are some specific parts that need to be addressed.

      There is a lack of information on how M/T cell numbers are quantified. Without the information, it is difficult to evaluate the claim. Using the tdTomato signal may miss cells that are not labeled due to the transgenic effect. 

      Although we cannot conclude that we are identifying the complete set of M/T cells (because the transgenic lines may fail to label some M/T cells), the number of M/T cells that we observed is similar to that previously reported (Richard et al., 2010). This concern has been included in the Results section (Lines 121-124).

      A more detailed description about M/T cells quantification has been added into the method section (Lines 627-632).

      There is a lack of information on the timeline of treatment and how measurement of the olfactory bulb volume is conducted.

      We now include a more detailed description of how the volume of the OB was measured in the methods (Lines 621-623).

      The volume measurement is inconsistent with the pictures shown. In Figure 1, supplemental data 2 panels B and C, it appears that the bulbs in DTA and DTR mice are about half in length in each dimension. This would translate into ~1/8 of the volume of the control mice.

      We measured the volume of the bulbs based on the Neurolucida reconstructions, and we observed that in both DTA and iDTR mice the volumes of their bulbs are roughly 50% compared to a wild type mouse. In Figure 1 - figure supplement 2 the sections that were shown for wild type, DTA and iDTR mice were not taken at the same position in the bulb, and this gave the impression that the bulbs from DTA and iDTR were much smaller than they really are. We now show sections for these three animals at equivalent positions in the bulb. 

      Figure 1 E and F have no legend.

      We apologize for this mistake - we have now added the legend for Figures 1E and F (Lines 1009-1013).

      Figure 3, supplemental data 2, it is not clear what the readers should be looking at. The data is confusing even for experts in the field. The authors should describe the figures more clearly, pointing out what they are supposed to show.

      We apologize for this, and we have now added a more detailed description of Figure3 – figure supplement 2 (Lines 1153-1167).

      In several figures, it is not clearly written what the comparisons were for where there are indications of statistical significance above the bars.

      We have now included a more detailed description of the statistics comparison in the figure legends.

      AAV serotype should be specified.

      The AAV serotype used to label M/T cells was the AAV-PHP.eB. We have added this information in the methods section of the manuscript. 

      Reviewer #2 (Recommendations For The Authors):

      Minor points

      Page 5, para 2: "The decrease in neuronal plasticity with age": it is unclear what "the decrease" refers to.

      We have changed this sentence in the text to make it clear:

      “The decrease in structural plasticity of M/T cells after apical dendrite refinement (Mizrahi and Katz, 2003),….”

      Line 146-148

      Is there a quantification of the effect of Kir2.1 overexpression alone (example shown in Figure 3D)?

      We did an experiment in IDTR animals in which a fraction of M/T cells expressed Kir2.1, and we split these animals in 2 groups: (a) animals that received an injection of DT, and (b) animals that did not receive any DT. We quantified the effect of Kir2.1 on M/T cells from animals that received DT injection (with an ablation of around of 90% of M/T cells) and we did not observe any clear statistically significant differences between cells expressing Kir2.1 or neurons that did not express Kir2.1 from other iDTR animals that also received DT injections. We did not quantify the possible effects of kir2.1 in the group of animals that did not receive DT because on a first inspection we did not observe any clear differences between Kir2.1 cells and neighboring wild type cells. 

      References

      Fujimoto S, Leiwe MN, Aihara S, Sakaguchi R, Muroyama Y, Kobayakawa R, Kobayakawa K, Saito T, Imai T. 2023. Activity-dependent local protection and lateral inhibition control synaptic competition in developing mitral cells in mice. Dev Cell S1534-5807(23)00237-X. doi:10.1016/j.devcel.2023.05.004

      Johnson RE, Tien N-W, Shen N, Pearson JT, Soto F, Kerschensteiner D. 2017. Homeostatic plasticity shapes the visual system’s first synapse. Nat Commun 8:1220. doi:10.1038/s41467-017-01332-7

      Lin DM, Wang F, Lowe G, Gold GH, Axel R, Ngai J, Brunet L. 2000. Formation of precise connections in the olfactory bulb occurs in the absence of odorant-evoked neuronal activity. Neuron 26:69–80. doi:10.1016/s0896-6273(00)81139-3

      Ma L, Wu Y, Qiu Q, Scheerer H, Moran A, Yu CR. 2014. A developmental switch of axon targeting in the continuously regenerating mouse olfactory system. Science 344:194–197. doi:10.1126/science.1248805

      Nishizumi H, Miyashita A, Inoue N, Inokuchi K, Aoki M, Sakano H. 2019. Primary dendrites of mitral cells synapse unto neighboring glomeruli independent of their odorant receptor identity. Commun Biol 2:1–12. doi:10.1038/s42003-018-0252-y

      Richard MB, Taylor SR, Greer CA. 2010. Age-induced disruption of selective olfactory bulb synaptic circuits. Proc Natl Acad Sci U S A 107:15613–15618. doi:10.1073/pnas.1007931107

      Yamaizumi M, Mekada E, Uchida T, Okada Y. 1978. One molecule of diphtheria toxin fragment A introduced into a cell can kill the cell. Cell 15:245–250. doi:10.1016/0092-8674(78)90099-5

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Freas et al. investigated if the exceedingly dim polarization pattern produced by the moon can be used by animals to guide a genuine navigational task. The sun and moon have long been celestial beacons for directional information, but they can be obscured by clouds, canopy, or the horizon. However, even when hidden from view, these celestial bodies provide directional information through the polarized light patterns in the sky. While the sun's polarization pattern is famously used by many animals for compass orientation, until now it has never been shown that the extremely dim polarization pattern of the moon can be used for navigation. To test this, Freas et al. studied nocturnal bull ants, by placing a linear polarizer in the homing path on freely navigating ants 45 degrees shifted to the moon's natural polarization pattern. They recorded the homing direction of an ant before entering the polarizer, under the polarizer, and again after leaving the area covered by the polarizer. The results very clearly show, that ants walking under the linear polarizer change their homing direction by about 45 degrees in comparison to the homing direction under the natural polarization pattern and change it back after leaving the area covered by the polarizer again. These results can be repeated throughout the lunar month, showing that bull ants can use the moon's polarization pattern even under crescent moon conditions. Finally, the authors show, that the degree in which the ants change their homing direction is dependent on the length of their home vector, just as it is for the solar polarization pattern. 

      The behavioral experiments are very well designed, and the statistical analyses are appropriate for the data presented. The authors' conclusions are nicely supported by the data and clearly show that nocturnal bull ants use the dim polarization pattern of the moon for homing, in the same way many animals use the sun's polarization pattern during the day. This is the first proof of the use of the lunar polarization pattern in any animal.

      Reviewer #2 (Public Review): 

      Summary: 

      The authors aimed to understand whether polarised moonlight could be used as a directional cue for nocturnal animals homing at night, particularly at times of night when polarised light is not available from the sun. To do this, the authors used nocturnal ants, and previously established methods, to show that the walking paths of ants can be altered predictably when the angle of polarised moonlight illuminating them from above is turned by a known angle (here +/- 45 degrees).

      Strengths: 

      The behavioural data are very clear and unambiguous. The results clearly show that when the angle of downwelling polarised moonlight is turned, ants turn in the same direction. The data also clearly show that this result is maintained even for different phases (and intensities) of the moon, although during the waning cycle of the moon the ants' turn is considerably less than may be expected.

      Weaknesses: 

      The final section of the results - concerning the weighting of polarised light cues into the path integrator - lacks clarity and should be reworked and expanded in both the Methods and the Results (also possibly with an extra methods figure). I was really unsure of what these experiments were trying to show or what the meaning of the results actually are.

      Rewrote these sections and added figure panel to Figure 6.

      Impact: 

      The authors have discovered that nocturnal bull ants while homing back to their nest holes at night, are able to use the dim polarised light pattern formed around the moon for path integration. Even though similar methods have previously shown the ability of dung beetles to orient along straight trajectories for short distances using polarised moonlight, this is the first evidence of an animal that uses polarised moonlight in homing. This is quite significant, and their findings are well supported by their data.

      Reviewer #3 (Public Review): 

      Summary: 

      This manuscript presents a series of experiments aimed at investigating orientation to polarized lunar skylight in a nocturnal ant, the first report of its kind that I am aware of.

      Strengths: 

      The study was conducted carefully and is clearly explained here. 

      Weaknesses: 

      I have only a few comments and suggestions, that I hope will make the manuscript clearer and easier to understand.

      Time compensation or periodic snapshots 

      In the introduction, the authors compare their discovery with that in dung beetles, which have only been observed to use lunar skylight to hold their course, not to travel to a specific location as the ants must. It is not entirely clear from the discussion whether the authors are suggesting that the ants navigate home by using a time-compensated lunar compass, or that they update their polarization compass with reference to other cues as the pattern of lunar skylight gradually shifts over the course of the night - though in the discussion they appear to lean towards the latter without addressing the former. Any clues in this direction might help us understand how ants adapted to navigate using solar skylight polarization might adapt use to lunar skylight polarization and account for its different schedule. I would guess that the waxing and waning moon data can be interpreted to this effect.

      Added a paragraph discussing this distinction in mechanisms and the limits of the current data set in untangling them. An interesting topic for a follow up to be sure.

      Effects of moon fullness and phase on precision 

      As well as the noted effect on shift magnitudes, the distributions of exit headings and reorientations also appear to differ in their precision (i.e., mean vector length) across moon phases, with somewhat shorter vectors for smaller fractions of the moon illuminated. Although these distributions are a composite of the two distributions of angles subtracted from one another to obtain these turn angles, the precision of the resulting distribution should be proportional to the original distributions. It would be interesting to know whether these differences result from poorer overall orientation precision, or more variability in reorientation, on quarter moon and crescent moon nights, and to what extent this might be attributed to sky brightness or degree of polarization.

      See below for response to this and the next reviewer comment

      N.B. The Watson-Williams tests for difference in mean angle are also sensitive to differences in sample variance. This can be ruled out with another variety of the test, also proposed by Watson and Williams, to check for unequal variances, for which the F statistic is = (n2-1)*(n1-R1) / (n1-1)*(n2-R2) or its inverse, whichever is >1. 

      We have looked at the amount of variance from the mean heading direction in terms of both the shifts and the reorientations and found no significant difference in variance between all relevant conditions. It is possible (and probably likely) that with a higher n we might find these differences but with the current data set we cannot make statistical statements regarding degradations in navigational precision.  

      As an additional analysis to address the Watson-Williams test‘s sensitivity to changes in variance, we have added var test comparisons for each of the comparisons, which is a well-established test to compare variance changes. None of these were significantly different, suggesting the observed differences in the WW tests are due to changes in the mean vector and not the distribution. We have added this test to the text.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      I have only very few minor suggestions to improve the manuscript: 

      (1) While I fully agree with the authors that their study, to the best of my knowledge, provides the first proof (in any animal) of the use of the moon's polarization pattern, the many repetitions of this fact disturb the flow of the text and could be cut at several instances. 

      Yes, it is indeed repeated to an annoying degree. 

      We have removed these beyond bookending mentions (Abstract and Discussion).

      (2) In my opinion, the authors did not change the "ambient polarization pattern" when using the linear polarization filter (e.g., l. 55, 170, 177 ...). The linear polarizer presents an artificial polarization pattern with a much higher degree of polarization in comparison to the ambient polarization pattern. I would suggest re-phrasing this, to emphasize the artificial nature of the polarization pattern under the polarizer.

      We have made these suggested changes throughout the text to clarify. We no longer say the ambient pattern was   

      (3) Line 377: I do not see the link between the sentence and Figure 7 

      Changed where in the discussion we refer to Figure 7.

      (4) Figure 7 upper part: In my opinion, the upper part of Figure 7 does not add any additional value to the illustration of the data as compared to Figure 5 and could be cut.

      We thought it might be easier for some reader to see the shifts as a dial representation with the shift magnitude converted to 0-100% rather than the shifts in Figure 5. This makes it somewhat like a graphical abstract summarising the whole study.

      I agree that Figure 5 tells the same story but a reader that has little background in directional stats might find figure 7 more intuitive. This was the intent at least. 

      If it becomes a sticking point, then we can remove the upper portion.  

      Reviewer #2 (Recommendations For The Authors): 

      MINOR CORRECTIONS AND QUERIES 

      Line 117: THE majority 

      Corrected

      Lines 129-130: Do you have a reference to support this statement? I am unaware of experiments that show that homing ants count their steps, but I could have missed it.

      We have added the references that unpack the ant pedometer.  

      Line 140: remove "the" in this line. 

      Removed

      Line 170: We need more details here about the spectral transmission properties of the polariser (and indeed which brand of filter, etc.). For instance, does it allow the transmission of UV light?

      Added

      Line 239: "...tested identicALLY to ...." 

      Corrected

      Lines 242-258 (Vector testing): I must admit I found the description of these experiments very difficult to follow. I read this section several times and felt no wiser as a result. I think some thought needs to be given to better introduce the reader to the rationale behind the experiment (e.g., start by expanding lines 243-246, and maybe add a methods figure that shows the different experimental procedures).

      I have rewritten this section of the methods to clearly state the experiment rational and to be clearer as to the methodology.

      Also Added a methods panel to Figure 6.

      Line 247: "reoriented only halfway". What does this mean? Do you mean with half the expected angle?

      Yes, this is a bit unclear. We have altered for clarity:

      ‘only altered their headings by about half of the 45° e-vector shift (25.2°± 3.7°), despite being tested on near-full-moon nights.’

      Results section (in general): In Figure 1 (which is a very nice figure!) you go to all the trouble of defining b degrees (exit headings) and c degrees (reorientation headings), which are very intuitive for interpreting the results, and then you totally abandon these convenient angles in favour of an amorphous Greek symbol Phi (Figs. 2-6) to describe BOTH exit and reorientation headings. Why?? It becomes even more confusing when headings described by Phi can be typically greater than 300 degrees in the figures, but they are never even close to this in the text (where you seem to have gone back to using the b degrees and c degrees angles, without explicitly saying so). Personally, I think the b degrees and c degrees angles are more intuitive (and should be used in both the text and the figures), but if you do insist on using Phi then you should use it consistently in both the text and the figures. 

      Replaced Phi with b° and c° for both figures and in the text.

      Finally, for reorientation angles in Figure 4A, you say that the angle is 16.5 degrees. This angle should have been 143.5 degrees to be consistent with other figures. 

      Yes, the reorientation was erroneously copied from the shift data (it is identical in both the +45 shift and reorientation for Figure 4A). This has now been corrected

      Line 280, and many other lines: Wherever you refer to two panels of the same figure, they should be written as (say) Figure 2A, B not Figure 2AB.

      Changed as requested throughout the text.

      Line 295 (Waxing lunar phases): For these experiments, which nest are you using? 1 or 2?

      We have added that this is nest 1. 

      Figure 3B: The title of this panel should be "Waxing Crescent Moon" I think. 

      Ah yes, this is incorrect in the original submission. I have fixed this.

      Lines 312-313: Here it sounds as though the ants went right back to the full +/- 45 degrees orientations when they clearly didn't (it was -26.6 degrees and 189.9 degrees). Maybe tone the language down a bit here.

      Changed this to make clear the orientation shift is only ‘towards’ the ambient lunar e-vector.

      Line 327: Insert "see" before "Figure 5" 

      Added

      Line 329: See comment for Line 295. 

      We have added that this is nest 1. 

      Lines 357-373 (Vector testing): Again, because of the somewhat confusing methods section describing these experiments, these results were hard to follow, both here and in the Discussion. I don't really understand what you have shown here. Re-think how you present this (and maybe re-working the Methods will be half the battle won). 

      I have rewritten these sections to try to make clear these are ant tested with differences in vector length 6m vs. 2m, tested at the same location. Hopefully this is much clearer, but I think if these portions remain a bit confusing that a full rename of the conditions is in order. Something like long vector and short vector would help but comes with the problem of not truly describing what the purpose of the test is which is to control for location, thus the current condition names. As it stands, I hope the new clarifications adequately describe the reasoning while keeping the condition names. Of course, I am happy to make more changes here as making this clear to readers is important for driving home that the path integrator is in play.

      See current change to results as an example: ‘Both forgers with a long ~6m remaining vector (Halfway Release), or a short ~2m remaining vector (Halfway Collection & Release), tested at the same location_,_ exhibited significant shifts to the right of initial headings when the e-vector was rotated clockwise +45°.’

      Line 361: I think this should be 16.8 not 6.8 

      Yes, you are correct. Fixed in text (16.8).

      Line 365: I think this should be -12.7 not 12.7 

      Yes, you are correct. Fixed in text (–12.7).

      Line 408: "morning twilight". Should this be "morning solar twilight"? Plus "M midas" should be "M. midas"

      Added and fixed respectively.

      Line 440. "location" is spelt wrong. 

      Fixed spelling.

      Line 444: "...WITH longer accumulated vectors, ..." 

      Added ‘with’ to sentence. 

      Line 447: Remove "that just as"

      Removed.

      Line 448: "Moonlight polarised light" should be "Polarised moonlight" 

      Corrected.

      Lines 450-453: This sentence makes little sense scientifically or grammatically. A "limiting factor" can't be "accomplished". Please rephrase and explain in more detail.

      This sentence has been rephrased:

      ‘The limiting factors to lunar cue use for navigation would instead be the ant’s detection threshold to either absolute light intensity, polarization sensitivity and spectral sensitivity. Moonlight is less UV rich compared to direct sunlight and the spectrum changes across the lunar cycle (Palmer and Johnsen 2015).’

      Line 474: Re-write as "... due to the incorporation of the celestial compass into the path integrator..."

      Added.

      Reviewer #3 (Recommendations For The Authors): 

      Minor comments 

      Line 84 I am not sure that we can infer attentional processes in orientation to lunar skylight, at least it has not yet been investigated.

      Yes, this is a good point. We have changed ‘attend’ to ‘use’.  

      Line 90 This description of polarized light is a little vague; what is meant by the phrase "waves which occur along a single plane"? (What about the magnetic component? These waves can be redirected, are they then still polarized? Circular polarization?). I would recommend looking at how polarized light is described in textbooks on optics.

      Response: We have rewritten the polarised light section to be clearer using optics and light physics for background. 

      Line 92 The phrase "e-vector" has not been described or introduced up to this point.

      We now introduce e-vector and define it. 

      ‘Polarised light comprises light waves which occur along a single plane and are produced as a by-product of light passing through the upper atmosphere (Horváth & Varjú 2004; Horváth et al., 2014). The scattering of this light creates an e-vector pattern in the sky, which is arranged in concentric circles around the sun or moon's position with the maximum degree of polarisation located 90° from the source. Hence when the sun/moon is near the horizon, the pattern of polarised skylight is particularly simple with uniform direction of polarisation approximately parallel to the north-south axes (Dacke et al., 1999, 2003; Reid et al. 2011; Zeil et al., 2014).’

      Happy to make further changes as well.  

      Line 107 Diurnal dung beetles can also orient to lunar skylight if roused at night (Smolka et al., 2016), provided the sky is bright enough. Perhaps diurnal ants might do the same?

      Added the diurnal dung beetles mention as well as the reference.

      Also, a very good suggestion using diurnal bull ants.

      Line 146 Instead of lunar calendar the authors appear to mean "lunar cycle". 

      Changed

      Line 165 In Figure 1B, it looks like visual access to the sky was only partly "unobstructed". Indeed foliage covers as least part of the sky right up to the zenith.

      We have added that the sky is partially obstructed. 

      Line 179 This could also presumably be checked with a camera? 

      For this testing we tried to keep equipment to a minimum for a single researcher walking to and from the field site given the lack of public transport between 1 and 4am. But yes, for future work a camera based confirmation system would be easier. 

      Line 243 The abbreviation "PI" has not been described or introduced up to this point.

      Changes to ‘path integration derived vector lengths….’

      Line 267 The method for comparing the leftwards and rightwards shifts should be described in full here (presumably one set of shifts was mirrored onto the other?).

      We have added the below description to indicate the full description of the mirroring done to counterclockwise shifts.

      ‘To assess shift magnitude between −45° and +45° foragers within conditions, we calculated the mirror of shift in each −45° condition, allowing shift magnitude comparisons within each condition. Mirroring the −45° conditions was calculated by mirroring each shift across the 0° to 180° plane and was then compared to the corresponding unaltered +45 condition.’

      Discussion Might the brightness and spectrum of lunar skylight also play a role here?

      We have added a section to the discussion to mention the aspects of moonlight which may be important to these animals, including the spectrum, brightness and polarisation intensity.  

      Line 451 The sensitivity threshold to absolute light intensity would not be the only limiting factor here. Polarization sensitivity and spectral sensitivity may also play a role (moonlight is less UV rich than sunlight and the spectrum of twilight changes across the lunar cycle: Palmer & Johnsen, 2015). 

      Added this clarification.

      Line 478 Instead of the "masculine ordinal" symbol used (U+006F) here a degree symbol (U+00B0) should be used.

      Ah thank you, we have replaced this everywhere in the text.  

      Line 485 It should be possible to calculate the misalignment between polarization pattern before and after this interruption of celestial cues. Does the magnitude of this misalignment help predict the size of the reorientation?

      Reorientations are highly correlated with the shift size under the filter, which makes sense as larger shifts mean that foragers need to turn back more to reorient to both the ambient pattern and to return to their visual route. Reorientation sizes do not show a consistent reduction compared to under-the-filter shifts when the lunar phase is low and is potentially harder to detect.

      I have reworked this line in the text as I do not think there is much evidence for misalignment and it might be more precise to say that overnight periods where the moon is not visible may adversely impact the path integrator estimate, though it is currently unknown the full impact of this celestial cue gap of if other cues might also play a role.

      Line 642 "from their" should be "relative to" 

      Changed as requested

      Figure 1B Some mention should be made of the differences in vegetation density. 

      Added a sentence to the figure caption discussing the differences in both vegetation along the horizon and canopy cover.

      Figures 2-6 A reference line at 0 degrees change might help the reader to assess the size of orientation changes visually. Confidence intervals around the mean orientation change would also help here.

      We have now added circular grid lines and confidence intervals to the circular plots. These should help make the heading changes clear to readers.

    1. Author response:

      The following is the authors’ response to the original reviews.

      eLife Assessment <br /> This valuable study is a companion to a paper introducing a theoretical framework and methodology for identifying Cancer Driving Nucleotides (CDNs). While the evidence that recurrent SNVs or CDNs are common in true cancer driver genes is solid, the evidence that many more undiscovered cancer driver mutations will have CDNs, and that this approach could identify these undiscovered driver genes with about 100,000 samples, is limited. 

      Same criticism as in the eLife assessment of eLife-RP-RA-2024-99340 (https://elifesciences.org/reviewed-preprints/99340). Hence, please refer to the responses to the companion paper.

      Public Reviews:

      Reviewer #1 (Public Review):

      The study investigates Cancer Driving Nucleotides (CDNs) using the TCGA database, finding that these recurring point mutations could greatly enhance our understanding of cancer genomics and improve personalized treatment strategies. Despite identifying 50-150 CDNs per cancer type, the research reveals that a significant number remain undiscovered, limiting current therapeutic applications, and underscoring the need for further larger-scale research.

      Strengths:

      The study provides a detailed examination of cancer-driving mutations at the nucleotide level, offering a more precise understanding than traditional gene-level analyses. The authors found a significant number of CDNs remain undiscovered, with only 0-2 identified per patient out of an expected 5-8, indicating that many important mutations are still missing. The study indicated that identifying more CDNs could potentially significantly impact the development of personalized cancer therapies, improving patient outcomes.

      Weaknesses:

      The study is constrained by relatively small sample sizes for each cancer type, which reduces the statistical power and robustness of the findings. ICGC and other large-scale WGS datasets are publicly available but were not included in this study.

      Thanks. We indeed have used all public data, including GENIE (figure 7 of the companion paper), ICGC and other integrated resources such as COSMIC. The main study is based on TCGA because it is unbiased for estimating the probability of CDN occurrences. In many datasets, the numerators are given but the denominators are not (the number of patients with the mutation / the total number of patients surveyed). In GENIE, we observed that E(u) estimated upon given sequencing panels are much smaller than in TCGA, this might be due to the selective report of nonsynonymous mutations for synonymous mutations are generally considered irrelevant in tumorigenesis.

      To be able to identify rare driver mutations, more samples are needed to improve the statistical power, which is well-known in cancer research. The challenges in direct functional testing of CDNs due to the complexity of tumor evolution and unknown mutation combinations limit the practical applicability of the findings.

      We fully agree. We now add a few sentences, making clear that the theory allows us to see how much more can be gained by each stepwise increase in sample size. For example, when the sample size reaches 106, further increases will yield almost no gain in confidence of CDNs identified (see figures of eLife-RP-RA-2024-99340. As pointed out in our provisional responses, an important strength of this pair of studies is that the results are testable. The complexity is the combination of mutations required for tumorigenesis and the identification of such combinations is the main goal and strength of this pair of studies. We add a few sentences to this effect.

      While the importance of large sample sizes in identifying cancer drivers is well-recognized, the analytical framework presented in the companion paper (https://elifesciences.org/reviewed-preprints/99340) goes a step further by quantitatively elucidating the relationship between sample size and the resolution of CDN detection.

      The question is very general as it is about multigene interactions, or epistasis. The challenges are true in all aspects of evolutionary biology, for example, the genetics of reproductive isolation(Wu and Ting 2004). The issue of epistasis is difficult because most, if not all, of the underlying mutations have to be identified in order to carry out functional tests. While the full identification is rarely feasible, it is precisely the objective of the CDN project. When the sample size increases to 100,000 for a cancer type, all point mutations for that cancer type should be identifiable.

      The QC of the TCGA data was not very strict, i.e, "patients with more than 3000 coding region point mutations were filtered out as potential hypermutator phenotypes", it would be better to remove patients beyond +/- 3*S.D from the mean number of mutations for each cancer type. Given some point mutations with >3 hits in the TCGA dataset, they were just false positive mutation callings, particularly in the large repeat regions in the human genome.

      Thanks. The GDC data portal offers data calls from multiple pipelines, enabling us to select mutations detected by at least two pipelines. While including patients with hypermutator phenotypes could introduce potential noise, as shown in Eq. 10 of the main text, our method for defining the upper limit of i* is relative robust to the fluctuations in the E(u) of the corresponding cancer population. Since readers may often ask about this, we expand the Methods section somewhat to emphasize this point.

      The codes for the statistical calculation (i.e., calculation of Ai_e, et al) are not publicly available, which makes the findings hard to be replicated.

      We have now updated the section of “Data Availability” in both papers. The key scripts for generating the major results are available at: https://gitlab.com/ultramicroevo/cdn_v1.

      Reviewer #2 (Public Review):

      Summary:

      The study proposes that many cancer driver mutations are not yet identified but could be identified if they harbor recurrent SNVs. The paper leverages the analysis from Paper #1 that used quantitative analysis to demonstrate that SNVs or CDNs seen 3 or more times are more likely to occur due to selection (ie a driver mutation) than they are to occur by chance or random mutation.

      Strengths:

      Empirically, mutation frequency is an excellent marker of a driver gene because canonical driver mutations typically have recurrent SNVs. Using the TCGA database, the paper illustrates that CDNs can identify canonical driver mutations (Figure 3) and that most CDNs are likely to disrupt protein function (Figure 2). In addition, CDNs can be shared between cancer types (Figure 4).

      Weaknesses:

      Driver alteration validation is difficult, with disagreements on what defines a driver mutation, and how many driver mutations are present in a cancer. The value proposed by the authors is that the identification of all driver genes can facilitate the design of patient-specific targeting therapies, but most targeted therapies are already directed towards known driver genes. There is an incomplete discussion of oncogenes (where activating mutations tend to target a single amino acid or repeat) and tumor suppressor genes (where inactivating mutations may be more spread across the gene). Other alterations (epigenetic, indels, translocations, CNVs) would be missed by this type of analysis.

      The above paragraph has three distinct points. We shall respond one by one.

      First, …  can facilitate the design of patient-specific targeting therapies, but most targeted therapies are already directed towards known driver genes…

      We state in the text of Discussion the following that shows only a few best-known driving mutations have been targeted. It is accurate to say that < 5% of CDNs we have identified are on the current targeting list. Furthermore, this list we have compiled is < 10% of what we expect to find.

      Direct functional test of CDNs would be to introduce putative cancer-driving mutations and observe the evolution of tumors. Such a task of introducing multiple mutations that are collectively needed to drive tumorigenesis has been done only recently, and only for the best-known cancer driving mutations (Ortmann et al. 2015; Takeda et al. 2015; Hodis et al. 2022). In most tumors, the correct combination of mutations needed is not known. Clearly, CDNs, with their strong tumorigenic strength, are suitable candidates.

      Second, “There is an incomplete discussion of oncogenes (where activating mutations tend to target a single amino acid or repeat) and tumor suppressor genes (where inactivating mutations may be more spread across the gene).”

      We sincerely thank the reviewer for this insightful comment. Below are two new paragraphs in the Discussion pertaining to the point:

      In this context, we should comment on the feasibility of targeting CDNs that may occur in either oncogenes (ONCs) or tumor suppressor genes (TSGs). It is generally accepted that ONCs drive tumorigenesis thanks to the gain-of-function (GOF) mutations whereas TSGs derive their tumorigenic powers by loss-of-function (LOF) mutations. It is worthwhile to point out that, since LOF mutations are likely to be more widespread on a gene, CDNs are biased toward GOF mutations. The often even distribution of non-sense mutations along the length of TSGs provide such evidence. As gene targeting aims to diminish gene functions, GOF mutations are perceived to be targetable whereas LOF mutations are not. By extension, ONCs should be targetable but TSGs are not. This last assertion is not true because mutations on TSGs may often be of the GOF kind as well.

      The data often suggest that mis-sense mutations on TSGs are of the GOF kind. If mis-sense mutations are far more prevalent than nonsense mutations in tumors, the mis-sense mutations cannot possibly be LOF mutations. (After all, it is not possible to lose more functions than nonsense mutations.) For example, AAA to AAC (K to Q) is a mis-sense mutation while AAA to AAT (K to stop) is a non-sense mutation. In a separate study (referred to as the escape-route analysis), we found many cases where the mis-sense mutations on TSGs are more prevalent (> 10X) than nonsense mutations. Another well-known example is the distribution of non-sense mutations TSGs. For example, on APC, a prominent TSG, non-sense mutations are far more common in the middle 20% of the gene than the rest (Zhang and Shay 2017; Erazo-Oliveras et al. 2023). The pattern suggests that even these non-sense mutations could have GOF properties. 

      The following response is about the clinical implications of our CDN analysis. Canonical targeted therapy often relies on the Tyrosine Kinase Inhibitors (TKIs) (Dang et al. 2017; Danesi et al. 2021; Waarts et al. 2022). Theoretically, any intervention that suppresses the expression of gain-of-function (GOF) CDNs could potentially have therapeutic value in cancer treatment. This leads us to a discussion of oncogenes versus TSGs in the context of GOF / LOF (loss of function) mutations. Not all mutations on oncogenes have oncogenic effect, besides, truncated mutations in oncogenes are often subject to negative selection (Bányai et al. 2021), the identification of CDNs within oncogenes is therefore crucial for developing effective cancer treatment guidelines. Secondly, while TSGs are generally believed to promote cancer development via loss of function mutations, research suggests that certain mutations within TSGs can have GOF-like effect, such as the dominant negative effect of truncated TP53 mutations (Marutani et al. 1999; de Vries et al. 2002; Gerasimavicius et al. 2022). Characterizing driver mutations as GOF or LOF mutations could potentially expand the scope of targeted cancer therapy. We’ll address this issue in a third study in preparation.

      The method could be more valuable when applied to the noncoding genome, where driver mutations in promoters or enhancers are relatively rare, or as yet to be discovered. Increasingly more cancers have had whole genome sequencing. Compared to WES, criteria for driver mutations in noncoding regions are less clear, and this method could potentially provide new noncoding driver CDNs. Observing the same mutation in more than one cancer specimen is empirically unusual, and the authors provide a solid quantitative analysis that indicates many recurrent mutations are likely to be cancer-driver mutations.

      Again, we are grateful for the comments which prompt us to expand a paragraph in Discussion, reproduced below.

      The CDN approach has two additional applications. First, it can be used to find CDNs in non-coding regions. Although the number of whole genome sequences at present is still insufficient for systematic CDN detection, the preliminary analysis suggests that the density of CDNs in non-coding regions is orders of magnitude lower than in coding regions. Second, CDNs can also be used in cancer screening with the advantage of efficiency as the targeted mutations are fewer. For the same reason, the false negative rate should be much lower too. Indeed, the false positive rate should be far lower than the gene-based screen which often shows a false positive rate of >50% (supplement File S1).

      Again, we are grateful that Reviewer #2 have addressed the potential value of our study in finding cancer drivers in non-coding regions. A major challenge in this area lies in defining the appropriate L value as presented in Eq. 10. In the main text, we used a gamma distribution to account for the variability of mutation rates across sites in coding region. For the non-coding region, we will categorize these regions based on biological annotations. The goal is to set different i* cutoffs for different genomic regions (such as heterochromatin / euchromatin, GC-rich regions or centromeric regions), and avoid false positive calls for CDN in repeated regions (Elliott and Larsson 2021; Peña et al. 2023).

      References

      Bányai L, Trexler M, Kerekes K, Csuka O, Patthy L. 2021. Use of signals of positive and negative selection to distinguish cancer genes and passenger genes. Elife 10:e59629.

      Danesi R, Fogli S, Indraccolo S, Del Re M, Dei Tos AP, Leoncini L, Antonuzzo L, Bonanno L, Guarneri V, Pierini A, et al. 2021. Druggable targets meet oncogenic drivers: opportunities and limitations of target-based classification of tumors and the role of Molecular Tumor Boards. ESMO Open 6:100040.

      Dang CV, Reddy EP, Shokat KM, Soucek L. 2017. Drugging the “undruggable” cancer targets. Nat Rev Cancer 17:502–508.

      Elliott K, Larsson E. 2021. Non-coding driver mutations in human cancer. Nat Rev Cancer 21:500–509.

      Erazo-Oliveras A, Muñoz-Vega M, Mlih M, Thiriveedi V, Salinas ML, Rivera-Rodríguez JM, Kim E, Wright RC, Wang X, Landrock KK, et al. 2023. Mutant APC reshapes Wnt signaling plasma membrane nanodomains by altering cholesterol levels via oncogenic β-catenin. Nat Commun 14:4342.

      Gerasimavicius L, Livesey BJ, Marsh JA. 2022. Loss-of-function, gain-of-function and dominant-negative mutations have profoundly different effects on protein structure. Nat Commun 13:3895.

      Hodis E, Triglia ET, Kwon JYH, Biancalani T, Zakka LR, Parkar S, Hütter J-C, Buffoni L, Delorey TM, Phillips D, et al. 2022. Stepwise-edited, human melanoma models reveal mutations’ effect on tumor and microenvironment. Science 376:eabi8175.

      Marutani M, Tonoki H, Tada M, Takahashi M, Kashiwazaki H, Hida Y, Hamada J, Asaka M, Moriuchi T. 1999. Dominant-negative mutations of the tumor suppressor p53 relating to early onset of glioblastoma multiforme. Cancer Res 59:4765–4769.

      Ortmann CA, Kent DG, Nangalia J, Silber Y, Wedge DC, Grinfeld J, Baxter EJ, Massie CE, Papaemmanuil E, Menon S, et al. 2015. Effect of Mutation Order on Myeloproliferative Neoplasms. N Engl J Med 372:601–612.

      Peña MV de la, Summanen PAM, Liukkonen M, Kronholm I. 2023. Chromatin structure influences rate and spectrum of spontaneous mutations in Neurospora crassa. Genome Res. 33:599–611.

      Takeda H, Wei Z, Koso H, Rust AG, Yew CCK, Mann MB, Ward JM, Adams DJ, Copeland NG, Jenkins NA. 2015. Transposon mutagenesis identifies genes and evolutionary forces driving gastrointestinal tract tumor progression. Nat Genet 47:142–150.

      de Vries A, Flores ER, Miranda B, Hsieh H-M, van Oostrom CThM, Sage J, Jacks T. 2002. Targeted point mutations of p53 lead to dominant-negative inhibition of wild-type p53 function. Proceedings of the National Academy of Sciences 99:2948–2953.

      Waarts MR, Stonestrom AJ, Park YC, Levine RL. 2022. Targeting mutations in cancer. J Clin Invest 132:e154943.

      Wu C-I, Ting C-T. 2004. Genes and speciation. Nat Rev Genet 5:114–122.

      Zhang L, Shay JW. 2017. Multiple Roles of APC and its Therapeutic Implications in Colorectal Cancer. JNCI: Journal of the National Cancer Institute 109:djw332.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      This work describes the induction of SIV-specific NAb responses in rhesus macaques infected with SIVmac239, a neutralization-resistant virus. Typically, host NAb responses are not detected in animals infected with SIVmac239. In this work, seventy SIVmac239-infected macaques were retrospectively screened for NAb responses and a subset of nine animals were identified as NAb-inducers. The viral genomes from 7/9 animals that induced NAb responses were found to encode nonsynonymous mutation in the Nef gene (amino acid G63E). In contrast, Nef G63E mutation was found only in 2/19 NAb non-inducers - implicating that the Nef G63E mutation is selected in NAb inducers. Measurement of Nef G63E frequencies in plasma viruses suggested that Nef G63E selection preceded NAb induction. Nef G63E mutation was found to mediate escape from Nef-specific CD8+ T-cell responses. To examine the functional phenotype of Nef G63E mutant, its effect on downmodulation of Nef-interacting host proteins was examined. Infection of rhesus and cynomolgus macaque CD4+ T cell lines with WT or Nef G63E mutant SIV suggested that Nef mutant reduces S473 phosphorylation of AKT. Using flow cytometry-based proximity ligation assay, it was shown that Nef G63E mutation reduced binding of Nef to PI3K p85/p110 and mTORC2 GβL/mLST8 and MTOR components - kinase complex responsible AKT-S473 phosphorylation. In vitro B-cell Nef invasion and in vivo imaging/flow cytometry-based assays were employed to suggest that Nef from infected cells can target Env-specific B cells. Lastly, it was determined that NAb inducers have significantly higher Env-specific B-cells responses after Nef G63E selection when compared to NAb non-inducers. Finally, a corollary was drawn between the Nef G63E-associated B-cell/NAb induction phenotype and activated PI3K delta syndrome (APDS), which is caused by activating GOF mutations in PI3K, to suggest that Nef G63E-meidated induction of NAb response is reciprocal to APDS.

      Strengths:

      This study aims to understand the viral-host interaction that governs NAb induction in SIVmac239-infected macaques - this could enable identification of determinants important for induction of NAb responses against hard-to-neutralize tier-2/3 HIV variants. The finding that SIV-specific B-cell responses are induced following Nef G63E CD8+ T-cell escape mutant selection argue for an evolutionary trade-off between CTL escape and NAb induction. Exploitation of such a cellular-humoral immune axis could be important for HIV/AIDS vaccine efforts.

      Although more validation and mechanistic basis are needed, the corollary between PI3K hyperactive signaling during autoimmune disorders and Nef-mediated abrogated PI3K signaling could help identify novel targets and modalities for targeting immune disorders and viral infections.

      We are grateful for the supportive and insightful comments. The work did seem to unintendedly highlight a conceptual link between extrinsic and intrinsic immune perturbations. We will keep working on both wings, aiming to evoke synergisms.

      Weaknesses:

      Although the paper does have strengths in principle, the weaknesses of the paper are that the mechanistic basis of Nef-mediated induction of NAb responses are not directly examined. For example, it remains unclear whether SIVmac239 with engineered G63E mutation in Nef would induce faster and potent NAb responses. A macaque challenge study is needed to address this point.

      We appreciate the point. We do have certain difficulties in availability of macaques for de novo experiments. As partially discussed in ver1, the identified Nef phenotype selected post-acute infection confers an enhanced CD4+ T cell-killing effect (revised Fig 4F), and it is likely that de novo infection with the mutant would redirect the trajectory of infection to rapid disease/AIDS progression accompanying generalized immune failure by boosting acute-phase CD4 destruction. In other words, mutant de novo infection may not necessarily be directly discussable as an attempt for reconstitution. It appears equally critical to understand the mutant in vitro on an immunosignaling basis, and in the current work we have focused on depicting this as the first step. We will work on reconstitution experiments with emphasis on pharmacology in our future study.

      As presented, the central premise of the paper involves infected cell-generated Nef (WT or G63E mutant) being targeted to adjacent Env-specific B cells. However, it remains unclear how this is transfer takes place. A direct evidence demonstrating CD4+ T cell-associated and/or cell-free Nef being transferred to B-cell is needed to address this concern.

      We appreciate the point, also pointed out by Reviewers 2 and 3. We have performed three sets of in vitro reconstitution experiments graphically/functionally addressing how Nef transfer from CD4+ T cells to B cells can be modulated (new Fig 6) and edited text accordingly.

      The interaction between Nef and PI3K signaling components (p85, p110, GβL/mLST8, and MTOR) has been explored using PLA assay, however, this requires validation using additional biochemical and/or immunoprecipitation-based approaches. For example, is Nef (WT or mutant form) sufficient to affect PI3K-induced phosphorylation of Akt in an in vitro kinase assay? Moreover, the details regarding the binding events of WT vs mutant Nef with PI3K signaling components is lacking in this study. Lastly, it is unclear whether the interaction of Nef with PI3K signaling components is a conserved function of all primate lentiviruses or is this SIV-specific phenotype.

      We appreciate the point. Co-immunoprecipitation analysis via pulldown with the mTORC2-intrinsic cofactor Sin1 (revised Fig 4E), showing decreased G63E-Nef binding, should confer robustness to the statement combined with initial manipulation results (Fig 4C). As Sin1 is mTORC2- and not mTORC1-intrinsic, results should be strengthened. Phosflow may be a standard readout nowadays for pAkt itself. Related with sequence variation, conservation will be addressed in studies ahead. We concisely mentioned on this in the revision (Lines 390-391).

      It has been previously reported that the region of Nef encoding glycine at position 63 is not conserved in HIV-1 (Schindler et al, Journal of Virology 2004). Thus, does HIV-1 Nef also function in induction of NAb responses in humans? or the observed phenotype specific to SIV?

      We appreciate the point, and do not have an answer at the moment. We will explore in our HIV-1-infected patient cohort (Hau et al, AIDS 2022) and other occasions whether corresponding phenotypes may exist. We have mentioned on this point in the revised manuscript (Line 392-393).

      Reviewer #2 (Public Review):

      It is well known that human and simian immunodeficiency viruses (HIV and SIV, respectively) evolved numerous mechanisms to compromise effective immune responses but the underlying mechanisms remain incompletely understood. Here, Yamamoto and Matano examined the humoral immune response in a large number of rhesus macaques infected with the difficult-to-neutralize SIVmac239 strain. They identified a subgroup of animals that showed significant neutralizing Ab responses. Sequence analyses revealed that in most of these animals (7/9) but only a minority in the control group (2/19) SIVmac variants containing a CD8+ T-cell escape mutation of G63E/R in the viral Nef gene emerged. They further show that this change attenuates the ability of Nef to stimulate PI3K/Akt/mTORC2 signaling. The authors propose that this induction of SIVmac239 nAb induction is reciprocal to antibody dysregulation caused by a previously identified human PI3K gain-of-function (Ref). Altogether, the results suggest that PI3K signaling plays a key role in B-cell maturation and generation of effective nAb responses.

      Strengths of the study are that the authors analyzed a large number of SIVmac-infected macaques to unravel the biological significance of the known effect of the interaction of Nef with PI3K/Akt/mTORC2 signaling. This is interesting and may provide a novel means to improve humoral immune responses to HIV. Weaknesses are that only G63E and not G63R that also emerged in most animals was examined in most functional assays. Some effects of the G63E mutation seem modest and comparison to a grossly nef-defective SIVmac construct would be desirable to better assess to impact of the mutation of Nef-mediated stimulation of PI3K. While the impact of this Nef mutations on PI3K and the association with improved nAb responses is largely convincing, the results on the potential impact of soluble Nef on neighboring B cells is much less clear. SIVmac239 infects and manipulates helper CD4 T cells and these are essential for the activation and differentiation of B cells into antibody-producing plasma cells and effective humoral immune responses. Without additional functional evidence that Nef indeed specifically targets and manipulated B cells these results and conclusions should be made with much greater caution. Finally, the presentation of the results and conclusions is partly very convoluted and difficult to comprehend. Editing to improve clarity is highly recommended.

      We are very grateful for the supportive and visionary review and suggestions. Experiments have been performed to improve the points raised. This work inevitably involved interdisciplinary factors to even hit on the schematic (NAbs, B cells, CD4+T, CD8+T, viral escape, immunosignaling, IEI as extrapolation & microscopy implementations) and convoluted sections should have existed. We attempted streamlining of certain portions and edited writing throughout, and hope that it became more straightforward.

      Reviewer #2 (Recommendations For The Authors):

      As outlined in the public review, I found the results potentially very interesting but parts of the manuscript much more complex and confusing than necessary. In addition, the methods on the potential impact of soluble Nef on neighboring B cells in vivo was difficult to assess but altogether this part was not convincing. Have the following specific suggestions:

      We are very grateful for the scholarly review, and encouraging and suggestive comments on this orphan work. In the revision we designed experiments to address the properties of Nef transfer to append understanding on the in vivo B-cell data. Recommendations have been addressed as follows.

      (1) Title: "AIDS virus-neutralizing antibody induction reciprocal to a PI3K gain-of-function disease". Think this title hardly reflects the data; SIVmac cause simian AIDS and is not the "AIDS virus" the 2nd part is more appropriate for discussion than for the title (and the abstract).

      We appreciate the point. The original intent of the title was to conceptually bridge two differing fields of virus-host interaction and inborn errors of immunity/immunosignaling on an original article basis. Certain papers (Mudd et al, Nature 2012 etc) do utilize the term AIDS virus, and we similarly chose the term for simplification to non-virologists at initial submission.

      That being said, we understand the scholarly point raised, and feel that the initial aim can be well attained by retaining the key host effector PI3K in the title, as in the revised submission titled “SIV-specific neutralizing antibody induction following selection of a PI3K drive-attenuated nef variant”.

      (2) Abstract and throughout: As the authors show, SIVmac is not generally "neutralization resistant"; difficult to neutralize is more appropriate and should be used throughout. Also, the abstract and other parts are more complicated than necessary.

      We appreciate the point. HIV/SIV Env immunology work utilizes “neutralization-resistant” for SIVmac239 (e.g., Mason et al, PLoS Pathog 2016), and autologous titer positivity of ~10% at this size of examination does appear low amongst lentiviruses. Nevertheless, as recommended, “difficult-to-neutralize” better describes the nature, and we have switched the term accordingly.

      Linked with title modification, we reflected the comment on abstract structure and switched the main introductory sentence (Here we…) to a more data-based one instead of depicting extrapolation, and have modified phrasings in the latter half.

      (3) The intro seems a bit biased. Immune evasion due to mutations and proviral integration that play key roles in viral persistence are not mentioned. nAbs are not known to efficiently control HIV or SIV replication in vivo (not even in the present study). Thus, a more "balanced" presentation of the role of nAbs in vivo is desirable.

      We agree with the comment. Introduction in ver1 submission was compressed to just display humoral immune perturbation examples across persistence-prone viral infections, and indeed it should be much better to layout the multiscale strategies of lentiviruses in manifesting viral persistence. We have appended two sets of texts, one on the fundamental integrating retroviral life cycle and another on the wide spectrum of accessory protein-driven perturbation. As pointed out, the current endogenous induction is of course not early enough to exert suppressive impact on replication as like in exogenous Ab passive infusions. We have accordingly modulated text to improve the balance.

      (4) Lines 73-76: rephrase for clarity.

      We acknowledge the comment and have rephrased accordingly.

      (5) Line 92: "linked with sustained Env-specific B-cell responses after the mutant Nef selection". After or during in one case; the time frame varies enormously and this should be discussed.

      We appreciate the comment. The six Nef-G63E mutant-selecting NAb inducers subjected to B-cell analysis were the ones that showed precedence in Fig 2D (mutant before induction). That being said, we modified text as suggested (Line 104 in revised uploaded text). Text related to temporal deviation has been appended (Lines 378-383 in revised uploaded text).

      (6) The authors should discuss G63R and include it in the functional analyses.

      We appreciate the comment. Discussion on Nef-G63R in ver1 submission was kept minimal because statistical significance for selection was marginal. We generated a Nef-G63R mutant and results are appended in Fig 4-Figure Supplement 2.

      (7) Lines 124/5: conservation only applies to SIVsmm/mac Nefs and this region is also frequently deleted/length-variable in primary HIV-1 Nefs.

      We appreciate the comment. We modified description of the region accordingly (Lines 139-141 in revised text).

      (8) Lines 153-155: Statement doesn't seem to make sense. The triple mutant Nef SIVmac construct was not attenuated for replication but specifically disrupted in CD3 down-modulation.

      We acknowledge the comment. It had meant that the consequent plasma viral load showed a trend of decrease (as in the Graphical Abstract of the work) which should (in a simplistic view) influence antigenicity for humoral immune responses. Yet it is very true that virological replicative capacity was comparable with wild-type as in Fig.1. We have taken down the related text and rephrased it (Ref remains cited in introduction).

      (9) Lines 178/9: levels in PI3K gain-of-function mice "with full disease phenotype (Avery et al., 2018)". This needs more information, e.g. what disease exactly are they talking about?

      We are grateful for the correction, and have appended text and introduced the mentioned congenital disease in the Introduction section in advance. In-detail description is also appended in the Discussion section.

      (10) Lines 186/7: "Env-stimulating high-MOI infection also accelerated phenotype appearance, with enhanced 50% reduction (Figure 4C, right)". Modify text and corresponding figure for clarity.

      We acknowledge the comment. We revised as: “A high-MOI SIV infection, comprising higher initial concentration of extracellular Env stimuli, also accelerated phenotype appearance from day 3 to day 1 post-infection with stronger pAkt reduction”.

      (11) The validity of the results described in the section "Targeting of lymph node Env-specific B cells by Nef in vivo" was difficult to assess. Altogether, however, I didn't find them convincing, especially since a negative control (e.g. macaques infected with nef-deleted SIVmac) are missing.

      We acknowledge the comment. As a pure experimental control, whole-Nef deletion may assist for subtracted baselines. Within this work, the staining per se at least should be highly specific (mAb multiply verified in other applications and cytometry panel also designed for minimal spillover into AF488 channel). On in vivo basis, direct comparison may be somewhat frustrated by the fact that reduction in other pleiotropic effects of Nef seem to more dominate upon Nef deletion, as a set of reduced viremia, robust CD8 responses, killer CD4 responses and increased binding Ab titers (Johnson et al, J Virol 1997, Gauduin et al, J Exp Med 2006, Fukazawa et al, Nat Med 2012, Adnan et al, PLoS Pathog 2016 etc) leading to altered trajectory. We promise that we will work on refinement of the methodology in studies ahead.

      (12) Lines 309-319: This paragraph made little sense to me (as did lines 328-331).

      We acknowledge the comment and have edited both sections.

      Reviewer #3 (Additional Reviewer):

      In this manuscript, Hiroyuki Yamamoto et al examined virus-specific antibody responses and identified a subgroup of nine individuals, out of seventy SIVmac239 rhesus macaques of Burmese origin infected with SIVmac239, that develop neutralizing antibodies (NAb). The authors propose the emergence of a nef mutant (Nef-G63E) that impacts on B cell maturation resulting in PI3K gain-of-function.

      My major concerns are:

      The authors by different aspect addressed the role of the emergence of Nef-G63E mutant in individuals developing NAb. The manuscript is confused and the rational not always clearly stated. This reflects the two aspects of the manuscript (i) NAb identification in a subgroup of macaque and (2) the identification this nef mutation.

      We are grateful for the comprehensive and scholarly comments. As pointed out, the work did need to confront potential bifurcation of the influence of the obtained viral immunosignaling phenotype for CD4-intrinsic (which might be your specialty) and B-cell-intrinsic impact. Based on your suggestions we have acquired additional data and revised the manuscript as attached.

      The authors used both males (n=57) and females (n=13). However, there is no indication related to the sex regarding NAb inducers versus non-NAb Inducers. The notion of "highly pathogenic" is certainly not correct (see the introduction). Pathogenicity is also depending on monkey origin. Thus, cynomolgus are less sensitive to SIVmac239 or SIVmac251 compared to rhesus macaques (Ling B Aids 2002; Reimann KA, J Virol 2005; Cumont MC, J Virol 2008), or to pigtails used in US. Indeed, the authors used Burmese macaques, and therefore the dynamics of pathogenicity is different to rhesus macaque (Indian origin) housed in US. How many animals have been sacrificed out of the 61 animals? Herein, the animals are surviving longer (more than one year), and therefore the notion of "highly pathogenic" merits to be modulated.

      We appreciate the comment. We have accordingly appended sex information (M/F: 8/1 versus 49/12 in NAb inducers vs non-inducers, p > 0.99 by Fisher’s exact test) in the methods section. As pointed out there are differences in the frequency and rate of AIDS progression among macaques of differing origin, whereas we have also previously reported reproducible AIDS progression dependent on MHC-I genotypes in the Burmese rhesus macaques utilized (Nomura, Yamamoto et al., J Virol 2012). Adhering to advice, we have attenuated the term to “pathogenic” in the revised manuscript and appended one reference showing pathogenesis gradation from a cell-death perspective (Cumont 2008).

      Furthermore, no indication is provided regarding CD4 T cell dynamics, or CD8 T cells. In particular, the extent of T cell immunodeficiency may compromise humoral response. Therefore, this data needs to be shown. Indeed, previous reports have indicated that early CD4 T cell depletion is associated with defective humoral response. Furthermore, Tfh cell depletion was reported in several immune tissues, which are essential for B cell immune response like the spleen. Thus, this should be discussed as an alternative mechanism to the absence of NAb. Indeed, the authors found higher and persistent env-specific plasmablast cells in NAb inducers than that observed in non-NAb inducers figure 6. Why to have selected twelve individuals out of 61 individuals for assessing anti-env response (Supplemental S3 for figure 1, panel 1), and only eleven for western blots. The explanation in the text is absent. This requires to be clearly stated. See lines 108-110.

      We appreciate the comment. As in other sections, this study utilized available cryopreserved samples from a retrospective cohort, also having heterogeneity in data acquisition along the way. We acknowledge that some supplemental data are particularly limited in information, which is also a reason they are presented in SI. We felt that one important core was to secure samples for Nef-G63E-selecting NAb inducers versus viremic non-inducers, for which we acquired six versus twelve in the B-cell analysis.

      We (Nakane et al, PLoS ONE 2013) and others (Hirsch et al, J Virol 2004) have already reported on western blotting-basis that SIV-infected rapid progressors tend to manifest serological failure (impaired binding Ab-WB bands). Therefore, to compare quantitative traits at this basal stage (Fig 1), we judged that NAb inducer comparison with more non-rapid-progressing (>60 wk survival) non-inducers would be a criterion. We have mentioned on this in the revised manuscript (results/methods). Additionally, we have replaced the immunoblotting result with one more non-inducer (n = 12) to enhance results. Please note that there are lot deviations in strip-coated antigen (e.g., gp160) but the result is comparable (now covers 12/13 of animals with >60-wk survival).

      The authors indicated the frequencies of Nef-G63E mutant in figure 2 panel C. However. no information is indicated in the legend about the number of NAb non-inducers used to calculate this frequency. The authors indicated line 127, "only in two of the nineteen NAb non-inducers, including one rapid progressor". Thus, different numbers of individuals are used through the manuscript. For the readers, this is clearly a statement that needs to be clarify and to refer to what. This is not homogeneous along the text and the analyses performed.

      We appreciate the comment, and have appended the number in the revised Fig 2C. As aforementioned, heterogeneity of sample number in different sections is indeed a limitation of the work, and have mentioned this in the Discussion.

      The rational related to the sentence lines 140-142. Please clarify.. "NAb induction is not associated with these MHC-I genotypes (P = 0.25 by Fisher's exact test, data not shown) but with the Nef-G63E mutation itself".

      We appreciate the comment. We have rephrased it as:

      “Ten of nineteen NAb non-inducers also had either of these alleles (Figure 1-figure supplement 1). This did not significantly differ with the NAb inducer group (P = 0.25 by Fisher’s exact test, data not shown), indicating that NAb induction was not simply linked with possession of these MHC-I genotypes but instead required furthermore specific selection of the Nef-G63E mutation.” (Lines 159-162).

      In supplemental figure 3, only 7 individuals have been tested, while the authors indicated "Ten of nineteen NAb non-inducers also had either of these alleles". Why only seven? In NAb Burmese monkeys, the authors indicate specific T cells capable to recognize WT nef peptide, but not G63E peptide mutant. Thus, nef is immunogenic in vivo generating T cells despite to be mutated.

      In contrary, non-NAb-inducers demonstrate the absence of nef specific T cells (supplemental figure 3, excepted R01-011 panel A). Although, the authors propose an escape mutant for CD8 T cells, this is not associated with the absence of immunogenicity and not with a difference in viral load in comparison to NAb inducers (panel C). Therefore, the conclusions merit to be revised. Thus, this part of the manuscript is confusing. Please clarify the rational to link NAb and Nef specific CD8 T cells.

      We appreciate the comment. 7 out of 8 non-inducers positive for the allele and not selecting for the Nef-G63E mutant was available for analysis. The relative contribution of this single Nef62-70 epitope-specific CTL response is speculated not to be largely impacting viral control, among the many induced. This is basally discussed in a previous paper (Nomura, Yamamoto et al., J Virol 2012), more suggestive of an MHC-I haplotype-level correlation with plasma viral load. We assume that the CTL pressure-driven selection of Nef-G63E mutant was a rather pure immunosignaling trigger under persistent viremia. We appended this in the revised text (Line 172).

      In the next part of the manuscript, the authors assessed the function of this Nef-G63E mutant. The rational to introduce Ferritin in this part of the document is not clear for the reader. Furthermore, a subgroup for each (NAb+ versus NAb-) is shown: 4 for NAbneg versus 6 for NAbpos.

      We appreciate the point. As introduced, Swingler et al Cell Host Microbe 2008 reported HIV-infected macrophage-derived ferritin as a potentially B cell-disrupting factor. In that paper, viral load, ferritin and binding antibody titers positively correlated. Current data shows that SIVmac239-specific NAb induction is distinct from such kinetics already versus viral load (Fig 3-Supplement 1C), and ferritin levels were measured for some available samples more simply for confirmation. We appended three more available samples in the NAb- group. (The six NAb+/G63E animals correspond to the ones with B-cell data in Figure 7.) Statistical results appear unaffected and robust, as shown in this version. The revised manuscript incorporates appended explanation for the former.

      Similarly, whereas the authors observed a role of nef mutant on pAkt Ser473 (less induced) in comparison to WT, the authors suggest that this may have an impact on T cell survival.

      We appreciate the point. In the first submission we obtained peripheral memory Tfh decrease, whereas it is true that this is indirect. In the current revision we have addressed apoptotic cell death, shown to increase with Nef-G63E mutation (Figure 4F).

      The rational to analyze CXCR3-CXCR5+PD-1+ memory follicular Th (Tfh) is not clear. Moreover, the references used are not the adequately cited. Indeed, these papers show an expansion. See the literature for a depletion (Xu H, J Immunol. 2015; Moukambi F, PLoS Pathog. 2015; Yamamoto T, Sci Transl Med. 2015; Xu H, J Immunol. 2018 Moukambi F, Mucosal Immunol. 2019).

      We appreciate these points on in vivo CD4+ T cells.

      Peripheral memory Tfh was reported to correlate with Ab cross-reactivity in one human cohort (Locci et al, Immunity 2013) and we concisely examined the subset in the current NAb induction. We mentioned this in the revised manuscript.

      Moukambi F et al, PLoS Pathog 2015 & Mucosal Immunol 2019 are demonstrative work on acute-phase destruction. We have cited non-neonatal/vaccine-related ones suggested, including these two, in the revised manuscript. The biphasic dysregulation of Th (acute-phase destruction and chronic-phase adverse hyper-expansion) may indeed have a unique role with the current phenotype, which is beyond aim of the current analysis. We have concisely mentioned on this in the Discussion.

      Then, the authors assess the potential B-cell-intrinsic influence of the G63E-Nef phenotype. The rational here is clearly indicated, making sense with figure 1. Furthermore, this part is clearer. The dot-plots merit to be revised and the markers used better stated. The authors indicate that Nef invasion upregulates pAkt Ser473 assuming aberrant PI3K/mTORC2 signaling. What is the impact of Nef-G63E mutant on pAkt Ser473 using in vitro model of transfer. This is not addressed for comparison.

      We appreciate the remarks/suggestions, also pointed out by Reviewers 1 and 2. We have performed three sets of in vitro reconstitution experiments visually and functionally addressing how Nef transfer to B cells can be modulated (new Fig 6), and edited text accordingly.

      Minor points are:

      - the presence of references in the legend.

      -some Ab clones are in the table, however they are not used such CD38 and CD138, which are well known to be non-valid B cell markers for monkeys."

      We appreciate the suggestions.

      Mentioning on reference have been removed from the legend (Fig.1, Fig. 3) and moved to the corresponding Methods section (Fig. 1).

      We also understood this well in advance (CD38/CD138), and incorporated them in the memory B-cell panel just to check whether they ever behave in a specific pattern. As expected, no notable behavior was observed in these NAb inducers.

    1. Crash course on typewriter maintenance and repair

      A list of resources and references for the budding typewriter repair person. There is a lot here that I've compiled and consumed over the last six months, so don't be overwhelmed. Half the battle is figuring out where to find all these things, so if nothing else, this should shave off a month of reading and researching.

      Basic Introductory Material

      Get a notebook and be ready to take some notes so you'll remember where you found the random information you're bound to pick up over time and are able to occasionally review it.

      Work your way through Sarah Everett's excellent Typewriter 101 videos (at least the first five): https://www.youtube.com/playlist?list=PLJtHauPh529XYHI5QNj5w9PUdi89pOXsS

      Read Richard Polt's book which is a great overview to the general space:<br /> Polt, Richard. The Typewriter Revolution: A Typist’s Companion for the 21st Century. 1st ed. Woodstock, VT: Countryman Press, 2015.

      Next watch the documentary California Typewriter. Documentary. Gravitas Pictures, 2016. https://www.imdb.com/title/tt5966990/. It has some interesting subtle material hiding within it, but it will give you a good idea of where you're headed off to.

      Get a machine (or four) you can practice on. Get a flat head screwdriver and maybe a small adjustable wrench. Buy some mineral spirits and a small headed toothbrush and clean out your first machine. Buy some light sewing machine oil and try oiling it. Search YouTube for videos about how to repair anything that may be wrong with it.

      Basic restoration advice: https://site.xavier.edu/polt/typewriters/tw-restoration.html

      On colloquial advice for degreasing, cleaning, and oiling manual typewriters https://boffosocko.com/2024/08/09/on-colloquial-advice-for-degreasing-cleaning-and-oiling-manual-typewriters/

      Repair Manuals

      Create an account on typewriterdatabase.com which will give you some additional access to catalogs, manuals, and dealer catalogs.

      They also have some openly accessible material like:<br /> * https://typewriterdatabase.com/manuals.php

      Printed manuals: https://www.lulu.com/search?adult_audience_rating=00&contributor=Ted+Munk&page=1&pageSize=50 PDF manuals: https://sellfy.com/twdb

      Ted Munk's website also has a plethora of ephemera that is often useful * https://munk.org/typecast/

      Richard Polt's list of service manuals, which also includes some correspondence course typewriter repair classes: https://site.xavier.edu/polt/typewriters/tw-manuals.html#servicemanuals

      Tools

      In rough order of increasing complexity:

      Tools can be expensive, so start out small with just a few things and expand as you need them. You'll be amazed at what you can accomplish with a single thin bladed flathead screwdriver, an adjustable wrench, a rag, a bottle of Simple Green cleaning solution, and a bottle of isopropyl alcohol.

      Videos

      Subscribe to and become acquainted with YouTube channels like the following:

      While watching a variety of videos is great, as you're doing specific repairs search YouTube and you're likely to find full demos of the repairs you're doing yourself.

      I've compiled a playlist of videos for repair of an Olympia SM3 which, while specific to the SM3, is a an excellent outline/overview of how to disassemble a portable typewriter, where many of the adjustment points are as well as an outline of the order to do them in.

      If you're not a good typist or don't have experience in the area, try out some of the following short films which will also provide some useful historical perspective:

      Internships & Apprenticeships

      If you have the time and flexibility try arranging an internship or apprenticeship with a local typewriter repair shop. Meet your local repair people even if you can't spend the time on an internship. You'll learn a lot and create relationships with businesses who will more easily swap/supply you with machines they're parting out or access to tools which may otherwise be difficult to source.

      Podcasts

      Some useful Bibliography

      Good luck on your journey!


      reply to u/fontinalispluma at https://old.reddit.com/r/typewriters/comments/1gaza5x/learning_typewriter_maintenance_and_repair/

    1. Author response:

      Reviewer #1 (Public Review):

      Padilha et al. aimed to find prospective metabolite biomarkers in serum of children aged 6-59 months that were indicative of neurodevelopmental outcomes. The authors leveraged data and samples from the cross-sectional Brazilian National Survey on Child Nutrition (ENANI-2019), and an untargeted multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) approach was used to measure metabolites in serum samples (n=5004) which were identified via a large library of standards. After correlating the metabolite levels against the developmental quotient (DQ), or the degree of which age-appropriate developmental milestones were achieved as evaluated by the Survey of Well-being of Young Children, serum concentrations of phenylacetylglutamine (PAG), cresol sulfate (CS), hippuric acid (HA) and trimethylamine-N-oxide (TMAO) were significantly negatively associated with DQ. Examination of the covariates revealed that the negative associations of PAG, HA, TMAO and valine (Val) with DQ were specific to younger children (-1 SD or 19 months old), whereas creatinine (Crtn) and methylhistidine (MeHis) had significant associations with DQ that changed direction with age (negative at -1 SD or 19 months old, and positive at +1 SD or 49 months old). Further, mediation analysis demonstrated that PAG was a significant mediator for the relationship of delivery mode, child's diet quality and child fiber intake with DQ. HA and TMAO were additional significant mediators of the relationship of child fiber intake with DQ.

      Strengths of this study include the large cohort size and study design allowing for sampling at multiple time points along with neurodevelopmental assessment and a relatively detailed collection of potential confounding factors including diet. The untargeted metabolomics approach was also robust and comprehensive allowing for level 1 identification of a wide breadth of potential biomarkers. Given their methodology, the authors should be able to achieve their aim of identifying candidate serum biomarkers of neurodevelopment for early childhood. The results of this work would be of broad interest to researchers who are interested in understanding the biological underpinnings of development and also for tracking development in pediatric populations, as it provides insight for putative mechanisms and targets from a relevant human cohort that can be probed in future studies. Such putative mechanisms and targets are currently lacking in the field due to challenges in conducting these kind of studies, so this work is important.

      However, in the manuscript's current state, the presentation and analysis of data impede the reader from fully understanding and interpreting the study's findings.

      Particularly, the handling of confounding variables is incomplete. There is a different set of confounders listed in Table 1 versus Supplementary Table 1 versus Methods section Covariates versus Figure 4. For example, Region is listed in Supplementary Table 1 but not in Table 1, and Mode of Delivery is listed in Table 1 but not in Supplementary Table 1. Many factors are listed in Figure 4 that aren't mentioned anywhere else in the paper, such as gestational age at birth or maternal pre-pregnancy obesity.

      We thank the reviewer for their comment. We would like to clarify that initially, the tables had different variables because they have different purposes. Table 1 aims to characterize the sample on variables directly related to the children’s and mother’s features and their nutritional status. Supplementary File 1(previously named supplementary table 1) summarizes the sociodemographic distribution of the development quotient. Neither of the tables concerned the metabolite-DQ relationships and their potential covariates, they only provide context for subsequent analyses by characterizing the sample and the outcome. Instead, the covariates included in the regression models were selected using the Direct Acyclic Graph presented in Figure 1.

      To avoid this potential confusion however, we included the same variables in Table 1 and Supplementary File 1(page 38) and we discussed the selection of model covariates in Figure 4 in more detail here in the letter and in the manuscript.

      The authors utilize the directed acrylic graph (DAG) in Figure 4 to justify the further investigation of certain covariates over others. However, the lack of inclusion of the microbiome in the DAG, especially considering that most of the study findings were microbial-derived metabolite biomarkers, appears to be a fundamental flaw. Sanitation and micronutrients are proposed by the authors to have no effect on the host metabolome, yet sanitation and micronutrients have both been demonstrated in the literature to affect microbiome composition which can in turn affect the host metabolome.

      Thank you for your comment. We appreciate that the use of DAG and lack of the microbiome in the DAG are concerns. This has been already discussed in reply #1 to the editor that has been pasted below for convenience:

      Thank you for the comment and suggestions. It is important to highlight that there is no data on microbiome composition. We apologize if there was an impression such data is available. The main goal of conducting this national survey was to provide qualified and updated evidence on child nutrition to revise and propose new policies and nutritional guidelines for this demographic. Therefore, collection of stool derived microbiome (metagenomic) data was not one of the objectives of ENANI-2019. This is more explicitly stated as a study limitation in the revised manuscript on page 17, lines 463-467:

      “Lastly, stool microbiome data was not collected from children in ENANI-2019 as it was not a study objective in this large population-based nutritional survey. However, the lack of microbiome data does not reduce the importance/relevance, since there is no evidence that microbiome and factors affecting microbiome composition are confounders in the association between serum metabolome and child development.”

      Besides, one must consider the difficulties and costs in collecting and analyzing microbiome composition in a large population-based survey. In contrast, the metabolome data has been considered a priority as there was already blood specimens collected to inform policy on micronutrient deficiencies in Brazil. However, due to funding limitations we had to perform the analysis in a subset of our sample, still representative and large enough to test our hypothesis with adequate study power (more details below).

      We would like to argue that there is no evidence that microbiome and factors affecting microbiome composition are confounders on the association between serum metabolome and child development. First, one should revisit the properties of a confounder according to the epidemiology literature that in short states that confounding refers to an alternative explanation for a given conclusion, thus constituting one of the main problems for causal inference (Kleinbaum, Kupper, and Morgenstern, 1991; Greenland & Robins, 1986; VanderWeele, 2019). In our study, we highlight that certain serum metabolites associated with the developmental quotient (DQ) in children were circulating metabolites (e.g., cresol sulfate, hippuric acid, phenylacetylglutamine, TMAO) previously reported to depend on dietary exposures, host metabolism and gut microbiota activity. Our discussion cites other published work, including animal models and observational studies, which have reported how these bioactive metabolites in circulation are co-metabolized by commensal gut microbiota, and may play a role in neurodevelopment and cognition as mediated by environmental exposures early in life.

      In fact, the literature on the association between microbiome and infant development is very limited. We performed a search using terms ‘microbiome’ OR ‘microbiota’ AND ‘child development’ AND ‘systematic’ OR ‘meta-analysis’ and found only one study: ‘Associations between the human immune system and gut microbiome with neurodevelopment in the first 5 years of life: A systematic scoping review’ (DOI 10.1002/dev.22360). The authors conclude: ‘while the immune system and gut microbiome are thought to have interactive impacts on the developing brain, there remains a paucity of published studies that report biomarkers from both systems and associations with child development outcomes.’ It is important to highlight that our criteria to include confounders on the directed acyclic graph (DAG) was based on the literature of systematic reviews or meta-analysis and not on single isolated studies.

      In summary, we would like to highlight that there is no microbiome data in ENANI-2019 and in the event such data was present, we are confident that based on the current stage of the literature, there is no evidence to consider such construct in the DAG, as this procedure recommends that only variables associated with the exposure and the outcome should be included. Please find more details on DAG below.

      Moreover, we would like to clarify that we have not stated that sanitation and micronutrients have no effect on the serum metabolome, instead, these constructs were not considered on the DAG.

      To make it clearer, we have modified the passage about DAG in the methods section. New text, page 9, lines 234-241:

      “The subsequent step was to disentangle the selected metabolites from confounding variables. A Directed Acyclic Graph (DAG; Breitling et al., 2021) was used to more objectively determine the minimally sufficient adjustments for the regression models to account for potentially confounding variables while avoiding collider variables and variables in the metabolite-DQ causal pathways, which if controlled for would unnecessarily remove explained variance from the metabolites and hamper our ability to detect biomarkers. To minimize bias from subjective judgments of which variables should and should not be included as covariates, the DAG only included variables for which there was evidence from systematic reviews or meta-analysis of relationships with both the serum metabolome and DQ (Figure 1). Birth weight, breastfeeding, child's diet quality, the child's nutritional status, and the child's age were the minimal adjustments suggested by the DAG. Birth weight was a variable with high missing data, and indicators of breastfeeding practice data (referring to exclusive breastfeeding until 6 months and/or complemented until 2 years) were collected only for children aged 0–23 months. Therefore, those confounders were not included as adjustments. Child's diet quality was evaluated as MDD, the child's nutritional status as w/h z-score, and the child's age in months.”

      Additionally, the authors emphasized as part of the study selection criteria the following, "Due to the costs involved in the metabolome analysis, it was necessary to further reduce the sample size. Then, samples were stratified by age groups (6 to 11, 12 to 23, and 24 to 59 months) and health conditions related to iron metabolism, such as anemia and nutrient deficiencies. The selection process aimed to represent diverse health statuses, including those with no conditions, with specific deficiencies, or with combinations of conditions. Ultimately, through a randomized process that ensured a balanced representation across these groups, a total of 5,004 children were selected for the final sample (Figure 1)."

      Therefore, anemia and nutrient deficiencies are assumed by the reader to be important covariates, yet, the data on the final distribution of these covariates in the study cohort is not presented, nor are these covariates examined further.

      Thank you for the comments. We apologize for the misunderstanding and will amend the text to make our rationale clearer in the revised version of the manuscript.

      We believed the original text was clear enough in stating that the sampling process was performed aiming to maintain the representativeness of the original sample. This sampling process considered anemia and nutritional deficiencies, among other variables. However, we did not aim to include all relevant covariates of the DQ-metabolome relationship; these were decided using the DAG, as described in the manuscript and other sessions of this letter. Therefore, we would like to emphasize that our description of the sampling process does not assumes anemia and nutritional deficiencies are important covariates for the DQ-metabolome relationship.

      We rewrote this text part, page 11, lines 279-285:

      “Due to the costs involved in the metabolome analysis, it was necessary to reduce the sample size that is equivalent to 57% of total participants from ENANI-2019 with stored blood specimens. Therefore, the infants were stratified by age groups (6 to 11, 12 to 23, and 24 to 59 months) and health conditions such as anemia and micronutrient deficiencies. The selection process aimed to represent diverse health statuses to the original sample. Ultimately, 5,004 children were selected for the final sample through a random sampling process that ensured a balanced representation across these groups (Figure 2).”

      The inclusion of specific covariates in Table 1, Supplementary Table 1, the statistical models, and the mediation analysis is thus currently biased as it is not well justified.

      We appreciate the reviewer comment. However, it would have been ideal to receive a comment/critic with a clearer and more straightforward argumentation, so we could try to address it based on our interpretation.

      Please refer to our response to item #1 above regarding the variables in the tables and figures. The covariates in the statistical models were selected using the DAG, which is a cutting-edge procedure that aims to avoid bias and overfitting, a common situation when confounders are adjusted for without a clear rationale. We elaborate on the advantages of using the DAG in response to item #6 and in page 9 of the manuscript. The statistical models we use follow the best practices in the field when dealing with a large number of collinear predictors and a continuous outcome (see our response to the editor’s 4th comment). Finally, the mediation analyses were done to explore a few potential explanations for our results from the PLSR and multiple regression analyses. We only ran mediation analyses for plausible mechanisms for which the variables of interest were available in our data. Please see our response to reviewer 3’s item #1 for a more detailed explanation on the mediation analysis.

      Finally, it is unclear what the partial-least squares regression adds to the paper, other than to discard potentially interesting metabolites found by the initial correlation analysis.

      Thank you for the question. As explained in response to the editor’s item #4, PLS-based analyses are among the most commonly used analyses for parsing metabolomic data (Blekherman et al., 2011; Wold et al., 2001; Gromski et al. 2015). This procedure is especially appropriate for cases in which there are multiple collinear predictor variables as it allows us to compare the predictive value of all the variables without relying on corrections for multiple testing. Testing each metabolite in separate correlations corrected for multiple comparisons is less appropriate because the correlated nature of the metabolites means the comparisons are not truly independent and would cause the corrections (which usually assume independence) to be overly strict. As such, we only rely on the correlations as an initial, general assessment that gives context to subsequent, more specific analyses. Given that our goal is to select the most predictive metabolites, discarding the less predictive metabolites is precisely what we aim to achieve. As explained above and in response to the editor’s item #4, the PLSR allows us to reach that goal without introducing bias in our estimates or losing statistical power.  

      Reviewer #2 (Public Review):

      A strength of the work lies in the number of children Padilha et al. were able to assess (5,004 children aged 6-59 months) and in the extensive screening that the Authors performed for each participant. This type of large-scale study is uncommon in low-to-middle-income countries such as Brazil.

      The Authors employ several approaches to narrow down the number of potentially causally associated metabolites.

      Could the Authors justify on what basis the minimum dietary diversity score was dichotomized? Were sensitivity analyses undertaken to assess the effect of this dichotomization on associations reported by the article? Consumption of each food group may have a differential effect that is obscured by this dichotomization.

      Thank you for the observation. We would like to emphasize that the child's diet quality was assessed using the minimum dietary diversity (MDD) indicator proposed by the WHO (World Health Organization & United Nations Children’s Fund (UNICEF), 2021). This guideline proposes the cutoff used in the present study. We understand the reviewer’s suggestion to use the consumption of healthy food groups as an evaluation of diet quality, but we chose to follow the WHO proposal to assess dietary diversity. This indicator is widely accepted and used as a marker and provides comparability and consistency with other published studies.

      Could the Authors specify the statistical power associated with each analysis?

      To the best of our knowledge, we are not aware of power calculation procedures for PLS-based analyses. However, given our large sample size, we do not believe power was an issue with the analyses. For our regression analyses, which typically have 4 predictors, we had 95% power to detect an f-squared of 0.003 and an r of 0.05 in a two-sided correlation test considering an alpha level of 0.05.

      New text, page 11, lines 296-298:

      “Given the size of our sample, statistical power is not an issue in our analyses. Considering an alpha of 0.05 for a two-sided test, a sample size of 5000 has 95% power to detect a correlation of r = 0.05 and an effect of f2 = 0.003 in a multiple regression model with 4 predictors.”

      Could the Authors describe in detail which metric they used to measure how predictive PLSR models are, and how they determined what the "optimal" number of components were?

      We chose the model with the fewest number of components that maximized R2 and minimized root mean squared error of prediction (RMSEP). In the training data, the model with 4 components had a lower R2 but a lower RMSEP, therefore we chose the model with 3 components which had a higher R2 than the 4-component model and lower RMSEP than the model with 2 components. However, the number of components in the model did not meaningfully change the rank order of the metabolites on the VIP index.

      New text, page 8, lines 220-224:

      “To better assess the predictiveness of each metabolite in a single model, a PLSR was conducted. PLS-based analyses are the most commonly used analyses when determining the predictiveness of a large number of variables as they avoid issues with collinearity, sample size, and corrections for multiple-testing (Blekherman et al., 2011; Wold et al., 2001; Gromski et al. 2015).”

      New text, page 12, lines 312-314:

      “In PLSR analysis, the training data suggested that three components best predicted the data (the model with three components had the highest R2, and the root mean square error of prediction (RMSEP) was only slightly lower with four components). In comparison, the test data showed a slightly more predictive model with four components (Figure 3—figure supplement 2).”

      The Authors use directed acyclic graphs (DAG) to identify confounding variables of the association between metabolites and DQ. Could the dataset generated by the Authors have been used instead? Not all confounding variables identified in the literature may be relevant to the dataset generated by the Authors.

      Thank you for the question. The response is most likely no, the current dataset should not be used to define confounders as these must be identified based on the literature. The use of DAGs has been widely explored as a valid tool for justifying the choice of confounding factors in regression models in epidemiology. This is because DAGs allow for a clear visualization of causal relationships, clarify the complex relationships between exposure and outcome. Besides, DAGs demonstrate the authors' transparency by acknowledging factors reported as important but not included/collected in the study. This has been already discussed in reply #1 to the editor that has been pasted below for convenience.

      Thank you for the comment and suggestions. It is important to highlight that there is no data on microbiome composition. We apologize if there was an impression such data is available. The main goal of conducting this national survey was to provide qualified and updated evidence on child nutrition to revise and propose new policies and nutritional guidelines for this demographic. Therefore, collection of stool derived microbiome (metagenomic) data was not one of the objectives of ENANI-2019. This is more explicitly stated as a study limitation in the revised manuscript on page 17, lines 463-467:

      “Lastly, stool microbiome data was not collected from children in ENANI-2019 as it was not a study objective in this large population-based nutritional survey. However, the lack of microbiome data does not reduce the importance/relevance, since there is no evidence that microbiome and factors affecting microbiome composition are confounders in the association between serum metabolome and child development.”

      Besides, one must consider the difficulties and costs in collecting and analyzing microbiome composition in a large population-based survey. In contrast, the metabolome data has been considered a priority as there was already blood specimens collected to inform policy on micronutrient deficiencies in Brazil. However, due to funding limitations we had to perform the analysis in a subset of our sample, still representative and large enough to test our hypothesis with adequate study power (more details below).

      We would like to argue that there is no evidence that microbiome and factors affecting microbiome composition are confounders on the association between serum metabolome and child development. First, one should revisit the properties of a confounder according to the epidemiology literature that in short states that confounding refers to an alternative explanation for a given conclusion, thus constituting one of the main problems for causal inference (Kleinbaum, Kupper, and Morgenstern, 1991; Greenland & Robins, 1986; VanderWeele, 2019). In our study, we highlight that certain serum metabolites associated with the developmental quotient (DQ) in children were circulating metabolites (e.g., cresol sulfate, hippuric acid, phenylacetylglutamine, TMAO) previously reported to depend on dietary exposures, host metabolism and gut microbiota activity. Our discussion cites other published work, including animal models and observational studies, which have reported how these bioactive metabolites in circulation are co-metabolized by commensal gut microbiota, and may play a role in neurodevelopment and cognition as mediated by environmental exposures early in life.

      In fact, the literature on the association between microbiome and infant development is very limited. We performed a search using terms ‘microbiome’ OR ‘microbiota’ AND ‘child development’ AND ‘systematic’ OR ‘meta-analysis’ and found only one study: ‘Associations between the human immune system and gut microbiome with neurodevelopment in the first 5 years of life: A systematic scoping review’ (DOI 10.1002/dev.22360). The authors conclude: ‘while the immune system and gut microbiome are thought to have interactive impacts on the developing brain, there remains a paucity of published studies that report biomarkers from both systems and associations with child development outcomes.’ It is important to highlight that our criteria to include confounders on the directed acyclic graph (DAG) was based on the literature of systematic reviews or meta-analysis and not on single isolated studies.

      In summary, we would like to highlight that there is no microbiome data in ENANI-2019 and in the event such data was present, we are confident that based on the current stage of the literature, there is no evidence to consider such construct in the DAG, as this procedure recommends that only variables associated with the exposure and the outcome should be included. Please find more details on DAG below.

      Moreover, we would like to clarify that we have not stated that sanitation and micronutrients have no effect on the serum metabolome, instead, these constructs were not considered on the DAG.

      To make it clearer, we have modified the passage about DAG in the methods section. New text, page 9, lines 234-241:

      “The subsequent step was to disentangle the selected metabolites from confounding variables. A Directed Acyclic Graph (DAG; Breitling et al., 2021) was used to more objectively determine the minimally sufficient adjustments for the regression models to account for potentially confounding variables while avoiding collider variables and variables in the metabolite-DQ causal pathways, which if controlled for would unnecessarily remove explained variance from the metabolites and hamper our ability to detect biomarkers. To minimize bias from subjective judgments of which variables should and should not be included as covariates, the DAG only included variables for which there was evidence from systematic reviews or meta-analysis of relationships with both the serum metabolome and DQ (Figure 1). Birth weight, breastfeeding, child's diet quality, the child's nutritional status, and the child's age were the minimal adjustments suggested by the DAG. Birth weight was a variable with high missing data, and indicators of breastfeeding practice data (referring to exclusive breastfeeding until 6 months and/or complemented until 2 years) were collected only for children aged 0–23 months. Therefore, those confounders were not included as adjustments. Child's diet quality was evaluated as MDD, the child's nutritional status as w/h z-score, and the child's age in months.”

      Were the systematic reviews or meta-analyses used in the DAG performed by the Authors, or were they based on previous studies? If so, more information about the methodology employed and the studies included should be provided by the Authors.

      Thank you for the question. The reviews or meta-analyses used in the DAG have been conducted by other authors in the field. This has been laid out more clearly in our methods section.

      New text, page 9, lines 234-241:

      “The subsequent step was to disentangle the selected metabolites from confounding variables. A Directed Acyclic Graph (DAG; Breitling et al., 2021) was used to more objectively determine the minimally sufficient adjustments for the regression models to account for potentially confounding variables while avoiding collider variables and variables in the metabolite-DQ causal pathways, which if controlled for would unnecessarily remove explained variance from the metabolites and hamper our ability to detect biomarkers. To minimize bias from subjective judgments of which variables should and should not be included as covariates, the DAG only included variables for which there was evidence from systematic reviews or meta-analysis of relationships with both the metabolome and DQ (Figure 1). Birth weight, breastfeeding, child's diet quality, the child's nutritional status, and the child's age were the minimal adjustments suggested by the DAG. Birth weight was a variable with high missing data, and indicators of breastfeeding practice data (referring to exclusive breastfeeding until 6 months and/or complemented until 2 years) were collected only for children aged 0–23 months. Therefore, those confounders were not included as adjustments. Child's diet quality was evaluated as MDD, the child's nutritional status as w/h z-score, and the child's age in months.”

      Approximately 72% of children included in the analyses lived in households with a monthly income superior to the Brazilian minimum wage. The cohort is also biased towards households with a higher level of education. Both of these measures correlate with developmental quotient. Could the Authors discuss how this may have affected their results and how generalizable they are?

      Thank you for your comment. This has been already discussed in reply #6 to the editor and that has been pasted below for convenience.

      Thank you for highlighting this point. The ENANI-2019 is a population-based household survey with national coverage and representativeness for macroregions, sex, and one-year age groups (< 1; 1-1.99; 2-2.99; 3-3.99; 4-5). Furthermore, income quartiles of the census sector were used in the sampling. The study included 12,524 households 14,588 children, and 8,829 infants with blood drawn.

      Due to the costs involved in metabolome analysis, it was necessary to further reduce the sample size to around 5,000 children that is equivalent to 57% of total participants from ENANI-2019 with stored blood specimens. To avoid a biased sample and keep the representativeness and generability, the 5,004 selected children were drawn from the total samples of 8,829 to keep the original distribution according age groups (6 to 11 months, 12 to 23 months, and 24 to 59 months), and some health conditions related to iron metabolism, e.g., anemia and nutrient deficiencies. Then, they were randomly selected to constitute the final sample that aimed to represent the total number of children with blood drawn. Hence, our efforts were to preserve the original characteristics of the sample and the representativeness of the original sample.

      The ENANI-2019 study does not appear to present a bias towards higher socioeconomic status. Evidence from two major Brazilian population-based household surveys supports this claim. The 2017-18 Household Budget Survey (POF) reported an average monthly household income of 5,426.70 reais, while the Continuous National Household Sample Survey (PNAD) reported that in 2019, the nominal monthly per capita household income was 1,438.67 reais. In comparison, ENANI-2019 recorded a household income of 2,144.16 reais and a per capita income of 609.07 reais in infants with blood drawn, and 2,099.14 reais and 594.74 reais, respectively, in the serum metabolome analysis sample.

      In terms of maternal education, the 2019 PNAD-Education survey indicated that 48.8% of individuals aged 25 or older had at least 11 years of schooling. When analyzing ENANI-2019 under the same metric, we found that 56.26% of ≥25 years-old mothers of infants with blood drawn had 11 years of education or more, and 51.66% in the metabolome analysis sample. Although these figures are slightly higher, they remain within a reasonable range for population studies.

      It is well known that higher income and maternal education levels can influence child health outcomes, and acknowledging this, ENANI-2019 employed rigorous sampling methods to minimize selection biases. This included stratified and complex sampling designs to ensure that underrepresented groups were adequately included, reducing the risk of skewed conclusions. Therefore, the evidence strongly suggests that the ENANI-2019 sample is broadly representative of the Brazilian population in terms of both socioeconomic status and educational attainment.

      Further to this, could the Authors describe how inequalities in access to care in the Brazilian population may have affected their results? Could they have included a measure of this possible discrepancy in their analyses?

      Thank you for the concern.

      The truth is that we are not in a position to answer this question because our study focused on gathering data on infant nutritional status and there is very limited information on access to care to allow us to hypothesize. Another important piece of information is that this national survey used sampling procedures that aimed to make the sample representative of the 15 million Brazilian infants under 5 years. Therefore, the sample is balanced according to socio-economic strata, so there is no evidence to make us believe inequalities in access to health care would have played a role.

      The Authors state that the results of their study may be used to track children at risk for developmental delays. Could they discuss the potential for influencing policies and guidelines to address delayed development due to malnutrition and/or limited access to certain essential foods?

      The point raised by the reviewer is very relevant. Recognizing that dietary and microbial derived metabolites involved in the gut-brain axis could be related to children's risk of developmental delays is the first step to bringing this topic to the public policy agenda. We believe the results can contribute to the literature, which should be used to accumulate evidence to overcome knowledge gaps and support the formulation and redirection of public policies aimed at full child growth and development; the promotion of adequate and healthy nutrition and food security; the encouragement, support, and protection of breastfeeding; and the prevention and control of micronutrient deficiencies.  

      Reviewer #3 (Public Review):

      The ENANI-2019 study provides valuable insights into child nutrition, development, and metabolomics in Brazil, highlighting both challenges and opportunities for improving child health outcomes through targeted interventions and further research.

      Readers might consider the following questions:

      (1) Should investigators study the families through direct observation of diet and other factors to look for a connection between food taken in and gut microbiome and child development?

      As mentioned before, the ENANI-2019 did not collect data on stool derived microbiome. However, there is data on child dietary intake with 24-hour recall that can be further explored in other studies.

      (2) Can an examination of the mother's gut microbiome influence the child's microbiome? Can the mother or caregiver's microbiome influence early childhood development?

      The questions raised by the reviewer are interesting and has been explored by other authors. However, we do not have microbiota data from the child nor from the mother/caregiver.

      (3) Is developmental quotient enough to study early childhood development? Is it comprehensive enough?

      Yes, we are confident it is comprehensive enough.

      According to the World Health Organization, the term Early Childhood Development (ECD) refers to the cognitive, physical, language, motor, social and emotional development between 0 - 8 years of age. The SWCY milestones assess the domains of cognition, language/communication and motor. Therefore, it has enough content validity to represent ECD.

      The SWYC is recommended for screening ECD by the American Society of Pediatrics. Furthermore, we assessed the internal consistency of the SWYC milestones questionnaire using ENANI-2019 data and Cronbach's alpha. The findings indicated satisfactory reliability (0.965; 95% CI: 0.963–0.968).

      The SWCY is a screening instrument and indicates if the ECD is not within the expected range. If one of the above-mentioned domains are not achieved as expected the child may be at risk of ECD delay. Therefore, DQ<1 indicates that a child has not reached the expected ECD for the age group. We cannot say that children with DQ≥1 have full ECD, since we do not assess the socio-emotional domains. However, DQ can track the risk of ECD delay.

      References

      Blekherman, G., Laubenbacher, R., Cortes, D. F., Mendes, P., Torti, F. M., Akman, S., ... & Shulaev, V. (2011). Bioinformatics tools for cancer metabolomics. Metabolomics, 7, 329-343.

      Gromski, P. S., Muhamadali, H., Ellis, D. I., Xu, Y., Correa, E., Turner, M. L., & Goodacre, R. (2015). A tutorial review: Metabolomics and partial least squares-discriminant analysis–a marriage of convenience or a shotgun wedding. Analytica chimica acta, 879, 10-23.

      Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics. Chemometrics and intelligent laboratory systems, 58(2), 109-130.

      LUIZ, RR., and STRUCHINER, CJ. Inferência causal em epidemiologia: o modelo de respostas potenciais [online]. Rio de Janeiro: Editora FIOCRUZ, 2002. 112 p. ISBN 85-7541-010-5. Available from SciELO Books http://books.scielo.org.

      GREENLAND, S. & ROBINS, J. M. Identifiability, exchangeability, and epidemiological Confounding. International Journal of Epidemiolgy, 15(3):413-419, 1986.

      Freitas-Costa NC, Andrade PG, Normando P, et al. Association of development quotient with nutritional status of vitamins B6, B12, and folate in 6–59-month-old children: Results from the Brazilian National Survey on Child Nutrition (ENANI-2019). The American journal of clinical nutrition 2023;118(1):162-73. doi: https://doi.org/10.1016/j.ajcnut.2023.04.026

      Sheldrick RC, Schlichting LE, Berger B, et al. Establishing New Norms for Developmental Milestones. Pediatrics 2019;144(6) doi: 10.1542/peds.2019-0374 [published Online First: 2019/11/16]

      Drachler Mde L, Marshall T, de Carvalho Leite JC. A continuous-scale measure of child development for population-based epidemiological surveys: a preliminary study using Item Response Theory for the Denver Test. Paediatric and perinatal epidemiology 2007;21(2):138-53. doi: 10.1111/j.1365-3016.2007.00787.x [published Online First: 2007/02/17]

      VanderWeele, TJ Princípios de seleção de fatores de confusão. Eur J Epidemiol 34, 211–219 (2019). https://doi.org/10.1007/s10654-019-00494-6

      David G. Kleinbaum, Lawrence L. Kupper; Hal Morgenstern. Epidemiologic Research: Principles and Quantitative Methods. 1991

      Yan R, Liu X, Xue R, Duan X, Li L, He X, Cui F, Zhao J. Association between internet exclusion and depressive symptoms among older adults: panel data analysis of five longitudinal cohort studies. EClinicalMedicine 2024;75. doi: 10.1016/j.eclinm.2024.102767.

      Zhong Y, Lu H, Jiang Y, Rong M, Zhang X, Liabsuetrakul T. Effect of homemade peanut oil consumption during pregnancy on low birth weight and preterm birth outcomes: a cohort study in Southwestern China. Glob Health Action. 2024 Dec 31;17(1):2336312.

      Aristizábal LYG, Rocha PRH, Confortin SC, et al. Association between neonatal near miss and infant development: the Ribeirão Preto and São Luís birth cohorts (BRISA). BMC Pediatr. 2023;23(1):125. Published 2023 Mar 18. doi:10.1186/s12887-023-03897-3

      Al-Haddad BJS, Jacobsson B, Chabra S, et al. Long-term risk of neuropsychiatric disease after exposure to infection in utero. JAMA Psychiatry. 2019;76(6):594-602. doi:10.1001/jamapsychiatry.2019.0029

      Chan, A.Y.L., Gao, L., Hsieh, M.HC. et al. Maternal diabetes and risk of attention-deficit/hyperactivity disorder in offspring in a multinational cohort of 3.6 million mother–child pairs. Nat Med 30, 1416–1423 (2024).

      Hernan MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC.

      Greenland S; Pearl J; Robins JM. Confounding and collapsibility in causal inference. Statist Sci. 14 (1) 29 - 46 1999. https://doi.org/10.1214/ss/1009211805

    1. Author response:

      Reviewer #2 (Public Review):

      M. El Amri et al., investigated the functions of Marcks and Marcks like 1 during spinal cord (SC) development and regeneration in Xenopus laevis. The authors rigorously performed loss of function with morpholino knock-down and CRISPR knock-out combining rescue experiments in developing spinal cord in embryo and regeneration in tadpole stage.

      For the assays in the developing spinal cord, a unilateral approach (knock-down/out only one side of the embryo) allowed the authors to assess the gene functions by direct comparing one-side (e.g. mutated SC) to the other (e.g. wild type SC on the other side). For the assays in regenerating SC, the authors microinject CRISPR reagents into 1-cell stage embryo. When the embryo (F0 crispants) grew up to tadpole (stage 50), the SC was transected. They then assessed neurite outgrowth and progenitor cell proliferation. The validation of the phenotypes was mostly based on the quantification of immunostaining images (neurite outgrowth: acetylated tubulin, neural progenitor: sox2, sox3, proliferation: EdU, PH3), that are simple but robust enough to support their conclusions. In both SC development and regeneration, the authors found that Marcks and Marcksl1 were necessary for neurite outgrowth and neural progenitor cell proliferation.

      The authors performed rescue experiments on morpholino knock-down and CRISPR knock-out conditions by Marcks and Marcksl1 mRNA injection for SC development and pharmacological treatments for SC development and regeneration. The unilateral mRNA injection rescued the loss-of-function phenotype in the developing SC. To explore the signalling role of these molecules, they rescued the loss-of-function animals by pharmacological reagents They used S1P: PLD activator, FIPI: PLD inhibitor, NMI: PIP2 synthesis activator and ISA-2011B: PIP2 synthesis inhibitor. The authors found the activator treatment rescued neurite outgrowth and progenitor cell proliferation in loss of function conditions. From these results, the authors proposed PIP2 and PLD are the mediators of Marcks and Marcksl1 for neurite outgrowth and progenitor cell proliferation during SC development and regeneration. The results of the rescue experiments are particularly important to assess gene functions in loss of function assays, therefore, the conclusions are solid. In addition, they performed gain-of-function assays by unilateral Marcks or Marcksl1 mRNA injection showing that the injected side of the SC had more neurite outgrowth and proliferative progenitors. The conclusions are consistent with the loss-of-function phenotypes and the rescue results. Importantly, the authors showed the linkage of the phenotype and functional recovery by behavioral testing, that clearly showed the crispants with SC injury swam less distance than wild types with SC injury at 10-day post surgery.

      Prior to the functional assays, the authors analyzed the expression pattern of the genes by in situ hybridization and immunostaining in developing embryo and regenerating SC. They confirmed that the amount of protein expression was significantly reduced in the loss of function samples by immunostaining with the specific antibodies that they made for Marcks and Marcksl1. Although the expression patterns are mostly known in previous works during embryo genesis, the data provided appropriate information to readers about the expression and showed efficiency of the knock-out as well.

      MARCKS family genes have been known to be expressed in the nervous system. However, few studies focus on the function in nerves. This research introduced these genes as new players during SC development and regeneration. These findings could attract broader interests from the people in nervous disease model and medical field. Although it is a typical requirement for loss of function assays in Xenopus laevis, I believe that the efficient knock-out for four genes by CRISPR/Cas9 was derived from their dedication of designing, testing and validation of the gRNAs and is exemplary.

      Weaknesses,

      (1) Why did the authors choose Marcks and Marcksl1? The authors mentioned that these genes were identified with a recent proteomic analysis of comparing SC regenerative tadpole and non-regenerative froglet (Line (L) 54-57). However, although it seems the proteomic analysis was their own dataset, the authors did not mention any details to select promising genes for the functional assays (this article). In the proteomic analysis, there must be other candidate genes that might be more likely factors related to SC development and regeneration based on previous studies, but it was unclear what the criteria to select Marcks and Marcksl1 was.

      To highlight the rationale for selecting these proteins, we reworded the sentence as follows: “A recent proteomic screen … after SCI identified a number of proteins that are highly upregulated at the tadpole stage but downregulated in froglets (Kshirsagar, 2020). These proteins included Marcks and Marcksl1, which had previously been implicated in the regeneration of other tissues (El Amri et al., 2018) suggesting a potential role for these proteins also in spinal cord regeneration.”

      (2) Gene knock-out experiments with F0 crispants,

      The authors described that they designed and tested 18 sgRNAs to find the most efficient and consistent gRNA (L191-195). However, it cannot guarantee the same phenotypes practically, due to, for example, different injection timing, different strains of Xenopus laevis, etc. Although the authors mentioned the concerns of mosaicism by themselves (L180-181, L289-292) and immunostaining results nicely showed uniformly reduced Marcks and Marcksl1 expression in the crispants, they did not refer to this issue explicitly.

      To address this issue, we state explicitly in line 208-212: “We also confirmed by immunohistochemistry that co-injection of marcks.L/S and marcksl1.L/S sgRNA, which is predicted to edit all four homeologs (henceforth denoted as 4M CRISPR) drastically reduced immunostaining for Marcks and Marcksl1 protein on the injected side (Fig. S6 B-G), indicating that protein levels are reduced in gene-edited embryos.”

      (3) Limitations of pharmacological compound rescue

      In the methods part, the authors describe that they performed titration experiments for the drugs (L702-704), that is a minimal requirement for this type of assay. However, it is known that a well characterized drug is applied, if it is used in different concentrations, the drug could target different molecules (Gujral TS et al., 2014 PNAS). Therefore, it is difficult to eliminate possibilities of side effects and off targets by testing only a few compounds.

      As explained in the responses to reviewer 1, we have completely rewritten and toned down our presentation of the pharmacological result and explicitly mention in our discussion now the possibility of side effects.

    1. Welcome back and in this demo lesson you're going to evolve the infrastructure which you've been using throughout this section of the course.

      In this demo lesson you're going to add private internet access capability using NAT gateways.

      So you're going to be applying a cloud formation template which creates this base infrastructure.

      It's going to be the animals for life VPC with infrastructure in each of three availability zones.

      So there's a database subnet, an application subnet and a web subnet in availability zone A, B and C.

      Now to this point what you've done is configured public subnet internet access and you've done that using an internet gateway together with routes on these public subnets.

      In this demo lesson you're going to add NAT gateways into each availability zone so A, B and C and this will allow this private EC2 instance to have access to the internet.

      Now you're going to be deploying NAT gateways into each availability zone so that each availability zone has its own isolated private subnet access to the internet.

      It means that if any of the availability zones fail then each of the others will continue operating because these route tables which are attached to the private subnets they point at the NAT gateway within that availability zone.

      So each availability zone A, B and C has its own corresponding NAT gateway which provides private internet access to all of the private subnets within that availability zone.

      Now in order to implement this infrastructure you're going to be applying a one-click deployment and that's going to create everything that you see on screen now apart from these NAT gateways and the route table configurations.

      So let's go ahead and move across to our AWS console and get started implementing this architecture.

      Okay so now we're at the AWS console as always just make sure that you're logged in to the general AWS account as the I am admin user and you'll need to have the Northern Virginia region selected.

      Now at the end of the previous demo lesson you should have deleted all of the infrastructure that you've created up until that point so the animals for live VPC as well as the Bastion host and the associated networking.

      So you should have a relatively clean AWS account.

      So what we're going to do first is use a one-click deployment to create the infrastructure that we'll need within this demo lesson.

      So attached to this demo lesson is a one-click deployment link so go ahead and open that link.

      That's going to take you to a quick create stack screen.

      Everything should be pre-populated the stack name should be a4l just scroll down to the bottom check this capabilities box and then click on create stack.

      Now this will start the creation process of this a4l stack and we will need this to be in a create complete state before we continue.

      So go ahead pause the video wait for your stack to change into create complete and then we good to continue.

      Okay so now this stacks moved into a create complete state then we good to continue.

      So what we need to do before we start is make sure that all of our infrastructure has finished provisioning.

      To do that just go ahead and click on the resources tab of this cloud formation stack and look for a4l internal test.

      This is an EC2 instance a private EC2 instance so this doesn't have any public internet connectivity and we're going to use this to test on that gateway functionality.

      So go ahead and click on this icon under physical ID and this is going to move you to the EC2 console and you'll be able to see this a4l - internal - test instance.

      Now currently in my case it's showing as running but the status check is showing as initializing.

      Now we'll need this instance to finish provisioning before we can continue with the demo.

      What should happen is this status check should change from initializing to two out of two status checks and once you're at that point you should be able to right click and select connect and choose session manager and then have the option of connecting.

      Now you'll see that I don't because this instance hasn't finished its provisioning process.

      So what I want you to do is to go ahead and pause this video wait for your status checks to change to two out of two checks and then just go ahead and try to connect to this instance using session manager.

      Only resume the video once you've been able to click on connect under the session manager tab and don't worry if this takes a few more minutes after the instance finishes provisioning before you can connect to session manager.

      So go ahead and pause the video and when you can connect to the instance you're good to continue.

      Okay so in my case it took about five minutes for this to change to two out of two checks past and then another five minutes before I could connect to this EC2 instance.

      So I can right click on here and put connect.

      I'll have the option now of picking session manager and then I can click on connect and this will connect me in to this private EC2 instance.

      Now the reason why you're able to connect to this private instance is because we're using session manager and I'll explain exactly how this product works elsewhere in the course but essentially it allows us to connect into an EC2 instance with no public internet connectivity and it's using VPC interface endpoints to do that which I'll be explaining elsewhere in the course but what you should find when you're connected to this instance if you try to ping any internet IP address so let's go ahead and type ping and then a space 1.1.1.1.1 and press enter you'll note that we don't have any public internet connectivity and that's because this instance doesn't have a public IP version for address and it's not in a subnet with a route table which points at the internet gateway.

      This EC2 instance has been deployed into the application a subnet which is a private subnet and it also doesn't have a public IP version for address.

      So at this point what we need to do is go ahead and deploy our NAT gateways and these NAT gateways are what will provide this private EC2 instance with connectivity to the public IP version for internet so let's go ahead and do that.

      Now to do that we need to be back at the main AWS console click in the services search box at the top type VPC and then right click and open that in a new tab.

      Once you do that go ahead and move to that tab once you there click on NAT gateways and create a NAT gateway.

      Okay so once you're here you'll need to specify a few things you'll need to give the NAT gateway a name you'll need to pick a public subnet for the NAT gateway to go into and then you'll need to give the NAT gateway an elastic IP address which is an IP address which doesn't change.

      So first we'll set the name of the NAT gateway and we'll choose to use a4l for animals for life -vpc1 -natgw and then -a because this is going into availability zone A.

      Next we'll need to pick the public subnet that the NAT gateway will be going into so click on the subnet drop down and then select the web a subnet which is the public subnet in availability zone a so sn -web -a.

      Now we need to give this NAT gateway an elastic IP it doesn't currently have one so we need to click on allocate elastic IP which gives it an allocation.

      Don't worry about the connectivity type we'll be covering that elsewhere in the course just scroll down to the bottom and create the NAT gateway.

      Now this process will take some time and so we need to go ahead and create the two other NAT gateways.

      So click on NAT gateways at the top and then we're going to create a second NAT gateway.

      So go ahead and click on create NAT gateway again this time we'll call the NAT gateway a4l -vpc1 -natgw -b and this time we'll pick the web b subnet so sn -web -b allocated elastic IP again and click on create NAT gateway then we'll follow the same process a third time so click create NAT gateway use the same naming scheme but with -c pick the web c subnet from the list allocate an elastic IP and then scroll down and click on create NAT gateway and at this point we've got the three NAT gateways that are being created they're all in appending state if we go to elastic IPs we can see the three elastic IPs which have been allocated to the NAT gateways and we can scroll to the right or left and see details on these IPs and if we wanted we could release these IPs back to the account once we'd finish with them now at this point you need to go ahead and pause the video and resume it once all three of those NAT gateways have moved away from appending state we need them to be in an available state ready to go before we can continue with this demo so go ahead and pause and resume once all three have changed to an available state okay so all these are now in an available state so that means they're good to go they're providing service now if you scroll to the right in this list you're able to see additional information about these NAT gateways so you can see the elastic and private IP address the VPC and then the subnet that each of these NAT gateways are located in what we need to do now is configure the routing so that the private instances can communicate via the NAT gateways so right click on route tables and open in a new tab and we need to create a new route table for each of the availability zones so go ahead and click on create route table first we need to pick the VPC for this route table so click on the VPC drop down and then select the animals for live VPC so a for L hyphen VPC one once selected go ahead and name at the route table we're going to keep the naming scheme consistent so a for L hyphen VPC one hyphen RT for route table hyphen private a so enter that and click on create then close that dialogue down and create another route table this time we'll use the same naming scheme but of course this time it will be RT hyphen private B select the animals for life VPC and click on create close that down and then finally click on create route table again this time a for L hyphen VPC one hyphen RT hyphen private C again click on the VPC drop down and select the animals for life VPC and then click on create so that's going to leave us with three route tables one for each availability zone what we need to do now is create a default route within each of these route tables and that route is going to point at the NAT gateway in the same availability zone so select the route table private a and then click on the routes tab once you've selected the routes tab click on edit routes and we're going to add a new route it's going to be the IP version for default route of 0.0.0.0/0 and then click on target and pick NAT gateway and we're going to pick the NAT gateway in availability zone a and because we named them it makes it easy to select the relevant one from this list so go ahead and pick a for L hyphen VPC one hyphen NAT GW hyphen a so because this is the route table in availability zone a we need to pick the same NAT gateway so save that and close and now we'll be doing the same process for the route table in availability zone B make sure the routes tab is selected and click on edit routes click on add route again 0.0.0.0/0 and then for target pick NAT gateway and then pick the NAT gateway that's in availability zone B so NAT GW hyphen B once you've done that save the route table and then next select the route table in availability zone C so select RT hyphen private C make sure the routes tab is selected and click on edit routes again we'll be adding a route it will be the IP version for default route so 0.0.0.0/0 select a target go to NAT gateway and pick the NAT gateway in availability zone C so NAT GW hyphen C once you've done that save the route table and now our private EC2 instance should be able to ping 1.1.1.1 because we have the routing infrastructure in place so let's move back to our private instance and we can see that it's not actually working now the reason for this is that although we have created these routes we haven't actually associated these route tables with any of the subnets subnets in a VPC which don't have an explicit route table association are associated with the main route table now we need to explicitly associate each of these route tables with the subnets inside that same AZ so let's go ahead and pick RT hyphen private A we'll go through in order so select it click on the subnet associations tab and edit subnet associations and then you need to pick all of the private subnets in AZ A so that's the reserved subnet so reserved hyphen A the app subnet so app hyphen A and the DB subnet so DB hyphen A so all of these are the private subnets in availability zone A notice how all the public subnets are associated with this custom route table you created earlier but the ones we're setting up now are still associated with the main route table so we're going to resolve that now by associating this route table with those subnets so click on save and this will associate all of the private subnets in AZ A with the AZ A route table so now we're going to do the same process for AZ B and AZ C and we'll start with AZ B so select the private B route table click on subnet associations edit subnet associations so select application B database B and then reserved B and then scroll down and save the associations and then select the private C route table click on subnet associations edit subnet associations and then select reserved C database C and then application C and then scroll down and save those associations and now that we've associated these route tables with the subnets and now that we've added those default routes if we go back to session manager where we still have the connection open to the private EC2 instance we should see that the ping has started to work and that's because we now have a NAT gateway providing service to each of the private subnets in all of the three availability zones okay so that's everything you needed to cover in this demo lesson now it's time to clean up the account and return it to the same state as it was at the start of this demo lesson from this point on within the course you're going to be using automation and so we can remove all the configuration that we've done inside this demo lesson so the first thing we need to do is to reverse the route table changes that we've done so we need to go ahead and select the RT hyphen private a route table go ahead and select subnet associations and then edit the subnet associations and then just uncheck all of these subnets and this will return these to being associated with the main route table so scroll down and click on save do the same for RT hyphen private be so deselect all of these associations and click on save and then the same for RT hyphen private see so select it go to subnet associations and then edit them and remove all of these subnets and click on save next select all of these private route tables these are the ones that we created in this lesson so select them all click on the actions drop down and then delete route table and confirm by clicking delete route tables go to NAT gateways on the left and we need to select each of the NAT gateways in turn so a and then click on actions and delete NAT gateway type delete click delete then select be and do the same process actions delete NAT gateway type delete click delete and finally the same for see so select the C NAT gateway click on actions and delete NAT gateway you'll need to type delete to confirm click on delete now we're going to need all of these to be in a fully deleted state before we can continue so hit refresh and make sure that all three NAT gateways are deleted if yours aren't deleted if they're still listed in a deleting state then go ahead and pause the video and resume once all of these have changed to deleted at this point all of the NAT gateways have deleted so you can go ahead and click on elastic IPs and we need to release each of these IPs so select one of them and then click on actions and release elastic IP addresses and click release and do the same process for the other two click on release then finally actions release IP click on release once that's done move back to the cloud formation console select the stack which was created by the one click deployment at the start of the lesson and click on delete and then confirm that deletion and that will remove the cloud formation stack and any resources created as part of this demo and at that point once that finishes deleting the account has been returned into the same state as it was at the start of this demo lesson so I hope this demo lesson has been useful just to reiterate what you've done you've created three NAT gateways for a region resilient design you've created three route tables one in each availability zone added a default IP version for route pointing at the corresponding NAT gateway and associated each of those route tables with the private subnets in those availability zones so you've implemented a regionally resilient NAT gateway architecture so that's a great job that's a pretty complex demo but it's going to be functionality that will be really useful if you're using AWS in the real world or if you have to answer any exam questions on NAT gateways with that being said at this point you have cleared up the account you've deleted all the resources so go ahead complete this video and when you're ready I'll see you in the next.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Review:

      Summary:

      Bursicon is a key hormone regulating cuticle tanning in insects. While the molecular mechanisms of its function are rather well studied--especially in the model insect Drosophila melanogaster, its effects and functions in different tissues are less well understood. Here, the authors show that bursicon and its receptor play a role in regulating aspects of the seasonal polyphenism of Cacopsylla chinensis. They found that low temperature treatment activated the bursicon signaling pathway during the transition from summer form to winter form and affect cuticle pigment and chitin content, and cuticle thickness. In addition, the authors show that miR-6012 targets the bursicon receptor, CcBurs-R, thereby modulating the function of bursicon signaling pathway in the seasonal polyphenism of C. chinensis. This discovery expands our knowledge of the roles of neuropeptide bursicon action in arthropod biology.

      However, the study falls short of its claim that it reveals the molecular mechanisms of a seasonal polyphenism. While cuticle tanning is an important part of the pear psyllid polyphenism, it is not the equivalent of it. First, there are other traits that distinguish between the two morphs, such as ovarian diapause (Oldfield, 1970), and the role of bursicon signaling in regulating these aspects of polyphenism were not measured. Thus, the phenotype in pear psyllids, whereby knockdown bursicon reduces cuticle tanning seems to simply demonstrate the phenotypes of Drosophila mutants for bursicon receptor (Loveall and Deitcher, 2010, BMC Dev Biol) in another species (Fig. 2I, 4H). Second, the study fails to address the threshold nature of cuticular tanning in this species, although it is the threshold response (specifically, to temperature and photoperiod) that distinguishes this trait as a part of a polyphenism. Whereas miR-6012 was found to regulate bursicon expression, there no evidence is provided that this microRNA either responds to or initiates a threshold response to temperature. In principle, miR-6012 could regulate bursicon whether or not it is part of a polyphenism. Thus, the impact of this work would be significantly increased if it could distinguish between seasonal changes of the cuticle and a bona fide reflection of polyphenism.

      Thanks for your valuable suggestion. We concur with the review’s comment that cuticle tanning does not equate to the C. chinensis polyphenism. To better reflect the core focus of our research, we have revised the title to "Neuropeptide Bursicon and its receptor mediated the transition from summer-form to winter-form of Cacopsylla chinensis".

      In response to the reviewer's inquiry regarding the threshold nature of cuticular tanning in C. chinensis, we have included a detailed analysis of the phenotypic changes (including nymph phenotypes, cuticle pigment absorbance, and cuticle thickness) during the transition from summer-form to winter-form in C. chinensis at distinct time intervals (3, 6, 9, 12, 15 days) under different temperature conditions (10°C and 25°C). As shown in Figure S1, nymphs exhibit a light yellow and transparent coloration at 3, 6, and 9 days, while nymphs at 12 and 15 days display shades of yellow-green or blue-yellow under 25°C conditions. At 10°C conditions, the abdomen end turns black at 3, 6, and 9 days. By the 12 days, numerous light black stripes appear on the chest and abdomen of nymphs at 10°C. At 15 days, nymphs exhibit an overall black-brown appearance, featuring dark brown stripes on the left and right sides of each chest and abdominal section. Furthermore, the end of the abdomen and back display a large black-brown coloration at 10°C (Figure S1A). The UV absorbance of the total pigment extraction at a 300 nm wavelength markedly increases following 10°C exposure for 6, 9, 12, and 15 days compared to the 25°C treatment group (Figure S1B). Cuticle thicknesses also increased following 10°C exposure for 6, 9, 12, and 15 days compared to the 25°C treatment group (Figure S1C). The detailed results (L122-143), materials and methods (L647-652), and discussion (L319-322) have been added in our revised manuscript.

      Regarding the response of miR-6012 to temperature, we have already determined its expression at 3, 6, 10 days under different temperatures in the previous Figure 5E. We now included additional time intervals (9, 12, 15 days) in the updated Figure 5E. Our results indicate a significant decrease in the expression levels of miR-6012 after 10°C treatment for 3, 6, 9, 12, 15 days compared to the 25°C treatment group. Detailed information regarding this has been integrated into the Materials and Methods (Line 608-610) of our revised manuscript.

      Strengths:

      This study convincingly identifies homologs of the genes encoding the bursicon subunits and its receptor, showing an alignment with those of another psyllid as well as more distant species. It also demonstrates that the stage- and tissue-specific levels of bursicon follow the expected patterns, as informed by other insect models, thus validating the identity of these genes in this species. They provide strong evidence that the expression of bursicon and its receptor depend on temperature, thereby showing that this trait is regulated through both parts of the signaling mechanism.

      Several parallel measurements of the phenotype were performed to show the effects of this hormone, its receptor, and an upstream regulator (miR-6012), on cuticle deposition and pigmentation (if not polyphenism per se, as claimed). Specifically, chitin staining and TEM of the cuticle qualitatively show difference between controls and knockdowns, and this is supported by some statistical tests of quantitative measurements (although see comments below). Thus, this study provides strong evidence that bursicon and its receptor play an important role in cuticle deposition and pigmentation in this psyllid.

      The study identified four miRNAs which might affect bursicon due to sequence motifs. By manipulating levels of synthetic miRNA agonists, the study successfully identified one of them (miR-6012) to cause a cuticle phenotype. Moreover, this miRNA was localized (by FISH) to the cuticle, body-wide. To our knowledge, this is the first demonstrated function for this miRNA, and this study provides a good example of using a gene of known function as an entry point to discovering others influencing a trait. Thus, this finding reveals another level of regulation of cuticle formation in insects.

      Weaknesses:

      (1) The introduction to this manuscript does not accurately reflect progress in the field of mechanisms underlying polyphenism (e.g., line 60). There are several models for polyphenism that have been used to uncover molecular mechanisms in at least some detail, and this includes seasonal polyphenisms in Hemiptera. Therefore, the justification for this study cannot be predicated on a lack of knowledge, nor is the present study original or unique in this line of research (e.g., as reviewed by Zhang et al. 2019; DOI: 10.1146/annurev-ento-011118-112448). The authors are apparently aware of this, because they even provide other examples (lines 104-108); thus the introduction seems misleading as framed.

      Thanks for your excellent suggestion. We have added the paper of Zhang et al. 2019 which recommended by reviewer (DOI: 10.1146/annurev-ento-011118-112448) in Line 57 of our revised manuscript. The statement has been revised to “However, the specific molecular mechanism underling temperature-dependent polyphenism still require further clarification” in Line 60-61 of our revised manuscript.

      (2) The data in Figure 2H show "percent of transition." However, the images in 2I show insects with tanned cuticle (control) vs. those without (knockdown). Yet, based on the description of the Methods provided, there appears to be no distinction between "percent of transition" and "percent with tanning defects". This an important distinction to make if the authors are going to interpret cuticle defects as a defect in the polyphenism. Furthermore, there is no mention of intermediate phenotypes. The data in 2H are binned as either present or absent, and these are the phenotypes shown in 2I. Was the phenotype really an all-or-nothing response? Instead of binning, which masks any quantitative differences in the tanning phenotypes, the authors should objectively quantify the degree of tanning and plot that. This would show if and to what degree intermediate tanning phenotypes occurred, which would test how bursicon affects the threshold response. This comment also applies to the data in Figures 4G and 6G. Since cuticle tanning is present in more insect than just those with seasonal polyphenism, showing how this responds as a threshold is needed to make claims about polyphenism.

      We appreciate your insightful comments. As shown in Figure 1 of our published paper (Zhang et al., 2013; doi.org/10.7554/eLife.88744.3) and Figure 2C-2I of the current manuscript, the transition from summer-form to winter-form entails not only external cuticular tanning but also alterations in internal cuticular chitin levels and cuticle thickness. While external cuticular tanning serves as a prominent and easily observable indicator of this transition, it is crucial to acknowledge that internal changes also play a significant role and should be taken into consideration. Therefore, we propose that the term "percent of transition" may be more suitable than "percent with tanning defects" to describe this process accurately.

      In order to provide a more visually comprehensive understanding of the phenotypic changes during the transition from summer-form to winter-form, we have included images at different time points (3, 6, 9, 12, 15 days) under different temperature conditions in Figure S1A of our revised manuscript. Specifically, under the 10°C condition, nymphs exhibit abdomen tanning after 6 and 9 days of treatment, while the thorax remains untanned. By days 12 to 15, both the abdomen and thorax of the nymphs show tanning, resulting in the majority of summer-form nymphs transitioning into winter-form, as depicted in Figure 2I for comparison. This observation indicates the presence of a critical threshold for cuticle tanning of C. chinensis following exposure to 10°C. Nymphs that did not undergo the transition to winter-form succumbed to the cold, highlighting the absence of intermediate phenotypes at 12-15 days under the 10°C condition. The UV absorbance of the total pigment extraction at a 300 nm wavelength markedly increases following 10°C exposure for 6, 9, 12, and 15 days compared to the 25°C treatment group (Figure S1B). Additionally, cuticle thickness shows an increase following 10°C exposure for 6, 9, 12, and 15 days compared to the 25°C treatment group (Figure S1C). These results highlight the relationship between the threshold of cuticular tanning and the transition process. The detailed description and information have been added in Results (L122-143), Materials and Methods (L647-652), and Discussion (L319-322) of our manuscript.

      (3) This study also does not test the threshold response of cuticle phenotypes to levels of bursicon, its receptor, or miR-6012. Hormone thresholds are the most widespread and, in most systems where polyphenism has been studied, the defining characteristic of a polyphenism (e.g., Nijhout, 2003, Evol Dev). Quantitative (not binned) measurements of a polyphenism marker (e.g., chitin) should be demonstrated to result as a threshold titer (or in the case of the receptor, expression level) to distinguish defects in polyphenism from those of its component trait.

      Thanks for your valuable feedback. We have supplemented additional data on the phenotypes (Figure S1A), cuticle pigment absorbance (Figure S1B), cuticle thickness (Figure S1C), expression levels of bursicon (Figure 1E and 1F), its receptors (Figure 3G), and miR-6012 (Figure 5E) corresponding to nymphs treated over different time periods (3, 6, 9, 12, 15 days) under both 10°C and 25°C conditions in our revised manuscript.

      While all these identified markers exhibit a strong correlation with the transition from summer-form to winter-form, it is important to note that they are not suitable as definitive thresholds due to the nature of relative gene expression quantification and chitin content assessment, rather than absolute quantitation. Further, given that tanning hormones are neuropeptides present in trace amounts in insects, unlike steroid hormones, determining their titers poses a considerable challenge.

      (4) Cuticle issue:

      (a) Unlike Fig. 6D and F, Figs. 2D and F do not correspond to each other. Especially the lack and reduction of chitin in ds-a+b! By fluorescence microscopy there is hardly any signal, whereas by TEM there is a decent cuticle. Additionally, the dsGFP control cuticle in 2D is cut obliquely with a thick and a thin chitin layer. This is misleading.

      Thanks for your insightful feedback. We have replaced the previous WGA chitin staining images in the dsCcbursα+β treatment of Figure 2D with new representative images aligning with Figure 2F. Furthermore, the presence of both thin and thick chitin layers observed in the dsEGFP treatment of Figure 2D could potentially be ascribed to the chitin content in the insect midgut or fat body as previously discussed (Zhu et al., 2016). It is notable that during the process of cuticle staining, the chitin located in the midgut and fat body of C. chinensis may exhibit green fluorescence, leading to the appearance of a thin chitin layer. A detailed analysis and elucidation of these observations have been added in the discussion section (Lines 347-352) of our revised manuscript.

      Zhu KY, Merzendorfer H, Zhang W, Zhang J, Muthukrishnan S. Biosynthesis, Turnover, and Functions of Chitin in Insects. Annu Rev Entomol. 2016;61:177-196. doi:10.1146/annurev-ento-010715-023933.

      (b) In Figs. 2F and 4F, the endocuticle appears to be missing, a portion of the procuticle that is produced post-molting. As tanning is also occurring post-molting, there seems to be a general problem with cuticle differentiation at this time point. This may be a timing issue. Please clarify.

      Thank you for your suggestion. The insect cuticle typically comprises three distinct layers (endocuticle, exocuticle, and epicuticle), with the thickness of each layer varying among different insect species. Cuticle differentiation is closely linked to the molting cycle of insects (Mrak et al., 2017). In our study, nymphal cuticles exhibited normal differentiation patterns, characterized by a thin epicuticle and comparable widths of the endocuticle and exocuticle following dsEGFP treatment, as illustrated in Figure 2F and 4F. Conversely, nymphs treated with dsCcBurs-α, dsCcBurs-β, and dsCcburs-R displayed impaired development, manifesting only the exocuticle without a discernible endocuticle layer. These findings suggest that bursicon genes and their receptor play a pivotal role in regulating insect cuticle development (Costa et al., 2016). We have added some discussion about these results in Lines 356-367 of our revised manuscript.

      Mrak, P., Bogataj, U., Štrus, J., & Žnidaršič, N. (2017). Cuticle morphogenesis in crustacean embryonic and postembryonic stages. Arthropod structure & development, 46(1), 77–95. https://doi.org/10.1016/j.asd.2016.11.001

      Costa, C. P., Elias-Neto, M., Falcon, T., Dallacqua, R. P., Martins, J. R., & Bitondi, M. (2016). RNAi-mediated functional analysis of Bursicon genes related to adult cuticle formation and tanning in the Honeybee, Apis mellifera. PloS one, 11(12), e0167421. https://doi.org/10.1371/journal.pone.0167421

      (c) To provide background information, it would be useful analyze cuticle formation in the summer and winter morphs of controls separately by light and electron microscopy. More baseline data on these two morphs is needed.

      Thanks for your valuable feedback. To provide more background information about cuticle formation, we supplied the results of nymph phenotypes, cuticle pigment absorbance, and cuticle thickness at distinct time intervals (3, 6, 9, 12, 15 days) under different temperatures of 10°C and 25°C in Figure S1 of our revised manuscript. Hope these results can help better understand the baseline data on these two morphs.

      (d) For the TEM study, it is not clear whether the same part of the insect's thorax is being sectioned each time, or if that matters. There is not an obvious difference in the number of cuticular layers, but only the relative widths of those layers, so it is difficult to know how comparable those images are. This raises two questions that the authors should clarify. First, is it possible that certain parts of the thoracic cuticle, such as those closer to the intersegmental membrane, are naturally thinner than other parts of the body? Second, is the tanning phenotype based on the thickness or on the number of chitin layers, or both? The data shown later in Figure 4I, J convincingly shows that the biosynthesis pathway for chitin is repressed, but any clarification of what this might mean for deposition of chitin would help to understand the phenotypes reported. Also, more details on how the data in Fig. 2G were collected would be helpful. This also goes for the data in Fig. 4 (bursicon receptor knockdowns).

      Thanks for your great comment. The TEM investigation adhered to a standardized protocol was used as previous description (Zhang et al., 2023), Initially, insect heads were uniformly excised and then fixed in 4% paraformaldehyde. Subsequently, a consistent cutting and staining procedure was executed at a uniform distance above the insect's thorax. The dorsal region of the thorax was specifically chosen for subsequent fluorescence imaging or transmission electron microscopy assessments with the specific objective of quantifying cuticle thickness. Regarding the measurement of cuticle thickness, use the built-in measuring ruler on the software to select the top and bottom of the same horizontal line on the cuticle. Measure the cuticle of each nymph at two close locations. Six nymphs were used for each sample. Randomly select 9 values and plot them. The related description has been added in the Materials and Methods (Line 660-668) of our revised manuscript.

      Zhang, S.D., Li, J.Y., Zhang, D.Y., Zhang, Z.X., Meng, S.L., Li, Z., & Liu, X.X. (2023). MiR-252 targeting temperature receptor CcTRPM to mediate the transition from summer-form to winter-form of Cacopsylla chinensis. eLife, 12. https://doi.org/10.7554/eLife.88744

      (5) Tissue issue:

      The timed experiments shown in all figures were done in whole animals. However, we know from Drosophila that Bursicon activity is complex in different tissues. There is, thus, the possibility, that the effects detected on different days in whole animals are misleading because different tissues--especially the brain and the epidermis, may respond differentially to the challenge and mask each other's responses. The animal is small, so the extraction from single tissue may be difficult. However, this important issue needs to be addressed.

      Thanks for your excellent suggestion. We express our heartfelt appreciation to the reviewer for their valuable input regarding the challenges involved in dissecting various tissue sections from the diminutive early instar nymphs of C. chinensis. In light of the metamorphic transition of C. chinensis across developmental stages, this study concentrated on examining the extensive phenotypic alterations. Consequently, intact samples of C. chinensis were specifically chosen for for qPCR analysis. The related descriptions have been added in the Materials and Methods (Line 513, 517, 553, 555, and 613) and Discussion (Line 327-329) of our revised manuscript.

      (6) No specific information is provided regarding the procedure followed for the rescue experiments with burs-α and burs-β (How were they done? Which concentrations were applied? What were the effects?). These important details should appear in the Materials and Methods and the Results sections.

      Thanks for your excellent suggestion. For the rescue experiments, the dsRNA of CcBurs-R and proteins of burs α-α, burs β-β homodimers, or burs α-β heterodimer (200 ng/μL) were fed together. The concentration of heterodimer protein of CcBurs-α+β was 200 ng/μL. The heterodimer protein of CcBurs-α+β fully rescued the effect of RNAi-mediated knockdown on CcBurs-R expression, while α+α or β+β homodimers did not (Figure 3F). Feeding the α+β heterodimer protein fully rescued the defect in the transition percent and morphological phenotype after CcBurs-R knockdown (Figure 4G-4H). We have added the detailed methods of rescued experiments and specific concentrations in the Materials and Methods (Line 561-563), and Results (Line 263) of our revised manuscript.

      (7) Pigmentation

      (a) The protocol used to assess pigmentation needs to be validated. In particular, the following details are needed: Were all pigments extracted? Were pigments modified during extraction? Were the values measured consistent with values obtained, for instance, by light microscopy (which should be done)?

      Thanks for your excellent comment. Our protocol for pigment extracted as detailed in Bombyx mori, the cuticles were pulverized in liquid nitrogen and then dissolved in 30 milliliters of acidified methanol (Futahashi et al., 2012; Osanai-Futahashi et al., 2012). Thus, all cuticle pigments were dissected and treated with acidified methanol. Pigments were not modified during extraction.. The details description have been integrated into the Materials and Methods (Line 630-633) of our revised manuscript.

      Futahashi, R., Kurita, R., Mano, H., & Fukatsu, T. (2012). Redox alters yellow dragonflies into red. Proceedings of the National Academy of Sciences of the United States of America, 109(31), 12626–12631. https://doi.org/10.1073/pnas.1207114109

      Osanai-Futahashi, M., Tatematsu, K. I., Yamamoto, K., Narukawa, J., Uchino, K., Kayukawa, T., Shinoda, T., Banno, Y., Tamura, T., & Sezutsu, H. (2012). Identification of the Bombyx red egg gene reveals involvement of a novel transporter family gene in late steps of the insect ommochrome biosynthesis pathway. The Journal of biological chemistry, 287(21), 17706–17714. https://doi.org/10.1074/jbc.M111.321331

      (b) In addition, pigmentation occurs post-molting; thus, the results could reflect indirect actions of bursicon signaling on pigmentation. The levels of expression of downstream pigmentation genes (ebony, lactase, etc) should be measured and compared in molting summer vs. winter morphs.

      Thanks for your valuable suggestion. Actually, we already studied the function of some downstream pigmentation genes, including ebony, Lactase, Tyrosine hydroxylase, Dopa decarboxylase, and Acetyltransferase. The variations in the expression patterns of these genes are closely tied to the molting dynamics of nymphs undergoing transitions between summer-form and winter-form. These findings will put in another manuscript currently being prepared for submission, thus detailed outcomes are not suitable for inclusion in the current manuscript.

      (8) L236: "while the heterodimer protein of CcBurs α+β could fully rescue the effect of CcBurs-R knockdown on the transition percent (Figure 4G 4H)". This result seems contradictory. If CcBurs-R is the receptor of bursicon, the heterodimer protein of CcBurs α+β should not be able to rescue the effect of CcBurs-R knockdown insects. How can a neuropeptide protein rescue the effect when its receptor is not there! If these results are valid, then the CcBurs-R would not be the (sole) receptor for CcBurs α+β heterodimer. This is a critical issue for this manuscript and needs to be addressed (also in L337 in Discussion).

      Thanks for your insightful suggestion. Following the administration of dsCcBur-R to C. chinensis, the expression of CcBurs-R exhibited a reduction of approximately 66-82% as depicted in Figure 4A, rather than complete suppression. Activation of endogenous CcBurs-R through feeding of the α+β heterodimer protein results in an increase in CcBurs-R expression, with the effectiveness of the rescue effect contingent upon the dosage of the α+β heterodimer protein. Consequently, the capacity of the α+β heterodimer protein to effectively mitigate the impacts of CcBurs-R knockdown on the conversion rate is clearly demonstrated. We have added additional discussion in Line 396-403 of our revised manuscript.

      (9) Fig. 5D needs improvement (the magnification is poor) and further explanation and discussion. mi6012 and CcBurs-R seem to be expressed in complementary tissues--do we see internal tissues also (see problem under point 2)? Again, the magnification is not high enough to understand and appreciate the relationships discussed.

      Thanks for your valuable suggestion. In order to enhance the resolution of the magnified images, we conducted FISH co-localization of miR-6012 and CcBurs-R in 3rd instar nymphs and obtained detailed zoomed-in images. As shown in the magnified view of Figure 5D, miR-6012 and CcBurs-R appear to exhibit complementary expression patterns in tissues. During the FISH assays, epidermis transparency of C. chinensis was achieved via decolorization treatment. Noteworthy observations from Figure 3G and Figure 5E reveal an inverse correlation in the expression profiles of CcBurs-R and miR-6012. Consequently, the FISH results distinctly highlight a significant disparity in the expression levels of CcBurs-R and miR-6012 within the same tissue. We have added related explanation and discussion in Line 291-293 of our revised manuscript.

      (10) The schematic in Fig. 7 is a useful summary, but there is a part of the logic that is unsupported by the data, specifically in terms of environmental influence on cuticle formation (i.e., plasticity). What is the evidence that lower temperatures influence expression of miR-6012? The study measures its expression over life stages, whether with an agonist or not, over a single temperature. Measuring levels of expression under summer form-inducing temperature is necessary to test the dependence of miR-6012 expression on temperature. Otherwise, this result cannot be interpreted as polyphenism control, but rather the control of a specific trait.

      Thanks for your great suggestion. We actually conducted the assessment of miR-6012 expression at specific time intervals (3, 6, 9, 12, 15 days) under different temperatures of 10°C and 25°C. As depicted in Figure 5E, the expression levels of miR-6012 were notably reduced at 10°C compared to 25°C. Additionally, the evaluation of agomir-6012 expression level of C. chinensis under 25°C conditions at various time points (3, 6, 9, 12, 15 days) revealed no significant changes. Hence, we suggest that the impact of miR-6012 on the seasonal morphological transition is influenced upon temperature.

      Recommendations for the authors:

      The authors report a novel role of Bursicon and its receptor in regulating the seasonal polyphenism of Cacopsylla chinensis. They found that low temperature treatment (10°C) activated the Bursicon signaling pathway during the transition from summer-form to winter-form, which influences cuticle pigment content, cuticle chitin content, and cuticle thickness. Moreover, the authors identified miR-6012 and show that it targets CcBurs-R, thereby modulating the function of Bursicon signaling pathway in the seasonal polyphenism of C. chinensis. This discovery expands our knowledge of multiple roles of neuropeptide bursicon action in arthropod biology. However, the m

      anuscript does have several major weaknesses, described under "Public review", which the authors need to address.

      Major issues:

      (1) L152-154 Fig S2E and S2F: Bursicon has been shown to be expressed in the CNS in a specific set of neurons. For example, In the larval CNS of Manduca sexta, bursicon expression is restricted to the subesophageal ganglion (SG), thoracic ganglia, and first abdominal ganglion. Pharate pupae and pharate adults show expression of this heterodimer in all ganglia. In Drosophila larvae, expression of a bursicon heterodimer is confined to abdominal ganglia. The additional neurons in the ventral nerve cord express only burs. In pharate adults, bursicon is produced by neurons in the SG and abdominal ganglia. I am wondering where bursicon subunits are expressed in the C. chinensis CNS? Since the authors have the antibodies, it would be useful to include immunocytochemical staining of bursicon alpha and beta in the CNS. The qPCR results from head or other tissues (Fig S2E and S2F) is not the most informative way to document localization of gene expression. Regarding the qPCR results, they show that the cuticle and the fat body express CcBurs-α and CcBurs-β. Can the authors confirm this unexpected results independently?

      Thanks for your insightful comment. In this study, we did not directly used antibodies targeting bursicon subunits, instead, the bursicon subunits along with a histidine tag were integrated into the expression vector pcDNA3.1 using homologous recombination. The experimental procedures were executed as follows: initially, the histidine tag was fused to the pcDNA3.1-mCherry vector through homologous recombination to generate the recombinant plasmid pcDNA3.1-his-mCherry. Subsequently, the amino acid sequences of the two bursicon subunits were introduced into the pcDNA3.1-his-mCherry vector via homologous recombination to produce the recombinant plasmids pcDNA3.1-CcBurs-α-his-mCherry and pcDNA3.1-CcBurs-β-his-mCherry. Finally, the P2A sequence was incorporated into the vector using reverse PCR to yield the recombinant plasmids pcDNA3.1-CcBurs-α-his-P2A-mCherry and pcDNA3.1-CcBurs-β-his-P2A-mCherry. Consequently, the bursicon subunits, along with the histidine tag, were capable of generating fusion proteins with the histidine tag. Western blot analysis was conducted using antibodies targeting the histidine tag, enabling the detection of histidine expression, which corresponds to the expression of the bursicon subunits. However, they are not suitable to conduct the in vivo immunocytochemical staining of bursicon alpha and beta in the CNS.

      Due to the diminutive size of the C. chinensis nymphs, dissection of the central nervous system (CNS) was unfeasible, precluding specific assessment of bursicon expression in the CNS. Prior literature has documented the expression of bursicon subunits in the epidermis and fat body of C. chinensis. Studies suggest that bursicon subunits not only play a role in the melanization and sclerotization processes of insect epidermis but also have significant roles in insect immunity (An et al., 2012). The presence of bursicon subunits in the epidermis, gut, and fat body of C. chinensis may indicate their crucial roles in the immune functions of these tissues. Further investigation is required to elucidate the specific immune functions they perform, hinting at the potential expression of these bursicon subunits in these two tissues.

      An, S., Dong, S., Wang, Q., Li, S., Gilbert, L. I., Stanley, D., & Song, Q. (2012). Insect neuropeptide bursicon homodimers induce innate immune and stress genes during molting by activating the NF-κB transcription factor Relish. PloS one, 7(3), e34510. https://doi.org/10.1371/journal.pone.0034510

      (2) L222: "CcBurs-R is the Bursicon receptor of C. chinensis". Is this statement supported by affinity binding assay results?

      Thanks for your excellent suggestion. We employed a fluorescence-based assay to quantify calcium ion concentrations and investigate the binding affinities of bursicon heterodimers and homodimers to the bursicon receptor across varying concentrations. Our findings suggest that activation of the receptor by the burs α-β heterodimer leads to significant alterations in intracellular calcium ion levels, whereas stimulation with burs α-α and burs β-β homodimers, in conjunction with Adipokinetic hormone (AKH), maintains consistent intracellular calcium ion levels. Consequently, this research definitively identifies CcBurs-R as the bursicon receptor. For further details, please refer to the Materials and Methods (Lines 493-504), Results (Lines 231-239), and Discussion (Lines 377-384) of our revised manuscript.

      (3) L245 Figure 4I-4J: Since knockdown of bursicon and its receptor cause a decrease pigment accumulation in the cuticle, it would be useful to examine 1-2 rate limiting enzyme-encoding genes in the bursicon regulated cuticle darkening process if possible (as was done for genes involved in cuticle thickening).

      Thanks for your excellent comment. Following the further study, a thorough analysis was conducted to evaluate the impact of bursicon and its receptor on the expression levels of Lactase, Tyrosine hydroxylase, Dopa decarboxylase, Acetyltransferase, and the effects of RNA interference targeting these genes on the seasonal morphological transition. The findings underscored their role in the bursicon-mediated cuticle darkening process. However, as this section is slated for inclusion in an upcoming manuscript intended for submission, it is deemed unsuitable for incorporation into the current manuscript.

      Minor issues:

      (1) L75 "stronger resistance (Ge et al., 2019; Tougeron et al., 2021)". Stronger resistance to what? Stronger resistance to environmental stress or weather condition? Please clarify.

      Thanks for your excellent suggestion. We have changed the statement to “stronger resistance to weather condition” in Line 75 of our revised manuscript.

      (2) L132 Figure 1A and 1B: Bursicon sequence was first identified and functionally characterized in Drosophila melanogaster: is there any reason why Drosophila bursicon sequences were not included in the comparison?

      Thanks for your excellent comment. We have added the sequence of Burs-α and Burs-β of D. melanogaster in the sequence alignment results of Figure 1A and 1B of our revised manuscript.

      (3) Although the authors clearly identify and validate the function for the bursicon genes and its receptor's, there is no mention of whether duplicates of this gene are also present in the pear psyllid. This has been known to happen in otherwise conserved hormone pathways (e.g., insulin receptor in some insects), so a formal check of this should be done.

      Thanks for your excellent comment. As shown in Figure S2A-S2B and 3B, there are two bursicon subunit genes and only one bursicon receptor gene in our selected insect species, for examples Drosophila melanogaster, Diaphorina citri, Bemisia tabaci, Nilaparvata lugens, and Sogatella furcifera. In our transcriptome database of C. chinensis, we also only identified two bursicon subunit genes and only one bursicon receptor gene.

      (4) Line 41: Here, as in the title, "fascinating" is a subjective judgement that does not improve a study's presentation.

      Thanks for your great comment. We have changed "fascinating" to "transformation" in Line 41 and also revised the title of our revised manuscript.

      (5) Line 44: What makes some fields "cutting-edge" and others not?

      Thanks for your excellent suggestion. The expression of "in cutting-edge fields" has been deleted in Line 44 of our revised manuscript.

      (6) Line 97: This is a peculiar choice of reference for the concept of slower development in cold temperatures. The concept of degree-days and growth rates is old and widespread in entomology.

      Thanks for your insightful comment. The reference of Nyamaukondiwa et al., 2011 in Line 95 has been deleted in our revised manuscript.

      (7) Lines 149-150: What justifies the assumption that higher levels of expression mean a more important role? This gene might be just as necessary for development of the summer form, even if expressed at lower levels.

      Thanks for your excellent suggestion. This sentence has been revised to “Increased gene expression levels may potentially contribute to the transition from summer-form to winter-form in C. chinensis.” in Line 168-169 of our revised manuscript.

      (8) The blue arrow in Fig. 7 is confusing.

      Thanks for your excellent suggestion. In Figure 7, the blue arrow represents the down-regulated expression of miR-6012. We have added a description about the blue arrow in Figure 7 of our revised manuscript.

    1. Author response:

      The following is the authors’ response to the current reviews.

      Many thanks to the editors for the reviewing of the revised manuscript.

      We are very grateful to the Reviewers for their time and for the appreciation of the revision.

      We thank the Reviewer 3 for acknowledging the use of sulforhodamine B (SRB) fluorescence as a real-time readout of astrocyte volume dynamics. Experimental data in brain slices were provided to validate this approach.<br /> The incomplete matching of our observation with early reported data in cultured astrocytes (e.g., Solenov et al., AJP-Cell, 2004), might reflect certain of their properties differing from the slice/in vivo counterparts as discussed in the manuscript.<br /> The study (T.R. Murphy et al., Front Cell Neurosci., 2017) showed that AQP4 knockout increased astrocyte swelling extent in response to hypoosmotic solution in brain slices (Fig 9), and discussed '... AQP4 can provide an efficient efflux pathway for water to leave astrocytes.’ Correspondingly, our data suggest that AQP4 mediate astrocyte water efflux in basal conditions.<br /> We have discussed the study (Igarashi et al., NeuroReport 2013); our current data would help to understand the cellular mechanisms underlying the finding of Igarashi et al.


      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      Pham and colleagues provide an illuminating investigation of aquaporin-4 water flux in the brain utilizing ex vivo and in vivo techniques. The authors first show in acute brain slices, and in vivo with fiber photometry, SRB-loaded astrocytes swell after inhibition of AQP4 with TGN-020, indicative of tonic water efflux from astrocytes in physiological conditions. Excitingly, they find that TGN-020 increases the ADC in DW-MRI in a region-specific manner, potentially due to AQP4 density. The resolution of the DW-MRI cannot distinguish between intracellular or extracellular compartments, but the data point to an overall accumulation of water in the brain with AQP4 inhibition. These results provide further clarity on water movement through AQP4 in health and disease.

      Overall, the data support the main conclusions of the article, with some room for more detailed treatment of the data to extend the findings.

      Strengths:

      The authors have a thorough investigation of AQP4 inhibition in acute brain slices. The demonstration of tonic water efflux through AQP4 at baseline is novel and important in and of itself. Their further testing of TGN-020 in hyper- and hypo-osmotic solutions shows the expected reduction of swelling/shrinking with AQP4 blockade.

      Their experiment with cortical spreading depression further highlights the importance of water efflux from astrocytes via AQP4 and transient water fluxes as a result of osmotic gradients. Inhibition of AQP4 increases the speed of tissue swelling, pointing to a role in the efflux of water from the brain.

      The use of DW-MRI provides a non-invasive measure of water flux after TGN-020 treatment.

      We thank the reviewer for the insightful comments.

      Weaknesses:

      The authors specifically use GCaMP6 and light sheet microscopy to image their brain sections in order to identify astrocytic microdomains. However, their presentation of the data neglects a more detailed treatment of the calcium signaling. It would be quite interesting to see whether these calcium events are differentially affected by AQP4 inhibition based on their cellular localization (ie. processes vs. soma vs. vascular end feet which all have different AQP4 expressions).

      Following the suggestion, we provide new data on the effect of AQP4 inhibition on spontaneous calcium signals in perivascular astrocyte end-feet. As shown now in Fig.S2, acute application of TGN020 induced Ca2+ oscillations in astrocyte end-feet regions where the GCaMP6 labeling lines the profile of the blood vessel. It is noted that on average, the strength of basal Ca2+ signals in the end-feet is higher than that observed across global astrocyte territories (4.65 ± 0.55 vs. 1.45 ± 0.79, p < 0.01), as does the effect of TGN (8.4 ± 0.62 vs. 6.35 ± 0.97, p < 0.05; Fig S2 vs. Fig 2B). This likely reflects the enrichment of AQP4 in astrocyte end-feet. We describe the data in Fig.S2, and on page 8, line 20 – 23.  

      We now use the transgenic line GLAST-GCaMP6 for cytosolic GCaMP6 expression in astrocytes. Spontaneous calcium signals, reflected by transient fluorescence rises, occur in discrete micro-domains whereas the basal GCaMP6 fluorescence in the soma is weak. In the present condition, it is difficult to unambiguously discriminate astrocyte soma from the highly intermingled processes. 

      The authors show the inhibition of AQP4 with TGN-020 shortens the onset time of the swelling associated with cortical spreading depression in brain slices. However, they do not show quantification for many of the other features of CSD swelling, (ie. the duration of swelling, speed of swelling, recovery from swelling).

      Regarding the features of the CSD swelling, we have performed new analysis to quantify the duration of swelling, speed of swelling and the recovery time from swelling in control condition and in the presence of TGN-020. The new analysis is now summarized in Fig. S5. Blocking AQP4 with TGN-020 increases the swelling speed, prolongs the duration of swelling and slows down the recovery from swelling, confirming our observation that acute inhibition of AQP4 water efflux facilitates astrocyte swelling while restrains shrinking. We describe the result on page 11, line 19-21. 

      Significance:

      AQP4 is a bidirectional water channel that is constitutively open, thus water flux through it is always regulated by local osmotic gradients. Still, characterizing this water flux has been challenging, as the AQP4 channel is incredibly water-selective. The authors here present important data showing that the application of TGN-020 alone causes astrocytic swelling, indicating that there is constant efflux of water from astrocytes via AQP4 in basal conditions. This has been suggested before, as the authors rightfully highlight in their discussion, but the evidence had previously come from electron microscopy data from genetic knockout mice.

      AQP4 expression has been linked with the glymphatic circulation of cerebrospinal fluid through perivascular spaces since its rediscovery in 2012 [1]. Further studies of aging[2], genetic models[3], and physiological circadian variation[4] have revealed it is not simply AQP4 expression but AQP4 polarization to astrocytic vascular endfeet that is imperative for facilitating glymphatic flow. Still, a lingering question in the field is how AQP4 facilitates fluid circulation. This study represents an important step in our understanding of AQP4's function, as the basal efflux of water via AQP4 might promote clearance of interstitial fluid to allow an influx of cerebrospinal fluid into the brain. Beyond glymphatic fluid circulation, clearly, AQP4-dependent volume changes will differentially alter astrocytic calcium signaling and, in turn, neuronal activity.

      (1) Iliff, J.J., et al., A Paravascular Pathway Facilitates CSF Flow Through the Brain Parenchyma and the Clearance of Interstitial Solutes, Including Amyloid β. Sci Transl Med, 2012. 4(147): p. 147ra111.

      (2) Kress, B.T., et al., Impairment of paravascular clearance pathways in the aging brain. Ann Neurol, 2014. 76(6): p. 845-61.

      (3) Mestre, H., et al., Aquaporin-4-dependent Glymphatic Solute Transport in the Rodent Brain. eLife, 2018. 7.

      (4) Hablitz, L., et al., Circadian control of brain glymphatic and lymphatic fluid flow. Nature Communications, 2020. 11(1).

      We thank the reviewer in acknowledging the significance of our study and the functional implication in brain glymphatic system. We have now highlighted the mentioned studies as well as the potential implication glymphatic fluid circulation (page 4, line 9-10; page 5, line 1-3; and page 19, line 3-10). 

      Reviewer #2 (Public Review):

      Summary:

      The paper investigates the role of astrocyte-specific aquaporin-4 (AQP4) water channel in mediating water transport within the mouse brain and the impact of the channel on astrocyte and neuron signaling. Throughout various experiments including epifluorescence and light sheet microscopy in mouse brain slices, and fiber photometry or diffusion-weighted MRI in vivo, the researchers observe that acute inhibition of AQP4 leads to intracellular water accumulation and swelling in astrocytes. This swelling alters astrocyte calcium signaling and affects neighboring neuron populations. Furthermore, the study demonstrates that AQP4 regulates astrocyte volume, influencing mainly the dynamics of water efflux in response to osmotic challenges or associated with cortical spreading depolarization. The findings suggest that AQP4-mediated water efflux plays a crucial role in maintaining brain homeostasis, and indicates the main role of AQP4 in this mechanism. However authors highlight that the report sheds light on the mechanisms by which astrocyte aquaporin contributes to the water environment in the brain parenchyma, the mechanism underlying these effects remains unclear and not investigated. The manuscript requires revision.

      Strengths:

      The paper elucidates the role of the astrocytic aquaporin-4 (AQP4) channel in brain water transport, its impact on water homeostasis, and signaling in the brain parenchyma. In its idea, the paper follows a set of complimentary experiments combining various ex vivo and in vivo techniques from microscopy to magnetic resonance imaging. The research is valuable, confirms previous findings, and provides novel insights into the effect of acute blockage of the AQP4 channel using TGN-020.

      We thank the reviewer for the constructive comments.

      Weaknesses:

      Despite the employed interdisciplinary approach, the quality of the manuscript provides doubts regarding the significance of the findings and hinders the novelty claimed by the authors. The paper lacks a comprehensive exploration or mention of the underlying molecular mechanisms driving the observed effects of astrocytic aquaporin-4 (AQP4) channel inhibition on brain water transport and brain signaling dynamics. The scientific background is not very well prepared in the introduction and discussion sections. The important or latest reports from the field are missing or incompletely cited and missconcluded. There are several citations to original works missing, which would clarify certain conclusions. This especially refers to the basis of the glymphatic system concept and recently published reports of similar content. The usage of TGN-020, instead of i.e. available AER-270(271) AQP4 blocker, is not explained. While employing various experimental techniques adds depth to the findings, some reasoning behind the employed techniques - especially regarding MRI - is not clear or seemingly inaccurate. Most of the time the number of subjects examined is lacking or mentioned only roughly within the figure captions, and there are lacking or wrongly applied statistical tests, that limit assessment and reproducibility of the results. In some cases, it seems that two different statistical tests were used for the same or linked type of data, so the results are contradictory even though appear as not likely - based on the figures. Addressing these limitations could strengthen the paper's impact and utility within the field of neuroscience, however, it also seems that supplementary experiments are required to improve the report.

      The current data hint at a tonic water efflux from astrocyte AQP4 in physiological condition, which helps to understand brain water homeostasis and the functional implication for the glymphatic system. The underlying molecular and cellular mechanisms appear multifaceted and functionally interconnected, as discussed (page 14 line 8 –page 15, line 3). We agree that a comprehensive exploration will further advance our understanding.

      The introduction and discussion are now strengthened by incorporating the important advances in glymphatic system while highlighting the relevant studies. 

      The use of TGN-020 was based on its validation by wide range of ex vivo and in vivo studies including the use of heterologous expression system and the AQP4 KO mice. The validation of AER-270(271, the water soluble prodrug) using AQP4 KO mice is reported recently (Giannetto et al., 2024). AER-271 was noted to impact brain water ADC (apparent diffusion coefficient evaluated by diffusion-weighted MRI) in AQP4 KO mice ~75 min after the drug application (Giannetto et al., 2024). This likely reflects that AER270(271) is also an inhibitor for κΒ nuclear factor (NF-κΒ) whose inhibition could reduce CNS water content independent of AQP4 targeting (Salman et al., 2022). In addition, the inhibition efficiency of AER-270(271) seems lower than TGN-020 (Farr et al., 2019; Giannetto et al., 2024; Huber et al., 2009; Salman et al., 2022). We have now supplemented this information in the manuscript (page 7, line 1-6 and page15, line 7-17).

      The description on the DW-MRI is now updated (page 4, line 10-14). 

      We also performed new experiments and data analysis as described in a point-to-point manner below in the section ‘Recommendations For The Authors’.

      Reviewer #3 (Public Review):

      Summary:

      In this manuscript, the authors propose that astrocytic water channel AQP4 represents the dominant pathway for tonic water efflux without which astrocytes undergo cell swelling. The authors measure changes in astrocytic sulforhodamine fluorescence as the proxy for cell volume dynamics. Using this approach, they perform a technically elegant series of ex vivo and in vivo experiments exploring changes in astrocytic volume in response to AQP4 inhibitor TGN-020 and/or neuronal stimulation. The key finding is that TGN-020 produces an apparent swelling of astrocytes and modifies astrocytic cell volume regulation after spreading depolarizations. Additionally, systemic application of TGN-020 produced changes in diffusion-weighted MRI signal, which the authors interpret as cellular swelling. This study is perceived as potentially significant. However, several technical caveats should be strongly considered and perhaps addressed through additional experiments.

      Strengths:

      (1) This is a technically elegant study, in which the authors employed a number of complementary ex vivo and in vivo techniques to explore functional outcomes of aquaporin inhibition. The presented data are potentially highly significant (but see below for caveats and questions related to data interpretation).

      (2) The authors go beyond measuring cell volume homeostasis and probe for the functional significance of AQP4 inhibition by monitoring Ca2+ signaling in neurons and astrocytes (GCaMP6 assay).

      (3) Spreading depolarizations represent a physiologically relevant model of cellular swelling. The authors use ChR2 optogenetics to trigger spreading depolarizations. This is a highly appropriate and much-appreciated approach.

      We thank the reviewer for the effort in evaluating our work.

      Weaknesses:

      (1) The main weakness of this study is that all major conclusions are based on the use of one pharmacological compound. In the opinion of this reviewer, the effects of TGN-020 are not consistent with the current knowledge on water permeability in astrocytes and the relative contribution of AQP4 to this process.

      Specifically: Genetic deletion of AQP4 in astrocytes reduces plasmalemmal water permeability by ~two-three-fold (when measured a 37oC, Solenov et al., AJP-Cell, 2004). This is a significant difference, but it is thought to have limited/no impact on water distribution. Astrocytic volume and the degree of anisosmotic swelling/shrinkage are unchanged because the water permeability of the AQP4null astrocytes remains high. This has been discussed at length in many publications (e.g., MacAulay et al., Neuroscience, 2004; MacAulay, Nat Rev Neurosci, 2021) and is acknowledged by Solenov and Verkman (2004).

      Keeping this limitation in mind, it is important to validate astrocytic cell volume changes using an independent method of cell volume reconstruction (diameter of sulforhodamine-labeled cell bodies? 3D reconstruction of EGFP-tagged cells? Else?)

      Solenov and coll. used the calcein quenching assay and KO mice demonstrating AQP4 as a functional water channel in cultured astrocytes (Solenov et al., 2004). AQP4 deletion reduced both astrocyte water permeability and the absolute amplitude of swelling over comparable time, and also slowed down cell shrinking, which overall parallels our results from acute AQP4 blocking. Yet in Solenovr’s study, the time to swelling plateau was prolonged in AQP4 KO astrocytes, differing from our data from the pharmacological acute blocking. This discrepancy may be due to compensatory mechanisms in chronic AQP4 KO, or reflect the different volume responses in cultured astrocytes from brain slices or in vivo results as suggested previously (Risher et al., 2009). 

      Soma diameter might be an indicator of cell volume change, yet it is challenging with our current fluorescence imaging method that is diffraction-limited and insufficient to clearly resolve the border of the soma in situ. In addition, the lateral diameter of cell bodies may not faithfully reflect the volume changes that can occur in all three dimensions. Rapid 3D imaging of astrocyte volume dynamics with sufficient high Z-axis resolution appears difficult with our present tools. 

      We have now accordingly updated the discussion with relevant literatures being cited (page 17 line 14 – page 18, line 3).

      (2) TGN-020 produces many effects on the brain, with some but not all of the observed phenomena sensitive to the genetic deletion of AQP4. In the context of this work, it is important to note that TGN020 does not completely inhibit AQP4 (70% maximal inhibition in the original oocyte study by Huber et al., Bioorg Med Chem, 2009). Thus, besides not knowing TGN-020 levels inside the brain, even

      "maximal" AQP4 inhibition would not be expected to dramatically affect water permeability in astrocytes.

      This caveat may be addressed through experiments using local delivery of structurally unrelated AQP4 blockers, or, preferably, AQP4 KO mice.

      It is an important point that TGN-020 partially blocks AQP4, implying the actual functional impact of AQP4 per se might be stronger than what we observed. TGN provides a means to acutely probe AQP4 function in situ, still we agree, its limitation needs be acknowledged. We mention this now on page 15, line 7-9 and 14-17.

      We agree that local delivery of an alternative blocker will provide additional information. Meanwhile, local delivery requires the stereotaxic implantation of cannula, which would cause inflammations to surrounding astrocytes (and neurons). The recently introduced AQP4 blocker AER-270(271) has received attention that it influences brain water dynamics (ADC in DW-MRI) in AQP4 KO mice (Giannetto et al., 2024), recalling that AER-270(271) is also an inhibitor for κΒ nuclear factor (NF-κΒ). This pathway can potentially perturb CNS water content and influence brain fluid circulation, in an AQP4independent manner (Salman et al., 2022). The inhibition efficiency on mouse AQP4 of AER-270 (~20%, Farr et al., 2019; Salman et al., 2022) appears lower than TGN-020 (~70%, Huber et al., 2009).

      We chose to use the pharmacological compound to achieve acute blocking of AQP4 thereby avoiding the chronic genetics-caused alterations in brain structural, functional and water homeostasis. Multiple lines of evidence including the recent study (Gomolka et al., 2023), have shown that AQP4 KO mice alters brain water content, extracellular space and cellular structures, which raises concerns to use the transgenic mouse to pinpoint the physiological functions of the AQP4 water channel. 

      We have now mentioned the concerns on AQP4 pharmacology by supplementing additional literatures in the field (page 15, line 8-18). 

      (3) This reviewer thinks that the ADC signal changes in Figure 5 may be unrelated to cellular swelling. Instead, they may be a result of the previously reported TGN-020-induced hyphemia (e.g., H. Igarashi et al., NeuroReport, 2013) and/or changes in water fluxes across pia matter which is highly enriched in AQP4. To amplify this concern, AQP4 KO brains have increased water mobility due to enlarged interstitial spaces, rather than swollen astrocytes (RS Gomolka, eLife, 2023). Overall, the caveats of interpreting DW-MRI signal deserve strong consideration.

      The previous observation show that TGN-020 increases regional cerebral blood flow in wild-type mice but not in AQP4 KO mice (Igarashi et al., 2013). Our current data provide a possible mechanism explanation that TGN-020 blocking of astrocyte AQP4 causes calcium rises that may lead to vasodilation as suggested previously (Cauli and Hamel, 2018). We now add updates to the discussion on page 15, line 3-7.

      We are in line with the reviewer regarding the structural deviations observed with the AQP4 KO mice

      (Gomolka et al., 2023), now mentioned on page 19, line 3-5. Following the Reviewer’s suggestion, we have also updated the interpretation of the DW-MRI signal and point that in addition to being related to the astrocyte swelling, the ADC signal changes may also be caused by indirect mechanisms, such as the transient upregulation of other water-permeable pathways in compensating AQP4 blocking. We now describe this alternative interpretation and the caveats of the DW-MRI signals (page 20, line 1-8). 

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Private recommendations

      My more broad experimental suggestions are in the "weaknesses" section. Some minor points that would improve the manuscript are included below:

      (1) A more detailed explanation for why SRB fluorescence reflects the astrocyte volume changes, whereas typical intracellular GFP does not.

      As an engineered fluorescence protein, the GFP has been used to tag specific type of cells. Meanwhile, as a relatively big protein (MW, 26.9 kDa), the diffusion rate of EGFP is expected to be much less than SRB, a small chemical dye (MW, 558.7 Da). Also, the IP injection of SRB enables geneticsless labeling of brain astrocytes, so to avoid the influence of protein overexpression on astrocyte volume and water transport responses. We have now stated this point in the manuscript (page 13, line 21 – page 14, line 4).

      (2) Figure 1 panel B should have clear labels on the figure and a description in the legend to delineate which part of the panel refers to hyper- or hypo-osmotic treatment.

      We have now updated the figure and the legend.  

      (3) For Figure 2, what is the rationale for analyzing the calcium signaling data between the cell types differently?

      We analyzed calcium micro-domains for astrocytes as their spontaneous signals occur mainly in discrete micro-domains (Shigetomi et al., 2013). While for neurons, we performed global analysis by calculating the mean fluorescence of imaging field of view, because calcium signal changes were only observed at global level rather than in micro-domains. This information is now included (page 24, line1820).

      (4) For Figure 3, the authors mention that TGN-020 likely caused swelling prior to the hypotonic solution administration. Do they have any measurements from these experiments prior to the TGN-020 application to use as a "true baseline" volume?

      The current method detects the relative changes in astrocyte volume (i.e., transmembrane water transport), which nevertheless is blind to the absolute volume value. We have no readout on baseline volumes.  

      (5) For Figures 3 and 4, did the authors see any evidence for regulatory volume decrease? And is this impaired by TGN-020? It is a well-characterized phenomenon that astrocytes will open mechanosensitive channels to extrude ions during hypo-osmotic induced swelling. This process is dependent on AQP4 and calcium signaling [5]

      Mola and coll. provided important results demonstrating the role of AQP4 in astrocyte volume regulation (Mola et al., 2016). In the present study in acute brain slices, when we applied hypotonic solution to induce astrocyte swelling, our protocol did not reveal rapid regulatory volume decrease (e.g., Fig. 3D). When we followed the volume changes of SRB-labeled astrocytes during optogenetically induced CSD, we observed the phase of volume decrease following the transient swelling (Fig. 4F), where the peak amplitude and the degree of recovery were both reduced by inhibiting AQP4 with TGN020. These data imply that regulatory astrocyte volume decrease may occur in specific conditions, which intriguingly has been suggested to be absent in brain slices and in vivo (e.g., Risher et al., 2009). We have not specifically investigated this phenomenon, and now briefly discuss this point on page18 line 6-14.

      (6) Figure 5 box plots do not show all data points, could the authors modify to make these plots show all the animals, or edit the legend to clarify what is plotted?

      We have now updated the plot and the legend. This plot is from all animals (n = 7 per condition).

      (7) pg. 9 line 6, there is a sentence that seems incomplete or otherwise unfinished. "We first followed the evoked water efflux and shrinking induced by hypertonic solution while."

      Fixed (now, page 9 line 17-18). 

      (8)  During the discussion on pg 13 line 11, it may be more clear to describe this as the cotransport of water into the cells with ions/metabolites as reviewed by Macaulay 2021 [6].

      We agree; the text is modified following this suggestion (now page14, line 12-13).  

      (1) Iliff, J.J., et al., A Paravascular Pathway Facilitates CSF Flow Through the Brain Parenchyma and the Clearance of Interstitial Solutes, Including Amyloid β. Sci Transl Med, 2012. 4(147): p. 147ra111.

      (2) Kress, B.T., et al., Impairment of paravascular clearance pathways in the aging brain. Ann Neurol, 2014. 76(6): p. 845-61.

      (3) Mestre, H., et al., Aquaporin-4-dependent Glymphatic Solute Transport in the Rodent Brain. eLife, 2018. 7.

      (4) Hablitz, L., et al., Circadian control of brain glymphatic and lymphatic fluid flow. Nature Communications, 2020. 11(1).

      (5) Mola, M., et al., The speed of swelling kinetics modulates cell volume regulation and calcium signaling in astrocytes: A different point of view on the role of aquaporins. Glia, 2016. 64(1).

      (6) MacAulay, N., Molecular mechanisms of brain water transport. Nat Rev Neurosci, 2021. 22(6): p. 326-344.

      We thank the reviewer. These important literatures are now supplemented to the manuscript together with the corresponding revisions.

      Reviewer #2 (Recommendations For The Authors):

      In its concept, the paper is interesting and provides additional value - however, it requires revision.

      Below, I provide the following remarks for the following sections/ pages/lines:

      ABSTRACT/page 2 (remarks here refer to the rest of the manuscript, where these sentences are repeated):

      - It seems that the 'homeostasis' provides not only physical protection, but also determines the diffusion of chemical molecules...' Please correct the sentence as it is grammatically incorrect.

      It is now corrected (page 2, line 1).

      - The term 'tonic water' is not clear. I understand, after reading the paper, that it is about tonicity of the solutes injected into the mouse.

      We use the term ‘tonic’ to indicate that in basal conditions, a constant water efflux occurs through the APQ4 channel.

      - 'tonic aquaporin water efflux maintains volume equilibrium' - I believe it is about maintaining volume and osmotic equilibrium?

      This description is now refined (now page 2, line 10).

      - It is not clear whether the tonic water outflow refers to the cellular level or outflow from the brain parenchyma (i.e., glymphatic efflux)

      It refers to the cellular level. 

      INTRODUCTION/page 3:

      - 'clearance of waste molecules from the brain as described in the glymphatic system' - The original papers describing the phenomena are not cited: Iliff et al. 2012, 2013, Mestre et al. 2018, as well as reviews by Nedergaard et al.

      Indeed. We have now cited these key literatures (now page 4, line 10).

      - 'brain water diffusion is the basis for diffusion-weighted magnetic resonance imaging (DW-MRI)' - The statement is wrong. it is the mobility of the water protons that DWI is based on, but not the diffusion of molecules in the brain. This should be clarified and based on the DW-MRI principle and the original works by Le Bihan from 1986, 1988, or 2015.

      This sentence is now updated (page 4, line10-14).

      - Similarly, I suggest correcting or removing the citations and the sentence part regarding the clinical use of DWI, as it has no value here. Instead, it would be worth mentioning what actually ADC reflects as a computational score, and what were the results from previous studies assessing glymphatic systems using DWI. This is especially important when considering the mislocalization of the AQP4 channel.

      We now states recent studies using DW-MRI to evaluate glymphatic systems (page 4, line16-17).  

      - 'In the brain, AQP4 is predominantly expressed in astrocytes'-please review the citations. I suggest reading the work by Nielsen 1997, Nagelhus 2013, Wolburg 2011, and Li and Wang from 2017. To my best knowledge, in the brain AQP4 is exclusively expressed in astrocytes.

      Thanks for the reviewer. It is described that while enriched in astrocytes, AQP4 is also expressed in ependymal cells lining the ventricles (e.g., (Mayo et al., 2023; Verkman et al., 2006)). ‘predominantly’ is now removed (page 4, line 21).

      - The conclusion: ' Our finding suggests that aquaporin acts as a water export route in astrocytes in physiological conditions, so as to counterbalance the constitutive intracellular water accumulation caused by constant transmitter and ion uptake, as well as the cytoplasmic metabolism processes. This mechanism hence plays a necessary role in maintaining water equilibrium in astrocytes, thereby brain water homeostasis' seems to be slightly beyond the actual findings in the paper. I suggest clarifying according to the described phenomena.

      We have now refined the conclusion sticking to the experimental observations (page 5, line16-18).

      - The introduction lacks important information on existing AQP4 blockers and their effects, pros and cons on why to use TGN-020. Among others, I would refer to recent work by Giannetto et al 2024, as well as previous work of Mestre et al. 2018 and Gomolka et al. 2023.

      We initiated the study by using TGN-020 as an AQP4 blocker because it has been validated by wide range of ex vivo and in vivo studies as documented in the text (page 7, line 1-6). We also update discussions on the recent advances in validating the AQP4 blocker AER-270(271) while citing the relevant studies (page 15, line 7-17).  

      RESULTS:

      - Page 5, lines 19-20: '...transport, we performed fluorescence intensity translated (FIT) imaging.' - this term was never introduced in the methods so it is difficult for the reader to understand it at first sight. -'To this end,' - it is not clear which action refers to 'this'. (is it about previous works or the moment that the brain samples were ready for imaging? Please clarify, as it is only starting to be clear after fully reading the methods.

      We now refine the description give the principle of our imaging method first, then explain the technical steps. To avoid ambiguity, the term ‘To this end’ is removed. The updated text is now on page 6, line 1-3.  

      - From page 6 onwards - all references to Figures lack information to which part of the figure subpanel the information refers (top/middle bottom or left/middle/right).

      We apologize. The complementary indication is now added for figure citations when applicable.  

      - 'whereas water export and astrocyte shrinking upon hyperosmotic manipulation increased astrocyte fluorescence (Figure 1B). Hence, FIT imaging enables real-time recording of astrocyte transmembrane water transport and volume dynamics.' - this part seems to be undescribed or not clear in the methods.

      We have now refined this description (page 6, line 19-20).

      - Page 6, lines 17-22: TGN-020. In addition to the above, I suggest familiarizing also with the following works by Igarashi 2011. doi: 10.1007/s10072-010-0431-1, and by Sun 2022. doi: 10.3389/fimmu.2022.870029.

      These studies are now cited (page 7, line 3-4).

      - Page 7: ' AQP4 is a bidirectional channel facilitating... ' - AQP4 water channel is known as the path of least resistance for water transfer, please see Manley, Nature Medicine, 2000 and Papadopoulos, Faseb J, 2004.

      This sentence is now updated (page 7, line 12-13).

      - ' astrocyte AQP4 by TGN-020 caused a gradual decrease in SRB fluorescence intensity, indicating an intracellular water accumulation' - tissue slice experiment is a very valuable method. However it seems right, the experiment does not comment on the cell swelling that may occur just due to or as a superposition of tissue deterioration and the effect of TGN-020. The AQP4 channel is blocked, and the influx of water into astrocytes should be also blocked. Thus, can swelling be also a part of another mechanism, as it was also observed in the control group? I suggest this should be addressed thoroughly.

      We performed this experiment in acute brain slices to well control the pharmacological environment and gain spatial-temporal information. Post slicing, the brain slices recovered > 1hr prior to recording, so that the slices were in a stable state before TGN-020 application as evidenced by the stable baseline. The constant decrease in the control trace is due to photobleaching which did not change its curve tendency in response to vehicle. TGN-020, in contrast, caused a down-ward change suggesting intracellular water accumulation and swelling. 

      The experiment was performed at basal condition without active water influx; a decrease in SRB fluorescence hints astrocyteintracellular water buildup. This result shows that in basal condition, astrocyte aquaporin mediates a constant (i.e., tonic) water efflux; its blocking causes intracellular water accumulation and swelling. 

      We have accordingly updated the description of this part (page 7, line 15-20).

      - From the Figure 1 legend: Only 4 mice were subjected to the experiment, and only 1 mouse as a control. I suggest expanding the experiment and performing statistics including two-way ANOVA for data in panels B, C, and D, as no results of statistical tests confirm the significance of the findings provided.

      The panel B confirms that cytosolic SRB fluorescence displays increasing tendency upon water efflux and volume shrinking, and vice versa. As for the panel C, the number of mice is now indicated. Also, the downward change in the SRB fluorescence was now respectively calculated for the phases prior and post to TGN (and vehicle) application, and this panel is accordingly updated. TGN-020 induced a declining in astrocyte SRB fluorescence, which is validated by t-test performed in MATLAB. To clarify, we now add cross-link lines to indicate statistical significance between the corresponding groups (Fig 1C, middle). As for panel D, we calculated the SRB fluorescence change (decrease) relative to the photobleaching tendency illustrated by the dotted line. The significance was also validated by t-test performed in MATLAB.  

      - Figure 1: Please correct the figure - pictures in panel A are low quality and do not support the specificity of SRB for astrocytes. Panels B-D are easier to understand if plotted as normal X/Y charts with associated statistical findings. Some drawings are cut or not aligned.

      In GFAP-EGFP transgenic, astrocytes are labeled by EGFP. SRB labeling (red fluorescence) shows colocalization with EGFP-positive astrocytes, meanwhile not all EGFP-positive astrocytes are labeled by SRB. The PDF conversion procedure during the submission may also somehow have compromised image quality. We have tried to update and align the figure panels.  

      - Page 12: ' TGN-020 increased basal water diffusion within multiple regions including the cortex,

      hippocampus and the striatum in a heterogeneous manner (Figure 5C).'

      This sentence is updated now (page 12, line 12 – page13, line 2). It reads ‘The representative images reveal the enough image quality to calculate the ADC, which allow us to examine the effect of TGN-020 on water diffusion rate in multiple regions (Fig. 5C).’

      - The expression of AQP4 within the brain parenchyma is known to be heterogenous. Please familiarize yourself with works by Hubbard 2015, Mestre 2018, and Gomolka 2023. A correlation between ADC score and AQP4 expression ROI-wise would be useful, but it is not substantial to conduct this experiment.

      We thank the reviewer. This point is stressed on page 19, line 12-14.

      DISCUSSION:

      - Most of the issues are commented on above, so I suggest following the changes applied earlier. -Page 16: 'We show by DW-MRI that water transport by astrocyte aquaporin is critical for brain water homeostasis.' This statement is not clear and does not refer to the actual impact of the findings. DWI is allowed only to verify the changes of ADC fter the application of TGN-020. I suggest commenting on the recent report by Giannetto 2024 here.

      This sentence is now refined (page 19, line 1-2), followed by the updates commenting on the recent studies employing DW-MRI to evaluate brain fluid transport, including the work of (Giannetto et al., 2024) (page 19, line 3-10). 

      METHODS:

      - Page 18: no total number of mice included in all experiments is provided, as well as no clearly stated number of mice used in each experiment. Please correct.

      We have now double checked the number of the mice for the data presented and updated the figure legends accordingly (e.g., updates in legends fig1, fig5, etc).

      -  Page 18, line 7: 'Axscience' is not a producer of Isoflurane, but a company offering help with scientific manuscript writing. If this company's help was used, it should be stated in the acknowledgments section. Reference to ISOVET should be moved from line 15 to line 7.

      We apologize. We did not use external writing help, and now have removed the ‘Axcience’. The Isoflurane was under the mark ‘ISOVET’ from ‘Piramal’. This info is now moved up (page 21, line 11). 

      - Page 18, line 9: ' modified artificial cerebrospinal fluid (aCSF)'. Additional information on the reason for the modified aCSF would be useful for the reader.

      In this modified solution, the concentration of depolarizing ions (Na+, Ca2+) was reduced to lower the potential excitotoxicity during the tissue dissection (i.e., injury to the brain) for preparing the brain slices. Extra sucrose was added to balance the solution osmolarity. This solution has been used previously for the dissection and the slicing steps in adult mice (Jiang et al., 2016). We now add this justification in the text and quote the relevant reference (page 21, line14-16). 

      - Page 19, line 6: a reasoning for using Tamoxifen would be helpful for the reader.

      The Glast-CreERT2 is an inducible conditional mouse line that expresses Cre recombinase selectively in astrocytes upon tamoxifen injection. We now add this information in the text (page 22, line 10-11). 

      - Line 8 - 'Sigma'

      Fixed.

      - Line 7/8: It is not clear if ethanol is of 10% solution or if proportions of ethanol+tamoxifen to oil were of 1:9. The reasoning for each performed step is missing.

      We have now clarified the procedure (page 22, line 11-15).

      - Line 10: '/' means 'or'?

      Here, we mean the bigenic mice resulting from the crossing of the heterozygous Cre-dependent GCaMP6f and Glast-CreERT2 mouse lines. We now modify it to ‘Glast-CreERT2::Ai95GCaMP6f//WT’, in consistence with the presentation of other mouse lines in our manuscript (page 22, line 16).

      - Lines 22-23: being in-line with legislation was already stated at the beginning of the Methods so I suggest combining for clearance.

      Done. 

      - Page 21, line 4: it is good to mention which printer was used, but it would be worth mentioning the material the chamber was printed from - was it ABS?

      Yes. We add this info in the text now (page 24, line 5).

      - Line 9 -'PI' requires spelling out.

      It is ‘Physik Instrumente’, now added (page 24, line 10).

      - Line 11-12: What is the reason for background subtraction - clearer delineation of astrocytes/ increasing SNR in post-processing, or because SRB signal was also visible and changing in the background over time? Was the background removed in each frame independently (how many frames)? How long was the time-lapse and was the F0 frame considered as the first frame acquired? The background signal should be also measured and plotted alongside the astrocytic signal, as a reference (Figure 1). This should be clarified so that steps are to be followed easily.

      We sought to follow the temporal changes in SRB fluorescence signal. The acquired fluorescent images contain not only the SRB signals, but also the background signals consisting of for instance the biological tissue autofluorescence, digital camera background noise and the leak light sources from the environments. The value of the background signal was estimated by the mean fluorescence of peripheral cell-free subregions (15 × 15 µm²) and removed from all frames of time-lapse image stack. The traces shown in the figures reflect the full lengths of the time-lapse recordings. F0 was identified as the mean value of the 10 data points immediately preceding the detected fluorescence changes. The text is now updated (page 24 line 21 - page 25 line 5).

      - Line 15: Was astrocyte image delineation performed manually or automatically? Where was the center of the region considered in the reference to the astrocyte image? It would be good to see the regions delineated for reference.

      Astrocytes labeled by SRB were delineated manually with the soma taken as the center of the region of interest. We now exemplify the delineated region in Fig 1A, bottom.

      - Page 22, line 2: 'x4 objective'.

      Added (now, page 25, line 16). 

      - Line 3: 'barrels' - reference to publication or the explanation missing.

      The relevant reference is now added on barrel cortex (Erzurumlu and Gaspar, 2020) (page 25, line 19-20). 

      - Line 19: were the coordinates referred to = bregma?

      Yes. This info is now added (page 26, line 12). 

      - Line 20: was the habituation performed directly at the acquisition date? It is rather difficult to say that it was a habituation, but rather acute imaging. I suggest correcting, that mice were allowed to familiarize themselves with the setup for 30 minutes prior to the imaging start.

      In this context, although it is a very nice idea and experiment, the influence of acute stress in animals familiar with the setup only from the day of acquisition is difficult to avoid. It is a major concern, especially when considering norepinephrine as a master driver of neuronal and vascular activity through the brain, and strong activation of the hypothalamic-adrenal axis in response to acute stress. It is well known, that the response of monoamines is reduced in animals subjected to chronic v.s acute stress, but still larger than that if the stressor is absent.

      Major remark: The animals should, preferably, be imaged at least after 3 days of habituation based on existing knowledge. I suggest exploring the topic of the importance of habituation. It is difficult though, to objectively review these findings without considering stress and associated changes in vascular dynamics.

      Many thanks for the reviewer to help to precise this information. The text is accordingly updated to describe the experiment (now page 26, line 14). 

      - Page 23, line 17: number of animals included in experiments missing.

      The number of animals is added in Methods (page 27, line 12) and indicated in the legend of Figure 5. 

      - Line 18/19: were the respiratory effects observed after injection of saline or TGN-020? Since DWI was performed, the exclusion of perfusive flow on ADC is impossible.

      I suggest an additional experiment in n=3 animals per group, verifying the HR (and if possible BP) response after injection of TGN-020 and saline in mice.

      The respiratory rate has been recorded. We added the averaged respiratory rate before and after injection of TGN-020 or saline (now, Fig. S6; page 13, line 5-6).

      - Line 22: Please, provide the model of the scanner, the model of the cryoprobe, as well as the model of the gradient coil used, otherwise it is difficult to assess or repeat these experiments.

      We have now added the information of MRI system in Methods section (page 27, line17-21).

      - Page 24: line 3/4: although the achieved spatial resolution of DWI was good and slightly lower than desired and achievable due to limitations of the method itself as well as cryoprobe, it is acceptable for EPI in mice.

      Still, there is no direct explanation provided on the reasoning for using surface instead of volumetric coil, as well as on assuming an anisotropic environment (6 diffusion directions) for DWI measurements. This is especially doubtful if such a long echo-time was used alongside lower-thanpossible spatial resolution. Longer echo time would lower the SNR of the depicted signal but also would favor the depiction of signal from slow-moving protons and larger water pools. On the other hand, only 3 b-values were used, which is the minimum for ADC measurements, while a good research protocol could encompass at least 5 to increase the accuracy of ADC estimation and avoid undersampling between 250 and 1800 b-values. What was the reason for choosing this particular set of b-values and not 50, 600, and 2000? Besides, gradient duration time was optimally chosen, however, I have concerns about the decision for such a long gradient separation times.

      If the protocol could have been better optimized, the assessment could have been also performed in respiratory-gated mode, allowing minimization of the effects of one of the glymphatic system driving forces.

      Thus, I suggest commenting on these issues.

      We chose the cryoprobe to increase the signal-to-noise ratio (SNR) in DW-MRI with long echo-time and high b-value. The volume coil has a more homogeneous SNR in the whole brain rather than the cryoprobe, but SNR should be reduced compared with cryoprobe. We confirmed that, even at the ventral part of the brain, the image quality of DW-MRI images was enough to investigate the ADC with cryoprobe (Fig. 5B-C). This is mentioned now in Methods (page 27, line 17-21).

      We performed DW-MRI scanning for 5 min at each time-point using the condition of anisotropic resolution and 3 b-values, to investigate the time-course of ADC change following the injection of TGN020. Because the effect of TGN-020 appears about dozen of minutes post the injection (Igarashi et al., 2011), fast DW-MRI scanning is required. If isotropic DW-MRI with lower echo-time and more direction is used, longer scan time at each time point is required, maybe more than 1h. We agree that three bvalues is minimum to calculate the ADC and more b-values help to increase the accuracy. However, to achieve the temporal resolution so as to better catch the change of water diffusion, we have decided to use the minimum b-values. The previous study also validates the enough accuracy of DW-MRI with three b-values (Ashoor et al., 2019). Furthermore, previous study that used long diffusion time (> 20 ms) and long echo time (40 ms) shows the good mean diffusivity (Aggarwal et al., 2020), supporting that our protocol is enough to investigate the ADC. We have now updated the description (page 28 line 5-9).  The reason why we choose the b = 250 and 1800 s/mm² is that 2000 s/mm² seems too high to get the good quality of image. In the previous study, we have optimized that ADC is measurable with b = 0, 250, and 1800 s/mm² (Debacker et al., 2020). 

      - Page 24, line 7: What was the post-processing applied for images acquired over 70 minutes? Did it consider motion-correction, co-registration, or drift-correction crucial to avoid pitfalls and mismatches in concluding data?

      The motion correction and co-registration were explained in Methods (page 28, line 12-14).

      Also, were these trace-weighted images or magnitude images acquired since DTI software was used for processing - while ADC fitting could be reliably done in Matlab, Python, or other software. Thus, was DSI software considering all 3 b-values or just used 0 and 1800 for the calculation of mean diffusivity for tractography (as ADC). The details should be explained.

      DSIstudio was used with all three b values (b = 0, 250, and 1800 s/mm²) to calculate the ADC. We added the description in Methods (page 28, line 16-18).

      To make sure that the results are not affected by the MR hardware, I suggest performing 3 control measurements in a standard water phantom, and presenting the results alongside the main findings.

      Thanks for this suggestion. We have performed new experiments and now added the control measurement with three phantoms, that is water, undecane, and dodecane. These new data are summarized now in Fig. S7, showing the stability of ADC throughout the 70 min scanning. We have updated the description on Method part (page 28, line 9-11) and on the Results (page 13, line 6-8).  

      - Line 13: were the ROI defined manually or just depicted from previously co-registered Allen Brain atlas?

      The ROIs of the cortex, the hippocampus, and the striatum were depicted with reference to Allen mouse brain atlas (https://scalablebrainatlas.incf.org/mouse/ABA12). This is explained in Methods (page 28, line 14-16).

      - Line 10: why the average from 1st and 2nd ADC was not considered, since it would reduce the influence of noise on the estimation of baseline ADC?

      We are sorry that it was a typo. The baseline was the average between 1st and 2nd ADC. We corrected the description (page 28, line 20).

      STATISTIC:

      Which type of t-test - paired/unpaired/two samples was used and why? Mann-Whitney U-tets are used as a substitution for parametric t-tests when the data are either non-parametric or assuming normal distribution is not possible. In which case Bonferroni's-Holm correction was used? - I couldn't find any mention of any multiple-group analysis followed by multiple comparisons. Each section of the manuscript should have a description of how the quantitative data were treated and in which aim. I suggest carefully correcting all figures accordingly, and following the remarks given to the Figure 1.

      We used unpaired t-test for data obtained from samples of different conditions. Indeed, MannWhitney U-test is used when the data are non-parametric deviating from normal distributions.  Bonferroni-Holm correction was used for multiple comparisons (e.g., Fig. 4D-E).

      Reviewer #3 (Recommendations For The Authors):

      I think that the following statement is insufficient: "The authors commit to share data, documentation, and code used in analysis". My understanding is eLife expects that all key data to be provided in a supplement.

      We thank the reviewer; we follow the publication guidelines of eLife. 

      References

      Aggarwal, M., Smith, M.D., and Calabresi, P.A. (2020). Diffusion-time dependence of diffusional kurtosis in the mouse brain. Magn Reson Med 84, 1564-1578.

      Ashoor, M., Khorshidi, A., and Sarkhosh, L. (2019). Estimation of microvascular capillary physical parameters using MRI assuming a pseudo liquid drop as model of fluid exchange on the cellular level. Rep Pract Oncol Radiother 24, 3-11.

      Cauli, B., and Hamel, E. (2018). Brain Perfusion and Astrocytes. Trends in neurosciences 41, 409-413.

      Debacker, C., Djemai, B., Ciobanu, L., Tsurugizawa, T., and Le Bihan, D. (2020). Diffusion MRI reveals in vivo and non-invasively changes in astrocyte function induced by an aquaporin-4 inhibitor. PLoS One 15, e0229702.

      Erzurumlu, R.S., and Gaspar, P. (2020). How the Barrel Cortex Became a Working Model for Developmental Plasticity: A Historical Perspective. J Neurosci 40, 6460-6473.

      Farr, G.W., Hall, C.H., Farr, S.M., Wade, R., Detzel, J.M., Adams, A.G., Buch, J.M., Beahm, D.L., Flask, C.A., Xu, K., et al. (2019). Functionalized Phenylbenzamides Inhibit Aquaporin-4 Reducing Cerebral Edema and Improving Outcome in Two Models of CNS Injury. Neuroscience 404, 484-498.

      Giannetto, M.J., Gomolka, R.S., Gahn-Martinez, D., Newbold, E.J., Bork, P.A.R., Chang, E., Gresser, M., Thompson, T., Mori, Y., and Nedergaard, M. (2024). Glymphatic fluid transport is suppressed by the aquaporin-4 inhibitor AER-271. Glia.

      Gomolka, R.S., Hablitz, L.M., Mestre, H., Giannetto, M., Du, T., Hauglund, N.L., Xie, L., Peng, W., Martinez, P.M., Nedergaard, M., et al. (2023). Loss of aquaporin-4 results in glymphatic system dysfunction via brain-wide interstitial fluid stagnation. eLife 12.

      Huber, V.J., Tsujita, M., and Nakada, T. (2009). Identification of aquaporin 4 inhibitors using in vitro and in silico methods. Bioorg Med Chem 17, 411-417.

      Igarashi, H., Huber, V.J., Tsujita, M., and Nakada, T. (2011). Pretreatment with a novel aquaporin 4 inhibitor, TGN-020, significantly reduces ischemic cerebral edema. Neurol Sci 32, 113-116.

      Igarashi, H., Tsujita, M., Suzuki, Y., Kwee, I.L., and Nakada, T. (2013). Inhibition of aquaporin-4 significantly increases regional cerebral blood flow. Neuroreport 24, 324-328.

      Jiang, R., Diaz-Castro, B., Looger, L.L., and Khakh, B.S. (2016). Dysfunctional Calcium and Glutamate Signaling in Striatal Astrocytes from Huntington's Disease Model Mice. J Neurosci 36, 3453-3470.

      Mayo, F., Gonzalez-Vinceiro, L., Hiraldo-Gonzalez, L., Calle-Castillejo, C., Morales-Alvarez, S., Ramirez-Lorca, R., and Echevarria, M. (2023). Aquaporin-4 Expression Switches from White to Gray Matter Regions during Postnatal Development of the Central Nervous System. Int J Mol Sci 24.

      Mola, M.G., Sparaneo, A., Gargano, C.D., Spray, D.C., Svelto, M., Frigeri, A., Scemes, E., and Nicchia, G.P. (2016). The speed of swelling kinetics modulates cell volume regulation and calcium signaling in astrocytes: A different point of view on the role of aquaporins. Glia 64, 139-154.

      Risher, W.C., Andrew, R.D., and Kirov, S.A. (2009). Real-time passive volume responses of astrocytes to acute osmotic and ischemic stress in cortical slices and in vivo revealed by two-photon microscopy. Glia 57, 207-221.

      Salman, M.M., Kitchen, P., Yool, A.J., and Bill, R.M. (2022). Recent breakthroughs and future directions in drugging aquaporins. Trends Pharmacol Sci 43, 30-42.

      Shigetomi, E., Bushong, E.A., Haustein, M.D., Tong, X., Jackson-Weaver, O., Kracun, S., Xu, J., Sofroniew, M.V., Ellisman, M.H., and Khakh, B.S. (2013). Imaging calcium microdomains within entire astrocyte territories and endfeet with GCaMPs expressed using adeno-associated viruses. J Gen Physiol 141, 633-647.

      Solenov, E., Watanabe, H., Manley, G.T., and Verkman, A.S. (2004). Sevenfold-reduced osmotic water permeability in primary astrocyte cultures from AQP-4-deficient mice, measured by a fluorescence quenching method. Am J Physiol Cell Physiol 286, C426-432.

      Verkman, A.S., Binder, D.K., Bloch, O., Auguste, K., and Papadopoulos, M.C. (2006). Three distinct roles of aquaporin-4 in brain function revealed by knockout mice. Biochim Biophys Acta 1758, 10851093.

    1. Social Media Architecture with IPFS

      not just distributed but personal first, local first, interpersonal interest based autonomous social networks

      for - hyperpost

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this paper, Misic et al showed that white matter properties can be used to classify subacute back pain patients that will develop persisting pain.

      Strengths:

      Compared to most previous papers studying associations between white matter properties and chronic pain, the strength of the method is to perform a prediction in unseen data. Another strength of the paper is the use of three different cohorts. This is an interesting paper that provides a valuable contribution to the field.

      We thank the reviewer for emphasizing the strength of our paper and the importance of validation on multiple unseen cohorts.

      Weaknesses:

      The authors imply that their biomarker could outperform traditional questionnaires to predict pain: "While these models are of great value showing that few of these variables (e.g. work factors) might have significant prognostic power on the long-term outcome of back pain and provide easy-to-use brief questionnaires-based tools, (21, 25) parameters often explain no more than 30% of the variance (28-30) and their prognostic accuracy is limited.(31)". I don't think this is correct; questionnaire-based tools can achieve far greater prediction than their model in about half a million individuals from the UK Biobank (Tanguay-Sabourin et al., A prognostic risk score for the development and spread of chronic pain, Nature Medicine 2023).

      We agree with the reviewer that we might have under-estimated the prognostic accuracy of questionnaire-based tools, especially, the strong predictive accuracy shown by Tangay-Sabourin 2023.  In this revised version, we have changed both the introduction and the discussion to reflect the questionnaire-based prognostic accuracy reported in the seminal work by Tangay-Sabourin. 

      In the introduction (page 4, lines 3-18), we now write:

      “Some studies have addressed this question with prognostic models incorporating demographic, pain-related, and psychosocial predictors.1-4 While these models are of great value showing that few of these variables (e.g. work factors) might have significant prognostic power on the long-term outcome of back pain, their prognostic accuracy is limited,5 with parameters often explaining no more than 30% of the variance.6-8. A recent notable study in this regard developed a model based on easy-to-use brief questionnaires to predict the development and spread of chronic pain in a variety of pain conditions capitalizing on a large dataset obtained from the UK-BioBank. 9 This work demonstrated that only few features related to assessment of sleep, neuroticism, mood, stress, and body mass index were enough to predict persistence and spread of pain with an area under the curve of 0.53-0.73. Yet, this study is unique in showing such a predictive value of questionnaire-based tools. Neurobiological measures could therefore complement existing prognostic models based on psychosocial variables to improve overall accuracy and discriminative power. More importantly, neurobiological factors such as brain parameters can provide a mechanistic understanding of chronicity and its central processing.”

      And in the conclusion (page 22, lines 5-9), we write:

      “Integrating findings from studies that used questionnaire-based tools and showed remarkable predictive power9 with neurobiological measures that can offer mechanistic insights into chronic pain development, could enhance predictive power in CBP prognostic modeling.”

      Moreover, the main weakness of this study is the sample size. It remains small despite having 3 cohorts. This is problematic because results are often overfitted in such a small sample size brain imaging study, especially when all the data are available to the authors at the time of training the model (Poldrack et al., Scanning the horizon: towards transparent and reproducible neuroimaging research, Nature Reviews in Neuroscience 2017). Thus, having access to all the data, the authors have a high degree of flexibility in data analysis, as they can retrain their model any number of times until it generalizes across all three cohorts. In this case, the testing set could easily become part of the training making it difficult to assess the real performance, especially for small sample size studies.

      The reviewer raises a very important point of limited sample size and of the methodology intrinsic of model development and testing. We acknowledge the small sample size in the “Limitations” section of the discussion.   In the resubmission, we acknowledge the degree of flexibility that is afforded by having access to all the data at once. However, we also note that our SLF-FA based model is a simple cut-off approach that does not include any learning or hidden layers and that the data obtained from Open Pain were never part of the “training” set at any point at either the New Haven or the Mannheim site.  Regarding our SVC approach we follow standard procedures for machine learning where we never mix the training and testing sets. The models are trained on the training data with parameters selected based on cross-validation within the training data. Therefore, no models have ever seen the test data set. The model performances we reported reflect the prognostic accuracy of our model. We write in the limitation section of the discussion (page 20, lines 20-21, and page 21, lines 1-6):

      “In addition, at the time of analysis, we had “access” to all the data, which may lead to bias in model training and development.  We believe that the data presented here are nevertheless robust since multisite validated but need replication. Additionally, we followed standard procedures for machine learning where we never mix the training and testing sets. The models were trained on the training data with parameters selected based on cross-validation within the training data. Therefore, no models have ever seen the test data set. The model performances we reported reflect the prognostic accuracy of our model”. 

      Finally, as discussed by Spisak et al., 10 the key determinant of the required sample size in predictive modeling is the ” true effect size of the brain-phenotype relationship”, which we think is the determinant of the replication we observe in this study. As such the effect size in the New Haven and Mannheim data is Cohen’s d >1.

      Even if the performance was properly assessed, their models show AUCs between 0.65-0.70, which is usually considered as poor, and most likely without potential clinical use. Despite this, their conclusion was: "This biomarker is easy to obtain (~10 min of scanning time) and opens the door for translation into clinical practice." One may ask who is really willing to use an MRI signature with a relatively poor performance that can be outperformed by self-report questionnaires?

      The reviewer is correct, the model performance is fair which limits its usefulness for clinical translation.  We wanted to emphasize that obtaining diffusion images can be done in a short period of time and, hence, as such models’ predictive accuracy improves, clinical translation becomes closer to reality. In addition, our findings are based on older diffusion data and limited sample sizes coming from different sites and different acquisition sequences.  This by itself would limit the accuracy especially since the evidence shows that sample size affects also model performance (i.e. testing AUC)10.  In the revision, we re-worded the sentence mentioned by the reviewer to reflect the points discussed here. This also motivates us to collect a more homogeneous and larger sample.  In the limitations section of the discussion, we now write (page 21, lines 6-9):

      “Even though our model performance is fair, which currently limits its usefulness for clinical translation, we believe that future models would further improve accuracy by using larger homogenous sample sizes and uniform acquisition sequences.”

      Overall, these criticisms are more about the wording sometimes used and the inference they made. I think the strength of the evidence is incomplete to support the main claims of the paper.

      Despite these limitations, I still think this is a very relevant contribution to the field. Showing predictive performance through cross-validation and testing in multiple cohorts is not an easy task and this is a strong effort by the team. I strongly believe this approach is the right one and I believe the authors did a good job.

      We thank the reviewer for acknowledging that our effort and approach were useful.

      Minor points:

      Methods:

      I get the voxel-wise analysis, but I don't understand the methods for the structural connectivity analysis between the 88 ROIs. Have the authors run tractography or have they used a predetermined streamlined form of 'population-based connectome'? They report that models of AUC above 0.75 were considered and tested in the Chicago dataset, but we have no information about what the model actually learned (although this can be tricky for decision tree algorithms). 

      We apologize for the lack of clarity; we did run tractography and we did not use a pre-determined streamlined form of the connectome.

      Finding which connections are important for the classification of SBPr and SBPp is difficult because of our choices during data preprocessing and SVC model development: (1) preprocessing steps which included TNPCA for dimensionality reduction, and regressing out the confounders (i.e., age, sex, and head motion); (2) the harmonization for effects of sites; and (3) the Support Vector Classifier which is a hard classification model11.

      In the methods section (page 30, lines 21-23) we added: “Of note, such models cannot tell us the features that are important in classifying the groups.  Hence, our model is considered a black-box predictive model like neural networks.”

      Minor:

      What results are shown in Figure 7? It looks more descriptive than the actual results.

      The reviewer is correct; Figure 7 and Supplementary Figure 4 were both qualitatively illustrating the shape of the SLF. We have now changed both figures in response to this point and a point raised by reviewer 3.  We now show a 3D depiction of different sub-components of the right SLF (Figure 7) and left SLF (Now Supplementary Figure 11 instead of Supplementary Figure 4) with a quantitative estimation of the FA content of the tracts, and the number of tracts per component.  The results reinforce the TBSS analysis in showing asymmetry in the differences between left and right SLF between the groups (i.e. SBPp and SBPr) in both FA values and number of tracts per bundle.

      Reviewer #2 (Public Review):

      The present study aims to investigate brain white matter predictors of back pain chronicity. To this end, a discovery cohort of 28 patients with subacute back pain (SBP) was studied using white matter diffusion imaging. The cohort was investigated at baseline and one-year follow-up when 16 patients had recovered (SBPr) and 12 had persistent back pain (SBPp). A comparison of baseline scans revealed that SBPr patients had higher fractional anisotropy values in the right superior longitudinal fasciculus SLF) than SBPp patients and that FA values predicted changes in pain severity. Moreover, the FA values of SBPr patients were larger than those of healthy participants, suggesting a role of FA of the SLF in resilience to chronic pain. These findings were replicated in two other independent datasets. The authors conclude that the right SLF might be a robust predictive biomarker of CBP development with the potential for clinical translation.

      Developing predictive biomarkers for pain chronicity is an interesting, timely, and potentially clinically relevant topic. The paradigm and the analysis are sound, the results are convincing, and the interpretation is adequate. A particular strength of the study is the discovery-replication approach with replications of the findings in two independent datasets.

      We thank reviewer 2 for pointing to the strength of our study.

      The following revisions might help to improve the manuscript further.

      - Definition of recovery. In the New Haven and Chicago datasets, SBPr and SBPp patients are distinguished by reductions of >30% in pain intensity. In contrast, in the Mannheim dataset, both groups are distinguished by reductions of >20%. This should be harmonized. Moreover, as there is no established definition of recovery (reference 79 does not provide a clear criterion), it would be interesting to know whether the results hold for different definitions of recovery. Control analyses for different thresholds could strengthen the robustness of the findings.

      The reviewer raises an important point regarding the definition of recovery.  To address the reviewers’ concern we have added a supplementary figure (Fig. S6) showing the results in the Mannheim data set if a 30% reduction is used as a recovery criterion, and in the manuscript (page 11, lines 1,2) we write: “Supplementary Figure S6 shows the results in the Mannheim data set if a 30% reduction is used as a recovery criterion in this dataset (AUC= 0.53)”.

      We would like to emphasize here several points that support the use of different recovery thresholds between New Haven and Mannheim.  The New Haven primary pain ratings relied on visual analogue scale (VAS) while the Mannheim data relied on the German version of the West-Haven-Yale Multidimensional Pain Inventory. In addition, the Mannheim data were pre-registered with a definition of recovery at 20% and are part of a larger sub-acute to chronic pain study with prior publications from this cohort using the 20% cut-off12. Finally, a more recent consensus publication13 from IMMPACT indicates that a change of at least 30% is needed for a moderate improvement in pain on the 0-10 Numerical Rating Scale but that this percentage depends on baseline pain levels.

      - Analysis of the Chicago dataset. The manuscript includes results on FA values and their association with pain severity for the New Haven and Mannheim datasets but not for the Chicago dataset. It would be straightforward to show figures like Figures 1 - 4 for the Chicago dataset, as well.

      We welcome the reviewer’s suggestion; we added these analyses to the results section of the resubmitted manuscript (page 11, lines 13-16): “The correlation between FA values in the right SLF and pain severity in the Chicago data set showed marginal significance (p = 0.055) at visit 1 (Fig. S8A) and higher FA values were significantly associated with a greater reduction in pain at visit 2 (p = 0.035) (Fig. S8B).”

      - Data sharing. The discovery-replication approach of the present study distinguishes the present from previous approaches. This approach enhances the belief in the robustness of the findings. This belief would be further enhanced by making the data openly available. It would be extremely valuable for the community if other researchers could reproduce and replicate the findings without restrictions. It is not clear why the fact that the studies are ongoing prevents the unrestricted sharing of the data used in the present study.

      We greatly appreciate the reviewer's suggestion to share our data sets, as we strongly support the Open Science initiative. The Chicago data set is already publicly available. The New Haven data set will be shared on the Open Pain repository, and the Mannheim data set will be uploaded to heiDATA or heiARCHIVE at Heidelberg University in the near future. We cannot share the data immediately because this project is part of the Heidelberg pain consortium, “SFB 1158: From nociception to chronic pain: Structure-function properties of neural pathways and their reorganization.” Within this consortium, all data must be shared following a harmonized structure across projects, and no study will be published openly until all projects have completed initial analysis and quality control.

      Reviewer #3 (Public Review):

      Summary:

      Authors suggest a new biomarker of chronic back pain with the option to predict the result of treatment. The authors found a significant difference in a fractional anisotropy measure in superior longitudinal fasciculus for recovered patients with chronic back pain.

      Strengths:

      The results were reproduced in three different groups at different studies/sites.

      Weaknesses:

      - The number of participants is still low.

      The reviewer raises a very important point of limited sample size. As discussed in our replies to reviewer number 1:

      We acknowledge the small sample size in the “Limitations” section of the discussion.   In the resubmission, we acknowledge the degree of flexibility that is afforded by having access to all the data at once. However, we also note that our SLF-FA based model is a simple cut-off approach that does not include any learning or hidden layers and that the data obtained from Open Pain were never part of the “training” set at any point at either the New Haven or the Mannheim site.  Regarding our SVC approach we follow standard procedures for machine learning where we never mix the training and testing sets. The models are trained on the training data with parameters selected based on cross-validation within the training data. Therefore, no models have ever seen the test data set. The model performances we reported reflect the prognostic accuracy of our model. We write in the limitation section of the discussion (page 20, lines 20-21, and page 21, lines 1-6):

      “In addition, at the time of analysis, we had “access” to all the data, which may lead to bias in model training and development.  We believe that the data presented here are nevertheless robust since multisite validated but need replication. Additionally, we followed standard procedures for machine learning where we never mix the training and testing sets. The models were trained on the training data with parameters selected based on cross-validation within the training data. Therefore, no models have ever seen the test data set. The model performances we reported reflect the prognostic accuracy of our model”. 

      Finally, as discussed by Spisak et al., 10 the key determinant of the required sample size in predictive modeling is the ” true effect size of the brain-phenotype relationship”, which we think is the determinant of the replication we observe in this study. As such the effect size in the New Haven and Mannheim data is Cohen’s d >1.

      - An explanation of microstructure changes was not given.

      The reviewer points to an important gap in our discussion.  While we cannot do a direct study of actual tissue microstructure, we explored further the changes observed in the SLF by calculating diffusivity measures. We have now performed the analysis of mean, axial, and radial diffusivity. 

      In the results section we added (page 7, lines 12-19): “We also examined mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) extracted from the right SLF shown in Fig.1 to further understand which diffusion component is different between the groups. The right SLF MD is significantly increased (p < 0.05) in the SBPr compared to SBPp patients (Fig. S3), while the right SLF RD is significantly decreased (p < 0.05) in the SBPr compared to SBPp patients in the New Haven data (Fig. S4). Axial diffusivity extracted from the RSLF mask did not show significant difference between SBPr and SBPp (p = 0.28) (Fig. S5).”

      In the discussion, we write (page 15, lines 10-20):

      “Within the significant cluster in the discovery data set, MD was significantly increased, while RD in the right SLF was significantly decreased in SBPr compared to SBPp patients. Higher RD values, indicative of demyelination, were previously observed in chronic musculoskeletal patients across several bundles, including the superior longitudinal fasciculus14.  Similarly, Mansour et al. found higher RD in SBPp compared to SBPr in the predictive FA cluster. While they noted decreased AD and increased MD in SBPp, suggestive of both demyelination and altered axonal tracts,15 our results show increased MD and RD in SBPr with no AD differences between SBPp and SBPr, pointing to white matter changes primarily due to myelin disruption rather than axonal loss, or more complex processes. Further studies on tissue microstructure in chronic pain development are needed to elucidate these processes.”

      - Some technical drawbacks are presented.

      We are uncertain if the reviewer is suggesting that we have acknowledged certain technical drawbacks and expects further elaboration on our part. We kindly request that the reviewer specify what particular issues need to be addressed so that we can respond appropriately.

      Recommendations For The Authors:

      We thank the reviewers for their constructive feedback, which has significantly improved our manuscript. We have done our best to answer the criticisms that they raised point-by-point.

      Reviewer #2 (Recommendations For The Authors):

      The discovery-replication approach of the current study justifies the use of the terminus 'robust.' In contrast, previous studies on predictive biomarkers using functional and structural brain imaging did not pursue similar approaches and have not been replicated. Still, the respective biomarkers are repeatedly referred to as 'robust.' Throughout the manuscript, it would, therefore, be more appropriate to remove the label 'robust' from those studies.

      We thank the reviewer for this valuable suggestion. We removed the label 'robust' throughout the manuscript when referring to the previous studies which didn’t follow the same approach and have not yet been replicated.

      Reviewer #3 (Recommendations For The Authors):

      This is, indeed, quite a well-written manuscript with very interesting findings and patient group. There are a few comments that enfeeble the findings.

      (1) It is a bit frustrating to read at the beginning how important chronic back pain is and the number of patients in the used studies. At least the number of healthy subjects could be higher.

      The reviewer raises an important point regarding the number of pain-free healthy controls (HC) in our samples. We first note that our primary statistical analysis focused on comparing recovered and persistent patients at baseline and validating these findings across sites without directly comparing them to HCs. Nevertheless, the data from New Haven included 28 HCs at baseline, and the data from Mannheim included 24 HCs. Although these sample sizes are not large, they have enabled us to clearly establish that the recovered SBPr patients generally have larger FA values in the right superior longitudinal fasciculus compared to the HCs, a finding consistent across sites (see Figs. 1 and 3). This suggests that the general pain-free population includes individuals with both low and high-risk potential for chronic pain. It also offers one explanation for the reported lack of differences or inconsistent differences between chronic low-back pain patients and HCs in the literature, as these differences likely depend on the (unknown) proportion of high- and low-risk individuals in the control groups. Therefore, if the high-risk group is more represented by chance in the HC group, comparisons between HCs and chronic pain patients are unlikely to yield statistically significant results. Thus, while we agree with the reviewer that the sample sizes of our HCs are limited, this limitation does not undermine the validity of our findings.

      (2) Pain reaction in the brain is in general a quite popular topic and could be connected to the findings or mentioned in the introduction.

      We thank the reviewer for this suggestion.  We have now added a summary of brain response to pain in general; In the introduction, we now write (page 4, lines 19-22 and page 5, lines 1-5):

      “Neuroimaging research on chronic pain has uncovered a shift in brain responses to pain when acute and chronic pain are compared. The thalamus, primary somatosensory, motor areas, insula, and mid-cingulate cortex most often respond to acute pain and can predict the perception of acute pain16-19. Conversely, limbic brain areas are more frequently engaged when patients report the intensity of their clinical pain20, 21. Consistent findings have demonstrated that increased prefrontal-limbic functional connectivity during episodes of heightened subacute ongoing back pain or during a reward learning task is a significant predictor of CBP.12, 22. Furthermore, low somatosensory cortex excitability in the acute stage of low back pain was identified as a predictor of CBP chronicity.23”

      (3) It is clearly observed structural asymmetry in the brain, why not elaborate this finding further? Would SLF be a hub in connectivity analysis? Would FA changes have along tract features? etc etc etc

      The reviewer raises an important point. There is ground to suggest from our data that there is an asymmetry to the role of the SLF in resilience to chronic pain. We discuss this at length in the Discussion section. We have, in addition, we elaborated more in our data analysis using our Population Based Structural Connectome pipeline on the New Haven dataset. Following that approach, we studied both the number of fiber tracts making different parts of the SLF on the right and left side. In addition, we have extracted FA values along fiber tracts and compared the average across groups. Our new analyses are presented in our modified Figures 7 and Fig S11.  These results support the asymmetry hypothesis indeed. The SLF could be a hub of structural connectivity. Please note however, given the nature of our design of discovery and validation, the study of structural connectivity of the SLF is beyond the scope of this paper because tract-based connectivity is very sensitive to data collection parameters and is less accurate with single shell DWI acquisition. Therefore, we will pursue the study of connectivity of the SLF in the future with well-powered and more harmonized data.

      (4) Only FA is mentioned; did the authors work with MD, RD, and AD metrics?

      We thank the reviewer for this suggestion that helps in providing a clearer picture of the differences in the right SLF between SBPr and SBPp. We have now extracted MD, AD, and RD for the predictive mask we discovered in Figure 1 and plotted the values comparing SBPr to SBPp patients in Fig. S3, Fig. S4., and Fig. S5 across all sites using one comprehensive harmonized analysis. We have added in the discussion “Within the significant cluster in the discovery data set, MD was significantly increased, while RD in the right SLF was significantly decreased in SBPr compared to SBPp patients. Higher RD values, indicative of demyelination, were previously observed in chronic musculoskeletal patients across several bundles, including the superior longitudinal fasciculus14.  Similarly, Mansour et al. found higher RD in SBPp compared to SBPr in the predictive FA cluster. While they noted decreased AD and increased MD in SBPp, suggestive of both demyelination and altered axonal tracts15, our results show increased MD and RD in SBPr with no AD differences between SBPp and SBPr, pointing to white matter changes primarily due to myelin disruption rather than axonal loss, or more complex processes. Further studies on tissue microstructure in chronic pain development are needed to elucidate these processes.”

      (5) There are many speculations in the Discussion, however, some of them are not supported by the results.

      We agree with the reviewer and thank them for pointing this out. We have now made several changes across the discussion related to the wording where speculations were not supported by the data. For example, instead of writing (page 16, lines 7-9): “Together the literature on the right SLF role in higher cognitive functions suggests, therefore, that resilience to chronic pain is a top-down phenomenon related to visuospatial and body awareness.”, We write: “Together the literature on the right SLF role in higher cognitive functions suggests, therefore, that resilience to chronic pain might be related to a top-down phenomenon involving visuospatial and body awareness.”

      (6) A method section was written quite roughly. In order to obtain all the details for a potential replication one needs to jump over the text.

      The reviewer is correct; our methodology may have lacked more detailed descriptions.  Therefore, we have clarified our methodology more extensively.  Under “Estimation of structural connectivity”; we now write (page 28, lines 20,21 and page 29, lines 1-19):

      “Structural connectivity was estimated from the diffusion tensor data using a population-based structural connectome (PSC) detailed in a previous publication.24 PSC can utilize the geometric information of streamlines, including shape, size, and location for a better parcellation-based connectome analysis. It, therefore, preserves the geometric information, which is crucial for quantifying brain connectivity and understanding variation across subjects. We have previously shown that the PSC pipeline is robust and reproducible across large data sets.24 PSC output uses the Desikan-Killiany atlas (DKA) 25 of cortical and sub-cortical regions of interest (ROI). The DKA parcellation comprises 68 cortical surface regions (34 nodes per hemisphere) and 19 subcortical regions. The complete list of ROIs is provided in the supplementary materials’ Table S6.  PSC leverages a reproducible probabilistic tractography algorithm 26 to create whole-brain tractography data, integrating anatomical details from high-resolution T1 images to minimize bias in the tractography. We utilized DKA 25 to define the ROIs corresponding to the nodes in the structural connectome. For each pair of ROIs, we extracted the streamlines connecting them by following these steps: 1) dilating each gray matter ROI to include a small portion of white matter regions, 2) segmenting streamlines connecting multiple ROIs to extract the correct and complete pathway, and 3) removing apparent outlier streamlines. Due to its widespread use in brain imaging studies27, 28, we examined the mean fractional anisotropy (FA) value along streamlines and the count of streamlines in this work. The output we used includes fiber count, fiber length, and fiber volume shared between the ROIs in addition to measures of fractional anisotropy and mean diffusivity.”

      (7) Why not join all the data with harmonisation in order to reproduce the results (TBSS)

      We have followed the reviewer’s suggestion; we used neuroCombat harmonization after pooling all the diffusion weighted data into one TBSS analysis. Our results remain the same after harmonization. 

      In the Supplementary Information we added a paragraph explaining the method for harmonization; we write (SI, page 3, lines 25-34):

      “Harmonization of DTI data using neuroCombat. Because the 3 data sets originated from different sites using different MR data acquisition parameters and slightly different recruitment criteria, we applied neuroCombat 29  to correct for site effects and then repeated the TBSS analysis shown in Figure 1 and the validation analyses shown in Figures 5 and 6. First, the FA maps derived using the FDT toolbox were pooled into one TBSS analysis where registration to a standard template FA template (FMRIB58_FA_1mm.nii.gz part of FSL) was performed.  Next, neuroCombat was applied to the FA maps as implemented in Python with batch (i.e., site) effect modeled with a vector containing 1 for New Haven, 2 for Chicago, and 3 for Mannheim originating maps, respectively. The harmonized maps were then skeletonized to allow for TBSS.”

      And in the results section, we write (page 12, lines 2-21):

      “Validation after harmonization

      Because the DTI data sets originated from 3 sites with different MR acquisition parameters, we repeated our TBSS and validation analyses after correcting for variability arising from site differences using DTI data harmonization as implemented in neuroCombat. 29 The method of harmonization is described in detail in the Supplementary Methods. The whole brain unpaired t-test depicted in Figure 1 was repeated after neuroCombat and yielded very similar results (Fig. S9A) showing significantly increased FA in the SBPr compared to SBPp patients in the right superior longitudinal fasciculus (MNI-coordinates of peak voxel: x = 40; y = - 42; z = 18 mm; t(max) = 2.52; p < 0.05, corrected against 10,000 permutations).  We again tested the accuracy of local diffusion properties (FA) of the right SLF extracted from the mask of voxels passing threshold in the New Haven data (Fig.S9A) in classifying the Mannheim and the Chicago patients, respectively, into persistent and recovered. FA values corrected for age, gender, and head displacement accurately classified SBPr  and SBPp patients from the Mannheim data set with an AUC = 0.67 (p = 0.023, tested against 10,000 random permutations, Fig. S9B and S7D), and patients from the Chicago data set with an AUC = 0.69 (p = 0.0068) (Fig. S9C and S7E) at baseline, and an AUC = 0.67 (p = 0.0098)  (Fig. S9D and S7F) patients at follow-up,  confirming the predictive cluster from the right SLF across sites. The application of neuroCombat significantly changes the FA values as shown in Fig.S10 but does not change the results between groups.”

      Minor comments

      (1) In the case of New Haven data, one used MB 4 and GRAPPA 2, these two factors accelerate the imaging 8 times and often lead to quite a poor quality.<br /> Any kind of QA?

      We thank the reviewer for identifying this error. GRAPPA 2 was in fact used for our T1-MPRAGE image acquisition but not during the diffusion data acquisition. The diffusion data were acquired with a multi-band acceleration factor of 4.  We have now corrected this mistake.

      (2) Why not include MPRAGE data into the analysis, in particular, for predictions?

      We thank the reviewer for the suggestion. The collaboration on this paper was set around diffusion data. In addition, MPRAGE data from New Haven related to prediction is already published (10.1073/pnas.1918682117) and MPRAGE data of the Mannheim data set is a part of the larger project and will be published elsewhere.

      (3) In preprocessing, the authors wrote: "Eddy current corrects for image distortions due to susceptibility-induced distortions and eddy currents in the gradient coil"<br /> However, they did not mention that they acquired phase-opposite b0 data. It means eddy_openmp works likely only as an alignment tool, but not susceptibility corrector.

      We kindly thank the reviewer for bringing this to our attention. We indeed did not collect b0 data in the phase-opposite direction, however, eddy_openmp can still be used to correct for eddy current distortions and perform motion correction, but the absence of phase-opposite b0 data may limit its ability to fully address susceptibility artifacts. This is now noted in the Supplementary Methods under Preprocessing section (SI, page 3, lines 16-18): “We do note, however, that as we did not acquire data in the phase-opposite direction, the susceptibility-induced distortions may not be fully corrected.”

      (4) Version of FSL?

      We thank the reviewer for addressing this point that we have now added under the Supplementary Methods (SI, page 3, lines 10-11): “Preprocessing of all data sets was performed employing the same procedures and the FMRIB diffusion toolbox (FDT) running on FSL version 6.0.”

      (5) Some short sketches about the connectivity analysis could be useful, at least in SI.

      We are grateful for this suggestion that improves our work. We added the sketches about the connectivity analysis, please see Figure 7 and Supplementary Figure 11.

      (6) Machine learning: functions, language, version?

      We thank the reviewer for pointing out these minor points that we now hope to have addressed in our resubmission in the Methods section by adding a detailed description of the structural connectivity analysis. We added: “The DKA parcellation comprises 68 cortical surface regions (34 nodes per hemisphere) and 19 subcortical regions. The complete list of ROIs is provided in the supplementary materials’ Table S7.  PSC leverages a reproducible probabilistic tractography algorithm 26 to create whole-brain tractography data, integrating anatomical details from high-resolution T1 images to minimize bias in the tractography. We utilized DKA 25 to define the ROIs corresponding to the nodes in the structural connectome. For each pair of ROIs, we extracted the streamlines connecting them by following these steps: 1) dilating each gray matter ROI to include a small portion of white matter regions, 2) segmenting streamlines connecting multiple ROIs to extract the correct and complete pathway, and 3) removing apparent outlier streamlines. Due to its widespread use in brain imaging studies27, 28, we examined the mean fractional anisotropy (FA) value along streamlines and the count of streamlines in this work. The output we used includes fiber count, fiber length, and fiber volume shared between the ROIs in addition to measures of fractional anisotropy and mean diffusivity.”

      The script is described and provided at: https://github.com/MISICMINA/DTI-Study-Resilience-to-CBP.git.

      (7) Ethical approval?

      The New Haven data is part of a study that was approved by the Yale University Institutional Review Board. This is mentioned under the description of the data “New Haven (Discovery) data set (page 23, lines 1,2).  Likewise, the Mannheim data is part of a study approved by Ethics Committee of the Medical Faculty of Mannheim, Heidelberg University, and was conducted in accordance with the declaration of Helsinki in its most recent form. This is also mentioned under “Mannheim data set” (page 26, lines 2-5): “The study was approved by the Ethics Committee of the Medical Faculty of Mannheim, Heidelberg University, and was conducted in accordance with the declaration of Helsinki in its most recent form.”

      (1) Traeger AC, Henschke N, Hubscher M, et al. Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain. PLoS Med 2016;13:e1002019.

      (2) Hill JC, Dunn KM, Lewis M, et al. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum 2008;59:632-641.

      (3) Hockings RL, McAuley JH, Maher CG. A systematic review of the predictive ability of the Orebro Musculoskeletal Pain Questionnaire. Spine (Phila Pa 1976) 2008;33:E494-500.

      (4) Chou R, Shekelle P. Will this patient develop persistent disabling low back pain? JAMA 2010;303:1295-1302.

      (5) Silva FG, Costa LO, Hancock MJ, Palomo GA, Costa LC, da Silva T. No prognostic model for people with recent-onset low back pain has yet been demonstrated to be suitable for use in clinical practice: a systematic review. J Physiother 2022;68:99-109.

      (6) Kent PM, Keating JL. Can we predict poor recovery from recent-onset nonspecific low back pain? A systematic review. Man Ther 2008;13:12-28.

      (7) Hruschak V, Cochran G. Psychosocial predictors in the transition from acute to chronic pain: a systematic review. Psychol Health Med 2018;23:1151-1167.

      (8) Hartvigsen J, Hancock MJ, Kongsted A, et al. What low back pain is and why we need to pay attention. Lancet 2018;391:2356-2367.

      (9) Tanguay-Sabourin C, Fillingim M, Guglietti GV, et al. A prognostic risk score for development and spread of chronic pain. Nat Med 2023;29:1821-1831.

      (10) Spisak T, Bingel U, Wager TD. Multivariate BWAS can be replicable with moderate sample sizes. Nature 2023;615:E4-E7.

      (11) Liu Y, Zhang HH, Wu Y. Hard or Soft Classification? Large-margin Unified Machines. J Am Stat Assoc 2011;106:166-177.

      (12) Loffler M, Levine SM, Usai K, et al. Corticostriatal circuits in the transition to chronic back pain: The predictive role of reward learning. Cell Rep Med 2022;3:100677.

      (13) Smith SM, Dworkin RH, Turk DC, et al. Interpretation of chronic pain clinical trial outcomes: IMMPACT recommended considerations. Pain 2020;161:2446-2461.

      (14) Lieberman G, Shpaner M, Watts R, et al. White Matter Involvement in Chronic Musculoskeletal Pain. The Journal of Pain 2014;15:1110-1119.

      (15) Mansour AR, Baliki MN, Huang L, et al. Brain white matter structural properties predict transition to chronic pain. Pain 2013;154:2160-2168.

      (16) Wager TD, Atlas LY, Lindquist MA, Roy M, Woo CW, Kross E. An fMRI-based neurologic signature of physical pain. N Engl J Med 2013;368:1388-1397.

      (17) Lee JJ, Kim HJ, Ceko M, et al. A neuroimaging biomarker for sustained experimental and clinical pain. Nat Med 2021;27:174-182.

      (18) Becker S, Navratilova E, Nees F, Van Damme S. Emotional and Motivational Pain Processing: Current State of Knowledge and Perspectives in Translational Research. Pain Res Manag 2018;2018:5457870.

      (19) Spisak T, Kincses B, Schlitt F, et al. Pain-free resting-state functional brain connectivity predicts individual pain sensitivity. Nat Commun 2020;11:187.

      (20) Baliki MN, Apkarian AV. Nociception, Pain, Negative Moods, and Behavior Selection. Neuron 2015;87:474-491.

      (21) Elman I, Borsook D. Common Brain Mechanisms of Chronic Pain and Addiction. Neuron 2016;89:11-36.

      (22) Baliki MN, Petre B, Torbey S, et al. Corticostriatal functional connectivity predicts transition to chronic back pain. Nat Neurosci 2012;15:1117-1119.

      (23) Jenkins LC, Chang WJ, Buscemi V, et al. Do sensorimotor cortex activity, an individual's capacity for neuroplasticity, and psychological features during an episode of acute low back pain predict outcome at 6 months: a protocol for an Australian, multisite prospective, longitudinal cohort study. BMJ Open 2019;9:e029027.

      (24) Zhang Z, Descoteaux M, Zhang J, et al. Mapping population-based structural connectomes. Neuroimage 2018;172:130-145.

      (25) Desikan RS, Segonne F, Fischl B, et al. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968-980.

      (26) Maier-Hein KH, Neher PF, Houde J-C, et al. The challenge of mapping the human connectome based on diffusion tractography. Nature Communications 2017;8:1349.

      (27) Chiang MC, McMahon KL, de Zubicaray GI, et al. Genetics of white matter development: a DTI study of 705 twins and their siblings aged 12 to 29. Neuroimage 2011;54:2308-2317.

      (28) Zhao B, Li T, Yang Y, et al. Common genetic variation influencing human white matter microstructure. Science 2021;372.

      (29) Fortin JP, Parker D, Tunc B, et al. Harmonization of multi-site diffusion tensor imaging data. Neuroimage 2017;161:149-170.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Using a knock-out mutant strain, the authors tried to decipher the role of the last gene in the mycofactocin operon, mftG. They found that MftG was essential for growth in the presence of ethanol as the sole carbon source, but not for the metabolism of ethanol, evidenced by the equal production of acetaldehyde in the mutant and wild type strains when grown with ethanol (Fig 3). The phenotypic characterization of ΔmftG cells revealed a growth-arrest phenotype in ethanol, reminiscent of starvation conditions (Fig 4). Investigation of cofactor metabolism revealed that MftG was not required to maintain redox balance via NADH/NAD+, but was important for energy production (ATP) in ethanol. Since mycobacteria cannot grow via substrate-level phosphorylation alone, this pointed to a role of MftG in respiration during ethanol metabolism. The accumulation of reduced mycofactocin points to impaired cofactor cycling in the absence of MftG, which would impact the availability of reducing equivalents to feed into the electron transport chain for respiration (Fig 5). This was confirmed when looking at oxygen consumption in membrane preparations from the mutant and would type strains with reduced mycofactocin electron donors (Fig 7). The transcriptional analysis supported the starvation phenotype, as well as perturbations in energy metabolism, and may be beneficial if described prior to respiratory activity data.

      We thank the reviewer for their thorough evaluation of our work. We carefully considered whether transcriptional data should be presented before the respirometry data. However, this would disrupt other transitions and the flow of thoughts between sections, so that we prefer to keep the order of sections as is.

      While the data and conclusions do support the role of MftG in ethanol metabolism, the title of the publication may be misleading as the mutant was able to grow in the presence of other alcohols (Supp Fig S2).

      We agree that ethanol metabolism was the focus of this work and that phenotypes connected to other alcohols were less striking. We, therefore, changed “alcohol” to “ethanol” in the title of the manuscript.

      Furthermore, the authors propose that MftG could not be involved in acetate assimilation based on the detection of acetate in the supernatant and the ability to grow in the presence of acetate. The minimal amount of acetate detected in the supernatant but a comparative amount of acetaldehyde could point to disruption of an aldehyde dehydrogenase.

      We do not agree that MftG might be involved in acetaldehyde oxidation. According to our hypothesis, the disruption of an acetaldehyde dehydrogenase would lead to the accumulation of acetaldehyde. However, we observed an equal amount of acetaldehyde in cultures of M. smegmatis WT and ∆mftG grown on ethanol as well as on ethanol + glucose. Furthermore, the amount of acetate detected in the supernatants is not “minimal” as the reviewer points out but higher as or comparable to the acetaldehyde concentration (Figure 3 E and F, note that acetate concentration are indicated in g/L, acetaldehyde concentrations in µM). Furthermore, the accumulation of mycofactocinols in ∆mftG mutants grown on ethanol is not in agreement with the idea of MftG being an aldehyde dehydrogenase but very well supports our hypothesis that MftG is involved in cofactor reoxidation.

      The link between mycofactocin oxidation and respiration is shown, however the mutant has an intact respiratory chain in the presence of ethanol (oxygen consumption with NADH and succinate in Fig 7C) and the NADH/NAD+ ratios are comparable to growth in glucose. Could the lack of growth of the mutant in ethanol be linked to factors other than respiration?

      Indeed, by using NADH and succinate as electron donors we show that the respiratory chain is largely intact in WT and ∆mftG grown on ethanol. Also, when mycofactocinols were used as an electron donor, we observed that respiration was comparable to succinate respiration in the WT. However, respiration was severely hampered in membranes of ∆mftG when mycofactocinols were offered as reducing agent. These findings support our hypothesis very well that MftG is necessary to shuttle electrons from mycofactocin to the respiratory chain, while the rest of the respiratory chain stayed intact. The fact that NADH/NAD+ ratios are comparable between ethanol and glucose conditions are interesting but indirectly support our hypothesis that mycofactocin and not NAD is the major cofactor in ethanol metabolism. Therefore, we do not see any evidence that the lack of growth of the mutant in ethanol is linked to factors other than respiration.

      To this end, bioinformatic investigation or other evidence to identify the membrane-bound respiratory partner would strengthen the conclusions.

      We generally agree that it is an important next step to identify the direct interaction partners of MftG. However, we are convinced that experimental evidence using several orthogonal approaches is required to unequivocally identify interaction partners of MftG. Nevertheless, we agree that a preliminary bioinformatics study, could guide follow-up studies. We therefore attempted to predict interaction partners of MftG using D-SCRIPT and Alphafold 2. However, our approach did not reveal any meaningful results. Thus, we prefer not to integrate this approach into the manuscript but briefly summarize our methodology here: To predict potential interaction partners of M. smegmatis mc2 155 MftG (MSMEG_1428), D-SCRIPT (Sledzieski et al. 2021, https://doi.org/10.1016/j.cels.2021.08.010) with the Topsy-Turvy model version 1 (Singh et al. 2022, https://doi.org/10.1093/bioinformatics/btac258) was employed to screen every combination of the MSMEG_1428 amino acid sequence with the amino acid sequence of every potential interaction partner from the M. smegmatis mc2 155 predicted total proteome (total 6602 combinations, UniProt UP000000757,  Genome Accession CP000480). Predictions failed for eight potential interaction partners due to size constraints (MSMEG_0019, MSMEG_0400, MSMEG_0402, MSMEG_0408, MSMEG_1252, MSMEG_3715, MSMEG_4727, MSMEG_4757; all amino acids sequences ≥ 2000 AA). Afterward, the top 100 predicted interaction partners, ranked by D-SCRIPT protein-protein-interaction score, were subjected to an Alphafold 2 multimer prediction using ColabFold batch version 1.5.5 (AlphaFold 2 with MMseqs2, Mirdita et al. 2022, https://doi.org/10.1038/s41592-022-01488-1) on a Google Colab T4 GPU with a Python 3 environment and the following parameters (msa_mode: MMseqs2 (UniRef+Environmental), num_models = 1, num_recycles = 3, stop_at_score = 100, num_relax = 0, relax_max_iterations = 200, use_templates = False). As input, the MSMEG_1428 amino acid sequence was used as protein 1 and the amino acid sequence of the potential interaction partner was used as protein 2. In addition, proteins of the electron transport chain and the dormancy regulon (dos regulon) were included as potential interaction partners. In total, 222 unique potential MftG interactions were predicted. The AlphaFold 2 model interface predicted template modelling (ipTM) score peaked at 0.45 for MftG-MftA. This score, however, lies below the threshold of 0.75, which indicates a likely false prediction of interaction (Yin et al. 2022, https://doi.org/10.1002/pro.4379). Nonetheless, the models with the highest ipTM scores (MftG with MftA, MSMEG_3233, MSMEG_4260, MSMEG_0419, MSMEG_5139, MSMEG_5140) were inspected manually using ChimeraX version 1.8 (Meng et al. 2023, https://doi.org/10.1002/pro.4792). However, no reasonable interaction was found.

      Reviewer #2 (Public Review):

      Summary

      Patrícia Graça et al., examined the role of the putative oxidoreductase MftG in regeneration of redox cofactors from the mycofactocin family in Mycolicibacerium smegmatis. The authors show that the mftG is often co-encoded with genes from the mycofactocin synthesis pathway in M. smegmatis genomes. Using a mftG deletion mutant, the authors show that mftG is critical for growth when ethanol is the only available carbon source, and this phenotype can be complemented in trans. The authors demonstrate the ethanol associated growth defect is not due to ethanol induced cell death, but is likely a result of carbon starvation, which was supported by multiple lines of evidence (imaging, transcriptomics, ATP/ADP measurement and respirometry using whole cells and cell membranes). The authors next used LC-MS to show that the mftG deletion mutant has much lower oxidised mycofactocin (MFFT-8 vs MMFT-8H2) compared to WT, suggesting an impaired ability to regenerate myofactocin redox cofactors during ethanol metabolism. These striking results were further supported by mycofactocin oxidation assays after over-expression of MftG in the native host, but also with recombinantly produced partially purified MftG from E. coli. The results showed that MftG is able to partially oxidise mycofactocin species, finally respirometry measurements with M. smegmatis membrane preparations from WT and mftG mutant cells show that the activity of MftG is indispensable for coupling of mycofactocin electron transfer to the respiratory chain. Overall, I find this study to be comprehensive and the conclusions of the paper are well supported by multiple complementary lines of evidence that are clearly presented.

      Strengths

      The major strengths of the paper are that it is clearly written and presented and contains multiple, complementary lines of experimental evidence that support the hypothesis that MftG is involved in the regeneration of mycofactocin cofactors, and assists with coupling of electrons derived from ethanol metabolism to the aerobic respiratory chain. The data appear to support the authors hypotheses.

      We thank the reviewer for their thorough evaluation of our work.

      Weaknesses

      No major weaknesses were identified, only minor weaknesses mostly surrounding presentation of data in some figures.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) In Fig 6 C and D, would it not be expected that MMFT-2H2 would be decreasing over time as MMFT-2 is increasing?

      This is true. MMFT-2H2 is indeed decreasing while MMFT-2 in increasing, however, since the y-axis is drawn in logarithmic scale the visible difference is not proportional to the actual changes. The increase of MMFT-2 against a very low starting point is more clearly visible than the decrease of MMFT-2H2, which was added in high quantities.

      (2) It would be beneficial to include rationale regarding the electron acceptors tested and why FAD was not included.

      FAD is a prosthetic group of the enzyme and was always a component of the assay. The other electron acceptors were chosen as potential external electron acceptors.

      (3) Bioinformatic analysis to capture possible interacting partners of MftG

      See our response to the previous review.

      Reviewer #2 (Recommendations For The Authors):

      Questions:

      (1) The co-occurrence analysis showed that one genome encoded mftG, but not mftC - do the authors think that this is a mftG mis-annotation?

      This is a good question. We have investigated this case more closely and conclude that this particular mftG is not a misannotation. Instead, it appears that the mftC gene underwent gene loss in this organism. We added on page 8, line 15: “Only one genome (Herbiconiux sp. L3-i23) encoding a bona fide MftG did not harbor any MftC homolog. However, close inspection revealed the presence of mftD, mftF, and a potential mftA gene but a loss of mftB,C and E in this organism.”

      (2) Figure 3A - the complemented mutant strain shows enhanced growth on ethanol when compared to the WT strain with the same mftG complementation vector, suggesting that dysregulation from the expression plasmid may not be responsible for this phenotype. Have the authors conducted whole genome sequencing on the mutant/complement isolate to rule out secondary mutations?

      This is an interesting point. We have not conducted further investigations into the complement mutant. However, we can confidently state that the complementation was successful in that it restored growth of the ∆mftG mutant on ethanol, thus confirming that the growth arrest of the mutant was due to the lack of mftG activity and not due to any secondary mutation. We also observed that both the complement strain and the overexpression strain, both of which are based on the same overexpression plasmid, exhibited shorter lag phases, faster growth and higher final cell densities compared to the wild type. We interpret these data in a way that overexpression of mftG might lift a growth limited step. Notably, this is only an interpretation, we do not make this claim. What we cannot explain at the moment, is the observation that the complement mutant grew to a higher OD than the overexpression strain. This is indeed interesting, and it might be due to an artefact or due to complex regulatory effects, which are hard to study without an in-depth characterization of the different strains involved. While this goes beyond the scope of this study, we are convinced that our main conclusions are not challenged by this phenomenon.

      (3) Figure 4C - could the yellow fluorescence that suggests growth arrest be quantified in these images similar to the size and septa/replication sites?

      In principle, this is a good suggestion. However, the amount of yellow fluorescence only differed in the starvation condition between genotypes. Since this condition was not a focus of this study, we preferred not to discuss these differences further.

      (4) Figure 4E - the complemented mutant strain has very high error, why is that? Could this phenotype not be complemented?

      It is true that the standard deviation (SD) is relatively high in this experiment. This is due to the fact that single-cell analyses based on microscopic images were conducted here - not bulk measurements of the average fluorescence. This means that the high variance partially reflects phenotypic heterogeneity of the population, rather than inefficient complementation. While it is interesting that not all cells behaved equally, a finding that deserves further investigations in the future, we conclude that the mean value is a good representative for the efficiency of the complementation.

      (5) While the whole cell extract experiment presented in Figure 6A is very clear, could the authors include SDS page or MS results of their partially purified MftG preparations used for figure B-F in the supplementary data to rule out any confounding factors that may be oxidising mycofactocin species in these preparations?

      We did not include SDS-Page or MS results since the enzyme preparations obtained were not pure. This is why we refer to the preparation as “partially purified fraction”. Since we were aware of the risk of confounding factors being potentially present in the preparation, we used two different expression hosts (M. smegmatismftG and E. coli) and included negative controls, i.e., a reaction using protein preparations from the same host that underwent the exact same purification steps but lacked the mftG gene. For instance, Figure 6A shows the negative control (M. smegmatismftG) and the verum (M. smegmatismftG-mftG_His6). Although this control is not shown in panels BCD for more clarity, we can assure that the proposed activity of MftG as never been detected in any extract of _M. smegmatismftG. Concerning MftG preparations obtained from heterologous expression in E. coli, we also performed empty vector controls and inactivated protein controls. We added a new Supplementary Figure S4 to show one example control. Taken together, the usage of two different expression hosts along with corresponding background controls clearly demonstrates that mycofactocinol oxidation only occurred in protein extracts of bacterial strains that contained the mftG gene. Taken together, these data indicate that the observed mycofactocinol dehydrogenase activity is connected to MftG and not to any background activity.

      Recommendations:

      • A suggestion - revise sub-titles in the results section to be more 'results-oriented' e.g. rather than 'the role of MftG in growth and metabolism of mycobacteria' consider instead 'MftG is critical for M. smegmatis capacity to utilise ethanol as a sole carbon source for growth' or something similar.

      In principle this is a good idea for many manuscripts. However, we have the impression that this approach does not reflect the complexity and additive aspect of the sections of our manuscript.

      • For clarity, revise all figures to include p-values in the figure legend rather than above the figures (use asterisks to indicate significance).

      We are not sure whether the deletion of p-values in the figures would enhance clarity. We would prefer to leave them within figures.

      • Figure 5B -revise colour legend, it is unclear which bar on the graph corresponds to which strain.

      The figure legend was enlarged to enhance readability.

      • Page 8 - MftG and MftC should be lowercase and italicised as the authors are writing about the co-occurrence of genes encoded in genomes, not proteins.

      Good point, we changed some instances of MftG / MftC to mftG / mftC, to more specifically refer to the gene level. However, in some cases, the protein level is more appropriate, for instance, the phylogenies are based on protein sequences. That is why we used the spelling MftG / MftC in these cases.

      • Page 9 - for clarity move Figure 3 after first in text citation.

      We moved Figure 3.

      • Page 17 - for clarity move Figure 5 after first in text citation.

      We moved Figure 5. We furthermore reformatted figure legend to fit onto the same page as the figures.

      • Page 20, line 17 - 'was attempted' change to 'was performed'. The authors did more than attempt purification, they succeeded!

      Since purification of MftG was not successful, we prefer the term “attempted” here. However, activity assays indeed indicate successful production of MftG.

      • Page 20, line 19-21 - data showing that the MftG-HIS6 complements ∆mftG could be included in supplementary information.

      Complementation was obvious by growth on media containing ethanol as a sole carbon source.

      • Page 26 line 25 - 'we also we' delete duplicated we.

      Thank you for the hint, we deleted the second instance of “we” in the manuscript.

      • Page 26 Line 26 - 'mycofactocinols were oxidised to mycofactocinols', should this read mycofactocinols were oxidised to mycofactocinones?

      Correct. We changed “mycofactocinols” to “mycofactocinones”

      • Page 28 line 17, huc hydrogenase operon

      We added (“huc operon”).

      • Page 38 line 24, 'Two' not 'to'.

      This is a misunderstanding. “To” is correct

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1:

      In this manuscript, Zhou et al describe a deaminase and reader protein-assisted RNA m5C sequencing method. The general strategy is similar to DART-seq for m6A sequencing, but the difference is that in DART-seq, m6A sites are always followed by C which can be deaminated by fused APOBEC1 to provide a high resolution of m6A sites, while in the case of m5C, no such obvious conserved motifs for m5C sites exist, therefore, the detection resolution is much lower. In addition, the authors used two known m5C binding proteins ALYREF and YBX1 to guide the fused deaminases, but it is not clear whether these two binding proteins can bind most m5C sites and compete with other m5C binding proteins.

      Thank you for your kind suggestion. RNA affinity chromatography and mass spectrometry analyses using biotin-labelled oligonucleotides with or without m5C were performed in previous reports (doi:10.1038/cr.2017.55 and doi: 10.1038/s41556-019-0361-y), and the results showed that ALYREF and YBX1 had a more prominent binding ability to m5C -modified oligonucleotides. Moreover, these two m5C -binding proteins are also responsible for mRNA m5C binding, so we chose to use their ability to bind targeted m5C to construct a DRAM detection system in anticipation of transcriptome-wide m5C detection. We hope to propose a suitable detection strategy for RNA m5C, and there will certainly be room for optimization of the DRAM system in the future with more in-depth studies of m5C binding proteins. We have discussed the above issue in lines 75-82 and 315-318.

      It is well known that two highly modified m5C sites exist in 28S RNA and many m5C sites exist in tRNA, the authors should validate their methods first by detecting these known m5C sites and evaluate the possible false positives in rRNA and tRNA.

      Thank you for your kind suggestion. We attempted PCR amplification of sequences flanking m5C sites 3782 and 4447 on 28S rRNA, as well as multiple m5C sites on tRNA, including m5C48 and m5C49 on tRNAVal, m5C48 and m5C49 on tRNAAsp, and m5C48 on tRNALys.

      However, Sanger sequencing revealed no valid mutations, which was implemented in Figure S3. We believe this outcome indicates that the DRAM system is more suited for transcriptome-wide m5C detection of mRNAs. This is supported by current reports that ALYREF and YBX1 are responsible for the m5C-binding proteins of mRNAs (doi:10.1038/cr.2017.55 and doi: 10.1038/s41556-019-0361-y). The above results and descriptions were added to lines 136-143.

      In mRNA, it is not clear what is the overlap between the technical replicates. In Figures 4A and 4C, they detected more than 10K m5C sites, and most of them did not overlap with sites uncovered by other methods. These numbers are much larger than expected and possibly most of them are false positives.

      Thank you for your kind suggestion. We observed significant overlap between the technical repeats by comparing the data across biological repeats, as shown in Figure S4C and described in lines 174-175. We considered m5C modification in a region only when editing events were detected in at least two biological replicates, ensuring a high-stringency screening process (details seen in the revised method in lines 448-455 and Figure 3F). With more in-depth research into m5C readers, we aim to achieve more accurate detection in the future.

      Besides, it is not clear what is the detection sensitivity and accuracy since the method is neither single base resolution nor quantitative.

      Thank you for your suggestion. As shown in Figure 3G, we found that the editing window of the DRAM system exhibited enrichment of approximately 20 bp upstream and downstream of the m5C site. Previous reports identified Type I m5C sites, which tend to have a downstream "NGGG" motif, and Type II m5C sites, which often contain a downstream "UCCA" motif. However, these m5C motifs do not fully characterize all m5C sites, and their presence downstream of an m5C site is not guaranteed (doi: 10.1038/s41594-019-0218-x). This limitation complicates single-base resolution analysis by the DRAM system. Nevertheless, we believe that with further exploration of m5C sequence features, precise single-base resolution detection can be achieved in the future. This point is also discussed in lines 314-322.

      Regarding the quantitative level of the assay, we conducted additional experiments by progressively reducing the expression levels of the fusion proteins. Sanger sequencing revealed that the editing efficiency of A-to-G and C-to-U within the m5C region significantly decreased as fusion protein expression diminished (Figure S9). These findings suggest that the DRAM system's transfection efficiency is concentration-dependent and that the ratio of editing efficiency to transfection efficiency could aid in the quantitative analysis of m5C using the DRAM system. The relative results were supplemented in Figure S9 and discussed in lines 263-271.

      There are no experiments to show that the detected m5C sites are responsive to the writer proteins such as NSUN2 and NSUN6, and the determination of the motifs of these writer proteins.

      Thank you for your kind suggestion. We have performed a motif enrichment analysis based on the sequences spanning 10 nt upstream and downstream of DRAM-editing sites. The relative results of this analysis were supplemented in Figure S4D and lines 168-171. Unfortunately, we did not identify any clear sequence preferences for the m5C sites catalyzed by the methyltransferases NSUN2 and NSUN6, which have previously been associated with “G”-rich sequences and the “CUCCA” motif. This limitation is mainly due to the DRAM detection system’s inability to achieve single-base resolution for m5C detection, which is also explained in the above response.

      Reviewer #2:

      (1) The use of two m5C reader proteins is likely a reason for the high number of edits introduced by the DRAM-Seq method. Both ALYREF and YBX1 are ubiquitous proteins with multiple roles in RNA metabolism including splicing and mRNA export. It is reasonable to assume that both ALYREF and YBX1 bind to many mRNAs that do not contain m5C.

      To substantiate the author's claim that ALYREF or YBX1 binds m5C-modified RNAs to an extent that would allow distinguishing its binding to non-modified RNAs from binding to m5C-modified RNAs, it would be recommended to provide data on the affinity of these, supposedly proven, m5C readers to non-modified versus m5C-modified RNAs. To do so, this reviewer suggests performing experiments as described in Slama et al., 2020 (doi: 10.1016/j.ymeth.2018.10.020). However, using dot blots like in so many published studies to show modification of a specific antibody or protein binding, is insufficient as an argument because no antibody, nor protein, encounters nanograms to micrograms of a specific RNA identity in a cell. This issue remains a major caveat in all studies using so-called RNA modification reader proteins as bait for detecting RNA modifications in epitranscriptomics research. It becomes a pertinent problem if used as a platform for base editing similar to the work presented in this manuscript.

      We thank the reviewer for the valuable suggestion. Previous studies have shown that while ALYREF and YBX1 can bind mRNAs without the m5C modification, their binding affinity for m5C-modified oligonucleotides is significantly higher than for unmethylated controls. This has been demonstrated through experiments such as in vitro tractography, electrophoretic mobility shift assay (EMSA) (doi:10.1038/cr.2017.55), and UHPLC-MRM-MS/MS. Additionally, isothermal titration calorimetry measurements and PAR-CLIP experiments have shown that mutations in the key amino acids responsible for m5C binding in ALYREF and YBX1 result in a significant reduction in their ability to m5C (doi: 10.1038/s41556-019-0361-y).

      Although Me-RIP analysis was unsuccessful in our laboratory, likely due to the poor specificity of the m5C antibody, we alternatively performed RNA pulldown experiments. These experiments verified that the ability of DRAMmut-expressing proteins to bind RNA with m5C modification was virtually absent compared to DRAM-expressing proteins, while their binding ability with non-modified RNA was not significantly affected. The relative RNA pulldown results were supplemented in Figure S1E, S1F and lines 110-111. Therefore, we believe that by integrating DRAMmut group, our DRAM system could effectively exclude the false-positive mutations caused by unspecific binding of DRAM’s reader protein to non-m5C-modified mRNAs.

      (2) Since the authors use a system that results in transient overexpression of base editor fusion proteins, they might introduce advantageous binding of these proteins to RNAs. It is unclear, which promotor is driving construct expression but it stands to reason that part of the data is based on artifacts caused by overexpression. Could the authors attempt testing whether manipulating expression levels of these fusion proteins results in different editing levels at the same RNA substrate?

      Thank you for pointing this out. To investigate how different expression levels of these proteins influence A-to-G and C-to-U editing within the same m5C region, we conducted a gradient transfection using plasmid concentrations of 1500 ng, 750 ng and 300 ng. This approach allowed us to progressively reduce the expression levels of the fusion proteins. Sanger sequencing revealed that the editing efficiency of A-to-G and C-to-U within the m5C region significantly decreased as fusion protein expression diminished. These findings suggest that the transfection efficiency of the DRAM system is concentration-dependent and that the ratio of editing efficiency to transfection efficiency may assist in the quantitative analysis of m5C using the DRAM system. The relative results and hypotheses were added and discussed in Figure S9 and lines 263-271 of the revised manuscript.

      (3) Using sodium arsenite treatment of cells as a means to change the m5C status of transcripts through the downregulation of the two major m5C writer proteins NSUN2 and NSUN6 is problematic and the conclusions from these experiments are not warranted. Sodium arsenite is a chemical that poisons every protein containing thiol groups. Not only do NSUN proteins contain cysteines but also the base editor fusion proteins. Arsenite will inactivate these proteins, hence the editing frequency will drop, as observed in the experiments shown in Figure 5, which the authors explain with fewer m5C sites to be detected by the fusion proteins.

      Thank you for pointing this out. We used bisulfite sequencing PCR to determine that the m5C levels in RPSA and AP5Z1 were significantly reduced after sodium arsenite treatment. This was followed by a significant decrease in editing frequency detected by the DRAM system in sodium arsenite-treated samples compared to untreated samples. This reduction aligns with the decreased editing efficiency observed in methyltransferase-deficient cells (as shown in Figures 2G and 2H), which initially convinced us that these results reflected the DRAM system's ability to monitor dynamic changes in m5C levels.

      However, as the reviewer pointed out, sodium arsenite treatment could potentially inactivate the fusion proteins, leading to the observed reduction in editing efficiency. This possibility has not been conclusively ruled out in our current experiments. Optimizing this validation may require the future development of more specific m5C inhibitors. In light of this, we have revised our previous results and conclusions in lines 235-244, and discussed these points in lines 308-315.

      (4) The authors should move high-confidence editing site data contained in Supplementary Tables 2 and 3 into one of the main Figures to substantiate what is discussed in Figure 4A. However, the data needs to be visualized in another way than an Excel format. Furthermore, Supplementary Table 2 does not contain a description of the columns, while Supplementary Table 3 contains a single row with letters and numbers.

      Thank you for your kind suggestion. We have visualized the data from Supplementary Tables 2 and 3 into Figure 3F, presenting it as a screening flowchart for high-confidence editing sites. In Supplementary Table 3, we have displayed only the DRAM-mutated genes, which is why it contains a single row with letters and numbers. As requested, we have included descriptions of each column and reorganized the Supplementary table 2 and 3 accordingly.

      (5) The authors state that "plotting the distribution of DRAM-seq editing sites in mRNA segments (5'UTR, CDS, and 3'UTR) highlighted a significant enrichment near the initiation codon (Figure 3F).", which is not true when this reviewer looks at Figure 3F.

      Thank you for your kind suggestion, and we replaced the expression of " near the initiation codon" with "in the CDS" in lines 192-193.

      (6) The authors state that "In contrast, cells expressing the deaminase exhibited a distinct distribution pattern of editing sites, characterized by a prevalence throughout the 5'UTR.", which is not true when this reviewer looks at Figure 3F.

      Thank you for your kind suggestion. This distribution was actually characterized by a prevalence throughout the "3'UTR", but not "5'UTR". We have also made the necessary changes in lines 193-195.

      (7) The authors claim in the final conclusion: "In summary, we developed a novel deaminase and reader protein assisted RNA m5C methylation approach...", which is not what the method entails. The authors deaminate As or Us close to 5mC sites based on the binding of a deaminase-containing protein.

      Thank you for your kind suggestion, and we have made the necessary changes in lines 331-334.

      (8) The authors claim that "The data supporting the findings of this study are available within the article and its Supplementary Information." However, no single accession number for the deposited sequencing data can be found in the text or the supplementary data. Without the primary data, none of the claims can be verified.

      Thank you for pointing this out. The sequencing data from this study has already been deposited to the GEO database (GEO assession number: GSE254194, GEO token:ororioukbdqtpcn), and we will ensure it is made publicly available in a timely manner.

      (a) To underscore point (1), a recent publication (https://doi.org/10.1038/s41419-023-05661-y) reported: "To further identify the potential mRNAs regulated by ALYREF, we performed RNA-seq analysis in control or ALYREF knockdown T24 cells. After knockdown of ALYREF, 143 mRNAs differentially expressed, including 94 downregulated mRNAs (NC reads >100, |Fold change | >1.5, P-value <0.05). Functional enrichment analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that regulated mRNAs by ALYREF are chiefly enriched in canonical cancer-related pathways (Fig. S4A), including TGF-β signaling, MAPK signaling, and NF-κB signaling, strongly supporting the oncogenic function of ALYREF in tumor progression. Among these 94 downregulated genes, 11 mRNA showed a significant reduction in m5C methylation after NUSN2 silencing in T24 cells, combined with previously transcriptome-wide RNA-BisSeq data of T24 cells [21] (Fig. 4A)."

      These results translate into 94 mRNAs are regulated by ALYREF in bladder cancer-derived cells. From those, very few (11) mRNA identities respond to NSUN2-dependent RNA methylation mediated by ALYREF binding.The question then arises, is that number sufficient to claim that ALYREF is a m5C-binding protein?

      And if so, how does the identification of 10.000+ edits by DRAM-Seq compare with the 94 mRNAs that are regulated by ALYREF? Were these 94 mRNAs identified by DRAM-Seq.

      Thank you for your kind suggestion. Previous reports by Yang et al. ( doi: 10.1038/cr.2017.55), including the literature you refer to, have detailed the close relationship between ALYREF and m5C modification, and the ALY/REF export factor (ALYREF) was identified as the first nuclear m5C reader, and it was demonstrated that many mRNAs are regulated by ALYREF, and is therefore considered to be an m5C-binding protein.

      As required, by comparing the DRAM-edited mRNAs with the reported 94 mRNAs, we found that only 55.32% of the 94 mRNAs regulated by ALYREF could be detected by the DRAM system. This indicates that the DRAM system specifically targets certain mRNAs, as illustrated in Figure S4E. The relevant results were described and discussed in lines 175-179.

      (b) Line 123:

      "The deep sequencing results showed that the deamination rates of RPSA and SZRD1 were 75.5% and 27.25%, respectively. (Fig. 2A, B)."

      The Figure shows exactly the opposite of bisulfite-mediated deamination. These are the cytosines that were not deaminated by the chemical treatment and therefore can be sequenced as cytosines and not thymidines. Hence, the term deamination rate is wrong.

      Thank you for your kind suggestion. We have made the necessary change in lines 129-130 to change the deamination rates to m⁵C fraction.

      (c) Line 157:

      "DRAM-seq analysis further confirmed that DRAM was detected in an m5C-dependent manner, with minimal mutations in AP5Z1 and RPSA mRNAs in methyltransferase knockout cells compared to wild-type cells (Fig. 3C, D)."

      There is no indication of what the authors mean by minimal mutation in these Figures. The term "minimal mutation" should be reconsidered as well.

      Thank you for your kind suggestion. We intended to express that "Mutations in AP5Z1 and RPSA mRNA are reduced in methyltransferase-deficient cells." There was an issue with the initial formulation, and we have made the necessary changes in lines 165-167.

      (d) Line 167:

      "To further delineate the characteristics of the DRAM-seq data, we compared the distribution of DRAM-seq editing sites within the gene structure, specifically examining their occurrences in the 5'untranslated region (5'UTR), 3' untranslated region (3'UTR), CDS and ncRNA."

      Which part of a coding RNA is meant by "ncRNA"?

      Thank you for pointing this out. This was actually the Intergenic or Intron region, but not ncRNA. We have also corrected this labelling in Figure 3G and lines 186-189 of the revised manuscript.

      (e) Line 189:

      "Subsequently, we assessed the capacity of DRAM-seq to detect m5C on a transcriptome-wide scale, comparing its performance to BS-seq that have been previously reported with great authority."

      The term "great authority" is not a scientific term. Please, remove adulation to senior authors.

      Thank you for your kind suggestion. We removed this unsuitable expression and made the necessary changes in lines 207-208.

      (f) Line 233:

      "Several experiments have highlighted the requirement of 100-500 ng of RNA for m5C-RIP-seq, while BS-seq necessitates an even more demanding 500-750 μg of RNA21,25,61."

      This reviewer doubts that RNA bisulfite sequencing required half to one mg of RNA input. Please, check these references.

      Thank you for your kind suggestion. According to the references, we corrected μg to ng and made the necessary changes in lines 251-252.

      (g) Line 247:

      "Several experiments have highlighted the requirement of 100-500 ng of RNA for m5C-RIP-seq, while BS-seq necessitates an even more demanding 500-750 μg of RNA21,25,61."

      This reviewer doubts that RNA bisulfite sequencing requires half to one mg of RNA input. Please, check these references.

      Thank you for your kind suggestion. According to the references, we corrected μg to ng and made the necessary changes in lines 251-252.

      (h) Line 292:

      "Since m5C lacks a fixed motif, DRAM has an apparent limitation in achieving single-base resolution for detecting m5C."

      m5C deposition by NSUN2 and NSUN6 occurs in particular motifs that were coined Type I and II motifs. Hence, this statement is not correct.

      Thank you for your kind suggestion. Previous reports identified Type I m5C sites, which tend to have a downstream "NGGG" motif, and Type II m5C sites, which often contain a downstream "UCCA" motif. However, these m5C motifs do not fully characterize all m5C sites, and their presence downstream of an m5C site is not guaranteed (doi: 10.1038/s41594-019-0218-x ). Therefore, we have corrected the expression “fixed motif” to “fixed base composition for characterizing all m5C modification sites” in lines 317.

      (i) Line 390:

      "1 μl of total cellular RNA was used for sequencing library gene..."

      1 uL does not allow us to deduce which RNA mass was used for cDNA synthesis.

      Thank you for your kind suggestion. According to our cDNA synthesis protocol, we corrected “1μl” to “1μg” in lines 422-423.

      (j) Line 405:

      "...was assessed on the Agilent 5400 system (Agilent, USA) and quantified by QPCR (1.5 nM)"

      What does the 1.5 nM refer to in this sentence?

      Thank you for your kind suggestion. Here, "1.5nM" means that the concentration of the constructed library should be no less than 1.5nM. We have also revised this expression in the methods in lines 436-438.

    1. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The authors use analysis of existing data, mathematical modelling, and new experiments, to explore the relationship between protein expression noise, translation efficiency, and transcriptional bursting.

      Strengths:

      The analysis of the old data and the new data presented is interesting and mostly convincing.

      Thank you for the constructive suggestions and comments. We address the individual comments below.

      Weaknesses:

      (1) My main concern is the analysis presented in Figure 4. This is the core of mechanistic analysis that suggests ribosomal demand can explain the observed phenomenon. I am both confused by the assumptions used here and the details of the mathematical modelling used in this section. Firstly, the authors' assumption that the fluctuations of a single gene mRNA levels will significantly affect ribosome demand is puzzling. On average the total level of mRNA across all genes would stay very constant and therefore there are no big fluctuations in the ribosome demand due to the burstiness of transcription of individual genes. Secondly, the analysis uses 19 mathematical functions that are in Table S1, but there are not really enough details for me to understand how this is used, are these included in a TASEP simulation? In what way are mRNA-prev and mRNA-curr used? What is the mechanistic meaning of different terms and exponents? As the authors use this analysis to argue ribosomal demand is at play, I would like this section to be very much clarified.

      Thank you for raising two important points. Regarding the first point, we agree that the overall ribosome demand in a cell will remain more or less the same even with fluctuations in mRNA levels of a few genes. However, what we refer to in the manuscript is the demand for ribosomes for translating mRNA molecules of a single gene. This demand will vary with the changes in the number of the mRNA molecules of that gene. When the mRNA copy number of the gene is low, the number of ribosomes required for translation is low. At a subsequent timepoint when the mRNA number of the same gene goes up rapidly due to transcriptional bursting, the number of ribosomes required would also increase rapidly. The process of allocation of ribosomes for translation of these mRNA molecules will vary between cells, and this process can lead to increased expression variation of that gene among cells.

      Regarding the second point, each of the 19 mathematical functions was individually tested in the TASEP model and stochastic simulation. The parameters ‘mRNA-curr’ and ‘mRNA-prev’ are the mRNA copy numbers at the current time point and the previous time point in the stochastic simulation, respectively. These numbers were calculated from the rate of production of mRNA, which is influenced by the burst frequency and the burst size, as well as the rate of mRNA removal. We would expand this section with explanation for all parameters and terms in the revised manuscript.

      (2) Overall, the paper is very long and as there are analytical expressions for protein noise (e.g. see Paulsson Nature 2004), some of these results do not need to rely on Gillespie simulations. Protein CV (noise) can be written as three terms representing protein noise contribution, mRNA expression contribution, and bursty transcription contribution. For example, the results in panel 1 are fully consistent with the parameter regime, protein noise is negligible compared to transcriptional noise.

      Thank you for referring to the paper on analytical expressions for protein noise. We introduced translational bursting and ribosome demand in our model, and these are linked to stochastic fluctuations in mRNA and ribosome numbers. In addition, our model couples transcriptional bursting with translational bursting and ribosome demand. Since these processes are all stochastic in nature, we felt that the stochastic simulation would be able to better capture the fluctuations in mRNA and protein expression levels originating from these processes. For consistency, we used stochastic simulations throughout even when the coupling between transcription and translation were not considered.

      Reviewer #2 (Public review):

      This work by Pal et al. studied the relationship between protein expression noise and translational efficiency. They proposed a model based on ribosome demand to explain the positive correlation between them, which is new as far as I realize. Nevertheless, I found the evidence of the main idea that it is the ribosome demand generating this correlation is weak. Below are my major and minor comments.

      Thank you for your helpful suggestions and comments. We note that the direct experimental support required for the ribosome demand model would need experimental setups that are beyond the currently available methodologies. We address the individual comments below.

      Major comments:

      (1) Besides a hypothetical numerical model, I did not find any direct experimental evidence supporting the ribosome demand model. Therefore, I think the main conclusions of this work are a bit overstated.

      Direct experimental evidence of the hypothesis would require generation of ribosome occupancy maps of mRNA molecules at the level of single cells and at time intervals that closely match the burst frequency of the genes. This is beyond the currently available methodologies. However, there are other evidences that support our model. For example, earlier work in cell-free systems have showed that constraining cellular resources required for transcription or translation can increase expression heterogeneity (Caveney et al., 2017). In addition, genome-wide analysis of expression noise in yeast also revealed that the association between protein noise and translational efficiency was highest in the group of genes with the most bursty transcription (Supplementary fig. S20).

      (2) I found that the enhancement of protein noise due to high translational efficiency is quite mild, as shown in Figure 6A-B, which makes the biological significance of this effect unclear.

      Although we agree with the reviewer’s comment that the effect of translational efficiency on protein noise may not be as substantial as the effect of transcriptional bursting, it has been observed in studies across bacteria, yeast and Arabidopsis (Ozbudak et al., 2003; Blake et al., 2003; Wu et al., 2022). In addition, the relationship between translational efficiency and protein noise is in contrast with the inverse relationship observed between mean expression and noise (Newman et al., 2006; Silander et al., 2012). We also note that the goal of the manuscript was not to evaluate the strength of the association, but to understand the basis of the influence of translational efficiency on protein noise.

      (3) The captions for most of the figures are short and do not provide much explanation, making the figures difficult to read.

      We will revise the figure captions to include more details as per the reviewer’s suggestion.

      (4) It would be helpful if the authors could define the meanings of noise (e.g., coefficient of variation?) and translational efficiency in the very beginning to avoid any confusion. It is also unclear to me whether the noise from the experimental data is defined according to protein numbers or concentrations, which is presumably important since budding yeasts are growing cells.

      For all published datasets where we had measurements from a large number of genes/promoters, we used the measures of adjusted noise (for mRNA noise) and Distance-to-median (DM, for protein noise). For experiments that we performed on a limited number of promoters, we used the measure of coefficient of variation (CV) to quantify noise, as calculation of adjusted noise or DM was not possible. Translational efficiency refers to translation rate which is determined by both the translation initiation rate and the translation elongation rate. The noise at the protein level was quantified from the signal intensity of GFP tagged proteins, which was proportional to protein numbers without considering cell volume. For quantification of noise at the mRNA level, single-cell RNA-seq data was used, which provided mRNA numbers in individual cells.

      (5) The conclusions from Figures 1D and 1E are not new. For example, the constant protein noise as a function of mean protein expression is a known result of the two-state model of gene expression, e.g., see Equation (4) in Paulsson, Physics of Life Reviews 2005.

      Yes, they are not new, but we included these results for setting the baseline for comparison with simulation results that appear in the later part of the manuscript where we included translational bursting and ribosome demand in our models.

      (6) In Figure 4C-D, it is unclear to me how the authors changed the mean protein expression if the translation initiation rate is a function of variation in mRNA number and other random variables.

      The translation initiation rate varied from a baseline initiation rate depending on the mRNA numbers and other variables. We changed the baseline initiation rate to alter the mean protein expression levels. We will elaborate this section in the revised manuscript.

      (7) If I understand correctly, the authors somehow changed the translation initiation rate to change the mean protein expression in Figures 4C-D. However, the authors changed the protein sequences in the experimental data of Figure 6. I am not sure if the comparison between simulations and experimental data is appropriate.

      It is an important observation. Even though we changed the translation initiation rate to change the mean expression (Fig. 4C-D), we noted in the description in the model (Fig. 3D) that the changes in the translation initiation rate was also linked with changes in the translation elongation rate. The translation initiation rate can only increase if the ribosomes already bound to the mRNA traverse quicker through the mRNA. This means that an increase in the translation initiation rate will occur only if the translation elongation rate is also increased, which will lead to lower traversal time of the ribosomes through the mRNA (Fig. 3D). Similarly, an increase in the translation elongation rate will allow more ribosomes to initiate translation. Thus, the parameters translation initiation rate and translation elongation rate are interconnected. This has also been observed in an experimental study by Barrington et al. (2023). Having said that, however, the models can also be expressed in terms of the translation elongation rate, instead of the translation initiation rate, and this modification will not change the results of the simulations due to interconnectedness of the initiation rate and the elongation rate.  

      References

      C. L. Barrington, G. Galindo, A. L. Koch, E. R. Horton, E. J. Morrison, S. Tisa, T. J. Stasevich, O. S. Rissland. Synonymous codon usage regulates translation initiation. Cell Rep. 42, 113413 (2023).

      W. J. Blake, M. Kaern, C. R. Cantor, J. J. Collins, Noise in eukaryotic gene expression. Nature 422, 633-637 (2003).

      P. M. Caveney, S. E. Norred, C. W. Chin, J. B. Boreyko, B. S. Razooky, S. T. Retterer, C. P. Collier, M. L. Simpson, Resource Sharing Controls Gene Expression Bursting. ACS Synth Biol. 6, 334-343 (2017)

      J. R. Newman, S. Ghaemmaghami, J. Ihmels, D. K. Breslow, M. Noble, J. L. DeRisi, J. S. Weissman, Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature, 441, 840-846 (2006).

      E. M. Ozbudak, M. Thattai, I. Kurtser, A. D. Grossman, A. van Oudenaarden, Regulation of noise in the expression of a single gene. Nat Genet. 31, 69-73 (2002).

      O. K. Silander, N. Nikolic, A. Zaslaver, A. Bren, I. Kikoin, U. Alon, M. Ackermann, A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli. PLoS Genet. 8, e1002443 (2012).

      H. W. Wu, E. Fajiculay, J. F. Wu, C. S. Yan, C. P. Hsu, S. H. Wu, Noise reduction by upstream open reading frames. Nat Plants. 8, 474-480 (2022).

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Freas et al. investigated if the exceedingly dim polarization pattern produced by the moon can be used by animals to guide a genuine navigational task. The sun and moon have long been celestial beacons for directional information, but they can be obscured by clouds, canopy, or the horizon. However, even when hidden from view, these celestial bodies provide directional information through the polarized light patterns in the sky. While the sun's polarization pattern is famously used by many animals for compass orientation, until now it has never been shown that the extremely dim polarization pattern of the moon can be used for navigation. To test this, Freas et al. studied nocturnal bull ants, by placing a linear polarizer in the homing path on freely navigating ants 45 degrees shifted to the moon's natural polarization pattern. They recorded the homing direction of an ant before entering the polarizer, under the polarizer, and again after leaving the area covered by the polarizer. The results very clearly show, that ants walking under the linear polarizer change their homing direction by about 45 degrees in comparison to the homing direction under the natural polarization pattern and change it back after leaving the area covered by the polarizer again. These results can be repeated throughout the lunar month, showing that bull ants can use the moon's polarization pattern even under crescent moon conditions. Finally, the authors show, that the degree in which the ants change their homing direction is dependent on the length of their home vector, just as it is for the solar polarization pattern. 

      The behavioral experiments are very well designed, and the statistical analyses are appropriate for the data presented. The authors' conclusions are nicely supported by the data and clearly show that nocturnal bull ants use the dim polarization pattern of the moon for homing, in the same way many animals use the sun's polarization pattern during the day. This is the first proof of the use of the lunar polarization pattern in any animal.

      Reviewer #2 (Public Review): 

      Summary: 

      The authors aimed to understand whether polarised moonlight could be used as a directional cue for nocturnal animals homing at night, particularly at times of night when polarised light is not available from the sun. To do this, the authors used nocturnal ants, and previously established methods, to show that the walking paths of ants can be altered predictably when the angle of polarised moonlight illuminating them from above is turned by a known angle (here +/- 45 degrees).

      Strengths: 

      The behavioural data are very clear and unambiguous. The results clearly show that when the angle of downwelling polarised moonlight is turned, ants turn in the same direction. The data also clearly show that this result is maintained even for different phases (and intensities) of the moon, although during the waning cycle of the moon the ants' turn is considerably less than may be expected.

      Weaknesses: 

      The final section of the results - concerning the weighting of polarised light cues into the path integrator - lacks clarity and should be reworked and expanded in both the Methods and the Results (also possibly with an extra methods figure). I was really unsure of what these experiments were trying to show or what the meaning of the results actually are.

      Rewrote these sections and added figure panel to Figure 6.

      Impact: 

      The authors have discovered that nocturnal bull ants while homing back to their nest holes at night, are able to use the dim polarised light pattern formed around the moon for path integration. Even though similar methods have previously shown the ability of dung beetles to orient along straight trajectories for short distances using polarised moonlight, this is the first evidence of an animal that uses polarised moonlight in homing. This is quite significant, and their findings are well supported by their data.

      Reviewer #3 (Public Review): 

      Summary: 

      This manuscript presents a series of experiments aimed at investigating orientation to polarized lunar skylight in a nocturnal ant, the first report of its kind that I am aware of.

      Strengths: 

      The study was conducted carefully and is clearly explained here. 

      Weaknesses: 

      I have only a few comments and suggestions, that I hope will make the manuscript clearer and easier to understand.

      Time compensation or periodic snapshots 

      In the introduction, the authors compare their discovery with that in dung beetles, which have only been observed to use lunar skylight to hold their course, not to travel to a specific location as the ants must. It is not entirely clear from the discussion whether the authors are suggesting that the ants navigate home by using a time-compensated lunar compass, or that they update their polarization compass with reference to other cues as the pattern of lunar skylight gradually shifts over the course of the night - though in the discussion they appear to lean towards the latter without addressing the former. Any clues in this direction might help us understand how ants adapted to navigate using solar skylight polarization might adapt use to lunar skylight polarization and account for its different schedule. I would guess that the waxing and waning moon data can be interpreted to this effect.

      Added a paragraph discussing this distinction in mechanisms and the limits of the current data set in untangling them. An interesting topic for a follow up to be sure.

      Effects of moon fullness and phase on precision 

      As well as the noted effect on shift magnitudes, the distributions of exit headings and reorientations also appear to differ in their precision (i.e., mean vector length) across moon phases, with somewhat shorter vectors for smaller fractions of the moon illuminated. Although these distributions are a composite of the two distributions of angles subtracted from one another to obtain these turn angles, the precision of the resulting distribution should be proportional to the original distributions. It would be interesting to know whether these differences result from poorer overall orientation precision, or more variability in reorientation, on quarter moon and crescent moon nights, and to what extent this might be attributed to sky brightness or degree of polarization.

      See below for response to this and the next reviewer comment

      N.B. The Watson-Williams tests for difference in mean angle are also sensitive to differences in sample variance. This can be ruled out with another variety of the test, also proposed by Watson and Williams, to check for unequal variances, for which the F statistic is = (n2-1)*(n1-R1) / (n1-1)*(n2-R2) or its inverse, whichever is >1. 

      We have looked at the amount of variance from the mean heading direction in terms of both the shifts and the reorientations and found no significant difference in variance between all relevant conditions. It is possible (and probably likely) that with a higher n we might find these differences but with the current data set we cannot make statistical statements regarding degradations in navigational precision.  

      As an additional analysis to address the Watson-Williams test‘s sensitivity to changes in variance, we have added var test comparisons for each of the comparisons, which is a well-established test to compare variance changes. None of these were significantly different, suggesting the observed differences in the WW tests are due to changes in the mean vector and not the distribution. We have added this test to the text.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      I have only very few minor suggestions to improve the manuscript: 

      (1) While I fully agree with the authors that their study, to the best of my knowledge, provides the first proof (in any animal) of the use of the moon's polarization pattern, the many repetitions of this fact disturb the flow of the text and could be cut at several instances. 

      Yes, it is indeed repeated to an annoying degree. 

      We have removed these beyond bookending mentions (Abstract and Discussion).

      (2) In my opinion, the authors did not change the "ambient polarization pattern" when using the linear polarization filter (e.g., l. 55, 170, 177 ...). The linear polarizer presents an artificial polarization pattern with a much higher degree of polarization in comparison to the ambient polarization pattern. I would suggest re-phrasing this, to emphasize the artificial nature of the polarization pattern under the polarizer.

      We have made these suggested changes throughout the text to clarify. We no longer say the ambient pattern was   

      (3) Line 377: I do not see the link between the sentence and Figure 7 

      Changed where in the discussion we refer to Figure 7.

      (4) Figure 7 upper part: In my opinion, the upper part of Figure 7 does not add any additional value to the illustration of the data as compared to Figure 5 and could be cut.

      We thought it might be easier for some reader to see the shifts as a dial representation with the shift magnitude converted to 0-100% rather than the shifts in Figure 5. This makes it somewhat like a graphical abstract summarising the whole study.

      I agree that Figure 5 tells the same story but a reader that has little background in directional stats might find figure 7 more intuitive. This was the intent at least. 

      If it becomes a sticking point, then we can remove the upper portion.  

      Reviewer #2 (Recommendations For The Authors): 

      Minor corrections and queries 

      Line 117: THE majority 

      Corrected

      Lines 129-130: Do you have a reference to support this statement? I am unaware of experiments that show that homing ants count their steps, but I could have missed it.

      We have added the references that unpack the ant pedometer.  

      Line 140: remove "the" in this line. 

      Removed

      Line 170: We need more details here about the spectral transmission properties of the polariser (and indeed which brand of filter, etc.). For instance, does it allow the transmission of UV light?

      Added

      Line 239: "...tested identicALLY to ...." 

      Corrected

      Lines 242-258 (Vector testing): I must admit I found the description of these experiments very difficult to follow. I read this section several times and felt no wiser as a result. I think some thought needs to be given to better introduce the reader to the rationale behind the experiment (e.g., start by expanding lines 243-246, and maybe add a methods figure that shows the different experimental procedures).

      I have rewritten this section of the methods to clearly state the experiment rational and to be clearer as to the methodology.

      Also added a methods panel to Figure 6.

      Line 247: "reoriented only halfway". What does this mean? Do you mean with half the expected angle?

      Yes, this is a bit unclear. We have altered for clarity:

      ‘only altered their headings by about half of the 45° e-vector shift (25.2°± 3.7°), despite being tested on near-full-moon nights.’

      Results section (in general): In Figure 1 (which is a very nice figure!) you go to all the trouble of defining b degrees (exit headings) and c degrees (reorientation headings), which are very intuitive for interpreting the results, and then you totally abandon these convenient angles in favour of an amorphous Greek symbol Phi (Figs. 2-6) to describe BOTH exit and reorientation headings. Why?? It becomes even more confusing when headings described by Phi can be typically greater than 300 degrees in the figures, but they are never even close to this in the text (where you seem to have gone back to using the b degrees and c degrees angles, without explicitly saying so). Personally, I think the b degrees and c degrees angles are more intuitive (and should be used in both the text and the figures), but if you do insist on using Phi then you should use it consistently in both the text and the figures. 

      Replaced Phi with b° and c° for both figures and in the text.

      Finally, for reorientation angles in Figure 4A, you say that the angle is 16.5 degrees. This angle should have been 143.5 degrees to be consistent with other figures. 

      Yes, the reorientation was erroneously copied from the shift data (it is identical in both the +45 shift and reorientation for Figure 4A). This has now been corrected

      Line 280, and many other lines: Wherever you refer to two panels of the same figure, they should be written as (say) Figure 2A, B not Figure 2AB.

      Changed as requested throughout the text.

      Line 295 (Waxing lunar phases): For these experiments, which nest are you using? 1 or 2?

      We have added that this is nest 1. 

      Figure 3B: The title of this panel should be "Waxing Crescent Moon" I think. 

      Ah yes, this is incorrect in the original submission. I have fixed this.

      Lines 312-313: Here it sounds as though the ants went right back to the full +/- 45 degrees orientations when they clearly didn't (it was -26.6 degrees and 189.9 degrees). Maybe tone the language down a bit here.

      Changed this to make clear the orientation shift is only ‘towards’ the ambient lunar e-vector.

      Line 327: Insert "see" before "Figure 5" 

      Added

      Line 329: See comment for Line 295. 

      We have added that this is nest 1. 

      Lines 357-373 (Vector testing): Again, because of the somewhat confusing methods section describing these experiments, these results were hard to follow, both here and in the Discussion. I don't really understand what you have shown here. Re-think how you present this (and maybe re-working the Methods will be half the battle won). 

      I have rewritten these sections to try to make clear these are ant tested with differences in vector length 6m vs. 2m, tested at the same location. Hopefully this is much clearer, but I think if these portions remain a bit confusing that a full rename of the conditions is in order. Something like long vector and short vector would help but comes with the problem of not truly describing what the purpose of the test is which is to control for location, thus the current condition names. As it stands, I hope the new clarifications adequately describe the reasoning while keeping the condition names. Of course, I am happy to make more changes here as making this clear to readers is important for driving home that the path integrator is in play.

      See current change to results as an example: ‘Both forgers with a long ~6m remaining vector (Halfway Release), or a short ~2m remaining vector (Halfway Collection & Release), tested at the same location_,_ exhibited significant shifts to the right of initial headings when the e-vector was rotated clockwise +45°.’

      Line 361: I think this should be 16.8 not 6.8 

      Yes, you are correct. Fixed in text (16.8).

      Line 365: I think this should be -12.7 not 12.7 

      Yes, you are correct. Fixed in text (–12.7).

      Line 408: "morning twilight". Should this be "morning solar twilight"? Plus "M midas" should be "M. midas"

      Added and fixed respectively.

      Line 440. "location" is spelt wrong. 

      Fixed spelling.

      Line 444: "...WITH longer accumulated vectors, ..." 

      Added ‘with’ to sentence. 

      Line 447: Remove "that just as"

      Removed.

      Line 448: "Moonlight polarised light" should be "Polarised moonlight" 

      Corrected.

      Lines 450-453: This sentence makes little sense scientifically or grammatically. A "limiting factor" can't be "accomplished". Please rephrase and explain in more detail.

      This sentence has been rephrased:

      ‘The limiting factors to lunar cue use for navigation would instead be the ant’s detection threshold to either absolute light intensity, polarization sensitivity and spectral sensitivity. Moonlight is less UV rich compared to direct sunlight and the spectrum changes across the lunar cycle (Palmer and Johnsen 2015).’

      Line 474: Re-write as "... due to the incorporation of the celestial compass into the path integrator..."

      Added.

      Reviewer #3 (Recommendations For The Authors): 

      Minor comments 

      Line 84 I am not sure that we can infer attentional processes in orientation to lunar skylight, at least it has not yet been investigated.

      Yes, this is a good point. We have changed ‘attend’ to ‘use’.  

      Line 90 This description of polarized light is a little vague; what is meant by the phrase "waves which occur along a single plane"? (What about the magnetic component? These waves can be redirected, are they then still polarized? Circular polarization?). I would recommend looking at how polarized light is described in textbooks on optics.

      We have rewritten the polarised light section to be clearer using optics and light physics for background. 

      Line 92 The phrase "e-vector" has not been described or introduced up to this point.

      We now introduce e-vector and define it. 

      ‘Polarised light comprises light waves which occur along a single plane and are produced as a by-product of light passing through the upper atmosphere (Horváth & Varjú 2004; Horváth et al., 2014). The scattering of this light creates an e-vector pattern in the sky, which is arranged in concentric circles around the sun or moon's position with the maximum degree of polarisation located 90° from the source. Hence when the sun/moon is near the horizon, the pattern of polarised skylight is particularly simple with uniform direction of polarisation approximately parallel to the north-south axes (Dacke et al., 1999, 2003; Reid et al. 2011; Zeil et al., 2014).’

      Happy to make further changes as well.  

      Line 107 Diurnal dung beetles can also orient to lunar skylight if roused at night (Smolka et al., 2016), provided the sky is bright enough. Perhaps diurnal ants might do the same?

      Added the diurnal dung beetles mention as well as the reference.

      Also, a very good suggestion using diurnal bull ants.

      Line 146 Instead of lunar calendar the authors appear to mean "lunar cycle". 

      Changed

      Line 165 In Figure 1B, it looks like visual access to the sky was only partly "unobstructed". Indeed foliage covers as least part of the sky right up to the zenith.

      We have added that the sky is partially obstructed. 

      Line 179 This could also presumably be checked with a camera? 

      For this testing we tried to keep equipment to a minimum for a single researcher walking to and from the field site given the lack of public transport between 1 and 4am. But yes, for future work a camera based confirmation system would be easier. 

      Line 243 The abbreviation "PI" has not been described or introduced up to this point.

      Changes to ‘path integration derived vector lengths….’

      Line 267 The method for comparing the leftwards and rightwards shifts should be described in full here (presumably one set of shifts was mirrored onto the other?).

      We have added the below description to indicate the full description of the mirroring done to counterclockwise shifts.

      ‘To assess shift magnitude between −45° and +45° foragers within conditions, we calculated the mirror of shift in each −45° condition, allowing shift magnitude comparisons within each condition. Mirroring the −45° conditions was calculated by mirroring each shift across the 0° to 180° plane and was then compared to the corresponding unaltered +45 condition.’

      Discussion Might the brightness and spectrum of lunar skylight also play a role here?

      We have added a section to the discussion to mention the aspects of moonlight which may be important to these animals, including the spectrum, brightness and polarisation intensity.  

      Line 451 The sensitivity threshold to absolute light intensity would not be the only limiting factor here. Polarization sensitivity and spectral sensitivity may also play a role (moonlight is less UV rich than sunlight and the spectrum of twilight changes across the lunar cycle: Palmer & Johnsen, 2015). 

      Added this clarification.

      Line 478 Instead of the "masculine ordinal" symbol used (U+006F) here a degree symbol (U+00B0) should be used.

      Ah thank you, we have replaced this everywhere in the text.  

      Line 485 It should be possible to calculate the misalignment between polarization pattern before and after this interruption of celestial cues. Does the magnitude of this misalignment help predict the size of the reorientation?

      Reorientations are highly correlated with the shift size under the filter, which makes sense as larger shifts mean that foragers need to turn back more to reorient to both the ambient pattern and to return to their visual route. Reorientation sizes do not show a consistent reduction compared to under-the-filter shifts when the lunar phase is low and is potentially harder to detect.

      I have reworked this line in the text as I do not think there is much evidence for misalignment and it might be more precise to say that overnight periods where the moon is not visible may adversely impact the path integrator estimate, though it is currently unknown the full impact of this celestial cue gap of if other cues might also play a role.

      Line 642 "from their" should be "relative to" 

      Changed as requested

      Figure 1B Some mention should be made of the differences in vegetation density. 

      Added a sentence to the figure caption discussing the differences in both vegetation along the horizon and canopy cover.

      Figures 2-6 A reference line at 0 degrees change might help the reader to assess the size of orientation changes visually. Confidence intervals around the mean orientation change would also help here.

      We have now added circular grid lines and confidence intervals to the circular plots. These should help make the heading changes clear to readers.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Removing claims of causality: To avoid confusion, we have now removed claims of causality from our manuscript and also changed the title of the manuscript accordingly

      "Electrophysiological dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall: A multi-experiment iEEG replication".

      Control analyses directly comparing AI and IFG: As per the reviewer’s suggestion, we have carried out additional control analyses by directly comparing the net inward/outward balance between the AI and the IFG. Our analysis revealed that the net outflow for the AI is significantly higher compared to the IFG during both encoding and recall phases, a pattern that was replicated across all four experiments. 

      These findings further highlight the unique role of the AI as a key hub in coordinating network interactions during episodic memory formation and retrieval, distinguishing it from a key anatomically adjacent prefrontal region implicated in cognitive control.

      We have incorporated these results into the manuscript (see new Figure S6 and updated Results section). 

      Control analyses directly comparing task with resting state: As per the reviewer’s suggestion, we compared the AI's net outflow during task periods to resting state, finding significantly higher outflow during both encoding and recall across all experiments (ps < 0.05). These results provide further evidence for enhanced role of AI net directed information flow to the DMN and FPN during memory processing compared to the resting state. 

      We have incorporated these results into the manuscript (see new Figure S9 and updated Results section). 

      Control analysis using every region of the brain outside the considered networks: We appreciate the reviewer's suggestion to conduct additional control analyses. However, we have concerns about implementing this approach for several reasons:

      (1) Hypothesis-driven research: Our study was designed based on a strong hypothesis derived from prior fMRI studies, which have consistently shown that the salience network (SN), anchored by the anterior insula (AI), plays a critical role in regulating the engagement and disengagement of the default mode network (DMN) and frontoparietal network (FPN) across diverse cognitive tasks.

      (2) Risk of p-hacking: Running analyses on a large number of brain regions outside our networks of interest without a priori hypotheses could lead to p-hacking, a practice strongly criticized in the scientific community, including by eLife editors (Makin & Orban de Xivry, 2019). Such an approach could potentially yield spurious results and undermine the validity of our findings.

      (3) Principled control region selection: Our choice of the inferior frontal gyrus (IFG) as a control region was hypothesis-driven, based on its: a) Anatomical adjacency to the AI b) Involvement in cognitive control functions, including response inhibition c) Frequent coactivation with the AI in fMRI studies. 

      (4) Robustness of current findings: Our PTE analysis involving the IFG, along with the additional control analyses requested by the reviewer (comparing the task-related net balance of the AI with the IFG and with resting state, see response to reviewer comment 2.1), strongly support a key role for the AI in orchestrating large-scale network dynamics during memory processes.

      (5) Specificity of findings: The contrast between AI and IFG results demonstrates that our observed patterns are not general to all task-active regions but are specific to the AI's role in network coordination. 

      We believe that our current analyses, including the additional controls, provide a comprehensive and rigorous examination of the AI's role in memory-related network dynamics. Adding analyses of numerous additional regions without clear hypotheses could potentially dilute the focus and interpretability of our results. 

      However, we acknowledge the importance of considering broader network interactions. In future studies, we could explore the role of other key regions in a hypothesis-driven manner, potentially expanding our understanding of the complex interactions between multiple brain networks during memory processes.

      These revisions, combined with our rigorous methodologies and comprehensive analyses, provide compelling support for the central claims of our manuscript. We believe these changes significantly enhance the scientific contribution of our work.

      Our point-by-point responses to the reviewers' comments are provided below.

      Reviewer 1:

      (1.1) Because phase-transfer entropy is referenced as a "causal" analysis in this investigation (PTE), I believe it is important to highlight for readers recent discussions surrounding the description of "causal mechanisms" in neuroscience (see "Confusion about causation" section from Ross and Bassett, 2024, Nature Neuroscience). A large proportion of neuroscientists (myself included) use "causal" only to refer to a mechanism whose modulation or removal (with direct manipulation, such as by lesion or stimulation) is known to change or control a given outcome (such as a successful behavior). As Ross and Bassett highlight, it is debatable whether such mechanistic causality is captured by Granger "causality" (a.k.a. Granger prediction) or the parametric PTE, and imprecise use of "causation" may be confusing. The authors have defined in the revised Introduction what their definition of "causality" is within the context of this investigation. 

      We appreciate the reviewer's feedback in terms of the terminology used in our manuscript. To avoid confusion, we have now removed claims of causality from our manuscript and also changed the title of the manuscript accordingly. 

      Reviewer 2:

      (2.1) Clarifying the new control analyses. The authors have been responsive to our feedback and implemented several new analyses. The use of a pre-task baseline period and a control brain region (IFG) definitively help to contextualize their results, and the findings shown in the revision do suggest that (1) relative to a pre-task baseline, directed interactions from the AI are stronger and (2) relative to a nearby region, the IFG, the AI exhibits greater outward-directed influence. 

      However, it is difficult to draw strong quantitative conclusions from the analyses as presented, because they do not directly statistically contrast the effect in question (directed interactions with the FPN and DMN) between two conditions (e.g. during baseline vs. during memory encoding/retrieval). As I understand it, in their main figures the authors ask, "Is there statistically greater influence from the AI to the DMN/FPN in one direction versus another?" And in the AI they show greater "outward" PTE than "inward" PTE from other networks during encoding/retrieval. The balance of directed information favors an outward influence from the AI to DMN/FPN. 

      But in their new analyses, they simply show that the degree of "outward" PTE is greater during task relative to baseline in (almost) all tasks. I believe a more appropriately matched analysis would be to quantify the inward/outward balance during task states, quantify the inward/outward balance during rest states, and then directly statistically compare the two. It could be that the relative balance of directed information flow is nonsignificantly changed between task and rest states, which would be important to know. 

      We thank the reviewer for this suggestion. We have now run additional analysis by directly comparing the inward/outward balance during the task versus the rest states. To calculate the net inward/outward balance, we calculated the net outflow as the difference between the total outgoing information and total incoming information (PTE(out)–PTE(in)). This analysis revealed that net outflow during task periods is significantly higher compared to rest, during both encoding and recall, and across the four experiments (ps < 0.05). These results provide further evidence for enhanced role of AI net directed information flow to the DMN and FPN during memory processing compared to the resting state. These new results have now been included in the revised manuscript (page 12). 

      Likewise, a similar principle applies to their IFG analysis. They show that the IFG tends to have an "inward" balance of influence from the DMN/FPN (the opposite of the AIs effect), but this does not directly answer whether the AI occupies a statistically unique position in terms of the magnitude of its influence on other regions. More appropriate, as I suggest above, would be to quantify the relative balance inward/outward influence, both for the IFG and the AI, and then directly compare those two quantities. (Given the inversion of the direction of effect, this is likely to be a significant result, but I think it deserves a careful approach regardless.) 

      We appreciate the reviewer's suggestion. As per the reviewer’s suggestion, we directly compared the net inward/outward balance between the AI and the IFG. Specifically, we compared the net outflow (PTE(out)–PTE(in)) for the AI with the IFG. This analysis revealed that the net outflow for the AI is significantly higher compared to the IFG during both encoding and recall, and across the four experiments. These findings further highlight a key role for the AI in orchestrating large-scale network dynamics during memory processes. The AI's pattern of directed information flow stands in contrast to that of the IFG, despite their anatomical proximity and shared involvement in cognitive control processes. This dissociation underscores the specificity of the AI's function in coordinating network interactions during memory formation and retrieval. These new results have now been included in our revised manuscript (page 11). 

      (2.2) Consider additional control regions. The authors justify their choice of IFG as a control region very well. In my original comments, I perhaps should have been more clear that the most compelling control analyses here would be to subject every region of the brain outside these networks (with good coverage) to the same analysis, quantify the degree of inward/outward balance, and then see how the magnitude of the AI effect stacks up against all possible other options. If the assertion is that the AI plays a uniquely important role in these memory processes, showing how its influence stacks up against all possible "competitors" would be a very compelling demonstration of their argument. 

      We thank the reviewer for this suggestion. However, please note that running a large number of random analysis by including a large number of brain regions (every region of the brain outside these networks) and comparing their dynamics to the AI without a hypothesis or solid principle amounts to p-hacking, which has been previously strongly criticized by the eLife editors (Makin & Orban de Xivry, 2019). Our study was strongly driven by a solid hypothesis based on prior fMRI studies that have shown that the SN, anchored by the anterior insula (AI), plays a critical role in regulating the engagement and disengagement of the DMN and FPN across diverse cognitive tasks (Bressler & Menon, 2010; Cai et al., 2016; Cai, Ryali, Pasumarthy, Talasila, & Menon, 2021; Chen, Cai, Ryali, Supekar, & Menon, 2016; Kronemer et al., 2022; Raichle et al., 2001; Seeley et al., 2007; Sridharan, Levitin, & Menon, 2008). Moreover, our selection of the IFG as a control region for comparison was also very strongly hypothesis driven, due to its anatomical adjacency to the AI, its involvement in a wide range of cognitive control functions including response inhibition (Cai, Ryali, Chen, Li, & Menon, 2014), and its frequent co-activation with the AI in fMRI studies. Furthermore, the IFG has been associated with controlled retrieval of memory (Badre, Poldrack, Paré-Blagoev, Insler, & Wagner, 2005; Badre & Wagner, 2007; Wagner, Paré-Blagoev, Clark, & Poldrack, 2001), making it a compelling region for comparison. Our findings related to the PTE analysis involving the IFG and also the additional control analyses requested by the reviewer (directly comparing the task-related net balance of the AI with the IFG and also to resting state, please see response to reviewer comment 2.1) strongly highlight a key role of the AI in orchestrating large-scale network dynamics during memory processes. 

      We believe that our current analyses, including the additional controls, provide a comprehensive and rigorous examination of the AI's role in memory-related network dynamics. Adding analyses of numerous additional regions without clear hypotheses could potentially dilute the focus and interpretability of our results.

      However, we acknowledge the importance of considering broader network interactions. In future studies, we could explore the role of other key regions in a hypothesis-driven manner, potentially expanding our understanding of the complex interactions between multiple brain networks during memory processes.

      (2.3) Reporting of successful vs. unsuccessful memory results. I apologize if I was not clear in my original comment (2.7, pg. 13 of the response document) regarding successful vs. unsuccessful memory. The fact that no significant difference was found in PTE between successful/unsuccessful memory is a very important finding that adds valuable context to the rest of the manuscript. I believe it deserves a figure, at least in the Supplement, so that readers can visualize the extent of the effect in successful/unsuccessful trials. This is especially important now that the manuscript has been reframed to focus more directly on claims regarding episodic memory processing; if that is indeed the focus, and their central analysis does not show a significant effect conditionalized on the success of memory encoding/retrieval, it is important that readers can see these data directly.

      As per the reviewer’s suggestion, we have now included a Figure related to the results for the successful versus unsuccessful comparison in the Supplementary materials of the revised manuscript (Figures S10, S11).   

      (2.4) Claims regarding causal relationships in the brain. I understand that the authors have defined "causal" in a specific way in the context of their manuscript; I do believe that as a matter of clear and transparent scientific communication, the authors nonetheless bear a responsibility to appreciate how this word may be erroneously interpreted/overinterpreted and I would urge further review of the manuscript to tone down claims of causality. Reflective of this, I was very surprised that even as both reviewers remarked on the need to use the word "causal" with extreme caution, the authors added it to the title in their revised manuscript.

      We thank the reviewer for this suggestion. To avoid confusion, we have now removed claims of causality from our manuscript and also changed the title of the manuscript accordingly. 

      References 

      Badre, D., Poldrack, R. A., Paré-Blagoev, E. J., Insler, R. Z., & Wagner, A. D. (2005). Dissociable controlled retrieval and generalized selection mechanisms in ventrolateral prefrontal cortex. Neuron, 47(6), 907-918. doi:10.1016/j.neuron.2005.07.023

      Badre, D., & Wagner, A. D. (2007). Left ventrolateral prefrontal cortex and the cognitive control of memory. Neuropsychologia, 45(13), 2883-2901. doi:10.1016/j.neuropsychologia.2007.06.015

      Bressler, S. L., & Menon, V. (2010). Large-scale brain networks in cognition: emerging methods and principles. Trends in Cognitive Sciences, 14(6), 277-290. doi:10.1016/j.tics.2010.04.004

      Cai, W., Chen, T., Ryali, S., Kochalka, J., Li, C. S., & Menon, V. (2016). Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation. Cereb Cortex, 26(5), 2140-2153. doi:10.1093/cercor/bhv046

      Cai, W., Ryali, S., Chen, T., Li, C. S., & Menon, V. (2014). Dissociable roles of right inferior frontal cortex and anterior insula in inhibitory control: evidence from intrinsic and taskrelated functional parcellation, connectivity, and response profile analyses across multiple datasets. J Neurosci, 34(44), 14652-14667. doi:10.1523/jneurosci.3048-14.2014

      Cai, W., Ryali, S., Pasumarthy, R., Talasila, V., & Menon, V. (2021). Dynamic causal brain circuits during working memory and their functional controllability. Nat Commun, 12(1), 3314. doi:10.1038/s41467-021-23509-x

      Chen, T., Cai, W., Ryali, S., Supekar, K., & Menon, V. (2016). Distinct Global Brain Dynamics and Spatiotemporal Organization of the Salience Network. PLOS Biology, 14(6), e1002469. doi:10.1371/journal.pbio.1002469

      Kronemer, S. I., Aksen, M., Ding, J. Z., Ryu, J. H., Xin, Q., Ding, Z., . . . Blumenfeld, H. (2022). Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity. Nat Commun, 13(1), 7342. doi:10.1038/s41467-022-35117-4

      Makin, T. R., & Orban de Xivry, J. J. (2019). Ten common statistical mistakes to watch out for when writing or reviewing a manuscript. Elife, 8. doi:10.7554/eLife.48175

      Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proc Natl Acad Sci U S A, 98(2), 676-682. doi:10.1073/pnas.98.2.676

      Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., . . . Greicius, M. D. (2007). Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control. Journal of Neuroscience, 27(9), 2349-2356. doi:10.1523/JNEUROSCI.5587-06.2007

      Sridharan, D., Levitin, D. J., & Menon, V. (2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences, 105(34), 12569-12574. doi:10.1073/pnas.0800005105

      Wagner, A. D., Paré-Blagoev, E. J., Clark, J., & Poldrack, R. A. (2001). Recovering meaning: left prefrontal cortex guides controlled semantic retrieval. Neuron, 31(2), 329-338. doi:10.1016/s0896-6273(01)00359-2

    1. Author response:

      The following is the authors’ response to the current reviews.

      We thank the reviewers and editor for their positive assessment of our work. For the Version of Record, we have made small revisions addressing the remaining concerns of reviewer #3. We have also reformatted the supplementary material to conform to eLife’s style.

      While the manuscript was under review, we discussed our work with Bill Bialek, who suggested clarifying the effect of cell rearrangements on genetic patterns. Using the tracked cell trajectories we found that the highly coordinated intercalations in the germ band preserve the relative AP positions of cells. We have added an Appendix subsection (Appendix 1.5) explaining this finding and highlighting its relevance in a short paragraph added to the discussion.

      Reviewer #2

      Main comment from 1st review:

      Weaknesses:

      The modeling is interesting, with the integration of tension through tension triangulation around vertices and thus integrating force inference directly in the vertex model. However, the authors are not using it to test their hypothesis and support their analysis at the tissue level. Thus, although interesting, the analysis at the tissue level stays mainly descriptive.

      Comments on the revised version:

      My main concern was that the author did not use the analysis of mutant contexts such as Snail and Twist to confirm their predictions. They made a series of modifications, clarifying their conclusions. In particular, they now included an analysis of Snail mutant and show that isogonal deformations in the ventro-lateral regions are absent when the external pulling force of the VF is abolished, supporting the idea that isogonal strain could be used as an indicator of external forces (Fig7 and S6).

      They further discuss their results in the context of what was published regarding the mutant backgrounds (fog, torso-like, scab, corkscrew, ksr) where midgut invagination is disrupted, and where germ band buckles, and propose that this supports the importance of internal versus external forces driving GBE.

      Overall, these modifications, in addition to clarifications in the text, clearly strengthen the manuscript.

      We thank the reviewer for assessing our manuscript again and are happy to hear that they find the added data on the snail mutant convincing and that our revised manuscript is stronger.

      Reviewer #3

      In their article "The Geometric Basis of Epithelial Convergent Extension", Brauns and colleagues present a physical analysis of drosophila axis extension that couples in toto imaging of cell contours (previously published dataset), force inference, and theory. They seek to disentangle the respective contributions of active vs passive T1 transitions in the convergent extension of the lateral ectoderm (or germband) of the fly embryo.

      The revision made by the authors has greatly improved their work, which was already very interesting, in particular the use of force inference throughout intercalation events to identify geometric signatures of active vs passive T1s, and the tension/isogonal decomposition. The new analysis of the Snail mutant adds a lot to the paper and makes their findings on the criteria for T1s very convincing.

      About the tissue scale issues raised during the first round of review. Although I do not find the new arguments fully convincing (see below), the authors did put a lot of effort to discuss the role of the adjacent posterior midgut (PMG) on extension, which is already great. That will certainly provide the interested readers with enough material and references to dive into that question.

      We appreciate the referee’s positive assessment of our manuscript and their careful reading and constructive feedback. In particular, we are happy to hear that the referee finds our added data on the snail mutant very convincing and finds that the extended discussion on the role of the PMG is helpful. We address the remaining concerns in our detailed response below.

      I still have some issues with the authors' interpretation on the role of the PMG, and on what actually drives the extension. Although it is clear that T1 events in the germ band are driven by active local tension anisotropy (which the authors show but was already well-established), it does not show that the tissue extension itself is powered by these active T1s. Their analysis of "fence" movies from Collinet et al 2015 (Tor mutants and Eve RNAi) is not fully convincing. Indeed, as the authors point out themselves, there is no flow in Tor mutant embryos, even though tension anisotropy is preserved. They argue that in Tor embryos the absence of PMG movement leaves no room for the germband to extend properly, thus impeding the flow. That suggests that the PMG acts as a barrier in Tor mutants - What is it attached to, then?

      We thank the referee for pointing out this omission: The PMG is attached to the vitelline membrane in the scab domain (Munster et al. Nature 2019) and is also obstructed from moving by more anterior laying tissue (amnioserosa). It therefore acts as an obstacle for GBE extension if it fails to invaginate (e.g. in a Tor embryo). We have clarified this in the discussion of the Tor mutants.

      The authors also argue that the posterior flow is reduced in "fenced" Eve RNAi embryos (which have less/no tension anisotropy), to justify their claim that it is the anisotropy that drives extension. However, previous data, including some of the authors' (Irvine and Wieschaus, 1994 - Fig 8), show that the first, rapid phase of germband extension is left completely unaffected in Eve mutants (that lack active tension anisotropy). Although intercalation in Eve mutants is not quantified in that reference, this was later done by others, showing that it is strongly reduced.

      The quantification of GBE in Irvine and Wieschaus 1994 was based on the position of the PMG from bright field imaging, making it hard to distinguish the contributions of ventral furrow, PMG, and germ band, particularly during the early phase of GBE where all these processes happen simultaneously. More detailed quantifications based on PIV analysis of in toto light-sheet imaging show significantly reduced tissue flow in eve mutants after the completion of ventral furrow invagination (Lefebvre et al., eLife 2023). That the initial fast flow is driven by ventral furrow invagination, not by the PMG is apparent from twist/snail embryos where the initial phase is significantly slower (Lefebvre et al., eLife 2023, Gustafson et al., Nat Comms 2022). We have added these references to the re-analysis and discussion of the Collinet et al 2015 experiments.

      Similarly, the Cyto-D phenotype from Clement et al 2017, in which intercalation is also strongly reduced, also displays normal extension.

      We agree that a careful quantification of tissue flow in Cyto-D-treated embryos would be interesting. Whether they show normal extension is not clear from the Clement et al. 2017 paper, as no quantification of total tissue flow is performed and no statements regarding extension are made there.

      Reviewer #3 (Recommendations For The Authors):

      • A lot of typos / grammar mistakes / repetitions are still found here and there in the paper. Authors should plan a careful re-reading prior to final publication.

      We have carefully checked the manuscript and fixed the typos and grammar mistakes.

      • I failed to point to a very relevant reference in the previous round of review, which I think the authors should cite and comment: A review by Guirao & Bellaiche on the mechanics of intercalation in the fly germband, which notably discusses the passive/active and stress-relaxing/stress-generating nature of T1s. (Guirao and Bellaiche, Current opinions in cell biology 2017), in particular figures 1 and 2.

      We thank the referee for pointing us to this relevant reference which we now cite in the introduction.

      • Any new arguments/discussion the authors see fit to include in the paper to comment on the Eve/Tor phenotypes. As far as I am concerned, I am not fully convinced at the moment (see review), but I think the paper has other great qualities and findings, and now (since the first round of review) sufficiently discusses that particular matter. I leave it up to the authors how much (more) they want to delve into this in their final version!

      We have added clarifications and references to the discussion of the Eve/Tor phenotypes.


      The following is the authors’ response to the original reviews.

      Public Review:

      Joint Public Review:

      Summary:

      Brauns et al. work to decipher the respective contribution of active versus passive contributions to cell shape changes during germ band elongation. Using a novel quantification tool of local tension, their results suggest that epithelial convergent extension results from internal forces.

      Reading this summary, and the eLife assessment, we realized that we failed to clearly communicate important aspects of our findings in the first version of our manuscript. We therefore decided to largely restructure and rewrite the abstract and introduction to emphasize that:

      ● Our analysis method identifies active vs passive contributions to cell and tissue shape changes during epithelial convergent extension

      ● In the context of Drosophila germ band extension, this analysis provides evidence for a major role for internal driving forces rather than external pulling force from neighboring tissue regions (posterior midgut), thus settling a question that has been debated due to apparently conflicting evidence from different experiments.

      ● Our findings have important implications for local, bottom-up self-organization vs top-down genetic control of tissue behaviors during morphogenesis.

      Strengths:

      The approach developed here, tension isogonal decomposition, is original and the authors made the demonstration that we can extract comprehensive data on tissue mechanics from this type of analysis.

      They present an elegant diagram that quantifies how active and passive forces interact to drive cell intercalations.

      The model qualitatively recapitulates the features of passive and active intercalation for a T1 event.

      Regions of high isogonal strains are consistent with the proximity of known active regions.

      We think this statement is somewhat ambiguous and does not summarize our findings precisely. A more precise statement would be that high isogonal strain identifies regions of passive deformation, which is caused by adjacent active regions.

      They define a parameter (the LTC parameter) which encompasses the geometry of the tension triangles and allows the authors to define a criterium for T1s to occur.

      The data are clearly presented, going from cellular scale to tissue scale, and integrating modeling approaches to complement the thoughtful description of tension patterns.

      Weaknesses:

      The modeling is interesting, with the integration of tension through tension triangulation around vertices and thus integrating force inference directly in the vertex model. However, the authors are not using it to test their hypothesis and support their analysis at the tissue level. Thus, although interesting, the analysis at the tissue level stays mainly descriptive.

      We fully agree that a full tissue scale model is crucial to support the claims about tissue scale self-organization we make in the discussion. However, the full analysis of such a model is beyond the scope of the present manuscript. We have therefore split off that analysis into a companion manuscript (Claussen et al. 2023). In this paper, we show that the key results of the tissue-scale analysis of the Drosophila embryo, in particular the order-to-disorder transition associated with slowdown of tissue flow, are reproduced and rationalized by our model.

      We now refer more closely to this companion paper to point the reader to the results presented there.

      Major points:

      (1) The authors mention that from their analysis, they can predict what is the tension threshold required for intercalations in different conditions and predict that in Snail and Twist mutants the T1 tension threshold would be around √2. Since movies of these mutants are most probably available, it would be nice to confirm these predictions.

      This is an excellent suggestion. We have included an analysis of a recording of a Snail mutant, which is presented in the new Figures 4 and S6. As predicted, we find that isogonal deformations in the ventro-lateral regions are absent when the external pulling force of the VF is abolished. Further, in the absence of isogonal deformation, T1 transitions indeed occur at a critical tension of approx. √2, as predicted by our model. Both of these results provide important experimental evidence for our model and for isogonal strain as a reliable indicator of external forces.

      (2) While the formalism is very elegant and convincing, and also convincingly allows making sense of the data presented in the paper, it is not all that clear whether the claims are compatible with previous experimental observations. In particular, it has been reported in different papers (including Collinet et al NCB 2015, Clement et al Curr Biol 2017) that affecting the initial Myosin polarity or the rate of T1s does not affect tissue-scale convergent extension. Analysis/discussion of the Tor phenotype (no extension with myosin anisotropy) and the Eve/Runt phenotype (extension without Myosin anisotropy), which seem in contradiction with an extension mostly driven by myosin anisotropy.

      We are happy to read that the referees find our approach elegant and convincing. The referees correctly point out that we have failed to clearly communicate how our findings connect to the existing literature on Drosophila GBE. Indeed, the conflicting results reported in the literature on what drives GBE – internal forces (myosin anisotropy) or external forces (pulling by the posterior midgut) – were a motivation for our study. We have extensively rewritten the introduction, results section (“Isogonal strain identifies regions of passive tissue deformation”), and discussion (“Internal and external contributions to germ band extension”) in response to the referee’s request.

      In brief, distinguishing active internal vs passive external driving of tissue flow has been a fundamental open question in the literature on morphogenesis. Our tension-isogonal decomposition now provides a way to answer this question on the cell scale, by identifying regions of passive deformation due to external forces. As we now explain more clearly, our analysis shows that germ band extension is predominantly driven by internal tension dynamics, and not pulling forces from the posterior midgut.

      We put this cell-scale evidence into the context of previous experimental observations on the tissue scale: Genetic mutants (fog, torso-like, scab, corkscrew, ksr), where posterior midgut invagination is disrupted (Muenster et al. 2019, Smits et al. 2023). In these mutants, the germ band buckles forming ectopic folds or twists into a corkscrew shape as it extends, pointing towards a buckling instability characteristic of internally driven extensile flows.

      To address the apparently conflicting evidence from Collinet et al. 2015, we carried out a

      quantitative re-analysis of the data presented in that reference (see new SI section 3 and Fig.

      S11). The results support the conclusion that the majority of GBE flow is driven internally, thus resolving the apparent conflict.

      Lastly, as far as we understand, Clement et al. 2017 appears to be compatible with our picture of active T1 transitions. Clement et al. report that the actin cortex, when loaded by external forces, behaves visco-elastically with a relaxation time of the order of minutes, in line with our model for emerging interfaces post T1.

      We again thank the referees for prompting us to address these important issues and believe that including their discussion has significantly strengthened our manuscript.

      Recommendations for the authors:

      Minor points:

      - Fig 2 : authors should state in the main text at which scale the inverse problem is solved. (Intercalating quartet, if I understood correctly from the methods) ? and they should explain and justify their choice (why not computing the inverse at a larger scale).

      We have rephrased the first sentence of the section “Cell scale analysis” to clarify that we use local tension inference. This local inference is informative about the relative tension of one interface to its four neighbors. The focus on this local level is justified because we are interested in local cell behaviors, namely rearrangements. Tension inference is also most robust on the local level, since this is where force balance, the underlying physical determinant of the link between mechanics and geometry, resides. In global tension inference, spurious large scale gradients can appear when small deviations from local force balance accumulate over large distances. We have added a paragraph in SI Sec. 1.4 to explain these points.

      -Fig 2 : how should one interpret that tension after passive intercalation (amnioserosa) is higher than before. On fig 2E, tension has not converged yet on the plot, what happens after 20 minutes ?

      Recall that the inferred tension is the total tension on an interface. While on contracting interfaces, the majority of this tension will be actively generated by myosin motors, on extending interfaces there is also a contribution carried by passive crosslinkers. The passive tension can be effectively viewed as viscous dissipation on the elongating interface as crosslinkers turn over (Clement et al. 2017). Note that this passive tension is explicitly accounted for in the model presented in Fig. 5. Notably, it is crucial for the T1 process to resolve in a new extending junction. In the amnioserosa, the tension post T1 remains elevated because the amnioserosa is continually stretched by the convergence of the germ band. The tension hence does not necessarily converge back to 1. However, our estimates for the tension after 20 mins post T1 are very noisy because most of the T1s happen relatively late in the movie (past the 25 min mark) and therefore there are only a few T1s where we can track the post-T1 dynamics for more than 20 mins.

      We have added a brief explanation of the high post-T1 tension at the end of the section entitled “Relative tension dynamics distinguishes active and passive intercalations”. Further, we have moved up the section describing the minimal model right after the analysis of the relative tension during intercalations. We believe that this helps the reader better understand these findings before moving on to the tension-isogonal decomposition which generalizes them to the tissue scale.

      Page 7-8 / Figure 3: It is unclear how the decomposition into 1) physical shape 2) tension shape 2) isogonal shape works exactly. A more detailed explanation and more clear illustration of what a quartet is and its labels could help.

      We have added a more detailed explanation in the main text. See our response to the longer question regarding this point below.

      -What exactly defines the boundary curve in figure 3E? How is it computed?

      We have added a sentence in the caption for Fig. 3E explaining that the boundary curve is found by solving Eq. (1) with l set to zero for the case of a symmetric quartet. We have also added a brief explanation immediately below Eq. (1) pointing out that this equation defines the T1 threshold in the space of local tensions T_i in terms of the isogonal length l_iso.

      -The authors should consider incorporating some details described in the SI file to the main text to clarify some points, as long as the accessible style of the manuscript can be kept. The points mentioned below may also be clarified in the SI doc. The specific points that could be elaborated are: Page 7-8 / Figure 3: It is unclear how the decomposition into 1) physical shape 2) tension shape 2) isogonal shape works exactly. A more detailed explanation and more clear illustration of what a quartet is and its labels could help. The mapping to Maxwell-Cremona space is fine, but which subset is the quartet? For a set of 4 cells with two shared vertices and a junction, aren't there 5 different tension vectors? Are we talking two closed force triangles? Separately, how do you exactly decompose the deformation (of 4 full cell shapes or a subset?) into isogonal and non-isogonal parts? What is the least squares fit done over - is this system underdetermined? Is this statistically averaged or computed per quartet and then averaged?

      We thank the referees for pointing us to unclear passages in our presentation. We hope that our revisions have resolved the referee’s questions. As described above, we have clarified the tension-isogonal decomposition in the main text. We have also revised the corresponding SI section (1.5) to address the above questions. A sketch of the quartet with labels is found in SI Fig. S7A which we now refer to explicitly in the main text.

      We always consider force-balance configurations, i.e. closed force triangles. Therefore in the “kite” formed by two adjacent tension triangles, only three tension vectors are independent.

      The decomposition of deformation is performed as follows: For each of the four cells, the center of mass c_i is calculated. Next, tension inference is performed to find the two tension triangles with tension vectors T_ij. Now there are three independent centroidal vectors c_j - c_i and three corresponding independent tension vectors T_ij. We define the isogonal deformation tensor I_quratet as the tensor that maps the centroidal vectors to the tension vectors. In general this is not possible exactly, because I_quartet has only three independent components, but there are six equations.

      The plots in Fig. 3C, C’ are obtained by performing this decomposition for each intercalating quartet individually. The data is then aligned in time and ensemble averages are calculated for each timepoint.

      For tissue-scale analysis in Fig. 6, the decomposition is performed for individual vertices (i.e. the corresponding centroidal and tension triangles) and then averaged locally to find the isogonal strain fields shown in Fig. 6B, B’.

      - Line 468: "Therefore, tissue-scale anisotropy of active tension is central to drive and orient convergent-extension flow [10, 57, 59, 60]." Authors almost never mention the contribution of the PMG to tissue extension. Yet it is known to be crucial (convergent extension in Tor mutants is very much affected). Please discuss this point further.

      The referees raise an important point: as discussed in our response to major point (2), we now explicitly discuss the role of internal (active tension) and external (PMG pulling) forces during germ band extension. Please see our response to major point (2) for the changes we made to the manuscript to address this.

      In particular, we now explain that in mutants where PMG invagination is impaired (fog, torso-like, torso, scab, corkscrew), the germ band buckles out of plane or extends in a twisted, corkscrew fashion (Smits et al. 2023). This shows that the germ band generates extensile forces largely internally. In torso mutants, the now stationary PMG acts as a barrier which blocks GBE extension; the germ band buckles as a response.

      The role of PMG invagination hence lies not in creating pulling forces to extend the germ band, but rather in “making room” to allow for its orderly extension. As shown by the genetics mutants just discussed, the synchronization of PMG invagination and GBE is crucial for successful gastrulation.

      -Typos:

      Line 74: how are intercalations are

      Line 84: vertices vertices

      Line 233: very differently

      Line 236: are can

      Line 390: energy which is the isogonal mode must

      Line 1585: reveals show

      Line 603: area Line 618: in terms of on the

      We have fixed these typos.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this study, the authors describe the participation of the Hes4-BEST4-Twist axis in controlling the process of epithelial-mesenchymal transition (EMT) and the advancement of colorectal cancers (CRC). They assert that this axis diminishes the EMT capabilities of CRC cells through a variety of molecular mechanisms. Additionally, they propose that reduced BEST4 expression within tumor cells might serve as an indicator of an adverse prognosis for individuals with CRC.

      Strengths:

      • Exploring the correlation between the Hes4-BEST4-Twist axis, EMT, and the advancement of CRC is a novel perspective and gives readers a fresh standpoint.<br /> • The whole transcriptome sequence analysis (Figure 5) showing low expression of BEST4 in CRC samples will be of broad interest to cancer specialists as well as cell biologists although further corroborative data is essential to strengthen these findings (See Weaknesses).

      Weaknesses:

      (1) The authors employed three kinds of CRC cell lines, but not untransformed cells such as intestinal epithelial organoids which are commonly used in recent research.

      Sincerely thanks for catching this issue. While we acknowledge the potential of intestinal epithelial organoids as a valuable model for this study and will consider establishing this system in future research, which falls outside the scope of our current work.

      (2) The authors use three different human CRC cell lines with a lack of consistency in the selection of them. Please clarify 1) how these lines are different from each other, 2) why they pick up one or two of them for each experiment. To be more convincing, at least two lines should be employed for each in vitro experiment.

      We apologize for any confusion caused to the reviewer. In our study, we employed HCT116 and Caco2 cell lines to investigate the overexpression of BEST4 in the biological functions of CRC and its involvement in EMT. The selection of HCT116, a human CRC cell line, was based on its relatively lower expression level of BEST4 compared to other CRC cell lines. Conversely, Caco2 is a human colon adenocarcinoma cell line that closely resembles differentiated intestinal epithelial cells and exhibits microvilli structures. Given that BEST4 serves as a marker for intestinal epithelial cells, these two cell lines were chosen for investigating the in vitro effects of overexpressing BEST4 on proliferation, clonality, invasion, migration of colon cancer tumor cells and expression of downstream EMT-related markers. Similarly, we selected the HCT-15 cell line derived from human CRC for BEST4 knockout due to its comparatively higher expression level of BEST4 among other CRC cell lines. We employed the CRISPR/Cas9 gene-editing technology to knockout BEST4 instead of utilizing shRNA for downregulating BEST4 expression, thereby limiting our selection to a single cell line.

      (3) The authors demonstrated associations between BEST4 and cell proliferation/ viability as well as migration/invasion, utilizing CRC cell lines, but it should be noted that these findings do not indicate a tumor-suppressive role of BEST4 as mentioned in line 120. Furthermore, while the authors propose that "BEST4 functions as a tumor suppressor in CRC" in line 50, there seems no supporting data to suggest BEST4 as a tumor suppressor gene.

      We apologize for these inaccurate expressions, and we have made the necessary modifications to the corresponding parts in the manuscript.

      (4) The HES4-BEST4-Twist1 axis likely plays a significant role in CRC progression via EMT but not CRC initiation. Some sentences could lead to a misunderstanding that the axis is important for CRC initiation.

      We apologize for these inaccurate expressions, and we have made the necessary modifications to the corresponding parts in the manuscript.

      (5) The authors mostly focus on the relationship of the HES4-BEST4-Twist1 axis with EMT, but their claims sometimes appear to deviate from this focus.

      We apologize for confusing the reviewer. The objectives of our study are as follows: (1) to establish the role of BEST4 in CRC growth both in vitro and in vivo; (2) to determine the underlying molecular mechanisms by which BEST4 interacts with Hes4 and Twist1, thereby regulating EMT; and (3) to investigate the correlation between BEST4 expression and prognosis of CRC. We have made the necessary modifications to the corresponding parts in the manuscript.

      (6) Some experiments do not appear to have a direct relevance to their claims. For example, the analysis using the xenograft model in Figure 2E-J is not optimal for analyzing EMT. The authors should analyze metastatic or invasive properties of the transplanted tumors if they intend to provide some supporting evidence for their claims.

      Sincerely thanks for catching this issue. The process of EMT transforms epithelial cells exhibiting a spindle fibroblast-like morphology, leading to the acquisition of mesenchymal characteristics and morphology, enabling these cells to acquire invasive and migratory abilities, with expression switching epithelial E-cadherin and Zo-1 to mesenchymal vimentin (Dongre and Weinberg, 2019)..The whole process is regulated by transcriptional factors of the Snail family and Twist1(Dongre and Weinberg, 2019). We utilized the xenograft model with overexpressed BEST4 to analyze the lysates of tumor tissue, revealing that BEST4 upregulated E-cadherin and downregulated vimentin and Twist1 (Figures 2I). These findings indicate that BEST4 inhibits EMT in vivo. Deletion of BEST4 may enable these cells to acquire invasive and migratory abilities, leading to metastasis in vivo. Therefore, we subsequently evaluated the metastatic potential of BEST4 in a CRC liver metastasis model by intrasplenically injecting HCT-15 cell lines with knockout of BEST4 (BEST4gRNA), wild-type control (gRNA), or knockout with rescue (BEST4-Rescued) into BALB/c nude mice. Our observations revealed a twofold increase in liver metastatic nodules in the absence of BEST4 compared to the control group (Fig. 2J-L). Although further in vivo experiments are required for confirmation, our research suggests a potential role for BEST4 in counteracting EMT induction in vivo.

      (7) In Figure 4H, ZO-1 and E-cad expression looks unchanged in the BEST4 KD.

      Sincerely thanks for catching this issue. We have implemented the necessary modifications to the corresponding sections in the manuscript and performed a comprehensive quantification of all Western Blot data to ensure statistically significant differences, including those presented in the supplementary file.

      (8) The in vivo and in vitro data supporting the whole transcriptome sequence analysis (Figure 5) is mostly insufficient. Including the following experiments will substantiate their claims: 1) BEST4 and HES4 immunostaining of human surgical tissue samples, 2) qPCR data of HES4, Twist1, Vimentin, etc. as shown in Figure 5C, 5D.

      Sincerely thanks for catching this issue.

      (1) Due to the substandard quality of the BEST4 antibody, we opted to evaluate the clinical significance of BEST4 in CRC by assessing mRNA results instead of protein levels using immunohistochemistry (IHC). After testing multiple antibodies for western blotting, only one (1:800; LsBio, LS-C31133) accurately indicated BEST4 protein expression while still exhibiting some non-specific bands. Consequently, we decided to transfect a HA-tagged BEST4 plasmid into the CRC cell line and used HA as a marker for BEST4 expression. Unfortunately, none of the antibodies employed for IHC were suitable as they failed to accurately distinguish between positive or negative staining for BEST4 and showed significant non-specific staining (data not shown). The challenge in detecting BEST4 protein in colorectal cancer tissues may be attributed to its low expression levels. Our findings are consistent with previous reports from the Human Protein Atlas database (https://www.proteinatlas.org/ENSG00000142959-BEST4/pathology), which also did not detect any BEST4 protein expression in colorectal cancer tissues through IHC analysis.

      (2) The qPCR data of E-cadherin, Twist1, and Vimentin mRNA expression in CRC tissue has already been published in other studies(Christou et al., 2017; Lazarova and Bordonaro, 2016; Zhu et al., 2015). It was found that E-cadherin is downregulated, while Twist1 and Vimentin are upregulated in CRC tissue compared to the adjacent normal tissues. The qPCR data of E-cadherin, Twist1, and Vimentin mRNA expression in CRC tissue has already been published in other studies(Christou et al., 2017; Lazarova and Bordonaro, 2016; Zhu et al., 2015). It was found that E-cadherin is downregulated, while Twist1 and Vimentin are upregulated in CRC tissue compared to the adjacent normal tissues. The analysis of mRNA expression data obtained from colorectal cancer samples and normal samples in the publicly available databases TCGA and GTEx also revealed a significant downregulation of _Hes_4 expression in colorectal cancer tissues, which will be our next research objective.

      (9) Some statements are inconsistent probably due to grammatical errors. (For example, some High/low may be reversed in lines 234-244.)

      We apologize for these mistakes. We have made corrections to this section in the manuscript.

      Reviewer #2 (Public Review):

      Summary:

      Using in vitro and in vivo approaches, the authors first demonstrate that BEST4 inhibits intestinal tumor cell growth and reduces their metastatic potential, possibly via downstream regulation of TWIST1.

      They further show that HES4 positively upregulates BEST4 expression, with direct interaction with BEST4 promoter region and protein. The authors further expand on this with results showing that negative regulation of TWIST1 by HES4 requires BEST4 protein, with BEST4 required for TWIST1 association with HES4. Reduction of BEST1 expression was shown in CRC tumor samples, with correlation of BEST4 mRNA levels with different clinicopathological factors such as sex, tumor stage, and lymph node metastasis, suggesting a tumor-suppressive role of BEST4 for intestinal cancer.

      Strengths:

      • Good quality western blot data.

      • Multiple approaches were used to validate the findings.

      • Logical experimental progression for readability.

      • Human patient data / In vivo murine model / Multiple cell lines were used, which supports translatability / reproducibility of findings.

      We sincerely thank Reviewer #2 for constructive feedback on this work

      Weaknesses:

      (1) Interpretation of figures and data (unsubstantiated conclusions).

      We apologize for this confusing presentation. We have made corrections to this section in the manuscript.

      (2) Figure quality.

      We apologize for the poor quality of the figures. The figure resolution was drastically reduced during the conversion of the manuscript to pdf on publisher web site. The figures have been re-uploaded and we have once again confirmed that each image has a resolution exceeding 300dpi.

      (3) Figure legends lack information.

      Sincere thanks for catching this issue. We have provided detailed figure legends including supplementary figure legends on pages 36-43 of the manuscript. We have rechecked this section and made improvements and additions.

      (4) Lacking/shallow discussion.

      We apologize for our shallow discussion. We have supplemented and improved some parts of the discussion

      (5) Requires more information for reproducibility regarding materials and methods.

      Sincere thanks for catching this issue. We have provided detailed information for reproducibility regarding materials and methods on pages 18-29; 43-47 of the manuscript. We have rechecked this section and made improvements and additions.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      We sincerely thank Reviewer #1 for constructive feedback on this work.

      Minor comments:

      (1) Line 73: "Variant 4" is not precise. The term "variant" should mean mutation in the gene or different transcription.

      We apologize for using an inaccurate expression. We have now changed Variant 4 to Bestrophin 4.

      (2) Line 78. Is it correct that BEST4+ cells coexist with Hes4+ cells?

      According to the previous study that published in Nature (Parikh et al., 2019), BEST4+ cells originate from the absorptive lineage and express the transcription factors Hes4. Additionally, we also observed the nuclear co-localization of BEST4 and Hes4 in HCT116 cells through immunofluorescence staining (Figure 3E)

      (3) Line 85. The reason "Best4 may be associated with Twist1" is unclear.

      We apologize for the lack of clarity in our previous statement. In a recent analysis utilizing single cell RNA-sequencing, it was discovered that a subset of mature colonocytes expresses BEST4 (Parikh et al., 2019). Additionally, this subset coexists with hairy/enhancer of split 4 positive (Hes4+) cells (Parikh et al., 2019). Previous research has demonstrated the antagonistic role of Hes4 in regulating Twist1 through protein-protein interaction, which governs the differentiation of bone marrow stromal/stem cell lineage (Cakouros et al., 2015). Based on these findings, we speculate that there may be an interactive regulation between BEST4/Hes4/Twist1, potentially influencing the process of cell polarity during epithelial-mesenchymal transition in colorectal cancer. We have made corrections to this section in the manuscript.

      (4) Line 87. Grammatical error (Establishing the role BEST4).

      We apologize for the grammatical error of this section. We have rectified the issue in the manuscript.

      (5) Please clarify the reason the authors do not show any data of BEST4-overexpressing Caco2 cells in Figure 2?

      We apologize for our negligence in not adding this data to in Figure 2. It has now been fully supplemented.

      (6) In line 145, the authors did not show any tumorigenic properties.

      We apologize for this confusing presentation. We have made corrections to this section in the manuscript.

      (7) Figure 3 shows 1) HES4 regulates BEST4 promotor activity, and 2) HES4 and BEST4 colocalized in nuclei, but these are very different biological processes. Please clarify how these two relate to each other.

      Trajectory analysis identifies the basic helix-loop-helix (bHLH) transcription factors Hairy/enhancer of split 4 (Hes4)-expressing colonocytes (Hes4+) in BEST4-expressing colonic epithelial lineage (BEST4+). Although they are very different biological processes, the recent identification of a heterogeneous BEST4+ and Hes4+ subgroup in a human colonic epithelial lineage (Parikh et al., 2019) led us to consider their potential role in regulating CRC progression. We firstly observed a responsive upregulation of both endogenous BEST4 mRNA and protein levels in Hes4 overexpression cells compared to the control transfectant, indicating that Hes4 is a potential upstream activator regulating BEST4 functional. We then confirmed that Hes4 interacted with BEST4, binding directly to its upstream promoter at the region of 1470-1569 bp enhancing its promoter activity as analysed by Co-IP, dual-luciferase assay and ChIP-qPCR, respectively. Essentially, they were co-localized in the nucleus, as shown in immunofluorescence staining after the transient co-transfection of Hes4 and BEST4 into HCT116, therefore indicating that BEST4 interacts with Hes4 at both transcriptional and translational levels (Figure 3; Figure 3-supplemental figure 1)

      (8) In line 182-185, please clarify the reason BEST4 mediates the inhibition of the Twist 1 promotor activity by Hes4.

      Because a step of Hes4 in committing to human bone marrow stromal/stem cell lineage-specific development is mediated by Twist1 downregulation (Cakouros et al., 2015), with evidence of direct interaction between BEST4 and Hes4 observed in HCT116, it is plausible that they could exploit Twist1 to regulate EMT. In the present study, we found that Twist1 colocalized with BEST4 in the nucleus, and their interaction destabilized Twist1 and significantly inhibited EMT induction. Hes4 caused the same effect; however, it required intermediation through BEST4. Although the mechanistic insights of their intercorrelation remain to be elucidated, the present study identified the axis of Hes4-BEST4-Twist1 governing the development of CRC, at least partially by counteracting EMT induction

      (9) In line 205, please rephrase "BEST4-mediated upstream Hes4" to be clearer.

      We apologize for this confusing presentation. We have made corrections to this section in the manuscript.

      Reviewer #2 (Recommendations For The Authors):

      We sincerely thank Reviewer #2 for constructive feedback on this work

      Major Comments:

      (1) The general quality of the figures requires improvement (text in some figures is illegible, and the resolution of the images is low) with more proofreading of the text for clarity. In addition, the resolution of the histology in Fig 2K does not allow a proper evalution of the data.

      We apologize for the poor quality of the figures. The figure resolution was drastically reduced during the conversion of the manuscript to pdf on publisher web site. The figures have been re-uploaded and we have once again confirmed that each image has a resolution exceeding 300dpi. Meanwhile, the Figure 2K was further enhanced and expanded.

      (2) While the authors show that the HES4/BEST4 complex interacts with the TWIST1 protein, they do not expand on the mechanisms underpinning the post-translational or transcriptional regulation of TWIST1. We would like the authors to prove or further speculate on the mechanisms behind this regulation in the discussion.

      Our present study showed that BEST4 inhibited EMT in conjunction with downregulation of Twist1 in both HCT116 and Caco2 CRC cell lines. A previous study has shown an antagonist role of Hes4 in regulating Twist1 via protein-protein interaction that controls the bone marrow stromal/stem cell lineage differentiation (Cakouros et al., 2015). We speculate a possible interactive regulation between Hes4/BEST4/Twist1 by which they deter the process of cell polarity during EMT in CRC. In the present study, we found that BEST4 mediates the inhibition of the Twist1 both in transcription and translation level by Hes4. Twist1 colocalized with BEST4 in the nucleus, and their interaction destabilized Twist1 and significantly inhibited EMT induction. Hes4 caused the same effect; however, it required intermediation through BEST4. The present study identified the axis of Hes4-BEST4-Twist1 governing the development of CRC, at least partially by counteracting EMT induction. We agree that further studies to elucidate mechanistic insights of their intercorrelation are needed that are beyond the scope of the current work.

      (3) The authors need to show or argue that why TWIST1 is necessary for the phenotypes observed, e.g. metastasis/proliferation.

      We apologize for the lack of clarity in articulating this question. The process of EMT transforms epithelial cells exhibiting a spindle fibroblast-like morphology, leading to the acquisition of mesenchymal characteristics and morphology, enabling these cells to acquire invasive and migratory abilities, with expression switching epithelial E-cadherin and Zo-1 to mesenchymal vimentin (Dongre and Weinberg, 2019). When diagnosed in advanced stages, EMT may occur as CRC metastasize to distal organs (Pastushenko and Blanpain, 2019; Sunlin Yong, 2021; Yeung and Yang, 2017; Zhang et al., 2021).The whole process is regulated by transcriptional factors of the Snail family and Twist1(Dongre and Weinberg, 2019). Twist1 (a basic helix-loop-helix transcription factor) reprograms EMT by repressing the expression of E-cadherin and ZO-1 (Nagai et al., 2016; Yang et al., 2004) and simultaneously inducing several mesenchymal markers, typically vimentin (Bulzico et al., 2019; Meng et al., 2018; Nagai et al., 2016; Yang et al., 2004), which is a pivotal predictor of CRC progression (Vesuna et al., 2008; Yang et al., 2004; Yusup et al., 2017; Zhu et al., 2015).Overexpression of Twist1 significantly enhances the migration and invasion capabilities of colorectal cancer cells; furthermore, it is closely associated with metastasis and poor prognosis in patients with colorectal cancer(Yusup et al., 2017; Zhu et al., 2015). We have supplemented and improved these parts of the introduction and discussion.

      (4) The authors sufficiently prove that HES4/BEST4 regulates TWIST1 downregulation, however, we believe the findings are not enough to show *direct* regulation (refer also to line 273). At least rephrasing the conclusions would be adequate, also while referring to the working model depicted in Fig. 5G.

      We apologize for this inaccurate presentation. Although the interaction may not be direct, our co-immunoprecipitation (CO-IP) results demonstrated nuclear colocalization of Twist1 and BEST4 (Figure 4D; Figure 4-supplemental figure 1A). Furthermore, their interaction destabilized Twist1 and significantly inhibited the induction of EMT. We have made corrections to this section in the manuscript.

      (5) The discussion is very short and not satisfactory; is BEST4 an evolutionary conserved protein (besides the channel region)? Any speculation on which domain(s) is(are) important for the interaction with HES4 and TWIST1? How do the findings in the current study compare with recent, potentially contradicting data indicating a pro-tumorigenic function of BEST4 for CRC, including its upregulation (and not downregulation) in malignant intestinal tissues, and activation of PI3K/AKT signaling (PMID: 35058597)?

      We apologize for our shallow discussion. We have supplemented and improved some parts of the discussion. The bestrophins are a highly conserved family of integral membrane proteins initially discovered in Caenorhabditis elegans(Sonnhammer and Durbin, 1997). Homologous sequences can be found across animals, fungi, and prokaryotes, while they are absent in protozoans or plants(Hagen et al., 2005). Conservation is primarily observed within the N-terminal 350–400 amino acids, featuring an invariant motif arginine-phenylalanine-proline (RFP) with unknown functional properties (Milenkovic et al., 2008). Mutations in this region can lead to the development of vitelliform macular dystrophy. However, the C-terminus is a potential site for protein modification and function(Marmorstein et al., 2002; Miller et al., 2019). There is currently no further literature research on the functional roles of different domains of BEST4. Although the crucial domain for the interaction with HES4 and TWIST1 is yet to be determined, requiring further investigation for clarification, our findings demonstrate that Hes4 directly binds to the upstream promoter region of BEST4 at 1470-1569 bp, thereby enhancing its promoter activity. These results provide valuable insights for future research.

      Sincere thanks for catching this publication to us. We carefully read this study and would like to point out a few things.

      a) Firstly, the study demonstrated that BEST4 expression is upregulated in clinical CRC samples, which contradicts the results of other published studies except for our own research. RNA-seq of tissue samples from 95 human individuals representing 27 different tissues was performed to determine the tissue specificity of all protein-coding genes, and the results indicated that the BEST4 gene is predominantly expressed in the colon (Fagerberg et al., 2014). In addition, BEST4 was reported to be exclusively expressed by human absorptive cells and could be induced during the process of human absorptive cell differentiation(Ito et al., 2013). Recently, the research from Simmons’s group that published in Nature further proved that human absorptive colonocytes distinctly express BEST4 by single-cell profiling of healthy human colonic epithelial cells, and is dysregulated in colorectal cancer patients(Parikh et al., 2019). Furthermore, the analysis of RNA-seq expression data obtained from colorectal cancer samples and normal samples in the publicly available databases TCGA and GTEx also revealed a significant downregulation of BEST4 expression in colorectal cancer tissues, which is consistent with our research findings. The literature above demonstrates a close relationship between BEST4 and the normal function of the human colon, and provide evidence for their loss in colorectal cancer patients.

      b) Their study showed an increased expression of BEST4 protein levels in colorectal cancer patients through Western Blot. However, the antibody they used was only suitable for IHC-P and not for Western Blot (Abcam , ab188823); . In our study, we also utilized WB technology to detect the expression of BEST4 in colorectal cancer tissues and adjacent normal tissues. The results revealed a decreased expression of BEST4 protein levels in colorectal cancer patients. The antibody we used was specifically designed for WB detection (1:800; LsBio, LS-C31133 https://www.lsbio.com/antibodies/best4-antibody-n-terminus-wb-western-ls-c31133/29602).

      c) The study demonstrated an upregulation of BEST4 protein levels in colorectal cancer patients using immunohistochemistry (IHC). However, the expression of BEST4 was assessed in colorectal cancer tissues through IHC utilizing publicly available protein expression databases such as the Human Protein Atlas. Interestingly, this analysis revealed a minimal presence of BEST4 protein in colorectal cancer tissues (https://www.proteinatlas.org/ENSG00000142959-BEST4/pathology), contradicting their research findings but aligning with our own observations.

      d) Literature based on single-cell genomics analysis reports that only OTOP2 and BEST4 genes are expressed in a subset of the normal colorectal epithelial cells but not the rest(Parikh et al., 2019). An inhibitory effect of OTOP2 on CRC has been recently shown BEST4, and the Otopetrin 2 (OTOP2), which encodes proton‐selective ion channel protein were reported to distinct expressed in normal absorptive colonocytes and colocalized with each other (Drummond et al., 2017; Ito et al., 2013; Parikh et al., 2019). OTOP2 has been recently demonstrated to have an inhibitory effect on the development of CRC via being regulated by wide-type p53(Qu et al., 2019), while the role of BEST4 in CRC is less well studied, that indicate the potential of BEST4 to inhibit colorectal cancer. The Gene set enrichment analysis (GSEA) conducted by them revealed a significant enrichment of gene signatures associated with oncogenic signaling and metastasis, such as the PI3K/Akt signaling pathway, in patients exhibiting higher BEST4 expression compared to those with lower BEST4 expression. However, our GSEA did not show any significant enrichment of the PI3K/Akt signaling pathway in patients with higher BEST4 expression compared to those with lower BEST4 expression. In contrast to their findings, our BEST4 overexpression cell line did not exhibit a significant increase in phosphorylated Akt levels. The present study concludes that our findings align with previous literature and public database analyses, providing evidence for the downregulation of BEST4 in colorectal cancer tissues and its potential as an anticancer agent. Discrepancies observed in other studies may be attributed to difference in experimental model, protocols, preparations or experimental conditions.

      Minor Comments:

      (1) Western blot data should be quantified.

      Sincere thanks for catching this point to us. We have conducted a comprehensive quantification of all the Western Blot data and included the results in the supplementary file.

      (2) Errors in labelling figures in the text should be corrected (Line 214 and more).

      We apologize for these mistakes. We have made corrections to this section in the manuscript.

      (3) The authors used the human HES4 gene, which is indicated with the incorrect nomenclature. The gene and protein nomenclature should be correctly used.

      We apologize for these mistakes. We have made corrections to this section in the manuscript.

      (4) Methods and Materials for certain assays should be further clarified; e.g transwell migration/invasion assays (reference to previous publication? transwell inserts used, etc.)

      Sincerely thanks for catching this issue. We have implemented enhancements and updates to the respective sections.

      (5) Figure 2K: Quality of histology is insufficient.

      We apologize for the poor quality of the figures. The quality of Figure 2K was further enhanced and expanded.

      (6) Figure 2K: Can the authors speculate on whether there is any increase in proliferation through BEST4-ko in HCT15 cells (with overexpression of BEST4 leading to reduced proliferation) and how this may impact the metastatic assay or engraftment/seeding onto the liver?

      Our in vitro experiment demonstrated that the ablation of BEST4 in HCT-15 cells resulted in increased cell proliferation, clonogenesis, migration and invasion (Figures 1 and Figure 1-supplemental figure 1). These findings suggest that BEST4 knockout may potentially contribute to tumor proliferation in vivo; however, further research is required for confirmation. EMT transforms epithelial cells exhibiting a spindle fibroblast-like morphology, leading to the acquisition of mesenchymal characteristics and morphology, enabling these cells to acquire invasive and migratory abilities (Dongre and Weinberg, 2019). When diagnosed in advanced stages, EMT may occur as CRC metastasize to distal organs (Pastushenko and Blanpain, 2019; Sunlin Yong, 2021; Yeung and Yang, 2017; Zhang et al., 2021).  Our study demonstrated that BEST4 inhibits EMT in colorectal cancer (CRC) both in vitro and in vivo. Conversely, ablation of BEST4 promotes EMT by upregulating the expression of EMT-related genes, thereby facilitating the metastasis of colorectal cancer cells to the liver.

      (7) Figure 2L: Authors should indicate in the figure that the BEST4-rescued is at 0 (and not blank).

      Sincerely thanks for catching this issue. We have made corrections to this section in the manuscript.

      (8) Figure 3B: Authors should introduce the usage of the new LS174T cell line in the text.

      Sincerely thanks for catching this issue. The human colorectal cancer cell line, LS174T, was selected for Hes4 knockdown due to its comparatively higher expression of Hes4 in comparison to other CRC cell lines. We have made corrections to this section in the manuscript.

      (9) Figure 3F: Why is there less FLAG in the input, compared to the IP?

      Sincerely thanks for catching this issue. Cell lysates (20 µg) were used for input, and 500ug for IP according to the manufacturer's protocols.

      (10) Figure 5F-G: the quality of the figure is not good enough for interpretation.

      Again, we apologize for poor quality of pictures due to manuscript conversion. We have made corrections to this section in the manuscript.

      (11) Table 1: Conclusions made by the authors are wrong (lines 237-239); instead "high BEST4 expression more prevalent in females" and "low BEST4 expression more prevalent among CRC patients with advanced tumor stage". And how are low and high BEST4 expressions defined (the same applies to the data in Fig. 5F)?

      We apologize for these mistakes, we set cutoff-high (50%) and cutoff-low (50%) values to split the high-expression and low-expression cohorts. We have made corrections to this section in the manuscript.

      (12) In all Figure legends, there should be an indication of the type of statistical tests that were applied, as well as information on the number of independent experiments that were performed and provided the same results

      Sincerely thanks for catching this issue. The types of statistical tests applied in the Materials and Method- Statistical analysis section are indicated. Information on the number of independent experiments used is provided in the figure legend section.

      Reference

      Bulzico, D., Pires, B.R.B., PAS, D.E.F., Neto, L.V., and Abdelhay, E. (2019). "Twist1 Correlates With Epithelial-Mesenchymal Transition Markers Fibronectin and Vimentin in Adrenocortical Tumors". Anticancer research 39, 173-175. 10.21873/anticanres.13094.

      Cakouros, D., Isenmann, S., Hemming, S.E., Menicanin, D., Camp, E., Zannetinno, A.C., and Gronthos, S. (2015). "Novel basic helix-loop-helix transcription factor hes4 antagonizes the function of twist-1 to regulate lineage commitment of bone marrow stromal/stem cells". Stem Cells Dev 24, 1297-1308. 10.1089/scd.2014.0471.

      Christou, N., Perraud, A., Blondy, S., Jauberteau, M.O., Battu, S., and Mathonnet, M. (2017). "E-cadherin: A potential biomarker of colorectal cancer prognosis". Oncol Lett 13, 4571-4576. 10.3892/ol.2017.6063.

      Dongre, A., and Weinberg, R.A. (2019). "New insights into the mechanisms of epithelial-mesenchymal transition and implications for cancer". Nature reviews. Molecular cell biology 20, 69-84. 10.1038/s41580-018-0080-4.

      Drummond, C.G., Bolock, A.M., Ma, C., Luke, C.J., Good, M., and Coyne, C.B. (2017). "Enteroviruses infect human enteroids and induce antiviral signaling in a cell lineage-specific manner". Proceedings of the National Academy of Sciences of the United States of America 114, 1672-1677. 10.1073/pnas.1617363114.

      Fagerberg, L., Hallstrom, B.M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., et al. (2014). "Analysis of the human tissue-specific expression by genome-wide integration of transcriptomics and antibody-based proteomics". Mol Cell Proteomics 13, 397-406. 10.1074/mcp.M113.035600.

      Hagen, A.R., Barabote, R.D., and Saier, M.H. (2005). "The bestrophin family of anion channels: identification of prokaryotic homologues". Molecular membrane biology 22, 291-302. 10.1080/09687860500129711.

      Ito, G., Okamoto, R., Murano, T., Shimizu, H., Fujii, S., Nakata, T., Mizutani, T., Yui, S., Akiyama-Morio, J., Nemoto, Y., et al. (2013). "Lineage-specific expression of bestrophin-2 and bestrophin-4 in human intestinal epithelial cells". PLoS One 8, e79693. 10.1371/journal.pone.0079693.

      Lazarova, D.L., and Bordonaro, M. (2016). "Vimentin, colon cancer progression and resistance to butyrate and other HDACis". Journal of cellular and molecular medicine 20, 989-993. 10.1111/jcmm.12850.

      Marmorstein, L.Y., McLaughlin, P.J., Stanton, J.B., Yan, L., Crabb, J.W., and Marmorstein, A.D. (2002). "Bestrophin interacts physically and functionally with protein phosphatase 2A". The Journal of biological chemistry 277, 30591-30597. 10.1074/jbc.M204269200.

      Meng, J., Chen, S., Han, J.X., Qian, B., Wang, X.R., Zhong, W.L., Qin, Y., Zhang, H., Gao, W.F., Lei, Y.Y., et al. (2018). "Twist1 Regulates Vimentin through Cul2 Circular RNA to Promote EMT in Hepatocellular Carcinoma". Cancer research 78, 4150-4162. 10.1158/0008-5472.Can-17-3009.

      Milenkovic, V.M., Langmann, T., Schreiber, R., Kunzelmann, K., and Weber, B.H. (2008). "Molecular evolution and functional divergence of the bestrophin protein family". BMC evolutionary biology 8, 72. 10.1186/1471-2148-8-72.

      Miller, A.N., Vaisey, G., and Long, S.B. (2019). "Molecular mechanisms of gating in the calcium-activated chloride channel bestrophin". eLife 8. 10.7554/eLife.43231.

      Nagai, T., Arao, T., Nishio, K., Matsumoto, K., Hagiwara, S., Sakurai, T., Minami, Y., Ida, H., Ueshima, K., Nishida, N., et al. (2016). "Impact of Tight Junction Protein ZO-1 and TWIST Expression on Postoperative Survival of Patients with Hepatocellular Carcinoma". Digestive diseases (Basel, Switzerland) 34, 702-707. 10.1159/000448860.

      Parikh, K., Antanaviciute, A., Fawkner-Corbett, D., Jagielowicz, M., Aulicino, A., Lagerholm, C., Davis, S., Kinchen, J., Chen, H.H., Alham, N.K., et al. (2019). "Colonic epithelial cell diversity in health and inflammatory bowel disease". Nature 567, 49-55. 10.1038/s41586-019-0992-y.

      Pastushenko, I., and Blanpain, C. (2019). "EMT Transition States during Tumor Progression and Metastasis". Trends in cell biology 29, 212-226. 10.1016/j.tcb.2018.12.001.

      Qu, H., Su, Y., Yu, L., Zhao, H., and Xin, C. (2019). "Wild-type p53 regulates OTOP2 transcription through DNA loop alteration of the promoter in colorectal cancer". FEBS open bio 9, 26-34. 10.1002/2211-5463.12554.

      Sonnhammer, E.L., and Durbin, R. (1997). "Analysis of protein domain families in Caenorhabditis elegans". Genomics 46, 200-216. 10.1006/geno.1997.4989.

      Sunlin Yong, Z.W., Tang Yuan, Chuang Cheng, Dan Jiang (2021). "Comparison of MMR protein and Microsatellite Instability Detection in Colorectal Cancer and Its Clinicopathological Features Analysis". Journal of Medical Research 50, 61-66. 10.11969/j.issn.1673-548X.2021.05.015

      Vesuna, F., van Diest, P., Chen, J.H., and Raman, V. (2008). "Twist is a transcriptional repressor of E-cadherin gene expression in breast cancer". Biochem Biophys Res Commun 367, 235-241. 10.1016/j.bbrc.2007.11.151.

      Yang, J., Mani, S.A., Donaher, J.L., Ramaswamy, S., Itzykson, R.A., Come, C., Savagner, P., Gitelman, I., Richardson, A., and Weinberg, R.A. (2004). "Twist, a master regulator of morphogenesis, plays an essential role in tumor metastasis". Cell 117, 927-939. 10.1016/j.cell.2004.06.006.

      Yeung, K.T., and Yang, J. (2017). "Epithelial-mesenchymal transition in tumor metastasis". Molecular oncology 11, 28-39. 10.1002/1878-0261.12017.

      Yusup, A., Huji, B., Fang, C., Wang, F., Dadihan, T., Wang, H.J., and Upur, H. (2017). "Expression of trefoil factors and TWIST1 in colorectal cancer and their correlation with metastatic potential and prognosis". World journal of gastroenterology 23, 110-120. 10.3748/wjg.v23.i1.110.

      Zhang, N., Ng, A.S., Cai, S., Li, Q., Yang, L., and Kerr, D. (2021). "Novel therapeutic strategies: targeting epithelial-mesenchymal transition in colorectal cancer". The Lancet. Oncology 22, e358-e368. 10.1016/s1470-2045(21)00343-0.

      Zhu, D.J., Chen, X.W., Zhang, W.J., Wang, J.Z., Ouyang, M.Z., Zhong, Q., and Liu, C.C. (2015). "Twist1 is a potential prognostic marker for colorectal cancer and associated with chemoresistance". American journal of cancer research 5, 2000-2011.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer 1:

      One major issue arises in Figure 4, the recording of VLPO Ca2+ activity. In Lines 211-215, they stated that they injected AAV2/9-DBH-GCaMP6m into the VLPO, while activating LC NE neurons. As they claimed in line 157, DBH is a specific promoter for NE neurons. This implies an attempt to label NE neurons in the VLPO, which is problematic because NE neurons are not present in the VLPO. This raises concerns about their viral infection strategy since Ca activity was observed in their photometry recording. This means that DBH promoter could randomly label some non-NE neurons. Is DBH promoter widely used? The authors should list references. Additionally, they should quantify the labeling efficiency of both DBH and TH-cre throughout the paper.

      In Figure 5, we found that the VLPO received the noradrenergic projection from LC, indicating the recorded Ca2+ activity may come from the axon fibers corresponding to the projection. Similarly, Gunaydin et al. (2014) demonstrated that fiber photometry can be used to selectively record from neuronal projection.

      We appreciate the reviewer's insightful suggestion to elaborate on the DBH promoter, we have now expanded our discussion to address the DBH (pg. 18): “DBH (Dopamine-beta-hydroxylase), located in the inner membrane of noradrenergic and adrenergic neurons, is an enzyme that catalyzes the conversion of dopamine to norepinephrine, and therefore plays an important role in noradrenergic neurotransmission. DBH is a marker of noradrenergic neurons. Zhou et al. (2020) clarified the probe specifically labeled noradrenergic neurons by immunolabeling for DBH. Recently, DBH promoter have been used in several studies (e.g., Han et al., 2024; Lian et al., 2023). The DBH-Cre mice are widely used to specifically labeled noradrenergic neurons (e.g., Li et al., 2023; Breton-Provencher et al., 2022; Liu et al., 2024). It is difficult to distinguish the role of NE or DA neurons when using the TH promoter in VLPO. Therefore, we used DBH promoter with more specific labeling. LC is the main noradrenergic nucleus of the central nervous system. In our study, we injected rAAV-DBH-GCaMP6m-WPRE (Figure 2 and 8) and rAAV-DBH-EGFP-S'miR-30a-shRNA GABAA receptor)-3’-miR30a-WPRES (Figure 9) into the LC. The results showed that DBH promoter could specifically label noradrenergic neurons in the LC, while non-specific markers outside the LC were almost absent.”

      As suggested, we have quantified the labeling efficiency of both DBH and TH-cre throughout the revised manuscript (Fig.2D; Fig.3D, N-O; Fig.4E-F, J, L; Fig.5E, L; Fig.6L, S, X; Fig.7G).

      A similar issue arises with chemogenetic activation in Fig. 5 L-R, the authors used TH-cre and DIO-Gq virus to label VLPO neurons. Were they labelling VLPO NE or DA neurons for recording? The authors have to clarify this.

      As previously addressed in response to Comment #1, we agree that it is difficult to distinguish the role of NE or DA neurons when using the TH promoter in the VLPO. Therefore, we injected the mixture of DBH-Cre-AAV and AAV-EF1a-DIO-hChR2(H134R)-eYFP/AAV-Ef1a-DIO-hM3Dq-mCherry viruses into bilateral LC and AAV-EF1a-DIO-hChR2(H134R)-eYFP/AAV-Ef1a-DIO-hM3Dq-mCherry virus into bilateral VLPO. Moreover, we quantified the labeling efficiency of DBH in the LC to demonstrate that this promoter can specifically label NE neurons (Fig. 5). Importantly, these corrections did not alter the outcomes of our results. Both photogenetic and chemogenetic activation of LC-NE terminals in the VLPO can effectively promote midazolam recovery (Fig. 5G, N).

      Another related question pertains to the specificity of LC NE downstream neurons in the VLPO. For example, do they preferentially modulate GABAergic or glutamatergic neurons?

      Our study primarily aimed to explore the role of the LC-VLPO NEergic neural circuit in modulating midazolam recovery. We acknowledge that our evidence for the role of LC NE downstream neurons in the VLPO, derived from activation of LC-NE terminals and pharmacological intervention in the VLPO (Fig.5, Fig.6, Fig.8, Fig.9) is limited. Accordingly, we now present the VLPO’s role as a promising direction for future research in the limitation section of our revised manuscript: “This study shows that the LC-VLPO NEergic neural circuit plays an important role in modulating midazolam recovery. However, the specificity of LC NE downstream neurons in the VLPO is not explained in this paper, which is our next research direction, VLPO neurons and their downstream regulatory mechanisms may be involved in other nervous systems except the NE nervous system, and the deeper and more complex mechanisms need to be further investigated.”

      In Figure 1A-D, in the measurement of the dosage-dependent effect of Mida in LORR, were they only performed one batch of testing? If more than one batch of mice were used, error bar should be presented in 1B. Also, the rationale of testing TH expression levels after Mid is not clear. Is TH expression level change related to NE activation specifically? If so, they should cite references.

      As recommended, we have supplemented error bar and modified the graph of LORR’s rate in the revised manuscript. (Fig. 1A-B; Fig. 9G-H).

      We agree that the use of TH as a marker of NE activation is controversial, so in the revised manuscript, we directly determined central norepinephrine content to reflect the change of NE activity after midazolam administration (Fig. 1D).

      Regarding the photometry recording of LC NE neurons during the entire process of midazolam injection in Fig. 2 and Fig. 4, it is unclear what time=0 stands for. If I understand correctly, the authors were comparing spontaneous activity during the four phases. Additionally, they only show traces lasting for 20s in Fig. 2F and Fig. 4L. How did the authors select data for analysis, and what criteria were used? The authors should also quantify the average Ca2+ activity and Ca2+ transient frequency during each stage instead of only quantifying Ca2+ peaks. In line 919, the legend for Figure 2D, they stated that it is the signal at the BLA; were they also recorded from the BLA?

      In this study, we used optical fiber calcium signal recording, which is a fluorescence imaging based on changes in calcium. The fluorescence signal is usually divided into different segments according to the behavior, and the corresponding segments are orderly according to the specific behavior event as the time=0. The mean calcium fluorescence signal in the time window 1.5s or 1s before the event behavior is taken as the baseline fluorescence intensity (F0), and the difference between the fluorescence intensity of the occurrence of the behavior and the baseline fluorescence intensity is divided by the difference between the baseline fluorescence intensity and the offset value. That is, the value ΔF/F0 represents the change of calcium fluorescence intensity when the event occurs. The results of the analysis are commonly represented by two kinds of graphs, namely heat map and event-related peri-event plot (e.g., Cheng et al., 2022; Gan-Or et al., 2023; Wei et al., 2018). In Fig. 2, the time points for awake, midazolam injection, LORR and RORR in mice were respectively selected as time=0, while in Fig. 4, RORR in mice was selected as time=0. The selected traces lasting for 20s was based on the length of a complete Ca2+ signal. We have explained the Ca2+ recording experiment more specifically in the figure legends and methods sections of our revised manuscript.

      To the BLA, we sincerely apologize for our carelessness, the signal we recorded were from the LC rather than the BLA. We have carefully checked and corrected similar problems in the revised manuscript.

      Reviewer 2:

      In figure legends, abbreviations in figure should be supplemented as much as possible. For example, "LORR" in Figure 1.

      As suggested, we have supplemented abbreviations in figure as much as possible in the revised manuscript.

      Additional recommendations:

      The main conceptual issue in the paper is the inflation of the conclusion regarding the mechanism of sedation induced by midazolam. The authors did not reveal the full mechanism of this but rather the relative contribution of NE system. Several conclusions in the text should be edited to take into account this starting from the title. I think the following examples are more appropriate: "NE contribution to rebooting unconsciousness caused by midazolam' or 'NE contribution to reverse the sedation induced by midazolam'.

      As suggested, we have moderated the assertions about the mechanism of sedation induced by midazolam in several conclusions starting from the title (Line 1,125,150,169,202,237,482), to present a more measured interpretation in the manuscript.

      Line 178-179, the authors state 'these suggest that intranuclear ... suppresses recovery from midazolam administration'. In fact, this intervention prolonged or postponed recovery from midazolam.

      In our revised manuscript, we have corrected this inappropriate term (Line 178).

      Pharmacology part (page 12) that aimed to pinpoint which NE receptor is implicated would suffer from specificity issues.

      In relation to the specificity issue, the focus on VLPO might be rational but again other areas are most likely involved given the pharmacological actions of midazolam.

      In the revised manuscript, we have discussed those specificity issues of NE receptor and areas involved throughout the midazolam-induced altered consciousness: “In addition, given the pharmacological actions of midazolam, other areas may also be involved. Current studies suggest that the neural network involved in the recovery of consciousness consists of the prefrontal cortex, basal forebrain, brain stem, hypothalamus and thalamus. The role of these regions in midazolam recovery remains to be further investigated. Therefore, we will apply more specific experimental methods to determine the importance of LC-VLPO NEergic neural circuit and related NE receptors in the midazolam recovery, and conduct further studies on other relevant brain neural regions, hoping to more fully elucidate the mechanism of midazolam recovery in the future”.

      Line 274, the authors used 'inhibitory EEG activity'. what does it mean? a description of which rhythm-related power density is affected would be more objective.

      Example of conclusion inflation: in line 477, the word 'contributes' is better than 'mediates' if the specificity issue is taken into account.

      As suggested, we have improved our expression of words in our revised manuscript (pg. 13-14).

      References

      Gunaydin LA, Grosenick L, Finkelstein JC, et al. Natural neural projection dynamics underlying social behavior. Cell. 2014;157(7):1535-1551. doi:10.1016/j.cell.2014.05.017

      Zhou N, Huo F, Yue Y, Yin C. Specific Fluorescent Probe Based on "Protect-Deprotect" To Visualize the Norepinephrine Signaling Pathway and Drug Intervention Tracers. J Am Chem Soc. 2020;142(41):17751-17755. doi:10.1021/jacs.0c08956

      Han S, Jiang B, Ren J, et al. Impaired Lactate Release in Dorsal CA1 Astrocytes Contributed to Nociceptive Sensitization and Comorbid Memory Deficits in Rodents. Anesthesiology. 2024;140(3):538-557. doi:10.1097/ALN.0000000000004756

      Lian X, Xu Q, Wang Y, et al. Noradrenergic pathway from the locus coeruleus to heart is implicated in modulating SUDEP. iScience. 2023;26(4):106284. Published 2023 Feb 27. doi:10.1016/j.isci.2023.106284

      Li C, Sun T, Zhang Y, et al. A neural circuit for regulating a behavioral switch in response to prolonged uncontrollability in mice. Neuron. 2023;111(17):2727-2741.e7. doi:10.1016/j.neuron.2023.05.023

      Breton-Provencher V, Drummond GT, Feng J, Li Y, Sur M. Spatiotemporal dynamics of noradrenaline during learned behaviour. Nature. 2022;606(7915):732-738. doi:10.1038/s41586-022-04782-2

      Liu Q, Luo X, Liang Z, et al. Coordination between circadian neural circuit and intracellular molecular clock ensures rhythmic activation of adult neural stem cells. Proc Natl Acad Sci U S A. 2024;121(8):e2318030121. doi:10.1073/pnas.2318030121

      Cheng J, Ma X, Li C, et al. Diet-induced inflammation in the anterior paraventricular thalamus induces compulsive sucrose-seeking. Nat Neurosci. 2022;25(8):1009-1013. doi:10.1038/s41593-022-01129-y

      Gan-Or B, London M. Cortical circuits modulate mouse social vocalizations. Sci Adv. 2023;9(39):eade6992. doi:10.1126/sciadv.ade6992

      Wei YC, Wang SR, Jiao ZL, et al. Medial preoptic area in mice is capable of mediating sexually dimorphic behaviors regardless of gender. Nat Commun. 2018;9(1):279. Published 2018 Jan 18. doi:10.1038/s41467-017-02648-0

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This is a well-written and detailed manuscript showing important results on the molecular profile of 4 different cohorts of female patients with lung cancer.

      The authors conducted comprehensive multi-omic profiling of air-pollution-associated LUAD to study the roles of the air pollutant BaP. Utilizing multi-omic clustering and mutation-informed interface analysis, potential novel therapeutic strategies were identified.

      Strengths:

      The authors used several different methods to identify potential novel targets for therapeutic interventions.

      Weaknesses:

      Statistical test results need to be provided in comparisons between cohorts.

      We appreciate your recognition and valuable suggestions.. We have revised statistical test results in the panels including: Fig. 3b, e and g.

      Reviewer #2 (Public Review):

      Summary:

      Zhang et al. performed a proteogenomic analysis of lung adenocarcinoma (LUAD) in 169 female never-smokers from the Xuanwei area (XWLC) in China. These analyses reveal that XWLC is a distinct subtype of LUAD and that BaP is a major risk factor associated with EGFR G719X mutations found in the XWLC cohort. Four subtypes of XWLC were classified with unique features based on multi-omics data clustering.

      Strengths:

      The authors made great efforts in performing several large-scale proteogenomic analyses and characterizing molecular features of XWLCs. Datasets from this study will be a valuable resource to further explore the etiology and therapeutic strategies of air-pollution-associated lung cancers, particularly for XWLC.

      Weaknesses:

      (1) While analyzing and interpreting the datasets, however, this reviewer thinks that authors should provide more detailed procedures of (i) data processing, (ii) justification for choosing methods of various analyses, and (iii) justification of focusing on a few target gene/proteins in the datasets for further validation in the main text.

      We appreciate your valuable feedback. In response to the suggestions for enhancing the manuscript's clarity, we have provided more detailed procedures in the main text and methods sections.

      (2) Importantly, while providing the large datasets, validating key findings is minimally performed, and surprisingly there is no interrogation of XWLC drug response/efficacy based on their findings, which makes this manuscript descriptive and incomplete rather than conclusive. For example, testing the efficacy of XWLC response to afatinib combined with other drugs targeting activated kinases in EGFR G719X mutated XWLC tumors would be one way to validate their datasets and new therapeutic options.

      We appreciate your suggestion. In reference to testing the efficacy of XWLC response to afatinib combined with drugs targeting kinases, we have planned to establish PDX and organoid models to validate the effectiveness of our therapeutic approach. Due to the extended timeframe required, we intend to present these results in a subsequent study.

      (3) The authors found MAD1 and TPRN are novel therapeutic targets in XWLC. Are these two genes more frequently mutated in one subtype than the other 3 XWLC subtypes? How these mutations could be targeted in patients?

      Thank you for your question. We have investigated the TPRN and MAD1 mutations in our dataset, identifying five TPRN mutations and eight MAD1 mutations. Among the TPRN mutations, XWLC_0046 and XWLC_0017 belong to the MCII subtype, XWLC_0012 belongs to the MCI subtype, and the subtype of the other three samples is undetermined, resulting in mutation frequencies of 1/16, 2/24, 0/15, and 0/13, respectively. Similarly, for the MAD1 mutations, XWLC_0115, XWLC_0021, and XWLC_0047 belong to the MCII subtype, XWLC_0055 containing two mutations belongs to the MCI subtype, and the subtype of the other three samples is undetermined, resulting in mutation frequencies of 1/16, 3/24, 0/15, and 0/13 across subtypes, respectively. Fisher’s test did not reveal significant differences between the subtypes.

      For targeting novel therapeutic targets such as MAD1 and TPRN, we propose a multi-step approach. Firstly, we advocate for conducting functional in vivo and in vitro experiments to verify their roles during cancer progression. Secondly, we suggest conducting small molecule drug screening based on the pharmacophore of these proteins, which may lead to the identification of potential therapeutic drugs. Lastly, we recommend testing the efficacy of these drugs to further validate their potential as effective treatments.

      (4) In Figures 2a and b: while Figure 2a shows distinct genomic mutations among each LC cohort, Figure 2b shows similarity in affected oncogenic pathways (cell cycle, Hippo, NOTCH, PI3K, RTK-RAS, and WNT) between XWLC and TNLC/CNLC. Considering that different genomic mutations could converge into common pathways and biological processes, wouldn't these results indicate commonalities among XWLC, TNLC, and CNLC? How about other oncogenic pathways not shown in Figure 2b?

      Thank you for your question. Based on the data presented in Fig. 2a, which encompasses all genomic mutations, it appears that the mutation landscape of XWLC bears the closest resemblance to TSLC (Fig. 2a). However, when considering oncogenic pathways (Fig. 2b) and genes (Fig. 2c), there is a notable disparity between the two cohorts. These findings suggest that while XWLC and TSLC exhibit similarities in terms of genomic mutations, they possess distinct characteristics in terms of oncogenic pathways and genes.

      Regarding the oncogenic signaling pathways, we referred to ten well-established pathways identified from TCGA cohorts. These members of oncogenic pathways are likely to serve as cancer drivers (functional contributors) or therapeutic targets, as highlighted by Sanchez-Vega et al. in 2018(Sanchez-Vega et al., 2018).

      (5) In Figure 2c, how and why were the four genes (EGFR, TP53, RBM10, KRAS) selected? What about other genes? In this regard, given tumor genome sequencing was done, it would be more informative to provide the oncoprints of XWLC, TSLC, TNLC, and CNLC for complete genomic alteration comparison.

      Thank you for your question and good suggestion. Building upon our previous study (Zhang et al., 2021), we found that EGFR, TP53, RBM10, and KRAS were the top mutated genes in Xuanwei lung cancer cohorts. Furthermore, we have included the mutation frequency of cancer driver genes (Bailey et al., 2018) across XWLC, TSLC, TNLC, and CNLC in Supplementary Table 2b.

      (6) Supplementary Table 11 shows a number of mutations at the interface and length of interface between a given protein-protein interaction pair. Such that, it does not provide what mutation(s) in a given PPI interface is found in each LC cohort. For example, it fails to provide whether MAD1 R558H and TPRN H550Q mutations are found significantly in each LC cohort.

      We appreciate your careful review. In Supplementary Table 11, we have provided significant onco_PPI data for each LC cohort, focusing on enriched mutations at the interface of two proteins. Our emphasis lies on onco_PPI rather than individual mutations, as any mutation occurring at the interface could potentially influence the function of the protein complex. Thus, our Supplementary Table 11 exclusively displays the onco_PPI rather than mutations. MAD1 R558H and TPRN H550Q were identified through onco_PPI analysis, and subsequent extensive literature research led us to focus specifically on these mutations.

      (7) Figure 7c and d are simulation data not from an actual binding assay. The authors should perform a biochemical binding assay with proteins or show that the mutation significantly alters the interaction to support the conclusion.

      We appreciate your suggestion. The relevant experiments are currently in progress, and we anticipate presenting the corresponding data in a subsequent study.

      Reviewer #3 (Public Review):

      Summary:

      The manuscript from Zhang et al. utilizes a multi-omics approach to analyze lung adenocarcinoma cases in female never smokers from the Xuanwei area (XWLC cohort) compared with cases associated with smoking or other endogenous factors to identify mutational signatures and proteome changes in lung cancers associated with air pollution. Mutational signature analysis revealed a mutation hotspot, EGFR-G719X, potentially associated with BaP exposure, in 20% of the XWLC cohort. This correlated with predicted MAPK pathway activations and worse outcomes relative to other EGFR mutations. Multi-omics clustering, including RNA-seq, proteomics, and phosphoproteomics identified 4 clusters with the XWLC cohort, with additional feature analysis pathway activation, genetic differences, and radiomic features to investigate clinical diagnostic and therapeutic strategy potential for each subgroup. The study, which nicely combines multi-modal omics, presents potentially important findings, that could inform clinicians with enhanced diagnosis and therapeutic strategies for more personalized or targeted treatments in lung adenocarcinoma associated with air pollution. The authors successfully identify four distinct clusters with the XWLC cohort, with distinct diagnostic characteristics and potential targets. However, many validating experiments must be performed, and data supporting BaP exposure linkage to XWLC subtypes is suggestive but incomplete to conclusively support this claim. Thus, while the manuscript presents important findings with the potential for significant clinical impact, the data presented are incomplete in supporting some of the claims and would benefit from validation experiments.

      Strengths:

      Integration of omics data from multimodalities is a tremendous strength of the manuscript, allowing for cross-modal comparison/validation of results, functional pathway analysis, and a wealth of data to identify clinically relevant case clusters at the transcriptomic, translational, and post-translational levels. The inclusion of phosphoproteomics is an additional strength, as many pathways are functional and therefore biologically relevant actions center around activation of proteins and effectors via kinase and phosphatase activity without necessarily altering the expression of the genes or proteins.

      Clustering analysis provides clinically relevant information with strong therapeutic potential both from a diagnostic and treatment perspective. This is bolstered by the individual microbiota, radiographic, wound healing, outcomes, and other functional analyses to further characterize these distinct subtypes.

      Visually the figures are well-designed and presented and for the most part easy to follow. Summary figures/histograms of proteogenomic data, and specifically highlighted genes/proteins are well presented.

      Molecular dynamics simulations and 3D binding analysis are nice additions.

      While I don't necessarily agree with the authors' interpretation of the microbiota data, the experiment and results are very interesting, and clustering information can be gleaned from this data.

      Weaknesses:

      (1) Statistical methods for assessing significance may not always be appropriate.

      We appreciate your suggestion. We have revised statistical test results in the panels including: Fig. 3b,e and g.

      (2) Necessary validating experiments are lacking for some of the major conclusions of the paper.

      Thank you for raising this point. However, we respectfully choose not to comment on this matter at present.

      (3) Many of the conclusions are based on correlative or suggestive results, and the data is not always substantive to support them.

      Thank you for raising this point. However, we respectfully choose not to comment on this matter at present.

      (4) Experimental design is not always appropriate, sometimes lacking necessary controls or large disparity in sample sizes.

      Thank you for raising this point. However, we respectfully choose not to comment on this matter at present.

      (5) Conclusions are sometimes overstated without validating measures, such as in BaP exposure association with the identified hotspot, kinase activation analysis, or the EMT function.

      Thank you for raising this point. However, we respectfully choose not to comment on this matter at present.

      Reviewer #1 (Recommendations For The Authors):

      (1) Please provide a justification for why only females were included in the study. I am concerned that the results obtained in this study can not be generalized as only females were included.

      We appreciate your suggestion. Lung cancer in never smokers (LCINS) accounts for approximately 25% of lung cancer cases (15% of lung cancer in men and 53% in women) (Parkin et al., 2005). Currently, the etiology and mechanisms of LCINS are not clear. Globally, LCINS shows remarkable gender and geographic variations, occurring more frequently among Asian women (Bray et al., 2018). Indoor coal burning for heating and cooking has been implicated as a risk factor for Chinese women, as they spend more time indoors (Mumford et al., 1987). Among men, the proportion of never smokers is lower, with less regional variation, and lung cancer in males is frequently caused by smoking. Thus, to better reveal the etiology and molecular mechanisms of LCINS, we collected data exclusively from female LCINS patients in the Xuanwei area, excluding potential confounding factors such as hormonal or smoking status. Our study specifically aims to uncover the etiology and mechanisms of LCINS in female patients, with future research planned to verify whether our conclusions can be generalized to LCINS in male patients.

      (2) "Therefore, the XWLC and TSLC cohorts are more explicitly influenced by environmental carcinogens, while the TNLC and CNLC cohorts may be more affected by age or endogenous risk factors." This statement in the results (starting line 142) does not have adequate support from the results. First, the average age in the 4 cohorts does not seem to be very different to me based on Figure 1b. if they are different, please provide statistical test results. Please make sure this statement is supported by other results, otherwise, I would recommend excluding it from the manuscript.

      We appreciate your suggestion. To gain biological insights, we frequently associate mutational signatures with factors such as age, defective DNA mismatch repair, or environmental exposures. These remain associations rather than causation. Thus, we agree with the suggestion to weaken the conclusion as follows:

      “Generally, exposure to tobacco smoking carcinogens (COSMIC signature 4) and chemicals such as BaP (Kucab signatures 49 and 20) were identified as the most significant contributing factors in both the XWLC and TSLC cohorts (Fig. 1f and 1g). In contrast, defective DNA mismatch repair (COSMIC signature ID: SBS6) was identified as the major contributor in both the TNLC and CNLC cohorts (Fig. 1h and 1i), with no potential chemicals identified based on signature similarities. Therefore, the XWLC and TSLC cohorts appear to be more explicitly associated with environmental carcinogens, while the TNLC and CNLC cohorts may be more associated with defective DNA mismatch repair processes.”

      (3) Please provide statistical test results in this subsection "The EGFR-G719X mutation, which is a hotspot associated with BaP exposure, possesses distinctive biological features " (Line 203) showing that the number of G719X is significantly different in XWLC.

      We appreciate your suggestion. Two-sided Fisher’s test was used to calculate p-values, which are labeled in Figure 3b.

      (4) "Analysis of overall survival and progression-free interval (PFI) revealed that patients with the G719X mutation had worse outcomes compared to other EGFR mutation subtypes " This statement (starting Line 232) should be supported by literature data.

      We appreciate your suggestion.

      In the Watanabe et al. post-hoc analysis, patients with the G719 mutation had significantly shorter OS with gefitinib compared to patients with the common mutations (Watanabe et al., 2014). We revised the sentences as following:

      “Analysis of overall survival and progression-free interval (PFI) revealed that patients with the G719X mutation had worse outcomes compared to other EGFR mutation subtypes (Fig. 3j and 3k) which was consistent with a previous study(Watanabe et al., 2014).”

      (5) I would suggest changing this statement to a "suggestion" as there is no experimental support for this, and mentioning that this requires further experimental validation with the suggested drugs "Therefore, a promising approach to overcome resistance in tumors with this mutation could involve combining afatinib, which targets activated EGFR, with FDA-approved drugs that specifically target the activated kinases associated with G719X. " (Line 260).

      We appreciate your suggestion. We change the sentences as following:

      "Therefore, we propose a potential approach to overcoming resistance in tumors with this mutation, which could involve combining afatinib, targeting activated EGFR, with FDA-approved drugs that specifically target the activated kinases associated with G719X. "

      (6) It is not clear to me how PPIs were integrated with missense. Please clarify the method.

      We appreciate your suggestion. To identify interactions enriched with missense mutations, we constructed mutation-associated protein–protein interactomes (PPIs). Initially, we downloaded protein-protein interactomes from Interactome INSIDER (v.2018.2) (Meyer et al., 2018). Subsequently, we identified interfaces carrying missense mutations by mapping mutation sites to PPI interface genomic coordinates using bedtools (v2.25.0)(Quinlan and Hall, 2010). Finally, we defined oncoPPI as those PPIs significantly enriched in interface mutations in either of the two protein-binding partners across individuals. For more details, please refer to the methods sections “Building mutation-associated protein–protein interactomes” and “Significance test of PPI interface mutations.”

      Reviewer #2 (Recommendations For The Authors):

      Regarding the tumor microbiota composition, it is not clear what the significance of these results would be. Are the specific microbiota associated with MC-IV more pathogenic than other species found in other subtypes? What are the unique features of these MC-IV microbiota? If these are difficult to address, this section could be removed from the manuscript.

      We appreciate your suggestion. This section is removed from the manuscript.

      Regarding the radiomic data section (Figure 6d and Extended Figure 6d), more description about the eight and five features (that are different between MC-II and others) would be helpful to better understand the importance and significance of these data.

      We appreciate your suggestion. We have added the description as following: “Features such as median and mean reflect average gray level intensity and Idmn and Gray Level Non-Uniformity measure the variability of gray-level intensity values in the image, with a higher value indicating greater heterogeneity in intensity values. These results suggest a denser and more heterogeneous image in the MC-II subtype.”

      Other minor comments:

      (1) If EGFR G719X is a known hotspot mutation associated with BaP, please cite previous literature.

      We appreciate your suggestion. Upon careful retrieval using "G719X" and "BaP" as keywords, we did not find previous literature discussing G719X as a known hotspot mutation associated with BaP.

      (2) In Figure 1d, it should be clearly written in the legend that tumor (T) and normal (N) tissue were analyzed.

      We appreciate your suggestion. We have clarified the figure legend of Figure 1d.

      (3) In Figure 1m, it is not obvious that EGFR pY1173 and pY1068 are more abundant in the Bap+S9 sample. Total EGFR bands are very faint. These western blots should be repeated and quantified.

      We appreciate your suggestion. We have removed Fig. 1m. After identifying the antibody with satisfactory performance, we will provide the revised results.

      (4) In Figure 2d, aren't the EGFR E746__A750del mutations more frequently found in CNLC, TSLC, and TNLC? (which is opposite to what the authors wrote in the text).

      We appreciate your suggestion. This mistake has been corrected.

      (5) In Figure 7f-i and Ext Figure 8, Does "CK" mean empty vector control? Then, it would be changed to "EV".

      We appreciate your suggestion. This mistake has been corrected.

      Reviewer #3 (Recommendations For The Authors):

      Methods:

      While previous work was referenced, a description of proteomics methods should still include: instrumentation, acquisition method, all software packages used, method for protein identification, method for protein quantification, how FDR was maintained for identification/quantification, definition of differentially expressed proteins, whether multiple testing correction was performed and if so what method.

      We appreciate your suggestion. We revised the description of label-free mass spectrometry methods accordingly.

      The paper would greatly benefit from brief methodological explanations throughout, as all methods are currently exclusively found in the supplementary information. This severely hampers the readability of the manuscript.

      Thank you for raising this point. However, we respectfully choose not to comment on this matter at present.

      Suggestions Throughout

      The paper would greatly benefit from proofreading/editing

      Line 157-158/Figure 1J for CYP1A1 displays protein concentrations while Figure 1K for AhR shows mRNA. Why this discrepancy? It would be preferable to show both mRNA and protein levels for both CYP1A1 and AhR. Also, there is a large discrepancy in the "n" between the normal and tumor groups, which makes the statistical comparison challenging. The AhR data is therefore unconvincing, and additional protein data is suggested. Thus the claim of significantly elevated AhR and CYP1A1 levels in tumors is not sufficiently supported and requires further investigation, both mRNA and protein, and with similarly sized sample groups.

      We appreciate your suggestion. We have thoroughly edited the revised manuscript, with all changes marked accordingly. Compared to mRNA level assessment, protein abundance is a better indicator of gene expression. Therefore, we reanalyzed the protein level of AhR for comparison and found no significant differences (Figure 1k). Additionally, the samples sequenced by mRNA-seq were not entirely consistent with those sequenced by label-free proteomics. The samples analyzed by different methods are shown in Figure 1d.

      Line 159 Figure 1I There is no control for the data serum data presented here. What are the serum levels for individuals not residing in the Xuanwei? It is unclear whether this represents elevated BPDE serum levels without appropriate controls. Thus nothing insightful can be derived from this data.

      We appreciate your suggestion. We have deleted the results concerning BPDE serum detection in the revised manuscript.

      Line 164 The statement "sites such as Y1173 and Y1068 of EGFR were more phosphorylated in BaP treated cells" is not sufficiently supported by the presented data and cannot be made. Figure 1M has no quantitation, no indication of "n" or whether this represents a single experiment or one validated with repeating. The western blot is also cropped with no indication of molecular weight or antibody specificity. This data is NOT convincing. The antibody signal is very weak, and not convincing with cropped blots. An updated figure, with an uncropped blot, and quantitation with multiple n's and statistical comparison is required. I am not sure the Wilcoxon rank sum test is appropriate to test significance in j-l. The null hypothesis should not be equal medians but equal means based on the experimental design.

      We appreciate your suggestion. We have removed Fig. 1m. After identifying the antibody with satisfactory performance, we will provide the revised results.

      Line 181 phrase "significant differences" should not be used unless making a claim about statistical significance.

      We appreciate your suggestion. We change “significant differences” to “noticeable differences”.

      Line 197: "The blood serum assay provided support..." As noted above this claim is not sufficiently supported by the presented data and requires more complete investigation.

      We appreciate your suggestion. This conclusion has been deleted in the revised manuscript.

      Line 219: Requires proofreading/editing.

      We appreciate your suggestion. We have thoroughly edited the revised manuscript, with all changes marked accordingly.

      Line 220: appears to have a typo and should read GGGC>GTGC

      We appreciate your suggestion. This mistake has been corrected in the revised manuscript.

      Line 223/224 Figure 3e-h. Again there is a large disparity between the n's of each group. Despite the WT having the highest frequency in the XWLC study population, it has only n=5 when comparing the protein and phosphosite for MAPKs. There is also no explanation for what the graph symbols indicate, what statistical test was performed to determine the statistical significance of the presented differences, and between which specific groups that significance exists. Thus, it is challenging to ascertain whether there are relevant differences in the MAPK signaling components.

      We appreciate your suggestion. We added the description of “N, number of tumor samples containing corresponding EGFR mutation” to the figure legend. p-values were calculated with a two-tailed Wilcoxon rank sum test, and p<0.05 was labeled on Figures 3e-i.

      Figure 3I Good figure. However, it would be beneficial to provide validation with Western Blotting for a few of these substrates using pospho-specific antibodies. It is suggested that this experiment be added.

      We appreciate your suggestion. Figure 3I showed the comparison of patients’ ages among subtypes. I guess you mean Figure 3g and Figure 3h. The relevant experiments are currently underway, and we will provide the corresponding data in the next revised version.

      Figure 4b. Very compelling figure.

      We appreciate your suggestion.

      Line 276: The AhR and CYP1A1 data presented earlier was not convincing, and CYP1A1 and AhR cannot be responsibly used as indicators of BaP activity based on potential. This is not an appropriate application.

      We appreciate your suggestion. CYP1A1 and AhR are two key regulators involved in BaP metabolism and signaling transduction, respectively. However, after examining the protein expression of AhR between tumor and normal tissues, we found no significant differences (Fig. 1k) and CYP1A1 has been proven to be highly expressed in tumor samples (Fig. 1j). Thus, we mainly examined the expression of CYP1A1 among the four subgroups. We changed our description as follows:

      “As CYP1A1 is a key regulator involved in BaP metabolism and has been proven to be highly expressed in tumor samples (Fig. 1j), we next examined the expression of CYP1A1 among the four subgroups to evaluate their associations with air pollution.”

      Figure 4d. Here it is AhR protein used rather than mRNA measured earlier. What is the explanation for this change?

      We appreciate your suggestion. As there was no significant differences of the protein expression of AhR between tumor and normal tissues (Fig. 1k), we deleted the expression comparison of AhR among subtypes.

      Line 281 "Moderately elevated expression level of AhR" is not supported by the presented data and should be removed.

      We appreciate your suggestion. We have deleted the result of comparison of AhR among subtypes.

      Figure 4: There is no indication or explanation of how the protein abundance is being measured. Is this from the proteomics (MS) approaches, by ELISA or by Western? If it is simply by MS then validation by another method is preferable. The data presented in Figure 4 do not adequately support the claim that MC-II subtype is more strongly associated with BaP exposure. What statistical test is used in 4F? Why is the n in the MC-II group, which is the highlighted group of interest nearly double the other groups?

      We appreciate your suggestion. Fig. 4e is derived from the proteomics data. The two-tailed Wilcoxon rank sum test was used to calculate p-values in panels c and e.

      Figure 4g: At least one or two of these should be validated by Western Blot or targeted MS.

      We appreciate your suggestion. The relevant experiments are currently underway, and we will provide the corresponding data in the next revised version.

      Figure 5a: Assuming these were also measured via proteomic analysis, how do their expression patterns compare across the different omics modes?

      Thank you for your suggestion. Figure 5 integrates transcriptomics (19182 genes), proteomics (9152 genes), and phosphoproteomics (5733 genes) data. In general, we utilized transcriptomics data to identify unique or distinct pathways among subgroups. Furthermore, proteomics and phosphoproteomics data were employed to validate key gene expressions, as they encompass fewer genes compared to transcriptomics data.

      For instance, in Fig. 5a-d, we observed higher expression levels of mesenchymal markers such as VIM, FN1, TWIST2, SNAI2, ZEB1, ZEB2, and others in the MC-IV subtype using transcriptomics data (Fig. 5a). Additionally, we calculated epithelial-mesenchymal transition (EMT) scores using the ssGSEA enrichment method based on protein levels and conducted GSEA analysis using transcriptomics data (Fig. 5b). Furthermore, using proteomics data, we evaluated Fibronectin (FN1), an EMT marker that promotes the dissociation, migration, and invasion of epithelial cells, at the protein level (Fig. 5c), and β-Catenin, a key regulator in initiating EMT, also at the protein level (Fig. 5d). Overall, our findings indicate that the MC-IV subtype exhibits an enhanced EMT capability, which may contribute to the high malignancy observed in this subtype.

      Line 314: Not compared with MCI, which appeared to be much lower at the mRNA level. Is there an explanation for this difference?

      We appreciate your suggestion. FN1 expression is lowest in MCI at the protein level (Fig. 5c). However, at the transcriptome level, FN1 expression is lowest in the MCIII subtype (Fig. 5a). You may wonder why these results are inconsistent. Discrepancies between mRNA and protein expression levels are common, and previous study showed that about 20% genes had a statistically significant correlation between protein and mRNA expression in lung adenocarcinomas (Chen et al., 2002). Post-transcriptional mechanisms, including protein translation, post-translational modification, and degradation, may influence the level of a protein present in a given cell or tissue. In this situation, we focused on identifying distinct biological pathways in each subgroup, supported by multi-omics data.

      Line 321: MC-IV *potentially* possesses an enhanced EMT capability. This statement cannot be conclusively made.

      We appreciate your suggestion. We changed our description as: “Collectively, our findings demonstrate that the MC-IV subtype is associated with enhanced EMT capability, which may contribute to the high malignancy observed in this subtype.”

      Lines 325 and 327 indicated dysregulation of cell cycle processes and activation of CDK1 and CDK2 pathways based on KSEA analysis which is closely linked to cell cycle regulation as two separate pieces of evidence. However, these are both drawn from the phosphoproteomics, and likely indicate conclusions drawn from the same phosphosite data. Said another way, if phosphosite data indicates differences in kinases linked to cell cycle regulation then you would also expect phosphosite data to indicate dysregulation of cell cycle.

      We appreciate your suggestion. You mentioned that Fig. 4f and Fig. 5e redundantly prove that the CDK1 and CDK2 pathways are dysregulated. However, KSEA analysis in Fig. 4f estimates changes in kinase activity based on the collective phosphorylation changes of its identified substrates (Wiredja et al., 2017). In contrast, Fig. 5e directly evaluates the abundance of protein and phosphosite levels of CDK1 and CDK2 across subtypes. These analyses mutually confirm each other rather than being redundant.

      Line 413/Figure 6b: While there may be a trend displayed by the figure, it is not convincing enough to state that MC-IV shows a conclusively distinguishable bacterial composition. Too much variability exists within groups MC-II and MC-III. However, it does show that MC-IV and MC-II have consistent composition within their groups, and that is interesting.

      We appreciate your suggestion. We have deleted the analysis of bacterial composition across subtypes.

      Figure 6: Overall very nice figure, with intriguing diagnostic potential. See the above note on 6a-b interpretation.

      We appreciate your suggestion. We have deleted the analysis of bacterial composition across subtypes, including Fig. 6a-6c.

      Figure 7c-f better labeling of the panels will aid reader comprehension.

      We appreciate your suggestion. Necessary labeling has been added to Fig. 7c-f to enhance comprehension.

      Figure 7 panel order is confusing, switching from right to left to vertical. Rearranging to either left to right or vertical would help orient readers.

      We appreciate your suggestion. We have adjusted the order of Fig. 7 and extended Fig. 8 panel.

      Figure 7 legend i: should read Cell colony* assay

      We appreciate your suggestion. We have corrected this mistake in the revised manuscript.

      The Discussion is very brief. While it includes a discussion of the potential impact of the study, it does not include an analysis of the caveats/drawbacks of the study. A more thorough discussion of other studies focusing on the impacts of BaP exposure is also suggested as this was a highlighted point by the authors.

      We appreciate your suggestion. we have added discussion about the associations between BaP exposure and lung cancer and also talked about the shortcomings of our study as followings:

      “Mechanistically, Qing Wang showed that BaP induces lung carcinogenesis, characterized by increased inflammatory cytokines, and cell proliferative markers, while decreasing antioxidant levels, and apoptotic protein expression(Wang et al., 2020). In our study, we used clinical samples and linked the mutational signatures of XWLC to the chemical compound BaP, which advanced the etiology and mechanism of air-pollution-induced lung cancer. In our study, several limitations must be acknowledged. Firstly, although our multi-omics approach provided a comprehensive analysis of the subtypes and their unique biological pathways, the sample size for each subtype was relatively small. This limitation may affect the robustness of the clustering results and the identified subtype-specific pathways. Larger cohort studies are necessary to confirm these findings and refine the subtype classifications. Secondly, although our study advanced the understanding of air-pollution-induced lung cancer by using clinical samples, the reliance on epidemiological data in previous studies introduces potential confounding factors. Our findings should be interpreted with caution, and further mechanistic studies are warranted to establish causal relationships more definitively. Thirdly, our in silico analysis suggested potential approach to drug resistence in G719X mutations. However, these predictions need to be validated through extensive in vitro and in vivo experiments. The reliance on computational models without experimental confirmation may limit the clinical applicability of these findings.”

      References:

      Bailey, M. H., Tokheim, C., Porta-Pardo, E., Sengupta, S., Bertrand, D., Weerasinghe, A., Colaprico, A., Wendl, M. C., Kim, J., Reardon, B., et al. (2018). Comprehensive Characterization of Cancer Driver Genes and Mutations. Cell 173, 371-385 e318.

      Bray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., and Jemal, A. (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68, 394-424.

      Chen, G., Gharib, T. G., Huang, C. C., Taylor, J. M., Misek, D. E., Kardia, S. L., Giordano, T. J., Iannettoni, M. D., Orringer, M. B., Hanash, S. M., and Beer, D. G. (2002). Discordant protein and mRNA expression in lung adenocarcinomas. Mol Cell Proteomics 1, 304-313.

      Meyer, M. J., Beltran, J. F., Liang, S., Fragoza, R., Rumack, A., Liang, J., Wei, X., and Yu, H. (2018). Interactome INSIDER: a structural interactome browser for genomic studies. Nat Methods 15, 107-114.

      Mumford, J. L., He, X. Z., Chapman, R. S., Cao, S. R., Harris, D. B., Li, X. M., Xian, Y. L., Jiang, W. Z., Xu, C. W., Chuang, J. C., and et al. (1987). Lung cancer and indoor air pollution in Xuan Wei, China. Science 235, 217-220.

      Parkin, D. M., Bray, F., Ferlay, J., and Pisani, P. (2005). Global cancer statistics, 2002. CA Cancer J Clin 55, 74-108.

      Quinlan, A. R., and Hall, I. M. (2010). BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841-842.

      Sanchez-Vega, F., Mina, M., Armenia, J., Chatila, W. K., Luna, A., La, K. C., Dimitriadoy, S., Liu, D. L., Kantheti, H. S., Saghafinia, S., et al. (2018). Oncogenic Signaling Pathways in The Cancer Genome Atlas. Cell 173, 321-337 e310.

      Wang, Q., Zhang, L., Huang, M., Zheng, Y., and Zheng, K. (2020). Immunomodulatory Effect of Eriocitrin in Experimental Animals with Benzo(a)Pyrene-induced Lung Carcinogenesis. J Environ Pathol Toxicol Oncol 39, 137-147.

      Watanabe, S., Minegishi, Y., Yoshizawa, H., Maemondo, M., Inoue, A., Sugawara, S., Isobe, H., Harada, M., Ishii, Y., Gemma, A., et al. (2014). Effectiveness of gefitinib against non-small-cell lung cancer with the uncommon EGFR mutations G719X and L861Q. J Thorac Oncol 9, 189-194.

      Wiredja, D. D., Koyuturk, M., and Chance, M. R. (2017). The KSEA App: a web-based tool for kinase activity inference from quantitative phosphoproteomics. Bioinformatics 33, 3489-3491.

      Zhang, H., Liu, C., Li, L., Feng, X., Wang, Q., Li, J., Xu, S., Wang, S., Yang, Q., Shen, Z., et al. (2021). Genomic evidence of lung carcinogenesis associated with coal smoke in Xuanwei area, China. Natl Sci Rev 8, nwab152.

  3. inst-fs-iad-prod.inscloudgate.net inst-fs-iad-prod.inscloudgate.net
    1. racking is never innoc t 1 . . . . en · n my supervision of student teachers m classrooms across multiple cities " h T · ,, h d f ' a i ity grouping and its more perilous effects are t e or er o the day In any d b · f d · gra e, ut particularly the early grades all too o ten stu-ents are sorted accord· h · ' h ' mg not tot eir demonstrated ability but to the teac er s assessment of their heh . l'k b' . P & avior, 1 a iltty, or academic potential (Smith Polloway, atton, Dowdy 2004) I l ' . . ' · n c assrooms where I have observed as a umverSity

      The passage begins by acknowledging that ability grouping may seem harmless, even logical, in educational settings. However, it quickly becomes clear that the practice has negative consequences, particularly for poor children and children of color, who are disproportionately labeled as less capable.

  4. Sep 2024
    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      Summary:

      Understanding large-scale neural activity remains a formidable challenge in neuroscience. While several methods have been proposed to discover the assemblies from such large-scale recordings, most previous studies do not explicitly model the temporal dynamics. This study is an attempt to uncover the temporal dynamics of assemblies using a tool that has been established in other domains.

      The authors previously introduced the compositional Restricted Boltzmann Machine (cRBM) to identify neuron assemblies in zebrafish brain activity. Building upon this, they now employ the Recurrent Temporal Restricted Boltzmann Machine (RTRBM) to elucidate the temporal dynamics within these assemblies. By introducing recurrent connections between hidden units, RTRBM could retrieve neural assemblies and their temporal dynamics from simulated and zebrafish brain data.

      Strengths:

      The RTRBM has been previously used in other domains. Training in the model has been already established. This study is an application of such a model to neuroscience. Overall, the paper is well-structured and the methodology is robust, the analysis is solid to support the authors' claim.

      Weaknesses:

      The overall degree of advance is very limited. The performance improvement by RTRBM compared to their cRBM is marginal, and insights into assembly dynamics are limited.

      (1) The biological insights from this method are constrained. Though the aim is to unravel neural ensemble dynamics, the paper lacks in-depth discussion on how this method enhances our understanding of zebrafish neural dynamics. For example, the dynamics of assemblies can be analyzed using various tools such as dimensionality reduction methods once we have identified them using cRBM. What information can we gain by knowing the effective recurrent connection between them? It would be more convincing to show this in real data.

      See below in the recommendations section.

      (2) Despite the increased complexity of RTRBM over cRBM, performance improvement is minimal. Accuracy enhancements, less than 1% in synthetic and zebrafish data, are underwhelming (Figure 2G and Figure 4B). Predictive performance evaluation on real neural activity would enhance model assessment. Including predicted and measured neural activity traces could aid readers in evaluating model efficacy.

      See below in the recommendations section.

      Recommendations:

      (1) The biological insights from this method are constrained. Though the aim is to unravel neural ensemble dynamics, the paper lacks in-depth discussion on how this method enhances our understanding of zebrafish neural dynamics. For example, the dynamics of assemblies can be analyzed using various tools such as dimensionality reduction methods once we have identified them using cRBM. What information can we gain by knowing the effective recurrent connection between them? It would be more convincing to show this in real data.

      We agree with the reviewer that our analysis does not explore the data far enough to reach the level of new biological insights. For practical reasons unrelated to the science, we cannot further explore the data in this direction at this point, however, funding permitting, we will pick up this question at a later stage. The only change we have made to the corresponding figure at the current stage was to adapt the thresholds, which better emphasizes the locality of the resulting clusters.

      (2) Despite the increased complexity of RTRBM over cRBM, performance improvement is minimal. Accuracy enhancements, less than 1% in synthetic and zebrafish data, are underwhelming (Figure 2G and Figure 4B). Predictive performance evaluation on real neural activity would enhance model assessment. Including predicted and measured neural activity traces could aid readers in evaluating model efficacy.

      We thank the reviewer kindly for the comments on the performance comparison between the two models. We would like to highlight that the small range of accuracy values for the predictive performance is due to both the sparsity and stochasticity of the simulated data, and is not reflective of the actual percentage in performance improvement. To this end, we have opted to use a rescaled metric that we call the normalised Mean Squared Error (nMSE), where the MSE is equal to 1 minus the accuracy, as the visible units take on binary values. This metric is also more in line with the normalised Log-Likelihood (nLLH) metric used in the cRBM paper in terms of interpretability. The figure shows that the RTRBM can significantly predict the state of the visible units in subsequent time-steps, whereas the cRBM captures the correct time-independent statistics but has no predictive power over time.

      We also thank the reviewer for pointing out that there is no predictive performance evaluation on the neural data. This has been chosen to be omitted for two reasons. First, it is clear from Fig. 2 that the (c)RBM has no temporal dependencies, meaning that the predictive performance is determined mostly by the average activity of the visible units. If this corresponds well with the actual mean activity per neuron, the nMSE will be around 0. This correspondence is already evaluated in the first panel of 3F. Second, as this is real data, we can not make an estimate of a lower bound on the MSE that is due to neural noise. Because of this, the scale of the predictive performance score will be arbitrary, making it difficult to quantitatively assess the difference in performance between both models.

      (3) The interpretation of the hidden real variable $r_t$ lacks clarity. Initially interpreted as the expectation of $\mathbf{h}_t$, its interpretation in Eq (8) appears different. Clarification on this link is warranted.

      We thank the reviewer kindly for the suggested clarification. However, we think the link between both values should already be sufficiently clear from the text in lines 469-470:

      “Importantly, instead of using binary hidden unit states 𝐡[𝑡−1], sampled from the expected real valued hidden states 𝐫[𝑡−1], the RTRBM propagates these real-valued hidden unit states directly.”

      In other words, both indeed are the same, one could sample a binary-valued 𝐡[𝑡-1] from the real-valued 𝐫[𝑡-1] through e.g. a Bernoulli distribution, where 𝐫[𝑡-1] would thus indeed act as an expectation over 𝐡[𝑡−1]. However, the RTRBM formulation keeps the real-valued 𝐫[𝑡-1] to propagate the hidden-unit states to the next time-step. The motivation for this choice is further discussed in the original RTRBM paper (Sutskever et al. 2008).

      (4) In Figure 3 panel F, the discrepancy in x-axis scales between upper and lower panels requires clarification. Explanation regarding the difference and interpretation guidelines would enhance understanding.

      Thank you for pointing out the discrepancy in x-axis scales between the upper and lower panels of Figure 3F. The reason why these scales are different is that the activation functions in the two models differ in their range, and showing them on the same scale would not do justice to this difference. But we agree that this could be unclear for readers. Therefore we added an additional clarification for this discrepancy in line 215:

      “While a direct comparison of the hidden unit activations between the cRBM and the RTRBM is hindered by the inherent discrepancy in their activation functions (unbounded and bounded, respectively), the analysis of time-shifted moments reveals a stronger correlation for the RTRBM hidden units ($r_s = 0.92$, $p<\epsilon$) compared to the cRBM ($r_s = 0.88$, $p<\epsilon$)”

      (5) Assessing model performance at various down-sampling rates in zebrafish data analysis would provide insights into model robustness.

      We agree that we would have liked to assess this point in real data, to verify that this holds as well in the case of the zebrafish whole-brain data. The main reason why we did not choose to do this in this case is that we would only be able to further downsample the data. Current whole brain data sets are collected at a few Hz (here 4 Hz, only 2 Hz in other datasets), which we consider to be likely slower than the actual interaction speed in neural systems, which is on the order of milliseconds between neurons, and on the order of ~100 ms (~10 Hz) between assemblies. Therefore reducing the rate further, we expect to only see a reduction in quality, which we considered less interesting than finding an optimum. Higher rates of imaging in light-sheet imaging are only achievable currently by imaging only single planes (which defies the goal of whole brain recordings), but may be possible in the future when the limiting factors (focal plane stepping and imaging) are addressed. For completeness, we have now performed the downstepping for the experimental data, which showed the expected decrease in performance. The results have been integrated into Figure 4.

      Reviewer #2 (Public Review):

      Summary:

      In this work, the authors propose an extension to some of the last author's previous work, where a compositional restricted Boltzmann machine was considered as a generative model of neuron-assembly interaction. They augment this model by recurrent connections between the Boltzmann machine's hidden units, which allow them to explicitly account for temporal dynamics of the assembly activity. Since their model formulation does not allow the training towards a compositional phase (as in the previous model), they employ a transfer learning approach according to which they initialise their model with a weight matrix that was pre-trained using the earlier model so as to essentially start the actually training in a compositional phase. Finally, they test this model on synthetic and actual data of whole-brain light-sheet-microscopy recordings of spontaneous activity from the brain of larval zebrafish.

      Strengths:

      This work introduces a new model for neural assembly activity. Importantly, being able to capture temporal assembly dynamics is an interesting feature that goes beyond many existing models. While this work clearly focuses on the method (or the model) itself, it opens up an avenue for experimental research where it will be interesting to see if one can obtain any biologically meaningful insights considering these temporal dynamics when one is able to, for instance, relate them to development or behaviour.

      Weaknesses:

      For most of the work, the authors present their RTRBM model as an improvement over the earlier cRBM model. Yet, when considering synthetic data, they actually seem to compare with a "standard" RBM model. This seems odd considering the overall narrative, and it is not clear why they chose to do that. Also, in that case, was the RTRBM model initialised with the cRBM weight matrix?

      Thank you for raising the important point regarding the RTRBM comparison in the synthetic data section. Initially, we aimed to compare the performance of the cRBM with the cRTRBM. However, we encountered significant challenges in getting the RTRBM to reach the compositional phase. To ensure a fair and robust comparison, we opted to compare the RBM with the RTRBM.

      A few claims made throughout the work are slightly too enthusiastic and not really supported by the data shown. For instance, when the authors refer to the clusters shown in Figure 3D as "spatially localized", this seems like a stretch, specifically in view of clusters 1, 3, and 4.

      Thanks for pointing out this inaccuracy. When going back to the data/analyses to address the question about locality, we stumbled upon a minor bug in the implementation of the proportional thresholding, causing the threshold to be too low and therefore too many neurons to be considered.

      Fixing this bug reduces the number of neurons, thereby better showing the local structure of the clusters. Furthermore, if one would lower the threshold within the hierarchical clustering, smaller, and more localized, clusters would appear. We deliberately chose to keep this threshold high to not overwhelm the reader with the number of identified clusters. We hope the reviewer agrees with these changes and that the spatial structure in the clusters presented are indeed rather localized.

      Moreover, when they describe the predictive performance of their model as "close to optimal" when the down-sampling factor coincided with the interaction time scale, it seems a bit exaggerated given that it was more or less as close to the upper bound as it was to the lower bound.

      We thank the reviewer for catching this error. Indeed, the best performing model does not lay very close to the estimated performance of an optimal model. The text has been updated to reflect this.

      When discussing the data statistics, the authors quote correlation values in the main text. However, these do not match the correlation values in the figure to which they seem to belong. Now, it seems that in the main text, they consider the Pearson correlation, whereas in the corresponding figure, it is the Spearman correlation. This is very confusing, and it is not really clear as to why the authors chose to do so.

      Thank you for identifying the discrepancy between the correlation values mentioned in the text and those presented in the figure. We updated the manuscript to match the correlation coefficient values in the figure with the correct values denoted in the text.

      Finally, when discussing the fact that the RTRBM model outperforms the cRBM model, the authors state it does so for different moments and in different numbers of cases (fish). It would be very interesting to know whether these are the same fish or always different fish.

      Thank you for pointing this out. Keeping track of the same fish across the different metrics makes sense. We updated the figure to include a color code for each individual fish. As it turns out each time the same fish are significantly better performing.

      Recommendations:

      Figure 1: While the schematic in A and D only shows 11 visible units ("neurons"), the weight matrices and the activity rasters in B and C and E and F suggest that there should be, in fact, 12 visible units. While not essential, I think it would be nice if these numbers would match up.

      Thank you for pointing out the inconsistency in the number of visible units depicted in Figure 1. We agree that this could have been confusing for readers. The figure has been updated accordingly. As you suggested, the schematic representation now accurately reflects the presence of 12 visible units in both the RBM and RTRBM models.

      Figure 3: Panel G is not referenced in the main text. Yet, I believe it should be somewhere in lines 225ff.

      Thank you for mentioning this. We added in line 233 a reference to figure 3 panel G to refer to the performance of the cRBM and RTRBM on the different fish.

      Line 637ff: The authors consider moments <v\_i h\_μ> and <v\_i h\_j>, and from the context, it seems they are not the same. However, it is not clear as to why because, judging from the notation, they should be the same.

      The second-order statistic <v\_i h\_j> on line 639 was indeed already mentioned and denoted as <v\_i h\_μ> on line 638. It has now been removed accordingly in the updated manuscript.

      I found the usage of U^ and U throughout the manuscript a bit confusing. As far as I understand, U^ is a learned representation of U. However, maybe the authors could make the distinction clearer.

      We understand the usage of Û and U throughout the text may be confusing for the reader. However, we would like to notify the reviewer that the distinction between these two variables is explained in line 142: “in addition to providing a close estimate (̂Û) to the true assembly connectivity matrix U”. However, for added clarification to the reader, we added additional mentions of the estimated nature of Û throughout the text in the updated manuscript.

      Equation 3: It would be great if the authors could provide some more explanation of how they arrived at the identities.

      These identities have previously been widely described in literature. For this reason, we decided not to include their derivation in our manuscript. However, for completeness, we kindly refer to:

      Goodfellow, I., Bengio, Y., & Courville, A. (2016). Chapter 20: Deep generative models [In Deep Learning]. MIT Press. https://www.deeplearningbook.org/contents/generative_models.html

      Typos:

      -  L. 196: "connectiivty" -> "connectivity"

      -  L. 197: Does it mean to say "very strong stronger"?

      -  L. 339: The reference to Dunn et al. (2016) should appear in parentheses.

      -  L. 504f: The colon should probably be followed by a full sentence.

      -  Eq. 2: In the first line, the potential V still appears, which should probably be changed to show the concrete form (-b * h) as in the second line.

      -  L. 351: Is there maybe a comma missing after "cRBM"?

      -  L. 271: Instead of "correlation", shouldn't it rather be "similarity"? - L. 218: "Figure 3D" -> "Figure 3F"

      We thank the reviewer for pointing out these typos, which have all (except one) been fixed in the text. We do emphasize the potential V to show that there are alternative hidden unit potentials that can be chosen. For instance, the cRBM utilizes dReLu hidden unit potentials.

      Reviewer #3 (Public Review):

      With ever-growing datasets, it becomes more challenging to extract useful information from such a large amount of data. For that, developing better dimensionality reduction/clustering methods can be very important to make sense of analyzed data. This is especially true for neuroscience where new experimental advances allow the recording of an unprecedented number of neurons. Here the authors make a step to help with neuronal analyses by proposing a new method to identify groups of neurons with similar activity dynamics. I did not notice any obvious problems with data analyses here, however, the presented manuscript has a few weaknesses:

      (1) Because this manuscript is written as an extension of previous work by the same authors (van der Plas et al., eLife, 2023), thus to fully understand this paper it is required to read first the previous paper, as authors often refer to their previous work for details. Similarly, to understand the functional significance of identified here neuronal assemblies, it is needed to go to look at the previous paper.

      We agree that the present Research Advance has been written in a way that builds on our previous publication. It was our impression that this was the intention of the Research Advance format, as spelled out in its announcement "eLife has introduced an innovative new type of article – the Research Advance – that invites the authors of any eLife paper to present significant additions to their original research". In the previous formatting guidelines from eLife this was more evident with a strong limitation on the number of figures and words, however, also for the present, more liberal guidelines, place an emphasis on the relation to the previous article. We have nonetheless tried in several places to fill in details that might simplify the reading experience.

      (2) The problem of discovering clusters in data with temporal dynamics is not unique to neuroscience. Therefore, the authors should also discuss other previously proposed methods and how they compare to the presented here RTRBM method. Similarly, there are other methods using neural networks for discovering clusters (assemblies) (e.g. t-SNE: van der Maaten & Hinton 2008, Hippocluster: Chalmers et al. 2023, etc), which should be discussed to give better background information for the readers.

      The clustering methods suggested by the reviewer do not include modeling any time dependence, which is the crucial advance presented here by the introduction of the RTRBM, in extending the (c)RBM. In our previous publication on the cRBM (an der Plas et al., eLife, 2023), this comparison was part of the discussion, although it focussed on a different set of methods. While clustering methods like t-SNE, UMAP and others certainly have their value in scientific analysis, we think it might be misleading the reader to think that they achieve the same task as an RTRBM, which adds the crucial dimension of temporal dependence.

      (3) The above point to better describe other methods is especially important because the performance of the presented here method is not that much better than previous work. For example, RTRBM outperforms the cRBM only on ~4 out of 8 fish datasets. Moreover, as the authors nicely described in the Limitations section this method currently can only work on a single time scale and clusters have to be estimated first with the previous cRBM method. Thus, having an overview of other methods which could be used for similar analyses would be helpful.

      We think that the perception that the RTRBM performs only slightly better is based on a misinterpretation of the performance measure, which we have tried to address (see comments above) in this rebuttal and the manuscript. In addition we would like to emphasize that the structural estimation (which is still modified by the RTRBM, only seeded by the cRBMs output), as shown in the simulated data, makes improved structural estimates, which is important, even in cases where the performance is comparable (which can be the case if the RBM absorbs temporal dependencies of assemblies into modified structure of assemblies). We have clarified this now in the discussion.

      Recommendations:

      (1) Line 181: it is not explained how a reconstruction error is defined.

      Dear reviewer, thanks for pointing this out. A definition of the (mean square) reconstruction error is added in this line.

      (2) How was the number of hidden neurons chosen and how does it affect performance?

      Thank you for pointing this out. Due to the fact that we use transfer learning, the number of hidden units used for the RTRBM is given by the number of hidden units used for training the cRBM. In further research, when the RTRBM operates in the compositional phase, we can exploit a grid search over a set of hyper parameters to determine the optimal set of hidden units and other parameters.

    1. Author response:

      Reviewer #1 (Public review):

      This manuscript from Schwintek and coworkers describes a system in which gas flow across a small channel (10^-4-10^-3 m scale) enables the accumulation of reactants and convective flow. The authors go on to show that this can be used to perform PCR as a model of prebiotic replication.

      Strengths:

      The manuscript nicely extends the authors' prior work in thermophoresis and convection to gas flows. The demonstration of nucleic acid replication is an exciting one, and an enzyme-catalyzed proof-of-concept is a great first step towards a novel geochemical scenario for prebiotic replication reactions and other prebiotic chemistry.

      The manuscript nicely combines theory and experiment, which generally agree well with one another, and it convincingly shows that accumulation can be achieved with gas flows and that it can also be utilized in the same system for what one hopes is a precursor to a model prebiotic reaction. This continues efforts from Braun and Mast over the last 10-15 years extending a phenomenon that was appreciated by physicists and perhaps underappreciated in prebiotic chemistry to increasingly chemically relevant systems and, here, a pilot experiment with a simple biochemical system as a prebiotic model.

      I think this is exciting work and will be of broad interest to the prebiotic chemistry community.

      Weaknesses:

      The manuscript states: "The micro scale gas-water evaporation interface consisted of a 1.5 mm wide and 250 µm thick channel that carried an upward pure water flow of 4 nl/s ≈ 10 µm/s perpendicular to an air flow of about 250 ml/min ≈ 10 m/s." This was a bit confusing on first read because Figure 2 appears to show a larger channel - based on the scale bar, it appears to be about 2 mm across on the short axis and 5 mm across on the long axis. From reading the methods, one understands the thickness is associated with the Teflon, but the 1.5 mm dimension is still a bit confusing (and what is the dimension in the long axis?) It is a little hard to tell which portion (perhaps all?) of the image is the channel. This is because discontinuities are present on the left and right sides of the experimental panels (consistent with the image showing material beyond the channel), but not the simulated panels. Based on the authors' description of the apparatus (sapphire/CNC machined Teflon/sapphire) it sounds like the geometry is well-known to them. Clarifying what is going on here (and perhaps supplying the source images for the machined Teflon) would be helpful.

      We understand. We will update the figures to better show dimensions of the experimental chamber. We will also add a more complete Figure in the supplementary information. Part of the complexity of the chamber however stems from the fact that the same chamber design has also been used to create defined temperature gradients which are not necessary and thus the chamber is much more complex than necessary.

      The data shown in Figure 2d nicely shows nonrandom residuals (for experimental values vs. simulated) that are most pronounced at t~12 m and t~40-60m. It seems like this is (1) because some symmetry-breaking occurs that isn't accounted for by the model, and perhaps (2) because of the fact that these data are n=1. I think discussing what's going on with (1) would greatly improve the paper, and performing additional replicates to address (2) would be very informative and enhance the paper. Perhaps the negative and positive residuals would change sign in some, but not all, additional replicates?

      To address this, we will show two more replicates of the experiment and include them in Figure 2.

      We are seeing two effects when we compare fluorescence measurements of the experiments.

      Firstly, degassing of water causes the formation of air-bubbles, which are then transported upwards to the interface, disrupting fluorescence measurements. This, however, mostly occurs in experiments with elevated temperatures for PCR reactions, such as displayed in Figure 4.

      Secondly, due to the high surface tension of water, the interface is quite flexible. As the inflow and evaporation work to balance each other, the shape of the interface adjusts, leading to alterations in the circular flow fields below.

      Thus the conditions, while overall being in steady state, show some fluctuations. The strong dependence on interface shape is also seen in the simulation. However, modeling a dynamic interface shape is not so easy to accomplish, so we had to stick to one geometry setting. Again here, the added movies of two more experiments should clarify this issue.

      The authors will most likely be familiar with the work of Victor Ugaz and colleagues, in which they demonstrated Rayleigh-Bénard-driven PCR in convection cells (10.1126/science.298.5594.793, 10.1002/anie.200700306). Not including some discussion of this work is an unfortunate oversight, and addressing it would significantly improve the manuscript and provide some valuable context to readers. Something of particular interest would be their observation that wide circular cells gave chaotic temperature profiles relative to narrow ones and that these improved PCR amplification (10.1002/anie.201004217). I think contextualizing the results shown here in light of this paper would be helpful.

      Thanks for pointing this out and reminding us. We apologize. We agree that the chaotic trajectories within Rayleigh-Bénard convection cells lead to temperature oscillations similar to the salt variations in our gas-flux system. Although the convection-driven PCR in Rayleigh-Bénard is not isothermal like our system, it provides a useful point of comparison and context for understanding environments that can support full replication cycles. We will add a section comparing approaches and giving some comparison into the history of convective PCR and how these relate to the new isothermal implementation.

      Again, it appears n=1 is shown for Figure 4a-c - the source of the title claim of the paper - and showing some replicates and perhaps discussing them in the context of prior work would enhance the manuscript.

      We appreciate the reviewer for bringing this to our attention. We will now include the two additional repeats for the data shown in Figure 4c, while the repeats of the PAGE measurements are already displayed in Supplementary Fig. IX.2. Initially, we chose not to show the repeats in Figure 4c due to the dynamic and variable nature of the system. These variations are primarily caused by differences at the water-air interface, attributed to the high surface tension of water. Additionally, the stochastic formation of air bubbles in the inflow—despite our best efforts to avoid them—led to fluctuations in the fluorescence measurements across experiments. These bubbles cause a significant drop in fluorescence in a region of interest (ROI) until the area is refilled with the sample.

      Unlike our RNA-focused experiments, PCR requires high temperatures and degassing a PCR master mix effectively is challenging in this context. While we believe our chamber design is sufficiently gas-tight to prevent air from diffusing in, the high surface-to-volume ratio in microfluidics makes degassing highly effective, particularly at elevated temperatures. We anticipate that switching to RNA experiments at lower temperatures will mitigate this issue, which is also relevant in a prebiotic context.

      The reviewer’s comments are valid and prompt us to fully display these aspects of the system. We will now include these repeats in Figure 4c to give readers a deeper understanding of the experiment's dynamics. Additionally, we will provide videos of all three repeats, allowing readers to better grasp the nature of the fluctuations in SYBR Green fluorescence depicted in Figure 4c.

      I think some caution is warranted in interpreting the PCR results because a primer-dimer would be of essentially the same length as the product. It appears as though the experiment has worked as described, but it's very difficult to be certain of this given this limitation. Doing the PCR with a significantly longer amplicon would be ideal, or alternately discussing this possible limitation would be helpful to the readers in managing expectations.

      This is a good point and should be discussed more in the manuscript. Our gel electrophoresis is capable of distinguishing between replicate and primer dimers. We know this since we were optimizing the primers and template sequences to minimize primer dimers, making it distinguishable from the desired 61mer product. That said, all of the experiments performed without a template strand added did not show any band in the vicinity of the product band after 4h of reaction, in contrast to the experiments with template, presenting a strong argument against the presence of primer dimers.

      Reviewer #2 (Public review):

      Schwintek et al. investigated whether a geological setting of a rock pore with water inflow on one end and gas passing over the opening of the pore on the other end could create a non-equilibrium system that sustains nucleic acid reactions under mild conditions. The evaporation of water as the gas passes over it concentrates the solutes at the boundary of evaporation, while the gas flux induces momentum transfer that creates currents in the water that push the concentrated molecules back into the bulk solution. This leads to the creation of steady-state regions of differential salt and macromolecule concentrations that can be used to manipulate nucleic acids. First, the authors showed that fluorescent bead behavior in this system closely matched their fluid dynamic simulations. With that validation in hand, the authors next showed that fluorescently labeled DNA behaved according to their theory as well. Using these insights, the authors performed a FRET experiment that clearly demonstrated the hybridization of two DNA strands as they passed through the high Mg++ concentration zone, and, conversely, the dissociation of the strands as they passed through the low Mg++ concentration zone. This isothermal hybridization and dissociation of DNA strands allowed the authors to perform an isothermal DNA amplification using a DNA polymerase enzyme. Crucially, the isothermal DNA amplification required the presence of the gas flux and could not be recapitulated using a system that was at equilibrium. These experiments advance our understanding of the geological settings that could support nucleic acid reactions that were key to the origin of life.

      The presented data compellingly supports the conclusions made by the authors. To increase the relevance of the work for the origin of life field, the following experiments are suggested:

      (1) While the central premise of this work is that RNA degradation presents a risk for strand separation strategies relying on elevated temperatures, all of the work is performed using DNA as the nucleic acid model. I understand the convenience of using DNA, especially in the latter replication experiment, but I think that at least the FRET experiments could be performed using RNA instead of DNA.

      We understand the request only partially. The modification brought about by the two dye molecules in the FRET probe to be able to probe salt concentrations by melting is of course much larger than the change of the backbone from RNA to DNA. This was the reason why we rather used the much more stable DNA construct which is also manufactured at a lower cost and in much higher purity also with the modifications. But we think the melting temperature characteristics of RNA and DNA in this range is enough known that we can use DNA instead of RNA for probing the salt concentration in our flow cycling.

      Only at extreme conditions of pH and salt, RNA degradation through transesterification, especially under alkaline conditions is at least several orders of magnitude faster than spontaneous degradative mechanisms acting upon DNA [Li, Y., & Breaker, R. R. (1999). Kinetics of RNA degradation by specific base catalysis of transesterification involving the 2 ‘-hydroxyl group. Journal of the American Chemical Society, 121(23), 5364-5372.]. The work presented in this article is however focussed on hybridization dynamics of nucleic acids. Here, RNA and DNA share similar properties regarding the formation of double strands and their respective melting temperatures. While RNA has been shown to form more stable duplex structures exhibiting higher melting temperatures compared to DNA [Dimitrov, R. A., & Zuker, M. (2004). Prediction of hybridization and melting for double-stranded nucleic acids. Biophysical Journal, 87(1), 215-226.], the general impact of changes in salt, temperature and pH [Mariani, A., Bonfio, C., Johnson, C. M., & Sutherland, J. D. (2018). pH-Driven RNA strand separation under prebiotically plausible conditions. Biochemistry, 57(45), 6382-6386.] on respective melting temperatures follows the same trend for both nucleic acid types. Also the diffusive properties of RNA and DNA are very similar [Baaske, P., Weinert, F. M., Duhr, S., Lemke, K. H., Russell, M. J., & Braun, D. (2007). Extreme accumulation of nucleotides in simulated hydrothermal pore systems. Proceedings of the National Academy of Sciences, 104(22), 9346-9351.].

      Since this work is a proof of principle for the discussed environment being able to host nucleic acid replication, we aimed to avoid second order effects such as degradation by hydrolysis by using DNA as a proxy polymer. This enabled us to focus on the physical effects of the environment on local salt and nucleic acid concentration. The experiments performed with FRET are used to visualize local salt concentration changes and their impact on the melting temperature of dissolved nucleic acids.  While performing these experiments with RNA would without doubt cover a broader application within the field of origin of life, we aimed at a step-by-step / proof of principle approach, especially since the environmental phenomena studied here have not been previously investigated in the OOL context. Incorporating RNA-related complexity into this system should however be addressed in future studies. This will likely require modifications to the experimental boundary conditions, such as adjusting pH, temperature, and salt concentration, to account for the greater duplex stability of RNA. For instance, lowering the pH would reduce the RNA melting temperature [Ianeselli, A., Atienza, M., Kudella, P. W., Gerland, U., Mast, C. B., & Braun, D. (2022). Water cycles in a Hadean CO2 atmosphere drive the evolution of long DNA. Nature Physics, 18(5), 579-585.].

      (2) Additionally, showing that RNA does not degrade under the conditions employed by the authors (I am particularly worried about the high Mg++ zones created by the flux) would further strengthen the already very strong and compelling work.

      Based on literature values for hydrolysis rates of RNA [Li, Y., & Breaker, R. R. (1999). Kinetics of RNA degradation by specific base catalysis of transesterification involving the 2 ‘-hydroxyl group. Journal of the American Chemical Society, 121(23), 5364-5372.], we estimate RNA to have a halflife of multiple months under the deployed conditions in the FRET experiment (High concentration zones contain <1mM of Mg2+). Additionally, dsRNA is multiple orders of magnitude more stable than ssRNA with regards to degradation through hydrolysis [Zhang, K., Hodge, J., Chatterjee, A., Moon, T. S., & Parker, K. M. (2021). Duplex structure of double-stranded RNA provides stability against hydrolysis relative to single-stranded RNA. Environmental Science & Technology, 55(12), 8045-8053.], improving RNA stability especially in zones of high FRET signal. Furthermore, at the neutral pH deployed in this work, RNA does not readily degrade. In previous work from our lab [Salditt, A., Karr, L., Salibi, E., Le Vay, K., Braun, D., & Mutschler, H. (2023). Ribozyme-mediated RNA synthesis and replication in a model Hadean microenvironment. Nature Communications, 14(1), 1495.], we showed that the lifetime of RNA under conditions reaching 40mM Mg2+ at the air-water interface at 45°C was sufficient to support ribozymatically mediated ligation reactions in experiments lasting multiple hours.

      With that in mind, gaining insight into the median Mg2+ concentration across multiple averaged nucleic acid trajectories in our system (see Fig. 3c&d) and numerically convoluting this with hydrolysis dynamics from literature would be highly valuable. We anticipate that longer residence times in trajectories distant from the interface will improve RNA stability compared to a system with uniformly high Mg2+ concentrations.

      (3) Finally, I am curious whether the authors have considered designing a simulation or experiment that uses the imidazole- or 2′,3′-cyclic phosphate-activated ribonucleotides. For instance, a fully paired RNA duplex and a fluorescently-labeled primer could be incubated in the presence of activated ribonucleotides +/- flux and subsequently analyzed by gel electrophoresis to determine how much primer extension has occurred. The reason for this suggestion is that, due to the slow kinetics of chemical primer extension, the reannealing of the fully complementary strands as they pass through the high Mg++ zone, which is required for primer extension, may outcompete the primer extension reaction. In the case of the DNA polymerase, the enzymatic catalysis likely outcompetes the reannealing, but this may not recapitulate the uncatalyzed chemical reaction.

      This is certainly on our to-do list. Our current focus is on templated ligation rather than templated polymerization and we are working hard to implement RNA-only enzyme-free ligation chain reaction, based on more optimized parameters for the templated ligation from 2’3’-cyclic phosphate activation that was just published [High-Fidelity RNA Copying via 2′,3′-Cyclic Phosphate Ligation, Adriana C. Serrão, Sreekar Wunnava, Avinash V. Dass, Lennard Ufer, Philipp Schwintek, Christof B. Mast, and Dieter Braun, JACS doi.org/10.1021/jacs.3c10813 (2024)]. But we first would try this at an air-water interface which was shown to work with RNA in a temperature gradient [Ribozyme-mediated RNA synthesis and replication in a model Hadean microenvironment, Annalena Salditt, Leonie Karr, Elia Salibi, Kristian Le Vay, Dieter Braun & Hannes Mutschler, Nature Communications doi.org/10.1038/s41467-023-37206-4 (2023)] before making the jump to the isothermal setting we describe here. So we can understand the question, but it was good practice also in the past to first get to know the setting with PCR, then jump to RNA.

      Reviewer #2 (Recommendations for the authors):

      (1) Could the authors comment on the likelihood of the geological environments where the water inflow velocity equals the evaporation velocity?

      This is an important point to mention in the manuscript, thank you for pointing that out. To produce a defined experiment, we were pushing the water out with a syringe pump, but regulated in a way that the evaporation was matching our flow rate. We imagine that a real system will self-regulate the inflow of the water column on the one hand side by a more complex geometry of the gas flow, matching the evaporation with the reflow of water automatically. The interface would either recede or move closer to the gas flux, depending on whether the inflow exceeds or falls short of the evaporation rate. As the interface moves closer, evaporation speeds up, while moving away slows it down. This dynamic process stabilizes the system, with surface tension ultimately fixing the interface in place.

      We have seen a bit of this dynamic already in the experiments, could however so far not yet find a good geometry within our 2-dimensional constant thickness geometry to make it work for a longer time. Very likely having a 3-dimensional reservoir of water with less frictional forces would be able to do this, but this would require a full redesign of a multi-thickness microfluidics. The more we think about it, the more we envisage to make the next implementation of the experiment with a real porous volcanic rock inside a humidity chamber that simulates a full 6h prebiotic day. But then we would lose the whole reproducibility of the experiment, but likely gain a way that recondensation of water by dew in a cold morning is refilling the water reservoirs in the rocks again. Sorry that I am regressing towards experiments in the future.

      (2) Could the authors speculate on using gases other than ambient air to provide the flux and possibly even chemical energy? For example, using carbonyl sulfide or vaporized methyl isocyanide could drive amino acid and nucleotide activation, respectively, at the gas-water interface.

      This is an interesting prospect for future work with this system. We thought also about introducing ammonia for pH control and possible reactions. We were amazed in the past that having CO2 instead of air had a profound impact on the replication and the strand separation [Water cycles in a Hadean CO2 atmosphere drive the evolution of long DNA, Alan Ianeselli, Miguel Atienza, Patrick Kudella, Ulrich Gerland, Christof Mast & Dieter Braun, Nature Physics doi.org/10.1038/s41567-022-01516-z (2022)]. So going more in this direction absolutely makes sense and as it acts mostly on the length-selectively accumulated molecules at the interface, only the selected molecules will be affected, which adds to the selection pressure of early evolutionary scenarios.

      Of course, in the manuscript, we use ambient air as a proxy for any gas, focusing primarily on the energy introduced through momentum transfer and evaporation. We speculate that soluble gasses could establish chemical gradients, such as pH or redox potential, from the bulk solution to the interface, similar to the Mg2+ accumulation shown in Figure 3c. The nature of these gradients would depend on each gas's solubility and diffusivity. We have already observed such effects in thermal gradients [Keil, L. M., Möller, F. M., Kieß, M., Kudella, P. W., & Mast, C. B. (2017). Proton gradients and pH oscillations emerge from heat flow at the microscale. Nature communications, 8(1), 1897.] and finding similar behavior in an isothermal environment would be a significant discovery.

      (3) Line 162: Instead of "risk," I suggest using "rate".

      Oh well - thanks for pointing this out! Will be changed.

      (4) Using FRET of a DNA duplex as an indicator of salt concentration is a decent proxy, but a more direct measurement of salt concentration would provide further merit to the explicit statement that it is the salt concentration that is changing in the system and not another hidden parameter.

      Directly observing salt concentration using microscopy is a difficult task. While there are dyes that change their fluorescence depending on the local Na+ or Mg2+ concentration, they are not operating differentially, i.e. by making a ratio between two color channels. Only then we are not running into artifacts from the dye molecules being accumulated by the non-equilibrium settings. We were able to do this for pH in the past, but did not find comparable optical salt sensors. This is the reason we ended up with a FRET pair, with the advantage that we actually probe the strand separation that we are interested in anyhow. Using such a dye in future work would however without a doubt enhance the understanding of not only this system, but also our thermal gradient environments.

      (5) Figure 3a: Could the authors add information on "Dried DNA" to the caption? I am assuming this is the DNA that dried off on the sides of the vessel but cannot be sure.

      Thanks to the reviewer for pointing this out. This is correct and we will describe this better in the revised manuscript.

      (6) Figure 4b and c: How reproducible is this data? Have the authors performed this reaction multiple independent times? If so, this data should be added to the manuscript.

      The data from the gel electrophoresis was performed in triplicates and is shown in full in supplementary information. The data in c is hard to reproduce, as the interface is not static and thus ROI measurements are difficult to perform as an average of repeats. Including the data from the independent repeats will however give the reader insight into some of the experimental difficulties, such as air bubbles, which form from degassing as the liquid heats up, that travel upwards to the interface, disrupting the ongoing fluorescence measurements.

      (7) Line 256: "shielding from harmful UV" statement only applies to RNA oligomers as UV light may actually be beneficial for earlier steps during ribonucleoside synthesis. I suggest rephrasing to "shielding nucleic acid oligomers from UV damage.".

      Will be adjusted as mentioned.

      (8) The final paragraph in the Results and Discussion section would flow better if placed in the Conclusion section.

      This is a good point and we will merge results and discussion closer together.

      (9) Line 262, "...of early Life" is slightly overstating the conclusions of the study. I suggest rephrasing to "...of nucleic acids that could have supported early life."

      This is a fair comment. We thank the reviewer for his detailed analysis of the manuscript!

      (10) In references, some of the journal names are in sentence case while others are in title case (see references 23 and 26 for example).

      Thanks - this will be fixed.

    1. (spuewap uonoe jo Aujeuoner ayp yor SIYS ayX JO uUoNSNpoHut sy Aepop Ise] I JO IsaLIE 0} paXojdap aq Aeul soyjo jo AWoyINe ay) YyNso1 B se pue ‘ssassod you Op JdYJO Sy} JO SJUSQUINOUT JUdLIND ay) YOY S]ITYS JeoruYyI) joaou Aq pauayeaiyy aq Avu gol ay 01 1y812 paysyqeisa ay} ‘aoueISUI 10J) YseID 0} pus) [LM om] ap yey Ajay] UeYY aOUN SI Wt JoLy UT “AUOULIEY Ut UIBUUaI PUB IPIOUIOD pnoys sano WpNE papunols ApussayjIp omy om Aya jno Sunuiod “aaamoy Noy — [PS peoTUYysa} yueaayas amp jo yep pue asdyjo sy) Jo AUOYINe sy} 0] paquose udIq sey IYyZIaM jenba ‘sisa3dns japow sy) pueurwios jo AyoeIOTY ayy UT IIMA ues 0 L

      I do kind of appreciate this being called out

    1. Author response:

      Reviewer #1 (Public review):

      Summary:

      Lejeune et al. demonstrated sex-dependent differences in the susceptibility to MRSA infection. The authors demonstrated the role of the microbiota and sex hormones as potential determinants of susceptibility. Moreover, the authors showed that Th17 cells and neutrophils contribute to sex hormone-dependent protection in female mice.

      Strengths:

      The role of microbiota was examined in various models (gnotobiotic, co-housing, microbiota transplantation). The identification of responsible immune cells was achieved using several genetic knockouts and cell-specific depletion models. The involvement of sex hormones was clarified using ovariectomy and the FCG model.

      Weaknesses:

      The mechanisms by which specific microbiota confer female-specific protection remain unclear.

      We thank the reviewer for highlighting the strength of the manuscript including the models and techniques we employ. We agree that the relationship between the microbiota and sex-dependent protection is less developed compared with other aspects of the study. In preparation of a revised manuscript, we intend on performing a more thorough comparison of male vs. female microbiota, along with quantification of sex hormones and downstream Th17 function (neutrophil recruitment and activation).

      Reviewer #2 (Public review):

      Overall, the paper nicely adds to the growing body of literature investigating how biological sex impacts the immune system and the burden of infectious disease. The conclusions are mostly supported by the data although there are some aspects of the data that could be better addressed and clarified.

      We thank the reviewer for appreciating our contribution. We intend on performing experiments to fill-in gaps and text revisions to increase clarity and acknowledge limitations.

      (1) There is something of a disconnect between the initial microbiome data and the later data that analyzes sex hormones and chromosomes. While there are clearly differences in microbial species across the two sites (NYU and JAX) how these bacterial species might directly interact with immune cells to induce female-specific responses is left unexplored. At the very least it would help to try and link these two distinct pieces of data to try and inform the reader how the microbiome is regulating the sex-specific response. Indeed, the reader is left with no clear exploration of the microbiota's role in the persistence of the infection and thus is left wanting.

      We agree. This comment is similar to Reviewer #1’s feedback. As mentioned above, we anticipate clarifying the association between sex differences and the microbiota. We will attempt to investigate specific bacteria, although some aspects of microbiota characterization may be outside the timeframe of the revision.

      (2) While the authors make a reasonable case that Th17 T cells are important for controlling infection (using RORgt knockout mice that cannot produce Th17 cells), it is not clear how these cells even arise during infection since the authors make most of the observations 2 days post-infection which is longer before a normal adaptive immune response would be expected to arise. The authors acknowledge this, but their explanation is incomplete. The increase in Th17 cells they observe is predicated on mitogenic stimulation, so they are not specific (at least in this study) for MRSA. It would be helpful to see a specific restimulation of these cells with MRSA antigens to determine if there are pre-existing, cross-reactive Th17 cells specific for MRSA and microbiota species which could then link these two as mentioned above.

      We acknowledge that this is a major limitation of our study. Although an experiment demonstrating pre-existing, cross-reactive T cells would help support our conclusion, aspects of MRSA biology may make the results of this experiment difficult to interpret. We have consulted with an expert on MRSA virulence factors, co-lead author Dr. Victor Torres, about the feasibility of this experiment. MRSA possess superantigens, such as Staphylococcal enterotoxin B, which bind directly to specific Vβ regions of T-cell receptors (TCR) and major histocompatibility complex (MHC) class II on antigen-presenting cells, resulting in hyperactivation of T lymphocytes and monocytes/macrophages. Additionally, other MRSA virulence factors, such as α-hemolysin and LukED, can induce cell death of lymphocytes. MRSA’s enterotoxins are heat stable, so heat-inactivation of the bacterium may not help in this matter.  For these reasons, restimulation of lymphocytes with MRSA antigens may be difficult to interpret. We humbly suggest that addressing this aspect of the mechanism is outside the scope of this manuscript.

      A study by Shao et al. provides an example of a host commensal species inducing Th17 cells with cross-reactivity against MRSA. Upon intestinal colonization, the intestinal fungus Candida albicans influences T cell polarization towards a Th17 phenotype in the spleen and peripheral lymph nodes which provided protection to the host against systemic candidemia. Interestingly, this induction of protective Th17 cells, increased IL-17 and responsiveness in circulating Ly6G+ neutrophils also protected mice from intravenous infection with MRSA, indicating that T cell activation and polarization by intestinal C. albicans leads to non-specific protective responses against extracellular pathogens.

      Shao TY, Ang WXG, Jiang TT, Huang FS, Andersen H, Kinder JM, Pham G, Burg AR, Ruff B, Gonzalez T, Khurana Hershey GK, Haslam DB, Way SS. Commensal Candida albicans Positively Calibrates Systemic Th17 Immunological Responses. Cell Host & Microbe. 2019 Mar 13;25(3):404-417.e6. doi: 10.1016/j.chom.2019.02.004. PMID: 30870622; PMCID: PMC6419754.

      Reviewer #3 (Public review):

      Strengths:

      A strength of the work is the rigorous experimental design. Appropriate controls were executed and, in most cases, multiple approaches were conducted to strengthen the authors' conclusions. The conclusions are supported by the data.

      The following suggestions are offered to improve an already strong piece of scholarship.

      Weaknesses:

      The correlation between female sex hormones and the elimination of S. aureus from the gut could be further validated by quantifying sex hormones produced in the four core genotype mice in response to colonization. Additionally, and this may not be feasible, but according to the proposed model administering female sex hormones to male mice should decrease colonization. Finally, knowing whether the quantity of IL-17a CD4+ cells change in the OVX mice has the potential to discern whether abundance/migration of the cells or their activation is promoted by female sex hormones.

      In the Discussion, the authors highlight previous work establishing a link between immune cells and sex hormone receptors, but whether the estrogen (and progesterone) receptor is differentially expressed in response to S. aureus colonization could be assessed in the RNAseq dataset. Differential expression of known X and Y chromosome-linked genes were discussed but specific sex hormones or sex hormone receptors, like the estrogen receptor, were not. This potential result could be highlighted.

      We appreciate the comment on the scholarship and thank the Reviewer for the insightful suggestions to improve this manuscript. We intend on measuring hormone levels and performing the recommended (or similar) experiments based on availability of reagents and mice during the revision period. We also apologize for not including references that address some of the Reviewer’s questions. Other research groups have compared the levels of hormones between XX and XY males and females in the four core genotypes model and have found similar levels of circulating testosterone in adult XX and XY males. No difference was found in circulating estradiol levels in XX vs XY- females when tested at 4-6 or 7-9 months of age.

      Karen M. Palaszynski, Deborah L. Smith, Shana Kamrava, Paul S. Burgoyne, Arthur P. Arnold, Rhonda R. Voskuhl, A Yin-Yang Effect between Sex Chromosome Complement and Sex Hormones on the Immune Response. Endocrinology, Volume 146, Issue 8, 1 August 2005, Pages 3280–3285, https://doi.org/10.1210/en.2005-0284

      Sasidhar MV, Itoh N, Gold SM, Lawson GW, Voskuhl RR. The XX sex chromosome complement in mice is associated with increased spontaneous lupus compared with XY. Ann Rheum Dis. 2012 Aug;71(8):1418-22. doi: 10.1136/annrheumdis-2011-201246. Epub 2012 May 12. PMID: 22580585; PMCID: PMC4452281.

      Examination of the levels of estrogen, progesterone, and androgen receptors in our cecal-colonic lamina propria RNA-seq dataset is an excellent idea. We will add these analyses to the revised manuscript. We are planning additional experiments to better understand the contributions of hormones or their receptors and anticipate including such data in either a response letter or revised manuscript.

    1. Author response

      The following is the authors’ response to the original reviews.

      We thank the editors and reviewers for their thoughtful comments on our manuscript. We greatly appreciated the suggestions and recommendations that helped us to improve the study. With adaptations, and inclusion of novel data and analyses, we have addressed all points raised, and hope that by these improvements the study further meets the standards for eLife. 

      Reviewer #1 (Recommendations For The Authors):

      Minor text edits should be made.

      (1.1) As a recent study from the Wong lab also showed sebaceous gland regeneration following complete ablation (Veniaminova et al., 2023), this finding should be mentioned in the text, and the abstract ("Most strikingly...") should be toned down.

      We thank the reviewer for the positive feedback, and for highlighting this part of the study from the Wong lab. Although we cited this study study in a different context, we had not discussed the sebaceous gland regeneration finding. We have now added this to the discussion section of the manuscript.

      (1.2) Introduction: In lines 31-33 discussing the connection of sebaceous glands with skin disorders, the 5 references cited seem to replicate the citations from a similar sentence in Veniaminova et al., 2019. The authors should vary their citations, as there are likely other publications that can be cited here.

      Additional references have been added.

      Reviewer #2 (Recommendations For The Authors):

      The manuscript is well written and the data are well presented in the figures.

      We thank the reviewer for the positive feedback.

      (2.1) Here are some points that could be taken into consideration to improve the manuscript:

      - Row 75 "the primary" regulator could be changed to "a crucial".

      We appreciate this suggestion and have made the text edit.

      - Row 86 could be added: ...is the dominant ligand of the Notch signalling.

      We have made the text edit as suggested.

      (2.2) Row 107-109 from the quantification of Figure 1G and Figure 2 it seems that only the aJ2 treatment has an SG phenotype. Why aJ1 doesn't have any effect? (same is true in other figures). If the data on aJ1 are maintained in the manuscript, this should be argued in the discussion section.

      The reviewer is correct in noting that the aJ1 treatment does not cause the phenotype, and this is indeed one of the key findings of the study. This is maintained throughout the manuscript. We have also cited references showing that embryonic and adult deletions of Jag1 do not cause any sebaceous gland defects. All these data argue that Jag1 is not the relevant Notch signaling ligand in sebocyte differentiation. We have further clarified this in the manuscript.

      (2.3) Related to Figure 3G. As the Lrig1 stem cells can go towards both the sebocyte differentiation, or the sebaceous duct differentiation, it would be interesting to evaluate if the differentiation impairment caused by the antibody treatment affects in a similar manner (or not) the sebaceous duct differentiation. This could be tested through immunofluorescence, selecting markers of sebaceous duct.

      We thank the reviewer for this thoughtful question. We are unable to find any unique markers of the sebaceous ducts (that are not expressed in other parts of the sebaceous gland, especially sebocytes) in the literature, thus, any analysis of markers would be confounded by its change of expression due to the loss of sebocytes.

      However, we have evaluated the histology using bursting sebocytes releasing sebum as a proxy of a functional sebaceous duct. We have not found any significant differences between treatments using this metric (Fig. S1).

      (2.4) As the word "therapeutic" is often underlined in the manuscript, maybe a few sentences on the transnational aspects of the results could be added to the discussion.

      We thank the reviewer for highlighting this point. We have added this to the discussion.

      (2.5) Figure 3 suggests that Jag2 is produced by basal sebocytes and used by these cells to induce sebocyte differentiation. I'm wondering if in an in vitro cell system (with a mixture of marked Jag2-expressing cells and marked Jag2-negative cells), it would be possible to understand if this mechanism of differentiation is a cell-autonomous mechanism or a mechanism based on cell competition (for instance, it would be possible that the progenitors compete for their niche on the basal layer by pushing neighbouring basal cells to differentiate presenting them Jag2).

      We thank the reviewer for the insightful suggestion. The mechanistic underpinning of how Notch signaling induces sebocyte differentiation is still unclear, and we find the reviewer’s suggestion very interesting. However, establishing an in vitro model that captures the aspects mentioned, would require a lot of optimization and validation. To help rapid dissemination of our findings we elected to keep this out of the manuscript, but we will certainly consider it for future studies.

      Reviewer #3 (Recommendations For The Authors):

      (3.1) The authors focussed on mouse back skin sebaceous glands to analyse the phenotype. Are the effects also reproducible in the sebaceous glands of the mouse ears and tail epidermis? If so, the data should be strengthened by quantifying the phenotype using tail epidermal whole mounts (Braun et al., 2003; Development, PMID: 12954714), ideally by co-staining sebaceous glands for differentiation markers (e.g. FASN, Adipophilin) or lipid deposits (e.g., Oil red O). Also, the authors need to clarify how many sebaceous glands were scored per mouse. If not, please provide a rationale explaining the location restriction.

      We thank the reviewer for pointing this out. Indeed, we have only incorporated data from the telogen dorsal skin of the animals. We have now more accurately reflected this in the revised manuscript. Additionally, we have added the number of sebaceous glands quantified in each figure per the reviewer’s suggestion.

      Since the stage of hair growth cycle can affect the sebaceous glands, we chose the resting (telogen) phase of the hair cycle to reliably study the sebaceous glands. At 8 weeks of age, hair follicles have uniformly entered the telogen phase. As subsequent re-entry into the anagen phase is asynchronous in the adult skin, the color of the dorsal skin of C57BL/6 mice can be used to determine whether the hair follicles are in the telogen phase or not. These reasons led us to choose this location, allowing us to study only telogen phase hair follicles.

      We also point out that previously reported data (Estrach et al., 2006) did not show differences between dorsal and tail skin, so we assume the mechanisms must largely be conserved. However, as the reviewer rightfully points out, we cannot be sure and have, therefore, indicated the dorsal location throughout the manuscript.

      (3.2) The micrographs in Figure 2 suggest that expression of both Jagged2 and Notch1 (intercellular domain) is not restricted to the sebaceous glands, as both molecules appear to be detected also in the isthmus and lower hair follicle. Of note, the online tool provided by the Kasper and Linnarsson labs (http://linnarssonlab.org/epidermis/) shows that both molecules are more widely expressed in mouse back skin. Please provide some analysis of the overall expression of these molecules in mouse skin. In line, is the observed effect of using the antagonising antibodies restricted to the sebaceous glands? Please provide additional data on proliferation and differentiation in the interfollicular epidermis, hair follicle cycling, and other skin compartments. For instance, the data published in the cited paper by Lafkas et al. (2005) suggest a thickening of the dermal adipocyte layer upon Jagged2 inhibition using monoclonal therapeutic antibodies.

      The reviewer is correct in noting that expression of both Jag2 and Notch1 is not restricted to the sebaceous gland. The Notch signaling pathway is a well-known regulator for epidermal differentiation, and members of the pathway are expressed in various locations of the skin, including the interfollicular epidermis and the hair follicle. The expression and function of Notch signaling in these locations has been reviewed in (Hsu et al., 2014; Nowell and Radtke, 2013; Watt et al., 2008). We have also added zoomed out images showing expression of Jag2 and Notch1 in the skin (Figure S2e,f).

      The effect of the antagonizing antibodies is not restricted to sebaceous glands, as we already noted in our discussion section: “While injections of the Notch blocking antibodies are systemic, we only observed a reduction in the number of Notch-active cells in the IFE, but not a complete loss.” The functional impact of the antibodies is likely beyond the sebaceous gland, as the reviewer points out, but understanding the full effect in other compartments, we consider beyond the scope of the current study.

      In our previous study (Lafkas et al., 2015), the skin was examined at different animal ages/gender and using different antibody dosing regimens, which is the likely explanation for the differences observed. We have now quantified the width of the adipocyte layer and the IFE and show that there are no significant differences between treatments (Figure S1g-j). This together with the histology suggest that there are no significant differences in the differentiation and proliferation of these compartments.

      (3.3) Since Jagged1 is a Wnt/beta-catenin target gene that is essential for (ectopic) hair follicle formation and differentiation (Estrach et al., 2006, Development, PMID: 17035290) and the sebaceous gland is widely considered as an epidermal compartment with absent/low Wnt/beta-catenin pathway activity during normal homeostasis (Lim & Nusse, 2013, Cold Spring Habor Perspectives in Biology, PMID: 23209129), how is the expression of Notch1 and Jagged2 regulated upstream in sebocyte progenitors? It would be important to bring some more mechanistic insights into the upstream regulation of Notch activity. In line with comment 2, how are the compartment-specific effects molecularly regulated if the effects are not restricted to the sebaceous glands?

      The reviewer is correct in noting that the Wnt pathway does not seem to be a likely candidate for driving sebocyte differentiation through Notch signaling. Indeed, Wnt inhibition is required for sebocyte differentiation (Merrill et al., 2001; Niemann et al., 2002), and the Jag2 promoter region also does not contain TCF binding sites (Katoh and Katoh, 2006).

      We speculate that Myc might regulate Notch signaling in the sebaceous gland. It is expressed in the sebaceous gland basal stem cells and has been reported to positively regulate sebocyte differentiation (Cottle et al., 2013). In addition, studies have shown that Jag2 is a Myc target gene (Fiaschetti et al., 2014; Yustein et al., 2010). However, evaluating which upstream pathway potentially regulates Notch signaling, and resolving the regulatory network of sebocyte differentiation beyond the direct Notch ligands and receptors would require extensive in vivo modeling using KO and transgenic animals, which we consider to be beyond the scope of the current manuscript.

      References

      Cottle DL, Kretzschmar K, Schweiger PJ, Quist SR, Gollnick HP, Natsuga K, Aoyagi S, Watt FM. 2013. c-MYC-Induced Sebaceous Gland Differentiation Is Controlled by an Androgen Receptor/p53 Axis. Cell Rep 3:427–441. doi:10.1016/j.celrep.2013.01.013

      Estrach S, Ambler CA, Celso CLL, Hozumi K, Watt FM. 2006. Jagged 1 is a β-catenin target gene required for ectopic hair follicle formation in adult epidermis. Development 133:4427–4438. doi:10.1242/dev.02644

      Fiaschetti G, Schroeder C, Castelletti D, Arcaro A, Westermann F, Baumgartner M, Shalaby T, Grotzer MA. 2014. NOTCH ligands JAG1 and JAG2 as critical pro-survival factors in childhood medulloblastoma. Acta Neuropathol Commun 2:39. doi:10.1186/2051-5960-2-39

      Hsu Y-C, Li L, Fuchs E. 2014. Emerging interactions between skin stem cells and their niches. Nat Med 20:847–856. doi:10.1038/nm.3643

      Katoh Masuko, Katoh Masaru. 2006. Notch ligand, JAG1, is evolutionarily conserved target of canonical WNT signaling pathway in progenitor cells. Int J Mol Med. doi:10.3892/ijmm.17.4.681

      Lafkas D, Shelton A, Chiu C, Boenig G de L, Chen Y, Stawicki SS, Siltanen C, Reichelt M, Zhou M, Wu X, Eastham-Anderson J, Moore H, Roose-Girma M, Chinn Y, Hang JQ, Warming S, Egen J, Lee WP, Austin C, Wu Y, Payandeh J, Lowe JB, Siebel CW. 2015. Therapeutic antibodies reveal Notch control of transdifferentiation in the adult lung. Nature 528:127–131. doi:10.1038/nature15715

      Merrill BJ, Gat U, DasGupta R, Fuchs E. 2001. Tcf3 and Lef1 regulate lineage differentiation of multipotent stem cells in skin. Genes Dev 15:1688–1705. doi:10.1101/gad.891401

      Niemann C, Owens DM, Hülsken J, Birchmeier W, Watt FM. 2002. Expression of ΔNLef1 in mouse epidermis results in differentiation of hair follicles into squamous epidermal cysts and formation of skin tumours. Development 129:95–109. doi:10.1242/dev.129.1.95

      Nowell C, Radtke F. 2013. Cutaneous Notch Signaling in Health and Disease. Cold Spring Harb Perspect Med 3:a017772. doi:10.1101/cshperspect.a017772

      Watt FM, Estrach S, Ambler CA. 2008. Epidermal Notch signalling: differentiation, cancer and adhesion. Curr Opin Cell Biol 20:171–179. doi:10.1016/j.ceb.2008.01.010

      Yustein JT, Liu Y-C, Gao P, Jie C, Le A, Vuica-Ross M, Chng WJ, Eberhart CG, Bergsagel PL, Dang CV. 2010. Induction of ectopic Myc target gene JAG2 augments hypoxic growth and tumorigenesis in a human B-cell model. Proc Natl Acad Sci 107:3534–3539. doi:10.1073/pnas.0901230107

    1. Author response:

      Reviewer #1 (Public review):

      Summary:

      Lodhiya et al. demonstrate that antibiotics with distinct mechanisms of action, norfloxacin, and streptomycin, cause similar metabolic dysfunction in the model organism Mycobacterium smegmatis. This includes enhanced flux through the TCA cycle and respiration as well as a build-up of reactive oxygen species (ROS) and ATP. Genetic and/or pharmacologic depression of ROS or ATP levels protect M. smegmatis from norfloxacin and streptomycin killing. Because ATP depression is protective, but in some cases does not depress ROS, the authors surmise that excessive ATP is the primary mechanism by which norfloxacin and streptomycin kill M. smegmatis. In general, the experiments are carefully executed; alternative hypotheses are discussed and considered; the data are contextualized within the existing literature. Clarification of the effect of 1) ROS depression on ATP levels and 2) ADP vs. ATP on divalent metal chelation would strengthen the paper, as would discussion of points of difference with the existing literature. The authors might also consider removing Figures 9 and 10A-B as they distract from the main point of the paper and appear to be the beginning of a new story rather than the end of the current one. Finally, statistics need some attention.

      Strengths:

      The authors tackle a problem that is both biologically interesting and medically impactful, namely, the mechanism of antibiotic-induced cell death.

      Experiments are carefully executed, for example, numerous dose- and time-dependency studies; multiple, orthogonal readouts for ROS; and several methods for pharmacological and genetic depletion of ATP.

      There has been a lot of excitement and controversy in the field, and the authors do a nice job of situating their work in this larger context.

      Inherent limitations to some of their approaches are acknowledged and discussed e.g., normalizing ATP levels to viable counts of bacteria.

      We sincerely thanks appreciate the reviewer’s encouraging feedback.

      Weaknesses:

      The authors have shown that treatments that depress ATP do not necessarily repress ROS, and therefore conclude that ATP is the primary cause of norfloxacin and streptomycin lethality for M. smegmatis. Indeed, this is the most impactful claim of the paper. However, GSH and dipyridyl beautifully rescue viability. Do these and other ROS-repressing treatments impact ATP levels? If not, the authors should consider a more nuanced model and revise the title, abstract, and text accordingly.

      We thank the reviewer for asking this question. In the revised version of the manuscript, we will include data on the impact of the antioxidant GSH on ATP levels.

      Does ADP chelate divalent metal ions to the same extent as ATP? If so, it is difficult to understand how conversion of ADP to ATP by ATP synthase would alter metal sequestration without concomitant burst in ADP levels.

      We sincerely thank the reviewer for raising this insightful question. Indeed, ADP and AMP can also form complexes with divalent metal ions; however, these complexes tend to be less stable. According to the existing literature, ATP-metal ion complexes exhibit a higher formation constant compared to ADP or AMP complexes. This has been attributed to the polyphosphate chain of ATP, which acts as an active site, forming a highly stable tridentate structure (Khan et al., 1962; Distefano et al., 1953). An antibiotic-induced increase in ATP levels, irrespective of any changes in ADP levels, could still result in the formation of more stable complexes with metal ions, potentially leading to metal ion depletion. Although recent studies indicate that antibiotic treatment stimulates purine biosynthesis (Lobritz MA et al., 2022; Yang JH et al., 2019), thereby imposing energy demands and enhancing ATP production, the possibility of a corresponding increase in total purine nucleotide levels (ADP+ATP) exist (is mentioned in discussion section). However, this hypothesis requires further investigation.

      Khan MMT, Martell AE. Metal Chelates of Adenosine Triphosphate. Journal of Physical Chemistry (US). 1962 Jan 1;Vol: 66(1):10–5

      Distefano v, Neuman wf. Calcium complexes of adenosinetriphosphate and adenosinediphosphate and their significance in calcification in vitro. Journal of Biological Chemistry. 1953 Feb 1;200(2):759–63

      Lobritz MA, Andrews IW, Braff D, Porter CBM, Gutierrez A, Furuta Y, et al. Increased energy demand from anabolic-catabolic processes drives β-lactam antibiotic lethality. Cell Chem Biol [Internet]. 2022 Feb 17.

      Yang JH, Wright SN, Hamblin M, McCloskey D, Alcantar MA, Schrübbers L, et al. A White-Box Machine Learning Approach for Revealing Antibiotic Mechanisms of Action. Cell [Internet]. 2019 May 30

      Some of the results in the paper diverge from what has been previously reported by some of the referenced literature. These discrepancies should be clarified.

      We apologize for any confusion, but we are uncertain about the specific discrepancies the reviewer is referring. In the discussion section, we have addressed and analysed our results within the broader context of the existing literature, regardless of whether our findings align with or differ from previous studies.

      Reviewer #2 (Public review):

      Summary:

      The authors are trying to test the hypothesis that ATP bursts are the predominant driver of antibiotic lethality of Mycobacteria.

      Strengths:

      This reviewer has not identified any significant strengths of the paper in its current form.

      Weaknesses:

      A major weakness is that M. smegmatis has a doubling time of three hours and the authors are trying to conclude that their data would reflect the physiology of M. tuberculosis which has a doubling time of 24 hours. Moreover, the authors try to compare OD measurements with CFU counts and thus observe great variabilities.

      If the authors had evidence to support the conclusion that ATP burst is the predominant driver of antibiotic lethality in mycobacteria then this paper would be highly significant. However, with the way the paper is written, it is impossible to make this conclusion.

      We have identified this new mechanism of antibiotic action in Mycobacterium smegmatis and have also mentioned that whether and how much of this mechanism is true in other organism needs to be tested as argued extensively in the discussion section of the manuscript.

      We have always drawn inferences from the CFU counts as the OD600nm is never a reliable method as reported in all of our experiments.

    1. Author response:

      eLife assessment

      This potentially valuable study examines the role of IL17-producing Ly6G PMNs as a reservoir for Mycobacterium tuberculosis to evade host killing activated by BCG immunisation. The authors report that IL17-producing polymorphonuclear neutrophils harbour a significant bacterial load in both wild-type and IFNg-/- mice and that targeting IL17 and Cox2 improved disease outcomes whilst enhancing BCG efficacy. Although the authors suggest that targeting these pathways may improve disease outcomes in humans, the evidence as it stands is incomplete and requires additional experimentation for the study to realise its full impact.

      Thank you for evaluating our manuscript. We understand the concern related to the direct role of Ly6G+Gra-derived IL17 in TB pathogenesis. For the revised manuscript, we will provide additional experimental evidence through direct regulation of IL-17 production in Mtb-infected mice and its impact on improving BCG efficacy.

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      Recruitment of neutrophils to the lungs is known to drive susceptibility to infection with M. tuberculosis. In this study, the authors present data in support of the hypothesis that neutrophil production of the cytokine IL-17 underlies the detrimental effect of neutrophils on disease. They claim that neutrophils harbor a large fraction of Mtb during infection, and are a major source of IL-17. To explore the effects of blocking IL-17 signaling during primary infection, they use IL-17 blocking antibodies, SR221 (an inverse agonist of TH17 differentiation), and celecoxib, which they claim blocks Th17 differentiation, and observe modest improvements in bacterial burdens in both WT and IFN-γ deficient mice using the combination of IL-17 blockade with celecoxib during primary infection. Celecoxib enhances control of infection after BCG vaccination. 

      Thank you for the summary.

      Strengths:

      The most novel finding in the paper is that treatment with celecoxib significantly enhances control of infection in BCG-vaccinated mice that have been challenged with Mtb. It was already known that NSAID treatments can improve primary infection with Mtb.

      Thank you.

      Weaknesses:

      The major claim of the manuscript - that neutrophils produce IL-17 that is detrimental to the host - is not strongly supported by the data. Data demonstrating neutrophil production of IL17 lacks rigor. 

      Our response: Neutrophil production of IL-17 is supported by two independent methods/ techniques in the current version: 

      (1) Through Flow cytometry- a large fraction of Ly6G+CD11b+ cells from the lungs of Mtb-infected mice were also positive for IL-17 (Fig. 3C).

      (2) IFA co-staining of Ly6G + cells with IL-17 in the lung sections from Mtb-infected mice (Fig. 3 E_G and Fig. 4H, Fig. 5I).

      However, to further strengthen this observation, we plan to analyse sorted Ly6G+Gra from the lungs of infected mice using IL-17 ELISPOT assay. This will unequivocally prove the Ly6+Gra production of IL-17. Several publications support the production of IL-17 by neutrophils (Li et al. 2010; Katayama et al. 2013; Lin et al. 2011). For example, neutrophils have been identified as a source of IL-17 in human psoriatic lesions (Lin et al. 2011), in neuroinflammation induced by traumatic brain injury (Xu et al. 2023) and in several mouse models of infectious and autoimmune inflammation (Ferretti et al. 2003; Hoshino et al. 2008) (Li et al. 2010). However, ours is the first study reporting neutrophil IL-17 production during Mtb pathology.

      The experiments examining the effects of inhibitors of IL-17 on the outcome of infection are very difficult to interpret. First, treatment with IL-17 inhibitors alone has no impact on bacterial burdens in the lung, either in WT or IFN-γ KO mice. This suggests that IL-17 does not play a detrimental role during infection. Modest effects are observed using the combination of IL-17 blocking drugs and celecoxib, however, the interpretation of these results mechanistically is complicated. Celecoxib is not a specific inhibitor of Th17. Indeed, it affects levels of PGE2, which is known to have numerous impacts on Mtb infection separate from any effect on IL-17 production, as well as other eicosanoids. 

      The reviewer correctly says that Celecoxib is not a specific inhibitor of Th17. However, COX-2 inhibition does have an effect on IL-17 levels, and numerous reports support this observation (Paulissen et al. 2013; Napolitani et al. 2009; Lemos et al. 2009). We elaborate on the results below for better clarity.

      Firstly, in the WT mice, Celecoxib treatment led to a complete loss of IL-17 production in the lungs of Mtb-infected mice (Fig. 5D). Interestingly, IL-17 production independent of IL-23 is known to require PGE2 (Paulissen et al. 2013; Polese et al. 2021). In the WT or IFNγ KO mice, we rather noted a decline in IL-23 levels post-infection, suggesting a possible role of PGE2 in IL-17 production. However, in the lung homogenates of Mtb-infected IFNγ KO mice, Celecoxib had no effect on IL-17 levels in the lung homogenates. Thus, celecoxib controls IL-17 levels only in the Mtb-infected WT mice. Including celecoxib with anti-IL17 in the IFNγ KO mice controls pathology and extends its survival.

      Second, the reviewer’s observation is only partially correct that IL-17 inhibition has a modest effect on the outcome of infection. While IL-17 neutralization and inhibition alone in the IFNγ KO mice and WT mice, respectively, did not bring down the lung CFU burden significantly, in both these cases, there was an improvement in the lung pathology. The reduced pathology coincided with reduced neutrophil recruitment and a reduced Ly6G+Graresident Mtb population in the WT mice. IL-17 neutralization alone improved IFNγ KO mice survival by ~10 days (Fig. 4F-G). 

      Third, regarding the SR2211 and Celecoxib combination study, we agree with the reviewer that Celecoxib has roles independent of IL-17 regulation. However, in the results presented in this study, there are three key aspects- 1) neutrophil-derived IL-17-dependent neutrophil recruitment, 2) the presence of a large proportion of intracellular Mtb in the neutrophils and 3) dissemination of Mtb to the spleen. Celecoxib treatment alone helps reduce lung Mtb burden in the WT mice. However, SR2211 fails to do so. It is evident that celecoxib is doing more than just inhibiting IL-17 production. The result shows that celecoxib blocks neutrophil recruitment (which could be an IL-17-dependent mechanism) and also controls the intraneutrophil bacterial population. Finally, either SR2211 or celecoxib could block dissemination to the spleen. The role of neutrophils in TB dissemination is only beginning to emerge (Hult et al. 2021). We will revise the description in the results and discussion section for this data to make it easier to understand.

      Finally, we have also done experiments with SR2211 in BCG-vaccinated animals, which shows the direct impact of IL-17 inhibition on the BCG vaccine efficacy. We will add this result in the revised version.

      Finally, the human data simply demonstrates that neutrophils and IL-17 both are higher in patients who experience relapse after treatment for TB, which is expected and does not support their specific hypothesis. 

      We disagree with the above statement. Why a higher IL-17 is expected in patients who show relapse, death or failed treatment outcomes? Classically, IL-17 is believed to be protective against TB, and the reviewer also points to that in the comments below. A very limited set of studies support the non-protective/pathological role of IL-17 in tuberculosis (Cruz et al. 2010). High IL-17 and neutrophilia at the baseline in the human subjects (i.e. at the time of recruitment in the study) highlight severe pathology in those subjects, which could have contributed to the failed treatment outcome. This observation in the human cohort strongly supports the overall theme and central observation in this study.

      The use of genetic ablation of IL-17 production specifically in neutrophils and/or IL-17R in mice would greatly enhance the rigor of this study. 

      The reviewer’s point is well-taken. Having a genetic ablation of IL-17 production, specifically in the neutrophils, would be excellent. At present, however, we lack this resource, and therefore, it is not feasible to do this experiment within a defined timeline. Instead, for the revised manuscript, we will present the data with SR2211, a direct inhibitor of RORgt and, therefore, IL-17, in BCG-vaccinated mice.

      The authors do not address the fact that numerous studies have shown that IL-17 has a protective effect in the mouse model of TB in the context of vaccination.

      Yes, there are a few articles that talk about the protective effect of IL-17 in the mouse model of TB in the context of vaccination (Khader et al. 2007; Desel et al. 2011; Choi et al. 2020). This part was discussed in the original manuscript (in the Introduction section). For the revised manuscript, we will also provide results from the experiment where we blocked IL-17 production by inhibiting RORgt using SR2211 in BCG-vaccinated mice. The results clearly show IL-17 as a negative regulator of BCG-mediated protective immunity. We believe some of the reasons for the observed differences could be 1) in our study, we analysed IL-17 levels in the lung homogenates at late phases of infection, and 2) most published studies rely on ex vivo stimulation of immune cells to measure cytokine production, whereas we actually measured the cytokine levels in the lung homogenates. We will elaborate on these points in the revised version.

      Finally, whether and how many times each animal experiment was repeated is unclear.

      We will provide the details of the number of experiments in the revised version. Briefly, the BCG vaccination experiment (Figure 1) and BCG vaccination with Celecoxib treatment experiment (Figure 6) were performed twice and thrice, respectively. The IL-17 neutralization experiment (Figure 4) and the SR2211 treatment experiment (Figure 5) were done once. We will add another SR2211 experiment data in the revised version. 

      Reviewer #2 (Public review):

      Summary:

      In this study, Sharma et al. demonstrated that Ly6G+ granulocytes (Gra cells) serve as the primary reservoirs for intracellular Mtb in infected wild-type mice and that excessive infiltration of these cells is associated with severe bacteremia in genetically susceptible IFNγ/- mice. Notably, neutralizing IL-17 or inhibiting COX2 reversed the excessive infiltration of Ly6G+Gra cells, mitigated the associated pathology, and improved survival in these susceptible mice. Additionally, Ly6G+Gra cells were identified as a major source of IL-17 in both wild-type and IFNγ-/- mice. Inhibition of RORγt or COX2 further reduced the intracellular bacterial burden in Ly6G+Gra cells and improved lung pathology.

      Of particular interest, COX2 inhibition in wild-type mice also enhanced the efficacy of the BCG vaccine by targeting the Ly6G+Gra-resident Mtb population.

      Thank you for the summary.

      Strengths:

      The experimental results showing improved BCG-mediated protective immunity through targeting IL-17-producing Ly6G+ cells and COX2 are compelling and will likely generate significant interest in the field. Overall, this study presents important findings, suggesting that the IL-17-COX2 axis could be a critical target for designing innovative vaccination strategies for TB.

      Thank you for highlighting the overall strengths of the study.  Weaknesses:

      However, I have the following concerns regarding some of the conclusions drawn from the experiments, which require additional experimental evidence to support and strengthen the overall study.

      Major Concerns:

      (1) Ly6G+ Granulocytes as a Source of IL-17: The authors assert that Ly6G+ granulocytes are the major source of IL-17 in wild-type and IFN-γ KO mice based on colocalization studies of Ly6G and IL-17. In Figure 3D, they report approximately 500 Ly6G+ cells expressing IL-17 in the Mtb-infected WT lung. Are these low numbers sufficient to drive inflammatory pathology? Additionally, have the authors evaluated these numbers in IFN-γ KO mice? 

      Thank you for pointing out about the numbers in Fig. 3D. It was our oversight to label the axis as No. of IL17+Ly6G+Gra/lung. For this data, only a part of the lung was used. For the revised manuscript, we will provide the number of these cells at the whole lung level from Mtb-infected WT mice. Unfortunately, we did not evaluate these numbers in IFN-γ KO mice through FACS. 

      For the assertion that Ly6G+Gra are the major source of IL-17 in TB, we have used two separate strategies- a) IFA and b) FACS. 

      However, as described above in response to the first reviewer, for the revision, we propose to perform an IL-17 ELISpot assay on the sorted Ly6G+Gra from the lungs of Mtb-infected WT mice.

      (2) Role of IL-17-Producing Ly6G Granulocytes in Pathology: The authors suggest that IL17-producing Ly6G granulocytes drive pathology in WT and IFN-γ KO mice. However, the data presented only demonstrate an association between IL-17+ Ly6G cells and disease pathology. To strengthen their conclusion, the authors should deplete neutrophils in these mice to show that IL-17 expression, and consequently the pathology, is reduced.

      Thank you for this suggestion. Others have done neutrophil depletion studies in TB, and so far, the outcomes remain inconclusive. In some studies, neutrophil depletion helps the pathogen (Rankin et al. 2022; Pedrosa et al. 2000; Appelberg et al. 1995), and in others, it helps the host (Lovewell et al. 2021; Mishra et al. 2017) ). One reason for this variability is the stage of infection when neutrophil depletion was done. However, another crucial factor is the heterogeneity in the neutrophil population. There are reports that suggest neutrophil subtypes with protective versus pathological trajectories (Nwongbouwoh Muefong et al. 2022; Lyadova 2017; Hellebrekers, Vrisekoop, and Koenderman 2018; Leliefeld et al. 2018). Depleting the entire population using anti-Ly6G could impact this heterogeneity and may impact the inferences drawn. A better approach would be to characterise this heterogeneous population, efforts towards which could be part of a separate study.

      For the revised manuscript, we will provide results from the SR2211 experiment in BCG-vaccinated mice and other results to show the role of IL-17-producing Ly6G+Gra in TB pathology.   

      (3) IL-17 Secretion by Mtb-Infected Neutrophils: Do Mtb-infected neutrophils secrete IL-17 into the supernatants? This would serve as confirmation of neutrophil-derived IL-17. Additionally, are Ly6G+ cells producing IL-17 and serving as pathogenic agents exclusively in vivo? The authors should provide comments on this.

      We have not directly measured IL-17 secretion by neutrophils in our experiments. However, Hu et al have reported IL-17 secretion by Mtb-infected neutrophils in vitro (Hu et al. 2017). Whether there are a few neutrophil roles exclusively seen under in vivo condition is an interesting proposition. We do have some observations that suggest in vitro phenotype of Mtb-infected neutrophils is different from in vivo.

      (4) Characterization of IL-17-Producing Ly6G+ Granulocytes: Are the IL-17-producing Ly6G+ granulocytes a mixed population of neutrophils and eosinophils, or are they exclusively neutrophils? Sorting these cells followed by Giemsa or eosin staining could clarify this.

      This is a very important point. While usually eosinophils do not express Ly6G markers in laboratory mice, under specific contexts, including infections, eosinophils can express Ly6G. Since we have not characterized these potential Ly6G+ sub-populations, that is one of the reasons we refer to the cell types as Ly6G+ granulocytes, which do not exclude Ly6G+ eosinophils. A detailed characterization of these subsets could be taken up as a separate study.

      Reviewer #3 (Public review):

      Summary:

      The authors examine how distinct cellular environments differentially control Mtb following BCG vaccination. The key findings are that IL17-producing PMNs harbor a significant Mtb load in both wild-type and IFNg-/- mice. Targeting IL17 and Cox2 improved disease and enhanced BCG efficacy over 12 weeks and neutrophils/IL17 are associated with treatment failure in humans. The authors suggest that targeting these pathways, especially in MSMD patients may improve disease outcomes.

      Thank you.

      Strengths:

      The experimental approach is generally sound and consists of low-dose aerosol infections with distinct readouts including cell sorting followed by CFU, histopathology, and RNA sequencing analysis. By combining genetic approaches and chemical/antibody treatments, the authors can probe these pathways effectively.

      Understanding how distinct inflammatory pathways contribute to control or worsen Mtb disease is important and thus, the results will be of great interest to the Mtb field.

      Thank you.

      Weaknesses:

      A major limitation of the current study is overlooking the role of non-hematopoietic cells in the IFNg/IL17/neutrophil response. Chimera studies from Ernst and colleagues (PMCID: PMC2807991) previously described this IDO-dependent pathway following the loss of IFNg through an increased IL17 response. This study is not cited nor discussed even though it may alter the interpretation of several experiments.

      Thank you for pointing out this earlier study, which we concede we missed discussing. We disagree on the point that results from that study may alter the interpretation of several experiments in our study. On the contrary, the main observation that loss of IFNγ causes severe IL-17 levels is aligned in both studies.

      IDO1 is known to alter Th cell differentiation towards Tregs and away from Th17 (Baban et al. 2009). It is absolutely feasible for the non-hematopoietic cells to regulate these events. However, that does not rule out the neutrophil production of IL-17 and the downstream pathological effect shown in this study. We will discuss and cite this study in the revised manuscript.

      Several of the key findings in mice have previously been shown (albeit with less sophisticated experimentation) and human disease and neutrophils are well described - thus the real new finding is how intracellular Mtb in neutrophils are more refractory to BCGmediated control. However, given there are already high levels of Mtb in PMNs compared to other cell types, and there is a decrease in intracellular Mtb in PMNs following BCG immunization the strength of this finding is a bit limited.

      The reviewer’s interpretation of the BCG-refractory Mtb population in the neutrophil is interesting. The reviewer is right that neutrophils had a higher intracellular Mtb burden, which decreased in the BCG-vaccinated animals. Thus, on that account, the reviewer rightly mentions that BCG is able to control Mtb even in neutrophils. However, BCG almost clears intracellular burden from other cell types analysed, and therefore, the remnant pool of intracellular Mtb in the lungs of BCG-vaccinated animals could be mostly those present in the neutrophils. This is a substantial novel development in the field and attracts focus towards innate immune cells for vaccine efficacy. 

      References:

      Appelberg, R., A. G. Castro, S. Gomes, J. Pedrosa, and M. T. Silva. 1995. 'SuscepBbility of beige mice to Mycobacterium avium: role of neutrophils', Infect Immun, 63: 3381-7.

      Baban, B., P. R. Chandler, M. D. Sharma, J. Pihkala, P. A. Koni, D. H. Munn, and A. L. Mellor. 2009. 'IDO activates regulatory T cells and blocks their conversion into Th17-like T cells', J Immunol, 183: 2475-83.

      Choi, H. G., K. W. Kwon, S. Choi, Y. W. Back, H. S. Park, S. M. Kang, E. Choi, S. J. Shin, and H. J. Kim. 2020. 'AnBgen-Specific IFN-gamma/IL-17-Co-Producing CD4(+) T-Cells Are the Determinants for ProtecBve Efficacy of Tuberculosis Subunit Vaccine', Vaccines (Basel), 8.

      Cruz, A., A. G. Fraga, J. J. Fountain, J. Rangel-Moreno, E. Torrado, M. Saraiva, D. R. Pereira, T. D. Randall, J. Pedrosa, A. M. Cooper, and A. G. Castro. 2010. 'Pathological role of interleukin 17 in mice subjected to repeated BCG vaccination after infection with Mycobacterium tuberculosis', J Exp Med, 207: 1609-16.

      Desel, C., A. Dorhoi, S. Bandermann, L. Grode, B. Eisele, and S. H. Kaufmann. 2011. 'Recombinant BCG DeltaureC hly+ induces superior protection over parental BCG by simulating a balanced combination of type 1 and type 17 cytokine responses', J Infect Dis, 204: 1573-84.

      Ferreg, S., O. Bonneau, G. R. Dubois, C. E. Jones, and A. Trifilieff. 2003. 'IL-17, produced by lymphocytes and neutrophils, is necessary for lipopolysaccharide-induced airway neutrophilia: IL-15 as a possible trigger', J Immunol, 170: 2106-12.

      Hellebrekers, P., N. Vrisekoop, and L. Koenderman. 2018. 'Neutrophil phenotypes in health and disease', Eur J Clin Invest, 48 Suppl 2: e12943.

      Hoshino, A., T. Nagao, N. Nagi-Miura, N. Ohno, M. Yasuhara, K. Yamamoto, T. Nakayama, and K. Suzuki. 2008. 'MPO-ANCA induces IL-17 production by activated neutrophils in vitro via classical complement pathway-dependent manner', J Autoimmun, 31: 79-89.

      Hu, S., W. He, X. Du, J. Yang, Q. Wen, X. P. Zhong, and L. Ma. 2017. 'IL-17 ProducBon of Neutrophils Enhances AnBbacteria Ability but Promotes ArthriBs Development During Mycobacterium tuberculosis InfecBon', EBioMedicine, 23: 88-99.

      Hult, C., J. T. Magla, H. P. Gideon, J. J. Linderman, and D. E. Kirschner. 2021. 'Neutrophil Dynamics Affect Mycobacterium tuberculosis Granuloma Outcomes and DisseminaBon', Front Immunol, 12: 712457.

      Katayama, M., K. Ohmura, N. Yukawa, C. Terao, M. Hashimoto, H. Yoshifuji, D. Kawabata, T. Fujii, Y. Iwakura, and T. Mimori. 2013. 'Neutrophils are essential as a source of IL-17 in the effector phase of arthritis', PLoS One, 8: e62231.

      Khader, S. A., G. K. Bell, J. E. Pearl, J. J. Fountain, J. Rangel-Moreno, G. E. Cilley, F. Shen, S. M. Eaton, S. L. Gaffen, S. L. Swain, R. M. Locksley, L. Haynes, T. D. Randall, and A. M. Cooper. 2007. 'IL-23 and IL-17 in the establishment of protective pulmonary CD4+ T cell responses after vaccination and during Mycobacterium tuberculosis challenge', Nat Immunol, 8: 369-77.

      Leliefeld, P. H. C., J. Pillay, N. Vrisekoop, M. Heeres, T. Tak, M. Kox, S. H. M. Rooijakkers, T. W. Kuijpers, P. Pickkers, L. P. H. Leenen, and L. Koenderman. 2018. 'DifferenBal antibacterial control by neutrophil subsets', Blood Adv, 2: 1344-55.

      Lemos, H. P., R. Grespan, S. M. Vieira, T. M. Cunha, W. A. Verri, Jr., K. S. Fernandes, F. O. Souto, I. B. McInnes, S. H. Ferreira, F. Y. Liew, and F. Q. Cunha. 2009. 'Prostaglandin mediates IL-23/IL-17induced neutrophil migraBon in inflammation by inhibiting IL-12 and IFNgamma production', Proc Natl Acad Sci U S A, 106: 5954-9.

      Li, L., L. Huang, A. L. Vergis, H. Ye, A. Bajwa, V. Narayan, R. M. Strieter, D. L. Rosin, and M. D. Okusa. 2010. 'IL-17 produced by neutrophils regulates IFN-gamma-mediated neutrophil migration in mouse kidney ischemia-reperfusion injury', J Clin Invest, 120: 331-42.

      Lin, A. M., C. J. Rubin, R. Khandpur, J. Y. Wang, M. Riblen, S. Yalavarthi, E. C. Villanueva, P. Shah, M. J. Kaplan, and A. T. Bruce. 2011. 'Mast cells and neutrophils release IL-17 through extracellular trap formation in psoriasis', J Immunol, 187: 490-500.

      Lovewell, R. R., C. E. Baer, B. B. Mishra, C. M. Smith, and C. M. Sasseg. 2021. 'Granulocytes act as a niche for Mycobacterium tuberculosis growth', Mucosal Immunol, 14: 229-41.

      Lyadova, I. V. 2017. 'Neutrophils in Tuberculosis: Heterogeneity Shapes the Way?', Mediators Inflamm, 2017: 8619307.

      Mishra, B. B., R. R. Lovewell, A. J. Olive, G. Zhang, W. Wang, E. Eugenin, C. M. Smith, J. Y. Phuah, J. E. Long, M. L. Dubuke, S. G. Palace, J. D. Goguen, R. E. Baker, S. Nambi, R. Mishra, M. G. Booty, C. E. Baer, S. A. Shaffer, V. Dartois, B. A. McCormick, X. Chen, and C. M. Sasseg. 2017. 'Nitric oxide prevents a pathogen-permissive granulocytic inflammation during tuberculosis', Nat Microbiol, 2: 17072.

      Napolitani, G., E. V. Acosta-Rodriguez, A. Lanzavecchia, and F. Sallusto. 2009. 'Prostaglandin E2 enhances Th17 responses via modulation of IL-17 and IFN-gamma production by memory CD4+ T cells', Eur J Immunol, 39: 1301-12.

      Nwongbouwoh Muefong, C., O. Owolabi, S. Donkor, S. Charalambous, A. Bakuli, A. Rachow, C. Geldmacher, and J. S. Sutherland. 2022. 'Neutrophils Contribute to Severity of Tuberculosis Pathology and Recovery From Lung Damage Pre- and Posnreatment', Clin Infect Dis, 74: 1757-66.

      Paulissen, S. M., J. P. van Hamburg, N. Davelaar, P. S. Asmawidjaja, J. M. Hazes, and E. Lubberts. 2013. 'Synovial fibroblasts directly induce Th17 pathogenicity via the cyclooxygenase/prostaglandin E2 pathway, independent of IL-23', J Immunol, 191: 1364-72.

      Pedrosa, J., B. M. Saunders, R. Appelberg, I. M. Orme, M. T. Silva, and A. M. Cooper. 2000. 'Neutrophils play a protective nonphagocytic role in systemic Mycobacterium tuberculosis infection of mice', Infect Immun, 68: 577-83.

      Polese, B., B. Thurairajah, H. Zhang, C. L. Soo, C. A. McMahon, G. Fontes, S. N. A. Hussain, V. Abadie, and I. L. King. 2021. 'Prostaglandin E(2) amplifies IL-17 production by gamma-delta T cells during barrier inflammation', Cell Rep, 36: 109456.

      Rankin, A. N., S. V. Hendrix, S. K. Naik, and C. L. Stallings. 2022. 'Exploring the Role of Low-Density Neutrophils During Mycobacterium tuberculosis InfecBon', Front Cell Infect Microbiol, 12: 901590.

      Xu, X. J., Q. Q. Ge, M. S. Yang, Y. Zhuang, B. Zhang, J. Q. Dong, F. Niu, H. Li, and B. Y. Liu. 2023. 'Neutrophil-derived interleukin-17A participates in neuroinflammation induced by traumatic brain injury', Neural Regen Res, 18: 1046-51.

    1. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      This study puts forth the model that under IFN-B stimulation, liquid-phase WTAP coordinates with the transcription factor STAT1 to recruit MTC to the promoter region of interferon-stimulated genes (ISGs), mediating the installation of m6A on newly synthesized ISG mRNAs. This model is supported by strong evidence that the phosphorylation state of WTAP, regulated by PPP4, is regulated by IFN-B stimulation, and that this results in interactions between WTAP, the m6A methyltransferase complex, and STAT1, a transcription factor that mediates activation of ISGs. This was demonstrated via a combination of microscopy, immunoprecipitations, m6A sequencing, and ChIP. These experiments converge on a set of experiments that nicely demonstrate that IFN-B stimulation increases the interaction between WTAP, METTL3, and STAT1, that this interaction is lost with the knockdown of WTAP (even in the presence of IFN-B), and that this IFN-B stimulation also induces METTL3-ISG interactions.

      Strengths:

      The evidence for the IFN-B stimulated interaction between METTL3 and STAT1, mediated by WTAP, is quite strong. Removal of WTAP in this system seems to be sufficient to reduce these interactions and the concomitant m6A methylation of ISGs. The conclusion that the phosphorylation state of WTAP is important in this process is also quite well supported.

      Weaknesses:

      The evidence that the above mechanism is fundamentally driven by different phase-separated pools of WTAP (regulated by its phosphorylation state) is weaker. These experiments rely relatively heavily on the treatment of cells with 1,6-hexanediol, which has been shown to have some off-target effects on phosphatases and kinases (PMID 33814344).

      Given that the model invoked in this study depends on the phosphorylation (or lack thereof) of WTAP, this is a particularly relevant concern.

      Related to this point, it is also interesting (and potentially concerning for the proposed model) that the initial region of WTAP that was predicted to be disordered is in fact not the region that the authors demonstrate is important for the different phase-separated states. Taking all the data together, it is also not clear to me that one has to invoke phase separation in the proposed mechanism.

      We are grateful for the Reviewer’s positive comment and constructive feedback. In this article, we claim a novel and important mechanism that de-phosphorylation-driven solid to liquid phase transition of WTAP mediates its co-transcriptional m6A modification. We first observed that WTAP underwent phase transition during virus infection and IFN-β stimulation, and confirmed the phase transition driven force of WTAP through multiple experiments. Besides 1,6‐hexanediol (1,6-hex) treatment, we also introduced S/T to D/A mutations to mimic the phosphorylation and de-phosphorylation WTAP in vitro and in cells, identified 5ST-D mutant as SLPS mutant, and 5ST-A mutant as LLPS mutant. We then performed 1,6-hex experiment to confirm the importance of phase separation for WTAP function, and revealed that 5ST-D SLPS mutant and 5ST-A LLPS mutant had different influence on WTAP-promoter region interaction and co-transcriptional m6A modification. Following the reviewer’s suggestion, we need to further clarify the phosphorylation of WTAP phase separation. We plan to repeat the experiments by introducing potent PP4 inhibitor, fostriecin, and performed further experiments to explore the effect of WTAP IDR domain, which is reported to play a critical role for its phase separation.

      1,6-hex was initially considered as the inhibitor of hydrophobic interaction which involved in various kinds of protein-protein interaction, indicating that off-target effects of 1,6-hex was inevitable. It is reported that 1,6-hex impaired RNA pol II CTD specific phosphatase and kinase activity at 5% concentration3. However, 1,6-hex is still widely used in the LLPS-associated functional studies despite its off-target effect. Related to this article, 10% 1,6-hex was reported to dissolve WTAP phase separation droplets2. Beside WTAP, 1,6-hex (5%-10% w/v) was also used to explore the phase separation characteristic and function on phosphorylated protein or even kinase, including p‐tau441, TAZ, HSF1 and so on4-6. 10% 1,6-hex inhibited the crucial role of phosphorylation-driven HSF1 LLPS in chromatin binding and transcriptional process presented by RNA-seq dataset6, indicating the function on kinase or phosphatase of 1,6-hex might not a global effect. To avoid the 1,6-hex-mediated kinase/phosphatase impairment in this project, we introduced the WTAP SLPS mutation and LLPS mutation besides 1,6-hex treatment to explore the m6A modification function of WTAP phase transition. We plan to repeat the experiments by lower the 1,6-hex concentration, check the WTAP phosphorylation status after 1,6-hex treatment, and discuss them in the discussion part.

      A considerable number of proteins undergo phase separation via interactions between intrinsically disordered regions (IDRs). IDR contains more charged and polar amino acids to present multiple weakly interacting elements, while lacking hydrophobic amino acids to show flexible conformations7. In our article, we used PLAAC websites (http://plaac.wi.mit.edu/) to predict IDR domain of WTAP, and a fragment (234-249 amino acids) was predicted as prion-like domain. However, deletion of this fragment failed to abolish the phase separation properties of WTAP, which might be the main confusion to reviewers. To explain this issue, we checked the WTAP structure (within part of MTC complex) from protein data bank (https://www.rcsb.org/structure/7VF2) and found that prediction of IDR has been renewed due to the update of different algorithm. IDR of WTAP has expanded to 245-396 amino acids, containing the whole CTD region. According to our results, lack of CTD inhibited WTAP liquid-liquid phase separation both in vitro and in cells, while the phosphorylation status on CTD had dramatic impact on WTAP phase transition, which was consistent with the LLPS-regulating function of IDR. Therefore, we will revise our description on WTAP IDR, and performed further experiment to test its function.

      Taken together, given the highly association between WTAP phosphorylation with phase separation status and its function during IFN-β stimulation, it is necessary to involve WTAP phase separation in our mechanism. We will perform further experiments to propose more convincing evidence and perfect our project.

      Reviewer #2 (Public review):

      In this study, Cai and colleagues investigate how one component of the m6A methyltransferase complex, the WTAP protein, responds to IFNb stimulation. They find that viral infection or IFNb stimulation induces the transition of WTAP from aggregates to liquid droplets through dephosphorylation by PPP4. This process affects the m6A modification levels of ISG mRNAs and modulates their stability. In addition, the WTAP droplets interact with the transcription factor STAT1 to recruit the methyltransferase complex to ISG promoters and enhance m6A modification during transcription. The investigation dives into a previously unexplored area of how viral infection or IFNb stimulation affects m6A modification on ISGs. The observation that WTAP undergoes a phase transition is significant in our understanding of the mechanisms underlying m6A's function in immunity. However, there are still key gaps that should be addressed to fully accept the model presented.

      Major points:

      (1) More detailed analyses on the effects of WTAP sgRNA on the m6A modification of ISGs:

      a. A comprehensive summary of the ISGs, including the percentage of ISGs that are m6A-modified. merip-isg percentage

      b. The distribution of m6A modification across the ISGs. topology

      c. A comparison of the m6A modification distribution in ISGs with non-ISGs. topology

      In addition, since the authors propose a novel mechanism where the interaction between phosphorylated STAT1 and WTAP directs the MTC to the promoter regions of ISGs to facilitate co-transcriptional m6A modification, it is critical to analyze whether the m6A modification distribution holds true in the data.

      We appreciate the reviewer‘s summary of our manuscript and the constructive assessment. We plan to perform the related analysis accordingly to present the m6A modification in ISGs in our model. 

      (2) Since a key part of the model includes the cytosol-localized STAT1 protein undergoing phosphorylation to translocate to the nucleus to mediate gene expression, the authors should focus on the interaction between phosphorylated STAT1 and WTAP in Figure 4, rather than the unphosphorylated STAT1. Only phosphorylated STAT1 localizes to the nucleus, so the presence of pSTAT1 in the immunoprecipitate is critical for establishing a functional link between STAT1 activation and its interaction with WTAP.

      We plan to repeat the immunoprecipitation experiments to clarify the function of pSTAT1 in WTAP interaction and m6A modification as the reviewer suggested.

      (3) The authors should include pSTAT1 ChIP-seq and WTAP ChIP-seq on IFNb-treated samples in Figure 5 to allow for a comprehensive and unbiased genomic analysis for comparing the overlaps of peaks from both ChIP-seq datasets. These results should further support their hypothesis that WTAP interacts with pSTAT1 to enhance m6A modifications on ISGs.

      We first performed the MeRIP-seq and RNA-seq and explored the critical role of WTAP in ISGs m6A modification and expression. By immunoprecipitation and immunofluorescence experiments, we found phase transition of WTAP enhanced its interaction to pSTAT1. These results indicate that WTAP mediated ISGs m6A modification and expression by enhanced its interaction with pSTAT1 during virus infection and IFN-β stimulation. However, we were still not sure how WTAP-mediated m6A modification related to pSTAT1-mediated transcription. By analyzing METTL3 ChIP-seq data or caPAR-CLIP-seq data, several researches have revealed the recruitment of m6A methylation complex (MTC) to transcription start sites (TSS) of coding genes and R-loop structure by interacting with transcriptional factors STAT5B or DNA helicase DDX21, indicating the engagement of MTC mediated m6A modification on nascent transcripts at the very beginning of transcription 8-10. Thus, we proposed that phase transition of WTAP could be recruited to the ISGs promoter region by pSTAT1, and verified this hypothesis by pSTAT1/WTAP-ChIP-qPCR. We believe ChIP-seq experiment is a good idea to explore the mechanism in depth, but the results in this article for now are enough to explain our mechanism. We will continuously focus on the whole genome chromatin distribution of WTAP and explore more functional effect of transcriptional factor-dependent WTAP-promoter region interaction in t.

      Minor points:

      (1) Since IFNb is primarily known for modulating biological processes through gene transcription, it would be informative if the authors discussed the mechanism of how IFNb would induce the interaction between WTAP and PPP4.

      (2) The authors should include mCherry alone controls in Figure 1D to demonstrate that mCherry does not contribute to the phase separation of WTAP. Does mCherry have or lack a PLD?

      (3) The authors should clarify the immunoprecipitation assays in the methods. For example, the labeling in Figure 2A suggests that antibodies against WTAP and pan-p were used for two immunoprecipitations. Is that accurate?

      (4) The authors should include overall m6A modification levels quantified of GFPsgRNA and WTAPsgRNA cells, either by mass spectrometry (preferably) or dot blot.

      We thank reviewer for raising these useful suggestions. We will perform related experiments and revised the manuscript carefully the as reviewer suggested.

      Reviewer #3 (Public review):

      Summary:

      This study presents a valuable finding on the mechanism used by WTAP to modulate the IFN-β stimulation. It describes the phase transition of WTAP driven by IFN-β-induced dephosphorylation. The evidence supporting the claims of the authors is solid, although major analysis and controls would strengthen the impact of the findings. Additionally, more attention to the figure design and to the text would help the reader to understand the major findings.

      Strength:

      The key finding is the revelation that WTAP undergoes phase separation during virus infection or IFN-β treatment. The authors conducted a series of precise experiments to uncover the mechanism behind WTAP phase separation and identified the regulatory role of 5 phosphorylation sites. They also succeeded in pinpointing the phosphatase involved.

      Weaknesses:

      However, as the authors acknowledge, it is already widely known in the field that IFN and viral infection regulate m6A mRNAs and ISGs. Therefore, a more detailed discussion could help the reader interpret the obtained findings in light of previous research.

      It is well-known that protein concentration drives phase separation events. Similarly, previous studies and some of the figures presented by the authors show an increase in WTAP expression upon IFN treatment. The authors do not discuss the contribution of WTAP expression levels to the phase separation event observed upon IFN treatment. Similarly, METTL3 and METTL14, as well as other proteins of the MTC are upregulated upon IFN treatment. How does the MTC protein concentration contribute to the observed phase separation event?

      How is PP4 related to the IFN signaling cascade?

      In general, it is very confusing to talk about WTAP KO as WTAPgRNA.

      We are grateful for the positive comments and the unbiased advice by reviewer. To interpret the findings in previous research, we will revise the manuscript carefully and preform more detailed discussion on ISGs m6A modification during virus infection or IFN stimulation. As previous reported, WTAP protein level will be induced by long time IFN-β stimulation or LPS stimulation, while LPS-induced WTAP expression promoted its phase separation ability2,11. Although there was no significant upregulation of WTAP expression level in our short time treatment, we hypothesized that WTAP phase separation will be promoted due to higher protein concentration after long time IFN stimulation, enhancing m6A modification deposition on ISGs mRNA, revealing a feedback loop between WTAP phase separation and m6A modification during specific stimulation. To discuss the effect of MTC protein concentration in our proposed event, we will perform immunoblotting experiments of MTC proteins and check the phase separation effect in different WTAP concentration.

      Protein phosphatase 4 (PP4) is a multi-subunit Ser/Thr phosphatase complex that participate in diverse cellular pathways including DDR, cell cycle progression, and apoptosis12. Protein phosphatase 4 catalytic subunit 4C (PPP4C) is one of the components of PP4 complex. Previous research showed that knockout of PPP4C enhanced IFN-β downstream signaling and gene expression, which was consistent with our findings that knockdown of PPP4C impaired WTAP-mediated m6A modification, enhanced the ISGs expression. Since there was no significant enhancement in PPP4C expression level during IFN-β stimulation in our results, we will consider to explore the post-translation modification that may influence the protein-protein interaction, such as ubiquitination.

      In this project, all the WTAP-deficient THP-1 cells were bulk cells treated with WTAPsgRNA, but not monoclonal knockout cells. We confirmed that WTAP expression was efficiently knockdown in WTAPsgRNA THP-1 cells, and the m6A modification level has been impaired, avoiding the compensatory effect on m6A modification by other possible proteins. Thus, we prefer to call it WTAPsgRNA THP-1 cells rather than WTAP KO THP-1 cells.  

      References

      (1) Raja, R., Wu, C., Bassoy, E.Y., Rubino, T.E., Jr., Utagawa, E.C., Magtibay, P.M., Butler, K.A., and Curtis, M. (2022). PP4 inhibition sensitizes ovarian cancer to NK cell-mediated cytotoxicity via STAT1 activation and inflammatory signaling. J Immunother Cancer 10. 10.1136/jitc-2022-005026.

      (2) Ge, Y., Chen, R., Ling, T., Liu, B., Huang, J., Cheng, Y., Lin, Y., Chen, H., Xie, X., Xia, G., et al. (2024). Elevated WTAP promotes hyperinflammation by increasing m6A modification in inflammatory disease models. J Clin Invest 134. 10.1172/JCI177932.

      (3) Duster, R., Kaltheuner, I.H., Schmitz, M., and Geyer, M. (2021). 1,6-Hexanediol, commonly used to dissolve liquid-liquid phase separated condensates, directly impairs kinase and phosphatase activities. J Biol Chem 296, 100260. 10.1016/j.jbc.2021.100260.

      (4) Wegmann, S., Eftekharzadeh, B., Tepper, K., Zoltowska, K.M., Bennett, R.E., Dujardin, S., Laskowski, P.R., MacKenzie, D., Kamath, T., Commins, C., et al. (2018). Tau protein liquid-liquid phase separation can initiate tau aggregation. The EMBO journal 37. 10.15252/embj.201798049.

      (5) Lu, Y., Wu, T., Gutman, O., Lu, H., Zhou, Q., Henis, Y.I., and Luo, K. (2020). Phase separation of TAZ compartmentalizes the transcription machinery to promote gene expression. Nat Cell Biol 22, 453-464. 10.1038/s41556-020-0485-0.

      (6) Zhang, H., Shao, S., Zeng, Y., Wang, X., Qin, Y., Ren, Q., Xiang, S., Wang, Y., Xiao, J., and Sun, Y. (2022). Reversible phase separation of HSF1 is required for an acute transcriptional response during heat shock. Nat Cell Biol 24, 340-352. 10.1038/s41556-022-00846-7.

      (7) Hou, S., Hu, J., Yu, Z., Li, D., Liu, C., and Zhang, Y. (2024). Machine learning predictor PSPire screens for phase-separating proteins lacking intrinsically disordered regions. Nat Commun 15, 2147. 10.1038/s41467-024-46445-y.

      (8) Hao, J.D., Liu, Q.L., Liu, M.X., Yang, X., Wang, L.M., Su, S.Y., Xiao, W., Zhang, M.Q., Zhang, Y.C., Zhang, L., et al. (2024). DDX21 mediates co-transcriptional RNA m(6)A modification to promote transcription termination and genome stability. Mol Cell 84, 1711-1726 e1711. 10.1016/j.molcel.2024.03.006.

      (9) Barbieri, I., Tzelepis, K., Pandolfini, L., Shi, J., Millan-Zambrano, G., Robson, S.C., Aspris, D., Migliori, V., Bannister, A.J., Han, N., et al. (2017). Promoter-bound METTL3 maintains myeloid leukaemia by m(6)A-dependent translation control. Nature 552, 126-131. 10.1038/nature24678.

      (10) Bhattarai, P.Y., Kim, G., Lim, S.C., and Choi, H.S. (2024). METTL3-STAT5B interaction facilitates the co-transcriptional m(6)A modification of mRNA to promote breast tumorigenesis. Cancer Lett 603, 217215. 10.1016/j.canlet.2024.217215.

      (11) Ge, Y., Ling, T., Wang, Y., Jia, X., Xie, X., Chen, R., Chen, S., Yuan, S., and Xu, A. (2021). Degradation of WTAP blocks antiviral responses by reducing the m(6) A levels of IRF3 and IFNAR1 mRNA. EMBO Rep 22, e52101. 10.15252/embr.202052101.

      (12) Dong, M.Z., Ouyang, Y.C., Gao, S.C., Ma, X.S., Hou, Y., Schatten, H., Wang, Z.B., and Sun, Q.Y. (2022). PPP4C facilitates homologous recombination DNA repair by dephosphorylating PLK1 during early embryo development. Development 149. 10.1242/dev.200351.

    1. Reviewer #3 (Public review):

      Summary:

      In this manuscript, the authors investigate the optical properties of brochosomes produced by leafhoppers. They hypothesize that brochosomes reduce light reflection on the leafhopper's body surface, aiding in predator avoidance. Their hypothesis is supported by experiments involving jumping spiders. Additionally, the authors employ a variety of techniques including micro-UV-Vis spectroscopy, electron microscopy, transcriptome and proteome analysis, and bioassays. This study is highly interesting, and the experimental data is well-organized and logically presented.

      Strengths:

      The use of brochosomes as a camouflage coating has been hypothesized since 1936 (R.B. Swain, Entomol. News 47, 264-266, 1936) with evidence demonstrated by similar synthetic brochosome systems in a number of recent studies (S. Yang, et al. Nat. Commun. 8:1285, 2017; L. Wang, et al., PNAS. 121: e2312700121, 2024). However, direct biological evidence or relevant field studies have been lacking to directly support the hypothesis that brochosomes are used for camouflage. This work provides the first biological evidence demonstrating that natural brochosomes can be used as a camouflage coating to reduce the leafhoppers' observability of their predators. The design of the experiments is novel.

      Weaknesses:

      (1) The observation that brochosome coatings become sparse after 25 days in both male and female leafhoppers, resulting in increased predation by jumping spiders, is intriguing. However, since leafhoppers consistently secrete and groom brochosomes, it would be beneficial to explore why brochosomes become significantly less dense after 25 days.

      (2) The authors demonstrate that brochosome coatings reduce UV (specular) reflection compared to surfaces without brochosomes, which can be attributed to the rough geometry of brochosomes as discussed in the literature. However, it would be valuable to investigate whether the proteins forming the brochosomes are also UV absorbing.

      (3) The experiments with jumping spiders show that brochosomes help leafhoppers avoid predators to some extent. It would be beneficial for the authors to elaborate on the exact mechanism behind this camouflage effect. Specifically, why does reduced UV reflection aid in predator avoidance? If predators are sensitive to UV light, how does the reduced UV reflectance specifically contribute to evasion?

      (4) An important reference regarding the moth-eye effect is missing. Please consider including the following paper: Clapham, P. B., and M. C. Hutley. "Reduction of lens reflection by the 'Moth Eye' principle." Nature 244: 281-282 (1973).

      (5) The introduction should be revised to accurately reflect the related contributions in literature. Specifically, the novelty of this work lies in the demonstration of the camouflage effect of brochosomes using jumping spiders, which is verified for the first time in leafhoppers. However, the proposed use of brochosome powder for camouflage was first described by R.B. Swain (R.B. Swain, Notes on the oviposition and life history of the leafhopper Oncometopta undata Fabr. (Homoptera: Cicadellidae), Entomol. News. 47: 264-266 (1936)). Recently, the antireflective and potential camouflage functions of brochosomes were further studied by Yang et al. based on synthetic brochosomes and simulated vision techniques (S. Yang, et al. "Ultra-antireflective synthetic brochosomes." Nature Communications 8: 1285 (2017)). Later, Lei et al. demonstrated the antireflective properties of natural brochosomes in 2020 (C.-W. Lei, et al., "Leafhopper wing-inspired broadband omnidirectional antireflective embroidered ball-like structure arrays using a nonlithography-based methodology." Langmuir 36: 5296-5302 (2020)). Very recently, Wang et al. successfully fabricated synthetic brochosomes with precise geometry akin to those natural ones, and further elucidated the antireflective mechanisms based on the brochosome geometry and their role in reducing the observability of leafhoppers to their predators (L. Wang et al. "Geometric design of antireflective leafhopper brochosomes." Proceedings of the National Academy of Sciences 121: e2312700121 (2024))

    1. Author response:

      The following is the authors’ response to the current reviews.

      Reviewer 2:

      In addition, it is still unacceptable for me that the number of ovulated oocytes in mice at 6 months of age is only one third of young mice (10 vs 30; Fig. S1E). The most of published literature show that mice at 12 months of age still have ~10 ovulated oocytes.

      We disagree with the reviewer’s comment, and the concerns raised were not shared by the other reviewers.  We have reported our data with full transparency (each data point is plotted). In the current study, we observed an intermediate phenotype in gamete number (assessed by both ovarian follicle counts and ovulated eggs) when comparing 6 month old mice to 6 week or 10 month old mice; this is as expected. It is well accepted that follicle counts are highly mouse strain dependent.  Although the reviewer mentions that mice at 12 months have ~10 ovulated oocytes, no actual references are provided nor are the mouse strain or other relevant experimental details mentioned.  Therefore, we do not know how these quoted metrics relate to the female FVB mice used in our current study.   As clearly explained and justified in our manuscript, we used mice at 6 months and 10 months to represent a physiologic aging continuum. 

      Moreover, based on the follicle counting method used in the present study (Fig. S1D), there are no antral follicles observed in mice at 6 months and 10 months of age, which is not reasonable.

      This statement is incorrect. Antral follicles were present at 6 and 10 months of age, but due to the scale of the y-axis and the normalization of follicle number/area in Fig. S1D, the values are small.  The absolute number of antral follicles per ovary (counted in every 5th section) was 31.3 ± 3.8 follicles for 6-week old mice, 9.3 ± 2.3 follicles for 6-month old mice, and 5.3 ± 1.8 follicles for 10-month old mice.  Moreover, it is important to note that these ovaries were not collected in a specific stage of the estrous cycle, so the number of antral follicles may not be maximal.  In addition, as described in the Materials and Methods, antral follicles were only counted when the oocyte nucleus was present in a section to avoid double counting.  Therefore, this approach (which was applied consistently across samples) could potentially underestimate the total number.


      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This manuscript by Bomba-Warczak describes a comprehensive evaluation of long-lived proteins in the ovary using transgenerational radioactive labelled 15N pulse-chase in mice. The transgenerational labeling of proteins (and nucleic acids) with 15N allowed the authors to identify regions enriched in long-lived macromolecules at the 6 and 10-month chase time points. The authors also identify the retained proteins in the ovary and oocyte using MS. Key findings include the relative enrichment in long-lived macromolecules in oocytes, pregranulosa cells, CL, stroma, and surprisingly OSE. Gene ontology analysis of these proteins revealed enrichment for nucleosome, myosin complex, mitochondria, and other matrix-type protein functions. Interestingly, compared to other post-mitotic tissues where such analyses have been previously performed such as the brain and heart, they find a higher fractional abundance of labeled proteins related to the mitochondria and myosin respectively.

      Response: We thank the reviewer for this thoughtful summary of our work.  We want to clarify that our pulse-chase strategy relied on a two-generation stable isotope-based metabolic labelling of mice using 15N from spirulina algae (for reference, please see (Fornasiero & Savas, 2023; Hark & Savas, 2021; Savas et al., 2012; Toyama et al., 2013)).  We did not utilize any radioactive isotopes.

      Strengths:

      A major strength of the study is the combined spatial analyses of LLPs using histological sections with MS analysis to identify retained proteins.

      Another major strength is the use of two chase time points allowing assessment of temporal changes in LLPs associated with aging.

      The major claims such as an enrichment of LLPs in pregranulosa cells, GCs of primary follicles, CL, stroma, and OSE are soundly supported by the analyses, and the caveat that nucleic acids might differentially contribute to this signal is well presented.

      The claims that nucleosomes, myosin complex, and mitochondrial proteins are enriched for LLPs are well supported by GO enrichment analysis and well described within the known body of evidence that these proteins are generally long-lived in other tissues.

      Weaknesses:

      Comment 1: One small potential weakness is the lack of a mechanistic explanation of if/why turnover may be accelerating at the 6-10 month interval compared to 1-6.

      Response 1: At the 6-month time point, we detected more long lived proteins than the 10 month time point in both the ovary and the oocyte.  We anticipated this because proteins are degraded over time, and substantially more time has elapsed at the later time point.  Moreover, at the 6–10-month time point, age-related tissue dysfunction is already evident in the ovary.  For example, in 6-9 month old mice, there is already a deterioration of chromosome cohesion in the egg which results in increased interkinetochore distances (Chiang et al., 2010), and by 10 months, there are multinucleated giant cells present in the ovarian stroma which is consistent with chronic inflammation (Briley et al., 2016).  Thus, the observed changes in protein dynamics may be another early feature of aging progression in the ovary.  

      Comment 2: A mild weakness is the open-ended explanation of OSE label retention. This is a very interesting finding, and the claims in the paper are nuanced and perfectly reflect the current understanding of OSE repair. However, if the sections are available and one could look at the spatial distribution of OSE signal across the ovarian surface it would interesting to note if label retention varied by regions such as the CLs or hilum where more/less OSE division may be expected. 

      Response 2: We agree that the enrichment of long-lived molecules in the OSE is interesting. To make interpretable conclusions about the dynamics of long-lived molecules in the OSE, we would need to generate a series of samples at precise stages of the estrous cycle or ideally across a timecourse of ovulation to capture follicular rupture and repair.  These samples do not currently exist and are beyond the scope of this study. However, this idea is an important future direction and it has been added to the discussion (lines 221-223). Furthermore, from a practical standpoint, MIMS imaging is resource and time intensive. Thus, we are not able to readily image entire ovarian sections.  Instead, we focused on structures within the ovary and took select images of follicles, stroma, and OSE.  We, therefore, do not have a comprehensive series of images of the OSE from the entire ovarian section for each mouse analyzed.

      Reviewer #2 (Public Review):

      Summary:

      The manuscript by Bomba-Warczak et al. applied multi-isotope imaging mass spectrometry (MIMS) analysis to identify the long-lived proteins in mouse ovaries during reproductive aging, and found some proteins related to cytoskeletal and mitochondrial dynamics persisting for 10 months.

      Response: We thank the reviewer for their summary and feedback.

      Strengths:

      The manuscript provides a useful dataset about protein turnover during ovarian aging in mice.

      Weaknesses:

      Comment 1: The study is pretty descriptive and short of further new findings based on the dataset. In addition, some results such as the numbers of follicles and ovulated oocytes in aged mice are not consistent with the published literature, and the method for follicle counting is not accurate. The conclusions are not fully supported by the presented evidence.

      Response 1: We agree with the reviewer that this study is descriptive. Our goal, as stated, was to use a discovery-based approach to define the long-lived proteome of the ovary and oocyte across a reproductive aging continuum.  As the prominent aging researcher, Dr. James Kirkland, stated: “although ‘descriptive’ is sometimes used as a pejorative term…descriptive or discovery research leading to hypothesis generation has become highly sophisticated and of great relevance to the aging field (Kirkland, 2013).”  We respectfully disagree with the reviewer that our study is short of new findings. In fact, this is the first time that a stable two-generation stable isotope-based metabolic labelling of mice in combination with two different state-of-the-art mass spectrometry methods has been used to identify and localize long lived molecules in the ovary and oocyte along this particular reproductive aging continuum in an unbiased manner.  We have identified proteins groups that were previously not known to be long lived in the ovary and oocyte.  Our hope is that this long-lived proteome will become an important hypothesis-generating resource for the field of reproductive aging.

      The age-dependent decline in number of follicles and eggs ovulated in mice has been well established by our group as well as others (Duncan et al., 2017; Mara et al., 2020).  Thus, we are unclear about the reviewer’s comments that our results are not consistent with the published literature.  The absolute numbers of follicles and eggs ovulated as well as the rate of decline with age are highly strain dependent.  Moreover, mice can have a very small ovarian reserve and still maintain fertility (Kerr et al., 2012).  In our study, we saw a consistent age-dependent decrease in the ovarian reserve (Figure 1 – figure supplement 1 D), the number of oocytes collected from large antral follicles following hyperstimulation with PMSG (used for LC-MS/MS), and the number of eggs collected from the oviduct following hyperstimulation and superovulation with PMSG and hCG (Figure 1 – figure supplement 1 E and F).  In all cases, the decline was greater in 10 month old compared to 6 month old mice demonstrating a relative reproductive aging continuum even at these time points.

      Our research team has significant expertise in follicle classification and counting as evidenced by our publication record (Duncan et al., 2017; Kimler et al., 2018; Perrone et al., 2023; Quan et al., 2020).  We used our established methods which we have further clarified in the manuscript text (lines 395-397).  Follicle counts were performed on every 5th tissue section of serial sectioned ovaries, and 1 ovary from 3 mice per timepoint were counted. Therefore, follicle counts were performed on an average of 48-62 total sections per ovary. The number of follicles was then normalized per total area (mm2) of the tissue section, and the counts were averaged. Figure 1 – figure supplement 1 C and D represents data averaged from all ovarian sections counted per mouse.   It is important to note that the same criteria were applied consistently to all ovaries across the study, and thus regardless of the technique used, the relative number of follicles or oocytes across ages can be compared.

      Reviewer #3 (Public Review):

      Summary:

      In this study, Bomba-Warczak et al focused on reproductive aging, and they presented a map for long-lived proteins that were stable during reproductive lifespan. The authors used MIMS to examine and show distinct molecules in different cell types in the ovary and tissue regions in a 6 month mice group, and they also used proteomic analysis to present different LLPs in ovaries between these two timepoints in 6-month and 10-month mice. The authors also examined the LLPs in oocytes in the 6-months mice group and indicated that these were nuclear, cytoskeleton, and mitochondria proteins.

      Response: We thank the reviewer for their summary and feedback.

      Strengths:

      Overall, this study provided basic information or a 'map' of the pattern of long-lived proteins during aging, which will contribute to the understanding of the defects caused by reproductive aging.

      Weaknesses:

      Comment 1: The 6-month mice were used as an aged model; no validation experiments were performed with proteomics analysis only.  

      Response 1:  We did not select the 6-month time point to be representative of the “aged model” but rather one of two timepoints on the reproductive aging continuum – 6 and 10 months.  In the manuscript (Figure 1 – figure supplement 1) we have demonstrated the relevance of the two timepoints by illustrating a decrease in follicle counts, number of fully grown oocytes collected, and number of eggs ovulated as well as a tendency towards increased stromal fibrosis (highlighted in the main text lines 78-85).  Inclusion of the 6-month timepoint ultimately turned out to be informative and essential as many long-lived proteins were absent by the 10 month timepoint. These results suggest that important shifts in the proteome occur during mid to advanced reproductive age.  The relevance of these timepoints is mentioned in the discussion (lines 247-270).

      Two independent mass spectrometry approaches (MIMS and LC-MS/MS) were used to validate the presence of long-lived macromolecules in the ovary and oocyte. Studies focused on the role of specific long-lived proteins in oocyte and ovarian biology as well as how they change with age in terms of function, turnover, and modification are beyond the scope of the current study but are ongoing.  We have acknowledged these important next steps in the manuscript text (lines 286-288, 311-312).

      It is important to note, that oocytes are biomass limited cells, and their numbers decrease with age.  Thus, we had to select ages where we could still collect enough from the mice available to perform LC-MS/MS. 

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Comment 1: The writing and figures are beautiful - it would be hard to improve this manuscript.

      Response 1: We greatly appreciate this enthusiastic evaluation of our work.

      Comment 2: In Fig S1E/F it would help to list the N number here. Why are there 2 groups at 6-12 wk?

      Response 2:  We did not have 6 month and 10-month-old mice available at the same time to be able to run the hyperstimulation and superovulation experiment in parallel.  Therefore, we performed independent experiments comparing the number of eggs collected from either 6-month-old or 10 month old mice relative to 6-12 week old controls.  In each trial, eggs were collected from pooled oviducts from between 3-4 mice per age group, and the average total number of eggs per mouse was reported.  Each point on the graph corresponds to the data from an individual trial, and two trials were performed.  This has been clarified in the figure legend (lines 395-397).  Of note, while addressing this reviewer’s comments, we noticed that we were missing Materials and Methods regarding the collection of eggs from the oviduct following hyperstimulation and superovulation with PMSG and hCG.  This information has now been added in Methods Section, lines 477-481.

      Comment 3: The manuscript would benefit from an explanation of why the pups were kept on a 1-month N15 diet after birth, since the oocytes are already labeled before birth, and granulosa at most by day 3-4. Would ZP3 have not been identified otherwise?

      Response 3:   The pups used in this study were obtained from fully labeled female dams that were maintained on an15N diet.  These pups had to be kept with their mothers through weaning.  To limit the pulse period only through birth, the pups would have had to be transferred to unlabeled foster mothers.  However, this would have risked pup loss which would have significantly impacted our ability to conduct the studies given that we only had 19 labeled female pups from three breeding pairs.  We have clarified this in the manuscript text in lines 78-80.  It is hard to know, without doing the experiment, whether we would have detected ZP3 if we only labeled through birth.  The expression of ZP3 in primordial follicles, albeit in human, would suggest that this protein is expressed quite early in development.

      Comment 4: What is happening to the mitochondria at 6-10 months? Does their number change in the oocyte? Is there a change in the rate of fission? Any chance to take a stab at it with these or other age-matched slides?

      Response 4:  The reviewer raises an excellent point.  As mentioned previously in the Discussion (lines 290-301), there are well documented changes in mitochondrial structure and function in the oocyte in mice of advanced reproductive age.  However, there is a paucity of data on the changes that may happen at earlier mid-reproductive age time points.  From the oocyte mitochondrial proteome perspective, our data demonstrate a prominent decline in the persistence of long-lived proteins between 6 and 10 months, and this occurs in the absence of a change in the total pool of mitochondrial proteins (both long and short lived populations) as assessed by spectral counts or protein IDs (figure below).  These data, which we have added into Figure 3 – figure supplement 1 and in the manuscript text (lines 164-170) are suggestive of similar numbers of mitochondria at these two timepoints. It would be informative to do a detailed characterization of oocyte mitochondrial structure and function within this window to see if there is a correlation with this shift in long lived mitochondrial proteins.  Although this analysis is beyond the scope of the current manuscript, it is an important next line of inquiry which we have highlighted in the manuscript text (lines 255-257 and 311-312).

      Reviewer #2 (Recommendations For The Authors):

      Several concerns are raised as shown below.

      Comment 1: In Fig. 2F, it is surprising that ZP3 disappeared in the ovary from mice at the age of 10 months by MIMS analysis, because quite a few oocytes with intact zona pellucida can still be obtained from mice at this age. Notably, ZP would not be renewed once formed.

      Response 1: To clarify, Figure 2F shows LC-MS/MS data and not MIMS data.  As mentioned in the Discussion, the detection of long-lived pools of ZP3 at 6 months cannot be derived from newly synthesized zona pellucidae in growing follicles because they would not have been present during the pulse period.  The only way we could detect ZP3 at 6 months is if it forms a primitive zona scaffold in the primordial follicle or if ZPs from atretic follicles of the first couple of waves of folliculogenesis incorporate into the extracellular matrix of the ovary.  The lack of persistence of ZP3 at 10 months could be due to protein degradation. Should ZP3 indeed form a primitive zona, its loss at 10 months would be predicted to result in poor formation of a bona fide zona pellucida upon follicle growth.  Interestingly, aging has been associated with alterations in zona pellucida structure and function.   These data open novel hypotheses regarding the zona pellucida (e.g. a primitive zona scaffold and part of the extracellular matrix) and will require significant further investigation to test. These points are highlighted in the Discussion lines 227-245.

      Comment 2: To determine whether those proteins that can not be identified by MIMS at the time point of 10 months are degraded or renewed, the authors should randomly select some of them to examine their protein expression levels in the ovary by immunoblotting analysis.

      Response 2: To clarify, proteins were identified by LC-MS/MS and not MIMS which was used to visualize long lived macromolecules.   Each protein will be comprised of old pools (15N containing) and newly synthesized pools (14N containing).  Degradation of the old pool of protein does not mean that there will be a loss of total protein.  Moreover, immunoblotting cannot distinguish old and newly synthesized pools of protein. Where overall peptide counts are listed for each protein identified at both time points.  As peptides derive from proteins, the table provided with the manuscript reflects what immunoblotting would, but on a larger and more precise scale.

      Comment 3: I think those proteins that can be identified by MIMS at the time point of 6 months but not 10 months deserve more analyses as they might be the key molecules that drive ovarian aging.

      Response 3:  This comment conflicts with comment 2 from Reviewer #3 (Recommendations For The Authors).  This underscores that different researchers will prioritize the value and follow up of such rich datasets differently.  We agree that the LLP identified at 6 months are of particular interest to reproductive aging, and we are planning to follow up on these in future studies.

      Comment 4:  Figure 1 – figure supplement 1 C-F, compared with the published literature, the numbers of follicles at different developmental stages and ovulated oocytes at both ages of 6 months and 10 months were dramatically low in this study. For 6-month-old female mice, the reproductive aging just begins, thus these numbers should not be expected to decrease too much. In addition, follicle counting was carried out only in an area of a single section, which is an inaccurate way, because the numbers and types of follicles in various sections differ greatly. Also, the data from a single section could not represent the changes in total follicle counts.

      Response 4: We have addressed these points in response to Comment 1 in the Reviewer #2 Public Review, and corresponding changes in the text have been noted.    

      Comment 5:  The study lacks follow-up verification experiments to validate their MIMS data.

      Response 5: Two independent mass spectrometry approaches (MIMS and LC-MS/MS) were used to validate the presence of long-lived macromolecules in the ovary and oocyte. Studies focused on the role of specific long-lived proteins in oocyte and ovarian biology as well as how they change with age in terms of function, turnover, and modification are beyond the scope of the current study but ongoing.  We have acknowledged these important next steps in the manuscript text (lines 286-288 and 311-312).

      Reviewer #3 (Recommendations For The Authors):

      Comment 1: The authors used the 6-month mice group to represent the aged model, and examined the LLPs from 1 month to 6 months. Indeed, 6-month-old mice start to show age-related changes; however, for the reproductive aging model, the most widely accepted model is that 10-month-old age mice start to show reproductive-related changes and 12-month-old mice (corresponding to 35-40 year-old women) exhibit the representative reproductive aging phenotypes. Therefore, the data may not present the typical situation of LLPs during reproductive aging.

      Response 1: As described in the response to Comment 1 in the Reviewer #3 Public Review, there were clear logistical and technical feasibility reasons why the 6 month and 10-month timepoints were selected for this study.  Importantly, however, these timepoints do represent a reproductive aging continuum as evidenced by age-related changes in multiple parameters.  Furthermore, there were ultimately very few LLPs that remained at 10 months in both the oocyte and ovary, so inclusion of the 6-month time point was an important intermediate.  Whether the LLPs at the 6-month timepoint serve as a protective mechanism in maintaining gamete quality or whether they contribute to decreased quality associated with reproductive aging is an intriguing dichotomy which will require further investigation.  This has been added to the discussion (lines 247-257).

      Comment 2:  Following the point above, the authors examined the ovaries in 6 months and 10 months mice by proteomics, and found that 6 months LLPs were not identical compared with 10 months, while there were Tubb5, Tubb4a/b, Tubb2a/b, Hist2h2 were both expressed at these two time points (Fig 2B), why the authors did not explore these proteins since they expressed from 1 month to 10 months, which are more interesting.

      Response 2:  The objective of this study was to profile the long-lived proteome in the ovary and oocyte as a resource for the field rather than delving into specific LLPs at a mechanistic level.  That being said, we wholeheartedly agree with the reviewer that the proteins that were identified at both 6 month and 10 months are the most robust and long lived and worthy of prioritizing for further study.  Interestingly, Tubb5 and Tubb4a have high homology to primate-specific Tubb8, and Tubb8 mutations in women are associated with meiosis I arrest in oocytes and infertility (Dong et al., 2023; Feng et al., 2016).  Thus, perturbation of these specific proteins by virtue of their long-lived nature may be associated with impaired function and poor reproductive outcomes.  We have highlighted the importance of these LLPs which are present at both timepoints and persist to at least 10 months in the manuscript text (lines 259-270).

      Comment 3:  The authors also need to provide a hypothesis or explanation as to why LLDs from 6 months LLPs were not identical compared with 10 months.

      Response 3:  We agree that LLDs identified at 10 months should be also identified as long-lived at 6 months. This is a common limitation of mass spectrometry-based proteomics where each sample is prepared and run individually, which introduces variability between biological replicates, especially when it comes to low abundant proteins. It is key to note that just because we do not identify a protein, it does not mean the protein is not there – it merely means that we were not able to detect it in this particular experiment, but low levels of the protein may still be there. To compensate for this known and inherent variability, we have applied stringent filtering criteria where we required long-lived peptides to be identified in an independent MS scan (alternative is to identify peptide in either heavy or light scan and use modeling to infer FA value based on m/z shift), which gave us peptides of highest confidence. Ideally, these experiments would be done using TMT (tandem mass tag) approach. However, TMT-based experiments typically require substantial amount of input (80-100ug per sample) which unfortunately is not feasible with oocytes obtained from a limited number of pulse-chased animals.  We have added this explanation to the discussion (lines 265-270).

      Comment 4:  The reviewer thinks that LLPs from 6 months to 10 months may more closely represent the long-lived proteins during reproductive aging.

      Response 4:  We fully agree that understanding the identity of LLPs between the 6 month and 10 month period will be quite informative given that this is a dynamic period when many of LLPs get degraded and thus might be key to the observed decline in reproductive aging. This is a very important point that we hope to explore in future follow-up studies.

      Comment 5: The authors used proteomics for the detection of ovaries and oocytes, however, there are no validation experiments at all. Since proteomics is mainly for screening and prediction, the authors should examine at least some typical proteins to confirm the validity of proteomics. For example, the authors specifically emphasized the finding of ZP3, a protein that is critical for fertilization.

      Response 5:  Thank you, we agree that closer examination of proteins relevant and critical for fertilization is of importance.  However, a detailed analysis of specific proteins fell outside of the scope of this study which aimed at unbiased identification of long-lived macromolecules in ovaries and oocytes. We hope to continue this important work in near future.

      Comment 6: For the oocytes, the authors indicated that cytoskeleton, mitochondria-related proteins were the main LLPs, however, previous studies reported the changes of the expression of many cytoskeleton and mitochondria-related proteins during oocyte aging. How do the authors explain this contrary finding?   

      Response 6:  Our findings are not contrary to the studies reporting changes in protein expression levels during oocyte aging – the two concepts are not mutually exclusive. The average FA value at 6-month chase for oocyte proteins is 41.3 %, which means that while 41.3% of long-lived proteins pool persisted for 6 months, the other 58.7% has in fact been renewed. With the exception of few mitochondrial proteins (Cmkt2 and Apt5l), and myosins (Myl2 and Myh7), which had FA values close to 100% (no turnover), most of the LLPs had a portion of protein pools that were indeed turned over. Moreover, we included new data analysis illustrating that we identify comparable number of mitochondrial proteins between the two time points, indicating that while the long-lived pools are changing over time, the total content remains stable (Figure 3 – figure supplement 1E-G).

      Comment 7:  The authors also should provide in-depth discussion about the findings of the current study for long-lived proteins. In this study, the authors reported the relationship between these "long-lived" proteins with aging, a process with multiple "changes". Do long-lived proteins (which are related to the cytoskeleton and mitochondria) contribute to the aging defects of reproduction? or protect against aging?

      Response 7: This is a very important comment and one that needs further exploration. The fact is – we do not know at this moment whether these proteins are protective or deleterious, and such a statement would be speculative at this stage of research into LLPs in ovaries and oocytes. Future work is needed to address this question in detail.

      Briley, S. M., Jasti, S., McCracken, J. M., Hornick, J. E., Fegley, B., Pritchard, M. T., & Duncan, F. E. (2016). Reproductive age-associated fibrosis in the stroma of the mammalian ovary. Reproduction, 152(3), 245-260. https://doi.org/10.1530/REP-16-0129

      Chiang, T., Duncan, F. E., Schindler, K., Schultz, R. M., & Lampson, M. A. (2010). Evidence that Weakened Centromere Cohesion Is a Leading Cause of Age-Related Aneuploidy in Oocytes. Current Biology, 20(17), 1522-1528. https://doi.org/10.1016/j.cub.2010.06.069

      Dong, J., Jin, L., Bao, S., Chen, B., Zeng, Y., Luo, Y., Du, X., Sang, Q., Wu, T., & Wang, L. (2023). Ectopic expression of human TUBB8 leads to increased aneuploidy in mouse oocytes. Cell Discov, 9(1), 105. https://doi.org/10.1038/s41421-023-00599-z

      Duncan, F. E., Jasti, S., Paulson, A., Kelsh, J. M., Fegley, B., & Gerton, J. L. (2017). Age-associated dysregulation of protein metabolism in the mammalian oocyte. Aging Cell, 16(6), 1381-1393. https://doi.org/10.1111/acel.12676

      Feng, R., Sang, Q., Kuang, Y., Sun, X., Yan, Z., Zhang, S., Shi, J., Tian, G., Luchniak, A., Fukuda, Y., Li, B., Yu, M., Chen, J., Xu, Y., Guo, L., Qu, R., Wang, X., Sun, Z., Liu, M., . . . Wang, L. (2016). Mutations in TUBB8 and Human Oocyte Meiotic Arrest. N Engl J Med, 374(3), 223-232. https://doi.org/10.1056/NEJMoa1510791

      Fornasiero, E. F., & Savas, J. N. (2023). Determining and interpreting protein lifetimes in mammalian tissues. Trends Biochem Sci, 48(2), 106-118. https://doi.org/10.1016/j.tibs.2022.08.011

      Hark, T. J., & Savas, J. N. (2021). Using stable isotope labeling to advance our understanding of Alzheimer's disease etiology and pathology. J Neurochem, 159(2), 318-329. https://doi.org/10.1111/jnc.15298

      Kerr, J. B., Hutt, K. J., Michalak, E. M., Cook, M., Vandenberg, C. J., Liew, S. H., Bouillet, P., Mills, A., Scott, C. L., Findlay, J. K., & Strasser, A. (2012). DNA damage-induced primordial follicle oocyte apoptosis and loss of fertility require TAp63-mediated induction of Puma and Noxa. Mol Cell, 48(3), 343-352. https://doi.org/10.1016/j.molcel.2012.08.017

      Kimler, B. F., Briley, S. M., Johnson, B. W., Armstrong, A. G., Jasti, S., & Duncan, F. E. (2018). Radiation-induced ovarian follicle loss occurs without overt stromal changes. Reproduction, 155(6), 553-562. https://doi.org/10.1530/REP-18-0089

      Kirkland, J. L. (2013). Translating advances from the basic biology of aging into clinical application. Exp Gerontol, 48(1), 1-5. https://doi.org/10.1016/j.exger.2012.11.014

      Mara, J. N., Zhou, L. T., Larmore, M., Johnson, B., Ayiku, R., Amargant, F., Pritchard, M. T., & Duncan, F. E. (2020). Ovulation and ovarian wound healing are impaired with advanced reproductive age. Aging (Albany NY), 12(10), 9686-9713. https://doi.org/10.18632/aging.103237

      Perrone, R., Ashok Kumaar, P. V., Haky, L., Hahn, C., Riley, R., Balough, J., Zaza, G., Soygur, B., Hung, K., Prado, L., Kasler, H. G., Tiwari, R., Matsui, H., Hormazabal, G. V., Heckenbach, I., Scheibye-Knudsen, M., Duncan, F. E., & Verdin, E. (2023). CD38 regulates ovarian function and fecundity via NAD(+) metabolism. iScience, 26(10), 107949. https://doi.org/10.1016/j.isci.2023.107949

      Quan, N., Harris, L. R., Halder, R., Trinidad, C. V., Johnson, B. W., Horton, S., Kimler, B. F., Pritchard, M. T., & Duncan, F. E. (2020). Differential sensitivity of inbred mouse strains to ovarian damage in response to low-dose total body irradiationdagger. Biol Reprod, 102(1), 133-144. https://doi.org/10.1093/biolre/ioz164

      Savas, J. N., Toyama, B. H., Xu, T., Yates, J. R., 3rd, & Hetzer, M. W. (2012). Extremely long-lived nuclear pore proteins in the rat brain. Science, 335(6071), 942. https://doi.org/10.1126/science.1217421

      Toyama, B. H., Savas, J. N., Park, S. K., Harris, M. S., Ingolia, N. T., Yates, J. R., 3rd, & Hetzer, M. W. (2013). Identification of long-lived proteins reveals exceptional stability of essential cellular structures. Cell, 154(5), 971-982. https://doi.org/10.1016/j.cell.2013.07.037

    1. Reviewer #3 (Public review):

      The manuscript by Fargeot and colleagues assesses the relative effects of species and genetic diversity on ecosystem functioning. This study is very well written and examines the interesting question of whether within-species or among-species diversity correlates with ecosystem functioning, and whether these effects are consistent across trophic levels. The main findings are that genetic diversity appears to have a stronger positive effect on function than species diversity (which appears negative). These results are interesting and have value.

      However, I do have some concerns that could influence the interpretation.

      (1) Scale: the different measures of diversity and function for the different trophic levels are measured over very different spatial scales, for example, trees along 200 m transects and 15 cm traps. It is not clear whether trees 200 m away are having an effect on small-scale function.

      (2) Size of diversity gradients: More information is needed on the actual diversity gradients. One of the issues with surveys of natural systems is that they are of species that have already gone through selection filters from a regional pool, and theoretically, if the environments are similar, you should get similar sets of species, without monocultures. So, if the species diversity gradients range from say, 6 to 8 species, but genetic diversity gradients span an order of magnitude more, you can explain much more variance with genetic diversity. Related to this, species diversity effects on function are often asymptotic at high diversity and so if you are only sampling at the high diversity range, we should expect a strong effect.

      (3) Ecosystem functions: The functions are largely biomass estimates (expect decomposition), and I fail to see how the biomass of a single species can be construed as an ecosystem function. Aren't you just estimating a selection effect in this case?

      Note that the article claims to be one of the only studies to look at function across trophic levels, but there are several others out there, for example:

      Li, F., Altermatt, F., Yang, J., An, S., Li, A., & Zhang, X. (2020). Human activities' fingerprint on multitrophic biodiversity and ecosystem functions across a major river catchment in China. Global change biology, 26(12), 6867-6879.

      Luo, Y. H., Cadotte, M. W., Liu, J., Burgess, K. S., Tan, S. L., Ye, L. J., ... & Gao, L. M. (2022). Multitrophic diversity and biotic associations influence subalpine forest ecosystem multifunctionality. Ecology, 103(9), e3745.

      Moi, D. A., Romero, G. Q., Antiqueira, P. A., Mormul, R. P., Teixeira de Mello, F., & Bonecker, C. C. (2021). Multitrophic richness enhances ecosystem multifunctionality of tropical shallow lakes. Functional Ecology, 35(4), 942-954.

      Wan, B., Liu, T., Gong, X., Zhang, Y., Li, C., Chen, X., ... & Liu, M. (2022). Energy flux across multitrophic levels drives ecosystem multifunctionality: Evidence from nematode food webs. Soil Biology and Biochemistry, 169, 108656.

      And the case was made strongly by:

      Seibold, S., Cadotte, M. W., MacIvor, J. S., Thorn, S., & Müller, J. (2018). The necessity of multitrophic approaches in community ecology. Trends in ecology & evolution, 33(10), 754-764.

    2. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      This work used a comprehensive dataset to compare the effects of species diversity and genetic diversity within each trophic level and across three trophic levels. The results showed that species diversity had negative effects on ecosystem functions, while genetic diversity had positive effects. These effects were observed only within each trophic level and not across the three trophic levels studied. Although the effects of biodiversity, especially genetic diversity across multi-trophic levels, have been shown to be important, there are still very few empirical studies on this topic due to the complex relationships and difficulty in obtaining data. This study collected an excellent dataset to address this question, enhancing our understanding of genetic diversity effects in aquatic ecosystems.

      Strengths:

      The study collected an extensive dataset that includes species diversity of primary producers (riparian trees), primary consumers (macroinvertebrate shredders), and secondary consumers (fish). It also includes the genetic diversity of the dominant species at each trophic level, biomass production, decomposition rates, and environmental data.

      The conclusions of this paper are mostly well supported by the data and the writing is logical and easy to follow.

      Weaknesses:

      While the dataset is impressive, the authors conducted analyses more akin to a "meta-analysis," leaving out important basic information about the raw data in the manuscript. Given the complexity of the relationships between different trophic levels and ecosystem functions, it would be beneficial for the authors to show the results of each SEM (structural equation model).

      We understand the point raised by the reviewer. Our objective was to focus the Results section on the main hypotheses, and for this we let away the raw statistics. We can definitively show the seven individual SEM, highlighting the major links, which may help understand some processes. This will be done in the next version of the manuscript.

      The main results presented in the manuscript are derived from a "metadata" analysis of effect sizes. However, the methods used to obtain these effect sizes are not sufficiently clarified. By analyzing the effect sizes of species diversity and genetic diversity on these ecosystem functions, the results showed that species diversity had negative effects, while genetic diversity had positive effects on ecosystem functions. The negative effects of species diversity contradict many studies conducted in biodiversity experiments. The authors argue that their study is more relevant because it is based on a natural system, which is closer to reality, but they also acknowledge that natural systems make it harder to detect underlying mechanisms. Providing more results based on the raw data and offering more explanations of the possible mechanisms in the introduction and discussion might help readers understand why and in what context species diversity could have negative effects.

      We hope you will be right. As said above, we will explore this possibility.

      Environmental variation was included in the analyses to test if the environment would modulate the effects of biodiversity on ecosystem functions. However, the main results and conclusions did not sufficiently address this aspect.

      This will be addressed by the more in-depth analysis of individual SEM, and we will discuss this further.

      Reviewer #2 (Public review):

      Summary:

      Fargeot et al. investigated the relative importance of genetic and species diversity on ecosystem function and examined whether this relationship varies within or between trophic-level responses. To do so, they conducted a well-designed field survey measuring species diversity at 3 trophic levels (primary producers [trees], primary consumers [macroinvertebrate shredders], and secondary consumers [fishes]), genetic diversity in a dominant species within each of these 3 trophic levels and 7 ecosystem functions across 52 riverine sites in southern France. They show that the effect of genetic and species diversity on ecosystem functions are similar in magnitude, but when examining within-trophic level responses, operate in different directions: genetic diversity having a positive effect and species diversity a negative one. This data adds to growing evidence from manipulated experiments that both species and genetic diversity can impact ecosystem function and builds upon this by showing these effects can be observed in nature.

      Strengths:

      The study design has resulted in a robust dataset to ask questions about the relative importance of genetic and species diversity of ecosystem function across and within trophic levels.

      Overall, their data supports their conclusions - at least within the system that they are studying - but as mentioned below, it is unclear from this study how general these conclusions would be.

      Weaknesses:

      (1) While a robust dataset, the authors only show the data output from the SEM (i.e., effect size for each individual diversity type per trophic level (6) on each ecosystem function (7)), instead of showing much of the individual data. Although the summary SEM results are interesting and informative, I find that a weakness of this approach is that it is unclear how environmental factors (which were included but not discussed in the results) nor levels of diversity were correlated across sites. As species and genetic diversity are often correlated but also can have reciprocal feedbacks on each other (e.g., Vellend 2005), there may be constraints that underpin why the authors observed positive effects of one type of diversity (genetic) when negative effects of the other (species). It may have also been informative to run SEM with links between levels of diversity. By focusing only on the summary of SEM data, the authors may be reducing the strength of their field dataset and ability to draw inferences from multiple questions and understand specific study-system responses.

      We will address this issue by performing a more in-depth analysis of each individual SEMs, and provide directly these raw data. Regarding the comment on species-genomic diversity correlations (SGDCs), we would like to point out that this has already been addressed in a previous paper (Fargeot et al. Oikos, 2023). There is actually no correlations between genomic and species diversity in these dataset, which is merely explain by the selection of the sampling sites. The relationships between species diversity, genomic diversity and environmental factors are also detailed in Fargeot et al. (2023). We precisely published this paper first to focus here “only” on BEFs. But we realize we need to provide further information and discuss further these issues. This will be done in the next version of the manuscript.

      (2) My understanding of SEM is it gives outputs of the strength/significance of each pathway/relationship and if so, it isn't clear why this wasn't used and instead, confidence intervals of Z scores to determine which individual BEFs were significant. In addition, an inclusion of the 7 SEM pathway outputs would have been useful to include in an appendix.

      Yes, we can provide p-values. Results from p-values will provide the same information than 95%Cis, both yield very similar (if not exactly the same) results/conclusions. We wil provide the 7 SEMs in Appendices.

      (3) I don't fully agree with the authors calling this a meta-analysis as it is this a single study of multiple sites within a single region and a specific time point, and not a collection of multiple studies or ecosystems conducted by multiple authors. Moreso, the authors are using meta-analysis summary metrics to evaluate their data. The authors tend to focus on these patterns as general trends, but as the data is all from this riverine system this study could have benefited from focusing on what was going on in this system to underpin these patterns. I'd argue more data is needed to know whether across sites and ecosystems, species diversity and genetic diversity have opposite effects on ecosystem function within trophic levels.

      We agree. “Meta-regression” would perhaps be more adequate than “meta-analyses”. As said above, more details will be provided on the next version of the manuscript.

      Reviewer #3 (Public review):

      The manuscript by Fargeot and colleagues assesses the relative effects of species and genetic diversity on ecosystem functioning. This study is very well written and examines the interesting question of whether within-species or among-species diversity correlates with ecosystem functioning, and whether these effects are consistent across trophic levels. The main findings are that genetic diversity appears to have a stronger positive effect on function than species diversity (which appears negative). These results are interesting and have value.

      However, I do have some concerns that could influence the interpretation.

      (1) Scale: the different measures of diversity and function for the different trophic levels are measured over very different spatial scales, for example, trees along 200 m transects and 15 cm traps. It is not clear whether trees 200 m away are having an effect on small-scale function.

      Trees identification and invertebrate (and fish) sampling are done on the same scale. Trees are spread along the river so that their leaves fall directly in the river. Traps have been installed all along the same transect in various micro-habitats. Diversity have been measured at the exact same scale for all organisms. We will try to be more precise.

      (2) Size of diversity gradients: More information is needed on the actual diversity gradients. One of the issues with surveys of natural systems is that they are of species that have already gone through selection filters from a regional pool, and theoretically, if the environments are similar, you should get similar sets of species, without monocultures. So, if the species diversity gradients range from say, 6 to 8 species, but genetic diversity gradients span an order of magnitude more, you can explain much more variance with genetic diversity. Related to this, species diversity effects on function are often asymptotic at high diversity and so if you are only sampling at the high diversity range, we should expect a strong effect.

      We will provide more information. The range of diversity also vary according to the trophic level; there are more invertebrate species than fish species. But overall the rage of species number is large.

      (3) Ecosystem functions: The functions are largely biomass estimates (expect decomposition), and I fail to see how the biomass of a single species can be construed as an ecosystem function. Aren't you just estimating a selection effect in this case?

      The biomass estimated for a certain area represent an estimate of productivity, whatever the number of species being considered. Obviously, productivity of a species can be due to environmental constraints; the biomass is expected to be lower at the niche margin (selection effect). But is these environmental effects are taken into account (which is the case in the SEMs), then the residual variation can be explained by biodiversity effects. We will try to make it more clear.

      Note that the article claims to be one of the only studies to look at function across trophic levels, but there are several others out there, for example:

      Thanks, we will cite some of these studies (and make our claim less strong)

      Li, F., Altermatt, F., Yang, J., An, S., Li, A., & Zhang, X. (2020). Human activities' fingerprint on multitrophic biodiversity and ecosystem functions across a major river catchment in China. Global change biology, 26(12), 6867-6879.

      Luo, Y. H., Cadotte, M. W., Liu, J., Burgess, K. S., Tan, S. L., Ye, L. J., ... & Gao, L. M. (2022). Multitrophic diversity and biotic associations influence subalpine forest ecosystem multifunctionality. Ecology, 103(9), e3745.

      Moi, D. A., Romero, G. Q., Antiqueira, P. A., Mormul, R. P., Teixeira de Mello, F., & Bonecker, C. C. (2021). Multitrophic richness enhances ecosystem multifunctionality of tropical shallow lakes. Functional Ecology, 35(4), 942-954.

      Wan, B., Liu, T., Gong, X., Zhang, Y., Li, C., Chen, X., ... & Liu, M. (2022). Energy flux across multitrophic levels drives ecosystem multifunctionality: Evidence from nematode food webs. Soil Biology and Biochemistry, 169, 108656.

      And the case was made strongly by:

      Seibold, S., Cadotte, M. W., MacIvor, J. S., Thorn, S., & Müller, J. (2018). The necessity of multitrophic approaches in community ecology. Trends in ecology & evolution, 33(10), 754-764.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      Line 127. Provide a few more words describing the voltage protocol. To the uninitiated, panels A and B will be difficult to understand. "The large negative step is used to first close all channels, then probe the activation function with a series of depolarizing steps to re-open them and obtain the max conductance from the peak tail current at -36 mV. "

      We have revised the text as suggested (revision lines 127 to Line 131): “From a holding potential within the gK,L activation range (here –74 mV), the cell is hyperpolarized to –124 mV, negative to EK and the activation range, producing a large inward current through open gK,L channels that rapidly decays as the channels deactivate. We use the large transient inward current as a hallmark of gK,L. The hyperpolarization closes all channels, and then the activation function is probed with a series of depolarizing steps, obtaining the max conductance from the peak tail current at –44 mV (Fig. 1A).”

      Incidentally, why does the peak tail current decay? 

      We added this text to the figure legend to explain this: “For steps positive to the midpoint voltage, tail currents are very large. As a result, K+ accumulation in the calyceal cleft reduces driving force on K+, causing currents to decay rapidly, as seen in A (Lim et al., 2011).”

      The decay of the peak tail current is a feature of gK,L (large K+ conductance) and the large enclosed synaptic cleft (which concentrates K+ that effluxes from the HC). See Govindaraju et al. (2023) and Lim et al. (2011) for modeling and experiments around this phenomenon.

      Line 217-218. For some reason, I stumbled over this wording. Perhaps rearrange as "In type II HCs absence of Kv1.8 significantly increased Rin and tauRC. There was no effect on Vrest because the conductances to which Kv1.8 contributes, gA and gDR activate positive to the resting potential. (so which K conductances establish Vrest???). 

      We kept our original wording because we wanted to discuss the baseline (Vrest) before describing responses to current injection.

      ->Vrest is presumably maintained by ATP-dependent Na/K exchangers (ATP1a1), HCN, Kir, and mechanotransduction currents. Repolarization is achieved by delayed rectifier and A-type K+ conductances in type II HCs.

      Figure 4, panel C - provides absolute membrane potential for voltage responses. Presumably, these were the most 'ringy' responses. Were they obtained at similar Vm in all cells (i.e., comparisons of Q values in lines 229-230). 

      We added the absolute membrane potential scale. Type II HC protocols all started with 0 pA current injection at baseline, so they were at their natural Vrest, which did not differ by genotype or zone. Consistent with Q depending on expression of conductances that activate positive to Vrest, Q did not co-vary with Vrest (Pearson’s correlation coefficient = 0.08, p = 0.47, n= 85).

      Lines 254. Staining is non-specific? Rather than non-selective? 

      Yes, thanks - Corrected (Line 264).

      Figure 6. Do you have a negative control image for Kv1.4 immuno? Is it surprising that this label is all over the cell, but Kv1.8 is restricted to the synaptic pole? 

      We don’t have a null-animal control because this immunoreactivity was done in rat. While the cuticular plate staining was most likely nonspecific because we see that with many different antibodies, it’s harder to judge the background staining in the hair cell body layer. After feedback from the reviewers, we decided to pull the KV1.4 immunostaining from the paper because of the lack of null control, high background, and inability to reproduce these results in mouse tissue. In our hands, in mouse tissue, both mouse and rabbit anti-KV1.4 antibodies failed to localize to the hair cell membrane. Further optimization or another method could improve that, but for now the single-cell expression data (McInturff et al., 2018) remain the strongest evidence for KV1.4 expression in murine type II hair cells.

      Lines 400-404. Whew, this is pretty cryptic. Expand a bit? 

      We simplified this paragraph (revision lines 411-413): “We speculate that gA and gDR(KV1.8) have different subunit composition: gA may include heteromers of KV1.8 with other subunits that confer rapid inactivation, while gDR(KV1.8) may comprise homomeric KV1.8 channels, given that they do not have N-type inactivation .”

      Line 428. 'importantly different ion channels'. I think I understand what is meant but perhaps say a bit more. 

      Revised (Line 438): “biophysically distinct and functionally different ion channels”.

      Random thought. In addition to impacting Rin and TauRC, do you think the more negative Vrest might also provide a selective advantage by increasing the driving force on K entry from endolymph? 

      When the calyx is perfectly intact, gK,L is predicted to make Vrest less negative than the values we report in our paper, where we have disturbed the calyx to access the hair cell (–80, Govindaraju et al., 2023, vs. –87 mV, here). By enhancing K+ accumulation in the calyceal cleft, the intact calyx shifts EK—and Vrest—positively (Lim et al., 2011), so the effect on driving force may not be as drastic as what you are thinking.

      Reviewer #2 (Recommendations For The Authors): 

      (1) Introduction: wouldn't the small initial paragraph stating the main conclusion of the study fit better at the end of the background section, instead of at the beginning? 

      Thank you for this idea, we have tried that and settled on this direct approach to let people know in advance what the goals of the paper are.

      (2) Pg.4: The following sentence is rather confusing "Between P5 and P10, we detected no evidence of a non-gK,L KV1.8-dependent.....". Also, Suppl. Fig 1A seems to show that between P5 and P10 hair cells can display a potassium current having either a hyperpolarised or depolarised Vhalf. Thus, I am not sure I understand the above statement. 

      Thank you for pointing out unclear wording. We used the more common “delayed rectifier” term in our revision (Lines 144-147): “Between P5 and P10, some type I HCs have not yet acquired the physiologically defined conductance, gK,L.. N effects of KV1.8 deletion were seen in the delayed rectifier currents of immature type I HCs (Suppl. Fig. 1B), showing that they are not immature forms of the Kv1.8-dependent gK,L channels. ”

      (3) For the reduced Cm of hair cells from Kv1.8 knockout mice, could another reason be simply the immature state of the hair cells (i.e. lack of normal growth), rather than less channels in the membrane? 

      There were no other signs to suggest immaturity or abnormal growth in KV1.8–/– hair cells or mice. Importantly, type II HCs did not show the same Cm effect.

      We further discussed the capacitance effect in lines 160-167: “Cm scales with surface area, but soma sizes were unchanged by deletion of KV1.8 (Suppl. Table 2). Instead, Cm may be higher in KV1.8+/+ cells because of gK,L for two reasons. First, highly expressed trans-membrane proteins (see discussion of gK,L channel density in Chen and Eatock, 2000) can affect membrane thickness (Mitra et al., 2004), which is inversely proportional to specific Cm. Second, gK,L could contaminate estimations of capacitive current, which is calculated from the decay time constant of transient current evoked by small voltage steps outside the operating range of any ion channels. gK,L has such a negative operating range that, even for Vm negative to –90 mV, some gK,L channels are voltage-sensitive and could add to capacitive current.”

      (4) Methods: The electrophysiological part states that "For most recordings, we used .....". However, it is not clear what has been used for the other recordings.

      Thanks for catching this error, a holdover from an earlier ms. version.  We have deleted “For most recordings” (revision line 466).

      Also, please provide the sign for the calculated 4 mV liquid junction potential. 

      Done (revision line 476).

      Reviewer #3 (Recommendations For The Authors): 

      (1) Some of the data in panels in Fig. 1 are hard to match up. The voltage protocols shown in A and B show steps from hyperpolarized values to -71mV (A) and -32 mV (B). However, the value from A doesn't seem to correspond with the activation curve in C.

      Thank you for catching this.  We accidentally showed the control I-X curve from a different cell than that in A. We now show the G-V relation for the cell in A.

      Also the Vhalf in D for -/- animals is ~-38 mV, which is similar to the most positive step shown in the protocol.

      The most positive step in Figure 1B is actually –25 mV. The uneven tick labels might have been confusing, so we re-labeled them to be more conventional.

      Were type I cells stepped to more positive potentials to test for the presence of voltage-activated currents at greater depolarizations? This is needed to support the statement on lines 147-148. 

      We added “no additional K+ conductance activated up to +40 mV” (revision line 149-150).  Our standard voltage-clamp protocol iterates up to ~+40 mV in KV1.8–/– hair cells, but in Figure 1 we only showed steps up to –25 mV because K+ accumulation in the synaptic cleft with the calyx distorts the current waveform even for the small residual conductances of the knockouts. KV1.8–/– hair cells have a main KV conductance with a Vhalf of ~–38 mV, as shown in Figure 1, and we did not see an additional KV conductance that activated with a more positive Vhalf up to +40 mV.

      (2) Line 151 states "While the cells of Kv1.8-/- appeared healthy..." how were epithelia assessed for health? Hair cells arise from support cells and it would be interesting to know if Kv1.8 absence influences supporting cells or neurons. 

      We added our criteria for cell health to lines 477-479: “KV1.8–/– hair cells appeared healthy in that cells had resting potentials negative to –50 mV, cells lasted a long time (20-30 minutes) in ruptured patch recordings, membranes were not fragile, and extensive blebbing was not seen.”

      Supporting cells were not routinely investigated. We characterized calyx electrical activity (passive membrane properties, voltage-gated currents, firing pattern) and didn’t detect differences between +/+, +/–, and –/– recordings (data not shown). KV1.8 was not detected in neural tissue (Lee et al., 2013). 

      (3) Several different K+ channel subtypes were found to contribute to inner hair cell K+ conductances (Dierich et al. 2020) but few additional K+ channel subtypes are considered here in vestibular hair cells. Further comments on calcium-activated conductances (lines 310-317) would be helpful since apamin-sensitive SK conductances are reported in type II hair cells (Poppi et al. 2018) and large iberiotoxin-sensitive BK conductances in type I hair cells (Contini et al. 2020). Were iberiotoxin effects studied at a range of voltages and might calcium-dependent conductances contribute to the enhanced resonance responses shown in Fig. 4? 

      We refer you to lines 310-317 in the original ms (lines 322-329 in the revised ms), where we explain possible reasons for not observing IK(Ca) in this study.

      (4) Similar to GK,L erg (Kv11) channels show significant Cs+-permeability. Were experiments using Cs+ and/or Kv11 antagonists performed to test for Kv11? 

      No. Hurley et al. (2006) used Kv11 antagonists to reveal Kv11 currents in rat utricular type I hair cells with perforated patch, which were also detected in rats with single-cell RT-PCR (Hurley et al. 2006) and in mice with single-cell RNAseq (McInturff et al., 2018).  They likely contribute to hair cell currents, alongside Kv7, Kv1.8, HCN1, and Kir. 

      (5) Mechanosensitive ("MET") channels in hair cells are mentioned on lines 234 and 472 (towards the end of the Discussion), but a sentence or two describing the sensory function of hair cells in terms of MET channels and K+ fluxes would help in the Introduction too. 

      Following this suggestion we have expanded the introduction with the following lines  (78-87): “Hair cells are known for their large outwardly rectifying K+ conductances, which repolarize membrane voltage following a mechanically evoked perturbation and in some cases contribute to sharp electrical tuning of the hair cell membrane.  Because gK,L is unusually large and unusually negatively activated, it strongly attenuates and speeds up the receptor potentials of type I HCs (Correia et al., 1996; Rüsch and Eatock, 1996b). In addition, gK,L augments a novel non-quantal transmission from type I hair cell to afferent calyx by providing open channels for K+ flow into the synaptic cleft (Contini et al., 2012, 2017, 2020; Govindaraju et al., 2023), increasing the speed and linearity of the transmitted signal (Songer and Eatock, 2013).”

      (6) Lines 258-260 state that GKL does not inactivate, but previous literature has documented a slow type of inactivation in mouse crista and utricle type I hair cells (Lim et al. 2011, Rusch and Eatock 1996) which should be considered. 

      Lim et al. (2011) concluded that K+ accumulation in the synaptic cleft can explain much of the apparent inactivation of gK,L. In our paper, we were referring to fast, N-type inactivation. We changed that line to be more specific; new revision lines 269-271: “KV1.8, like most KV1 subunits, does not show fast inactivation as a heterologously expressed homomer (Lang et al., 2000; Ranjan et al., 2019; Dierich et al., 2020), nor do the KV1.8-dependent channels in type I HCs, as we show, and in cochlear inner hair cells (Dierich et al., 2020).”

      (7) Lines 320-321 Zonal differences in inward rectifier conductances were reported previously in bird hair cells (Masetto and Correia 1997) and should be referenced here.

      Zonal differences were reported by Masetto and Correia for type II but not type I avian hair cells, which is why we emphasize that we found a zonal difference in I-H in type I hair cells. We added two citations to direct readers to type II hair cell results (lines 333-334): “The gK,L knockout allowed identification of zonal differences in IH and IKir in type I HCs, previously examined in type II HCs (Masetto and Correia, 1997; Levin and Holt, 2012).”

      Also, Horwitz et al. (2011) showed HCN channels in utricles are needed for normal balance function, so please include this reference (see line 171). 

      Done (line 184).

      (8) Fig 6A. Shows Kv1.4 staining in rat utricle but procedures for rat experiments are not described. These should be added. Also, indicate striola or extrastriola regions (if known). 

      We removed KV1.4 immunostaining from the paper, see above.

      (9) Table 6, ZD7288 is listed -was this reagent used in experiments to block Gh? If not please omit. 

      ZD7288 was used to block gH to produce a clean h-infinity curve in Figure 6, which is described in the legend.

      (10) In supplementary Fig. 5A make clear if the currents are from XE991 subtraction. Also, is the G-V data for single cell or multiple cells in B? It appears to be from 1 cell but ages P11-505 are given in legend. 

      The G-V curve in B is from XE991 subtraction, and average parameters in the figure caption are for all the KV1.8–/–  striolar type I hair cells where we observed this double Boltzmann tail G-V curve. I added detail to the figure caption to explain this better.

      (11) Supplementary Fig. 6A claims a fast activation of inward rectifier K+ channels in type II but not type I cells-not clear what exactly is measured here.

      We use “fast inward rectifier” to indicate the inward current that increases within the first 20 ms after hyperpolarization from rest (IKir, characterized in Levin & Holt, 2012) in contrast to HCN channels, which open over ~100 ms. We added panel C to show that the activation of IKir is visible in type II hair cells but not in the knockout type I hair cells that lack gK,L. IKir was a reliable cue to distinguish type I and type II hair cells in the knockout.

      For our actual measurements in Fig 6B, we quantified the current flowing after 250 ms at –124 mV because we did not pharmacologically separate IKir and IH.

      Could the XE991-sensitive current be activated and contributing?

      The XE991-sensitive current could decay (rapidly) at the onset of the hyperpolarizing step, but was not contributing to our measurement of IKir­ and IH, made after 250 ms at –124 mV, at which point any low-voltage-activated (LVA) outward rectifiers have deactivated. Additionally, the LVA XE991-sensitive currents were rare (only detected in some striolar type I hair cells) and when present did not compete with fast IKir, which is only found in type II hair cells.

      Also, did the inward rectifier conductances sustain any outward conductance at more depolarized voltage steps? 

      For the KV1.8-null mice specifically, we cannot answer the question because we did not use specific blocking agents for inward rectifiers.  However, we expect that there would only be sustained outward IR currents at voltages between EK and ~-60 mV: the foot of IKir’s I-V relation according to published data from mouse utricular hair cells – e.g., Holt and Eatock 1995, Rusch and Eatock 1996, Rusch et al. 1998, Horwitz et al., 2011, etc.  Thus, any such current would be unlikely to contaminate the residual outward rectifiers in Kv1.8-null animals, which activate positive to ~-60 mV. 

      (I-HCN is also not a problem, because it could only be outward positive to its reversal potential at ~-40 mV, which is significantly positive to its voltage activation range.)

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      In this manuscript, the authors use a large dataset of neuroscience publications to elucidate the nature of self-citation within the neuroscience literature. The authors initially present descriptive measures of self-citation across time and author characteristics; they then produce an inclusive model to tease apart the potential role of various article and author features in shaping self-citation behavior. This is a valuable area of study, and the authors approach it with an appropriate and well-structured dataset.

      The study's descriptive analyses and figures are useful and will be of interest to the neuroscience community. However, with regard to the statistical comparisons and regression models, I believe that there are methodological flaws that may limit the validity of the presented results. These issues primarily affect the uncertainty of estimates and the statistical inference made on comparisons and model estimates - the fundamental direction and magnitude of the results are unlikely to change in most cases. I have included detailed statistical comments below for reference.

      Conceptually, I think this study will be very effective at providing context and empirical evidence for a broader conversation around self-citation. And while I believe that there is room for a deeper quantitative dive into some finer-grained questions, this paper will be a valuable catalyst for new areas of inquiry around citation behavior - e.g., do authors change self-citation behavior when they move to more or less prestigious institutions? do self-citations in neuroscience benefit downstream citation accumulation? do journals' reference list policies increase or decrease self-citation? - that I hope that the authors (or others) consider exploring in future work.

      Thank you for your suggestions and your generally positive view of our work. As described below, we have made the statistical improvements that you suggested.

      Statistical comments:

      (1) Throughout the paper, the nested nature of the data does not seem to be appropriately handled in the bootstrapping, permutation inference, and regression models. This is likely to lead to inappropriately narrow confidence bands and overly generous statistical inference.

      We apologize for this error. We have now included nested bootstrapping and permutation tests. We defined an “exchangeability block” as a co-authorship group of authors. In this dataset, that meant any authors who published together (among the articles in this dataset) as a First Author / Last Author pairing were assigned to the same exchangeability block. It is not realistic to check for overlapping middle authors in all papers because of the collaborative nature of the field. In addition, we believe that self-citations are primarily controlled by first and last authors, so we can assume that middle authors do not control self-citation habits. We then performed bootstrapping and permutation tests in the constraints of the exchangeability blocks.

      We first describe this in the results (page 3, line 110):

      “Importantly, we accounted for the nested structure of the data in bootstrapping and permutation tests by forming co-authorship exchangeability blocks.”

      We also describe this in 4.8 Confidence Intervals (page 21, line 725):

      “Confidence intervals were computed with 1000 iterations of bootstrap resampling at the article level. For example, of the 100,347 articles in the dataset, we resampled articles with replacement and recomputed all results. The 95% confidence interval was reported as the 2.5 and 97.5 percentiles of the bootstrapped values.

      We grouped data into exchangeability blocks to avoid overly narrow confidence intervals or overly optimistic statistical inference. Each exchangeability block comprised any authors who published together as a First Author / Last Author pairing in our dataset. We only considered shared First/Last Author publications because we believe that these authors primarily control self-citations, and otherwise exchangeability blocks would grow too large due to the highly collaborative nature of the field. Furthermore, the exchangeability blocks do not account for co-authorship in other journals or prior to 2000. A distribution of the sizes of exchangeability blocks is presented in Figure S15.”

      In describing permutation tests, we also write (page 21, line 739):

      “4.9 P values

      P values were computed with permutation testing using 10,000 permutations, with the exception of regression P values and P values from model coefficients. For comparing different fields (e.g., Neuroscience and Psychiatry) and comparing self-citation rates of men and women, the labels were randomly permuted by exchangeability block to obtain null distributions. For comparing self-citation rates between First and Last Authors, the first and last authorship was swapped in 50% of exchangeability blocks.”

      For modeling, we considered doing a mixed effects model but found difficulties due to computational power. For example, with our previous model, there were hundreds of thousands of levels for the paper random effect, and tens of thousands of levels for the author random effect. Even when subsampling or using packages designed for large datasets (e.g., mgcv’s bam function: https://www.rdocumentation.org/packages/mgcv/versions/1.9-1/topics/bam), we found computational difficulties.

      As a result, we switched to modeling results at the paper level (e.g., self-citation count or rate). We found that results could be unstable when including author-level random effects because in many cases there was only one author per group. Instead, to avoid inappropriately narrow confidence bands, we resampled the dataset such that each author was only represented once. For example, if Author A had five papers in this dataset, then one of their five papers was randomly selected. We updated our description of our models in the Methods section (page 21, line 754):

      “4.10 Exploring effects of covariates with generalized additive models

      For these analyses, we used the full dataset size separately for First and Last Authors (Table S2). This included 115,205 articles and 5,794,926 citations for First Authors, and 114,622 articles and 5,801,367 citations for Last Authors. We modeled self-citation counts, self-citation rates, and number of previous papers for First Authors and Last Authors separately, resulting in six total models.

      We found that models could be computationally intensive and unstable when including author-level random effects because in many cases there was only one author per group. Instead, to avoid inappropriately narrow confidence bands, we resampled the dataset such that each author was only represented once. For example, if Author A had five papers in this dataset, then one of their five papers was randomly selected. The random resampling was repeated 100 times as a sensitivity analysis (Figure S12).

      For our models, we used generalized additive models from mgcv’s “gam” function in R 49. The smooth terms included all the continuous variables: number of previous papers, academic age, year, time lag, number of authors, number of references, and journal impact factor. The linear terms included all the categorical variables: field, gender affiliation country LMIC status, and document type. We empirically selected a Tweedie distribution 50 with a log link function and p=1.2. The p parameter indicates that the variance is proportional to the mean to the p power 49. The p parameter ranges from 1-2, with p=1 equivalent to the Poisson distribution and p=2 equivalent to the gamma distribution. For all fitted models, we simulated the residuals with the DHARMa package, as standard residual plots may not be appropriate for GAMs 51. DHARMa scales the residuals between 0 and 1 with a simulation-based approach 51. We also tested for deviation from uniformity, dispersion, outliers, and zero inflation with DHARMa. Non-uniformity, dispersion, outliers, and zero inflation were significant due to the large sample size, but small in effect size in most cases. The simulated quantile-quantile plots from DHARMa suggested that the observed and simulated distributions were generally aligned, with the exception of slight misalignment in the models for the number of previous papers. These analyses are presented in Figure S11 and Table S7.

      In addition, we tested for inadequate basis functions using mgcv’s “gam.check()” function 49. Across all smooth predictors and models, we ultimately selected between 10-20 basis functions depending on the variable and outcome measure (counts, rates, papers). We further checked the concurvity of the models and ensured that the worst-case concurvity for all smooth predictors was about 0.8 or less.”

      The direction of our results primarily stayed the same, with the exception of gender results. Men tended to self-cite slightly less (or equal self-citation rates) after accounting for numerous covariates. As such, we also modeled the number of previous papers to explain the discrepancy between our raw data and the modeled gender results. Please find the updated results text below (page 11, line 316):

      “2.9 Exploring effects of covariates with generalized additive models

      Investigating the raw trends and group differences in self-citation rates is important, but several confounding factors may explain some of the differences reported in previous sections. For instance, gender differences in self-citation were previously attributed to men having a greater number of prior papers available to self-cite 7,20,21. As such, covarying for various author- and article-level characteristics can improve the interpretability of self-citation rate trends. To allow for inclusion of author-level characteristics, we only consider First Author and Last Author self-citation in these models.

      We used generalized additive models (GAMs) to model the number and rate of self-citations for First Authors and Last Authors separately. The data were randomly subsampled so that each author only appeared in one paper. The terms of the model included several article characteristics (article year, average time lag between article and all cited articles, document type, number of references, field, journal impact factor, and number of authors), as well as author characteristics (academic age, number of previous papers, gender, and whether their affiliated institution is in a low- and middle-income country). Model performance (adjusted R2) and coefficients for parametric predictors are shown in Table 2. Plots of smooth predictors are presented in Figure 6.

      First, we considered several career and temporal variables. Consistent with prior works 20,21, self-citation rates and counts were higher for authors with a greater number of previous papers. Self-citation counts and rates increased rapidly among the first 25 published papers but then more gradually increased. Early in the career, increasing academic age was related to greater self-citation. There was a small peak at about five years, followed by a small decrease and a plateau. We found an inverted U-shaped trend for average time lag and self-citations, with self-citations peaking approximately three years after initial publication. In addition, self-citations have generally been decreasing since 2000. The smooth predictors showed larger decreases in the First Author model relative to the Last Author model (Figure 6).

      Then, we considered whether authors were affiliated with an institution in a low- and middle-income country (LMIC). LMIC status was determined by the Organisation for Economic Co-operation and Development. We opted to use LMIC instead of affiliation country or continent to reduce the number of model terms. We found that papers from LMIC institutions had significantly lower self-citation counts (-0.138 for First Authors, -0.184 for Last Authors) and rates (-12.7% for First Authors, -23.7% for Last Authors) compared to non-LMIC institutions. Additional results with affiliation continent are presented in Table S5. Relative to the reference level of Asia, higher self-citations were associated with Africa (only three of four models), the Americas, Europe, and Oceania.

      Among paper characteristics, a greater number of references was associated with higher self-citation counts and lower self-citation rates (Figure 6). Interestingly, self-citations were greater for a small number of authors, though the effect diminished after about five authors. Review articles were associated with lower self-citation counts and rates. No clear trend emerged between self-citations and journal impact factor. In an analysis by field, despite the raw results suggesting that self-citation rates were lower in Neuroscience, GAM-derived self-citations were greater in Neuroscience than in Psychiatry or Neurology.

      Finally, our results aligned with previous findings of nearly equivalent self-citation rates for men and women after including covariates, even showing slightly higher self-citation rates in women. Since raw data showed evidence of a gender difference in self-citation that emerges early in the career but dissipates with seniority, we incorporated two interaction terms: one between gender and academic age and a second between gender and the number of previous papers. Results remained largely unchanged with the interaction terms (Table S6).

      2.10 Reconciling differences between raw data and models

      The raw and GAM-derived data exhibited some conflicting results, such as for gender and field of research. To further study covariates associated with this discrepancy, we modeled the publication history for each author (at the time of publication) in our dataset (Table 2). The model terms included academic age, article year, journal impact factor, field, LMIC status, gender, and document type. Notably, Neuroscience was associated with the fewest number of papers per author. This explains how authors in Neuroscience could have the lowest raw self-citation rates but the highest self-citation rates after including covariates in a model. In addition, being a man was associated with about 0.25 more papers. Thus, gender differences in self-citation likely emerged from differences in the number of papers, not in any self-citation practices.”

      (2) The discussion of the data structure used in the regression models is somewhat opaque, both in the main text and the supplement. From what I gather, these models likely have each citation included in the model at least once (perhaps twice, once for first-author status and one for last-author status), with citations nested within citing papers, cited papers, and authors. Without inclusion of random effects, the interpretation and inference of the estimates may be misleading.

      Please see our response to point (1) to address random effects. We have also switched to GAMs (see point #3 below) and provided more detail in the methods. Notably, we decided against using author-level effects due to poor model stability, as there can be as few as one author per group. Instead, we subsampled the dataset such that only one paper appeared from each author.

      (3) I am concerned that the use of the inverse hyperbolic sine transform is a bit too prescriptive, and may be producing poor fits to the true predictor-outcome relationships. For example, in a figure like Fig S8, it is hard to know to what extent the sharp drop and sign reversal are true reflections of the data, and to what extent they are artifacts of the transformed fit.

      Thank you for raising this point. We have now switched to using generalized additive models (GAMs). GAMs provide a flexible approach to modeling that does not require transformations. We described this in detail in point (1) above and in Methods 4.10 Exploring effects of covariates with generalized additive models (page 21, line 754).

      “4.10 Exploring effects of covariates with generalized additive models

      For these analyses, we used the full dataset size separately for First and Last Authors (Table S2). This included 115,205 articles and 5,794,926 citations for First Authors, and 114,622 articles and 5,801,367 citations for Last Authors. We modeled self-citation counts, self-citation rates, and number of previous papers for First Authors and Last Authors separately, resulting in six total models.

      We found that models could be computationally intensive and unstable when including author-level random effects because in many cases there was only one author per group. Instead, to avoid inappropriately narrow confidence bands, we resampled the dataset such that each author was only represented once. For example, if Author A had five papers in this dataset, then one of their five papers was randomly selected. The random resampling was repeated 100 times as a sensitivity analysis (Figure S12).

      For our models, we used generalized additive models from mgcv’s “gam” function in R 48. The smooth terms included all the continuous variables: number of previous papers, academic age, year, time lag, number of authors, number of references, and journal impact factor. The linear terms included all the categorical variables: field, gender affiliation country LMIC status, and document type. We empirically selected a Tweedie distribution 49 with a log link function and p=1.2. The p parameter indicates that the variance is proportional to the mean to the p power 48. The p parameter ranges from 1-2, with p=1 equivalent to the Poisson distribution and p=2 equivalent to the gamma distribution. For all fitted models, we simulated the residuals with the DHARMa package, as standard residual plots may not be appropriate for GAMs 50. DHARMa scales the residuals between 0 and 1 with a simulation-based approach 50. We also tested for deviation from uniformity, dispersion, outliers, and zero inflation with DHARMa. Non-uniformity, dispersion, outliers, and zero inflation were significant due to the large sample size, but small in effect size in most cases. The simulated quantile-quantile plots from DHARMa suggested that the observed and simulated distributions were generally aligned, with the exception of slight misalignment in the models for the number of previous papers. These analyses are presented in Figure S11 and Table S7.

      In addition, we tested for inadequate basis functions using mgcv’s “gam.check()” function 48. Across all smooth predictors and models, we ultimately selected between 10-20 basis functions depending on the variable and outcome measure (counts, rates, papers). We further checked the concurvity of the models and ensured that the worst-case concurvity for all smooth predictors was about 0.8 or less.”

      (4) It seems there are several points in the analysis where papers may have been dropped for missing data (e.g., missing author IDs and/or initials, missing affiliations, low-confidence gender assessment). It would be beneficial for the reader to know what % of the data was dropped for each analysis, and for comparisons across countries it would be important for the authors to make sure that there is not differential missing data that could affect the interpretation of the results (e.g., differences in self-citation being due to differences in Scopus ID coverage).

      Thank you for raising this important point. In the methods section, we describe how the data are missing (page 18, line 623):

      “4.3 Data exclusions and missingness

      Data were excluded across several criteria: missing covariates, missing citation data, out-of-range values at the citation pair level, and out-of-range values at the article level (Table 3). After downloading the data, our dataset included 157,287 articles and 8,438,733 citations. We excluded any articles with missing covariates (document type, field, year, number of authors, number of references, academic age, number of previous papers, affiliation country, gender, and journal). Of the remaining articles, we dropped any for missing citation data (e.g., cannot identify whether a self-citation is present due to lack of data). Then, we removed citations with unrealistic or extreme values. These included an academic age of less than zero or above 38/44 for First/Last Authors (99th percentile); greater than 266/522 papers for First/Last Authors (99th percentile); and a cited year before 1500 or after 2023. Subsequently, we dropped articles with extreme values that could contribute to poor model stability. These included greater than 30 authors; fewer than 10 references or greater than 250 references; and a time lag of greater than 17 years. These values were selected to ensure that GAMs were stable and not influenced by a small number of extreme values.

      In addition, we evaluated whether the data were not missing at random (Table S8). Data were more likely to be missing for reviews relative to articles, for Neurology relative to Neuroscience or Psychiatry, in works from Africa relative to the other continents, and for men relative to women. Scopus ID coverage contributed in part to differential missingness. However, our exclusion criteria also contribute. For example, Last Authors with more than 522 papers were excluded to help stabilize our GAMs. More men fit this exclusion criteria than women.”

      Due to differential missingness, we wrote in the limitations (page 16, line 529):

      “Ninth, data were differentially missing (Table S8) due to Scopus coverage and gender estimation. Differential missingness could bias certain results in the paper, but we hope that the dataset is large enough to reduce any potential biases.”

      Reviewer #2 (Public Review):

      The authors provide a comprehensive investigation of self-citation rates in the field of Neuroscience, filling a significant gap in existing research. They analyze a large dataset of over 150,000 articles and eight million citations from 63 journals published between 2000 and 2020. The study reveals several findings. First, they state that there is an increasing trend of self-citation rates among first authors compared to last authors, indicating potential strategic manipulation of citation metrics. Second, they find that the Americas show higher odds of self-citation rates compared to other continents, suggesting regional variations in citation practices. Third, they show that there are gender differences in early-career self-citation rates, with men exhibiting higher rates than women. Lastly, they find that self-citation rates vary across different subfields of Neuroscience, highlighting the influence of research specialization. They believe that these findings have implications for the perception of author influence, research focus, and career trajectories in Neuroscience.

      Overall, this paper is well written, and the breadth of analysis conducted by authors, with various interactions between variables (eg. gender vs. seniority), shows that the authors have spent a lot of time thinking about different angles. The discussion section is also quite thorough. The authors should also be commended for their efforts in the provision of code for the public to evaluate their own self-citations. That said, here are some concerns and comments that, if addressed, could potentially enhance the paper:

      Thank you for your review and your generally positive view of our work.

      (1) There are concerns regarding the data used in this study, specifically its bias towards top journals in Neuroscience, which limits the generalizability of the findings to the broader field. More specifically, the top 63 journals in neuroscience are based on impact factor (IF), which raises a potential issue of selection bias. While the paper acknowledges this as a limitation, it lacks a clear justification for why authors made this choice. It is also unclear how the "top" journals were identified as whether it was based on the top 5% in terms of impact factor? Or 10%? Or some other metric? The authors also do not provide the (computed) impact factors of the journals in the supplementary.

      We apologize for the lack of clarity about our selection of journals. We agree that there are limitations to selecting higher impact journals. However, we needed to apply some form of selection in order to make the analysis manageable. For instance, even these 63 journals include over five million citations. We better describe our rationale behind the approach as follows (page 17, line 578):

      “We collected data from the 25 journals with the highest impact factors, based on Web of Science impact factors, in each of Neurology, Neuroscience, and Psychiatry. Some journals appeared in the top 25 list of multiple fields (e.g., both Neurology and Neuroscience), so 63 journals were ultimately included in our analysis. We recognize that limiting the journals to the top 25 in each field also limits the generalizability of the results. However, there are tradeoffs between breadth of journals and depth of information. For example, by limiting the journals to these 63, we were able to look at 21 years of data (2000-2020). In addition, the definition of fields is somewhat arbitrary. By restricting the journals to a set of 63 well-known journals, we ensured that the journals belonged to Neurology, Neuroscience, or Psychiatry research. It is also important to note that the impact factor of these journals has not necessarily always been high. For example, Acta Neuropathologica had an impact factor of 17.09 in 2020 but 2.45 in 2000. To further recognize the effects of impact factor, we decided to include an impact factor term in our models.”

      In addition, we have now provided the 2020 impact factors in Table S1.

      By exclusively focusing on high impact journals, your analysis may not be representative of the broader landscape of self-citation patterns across the neuroscience literature, which is what the title of the article claims to do.

      We agree that this article is not indicative of all neuroscience literature, but rather the top journals. Thus, we have changed the title to: “Trends in Self-citation Rates in High-impact Neurology, Neuroscience, and Psychiatry Journals”. We would also like to note that compared to previous bibliometrics works in neuroscience (Bertolero et al. 2020; Dworkin et al. 2020; Fulvio et al. 2021), this article includes a wider range of data.

      (2) One other concern pertains to the possibility that a significant number of authors involved in the paper may not be neuroscientists. It is plausible that the paper is a product of interdisciplinary collaboration involving scientists from diverse disciplines. Neuroscientists amongst the authors should be identified.

      In our opinion, neuroscience is a broad, interdisciplinary field. Individuals performing neuroscience research may have a neuroscience background. Yet, they may come from many backgrounds, such as physics, mathematics, biology, chemistry, or engineering. As such, we do not believe that it is feasible to characterize whether each author considers themselves a neuroscientist or not. We have added the following to the limitations section (page 16, line 528):

      “Eighth, authors included in this work may not be neurologists, neuroscientists, or psychiatrists. However, they still publish in journals from these fields.”

      (3) When calculating self-citation rate, it is important to consider the number of papers the authors have published to date. One plausible explanation for the lower self-citation rates among first authors could be attributed to their relatively junior status and short publication record. As such, it would also be beneficial to assess self-citation rate as a percentage relative to the author's publication history. This number would be more accurate if we look at it as a percentage of their publication history. My suspicion is that first authors (who are more junior) might be more likely to self-cite than their senior counterparts. My suspicion was further raised by looking at Figures 2a and 3. Considering the nature of the self-citation metric employed in the study, it is expected that authors with a higher level of seniority would have a greater number of publications. Consequently, these senior authors' papers are more likely to be included in the pool of references cited within the paper, hence the higher rate.

      While the authors acknowledge the importance of the number of past publications in their gender analysis, it is just as important to include the interplay of seniority in (1) their first and last author self-citation rates and (2) their geographic analysis.

      Thank you for this thoughtful comment. We agree that seniority and prior publication history play an important role in self-citation rates.

      For comparing First/Last Author self-citation rates, we have now included a plot similar to Figure 2a, where self-citation as a percentage of prior publication history is plotted.

      (page 4, line 161): “Analyzing self-citations as a fraction of publication history exhibited a similar trend (Figure S3). Notably, First Authors were more likely than Last Authors to self-cite when normalized by prior publication history.

      For the geographic analysis, we made two new maps: 1) that of the number of previous papers, and 2) that of the journal impact factor (see response to point #4 below).

      (page 5, line 185): “We also investigated the distribution of the number of previous papers and journal impact factor across countries (Figure S4). Self-citation maps by country were highly correlated with maps of the number of previous papers (Spearman’s r\=0.576, P=4.1e-4; 0.654, P=1.8e-5 for First and Last Authors). They were significantly correlated with maps of average impact factor for Last Authors (0.428, P=0.014) but not Last Authors (Spearman’s r\=0.157, P=0.424). Thus, further investigation is necessary with these covariates in a comprehensive model.”

      Finally, we included a model term for the number of previous papers (Table 2). We analyzed this both for self-citation counts and self-citation rates and found a strong relationship between publication history and self-citations. We also included the following section where we modeled the number of previous papers for each author (page 13, line 384):

      “2.10 Reconciling differences between raw data and models

      The raw and GAM-derived data exhibited some conflicting results, such as for gender and field of research. To further study covariates associated with this discrepancy, we modeled the publication history for each author (at the time of publication) in our dataset (Table 2). The model terms included academic age, article year, journal impact factor, field, LMIC status, gender, and document type. Notably, Neuroscience was associated with the fewest number of papers per author. This explains how authors in Neuroscience could have the lowest raw self-citation rates but the highest self-citation rates after including covariates in a model. In addition, being a man was associated with about 0.25 more papers. Thus, gender differences in self-citation likely emerged from differences in the number of papers, not in any self-citation practices.”

      (4) Because your analysis is limited to high impact journals, it would be beneficial to see the distribution of the impact factors across the different countries. Otherwise, your analysis on geographic differences in self-citation rates is hard to interpret. Are these differences really differences in self-citation rates, or differences in journal impact factor? It would be useful to look at the representation of authors from different countries for different impact factors.

      We made a map of this in Figure S4 (see our response to point #3 above).

      (page 5, line 185): “We also investigated the distribution of the number of previous papers and journal impact factor across countries (Figure S4). Self-citation maps by country were highly correlated with maps of the number of previous papers (Spearman’s r=0.576, P=4.1e-4; 0.654, P=1.8e-5 for First and Last Authors). They were significantly correlated with maps of average impact factor for Last Authors (0.428, P=0.014) but not Last Authors (Spearman’s r=0.157, P=0.424). Thus, further investigation is necessary with these covariates in a comprehensive model.”

      We also included impact factor as a term in our model. The results suggest that there are still geographic differences (Table 2, Table S5).

      (5) The presence of self-citations is not inherently problematic, and I appreciate the fact that authors omit any explicit judgment on this matter. That said, without appropriate context, self-citations are also not the best scholarly practice. In the analysis on gender differences in self-citations, it appears that authors imply an expectation of women's self-citation rates to align with those of men. While this is not explicitly stated, use of the word "disparity", and also presentation of self-citation as an example of self-promotion in discussion suggest such a perspective. Without knowing the context in which the self-citation was made, it is hard to ascertain whether women are less inclined to self-promote or that men are more inclined to engage in strategic self-citation practices.

      We agree that on the level of an individual self-citation, our study is not useful for determining how related the papers are. Yet, understanding overall trends in self-citation may help to identify differences. Context is important, but large datasets allow us to investigate broad trends. We added the following text to the limitations section (page 16, line 524):

      “In addition, these models do not account for whether a specific citation is appropriate, as some situations may necessitate higher self-citation rates.”

      Reviewer #3 (Public Review):

      This paper analyses self-citation rates in the field of Neuroscience, comprising in this case, Neurology, Neuroscience and Psychiatry. Based on data from Scopus, the authors identify self-citations, that is, whether references from a paper by some authors cite work that is written by one of the same authors. They separately analyse this in terms of first-author self-citations and last-author self-citations. The analysis is well-executed and the analysis and results are written down clearly. There are some minor methodological clarifications needed, but more importantly, the interpretation of some of the results might prove more challenging. That is, it is not always clear what is being estimated, and more importantly, the extent to which self-citations are "problematic" remains unclear.

      Thank you for your review. We attempted to improve the interpretation of results, as described in the following responses.

      When are self-citations problematic? As the authors themselves also clarify, "self-citations may often be appropriate". Researchers cite their own previous work for perfectly good reasons, similar to reasons of why they would cite work by others. The "problem", in a sense, is that researchers cite their own work, just to increase the citation count, or to promote their own work and make it more visible. This self-promotional behaviour might be incentivised by certain research evaluation procedures (e.g. hiring, promoting) that overly emphasise citation performance. However, the true problem then might not be (self-)citation practices, but instead, the flawed research evaluation procedures that emphasis citation performance too much. So instead of problematising self-citation behaviour, and trying to address it, we might do better to address flawed research evaluation procedures. Of course, we should expect references to be relevant, and we should avoid self-promotional references, but addressing self-citations may just have minimal effects, and would not solve the more fundamental issue.

      We agree that this dataset is not designed to investigate the downstream effects of self-citations. However, self-citation practices are more likely to be problematic when they differ across specific groups. This work can potentially spark more interest in future longitudinal designs to investigate whether differences in self-citation practices leads to differences in career outcomes, for example. We added the following text to clarify (page 17, line 565):

      “Yet, self-citation practices become problematic when they are different across groups or are used to “game the system.” Future work should investigate the downstream effects of self-citation differences to see whether they impact the career trajectories of certain groups. We hope that this work will help to raise awareness about factors influencing self-citation practices to better inform authors, editors, funding agencies, and institutions in Neurology, Neuroscience, and Psychiatry.”

      Some other challenges arise when taking a statistical perspective. For any given paper, we could browse through the references, and determine whether a particular reference would be warranted or not. For instance, we could note that there might be a reference included that is not at all relevant to the paper. Taking a broader perspective, the irrelevant reference might point to work by others, included just for reasons of prestige, so-called perfunctory citations. But it could of course also include self-citations. When we simply start counting all self-citations, we do not see what fraction of those self-citations would be warranted as references. The question then emerges, what level of self-citations should be counted as "high"? How should we determine that? If we observe differences in self-citation rates, what does it tell us?

      Our focus is when the self-citation practices differ across groups. We agree that, on a case-by-case basis, there is no exact number for a self-citation rate that is “high.” With a dataset of the current size, evaluating whether each individual self-citation is appropriate is not feasible. If we observe differences in self-citation rate, this may tell us about broad (not individual-level) trends and differences in self-citing practice. If one group is self-citing much more highly compared to another group–even after covarying relevant variables such as prior publication history–then the self-citation differences can likely be attributed to differences in self-citation practices/behaviors.

      For example, the authors find that the (any author) self-citation rate in Neuroscience is 10.7% versus 15.9% in Psychiatry. What does this difference mean? Are psychiatrists citing themselves more often than neuroscientists? First author men showed a self-citation rate of 5.12% versus a self-citation rate of 3.34% of women first authors. Do men engage in more problematic citation behaviour? Junior researchers (10-year career) show a self-citation rate of about 5% compared to a self-citation rate of about 10% for senior researchers (30-year career). Are senior researchers therefore engaging in more problematic citation behaviour? The answer is (most likely) "no", because senior authors have simply published more, and will therefore have more opportunities to refer to their own work. To be clear: the authors are aware of this, and also take this into account. In fact, these "raw" various self-citation rates may, as the authors themselves say, "give the illusion" of self-citation rates, but these are somehow "hidden" by, for instance, career seniority.

      We included numerous covariates in our model. In addition, to address the difference between “raw” and “modeled” self-citation rates, we added the following section (page 13, line 384):

      “2.10 Reconciling differences between raw data and models

      The raw and GAM-derived data exhibited some conflicting results, such as for gender and field of research. To further study covariates associated with this discrepancy, we modeled the publication history for each author (at the time of publication) in our dataset (Table 2). The model terms included academic age, article year, journal impact factor, field, LMIC status, gender, and document type. Notably, Neuroscience was associated with the fewest number of papers per author. This explains how authors in Neuroscience could have the lowest raw self-citation rates but the highest self-citation rates after including covariates in a model. In addition, being a man was associated with about 0.25 more papers. Thus, gender differences in self-citation likely emerged from differences in the number of papers, not in any self-citation practices.”

      Again, the authors do consider this, and "control" for career length and number of publications, et cetera, in their regression model. Some of the previous observations then change in the regression model. Neuroscience doesn't seem to be self-citing more, there just seem to be junior researchers in that field compared to Psychiatry. Similarly, men and women don't seem to show an overall different self-citation behaviour (although the authors find an early-career difference), the men included in the study simply have longer careers and more publications.

      But here's the key issue: what does it then mean to "control" for some variables? This doesn't make any sense, except in the light of causality. That is, we should control for some variable, such as seniority, because we are interested in some causal effect. The field may not "cause" the observed differences in self-citation behaviour, this is mediated by seniority. Or is it confounded by seniority? Are the overall gender differences also mediated by seniority? How would the selection of high-impact journals "bias" estimates of causal effects on self-citation? Can we interpret the coefficients as causal effects of that variable on self-citations? If so, would we try to interpret this as total causal effects, or direct causal effects? If they do not represent causal effects, how should they be interpreted then? In particular, how should it "inform author, editors, funding agencies and institutions", as the authors say? What should they be informed about?

      We apologize for our misuse of language. We will be more clear, as in most previous self-citation papers, that our analysis is NOT causal. Causal datasets do have some benefits in citation research, but a limitation is that they may not cover as wide of a range of authors. Furthermore, non-causal correlational studies can still be useful in informing authors, editors, funding agencies, and institutions. Association studies are widely used across various fields to draw non-causal conclusions. We made numerous changes to reduce our causal language.

      Before: “We then developed a probability model of self-citation that controls for numerous covariates, which allowed us to obtain significance estimates for each variable of interest.”

      After (page 3, line 113): “We then developed a probability model of self-citation that includes numerous covariates, which allowed us to obtain significance estimates for each variable of interest.”

      Before: “As such, controlling for various author- and article-level characteristics can improve the interpretability of self-citation rate trends.”

      After (page 11, line 321): “As such, covarying various author- and article-level characteristics can improve the interpretability of self-citation rate trends.”

      Before: “Initially, it appeared that self-citation rates in Neuroscience are lower than Neurology and Psychiatry, but after controlling for various confounds, the self-citation rates are higher in Neuroscience.”

      After (page 15, line 468): “Initially, it appeared that self-citation rates in Neuroscience are lower than Neurology and Psychiatry, but after considering several covariates, the self-citation rates are higher in Neuroscience.”

      We also added the following text to the limitations section (page 16, line 526):

      “Seventh, the analysis presented in this work is not causal. Association studies are advantageous for increasing sample size, but future work could investigate causality in curated datasets.”

      The authors also "encourage authors to explore their trends in self-citation rates". It is laudable to be self-critical and review ones own practices. But how should authors interpret their self-citation rate? How useful is it to know whether it is 5%, 10% or 15%? What would be the "reasonable" self-citation rate? How should we go about constructing such a benchmark rate? Again, this would necessitate some causal answer. Instead of looking at the self-citation rate, it would presumably be much more informative to simply ask authors to check whether references are appropriate and relevant to the topic at hand.

      We believe that our tool is valuable for authors to contextualize their own self-citation rates. For instance, if an author has published hundreds of articles, it is not practical to count the number of self-citations in each. We have added two portions of text to the limitations section:

      (page 16, line 524): “In addition, these models do not account for whether a specific citation is appropriate, though some situations may necessitate higher self-citation rates.”

      (page 16, line 535): “Despite these limitations, we found significant differences in self-citation rates for various groups, and thus we encourage authors to explore their trends in self-citation rates. Self-citation rates that are higher than average are not necessarily wrong, but suggest that authors should further reflect on their current self-citation practices.”

      In conclusion, the study shows some interesting and relevant differences in self-citation rates. As such, it is a welcome contribution to ongoing discussions of (self) citations. However, without a clear causal framework, it is challenging to interpret the observed differences.

      We agree that causal studies provide many benefits. Yet, association studies also provide many benefits. For example, an association study allowed us to analyze a wider range of articles than a causal study would have.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Statistical suggestions:

      (1) To improve statistical inference, nesting should be accounted for in all of the analyses. For example, the logistic regression model using citing/cited pairs should include random effects for article, author, and perhaps subfield, in order for independence of observations to be plausible. Similarly, bootstrapping and permutation would ideally occur at the author level rather than (or in addition to) the paper level.

      Detailed updates addressing these points are in the public review. In short, we found computational challenges with many levels of the random effects (>100,000) and millions of observations at the citation pairs level. As such, we decided to model citations rates and counts by paper. In this case, we found that results could be unstable when including author-level random effects because in many cases there was only one author per group. Instead, to avoid inappropriately narrow confidence bands, we resampled the dataset such that each author was only represented once. For example, if Author A had five papers in this dataset, then one of their five papers was randomly selected. We repeated the random resampling 100 times (Figure S12). We updated our description of our models in the Methods section (page 21, line 754).

      For permutation tests and bootstrapping, we now define an “exchangeability block” as a co-authorship group of authors. In this dataset, that meant any authors who published together (among the articles in this dataset) as a First Author / Last Author pairing were assigned to the same exchangeability block. It is not realistic to check for overlapping middle authors in all papers because of the collaborative nature of the field. In addition, we believe that self-citations are primarily controlled by first and last authors, so we can assume that middle authors do not control self-citation habits. We then performed bootstrapping and permutation tests in the constraints of the exchangeability blocks.

      (2) In general, I am having trouble understanding the structure of the regression models. My current belief is that rows are composed of individual citations from papers' reference lists, with the outcome representing their status as a self-citation or not, and with various citing article and citing author characteristics as predictors. However, the fact that author type is included in the model as a predictor (rather than having a model for FA self-citations and another for LA self-citations) suggests to me that each citation is entered as two separate rows - once noting whether it was a FA self-citation and once noting whether it was an LA self-citation - and then it is run as a single model.

      (2a) If I am correct, the model is unlikely to be producing valid inference. I would recommend breaking this analysis up into two separate models, and including article-, author-, and subfield-level random effects. You could theoretically include a citation-level random effect and keep it as one model, but each 'group' would only have two observations and the model would be fairly unstable as a result.

      (2b) If I am misunderstanding (and even if not), I would encourage you to provide a more detailed description of the dataset structure and the model - perhaps with a table or diagram

      We split the data into two models and decided to model on the level of a paper (self-citation rate and self-citation count). In addition, we subsampled the dataset such that each author only appears once to avoid misestimation of confidence intervals (see point (1) above). As described in the public review, we included much more detail in our methods section now to improve the clarity of our models.

      (3) I would suggest removing the inverse hyperbolic sine transform and replacing it with a more flexible approach to estimating the relationships' shape, like generalized additive models or other spline-based methods to ensure that the chosen method is appropriate - or at the very least checking that it is producing a realistic fit that reflects the underlying shape of the relationships.

      More details are available in the public review, but we now use GAMs throughout the manuscript.

      (4) For the "highly self-citing" analysis, it is unclear why papers in the 15-25% range were dropped rather than including them as their own category in an ordinal model. I might suggest doing the latter, or explaining the decision more fully

      We previously included this analysis as a paper-level model because our main model was at the level of citation pairs. Now, we removed this analysis because we model self-citation rates and counts by paper.

      (5) It would be beneficial for the reader to know what % of the data was dropped for each analysis, and for your team to make sure that there is not differential missing data that could affect the interpretation of the results (e.g., differences in self-citation being due to differences in Scopus ID coverage).

      Thank you for this suggestion. We added more detailed missingness data to 4.3 Data exclusions and missingness. We did find differential missingness and added it to the limitations section. However, certain aspects of this cannot be corrected because the data are just not available (e.g., Scopus coverage issues). Further details are available in the public review.

      Conceptual thoughts:

      (1) I agree with your decision to focus on the second definition of self-citation (self-cites relative to my citations to others' work) rather than the first (self-cites relative to others' citations to my work). But it does seem that the first definition is relevant in the context of gaming citation metrics. For example, someone who writes one paper per year with a reference list of 30% self-citations will have much less of an impact on their H-index than someone who writes 10 papers per year with 10% self-citations. It could be interesting to see how these definitions interact, and whether people who are high on one measure tend to be high on the other.

      We agree this would be interesting to investigate in the future. Unfortunately, our dataset is organized at the level of the paper and thus does not contain information regarding how many times the authors cite a particular work. We hope that we can explore this interaction in the future.

      (2) This is entirely speculative, but I wonder whether the increasing rate of LA self-citation relative to FA self-citation is partly due to PIs over-citing their own lab to build up their trainees' citation records and help them succeed in an increasingly competitive job market. This sounds more innocuous than doing it to benefit their own reputation, but it would provide another mechanism through which students from large and well-funded labs get a leg-up in the job market. Might be interesting to explore, though I'm not exactly sure how :)

      This is a very interesting point. We do not have any means to investigate this with the current dataset, but we added it to the discussion (page 14, line 421):

      “A third, more optimistic explanation is that principal investigators (typically Last Authors) are increasingly self-citing their lab’s papers to build up their trainee’s citation records for an increasingly competitive job market.”

      Reviewer #2 (Recommendations For The Authors):

      (1) In regards to point 1 in the public review: In the spirit of transparency, the authors would benefit from providing a rationale for their choice of top journals, and the methodology used to identify them. It would also be valuable to include the impact factor of each journal in the S1 table alongside their names.

      Given the availability and executability of code, it would be useful to see how and if the self-citation trends vary amongst the "low impact" journals (as measured by the IF). This could go in any of the three directions:

      a. If it is found that self-citations are not as prevalent in low impact journals, this could be a great starting point for a conversation around the evaluation of journals based on impact factor, and the role of self-citations in it.

      b. If it is found that self-citations are as prevalent in low impact journals as high impact journals, that just strengthens your results further.

      c. If it is found that self-citations are more prevalent in low impact journals, this would mean your current statistics are a lower bound to the actual problem. This is also intuitive in the sense that high impact journals get more external citations (and more exposure) than low impact journals, as such authors (and journals) may be less likely to self-cite.

      Expanding the dataset to include many more journals was not feasible. Instead, we included an impact factor term in our models, as detailed in the public review. We found no strong trends in the association between impact factor and self-citation rate/count. Another important note is that these journals were considered “high impact” in 2020, but many had lower impact factors in earlier years. Thus, our modeling allows us to estimate how impact factor is related to self-citations across a wide range of impact factors.

      It is crucial to consider utilizing such a comprehensive database as Scopus, which provides a more thorough list of all journals in Neuroscience, to obtain a more representative sample. Alternatively, other datasets like Microsoft Academic Graph, and OpenAlex offer information on the field of science associated with each paper, enabling a more comprehensive analysis.

      We agree that certain datasets may offer a wider view of the entire field. However, we included a large number of papers and journals relative to previous studies. In addition, Scopus provides a lot of detailed and valuable author-level information. We had to limit our calls to the Scopus API so restricted journals by 2020 impact factor.

      (2) In regards to point 2 in the public review: To enhance the accuracy and specificity of the analysis, it would be beneficial to distinguish neuroscientists among the co-authors. This could be accomplished by examining their publication history leading up to the time of publication of the paper, and identify each author's level of engagement and specialization within the field of neuroscience.

      Since the field of neuroscience is largely based on collaborations, we find that it might be impossible to determine who is a neuroscientist. For example, a researcher with a publication history in physics may now be focusing on computational neuroscience research. As such, we feel that our current work, which ensures that the papers belong to neuroscience, is representative of what one may expect in terms of neuroscience research and collaboration.

      (3) In regards to point 3 in the public review: I highly recommend plotting self-citation rate as the number of papers in the reference list over the number of total publications to date of paper publication.

      As described in the public review, we have now done this (Figure S3).

      (4) In regards to point 5 in the public review: It would be useful to consider the "quality" of citations to further the discussion on self-citations. For instance, differentiating between self-citations that are perfunctory and superficial from those that are essential for showing developmental work, would be a valuable contribution.

      Other databases may have access to this information, but ours unfortunately does not. We agree that this is an interesting area of work.

      (5) The authors are to be commended for their logistic regression models, as they control for many confounders that were lacking in their earlier descriptive statistics. However, it would be beneficial to rerun the same analysis but on a linear model whereby the outcome variable would be the number of self-citations per author. This would possibly resolve many of the comments mentioned above.

      Thank you for your suggestion. As detailed in the public review, we now model the number of self-citations. This is modeled on the paper level, not the author level, because our dataset was downloaded by paper, not by author.

      Minor suggestions:

      (1) Abstract says one of your findings is: "increasing self-citation rates of First Authors relative to Last Authors". Your results actually show the opposite (see Figure 1b).

      Thank you for catching this error. We corrected it to match the results and discussion in the paper:

      “…increasing self-citation rates of Last Authors relative to First Authors.”

      (2) It might be interesting to compute an average academic age for each paper, and look at self-citation vs average academic age plot.

      We agree that this would be an interesting analysis. However, to limit calls to the API, we collected academic age data only on First and Last Authors.

      (3) It may be interesting to look at the distribution of women in different subfields within neuroscience, and the interaction of those in the context of self-citations.

      Thank you for this interesting suggestion. We added the following analysis (page 9, line 305):

      “Furthermore, we explored topic-by-gender interactions (Figure S10). In short, men and women were relatively equally represented as First Authors, but more men were Last Authors across all topics. Self-citation rates were higher for men across all topics.”

      Reviewer #3 (Recommendations For The Authors):

      - In the abstract, "flaws in citation practices" seems worded rather strongly.

      We respectfully disagree, as previous works have shown significant bias in citation practices. For example, Dworkin et al. (Dworkin et al. 2020) found that neuroscience reference lists tended to under-cite women, even after including various covariates.

      - Links of the references to point to (non-accessible) paperpile references, you would probably want to update this.

      We apologize for the inconvenience and have now removed these links.

      - p 2, l 24: The explanation of ref. (5) seems to be a bit strangely formulated. The point of that article is that citations to work that reinforce a particular belief are more likely to be cited, which *creates* unfounded authority. The unfounded authority itself is hence no part of the citation practices

      Thank you for catching our misinterpretation. We have now removed this part of the sentence.

      - p 3, l 16: "h indices" or "citations" instead of "h-index".

      We now say “h-indices”.

      - p 5, l 5: how was the manual scoring done?

      We added the following to the caption of Figure S1.

      “Figure S1. Comparison between manual scoring of self-citation rates and self-citation rates estimated from Python scripts in 5 Psychiatry journals: American Journal of Psychiatry, Biological Psychiatry, JAMA Psychiatry, Lancet Psychiatry, and Molecular Psychiatry. 906 articles in total were manually evaluated (10 articles per journal per year from 2000-2020, four articles excluded for very large author list lengths and thus high difficulty of manual scoring). For manual scoring, we downloaded information about all references for a given article and searched for matching author names.”

      - p 5, l 23: Why this specific p-value upper bound of 4e-3? From later in the article, I understand that this stems from the 10000 bootstrap sample, with then taking a Bonferroni correction? Perhaps good to clarify this briefly somewhere.

      Thank you for this suggestion. We now perform Benjamini/Hochberg false discovery rate (FDR) correction, but we added a description of the minimum P value from permutations (page 21, line 748):

      “All P values described in the main text were corrected with the Benjamini/Hochberg 16 false discovery rate (FDR) correction. With 10,000 permutations, the lowest P value after applying FDR correction is P=2.9e-4, which indicates that the true point would be the most extreme in the simulated null distribution.”

      - Fig. 1, caption: The (a) and (b) labelling here is a bit confusing, because the first sentence suggests both figures portray the same, but do so for different time periods. Perhaps rewrite, so that (a) and (b) are both described in a single sentence, instead of having two different references to (a) and (b).

      Thank you for pointing this out. We fixed the labeling of this caption:

      “Figure 1. Visualizing recent self-citation rates and temporal trends. a) Kernel density estimate of the distribution of First Author, Last Author, and Any Author self-citation rates in the last five years. b) Average self-citation rates over every year since 2000, with 95% confidence intervals calculated by bootstrap resampling.”

      - p7, l 9: Regarding "academic age", note that there might be a difference between "age" effects and "cohort" effects. That is, there might be difference between people with a certain career age who started in 1990 and people with the same career age, but who started in 2000, which would be a "cohort" effect.

      We agree that this is a possible effect and have added it to the limitations (page 16, line 532):

      “Tenth, while we considered academic age, we did not consider cohort effects. Cohort effects would depend on the year in which the individual started their career.”

      - p 7, l 15: "jumps" suggests some sort of sudden or discontinuous transition, I would just say "increases".

      We now say “increases.”

      - Fig. 2: Perhaps it should be made more explicit that this includes only academics with at least 50 papers. Could the authors please clarify whether the same limitation of at least 50 papers also features in other parts of the analysis where academic age is used? This selection could affect the outcomes of the analysis, so its consequences should be carefully considered. One possibility for instance is that it selects people with a short career length who have been exceptionally productive, namely those that have had 50 papers, but only started publishing in 2015 or so. Such exceptionally productive people will feature more highly in the early career part, because they need to be so productive in order to make the cut. For people with a longer career, the 50 papers would be less of a hurdle, and so would select more and less productive people more equally.

      We apologize for the lack of clarity. We did not use this requirement where academic age was used. We mainly applied this requirement when aggregating by country, as we did not want to calculate self-citation rate in a country based on only several papers. We have clarified various data exclusions in our new section 4.3 Data exclusions and missingness.

      - p 8, l 11: The affiliated institution of an author is not static, but rather changes throughout time. Did the authors consider this? If not, please clarify that this refers to only the most recent affiliation (presumably). Authors also often have multiple affiliations. How did the authors deal with this?

      The institution information is at the time of publication for each paper. We added more detail to our description of this on page 19, line 656:

      “For both First and Last Authors, we found the country of their institutional affiliation listed on the publication. In the case of multiple affiliations, the first one listed in Scopus was used.”

      - p 10, l 6: How were these self-citation rates calculated? This is averaged per author (i.e. only considering papers assigned to a particular topic) and then averaged across authors? (Note that in this way, the average of an author with many papers will weigh equally with the average of an author with few papers, which might skew some of the results).

      We calculate it across the entire topic (i.e., do NOT calculate by author first). We updated the description as follows (page 7, line 211):

      “We then computed self-citation rates for each of these topics (Figure 4) as the total number of self-citations in each topic divided by the total number of references in each topic…”

      - p 13, l 18: Is the academic age analysis here again limited to authors having at least 50 papers?

      This is not limited to at least 50 papers. To clarify, the previous analysis was not limited to authors with 50 papers. It was instead limited to ages in our dataset that had at least 50 data points. e.g., If an academic age of 70 only had 20 data points in our dataset, it would have been excluded.

      - Fig. 5: Here, comparing Fig. 5(d) and 5(f) suggests that partly, the self-citation rate differences between men and women, might be the result of the differences in number of papers. That is, the somewhat higher self-citation rate at a given academic age, might be the result of the higher number of papers at that academic age. It seems that this is not directly described in this part of the analysis (although this seems to be the case from the later regression analysis).

      We agree with this idea and have added a new section as follows (page 13, line 384):

      “2.10 Reconciling differences between raw data and models

      The raw and GAM-derived data exhibited some conflicting results, such as for gender and field of research. To further study covariates associated with this discrepancy, we modeled the publication history for each author (at the time of publication) in our dataset (Table 2). The model terms included academic age, article year, journal impact factor, field, LMIC status, gender, and document type. Notably, Neuroscience was associated with the fewest number of papers per author. This explains how authors in Neuroscience could have the lowest raw self-citation rates by highest self-citation rates after including covariates in a model. In addition, being a man was associated with about 0.25 more papers. Thus, gender differences in self-citation likely emerged from differences in the number of papers, not in any self-citation practices.”

      - Section 2.10. Perhaps the authors could clarify that this analysis takes individual articles as the unit of analysis, not citations.

      We updated all our models to take individual articles and have clarified this with more detailed tables.

      - p 18, l 10: "Articles with between 15-25% self-citation rates were 10 discarded" Why?

      We agree that these should not be discarded. However, we previously included this analysis as a paper-level model because our main model was at the level of citation pairs. Now, we removed this analysis because we model self-citation rates and counts by paper.

      - p 20, l 5: "Thus, early-career researchers may be less incentivized to 5 self-promote (e.g., self-cite) for academic gains compared to 20 years ago." How about the possibility that there was less collaboration, so that first authors would be more likely to cite their own paper, whereas with more collaboration, they will more often not feature as first author?

      This is an interesting point. We feel that more collaboration would generally lead to even more self-citations, if anything. If an author collaborates more, they are more likely to be on some of the references as a middle author (which by our definition counts toward self-citation rates).

      - p 20, l 15: Here the authors call authors to avoid excessive self-citations. Of course, there's nothing wrong with calling for that, but earlier the authors were more careful to not label something directly as excessive self-citations. Here, by stating it like this, the authors suggest that they have looked at excessive self-citations.

      We rephrased this as follows:

      Before: “For example, an author with 30 years of experience cites themselves approximately twice as much as one with 10 years of experience on average. Both authors have plenty of works that they can cite, and likely only a few are necessary. As such, we encourage authors to be cognizant of their citations and to avoid excessive self-citations.”

      After: “For example, an author with 30 years of experience cites themselves approximately twice as much as one with 10 years of experience on average. Both authors have plenty of works that they can cite, and likely only a few are necessary. As such, we encourage authors to be cognizant of their citations and to avoid unnecessary self-citations.”

      - p 22, l 11: Here again, the same critique as p 20, l15 applies.

      We switched “excessively” to “unnecessarily.”

      - p 23, l 12: The authors here critique ref. (21) of ascertainment bias, namely that they are "including only highly-achieving researchers in the life 12 sciences". But do the authors not do exactly the same thing? That is, they also only focus on the top high-impact journals.

      We included 63 high-impact journals with tens of thousands of authors. In addition, some of these journals were not high-impact at the time of publication. For example, Acta Neuropathologica had an impact factor of 17.09 in 2020 but 2.45 in 2000. This still is a limitation of our work, but we do cover a much broader range of works than the listed reference (though their analysis also has many benefits since it included more detailed information).

      - p 26, l 22-26: It seems that the matching is done quite broadly (matching last names + initials at worst) for self-citations, while later (in section 4.9, p 31, l 9), the authors switch to only matching exact Scopus Author IDs. Why not use the same approach throughout? Or compare the two definitions (narrow / broad).

      Thank you for catching this mistake. We now use the approach of matching Scopus Author IDs throughout.

      - S8: it might be nice to explore open alternatives, such as OpenAlex or OpenAIRE, instead of the closed Scopus database, which requires paid access (which not all institutions have, perhaps that could also be corrected in the description in GitHub).

      Thank you for this suggestion. Unfortunately, switching databases would require starting our analysis from the beginning. On our GitHub page, we state: “Please email matthew.rosenblatt@yale.edu if you have trouble running this or do not have institutional access. We can help you run the code and/or run it for you and share your self-citation trends.” We feel that this will allow us to help researchers who may not have institutional access. In addition, we released our aggregated, de-identified (title and paper information removed) data on GitHub for other researchers to use.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Dong et al. study the directed cell migration of tracheal stem cells in Drosophila pupae. The migration of these cells which are found in two nearby groups of cells normally happens unidirectionally along the dorsal trunk towards the posterior. Here, the authors study how this directionality is regulated. They show that inter-organ communication between the tracheal stem cells and the nearby fat body plays a role. They provide compelling evidence that Upd2 production in the fat body and JAK/STAT activation in the tracheal stem cells play a role. Moreover, they show that JAK/STAT signalling might induce the expression of apicobasal and planar cell polarity genes in the tracheal stem cells which appear to be needed to ensure unidirectional migration. Finally, the authors suggest that trafficking and vesicular transport of Upd2 from the fat body towards the tracheal cells might be important.

      Strengths:

      The manuscript is well written. This novel work demonstrates a likely link between Upd2-JAK/STAT signalling in the fat body and tracheal stem cells and the control of unidirectional cell migration of tracheal stem cells. The authors show that hid+rpr or Upd2RNAi expression in a fat body or Dome RNAi, Hop RNAi, or STAT92E RNAi expression in tracheal stem cells results in aberrant migration of some of the tracheal stem cells towards the anterior. Using ChIP-seq as well as analysis of GFP-protein trap lines of planar cell polarity genes in combination with RNAi experiments, the authors show that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells which appear to be needed for unidirectional migration. Moreover, the authors hypothesise that extracellular vesicle transport of Upd2 might be involved in this Upd2-JAK/STAT signalling in the fat body and tracheal stem cells, which, if true, would be quite interesting and novel.

      Overall, the work presented here provides some novel insights into the mechanism that ensures unidirectional migration of tracheal stem cells that prevents bidirectional migration. This might have important implications for other types of directed cell migration in invertebrates or vertebrates including cancer cell migration.

      Weaknesses:

      It remains unclear to what extent Upd2-JAK/STAT signalling regulates unidirectional migration. While there seems to be a consistent phenotype upon genetic manipulation of Upd2-JAK/STAT signalling and planar cell polarity genes, as in the aberrant anterior migration of a fraction of the cells, the phenotype seems to be rather mild, with the majority of cells migrating towards the posterior.

      While I am not an expert on extracellular vesicle transport, the data presented here regarding Upd2 being transported in extracellular vesicles do not appear to be very convincing.

      Major comments:

      (1) The graphs showing the quantification of anterior (and in some cases also posterior migration) are quite confusing. E.g. Figure 1F (and 5E and all others): These graphs are difficult to read because the quantification for the different conditions is not shown separately. E.g. what is the migration distance for Fj RNAi anterior at 3h in Fig5E? Around -205micron (green plus all the other colors) or around -70micron (just green, even though the green bar goes to -205micron). If it's -205micron, then the images in C' or D' do not seem to show this strong phenotype. If it's around -70, then the way the graph shows it is misleading, because some readers will interpret the result as -205.

      Moreover, it's also not clear what exactly was quantified and how it was quantified. The details are also not described in the methods. It would be useful, to mark with two arrowheads in the image (e.g. 5 A' -D') where the migration distance is measured (anterior margin and point zero).

      Overall, it would be better, if the graph showed the different conditions separately. Also, n numbers should be shown in the figure legend for all graphs.

      (2) Figure 2-figure supplement 1: C-L and M: From these images and graph it appears that Upd2 RNAi results in no aberrant anterior migration. Why is this result different from Figures 2D-F where it does?

      (3) Figure 5F: The data on the localisation of planar cell polarity proteins in the tracheal stem cell group is rather weak. Figure 5G and J should at least be quantified for several animals of the same age for each genotype. Is there overall more Ft-GFP in the cells on the posterior end of the cell group than on the opposite side? Or is there a more classic planar cell polarity in each cell with Ft-GFP facing to the posterior side of the cell in each cell? Maybe it would be more convincing if the authors assessed what the subcellular localisation of Ft is through the expression of Ft-GFP in clones to figure out whether it localises posteriorly or anteriorly in individual cells.

      (4) Regarding the trafficking of Upd2 in the fat body, is it known, whether Grasp65, Lbm, Rab5, and 7 are specifically needed for extracellular vesicle trafficking rather than general intracellular trafficking? What is the evidence for this?

      (5) Figure 8A-B: The data on the proximity of Rab5 and 7 to the Upd2 blobs are not very convincing.

      (6) The authors should clarify whether or not their work has shown that "vesicle-mediated transport of ligands is essential for JAK/STAT signaling". In its current form, this manuscript does not appear to provide enough evidence for extracellular vesicle transport of Upd2.

      (7) What is the long-term effect of the various genetic manipulations on migration? The authors don't show what the phenotype at later time points would be, regarding the longer-term migration behaviour (e.g. at 10h APF when the cells should normally reach the posterior end of the pupa). And what is the overall effect of the aberrant bidirectional migration phenotype on tracheal remodelling?

      (8) The RNAi experiments in this manuscript are generally done using a single RNAi line. To rule out off-target effects, it would be important to use two non-overlapping RNAi lines for each gene.

    1. Looking for a keyboarded writing device without harsh screen lights...

      Since you're asking in r/typewriters, here's a list of what some well known playwrights, screenwriters, and directors used and would likely have recommended for writing tools without harsh screens. Personally I'm in Tom Hank's camp and would recommend a Smith-Corona Clipper.

      • Edward Albee: Remington 17 or KMC
      • Ray Bradbury: Underwood (no. 5?), 1947 Royal KMM #3756210, IBM Selectric, IBM Wheelwriter, Silver-Seiko ultraportable (likely branded as Royal)
      • Bertolt Brecht: Erika
      • Mikhail Bulgakov: Olympia 8 (photo from Bulgakov museum)
      • Paddy Chayefsky (playwright, May 1954): Underwood Standard Model 6, ca. 1946; Royal HH; Olympia SG3
      • William Goldman: Olympia SM9
      • Matt Groening: Hermes Rocket
      • Alfred Hitchcock: '30s black Underwood Champion portable
      • Sidney Howard (screenwriter, Gone With the Wind): Remington Noiseless Portable #N49669
      • John Hughes (director): Olympia SM3
      • Buster Keaton: Blickensderfer no. 5
      • Stanley Kubrick: Adler Tippa S
      • Ring Lardner: L. C. Smith
      • Ernest Lehman: Royal Electress
      • David Mamet: Smith-Corona portable, Olympia SM4, Olympia SM9, IBM Selectric
      • Arthur Miller bought a used Smith-Corona portable in the late '30s (for one anonymous contest, he submitted a play that he said was "by Corona."). Later he used a '50s Smith-Corona Silent Super and a Royal KMG (1955 photo, another photo). He wrote his later plays on an IBM desktop computer. (Arthur Miller: His Life and Work, by Martin Gottfried, p. 26, 112, and 381.)
      • F. W. Murnau: Remington portable no. 2 (1931 photo)
      • Clifford Odets (1962): Royal Quiet DeLuxe, ca. 1957
      • Rod Serling: Royal KMG (photo 1, photo 2)
      • Neil Simon: Olympia SM9
      • Steven Spielberg: Smith-Corona Coronamatic 2200 (photo 1, photo 2)
      • James Thurber: Underwood no. 5
      • John Waters: ca. 1950 Underwood (1961 photo), IBM A or B
      • Orson Welles: 1926 woodgrain Underwood portable #4B73700 (Welles typing on it), ’30s Underwood Noiseless Portable, Smith-Corona (?)
      • Tennessee Williams: Remington portable no. 2, 1936 Corona Junior #1F9874J (formerly in Steve Soboroff's collection), mid-1940s Corona Sterling, Royal KMM, Hermes Baby (gift from Margo Jones, 1947, according to John Lahr, Tennessee Williams: Mad Pilgrimage of the Flesh, Bloomsbury, 2014), Olivetti Studio 44 (picture 1, picture 2, picture 3, picture 4 1955), Remington portable #5 flat top, Remington Standard M, Olympia SM8. (This man loved to have himself photographed with his writing machines!)

      If you need some other recommendations from novelists and others, you could try: https://site.xavier.edu/polt/typewriters/typers.html

      If you like Scrivener, but want to get away from screens, you can look back to Frank Daniels' method with index cards which he taught to thousands of screenwriters including David Lynch. Variations can be seen at https://www.youtube.com/watch?v=vrvawtrRxsw and https://www.youtube.com/watch?v=mwKjuBvNi40. Vladimir Nabokov used a very similar method for his novels which is fairly well documented: https://www.openculture.com/2014/02/the-notecards-on-which-vladimir-nabokov-wrote-lolita.html

    1. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Referee #2

      Evidence, reproducibility and clarity

      In this manuscript the authors have investigated the role of sub chromosomal deletion found in new world Leishmania infantum species. The deletion (12 kb) spans over across the four copies of tetrasomic chromosome 31 which includes the loss of four open reading frames (ORF) LinJ.31.2370 (ecto-3ʹ-nucleotidase/nuclease), LinJ.31.2380 (ecto-3'-nucleotidase precursor), LinJ.31.2390 (helicase-like protein) and LinJ.31.2400 (3,2-trans-enoyl-CoA isomerase). The ecto-3'-nucleotidase/nuclease (3'NU/NT) activity has been shown to have an important role in trypanosomatids in the purine salvage pathway implicated as virulence factor affecting the parasite's ability to infect macrophages. The authors showed that having such deletions enhances the metacyclogenesis in vitro but are highly susceptible to killing by neutrophils and macrophages. In addition, they are also less virulent in vivo. The authors claim that enhanced metacyclogenesis increases its transmissibility in the invertebrate host but may not be highly infectious in the vertebrate host. They speculate that that such parasites may provide immune response that may control the infection in endemic population by having large group of asymptomatic individuals. These outcomes are highly speculative. This study is thought provoking but needs to be studied thoroughly.

      Following are the comments:

      1. Leishmania 3"NU/NT plays an important role in virulence of the parasite and its survival,

      a. how do 3'-NU/NT DEL parasites survive in the host which lack all the 4 copies of NT?

      b. what is the advantage of having such parasites circulating in the endemic areas? 2. Since metacyclics are important for the pathogenesis of the parasites,

      a. What is the mechanism of increased metacyclogenesis of L. Infantum 3'-NU/NT DEL parasites in the absence of 3'-NU/NT activity which is essential for the virulence? 3. How does lack of 3'NU/NT enhance transmissibility since such metacyclics from 3'-NU/NT DEL parasites barely survive in vivo?

      a. the parasites are less resistant to NET and are killed easily.

      b. there is reduced recruitment of neutrophils (NT) and monocytes in the ear. 4. Fig.7C: what is the reason for higher parasite load of DEL in dLN? 5. Do you think there is reduced recruitment of NT in the infected site which would have controlled the parasites, hence they migrate quickly in the dLN? To test this possibility the authors should perform an in vitro NT recruitment assay. 6. Line 417: How are the 3'-NU/NT DEL parasites continuous source for infection in sand flies, If such parasites are not infectious and will be cleared by the host? 7. Line 400: Is it possible that having 3'-NU/NT DEL parasites in circulation dampens the infectivity of the NON-DEL and thus over all infection rate in the population goes down? 8. Could the 3'-NU/NT DEL parasites be the source of asymptomatic infections? 9. Is there literature evidence for such a possibility in the endemic region?

      Significance

      The authors claim that enhanced metacyclogenesis increases transmissibility of Leishmania in the invertebrate host but may not be highly infectious in the vertebrate host. They speculate that that such parasites may provide immune response that may control the infection in endemic population by having large group of asymptomatic individuals. These outcomes are highly speculative. This study is thought provoking but needs to be studied thoroughly.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      In this manuscript, Ferhat and colleagues describe their study aimed at developing a blood-brain barrier (BBB) penetrant agent that could induce hypothermia and provide neuroprotection from the sequelae of status epilepticus (SE) in mice. Hypothermia is used clinically in an attempt to reduce neurological sequelae of injury and disease. Hypothermia can be effective, but physical means used to reduce core body temperature are associated with untoward effects. Pharmacological means to induce hypothermia could be as effective with fewer untoward complications. Intracerebroventricularly applied neurotensin can cause hypothermia; however, neurotensin applied peripherally is degraded and does not cross the BBB. Here the authors develop and characterize a neurotensin conjugate that can reach the brain, induce hypothermia, and reduce seizures, cognitive changes, and inflammatory changes associated with status epilepticus. 

      Strengths: <br /> (1) In general, the study is well-reasoned, well-designed, and seemingly well-executed. 

      (2) Strong dose-response assessment of multiple neurotensin conjugates in mice. 

      (3) Solid assessment of binding affinity, in vitro stability in blood, and brain uptake of the conjugate. 

      (4) Appropriate inclusion of controls for SE and for drug injections. However, perhaps a vehicle control could have been employed. 

      Sham animals received saline 0.9% which is the vehicle control considering it was used to dilute the water-soluble VH-N412 molecule.

      (5) Multifaceted assessment of neurodegeneration, inflammation, and mossy fiber sprouting in the different groups. 

      (6) Inclusion of behavioral assessments. 

      (7) Evaluates NSTR1 receptor distribution in multiple ways; however, does not evaluate changes in receptor distribution or ping wo/w SE and/or various drugs. 

      (8) Demonstrates that this conjugate can induce hypothermia and have positive effects on the sequelae of SE. Could have a great impact on the application of pharmacologically-induced hypothermia as a neuroprotective measure in patients. 

      Weaknesses: 

      (1) The authors make the claim, repeatedly, that the hypothermia caused by the neurotensin conjugate is responsible for the effects they see; however, what they really show is that the conjugate causes hypothermia AND has favorable effects on the sequelae of SE. They need to discuss that they did not administer the conjugate without allowing the pharmacological hypothermia (e.g., by warming the animal, etc.). 

      We agree with Reviewer 1. We indeed hypothesize that it is principally the hypothermia induced by the NT conjugate that is responsible for the effects we observe. However, we do not exclude the possibility that the conjugate itself can have direct effects on the sequelae of SE. We tried to address this question with the in vitro experiments. Our results suggest that indeed, in the absence of hypothermia, the conjugate showed intrinsic neuroprotection of cultured hippocampal neurons challenged with excitotoxic agents such as NMDA or KA. Besides the description of these results in the “Results Section”, end of page 19 of the original manuscript, we had discussed them at the end of the “Discussion Section”, top of page 43 of the original manuscript.

      In order to separate the hypothermia component from the potential direct neuroprotective effects of the NT conjugate, we did consider abolishing hypothermia in animals that were injected with the NT conjugate by warming them up. However, it is particularly difficult to increase in a well- controlled manner the body temperature of mice, in particular undergoing seizures, in a closed temperature-controlled chamber. In response to Reviewer 1 demand, we added a few sentences in the “Discussion Section”, page 45 of the revised version.

      (2) In the status epilepticus studies, it is unclear how or whether they monitored animals for the development of spontaneous seizures. Can the authors please describe this?

      The KA model we used was originally discovered more than 30 years ago, developed and very well characterized and mastered in our laboratory by Ben-Ari (Ben-Ari et al., 1979). Most of KA-treated mice that developed SE after KA injection developed spontaneous seizures subsequent to a latent period of about 1 week as described in Figure 3A, Results Section page 11 and in the reference we had mentioned in the Materials and Methods Section, page 27 (Schauwecker and Steward, 1997).

      We agree that information regarding the development of spontaneous seizures is missing. We added 2 references, Gröticke et al., 2008; Wu et al., 2021 in the Materials and Methods Section, page 28 of the revised version, that describe the occurrence of spontaneous seizures after KA administration in mice. We also now added the following information in the Materials and Methods Section, end of page 29: In order to study mice in the chronic stage of epilepsy with spontaneous seizures, they were observed daily (at least 3 hours per day) for general behavior and occurrence of SRS. These are highly reproducible in the mouse KA model, allowing for visual monitoring and scoring of epileptic activity. After 3 weeks, most animals exhibited SRS, with 2 to 3 seizures per day, similar to previous observations (Wu et al., 2021). The detection of at least one spontaneous seizure per day was used as criterion indicating the animals had reached chronic phase that can ultimately be confirmed by mossy fiber sprouting (see Figure 7).

      (3) They do not evaluate changes in receptor distribution or ping wo/w SE and/or various drugs. 

      It is not clear to us what changes in receptor distribution need evaluation. We suppose the question concerns NTSR1 receptor. It would indeed be very interesting to compare NTSR1 in brain regions and different brain cells wo/w SE and/or various drugs, to assess receptor distribution or re-distribution, if any. However, addressing such a question is a project in itself that could not be addressed in the present study. Reviewer 1 also evokes ping wo/w SE and/or various drugs and if our understanding is correct, Reviewer 1 alludes to PING, Pyramidal Interneuronal Network γ (Dugladze et al., 2013, see reference below). Although we did not assess PING per se, we used multi-electrode arrays (MEA) on hippocampal brain slices stimulated wo/w KA to assess whether the VH-N412 conjugate could modulate pyramidal neuron activity. In order to respond to Reviewer 1 concern we added these data as Figure S2 with corresponding modifications in the Material and Methods Section (pages 34-35), in the Results Section (page 19) and in the Discussion Section page 43 of the revised version of our manuscript.

      Dugladze T, Maziashvili N, Börgers C, Gurgenidze S, Häussler U, Winkelmann A, Haas CA, Meier JC, Vida I, Kopell NJ, Gloveli T. GABA(B) autoreceptor-mediated cell type-specific reduction of inhibition in epileptic mice. Proc Natl Acad Sci U S A. 2013 Sep 10;110(37):15073-8. doi: 10.1073/pnas.1313505110. Epub 2013 Aug 26. PMID: 23980149; PMCID: PMC3773756.

      Bas du formulaire

      (4) It is not clear why several different mouse strains were employed. 

      We used 2 mouse strains in our work as mentioned in the Materials and Methods Section, page 21. The conjugates we developed and hypothermia evaluation were initially tested on adult Swiss CD-1 males. For the KA model and for behavioral tests, adult male FVB/N mice were used because they are considered as reliable and well described mouse models of epilepsy, where seizures are associated with cell death (Schauwecker, 2003). This not the case for a number of mouse strains that demonstrate very heterogeneous behavior in SE and heterogeneous neuronal death, sprouting and neuroinflammation. The FVB/N are also well suited for behavioral tests.

      In response to the Reviewer 1 demand, the following sentence has been introduced in the Results Section, page 11 and in the Materials and Methods Section, page 21 of the revised manuscript: We assessed our conjugates in a model of KA-induced seizures using adult male FVB/N mice. This mouse strain was selected as a reliable and well described mouse model of epilepsy, where seizures are associated with cell death and neuroinflammation (Schauwecker, 2003; Wu et al., 2021).

      Reviewer #2 (Public Review): 

      Summary: 

      The authors generated analogs consisting of modified neurotensin (NT) peptides capable of binding to low-density lipoprotein (LDL) and NT receptors. Their lead analog was further evaluated for additional validation as a novel therapeutic. The putative mechanism of action for NT in its antiseizure activity is hypothermia, and as therapeutic hypothermia has been demonstrated in epilepsy, NT analogs may confer antiseizure activity and avoid the negative effects of induced hypothermia. 

      Strengths: 

      The authors demonstrate an innovative approach, i.e. using LDLR as a means of transport into the brain, that may extend to other compounds. They systematically validate their approach and its potential through binding, brain penetration, in vivo antiseizure efficacy, and neuroprotection studies. 

      Weaknesses: 

      Tolerability studies are warranted, given the mechanism of action and the potential narrow therapeutic index. In vivo studies were used to assess the efficacy of the peptide conjugate analogs in the mouse KA model. However, it would be beneficial to have shown tolerability in naïve animals to better understand the therapeutic potential of this approach. 

      Tolerability studies were performed, but the results were not presented in the first version of the manuscript. In order to comply with Reviewer 2 demand, we have added the following text in the Results section, page 11 of the revised version to describe our tolerability results.

      Finally, tolerability studies were performed with the administration up to 20 and 40 mg/kg Eq. NT (i.e. 25.8 and 51.6 mg/kg of VH-N412) with n=3 for these doses. The rectal temperature of the animals did not fall below 32.5 to 33.2°C, similar to the temperature induced with the 4 mg/kg Eq. NT dose. We observed no mortality or notable clinical signs other than those associated with the rapid HT effect such as a decrease in locomotor activity. We thus report a very interesting therapeutic index since the maximal tolerated dose (MTD) was > 40 mg/kg Eq. NT, while the maximum effect is observed at a 10x lower dose of 4 mg/kg Eq. NT and an ED50 established at 0.69 mg/kg as shown in Figure 1G.

      Mice may be particularly sensitive to hypothermia. It would be beneficial to show similar effects in a rat model. 

      We have tested our conjugate in mice, rats, and pigs, with in all cases nice dose response curves. We added a few words in the Discussion Section, page 38 of the revised version to mention that we can elicit hypothermia with our conjugates in the above-mentioned species.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      (1) In Figures 4, 5, 6, 8, and 9, scale bars are needed on all panels. 

      We have looked carefully at the Figures. Scale bars are present on all Figures, as mentioned in the Legends of all Figures, but not necessarily on all panel pictures at the same magnification.

      (2) The supplemental would seemingly be better moved into the main body of the manuscript. 

      In agreement with Reviewer 1 demand, we moved the Supplemental Figures into the main body of the manuscript, except for Figure S1, previously Figure S3, and the new Figure S2. Tables S1 to S5 remain as Supplemental files.

      Reviewer #2 (Recommendations For The Authors): 

      Activation of LDLRs can have widespread effects in the CNS and peripherally. The authors should further discuss any beneficial or untoward effects of binding to LDL and activating LDLRs. 

      As mentioned in the Introduction and in a number of references where we describe the development of our family of LDLR peptide ligands (see below), we only selected peptide ligands that do not compete with LDL, one of the major ligands of the LDLR. We indeed showed that while LDL binds the ligand-binding domain of the LDLR, the peptide ligands we developed bind to the EGF-precursor homology domain of the receptor (See Malcor et al., 2008 below).

      We have studied our peptide ligands in vitro and in vivo for more than 15 years and we have not observed beneficial or adverse effects. Actually, one of the members of our LDLR peptide family has been validated as a theragnostic agent and is in Phase 1 clinical trials for brain glioblastoma and pancreatic cancer. Hence, to our knowledge, the peptide ligand we describe in the present study shows no beneficial or untoward effects on LDL binding and activation of the LDLR. In response to Reviewer 2 recommendation, we added the following information and references in the Introduction Section, page 6 of the revised version of our manuscript: These peptides bind the EGF precursor homology domain of the LDLR and thus do not compete with LDL binding on the ligand-binding domain. To our knowledge, they have no beneficial or untoward effects on LDL binding and LDLR activity (Malcor et al., 2012; Jacquot et al., 2016; David et al., 2018; Varini et al., 2019; Acier et al., 2021, Yang et al., 2023; Broc et al., 2024).

      Broc B, Varini K, Sonnette R, Pecqueux B, Benoist F, Masse M, Mechioukhi Y, Ferracci G, Temsamani J, Khrestchatisky M, Jacquot G, Lécorché P. LDLR-Mediated Targeting and Productive Uptake of siRNA-Peptide Ligand Conjugates In Vitro and In Vivo. Pharmaceutics. 2024 Apr 17;16(4):548. doi: 10.3390/pharmaceutics16040548. PMID: 38675209; PMCID: PMC11054735.

      Yang X, Varini K, Godard M, Gassiot F, Sonnette R, Ferracci G, Pecqueux B, Monnier V, Charles L, Maria S, Hardy M, Ouari O, Khrestchatisky M, Lécorché P, Jacquot G, Bardelang D. Preparation and In Vitro Validation of a Cucurbit[7]uril-Peptide Conjugate Targeting the LDL Receptor. J Med Chem. 2023 Jul 13;66(13):8844-8857. doi: 10.1021/acs.jmedchem.3c00423. Epub 2023 Jun 20. PMID: 37339060. 

      Acier A, Godard M, Gassiot F, Finetti P, Rubis M, Nowak J, Bertucci F, Iovanna JL, Tomasini R, Lécorché P, Jacquot G, Khrestchatisky M, Temsamani J, Malicet C, Vasseur S, Guillaumond F. LDL receptor-peptide conjugate as in vivo tool for specific targeting of pancreatic ductal adenocarcinoma. Commun Biol. 2021 Aug 19;4(1):987. doi: 10.1038/s42003-021-02508-0. PMID: 34413441; PMCID: PMC8377056.

      Varini K, Lécorché P, Sonnette R, Gassiot F, Broc B, Godard M, David M, Faucon A, Abouzid K, Ferracci G, Temsamani J, Khrestchatisky M, Jacquot G. Target engagement and intracellular delivery of mono- and bivalent LDL receptor- binding peptide-cargo conjugates: Implications for the rational design of new targeted drug therapies. J Control Release. 2019 Nov 28;314:141-161. doi: 10.1016/j.jconrel.2019.10.033. Epub 2019 Oct 20. PMID: 31644939.

      David M, Lécorché P, Masse M, Faucon A, Abouzid K, Gaudin N, Varini K, Gassiot F, Ferracci G, Jacquot G, Vlieghe P, Khrestchatisky M. Identification and characterization of highly versatile peptide-vectors that bind non- competitively to the low-density lipoprotein receptor for in vivo targeting and delivery of small molecules and protein cargos. PLoS One. 2018 Feb 27;13(2):e0191052. doi: 10.1371/journal.pone.0191052. PMID: 29485998; PMCID: PMC5828360.

      Molino Y, David M, Varini K, Jabès F, Gaudin N, Fortoul A, Bakloul K, Masse M, Bernard A, Drobecq L, Lécorché P, Temsamani J, Jacquot G, Khrestchatisky M. Use of LDL receptor-targeting peptide vectors for in vitro and in vivo cargo transport across the blood-brain barrier. FASEB J. 2017 May;31(5):1807-1827. doi: 10.1096/fj.201600827R. Epub 2017 Jan 20. PMID: 28108572.

      Jacquot G, Lécorché P, Malcor JD, Laurencin M, Smirnova M, Varini K, Malicet C, Gassiot F, Abouzid K, Faucon A, David M, Gaudin N, Masse M, Ferracci G, Dive V, Cisternino S, Khrestchatisky M. Optimization and in Vivo Validation of Peptide Vectors Targeting the LDL Receptor. Mol Pharm. 2016 Dec 5;13(12):4094-4105. doi: 10.1021/acs.molpharmaceut.6b00687. Epub 2016 Oct 11. PMID: 27656777.

      Malcor JD, Payrot N, David M, Faucon A, Abouzid K, Jacquot G, Floquet N, Debarbieux F, Rougon G, Martinez J, Khrestchatisky M, Vlieghe P, Lisowski V. Chemical optimization of new ligands of the low-density lipoprotein receptor as potential vectors for central nervous system targeting. J Med Chem. 2012 Mar 8;55(5):2227-41. doi: 10.1021/jm2014919. Epub 2012 Feb 14. PMID: 22257077.

      As described above, the authors should also comment on the tolerability of these analogs. 

      Tolerability studies were performed, but the results were not presented in the first version of the manuscript. In order to comply with Reviewer 2 demand, we have added the following text in the Results section, page 11 of the revised version to describe our tolerability results.

      Finally, tolerability studies were performed with the administration up to 20 and 40 mg/kg Eq. NT (i.e. 25.8 and 51.6 mg/kg of VH-N412) with n=3 for these doses. The rectal temperature of the animals did not fall below 32.5 to 33.2°C, similar to the temperature induced with the 4 mg/kg Eq. NT dose. We observed no mortality or notable clinical signs other than those associated with the rapid HT effect such as a decrease in locomotor activity. We thus report a very interesting therapeutic index since the maximal tolerated dose (MTD) was > 40 mg/kg Eq. NT, while the maximum effect is observed at a 10x lower dose of 4 mg/kg Eq. NT and an ED50 established at 0.69 mg/kg as shown in Figure 1G.

    1. Author response:

      The following is the authors’ response to the original reviews.

      We are deeply appreciative of the reviewers' insightful comments and constructive feedback on our manuscript. In response, we have implemented substantial revisions to enhance the clarity and impact of our work. Key changes include: 

      Reframing: We have shifted our focus from cognitive control to attention and memory processes, aligning more closely with our experimental design. This reframing is reflected throughout the manuscript, including additional citations highlighting the triple network model's involvement in memory processing. To reflect this change, we have updated the title to "Causal dynamics of salience, default mode, and frontoparietal networks during episodic memory formation and recall: A multi-experiment iEEG replication".

      Control analyses using resting-state epochs: We have conducted new analyses comparing task periods to resting baseline epochs. These results demonstrate enhanced directed information flow from the anterior insula to both the default mode and frontoparietal networks during encoding and recall periods compared to resting state across all four experiments. This finding underscores the anterior insula's critical role in memory and attention processing.

      Control analysis using the inferior frontal gyrus: To address specificity concerns, we performed control analyses using the inferior frontal gyrus as a comparison region. This analysis confirms that the observed directed information flow to the default mode and frontoparietal networks is specific to the anterior insula, rather than a general property of task-engaged brain regions.

      These revisions, combined with our rigorous methodologies and comprehensive analyses, provide compelling support for the central claims of our manuscript. We believe these changes significantly enhance the scientific contribution of our work.

      Our point-by-point responses to the reviewers' comments are provided below.

      Reviewer 1:

      -  The authors present results from an impressively sized iEEG sample. For reader context, this type of invasive human data is difficult and time-consuming to collect and many similar studies in high-level journals include 5-20 participants, typically not all of whom have electrodes in all regions of interest. It is excellent that they have been able to leverage open-source data in this way. 

      -  Preprocessing of iEEG data also seems sensible and appropriate based on field standards. 

      -  The authors tackle the replication issues inherent in much of the literature by replicating findings across task contexts, demonstrating that the principles of network communication evidenced by their results generalize in multiple task memory contexts. Again, the number of iEEG patients who have multiple tasks' worth of data is impressive. 

      We thank the reviewer for the encouraging comments and appreciate the positive feedback.  

      (1.1) The motivation for investigating the tripartite network during memory tasks is not currently well-elaborated. Though the authors mention, for example, that "the formation of episodic memories relies on the intricate interplay between large-scale brain networks (p. 4)", there are no citations provided for this statement, and the reader is unable to evaluate whether the nodes and networks evidenced to support these processes are the same as networks measured here. 

      Recommendation: Detail with citations the motivation for assessing the tripartite network in these tasks. Include work referencing network-level and local effects during encoding and recall.

      We appreciate the reviewer's feedback and suggestions for improving our framing. We have substantially expanded and revised the Introduction to elaborate on the motivation for investigating the tripartite network during memory tasks, supported by relevant citations.

      We now provide a stronger rationale for examining these networks in the context of episodic memory, emphasizing that while the tripartite network has been extensively studied in cognitive control tasks, growing evidence suggests its relevance to episodic memory as a domain-general network. We cite several key studies that demonstrate the involvement of the salience, default mode, and frontoparietal networks in memory processes, including work by Sestieri et al. (2014) and Vatansever et al. (2021), which show the consistent engagement of these networks during memory tasks. We have also included references to studies examining network-level and local effects during encoding and recall, such as the work by Xie et al. (2012) on disrupted intrinsic connectivity in amnestic mild cognitive impairment, and Le Berre et al. (2017) on the role of insula connectivity in memory awareness (pages 4-5).

      Furthermore, we have clarified how our study aims to address gaps in the current understanding by investigating the electrophysiological basis of these network interactions during memory formation and retrieval, which has not been explored in previous research. This expanded framing provides a clearer motivation for our investigation and places our study within the broader context of memory and network neuroscience research (pages 3-6).  

      (1.2) In addition, though the tripartite network has been proposed to support cognitive control processes, and the neural basis of cognitive control is the framed focus of this work, the authors do not demonstrate that they have measured cognitive control in addition to simple memory encoding and retrieval processes. Tasks that have investigated cognitive control over memory (such as those cited on p. 13 - Badre et al., 2005; Badre & Wagner, 2007; Wagner et al., 2001; Wagner et al., 2005) generally do not simply include encoding, delay, and recall (as the tasks used here), but tend to include some manipulation that requires participants to engage control processes over memory retrieval, such as task rules governing what choice should be made at recall (e.g., from Badre et al., 2005 Fig. 1: congruency of match, associative strength, number of choices, semantic similarity). Moreover, though there are task-responsive signatures in the nodes of the tripartite networks, concluding that cognitive control is present because cognitive control networks are active would be a reverse inference.

      Recommendation: If present, highlight components of the tasks that are known to elicit cognitive control processes and cite relevant literature. If the tasks cannot be argued to elicit cognitive control, reframe the motivation to focus on task-related attention or memory processes. If the latter, reframe the motivation for investigating the tripartite network in this context absent control.

      We appreciate the reviewer's insightful comment and recommendation. We acknowledge that our tasks do not include specific manipulations designed to elicit cognitive control processes over memory retrieval. In light of this, we have reframed our motivation and discussion to focus on the role of the tripartite network in attention and memory processes more broadly, rather than cognitive control specifically (pages 3-6).

      As noted in Response 1.1, we have revised the Introduction to emphasize the domain-general nature of these networks and their involvement in various cognitive processes, including memory. We also highlight how the salience, default mode, and frontoparietal networks contribute to different aspects of memory formation and retrieval, drawing on relevant literature.

      Our revised framing examines the salience network's role in detecting behaviorally relevant stimuli and orienting attention during encoding, the default mode network's involvement in internally-driven processes during recall, and the frontoparietal network's contribution to maintaining and manipulating information in working memory. We now present our study as an investigation into how these networks interact during different phases of memory processing, rather than focusing specifically on cognitive control. This approach aligns better with our experimental design and allows us to explore the broader applicability of the tripartite network model to memory processes. 

      This revised reframing provides a more accurate representation of our study's scope and contribution to understanding the role of large-scale brain networks in memory formation and retrieval (pages 3-6). 

      (1.3) It is currently unclear if the directed information flow from AI to DMN and FPN nodes truly arises from task-related processes such as cognitive control or if it is a function of static brain network characteristics constrained by anatomy (such as white matter connection patterns, etc.). This is a concern because the authors did not find that influences of AI on DMN or FPN are increased relative to a resting baseline (collected during the task) or that directed information flow differs in successful compared to unsuccessful retrieval. I doubt that this AI influence is 1) supporting a switch between the DMN and FPN via the SN or 2) relevant for behavior if it doesn't differ from baseline-active task or across accuracy conditions. An additional comparison that may help investigate whether this is reflective of static connectivity characteristics would be a baseline comparison during non-task rest or sleep periods.  

      Recommendation: As described in the task of the concern, analyze the PTE across the same contacts during sleep or task-free rest periods (if present in the dataset). 

      We thank the reviewer for this suggestion. We have now carried out additional analyses using resting-state baseline epochs. We found that directed information flow from the AI to both the DMN and FPN were enhanced during the encoding and recall periods compared to resting-state baseline in all four experiments. These new results have now been included in the revised Results (page 12):    

      “Enhanced information flow from the AI to the DMN and FPN during episodic memory processing, compared to resting-state baseline  

      We next examined whether directed information flow from the AI to the DMN and FPN nodes during the memory tasks differed from the resting-state baseline. Resting-state baselines were extracted immediately before the start of the task sessions and the duration of task and rest epochs were matched to ensure that differences in network dynamics could not be explained by differences in duration of the epochs. Directed information flow from the AI to both the DMN and FPN were higher during both the memory encoding and recall phases and across the four experiments, compared to baseline in all but two cases (Figures S6, S7). These findings provide strong evidence for enhanced role of AI directed information flow to the DMN and FPN during memory processing compared to the resting state.” 

      (1.4) Related to the above concern, it is also questionable how directed information flow from AI facilitates switching between FPN and DMN during both encoding and recall if high gamma activity does not significantly differ in AI versus PCC or mPFC during recall as it does during encoding. It seems erroneous to conclude that the network-level communication is happening or happening with the same effect during both task time points when these effects are decoupled in such a way from the power findings.  

      We appreciate the reviewer's insightful observation regarding the apparent discrepancy between our directed information flow findings and the high-gamma activity results. This comment highlights an important distinction in interpreting our results, and we thank the reviewer for the opportunity to address this point.

      Our findings demonstrate that directed information flow from the AI to the DMN and FPN persists during both encoding and recall, despite differences in local high-gamma activity patterns. This dissociation suggests that the network-level communication facilitated by the AI may operate independently of local activation levels in individual nodes. It is important to note that our directed connectivity analysis (using phase transfer entropy) was conducted on broadband signals (0.5-80 Hz), while the power analysis focused specifically on the high-gamma band (80-160 Hz). These different frequency ranges may capture distinct aspects of neural processing. The broadband connectivity might reflect more general, sustained network interactions, while high-gamma activity may be more sensitive to specific task demands or cognitive processes.

      The phase transfer entropy analysis captures directed interactions over extended time periods, while the high-gamma power analysis provides a more temporally precise measure of local neural activity. The persistent directed connectivity from AI during recall, despite changes in local activity, might reflect the AI's ongoing role in coordinating network interactions, even when its local activation is not significantly different from other regions.

      Rather than facilitating "switching" between FPN and DMN, as we may have previously overstated, our results suggest that the AI maintains a consistent pattern of influence on both networks across task phases. This influence might serve different functions during encoding (e.g., orienting attention to external stimuli) and recall (e.g., monitoring and evaluating retrieved information), even if local activation patterns differ.

      It is crucial to note that in the three verbal tasks, our analysis of memory recall is time-locked to word production onset. However, the precise timing of the internal recall process initiation is unknown. This limitation may affect our ability to capture the full dynamics of network interactions during recall, particularly in the early stages of memory retrieval. Interestingly, in the spatial memory task WMSM, the PCC/precuneus exhibited an earlier onset and enhanced activity compared to the AI. This task may provide a clearer window into recall processes:

      findings align with the view that DMN nodes may play a crucial role in triggering internal recall processes. However, the precise timing of internal retrieval initiation remains a challenge in the three verbal tasks, potentially limiting our ability to capture the full dynamics of regional activity, and its replicability, during early stages of recall.

      These observations highlight the need for more detailed investigation of the temporal dynamics of network interactions during memory recall. To further elucidate the relationship between directed connectivity and local activity, future studies could employ time-resolved connectivity analyses and investigate coupling between different frequency bands. This could provide a more precise understanding of how network-level communication relates to local neural dynamics across different task phases.

      We have revised the manuscript to more accurately reflect these points and avoid overstating the implications of our findings (pages 15-19). We thank the reviewer for prompting this important clarification, which we believe strengthens the interpretation and discussion of our results.

      (1.5) Missing information about the methods used for time-frequency conversion for power calculation and the power normalization/baseline-correction procedure bars a thorough evaluation of power calculation methods and results. 

      Recommendation: Include more information about how power was calculated. For example, how were time-series data converted to time-frequency (with complex wavelets, filter-hilbert, etc.)? What settings were used (frequency steps, wavelet length)? How were power values checked for outliers and normalized (decibels, Z-transform)? How was baseline correction applied (subtraction, division)?

      We have now included detailed information related to our power calculation and normalization steps as we note on page 28: “We first filtered the signals in the high-gamma (80160 Hz) frequency band (Canolty et al., 2006; Helfrich & Knight, 2016; Kai J. Miller, Weaver, & Ojemann, 2009) using sequential band-pass filters in increments of 10 Hz (i.e., 80–90 Hz, 90– 100 Hz, etc.), using a fourth order two-way zero phase lag Butterworth filter. We used these narrowband filtering processing steps to correct for the 1/f decay of power. We then calculated the amplitude (envelope) of each narrow band signal by taking the absolute value of the analytic signal obtained from the Hilbert transform (Foster, Rangarajan, Shirer, & Parvizi, 2015). Each narrow band amplitude time series was then normalized to its own mean amplitude, expressed as a percentage of the mean. Finally, we calculated the mean of the normalized narrow band amplitude time series, producing a single amplitude time series. Signals were then smoothed using 0.2s windows with 90% overlap (Kwon et al., 2021) and normalized with respect to 0.2s pre-stimulus periods by subtracting the pre-stimulus baseline from the post-stimulus signal.” 

      (1.6) If revisions to the manuscript can address concerns about directed information flow possibly being due to anatomical constraints - such as by indicating that directed information flow is not present during non-task rest or sleep - this work may convey important information about the structure and order of communication between these networks during attention to tasks in general. However, the ability of the findings to address cognitive control-specific communication and the nature of neurophysiological mechanisms of this communication - as opposed to the temporal order and structure of recruited networks - may be limited.

      We appreciate the reviewer's insightful feedback, which has led to significant improvements in our manuscript. In response, we have made the following key changes. We have shifted our focus from cognitive control to the broader roles of the tripartite network in attention and memory processes. This reframing aligns more closely with our experimental design and the nature of our tasks. We have revised the Introduction, Results, and Discussion sections to reflect this perspective, providing a more accurate representation of our study's scope and contribution. Additionally, to strengthen our findings, we have conducted new analyses comparing task periods to resting-state baselines. These analyses revealed that directed information flow from the anterior insula to both the DMN and FPN was significantly enhanced during memory encoding and recall periods compared to resting-state across all four experiments. This finding provides robust evidence for the specific involvement of these network interactions in memory processing. Please also see Response 1.2 above. 

      (1.7) Because phase-transfer entropy is presented as a "causal" analysis in this investigation (PTE), I also believe it is important to highlight for readers recent discussions surrounding the description of "causal mechanisms" in neuroscience (see "Confusion about causation" section from Ross and Bassett, 2024, Nature Neuroscience). A large proportion of neuroscientists (admittedly, myself included) use "causal" only to refer to a mechanism whose modulation or removal (with direct manipulation, such as by lesion or stimulation) is known to change or control a given outcome (such as a successful behavior). As Ross and Bassett highlight, it is debatable whether such mechanistic causality is captured by Granger "causality" (a.k.a. Granger prediction) or the parametric PTE, and the imprecise use of "causation" may be confusing. The authors could consider amending language regarding this analysis if they are concerned about bridging these definitions of causality across a wide audience. 

      We thank the reviewer for this suggestion. We would like to clarify here that we define causality in our manuscript as follows: a brain region has a causal influence on a target if knowing the past history of temporal signals in both regions improves the ability to predict the target's signal in comparison to knowing only the target's past, as defined in earlier studies (Granger, 1969; Lobier, Siebenhühner, Palva, & Matias, 2014). We have now included this clarification in the Introduction section (page 6).  

      We also agree with the reviewer that to more mechanistically establish a causal link between the neural dynamics and behavior, lesion or brain stimulation studies are necessary. We have now acknowledged this in the revised Discussion as we note: “Although our computational methods suggest causal influences, direct causal manipulations, such as targeted brain stimulation during memory tasks, are needed to establish definitive causal relationships between network nodes.” (page 19). 

      Minor additional information that would be helpful to the reader to include: 

      (1.8) How exactly was line noise (p. 24) removed? (For example, if notch filtered, how were slight offsets of the line noise from exactly 60.0Hz and harmonics identified and handled?). 

      We would like to clarify here that to filter line noise and its harmonics, we used bandstop filters at 57-63 Hz, 117-123 Hz, and 177-183 Hz. To create a band-stop filter, we used a fourth order two-way zero phase lag Butterworth filter. This information has now been included in the revised Methods (page 26). 

      (1.9) Why were the alpha and beta bands collapsed for narrowband filtering?

      Please note that we did not combine the alpha (8-12 Hz) and beta (12-30 Hz) bands for narrowband filtering, rather these two frequency bands were analyzed separately. However, we combined the delta (0.5-4 Hz) and theta (4-8 Hz) frequency bands into a combined delta-theta (0.5-8 Hz) frequency band for our analysis since previous human electrophysiology studies have not settled on a specific band of frequency (delta or theta) for memory processing. Previous human iEEG (Ekstrom et al., 2005; Ekstrom & Watrous, 2014; Engel & Fries, 2010; Gonzalez et al., 2015; Watrous, Tandon, Conner, Pieters, & Ekstrom, 2013) as well as scalp EEG and MEG studies, have shown that both the delta and theta frequency band oscillations play a prominent role for human memory encoding as well as retrieval (Backus, Schoffelen, Szebényi, Hanslmayr, & Doeller, 2016; Clouter, Shapiro, & Hanslmayr, 2017; Griffiths, Martín-Buro, Staresina, & Hanslmayr, 2021; Guderian & Düzel, 2005; Guderian, Schott, Richardson-Klavehn, & Düzel, 2009).  

      Reviewer 2:

      In this study, the authors leverage a large public dataset of intracranial EEG (the University of Pennsylvania RAM repository) to examine electrophysiologic network dynamics involving the participation of salience, frontoparietal, and default mode networks in the completion of several episodic memory tasks. They do this through a focus on the anterior insula (AI; salience network), which they hypothesize may help switch engagement between the DMN and FPN in concert with task demands. By analyzing high-gamma spectral power and phase transfer entropy (PTE; a putative measure of information "flow"), they show that the AI shows higher directed PTE towards nodes of both the DMN and FPN, during encoding and recall, across multiple tasks. They further demonstrate that high-gamma power in the PCC/precuneus is decreased relative to the AI during memory encoding. They interpret these results as evidence of "triple-network" control processes in memory tasks, governed by a key role of the AI. 

      I commend the authors on leveraging this large public dataset to help contextualize network models of brain function with electrophysiological mechanisms - a key problem in much of the fMRI literature. I also appreciate that the authors emphasized replicability across multiple memory tasks, in an effort to demonstrate conserved or fundamental mechanisms that support a diversity of cognitive processes. However, I believe that their strong claims regarding causal influences within circumscribed brain networks cannot be supported by the evidence as presented. In my efforts to clearly communicate these inadequacies, I will suggest several potential analyses for the authors to consider that might better link the data to their central hypotheses.

      We thank the reviewer for the encouraging comments and suggestions for improving the manuscript. Please see our detailed responses and clarifications below. 

      (2.1) As a general principle, the effects that the authors show - both in regards to their highgamma power analysis and PTE analysis - do not offer sufficient specificity for a reader to understand whether these are general effects that may be repeated throughout the brain, or whether they reflect unique activity to the networks/regions that are laid out in the Introduction's hypothesis. This lack of specificity manifests in several ways, and is best communicated through examples of control analyses. 

      We appreciate the reviewer's insightful comment regarding the specificity of our findings. We agree that additional analyses could provide valuable context for interpreting our results. In response, we have conducted the following additional analyses and made corresponding revisions to the manuscript:

      Following the reviewer's suggestion, we have selected the inferior frontal gyrus (IFG, BA 44) as a control region. The IFG serves as an ideal control region due to its anatomical adjacency to the AI, its involvement in a wide range of cognitive control functions including response inhibition (Cai, Ryali, Chen, Li, & Menon, 2014), and its frequent co-activation with the AI in fMRI studies. Furthermore, the IFG has been associated with controlled retrieval of memory (Badre et al., 2005; Badre & Wagner, 2007; Wagner et al., 2001), making it a compelling region for comparison. We repeated our PTE analysis using the IFG as the source region, comparing its directed influence on the DMN and FPN nodes to that of the AI.  

      Our analysis revealed a striking contrast between the AI and IFG in their patterns of directed information flow. While the AI exhibited strong causal influences on both the DMN and FPN, the IFG showed the opposite pattern. Specifically, both the DMN and FPN demonstrated higher influence on the IFG than the reverse, during both encoding and recall periods, and across all four memory experiments (Figures S4, S5). 

      These findings highlight the unique role of the AI in orchestrating large-scale network dynamics during memory processes. The AI's pattern of directed information flow stands in contrast to that of the IFG, despite their anatomical proximity and shared involvement in cognitive control processes. This dissociation underscores the specificity of the AI's function in coordinating network interactions during memory formation and retrieval. These results have now been included in our revised Results on page 11.  

      (2.2) First, the PTE analysis is focused solely on the AI's interactions with nodes of the DMN and FPN; while it makes sense to focus on this putative "switch" region, the fact that the authors report significant PTE from the AI to nodes of both networks, in encoding and retrieval, across all tasks and (crucially) also at baseline, raises questions about the meaningfulness of this statistic. One way to address this concern would be to select a control region that would be expected to have little/no directed causal influence on these networks and repeat the analysis. Alternatively (or additionally), the authors could examine the time course of PTE as it evolves throughout an encoding/retrieval interval, and relate that to the timing of behavioral events or changes in high-gamma power. This would directly address an important idea raised in their own Discussion, "the AI is wellpositioned to dynamically engage and disengage with other brain areas."  

      Please see Response 2.1 above for additional analyses related to control region.  

      We also appreciate the reviewer's suggestion regarding time-resolved PTE analysis. However, it's important to note that our current methodology does not allow for such fine-grained temporal analysis. This is due to the fact that PTE, which is an information theoretic measure and relies on constructing histograms of occurrences of singles, pairs, or triplets of instantaneous phase estimates from the phase time-series (Hillebrand et al., 2016) (Methods), requires sufficient number of cycles in the phase time-series for its reliable estimation (Lobier et al., 2014). PTE is based on estimating the time-delayed directed influences from one time-series to the other and its estimate is the most accurate when a large number of time-points (cycles) are available (Lobier et al., 2014). Since our encoding and recall epochs in the verbal recall tasks were only 1.6 seconds long, which corresponds to only 800 time-points with a 500 Hz sampling rate, we used the entire encoding and recall epochs for the most efficient estimate of PTE, rather than estimating PTE in a time-resolved manner. Please note that this is consistent with previous literature which have used ~ 225000 time-points (3 minutes of resting-state data with 1250 Hz sampling rate) for estimating PTE, for example, see (Hillebrand et al., 2016). 

      This limitation prevents us from examining how directed connectivity evolves throughout the encoding and retrieval intervals on a moment-to-moment basis. Future studies employing longer task epochs or alternative methods for time-resolved connectivity analysis could provide valuable insights into the dynamic engagement and disengagement of the AI with other brain areas based on task demands. Such analyses could potentially reveal task-specific temporal patterns in the AI's influence on DMN and FPN nodes during different phases of memory processing.

      Finally, it is crucial to note that in the three verbal tasks, our analysis of memory recall is timelocked to word production onset. However, the precise timing of the internal retrieval process initiation is unknown. This limitation may affect our ability to capture the full dynamics of network interactions during recall, particularly in the early stages of memory retrieval. Interestingly, in the spatial memory task, where this timing issue is less problematic due to the nature of the task, we observe that the PCC/precuneus shows an earlier onset of activity compared to the AI. This process is aligned with the view that DMN nodes may trigger internal recall processes, the full extent and replication of which across verbal and spatial tasks could not be examined in this study.  

      We have added a discussion of these limitations and future directions to the manuscript to provide a more nuanced interpretation of our findings and to highlight important areas for further investigation (page 19). 

      (2.3) Second, the authors state that high-gamma suppression in the PCC/precuneus relative to the AI is an anatomically specific signature that is not present in the FPN. This claim does not seem to be supported by their own evidence as presented in the Supplemental Data (Figures S2 and S3), which to my eye show clear evidence of relative suppression in the MFG and dPPC (e.g. S2a and S3a, most notably) which are notated as "significant" with green bars. I appreciate that the magnitude of this effect may be greater in the PCC/precuneus, but if this is the claim it should be supported by appropriate statistics and interpretation.  

      We thank the reviewer for raising this point. We have now directly compared the high-gamma power of the PCC/precuneus with the dPPC and MFG nodes of the FPN and we note that the suppression effects of the PCC/precuneus are stronger compared to those of the dPPC and MFG during memory encoding (Figures S8, S9). 

      (2.4) I commend the authors on emphasizing replicability, but I found their Bayes Factor (BF) analysis to be difficult to interpret and qualitatively inconsistent with the results that they show. For example, the authors state that BF analysis demonstrates "high replicability" of the gamma suppression effect in Figure 3a with that of 3c and 3d. While it does appear that significant effects exist across all three tasks, the temporal structure of high gamma signals appears markedly different between the two in ways that may be biologically meaningful. Moreover, it appears that the BF analysis did not support replicability between VFR and CATVFR, which is very surprising; these are essentially the same tasks (merely differing in the presence of word categories) and would be expected to have the highest degree of concordance, not the lowest. I would suggest the authors try to analytically or conceptually reconcile this surprising finding. 

      We appreciate the reviewer's commendation on our emphasis on replicability and thank the reviewer for the opportunity to provide clarification.

      First, we would like to clarify the nature of our BF analysis. Bayes factors are calculated as the ratio of the marginal likelihood of the replication data, given the posterior distribution estimated from the original data, and the marginal likelihood for the replication data under the null hypothesis of no effect (Ly, Etz, Marsman, & Wagenmakers, 2019). Specifically, BFs use the posterior distribution from the first experiment as a prior distribution for the replication test of the second experiment to constitute a joint multivariate distribution (i.e., the additional evidence for the alternative hypothesis given what was already observed in the original study) and this joint distribution is dependent on the similarity between the two experiments (Ly et al., 2019).  This analysis revealed that PCC/precuneus suppression, in comparison to the AI during memory encoding, observed in the VFR during memory encoding was detected in two other tasks, PALVCR, and WMSM with high BFs. In the CATVFR task, although there were short time periods of PCC/precuneus suppression (Figure 3), the effects were not strong enough like the three other tasks.  

      Regarding the high-gamma suppression effect, our BF analysis indeed supports replicability across the VFR, PALVCR, and WMSM tasks. While we agree with the reviewer that the temporal structure of high-gamma signals appears different across tasks, the BF analysis focuses on the overall presence of the suppression effect rather than its precise temporal profile. The high BFs indicate that the core finding - PCC/precuneus suppression relative to the AI during memory encoding - is replicated across these tasks, despite differences in the timing of this suppression. Moreover, at no time point did responses in the PCC/precuneus exceed that of the AI in any of the four memory encoding tasks. 

      The reason for differences in temporal profiles is not clear. While VFR and CATVFR are similar, the addition of categorical structure in CATVFR may have introduced cognitive processes that alter the temporal dynamics of regional responses. Moreover, differences in electrode placements across participants in each experiment may also have contributed to variability in the observed effects. Further studies using within-subjects experimental designs are needed to address this. 

      We have updated our Results and Discussion sections to reflect these points and to provide a more nuanced interpretation of the replicability across tasks.  

      (2.5) To aid in interpretability, it would be extremely helpful for the authors to assess acrosstask similarity in high-gamma power on a within-subject basis, which they are wellpowered to do. For example, could they report the correlation coefficient between HGP timecourses in paired-associates versus free-recall tasks, to better establish whether these effects are consistent on a within-subject basis? This idea could similarly be extended to the PTE analysis. Across-subject correlations would also be a welcome analysis that may provide readers with better-contextualized effect sizes than the output of a Bayes Factor analysis.  

      We thank the reviewer for this suggestion. However, a within-subject analysis was not possible because very few participants participated in multiple memory tasks. 

      For example, for the AI-PCC/Pr analysis, only 1 individual participated in both the VFR and PALVCR tasks (Tables S2a, S2c). Similarly, for AI-mPFC analysis, only 3 subjects participated in both the VFR and PALVCR tasks (Tables S2a, S2c).  

      Due to these small sample sizes, it was not feasible for us to assess replicability across tasks on a within-subject basis in our dataset. Therefore, for all our analysis, we have pooled electrode pairs across subjects and then subjected these to a linear mixed effects modeling framework for assessing significance and then subsequently assessing replicability of these effects using the Bayes factor (BF) framework.    

      Recommendations For The Authors: 

      (2.6) I would emphasize manuscript organization in a potential rewrite; it was very difficult to follow which analyses were attempting to show a contrast between effects versus a similarity between effects. Results were grouped by the underlying experimental conditions (e.g. encoding/recall, network identity, etc.) but may be better grouped according to the actual effects that were found. 

      We thank the reviewer for this suggestion. We considered this possibility, but we feel that the Results section is best organized in the order of the hypotheses we set out to test, starting from analyzing local brain activity using high-gamma power analysis, and then results related to analyzing brain connectivity using PTE. All these results are systematically ordered by presenting results related to encoding first and then the recall periods as they appear sequentially in our task-design, presenting the results related to the VFR task first and then demonstrating replicability of the results in the three other experiments. Results are furthermore arranged by nodes, where we first discuss results related to the DMN nodes, and then the same for the FPN nodes. This is to ensure systematic, unbiased organization of all our results for the readers to clearly follow the hypotheses, statistical analyses, and the brain regions considered. Therefore, for transparency and ethical reasons, we would respectfully like to present our results as they appear in our current manuscript, rather than presenting the results based on effect sizes. 

      However, please note that we indeed have ordered our results in the Discussion section based on actual effects, as suggested by the reviewer.  

      (2.7) The absence of a PTE effect when analyzing through the lens of successful vs. unsuccessful memory is an important limitation of the current study and a significant departure from the wealth of subsequent memory effects reported in the literature (which the authors have already done a good job citing, e.g. Burke et al. 2014 Neuroimage). I'm glad that the authors raised this in their Discussion, but it is important that the results of such an analysis actually be shown in the manuscript. 

      We thank the reviewer for this suggestion. We have now included the results related to PTE dynamics for successful vs. unsuccessful memory trials in the revised Results section as we note on page 12: 

      “Differential information flow from the AI to the DMN and FPN for successfully recalled and forgotten memory trials 

      We examined memory effects by comparing PTE between successfully recalled and forgotten memory trials. However, this analysis did not reveal differences in directed influence from the AI on the DMN and FPN or the reverse, between successfully recalled and forgotten memory trials during the encoding as well as recall periods in any of the memory experiments (all ps>0.05).”

      (2.8) I believe the claims of causality through the use of the PTE are overstated throughout the manuscript and may contribute to further confusion in the literature regarding how causality in the brain can actually be understood. See Mehler and Kording, 2018 arXiv for an excellent discussion on the topic (https://arxiv.org/abs/1812.03363). My recommendation would be to significantly tone down claims that PTE reflects causal interactions in the brain. 

      We thank the reviewer for this suggestion. We would like to clarify here that we define causality in our manuscript as follows: a brain region has a causal influence on a target if knowing the past history of temporal signals in both regions improves the ability to predict the target's signal in comparison to knowing only the target's past, as defined in earlier studies (Granger, 1969; Lobier et al., 2014). We have now included this clarification in the Introduction section (page 6).  

      We also agree with the reviewer that to more mechanistically establish a causal link between the neural dynamics and behavior, lesion or brain stimulation studies are necessary. We have now acknowledged this in the revised Discussion as we note: “Although our computational methods suggest causal influences, direct causal manipulations, such as targeted brain stimulation during memory tasks, are needed to establish definitive causal relationships between network nodes.” (page 19). 

      Finally, we have now significantly toned down our claims that PTE reflects causal interactions in the brain, in the Introduction, Results, and Discussion sections of our revised manuscript.  

      (2.9) Relatedly, it may be useful for the authors to consider a supplemental analysis that uses classic measures of inter-regional synchronization, e.g. the PLV, and compare to their PTE findings. They cite literature to suggest a metric like the PTE may be useful, but this hardly rules out the potential utility of investigating narrowband phase synchronization. 

      We thank the reviewer for this suggestion. We have now run new analyses based on PLV to examine phase synchronization between the AI and the DMN and FPN. However, we did not find a significant PLV for the interactions between the AI and DMN and FPN nodes for the different task periods compared to the resting baselines, as we note on page 13: 

      “Narrowband phase synchronization between the AI and the DMN and FPN during encoding and recall compared to resting baseline  

      We next directly compared the phase locking values (PLVs) (see Methods for details) between the AI and the PCC/precuneus and mPFC nodes of the DMN and also the dPPC and MFG nodes of the FPN for the encoding and the recall periods compared to resting baseline. However, narrowband PLV values did not significantly differ between the encoding/recall vs. rest periods, in any of the delta-theta (0.5-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), gamma (30-80 Hz), and high-gamma (80-160 Hz) frequency bands. These results indicate that PTE, rather than phase synchronization, more robustly captures the AI dynamic interactions with the DMN and the FPN.” 

      Please note that phase locking measures such as the PLV or coherence do not probe directed causal influences and cannot address how one region drives another. Instead, our study examined the direction of information flow between the AI and the DMN and FPN using robust estimators of the direction of information flow. PTE assesses with the ability of one time-series to predict future values of other time-series, thus estimating the time-delayed causal influences between the two time-series, whereas PLV or coherence can only estimate “instantaneous” phase synchronization, but not predict the future time-series. 

      Additionally, please note that the directed information flow from the AI to both the DMN and FPN were enhanced during the encoding and recall periods compared to resting state across all four experiments, in a new set of analyses that we have carried out in our revised manuscript. Specifically, we have now carried out our task versus rest comparison by using resting baseline epochs before the start of the entire session of the task periods, rather than our previously used rest epochs which were in between the task periods. These new results have now been included in the revised Results as we note on page 12:  

      “Enhanced information flow from the AI to the DMN and FPN during episodic memory processing, compared to resting-state baseline

      We next examined whether directed information flow from the AI to the DMN and FPN nodes during the memory tasks differed from the resting-state baseline. Resting-state baselines were extracted immediately before the start of the task sessions and the duration of task and rest epochs were matched to ensure that differences in network dynamics could not be explained by differences in duration of the epochs. Directed information flow from the AI to both the DMN and FPN were higher during both the memory encoding and recall phases and across the four experiments, compared to baseline in all but two cases (Figures S6, S7). These findings provide strong evidence for enhanced role of AI directed information flow to the DMN and FPN during memory processing compared to the resting state.”  

      References 

      Backus, A. R., Schoffelen, J. M., Szebényi, S., Hanslmayr, S., & Doeller, C. F. (2016). Hippocampal-Prefrontal Theta Oscillations Support Memory Integration. Curr Biol, 26(4), 450-457. doi:10.1016/j.cub.2015.12.048

      Bastos, A. M., Vezoli, J., Bosman, C. A., Schoffelen, J. M., Oostenveld, R., Dowdall, J. R., . . . Fries, P. (2015). Visual areas exert feedforward and feedback influences through distinct frequency channels. Neuron, 85(2), 390-401. doi:10.1016/j.neuron.2014.12.018

      Canolty, R. T., Edwards, E., Dalal, S. S., Soltani, M., Nagarajan, S. S., Kirsch, H. E., . . . Knight, R. T. (2006). High gamma power is phase-locked to theta oscillations in human neocortex. Science, 313(5793), 1626-1628. doi:10.1126/science.1128115

      Canolty, R. T., & Knight, R. T. (2010). The functional role of cross-frequency coupling. Trends Cogn Sci, 14(11), 506-515. doi:10.1016/j.tics.2010.09.001

      Chen, L., Wassermann, D., Abrams, D. A., Kochalka, J., Gallardo-Diez, G., & Menon, V. (2019). The visual word form area (VWFA) is part of both language and attention circuitry. Nat Commun, 10(1), 5601. doi:10.1038/s41467-019-13634-z

      Clouter, A., Shapiro, K. L., & Hanslmayr, S. (2017). Theta Phase Synchronization Is the Glue that Binds Human Associative Memory. Curr Biol, 27(20), 3143-3148.e3146. doi:10.1016/j.cub.2017.09.001

      Crone, N. E., Boatman, D., Gordon, B., & Hao, L. (2001). Induced electrocorticographic gamma activity during auditory perception. Brazier Award-winning article, 2001. Clin Neurophysiol, 112(4), 565-582. doi:10.1016/s1388-2457(00)00545-9

      Daitch, A. L., & Parvizi, J. (2018). Spatial and temporal heterogeneity of neural responses in human posteromedial cortex. Proc Natl Acad Sci U S A, 115(18), 4785-4790. doi:10.1073/pnas.1721714115

      Das, A., de Los Angeles, C., & Menon, V. (2022). Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during restingstate and cognition. Neuroimage, 250, 118927. doi:10.1016/j.neuroimage.2022.118927

      Das, A., & Menon, V. (2020). Spatiotemporal Integrity and Spontaneous Nonlinear Dynamic Properties of the Salience Network Revealed by Human Intracranial Electrophysiology: A Multicohort Replication. Cereb Cortex, 30(10), 5309-5321. doi:10.1093/cercor/bhaa111

      Das, A., & Menon, V. (2021). Asymmetric Frequency-Specific Feedforward and Feedback Information Flow between Hippocampus and Prefrontal Cortex during Verbal Memory Encoding and Recall. J Neurosci, 41(40), 8427-8440. doi:10.1523/jneurosci.080221.2021

      Das, A., & Menon, V. (2022). Replicable patterns of causal information flow between hippocampus and prefrontal cortex during spatial navigation and spatial-verbal memory formation. Cereb Cortex, 32(23), 5343-5361. doi:10.1093/cercor/bhac018

      Das, A., & Menon, V. (2023). Concurrent- and after-effects of medial temporal lobe stimulation on directed information flow to and from prefrontal and parietal cortices during memory formation. J Neurosci, 43(17), 3159-3175. doi:10.1523/jneurosci.1728-22.2023

      Edwards, E., Soltani, M., Deouell, L. Y., Berger, M. S., & Knight, R. T. (2005). High gamma activity in response to deviant auditory stimuli recorded directly from human cortex. J Neurophysiol, 94(6), 4269-4280. doi:10.1152/jn.00324.2005

      Ekstrom, A. D., Caplan, J. B., Ho, E., Shattuck, K., Fried, I., & Kahana, M. J. (2005). Human hippocampal theta activity during virtual navigation. Hippocampus, 15(7), 881-889. doi:10.1002/hipo.20109

      Ekstrom, A. D., & Watrous, A. J. (2014). Multifaceted roles for low-frequency oscillations in bottom-up and top-down processing during navigation and memory. Neuroimage, 85 Pt 2, 667-677. doi:10.1016/j.neuroimage.2013.06.049

      Engel, A. K., & Fries, P. (2010). Beta-band oscillations--signalling the status quo? Curr Opin Neurobiol, 20(2), 156-165. doi:10.1016/j.conb.2010.02.015

      Foster, B. L., Rangarajan, V., Shirer, W. R., & Parvizi, J. (2015). Intrinsic and task-dependent coupling of neuronal population activity in human parietal cortex. Neuron, 86(2), 578590. doi:10.1016/j.neuron.2015.03.018

      Gonzalez, A., Hutchinson, J. B., Uncapher, M. R., Chen, J., LaRocque, K. F., Foster, B. L., . . . Wagner, A. D. (2015). Electrocorticography reveals the temporal dynamics of posterior parietal cortical activity during recognition memory decisions. Proc Natl Acad Sci U S A, 112(35), 11066-11071. doi:10.1073/pnas.1510749112

      Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Crossspectral Methods. Econometrica, 37(3), 424-438. doi:10.2307/1912791

      Griffiths, B. J., Martín-Buro, M. C., Staresina, B. P., & Hanslmayr, S. (2021). Disentangling neocortical alpha/beta and hippocampal theta/gamma oscillations in human episodic memory formation. Neuroimage, 242, 118454. doi:10.1016/j.neuroimage.2021.118454

      Guderian, S., & Düzel, E. (2005). Induced theta oscillations mediate large-scale synchrony with mediotemporal areas during recollection in humans. Hippocampus, 15(7), 901-912. doi:10.1002/hipo.20125

      Guderian, S., Schott, B. H., Richardson-Klavehn, A., & Düzel, E. (2009). Medial temporal theta state before an event predicts episodic encoding success in humans. Proc Natl Acad Sci U S A, 106(13), 5365-5370. doi:10.1073/pnas.0900289106

      Helfrich, R. F., & Knight, R. T. (2016). Oscillatory Dynamics of Prefrontal Cognitive Control. Trends Cogn Sci, 20(12), 916-930. doi:10.1016/j.tics.2016.09.007

      Hillebrand, A., Tewarie, P., van Dellen, E., Yu, M., Carbo, E. W., Douw, L., . . . Stam, C. J. (2016). Direction of information flow in large-scale resting-state networks is frequencydependent. Proc Natl Acad Sci U S A, 113(14), 3867-3872. doi:10.1073/pnas.1515657113

      Jeffreys, H. (1998). The Theory of Probability (3rd ed.). Oxford, England: Oxford University Press.

      Kwon, H., Kronemer, S. I., Christison-Lagay, K. L., Khalaf, A., Li, J., Ding, J. Z., . . . Blumenfeld, H. (2021). Early cortical signals in visual stimulus detection. Neuroimage, 244, 118608. doi:10.1016/j.neuroimage.2021.118608

      Lachaux, J. P., George, N., Tallon-Baudry, C., Martinerie, J., Hugueville, L., Minotti, L., . . . Renault, B. (2005). The many faces of the gamma band response to complex visual stimuli. Neuroimage, 25(2), 491-501. doi:10.1016/j.neuroimage.2004.11.052

      Lobier, M., Siebenhühner, F., Palva, S., & Matias, P. J. (2014). Phase transfer entropy: A novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions. Neuroimage, 85, 853-872. doi:10.1016/j.neuroimage.2013.08.056

      Ly, A., Etz, A., Marsman, M., & Wagenmakers, E. J. (2019). Replication Bayes factors from evidence updating. Behav Res Methods, 51(6), 2498-2508. doi:10.3758/s13428-0181092-x

      Mainy, N., Kahane, P., Minotti, L., Hoffmann, D., Bertrand, O., & Lachaux, J. P. (2007). Neural correlates of consolidation in working memory. Hum Brain Mapp, 28(3), 183-193. doi:10.1002/hbm.20264

      Miller, K. J., Leuthardt, E. C., Schalk, G., Rao, R. P., Anderson, N. R., Moran, D. W., . . . Ojemann, J. G. (2007). Spectral changes in cortical surface potentials during motor movement. J Neurosci, 27(9), 2424-2432. doi:10.1523/jneurosci.3886-06.2007

      Miller, K. J., Weaver, K. E., & Ojemann, J. G. (2009). Direct electrophysiological measurement of human default network areas. Proceedings of the National Academy of Sciences, 106(29), 12174-12177. doi:10.1073/pnas.0902071106

      Nuzzo, R. L. (2017). An Introduction to Bayesian Data Analysis for Correlations. Pm r, 9(12), 1278-1282. doi:10.1016/j.pmrj.2017.11.003

      Ray, S., Crone, N. E., Niebur, E., Franaszczuk, P. J., & Hsiao, S. S. (2008). Neural correlates of high-gamma oscillations (60-200 Hz) in macaque local field potentials and their potential implications in electrocorticography. J Neurosci, 28(45), 11526-11536. doi:10.1523/jneurosci.2848-08.2008

      Sederberg, P. B., Schulze-Bonhage, A., Madsen, J. R., Bromfield, E. B., Litt, B., Brandt, A., & Kahana, M. J. (2007). Gamma oscillations distinguish true from false memories. Psychol Sci, 18(11), 927-932. doi:10.1111/j.1467-9280.2007.02003.x

      Tallon-Baudry, C., Bertrand, O., Hénaff, M. A., Isnard, J., & Fischer, C. (2005). Attention modulates gamma-band oscillations differently in the human lateral occipital cortex and fusiform gyrus. Cereb Cortex, 15(5), 654-662. doi:10.1093/cercor/bhh167

      Watrous, A. J., Tandon, N., Conner, C. R., Pieters, T., & Ekstrom, A. D. (2013). Frequencyspecific network connectivity increases underlie accurate spatiotemporal memory retrieval. Nature Neuroscience, 16(3), 349-356. doi:10.1038/nn.3315

      Wetzels, R., & Wagenmakers, E. J. (2012). A default Bayesian hypothesis test for correlations and partial correlations. Psychon Bull Rev, 19(6), 1057-1064. doi:10.3758/s13423-0120295-x

    1. Skip to content <link href="//diddy.com/cdn/shop/t/18/assets/component-list-menu.css?v=151968516119678728991696719192" rel="stylesheet" type="text/css" media="all" /> <link href="//diddy.com/cdn/shop/t/18/assets/component-search.css?v=130382253973794904871696719192" rel="stylesheet" type="text/css" media="all" /> <link href="//diddy.com/cdn/shop/t/18/assets/component-menu-drawer.css?v=160161990486659892291696719192" rel="stylesheet" type="text/css" media="all" /> <link href="//diddy.com/cdn/shop/t/18/assets/component-cart-notification.css?v=54116361853792938221696719192" rel="stylesheet" type="text/css" media="all" /> <link href="//diddy.com/cdn/shop/t/18/assets/component-cart-items.css?v=4628327769354762111696719192" rel="stylesheet" type="text/css" media="all" /> header-drawer { justify-self: start; margin-left: -1.2rem; }.scrolled-past-header .header__heading-logo-wrapper { width: 75%; }@media screen and (min-width: 990px) { header-drawer { display: none; } }.menu-drawer-container { display: flex; } .list-menu { list-style: none; padding: 0; margin: 0; } .list-menu--inline { display: inline-flex; flex-wrap: wrap; } summary.list-menu__item { padding-right: 2.7rem; } .list-menu__item { display: flex; align-items: center; line-height: calc(1 + 0.3 / var(--font-body-scale)); } .list-menu__item--link { text-decoration: none; padding-bottom: 1rem; padding-top: 1rem; line-height: calc(1 + 0.8 / var(--font-body-scale)); } @media screen and (min-width: 750px) { .list-menu__item--link { padding-bottom: 0.5rem; padding-top: 0.5rem; } } .header { padding-top: 10px; padding-bottom: 10px; } .section-header { position: sticky; /* This is for fixing a Safari z-index issue. PR #2147 */ margin-bottom: 0px; } @media screen and (min-width: 750px) { .section-header { margin-bottom: 0px; } } @media screen and (min-width: 990px) { .header { padding-top: 20px; padding-bottom: 20px; } } Home page The Love Album: Off The Grid Contact Log in<form method="post" action="/localization" id="HeaderCountryMobileFormNoScriptDrawer" accept-charset="UTF-8" class="localization-form" enctype="multipart/form-data"><input type="hidden" name="form_type" value="localization" /><input type="hidden" name="utf8" value="✓" /><input type="hidden" name="_method" value="put" /><input type="hidden" name="return_to" value="/" /><div class="localization-form__select"> <h2 class="visually-hidden" id="HeaderCountryMobileLabelNoScriptDrawer"> Country/region </h2> <select class="localization-selector link" name="country_code" aria-labelledby="HeaderCountryMobileLabelNoScriptDrawer" ><option value="AF" > Afghanistan (AFN ؋) </option><option value="AX" > Åland Islands (EUR €) </option><option value="AL" > Albania (ALL L) </option><option value="DZ" > Algeria (DZD د.ج) </option><option value="AD" > Andorra (EUR €) </option><option value="AO" > Angola (USD $) </option><option value="AI" > Anguilla (XCD $) </option><option value="AG" > Antigua &amp; Barbuda (XCD $) </option><option value="AR" > Argentina (USD $) </option><option value="AM" > Armenia (AMD դր.) </option><option value="AW" > Aruba (AWG ƒ) </option><option value="AC" > Ascension Island (SHP £) </option><option value="AU" > Australia (AUD $) </option><option value="AT" > Austria (EUR €) </option><option value="AZ" > Azerbaijan (AZN ₼) </option><option value="BS" > Bahamas (BSD $) </option><option value="BH" > Bahrain (USD $) </option><option value="BD" > Bangladesh (BDT ৳) </option><option value="BB" > Barbados (BBD $) </option><option value="BY" > Belarus (USD $) </option><option value="BE" > Belgium (EUR €) </option><option value="BZ" > Belize (BZD $) </option><option value="BJ" > Benin (XOF Fr) </option><option value="BM" > Bermuda (USD $) </option><option value="BT" > Bhutan (USD $) </option><option value="BO" > Bolivia (BOB Bs.) </option><option value="BA" > Bosnia &amp; Herzegovina (BAM КМ) </option><option value="BW" > Botswana (BWP P) </option><option value="BR" > Brazil (USD $) </option><option value="VG" > British Virgin Islands (USD $) </option><option value="BN" > Brunei (BND $) </option><option value="BG" > Bulgaria (BGN лв.) </option><option value="BF" > Burkina Faso (XOF Fr) </option><option value="BI" > Burundi (BIF Fr) </option><option value="KH" > Cambodia (KHR ៛) </option><option value="CM" > Cameroon (XAF Fr) </option><option value="CA" > Canada (CAD $) </option><option value="CV" > Cape Verde (CVE $) </option><option value="BQ" > Caribbean Netherlands (USD $) </option><option value="KY" > Cayman Islands (KYD $) </option><option value="CF" > Central African Republic (XAF Fr) </option><option value="TD" > Chad (XAF Fr) </option><option value="CL" > Chile (USD $) </option><option value="CN" > China (CNY ¥) </option><option value="CO" > Colombia (USD $) </option><option value="KM" > Comoros (KMF Fr) </option><option value="CG" > Congo - Brazzaville (XAF Fr) </option><option value="CD" > Congo - Kinshasa (CDF Fr) </option><option value="CK" > Cook Islands (NZD $) </option><option value="CR" > Costa Rica (CRC ₡) </option><option value="CI" > Côte d’Ivoire (XOF Fr) </option><option value="HR" > Croatia (EUR €) </option><option value="CW" > Curaçao (ANG ƒ) </option><option value="CY" > Cyprus (EUR €) </option><option value="CZ" > Czechia (CZK Kč) </option><option value="DK" > Denmark (DKK kr.) </option><option value="DJ" > Djibouti (DJF Fdj) </option><option value="DM" > Dominica (XCD $) </option><option value="DO" > Dominican Republic (DOP $) </option><option value="EC" > Ecuador (USD $) </option><option value="EG" > Egypt (EGP ج.م) </option><option value="SV" > El Salvador (USD $) </option><option value="GQ" > Equatorial Guinea (XAF Fr) </option><option value="ER" > Eritrea (USD $) </option><option value="EE" > Estonia (EUR €) </option><option value="SZ" > Eswatini (USD $) </option><option value="ET" > Ethiopia (ETB Br) </option><option value="FK" > Falkland Islands (FKP £) </option><option value="FO" > Faroe Islands (DKK kr.) </option><option value="FJ" > Fiji (FJD $) </option><option value="FI" > Finland (EUR €) </option><option value="FR" > France (EUR €) </option><option value="GF" > French Guiana (EUR €) </option><option value="PF" > French Polynesia (XPF Fr) </option><option value="GA" > Gabon (XOF Fr) </option><option value="GM" > Gambia (GMD D) </option><option value="GE" > Georgia (USD $) </option><option value="DE" > Germany (EUR €) </option><option value="GH" > Ghana (USD $) </option><option value="GI" > Gibraltar (GBP £) </option><option value="GR" > Greece (EUR €) </option><option value="GL" > Greenland (DKK kr.) </option><option value="GD" > Grenada (XCD $) </option><option value="GP" > Guadeloupe (EUR €) </option><option value="GT" > Guatemala (GTQ Q) </option><option value="GG" > Guernsey (GBP £) </option><option value="GN" > Guinea (GNF Fr) </option><option value="GW" > Guinea-Bissau (XOF Fr) </option><option value="GY" > Guyana (GYD $) </option><option value="HT" > Haiti (USD $) </option><option value="HN" > Honduras (HNL L) </option><option value="HK" > Hong Kong SAR (HKD $) </option><option value="HU" > Hungary (HUF Ft) </option><option value="IS" > Iceland (ISK kr) </option><option value="IN" > India (INR ₹) </option><option value="ID" > Indonesia (IDR Rp) </option><option value="IQ" > Iraq (USD $) </option><option value="IE" > Ireland (EUR €) </option><option value="IM" > Isle of Man (GBP £) </option><option value="IL" > Israel (ILS ₪) </option><option value="IT" > Italy (EUR €) </option><option value="JM" > Jamaica (JMD $) </option><option value="JP" > Japan (JPY ¥) </option><option value="JE" > Jersey (USD $) </option><option value="JO" > Jordan (USD $) </option><option value="KZ" > Kazakhstan (KZT 〒) </option><option value="KE" > Kenya (KES KSh) </option><option value="KI" > Kiribati (USD $) </option><option value="XK" > Kosovo (EUR €) </option><option value="KW" > Kuwait (USD $) </option><option value="KG" > Kyrgyzstan (KGS som) </option><option value="LA" > Laos (LAK ₭) </option><option value="LV" > Latvia (EUR €) </option><option value="LB" > Lebanon (LBP ل.ل) </option><option value="LS" > Lesotho (USD $) </option><option value="LR" > Liberia (USD $) </option><option value="LY" > Libya (USD $) </option><option value="LI" > Liechtenstein (CHF CHF) </option><option value="LT" > Lithuania (EUR €) </option><option value="LU" > Luxembourg (EUR €) </option><option value="MO" > Macao SAR (MOP P) </option><option value="MG" > Madagascar (USD $) </option><option value="MW" > Malawi (MWK MK) </option><option value="MY" > Malaysia (MYR RM) </option><option value="MV" > Maldives (MVR MVR) </option><option value="ML" > Mali (XOF Fr) </option><option value="MT" > Malta (EUR €) </option><option value="MQ" > Martinique (EUR €) </option><option value="MR" > Mauritania (USD $) </option><option value="MU" > Mauritius (MUR ₨) </option><option value="YT" > Mayotte (EUR €) </option><option value="MX" > Mexico (MXN $) </option><option value="MD" > Moldova (MDL L) </option><option value="MC" > Monaco (EUR €) </option><option value="MN" > Mongolia (MNT ₮) </option><option value="ME" > Montenegro (EUR €) </option><option value="MS" > Montserrat (XCD $) </option><option value="MA" > Morocco (MAD د.م.) </option><option value="MZ" > Mozambique (USD $) </option><option value="MM" > Myanmar (Burma) (MMK K) </option><option value="NA" > Namibia (USD $) </option><option value="NR" > Nauru (AUD $) </option><option value="NP" > Nepal (NPR ₨) </option><option value="NL" > Netherlands (EUR €) </option><option value="NC" > New Caledonia (XPF Fr) </option><option value="NZ" > New Zealand (NZD $) </option><option value="NI" > Nicaragua (NIO C$) </option><option value="NE" > Niger (XOF Fr) </option><option value="NG" > Nigeria (NGN ₦) </option><option value="NU" > Niue (NZD $) </option><option value="NF" > Norfolk Island (AUD $) </option><option value="MK" > North Macedonia (MKD ден) </option><option value="NO" > Norway (USD $) </option><option value="OM" > Oman (USD $) </option><option value="PK" > Pakistan (PKR ₨) </option><option value="PS" > Palestinian Territories (ILS ₪) </option><option value="PA" > Panama (USD $) </option><option value="PG" > Papua New Guinea (PGK K) </option><option value="PY" > Paraguay (PYG ₲) </option><option value="PE" > Peru (PEN S/.) </option><option value="PH" > Philippines (PHP ₱) </option><option value="PN" > Pitcairn Islands (NZD $) </option><option value="PL" > Poland (PLN zł) </option><option value="PT" > Portugal (EUR €) </option><option value="QA" > Qatar (QAR ر.ق) </option><option value="RE" > Réunion (EUR €) </option><option value="RO" > Romania (RON Lei) </option><option value="RU" > Russia (USD $) </option><option value="RW" > Rwanda (RWF FRw) </option><option value="WS" > Samoa (WST T) </option><option value="SM" > San Marino (EUR €) </option><option value="ST" > São Tomé &amp; Príncipe (STD Db) </option><option value="SA" > Saudi Arabia (SAR ر.س) </option><option value="SN" > Senegal (XOF Fr) </option><option value="RS" > Serbia (RSD РСД) </option><option value="SC" > Seychelles (USD $) </option><option value="SL" > Sierra Leone (SLL Le) </option><option value="SG" > Singapore (SGD $) </option><option value="SX" > Sint Maarten (ANG ƒ) </option><option value="SK" selected > Slovakia (EUR €) </option><option value="SI" > Slovenia (EUR €) </option><option value="SB" > Solomon Islands (SBD $) </option><option value="SO" > Somalia (USD $) </option><option value="ZA" > South Africa (USD $) </option><option value="KR" > South Korea (KRW ₩) </option><option value="SS" > South Sudan (USD $) </option><option value="ES" > Spain (EUR €) </option><option value="LK" > Sri Lanka (LKR ₨) </option><option value="BL" > St. Barthélemy (EUR €) </option><option value="SH" > St. Helena (SHP £) </option><option value="KN" > St. Kitts &amp; Nevis (XCD $) </option><option value="LC" > St. Lucia (XCD $) </option><option value="MF" > St. Martin (EUR €) </option><option value="PM" > St. Pierre &amp; Miquelon (EUR €) </option><option value="VC" > St. Vincent &amp; Grenadines (XCD $) </option><option value="SD" > Sudan (USD $) </option><option value="SR" > Suriname (USD $) </option><option value="SJ" > Svalbard &amp; Jan Mayen (USD $) </option><option value="SE" > Sweden (SEK kr) </option><option value="CH" > Switzerland (CHF CHF) </option><option value="TW" > Taiwan (TWD $) </option><option value="TJ" > Tajikistan (TJS ЅМ) </option><option value="TZ" > Tanzania (TZS Sh) </option><option value="TH" > Thailand (THB ฿) </option><option value="TL" > Timor-Leste (USD $) </option><option value="TG" > Togo (XOF Fr) </option><option value="TK" > Tokelau (NZD $) </option><option value="TO" > Tonga (TOP T$) </option><option value="TT" > Trinidad &amp; Tobago (TTD $) </option><option value="TA" > Tristan da Cunha (GBP £) </option><option value="TN" > Tunisia (USD $) </option><option value="TR" > Türkiye (USD $) </option><option value="TM" > Turkmenistan (USD $) </option><option value="TC" > Turks &amp; Caicos Islands (USD $) </option><option value="TV" > Tuvalu (AUD $) </option><option value="UM" > U.S. Outlying Islands (USD $) </option><option value="UG" > Uganda (UGX USh) </option><option value="UA" > Ukraine (UAH ₴) </option><option value="AE" > United Arab Emirates (AED د.إ) </option><option value="GB" > United Kingdom (GBP £) </option><option value="US" > United States (USD $) </option><option value="UY" > Uruguay (UYU $) </option><option value="UZ" > Uzbekistan (UZS ) </option><option value="VU" > Vanuatu (VUV Vt) </option><option value="VA" > Vatican City (EUR €) </option><option value="VE" > Venezuela (USD $) </option><option value="VN" > Vietnam (VND ₫) </option><option value="WF" > Wallis &amp; Futuna (XPF Fr) </option><option value="EH" > Western Sahara (MAD د.م.) </option><option value="YE" > Yemen (YER ﷼) </option><option value="ZM" > Zambia (USD $) </option><option value="ZW" > Zimbabwe (USD $) </option></select> <svg aria-hidden="true" focusable="false" class="icon icon-caret" viewBox="0 0 10 6"> <path fill-rule="evenodd" clip-rule="evenodd" d="M9.354.646a.5.5 0 00-.708 0L5 4.293 1.354.646a.5.5 0 00-.708.708l4 4a.5.5 0 00.708 0l4-4a.5.5 0 000-.708z" fill="currentColor"> </svg> </div> <button class="button button--tertiary">Update country/region</button></form> Country/region EUR € | Slovakia AFN ؋ | Afghanistan EUR € | Åland Islands ALL L | Albania DZD د.ج | Algeria EUR € | Andorra USD $ | Angola XCD $ | Anguilla XCD $ | Antigua & Barbuda USD $ | Argentina AMD դր. | Armenia AWG ƒ | Aruba SHP £ | Ascension Island AUD $ | Australia EUR € | Austria AZN ₼ | Azerbaijan BSD $ | Bahamas USD $ | Bahrain BDT ৳ | Bangladesh BBD $ | Barbados USD $ | Belarus EUR € | Belgium BZD $ | Belize XOF Fr | Benin USD $ | Bermuda USD $ | Bhutan BOB Bs. | Bolivia BAM КМ | Bosnia & Herzegovina BWP P | Botswana USD $ | Brazil USD $ | British Virgin Islands BND $ | Brunei BGN лв. | Bulgaria XOF Fr | Burkina Faso BIF Fr | Burundi KHR ៛ | Cambodia XAF Fr | Cameroon CAD $ | Canada CVE $ | Cape Verde USD $ | Caribbean Netherlands KYD $ | Cayman Islands XAF Fr | Central African Republic XAF Fr | Chad USD $ | Chile CNY ¥ | China USD $ | Colombia KMF Fr | Comoros XAF Fr | Congo - Brazzaville CDF Fr | Congo - Kinshasa NZD $ | Cook Islands CRC ₡ | Costa Rica XOF Fr | Côte d’Ivoire EUR € | Croatia ANG ƒ | Curaçao EUR € | Cyprus CZK Kč | Czechia DKK kr. | Denmark DJF Fdj | Djibouti XCD $ | Dominica DOP $ | Dominican Republic USD $ | Ecuador EGP ج.م | Egypt USD $ | El Salvador XAF Fr | Equatorial Guinea USD $ | Eritrea EUR € | Estonia USD $ | Eswatini ETB Br | Ethiopia FKP £ | Falkland Islands DKK kr. | Faroe Islands FJD $ | Fiji EUR € | Finland EUR € | France EUR € | French Guiana XPF Fr | French Polynesia XOF Fr | Gabon GMD D | Gambia USD $ | Georgia EUR € | Germany USD $ | Ghana GBP £ | Gibraltar EUR € | Greece DKK kr. | Greenland XCD $ | Grenada EUR € | Guadeloupe GTQ Q | Guatemala GBP £ | Guernsey GNF Fr | Guinea XOF Fr | Guinea-Bissau GYD $ | Guyana USD $ | Haiti HNL L | Honduras HKD $ | Hong Kong SAR HUF Ft | Hungary ISK kr | Iceland INR ₹ | India IDR Rp | Indonesia USD $ | Iraq EUR € | Ireland GBP £ | Isle of Man ILS ₪ | Israel EUR € | Italy JMD $ | Jamaica JPY ¥ | Japan USD $ | Jersey USD $ | Jordan KZT 〒 | Kazakhstan KES KSh | Kenya USD $ | Kiribati EUR € | Kosovo USD $ | Kuwait KGS som | Kyrgyzstan LAK ₭ | Laos EUR € | Latvia LBP ل.ل | Lebanon USD $ | Lesotho USD $ | Liberia USD $ | Libya CHF CHF | Liechtenstein EUR € | Lithuania EUR € | Luxembourg MOP P | Macao SAR USD $ | Madagascar MWK MK | Malawi MYR RM | Malaysia MVR MVR | Maldives XOF Fr | Mali EUR € | Malta EUR € | Martinique USD $ | Mauritania MUR ₨ | Mauritius EUR € | Mayotte MXN $ | Mexico MDL L | Moldova EUR € | Monaco MNT ₮ | Mongolia EUR € | Montenegro XCD $ | Montserrat MAD د.م. | Morocco USD $ | Mozambique MMK K | Myanmar (Burma) USD $ | Namibia AUD $ | Nauru NPR ₨ | Nepal EUR € | Netherlands XPF Fr | New Caledonia NZD $ | New Zealand NIO C$ | Nicaragua XOF Fr | Niger NGN ₦ | Nigeria NZD $ | Niue AUD $ | Norfolk Island MKD ден | North Macedonia USD $ | Norway USD $ | Oman PKR ₨ | Pakistan ILS ₪ | Palestinian Territories USD $ | Panama PGK K | Papua New Guinea PYG ₲ | Paraguay PEN S/. | Peru PHP ₱ | Philippines NZD $ | Pitcairn Islands PLN zł | Poland EUR € | Portugal QAR ر.ق | Qatar EUR € | Réunion RON Lei | Romania USD $ | Russia RWF FRw | Rwanda WST T | Samoa EUR € | San Marino STD Db | São Tomé & Príncipe SAR ر.س | Saudi Arabia XOF Fr | Senegal RSD РСД | Serbia USD $ | Seychelles SLL Le | Sierra Leone SGD $ | Singapore ANG ƒ | Sint Maarten EUR € | Slovakia EUR € | Slovenia SBD $ | Solomon Islands USD $ | Somalia USD $ | South Africa KRW ₩ | South Korea USD $ | South Sudan EUR € | Spain LKR ₨ | Sri Lanka EUR € | St. Barthélemy SHP £ | St. Helena XCD $ | St. Kitts & Nevis XCD $ | St. Lucia EUR € | St. Martin EUR € | St. Pierre & Miquelon XCD $ | St. Vincent & Grenadines USD $ | Sudan USD $ | Suriname USD $ | Svalbard & Jan Mayen SEK kr | Sweden CHF CHF | Switzerland TWD $ | Taiwan TJS ЅМ | Tajikistan TZS Sh | Tanzania THB ฿ | Thailand USD $ | Timor-Leste XOF Fr | Togo NZD $ | Tokelau TOP T$ | Tonga TTD $ | Trinidad & Tobago GBP £ | Tristan da Cunha USD $ | Tunisia USD $ | Türkiye USD $ | Turkmenistan USD $ | Turks & Caicos Islands AUD $ | Tuvalu USD $ | U.S. Outlying Islands UGX USh | Uganda UAH ₴ | Ukraine AED د.إ | United Arab Emirates GBP £ | United Kingdom USD $ | United States UYU $ | Uruguay UZS | Uzbekistan VUV Vt | Vanuatu EUR € | Vatican City USD $ | Venezuela VND ₫ | Vietnam XPF Fr | Wallis & Futuna MAD د.م. | Western Sahara YER ﷼ | Yemen USD $ | Zambia USD $ | Zimbabwe Twitter Facebook Instagram TikTok Snapchat YouTube Search Home page The Love Album: Off The Grid Contact <form method="post" action="/localization" id="HeaderCountryMobileFormNoScript" accept-charset="UTF-8" class="localization-form" enctype="multipart/form-data"><input type="hidden" name="form_type" value="localization" /><input type="hidden" name="utf8" value="✓" /><input type="hidden" name="_method" value="put" /><input type="hidden" name="return_to" value="/" /><div class="localization-form__select"> <h2 class="visually-hidden" id="HeaderCountryMobileLabelNoScript">Country/region</h2> <select class="localization-selector link" name="country_code" aria-labelledby="HeaderCountryMobileLabelNoScript"><option value="AF"> Afghanistan (AFN ؋) </option><option value="AX"> Åland Islands (EUR €) </option><option value="AL"> Albania (ALL L) </option><option value="DZ"> Algeria (DZD د.ج) </option><option value="AD"> Andorra (EUR €) </option><option value="AO"> Angola (USD $) </option><option value="AI"> Anguilla (XCD $) </option><option value="AG"> Antigua &amp; Barbuda (XCD $) </option><option value="AR"> Argentina (USD $) </option><option value="AM"> Armenia (AMD դր.) </option><option value="AW"> Aruba (AWG ƒ) </option><option value="AC"> Ascension Island (SHP £) </option><option value="AU"> Australia (AUD $) </option><option value="AT"> Austria (EUR €) </option><option value="AZ"> Azerbaijan (AZN ₼) </option><option value="BS"> Bahamas (BSD $) </option><option value="BH"> Bahrain (USD $) </option><option value="BD"> Bangladesh (BDT ৳) </option><option value="BB"> Barbados (BBD $) </option><option value="BY"> Belarus (USD $) </option><option value="BE"> Belgium (EUR €) </option><option value="BZ"> Belize (BZD $) </option><option value="BJ"> Benin (XOF Fr) </option><option value="BM"> Bermuda (USD $) </option><option value="BT"> Bhutan (USD $) </option><option value="BO"> Bolivia (BOB Bs.) </option><option value="BA"> Bosnia &amp; Herzegovina (BAM КМ) </option><option value="BW"> Botswana (BWP P) </option><option value="BR"> Brazil (USD $) </option><option value="VG"> British Virgin Islands (USD $) </option><option value="BN"> Brunei (BND $) </option><option value="BG"> Bulgaria (BGN лв.) </option><option value="BF"> Burkina Faso (XOF Fr) </option><option value="BI"> Burundi (BIF Fr) </option><option value="KH"> Cambodia (KHR ៛) </option><option value="CM"> Cameroon (XAF Fr) </option><option value="CA"> Canada (CAD $) </option><option value="CV"> Cape Verde (CVE $) </option><option value="BQ"> Caribbean Netherlands (USD $) </option><option value="KY"> Cayman Islands (KYD $) </option><option value="CF"> Central African Republic (XAF Fr) </option><option value="TD"> Chad (XAF Fr) </option><option value="CL"> Chile (USD $) </option><option value="CN"> China (CNY ¥) </option><option value="CO"> Colombia (USD $) </option><option value="KM"> Comoros (KMF Fr) </option><option value="CG"> Congo - Brazzaville (XAF Fr) </option><option value="CD"> Congo - Kinshasa (CDF Fr) </option><option value="CK"> Cook Islands (NZD $) </option><option value="CR"> Costa Rica (CRC ₡) </option><option value="CI"> Côte d’Ivoire (XOF Fr) </option><option value="HR"> Croatia (EUR €) </option><option value="CW"> Curaçao (ANG ƒ) </option><option value="CY"> Cyprus (EUR €) </option><option value="CZ"> Czechia (CZK Kč) </option><option value="DK"> Denmark (DKK kr.) </option><option value="DJ"> Djibouti (DJF Fdj) </option><option value="DM"> Dominica (XCD $) </option><option value="DO"> Dominican Republic (DOP $) </option><option value="EC"> Ecuador (USD $) </option><option value="EG"> Egypt (EGP ج.م) </option><option value="SV"> El Salvador (USD $) </option><option value="GQ"> Equatorial Guinea (XAF Fr) </option><option value="ER"> Eritrea (USD $) </option><option value="EE"> Estonia (EUR €) </option><option value="SZ"> Eswatini (USD $) </option><option value="ET"> Ethiopia (ETB Br) </option><option value="FK"> Falkland Islands (FKP £) </option><option value="FO"> Faroe Islands (DKK kr.) </option><option value="FJ"> Fiji (FJD $) </option><option value="FI"> Finland (EUR €) </option><option value="FR"> France (EUR €) </option><option value="GF"> French Guiana (EUR €) </option><option value="PF"> French Polynesia (XPF Fr) </option><option value="GA"> Gabon (XOF Fr) </option><option value="GM"> Gambia (GMD D) </option><option value="GE"> Georgia (USD $) </option><option value="DE"> Germany (EUR €) </option><option value="GH"> Ghana (USD $) </option><option value="GI"> Gibraltar (GBP £) </option><option value="GR"> Greece (EUR €) </option><option value="GL"> Greenland (DKK kr.) </option><option value="GD"> Grenada (XCD $) </option><option value="GP"> Guadeloupe (EUR €) </option><option value="GT"> Guatemala (GTQ Q) </option><option value="GG"> Guernsey (GBP £) </option><option value="GN"> Guinea (GNF Fr) </option><option value="GW"> Guinea-Bissau (XOF Fr) </option><option value="GY"> Guyana (GYD $) </option><option value="HT"> Haiti (USD $) </option><option value="HN"> Honduras (HNL L) </option><option value="HK"> Hong Kong SAR (HKD $) </option><option value="HU"> Hungary (HUF Ft) </option><option value="IS"> Iceland (ISK kr) </option><option value="IN"> India (INR ₹) </option><option value="ID"> Indonesia (IDR Rp) </option><option value="IQ"> Iraq (USD $) </option><option value="IE"> Ireland (EUR €) </option><option value="IM"> Isle of Man (GBP £) </option><option value="IL"> Israel (ILS ₪) </option><option value="IT"> Italy (EUR €) </option><option value="JM"> Jamaica (JMD $) </option><option value="JP"> Japan (JPY ¥) </option><option value="JE"> Jersey (USD $) </option><option value="JO"> Jordan (USD $) </option><option value="KZ"> Kazakhstan (KZT 〒) </option><option value="KE"> Kenya (KES KSh) </option><option value="KI"> Kiribati (USD $) </option><option value="XK"> Kosovo (EUR €) </option><option value="KW"> Kuwait (USD $) </option><option value="KG"> Kyrgyzstan (KGS som) </option><option value="LA"> Laos (LAK ₭) </option><option value="LV"> Latvia (EUR €) </option><option value="LB"> Lebanon (LBP ل.ل) </option><option value="LS"> Lesotho (USD $) </option><option value="LR"> Liberia (USD $) </option><option value="LY"> Libya (USD $) </option><option value="LI"> Liechtenstein (CHF CHF) </option><option value="LT"> Lithuania (EUR €) </option><option value="LU"> Luxembourg (EUR €) </option><option value="MO"> Macao SAR (MOP P) </option><option value="MG"> Madagascar (USD $) </option><option value="MW"> Malawi (MWK MK) </option><option value="MY"> Malaysia (MYR RM) </option><option value="MV"> Maldives (MVR MVR) </option><option value="ML"> Mali (XOF Fr) </option><option value="MT"> Malta (EUR €) </option><option value="MQ"> Martinique (EUR €) </option><option value="MR"> Mauritania (USD $) </option><option value="MU"> Mauritius (MUR ₨) </option><option value="YT"> Mayotte (EUR €) </option><option value="MX"> Mexico (MXN $) </option><option value="MD"> Moldova (MDL L) </option><option value="MC"> Monaco (EUR €) </option><option value="MN"> Mongolia (MNT ₮) </option><option value="ME"> Montenegro (EUR €) </option><option value="MS"> Montserrat (XCD $) </option><option value="MA"> Morocco (MAD د.م.) </option><option value="MZ"> Mozambique (USD $) </option><option value="MM"> Myanmar (Burma) (MMK K) </option><option value="NA"> Namibia (USD $) </option><option value="NR"> Nauru (AUD $) </option><option value="NP"> Nepal (NPR ₨) </option><option value="NL"> Netherlands (EUR €) </option><option value="NC"> New Caledonia (XPF Fr) </option><option value="NZ"> New Zealand (NZD $) </option><option value="NI"> Nicaragua (NIO C$) </option><option value="NE"> Niger (XOF Fr) </option><option value="NG"> Nigeria (NGN ₦) </option><option value="NU"> Niue (NZD $) </option><option value="NF"> Norfolk Island (AUD $) </option><option value="MK"> North Macedonia (MKD ден) </option><option value="NO"> Norway (USD $) </option><option value="OM"> Oman (USD $) </option><option value="PK"> Pakistan (PKR ₨) </option><option value="PS"> Palestinian Territories (ILS ₪) </option><option value="PA"> Panama (USD $) </option><option value="PG"> Papua New Guinea (PGK K) </option><option value="PY"> Paraguay (PYG ₲) </option><option value="PE"> Peru (PEN S/.) </option><option value="PH"> Philippines (PHP ₱) </option><option value="PN"> Pitcairn Islands (NZD $) </option><option value="PL"> Poland (PLN zł) </option><option value="PT"> Portugal (EUR €) </option><option value="QA"> Qatar (QAR ر.ق) </option><option value="RE"> Réunion (EUR €) </option><option value="RO"> Romania (RON Lei) </option><option value="RU"> Russia (USD $) </option><option value="RW"> Rwanda (RWF FRw) </option><option value="WS"> Samoa (WST T) </option><option value="SM"> San Marino (EUR €) </option><option value="ST"> São Tomé &amp; Príncipe (STD Db) </option><option value="SA"> Saudi Arabia (SAR ر.س) </option><option value="SN"> Senegal (XOF Fr) </option><option value="RS"> Serbia (RSD РСД) </option><option value="SC"> Seychelles (USD $) </option><option value="SL"> Sierra Leone (SLL Le) </option><option value="SG"> Singapore (SGD $) </option><option value="SX"> Sint Maarten (ANG ƒ) </option><option value="SK" selected> Slovakia (EUR €) </option><option value="SI"> Slovenia (EUR €) </option><option value="SB"> Solomon Islands (SBD $) </option><option value="SO"> Somalia (USD $) </option><option value="ZA"> South Africa (USD $) </option><option value="KR"> South Korea (KRW ₩) </option><option value="SS"> South Sudan (USD $) </option><option value="ES"> Spain (EUR €) </option><option value="LK"> Sri Lanka (LKR ₨) </option><option value="BL"> St. Barthélemy (EUR €) </option><option value="SH"> St. Helena (SHP £) </option><option value="KN"> St. Kitts &amp; Nevis (XCD $) </option><option value="LC"> St. Lucia (XCD $) </option><option value="MF"> St. Martin (EUR €) </option><option value="PM"> St. Pierre &amp; Miquelon (EUR €) </option><option value="VC"> St. Vincent &amp; Grenadines (XCD $) </option><option value="SD"> Sudan (USD $) </option><option value="SR"> Suriname (USD $) </option><option value="SJ"> Svalbard &amp; Jan Mayen (USD $) </option><option value="SE"> Sweden (SEK kr) </option><option value="CH"> Switzerland (CHF CHF) </option><option value="TW"> Taiwan (TWD $) </option><option value="TJ"> Tajikistan (TJS ЅМ) </option><option value="TZ"> Tanzania (TZS Sh) </option><option value="TH"> Thailand (THB ฿) </option><option value="TL"> Timor-Leste (USD $) </option><option value="TG"> Togo (XOF Fr) </option><option value="TK"> Tokelau (NZD $) </option><option value="TO"> Tonga (TOP T$) </option><option value="TT"> Trinidad &amp; Tobago (TTD $) </option><option value="TA"> Tristan da Cunha (GBP £) </option><option value="TN"> Tunisia (USD $) </option><option value="TR"> Türkiye (USD $) </option><option value="TM"> Turkmenistan (USD $) </option><option value="TC"> Turks &amp; Caicos Islands (USD $) </option><option value="TV"> Tuvalu (AUD $) </option><option value="UM"> U.S. Outlying Islands (USD $) </option><option value="UG"> Uganda (UGX USh) </option><option value="UA"> Ukraine (UAH ₴) </option><option value="AE"> United Arab Emirates (AED د.إ) </option><option value="GB"> United Kingdom (GBP £) </option><option value="US"> United States (USD $) </option><option value="UY"> Uruguay (UYU $) </option><option value="UZ"> Uzbekistan (UZS ) </option><option value="VU"> Vanuatu (VUV Vt) </option><option value="VA"> Vatican City (EUR €) </option><option value="VE"> Venezuela (USD $) </option><option value="VN"> Vietnam (VND ₫) </option><option value="WF"> Wallis &amp; Futuna (XPF Fr) </option><option value="EH"> Western Sahara (MAD د.م.) </option><option value="YE"> Yemen (YER ﷼) </option><option value="ZM"> Zambia (USD $) </option><option value="ZW"> Zimbabwe (USD $) </option></select> <svg aria-hidden="true" focusable="false" class="icon icon-caret" viewBox="0 0 10 6"> <path fill-rule="evenodd" clip-rule="evenodd" d="M9.354.646a.5.5 0 00-.708 0L5 4.293 1.354.646a.5.5 0 00-.708.708l4 4a.5.5 0 00.708 0l4-4a.5.5 0 000-.708z" fill="currentColor"> </svg> </div> <button class="button button--tertiary">Update country/region</button></form> Country/region EUR € | Slovakia AFN ؋ | Afghanistan EUR € | Åland Islands ALL L | Albania DZD د.ج | Algeria EUR € | Andorra USD $ | Angola XCD $ | Anguilla XCD $ | Antigua & Barbuda USD $ | Argentina AMD դր. | Armenia AWG ƒ | Aruba SHP £ | Ascension Island AUD $ | Australia EUR € | Austria AZN ₼ | Azerbaijan BSD $ | Bahamas USD $ | Bahrain BDT ৳ | Bangladesh BBD $ | Barbados USD $ | Belarus EUR € | Belgium BZD $ | Belize XOF Fr | Benin USD $ | Bermuda USD $ | Bhutan BOB Bs. | Bolivia BAM КМ | Bosnia & Herzegovina BWP P | Botswana USD $ | Brazil USD $ | British Virgin Islands BND $ | Brunei BGN лв. | Bulgaria XOF Fr | Burkina Faso BIF Fr | Burundi KHR ៛ | Cambodia XAF Fr | Cameroon CAD $ | Canada CVE $ | Cape Verde USD $ | Caribbean Netherlands KYD $ | Cayman Islands XAF Fr | Central African Republic XAF Fr | Chad USD $ | Chile CNY ¥ | China USD $ | Colombia KMF Fr | Comoros XAF Fr | Congo - Brazzaville CDF Fr | Congo - Kinshasa NZD $ | Cook Islands CRC ₡ | Costa Rica XOF Fr | Côte d’Ivoire EUR € | Croatia ANG ƒ | Curaçao EUR € | Cyprus CZK Kč | Czechia DKK kr. | Denmark DJF Fdj | Djibouti XCD $ | Dominica DOP $ | Dominican Republic USD $ | Ecuador EGP ج.م | Egypt USD $ | El Salvador XAF Fr | Equatorial Guinea USD $ | Eritrea EUR € | Estonia USD $ | Eswatini ETB Br | Ethiopia FKP £ | Falkland Islands DKK kr. | Faroe Islands FJD $ | Fiji EUR € | Finland EUR € | France EUR € | French Guiana XPF Fr | French Polynesia XOF Fr | Gabon GMD D | Gambia USD $ | Georgia EUR € | Germany USD $ | Ghana GBP £ | Gibraltar EUR € | Greece DKK kr. | Greenland XCD $ | Grenada EUR € | Guadeloupe GTQ Q | Guatemala GBP £ | Guernsey GNF Fr | Guinea XOF Fr | Guinea-Bissau GYD $ | Guyana USD $ | Haiti HNL L | Honduras HKD $ | Hong Kong SAR HUF Ft | Hungary ISK kr | Iceland INR ₹ | India IDR Rp | Indonesia USD $ | Iraq EUR € | Ireland GBP £ | Isle of Man ILS ₪ | Israel EUR € | Italy JMD $ | Jamaica JPY ¥ | Japan USD $ | Jersey USD $ | Jordan KZT 〒 | Kazakhstan KES KSh | Kenya USD $ | Kiribati EUR € | Kosovo USD $ | Kuwait KGS som | Kyrgyzstan LAK ₭ | Laos EUR € | Latvia LBP ل.ل | Lebanon USD $ | Lesotho USD $ | Liberia USD $ | Libya CHF CHF | Liechtenstein EUR € | Lithuania EUR € | Luxembourg MOP P | Macao SAR USD $ | Madagascar MWK MK | Malawi MYR RM | Malaysia MVR MVR | Maldives XOF Fr | Mali EUR € | Malta EUR € | Martinique USD $ | Mauritania MUR ₨ | Mauritius EUR € | Mayotte MXN $ | Mexico MDL L | Moldova EUR € | Monaco MNT ₮ | Mongolia EUR € | Montenegro XCD $ | Montserrat MAD د.م. | Morocco USD $ | Mozambique MMK K | Myanmar (Burma) USD $ | Namibia AUD $ | Nauru NPR ₨ | Nepal EUR € | Netherlands XPF Fr | New Caledonia NZD $ | New Zealand NIO C$ | Nicaragua XOF Fr | Niger NGN ₦ | Nigeria NZD $ | Niue AUD $ | Norfolk Island MKD ден | North Macedonia USD $ | Norway USD $ | Oman PKR ₨ | Pakistan ILS ₪ | Palestinian Territories USD $ | Panama PGK K | Papua New Guinea PYG ₲ | Paraguay PEN S/. | Peru PHP ₱ | Philippines NZD $ | Pitcairn Islands PLN zł | Poland EUR € | Portugal QAR ر.ق | Qatar EUR € | Réunion RON Lei | Romania USD $ | Russia RWF FRw | Rwanda WST T | Samoa EUR € | San Marino STD Db | São Tomé & Príncipe SAR ر.س | Saudi Arabia XOF Fr | Senegal RSD РСД | Serbia USD $ | Seychelles SLL Le | Sierra Leone SGD $ | Singapore ANG ƒ | Sint Maarten EUR € | Slovakia EUR € | Slovenia SBD $ | Solomon Islands USD $ | Somalia USD $ | South Africa KRW ₩ | South Korea USD $ | South Sudan EUR € | Spain LKR ₨ | Sri Lanka EUR € | St. Barthélemy SHP £ | St. Helena XCD $ | St. Kitts & Nevis XCD $ | St. Lucia EUR € | St. Martin EUR € | St. Pierre & Miquelon XCD $ | St. Vincent & Grenadines USD $ | Sudan USD $ | Suriname USD $ | Svalbard & Jan Mayen SEK kr | Sweden CHF CHF | Switzerland TWD $ | Taiwan TJS ЅМ | Tajikistan TZS Sh | Tanzania THB ฿ | Thailand USD $ | Timor-Leste XOF Fr | Togo NZD $ | Tokelau TOP T$ | Tonga TTD $ | Trinidad & Tobago GBP £ | Tristan da Cunha USD $ | Tunisia USD $ | Türkiye USD $ | Turkmenistan USD $ | Turks & Caicos Islands AUD $ | Tuvalu USD $ | U.S. Outlying Islands UGX USh | Uganda UAH ₴ | Ukraine AED د.إ | United Arab Emirates GBP £ | United Kingdom USD $ | United States UYU $ | Uruguay UZS | Uzbekistan VUV Vt | Vanuatu EUR € | Vatican City USD $ | Venezuela VND ₫ | Vietnam XPF Fr | Wallis & Futuna MAD د.م. | Western Sahara YER ﷼ | Yemen USD $ | Zambia USD $ | Zimbabwe Search Log in Cart Item added to your cart View cart Check out Continue shopping .cart-notification { display: none; } { "@context": "http://schema.org", "@type": "Organization", "name": "DIDDY", "logo": "https:\/\/diddy.com\/cdn\/shop\/files\/LOGO_copy.png?v=1687218799\u0026width=500", "sameAs": [ "https:\/\/twitter.com\/diddy", "https:\/\/www.facebook.com\/Diddy", "", "https:\/\/www.instagram.com\/diddy\/", "https:\/\/www.tiktok.com\/@diddy?lang=en", "", "https:\/\/www.snapchat.com\/add\/puffdaddy?web_client_id=a5643135-4b9c-489e-be5a-a7a04bc17ca8", "https:\/\/youtube.com\/diddy", "" ], "url": "https:\/\/diddy.com" } { "@context": "http://schema.org", "@type": "WebSite", "name": "DIDDY", "potentialAction": { "@type": "SearchAction", "target": "https:\/\/diddy.com\/search?q={search_term_string}", "query-input": "required name=search_term_string" }, "url": "https:\/\/diddy.com" } @media screen and (max-width: 749px) { #Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14::before, #Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14 .banner__media::before, #Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14:not(.banner--mobile-bottom) .banner__content::before { padding-bottom: 100.0%; content: ''; display: block; } } @media screen and (min-width: 750px) { #Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14::before, #Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14 .banner__media::before { padding-bottom: 100.0%; content: ''; display: block; } }#Banner-template--21312169541928__1fee5694-1b2d-4712-b35d-8a2a2dcf6e14::after { opacity: 0.0; } .section-template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13-padding { padding-top: 27px; padding-bottom: 27px; } @media screen and (min-width: 750px) { .section-template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13-padding { padding-top: 36px; padding-bottom: 36px; } } <div class="product__media media"> <img src="//diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1946" alt="" srcset="//diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=246 246w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=493 493w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=600 600w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=713 713w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=823 823w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=990 990w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1100 1100w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1206 1206w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1346 1346w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1426 1426w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1646 1646w, //diddy.com/cdn/shop/files/COVER_VINYL_FRONT.png?v=1696881212&amp;width=1946 1946w" width="1946" height="1946" loading="lazy" sizes="(min-width: 1200px) 605px, (min-width: 990px) calc(55.0vw - 10rem), (min-width: 750px) calc((100vw - 11.5rem) / 2), calc(100vw / 1 - 4rem)"> </div> Open media 1 in modal DIDDYThe Love Album: Off The Grid – Standard Double Red Vinyl Add to cart More payment options#more-payment-options-link{cursor:pointer} View full details { "@context": "http://schema.org/", "@type": "Product", "name": "The Love Album: Off The Grid – Standard Double Red Vinyl", "url": "https:\/\/diddy.com\/products\/the-love-album-off-the-grid-standard-double-red-vinyl", "image": [ "https:\/\/diddy.com\/cdn\/shop\/files\/COVER_VINYL_FRONT.png?v=1696881212\u0026width=1920" ], "description": "\n‘The Love Album: Off The Grid’\nDouble LP (2 Discs)\nCustom Opaque Red Vinyl Discs with Printed Inner Sleeves\n \nSIDE A:\nBrought My Love (Diddy feat. The-Dream \u0026amp; Herb Alpert\nWhat's Love (Diddy, NOVA WAV)\nDeliver Me (Diddy, Busta Rhymes, Dirty Money, Dawn Richard, Kalenna)\nStay Awhile (Diddy, Nija)\nHomecoming (Diddy, Jozzy)\nPick Up (Diddy, Jacquees feat. Fabolous)\n \nSIDE B:\nTough Love (Diddy feat. Swae Lee) \nStay Long (Diddy feat. Summer Walker) \nIt Belongs to You (Diddy, Jozzy) \nAnother One of Me (Diddy, The Weeknd, French Montana feat. 21 Savage)\nIntermission (Side B)\nMoments (Diddy feat. Justin Bieber) \n \nSIDE C:\nNeed Somebody (Diddy, Jazmine Sullivan)\nBosses In Love (Diddy, NOVA WAV)\nMind Your Business (Diddy feat. Ty Dolla $ign, Kehlani)\nNasty (Interlude) (Diddy, Jozzy) \nReachin' (Diddy feat. Ty Dolla $ign, Coco Jones)\nStay Pt. 1 (Diddy, Kalan.FrFr, K-Ci Hailey feat. Jeremih)\nI Like (Diddy, Mary J. Blige)\n \nSIDE D: \nCloser to God (Diddy feat. Teyana Taylor)\nBoohoo (Diddy feat. Jeremih)\nBurna Boy Interlude (Diddy feat. Burna Boy)\nKim Porter (Diddy, Babyface feat. John Legend)\nSpace (Diddy, H.E.R.)", "sku": "500", "brand": { "@type": "Brand", "name": "DIDDY" }, "offers": [{ "@type" : "Offer","sku": "500","gtin12": 193436353519,"availability" : "http://schema.org/InStock", "price" : 36.95, "priceCurrency" : "EUR", "url" : "https:\/\/diddy.com\/products\/the-love-album-off-the-grid-standard-double-red-vinyl?variant=46922529898792" } ] } document.addEventListener('DOMContentLoaded', function () { function isIE() { const ua = window.navigator.userAgent; const msie = ua.indexOf('MSIE '); const trident = ua.indexOf('Trident/'); return msie > 0 || trident > 0; } if (!isIE()) return; const hiddenInput = document.querySelector('#product-form-template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13 input[name="id"]'); const noScriptInputWrapper = document.createElement('div'); const variantSwitcher = document.querySelector('variant-radios[data-section="template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13"]') || document.querySelector('variant-selects[data-section="template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13"]'); noScriptInputWrapper.innerHTML = document.querySelector( '.product-form__noscript-wrapper-template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13' ).textContent; variantSwitcher.outerHTML = noScriptInputWrapper.outerHTML; document.querySelector('#Variants-template--21312169541928__1bca3c7e-feb9-41bc-88ea-6e3d6a859a13').addEventListener('change', function (event) { hiddenInput.value = event.currentTarget.value; }); }); .section-template--21312169541928__e94c0218-3c4c-4a2e-b302-5cc495bf14d5-padding { padding-top: 27px; padding-bottom: 27px; } @media screen and (min-width: 750px) { .section-template--21312169541928__e94c0218-3c4c-4a2e-b302-5cc495bf14d5-padding { padding-top: 36px; padding-bottom: 36px; } } The Love Album: Off The Grid - Official Merch The Love Album: Off The Grid - Digital Album The Love Album: Off The Grid - Digital Album Regular price €14,95 EUR Regular price Sale price €14,95 EUR Unit price /  per  The Love Album: Off The Grid – Standard Double Red Vinyl The Love Album: Off The Grid – Standard Double Red Vinyl Regular price €36,95 EUR Regular price Sale price €36,95 EUR Unit price /  per  .section-template--21312169541928__6b33365c-58ac-4cdc-a1eb-4b638784ad77-padding { padding-top: 27px; padding-bottom: 42px; } @media screen and (min-width: 750px) { .section-template--21312169541928__6b33365c-58ac-4cdc-a1eb-4b638784ad77-padding { padding-top: 36px; padding-bottom: 56px; } } Diddy - Closer To God (ft. Teyana Taylor) [Official Video] <div class="video-section__media" style="--ratio-percent: 100.0%;" ><a href="https://www.youtube.com/watch?v=aPF3l1p8GKY" class="video-section__poster media media--transparent" ><img src="//diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=3840" alt="Load video: " srcset="//diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=375 375w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=750 750w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=1100 1100w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=1500 1500w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=1780 1780w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=2000 2000w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=3000 3000w, //diddy.com/cdn/shop/files/closer_to_god_v3_de6e5843-a3bc-487d-9a9f-2f2ee5b1e992.jpg?v=1697063908&amp;width=3840 3840w" width="3840" height="3840" loading="lazy" sizes="(min-width: 1200px) 1100px, (min-width: 750px) calc(100vw - 10rem), 100vw "> </a></div> .footer { margin-top: 0px; } .section-sections--21312164528424__footer-padding { padding-top: 30px; padding-bottom: 27px; } @media screen and (min-width: 750px) { .footer { margin-top: 0px; } .section-sections--21312164528424__footer-padding { padding-top: 40px; padding-bottom: 36px; } }SUBSCRIBE FOR UPDATES & ANNOUNCEMENTS Email Facebook Instagram YouTube TikTok Twitter Snapchat <form method="post" action="/localization" id="FooterCountryFormNoScript" accept-charset="UTF-8" class="localization-form" enctype="multipart/form-data"><input type="hidden" name="form_type" value="localization" /><input type="hidden" name="utf8" value="✓" /><input type="hidden" name="_method" value="put" /><input type="hidden" name="return_to" value="/" /><div class="localization-form__select"> <h2 class="visually-hidden" id="FooterCountryLabelNoScript">Country/region</h2> <select class="localization-selector link" name="country_code" aria-labelledby="FooterCountryLabelNoScript" ><option value="AF" > Afghanistan (AFN ؋) </option><option value="AX" > Åland Islands (EUR €) </option><option value="AL" > Albania (ALL L) </option><option value="DZ" > Algeria (DZD د.ج) </option><option value="AD" > Andorra (EUR €) </option><option value="AO" > Angola (USD $) </option><option value="AI" > Anguilla (XCD $) </option><option value="AG" > Antigua &amp; Barbuda (XCD $) </option><option value="AR" > Argentina (USD $) </option><option value="AM" > Armenia (AMD դր.) </option><option value="AW" > Aruba (AWG ƒ) </option><option value="AC" > Ascension Island (SHP £) </option><option value="AU" > Australia (AUD $) </option><option value="AT" > Austria (EUR €) </option><option value="AZ" > Azerbaijan (AZN ₼) </option><option value="BS" > Bahamas (BSD $) </option><option value="BH" > Bahrain (USD $) </option><option value="BD" > Bangladesh (BDT ৳) </option><option value="BB" > Barbados (BBD $) </option><option value="BY" > Belarus (USD $) </option><option value="BE" > Belgium (EUR €) </option><option value="BZ" > Belize (BZD $) </option><option value="BJ" > Benin (XOF Fr) </option><option value="BM" > Bermuda (USD $) </option><option value="BT" > Bhutan (USD $) </option><option value="BO" > Bolivia (BOB Bs.) </option><option value="BA" > Bosnia &amp; Herzegovina (BAM КМ) </option><option value="BW" > Botswana (BWP P) </option><option value="BR" > Brazil (USD $) </option><option value="VG" > British Virgin Islands (USD $) </option><option value="BN" > Brunei (BND $) </option><option value="BG" > Bulgaria (BGN лв.) </option><option value="BF" > Burkina Faso (XOF Fr) </option><option value="BI" > Burundi (BIF Fr) </option><option value="KH" > Cambodia (KHR ៛) </option><option value="CM" > Cameroon (XAF Fr) </option><option value="CA" > Canada (CAD $) </option><option value="CV" > Cape Verde (CVE $) </option><option value="BQ" > Caribbean Netherlands (USD $) </option><option value="KY" > Cayman Islands (KYD $) </option><option value="CF" > Central African Republic (XAF Fr) </option><option value="TD" > Chad (XAF Fr) </option><option value="CL" > Chile (USD $) </option><option value="CN" > China (CNY ¥) </option><option value="CO" > Colombia (USD $) </option><option value="KM" > Comoros (KMF Fr) </option><option value="CG" > Congo - Brazzaville (XAF Fr) </option><option value="CD" > Congo - Kinshasa (CDF Fr) </option><option value="CK" > Cook Islands (NZD $) </option><option value="CR" > Costa Rica (CRC ₡) </option><option value="CI" > Côte d’Ivoire (XOF Fr) </option><option value="HR" > Croatia (EUR €) </option><option value="CW" > Curaçao (ANG ƒ) </option><option value="CY" > Cyprus (EUR €) </option><option value="CZ" > Czechia (CZK Kč) </option><option value="DK" > Denmark (DKK kr.) </option><option value="DJ" > Djibouti (DJF Fdj) </option><option value="DM" > Dominica (XCD $) </option><option value="DO" > Dominican Republic (DOP $) </option><option value="EC" > Ecuador (USD $) </option><option value="EG" > Egypt (EGP ج.م) </option><option value="SV" > El Salvador (USD $) </option><option value="GQ" > Equatorial Guinea (XAF Fr) </option><option value="ER" > Eritrea (USD $) </option><option value="EE" > Estonia (EUR €) </option><option value="SZ" > Eswatini (USD $) </option><option value="ET" > Ethiopia (ETB Br) </option><option value="FK" > Falkland Islands (FKP £) </option><option value="FO" > Faroe Islands (DKK kr.) </option><option value="FJ" > Fiji (FJD $) </option><option value="FI" > Finland (EUR €) </option><option value="FR" > France (EUR €) </option><option value="GF" > French Guiana (EUR €) </option><option value="PF" > French Polynesia (XPF Fr) </option><option value="GA" > Gabon (XOF Fr) </option><option value="GM" > Gambia (GMD D) </option><option value="GE" > Georgia (USD $) </option><option value="DE" > Germany (EUR €) </option><option value="GH" > Ghana (USD $) </option><option value="GI" > Gibraltar (GBP £) </option><option value="GR" > Greece (EUR €) </option><option value="GL" > Greenland (DKK kr.) </option><option value="GD" > Grenada (XCD $) </option><option value="GP" > Guadeloupe (EUR €) </option><option value="GT" > Guatemala (GTQ Q) </option><option value="GG" > Guernsey (GBP £) </option><option value="GN" > Guinea (GNF Fr) </option><option value="GW" > Guinea-Bissau (XOF Fr) </option><option value="GY" > Guyana (GYD $) </option><option value="HT" > Haiti (USD $) </option><option value="HN" > Honduras (HNL L) </option><option value="HK" > Hong Kong SAR (HKD $) </option><option value="HU" > Hungary (HUF Ft) </option><option value="IS" > Iceland (ISK kr) </option><option value="IN" > India (INR ₹) </option><option value="ID" > Indonesia (IDR Rp) </option><option value="IQ" > Iraq (USD $) </option><option value="IE" > Ireland (EUR €) </option><option value="IM" > Isle of Man (GBP £) </option><option value="IL" > Israel (ILS ₪) </option><option value="IT" > Italy (EUR €) </option><option value="JM" > Jamaica (JMD $) </option><option value="JP" > Japan (JPY ¥) </option><option value="JE" > Jersey (USD $) </option><option value="JO" > Jordan (USD $) </option><option value="KZ" > Kazakhstan (KZT 〒) </option><option value="KE" > Kenya (KES KSh) </option><option value="KI" > Kiribati (USD $) </option><option value="XK" > Kosovo (EUR €) </option><option value="KW" > Kuwait (USD $) </option><option value="KG" > Kyrgyzstan (KGS som) </option><option value="LA" > Laos (LAK ₭) </option><option value="LV" > Latvia (EUR €) </option><option value="LB" > Lebanon (LBP ل.ل) </option><option value="LS" > Lesotho (USD $) </option><option value="LR" > Liberia (USD $) </option><option value="LY" > Libya (USD $) </option><option value="LI" > Liechtenstein (CHF CHF) </option><option value="LT" > Lithuania (EUR €) </option><option value="LU" > Luxembourg (EUR €) </option><option value="MO" > Macao SAR (MOP P) </option><option value="MG" > Madagascar (USD $) </option><option value="MW" > Malawi (MWK MK) </option><option value="MY" > Malaysia (MYR RM) </option><option value="MV" > Maldives (MVR MVR) </option><option value="ML" > Mali (XOF Fr) </option><option value="MT" > Malta (EUR €) </option><option value="MQ" > Martinique (EUR €) </option><option value="MR" > Mauritania (USD $) </option><option value="MU" > Mauritius (MUR ₨) </option><option value="YT" > Mayotte (EUR €) </option><option value="MX" > Mexico (MXN $) </option><option value="MD" > Moldova (MDL L) </option><option value="MC" > Monaco (EUR €) </option><option value="MN" > Mongolia (MNT ₮) </option><option value="ME" > Montenegro (EUR €) </option><option value="MS" > Montserrat (XCD $) </option><option value="MA" > Morocco (MAD د.م.) </option><option value="MZ" > Mozambique (USD $) </option><option value="MM" > Myanmar (Burma) (MMK K) </option><option value="NA" > Namibia (USD $) </option><option value="NR" > Nauru (AUD $) </option><option value="NP" > Nepal (NPR ₨) </option><option value="NL" > Netherlands (EUR €) </option><option value="NC" > New Caledonia (XPF Fr) </option><option value="NZ" > New Zealand (NZD $) </option><option value="NI" > Nicaragua (NIO C$) </option><option value="NE" > Niger (XOF Fr) </option><option value="NG" > Nigeria (NGN ₦) </option><option value="NU" > Niue (NZD $) </option><option value="NF" > Norfolk Island (AUD $) </option><option value="MK" > North Macedonia (MKD ден) </option><option value="NO" > Norway (USD $) </option><option value="OM" > Oman (USD $) </option><option value="PK" > Pakistan (PKR ₨) </option><option value="PS" > Palestinian Territories (ILS ₪) </option><option value="PA" > Panama (USD $) </option><option value="PG" > Papua New Guinea (PGK K) </option><option value="PY" > Paraguay (PYG ₲) </option><option value="PE" > Peru (PEN S/.) </option><option value="PH" > Philippines (PHP ₱) </option><option value="PN" > Pitcairn Islands (NZD $) </option><option value="PL" > Poland (PLN zł) </option><option value="PT" > Portugal (EUR €) </option><option value="QA" > Qatar (QAR ر.ق) </option><option value="RE" > Réunion (EUR €) </option><option value="RO" > Romania (RON Lei) </option><option value="RU" > Russia (USD $) </option><option value="RW" > Rwanda (RWF FRw) </option><option value="WS" > Samoa (WST T) </option><option value="SM" > San Marino (EUR €) </option><option value="ST" > São Tomé &amp; Príncipe (STD Db) </option><option value="SA" > Saudi Arabia (SAR ر.س) </option><option value="SN" > Senegal (XOF Fr) </option><option value="RS" > Serbia (RSD РСД) </option><option value="SC" > Seychelles (USD $) </option><option value="SL" > Sierra Leone (SLL Le) </option><option value="SG" > Singapore (SGD $) </option><option value="SX" > Sint Maarten (ANG ƒ) </option><option value="SK" selected > Slovakia (EUR €) </option><option value="SI" > Slovenia (EUR €) </option><option value="SB" > Solomon Islands (SBD $) </option><option value="SO" > Somalia (USD $) </option><option value="ZA" > South Africa (USD $) </option><option value="KR" > South Korea (KRW ₩) </option><option value="SS" > South Sudan (USD $) </option><option value="ES" > Spain (EUR €) </option><option value="LK" > Sri Lanka (LKR ₨) </option><option value="BL" > St. Barthélemy (EUR €) </option><option value="SH" > St. Helena (SHP £) </option><option value="KN" > St. Kitts &amp; Nevis (XCD $) </option><option value="LC" > St. Lucia (XCD $) </option><option value="MF" > St. Martin (EUR €) </option><option value="PM" > St. Pierre &amp; Miquelon (EUR €) </option><option value="VC" > St. Vincent &amp; Grenadines (XCD $) </option><option value="SD" > Sudan (USD $) </option><option value="SR" > Suriname (USD $) </option><option value="SJ" > Svalbard &amp; Jan Mayen (USD $) </option><option value="SE" > Sweden (SEK kr) </option><option value="CH" > Switzerland (CHF CHF) </option><option value="TW" > Taiwan (TWD $) </option><option value="TJ" > Tajikistan (TJS ЅМ) </option><option value="TZ" > Tanzania (TZS Sh) </option><option value="TH" > Thailand (THB ฿) </option><option value="TL" > Timor-Leste (USD $) </option><option value="TG" > Togo (XOF Fr) </option><option value="TK" > Tokelau (NZD $) </option><option value="TO" > Tonga (TOP T$) </option><option value="TT" > Trinidad &amp; Tobago (TTD $) </option><option value="TA" > Tristan da Cunha (GBP £) </option><option value="TN" > Tunisia (USD $) </option><option value="TR" > Türkiye (USD $) </option><option value="TM" > Turkmenistan (USD $) </option><option value="TC" > Turks &amp; Caicos Islands (USD $) </option><option value="TV" > Tuvalu (AUD $) </option><option value="UM" > U.S. Outlying Islands (USD $) </option><option value="UG" > Uganda (UGX USh) </option><option value="UA" > Ukraine (UAH ₴) </option><option value="AE" > United Arab Emirates (AED د.إ) </option><option value="GB" > United Kingdom (GBP £) </option><option value="US" > United States (USD $) </option><option value="UY" > Uruguay (UYU $) </option><option value="UZ" > Uzbekistan (UZS ) </option><option value="VU" > Vanuatu (VUV Vt) </option><option value="VA" > Vatican City (EUR €) </option><option value="VE" > Venezuela (USD $) </option><option value="VN" > Vietnam (VND ₫) </option><option value="WF" > Wallis &amp; Futuna (XPF Fr) </option><option value="EH" > Western Sahara (MAD د.م.) </option><option value="YE" > Yemen (YER ﷼) </option><option value="ZM" > Zambia (USD $) </option><option value="ZW" > Zimbabwe (USD $) </option></select> <svg aria-hidden="true" focusable="false" class="icon icon-caret" viewBox="0 0 10 6"> <path fill-rule="evenodd" clip-rule="evenodd" d="M9.354.646a.5.5 0 00-.708 0L5 4.293 1.354.646a.5.5 0 00-.708.708l4 4a.5.5 0 00.708 0l4-4a.5.5 0 000-.708z" fill="currentColor"> </svg> </div> <button class="button button--tertiary">Update country/region</button></form> Country/region EUR € | Slovakia AFN ؋ | Afghanistan EUR € | Åland Islands ALL L | Albania DZD د.ج | Algeria EUR € | Andorra USD $ | Angola XCD $ | Anguilla XCD $ | Antigua & Barbuda USD $ | Argentina AMD դր. | Armenia AWG ƒ | Aruba SHP £ | Ascension Island AUD $ | Australia EUR € | Austria AZN ₼ | Azerbaijan BSD $ | Bahamas USD $ | Bahrain BDT ৳ | Bangladesh BBD $ | Barbados USD $ | Belarus EUR € | Belgium BZD $ | Belize XOF Fr | Benin USD $ | Bermuda USD $ | Bhutan BOB Bs. | Bolivia BAM КМ | Bosnia & Herzegovina BWP P | Botswana USD $ | Brazil USD $ | British Virgin Islands BND $ | Brunei BGN лв. | Bulgaria XOF Fr | Burkina Faso BIF Fr | Burundi KHR ៛ | Cambodia XAF Fr | Cameroon CAD $ | Canada CVE $ | Cape Verde USD $ | Caribbean Netherlands KYD $ | Cayman Islands XAF Fr | Central African Republic XAF Fr | Chad USD $ | Chile CNY ¥ | China USD $ | Colombia KMF Fr | Comoros XAF Fr | Congo - Brazzaville CDF Fr | Congo - Kinshasa NZD $ | Cook Islands CRC ₡ | Costa Rica XOF Fr | Côte d’Ivoire EUR € | Croatia ANG ƒ | Curaçao EUR € | Cyprus CZK Kč | Czechia DKK kr. | Denmark DJF Fdj | Djibouti XCD $ | Dominica DOP $ | Dominican Republic USD $ | Ecuador EGP ج.م | Egypt USD $ | El Salvador XAF Fr | Equatorial Guinea USD $ | Eritrea EUR € | Estonia USD $ | Eswatini ETB Br | Ethiopia FKP £ | Falkland Islands DKK kr. | Faroe Islands FJD $ | Fiji EUR € | Finland EUR € | France EUR € | French Guiana XPF Fr | French Polynesia XOF Fr | Gabon GMD D | Gambia USD $ | Georgia EUR € | Germany USD $ | Ghana GBP £ | Gibraltar EUR € | Greece DKK kr. | Greenland XCD $ | Grenada EUR € | Guadeloupe GTQ Q | Guatemala GBP £ | Guernsey GNF Fr | Guinea XOF Fr | Guinea-Bissau GYD $ | Guyana USD $ | Haiti HNL L | Honduras HKD $ | Hong Kong SAR HUF Ft | Hungary ISK kr | Iceland INR ₹ | India IDR Rp | Indonesia USD $ | Iraq EUR € | Ireland GBP £ | Isle of Man ILS ₪ | Israel EUR € | Italy JMD $ | Jamaica JPY ¥ | Japan USD $ | Jersey USD $ | Jordan KZT 〒 | Kazakhstan KES KSh | Kenya USD $ | Kiribati EUR € | Kosovo USD $ | Kuwait KGS som | Kyrgyzstan LAK ₭ | Laos EUR € | Latvia LBP ل.ل | Lebanon USD $ | Lesotho USD $ | Liberia USD $ | Libya CHF CHF | Liechtenstein EUR € | Lithuania EUR € | Luxembourg MOP P | Macao SAR USD $ | Madagascar MWK MK | Malawi MYR RM | Malaysia MVR MVR | Maldives XOF Fr | Mali EUR € | Malta EUR € | Martinique USD $ | Mauritania MUR ₨ | Mauritius EUR € | Mayotte MXN $ | Mexico MDL L | Moldova EUR € | Monaco MNT ₮ | Mongolia EUR € | Montenegro XCD $ | Montserrat MAD د.م. | Morocco USD $ | Mozambique MMK K | Myanmar (Burma) USD $ | Namibia AUD $ | Nauru NPR ₨ | Nepal EUR € | Netherlands XPF Fr | New Caledonia NZD $ | New Zealand NIO C$ | Nicaragua XOF Fr | Niger NGN ₦ | Nigeria NZD $ | Niue AUD $ | Norfolk Island MKD ден | North Macedonia USD $ | Norway USD $ | Oman PKR ₨ | Pakistan ILS ₪ | Palestinian Territories USD $ | Panama PGK K | Papua New Guinea PYG ₲ | Paraguay PEN S/. | Peru PHP ₱ | Philippines NZD $ | Pitcairn Islands PLN zł | Poland EUR € | Portugal QAR ر.ق | Qatar EUR € | Réunion RON Lei | Romania USD $ | Russia RWF FRw | Rwanda WST T | Samoa EUR € | San Marino STD Db | São Tomé & Príncipe SAR ر.س | Saudi Arabia XOF Fr | Senegal RSD РСД | Serbia USD $ | Seychelles SLL Le | Sierra Leone SGD $ | Singapore ANG ƒ | Sint Maarten EUR € | Slovakia EUR € | Slovenia SBD $ | Solomon Islands USD $ | Somalia USD $ | South Africa KRW ₩ | South Korea USD $ | South Sudan EUR € | Spain LKR ₨ | Sri Lanka EUR € | St. Barthélemy SHP £ | St. Helena XCD $ | St. Kitts & Nevis XCD $ | St. Lucia EUR € | St. Martin EUR € | St. Pierre & Miquelon XCD $ | St. Vincent & Grenadines USD $ | Sudan USD $ | Suriname USD $ | Svalbard & Jan Mayen SEK kr | Sweden CHF CHF | Switzerland TWD $ | Taiwan TJS ЅМ | Tajikistan TZS Sh | Tanzania THB ฿ | Thailand USD $ | Timor-Leste XOF Fr | Togo NZD $ | Tokelau TOP T$ | Tonga TTD $ | Trinidad & Tobago GBP £ | Tristan da Cunha USD $ | Tunisia USD $ | Türkiye USD $ | Turkmenistan USD $ | Turks & Caicos Islands AUD $ | Tuvalu USD $ | U.S. Outlying Islands UGX USh | Uganda UAH ₴ | Ukraine AED د.إ | United Arab Emirates GBP £ | United Kingdom USD $ | United States UYU $ | Uruguay UZS | Uzbekistan VUV Vt | Vanuatu EUR € | Vatican City USD $ | Venezuela VND ₫ | Vietnam XPF Fr | Wallis & Futuna MAD د.م. | Western Sahara YER ﷼ | Yemen USD $ | Zambia USD $ | Zimbabwe Payment methods American Express Apple Pay Discover Google Pay Mastercard Shop Pay Visa © 2024, DIDDY Choosing a selection results in a full page refresh. Opens in a new window. window.shopUrl = 'https://diddy.com'; window.routes = { cart_add_url: '/cart/add', cart_change_url: '/cart/change', cart_update_url: '/cart/update', cart_url: '/cart', predictive_search_url: '/search/suggest', }; window.cartStrings = { error: `There was an error while updating your cart. Please try again.`, quantityError: `You can only add [quantity] of this item to your cart.`, }; window.variantStrings = { addToCart: `Add to cart`, soldOut: `Sold out`, unavailable: `Unavailable`, unavailable_with_option: `[value] - Unavailable`, }; window.accessibilityStrings = { imageAvailable: `Image [index] is now available in gallery view`, shareSuccess: `Link copied to clipboard`, pauseSlideshow: `Pause slideshow`, playSlideshow: `Play slideshow`, };

      OGM ITS DIDDY!

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Public reviews

      This study describes a group of CRH-releasing neurons, located in the paraventricular nucleus of the hypothalamus, which, in mice, affects both the state of sevoflurane anesthesia and a grooming behavior observed after it. PVHCRH neurons showed elevated calcium activity during the post-anesthesia period. Optogenetic activation of these PVHCRH neurons during sevoflurane anesthesia shifts the EEG from burst-suppression to a seemingly activated state (an apparent arousal effect), although without a behavioral correlate. Chemogenetic activation of the PVHCRH neurons delays sevoflurane-induced loss of righting reflex (another apparent arousal effect). On the other hand, chemogenetic inhibition of PVHCRH neurons delays recovery of righting reflex and decreases sevoflurane-induced stress (an apparent decrease in the arousal effect). The authors conclude that PVHCRH neurons "integrate" sevoflurane-induced anesthesia and stress. The authors also claim that their findings show that sevoflurane itself produces a post-anesthesia stress response that is independent of any surgical trauma, such as an incision. In its revised form, the article does not achieve its intended goal and will not have impact on the clinical practice of anesthesiology nor on anesthesiology research.

      Thanks for the reviews. Please see our responses to the following comments.

      Weaknesses:

      The most significant weaknesses remain:

      a) overinterpretation of the significance of their findings

      b) the failure to use another anesthetic as a control,

      c) a failure to compellingly link their post-sevoflurane measures in mice to anything measured in humans, and

      d) limitations in the novelty of the findings. These weaknesses are related to the primary concerns described below:

      Concerns about the primary conclusion that PVHCRH neurons integrate the anesthetic effects and post-anesthesia stress response of sevoflurane GA

      (1) After revision, their remain multiple places where it is claimed that PVHCRH neurons mediate the anesthetic effects of sevoflurane (impact statement: we explain "how sevoflurane-induced general anesthesia works..."; introduction: "the neuronal mechanisms that mediate the anesthetic effects...of sevoflurane GA remain poorly understood" and "PVHCRH neurons may act as a crucial node integrating the anesthetic effect and stress response of sevoflurane").The manuscript simply does not support these statements. The authors show that a short duration exposure to sevoflurane inhibits PVHCRH neurons, but this is followed by hyperexcitability of these neurons for a short period after anesthesia is terminated. They show that the induction and recovery from sevoflurane anesthesia can be modulated by PVHCRH neuronal activity, most likely through changes in brain state (measured by EEG). They also show that PVHCRH neuronal activity modulates corticosterone levels and grooming behavior observed post-anesthesia (which the authors argue are two stress responses).These two things (effects during anesthesia and effects post-anesthesia)may be mechanistically unrelated to each other. None of these observations relate to the primary mechanism of action for sevoflurane. All claims relating to "anesthetic effects" should be removed. Even the term "integration" seems wrong-it implies the PVH is combining information about the anesthetic effect and post-anesthesia stress responses.

      As requested, we have removed all claims related to ‘anesthetic effects’ or ‘integration’. Please see the revised manuscript.

      (2) lt is important to compare the effects of sevoflurane with at least one other inhaled ether anesthetic as one step towards elevating the impact of this paper to the level required for a journal such as eLife. Isoflurane, desflurane, and enflurane are ether anesthetics that are very similar to each other, as well as being similar to sevoflurane. For example, one study cited by the authors (Marana et al.2013) concludes that there is weak evidence for differences in stress-related hormones between sevoflurane and desflurane, with lower levels of cortisol and ACTH observed during the desflurane intraoperative period. It is important to determine whether desflurane activates PVHCRH neurons in the post-anesthesia period, and whether this is accompanied by excess grooming in the mice, because this will distinguish whether the effects of sevoflurane generalize to other inhaled anesthestics, or, alternatively, relate to unique idiosyncratic properties of this gas that may not be a part of its anesthetic properties.

      Thanks for your insightful comments and suggestions. Regarding your request for additional experiments, we acknowledge the value they could add to our study. However, investigating whether the effects of sevoflurane generalize to other inhaled anesthetics is beyond the scope of our current study. There is evidence indicating the prevalence of anesthetic stress caused by inhaled ether anesthetics1,2. The post-anesthesia stress-related behaviors caused by sevoflurane administration are reminiscent of delirium observed clinically. Notably, studies have shown that the use of desflurane for maintenance of anesthesia did not significantly affect the incidence or duration of delirium compared to sevoflurane administration3. This suggests that our observations likely represent a generalized response to inhaled ether anesthetic rather than being specific to sevoflurane.

      Concerns about the clinical relevance of the experiments

      In anesthesiology practice, perioperative stress observed in patients is more commonly related to the trauma of the surgical intervention, with inadequate levels of antinociception or unconsciousness intraoperatively and/or poor post-operative pain control. The authors seem to be suggesting that the sevoflurane itself is causing stress because their mice receive sevoflurane but no invasive procedures, but there is no evidence of sevoflurane inducing stress in human patients. It is important to know whether sevoflurane effectively produces behavioral stress in the recovery room in patients that could be related to the putative stress response (excess grooming) observed in mice. For example, in surgeries or procedures which required only a brief period of unconsciousness that could be achieved by administering sevoflurane alone (comparable to the 30 min administered to the mice), is there clinical evidence of post-operative stress? It is also important to describe a rationale for using a 30 min sevoflurane exposure. What proportion of human surgeries using sevoflurane use exposure times that are comparable to this?

      It is also the case that there are explicit published findings showing that mild and moderate surgical procedures in children receiving sevoflurane (which might be the closest human proxy to the brief 30 minutes sevoflurane exposure used here) do not have elevated cortisol (Taylor et al, J Clin Endocrinol Metab, 2013). This again raises the question of whether the enhanced grooming or elevated corticosterone observed in the mice here has any relevance to humans.

      Thanks for the comments. Most ear, nose, and throat surgeries in children involve a short period of anesthesia with sevoflurane alone4-6, which is similar to the 30-minute exposure in our mouse study. In clinical settings, emergence delirium and agitation are common in young children undergoing sevoflurane anesthesia7, often accompanied by troublesome excitation phenomena during induction and awakening8. These clinical observations align with the post-operative stress response (e.g., excessive grooming) we identified in our study.

      It is the experience of one of the reviewers that human patients who receive sevoflurane as the primary anesthetic do not wake up more stressed than if they had had one of the other GABAergic anesthetics. If there were signs of stress upon emergence (increased heart rate, blood pressure, thrashing movements) from general anesthesia, this would be treated immediately. The most likely cause of post-operative stress behaviors in humans is probably inadequate anti-nociception during the procedure, which translates into inadequate post-op analgesia and likely delirium. It is the case that children receiving sevoflurane do have a higher likelihood of post-operative delirium. Perhaps the authors' studies address a mechanism for delirium associated with sevoflurane, but this is barely mentioned. Delirium seems likely to be the closest clinical phenomenon to what was studied. As noted by the Besnier et al (2017) article cited by the authors, surgery can elevate postoperative glucocorticoidstress hormones, but it generally correlates with the intensity of the surgical procedure. Besnier et al also note the elevation of glucocorticoids is generally considered to be adaptive. Thus, reducing glucocorticoids during surgery with sevoflurane may hamper recovery, especially as it relates to tissue damage, which was not measured or considered here. This paper only considers glucocorticoid release as a negative factor, which causes "immunosuppression", "proteolysis", and "delays postoperative recovery and leads to increased morbidity".

      Thanks for the comments. We agree that the post-anesthetic stress behaviors mentioned in our manuscript are similar to the clinical phenomenon of delirium, which were defined in Cheng Li’s study as ‘sevoflurane-induced post-operative delirium’9. Therefore, we conducted additional behavioral tests for cognitive function, including the Y-maze and novel object recognition test, in mice administrated 30-minute sevoflurane anesthesia. The results demonstrate that chemogenetic inhibition of PVHCRH neurons ameliorated the short-term memory impairment in mice exposed to 30-minute sevoflurane GA (Figure 7-figure supplement 9), suggesting PVHCRH neurons may involve in modulating sevoflurane-induced postoperative delirium.

      Concerns about the novelty of the findings:

      The key finding here is that CRH neurons mediate measures of arousal, and arousal modulates sevoflurane anesthesia induction and recovery. However, CRH is associated with arousal in numerous studies. In fact, the authors' own work, published in eLife in 2021, showed that stimulating the hypothalamic CRH cells lead to arousal and their inhibition promoted hypersomnia. In both papers the authors use fos expression in CRH cells during a specific event to implicate the cells, then manipulate them and measure EEG responses. In the previous work, the cells were active during wakefulness; here- they were active in the awake state the follows anesthesia (Figure1). Thus, the findings in the current work are incremental and not particularly impactful. Claims like "Here, a core hypothalamic ensemble, corticotropin-releasing hormone neurons in the paraventricular nucleus of the hypothalamus, is discovered" are overstated. PVHCRH cell populations were discovered in the 1980s. Suggesting that it is novel to identify that hypothalamic CRH cells regulate post-anesthesia stress is unfounded as well: this PVH population has been shown over four decades to regulate a plethora of different responses to stress. Anesthesia stress is no different. Their role in arousal is not being discovered in this paper. Even their role in grooming is not discovered in this paper.

      Thanks for the comments. As requested, we have revised our manuscript by removing overstated sentences. Please see the revised manuscript. In terms of novelty, our study reveals that PVHCRH neurons are implicated not only in the induction and emergence of sevoflurane general anesthesia but also in sevoflurane-induced post-operative delirium. This finding represents a novel contribution to the field, as it has not been previously reported by other studies.

      The activation of CRH cells in PVH has already been shown to result in grooming by Jaideep Bains (a paper cited by the authors). Thus, the involvement of these cells in this behavior is not surprising. The authors perform elaborate manipulations of CRH cells and numerous analyses of grooming and related behaviors. For example, they compare grooming and paw licking after anesthesia with those after other stressors such as forced swim, spraying mice with water, physical attack and restraint. The authors have identified a behavioral phenomenon in a rodent model that does not have a clear correlation with a behavior state observed in humans during the use of sevoflurane as part of an anesthetic regimen. The grooming behaviors are not a model of the emergence delirium or the cognitive dysfunction observed commonly in patients receiving sevoflurane for general anesthesia. Emergence delirium is commonly seen in children after sevoflurane is used as part of general anesthesia and cognitive dysfunction is commonly observed in adults-particularly the elderly-- following general anesthesia. No features of delirium or cognitive dysfunction are measured here.

      As requested, behavioral tests for cognitive function have been conducted and displayed in Figure 7-figure supplement 9.

      Other concerns:

      In Figure 2, cFos was measured in the PVH at different points before, during and after sevoflurane. The greatest cFos expression was seen in Post 2, the latest time point after anesthesia. However, this may simply reflect the fact that there is a delay between activity levels and expression of cFos (as noted by the authors, 2-3 hours). Thus, sacrificing mice 30 minutes after the onset of sevoflurane application would be expected to drive minimal cFos expression, and the cFos observed at 30 minutes would not accurately reflect the activity levels during the sevoflurane. Also, the authors state that the hyperactivity, as measured by cFos, lasted "approximately 1 hours before returning to baseline", but there is no data to support this return to baseline.

      Thanks for the comments. We apologize that the protocol we used for c-fos staining may not accurately reflect the activity levels, so we have removed Figure 2F. The sentence ‘lasted approximately 1 hours before returning to baseline’ refers to the calcium signal but not c-fos level.

      In Figure 7, the number of animals appears to change from panel to panel even though they are supposed to show animals from the same groups. For example, cort was measured in only 3 saline-treated O2 animals (Fig 7E), but cFos and CRH were assessed in 4 (Fig C,D). Similarly, grooming time and time spent in open arms was measured in 6 saline-treated O2 controls (Fig 7F, H) but central distance was measured in 8(Fig 7G). There are other group number discrepancies in this figure--the number of data points in the plots do not match what is reported in the legend for numerous groups. Similarly, Figure 4 has a mismatch between the Ns reported in the legend and the number of points plotted per bar. For example, there were 10 animals in the hM3Di group; all are shown for the LORR and time to emergence plots, but only8 were used for time to induction. The legends reported N=7 for the mCherry group, yet 9 are shown for the time to emergence panel. No reason for exclusions is cited. These figures (and their statistics) should be corrected.

      Thanks for the comments. We have rechecked and corrected our figures and illustrations in the revised manuscript.

      Recommendations for the authors:

      In Figure 6, the BSR pre-stim data points for panels F and H look exactly identical, even though these data are from two different sets of mice. It seems likely that one of these panels is not depicting the correct pre-stim data points. Please check this.

      Thanks for the comments. We have corrected this mistake.

      General anesthesia is a combination of behavioral and physiological states induced and maintained primarily by pharmacologic agents. The authors do not provide a definition of general anesthesia.

      Thanks for the advice. We have added the definition of general anesthesia in the introduction part.

      The first sentence of the abstract closely resembles the first sentence of the abstract of Brown,Purdon and Van Dort,Annu. Rev. Neurosci. 2011,34:601-28 yet, there is no citation.

      Thanks for the comments. We have revised the first sentence.

      ln the Discussion, the authors cite the research on circuitry that is relevant for emergence from general anesthesia. Conspicuously missing from this section of the paper is the large body of work by Solt and colleagues which has demonstrated that dopamine agonists (such as methylphenidate), electrical stimulation of the ventral tegmental area and optogenetic stimulation of the D1 neurons in the ventral tegmental area can hasten emergence from general anesthesia. Also omitted is the work of Kelzand colleagues and a discussion of neural inertia.

      Thanks for the suggestions. We have added these citations as requested.

      As regards the weaknesses of p-values for reporting the results of scientific studies, l offer the following reference to the authors. Ronald L. Wasserstein & Nicole A.Lazar (2016)The ASA Statement on p-Values: Context, Process, and Purpose, The American Statistician,70:2,129- 133, DOl:10.1080/00031305.2016.1154108

      Thanks for the suggestions. We have revised the manuscript as requested.

      The methods for the CRF antibody are unclear. It was previously suggested that the antibody be validated (for example, show an absence of immunostaining with CRF knockdown) because the concentration of antiserum (1:800) is quite high, suggesting either the antibody is not potent or (more concerning) not specific. The methods also indicated that colchicine was infused ICV prior to perfusion for staining of cFos and CRF, but no surgical methods are described that would enable ICV infusion, and it is not clear why colchicine was used. Please clarify.

      The anti-CRF antibody is validated by other studies11,12. F For CRF immunostaining, animals' brains were pre-treated with intraventricular injections of colchicine (20 μg in 500 nL saline) 24 hours before perfusion to inhibit fast axonal transport13,14. Additional details regarding these methods have been included in the Method section of the revised manuscript.

      Editor's note:

      Full statistical reporting including exact p-values alongside summary statistics (test statistic and df) and 95% confidence intervals is lacking.

      Thanks for the suggestions. We have added full statistical reporting in the revised manuscript as requested.

      Reference

      (1) Marana, E. et al. Desflurane versus sevoflurane: a comparison on stress response. Minerva Anestesiol 79, 7-14 (2013).

      (2) Yang, L., Chen, Z. & Xiang, D. Effects of intravenous anesthesia with sevoflurane combined with propofol on intraoperative hemodynamics, postoperative stress disorder and cognitive function in elderly patients undergoing laparoscopic surgery. Pak J Med Sci 38, 1938-1944, doi:10.12669/pjms.38.7.5763 (2022).

      (3) Driscoll, J. N. et al. Comparing incidence of emergence delirium between sevoflurane and desflurane in children following routine otolaryngology procedures. Minerva Anestesiol 83, 383-391, doi:10.23736/s0375-9393.16.11362-8 (2017).

      (4) Galinkin, J. L. et al. Use of intranasal fentanyl in children undergoing myringotomy and tube placement during halothane and sevoflurane anesthesia. Anesthesiology 93, 1378-1383, doi:10.1097/00000542-200012000-00006 (2000).

      (5) Greenspun, J. C., Hannallah, R. S., Welborn, L. G. & Norden, J. M. Comparison of sevoflurane and halothane anesthesia in children undergoing outpatient ear, nose, and throat surgery. J Clin Anesth 7, 398-402, doi:10.1016/0952-8180(95)00071-o (1995).

      (6) Messieha, Z. Prevention of sevoflurane delirium and agitation with propofol. Anesth Prog 60, 67-71, doi:10.2344/0003-3006-60.3.67 (2013).

      (7) Shi, M. et al. Dexmedetomidine for the prevention of emergence delirium and postoperative behavioral changes in pediatric patients with sevoflurane anesthesia: a double-blind, randomized trial. Drug Des Devel Ther 13, 897-905, doi:10.2147/dddt.S196075 (2019).

      (8) Veyckemans, F. Excitation and delirium during sevoflurane anesthesia in pediatric patients. Minerva Anestesiol 68, 402-405 (2002).

      (9) Xu, Y., Gao, G., Sun, X., Liu, Q. & Li, C. ATPase Inhibitory Factor 1 Is Critical for Regulating Sevoflurane-Induced Microglial Inflammatory Responses and Caspase-3 Activation. Front Cell Neurosci 15, 770666, doi:10.3389/fncel.2021.770666 (2021).

      (10) Friedman, E. B. et al. A conserved behavioral state barrier impedes transitions between anesthetic-induced unconsciousness and wakefulness: evidence for neural inertia. PLoS One 5, e11903, doi:10.1371/journal.pone.0011903 (2010).

      (11) Giardino, W. J. et al. Parallel circuits from the bed nuclei of stria terminalis to the lateral hypothalamus drive opposing emotional states. Nat Neurosci 21, 1084-1095, doi:10.1038/s41593-018-0198-x (2018).

      (12) Yeo, S. H., Kyle, V., Blouet, C., Jones, S. & Colledge, W. H. Mapping neuronal inputs to Kiss1 neurons in the arcuate nucleus of the mouse. PLoS One 14, e0213927, doi:10.1371/journal.pone.0213927 (2019).

      (13) de Goeij, D. C. et al. Repeated stress-induced activation of corticotropin-releasing factor neurons enhances vasopressin stores and colocalization with corticotropin-releasing factor in the median eminence of rats. Neuroendocrinology 53, 150-159, doi:10.1159/000125712 (1991).

      (14) Yuan, Y. et al. Reward Inhibits Paraventricular CRH Neurons to Relieve Stress. Curr Biol 29, 1243-1251.e1244, doi:10.1016/j.cub.2019.02.048 (2019).

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The authors of this study aim to use an optimization algorithm approach, based on the established NelderMead method, to infer polymer models that best match input bulk Hi-C contact data. The procedure infers the best parameters of a generic polymer model that combines loop-extrusion (LE) dynamics and compartmentalization of chromatin types driven by weak biochemical affinities. Using this and DNA FISH, the authors investigate the chromatin structure of the MYC locus in leukemia cells, showing that loop extrusion alone cannot explain local pathogenic chromatin rearrangements. Finally, they study the locus single-cell heterogeneity and time dynamics.

      Strengths:

      - The optimization method provides a fast computational tool that speeds up the parameter search of complex chromatin polymer models and is a good technical advancement.

      - The method is not restricted to short genomic regions, as in principle it can be applied genome-wide to any input Hi-C dataset, and could be potentially useful for testing predictions on chromatin structure.

      Weaknesses:

      (1) The optimization is based on the iterative comparison of simulated and Hi-C contact matrices using the Spearman correlation. However, the inferred set of the best-fit simulation parameters could sensitively depend on such a specific metric choice, questioning the robustness of the output polymer models. How do results change by using different correlation coefficients?

      This is an important question. We have tested several metrics in the process of building the fitting procedure. We now showcase side-by-side comparisons of the fitting results obtained using these different metrics in supplementary figure 2.

      (2) The best-fit contact threshold of 420nm seems a quite large value, considering that contact probabilities of pairs of loci at the mega-base scale are defined within 150nm (see, e.g., (Bintu et al. 2018) and  (Takei et al. 2021)).

      This is a good point. Unfortunately, there is no established standard distance cutoff to map distances to Hi-C contact frequency data. Indeed, previous publications have used anywhere between 120 nm to 500 nm (see e.g. (Cardozo Gizzi et al. 2019), (Cattoni et al. 2017) , (Mateo et al. 2019), (Hafner et al. 2022), (Murphy and Boettiger 2022), (Takei et al. 2021), (Fudenberg and Imakaev 2017) , (Wang et al. 2016), (Su et al. 2020), (Chen et al. 2022), (Finn et al. 2019)). 

      We have included a supplementary table in the revised preprint (supplementary table 3) listing these values to demonstrate the lack of consensus. This large variation could reflect different chromatin compaction levels across distinct model systems, and different spatial resolutions in DNA FISH experiments performed by different labs. The variance in the threshold choice is also likely partially explained by Hi-C experimental details, e.g. the enzyme used for digestion, which biases the effective length scale of interactions detected (Akgol Oksuz et al. 2021). Among commonly used restriction enzymes, HindIII has a relatively low cutting frequency which results in a lower sensitivity to short-range interactions; on the other hand, MboI has a higher cutting frequency which results in a higher sensitivity to short-range interactions (Akgol Oksuz et al. 2021). Because the Hi-C data we used for the Myc locus in (Kloetgen et al. 2020) was generated using HindIII, we chose a distance cutoff close to the larger end of published values (420 nm). 

      (3) In their model, the authors consider the presence of LE anchor sites at Hi-C TAD boundaries. Do they correspond to real, experimentally found CTCF sites located at genomic positions, or they are just assumed? A track of CTCF peaks of the considered chromatin loci would be needed.

      We apologize this was not clear. The LE anchor sites in the simulation model were chosen because they correspond to experimental CTCF sites and ChIP-seq peaks located at the corresponding genomic positions. Representative CTCF ChIP-seq tracks from (Kloetgen et al. 2020) have been added to figure 2A in the revised preprint version to emphasize this point.

      (4) In the model, each TAD is assigned a specific energy affinity value. Do the different domain types (i.e., different colors) have a mutually attractive energy? If so, what is its value and how is it determined? The simulated contact maps (e.g., Figure 2C) seem to allow attractions between different blocks, yet this is unclear.

      Sorry this was not explicit. The attraction energy between a pair of monomers in the simulation is determined using the geometric mean of the affinities of the two monomers. This applies to both monomers within the same domain and in different domains. This detail has been clarified in the Methods section: “To optimize the simulation duration to streamline the parameter search (Supp. Fig. 1 B), we computed the autocorrelation function of the TAD2-TAD4 inter-TAD distance using the initial guess simulation parameters of the MYC locus in CUTLL. The simulation was saved every 5 simulation blocks.”

      (5) To substantiate the claim that the simulations can predict heterogeneity across single cells, the authors should perform additional analyses. For instance, they could plot the histograms (models vs. experiments) of the TAD2-TAD4 distance distributions and check whether the models can recapitulate the FISH-observed variance or standard deviation. They could also add other testable predictions, e.g., on gyration radius distributions, kurtosis, all-against-all comparison of single-molecule distance matrices, etc,.

      We agree that heterogeneity prediction is a key advantage of the simulations. We do note that the histograms (models vs. experiments) of the TAD2-TAD4 distance distributions measured by FISH were plotted in Fig. 3C as empirical cumulative probability distributions (as is standard in the field), side by side with the simulation predictions. Simulations indeed recapitulate the variance observed by FISH. We also had emphasized this important point in the main text: “Importantly, not just the average distances, but the shape of the distance distribution across individual cells closely matches the predictions of the simulations in both cell types, further confirming that the simulations can predict heterogeneity across cells.”

      (6) The authors state that loop extrusion is crucial for enhancer function only at large distances. How does that reconcile, e.g., with Mach et al. Nature Gen. (2022) where LE is found to constrain the dynamics of genomically close (150kb) chromatin loci?

      This is an interesting question. In (Mach et al. 2022), the authors tracked the physical distance between two fluorescent labels positioned next to either anchor of a ~150 kb engineered topological domain using live-cell imaging. They found that abrogation of the loop anchors by ablation of the CTCF binding motifs, or knock-down of the cohesin subunit Rad21 resulted in increased physical distance between the loci. HMM Modeling of the distance over time traces suggests that the increased distance resulted from rarer and shorter contacts between the anchors. While this might seem at odds with the results of Fig. 4L, we note a key difference between the loci. While (Mach et al. 2022) observed the dynamics of the distance separating two CTCF loop anchors, in our model only the MYC promoter is proximal to a loop anchor, while the position of the second locus is varied, but remains far from the other anchor. The deletion of the CTCF sites at both anchors in (Mach et al. 2022) indeed results in a lowered sensitivity of the physical distance to Rad21 knock-down, reminiscent of the results of Fig. 4L in our work. This result demonstrates that loop extrusion disruption disproportionately impacts distances between loci close to loop anchors, consistent with Hi-C results (Rao et al. 2017; Nora et al. 2017). We therefore believe that the models in our work and (Mach et al. 2022) are not at odds, but simply reflect that loop extrusion perturbations impact distances between loop anchors the most.  Enhancer-Promoter loops are generally distinct from CTCF-mediated loops (Hsieh et al. 2020, 2022). While (Mach et al. 2022) represents a landmark study in our understanding of the dynamics of genomic folding by loop extrusion, we therefore believe that the locus we chose here - which matches the endogenous MYC architecture - may more accurately represent Enhancer-Promoter dynamics than a synthetic CTCF loop.  To better articulate the similarities between model predictions and differences between the two loci, we have simulated a synthetic locus matching that of (Mach et al. 2022) in the revised preprint. Our simulation recapitulates the results obtained by Mach et al, including the sensitivity of contact frequency and duration to in silico cohesin knock-down (supplementary figure 6). We have updated the Results section accordingly: “The dependence of contact dynamics on loop extrusion in our simulations of MYC differs from that previously observed for two TAD boundaries (45). To check whether the different results are the product of different simulation models, we simulated contact dynamics across two TAD boundaries matching the locus of (45). Our simulations recapitulate the distance distribution and loop extrusion dependence previously observed (Supp. Fig. 6), establishing that the differences between the two systems are biological. While loop extrusion controls both the frequency and duration of contacts at TAD boundaries, it exerts a more nuanced effect on the frequency of contacts in loci pairs like the MYC locus that might better reflect typical enhancer-promoter pairs.”

      Reviewer #2 (Public Review):

      Summary:

      The authors Fu et al., developed polymer models that combine loop extrusion with attractive interactions to best describe Hi-C population average data. They analyzed Hi-C data of the MYC locus as an example and developed an optimization strategy to extract the parameters that best fit this average Hi-C data.

      Strengths:

      The model has an intuitive nature and the authors masterfully fitted the model to predict relevant biology/Hi-C methodology parameters. This includes loop extrusion parameters, the need for self-interaction with specific energies, and the time and distance parameters expected for Hi-C capture.

      Weaknesses:

      (1) We are no longer in the age in which the community only has access to population average Hi-C. Why was only the population average Hi-C used in this study?

      Can single-cell data: i.e. single-cell Hi-C/Dip-C data or chromatin tracing data (i.e. see Tan et al Science 2018 - for Dip-C, Bintu et al Science 2018, Su et al Cell 2020 for chromatin tracing, etc.) or even 2 color DNA FISH data (used here only as validation) better constrain these models? At the very least the simulations themselves could be used to answer this essential question.

      I am expecting that the single-cell variance and overall distributions of distances between loci might better constrain the models, and the authors should at least comment on it.

      We agree that it is possible to recapitulate single-cell Hi-C or chromatin tracing data with simulations, and that these data modalities have a superior potential to constrain polymer models because they provide an ensemble of single allele structures rather than population-averaged contact frequencies. However, these data remain out of reach for most labs compared to Hi-C. Our goal with this work was to provide an approachable method that anyone interested could deploy on their locus of choice, and reasoned that Hi-C currently remains the data modality available to most. We envision this strategy will help reach labs beyond the small number of groups expert in single cell chromatin architecture, and thus hopefully broaden the impact of polymer simulations in the chromatin organization field. 

      Nevertheless, we do agree that the comparison of single-cell chromatin architectures to simulations is a fertile ground for future studies, and have modified the preprint accordingly (Discussion):

      “Future work extending this framework to single cell readouts out chromatin architecture (e.g. single-cell Hi-C or chromatin tracing) holds promise to further constrain chromatin models.”

      (2) The authors claimed "Our parameter optimization can be adapted to build biophysical models of any locus of interest. Despite the model's simplicity, the best-fit simulations are sufficient to predict the contribution of loop extrusion and domain interactions, as well as single-cell variability from Hi-C data. Modeling dynamics enables testing mechanistic relationships between chromatin dynamics and transcription regulation. As more experimental results emerge to define simulation parameters, updates to the model should further increase its power." The focus on the Myc locus in this study is too narrow for this claim. I am expecting at least one more locus for testing the generality of this model.

      We note that we used two distinct loci in the initial version of our study, the MYC locus in leukemia vs T cells (Figs. 2-3) and a representative locus in experiments comparing WT CTCF with a mutant that leads to loss of a subset of CTCF binding sites (Fig. 1L). To further demonstrate generality, we have added to the revised preprint a demonstration of the simulation fitting to other loci acquired in different cell types (supplementary figure 3).

      Recommendations for the authors:.

      Reviewer #1 (Recommendations For The Authors):

      (1) The Methods part of the imaging analysis lacks some quantitative details that could be useful for the readers: what is the frequency of double detections? How "small" is the 3D region around the centroid? How many cells with no spots or more than four spots are excluded?

      We have clarified these important analysis parameters in the revised version of the preprint (Methods), including supplementary Table 2, listing the statistics of excluded cells:

      “We then cropped out a small 3D region (20x20x10 pixels) around each approximate centroid, and subtracted the surrounding background intensity.”

      “Cells with no spots or more than four spots were excluded from the cell cycle analysis (statistics in Supp. Table 2).”

      (2) How is the autocorrelation function of chromatin structures computed?

      We computed the autocorrelation function of the TAD2-TAD4 inter-TAD distance using the initial guess simulation parameters (Eattr, boundary permeabilities) of the MYC locus in CUTLL. All other simulation parameters are the same as other simulations in the preprint. The structure of the locus was saved every 5 simulation blocks. These structures were used to compute the TAD2-TAD4 inter-TAD distance as a function of time, which was used to calculate the autocorrelation function. This has been clarified in the revised version of the preprint (Methods):

      “To optimize the simulation duration to streamline the parameter search (Supp. Fig. 1 B), we computed the autocorrelation function of the TAD2-TAD4 inter-TAD distance using the initial guess simulation parameters of the MYC locus in CUTLL. The simulation was saved every 5 simulation blocks.”

      (3) How is the monomer length (35nm) chosen to best compare FISH data?

      Because monomer length is difficult to derive from first principles, the standard in the field is to convert the size of a simulated monomer into a physical distance using a reference measurement in the system of choice. Similar to the Hi-C distance threshold, values for monomer size vary throughout the literature, e.g. 53 nm per 3 kbp monomer (Giorgetti et al. 2014), 50 nm per 2.5 kbp monomer (Nuebler et al. 2018), or from 36 to 60 nm per 3 kbp monomer, depending on the cell line or model details (Conte et al. 2022; Conte et al. 2020). 

      Here we used the mean of the median TAD2-TAD4 distances in T Cells and CUTLL as our length reference, and converted simulation distances into nm by matching this value. We obtained 35 nm per 2.5 kbp monomer, a value well within the range of the literature values (see above).

      Using this simple conversion, the simulated distance distributions recapitulate two independent metrics accessible by DNA FISH: the shift in median distances between T cell and CUTLL, and the width of each distribution. This agreement indicates that simulations recapitulate both the differences between the two cell types, and the single cell heterogeneity within each cell type. 

      (4) The main text does not make clear the "known" biophysical parameters that establish the model ground truth.

      In the initial validation of the fitting procedure, by “known biophysical parameters”, we meant that we generated simulated Hi-C maps in which we set the left/right permeabilities at each boundary, and Eattr values within each TAD to known values. We then assessed how well the fitting could recover these known ground truth values by trying to match the simulated representative Hi-C map. The specific values chosen are plotted for each set of simulations in Fig.1 F, H, J. The main text has been made more explicit in the revised preprint version (Results):

      “We first validated the optimization method using ground truth maps built from simulation runs with known values of StallL, StallR, Eattr for each boundary/domainbiophysical parameters.”

      (5) What are the correlation coefficients between experimental and model contact maps in Figure 1L?

      We apologize for the oversight. The missing coefficient values have been added in the revised version of the manuscript (Results):

      “As expected, the simulation predicted a significant drop of 0.13 in boundary permeability in CTCFmut compared to WT (Fig. 1 L; Spearman Correlation: 0.85±0.02 for CTCFmut, 0.82±0.01 for WT).”

      (6) Figure 2A, B: Contact matrices look oversaturated. Next, why do model contact maps have negative values?

      We apologize this was not clear. Figure 2 A,B plotted the log value of the contact matrices, thus the negative values. This has been made explicit in the revised version of the preprint (Fig. 2 Legend). 

      (7) For model reproducibility, the authors could report the coordinates of the Hi-C TAD boundaries employed for the model.

      We have included in the revised version of the preprint an explicit mention of all genomic coordinates of the loci simulated in the Methods section:

      “The model used to fit into MYC Hi-C data consists of 1920 monomers representing chr8:126,720,000131,680,000, with the TAD boundaries located at monomer 456 (chr8: 127,840,000 - 127,880,001), monomer

      808 (chr8: 128,720,000 - 128,760,001), monomer 1178 (chr8: 130,160,000 - 130,200,001) and monomer 1592 (chr8: 130,680,000 - 130,720,001).”

      (8) What is the shaded area in Figure 3C?

      The shaded area in Figure 3C is the standard deviation calculated from three independent DNA FISH or simulation replicates for each bin of the histogram. This detail has been clarified in the revised preprint (Figure 3 legend). 

      (9) In the Discussion, I suggest changing as follows: "the time- and distance-gated model proposed here recapitulates several observations" -> "the time- and distance-gated model proposed here could recapitulate several observations", as they are speculations.

      The sentence has been changed accordingly in the revised preprint (Discussion). Thank you for the suggestion. 

      Reviewer #2 (Recommendations For The Authors):

      Suggest analyzing the ability of single-cell data to better constrain dynamical models.

      While we agree that modeling single-cell distributions is a worthwhile endeavor to be explored in future work, we believe that the tool presented here serves a slightly different purpose: enabling labs that only have access to the most widespread technique at present to perform simulations to interrogate the forces that shape the organization of an arbitrary locus in their model of choice. Analyzing single-cell data is in principle very powerful, but would by necessity be limited to the small number of systems where these cutting-edge techniques have been deployed. 

      Suggest selecting another locus other than MYC to demonstrate generality.

      We note that we used two distinct loci in the study, the MYC locus in leukemia vs. T cells (Figs. 2-3) and a representative locus in experiments comparing WT CTCF with a mutant that leads to loss of a subset of CTCF binding sites (Fig. 1L). To further demonstrate generality, we have added to the revised preprint a demonstration of the simulation fitting to other loci acquired in different cell types (supplementary figure 3).

      Akgol Oksuz, Betul, Liyan Yang, Sameer Abraham, Sergey V. Venev, Nils Krietenstein, Krishna Mohan Parsi, Hakan Ozadam, et al. 2021. “Systematic Evaluation of Chromosome Conformation Capture Assays.” Nature Methods 18 (9): 1046–55.

      Bintu, Bogdan, Leslie J. Mateo, Jun-Han Su, Nicholas A. Sinnott-Armstrong, Mirae Parker, Seon Kinrot, Kei Yamaya, Alistair N. Boettiger, and Xiaowei Zhuang. 2018. “Super-Resolution Chromatin Tracing Reveals Domains and Cooperative Interactions in Single Cells.” Science 362 (6413). https://doi.org/10.1126/science.aau1783.

      Cardozo Gizzi, Andrés M., Diego I. Cattoni, Jean-Bernard Fiche, Sergio M. Espinola, Julian Gurgo, Olivier Messina, Christophe Houbron, et al. 2019. “Microscopy-Based Chromosome Conformation Capture Enables Simultaneous Visualization of Genome Organization and Transcription in Intact Organisms.” Molecular Cell 74 (1): 212–22.e5.

      Cattoni, Diego I., Andrés M. Cardozo Gizzi, Mariya Georgieva, Marco Di Stefano, Alessandro Valeri, Delphine Chamousset, Christophe Houbron, et al. 2017. “Single-Cell Absolute Contact Probability Detection Reveals Chromosomes Are Organized by Multiple Low-Frequency yet Specific Interactions.” Nature Communications 8 (1): 1753.

      Chen, Liang-Fu, Hannah Katherine Long, Minhee Park, Tomek Swigut, Alistair Nicol Boettiger, and Joanna Wysocka. 2022. “Structural Elements Facilitate Extreme Long-Range Gene Regulation at a Human Disease Locus.” bioRxiv. https://doi.org/10.1101/2022.10.20.513057.

      Finn, Elizabeth H., Gianluca Pegoraro, Hugo B. Brandão, Anne-Laure Valton, Marlies E. Oomen, Job Dekker, Leonid Mirny, and Tom Misteli. 2019. “Extensive Heterogeneity and Intrinsic Variation in Spatial Genome Organization.” Cell 176 (6): 1502–15.e10.

      Fudenberg, Geoffrey, and Maxim Imakaev. 2017. “FISH-Ing for Captured Contacts: Towards Reconciling FISH and 3C.” Nature Methods 14 (7): 673–78.

      Hafner, Antonina, Minhee Park, Scott E. Berger, Elphège P. Nora, and Alistair N. Boettiger. 2022. “Loop Stacking Organizes Genome Folding from TADs to Chromosomes.” bioRxiv. https://doi.org/10.1101/2022.07.13.499982.

      Hsieh, Tsung-Han S., Claudia Cattoglio, Elena Slobodyanyuk, Anders S. Hansen, Xavier Darzacq, and Robert Tjian. 2022. “Enhancer-Promoter Interactions and Transcription Are Largely Maintained upon Acute Loss of CTCF, Cohesin, WAPL or YY1.” Nature Genetics 54 (12): 1919–32.

      Hsieh, Tsung-Han S., Claudia Cattoglio, Elena Slobodyanyuk, Anders S. Hansen, Oliver J. Rando, Robert Tjian, and Xavier Darzacq. 2020. “Resolving the 3D Landscape of Transcription-Linked Mammalian Chromatin Folding.” Molecular Cell 78 (3): 539–53.e8.

      Kloetgen, Andreas, Palaniraja Thandapani, Panagiotis Ntziachristos, Yohana Ghebrechristos, Sofia Nomikou, Charalampos Lazaris, Xufeng Chen, et al. 2020. “Three-Dimensional Chromatin Landscapes in T Cell Acute Lymphoblastic Leukemia.” Nature Genetics 52 (4): 388–400.

      Mach, Pia, Pavel I. Kos, Yinxiu Zhan, Julie Cramard, Simon Gaudin, Jana Tünnermann, Edoardo Marchi, et al. 2022. “Cohesin and CTCF Control the Dynamics of Chromosome Folding.” Nature Genetics 54 (12): 1907–18.

      Mateo, Leslie J., Sedona E. Murphy, Antonina Hafner, Isaac S. Cinquini, Carly A. Walker, and Alistair N. Boettiger. 2019. “Visualizing DNA Folding and RNA in Embryos at Single-Cell Resolution.” Nature 568 (7750): 49–54.

      Murphy, Sedona, and Alistair Nicol Boettiger. 2022. “Polycomb Repression of Hox Genes Involves Spatial Feedback but Not Domain Compaction or Demixing.” bioRxiv. https://doi.org/10.1101/2022.10.14.512199.

      Nora, Elphège P., Anton Goloborodko, Anne-Laure Valton, Johan H. Gibcus, Alec Uebersohn, Nezar Abdennur, Job Dekker, Leonid A. Mirny, and Benoit G. Bruneau. 2017. “Targeted Degradation of CTCF Decouples Local Insulation of Chromosome Domains from Genomic Compartmentalization.” Cell 169 (5): 930–44.e22.

      Nuebler, Johannes, Geoffrey Fudenberg, Maxim Imakaev, Nezar Abdennur, and Leonid A. Mirny. 2018. “Chromatin Organization by an Interplay of Loop Extrusion and Compartmental Segregation.” Proceedings of the National Academy of Sciences of the United States of America 115 (29): E6697–6706.

      Rao, Suhas S. P., Su-Chen Huang, Brian Glenn St Hilaire, Jesse M. Engreitz, Elizabeth M. Perez, Kyong-Rim Kieffer-Kwon, Adrian L. Sanborn, et al. 2017. “Cohesin Loss Eliminates All Loop Domains.” Cell 171 (2): 305–20.e24.

      Su, Jun-Han, Pu Zheng, Seon S. Kinrot, Bogdan Bintu, and Xiaowei Zhuang. 2020. “Genome-Scale Imaging of the 3D Organization and Transcriptional Activity of Chromatin.” Cell 182 (6): 1641–59.e26.

      Takei, Yodai, Shiwei Zheng, Jina Yun, Sheel Shah, Nico Pierson, Jonathan White, Simone Schindler, Carsten H. Tischbirek, Guo-Cheng Yuan, and Long Cai. 2021. “Single-Cell Nuclear Architecture across Cell Types in the Mouse Brain.” Science 374 (6567): 586–94.

      Wang, Siyuan, Jun-Han Su, Brian J. Beliveau, Bogdan Bintu, Jeffrey R. Moffitt, Chao-Ting Wu, and Xiaowei Zhuang. 2016. “Spatial Organization of Chromatin Domains and Compartments in Single Chromosomes.” Science 353 (6299): 598–602.

    1. Author response:

      The following is the authors’ response to the original reviews.

      eLife assessment 

      This valuable manuscript reports alterations in autophagy present in dopaminergic neurons differentiated from iPSCs in patients with WDR45 mutations. The authors identified compounds that improved the defects present in mutant cells by generating isogenic iPSC without the mutation and performing an automated drug screening. The methodological approaches are solid, but the claims still need to be completed: showing the effects of the identified compounds on iron-related alterations is crucial. The effects of these drugs in vivo would be a great addition to the study. 

      Thank you for this assessment. We agree that further hit validation would be a great addition to the study. At present, we provide this through RNAseq data but not at the protein level. Further validation using in vivo models would also be warranted but is beyond the scope of the current work.

      Public Reviews:

      Reviewer #1 (Public Review): 

      Summary: 

      In the current study, Papandreou et al. developed an iPSC-based midbrain dopaminergic neuronal cell model of Beta-Propeller Protein-Associated Neurodegeneration (BPAN), which is caused by mutations in the WDR45 gene and is known to impair autophagy. They also noted defective autophagy and abnormal BPAN-related gene expression signatures. Further, they performed a drug screening and identified five cardiac glycosides. Treatment with these drugs effectively in improved autophagy defects and restored gene expression. 

      Strengths: 

      Seeing the autophagy defects and impaired expression of BPAN-related genes adds strength to this study. Importantly, this work shows the value of iPSC-based modeling in studying disease and finding therapeutic strategies for genetic disorders, including BPAN. 

      Weaknesses: 

      It is unclear whether these cells show iron metabolism defects and whether treatment with these drugs can ameliorate the iron metabolism phenotypes. 

      We are pleased to ascertain that the reviewer feels the work is an important step in the field for BPAN. We also absolutely agree that secondary hit validation assays showing cardiac glycoside efficacy in restoring patient-related in vitro phenotypes would be very valuable. 

      We set up  assays to investigate iron metabolism phenotypes, including  western blotting for Ferritin Heavy Chain 1, Transferrin and Ferroportin 1 (SLC40A1) at day 65 of differentiation, but found no significant difference when comparing patient lines to controls (data not shown). 

      We also performed cell viability studies using the Alamar Blue assay on Day 11 ventral midbrain progenitors after 24 hour exposure to a) glucose starvation, b) media with no antioxidants (L-ascorbic acid and B-27 supplement), c) oxidative stressors MPP+ 1mM and FeCl3 100 uM (MPP+ and FeCl3 as suggested by  Seibler et al  (Brain 2018 PMID: 30169597). We found no difference in cell viability between patients, age-matched controls and CRISPR lines (data not shown). Additionally, we examined lysosomal function in BPAN Day 11 progenitors (2 age-matched controls, 3 patient lines, 2 isogenic controls); again, using the autophagy flux treatments mentioned above) via LAMP1 high content imaging immunofluorescence. We have seen no difference in LAMP1 puncta production between patient lines and controls and, therefore, have not included this data in our revision.

      Overall, we agree with the reviewer that  more validation of the compound hits’ ability to restore robust BPAN-related in vitro and in vivo phenotypes (including studies of iron metabolism/ homeostasis) will be needed in the future – this could be undertaken in more mature 2D culture systems, 3D organoid models and disease-relevant animal models.

      Reviewer #2 (Public Review): 

      Summary: 

      In this manuscript, the authors aim to demonstrate that cardiac glycosides restore autophagy flux in an iPSC-derived mDA neuronal model of WDR45 deficiency. They established a patientderived induced pluripotent stem cell (iPSC)-based midbrain dopaminergic (mDA) neuronal model and performed a medium-throughput drug screen using high-content imaging-based IF analysis. Several compounds were identified to ameliorate disease-specific phenotypes in vitro. 

      Strengths: 

      This manuscript engaged in an important topic and yielded some interesting data. 

      Weaknesses: 

      This manuscript failed to provide solid evidence to support the conclusion. 

      We are pleased that the reviewer assesses the work as conceptually important and interesting. We also agree that more work to understand the pathophysiology underpinning BPAN, and the mechanisms through which cardiac glycosides help restore affected intracellular pathways are warranted. More validation of the compound hits’ ability to restore broader disease-specific in vitro and in vivo phenotypes is also needed in future studies. 

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors): 

      Overall, this is a nicely executed study. Here are my suggestions:

      (1) Showing the iron phenotypes in these cells and testing if treatment with these drugs rescues iron-related phenotypes will add significant value to this work. 

      We absolutely agree that secondary hit validation assays showing  glycoside efficacy in restoring disease-related in vitro phenotypes is warranted. The main issue here is identifying how WDR45 deficiency leads to cellular dysfunction or dyshomeostasis and early death. Unfortunately, the mechanism by which this happens is not yet delineated, and more relevant future work is needed. 

      In our lab, we set up such assays. Regarding iron metabolism-related phenotypes, we performed western blotting for Ferritin Heavy Chain 1, Transferrin and Ferroportin 1 (SLC40A1) but found no significant difference when comparing patient lines to controls (data not shown). We also performed cell viability studies using the Alamar Blue assay on Day 11 ventral midbrain progenitors after 24 hour exposure to a) glucose starvation, b) media with no antioxidants (L-ascorbic acid and B-27 supplement), c) oxidative stressors MPP+ 1mM and FeCl3 100 uM (MPP+ and FeCl3, as suggested by the Seibler et al paper, Brain 2018 PMID: 30169597). We found no difference in cell viability between patients, age-matched controls and CRISPR lines (data not shown). Additionally, we examined lysosomal function in BPAN Day 11 progenitors (2 age-matched controls, 3 patient lines, 2 isogenic controls; again, using the autophagy flux treatments mentioned above) via LAMP1 high content imaging immunofluorescence. We have seen no difference in LAMP1 puncta production between patient lines and controls and, therefore, have not included this data in our revision.

      (2) Assessing the effects of these drugs in an in vivo model will strengthen this study. 

      This is a valid point, and we agree that further validation using in vivo models such as the reported BPAN mouse models, would be warranted in the future.

      Reviewer #2 (Recommendations For The Authors): 

      While this manuscript engaged in an important topic and yielded exciting data, there are still some concerns for the authors to address. 

      (1) The biggest concern is that the characterization of autophagic flux solely with LC3 is not convincing enough. Although ATG2A and ATG2B are required for phagophore formation during autophagy, their interaction with WDR45 seems dispensable for phagophore formation for a mild autophagy defect observed in WDR45 knockout cell models and mouse models. All wdr45/- mice are born normally and survive the postnatal starvation period, unlike mice lacking essential ATG proteins, like ATG5, ATG7, and VMP1. The functional relevance of WDR45 and autophagy remains to be fully established. Overall, this manuscript failed to provide solid evidence to support the conclusion. 

      This is a valid point. We have looked at autophagy flux in fibroblasts and Day 11 ventral midbrain stage. For fibroblasts, 1 control line and three patient lines were used; for Day 11 progenitors, 2 control lines, 2 patient lines and one isogenic control were used. Cells from different lines were cultured on the same 96-well plates, at the same plating density, and treated concurrently to minimise fluctuations in flux due to unaccounted factors, e.g., confluence, incubator temperature etc. Treatments consisted of a) DMSO (basal condition), b) Bafilomycin A1 (flux inhibition via autophagosome/ lysosome fusion blockage), c) Torin A1 (mTOR inhibitor, flux inducer) and d) combination of Bafilomycin A1 and Torin 1, for a total of 3 hours. In all these conditions, LC3 puncta production in BPAN lines was reduced when compared to controls. We believe that these results indicate defective autophagy flux in BPAN in different cell types.

      Moreover, we have demonstrated defects in autophagy-related gene (ATG) expression through RNA sequencing, that is restored after CRISPR/Cas9-mediated correction of the disease-causing mutation in a patient derived line, but also after treatments with torin 1 and digoxin. These results suggest a dysregulated ATG network in WDR45 deficiency. 

      (2) WDR45 is linked to BPAN. Do the authors detect any iron accumulation in DA progenitors or mDA neurons? 

      Regarding iron metabolism-related phenotypes, we performed western blotting for Ferritin Heavy Chain 1, Transferrin and Ferroportin 1 (SLC40A1) but found no significant difference when comparing patient lines to controls (data not shown). We agree that more studies into the links between WDR45 deficiency, iron metabolism and neurodegeneration are needed. 

      (3) It is necessary to detect LC3 protein levels by western blot to distinguish LC3I and LC3II and gain a more accurate understanding for the process of LC3 - marked autophagosome. 

      Thank you for this valid point. 

      Due to the very dynamic nature of autophagy, and many factors influencing flux , we have not been able to meaningfully examine autophagy-related markers in an iPSC-derived system that is also inherently prone to variability.  Therefore, LC3 and p62 values exhibited high variability, and hence we are unable to adequately interpret them (data not shown). Instead, in this manuscript we have focused on high-content assays with cells cultured and treated simultaneously at Day 11 of differentiation, which have shown autophagy flux defects.

      We have looked at autophagy flux in fibroblasts and at Day 11 ventral midbrain stage. For fibroblasts, 1 control line and three patient lines were used; for Day 11 progenitors, 2 control lines, 2 patient lines and one isogenic control were used. Cells from different lines were cultured on the same 96-well plates, at the same plating density, and treated concurrently to minimise fluctuations in flux due to unaccounted factors, e.g., confluence, incubator temperature etc. Treatments consisted of a) DMSO (basal condition), b) Bafilomycin A1 (flux inhibition via autophagosome/ lysosome fusion blockage), c) Torin A1 (mTOR inhibitor, flux inducer) and d) combination of Bafilomycin A1 and Torin 1, for a total of 3 hours. In all these conditions, LC3 puncta production in BPAN lines was reduced when compared to controls. We believe that these results indicate defective autophagy flux in BPAN in different cell types.

      (4)  Some methodological details need to be included - detailed descriptions of various quantifications for IF staining should be provided. For example, it is unclear how "% cells+ ve for marker combination" (Fig.1B) was quantified, and there are many unconventional units such as "% cells+ ve for marker combination "; please check and correct them. 

      Thank you for pointing this out. We have changed the legends in Figure 1B and Supplementary Figure 2C to ‘percentage of cells positive for marker combination’. Moreover, in our Methods section (Immunocytochemistry sub-section), we have updated the text as follows, to give more clarification on the process of marker quantification (Page 25, Paragraph 2): ‘For quantification, 4 random fields were imaged from each independent experiment. Subsequently, 1200 to 1800 randomly selected nuclei were quantified using ImageJ (National Institutes of Health). Manual counting for nuclear (DAPI) staining and co-staining with the marker of interest was performed, and percentages of cells expressing combinations of markers were calculated as needed.’

      (5) In Figure 3 and Figure 4, the quantifications for IF images were inconsistent with the shown IF image, for example, the representative IF image for detection of LC3 with Tor1 treatment. 

      Due to space restrictions, we have not included representative images from all patient lines, and every treatment condition depicted in the graphs. In Figure 3 (describing the set-up of the LC3 screening assay), only one control line and one patient line is shown in basal (DMSO-treated) conditions. In Supplementary Figure 4D, only one patient line and the corresponding isogenic control line are depicted after Torin 1 treatments.

      Quantification of the LC3 puncta in this assay (20 fields per well, each condition in a technical duplicate, n=8 biological replicates) was automated, using ImageJ and R Studio, with subsequent statistical significance calculation on GraphPad Prism. Hence, the immunofluorescence figures depict a reduction in LC3 puncta per nuclei numbers in patient-derived lines versus controls, but not the exact difference after automated image analysis. We have detailed this in the Methods section (High content imaging-based immunofluorescence subsection) of our manuscript (Page 26, Paragraph 2): ‘For all high content imaging-based experiments, the PerkinElmer Opera Phenix microscope was used for imaging. 20 fields were imaged per well, at 40 x magnification, Numerical Aperture 1.1, Binning 1. Image analysis was performed using ImageJ and R Studio.60 For the drug screen, puncta values were normalised according to positive and negative controls from each plate and Z-scores for each compound screened were generated.  Statistical significances were calculated on GraphPad Prism V.

      8.1.2. software (GraphPad Software, Inc.; https://www.graphpad.com/scientific-software/prism/).’

      (6)  In Figure 4C, LC3 should be co-stain with the DA progenitor maker to indicate that the intercellular LC3 level within the projectors. 

      Thank you for raising this point. The images from Figure 4C were obtained during the medium throughput drug screen, where the FOXA2 co-stain was not used. The FOXA2 stain was only used during the initial set-up of the LC3 screening assay, to confirm that the Day 11 cells had ventral midbrain identities. Indeed, most of the Day 11 cells used in the high content imaging-related experiments were FOXA2-positive, as shown in Figure 3 and Supplementary Figure 4.

      (7) Examining P62, one of the most important indicators for autophagic flux, should be parallel with LC3 detection. In Figure 5A, P62 accumulation seems not significant in patient 02 Day 11 ventral midbrain projectors; how about that in Day 65? 

      The reviewer is raising a valid point. We have not examined p62 and LC3 staining in parallel in high content imaging-based experiments but agree that this would be good to examine in future studies. 

      Some other minor points 

      (8) It needs to give a more detailed description of the tested compounds you mentioned in the text. 

      Thank you for this point. We have elaborated on the contents of the Prestwick library used for the screening, as below (Page 9, Paragraph 3): ‘We then utilised this high-content imaging LC3 assay to identify novel compounds of potential therapeutic interest for BPAN by screening the Prestwick Chemical Library containing 1,280 compounds, of which more than 95% FDA/ EMA approved.’

      In the Methods Section, Page 25, Paragraph 5, we also detail the library as follows: ‘For drug screening, the Prestwick Chemical Library (1,280 compounds, 95% FDA/ EMA approved, 10 mM in DMSO, https://www.prestwickchemical.com/screening-libraries/prestwick-chemical-library/) was used; cells were treated with compounds for 24 hours at 10 μM final concentration.’

      (9) Please pay attention to the abbreviation; many gene names only have abbreviations without full names when they first appear in the context. 

      Thank you for this point. We have corrected this in various places throughout the manuscript and especially in the introduction section.

      (10) Almost all figures have the problem of insufficient image resolution, or the font of the indicated words needs to be bigger to be distinguished clearly, like in Fig.1B, 1C, 1E. 

      Thank you for this point, we have ensured that all figures have adequate image resolution as specified by the journal requirements. 

      (11) The sample size or biological repeated times should be given in figure legends. 

      Thank you for this point. We have now indicated numbers of biological replicates where appropriate.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The study investigated how root cap cell corpse removal affects the ability of microbes to colonize Arabidopsis thaliana plants. The findings demonstrate how programmed cell death and its control in root cap cells affect the establishment of symbiotic relationships between plants and fungi. Key details on molecular mechanisms and transcription factors involved are also given. The study suggests reevaluating microbiome assembly from the root tip, thus challenging traditional ideas about this process. While the work presents a key foundation, more research along the root axis is recommended to gain a better understanding of the spatial and temporal aspects of microbiome recruitment.

      We thank Reviewer #1 for their positive evaluation and critical feedback.

      Reviewer #2 (Public Review):

      Summary:

      The authors identify the root cap as an important key region for establishing microbial symbioses with roots. By highlighting for the first time the crucial importance of tight regulation of a specific form of programmed cell death of root cap cells and the clearance of their cell corpses, they start unraveling the molecular mechanisms and its regulation at the root cap (e.g. by identifying an important transcription factor) for the establishment of symbioses with fungi (and potentially also bacterial microbiomes).<br /> Strengths:

      It is often believed that the recruitment of plant microbiomes occurs from bulk soil to rhizosphere to endosphere. These authors demonstrate that we have to re-think microbiome assembly as a process starting and regulated at the root tip and proceeding along the root axis.

      Weaknesses:

      The study is a first crucial starting point to investigate the spatial recruitment of beneficial microorganisms along the root axis of plants. It identifies e.g. an important transcription factor for programmed cell death, but more detailed investigations along the root axis are now needed to better understand - spatially and temporally - the orchestration of microbiome recruitment.

      We appreciate Reviewers #2 insightful comments and agree that further investigations are needed to gain a deeper understanding of the intricate interplay between the spatial and temporal recruitment of the microbiome and developmental cell death in future studies.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      - Given that the smb-3 altered PCD phenotype has already been reported in several publications, the aim of using Evans blue staining to highlight LRC cell corpses along the root surface of smb-3 is not clear. Maybe S1 would be more informative as main figure.

      As an indicator of membrane integrity loss and cell death, Evans blue staining was used to characterize all dPCD mutants described in this study and their interactions with S. indica. To avoid redundancies with other publications, we restructured Figure 1, incorporating panel S1A to provide an introductory overview of the smb-3 phenotype. The former Figure 1B is now located in Figure S1.

      - It is not clear how the analysis of protein aggregates fits into the rationale, why analyze these formations? What role should they have in the process of PCD or interaction with microbes?

      The manuscript has been modified the following way to clarify the analysis of protein aggregates in the dPCD mutants: “The transcription factor SMB promotes the expression of various dPCD executor genes, including proteases that break down and clear cellular debris and protein aggregates following cell death induction. In the LRCs of smb-3 mutants, the absence of induction of these proteases potentially explains the accumulation of protein aggregates in uncleared dead LRC cells.”.

      - Is the accumulation of misfolded and aggregated proteins also present during physiological PCD of LRC cells in the WT?

      The biochemical mechanisms underlying PCD can vary depending on the affected cell types and tissues. Within the root tip of Arabidopsis, two different modes of PCD have been described, differentiating between columella root cap cells and LRC cells. For clarification the manuscript has been adjusted the following way:” Under physiological conditions in WT roots, we previously observed protein aggregate accumulation in sloughed columella cell packages, but not during dPCD of distal LRC clearance (Llamas et al., 2021). This aligns with the findings that dPCD of the columella is affected by the loss of autophagy, while dPCD of the LRC is not (Feng et al., 2022).”.

      - I suggest being more careful when using the term "root cap" instead of "LRC" to reduce ambiguity (i.e. lines 56; 137), maybe you need to double-check the text.

      We agree with the reviewer that a clear distinction between “root cap” and “LRC” is very important. We have adjusted the manuscript to avoid any misunderstandings.

      - A technical question regarding qPCR sample preparation: doesn't washing the smb-3 roots cause a loss of LRC stretched cells and would it therefore lead to an alteration of the results?

      The mechanical washing of roots is essential to ensure a clear distinction between intraradical fungal growth and accommodation around roots. While we cannot exclude the possibility that mechanical washing removes LRC cells, intraradical quantification of fungal biomass aims to measure S. indica growth in the epidermal and cortical cell layers, underneath the uncleared LRC cells. Thus, we complemented this assay with extraradical colonization assays to quantify external fungal biomass with intact LRC cells.

      - It is not clear if S. indica promotes PCD in wt and/or in smb-3, could you comment on it?

      It remains an open question whether and to what extent S. indica promotes PCD, although there are strong indications that this fungus activates different cell death pathways at various developmental stages, including dAdo mediated cell death. We posit that certain microbes have evolved to regulate and manipulate different dPCD processes to enhance colonization, implicating a complex crosstalk between various PCD pathways. We have adjusted the manuscript to underscore this perspective the following way:” Transcriptomic analysis of both established and predicted key dPCD marker genes revealed diverse patterns of upregulation and downregulation during S. indica colonization. These findings provide a valuable foundation for future studies investigating the dynamics of dPCD processes during beneficial symbiotic interactions and the potential manipulation of these processes by symbiotic partners.”.

      - How analysis of BFN1 expression in whole root confirms its downregulation at the onset of cell death in S. indica-colonized plants. Moreover, is the transcriptional regulation of BFN1 important for PCD, or is the BFN1 protein level correlated with the establishment of cell death?

      BFN1 gene expression in Arabidopsis shows a transient decrease around 6–8 days after S. indica inoculation, coinciding with the proposed onset of S. indica-induced cell death. While we can only speculate on a potential correlation between BFN1 downregulation and the onset of S. indica-induced cell death, we have described other pathways through which S. indica induces cell death. For example, it produces small metabolites such as dAdo through the synergistic activity of two secreted fungal effector proteins (Dunken et al., 2023). This suggests that S. indica recruits different pathways to induce cell death, which may vary depending on the host plant and interact with each other as shown for many other immunity related cell death pathways which share some components.

      Regarding the second part of the question, BFN1 expression correlates positively with cells primed for dPCD (Olvera-Carrillo et al., 2015). BFN1 protein accumulates in the ER lumen and is released into the cytoplasm upon cell death induction to exert its DNase functions (Fendrych et al., 2014). If accumulation of BFN1 is cause or consequence of cell death remains to be validated.

      - Line 190: there is a typo "in the nucleus", this is superfluous given that the reporter is nuclear.

      The manuscript has been adjusted accordingly; see line L208. However, we consider the distinction important as we aim to emphasize the difference between the nuclear localization of the fluorescent signal in "healthy" cells and the dispersed fluorescent signal spreading in the cytoplasm of cells priming or undergoing dPCD.

      - Line 255: there is a typo, stem cells can not differentiate.

      The manuscript has been adjusted.

      - During root hair development some epidermal cells undergo PCD to allow the emergence of root hairs. Furthermore, during plant defense against pathogens, epidermal cells undergo cell death to prevent further colonization. Have these cell death events been reported to occur under physiological conditions during development?

      Plant defence responses in roots and the hypersensitive response (HR) still remain largely unexplored. The HR is a defence mechanism that consists of a localized and rapid cell death at the site of pathogen invasion. It is triggered by pathogenic effector proteins, usually recognized by intracellular immune receptors (NLRs), and accompanied by other features such as ROS signalling, Ca2+ bursts and cell wall modifications (Balint-Kurti, 2019). Notably, HR has been widely described in leaves, but no strong evidence has been shown for the occurrence of HR in plant roots (Hermanns et al., 2003, Radwan et al., 2005). Additionally, previous studies have not shown any transcriptional parallels between common dPCD marker genes and HR PCD in Arabidopsis (Olvera-Carrillo et al., 2015; Salguero-Linares et al., 2022).

      While S. indica is a beneficial root endophyte that does not induce classical hypersensitive response (HR) in host plants, the impact of dPCD on S. indica colonization should not be overlooked. S. indica promotes root hair formation in its hosts (Saleem et al., 2022), and in Arabidopsis, root hair cells naturally undergo cell death 2–3 weeks after emergence (Tan et al., 2016). This aspect could be particularly relevant for understanding the dynamics of S. indica colonization.

      - Showing the analysis of pBFN1 in smb-3 would help in validating the idea that the downregulation of BFN1 by S. indica is regulated independently of SMB.

      SMB is known to be a root cap specific transcription factor (Willemsen et al., 2008; Fendrych et al., 2014). The pBFN1:tdTOMATO reporter line shows that BFN1 expression occurs in many different tissues undergoing dPCD, above and below ground, where SMB is not expressed or present. Therefore, we can postulate that the downregulation of BFN1 by S. indica in the differentiation zone is regulated independently of SMB.

      - A question of great interest still remains open: is it the microbe that induces the regulation of BFN1 causing a delay in cell clearance and favoring the infection or is it the plant that reduces BFN1 to favor the interaction with the microbe? In other words, is the mechanism a response to stress or a consolidation of the interaction with the host?

      We agree with this reviewer that this question remains open. Whether active interference by fungal effector proteins, fungal-derived signaling molecules, or a systemic response of Arabidopsis roots underlies BFN1 downregulation during S. indica colonization remains to be investigated. Yet, it is noteworthy that the downregulation of BFN1 in Arabidopsis is not specific to S. indica but also occurs during interactions with other beneficial microbes such as S. vermifera and two bacterial synthetic communities. This suggests that it could be a broader plant response to microbial presence. However, at this stage, we can only speculate on these possibilities. We therefore changed some of the statements in the paper to moderate our conclusions: e.g. “Expression of plant nuclease BFN1, which is associated with senescence, is modulated to facilitate root accommodation of beneficial microbes” to leave open who exactly is controlling BFN1, the plant or the microbes.

      Reviewer #2 (Recommendations For The Authors):

      This is a straightforward study, well executed and well written. I have only a few specific comments, and some concern the statistics which is a bit more serious and where I would like to get answers first. Looking at the figures, I am sure that the authors can easily clarify the issues in the manuscript.

      We appreciate the positive feedback and included clarifications in the statistical section in the material and methods.

      Statistics:

      - The statistics are not detailed in Material and Methods, but are only briefly indicated in the headings of the figures. Include a statistics section in Material and Methods.

      We added an extra paragraph with statistical analysis in the Material and Method section for clarifications, which reads as follows:” All statistical analyses, except for the transcriptomic analysis, were performed using Prism8. Individual figures state the applied statistical methods, as well as p and F values. p-values and corresponding asterisks are defined as following, p<0.05 *, p<0.01**, p<0.001***.”.

      - Figure 1/ Figure S3, etc: First of all, a **** with p< 0.00001 does not exist! Significance in statistics just means that we assume that there is a difference with some kind of probability that has been defined as p<0.05 *, p<0.01**, p<0.001***, and NOT more! Even if p<0.000001, it is still p<0.001***. Stating the meaning of asterisks in a separate Statistics section in Materials and Methods would also avoid repetitive explanations (e.g. Figure 4, L68: 'Asterisk indicates significantly different...').

      We agree and have updated the manuscript accordingly. See comment above.  

      - Also, it is advisable to reduce the digits of the p-values to a meaningful length (e.g. Figure 2 L 36: (*P<0.0466) should be (F[1, ?] = ?; p<0.047). The * is not necessary in the text, as p<0.05 is already given. We do not obtain more information by a more exact p-value, because all we need to know is that p<0.05.

      We adjusted the p-values accordingly throughout the manuscript.

      - It is NOT sufficient to communicate just the p-value of a statistical analysis. What is always needed is the F-value (student test and ANOVA) with both nominator and denominator degrees of freedom (e.g. F[2, 10] =) AND the p-value.

      We included F-values throughout the manuscript in all main and supplemental figures to provide more clarity for the readers.

      - The reason becomes clear in Fig. 2D where the authors state that they used 3 biological replicates, each with 40 plants. I assume the statistics was wrongly based on calculating with 120 plants (F[1,120] =) as technical replicates instead of correctly the biological replicates (3 means of 40 technical replicates each, (F[1,3] =))?? If F-value and df had been given, errors like this would be immediately visible - for any reviewer/reader, but also to the authors.<br /> \=>Please re-analyze the statistics correctly.

      To assess S. indica-induced growth promotion, we measured and compared the root length of Arabidopsis plants under S. indica colonization or mock conditions at three different time points. Each genotype and treatment combination involved measuring 50 plants, with each plant serving as an independent biological replicate inoculated with the same S. indica spore solution. For comprehensive statistical analysis, we conducted the experiment a total of 3 times, using fresh fungal inoculum each time, originally referred to as "three biological replicates." We maintain that including all plant measurements is essential for a thorough statistical analysis of our growth promotion experiment. However, in order to avoid confusion, we have updated the figure legend to clarify the experimental set-up as following: “(D) Root length measurements of WT plants and smb-3 mutant plants, during S. indica colonization (seed inoculated) or mock treatment. 50 plants for each genotype and treatment combination were observed and individually measured over a time period of two weeks. WT roots show S. indica-induced growth promotion, while growth promotion of smb-3 mutants was delayed and only observed at later stages of colonization. This experiment was repeater 2 more independent times, each time with fresh fungal material. Statistical analysis was performed via one-way ANOVA and Tukey’s post hoc test (F [11, 1785] = 1149; p < 0.001). For visual representation of statistical relevance each time point was additionally evaluated via one-way ANOVA and Tukey’s post hoc test at 8dpi (F [3, 593] = 69.24; p < 0.001), 10dpi (F [3, 596] = 47.59; p < 0.001) and 14dpi (F [3, 596] = 154.3; p < 0.001).”

      - Figure 2, L 18; Figure 5, L 95, Figure S5 L53, etc: I am worried about executing a statistical test 'before normalization' - what does it mean?? WHY was a normalization necessary, WHAT EXACTLY was normalized and do we see normalized plots that do NOT correspond to the data on which the statistics was based? At least this implies 'before normalization'! Please explain, and/or re-analyze the statistics correctly.

      We agree that the phrasing “before normalization” may lead to confusion, as the normalization of data to the mean of the control group does not alter the statistical analysis. Normalization was performed to achieve a clearer visual representation. Additionally, Evans blue staining is quantified by measuring the mean grey value, which does not correspond to a specific unit. Normalizing the data allows for the representation of relative staining intensities. The manuscript has been adjusted accordingly throughout.

      - Statistics in Figure 1: L8/9: 'in reference to B' is unclear, I guess the mean of the control was used as a reference? This would also explain the variation in relative staining intensity (Figure 1C). if normalization was carried out (see above) all control (WT) values should be exactly 1, but they are not. I guess it was normalized to the mean of the control?

      “In reference to X” or “corresponding to X” typically means that Figure X shows an example image from the dataset on which the statistical quantification is based. We have updated the manuscript throughout the main and supplemental figure legends to use “refers to image shown in X” to avoid confusion.  

      Figure S4, L 42: '(corresponding to A)', see comment above.

      See comment above.

      Figure 5B, L 87: '(in reference to A)'; L93: (in reference to C), etc. - see above. Unclear how A was used as a reference. Was it the mean of A? BUT again only 3 biological replicates! So it has to be the mean of 3 reps that was used as control! OR can we at least say that the 10 measured roots were independent of each other (crucial (!) precondition for executing student's test or ANOVA? Then you would have at least 10 replicates (mean of 4 pictures taken per root for each).

      Quantification of Evans blue staining intensity involved taking 4 pictures along the main root axis of each plant. We re-evaluated the statistical analysis correctly with the averaged datapoints for each plant root. We adjusted main figures (Fig.1C and 5B) and supplementary figures (Fig. S1C and S4B) and changed the material and methods section of the manuscript as following: “4 pictures were taken along the main root axis of each plant and averaged together, for an overview of cell death in the differentiation zone.”.

      - Statistics in Figure 4, L 69: what means 'adjusted p-value'? Which analysis?

      The material and method section of the manuscript has been adjusted as following for clarification: “Differential gene expression analysis was performed using the R package DESeq2 (Love et al., 2014). Genes with an FDR adjusted p-value < 0.05 were considered as differentially expressed genes (DEGs). The adjusted p-value refers to the transformation of the p-value obtained with the Wald test after considering multiple testing. To visualize gene expression, genes expression levels were normalized as Transcript Per kilobase million (TPM).”.

      - Statistics in Figure 5, L102-105: see above! Were the statistics correctly calculated with 7 reps, or wrongly with 30? # I guess each time point was normalized to the mean of WT? By the way, it is not clear if repeated measurements were done on the same plants. If repeated measurements were done on the SAME plants, then these data are statistically not independent anymore (time-series analysis), and e.g. MANOVA must be used and significant (!) before proceeding to ANOVA and Tukey.

      The statistics for quantifying intraradical colonization of Arabidopsis roots were calculated with 7 replicates. For each replicate, 30 plants were pooled to obtain sufficient material for RNA extraction and cDNA synthesis. Plants from the same genotype were harvested separately for each time point, ensuring that the time points are statistically independent from one another.

      Statistics Fig. S1, L 11-12: see above, '5 plants were imaged for each mock and ..., evaluating 4 pictures ...' That means you have means of 4 pictures for 5 biological replicates - the figure shows 20 replicates. However, the statistics must be based on 5 reps! You may indicate the 4 pictures per root by different colours. Change throughout all figures and calculate the statistics correctly (show this by indicating the correct df in your statistics as discussed above).

      We have conducted a re-evaluation of the statistical analysis of Evans blue staining for all figures presented throughout the manuscript. See comment above.

      Statistics Fig. S3, L 31: 'Relative quantification of ...' see above, relative to what? Explain this also clearly in Statistics in Materials and Methods.

      Relative quantification refers to normalizing data to the mean of the corresponding control group. Figure legends have been revised to clarify this point.

      Statistics Fig. S5, L 57/58: 'Genes are clustered using spearmen correlation as distance measure'. If I understand it correctly, Spearman correlation is NOT a distance measure. You used Spearman correlation to cluster gene expression. Now it would be interesting to know WHICH clustering method was used, e.g. a hierarchical or non-hierarchical clustering method? and which one, e.g. single linkage, complete linkage? The outcome depends very much on the clustering method. Therefore, this information is important.

      To perform gene clustering, we set the option “clustering_distance_rows = "spearman" “ of the Heatmap function included in the ComplexHeatmap package. The function first computes the distance matrix using the formula 1 - cor(x, y, method) with Spearman as correlation method. It then performs hierarchical clustering using the complete linkage method by default.

      # Arabidopsis is a genus name and by convention, this has to be written throughout the MS in italics - even if the authors define Arabidopsis thaliana (in italics) = Arabidopsis (without).

      # typos

      L 24: smb-3 mutants (must be explained)

      L 83 insert: ...two well-characterized SMB loss-of-function ...

      While smb-3 is a SMB loss-of-function mutant bfn1-1 is a BFN1 loss-of-function mutant, independent of SMB.

      L 93: The switch between the biotrophic..

      L 119: distal border

      L 125: aggregates in the smb-3 mutant

      L 132: between the meristematic

      L 177/178: was observed at 6 dpi in Arabidopsis colonized by S. indica.

      L 250: colonization stages by S. indica.

      L 288: and root cell death (RCD)

      L 289: and towards...

      L 296: dPCD protects the

      L 304: This raises the

      L 351: to remove loose

      All the above-mentioned typos have been addressed in the manuscript.

      Materials and Methods

      L 327: give composition and supplier of MYP medium

      L 344 name supplier of MS medium

      L 338 name supplier of PNM medium

      L 353: replace 'Following,..' with 'Subsequently, ..'

      L 360: replace 'on plate' with 'on the agar plate' - change throughout the Materials and methods!

      L 360: name supplier of Alexa Fluor 488

      L 363: name supplier of (MS) square plate

      L 377: insert comma: After cleaning, the roots...

      L 394: explain the acronym and name supplier of PBS

      L 399: explain the acronym and name supplier of TBST

      All the above-mentioned comments in the material and methods have been addressed in the manuscript.  

      Figure 2G) x-axis, change order: Hoechst/Proteostat

      Figure 3, L53: propidium iodide: name supplier

      Figure 4, L68: Asterisks

      L 60: explain LRC

      L 67, L69, L70: explain the acronym TPM and how expression values were measured in Materials and Methods, the brief explanation in the figure is unclear and not sufficient

      All the above-mentioned comments in the figure legends have been addressed.

      Figure S5, L50: explain 'SynComs'

      L 51: corrects 30 plans => 30 plants

      L 56: vaules => values

      L 57: use capital letter: Spearman correlation

      All the above-mentioned comments in the supplemental figure legends have been addressed.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this manuscript the authors investigate the contributions of the long noncoding RNA snhg3 in liver metabolism and MAFLD. The authors conclude that liver-specific loss or overexpression of Snhg3 impacts hepatic lipid content and obesity through epigenetic mechanisms. More specifically, the authors invoke that nuclear activity of Snhg3 aggravates hepatic steatosis by altering the balance of activating and repressive chromatin marks at the Pparg gene locus. This regulatory circuit is dependent on a transcriptional regulator SNG1.

      Strengths:

      The authors developed a tissue specific lncRNA knockout and KI models. This effort is certainly appreciated as few lncRNA knockouts have been generated in the context of metabolism. Furthermore, lncRNA effects can be compensated in a whole organism or show subtle effects in acute versus chronic perturbation, rendering the focus on in vivo function important and highly relevant. In addition, Snhg3 was identified through a screening strategy and as a general rule the authors the authors attempt to follow unbiased approaches to decipher the mechanisms of Snhg3.

      Weaknesses:

      Despite efforts at generating a liver-specific knockout, the phenotypic characterization is not focused on the key readouts. Notably missing are rigorous lipid flux studies and targeted gene expression/protein measurement that would underpin why loss of Snhg3 protects from lipid accumulation. Along those lines, claims linking the Snhg3 to MAFLD would be better supported with careful interrogation of markers of fibrosis and advanced liver disease. In other areas, significance is limited since the presented data is either not clear or rigorous enough. Finally, there is an important conceptual limitation to the work since PPARG is not established to play a major role in the liver.

      We thank the reviewer for the nice comment. As the reviewer comment, the manuscript still exists some shortcomings, we added partial shortcomings in the section of Discussion, please check them in the third paragraph on p17 and the first paragraph on p18.

      We agree the reviewer comment, there are still conflicting conclusions about the role of PPARγ in MASLD. We had discussed it in the section of Discussion, please check them in the first paragraph on p13.

      Reviewer #2 (Public Review):

      Through RNA analysis, Xie et al found LncRNA Snhg3 was one of the most down-regulated Snhgs by high fat diet (HFD) in mouse liver. Consequently, the authors sought to examine the mechanism through which Snhg3 is involved in the progression of metabolic dysfunction-associated fatty liver diseases (MASLD) in HFD-induced obese (DIO) mice. Interestingly, liver-specific Sngh3 knockout reduced, while Sngh3 over-expression potentiated fatty liver in mice on a HFD. Using the RNA pull-down approach, the authors identified SND1 as a potential Sngh3 interacting protein. SND1 is a component of the RNA-induced silencing complex (RISC). The authors found that Sngh3 increased SND1 ubiquitination to enhance SND1 protein stability, which then reduced the level of repressive chromatin H3K27me3 on PPARg promoter. The upregulation of PPARg, a lipogenic transcription factor, thus contributed to hepatic fat accumulation.

      The authors propose a signaling cascade that explains how LncRNA sngh3 may promote hepatic steatosis. Multiple molecular approaches have been employed to identify molecular targets of the proposed mechanism, which is a strength of the study. There are, however, several potential issues to consider before jumping to the conclusion.

      (1) First of all, it's important to ensure the robustness and rigor of each study. The manuscript was not carefully put together. The image qualities for several figures were poor, making it difficult for the readers to evaluate the results with confidence. The biological replicates and numbers of experimental repeats for cell-based assays were not described. When possible, the entire immunoblot imaging used for quantification should be presented (rather than showing n=1 representative). There were multiple mis-labels in figure panels or figure legends (e.g., Fig. 2I, Fig. 2K and Fig. 3K). The b-actin immunoblot image was reused in Fig. 4J, Fig. 5G and Fig. 7B with different exposure times. These might be from the same cohort of mice. If the immunoblots were run at different times, the loading control should be included on the same blot as well.

      We thank the reviewer for the detailed comment. We have provided the clear figures in revised manuscript, please check them.

      The biological replicates and numbers of experimental repeats for cell-based assays had been updated and please check them in the manuscript.

      The entire immunoblot imaging used for quantification had been provided in the primary data. Please check them.

      The original Figure 2I, Figure 2K, Figure 3K have been revised and replaced with new Figure 2F, 2H, 3H, and their corresponding figure legends has also been corrected in revised manuscript.

      The protein levels of CD36, PPARγ and β-ACTIN were examined at the same time and we had revised the manuscript, please check them in revised Figure 7B and C.

      (2) The authors can do a better job in explaining the logic for how they came up with the potential function of each component of the signaling cascade. Sngh3 is down-regulated by HFD. However, the evidence presented indicates its involvement in promoting steatosis. In Fig. 1C, one would expect PPARg expression to be up-regulated (when Sngh3 was down-regulated). If so, the physiological observation conflicts with the proposed mechanism. In addition, SND1 is known to regulate RNA/miRNA processing. How do the authors rule out this potential mechanism? How about the hosting snoRNA, Snord17? Does it involve in the progression of NASLD?

      We thank the reviewer for the detailed comment. In this study, although the expression of Snhg3 was decreased in DIO mice, Snhg3 deficiency decreased the expression of hepatic PPARγ and alleviated hepatic steatosis in DIO mice, and Snhg3 overexpression induced the opposite effect, which led us to speculate that the downregulation of Snhg3 in DIO mice might be a stress protective reaction to high nutritional state, but the specific details need to be clarified. This is probably similar to FGF21 and GDF15, whose endogenous expression and circulating levels are elevated in obese humans and mice despite their beneficial effects on obesity and related metabolic complications (Keipert and Ost, 2021). We had added the content in the Discussion section, please check it in the second paragraph on p12.

      SND1 has multiple roles through associating with different types of RNA molecules, including mRNA, miRNA, circRNA, dsRNA and lncRNA. We agree with the reviewer good suggestion, the potential mechanism of SND1/lncRNA-Snhg3 involved in hepatic lipid metabolism needs to be further investigated. We also discussed the limitation in the manuscript and please refer the section of Discussion in the third paragraph on p17.

      Snhg3 serves as host gene for producing intronic U17 snoRNAs, the H/ACA snoRNA. A previous study found that cholesterol trafficking phenotype was not due to reduced Snhg3 expression, but rather to haploinsufficiency of U17 snoRNA (Jinn et al., 2015). Additionally, knockdown of U17 snoRNA in vivo protected against hepatic steatosis and lipid-induced oxidative stress and inflammation (Sletten et al., 2021). In this study, the expression of U17 snoRNA decreased in the liver of DIO Snhg3-HKO mice and remain unchanged in the liver of DIO Snhg3-HKI mice, but overexpression of U17 snoRNA had no effect on the expression of SND1 and PPARγ (figure supplement 5A-C), indicating that Sngh3 induced hepatic steatosis was independent on U17 snoRNA. We had discussed it in revised manuscript, please refer to p15 of the Discussion section.

      References

      JINN, S., BRANDIS, K. A., REN, A., CHACKO, A., DUDLEY-RUCKER, N., GALE, S. E., SIDHU, R., FUJIWARA, H., JIANG, H., OLSEN, B. N., SCHAFFER, J. E. & ORY, D. S. 2015. snoRNA U17 regulates cellular cholesterol trafficking. Cell Metab, 21, 855-67. DIO:10.1016/j.cmet.2015.04.010, PMID:25980348

      KEIPERT, S. & OST, M. 2021. Stress-induced FGF21 and GDF15 in obesity and obesity resistance. Trends Endocrinol Metab, 32, 904-915. DIO:10.1016/j.tem.2021.08.008, PMID:34526227

      SLETTEN, A. C., DAVIDSON, J. W., YAGABASAN, B., MOORES, S., SCHWAIGER-HABER, M., FUJIWARA, H., GALE, S., JIANG, X., SIDHU, R., GELMAN, S. J., ZHAO, S., PATTI, G. J., ORY, D. S. & SCHAFFER, J. E. 2021. Loss of SNORA73 reprograms cellular metabolism and protects against steatohepatitis. Nat Commun, 12, 5214. DIO:10.1038/s41467-021-25457-y, PMID:34471131

      (3) The role of PPARg in fatty liver diseases might be a rodent-specific phenomenon. PPARg agonist treatment in humans may actually reduce ectopic fat deposition by increasing fat storage in adipose tissues. The relevance of the finding to human diseases should be discussed.

      We thank the reviewer for the detailed comment. We agree the reviewer comment, there are still conflicting conclusions about the role of PPARγ in MASLD. We had discussed it in the section of Discussion, please check them in the first paragraph on p13.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      I do not have further recommendations beyond what I mentioned in the original review. The authors have not adequately addressed all the issues but the manuscript has improved and the overall strength of evidence is now solid from incomplete.

      We appreciate positive feedback from the reviewer. While we acknowledge that the updated manuscript has significantly improved, we recognize that it remains incomplete and additional details regarding Snhg3 will be warranted in our future studies. Moreover, we have discussed those potential weakness in the section of Discussion (please refer in the third paragraph on p17 and the first paragraph on p18).

      Reviewer #2 (Recommendations For The Authors):

      The authors have provided explanations and some new data to clarify the comments from the first submission. They have also included the original immunoblots for all the experimental repeats. The CHX protein stability results shown in Fig. 5J were not consistent between experiments, perhaps because the difference was subtle. The results on PPARg protein expression were not clearcut. The inclusion of a PPARg knockdown control would be helpful to validate the specificity of the antibody. Of note, the immunoblots used for Fig. 5I (PA treated) repeats 2, 4 and 1 were identical to those of Fig. 7F repeats 3, 1 and 5. The authors should provide an explanation for the potential issue.

      We thank the further comments and suggestions from the reviewer. We agree with the reviewer comment about Snhg3-mediated SND1 protein stability. In this study, Snhg3 promoted the protein, not mRNA, level of SND1, but Snhg3 subtly increased the SND1 protein stability. We revised the description in the manuscript, “Meanwhile, Snhg3 regulated the protein, not mRNA, expression of SND1 in vivo and in vitro by mildly promoting the stability of SND1 protein (Figures 5G-I).” This revision can be found in the second paragraph on p9. While our findings indicated that Snhg3 can influence SND1 expression at the protein level, we acknowledge the possibility of additional mechanisms contributing to this complex regulatory network. Therefore, further investigation is necessary to clarify whether Snhg3 regulates SND1 protein expression through other potential mechanisms. In light of this, we have added it in the Discussion section. Please refer to the second paragraph on p16.

      In this study, the protein level of PPARγ (molecular weight ~57 kDa) was detected using anti-PPARγ antibody (Abclonal, Cat. A11183), which has been used to determine PPARγ protein expression in 13 published papers as showed in the ABclonal Technology Co., Ltd. (https://abclonal.com.cn/catalog/A11183). And the specificity of this antibody has been validated in Zhang’s study by PPARγ knockdown (Zhang et al., 2019). In our study, hepatic PPARγ protein sometimes showed two bands (~ 57kDa and > 75kDa) using this antibody. It is well established that the PPARγ gene encodes two protein isoforms (PPARγ1, a 477 amino acid protein, and PPARγ2, a 505 amino acid protein) via differential promoter usage and alternative splicing (Gene: Pparg (ENSMUSG00000000440) - Transcript comparison - Mus_musculus - Ensembl genome browser 112) (Hernandez-Quiles et al., 2021). The molecular weight difference between PPARγ1 and PPARγ2 is about 3kd. Therefore, we consider that the band shown larger than 75kd in our study is likely nonspecific. In line with the reviewer’s suggestion, the antibody’s specificity could be further validated by knockdown or knockout of PPARγ in the future.

      We thank the reviewer for the detailed comment. In this study, we tested the effect of Snhg3 overexpression on SND1 protein level and the effect of Snhg3 or Snd1 overexpression on PPARγ protein level in Hepa1-6 cells by transfecting with Snhg3, SND1 and the control, respectively. The results indicated that overexpression of Snhg3 promoted the protein levels of SND1 and PPARγ, and overexpression of SND1 also induced the protein level of PPARγ. Considering scholarly and professional thinking and writing, we firstly showed that overexpression of Snhg3 promoted the protein level of SND1 in Figure 5I, followed by demonstrating that the overexpression of Snhg3 or SND1 elicited PPARγ expression in Figures 7F. However, we acknowledge that this order of presentation may cause confusion. In fact, these experiments were repeatedly performed by multiple times, and we have provided the new original western blot data and analysis for Figure 5I (PA treatment) for further clarification. Please check them.

      References

      HERNANDEZ-QUILES, M., BROEKEMA, M. F. & KALKHOVEN, E. 2021. PPARgamma in Metabolism, Immunity, and Cancer: Unified and Diverse Mechanisms of Action. Front Endocrinol (Lausanne), 12, 624112. DIO:10.3389/fendo.2021.624112, PMID:33716977

      ZHANG, Z., ZHAO, G., LIU, L., HE, J., DARWAZEH, R., LIU, H., CHEN, H., ZHOU, C., GUO, Z. & SUN, X. 2019. Bexarotene Exerts Protective Effects Through Modulation of the Cerebral Vascular Smooth Muscle Cell Phenotypic Transformation by Regulating PPARgamma/FLAP/LTB(4) After Subarachnoid Hemorrhage in Rats. Cell Transplant, 28, 1161-1172. DIO:10.1177/0963689719842161, PMID:31010302

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This paper reports a number of somewhat disparate findings on a set of colorectal tumour and infiltrating T-cells. The main finding is a combined machine-learning tool which combines two previous state-of-the-art tools, MHC prediction, and T-cell binding prediction to predict immunogenicity. This is then applied to a small set of neoantigens and there is a small-scale validation of the prediciton at the end.

      Strengths:

      The prediction of immunogenic neoepitopes is an important and unresolved question.

      Weaknesses:

      The paper contains a lot of extraneous material not relevant to the main claim. Conversely, it lacks important detail on the major claim.

      (1) The analysis of T cell repertoire in Figure 2 seems irrelevant to the rest of the paper. As far as I could ascertain, this data is not used further.

      We appreciate the reviewer for their valuable feedback. We concur with the reviewer's observation that the analysis of the TCR repertoire in Figure 2 should be moved to the supplementary section. We have moved Figures 2B to 2F to Supplementary Figure 2.

      However, the analysis of TCR profiles is still presented in Figure 2, as it plays a pivotal role in the process of neoantigen selection. This is because the TCR profiles of eight (out of 28) patients were used for neoantigen prediction. We have added the following sentences to the results section to explain the importance of TCR profiling: “Furthermore, characterizing T cell receptors (TCRs) can complement efforts to predict immunogenicity.” (Results, Lines 311-312, Page 11)

      (2) The key claim of the paper rests on the performance of the ML algorithm combining NETMHC and pmtNET. In turn, this depends on the selection of peptides for training. I am unclear about how the negative peptides were selected. Are they peptides from the same databases as immunogenic petpides but randomised for MHC? It seems as though there will be a lot of overlap between the peptides used for testing the combined algorithm, and the peptides used for training MHCNet and pmtMHC. If this is so, and depending on the choice of negative peptides, it is surely expected that the tools perform better on immunogenic than on non-immunogenic peptides in Figure 3. I don't fully understand panel G, but there seems very little difference between the TCR ranking and the combined. Why does including the TCR ranking have such a deleterious effect on sensitivity?

      We thank the reviewer for their valuable feedback. We believe the reviewer implies 'MHCNet' as NetMHCpan and 'pmtMHC' as pMTnet tools. First, the negative peptides, which have been excluded from PRIME (1), were not randomized with MHC (HLA-I) but were randomized with TCR only. Secondly, the positive peptides selected for our combined algorithms are chosen from many databases such as 10X Genomics, McPAS, VDJdb, IEDB, and TBAdb, while MHCNet uses peptides from the IEDB database and pMTNet uses a totally different dataset from ours for training. Therefore, there is not much overlap between our training data and the training datasets for MHCNet and pMTNet. Thus, the better performance of our tool is not due to overlapping training datasets with these tools or the selection of negative peptides.

      To enhance the clarity of the dataset construction, we have added Supplementary Figure 1, which demonstrates the workflow of peptide collection and the random splitting of data to generate the discovery and validation datasets. Additionally, we have revised the following sentence: "To objectively train and evaluate the model, we separated the dataset mentioned above into two subsets: a discovery dataset (70%) and a validation dataset (30%). These subsets are mutually exclusive and do not overlap.” (Methods, lines 221-223, page 8).

      Initially, the "combine" label in Figure 3G was confusing and potentially misleading when compared to our subsequent approach using a combined machine learning model. In Figure 3G, the "combine" approach simply aggregates the pHLA and pHLA-TCR criteria, whereas our combined machine learning model employs a more sophisticated algorithm to integrate these criteria effectively. The combined analysis in Figure 3G utilizes a basic "AND" algorithm between pHLA and pHLA-TCR criteria, aiming for high sensitivity in HLA binding and high specificity. However, this approach demonstrated lower efficacy in practice, underscoring the necessity for a more refined integration method through machine learning. This was the key point we intended to convey with Figure 3G. To address this issue, we have revised Figure 3G to replace "combined" with "HLA percentile & TCR ranking" to clarify its purpose and minimize confusion.

      (3) The key validation of the model is Figure 5. In 4 patients, the authors report that 6 out 21 neo-antigen peptides give interferon responses > 2 fold above background. Using NETMHC alone (I presume the tool was used to rank peptides according to binding to the respective HLAs in each individual, but this is not clear), identified 2; using the combined tool identified 4. I don't think this is significant by any measure. I don't understand the score shown in panel E but I don't think it alters the underlying statistic.

      Acknowledging the limitations of our study's sample size, we proceeded to further validate our findings with four additional patients to acquire more data. The final results revealed that our combined model identified seven peptides eliciting interferon responses greater than a two-fold increase, compared to only three peptides identified by NetMHCpan (Figure 5)

      In conclusion, the paper demonstrates that combining MHCNET and pmtMHC results in a modest increase in the ability to discriminate 'immunogenic' from 'non-immunogenic' peptide; however, the strength of this claim is difficult to evaluate without more knowledge about the negative peptides. The experimental validation of this approach in the context of CRC is not convincing.

      Reviewer #2 (Public Review):

      Summary:

      This paper introduces a novel approach for improving personalized cancer immunotherapy by integrating TCR profiling with traditional pHLA binding predictions, addressing the need for more precise neoantigen CRC patients. By analyzing TCR repertoires from tumor-infiltrating lymphocytes and applying machine learning algorithms, the authors developed a predictive model that outperforms conventional methods in specificity and sensitivity. The validation of the model through ELISpot assays confirmed its potential in identifying more effective neoantigens, highlighting the significance of combining TCR and pHLA data for advancing personalized immunotherapy strategies.

      Strengths:

      (1) Comprehensive Patient Data Collection: The study meticulously collected and analyzed clinical data from 27 CRC patients, ensuring a robust foundation for research findings. The detailed documentation of patient demographics, cancer stages, and pathology information enhances the study's credibility and potential applicability to broader patient populations.

      (2) The use of machine learning classifiers (RF, LR, XGB) and the combination of pHLA and pHLA-TCR binding predictions significantly enhance the model's accuracy in identifying immunogenic neoantigens, as evidenced by the high AUC values and improved sensitivity, NPV, and PPV.

      (3) The use of experimental validation through ELISpot assays adds a practical dimension to the study, confirming the computational predictions with actual immune responses. The calculation of ranking coverage scores and the comparative analysis between the combined model and the conventional NetMHCpan method demonstrate the superior performance of the combined approach in accurately ranking immunogenic neoantigens.

      (4) The use of experimental validation through ELISpot assays adds a practical dimension to the study, confirming the computational predictions with actual immune responses.

      Weaknesses:

      (1) While multiple advanced tools and algorithms are used, the study could benefit from a more detailed explanation of the rationale behind algorithm choice and parameter settings, ensuring reproducibility and transparency.

      We thank the reviewer for their comment. We have revised the explanation regarding the rationale behind algorithm choice and parameter settings as follows: “We examined three machine learning algorithms - Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGB) - for each feature type (pHLA binding, pHLA-TCR binding), as well as for combined features. Feature selection was tested using a k-fold cross-validation approach on the discovery dataset with 'k' set to 10-fold. This process splits the discovery dataset into 10 equal-sized folds, iteratively using 9 folds for training and 1 fold for validation. Model performance was evaluated using the ‘roc_auc’ (Receiver Operating Characteristic Area Under the Curve) metric, which measures the model's ability to distinguish between positive and negative peptides. The average of these scores provides a robust estimate of the model's performance and generalizability. The model with the highest ‘roc_auc’ average score, XGB, was chosen for all features.” (Method, lines 225-234, page 8).

      (2) While pHLA-TCR binding displayed higher specificity, its lower sensitivity compared to pHLA binding suggests a trade-off between the two measures. Optimizing the balance between sensitivity and specificity could be crucial for the practical application of these predictions in clinical settings.

      We appreciate the reviewer's suggestion. Due to the limited availability of patient blood samples and time constraints for validation, we have chosen to prioritize high specificity and positive predictive value to enhance the selection of neoantigens.

      (3) The experimental validation was performed on a limited number of patients (four), which might affect the generalizability of the findings. Increasing the number of patients for validation could provide a more comprehensive assessment of the model's performance.

      This has been addressed earlier. Here, we restate it as follows: Acknowledging the limitations of our study's sample size, we proceeded to further validate our findings with four additional patients to acquire more data. The final results revealed that our combined model identified seven peptides eliciting interferon responses greater than a two-fold increase, compared to only three peptides identified by NetMHCpan (Figure 5).

      Reviewer #3 (Public Review):

      Summary:

      This study presents a new approach of combining two measurements (pHLA binding and pHLA-TCR binding) in order to refine predictions of which patient mutations are likely presented to and recognized by the immune system. Improving such predictions would play an important role in making personalized anti-cancer vaccinations more effective.

      Strengths:

      The study combines data from pre-existing tools pVACseq and pMTNet and applies them to a CRC patient population, which the authors show may improve the chance of identifying immunogenic, cancer-derived neoepitopes. Making the datasets collected publicly available would expand beyond the current datasets that typically describe caucasian patients.

      Weaknesses:

      It is unclear whether the pNetMHCpan and pMTNet tools used by the authors are entirely independent, as they appear to have been trained on overlapping datasets, which may explain their similar scores. The pHLA-TCR score seems to be driving the effects, but this not discussed in detail.

      The HLA percentile from NetMHCpan and the TCR ranking from pMTNet are independent. NetMHCpan predicts the interaction between peptides and MHC class I, while pMTNet predicts the TCR binding specificity of class I MHCs and peptides.Additionally, we partitioned the dataset mentioned above into two subsets: a discovery dataset (70%) and a validation dataset (30%), ensuring no overlap between the training and testing datasets.

      To enhance the clarity of the dataset construction, we have added Supplementary Figure 1, which demonstrates the workflow of peptide collection and the random splitting of data to generate the discovery and validation datasets. Additionally, we have revised the following sentence: "To objectively train and evaluate the model, we separated the dataset mentioned above into two subsets: a discovery dataset (70%) and a validation dataset (30%). These subsets are mutually exclusive and do not overlap.” (Methods, lines 221-223, page 8). We also included the dataset construction workflow in Supplementary Figure 1.

      Due to sample constraints, the authors were only able to do a limited amount of experimental validation to support their model; this raises questions as to how generalizable the presented results are. It would be desirable to use statistical thresholds to justify cutoffs in ELISPOT data.

      We chose a cutoff of 2 for ELISPOT, following the recommendation of the study by Moodie et al. (2). The study provides standardized cutoffs for defining positive responses in ELISPOT assays. It presents revised criteria based on a comprehensive analysis of data from multiple studies, aiming to improve the precision and consistency of immune response measurements across various applications.

      Some of the TCR repertoire metrics presented in Figure 2 are incorrectly described as independent variables and do not meaningfully contribute to the paper. The TCR repertoires may have benefitted from deeper sequencing coverage, as many TCRs appear to be supported only by a single read.

      We appreciate the reviewer’s feedback. We have moved Figures 2B through 2F to Supplementary Figure 2. We agree with the reviewer that deeper sequencing coverage could potentially benefit the repertoires. However, based on our current sequencing depth, we have observed that many of our samples (14 out of 28) have reached sufficient saturation, as indicated by Figure 2C. The TCR clones selected in our studies are unique molecular identifier (UMI)-collapsed reads, each representing at least three raw reads sharing the same UMI. This approach ensures that the data is robust despite the variability. It is important to note that Tumor-Infiltrating Lymphocytes (TILs) differ across samples, resulting in non-uniform sequencing coverage among them.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      (1) Please open source the raw and processed data, code, and software output (NetMHCpan, pMTnet), which are important to verify the results.

      NetMHCpan and pMTNet are publicly available software tools (3, 4). In our GitHub repository, we have included links to the GitHub repositories for NetMHCpan and pMTNet (https://github.com/QuynhPham1220/Combined-model).

      (2) Comparison with more state-of-the-art neoantigen prediction models could provide a more comprehensive view of the combined model's performance relative to the current field.

      To further evaluate our model, we gathered additional public data and assessed its effectiveness in comparison to other models. We utilized immunogenic peptides from databases such as NEPdb (5), NeoPeptide (6), dbPepneo (7), Tantigen (8), and TSNAdb (9), ensuring there was no overlap with the datasets used for training and validation. For non-immunogenic peptides, we used data from 10X Genomics Chromium Single Cell Immune Profiling (10-13).The findings indicate that the combined model from pMTNet and NetMHCpan outperforms NetTCR tool (14). To address the reviewer's inquiry, we have incorporated these results in Supplementary Table 6.

      (3) While the combined model shows a positive overall rank coverage score, indicating improved ranking accuracy, the scores are relatively low. Further refinement of the model or the inclusion of additional predictive features might enhance the ranking accuracy.

      We appreciate the reviewer’s suggestion. The RankCoverageScore provides an objective evaluation of the rank results derived from the final peptide list generated by the two tools. The combined model achieved a higher RankCoverageScore than pMTNet, indicating its superior ability to identify immunogenic peptides compared to existing in silico tools. In order to provide a more comprehensive assessment, we included an additional four validated samples to recalculate the rank coverage score. The results demonstrate a notable difference between NetMHCpan and the Combined model (-0.37 and 0.04, respectively). We have incorporated these findings into Supplementary Figure 6 to address the reviewer's question. Additionally, we have modified Figure 5E to present a simplified demonstration of the superior performance of the combined model compared to NetMHCpan.

      (4) Collect more public data and fine-tune the model. Then you will get a SOTA model for neoantigen selection. I strongly recommend you write Python scripts and open source.

      We thank the reviewer for their feedback. We have made the raw and processed data, as well as the model, available on GitHub. Additionally, we have gathered more public data and conducted evaluations to assess its efficiency compared to other methods. You can find the repository here: https://github.com/QuynhPham1220/Combined-model.

      Reviewer #3 (Recommendations For The Authors):

      The Methods section seems good, though HLA calling is more accurate using arcasHLA than OptiType. This would be difficult to correct as OptiType is integrated into pVACtools.

      We chose Optitype for its exceptional accuracy, surpassing 99%, in identifying HLA-I alleles from RNA-Seq data. This decision was informed by a recent extensive benchmarking study that evaluated its performance against "gold-standard" HLA genotyping data, as described in the study by Li et al.(15). Furthermore, we have tested two tools using the same RNA-Seq data from FFPE samples. The allele calling accuracy of Optitype was found to be superior to that of Acras-HLA. To address the reviewer's question, we have included these results in Supplementary Table 2, along with the reference to this decision (Method, line 200, page 07).

      I am not sufficiently expert in machine learning to assess this part of the methods.<br /> TCR beta repertoire analysis of biopsy is highly variable; though my expertise lies largely in sequencing using the 10X genomics platform, typically one sees multiple RNAs per cell. Seeing the majority of TCRs supported by only a single read suggests either problems with RNA capture (particularly in this case where the recovered RNA was split to allow both RNAseq and targeted TCR seq) or that the TCR library was not sequenced deeply enough. I'd like to have seen rarefaction plots of TCR repertoire diversity vs the number of reads to ensure that sufficiently deep sequencing was performed.

      We appreciate the suggestions provided by the reviewer. We agree that deeper sequencing coverage could potentially benefit the repertoires. However, based on our current sequencing depth, we have observed that many of our samples (14 out of 28) have reached sufficient saturation, as indicated by Figure 2C. In addition, the TCR clones selected in our studies are unique molecular identifier (UMI)-collapsed reads, each representing at least three raw reads sharing the same UMI. This approach ensures that the data is robust despite variability. It is important to note that Tumor-Infiltrating Lymphocytes (TILs) differ across samples, resulting in non-uniform sequencing coverage among them. We have already added the rarefaction plots of TCR repertoire diversity versus the number of reads in Figure 2C. These have been added to the main text (lines 329-335).

      In order to support the authors' conclusions that MSI-H tumors have fewer TCR clonotypes than MSS tumors (Figure S2a) I would have liked to see Figure 2a annotated so that it was easy to distinguish which patient was in which group, as well as the rarefaction plots suggested above, to be sure that the difference represented a real difference between samples and not technical variance (which might occur due to only 4 samples being in the MSI-H group).

      We thank the reviewer for their recommendation. Indeed, it's worth noting that the number of MSI-H tumors is fewer than the MSS groups, which is consistent with the distribution observed in colorectal cancer, typically around 15%. This distribution pattern aligns with findings from several previous studies, as highlighted in these studies (16, 17). To provide further clarification on this point, we have included rarefaction plots illustrating TCR repertoire diversity versus the number of reads in Supplementary Figure 3 (line 339). Additionally, MSI-H and MSS samples have been appropriately labeled for clarity.

      The authors write: "in accordance with prior investigations, we identified an inverse relationship between TCR clonality and the Shannon index (Supplementary Figure S1)" >> Shannon index is measure of TCR clonality, not an independent variable. The authors may have meant TCR repertoire richness (the absolute number of TCRs), and the Shannon index (a measure of how many unique TCRs are present in the index).

      We thank the reviewer for their comment regarding the correlation between the number of TCRs and the Shannon index. We have revised the figure to illustrate the relationship between the number of TCRs and the Shannon index, and we have relocated it to Figure 2B.

      The authors continue: "As anticipated, we identified only 58 distinct V (Figure 2C) and 13 distinct J segments (Figure 2D), that collectively generated 184,396 clones across the 27 tumor tissue samples, underscoring the conservation of these segments (Figure 2C & D)" >> it is not clear to me what point the authors are making: it is well known that TCR V and J genes are largely shared between Caucasian populations (https://pubmed.ncbi.nlm.nih.gov/10810226/), and though IMGT lists additional forms of these genes, many are quite rare and are typically not included in the reference sequences used by repertoire analysis software. I would clarify the language in this section to avoid the impression that patient repertoires are only using a restricted set of J genes.

      We thank for the reviewer’s feedback. We have revised the sentence as follows: " As anticipated, we identified 59 distinct V segments (Supplementary Figure 2C) and 13 distinct J segments (Supplementary Figure 2D), collectively sharing 185,627 clones across the 28 tumor tissue samples. This underscores the conservation of these segments (Supplementary Figure 2C & D)” (Result, lines 354-356, page 12)

      As a result I would suggest moving Figure 2 with the exception of 2A into the supplementals - I would have been more interested in a plot showing the distribution of TCRs by frequency, i.e. how what proportion of clones are hyperexpanded, moderately expanded etc. This would be a better measure of the likely immune responses.

      We thank the reviewer for their comment. With the exception of Figure 2A, we have relocated Figures 2B through 2F to Supplementary Figure 2.

      The authors write "To accomplish this, we gathered HLA and TCRβ sequences from established datasets containing immunogenic and non-immunogenic peptides (Supplementary Table 3)" >> The authors mean to refer to Table S4.

      We appreciate the reviewer's feedback. Here's the revised sentence: "To accomplish this, we gathered HLA and TCRβ sequences from established datasets containing immunogenic and non-immunogenic pHLA-TCR complexes (Supplementary Table 5)” (lines 368-370).

      The authors write "As anticipated, our analysis revealed a significantly higher prevalence of peptides with robust HLA binding (percentile rank < 2%) among immunogenic peptides in contrast to their non-immunogenic counterparts (Figure 3A & B, p< 0.00001)" >> this is not surprising, as tools such as NetMHCpan are trained on databases of immunogenic peptides, and thus it is likely that these aren't independent measures (in https://academic.oup.com/nar/article/48/W1/W449/5837056 the authors state that "The training data have been vastly extended by accumulating MHC BA and EL data from the public domain. In particular, EL data were extended to include MA data"). In the pMTNet paper it is stated that pMNet encoded pMHC information using "the exact data that were used to train the netMHCpan model" >> While I am not sufficiently expert to review details on machine learning training models, it would seem that the pHLA scores from NetMHCpan and pMTNet may not be independent, which would explain the concordance in scores that the authors describe in Figures 3B and 3D. I would invite the authors to comment on this.

      The HLA percentiles from NetMHCpan and TCR rankings from pMTNet are independent. NetMHCpan predicts the interaction between peptides and MHC class I, while pMTNet predicts the TCR binding specificity of class I MHCs and peptides. NetMHCpan is trained to predict peptide-MHC class I interactions by integrating binding affinity and MS eluted ligand data, using a second output neuron in the NNAlign approach. This setup produces scores for both binding affinity and ligand elution. In contrast, pMTNet predicts TCR binding specificity of class I pMHCs through three steps:

      (1) Training a numeric embedding of pMHCs (class I only) to numerically represent protein sequences of antigens and MHCs.

      (2) Training an embedding of TCR sequences using stacked auto-encoders to numerically encode TCR sequence text strings.

      (3) Creating a deep neural network combining these two embeddings to integrate knowledge from TCRs, antigenic peptide sequences, and MHC alleles. Fine-tuning is employed to finalize the prediction model for TCR-pMHC pairing.

      Therefore, pHLA scores from NetMHCpan and pMTNet are independent. Furthermore, Figures 3B and 3D do not show concordance in scores, as there was no equivalence in the percentage of immunogenic and non-immunogenic peptides in the two groups (≥2 HLA percentile and ≥2 TCR percentile).

      Many of the authors of this paper were also authors of the epiTCR paper, would this not have been a better choice of tool for assessing pHLA-TCR binding than pMTNet?

      When we started this project, EpiTCR had not been completed. Therefore, we chose pMTNet, which had demonstrated good performance and high accuracy at that time. The validated performance of EpiTCR is an ongoing project that will implement immunogenic assays (ELISpot and single-cell sequencing) to assess the prediction and ranking of neoantigens. This study is also mentioned in the discussion: "Moreover, to improve the accuracy and effectiveness of the machine learning model in predicting and ranking neoantigens, we have developed an in-house tool called EpiTCR. This tool will utilize immunogenic assays, such as ELISpot and single-cell sequencing, for validation." (lines 532-535).

      In Figure 3G it would appear that the pHLA-TCR score is driving the interaction, could the authors comment on this?

      The authors sincerely appreciate the reviewer for their valuable feedback. Initially, the "combine" label in Figure 3G was confusing and potentially misleading when compared to our subsequent approach using a combined machine learning model. In Figure 3G, the "combine" approach simply aggregates the pHLA and pHLA-TCR criteria, whereas our combined machine learning model employs a more sophisticated algorithm to integrate these criteria effectively.

      The combined analysis in Figure 3G utilizes a basic "AND" algorithm between pHLA and pHLA-TCR criteria, aiming for high sensitivity in HLA binding and high specificity. However, this approach demonstrated lower efficacy in practice, underscoring the necessity for a more refined integration method through machine learning. This was the key point we intended to convey with Figure 3G. To address this issue, we have revised Figure 3G to replace "combined" with "HLA percentile & TCR ranking" to clarify its purpose and minimize confusion.

      In Figure 4A I would invite the authors to comment on how they chose the sample sizes they did for the discovery and validation datasets: the numbers seem rather random. I would question whether a training dataset in which 20% of the peptides are immunogenic accurately represents the case in patients, where I believe immunogenic peptides are less frequent (as in Figure 5).

      We aimed to maximize the number of experimentally validated immunogenic peptides, including those from viruses, with only a small percentage from tumors available for training. This limitation is inherent in the field. However, our ultimate objective is to develop a tool capable of accurately predicting peptide immunogenicity irrespective of their source. Therefore, the current percentage of immunogenic peptides may not accurately reflect real-world patient cases, but this is not crucial to our development goals.

      For Figure 5C I would invite the authors to consider adding a statistical test to justify the cutoff at 2fold enrichments.

      Thank you for your feedback. Instead of conducting a statistical test, we have implemented standardized cutoffs as defined in the cited study (2). This research introduces refined criteria for identifying positive responses in ELISPOT assays through a comprehensive analysis of data from multiple studies. These criteria aim to improve the accuracy and consistency of immune response measurements across various applications. The reference to this study has been properly incorporated into the manuscript (Method, line 281, page 10).

      Minor points:

      "paired white blood cells" >> use "paired Peripheral Blood Mononuclear Cells".

      We appreciate the reviewer for the feedback. We agree with the reviewer's observation. The sentence has been revised as follows: "Initially, DNA sequencing of tumor tissues and paired Peripheral Blood Mononuclear Cells identifies cancer-associated genomic mutations. RNA sequencing then determines the patient's HLA-I allele profile and the gene expression levels of mutated genes." (Introduction, lines 55-58, page 2).

      "while RNA sequencing determines the patient's HLA-I allele profile and gene expression levels of mutated genes." >> RNA sequencing covers both the mutant and reference form of the gene, allowing assessment of variant allele frequency.

      "the current approach's impact on patient outcomes remains limited due to the scarcity of effective immunogenic neoantigens identified for each patient" >> Some clearer language here would have been preferred as different tumor types have different mutational loads

      We thank the reviewer for their valuable feedback. We agree with the reviewer's observation. The passage has been revised accordingly: “The current approach's impact on patient outcomes remains limited due to the scarcity of mutations in cancer patients that lead to effective immunogenic neoantigens.” (Introduction, lines 62-64, page 3).

      References

      (1) J. Schmidt et al., Prediction of neo-epitope immunogenicity reveals TCR recognition determinants and provides insight into immunoediting. Cell Rep Med 2, 100194 (2021).

      (2) Z. Moodie et al., Response definition criteria for ELISPOT assays revisited. Cancer Immunol Immunother 59, 1489-1501 (2010).

      (3) V. Jurtz et al., NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. J Immunol 199, 3360-3368 (2017).

      (4) T. Lu et al., Deep learning-based prediction of the T cell receptor-antigen binding specificity. Nat Mach Intell 3, 864-875 (2021).

      (5) J. Xia et al., NEPdb: A Database of T-Cell Experimentally-Validated Neoantigens and Pan-Cancer Predicted Neoepitopes for Cancer Immunotherapy. Front Immunol 12, 644637 (2021).

      (6) W. J. Zhou et al., NeoPeptide: an immunoinformatic database of T-cell-defined neoantigens. Database (Oxford) 2019 (2019).

      (7) X. Tan et al., dbPepNeo: a manually curated database for human tumor neoantigen peptides. Database (Oxford) 2020 (2020).

      (8) G. Zhang, L. Chitkushev, L. R. Olsen, D. B. Keskin, V. Brusic, TANTIGEN 2.0: a knowledge base of tumor T cell antigens and epitopes. BMC Bioinformatics 22, 40 (2021).

      (9) J. Wu et al., TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis. Genomics Proteomics Bioinformatics 16, 276-282 (2018).

      (10) https://www.10xgenomics.com/resources/datasets/cd-8-plus-t-cells-of-healthy-donor-1-1-standard-3-0-2.

      (11) https://www.10xgenomics.com/resources/datasets/cd-8-plus-t-cells-of-healthy-donor-2-1-standard-3-0-2.

      (12) https://www.10xgenomics.com/resources/datasets/cd-8-plus-t-cells-of-healthy-donor-3-1-standard-3-0-2.

      (13) https://www.10xgenomics.com/resources/datasets/cd-8-plus-t-cells-of-healthy-donor-4-1-standard-3-0-2.

      (14) A. Montemurro et al., NetTCR-2.0 enables accurate prediction of TCR-peptide binding by using paired TCRalpha and beta sequence data. Commun Biol 4, 1060 (2021).

      (15) G. Li et al., Splicing neoantigen discovery with SNAF reveals shared targets for cancer immunotherapy. Sci Transl Med 16, eade2886 (2024).

      (16) Z. Gatalica, S. Vranic, J. Xiu, J. Swensen, S. Reddy, High microsatellite instability (MSI-H) colorectal carcinoma: a brief review of predictive biomarkers in the era of personalized medicine. Fam Cancer 15, 405-412 (2016).

      (17) N. Mulet-Margalef et al., Challenges and Therapeutic Opportunities in the dMMR/MSI-H Colorectal Cancer Landscape. Cancers (Basel) 15 (2023).

    1. Reviewer #1 (Public review):

      In this manuscript, the authors address an important issue in Babesia research by repurposing Cipargamin (CIP) as a potential therapeutic against selective Babesia spp. In this study, CIP demonstrated potent in vitro inhibition of B. bovis and B. gibsoni with IC50 values of 20.2 {plus minus} 1.4 nM and 69.4 {plus minus} 2.2 nM, respectively, and the in vivo efficacy against Babesia spp using mouse model. The authors identified two key resistance mutations in the BgATP4 gene (BgATP4L921I and BgATP4L921V) and explored their implications through phenotypic characterization of the parasite using cell biological experiments, complemented by in silico analysis. Overall, the findings are promising and could significantly advance Babesia treatment strategies.

      Strengths:

      In this manuscript, the authors effectively repurpose Cipargamin (CIP) as a potential treatment for Babesia spp. They provide compelling in vitro and in vivo data showing strong efficacy. Key resistance mutations in the BgATP4 gene are identified and analyzed through both phenotypic and in silico methods, offering valuable insights for advancing treatment strategies.

      Weaknesses:

      The manuscript explores important aspects of drug repurposing and rational drug design using Cipargamin (CIP) against Babesia. However, several weaknesses should be addressed. The study lacks novelty as similar research on Cipargamin has been conducted, and the experimental design could be improved. The rationale for choosing CIP over other ATP4-targeting compounds is not well-explained. Validation of mutations relies heavily on in silico predictions without sufficient experimental support. The Ion Transport Assay has limitations and would benefit from additional assays like Radiolabeled Ion Flux and Electrophysiological Assays. Also, the study lacks appropriate control drugs and detailed functional characterization. Further clarity on mutation percentages, additional safety testing, and exploration of cross-resistance would strengthen the findings.

      (1) It is commendable to explore drug repurposing, drug deprescribing, drug repositioning, and rational drug design, especially using established ATP4 inhibitors that are well-studied in Plasmodium and other protozoan parasites. While the study provides some interesting findings, it appears to lack novelty, as similar investigations of Cipargamin on other protozoan parasites have been conducted. The study does not introduce new concepts, and the experimental design could benefit from refinement to strengthen the results. Additionally, the rationale for choosing CIP over other MMV compounds targeting ATP4 is not clearly articulated. Clarifying the specific advantages CIP may offer against Babesia would be beneficial. Finally, the validation of the identified mutations might be strengthened by additional experimental support, as reliance on in silico predictions alone may not fully address the functional impact, particularly given the potential ambiguity of the mutations (BgATP4 L to V and I).

      (2) Conducting an Ion Transport Assay is useful but has limitations. Non-specific binding or transport by other cellular components can lead to inaccurate results, causing false positives or negatives and making data interpretation difficult. Indirect measurements, like changes in fluorescence or electrical potential, can introduce artifacts. To improve accuracy, consider additional assays such as<br /> a. Radiolabeled Ion Flux Assay: tracks the movement of Na^+ using radiolabeled ions, providing direct evidence of ion transport.<br /> b. Electrophysiological Assay: measures ionic currents in real-time with patch-clamp techniques, offering detailed information about ATP4 activity.

      (3) In-silico predictions can provide plausible outcomes, but it is essential to evaluate how the recombinant purified protein and ligand interact and function at physiological levels. This aspect is currently missing and should be included. For example, incorporating immunoprecipitation and ATPase activity assays with both wild-type and mutant proteins, as well as detailed kinetic studies with Cipargamin, would be recommended to validate the findings of the study.

      (4) The study lacks specific suitable control drugs tested both in vitro and in vivo. For accurate drug assessment, especially when evaluating drugs based on a specific phenotype, such as enlarged parasites, it is important to use ATP4 gene-specific inhibitors. Including similar classes of drugs, such as Aminopyrazoles, Dihydroisoquinolines, Pyrazoleamides, Pantothenamides, Imidazolopiperazines (e.g., GNF179), and Bicyclic Azetidine Compounds, would provide more comprehensive validation.

      (5) Functional characterization of CIP through microscopic examination and quantification for assessing parasite size enlargement is not entirely reliable. A Flow Cytometry-Based Assay is recommended instead 9 along with suitable control antiparasitic drugs). To effectively monitor Cipargamin's action, conducting time-course experiments with 6-hour intervals is advisable rather than relying solely on endpoint measurements. Additionally, for accurate assessment of parasite morphology, obtaining representative qualitative images using Scanning Electron Microscopy (SEM) or Transmission Electron Microscopy (TEM) for treated versus untreated samples is recommended for precise measurements.

      (6) A notable contradiction observed is that mutant cells displayed reduced efficacy and affinity but more pronounced phenotypic effects. The BgATP4L921I mutation shows a 2x lower susceptibility (IC50 of 887.9 {plus minus} 61.97 nM) and a predicted binding affinity of -6.26 kcal/mol with CIP. However, the phenotype exhibits significantly lower Na+ concentration in BgATP4L921I (P = 0.0087) (Figure 3E).

      (7) The manuscript does not clarify the percentage of mutations, and the number of sequence iterations performed on the ATP4 gene. It is also unclear whether clonal selection was carried out on the resistant population. If mutations are not present in 100% of the resistant parasites, please indicate the ratio of wild-type to mutant parasites and represent this information in the figure, along with the chromatograms.

      (8) While the compound's toxicity data is well-established, it is advisable to include additional testing in epithelial cells and liver-specific cell lines (e.g., HeLa, HCT, HepG2) if feasible for the authors. This would provide a more comprehensive assessment of the compound's safety profile.

      (9) In the in vivo efficacy study, recrudescent parasites emerged after 8 days of treatment. Did these parasites harbor the same mutation in the ATP4 gene? The authors did not investigate this aspect, which is crucial for understanding the basis of recrudescence.

      (10) The authors should explain their choice of Balb/c mice for evaluating CIP efficacy, as these mice clear the infection and may not fully represent the compound's effectiveness. Investigating CIP efficacy in SCID mice would be valuable, as they provide a more reliable model and eliminate the influence of the immune system. The rationale for not using SCID mice should be clarified.

      (11) Do the in vitro-resistant parasites show any potential for cross-resistance with commonly used antiparasitic drugs? Have the authors considered this possibility, and what are their expectations regarding cross-resistance?

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public review):

      …the degree to which the predictions can vary according to environmental composition remains difficult to quantify, and the work does not address the sensitivity of the modeling predictions beyond a simulated medium containing 33 root exudates. I find this especially important given that relatively few (84 of 243) species were predicted to grow even after cross-feeding, suggesting that a richer medium could lead to different interaction network structures. While the authors do state the importance of environmental composition and have carefully designed an in silico medium, I believe that simulating a broader set of resource pools would add necessary insight into both the predictive power of the models themselves and trophic interactions in the rhizosphere more generally.

      The original analyses were indeed focused on a single well-defined environment supporting the growth of only a subset of the species. We have added a paragraph to the discussion section dealing with the potential limitations of this approach. 

      On line 289 we write:

      "Overall, the successive iterations connected 84 out of 243 native members of the apple rhizosphere GSMM community via trophic exchanges. The inability of the remaining bacteria to grow, despite being part of the native root microbiome, possibly reflects the selectiveness of the root environment, which fully supports the nutritional demands of only part of the soil species, whereas specific compounds that might be essential to other species are less abundant1. It is important to note that the specific exudate profile used here represent a snapshot of the root metabolome as root secretion-profiles are highly dynamic, reflecting both environmental and plant developmental conditions. A possible complementary explanation to the observed selective growth might be the partiality of our simulation platform, which examined only plant-bacteria and bacteria-bacteria interactions while ignoring other critical components of the rhizosphere system such as fungi, archaea, protists and mesofauna, as well as less abundant bacterial species, components all known to metabolically interact2. Finally, the MAG collection, while relatively substantial, represents only part of the microbial community. Accordingly, the iterative growth simulations represent a subset of the overall hierarchical-trophic exchanges in the root environment, necessarily reflecting the partiality of the dataset."

      In addition, we have tried to better explain the advantages of a limited/defined medium to such an analysis. On Line 231 we add:

      "By avoiding the inclusion of non-exudate organic metabolites, the true-to-source rhizosphere environment was designed to reveal the hierarchical directionality of the trophic exchanges in soil, as rich media often mask various trophic interactions taking place in native communities3"

      More generally, beyond the above justification of our specific medium selection, we agree that simulating a broader set of resource pools would contribute to a more comprehensive understanding of the trophic interactions. Therefore, we conducted the analysis in an additional environment, in which cellulose was used as an input. We were able to follow its well-documented degradation via multiple steps, conducted by different community members, to serve as a benchmark to our suggested framework. 

      On line 357 we add:

      "To validate the ability of MCSM to capture trophic dependencies and succession, we further tested whether it can trace the well-documented example of cellulose degradation - a multi-step process conducted by several bacterial strains that go through the conversion of cellulose and its oligosaccharide derivatives into ethanol, acetate and glucose, which are all eventually oxidized to CO24. Here, the simulation followed the trophic interactions in an environment provided with cellulose oligosaccharides (4 and 6 glucose units) on the 1st iteration (Supp. Table 3). The formed trophic successions detected along iterations captured the reported multi-step process (Supp.

      Fig.7)." 

      Finally, we have included additional text regarding the challenge of defining our simulation environment in the Discussion section. 

      On line 532 we add:

      "In the current study, the root environment was represented by a single pool of resources (metabolites). As genuine root environments are highly dynamic and responsive to stimuli, a single environment can represent, at best, a temporary snapshot of the conditions. Conductance of simulations with several sets of resource pools (e.g., representing temporal variations in exudation profile) can add insights regarding their effect on trophic interactions and community dynamics. In parallel, confirming predictions made in various environments will support an iterative process that will strengthen the predictive power of the framework and improve its accuracy as a tool for generating testable hypotheses. Similarly, complementing the genomicsbased approaches used here with additional layers of 'omics information (mainly transcriptomics & metabolomics) can further constrain the solution space, deflate the number of potential metabolic routes and yield more accurate predictions of GSMMs' performances5."

      And we add in Line 520:

      "For these reasons, among others, the framework presented here is not intended to be used as a stand-alone tool for determining microbial function. The framework presented is designed to be used as a platform to generate educated hypotheses regarding bacterial function in a specific environment in conjunction with actual carbon substrates available in the particular ecosystem under study. The hypotheses generated provide a starting point for experimental testing required to gain actual, targeted and feasible applicable insights6,7. While recognizing its limitations, this framework is in fact highly versatile and can be used for the characterization of a variety of microbial communities and environments. Given a set of MAGs derived from a specific environment and environmental metabolomics data, this computational framework provides a generic simulation platform for a wide and diverse range of future applications." 

      Reviewer #2 (Public review):

      There are two main drawback approaches like the one described here, both related only partially to the authors' work yet with great impact in the presented framework. First, the usage of automatic GSMM reconstruction requires great caution. It is indicative of how the semicurated AGORA models are still considered reconstructions and expect the user to parameterize those in a model. In this study, CarveMe was used. CarveMe is a well-known tool with several pros [1]. Yet, several challenges need to be considered when using it [2]. For example, the biomass function used might lead to an overestimation of auxotrophies. Also, as its authors admit in their reply paper, CarveMe does gap fill in a way [3]; models are constructed to ensure no gaps and also secure a minimum growth. However, curation of such a high number of GSMMs is probably not an option. Further, even if FVA is way more useful than FBA for the authors' aim, it does not yet ensure that when a species secretes one compound (let's say metabolite A), the same flux vector, i.e. the same metabolic functioning profile, secretes another compound (metabolite B) at the same time, even if the FVA solution suggests that metabolite B could be secreted in general.

      We thank Reviewer #2 for highlighting this key limitation of our analysis. Below and in the 'recommendations to authors' section we address these concerns. 

      Concerning the first point raised (models' accuracy) we have now clearly acknowledged in the text the limitations of using an automated GSMM reconstruction tool such as CarveMe. More generally, the framework applied here was built in order to meet the challenges of analyzing highthroughput data while acknowledging the inherent potential of introducing inaccuracies. Pros & cons are now discussed. 

      On line 507 we write:

      "Moreover, the use of an automatic GSMM reconstruction tool (CarveMe8), though increasingly used for depicting phenotypic landscapes, is typically less accurate than manual curation of metabolic models9. This approach typically neglects specialized functions involving secondary metabolism10 and introduces additional biases such as the overestimation of auxotrophies11,12. Nevertheless, manual curation is practically non-realistic for hundreds of MAGs, an expected outcome considering the volume of nowadays sequencing projects. As the primary motivation of this framework is the development of a tool capable of transforming high-throughput, low-cost genomic information into testable predictions, the use of automatic metabolic network reconstruction tools was favored, despite their inherent limitations, in pursuit of addressing the necessity of pipelines systematically analyzing metagenomics data." 

      Regarding using FVA solutions, indeed such solutions return all potential metabolic fluxes in GSMMs (ranges of all fluxes satisfying the objective function, which by default is set to biomass increase) in a given environment. However, as indicated by the reviewer, predicted fluxes do not necessarily co-occur (i.e., when a metabolite is secreted another metabolite is not necessarily secreted too), yet, they provide the full set of potential solutions (unlike the single solution provided by FBA). A possible strategy to reduce inflated predictions provided by FVA and further constrain the solution space (reduce the set of metabolic fluxes) can be the incorporation of additional `omics data layers, as for example was done in the work of Zampieri et al5. Such approach could allow for instance limiting active reactions (blocking fluxes) from the network reconstructions if not coming to play in situ, and therefore impose further constraints and narrow the solution space. We now refer in the text to this limitation and to potential routes to overcome it. 

      On line 541 we now write:

      Similarly, complementing the genomics-based approaches done here with additional layers of 'omics information (mainly transcriptomics & metabolomics) can further constrain the solution space, deflate the number of potential metabolic routes and yield more accurate predictions of GSMMs' performances5.  

      Reviewer #3 (Public review):

      When presenting a computational framework, best practices include running it on artificial (synthetic) data where the ground truth is known and therefore the precision and accuracy of the method may be assessed. This is not an optional step, the same way that positive/negative controls in lab experiments are not optional. Without this validation step, the manuscript is severely limited. The authors should ask themselves: what have we done to convince the reader that the framework actually works, at least on our minimal synthetic data? 

      Thank you for this suggestion. To validate the ability of MCSM to capture trophic succession, we conducted an additional analysis testing whether it can track the well documented example of cellulose degradation - a multi-step process conducted by several bacterial strains. This example has been included in the manuscript to serve as a case study (i.e. positive control) for metabolic interactions occurring within the bacterial community (Supp. Fig. 7). 

      On line 357 we add:

      "To validate the ability of MCSM to capture trophic dependencies and succession, we further tested whether it can track the well-documented example of cellulose degradation - a multi-step process conducted by several bacterial strains that go through the conversion of cellulose and its oligosaccharide derivatives into ethanol, acetate and glucose, which are all eventually oxidized to CO24. Here, the simulation followed the trophic interactions in an environment provided with cellulose oligosaccharides (4 and 6 glucose units) on the 1st iteration (Supp. Table 3). The formed trophic successions detected along iterations captured the reported multi-step process (Supp. Fig.

      7)."  

      "Supplementary Figure 7. Application of MCSM over the process of cellulose decomposition as described by Kato et al4. 5-partite network exhibiting the uptake of cellulose oligomers (4 and 6 units of connected D-glucose) by primary decomposers, through secretion of intermediate compounds and their metabolization by secondary decomposers to CO2. Distribution of phyla of primary and secondary decomposers is denoted by pie charts. Though MAGs were not constructed for the original species as in Kato et al., among the primary consumers, species corresponding to the Acidobacteria (Acidobacteriales)13, Actinobacteria14, Bacteriodetes15, Proteobacteria (Xanthomonadales)16 and Verrucobacteria17 groups are found to be capable of degrading cellulose compounds via enzymatic mechanisms."

      More generally, beyond the above addition, the relevance of the framework to the analysis of the data is discussed throughout the analysis (in the original version of the manuscript). We have scrutinized each of our observations in light of current available information and provided a corroborating evidence as well as a few discrepancies for multiple steps in the analysis.  Examples include the following discussions:

      On line 312, we discuss the biological relevance of taxonomic classes classified as primary versus secondary degraders

      "As in the full GSMM data set (Community bar, Fig. 3C), most of the species which grew in the 1st iteration belonged to the phyla Acidobacteriota, Proteobacteria, and Bacteroidota. This result concurred with findings from the work of Zhalnina et al, which reported that bacteria assigned to these phyla are the primary beneficiaries of root exudates18. Species from three out of the 17 phyla that did not grow in the first iteration - Elusimicrobiota, Chlamydiota, and Fibrobacterota, did grow on the 2nd iteration (Fig. 3C). Members of these phyla are known for their specialized metabolic dependencies. Such is the case for example with members of the Elusimicrobiota phylum, which include mostly uncultured species whose nutritional preferences are likely to be selective19.

      At the order level, bacteria classified as Sphingomonadales (class Alphaproteobacteria), a group known to include typical inhabitants of the root environment20, grew in the initial Root environment. In comparison, other root-inhabiting groups including the orders Rhizobiales and Burkholderiales_20, did not grow in the first iteration. _Rhizobiales and Burkholderiales did, however, grow in the second and third iterations, respectively, indicating that in the simulations, the growth of these groups was dependent on exchange metabolites secreted by other community members (Supp. Fig. 4)."

      On line 331, we provide support to the classification of specific metabolites as exchange molecules

      "Overall, 158 organic compounds were secreted throughout the MCSM simulation (from which 12 compounds overlapped with the original exudate medium). These compounds varied in their distribution and were mapped into 12 biochemical categories (Fig. 3D). Whereas plant secretions are a source of various organic compounds, microbial secretions provide a source of multiple vitamins and co-factors not secreted by the plant. Microbial-secreted compounds included siderophores (staphyloferrin, salmochelin, pyoverdine, and enterochelin), vitamins (pyridoxine, pantothenate, and thiamin), and coenzymes (coenzyme A, flavin adenine dinucleotide, and flavin mononucleotide) – all known to be exchange compounds in microbial communities21,22. In addition, microbial secretions included 11 amino acids (arginine, lysine, threonine, alanine, serine, phenylalanine, tyrosine, leucine, glutamate, isoleucine, and methionine), also known as a common exchange currency in microbial communities23. Some microbial-secreted compounds, such as phenols and alkaloids, were reported to be produced by plants as secondary metabolites24,25. Additional information regarding mean uptake and secretion degrees of compounds classified to biochemical groups is found in Supp. Fig. 5."

      On line 432, we provide corroborative support to the classification of exudates as associated with beneficial/non beneficial root communities

      "Notably, the S-classified root exudates included compounds reported to support dysbiosis and ARD progression. For example, the S-classified compounds gallic acid and caffeic acid (3,4-dihidroxy-trans-cinnamate) are phenylpropanoids – phenylalanine intermediate phenolic compounds secreted from plant roots following exposure to replant pathogens26. Though secretion of these compounds is considered a defense response, it is hypothesized that high levels of phenolic compounds can have autotoxic effects, potentially exacerbating ARD. Additionally, it was shown that genes associated with the production of caffeic acid were upregulated in ARD-infected apple roots, relative to those grown in γ-irradiated ARD soil27,28, and that root and soil extracts from replant-diseased trees inhibited apple seedling growth and resulted in increased seedling root production of caffeic acid29."

      On line 446, we provide a supporting evidence to the classification of secreted compounds as associated with beneficial/non beneficial root communities

      "Several secreted compounds classified as healthy exchanges (H) were reported to be potentially associated with beneficial functions. For instance, the compounds L-Sorbose (EX_srb__L_e) and Phenylacetaladehyde (EX_pacald_e), both over-represented in H paths (Fig. 5C), have been shown to inhibit the growth of fungal pathogens associated with replant disease30,31.

      Phenylacetaladehyde has also been reported to have nematicidal qualities32."

      On line 453 we discuss the correspondence of specific exudate uptakes and compound secretions via specific subnetwork motifs (PM) and their literature/experimental evidence 

      "Combining both exudate uptake data and metabolite secretion data, the full H-classified PM path 4-Hydroxybenzoate; GSMM_091; catechol (Fig. 4C; the consumed exudate, the GSMM, and the secreted compound, respectively) provides an exemplary model for how the proposed framework can be used to guide the design of strategies which support specific, advantageous exchanges within the rhizobiome. The root exudate 4-Hydroxybenzoate is metabolized by GSMM_091 (class Verrucomicrobiae, order Pedosphaerales) to catechol. Catechol is a precursor of a number of catecholamines, a group of compounds which was recently shown to increase apple tolerance to ARD symptoms when added to orchard6,33. This analysis (PM; Fig 4C), leads to formulating the testable prediction that 4-Hydroxybenzoate can serve as a selective enhancer of catecholamine synthesizing bacteria associated with reduced ARD symptoms, and therefore serve as a potential source for indigenously produced beneficial compounds."

      Moreover, we perceive our analysis as a strategy for integrating high throughput genomic data into testable predictions allowing narrowing the solution space while acknowledging potential inaccuracies that are inherent to the analysis. We have revised the text in order to clearly acknowledge this limitation.

      On line 497 we write: 

      "The framework we present is currently conceptual."

      On line 520 we write: 

      "For these reasons, among others, the framework presented here is not intended to be used as a stand-alone tool for determining microbial function. The framework presented is designed to be used as a platform to generate educated hypotheses regarding bacterial function in a specific environment in conjunction with actual carbon substrates available in the particular ecosystem under study. The hypotheses generated provide a start point for experimental testing required to gain actual, targeted and feasibly applicable insights6,7."

      On line 532 we add: 

      "In the current study, the root environment was represented by a single pool of resources (metabolites). As genuine root environments are highly dynamic and responsive to stimuli, a single environment can represent, at best, a temporary snapshot of the conditions. Conductance of simulations with several sets of resource pools (e.g., representing temporal variations in exudation profile) can add insights regarding their effect on trophic interactions and community dynamics. In parallel, confirming predictions made in various environments will support an iterative process that will strengthen the predictive power of the framework and improve its accuracy as a tool for generating testable hypotheses. Similarly, complementing the genomicsbased approaches used here with additional layers of 'omics information (mainly transcriptomics & metabolomics) can further constrain the solution space, deflate the number of potential metabolic routes and yield more accurate predictions of GSMMs' performances5."

      Recommendations for the authors:

      Reviewer #1( Recommendations for the authors):

      (1) Line 219: "Feasibility" - this term/concept may be difficult to understand for readers unfamiliar with GSMMs. I would recommend either clarifying or rephrasing, perhaps as "simulations confirmed the existence of a feasible solution space for all the 243 models, as well as their capacity to predict growth in the respective environment."

      Thanks, done. We have modified this section as suggested (line 221). 

      (2) Line 244: How does MCSM fit within/build upon existing frameworks that simulate patterns of niche construction and cross-feeding with constraint-based modeling?

      This is now addressed. On line 250 we write:  

      "Unlike tools designed for modelling microbial interactions34,35, MCSM bypasses the need for defining a community objective function as the growth of each species is simulated individually. Trophic interactions are then inferred by the extent to which compounds secreted by bacteria could support the growth of other community members."

      (3) Figure 4A: While illustrating the general complexity of the predicted trophic interactions, the density of the network makes it very difficult to interpret specific exchanges. Moreover, the naming conventions of the metabolites make it difficult to understand what they represent. I would recommend either restructuring the graph such that the label of each node is legible, or removing the labels altogether.

      Thanks, done. Labels were removed and a zoom-in-window to the exchanges highlighted in Figure 4C were added. Caption was revised to indicate that node colors correspond to differential abundance classification of GSMMs in the different plots (H, S, NA are Healthy, Sick, Not-Associated, respectively).

      Reviewer #2 (Recommendations for the authors):

      CarveMe solves a Mixed Integer Linear Program (MILP) that enforces network connectivity, thus requiring gapless pathways. It's puzzling how to deal with such a great number of GSMMs that is for sure, especially when coming from such an environment as soil and the vast majority of their corresponding MAGs represent most likely novel taxa. One alternative approach for using CarveMe might be to use the rich medium as a medium to gap-fill during the reconstruction. In this case, the gene annotation scores that CarveMe calculates in its initial step, are used to prioritise the reactions selected for gap-filling. This would lead to a new series of challenges but might be a useful comparison with the current GSMMs of the study.

      Though indeed CraveMe includes a gap-filling option, here we have purposely avoided the gapfilling option as we aimed to adhere to genomic content of the corresponding genomes and to avoid masking their metabolic dependencies emerging due to their incompleteness. This is noted in the Methods section, which we revised to emphasize the adherence to the genomic content of the models: 

      On line 615 we now write:

      "All GSMMs were drafted without gap filling in order to adhere to genomic content and to avoid masking metabolic co-dependencies51"

      More generally, we now refer to the limitation of automatic reconstruction in the context of the current analysis. On line 507 we write:

      "Moreover, the use of an automatic GSMM reconstruction tool (CarveMe8), though increasingly used for depicting phenotypic landscapes, is typically less accurate than manual curation of metabolic models9. This approach typically neglects specialized functions involving secondary metabolism10 and introduces additional biases such as the overestimation of auxotrophies11,12. Nevertheless, manual curation is practically non-realistic for hundreds of MAGs, an expected outcome considering the volume of nowadays sequencing projects. As the primary motivation of this framework is the development of a tool capable of transforming high-throughput, low-cost genomic information into testable predictions, the use of automatic, semi-curated, metabolic network reconstruction tools was favored, despite their inherent limitations, in pursuit of developing pipelines for the systematic analysis of metagenomics data."

      Thermodynamically infeasible loops have been a challenge in constraint-based analysis [1].

      However, for the case of FBA and FVA time efficient implementations are already available. Therefore, I would suggest using the loopless flag of the cobrapy package when performing FVA. 

      Also, it would be nice to show/discuss how many exchange reactions each GSMM includes and what is the number of those with at least a non-zero minimum or maximum in the FVA using each of the three media.

      Done. In Supplementary Figure 4, we added a graphic summary of active FVA ranges for each GSMM in the three different environments (exchange reactions, non-zero flux). Additionally, we analyzed a subset of models and compared their regular FVA results vs loopless FVA results.

      On line 217 we write:

      "The number of active exchange fluxes in each medium corresponds with the respective growth performances displaying noticably higher number of potentially active fluxes in the rich environment (also when applying loopless FVA) (Supp. Fig. 4). Overall, Simulations confirmed the existence of a feasible solution space for  all the 243 models as well as their capacity to predict growth in the respective environemnt (Supp. Data 5)."

      "Supplementary Figure 4. FVA performances of GSMMs in different environments (Supp. Fig.

      3; Supp. Data 5). A. Distribution of potentially active exchange reactions (non-zero minimum FVA flux) in the different environments. Solid line inside each violin indicates the interquartile range (IQR). White point in IQR indicates the median value. Whiskers extending from the IQR indicate the range within 1.5 times the IQR from the quartiles. Violin width at a given value represents the density of data points at that value. B. Loopless FVA scores compared to regular FVA for models in the 3 different environments. Bars indicate the count of active fluxes (nonzero minimum FVA flux). Only a subset of models was used for this analysis."

      This brings us to the main challenge of your framework in my opinion: FVA returns the minimum and the maximum a flux may get. However, it does not ensure that when a metabolite is being secreted, another does the same too. That could lead to an overrepresentation of secreted metabolites after each iteration. To my understanding, unbiased methods focusing on metabolite exchanges would be a much better alternative for such questions. Unbiased constraint-based methods are known for requiring essential computational requirements, yet when focusing on specific parts of the models, recent implementations support them. A great showcase of such techniques is presented in [2].

      Indeed, FVA solutions return all potential metabolic fluxes in GSMMs (ranges of all fluxes satisfying the objective function, which by default is set to biomass increase) but they do not ensure that all fluxes actually co-occur (i.e., when a metabolite is secreted necessarily another metabolite is secreted too). However, though FVA solutions do not necessarily ensure cooccurrence regarding secretion and uptake, they provide a broader metabolic picture (the full set of potential solutions), unlike the arbitrary single solution provided by FBA, which is limited in providing information about potential secretions and uptakes in a specific environment. Here, we tried to elucidate the connection between a specific environment (root exudates) and the growth and metabolic capabilities of native bacteria. To the best of our understanding,  unbiased approaches (such as the one displayed in Wedmark et al.36) are not environment dependent but rather calculate all possible metabolic elements and routes within a metabolic network. Therefore, using FVA is well adapted to explore environment-dependent growth. The sensitivity of FVA predicted active fluxes to the environments is now also implied by Sup. Fig. 3B demonstrating the number of potential active fluxes is proportional to growth performances.  In addition, inquiring all possible metabolic routes across a large dataset of hundreds of MAGS, is central to the current analysis, thus the easy implementation of FVA further justifies its use in the current study.

      An alternative strategy to reduce inflated FVA predictions and further constrain the solution space of predicted active fluxes can be the incorporation of additional layers of `omics data, as for example was done in the work of Zampieri et al5. Such approach could allow for instance removing reactions from the network reconstructions if not coming to play in situ, and therefore impose further constraints and narrow down the solution space. Currently, the complexity of the soil community might impede or at least constrain a high coverage recovery of transcriptomic data, though future works utilizing additional layers of `omics data are expected to significantly reduce the number of potential solutions and thus improve the accuracy of GEMs predictions. 

      This is now discussed in the text. In line 541 we write:

      "Similarly, complementing the genomic-based approaches done here, with additional layers of 'omics information (mainly transcriptomics & metabolomics) can further constrain the solution space, deflate the number of potential metabolic routes and yield more accurate predictions of GSMMs' performances5."  

      In case it was the first version of CheckM used, the authors could consider repeating this check with CheckM2. As they state in line 293, Archaea may play an essential role in the community. Yet, among the high-quality MAGs only one corresponded to Archaea. However, that is quite possible to be the case because CheckM underestimates the completeness of archaeal genomes. If CheckM2 suggests that archaeal MAGs could be used, these would probably benefit a lot for the aim of the study.

      The analysis was conducted with the first version of CheckM to assess MAGs quality. In future analyses we will use CheckM2. However, also before MAG recovery, we already know from the work of Beirhu et al., that Archaea species have a very low representation in the metagenomics data used here (Berihu et al., Additional data 2. Supp. fig. 4; "others" group)6, with less than 0.5% of the contigs mapped to archaeal genomes. The overall taxonomic distribution of the high-quality MAGs was compared to the distribution inferred from the non-binned data (contigs) and amplicon sequencing and the three different data sets are very similar (Fig. 2). 

      On line 130 we write:

      "Overall, the taxonomic distribution of the MAG collection corresponded with the profile reported for the same samples using alternative taxonomic classification approaches such as 16S rRNA amplicon sequencing and gene-based taxonomic annotations of the non-binned shotgun contigs

      (Fig. 2B)."

      The visualisation of the network in Figure 4A is hard to follow. An alternative could be a 5partite plot having taxa in columns one, three, and five and compounds in the other two. An alternative visualisation is necessary.

      The full list of the 5 and 3 partite graphs is provided in supplementary data 10 (also noted in the figure legend now). Figure 4 was revised to improve its visualization. Labels were removed and a zoom in to 5 and 3 partite plots were added (PMM and PM subnetworks, respectively). 

      Line 509: If I get the point of the authors right, they refer to the "from shotgun data to GEMs" approach. I would suggest skipping this statement. Here is a recent study implementing this: https://doi.org/10.1016/j.crmeth.2022.100383.

      Thank you for your comment and reference. The intention behind the phrase in line 509 (in previous version) was to refer to going from metagenomics data to GEMs in soil-rhizosphere microbiome while linking environmental inputs (crop-plants exudates metabolomics data) and the agricultural-related metabolic function of bacteria. This phrase has been modified to clearly make a more modest claim while acknowledging other related studies.

      On line 548 we write

      "Where recent studies begin to apply GSMM reconstruction and analysis starting from MAGs5,37 , this work applies the MAGs to GSMMs approach to conduct a large-scale CBM analysis over highquality MAGs derived from a native rhizosphere and explore the complex network of interactions in light of the functioning of the respective agro-ecosystem. "

      Line 820: Reference format is broken.

      Corrected.

      In the caption of Figure 4, please add the meaning of H, S, and NA so it is selfexplanatory.

      Done. In Figure 4 legend we added:

      "Node colors correspond to differential abundance classification of GSMMs in the different plots; H, S, NA are Healthy, Sick, Not-Associated, respectively."

      Reviewer #3 (Recommendations for the authors):

      (1) Figure 4A is unreadable. It is not clear what insight the reader could gain by examining this figure.

      Thanks. Figure was revised. Labels were removed and a zoom-in-window to the exchanges highlighted in Figure 4C were added. Caption was revised to indicate that node colors correspond to differential abundance classification of GSMMs in the different plots (H, S, NA are Healthy, Sick, Not-Associated, respectively).

      (2) In Figure 5, it is not apparent what the units of "prevalence" are, that is, what is the scale. What does 140 mean? How does that compare to 350?

      Thanks. Prevalence in the context of Figure. 5B,C refers to the count of the compounds in each category (significantly affiliated with either healthy or symptomized soils) in sub-network motifs corresponding to this DA classification. We revised the figures (Y axes) and legend to be more specific (B: # of exudates; C: # of secreted compounds).

      "B. Bar plot indicating the number of exudates significantly associated with H or S-classified PM sub-networks (Hypergeometric test; FDR <= 0.05; green: healthy-H, red: sick-S). C. Bar plots indicate the number of secreted compounds in PM sub-networks, which are significantly associated with H-classified (upper, colored green), or S-classified (lower, colored red) (Hypergeometric test; FDR <= 0.05)."

      References

      (1) Buée, M., de Boer, W., Martin, F., van Overbeek, L. & Jurkevitch, E. The rhizosphere zoo: An overview of plant-associated communities of microorganisms, including phages, bacteria, archaea, and fungi, and of some of their structuring factors. Plant Soil 321, 189– 212 (2009).

      (2) Bardgett, R. D. & Van Der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).

      (3) Opatovsky, I. et al. Modeling trophic dependencies and exchanges among insects’ bacterial symbionts in a host-simulated environment. BMC Genomics 19, 1–14 (2018).

      (4) Kato, S., Haruta, S., Cui, Z. J., Ishii, M. & Igarashi, Y. Stable coexistence of five bacterial strains as a cellulose-degrading community. Appl. Environ. Microbiol. 71, 7099–7106 (2005).

      (5) Zampieri, G., Campanaro, S., Angione, C. & Treu, L. Metatranscriptomics-guided genomescale metabolic modeling of microbial communities. Cell Reports Methods 3, 100383 (2023).

      (6) Berihu, M. et al. A framework for the targeted recruitment of crop ‑ beneficial soil taxa based on network analysis of metagenomics data. Microbiome 1–21 (2023) doi:10.1186/s40168-022-01438-1.

      (7) Dhakar, K. et al. Modeling-Guided Amendments Lead to Enhanced Biodegradation in Soil. mSystems 7, (2022).

      (8) Machado, D., Andrejev, S., Tramontano, M. & Patil, K. R. Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. Nucleic Acids Res. 46, 7542–7553 (2018).

      (9) Henry, C. S. et al. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat. Biotechnol. 28, 977–982 (2010).

      (10) Freilich, S. et al. Competitive and cooperative metabolic interactions in bacterial communities. Nat. Commun. 2, (2011).

      (11) Price, M. Erroneous predictions of auxotrophies by CarveMe. Nat. Ecol. Evol. 7, 194–195 (2023).

      (12) Machado, D. & Patil, K. R. Reply to: Erroneous predictions of auxotrophies by CarveMe. Nat. Ecol. Evol. 7, 196–197 (2023).

      (13) Kulichevskaya, I. S. et al. Acidicapsa borealis gen. nov., sp. nov. and Acidicapsa ligni sp. nov., subdivision 1 Acidobacteria from Sphagnum peat and decaying wood. Int. J. Syst. Evol. Microbiol. 62, 1512–1520 (2012).

      (14) Depart-, M. & Building, L. S. Lignocellulose-degrading actinomycetes. 46, 145–163 (1987).

      (15)Thomas, F., Hehemann, J. H., Rebuffet, E., Czjzek, M. & Michel, G. Environmental and gut Bacteroidetes: The food connection. Front. Microbiol. 2, 1–16 (2011).

      (16) Dow, J. M. & Daniels, M. J. Pathogenicity determinants and global regulation of pathogenicity of Xanthomonas campestris pv. campestris. Curr. Top. Microbiol. Immunol. 192, 29–41 (1994).

      (17) Bergmann, G. T. et al. The under-recognized dominance of Verrucomicrobia in soil bacterial communities. Soil Biol. Biochem. 43, 1450–1455 (2011).

      (18) Zhalnina, K. et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat. Microbiol. 3, 470–480 (2018).

      (19) Uzun, M. et al. Recovery and genome reconstruction of novel magnetotactic Elusimicrobiota from bog soil. ISME J. 1–11 (2022) doi:10.1038/s41396-022-01339-z.

      (20) Lei, S. et al. Analysis of the community composition and bacterial diversity of the rhizosphere microbiome across different plant taxa. Microbiologyopen 8, 1–10 (2019).

      (21) Ghosh, S. K., Banerjee, S. & Sengupta, C. Bioassay, characterization and estimation of siderophores from some important antagonistic fungi. J. Biopestic. 10, 105–112 (2017).

      (22) Lu, X., Heal, K. R., Ingalls, A. E., Doxey, A. C. & Neufeld, J. D. Metagenomic and chemical characterization of soil cobalamin production. ISME J. 14, 53–66 (2020).

      (23) Mee, M. T., Collins, J. J., Church, G. M. & Wang, H. H. Syntrophic exchange in synthetic microbial communities. Proc. Natl. Acad. Sci. U. S. A. 111, (2014).

      (24) Justin, K., Edmond, S., Ally, M. & Xin, H. Plant Secondary Metabolites: Biosynthesis, Classification, Function and Pharmacological Properties. J. Pharm. Pharmacol. 2, 377–392 (2014).

      (25) Yang, W. et al. A Genomic Analysis of Bacillus megaterium HT517 Reveals the Genetic Basis of Its Abilities to Promote Growth and Control Disease in Greenhouse Tomato. Genet. Res. (Camb). 2022, (2022).

      (26) Balbín-Suárez, A. et al. Root exposure to apple replant disease soil triggers local defense response and rhizoplane microbiome dysbiosis. FEMS Microbiol. Ecol. 97, 1–14 (2021).

      (27) Weiß, S., Liu, B., Reckwell, D., Beerhues, L. & Winkelmann, T. Impaired defense reactions in apple replant disease-Affected roots of Malus domestica ‘M26’. Tree Physiol. 37, 1672–1685 (2017).

      (28) Weiß, S., Bartsch, M. & Winkelmann, T. Transcriptomic analysis of molecular responses in Malus domestica ‘M26’ roots affected by apple replant disease. Plant Mol. Biol. 94, 303– 318 (2017).

      (29) Sun, N. et al. Effects of Organic Acid Root Exudates of Malus hupehensis Rehd. Derived from Soil and Root Leaching Liquor from Orchards with Apple Replant Disease. Plants 11, (2022).

      (30) Howell, C. R. Seed Treatment with L-Sorbose to Control Damping-Off or Cotton Seedlings by Rhizoctonia solani. Phytopathology 68, 1096 (1978).

      (31) Zou, C. S., Mo, M. H., Gu, Y. Q., Zhou, J. P. & Zhang, K. Q. Possible contributions of volatile-producing bacteria to soil fungistasis. Soil Biol. Biochem. 39, 2371–2379 (2007).

      (32) Gomes, V. A. et al. Activity of papaya seeds (Carica papaya) against Meloidogyne incognita as a soil biofumigant. J. Pest Sci. (2004). 93, 783–792 (2020).

      (33) Gao, T. et al. Exogenous dopamine and overexpression of the dopamine synthase gene MdTYDC alleviated apple replant disease. Tree Physiol. 41, 1524–1541 (2021).

      (34) Diener, C., Gibbons, S. M. & Resendis-Antonio, O. MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota. mSystems 5, (2020).

      (35) Dukovski, I. et al. A metabolic modeling platform for the computation of microbial ecosystems in time and space (COMETS). Nat. Protoc. 16, 5030–5082 (2021).

      (36) Katarina Wedmark, Y., Olav Vik, J. & Øyås, O. A hierarchy of metabolite exchanges in metabolic models of microbial species and communities. bioRxiv 1–19 (2023).

      (37) Zorrilla, F., Buric, F., Patil, K. R. & Zelezniak, A. MetaGEM: Reconstruction of genome scale metabolic models directly from metagenomes. Nucleic Acids Res. 49, (2021).

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      It is suggested that for each limb the RG (rhythm generator) can operate in three different regimes: a non-oscillating state-machine regime, and in a flexor driven and a classical half-center oscillatory regime. This means that the field can move away from the old concept that there is only room for the classic half-center organization

      Strengths:

      A major benefit of the present paper is that a bridge was made between various CPG concepts ( "a potential contradiction between the classical half-center and flexor-driven concepts of spinal RG operation"). Another important step forward is the proposal about the neural control of slow gait ("at slow speeds ({less than or equal to} 0.35 m/s), the spinal network operates in a state regime and requires external inputs for phase transitions, which can come from limb sensory feedback and/or volitional inputs (e.g. from the motor cortex").

      Weaknesses:

      Some references are missing

      We thank the Reviewer for the thoughtful and constructive comments. We have added additional text to meet the specific Reviewer’s recommendations and several references suggested by the Reviewer.  

      Reviewer #2 (Public Review):

      Summary:

      The biologically realistic model of the locomotor circuits developed by this group continues to define the state of the art for understanding spinal genesis of locomotion. Here the authors have achieved a new level of analysis of this model to generate surprising and potentially transformative new insights. They show that these circuits can operate in three very distinct states and that, in the intact cord, these states come into successive operation as the speed of locomotion increases. Equally important, they show that in spinal injury the model is "stuck" in the low speed "state machine" behavior.

      Strengths:

      There are many strengths for the simulation results presented here. The model itself has been closely tuned to match a huge range of experimental data and this has a high degree of plausibility. The novel insight presented here, with the three different states, constitutes a truly major advance in the understanding of neural genesis of locomotion in spinal circuits. The authors systematically consider how the states of the model relate to presently available data from animal studies. Equally important, they provide a number of intriguing and testable predictions. It is likely that these insights are the most important achieved in the past 10 years. It is highly likely proposed multi-state behavior will have a transformative effect on this field.

      Weaknesses:

      I have no major weaknesses. A moderate concern is that the authors should consider some basic sensitivity analyses to determine if the 3 state behavior is especially sensitive to any of the major circuit parameters - e.g. connection strengths in the oscillators or?

      We thank the Reviewer for the thoughtful and constructive comments. The sensitivity analysis has been included as Supplemental file.

      Reviewer #3 (Public Review):

      Summary:

      This work probes the control of walking in cats at different speeds and different states (split-belt and regular treadmill walking). Since the time of Sherrington there has been ongoing debate on this issue. The authors provide modeling data showing that they could reproduce data from cats walking on a specialized treadmill allowing for regular and split-belt walking. The data suggest that a non-oscillating state-machine regime best explains slow walking - where phase transitions are handled by external inputs into the spinal network. They then show at higher speeds a flexor-driven and then a classical halfcenter regime dominates. In spinal animals, it appears that a non-oscillating state-machine regime best explains the experimental data. The model is adapted from their previous work, and raises interesting questions regarding the operation of spinal networks, that, at low speeds, challenge assumptions regarding central pattern generator function. This is an interesting study. I have a few issues with the general validity of the treadmill data at low speeds, which I suspect can be clarified by the authors.

      Strengths:

      The study has several strengths. Firstly the detailed model has been well established by the authors and provides details that relate to experimental data such as commissural interneurons (V0c and V0d), along with V3 and V2a interneuron data. Sensory input along with descending drive is also modelled and moreover the model reproduces many experimental data findings. Moreover, the idea that sensory feedback is more crucial at lower speeds, also is confirmed by presynaptic inhibition increasing with descending drive. The inclusion of experimental data from split-belt treadmills, and the ability of the model to reproduce findings here is a definite plus.

      Weaknesses:

      Conceptually, this is a very useful study which provides interesting modeling data regarding the idea that the network can operate in different regimes, especially at lower speeds. The modelling data speaks for itself, but on the other hand, sensory feedback also provides generalized excitation of neurons which in turn project to the CPG. That is they are not considered part of the CPG proper. In these scenarios, it is possible that an appropriate excitatory drive could be provided to the network itself to move it beyond the state-machine state - into an oscillatory state. Did the authors consider that possibility? This is important since work using L-DOPA, for example, in cats or pharmacological activation of isolated spinal cord circuits, shows the CPG capable of producing locomotion without sensory or descending input.

      We thank the Reviewer for the thoughtful and constructive comments. We have added additional texts, references, and discussed the issues raised by the Reviewer. Particularly, in section “Model limitations and future directions” we now admit that afferent feedback can provide some constant level excitation to the RG circuits after spinal transection which can partly compensate for the lack of supraspinal drive and hence affect (shift) the timing of transitions between the considered regimes. We mentioned that this is one of the limitations of the present model. The potential effects of neuroactive drugs, like DOPA, on CPG circuits after spinal transection were left out because they are outside the scope of the present modeling studies.    

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      specific feedback to the authors:

      Nevertheless, there are some minor points, worth considering.

      Link to HUMAN DATA

      Here the authors may be interested to know that human data supports their proposal. This is relevant since there is ample evidence for the operation of spinal CPG's in humans (Duysens and van de Crommert,1998). The present model predicts that the basic output of the CPG remains even at very slow speeds, thus leading to similarity in EMG output. This prediction fits the experimental data (den Otter AR, Geurts AC, Mulder T, Duysens J. Speed related changes in muscle activity from normal to very slow walking speeds. Gait Posture. 2004 Jun;19(3):270-8). To investigate whether the basic CPG output remains basically the same even at very slow speeds (as also predicted by the current model), humans walked slowly on a treadmill (speeds as slow as 0.28 m s−1). Results showed that the phasing of muscle activity remained relatively stable over walking speeds despite substantial changes in its amplitude. Some minor additions were seen, consistent with the increased demands of postural stability. Similar results were obtained in another study: Hof AL, Elzinga H, Grimmius W, Halbertsma JP. Speed dependence of averaged EMG profiles in walking. Gait Posture. 2002 Aug;16(1):78-86. doi:

      10.1016/s0966-6362(01)00206-5. PMID: 12127190.

      These authors wrote: "The finding that the EMG profiles of many muscles at a wide range of speeds can be represented by addition of few basic patterns is consistent with the notion of a central pattern generator (CPG) for human walking". The basic idea is that the same CPG can provide the motor program at slow and fast speeds but that the drive to the CPG differs. This difference is accentuated under some conditions in pathology, such as in Parkinson's Kinesia Paradoxa. It was argued that the paradox is not really a paradox but is explained as the CPGs are driven by different systems at slow and at fast speeds (Duysens J, Nonnekes J. Parkinson's Kinesia Paradoxa Is Not a Paradox. Mov Disord. 2021 May;36(5):1115-1118. doi: 10.1002/mds.28550. Epub 2021 Mar 3. PMID: 33656203.)

      These ideas are well in line with the current proposal ("Based on our predictions, slow (conditionally exploratory) locomotion is not "automatic", but requires volitional (e.g. cortical) signals to trigger stepby-step phase transitions because the spinal network operates in a state-machine regime. In contrast, locomotion at moderate to high speeds (conditionally escape locomotion) occurs automatically under the control of spinal rhythm-generating circuits receiving supraspinal drives that define locomotor speed, unless voluntary modifications or precise stepping are required to navigate complex terrain").

      As mentioned in the present paper, other examples exist from pathology ("...Another important implication of our results relates to the recovery of walking in movement disorders, where the recovered pattern is generally very slow. For example, in people with spinal cord injury, the recovered walking pattern is generally less than 0.1 m/s and completely lacks automaticity 77-79. Based on our predictions, because the spinal locomotor network operates in a state-machine regime at these slow speeds, subjects need volition, additional external drive (e.g., epidural spinal cord stimulation) or to make use of limb sensory feedback by changing their posture to perform phase transitions"). As mentioned above, another example is provided by Parkinson's disease. The authors may also be interested in work on flexible generators in SCI: Danner SM, Hofstoetter US, Freundl B, Binder H, Mayr W, Rattay F, Minassian K. Human spinal locomotor control is based on flexibly organized burst generators. Brain. 2015 Mar;138(Pt 3):577-88. doi: 10.1093/brain/awu372. Epub 2015 Jan 12. PMID: 25582580; PMCID: PMC4408427.

      We thank the reviewer for these additional and interesting insights. We added a new paragraph in the Discussion to bolster the link with human data that includes references suggested by the Reviewer.

      CHAIN OF REFLEXES

      It reads: "... in opposition to the previously prevailing viewpoint of Charles Sherrington 21,22 that locomotion is generated through a chain of reflexes, i.e., critically depends on limb sensory feedback (reviewed in 23)." This is correct but incomplete. The reference cited (23: Stuart, D.G. and Hultborn, H, "Thomas Graham Brown (1882--1965), Anders Lundberg (1920-), and the neural control of stepping," Brain Res. Rev. 59(1), 74-95 (2008)) actually reads: "Despite the above findings, the doctrinaire position in the early 1900s was that the rhythm and pattern of hind limb stepping movements was attributable to sequential hind limb reflexes. According to Graham Brown (1911c) this viewpoint was largely due to the arguments of Sherrington and a Belgian physiologist, Maurice Philippson (1877-1938). Philippson studied stepping movements in chronically maintained spinal dogs, using techniques he had acquired in the Strasbourg laboratory of the distinguished German physiologist, Friedrich Goltz (1834-1902). He also analyzed kinematically moving pictures of dog locomotion, which had been sent to him by the renowned French physiologist, Etienne-Jules Marey (1830-1904). Philippson (1905) certainly presented arguments explaining his perception of how sequential spinal reflexes contributed to the four phases of the step cycle (see Fig. 1 in Clarac, 2008). In retrospect, it is likely that Graham Brown was correct in attributing to Philippson and Sherrington the then-prevailing viewpoint that reflexes controlled spinal stepping. It is puzzling, nonetheless, that far less was said then and even now about Philippson's belief that the spinal control was due to a combination of central and reflex mechanisms (Clarac, 2008),4,5 4 We are indebted to François Clarac for drawing to our attention Philippson's statement on p. 37 of his 1905 article that "Nos expériences prouvent d'une part que la moelle lombaire séparée du reste de l'axe cérébro-spinal est capable de produire les mouvements coordonnés dans les deux types de locomotion, trot et gallop. [Our experiments prove that one side of the spinal cord separated from the cerebro-spinal axis is able to produce coordinated movements in two types of locomotion, trot and gallop]." Then, on p. 39 Philippson (1905) states that "Nous voyons donc, en résumé que la coordination locomotrice est une fonction exclusivement médullaire, soutenue d'une part par des enchainements de réflexes directs et croisés, dont l'excitant est tantot le contact avec le sol, tantot le mouvement même du membre. [In summary, we see that locomotor coordination is an exclusive function of the spinal cord supported by a sequencing of direct and crossed reflexes, which are activated sometimes by contact with the ground and sometimes even by leg movement]. A coté de cette coordination basée sur des excitations périphériques, il y a une coordination centrale provenant des voies d'association intra-médullaires. [In conjunction with this peripherally excited coordination, there is a central coordination arising from intraspinal pathways]." (The English translations have also been kindly supplied by François Clarac.) Clearly, Philippson believed in both a central spinal and a reflex control of stepping! 5 In part 1 of his 1913/1916 review Graham Brown discussed Philippson's 1905 article in much detail (pp. 345-350 in Graham Brown, 1913b). He concludes with the statement that "... Philippson die wesentlichen Factoren des Fortbewegungsaktes in das exterozeptive Nervensystem verlegt. Er nimmt an, dass die zyklischen Bewegungen automatisch durch äussere Reize erhalten werden, welche in sich selbst thythmisch als Folge der Reflexakte welche sie selbst erzeugen, wiederholt werden. [Philippson assigns the important factors of the act of locomotion to the exteroceptive nervous system. He assumes that the cyclic movements are automatically maintained by external stimuli which, by themselves, are rhythmically repeated as a consequence of the reflexive actions that they generate themselves]." (English translation kindly supplied by Wulfila Gronenberg). This interpretation clearly ignores Philippson's emphasis on a central spinal component in the control of stepping....). "

      Hence it is a simplification to give all credits to Sherrington and ignoring the role of Philippson concerning the chain of reflexes idea.

      We again thank the Reviewer for these additional and interesting insights. We added the Philippson (1905) and Clarac (2008) references. The important contribution of Philippson is now indicated.

      GTO Ib feedback

      It reads: "This effect and the role of Ib feedback from extensor afferents has been demonstrated and described in many studies in cats during real and fictive locomotion 2,57-59."

      These citations are appropriate but it is surprising to see that the Hultborn contribution is limited to the Gossard reference while the even more important earlier reference to Conway et al is missing (Conway BA, Hultborn H, Kiehn O. Proprioceptive input resets central locomotor rhythm in the spinal cat. Exp Brain Res. 1987;68(3):643-56. doi: 10.1007/BF00249807. PMID: 3691733).

      Yes, the Conway et al. reference has been added.

      Other species

      The authors may also look at other species. The flexible arrangement of the CPGs, as described in this article, is fully in line with work on other species, showing cpg networks capable to support gait, but also scratching, swimming ..etc (Berkowitz A, Hao ZZ. Partly shared spinal cord networks for locomotion and scratching. Integr Comp Biol. 2011 Dec;51(6):890-902. doi: 10.1093/icb/icr041. Epub 2011 Jun 22. PMID: 21700568. Berkowitz A, Roberts A, Soffe SR. Roles for multifunctional and specialized spinal interneurons during motor pattern generation in tadpoles, zebrafish larvae, and turtles. Front Behav Neurosci. 2010 Jun 28;4:36. doi: 10.3389/fnbeh.2010.00036. PMID: 20631847; PMCID: PMC2903196.)

      Similar ideas about flexible coupling can also be found in: Juvin L, Simmers J, Morin D. Locomotor rhythmogenesis in the isolated rat spinal cord: a phase-coupled set of symmetrical flexion extension oscillators. J Physiol. 2007 Aug 15;583(Pt 1):115-28. doi: 10.1113/jphysiol.2007.133413. Epub 2007 Jun 14. PMID: 17569737; PMCID: PMC2277226. Or zebrafish: Harris-Warrick RM. Neuromodulation and flexibility in Central Pattern Generator networks. Curr Opin Neurobiol. 2011 Oct;21(5):685-92. doi: 10.1016/j.conb.2011.05.011. Epub 2011 Jun 7. PMID: 21646013; PMCID: PMC3171584.

      We added a sentence in the Discussion along with supporting references.

      Standing

      In the view of the present reviewer, the model could even be extended to standing in humans. It reads: "at slow speeds ({less than or equal to} 0.35 m/s), the spinal network operates in a state regime and requires external inputs"; similarly (personal experience) when going from sit to stand: as soon as weight is over support, extension is initiated and the body raises, as one would expect when the extensor center is activated by reinforcing load feedback, replacing GTO inhibition (Faist M, Hoefer C, Hodapp M, Dietz V, Berger W, Duysens J. In humans Ib facilitation depends on locomotion while suppression of Ib inhibition requires loading. Brain Res. 2006 Mar 3;1076(1):87-92. doi:

      Yes, we agree that the model could be extended to standing and the transition from standing to walking is particularly interesting. However, for this paper, we will keep the focus on locomotion over a range of speeds.

      Reviewer #2 (Recommendations For The Authors):

      The presentation is exceedingly well done and very clear.

      A moderate concern is that the authors do not make use of the capacity of computer simulations for sensitivity analyses. Perhaps these have been previously published? In any case, the question here is whether the 3 state behavior is especially sensitive to excitability of one of the main classes of neurons or a crucial set of connections.

      The sensitivity analysis has been made and included as Supplemental file.

      Minor point. I have but two minor points. A bit more explanation should be provided for the use of the terms "state machine" to describe the lowest speed state. Perhaps this is a term from control theory? In any case, it is not clear why this is term is appropriate for a state in which the oscillator circuits are "stuck" in a constant output form and need to be "pushed" by sensory input.

      Yes, we now provide a definition in the Introduction.

      Minor point: it is of course likely that neuromodulation of multiple types of spinal neurons occurs via inputs that activate G protein coupled receptors. These types of inputs are absent from the model, which is fine, but some sort of brief discussion should be included. One possibility is to note that the circuit achieves transitions between different states without the need for neuromodulatory inputs. This appears to me to be a very interesting and surprising insight.

      In section “Model limitations and future directions” in the Discussion, we now mention that the term “supraspinal drive” in our model is used to represent supraspinal inputs providing both electrical and neuromodulator effects on spinal neurons increasing their excitability, which disappear after spinal transection.” We think that it is so far too early to simulate the exact effects of the descending neuromodulation, since there is almost no data on the effect of different modulators on specific types of spinal interneurons.

      Reviewer #3 (Recommendations For The Authors):

      Minor Comments  

      Page numbers would be useful.

      Abstract

      Following spinal transection, the network can only operate in a state-machine regime. This is a bit strong since it applies to computational data. Clarify this statement.

      We agree. Sentence has been changed to: “Following spinal transection, the model predicts that the spinal network can only operate in the state-machine regime.”

      Introduction

      Intro - "This is somewhat surprising...". It gives the impression that spinal cats are autonomously stable on the belt. They are stabilized by the experimenter.

      The text has been changed to: “This is somewhat surprising because intact and spinal cats rely on different control mechanisms. Intact cats walking freely on a treadmill engage vision for orientation in space and their supraspinal structures process visual information and send inputs to the spinal cord to control locomotion on a treadmill that maintains a fixed position of the animal relative to the external space. Spinal cats, whose position on the treadmill relative to the external space is fixed by an experimenter, can only use sensory feedback from the hindlimbs to adjust locomotion to the treadmill speed.”

      "Cannot consistently perform treadmill locomotion" - likely a context-dependent result. Certainly, cats can do this easily off a treadmill - stalking, for example. Perhaps somewhere, mention that treadmill locomotion is not entirely similar to overground locomotion.

      We completely agree. Stalking is an excellent example showing that during overground locomotion slow movements (and related phase transitions) can be controlled by additional voluntary commands from supraspinal structures, which differs from simple treadmill locomotion, performing out of specific goalor task-dependent contexts. Based on this, we suggest a difference between a relatively slow (exploratory-type, including stalking) and relatively fast (escape-type) overground locomotion. We added the following sentence to the introduction:” This is evidently context dependent and specific for the treadmill locomotion as cats, humans  and other animals can voluntarily decide to perform consistent overground locomotion at slow speeds.”

      The authors introduce the concept of the state machine regime. In my opinion, this could use some more explanation and citations to the literature. Was it a term coined by the authors, or is there literature reinforcing this point?

      This is a computer science and automata theory term that has already been used in descriptions of locomotion (see our references in the 2nd paragraph of Discussion). We added a definition and corresponding references in the Introduction.

      In terms of sensory feedback, particularly group II input, it would be interesting to calculate if the conduction delay to the spinal cord at higher speeds would have a certain cutoff point at which it would no longer be timed effectively for phase transitions. This could reinforce your point.

      This is an interesting proposition but it is unlikely to be a factor over the range of speeds that we investigated (0.1 to 1.0 m/s). Assuming that group II afferents transmit their signals to spinal circuits at a latency of 10-20 ms, this is more than enough time to affect phase transitions, even at the highest speed considered. This might be a factor at very high speeds (e.g. galloping) or in small animals with high stepping frequencies.

      Results.

      The assertion that intact cats are inconsistent in terms of walking at slow speeds needs to be bolstered. For example, if a raised platform were built for a tray of food, would the intact cat consistently walk at slower speeds and eat? I suspect so. By the same token, would they walk slowly during bipedal walking? It is pretty easy to check this. Also, reports from the literature show differential effects of runway versus treadmill gait analysis, specifically when afferent input is removed.

      The Reviewer is correct that raising a platform for a food tray or even having intact cats walk with their hindlimbs only (with forelimbs on a stationary platform) may allow for consistent stepping at slow speeds (0.1 – 0.3 m/s). However, this effectively removes voluntary control of locomotion and makes the pattern more automatic (spinal + limb sensory feedback). These examples provide additional specific contexts, and we have already mentioned (see above) that slow locomotion of intact cat is context dependent. 

      "We believe that intact animals walking on a treadmill..." Citations for this? Certainly, this is not a new point.

      No, this is not new. We changed the sentence and added a reference to the statement: “Intact animals walking on a treadmill use visual cues and supraspinal signals to adjust their speed and maintain a fixed position relative to the external space with reference to Salinas et al. (Salinas, M.M., Wilken, J M, and Dingwell, J B, "How humans use visual optic flow to regulate stepping during walking," Gait. Posture. 57, 15-20, 2017).

      The presentation of the results is somewhat disjointed. The intact data is presented for tied and splitbelt results, but this is not addressed explicitly until figure 4. Would it not be better to create a figure incorporating both intact and modelling data and present the intact data where appropriate?

      We tried to do this initially, but this way required changing the style of the whole paper and we decided against this idea. Therefore, we prefer to keep the presentation of results as it is now. 

      Regarding the role of sensory feedback being especially important at low speeds, it is interesting that egr3+ mice (lacking spindle input) show an inability to walk at high speeds >40 cm/s but can walk at lower speeds (up to 7 cm/s) (Takeoka et al 2014). Similar findings were found with a lesion affecting Group I afferents in general (Takeoka and Arber 2019). Also, Grillner and colleagues show that cats can produce fictive locomotion in the absence of sensory input.

      In the Takeoka experiments it is difficult to assess the effect of removing somatosensory feedback because animals can simply decide to not step at higher speeds to avoid injury. Their mice deprived of somatosensory feedback can walk at slow speeds, likely thanks to voluntary commands, and cannot do so at higher speeds because (1) maybe somatosensory feedback is indeed necessary and/or (2) because they feel threatened because of impaired posture and poor control in general. In other words, they choose to not walk at faster speeds to avoid injury.

      Fictive locomotion by definition is without phasic somatosensory feedback as the animals are curarized or studies are performed in isolated spinal cord preparations. Depending on the preparation, pharmacology or brainstem stimulation is required to evoke fictive locomotion. If animals are deafferented, pharmacology or brainstem stimulation are required to induce fictive locomotion to offset the loss of spinal neuronal excitability provided by primary afferents. At the same time, our preliminary analysis of old fictive locomotion data in the University of Manitoba Spinal Cord center (Drs. Markin and Rybak had an official access to these data base during our collaboration with Dr. David McCrea) has shown that the frequency of stable fictive locomotion in cats usually exceeded 0.6 - 0.7 Hz, which approximately corresponds to the speed above 0.3 - 0.4 m/s. These data and estimation are just approximate; they have not been statistically analyzed and published and hence have not been included in our paper.

      Discussion. The statement that sensory feedback is required for animals to locomote may need to be qualified. Animals need some sensory feedback to locomote is perhaps better. For example, lesion studies by Rossignol in the early 2000s showed that cutaneous feedback from the paw was seemingly quite critical (in spinal cats). Also, see previous comments above.

      We changed this to: “… requires some sensory feedback to locomote, …”

      Figures

      Figure 1C. This figure is somewhat confusing. If intact cats do not walk (arrow), how are the data for swing and stance computed? Also raw traces would be useful to indicate that there is variability. Also, while duration is useful, would you not want to illustrate the co-efficient of variation as well as another way to show that the stepping pattern was inconsistent?

      This is probably a misunderstanding. The left panel of Fig. 1C superimposes data of intact cats from panel A (with speed range from 0.4 m/s to 1.0 m/s) and data from spinal cats from panel B (with speed range from 0.1 m/s and 1.0 m/s). Therefore, the left part of this left panel 1C (with speed range from 0.1 m/s to 0.4 m/s (pointed out by the arrow) corresponds only to spinal cats (not to intact cats). The standard deviations of all measurements are shown. All these figures were reproduced from the previous publications. We did not apply new statistical analysis to these previously published data/figures.

      Figure 4. 'All supraspinal drives (and their suppression of sensory feedback) are eliminated from the schematic shown in A. ' However, it is labelled 'brainstem drives,' which is confusing. Moreover, many of the abbreviations are confusing. Do you need l-SF-E1 in the figure, or could you call it 'Feedback 1' and then refer to l-SF-E1 in the legend? The same goes for βr, etc. Can they move to the legend?

      In the intact model (Fig. 4A), we have supraspinal drives (𝛼𝐿 and 𝛼𝑅, and  𝛾𝐿 and 𝛾𝑅 ), some of which provide presynaptic inhibition of sensory feedback (SF-E1 and SF-E2) as shown in Fig. 4A. In spinaltransected model (Fig. 4B), the above brainstem drives and their effects (presynaptic inhibition) on both feedback types are eliminated (therefore, there is no label “Brainstem drives in Fig. 4B). Also, we do not see a strong reason to change the feedback names, since they are explained in the text.

      I appreciate the detail of these figures, but they are difficult to conceptualize. They are useful in the context of 3C. Perhaps move this figure to supplementary and then show the proposed schematics for the system operating at slow, medium, and fast speeds in a replacement figure?

      We apologize for the resistance, but we would like to keep the current presentation.

      There is a lack of raw data (models or experimental) data reinforcing the figures. I would add these to all figures, which would nicely complement the graphs.

      These raw data can be found in the cited manuscripts. It would be the same figures.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC-2024-02546

      Corresponding author: Woo Jae, Kim

      1. General Statements

      The goal of this study is to provide the insights of one specific neuron ‘SIFa’ controls interval timing behavior by its receptor ‘SIFaR’ through neuropeptide relay. Interval timing, or the sense of time in the seconds to hours range, is important in foraging, decision making, and learning in humans via activation of cortico-striatal circuits. Interval timing requires completely distinct brain processes from millisecond or circadian timing. In summary, interval timing allows us to subjectively sense the passage of physical time, allowing us to integrate action sequences, thoughts, and behavior, detect developing trends, and predict future consequences.

      Many researchers have tried to figure out how animals, including humans, can estimate time intervals with such precision. However, most investigations have been conducted in the realm of psychology rather than biology thus far. Because the study of interval timing was limited in its ability to intervene in the human brain, many psychologists concentrated on developing convincing theoretical models to explain the known occurrence of interval timing.

      To overcome the limits of studying interval timing in terms of genetic control, we have reported that the time investment strategy for mating in Drosophila males can be a suitable behavioral platform to genetically dissect the principle of brain circuit mechanism for interval timing. For example, we previously reported that males prolong their mating when they have previously been exposed to rivals (Kim, Jan & Jan, "Contribution of visual and circadian neural circuits to memory for prolonged mating induced by rivals" Nature Neuroscience, 2012) (Kim et al, 2012), and this behavior is regulated by visual stimuli, clock genes, and neuropeptide signaling in a subset of neurons (Kim, Jan & Jan, “A PDF/NPF Neuropeptide Signaling Circuitry of Male Drosophila melanogaster Controls Rival-Induced Prolonged Mating” Neuron, 2013) (Kim et al, 2013). And we also reported that the sensory inputs are required for sexual experienced males to shorten their mating time (Lee, Sun, et al, “Taste and pheromonal inputs govern the regulation of time investment for mating by sexual experience in male Drosophila melanogaster” PLOS genetics, 2023) (Lee et al, 2023).

      Throughout their lives, all animals must make decisions in order to optimize their utility function. Male reproductive success is determined by how many sperms successfully fertilize an egg with a restricted number of investment resources. To optimize male reproductive fitness, a time investment strategy has been devised. As a consequence, we believe that the flexible responses of mating duration to different environmental contexts in Drosophila males might be an excellent model to investigate neural circuits for interval timing.

      The most well-known features of mammalian modulating energy homeostasis between the gut and the brain is one of the most intensively studied neuro-modulatory circuits via the neuronal relay of neuropeptides. In this article, we report that SIFa controls two alternate interval timing behaviors through neuropeptide relay signaling by SIFaR and other important neuropeptides and transmits the internal states of the male brain into decision making. According to our findings, male Drosophila utilize SIFa-SIFaR signaling modulating LMD and SMD behaviors. During our investigation in this regulation, we found a subset of cells that express SIFaR in SOG and AG region are important for the modulation of interval timing behaviors. Furthermore, we discovered a neuropeptide named Corazonin (Crz) which expressed in SIFaR is important for both LMD and SMD behaviors.

      Our discovery of neuropeptide relay of SIFa-SIFaR-Crz-CrzR in male Drosophila in modulating interval timing behaviors will be a huge step forward in our knowledge of interval timing behavior.

      2. Point-by-point description of the revisions

      Reviewer #1

      Comment 1. The authors are to be commended for the sheer quantity of data they have generated, but I was often overwhelmed by the figures, which try to pack too much into the space provided. As a result, it is often unclear what components belong to each panel. Providing more space between each panel would really help.

      __ Answer:__ We are grateful for the insightful feedback regarding the structure of our data presentation. In response to your valuable suggestion, we have made adjustments in this revised version by downsizing the diagram and ensuring the spacing between the panels.

      Comment 2. The use of three independent RNAi lines to knock down SIFaR expression is experimentally solid, as the common phenotype observed with all 3 lines supports the conclusion that the SIFaR is important for mating duration choice. However, the authors have not tested whether these lines effectively reduce SIFaR expression, nor whether the GAL80 constructs used to delimit knockdown are able to effectively do so. This makes it hard to make definitive conclusions with these manipulations, especially in the face of negative results. A lack of complete knockdown is suggested by the fact that the F24F06 driver rescues lethality when used to express SIFaR in the B322 mutant background, but does not itself produce lethality when used to express SIFaR RNAi. The authors should either conduct experiments to determine knockdown efficiency or explicitly acknowledge this limitation in drawing conclusions from their experiments. A similar concern relates to the CrzR knockdown experiments (eg Figure 7).

         __Answer:__ We appreciate the reviewer's attention to the details of our experimental design. Indeed, the validation of SIFaR-RNAi efficiency is crucial for interpreting our results accurately. In our initial experiments, we focused on the consistent phenotypic outcomes across the three independent RNAi lines, which collectively suggest the importance of SIFaR in LMD and SMD behaviors. However, we recognize the importance of confirming the effectiveness of our RNAi constructs in reducing SIFaR expression. Initially, we incorporated experiments utilizing *elav-GAL80* to demonstrate that the SIFaR knockdown mediated by the *elavc155* driver is sufficient to eliminate LMD and SMD behaviors. The corresponding results are presented in Figure 1C-D, with a detailed description provided in the manuscript as detailed below.
      

      "The inclusion of elav-GAL80, which suppresses GAL4 activity in a pan-neuronal context, was found to restore both LMD and SMD behaviors when SIFaR was knocked down by a pan-neuronal elavc155 driver (Fig. 1C-D). This observation suggests that the reduction in SIFaR expression mediated by the elavc155 driver is sufficient to significantly impair LMD and SMD behaviors."

         In response to the comments, we have conducted a thorough reevaluation in our revised manuscript. Specifically, we have confirmed the efficiency of the SIFaR-RNAi line HMS00299, which exhibited the most pronounced phenotype when co-expressed with the tub-GAL4 and nSyb-GAL4 drivers, using quantitative real-time PCR (qRT-PCR). It has come to our attention that we omitted mentioning the embryonic lethality induced by the HMS00299 line when combined with either tub-GAL4 or nSyb-GAL4 drivers, which is consistent with the homozygous lethality observed in the *SIFaRB322* mutant. To address this, we have performed qRT-PCR experiments by crossing the HMS00299 line with tub-GAL4; tub-GAL80ts, allowing for the temporary knockdown of SIFaR specifically during the adult stage. We utilized w-/SIFaR-RNAis as a control in these experiments. The outcomes are illustrated in Figure 1E, and we have made the necessary modifications and additions to the manuscript to accurately reflect the efficiency of the SIFaR-RNAi line as detailed below.
      

      "To ensure that RNAi did not have an off-target effect, we tested three independent RNAi strains and found that all three RNAi successfully disrupted LMD/SMD when expressed in neuronal populations. (Fig. S1E-J). We chose to use the HMS00299 line as SIFaR-RNAi for all our experiments because it efficiently disrupts LMD/SMD without UAS-dicer expression. Employment of broad drivers, including the tub-GAL4 and the strong neuronal driver nSyb-GAL4, with HMS00299 line consistently results in 100% embryonic lethality (data not shown). This phenotype mirrors the homozygous lethality observed in the SIFaRB322 mutant. The efficiency of HMS00299 SIFaR-RNAi lines was also validated through quantitative PCR analysis (Fig. 1E). Consequently, we infer that the knockdown of SIFaR using the HMS00299 line nearly completely diminishes the levels of the SIFaR protein."

      We also examined the knockdown efficiency of CrzR in the experiments related to Figure 8 (revised version), following a similar approach (Fig. S7K).

      Comment 3. Most of the behavioral experiments lack traditional controls, for example flies that contain either the GAL4 or UAS elements alone. The authors should explain their decision to omit these control experiments and provide an argument for why they are not necessary to correctly interpret the data. In this vein, the authors have stated in the methods that stocks were outcrossed at least 3x to Canton-S background, but 3 outcrosses is insufficient to fully control for genetic background.

      • *Answer: We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. Consequently, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.

      "Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

      However, we understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

      "__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

         We appreciate the reviewer's inquiry regarding the genetic background of our experimental lines. In response to the comments, we would like to clarify the following. All of our GAL4, UAS, or RNAi lines, which were utilized as the virgin female stock for outcrosses, have been backcrossed to the Canton-S (CS) genetic background for over ten generations. The majority of these lines, particularly those employed in LMD assays, have been maintained in a CS backcrossed status for several years, ensuring a consistent genetic background across multiple generations. Our experience has indicated that the genetic background, particularly that of the X chromosome inherited from the female parent, plays a pivotal role in the expression of certain behavioral traits. Therefore, we have consistently employed these fully outcrossed females as virgins for conducting experiments related to LMD and SMD behaviors. It is noteworthy that, in contrast to the significance of genetic background for LMD behaviors, we have previously established in our work (Lee *et al*, 2023) that the genetic background does not significantly influence SMD behaviors. This distinction is important for the interpretation of our findings. To provide a comprehensive understanding of our experimental design, we have detailed the genetic background considerations in the __"Materials and Methods"__ section, specifically in the subsection __"Fly Stocks and Husbandry"__ as outlined below.
      

      "To reduce the variation from genetic background, all flies were backcrossed for at least 3 generations to CS strain. For the generation of outcrosses, all GAL4, UAS, and RNAi lines employed as the virgin female stock were backcrossed to the CS genetic background for a minimum of ten generations. Notably, the majority of these lines, which were utilized for LMD assays, have been maintained in a CS backcrossed state for long-term generations subsequent to the initial outcrossing process, exceeding ten backcrosses. Based on our experimental observations, the genetic background of primary significance is that of the X chromosome inherited from the female parent. Consequently, we consistently utilized these fully outcrossed females as virgins for the execution of experiments pertaining to LMD and SMD behaviors. Contrary to the influence on LMD behaviors, we have previously demonstrated that the genetic background exerts negligible influence on SMD behaviors, as reported in our prior publication (Lee et al, 2023). All mutants and transgenic lines used here have been described previously."

      Comment 4. Throughout the manuscript, the authors appear to use a single control condition (sexually naïve flies raised in groups) to compare to both males raised singly and males with previous sexual experience. These control conditions are duplicated in two separate graphs, one for long mating duration and one for short mating duration, but they are given different names (group vs naïve) depending on the graph. If these are actually the same flies, then this should be made clear, and they should be given a consistent name across the different "experiments".

      * * Answer: We are grateful to the reviewer for highlighting the potential for confusion among readers regarding the visualization methods used in our figures. In response to this valuable feedback, we have now included a more detailed explanation of the graph visualization techniques in the legends of Figure 1, as detailed below. This additional information should enhance the clarity and understanding of the figure for all readers.

      "In the mating duration (MD) assays, light grey data points denote males that were group-reared (or sexually naïve), whereas blue (or pink) data points signify males that were singly reared (or sexually experienced). The dot plots represent the MD of each male fly. The mean value and standard error are labeled within the dot plot (black lines). Asterisks represent significant differences, as revealed by the unpaired Student’s t test, and ns represents non-significant differences (*p* *

      Comment 5.* The authors have consistently conflated overlap of neuronal processes with synaptic connections. Claims of synaptic connectivity deriving solely from overlap of processes should be tempered and qualified.

      • For example, they say (Lines 201-202) "These findings suggest that SIFa neurons and GAL424F06-positive neurons form more synapses in the VNC than in the brain." This is misleading. Overlap of 24F06-LexA>CD8GFP and SIFa-GAL4>CD8RFP tells us nothing about synapse number, or even whether actual synapses are being formed.*

      • *Answer: We sincerely thank the reviewer for their insightful and constructive feedback regarding the interpretation of our data. We acknowledge the important point raised about the limitations of inferring synapse numbers from the overlap of membrane GFP and RFP signals. We fully concur that more specific techniques, such as the GRASP method, are necessary to accurately quantify synapse numbers, as we have demonstrated in subsequent sections of our manuscript. In the section where we describe the SIFa-SIFaR neuronal architecture labeled with membrane GFP and RFP, we recognize the need for caution in not overstating the implications of these findings as indicative of synapse formation. In light of the reviewer's comments, we have revised our discussion to more accurately reflect the nature of the SIFa-SIFaR neuronal arborizing patterns, as detailed below. This revision aims to provide a more nuanced interpretation of our observations and to align with the current scientific understanding of synaptic quantification.

      "As previously reported, SIFa neurons arborize extensively throughout the CNS, but the neuronal processes of GAL424F06-positive neurons are enriched in the optic lobe (OL), sub-esophageal ganglion (SOG), and abdominal ganglion (AG) (GFP signal in Fig. 2F). Neuronal processes that are positive for SIFa and SIFaR strongly overlap in the prow (PRW), prothoracic and metathoracic neuromere (ProNm and MesoNm), and AG regions (yellow signals in Fig. S3A). We quantified these overlapping neuronal processes between SIFa- and SIFaR-positive neurons and found that approximately 18% of SIFa neurons and 52% of GAL424F06-positive neurons overlap in brain (Fig. S3B, C), whereas approximately 48% of SIFa and 54% of GAL424F06-positive neurons overlap in VNC (Fig. S3D, E). These findings suggest that SIFa neurons and GAL424F06-positive neurons form more neuronal processes in the VNC than in the brain."

      • * Lines 210-211: "The overlap of DenMark and syt.EGFP signals was highly enriched in both SOG and ProNm regions, indicating that these regions are where GAL424F06 neurons form interconnected networks". This is misleading. Overlap of DenMark and syt.EGFP does not indicate synapses (especially since these molecules can be expressed outside the expected neuronal compartment if driven at high enough levels).*

      • *Answer: We are grateful for the reviewer's critical insights regarding our interpretation of the DenMark and syt.eGFP experiments. We acknowledge the reviewer's point that the overlap of DenMark and syt.eGFP signals does not conclusively indicate synapses and that some of these signals can be expressed outside the expected neuronal compartments, particularly at high levels.

        It is important to note that DenMark and syt.eGFP are markers of synaptic polarity. In the original publication of DenMark, the authors demonstrated that while these two markers are closely apposed, they do not necessarily overlap, as seen in the labeled yellow areas. They concluded that these areas could represent closely apposed regions where "LNv neurons establish presynaptic contacts within the aMe, suggesting that these contacts are on the postsynaptic sites of the LNv neurons themselves. (Nicolaï et al, 2010)" The authors also observed that DenMark-enriched structures appear juxtaposed to, rather than coexpressed with, syt.eGFP, indicating a potential for synapse formation between R neurons within the eb. In contrast, projections to the suboesophageal ganglion, which show strong Syt–GFP expression, are devoid of DenMark, suggesting a different interpretation of the signals (Nicolaï et al, 2010).

        Building on these findings, we have reanalyzed our data with caution (as shown in Figure S3). In the SOG region, where we observed strong yellow signals, these were not limited to cell bodies but also extended to the middle region filled with neural processes. Upon close examination of the DenMark and syt.eGFP signals, we confirmed that these yellow signals are closely juxtaposed, suggesting the possibility of synapse formation between SIFaR24F06 neurons within the SOG. We emphasize that this interpretation is based on the original findings from the DenMark study. To provide clarity for general readers, we have added further explanations regarding the interpretation of these signals, as detailed below. We believe that our revised analysis and the additional explanations will help to clarify the potential implications of our findings, while also acknowledging the limitations and the need for further investigation.

      "DenMark-enriched structures, localized within the SOG, are observed in close apposition to syt.eGFP signals, as indicated by the white-dashed circles (Fig. S3Fa). This spatial relationship suggests that SIFaR-expressing neurons, identified by GAL424F06 labeling, may form synapses with one another within the SOG. The colocalization of yellow signals resulting from the interaction between DenMark and syt.eGFP has been previously interpreted and validated by other researchers, supporting our observation (Nicolaï 2010,Kennedy 2018). In contrast to the yellow signals observed in the SOG, which are indicative of neural processes, the yellow signals detected in the ProNm appear to be associated with cell bodies rather than neural processes, as DenMark signals are often observed to leak out (as shown in Fig. S3Fb) (Nicolaï 2010,Kennedy 2018). Despite the presence of juxtaposed DenMark and syt.GFP signals in the ProNm, the interpretation of the yellow signals as potential synapses between SIFaR neurons remains an open question (indicated by the question mark in Fig. S3K).

        • Lines 320-322: "Neurons expressing Crz exhibit robust synaptic connections with SIFaR24F06 neurons located in the PRW region of the SOG in the brain (panels of Brain and SOG in Fig. 5A)". This is again misleading. They are not actually measuring synapses here, but instead looking at area of overlap between neuronal processes of Crz and SIFaR cells.*

        Answer: We sincerely appreciate the reviewer's critical feedback regarding our initial data interpretation. We acknowledge the important distinction that overlapping membrane markers do not provide a direct measure of synapse formation. In line with the reviewer's suggestion, we have revised the relevant sentence to more accurately reflect this understanding, as detailed below.

      "Neurons expressing Crz were observed in close proximity to SIFaR24F06-expressing neurons within the PRW-SOG of the brain (panels of Brain and SOG in Fig. 6A)."

      • * In Figs 3B and S4A, they are claiming that all neuronal processes within a given delineated brain area are synapses. The virtual fly brain and hemibrain resource have a way to actually identify synapses. This should be used in addition to the neuron skeleton. Otherwise, it is misleading to label these as synapses.*

        Answer: We are grateful for the reviewer's insightful comments that highlighted the potential for misleading information in our previous submission. Upon careful reexamination of the virtual fly brain model, we have made the necessary corrections and updated the figures in our revised manuscript (Figure 3B and S4B). This reanalysis has allowed us to further substantiate our findings, confirming that SIFa neurons indeed establish dense synaptic connections with multiple regions of the central brain.

      • * Furthermore, measuring the area of GRASP signal is not the same as quantifying synapses. We don't know if synapse number changes (eg in lines 240-242).*

      • Answer: We sincerely appreciate the reviewer's valuable suggestion regarding our quantification methods for assessing synaptic changes using GRASP signals. We acknowledge the reviewer's accurate observation that GRASP signals alone cannot provide an exact quantification of synapse number changes. In response to this feedback, we have employed the 'Particle analysis' function of ImageJ to infer the number of synapses from GRASP signals, clearly labeling them as 'number of particles' (as exemplified in Figures S4G and S4J). Additionally, we have compared the average size of each particle to enable a more precise comparison of synapse number changes (as shown in Figures S4H and S4K). While it is true that GRASP signals should not be directly equated with synapse counts, the quantification of GRASP signal intensity can still provide insights into the underlying synaptic connectivity, as described in the original GRASP paper (Feinberg et al, 2008a). Following this approach, previous studies have used signal intensity quantifications to draw conclusions about changes in synaptic specificity in various mutants. Since our methods for measuring GRASP intensity are consistent with the original techniques, we have updated our Y-axis labeling to reflect 'normalized GFP intensity (Norm. GFP Int.)', as exemplified in Figure 4. This change aims to provide a clearer and more accurate representation of our data.

      Comment 6.* In general, the first part of the manuscript (implicating SIFaR in mating duration) is much stronger than the second part, which attempts to demonstrate that SIFa acts through Crz-expressing neurons to induce its effects. The proof that SIFa acts through Crz-expressing neurons to modify mating duration is tenuous. The most direct evidence of this, achieved via knockdown on Crz in SIFaR-expressing cells, is relegated to supplemental figures. The calcium response of the Crz neurons to SIFa neuron activation (Fig. 6) is more of a lack of a decrease that is observed in controls. Also, this is only done in the VNC. Why not look in the brain, because the authors previously stated a hypothesis that the "transmission of signals through SIFaR in Crz-expressing neurons is limited to the brain" (lines 381-382)?

      Furthermore, the authors suggest that Crz acts on cells in the heart to regulate mating duration. It would be useful to add a discussion/speculation as to possible mechanisms for heart cells to regulate mating decisions. Is there evidence of CrzR in the heart? The SCope data presented in Fig. 7I-L and S7G-H is hard to read.*

      • Answer: We sincerely appreciate the reviewer's constructive feedback on the section of our manuscript that discusses the role of the SIFa-SIFaR connection in regulating mating duration. We understand that the initial presentation may not have been sufficiently convincing. As we detailed in our previous biorXiv preprint (Wong et al, 2019), we conducted a comprehensive screen of numerous neuropeptides and their receptors that mediate SIFa signals through SIFaR and added those data in Supplementary Table S1 and S2. Among these, Crz was identified as a key neuropeptide in this pathway and is also well-documented for its role in mating duration (Tayler et al, 2012). Our data clearly demonstrate that Crz neurons are responsive to the activity of SIFa neurons, supporting the validity of this connection. Additionally, in another manuscript focusing on the input signals for SIFa (Kim et al*, 2024), we established that CrzR does not function in SIFa neurons, confirming the bidirectional nature of SIFa-to-Crz signaling.

        Inadvertently, we had relegated the Crz knockdown results to supplementary figures, under the assumption that our screening results regarding the relationship between SIFaR and neuropeptides were already well-covered (Wong et al, 2019). In light of the reviewer's comments, we have now relocated the Crz knockdown results, particularly those involving SIFaR-expressing cells, to the main figures (Figure 6F-G). We have also included a more detailed description of our previous screening results within the manuscript, as outlined below, to provide a more comprehensive understanding of our findings.

      "Furthermore, the Crz peptide and Crz-expressing neurons have been characterized as pivotal relay signals in the SIFa-to-SIFaR pathway, which is essential for modulating interval timing behaviors (Wong 2019)."

         We greatly appreciate the reviewer's critical and constructive feedback regarding the detection of SIFa-to-Crz long-distance signaling, particularly their observation that this signaling is detectable from the brain to the VNC but not between brain regions. In response to the reviewer's suggestions, we have made the following adjustments to our manuscript:
      
      1. We have relocated our SIFa-Crz GCaMP data pertaining to the VNC region to the Figures 6L-O) to maintain focus on the primary findings within the main text.
      2. Our deeper analysis has led to the identification of two cells in the Super Intermediate Protocerebrum (SIP) regions that coexpress both Crz and SIFaR24F06, as well as OL cells (Figure 6D-E).
      3. We have included GCaMP data from the brain region in the main figure to provide a comprehensive view of the signaling dynamics (Fig. 6P-R and Fig. S6N-P).
      4. Upon examining the SIFa-to-Crz signaling through GCaMP calcium imaging, we observed that the calcium levels in Crz+/SIFaR+ SIP neurons consistently decreased upon SIFa activation (Figure 6P-R). In contrast, the calcium signals in Crz+/SIFaR+ OL neurons increased upon SIFa activation, similar to the pattern observed in Crz+ AG neurons in the VNC (Figure 6M-O and Figure S6N-P).
      5. We have summarized these findings in Figure 6S and provided a detailed description of the results in the manuscript, as outlined below. "To elucidate the direct response of Crz neurons to the activity of SIFa neurons, we conducted live calcium (Ca2+) imaging in the Super Intermediate Protocererbrum (SIP), OL and AG region of the VNC, where Crz neurons are situated (Fig. 6D, Fig. S6M). Upon optogenetic stimulation of SIFa neurons, we observed a significant increase in the activity of Crz in OL and AG region (Fig. 6L-O, Fig. S6N-P), evidenced by a sustained elevation in intracellular Ca2+ levels that persisted in a high level before gradually declining to baseline levels, where the cells in top region of the SIP exhibit consistently drop down after stimulated the SIFa neurons (Fig. 6P-R). These calcium level changes were in contrast to the control group (without all-trans retinal, ATR) (Fig. 6L-R, Fig. S6N-P). These findings confirm that Crz neurons in OL and AG are activated in response to SIFa neuronal activity, but the activity of Crz neurons in SIP are inhibited by the activition of SIFa neuron, reinforcing their role as postsynaptic effectors in the neural circuitry governed by SIFa neurons. Moreover, these results provide empirical support for the hypothesis that SIFa-SIFaR/Crz-CrzR long-range neuropeptide relay underlies the neuronal activity-based measurement of interval timing."

        We are grateful for the reviewer's opportunity to elaborate on the intriguing findings concerning the expression of CrzR in the heart and its potential link to mating duration. In the context of traditional interval timing models (Meck et al, 2012; Matell, 2014; Buhusi & Meck, 2005), the role of a pacemaker in generating a temporal flow for measuring time is considered essential. The heart, being a well-known pacemaker organ in animals, provides a compelling framework for our discussion. In response to the reviewer's insightful comments, we have expanded upon our hypotheses in the DISCUSSION section, exploring the possible connections between cardiac function and the regulation of mating duration. Our reflections on this topic are detailed as follows:


      "It has been reported that the interaction between the brain and the heart can influence time perception in humans (Khoshnoud et al, 2024). Heart rate is governed by intrinsic mechanisms, such as the muscle pacemaker, as well as extrinsic factors including neural and hormonal inputs (Andersen et al, 2015). Moreover, the pacemaker function is essential for the generation of interval timing capabilities (Meck et al, 2012; Matell, 2014; Buhusi & Meck, 2005), with the heart being recognized as the primary pacemaker organ within the animal body. Consequently, the CrzR in the fly heart may respond to the Crz signal sent by SIFaR+/Crz+ cells and modulate the heart rate, thereby impacting the perception of time in male flies."

         We appreciate the reviewer's interest in the expression of CrzR in the heart and its potential implications for our study. In response to the reviewer's comments, we have conducted a thorough examination of the fly SCope RNAseq dataset. Our analysis revealed that CrzR is indeed broadly expressed in heart tissue, particularly in areas where the Hand gene is also expressed. This significant finding has been incorporated into our manuscript and is depicted in Figure 8L. As illustrated in Figures 8I-L, which present the SCope tSNE plot for various cell types including neurons, glial cells, muscle systems, and heart, the heart tissue exhibits the most robust expression of CrzR. This observation suggests that the Hand-GAL4 mediated CrzR knockdown experiments may provide insights into the role of CrzR expression in the heart and its influence on the interval timing behavior of male fruit flies. We have expanded upon this interpretation in the relevant sections of our manuscript to ensure a clear and comprehensive understanding of our results.
      
      • *

      Comment 7. In several cases, the effects of being raised single are opposite the effects of sexual experience. For example, in Fig. 4T, calcium activity is increased in the AG following sexual experience, but decreased in flies raised singly. Likewise, Crz-neurons in the OL have increased CaLexA signal in singly-raised flies but reduced signals in flies with previous sexual experience. In some cases, manipulations selectively affect LMD or SMD. It would be useful to discuss these differences and consider the mechanistic implications of these differential changes, when they all result in decreased mating duration. This could help to clarify the big picture of the manuscript.

         __Answer:__ We sincerely appreciate the reviewer's insightful suggestions regarding the potential mechanistic underpinnings of how differential calcium activities may modulate LMD and SMD behaviors. In response to this valuable input, we have expanded our discussion to include a hypothesis on how neuropeptide relays could potentially induce context-dependent modulation of synaptic changes and calcium activities within distinct neuronal subsets. This addition aims to provide a more comprehensive understanding of the complex interactions at play, as detailed in the revised manuscript.
      

      "Employing two distinct yet comparable models of interval timing behavior, LMD and SMD, we demonstrated that differential SIFa to SIFaR signaling is capable of modulating context-dependent behavioral responses. Synaptic strengths between SIFa and SIFaR neurons was notably enhanced in group-reared naive males. However, these synaptic strengths specifically diminished in the OL, CB, and AG when males were singly reared, with a particular decrease in the AG region when males were sexually experienced (Fig. 4A-J). Intriguingly, overall calcium signaling within SIFaR24F06 neurons was significantly reduced in group-reared naive males, yet these signals surged dramatically in the OL with social isolation and in the AG with sexual experience (Fig. 4K-T). These calcium signals, as reported by the transcriptional calcium reporter CaLexA, were corroborated by GCaMP live imaging in both the AG and OL regions (Fig. 6L-O and Fig. S6N-P), indicating a close association between elevated calcium levels and LMD and SMD behaviors. The modulation of context-dependent synaptic plasticity and calcium dynamics by the SIFa neuropeptide through a single SIFaR receptor raises the question of how a single receptor can elicit such diverse responses. Recent neuroscientific studies in Drosophila have shown that individual neurons can produce multiple neurotransmitters and that neuropeptides are often colocalized with small molecule neurotransmitters (Nässel 2018,Deng 2019,Croset 2018,Kondo 2020). Consistent with this, we have previously reported that SIFa neurons utilize a variety of neurotransmitters, including glutamate, dopamine, and tyramine (Kim 2024). Therefore, we propose that the SIFa-SIFaR-Crz-CrzR neuropeptidergic relay circuitry may interact with different neurotransmitters in distinct neuronal subpopulations to regulate context-dependent behaviors. Supporting this hypothesis, glutamate, known to function as an inhibitory neurotransmitter in the olfactory pathway of Drosophila (Liu 2013), may be one such candidate. We speculate that neuropeptide cotransmission could underlie the mechanisms facilitating these complex, context-dependent behavioral patterns. Further research is warranted to elucidate how such cotransmission contributes to the intricate behavioral repertoire of the fly."

      Minor Comments: Comment 8. For CaLexA experiments (eg Fig 7A-D), signal intensity should be quantified in addition to area covered. Increased intensity would indicate greater calcium activity within a particular set of neurons.

      • *Answer: We appreciate the reviewer's insightful comments and acknowledge the importance of using intensity measurements in our analysis of CaLexA signals. We concur that the intensity of these signals is indeed correlated with the area measurements, which is a critical factor to consider. In response to the reviewer's valuable suggestion, we have revised our approach and now present our data based on intensity measurements. These have been incorporated as a primary dataset in all our CaLexA results to provide a more accurate representation of our findings. Additionally, we have updated the labeling of our Y-axis to "Norm. GFP Int.", which stands for "normalized GFP intensity". This change ensures clarity and consistency in the presentation of our data, aligning with the reviewer's recommendations and enhancing the overall quality of our manuscript.

      Comment 9. In Figure 5K: quantification of cell overlap is missing. In the text they state that there are ~100 neurons that co-express SIFaR24F06 and Crz. How was this determined? Is there a graph or numerical summary of this assertion?

          __Answer:__ We sincerely thank the reviewer for pointing out the oversight in our initial submission regarding the quantification data. In response to this valuable feedback, we have now included the quantification of neurons co-expressing SIFaR24F06 and Crz in the optic lobe (OL) within Figure 6E. This addition ensures that the figure is complete and provides the necessary numerical support for our observations.
      

      Comment 10. In lines 709-711: "Our experience suggests that the relative mating duration differences between naïve and experienced condition and singly reared are always consistent; however, both absolute values and the magnitude of the difference in each strain can vary. So, we always include internal controls for each treatment as suggested by previous studies." I had trouble understanding this section of methods. What is done with the data from the internal controls?

         __Answer:__ We appreciate the reviewer's attention to the methodology of our study, particularly regarding the use of internal controls in our mating duration assays. As referenced in our cited work by Bretman et al. (2011) (Bretman *et al*, 2011), our internal control strategy involves a comparison of mating durations between males that have been presented with specific sensory cues and those that have not. This approach includes assessing both males that have been exposed to signals and those that have not, which serves as an internal control for each experimental setup. The purpose of this design is to isolate the effects of our manipulations from other potential confounding factors. In response to the reviewer's comments, we have provided a more detailed description of our mating duration assay in the Methods section. We have also expanded our explanation to clarify how this internal control mechanism ensures that any observed differences in mating duration are attributable to the experimental manipulations and not to extraneous variables. This additional information should provide a clearer understanding of our methodology and the rationale behind our experimental design.
      

      Comment 11. Could the authors comment on why the brain GRASP signal is so different in Figures 3A and 4A? I realize that different versions of GRASP were used in these experiments, but I would expect broad agreement between the different approaches.

         __Answer: __We appreciate the reviewer’s insight. GRASP and t-GRASP are similar technologies that can clearly show the synaptic connection between neurons. GRASP technology was first generated and performed in *C. elegens* (Feinberg *et al*, 2008b). In 2018, the researchers developed a targeted GFP Reconstitution Across Synaptic Partners method, t-GRASP, which resulted in a strong preferential GRASP signal in synaptic regions.
      
         In our study, we utilized both techniques because of the limitations of the chromosomes where GAL4 and lexA lines located. We also found that during data processing, our method could clearly distinguish the changes in GRASP and t-GRASP signals across three different conditions (naïve, single, and exp.). Therefore, we do not have a particular preference for one technique over the other; both methods are applicable to our experiment.
      
         The genotype we used in Figure 3A is *SIFa2A-lexA, GAL424F06; lexAop-nSyb-spGFP1-10, UAS-CD4-spGFP11*, where the synaptic transmission occurs from *SIFa2A-lexA *to* GAL424F06*. In Figure 4A, the genotype we used is *GAL4SIFa.PT, lexASIFaR-2A; lexAop-2-post-t-GRASP, UAS-pre-t-GRASP*, where the synaptic transmission occurs from SIFa. PT to SIFaR-2A.
      
         In our back-to-back submission paper, “Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male *Drosophila melanogaster,*” (Kim *et al*, 2024) we identified that *SIFa2A* can label posterior-ventral SIFa neurons (SIFaVP), which can only project to ellipsoid body and fan-shaped body. Combining the GRASP technique, Figure 3A cannot show a strong signal as in Figure 4A. We’ve shown in Figure 1G that *SIFaR-2A *covers almost the whole CNS in *Drosophila*. Thus, the synaptic transmission from SIFa. PT (label 4 SIFa neurons) to SIFaR-2A shows a strong signal under the use of the t-GRASP technique. In this case, the GRASP signals in Figure 3A and Figure 4A are so different because of the usage of different GRASP techniques and different fly lines. We appreciate the reviewer's attention to the clarity of our presentation. In response to the comments, we have taken the opportunity to meticulously revise the figure legends to ensure that the differences are explicitly highlighted and easily understood by the readers.
      

      __ __


      Reviewer #2

      Major concerns: Comment 1.* It is highly interesting that the duration of mating behavior is dependent on external and motivational factors. In fact, that provides an elegant way to study which neuronal mechanisms orchestrate these factors. However, it remains elusive why the authors link the differentially motivated durations of mating behavior to the psychological concept of interval timing. This distracts from the actually interesting neurobiology, and is not necessary to make the study interesting. *

      * * Answer: We are grateful for the opportunity provided by the reviewer to elaborate on our rationale for utilizing the mating duration of male fruit flies as an exemplary genetic model for studying interval timing. At the outset, we would like to acknowledge that mating duration has gained recognition as a valuable genetic model for interval timing, as evidenced by the NIH-NIGMS R01 grant awarded to Michael Crickmore. This grant, which can be reviewed at the provided link (https://grantome.com/grant/NIH/R01-GM134222-01), underscores the significance of this model. Crickmore and colleagues have described in the grant's abstract that "mating duration in Drosophila offers a powerful system for exploring changes in motivation over time as behavioral goals are achieved," and it has the potential to provide "the first mechanistic description of a neuronal interval timing system."

         In light of this, we have incorporated our rationale into the INTRODUCTION section of our manuscript, as detailed below. We believe that our argumentation, supported by the grant's emphasis on the topic, will not only address the reviewer's concerns but also demonstrate to the broader scientific community the significance of the fruit fly's mating duration as a model for interval timing. This concept has been a cornerstone in the historical development of neuroscientific understanding of time perception. We hope that our expanded discussion will effectively convey the potential of the fruit fly mating duration as a genetic model to offer profound insights into the neural mechanisms underlying interval timing, a concept of enduring importance in the field of neuroscience.
      

      "The dimension of time is the fundamental basis for an animal's survival. Being able to estimate and control the time between events is crucial for all everyday activities (RICHELLE & LEJEUNE, 1980). The perception of time in the seconds-to-hours range, referred to as ‘interval timing’, is involved in foraging, decision making, and learning via activation of cortico-striatal circuits in mammals (Golombek et al, 2014). Interval timing requires entirely different neural mechanisms from millisecond or circadian timing (Meck et al, 2012; Merchant et al, 2012; Buhusi & Meck, 2005). There is abundant psychological research on time perception because it is a universal cognitive dimension of experience and behavioral plasticity. Despite decades of research, the genetic and neural substrates of temporal information processing have not been well established except for the molecular bases of circadian timing (Buhusi et al, 2009; Tucci et al, 2014). Thus, a simple genetic model system to study interval timing is required. Considering that the mating duration in fruit flies, which averages approximately 20 minutes, is well within the range addressed by interval timing mechanisms, this behavioral parameter provides a relevant context for examining the neural circuits that modulate the Drosophila's perception of time intervals. Such an investigation necessitates an understanding of the extensive neural and behavioral plasticity underlying interval timing (Thornquist et al, 2020; Gautham et al, 2024; Crickmore & Vosshall, 2013)."

      Comment 2.* In figure 4 A and 4K, fluorescence microscopy images of brains and ventral nerve chords are shown, one illustrating GRASP experiments, and one showing CaLexA experiments. The extreme difference between the differentially treated flies (bright fluorescence versus almost no fluorescence) is - in its drastic form- surprising. Online access to the original confocal microscopy images (raw data) might help to convince the reader that these illustrations do not reflect the most drastic "representative" examples out of a series of brain stainings. *

      * * Answer: We sincerely appreciate the reviewer's thoughtful suggestion to enhance the accessibility of our microscopy images for readers who may be interested. In response to this valuable feedback, we have compiled all of our quantified image files into zip format and included them as Supplementary Information 2 and 3. We believe that this additional material will be beneficial for readers seeking a more in-depth view of our data.

      Comment 3. In particular for behavioral experiments, genetic controls should always be conducted. That is, both the heterozygous Gal4-line as well as the heterozygous UAS-line should be used as controls. This is laborious, but important.

         __Answer:__ We sincerely appreciate the reviewer's critical feedback regarding the genetic controls in our study. We acknowledge the importance of this aspect and wish to clarify that we have indeed conducted a substantial number of genetic control experiments for both LMD and SMD behaviors. It is worth noting that much of this data has been previously published in other works. Recognizing the interest from another reviewer on the same topic, we have chosen to reiterate our response here for clarity and convenience. Our comprehensive approach to genetic controls ensures the robustness of our findings, and we believe that the published data further substantiates the reliability of our experimental procedures.
      
         We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. However, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.
      

      "Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information. 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

      We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

      "__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

      Minor comments: Comment 4.* Line 75: word missing ("...including FEEDING-RELATED BEHAVIOR, courtship, ..."). *

         __Answer:__ We appreciate your vigilance in identifying this error. We have made the necessary correction to ensure the accuracy of our manuscript.*
      

      *

      Comment 5.* Line 120: word missing ("SIFaR expression in adult neurons BUT not glia..."). *

         __Answer:__ We appreciate your careful review and attention to detail. Thank you for bringing this to our notice. We have made the necessary corrections to address the error.*
      

      *

      Comment 6.* I find the figures often to be quite overloaded, and anatomical details often very small (e.g., figure 7A). *

      * * Answer: We appreciate the constructive critique on the layout of our data presentation. Following your insightful recommendation, we have revised the manuscript to enhance clarity. Specifically, we have resized the diagram to be more compact and have also increased the spacing between the panels for better readability.


      __ __


      Reviewer #3

      Major Comments Comment 1.* Are the key conclusions convincing? The key conclusions are intriguing but require more robust data to be fully convincing. While the study presents compelling evidence for the involvement of SIFa and SIFaR in mating behaviors, additional experiments are needed to firmly establish the proposed mechanisms. *

      * * Answer: We are deeply grateful for the insightful and constructive feedback provided by the reviewer on the SIFa-to-SIFaR signaling pathway. We are particularly encouraged by the reviewer's agreement with our findings that support the role of SIFa and SIFaR in regulating mating duration. We concur with the reviewer's suggestion that additional experiments and mechanistic insights are essential to substantiate our conclusions. To this end, we have conducted and included several new experiments, particularly GCaMP data, in the main figures (Figure 6 and S6). Our focus has been intensified on the SIFa-to-Crz signaling, given Crz's established role in controlling mating duration behavior. Below is a summary of the additional experiments we have incorporated:

      1. We have repositioned the SIFa-Crz GCaMP data related to the VNC to Figures 6L-O to ensure that the main text highlights our primary findings.
      2. Our more detailed analysis has identified two cells in the Super Intermediate Protocerebrum (SIP) regions that co-express Crz and SIFaR24F06, along with OL cells (Figure 6D-E).
      3. To provide a complete view of the signaling dynamics, we have included GCaMP data from the brain region in the main figure (Figure 6P-R and Supplementary Figure S6N-P).
      4. Through GCaMP calcium imaging to assess SIFa-to-Crz signaling, we found that calcium levels in Crz+/SIFaR+ SIP neurons consistently decreased with SIFa activation (Figure 6P-R). Conversely, calcium signals in Crz+/SIFaR+ OL neurons increased with SIFa activation, mirroring the pattern seen in Crz+ AG neurons in the VNC (Figure 6M-O and Supplementary Figure S6N-P).
      5. A synthesis of these results is presented in Figure 6S, and we have elaborated on these findings in the manuscript with a detailed description, as detailed below. "To elucidate the direct response of Crz neurons to the activity of SIFa neurons, we conducted live calcium (Ca2+) imaging in the Super Intermediate Protocererbrum (SIP), OL and AG region of the VNC, where Crz neurons are situated (Fig. 6D, Fig. S6M). Upon optogenetic stimulation of SIFa neurons, we observed a significant increase in the activity of Crz in OL and AG region (Fig. 6L-O, Fig. S6N-P), evidenced by a sustained elevation in intracellular Ca2+ levels that persisted in a high level before gradually declining to baseline levels, where the cells in top region of the SIP exhibit consistently drop down after stimulated the SIFa neurons (Fig. 6P-R). These calcium level changes were in contrast to the control group (without all-trans retinal, ATR) (Fig. 6L-R, Fig. S6N-P). These findings confirm that Crz neurons in OL and AG are activated in response to SIFa neuronal activity, but the activity of Crz neurons in SIP are inhibited by the activition of SIFa neuron, reinforcing their role as postsynaptic effectors in the neural circuitry governed by SIFa neurons. Moreover, these results provide empirical support for the hypothesis that SIFa-SIFaR/Crz-CrzR long-range neuropeptide relay underlies the neuronal activity-based measurement of interval timing."

        We are truly grateful for the reviewer's perceptive recommendations concerning the possible mechanisms of LMD and SMD behaviors. In light of this constructive feedback, we have enhanced our discussion to encompass a theoretical framework on the potential role of neuropeptide relays in mediating context-dependent adjustments of synaptic plasticity and calcium signaling within specific neuronal populations. This supplementary perspective is designed to elucidate the intricate dynamics involved, as further elaborated in the updated manuscript.

      "Employing two distinct yet comparable models of interval timing behavior, LMD and SMD, we demonstrated that differential SIFa to SIFaR signaling is capable of modulating context-dependent behavioral responses. Synaptic strengths between SIFa and SIFaR neurons was notably enhanced in group-reared naive males. However, these synaptic strengths specifically diminished in the OL, CB, and AG when males were singly reared, with a particular decrease in the AG region when males were sexually experienced (Fig. 4A-J). Intriguingly, overall calcium signaling within SIFaR24F06 neurons was significantly reduced in group-reared naive males, yet these signals surged dramatically in the OL with social isolation and in the AG with sexual experience (Fig. 4K-T). These calcium signals, as reported by the transcriptional calcium reporter CaLexA, were corroborated by GCaMP live imaging in both the AG and OL regions (Fig. 6L-O and Fig. S6N-P), indicating a close association between elevated calcium levels and LMD and SMD behaviors. The modulation of context-dependent synaptic plasticity and calcium dynamics by the SIFa neuropeptide through a single SIFaR receptor raises the question of how a single receptor can elicit such diverse responses. Recent neuroscientific studies in Drosophila have shown that individual neurons can produce multiple neurotransmitters and that neuropeptides are often colocalized with small molecule neurotransmitters (Nässel 2018,Deng 2019,Croset 2018,Kondo 2020). Consistent with this, we have previously reported that SIFa neurons utilize a variety of neurotransmitters, including glutamate, dopamine, and tyramine (Kim 2024). Therefore, we propose that the SIFa-SIFaR-Crz-CrzR neuropeptidergic relay circuitry may interact with different neurotransmitters in distinct neuronal subpopulations to regulate context-dependent behaviors. Supporting this hypothesis, glutamate, known to function as an inhibitory neurotransmitter in the olfactory pathway of Drosophila (Liu 2013), may be one such candidate. We speculate that neuropeptide cotransmission could underlie the mechanisms facilitating these complex, context-dependent behavioral patterns. Further research is warranted to elucidate how such cotransmission contributes to the intricate behavioral repertoire of the fly."

      • *

      Comment 2. Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? The authors should qualify certain claims as preliminary or speculative. Specifically, the proposed SIFa-SIFaR/Crz-CrzR neuropeptide relay pathway is only investigated via imaging approach. More experiments using behavioral tests are needed to confirm that Crz relays the SIFa signaling pathway. For example, Crz-Gal4>UAS-SIFaR RNAi should be done to show that SIFaR+ Crz+ cells are necessary for LMD and SMD.

         __Answer:__ We are grateful for the reviewer's constructive suggestion regarding the need to provide additional behavioral assays using RNAi knockdown to substantiate the SIFa-SIFaR/Crz-CrzR neuropeptide relay. Following the reviewer's advice, we have conducted experiments involving SIFaR24F06/Crz-RNAi and Crz-GAL4/SIFaR-RNAi. The outcomes of these experiments have been detailed and are now presented in a clear and comprehensive manner.
      
         To further aid in the understanding of our results, we have also included a summary diagram in Figure 6S, which illustrates the key findings from these assays. This visual representation is intended to provide a concise overview of the data and to highlight the significance of the SIFa-SIFaR/Crz-CrzR neuropeptide relay in the context of our study.
      

      Comment 3.* Would additional experiments be essential to support the claims of the paper? Yes, additional experiments are essential. Detailed molecular and imaging studies are needed to support claims about synaptic reorganization. For example: ○ More controls are needed for RNAi and Gal80ts experiments, such as Gal4-only control, RNAi-only control, etc. *

         __Answer:__ We sincerely appreciate the reviewer's critical feedback regarding the genetic controls in our study. We acknowledge the importance of this aspect and wish to clarify that we have indeed conducted a substantial number of genetic control experiments for both LMD and SMD behaviors. It is worth noting that much of this data has been previously published in other works. Recognizing the interest from another reviewer on the same topic, we have chosen to reiterate our response here for clarity and convenience. Our comprehensive approach to genetic controls ensures the robustness of our findings, and we believe that the published data further substantiates the reliability of our experimental procedures.
      
         We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. However, in accordance with the reviewer's recommendation, we conducted genetic validation experiments on novel genetic crosses, including SIFaR-RNAi/+, CrzR-RNAi/+, and GAL4NP5270/+, and incorporated the results in the supplementary figures (Supplementary information 1). We have made the necessary modifications and additions to the manuscript as below.
      

      "Given those genetic controls, as evidenced by consistent exhibition of normal LMD and SMD behaviors (Supplemental information 1), the observed reduction in SIFaR expression, driven by elavc155, is deemed sufficient to induce significant disruptions in LMD and SMD behaviors."

      We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

      "__Mating Duration Assays for Successful Copulation__The mating duration assay in this study has been reported (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023). To enhance the efficiency of the mating duration assay, we utilized the Df(1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR) (Parks et al. 2004; Yapici et al. 2008). Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males (Yapici et al. 2008). We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For group reared (naïve) males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female into the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors (Kim et al. 2012; Kim et al. 2013; Lee et al. 2023; Huang et al. 2024; Zhang et al. 2024). Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test."

      *○ Using synaptic markers and high-resolution imaging to observe synaptic changes directly. *

         __Answer:__ We sincerely appreciate the reviewer's constructive suggestion to provide high-resolution imaging for a more direct observation of synaptic changes. While we have already included high-resolution imaging data showcasing postsynaptic and presynaptic alterations using Denmark and syt.eGFP (Figure S3), GRASP (Figure 3A-D), and tGRASP (Figure 4A-J), we recognize the value of further elucidation. Consequently, we have conducted additional experiments to examine the presynaptic changes in SIFaR24F06 neurons under varying social contexts, as presented in Figure 5A-G. We are confident that the comprehensive dataset we have now provided, which includes these new findings, will not only address the reviewer's concerns but also effectively convey to the readers the dynamic and critical nature of SIFa-SIFaR synaptic changes in modulating interval timing behaviors.
      

      *○ Electrophysiological recordings from neurons expressing SIFa and SIFaR to analyze their functional connectivity and activity patterns. *

         __Answer:__ We sincerely appreciate the reviewer's constructive suggestions regarding the inclusion of electrophysiological recordings from neurons expressing SIFa and SIFaR to analyze functional connectivity and activity patterns. In response to this valuable feedback, we have conducted *in vivo* calcium imaging using the GCaMP indicator. The results have been incorporated into our manuscript, demonstrating SIFa-SIFaR connectivity and alterations in activity patterns (Figure 5H-L), as well as SIFa-Crz connectivity and changes in activity patterns (Figure 6 and Figure S6). We are confident that these additional data provide compelling evidence supporting the notion that the SIFa-SIFaR/Crz-CrzR neuropeptide relay circuits are robustly interconnected and exhibit activity changes in concert with the observed neuronal modifications.
      
      • *

      Comment 4.* Are the suggested experiments realistic in terms of time and resources? The suggested experiments are realistic but will require considerable time and resources. Detailed molecular interaction studies, imaging synaptic plasticity, and electrophysiological recordings could take several months to over a year, depending on the complexity and availability of necessary equipment and expertise. The cost would be moderate to high, involving expenses for reagents, imaging equipment, and animal husbandry for maintaining Drosophila stocks. *

      * * Answer: We are grateful for the reviewers' understanding and support for our additional analysis in the revision experiments. While we have already conducted a multitude of experiments pertinent to this manuscript, we are well-positioned to provide a comprehensive revision of the data within a relatively short timeframe.

      Comment 5. Are the data and the methods presented in such a way that they can be reproduced? The methods are generally described in detail, allowing for potential reproducibility. However, more precise documentation of certain experimental conditions, such as the timing and conditions of RNAi induction and temperature controls, is necessary. The methods about imaging analysis are too detailed. The exact steps about how to use ImageJ should be removed.

      * * Answer: We sincerely appreciate the reviewer's meticulous comments regarding the omission of certain methodological details in our manuscript. In response, we have now included a detailed description of the temperature control procedures for conditional RNAi induction in the "Fly Stocks and Husbandry" section, as detailed below.

      "For temperature-controlled experiments, including those utilizing the temperature-sensitive tub-GAL80ts driver, the flies were initially crossed and maintained at a constant temperature of 22℃ within an incubator. The temperature shift was initiated post-eclosion. Once the flies had emerged, they were transferred to an incubator set at an elevated temperature of 29℃ for a defined period, after which the experimental protocols were carried out. Wild-type flies were Canton-S (CS)."

         We appreciate the reviewer's guidance on refining our manuscript. In response to the suggestion, we have streamlined the image analysis methods section, removing excessive details to present the information in a more concise and clear manner as below.
      

      "Quantitative analysis of fluorescence intensity

      To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. The GFP signal in the brains and VNCs was amplified through immunostaining with chicken anti-GFP primary antibody. Image analysis was conducted using ImageJ software. For the quantification of fluorescence intensities, an investigator, blinded to the fly's genotype, thresholded the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods (Feinberg 2008). The total fluorescent area or region of interest (ROI) was then quantified using ImageJ, as previously reported. For CaLexA signal quantification, we adhered to protocols detailed by Kayser et al. (Kayser et al, 2014), which involve measuring the ROI's GFP-labeled area by summing pixel values across the image stack. This method assumes that changes in the GFP-labeled area are indicative of alterations in the CaLexA signal, reflecting synaptic activity. ROI intensities were background-corrected by measuring and subtracting the fluorescent intensity from a non-specific adjacent area, as per Kayser et al. (Kayser et al, 2014). For the analysis of GRASP or tGRASP signals, a sub-stack encompassing all synaptic puncta was thresholded by a genotype-blinded investigator to achieve the optimal signal-to-noise ratio. The fluorescence area or ROI for each region was quantified using ImageJ, employing a similar approach to that used for CaLexA quantification (Feinberg 2008)."

      Comment 6. Are the experiments adequately replicated and statistical analysis adequate? Most figures in the manuscript need to be re-plotted. The right y-axis "Difference between means" is not necessary, if not confusing. The image panels are too small to see, while the quantification of overlapping cells are unnecessarily large. The figures are too crowded with labels and texts, which makes it extremely difficult to comprehend the data.

         __Answer:__ We appreciate the reviewer's suggestion to refine our figures, and we have indeed reformatted them to provide clearer presentation and improved readability. Regarding the removal of dot blot membranes (DBMs), we have given this considerable thought. While we understand the recommendation, we have chosen to retain the DBMs in our manuscript. Our decision is based on the fact that our analysis encompasses not only traditional t-tests but also incorporates estimation statistics, which have been demonstrated to be effective for biological data analysis (Claridge-Chang & Assam, 2016). The inclusion of DBMs is essential for the accurate interpretation of these estimation statistics, ensuring a comprehensive representation of our findings.
      

      Minor Comments Comment 7. Specific experimental issues that are easily addressable. Clarify the timing of RNAi induction and provide more detailed figure legends for better understanding and reproducibility.

         __Answer:__ We sincerely appreciate the reviewer's suggestion aimed at enhancing our manuscript. As previously addressed in our response to __*Comment 5*__, we have incorporated additional details regarding the timing of RNAi induction within the Methods section. Furthermore, we have expanded upon the figure legends to provide a clearer understanding of our findings, ensuring that the content is accessible to a broader readership.
      

      * Comment 8. Are prior studies referenced appropriately? Yes. *

      __ Answer:__ We are grateful for the reviewer's acknowledgment that our references have been appropriately included and integrated into the manuscript.

      * Comment 9. Are the text and figures clear and accurate? The text is generally clear, but the figures need re-work. See comment above. *

      • *Answer: We appreciate the feedback from the reviewers regarding the clarity of our figures. In response to other reviewers' concerns about the figures appearing too crowded, we have carefully revised the layout of all figures to ensure they are more spacious and aesthetically improved for better readability and visual appeal.

      * Comment 10. Suggestions to improve the presentation of data and conclusions. Use smaller fonts in the bar plots and make the plots smaller. Enlarge the imaging panels and let the pictures tell the story. *

      * * Answer: We sincerely appreciate the reviewer's constructive suggestion. In response, we have revised the figures by enlarging the images and adjusting the font sizes in the bar plots to enhance readability and clarity.

      REFERENCES

      Andersen JL, MacMillan HA & Overgaard J (2015) Temperate Drosophila preserve cardiac function at low temperature. J Insect Physiol 77: 26–32

      Bretman A, Westmancoat JD, Gage MJG & Chapman T (2011) Males Use Multiple, Redundant Cues to Detect Mating Rivals. Curr Biol 21: 617–622

      Buhusi CV, Aziz D, Winslow D, Carter RE, Swearingen JE & Buhusi MC (2009) Interval Timing Accuracy and Scalar Timing in C57BL/6 Mice. Behav Neurosci 123: 1102–1113

      Buhusi CV & Meck WH (2005) What makes us tick? Functional and neural mechanisms of interval timing. Nat Rev Neurosci 6: 755–765

      Claridge-Chang A & Assam PN (2016) Estimation statistics should replace significance testing. Nat Methods 13: 108–109

      Crickmore MA & Vosshall LB (2013) Opposing Dopaminergic and GABAergic Neurons Control the Duration and Persistence of Copulation in Drosophila. Cell 155: 881–893

      Feinberg EH, VanHoven MK, Bendesky A, Wang G, Fetter RD, Shen K & Bargmann CI (2008a) GFP Reconstitution Across Synaptic Partners (GRASP) Defines Cell Contacts and Synapses in Living Nervous Systems. Neuron 57: 353–363

      Feinberg EH, VanHoven MK, Bendesky A, Wang G, Fetter RD, Shen K & Bargmann CI (2008b) GFP Reconstitution Across Synaptic Partners (GRASP) Defines Cell Contacts and Synapses in Living Nervous Systems. Neuron 57: 353–363

      Gautham AK, Miner LE, Franco MN, Thornquist SC & Crickmore MA (2024) Molecular control of temporal integration matches decision-making to motivational state. bioRxiv: 2024.03.01.582988

      Golombek DA, Bussi IL & Agostino PV (2014) Minutes, days and years: molecular interactions among different scales of biological timing. Philosophical Transactions Royal Soc B Biological Sci 369: 20120465

      Khoshnoud S, Leitritz D, Bozdağ MÇ, Igarzábal FA, Noreika V & Wittmann M (2024) When the heart meets the mind: Exploring the brain-heart interaction during time perception. J Neurosci: e2039232024

      Kim WJ, Jan LY & Jan YN (2012) Contribution of visual and circadian neural circuits to memory for prolonged mating induced by rivals. Nat Neurosci 15: 876–883

      Kim WJ, Jan LY & Jan YN (2013) A PDF/NPF Neuropeptide Signaling Circuitry of Male Drosophila melanogaster Controls Rival-Induced Prolonged Mating. Neuron 80: 1190–1205

      Kim WJ, Song Y, Zhang T, Zhang X, Ryu TH, Wong KC, Wu Z, Wei Y, Schweizer J, Nguyen K-NH, et al (2024) Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male Drosophila melanogaster. bioRxiv: 2024.06.04.597277

      Lee SG, Sun D, Miao H, Wu Z, Kang C, Saad B, Nguyen K-NH, Guerra-Phalen A, Bui D, Abbas A-H, et al (2023) Taste and pheromonal inputs govern the regulation of time investment for mating by sexual experience in male Drosophila melanogaster. PLOS Genet 19: e1010753

      Matell MS (2014) Neurobiology of Interval Timing. Adv Exp Med Biol: 209–234

      Meck WH, Doyère V & Gruart A (2012) Interval Timing and Time-Based Decision Making. Frontiers Integr Neurosci 6: 13

      Merchant H, Harrington DL & Meck WH (2012) Neural Basis of the Perception and Estimation of Time. Annu Rev Neurosci 36: 313–336

      Nicolaï LJJ, Ramaekers A, Raemaekers T, Drozdzecki A, Mauss AS, Yan J, Landgraf M, Annaert W & Hassan BA (2010) Genetically encoded dendritic marker sheds light on neuronal connectivity in Drosophila. Proc National Acad Sci 107: 20553–20558

      RICHELLE M & LEJEUNE H (1980) Time in Animal Behaviour. Part III: Mech: 188–199

      Tayler TD, Pacheco DA, Hergarden AC, Murthy M & Anderson DJ (2012) A neuropeptide circuit that coordinates sperm transfer and copulation duration in Drosophila. Proc National Acad Sci 109: 20697–20702

      Thornquist SC, Langer K, Zhang SX, Rogulja D & Crickmore MA (2020) CaMKII Measures the Passage of Time to Coordinate Behavior and Motivational State. Neuron 105: 334-345.e9

      Tucci V, Buhusi CV, Gallistel R & Meck WH (2014) Towards an integrated understanding of the biology of timing. Philosophical Transactions Royal Soc B Biological Sci 369: 20120470

      Wong K, Schweizer J, Nguyen K-NH, Atieh S & Kim WJ (2019) Neuropeptide relay between SIFa signaling controls the experience-dependent mating duration of male Drosophila. Biorxiv: 819045

    1. Reviewer #1 (Public review):

      This paper examines the role of MLCK (myosin light chain kinase) and MLCP (myosin light chain phosphatase) in axon regeneration. Using loss-of-function approaches based on small molecule inhibitors and siRNA knockdown, the authors explore axon regeneration in cell culture and in animal models. Their evidence shows that MLCK activity facilitates axon extension/regeneration, while MLCP prevents it.

      Major concern:

      A global inconsistency in the conclusions of the authors is evident when trying to understand the role of NMII in axon growth and to understand the present results in light of previous reports by the authors and many others on the role of NMII in axon extension. The discussion of the matter fails to acknowledge a vast literature on how NMII activity is regulated. The authors study enzymes responsible for the phosphorylation and dephosphorylation of NMII, referring to something that is strongly proven elsewhere, that phosphorylation activates NMII and dephosphorylation deactivates it. The authors mention their own previous evidence using inhibitors of NMII ATPase activity (blebbistatin, Bleb for short) and inhibitors of a kinase that phosphorylates NMII (ROCK), highlighting that Bleb increases axon growth. Since Bleb inhibits the ATPase activity of NMII, it follows that NMII is in itself an inhibitor of axon growth, and hence when NMII is inhibited, the inhibition on axon growth is relieved, and axonal growth takes place (REF1). It is known that NMII exists in an inactive folded state, and ser19 phosphorylation (by MLCK or ROCK) extends the protein, allowing NMII filament formation, ATPase activity, and force generation on actin filaments (REF2). From this, it is derived that if MLCK is inhibited, then there is no NMII phosphorylation, and hence no NMII activity, and, according to their previous work, this should promote axon growth. On the contrary, the authors show the opposite effect: in the lack of phospho-MLC, authors show axon growth inhibition.

      Reporting evidence challenging previous conclusions is common business in scientific endeavors, but the problem with the current manuscript is that it fails to point to and appropriately discuss this contradiction. Instead, the authors refer to the fact that MLCK and Bleb inhibit NMII in different steps of the activation process. While this is true, this explanation does not solve the contradiction. There are many options to accommodate the information, but it is not the purpose of this revision to provide them. Since the manuscript is focused solely on phosphorylation states of MLC and axon extension, the claims are simply at odds with the current literature, and this important finding, if true, is not properly discussed.

      What follows is a discussion of the merits and limitations of different claims of the manuscript in light of the evidence presented.

      (1) Using western blot and immunohistochemical analyses, authors first show that MLCK expression is increased in DRG sensory neurons following peripheral axotomy, concomitant to an increase in MLC phosphorylation, suggesting a causal effect (Figure 1). The authors claim that it is common that axon growth-promoting genes are upregulated. It would have been interesting at this point to study in this scenario the regulation of MLCP, which is a main subject in this work, and expect its downregulation.

      (2) Using DRG cultures and sciatic nerve crush in the context of MLCK inhibition and down-regulation, authors conclude that MLCK activity is required for mammalian peripheral axon regeneration both in vitro and in vivo (Figure 2).

      The in vitro evidence is of standard methods and convincing. However, here, as well as in all other experiments using siRNAs, it is not clear what the control is about (the identity of the plasmids and sequences, if any).

      Related to this, it is not helpful to show the same exact picture as a control example in Figures 2 and 3 (panels J and E, respectively). Either because they should not have received the same control treatment, or simply because it raises concern that there are no other control examples worth showing. In these images, it is not also clear where and how the crush site is determined in the GFP channel. This is of major importance since the axonal length is measured from the presumed crush site. Apart from providing further details in the text, the authors should include convincing images.

      (3) The authors then examined the role of the phosphatase MLCP in axon growth during regeneration. The authors first use a known MLCP blocker, phorbol 12,13-dibutyrate (PDBu), to show that is able to increase the levels of p-MLC, with a concomitant increase in the extent of axon regrowth of DRG neurons, both in permissive as well as non-permissive. The authors repeat the experiments using the knockdown of MYPT1, a key component of the MLC-phosphatase, and again can observe a growth-promoting effect (Figure 3).

      The authors further show evidence for the growth-enhancing effect in vivo, in nerve crush experiments. The evidence in vivo deserves more evidence and experimental details (see comment 2). Some key weaknesses of the data were mentioned previously (unclear RNAi controls and duplication of shown images), but in this case, it is also not clear if there is a change only in the extent of growth, or also in the number of axons that are able to regenerate.

      (4) In the next set of experiments (presented in Figure 4) authors extend the previous observations in primary cultures from the CNS. For that, they use cortical and hippocampal cultures, and pharmacological and genetic loss-of-function using the above-mentioned strategies. The expected results were obtained in both CNS neurons: inhibition or knockdown of the kinase decreases axon growth, whereas inhibition or knockdown of the phosphatase increases growth. A main weakness in this set is that it is not indicated when (at what day in vitro, DIV) the treatments are performed. This is important to correctly interpret the results, since in the first days in vitro these neurons follow well-characterized stages of development, with characteristic cellular events with relevance to what is being evaluated. Importantly, this would be of value to understand whether the treatments affect axonal specification and/or axonal extension. Although these events are correlated, they imply a different set of molecular events.

      The title of this section is misleading: line 241 "MLCK/MLCP activity regulated axon growth in the embryonic CNS"... the title (and the conclusion) implies that the experiments were performed in situ, looking at axons in the developing brain. The most accurate title and conclusion should mention that the evidence was collected in CNS primary cultures derived from embryos.

      (5) Performing nerve crush injury in CNS nerves (optic nerve and spinal cord), and the local application of PBDu, the author shows contrasting results (Figure 5). In the ON nerve, they can see axons extending beyond the lesion site due to PBDu. On the contrary, the authors fail to observe so in the corticospinal tract present in the spinal cord. The authors fail to discuss this matter in detail. Also, they accommodate the interpretation of the evidence in light of a process known as axon retraction, and its prevention by MLCP inhibition. Since the whole paper is on axon extension, and it is known that mechanistically axon retraction is not merely the opposite of axon extension, the claim needs far more evidence.

      In panel 5F and the supplementary data, the authors mention the occurrence of retraction bulbs, but the images are too small to support the claim, and it is not clear how these numbers were normalized to the number of axons labeled in each condition.

      (6) The author combines MLCK and MLCP inhibitors with Bleb, trying to verify if both pairs of inhibitors act on the same target/pathway (Figure 6). The rationale is wrong for at least two reasons.<br /> a- Because both lines of evidence point to contrasting actions of NMII on axon growth, one approach could never "rescue" the other.<br /> b- Because the approaches target different steps on NMII activation, one could never "prevent" or rescue the other. For example, for Bleb to provide a phenotype, it should find any p-MLC, because it is only that form of MLC that is capable of inhibiting its ATPase site. In light of this, it is not surprising that Bleb is unable to exert any action in a situation where there is no p-MLC (ML-7, which by inhibiting the kinase drives the levels of p-MLC to zero, Figure 4A). Hence, the results are not possible to validate in the current general interpretation of the authors. (See 'major concern').

      (7) In Figure 7, the authors argue that the scheme of replating and using ML7 before or after replating is evidence for a local cytoskeletal action of the drug. However, an alternative simpler explanation is that the drug acts acutely on its target, and that, as such, does not "survive" the replating procedure. Hence, the conclusion raised by the evidence shown is not supported.

      (8) In Figure 8, the authors show that the inhibitory treatments on MLCK and MLCP (ML7 and PRBu) alter the morphology of growth cones. However, it is not clear how this is correlated with axon growth. The authors also mention in various parts of the text that a local change in the growth cone is evidence for a local action/activity of the drug or enzyme. However the local change<->local action is not a logical truth. It can well be that MLCK and MLCP activity trigger molecular events that ultimately have an effect elsewhere, and by looking at "elsewhere" one observes of course a local effect, but is not because the direct action of MLCK or MLCP are localized. To prove true localized effects there are numerous efforts that can be made, starting from live imaging, fluorescent sensors, and compartmentalized cultures, just to mention a few.

      References:

      (1) Eun-Mi Hur 1, In Hong Yang, Deok-Ho Kim, Justin Byun, Saijilafu, Wen-Lin Xu, Philip R Nicovich, Raymond Cheong, Andre Levchenko, Nitish Thakor, Feng-Quan Zhou. 2011. Engineering neuronal growth cones to promote axon regeneration over inhibitory molecules. Proc Natl Acad Sci U S A. 2011 Mar 22;108(12):5057-62. doi: 10.1073/pnas.1011258108.

      (2) Garrido-Casado M, Asensio-Juárez G, Talayero VC, Vicente-Manzanares M. 2024. Engines of change: Nonmuscle myosin II in mechanobiology. Curr Opin Cell Biol. 2024 Apr;87:102344. doi: 10.1016/j.ceb.2024.102344.

      (3) Karen A Newell-Litwa 1, Rick Horwitz 2, Marcelo L Lamers. 2015. Non-muscle myosin II in disease: mechanisms and therapeutic opportunities. Dis Model Mech. 2015 Dec;8(12):1495-515. doi: 10.1242/dmm.022103.

    1. It is essential that building works are carefully planned in advance

      It is essential that building works are carefully planned in advance and follow a specific infection control risk assessment policy.

      Talento AF, Fitzgerald M, Redington B, O'Sullivan N, Fenelon L, Rogers TR. Prevention of healthcare-associated invasive aspergillosis during hospital construction/renovation works. J Hosp Infect. 2019 Sep;103(1):1-12.

      Mareković I. What's New in Prevention of Invasive Fungal Diseases during Hospital Construction and Renovation Work: An Overview. J Fungi (Basel). 2023 Jan 23;9(2):151.

    1. Welcome back.

      This demo is going to bring together some really important theory and architecture that you've learned over the past few lessons.

      What we're starting this demo lesson with is this architecture.

      We have our VPC, the Animals for Life VPC in US East 1.

      It uses the 10.16.0.0/16 side range.

      It has 12 subnets created inside it, over three AZs with four tiers, Reserve, DB, Application and Web.

      Now currently all the subnets are private and can't be used for communication with the internet or the AWS public zone.

      In this demo we want to reconfigure the VPC to allow that.

      So the first step is to create an internet gateway and attach it.

      To do that, I'm going to move across to my desktop.

      Now to do this in your environment, you'll need the VPC and subnet configuration as you set it up in the previous demo lesson.

      So that configuration needs to be in place already.

      You need to be logged in as the I am admin user of the management account of the organization and have the Northern Virginia region selected, so US - East - 1.

      So go ahead and move across to the VPC console.

      Now this should already be in the recently visited services because you were using this in the previous demo lesson, but if it's not visible just click in the services drop down, type VPC and then click to move to the VPC console.

      Now if you do still have the configuration as it was at the end of the previous demo lesson, you should be able to click on subnets on the menu on the left and see a list of lots of subnets.

      You'll see the ones for the default VPC without a name.

      And if you have the correct configuration, you should see a collection of 12 subnets, 3 application subnets, 3 database subnets, 3 reserved subnets and then 3 web subnets.

      So all of these should be in place within the Animals for Life VPC in order to do the tasks within this demo lesson.

      So I'm going to assume from this point onwards that you do have all of these subnets created and configured.

      Now what we're going to be doing in this demo lesson is configuring the 3 web subnets, so web A, web B and web C, to be public subnets.

      Being a public subnet means that you can launch resources into the subnet, have them allocated with a public IP version 4 address and have connectivity to and from the public IP version 4 internet.

      And in order to enable that functionality, there are a number of steps that we need to perform and I want you to get the practical experience of implementing these within your own environment.

      Now the first step to making subnets public is that we need an internet gateway attached to this VPC.

      So internet gateways, as I talked about in the previous theory lesson, are highly available gateway objects which can be used to allow public routing to and from the internet.

      So we need to create one.

      So let's click on internet gateways on the menu on the left.

      They'll already be an internet gateway in place for the default VPC.

      Remember when you created the default VPC, all this networking infrastructure is created and configured on your behalf.

      But because we created a custom VPC for animals for life, we need to do this manually.

      So to do that, go ahead and click on create internet gateway.

      We're going to call the internet gateway A4L, so animals for life, VPC 1, which is the VPC we're going to attach it to and then IGW for internet gateway.

      So A4L-VPC1-IGW.

      Now that's the only information that we need to enter, so scroll down and click on create internet gateway.

      Internet gateways are initially not attached to a VPC and we can tell that because it's initially in.

      We need to attach this to the animals for life VPC.

      So click on actions and then attach to VPC inside the available VPCs box.

      Just click and then select A4L-IVAN-VPC1.

      Once selected, go ahead and click on attach internet gateway and that will attach our brand new internet gateway to the animals for life VPC.

      And that means that it's now available within that VPC as a gateway object, which gives the VPC the capability to communicate to and receive communications from the public internet and the AWS public zone.

      Now the next step is that we want to make all the subnets in the web tier public, so the services deployed into these subnets can take advantage of this functionality.

      So we want the web subnets to be able to communicate to and receive communications from the public internet and AWS public services.

      Now there are a number of steps that we need to do to accomplish this.

      We need to create a route table for the public subnets.

      We need to associate this route table with the three public subnets, so web A, web B and web C and then we need to add two routes to this route table.

      One route will be a default route for IP version 4 traffic and the other will be a default route for IP version 6 traffic.

      And both of these routes for their target will be pointing at the internet gateway that you've just created and attached to this VPC.

      Now this will configure the VPC router to forward any data intended for anything not within our VPC to the internet gateway.

      Finally, on each of these web subnets will be configuring the subnet to auto assign a public IP version 4 address and that will complete the process of making them public.

      So let's perform all of these sets of configuration.

      So now that we're back at the AWS console, we need to create a route table.

      So go ahead and click on route tables on the menu on the left and then we're going to create a new route table.

      First we'll select the VPC that this route table will belong to and it's going to be the animals for life.

      If a VPC, so go ahead and select that VPC and then we're going to give this route table a name.

      And I like to keep the naming scheme consistent, so we're going to use A4, L4, animals for life and then a hyphen.

      VPC1 because this is the VPC the route table will belong to and then hyphen RT for route table and then hyphen and then web because this route table is going to be used for the web subnets.

      So go ahead and create this route table and click route tables on the menu on the left.

      If we select the route table that we've just created, so that's the one that's called A4, L hyphen VPC1 hyphen RT hyphen web and then just expand this overview area at the bottom.

      We'll be able to see all the information about this route table.

      Now there are a number of areas of this which are important to understand.

      One is the routes area which lists all the routes on this route table and the other is subnet associations.

      This determines which subnets this route table is.

      So let's go to subnet associations and currently we can see that it's not actually associated with any subnets within this VPC.

      We need to adjust that so go ahead and edit those associations and we're going to associate it with the three web subnets.

      So you need to select web A, web B and web C.

      Now notice how all those are currently associated with the main route table of the VPC.

      Remember a subnet can only be associated with one route table at a time.

      If you don't explicitly associate a route table with a subnet then it's associated with the main route table.

      We're going to change that.

      We're going to explicitly associate this new route table with the web A, web B and web C subnets.

      So go ahead and say that.

      So now this route table has been associated with web A, web B and web C.

      Those subnets are no longer associated with the main route table of the VPC.

      So now we've configured the association as a route to routes.

      And we can see that this route table has two local routes.

      We've got the IP version 4 side of the VPC and the app.

      IP version 6 side of the VPC.

      So these two routes on this route table will mean that web A, web B and web C will know how to direct traffic towards any other IP version 4 or IP version 6 addresses within this VPC.

      Now these local routes can never be adjusted or removed, but what we can do is add additional routes.

      So we're going to add two routes, a default route for IP version 4 and a default route for IP version 6.

      So we'll do that.

      We'll start with IP version 4.

      So we'll edit those routes and then we'll add a route.

      The format for the IP version 4 default route is 0.0.0.0/0.

      And this means any IP addresses.

      Now I've talked elsewhere in the course how there is a priority to routing.

      Within a VPC there's a more specific route always takes priority.

      So this route, the /16 is more specific than this default route.

      So this default route will only affect IP version 4 traffic, which is not matched by this local route.

      So essentially anything which is IP version 4, which is not destined for the VPC, will use this default route.

      Now we need to pick the internet gateway as the target for this route.

      So click in the target box on this row, select internet gateway.

      There should only be one that's highlighted.

      That's the Animals for Life internet gateway you created moments ago.

      So select that and that means that any IP version 4 traffic which is not destined for the VPC side of it. [siren] Range will be sent to the Internet Gateway.

      Now we're going to do the same for IPv6.

      So go ahead and add another route.

      And the format for IPv60 default routes is double colon, forward slash zero.

      And this is the same architecture. [siren] It essentially means this matches all IPv6 addresses, but it's less specific than the IPv6 and version 6 local route on this top row.

      So this will only be used for any IPv6 addresses which are not in the IPv6 VPC side range.

      So go ahead and select Target, go to Internet Gateway, and select the Animals for Life Internet Gateway.

      And once you've done both of those, go ahead and click on Save Changes.

      Now this means that we now have two default routes, an IPv4 default route, and an IPv6 default route.

      So this means that anything which is associated with these route tables will now send any unknown traffic towards the Internet Gateway.

      But what we need to do before this works is we need to ensure that any resources launched into the Web A, Web B, or Web C subnets are allocated with public IPv4 addresses.

      To do that, go ahead and click on Subnets.

      In the list, we need to locate Web A, Web B, and Web C.

      So we'll start with Web A, so select Web A, click on Actions, and then Edit Subnet Settings.

      And this time, we're going to modify this subnet so that it automatically assigns a public IPv4 address.

      So check this box into the Save, and that means that any resources launched into the Web A subnet will be allocated with a public IPv4 address.

      Now we need to follow the same process for the other web subnets, so select the Web B subnet, click on Actions, and then Edit Subnet Settings.

      Enable IPv4, click on Save, and then do that same process for Web C.

      So locate Web C, click on Actions, and then Edit Subnet Settings.

      And then enable public IPv4 addresses and click on Save.

      So that's all the network configuration done.

      We've created an Internet Gateway.

      We've associated the Internet Gateway with the Animals for IPPC.

      We've created a Routetable for the web subnets.

      We've associated this Routetable with the web subnets.

      We've added default routes onto this Routetable, pointing at the Internet Gateway as a default IPv4 and IPv6 route.

      And then we've enabled the allocation of public IPv4 addresses for Web A, Web B, and Web C.

      Okay, so this is the end of Part 1 of this lesson.

      It was getting a little bit on the long side, and so I wanted to add a break.

      It's an opportunity just to take a rest or grab a coffee.

      Part 2 will be continuing immediately from the end of Part 1.

      To go ahead, complete the video, I'm ready, join me in part two.

    1. Author Response

      We thank the reviewers for their positive comments and constructive feedback following their thorough reading of the manuscript. In this provisional reply we will briefly address the reviewer’s comments and suggestions point by point. In the forthcoming revised manuscript, we will more thoroughly address the reviewer’s comments and provide additional supporting data.

      (1) The expression 'randomly clustered networks' needs to be explained in more detail given that in its current form risks to indicate that the network might be randomly organized (i.e., not organized). In particular, a clustered network with future functionality based on its current clustering is not random but rather pre-configured into those clusters. What the authors likely meant to say, while using the said expression in the title and text, is that clustering is not induced by an experience in the environment, which will only be later mapped using those clusters. While this organization might indeed appear as randomly clustered when referenced to a future novel experience, it might be non-random when referenced to the prior (unaccounted) activity of the network. Related to this, network organization based on similar yet distinct experiences (e.g., on parallel linear tracks as in Liu, Sibille, Dragoi, Neuron 2021) could explain/configure, in part, the hippocampal CA1 network organization that would appear otherwise 'randomly clustered' when referenced to a future novel experience.

      As suggested by the reviewer, we will revise the text to clarify that the random clustering is random with respect to any future, novel environment. The cause of clustering could be prior experiences (e.g. Bourjaily M & Miller P, Front. Comput. Neurosci. 5:37, 2011) or developmental programming (e.g. Perin R, Berger TK, & Markram H, Proc. Natl. Acad. Sci. USA 108:5419, 2011).

      (2) The authors should elaborate more on how the said 'randomly clustered networks' generate beyond chance-level preplay. Specifically, why was there preplay stronger than the time-bin shuffle? There are at least two potential explanations:

      (2.1) When the activation of clusters lasts for several decoding time bins, temporal shuffle breaks the continuity of one cluster's activation, thus leading to less sequential decoding results. In that case, the preplay might mainly outperform the shuffle when there are fewer clusters activating in a PBE. For example, activation of two clusters must be sequential (either A to B or B to A), while time bin shuffle could lead to non-sequential activations such as a-b-a-b-a-b where a and b are components of A and B;

      (2.2) There is a preferred connection between clusters based on the size of overlap across clusters. For example, if pair A-B and B-C have stronger overlap than A-C, then cluster sequences A-B-C and C-B-A are more likely to occur than others (such as A-C-B) across brain states. In that case, authors should present the distribution of overlap across clusters, and whether the sequences during run and sleep match the magnitude of overlap. During run simulation in the model, as clusters randomly receive a weak location cue bias, the activation sequence might not exactly match the overlap of clusters due to the external drive. In that case, the strength of location cue bias (4% in the current setup) could change the balance between the internal drive and external drive of the representation. How does that parameter influence the preplay incidence or quality?

      Based on our finding that preplay occurs only in networks that sustain cluster activity over multiple decoding time bins (Figure 5d-e), our understanding of the model’s function is consistent with the reviewers first explanation. We will provide additional analysis in the forthcoming revised manuscript in order to directly test the first explanation and will also test the intriguing possibility that the reviewer’s second suggestion contributes to above-chance preplay.

      (3) The manuscript is focused on presenting that a randomly clustered network can generate preplay and place maps with properties similar to experimental observations. An equally interesting question is how preplay supports spatial coding. If preplay is an intrinsic dynamic feature of this network, then it would be good to study whether this network outperforms other networks (randomly connected or ring lattice) in terms of spatial coding (encoding speed, encoding capacity, tuning stability, tuning quality, etc.)

      We agree that this is an interesting future direction, but we see it as outside the scope of the current work. There are two interesting avenues of future work: 1) Our current model does not include any plasticity mechanisms, but a future model could study the effects of synaptic plasticity during preplay on long-term network dynamics, and 2) Our current model does not include alternative approaches to constructing the recurrent network, but future studies could systematically compare the spatial coding properties of alternative types of recurrent networks.

      (4) The manuscript mentions the small-world connectivity several times, but the concept still appears too abstract and how the small-world index (SWI) contributes to place fields or preplay is not sufficiently discussed.

      For a more general audience in the field of neuroscience, it would be helpful to include example graphs with high and low SWI. For example, you can show a ring lattice graph and indicate that there are long paths between points at opposite sides of the ring; show randomly connected graphs indicating there are no local clustered structures, and show clustered graphs with several hubs establishing long-range connections to reduce pair-wise distance.

      How this SWI contributes to preplay is also not clear. Figure 6 showed preplay is correlated with SWI, but maybe the correlation is caused by both of them being correlated with cluster participation. The balance between cluster overlap and cluster isolation is well discussed. In the Discussion, the authors mention "...Such a balance in cluster overlap produces networks with small-world characteristics (Watts and Strogatz, 1998) as quantified by a small-world index..." (Lines 560-561). I believe the statement is not entirely appropriate, a network similar to ring lattice can still have the balance of cluster isolation and cluster overlap, while it will have small SWI due to a long path across some node pairs. Both cluster structure and long-range connection could contribute to SWI. The authors only discuss the necessity of cluster structure, but why is the long-range connection important should also be discussed. I guess long-range connection could make the network more flexible (clusters are closer to each other) and thus increase the potential repertoire.

      We agree that the manuscript would benefit from a more concrete explanation of the small-world index. We will revise the text and add illustrative figures.

      We note that while our most successful clustered networks are indeed those with small-world characteristics, there are other ways of producing small-world networks which may not show good place fields or preplay. We will test another type of small-world network if time permits.

      Our discussion of “cluster overlap” is specific to our type of small-world network in which there is no pre-determined spatial dimension (unlike the ring network of Watts and Strogatz). Therefore, because clusters map randomly to location once a particular spatial context is imposed, the random overlap between clusters produces long-range connections in that context (and any other context) so one can think of the amount of overlap between clusters as representing the number of long-range connections in a Watts-Strogatz model, except, we wish to iterate, such models involve a spatial topology within the network, which we do not include.

      (5) What drives PBE during sleep? Seems like the main difference between sleep and run states is the magnitude of excitatory and inhibitory inputs controlled by scaling factors. If there are bursts (PBE) in sleep, do you also observe those during run? Does the network automatically generate PBE in a regime of strong excitation and weak inhibition (neural bifurcation)?

      During sleep simulations, the PBEs are spontaneously generated by the recurrent connections in the network. The constant-rate Poisson inputs drive low-rate stochastic spiking in the recurrent network, which then randomly generates population events when there is sufficient internal activity to transiently drive additional spiking within the network.

      During run simulations, the spatially-tuned inputs drive greater activity in a subset of the cells at a given point on the track, which in turn suppress the other excitatory cells through the feedback inhibition.

      (6) Is the concept of 'cluster' similar to 'assemblies', as in Peyrache et al, 2010; Farooq et al, 2019? Does a classic assembly analysis during run reveal cluster structures?

      Yes, we are highly confident that the clusters in our network would correspond to the functional assemblies that have been studied through assembly analysis and will present the relevant data in a revision.

      (7) Can the capacity of the clustered network to express preplay for multiple distinct future experiences be estimated in relation to current network activity, as in Dragoi and Tonegawa, PNAS 2013?

      We agree this is an interesting opportunity to compare the results of our model to what has been previously found experimentally and will test this if time permits.

      Reviewer # 2

      Weaknesses:

      My main critiques of the paper relate to the form of the input to the network.

      First, because the input is the same across trials (i.e. all traversals are the same duration/velocity), there is no ability to distinguish a representation of space from a representation of time elapsed since the beginning of the trial. The authors should test what happens e.g. with traversals in which the animal travels at different speeds, and in which the animal's speed is not constant across the entire track, and then confirm that the resulting tuning curves are a better representation of position or duration.

      We agree that this is an important question, and we plan to run further simulations where we test the effects of varying the simulated speed. We will present results in the resubmission.

      Second, it's unclear how much the results depend on the choice of a one-dimensional environment with ramping input. While this is an elegant idealization that allows the authors to explore the representation and replay properties of their model, it is a strong and highly non-physiological constraint. The authors should verify that their results do not depend on this idealization. Specifically, I would suggest the authors also test the spatial coding properties of their network in 2-dimensional environments, and with different kinds of input that have a range of degrees of spatial tuning and physiological plausibility. A method for systematically producing input with varying degrees of spatial tuning in both 1D and 2D environments has been previously used in (Fang et al 2023, eLife, see Figures 4 and 5), which could be readily adapted for the current study; and behaviorally plausible trajectories in 2D can be produced using the RatInABox package (George et al 2022, bioRxiv), which can also generate e.g. grid cell-like activity that could be used as physiologically plausible input to the network.

      We agree that testing the robustness of our results to different models of feedforward input is important and we plan to do this in our revised manuscript for the linear track and W-track.

      Testing the model in a 2D environment is an interesting future direction, but we see it as outside the scope of the current work. To our knowledge there are no experimental findings of preplay in 2D environments, but this presents an interesting opportunity for future modeling studies.

      Finally, I was left wondering how the cells' spatial tuning relates to their cluster membership, and how the capacity of the network (number of different environments/locations that can be represented) relates to the number of clusters. It seems that if clusters of cells tend to code for nearby locations in the environment (as predicted by the results of Figure 5), then the number of encodable locations would be limited (by the number of clusters). Further, there should be a strong tendency for cells in the same cluster to encode overlapping locations in different environments, which is not seen in experimental data.

      Thank you for making this important point and giving us the opportunity to clarify. We do find that subsets of cells with identical cluster membership have correlated place fields, but as we show in Figure 7b the network place map as a whole shows low remapping correlations across environments, which is consistent with experimental data (Hampson RE et al, Hippocampus 6:281, 1996; Pavlides C, et al, Neurobiol Learn Mem 161:122, 2019). Our model includes a relatively small number of cells and clusters compared to CA3, and with a more realistic number of clusters, the level of correlation across network place maps should reduce even further in our model network. The reason for a low level of correlation is because cluster membership is combinatorial, whereby cells that share membership in one cluster can also belong to separate/distinct other clusters, rendering their activity less correlated than might be anticipated. In our revised manuscript we will address this point more carefully and cite the relevant experimental support.

      Reviewer # 3

      Weaknesses:

      To generate place cell-like activity during a simulated traversal of a linear environment, the authors drive the network with a combination of linearly increasing/decreasing synaptic inputs, mimicking border cell-like inputs. These inputs presumably stem from the entorhinal cortex (though this is not discussed). The authors do not explore how the model would behave when these inputs are replaced by or combined with grid cell inputs which would be more physiologically realistic.

      We chose the linearly varying spatial inputs as the minimal model of providing spatial input to the network so that we could focus on the dynamics of the recurrent connections. We agree our results will be strengthened by testing alternative types of border-like input so will present such additional results in our revised version. However, given that a sub-goal of our model was to show that place fields could arise in locations at which no neurons receive a peak in external input, whereas combining input from multiple grid cells produces peaked place-field like input, adding grid cell input (and the many other types of potential hippocampal input) is beyond the scope of the paper.

      Even though the authors claim that no spatially-tuned information is needed for the model to generate place cells, there is a small location-cue bias added to the cells, depending on the cluster(s) they belong to. Even though this input is relatively weak, it could potentially be driving the sequential activation of clusters and therefore the preplays and place cells. In that case, the claim for non-spatially tuned inputs seems weak. This detail is hidden in the Methods section and not discussed further. How does the model behave without this added bias input?

      First, we apologize for a lack of clarity if we have caused confusion about the type of inputs (linear and cluster-dependent as we had attempted to portray prominently in Figure 1, where it is described in the caption, l. 156-157, and Results, l. 189-190 & l. 497-499, as well as in the Methods, l. 671-683) and if we implied an absence of spatially-tuned information in the network. In the revision we will clarify that for reliable place fields to appear, the network must receive spatial information and that one point of our paper is that the information need not arrive as peaks of external input already resembling place cells or grid cells. We chose linearly ramping boundary inputs as the minimally place-field like stimulus (that still contains spatial information) but in our revision we will include alternatives. We should note that during sleep, when “preplay” occurs, there is no such spatial bias (which is why preplay can equally correlate with place field sequences in any context). In the revision, we will update Figure 1 to show more clearly the cluster-dependent linearly ramping input received by some specific cells with both similar and different place fields.

      Unlike excitation, inhibition is modeled in a very uniform way (uniform connection probability with all E cells, no I-I connections, no border-cell inputs). This goes against a long literature on the precise coordination of multiple inhibitory subnetworks, with different interneuron subtypes playing different roles (e.g. output-suppressing perisomatic inhibition vs input-gating dendritic inhibition). Even though no model is meant to capture every detail of a real neuronal circuit, expanding on the role of inhibition in this clustered architecture would greatly strengthen this work.

      This is an interesting future direction, but we see it as outside the scope of our current work. While inhibitory microcircuits are certainly important physiologically, we focus here on a minimal model that produces the desired place cell activity and preplay, as measured in excitatory cells.

      For the modeling insights to be physiologically plausible, it is important to show that CA3 connectivity (which the model mimics) shares the proposed small-world architecture. The authors discuss the existence of this architecture in various brain regions but not in CA3, which is traditionally thought of and modeled as a random or fully connected recurrent excitatory network. A thorough discussion of CA3 connectivity would strengthen this work.

      We agree this is an important point that is missing, and we will revise the text to specifically address CA3 connectivity (Guzman et al., Science 353 (6304), 1117-1123 2016) and the small-world structure therein due to the presence of “assemblies”.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      1. Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      Reviewer #1 (Evidence, reproducibility, and clarity (Required)): This is an interesting manuscript from the Jagannathan laboratory, which addresses the interaction proteome of two satellite DNA-binding proteins, D1 and Prod. To prevent a bias by different antibody affinities they use GFP-fusion proteins of D1 and Prod as baits and purified them using anti GFP nanobodies. They performed the purifications in three different tissues: embryo, ovary and GSC enriched testes. Across all experiments, they identified 500 proteins with surprisingly little overlap among tissues and between the two different baits. Based on the observed interaction of prod and D1 with members of the canonical piRNA pathway the authors hypothesized that both proteins might influence the expression of transposable elements. However, neither by specific RNAi alleles or mutants that lead to a down regulation of D1 and Prod in the gonadal soma nor in the germline did they find an effect on the repression of transposable elements. They also did not detect an effect of a removal of piRNA pathway proteins on satellite DNA clustering, which is mediated by Prod and D1. However, they do observe a mis-localisation of the piRNA biogenesis complex to an expanded satellite DNA in absence of D1, which presumably is the cause of a mis-regulation of transposable elements in the F2 generation.This is an interesting finding linking satellite DNA and transposable element regulation in the germline. However, I find the title profoundly misleading as the link between satellite DNA organization and transgenerational transposon repression in Drosophila has not been identified by multi-tissue proteomics but by a finding of the Brennecke lab that the piRNA biogenesis complex has a tendency to localise to satellite DNA when the localisation to the piRNA locus is impaired. Nevertheless, the investigation of the D1 and Prod interactome is interesting and might reveal insights into the pathways that drive the formation of centromeres in a tissue specific manner.

      We thank the reviewer for the overall positive comments on our manuscript. As noted above, we have performed a substantial number of revision experiments and improved our text. We believe that our revised manuscript demonstrates a clear link between our proteomics data and the transposon repression. We would like to make three main points,

      1. Our proteomics data identified that D1 and Prod co-purified transposon repression proteins in embryos. To test the functional significance of this association, we have used Drosophila genetics to generate flies lacking embryonic D1. In adult ovaries from these flies, we observe a striking elevation in transposon expression and Chk2-dependent gonadal atrophy. Along with the results from the control genotypes (F1 D1 mutant, F2 D1 het), our data clearly indicate that embryogenesis (and potentially early larval development) are a period when D1 establishes heritable TE silencing that can persist throughout development.
      2. Based on the newly acquired RNA-seq and small RNA seq data, we have edited our title to more accurately reflect our data. Specifically, we have substituted the word 'transgenerational' with 'heritable', meaning that the presence of D1 during early development alone is sufficient to heritably repress TEs at later stages of development.
      3. In addition, our RNA seq and small RNA seq experiments demonstrate that D1 makes a negligible contribution to piRNA biogenesis and TE repression in adults, despite the significant mislocalization of the RDC complex. In this regard, our results are substantially different from the recent Kipferl study from the Brennecke lab (Baumgartner et al. 2022).

        Major comments Unfortunately, the proteomic data sets are not very convincing. Not even the corresponding baits are detected in all assays. I wonder whether the extraction procedure really allows the authors to analyze all functionally relevant interactions of Prod and D1. It would be good to see a western blot or an MS analysis of the soluble nuclear extract they use for purification compared to the insoluble chromatin. It may well be that a large portion of Prod or D1 is lost in this early step. I also find the description of the proteomic results hard to follow as the authors mostly list which proteins the find as interactors of Prod and D1 without stating in which tissue or with what bait they could purify them (i.e. p7: Importantly, our hits included known chromocenter-associated or pericentromeric heterochromatin-associated proteins, such as Su(var)3-9[52], ADD1[23,24], HP5[23,24],mei-S332[53], Mes-4[23], Hmr[24,39,54], Lhr[24,39], and members of the chromosome passenger complex, such as borr and Incenp[55]). It would be interesting to at least discuss tissue specific interactions.

      Out of six total AP-MS experiments in this manuscript (D1 x 3, Prod x 2 and Piwi), we observe a strong enrichment of the bait in 5/6 attempts (log2FC between 4-12). In the initial submission, the lack of a third high-quality biological replicate for the D1 testis sample meant that only the p-value (0.07) was not meeting the cutoff. To address this, we have repeated this experiment with an additional biological replicate (Fig. S2A), and our data now clearly show that D1 is significantly enriched in the testis sample.

      As suggested by the reviewer, we have also assessed our lysis conditions (450mM NaCl and benzonase) and the solubilization of our baits post-lysis. In Fig. S1D, we have blotted equivalent fractions of the soluble supernatant and insoluble pellet from GFP-Piwi embryos and show that both GFP-Piwi and D1 are largely solubilized following lysis. In Fig. S1E, we also show that our IP protocol works efficiently.

      GFP-Prod pulldown in embryos is the only instance in which we do not detect the bait by mass spectrometry. Here, one reason could be relatively low expression of GFP-Prod in comparison to GFP-D1 (Fig. S1E), which may lead to technical difficulties in detecting peptides corresponding to Prod. However, we note that Prod IP co-purified proteins such as Bocks that were previously suggested as Prod interactors from high-throughput studies (Giot et al. 2003; Guruharsha et al. 2011). In addition, Prod IP from embryos also co-purified proteins known to associate with chromocenters such as Hcs and Saf-B. Finally, the concordance between D1 and Prod co-purified proteins from embryo lysates (Fig. 2A, C) suggest that the Prod IP from embryos is of reasonable quality.

      We also acknowledge the reviewer's comment that the description of the proteomic data was hard to follow. Therefore, we have revised our text to clearly indicate which bait pulled down which protein in which tissue (lines 148-156). We have also highlighted and discussed bait-specific and tissue-specific interactions in the text (lines 162-173).

      Minor comments The authors may also want to provide a bit more information on the quantitation of the proteomic data such as how many values were derive from the match-between runs function and how many were imputed as this can severely distort the quantification.

      Figure 1: Distribution of data after imputation in embryo (left), ovary (middle) and testis (right) datasets. Imputation is performed with random sampling from the 1% least intense values generated by a normal distribution.

      To ensure the robustness of our data analysis, we considered only those proteins that were consistently identified in all replicates for at least one bait (GFP-D1, GFP-Prod or NLS-GFP). This approach resulted in a relative low number of missing values. However, it is also important to bear in mind that in an AP-MS experiment, the number of missing values is higher, as interactors are not identified in the control pulldown. Importantly, the imputation of missing values during the data analysis did not alter the normal distribution of the dataset (Fig. 1, this document). Detailed information regarding the imputed values is also provided (Table 1, this document). The coding script used for the data analysis is available in the PRIDE submission of the dataset (Table 2, this document). This information has been added to our methods section under data availability.

      Table 1: ____Number of match-between-runs and imputations for embryo, ovary and testis datasets

      Dataset

      #match-between-runs

      %match-between-runs

      %imputation

      Embryo

      5541/27543

      20.11%

      8.36%

      Ovary

      1936/9530

      20.30%

      8.18%

      Testis

      1748/7168

      24.39%

      3.12%

      Table 2: ____Access to the PRIDE submission of the datasets

      Name

      ID PRIDE

      UN reviewer

      PW reviewer

      IP-MS of D1 from Testis tissue

      PXD044026

      reviewer_pxd044026@ebi.ac.uk

      ydswDQVW

      IP-MS of Piwi from Embryo tissue

      PXD043237

      reviewer_pxd043237@ebi.ac.uk

      TMCoDsdx

      IP-MS of Prod and D1 proteins from Ovary tissue

      PXD043236

      reviewer_pxd043236@ebi.ac.uk

      VOHqPmaS

      IP-MS of Prod and D1 proteins from Embryo tissue

      PXD043234

      reviewer_pxd043234@ebi.ac.uk

      L77VXdvA

      **Referee Cross-Commenting** I agree with the two other reviewers that the connection between the interactome and the transgenerational phenotype is unclear. This is also what I meant i my comment that the title is somewhat misleading. A systematic analysis of the D1 and Prod knock down effect on mRNAs and small Rnas would indeed be helpful to better understand the interesting effect.

      As suggested by the reviewer, we have performed RNA seq and small RNA seq in control and D1 mutant ovaries (Fig. 4) to fully understand the contribution of D1 in piRNA biogenesis and TE repression. Briefly, the mislocalization of RDC complex in D1 mutant ovaries does not significantly affect TE-mapping piRNA biogenesis (Fig. 4C, E). In addition, loss of D1 does not substantially alter TE expression in the ovaries (Fig. 4B) or alter the expression of genes involved in TE repression (Fig. 4F). Along with the results presented in Fig. 5 and Fig. 6, our data clearly indicate that embryogenesis (and potentially early larval development) is a critical period during which D1 makes an important contribution to TE repression.

      Reviewer #1 (Significance (Required)): Nevertheless, the investigation of the D1 and Prod interactome is interesting and might reveal insights into the pathways that drive the formation of centromeres in a tissue specific manner. It may be mostly interesting for the Drosophila community but could also be exiting for a broader audience interested in the connection of heterochromatin and its indirect effect on the regulation of transposable elements.

      We thank the reviewer again for the helpful and constructive comments, which have enabled us to significantly improve our study. We are excited by the results from our study, which illuminate unappreciated aspects of transcriptional silencing in constitutive heterochromatin.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)): Chavan et al. set out to enrich our compendium of pericentric heterochromatin-associated proteins - and to learn some new biology along the way. An ambitious AP-Mass baited with two DNA satellite-binding proteins (D1 and Prod), conducted across embryos, ovaries, and testes, yielded hundreds of candidate proteins putatively engaged at chromocenters. These proteins are enriched for a restricted number of biological pathways, including DNA repair and transposon regulation. To investigate the latter in greater depth, the authors examine D1 and prod mutants for transposon activity changes using reporter constructs for multiple elements. These reporter constructs revealed no transposon activation in the adult ovary, where many proteins identified in the mass spec experiments restrict transposons. However, the authors suggest that the D1 mutant ovaries do show disrupted localization of a key member of a transposon restriction pathway (Cuff), and infer that this mislocalization triggers a striking, transposon derepression phenotype in the F2 ovaries.

      The dataset produced by the AP-Mass Spec offers chromosome biologists an unprecedented resource. The PCH is long-ignored chromosomal region that has historically received minimal attention; consequently, the pathways that regulate heterochromatin are understudied. Moreover, attempting to connect genome organization to transposon regulation is a new and fascinating area. I can easily envision this manuscript triggering a flurry of discovery; however, there is quite a lot of work to do before the data can fully support the claims.

      We appreciate the reviewer taking the time to provide thoughtful comments and constructive suggestions to improve the manuscript. We believe that we have addressed all the comments raised to the significant advantage of our paper.

      Major comments 1. The introduction requires quite a radical restructure to better highlight the A) importance of the work and B) limit information whose relevance is not clear early in the manuscript. A. Delineating who makes up heterochromatin is a long-standing problem in chromosome biology. This paper has huge potential to contribute to this field; however, it is not the first. Others are working on this problem in other systems, for example PMID:29272703. Moreover, we have some understanding of the distinct pathways that may impact heterochromatin in different tissues (e.g., piRNA biology in ovaries vs the soma). Also, the mutant phenotypes of prod and D1 are different. Fleshing out these three distinct points could help the reader understand what we know and what we don't know about heterochromatin composition and its special biology. Understanding where we are as a field will offer clear predictions about who the interactors might be that we expect to find. For example, given the dramatically different D1 and prod mutant phenotypes (and allele swap phenotypes), how might the interactors with these proteins differ? What do we know about heterochromatin formation differences in different tissues? And how might these differences impact heterochromatin composition?

      The reviewer brings up a fair point and we have significantly reworked our introduction. We share the reviewer's opinion that improved knowledge of the constitutive heterochromatin proteome will reveal novel biology.

      1. The attempt to offer background on the piRNA pathway and hybrid dysgenesis in the Introduction does not work. As a naïve reader, it was not clear why I was reading about these pathways - it is only explicable once the reader gets to the final third of the Results. Moreover, the reader will not retain this information until the TE results are presented many pages later. I strongly urge the authors to shunt the two TE restriction paragraphs to later in the manuscript. They are currently a major impediment to understanding the power of the experiment - which is to identify new proteins, pathways, and ultimately, biology that are currently obscure because we have so little handle on who makes up heterochromatin.

      We agree with this suggestion. We have introduced the piRNA pathway in the results section (lines 205 - 216), right before this information is needed. We've also removed the details on hybrid dysgenesis, since our new data argues against a maternal effect from the D1 mutant.

      The implications of the failure to rescue female fertility by the tagged versions of both D1 and Prod are not discussed. Consequently, the reader is left uneasy about how to interpret the data.

      We understand this point raised by the reviewer. However, in our proteomics experiments, we have used GFP-D1 and GFP-Prod ovaries from ~1 day old females (line 579, methods). These ovaries are morphologically similar to the wild type (Fig. S1C) and their early germ cell development appears to be intact. Moreover, chromocenter formation in female GSCs is comparable to the wildtype (Fig. 1C-D). These data, along with the rescue of the viability of the Prod mutant (Fig. S1A-B), suggest that the presence of a GFP tag is not compromising D1 or Prod function in the early stages of germline development and is consistent with published and unpublished data from our lab. In addition, D1 and Prod from ovaries co-purify proteins such as Rfc38 (D1), Smn (D1), CG15107 (Prod), which have been identified in previous high-throughput screens (Guruharsha et al. 2011; Tang et al. 2023). For these reasons, we believe that GFP-D1 and GFP-Prod ovaries are a good starting point for the AP-MS experiment. We speculate that the failure to completely rescue female fertility may be due to improper expression levels of GFP-D1 or GFP-Prod flies at later stages of oogenesis, which are not present in ovaries from newly eclosed females and therefore unlikely to affect our proteomic data.

      1. How were the significance cut-offs determined? Is the p-value reported the adjusted p-value? As a non-expert in AP-MS, I was surprised to find that the p-value, at least according to the Methods, was not adjusted based on the number of tests. This is particularly relevant given the large/unwieldy(?) number of proteins that were identified as signficant in this study. Moreover, the D1 hit in Piwi pull down is actually not significant according to their criteria of p We used a standard cutoff of log2FC>1 and p2FC and low p-value) since these are more likely to be bona fide interactors. Third, we have used string-DB for functional analyses where we can place our hits in existing protein-protein interaction networks. Using this approach, we detect that Prod (but not D1) pulls down multiple members of the RPA complex in the embryo (RPA2 and RpA-70, Fig. S2B) while embryonic D1 (but not Prod) pulls down multiple components of the origin recognition complex (Orc1, lat, Orc5, Orc6, Fig. S2C) and the condensin I complex (Cap-G, Cap-D2, barr, Fig. S2D). Altogether, these filtering strategies allow us to eliminate as many false positives as possible while making sure to minimize the loss of true hits through multiple testing correction.

      How do we know if the lack of overlap across tissues is indeed germline- or soma-specialization rather than noise?

      To address this part of the comment, we have amended our text (lines 162-173) as follows,

      'We also observed a substantial overlap between D1- and Prod-associated proteins (yellow points in Fig. 2A, B, Table S1-3), with 61 hits pulled down by both baits (blue arrowheads, Fig. 2C) in embryos and ovaries. This observation is consistent with the fact that both D1 and Prod occupy sub-domains within the larger constitutive heterochromatin domain in nuclei. Surprisingly, only 12 proteins were co-purified by the same bait (D1 or Prod) across different tissues (magenta arrowheads, Fig. 2C, Table S1-3). In addition, only a few proteins such as an uncharacterized DnaJ-like chaperone, CG5504, were associated with both D1 and Prod in embryos and ovaries (Fig. 2D). One interpretation of these results is that the protein composition of chromocenters may be tailored to cell- and tissue-specific functions in Drosophila. However, we also note that the large number of unidentified peptides in AP-MS experiments means that more targeted experiments are required to validate whether certain proteins are indeed tissue-specific interactors of D1 and Prod.'

      To make this inference, conducting some validation would be required. More generally, I was surprised to see no single interactor validated by reciprocal IP-Westerns to validate the Mass-Spec results, though I am admittedly only adjacent to this technique. Note that colocalization, to my mind, does not validate the AP-MS data - in fact, we would a priori predict that piRNA pathway members would co-localize with PCH given the enrichment of piRNA clusters there.

      Here, we would point out that we have conducted multiple validation experiments with a specific focus on the functional significance of the associations between D1/Prod and TE repression proteins in embryos. While the reviewer suggests that piRNA pathway proteins may be expected to enrich at the pericentromeric heterochromatin, this is not always the case. For example, Piwi and Mael are present across the nucleus (pulled down by D1/Prod in embryos) while Cutoff, which is present adjacent to chromocenters in nurse cells, was not observed to interact with either D1 or Prod in the ovary samples.

      Therefore, for Piwi, we performed a reciprocal AP-MS experiment in embryos due to the higher sensitivity of this method (GFP-Piwi AP-MS, Fig. 3B). Excitingly, this experiment revealed that four largely uncharacterized proteins (CG14715, CG10208, Ugt35D1 and Fit) were highly enriched in the D1, Prod and Piwi pulldowns and these proteins will be an interesting cohort for future studies on transposon repression in Drosophila (Fig. 3C).

      Furthermore, we believe that determining the localization of proteins co-purified by D1/Prod is an important and orthogonal validation approach. For Sov, which is implicated in piRNA-dependent heterochromatin formation, we observe foci that are in close proximity to D1- and Prod-containing chromocenters (Fig. 3A).

      As for suggestion to validate by IP-WBs, we would point out that chromocenters exhibit properties associated with phase separated biomolecular condensates. Based on the literature, these condensates tend to associate with other proteins/condensates through low affinity or transient interactions that are rarely preserved in IP-WBs, even if there are strong functional relationships. One example is the association between D1 and Prod, which do not pull each other down in an IP-WB (Jagannathan et al. 2019), even though D1 and Prod foci dynamically associate in the nucleus and mutually regulate each other's ability to cluster satellite DNA repeats (Jagannathan et al. 2019). Similarly, IP-WB using GFP-Piwi embryos did not reveal an interaction with D1 (Fig. S4B). However, our extensive functional validations (Figures 4-6) have revealed a critical role for D1 in heritable TE repression.

      The AlphaFold2 data are very interesting but seem to lack of negative control. Is it possible to incorporate a dataset of proteins that are not predicted to interact physically to elevate the impact of the ones that you have focused on? Moreover, the structural modeling might suggest a competitive interaction between D1 and piRNAs for Piwi. Is this true? And even if not, how does the structural model contribute to your understanding for how D1 engages with the piRNA pathway? The Cuff mislocalization?

      In the revised manuscript, we have generated more structural models using AlphaFold Multimer (AFM) for proteins (log2FC>2, p0.5 and ipTM>0.8), now elaborated in lines 175-177. Despite the extensive disorder in D1 and Prod, we identified 22 proteins, including Piwi, that yield interfaces with ipTM scores >0.5 (Table S4, Table S8). These hits are promising candidates to further understand D1 and Prod function in the future.

      For the predicted model between Prod/D1 and Piwi (Fig. S4A), one conclusion could indeed be competition between D1/Prod and piRNAs for Piwi. Another possibility is that a transient interaction mediated by disordered regions on D1/Prod could recruit Piwi to satellite DNA-embedded TE loci in the pericentromeric heterochromatin. These types of interactions may be especially important in the early embryonic cycles, where repressive histone modifications such as H3K9me2/3 must be deposited at the correct loci for the first time. We suggest that mutating the disordered regions on D1 and Prod to potentially abrogate the interaction with Piwi will be important for future studies.

      The absence of a TE signal in D1 and Prod mutant ovaries would be much more compelling if investigated more agnostically. The observation that not all TE reporter constructs show a striking signal in the F2 embryos makes me wonder if Burdock and gypsy are not regulated by these two proteins but possibly other TEs are. Alternatively, small RNA-seq would more directly address the question of whether D1 and Prod regulate TEs through the piRNA pathway.

      We completely agree with this comment from the reviewer. We have performed RNA seq on D1 heterozygous (control) and D1 mutant ovaries in a chk26006 background. Since Chk2 arrests germ cell development in response to TE de-repression and DNA damage(Ghabrial and Schüpbach 1999; Moon et al. 2018), we reasoned that the chk2 mutant background would prevent developmental arrest of potential TE-expressing germ cells and we observed that both genotypes exhibited similar gonad morphology (Fig. 4A). From our analysis, we do not observe a significant effect on TE expression in the absence of D1, except for the LTR retrotransposon tirant (Fig. 4B). We also do not observe differential expression of TE repression genes (Fig. 4F).

      We have complemented our RNA seq experiment with small RNA profiling from D1 heterozygous (control) and D1 mutant ovaries. Here, overall piRNA production and antisense piRNAs mapping to TEs were largely unperturbed (Fig. 4C-E).

      Overall, our data is consistent with the TE reporter data (Fig. S7) and suggests that zygotic depletion of D1 does not have a prominent role in TE repression. However, we have uncovered that the presence of D1 during embryogenesis is critical for TE repression in adult gonads (Fig. 6, Fig. S9).

      I had trouble understanding the significance of the Cuff mis-localization when D1 is depleted. Given Cuff's role in the piRNA pathway and close association with chromatin, what would the null hypothesis be for Cuff localization when a chromocenter is disrupted? What is the null expectation of % Cuff at chromocenter given that the chromocenter itself expands massively in size (Figure 4D). The relationship between these two factors seems rather indirect and indeed, the absence of Cuff in the AP would suggest this. The biggest surprise is the absence of TE phenotype in the ovary, given the Cuff mutant phenotype - but we can't rule out given the absence of a genome-wide analysis. I think that these data leave the reader unconvinced that the F2 phenotype is causally linked to Cuff mislocalization.

      We apologize that this data was not more clearly represented. In a wild-type context, Cuff is distributed in a punctate manner across the nurse cell nuclei, with the puncta likely representing piRNA clusters (Fig. 5A-B). We find that a small fraction of Cuff (~5%) is present adjacent to the nurse cell chromocenter (inset, Fig. 5A and Fig. 5D). In the absence of D1, the nurse cell chromocenters increase ~3-4 fold in size. However, the null expectation is still that ~5% of total Cuff would be adjacent to the chromocenter, since the piRNA clusters are not expected to expand in size. In reality, we observe ~27% of total Cuff is mislocalized to chromocenters. Our data indicate that the satellite DNA repeats at the larger chromocenters must be more accessible to Cuff in the D1 mutant nurse cells. This observation is corroborated by the significant increase in piRNAs corresponding to the 1.688 satellite DNA repeat family (Fig. 4E).

      The lack of TE expression in the F1 D1 mutant was indeed surprising based on the Cuff mislocalization but as the reviewers pointed out, we only analyzed two TE reporter constructs in the initial submission. In the revised manuscript, we have performed both RNA seq and small RNA seq. Surprisingly, our data reveal that the Cuff mislocalization does not significantly affect piRNA biogenesis (Fig. 4C, D) and piRNAs mapping to TEs. As a result, both TE repression (Fig. 4B) and fertility (Fig. 6D) are largely preserved in the absence of D1 in adult ovaries.

      Finally, we thank the reviewer for their excellent suggestion to incorporate the F2 D1 heterozygote (Fig. S9) in our analysis! This important control has revealed that the maternal effect of the D1 mutant is negligible for gonad development and fertility (Fig. 6B-D). Rather, our data clearly emphasize embryogenesis (or early larval development) as a key period during which D1 can promote heritable TE repression. Essentially, D1 is not required during adulthood for TE repression if it was present in the early stages of development.

      Apologies if I missed this, but Figure 5 shows the F2 D1 mutant ovaries only. Did you look at the TM6 ovaries as well? These ovaries should lack the maternally provisioned D1 (assuming that females are on the right side) but have the zygotic transcription.

      As mentioned above, this was a great suggestion and we've now characterized this important control in the context of germline development and fertility, to the significant advantage of our paper.

      Minor comments 9. Add line numbers for ease of reference

      We apologize for this. Line numbers have been added in the full revision.

      1. The function of satellite DNA itself is still quite controversial - I would recommend being a bit more careful here - the authors could refer instead to genomic regions enriched for satellite DNA are linked to xyz function (see Abstract line 2 and 7, for example.)

      The abstract has been rewritten and does not directly implicate satellite DNA in a specific cellular function. However, we have taken the reviewer's suggestion in the introduction (line 57-58).

      "Genetic conflicts" in the introduction needs more explanation.

      This sentence has been removed from the introduction in the revised manuscript.

      "In contrast" is not quite the right word. Maybe "However" instead (1st line second paragraph of Intro)

      Done. Line 57 of the revised manuscript.

      Results: what is the motivation for using GSC-enriched testis?

      We use GSC-enriched testes for practical reasons. First, they contain a relatively uniform population of mitotically dividing germ cells unlike regular testes which contain a multitude of post-mitotic germ cells such as spermatocytes, spermatids and sperm. Second, GSC-enriched testes are much larger than normal testes and reduced the number of dissections that were needed for each replicate.

      1. Clarify sentence about the 500 proteins in the Results section - it's not clear from context that this is the union of all experiments.

      Done. Lines 145-149 in the revised manuscript.

      The data reported are not the first to suggest that satellite DNA may have special DNA repair requirements. e.g., PMID: 25340780

      We apologize if we gave the impression that we were making a novel claim. Specialized DNA repair requirements at repetitive sequences have indeed been previously hypothesized(Charlesworth et al. 1994) and studied and we have altered the text to better reflect this (lines 193-195). We have cited the study suggested by the reviewer as well as studies from the Chiolo(Chiolo et al. 2011; Ryu et al. 2015; Caridi et al. 2018) and Soutoglou(Mitrentsi et al. 2022) labs, which have also addressed this fascinating question.

      Page 10: indicate-> indicates.

      Done.

      1. Page 14: revise for clarity: "investigate a context whether these interactions could not take place"

      We've incorporated this suggestion in the revised text (lines 383-386).

      1. Might be important to highlight the 500 interactions are both direct and indirect. "Interacting proteins" alone suggests direct interactions only.

      Done. Lines 145-149.

      The effect of the aub mutant on chromocenter foci did not seem modest to me - however, the bar graphs obscure the raw data - consider plotting all the data not just the mean and error?

      Done. This data is now represented by a box-and-whisker plot (Fig. S5), which shows the distribution of the data.

      Reviewer #2 (Significance (Required)):

      The dataset produced by the AP-Mass Spec offers chromosome biologists an unprecedented resource. The PCH is long-ignored chromosomal region that has historically received minimal attention; consequently, the pathways that regulate heterochromatin are understudied. Moreover, attempting to connect genome organization to transposon regulation is a new and fascinating area. I can easily envision this manuscript triggering a flurry of discovery; however, there is quite a lot of work to do before the data can fully support the claims.

      This manuscript represents a significant contribution to the field of chromosome biology.

      We thank the reviewer for the positive evaluation of our manuscript, and we really appreciate the great suggestion for the F2 D1 heterozygote control! Overall, we believe that our manuscript is substantially improved with the addition of RNA seq, small RNA seq and important genetic controls. Moreover, we are excited by the potential of our study to open new doors in the study of pericentromeric heterochromatin.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)): In the manuscript entitled "Multi-tissue proteomics identifies a link between satellite DNA organization and transgenerational transposon repression", the authors used two satellite DNA-binding proteins, D1 and Prod, as baits to identify chromocenter-associated proteins through quantitative mass spectrometry. The proteomic analysis identified ~500 proteins across embryos, ovaries, and testes, including several piRNA pathways proteins. Depletion of D1 or Prod did not directly contribute to transposon repression in ovary. However, in the absence of maternal and zygotic D1, there was a dramatic increase of agametic ovaries and transgenerational transposon de-repression. Although the study provides a wealth of proteomic data, it lacks mechanistic insights into how satellite DNA organization influence the interactions with other proteins and their functional consequences.

      We thank the reviewer for highlighting that this study will be a valuable resource for future studies on the composition and function of pericentromeric heterochromatin. Based on the reviewer's request for more mechanistic knowledge into how satellite DNA organization affects transposon repression, we have performed RNA seq and small RNA seq, added important genetic controls and significantly improved our text. In the revised manuscript, our data clearly demonstrate that embryogenesis (and potentially early larval development) is a critical time period when D1 contributes to heritable TE repression. Flies lacking D1 during embryogenesis exhibit TE expression in germ cells as adults, which is associated with Chk2-dependent gonadal atrophy. We are particularly excited by these data since TE loci are embedded in the satellite DNA-rich pericentromeric heterochromatin and our study demonstrates an important role for a satellite DNA-binding protein in TE repression.

      Major____ comments 1. While the identification of numerous interactions is significant, it would be helpful to acknowledge that lots of these proteins were known to bind DNA or heterochromatin regions. To strengthen the study, I recommend conducting functional validation of the identified interactions, in addition to the predictions made by Alphfold 2.

      We are happy to take this comment on board. In fact, we believe that the large number of DNA-binding and heterochromatin-associated proteins identified in this study are a sign of quality for the proteomic datasets. In the revised manuscript, we have highlighted known heterochromatin proteins co-purified by D1/Prod in lines 148-151 as well as proteins previously suggested to interact with D1/Prod from high-throughput studies in lines 153-156 (Guruharsha et al. 2011; Tang et al. 2023). In this study, we have focused on the previously unknown associations between D1/Prod and TE repression proteins and functionally validated these interactions as presented in Figures 3-6.

      The observation of transgenerational de-repression is intriguing. However, to better support this finding, it would be better to provide a mechanistic explanation based on the data presented.

      We appreciate this comment from the reviewer, which is similar to major comment #6 raised by reviewer #2. To generate mechanistic insight into the underlying cause of gonad atrophy in the F2 D1 mutant, we have performed RNA seq, small RNA seq and analyzed germline development and fertility in the F2 D1 heterozygous control (Fig. S9).

      For the RNA seq, we used D1 heterozygous (control) and D1 mutant ovaries in a chk26006 background. Since Chk2 arrests germ cell development in response to TE de-repression and DNA damage(Ghabrial and Schüpbach 1999; Moon et al. 2018), we reasoned that the chk2 mutant background would prevent developmental arrest of potential TE-expressing germ cells and we observed that both genotypes exhibited similar gonad morphology (Fig. 4A). From our analysis, we do not observe a significant effect on TE expression in the absence of D1, except for the LTR retrotransposon tirant (Fig. 4B). We also do not observe differential expression of TE repression genes (Fig. 4F).

      We have complemented our RNA seq experiment with small RNA profiling from D1 heterozygous (control) and D1 mutant ovaries. Here, overall piRNA production and antisense piRNAs mapping to TEs were largely unperturbed (Fig. 4C-E). Together, these data are consistent with the TE reporter data (Fig. S7) and suggests that zygotic depletion of D1 does not have a prominent role in TE repression.

      However, we have uncovered that the presence of D1 during embryogenesis is critical for TE repression in adult gonads (Fig. 6, Fig. S9). Essentially, either only maternal deposited D1 (F1 D1 mutant) or only zygotically expressed D1 (F2 D1 het) were sufficient to ensure TE repression and fertility. In contrast, a lack of D1 during embryogenesis (F2 D1 mutant) led to elevated TE expression and Chk2-mediated gonadal atrophy.

      Our results also explain why previous studies have not implicated either D1 or Prod in TE repression, since D1 likely persists during embryogenesis when using depletion approaches such as RNAi-mediated knockdown or F1 generation mutants.

      Minor____ comments 3. Given the maternal effect of the D1 mutant, in Figure 4, I suggest analyzing not only nurse cells but also oocytes to gain a more comprehensive understanding.

      We agree with the reviewer that this experiment can be informative. In the F2 D1 mutant ovaries, germ cell development does not proceed to a stage where oocytes are specified, thus limiting microscopy-based approaches. Nevertheless, we have gauged oocyte quality in all the genotypes using a fertility assay (Fig. 6D) since even ovaries that have a wild-type appearance can produce dysfunctional gametes. In this experiment, we observe that fertility is largely intact in the F1 D1 mutant and F2 D1 heterozygote strains, suggesting that it is the presence of D1 during embryogenesis (or early larval development) that is critical for heritable TE repression and proper oocyte development.

      The conclusion that D1 and Prod do not directly contribute to the repression of transposons needs further analysis from RNA-seq data. Alternatively, the wording could be adjusted to indicate that D1 and Prod are not required for specific transposon silencing, such as Burdock and gypsy.

      Agreed. We have performed RNA-seq in D1 heterozygous (control) and D1 mutant ovaries in a chk26006 background (Fig. 4A, B) as described above.

      As D1 mutation affects Cuff nuclear localization, it would be insightful to sequence the piRNA in the ovaries.

      Agreed. We have performed small RNA profiling from D1 heterozygous (control) and D1 mutant ovaries. Despite the significant mislocalization of the RDC complex, overall piRNA production and antisense piRNAs mapping to TEs were largely unaffected (Fig. 4C-E). However, we observed significant changes in piRNAs mapping to complex satellite DNA repeats (Fig. 4D), but these changes were not associated with a maternal effect on germline development or fertility (F2 D1 heterozygote, Fig. 6B-D).

      **Referee Cross-Commenting**

      I appreciate the valuable insights provided by the other two reviewers regarding this manuscript. I concur with their assessment that substantial improvements are needed before considering this manuscript for publication.

      1. The proteomics data has the potential to be a valuable resource for other scientific community. However, I share the concerns raised by reviewer 1 about the current quality of the data sets. Addressing this, it will augment the manuscript with additional data to show the success of the precipitation. Moreover, as reviewer 2 and I suggested, additional co-IP validations of the IP-MS results are needed to enhance the reliability.

      In the revised manuscript, we have performed multiple experiments to address the quality of the MS datasets based on comments raised by reviewer #1. They are as follows,

      Out of six total AP-MS experiments in this manuscript (D1 x 3, Prod x 2 and Piwi), we observe a strong enrichment of the bait in 5/6 attempts (log2FC between 4-12, Fig. 2A, B, Fig. S2A, Table S1-S3, Table S7). In the D1 testis sample from the initial submission, the lack of a third biological replicate meant that only the p-value (0.07) was not meeting the cutoff. To address this, we have repeated this experiment with an additional biological replicate (Fig. S2A), and our data now clearly show that D1 is also significantly enriched in the testis sample.

      As suggested by the reviewer #1, we have assessed our lysis conditions (450mM NaCl and benzonase) and the solubilization of our baits post-lysis. In Fig. S1D, we have blotted equivalent fractions of the soluble supernatant and insoluble pellet from GFP-Piwi embryos and show that both GFP-Piwi and D1 are largely solubilized following lysis. In Fig. S1E, we also show that our IP protocol works efficiently.

      The only instance in which we do not detect the bait by mass spectrometry is for GFP-Prod pulldown in embryos. Here, one reason could be relatively low expression of GFP-Prod in comparison to GFP-D1 (Fig. S1E), which may lead to technical difficulties in detecting peptides corresponding to Prod. However, we note that Prod IP from embryos co-purified proteins such as Bocks that were previously suggested as Prod interactors from high-throughput studies (Giot et al. 2003; Guruharsha et al. 2011). In addition, Prod IP from embryos also co-purified proteins known to associate with chromocenters such as Hcs(Reyes-Carmona et al. 2011) and Saf-B(Huo et al. 2020). Finally, the concordance between D1 and Prod co-purified proteins from embryo lysates (Fig. 2A, C) suggest that the Prod IP from embryos is of reasonable quality.

      As for the IP-WB validations, we would point out that chromocenters exhibit properties associated with phase separated biomolecular condensates. In our experience, these condensates tend to associate with other proteins/condensates through low affinity or transient interactions that are rarely preserved in IP-WBs, even if there are strong functional relationships. One example is the association between D1 and Prod, which do not pull each other down in an IP-WB (Jagannathan et al. 2019), even though D1 and Prod foci dynamically associate in the nucleus and mutually regulate each other's ability to cluster satellite DNA repeats (Jagannathan et al. 2019). Similarly, IP-WB using GFP-Piwi embryos did not reveal an interaction with D1 (Fig. S4B). However, our extensive functional validations (Figures 4-6) have revealed a critical role for D1 in heritable TE repression.

      I agree with reviewer 2 that the present conclusion is not appropriate regarding D1 and Prod do not contribute to transposon silencing. As reviewer 2 and I suggested, the systematical analysis by using both mRNA-seq and small RNA-seq is required to draw the conclusion.

      Agreed. We have performed RNA seq and small RNA seq as elaborated above. Our conclusions on the role of D1 in TE repression are now much stronger.

      1. The transgenerational phenotype is an intriguing aspect of the study. I agree with reviewer 2 that the inclusion of TM6 ovaries would be a nice control. Further, it is hard to connect this phenotype with the interactions identified in this manuscript. It would be appreciated if the author could provide a mechanistic explanation.

      We have significantly improved these aspects of our study in the revised manuscript. Through the analysis of germline development in the F2 D1 heterozygotes as suggested by reviewer #2, in addition to the recommended RNA seq and small RNA seq, we have now identified embryogenesis (and potentially early larval development) as a time period when D1 makes an important contribution to TE repression. Loss of D1 during embryogenesis leads to TE expression in adult germline cells, which is associated with Chk2-dependent gonadal atrophy. Taken together, we have pinpointed the specific contribution of a satellite DNA-binding protein to transposon repression.

      Reviewer #3 (Significance (Required)):

      Although this study successfully identified several interactions, the authors did not fully elucidate how these interactions contribute to the transgenerational silencing of transposons or ovary development.

      We thank the reviewer for the thoughtful comments and overall positive evaluation of our study, especially the proteomic dataset. We are confident that the revised manuscript has improved our mechanistic understanding of the contribution made by a satellite DNA-binding protein in TE repression.

      References

      Baumgartner L, Handler D, Platzer SW, Yu C, Duchek P, Brennecke J. 2022. The Drosophila ZAD zinc finger protein Kipferl guides Rhino to piRNA clusters eds. D. Bourc'his, K. Struhl, and Z. Zhang. eLife 11: e80067.

      Caridi CP, D'Agostino C, Ryu T, Zapotoczny G, Delabaere L, Li X, Khodaverdian VY, Amaral N, Lin E, Rau AR, et al. 2018. Nuclear F-actin and myosins drive relocalization of heterochromatic breaks. Nature 559: 54-60.

      Charlesworth B, Sniegowski P, Stephan W. 1994. The evolutionary dynamics of repetitive DNA in eukaryotes. Nature 371: 215-220.

      Chiolo I, Minoda A, Colmenares SU, Polyzos A, Costes SV, Karpen GH. 2011. Double-strand breaks in heterochromatin move outside of a dynamic HP1a domain to complete recombinational repair. Cell 144: 732-744.

      Ghabrial A, Schüpbach T. 1999. Activation of a meiotic checkpoint regulates translation of Gurken during Drosophila oogenesis. Nat Cell Biol 1: 354-357.

      Giot L, Bader JS, Brouwer C, Chaudhuri A, Kuang B, Li Y, Hao YL, Ooi CE, Godwin B, Vitols E, et al. 2003. A protein interaction map of Drosophila melanogaster. Science 302: 1727-1736.

      Guruharsha KG, Rual JF, Zhai B, Mintseris J, Vaidya P, Vaidya N, Beekman C, Wong C, Rhee DY, Cenaj O, et al. 2011. A protein complex network of Drosophila melanogaster. Cell 147: 690-703.

      Huo X, Ji L, Zhang Y, Lv P, Cao X, Wang Q, Yan Z, Dong S, Du D, Zhang F, et al. 2020. The Nuclear Matrix Protein SAFB Cooperates with Major Satellite RNAs to Stabilize Heterochromatin Architecture Partially through Phase Separation. Molecular Cell 77: 368-383.e7.

      Jagannathan M, Cummings R, Yamashita YM. 2019. The modular mechanism of chromocenter formation in Drosophila eds. K. VijayRaghavan and S.A. Gerbi. eLife 8: e43938.

      Mitrentsi I, Lou J, Kerjouan A, Verigos J, Reina-San-Martin B, Hinde E, Soutoglou E. 2022. Heterochromatic repeat clustering imposes a physical barrier on homologous recombination to prevent chromosomal translocations. Molecular Cell 82: 2132-2147.e6.

      Moon S, Cassani M, Lin YA, Wang L, Dou K, Zhang ZZ. 2018. A Robust Transposon-Endogenizing Response from Germline Stem Cells. Dev Cell 47: 660-671 e3.

      Pascovici D, Handler DCL, Wu JX, Haynes PA. 2016. Multiple testing corrections in quantitative proteomics: A useful but blunt tool. PROTEOMICS 16: 2448-2453.

      Reyes-Carmona S, Valadéz-Graham V, Aguilar-Fuentes J, Zurita M, León-Del-Río A. 2011. Trafficking and chromatin dynamics of holocarboxylase synthetase during development of Drosophila melanogaster. Molecular Genetics and Metabolism 103: 240-248.

      Ryu T, Spatola B, Delabaere L, Bowlin K, Hopp H, Kunitake R, Karpen GH, Chiolo I. 2015. Heterochromatic breaks move to the nuclear periphery to continue recombinational repair. Nat Cell Biol 17: 1401-1411.

      Tang H-W, Spirohn K, Hu Y, Hao T, Kovács IA, Gao Y, Binari R, Yang-Zhou D, Wan KH, Bader JS, et al. 2023. Next-generation large-scale binary protein interaction network for Drosophila melanogaster. Nat Commun 14: 2162.

    1. of both race and gender that remained in place—particularly among its women employees known as computers..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11211Darden’s arrival at Langley coincided with the early days of digital computing. Although Langley could claim one of the most advanced computing systems of the time—an IBM 704, the first computer to support floating-point math—its resources were still limited. For most data analysis tasks, Langley’s Advanced Computing Division relied upon human computers like Darden herself. These computers were all women, trained in math or a related field, and tasked with performing the calculations that determined everything from the best wing shape for an airplane, to the best flight path to the moon. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Aneta SwianiewiczBut despite the crucial roles they played in advancing this and other NASA research, they were treated like unskilled temporary workers.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11. They were brought into research groups on a project-by-project basis, often without even being told anything about the source of the data they were asked to analyze..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Lena Zlock Most of the engineers, who were predominantly men, never even bothered to learn the computers’ names.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1111.These women computers have only recently.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Michela Banks begun to receive credit for their crucial work, thanks to scholars of the history of computing.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Roujia Wang—and to journalists like Margot Lee Shetterly, whose book, Hidden Figures: The American Dream and the Untold Story of the Black Women Who Helped Win the Space Race,.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi along with its film adaptation.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Fagana Stone, is responsible for bringing Christine Darden’s story into the public eye.2 Her story, like those of her colleagues, is one of hard work under discriminatory conditions. Each of these women computers was required to advocate for herself—and some, like Darden, chose also to advocate for others. It is because of both her contributions to data science and her advocacy for women that we have chosen to begin our book, Data Feminism, with Darden’s story. For feminism begins with a belief in the “political, social, and economic equality of the sexes,”.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Michela Banks as the Merriam-Webster Dictionary defines the term—as does, for the record, Beyoncé.3 And any definition of feminism also necessarily includes the activist work that is required to turn that belief into reality.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yolanda Yang. In Data Feminism, we bring these two aspects of feminism together, demonstrating a way of thinking about data, their analysis, and their display, that is informed by this tradition of feminist activism as well as the legacy of feminist critical thought..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah beanAs for Darden, she did not only apply her skills of data analysis to spaceflight trajectories; she also applied them to her own career path..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yasin Chowdhury After working at Langley for a number of years, she began to notice two distinct patterns in her workplace: men with math credentials were placed in engineering positions, where they could be promoted through the ranks of the civil service, while women with the same degrees were sent to the computing pools, where they languished until they retired or quit.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }211..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Joe Masnyy She did not want to become one of those women, nor did she want others to experience the same fate. So she gathered up her courage and decided to approach the chief of her division to ask him why..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yasin Chowdhury As Darden, now seventy-five, told Shetterly in an interview for Hidden Figures, his response was sobering: “Well, nobody’s ever complained,” he told Darden. “The women seem to be happy doing that, so that’s just what they do.”.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }21111In today’s world, Darden might have gotten her boss fired—or at least served with an Equal Employment Opportunity Commission complaint. But at the time that Darden posed her question, stereotypical remarks about “what women do” were par for the course..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Roujia Wang In fact, challenging assumptions about what women could or couldn’t do—especially in the workplace—was the central subject of Betty Friedan’s best-selling book, The Feminine Mystique. Published in 1963, The Feminine Mystique.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten is often credited with starting feminism’s so-called second wave.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yolanda Yang.4 Fed up with the enforced return to domesticity following the end of World War II, and inspired by the national conversation about equality of opportunity prompted by the civil rights movement, women across the United States began to organize around a wide range of issues, including reproductive rights.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }21 and domestic violence, as well as the workplace inequality and restrictive gender roles that Darden faced at Langley.That said, Darden’s specific experience as a Black woman with a full-time job was quite different than that of a white suburban housewife—the central focus of The Feminine Mystique. And when critics rightly called out Friedan for failing to acknowledge the range of experiences of women in the United States (and abroad), it was women like Darden, among many others, whom they had in mind. In Feminist Theory: From Margin to Center, another landmark feminist book published in 1984, bell hooks puts it plainly: “[Friedan] did not discuss who would be called in to take care of the children and maintain the home if more women like herself were freed from their house labor and given equal access with white men to the professions. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11She did not speak of the needs of women without men, without children, without homes. She ignored the existence of all non-white women and poor white women..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi She did not tell readers whether it was more fulfilling to be a maid, a babysitter, a factory worker, a clerk, or a prostitute than to be a leisure-class housewife.”.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten5In other words, Friedan had failed to consider how those additional dimensions of individual and group identity—like race and class, not to mention sexuality, ability, age, religion, and geography, among many others—intersect with each other to determine one’s experience in the world.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jayri Ramirez. Although this concept—intersectionality.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11—did not have a name when hooks described it, the idea that these dimensions cannot be examined in isolation from each other has a much longer intellectual history..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }116 Then, as now, key scholars and activists were deeply attuned to how the racism embedded in US culture.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Fagana Stone, Amanda Christopher, coupled with many other forms of oppression, made it impossible to claim a common experience.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi—or a common movement—for all women everywhere. Instead, what was needed was “the development of integrated analysis and practice based upon the fact that the major systems of oppression are interlocking.”7 These words are from the Combahee River Collective Statement, written in 1978 by the famed Black feminist activist group out of Boston. In this book, we draw heavily from intersectionality and other concepts developed through the work of Black feminist scholars and activists because they offer some of the best ways for negotiating this multidimensional terrain.Indeed, feminism must be intersectional if it seeks to address the challenges of the present moment..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Angela Li, Cynthia Lisee We write as two straight, white women based in the United States, with four advanced degrees and five kids between us. We identify as middle-class and cisgender—meaning that our gender identity matches the sex that we were assigned at birth. We have experienced.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten sexism in various ways at different points of our lives—being women in tech and academia, birthing and breastfeeding babies, and trying to advocate for ourselves and our bodies in a male-dominated health care system. But we haven’t experienced sexism in ways that other women certainly have or that nonbinary people have, for there are many dimensions of our shared identity, as the authors of this book, that align with dominant group positions. This fact makes it impossible for us to speak from experience about some oppressive forces—racism, for example. But it doesn’t make it impossible for us to educate ourselves.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi and then speak about racism and the role that white people play in upholding it..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Peem Lerdp Or to challenge ableism and the role that abled people play in upholding it. Or to speak about class and wealth inequalities and the role that well-educated, well-off people play in maintaining those..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Fagana Stone Or to believe in the logic of co-liberation. Or to advocate for justice through equity. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah beanIndeed, a central aim of this book is to describe a form of intersectional feminism that takes the inequities of the present moment as its starting point and begins its own work by asking: How can we use data to remake the world?8This is a complex and weighty task, and it will necessarily remain unfinished. But its size and scope need not stop us—or you, the readers of this book—from taking additional steps toward justice. Consider Christine Darden, who, after speaking up to her division chief, heard nothing from him but radio silence. But then, two weeks later, she was indeed promoted.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Amanda Christopher and transferred to a group focused on sonic boom research. In her new position, Darden was able to begin directing her own research projects and collaborate with colleagues of all genders as a peer. Her self-advocacy serves as a model: a sustained attention to how systems of oppression intersect with each other, informed by the knowledge that comes from direct experience. It offers a guide for challenging power and working toward justice.What Is Data Feminism?Christine Darden would go on to conduct groundbreaking research on sonic boom minimization techniques, author more than sixty scientific papers in the field of computational fluid dynamics, and earn her PhD in mechanical engineering—all while “juggling the duties of Girl Scout mom, Sunday school teacher, trips to music lessons, and homemaker,” Shetterly reports. But even as she ascended the professional ranks, she could tell that her scientific accomplishments were still not being recognized as readily as those of her male counterparts; the men, it seemed, received promotions far more quickly.Darden consulted with Langley’s Equal Opportunity Office, where a white woman by the name of Gloria Champine had been compiling a set of statistics about gender and rank. The data confirmed Darden’s direct experience: that women and men.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten—even those with identical academic credentials, publication records, and performance reviews—were promoted at vastly different rates. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Aneta SwianiewiczChampine recognized that her data could support Darden in her pursuit of a promotion and, furthermore, that these data could help communicate the systemic nature of the problem at hand. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yuanxi LiChampine visualized the data in the form of a bar chart, and presented the chart to the director of Darden’s division.9 He was “shocked at the disparity,” Shetterly reports, and Darden received the promotion she had long deserved.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Angela Li, Fagana Stone.10 Darden would advance to the top rank in the federal civil service, the first Black woman at Langley to do so. By the time that she retired from NASA, in 2007, Darden was a director herself..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Joe Masnyy11Although Darden’s rise into the leadership ranks at NASA was largely the result of her own knowledge, experience, and grit, her story is one that we can only tell as a result of the past several decades of feminist activism and critical thought. It was a national feminist movement that brought women’s issues to the forefront of US cultural politics, and the changes brought about by that movement were vast. They included both the shifting gender roles that pointed Darden in the direction of employment at NASA and the creation of reporting mechanisms.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; } like the one that enabled her to continue her professional rise..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Roujia Wang, Seyoon Ahn But Darden’s success in the workplace was also, presumably, the result of many unnamed colleagues and friends who may or may not have considered themselves feminists. These were the people who provided her with community and support.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi—and likely a not insignificant number of casserole dinners—as she ascended the government ranks. These types of collective efforts have been made increasingly legible, in turn, because of the feminist scholars and activists whose decades of work have enabled us to recognize that labor—emotional as much as physical—as such today.As should already be apparent, feminism has been defined and used in many ways. Here and throughout the book, we employ the term feminism as a shorthand for the diverse and wide-ranging projects that name and challenge sexism and other forces of oppression, as well as those which seek to create more just, equitable, and livable futures. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }312Because of this broadness, some scholars prefer to use the term feminisms, which clearly signals the range of—and, at times, the incompatibilities among—these various strains of feminist activism and political thought. For reasons of readability, we choose to use the term feminism here, but our feminism is intended to be just as expansive. It includes the work of regular folks like Darden and Champine, public intellectuals like Betty Friedan and bell hooks, and organizing groups like the Combahee River Collective, which have taken direct action to achieve the equality of the sexes. It also includes the work of scholars and other cultural critics—like Kimberlé Crenshaw and Margot Lee Shetterly, among many more—who have used writing to explore the social, political, historical, and conceptual reasons behind the inequality of the sexes that we face today.In the process, these writers and activists have given voice to the many ways in which today’s status quo is unjust.12 These injustices are often the result of historical and contemporary differentials of power, including those among men, women, and nonbinary people, as well as those among white women and Black women, academic researchers and Indigenous communities, and people in the Global North and the Global South..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; } Feminists analyze these power differentials so that they can change them..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1athmar al-ghanim Such a broad focus—one that incorporates race, class, ability, and more—would have sounded strange to Friedan or to the white women largely credited for leading the fight for women’s suffrage in the nineteenth century.13 But the reality is that women of color have long insisted that any movement for gender equality must also consider the ways in which privilege and oppression are intersectional..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah beanBecause the concept of intersectionality is essential for this whole book, let’s get a bit more specific. The term was coined by legal theorist Kimberlé Crenshaw in the late 1980s..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah bean14 In law school, Crenshaw had come across the antidiscrimination case of DeGraffenreid v. General Motors. Emma DeGraffenreid was a Black working mother who had sought a job at a General Motors factory in her town. She was not hired and sued GM for discrimination. The factory did have a history of hiring Black people: many Black men worked in industrial and maintenance jobs there. They also had a history of hiring women: many white women worked there as secretaries. These two pieces of evidence provided the rationale for the judge to throw out the case. Because the company did hire Black people and did hire women, it could not be discriminating based on race or gender. But, Crenshaw wanted to know, what about discrimination on the basis of race and gender together? This was something different, it was real, and it needed to be named. Crenshaw not only named the concept, but would go on to explain and elaborate the idea of intersectionality in award-winning books, papers, and talks.15Key to the idea of intersectionality is that it does not only describe the intersecting aspects of any particular person’s identity (or positionalities, as they are sometimes termed).16 It also describes the intersecting forces of privilege and oppression at work in a given society. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }111Oppression involves the systematic mistreatment of certain groups of people by other groups. It happens when power is not distributed equally—when one group controls the institutions of law, education, and culture, and uses its power to systematically exclude other groups while giving its own group unfair advantages (or simply maintaining the status quo).17 In the case of gender oppression, we can point to the sexism, cissexism.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Amanda Christopher, and patriarchy that is evident in everything from political representation to the wage gap to who speaks more often (or more loudly.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten) in a meeting..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Tegan Lewis18 In the case of racial oppression, this takes the form of racism and white supremacy. Other forms of oppression include ableism, colonialism, and classism. Each has its particular history and manifests differently in different cultures and contexts, but all involve a dominant group that accrues power and privilege at the expense of others. Moreover, these forces of power and privilege on the one hand and oppression on the other mesh together in ways that multiply their effects.The effects of privilege and oppression are not distributed evenly across all individuals and groups, however. For some, they become an obvious and unavoidable part of daily life, particularly for women and people of color and queer people and immigrants: the list goes on. If you are a member of any or all of these (or other) minoritized groups, you experience their effects everywhere, shaping the choices you make (or don’t get to make) each day. These systems of power are as real as rain..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Eva Maria Chavez But forces of oppression can be difficult to detect when you benefit from them (we call this a privilege hazard later in the book).d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Yolanda Yang, Jillian McCarten. And this is where data come in: it was a set of intersecting systems of power and privilege that Darden was intent on exposing when she posed her initial question to her division chief. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1g mAnd it was that same set of intersecting systems of power and privilege that Darden sought to challenge when she approached Champine. Darden herself didn’t need any more evidence of the problem she faced; she was already living it every day.19 But when her experience was recorded as data and aggregated with others’ experiences, it could be used to challenge institutional systems of power and have far broader impact than on her career trajectory alone..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1111In this way, Darden models what we call data feminism: a way of thinking about data, both their uses and their limits, that is informed by direct experience, by a commitment to action, and by intersectional feminist thought..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Tegan Lewis T.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11he starting point for data feminism is something that goes mostly unacknowledged in data science: power is not distributed equally in the world. Those who wield power are disproportionately elite, straight, white, able-bodied, cisgender men from the Global North.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Seng Aung Sein Myint.20 The work of data feminism is first to tune into how standard practices in data science serve to reinforce these existing inequalities and second to use data science to challenge and change the distribution of power..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Megan Foesch21 Underlying data feminism is a belief in and commitment to co-liberation: the idea that oppressive systems of power harm all of us, that they undermine the quality and validity of our work, and that they hinder us from creating true and lasting social impact with data science..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah beanWe wrote this book because we are data scientists and data feminists. Although we speak as a “we” in this book, and share certain identities, experiences, and skills, we have distinct life trajectories and motivations for our work on this project. If we were sitting with you right now, we would each introduce ourselves by answering the question: What brings you here today? Placing ourselves in that scenario, here is what we would have to say.Catherine: I am a hacker mama. I spent fifteen years as a freelance software developer and experimental artist, now professor, working on projects ranging from serendipitous news-recommendation systems to countercartography to civic data literacy to making breast pumps not suck. I’m here writing this book because, for one, the hype around big data and AI is deafeningly male and white and technoheroic .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCartenand the time is now to reframe that world with a feminist lens. The second reason I’m here is that my recent experience running a large, equity-focused hackathon taught me just how much people like me—basically, well-meaning liberal white people—are part of the problem in struggling for social justice. This book is one attempt to expose such workings of power, which are inside us as much as outside in the world.22Lauren: I often describe myself as a professional nerd. I worked in software development before going to grad school to study English, with a particular focus on early American literature and culture. (Early means very early—like, the eighteenth century.) As a professor at an engineering school, I now work on research projects that translate this history into contemporary contexts. For instance, I’m writing a book about the history of data visualization, employing machine-learning techniques to analyze abolitionist newspapers, and designing a haptic recreation of a hundred-year-old visualization scheme that looks like a quilt. Through projects like these, I show how the rise of the concept of “data” (which, as it turns out, really took off in the eighteenth century.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten) is closely connected to the rise of our current concepts of gender and race. So one of my reasons for writing this book is to show how the issues of racism and sexism that we see in data science today are by no means new. The other reason is to help translate humanistic thinking into practice and, in so doing, create more opportunities for humanities scholars to engage with activists, organizers, and communities.23We both strongly believe that data can do good in the world. But for it to do so, we must explicitly acknowledge that a key way that power and privilege operate in the world today has to do with the word data itself..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Seng Aung Sein Myint The word dates to the mid-seventeenth century, when it was introduced to supplement existing terms such as evidence and fact..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Tegan Lewis Identifying information as data, rather than as either of those other two terms, served a rhetorical purpose.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCarten.24 It converted otherwise debatable information into the solid basis for subsequent claims. But what information needs to become data before it can be trusted? Or, more precisely, whose information needs to become data before it can be considered as fact and acted upon?.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Peem Lerdp, Fagana Stone25 Data feminism must answer these questions, too..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }211The story that begins with Christine Darden entering the gates of Langley, passes through her sustained efforts to confront the structural oppression she encountered there, and concludes with her impressive array of life achievements, is a story about the power of data. Throughout her career, in ways large and small, Darden used data to make arguments and transform lives. But that’s not all. Darden’s feel-good biography is just as much a story about the larger systems of power that required data—rather than the belief in her lived experience.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Cynthia Lisee—to perform that transformative work. An institutional mistrust of Darden’s experiential knowledge was almost certainly a factor in Champine’s decision to create her bar chart. Champine likely recognized, as did Darden herself, that she would need the bar chart to be believed..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11In this way, the alliance between Darden and Champine, and their work together, underscores the flaws and compromises that are inherent in any data-driven project. The process of converting life experience into data always necessarily entails a reduction of that experience.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Tegan Lewis—along with the historical and conceptual burdens of the term. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11That Darden and Champine were able to view their work as a success despite these inherent constraints underscores even more the importance of listening to and learning from people whose lives and voices are behind the numbers. No dataset or analysis or visualization or model or algorithm is the result of one person working alone. Data feminism can help to remind us that before there are data, there are people—people who offer up their experience to be counted and analyzed, people who perform that counting and analysis, people who visualize the data and promote the findings of any particular project, and people who use the product in the end..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah bean There are also, always, people who go uncounted—for better or for worse.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11. And there are problems that cannot be represented—or addressed—by data alone. And so data feminism, like justice, must remain both a goal and a process, one that guides our thoughts and our actions as we move forward toward our goal of remaking the world..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }111Data and Power.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Kaiyun ZhengIt took five state-of-the-art IBM System/360 Model 75 machines to guide the Apollo 11 astronauts to the moon. Each was the size of a car and cost $3.5 million dollars. Fast forward to the present. We now have computers in the form of phones that fit in our pockets and—in the case of the 2019 Apple iPhone XR—can perform more than 140 million more instructions per second than a standard IBM System/360..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Kotaro Garvin26 That rate of change is astounding; it represents an exponential growth in computing capacity (figure 0.2a). We’ve witnessed an equally exponential growth in our ability to collect and record information in digital form—and in the ability to have information collected about us (figure 0.2b).Figure 0.2: (a) The time-series chart included in the original paper on Moore’s law, published in 1965, which posited that the number of transistors that could fit on an integrated circuit (and therefore contribute to computing capacity) would double every year. Courtesy of Gordon Moore. (b) Several years ago, researchers concluded that transistors were approaching their smallest size and that Moore’s law would not hold. Nevertheless, today’s computing power is what enabled Dr. Katie Bouman, a postdoctoral fellow at MIT, to contribute to a project that involved processing and compositing approximately five petabytes of data captured by the Event Horizon Telescope to create the first ever image of a black hole. After the publication of this photo in April 2019 showing her excitement—as one of the scientists on the large team that worked for years to capture the image—Bouman was subsequently trolled and harassed online. Courtesy of Tamy Emma Pepin/Twitter.But the act of collecting and recording data about people is not new at all. From the registers of the dead that were published by church officials in the early modern era to the counts of Indigenous populations that appeared in colonial accounts of the Americas, data collection has long been employed as a technique of consolidating knowledge about the people whose data are collected, and therefore consolidating power over their lives..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Sara Blumenstein27 The close relationship between data and power is perhaps most clearly visible in the historical arc that begins with the logs of people captured and placed aboard slave ships, reducing richly lived lives to numbers and names..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11 It passes through the eugenics movement, in the late nineteenth and early twentieth centuries, which sought to employ data to quantify the superiority of white people over all others. It continues today in the proliferation of biometrics technologies that, as sociologist Simone Browne has shown, are disproportionately deployed to surveil Black bodies..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }28When Edward Snowden, the former US National Security Agency contractor, leaked his cache of classified documents to the press in 2013, he revealed the degree to which the federal government routinely collects data on its citizens—often with minimal regard to legality or ethics..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Natalie Pei Xu29 At the municipal level, too, governments are starting to collect data on everything from traffic movement to facial expressions in the interests of making cities “smarter.”30 This often translates to reinscribing traditional urban patterns of power such as segregation, the overpolicing of communities of color, and the rationing of ever-scarcer city services..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi31But the government is not alone in these data-collection efforts; corporations do it too—with profit as their guide. The words and phrases we search for on Google, the times of day we are most active on Facebook, and the number of items we add to our Amazon carts are all tracked and stored as data—data that are then converted into corporate financial gain.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }12. The most trivial of everyday actions—searching for a way around traffic, liking a friend’s cat video, or even stepping out of our front doors in the morning—are now hot commodities. This is not because any of these actions are exceptionally interesting (although we do make an exception for Catherine’s cats) but because these tiny actions can be combined with other tiny actions to generate targeted advertisements and personalized recommendations—in other words, to give us more things to click on, like, or buy.32.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Esmeralda OrrinThis is the data economy, and corporations, often aided by academic researchers, are currently scrambling to see what behaviors—both online and off—remain to be turned into data and then monetized. Nothing is outside of datafication.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi, as this process is sometimes termed—not your search history, or Catherine’s cats, or the butt that Lauren is currently using to sit in her seat. To wit: Shigeomi Koshimizu, a Tokyo-based professor of engineering, has been designing matrices of sensors that collect data at 360 different positions around a rear end while it is comfortably ensconced in a chair.33 He proposes that people have unique butt signatures, as unique as their fingerprints. In the future, he suggests, our cars could be outfitted with butt-scanners instead of keys or car alarms to identify the driver..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Kotaro GarvinAlthough datafication may occasionally verge into the realm of the absurd, it remains a very serious issue. Decisions of civic, economic, and individual importance are already and increasingly being made by automated systems sifting through large amounts of data. For example, PredPol, a so-called predictive policing company founded in 2012 by an anthropology professor at the University of California, Los Angeles, has been employed by the City of Los Angeles for nearly a decade to determine which neighborhoods to patrol more heavily, and which neighborhoods to (mostly) ignore. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Jillian McCartenBut because PredPol is based on historical crime data and US policing practices have always disproportionately surveilled and patrolled neighborhoods of color, the predictions of where crime will happen in the future look a lot like the racist practices of the past..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }3Fagana Stone, Melinda Rossi, Amanda Christopher34 These systems create what mathematician and writer Cathy O’Neil, in Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, calls a “pernicious feedback loop,” amplifying the effects of racial bias and of the criminalization of poverty that are already endemic to the United States..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Kaiyun ZhengO’Neil’s solution is to open up the computational systems that produce these racist results. Only by knowing what goes in, she argues, can we understand what comes out. This is a key step in the project of mitigating the effects of biased data. Data feminism additionally requires that we trace those biased data back to their source. PredPol and the “three most objective data points” that it employs certainly amplify existing biases, but they are not the root cause.35 The cause, rather, is the long history of the criminalization of Blackness in the United States, which produces biased policing practices, which produce biased historical data, which are then used to develop risk models for the future..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }36 Tracing these links to historical and ongoing forces of oppression can help us answer the ethical question, Should this system exist?37 In the case of PredPol, the answer is a resounding no.Understanding this long and complicated chain reaction is what has motivated Yeshimabeit Milner, along with Boston-based activists, organizers, and mathematicians, to found Data for Black Lives, an organization dedicated to “using data science to create concrete and measurable change in the lives of Black communities.”38 Groups like the Stop LAPD Spying coalition are using explicitly feminist and antiracist methods to quantify and challenge invasive data collection by law enforcement.39 Data journalists are reverse-engineering algorithms and collecting qualitative data at scale about maternal harm.40 Artists are inviting participants to perform ecological maps and using AI for making intergenerational family memoirs.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi (figure 0.3a).41All these projects are data science. Many people think of data as numbers alone, but data can also consist of words or stories, colors or sounds, or any type of information that is systematically collected, organized, and analyzed .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }12(figures 0.3b, 0.3c).42 The science in data science simply implies a commitment to systematic methods of observation and experiment. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Peem LerdpThroughout this book, we deliberately place diverse data science examples alongside each other. They come from individuals and small groups, and from across academic, artistic, nonprofit, journalistic, community-based, and for-profit organizations. This is due to our belief in a capacious definition of data science, one that seeks to include rather than exclude and does not erect barriers based on formal credentials, professional affiliation, size of data, complexity of technical methods, or other external markers of expertise..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Cynthia Lisee Such markers, after all, have long been used to prevent women from fully engaging in any number of professional fields, even as those fields—which include data science and computer science, among many others—were largely built on the knowledge that women were required to teach themselves.43 An attempt to push back against this gendered history is foundational to data feminism, too.Throughout its own history, feminism has consistently had to work to convince the world that it is relevant to people of all genders.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Fagana Stone, Amanda Christopher. We make the same argument: that data feminism is for everybody. (And here we borrow a line from bell hooks.).d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }2Peem Lerdp, Vibha Sathish Kumar44 You will notice that the examples we use are not only about women, nor are they created only by women. That’s because data feminism isn’t only about women. It takes more than one gender to have gender inequality and more than one gender to work toward justice. Likewise, data feminism isn’t only for women. Men, nonbinary, and genderqueer people are proud to call themselves feminists and use feminist thought in their work. Moreover, data feminism isn’t only about gender. Intersectional feminists have keyed us into how race, class, sexuality, ability, age, religion, geography, and more are factors that together influence each person’s experience and opportunities in the world. Finally, data feminism is about power.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Peem Lerdp—about who has it and who doesn’t. Intersectional feminism examines unequal power.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Megan Foesch. And in our contemporary world, data is power too. Because the power of data is wielded unjustly, it must be challenged and changed..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1nyah beanData Feminism in ActionData is a double-edged sword. In a very real sense, data have been used as a weapon by those in power to consolidate their control—over places and things, as well as people. Indeed, a central goal of this book is to show how governments and corporations have long employed data and statistics as management techniques to preserve an unequal status quo. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }3Tegan Lewis, Melinda Rossi, Jillian McCartenWorking with data from a feminist perspective requires knowing and acknowledging this history. To frame the trouble with data in another way: it’s not a coincidence that the institution that employed Christine Darden and enabled her professional rise is the same that wielded the results of her data analysis to assert the technological superiority of the United States over its communist adversaries and to plant an American flag on the moon. But this flawed history does not mean ceding control of the future to the powers of the past. Data are part of the problem, to be sure. But they are also part of the solution. Another central goal of this book is to show how the power of data can be wielded back.Figure 0.3: We define data science expansively in this book—here are three examples. (a) Not the Only One by Stephanie Dinkins (2017), is a sculpture that features a Black family through the use of artificial intelligence. The AI is trained and taught by the underrepresented voices of Black and brown individuals in the tech sector. (b) Researcher Margaret Mitchell and colleagues, in “Seeing through the Human Reporting Bias” (2016), have worked on systems to infer what is not said in human speech for the purposes of image classification. For example, people say “green bananas” but not “yellow bananas” because yellow is implied as the default color of the banana. Similarly, people say “woman doctor” but do not say “man doctor,” so it is the words that are not spoken that encode the bias. (c) A gender analysis of Hollywood film dialogue, “Film Dialogue from 2,000 Screenplays Broken Down by Gender and Age,” by Hanah Anderson and Matt Daniels, created for The Pudding, a data journalism start-up (2017).To guide us in this work, we have developed seven core principles. Individually and together, these principles emerge from the foundation of intersectional feminist thought. Each of the following chapters is structured around a single principle. The seven principles of data feminism are as follows:.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Monserrat PadillaExamine power. Data feminism begins by analyzing how power operates in the world.Challenge power. Data feminism commits to challenging unequal power structures and working toward justice.Elevate emotion and embodiment. Data feminism teaches us to value multiple forms of knowledge, including the knowledge that comes from.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11 people as living, feeling bodies in the world.Rethink binaries and hierarchies. Data feminism requires us to challenge the gender binary, along with other systems of counting and classification that perpetuate oppression..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Eva Maria ChavezEmbrace pluralism. Data feminism insists that the most complete knowledge comes from synthesizing multiple perspectives, with priority .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }3Eva Maria Chavez, Fagana Stone, Tegan Lewisgiven to local, Indigenous, and experiential ways of knowing.Consider context. Data feminism asserts that data are not neutral or objective. They are the products of unequal social relations, and this context is essential for conducting accurate, ethical analysis..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Natalie Pei XuMake labor visible. The work of data science, like all work in the world, is the work of many hands. .d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda RossiData feminism makes this labor visible so that it can be recognized and valued.Each of the following chapters takes up one of these principles, drawing upon examples from the field of data science, expansively defined, to show how that principle can be put into action. Along the way, we introduce key feminist concepts like the matrix of domination (Patricia Hill Collins; see chapter 1), situated knowledge (Donna Haraway; see chapter 3), and emotional labor (Arlie Hochschild; see chapter 8), as well as some of our own ideas about what data feminism looks like in theory and practice. To this end, we introduce you to people at the cutting edge of data and justice. These include engineers and software developers, activists and community organizers, data journalists, artists, and scholars. This range of people, and the range of projects they have helped to create, is our way of answering the question: What makes a project feminist? As will become clear, a project may be feminist in content, in that it challenges power by choice of subject matter; in form, in that it challenges power by shifting the aesthetic and/or sensory registers of data communication; and/or in process, in that it challenges power by building participatory, inclusive processes of knowledge production.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }11. What unites this broad scope of data-based work is a commitment to action and a desire to remake the world..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Sara BlumensteinOur overarching goal is to take a stand against the status quo—against a world that benefits us, two white college professors, at the expense of others..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Justine Smith To work toward this goal, we have chosen to feature the voices of those who speak from the margins, whether because of their gender, sexuality, race, ability, class, geographic location, or any combination of those (and other) subject positions. We have done so, moreover, because of our belief that those with direct experience of inequality know better than we do about what actions to take next. For this reason, we have attempted to prioritize the work of people in closer proximity to issues of inequality over those who study inequality from a distance..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Natalie Pei Xu In this book, we pay particular attention to inequalities at the intersection of gender and race. This reflects our location in the United States, where the most entrenched issues of inequality have racism at their source. Our values statement, included as an appendix to this book, discusses the rationale for these authorial choices in more detail.Any book involves making choices about whose voices and whose work to include and whose voices and work to omit. We ask that those who find their perspectives insufficiently addressed or their work insufficiently acknowledged view these gaps as additional openings for conversation. Our sincere hope is to contribute in a small way to a much larger conversation, one that began long before we embarked upon this writing process and that will continue long after these pages are through.This book is intended to provide concrete steps to action for data scientists seeking to learn how feminism can help them work toward justice, and for feminists seeking to learn how their own work can carry over to the growing field of data science. It is also addressed to professionals in all fields in which data-driven decisions are being made.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Melinda Rossi, as well as to communities that want to resist or mobilize the data that surrounds them. It is written for everyone who seeks to better understand the charts and statistics that they encounter in their day-to-day lives, and for everyone who seeks to communicate the significance of such charts and statistics to others..d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Peem LerdpOur claim, once again, is that data feminism is for everyone. It’s for people of all genders. It’s by people of all genders. And most importantly: it’s about much more than gender. Data feminism is about power, about who has it and who doesn’t, and about how those differentials of power can be challenged and changed using data.d-undefined, .lh-undefined { background-color: rgba(0, 0, 0, 0.2) !important; }1Yolanda Yang. We invite you, the readers of this book, to join us on this journey toward justice and toward remaking our data-driven world.Connections1 of 2children and siblingsfilterA Translation of this Pubمقدمه: چرا علم داده به فمینیسم احتیاج داردby Catherine D'Ignazio and Lauren KleinShow DescriptionPublished on Mar 07, 2024data-feminism.mitpress.mit.eduDescriptionترجمه توسط امیرحسین پی‌براهA Translation of this PubIntroducción: por qué la ciencia de datos necesita feminismoby Catherine D'Ignazio and Lauren KleinShow DescriptionPublished on Apr 23, 2023data-feminism.mitpress.mit.eduDescriptionDataGénero (Coordinación: Mailén García. Traductoras: Ivana Feldfeber,Sofía García, Gina Ballaben, Giselle Arena y Mariángela Petrizzo. Revisión: Helena Suárez Val.Con la ayuda de Diana Duarte Salinas, Ana Amelia Letelier, y Patricia Maria Garcia Iruegas)Footnotes44LicenseCreative Commons Attribution 4.0 International License (CC-BY 4.0)Comments168 .discussion-list .discussion-thread-component.preview:hover, .discussion-list .discussion-thread-component.expanded-preview { border-left: 3px solid #2D2E2F; padding-left: calc(1em - 2px); } ?Login to discussHappy Polarbear: This passage describing the attitude of most male engineers towards their work is both painfully accurate and poignant, portraying them not as respected individuals deserving recognition for their achievements, but merely as inanimate objects, tools for calculation.?Cynthia Lisee: Such a fertile approach”?Cynthia Lisee: There is somethig immeasurable in lived experience, somethind stat would never reach. data not subject to an ethic of human relations based on "welcoming the Other" are mere abstractions and sources of violence Jamia Williams: Thank you! Reframing is essential when many of these events were deemed “riots” when it was Black folks rising up against various systems.Jamia Williams: Still happening today!?Jillian McCarten: The context in which numbers are collected?Jillian McCarten: The idea that some areas, and therefore some people don’t need to be monitored feels immoral. ?Jillian McCarten: I’ve been thinking about how it’s not what you’re doing but what your goal is, and corporations using our data to make more money off us definitely does not feel the same as collecting data on gender discrimination to stop the practice. ?Jillian McCarten: curious what examples it’s better?Jillian McCarten: It’s interesting what we need evidence to believe, and what we willingly believe without evidence ?Jillian McCarten: the word data origionaly meant to communicate that the fact is confirmed to be true- to shut down disputes ?Jillian McCarten: I love linguistic history, I’d like to learn more about this?Jillian McCarten: Yes, I’m afraid how how biases are baked into AI, and then reinforced ?Jillian McCarten: This reminds me of how priviledge is a lot less visible to those who hold it. ?Jillian McCarten: I wonder if she also had access to data on promotions across race. There’s all kinds of discrimination, and the kinds of data seen as worth collecting also reveal bias. I wonder if the white woman who collected the data focused on gender and missed other identities experiencing discrimination. ?Jillian McCarten: I appreciate how the authors directly state their most salient identities; this should be the norm. Oftentimes when I read a book like this I have to research the authors to learn their identities. Identities always influence the way we think and see the world. ?Jillian McCarten: Compelling quote about power?Jillian McCarten: It’s interesting to me that Darden’s story and the book are the two examples given so far. When I took Into to Women’s Studies in undergrad, this book was heavily criticized for mostly speaking on white feminist issues. I appreciate the author giving a more nuanced intersectional framing in the next paragraph. Jamia Williams: Love to know this! Jamia Williams: And it still far from being accomplished?Jillian McCarten: I’m curious which numbers would help communicate that, and how research can help illustrate the prevelence of this type of sexism. ?Jillian McCarten: This is a compelling example of how in our systems of power some people are seen as more valuable than others, and that likely connects to what data sources are seen as valuable.Jamia Williams: “Hidden figure” Jamia Williams: Thank you! Reframing is essential when many of these events were deemed “riots” when it was Black folks rising up against various systems.Jamia Williams: Still happening today!?Jillian McCarten: I think data is especially important in communicating how segregation persists, and how unofficial segregation is often harder to confront. ?Jillian McCarten: I think it’s important to confront the differences between the image of the US presented and the realities that people live in. I resonate with this statement- growing up I was told over and over how the US is the best place to live, and in the past few years I’ve been learning more about the historical and current harms perpetuated by our government?Jillian McCarten: So many decisions and judgement-calls that go into telling historical events, especially a quick summary like this. I’m glad that this author presents the police this way; I think a lot of authors I’ve read will ignore this reality. ?Amanda Christopher: This is a new term for me! ?Amanda Christopher: This makes me wonder how many women before her advocated for themselves, or if she was the first women at NASA to do so as her supervisor claimed. If she was not, why was her case different? What about the culture of the time at NASA allowed for her to be promoted? If she was the first, what would have happened if other women before her had the courage like Christine to speak up.?Melinda Rossi: Perfect for educators!?Melinda Rossi: I like that the authors are working to offer this knowledge to all.?Melinda Rossi: I like this. Giving credit where credit is due…what a concept!?Melinda Rossi: Ok, here’s the good-for-humanity stuff!?Melinda Rossi: The sad part is that it’s mostly used for financial gains, and not for the good of society/humanity. ?Melinda Rossi: This is sad and terrifying…and yet also seems about right. ?Melinda Rossi: I like this. Data can never capture all and that’s important to remember when we are looking at data and generalizing as if all are spoken for.?Tegan Lewis: This sums up our education system-using data and test scores to maintain the inequity in our school system.?Melinda Rossi: Yes! THIS! + 1 more...?Tegan Lewis: Data is more than numbers. What other data could be gathered in a school system??Tegan Lewis: Does it have to??Tegan Lewis: Would this be considered a misuse of data? Or more of the root of bias??Tegan Lewis: data feminism-can be used to expose inequity and challenge systems of power.Esmeralda Orrin: .Ah, capitalism,’?Tegan Lewis: gender oppression-was evident in the case of Darden?Tegan Lewis: Identity?Tegan Lewis: Would this apply to all forms of sexism, regardless of gender??Amanda Christopher: I would say absolutely, yes. I think one large misconception about feminism is that it only focuses on women, not all genders and sexes.Esmeralda Orrin: somehow I’m not surprised that men know what women are happy doing?Melinda Rossi: Finding a supportive community is key! ?Melinda Rossi: I think this part is so important. Being willing to educate themselves on issues that they might unconsciously contribute to is critical.?Melinda Rossi: We are not a monolith!?Melinda Rossi: bell hooks coming in hot with the truth.?Melinda Rossi: Hidden Figures was (sadly) the first time I had ever heard of Black women at NASA.Fagana Stone: The article could have had more power had the authors also included a note about countless studies that show invaluable contribution of diverse backgrounds and perspectives to innovation and progress. Fagana Stone: Not applicable to all cultures, as there are cultures ruled by matriarchs.?Amanda Christopher: Yes and in those cultures feminism may look differently as feminism is focused on equal rights for all genders. Many of the matriarchical cultures have more than two genders. And just about all societies have some form of gender inequalities.Fagana Stone: Wouldn’t the algorithm update itself as more surveillance data is available rather than fixate on old historical data??Melinda Rossi: That’s a good point. You would think it would be able to update with technology advancing as much as it has. + 1 more...Fagana Stone: In a capitalist country, it should be expected to have wealth inequalities… Not everyone can be wealthy nor can everyone struggle financially. Yes, there are systemic injustices, but it takes all parties involved to improve access to and understand importance of education. Dominated by two political parties running on opposing views, I can’t help but feel very pessimistic about significant progress on these issues in the near future (while the country is enacting backward looking policies and laws). Fagana Stone: “Racism” is a learned concept. Born and raised in Azerbaijan, we did not have a concept of racism, to which I was exposed to after having moved to the states. ?Amanda Christopher: Great point to add to the authors’; that it is “impossible to claim a common experience… for all women, everywhere.”Fagana Stone: It is important to note that men too struggle with sufficient paternity leave. It is critical to shift the thought from women being the only ones fit for childcare role to include men as well.Fagana Stone: Women in some states still fight for their reproductive rights!?Melinda Rossi: Fagana, that’s exactly what I was thinking. Some things change, and some things stay the same. Fagana Stone: Critical lesson in articulating the needs with the hope to identify and operationalize solutions.Fagana Stone: Excellent film! I highly recommend it.Fagana Stone: “The Soviet Union was responsible for launching the first human to space, carrying out the first spacewalk, sending the first woman to space, assembling the first modular space station in orbit around Earth (Mir) — and most of these achievements were accomplished using the same space capsule used in the 1960s.”Fagana Stone: Being from one of the former Soviet Union countries, it is also important to note that the Soviet Union had a more considerable tolerance for risk, hence the advancements mentioned in the field of astronautics. ?Rayon Ston: qKaiyun Zheng: I’ve listened to a podcast before, which is called What happens when an algorithm gets it wrong, In Machines We Trust, MIT Technology Review. It mainly talks about the technology of the use of facial recognition in public and where it can go wrong.The podcast begins with a story about a man who is accused of stealing because a computer matches his photo with a picture of the thief caught on a public camera. But in fact, it was a computer error. The computer can't tell whether the thief is a man or a black man, and the police blindly trust the computer's judgment, and moreover, he says that historically black people steal a lot. And based on the conversation in the podcast, the facial recognition technology isn't perfect, it makes mistakes and matches the wrong people. Such problems are not rare, and involve both privacy violations and potential discrimination.It made me realize that we have a lot more to do in data science.Kaiyun Zheng: We’ve learned about the differences between information and data in the very beginning lessons, and this makes me think about why we emphasize “data” instead of “info” here before the term "feminism".Kaiyun Zheng: The mention of the uneven distribution of power in this book piques my curiosity about how the topic will be addressed. I have previously read a book called "Foundation of Information," which discusses the relationship between power and information. The book suggests that when power is concentrated, the information gathered can sometimes deviate from the truth. As a result, I am curious about how data feminism ensures the authenticity and effectiveness of information collection.Additionally, the information of researching history is also mentioned in the later interview, which makes me curious about how the information of the past can be useful in the present so that it can be used as part of data feminism.Kaiyun Zheng: Intersectionality as a new term which appears after feminism is really interesting. I like how it is introduced here which talks about the example of a black woman since I thought it is the manifestation of a much broader phenomenon in the society. From Google, it is defined as "the interconnected nature of social categorizations such as race, class, and gender, regarded as creating overlapping and interdependent systems of discrimination or disadvantage" which strongly linked to the topic "feminism" (actually closer to equal rights).Each person has multiple identities. For example, I am a university student, an employee at a company, and a kid at home. These are just a few of the many labels that can be applied to an individual, including larger categories such as race, gender, and education. In an information-oriented society, labels can often obscure our understanding of the true nature of things and the individuality of a person can be overlooked. Intersectionality, while still categorizing individuals, does so in a more nuanced manner by connecting multiple labels to form a more specific and accurate representation. This can help individuals overcome challenges and reduce the oppression of vulnerable groups by dominant societal forces.Although from my personal point of view, classifying people is not a very good behavior after all, its emergence also reflects the response to various situations, so as to reduce the oppression of the dominant group of society on the vulnerable group.?Yuanxi Li: It's heartening that the value women create in terms of data has ultimately been validated by data itself, and this result has been achieved through mutual assistance among women.?Yuanxi Li: Intersectionality is an important term that shows how race, class, gender, and other individual characteristics affect with each other?Joe Masnyy: This story has shown the possibilities of this sort of advocation, though as stated early this is clearly not the norm. I appreciate the value of anecdotes such as these, although this text would benefit from hard data to show the scope and magnitude of the issue. Hopefully this is something that is explored further on in the text.?Joe Masnyy: This reality was, in the grand scheme of things, not very long ago. You could argue this still persists even today, with many STEM fields still being largely male in demographics. Even still, women tend to make less than men on average in the exact same fields.?Kotaro Garvin: We have so much more capability then before, but why does it seem like we are not making the same kind of progress? Is it not happening? or is it just unrecognized? ?Kotaro Garvin: I think this is one of the greatest ideas I have ever read, but it also shows why data is so important, everybody is unique but we can still be categorized using data. ?Justine Smith: taking a stand against system that is benefit you?Seng Aung Sein Myint: The decision making process is alway opaque. Hope there is some kind of US federal law which push the school to be a little bit transparent than before. ?Seng Aung Sein Myint: This kind of statistic of average, also make something very simple. No, I am not arguing about this data. ?Seng Aung Sein Myint: Hmm. It is strange to read now. ?Finch Brown: This is such a great line! No wonder someone has already commented on it. I have been thinking a lot recently about how subjective human experiences align and diverge, and how insufficient language and data are in describing experiences. A cool article I just read that reminds me of this is from the New Yorker: How We Should Think About Different Styles of Thinking. One main draw for me in data science is tackling the challenge of most accurately representing data and the stories it tells, given its inescapable constraints.?Yasin Chowdhury: Skill is important everywhere but in a different ways. so its good to have skills. ?Yasin Chowdhury: Without this line the entire story would not exist. But still now a days we do not see that courage specially in black women whoa really talented but chose towards non stem fields because of the difference in ratio. ?Jayri Ramirez: I believe that it is important to understand that it is more than ones gender that can affect the experiences of women. I think this statement is a good description of how there are many dimensions which affect racism and other forms of oppression. ?Roujia Wang: This shows that feminism can meet two kinds of human needs, the first is the detailed technical needs of NASA space agency, and the other is to meet the need of women also need equal status and need the same rights as men to achieve their dreams. In this process, feminism and data science are inextricably linked to each other's achievements.?Seyoon Ahn: As it was discussed in comment above, this part demonstrates the needs of feminism in data science and how not just the individuals but the society as a whole can benefit from data science with an approach of feminism. ?Roujia Wang: In that world, the stereotype of women was that women were not allowed to work in the sciences and that women were more at home with young children and taking care of the family than working outside the home. But such stereotypes prevented many talented women from having a chance to make a career out of it.?Roujia Wang: When people are misogynistic, female scientists contribute to data science research, because women can make up for the shortcomings of men in many ways. Women also use their abilities to change the perception of women in the world?Monserrat Padilla: I am really eager to learn and practice more methodically these principles. The key value in being able to analyze data holistically and seeing the subject matter as a whole at the intersections. Putting these principles into practice will allow for a more complete truth to be available while producing data and/or reading data.?Caroline Hayes: I think it is really moving that they decided to use someone as powerful as Darden’s story to start this textbook. As such a strong, smart women she was able to work in an intellectual field and challenge norms like she did in this instance. In a way she is breaking from the data so commonly released on women in and out of the work field. Instead of becoming one of the computers like 100% of the women before her, she became a part of the 1% who changed it for everyone.?Vibha Sathish Kumar: I agree, this part also resounded with me as well. It also makes you wonder about those other women who were stuck in the same situation for years. Many of those women likely didn’t have access to data or have the means to stand up for themselves in the environment set-up for them. I wonder if this issue is also relevant today, where some women do not have the opportunity to share their experience or have it accounted as data. It takes time to have others recognize their privilege and use it to bring others up - maybe data feminism could be a way to do that. ?Natalie Pei Xu: That is sad to notice that there are still many woman is being ignored and stay silence from some reasons. ?Natalie Pei Xu: First hand resource will be more helpful.?Natalie Pei Xu: This conscious awareness of “product of unequal social relation” is important while collecting, analyzing and concluding, since there is already been a lens filtered the primary source. ?Natalie Pei Xu: Besides using data as a powerful tool to pursuit justice, personal privacy is also a critical concern. ?Natalie Pei Xu: This is very inclusive and thoughtful description about feminism which makes it open up to various people among physical and mental features that aiming at the same thing: justice.Eva Maria Chavez: .Eva Maria Chavez: ecFagana Stone: If we were to focus on collecting unbiased data, then why would the authors even mention “priority” in qualifying it? + 1 more...Eva Maria Chavez: ECEva Maria Chavez: emEva Maria Chavez: collective powerEva Maria Chavez: EMCEva Maria Chavez: ?Kim Martin: test?nyah bean: -?nyah bean: -Fagana Stone: Qualitative data can be so powerful!?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: yes?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?nyah bean: -?Yolanda Yang: We should know that “We are under this situation.“?Yolanda Yang: Very personally, I am always shocked by how precise the content they suggest “what I may also interested.“ Also reminds me of Health on the phone, that it reminds us of our next coming period time, and usually also precise.?Melinda Rossi: Yes!?Yolanda Yang: People with privilege cannot recognize, even if they do, they are less likely to make any change, as this would decrease their benefit?Jillian McCarten: One quote that I think of often is “when one has held a position of privilege for so long, equality feels like oppression.” ?Yolanda Yang: “Speak“ and MeToo. Makes it visible.?Yolanda Yang: Looking for equality = we need make efforts ahead to it. Need to uncover it. ?Yolanda Yang: Reminds me of china girl or china head, that used at the beginning of analog films, those are females without names that contribute to film industry, but they were not even supposed to be presented to the audiences.?Yolanda Yang: Even though this has been desegregated for years, it still exists among people’s unconsciousness. ?Jeraldynne Gomez: systematically desgined so that women were stagnant in their positions. The disparity of power and the assertion of such system is correlated as it benefits the men who are implementing it ?Michela Banks: Important Annabel DeLair-Dobrovolny: Converting people into data as a means to assert power and dehumanize the “other”.?Michela Banks: definition ?Michela Banks: At least 50 years later. Why at this time??Michela Banks: power distance between men and women ?Michela Banks: were not recognized for intelligence ?Michela Banks: indicates perception of women in workplace?Michela Banks: note segregation during time of education?Michela Banks: describes environment?ethan chang: Shows how much has changed since then… even though can still be seen to this day.Annabel DeLair-Dobrovolny: Power imbalances contributing to the dehumanization of women in the workplace.?athmar al-ghanim: exactly!!! some individuals have such a negative connotation toward “feminism”. but here, it proves that feminism is just a group of like-minded individuals peacefully going after what they want. all feminists want is change, because for so long, there has been none. and it is about time we stopped neglecting the minority and start appreciating and uplifting them.?athmar al-ghanim: its quite sad to see how barely anything has changed in regard to men having the upper hand in workforces, especially those in STEM related fields. ?athmar al-ghanim: this passage resonates with me as it is a big fear of mine, a woman, going into STEM, that I will constantly have to fight twice as hard as a man, just to show that I am worthy of a position that I am qualified for.?Angela Li: I question how long this took and whether there was an internal fight for Darden to receive her long deserved promotion. The reason being is that I find it hard to believe that the men in power are so readily to accept change in which they lose power or control that benefits them. Earlier in this text, when Darden was working as a calculator with no respect or recognition, her supervisor said that the reason women and men lead such different career paths despite having the same credentials was because no one had ever complained. Through these quotes It sounds like the narrative being pushed is that main reason women are oppressed is because men are unaware of the the disparate treatment and effects of their actions which seems too excusable to not be questioned.Fagana Stone: I read this as the systemic discrimination against women was so normalized that it was essentially on everyone’s blindspot. Having such data showed a trend, a factual analysis that no one could ignore. Also, it takes a lot of courage to challenge the status quo, and these ladies found the way to communicate it to their superiors - through numbers!?Angela Li: I’d like to expand and connect on this idea to reaffirm the highlighted statement. I’m connecting it to to the text “Feminism is for Everybody” by Bell Hooks. In early stages of feminism there were a select few types of feminism that were identified. Of these types there were reformist and visionary feminism. reformist feminism focused mainly on equality with men in the workforce which overshadowed the original radical foundations of contemporary feminism which called for reform and restructuring of society to form a fundamentally anti-sexist nation. while white supremacist capitalist patriarchy suppressed visionary feminism, reformist feminists were also eager to silence them because they could maximize their freedom within the existing system and exploit the lower class of subordinated women.?Cynthia Lisee: Thank you for this important insight?Kat Rohrmeier: The definition of dehumanizing.?Melinda Rossi: Right? Gross.?Aneta Swianiewicz: ?Aneta Swianiewicz: ?Aneta Swianiewicz: ?Aneta Swianiewicz: data to expose inequality?Aneta Swianiewicz: ?g m: “institutional mistrust”?g m: Not only looking @ data, but the how. How was it collected? How has it been processed, and by who??Melinda Rossi: ^^^ Yes! Great point!?g m: Why data is important: challenges privileged hazard by making invisible systems visible.?Lena Zlock: Power dynamics and access to knowledge // needs an equitable foundation, clear statement of relations?Lena Zlock: DH as a countercultural phenomenon?Peem Lerdp: Target goals and audiecnes.?Peem Lerdp: Theme 2?Peem Lerdp: Theme 1?Vibha Sathish Kumar: I find it interesting that the authors mention this explicitly to the readers. A clear stated point that everyone is involved with change. ?Peem Lerdp: Insight on “science” in the phrase data science.?Peem Lerdp: Problems with distinction between what is data and what is information involve deciding who holds the power to make those distinction.Fagana Stone: It is important to add that how we interpret data matters as well.?Peem Lerdp: Def’n?Peem Lerdp: Using data to corroborate lived exp.?Peem Lerdp: Dissociating the identity of the author with the ideas discussed by the author.?Peem Lerdp: Intersectionality and its historic roots.?Peem Lerdp: History of gender inequality in workplace.?Megan Foesch: I think this is such an important lens to have when analyzing the world and what is important. Often times, we get caught up in trivial things that are not important in the bigger picture. We must remind ourselves that issues like justice, race, feminism, equality, and power are all crucial everyday issues that we must solve in order to live as a flourishing community. In order to have justice, each individual must be heard and seen which is currently not happening and needs to. ?Megan Foesch: Throughout this whole article I think that this sentence is one of the most important. The authors reflect on how data feminism is truly about power and how the lack of power between genders signifies that there is an inequality. It is important for us to acknowledge and address this inequality so women can feel as empowered, strong, and safe, as men feel. I think it is also important to point out that data feminism isn’t only for women but “men, nonbinary, and genderqueer people”. In order for a change to be made everyone must accept and acknowledge the imbalance of power that occurs in society. ?Megan Foesch: Before taking this class, I had very rarely heard the term Data Feminism, therefore this idea was somewhat new to me. I am familiar with the ideas of feminism however thinking about feminism from a scientific standpoint is one that can help reinforce popular opinions about lack of equality among genders. It is very difficult to argue something when it is science especially when focusing on systems of power and who holds that power as it is backed by scientific data and evidence.?Nick Klagge: It appears that a word or phrase is missing from the end of this sentence. Perhaps “lived experience” or something like that??Sara Blumenstein: What makes a project feminist??Sara Blumenstein: Data as “consolidating power over lives”?Sara Blumenstein: “Data feminism” as goal and process?Sara Blumenstein: Data vs. fact?Sara Blumenstein: Aggregating data to challenge institutional systems of power?will richardson: This is a very deep statement about feminism. It is also very relevent to the readings.?Sara Blumenstein: Defining “feminism” + 1 more...Data FeminismMIT PressRSSLegalPublished withCommunityData FeminismCollectionDData FeminismPubIntroduction: Why Data Science Needs FeminismcollectionData FeminismCite as D’Ignazio, C., & Klein, L. (2020). Introduction: Why Data Science Needs Feminism. In Data Feminism. Retrieved from https://data-feminism.mitpress.mit.edu/pub/frfa9szdduplicateCopymoreMore Cite OptionsTwitterRedditFacebookLinkedInEmailAuto Generated DownloadPDFWordMarkdownEPUBHTMLOpenDocumentPlain TextJATS XMLLaTeXWhat Is Data Feminism?Data and PowerData Feminism in ActiontickRelease #6Aug 25, 2021 3:54 PMdocument-shareRelease #5Aug 25, 2021 3:22 PMdocument-shareRelease #4Feb 11, 2021 10:25 AMdocument-shareRelease #3Jul 27, 2020 9:43 AMdocument-shareRelease #2Jul 27, 2020 9:42 AMdocument-shareRelease #1Mar 16, 2020 9:12 AMWhat Is Data Feminism?Data and PowerData Feminism in Action(function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'8be8b165eed78191',t:'MTcyNTU2NTI0Ni4wMDAwMDA='};var a=document.createElement('script');a.nonce='';a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();error

      This is another example of how we need more women in STEM. There are so many officially desegregated organizations. But segragation is embedded in behavior and that is what needs coaching.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      My main point of concern is the precision of dissection. The authors distinguish cells isolated from the tailbud and different areas in the PSM. They suggest that the cell-autonomous timer is initiated, as cells exit the tailbud.

      This is also relevant for the comparison of single cells isolated from the embryo and cells within the embryo. The dissection will always be less precise and cells within the PSM4 region could contain tailbud cells (as also indicated in Figure 1A), while in the analysis of live imaging data cells can be selected more precisely based on their location. This could therefore contribute to the difference in noise between isolated single cells and cells in the embryo. This could also explain why there are "on average more peaks" in isolated cells (p. 6, l. 7).

      This aspect should be considered in the interpretation of the data and mentioned at least in the discussion. (It does not contradict their finding that more anterior cells oscillate less often and differentiate earlier than more posterior ones.)

      Reviewer #1 rightly points out that selecting cells in a timelapse is more precise than manual dissection. Manual dissection is inherently variable but we believe in general it is not a major source of noise in our experiments. To control for this, we compared the results of 11 manual dissections of the posterior quarter of the PSM (PSM4) with those of the pooled PSM4 data. In general, we did not see large differences in the distributions of peak number or arrest timing that would markedly increase the variability of the pooled data above that of the individual dissections (Figure 1 – supplement figure 7). We have edited the text in the Results to highlight this control experiment (page 6, lines 13-17).

      It is of course possible that we picked up adjacent TB cells when dissecting PSM4, however the reviewer’s assertion that inclusion of TB cells “could also explain why there are "on average more peaks" in isolated cells” is incorrect. Later in the paper we show that cells from the TB have almost identical distributions to PSM4 (mean ± SD, PSM4 4.36 ± 1.44; TB 4.26 ± 1.35; Figure 4 _ supplement 1). Thus, inadvertent inclusion of TB cells while dissecting would in fact not increase the number of peaks.

      Here, the authors focus on the question of how cells differentiate. The reverse question is not addressed at all. How do cells maintain their oscillatory state in the tailbud? One possibility is that cells need external signals to maintain that as indicated in Hubaud et al. 2014. In this regard, the definition of tailbud is also very vague. What is the role of neuromesodermal progenitors? The proposal that the timer is started when cells exit the tailbud is at this point a correlation and there is no functional proof, as long as we do not understand how cells maintain the tailbud state. These are points that should be considered in the discussion.

      The reviewer asks “How do cells maintain their oscillatory state in the tailbud?”. This is a very interesting question, but as recognized by the reviewer, beyond the scope of our current paper.

      We now further emphasize the point “One possibility is that cells need external signals to maintain … as indicated in Hubaud et al. 2014” in the Discussion and added a reference to the review Hubaud and Pourquié 2014 (Signalling dynamics in vertebrate segmentation. Nat Rev Mol Cell Biol 15, 709–721 (2014). https://doi.org/10.1038/nrm3891) (page 18, lines 19-22).

      To clarify the definition of the TB, we have stated more clearly in the results (page 15, lines 8-12) that we defined TB cells as all cells posterior to the notochord (minus skin) and analyzed those that survived

      >5 hours post-dissociation, did not divide, and showed transient Her1-YFP dynamics.

      The reviewer asks: What is the role of neuromesodermal progenitors? In responding to this, we refer to Attardi et al., 2018 (Neuromesodermal progenitors are a conserved source of spinal cord with divergent growth dynamics. Development. 2018 Nov 9;145(21):dev166728. doi: 10.1242/dev.166728).

      Around the stage of dissection in zebrafish in our work, there is a small remaining group of cells characterized as NMPs (Sox2 +, Tbxta+ expression) in the dorsal-posterior wall of the TB. These NMPs rarely divide and are not thought to act as a bipotential pool of progenitors for the elongating axis, as is the case in amniotes, rather contributing to the developing spinal cord. How this particular group of cells behaves in culture is unclear as we did not subdivide the TB tissue before culturing. It would be possible to specifically investigate these NMPs regarding a role in TB oscillations, but given the results of Attardi et al., 2018 (small number of cells, low bipotentiality), we argue that it would not be significant for the conclusions of the current work. To indicate this, we included a sentence and a citation of this paper in the results towards the beginning of the section on the tail bud (page 15, lines 8-12).

      The authors observe that the number of oscillations in single cells ex vivo is more variable than in the embryo. This is presumably due to synchronization between neighbouring cells via Notch signalling in the embryo. Would it be possible to add low doses of Notch inhibitor to interfere with efficient synchronization, while at the same time keeping single cell oscillations high enough to be able to quantify them?

      It is a formal possibility that Delta-Notch signaling may have some impact on the variability in the number of oscillations. However, we argue that the significant amount of cell tracking work required to carry out the suggested experiments would not be justified, considering what has been previously shown in the literature. If Delta-Notch signaling was a major factor controlling the variability of the intrinsic program that we describe, then we would expect that in Delta-Notch mutants the anterior- posterior limits of cyclic gene expression in the PSM would extend beyond those seen in wildtype embryos. Specifically, we might expect to see her1 expression extending more anteriorly in mutants to account for the dramatic increase in the number of cells that have 5, 6, 7 and 8 cycles in culture (Fig. 1E versus Fig. 1I). However, as shown in Holley et al., 2002 (Fig. 5A, B; her1 and the notch pathway function within the oscillator mechanism that regulates zebrafish somitogenesis. Development. 2002 Mar;129(5):1175-83. doi: 10.1242/dev.129.5.1175), the anterior limit of her1 expression in the PSM in DeltaD mutants (aei) is not different to WT. Thus, Delta-Notch signaling may exert a limited control over the number of oscillations, but likely not in excess of one cycle difference.

      In the same direction, it would be interesting to test if variation is decreased, when the number of isolated cells is increased, i.e. if cells are cultured in groups of 2, 3 or 4 cells, for instance.

      This is a great proposal – however the culture setup used here is a wide-field system that doesn’t allow us to accurately follow more than one cell at a time. Cells that adhere to each other tend to crawl over each other, blurring their identity in Z. This is also why we excluded dividing cells in culture from the analysis. Experiments carried out with a customized optical setup will be needed to investigate this in the future.

      It seems that the initiation of Mesp2 expression is rather reproducible and less noisy (+/- 2 oscillation cycles), while the number of oscillations varies considerably (and the number of cells continuing to oscillate after Mesp2 expression is too low to account for that). How can the authors explain this apparent discrepancy?

      The observed tight linkage of the Mesp onset and Her1 arrest argue for a single timing mechanism that is upstream of both gene expression events; indeed, this is one of the key implications of the paper. However, the infrequent dissociation of these events observed in FGF-treated cells suggests that more than one timing pathway could be involved, although there are other interpretations. We’ve added more discussion in the text on one vs multi-timers (page 17, lines 19-23 – page 18, line 1 - 8)., see next point.

      The observation that some cells continue oscillating despite the upregulation of Mesp2 should be discussed further and potential mechanism described, such as incomplete differentiation.

      This is an infrequent (5 out of 54 cells) and interesting feature of PSM4 cells in the presence of FGF. We imagine that this disassociation of clock arrest from mesp on-set timing could be the result of alterations in the thresholds in the sensing mechanisms controlling these two processes. Alternatively - as reviewer 2 argues - it might reflect multiple timing mechanisms at work. We have added a discussion of these alternative interpretations (page 17, lines 19-23 – page 18, line 1 - 8).

      Fig. 3 supplement 3 B missing

      It’s there in the BioRxiv downloadable PDF and full text – but seems to not be included when previewing the PDF. Thanks for the heads up.

      Reviewer #2 (Public Review):

      The authors demonstrate convincingly the potential of single mesodermal cells, removed from zebrafish embryos, to show cell-autonomous oscillatory signaling dynamics and differentiation. Their main conclusion is that a cell-autonomous timer operates in these cells and that additional external signals are integrated to tune cellular dynamics. Combined, this is underlying the precision required for proper embryonic segmentation, in vivo. I think this work stands out for its very thorough, quantitative, single-cell real-time imaging approach, both in vitro and also in vivo. A very significant progress and investment in method development, at the level of the imaging setup and also image analysis, was required to achieve this highly demanding task. This work provides new insight into the biology underlying embryo axis segmentation.

      The work is very well presented and accessible. I think most of the conclusions are well supported. Here a my comments and suggestions:

      The authors state that "We compare their cell-autonomous oscillatory and arrest dynamics to those we observe in the embryo at cellular resolution, finding remarkable agreement."

      I think this statement needs to be better placed in context. In absolute terms, the period of oscillations and the timing of differentiation are actually very different in vitro, compared to in vitro. While oscillations have a period of ~30 minutes in vivo, oscillations take twice as long in vitro. Likewise, while the last oscillation is seen after 143 minutes in vivo, the timing of differentiation is very significantly prolonged, i.e.more than doubled, to 373min in vitro (Supplementary Figure 1-9). I understand what the authors mean with 'remarkable agreement', but this statement is at the risk of being misleading. I think the in vitro to in vivo differences (in absolute time scales) needs to be stated more explicitly. In fact, the drastic change in absolute timescales, while preserving the relative ones, i.e. the number of oscillations a cell is showing before onset of differentiation remains relatively invariant, is a remarkable finding that I think merits more consideration (see below).

      We have changed the text in the abstract (page 1, line 28) to clarify that the agreement is in the relative slowing, intensity increases and peak numbers.

      One timer vs. many timers

      The authors show that the oscillation clock slowing down and the timing of differentiation, i.e. the time it takes to activate the gene mesp, are in principle dissociable processes. In physiological conditions, these are however linked. We are hence dealing with several processes, each controlled in time (and thereby space). Rather than suggesting the presence of ‘a timer’, I think the presence of multiple timing mechanisms would reflect the phenomenology better. I would hence suggest separating the questions more consistently, for instance into the following three:

      a.  what underlies the slowing down of oscillations?

      b.  what controls the timing of onset of differentiation?

      c.  and finally, how are these processes linked?

      Currently, these are discussed somewhat interchangeably, for instance here: “Other models posit that the slowing of Her oscillations arise due to an increase of time-delays in the negative feedback loop of the core clock circuit (Yabe, Uriu, and Takada 2023; Ay et al. 2014), suggesting that factors influencing the duration of pre-mRNA splicing, translation, or nuclear transport may be relevant. Whatever the identity, our results indicate the timer ought to exert control over differentiation independent of the clock.”(page 14). In the first part, the slowing down of oscillations is discussed and then the authors conclude on 'the timer', which however is the one timing differentiation, not the slowing down. I think this could be somewhat misleading.

      To help distinguish the clock’s slowing & arrest from differentiation, we have clarified the text in how we describe our experiments using her1-/-; her7-/- cells (page 10, lines 9-20).

      From this and previous studies, we learn/know that without clock oscillations, the onset of differentiation still occurs. For instance in clock mutant embryos (mouse, zebrafish), mesp onset is still occurring, albeit slightly delayed and not in a periodic but smooth progression. This timing of differentiation can occur without a clock and it is this timer the authors refer to "Whatever the identity, our results indicate the timer ought to exert control over differentiation independent of the clock." (page 14). This 'timer' is related to what has been previously termed 'the wavefront' in the classic Clock and Wavefront model from 1976, i.e. a "timing gradient' and smooth progression of cellular change. The experimental evidence showing it is cell-autonomous by the time it has been laid down,, using single cell measurements, is an important finding, and I would suggest to connect it more clearly to the concept of a wavefront, as per model from 1976.

      We have been explicit about the connection to the clock & wavefront in the discussion (page 17, line 12-17).

      Regarding question a., clearly, the timer for the slowing down of oscillations is operating in single cells, an important finding of this study. It is remarkable to note in this context that while the overall, absolute timescale of slowing down is entirely changed by going from in vivo to in vitro, the relative slowing down of oscillations, per cycle, is very much comparable, both in vivo and in vivo.

      We have now pointed out the relative nature of this phenomenon in the abstract, page 1, line 28.

      To me, while this study does not address the nature of this timer directly, the findings imply that the cell-autonomous timer that controls slowing down is, in fact, linked to the oscillations themselves. We have previously discussed such a timer, i.e. a 'self-referential oscillator' mechanism (in mouse embryos, see Lauschke et al., 2013) and it seems the new exciting findings shown here in zebrafish provide important additional evidence in this direction. I would suggest commenting on this potential conceptual link, especially for those readers interested to see general patterns.

      While we posit that the timer provides positional info to the clock to slow oscillations and instruct its arrest – we do not believe that “the findings imply that the cell-autonomous timer that controls slowing down is, in fact, linked to [i.e., governed by] the oscillations themselves.”. As we show, in her1-/-; her7-/- embryos lacking oscillations, the timing / positional information across the PSM still exists as read-out by Mesp expression. Is this different positional information than that used by the clock? – possibly – but given the tight linkage between Mesp onset and the timing/positioning of clock arrest, both cell-autonomously and in the embryo, we argue that the simplest explanation is that the timing/positional information used by the clock and differentiation are the same. Please see page 10, lines 9-20, as well as the discussion (page 17, lines 19-23; page 18. Lines 1-8 ).

      We agree that the timer must communicate to the clock– but this does not mean it is dependent on the clock for positional information.

      Regarding question c., i.e. how the two timing mechanisms are functionally linked, I think concluding that "Whatever the identity, our results indicate the timer ought to exert control over differentiation independent of the clock." (page 14), might be a bit of an oversimplification. It is correct that the timer of differentiation is operating without a clock, however, physiologically, the link to the clock (and hence the dependence of the timescale of clock slowing down), is also evident. As the author states, without clock input, the precision of when and where differentiation occurs is impacted. I would hence emphasize the need to answer question c., more clearly, not to give the impression that the timing of differentiation does not integrate the clock, which above statement could be interpreted to say.

      As far as we can tell, we do not state that “without clock input, the precision of when and where differentiation occurs is impacted”, and we certainly do not want to give this impression. In contrast, as mentioned above, the her1-/-; her7-/- mutant embryo studies indicate that the lack of a clock signal does not change the differentiation timing, i.e. it does not integrate the clock. Of course, in the formation of a real somite in the embryo, the clock’s input might be expected to cause a given cell to differentiate a little earlier or later so as to be coordinated with its neighbors, for example, along a boundary. But this magnitude of timing difference is within one clock cycle at most, and does not match the large variation seen in the cultured cells that spans over many clock cycles.

      A very interesting finding presented here is that in some rare examples, the arrest of oscillations and onset of differentiation (i.e. mesp) can become dissociated. Again, this shows we deal here with interacting, but independent modules. Just as a comment, there is an interesting medaka mutant, called doppelkorn (Elmasri et al. 2004), which shows a reminiscent phenotype "the Medaka dpk mutant shows an expansion of the her7 expression domain, with apparently normal mesp expression levels in the anterior PSM.". The authors might want to refer to this potential in vivo analogue to their single cell phenotype.

      Thank you, we had forgotten this result. Although we do not agree that this result necessarily means there are two interacting modules, we have included a citation to the paper, along with a discussion of alternative explanations for the dissociation (page 18, lines 2-14).

      One strength of the presented in vitro system is that it enables precise control and experimental perturbations. A very informative set of experiments would be to test the dependence of the cell-autonomous timing mechanisms (plural) seen in isolated cells on ongoing signalling cues, for instance via Fgf and Wnt signaling. The inhibition of these pathways with well-characterised inhibitors, in single cells, would provide important additional insight into the nature of the timing mechanisms, their dependence on signaling and potentially even into how these timers are functionally interdependent.

      We agree and in future experiments we are taking advantage of this in vitro system to directly investigate the effect of signaling cues on the intrinsic timing mechanism.

    1. For mos h · 1 h h b' 1 . . t the eastern savanna s, as previous y t oug t: our 10 og1cal b t not ius h f u ere distributed everyw ere rom Morocco to the Cape.3 ncestors w . d . l d f a . f · those populations remame 1so ate rom each another for Some O en hundreds of thousands of years, cut off from their nearest tens or ev . by deserts and rainforests. Strong regional traits developed.4 relanves · The result probably would. have. struck a m~dern_ observer as some-hin more akin to a world mhab1ted by hobb1ts, giants and elves than :n:hing ;e have direct experience of today, or in the more recent St Those elements that make·up modern humans -

      This passage interests me because it highlights the deep regional differences among early human populations, suggesting they were far more distinct from each other than we are today. The idea that our ancestors might have appeared as different as "hobbits, giants, and elves" challenges my understanding of human diversity and evolution.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this work, Qiu and colleagues examined the effects of preovulatory (i.e., proestrous or late follicular phase) levels of circulating estradiol on multiple calcium and potassium channel conductances in arcuate nucleus kisspeptin neurons. Although these cells are strongly linked to a role as the "GnRH pulse generator," the goal here was to examine the physiological properties of these cells in a hormonal milieu mimicking late proestrus, the time of the preovulatory GnRH-LH surge. Computational modeling is used to manipulate multiple conductances simultaneously and support a role for certain calcium channels in facilitating a switch in firing mode from tonic to bursting. CRISPR knockdown of the TRPC5 channel reduced overall excitability, but this was only examined in cells from ovariectomized mice without estradiol treatment. The patch clamp experiments are comprehensive and overall solid but a direct demonstration of the role of these conductances in being necessary for surge generation (or at least having a direct physiological consequence on surge properties) is lacking, substantially reducing the impact of the findings.

      Strengths:

      (1) Examination of multiple types of calcium and potassium currents, both through electrophysiology and molecular biology.

      (2) Focus on arcuate kisspeptin neurons during the surge is relatively conceptually novel as the anteroventral periventricular nucleus (AVPV) kisspeptin neurons have received much more attention as the "surge generator" population.

      (3) The modeling studies allow for direct examination of manipulation of single and multiple conductances, whereas the electrophysiology studies necessarily require examination of each current in isolation. The construction of an arcuate kisspeptin neuron model promises to be of value to the reproductive neuroendocrinology field.

      We thank the reviewer for recognizing our comprehensive examination of Kiss-ARH neurons through electrophysiological, molecular and computational modeling of their activity during the preovulatory surge, which as the reviewer pointed out is “conceptually novel.”  We  have bolstered our argument that Kiss1-ARH neurons transition from synchronized firing to burst firing with the E2-mediated regulation of channel expression with the addition of new experiments. We have addressed the recommendations as follows:

      Weaknesses:

      (1) The novelty of some of the experiments needs to be clarified. This reviewer's understanding is that prior experiments largely used a different OVX+E2 treatment paradigm mimicking periods of low estradiol levels, whereas the present work used a "high E2" treatment model. However, Figures 10C and D are repeated from a previous publication by the same group, according to the figure legend. Findings from "high" vs. "low" E2 treatment regimens should be labeled and clearly separated in the text. It would also help to have direct comparisons between results from low E2 and high E2 treatment conditions.

      We have revised Figures 10C and 10D to include new findings (only) on Tac2 and Vglut2 expression in OVX and E2-treated Kiss1ARH.  Most importantly, our E2 treatment regime is clearly stated in the Methods and is exactly the same that was used previously (Qiu, eLife 2016 and Qiu, eLife 2018) for the induction of the LH surge in OVX mice (Bosch, Molecular and Cellular Endocrinology 2013) .

      (2) In multiple places, links are made between the changes in conductances and the transition from peptidergic to glutamatergic neurotransmission. However, this relationship is never directly assessed. The data that come closest are the qPCR results showing reduced Tac2 and increased Vglut2 mRNA, but in the figure legend, it appears that these results are from a prior publication using a different E2 treatment regimen.

      In the revised Figure 1, we have now included a clear depiction of the transition from synchronized firing driven by NKB signaling in OVX females to burst firing driven by glutamate in E2-treated females. All of the qPCR results in the revised manuscript are new.  We have used the same E2 treatment paradigm as previously published (Qiu, eLife 2018).

      (3) Similarly, no recordings of arcuate-AVPV glutamatergic transmission are made so the statements that Kiss1ARH neurons facilitate the GnRH surge via this connection are still only conjecture and not supported by the present experiments.

      Using a horizontal hypothalamic slice preparation, we have shown that Kiss1-ARH neurons excite GnRH neurons via Kiss1ARH glutaminergic input to Kiss1AvPV/Pen neurons (summarized in Fig. 12, Qiu, eLife 2016). We did not think that it was necessary to repeat these experiments for the current manuscript.

      (4) Figure 1 is not described in the Results section and is only tenuously connected to the statement in the introduction in which it is cited. The relevance of panels C and D is not clear. In this regard, much is made of the burst firing pattern that arises after E2 treatment in the model, but this burst firing pattern is not demonstrated directly in the slice electrophysiology examples.

      We have extensively revised Figure 1 to include new whole-cell, current clamp recordings that document burst firing  in  E2-treated, OVX females, which is now cited in the Results.

      (5) In Figure 3, it would be preferable to see the raw values for R1 and R2 in each cell, to confirm that all cells were starting from a similar baseline. In addition, it is unclear why the data for TTA-P2 is not shown, or how many cells were recorded to provide this finding.

      Before initiating photo-stimulation for each Kiss1-ARH neuron, we adjust the resting membrane potential to -70 mV, as noted  in each panel in Figure 3, through current injections. We have now included new findings on the effects of the T-channel blocker TTA-P2 on slow EPSP in the revised Figure 3. The number of cells tested with each calcium channel blocker is depicted in each of the bar graphs summarizing the effects of the blockers (Figure 3E).

      (6) In Figure 5, panel C lists 11 cells in the E2 condition but panel E lists data from 37 cells. The reason for this discrepancy is not clear.

      In Figure 5D, we measured the L-, N-, P/Q and R channel currents after pretreatment with TTA-P2 to block the T-type current, whereas in Figure 5C, we measured the total current without TTA-P2.

      (7) In all histogram figures, it would be preferable to have the data for individual cells superimposed on the mean and SEM.

      In the revised Figures we have included the individual data points for the individual neurons and animals (qPCR). 

      (8) The CRISPR experiments were only performed in OVX mice, substantially limiting interpretation with respect to potential roles for TRPC5 in shaping arcuate kisspeptin neuron function during the preovulatory surge.

      The TRPC5 channels are most  important for generating slow EPSPs when expression of NKB is high in the OVX state. Conversely, the glutamatergic response becomes more significant when the expression of NKB and TRPC5 channel are muted in the E2-treated state. Therefore, the CRISPR experiments were specifically conducted in OVX mice to maximize the effects.

      (9) Furthermore, there are no demonstrations that the CRISPR manipulations impair or alter the LH surge.

      In this manuscript, our focus is on the cellular electrophysiological activity of the Kiss1ARH neurons in OVX and E2-treated OVX females. Exploration of CRISPR manipulations related to the LH surge is certainly slated for future  experiments, but these in vivo experiments are  beyond the scope of these comprehensive cellular electrophysiological and molecular studies.

      (10) The time of day of slice preparation and recording needs to be specified in the Methods.

      We have provided the times of slice preparation and recordings in the revised Methods and Materials.

      Reviewer #2 (Public Review):

      Summary:

      Kisspeptin neurons of the arcuate nucleus (ARC) are thought to be responsible for the pulsatile GnRH secretory pattern and to mediate feedback regulation of GnRH secretion by estradiol (E2). Evidence in the literature, including the work of the authors, indicates that ARC kisspeptin coordinate their activity through reciprocal synaptic interactions and the release of glutamate and of neuropeptide neurokinin B (NKB), which they co-express. The authors show here that E2 regulates the expression of genes encoding different voltage-dependent calcium channels, calcium-dependent potassium channels, and canonical transient receptor potential (TRPC5) channels and of the corresponding ionic currents in ARC kisspeptin neurons. Using computer simulations of the electrical activity of ARC kisspeptin neurons, the authors also provide evidence of what these changes translate into in terms of these cells' firing patterns. The experiments reveal that E2 upregulates various voltage-gated calcium currents as well as 2 subtypes of calcium-dependent potassium currents while decreasing TRPC5 expression (an ion channel downstream of NKB receptor activation), the slow excitatory synaptic potentials (slow EPSP) elicited in ARC kisspeptin neurons by NKB release and expression of the G protein-associated inward-rectifying potassium channel (GIRK). Based on these results, and on those of computer simulations, the authors propose that E2 promotes a functional transition of ARC kisspeptin neurons from neuropeptide-mediated sustained firing that supports coordinated activity for pulsatile GnRH secretion to a less intense firing in glutamatergic burst-like firing pattern that could favor glutamate release from ARC kisspeptin. The authors suggest that the latter might be important for the generation of the preovulatory surge in females.

      Strengths:

      The authors combined multiple approaches in vitro and in silico to gain insights into the impact of E2 on the electrical activity of ARC kisspeptin neurons. These include patch-clamp electrophysiology combined with selective optogenetic stimulation of ARC kisspeptin neurons, reverse transcriptase quantitative PCR, pharmacology, and CRIPR-Cas9-mediated knockdown of the Trpc5 gene. The addition of computer simulations for understanding the impact of E2 on the electrical activity of ARC kisspeptin cells is also a strength.

      The authors add interesting information on the complement of ionic currents in ARC kisspeptin neurons and on their regulation by E2 to what was already known in the literature. Pharmacological and electrophysiological experiments appear of the highest standards. Robust statistical analyses are provided throughout, although some experiments (illustrated in Figures 7 and 8) do have rather low sample numbers.

      The impact of E2 on calcium and potassium currents is compelling. Likewise, the results of Trpc5 gene knockdown do provide good evidence that the TRPC5 channel plays a key role in mediating the NKB-mediated slow EPSP. Surprisingly, this also revealed an unsuspected role for this channel in regulating the membrane potential and excitability of ARC kisspeptin neurons.

      We thank the reviewer for recognizing that the “pharmacological and electrophysiological experiments appear of the highest standards” and “the addition of the computer modeling for understanding the impact of E2 on the electrical activity of ARC kisspeptin cells is also a strength.  However, we agree with the reviewer that we needed to provide a direct demonstration of “burst-like” firing of Kiss1-ARH neurons, which we have provided in Figure 1. We have addressed the other recommendations as follows:

      Weaknesses:

      The manuscript also has weaknesses that obscure some of the conclusions drawn by the authors.

      One has to do with the fact that "burst-like" firing that the authors postulate ARC kisspeptin neurons transition to after E2 replacement is only seen in computer simulations, and not in slice patch-clamp recordings. A more direct demonstration of the existence of this firing pattern, and of its prominence over neuropeptide-dependent sustained firing under conditions of high E2 would make a more convincing case for the authors' hypothesis.

      We have provided  a more direct demonstration of the existence of this firing pattern in the whole-cell current clamp experiments in the revised Figure 1.

      In addition, and quite importantly, the authors compare here two conditions, OVX versus OVX replaced with high E2, that may not reflect the physiological conditions (the diestrous [low E2] and proestrous [high E2] stages of the estrous cycle) under which the proposed transition between neuropeptide-dependent sustained firing and less intense burst firing might take place. This is an important caveat to keep in mind when interpreting the authors' findings. Indeed, that E2 alters certain ionic currents when added back to OVX females, does not mean that the magnitude of these ionic currents will vary during the estrous cycle.

      We have published that the magnitude of the slow EPSP, which is TRPC5 channel mediated, varies throughout the estrous cycle with the slow EPSP reaching a maximal amplitude during diestrus, which was significantly reduced during proestrus,  similar to that found in OVX compared to E2-treated, OVX females (Figure 2, Qiu, eLife 2016).  Moreover, TRPC5 channel mRNA expression,  similar to the peptides, is downregulated by an E2 treatment (Figure 10 this manuscript) that mimics proestrus levels of the steroid (Bosch et al., Mol Cell Endocrinology 2013). Furthermore, the magnitude of ionic currents is directly proportional to the number of ion channels expressed in the plasma membrane, which we have found correlates with mRNA expression. Therefore, it is likely that the magnitude of these ionic currents will vary during the estrous cycle.

      Lastly, the results of some of the pharmacological and genetic experiments may be difficult to interpret as presented. For example, in Figure 3, although it is possible that blockade of individual calcium channel subtypes suppresses the slow EPSP through decreased calcium entry at the somato-dendritic compartment to sustain TRPC5 activation and the slow depolarization (as the authors imply), a reasonable alternative interpretation would be that at least some of the effects on the amplitude of the slow EPSP result from suppression of presynaptic calcium influx and, thus, decreased neurotransmitter and neuropeptide secretion. Along the same lines, in Figure 12, one possible interpretation of the observed smaller slow EPSPs seen in mice with mutant TRPC5 could be that at least some of the effect is due to decreased neurotransmitter and neuropeptide release due to the decreased excitability associated with TRPC5 knockdown.

      The reviewer raises a good point, but our previous findings clearly demonstrated that chelating intracellular calcium with BAPTA in whole-cell current clamp recordings abolishes the slow EPSP and persistent firing (Qiu et al., J. Neurosci 2021), which we have noted is the  rationale for dissecting out the contribution of T, R, N, L and P/Q calcium channels to the slow EPSP in our current studies.  The revised Figure 3 also includes the effects of T-channel blocker.

      However, to further bolster the argument for the post-synaptic contribution of the calcium channels to the slow EPSP  and eliminate the potential presynaptic effects of the calcium channel blockers on the postsynaptic slow EPSP amplitude, which may result from reduced presynaptic calcium influx and subsequently decreased neurotransmitter release, we have utilized an additional strategy. Specifically, we have measured the response to the externally administered TACR3 agonist senktide under conditions in which the extracellular calcium influx, as well as neurotransmitter and neuropeptide release, are blocked (revised Figure 3).

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) The use of optogenetics in Figure 3 to trigger the slow EPSP could be better clarified in the text.

      We have clarified in the Methods the optogenetic protocol for generating the slow EPSP, which we have published previously (Qiu et al., eLife 2016; eLife 2018, J. Neurosci 2021).

      (2) The citation for Figure 4C in the text does not match what is shown in the figure.

      Figure 4C has been removed in the revised manuscript.

      (3) Figure 5 - it would be clearer to have panel D labeled as "model results" or similar to distinguish it from the slice recording data.

      Panel D has been labeled as "Model results”.

      (4) The text in lines 191-197 in the Results may be better suited to the Discussion.

      We have modified the text in order to present the new findings without the discussion points.

      (5) It is somewhat confusing to have figure panels cited out of order in the main text (e.g., 7H before 7G and 8H before 8G).

      We have edited the text to report the findings in the proper order of the panels in Figures 7 and 8.

      Reviewer #2 (Recommendations For The Authors):

      - The observations that E2 treatment of OVX mice has an effect on the magnitude of a number of ionic currents does not necessarily mean that these changes will be seen during the estrous cycle, in response to fluctuations in circulating E2 concentrations. Experiments comparing either different estrous cycle stages or OVX mice treated with low or high E2 would be required to gain insight into this question. As such, the relevance of the authors' findings (however interesting these are as they stand) to any potential physiological endocrine/reproductive state transition is questionable, in the reviewer's opinion. The authors should acknowledge this important caveat and moderate the interpretations of their findings and the conclusions of their manuscript accordingly.

      We have published that the magnitude of the slow EPSP, which is TRPC5 channel mediated, varies throughout the estrous cycle with the slow EPSP being large during diestrus and significantly reduced during proestrus,  similar to that found in OVX compared to E2-treated, OVX females (Figure 2, Qiu, eLife 2016).  Moreover, TRPC5 channel mRNA expression,  similar to the peptides, is downregulated by an E2 treatment (Figure 10 this manuscript) that mimics proestrus levels of the steroid (Bosch et al., Mol Cell Endocrinology 2013). Furthermore, the magnitude of ionic currents is directly proportional to the number of ion channels expressed in the plasma membrane, which we have found correlates with mRNA expression. Therefore, it is likely that the magnitude of these ionic currents will vary during the estrous cycle.

      - The bursting firing pattern that the authors refer to and postulate will favor glutamate release under high E2 conditions is only seen in the computer simulations, not in patch-clamp recordings in brain slices (see also comment below). This substantially weakens some of the conclusions of the manuscript. Unless the authors can convincingly demonstrate a change in ARC kisspeptin firing pattern in response to increasing E2 using electrophysiology, these conclusions should be moderated.

      We now include examples of burst firing activity under E2-treatment conditions in Figure 1 and have included summary figure (pie chart) documenting that a significant percentage of cells exhibit this activity with E2 treatment.  

      Other comments:

      - Title: "E2 elicits distinct firing patterns" is not shown in this work. As such, the title needs to be revised.

      We now show these distinct firing patterns in Figure 1, so we think the wording in the title is an accurate reflection of our findings. 

      - Abstract: some of the interpretations are overstated, in the reviewer's opinion.

      Line 23, "... elevating the whole-cell calcium current and contributing to high-frequency firing" should be moderated, as what is shown by the authors is that blockade of calcium channel subtypes suppresses the slow EPSP and associated firing, the frequency of which is not reported (see also a later comment).

      We now include examples of burst firing activity under E2-treatment conditions in Figure 1 and have modified the abstract to state “high frequency burst firing.”

      Lines 26-28, that "mathematical modeling confirmed the importance of TRPC5 channels for initiating and sustaining synchronous firing, while GIRK channels, activated by Dyn binding to kappa opioid receptors, were responsible for repolarization" is simply not what the simulations show, in the reviewer's opinion. Indeed, there is no consideration of synchronous activity in the model, which simulates the firing of a single ARC kisspeptin neuron. Further, the model shows that TRPC5 can contribute to overall excitability (firing in response to current injection, Figure 12G) and that increasing TRPC5 conductance increases firing in response to NKB while this is decreased by adding GIRK conductance to the model (Figure 13A). Therefore, considerations of the importance of TRPC5 channels in initiating synchronous firing and the role of Dyn A-induced GIRK activity should not be included in the interpretations of the mathematical simulations.

      The significance of synchronization lies in the fact that when neuronal networks synchronize, the behavior of each neuron within the network becomes identical. In such scenarios, the firing of a single neuron mirrors the activity of the entire neuronal network. Consequently, our model simulations, based on a single-cell neuronal model, can be utilized to make reliable inferences about synchronized neuronal activity.

      Lines 31-33 (also lines 92-95), that "the transition to burst firing with high, preovulatory levels of E2 facilitates the GnRH surge through its glutamatergic synaptic connection to preoptic Kiss1 neurons" is not supported by the experiments (physiologic or computational) described in the manuscript, and is, therefore, only speculative. These statements should be removed throughout the manuscript.

      Previously, we (Qiu et al., (eLife 2016) documented a direct glutamatergic projection from Kiss1-ARH neurons to Kiss1-AVPV/PeN neurons.  Moreover, Lin et al. (Frontiers Endocrinology 2021) demonstrated that low frequency stimulation of Kiss1-ARH:ChR2 neurons, that is known to only release glutamate, boosts the LH surge, and in a follow-up paper the O’Byrne lab blocked this stimulation with ionotropic glutamate antagonists (Shen et al., Frontiers in Endocrinology 2022).  We have included these references in the Introduction and Discussion, but we did not think that it was necessary to cite these papers in the Abstract.  However, we have re-worded this final statement in the Abstract to: “the transition to burst firing with high, preovulatory levels of E2 would facilitate the GnRH surge….” 

      - Introduction: the usefulness of Figure 1 is questionable. From reading the figure legend, it is the reviewer's understanding that panels A and B are published elsewhere (there is no description of methods or results in the manuscript). Further, panels C and D are meant to illustrate that ARC kisspeptin neurons display different types of firing in OVX vs E2-treated OVX mice. The legend to C indicates that the trace illustrates "synchronous firing" but shows one cell (how can this be claimed as synchronous?) - the legend to D indicates that the trace "demonstrates" burst firing in ARC kisspeptin neurons. This part of the figure is, in the reviewer's opinion, misleading because these are only two examples (no quantifications or replicates are provided) obtained by stimulating firing in two different endocrine conditions by two different agonists. The "demonstration" of differential firing patterns would require a thorough examination of firing patterns in response to current injections (as in Figure 12 E-F) or in response to the two agonists, under the different hormonal conditions.

      Figure 1 has now been completely revised to include new data documenting the different firing patterns.  The methods detailing these experiments can be found in the Material and Methods section.

      The introduction presents a rather incomplete picture of what is known regarding how ARC kisspeptin neurons might coordinate their activity to drive episodic GnRH secretion, and it omits published work showing that blockade of glutamate receptors (in particular AMPA receptors) decreases ARC kisspeptin neuron coordinated activity in the brain slices and in vivo and suppresses pulsatile GnRH/LH secretion in mice.

      If we are not mistaken, the reviewer is referring to fiber photometry recordings of GCaMP activity, which we cite in the Discussion.  However, for the Introduction we tried to “set the stage” for our studies on measuring the individual channels underlying the different firing patterns and how they are regulated by E2.

      The introduction is also quite long with extensive descriptions of previous work by the authors and in other brain areas that would be better suited for the discussion.

      Again, we are trying to rationalize why we focused on particular ion channels based on the literature.

      - Results: lines 129-132 should be moderated, as whether calcium channels increase excitability or facilitate TRPC5 channel opening has not been directly assessed here.

      High frequency optogenetic stimulation of Kiss1-ARH neurons and NKB through its cognate receptor (TACR3) activates TRPC 5 channels (Qiu et al., eLife 2016; J. Neurosci 2021). BAPTA prevents the opening of TRPC5 channels and abrogates the slow EPSP following high frequency stimulation.  Figure 3 documents that inhibition of voltage-activated calcium channels attenuates the slow EPSP, which results in a decrease in excitability.

      Lines 145-146, one limitation of this experiment is that blockade of calcium channel subtypes will not only affect calcium entry and subsequent actions of calcium on TRPC5 channels but also impair the release of neurotransmitters and neuropeptides from kisspeptin neurons. The interpretation that "calcium channels contribute to maintaining the sustained depolarization underlying the slow EPSP" needs, therefore, to be moderated as it is not possible to extract the direct contribution of calcium channels to the activation of TRPC5 channels from these experiments.

      We cited our previous findings documenting that chelating intracellular calcium with BAPTA abolishes the slow EPSP and persistent firing (Qiu et al., J Neurosci 2021).  However, to eliminate the potential effects of calcium channel blockers on the slow EPSP amplitude, which may result from reduced presynaptic calcium influx and subsequently decreased neurotransmitter and neuropeptide secretion, we adopted a different strategy by comparing responses between Senktide and Cd2+ plus Senktide. Our findings revealed that the non-selective Ca2+ channel blocker Cd2+ significantly inhibited Senk-induced inward current (Figures 3F-H).

      Panel C should be removed from Figure 4, as it is published elsewhere.

      Figure 4C has been removed.

      Lines 168-169, "...E2 treatment led to a significant increase in the peak calcium current density in Kiss1ARH neurons, which was recapitulated as predicted by our computational modeling..." How did the model "predict" this increase in calcium current density? As no information is provided in the methods or supplementary information as to how the effect of E2 was integrated into the model, the authors will need to provide additional narration in the text to explain this statement. The "T-channel inflection" referred to in the figure legend will also need to be explained. Lastly, in Figure 5C, the current density unit should be pA/pF. 

      We have added text in the supplementary information to explain how we used the qPCR and electrophysiological data to inform the model regarding the effect that E2 has on the various ionic currents and noted in the Figure 13 legend that the increase/decrease in the conductances is physiologically mediated by E2. We have eliminated the T-channel inflection point (Figure 5D) and corrected the current density label (Figure 5C).

      Lines 198-199, please clarify "E2 does not modulate calcium channel kinetics directly but rather alters the mRNA expression to increase the conductance".

      We have clarified that “that long-term E2 treatment does not modulate calcium channel kinetics but rather alters the mRNA expression to increase the calcium channel conductance” by referring to the specific figures (i.e., Figures 4, 6) in a previous sentence.

      Figures 7 and 8 titles do not accurately reflect the contents: there is nothing about repolarization in the experiments illustrated in Figure 7 or Figure 8. The sample sizes (3 to 4 cells) are also quite small for these experiments.

      We have modified the Figure titles per the reviewer’s comments and increased the cell numbers.

      The title of Figure 9 also does not fully reflect the figure's contents. Although panel G does suggest that the M current contributes to regulating the membrane potential, the reviewer's reading of this figure panel is that the fractional contribution of the M current does not vary during a short burst of action potentials. The suggestion that "KCNQ channels play a key role in repolarizing Kiss1ARH neurons following burst firing" (line 272) and the statement that "our modeling predicted that M-current contributed to the repolarization following burst firing" (line 273) should be revised accordingly.

      The point is that the M-current contributes, albeit a small fraction, to the repolarization during burst firing.

      Line 288, please indicate what figure informs this statement.

      We have revised the statement since the modeling (Figure 13) comes later in the Results.

      Line 311-313, this sentence only superficially describes the simulation, in the reviewer's opinion. Does the model inform on how TRPC5 channels/currents do that? The supplementary information indicates that there is a tone of extracellular neurokinin B embedded in the model. This is important information that should be clearly stated in the manuscript. The authors should also consider discussing the influence of this neurokinin B tone on the contribution of TRPC5 to cell excitability. As a neurokinin B tone in the extracellular space will likely alter the firing of kisspeptin neurons in the model, readers will likely need more information about all this.

      In our current ramp simulations of the model (Fig 12 G&H) there is no involvement of neurokinin B (i.e., the NKB parameter  is set to zero), and the effect on the rheobase is solely due to the decrease of the TRPC5 conductance.  In the model, TRPC5 channels are activated by intracellular calcium levels and are therefore contributing to cell excitability even in the absence of extracellular NKB. The NKB tone is used for the simulations presented in Figure 13 where we vary the TRPC5 conductance under saturating levels of extracellular NKB.

      Lines 316-318 also read as quite superficial. More explanations of what is illustrated in Figure 13 are needed. In particular, it is unclear from the methods and supplementary information what the different ratios of conductances in OVX+E2 vs in OVX are and how they were varied in the model. Furthermore, it is unclear to the reviewer how the outcome of these simulations matches the authors' postulate that E2 enables a transition to a burst firing pattern that favors glutamate release. Looking at simulated firing in Figure 13B, E2 (by increasing calcium conductances) would tend to enable high-frequency firing within bursts (nearing 50 Hz by eye) and high burst rates (approximately 4 bursts per second), which the reviewer would argue might be expected to cause significant neuropeptide release in addition to that of glutamate.

      We have added to the text: “Furthermore, the burst firing of the OVX+E2 parameterized model was supported by elevated h- and Ca 2+-currents (Figure 13B) as well as by the high conductance of Ca2+ channels relative to the conductance of TRPC5 channels (Figure 13C).” We have also provided in the Supplemental Information (Table of Model Parameters) the specific conductances in the OVX and OVX+E2 state and how they are varied to produce the model simulations.

      Granted the high frequency firing during a burst could release peptide, but in the E2-treated, OVX females the expression of the peptides are at “rock bottom.”  Therefore, the sustained high frequency firing during the slow EPSP in the OVX state would generate maximum peptide release.

      In Figure 13C, the reviewer is unclear on the ranges of TRPC5 conductances shown. The in vitro experiments suggest that E2 suppresses Trpc5 gene expression and might suppress TRPC5 currents. The ratio of gTRPC5(OVX+E2)/gTRPC5(OVX) should, thus, be <1.0. This is not represented in the parameter space provided, making the interpretation of this simulation difficult. Please clarify what the effect of decreasing gTRPC5 will be on firing patterns in the model.

      Thank you for pointing this typographical error.  The ratio should be gTRPC5 (OVX)/TRPC5(OVX + E2) for the X-axis.

      - Discussion: many statements and conclusions are overreaching and need to be revised; for example lines 320-322, 329-330, 335-338, 369, 371-373, 391-394, 463-464, and 489-494;

      We have tempered these statements, so they are not “overreaching.”

      Lines 489-494: the authors should integrate published observations that i) ablation of ARC kisspeptin neurons results in increased LH surges in mice and rats and that ii) optogenetic stimulation of ARC kisspeptin fibers in the POA is only effective at increasing LH secretion in a surge-like manner when done at high frequencies (20 Hz), in their discussion of the role of ARC kisspeptin neurons and their firing patterns in the preovulatory surge.

      We have included the paper from the O’Byrne lab (Shen et al. Frontiers in Endocrinology 2022) in the Discussion. However, the Mittleman-Smith paper (Endocrinology, 2016) ablating KNDy neurons using NK3-saporin not only targeted KNDy neurons but other arcuate neurons that express NK3 receptors.  Therefore, we have not cited it in the Discussion.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      Major comments: 

      My main concern about the manuscript is the extent of both clinical and statistical heterogeneity, which complicates the interpretation of the results. I don't understand some of the antibiotic comparisons that are included in the systematic review. For instance the study by Paul et al (50), where vancomycin (as monotherapy) is compared to co-trimoxazole (as combination therapy). Emergence (or selection) of co-trimoxazole in S. aureus is in itself much more common than vancomycin resistance. It is logical and expected to have more resistance in the co-trimoxazole group compared to the vancomycin group, however, this difference is due to the drug itself and not due to co-trimoxazole being a combination therapy. It is therefore unfair to attribute the difference in resistance to combination therapy. Another example is the study by Walsh (71) where rifampin + novobiocin is compared to rifampin + co-trimoxazole. There is more emergence of resistance in the rifampin + co-trimoxazole group but this could be attributed to novobiocin being a different type of antibiotic than co-trimoxazole instead of the difference being attributed to combination therapy. To improve interpretation and reduce heterogeneity my suggestion would be to limit the primary analyses to regimens where the antibiotics compared are the same but in one group one or more antibiotic(s) are added (i.e. A versus A+B). The other analyses are problematic in their interpretation and should be clearly labeled as secondary and their interpretation discussed. 

      Thank you for raising these important points and highlighting the need for clarification. We understand that the reviewer has concerns regarding the following points:

      (1) The structure of presenting our analyses, i.e. main analyses and sub-group analyses and their corresponding discussion and interpretation

      Our primary interest was whether combining antibiotics has an overarching effect on resistance and to identify factors that explain potential differences of the effect of combining antibiotic across pathogens/drugs. Therefore, pooling all studies, and thereby all combinations of antibiotics, is one of our main analyses. The decision to pool all studies that compare a lower number of antibiotics to a higher number of antibiotics was hence predefined in our previously published study protocol (PROSPERO CRD42020187257).

      We indeed, find that heterogeneity is high in our statistical analyses. As planned in our study protocol, we did perform several prespecified sub-group analyses and added additional ones. We now emphasize that several sub-group analyses were performed to investigate heterogeneity (L 119ff): “The overall pooled estimates are based on studies that focus on various clinical conditions/pathogens and compare different antibiotics treatments. To explore the impact of these and other potential sources of heterogeneity on the resistance estimates we performed various sub-group analyses and metaregression.” 

      The performed sub-group analyses specifically focused on specific pathogens/clinical conditions (figure 3) or explored heterogeneity due to different antibiotics in comparator arms – as suggested by the reviewer (figure 3B, SI section 6). We find that the heterogeneity remains high even if only resistances to antibiotics common to both arms are considered (SI section 6.1.8). With this analysis we excluded comparisons of different antibiotics (e.g., A vs B+C), such as those between vancomycin and cotrimoxazole named by the reviewer. While we aimed to explore heterogeneity and investigate potential factors affecting the effect of combining antibiotic on resistance, limitations arose due to limited evidence and the nature of data provided by the identified studies. Therefore, interpretability remains also limited for the subgroup analyses, which we highlight in the discussion. (L 186 ff: We accounted for many sources of heterogeneity using stratification and meta-regression, but analyses were limited by missing information and sparse data.) Further, specific subgroup analyses are discussed in more detail in the SI.

      (2) Difference in resistance development due to the type of the antibiotics or due to combination therapy?

      The reviewer raises an important point, which we also try to make: future studies should be systematically designed to compare antibiotic combination therapy, i.e. identical antibiotics in treatment arms should be used, except for additional antibiotics used in both treatment arms. We already mentioned this point in our discussion but highlight this now by emphasizing how many studies did not have identical antibiotics in their treatment arms. We write in L194ff: “19 (45%) of our included studies compared treatment arms with no antibiotics in common, and 22 studies (52%) had more than one antibiotic not identical in the treatment arms (table 1). To better evaluate the effect of combination therapy, especially more RCTs would be needed where the basic antibiotic treatment is consistent across both treatment arms, i.e. the antibiotics used in both treatment arms should be identical, except for the additional antibiotic added in the comparator arm (table 1).”

      Furthermore, we investigated the importance of the type of antibiotics with several subgroup analyses (e.g. SI sections 6.1.8 and 6.1.10). We now further highlight the concern of the type of antibiotics in the result section of the main manuscript, where we discuss the sub-group analysis with no common antibiotics in the treatment arms 131 ff: “Furthermore, a lower number of antibiotics performed better than a higher number if the compared treatment arms had no antibiotics in common (pooled OR 4.73, 95% CI 2.14 – 10.42; I2\=37%, SI table S3), which could be due to different potencies or resistance prevalences of antibiotics as discussed in SI (SI section 6.1.10).” As mentioned above we also perform sub-group analyses, where only resistances of antibiotics common to both arms are considered (SI section 6.1.8). However, as discussed in the corresponding sections, the systematic assessment of antibiotic combination therapy remains challenging as not all resistances against antibiotics used in the arms were systematically measured and reported. Furthermore, the power of these sub-group analyses is naturally a concern, as they include fewer studies. 

      Another concern is about the definition of acquisition of resistance, which is unclear to me. If for example meropenem is administered and the follow-up cultures show Enterococcus species (which is intrinsically resistant to meropenem), does this constitute acquisition of resistance? If so, it would be misleading to determine this as an acquisition of resistance, as many people are colonized with Enterococci and selection of Enterococci under therapy is very common. If this is not considered as the acquisition of resistance please include how the acquisition of resistance is defined per included study. Table S1 is not sufficiently clear because it often only contains how susceptibility testing was done but not which antibiotics were tested and how a strain was classified as resistant or susceptible. 

      Thank you for pointing out this potential ambiguity. The definition of acquisition of resistance reads now (L 275 ff): “A patient was considered to have acquired resistance if, at the follow-up culture, a resistant bacterium (as defined by the study authors) was detected that was not present in the baseline culture.” We also changed the definition accordingly in the abstract (L 36 ff). We hope that the definition of acquisition is now clearer. Our definition of “acquisition of resistance” is agnostic to bacterial species and hence intrinsically resistant species, as the example raised by the reviewer, can be included if they were only detected during the follow-up culture by the studies. Generally, it was not always clear from the studies, which pathogens were screened for and whether the selection of intrinsically resistant bacteria was reported or not. Therefore, we rely on the studies' specifications of resistant and non-resistant without further distinction from our side, i.e. classifying data into intrinsic and non-intrinsic resistance. Overall, the outcome “acquisition of resistance” can be interpreted as a risk assessment for having any resistant bacterium during or after treatment. In contrast, the outcome “emergence of resistance” is more rigorous, demanding the same species to be detected as more resistant during or after treatment.

      The information, which antibiotic susceptibility tests were performed in each individual study can be found in the main text in table 1. However, we agree that this information should be better linked and highlighted again in table S1. We therefore now refer to table 1 in the table description of table S1. L134 ff.: “See table 1 in the main text for which antibiotics the antibiotics tested and reported extractable resistance data”. Furthermore, we added the breakpoints for resistant and susceptible classification if specifically stated in the main text of the study. However, we did not do further research into old guidelines, manufactures manuals or study protocols in case the breakpoints are not specifically stated in the main text as the main goal of this table, in our opinion, is to show a justification, why the studies could be considered for a resistance outcome. We therefore decided against further breakpoint investigations for studies, where the breakpoint is not specifically stated in the main text. 

      Line 85: "Even though within-patient antibiotic resistance development is rare, it may contribute to the emergence and spread of resistance." 

      Depending on the bug-drug combination, there is great variation in the propensity to develop within-patient antibiotic resistance. For example: within-patient development of ciprofloxacin resistance in Pseudomonas is fairly common while within-patient development of methicillin resistance in S. aureus is rare. Based on these differences, large clinical heterogeneity is expected and it is questionable where these studies should be pooled. 

      We agree that our formulation neglects differences in prevalence of within-host resistance emergence depending on bug-drug combinations. We changed our statement in L 86 to: “Within-patient antibiotic resistance development, even if rare, may contribute to the emergence and spread of resistance.”

      Line 114: "The overall pooled OR for acquisition of resistance comparing a lower number of antibiotics versus a higher one was 1.23 (95% CI 0.68 - 2.25), with substantial heterogeneity between studies (I2=77.4%)" 

      What consequential measures did the authors take after determining this high heterogeneity? Did they explore the source of this large heterogeneity? Considering this large heterogeneity, do the authors consider it appropriate to pool these studies?

      Thank you for highlighting this lack of clarity. As mentioned above, we now highlight that we performed several subgroup analyses to investigate heterogeneity. (L 116ff): “The overall pooled estimates are based on studies that focus on various clinical conditions/pathogens and compare different antibiotics treatments. To explore the impact of these and other potential sources of heterogeneity on the resistance estimates we performed various subgroup analyses and meta-regression.” Nevertheless, these analyses faced limitations due to the scarcity of evidence and often still showed a high amount of heterogeneity. Given the lack of appropriate evidence, it is hard to identify the source of heterogeneity. The decision to pool all studies was pre-specified in our previously published study protocol (PROSPERO CRD42020187257) and was motivated by the question whether there is a general effect of combination therapy on resistance development or identify factors that explain potential differences of the effect of combination therapy across bug-drug combinations. Therefore, we think that the presentation of the overall pooled estimate is appropriate, as it was predefined, and potential heterogeneity is furthermore explored in the subgroup analyses. 

      Reviewer #1 (Recommendations For The Authors): 

      I want to congratulate the investigators for the rigorous approach followed and the - in my opinion - correct interpretation of the data and analysis. The disappointing outcome is independent of the quality of the approach used. Yet, the consequences of that outcome are rather limited, and will not be surprising for - at least - some in the field of antibiotic resistance. 

      Thank you for your positive and differentiated feedback.

      Reviewer #2 (Recommendations For The Authors): 

      Line 93: "The screening of the citations of the 41 studies identified one additional eligible study, for a total of 42 studies". 

      Why was this study missed in the search strategy? 

      What is the definition of "quasi-RCTs"? Why were these included in the analysis? 

      Thank you for pointing out this lack of clarity. The additional study, which was found through screening the references of included studies, was not identified with our search strategy as neither the abstract nor database specific identifiers provided any indications that resistance was measured in this study. We added an explanation in the supplementary materials L 792 ff. and refer to this explanation in the main manuscript (L 95). 

      Quasi-randomized trials are trials that use allocation methods, which are not considered truly random. We added this specification in L 95. It now reads: “….two quasi-RCTs, where the allocation method used is not truly random” and in L 252 ff: “Studies were classified as quasi-RCTs if the allocation of participants to study arms was not truly random.” For instance, the study Macnab et al. (1994) assigned patients alternately to the treatment arms. Quasi-randomized controlled trials can lead to biases and especially old studies are more likely to have used quasi-random allocation methods. This can also be seen in our study, where the two quasi-randomized controlled trials were published in 1994 and 1997. The bias is considered in the risk of bias assessment and in our conducted sensitivity analysis regarding the impact of risk of bias on our estimates (supplementary information sections 3.0 and 4.2). Furthermore, one of the two previous conducted meta-analyses comparing beta-lactam monotherapy to beta-lactam and aminoglycoside, which assessed resistance development also included quasi-randomized controlled trials Paul et al 2014. Overall, while designing the study, we decided to include quasi-randomized controlled trials to increase statistical power as we expected that limited statistical power might be a concern and decided to assess potential biases in the risk of bias assessment.  

      Line 100: "Consequently, most studies did not have the statistical power to detect a large effect on within-patient resistance development (figure 2 B, SI p 14).". 

      Small studies actually have more power to detect large effects while smaller power to detect small effects. Please rephrase. 

      Thank you for pointing out this lack of clarity. We rephrased the sentence in order to emphasize our point that the studies are underpowered even if we assume in our power analysis a large effect on resistance development between treatment arms. In this context “the small” studies include too few patients to detect a large difference in resistance development. As resistance development is a rare event, generally studies have to include a larger number of patients to estimate the effect of intervention. We rephrased the sentence in L 101ff to: “Consequently, most studies did not have the statistical power to detect differences in within-patient resistance development even if we assume that the effect on resistance development is large between treatment arms.”

      Line 108: "... and prophylaxis for blood cancer patients with four studies (10%) respectively.". 

      I would suggest using the medical term hematological malignancy patients. 

      Thank you for the suggestion, we changed it as suggested to hematological malignancy patients, also accordingly in the figures, and table 1.

      Line 117: "Since the results for the two resistance outcomes are comparable, our focus in the following is on the acquisition of resistance". 

      The first OR is 1.23 and the second is 0.74, why do you consider these outcomes as comparable? 

      Thank you for pointing out our unprecise formulation. Due to the lack of power the exact estimates need to be interpreted with care. Here, we wanted to make the point that qualitatively the results of both outcomes do not differ in the sense that our analysis shows no substantial difference between a higher and a lower number of antibiotics. We rephrased the sentence to be more precise (L 123ff): “The results for the two resistance outcomes are qualitatively comparable in the sense that individual estimates may differ, but show similar absence of evidence to support either the benefit, harm or equivalence of treating with a higher number of antibiotics. Therefore, our …”. More detailed discussion about differences in estimates can be found in the SI, when the estimates of emergence of resistance are presented (e.g. SI section 2.1).

      Line 123: "Furthermore, a lower number of antibiotics performed better than a higher number if the compared treatment arms had no antibiotics in common (pooled OR 4.73, 95% CI 2.14 - 10.42; I 2 =37%, SI p 7).". 

      How do you explain this? What does this mean? 

      We now added a more detailed explanation in the supplement (L 376ff.): “The result that if the treatment arms had no antibiotics in common a lower number of antibiotics performed better than a higher number of antibiotics could be due to different potencies of antibiotics or resistance prevalences. Further, there could be a bias to combine less potent antibiotics or antibiotics with higher resistance prevalence to ensure treatment efficacy, which couldlead to higher chances to detect resistances in the treatment arm with higher number of antibiotics, e.g. by selecting pre-existing resistance due to antibiotic treatment (see also section 6.1.9).” We furthermore already specifically mention this point in the main manuscript and refer then to the detailed explanation in the SI (L134 ff, “which could be due to different potencies or resistance prevalences of antibiotics as discussed in SI (SI section 6.1.10)”)

      Overall, we want to point out that these results need to be interpreted with caution as overall the statistical power is limited to confidently estimate the difference in effect of a higher and lower number of antibiotics.

      Line 125: ". In contrast, when restricting the analysis to studies with at least one common antibiotic in the treatment arms are pooled there was little evidence of a difference (pooled OR 0.55, 95% CI 0.28 - 1.07". 

      The difference was not statistically significant but there does seem to be an indication of a difference, please rephrase. 

      We rephrased the sentence to (L135 ff.): “In contrast, when restricting the analysis to studies with at least one common antibiotic in the treatment arms we found no evidence of a difference, only a weak indication that a higher number of antibiotics performs better (pooled OR 0.55, 95% CI 0.28 – 1.07; I2 \=74%, figure 3B).” 

      Line 190: "Similarly, today, relevant cohort studies could be analysed collaboratively using various modern statistical methods to address confounding by indication and other biases (66, 67)". 

      However, residual confounding by indication is likely. Please also mention the disadvantages of observational studies compared to RCTs. 

      We now highlight that causal inference with observational data comes with its own challenges and stress that randomized controlled trials are still considered the gold standard. L 204ff now reads: “However, even with appropriate causal inference methods, residual confounding cannot be excluded when using observational data (67). Therefore, will remain the gold standard to estimate causal relationships.”

      Line 230: "Gram-negative bacteria have an outer membrane, which is absent in grampositive bacteria for instance, therefore intrinsic resistance against antibiotics can be observed in gram-negative bacteria (11)". 

      Intrinsic resistance is not unique for Gram-negative bacteria but also exists for Grampositive bacteria. 

      We agree with the reviewer that intrinsic resistance is not unique to gram-negative bacteria and refined our writing. We additionally added that differences between gram-negative and gram-positive bacteria are not only to be expected due to differing intrinsic resistances but also due to potential differences in the mechanistic interactions of antibiotics, i.e., synergy or antagonism. The paragraph reads now (SI L289): “The gram status of a bacterium may potentially determine how effective an antibiotic, or an antibiotic combination is. Differences between gram-negative and gram-positive bacteria such as distinct bacterial surface organisation can lead to specific intrinsic resistances of gram-negative and grampositive bacteria against antibiotics (55). These structural differences can lead to varying effects of antibiotic combinations between gram-negative and gram-positive bacteria (56).”

    1. Author response:

      The following is the authors’ response to the original reviews.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Line 127. Provide a few more words describing the voltage protocol. To the uninitiated, panels A and B will be difficult to understand. "The large negative step is used to first close all channels, then probe the activation function with a series of depolarizing steps to re-open them and obtain the max conductance from the peak tail current at -36 mV. "

      We have revised the text as suggested (revision lines 127 to Line 131): “From a holding potential within the gK,L activation range (here –74 mV), the cell is hyperpolarized to –124 mV, negative to EK and the activation range, producing a large inward current through open gK,L channels that rapidly decays as the channels deactivate. We use the large transient inward current as a hallmark of gK,L. The hyperpolarization closes all channels, and then the activation function is probed with a series of depolarizing steps, obtaining the max conductance from the peak tail current at –44 mV (Fig. 1A).”

      Incidentally, why does the peak tail current decay? 

      We added this text to the figure legend to explain this: “For steps positive to the midpoint voltage, tail currents are very large. As a result, K+ accumulation in the calyceal cleft reduces driving force on K+, causing currents to decay rapidly, as seen in A (Lim et al., 2011).”

      The decay of the peak tail current is a feature of gK,L (large K+ conductance) and the large enclosed synaptic cleft (which concentrates K+ that effluxes from the HC). See Govindaraju et al. (2023) and Lim et al. (2011) for modeling and experiments around this phenomenon.

      Line 217-218. For some reason, I stumbled over this wording. Perhaps rearrange as "In type II HCs absence of Kv1.8 significantly increased Rin and tauRC. There was no effect on Vrest because the conductances to which Kv1.8 contributes, gA and gDR activate positive to the resting potential. (so which K conductances establish Vrest???). 

      We kept our original wording because we wanted to discuss the baseline (Vrest) before describing responses to current injection.

      Vrest is presumably maintained by ATP-dependent Na/K exchangers (ATP1a1), HCN, Kir, and mechanotransduction currents. Repolarization is achieved by delayed rectifier and A-type K+ conductances in type II HCs.

      Figure 4, panel C - provides absolute membrane potential for voltage responses. Presumably, these were the most 'ringy' responses. Were they obtained at similar Vm in all cells (i.e., comparisons of Q values in lines 229-230). 

      We added the absolute membrane potential scale. Type II HC protocols all started with 0 pA current injection at baseline, so they were at their natural Vrest, which did not differ by genotype or zone. Consistent with Q depending on expression of conductances that activate positive to Vrest, Q did not co-vary with Vrest (Pearson’s correlation coefficient = 0.08, p = 0.47, n= 85).

      Lines 254. Staining is non-specific? Rather than non-selective? 

      Yes, thanks - Corrected (Line 264).

      Figure 6. Do you have a negative control image for Kv1.4 immuno? Is it surprising that this label is all over the cell, but Kv1.8 is restricted to the synaptic pole? 

      We don’t have a null-animal control because this immunoreactivity was done in rat. While the cuticular plate staining was most likely nonspecific because we see that with many different antibodies, it’s harder to judge the background staining in the hair cell body layer. After feedback from the reviewers, we decided to pull the KV1.4 immunostaining from the paper because of the lack of null control, high background, and inability to reproduce these results in mouse tissue. In our hands, in mouse tissue, both mouse and rabbit anti-KV1.4 antibodies failed to localize to the hair cell membrane. Further optimization or another method could improve that, but for now the single-cell expression data (McInturff et al., 2018) remain the strongest evidence for KV1.4 expression in murine type II hair cells.

      Lines 400-404. Whew, this is pretty cryptic. Expand a bit? 

      We simplified this paragraph (revision lines 411-413): “We speculate that gA and gDR(KV1.8) have different subunit composition: gA may include heteromers of KV1.8 with other subunits that confer rapid inactivation, while gDR(KV1.8) may comprise homomeric KV1.8 channels, given that they do not have N-type inactivation .”

      Line 428. 'importantly different ion channels'. I think I understand what is meant but perhaps say a bit more. 

      Revised (Line 438): “biophysically distinct and functionally different ion channels”.

      Random thought. In addition to impacting Rin and TauRC, do you think the more negative Vrest might also provide a selective advantage by increasing the driving force on K entry from endolymph? 

      When the calyx is perfectly intact, gK,L is predicted to make Vrest less negative than the values we report in our paper, where we have disturbed the calyx to access the hair cell (–80, Govindaraju et al., 2023, vs. –87 mV, here). By enhancing K+ accumulation in the calyceal cleft, the intact calyx shifts EK—and Vrest—positively (Lim et al., 2011), so the effect on driving force may not be as drastic as what you are thinking.

      Reviewer #2 (Recommendations For The Authors):

      (1) Introduction: wouldn't the small initial paragraph stating the main conclusion of the study fit better at the end of the background section, instead of at the beginning? 

      Thank you for this idea, we have tried that and settled on this direct approach to let people know in advance what the goals of the paper are.

      (2) Pg.4: The following sentence is rather confusing "Between P5 and P10, we detected no evidence of a non-gK,L KV1.8-dependent.....". Also, Suppl. Fig 1A seems to show that between P5 and P10 hair cells can display a potassium current having either a hyperpolarised or depolarised Vhalf. Thus, I am not sure I understand the above statement. 

      Thank you for pointing out unclear wording. We used the more common “delayed rectifier” term in our revision (Lines 144-147): “Between P5 and P10, some type I HCs have not yet acquired the physiologically defined conductance, gK,L.. N effects of KV1.8 deletion were seen in the delayed rectifier currents of immature type I HCs (Suppl. Fig. 1B), showing that they are not immature forms of the Kv1.8-dependent gK,L channels. ”

      (3) For the reduced Cm of hair cells from Kv1.8 knockout mice, could another reason be simply the immature state of the hair cells (i.e. lack of normal growth), rather than less channels in the membrane? 

      There were no other signs to suggest immaturity or abnormal growth in KV1.8–/– hair cells or mice. Importantly, type II HCs did not show the same Cm effect.

      We further discussed the capacitance effect in lines 160-167: “Cm scales with surface area, but soma sizes were unchanged by deletion of KV1.8 (Suppl. Table 2). Instead, Cm may be higher in KV1.8+/+ cells because of gK,L for two reasons. First, highly expressed trans-membrane proteins (see discussion of gK,L channel density in Chen and Eatock, 2000) can affect membrane thickness (Mitra et al., 2004), which is inversely proportional to specific Cm. Second, gK,L could contaminate estimations of capacitive current, which is calculated from the decay time constant of transient current evoked by small voltage steps outside the operating range of any ion channels. gK,L has such a negative operating range that, even for Vm negative to –90 mV, some gK,L channels are voltage-sensitive and could add to capacitive current.”

      (4) Methods: The electrophysiological part states that "For most recordings, we used .....". However, it is not clear what has been used for the other recordings.

      Thanks for catching this error, a holdover from an earlier ms. version.  We have deleted “For most recordings” (revision line 466).

      Also, please provide the sign for the calculated 4 mV liquid junction potential. 

      Done (revision line 476).

      Reviewer #3 (Recommendations For The Authors): 

      (1) Some of the data in panels in Fig. 1 are hard to match up. The voltage protocols shown in A and B show steps from hyperpolarized values to -71mV (A) and -32 mV (B). However, the value from A doesn't seem to correspond with the activation curve in C.

      Thank you for catching this.  We accidentally showed the control I-X curve from a different cell than that in A. We now show the G-V relation for the cell in A.

      Also the Vhalf in D for -/- animals is ~-38 mV, which is similar to the most positive step shown in the protocol.

      The most positive step in Figure 1B is actually –25 mV. The uneven tick labels might have been confusing, so we re-labeled them to be more conventional.

      Were type I cells stepped to more positive potentials to test for the presence of voltage-activated currents at greater depolarizations? This is needed to support the statement on lines 147-148. 

      We added “no additional K+ conductance activated up to +40 mV” (revision line 149-150).  Our standard voltage-clamp protocol iterates up to ~+40 mV in KV1.8–/– hair cells, but in Figure 1 we only showed steps up to –25 mV because K+ accumulation in the synaptic cleft with the calyx distorts the current waveform even for the small residual conductances of the knockouts. KV1.8–/– hair cells have a main KV conductance with a Vhalf of ~–38 mV, as shown in Figure 1, and we did not see an additional KV conductance that activated with a more positive Vhalf up to +40 mV.

      (2) Line 151 states "While the cells of Kv1.8-/- appeared healthy..." how were epithelia assessed for health? Hair cells arise from support cells and it would be interesting to know if Kv1.8 absence influences supporting cells or neurons. 

      We added our criteria for cell health to lines 477-479: “KV1.8–/– hair cells appeared healthy in that cells had resting potentials negative to –50 mV, cells lasted a long time (20-30 minutes) in ruptured patch recordings, membranes were not fragile, and extensive blebbing was not seen.”

      Supporting cells were not routinely investigated. We characterized calyx electrical activity (passive membrane properties, voltage-gated currents, firing pattern) and didn’t detect differences between +/+, +/–, and –/– recordings (data not shown). KV1.8 was not detected in neural tissue (Lee et al., 2013). 

      (3) Several different K+ channel subtypes were found to contribute to inner hair cell K+ conductances (Dierich et al. 2020) but few additional K+ channel subtypes are considered here in vestibular hair cells. Further comments on calcium-activated conductances (lines 310-317) would be helpful since apamin-sensitive SK conductances are reported in type II hair cells (Poppi et al. 2018) and large iberiotoxin-sensitive BK conductances in type I hair cells (Contini et al. 2020). Were iberiotoxin effects studied at a range of voltages and might calcium-dependent conductances contribute to the enhanced resonance responses shown in Fig. 4? 

      We refer you to lines 310-317 in the original ms (lines 322-329 in the revised ms), where we explain possible reasons for not observing IK(Ca) in this study.

      (4) Similar to GK,L erg (Kv11) channels show significant Cs+-permeability. Were experiments using Cs+ and/or Kv11 antagonists performed to test for Kv11? 

      No. Hurley et al. (2006) used Kv11 antagonists to reveal Kv11 currents in rat utricular type I hair cells with perforated patch, which were also detected in rats with single-cell RT-PCR (Hurley et al. 2006) and in mice with single-cell RNAseq (McInturff et al., 2018).  They likely contribute to hair cell currents, alongside Kv7, Kv1.8, HCN1, and Kir. 

      (5) Mechanosensitive ("MET") channels in hair cells are mentioned on lines 234 and 472 (towards the end of the Discussion), but a sentence or two describing the sensory function of hair cells in terms of MET channels and K+ fluxes would help in the Introduction too. 

      Following this suggestion we have expanded the introduction with the following lines  (78-87): “Hair cells are known for their large outwardly rectifying K+ conductances, which repolarize membrane voltage following a mechanically evoked perturbation and in some cases contribute to sharp electrical tuning of the hair cell membrane.  Because gK,L is unusually large and unusually negatively activated, it strongly attenuates and speeds up the receptor potentials of type I HCs (Correia et al., 1996; Rüsch and Eatock, 1996b). In addition, gK,L augments a novel non-quantal transmission from type I hair cell to afferent calyx by providing open channels for K+ flow into the synaptic cleft (Contini et al., 2012, 2017, 2020; Govindaraju et al., 2023), increasing the speed and linearity of the transmitted signal (Songer and Eatock, 2013).”

      (6) Lines 258-260 state that GKL does not inactivate, but previous literature has documented a slow type of inactivation in mouse crista and utricle type I hair cells (Lim et al. 2011, Rusch and Eatock 1996) which should be considered. 

      Lim et al. (2011) concluded that K+ accumulation in the synaptic cleft can explain much of the apparent inactivation of gK,L. In our paper, we were referring to fast, N-type inactivation. We changed that line to be more specific; new revision lines 269-271: “KV1.8, like most KV1 subunits, does not show fast inactivation as a heterologously expressed homomer (Lang et al., 2000; Ranjan et al., 2019; Dierich et al., 2020), nor do the KV1.8-dependent channels in type I HCs, as we show, and in cochlear inner hair cells (Dierich et al., 2020).”

      (7) Lines 320-321 Zonal differences in inward rectifier conductances were reported previously in bird hair cells (Masetto and Correia 1997) and should be referenced here.

      Zonal differences were reported by Masetto and Correia for type II but not type I avian hair cells, which is why we emphasize that we found a zonal difference in I-H in type I hair cells. We added two citations to direct readers to type II hair cell results (lines 333-334): “The gK,L knockout allowed identification of zonal differences in IH and IKir in type I HCs, previously examined in type II HCs (Masetto and Correia, 1997; Levin and Holt, 2012).”

      Also, Horwitz et al. (2011) showed HCN channels in utricles are needed for normal balance function, so please include this reference (see line 171). 

      Done (line 184).

      (8) Fig 6A. Shows Kv1.4 staining in rat utricle but procedures for rat experiments are not described. These should be added. Also, indicate striola or extrastriola regions (if known). 

      We removed KV1.4 immunostaining from the paper, see above.

      (9) Table 6, ZD7288 is listed -was this reagent used in experiments to block Gh? If not please omit. 

      ZD7288 was used to block gH to produce a clean h-infinity curve in Figure 6, which is described in the legend.

      (10) In supplementary Fig. 5A make clear if the currents are from XE991 subtraction. Also, is the G-V data for single cell or multiple cells in B? It appears to be from 1 cell but ages P11-505 are given in legend. 

      The G-V curve in B is from XE991 subtraction, and average parameters in the figure caption are for all the KV1.8–/–  striolar type I hair cells where we observed this double Boltzmann tail G-V curve. I added detail to the figure caption to explain this better.

      (11) Supplementary Fig. 6A claims a fast activation of inward rectifier K+ channels in type II but not type I cells-not clear what exactly is measured here.

      We use “fast inward rectifier” to indicate the inward current that increases within the first 20 ms after hyperpolarization from rest (IKir, characterized in Levin & Holt, 2012) in contrast to HCN channels, which open over ~100 ms. We added panel C to show that the activation of IKir is visible in type II hair cells but not in the knockout type I hair cells that lack gK,L. IKir was a reliable cue to distinguish type I and type II hair cells in the knockout.

      For our actual measurements in Fig 6B, we quantified the current flowing after 250 ms at –124 mV because we did not pharmacologically separate IKir and IH.

      Could the XE991-sensitive current be activated and contributing?

      The XE991-sensitive current could decay (rapidly) at the onset of the hyperpolarizing step, but was not contributing to our measurement of IKir­ and IH, made after 250 ms at –124 mV, at which point any low-voltage-activated (LVA) outward rectifiers have deactivated. Additionally, the LVA XE991-sensitive currents were rare (only detected in some striolar type I hair cells) and when present did not compete with fast IKir, which is only found in type II hair cells.

      Also, did the inward rectifier conductances sustain any outward conductance at more depolarized voltage steps? 

      For the KV1.8-null mice specifically, we cannot answer the question because we did not use specific blocking agents for inward rectifiers.  However, we expect that there would only be sustained outward IR currents at voltages between EK and ~-60 mV: the foot of IKir’s I-V relation according to published data from mouse utricular hair cells – e.g., Holt and Eatock 1995, Rusch and Eatock 1996, Rusch et al. 1998, Horwitz et al., 2011, etc.  Thus, any such current would be unlikely to contaminate the residual outward rectifiers in Kv1.8-null animals, which activate positive to ~-60 mV. 

      (I-HCN is also not a problem, because it could only be outward positive to its reversal potential at ~-40 mV, which is significantly positive to its voltage activation range.)

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      [...] Overall the manuscript is well written, and the successful generation of the new endogenous Cac tags (Td-Tomato, Halo) and CaBeta, stj, and stolid genes with V5 tags will be powerful reagents for the field to enable new studies on calcium channels in synaptic structure, function, and plasticity. There are also some interesting, though not entirely unexpected, findings regarding how Brp and homeostatic plasticity modulate calcium channel abundance. However, a major concern is that the conclusions about how "molecular and organization diversity generate functional synaptic heterogeneity" are not really supported by the data presented in this study. In particular, the key fact that frames this study is that Cac levels are similar at Ib and Is active zones, but that Pr is higher at Is over Ib (which was previously known). While Pr can be influenced by myriad processes, the authors should have first assessed presynaptic calcium influx - if they had, they would have better framed the key questions in this study. As the authors reference from previous studies, calcium influx is at least two-fold higher per active zone at Is over Ib, and the authors likely know that this difference is more than sufficient to explain the difference in Pr at Is over Ib. Hence, there is no reason to invoke differences in "molecular and organization diversity" to explain the difference in Pr, and the authors offer no data to support that the differences in active zone structure at Is vs Ib are necessary for the differences in Pr. Indeed, the real question the authors should have investigated is why there are such differences in presynaptic calcium influx at Is over Ib despite having similar levels/abundance of Cac. This seems the real question, and is all that is needed to explain the Pr differences shown in Fig. 1. The other changes in active zone structure and organization at Is vs Ib may very well contribute to additional differences in Pr, but the authors have not shown this in the present study, and rely on other studies (such as calcium-SV coupling at Is vs Ib) to support an argument that is not necessitated by their data. At the end of this manuscript, the authors have found an interesting possibility that Stj levels are reduced at Is vs Ib, that might perhaps contribute to the difference in calcium influx. However, at present this remains speculative.

      Overall, the authors have generated powerful reagents for the field to study calcium channels and how they are regulated, but draw conclusions about active zone structure and organization contributing to functional heterogeneity that are not strongly supported by the data presented.

      Reviewer 1 raises an interesting question that we agree will form the basis of important studies. Here, we set out to address a different question, which we will work to better frame. While we and others had previously found a strong correlation between calcium channel abundance and synaptic release probability (Pr (Akbergenova et al., 2018; Gratz et al., 2019; Holderith et al., 2012; Nakamura et al., 2015; Sheng et al., 2012)), more recent studies found that calcium channel abundance does not necessarily predict synaptic strength (Aldahabi et al., 2022; Rebola et al., 2019). Our study explores this paradox and presents findings that provide an explanation: calcium channel abundance predicts Pr among individual synapses of either low-Pr type-Ib or high-Pr type-Is inputs where modulating channel number tunes synaptic strength, but does not predict Pr between the two inputs, indicating an inputspecific role for calcium channel abundance in promoting synaptic strength. Thus, we propose that calcium channel abundance predictably modulates synaptic strength among individual synapses of a single input or synapse subtype, which share similar molecular and spatial organization, but not between distinct inputs where the underlying organization of active zones differs. Consistently, in the mouse, calcium channel abundance correlates strongly with release probability specifically when assessed among homogeneous populations of connections (Aldahabi et al., 2022; Holderith et al., 2012; Nakamura et al., 2015; Rebola et al., 2019; Sheng et al., 2012).

      As Reviewer 1 notes, the two-fold difference in calcium influx at type-Is synapses is certainly an important difference underlying three-fold higher Pr. However, growing evidence indicates that calcium influx alone, like calcium channel abundance, does not reliably predict synaptic strength between inputs. For example, Rebola et al. (2019) compared cerebellar synapses formed by granule and stellate cells and found that lower Pr granule synapses exhibit both higher calcium channel abundance and calcium influx. In another example, Aldahabi et al. (2023) demonstrate that even when calcium influx is greater at high-Pr synapses, it does not necessarily explain differences in synaptic strength between inputs. Studying excitatory hippocampal CA1 synapses onto distinct interneuronal targets, they found that raising calcium entry at low-Pr inputs to high-Pr synapse levels is not sufficient to increase synaptic strength to high-Pr synapse levels. Similarly, at the Drosophila NMJ, the finding that type-Ib synapses exhibit loose calcium channel-synaptic vesicle coupling whereas type-Is synapses exhibit tight coupling suggests factors beyond calcium influx also contribute to differences in Pr between the two inputs (He et al., 2023). Consistently, a two-fold increase in external calcium does not induce a three-fold increase in release at low-Pr type-Ib synapses (He et al., 2023). Thus, upon finding that calcium channel abundance is similar at type-Ib and -Is synapses, we focused on identifying differences beyond calcium channel abundance and calcium influx that might contribute their distinct synaptic strengths. We agree that these studies, ours included, cannot definitively determine the contribution of identified organizational differences to distinct release probabilities because it is not currently possible to specifically alter subsynaptic organization, and will ensure that our language is tempered accordingly. However, in addition to the studies cited above and our findings, recent work demonstrating that homeostatic potentiation of neurotransmitter release is accompanied by greater spatial compaction of multiple active zone proteins (Dannhauser et al., 2022; Mrestani et al., 2021) and decreased calcium channel mobility (Ghelani et al., 2023) provide support for the interpretation that subsynaptic organization is a key parameter for modulating Pr.

      Reviewer #2 (Public Review):

      The authors aim to investigate how voltage-gated calcium channel number, organization, and subunit composition lead to changes in synaptic activity at tonic and phasic motor neuron terminals, or type Is and Ib motor neurons in Drosophila. These neuron subtypes generate widely different physiological outputs, and many investigations have sought to understand the molecular underpinnings responsible for these differences. Additionally, these authors explore not only static differences that exist during the third-instar larval stage of development but also use a pharmacological approach to induce homeostatic plasticity to explore how these neuronal subtypes dynamically change the structural composition and organization of key synaptic proteins contributing to physiological plasticity. The Drosophila neuromuscular junction (NMJ) is glutamatergic, the main excitatory neurotransmitter in the human brain, so these findings not only expand our understanding of the molecular and physiological mechanisms responsible for differences in motor neuron subtype activity but also contribute to our understanding of how the human brain and nervous system functions.

      The authors employ state-of-the-art tools and techniques such as single-molecule localization microscopy 3D STORM and create several novel transgenic animals using CRISPR to expand the molecular tools available for exploration of synaptic biology that will be of wide interest to the field. Additionally, the authors use a robust set of experimental approaches from active zone level resolution functional imaging from live preparations to electrophysiology and immunohistochemical analyses to explore and test their hypotheses. All data appear to be robustly acquired and analyzed using appropriate methodology. The authors make important advancements to our understanding of how the different motor neuron subtypes, phasic and tonic-like, exhibit widely varying electrical output despite the neuromuscular junctions having similar ultrastructural composition in the proteins of interest, voltage gated calcium channel cacophony (cac) and the scaffold protein Bruchpilot (brp). The authors reveal the ratio of brp:cac appears to be a critical determinant of release probability (Pr), and in particular, the packing density of VGCCs and availability of brp. Importantly, the authors demonstrate a brp-dependent increase in VGCC density following acute philanthotoxin perfusion (glutamate receptor inhibitor). This VGCC increase appears to be largely responsible for the presynaptic homeostatic plasticity (PHP) observable at the Drosophila NMJ. Lastly, the authors created several novel CRISPRtagged transgenic lines to visualize the spatial localization of VGCC subunits in Drosophila. Two of these lines, CaBV5-C and stjV5-N, express in motor neurons and in the nervous system, localize at the NMJ, and most strikingly, strongly correlate with Pr at tonic and phasic-like terminals.

      (1) The few limitations in this study could be addressed with some commentary, a few minor follow-up analyses, or experiments. The authors use a postsynaptically expressed calcium indicator (mhcGal4>UAS -GCaMP) to calculate Pr, yet do not explore the contribution that glutamate receptors, or other postsynaptic contributors (e.g. components of the postsynaptic density, PSD) may contribute. A previous publication exploring tonic vs phasic-like activity at the drosophila NMJ revealed a dynamic role for GluRII (Aponte-Santiago et al, 2020). Could the speed of GluR accumulation account for differences between neuron subtypes?

      We did observe that GCaMP signals are higher at type Is synapses, where synapses tend to form later but GluRs accumulate more rapidly upon innervation (Aponte-Santiago et al., 2020). However, because we are using our GCaMP indicator as a plus/minus readout of synaptic vesicle release at mature synapses, we do not expect differences in GluR accumulation to have a significant effect on our measures. Consistently, the difference in Pr we observe between type-Ib and -Is inputs (Fig. 1C) is similar to that previously reported (He et al., 2023; Lu et al., 2016; Newman et al., 2022).

      (2) The observation that calcium channel density and brp:cac ratio as a critical determinant of Pr is an important one. However, it is surprising that this was not observed in previous investigations of cac intensity (of which there are many). Is this purely a technical limitation of other investigations, or are other possibilities feasible? Additionally, regarding VGCC-SV coupling, the authors conclude that this packing density increases their proximity to SVs and contributes to the steeper relationship between VGCCs and Pr at phasic type Is. Is it possible that brp or other AZ components could account for these differences. The authors possess the tools to address this directly by labeling vesicles with JanellaFluor646; a stronger signal should be present at Is boutons. Additionally, many different studies have used transmission electron microscopy to explore SVs location to AZs (t-bars) at the Drosophila NMJ.

      To date, the molecular underpinnings of heterogeneity in synaptic strength have primarily been investigated among individual type-Ib synapses. However, a recent study investigating differences between type-Ib and -Is synapses also found that the Cac:Brp ratio is higher at type-Is synapses (He et al., 2023).

      At this point, we do not know which active zone components are responsible for the organizational (Figs. 1, 2) and coupling (now demonstrated by He et al., 2023) differences between type-Ib and -Is synapses or what establishes the differences in active zone protein levels we observe (Figs. 3,6), although Brp likely plays a local role. We find that Brp is required for dynamically regulating calcium channel levels during homeostatic plasticity and plays distinct roles at type-Ib and -Is synapses (Figs. 3, 4). Brp regulates a number of proteins critical for the distribution of docked synaptic vesicles near T bars of type Ib active zones, including Unc13 (Bohme et al., 2016). Extending these studies to type-Is synapses will be of great interest.

      (3) In reference to the contradictory observations that VGCC intensity does not always correlate with, or determine Pr. Previous investigations have also observed other AZ proteins or interactors (e.g. synaptotagmin mutants) critically control release, even when the correlation between cac and release remains constant while Pr dramatically precipitates.

      This is an important point as a number of molecular and organizational differences between high- and low-Pr synapses certainly contribute to baseline functional differences. The other proteins we (Figs. 3,6) and others (Dannhauser et al., 2022; Ehmann et al., 2014; He et al., 2023; Jetti et al., 2023; Mrestani et al., 2021; Newman et al., 2022) have investigated are less abundant and/or more densely organized at type-Is synapses. Investigating additional active zone proteins, including synaptic proteins, and determining how these factors combine to yield increased synaptic strength are important next steps.

      (4) To confirm the observations that lower brp levels results in a significantly higher cac:brp ratio at phasic-like synapses by organizing VGCCs; this argument could be made stronger by analyzing their existing data. By selecting a population of AZs in Ib boutons that endogenously express normal cac and lower brp levels, the Pr from these should be higher than those from within that population, but comparable to Is Pr. I believe the authors should also be able to correlate the cac:brp ratio with Pr from their data set generally; to determine if a strong correlation exists beyond their observation for cac correlation.

      We do not have simultaneous measures of Pr and Cac and Brp abundance. However, our findings suggest that distinct Cac:Brp ratios at type Ib and Is inputs reflect underlying organizational differences that contribute to distinct release probabilities between the two synaptic subtypes. In contrast, within either synaptic subtype, release probability is positively correlated with both Cac and Brp levels. Thus, the mechanisms driving functional differences between synaptic subtypes are distinct from those driving functional heterogeneity within a subtype, so we do not expect Cac:Brp ratio to correlate with Pr among individual type-Ib synapses. We will work to clarify this point in the revised text.

      (5) For the philanthotoxin induced changes in cac and brp localization underlying PHP, why do the authors not show cac accumulation after PhTx on live dissected preparations (i.e. in real time)? This also be an excellent opportunity to validate their brp:cac theory. Do the authors observe a dynamic change in brp:cac after 1, or 5 minutes; do Is boutons potentiate stronger due to proportional increases in cac and brp? Also regarding PhTx-induced PHP, their observations that stj and α2δ-3 are more abundant at Is synapses, suggests that they may also play a role in PhTx induced changes in cac. If either/both are overexpressed during PhTx, brp should increase while cac remains constant. These accessory proteins may determine cac incorporation at AZs.

      As we have previously followed Cac accumulation in live dissected preparations and found that levels increase proportionally across individual synapses (Gratz et al., 2019), we did not attempt to repeat these challenging experiments at smaller type-Is synapses. We will reanalyze our data to investigate Cac:Brp ratio at individual active zones post PhTx. However, as noted above, we do not expect changes in the Cac:Brp ratio to correlate with Pr among individual synapses of single inputs as this measure reflects organization differences between inputs and PhTx induces an increase in the abundance of both proteins at both inputs.

      Determining the effect of PhTx on Stj levels at type-Ib and -Is active zones is an excellent idea and might provide insight into how lower Stj levels correlate with higher Pr at type-Is synapses. While prior studies have demonstrated critical roles for Stj in regulating Cac accumulation during development and in promoting presynaptic homeostatic potentiation (Cunningham et al., 2022; Dickman et al., 2008; Kurshan et al., 2009; Ly et al., 2008; Wang et al., 2016), its regulation during PHP has not been investigated.

      Taken together this study generates important data-driven, conceptional, and theoretical advancements in our understanding of the molecular underpinnings of different motor neurons, and our understanding of synaptic biology generally. The data are robust, thoroughly analyzed, appropriately depicted. This study not only generates novel findings but also generated novel molecular tools which will aid future investigations and investigators progress in this field.

      References

      Akbergenova, Y., K.L. Cunningham, Y.V. Zhang, S. Weiss, and J.T. Littleton. 2018. Characterization of developmental and molecular factors underlying release heterogeneity at Drosophila synapses. eLife. 7.

      Aldahabi, M., F. Balint, N. Holderith, A. Lorincz, M. Reva, and Z. Nusser. 2022. Different priming states of synaptic vesicles underlie distinct release probabilities at hippocampal excitatory synapses. Neuron. 110:4144-4161 e4147.

      Aponte-Santiago, N.A., K.G. Ormerod, Y. Akbergenova, and J.T. Littleton. 2020. Synaptic Plasticity Induced by Differential Manipulation of Tonic and Phasic Motoneurons in Drosophila. The Journal of neuroscience : the official journal of the Society for Neuroscience. 40:6270-6288.

      Bohme, M.A., C. Beis, S. Reddy-Alla, E. Reynolds, M.M. Mampell, A.T. Grasskamp, J. Lutzkendorf, D.D. Bergeron, J.H. Driller, H. Babikir, F. Gottfert, I.M. Robinson, C.J. O'Kane, S.W. Hell, M.C. Wahl, U. Stelzl, B. Loll, A.M. Walter, and S.J. Sigrist. 2016. Active zone scaffolds differentially accumulate Unc13 isoforms to tune Ca(2+) channel-vesicle coupling. Nature neuroscience. 19:1311-1320.

      Cunningham, K.L., C.W. Sauvola, S. Tavana, and J.T. Littleton. 2022. Regulation of presynaptic Ca(2+) channel abundance at active zones through a balance of delivery and turnover. Elife. 11.

      Dannhauser, S., A. Mrestani, F. Gundelach, M. Pauli, F. Komma, P. Kollmannsberger, M. Sauer, M. Heckmann, and M.M. Paul. 2022. Endogenous tagging of Unc-13 reveals nanoscale reorganization at active zones during presynaptic homeostatic potentiation. Front Cell Neurosci. 16:1074304.

      Dickman, D.K., P.T. Kurshan, and T.L. Schwarz. 2008. Mutations in a Drosophila alpha2delta voltage gated calcium channel subunit reveal a crucial synaptic function. The Journal of neuroscience : the official journal of the Society for Neuroscience. 28:31-38.

      Ehmann, N., S. Van De Linde, A. Alon, D. Ljaschenko, X.Z. Keung, T. Holm, A. Rings, A. Diantonio, S. Hallermann, U. Ashery, M. Heckmann, M. Sauer, and R.J. Kittel. 2014. Quantitative super-resolution imaging of Bruchpilot distinguishes active zone

      states. Nature Communications. 5.

      Ghelani, T., M. Escher, U. Thomas, K. Esch, J. Lützkendorf, H. Depner, M. Maglione, P. Parutto, S. Gratz, T. Matkovic-Rachid, S. Ryglewski, A.M. Walter, D. Holcman, K. O‘Connor Giles, M. Heine, and S.J. Sigrist. 2023. Interactive nanocluster compaction of the ELKS scaffold and Cacophony Ca<sup>2+</sup> channels drives sustained active zone potentiation. Science Advances. 9:eade7804.

      Gratz, S.J., P. Goel, J.J. Bruckner, R.X. Hernandez, K. Khateeb, G.T. Macleod, D. Dickman, and K.M. O'Connor-Giles. 2019. Endogenous tagging reveals differential regulation of Ca<sup>2+</sup> channels at single AZs during presynaptic homeostatic potentiation and depression. The Journal of Neuroscience:3068-3018.

      He, K., Y. Han, X. Li, R.X. Hernandez, D.V. Riboul, T. Feghhi, K.A. Justs, O. Mahneva, S. Perry, G.T. Macleod, and D. Dickman. 2023. Physiologic and Nanoscale Distinctions Define Glutamatergic Synapses in Tonic vs Phasic Neurons. The Journal of neuroscience : the official journal of the Society for Neuroscience. 43:4598-4611.

      Holderith, N., A. Lorincz, G. Katona, B. Rózsa, A. Kulik, M. Watanabe, and Z. Nusser. 2012. Release probability of hippocampal glutamatergic terminals scales with the size of the active zone. Nature neuroscience. 15:988-997.

      Jetti, S.K., A.B. Crane, Y. Akbergenova, N.A. Aponte-Santiago, K.L. Cunningham, C.A. Whittaker, and J.T. Littleton. 2023. Molecular Logic of Synaptic Diversity Between Drosophila Tonic and Phasic Motoneurons. bioRxiv:2023.2001.2017.524447.

      Kurshan, P.T., A. Oztan, and T.L. Schwarz. 2009. Presynaptic alpha2delta-3 is required for synaptic morphogenesis independent of its Ca2+-channel functions. Nature neuroscience. 12:1415-1423.

      Lu, Z., A.K. Chouhan, J.A. Borycz, Z. Lu, A.J. Rossano, K.L. Brain, Y. Zhou, I.A. Meinertzhagen, and G.T. Macleod. 2016. High-Probability Neurotransmitter Release Sites Represent an Energy-Efficient Design. Current biology : CB. 26:2562-2571.

      Ly , C.V., C.-K. Yao , P. Verstreken , T. Ohyama , and H.J. Bellen 2008. straightjacket is required for the synaptic stabilization of cacophony, a voltage-gated calcium channel α1 subunit. Journal of Cell Biology. 181:157-170.

      Mrestani, A., M. Pauli, P. Kollmannsberger, F. Repp, R.J. Kittel, J. Eilers, S. Doose, M. Sauer, A.-L. Sirén, M. Heckmann, and M.M. Paul. 2021. Active zone compaction correlates with presynaptic homeostatic potentiation. Cell Reports. 37:109770.

      Nakamura, Y., H. Harada, N. Kamasawa, K. Matsui, Jason S. Rothman, R. Shigemoto, R.A. Silver, David A. DiGregorio, and T. Takahashi. 2015. Nanoscale Distribution of Presynaptic Ca2+ Channels and Its Impact on Vesicular Release during Development. Neuron. 85:145-158.

      Newman, Z.L., D. Bakshinskaya, R. Schultz, S.J. Kenny, S. Moon, K. Aghi, C. Stanley, N. Marnani, R. Li, J. Bleier, K. Xu, and E.Y. Isacoff. 2022. Determinants of synapse diversity revealed by superresolution quantal transmission and active zone imaging. Nature Communications. 13:229.

      Rebola, N., M. Reva, T. Kirizs, M. Szoboszlay, A. Lőrincz, G. Moneron, Z. Nusser, and D.A. Digregorio. 2019. Distinct Nanoscale Calcium Channel and Synaptic Vesicle Topographies Contribute to the Diversity of Synaptic Function. Neuron. 104:693-710.e699.

      Sheng, J., L. He, H. Zheng, L. Xue, F. Luo, W. Shin, T. Sun, T. Kuner, D.T. Yue, and L.-G. Wu. 2012. Calcium-channel number critically influences synaptic strength and plasticity at the active zone. Nature neuroscience. 15:998-1006.

      Wang, T., R.T. Jones, J.M. Whippen, and G.W. Davis. 2016. alpha2delta-3 Is Required for Rapid Transsynaptic Homeostatic Signaling. Cell Rep. 16:2875-2888.

      Reviewer #1 (Recommendations For The Authors): 

      Major points: 

      (1) A central question regarding VGCC differences at Is vs Ib active zones is why is calcium influx higher at Is active zones compared to Ib. Ideally, the authors would have started this study by showing correlations between Cac abundance, presynaptic calcium influx, and Pr at Is vs Ib active zones. If they had, they would likely find that Cac abundance scales with calcium influx and Pr within Is vs Ib, but that calcium influx is over two-fold enhanced at Is over Ib when normalized to the same Cac abundance. This is more than sufficient to explain the Pr differences, so the rest of the study should have focused on revealing why influx is different at Is over Ib despite an apparently similar level of Cac abundance. Then the examination of CaBeta, Stj, etc could have been used to help explain this conundrum. 

      A lesson might be gleaned in how to structure this narrative from the Rebola 2019 study, which the authors cite and discuss at length. Similar to the current study, that paper started with two synapses ("strong" vs "weak") and sought to explain why they were so different in synaptic strength. First, they examined presynaptic calcium influx, and surprisingly found that the strong synapse had reduced calcium influx compared to the weak. Then the rest of the paper sought to explain why synaptic strength (Pr) was higher at the strong synapse despite reduced calcium influx. The authors do not use this logical flow and narrative in the present study, despite the focus being on how Cav2 channels contribute to strong vs weak synapses - and the primary function of Cav2 channels is to pass calcium at active zones to drive vesicle fusion. 

      Although the authors did not show that presynaptic calcium influx is higher at Is vs Ib active zones in the current manuscript, other studies have previously established that calcium influx is two-fold higher at Is active zones vs Ib (as the authors cite). Rather than focusing so much on Pr at Is vs Ib active zones, which as the authors know can be influenced by myriad differences, it seems the more relevant parameter to study is simply to address presynaptic calcium influx at Is vs Ib, which is the primary function of Cac. Put more simply, if Cac levels are the same at Is vs Ib active zones, why is calcium influx at least two-fold higher at Is? 

      It would therefore seem crucial for the authors to determine presynaptic calcium influx levels (ideally at individual AZs) to really understand how Cac intensity levels correlate with calcium influx. The authors instead map Pr at individual AZs, but as the authors know there are many variables that influence whether a SV releases in addition to calcium influx. There are a number of options for this kind of imaging in Drosophila, including genetically encoded calcium indicators targeted to active zones. But since several studies have previously established that influx is higher at Is active zones over Ib, this may not be necessary. That being said, there is a lot of value in quantitatively analyzing Cac/Stj/CaBeta abundance, calcium influx, and Pr together at individual active zones.

      We appreciate the perspective that we could have focused on why Ca2+ influx is 2x greater at type Is active zones, which we agree is an important and interesting question. However, growing evidence indicates that Ca2+ influx alone, like Ca2+ channel abundance, does not reliably predict synaptic strength between inputs. So, here we focused instead on how other differences between synapses influence Pr and contribute to synaptic heterogeneity between and/or among synapses formed by strong and weak inputs. We have changed our title and framing to better reflect this focus. 

      As Reviewer 1 notes, Rebola et al. (2019) found that lower Pr granule synapses exhibit higher Ca2+ influx (and Ca2+ channel abundance). In another example, Aldahabi et al. (2022) demonstrated that even when Ca2+ influx is greater at high-Pr synapses, it does not necessarily explain differences in synaptic strength as raising Ca2+ entry at low-Pr synapses to high-Pr synapse levels was not sufficient to increase synaptic strength to high-Pr input levels. Similar findings have been reported at tonic and phasic synapses of the Crayfish NMJ (Msghina, 1999).

      Several lines of evidence argue that factors beyond Ca2+ influx also play important roles in establishing distinct release properties at the Drosophila NMJ. A recent study using using a botulinum transgene to isolate type Ib and Is synapses for electrophysiological analysis found that increasing external [Ca2+] from physiological levels (1.8 mM) to 3 mM or even 6 mM does not result in a 3-fold increase in EPSCs or quantal content at type Ib synapses despite the prediction that the increase would be even greater given the power dependence of release on between Ca2+ concentration (He et al., 2023). The authors further found that type Ib synapses are more sensitive than type Is synapses to the slow Ca2+ chelator EGTA, indicating looser Ca2+ channel-SV coupling. 

      Consistently, we find that although VGCC levels are similar at the two inputs, their density is greater at type Is active zones (Figs. 1 and 2). Our findings also reveal additional molecular differences that may contribute to the observed differences in neurotransmitter release properties between the two inputs, including lower levels of the active zone protein Brp (Fig 3) and the auxiliary subunit α2δ-3/Stj (Fig. 6) at high Pr type Is inputs. In contrast, levels of each of these proteins positively correlate with synaptic strength among active zones of a single input, whether low- or high-Pr (Figs. 1, 3, 6). Similarly, levels of each of these proteins increase during homeostatic potentiation of neurotransmitter release (Figs. 4 and 7). Thus, we propose that two broad mechanisms contribute to synaptic diversity in the nervous system: (1) spatial organization and relative molecular content establish distinct average basal release probabilities that differ between inputs and (2) among individual synapses of distinct inputs, coordinated modulation of Ca2+ channel and active zone protein abundance independently tunes Pr. These intersecting mechanisms provide a framework for understanding the extensive and dynamic synaptic diversity observed across nervous systems.

      (2) In addition to key points made above, it seems the authors should at least consider (if not experimentally test) what other differences might contribute to the higher calcium influx at Is over Ib:  

      - Distinct splice isoforms of Cac (and/or Stj/Cabeta): The recent RNAseq analysis of gene expression at Is vs Ib motor neurons from Troy Littleton's group may inform this consideration? 

      - Stj reduction at Is: Do channel studies in heterologous systems give any insight into VGCC channel function with and without a2d-3? Do Cav2 channels without a2d pass more calcium? This would then offer an obvious solution to the key conundrum underlying this study. 

      These are excellent questions that we are actively pursuing. While there is no evidence of differentially expressed splice isoforms of Stj or Ca-β in the recent RNA-seq data from Jetti et al., 2023, subtle changes in Cac isoform usage were observed that may contribute to differences in Ca2+ influx. In heterologous systems, α2δ expression generally increases Ca2+ channel membrane insertion and  Ca2+ currents. However, in vivo α2δ’s can also mediate extracellular interactions that may modulate channel function. We address these points in greater detail in the revised discussion.  

      (3) Assess Stj and CaBeta levels at AZs after PhTx: The successful generation of endogenously tagged Stj and CaBeta enables some relatively easy experiments that would be of interest, similar to what the authors present for Cac. Does Brp similarly control Stj and CaBeta at Is vs Ib compared to what they show for Cac? In addition, does homeostatic plasticity similarly change Stj and CaBeta at Is vs Ib compared to what the authors have shown for Cac? i.e., do they both similarly increase in intensity, by the same amount, as Cac? 

      We agree and have included an analysis of α2δ-3/Stj levels following PhTx exposure (Fig. 7A-C). We have also investigated the regulation of Stj during chronic presynaptic homeostatic potentiation (Fig. 7D-F). In both cases, StjV5-N levels significantly increase at type Ib and Is active zones, consistent with our finding that among AZs of either type Ib or Is inputs, Stj levels correlate with Cac abundance and, thus, Pr. Together with our and others’ findings, this suggests that coordinated increases Ca2+ channel, auxiliary subunit,  and active zone protein abundance positively tunes synaptic strength at diverse synaptic subtypes.

      Minor points: 

      (1) Including line numbers would make reviewing/commenting easier. 

      We apologize for this oversight and have added line numbers to the revised manuscript.

      (2) Fig. 2I: It is not apparent what the mean cluster density is between Ib vs Is (as it is in Fig. 2F-H graphs). The mean and error bars should be included in 2I as it is in 2G. Same with Fig. 3C. 

      Thank you for pointing this out. We have added error bars to the paired analysis in 2I as well as in 3C and 1C.

      (3) Fig. 4 - it might make more sense to normalize Brp and Cac intensity as a percentage of baseline (PhTx at Is or Ib) rather than normalizing everything to control Ib. 

      We have revised the graphs as suggested in Figure 4 and throughout.

      (4) Page 5 bottom - REFS missing after Fig. 1E. 

      Thank you for catching this. We have fixed it.

      Reviewer #2 (Recommendations For The Authors): 

      This reader found differentiating between low Pr sites (deep purple) and cac measurements (black) difficult in Fig 1B. You may consider depicting this differently. 

      Thank you for this feedback. We have changed the color scheme to improve readability.

      I found it difficult to discern the difference between experiments Fig 1E and Fig 1J. Why are individual dots distributed differently? 

      The individual data points are the same as in 1E and 1F, but we have removed the individual NMJ dimensionality to combine all Is and Ib data points together along with best fit lines for comparison of their slopes. We have added text to the revised manuscript to clarify this.

      Results section, second paragraph, add references, remove 'REF': We next investigated the correlation between Pr and VGCC levels and found that at type Is inputs, single-AZ Cac intensity positively correlates with Pr (Fig. 1E; REFS). 

      Thank you. We have corrected this error.

    1. AbstractAs single-cell sequencing data sets grow in size, visualizations of large cellular populations become difficult to parse and require extensive processing to identify subpopulations of cells. Managing many of these charts is laborious for technical users and unintuitive for non-technical users. To address this issue, we developed TooManyCellsInteractive (TMCI), a browser-based JavaScript application for visualizing hierarchical cellular populations as an interactive radial tree. TMCI allows users to explore, filter, and manipulate hierarchical data structures through an intuitive interface while also enabling batch export of high-quality custom graphics. Here we describe the software architecture and illustrate how TMCI has identified unique survival pathways among drug-tolerant persister cells in a pan-cancer analysis. TMCI will help guide increasingly large data visualizations and facilitate multi-resolution data exploration in a user-friendly way.

      A version of this preprint has been published in the Open Access journal GigaScience (see paper https://doi.org/10.1093/gigascience/giae056), where the paper and peer reviews are published openly under a CC-BY 4.0 license. These peer reviews were as follows:

      Reviewer 3: Georgios Fotakis

      1) General comments In this manuscript the authors present TooManyCellsInteractive (TMCI), a browser-based TypeScript graphical user interface for the visualization and interactive exploration of single-cell data. TMCI facilitates the visualization of single-cell data by representing it as a radial tree of nested cell clusters. It relies on TooManyCells, a suite of tools designed for multi-resolution and multifaceted exploration of single-cell clades based on a matrix-free divisive hierarchical spectral clustering method. A key advantage of TCMI lies in its capability to provide a quantitative depiction of relationships among clusters, allowing for the delineation of context-dependent rare and abundant cell populations, as showcased in the original publication [1] and in the present manuscript. TMCI extends the capabilities of TMC significantly, notably enhancing computational performance, particularly in scenarios where multiple features are overlaid (an improvement that is attributed to the persistent feature of the PostgreSQL database).

      A notable aspect of this manuscript is the fact that the authors performed a benchmark using publicly available scRNAseq datasets. This benchmark highlights TMCI's superior performance over TMC and its comparable performance to two other commonly utilized tools (Cirrocumulus and CELLxGENE). Moreover, the authors showcase TMCI's applicability through aggregating publicly available scRNAseq data. Here, they successfully delineate sub-populations of cancer drug-tolerant persister cells by employing minimum distance search pruning, enhancing the visibility of small sub-populations. Additionally, the authors note an increase in ID2 gene expression among persister-cell populations, as well as the enrichment of unique biological programs between short- and long-term persister-cell populations. Furthermore, they observe an upregulation of the diapause gene signature across all treated sub-populations. The biological insights the authors glean are novel and highly intriguing. In general, this manuscript is well written, with the authors offering comprehensive documentation that covers the essential steps for installing and running TMCI through their GitHub repository. Additionally, they provide a minimal dataset as an example for users. However, there are a few minor adjustments that, once implemented, would enhance the manuscript's value by improving clarity and providing valuable insights to the field.

      2) Specific comments for revision a) Major - As stated in the manuscript's abstract, visualising large cell populations from single-cell atlases poses greater challenges and demands compute-intensive processes. One of my major concerns revolves around TMCI's scalability when handling large datasets. The authors conducted benchmarking on relatively modest datasets (ranging from 18,859 to 54,220 cells). Based on the data provided in Supplementary Table S3, while TMCI demonstrates comparable performance to CELLxGENE on the Tabula Muris dataset and its subset (with mean memory consumption differences ranging from 870 MB to 1.8 GB), the disparity significantly increases when loading and rendering visualizations of the larger dataset, reaching 8.5 GB of RAM. It would be of great interest if the authors conducted a similar benchmark using a larger dataset to elucidate how TMCI scales with increased cell numbers, especially considering the trend in the field towards single-cell atlases and the availability of datasets consisting up to millions of cells (like the Tabula Sapiens [2] dataset or similar [3, 4]).

      • In the "Results" section, under the title "TMCI identifies sub-populations with highly expressed diapause programs," the authors assert that "the significantly different sub-populations were more easily seen in TMCI's tree". Since perception can be subjective (for instance, a user more accustomed to UMAP plots may find it challenging to interpret a tree representation), it would be beneficial for the authors to allocate a section of the supplementary material to demonstrate the clarity advantages of TMCI's tree visualization. One approach could involve a side-by-side comparison of visualizations generated by TMCI and CELLxGENE using the same color scheme. For instance, Figure 4b could be compared with Supplementary Figure S1g, Figure 4j with Supplementary Figure S1h, and so forth.

      • The "Discussion" section overlooks the future prospects of TMCI. As demonstrated in the case study, TMCI exhibits potential beyond serving as a visualization tool for identifying tree-based relationships in single-cell data. Are there any plans for integrating analytical functionalities to provide insights into cellular compositions and underlying biology, such as marker gene identification, differential gene expression analysis, and gene set enrichment analysis? In the future, could TMCI support the visualization of such results using methods like violin plots, heatmaps, and others?

      • In the "Materials and Methods'' section, the authors outline the process of aggregating the scRNAseq datasets used for the case study, including filtering and normalization steps. However, scRNAseq technologies are prone to significant noise resulting from amplification and dropout events. Additionally, when integrating different scRNAseq datasets, users need to consider potential batch effects. Did the authors employ any de-noising or batch correction methods? If not, what was the rationale behind this decision? It would be intriguing to observe any potential differences in the results following the application of such methods.

      • Remaining within the "Materials and Methods" section, providing a brief description of the methods and tools utilized for the differential gene expression analysis, the GSEA (if not solely conducted through Metascape), and the packages utilized to generate the plots in Figures 3 and 4 would enhance clarity and facilitate reproducibility.

      • Figure 4 - b: Distinguishing between the various cell lines on the partitioned nodes based on the current color coding—particularly for the MDA-MB-231 and PC9 cell lines, as well as between the treated and untreated populations of the SK-MEL-28 cell line—is quite challenging. Employing a different color scheme would significantly enhance clarity, making the different cell populations more distinguishable.

      • Figure 4 - d and k: The authors should add statistics as relying solely on the box and whisker plots makes it challenging to ascertain whether there is a significant difference between the conditions. For instance, it appears that ID2 is over-expressed between the control and treated population only in the SK-MEL-28 cell line.

      b) Minor - In the "Results" section, under the title "TMCI reduces time to display trees," the authors state: "these benchmarks indicate not only the superior performance of TMCI to generate static and interactive tree of single-cell data compared to other tools…". However, based on the results presented in the manuscript and the supplementary material, it seems that TMCI may not be outperforming alternative interactive visualization methods. This phrase should be revised to accurately reflect the benchmark results.

      References 1. Schwartz GW, Zhou Y, Petrovic J, Fasolino M, et al. TooManyCells identifies and visualizes relationships of single-cell clades. Nat Methods 2020;17(4):405-413. PMID: 32123397 2. The Tabula Sapiens Consortium, The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans. Science 2022;376, eabl4896. DOI:10.1126/science.abl4896 3. Sikkema L, Ramírez-Suástegui C, Strobl DC, et al. An integrated cell atlas of the lung in health and disease. Nat Med 2023;29, 1563-1577. DOI:10.1038/s41591-023-02327-2 4. Salcher S, Sturm G, Horvath L, et al. High-resolution single-cell atlas reveals diversity and plasticity of tissue-resident neutrophils in non-small cell lung cancer. Cancer cell 2022;40(12):1503-1520.E8. DOI:10.1016/j.ccell.2022.10.008

  5. Aug 2024
    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      In this study, the authors used a stopped-flow method to investigate the kinetics of substrate translocation through the channel in hexameric ClpB, an ATP-dependent bacterial protein disaggregase. They engineered a series of polypeptides with the N-terminal RepA ClpB-targeting sequence followed by a variable number of folded titin domains. The authors detected translocation of the substrate polypeptides by observing the enhancement of fluorescence from a probe located at the substrate's C-terminus. The total time of the substrates' translocation correlated with their lengths, which allowed the authors to determine the number of residues translocated by ClpB per unit time.

      Strengths:

      This study confirms a previously proposed model of processive translocation of polypeptides through the channel in ClpB. The novelty of this work is in the clever design of a series of kinetic experiments with an engineered substrate that includes stably folded domains. This approach produced a quantitative description of the reaction rates and kinetic step sizes. Another valuable aspect is that the method can be used for other translocases from the AAA+ family to characterize their mechanism of substrate processing.

      Weaknesses:

      The main limitation of the study is in using a single non-physiological substrate of ClpB, which does not replicate the physical properties of the aggregated cellular proteins and includes a non-physiological ClpB-targeting sequence. Another limitation is in the use of ATPgammaS to stimulate the substrate processing. It is not clear how relevant the results are to the ClpB function in living cells with ATP as the source of energy, a multitude of various aggregated substrates without targeting sequences that need ClpB's assistance, and in the presence of the co-chaperones.

      Indeed, we agree that our RepA-Titinx substrates are not aggregates but are model, soluble, substrates used to reveal information about enzyme catalyzed protein unfolding and translocation.  Our substrates are similar to RepA-GFP and GFP-SsrA used by multiple labs including Wickner, Horwich, Sauer, Baker, Shorter, Bukua, to name only a few.  The fact that “this is what everyone does” does not make the substrates physiological or the most ideal. However, this is the technology we currently have until we and others develop something better. In the meantime, we contend that  the results presented here do advance our knowledge on enzyme catalyzed protein unfolding

      Part of what this manuscript seeks to accomplish is presenting the development of a single-turnover experiment that reports on processive protein unfolding by AAA+ molecular motors, in this case, ClpB.  Importantly, we are treating translocation on an unfolded polypeptide chain and protein unfolding of stably folded proteins as two distinct reactions catalyzed by ClpB. If these functions are used to disrupt protein aggregates, in vivo, then this remains to be seen.

      We contend that processive ClpB catalyzed protein unfolding has not been rigorously demonstrated prior to our results presented here.  Avellaneda et al mechanically unfolded their substrate before loading ClpB (Avellaneda, Franke, Sunderlikova et al. 2020).  Thus, their experiment represents valuable observations reflecting polypeptide translocation on a pre-unfolded protein.  Our previous work using single-turnover stopped-flow experiments employed unstructured synthetic polypeptides and therefore reflects polypeptide translocation and not protein unfolding (Li, Weaver, Lin et al. 2015).  Weibezahn et al used unstructured substrates in their study with ClpB (BAP/ClpP), and thus their results represent translocation of a pre-unfolded polypeptide and not enzyme catalyzed protein unfolding (Weibezahn, Tessarz, Schlieker et al. 2004). 

      Many studies have reported the use of  GFP with tags or RepA-GFP and used the loss of GFP fluorescence to conclude protein unfolding.  However, such results do not reveal if ClpB processively and fully translocates the substrate through its axial channel.  One cannot rule out, even when trapping with “GroEL trap”, the possibility that ClpB only needs to disrupt some of the fold in GFP before cooperative unfolding occurs leading to loss of fluorescence.  Once the cooperative collapse of the structure occurs and fluorescence is lost it has not been shown that ClpB will continue to translocate on the newly unfolded chain or dissociate. In fact, the Bukau group showed that folded YFP remained intact after luciferase was unfolded (Haslberger, Zdanowicz, Brand et al. 2008).  Our approach, reported here, yields signal upon arrival of the motor at the c-terminus or within the PIFE distance thus we can be certain that the motor does arrive at the c-terminus after unfolding up to three tandem repeats of the Titin I27 domain.

      ATPgS is a non-physiological nucleotide analog.  However, ClpB has been shown to exhibit curious behavior in its presence that we and others, as the reviewer acknowledges, do not fully understand (Doyle, Shorter, Zolkiewski et al. 2007).  Some of the experiments reported here are seeking to better understand that fact.  Here we have shown that ATPgS alone will support processive protein unfolding. With this assay in hand, we are now seeking to go forward and address many of the points raised by this reviewer. 

      The authors do not attempt to correlate the kinetic step sizes detected during substrate translocation and unfolding with the substrate's structure, which should be possible, given how extensively the stability and unfolding of the titin I27 domain were studied before. Also, since the substrate contains up to three I27 domains separated with unstructured linkers, it is not clear why all the translocation steps are assumed to occur with the same rate constant.

      We assume that all protein unfolding steps occur with the same rate constant, ku.  We conclude that we are not detecting the translocation rate constant, kt, as our results support a model where kt is much faster than ku.  We do think it makes sense that the same slow step occurs between each cycle of protein unfolding.

      We have added a discussion relating our observations to mechanical unfolding of tandem repeats of Titin I27 from AFM experiments  (Oberhauser, Hansma, Carrion-Vazquez and Fernandez 2001). Most interestingly, they report unfolding of Titin I27 in 22 nm steps.  Using 0.34 nm per amino acids this yields ~65 amino acids per unfolding step, which is comparable to our kinetic step-size of 57 – 58 amino acids per step.

      Some conclusions presented in the manuscript are speculative:

      The notion that the emission from Alexa Fluor 555 is enhanced when ClpB approaches the substrate's C-terminus needs to be supported experimentally. Also, evidence that ATPgammaS without ATP can provide sufficient energy for substrate translocation and unfolding is missing in the paper.

      In our previous work we have used fluorescently labeled 50 amino acid peptides as substrates to examine ClpB binding (Li, Lin and Lucius 2015, Li, Weaver, Lin et al. 2015).  In that work we have used fluorescein, which exhibits quenching upon ClpB binding.  We have added a control experiment where we have attached alexa fluor 555 to the 50 amino acid substrate so we can be assured the ClpB binds close to the fluorophore.  As seen in supplemental Fig. 1 A  upon titration with ClpB, in the presence of ATPγS, we observe an increase in fluorescence from AF555, consistent with PIFE.  Supplemental Fig. 1 B shows the relative fluorescence enhancement at the peak max increases up to ~ 0.2 or a 20 % increase in fluorescence, due to PIFE, upon ClpB binding.   

      Further, peak time is our hypothesized measure of ClpB’s arrival at the dye. Our results indicate that the peak time linearly increases as a function of an increase in the number of folded TitinI27 repeats in the substrates which also supports the PIFE hypothesis. Finally, others have shown that AF555 exhibits PIFE and we have added those references.

      The evidence that ATPγS alone can support translocation is shown in Fig. 2 and supplemental Figure 1.  Fig. 2 and supplemental Figure 1 are two different mixing strategies where we use only ATPgS and no ATP at all.  In both cases the time courses are consistent with processive protein unfolding by ClpB with only ATPγS.

      Reviewer #2 (Public Review):

      Summary:

      The current work by Banwait et al. reports a fluorescence-based single turnover method based on protein-induced fluorescence enhancement (PIFE) to show that ClpB is a processive motor. The paper is a crucial finding as there has been ambiguity on whether ClpB is a processive or non-processive motor. Optical tweezers-based single-molecule studies have shown that ClpB is a processive motor, whereas previous studies from the same group hypothesized it to be a non-processive motor. As co-chaperones are needed for the motor activity of the ClpB, to isolate the activity of ClpB, they have used a 1:1 ratio ATP and ATPgS, where the enzyme is active even in the absence of its co-chaperones, as previously observed. A sequential mixing stop-flow protocol was developed, and the unfolding and translocation of RepA-TitinX, X = 1,2,3 repeats was monitored by measuring the fluorescence intensity with the time of Alexa F555 which was labelled at the C-terminal Cysteine. The observations were a lag time, followed by a gradual increase in fluorescence due to PIFE, and then a decrease in fluorescence plausibly due to the dissociation from the substrate allowing it to refold. The authors observed that the peak time depends on the substrate length, indicating the processive nature of ClpB. In addition, the lag and peak times depend on the pre-incubation time with ATPgS, indicating that the enzyme translocates on the substrates even with just ATPgS without the addition of ATP, which is plausible due to the slow hydrolysis of ATPgS. From the plot of substrate length vs peak time, the authors calculated the rate of unfolding and translocation to be ~0.1 aas-1 in the presence of ~1 mM ATPgS and increases to 1 aas-1 in the presence of 1:1 ATP and ATPgS. The authors have further performed experiments at 3:1 ATP and ATPgS concentrations and observed ~5 times increase in the translocation rates as expected due to faster hydrolysis of ATP by ClpB and reconfirming that processivity is majorly ATP driven. Further, the authors model their results to multiple sequential unfolding steps, determining the rate of unfolding and the number of amino acids unfolded during each step. Overall, the study uses a novel method to reconfirm the processive nature of ClpB.

      Strengths:

      (1) Previous studies on understanding the processivity of ClpB have primarily focused on unfolded or disordered proteins; this study paves new insights into our understanding of the processing of folded proteins by ClpB. They have cleverly used RepA as a recognition sequence to understand the unfolding of titin-I27 folded domains.

      (2) The method developed can be applied to many disaggregating enzymes and has broader significance.

      (3) The data from various experiments are consistent with each other, indicating the reproducibility of the data. For example, the rate of translocation in the presence of ATPgS, ~0.1 aas-1 from the single mixing experiment and double mixing experiment are very similar.

      (4) The study convincingly shows that ClpB is a processive motor, which has long been debated, describing its activity in the presence of only ATPgS and a mixture of ATP and ATPgS.

      (5) The discussion part has been written in a way that describes many previous experiments from various groups supporting the processive nature of the enzyme and supports their current study.

      Weaknesses:

      (1) The authors model that the enzyme unfolds the protein sequentially around 60 aa each time through multiple steps and translocates rapidly. This contradicts our knowledge of protein unfolding, which is generally cooperative, particularly for titinI27, which is reported to unfold cooperatively or utmost through one intermediate during enzymatic unfolding by ClpX and ClpA.

      We do not think this represents a contradiction.  In fact, our observations are in good agreement with mechanical unfolding of tandem repeats of Titin I27 using AFM experiments (Oberhauser, Hansma, Carrion-Vazquez and Fernandez 2001).  They showed that tandem repeats of TitinI27 unfolded in steps of ~22 nm.  Dividing 22 nm by 0.34 nm/Amino Acid gives ~65 amino acids per unfolding event.  This implies that, under force, ~65 amino acids of folded structure unfolds in a single step.  This number is in excellent agreement with our kinetic step-size of 65 AA/step. 

      Importantly, the experiments cited by the reviewer on ClpA and ClpX are actually with ClpAP and ClpXP.  We assert that this is an important distinction as we have shown that ClpA employs a different mechanism than ClpAP (Rajendar and Lucius 2010, Miller, Lin, Li and Lucius 2013, Miller and Lucius 2014).  Thus, ClpA and ClpAP should be treated as different enzymes but, without question, ClpB and ClpA are different enzymes.

      (2) It is also important to note that the unfolding of titinI27 from the N-terminus (as done in this study) has been reported to be very fast and cannot be the rate-limiting step as reported earlier(Olivares et al, PNAS, 2017). This contradicts the current model where unfolding is the rate-limiting step, and the translocation is assumed to be many orders faster than unfolding.

      Most importantly, the Olivares paper is examining ClpXP and ClpAP catalyzed protein unfolding and translocation and not ClpB.  These are different enzymes.  Additionally, we have shown that ClpAP and ClpA translocate unfolded polypeptides with different rates, rate constants, and kinetic step-sizes indicating that ClpP allosterically impacts the mechanism employed by ClpA to the extent that even ClpA and ClpAP should be considered different enzymes (Rajendar and Lucius 2010, Miller, Lin, Li and Lucius 2013).  We would further assert that there is no reason to assume ClpAP and ClpXP would catalyze protein unfolding using the same mechanism as ClpB as we do not think it should be assumed ClpA and ClpX use the same mechanism as ClpAP and ClpXP, respectively. 

      The Olivares et al paper reports a dwell time preceding protein unfolding of ~0.9 and ~0.8 s for ClpXP and ClpAP, respectively.   The inverse of this can be taken as the rate constant for protein unfolding and would yield a rate constant of ~1.2 s-1, which is in good agreement with our observed rate constant of 0.9 – 4.3 s-1 depending on the ATP:ATPγS mixing ratio.  For ClpB, we propose that the slow unfolding is then followed by rapid translocation on the unfolded chain where translocation by ClpB must be much faster than for ClpAP and ClpXP.  We think this is a reasonable interpretation of our results and not a contradiction of the results in Olivares et al. Moreover, this is completely consistent with the mechanistic differences that we have reported, using the same single-turnover stopped flow approach on the same unfolded polypeptide chains with ClpB, ClpA, and ClpAP (Rajendar and Lucius 2010, Miller, Lin, Li and Lucius 2013, Miller and Lucius 2014, Li, Weaver, Lin et al. 2015).

      (3) The model assumes the same time constant for all the unfolding steps irrespective of the secondary structural interactions.

      Yes, we contend that this is a good assumption because it represents repetition of protein unfolding catalyzed by ClpB upon encountering the same repeating structural elements, i.e. Beta sheets. 

      (4) Unlike other single-molecule optical tweezer-based assays, the study cannot distinguish the unfolding and translocation events and assumes that unfolding is the rate-limiting step.

      Although we cannot, directly, distinguish between protein unfolding and translocation we have logically concluded that protein unfolding is likely rate limiting. This is because the large kinetic step-size represents the collapse of ~60 amino acids of structure between two rate-limiting steps, which we interpret to represent cooperative protein unfolding induced by ClpB.  It is not an assumption it is our current best interpretation of the observations that we are now seeking to further test. 

      Reviewer #3 (Public Review):

      Summary:

      The authors have devised an elegant stopped-flow fluorescence approach to probe the mechanism of action of the Hsp100 protein unfoldase ClpB on an unfolded substrate (RepA) coupled to 1-3 repeats of a folded titin domain. They provide useful new insight into the kinetics of ClpB action. The results support their conclusions for the model setup used.

      Strengths:

      The stopped-flow fluorescence method with a variable delay after mixing the reactants is informative, as is the use of variable numbers of folded domains to probe the unfolding steps.

      Weaknesses:

      The setup does not reflect the physiological setting for ClpB action. A mixture of ATP and ATPgammaS is used to activate ClpB without the need for its co-chaperones, Hsp70. Hsp40 and an Hsp70 nucleotide exchange factor. This nucleotide strategy was discovered by Doyle et al (2007) but the mechanism of action is not fully understood. Other authors have used different approaches. As mentioned by the authors, Weibezahn et al used a construct coupled to the ClpA protease to demonstrate translocation. Avellaneda et al used a mutant (Y503D) in the coiled-coil regulatory domain to bypass the Hsp70 system. These differences complicate comparisons of rates and step sizes with previous work. It is unclear which results, if any, reflect the in vivo action of ClpB on the disassembly of aggregates.

      We agree with the reviewer, there are several strategies that have been employed to bypass the need for Hsp70/40 or KJE to simplify in vitro experiments.  Here we have developed a first of its kind transient state kinetics approach that can be used to examine processive protein unfolding.  We now seek to go forward with examining the mechanisms of hyperactive mutants, like Y503D, and add the co-chaperones so that we can address the limitations articulated by the reviewer.   In fact we already began adding DnaK to the reaction and found that DnaK induced ClpB to release the polypeptide chain (Durie, Duran and Lucius 2018).  However, the sequential mixing strategy developed here was needed to go forward with examining the impact of co-chaperones. 

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Line 1: I recommend changing the title of the paper to remove the terms that are not clearly defined in the text: "robust" and "processive". What are the Authors' criteria for describing a molecular machine as "robust" vs. "not robust"? A definition of processivity is given in equation 2, but its value for ClpB is not reported in the text, and the criteria for classifying a machine as "processive" vs. "non-processive" are not included. Besides, the Authors have previously reported that ClpB is non-processive (Biochem. J., 2015), so it is now clear that a more nuanced terminology should be applied to this protein. Also, Escherichia coli should be fully spelled out in the title.

      The title has been changed.  We have removed “robust” as we agree with the reviewer, there is no way to quantify “robust”.  However, we have kept “processive” and have added to the discussion a calculation of processivity since we can quantify processivity.  Importantly, the unstructured substrates used in our previous studies represent translocation and not protein unfolding.  here, on folded substrates, we detect rate-limiting protein unfolding followed by rapid translocation.  Thus, we report a lower bound on protein unfolding processivity of 362 amino acids. 

      Line 20: The comment about mitochondrial SKD3 should be removed. SKD3, like ClpB, belongs to the AAA+ family, and it is simply a coincidence that the original study that discovered SKD3 termed it an Hsp100 homolog. The similarity between SKD3 and ClpB is limited to the AAA+ module, so there are many other metazoan ATPases, besides SKD3, that could be called homologs of ClpB, including mitochondrial ClpX, ER-localized torsins, p97, etc.

      Removed.

      Lines 133-139. Contrary to what the authors state, it is not clear that the "lag-phase" becomes significantly shorter for subsequent mixing experiments (Figure 1E) perhaps except for the last one (2070 s). It is clear, however, that the emission enhancement becomes stronger for later mixes. This effect should be discussed and explained, as it suggests that the pre-equilibrations shorter than ~2000 sec do not produce saturation of ClpB binding to the substrate.

      We have added supplemental figure 2, which represents a zoom into the lag region.  This better illustrates what we were seeing but did not clearly show to the reader.  In addition, we address all three changes in the time courses, i.e. extend of lag, change in peak position, and the change in peak height. 

      Line 175. The hydrolysis rate of ATPgammaS in the presence of ClpB should be measured and compared to the hydrolysis rate with ATP/ATPgammaS to check if the ratio of those rates agrees with the ratio of the translocation rates. These experiments should be performed with and without the RepA-titin substrate, which could reveal an important linkage between the ATPase engine and substrate translocation. These experiments are essential to support the claim of substrate translocation and unfolding with ATPgammaS as the sole energy source.

      The time courses shown in figure 2 and supplemental Figure 1 are collected with only ATPgS and no ATP.  The time courses show a clear increase in lag and appearance of a peak with increasing number of tandem repeats of titin domains.  We do not see an alternate explanation for this observation other than ATPγS supports ClpB catalyzed protein unfolding and translocation.  What is the reviewers alternate explanation for these observations?

      We agree with the reviewer that the linkage of ATP hydrolysis to protein unfolding and translocation is essential and we are seeking to acquire this knowledge.  However, a simple comparison of the ratio of rates is not adequate. We contend that a complete mechanistic study of ATP turnover by ClpB is required to properly address this linkage and such a study is too substantial to be included here but is currently underway. 

      All that said, the statement on line 175 was removed since we do not report any ATPase measurements in this paper.

      Line 199: It is an over-simplification to state that "1:1 mix of ATP to ATPgammaS replaces the need for co-chaperones". This sentence should be corrected or removed. The ClpB co-chaperones (DnaK, DnaJ, GrpE) play a major role in targeting ClpB to its aggregated substrates in cells and in regulating the ClpB activity through interactions with its middle domain. ATPgammaS does not replace the co-chaperones; it is a chemical probe that modifies the mechanism of ClpB in a way that is not entirely understood.

      We agree with the reviewer.  The sentence has been modified to point out that the mix of ATP and ATPγS activates ClpB.

      Figure 3B, Supplementary Figure 5A. The solid lines from the model fit cannot be distinguished from the data points. Please modify the figures' format to clearly show the fits and the data points.

      Done.

      Lines 326, 329. It is not clear why the authors mention a lack of covalent modification of substrates by ClpB. AAA+ ATPases do not produce covalent modifications of their substrates.

      The issue of covalent modification was presented in the introduction lines 55 – 60 pointing out that much of what we have learned about protein unfolding and translocation catalyzed by ClpA and ClpX is from the observations of proteolytic degradation catalyzed by the associated protease ClpP.  However, this approach is not possible for ClpB/Hsp104 as these motors do not associate with a protease unless they have been artificially engineered to do so. 

      Lines 396-399. I am puzzled why the authors try to correlate the size of the detected kinetic step with the length of the ClpB channel instead of the size characteristics of the substrate.

      We are attempting to discuss/rationalize the observed large kinetic step-size which, in part, is defined by the structural properties of the enzyme as well as the size characteristics of the substrate.  We have attempted to clarify this and better discuss the properties of the substrate as well as ClpB.

      As I mentioned in the Public Review, it is essential to demonstrate that the emission increase used as the only readout of the ClpB position along the substrate is indeed caused by the proximity of ClpB to the fluorophore. One way to accomplish that would be to place the fluorophore upstream from the first I27 domain and determine if the "lag phase" in the emission enhancement disappears.

      Alexa Fluor 555 is well established to exhibit PIFE.  However, as in the response to the public review, we have included an appropriate control showing this in supplemental Fig. 1.

      Finally, the authors repetitively place their results in opposition to the study of Weibezahn et al. published in 2004 which first demonstrated substrate translocation by engineering a peptidase-associated variant of ClpB. It should be noted that the field of protein disaggregases has moved since the time of that publication from the initial "from-start-to-end" translocation model to a more nuanced picture of partial translocation of polypeptide loops with possible substrate slipping through the ClpB channel and a dynamic assembly of ClpB hexamers with possible subunit exchange, all of which may affect the kinetics in a complex way. However, the present study confirmed the "start-to-end" translocation model, albeit for a non-physiological ClpB substrate, and that is the take-home message, which should be included in the text.

      It is not clear to us that the field has “moved on” since Weibezahn et al 2004.  Their engineered construct that they term “BAP” with ClpP is still used in the field despite us reporting that proteolytic degradation is observed in the absence of ATP with that system  (Li, Weaver, Lin et al. 2015) and should, therefore, not be used to conclude processive energy driven translocation. The “partial translocation” by ClpB is also grounded in observations of partial degradation catalyzed by ClpP with BAP from the same group (Haslberger, Zdanowicz, Brand et al. 2008). It is not clear to us that the idea of subunit exchange leading to the possibility of assembly around internal sequences is being considered.  We do agree that this is an important mechanistic possibility that needs further interrogation. We agree with the reviewer, all these factors are confounding and lead to a more nuanced view of the mechanism.

      All that said, we have removed some of the opposition in the discussion.

      Reviewer #2 (Recommendations For The Authors):

      (1) It is assumed that the lag phase will be much longer than the phase in which we see a gradual increase in fluorescence, as the effect of PIFE is significant only when the enzyme is very close to the fluorophore. Particularly for RepA-titin3, the enzyme has to translocate many tens of nm before it is closer to the C-terminus fluorophore. However, in all cases, the lag time is lower or similar to the gradual increase phase (for example, Figure 3B). Could the authors explain this?

      The extent of the lag, or time zero until the signal starts to increase, is interpreted to indicate the time the motor moves from it’s initial binding site until it gets close enough to the fluorophore that PIFE starts to occur.  In our analysis we apply signal change to the last intermediate and dissociation or release of unfolded RepA-TitinX.  The increase in PIFE is not “all or nothing”.  Rather, it is starting to increase gradually.  Further, because these are ensemble measurements, and each molecule will exhibit variability in rate there is increased breadth of the peak due to ensemble averaging. 

      (2) Although the reason for differences in the peak position (for example, Figure 1E, 2B) is apparent, the reason for variations in the relative intensities has to be given or speculated.

      We have addressed the reason for the different peak heights in the revised manuscript.  It is the consequence of the fact that each substrate has slightly different fluorescent labeling efficiencies.  Thus, for each sample there is a mix of labeled and unlabeled substrates both of which will bind to ClpB but the unlabeled ClpB bound substrates do not contribute to the fluorescence signal, but will represent a binding competitor.  Thus, for low labeling efficiency there is a lower concentration of ClpB bound to fluorescent RepA-Titinx and for higher labeling efficiency there is higher concentration of ClpB bound to RepA-Titinx leading to an increased peak height.  RepA-Titin2 has the highest labeling efficiency and thus the largest peak height.

      Reviewer #3 (Recommendations For The Authors):

      The authors should make it clear that they and previous authors have used different constructs or conditions to bypass the physiological regulation of ClpB action by Hsp70 and its co-factors as mentioned above. In particular, the construct used by Avellaneda et al should be explained when they challenge the findings of those authors.

      Minor points:

      The lines fitting the experimental points are difficult or impossible to see in Figures 2B, 3B, and s5B.

      Fixed

      Typo bottom of p6 - "averge"

      Fixed

      Avellaneda, M. J., K. B. Franke, V. Sunderlikova, B. Bukau, A. Mogk and S. J. Tans (2020). "Processive extrusion of polypeptide loops by a Hsp100 disaggregase." Nature.

      Doyle, S. M., J. Shorter, M. Zolkiewski, J. R. Hoskins, S. Lindquist and S. Wickner (2007). "Asymmetric deceleration of ClpB or Hsp104 ATPase activity unleashes protein-remodeling activity." Nature structural & molecular biology 14(2): 114-122.

      Durie, C. L., E. C. Duran and A. L. Lucius (2018). "Escherichia coli DnaK Allosterically Modulates ClpB between High- and Low-Peptide Affinity States." Biochemistry 57(26): 3665-3675.

      Haslberger, T., A. Zdanowicz, I. Brand, J. Kirstein, K. Turgay, A. Mogk and B. Bukau (2008). "Protein disaggregation by the AAA+ chaperone ClpB involves partial threading of looped polypeptide segments." Nat Struct Mol Biol 15(6): 641-650.

      Li, T., J. Lin and A. L. Lucius (2015). "Examination of polypeptide substrate specificity for Escherichia coli ClpB." Proteins 83(1): 117-134.

      Li, T., C. L. Weaver, J. Lin, E. C. Duran, J. M. Miller and A. L. Lucius (2015). "Escherichia coli ClpB is a non-processive polypeptide translocase." Biochem J 470(1): 39-52.

      Miller, J. M., J. Lin, T. Li and A. L. Lucius (2013). "E. coli ClpA Catalyzed Polypeptide Translocation is Allosterically Controlled by the Protease ClpP." Journal of Molecular Biology 425(15): 2795-2812.

      Miller, J. M. and A. L. Lucius (2014). "ATP-gamma-S Competes with ATP for Binding at Domain 1 but not Domain 2 during ClpA Catalyzed Polypeptide Translocation." Biophys Chem 185: 58-69.

      Oberhauser, A. F., P. K. Hansma, M. Carrion-Vazquez and J. M. Fernandez (2001). "Stepwise unfolding of titin under force-clamp atomic force microscopy." Proc Natl Acad Sci U S A 98(2): 468-472.

      Rajendar, B. and A. L. Lucius (2010). "Molecular mechanism of polypeptide translocation catalyzed by the Escherichia coli ClpA protein translocase." J Mol Biol 399(5): 665-679.

      Weibezahn, J., P. Tessarz, C. Schlieker, R. Zahn, Z. Maglica, S. Lee, H. Zentgraf, E. U. Weber-Ban, D. A. Dougan, F. T. Tsai, A. Mogk and B. Bukau (2004). "Thermotolerance requires refolding of aggregated proteins by substrate translocation through the central pore of ClpB." Cell 119(5): 653-665.

    1. Reviewer #2 (Public Review):

      Chong Wang et al. investigated the role of H3K4me2 during the reprogramming processes in mouse preimplantation embryos. The authors show that H3K4me2 is erased from GV to MII oocytes and re-established in the late 2-cell stage by performing Cut & Run H3K4me2 and immunofluorescence staining. Erasure and re-establishment of H3K4me2 have not been studied well, and profiling of H3K4me2 in germ cells and preimplantation embryos is valuable to understanding the reprogramming process and epigenetic inheritance.

      (1) The authors claim that the Cut & Run worked for MII oocytes, zygotes, and the 2-cell embryos. However, it is unclear if H3K4me2 is erased during the stage or if the Cut & Run did not work for these samples. To support the hypothesis of the erasure of H3K4me2, the authors conducted immunofluorescence staining, and H3k4me2 was undetected in the MII oocyte, PN5, and 2-cell stage. However, the published papers showed strong staining of H3K4me2 at the zygote stage and 2-cell stage ((Ancelin et al., 2016; Shao et al., 2014)). The authors need to cite these papers and discuss the contradictory findings.

      The authors used 165 MII oocytes and 190 GV oocytes for the Cut & Run. The amount of DNA in MII oocytes is halved because of the emission of the first polar body. Would it be a reason that H3K4me2 has fewer H3K4me2 peaks in MII oocytes than GV oocytes?

      In Figure 3C, 98% (13,183/13,428) of H3K4me2 marked genes in GV oocytes overlap with those in the 4-cell stage. Furthermore, 92% (14,049/15,112) of H3K4me2 marked genes in sperm overlap with those in the 4-cell stage. Therefore, most regions maintain germ line-derived H3K4me2 in the 4-cell stage. The authors need to clarify which regions of germ line-derived H3K4me2 are maintained or erased in preimplantation embryos. Additionally, it would be interesting to investigate which regions show the parental allele-specific H3K4me2 in preimplantation embryos since the authors used hybrid preimplantation embryos (B6 x DBA).

      (2) The authors claim that Kdm1a is rarely expressed during mouse embryonic development (Figure 4A). However, the published paper showed that KDM1a is present in the zygote and 2-cell stage using immunostaining and western blotting ((Ancelin et al., 2016)). Additionally, this paper showed that depletion of maternal KDM1A protein results in developmental arrest at the two-cell stage, and therefore, KDM1a is functionally important in early development. The authors should have cited the paper and described the role of KDM1a in early embryos.

      (3) The authors used the published RNA data set and interpreted that KDM1B (LSD2) was highly expressed at the MII stage (Figure S3A). However, the heat map shows that KDM1B expression is high in growing oocytes but not at 8w_oocytes and MII oocytes. The authors need to interpret the data accurately.

      (4) All embryos in the TCP group were arrested at the four-cell stage. Embryos generated from KDM1b KO females can survive until E10.5 (Ciccone et al., 2009); therefore, TCP-treated embryos show a more severe phenotype than oocyte-derived KDM1b deleted embryos. Depletion of maternal KDM1A protein results in developmental arrest at the two-cell stage ((Ancelin et al., 2016)). The authors need to examine whether TCP treatment affects KDM1a expression. Western blotting would be recommended to quantify the expression of KDM1A and KDM1B in the TCP-treated embryos.

      (5) H3K4me2 is increased dramatically in the TCP-treated embryos in Figure 4 (the intensity is 1,000 times more than the control). However, the Cut & Run H3K4me2 shows that the H3K4me2 signal is increased in 251 genes and decreased in 194 genes in the TCP-treated embryos (Fold changes > 2, P < 0.01). The authors need to explain why the gain of H3K4me2 is less evident in the Cut & Run data set than in the immunofluorescence result.

      References

      Ancelin, K., ne Syx, L., Borensztein, M., mie Ranisavljevic, N., Vassilev, I., Briseñ o-Roa, L., Liu, T., Metzger, E., Servant, N., Barillot, E., Chen, C.-J., Schü le, R., & Heard, E. (2016). Maternal LSD1/KDM1A is an essential regulator of chromatin and transcription landscapes during zygotic genome activation. https://doi.org/10.7554/eLife.08851.001

      Ciccone, D. N., Su, H., Hevi, S., Gay, F., Lei, H., Bajko, J., Xu, G., Li, E., & Chen, T. (2009). KDM1B is a histone H3K4 demethylase required to establish maternal genomic imprints. Nature, 461(7262), 415-418. https://doi.org/10.1038/nature08315

      Shao, G. B., Chen, J. C., Zhang, L. P., Huang, P., Lu, H. Y., Jin, J., Gong, A. H., & Sang, J. R. (2014). Dynamic patterns of histone H3 lysine 4 methyltransferases and demethylases during mouse preimplantation development. In Vitro Cellular and Developmental Biology - Animal, 50(7), 603-613. https://doi.org/10.1007/s11626-014-9741-6

    2. Author response:

      Public Reviews:

      Reviewer #1 (Public Review): 

      By mapping H3K4me2 in mouse oocytes and pre-implantation embryos, the authors aim to elucidate how this histone modification is erased and re-established during the parental-to-zygotic transition, as well as how the reprogramming of H3K4me2 regulates gene expression and facilitates zygotic genome activation.

      Employing an improved CUT&RUN approach, the authors successfully generated H3K4me2 profiling data from a limited number of embryos. While the profiling experiments are very well executed, several weaknesses, particularly in data analysis, are apparent:

      (1) The study emphasizes H3K4me2, which often serves as a precursor to H3K4me3, a well-studied modification during early development. Analyzing the new H3K4me2 dataset alongside published H3K4me3 data is crucial for comprehensively understanding epigenetic reprogramming post-fertilization and the interplay between histone modifications. However, the current analysis is preliminary and lacks depth.

      Thank you very much for your valuable suggestions. The data of histone H3K4me3 in humans and mice has been published,and our previous data revealed the unique pattern of H3K4me3 during early human embryos and oocytes (Xia et al., 2019). So, this study mainly focuses on the localization of H3K4me2 in mouse oocytes and preimplantation embryos, how it is erased and re-established during mammalian parental-to-zygote transition, and its function. The combined analysis of H3K4me2 and H3K4me3 is not our main work, but it is not ruled out that there may be new discoveries between these two histones. Previously, our data tended to show that the H3K4me2 not only acts as a precursor of H3K4me3, but also plays its role independently.

      (2) Tranylcypromine (TCP) is known as an irreversible inhibitor of monoamine oxidase and LSD1. While the authors suggest TCP inhibits the expression of LSD2, this assertion is questionable. Given TCP's potential non-specific effects in cells, conclusions related to the experiments using TCP should be made with caution.

      Thank you for pointing this out, and we thank the reviewer again for the important suggestion. We found that the previous study indicated that TCP was a non-reversible inhibitor of LSD1 and LSD2, but according to our data, the content of LSD1 was very low in the early stages of mouse embryos, which mainly inhibited the function of LSD2. (Binda et al., 2010; Fang et al., 2010 )

      (3) Some batches of H3K4me2 antibody are known to cross-react with H3K4me3. Has the H3K4me2 antibody used in CUT&RUN been tested for such cross-reactivity? Heatmaps in the figures indeed show similar distribution for H3K4me2 and H3K4me3, further raising concerns about antibody specificity.

      We thank the reviewer for the insightful comments. The H3K4me2 antibody was purchased from Millipore (cat. 07030). Figure 2A shows the specific enrichment area of H3K4me2 in promoter and distal region. Some batches of H3K4me2 antibody are known to cross-react with H3K4me3, but the H3K4me2 antibody we used in our CUT&RUN seems to have Low cross-reactivity.

      (4) Certain statements lack supporting references or figures (examples on page 9 can be found on line 245, line 254, and line 258).

      Thank you for pointing this out, and we will add references to support the statement in the paper as suggested.

      (5) Extensive language editing is recommended to clarify ambiguous sentences. Additionally, caution should be taken to avoid overstatement - most analyses in this study only suggest correlation rather than causality.

      Thank you for your kind comments. We will revise the expression in the manuscript later.

      Reviewer #2 (Public Review):

      Chong Wang et al. investigated the role of H3K4me2 during the reprogramming processes in mouse preimplantation embryos. The authors show that H3K4me2 is erased from GV to MII oocytes and re-established in the late 2-cell stage by performing Cut & Run H3K4me2 and immunofluorescence staining. Erasure and re-establishment of H3K4me2 have not been studied well, and profiling of H3K4me2 in germ cells and preimplantation embryos is valuable to understanding the reprogramming process and epigenetic inheritance.

      (1) The authors claim that the Cut & Run worked for MII oocytes, zygotes, and the 2-cell embryos. However, it is unclear if H3K4me2 is erased during the stage or if the Cut & Run did not work for these samples. To support the hypothesis of the erasure of H3K4me2, the authors conducted immunofluorescence staining, and H3k4me2 was undetected in the MII oocyte, PN5, and 2-cell stage. However, the published papers showed strong staining of H3K4me2 at the zygote stage and 2-cell stage ((Ancelin et al., 2016; Shao et al., 2014)). The authors need to cite these papers and discuss the contradictory findings.

      The authors used 165 MII oocytes and 190 GV oocytes for the Cut & Run. The amount of DNA in MII oocytes is halved because of the emission of the first polar body. Would it be a reason that H3K4me2 has fewer H3K4me2 peaks in MII oocytes than GV oocytes?

      First of all, thank you for your valuable advice. The published papers showed strong staining of H3K4me2 at the zygote stage and 2-cell stage, which is interesting. I think we may have used different parameters in the confocal laser shooting process(Ancelin et al., 2016). We used the same parameter to continuously shoot the blastocyst stage from the GV stage. If we only shot the fertilized egg and the 2-cell stage, I think we may also see weak fluorescence at the 2-cell stage under different parameters. We will refer to this reference and discuss it in the resubmitted version.

      Moreover, you mentioned the H3K4me2 has fewer H3K4me2 peaks in MII oocytes than GV oocytes, because the MII expelled the polar body. There is no problem with this logic. However, the first polar body expelled from the MII stage is still in the zona pellucida, and we also collected the polar body in the CUT&RUN experiment; Therefore, compared to GV, the DNA content of MII samples is not halved. After further discussion, we believe that the reduction of H3K4me2 peaks in MII stage compared with GV stage may be closely related to oocyte maturation. It is the specific modification of histones in different forms at different times that affects the chromatin structure change appropriately with the different stages of meiosis. At present, it has been confirmed that H3K4me3 gradually decreases from GV to MII stage during the maturation of human oocytes. H3K27me3 did not change from GV to MII stage.

      In Figure 3C, 98% (13,183/13,428) of H3K4me2 marked genes in GV oocytes overlap with those in the 4-cell stage. Furthermore, 92% (14,049/15,112) of H3K4me2 marked genes in sperm overlap with those in the 4-cell stage. Therefore, most regions maintain germ line-derived H3K4me2 in the 4-cell stage. The authors need to clarify which regions of germ line-derived H3K4me2 are maintained or erased in preimplantation embryos. Additionally, it would be interesting to investigate which regions show the parental allele-specific H3K4me2 in preimplantation embryos since the authors used hybrid preimplantation embryos (B6 x DBA).

      Thank you very much for your suggestion. Further analysis of which regions show the parental allele-specific H3K4me2 in preimplantation embryos will make the study more interesting. We will discuss this in depth in resubmitted vision.

      (2) The authors claim that Kdm1a is rarely expressed during mouse embryonic development (Figure 4A). However, the published paper showed that KDM1a is present in the zygote and 2-cell stage using immunostaining and western blotting ((Ancelin et al., 2016)). Additionally, this paper showed that depletion of maternal KDM1A protein results in developmental arrest at the two-cell stage, and therefore, KDM1a is functionally important in early development. The authors should have cited the paper and described the role of KDM1a in early embryos.

      In the analysis of this experiment, we believe that in the early embryonic development of mice, the expression of KDM1A is lower than that of KDM1B, which is relative. Similarly, the transcriptome data we cite also show that KDM1A is expressed at elevated levels during oocyte maturation and fertilization compared to immature oocytes. In addition, the effects of loss of maternal KDM1a on embryonic development were not discussed. We believe that the absence of maternal KDM1b blocks embryonic development, and we will cite and discus the references later.

      (3) The authors used the published RNA data set and interpreted that KDM1B (LSD2) was highly expressed at the MII stage (Figure S3A). However, the heat map shows that KDM1B expression is high in growing oocytes but not at 8w_oocytes and MII oocytes. The authors need to interpret the data accurately.

      After re-checking the data, we found that there was a problem with the normalization method of our heat map, and we will re-make the heatmap and submit it in the modified version. With reference to Figure 4A, the content of Kdm1b is indeed higher than that of Kdm1a.

      (4) All embryos in the TCP group were arrested at the four-cell stage. Embryos generated from KDM1b KO females can survive until E10.5 (Ciccone et al., 2009); therefore, TCP-treated embryos show a more severe phenotype than oocyte-derived KDM1b deleted embryos. Depletion of maternal KDM1A protein results in developmental arrest at the two-cell stage ((Ancelin et al., 2016)). The authors need to examine whether TCP treatment affects KDM1a expression. Western blotting would be recommended to quantify the expression of KDM1A and KDM1B in the TCP-treated embryos.

      We will further dig the transcriptome data to confirm the specificity of TCP to KDM1b. In addition, the intervention of TCP on the whole fertilized egg in this study increased the H3K4me2 content, and the embryo development retarding effect was more significant than that obtained by crossing with normal paternal lines after knocking down KDM1B from the mother.

      (5) H3K4me2 is increased dramatically in the TCP-treated embryos in Figure 4 (the intensity is 1,000 times more than the control). However, the Cut & Run H3K4me2 shows that the H3K4me2 signal is increased in 251 genes and decreased in 194 genes in the TCP-treated embryos (Fold changes > 2, P < 0.01). The authors need to explain why the gain of H3K4me2 is less evident in the Cut & Run data set than in the immunofluorescence result.

      Thanks a lot for your question. In the experimental group, the fluorescence value of H3K4me2 in IF was increased by 1000 times (Figure 4E), and the expression of H3K4Me2-related genes in CR was up-regulated and down-regulated for a total of 445 changes (Figure 6A). In our opinion, as a semi-quantitative analysis, immunofluorescence cannot be compared with the quantitative analysis method of CR because of the different analysis models and threshold Settings.

      References

      Ancelin, K., ne Syx, L., Borensztein, M., mie Ranisavljevic, N., Vassilev, I., Briseñ o-Roa, L., Liu, T., Metzger, E., Servant, N., Barillot, E., Chen, C.-J., Schü le, R., & Heard, E. (2016). Maternal LSD1/KDM1A is an essential regulator of chromatin and transcription landscapes during zygotic genome activation. https://doi.org/10.7554/eLife.08851.001

      Ciccone, D. N., Su, H., Hevi, S., Gay, F., Lei, H., Bajko, J., Xu, G., Li, E., & Chen, T. (2009). KDM1B is a histone H3K4 demethylase required to establish maternal genomic imprints. Nature, 461(7262), 415-418. https://doi.org/10.1038/nature08315

      Shao, G. B., Chen, J. C., Zhang, L. P., Huang, P., Lu, H. Y., Jin, J., Gong, A. H., & Sang, J. R. (2014). Dynamic patterns of histone H3 lysine 4 methyltransferases and demethylases during mouse preimplantation development. In Vitro Cellular and Developmental Biology - Animal, 50(7), 603-613. https://doi.org/10.1007/s11626-014-9741-6

      References

      Xia W, Xu J, Yu G, Yao G, Xu K, Ma X, Zhang N, Liu B, Li T, Lin Z, Chen X, Li L, Wang Q, Shi D, Shi S, Zhang Y, Song W, Jin H, Hu L, Bu Z, Wang Y, Na J, Xie W, Sun YP. Resetting histone modifications during human parental-to-zygotic transition. Science. 2019 Jul 26;365(6451):353-360. doi: 10.1126/science.aaw5118. Epub 2019 Jul 4. PMID: 31273069.

      Binda C, Valente S, Romanenghi M, Pilotto S, Cirilli R, Karytinos A, Ciossani G, Botrugno OA, Forneris F, Tardugno M, Edmondson DE, Minucci S, Mattevi A, Mai A. Biochemical, structural, and biological evaluation of tranylcypromine derivatives as inhibitors of histone demethylases LSD1 and LSD2. J Am Chem Soc. 2010 May 19;132(19):6827-33.

      Fang R, Barbera AJ, Xu Y, Rutenberg M, Leonor T, Bi Q, Lan F, Mei P, Yuan GC, Lian C, Peng J, Cheng D, Sui G, Kaiser UB, Shi Y, Shi YG. Human LSD2/KDM1b/AOF1 regulates gene transcription by modulating intragenic H3K4me2 methylation. Mol Cell. 2010 Jul 30;39(2):222-33. doi: 10.1016/j.molcel.2010.07.008. PMID: 20670891; PMCID: PMC3518444.

      Ancelin K, Syx L, Borensztein M, Ranisavljevic N, Vassilev I, Briseño-Roa L, Liu T, Metzger E, Servant N, Barillot E, Chen CJ, Schüle R, Heard E. Maternal LSD1/KDM1A is an essential regulator of chromatin and transcription landscapes during zygotic genome activation. Elife. 2016 Feb 2;5:e08851. doi: 10.7554/eLife.08851. PMID: 26836306; PMCID: PMC4829419.

      Reviewer #3 (Public Review):

      Summary:

      This study explores the dynamic reprogramming of histone modification H3K4me2 during the early stages of mammalian embryogenesis. Utilizing the advanced CUT&RUN technique coupled with high-throughput sequencing, the authors investigate the erasure and re-establishment of H3K4me2 in mouse germinal vesicle (GV) oocytes, metaphase II (MII) oocytes, and early embryos.

      Strengths:

      The findings provide valuable insights into the temporal and spatial dynamics of H3K4me2 and its potential role in zygotic genome activation (ZGA).

      Weaknesses:

      The study primarily remains descriptive at this point. It would be advantageous to conduct further comprehensive functional validation and mechanistic exploration.

      Key areas for improvement include enhancing the innovation and novelty of the study, providing robust functional validation, establishing a clear model for H3K4me2's role, and addressing technical and presentation issues. The text would benefit from the introduction of a novel conceptual framework or model that provides a clear explanation of the functional consequences and molecular mechanisms underlying H3K4me2 reprogramming in the transition from parental to early embryonic development.

      While the findings are significant, the current manuscript falls short in several critical areas. Addressing major and minor issues will significantly strengthen the study's contribution to the field of epigenetic reprogramming and embryonic development.

    1. Author response:

      The following is the authors’ response to the original reviews.

      eLife assessment

      This is an important study on the regulation of chlorophyll biosynthesis in rice embryos. It provides insights into the genetic and molecular interactions that underlie chlorophyll accumulation, highlighting the inhibition of OsGLK1 by OsNF-YB7 and the broader implications for understanding chloroplast development and seed maturation in angiosperms. The results presented, including mutation analysis, gene expression profiles, and protein interaction studies, provide convincing evidence for the function of OsNF-YB7 as a repressor in the chlorophyll biosynthesis pathway.

      Thank you very much for your positive assessment of our manuscript. We have carefully revised the manuscript according to the reviewers’ valuable suggestions and comments. For more details, please see the point-to-point response to the reviewers below.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This manuscript investigates the regulation of chlorophyll biosynthesis in rice embryos, focusing on the role of OsNF-YB7. The rigorous experimental approach, combining genetic, biochemical, and molecular analyses, provides a robust foundation for these findings. The research achieves its objectives, offering new insights into chlorophyll biosynthesis regulation, with the results convincingly supporting the authors' conclusions.

      Strengths:

      The major strengths include the detailed experimental design and the findings regarding OsNF-YB7's inhibitory role.

      Weaknesses:

      However, the manuscript's discussion on the practical implications for agriculture and the evolutionary analysis of regulatory mechanisms could be expanded.

      Thank you for your insightful comments and suggestions. In the revised manuscript, we discussed the potential application of the chlorophyllous embryo (please see line 270-274). The presence of chlorophyll in the embryo facilitates photosynthesis at early developmental stages, potentially leading to improved seedling growth and vigor (Smolikova and Medvedev, 2016). In crops such as soybean and canola, green embryo is considered as a valuable trait due to its association with enhanced photosynthetic capacity, which consequently promotes fatty acid biosynthesis (Ruuska et al., 2004). However, chlorophyll degradation must be carefully managed during seed maturation to avoid negative effects on seed viability and meal quality (Chung et al., 2006). Interestingly, the green embryo of lotus (Nelumbo nucifera) is widely used as a food ingredient in Asian, Australia, and North America. It is employed in herbal medicine to treat nervous disorders, insomnia, and other conditions (Zhu et al., 2017; Ha et al., 2022), highlighting the significant potential value of the green embryo.

      In many chloroembryophytes, such as Arabidopsis, the embryo occupies a large proportion of the seed. From an evolutionary perspective, the presence of chlorophyll in the embryo may promote adaptation in such chloroembryophytes because more reserves can be accumulated in the seed through active photosynthesis, better supporting the embryo development and subsequent seedling growth (Sela et al., 2020). On the other hand, some leucoembryophytes, such as rice, have persistent endosperm rich in storage reserves to nourish embryo development (Liu et al., 2022). Gaining the ability to accumulate chlorophyll in the embryo is unnecessary for such species. In agreement with this hypothesis, cholorophyllous embryos are more prevalent in non-endospermous seeds (Dahlgren, 1980). However, we would like to emphasize that the evolutionary force driving the divergence of chloroembryophytes and leucoembryophytes is currently almost completely unknown and deserves in-depth investigation in the future. We discussed the possible evolution of the ability to accumulate chlorophyll in the embryo, please find the details in Line 276-295.

      Reviewer #2 (Public Review):

      Summary:

      The authors set out to establish the role of the rice LEC1 homolog OsNF-YB7 in embryo development, especially as it pertains to the development of photosynthetic capacity, with chlorophyll production as a primary focus.

      Strengths:

      The results are well-supported and each approach used complements each other. There are no major questions left unanswered and the central hypothesis is addressed in every figure.

      Weaknesses:

      There are a handful of sections that could use clarifying for readers, but overall this is a solidly composed manuscript.

      The authors clearly achieved their aims; the results compellingly establish a disparity between how this system operates in rice and Arabidopsis. Conclusions are thoroughly supported by the provided data and interpretations. This work will force a reconsideration of the value of Arabidopsis as a model organism for embryo chlorophyll biosynthesis and possibly photosynthesis during embryo maturation more broadly, as rice is a major crop organism and it very clearly does not follow the Arabidopsis model. It will thus be useful to carry out similar tests in other organisms rather than relying on Arabidopsis and attempting to more fully establish the regulatory mechanism in rice.

      Thank you very much for your positive comments. We have carefully revised the manuscript according to your and the other reviewers’ comments and suggestions. Particularly, we emphasized the necessary to carry out similar tests in other organisms rather than relying on Arabidopsis to better understand the regulatory mechanism in rice.

      Reviewer #3 (Public Review):

      Summary:

      In this study, the authors set out to understand the mechanisms behind chlorophyll biosynthesis in rice, focusing in particular on the role of OsNF-YB7, an ortholog of Arabidopsis LEC1, which is a positive regulator of chlorophyll (Chl) biosynthesis in Arabidopsis. They showed that OsNF-YB7 loss-of-function mutants in rice have chlorophyll-rich embryos, in contrast to Arabidopsis LEC1 loss-of-function mutants. This contrasting phenotype led the authors to carry out extensive molecular studies on OsNF-YB7, including in vitro and in vivo protein interaction studies, gene expression profiling, and protein-DNA interaction assays. The evidence provided well supported the core arguments of the authors, emphasising that OsNF-YB7 is a negative regulator of Chl biosynthesis in rice embryos by mediating the expression of OsGLK1, a transcription factor that regulates downstream Chl biosynthesis genes. In addition, they showed that OsNF-YB7 interacts with OsGLK1 to negatively regulate the expression of OsGLK1, demonstrating the broad involvement of OsNF-YB7 in rice Chl biosynthetic pathways.

      Strengths:

      This study clearly demonstrated how OsNF-YB7 regulates its downstream pathways using several in vitro and in vivo approaches. For example, gene expression analysis of OsNF-YB7 loss-of-function and gain-of-function mutants revealed the expression of selected downstream chl biosynthetic genes. This was further validated by EMSA on the gel. The authors also confirmed this using luciferase assays in rice protoplasts. These approaches were used again to show how the interaction of OsNF-YB7 and OsGLK1 regulates downstream genes. The main idea of this study is very well supported by the results and data.

      Weaknesses:

      From an evolutionary perspective, it is interesting to see how two similar genes have come to play opposite roles in Arabidopsis and rice. It would have been more interesting if the authors had carried out a cross-species analysis of AtLEC1 and OsNF-YB7. For example, overexpressing AtLEC1 in an osnf-yb7 mutant to see if the phenotype is restored or enhanced. Such an approach would help us understand how two similar proteins can play opposite roles in the same mechanism within their respective plant species.

      We appreciate your insightful comments and suggestions. It is a very interesting question whether AtLEC1 can fully restore osnf-yb7, given the possible functional divergence between the genes in terms of regulation of chlorophyll biosynthesis in the embryo. We have previously expressed OsNF-YB7 in the lec1-1 background in Arabidopsis, driven by the native promoter of LEC1 (Niu et al., 2021). We found that OsNF-YB7 could almost completely rescue the embryo defects in Arabidopsis, indicating that OsNF-YB7 plays a resemble role in rice as the LEC1 does in Arabidopsis (Niu et al., 2021). We sought to determine whether AtLEC1 can complement the chlorophyll defect in osnf-yb7. However, given the fact that osnf-yb7 shows severe callus induction defect, which is not surprising, because many studies have shown that LEC1 is indispensable for somatic embryo development in various plant species, we are struggling to obtain the genetic materials for analysis. We have to transform OsNF-YB7pro::AtLEC1 into the WT background first, and then cross the transformant with the osnf-yb7 mutant. This is a time-consuming process in rice, but hopefully we will able to isolate a line expressing OsNF-YB7pro::AtLEC1 in the osnf-yb7 background from the resulting segregating population.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      A minor comment regarding the chlorophyll contents quantification in the study. Line 87: "The results showed that WT had an achlorophyllous embryo throughout embryonic development,...." In the TEM result, chloroplast was not observed in the WT embryo sections, indicating a lack of chlorophyll-containing structures, contrary to what was found in the osnf-yb7 embryos where chloroplasts were observed.

      The authors stated that the embryo morphologies and Chl autofluorescence data showed that WT had an achlorophyllous embryo throughout embryonic development. However, the quantification of Chl levels in Figure 1D and Figure 4C showed that WT does produce some chlorophylls, albeit at lower levels than osnf-yb7 or OSGLK-OX embryos (WT values in the two figures are slightly different). This discrepancy warrants clarification to ensure consistency and accuracy in the manuscript's findings.

      We re-evaluated the Chl content in the embryos of WT and OsGLK1-OX mature seeds. The result confirmed our previous finding that WT embryos produce a small amount of chlorophyll (please see the updated Fig. 4C). Notably, we observed that the dark-grown etiolated plants still have measurable chlorophyll content as reported in many studies (for example, Wang et al., 2017; Yoo et al., 2019), suggesting that there is potential bias in measuring chlorophyll content using an absorbance-based approach. We assume this possibly explains the concern you have raised.

      Reviewer #2 (Recommendations For The Authors):

      Mild editing for grammar is needed throughout, e.g. line 73, "It is still a mysterious why plant species".

      We have carefully edited the grammar.

      As a minor point, the placement of figure panels, such as in Figure 1, is not always intuitive.

      Thank you for your suggestion. This figure has been revised as suggested. Please see the updated Fig. 1.

      What is the significance of the two GFP mutants in Figures 2C and 2D? Is one of those the mislabeled Flag mutant?

      The lines showed in Fig. 2C and D were not mislabeled. They were two independent transgenic events, both of which showed that OsNF-YB7 inhibited the expression of OsPORA and OsLHCB4 in rice. The transgenic lines overexpressing OsNF-YB7 tagging with the 3× Flag (NF-YB7-Flag) were also used for this experiment. In agreement, OsPORA and OsLHCB4 were significantly downregulated in the three independent NF-YB7-Flag lines (Fig. S4C), confirming the results showed in Fig. 2C and D.

      In Figures 2G and 2H, what is that enormous band at the bottom of the gel?

      The bands at the bottom of the gel were free probes. We indicated this in the revised figure.

      Not until the Materials and Methods section did I realize that any of this study was being done in tobacco; the Introduction implies it's rice vs. Arabidopsis and it might be a good idea to mention the organism of study somewhere before Figure 6.

      We apologize for any confusion caused by our previous writing. While the majority of this study was performed with rice plants or protoplasts, the split complementary LUC assays and BiFC assays were performed with tobacco. We have specified these in the revised manuscript as suggested.

      Reviewer #3 (Recommendations For The Authors):

      It would be nice if the author could show what the phenotype is in AtLEC1 OX in osnf-yb7 and also OsNF-YB7 OX in atlec1 mutants.

      Thank you for your suggestion. We have previously expressed OsNF-YB7 in the lec1-1 background of Arabidopsis, driven by the native promoter of Arabidopsis LEC1 (Niu et al., 2021). Since OsNF-YB7 could rescue the embryo morphogenesis defects in Arabidopsis (Niu et al., 2021), we assumed that OsNF-YB7 plays a similar role in rice as the LEC1 does in Arabidopsis. However, it remains unknown whether expression of LEC1 in osnf-yb7 may restore the chlorophyllous embryo phenotype in rice. As the generation of genetic material is time-consuming, and especially given the fact that osnf-yb7 has a severe callus induction defect, we are struggling to obtain the complementary line for analysis. We have to transform OsNF-YB7pro::AtLEC1 in a WT background first, and then cross the transformant with the osnf-yb7 mutant. Hopefully, we will be able to isolate a line expressing OsNF-YB7pro::AtLEC1 in osnf-yb7 background, from the derived segregating population. We discussed the reviewer’s concern in the revised manuscript, please see Line 369-376.

      Line 46, I think it is vague to mention that 'Like most plant species'. Some species might have different copy numbers, for example, a single GLK in liverwort M. polymorpha.

      The statement has been revised. Please see Line 46.

      Figures 2F and 5B, why was only one promoter region used for OsLHCB4? It would be better to have more regions like OsPORA.

      Thank you for your comments. Here, we have examined more promoter regions (P1, P2 and P3) in the revised manuscript as suggested, among which, the previously selected promoter region (P3) contains both the G-box and CCAATC motifs that can be potentially recognized by GLK1. Consistent to our previous report, the results showed that OsNF-YB7 (left) and OsGLK1 (right) were associated with the P3 region, but showed no significant differences in the other probes. Please see the results in Fig. 2F and Fig. 5B of the revised manuscript.

      Legend of Figures 2G, H, OsPORA (I), and OsLHCB (J) should be (G) and (H) respectively.

      Corrected.

      References

      Chung, D.W., Pruzinska, A., Hortensteiner, S., and Ort, D.R. (2006). The role of pheophorbide a oxygenase expression and activity in the canola green seed problem. Plant Physiol 142, 88-97.

      Ha, T., Kim, M.S., Kang, B., Kim, K., Hong, S.S., Kang, T., Woo, J., Han, K., Oh, U., Choi, C.W., and Hong, G.S. (2022). Lotus Seed Green Embryo Extract and a Purified Glycosyloxyflavone Constituent, Narcissoside, Activate TRPV1 Channels in Dorsal Root Ganglion Sensory Neurons. J Agric Food Chem 70, 3969-3978.

      Liu, J., Wu, M.W., and Liu, C.M. (2022). Cereal Endosperms: Development and Storage Product Accumulation. Annu Rev Plant Biol 73, 255-291.

      Niu, B., Zhang, Z., Zhang, J., Zhou, Y., and Chen, C. (2021). The rice LEC1-like transcription factor OsNF-YB9 interacts with SPK, an endosperm-specific sucrose synthase protein kinase, and functions in seed development. Plant J 106, 1233-1246.

      Ruuska, S.A., Schwender, J., and Ohlrogge, J.B. (2004). The capacity of green oilseeds to utilize photosynthesis to drive biosynthetic processes. Plant Physiol 136, 2700-2709.

      Sela, A., Piskurewicz, U., Megies, C., Mene-Saffrane, L., Finazzi, G., and Lopez-Molina, L. (2020). Embryonic Photosynthesis Affects Post-Germination Plant Growth. Plant Physiol 182, 2166-2181.

      Smolikova, G.N., and Medvedev, S.S. (2016). Photosynthesis in the seeds of chloroembryophytes. Russ J Plant Physl+ 63, 1-12.

      Wang, Z., Hong, X., Hu, K., Wang, Y., Wang, X., Du, S., Li, Y., Hu, D., Cheng, K., An, B., and Li, Y. (2017). Impaired Magnesium Protoporphyrin IX Methyltransferase (ChlM) Impedes Chlorophyll Synthesis and Plant Growth in Rice. Front Plant Sci 8, 1694.

      Yoo, C.Y., Pasoreck, E.K., Wang, H., Cao, J., Blaha, G.M., Weigel, D., and Chen, M. (2019). Phytochrome activates the plastid-encoded RNA polymerase for chloroplast biogenesis via nucleus-to-plastid signaling. Nat Commun 10, 2629.

      Zhu, M., Liu, T., Zhang, C., and Guo, M. (2017). Flavonoids of Lotus (Nelumbo nucifera) Seed Embryos and Their Antioxidant Potential. J Food Sci 82, 1834-1841.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      As a reviewer for this manuscript, I recognize its significant contribution to understanding the immune response to saprophytic Leptospira exposure and its implications for leptospirosis prevention strategies. The study is well-conceived, addressing an innovative hypothesis with potentially high impact. However, to fully realize its contribution to the field, the manuscript would benefit greatly from a more detailed elucidation of immune mechanisms at play, including specific cytokine profiles, antigen specificity of the antibody responses, and long-term immunity. Additionally, expanding on the methodological details, such as immunophenotyping panels, qPCR normalization methods, and the rationale behind animal model choice, would enhance the manuscript's clarity and reproducibility. Implementing functional assays to characterize effector T-cell responses and possibly investigating the microbiota's role could offer novel insights into the protective immunity mechanisms. These revisions would not only bolster the current findings but also provide a more comprehensive understanding of the potential for saprophytic Leptospira exposure in leptospirosis vaccine development. Given these considerations, I believe that after substantial revisions, this manuscript could represent a valuable addition to the literature and potentially inform future research and vaccine strategy development in the field of infectious diseases.

      Reviewer #2 (Public Review):

      Summary:

      The authors try to achieve a method of protection against pathogenic strains using saprophytic species. It is undeniable that the saprophytic species, despite not causing the disease, activates an immune response. However, based on these results, using the saprophytic species does not significantly impact the animal's infection by a virulent species.

      Strengths:

      Exposure to the saprophytic strain before the virulent strain reduces animal weight loss, reduces tissue kidney damage, and increases cellular response in mice.

      Weaknesses:

      Even after the challenge with the saprophyte strain, kidney colonization and the release of bacteria through urine continue. Moreover, the authors need to determine the impact on survival if the experiment ends on the 15th.

      Reviewer #3 (Public Review):

      Summary:

      Kundu et al. investigated the effects of pre-exposure to a non-pathogenic Leptospira strain in the prevention of severe disease following subsequent infection by a pathogenic strain. They utilized a single or double exposure method to the non-pathogen prior to challenge with a pathogenic strain. They found that prior exposure to a non-pathogen prevented many of the disease manifestations of the pathogen. Bacteria, however, were able to disseminate, colonize the kidneys, and be shed in the urine. This is an important foundational work to describe a novel method of vaccination against leptospirosis. Numerous studies have attempted to use recombinant proteins to vaccinate against leptospirosis, with limited success. The authors provide a new approach that takes advantage of the homology between a non-pathogen and a pathogen to provide heterologous protection. This will provide a new direction in which we can approach creating vaccines against this re-emerging disease.

      Strengths:

      The major strength of this paper is that it is one of the first studies utilizing a live non-pathogenic strain of Leptospira to immunize against severe disease associated with leptospirosis. They utilize two independent experiments (a single and double vaccination) to define this strategy. This represents a very interesting and novel approach to vaccine development. This is of clear importance to the field.

      The authors use a variety of experiments to show the protection imparted by pre-exposure to the non-pathogen. They look at disease manifestations such as death and weight loss. They define the ability of Leptospira to disseminate and colonize the kidney. They show the effects infection has on kidney architecture and a marker of fibrosis. They also begin to define the immune response in both of these exposure methods. This provides evidence of the numerous advantages this vaccination strategy may have. Thus, this study provides an important foundation for future studies utilizing this method to protect against leptospirosis.

      Weaknesses:

      Although they provide some evidence of the utility of pretreatment with a non-pathogen, there are some areas in which the paper needs to be clarified and expanded.

      The authors draw their conclusions based on the data presented. However, they state the graphs only represent one of two independent experiments. Each experiment utilized 3-4 mice per group. In order to be confident in the conclusions, a power analysis needs to be done to show that there is sufficient power with 3-4 mice per group. In addition, it would be important to show both experiments in one graph which would inherently increase the power by doubling the group size, while also providing evidence that this is a reproducible phenotype between experiments. Overall, this weakens the strength of the conclusions drawn and would require additional statistical analysis or additional replicates to provide confidence in these conclusions.

      A direct comparison between single and double exposure to the non-pathogen is not able to be determined. The ages of mice infected were different between the single (8 weeks) and double (10 weeks) exposure methods, thus the phenotypes associated with LIC infection are different at these two ages. The authors state that this is expected, but do not provide a reasoning for this drastic difference in phenotypes. It is therefore difficult to compare the two exposure methods, and thus determine if one approach provides advantages over the other. An experiment directly comparing the two exposure methods while infecting mice at the same age would be of great relevance to and strengthen this work.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Major Comments

      (1) Elucidation of Immune Mechanisms: The manuscript intriguingly suggests that exposure to saprophytic Leptospira primes the host for a Th1-biased immune response, contributing to survival and mitigation of disease severity upon subsequent pathogenic challenge. However, the underlying mechanisms remain broadly defined. A more detailed investigation into the cytokine profiles, particularly the levels of IFN-γ, IL-12, and other Th1-associated cytokines, could clarify the mechanism of Th1 bias. Moreover, exploring the role of antigen-presenting cells (APCs) in priming T cells towards a Th1 phenotype would add valuable insights.

      In this study we continue to elucidate the immune mechanisms engaged by pathogenic and non-pathogenic Leptospira as a follow up to our previous work (Shetty et al, 2021 PMID: 34249775, and Kundu et al 2022 PMID 35392072). We, and others, have shown that saprophytic L. biflexa and pathogenic L. interrogans induce major chemo-cytokines associated with Th1 biased immune responses (Shetty et al. 2021; Cagliero et al. 2022; Krangvichian et al. 2023) and engage myeloid immune cells such as macrophages and dendritic cells. The role of antigen presenting cells such as dendritic cells in priming T cells and activating adaptive response is a separate question and can be addressed in the future. To further address this question, a recent mechanistic study (Krangvichian et al. 2023) showed that non-pathogenic leptospires (L. biflexa) promote MoDC maturation and stimulate the proliferation of IFN-γ-producing CD4+ T cells and potentially elicit a Th1-type response in mice, which also supports our current claim and it is referenced in our manuscript.

      (2) Quantitative Analysis of Kidney Colonization: The manuscript reports that pre-exposure to L. biflexa did not prevent the colonization of kidneys by L. interrogans but led to a more regulated immune response and reduced fibrosis. A more nuanced quantification of bacterial loads in the kidneys, using techniques such as CFU counting or more sensitive qPCR methods, could provide a clearer picture of how saprophytic exposure affects the ability of pathogenic Leptospira to establish infection. Additionally, a time-course study showing the kinetics of bacterial colonization and clearance post-infection would be informative.

      We are currently validating digital PCR to use in the future and plan to do time course studies.

      (3) Characterization of B Cell and T Cell Responses: While the manuscript mentions increased B cell frequencies and effector T helper cell responses, specifics regarding the nature of these responses are lacking. For instance, detailing the isotype and specificity of antibodies produced, the proliferation rates of specific B and T cell subsets, and their functional capabilities (e.g., cytotoxicity, help for B cells) would significantly enrich the understanding of the immune response elicited by pre-exposure to saprophytic Leptospira.

      Indeed, additional experiments need to be conducted to flush out the immune responses engaged after pre-exposure to saprophytic Leptospira followed by LIC challenge.

      (4) Comparative Analysis with Other Models of Pre-exposure: The study primarily focuses on pre-exposure to a live saprophytic Leptospira. Including a comparison with pre-exposure to killed saprophytic bacteria, or even to other non-pathogenic microbes, could help discern whether the observed protective effect is unique to live saprophytic Leptospira exposure or if it represents a more general phenomenon of trained immunity.

      Regarding the use of other non-pathogenic microbes, our lab has shown in the past that oral use of probiotic strain Lactobacillus plantarum (Potula et al 2017) also reduces the severity of Leptospirosis by recruiting myeloid cells. Thus, there may be a general phenomenon of trained immunity involved. We added this to the discussion.

      (5) Assessment of Long-term Immunity: The study provides valuable insights into the short-term outcomes following saprophytic Leptospira exposure and subsequent pathogenic challenge. Extending these observations to assess long-term immunity, including memory B and T cell responses several months post-infection, would be crucial for understanding the potential of saprophytic Leptospira exposure in providing lasting protection against leptospirosis.

      Long term immunity is a complex and separate question that we plan to address later.

      Minor Comments

      (1) Technical Specifics of Flow Cytometry Analysis: The manuscript could benefit from including more details on the flow cytometry gating strategy and the specific markers used to identify different immune cell subsets. This addition would aid in the reproducibility of the results and allow for a clearer interpretation of the immune profiling data.

      We included the technical specifics of the flow-cytometry analysis in the materials and methods section. The gating strategy (Fig S1) and the specific markers (TableS1) used to identify different immune cell subsets were incorporated in the supplementary datasheet. The cell specific markers were incorporated in the figures (Fig 5 and 6) under each representative cell subset which facilitates clarity and reproducibility of immune profiling.

      (2) Statistical Methodology for IgG Subtyping: The analysis of IgG subtypes in response to Leptospira exposure is intriguing but would be strengthened by specifying the statistical tests used to compare IgG1, IgG2a, and IgG3 levels between groups. Additionally, discussing the biological significance of the observed differences in IgG subtype levels would provide a more comprehensive understanding of the immune response.

      We applied the ordinary One-way ANOVA test to compare the IgG subtypes between groups followed by a Tukey’s multiple comparison correction analysis (included in the figure legend of Fig 4). We addressed the biological relevance of the observed differences in IgG subtype levels in the discussion section.

      (3) Details on Animal Welfare and Ethical Approval: While the manuscript mentions compliance with institutional animal care and use committee protocols, providing the specific ethical guidelines followed, such as the 3Rs (Replacement, Reduction, Refinement), would reinforce the commitment to ethical research practices.

      This is addressed in our institutional IACUC which is approved and listed in Methods.

      (4) Clarification of Figure Legends: Some figure legends are brief and could be expanded to more thoroughly describe what the figures show, including details on what specific data points, error bars, and statistical symbols represent.

      We updated and expanded the figure legends (Fig 1-4).

      (5) Revision of Introduction and Background: The introduction provides a good overview of leptospirosis and the rationale behind the study. However, it could be further improved by briefly summarizing current challenges in vaccine development against leptospirosis and how understanding the immune response to saprophytic Leptospira could address these challenges.

      We revised the introduction keeping this comment in mind.

      Reviewer #2 (Recommendations For The Authors):

      - Perform the same challenge experiment with a hamster.

      We clarified throughout the manuscript that all the work was done using the C3H-HeJ mouse model which was developed in our lab for the purpose of measuring differences in sublethal and lethal LIC infections. We leave the experiments using hamster to the investigators that have thoroughly validated the hamster model of lethal Leptospira infection.

      - Review the written part where it is understood that the challenge with saprophyte strain before virulence prevents the disease.

      We reviewed the manuscript to be understood that inoculation of mice with a saprophyte Leptospira before pathogenic challenge prevents severe leptospirosis and promotes kidney homeostasis and increased shedding of Leptospira in urine which is interesting. The last 2 sentences of the abstract read: “Thus, mice exposed to live saprophytic Leptospira before facing a pathogenic serovar may withstand infection with far better outcomes. Furthermore, a status of homeostasis may have been reached after kidney colonization that helps LIC complete its enzootic cycle.”

      Reviewer #3 (Recommendations For The Authors):

      (1) Line 83: The authors refer to the classification of Leptospira by old nomenclature. The bacteria are now categorized into clades P1, P2, S1 and S2. See Vincent et al. Revisiting the taxonomy and evolution of pathogenicity of the genus Leptospira through the prism of genomics. PLoS Negl Trop Dis. 2019 May 23;13(5):e0007270. doi: 10.1371/journal.pntd.0007270. PMID: 31120895; PMCID: PMC6532842.

      We have included the categories (S1 for L. biflexa and P1+ for L. interrogans) in introduction and methods but we did not update the figures because we want to be specific about the species used in these experiments. We also include a few sentences on evolution of Leptospira species in discussion and reference Thibeaux 2018, Vincent 2019 and Giraud-Gatineau, 2024.

      (2) Line 133: Please remove the extra line to be consistent with the rest of the method section format.

      We addressed all formatting issues.

      (3) Line 137: Are these primers specific to pathogenic L. interrogans? Or do they cross react with L. biflexa? If not specific, how long does L. biflexa stick around after infection?

      The primers are specific to the genus Leptospira. Surdel et al. in 2022 used 16s rRNA target sequence to amplify L. biflexa Patoc in mice at 6 hours post infection. We did not detect any positive sample for L. biflexa with the 16s rRNA primer set because we do our analysis 30 days and 45 days post inoculation with L. biflexa. We clarified this issue in methods and results.

      (4) Statistical analysis:

      (a) Some of your graphs have more than 4 points on them (such as Figure 4), while the legend still reads "represents one of two independent experiments". Are these actually combined replicates in the same graph? Combining them would provide strength to your conclusions throughout your manuscript and may provide stronger power for comparisons. If they are not included, why are they not included together? Please clarify what is included in each graph, and why the two experiments were not included together.

      We updated the legends with the total number of mice used in the experiment represented in the figure. Figures 1, 2, 4 and S2 contain the combined results from two independent experiments. Figures 3, 5 and 6 represent data from one of two independent experiments. For Fig 3 it would be redundant to show HE images of two experiments. Regarding Figs 5 and 6, the flow-cytometry equipment acquires data at different voltage every single time and biological samples vary between experiments even if all the markers and procedures are the same. So, we reproduce the experiment and show results from one experiment after confirming that the trend between individual experiments are the same.

      (b) If ANOVA was used, were all columns compared to each other? Why in some graphs are "ns" labeled only for certain comparisons? I would suggest removing the "ns" comparisons and only highlighting the significant differences.

      We have incorporated the comparison analysis between control (PBS) versus the PBS-LIC, LB versus LB-LIC and PBS-LIC versus LB-LIC in both the studies although we have compared significance between all groups.

      (5) Line 165: Bacteria were not plated, extract was plated. Perhaps you mean "extract corresponding to 107-108 bacteria"?

      We addressed it as follows: “Nunc MaxiSorp flat-bottom 96 well plates (eBioscience, San Diego, CA) were coated with extracts prepared from 107-108 bacteria per well and incubated at 4℃ overnight” …

      (6) Line 260: The authors claim that "Exposure to non-pathogenic L. biflexa before pathogenic L. interrogans challenge provided a significant immune cell boost with an increase in overall B and helper T cell frequencies..." However, in Figure 5A, the number of B cells in both the PBS2LIC2 and the LB2LIC2 are not significantly different. Thus, the claim is not supported by the evidence provided. It appears that infection with LIC led to similar increases in B cells regardless of pretreatment.

      We rephrased that title to reflect the finding that increased differences were measured in effector Helper T cells between PBS2LIC2 and LB2LIC2 (Figs 5D and 6B, 6C) and we re-wrote this section for clarity.

      (7) Lines 314-315: The authors claim that it protected against kidney fibrosis, however, the data only supports that only a single exposure to LB reduced levels of a marker associated with kidney fibrosis. Fibrosis was never directly measured.

      Indeed, we didn’t do Mason’s Trichrome stain to get supporting data for kidney fibrosis and only measured a fibrosis marker ColA1. We toned down this section: “ …. it may confer protection against kidney fibrosis.”

      (8) Line 317: Authors state that pre-exposure induced higher antibodies in serum, however, this was never shown. Only an increase in IgG2a was shown. Please word this statement to make it clear total antibodies were never measured.

      We did measure total anti-Leptospira interrogans IgM and IgG antibodies. We added the following sentence to description of these results: “In both experiments, total IgM and IgG were significantly increased in PBS-LIC and LB-LIC when compared to the respective controls, but not between PBS-LIC and LB-LIC.  Regarding IgG isotypes, IgG1…”

      (9) Line 323: The authors state that the exposure "induced antibody responses that provided heterologous protection." There is no evidence that the protection is due to the antibody response in these experiments. In fact, they also showed that it induced increased T cell responses.

      We toned down this statement: “In our study, exposure to a saprophytic Leptospira induced antibody responses that may provide heterologous protection against the pathogenic strain of Leptospira.”

      (10) Line 328: The authors us the term "stark difference", however, only slight differences are seen.

      We toned down that statement as follows:  “Differences in antibody titer among the L. interrogans infected….”

      (11) Line 490: reword this sentence to provide clarity and easier to read: "inoculated once with 10^8 L. biflexa at 6 weeks and they were challenged with 10^8 L. interrogans SEROVAR Copenhageni FioCruz (LIC) at 8 weeks."

      We revised the sentence.

      (12) Figure 1 and 2: Quantifying bacteria in culture after infection is not meaningful, as there are numerous factors that can affect the replication in culture after infection, such as how the organ perhaps was cut before placing it in culture. The comparisons in Figure 2E and F therefore are not interpretable. I would suggest presenting this data as Culture Positive or Culture Negative.

      We added these data to the figure under DFM (dark field microscopy).

      (13) Figure 3A: H&E staining often leads to different qualities of stains. But is there a better image that can be chosen for the PBS1LIC1 that provides a better comparison with the other images chosen? This is not worth repeating the experiment to get one, just make the figure look better if you have one available.

      We screened the images again but the one incorporated in the figure3A for PBS1LIC1 is the best.

      (14) Figure 3D: I agree that the PBS-LIC treatment is significant, but please include P value, as it looks very similar to the LB-LIC group. The two LIC groups are not significantly different, so the conclusion would be pre-exposure does not mitigate renal fibrosis marker ColA in the double-exposure study.

      We included the p-values in this figure. The two LIC groups are significantly different (ColA1) in the single exposure experiment, and the in double exposure we don’t expect to be able to measure ColA1 differences because the mice are older (10 wk) when we do the LIC challenge.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      Tang et al present an important manuscript focused on endogenous virus-like particles (eVLP) for cancer vaccination with solid in vivo studies. The author designed eVLP with high protein loading and transfection efficiency by PEG10 self-assembling while packaging neoantigens inside for cancer immunotherapy. The eVLP was further modified with CpG-ODN for enhanced dendritic cell targeting. The final vaccine ePAC was proven to elicit strong immune stimulation with increased killing effect against tumor cells in 2 mouse models. Below are my specific comments:

      Thanks very much to comment our work as “important”. We sincerely appreciate the extremely helpful comments from the reviewer to significantly improve the quality of our manuscript.

      (1) The figures were well prepared with minor flaws, such as missed scale bars in Figures 4B, 4K, 5B, and 5C. The author should also add labels representing statistical analysis for Figures 3C, 3D, and 3E. In Figure 6G, the authors should label which cell type is the data for.

      Thanks very much for the very suggestive comments. The scale bars and statistical analysis have been added in Figures 4B, 4K, 5B, 5C, 3C, 3D, and 3E. For Figure 6G, we have added “CD44+ CD62L- in CD8+ T cells” to explain the cell type.

      (2) In Figure 3H, the antigen-presenting cells (APCs) increased significantly, but there was also a non-negligible 10% of APCs found in the control group, indicating some potential unwanted immune response; the authors need to explain this phenomenon or add a cytotoxic test on the normal liver or other cell lines for confirmation.

      Thanks very much for this extremely helpful suggestion. The antigen-presenting cells (APCs) in Figure 3H were isolated from mouse bone marrow and then cultured in vitro for about 5 days with cytokine stimulation (IL-4 and GM-CSF). Due to the stimulation effects of IL-4 and GM-CSF, a small proportion of the APCs (~10%) was tending to mature (co-expressing CD80 and CD86) in the control group, as pointing out by the reviewer. Similarly, in Figure 3I, these 10% activated APCs can activate T cells in vitro and exhibit certain cytotoxicity. Since APCs must be induced and cultured in vitro before using in this experiment, the background cytotoxicity induced by cytokines is unavoidable, and this has been well documented in literatures.

      (3) In Figure 3I, the ePAC seems to have a very similar effect on cytotoxic T-cell tumor killing compared to the peptides + CpG group. If the concentrations were also the same, based on that, questions will arise as to what is the benefit of using the compact vector other than just free peptide and CpG? Please explain and elaborate.

      Thanks very much for the comment. In vitro experiments indeed demonstrated that peptides + CpG had the same T cell activating ability as ePAC, as pointing out by the reviewer. However, due to the instability of peptides and the lack of targeting, the efficiency of activating the immune system for peptides + CpG after subcutaneous injection is significantly lower than that for ePAC in vivo, as shown in Figure 3D and Figure 2A. Then, as expected, the antitumor efficacy induced by peptides alone + CpG is significantly lower than that induced by ePAC in Figure 5. We have provided a detailed description in “Results” section of “Antitumor effect of ePAC in subcutaneous HCC model” as follows: Furthermore, ePAC with the ability to target DCs and increased stability by encapsulating peptides, exhibited significantly higher tumor growth inhibition efficiency (p=0.0002) comparing with the eVLP + CpG-ODN treated group similar to the simple mixture of neoantigen peptides and adjuvant (Figures 5B and 5C). Meanwhile, the Kaplan-Meier analysis of tumor progression free survival (PFS) also clearly demonstrated the therapeutic advantages of our ePAC (p=0.0194, Figure 5B).

      (4) In the animal experiment in Figures 4F to L, the activation effect of APCs was similar between ePAC and CpG-only groups with no significance, but when it comes to the HCC mouse model in Figure 5, the anti-tumor effect was significantly increased between ePAC and CpG-only group. The authors should explain the difference between these two results.

      Thanks very much for the comment. Since PEG10 protein does not have an adjuvant effect, the adjuvant effect of ePAC mainly comes from the modified CpG. Therefore, although ePAC can effectively deliver tumor neoantigens, it does not have a significant advantage over free CpG in activating APCs. However, CpG only possesses the adjuvant effect and does not carry neoantigens. While it can promote the maturation of APCs, it cannot generate neoantigen-specific T cells. Consequently, the antitumor effect of CpG-only is much lower than that of ePAC in Figure 5.

      Reviewer #2 (Public Review):

      Summary:

      The authors provided a novel antigen delivery system that showed remarkable efficacy in transporting antigens to develop cancer therapeutic vaccines.

      Strengths:

      This manuscript was innovative, meaningful, and had a rich amount of data.

      Weaknesses:

      There are still some issues that need to be addressed and clarified.

      Thanks very much to comment our work as “innovative”. We sincerely appreciate the extremely helpful comments from the reviewer to significantly improve the quality of our manuscript, and the listed weaknesses have been all carefully addressed.

      (1) The format of images and data should be unified. Specifically, as follows: a. The presentation of flow cytometry results; b, The color schemes for different groups of column diagrams.

      Thanks very much. Following the reviewer’s comment, we have unified the format of all images and data as suggested.

      (2) The P-value should be provided in Figures, including Figure 1F, 1H, 3C, 3D, and 3E.

      Thanks very much. We have provided the corresponding P-values in Figure 1F, 1H, 3C, 3D, and 3E.

      (3) The quality of Figure 1C was too low to support the conclusion. The author should provide higher-quality images with no obvious background fluorescent signal. Meanwhile, the fluorescent image results of "Egfp+VSVg" group were inconsistent with the flow cytometry data. Additionally, the reviewer recommends that the authors use a confocal microscope to repeat this experiment to obtain a more convincing result.

      Thanks very much for this comment. Following the reviewer’s suggestion, we uniformly adjusted the original images in Figure 1C to reduce background interference and increase its quality. After eliminating background interference, the fluorescence image of the "Egfp+VSVg" group was consistent with the flow cytometry result.

      (4) The survival situation of the mouse should be provided in Figure 5, Figure 6, and Figure 7 to support the superior tumor therapy effect of ePAC.

      Thanks very much for the extremely helpful comment. Following the reviewer’s suggestion, we have added the progression free survival (PFS) of mice in Figure 5 and described this result in the “Results” section of “Antitumor effect of ePAC in subcutaneous HCC model” as follows: Meanwhile, the Kaplan-Meier analysis of tumor progression free survival (PFS) also clearly demonstrated the therapeutic advantages of our ePAC (p=0.0194, Figure 5B). For Figure 6 and Figure 7, to promptly detect the immune changes in the tumor microenvironment after vaccination, we were unable to conduct long-term observations on tumor-bearing mice, and therefore, we did not provide the survival curve. However, we monitored the tumor volume changes in real-time, which also can serve as an important measure for evaluating antitumor efficacy.

      (5) To demonstrate that ePAC could trigger a strong immune response, the positive control group in Figure 4K should be added.

      Thanks very much for this very helpful comment. Following the reviewer’s suggestion, the mouse anti-CD3 antibody was used as the positive control in vitro to activate splenic T cells for ELISPOT assay, and the corresponding results have been added in revised Figure 4K. To address this, we have provided a detailed description in “Figure legends” section of “Figure 4. ePAC delivery and immune activation in vivo” as follows: The mouse anti-CD3 antibody was used to activate splenic T cells in vitro as the positive control for ELISPOT assay.

      (6) In Figure 6G-I and other figures, the author should indicate the time point of detection. Meanwhile, there was no explanation for the different numbers of mice in Figure 6G-I. If the mouse was absent due to death, it may be necessary to advance the detection time to obtain a more convincing result.

      Thanks very much for the comment. The samples for Figure 6 G-I data were collected and analyzed at the day 28 after the start of treatment. Following the reviewer’s suggestion, we have specifically marked the time point of “Sacrifice for sampling” in Figure 6A. And we have provided a detailed description in “Figure legends” section of “Figure 6. Evaluation ePAC antitumor efficacy in orthotopic HCC model by αTIM-3 combination” as follows: The mice were sacrificed and sampled for analysis on the day of 28 after initiating treatment. In addition, in Figure 6G-I we have clearly indicated the sample size for each group. Although three mice in the PBS group died, we still have obtained enough samples for statistical analysis (n>3).

      (7) In Figure 6B, the rainbow color bar with an accurate number of maximum and minimum fluorescence intensity should be provided. In addition, the corresponding fluorescence intensity in Figure 6B should be noted.

      Thanks very much for this very helpful comment. Following the reviewer’s suggestion, we have added the rainbow color bar with an accurate number of maximum and minimum fluorescence intensity, and the statistic results in revised Figure 6B.

      (8) The quality of images in Figure 1D and Figure S1B could not support the author's conclusion; please provide higher-quality images.

      Thanks very much. In Figure 1D and Figure S1B, to ensure the authenticity of the results, we tried our best to improve the quality of the pictures and provided the WB results with the full membrane scan. Although some non-specific bands appeared in the results, the target bands remained prominent. Additionally, we used two tags (HA and eGFP) for verification, which fully guarantees the reliability of our findings.

      (9) In Figure 2F, the bright field in the overlay photo may disturb the observation. Meanwhile, the scale bar should be provided in enlarged images.

      Thanks very much. Following the reviewer’s suggestion, we have deleted the bright field in revised Figure 2F and added the scale bar in the enlarged images.

      Reviewer #3 (Public Review):

      Summary:

      The authors harnessed the potential of mammalian endogenous virus-like proteins to encapsulate virus-like particles (VLPs), enabling the precise delivery of tumor neoantigens. Through meticulous optimization of the VLP component ratios, they achieved remarkable stability and efficiency in delivering these crucial payloads. Moreover, the incorporation of CpG-ODN further heightened the targeted delivery efficiency and immunogenicity of the VLPs, solidifying their role as a potent tumor vaccine. In a diverse array of tumor mouse models, this novel tumor vaccine, termed ePAC, exhibited profound efficacy in activating the murine immune system. This activation manifested through the stimulation of dendritic cells in lymph nodes, the generation of effector memory T cells within the spleen, and the infiltration of neoantigen-specific T cells into tumors, resulting in robust anti-tumor responses.

      Strengths:

      This study delivered tumor neoantigens using VLPs, pioneering a new method for neoantigen delivery. Additionally, the gag protein of VLP is derived from mammalian endogenous virus-like protein, which offers greater safety compared to virus-derived gag proteins, thereby presenting a strong potential for clinical translation. The study also utilized a humanized mouse model to further validate the vaccine's efficacy and safety. Therefore, the anti-tumor vaccine designed in this study possesses both innovation and practicality.

      Thanks very much to comment our work as “novel”, “innovation” and “practicality”. We sincerely appreciate the extremely helpful comments from the reviewer to significantly improve the quality of our manuscript.

      Weaknesses:

      (1) CpG-ODN is an FDA-approved adjuvant with various sequence structures. Why was CpG-ODN 1826 directly chosen in this study instead of other types of CpG-ODN? Additionally, how does DEC-205 recognize CpG-ODN 1826, and can DEC-205 recognize other types of CpG-ODN?

      Thanks very much for the comment. CpG-ODNs are classified into three main types based on their structural composition: A, B, and C. Among them, only the B-class CpG-ODNs 1668, 1826, and 2006 have been directly proven to effectively bind DEC-205 and activate DC cells [1]. Therefore, in this study, B-class CpG-ODN 1826 was chosen as the ligand targeting DEC-205 on the surface of DC cells. DEC-205 primarily binds sequences containing the CpG motif core in a pH-dependent manner, thus theoretically allowing DEC-205 to bind a wide range of CpG-ODNs.

      [1] Lahoud MH et al. DEC-205 is a cell surface receptor for CpG oligonucleotides. PNAS. 2012

      (2) Why was it necessary to treat DCs with virus-like particles three times during the in vitro activation of T cells? Can this in vitro activation method effectively obtain neoantigen-responsive T cells?

      Thanks very much for the comment. DCs need to be pre-stimulated before being used to activate T cells. Although Single DC stimulation can activate T cells, but the activation efficiency is insufficient. Current research suggests that three DC-T interactions can more effectively activate T cells [2]. Therefore, we prepared virus-like particle stimulated DCs for three times to fully activate T cells. Our results in Figures 3I and 7D also demonstrate that three-time stimulations effectively activated antigen-specific T cells, resulting in stronger tumor cell killing effects.

      [2] Ali M et al. Induction of neoantigen-reactive T cells from healthy donors. Nature protocol. 2019.

      (3) In the humanized mouse model, the authors used Hepa1-6 cells to construct the tumor model. To achieve the vaccine's anti-tumor function, these Hepa1-6 cells were additionally engineered to express HLA-A0201. However, in the in vitro experiments, the authors used the HepG2 cell line, which naturally expresses HLA-A0201. Why did the authors not continue to use HepG2 cells to construct the tumor model, instead of Hepa1-6 cells?

      Thanks very much for the comment. HepG2 cells are derived from human liver cancer. When directly implant into immunocompetent mice, they will be cleared by the mouse immune system and will not form tumors. Therefore, we have not continued to use HepG2 cells to construct the tumor model.

      (4) The advantages of low immunogenicity viruses as vaccines compared with conventional adenovirus and lentivirus, etc. should be discussed.

      Thanks very much for the very suggestive comment. In the introduction starting from line 76, we first described the structure and function of lentiviruses and discussed the design and application of virus-like particles (VLPs) based on lentiviruses. To provide a more comprehensive comparison, we included a discussion on VLPs, lentiviruses, and adenoviruses in the discuss section (from line 441 to line 447) as follows: “Furthermore, comparing to the virus-based delivery vectors, the lentiviruses although can stably integrate into the host genome but carry risks of insertional mutagenesis; adenoviruses although have high transduction efficiency but strong immunogenicity, which leads to fast clearance by the immune system of the host and affects the efficiency of the secondary injection. Instead, our VLPs offer low immunogenicity and superior safety, making them more suitable for repeated use and vaccine development.”

      (5) In Figure 6B, the authors should provide statistical results.

      Thanks very much. We have provided the statistical results in revised Figure 6B following the reviewer’s suggestion.

      (6) The entire article demonstrates a clear logical structure and substantial content in its writing. However, there are still some minor errors, such as the misspelling of "Spleenic" in Figure 3B, and the sentence from line 234 should be revised.

      Thanks very much. We have carefully checked and corrected the typos throughout the whole manuscript as much as possible.

      (7) The authors demonstrated the efficiency of CpG-ODN membrane modification by varying the concentration of DBCO, ultimately determining the optimal modification scheme for eVLP as 3.5 nmol of DBCO. However, in Figure 2B, the author did not provide the modification efficiency when the DBCO concentration is lower than 3.5 nmol. These results should be provided.

      Thanks very much for the suggestion. We have repeated the experiment and reduced the concentration of DBCO to 2.1 nmol and 0.7 nmol, respectively. The results showed that in a 200 µl eVLP reaction system, 3.5 nmol DBCO achieved the highest modification efficiency. We have provided a detailed description in “Results” section of “Envelope decoration of neoantigen-loaded eVLP” as follows: Furthermore, by varying the concentration of DBCO-C6-NHS Ester from 0 to 14 nmol, ePAC exhibited different CpG-ODN loading efficiency as evidenced by agarose gel electrophoresis (Figure 2B and Figure S3). And the results showed that in a 200 µl eVLP reaction system, 3.5 nmol DBCO achieved the highest modification efficiency.

      (8) In Figure 3, the authors presented a series of data demonstrating that ePAC can activate mouse DC2.4 cells and BMDCs in vitro. However, in Figure 7, there is no evidence showing whether human DC cells can be activated by ePAC in vitro. This data should be provided.

      Thanks very much for this very helpful suggestion. We used ePAC to activate human DCs and the results indicate that, compared to the blank control group, both eVLP and ePAC increased the co-expression of CD80 and CD86 in DCs, and ePAC was the most efficient. We have provided a detailed description in the “Results” section of “Antitumor effect by HLA-A*0201 restricted vaccine” as follows: After the stimulation, the DCs in ePAC treated group showed the highest level of maturation comparing to the eVLP treated group and control group (Figure S4), by using flow cytometry analysis.”

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Recommendations For The Authors):

      (1) Figure 2B and 2D: unlike what is written in the results part, the results are not consistent, but opposite: LSS has higher activity in 2B, less in 2D. 

      The activities in Figure 2B come from NMR kinetic experiments with pGly, whereas Figure 2D reports on activity towards whole S. aureus cells. The LytM and LSS activities in these two experiments are indeed not directly comparable, but served to highlight the fact that simple pentaglycine is a poor model substrate for M23 enzymes. We carried out a turbidity assay with pristine enzymatic preparation and indeed it is highly consistent both with the kinetic assay using pentaglycine (Fig. 2B) as well as with larger PG fragments (Fig. 2K) indicating that the catalytic domain of LSS is significantly more efficient than LytM in hydrolyzing cells from community acquired methicillin resistant S. aureus strain USA300 as well as synthetic PG fragments.  The corresponding paragraph in Results has now been updated and rephrased.

      (2) Figure 2, panel K missing statistical analysis, which makes it difficult to appreciate if the difference is significant. If it is a one-time experiment or a single value, the value should be presented as a table. The corresponding text in the results part is confusing. The fold change or drop in percentage is unclear in the figure. 

      We have added a table (panel L) to Figure 2, which shows absolute values of LSS and LytM hydrolysis rates. Indeed, most of the values are from single NMR kinetic measurements, however, PG fragment (2) for LSS and PG fragment (3) for LytM were measured as duplicates to verify the reproducibility of the data. This is now mentioned in Figure 3 legend and in the Materials and Methods. Also, the corresponding text in the Results has been updated and rephrased.

      (3) Figure 3H: the cleavage of D-ala-gly is unclear, the cleavage products need to be labeled and quantified. The experiment used purified PG treated with mutanolysin. Presumably, mixed monomers, dimers, trimers, and multimers are used. It would be helpful to show the HPLC profile of the purified muropeptide. It would be informative to analyze which fractions generate D-ala-gly. In addition, the intact murein sacculus should be included. 

      For the sake of clarity, we have moved the 13C-HMBC spectra presented in Figure 3H to Fig. S7 in the Supplementary Material. The full carbonyl carbon region of the reference (prior to addition of enzyme) 13C-HMBC spectrum together with larger expansions of spectra acquired from enzyme-treated muropeptides are now shown. Furthermore, graphical presentations of identified PG fragments due to LSS/LytM activity are included. No HPLC analysis of the muropeptides was performed at this stage. Being insoluble, the intact murein sacculus is not amenable to liquid-state NMR studies, but we envisage studies of this remarkably complex structure also with solid-state NMR.

      Reviewer #2 (Recommendations For The Authors): 

      Overall, the experiments address the question asked by the authors and no additional experiments are required to strengthen the conclusions drawn. 

      Abstract: 

      The abstract is not well written and more specific (and accurate) information should be provided by the authors. 

      We are grateful for the constructive and helpful comments to improve our manuscript. The abstract has now been modified by taking into account the Reviewer’s suggestions.

      Introduction 

      The intro is relatively long and wordy. It could most certainly be shortened and written in a more simple way to make it more impactful.

      The introduction has now been modified by taking into account the Reviewer’s suggestions.

      (2) One of the peptide stems in Figure 1 is missing a pentaglycine side chain; I would recommend increasing the font size; the peptide stem looks like it is attached to the carbon in position 2, it may be a good idea to move it to the left? 

      We thank the Reviewer for this comment. Figure 1 has been improved, the frameshift has been fixed and the non-cross-linked pGly bridge has been included to the lysine side-chain in tetraStem.

      Results 

      Figure 2 is a bit overwhelming and its description is sketchy. Fig 2B shows a much higher activity of LSS on pGly as compared to LytM whilst 2K shows a very similar rate. 

      We have rearranged Figures 1 and 2 by moving the original panel J in Figure 2 (structures of PG fragments) to Figure 1 panel C. The bar graph in Figure 2J now shows absolute rates of substrate hydrolysis for 2 mM LSS and LytM. These indicate that LSS is much more efficient against PG fragments in vitro in comparison to LytM. Rates normalized with respect to pGly are shown in Figure 2K. Also, a table showing absolute rates of hydrolysis for 2 mM LSS and 50 mM LytM has been included in Figure 2, panel L. In this Table, the values for PG fragments 2 and 3 were determined by two independent measurements to test and accredit the reproducibility of the method. This is also now elaborated further in the Materials and Methods.

      Figure 3 is impressive and very informative but again hard to follow. 

      - Panels 3A and 3B are nicely conceived but the resolution is rather poor and it is difficult to know exactly where the arrows point. 

      We very much value suggestions given by the Reviewer to improve readability of our manuscript. In the case of Figure 3, we have now greatly enhanced the resolution and readability of the figure by horizontal scaling of panels A and B.

      Figure 4 shows a comparative analysis of catalytic rate using various substrates, the authors may want to present graphs with the same y-axis to get the most out of the comparison between substrates. 

      The scaling of the y-axis is the same for all the substrates now. In addition, we have reorganized the panels in the figure to enhance readability.

      Figure 5: - The same remark as above, please cite all panels in alphabetical order. 

      Citing to Figure 5 has now been revised.

      Material and methods: 

      - How were the peptide concentrations determined? It may be useful to indicate if specific conditions were required to solubilize some peptides, pGly is particularly insoluble in aqueous solutions. 

      - Page 19, replace cpm by rpm; biological or technical replicates?

      These have now been added and edited accordingly.

    1. Author response:

      The following is the authors’ response to the current reviews.

      The concerns raised during the review have been incorporated into the discussion of the results, and the need for further research is acknowledged in the paper. This is not possible in the present study, as the clinical project has been completed and further patients cannot be enrolled without starting a new project. We are confident that the results are scientifically valid and that the methodology was scientifically sound and up to date. They were obtained on a dataset that was obviously large enough to allow 20% of it to be set aside and a machine-learned classifier to be trained on the remaining 80%, which then assigned samples to neuropathy with an accuracy better than guessing.

      Furthermore, our results are at least tentatively replicated in a completely independent data set from another patient cohort. The strengths and limitations of the study design, in particular the latter, are discussed in the necessary depth. In summary, the machine-learned results provided major hits on one side and probably unimportant lipids on the other side of the variable importance scale. Both could be verified in vitro. We are therefore confident that we have contributed to the advancement of knowledge about cancer therapy-associated neuropathy and look forward to further developments in this area.


      The following is the authors’ response to the original reviews.

      Weaknesses Reviewer 1: 

      There are a number of weaknesses in the study. The small sample size is a significant limitation of the study. Out of 31 patients, only 17 patients were reported to develop neuropathy, with significant neuropathy (grade 2/3) in only 5 patients. The authors acknowledge this limitation in the results and discussion sections of the manuscript, but it limits the interpretation of the results. Also acknowledged is the limited method used to assess neuropathy. 

      We agree with the reviewer that the cohort size and assessment of neuropathy are limitations of our study as we already described in the corresponding section of the manuscript. However, occurrence and grade of the neuropathy are in line with results reported from previous studies. From these studies, the expected occurrence of neuropathy with our therapeutic regimen is around 50-70% (54.9% in our cohort), and most patients (80-90%) are expected to experience Grade 1 neuropathy after 12 weeks (13). In these studies, neuropathy is assessed by using questionnaires or by grading via NCTCTCAE as in our study. In summary, assessment and occurrence of neuropathy of our reported cohort are in line with previous reports.

      Potentially due to this small number of patients with neuropathy, the machine learning algorithms could not distinguish between samples with and without neuropathy. Only selected univariate analyses identified differences in lipid profiles potentially related to neuropathy.  

      The data analysis consistently followed a "mixture of experts" approach, as this seems to be the most successful way to deal with omics data. We have elaborated on this in the Methods section, including several supporting references. Regarding the quoted sentence from the results section, after rereading it, we realized that it was somewhat awkwardly worded. What we mean is now better worded in the results section, namely “Although the three algorithms detected neuropathy in new cases, unseen during training, at balanced accuracy of up to 0.75, while only the guess level of 0.5 was achieved when using permuted data for training, the 95% CI of the performance measures was not separated from guess level”. Therefore, multivariate feature selection was not considered a valid approach, since it requires that the algorithms from which the feature importance is read can successfully perform their task of class assignment (4). Therefore, univariate methods (Cohen's d, FPR, FWE) were preferred, as well as a direct hypothesis transfer of the top hits from the abovementioned day1/2 assessments to neuropathy. Classical statistics consisting of direct group comparisons using Kruskal-Wallis tests (5) were performed.” 

      It was our approach to investigate the data set in an unbiased manner by different machine learning algorithms and select those lipids that the majority of the algorithms considered important for distinguishing the patient groups (majority voting). This way, the inconsistencies and limitations of a single evaluation method, such as regression analysis, that occur in some datasets, can be mitigated. 

      Three sphingolipid mediators including SA1P differed between patients with and without neuropathy at the end of treatment. These sphingolipids were elevated at the end of treatment in the cohort with neuropathy, relative to those without neuropathy. However, across all samples from pre to post-paclitaxel treatment, there was a significant reduction in SA1P levels. It is unclear from the data presented what the underlying mechanism for this result would be. 

      We agree with the reviewer that our study does not identify the mechanism by which paclitaxel treatment alters sphingolipid concentrations in the plasma of patients. It has been reported before that paclitaxel may increase expression and activity of serine palmitoyltransferase (SPT) which is the crucial enzyme and rate-limiting step in the denovo synthesis of sphingolipids. This may be associated with a shift towards increased synthesis of 1-deoxysphingolipids and a decrease of “classical” sphingolipids (6) and may explain the general reduction of SA1P and other sphingolipid levels after paclitaxel treatment in our study. 

      It is also conceivable that paclitaxel reduces the release of sphingolipids into the plasma. Paclitaxel is a microtubule stabilizing agent (7) that may interfere with intracellular transport processes and release of paracrine mediators. 

      The mechanistic details of paclitaxel involvement in sphingolipid metabolism or transport are highly interesting but identifying them is beyond the scope of our manuscript.

      If elevated SA1P is associated with neuropathy development, it would be expected to increase in those who develop neuropathy from pre to post-treatment time points. 

      There is a general trend of reduced plasma SA1P concentrations following paclitaxel treatment. Nevertheless, patients experiencing neuropathy exhibit significantly elevated SA1P levels post-treatment. 

      It has been shown before that paclitaxel-induced neuropathic pain requires activation of the S1P1 receptor in a preclinical study (8). Moreover, a meta-analysis of genome-wide association studies (GWAS) from two clinical cohorts identified multiple regulatory elements and increased activity of S1PR1 associated with paclitaxel-induced neuropathy (9). These data imply that enhanced S1P receptor activity and signaling are key drivers of paclitaxel-induced neuropathy. It seems that both, increased levels of the sphingolipid ligands in combination with enhanced expression and activity of S1P receptors can potentiate paclitaxel-induced neuropathy in patients. This explains why also decreased SA1P concentrations after paclitaxel treatment can still enhance neuropathy via the S1PRTRPV1 axis in sensory neurons.

      We added this paragraph to the discussions section of our manuscript.

      Primary sensory neuron cultures were used to examine the effects of SA1P application.

      SA1P application produced calcium transients in a small proportion of sensory neurons. It is not clear how this experimental model assists in validating the role of SA1P in neuropathy development as there is no assessment of sensory neuron damage or other hallmarks of peripheral neuropathy. These results demonstrate that some sensory neurons respond to SA1P and that this activity is linked to TRPV1 receptors. However, further studies will be required to determine if this is mechanistically related to neuropathy.

      As we detected elevated levels of SA1P in the plasma of PIPN patients, we can assume higher concentrations in the vicinity of sensory neurons. These neurons are the main drivers for neuropathy and neuropathic pain and are strongly affected by paclitaxel in their activity (10-15). Also, TRPV1 shows altered activity patterns in response to paclitaxel treatment (16). Because of its relevance for nociception and pathological pain, TRPV1 activity is a suitable and representative readout for pathological pain states in peripheral sensory neurons (17, 18), which is why we investigated them.

      We would like to point out the potency of SA1P to increase capsaicin-induced calciumtransients in sensory neurons at submicromolar concentrations. 

      We also agree with the reviewer that further studies need to investigate the underlying mechanisms in more detail. We added this sentence to the final paragraph in the discussion section of our manuscript.

      Weaknesses Reviewer 2: 

      The article is poorly written, hindering a clear understanding of core results. While the study's goals are apparent, the interpretation of sphingolipids, particularly SA1P, as key mediators of paclitaxel-induced neuropathy lacks robust evidence. 

      We agree that the relevance of SA1P as key mediator of paclitaxel-induced neuropathy might be overstated and changed the wording throughout the manuscript accordingly. However, we would like to point out the potency of this lipid to increase capsaicin-induced calcium-transients in sensory neurons at submicromolar concentrations. 

      Also, the lipid signature in the plasma of PIPN patients shows a unique pattern and sphingolipids are the group that showed the strongest alterations when comparing the patient groups. We also measured eicosanoids, such as prostaglandins, linoleic acid metabolites, endocannabinoids and other lipid groups that have previously been associated with influences on pain perception or nociceptor sensitization. However, none of these lipids showed significant differences in their concentrations in patient plasma. This is why we consider sphingolipids as contributors to or markers of paclitaxel-induced neuropathy in patients.

      We also revised the entire article to improve its clarity.

      The introduction fails to establish the significance of general neuropathy or peripheral neuropathy in anticancer drug-treated patients, and crucial details, such as the percentage of patients developing general neuropathy or peripheral neuropathy, are omitted. This omission is particularly relevant given that only around 50% of patients developed neuropathy in this study, primarily of mild Grade 1 severity with negligible symptoms, contradicting the study's assertion of CIPN as a significant side effect. 

      As we already described in the introduction, CIPN is a serious dose- and therapy-limiting side effect, which affects up to 80% of treated patients. This depends on dose and combination of chemotherapeutic agents. For paclitaxel, therapeutic doses range from 80 – 225 mg/m². As CIPN symptoms are dose-dependent, the number of PIPN patients that receive a high paclitaxel dose is higher than the number of PIPN patient receiving a low dose.

      In our study, we mainly used a low dose paclitaxel, because this therapeutic regimen is the most widely used paclitaxel monotherapy. From previous studies, the expected occurrence of neuropathy with this therapeutic regimen is around 50-70%, and most patients (8090%) are expected to experience Grade 1 neuropathy after 12 weeks (1-3).

      Our results are within the range reported by these studies (54.9% patients with neuropathy). Also, as we highlight in Table S1, the neuropathy symptoms persist in most cases for several years after chemotherapy, affecting quality of life of these patients which makes it far from being a negligible symptom.

      We added some more information concerning PIPN in the introduction section in which we emphasize the clinical problem.

      The lack of clarity in distinguishing results obtained by lipidomics using machine learning methods and conventional methods adds to the confusion. The poorly written results section fails to specify SA1P's downregulation or upregulation, and the process of narrowing down to sphingolipids and SA1P is inadequately explained. 

      We have tried to keep the machine learning part in the main manuscript short and moved major parts of it to a supplement. However, as this has been claimed to have led to a lack of clarity, we have expanded the description of the data analysis and added extensive explanations and supporting references for the mixed expert approach that was used throughout the analysis. We hope this is now clear.

      Integrating a significant portion of the discussion section into the results section could enhance clarity. An explanation of the utility of machine learning in classifying patient groups over conventional methods and the citation of original research articles, rather than relying on review articles, may also add clarity to the usefulness of the study. 

      As suggested by the reviewer, we moved the relevant parts from the discussion to the results section in the revised version of our manuscript.

      Reviewer #1 (Recommendations For The Authors): 

      Figure 2 should be better explained or removed. In its current form, it does not add to the interpretation of the manuscript.  

      As mentioned above, we have expanded the description of the ESOM/U-matrix method in the Methods section and rewritten the figure legend. In addition, we have annotated the U-matrix in the figure. The method has been reported extensively in the computer science and biomedical literature, and a more detailed description in the referenced papers would go beyond the current focus on lipidomics. However, we believe that this discussion is sufficiently detailed for the readers of this report: "… a second unsupervised approach was used to verify the agreement between the lipidomics data structure and the prior classification, implemented as self-organizing maps (SOM) of artificial neurons (19). In the special form of an “emergent” SOM (ESOM (20)), the present map consisted of 4,000 neurons arranged on a two-dimensional toroidal grid with 50 rows and 80 columns (21, 22). ESOM was used because it has been repeatedly shown to correctly detect subgroup structures in biomedical data sets comparable to the present one (20, 22, 23). The core principle of SOM learning is to adjust the weights of neurons based on their proximity to input data points. In this process, the best matching unit (BMU) is identified as the neuron closest to a given data point. The adaptation of the weights is determined by a learning rate (η) and a neighborhood function (h), both of which gradually decrease during the learning process. Finally, the groups are projected onto separate regions of the map. On top of the trained ESOM, the distance structure in the high-dimensional feature space was visualized in the form of a so-called U-matrix (24) which is the canonical tool for displaying the distance structures of input data on ESOM (21). 

      The visual presentation facilitates data group separation by displaying the distances between BMUs in high-dimensional space in a color-coding that uses a geographical map analogy, where large "heights" represent large distances in feature space, while low "valleys" represent data subsets that are similar. "Mountain ranges" with "snow-covered" heights visually separate the clusters in the data. Further details about ESOM can be found in (24)."

      The second patient cohort is only included in the discussion - with cohort details in the supplementary material and figures included in the main text. Perhaps these data should be removed entirely. The findings are described as trends and not statistically significant and multiple issues with this second cohort are mentioned in the discussion. 

      We agree with the reviewer that including the second patient cohort in the discussion is inadequate. Of course, there are differences between the patient cohorts that do not allow direct comparison and that are highlighted in the section on limitations of the study. However, we still think it is interesting and relevant to show these data, because we used our algorithms trained on the first patient cohort to analyze the second cohort. And these data support the main results. 

      We therefore moved the entire paragraph to the results section of to improve coherence of our manuscript. The passage was introduced with the subheading:  “Support of the main results in an independent second patient cohort”.

      The title does not reflect the content of the paper and should be changed to better reflect the content and its significance. 

      We change the title to “Machine learning and biological validation identify sphingolipids as potential mediators of paclitaxel-induced neuropathy in cancer patients” to avoid overstating the results as suggested by the Reviewer.

      Further, the discussion should be modified to avoid overstating the results. 

      As the reviewer suggests, we changed the wording to avoid overstating the results. 

      Reviewer #2 (Recommendations For The Authors): 

      Please address the absence of clear neuropathy in the majority of patients after treatment with paclitaxel in your discussion. 

      As stated above, occurrence and grade of the neuropathy are in line with the results from previous studies. From these studies, the expected occurrence of neuropathy with our therapeutic regimen is around 50-70%, (the variability is due to differences in the assessment methods) and most patients (80-90%) are expected to experience Grade 1 neuropathy after 12 weeks (1-3). 

      We added this information in the discussion section of the revised manuscript.

      Line 65: Kindly replace review articles with original research articles for proper citation. 

      We replaced the review articles with original publications, focusing on clinical observations. We added the following publications: Jensen et al., Front Neurosci 2020; Chen et al., Neurobiol Aging 2018; Igarashi et al., J Alzheimers Dis. 2011; Kim et al., Oncotarget 2017 as references 17-20 in the revised version of our manuscript.

      Line 260: The mention of SA1P is introduced here without prior reference (do not use words like "again", or "see above", if it is not previously mentioned). Adjust the text for coherence.

      We agree with the reviewer that the introduction of SA1P in this passage in incoherent. We replaced the sentence in line 260 with: 

      The small set of lipid mediators emerging from all three methods as informative for neuropathy included the sphingolipid sphinganine-1-phosphate (SA1P), also known as dihydrosphingosine-1-phosphate (DH-S1P)…”

      Lines 301-315: Consider relocating several lines from this section to the results section for improved clarity. 

      We moved the lines 309-312 explaining the algorithm selection and their validation success in the corresponding results section (Lipid mediators informative for assigning postpaclitaxel therapy samples to neuropathy).

      Lines 382-396: Move this content to the results section to enhance the organization and coherence of the manuscript. 

      We moved the entire paragraph to the results section of our manuscript to improve coherence. The passage was introduced with the subheading:  “Support of the main results in an independent second patient cohort”.

      References

      (1) Barginear M, Dueck AC, Allred JB, Bunnell C, Cohen HJ, Freedman RA, et al. Age and the Risk of Paclitaxel-Induced Neuropathy in Women with Early-Stage Breast Cancer (Alliance A151411): Results from 1,881 Patients from Cancer and Leukemia Group B (CALGB) 40101. Oncologist. 2019;24(5):617-23.

      (2) Mauri D, Kamposioras K, Tsali L, Bristianou M, Valachis A, Karathanasi I, et al. Overall survival benefit for weekly vs. three-weekly taxanes regimens in advanced breast cancer: A metaanalysis. Cancer Treat Rev. 2010;36(1):69-74.

      (3) Budd GT, Barlow WE, Moore HC, Hobday TJ, Stewart JA, Isaacs C, et al. SWOG S0221: a phase III trial comparing chemotherapy schedules in high-risk early-stage breast cancer. J Clin Oncol. 2015;33(1):58-64.

      (4) Lötsch J, and Ultsch A. Pitfalls of Using Multinomial Regression Analysis to Identify ClassStructure-Relevant Variables in Biomedical Data Sets: Why a Mixture of Experts (MOE) Approach Is Better. BioMedInformatics. 2023;3(4):869-84.

      (5) Kruskal WH, and Wallis WA. Use of Ranks in One-Criterion Variance Analysis. J Am Stat Assoc. 1952;47(260):583-621.

      (6) Kramer R, Bielawski J, Kistner-Griffin E, Othman A, Alecu I, Ernst D, et al. Neurotoxic 1deoxysphingolipids and paclitaxel-induced peripheral neuropathy. FASEB J. 2015;29(11):4461-72.

      (7) Field JJ, Diaz JF, and Miller JH. The binding sites of microtubule-stabilizing agents. Chem Biol. 2013;20(3):301-15.

      (8) Janes K, Little JW, Li C, Bryant L, Chen C, Chen Z, et al. The development and maintenance of paclitaxel-induced neuropathic pain require activation of the sphingosine 1-phosphate receptor subtype 1. J Biol Chem. 2014;289(30):21082-97.

      (9) Chua KC, Xiong C, Ho C, Mushiroda T, Jiang C, Mulkey F, et al. Genomewide Meta-Analysis Validates a Role for S1PR1 in Microtubule Targeting Agent-Induced Sensory Peripheral Neuropathy. Clin Pharmacol Ther. 2020;108(3):625-34.

      (10) Kawakami K, Chiba T, Katagiri N, Saduka M, Abe K, Utsunomiya I, et al. Paclitaxel increases high voltage-dependent calcium channel current in dorsal root ganglion neurons of the rat. J Pharmacol Sci. 2012;120(3):187-95.

      (11) Pittman SK, Gracias NG, Vasko MR, and Fehrenbacher JC. Paclitaxel alters the evoked release of calcitonin gene-related peptide from rat sensory neurons in culture. Exp Neurol. 2013.

      (12) Luo H, Liu HZ, Zhang WW, Matsuda M, Lv N, Chen G, et al. Interleukin-17 Regulates NeuronGlial Communications, Synaptic Transmission, and Neuropathic Pain after Chemotherapy.

      Cell reports. 2019;29(8):2384-97 e5.

      (13) Pease-Raissi SE, Pazyra-Murphy MF, Li Y, Wachter F, Fukuda Y, Fenstermacher SJ, et al. Paclitaxel Reduces Axonal Bclw to Initiate IP3R1-Dependent Axon Degeneration. Neuron. 2017;96(2):373-86 e6.

      (14) Duggett NA, Griffiths LA, and Flatters SJL. Paclitaxel-induced painful neuropathy is associated with changes in mitochondrial bioenergetics, glycolysis, and an energy deficit in dorsal root ganglia neurons. Pain. 2017.

      (15) Li Y, Adamek P, Zhang H, Tatsui CE, Rhines LD, Mrozkova P, et al. The Cancer Chemotherapeutic Paclitaxel Increases Human and Rodent Sensory Neuron Responses to TRPV1 by Activation of TLR4. J Neurosci. 2015;35(39):13487-500.

      (16) Hara T, Chiba T, Abe K, Makabe A, Ikeno S, Kawakami K, et al. Effect of paclitaxel on transient receptor potential vanilloid 1 in rat dorsal root ganglion. Pain. 2013;154(6):882-9.

      (17) Jardin I, Lopez JJ, Diez R, Sanchez-Collado J, Cantonero C, Albarran L, et al. TRPs in Pain Sensation. Front Physiol. 2017;8:392.

      (18) Julius D. TRP Channels and Pain. Annual review of cell and developmental biology.

      2013;29:355-84.

      (19) Kohonen T. Self-Organized Formation of Topologically Correct Feature Maps. Biol Cybern. 1982;43(1):59-69.

      (20) Lötsch J, Lerch F, Djaldetti R, Tegder I, and Ultsch A. Identification of disease-distinct complex biomarker patterns by means of unsupervised machine-learning using an interactive R toolbox (Umatrix). Big Data Analytics. 2018;3(1):5.

      (21) Ultsch A. 2003.

      (22) Lotsch J, Geisslinger G, Heinemann S, Lerch F, Oertel BG, and Ultsch A. Quantitative sensory testing response patterns to capsaicin- and ultraviolet-B-induced local skin hypersensitization in healthy subjects: a machine-learned analysis. Pain. 2018;159(1):11-24.

      (23) Lötsch J, Thrun M, Lerch F, Brunkhorst R, Schiffmann S, Thomas D, et al. Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects. Int J Mol Sci. 2017;18(6).

      (24) Lötsch J, and Ultsch A. Cham: Springer International Publishing; 2014:249-57.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      eLife assessment

      Shore et al. report important effects of a heterozygous mutation in the KCNT1 potassium channel on ion currents and firing behavior of excitatory and inhibitory neurons in the cortex of KCNT1-Y777H mice. The authors provide solid evidence of physiological differences between this heterozygous mutation and their previous work with homozygotes. The reviewers appreciated the inclusion of recordings in ex vivo slices and dissociated cortical neurons, as well as the additional evidence showing an increase in persistent sodium currents (INaP) in parvalbumin-positive interneurons in heterozygotes. However, they were unclear regarding the likelihood of the increased sodium influx through INaP channels increasing sodium-activated potassium currents in these neurons.

      Regarding the last sentence of the eLife assessment, we’ve added a new paragraph to the Discussion section of the paper to address this concern. Please see the response to comment 1B of Reviewer #1 below for more details. We feel that the question of whether an increase in INaP would further increase KCNT1 activity is a valid discussion point but not a limitation of the importance or rigor of the work itself.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This manuscript reports the effects of a heterozygous mutation in the KCNT1 potassium channels on the properties of ion currents and firing behavior of excitatory and inhibitory neurons in the cortex of mice expressing KCNT1-Y777H. In humans, this mutation as well as multiple other heterozygotic mutations produce very severe early-onset seizures and produce a major disruption of all intellectual function. In contrast, in mice, this heterozygous mutation appears to have no behavioral phenotype or any increased propensity to seizures. A relevant phenotype is, however, evident in mice with the homozygous mutation, and the authors have previously published the results of similar experiments with the homozygotes. As perhaps expected, the neuronal effects of the heterozygous mutation presented in this manuscript are generally similar but markedly smaller than the previously published findings on homozygotes. There are, however, some interesting differences, particularly on PV+ interneurons, which appear to be more excitable than wild type in the heterozygotes but more excitable in the heterozygotes. This raises the interesting question, which has been explicitly discussed by the authors in the revised manuscript, as to whether the reported changes represent homeostatic events that suppress the seizure phenotype in the mouse heterozygotes or simply changes in excitability that do not reach the threshold for behavioral outcomes.

      Strengths and Weaknesses:

      (1) The authors find that the heterozygous mutation in PV+ interneurons increases their excitability, a result that is opposite from their previous observation in neurons with the corresponding homozygous mutation. They propose that this results from the selective upregulation of a persistent sodium current INaP in the PV+ interneurons. These observations are very interesting ones, and they raised some issues in the original submission:

      A) The protocol for measuring the INaP current could potentially lead to results that could be (mis)interpreted in different ways in different cells. First, neither K currents nor Ca currents are blocked in these experiments. Instead, TTX is applied to the cells relatively rapidly (within 1 second) and the ramp protocol is applied immediately thereafter. It is stated that, at this time, Na currents and INaP are fully blocked but that any effects on Na-activated K currents are minimal. In theory this would allow the pre- to post- difference current to represent a relatively uncontaminated INaP. This would, however, only work if activation of KNa currents following Na entry is very slow, taking many seconds. A good deal of literature has suggested that the kinetics of activation of KNa currents by Na influx vary substantially between cell types, such that single action potentials and single excitatory synaptic events rapidly evoke KNa currents in some cell types. This is, of course, much faster than the time of TTX application. Most importantly, the kinetics of KNa activation may be different in different neuronal types, which would lead to errors that could produce different estimates of INaP in PV+ interneurons vs other cell types.

      In their revised manuscript, the authors have provided good data demonstrating that, at least for the PV and SST neurons, loss of KNa currents after TTX application is slow relative to the time course of loss of INaP, justifying the use of this protocol for these neuronal types.

      B) As the authors recognize, INaP current provides a major source of cytoplasmic sodium ions for the activation. An expected outcome of increased INaP is, therefore, further activation of KNa currents, rather than a compensatory increase in an inward current that counteracts the increase in KNa currents, as is suggested in the discussion.

      The authors comment in the rebuttal that, despite the fact that sodium entry through INaP is known to activate KNa channels, an increase in INaP does not necessarily imply increased KNa current. This issue should be addressed directly somewhere in the text, perhaps most appropriately in the discussion.

      We’ve added the following new paragraph to the Discussion section of the manuscript to address this concern:

      “As the persistent sodium current has been shown to act as a source of cytoplasmic sodium ions for KCNT1 channel activation in some neuron types (Hage & Salkoff, 2012), one might expect that the compensatory increase in INaP in YH-HET PV neurons would further increase, rather than counteract, KNa currents. Unfortunately, there is insufficient information on the relative locations of the INaP and KCNT1 channels, as well as the kinetics of sodium transfer to KCNT1 channels, among cortical neuron subtypes, and even less is known in the context of KCNT1 GOF neurons; thus, it is difficult to predict how alterations in one of these currents may affect the other. One plausible reason that increased INaP would not alter KNa currents in YH-HET PV neurons is that the particular sodium channels that are responsible for the increased INaP are not located within close proximity to the KCNT1 channels. Moreover, homeostatic mechanisms that modify the length and/or location of the sodium channel-enriched axon initial segment (AIS) in neurons in response to altered excitability are well described (Grubb & Burrone, 2010; Kuba et al., 2010); thus, it is possible that in YH-HET PV neurons, the length or location of the AIS is altered, leading to uncoupling of the sodium channels that are responsible for the increased INaP to the KCNT1 channels. Future studies will aim to further investigate potential mechanisms of neuron-type-specific alterations in NaP and KNa currents downstream of KCNT1 GOF.”  

      C) The numerical simulations, in general, provide a very useful way to evaluate the significance of experimental findings. Nevertheless, while the in-silico modeling suggests that increases in INaP can increase firing rate in models of PV+ neurons, there is as yet insufficient information on the relative locations of the INaP channels and the kinetics of sodium transfer to KNa channels to evaluate the validity of this specific model.

      The authors have now put in all of the appropriate caveats on this very nicely in the revised manuscript.

      (2) The effects of the KCNT1 channel blocker VU170 on potassium currents are somewhat larger and different from those of TTX, suggesting that additional sources of sodium may contribute to activating KCNT1, as suggested by the authors. Because VU170 is, however, a novel pharmacological agent, it may be appropriate to make more careful statements on this. While the original published description of this compound reported no effect on a variety of other channels, there are many that were not tested, including Na and cation channels that are known to activate KCNT1, raising the possibility of off-target effects.

      In the revised version, the authors have added more to the manuscript on this issue and have added a very clear discussion of this to the text (in the discussion section).

      This is a very clear and thorough piece of work, and the authors are to be congratulated on this. My one remaining suggestion would be to make an explicit statement about whether increased sodium influx through INaP channels, which is thought to activate KNa channels, would be likely to increase KNa current in these neurons (see comment 1B).

      Please see response to comment 1B.

      Reviewer #2 (Public Review):

      Summary:

      In this manuscript, Shore et al. investigate the consequent changes in excitability and synaptic efficacy of diverse neuronal populations in an animal model of juvenile epilepsy. Using electrophysiological patch-clamp recordings from dissociated neuronal cultures, the authors find diverging changes in two major populations of inhibitory cell types, namely somatostatin (SST)- and parvalbumin (PV)-positive interneurons, in mice expressing a variant of the KCNT1 potassium channel. They further suggest that the differential effects are due to a compensatory increase in the persistent sodium current in PV interneurons in pharmacological and in silico experiments. It remains unclear why this current is selectively enhanced in PV-interneurons.

      Strengths:

      (1) Heterozygous KCNT1 gain of function variant was used which more accurately models the human disorder.

      (2) The manuscript is clearly written, and the flow is easy to follow. The authors explicitly state the similarities and differences between the current findings and the previously published results in the homozygous KCNT1 gain of function variant.

      (3) This study uses a variety of approaches including patch clamp recording, in silico modeling and pharmacology that together make the claims stronger.

      (4) Pharmacological experiments are fraught with off-target effects and thus it bolsters the authors' claims when multiple channel blockers (TTX and VU170) are used to reconstruct the sodium-activated potassium current.

      Weaknesses:

      (1) This study mostly relies on recordings in dissociated cortical neurons. Although specific WT interneurons showed intrinsic membrane properties like those reported for acute brain slices, it is unclear whether the same will be true for those cells expressing KCNT1 variants, especially when the excitability changes are thought to arise from homeostatic compensatory mechanisms. The authors do confirm that mutant SST-interneurons are hypoexcitable using an ex vivo slice preparation which is consistent with work for other KCTN1 gain of function variants (e.g. Gertler et al., 2022). However, the key missing evidence is the excitability state of mutant PV-interneurons, given the discrepant result of reduced excitability of PV cells reported by Gertler et al in acute hippocampal slices.

      Reviewer #3 (Public Review):

      Summary:

      The present manuscript by Shore et al. entitled Reduced GABAergic Neuron Excitability, Altered Synaptic Connectivity, and Seizures in a KCNT1 Gain-of-Function Mouse Model of Childhood Epilepsy" describes in vitro and in silico results obtained in cortical neurons from mice carrying the KCNT1-Y777H gain-of-function (GOF) variant in the KCNT1 gene encoding for a subunit of the Na+-activated K+ (KNa) channel. This variant corresponds to the human Y796H variant found in a family with Autosomal Dominant Nocturnal Frontal lobe epilepsy. The occurrence of GOF variants in potassium channel encoding genes is well known, and among potential pathophysiological mechanisms, impaired inhibition has been documented as responsible for KCNT1-related DEEs. Therefore, building on a previous study by the same group performed in homozygous KI animals, and considering that the largest majority of pathogenic KCNT1 variants in humans occur in heterozygosis, the Authors have investigated the effects of heterozygous Kcnt1-Y777H expression on KNa currents and neuronal physiology among cortical glutamatergic and the 3 main classes of GABAergic neurons, namely those expressing vasoactive intestinal polypeptide (VIP), somatostatin (SST), and parvalbumin (PV), crossing KCNT1-Y777H mice with PV-, SST- and PV-cre mouse lines, and recording from GABAergic neurons identified by their expression of mCherry (but negative for GFP used to mark excitatory neurons).

      The results obtained revealed heterogeneous effects of the variant on KNa and action potential firing rates in distinct neuronal subpopulations, ranging from no change (glutamatergic and VIP GABAergic) to decreased excitability (SST GABAergic) to increased excitability (PV GABAergic). In particular, modelling and in vitro data revealed that an increase in persistent Na current occurring in PV neurons was sufficient to overcome the effects of KCNT1 GOF and cause an overall increase in AP generation.

      Strengths:

      The paper is very well written, the results clearly presented and interpreted, and the discussion focuses on the most relevant points.

      The recordings performed in distinct neuronal subpopulations (both in primary neuronal cultures and, for some subpopulations, in cortical slices, are a clear strength of the paper. The finding that the same variant can cause opposite effects and trigger specific homeostatic mechanisms in distinct neuronal populations is very relevant for the field, as it narrows the existing gap between experimental models and clinical evidence.

      Weaknesses:

      My main concern regarding the epileptic phenotype of the heterozygous mice investigated has been clarified in the revision, where the infrequent occurrence of seizures is more clearly stated. Also, a more detailed statistical analysis of the modeled neurons has been added in the revision.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      This is a very clear and thorough piece of work, and the authors are to be congratulated on this. My one remaining suggestion would be to make an explicit statement about whether increased sodium influx through INaP channels, which is thought to activate KNa channels, would be likely to increase KNa current in these neurons (see comment 1B).

      Please see response to comment 1B.

      Reviewer #2 (Recommendations For The Authors):

      This revised manuscript is significantly improved and addresses most of my concerns. However, I would still recommend including the ex vivo slice recordings in mutant PV-interneurons as the authors proposed in their rebuttal. The I-V recordings using sequential TTX and VU170 blockade in WT SST and PV-interneurons that are provided in the rebuttal are interesting and may point to a preferential expression of persistent sodium currents in PV-interneurons normally. It would be helpful to readers as a supplemental figure.

      As proposed in the rebuttal, we are currently recording PV neurons using ex vivo slice preparations from WT and Kcnt1-YH Het mice. We look forward to including those data in a future manuscript.

      We agree with the reviewer that the differences in INaP between WT PV and SST neurons are notable. The data provided in the rebuttal were only from 5 neurons/group, and they were meant to illustrate a side-by-side comparison of TTX and VU170 subtraction methods to assess KNa currents. However, in Figure 7 of the manuscript, we performed more robust measurements of INaP and observed differences in the current between WT PV and SST neurons. Thus, we’ve added the following sentence to the Results section:

      “Interestingly, the mean peak amplitude of INaP in WT PV neurons was 70% larger than that in WT SST neurons (-1.42 ± 0.16 vs. -0.85 ± 0.07 pA/pF; Fig. 7B and 7D), suggesting there may be differences in sodium channel expression, localization, or regulation inherent to each neuron type that confer their differential response to KCNT1 GOF.”

      References

      Grubb, M. S., & Burrone, J. (2010). Activity-dependent relocation of the axon initial segment fine-tunes neuronal excitability. Nature, 465(7301), 1070-1074. https://doi.org/10.1038/nature09160

      Hage, T. A., & Salkoff, L. (2012). Sodium-activated potassium channels are functionally coupled to persistent sodium currents. J Neurosci, 32(8), 2714-2721. https://doi.org/10.1523/JNEUROSCI.5088-11.2012

      Kuba, H., Oichi, Y., & Ohmori, H. (2010). Presynaptic activity regulates Na(+) channel distribution at the axon initial segment. Nature, 465(7301), 1075-1078. https://doi.org/10.1038/nature09087

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This interesting study explores the mechanism behind an increased susceptibility of daf-18/PTEN mutant nematodes to paralyzing drugs that exacerbate cholinergic transmission. The authors use state-of-theart genetics and neurogenetics coupled with locomotor behavior monitoring and neuroanatomical observations using gene expression reporters to show that the susceptibility occurs due to low levels of DAF-18/PTEN in developing inhibitory GABAergic neurons early during larval development (specifically, during the larval L1 stage). DAF-18/PTEN is convincingly shown to act cell-autonomously in these cells upstream of the PI3K-PDK-1-AKT-DAF-16/FOXO pathway, consistent with its well-known role as an antagonist of this conserved signaling pathway. The authors exclude a role for the TOR pathway in this process and present evidence implicating selectivity towards developing GABAergic neurons. Finally, the authors show that a diet supplemented with a ketogenic body, β-hydroxybutyrate, which also counteracts the PI3K-PDK-1-AKT pathway, promoting DAF-16/FOXO activity, partially rescues the proper development (morphology and function) of GABAergic neurons in daf-18/PTEN mutants, but only if the diet is provided early during larval development. This strongly suggests that the critical function of DAF18/PTEN in developing inhibitory GABAergic neurons is to prevent excessive PI3K-PDK-1-AKT activity during this critical and particularly sensitive period of their development in juvenile L1 stage worms. Whether or not the sensitivity of GABAergic neurons to DAF-18/PTEN function is a defining and widespread characteristic of this class of neurons in C. elegans and other animals, or rather a particularity of the unique early-stage GABAergic neurons investigated remains to be determined.

      Strengths:

      The study reports interesting and important findings, advancing the knowledge of how daf-18/PTEN and the PI3K-PDK-1-AKT pathway can influence neurodevelopment, and providing a valuable paradigm to study the selectivity of gene activities towards certain neurons. It also defines a solid paradigm to study the potential of dietary interventions (such as ketogenic diets) or other drug treatments to counteract (prevent or revert?) neurodevelopment defects and stimulate DAF-16/FOXO activity.

      Weaknesses:

      (1) Insufficiently detailed methods and some inconsistencies between Figure 4 and the text undermine the full understanding of the work and its implications.

      The incomplete methods presented, the imprecise display of Figure 4, and the inconsistency between this figure and the text, make it presently unclear what are the precise timings of observations and treatments around the L1 stage. What exactly do E-L1 and L1-L2 mean in the figure? The timing information is critical for the understanding of the implications of the findings because important changes take place with the whole inhibitory GABAergic neuronal system during the L1 stage into the L2 stage. The precise timing of the events such as neuronal births and remodelling events are welldescribed (e.g., Figure 2 in Hallam and Jin, Nature 1998; Fig 7 in Mulcahy et al., Curr Biol, 2022). Likewise, for proper interpretation of the implication of the findings, it is important to describe the nature of the defects observed in L1 larvae reported in Figure 1E - at present, a representative figure is shown of a branched commissure. What other types of defects, if any, are observed in early L1 larvae? The nature of the defects will be informative. Are they similar or not to the defects observed in older larvae?

      We thank the reviewer for highlighting these areas for improvement. We have updated and clarified the timing of observation in the text, figures, and methodology section accordingly.

      All experiments were conducted using age-synchronized animals. Gravid worms were placed on NGM plates and removed after two hours. The assays were then carried out on animals that hatched from the eggs laid during this specific timeframe.

      Regarding the detailed timings outlined in the original Figure 4 (now Figure 5 in the revised version), we provided the following information in the revised version: For experiments involving continuous exposure to βHB throughout development, the gravid worms were placed on NGM plates containing the ketone body and removed after two hours. Therefore, this exposure covered the ex-utero embryonic development period up to the L4-Young adult stage when the experiments were conducted.

      In experiments involving exposure at different developmental stages as those depicted in Figure 4 of the original version, (now Figure 5, revised version), animals were transferred between plates with and without βHB as required. We exposed daf-18/PTEN mutant animals to βHB-supplemented diets for 18-hour periods at different developmental stages (Figure 5A, revised version). The earliest exposure occurred during the 18 hours following egg laying, covering ex-utero embryonic development and the first 8-9 hours of the L1 stage. The second exposure period encompassed the latter part of the L1 stage, the entire L2 stage, and most of the L3 stage. The third exposure spanned the latter part of the L3 stage (~1-2 hours), the entire L4 stage, and the first 6-7 hours of the adult stage.

      All this information has been conveniently included in Figure 5, text (Page13, lines 259-276), and in methodology (Page 4, Lines 85-90, Revised Methods and Supplementary information) of the revised manuscript.

      In response to the reviewer's suggestion, we have also included photos of daf-18 worms at the L1 stage (30 min/1h post-hatching). Defects are already present at this early stage, such as handedness and abnormal branching commissures, which are also observed in adult worm neurons (see Supplementary Figure 4, revised version). 

      These defects manifest in DD neurons shortly after larval birth. The prevalence of animals with errors is higher in L4 worms (when both VDs and DDs are formed) compared to early L1s (Figures 3 C-E and Supplementary Figure 4, revised version). This suggests that defects in VD neurons also occur in daf-18 mutants. Indeed, when we analyzed the neuronal morphology of several wild-type and daf-18 mutant animals, we found defects in the commissures corresponding to both DD and VD neurons (Supplementary Figure 3, revised version). 

      These data are now included in the revised version (Results (Page 10, lines 177-196), Discussion (Pages 14-16), Main Figure 3, and Supplementary Figures 3, 4 and 7 revised version)

      (2) The claim of proof of concept for a reversal of neurodevelopment defects is not fully substantiated by data.

      The authors state that the work "constitutes a proof of concept of the ability to revert a neurodevelopmental defect with a dietary intervention" (Abstract, Line 56), however, the authors do not present sufficient evidence to distinguish between a "reversal" or prevention of the neurodevelopment defect by the dietary intervention. This clarification is critical for therapeutic purposes and claims of proof-of-concept. From the best of my understanding, reversal formally means the defect was present at the time of therapy, which is then reverted to a "normal" state with the therapy. On the other hand, prevention would imply an intervention that does not allow the defect to develop to begin with, i.e., the altered or defective state never arises. In the context of this study, the authors do not convincingly show reversal. This would require showing "embryonic" GABAergic neuron defects or showing convincing data in newly hatched L1 (0-1h), which is unclear if they do so or not, as I have failed to find this information in the manuscript. Again, the method description needs to be improved and the implications can be very different if the data presented in Figure 2D-E regard newly born L1 animals (0-1h) or L1 animals at say 5-7h after hatching. This is critical because the development of the embryonically-born GABAergic DD neurons, for instance, is not finalized embryonically. Their neurites still undergo outgrowth (albeit limited) upon L1 birth (see DataS2 in Mulcahy et al., Curr Biol 2022), hence they are susceptible to both committing developmental errors and to responding to nutritional interventions to prevent them. In contrast to embryonic GABAergic neurons, embryonic cholinergic neurons (DA/DB) do not undergo neurite outgrowth post-embryonically (Mulcahy et al., Curr Biol 2022), a fact which could provide some mechanistic insight considering the data presented. However, neurites from other post-embryonically-born neurons also undergo outgrowth postembryonically, but mostly during the second half of the L1 stage following their birth up to mid-L2, with significant growth occurring during the L1-L2 transition. These are the cholinergic (VA/VB and AS neurons) and GABAergic (VD) neurons. The fact that AS neurons undergo a similar amount of outgrowth as VD neurons is informative if VD neurons are or are not susceptible to daf-18/PTEN activity. Independently, DD neurons are still quite unique on other aspects (see below), which could also bring insight into their selective response.

      Finally, even adjusting the claim to "constitutes a proof-of-concept of the ability of preventing a neurodevelpmental defect with a dietary intervention" would not be completely precise, because it is unclear how much this work "constitutes a proof of concept". This is because, unless I misunderstood something, dietary interventions are already applied to prevent neurodevelopment defects, such as when folic acid supplementation is recommended to pregnant women to prevent neural tube defects in newborns.

      Thank you very much for pointing out this issue and highlighting the need to further investigate the ameliorative capacity of βHB on GABAergic defects in daf-18 mutants. In the revised version, we have included experiments to address this point.

      Our microscopy analyses strongly indicate that the development of DD neurons is affected, with errors observed as early as one-hour post-hatching (Main Figure 3, and Supplementary Figures  4 and 7, revised version). Additionally, based on the position of the commissures in L4s, our results strongly suggest that VD neurons are also affected (Supplementary Figure 3, revised version). Both, the frequency of animals with errors and the number of errors per animal are higher in L4s compared to L1 larvae (Main Figures 3,  and Supplementary Figure 4 and 7, revised version). It is very likely that the errors in VD neurons, which are born in the late L1 stage, are responsible for the higher frequency of defects observed in L4 animals. 

      As the reviewer noted, GABAergic DD neurons, which are born embryonically, do not complete their development during the embryonic stages. Some defects in DD neurons may arise during the postembryonic period. Following the reviewer's suggestion, we analyzed L1 larvae at different times before the appearance of VDs (1 hour post-hatching and 6 hours post-hatching). We did not observe an increase in error prevalence, suggesting that DD defects in daf-18 mutants are mostly embryonic (Supplementary Fig 4B, Revised Version). 

      Our findings suggest that βHB's enhancement is not due to preventive effects in DDs, as defects persist in newly hatched larvae regardless of βHB presence (Supplementary Figure 7, revised version), and postembryonic DD growth does not introduce new errors (Supplementary Figure 4, revised version). This lack of preventive effect could be due to βHB's limited penetration into the embryonic environment. Unlike early L1s, significant improvement occurs in L4s upon βHB early exposure (Supplementary Figure 7, revised version). This could be explained by a reversing effect on malformed DD neurons and/or a protective influence on VD neuron development. While we cannot rule out the first option, even if all errors in DDs in L1 were repaired (which is very unlikely), it wouldn't explain the level of improvement in L4 (Supplementary Figure 7, revised version). Therefore, we speculate that VDs may be targeted by βHB. The notion that exposure to βHB during early L1 can ameliorate defects in neurons primarily emerging in late L1s (VDs) is intriguing. We may hypothesize that residual βHB or a metabolite from prior exposure could forestall these defects in VD neurons. Notably, βHB has demonstrated a capacity for long-lasting effects through epigenetic modifications (Reviewed in He et al, 2023, https://doi.org/10.1016%2Fj.heliyon.2023.e21098). More work is needed to elucidate the underlying fundamental mechanisms regarding the ameliorating effects of βHB supplementation. We have now discussed these possibilities under discussion (Page 17, lines 369-383, revised version).

      We agree with the reviewer that the term "reversal" is not accurate, and we have avoided using this terminology throughout the text. Furthermore, in the title, we have decided to change the word "rescue" to "ameliorate," as our experiments support the latter term but not the former. Additionally, the reviewer is correct that folic acid administration to pregnant women is already a metabolic intervention to prevent neural tube defects. In light of this, we have avoided claiming this as proof of concept in the revised manuscript 

      (3) The data presented do not warrant the dismissal of DD remodeling as a contributing factor to the daf-18/PTEN defects.

      Inhibitory GABAergic DD neurons are quite unique cells. They are well-known for their very particular property of remodeling their synaptic polarity (DD neurons switch the nature of their pre- and postsynaptic targets without changing their wiring). This process is called DD remodeling. It starts in the second half of the L1 stage and finishes during the L2 stage. Unfortunately, the fact that the authors find a specific defect in early GABAergic neurons (which are very likely these unique DD neurons) is not explored in sufficient detail and depth. The facts that these neurons are not fully developed at L1, that they still undergo limited neurite growth, and that they are poised for striking synaptic plasticity in a few hours set them apart from the other explored neurons, such as early cholinergic neurons, which show a more stable dynamics and connectivity at L1 (see Mulcahy et al., Curr Biol 2022).

      The authors use their observation that daf-18/PTEN mutants present morphological defects in GABAergic neurons prior to DD remodeling to dismiss the possibility that the DAF-18/PTEN-dependent effects are "not a consequence of deficient rearrangement during the early larval stages". However, DD remodeling is just another cell-fate-determined process and as such, its timing, for instance, can be affected by mutations in genes that affect cell fates and developmental decisions, such as daf-18 and daf-16, which affect developmental fates such as those related with the dauer fate. Specifically, the authors do not exclude the possibility that the defects observed in the absence of either gene could be explained by precocious DD remodeling. Precocious DD remodeling can occur when certain pathways, such as the lin-14 heterochronic pathway, are affected. Interestingly, lin-14 has been linked with daf16/FOXO in at least two ways: during lifespan determination (Boehm and Slack, Science 2005) and in the

      L1/L2 stages via the direct negative regulation of an insulin-like peptide gene ins-33 (Hristova et al., Mol Cell Bio 2005). It is likely that the prevention of DD dysfunction requires keeping insulin signaling in check (downregulated) in DD neurons in early larval stages, which seems to coincide with the critical timing and function of daf-18/PTEN. Hence, it will be interesting to test the involvement of these genes in the daf-18/daf-16 effects observed by the authors.

      This is another interesting point raised by the reviewer. We have demonstrated that defects manifest in early L1 (30 min-1 hour post-hatching) which corresponds to a pre-remodeling time in wild-type worms.

      We acknowledge the possibility of early remodeling in specific mutants as pointed out by the reviewer.

      However, the following points suggest that the effects of these mutations may extend beyond the particularity of DD remodeling: i) Our experiments also show defects in VD neurons in daf-18 mutants (Supplementary Figure 3, revised version), as discussed in our previous response. These neurons do not undergo significant remodeling during their development. ii) DAF-18 and DAF-16 deficiencies produce neurodevelopmental alteration on other Non-Remodeling Neurons: Severe neurite defects in neurons that are nearly fully formed at larval hatching, such as AIY in daf-18 and daf-16 mutants, have been previously reported (Christensen et al., 2011). Additionally, the migration of another neuron, HSN, is severely affected in these mutants (Kennedy et al., 2013). iii) To the best of our knowledge, DD remodeling only alters synaptic polarity without forming new commissures or significant altering the trajectory of the formed ones. Thus, it is unlikely (though not impossible) for remodeling defects to cause the observed commissural branching and handedness abnormalities in DD neurons. Therefore, we think that the impact of daf-18 mutations on GABAergic neurons is not primarily linked to DD remodeling but extends to various neuron types. It is intriguing and requires further exploration in the future, the apparent resilience of cholinergic motor neurons to these mutations. This resilience is not limited to daf18/PTEN animals since mutants in certain genes expressed in both neuron types (such as neuronal integrin ina-1 or eel-1, the C. elegans ortholog of HUWE1) alter the function or morphology of GABAergic neurons but not cholinergic motor neurons (Kowalski, J. R. et al. Mol Cell Neurosci 2014; Oliver, D. et al. J Dev Biol (2019); Opperman, K. J. et al. Cell Rep 2017). These points are discussed in the manuscript (Discussion, page 15, lines 311-322, revised version) and reveal the existence of compensatory or redundant mechanisms in these excitatory neurons, rendering them much more resistant to both morphological and functional abnormalities.

      Discussion on the impact of the work on the field and beyond:

      The authors significantly advance the field by bringing insight into how DAF-18/PTEN affects neurodevelopment, but fall short of understanding the mechanism of selectivity towards GABAergic neurons, and most importantly, of properly contextualizing their findings within the state-of-the-art C. elegans biology.

      For instance, the authors do not pinpoint which type of GABAergic neuron is affected, despite the fact that there are two very well-described populations of ventral nerve cord inhibitory GABAergic neurons with clear temporal and cell fate differences: the embryonically-born DD neurons and the postembryonically-born VD neurons. The time point of the critical period apparently defined by the authors (pending clarifications of methods, presentation of all data, and confirmation of inconsistencies between the text and figures in the submitted manuscript) could suggest that DAF-18/PTEN is required in either or both populations, which would have important and different implications. An effect on DD neurons seems more likely because an image is presented (Figure 2D) of a defect in an L1 daf-18/PTEN mutant larva with 6 neurons (which means the larva was processed at a time when VD neurons were not yet born or expressing pUnc-47, so supposedly it is an image of a larva in the first half of the L1 stage (0-~7h?)). DD neurons are also likely the critical cells here because the neurodevelopment errors are partially suppressed when the ketogenic diet is provided at an "early" L1 stage, but not later (e.g., from L2-L3, according to the text, L2-L4 according to the figure? ).

      Thank you for this insightful input. As previously mentioned, we conducted experiments in this revision to clarify the specificity of GABAergic errors in daf-18/PTEN mutants, in particular, whether they affect DDs, VDs, or both. Our results suggest that commissural defects are not limited to DD neurons but also occur in VD neurons (Supplementary Figure 3). Regarding the effect of βHB, our findings suggest that VD neurons are targets of βHB action. As mentioned in the previous response and the discussion section (Page 17, lines 369-383, revised version), we might speculate that lingering βHB or a metabolite from prior exposure could mitigate these defects in VD neurons that are born in Late L1s-Early L2s. Additionally, βHB has been noted for its capacity to induce long-term epigenetic changes. Therefore, it could act on precursor cells of VD neurons, with the resulting changes manifesting during VD development independently of whether exposure has ceased. All these possibilities are now discussed in the manuscript.

      Acknowledging that our work raises several questions that we aim to address in the future, we believe our manuscript provides valuable information regarding how the PI3K pathway modulates neuronal development and how dietary interventions can influence this process.

      This study brings important contributions to the understanding of GABAergic neuron development in C. elegans, but unfortunately, it is justified and contextualized mostly in distantly-related fields - where the study has a dubious impact at this stage rather than in the central field of the work (post-embryonic development of C. elegans inhibitory circuits) where the study has stronger impact. This study is fundamentally about a cell fate determination event that occurs in a nutritionally-sensitive

      developmental stage (post-embryonic L1 larval stage) yet the introduction and discussion are focused on more distantly related problems such as excitatory/inhibitory (E/I) balance, pathophysiology of human diseases, and treatments for them. Whereas speculation is warranted in the discussion, the reduced indepth consideration of the known biology of these neurons and organisms weakens the impact of the study as redacted. For instance, the critical role of DAF-18/PTEN seems to occur at the early L1 larval stage, a stage that is particularly sensitive to nutritional conditions. The developmental progression of L1 larvae is well-known to be sensitive to nutrition - eg, L1 larvae arrest development in the absence of food, something that is explored in nematode labs to synchronize animals at the L1 stage by allowing embryos to hatch into starvation conditions (water). Development resumes when they are exposed to food. Hence, the extensive postembryonic developmental trajectory that GABAergic neurons need to complete is expected to be highly susceptible to nutrition. Is it? The sensitivity towards the ketogenic diet intervention seems to favor this. In this sense, the attribution of the findings to issues with the nutrition-sensitive insulin-like signaling pathway seems quite plausible, yet this possibility seems insufficiently considered and discussed.

      We greatly appreciate the reviewer's emphasis on the sensitivity of the L1 stage to nutritional status. As the reviewer points out, C. elegans adjusts its development based on food availability, potentially arresting development in L1 in the absence of food. It is therefore reasonable that both the completion of DD neuron trajectories and the initial development steps of VD neurons are particularly sensitive to dietary modulation of the insulin pathway, in which both DAF-18 and DAF-16 play roles. This important point has also been included in the discussion (Page 18, lines 384-407, revised version).

      Finally, the fact that imbalances in excitatory/inhibitory (E/I) inputs are linked to Autism Spectrum Disorders (ASD) is used to justify the relevance of the study and its findings. Maybe at this stage, the speculation would be more appropriate if restricted to the discussion. In order to be relevant to ASD, for instance, the selectivity of PTEN towards inhibitory neurons should occur in humans too. However, at present, the E/I balance alteration caused by the absence of daf-18/PTEN in C. elegans could simply be a coincidence due to the uniqueness of the post-embryonic developmental program of GABAergic neurons in C. elegans. To be relevant, human GABAergic neurons should also pass through a unique developmental stage that is critically susceptible to the PI3K-PDK1-AKT pathway in order for DAF18/PTEN to have any role in determining their function. Is this the case? Hence, even in the discussion, where the authors state that "this study provides universally relevant information on.... the mechanisms underlying the positive effects of ketogenic diets on neuronal disorders characterized by GABA dysfunction and altered E/I ratios", this claim seems unsubstantiated as written particularly without acknowledging/mentioning the criteria that would have to be fulfilled and demonstrated for this claim to be true.

      Our results suggest that defects in GABAergic neurons are not limited to DDs, which, as the reviewer rightly notes, are quite unique in their post-embryonic development primarily due to the synaptic remodeling process they undergo. These defects also extend to VD neurons, which do not exhibit significant developmental peculiarities once they are born. Therefore, we think that the defects are not specific to the developmental program of DD neurons but are more related to all GABAergic motoneurons. Additionally, the observation of defects in non-GABAergic neurons in C. elegans daf-18 mutants supports the hypothesis that the role of daf-18 is not limited to DD neurons (Christensen et al., 2011; Kennedy et al., 2013).

      In mammals, Pten conditional knockout (cKO) animals have been extensively studied for synaptic connectivity and plasticity, revealing an imbalance between synaptic excitation and inhibition (E/I balance) (Reviewed in Rademacher and Eickholt, 2019, Cold Spring Harbor Perspect Med, https://doi.org/10.1101%2Fcshperspect.a036780). This imbalance is now widely accepted as a key pathological mechanism linked to the development of ASD-related behavior (Lee et al, 2017; Biological Psychiatry, https://doi.org/10.1016/j.biopsych.2016.05.011) . The importance of PTEN in the development of GABAergic neurons in mammals is well-documented. For instance, embryonic PTEN deletion from inhibitory neurons impacts the establishment of appropriate numbers of parvalbumin and somatostatin-expressing interneurons, indicating a central role for PTEN in inhibitory cell development (Vogt et al, 2015, Cell Rep, https://doi.org/10.1016%2Fj.celrep.2015.04.019). Additionally, conditional PTEN knockout in GABAergic neurons is sufficient to generate mice with seizures and autism-related behavioral phenotypes (Shin et al, 2021, Molecular Brain, https://doi.org/10.1186%2Fs13041-02100731-8). Moreover, while mice in which PV GABAergic neurons lacked both copies of Pten experienced seizures and died, heterozygous animals (PV-Pten+/−) showed impaired formation of perisomatic inhibition (Baohan et al, 2016, Nature Comm, OI: 10.1038/ncomms12829). Therefore, there is substantial evidence in mammals linking PTEN mutations to neurodevelopmental disorders in general and affecting GABAergic neurons in particular. Hence, we believe that the role of daf-18/PTEN in GABAergic development could be a more widespread phenomenon across the animal kingdom rather than a specific process unique to C. elegans.

      Beyond the points discussed, we have addressed the reviewer's comment regarding the last sentence of the abstract. We have revised it to more cautiously frame the relationship between our findings, ASD, and mammalian neurodevelopmental disorders.

      Reviewer #2 (Public Review):

      Summary:

      Disruption of the excitatory/inhibitory (E/I) balance has been reported in Autism Spectrum Disorders

      (ASD), with which PTEN mutations have been associated. Giunti et al choose to explore the impact of PTEN mutations on the balance between E/I signaling using as a platform the C. elegans neuromuscular system where both cholinergic (E) and GABAergic (I) motor neurons regulate muscle contraction and relaxation. Mutations in daf-18/PTEN specifically affect morphologically and functionally the GABAergic (I) system, while leaving the cholinergic (E) system unaffected. The study further reveals that the observed defects in the GABAergic system in daf-18/PTEN mutants are attributed to reduced activity of DAF-16/FOXO during development.

      Moreover, ketogenic diets (KGDs), known for their effectiveness in disorders associated with E/I imbalances such as epilepsy and ASD, are found to induce DAF-16/FOXO during early development. Supplementation with β-hydroxybutyrate in the nematode at early developmental stages proves to be both necessary and sufficient to correct the effects on GABAergic signaling in daf-18/PTEN mutants.

      Strengths:

      The authors combined pharmacological, behavioral, and optogenetic experiments to show the

      GABAergic signaling impairment at the C. elegans neuromuscular junction in DAF-18/PTEN and DAF-

      16/FOXO mutants. Moreover, by studying the neuron morphology, they point towards

      neurodevelopmental defects in the GABAergic motoneurons involved in locomotion. Using the same set of experiments, they demonstrate that a ketogenic diet can rescue the inhibitory defect in the daf18/PTEN mutant at an early stage.

      Weaknesses:

      The morphological experiments hint towards a pre-synaptic defect to explain the GABAergic signaling impairment, but it would have also been interesting to check the post-synaptic part of the inhibitory neuromuscular junctions such as the GABA receptor clusters to assess if the impairment is only presynaptic or both post and presynaptic.

      Moreover, all observations done at the L4 stage and /or adult stage don't discriminate between the different GABAergic neurons of the ventral nerve cord, ie the DDs which are born embryonically and undergo remodeling at the late L1 stage, and VDs which are born post-embryonically at the end of the L1 stage. Those additional elements would provide information on the mechanism of action of the FOXO pathway and the ketone bodies.

      Thank you for your insightful suggestions. 

      This is an initial study that serves as a cornerstone, demonstrating the sensitivity of GABAergic neuron development to alterations in the PI3K pathway and how these alterations can be mitigated by a dietary intervention with a ketone body. While we have determined that the transcription factor DAF-16/FOXO is essential in the neurodevelopmental process and is the target of ketone bodies to alleviate defects, there are still underlying mechanisms to be elucidated. This is only the first step that opens many avenues for further investigation, including the study of post-synaptic partners.

      While our current study primarily focuses on neuronal alterations without delving into potential postsynaptic effects, we do plan to investigate this aspect in future research. This includes examining GABAergic receptors as well as cholinergic receptors, as exacerbation of cholinergic signaling cannot be ruled out. To conduct a comprehensive study of post-synaptic structure and functionality, we would need strains with fluorescent markers for both pre- and post-synaptic components (such as rab-3, unc-49, unc29, acr-16 fusion to GFP or mCherry). Unfortunately, most of these strains are not currently available in our laboratory. Unlike the US or Europe, acquiring these strains from the C. elegans CGC repository in Argentina is challenging due to common customs delays, which require significant time and resources to navigate. Discussions at the Latin American C. elegans conference with CGC administrators, such as Ann Rougvie, have been initiated to address this issue, but a solution has not been reached yet.  Additionally, to analyze post-synaptic functionality in-depth, studying the response to perfusion with various agonists using electrophysiology would be beneficial. We are in the process of acquiring the capability to conduct electrophysiology experiments in our laboratory, but progress is slow due to limited funding.

      While we believe these experiments are very informative, they will require a considerable amount of time due to our current circumstances. We consider them non-essential to the primary message of the paper, which focuses on neuronal developmental defects leading to functional alterations in daf-18/PTEN mutants and the novel finding that these can be mitigated by supplementing food with hydroxybutyrate. We will study the structure and functionality of the post-synapse in our future projects and also plan to extend this investigation to mutants with deficiencies in genes closely related to neurodevelopmental defects, such as neuroligin, neurexin, or shank-3, which have been implicated in synaptic architecture.

      We also agree that discriminating between DD and VD neurons provides significant insights into the neurodevelopmental phenomena dependent on the FOXO pathway and the action of βHB. In this revised version, we present evidence that not only DD neurons are affected but also VD neurons (see

      Supplementary Figure 3, revised version). This allows us to suggest that daf-18 affects the development of GABAergic neurons regardless of whether they are born embryonically (DDs) or post-embryonically (VDs) (see also our response to the previous reviewer). We hope to distinguish the defects observed in each type of neuron in future studies. For this, we would need to use strains specifically marked in one neuronal type or another, which, for the same reasons mentioned earlier, would take a considerable amount of time under current conditions. 

      Conclusion:

      Giunti et al provide fundamental insights into the connection between PTEN mutations and neurodevelopmental defects through DAF-16/FOXO and shed light on the mechanisms through which ketogenic diets positively impact neuronal disorders characterized by E/I imbalances.  

      Reviewer #3 (Public Review):

      Summary:

      This is a conceptually appealing study by Giunti et al in which the authors identify a role for PTEN/daf-18 and daf-16/FOXO in the development of inhibitory GABA neurons, and then demonstrate that a diet rich in ketone body β-hydroxybutyrate partially suppresses the PTEN mutant phenotypes. The authors use three assays to assess their phenotypes: (1) pharmacological assays (with levamisole and aldicarb); (2) locomotory assays and (3) cell morphological assays. These assays are carefully performed and the article is clearly written. While neurodevelopmental phenotypes had been previously demonstrated for PTEN/daf-18 and daf-16/FOXO (in other neurons), and while KB β-hydroxybutyrate had been previously shown to increase daf-16/FOXO activity (in the context of aging), this study is significant because it demonstrates the importance of KB β-hydroxybutyrate and DAF-16 in the context of neurodevelopment. Conceptually, and to my knowledge, this is the first evidence I have seen of a rescue of a developmental defect with dietary metabolic intervention, linking, in an elegant way, the underpinning genetic mechanisms with novel metabolic pathways that could be used to circumvent the defects.

      Strengths:

      What their data clearly demonstrate, is conceptually appealing, and in my opinion, the biggest contribution of the study is the ability of reverting a neurodevelopmental defect with a dietary intervention that acts upstream or in parallel to DAF-16/FOXO.

      Weaknesses:

      The model shows AKT-1 as an inhibitor of DAF-16, yet their studies show no differences from wildtype in akt-1 and akt-2 mutants. AKT is not a major protein studied in this paper, and it can be removed from the model to avoid confusion, or the result can be discussed in the context of the model to clarify interpretation.

      Thank you very much for the suggestion. We agree with the reviewer's appreciation that the study of AKT's action itself is too limited in this study to draw conclusions that would allow its inclusion in the proposed model. Therefore, following the reviewer's suggestion, we have removed this protein from our model

      When testing additional genes in the DAF-18/FOXO pathway, there were no significant differences from wild-type in most cases. This should be discussed. Could there be an alternate pathway via DAF-18/DAF16, excluding the PI3K pathway or are there variations in activity of PI3K genes during a ketogenic diet that are hard to detect with current assays?

      Thank you for bringing up this point. Our pharmacological experiments indeed demonstrate that all mutants associated with an exacerbation of the PI3K pathway, which typically inhibits nuclear translocation and activity of the transcription factor DAF-16, lead to imbalances in E/I

      (excitation/inhibition) that manifest as hypersensitivity to cholinergic drugs. This includes the gain of function of pdk-1 and the loss of function of daf-18 and daf-16 itself. In our subsequent experiments, we demonstrate that this exacerbation of the PI3K pathway leads to errors in the neurodevelopment of GABAergic neurons, which explains the hypersensitivity to aldicarb and levamisole.

      As the reviewer remarks, it is intriguing why mutants inhibiting this pathway do not show differences in their sensitivity to cholinergic drugs compared to wild-type animals. We can speculate, for instance, that during neurodevelopment, there is a critical period where the PI3K pathway must remain with very low activity (or even deactivated) for proper development of GABAergic neurons. This could explain why there are no differences in sensitivity to cholinergic drugs between mutants that inhibit the PI3K pathway and the wild type. The PI3K pathway depends on insulin-like signals, which are in turn positively modulated by molecules associated with the presence of food. Interestingly, larval stage 1 is particularly sensitive to nutritional status, being able to completely arrest development in the absence of food. Therefore, dietary intervention with BHB may generate a signal of dietary restriction (as seen in mammals) and, as a consequence of this dietary restriction, the PI3K pathway is inhibited, resulting in increased DAF-16 activity. This could restore the proper neurodevelopment of GABAergic neurons. However, this is mere speculation, and further deeper experiments (than the pharmacology ones we performed here) with mutants in different genes within the PI3K pathway may shed light on this point.

      Following the reviewer's suggestion, this point has been discussed in the revised version of the manuscript. (Discussion Page 18, Lines 384-407).

      The consequence of SOD-3 expression in the broader context of GABA neurons was not discussed. SOD3 was also measured in the pharynx but measuring it in neurons would bolster the claims.

      SOD-3 is a known target of DAF-16. Previous studies have shown that βHB induces SOD-3 expression through the induction of DAF-16 (Edwards et al, 2014, Aging,

      https://doi.org/10.18632%2Faging.100683). The highest levels of SOD-3 expression are typically observed in the pharynx or intestine (DeRosa et al, 2019 https://doi.org/10.1038/s41586-019-1524-5;  Zheng et al., 2021, PNAS, https://doi.org/10.1073/pnas.2021063118), and it is often used as a measure of general upregulation of DAF-16. Therefore, we used this parameter as a measure of βHB upregulating systemic DAF-16 activity.  While we agree with the reviewer that observing variations in SOD-3 expression in neurons would further support our conclusions, unfortunately, we did not detect measurable signals of SOD-3 in motor neurons in either the control condition or the daf-18 background even upon stress or BHB-exposure. This may be because SOD-3 is a minor target of DAF-16 in these neurons, or its modulation may not correspond to the timing of fluorescence measurements (L4-adults).

      Despite this, our genetic experiments and neuron-specific rescue experiments lead us to conclude that DAF-16 must act autonomously in GABAergic neurons to ensure proper neurodevelopment.

      If they want to include AKT-1, seeing its effect on SOD-3 expression could be meaningful to the model.

      Thank you for this suggestion. We believe that even measuring SOD-3 levels in akt mutant backgrounds would still provide limited information to give it a predominant value in our work. Additionally, to have a complete understanding of the total role of AKT, it would be necessary to measure it in a double mutant background of akt-1; akt-2, and these double mutants generate 100 % dauers even at 15C (Oh et al., PNAS 2005, https://doi.org/10.1073/pnas.0500749102; Quevedo et al., Current Biology 2007, http://dx.doi.org/10.1016/j.cub.2006.12.038; Gatzi et al., PLOS ONE 2014,

      https://doi.org/10.1371/journal.pone.0107671), greatly complicating the execution of these experiments. Therefore, following the first advice of this reviewer, we have decided to modify our model by excluding AKT.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      ⁃ Please include earlier in the main text the rationale for using unc-25 as a control/reference already when mentioning Figure 1A.

      Thank you for pointing out the need to reference this control earlier. We have included the following paragraph in the description of Figure 1 (Page 5, line 71, revised version):

      “Hypersensitivity to cholinergic drugs is typical of animals with an increased E/I ratio in the neuromuscular system, such as mutants in unc-25 (the C. elegans orthologue for glutamic acid decarboxylase, an essential enzyme for synthesizing GABA). While daf-18/PTEN mutants become paralyzed earlier than wild-type animals, their hypersensitivity to cholinergic drugs is not as severe as that observed in animals completely deficient in GABA synthesis, such unc-25 null mutants (Figures 1B and 1C) indicating a less pronounced imbalance between excitatory and inhibitory signals.”

      ⁃ Please discuss the greater sensitivity of pdk-1(gf) animals to levamisole than to aldicarb.

      Thank you for bringing up this subtle point.  We understand that the reviewer is referring to the paralysis curve in response to aldicarb in pdk-1(gf), which is closer to unc-25 than the curve for levamisole (in both cases, they are more sensitive than the wild type). Therefore, pdk-1(gf) animals seem to be more sensitive to aldicarb than to levamisole. These results are now shown in Figure 1D (revised version).

      The PI3K pathway does not only act in neurons but also in muscles. Gain of function in pdk-1 has been shown to modulate muscle protein degradation (Szewczyk et al, EMBO Journal, 2008. https://doi.org/10.1038/sj.emboj.7601540). In contrast,  no effect on protein degradation has been reported for null mutants in this gene. Several studies have demonstrated that protein degradation levels can differentially affect receptor subunits, particularly acetylcholine receptors (Reviewed in Crespi et al, Br J Pharmacol, 2018). C. elegans is characterized by a wide repertoire of AChR subunits, and there are at least two subtypes of ACh receptors in muscles (one multimeric sensitive to levamisole and one homomeric (ACR-16) insensitive to levamisole) (Richmond et al, 1999 Nature Neuroscience http://dx.doi.org/10.1038/12160; Touroutine D, JBC 2005 https://doi.org/10.1074/jbc.M502818200).

      Interestingly, acr-16 null mutants are hypersensitive to aldicarb (Zeng et al, JCB, 2023, https://doi.org/10.1083/jcb.202301117) while the electrophysiological response to levamisole in this mutant remains similar to that of wild-type (Tourorutine et al, 2005). Therefore, it may be that the gain of function in pdk-1 induces a change in the expression of AChR subtypes in muscle that differentially affect sensitivity to levamisole and ACh. This is purely speculative, and there may be many other explanations. While it would be interesting to explore this difference further, it goes far beyond the scope of this study. The cholinergic drug sensitivity assay is purely exploratory and allowed us to delve into the GABAergic and cholinergic signals in daf-18 mutants. In this sense, the hypersensitivity of pdk-1(gf) to both drugs supports the idea that an increase in PI3K signaling leads to an increased E/I ratio.

      ⁃ Please explain the rationale to perform akt-1 and akt-2 assays separated. Why not test doublemutants? Has their lack of redundancy been determined?.  

      Our pharmacological assays are conducted at the L4 larval stage, making it impossible to analyze the potential redundancy of akt-1 and akt-2 in sensitivity to levamisole and aldicarb. This impossibility arises because the akt-1;akt-2 double mutant exhibits nearly 100% arrest as dauer even at 15°C, as reported in several prior studies (Oh et al., PNAS 2005, https://doi.org/10.1073/pnas.0500749102; Quevedo et al., Current Biology 2007, http://dx.doi.org/10.1016/j.cub.2006.12.038; Gatzi et al., PLOS ONE 2014, https://doi.org/10.1371/journal.pone.0107671). While the increased dauer arrest in the double mutant compared to the single mutants might suggest redundant functions in dauer entry, there are also reports indicating the absence of redundancy in other processes, such as vulval development (Nakdimon et al., PLOS Genetics 2012, https://doi.org/10.1371%2Fjournal.pgen.1002881).

      The complete Dauer arrest likely underlies why other studies focusing on the role of the PI3K pathway in neurodevelopment utilize both mutants separately (Christensen et al, Development 2011,

      https://doi.org/10.1242/dev.069062). While determining the potential redundancy of these genes is not feasible for this assay, we utilized various mutants of the pathway (age-1, pdk-1, daf-18, daf-16 and daf16;daf-18 in addition to the akt-s) that support the conclusion, which is that exacerbating the PI3K pathway activity makes animals hypersensitive to cholinergic drugs.

      In response to the reviewer's concern, we have added a sentence in the text explaining the impossibility of performing the assay in the akt-1;akt-2 double mutant (Page 6, lines90-92) 

      Figure 1C and D (This applies to all similarly presented bar figures). Please show data points and dispersion (preferably data, median+- 25-75% or average+-SD). 

      Thank you. Done

      ⁃ Line 112 -maybe "and resumes"? 

      Thank you. Done (Line 126, revised version)

      ⁃ Figure 1E and F. Please present mean +-SD (not SEM) of fluctuations. Please change slightly the tones so that the dispersion is easier to distinguish on the "blue light on" box.

      Thank you for the suggestion. We have adjusted the tones as recommended to enhance the visualization of the "blue light on" box. For visualization purposes, we present the shading of the standard error of the mean (SEM), as is usual in these types of optogenetic experiments where traces of animal length variations are measured (Liewald et al, Nature Methods, 2008, doi: 10.1038/nmeth.1252; Schulstheis et al, J. Neurophysiology, 2011, doi: 10.1152/jn.00578.2010; Koopman et al, BMC Biology 2021, https://doi.org/10.1186/s12915-021-01085-2; Seidhenthal et al, Micro Publication Biology, 2022, https://doi.org/10.17912%2Fmicropub.biology.000607 ).

      For the revised version, we have also included bar graphs for each optogenetic experiment, representing the mean of the length average of each worm measured from the first second after the blue light was turned on until the second before the light was turned off (in the graph, this corresponds to the period between seconds 6 and 9 of the traces). These graphs include the standard deviation and the corresponding significance levels. All of this has been included in the new legend (Figure 2D, 2E, 4E-J).

      ⁃ Figure 1A&1B & Supplementary Figure 1D x Supplementary Figure 1E&1F. What is the difference between these experiments? Whereas the unc-25 mutants paralyze in the same amount of time, the WT animals paralyze ~1 h later in Supplementary Figure 1E-1F in response to either drug. Please revise experimental conditions to see if anything can be learned eg, maybe this is a nutritional response from experiments done at different timepoints? Maybe different food recipes affected sensitivity to paralysis?

      Thank you for pointing this out. While the experiments with daf-18 (in both alleles) and daf-16 were conducted at the beginning of this project (2019-2020), the assays with the other mutants in the PI3K and mTOR pathways were performed years later. Changes in the reagents used (agar, peptone, cholesterol, etc.) to grow the worms have occurred, potentially altering the animals' response directly or through the nutritional quality of the bacteria they grow on. In addition, the difference may be attributed to the fact that experiments at the project's outset were conducted by one author, while more recent experiments were carried out by another. The goal is to quantify paralysis in non-responsive worms after touch stimulation. The force of this probing or the thickness of the hair used for touching can be slightly operator-dependent and can lead to variable responses. In addition, always the presence of wild-type and unc-25 strain is included as internal control in every experiment. Nevertheless, despite this userdependent variation, the experiments were always conducted blindly (except for unc-25, whose uncoordinated phenotype is easily identifiable), thus we trust in the outcomes.

      ⁃ Supplementary Figure 1G - Length and Width appear to be switched in both left and right panels - please revise and include a description of N and of statistics depicted. 

      Unfortunately, we don't see the switching error that the reviewer mentioned. In the left panel, we demonstrate that optogenetic activation of GABAergic neurons leads to an increase in length without modifying the width of the animal. Therefore, we conclude that the increase in area, as observed in our Fiji macro for optogenetic response analysis, is due to an increase in the animal's length. In the cholinergic activation shown in the right panel, the animal shortens (decreasing length) without modifying the width, resulting in the reduction of the total body area. 

      We have included information about N (sample size) and the statistical test used in the legends as suggested. These graphs are now shown as Figures 2F and G, revised version.

      ⁃ Supplementary Figure 1G legend lines 779-780. Please describe the post-hoc test applied following ANOVA to obtain the denoted p values. This applies to all datasets where ANOVA or Krusal-Wallis tests were applied.

      Following reviewer´s suggestion, all the post-hoc tests applied after ANOVA or Kruskal-Wallis analysis were included in the legend of each figure and Materials and Methods (statistical analysis section).

      ⁃ Line 174 maybe "arises *from* the hyperactivation" instead of *for*?.

      Corrected. Thank you. Line 190, revised version.

      ⁃ Supplementary Figure 4. On line 816 it says n=40-90, but please check the n of the daf-18, daf-16 samples, which seem to have less than 40 animals.

      We understand that the reviewer is referring to Supplementary Figure 3 from the original version (now Supplementary Figure 5 in the revised version). We have now included the number of observations below each data point cloud to clearly indicate the sample size for each condition

      ⁃ Supplementary Figure 4 - please state what are the bars on the graphs. Please state which post-hoc test was performed after Kruskal-Wallis and present at least the p values obtained between treated controls and each genotype. Alternatively, present the whole truth table in supplementary daita.

      We understand that the reviewer is referring to Supplementary Figure 3 from the original version (now Supplementary Figure 5 in the revised version). There was an error in the original legend (thank you for bringing this to our attention) since the statistics were not performed using Kruskall-Wallis in this case, but rather each treated condition was compared to its own untreated control using Mann-Whitney test. We have now added the p-values to the graph. All raw data for this figure, as well as for all other figures, are available in Open Science Framework (https://osf.io/mdpgc/?view_only=3edb6edf2298421e94982268d9802050).

      ⁃ Please cite the figure panels in order: eg, Figure 3E is mentioned in the text after panels Figure 3F-K.

      Done. We have rearranged the figures to adapt them to the text order (Figure 4, revised version)

      ⁃ Figure 4 - line 610 please revise "(n=20-30 (n: 20-25 animals per genotype/trial)."

      Thank you. Corrected.

      ⁃ Figure 4 - there appears to be an inconsistency in the figure with the text (lines 223-225). In figures it says E-L1, but in the text, it says "solely in L1". Does E-L1 include the whole L1 stage? If not- E-L1 can be interpreted only as during the embryonic stage, hence, no exposure to betaHB due to the impermeable chitin eggshell. Then there is L1-L2, which should cover the L1 stage and the L2 or something else. Please revise. The text mentions L2-L3 or L3-L4 and these categories are not in the figures. This clarification is key for the interpretation of the results. The precise developmental time of the exposures is not defined either in the methods or in the figures. Please provide precise times relative to hours and/or molts and revise the text/figure for consistency.

      The reviewer is entirely correct in pointing out the lack of relevant data regarding the exposure time to βHB. We have now clarified the information For the revised version, we have adjusted the nomenclature of each exposure period to precisely reflect the developmental stages involved.

      For the experiments involving continuous exposure to βHB throughout development, the NGM plate contained the ketone body. Therefore, the exposure encompassed, in principle, the ex-utero embryonic development period up to L4-Young adults (E-L4/YA, in Figure 5A) when the experiments were conducted. Since it could be a restriction to drug penetration through the chitin shell of the eggs (see Supplementary Figure 7), we can ensure βHB exposure from hatching.

      In experiments involving exposure at different developmental stages as those depicted in Figure 4 of the original version, (now Figure 5), animals were transferred between plates with and without βHB as required. We exposed daf-18/PTEN mutant animals to βHB-supplemented diets for 18-hour periods at different developmental stages (Figure 5A). The earliest exposure occurred during the 18 hours following egg laying, covering ex-utero embryonic development and the first 8-9 hours of the L1 stage (This period is called E-L1, in figure 5 revised version). The second exposure period encompassed the latter part of the L1 stage, the entire L2 stage, and most of the L3 stage (L1-L3). The third exposure spanned the latter part of the L3 stage (~1-2 hours), the entire L4 stage, and the first 6-7 hours of the adult stage (L3-YA).

      All this information has been conveniently included in Figure 5 (and its legend), text (Page 13, lines 259276), and Material and Methods of the revised manuscript.

      ⁃ Some methods are not sufficiently well described. Specifically, how the animals were exposed to treatments and how stages were obtained for each experiment. Was synchronization involved? If so, in which experiments and how exactly was it performed?

      As mentioned in previous responses all the experiments were performed in age-synchronized animals. We include the following sentence in Materials and Methods (C. elegans culture and maintenance section): “All experiments were conducted on age-synchronized animals. This was achieved by placing gravid worms on NGM plates and removing them after two hours. The assays were performed on the animals hatched from the eggs laid in these two hours”.

      Reviewer #2 (Recommendations For The Authors):

      Major points

      (1) To complete the study on the GABAergic signaling at the NMJs, it would be interesting to assess the status of the post-synaptic part of the synapse such as the GABAR clustering. It would also tell if the impairment is only presynaptic or both post and presynaptic.

      Thank you for your insightful suggestion. We agree that exploring post-synaptic elements can shed light on whether the impairment is solely presynaptic or involves both pre and post-synaptic components.

      While our current study primarily focuses on neuronal alterations without delving into potential postsynaptic effects, we do plan to investigate this aspect in the future. This includes not only examining GABAergic receptors but also exploring cholinergic receptors, as exacerbation of cholinergic signaling cannot be ruled out. To conduct a comprehensive study of post-synaptic structure and functionality, we would need strains with fluorescent markers for both pre and post-synaptic components (rab-3, unc-49, unc-29, acr-16 driving GFP or mCherry). However, most of these strains are not currently available in our laboratory. Unlike the US or Europe, acquiring these strains from the C. elegans CGC repository in Argentina is challenging due to common customs delays, requiring significant time and resources to navigate. Discussions at the Latin American C. elegans conference with CGC administrators, such as Ann Rougvie, have been initiated to address this issue, but a solution has not been reached yet. 

      Additionally, to analyze post-synaptic functionality in-depth, studying the response to perfusion with various agonists using electrophysiology would be beneficial. We are in the process of acquiring the capability to conduct electrophysiology experiments in our laboratory, but progress is slow due to limited funding.

      While we believe these experiments are very informative, they will require a considerable amount of time due to our current circumstances. We consider them non-essential to the primary message of the paper, which focuses on neuronal morphological defects leading to functional alterations in daf-18/PTEN mutants.

      We will include these experiments in our future projects, also planning to extend this investigation to mutants with deficiencies in genes closely related to neurodevelopmental defects, such as neuroligin, neurexin, or shank-3, which have been implicated in synaptic architecture.

      (2) The author always referred to unc-47 promoter or unc-17 promoter, never specifying where those promoters are driving the expression (and in the Materials & Methods, no information on the corresponding sequence). Depending on the promoters they may not only be expressed in the motoneurons involved in locomotion (VA, VB, DA, DB, VD, and DD), but they could also be expressed in other neurons which could be of importance for the conclusions of the optogenetic assays but also the daf-18 expression in GABAergic neurons.

      We appreciate the reviewer's insight regarding the broader expression patterns of the unc-17 and unc-47 promoters in all cholinergic and GABAergic neurons, respectively. The strains expressing constructs with these promoters were obtained from the CGC or other labs and have been widely used in previous papers (Liewald et al, Nature Methods, https://www.nature.com/articles/nmeth.1252 (2008); Byrne, A. B. et al. Neuron 81, 561-573, doi:10.1016/j.neuron.2013.11.019 (2014).

      Regarding the optogenetic assays, the readout utilized (body length elongation or contraction) is primarily associated with the activity of cholinergic and GABAergic motor neurons and has been used in numerous studies to measure motor neuron functionality (Liewald et al, Nature Methods, https://www.nature.com/articles/nmeth.1252 (2008);Hwang, H. et al. Sci Rep 6, 19900, doi:10.1038/srep19900 (2016); Schultheis et al,  . J Neurophysiol 106, 817-827, doi:10.1152/jn.00578.2010 (2011); Koopman, M., Janssen, L. & Nollen, E. A. BMC Biol 19, 170, doi:10.1186/s12915-021-01085-2 (2021);). It has previously been established that the shortening observed after optogenetic activation of the unc-17 promoter, while active in various interneurons, depends on the activity of cholinergic motor neurons (Liewald et al., Nature Methods, https://www.nature.com/articles/nmeth.1252 (2008)). This was demonstrated by examining transgenic worms expressing ChR2-YFP from another cholinergic, motoneuronspecific but weaker promoter, Punc-4. They observed contraction and coiling upon illumination, albeit to a milder degree.

      In terms of GABAergic neurons, only 3 do not directly synapse to body wall muscles (AVL, PDV, and RIS) and are primarily involved in defecation. Of the 23 GABAergic motor neurons, 19 are Dtype motoneurons, while the remaining 4 innervate head muscles (Pereira et al, eLife 2015, https://doi.org/10.7554/eLife.12432). It is therefore expected that while there may be some contribution from these latter neurons to the elongation after optogenetic activation in animals containing punc-47::ChR2, the main contribution should be from the D-type neurons. Additionally, while there may be some influence on D-type neuron development due to daf-18 rescue in neurons like RME, DVB or AVL, the most direct explanation for the rescue is that daf-18 acts autonomously in D-type cells.  Additionally, we have pharmacological and behavioral assays that support the findings of optogenetics and enable us to reach final conclusions.

      (3) DD neurons are born during embryogenesis and newborn L1s have neurites even though less than at a later stage. If possible, it would be interesting to take a look at them to see if βHB has an effect or not. It will corroborate the hypothesis that βHB action is prevented by the impermeable eggshell on a system that can respond at a later stage. Moreover, using a specific DD, DA, and DB promoter, it would be possible to check if there is a difference in the morphological defects between embryonic and post-embryonic neurons.

      This is a very interesting point raised by the reviewer. We conducted experiments to analyze the morphology of GABAergic neurons in animals exposed to βHB only during the ex-utero embryonic development (in their laid egg state). We observed that this incubation was not sufficient to rescue the defects in GABAergic neurons (Supplementary Figure 7, revised version). As reported by other authors and discussed in our paper, the chitinous eggshell might act as an impermeable barrier to most drugs. However, we cannot rule out that incubation during this period is necessary but not sufficient to mitigate the defects. We have included these experiments in Supplementary Figure 7 and in the text (Page 13, lines 272-276)

      Additionally, we analyzed confocal images where, based on their position, we could identify and assess errors in DD (embryonic) and VD (Post-embryonic) neurons (Supplementary Figure 3, revised version). These experiments show that the effects are observed in both types of neurons, and we did not observe any differential alterations in neuronal morphology between the two types of neurons.

      Minor points

      (1)   Expression of daf-18/PTEN in muscle or hypodermis, could it ensure a proper development? It could give insights into the action mechanism of βHB.

      The reviewer's observation is indeed very intriguing. Previous studies from the Grishok lab (Kennedy et al, 2013) have demonstrated that the expression of daf-18 or daf-16 in extraneuronal tissues, specifically in the hypodermis, can rescue migratory defects in the serotoninergic neuron HSN in daf-18 or daf-16 null mutants of C. elegans. Clearly, this could also be an option for rescuing the morphological and functional defects of GABAergic motoneurons.

      However, the fact that the expression of daf-18 in GABAergic neurons rescues these defects strongly suggests an autonomous effect. In this regard, autonomous effects of DAF-18 or DAF-16 on neurodevelopmental defects have also been reported in interneurons in C. elegans (Christensen et al, 2011). This is included in the discussion (Page 15, lines 330-335)

      (2) Re-organise the introduction. The paragraph on ketogenic diets (lines 35-38) is not logically linked.

      Following reviewer´s suggestion we have reorganized the introduction and changed the order of explanation regarding the significance of ketogenic diets, linking it with their proven effectiveness in alleviating symptoms of diseases with E/I imbalance (Lines 23-60, revised version)

      (3) Incorporate titles in the result section to guide the reader.

      Done. Thank you

      (4) Systematically add PTEN or FOXO when daf-18 or daf-16 are mentioned (for example lines 69, 84, 85).

      Done. Thank you  

      (5) Strain lists: lines 646 to 653: some information is missing on the different transgenes used in this study (integrated (Is) or extrachromosomal (Ex) with their numbers).

      Thank you for bringing this to our attention. We have now included all the information regarding the different transgenes used in this study, including whether they are integrated (Is) or extrachromosomal (Ex) and their respective numbers. This information can be found in the revised version of the manuscript (Materials and Methods, C. elegans culture and maintenance section highlighted in yellow).

      Reviewer #3 (Recommendations For The Authors):

      In Figure 1, some experiments were done with the unc-25 control while others, such as the optogenetic experiments, were done without those controls.

      Thank you for pointing this out. In the optogenetic experiments, we waited for the worm to move forward for 5 seconds at a sustained speed before exposing it to blue light to standardize the experiment, as the response can vary if the animal is in reverse, going forward, or stationary. Due to the severity of the uncoordinated movement in unc-25 mutants, achieving this forward movement before exposure is very difficult. Additionally, this lack of coordination prevents these animals from performing the escape response tests, as they barely move. Therefore, we limited the use of this severe GABAergic-deficient control to pharmacological or post-prodding shortening experiments.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Recommendations For The Authors):

      Additional experiments to characterize what this novel cell type becomes in older animals would be ideal to strengthen the manuscript, but the authors should at least address this in the Discussion.

      The manuscript could be significantly improved if the authors included, for example, a timeline and/or cartoon contextualizing these cells relative to the formation of other CN neurons and their locations, perhaps as a summary figure at the end. Furthermore, the logic of each figure could be enhanced if the authors graphically show - again, perhaps with a schematic/cartoon - the question being tested for each figure. Furthermore, making the figure titles less descriptive and more explanatory would also help a reader follow the logic of the experiments.

      These are indeed valid and important questions for our research, and understanding the distribution, fate, and connectivity of this new cell type in the cerebellar nuclei postnatally is a focus of ongoing investigation in our lab. To address these questions, we are currently utilizing SNCA-GFP mice, a project led by a PhD student in my lab. While this work will be the subject of a full-length research paper, we do add a sentence to the paper concerning a recent report about the presence of SNCA neurons in the adult CN.  We have included a reference to the postnatal expression of SNCA (“In adult mice, postnatal expression of SNCA has been reported in medial CN neurons. PMID: 32639229”.) on page 8 of our manuscript (highlighted in yellow). In addition, we have included a cartoon as a summary figure (Fig. 9) illustrating the origin of cerebellar nuclei from the caudal and rostral ends in both Atoh1+/+ and Atoh1-/- mice. Thank you once again, we have revised and improved the Fig. titles accordingly.

      Reviewer #2 (Recommendations For The Authors):

      Figure 3:

      (1) If most SNCA+ cells are OTX2+ based on the IHCs, why are there so many SNCA+ Otx2- cells in the sort?

      In each group, 350,000 cells were sorted. Due to the relatively small population size of this subset of cerebellar nuclei neurons, the sorting procedure could not perfectly mirror our immunohistochemistry results. In each group, 350,000 cells were sorted. Due to the relatively small population size of this subset of cerebellar nuclei neurons, the sorting procedure could not perfectly mirror our immunohistochemistry results. However, it is noteworthy that a portion of sorted cells expressed SNCA or Otx2 while a smaller population co-expressed both Otx2 and SNCA in the cerebellar primordium.

      (2) Panel 3F: FACS graphs - the resolution of the figures is too poor on the PDF to read any of the text of these graphs. What are the axes?

      We thank the reviewer for this comment. In the revision a high resolution of the FACS graph has replaced the lower quality graph in panel 3F. This clearly identifies the axes and text for this panel.

      Figure 4:

      (1) Arrowheads are making a subset of + cerebellar cells -Why? Not defined in the legend.

      The population of cells indicated by the arrowheads are now defined in the legend. We have added the statement “Examples of Otx2 expressing cells are indicated by arrowheads in panels B, D, E, and F.”

      (2) The orientation of panels E and F is unclear - please provide low mag panel insets.

      An orientation marker (ie, (r-c and d-v; rostral caudal and dorsal ventral, respectively)) has been added to panel A, which applies to all panels, including panels E and F. Furthermore, the isthmus is noted with an “i” to provide further orientation.

      (3) G - and throughout the paper - whisker plots (not simple box plots) are required. Also, it is unclear from the methods how Otx2+ cells were counted - how many embryos/age? The description of 10 sections across 3 slides is incomplete. Are these cells distributed equally across the mediolateral axis of the anlage? Where are comparable M/L sections compared across ages? Is the increase in # across time because these cells are proliferative or are more migrating into the anlage?

      The plot has been replaced with whisker plots. A more detailed description of the Method used has been on page 15; “To assess the number of OTX2-positive cells, we conducted immunohistochemistry (IHC) labeling on slides containing serial sections from embryonic days 12, 13, 14, and 15 (n=3 at each timepoint). Under the microscope, we systematically counted OTX2-positive cells within the cerebellar primordium. This analysis encompassed a minimum of 10 sections, spread across at least 3 slides, ensuring comprehensive coverage of OTX2 expression along the mediolateral axis of the cerebellar primordium. For each slide, the counts of OTX2-positive cells from all sections were cumulatively calculated to determine the total number of positive cells per slide. Subsequently, statistical analysis was employed to compare the results obtained different developmental time points.”

      Figure 5:

      The use of confocal microscopy creates clear data re Otx2-GFP expression, but I cannot understand the origin of the panels. How do they relate to E/F and H/I? Different sections?

      In Figure 5, panels A-D display Otx2 expressing cells in the cerebellar primordium of Otx2-GFP transgenic mice, whereas panels E-J depict RNAscope fluorescence in situ hybridization (FISH) for the Otx2 probe in wild type mice. These represent complementary approaches to map Otx2+ cells in the developing cerebellum. This is made clear in a revised legend in Fig 5.

      Figure 6:

      The justification for the in-culture experiments, particularly the long (4 and 21DIV) times is unclear and needs to be strengthened or the in vitro data should be removed.

      Thank you for the respected reviewer’s comment. The E-H panels, show the co-expression of SNCA and p75NTR, highlight a significant role in the differentiation of specific neuronal populations during development. These findings validate our previous results (PMID: 31509576) and are consistent with the results of our current study. Therefore, we have chosen to keep these panels. However, in line with the suggestion from the reviewer, we have removed panels I-L from Fig. 6.

      Figure 7:

      SNCA expression in panels A and G is not specific nor is the Otx2 staining in panel B making the data in panels C and I uninterpretable and these panels need to be replaced. The Meis2 data however is much better and I agree this data shows that the dorsal RL-derived cells are deleted in Atoh1-/- while the SNCA+ cells remain. This is strong data supporting the dual origins of NTZ.

      Thank you for the points, Panel A and G have been replaced with high-resolution images. In addition, panels A-C have been carefully cropped to enhance focus on the NTZ area, to improve the quality and visibility of panels.  To enhance clarity, we have included a summary fig. 9 for clarification.

      Figure 8:

      The diI experiments are a key addition to this paper and clearly show the direct movement of some cells from the mesencephalon into the developing cerebellum, but data presentation must be considerably strengthened.

      (1) What is the inset in panel A? Low mag of embryo? Perhaps conversion of image to PDF degraded resolution - add a description in the legend. Arrowhead and arrow identities are reversed in the legend. The arrow points to the isthmus.

      Thank you for the comment, for clarification we have included information in the Fig. legend (highlighted in yellow). In addition, the issues with the arrows have been addressed and corrected.

      (2) Panels B and C are also shown in Supplementary Figure 2 with arrows indicating rostral and caudal movement - these arrows need to be added here. There is no need to replicate these same panels in the supplement.

      Thanks, arrows have been added in panels B, C of Fig. 8.

      (3) The text states that "almost all DiI cells migrated caudally into the cerebellum" and refers to Figure 8E and Suppementl 3 but there is no evidence/support shown for this, just a few + cells in 8E and some very difficult-to-see positive cells in sections in Supplement E-F. Given the importance of this data, I am surprised that the authors chose bright field/phase microscopy to show this. This section's data is not convincing data at all. I find it very difficult to see specific staining. These panels must be improved. This is key data for paper conclusions.

      These are valid points, and we acknowledge that this experiment alone may not provide conclusive evidence regarding the subset of CN originating from mesencephalon. At this stage of the study, we do not claim definitively that the SNCA/OTX2/MEIS2 positive cells originate from the mesencephalon. As stated in our manuscript, "In conclusion, our study indicates that the SNCA+/ OTX2+/ MEIS2+/ p75NTR+/ LMX1A- rostroventral subset of CN neurons do not originate from the well-known distinct germinative zones of the cerebellar primordium. Instead, our findings suggest the existence of a previously unidentified extrinsic germinal zone, potentially the mesencephalon."  We have also discussed embryonic culture approaches in the manuscript, which could involve the use of other agents such as plasmid/viral vectors, hinting at the possibility of origin from the mesencephalon. While tracing the origin from the mesencephalon in vivo and in vitro is promising and on our to-do list, the data will not be available for this manuscript. To prevent confusion, we have eliminated redundant panels of Fig. 8 with Supplementary Fig. 2 and 3. However, if the reviewer deems it necessary to remove these panels, we are prepared to do so.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review):

      […]

      (1) The authors claim that the negative frequency dependence that maintains polymorphism in their model results from a non-linear relationship between the display trait and sexual success [...] Maybe I missed something, but the authors do not provide support for their claim about the negative frequency-dependence of sexual selection in their simulations. To do so they could (1) extract the relationship between the relative mating success of the two male types from the simulations and (2) demonstrate that polymorphism is not maintained if the relationship between male display trait and mating success is linear.

      We believe that there is a confusion of terminology here. We agree that for the two alleles at a locus impacting male display in our model, the allele conferring inferior display quality will have a fitness that increases as its frequency increases, so this allele displays positive frequency dependent fitness. And, the alternate, display-favoring allele at the locus does display negative frequency dependence. Our use of the terminology ‘negative frequency dependence’ was meant to refer to the negative dependence of the fitness of the display-favoring allele with respect to its own frequency. However, a significant body of literature instead discusses models in which both an allele and its alternate(s) are beneficial when at low frequency and deleterious when at high frequency under the same selective challenge, entailing negative frequency dependence of fitness for all alleles involved. This benefit-when-rare model of a single trait is often described simply as negative frequency dependence, and generates balancing selection at the locus, but is not the model we are presenting here, and does not encompass all models involving negative frequency dependent fitness. This lexical expectation may make the interpretation of our work more difficult, and we have amended the manuscript to make our model clearer (lines 227-231). In this model, we have a negative frequency dependence for the fitness of the display-favoring allele in mate competition, but the net selective disadvantage of this allele at high frequency is due to a cost in another, pleiotropic, fitness challenge: the constant survival effect. So, the alleles are under balancing selection where alternate alleles are favored by selection when rare, but not due solely to selection during mate competition. Instead, our model relies on pleiotropy for an emergent form of frequency-dependent balancing selection (in the sense that each allele is predicted to be beneficial on balance when rare).

      In the reviewer’s model of the success of two alleles at one locus, the ratio of success is vaguely linear with allele frequency for n=3, though it starts quite convex and has an inflection point between convex and concave segments (for the disfavored allele) at p≈0.532. This is visualized easily by plotting the function and its derivatives in Wolfram-Alpha. For n>=4, the fitness function with respect to the display-favoring/disfavoring allele becomes increasingly concave/convex respectively, and this specific nonlinearity is needed to act along with the antagonistic pleiotropy to maintain balancing selection, rather than being maintained by a model that favors any rare allele on the basis of its rarity in some manner. In an attempt to make the importance of the encounter number parameter clearer, we’ve generated new panels for Figure S1 which simulate encounter numbers 2, 3, and 4, and we have updated corresponding text and figure references in lines 335-338.

      For (1-2), it is not clear how to modify the simulation such that the relationship between the trait value and mating success can be perfectly linear - either linear with respect to allele frequency in a one locus model or linear with respect to trait value at a specific population composition, without removing the simulation of mate competition altogether. While it may be of interest to explore a more comprehensive range of biological trade-offs in future studies, we are not able to meaningfully do so within the context of the present manuscript.

      (2) The authors only explore versions of the model where the survival costs are paid by females or by both sexes. We do not know if polymorphism would be maintained or not if the survival cost only affected males, and thus if sexual antagonism is crucial.

      We now present simulations with male costs only as added panels to Figure S1 and mention these results in the main text (lines 334-335). Maintenance of the polymorphism is significantly reduced or completely absent in such simulations.

      (3) The authors assume no cost to aneuploidy, with no justification. Biologically, investment in aneuploid eggs would not be recoverable by Drosophila females and thus would potentially act against inversions when they are rare.

      We did offer some discussion and justification of our decision to model no inherent fitness of the inversion mutation itself, specifically aneuploidy, in lines 36-39 and 78-80 of the original reviewed preprint. Previous research suggests that D. melanogaster females may not actually invest in aneuploid eggs generated from crossover within paracentric inversions. While surprising, and potentially limited to a subset of clades, many ‘r-selected’ taxa or those in which maternal investment is spread out over time may have some degree of reproductive compensation for non-viable offspring, which can reduce the costs of generating aneuploids significantly (for example, t-haplotypes in mice). We have added this example and citation to lines 34ff in the current draft.

      (4) The authors appear to define balanced polymorphism as a situation in which the average allele frequency from multiple simulation runs is intermediate between zero and one (e.g., Figure 3). However, a situation where 50% of simulation runs end up with the fixation of allele A and the rest with the fixation of allele B (average frequency of 0.5) is not a balanced polymorphism. The conditions for balanced polymorphism require that selection favors either variant when it is rare.

      We originally chose mean final frequency for presenting the single locus simulations based on the ease of generating a visual plot that included information on fixation vs loss and equilibrium frequency. Figure 3 and related supplemental images have been changed to now also represent the proportion of simulations retaining polymorphism at the locus in the final generation.

      (5) Possibly the most striking result of the experiment is the fact that for 14 out of 16 combinations of inversion x maternal background, the changes in allele frequencies between embryo and adult appear greater in magnitude in females than in males irrespective of the direction of change, being the same in the remaining two combinations. The authors interpret this as consistent with sexually antagonistic pleiotropy in the case of In(3L)Ok and In(3R)K. The frequencies of adult inversion frequencies were, however, measured at the age of 2 months, at which point 80% of flies had died. For all we know, this may have been 90% of females and 70% of males that died at this point. If so, it might well be that the effects of inversion on longevity do not systematically differ between the ages and the difference in Figure 9B results from the fact that the sample includes 30% longest-lived males and 10% longest-lived females.

      This critique deserves some consideration. The aging adults were separated by sex during aging, but while we recorded the number of survivors, we did not record the numbers of eclosed adults and their sexes initially collected out of an interest in maintaining high throughput collection. We therefore cannot directly calculate the associated survival proportions, but we can estimate them. We collected 1960 females and 3156 males, and we can very roughly estimate survival if we assume that equal numbers of each sex eclosed, and that the survivors represent 20% of the original population. That gives 12790 individuals per sex, or 84.7% female mortality and 75.3% male mortality.

      So, we have added a qualification discussing the possibility of stronger selection on females and its influence on observed sex-specific frequency changes, on lines 602-605.

      (6) Irrespective of the above problem, survival until the age of 2 months is arguably irrelevant from the viewpoint of fitness consequences and thus maintenance of inversion polymorphism in nature. It would seem that trade-offs in egg-to-adult survival (as assumed in the model), female fecundity, and possibly traits such as females resistance to male harm would be much more relevant to the maintenance of inversion polymorphisms.

      Adult Drosophila will continue to reproduce in good conditions until mortality, and the estimated age of a mean reproductive event for a Drosophila melanogaster individual is 24 days (Pool 2015), and likewise for D. simulans (Turelli and Hoffman 1995). Given that reproduction is centered around 24 days, we expect sampling at 2 months of age to still be relevant to fitness. In seasonally varying climates, either temperate or with long dry season, survival through challenging conditions is expected to require several months. In many such cases, females are in reproductive diapause, and so longevity is the main selective pressure. See lines 931-936 in the revised manuscript.

      As we agreed above, it would of interest to investigate a wider range of trade-offs in future studies. We focused here on the balanced between survival and male reproductive success because the latter trait generates negative frequency dependence for display-favoring alleles and a disproportionate skew towards higher quality competitors, whereas many other fitness-relevant traits lack that property.

      (7) The experiment is rather minimalistic in size, with four cages in total; given that each cage contains a different female strain, it essentially means N=1. The lack of replication makes statements like " In(2L)t and In(2R)NS each showed elevated survival with all maternal strains except ZI418N" (l. 493) unsubstantiated because the claimed special effect of ZI418N is based on a single cage subject to genetic drift and sampling error. The same applies to statements on inversion x female background interac7on (e.g., l. 550), as this is inseparable from residual variation. It is fortunate that the most interesting effects appear largely consistent across the cages/female backgrounds. Still, I am wondering why more replicates had not been included.

      Our experimental approach might be described as “diversity replication”. Essentially, the four maternal genetic backgrounds are serving dual purposes – both to assess experimental consistency and to ensure that our conclusions are not solely driven by a single non-representative genotype (which in so many published studies, can not be ruled out). It would indeed be interesting if we could have quadrupled the size of our experiment by having four replicates per maternal background. However, we suspect the reviewer may not recognize the substantial effort involved in our four existing experiments. Each of these involved collecting 500+ virgin females, hand-picking thousands of embryos during the duration of egg-laying, and repeatedly transferring offspring to maintain conditions during aging, such that cages had to be staggered by more than a month. These four cages took a year of benchwork just to collect frozen samples, before any preparation and quality control of the associated amplicon libraries for sequencing. Adding a further multiplier would take it well beyond the scope of a single PhD thesis.  Fortunately, we were able to obtain the key results of interest without that additional effort, even if clearer insights into the role of maternal background would also be of strong interest.

      We do agree that no firm conclusions about maternal background can be reached without further replication, and so we have qualified or removed relevant statements accordingly (lines 568ff, 620-622).

      Reviewer #1 (Recommendations For The Authors):

      The description of the model is confusing and incomplete, e.g., the values of several parameters used to obtain the numerical results are not given. It is first stated (l. 223) that the model is haploid, but text elsewhere talks about homozygotes and heterozygotes. If the model is diploid (this in itself is not clear), what is assumed about dominance?

      We are not presenting results for a mathematical model estimated numerically. We have now clarified our transition from a conceptual depiction of our model, in which we use haploid representations for simplified presentation, to our forward population genetic simulations, which are entirely diploid. More broadly, we have improved our communication of the assumptions and parameters used in our simulations. The scenarios we investigate involve purely additive trait effects within and between loci (except that survival probabilities are multiplicative to avoid negative values). We think that considering other dominance scenarios would be a worthy subject for a follow-up study, whereas the present manuscript is already covering a great deal of ground.   

      Similarly, it is hard to understand the design (l.442ff). I was confused as to whether a population was set up for each inversion or for all of them and what the unit or replication was. I found the description in Methods (l. 763-771) much clearer and only slightly longer; I suggest the authors transfer it to the Results. Also, Figure 8 should contain the entire crossing scheme; the current version is misleading in that it implies males with only two genotypes.

      All four tested inversions were segregating within the same karyotypically diverse population of males, and were assayed from the same experiments. We have attempted to improve the relevant description. For Figure 8, we had trouble conceiving a graphic update that contained a more complete cross scheme without seeming much more confused and cluttered. We have tried to clarify in the relevant text and the figure caption instead.

      There are a number of small issues that should be addressed:

      - No epistasis for viability assumed - what would be the consequence?

      We explored a model in which we intentionally included no terms for epistatic effects on phenotype. All epistasis with regard to fitness is emergent from competition between individuals with phenotypes composed of non-epistatic, non-dominant genetic effects. So, the simplest model of antagonism would have no epistasis for viability whatsoever. One could explore a model that has emergent viability epistasis in a similar way, by implementing stabilizing selection on a quantitative trait with a gaussian or similar non-linear phenotype-to-fitness map, but that might be better served as a topic for a future study. We have, however, tried to make this intent clearer in the text.

      l. 750 implies that aneuploidy generated by the inversion has no cost (aneuploid games are resampled)

      Yes, as addressed in public review item (3). Alternately see lines 34ff, 293, 369, 392 for in-text edits.

      l. 24-25: unclear; is this to mean that there is haplotype x sex interaction for survival?

      l. 25: success in what? (I assume this will be explained in the paper, but the abstract should stand on its own).

      l. 193-4: "producing among most competitive males": something missing or a word too much?? Figure 1B,C: a tiny detail, but the plots would be more intuitive if the blue (average) bars were ager (i.e., to the right) of the male and female ones, given that the average is derived from the two sex-specific values.

      Each of the above have been edited or implemented as suggested

      l. 205. It is convex function, but I do not understand what the authors mean by "convex distribution".

      Hopefully the updated text is clearer: “yielding a distribution of male reproductive output that follows a relatively convex trend”.

      l. 223ff: some references to Fig 1 panels in this paragraph seem off by one letter (i.e., A should be B, etc.).

      l. 231 "fitness...are equally fit": rephrase 

      l. 260: maybe "thrown out" is not the most fortunate term, maybe "eliminated" would be better?

      Each of the above have been edited or implemented as suggested

      Figure 3: I do not understand the meaning of "additive" and "multiplicative" in the case of a single locus haploid model

      All presented simulations are diploid, and these refer to the interactions between the two alleles at the locus. Hopefully the language is overall clearer in this draft.

      l. 274: "Mutation of new nucleotide" meaning what? Or is it mutation _to_ a new nucleotide?

      Hopefully the revised text is clearer.

      Figure 5. The right panel of figure 5A implies that, with the inversion, the population evolves to an extreme display trait that is so costly that it fills 95% of all individuals (or of all females?

      What is assumed about this here?). Apart from the biological realism of this result, what does it say about the accumulation of polymorphism and maintenance of the inversion? The graphs in fig 5B do plot a divergence between haplotypes, but it is not clear how they relate to those in panel A - the parameter values used to generate these plots are again not listed. Furthermore, from the viewpoint of the polymorphism, it would be good to report the frequencies at the steady-state.

      We have now clarified the figure description, including the parameter values used. The distribution of frequencies at the end of the simulation is represented in figure 6. Given that we set up the simulation with assumptions that are otherwise common to population models, what biological process would prevent this extreme? Why isn’t this extreme observed in natural populations? One possible explanation is that they become sex chromosomes, with increasing likelihood as the cost increases. Or other compensatory changes may occur that we don’t simulate, like regulatory evolution giving a complementary phenotype. Maybe genetic constraints in natural populations prevent the mutation of the kind of pleiotropic mutations that drive this dynamic. The populations still survive, though they are parameterized by relative fitness. What would an absolute fitness population function be? Would it go extinct or not? It would be of interest to explore a wider range of models, but it is the purpose of this paper to establish that this is a viable model for the maintenance of sexually antagonistic polymorphism and association with inversions. We have added a paragraph motivated by this comment to the Discussion starting on line 765.

      l. 401-2: Z-like, W-like : please specify you are talking about patterns resembling sex chromosomes. 

      l. 738: "population calculates"?

      l. 743-4 and 746-7: is this the same thing said twice, or are there two components of noise?  l. 357: there is no figure 5C.

      Each of the above have been addressed with text edits.

      L. 473-5: Yes, the offspring did not contain inversion homozygotes, but the sire pool did, didn't it? So homozygous inversions may have affected male reproductive success. Anyway, most of this paragraph (from line 473) seems to belong in Discussion rather than Results.

      We have revised this sentence to focus on offspring survival. 

      We can understand the reviewer’s suggestion about Results vs. Discussion text. While this can often be a challenging balance, we find that papers are often clearer if some initial interpretation is offered within the Results text. However, we moved the portion of this paragraph relating our findings to the published literature to the Discussion.

      l. 516: " In(3L)Ok favored male survival": this is misleading/confusing given the data, " In(3L)Ok reduced female survival more strongly than male survival..."

      Hopefully the phrasing is clearer now.

      l. 663ff: I did not have an impression that this section added anything new and could safely be cut.

      We have done some editing to make this more concise and emphasize what we think is essential, but we believe that the model of an autosomal, sexually antagonistic inversion differentiating before contributing to the origin of a sex chromosome is novel and interesting. And, that this additional emphasis is worthwhile to encourage thought and consideration of this idea in future research and among interested researchers.

      l. 751: "flat probability per locus": do the authors mean a constant probability?

      Edited.

      Reviewer #2 (Public Review):

      The manuscript lacks clarity of writing. It is impossible to fully grasp what the authors did in this study and how they reached their conclusions. Therefore, I will highlight some cases that I found problematic.

      Hopefully the revised manuscript improves writing clarity. 

      Although this is an interesting idea, it clearly cannot explain the apparent influence of seasonal and clinal variation on inversion frequencies.

      We do not believe that our model predicts a non-existence of temporal and spatial dependence of the fitness of inverted haplotypes, nor do we seek to identify the manner in which seasonal and clinal differences affect fitness of inverted haplotypes. Rather, we argued that the influence of seasonal and clinal selection on inversions does not on its own predict the observed maintenance of inversions at low to intermediate frequencies across such a diverse geographic range, along with the higher frequencies of many derived inversions in more ancestral environments. 

      We might imagine that trade-offs between life history traits such as mate competition and survival should be universal across the range of an organism. But in practice, the fitness benefits and costs of a pleiotropic variant (or haplotype) may be heavily dependent on the environment. A harsh environment such as a temperate winter may both reduce the number of females that a male encounters (decreasing the benefit of display-enhancing variants) and also increase the likelihood that survival-costly variants lead to mortality (thus increasing their survival penalty). In light of such dynamics, our model would predict that equilibrium inversion frequencies should be spatially and temporally variable, in agreement with a number of empirical observations regarding D. melanogaster inversions.

      We have edited the introduction to emphasize that inversion frequencies vary temporally as well as seasonally, on lines 144ff. We also note relevant discussion of the potential interplay between the environment and trade-offs such as those we investigate, on lines 153-155.

      The simulations are highly specific and make very strong assumptions, which are not well-justified.

      We respond to all specific concerns expressed in the Recommendations For The Authors section below. We also note that we have made further clarifications throughout the text regarding the assumptions made in our analysis and their justification.  

      Reviewer #2 (Recommendations For The Authors):

      I think that the manuscript would greatly benefit from a major rewrite and probably also a reanalysis of the empirical data.

      In particular, a genome-wide analysis of differences in SNP frequencies between sexes and developmental stages would help the reader to appreciate that inversions are special.

      [moved up within this section for clarity] We are lacking a genomic null model-how often do the authors see similar allele frequency differences when looking at the entire genome? This could be easily done with whole genome Pool-Seq and would tell us whether inversions are really different from the genomic background. I think that this information would be essential given the many uncertainties about the statistical tests performed. 

      We expect that autosome-wide SNP frequencies will be heavily influenced by the frequencies of inversions, which occur on all four major autosomal chromosome arms. These inversions often show moderate disequilibrium with distant variants (e.g. Corbett-Detig & Hartl 2012).

      Furthermore, the limited number of haplotypes present, given that the paternal population was founded from 10 inbred lines, would further enhance associations between inversions and distant variants. Therefore, we do not expect that whole-genome Pool-Seq data would provide an appropriate empirical null distribution for frequency changes. Instead, we have generated appropriate null predictions by accounting for both sampling effects and experimental variance, and we have aimed to make this methodology clearer in the current draft. 

      Some basic questions:

      why start at a frequency of 50% (line 287)?

      Isn't it obvious that in this scenario strong alleles with sexually antagonistic effects can survive?

      The initial goal of the associated Figure 4 was not to show that a strongly antagonistic variant could persist. Instead, we wanted to test the linkage conditions in which a second, relatively weaker antagonistic variant survived – which did not occur in the absence of strong linkage. 

      We have now added simulations with relatively lower initial frequencies, in which the weaker variant and the inversion both start at 0.05 frequency, while the stronger variant is still initialized at 0.5 to reflect the initial presence of one balanced locus with a strongly antagonistic variant. Here, the weaker antagonistic variant is still usually maintained when it is close to the stronger variant, and while the inversion-mediated maintenance of the weaker variant at greater distance from the stronger variant because less frequent than the original investigated case, it still happens often enough to hypothetically allow for such outcomes over evolutionary time-scales.

      Still, we should also emphasize that the goals of this proof-of-concept analysis are to establish and convey some basic elements of our model. Subsequently, analyses such as those presented in Figures 5 and 6 provide clearer evidence that the hypothesized dynamics of inversions facilitating the accumulation of sexual antagonism actually occur in our simulations.

      The experiments seem to be conducted in replicate (which is of course essential), but I could not find a clear statement of how many replicates were done for each maternal line cross.

      How did the authors arrive at 16 binomial trials (line 473)? 4 inversions, 4 maternal genotypes?

      How were replicates dealt with?

      In Figure 9, it would be important to visualize the variation among replicates.

      Unfortunately, we did not have the bandwidth to perform replicates of each maternal line. Instead, we use four maternal backgrounds to simultaneously establish consistency across independent experiments and genetic backgrounds (see our response to Reviewer 1, point 7). We’ve edited the draft to make this clearer and more clearly delineate what is supported and not supported by our data. Replicate variation for the control replicates of the extraction and sequencing process, and the exact read counts of the experiment, are available in Supplemental Tables S5, S6, and S7.

      The statistical analysis of trade-off is not clear: which null model was tested? No frequency change? In my opinion, two significances are needed: a significant difference between parental and embryo and then embryo and adult offspring. The issue with this is, however, that the embryo data are used twice and an error in estimating the frequency of the embryos could be easily mistaken as antagonistic selection.

      Hopefully the description of our null model is clearer in the text, now starting around line 967 in the Methods. We are aware of the positive dependence when performing tests comparing the paternal to embryo and then embryo to offspring frequencies, and this is accounted for by our analysis strategy - see lines 1009-1012.

      It was not clear how the authors adjusted their chi-squared test expectations. Were they reinventing the wheel? There is an improved version of the chi-squared test, which accounts for sampling variation.

      We did not actually perform chi-square tests. Instead, we used the chi statistic from the chi-squared test as a quantitative summary of the differences in read counts between samples. We compared an observed value of chi to values for this statistic obtained from simulated replicates of the experiment. Sampling from this simulation generated our ‘expected’ distribution of read counts, sampled to match sources of variance introduced in the experimental procedure, but without any effect of natural selection, per lines 825ff in the original submission. Hence, we are approximating the likelihood of observing an empirical chi statistic by generating random draws from a model of the experiment and comparing values calculated from each draw to the experimental value: a Monte Carlo method of approximating a p-value for our data. We have attempted to make the structure of these simulations and their use as a null-model clearer in this draft.

      It is not sufficiently motivated why the authors model differences in the extraction procedure with a binomial distribution.

      Adding a source of variance here seemed necessary as running control sequencing replicates revealed that there was residual variance not fully recapitulated by sample-size-dependent resampling. Given that we were still sampling a number of draws from a binomial outcome (the read being from the inverted or standard arrangement), a binomial distribution seemed a reasonable model, and we fit the level of this additional noise source to an experiment-wide constant, read-count or genome-count independent parameter that best fit the variance observed in the controls (lines 830ff in the original draft). Clarification is made in this manuscript draft, lines 979-989.

      How many reads were obtained from each amplicon? It looks like the authors tried to mimic differences between technical replicates by a binomial distribution, which matches the noise for a given sample size, but this depends on the sequence coverage of the technical replicates.

      We provide read counts in Supplemental Tables S6 and S7. The relevant paragraph in the methods has been edited for clarity, lines 972ff. Accounting for sampling differences between replicates used a hypergeometric distribution for paternal samples to account for paternal mortality before collection, and the rest were resampled with a binomial distribution. There were two additional binomial samplings, to account for resampling the read counts and to capture further residual variance in the library prep that did not seem to depend on either allele or read counts.

      It would be good to see an estimate for the strength of selection: 10% difference in a single generation appears rather high to me.

      Estimates of selection strength based on solving for a Wright-Fisher selection coefficient for each tested comparison can now be found in Table S8, mentioned in text on lines 589-590. The mean magnitude of selection coefficients for all paternal to embryo comparisons was 0.322, and for embryo to all adult offspring it was 0.648. For In(3L)Ok the mean selection coefficients were 0.479 and -0.53, and for In(3R)K they were -0.189 and 1.28, respectively. Some are of quite large magnitude, but we emphasize that the coefficients for embryo to adult are based on survival to old age, rather than developmental viability. That factor, in addition to the laboratory environment, makes these estimates distinct from selection coefficients that might be experienced in natural populations.

      Reviewer #3 (Public Review):

      Strengths:

      (1) …the authors developed and used a new simulator (although it was not 100% clear as to why SLiM could not have been used as SLiM has been used to study inversions).

      Before SLiM 3.7 or so (and including when we did the bulk of our simulation work), we do not think it would have been feasible to use SLiM to model the mutation of inversions with random breakpoints and recombination between without altering the SLiM internals. Separately, needing to script custom selection, mutation, and recombination functions in Eidos would have slowed SLiM down significantly. Given our greater familiarity with python and numpy, and the ability to implement a similar efficiency simulator more quickly than through learning C++ and Eidos, we chose to write our own.

      It should be a fair bit easier to implement comparable simulations in SLiM now, but it will still require scripting custom mutation, selection, and recombination functions and would still result in a similarly slow runtime. The current script recipe recommended by SLiM for simulating inversions uses constants to specify the breakpoints of a single inversion, without the ability to draw multiple inversions from a mutational distribution, or model recombination between more complicated karyotypes. Hence, our simulator still seems to be a more versatile and functional option for the purposes of this study.

      Weaknesses:

      [Comments 1 through 4 on Weaknesses included numerous citation suggestions, and some discussion recommendations as well. In our revised manuscript, we have substantially implemented these suggestions. In particular, we have deepened our introduction of mechanisms of balancing selection and prior work on inversion polymorphism, integrating many

      suggested references. While especially helpful, these suggestions are too extensive to completely quote and respond to in this already-copious document. Therefore, we focus our response on two select topics from these comments, and then proceed to comment 5 thereafter.]

      (2) The general reduction principle and inversion polymorphism. In Section 1.2., the authors state that "there has not been a proposed mechanism whereby alleles at multiple linked loci would directly benefit from linkage and thereby maintain an associated inversion polymorphism under indirect selection." Perhaps I am misunderstanding something, but in my reading, this statement is factually incorrect. In fact, the simplest version of Dobzhansky's epistatic coadaptation model

      (see Charlesworth 1974; also see Charlesworth and Charlesworth 1973 and discussion in Charlesworth & Flatt 2021; Berdan et al. 2023) seems to be an example of exactly what the authors seem to have in mind here: two loci experiencing overdominance, with the double heterozygote possessing the highest fitness (i.,e., 2 loci under epistatic selection, inducing some degree of LD between these loci), with subsequent capture by an inversion; in such a situation, a new inversion might capture a haplotype that is present in excess of random expectation (and which is thus filer than average)…

      We agree that the quoted statement could be misleading and have rewritten it. We intended to point out that we are presenting a model in which all loci contribute additively (with respect to display) or multiplicatively (with respect to survival probability), without any dominance relationships or genetic interaction terms. And yet, the model generates epistatic balancing selection in a panmictic population under a constant environment. This represents a novel mechanism by which (the life-history characteristics of) a population would generate epistatic balancing selection as an emergent property, instead of assuming a priori that there is some balancing mechanism and representing frequency dependence, dominance effects, or epistatic interactions directly using model parameters. We have therefore refined the scope of the statement in question (lines 155-158). 

      (4) Hearn et al. 2022 on Littorina saxatilis snails. 

      A good reference. There is considerable work on ecotype-associated inversions in L. saxatalis, but we previously cut some discussion of this and of other populations with high gene flow but identifiable spatial structure for inversion-associated phenotypes (e.g. butterfly mimicry polymorphisms, Mimulus, etc.). Due to the spatially discrete environmental preferences and sampled ranges of the inversions in these populations, we considered these examples to be somewhat distinct from explaining inversion polymorphism in a potentially homogenous and panmictic environment. 

      (4) cont. A very interesting paper that may be worth discussing is Connallon & Chenoweth (2019) about dominance reversals of antagonistically selected alleles (even though C&C do not discuss inversions): AP alleles (with dominance reversals) affecting two or more life-history traits provide one example of such antagonistically selected alleles (also see Rose 1982, 1985; Curtsinger et al. 1994) and sexually antagonistically selected alleles provide another. The two are of course not necessarily mutually exclusive, thus making a conceptual connection to what the authors model here.

      We had removed a previously drafted discussion of dominance reversal for brevity’s sake, but this topic is once again represented in the updated draft of the manuscript with a short reference in the introduction, lines 76-80. We also mention ‘segregation lift’ (Wittmann et al. 2017) involving a similar reversal of dominance for fitness between temporally fluctuating conditions, as opposed to between sexes or life history stages. 

      (5) The model. In general, the description of the model and of the simulation results was somewhat hard to follow and vague. There are several aspects that could be improved:  [5](1) it would help the reader if the terminology and distinction of inverted vs. standard arrangements and of the three karyotypes would be used throughout, wherever appropriate.

      We have attempted to do so, using the suggested heterokaryotypic/homokaryotypic terminology.

      [5](2) The mention of haploid populations/situations and haploid loci (e.g., legend to Figure 1) is somewhat confusing: the mechanism modelled here, of course, requires suppressed recombination in the inversion/standard heterokaryotype; and thus, while it may make sense to speak of haplotypes, we're dealing with an inherently diploid situation. 

      While eukaryotes with haploid-dominant life history may still experience similar dynamics, we do expect that most male display competition is in diploid animals, and we are only simulating diploid fitnesses and experimenting with diploid Drosophila. We have tried to minimize the discussion of haploids in this draft.

      [5](3) The authors have a situation in mind where the 2 karyotypes (INV vs. STD) in the heterokaryotype carry distinct sets of loci in LD with each other, with one karyotype/haplotype carrying antagonistic variants favoring high male display success and with the other karyotype/haplotype carrying non-antagonistic alternative alleles at these loci and which favor survival. Thus, at each of the linked loci, we have antagonistic alleles and non-antagonistic alleles - however, the authors don't mention or discuss the degree of dominance of these alleles. The degree of dominance of the alleles could be an important consideration, and I found it curious that this was not mentioned (or, for that matter, examined). 

      In this study, our goal was to show that the investigated model could produce balanced and increasing antagonism without the need to invoke dominance. We think there would be a strong case for a follow-up study that more investigates how dominance and other variables impact the parameter space of balanced antagonism, but this goal is beyond our capacity to pursue in this initial study. We’ve added several lines clarifying the absence of dominance from our investigated models, and pointing out that dominance could modulate the predictions of these models (lines 211-213, 278-282).  

      [5](4) In many cases, the authors do not provide sufficient detail (in the main text and the main figures) about which parameter values they used for simulations; the same is true for the Materials & Methods section that describes the simulations. Conversely, when the text does mention specific values (e.g., 20N generations, 0.22-0.25M, etc.), little or no clear context or justification is being provided. 

      We have sought to clarify in this draft that 20N was chosen as an ample time frame to establish equilibrium levels and frequencies of genetic variation under neutrality. We present a time sequence in Figure 5, and these results indicate that that antagonism has stabilized in models without inversions or with higher recombination rates, whereas its rate of increase has slowed in a model with inversions and lower levels of crossing over. 

      The inversion breakpoints and the position of the locus with stronger antagonistic effects in Figure 4 were chosen arbitrarily for this simple proof of concept demonstration, with the intent that this locus was close to one breakpoint. Hopefully these and other parameters are clearer in the revised manuscript.

      [5](5) The authors sometimes refer to "inversion mutation(s)" - the meaning of this terminology is rather ambiguous.

      Edited, hopefully the wording is clearer now. The quoted phrase had uniformly referred to the origin of new inversions by a mutagenic process. 

      (6) Throughout the manuscript, especially in the description and the discussion of the model and simulations, a clearer conceptual distinction between initial "capture" and subsequent accumulation / "gain" of variants by an inversion should be made. This distinction is important in terms of understanding the initial establishment of an inversion polymorphism and its subsequent short- as well as long-term fate. For example, it is clear from the model/simulations that an inversion accumulates (sexually) antagonistic variants over time - but barely anything is said about the initial capture of such loci by a new inversion.

      We do not have a good method of assessing a transition between these two phases for the simulations in which both antagonistic alleles and inversions arise stochastically by a mutagenic process. However, we have tried to be clearer on the distinction in this draft: we have included simulations in Figure 4 with variants starting at lower frequencies, and we have tried to better contextualize the temporal trajectories in Figure 5 as (in part) modeling the accumulation of variants after such an origin.

      Reviewer #3 (Recommendations For The Authors):

      - In general: the whole paper is quite long, and I felt that many parts could be written more clearly and succinctly - the whole manuscript would benefit from shortening, polishing, and making the wording maximally precise. Especially the Introduction (> 8 pages) and Discussion (7.5 pages) sections are quite long, and the description of the model and model results was quite hard to follow.

      We have attempted to condense some portions of the manuscript, but inevitably added to others based on important reviewer suggestions. Regarding the length Introduction and Discussion, we are covering a lot of intellectual territory in this study, and we aim to make it accessible to readers with less prior familiarity. At this point, we have well over 100 citations – far more than a typical primary research paper – in part thanks to the relevant sources provided by this reviewer. We are therefore optimistic that our text will provide a valuable reference point for future studies. We have also made significant efforts to clarify the Results and Methods text in this draft without notably expanding these sections.

      - In general: the conceptual parts of the paper (introduction, discussion) could be better connected to previous work - this concerns e.g. the theoretical mechanisms of balancing selection that might be involved in maintaining inversions; the general, theoretical role of antagonistic pleiotropy (AP) and trade-offs in maintaining polymorphisms; previously made empirical connections between inversions and AP/trade-offs; previously made empirical connections between inversions and sexual antagonism.

      In the revised manuscript, we have improved the connection of these topics to prior work.

      - L3: "accumulate". A clearer distinction could be made, throughout, between initial capture of alleles/haplotypes by an inversion vs. subsequent gain.

      Please see point 6 in the response to the Public Review, above.

      - L29: I basically agree about the enigma, however, there are quite many empirical examples in D. melanogaster / D. pseudoobscura and other species where we do know something about the nature of selection involved, e.g., cases of NFDS, spatially and temporally varying selection, fitness trade-offs, etc.

      At least for our focal species, we have emphasized that geographic (and now temporal) associations have been found for some inversions. For the sake of length and focus, we probably should not go down the road of documenting each phenotypic association that has been reported for these inversions, or say too much about specific inversions found in other species. As indicated in our response to reviewer 2, some previously documented inversion-associated trade-offs may be compatible with the model presented here. However, we did locate and add to our Discussion one report of frequency-dependent selection on a D. melanogaster inversion (Nassar et al. 1973).

      - L43: it is actually rather unlikely, though not impossible, that new inversions are ever completely neutral (see the review by Berdan et al. 2023).

      This line was intended to convey that, in line with Said et al. 2018’s results, the structural alterations involved in common segregating inversions are not expected to contribute significantly to the phenotype and fitness (as indicated by lack of strong regulatory effects), and that their phenotypic consequences are instead due to linked variation. We have rewritten this passage to better communicate this point, now lines 44-52. Interpreting Section 2 and Figure 1 of Berdan et al. 2023, the linked variation may be what is in mind when saying that inversions are almost never neutral. We have also added a line referencing the expected linked variation of a new inversion (lines 49-52).

      - L51-73: I felt this overview should be more comprehensive. The model by Kirkpatrick & Barton (2016 ) is in many ways less generic than the one of Charlesworth (1974) which essentially represents one way of modeling Dobzhansky's epistatic coadaptation. Also, the AOD mechanism is perhaps given too much weight here as this mechanism is very unlikely to be able to explain the establishment of a balanced inversion polymorphism (see Charlesworth 2023 preprint on bioRxiv). NFDS, spatially varying selection and temporally varying selection (for all of which there is quite good empirical evidence) should all be mentioned here, including the classical study of Wright and Dobzhansky (1946) which found evidence for NFDS (also see Chevin et al. 2021 in Evol. Lett.)

      On reflection, we agree that we put too much emphasis on AOD and have edited the section to be more representative.

      - L57. Two earlier Dobzhansky references, about epistatic coadaptation, would be: Dobzhansky, T. (1949). Observations and experiments on natural selection in Drosophila. Hereditas, 35(S1), 210-224. hlps://doi.org/10.1111/j.1601-5223.1949.tb033 34.xM; Dobzhansky, T. (1950). Genetics of natural populations. XIX. Origin of heterosis through natural selection in populations of Drosophila pseudoobscura. Genetics, 35, 288-302.hlps://doi.org/10.1093/gene7cs/35.3.288 - In general, in the introduction, the classical chapter by Lemeunier and Aulard (1992) should be cited as the primary reference and most comprehensive review of D. melanogaster inversion polymorphisms.

      - L101: this is of course true, though there are some exceptions, such as In(3R)Mo.

      - L110: the papers by Knibb, the chapter by Lemeunier and Aulard (1992), and the meta-analysis of INV frequencies by Kapun & Flatt (2019) could be cited here as well.

      Citation suggestions integrated.

      - L123 and elsewhere: the common D. melanogaster inversions are old but perhaps not THAT old - if we take the Corbett-Detig & Hartl (2012) es7mates, then most of them do not really exceed an age of Ne generations, or at least not by much. I mean: yes, they are somewhat old but not super-old (cf. discussion in Andolfatto et al. 2001).

      Edited to curb any hyperbole. We agree that there are much more ancient polymorphisms in populations.

      - L133-135. This needs to be rewritten: this claim is incorrect, to my mind (Charlesworth 1974; also see Charlesworth and Charlesworth 1973; discussion in Charlesworth & Flatt 2021).

      Edited. See public review response (2).

      - L154: the example of inversion polymorphism is actually explicitly discussed in Altenberg's and Feldman's (1987) paper on the reduction principle.

      Edited to mention this. Inversions are also mentioned in Feldman et al. 1980, Feldman and Balkau 1973, Feldman 1972, and have been in discussion since the origins of the idea.

      - L162ff: see Connallon & Chenoweth (2019).

      Citation suggestion integrated, along with Cox & Calsbeek 2009 which seems more directly applicable, now line 185ff.

      - L169: why? There is much evidence for other important trade-offs in this system.

      Reworded.

      - L178-179: other studies have found that trade-offs/AP contribute to the maintenance of inversion polymorphisms, e.g. Mérot et al. 2020 and Betrán et al. 1998, etc.

      Added Betrán et al. 1998 - a good reference. Moved up mention of Mérot et al. 2020 from later in the text and directed readers to the Discussion, lines 202-205.

      - L198. "alternate inversion karyotypes" - you mean INV vs. STD? It would be good to adopt a maximally clear, uniform terminology throughout.

      Edited to communicate this better.

      - L215-217: this is a theoretically well-known result due to Hazel (1943); Dickerson (1955); Robertson (1955); e.g., see the discussion in the quantative genetics book by Roff (1997) or in the review of Flatt (2020).

      Citations integrated, now lines 232ff.

      - L223 and L245: "haploid" - somewhat confusing (see public review). 

      - L259-260: This may need some explanation. 

      - L261-262: simply state that there is no recombination in D. melanogaster males.

      Edited for increased clarity.

      - L274 (and elsewhere): the meaning of "mutation...of new..inversion polymorphisms" is ambiguous - do you mean a polymorphic inversion and hence a new inversion polymorphism or do you mean polymorphisms/variants accumulating in an inversion?

      - L275: maybe better heterokaryotypic instead of heterozygous? (note that INV homokaryotypes or STD homokaryotypes can be homo- or heterozygous, so when referring to chromosomal heterozygotes instead of heterozygous chromosomes it may be best to refer to heterokaryotypes).

      Per [5](1) and [5](5) in the public review, we have edited our terminology.

      - L276: referral to M&M - I found the description of the model/simulation details there to be somewhat vague, e.g. in terms of parameter settings, etc.

      Further described.

      - L281-282: would SLiM not have worked?

      See public review response.

      - L286-287: why these parameters?

      Further described.

      - L296ff: it is not immediately clear that the loci under consideration are polymorphic for antagonistic alleles vs. non-antagonistic alternative alleles - maybe this could be made clear very explicitly.

      Edited to be explicit as suggested.

      - L341, 343: "inversion mutation" - meaning ambiguous.

      - L348, 352: "specified rate" - vague.

      - L354-357: initial capture and/or accumulation/gain? 

      - L401, 402, 404: Z-, W- and Y- are brought up here without sufficient context/explanation.

      The above have been addressed by edits in the text.

      - L523, 557, 639, 646, and elsewhere: not the first evidence - see the paper by Mérot et al. (2020) (and e.g. also by Yifan Pei et al. (2023)). 

      Citations integrated in the introduction and discussion. Mérot et al. (2020) was cited (L486 in original) but discussion was curtailed in the previous draft. 

      - L558-559. I agree but it is clear that there are many mechanisms of balancing selection that can achieve this, at least in principle; for some of them (NFDS, etc.) we have pretty good evidence. 

      - L576-577. This is correct but for In(3R)C that study did find a differential hot vs. cold selection response.

      Addressed with text edit. 

      - L584-L586: cf. Betrán et al. (1998), Mérot et al. (2020), Pei et al. (2023), etc.

      - L591. "other forms of balancing selection": yes! This should be stressed throughout. Multiple forms of balancing selection exist and they are not mutually exclusive. 

      - L593: consider adding Dobzhansky (1943), Machado et al. (2021) 

      - L596-597: this is rather unlikely, at least in terms of inversion establishment (see Charlesworth 2023; hlps://www.biorxiv.org/content/10.1101/2023.10.16.562579v1).

      - L608: consider adding Kapun & Flal (2019). 

      - L611-612: see studies by Mukai & Yamaguchi, 1974; and Watanabe et al., 1976. 

      - L639, 646: AP - see general literature on AP as a factor in maintaining polymorphism (Rose

      1982, 1985; Curtsinger et al. 1994; Charlesworth & Hughes 2000 chapter in Lewontin Festschrift; Conallon & Chenoweth 2019 - this latter paper is par7cularly relevant in terms of AP effects in the context of sexual antagonism) 

      Citation suggestions integrated.

      - L657: inversion polymorphism is explicitly discussed in Altenberg's and Feldman's (1987) paper on the reduction principle.

      Hopefully this is better communicated.

      - L724-755: I felt that this section generally lacks sufficient details, especially in terms of parameter choices and settings for the simula7ons. 

      - L732L: why not state these rates?

      Parameter values are now given a fuller description in figure legends and in the methods.  

      - L746: but we know that mutational effect sizes are not uniformly distributed (?).

      We made this choice for simplicity and to avoid invoking seemingly arbitrary distribution, but one could instead simulate trait effects with some gamma distribution. Display values would still have variable fitness effects that fluctuate with population composition, but we agree that distribution shifted toward small effects would be more realistic.

      - L765: In(3R)P is not mentioned elsewhere - is this really correct?

      That was incorrect, fixed.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Reviewer #1

      Evidence, reproducibility, and clarity

      Singh et al. analyze the expression and putative contribution of TEs in CD4+ T cells in HIV elite controllers. Through re-analysis of existing datasets, the authors describe broad differences in expression of TEs in ECs through analysis of RNA-seq and ATAC-seq data and come up with convincing examples where differentially-expressed innate immune genes correlate with increased accessibility of proximal TEs. Overall, the authors' conclusions are appropriately measured, though the manuscript text should be re-organized for clarity and a few further analyses are needed to support the main message of the paper.

      Major comments

      The manuscript would benefit from a re-organization of the figures to focus on TEs - in particular, Fig 1B, Fig 2, and Fig 3 reproduce known transcriptional differences between ECs and HCs and serve as quality controls for the authors' computational analysis. Conversely, Supplementary Fig 6 contains very interesting data on KZNF expression and should be included in the main figures.

      Authors: Thank you for the suggestion. We agree that Figure S6 should be featured more prominently in the manuscript. Accordingly, we have now incorporated it into the main text as Figure 6. The TE-KZNF correlation plots, previously Figure 5C, have been relocated to this new figure to provide a cohesive presentation of all KZNF-related data within the same figure.

      We’ve chosen to keep Figures 1B, 2, and 3 in their original places. We contend that they provide a foundational view of transcriptional variances in gene expression between patient groups, encompassing both previously identified and novel DEGs, which we believe warrants their placement in the main text. Furthermore, they serve as robust quality control measures for subsequent TE-centric transcriptional analyses. Given that there is no limitation in the number of figures in Genome Biology articles, we think it’s adequate to retain them as main figures.

      It remains unclear whether differences in TE expression described are specific to ECs or to EC-like CD4+ T cell states. As there are plenty of datasets available that compare the transcriptome of naïve, activated, exhausted, and regulatory CD4+ T cells, the authors should compare the TE expression patterns observed in ECs to activated CD4+ T cells, particularly those with a Th1 and cytotoxic phenotype analogous to those observed in ECs, from healthy donors.

      Authors: We thank the reviewer for this constructive suggestion to further study the foundations of HIV-1 elite control. In our initial study, we demonstrate that PBMCs from elite controllers (ECs) exhibit a heightened proportion of activated CD4+ T cells compared to PBMCs of healthy controls (HCs) and a heightened proportion of macrophages, naïve CD4+ T cells, and NK cells compared to PBMCs of treatment-naïve viremic progressors (VPs) (Figure 2D). Additionally, through clustering analysis of deconvoluted CD4+ T cell samples from elite controllers, we ascertain that the clustering pattern is not predicated on the CD4+ T cell subtype (Figure 3B). To further explore the reviewer’s inquiry, we compared the TE expression profile of ECs with that of unstimulated and stimulated CD4+ T cell subsets from HCs (data source: PMID 31570894), integrated into the revised manuscript as Figure S3B.

      “Unsupervised clustering of these samples shows that the TE expression pattern of ECs is most similar to that of Th2 progenitor cells, which are associated with HIV-1-specific adaptive immune responses (61). Still, we observed that, for the majority of families, TE expression was higher on average in all EC CD4+ T cell subsets than in CD4+ T cell subsets from HCs, regardless of stimulation (Figure S3B). While a subset of TE families exhibited an expression pattern in ECs similar to that of activated CD4+ T cells of HCs (e.g., high expression of L1s and THE1B), multiple TE families appear to be upregulated in an EC-specific way (e.g., LTR12C and LTR7). Together, these findings underscore the unique immune cell composition, transcriptome, and retrotranscriptome of ECs.” [pg.13-14, L226-235]

      While these observations are interesting, pursuing this question further falls beyond the scope of our study, as we note in the Discussion of the revised manuscript. We believe the reviewer’s inquiry pertains to a distinct research question, namely whether the potential for elite control of HIV-1 infection manifests as a detectable phenotype pre-infection within healthy CD4 T cell subsets (i.e., EC-like CD4+ T cell states) or is a unique phenotype that emerges solely after HIV-1 infection.

      “Another outstanding question is whether the gene and TE signatures revealed by our analysis of ECs exist in the general population independent of HIV-1 infection or if they are driven by the initial infection. While this inquiry is beyond the scope of this study, we have presented here evidence of common TE signatures between EC CD4+ T cells and Th2 progenitors from HCs (Figure S3B) and established that ECs possess a unique CD4+ T cell retrotranscriptome with potential implications for natural HIV-1 control. Future studies designed to assess elite control prediction should explore whether these TE profiles can serve as predictive variables for whether an individual displays enhanced viral control.” [pg. 38, L663-671]

      Therefore, while we appreciate the reviewer's suggestion and offer the addition of these preliminary findings, we believe that further investigation would be better suited for future studies specifically designed to address that question. Our manuscript aims to provide insight into the retrotranscriptome dynamics in ECs and their potential implications for natural HIV-1 control.

      In Fig 1, the authors demonstrate differential expression of both innate immune genes and TEs, but the link between the two is unclear. Is there any enrichment in differential expression for TEs located proximal to innate immune genes? This type of analysis should be possible using the authors' own software to map TE expression to specific genomic loci.

      __Authors: __Thank you for this excellent question. To answer this inquiry, we used the paired ATAC-seq and RNA-seq datasets for from ECs and HCs (used in Figures 1 and 4) to produce a new list of TE-gene pairs on which we could perform gene set enrichment analysis, the results of which have been integrated into the revised manuscript as Figure 4A.

      “We used paired ATAC-seq – which measures chromatin accessibility – and RNA-seq datasets for ECs (n=4) and HCs (n=4) to create a list of TE-gene pairs where the TE locus and gene show increased accessibility and expression, respectively, in ECs compared to HCs (Table S7, see Methods for details). These loci and genes were paired based on proximity, with a maximum distance of 10kb between the TE locus and the gene’s transcription start site, to increase the likelihood of a direct cis-regulatory influence of the TE over the nearby gene. Subsequent gene set enrichment analysis revealed that these genes were predominantly involved in cellular activation, cytokine production, and immune response regulation (Figure 4A). The enrichment for differential accessibility of TE loci near genes involved in these pathways suggests that the distinct TE landscape observed in ECs may contribute significantly to a unique immune regulome in these individuals.” [pg. 21, L357-368]

      Thus, we conclude that yes, there is an enrichment for immune-related genes with higher expression in ECs, proximal to differentially accessible TEs. We highlight six of these TE-gene pairs in Figure 4B-C. While we have high confidence in our analyses, future experimental validation is needed to confirm these regulatory relationships.

      Optional: In Fig 3, the authors cluster CD4+ T cells based on transcriptomic profiles. It would be interesting to re-cluster these samples based on TE expression alone, given the differences in TE expression described in Fig 5.

      __Authors: __Thank you for the suggestion. We agree that it would be valuable to assess how the EC clustering is altered when considering TE expression alone, as opposed to combining gene and TE family expression. To address this, we used the same graph-based k-nearest neighbors method to re-cluster the EC CD4+ T cell RNA-seq samples based only on locus-level TE expression, integrated into the revised manuscript as Figure S7.

      “To further explore locus-level expression patterns, we re-clustered the same EC samples (n=128) using only locus-level TE expression. This again resolved four EC clusters (Figure S7A), which interestingly appeared even more distinct than those identified by gene and TE family expression (Figure 3A). The TE locus-based clusters (TL-Cs) aligned well with the gene and TE family clusters (GT-Cs), with an average 70% overlap in samples between each GT-C and its corresponding TL-C (Figure S7B), indicating high consistency (Table S8). The remaining 30% of samples that shifted between clusters did so consistently within individuals, not cohorts, maintaining heterogeneous TL-C compositions similar to the GT-Cs (Figures S7C & S5A). An exception to this heterogeneity was TL-C4, comprising 22 samples from GT-C1 that were almost entirely from the CD4+ T cell subsets of only four participants in the Jiang cohort (Figure S7C, Table S8). No other samples from the Jiang cohort shifted to this cluster from other GT-Cs, suggesting that these patterns reflect individual variation rather than cohort bias. Like the GT-Cs, each TL-C included samples from all five CD4+ T cell subsets and was largely heterogeneous (Figure S7C). Notably, TL-C2 mirrored corresponding GT-C3 in its overrepresentation of EM and TM cells, while TL-C1 uniquely showed an overrepresentation of naïve CD4+ T cells. Beyond sample composition, each TL-C was characterized by a unique pattern of expressed TE loci (Figure S7D). These signatures were heterogeneous across families, with subsets of variable loci from one TE family marking separate clusters (Figure S7E), some of which did not reach the threshold of significance in earlier analyses when analyzed at the family-level, like SVA-D. Many families maintained their cluster-specific signatures, like THE1B (a marker of GT-C2), for which the majority of variable loci were found in corresponding TL-C1. However, some TE families, like the L1s that marked GT-C1, showed more heterogeneous signatures with variable loci marking multiple TL-Cs. These findings underscore the need for future locus-level investigations with high-depth sequencing to fully capture the complexity of TE expression.” [pg. 27-28, L462-488]

      We believe these findings not only validate the distinct clustering patterns observed but also highlight the potential of locus-level TE analysis to reveal additional layers of retrotranscriptomic diversity in EC CD4+ T cells.

      Significance

      The manuscript by Singh et al. describes for the first time the role of TEs in HIV elite controllers, suggesting that TEs may be co-opted for cis-regulatory function. This study builds off prior work demonstrating that HIV-infected CD4+ T cells activate LTR elements that may regulate the expression of interferon-inducible genes, demonstrating that ECs show further upregulation of innate immune genes. While these findings will need to be experimentally validated, this study constitutes a useful resource and adds to the growing body of evidence implicating TEs in cis-regulatory control of immune genes. This study will be of interest to basic scientists interested in genetic mechanisms of HIV control, and if further developed may comprise a useful source of biomarkers to predict viral kinetics in HIV-infected individuals. My expertise is in immunology, TE biology, and viral infection.

      Authors: We greatly appreciate this positive evaluation of our manuscript and recognition of its significance in uncovering novel evidence of TE co-option for immune regulatory function in HIV-1 elite control, as well as the suggestion of promising avenues for future research in this field.

      Reviewer #2

      Evidence, reproducibility and clarity

      The authors have re-analyzed published RNA-Seq data from CD4 T cells isolated from HIV elite controllers and reference cohorts, including HIV negative persons, viremic progressors and ART-treated persons. Their main finding is that in some of their comparisons, EC have higher levels of interferon-stimulated genes (ISG), paired with distinct expression patterns of transposable elements. The authors suggest that expression of transposable elements may induce altered expression of ISG, presumably due to immune recognition of TE. They also suggest that reduced expression of KZNF genes, which encode for transcription factors that can suppress TE, may be responsible for enhanced expression of TE. I have the following comments:

      1. All data included in this manuscript derive from previously published data. A new dataset, specifically designed to focus on a high-resolution analysis of TE expression, would be better suited to address the proposed questions.

      Authors: We agree that a new dataset tailored specifically for high-resolution analysis of TE expression would be optimal for addressing the proposed inquiries, and we emphasize this point in the Discussion of the revised manuscript.

      “We found that distinct sets of innate immunity genes and restriction factors are upregulated in different EC clusters even in the absence of active viremia, suggesting that elevated basal expression of these factors plays a previously underappreciated role in the EC phenotype. Further studies will be necessary to cement this idea and would especially benefit from the integration of single-cell omics to dissect TE regulation and clustering in deconvoluted CD4+ T cells of ECs. We also acknowledge that our study is limited by the small number of EC individuals with available omics data, which likely limited our ability to identify significant relationships between transcriptome clustering and available participant metadata (Figure S5). While the rarity of ECs in the seropositive population makes it challenging to study this phenotype, the transcriptomic heterogeneity revealed by our analyses underscores the need for surveying larger and more diverse EC cohorts.” [pg. 37-38, L651-662]

      Regrettably, we do not have access to elite controller samples (which are exceedingly rare), and as such the addition of a novel dataset was not feasible within the scope of this revision. Nevertheless, we assert that the publicly available sequencing data analyzed here is robust and suitable for locus- and family-level TE analysis. All sequencing runs were paired-end and of high depth, ensuring proper alignment to and high coverage of TEs at a locus-specific resolution. Additionally, we use in-house pipelines curated for TE analysis, to optimize the accuracy and quantity of TE-assigned reads (see Methods and our GitHub Repository for more details).

      Authors: We agree that a new dataset tailored specifically for high-resolution analysis of TE expression would be optimal for addressing the proposed inquiries, and we emphasize this point in the Discussion of the revised manuscript.

      “We found that distinct sets of innate immunity genes and restriction factors are upregulated in different EC clusters even in the absence of active viremia, suggesting that elevated basal expression of these factors plays a previously underappreciated role in the EC phenotype. Further studies will be necessary to cement this idea and would especially benefit from the integration of single-cell omics to dissect TE regulation and clustering in deconvoluted CD4+ T cells of ECs. We also acknowledge that our study is limited by the small number of EC individuals with available omics data, which likely limited our ability to identify significant relationships between transcriptome clustering and available participant metadata (Figure S5). While the rarity of ECs in the seropositive population makes it challenging to study this phenotype, the transcriptomic heterogeneity revealed by our analyses underscores the need for surveying larger and more diverse EC cohorts.” [pg. 37-38, L651-662]

      Regrettably, we do not have access to elite controller samples (which are exceedingly rare), and as such the addition of a novel dataset was not feasible within the scope of this revision. Nevertheless, we assert that the publicly available sequencing data analyzed here is robust and suitable for locus- and family-level TE analysis. All sequencing runs were paired-end and of high depth, ensuring proper alignment to and high coverage of TEs at a locus-specific resolution. Additionally, we use in-house pipelines curated for TE analysis, to optimize the accuracy and quantity of TE-assigned reads (see Methods and our GitHub Repository for more details).

      1. As the authors acknowledge, the described investigations are exploratory, and do not allow to draw firm conclusions. Mechanistic experiments are recommended to address the authors' hypotheses.

      Authors: We agree and have duly acknowledged throughout the Discussion the exploratory nature of our investigations and the need for future mechanistic experiments to validate our model. Below are passages from the revised manuscript which we’ve added to emphasize these points.

      “These findings underscore the need for future locus-level investigations with high-depth sequencing to fully capture the complexity of TE expression.” [pg. 28, L486-488]

      “Each step in the model will require experimental work to be validated. First and foremost, it will be important to confirm that the TEs exhibiting increased transcript levels and accessibility in ECs are indeed boosting the innate immune response and control of HIV-1 in these individuals.” [pg. 34, L583-586]

      “CRISPR-Cas9 editing was used in cell lines to demonstrate that a subset of MER41 elements function as enhancers driving the interferon-inducibility of several innate immune genes. However, the specific MER41 loci we identified here as differentially active in ECs have not been tested experimentally for enhancer activity. Thus, further work is warranted to confirm the regulatory function of these loci under the control of STAT1 or other immune TFs, as well as other TE families identified as targets of immune-related TFs (Figure S8).” [pg. 35, L594-600]

      “Overall, our results reinforce the concept that TEs are important players in the human antiviral response (25,93) and uncover specific candidate elements for boosting cellular defenses against HIV-1 in ECs. We acknowledge that these associations are drawn from correlative patterns and manipulative experiments are needed to infer causality between chromatin changes at these TEs and increased expression of nearby immunity genes.” [pg. 36, L618-623]

      “Further work is needed to validate TE-KZNF regulatory interactions in T cells, probe their connection to epigenetic variation at individual TE loci, and explore their repercussions on gene expression variation in CD4+ T cells, with and without HIV-1 infection.” [pg. 40, L715-718]

      Thus, while we appreciate and agree with the suggestion of experimental validation, we contend that these experiments fall beyond the scope of the present study, which is a computational investigation providing insight into the EC retrotranscriptome and its potential implications for natural HIV-1 control.

      1. An important limitation is that virological data of EC are not considered. For example, I believe it is a lot more likely that the upregulation of ISG in EC relates to ongoing low-level viral replication. The authors could analyze cell-associated HIV RNA and DNA levels and determine how they associate with ISG expression.

      Authors: Thank you for bringing up this important consideration. It's worth noting that the public datasets used in our study reported undetectable viremia in the EC volunteers (PMIDs 30964004, 29269040, 32848246, 27453467). Nonetheless, we sought to address this limitation and explore the potential association between ISG expression and viremia as recommended by the reviewer. These analyses were integrated into the revised manuscript as Figure S6.

      “To exclude the possibility that these gene expression signatures in ECs are associated with viremia, we quantified HIV-1 transcript levels in deconvoluted CD4+ T cell RNA-seq samples from ECs and ART-treated PLWH for comparison. In the original studies, all samples were reported to have undetected viremia by blood tests (9,37-39). Consistent with this, we found that the vast majority of the EC and ART samples taken from PBMCs exhibited very low HIV-1 transcript levels, with TPM values generally below 1. However, in samples originating from the lymph nodes of EC individuals (n = 22) (37), we detected HIV-1 expression in some subsets (Figure S6A&B). In agreement with the corresponding study (37), we found elevated HIV-1 transcript levels in germinal center and non-germinal center T follicular helper cells (GC Tfh & nGC Tfh, not included in our clustering analyses) -- and to a lesser extent in T effector memory (EM) cells (Figure S6A, average TPM This added analysis confirms that the increased expression of ISGs in ECs is not correlated with virological transcription and is therefore likely not to be driven by viremia.

      1. KZNF genes seem downregulated in EC. Can the authors propose a reason/mechanism for that?

      Authors: There is the possibility that KZNF regulatory loops are the cause of their transcriptional downregulation, which has been documented in embryogenesis (PMID 31006620) and cancer (PMID 33087347). We’ve incorporated this hypothesis into the Discussion as an additional consideration for the reader.

      “These observations suggest that interindividual variation in KZNF expression in CD4+ T cells could explain why certain TEs are variably expressed and accessible across ECs. But what are the mechanisms underlying variation in ZNF expression? It is possible that TE-KZNF regulatory loops are involved, in which a copy of the TE family targeted by a KZNF is inserted near and regulates the KZNF gene, thereby introducing a negative feedback loop. This phenomenon has been documented in prior studies of KZNF activity in embryogenesis (51) and cancer (115).” [pg. 39-40, L705-711]

      While we believe this is a viable hypothesis, it requires further experimentation to confirm the existence of this phenomenon and its impacts in the context of immune cells.

      Significance

      Overall, I think this is an interesting manuscript that proposes distinct and potentially important mechanisms that may contribute to immune control of HIV. My suggestions to improve the manuscript are complex and cannot be easily addressed through experimental work. I believe a possible option would be to publish the present manuscript without my proposed modifications but highlight the weaknesses of the current paper more clearly; mechanistic studies could then be deferred to a future study.

      Authors: We appreciate the reviewer's positive assessment of our manuscript and their recognition of its significance in elucidating novel TE-derived mechanisms that may contribute to natural HIV-1 control. We agree that mechanistic studies are required to test our predictions. As the reviewer suggests, these would be complex experiments that we feel fall beyond the scope of this study. With the additions detailed above in response to the reviewer’s point #2, we believe that we have clearly highlighted the limitations of our work and emphasized the need for future experimentation to validate our findings.

      Reviewer #3

      Evidence, reproducibility, and clarity

      Summary: This manuscript presents an analysis of published gene expression (RNA-seq and ATAC-seq) data from a couple of cohorts of HIV-infected elite controllers (EC), as compared to uninfected controls, (HC), virological progressors (VP). The authors report that HIV elite controllers may exhibit 4 distinct patterns of TE (and gene) expression and suggest that TE expression may drive some form of antiviral gene expression. Further, they show that heterogeneous TE expression may be determined by differential KZNF gene activity among the different clusters of elite controllers. These results are very interesting, even though the conclusions are very preliminary. It presents intriguing correlations between expression of certain TE groups of LINES and HERVs, and the clustering into 4 gene expression groups in EC and is a novel finding. That said, correlation is not causation, and the authors need to be more cautious in presenting their highly preliminary model in Figure 6.

      Authors: We are grateful for the reviewer's insightful assessment of our manuscript, acknowledging the novelty and interest of our findings regarding TE expression patterns in HIV-1 elite controllers. We also appreciate their constructive feedback regarding the cautious interpretation of preliminary conclusions. In the revised manuscript, we have underscored the exploratory nature of our investigations and the need for future mechanistic experiments to validate our model.

      “These findings underscore the need for future locus-level investigations with high-depth sequencing to fully capture the complexity of TE expression.” [pg. 28, L486-488]

      “Each step in the model will require experimental work to be validated. First and foremost, it will be important to confirm that the TEs exhibiting increased transcript levels and accessibility in ECs are indeed boosting the innate immune response and control of HIV-1 in these individuals.” [pg. 34, L583-586]

      “CRISPR-Cas9 editing was used in cell lines to demonstrate that a subset of MER41 elements function as enhancers driving the interferon-inducibility of several innate immune genes. However, the specific MER41 loci we identified here as differentially active in ECs have not been tested experimentally for enhancer activity. Thus, further work is warranted to confirm the regulatory function of these loci under the control of STAT1 or other immune TFs, as well as other TE families identified as targets of immune-related TFs (Figure S8).” [pg. 35, L594-600]

      “Overall, our results reinforce the concept that TEs are important players in the human antiviral response (25,93) and uncover specific candidate elements for boosting cellular defenses against HIV-1 in ECs. We acknowledge that these associations are drawn from correlative patterns and manipulative experiments are needed to infer causality between chromatin changes at these TEs and increased expression of nearby immunity genes.” [pg. 36, L618-623]

      “Further work is needed to validate TE-KZNF regulatory interactions in T cells, probe their connection to epigenetic variation at individual TE loci, and explore their repercussions on gene expression variation in CD4+ T cells, with and without HIV-1 infection.” [pg. 40, L715-718]

      We hope these passages provide sufficient caution and clarity in the presentation of our scientific inquiry.

      Major comments:

      Overall, although preliminary, as the authors note, the results are interesting and worthy of follow-up. At this point, however, a number of issues arise that need further clarification and analysis before I would consider this study complete.

      First, the analyses shown in Figures 3-5 based on data from studies on EC of CD4 cells are apparently motivated by the differential TE expression in total PBMCs shown in Fig 1 and 2. Yet, the TE groups (please don't use taxonomic terms like "subfamily") identified in Fig 2 and Fig 4 are completely different, with no overlap. This discrepancy underscores the possibility that the differential expression observed is, at least in part, due to the differences among the groups or clusters in cell type composition, as seen in Fig 2D and 3B which, themselves, could be a consequence of HIV infection and elite control (which has been shown to involve ongoing, albeit low-level, virus replication). This issue must be addressed.

      Authors: Thank you for the suggestion. First, we’d like to clarify that the data used in Figures 1 and 2 were not both derived from PBMCs. Figures 1 and S1 examine the differential expression of TEs in EC CD4+ T cells compared to HCs and ART-treated PLWH, respectively. Figure 2 examines differential expression of TEs in EC PBMCs compared to treatment-naïve VPs. Second, regarding Figure 4B-C, the TE loci that we chose to highlight were not based on our results from the PBMC analysis in Figure 2, which is why there is no overlap in the TE families presented. Instead, we selected those TE-gene pairs based on 1) known function of the genes in immunity and/or HIV-1 restriction, 2) known contribution of the TE families to immunity, and 3) differential accessibility and expression of the TEs and genes respectively in ECs compared to HCs. Thus, Figure 4B-C represents select examples that we deemed particularly relevant to the EC phenotype. We have revised the manuscript to better explain the process of TE-gene pair identification and the rationale behind our selection for Figure 4B-C.

      “We used paired ATAC-seq – which measures chromatin accessibility – and RNA-seq datasets from the CD4+ T cells of ECs (n=4) and HCs (n=4) (39) to create a list of TE-gene pairs where the TE locus and gene show increased accessibility and expression, respectively, in ECs compared to HCs (Table S7, see Methods for details). These loci and genes were paired based on proximity, with a maximum distance of 10kb between the TE locus and the gene’s transcription start site, to increase the likelihood of a direct cis-regulatory influence of the TE over the nearby gene.” [pg. 21, L357-363)

      “In Figure 4B & 4C, we have highlighted six of the TE-gene pairs from Table S7 based on the gene’s function in HIV-1 restriction and the TE family’s known contribution to immune gene regulation.” [pg. 21, L369-371]

      Regarding cell type composition, we acknowledge that the differences observed in the proportion of immune cell subtypes may contribute to the differential expression between ECs, VPs, and HCs (Figures 2D and S3A). However, we provide evidence that cell type composition cannot be the sole driver for the clustering of deconvoluted CD4+ T cell RNA-seq samples (Figure 3B and S5D). Cell subtype alone could not explain the observed clustering of EC samples by gene and TE family expression. Clusters 1 and 2, for example, had nearly identical subtype compositions, but were clearly separated on the UMAP (Figures 3A, 3B, and S5D). We remark on this in the Results of the revised manuscript.

      “[W]e visualized the samples by cellular subtype, as identified in the original studies, to assess whether the clustering could be explained by CD4+ T cell subtype composition (Figure S5D). Clusters 1 and 2 were essentially indistinguishable in cell type composition, whereas Clusters 3 and 4 showed an overrepresentation of TM/EM and naïve/CM cell types, respectively (Figure 3B). Thus, cell subtype composition could only partially explain the clustering.” [pg. 16, L271-276]

      The EC CD4+ T cell clusters also had unique gene ontology, gene & TE expression, and TE accessibility profiles (Figures 3C, 3D, 5). Moreover, while we do not have parallel RNA- and ATAC-seq data from similarly deconvoluted CD4+ T cells of ECs like those used in the clustering analysis (PMIDs 32848246 & 27453467), the original article from which we sourced the parallel RNA- and ATAC-seq data used in Figures 1 and 4 reported that these samples are predominantly effector memory CD4+ T cells (PMID 30964004). If new deconvoluted, multi-omic datasets from ECs become available, we would be interested in further exploring the contribution of cell type composition. However, the current data indicate that it is not a major contributor to the differential TE expression identified in our analyses.

      Regarding the impact of ongoing HIV-1 replication upon the unique expression patterns in the EC participants, it's worth noting that the public datasets used in our study reported undetectable viremia in the EC volunteers (PMIDs 30964004, 29269040, 32848246, 27453467). Nonetheless, we sought to address this by quantifying HIV-1 transcription and exploring its potential association with interferon-stimulated gene (ISG) expression, a group of genes that we know would be reactive to active viremia. These analyses were integrated into the revised manuscript as Figure S6.

      “To exclude the possibility that these gene expression signatures in ECs are associated with viremia, we quantified HIV-1 transcript levels in deconvoluted CD4+ T cell RNA-seq samples from ECs and ART-treated PLWH for comparison. In the original studies, all samples were reported to have undetected viremia by blood tests (9,37-39). Consistent with this, we found that the vast majority of the EC and ART samples taken from PBMCs exhibited very low HIV-1 transcript levels, with TPM values generally below 1. However, in samples originating from the lymph nodes of EC individuals (n = 22) (37), we detected HIV-1 expression in some subsets (Figure S6A&B). In agreement with the corresponding study (37), we found elevated HIV-1 transcript levels in germinal center and non-germinal center T follicular helper cells (GC Tfh & nGC Tfh, not included in our clustering analyses) -- and to a lesser extent in T effector memory (EM) cells (Figure S6A, average TPM Based on these results, we have concluded that the differential expression of genes and TEs in the EC clusters are not a consequence of low-level viral transcription in ECs.

      Finally, a remark on TE nomenclature: The reviewer suggests that we use the term “TE groups” as opposed to taxonomic terms such as TE subfamily or TE family. We respectfully disagree. This nomenclature of TEs has been well defined (PMIDs 26612867, 26612867, 17984973) and is widely used in TE literature. Throughout the manuscript, we have conformed to the nomenclature used to annotate the human genome. One can debate the way TE families and subfamilies have been classified in Dfam (the database through which repetitive elements in the human genome have been annotated), but it is outside the scope of this study to revisit that nomenclature.

      Similarly, of the 12 DE TE groups in EC in Fig 5A, only 3 overlap with the 16 in EC Fig S1.

      Authors: This is correct, but we don’t believe it’s concerning. In Figure 5A, we are comparing the expression of TE families between separate EC clusters. In Figure S1, we are comparing the expression of TE families in ECs compared to ART-treated PLWH. These are fundamentally different comparisons and thus the differences in the identified DE-TEs between the two figures reflect the distinct biological contexts being investigated in each analysis.

      Second, the introduction points out the strongly supported association between elite control and immunogenetic determinants, most notably specific HLA-B types, but also innate immunity factors. This cries out for inclusion of these factors in the analyses of this manuscript, in the format of Figure S4, for example, but none is to be found. The relevant genotypes are likely available in the metadata in the references cited, but, if not, could be inferred from the RNA-seq data.

      Authors: Thank you for the recommendation. While our project’s primary focus is on the transcriptomic and epigenomic signatures, we agree that studying the HLA-B genotypes of all EC participants could provide valuable context for understanding the clustering of elite controllers. To explore this, we inferred the HLA-B alleles in each EC participant whose RNA-seq data was included in the clustering analysis, utilizing the arcasHLA tool (PMID: 31173059) on the total CD4+ T cell samples. We then validated these inferred HLA-B alleles against the available metadata from one of the source studies (PMID 27453467) and found that they matched for all participants. This strengthened our confidence in the accuracy of the HLA-B genotype inferences for the other samples where comprehensive HLA-B data was not provided.

      In order to assess how these protective HLA-B alleles segregated between the four EC clusters derived from gene and TE family expression, we chose to visualize three of the most common alleles associated with HIV-1 elite control: HLA-B*27:03, *57:01, and *57:03 (PMIDs 30964004, 25119688, 21051598) (Figure R1, available in the Response to Reviewers PDF).

      Our analysis revealed that these major protective alleles were not significantly overrepresented in any particular cluster. Consequently, we believe that HLA-B genotype does not have a major impact on the clustering observed in Figure 3.

      It would also be very useful to present the KZNF data in Figure 5 the same way, since, looking at Fig 5C, the correlation of high and low KZNF expression, while clearly correlated with a that of few groups of elements, with clustering into specific groups does not appear to be well supported.

      Authors: Thank you for the insightful suggestion. While the KZNF genes are included in the gene set used for the clustering analysis in Figure 3, we agree that clustering based solely on KZNF expression and displaying it as we have in Figures 3A and S5 could provide valuable insights. However, when we attempted to cluster the EC RNA-seq samples using only KZNF expression data, we were limited by the relatively low number of KZNF genes that showed sufficient variability across samples (n = 120). For robust statistical power, we require at least 200 features to reliably cluster the 128 EC CD4+ T cell samples. We believe this limitation does not diminish the relevance of KZNFs in the observed clustering patterns but rather highlights the nuanced role each KZNF plays in the regulation of the transcriptome. Each individual KZNF is responsible for the regulation of hundreds to thousands of TE loci (PMID 37730438). Thus, while a clustering approach based solely on KZNF expression may not be feasible, the integral role of KZNFs in modulating the transcriptome through TE regulation remains evident and supports their inclusion in Figure 6 of the revised manuscript.

      In general, other than the cell type composition differences, there is no presentation of evidence for any biologically important feature associated with the clusters found.

      Authors: We agree that the root cause of the transcriptomic differences between the EC clusters is hard to pin down but we do identify several distinctive features of the clusters that we believe are biologically significant. First, having extracted the lists of genes whose differential expression defined the four EC clusters, gene set enrichment analysis revealed that the clusters were functionally distinct, each characterized by a unique list of top GO terms (Figure 3C). Second, we provide evidence that KZNFs expressed in CD4+ T cells significantly bind to the candidate TE families whose expression defines each of these clusters (Figure 6D) and have significantly decreased expression in ECs compared to VPs (Figure 6C). This is corroborated by pairwise correlation analysis that revealed cluster-specific anticorrelation patterns between these KZNFs and their target TEs (Figure 6A). We present this data in support of our hypothesized KZNF-based mechanism for TE co-option in viral immunity. We do not yet have data indicative of the mechanism by which KZNF expression is in turn regulated. However, we speculate that negative feedback loops may be contributing to changes in KZNF expression.

      “These observations suggest that interindividual variation in KZNF expression in CD4+ T cells could explain why certain TEs are variably expressed and accessible across ECs. But what are the mechanisms underlying variation in ZNF expression? It is possible that TE-KZNF regulatory loops are involved, in which a copy of the TE family targeted by a KZNF is inserted near and regulates the KZNF gene, thereby introducing a negative feedback loop. This phenomenon has been documented in prior studies of KZNF activity in embryogenesis (51) and cancer (115).” [pg. 39-40, L705-711]

      Overall, our study presents preliminary evidence that the four EC clusters derived from gene & TE family expression may be distinguished by complex interplay of activators (Figure S8) and repressors (Figure 6) altering the activity of infection-responsive TE families to co-opt specific elements for immune regulatory function. While not yet validated in an experimental setting, we believe these results are of biological significance.

      Third, the figures present values that have been very heavily analyzed, and it is difficult to impossible to infer what the underlying data look like. For example, with the exception of a few selected examples in Figs 4 and 5, individual provirus data are lacking. Nor can we tell how consistent the distribution of expression values within a TE group is, whether the TEs included solo LTRs (which constitute the majority of all ERVs), the possible contribution of other TFs to expression (with the exception of a brief mention of STAT1).

      Authors: We respectfully disagree that the values presented in our figures are heavily analyzed. As this manuscript represents the first investigation of TEs’ role in HIV-1 elite control, we believe the most reasonable initial approach was to compile and visualize the data at the family level, rather than at the level of individual loci, which is harder to interpret due to mapping issues, commonly low transcription, and often idiosyncratic behavior of individual loci. Nonetheless, we did not limit our analysis to full-length HERVs (proviruses) and thus retain all solo LTR data in our analyses. This was added to the Methods of the revised manuscript.

      “To facilitate comprehensive expression quantification, we curated a reference transcriptome by combining gene, TE, and HIV-1 genomic sequences. This was achieved by integrating the locus-level TE classification from RepeatMasker, the hg19 GenCode gene annotation,

      and the HXB2 reference HIV-1 annotation. For the TEs, we removed simple repeats, SINE elements, and DNA transposons, retaining LINE and HERV loci, including all solo LTRs. We also removed any loci within gene exons/UTRs. The remaining sequences were appended in fasta format, and all sequences were annotated with their respective gene, TE locus, or HIV subunit and modeled in GTF format.” [pg. 55, L869-878]

      For the sake of transparency, all relevant details on sequencing data analysis and the corresponding scripts are available in the Methods and our GitHub Repository.

      Additionally, while most of our figures make comparisons at the family level, we do visualize multiple TE loci (Figure 4C) and provide a list of putative locus-level TE-gene pairs from which those shown in Figure 4C were selected (Table S7). In our revisions, we also re-clustered the 128 EC CD4+ T cell RNA-seq samples based only on locus-level TE expression, using the same graph-based k-nearest neighbors method as in Figure 3. The results of this new analysis have been integrated into the revised manuscript as Figure S7.

      “To further explore locus-level expression patterns, we re-clustered the same EC samples (n=128) using only locus-level TE expression. This again resolved four EC clusters (Figure S7A), which interestingly appeared even more distinct than those identified by gene and TE family expression (Figure 3A). The TE locus-based clusters (TL-Cs) aligned well with the gene and TE family clusters (GT-Cs), with an average 70% overlap in samples between each GT-C and its corresponding TL-C (Figure S7B), indicating high consistency (Table S8). The remaining 30% of samples that shifted between clusters did so consistently within individuals, not cohorts, maintaining heterogeneous TL-C compositions similar to the GT-Cs (Figures S7C & S5A). An exception to this heterogeneity was TL-C4, comprising 22 samples from GT-C1 that were almost entirely from the CD4+ T cell subsets of only four participants in the Jiang cohort (Figure S7C, Table S8). No other samples from the Jiang cohort shifted to this cluster from other GT-Cs, suggesting that these patterns reflect individual variation rather than cohort bias. Like the GT-Cs, each TL-C included samples from all five CD4+ T cell subsets and was largely heterogeneous (Figure S7C). Notably, TL-C2 mirrored corresponding GT-C3 in its overrepresentation of EM and TM cells, while TL-C1 uniquely showed an overrepresentation of naïve CD4+ T cells. Beyond sample composition, each TL-C was characterized by a unique pattern of expressed TE loci (Figure S7D). These signatures were heterogeneous across families, with subsets of variable loci from one TE family marking separate clusters (Figure S7E), some of which did not reach the threshold of significance in earlier analyses when analyzed at the family-level, like SVA-D. Many families maintained their cluster-specific signatures, like THE1B (a marker of GT-C2), for which the majority of variable loci were found in corresponding TL-C1. However, some TE families, like the L1s that marked GT-C1, showed more heterogeneous signatures with variable loci marking multiple TL-Cs. These findings underscore the need for future locus-level investigations with high-depth sequencing to fully capture the complexity of TE expression.” [pg. 27-28, L462-488]

      With this addition, we include significantly more data analyzed at the locus level, which we believe not only validate the distinct clustering observed in Figure 3, but also underscore the potential for locus resolution analysis to reveal additional layers of retrotranscriptomic diversity in EC CD4+ T cells.

      Finally, we agree with the reviewer that TFs other than STAT1 may contribute to the observed changes in TE expression. To investigate this, we analyzed several TFs expressed in CD4+ T cells and, for TFs enriched over TEs of interest, subsequently examined the correlation between TF and target TE expression in the deconvoluted EC CD4+ T cell samples used for the clustering. The results of this analysis have been integrated into the revised manuscript at Figure S8.

      “In addition to KZNF repressors, transcriptional activators may also drive the differential expression of specific TE families across ECs (83). To investigate this, we focused on transcription factors (TFs) expressed in CD4+ T cells and mined ChIP-seq data from the ENCODE Consortium (84) to identify TFs with binding enrichment to TE families of interest, selected for their elevated, cluster-specific expression in ECs (highlighted in Figures 4, 5, and S4). We then examined the correlation between TF and target TE expression in the deconvoluted CD4+ T cell samples from ECs used for our clustering analysis (Figure 3) (9,37). We observed several significant positive correlations between TF and TE expression across ECs (Figure S8). Thus, differential expression of immune-related TFs may also contribute to the variation in TE expression and cis-regulatory activity across ECs, in tandem with the repressive activities of KZNFs.” [pg. 30, L517-527]

      This evidence supports the reviewer’s suggestion that other TFs may be contributing to the unique EC retrotranscriptome we profile in this study. These added analyses, mimicking those conducted for KZNFs in Figure 6B & 6D, demonstrate that transcriptional activators may indeed play a crucial role in shaping the TE landscape in ECs.

      Other issues

      Figure 1:

      A) Log2 fold change of what? TPM values? Needs to be specified.

      Authors: Thank you for pointing out this ambiguity. The log2-transformed fold change values plotted in Figure 1A refer to DESeq2-normalized expression. They were extracted from the results of the DESeq2 pipeline, which we applied to the raw count expression matrix (see our Methods for more details). Following your suggestion, we have clarified this point in the figure legend in the revised manuscript.

      “Total detected genes and TE loci are plotted by log2-transformed fold change of DESeq2-normalized counts (EC vs. HC).” [pg. 10, L163-164]

      We have similarly made these changes to any figure legend which was ambiguous in its description of the expression data.

      Why Bonferroni correction? Usually BH q values or other less stringent adjustments are used nowadays.

      Authors: In our analysis, we opted for the Bonferroni correction due to its well-established reliability and stringent control of the family-wise error rate when conducting multiple tests. Given the exploratory nature of our investigation and the desire to minimize the risk of false positive findings, we chose to employ this traditional correction method within our analytical pipelines.

      B,C): Z-score of what? Scaled, normalized counts? Scaled TPM values?

      Authors: Thank you again for highlighting this point of uncertainty. We now clarify this in the figure legend in the revised manuscript.

      “Heatmap displaying the expression of the top differentially expressed genes in CD4+ T cells of ECs (n=4; red bar) vs. HCs (n=5; blue bar). Relative expression levels are representative of row-wise scaled, log2-transformed expression in transcripts per million (TPM). Heatmap coloration is based on the z-score distribution from low (gold) to high (purple) expression.” [pg. 11, L167-171]

      Figure 2:

      B) The blue font color is very difficult to see.

      Authors: We have changed the blue font color to make it more easily distinguishable from the black.

      C) This heatmap should demarcate or separate genes versus TE clades. If that's not possible, then the two should be shown separately.

      Authors: We appreciate your suggestion regarding the heatmap presentation. While we understand the rationale for demarcating genes versus TE clades, we have chosen to retain the original figure layout. In this analysis, TEs were analyzed simultaneously with genes. The order in which they are shown was obtained by default clustering of the expression matrix using the hclust function. We chose to present them together and in this order to provide a comprehensive visualization of the differential expression patterns between the two groups and highlight the homogenous nature of gene and TE expression across VPs.

      L191: How many groups (NOT families) and how many total elements were examined?

      Authors: We begin with the RepeatMasker annotation of the hg19 assembly and filter out the SINE elements, DNA transposons, simple repeats, and all loci within gene exons/UTRs. These details are provided in the Methods of the revised manuscript, as was quoted above. In total, our analyses examine 1,104,828 loci from 603 TE groups (which we refer to as families). We apologize if this figure is not accurate to a separate classification of TEs into groups, rather than families. Any such method of grouping TEs is unfamiliar to us and outside of the Dfam annotation.

      L198: 2B, not C

      Authors: Thank you for catching this. The figures labelled were swapped in error and have been changed to reflect in Figure 2 to match the in-text references.

      L205: Did the expressed proviruses have STAT1 sites?

      Authors: Thank you for your question. The identification of LTR13’s increased expression in ECs compared to VPs was the result of a family level analysis which considered expression additively across the LTR13 loci in our annotation. To answer your question, we analyzed STAT1 ChIP-seq data from the ENCODE Consortium to characterize which LTR13 loci were bound by STAT1 (corroborated by motif prediction calls). We then integrated the EC RNA-seq data and found that the expressed LTR13 proviruses significantly overrepresented those with bound STAT1 sites (Figure R2, available in the Response to Reviewers PDF).

      These data suggest that STAT1 binding may play a critical role in the transcriptional regulation of LTR13 in ECs, contributing to their differential expression profile. Further exploration into the contribution of activating, immune-related TFs is explored in Figure S8 in the revised manuscript.

      L333: 10 kb is very close. Why was it chosen?

      Authors: We chose 10 kb as our cutoff for selection because it allowed for very high confidence in the TE loci’s cis-regulatory capacity over the nearby genes. For transparency, we have made this clearer in the Results text of the revised manuscript.

      “These loci and genes were paired based on proximity, with a maximum distance of 10kb between the TE locus and the gene’s transcription start site, to increase the likelihood of a direct cis-regulatory influence of the TE over the nearby gene.” [pg. 21, L360-363]

      However, if desired, a less stringent cutoff could also be used with relative confidence (e.g., 50 kb).

      L351-352: Again, correlation is not causation. How do the authors know it's not the other way around?

      Authors: The candidates that we chose to display in Figure 4 (the figure to which these lines refers) are from MER41, ERV3-16, and LTR12C. Our lab and others have shown that these specific loci or other loci in these TE families are capable of regulating neighboring genes’ expression, with specific evidence in the context of immunity (PMID Smitha, Ed, APOBEC, etc.). Based on this knowledge, we believe that it’s most likely that TE-derived regulatory sequences are the cause of the increased restriction factor expression, rather than TE accessibility being a consequence of the transcriptional activation of the neighboring genes. However, we recognize that these results are correlative, as the reviewer notes, and we emphasize this in the revised manuscript. Most notably:

      “We acknowledge that these associations are drawn from correlative patterns and manipulative experiments are needed to infer causality between chromatin changes at these TEs and increased expression of nearby immunity genes.” [pg. 36, L620-623]

      Figure 4

      B) Need to show a scale of the genome region, the orientation of both the gene and the TE, whether it is a solo LTR

      Authors: Thank you for the suggestion. Genomic scale and orientation have been added to Figure 4C. All loci visualized were solo LTRs, save for HCP5, which is a lncRNA derived from a full-length ERV3 element.

      Figure 5

      A) Would benefit from also showing HCs

      Authors: Thank you for the recommendation. The RNA-seq datasets used in this analysis do not include HC samples. Additionally, this analysis is meant to highlight differences in TE expression between the four EC clusters. Thus, we have chosen to keep Figure 5A as it appears in the original manuscript.

      C) Would be helped by showing adjusted p-values, and also should show examples of non-correlating relationships between these KZNF genes and other TEs.

      Authors: Thank you for the suggestion. All correlation analyses had adjusted p-values below 0.01, derived from corr.test in R. We’ve added this to the figure legends of Figure 6B [pg. 32, L539] and S8B [pg. 53, L835]. However, we have chosen not to integrate non-correlating examples into the revised manuscript for the sake of space.

      Figure 6

      Title: should start with "proposed model for.." or some such.

      Authors: Thank you for the suggestion. The title has been changed to “Proposed model for the interplay of KZNFs and TEs regulating proximal antiviral gene expression in elite controllers of HIV-1” in the revised manuscript [pg. 34, L580-581].

      L 537: Again, how do the alleles segregate in the clusters?

      Authors: This question has been addressed in response to an earlier comment from Reviewer #3.

      Generally, in the correlation analyses, I'd like to see adjusted p-values and examples of non-correlated results.

      Authors: Thank you for the suggestion. As mentioned above, all correlation analyses have been annotated with the adjusted p-value threshold. Additionally, below we’ve included examples of non-correlated results from two analyses. First, we show a TE-gene pair whose increased TE accessibility in HCs compared to ECs does not correlate with increased expression of the proximal gene (Figure R3, available in the Response to Reviewers PDF). Notably, this gene does not play a role in HIV-1 infection response. Here, we show that genes with proximal (Second, we show the pairwise correlation and linear regression results of L1PA6 and ZNF2 (Figure R4, available in the Response to Reviewers PDF). ZNF2 is one of the KZNFs highlighted in Figure 6 for its low expression in ECs, anticorrelated to its repressive target LTR12C. On the other hand, L1PA6 is active in ECs, with variably high expression across samples. ZNF2 ChIP-exo revealed that ZNF2 has no capacity to bind to L1PA6 loci (adj. p-value = 1; PMID 37730438). Thus, even though both genes are variable across samples, we observe no significant (anti)correlation between the two variables (rho = 0.051 & p-value = 0.866).

      While we have not integrated these results into the revised manuscript for the sake of space, we hope that the provided examples satisfactorily demonstrate the presence of non-correlated results in our analyses, further reinforcing the specificity and robustness of our significant findings.

      Significance:

      This study presents an in-depth analysis of the reverse transcriptome in Elite controllers. It will be of interest to both HIV researchers and those interested in the regulation of the human retrotranscriptome and its consequences.

      Provides an avenue for future explanation into elite controllers and TE involvement in the phenotype.

      Does a good job of placing the work in the context of existing lit, synthesizing other papers regarding TEs and immune control.

      Potential immune regulatory involvement of specific HERV clades.

      Authors: We’d like to thank the reviewer for their encouraging feedback. We’re pleased that they found our analysis of the EC retrotranscriptome to be of broad interest and appreciate their recognition of our efforts to synthesize existing literature, contextualizing our findings within the broader field. We agree that our study opens new avenues for exploring the role of TEs, particularly specific HERV clades, in not only the EC phenotype but immune regulation as a whole.

    2. Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      This manuscript presents an analysis of published gene expression (RNA-seq and ATAC-seq) data from a couple of cohorts of HIV-infected elite controllers (EC), as compared to uninfected controls, (HC), virological progressors (VP). The authors report that HIV elite controllers may exhibit 4 distinct patterns of TE (and gene) expression and suggest that TE expression may drive some form of antiviral gene expression. Further, they show that heterogeneous TE expression may be determined by differential KZHF gene activity among the different clusters of elite controllers. These results are very interesting, even though the conclusions are very preliminary. It presents intriguing correlations between expression of certain TE groups of LINES and HERVs, and the clustering into 4 gene expression groups in EC and is a novel finding. That said, correlation is not causation, and the authors need to be more cautious in presenting their highly preliminary model in Figure 6.

      Major comments:

      Overall, although preliminary, as the authors note, the results are interesting and worthy of follow-up. At this point, however, a number of issues arise that need further clarification and analysis before I would consider this study complete. First, the analyses shown in Figures 3-5 based on data from studies on EC of CD4 cells are apparently motivated by the differential TE expression in total PBMCs shown in Fig 1 and 2. Yet, the TE groups (please don't use taxonomic terms like "subfamily") identified in Fig 2 and Fig 4 are completely different, with no overlap. This discrepancy underscores the possibility that the differential expression observed is, at lest in part, due to the differences among the groups or clusters in cell type composition, as seen in Fig 2D and 3B which, themselves, could be a consequence of HIV infection and elite control (which has been shown to involve ongoing, albeit low-level, virus replication). This issue must be addressed. Similarly, of the 12 DE TE groups in EC in Fig 5A, only 3 overlap with the 16 in EC Fig S1.<br /> Second, The introduction points out the strongly supported, association between elite control and immunogenetic determinants, most notably specific HLA-B types, but also innate immunity factors. This cries out for inclusion of these factors in the analyses of this manuscript, in the format of Figure S4, for example, but none is to be found. The relevant genotypes are likely available in the metadata in the references cited, but, if not, could be inferred from the RNA-seq data. It would also be very useful to present the KZNF data in Figure 5 the same way, since, looking at Fig 5C, the correlation of high and low KZNF expression, while clearly correlated with a that of few groups of elements, with clustering into specific groups does not appear to be well supported. I n general, other than the cell type composition differences, there is no presentation of evidence for any biologically important feature associated with the clusters found.<br /> Third, the figures present values that have been very heavily analyzed, and it is difficult to impossible to infer what the underlying data look like. For example, with the exception of a few selected examples in Figs 4 and 5, individual provirus data are lacking. Nor can we tell how consistent the distribution of expression values within a TE group is, whether the TEs included solo LTRs (which constitute the majority of all ERVs), the possible contribution of other TFs to expression (with the exception of a brief mention of STAT1).

      Other issues

      Figure 1: A) Log2 fold change of what? TPM values? Needs to be specified.

      Why Bonferroni correction? Usually BH q values or other less stringent adjustments are used nowadays. B,C): Z-score of what? Scaled, normalized counts? Scaled TPM values?

      Figure 2: B) The blue font color is very difficult to see C) This heatmap should demarcate or separate genes versus TE clades. If that's not possible, then the two should be shown separately.

      L191: How many groups (NOT Fam1lies) and how many total elements were examined?

      L198: 2B, not C

      L205: Did the expressed proviruses have STAT1 sites?

      L333: 10 kb is very close. Why was it chosen?

      L351-352: Again., correlation is not causation. How do the authors know it's not the other way around?

      Figure 4 Title: For "induction" Substitute "correlation"

      Panel B: Need to show a sclae of the genome region, the orientation of both the gene and the TE, whether it is a solo LTR 5 Panel A: Would benefit from also showing HCs C: Would be helped by showing adjusted p-values, and also should show examples of non-correlating relationships between these KZNF genes and other TEs. 6 Title: should start with "proposed model for.." or some such. L 537: Again, how do the alleles segregate in the clusters?

      General

      In the correlation analyses, I'd like to see adjusted p-values and examples of non-correlated results.

      Significance

      This tudy presents an in depth analysis of the reverse transcriptome in Elite controllers. It will be of interest to both HIV researchers and thos interested in the regulation of the human retrotranscriptome and its consequences

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

      Provides an avenue for future explanation into elite controllers and TE involvement in the phenotype. - Place the work in the context of the existing literature (provide references, where appropriate).

      Does a good job of this, synthesizing other papers regarding TEs and immune control. - State what audience might be interested in and influenced by the reported findings.

      Potential immune regulatory involvement of specific HERV clades. - Define your field of expertise with a few keywords to help the authors contextualize your point of view.

      Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

    1. Author response:

      The following is the authors’ response to the original reviews.

      eLife assessment

      The authors develop a self-returning self-avoiding polymer model of chromosome organization and show that their framework can recapitulate at the same time local density and large-scale contact structural properties observed experimentally by various technologies. The presented theoretical framework and the results are valuable for the community of modelers working on 3D genomics. The work provides solid evidence that such a framework can be used, is reliable in describing chromatin organization at multiple scales, and could represent an interesting alternative to standard molecular dynamics simulations of chromatin polymer models.

      We appreciate the editor for an accurate description of the scope of the paper.

      Public Reviews:

      Reviewer #1 (Public Review):

      Carignano et al propose an extension of the self-returning random walk (SRRW) model for chromatin to include excluded volume aspects and use it to investigate generic local and global properties of the chromosome 3D organization inside eukaryotic nuclei. In particular, they focus on chromatin volumic density, contact probability, and domain size and suggest that their framework can recapitulate several experimental observations and predict the effect of some perturbations.

      We thanks the reviewer for the attention paid to the manuscript and all the relevant comments.

      Strengths:

      - The developed methodology is convincing and may offer an alternative - less computationally demanding - framework to investigate the single-cell and population structural properties of 3D genome organization at multiple scales.

      - Compared to the previous SRRW model, it allows for investigation of the role of excluded volume locally.

      Excluded volume is accounted for everywhere, not locally. We emphasized this on page 3, line 182:

      “The method that we employ to remove overlaps is a low-temperature-controlled molecular dynamics simulation using a soft repulsive interaction potential between initially overlapping beads, that is terminated as soon as all overlaps have been resolved, as described in the Appendix 3.”


      - They perform some experiments to compare with model predictions and show consistency between the two.

      Weaknesses:

      - The model is a homopolymer model and currently cannot fully account for specific mechanisms that may shape the heterogeneous, complex organization of chromosomes (TAD at specific positions, A/B compartmentalization, promoter-enhancer loops, etc.).

      The SR-EV model is definitely not a homo-polymer, as it is not a regular concatenation of a single monomeric unit.

      The model includes loops, which may happen in two ways: 1) As in the SRRW, branching structures emerging from the configuration backbone can be interpreted as nested loops and 2) A relatively long forward step followed by a return is a single loop. The model induces the formation of packing domains, which are not TADs, and are quantitatively in agreement with ChromSTEM experiments.

      We consider convenient to add a new figure that will further clarify the structures obtained with the SR-EV model. The following paragraph and figure has been added in page 5:

      “The density heterogeneity displayed by the SR-EV configurations can be analyzed in terms of the accessibility. One way to reveal this accessibility is by calculating the coordinations number (CN) for each nucleosome, using a coordination radius of 11.5 nm, along the SR-EV configuration. CN values range from 0 for an isolated nucleosome to 12 for a nucleosome immersed in a packing domain. In Figure 3 we show the SR-EV configuration showed in Figure 2, but colored according to CN. CN can be also considered as a measure to discriminate heterochromatin (red) and euchromatin (blue). Figure 3-A shows how the density inhomogeneity is coupled to different CN, with high CN represented in red and low CN represented in blue. Figure 3-B show a 50 nm thick slab obtained from the same configuration that clearly show the nucleosomes at the center of each packing domains are almost completely inaccesible, while those outside are open and accessible. It is also clear that the surface of the packing domains are characterized by nearly white nucleosomes, i.e. coordinated towards the center of the domain and open in the opposite direction.”

      - By construction of their framework, the effect of excluded volume is only local and larger-scale properties for which excluded volume could be a main actor (formation of chromosome territories [Rosa & Everaers, PLoS CB 2009], bottle-brush effects due to loop extrusion [Polovnikov et al, PRX 2023], etc.) cannot be captured.

      Excluded volume is considered for all nucleosomes, including overlapping beads distant along the polymer chain. Chromosome territories can be treated, but it is not in this case because we look at a single model chromosome.

      - Apart from being a computationally interesting approach to generating realistic 3D chromosome organization, the method offers fewer possibilities than standard polymer models (eg, MD simulations) of chromatin (no dynamics, no specific mechanisms, etc.) with likely the same predictive power under the same hypotheses. In particular, authors often claim the superiority of their approach to describing the local chromatin compaction compared to previous polymer models without showing it or citing any relevant references that would show it.

      We apologize if the text transmit an idea of superiority over other methods that was not intended. SR-EV is an alternative tool that may give a different, even complementary point of view, to standard polymer models.

      - Comparisons with experiments are solid but are not quantified.

      The comparisons that we have presented are quantitative. We do not have so far a way to characterize alpha or phi, a priori, for a particular system.

      Impact:

      Building on the presented framework in the future to incorporate TAD and compartments may offer an interesting model to study the single-cell heterogeneity of chromatin organization. But currently, in this reviewer's opinion, standard polymer modeling frameworks may offer more possibilities.

      We thank the reviewer for the positive opinion on the potential of the presented method. The incorporation of TADs and compartments is left for a future evolution of the model as its complexity will make this work extremely long.

      Reviewer #2 (Public Review):

      Summary:

      The authors introduce a simple Self Returning Excluded Volume (SR-EV) model to investigate the 3D organization of chromatin. This is a random walk with a probability to self-return accounting for the excluded volume effects. The authors use this method to study the statistical properties of chromatin organization in 3D. They compute contact probabilities, 3D distances, and packing properties of chromatin and compare them with a set of experimental data.

      We thank the reviewer for the attention paid to our manuscript.

      Strengths:

      (1) Typically, to generate a polymer with excluded volume interactions, one needs to run long simulations with computationally expensive repulsive potentials like the WeeksChanlder-Anderson potential. However, here, instead of performing long simulations, the authors have devised a method where they can grow polymer, enabling quick generation of configurations.

      (2) Authors show that the chromatin configurations generated from their models do satisfy many of the experimentally known statistical properties of chromatin. Contact probability scalings and packing properties are comparable with Chromatin Scanning Transmission Electron Microscopy (ChromSTEM)  experimental data from some of the cell types.

      Weaknesses:

      This can only generate broad statistical distributions. This method cannot generate sequence-dependent effects, specific TAD structures, or compartments without a prior model for the folding parameter alpha. It cannot generate a 3D distance between specific sets of genes. This is an interesting soft-matter physics study. However, the output is only as good as the alpha value one provides as input.

      We proposed a model to create realistic chromatin configuration that we have contrasted with specific single cell experiments, and also reproducing ensemble average properties. 3D distances between genes can be calculated after mapping the genome to the SR-EV configuration. The future incorporation of the genome sequence will also allow us to describe TADs and A/B compartments. See added paragraph in the Discussion section:

      “The incorporation of genomic character to the SR-EV model will allow us to study all individual single chromosomes properties, and also topological associated domains and A/B compartmentalization from ensemble of configurations as in HiC experiments. “

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Major:

      - In the introduction and along the text, the authors are often making strong criticisms of previous works (mostly polymer simulation-based) to emphasize the need for an alternative approach or to emphasize the outcomes of their model. Most of these statements (see below) are incomplete if not wrong. I would suggest tuning down or completely removing them unless they are explicitly demonstrated (eg, by explicit quantitative comparisons). There is no need to claim any - fake - superiority over other approaches to demonstrate the usefulness of an approach. Complementarity or redundance in the approaches could also be beneficial.

      We regret if we unintentionally transmitted a claim of superiority. We have made several small edits to change that.

      - Line 42-43: at least there exist many works towards that direction (including polymer modeling, but also statistical modeling). For eg, see the recent review of Franck Alber.

      Line removed. Citation to Franck Alber included below in the text.

      - Line 54-57: Point 1 is correct but is it a fair limitation? These models can predict TADs & compartments while SR-EV no. Point 2 is wrong, it depends on the resolution of the model and computer capacity but it is not an intrinsic limitation. Point 3 is wrong, such models can predict very well single-cell properties, and again it is not an intrinsic limitation of the model. Point 4 is incorrect. The space-filling/fractal organization was an (unfortunate) picture to emphasize the typical organization of chromosomes in the early times (2009), but crumpled polymers which are a more realistic description are not space-filling (see Halverson et al, 2013).

      Text involving points 1 to 4 removed. It was unnecessary and does not change the line of the paper.

      - L400-402 + 409-411: in such a model, the biphasic structure may emerge from loop extrusion but also naturally from the crumpled polymer organization. Simple crumpled polymer without loop extrusion and phase separation would also produce biphasic structures.

      Yes, we agree. Also SR-EV leads to biphasic structures.

      - L 448-449: any data to show that existing polymer modeling would predict a strong dependency of C_p(n) on the volumic fraction (in the range studied here)?

      No, I don’t know a work predicting that.

      - Fig. 4:

      - Large-scale structural properties (R^2(n) and C_p(n)) are not dependent on phi. Is it surprising that by construction, SR-EV only relaxes the system locally after SRRW application?

      Excluded volume is considered at all length scales. However, as the decreasing C_p curves observed in theories and experiments imply, the fraction of overlap (or contacts) is more important at small separations (local) than at large separations. Yet, it was a surprise for us to observed negligible effect on phi.

      - Why not make a quantitative comparison between predicted and measured C_p(n)? Or at least plotting them on the same panel.

      Panels B and C are in the same scale and show a good agreement between SR-EV and experiments. However, it is not perfectly quantitative agreement. SR-EV represents the generic structure of chromatin and perfect agreement should not be expected.

      - Comparison with an average C_p(n) over all the chromosomes would be better.

      Possibly, but we don’t think it adds anything to the paper.

      - In Figure 5,6,7 (and related text): authors often describe some parameter values that are 'closest to experiment findings'. Can the authors quantify/justify this? The various 'closest' parameters are different. Can the authors comment?

      The folding parameter and average volume fraction are chose so that the agreement is best with the displayed experimental system, different cell for each case.

      - Figure 5: why not show the experimental distribution from Ou et al?

      - Figure 6 & 7: experimental results. Can the authors show images from their own experiments? Can they show that cohesion/RAD21 is really depleted after auxin treatment?

      It is currently under review in a different journal.

      - In the Discussion, a fair discussion on the limitations of the methods (dynamics, etc) is missing.

      Minor

      - Line 34-36: the logical relationship between this sentence and the ones before and after is very unclear.

      - Along the text, authors use the term 'connectivity' to describe 3D (Hi-C) contacts between different regions of the same chromosome/polymer. This is misleading as connectivity in polymer physics describes the connection along the polymer and not in the 3D space.

      No. I don’t think we used connectivity in that sense. We agree with your statement on the use of connectivity in polymer physics, and is what we always had in mind for this model.

      - Line 92: typo.

      - On the SR-EV method: does the relaxation process create local knots in the structure?

      We have not checked for knots.

      - Table 1: the good correspondence with linker length is remarkable but likely 'fortunate', other chosen resolutions would have led to other results. Moreover, the model cannot account for the fine structure of chromatin fiber. Can the authors comment on that?

      Fortunate to the extent that we sample the model parameter to overall catch the structure of chromatin.

      - Line 211: 'without the need of imposing any parameter': alpha is a parameter, no?

      Correct. Phrase deleted.

      - L267-269 & 450-451: actually in Liu & Dekker, they do observe an effect on Hi-C map (C_p(n)), weak but significant and not negligible.

      Our statements read ‘minimal’ and ‘relatively insensitive’. It is observed, but very small.

      - L283-286: This is a perspective statement that should be in the discussion.

      Moved to the Discussion, as suggested.

      - L239-241: The authors seem to emphasize some contradictions with recent results on phase separation. This is unclear and should be relocated to discussion.

      We just pointed out recent experiments, as stated. No intention to generate a discussion with any of them.

      - L311-313: Unclear statement.

      - L316-325: This is not results but discussion/speculation.

      Moved to Discussion

      - Along the text: 'promotor'-> 'promoter'. 

      - Corrected.

      - L364: explain more in detail PWS microscopy.

      Reviewer #2 (Recommendations For The Authors):

      Even though there are claims about nucleosome-resolution chromatin polymer, it is not clear that this work can generate structures with known nucleosome-resolution features. Nucleosome-level structure is much beyond a random walk with excluded volume and is driven by specific interactions. The authors should clarify this.

    1. BHEESHMA LOVED BOTH > THE PANDA l?A5 A N D THE KAC/RAISAS,BUT HEWAS D U TY -B O U N D TO F IG H T O N THE S ID E O F THE RAURA ISAS .THEYWERE THE SO NS OF THE R E IG N IN G K IN G , DHW TA&ASHTRA

      A tragic dilemma is once again placed on Bhishma but he chooses dharma over affection. Even though he has seen the five Pandava brothers grow up to become the people they are now, he is forced to fight alongside the Kauravas because of his loyalty to the Kuru Dynasty. It serves as an important lesson to the reader that there are times when duty and responsibility are more important than affection but that is on a case by case scenario. There must be an immense amount of emotions running through his mind as he must fight his own blood in the Pandavas which does not sound right. The sight of having to fight and kill your own family would not sit right with anyone but Bhishma does it without question because of dharma. While his loyalty is very admirable, it raises questions about his morals because how does someone go out of their way to fight family. CC BY Ajey Sasimugunthan (contact)

    1. Introduction In the year 1914 the University Museum secured by purchase a large six column tablet nearly complete, carrying originally, according to the scribal note, 240 lines of text. The contents supply the South Babylonian version of the second book of the epic ša nagba imuru, “He who has seen all things,” commonly referred to as the Epic of Gilgamish. The tablet is said to have been found at Senkere, ancient Larsa near Warka, modern Arabic name for and vulgar descendant of the ancient name Uruk, the Biblical Erech mentioned in Genesis X. 10. This fact makes the new text the more interesting since the legend of Gilgamish is said to have originated at Erech and the hero in fact figures as one of the prehistoric Sumerian rulers of that ancient city. The dynastic list preserved on a Nippur tablet1 mentions him as the fifth king of a legendary line of rulers at Erech, who succeeded the dynasty of Kish, a city in North Babylonia near the more famous but more recent city Babylon. The list at Erech contains the names of two well known Sumerian deities, Lugalbanda2 and Tammuz. The reign of the former is given at 1,200 years and that of Tammuz at 100 years. Gilgamish ruled 126 years. We have to do here with a confusion of myth and history in which the real facts are disengaged only by conjecture. The prehistoric Sumerian dynasties were all transformed [208]into the realm of myth and legend. Nevertheless these rulers, although appearing in the pretentious nomenclature as gods, appear to have been real historic personages.3 The name Gilgamish was originally written dGi-bil-aga-miš, and means “The fire god (Gibil) is a commander,” abbreviated to dGi-bil-ga-miš, and dGi(š)-bil-ga-miš, a form which by full labialization of b to u̯ was finally contracted to dGi-il-ga-miš.4 Throughout the new text the name is written with the abbreviation dGi(š),5 whereas the standard Assyrian text has consistently the writing dGIŠ-ṬU6-BAR. The latter method of writing the name is apparently cryptographic for dGiš-bar-aga-(miš); the fire god Gibil has also the title Giš-bar. A fragment of the South Babylonian version of the tenth book was published in 1902, a text from the period of Hammurapi, which showed that the Babylonian epic differed very much from the Assyrian in diction, but not in content. The new tablet, which belongs to the same period, also differs radically from the diction of the Ninevite text in the few lines where they duplicate each other. The first line of the new tablet corresponds to Tablet I, Col. V 25 of the Assyrian text,7 where Gilgamish begins to relate his dreams to his mother Ninsun.8 [209] The last line of Col. I corresponds to the Assyrian version Book I, Col. VI 29. From this point onward the new tablet takes up a hitherto unknown portion of the epic, henceforth to be assigned to the second book.9 At the end of Book I in the Assyrian text and at the end of Col. I of Book II in the new text, the situation in the legend is as follows. The harlot halts outside the city of Erech with the enamoured Enkidu, while she relates to him the two dreams of the king, Gilgamish. In these dreams which he has told to his mother he receives premonition concerning the advent of the satyr Enkidu, destined to join with him in the conquest of Elam. Now the harlot urges Enkidu to enter the beautiful city, to clothe himself like other men and to learn the ways of civilization. When he enters he sees someone, whose name is broken away, eating bread and drinking milk, but the beautiful barbarian understands not. The harlot commands him to eat and drink also: “It is the conformity of life, Of the conditions and fate of the Land.” He rapidly learns the customs of men, becomes a shepherd and a mighty hunter. At last he comes to the notice of Gilgamish himself, who is shocked by the newly acquired manner of Enkidu. “Oh harlot, take away the man,” says the lord of Erech. Once again the faithful woman instructs her heroic lover in the conventions of society, this time teaching him the importance of the family in Babylonian life, and obedience to the ruler. Now the people of Erech assemble about him admiring his [210]godlike appearance. Gilgamish receives him and they dedicate their arms to heroic endeavor. At this point the epic brings in a new and powerful motif, the renunciation of woman’s love in the presence of a great undertaking. Gilgamish is enamoured of the beautiful virgin goddess Išhara, and Enkidu, fearing the effeminate effects of his friend’s attachment, prevents him forcibly from entering a house. A terrific combat between these heroes ensues,10 in which Enkidu conquers, and in a magnanimous speech he reminds Gilgamish of his higher destiny. In another unplaced fragment of the Assyrian text11 Enkidu rejects his mistress also, apparently on his own initiative and for ascetic reasons. This fragment, heretofore assigned to the second book, probably belongs to Book III. The tablet of the Assyrian version which carries the portion related on the new tablet has not been found. Man redeemed from barbarism is the major theme of Book II. The newly recovered section of the epic contains two legends which supplied the glyptic artists of Sumer and Accad with subjects for seals. Obverse III 28–32 describes Enkidu the slayer of lions and panthers. Seals in all periods frequently represent Enkidu in combat with a lion. The struggle between the two heroes, where Enkidu strives to rescue his friend from the fatal charms of Išhara, is probably depicted on seals also. On one of the seals published by Ward, Seal Cylinders of Western Asia, No. 459, a nude female stands beside the struggling heroes.12 This scene not improbably illustrates the effort of Enkidu to rescue his friend from the goddess. In fact the satyr stands between Gilgamish and Išhara(?) on the seal. [211] 1 Ni. 13981, published by Dr. Poebel in PBS. V, No. 2. 2 The local Bêl of Erech and a bye-form of Enlil, the earth god. Here he is the consort of the mother goddess Ninsun. 3 Tammuz is probably a real personage, although Dumu-zi, his original name, is certainly later than the title Ab-ú, probably the oldest epithet of this deity, see Tammuz and Ishtar, p. 8. Dumu-zi I take to have been originally the name of a prehistoric ruler of Erech, identified with the primitive deity Abu. 4 See ibid., page 40. 5 Also Meissner’s early Babylonian duplicate of Book X has invariably the same writing, see Dhorme, Choix de Textes Religieux, 298–303. 6 Sign whose gunufied form is read aga. 7 The standard text of the Assyrian version is by Professor Paul Haupt, Das Babylonische Nimrodepos, Leipzig, 1884. 8 The name of the mother of Gilgamish has been erroneously read ri-mat ilatNin-lil, or Rimat-Bêlit, see Dhorme 202, 37; 204, 30, etc. But Dr. Poebel, who also copied this text, has shown that Nin-lil is an erroneous reading for Nin-sun. For Ninsun as mother of Gilgamish see SBP. 153 n. 19 and R.A., IX 113 III 2. Ri-mat ilatNin-sun should be rendered “The wild cow Ninsun.” 9 The fragments which have been assigned to Book II in the British Museum collections by Haupt, Jensen, Dhorme and others belong to later tablets, probably III or IV. 10 Rm. 289, latter part of Col. II (part of the Assyrian version) published in HAUPT, ibid., 81–4 preserves a defective text of this part of the epic. This tablet has been erroneously assigned to Book IV, but it appears to be Book III. 11 K. 2589 and duplicate (unnumbered) in Haupt, ibid., 16–19. 12 See also Ward, No. 199. Transliteration 1it-bi-e-ma iluGilgamiš šu-na-tam i-pa-aš-šar. 2iz-za-kar-am1 a-na um-mi-šu 3um-mi i-na ša-a-at mu-ši-ti-i̭a 4ša-am-ḫa-ku-ma at-ta-na-al-la-ak 5i-na bi-ri-it id-da-tim 6ib-ba-šu-nim-ma ka-ka-’a2 ša-ma-i 7ki-?-?-rum3 ša a-nim im-ku-ut a-na ṣi-ri-i̭a 8áš-ši-šu-ma ik-ta-bi-it4 e-li-i̭a 9ilam5 iš-šu-ma nu-uš-ša-šu6 u-ul el-ti-’i̭ 10ad-ki ma-tum pa-ḫi-ir7 e-li-šu 11id-lu-tum ú-na-ša-ku ši-pi-šu 12ú-um-mi-id-ma     pu-ti 13i-mi- du         i̭a-ti 14aš-ši-a-šu-ma at-ba-la-áš-šu a-na ṣi-ri-ki 15um-mi iluGilgamiš mu-u-da-a-at ka-la-ma 16iz-za-kar-am a-na iluGilgamiš [212] 17mi-in-di iluGilgamish ša ki-ma ka-ti 18i-na ṣi-ri   i-wa-li-id-ma 19ú-ra-ab-bi-šu   ša-du-ú 20ta-mar-šu-ma [sa(?)]-ap-ḫa-ta at-ta 21id-lu-tum ú-na-ša-ku ši-pi-šu8 22te-iṭ-ṭi-ra-šu(?) … šu-ú-zu 23ta-tar-ra-[’a]-šu a-na ṣi-[ri-i̭]a 24[iš-(?)] ti-lam-ma9 i-ta-mar ša-ni-tam 25[šu-na-]ta i-ta-wa-a-am a-na um-mi-šu 26[um-m]i a-ta-mar ša-ni-tam 27[šu-na-ta a-ta]mar e-mi-a i-na zu-ki-im 28[i-na?] Unuk-(ki) ri-bi-tim10 29ḫa-aṣ-ṣi-nu   na-di-i-ma 30e-li-šu   pa-aḫ- ru 31ḫa-aṣ-ṣi-nu-um-ma ša-ni bu-nu-šu 32a-mur-šu-ma aḫ-ta-ta a-na-ku 33a-ra-am-šu-ma ki-ma áš-ša-tim 34a-ḫa-ap-pu-up   el-šu 35el-ki-šu-ma áš-ta-ka-an-šu 36a-na     a-ḫi-i̭a 37um-mi iluGilgamish mu-da-at ka-la-ma 38[iz-za-kar-am a-na iluGilgamish] ................................... [213] COL. II 1aš-šum uš-[ta-] ma-ḫa-ru it-ti-ka. 2iluGilgamish šu-na-tam i-pa-šar 3iluEn-ki-[dû w]a?-ši-ib ma-ḫar ḫa-ri-im-tim 4UR [ ]-ḫa-mu DI-?-al-lu-un 5[ ] im-ta-ši a-šar i-wa-al-du 6ûmê 611 ù 7 mu-ši- a-tim 7iluEn-ki-dû te-bi-   i-ma 8ša-[am-ka-ta]   ir- ḫi 9ḫa-[ri-im-tu pa-a]-ša i-pu-ša-am-ma 10iz-za-[kar-am] a-na iluEn-ki-dû12 11a-na-ṭal-ka dEn-ki-dû ki-ma ili ta-ba-áš-ši 12am-mi-nim it-ti na-ma-áš-te-e13 13ta-at-ta-[na-al-]la -ak ṣi-ra-am 14al-kam   lu-ùr-di-   ka 15a-na libbi Uruk-(ki) ri-bi-tim 16a-na biti [el-]lim mu-ša-bi ša A-nim 17dEn-ki-dû ti-bi lu-ru-ka 18a-na É-[an-n]a mu-ša-bi ša A-nim 19a-šar [iluGilgamiš] it-[.........] ne-pi-ši-tim(?) 20ù at-[   ]-di [   -] ma 21ta-[   ] ra-ma-an-   ka [214] 22al-ka ti-ba i-[na] ga-ag-ga-ri 23ma-a-a?14 -ak ri-i-im 24iš-me a-wa-az-za im-ta-gár ga-ba-ša 25mi-il-kum ša sinništi 26im-ta-[ku]-ut a-na libbi-šu 27iš-ḫu-uṭ li-ib-ša-am 28iš-ti-nam [ú]-la-ab-bi-iš-šu 29li-ib- [ša-am] ša-ni-a-am 30ši-i it-ta-al-ba- áš 31ṣa-ab-ta-at ga-az- zu 32ki-ma ? i-ri-id-di-šu 33a-na gu-up-ri ša ri-i-im 34a-š[ar   ] tar-ba-ṣi-im 35i-na [   ]-ḫu-ru ri-i̭a-ú15 36............................. (About two lines broken away.) COL. III 1ši-iz-ba ša na-ma-áš-te-e 2i-te-en-   ni-   iḳ 3a-ka-lam iš-ku-nu ma-ḫar-šu 4ip-te-iḳ-ma i-na -aṭ-ṭal16 5ù ip-pa-al-la-   as 6u-ul i-di dEn-ki- dû 7aklam a-na a-ka-lim 8šikaram   a-na ša-te-e-im 9la-a   lum-mu-   ud [215] 10ḫa-ri-im-lum pi-ša i-pu-ša-am- ma 11iz-za-kar-am a-na iluEn-ki-dû 12a-ku-ul ak-lam dEn-ki-dû 13zi-ma-at ba-la-ṭi-im 14bi-ši-ti ši-im-ti ma-ti 15i-ku-ul a-ak-lam iluEn-ki-dû 16a-di ši-bi-e-šu 17šikaram iš-ti-a-am 187 aṣ-ṣa-am-mi-im17 19it-tap-šar kab-ta-tum i-na-an-gu 20i-li-iṣ libba- šu- ma 21pa-nu-šu [it-]ta(?)-bir -ru18 22ul-tap-pi-it [............]-i 23šu-ḫu-ra-am pa-ga-ar-šu 24ša-am-nam ip-ta-ša-áš-ma 25a-we-li-iš i-mē 26il-ba- áš li-ib-ša-am 27ki-ma mu-ti i-ba-áš-ši 28il-ki ka-ak-ka-šu 29la-bi ú gi-ir- ri 30iš-sa-ak-pu šab-[ši]-eš mu-ši-a-ti 31ut- tap -pi-iš šib-ba-ri19 32la-bi uk-t[a ]-ši-id 33it-ti immer na-ki-[e?] ra-bu-tum 34iluEn-ki-dû ma-aṣ-ṣa-ar-šu-nu 35a-we-lum wa-ru-um 36iš-[te]-en id-lum 37a-na[ ........ u]-za-ak-ki-ir ........................... (About five lines broken away.) [216] REVERSE I .............................. 1i-ip-pu-uš     ul-ṣa-am 2iš-ši-ma   i-ni-i-šu 3i-ta-mar   a-we-lam 4iz20-za-kar-am   a-na ḫarimti 5ša-am-ka-at uk-ki-ši21 a-we-lam 6a-na mi-nim    il-li-kam 7zi-ki-ir-šu   lu-uš-šu22 8ḫa-ri-im-tum iš-ta-si a-we-lam 9i-ba-uš-šu-um-ma i-ta-mar-šu 10e-di-il23 e-eš-ta-ḫi-[ṭa-am] 11mi-nu   a-la-ku-zu na-aḫ-24 [     -]ma 12e pi-šu    i-pu-ša-am-[ma] 13iz-za-kar-am a-na iluEn-[ki-dû] 14bi-ti-iš e-mu-tim [                ] 15ši-ma-a-at    ni-ši-i-   ma 16tu-ṣa25-ar pa-a-ta-tim26 17a-na âli dup-šak-ki-i e ṣi-en 18UG-AD-AD-LIL e-mi ṣa-a-a-ḫa-tim [217] 19a-na šarri Unuk-(ki) ri-bi-tim 20pi-ti pu-uk epši27 a-na ḫa-a-a-ri 21a-na iluGilgamiš šarri ša Unuk-(ki) ri-bi-tim 22pi-ti pu-uk epši28 23a-na ha-a-a-ri 24áš-ša-at ši-ma-tim i-ra-aḫ-ḫi 25šu-u pa-na-nu-um-ma 26mu-uk wa-ar-ka-nu 27i-na mi-il-ki ša ili ga-bi-ma 28i-na bi-ti-iḳ a-pu-un-na-ti-šu29 29ši- ma- az- zum 30a-na zi-ik-ri id-li-im 31i-ri-ku pa-nu-šu REVERSE II ............................................................ (About five lines broken away.) 1i-il-la-ak- .......... 2ù ša-am-ka-at[     ]ar-ki-šu 3i- ru- ub-ma30 a-na31 libbi Uruk-(ki) ri-bi-tim 4ip-ḫur um-ma-nu-um i-na ṣi-ri-šu 5iz-zi-za-am-ma i-na zu-ki-im 6ša Unuk-(ki) ri-bi-tim 7pa-aḫ-ra-a-ma ni-šu [218] 8i-ta-mē-a   i-na ṣi-ri-šu pi(?)-it-tam32 9a-na mi-[ni]33 iluGilgamiš ma-ši-il 10la-nam   ša- pi-  il 11e-ṣi[   pu]-uk-ku-ul 12    i ? -ak-ta 13i[-    -]di   i-ši? 14ši-iz-ba ša[na-ma-]áš-[te]-e 15i-te-  en-  ni-   iḳ 16ka-i̭ā-na i-na [libbi] Uruk-(ki) kak-ki-a-tum34 17id-lu-tum u-te-el-li-   lu 18ša-ki-in  ip-ša-   nu35 19a-na idli ša i-tu-ru   zi-mu-šu 20a-na iluGilgamiš ki-ma i-li-im 21ša-ki-iš-šum36 me-iḫ-rum 22a-na ilatIš-ḫa-ra ma-i̭ā-lum 23na-   [di]-i-   ma 24iluGilgamish id-[   ]na-an(?)... 25i-na mu-ši in-ni-[    -]id 26i-na-ak37-ša-am- ma 27it-ta-[    ]i-na zûki 28ip-ta-ra-[ku   ]-ak-tām 29ša   iluGilgamish 30........... da-na(?) ni-iš-šu COL. III 1ur-(?)ḫa ..................... 2iluGilgamiš ................ 3i-na ṣi-ri .................... [219] 4i-ḫa-an-ni-ib [pi-ir-ta-šu?] 5it-bi-ma ... 6a-na pa-ni- šu 7it-tam-ḫa-ru i-na ri-bi-tu ma-ti 8iluEn-ki-dû ba-ba-am ip-ta-ri-ik 9i-na ši-pi-šu 10iluGilgamiš e-ri-ba-am u-ul id-di-in 11iṣ-ṣa-ab-tu-ma ki-ma li-i-im 12i- lu- du38 13zi-ip-pa-am ’i-bu- tu 14i-ga-rum ir-tu-tū39 15iluGilgamiš ù iluEn-ki- dû 16iṣ-ṣa-ab-tu-ù- ma 17ki-ma li-i-im i-lu-du 18zi-ip-pa-am ’i-bu- tu 19i-ga-rum ir-tu-tū 20ik-mi-is-ma iluGilgamiš 21i-na ga-ga-ag-ga-ri ši-ip-šu 22ip-ši-iḫ40 uṣ-ṣa-šu- ma 23i-ni-’i i-ra-az-zu 24iš-tu i-ra-zu i-ni-ḫu41 25iluEn-ki-dû a-na ša-ši-im 26iz-za-kar-am a-na iluGilgamiš 27ki-ma iš-te-en-ma um-ma-ka 28ú- li- id- ka 29ri-im-tum ša zu- pu-ri 30ilat-Nin- sun- na 31ul-lu e-li mu-ti ri-eš-su [220] 32šar-ru-tam ša ni-ši 33i-ši-im-kum iluEn-lil duppu 2 kam-ma šu-tu-ur e-li … 4 šu-ši42 1 Here this late text includes both variants pašāru and zakāru. The earlier texts have only the one or the other. 2 For kakabê; b becomes u̯ and then is reduced to the breathing. 3 The variants have kima kiṣri; ki-[ma]?-rum is a possible reading. The standard Assyrian texts regard Enkidu as the subject. 4 Var. da-an 5 ŠAM-KAK = ilu, net. The variant has ultaprid ki-is-su-šu, “he shook his murderous weapon.” For kissu see ZA. 9,220,4 = CT. 12,14b 36, giš-kud = ki-is-su. 6 Var. nussu for nuš-šu = nušša-šu. The previous translations of this passage are erroneous. 7 This is to my knowledge the first occurence of the infinitive of this verb, paḫēru, not paḫāru. 8 Text ma? 9 ištanamma > ištilamma. 10 Cf. Code of Hammurapi IV 52 and Streck in Babyloniaca II 177. 11 Restored from Tab. I Col. IV 21. 12 Cf. Dhorme Choix de Textes Religieux 198, 33. 13 namaštû a late form which has followed the analogy of reštû in assuming the feminine t as part of the root. The long û is due to analogy with namaššû a Sumerian loan-word with nisbe ending. 14 Room for a small sign only, perhaps A; māi̭āk? For mâka, there, see BEHRENS, LSS. II page 1 and index. 15 Infinitive “to shepherd”; see also Poebel, PBS. V 106 I, ri-i̭a-ú, ri-te-i̭a-ú. 16 The text has clearly AD-RI. 17 Or azzammim? The word is probably an adverb; hardly a word for cup, mug (??). 18 it is uncertain and ta more likely than uš. One expects ittabriru. Cf. muttabrirru, CT. 17, 15, 2; littatabrar, EBELING, KTA. 69, 4. 19 For šapparu. Text and interpretation uncertain. uttappiš II² from tapāšu, Hebrew tāpaś, seize. 20 Text ta! 21 On ekēšu, drive away, see Zimmern, Shurpu, p. 56. Cf. uk-kiš Myhrman, PBS. I 14, 17; uk-ki-ši, King, Cr. App. V 55; etc., etc. 22 The Hebrew cognate of mašû, to forget, is našâ, Arabic nasijia, and occurs here in Babylonian for the first time. See also Brockelman, Vergleichende Grammatik 160 a. 23 Probably phonetic variant of edir. The preterite of edēru, to be in misery, has not been found. If this interpretation be correct the preterite edir is established. For the change r > l note also attalaḫ < attaraḫ, Harper, Letters 88, 10, bilku < birku, RA. 9, 77 II 13; uttakkalu < uttakkaru, Ebeling, KTA. 49 IV 10. 24 Also na-’-[     -]ma is possible. 25 The text cannot be correct since it has no intelligible sign. My reading is uncertain. 26 Text uncertain, kal-lu-tim is possible. 27 KAK-ši. 28 KAK-ši. 29 Literally nostrils. pitik apunnati-šu, work done in his presence(?). The meaning of the idiom is uncertain. 30 Text ZU! 31 Text has erroneous form. 32 Text PA-it-tam clearly! 33 Omitted by the scribe. 34 Sic! The plural of kakku, kakkîtu(?). 35 Cf. e-pi-ša-an-šu-nu libâru, “May they see their doings,” Maḳlu VII 17. 36 For šakin-šum. 37 On the verb nâku see the Babylonian Book of Proverbs § 27. 38 The verb la’āṭu, to pierce, devour, forms its preterite iluṭ; see VAB. IV 216, 1. The present tense which occurs here as iluṭ also. 39 Note BUL(tu-ku) = ratātu (falsely entered in Meissner, SAI. 7993), and irattutu in Zimmern, Shurpu, Index. 40 “For ipšaḫ.” 41 Sic! ḫu reduced to the breathing ’u; read i-ni-’u. 42 The tablet is reckoned at forty lines in each column, Translation 1Gilgamish arose interpreting dreams, 2addressing his mother. 3“My mother! during my night 4I, having become lusty, wandered about 5in the midst of omens. 6And there came out stars in the heavens, 7Like a … of heaven he fell upon me. 8I bore him but he was too heavy for me. 9He bore a net but I was not able to bear it. 10I summoned the land to assemble unto him, 11that heroes might kiss his feet. 12He stood up before me1 13and they stood over against me. 14I lifted him and carried him away unto thee.” 15The mother of Gilgamish she that knows all things, 16said unto Gilgamish:— [212] 17“Truly oh Gilgamish he is 18born2 in the fields like thee. 19The mountains have reared him. 20Thou beholdest him and art distracted(?) 21Heroes kiss his feet. 22Thou shalt spare him…. 23Thou shalt lead him to me.” 24Again he dreamed and saw another dream 25and reported it unto his mother. 26“My mother, I have seen another 27[dream. I beheld] my likeness in the street. 28In Erech of the wide spaces3 29he hurled the axe, 30and they assembled about him. 31Another axe seemed his visage. 32I saw him and was astounded. 33I loved him as a woman, 34falling upon him in embrace. 35I took him and made him 36my brother.” 37The mother of Gilgamish she that knows all things 38[said unto Gilgamish:—] ................................... [213] COL. II 1that he may join with thee in endeavor.” 2(Thus) Gilgamish solves (his) dream. 3Enkidu sitting before the hierodule 4 5[   ] forgot where he was born. 6Six days and seven nights 7came forth Enkidu 8and cohabited with the courtesan. 9The hierodule opened her mouth 10speaking unto Enkidu. 11“I behold thee Enkidu; like a god thou art. 12Why with the animals 13wanderest thou on the plain? 14Come! I will lead thee 15into the midst of Erech of the wide places, 16even unto the holy house, dwelling place of Anu. 17Oh Enkidu, arise, I will conduct thee 18unto Eanna dwelling place of Anu, 19where Gilgamish [oppresses] the souls of men(?) 20And as I ............ 21thou shalt ........ thyself. [214] 22Come thou, arise from the ground 23unto the place yonder (?) of the shepherd.” 24He heard her speak and accepted her words with favor. 25The advice of the woman 26fell upon his heart. 27She tore off one garment 28and clothed him with it. 29With a second garment 30she clothed herself. 31She clasped his hand, 32guiding him like .............. 33unto the mighty presence of the shepherd, 34unto the place of the ... of the sheepfolds. 35In ......... to shepherd 36............................. (About two lines broken away.) COL. III 1Milk of the cattle 2he drank. 3Food they placed before him. 4He broke bread4 5gazing and looking. 6But Enkidu understood not. 7Bread to eat, 8beer to drink, 9he had not been taught. [215] 10The hierodule opened her mouth 11and said unto Enkidu:— 12“Eat bread, oh Enkidu! 13It is the conformity of life, 14of the conditions and the fate of the land.” 15Enkidu ate bread, 16until he was satiated. 17Beer he drank 18seven times(?). 19His thoughts became unbounded and he shouted loudly. 20His heart became joyful, 21and his face glowed. 22He stroked................. 23the hair of the head.5 His body 24with oil he anointed. 25He became like a man. 26He attired himself with clothes 27even as does a husband. 28He seized his weapon, 29which the panther and lion 30fells in the night time cruelly. 31He captured the wild mountain goats. 32The panther he conquered. 33Among the great sheep for sacrifice 34Enkidu was their guard. 35A man, a leader, 36A hero. 37Unto .......... he elevated ........................... (About five lines broken away.) [216] REVERSE I .............................. 1And he made glad. 2He lifted up his eyes, 3and beheld the man, 4and said unto the hierodule:— 5“Oh harlot, take away the man. 6Wherefore did he come to me? 7I would forget the memory of him.” 8The hierodule called unto the man 9and came unto him beholding him. 10She sorrowed and was astonished 11how his ways were ............ 12Behold she opened her mouth 13saying unto Enkidu:— 14“At home with a family [to dwell??] 15is the fate of mankind. 16Thou shouldest design boundaries(??) 17for a city. The trencher-basket put (upon thy head). 18.... ......an abode of comfort. [217] 19For the king of Erech of the wide places 20open, addressing thy speech as unto a husband. 21Unto Gilgamish king of Erech of the wide places 22open, addressing thy speech 23as unto a husband. 24He cohabits with the wife decreed for him, 25even he formerly. 26But henceforth 27in the counsel which god has spoken, 28in the work of his presence 29shall be his fate.” 30At the mention of the hero 31his face became pale. REVERSE II ............................................................ (About five lines broken away.) 1going ....................... 2and the harlot ..... after him. 3He entered into the midst of Erech of the wide places. 4The artisans gathered about him. 5And as he stood in the street 6of Erech of the wide places, 7the people assembled [218] 8disputing round about him:— 9“How is he become like Gilgamish suddenly? 10In form he is shorter. 11In ........ he is made powerful. 12 13 14Milk of the cattle 15he drank. 16Continually in the midst of Erech weapons 17the heroes purified. 18A project was instituted. 19Unto the hero whose countenance was turned away, 20unto Gilgamish like a god 21he became for him a fellow. 22For Išhara a couch 23was laid. 24Gilgamish ................... 25In the night he .............. 26embracing her in sleep. 27They ........ in the street 28halting at the ................ 29of Gilgamish. 30.......... mightily(?) COL. III 1A road(?) .................... 2Gilgamish ................... 3in the plain .................. [219] 4his hair growing thickly like the corn. 5He came forth ... 6into his presence. 7They met in the wide park of the land. 8Enkidu held fast the door 9with his foot, 10and permitted not Gilgamish to enter. 11They grappled with each other 12goring like an ox. 13The threshold they destroyed. 14The wall they demolished. 15Gilgamish and Enkidu 16grappled with each other, 17goring like an ox. 18The threshold they destroyed. 19The wall they demolished. 20Gilgamish bowed 21to the ground at his feet 22and his javelin reposed. 23He turned back his breast. 24After he had turned back his breast, 25Enkidu unto that one 26spoke, even unto Gilgamish. 27“Even as one6 did thy mother 28bear thee, 29she the wild cow of the cattle stalls, 30Ninsunna, 31whose head she exalted more than a husband. [220] 32Royal power over the people 33Enlil has decreed for thee.” Second tablet. Written upon ... 240 (lines). [221] 1 Literally “he attained my front.” 2 IV¹ of walādu. 3 I.e., in the suburb of Erech. 4 patāḳu has apparently the same sense originally as batāḳu, although the one forms its preterite iptiḳ, and the other ibtuḳ. Cf. also maḫāṣu break, hammer and construct. 5 The passage is obscure. Here šuḫuru is taken as a loan-word from suģur = ḳimmatu, hair of the head. The infinitive II¹ of saḫāru is philologically possible. 6 I.e., an ordinary man. Index to Parts 2 and 3 A. Adab, city, 123, 23. addi, wailing, 117, 31; 137, 22; 161, 12. aḫu, brother, 212, 36. Aja, goddess, 198, 9. al (giš), al-gar (giš), a musical instrument, 187–191. See also No. 20 Rev. 7–12. al-bi, compound verb, 189 n. 6. In Ni. 8164 (unpublished) al-gar, al-gar-balag in list with (giš)-á-lá, also an instrument of music. alad, protecting genius, 154, 18. ameliš, like a man, 215, 25. Amurrû, god. Psalm to, 118; 119. angubba, sentinel, 180, 14. Anu, god. 116, 18:26 ff. 131, 8; 165, 9; 180, 20. Anunnaki, gods, 114, 17:21; 116, 25; 116 n. 7; 128, 13; 135, 31; 189, 21. Anunit, goddess, 158, 12; 166, 2. apunnatu, nostrils, pitiḳ, apunnāti, 217, 28. aṣṣammim (?), 215, 18. Arallû, 132, 26; 134, 7. arāmu, cover, 198 n. 2. arāḳu, be pale, Prt. iriku, 217, 31. arḫiš, quickly, 199, 28. Aruru, goddess. Lamentation to, 115. Sister of Enlil, 115, 2; 171, 29; 190, 25. Other references, 116, 13:15:18; 117, 34 f. Asarludug, god, 163, 8; 170, 4. Aš-im-ur, title of Moon-god, 136, 12. áš omitted, No. 19, 2. aš-me, disk, 133, 38. Ašširgi, god, No. 22, Rev. 7. Azagsud, goddess, 196, 30:33; 197, 38. B. Babbar, god, 116, 24; 139, 43; 147, 21; 148, 3; 152. Babylon, city, 158, 14; 160, 6; 163, 8; 166, 4:11. badara, see 200 n. 2. badarani, a weapon, 133, 36. balag, lyre, 138, 52. bansur, table; title of a goddess, 175, 3. Bau, goddess, 179, 2; 181, 30; 182, 32; 141, 7:10. bišîtu, condition, 215, 14. bi’u, cavern, 196, 29. bulukku, crab, 174, 5. burgul, engraver, 185, 8. C. Cutha, city. Center of the cult of Nergal, 167, 15. D. Dada, god, 192, 6. Dagan, West Semitic god, 149, 21. Damu, title of Tammuz, 176, 7. Deification of kings, 106–9; 127 n. 1. dêpu, shatter, 195 n. 16. [222] DI-BAL, ideogram in incantations, 194, 10. Dilbat, city, 167, 16. Dilmun, land and city, 112, 2:4. dimgul, dimdul, master workman, 150. dingir-gal-gal-e-ne, the great gods, the Anunnaki, 114, 21:125; 149, 19. dumu-anna, daughter of heaven, title of Bau, 179, 5; 181, 28; 184, 28. dumu-sag, title of Tašmet, 163, 12. Dungi, king of Ur, liturgy to, 136. dupšakku, trencher basket, 216, 17. Duranki, epithet for Nippur, 122, 18; 180, 11. E. E-anna, temple in Erech, 123, 30; 125; 148, 12; 213, 18. E-babbar, temple of the sun god, 152; 158, 11; 166, 1. Perhaps read E-barra. E-daranna, temple of Enki in Babylon, 169, 25; 170, 29. See BL. 133. edēlu = edēru, be gloomy, 216, 10. é-dub, house of learning, 117, 39. é-gal, palace, No. 19, Rev. 3; 115, 11; 131, 7; 134, 22; 158, 9. é-gig = ḳiṣṣu, 191, 11. E-ibe-Anu, temple in Dilbat, 167, 16. E-kinammaka, temple, 115, 10. E-kišibba, temple in Kish, 166, 13. E-kur, temple, 180, 12; 183, 23; 190, 7; 146, 9; 147, 17; 158, 8; 160, 4; 166, 17; 169, 23. Emaḫ, Ešmaḫ, ritual house of the water cult of Marduk, 163, 7; 115, 4. E-malga-sud, temple, 181, 24; 141, 3. E-meteg, daughter of Ninkasi, 144. E-mete-ursag, temple in Kish, 166, 13. E-namtila, temple, 160, 4; 169, 24. en-a-nu-un, en-á-nun, title of Innini and Gula, 173, 2. Enbilulu, title of Marduk, 170, 5. E-ninnû, temple, 181, 22. EN-ḪUL-tim-mu, 194 n. 2. EN-KA-KA, bêl dabābi, 194, 2. Enki, god. Hymn to, No. 20, 113, 7; 114, 10; 116, 21; 122, 7; 149, 16. Enkidu, satyr, 213, 3:7:10:11; 214, 6; 215, 11:12:15:34; 216, 13; 219, 8:15:25; 131, 11; 134, 16; 178, 13. Enlil, god. Liturgy to, 155–184. Regarded as god of light, 157, 1 ff. 158, 3 f. Other references, 114, 19; 115, 2; 116, 19; 131, 6; 136, 5; 139, 40; 149, 22; 146, 3:7:14; 189, 11:19; 220, 33. Enul, god, 149, 16. Enzu, god, 139, 41; 146, 3. epšānu, deeds, 218, 18. epû, be dark, I² itêpû, 196, 29. Erech, city, 125; 149, 13. Erech ribîtim, 212, 28; 213, 15; 217, 19:21; 217, 3:6. eri-azag, holy city, Isin, 141, 8. erida, title, 175, 1. Eridu, city, 113, 20; 136, 13. Erishkigal, goddess, 131, 10; 134, 11. eršagtugmal, penitential psalm, 118. E-sagila, temple, 152. E-sakudkalamma, temple, 166, 10; 169 n. 4. ešendili, a title, 177, 10. [223] eškar, fixed tax, 188, 9. eš-lal, a sacred place, 161, 14. E-temen-anki, temple, 169, 25. E-turkalamma, temple, 166, 14. Euphrates, river, 183, 12; 183, 20. E-zida, temple, 166, 12. Ezina, grain goddess, 174, 9. Ezira, reading of the divine name KA-DI, 177, 11. F. Fara, modern Arabic name for the site of Isin (?), 177 n. 4. G. GAB, baked bread, 200, 33. GAB-LAL, a cake made with honey, 195, 22; 200, 35. GAR-šunnu = epišan-šunu, 198, 13. gašan-gula, title of Ninâ, 119 n. 2. gepar, dark chamber, 123, 30 f., 148, 10; 161, 18. Gibil, god, 197, 3. gi-gál(giš),interlude, 151 n. 1; 182, 33. gigunna, 114, 23. Gilgamish, king of Erech, 207; 211, 1:115 f. 212, 17:37; 213, 2; 217, 21; 218, 9:20:24:29 and below 2; 219, 10;15:20:26. Derivation of name, 208. See also No. 16 Rev. II 15; 197, 42; 124 f. gilsa, a sacred relic, 132, 22. Girra, Irra, god, 174, 7; 177, 12. girru, lion, 215, 29. Girsu, city, 181, 23. Guanna, deity, No. 16 Rev. II 18. Guedin, province, 129, 28. Gunura, goddess of healing, 176, 6. gupru, mighty, 214, 33. Gutium, land, 120 ff. H. Hallab, city, 125; 141. ḫanābu, grow thickly, Prs. ibannib, 219, 4. ḫapāpu, embrace, 212, 34. ḫaṣṣinu, axe, 212, 29:31. ḫarbatu, waste place, 200, 39. Harsagkalamma, temple, 166, 14. Hubur, mythical river, 197, 42. ḫûlu, a bird, 199, 31. ḫûḳu, a bird, 199, 31. I. Ibi-Sin, king of Ur, 151 n. 2. ibsi, liturgical expression, 120, 5. Igigi, heaven spirits, 116 n. 6. IGI-NAGIN-NA, 194, 11. imib, weapon, 131, 8. mi-ib, ibid. n.3. imin, seven. Seven lands, 130, 35; seventh day, 134, 18. Immer, god, 177, 8. Indag, god, consort of Gula, 173, 3. Innini, goddess, 123. Liturgy to, 184; 123, 29. Consort of Shamash, 148, 4. Other references, 154, 21. iṣṣur šamê, unclean birds, 195 n. 10. Išhara, goddess, 218, 22. Isin, city, 122, 15; 176, 4. Ishme-Dagan, 178 ff. Son of Enlil, 181, 29; 182, 32. Liturgy to, 143. K. KA-DIB-BI, sibit pî, 194, 10. KAK-DIG, a weapon, 130, 4. kakkitu (?), weapon. Pl. kakkiatum, 218, 16. KAK-SIR, a weapon (?), 130, 4. [121] kalama, the Land, Sumer, 138, 25; 141, 5; 147, 22; 150, 4; 154, 17; 177, 9. kanami=kalama, land, 120, 8. KA-NE, a new ideograph, 153 n. 10. kasû, bind. I² liktisu, 198, 20. Kenurra, chapel of Ninlil, 114, 22; 123, 20; 160, 4; 166, 18; 166, 8; 169, 24. Keš, city, 115, 11; 123, 22. kešda-azag, a relic, 132, 27. ki, kin for gim = kima, 120, 6. KI-AG-MAL, râmu, 194 n. 4. Kidurkazal, daughter of Ninkasi, 145. ki-malla, to bend. tig-zu ki-ma-al-la nu-gí-gí, “Thy neck wearies not in bending,” 168, 2. [Correct the translation.] ki-in-gin, ki-en-gin, Sumer, 115, 24; 134, 19; 189, 17. KI-SAR, ḳaḳḳara tašabbiṭ, 199, 29. Kish, city, 129, 30; 166, 12. é kiš-(ki)-šú, so read, No. 5 Obv. 8. Kullab, city, 149, 14; 173, 1. kunin, gunin, reed basket, 150 n. 3. kurgal, “great mountain,” title of Sumer, 114, 11. Of Enlil, 114, 19; 182, 5. KURUN-NA, (amelu), 196, 34. KUŠ-KU-MAL, 194, 11. L. la’aṭu, gore. Prt. ilûdu, 219, 12:17. labu, panther, 215, 29:32. Lagash, city, 181, 23:26. Laḫama, goddess of Chaos, 113, 5. Laws, promulgated by Dungi, 138, 31. Libit-Ishtar, king, 141. libšu, garment, 214, 27:29; 215, 26. Ligirsig, a god, 113, 3. lilazag, epithet of a deified king, 141, 1. Lillaenna, goddess, 192, 5. limēnu, be evil. II¹ ulammenu-inni, 197, 7. Lugal-dīg, god, 197, 5. lu’ûtu, pollution, 195, 19. M. Magan, land, 112, 2:5. mai̭ālu, couch, 218, 22. malāšu, shear, 195, 20. Mamit, 200, 41. mandatu, form, 195, 21. mal-gar (gi), a musical instrument, 191, 10. mangu, disease, 195, 19. Marduk, god, 151. markasu, leader, 150. masû, seize, 195 n. 5. mašû, to forget, 216, 7. Me-azag, daughter of Ninkasi, 144. meḫru, fellow, 218, 21. Meḫuš, daughter of Ninkasi, 144. Meluḫḫa, land, 112, 6. Meslam, temple in Cutha, 167, 15. mesû, a tree, 159, 23. muk, now, but now, 217, 26. Mulgenna, Saturn, 137, 18. Mulmul, gods, 142. N. nâdu, water bottle, 198, 17. nadîtu, temple devotee, 188, 7. nagû, shout. Prs. inangu, 215, 19. nâku, embrace, 218, 26. namaštû, cattle, etc., 213, 12:17; 214, 1; 219, 14. Namtar, god, 197, 3; 132, 24. Nangt, goddess, 192, 7. [225] Nannar, god, 115, 12; 116, 23; 133, 38; 137, 11; 150, 2. Nergal, god, 131, 6. Nidaba, goddess, 191. ni-gál, cattle, 121, 6. nimir = ligir, 174, 4. ninda, linear measure, 133, 41. Ningal, goddess, No. 19, 5; 148, 3; 151, 3. Ningišzida, god, 133, 34. Nin-isinna, goddess, 122, 16; 191, 15. Ninkasi, goddess, 144. Ninki, goddess, 149, 16. Ninlil, goddess, 116, 20; 123, 20; 137, 12; 146, 14. Ninmada, daughter of Ninkasi, 144. Ninmaḫ, goddess, 116, 22. Ninmenna, epithet of Damgalnunna, 190, 27. Ninsun, goddess, 219, 30; 208 n. 6; 129; 131, 16 (?). Nintudri, goddess, 123, 26. Nintudra, 137, 16. Creatress of man and woman, 192. Ninul, goddess, 149, 16. Ninurašâ, god, 191, 12; 146, 12. Ninzuanna, goddess, 122, 13. Nippur, city, 112, 8; 122, 18:19; 160, 3; 169, 21; 180, 11; 149, 18; 158, 7; 165, 16. NI-SUR (amelu), 196, 35. Nudimmud, god, 199, 25. No. 20, 10. nugiganna, epithet of Innini, 185, 2. nûn apsi, unclean fish, 195 n. 11. Nunamnirri, god, 190, 28; 146, 13; 180, 10:13:17. nun-ùr, epithet of Amurrû, 119, 3. Nusiligga, daughter of Ninkasi, 144. Nusku, god, 146, 7; 163, 13. P. Pabilsag, god. Son and consort of Gula, 173 n. 3; 176, 5. A form of Tammuz. pananumma, formerly, 217, 25. Panunnaki, goddess, consort of Marduk, 163, 9. patāḳu, fashion, break, 214, 4. paturru, a weapon, 200, 37. Pleiades, 142. R. ratātu, demolish, 219, 19. Rimat ilatNinsun, 208 n. 6; 219, 29. Ruškišag, goddess, 132, 28. RU-TIG, an epithet, 141, 2. S. sa-bar; sa-sud-da, liturgical note, 182, 31. šabšiš, cruelly, 215, 30. Sagilla, temple, 158, 15. E-sagila, 160, 5; 166, 5; 166, 11. šaḫātu, be astounded, 216, 10. Arabic saḫiṭa. ṣai̭āḫatu, desire, comfort, 216, 18. šakāpu, fell. I² išsakpu, 215, 30. ṣalûtu, enmity, 199, 27. Šamaš, god, 197, 4:8; 198, 10:13; 199, 25:31. Šamaš-šum-ukin, king. Incantations for, 193–200; 199, 23. Samsuiluna, king, 151. SAR-DI-DA, a relic, 133, 37. Serpent adversary, 183, 21; 148, 12. Seven, sacred number. Seven gods, 196, 30. Ship, in legend, 113, 2. Silsirsir, a chapel. Sin, god. Hymn to, No. 19. sippu, threshold, 219, 13:18. [226] Sippar, city, 158, 10; 160, 5; 166, 19. sirgidda, long song, 140, 54. Siriš, daughter of Ninkasi, 144. Siriškaš, daughter of Ninkasi, 144. Siriškašgig, daughter of Ninkasi, 144. sirsagga, first melody, 117, 28; 139, 48. ŠU-AN = kat ili, 194, 12. See also ŠU-dINNINI, 194, 12. ŠU-NAM-ERIM-MA, 194, 13. ŠU-NAM-LU-GAL-LU, 194, 13. subura, earth, 175, 3. su-ud, sú-ud-ám, epithet of goddess of Šuruppak, 177, 10 and note 4. šuḫuru, hair (?), 215, 23. sukkal-zid, title of Nebo, 163, 10. Šulpae, god, No. 16 II 22. Sumer, land, 113, 21; 114, 11; 136, 2. sumugan, title of Girra, 177, 12 and note; 179, 3. T. Tablet of fates, 132 n. 3. Tammuz, ancient ruler, 208. Liturgy to, 191. Other references, 126; 208; 131, 20. tapāšu, seize, capture, II² uttappiš, 215, 31. temēru, cook, 196, 35. Tigris, river, 183, 12. Tummal, land, 190, 9; 191, 10. U. ud, spirit, word, 150, 1:4; 158, 16; 159, 17:24. ul-al-tar, 191 n. 6. ulinnu, girdle cord, 195, 20. Ulmaš, temple of Anunit, 158, 13; 166, 3. Ur, city, 134, 21; 137, 6. Lamentation for, 150. Other references, No. 19, 4:7:8:16:28: Rev. 5; 151, 3. Ur-azag, king of Isin (?), 140 n. 2. Ur-Engur, king of Ur, 126 ff. urinu, spear (?), 173, 3. ursaggal, epithet for Ninurašā, 165, 11. For Enbilulu, 170, 5. ušumgal, 117, 33. Z. zâbu, flow. li-zu-bu, 198, 16. Cf. gàm = za’ibu, miṭirtu, words for canal, SAI. 691–3. zag-sal, liturgical note, 103 f. No. 21 end. za-am, 138, 34; 139, 38; 140, 56. zênu, be enraged, II¹ uzinu-inni, 197, 6. ZI-TAR-RU-DA = nikis napišti, 194 n. 6. [124] Description of Tablets Number in this volume. 1 Museum number. 7771 Description. Dark brown unbaked tablet. Three columns. Lower edge slightly broken. Knobs at left upper and left lower corners to facilitate the holding of the tablet. H. 7 inches: W. 6½; T. 1½. Second tablet of the Epic of Gilgamish. [125] Autograph Plates Plate LXIII. Plate LXIV. Plate LXV. Plate LXVI. Plate LXVII. Plate LXVIII. Plate LXIX. Tablet of the Gilgamish Epic (Obverse) Plate LXX. Tablet of the Gilgamish Epic (Reverse) *** END OF THE PROJECT GUTENBERG EBOOK THE EPIC OF GILGAMISH ***

      Comparing this version of the Babylonian text, there is a greater focus on when Gilgamesh was with Enkidu on how he was a great companion for him. Dreams are seen as divine in Mesopotamian culture so it is interesting that Gilgamesh was able to foreshadow the presence of Enkidu ahead of time. Because of this dream, it shows that it was a part of destiny for Gilgamesh to find his equal and was a journey for his own identity to become what it is now. Not to mention, Enkidu becoming tame as time went along and reforming into societal norms shows that outsiders can be assimilated and that is what is needed in many nations in order for them to be successful and functional. One instance of us vs them situation would be for Enkidu. He was a wild man at first which was very different from "them" which were the Uruk people as they were calm and controlled. The transition for Enkidu to becoming like the others were crucial if he wanted to be a companion of Gilgamesh and also become a figure that would be respected by others. It also points to the fact that people need to be like others to some extent in order to be liked and respected. Because Enkidu and Gilgamesh are the only prominent characters that are also male, it suggests that during this time period that females were inferior to some extent and did not hold the same respect or regard because they were unable to showcase their own skills or talents. This may have affected the way that the text is written because the perspective of males can contrast those of women because they tend to be more caring and honest. Not to mention, the other translations of the text mention more about Gilgamesh's longing for immortality so the absence or lack of information on that aspect creates a more biased view of Enkidu and alters the way that Gilgamesh is viewed as well. The low point of the text has to be more in the beginning when the people are complaining about the rule of Gilgamesh because he does not contain the same qualities of a good leader that he obtains later on. With that being the case, the text reaches a high point when Gilgamesh sees Enkidu as an equal to himself and embraces him as a companion which allows him to be a much better leader and also allows the people in his land to feel better as a result. CC BY Ajey Sasimugunthan (contact)

    1. The Gilgamesh Epic is the most notable literary product of Babylonia as yet discovered in the mounds of Mesopotamia. It recounts the exploits and adventures of a favorite hero, and in its final form covers twelve tablets, each tablet consisting of six columns (three on the obverse and three on the reverse) of about 50 lines for each column, or a total of about 3600 lines. Of this total, however, barely more than one-half has been found among the remains of the great collection of cuneiform tablets gathered by King Ashurbanapal (668–626 B.C.) in his palace at Nineveh, and discovered by Layard in 18541 in the course of his excavations of the mound Kouyunjik (opposite Mosul). The fragments of the epic painfully gathered—chiefly by George Smith—from the circa 30,000 tablets and bits of tablets brought to the British Museum were published in model form by Professor Paul Haupt;2 and that edition still remains the primary source for our study of the Epic. [10] For the sake of convenience we may call the form of the Epic in the fragments from the library of Ashurbanapal the Assyrian version, though like most of the literary productions in the library it not only reverts to a Babylonian original, but represents a late copy of a much older original. The absence of any reference to Assyria in the fragments recovered justifies us in assuming that the Assyrian version received its present form in Babylonia, perhaps in Erech; though it is of course possible that some of the late features, particularly the elaboration of the teachings of the theologians or schoolmen in the eleventh and twelfth tablets, may have been produced at least in part under Assyrian influence. A definite indication that the Gilgamesh Epic reverts to a period earlier than Hammurabi (or Hammurawi)3 i.e., beyond 2000 B. C., was furnished by the publication of a text clearly belonging to the first Babylonian dynasty (of which Hammurabi was the sixth member) in CT. VI, 5; which text Zimmern4 recognized as a part of the tale of Atra-ḫasis, one of the names given to the survivor of the deluge, recounted on the eleventh tablet of the Gilgamesh Epic.5 This was confirmed by the discovery6 of a [11]fragment of the deluge story dated in the eleventh year of Ammisaduka, i.e., c. 1967 B.C. In this text, likewise, the name of the deluge hero appears as Atra-ḫasis (col. VIII, 4).7 But while these two tablets do not belong to the Gilgamesh Epic and merely introduce an episode which has also been incorporated into the Epic, Dr. Bruno Meissner in 1902 published a tablet, dating, as the writing and the internal evidence showed, from the Hammurabi period, which undoubtedly is a portion of what by way of distinction we may call an old Babylonian version.8 It was picked up by Dr. Meissner at a dealer’s shop in Bagdad and acquired for the Berlin Museum. The tablet consists of four columns (two on the obverse and two on the reverse) and deals with the hero’s wanderings in search of a cure from disease with which he has been smitten after the death of his companion Enkidu. The hero fears that the disease will be fatal and longs to escape death. It corresponds to a portion of Tablet X of the Assyrian version. Unfortunately, only the lower portion of the obverse and the upper of the reverse have been preserved (57 lines in all); and in default of a colophon we do not know the numeration of the tablet in this old Babylonian edition. Its chief value, apart from its furnishing a proof for the existence of the Epic as early as 2000 B. C., lies (a) in the writing Gish instead of Gish-gi(n)-mash in the Assyrian version, for the name of the hero, (b) in the writing En-ki-dũ—abbreviated from dũg—() “Enki is good” for En-ki-dú () in the Assyrian version,9 and (c) in the remarkable address of the maiden Sabitum, dwelling at the seaside, to whom Gilgamesh comes in the course of his wanderings. From the Assyrian version we know that the hero tells the maiden of his grief for his lost companion, and of his longing to escape the dire fate of Enkidu. In the old Babylonian fragment the answer of Sabitum is given in full, and the sad note that it strikes, showing how hopeless it is for man to try to escape death which is in store for all mankind, is as remarkable as is the philosophy of “eat, drink and be merry” which Sabitum imparts. The address indicates how early the tendency arose to attach to ancient tales the current religious teachings. [12] “Why, O Gish, does thou run about? The life that thou seekest, thou wilt not find. When the gods created mankind, Death they imposed on mankind; Life they kept in their power. Thou, O Gish, fill thy belly, Day and night do thou rejoice, Daily make a rejoicing! Day and night a renewal of jollification! Let thy clothes be clean, Wash thy head and pour water over thee! Care for the little one who takes hold of thy hand! Let the wife rejoice in thy bosom!” Such teachings, reminding us of the leading thought in the Biblical Book of Ecclesiastes,10 indicate the didactic character given to ancient tales that were of popular origin, but which were modified and elaborated under the influence of the schools which arose in connection with the Babylonian temples. The story itself belongs, therefore, to a still earlier period than the form it received in this old Babylonian version. The existence of this tendency at so early a date comes to us as a genuine surprise, and justifies the assumption that the attachment of a lesson to the deluge story in the Assyrian version, to wit, the limitation in attainment of immortality to those singled out by the gods as exceptions, dates likewise from the old Babylonian period. The same would apply to the twelfth tablet, which is almost entirely didactic, intended to illustrate the impossibility of learning anything of the fate of those who have passed out of this world. It also emphasizes the necessity of contenting oneself with the comfort that the care of the dead, by providing burial and food and drink offerings for them affords, as the only means of ensuring for them rest and freedom from the pangs of hunger and distress. However, it is of course possible that the twelfth tablet, which impresses one as a supplement to the adventures of Gilgamesh, ending with his return to Uruk (i.e., Erech) at the close of the eleventh tablet, may represent a later elaboration of the tendency to connect religious teachings with the exploits of a favorite hero. [13] We now have further evidence both of the extreme antiquity of the literary form of the Gilgamesh Epic and also of the disposition to make the Epic the medium of illustrating aspects of life and the destiny of mankind. The discovery by Dr. Arno Poebel of a Sumerian form of the tale of the descent of Ishtar to the lower world and her release11—apparently a nature myth to illustrate the change of season from summer to winter and back again to spring—enables us to pass beyond the Akkadian (or Semitic) form of tales current in the Euphrates Valley to the Sumerian form. Furthermore, we are indebted to Dr. Langdon for the identification of two Sumerian fragments in the Nippur Collection which deal with the adventures of Gilgamesh, one in Constantinople,12 the other in the collection of the University of Pennsylvania Museum.13 The former, of which only 25 lines are preserved (19 on the obverse and 6 on the reverse), appears to be a description of the weapons of Gilgamesh with which he arms himself for an encounter—presumably the encounter with Ḫumbaba or Ḫuwawa, the ruler of the cedar forest in the mountain.14 The latter deals with the building operations of Gilgamesh in the city of Erech. A text in Zimmern’s Sumerische Kultlieder aus altbabylonischer Zeit (Leipzig, 1913), No. 196, appears likewise to be a fragment of the Sumerian version of the Gilgamesh Epic, bearing on the episode of Gilgamesh’s and Enkidu’s relations to the goddess Ishtar, covered in the sixth and seventh tablets of the Assyrian version.15 Until, however, further fragments shall have turned up, it would be hazardous to institute a comparison between the Sumerian and the Akkadian versions. All that can be said for the present is that there is every reason to believe in the existence of a literary form of the Epic in Sumerian which presumably antedated the Akkadian recension, [14]just as we have a Sumerian form of Ishtar’s descent into the nether world, and Sumerian versions of creation myths, as also of the Deluge tale.16 It does not follow, however, that the Akkadian versions of the Gilgamesh Epic are translations of the Sumerian, any more than that the Akkadian creation myths are translations of a Sumerian original. Indeed, in the case of the creation myths, the striking difference between the Sumerian and Akkadian views of creation17 points to the independent production of creation stories on the part of the Semitic settlers of the Euphrates Valley, though no doubt these were worked out in part under Sumerian literary influences. The same is probably true of Deluge tales, which would be given a distinctly Akkadian coloring in being reproduced and steadily elaborated by the Babylonian literati attached to the temples. The presumption is, therefore, in favor of an independent literary origin for the Semitic versions of the Gilgamesh Epic, though naturally with a duplication of the episodes, or at least of some of them, in the Sumerian narrative. Nor does the existence of a Sumerian form of the Epic necessarily prove that it originated with the Sumerians in their earliest home before they came to the Euphrates Valley. They may have adopted it after their conquest of southern Babylonia from the Semites who, there are now substantial grounds for believing, were the earlier settlers in the Euphrates Valley.18 We must distinguish, therefore, between the earliest literary form, which was undoubtedly Sumerian, and the origin of the episodes embodied in the Epic, including the chief actors, Gilgamesh and his companion Enkidu. It will be shown that one of the chief episodes, the encounter of the two heroes with a powerful guardian or ruler of a cedar forest, points to a western region, more specifically to Amurru, as the scene. The names of the two chief actors, moreover, appear to have been “Sumerianized” by an artificial process,19 and if this view turns out to be [15]correct, we would have a further ground for assuming the tale to have originated among the Akkadian settlers and to have been taken over from them by the Sumerians. New light on the earliest Babylonian version of the Epic, as well as on the Assyrian version, has been shed by the recovery of two substantial fragments of the form which the Epic had assumed in Babylonia in the Hammurabi period. The study of this important new material also enables us to advance the interpretation of the Epic and to perfect the analysis into its component parts. In the spring of 1914, the Museum of the University of Pennsylvania acquired by purchase a large tablet, the writing of which as well as the style and the manner of spelling verbal forms and substantives pointed distinctly to the time of the first Babylonian dynasty. The tablet was identified by Dr. Arno Poebel as part of the Gilgamesh Epic; and, as the colophon showed, it formed the second tablet of the series. He copied it with a view to publication, but the outbreak of the war which found him in Germany—his native country—prevented him from carrying out this intention.20 He, however, utilized some of its contents in his discussion of the historical or semi-historical traditions about Gilgamesh, as revealed by the important list of partly mythical and partly historical dynasties, found among the tablets of the Nippur collection, in which Gilgamesh occurs21 as a King of an Erech dynasty, whose father was Â, a priest of Kulab.22 The publication of the tablet was then undertaken by Dr. Stephen Langdon in monograph form under the title, “The Epic of Gilgamish.”23 In a preliminary article on the tablet in the Museum Journal, Vol. VIII, pages 29–38, Dr. Langdon took the tablet to be of the late [16]Persian period (i.e., between the sixth and third century B. C.), but his attention having been called to this error of some 1500 years, he corrected it in his introduction to his edition of the text, though he neglected to change some of his notes in which he still refers to the text as “late.”24 In addition to a copy of the text, accompanied by a good photograph, Dr. Langdon furnished a transliteration and translation with some notes and a brief introduction. The text is unfortunately badly copied, being full of errors; and the translation is likewise very defective. A careful collation with the original tablet was made with the assistance of Dr. Edward Chiera, and as a consequence we are in a position to offer to scholars a correct text. We beg to acknowledge our obligations to Dr. Gordon, the Director of the Museum of the University of Pennsylvania, for kindly placing the tablet at our disposal. Instead of republishing the text, I content myself with giving a full list of corrections in the appendix to this volume which will enable scholars to control our readings, and which will, I believe, justify the translation in the numerous passages in which it deviates from Dr. Langdon’s rendering. While credit should be given to Dr. Langdon for having made this important tablet accessible, the interests of science demand that attention be called to his failure to grasp the many important data furnished by the tablet, which escaped him because of his erroneous readings and faulty translations. The tablet, consisting of six columns (three on the obverse and three on the reverse), comprised, according to the colophon, 240 lines25 and formed the second tablet of the series. Of the total, 204 lines are preserved in full or in part, and of the missing thirty-six quite a number can be restored, so that we have a fairly complete tablet. The most serious break occurs at the top of the reverse, where about eight lines are missing. In consequence of this the connection between the end of the obverse (where about five lines are missing) and the beginning of the reverse is obscured, though not to the extent of our entirely losing the thread of the narrative. [17] About the same time that the University of Pennsylvania Museum purchased this second tablet of the Gilgamesh Series, Yale University obtained a tablet from the same dealer, which turned out to be a continuation of the University of Pennsylvania tablet. That the two belong to the same edition of the Epic is shown by their agreement in the dark brown color of the clay, in the writing as well as in the size of the tablet, though the characters on the Yale tablet are somewhat cramped and in consequence more difficult to read. Both tablets consist of six columns, three on the obverse and three on the reverse. The measurements of both are about the same, the Pennsylvania tablet being estimated at about 7 inches high, as against 72/16 inches for the Yale tablet, while the width of both is 6½ inches. The Yale tablet is, however, more closely written and therefore has a larger number of lines than the Pennsylvania tablet. The colophon to the Yale tablet is unfortunately missing, but from internal evidence it is quite certain that the Yale tablet follows immediately upon the Pennsylvania tablet and, therefore, may be set down as the third of the series. The obverse is very badly preserved, so that only a general view of its contents can be secured. The reverse contains serious gaps in the first and second columns. The scribe evidently had a copy before him which he tried to follow exactly, but finding that he could not get all of the copy before him in the six columns, he continued the last column on the edge. In this way we obtain for the sixth column 64 lines as against 45 for column IV, and 47 for column V, and a total of 292 lines for the six columns. Subtracting the 16 lines written on the edge leaves us 276 lines for our tablet as against 240 for its companion. The width of each column being the same on both tablets, the difference of 36 lines is made up by the closer writing. Both tablets have peculiar knobs at the sides, the purpose of which is evidently not to facilitate holding the tablet in one’s hand while writing or reading it, as Langdon assumed26 (it would be quite impracticable for this purpose), but simply to protect the tablet in its position on a shelf, where it would naturally be placed on the edge, just as we arrange books on a shelf. Finally be it noted that these two tablets of the old Babylonian version do not belong to the same edition as the Meissner tablet above described, for the latter consists [18]of two columns each on obverse and reverse, as against three columns each in the case of our two tablets. We thus have the interesting proof that as early as 2000 B.C. there were already several editions of the Epic. As to the provenance of our two tablets, there are no definite data, but it is likely that they were found by natives in the mounds at Warka, from which about the year 1913, many tablets came into the hands of dealers. It is likely that where two tablets of a series were found, others of the series were also dug up, and we may expect to find some further portions of this old Babylonian version turning up in the hands of other dealers or in museums. Coming to the contents of the two tablets, the Pennsylvania tablet deals with the meeting of the two heroes, Gilgamesh and Enkidu, their conflict, followed by their reconciliation, while the Yale tablet in continuation takes up the preparations for the encounter of the two heroes with the guardian of the cedar forest, Ḫumbaba—but probably pronounced Ḫubaba27—or, as the name appears in the old Babylonian version, Ḫuwawa. The two tablets correspond, therefore, to portions of Tablets I to V of the Assyrian version;28 but, as will be shown in detail further on, the number of completely parallel passages is not large, and the Assyrian version shows an independence of the old Babylonian version that is larger than we had reason to expect. In general, it may be said that the Assyrian version is more elaborate, which points to its having received its present form at a considerably later period than the old Babylonian version.29 On the other hand, we already find in the Babylonian version the tendency towards repetition, which is characteristic of Babylonian-Assyrian tales in general. Through the two Babylonian tablets we are enabled to fill out certain details [19]of the two episodes with which they deal: (1) the meeting of Gilgamesh and Enkidu, and (2) the encounter with Ḫuwawa; while their greatest value consists in the light that they throw on the gradual growth of the Epic until it reached its definite form in the text represented by the fragments in Ashurbanapal’s Library. Let us now take up the detailed analysis, first of the Pennsylvania tablet and then of the Yale tablet. The Pennsylvania tablet begins with two dreams recounted by Gilgamesh to his mother, which the latter interprets as presaging the coming of Enkidu to Erech. In the one, something like a heavy meteor falls from heaven upon Gilgamesh and almost crushes him. With the help of the heroes of Erech, Gilgamesh carries the heavy burden to his mother Ninsun. The burden, his mother explains, symbolizes some one who, like Gilgamesh, is born in the mountains, to whom all will pay homage and of whom Gilgamesh will become enamoured with a love as strong as that for a woman. In a second dream, Gilgamesh sees some one who is like him, who brandishes an axe, and with whom he falls in love. This personage, the mother explains, is again Enkidu. Langdon is of the opinion that these dreams are recounted to Enkidu by a woman with whom Enkidu cohabits for six days and seven nights and who weans Enkidu from association with animals. This, however, cannot be correct. The scene between Enkidu and the woman must have been recounted in detail in the first tablet, as in the Assyrian version,30 whereas here in the second tablet we have the continuation of the tale with Gilgamesh recounting his dreams directly to his mother. The story then continues with the description of the coming of Enkidu, conducted by the woman to the outskirts of Erech, where food is given him. The main feature of the incident is the conversion of Enkidu to civilized life. Enkidu, who hitherto had gone about naked, is clothed by the woman. Instead of sucking milk and drinking from a trough like an animal, food and strong drink are placed before him, and he is taught how to eat and drink in human fashion. In human fashion he also becomes drunk, and his “spree” is naïvely described: “His heart became glad and his face shone.”31 [20]Like an animal, Enkidu’s body had hitherto been covered with hair, which is now shaved off. He is anointed with oil, and clothed “like a man.” Enkidu becomes a shepherd, protecting the fold against wild beasts, and his exploit in dispatching lions is briefly told. At this point—the end of column 3 (on the obverse), i.e., line 117, and the beginning of column 4 (on the reverse), i.e., line 131—a gap of 13 lines—the tablet is obscure, but apparently the story of Enkidu’s gradual transformation from savagery to civilized life is continued, with stress upon his introduction to domestic ways with the wife chosen or decreed for him, and with work as part of his fate. All this has no connection with Gilgamesh, and it is evident that the tale of Enkidu was originally an independent tale to illustrate the evolution of man’s career and destiny, how through intercourse with a woman he awakens to the sense of human dignity, how he becomes accustomed to the ways of civilization, how he passes through the pastoral stage to higher walks of life, how the family is instituted, and how men come to be engaged in the labors associated with human activities. In order to connect this tale with the Gilgamesh story, the two heroes are brought together; the woman taking on herself, in addition to the rôle of civilizer, that of the medium through which Enkidu is brought to Gilgamesh. The woman leads Enkidu from the outskirts of Erech into the city itself, where the people on seeing him remark upon his likeness to Gilgamesh. He is the very counterpart of the latter, though somewhat smaller in stature. There follows the encounter between the two heroes in the streets of Erech, where they engage in a fierce combat. Gilgamesh is overcome by Enkidu and is enraged at being thrown to the ground. The tablet closes with the endeavor of Enkidu to pacify Gilgamesh. Enkidu declares that the mother of Gilgamesh has exalted her son above the ordinary mortal, and that Enlil himself has singled him out for royal prerogatives. After this, we may assume, the two heroes become friends and together proceed to carry out certain exploits, the first of which is an attack upon the mighty guardian of the cedar forest. This is the main episode in the Yale tablet, which, therefore, forms the third tablet of the old Babylonian version. In the first column of the obverse of the Yale tablet, which is badly preserved, it would appear that the elders of Erech (or perhaps the people) are endeavoring to dissuade Gilgamesh from making the [21]attempt to penetrate to the abode of Ḫuwawa. If this is correct, then the close of the first column may represent a conversation between these elders and the woman who accompanies Enkidu. It would be the elders who are represented as “reporting the speech to the woman,” which is presumably the determination of Gilgamesh to fight Ḫuwawa. The elders apparently desire Enkidu to accompany Gilgamesh in this perilous adventure, and with this in view appeal to the woman. In the second column after an obscure reference to the mother of Gilgamesh—perhaps appealing to the sun-god—we find Gilgamesh and Enkidu again face to face. From the reference to Enkidu’s eyes “filled with tears,” we may conclude that he is moved to pity at the thought of what will happen to Gilgamesh if he insists upon carrying out his purpose. Enkidu, also, tries to dissuade Gilgamesh. This appears to be the main purport of the dialogue between the two, which begins about the middle of the second column and extends to the end of the third column. Enkidu pleads that even his strength is insufficient, “My arms are lame, My strength has become weak.” (lines 88–89) Gilgamesh apparently asks for a description of the terrible tyrant who thus arouses the fear of Enkidu, and in reply Enkidu tells him how at one time, when he was roaming about with the cattle, he penetrated into the forest and heard the roar of Ḫuwawa which was like that of a deluge. The mouth of the tyrant emitted fire, and his breath was death. It is clear, as Professor Haupt has suggested,32 that Enkidu furnishes the description of a volcano in eruption, with its mighty roar, spitting forth fire and belching out a suffocating smoke. Gilgamesh is, however, undaunted and urges Enkidu to accompany him in the adventure. “I will go down to the forest,” says Gilgamesh, if the conjectural restoration of the line in question (l. 126) is correct. Enkidu replies by again drawing a lurid picture of what will happen “When we go (together) to the forest…….” This speech of Enkidu is continued on the reverse. In reply Gilgamesh emphasizes his reliance upon the good will of Shamash and reproaches Enkidu with cowardice. He declares himself superior to Enkidu’s warning, and in bold terms [22]says that he prefers to perish in the attempt to overcome Ḫuwawa rather than abandon it. “Wherever terror is to be faced, Thou, forsooth, art in fear of death. Thy prowess lacks strength. I will go before thee, Though thy mouth shouts to me: ‘thou art afraid to approach,’ If I fall, I will establish my name.” (lines 143–148) There follows an interesting description of the forging of the weapons for the two heroes in preparation for the encounter.33 The elders of Erech when they see these preparations are stricken with fear. They learn of Ḫuwawa’s threat to annihilate Gilgamesh if he dares to enter the cedar forest, and once more try to dissuade Gilgamesh from the undertaking. “Thou art young, O Gish, and thy heart carries thee away, Thou dost not know what thou proposest to do.” (lines 190–191) They try to frighten Gilgamesh by repeating the description of the terrible Ḫuwawa. Gilgamesh is still undaunted and prays to his patron deity Shamash, who apparently accords him a favorable “oracle” (têrtu). The two heroes arm themselves for the fray, and the elders of Erech, now reconciled to the perilous undertaking, counsel Gilgamesh to take provision along for the undertaking. They urge Gilgamesh to allow Enkidu to take the lead, for “He is acquainted with the way, he has trodden the road [to] the entrance of the forest.” (lines 252–253) The elders dismiss Gilgamesh with fervent wishes that Enkidu may track out the “closed path” for Gilgamesh, and commit him to the care of Lugalbanda—here perhaps an epithet of Shamash. They advise Gilgamesh to perform certain rites, to wash his feet in the stream of Ḫuwawa and to pour out a libation of water to Shamash. Enkidu follows in a speech likewise intended to encourage the hero; and with the actual beginning of the expedition against Ḫuwawa the tablet ends. The encounter itself, with the triumph of the two heroes, must have been described in the fourth tablet. [23] Now before taking up the significance of the additions to our knowledge of the Epic gained through these two tablets, it will be well to discuss the forms in which the names of the two heroes and of the ruler of the cedar forest occur in our tablets. As in the Meissner fragment, the chief hero is invariably designated as dGish in both the Pennsylvania and Yale tablets; and we may therefore conclude that this was the common form in the Hammurabi period, as against the writing dGish-gì(n)-mash34 in the Assyrian version. Similarly, as in the Meissner fragment, the second hero’s name is always written En-ki-dũ35 (abbreviated from dúg) as against En-ki-dú in the Assyrian version. Finally, we encounter in the Yale tablet for the first time the writing Ḫu-wa-wa as the name of the guardian of the cedar forest, as against Ḫum-ba-ba in the Assyrian version, though in the latter case, as we may now conclude from the Yale tablet, the name should rather be read Ḫu-ba-ba.36 The variation in the writing of the latter name is interesting as pointing to the aspirate pronunciation of the labial in both instances. The name would thus present a complete parallel to the Hebrew name Ḫowawa (or Ḫobab) who appears as the brother-in-law of Moses in the P document, Numbers 10, 29.37 Since the name also occurs, written precisely as in the Yale tablet, among the “Amoritic” names in the important lists published by Dr. Chiera,38 there can be no doubt that [24]Ḫuwawa or Ḫubaba is a West Semitic name. This important fact adds to the probability that the “cedar forest” in which Ḫuwawa dwells is none other than the Lebanon district, famed since early antiquity for its cedars. This explanation of the name Ḫuwawa disposes of suppositions hitherto brought forward for an Elamitic origin. Gressmann39 still favors such an origin, though realizing that the description of the cedar forest points to the Amanus or Lebanon range. In further confirmation of the West Semitic origin of the name, we have in Lucian, De Dea Syria, § 19, the name Kombabos40 (the guardian of Stratonika), which forms a perfect parallel to Ḫu(m)baba. Of the important bearings of this western character of the name Ḫuwawa on the interpretation and origin of the Gilgamesh Epic, suggesting that the episode of the encounter between the tyrant and the two heroes rests upon a tradition of an expedition against the West or Amurru land, we shall have more to say further on. The variation in the writing of the name Enkidu is likewise interesting. It is evident that the form in the old Babylonian version with the sign dũ (i.e., dúg) is the original, for it furnishes us with a suitable etymology “Enki is good.” The writing with dúg, pronounced dū, also shows that the sign dú as the third element in the form which the name has in the Assyrian version is to be read dú, and that former readings like Ea-bani must be definitely abandoned.41 The form with dú is clearly a phonetic writing of the Sumerian name, the sign dú being chosen to indicate the pronunciation (not the ideograph) of the third element dúg. This is confirmed by the writing En-gi-dú in the syllabary CT XVIII, 30, 10. The phonetic writing is, therefore, a warning against any endeavor to read the name by an Akkadian transliteration of the signs. This would not of itself prove that Enkidu is of Sumerian origin, for it might well be that the writing En-ki-dú is an endeavor to give a Sumerian aspect to a name that may have been foreign. The element dúg corresponds to the Semitic ṭâbu, “good,” and En-ki being originally a designation of a deity as the “lord of the land,” which would be the Sumerian [25]manner of indicating a Semitic Baal, it is not at all impossible that En-ki-dúg may be the “Sumerianized” form of a Semitic בַּעל טזֹב “Baal is good.” It will be recalled that in the third column of the Yale tablet, Enkidu speaks of himself in his earlier period while still living with cattle, as wandering into the cedar forest of Ḫuwawa, while in another passage (ll. 252–253) he is described as “acquainted with the way … to the entrance of the forest.” This would clearly point to the West as the original home of Enkidu. We are thus led once more to Amurru—taken as a general designation of the West—as playing an important role in the Gilgamesh Epic.42 If Gilgamesh’s expedition against Ḫuwawa of the Lebanon district recalls a Babylonian campaign against Amurru, Enkidu’s coming from his home, where, as we read repeatedly in the Assyrian version, “He ate herbs with the gazelles, Drank out of a trough with cattle,”43 may rest on a tradition of an Amorite invasion of Babylonia. The fight between Gilgamesh and Enkidu would fit in with this tradition, while the subsequent reconciliation would be the form in which the tradition would represent the enforced union between the invaders and the older settlers. Leaving this aside for the present, let us proceed to a consideration of the relationship of the form dGish, for the chief personage in the Epic in the old Babylonian version, to dGish-gi(n)-mash in the Assyrian version. Of the meaning of Gish there is fortunately no doubt. It is clearly the equivalent to the Akkadian zikaru, “man” (Brünnow No. 5707), or possibly rabû, “great” (Brünnow No. 5704). Among various equivalents, the preference is to be given to itlu, “hero.” The determinative for deity stamps the person so designated as deified, or as in part divine, and this is in accord with the express statement in the Assyrian version of the Gilgamesh Epic which describes the hero as “Two-thirds god and one-third human.”44 [26]Gish is, therefore, the hero-god par excellence; and this shows that we are not dealing with a genuine proper name, but rather with a descriptive attribute. Proper names are not formed in this way, either in Sumerian or Akkadian. Now what relation does this form Gish bear to as the name of the hero is invariably written in the Assyrian version, the form which was at first read dIz-tu-bar or dGish-du-bar by scholars, until Pinches found in a neo-Babylonian syllabary45 the equation of it with Gi-il-ga-mesh? Pinches’ discovery pointed conclusively to the popular pronunciation of the hero’s name as Gilgamesh; and since Aelian (De natura Animalium XII, 2) mentions a Babylonian personage Gilgamos (though what he tells us of Gilgamos does not appear in our Epic, but seems to apply to Etana, another figure of Babylonian mythology), there seemed to be no further reason to question that the problem had been solved. Besides, in a later Syriac list of Babylonian kings found in the Scholia of Theodor bar Koni, the name גלמגום with a variant גמיגמוס occurs,46 and it is evident that we have here again the Gi-il-ga-mesh, discovered by Pinches. The existence of an old Babylonian hero Gilgamesh who was likewise a king is thus established, as well as his identification with It is evident that we cannot read this name as Iz-tu-bar or Gish-du-bar, but that we must read the first sign as Gish and the third as Mash, while for the second we must assume a reading Gìn or Gi. This would give us Gish-gì(n)-mash which is clearly again (like En-ki-dú) not an etymological writing but a phonetic one, intended to convey an approach to the popular pronunciation. Gi-il-ga-mesh might well be merely a variant for Gish-ga-mesh, or vice versa, and this would come close to Gish-gi-mash. Now, when we have a name the pronunciation of which is not definite but approximate, and which is written in various ways, the probabilities are that the name is foreign. A foreign name might naturally be spelled in various ways. The [27]Epic in the Assyrian version clearly depicts dGish-gì(n)-mash as a conqueror of Erech, who forces the people into subjection, and whose autocratic rule leads the people of Erech to implore the goddess Aruru to create a rival to him who may withstand him. In response to this appeal dEnkidu is formed out of dust by Aruru and eventually brought to Erech.47 Gish-gì(n)-mash or Gilgamesh is therefore in all probability a foreigner; and the simplest solution suggested by the existence of the two forms (1) Gish in the old Babylonian version and (2) Gish-gì(n)-mash in the Assyrian version, is to regard the former as an abbreviation, which seemed appropriate, because the short name conveyed the idea of the “hero” par excellence. If Gish-gì(n)-mash is a foreign name, one would think in the first instance of Sumerian; but here we encounter a difficulty in the circumstance that outside of the Epic this conqueror and ruler of Erech appears in quite a different form, namely, as dGish-bil-ga-mesh, with dGish-gibil(or bìl)-ga-mesh and dGish-bil-ge-mesh as variants.48 In the remarkable list of partly mythological and partly historical dynasties, published by Poebel,49 the fifth member of the first dynasty of Erech appears as dGish-bil-ga-mesh; and similarly in an inscription of the days of Sin-gamil, dGish-bil-ga-mesh is mentioned as the builder of the wall of Erech.50 Moreover, in the several fragments of the Sumerian version of the Epic we have invariably the form dGish-bil-ga-mesh. It is evident, therefore, that this is the genuine form of the name in Sumerian and presumably, therefore, the oldest form. By way of further confirmation we have in the syllabary above referred to, CT, XVIII, 30, 6–8, three designations of our hero, viz: dGish-gibil(or bíl)-ga-mesh muḳ-tab-lu (“warrior”) a-lik pa-na (“leader”) All three designations are set down as the equivalent of the Sumerian Esigga imin i.e., “the seven-fold hero.” [28] Of the same general character is the equation in another syllabary:51 Esigga-tuk and its equivalent Gish-tuk = “the one who is a hero.” Furthermore, the name occurs frequently in “Temple” documents of the Ur dynasty in the form dGish-bil-ga-mesh52 with dGish-bil-gi(n)-mesh as a variant.53 In a list of deities (CT XXV, 28, K 7659) we likewise encounter dGish-gibil(or bíl)-ga-mesh, and lastly in a syllabary we have the equation54 dGish-gi-mas-[si?] = dGish-bil-[ga-mesh]. The variant Gish-gibil for Gish-bil may be disposed of readily, in view of the frequent confusion or interchange of the two signs Bil (Brünnow No. 4566) and Gibil or Bíl (Brünnow No. 4642) which has also the value Gi (Brünnow 4641), so that we might also read Gish-gi-ga-mesh. Both signs convey the idea of “fire,” “renew,” etc.; both revert to the picture of flames of fire, in the one case with a bowl (or some such obiect) above it, in the other the flames issuing apparently from a torch.55 The meaning of the name is not affected whether we read dGish-bil-ga-mesh or dGish-gibil(or bíl)-ga-mesh, for the middle element in the latter case being identical with the fire-god, written dBil-gi and to be pronounced in the inverted form as Gibil with -ga (or ge) as the phonetic complement; it is equivalent, therefore, to the writing bil-ga in the former case. Now Gish-gibil or Gish-bíl conveys the idea of abu, “father” (Brünnow No. 5713), just as Bil (Brünnow No. 4579) has this meaning, while Pa-gibil-(ga) or Pa-bíl-ga is abu abi, “grandfather.”56 This meaning may be derived from Gibil, as also from Bíl = išatu, “fire,” then eššu, “new,” then abu, “father,” as the renewer or creator. Gish with Bíl or Gibil would, therefore, be “the father-man” or “the father-hero,” [29]i.e., again the hero par excellence, the original hero, just as in Hebrew and Arabic ab is used in this way.57 The syllable ga being a phonetic complement, the element mesh is to be taken by itself and to be explained, as Poebel suggested, as “hero” (itlu. Brünnow No. 5967). We would thus obtain an entirely artificial combination, “man (or hero), father, hero,” which would simply convey in an emphatic manner the idea of the Ur-held, the original hero, the father of heroes as it were—practically the same idea, therefore, as the one conveyed by Gish alone, as the hero par excellence. Our investigation thus leads us to a substantial identity between Gish and the longer form Gish-bil(or bíl)-ga-mesh, and the former might, therefore, well be used as an abbreviation of the latter. Both the shorter and the longer forms are descriptive epithets based on naive folk etymology, rather than personal names, just as in the designation of our hero as muḳtablu, the “fighter,” or as âlik pâna, “the leader,” or as Esigga imin, “the seven-fold hero,” or Esigga tuk, “the one who is a hero,” are descriptive epithets, and as Atra-ḫasis, “the very wise one,” is such an epithet for the hero of the deluge story. The case is different with Gi-il-ga-mesh, or Gish-gì(n)-mash, which represent the popular and actual pronunciation of the name, or at least the approach to such pronunciation. Such forms, stripped as they are of all artificiality, impress one as genuine names. The conclusion to which we are thus led is that Gish-bil(or bíl)-ga-mesh is a play upon the genuine name, to convey to those to whom the real name, as that of a foreigner, would suggest no meaning an interpretation fitting in with his character. In other words, Gish-bil-ga-mesh is a “Sumerianized” form of the name, introduced into the Sumerian version of the tale which became a folk-possession in the Euphrates Valley. Such plays upon names to suggest the character of an individual or some incident are familiar to us from the narratives in Genesis.58 They do not constitute genuine etymologies and are rarely of use in leading to a correct etymology. Reuben, e.g., certainly does not mean “Yahweh has seen my affliction,” which the mother is supposed to have exclaimed at [30]the birth (Genesis 29, 32), with a play upon ben and be’onyi, any more than Judah means “I praise Yahweh” (v. 35), though it does contain the divine name (Yehô) as an element. The play on the name may be close or remote, as long as it fulfills its function of suggesting an etymology that is complimentary or appropriate. In this way, an artificial division and at the same time a distortion of a foreign name like Gilgamesh into several elements, Gish-bil-ga-mesh, is no more violent than, for example, the explanation of Issachar or rather Issaschar as “God has given my hire” (Genesis 30, 18) with a play upon the element sechar, and as though the name were to be divided into Yah (“God”) and sechar (“hire”); or the popular name of Alexander among the Arabs as Zu’l Karnaini, “the possessor of the two horns.” with a suggestion of his conquest of two hemispheres, or what not.59 The element Gil in Gilgamesh would be regarded as a contraction of Gish-bil or gi-bil, in order to furnish the meaning “father-hero,” or Gil might be looked upon as a variant for Gish, which would give us the “phonetic” form in the Assyrian version dGish-gi-mash,60 as well as such a variant writing dGish-gi-mas-(si). Now a name like Gilgamesh, upon which we may definitely settle as coming closest to the genuine form, certainly impresses one as foreign, i.e., it is neither Sumerian nor Akkadian; and we have already suggested that the circumstance that the hero of the Epic is portrayed as a conqueror of Erech, and a rather ruthless one at that, points to a tradition of an invasion of the Euphrates Valley as the background for the episode in the first tablet of the series. Now it is significant that many of the names in the “mythical” dynasties, as they appear in Poebel’s list,61 are likewise foreign, such as Mes-ki-in-ga-še-ir, son of the god Shamash (and the founder of the “mythical” dynasty of Erech of which dGish-bil-ga-mesh is the fifth member),62 and En-me-ir-kár his son. In a still earlier “mythical” dynasty, we encounter names like Ga-lu-mu-um, Zu-ga-gi-ib, Ar-pi, [31]E-ta-na,63 which are distinctly foreign, while such names as En-me(n)-nun-na and Bar-sal-nun-na strike one again as “Sumerianized” names rather than as genuine Sumerian formations.64 Some of these names, as Galumum, Arpi and Etana, are so Amoritic in appearance, that one may hazard the conjecture of their western origin. May Gilgamesh likewise belong to the Amurru65 region, or does he represent a foreigner from the East in contrast to Enkidu, whose name, we have seen, may have been Baal-Ṭôb in the West, with which region he is according to the Epic so familiar? It must be confessed that the second element ga-mesh would fit in well with a Semitic origin for the name, for the element impresses one as the participial form of a Semitic stem g-m-š, just as in the second element of Meskin-gašer we have such a form. Gil might then be the name of a West-Semitic deity. Such conjectures, however, can for the present not be substantiated, and we must content ourselves with the conclusion that Gilgamesh as the real name of the hero, or at least the form which comes closest to the real name, points to a foreign origin for the hero, and that such forms as dGish-bil-ga-mesh and dGish-bíl-gi-mesh and other variants are “Sumerianized” forms for which an artificial etymology was brought forward to convey the [32]idea of the “original hero” or the hero par excellence. By means of this “play” on the name, which reverts to the compilers of the Sumerian version of the Epic, Gilgamesh was converted into a Sumerian figure, just as the name Enkidu may have been introduced as a Sumerian translation of his Amoritic name. dGish at all events is an abbreviated form of the “Sumerianized” name, introduced by the compilers of the earliest Akkadian version, which was produced naturally under the influence of the Sumerian version. Later, as the Epic continued to grow, a phonetic writing was introduced, dGish-gi-mash, which is in a measure a compromise between the genuine name and the “Sumerianized” form, but at the same time an approach to the real pronunciation. Next to the new light thrown upon the names and original character of the two main figures of the Epic, one of the chief points of interest in the Pennsylvania fragment is the proof that it furnishes for a striking resemblance of the two heroes, Gish and Enkidu, to one another. In interpreting the dream of Gish, his mother. Ninsun, lays stress upon the fact that the dream portends the coming of someone who is like Gish, “born in the field and reared in the mountain” (lines 18–19). Both, therefore, are shown by this description to have come to Babylonia from a mountainous region, i.e., they are foreigners; and in the case of Enkidu we have seen that the mountain in all probability refers to a region in the West, while the same may also be the case with Gish. The resemblance of the two heroes to one another extends to their personal appearance. When Enkidu appears on the streets of Erech, the people are struck by this resemblance. They remark that he is “like Gish,” though “shorter in stature” (lines 179–180). Enkidu is described as a rival or counterpart.66 This relationship between the two is suggested also by the Assyrian version. In the creation of Enkidu by Aruru, the people urge the goddess to create the “counterpart” (zikru) of Gilgamesh, someone who will be like him (ma-ši-il) (Tablet I, 2, 31). Enkidu not only comes from the mountain,67 but the mountain is specifically designated [33]as his birth-place (I, 4, 2), precisely as in the Pennsylvania tablet, while in another passage he is also described, as in our tablet, as “born in the field.”68 Still more significant is the designation of Gilgamesh as the talimu, “younger brother,” of Enkidu.69 In accord with this, we find Gilgamesh in his lament over Enkidu describing him as a “younger brother” (ku-ta-ni);70 and again in the last tablet of the Epic, Gilgamesh is referred to as the “brother” of Enkidu.71 This close relationship reverts to the Sumerian version, for the Constantinople fragment (Langdon, above, p. 13) begins with the designation of Gish-bil-ga-mesh as “his brother.” By “his” no doubt Enkidu is meant. Likewise in the Sumerian text published by Zimmern (above, p. 13) Gilgamesh appears as the brother of Enkidu (rev. 1, 17). Turning to the numerous representations of Gilgamesh and Enkidu on Seal Cylinders,72 we find this resemblance of the two heroes to each other strikingly confirmed. Both are represented as bearded, with the strands arranged in the same fashion. The face in both cases is broad, with curls protruding at the side of the head, though at times these curls are lacking in the case of Enkidu. What is particularly striking is to find Gilgamesh generally a little taller than Enkidu, thus bearing out the statement in the Pennsylvania tablet that Enkidu is “shorter in stature.” There are, to be sure, also some distinguishing marks between the two. Thus Enkidu is generally represented with animal hoofs, but not always.73 Enkidu is commonly portrayed with the horns of a bison, but again this sign is wanting in quite a number of instances.74 The hoofs and the horns mark the period when Enkidu lived with animals and much like an [34]animal. Most remarkable, however, of all are cylinders on which we find the two heroes almost exactly alike as, for example, Ward No. 199 where two figures, the one a duplicate of the other (except that one is just a shade taller), are in conflict with each other. Dr. Ward was puzzled by this representation and sets it down as a “fantastic” scene in which “each Gilgamesh is stabbing the other.” In the light of the Pennsylvania tablet, this scene is clearly the conflict between the two heroes described in column 6, preliminary to their forming a friendship. Even in the realm of myth the human experience holds good that there is nothing like a good fight as a basis for a subsequent alliance. The fragment describes this conflict as a furious one in which Gilgamesh is worsted, and his wounded pride assuaged by the generous victor, who comforts his vanquished enemy by the assurance that he was destined for something higher than to be a mere “Hercules.” He was singled out for the exercise of royal authority. True to the description of the two heroes in the Pennsylvania tablet as alike, one the counterpart of the other, the seal cylinder portrays them almost exactly alike, as alike as two brothers could possibly be; with just enough distinction to make it clear on close inspection that two figures are intended and not one repeated for the sake of symmetry. There are slight variations in the manner in which the hair is worn, and slightly varying expressions of the face, just enough to make it evident that the one is intended for Gilgamesh and the other for Enkidu. When, therefore, in another specimen, No. 173, we find a Gilgamesh holding his counterpart by the legs, it is merely another aspect of the fight between the two heroes, one of whom is intended to represent Enkidu, and not, as Dr. Ward supposed, a grotesque repetition of Gilgamesh.75 The description of Enkidu in the Pennsylvania tablet as a parallel figure to Gilgamesh leads us to a consideration of the relationship of the two figures to one another. Many years ago it was pointed out that the Gilgamesh Epic was a composite tale in which various stories of an independent origin had been combined and brought into more or less artificial connection with the heros eponymos of southern Babylonia.76 We may now go a step further and point out that not [35]only is Enkidu originally an entirely independent figure, having no connection with Gish or Gilgamesh, but that the latter is really depicted in the Epic as the counterpart of Enkidu, a reflection who has been given the traits of extraordinary physical power that belong to Enkidu. This is shown in the first place by the fact that in the encounter it is Enkidu who triumphs over Gilgamesh. The entire analysis of the episode of the meeting between the two heroes as given by Gressmann77 must be revised. It is not Enkidu who is terrified and who is warned against the encounter. It is Gilgamesh who, during the night on his way from the house in which the goddess Ishḫara lies, encounters Enkidu on the highway. Enkidu “blocks the path”78 of Gilgamesh. He prevents Gilgamesh from re-entering the house,79 and the two attack each other “like oxen.”80 They grapple with each other, and Enkidu forces Gilgamesh to the ground. Enkidu is, therefore, the real hero whose traits of physical prowess are afterwards transferred to Gilgamesh. Similarly in the next episode, the struggle against Ḫuwawa, the Yale tablet makes it clear that in the original form of the tale Enkidu is the real hero. All warn Gish against the undertaking—the elders of Erech, Enkidu, and also the workmen. “Why dost thou desire to do this?”81 they say to him. “Thou art young, and thy heart carries thee away. Thou knowest not what thou proposest to do.”82 This part of the incident is now better known to us through the latest fragment of the Assyrian version discovered and published by King.83 The elders say to Gilgamesh: “Do not trust, O Gilgamesh, in thy strength! Be warned(?) against trusting to thy attack! The one who goes before will save his companion,84 He who has foresight will save his friend.85 [36] Let Enkidu go before thee. He knows the roads to the cedar forest; He is skilled in battle and has seen fight.” Gilgamesh is sufficiently impressed by this warning to invite Enkidu to accompany him on a visit to his mother, Ninsun, for the purpose of receiving her counsel.86 It is only after Enkidu, who himself hesitates and tries to dissuade Gish, decides to accompany the latter that the elders of Erech are reconciled and encourage Gish for the fray. The two in concert proceed against Ḫuwawa. Gilgamesh alone cannot carry out the plan. Now when a tale thus associates two figures in one deed, one of the two has been added to the original tale. In the present case there can be little doubt that Enkidu, without whom Gish cannot proceed, who is specifically described as “acquainted with the way … to the entrance of the forest”87 in which Ḫuwawa dwells is the original vanquisher. Naturally, the Epic aims to conceal this fact as much as possible ad majorem gloriam of Gilgamesh. It tries to put the one who became the favorite hero into the foreground. Therefore, in both the Babylonian and the Assyrian version Enkidu is represented as hesitating, and Gilgamesh as determined to go ahead. Gilgamesh, in fact, accuses Enkidu of cowardice and boldly declares that he will proceed even though failure stare him in the face.88 Traces of the older view, however, in which Gilgamesh is the one for whom one fears the outcome, crop out; as, for example, in the complaint of Gilgamesh’s mother to Shamash that the latter has stirred the heart of her son to take the distant way to Ḫu(m)baba, “To a fight unknown to him, he advances, An expedition unknown to him he undertakes.”89 Ninsun evidently fears the consequences when her son informs her of his intention and asks her counsel. The answer of Shamash is not preserved, but no doubt it was of a reassuring character, as was the answer of the Sun-god to Gish’s appeal and prayer as set forth in the Yale tablet.90 [37] Again, as a further indication that Enkidu is the real conqueror of Ḫuwawa, we find the coming contest revealed to Enkidu no less than three times in dreams, which Gilgamesh interprets.91 Since the person who dreams is always the one to whom the dream applies, we may see in these dreams a further trace of the primary rôle originally assigned to Enkidu. Another exploit which, according to the Assyrian version, the two heroes perform in concert is the killing of a bull, sent by Anu at the instance of Ishtar to avenge an insult offered to the goddess by Gilgamesh, who rejects her offer of marriage. In the fragmentary description of the contest with the bull, we find Enkidu “seizing” the monster by “its tail.”92 That Enkidu originally played the part of the slayer is also shown by the statement that it is he who insults Ishtar by throwing a piece of the carcass into the goddess’ face,93 adding also an insulting speech; and this despite the fact that Ishtar in her rage accuses Gilgamesh of killing the bull.94 It is thus evident that the Epic alters the original character of the episodes in order to find a place for Gilgamesh, with the further desire to assign to the latter the chief rôle. Be it noted also that Enkidu, not Gilgamesh, is punished for the insult to Ishtar. Enkidu must therefore in the original form of the episode have been the guilty party, who is stricken with mortal disease as a punishment to which after twelve days he succumbs.95 In view of this, we may supply the name of Enkidu in the little song introduced at the close of the encounter with the bull, and not Gilgamesh as has hitherto been done. “Who is distinguished among the heroes? Who is glorious among men? [Enkidu] is distinguished among heroes, [Enkidu] is glorious among men.”96 [38]Finally, the killing of lions is directly ascribed to Enkidu in the Pennsylvania tablet: “Lions he attacked *     *     *     *     * Lions he overcame”97 whereas Gilgamesh appears to be afraid of lions. On his long search for Utnapishtim he says: “On reaching the entrance of the mountain at night I saw lions and was afraid.”98 He prays to Sin and Ishtar to protect and save him. When, therefore, in another passage some one celebrates Gilgamesh as the one who overcame the “guardian,” who dispatched Ḫu(m)baba in the cedar forest, who killed lions and overthrew the bull,99 we have the completion of the process which transferred to Gilgamesh exploits and powers which originally belonged to Enkidu, though ordinarily the process stops short at making Gilgamesh a sharer in the exploits; with the natural tendency, to be sure, to enlarge the share of the favorite. We can now understand why the two heroes are described in the Pennsylvania tablet as alike, as born in the same place, aye, as brothers. Gilgamesh in the Epic is merely a reflex of Enkidu. The latter is the real hero and presumably, therefore, the older figure.100 Gilgamesh resembles Enkidu, because he is originally Enkidu. The “resemblance” motif is merely the manner in which in the course of the partly popular, partly literary transfer, the recollection is preserved that Enkidu is the original, and Gilgamesh the copy. The artificiality of the process which brings the two heroes together is apparent in the dreams of Gilgamesh which are interpreted by his mother as portending the coming of Enkidu. Not the conflict is foreseen, but the subsequent close association, naïvely described as due to the personal charm which Enkidu exercises, which will lead Gilgamesh to fall in love with the one whom he is to meet. The two will become one, like man and wife. [39] On the basis of our investigations, we are now in a position to reconstruct in part the cycle of episodes that once formed part of an Enkidu Epic. The fight between Enkidu and Gilgamesh, in which the former is the victor, is typical of the kind of tales told of Enkidu. He is the real prototype of the Greek Hercules. He slays lions, he overcomes a powerful opponent dwelling in the forests of Lebanon, he kills the bull, and he finally succumbs to disease sent as a punishment by an angry goddess. The death of Enkidu naturally formed the close of the Enkidu Epic, which in its original form may, of course, have included other exploits besides those taken over into the Gilgamesh Epic. There is another aspect of the figure of Enkidu which is brought forward in the Pennsylvania tablet more clearly than had hitherto been the case. Many years ago attention was called to certain striking resemblances between Enkidu and the figure of the first man as described in the early chapters of Genesis.101 At that time we had merely the Assyrian version of the Gilgamesh Epic at our disposal, and the main point of contact was the description of Enkidu living with the animals, drinking and feeding like an animal, until a woman is brought to him with whom he engages in sexual intercourse. This suggested that Enkidu was a picture of primeval man, while the woman reminded one of Eve, who when she is brought to Adam becomes his helpmate and inseparable companion. The Biblical tale stands, of course, on a much higher level, and is introduced, as are other traditions and tales of primitive times, in the style of a parable to convey certain religious teachings. For all that, suggestions of earlier conceptions crop out in the picture of Adam surrounded by animals to which he assigns names. Such a phrase as “there was no helpmate corresponding to him” becomes intelligible on the supposition of an existing tradition or belief, that man once lived and, indeed, cohabited with animals. The tales in the early chapters of Genesis must rest on very early popular traditions, which have been cleared of mythological and other objectionable features in order to adapt them to the purpose of the Hebrew compilers, to serve as a medium for illustrating [40]certain religious teachings regarding man’s place in nature and his higher destiny. From the resemblance between Enkidu and Adam it does not, of course, follow that the latter is modelled upon the former, but only that both rest on similar traditions of the condition under which men lived in primeval days prior to the beginnings of human culture. We may now pass beyond these general indications and recognize in the story of Enkidu as revealed by the Pennsylvania tablet an attempt to trace the evolution of primitive man from low beginnings to the regular and orderly family life associated with advanced culture. The new tablet furnishes a further illustration for the surprisingly early tendency among the Babylonian literati to connect with popular tales teachings of a religious or ethical character. Just as the episode between Gilgamesh and the maiden Sabitum is made the occasion for introducing reflections on the inevitable fate of man to encounter death, so the meeting of Enkidu with the woman becomes the medium of impressing the lesson of human progress through the substitution of bread and wine for milk and water, through the institution of the family, and through work and the laying up of resources. This is the significance of the address to Enkidu in column 4 of the Pennsylvania tablet, even though certain expressions in it are somewhat obscure. The connection of the entire episode of Enkidu and the woman with Gilgamesh is very artificial; and it becomes much more intelligible if we disassociate it from its present entanglement in the Epic. In Gilgamesh’s dream, portending the meeting with Enkidu, nothing is said of the woman who is the companion of the latter. The passage in which Enkidu is created by Aruru to oppose Gilgamesh102 betrays evidence of having been worked over in order to bring Enkidu into association with the longing of the people of Erech to get rid of a tyrannical character. The people in their distress appeal to Aruru to create a rival to Gilgamesh. In response, “Aruru upon hearing this created a man of Anu in her heart.” Now this “man of Anu” cannot possibly be Enkidu, for the sufficient reason that a few lines further on Enkidu is described as an [41]offspring of Ninib. Moreover, the being created is not a “counterpart” of Gilgamesh, but an animal-man, as the description that follows shows. We must separate lines 30–33 in which the creation of the “Anu man” is described from lines 34–41 in which the creation of Enkidu is narrated. Indeed, these lines strike one as the proper beginning of the original Enkidu story, which would naturally start out with his birth and end with his death. The description is clearly an account of the creation of the first man, in which capacity Enkidu is brought forward. “Aruru washed her hands, broke off clay, threw it on the field103 … created Enkidu, the hero, a lofty offspring of the host of Ninib.”104 The description of Enkidu follows, with his body covered with hair like an animal, and eating and drinking with the animals. There follows an episode105 which has no connection whatsoever with the Gilgamesh Epic, but which is clearly intended to illustrate how Enkidu came to abandon the life with the animals. A hunter sees Enkidu and is amazed at the strange sight—an animal and yet a man. Enkidu, as though resenting his condition, becomes enraged at the sight of the hunter, and the latter goes to his father and tells him of the strange creature whom he is unable to catch. In reply, the father advises his son to take a woman with him when next he goes out on his pursuit, and to have the woman remove her dress in the presence of Enkidu, who will then approach her, and after intercourse with her will abandon the animals among whom he lives. By this device he will catch the strange creature. Lines 14–18 of column 3 in the first tablet in which the father of the hunter refers to Gilgamesh must be regarded as a later insertion, a part of the reconstruction of the tale to connect the episode with Gilgamesh. The advice of the father to his son, the hunter, begins, line 19, “Go my hunter, take with thee a woman.” [42]In the reconstructed tale, the father tells his son to go to Gilgamesh to relate to him the strange appearance of the animal-man; but there is clearly no purpose in this, as is shown by the fact that when the hunter does so, Gilgamesh makes precisely the same speech as does the father of the hunter. Lines 40–44 of column 3, in which Gilgamesh is represented as speaking to the hunter form a complete doublet to lines 19–24, beginning “Go, my hunter, take with thee a woman, etc.” and similarly the description of Enkidu appears twice, lines 2–12 in an address of the hunter to his father, and lines 29–39 in the address of the hunter to Gilgamesh. The artificiality of the process of introducing Gilgamesh into the episode is revealed by this awkward and entirely meaningless repetition. We may therefore reconstruct the first two scenes in the Enkidu Epic as follows:106 Tablet I, col. 2, 34–35: Creation of Enkidu by Aruru. 36–41: Description of Enkidu’s hairy body and of his life with the animals. 42–50: The hunter sees Enkidu, who shows his anger, as also his woe, at his condition. 3, 1–12: The hunter tells his father of the strange being who pulls up the traps which the hunter digs, and who tears the nets so that the hunter is unable to catch him or the animals. 19–24: The father of the hunter advises his son on his next expedition to take a woman with him in order to lure the strange being from his life with the animals. Line 25, beginning “On the advice of his father,” must have set forth, in the original form of the episode, how the hunter procured the woman and took her with him to meet Enkidu. Column 4 gives in detail the meeting between the two, and naïvely describes how the woman exposes her charms to Enkidu, who is captivated by her and stays with her six days and seven nights. The animals see the change in Enkidu and run away from him. [43]He has been transformed through the woman. So far the episode. In the Assyrian version there follows an address of the woman to Enkidu beginning (col. 4, 34): “Beautiful art thou, Enkidu, like a god art thou.” We find her urging him to go with her to Erech, there to meet Gilgamesh and to enjoy the pleasures of city life with plenty of beautiful maidens. Gilgamesh, she adds, will expect Enkidu, for the coming of the latter to Erech has been foretold in a dream. It is evident that here we have again the later transformation of the Enkidu Epic in order to bring the two heroes together. Will it be considered too bold if we assume that in the original form the address of the woman and the construction of the episode were such as we find preserved in part in columns 2 to 4 of the Pennsylvania tablet, which forms part of the new material that can now be added to the Epic? The address of the woman begins in line 51 of the Pennsylvania tablet: “I gaze upon thee, Enkidu, like a god art thou.” This corresponds to the line in the Assyrian version (I, 4, 34) as given above, just as lines 52–53: “Why with the cattle Dost thou roam across the field?” correspond to I, 4, 35, of the Assyrian version. There follows in both the old Babylonian and the Assyrian version the appeal of the woman to Enkidu, to allow her to lead him to Erech where Gilgamesh dwells (Pennsylvania tablet lines 54–61 = Assyrian version I, 4, 36–39); but in the Pennsylvania tablet we now have a second speech (lines 62–63) beginning like the first one with al-ka, “come:” “Come, arise from the accursed ground.” Enkidu consents, and now the woman takes off her garments and clothes the naked Enkidu, while putting another garment on herself. She takes hold of his hand and leads him to the sheepfolds (not to Erech!!), where bread and wine are placed before him. Accustomed hitherto to sucking milk with cattle, Enkidu does not know what to do with the strange food until encouraged and instructed by the woman. The entire third column is taken up with this introduction [44]of Enkidu to civilized life in a pastoral community, and the scene ends with Enkidu becoming a guardian of flocks. Now all this has nothing to do with Gilgamesh, and clearly sets forth an entirely different idea from the one embodied in the meeting of the two heroes. In the original Enkidu tale, the animal-man is looked upon as the type of a primitive savage, and the point of the tale is to illustrate in the naïve manner characteristic of folklore the evolution to the higher form of pastoral life. This aspect of the incident is, therefore, to be separated from the other phase which has as its chief motif the bringing of the two heroes together. We now obtain, thanks to the new section revealed by the Pennsylvania tablet, a further analogy107 with the story of Adam and Eve, but with this striking difference, that whereas in the Babylonian tale the woman is the medium leading man to the higher life, in the Biblical story the woman is the tempter who brings misfortune to man. This contrast is, however, not inherent in the Biblical story, but due to the point of view of the Biblical writer, who is somewhat pessimistically inclined and looks upon primitive life, when man went naked and lived in a garden, eating of fruits that grew of themselves, as the blessed life in contrast to advanced culture which leads to agriculture and necessitates hard work as the means of securing one’s substance. Hence the woman through whom Adam eats of the tree of knowledge and becomes conscious of being naked is looked upon as an evil tempter, entailing the loss of the primeval life of bliss in a gorgeous Paradise. The Babylonian point of view is optimistic. The change to civilized life—involving the wearing of clothes and the eating of food that is cultivated (bread and wine) is looked upon as an advance. Hence the woman is viewed as the medium of raising man to a higher level. The feature common to the Biblical and Babylonian tales is the attachment of a lesson to early folk-tales. The story of Adam and Eve,108 as the story of Enkidu and the woman, is told with a purpose. Starting with early traditions of men’s primitive life on earth, that may have arisen independently, Hebrew and [45]Babylonian writers diverged, each group going its own way, each reflecting the particular point of view from which the evolution of human society was viewed. Leaving the analogy between the Biblical and Babylonian tales aside, the main point of value for us in the Babylonian story of Enkidu and the woman is the proof furnished by the analysis, made possible through the Pennsylvania tablet, that the tale can be separated from its subsequent connection with Gilgamesh. We can continue this process of separation in the fourth column, where the woman instructs Enkidu in the further duty of living his life with the woman decreed for him, to raise a family, to engage in work, to build cities and to gather resources. All this is looked upon in the same optimistic spirit as marking progress, whereas the Biblical writer, consistent with his point of view, looks upon work as a curse, and makes Cain, the murderer, also the founder of cities. The step to the higher forms of life is not an advance according to the J document. It is interesting to note that even the phrase the “cursed ground” occurs in both the Babylonian and Biblical tales; but whereas in the latter (Gen. 3, 17) it is because of the hard work entailed in raising the products of the earth that the ground is cursed, in the former (lines 62–63) it is the place in which Enkidu lives before he advances to the dignity of human life that is “cursed,” and which he is asked to leave. Adam is expelled from Paradise as a punishment, whereas Enkidu is implored to leave it as a necessary step towards progress to a higher form of existence. The contrast between the Babylonian and the Biblical writer extends to the view taken of viniculture. The Biblical writer (again the J document) looks upon Noah’s drunkenness as a disgrace. Noah loses his sense of shame and uncovers himself (Genesis 9, 21), whereas in the Babylonian description Enkidu’s jolly spirit after he has drunk seven jars of wine meets with approval. The Biblical point of view is that he who drinks wine becomes drunk;109 the Babylonian says, if you drink wine you become happy.110 If the thesis here set forth of the original character and import of the episode of Enkidu with the woman is correct, we may again regard lines 149–153 of the Pennsylvania tablet, in which Gilgamesh is introduced, as a later addition to bring the two heroes into association. [46]The episode in its original form ended with the introduction of Enkidu first to pastoral life, and then to the still higher city life with regulated forms of social existence. Now, to be sure, this Enkidu has little in common with the Enkidu who is described as a powerful warrior, a Hercules, who kills lions, overcomes the giant Ḫuwawa, and dispatches a great bull, but it is the nature of folklore everywhere to attach to traditions about a favorite hero all kinds of tales with which originally he had nothing to do. Enkidu, as such a favorite, is viewed also as the type of primitive man,111 and so there arose gradually an Epic which began with his birth, pictured him as half-animal half-man, told how he emerged from this state, how he became civilized, was clothed, learned to eat food and drink wine, how he shaved off the hair with which his body was covered,112 anointed himself—in short, “He became manlike.”113 Thereupon he is taught his duties as a husband, is introduced to the work of building, and to laying aside supplies, and the like. The fully-developed and full-fledged hero then engages in various exploits, of which some are now embodied in the Gilgamesh Epic. Who this Enkidu was, we are not in a position to determine, but the suggestion has been thrown out above that he is a personage foreign to Babylonia, that his home appears to be in the undefined Amurru district, and that he conquers that district. The original tale of Enkidu, if this view be correct, must therefore have been carried to the Euphrates Valley, at a very remote period, with one of the migratory waves that brought a western people as invaders into Babylonia. Here the tale was combined with stories current of another hero, Gilgamesh—perhaps also of Western origin—whose conquest of Erech likewise represents an invasion of Babylonia. The center of the Gilgamesh tale was Erech, and in the process of combining the stories of Enkidu and Gilgamesh, Enkidu is brought to Erech and the two perform exploits [47]in common. In such a combination, the aim would be to utilize all the incidents of both tales. The woman who accompanies Enkidu, therefore, becomes the medium of bringing the two heroes together. The story of the evolution of primitive man to civilized life is transformed into the tale of Enkidu’s removal to Erech, and elaborated with all kinds of details, among which we have, as perhaps embodying a genuine historical tradition, the encounter of the two heroes. Before passing on, we have merely to note the very large part taken in both the old Babylonian and the Assyrian version by the struggle against Ḫuwawa. The entire Yale tablet—forming, as we have seen, the third of the series—is taken up with the preparation for the struggle, and with the repeated warnings given to Gilgamesh against the dangerous undertaking. The fourth tablet must have recounted the struggle itself, and it is not improbable that this episode extended into the fifth tablet, since in the Assyrian version this is the case. The elaboration of the story is in itself an argument in favor of assuming some historical background for it—the recollection of the conquest of Amurru by some powerful warrior; and we have seen that this conquest must be ascribed to Enkidu and not to Gilgamesh. If, now, Enkidu is not only the older figure but the one who is the real hero of the most notable episode in the Gilgamesh Epic; if, furthermore, Enkidu is the Hercules who kills lions and dispatches the bull sent by an enraged goddess, what becomes of Gilgamesh? What is left for him? In the first place, he is definitely the conqueror of Erech. He builds the wall of Erech,114 and we may assume that the designation of the city as Uruk supûri, “the walled Erech,”115 rests upon this tradition. He is also associated with the great temple Eanna, “the heavenly house,” in Erech. To Gilgamesh belongs also the unenviable tradition of having exercised his rule in Erech so harshly that the people are impelled to implore Aruru to create a rival who may rid [48]the district of the cruel tyrant, who is described as snatching sons and daughters from their families, and in other ways terrifying the population—an early example of “Schrecklichkeit.” Tablets II to V inclusive of the Assyrian version being taken up with the Ḫuwawa episode, modified with a view of bringing the two heroes together, we come at once to the sixth tablet, which tells the story of how the goddess Ishtar wooed Gilgamesh, and of the latter’s rejection of her advances. This tale is distinctly a nature myth. The attempt of Gressmann116 to find some historical background to the episode is a failure. The goddess Ishtar symbolizes the earth which woos the sun in the spring, but whose love is fatal, for after a few months the sun’s power begins to wane. Gilgamesh, who in incantation hymns is invoked in terms which show that he was conceived as a sun-god,117 recalls to the goddess how she changed her lovers into animals, like Circe of Greek mythology, and brought them to grief. Enraged at Gilgamesh’s insult to her vanity, she flies to her father Anu and cries for revenge. At this point the episode of the creation of the bull is introduced, but if the analysis above given is correct it is Enkidu who is the hero in dispatching the bull, and we must assume that the sickness with which Gilgamesh is smitten is the punishment sent by Anu to avenge the insult to his daughter. This sickness symbolizes the waning strength of the sun after midsummer is past. The sun recedes from the earth, and this was pictured in the myth as the sun-god’s rejection of Ishtar; Gilgamesh’s fear of death marks the approach of the winter season, when the sun appears to have lost its vigor completely and is near to death. The entire episode is, therefore, a nature myth, symbolical of the passing of spring to midsummer and then to the bare season. The myth has been attached to Gilgamesh as a favorite figure, and then woven into a pattern with the episode of Enkidu and the bull. The bull episode can be detached from the nature myth without any loss to the symbolism of the tale of Ishtar and Gilgamesh. As already suggested, with Enkidu’s death after this conquest of the bull the original Enkidu Epic came to an end. In order to connect Gilgamesh with Enkidu, the former is represented as sharing [49]in the struggle against the bull. Enkidu is punished with death, while Gilgamesh is smitten with disease. Since both shared equally in the guilt, the punishment should have been the same for both. The differentiation may be taken as an indication that Gilgamesh’s disease has nothing to do with the bull episode, but is merely part of the nature myth. Gilgamesh now begins a series of wanderings in search of the restoration of his vigor, and this motif is evidently a continuation of the nature myth to symbolize the sun’s wanderings during the dark winter in the hope of renewed vigor with the coming of the spring. Professor Haupt’s view is that the disease from which Gilgamesh is supposed to be suffering is of a venereal character, affecting the organs of reproduction. This would confirm the position here taken that the myth symbolizes the loss of the sun’s vigor. The sun’s rays are no longer strong enough to fertilize the earth. In accord with this, Gilgamesh’s search for healing leads him to the dark regions118 in which the scorpion-men dwell. The terrors of the region symbolize the gloom of the winter season. At last Gilgamesh reaches a region of light again, described as a landscape situated at the sea. The maiden in control of this region bolts the gate against Gilgamesh’s approach, but the latter forces his entrance. It is the picture of the sun-god bursting through the darkness, to emerge as the youthful reinvigorated sun-god of the spring. Now with the tendency to attach to popular tales and nature myths lessons illustrative of current beliefs and aspirations, Gilgamesh’s search for renewal of life is viewed as man’s longing for eternal life. The sun-god’s waning power after midsummer is past suggests man’s growing weakness after the meridian of life has been left behind. Winter is death, and man longs to escape it. Gilgamesh’s wanderings are used as illustration of this longing, and accordingly the search for life becomes also the quest for immortality. Can the precious boon of eternal life be achieved? Popular fancy created the figure of a favorite of the gods who had escaped a destructive deluge in which all mankind had perished.119 Gilgamesh hears [50]of this favorite and determines to seek him out and learn from him the secret of eternal life. The deluge story, again a pure nature myth, symbolical of the rainy season which destroys all life in nature, is thus attached to the Epic. Gilgamesh after many adventures finds himself in the presence of the survivor of the Deluge who, although human, enjoys immortal life among the gods. He asks the survivor how he came to escape the common fate of mankind, and in reply Utnapishtim tells the story of the catastrophe that brought about universal destruction. The moral of the tale is obvious. Only those singled out by the special favor of the gods can hope to be removed to the distant “source of the streams” and live forever. The rest of mankind must face death as the end of life. That the story of the Deluge is told in the eleventh tablet of the series, corresponding to the eleventh month, known as the month of “rain curse”120 and marking the height of the rainy season, may be intentional, just as it may not be accidental that Gilgamesh’s rejection of Ishtar is recounted in the sixth tablet, corresponding to the sixth month,121 which marks the end of the summer season. The two tales may have formed part of a cycle of myths, distributed among the months of the year. The Gilgamesh Epic, however, does not form such a cycle. Both myths have been artificially attached to the adventures of the hero. For the deluge story we now have the definite proof for its independent existence, through Dr. Poebel’s publication of a Sumerian text which embodies the tale,122 and without any reference [51]to Gilgamesh. Similarly, Scheil and Hilprecht have published fragments of deluge stories written in Akkadian and likewise without any connection with the Gilgamesh Epic.123 In the Epic the story leads to another episode attached to Gilgamesh, namely, the search for a magic plant growing in deep water, which has the power of restoring old age to youth. Utnapishtim, the survivor of the deluge, is moved through pity for Gilgamesh, worn out by his long wanderings. At the request of his wife, Utnapishtim decides to tell Gilgamesh of this plant, and he succeeds in finding it. He plucks it and decides to take it back to Erech so that all may enjoy the benefit, but on his way stops to bathe in a cool cistern. A serpent comes along and snatches the plant from him, and he is forced to return to Erech with his purpose unachieved. Man cannot hope, when old age comes on, to escape death as the end of everything. Lastly, the twelfth tablet of the Assyrian version of the Gilgamesh Epic is of a purely didactic character, bearing evidence of having been added as a further illustration of the current belief that there is no escape from the nether world to which all must go after life has come to an end. Proper burial and suitable care of the dead represent all that can be done in order to secure a fairly comfortable rest for those who have passed out of this world. Enkidu is once more introduced into this episode. His shade is invoked by Gilgamesh and rises up out of the lower world to give a discouraging reply to Gilgamesh’s request, “Tell me, my friend, tell me, my friend, The law of the earth which thou hast experienced, tell me,” The mournful message comes back: “I cannot tell thee, my friend, I cannot tell.” Death is a mystery and must always remain such. The historical Gilgamesh has clearly no connection with the figure introduced into [52]this twelfth tablet. Indeed, as already suggested, the Gilgamesh Epic must have ended with the return to Erech, as related at the close of the eleventh tablet. The twelfth tablet was added by some school-men of Babylonia (or perhaps of Assyria), purely for the purpose of conveying a summary of the teachings in regard to the fate of the dead. Whether these six episodes covering the sixth to the twelfth tablets, (1) the nature myth, (2) the killing of the divine bull, (3) the punishment of Gilgamesh and the death of Enkidu, (4) Gilgamesh’s wanderings, (5) the Deluge, (6) the search for immortality, were all included at the time that the old Babylonian version was compiled cannot, of course, be determined until we have that version in a more complete form. Since the two tablets thus far recovered show that as early as 2000 B.C. the Enkidu tale had already been amalgamated with the current stories about Gilgamesh, and the endeavor made to transfer the traits of the former to the latter, it is eminently likely that the story of Ishtar’s unhappy love adventure with Gilgamesh was included, as well as Gilgamesh’s punishment and the death of Enkidu. With the evidence furnished by Meissner’s fragment of a version of the old Babylonian revision and by our two tablets, of the early disposition to make popular tales the medium of illustrating current beliefs and the teachings of the temple schools, it may furthermore be concluded that the death of Enkidu and the punishment of Gilgamesh were utilized for didactic purposes in the old Babylonian version. On the other hand, the proof for the existence of the deluge story in the Hammurabi period and some centuries later, independent of any connection with the Gilgamesh Epic, raises the question whether in the old Babylonian version, of which our two tablets form a part, the deluge tale was already woven into the pattern of the Epic. At all events, till proof to the contrary is forthcoming, we may assume that the twelfth tablet of the Assyrian version, though also reverting to a Babylonian original, dates as the latest addition to the Epic from a period subsequent to 2000 B.C.; and that the same is probably the case with the eleventh tablet. To sum up, there are four main currents that flow together in the Gilgamesh Epic even in its old Babylonian form: (1) the adventures of a mighty warrior Enkidu, resting perhaps on a faint tradition [53]of the conquest of Amurru by the hero; (2) the more definite recollection of the exploits of a foreign invader of Babylonia by the name of Gilgamesh, whose home appears likewise to have been in the West;124 (3) nature myths and didactic tales transferred to Enkidu and Gilgamesh as popular figures; and (4) the process of weaving the traditions, exploits, myths and didactic tales together, in the course of which process Gilgamesh becomes the main hero, and Enkidu his companion. Furthermore, our investigation has shown that to Enkidu belongs the episode with the woman, used to illustrate the evolution of primitive man to the ways and conditions of civilized life, the conquest of Ḫuwawa in the land of Amurru, the killing of lions and also of the bull, while Gilgamesh is the hero who conquers Erech. Identified with the sun-god, the nature myth of the union of the sun with the earth and the subsequent separation of the two is also transferred to him. The wanderings of the hero, smitten with disease, are a continuation of the nature myth, symbolizing the waning vigor of the sun with the approach of the wintry season. The details of the process which led to making Gilgamesh the favorite figure, to whom the traits and exploits of Enkidu and of the sun-god are transferred, escape us, but of the fact that Enkidu is the older figure, of whom certain adventures were set forth in a tale that once had an independent existence, there can now be little doubt in the face of the evidence furnished by the two tablets of the old Babylonian version; just as the study of these tablets shows that in the combination of the tales of Enkidu and Gilgamesh, the former is the prototype of which Gilgamesh is the copy. If the two are regarded as brothers, as born in the same place, even resembling one another in appearance and carrying out their adventures in common, it is because in the process of combination Gilgamesh becomes the reflex of Enkidu. That Enkidu is not the figure created by Aruru to relieve Erech of its tyrannical ruler is also shown by the fact that Gilgamesh remains in control of Erech. It is to Erech that he returns when he fails of his purpose to learn the secret of escape from old age and death. Erech is, therefore, not relieved of the presence of the ruthless ruler through Enkidu. The “Man of Anu” formed by Aruru as a deliverer is confused in the course of the growth of the [54]Epic with Enkidu, the offspring of Ninib, and in this way we obtain the strange contradiction of Enkidu and Gilgamesh appearing first as bitter rivals and then as close and inseparable friends. It is of the nature of Epic compositions everywhere to eliminate unnecessary figures by concentrating on one favorite the traits belonging to another or to several others. The close association of Enkidu and Gilgamesh which becomes one of the striking features in the combination of the tales of these two heroes naturally recalls the “Heavenly Twins” motif, which has been so fully and so suggestively treated by Professor J. Rendell Harris in his Cult of the Heavenly Twins, (London, 1906). Professor Harris has conclusively shown how widespread the tendency is to associate two divine or semi-divine beings in myths and legends as inseparable companions125 or twins, like Castor and Pollux, Romulus and Remus,126 the Acvins in the Rig-Veda,127 Cain and Abel, Jacob and Esau in the Old Testament, the Kabiri of the Phoenicians,128 Herakles and Iphikles in Greek mythology, Ambrica and Fidelio in Teutonic mythology, Patollo and Potrimpo in old Prussian mythology, Cautes and Cautopates in Mithraism, Jesus and Thomas (according to the Syriac Acts of Thomas), and the various illustrations of “Dioscuri in Christian Legends,” set forth by Dr. Harris in his work under this title, which carries the motif far down into the period of legends about Christian Saints who appear in pairs, including the reference to such a pair in Shakespeare’s Henry V: “And Crispin Crispian shall ne’er go by From that day to the ending of the world.”—(Act, IV, 3, 57–58.) There are indeed certain parallels which suggest that Enkidu-Gilgamesh may represent a Babylonian counterpart to the “Heavenly [55]Twins.” In the Indo-Iranian, Greek and Roman mythology, the twins almost invariably act together. In unison they proceed on expeditions to punish enemies.129 But after all, the parallels are of too general a character to be of much moment; and moreover the parallels stop short at the critical point, for Gilgamesh though worsted is not killed by Enkidu, whereas one of the “Heavenly Twins” is always killed by the brother, as Abel is by Cain, and Iphikles by his twin brother Herakles. Even the trait which is frequent in the earliest forms of the “Heavenly Twins,” according to which one is immortal and the other is mortal, though applying in a measure to Enkidu who is killed by Ishtar, while Gilgamesh the offspring of a divine pair is only smitten with disease, is too unsubstantial to warrant more than a general comparison between the Enkidu-Gilgamesh pair and the various forms of the “twin” motif found throughout the ancient world. For all that, the point is of some interest that in the Gilgamesh Epic we should encounter two figures who are portrayed as possessing the same traits and accomplishing feats in common, which suggest a partial parallel to the various forms in which the twin-motif appears in the mythologies, folk-lore and legends of many nations; and it may be that in some of these instances the duplication is due, as in the case of Enkidu and Gilgamesh, to an actual transfer of the traits of one figure to another who usurped his place. In concluding this study of the two recently discovered tablets of the old Babylonian version of the Gilgamesh Epic which has brought us several steps further in the interpretation and in our understanding of the method of composition of the most notable literary production of ancient Babylonia, it will be proper to consider the literary relationship of the old Babylonian to the Assyrian version. We have already referred to the different form in which the names of the chief figures appear in the old Babylonian version, dGish as against dGish-gì(n)-mash, dEn-ki-dũ as against dEn-ki-dú, Ḫu-wa-wa as against Ḫu(m)-ba-ba. Erech appears as Uruk ribîtim, “Erech of [56]the Plazas,” as against Uruk supûri, “walled Erech” (or “Erech within the walls”), in the Assyrian version.130 These variations point to an independent recension for the Assyrian revision; and this conclusion is confirmed by a comparison of parallel passages in our two tablets with the Assyrian version, for such parallels rarely extend to verbal agreements in details, and, moreover, show that the Assyrian version has been elaborated. Beginning with the Pennsylvania tablet, column I is covered in the Assyrian version by tablet I, 5, 25, to 6, 33, though, as pointed out above, in the Assyrian version we have the anticipation of the dreams of Gilgamesh and their interpretation through their recital to Enkidu by his female companion, whereas in the old Babylonian version we have the dreams directly given in a conversation between Gilgamesh and his mother. In the anticipation, there would naturally be some omissions. So lines 4–5 and 12–13 of the Pennsylvania tablet do not appear in the Assyrian version, but in their place is a line (I, 5, 35), to be restored to ”[I saw him and like] a woman I fell in love with him.” which occurs in the old Babylonian version only in connection with the second dream. The point is of importance as showing that in the Babylonian version the first dream lays stress upon the omen of the falling meteor, as symbolizing the coming of Enkidu, whereas the second dream more specifically reveals Enkidu as a man,131 of whom Gilgamesh is instantly enamored. Strikingly variant lines, though conveying the same idea, are frequent. Thus line 14 of the Babylonian version reads “I bore it and carried it to thee” and appears in the Assyrian version (I, 5, 35b supplied from 6, 26) “I threw it (or him) at thy feet”132 [57]with an additional line in elaboration “Thou didst bring him into contact with me”133 which anticipates the speech of the mother (Line 41 = Assyrian version I, 6, 33). Line 10 of the Pennsylvania tablet has pa-ḫi-ir as against iz-za-az I, 5, 31. Line 8 has ik-ta-bi-it as against da-an in the Assyrian version I, 5, 29. More significant is the variant to line 9 “I became weak and its weight I could not bear” as against I, 5, 30. “Its strength was overpowering,134 and I could not endure its weight.” The important lines 31–36 are not found in the Assyrian version, with the exception of I, 6, 27, which corresponds to lines 33–34, but this lack of correspondence is probably due to the fact that the Assyrian version represents the anticipation of the dreams which, as already suggested, might well omit some details. As against this we have in the Assyrian version I, 6, 23–25, an elaboration of line 30 in the Pennsylvania tablet and taken over from the recital of the first dream. Through the Assyrian version I, 6, 31–32, we can restore the closing lines of column I of the Pennsylvania tablet, while with line 33 = line 45 of the Pennsylvania tablet, the parallel between the two versions comes to an end. Lines 34–43 of the Assyrian version (bringing tablet I to a close)135 represent an elaboration of the speech of Ninsun, followed by a further address of Gilgamesh to his mother, and by the determination of Gilgamesh to seek out Enkidu.136 Nothing of this sort appears to have been included in the old Babylonian version.[58]Our text proceeds with the scene between Enkidu and the woman, in which the latter by her charms and her appeal endeavors to lead Enkidu away from his life with the animals. From the abrupt manner in which the scene is introduced in line 43 of the Pennsylvania tablet, it is evident that this cannot be the first mention of the woman. The meeting must have been recounted in the first tablet, as is the case in the Assyrian version.137 The second tablet takes up the direct recital of the dreams of Gilgamesh and then continues the narrative. Whether in the old Babylonian version the scene between Enkidu and the woman was described with the same naïve details, as in the Assyrian version, of the sexual intercourse between the two for six days and seven nights cannot of course be determined, though presumably the Assyrian version, with the tendency of epics to become more elaborate as they pass from age to age, added some realistic touches. Assuming that lines 44–63 of the Pennsylvania tablet—the cohabitation of Enkidu and the address of the woman—is a repetition of what was already described in the first tablet, the comparison with the Assyrian version I, 4, 16–41, not only points to the elaboration of the later version, but likewise to an independent recension, even where parallel lines can be picked out. Only lines 46–48 of the Pennsylvania tablet form a complete parallel to line 21 of column 4 of the Assyrian version. The description in lines 22–32 of column 4 is missing, though it may, of course, have been included in part in the recital in the first tablet of the old Babylonian version. Lines 49–59 of the Pennsylvania tablet are covered by 33–39, the only slight difference being the specific mention in line 58 of the Pennsylvania tablet of Eanna, the temple in Erech, described as “the dwelling of Anu,” whereas in the Assyrian version Eanna is merely referred to as the “holy house” and described as “the dwelling of Anu and Ishtar,” where Ishtar is clearly a later addition. Leaving aside lines 60–61, which may be merely a variant (though independent) of line 39 of column 4 of the Assyrian version, we now have in the Pennsylvania tablet a second speech of the woman to Enkidu (not represented in the Assyrian version) beginning like the first one with alka, “Come” (lines 62–63), in which she asks Enkidu to leave the “accursed ground” in which he dwells. This speech, as the description which follows, extending into columns 3–4, [59]and telling how the woman clothed Enkidu, how she brought him to the sheep folds, how she taught him to eat bread and to drink wine, and how she instructed him in the ways of civilization, must have been included in the second tablet of the Assyrian version which has come down to us in a very imperfect form. Nor is the scene in which Enkidu and Gilgamesh have their encounter found in the preserved portions of the second (or possibly the third) tablet of the Assyrian version, but only a brief reference to it in the fourth tablet,138 in which in Epic style the story is repeated, leading up to the second exploit—the joint campaign of Enkidu and Gilgamesh against Ḫuwawa. This reference, covering only seven lines, corresponds to lines 192–231 of the Pennsylvania tablet; but the former being the repetition and the latter the original recital, the comparison to be instituted merely reveals again the independence of the Assyrian version, as shown in the use of kibsu, “tread” (IV, 2, 46), for šêpu, “foot” (l. 216), i-na-uš, “quake” (line 5C), as against ir-tu-tu (ll. 221 and 226). Such variants as dGish êribam ûl iddin (l. 217) against dGilgamesh ana šurûbi ûl namdin, (IV, 2, 47). and again iṣṣabtûma kima lîm “they grappled at the gate of the family house” (IV, 2, 48), against iṣṣabtûma ina bâb bît emuti, “they grappled at the gate of the family house” (IV, 2, 48), all point once more to the literary independence of the Assyrian version. The end of the conflict and the reconciliation of the two heroes is likewise missing in the Assyrian version. It may have been referred to at the beginning of column 3139 of Tablet IV. Coming to the Yale tablet, the few passages in which a comparison [60]may be instituted with the fourth tablet of the Assyrian version, to which in a general way it must correspond, are not sufficient to warrant any conclusions, beyond the confirmation of the literary independence of the Assyrian version. The section comprised within lines 72–89, where Enkidu’s grief at his friend’s decision to fight Ḫuwawa is described140, and he makes confession of his own physical exhaustion, may correspond to Tablet IV, column 4, of the Assyrian version. This would fit in with the beginning of the reverse, the first two lines of which (136–137) correspond to column 5 of the fourth tablet of the Assyrian version, with a variation “seven-fold fear”141 as against “fear of men” in the Assyrian version. If lines 138–139 (in column 4) of the Yale tablet correspond to line 7 of column 5 of Tablet IV of the Assyrian version, we would again have an illustration of the elaboration of the later version by the addition of lines 3–6. But beyond this we have merely the comparison of the description of Ḫuwawa “Whose roar is a flood, whose mouth is fire, and whose breath is death” which occurs twice in the Yale tablet (lines 110–111 and 196–197), with the same phrase in the Assyrian version Tablet IV, 5, 3—but here, as just pointed out, with an elaboration. Practically, therefore, the entire Yale tablet represents an addition to our knowledge of the Ḫuwawa episode, and until we are fortunate enough to discover more fragments of the fourth tablet of the Assyrian version, we must content ourselves with the conclusions reached from a comparison of the Pennsylvania tablet with the parallels in the Assyrian version. It may be noted as a general point of resemblance in the exterior form of the old Babylonian and Assyrian versions that both were inscribed on tablets containing six columns, three on the obverse and three on the reverse; and that the length of the tablets—an average of 40 to 50 lines—was about the same, thus revealing in the external form a conventiona1 size for the tablets in the older period, which was carried over into later times. [61] 1 See for further details of this royal library, Jastrow, Civilization of Babylonia and Assyria, p. 21 seq. 2 Das Babylonische Nimrodepos (Leipzig, 1884–1891), supplemented by Haupt’s article Die Zwölfte Tafel des Babylonischen Nimrodepos in BA I, pp. 48–79, containing the fragments of the twelfth tablet. The fragments of the Epic in Ashurbanapal’s library—some sixty—represent portions of several copies. Sin-liḳî-unnini—perhaps from Erech, since this name appears as that of a family in tablets from Erech (see Clay, Legal Documents from Erech, Index, p. 73)—is named in a list of texts (K 9717—Haupt’s edition No. 51, line 18) as the editor of the Epic, though probably he was not the only compiler. Since the publication of Haupt’s edition, a few fragments were added by him as an appendix to Alfred Jeremias Izdubar-Nimrod (Leipzig, 1891) Plates II–IV, and two more are embodied in Jensen’s transliteration of all the fragments in the Keilinschriftliche Bibliothek VI; pp. 116–265, with elaborate notes, pp. 421–531. Furthermore a fragment, obtained from supplementary excavations at Kouyunjik, has been published by L. W. King in his Supplement to the Catalogue of the Cuneiform Tablets in the Kouyunjik Collection of the British Cuneiform Tablets in the Kouyunjik Collection of the British Museum No. 56 and PSBA Vol. 36, pp. 64–68. Recently a fragment of the 6th tablet from the excavations at Assur has been published by Ebeling, Keilschrifttexte aus Assur Religiösen Inhalts No. 115, and one may expect further portions to turn up. The designation “Nimrod Epic” on the supposition that the hero of the Babylonian Epic is identical with Nimrod, the “mighty hunter” of Genesis 10, has now been generally abandoned, in the absence of any evidence that the Babylonian hero bore a name like [10n]Nimrod. For all that, the description of Nimrod as the “mighty hunter” and the occurrence of a “hunter” in the Babylonian Epic (Assyrian version Tablet I)—though he is not the hero—points to a confusion in the Hebrew form of the borrowed tradition between Gilgamesh and Nimrod. The latest French translation of the Epic is by Dhorme, Choix de Textes Religieux Assyro-Babyloniens (Paris, 1907), pp. 182–325; the latest German translation by Ungnad-Gressmann, Das Gilgamesch-Epos (Göttingen, 1911), with a valuable analysis and discussion. These two translations now supersede Jensen’s translation in the Keilinschriftliche Bibliothek, which, however, is still valuable because of the detailed notes, containing a wealth of lexicographical material. Ungnad also gave a partial translation in Gressmann-Ranke, Altorientalische Texte and Bilder I, pp. 39–61. In English, we have translations of substantial portions by Muss-Arnolt in Harper’s Assyrian and Babylonian Literature (New York, 1901), pp. 324–368; by Jastrow, Religion of Babylonia and Assyria (Boston, 1898), Chap. XXIII; by Clay in Light on the Old Testament from Babel, pp. 78–84; by Rogers in Cuneiform Parallels to the Old Testament, pp. 80–103; and most recently by Jastrow in Sacred Books and Early Literature of the East (ed. C. F. Horne, New York, 1917), Vol. I, pp. 187–220. 3 See Luckenbill in JAOS, Vol. 37, p. 452 seq. Prof. Clay, it should be added, clings to the older reading, Hammurabi, which is retained in this volume. 4 ZA, Vol. 14, pp. 277–292. 5 The survivor of the Deluge is usually designated as Ut-napishtim in the Epic, but in one passage (Assyrian version, Tablet XI, 196), he is designated as Atra-ḫasis “the very wise one.” Similarly, in a second version of the Deluge story, also found in Ashurbanapal’s library (IV R² additions, p. 9, line 11). The two names clearly point to two versions, which in accordance with the manner of ancient compositions were merged into one. See an article by Jastrow in ZA, Vol. 13, pp. 288–301. 6 Published by Scheil in Recueil des Travaux, etc. Vol. 20, pp. 55–58. 7 The text does not form part of the Gilgamesh Epic, as the colophon, differing from the one attached to the Epic, shows. 8 Ein altbabylonisches Fragment des Gilgamosepos (MVAG 1902, No. 1). 9 On these variant forms of the two names see the discussion below, p. 24. 10 The passage is paralleled by Ecc. 9, 7–9. See Jastrow, A Gentle Cynic, p. 172 seq. 11 Among the Nippur tablets in the collection of the University of Pennsylvania Museum. The fragment was published by Dr. Poebel in his Historical and Grammatical Texts No. 23. See also Poebel in the Museum Journal, Vol. IV, p. 47, and an article by Dr. Langdon in the same Journal, Vol. VII, pp. 178–181, though Langdon fails to credit Dr. Poebel with the discovery and publication of the important tablet. 12 No. 55 in Langdon’s Historical and Religious Texts from the Temple Library of Nippur (Munich, 1914). 13 No. 5 in his Sumerian Liturgical Texts. (Philadelphia, 1917) 14 See on this name below, p. 23. 15 See further below, p. 37 seq. 16 See Poebel, Historical and Grammatical Texts, No. 1, and Jastrow in JAOS, Vol. 36, pp. 122–131 and 274–299. 17 See an article by Jastrow, Sumerian and Akkadian Views of Beginnings (JAOS Vol. 36, pp. 274–299). 18 See on this point Eduard Meyer, Sumerier und Semiten in Babylonien (Berlin, 1906), p. 107 seq., whose view is followed in Jastrow, Civilization of Babylonia and Assyria, p. 121. See also Clay, Empire of the Amorites (Yale University Press, 1919), p. 23 et seq. 19 See the discussion below, p. 24 seq. 20 Dr. Poebel published an article on the tablet in OLZ, 1914, pp. 4–6, in which he called attention to the correct name for the mother of Gilgamesh, which was settled by the tablet as Ninsun. 21 Historical Texts No. 2, Column 2, 26. See the discussion in Historical and Grammatical Texts, p. 123, seq. 22 See Fostat in OLZ, 1915, p. 367. 23 Publications of the University of Pennsylvania Museum, Babylonian Section, Vol. X, No. 3 (Philadelphia, 1917). It is to be regretted that Dr. Langdon should not have given full credit to Dr. Poebel for his discovery of the tablet. He merely refers in an obscure footnote to Dr. Poebel’s having made a copy. 24 E.g., in the very first note on page 211, and again in a note on page 213. 25 Dr. Langdon neglected to copy the signs 4 šú-si = 240 which appear on the edge of the tablet. He also misunderstood the word šú-tu-ur in the colophon which he translated “written,” taking the word from a stem šaṭâru, “write.” The form šú-tu-ur is III, 1, from atâru, “to be in excess of,” and indicates, presumably, that the text is a copy “enlarged” from an older original. See the Commentary to the colophon, p. 86. 26 Museum Journal, Vol. VIII, p. 29. 27 See below, p. 23. 28 I follow the enumeration of tablets, columns and lines in Jensen’s edition, though some fragments appear to have been placed by him in a wrong position. 29 According to Bezold’s investigation, Verbalsuffixformen als Alterskriterien babylonisch-assyrischer Inschriften (Heidelberg Akad. d. Wiss., Philos.-Histor. Klasse, 1910, 9te Abhandlung), the bulk of the tablets in Ashurbanapal’s library are copies of originals dating from about 1500 B.C. It does not follow, however, that all the copies date from originals of the same period. Bezold reaches the conclusion on the basis of various forms for verbal suffixes, that the fragments from the Ashurbanapal Library actually date from three distinct periods ranging from before c. 1450 to c. 700 B.C. 30 “Before thou comest from the mountain, Gilgamesh in Erech will see thy dreams,” after which the dreams are recounted by the woman to Enkidu. The expression “thy dreams” means here “dreams about thee.” (Tablet I, 5, 23–24). 31 Lines 100–101. 32 In a paper read before the American Oriental Society at New Haven, April 4, 1918. 33 See the commentary to col. 4 of the Yale tablet for further details. 34 This is no doubt the correct reading of the three signs which used to be read Iz-tu-bar or Gish-du-bar. The first sign has commonly the value Gish, the second can be read Gin or Gi (Brünnow No. 11900) and the third Mash as well as Bar. See Ungnad in Ungnad-Gressmann, Das Gilgamesch-Epos, p. 76, and Poebel, Historical and Grammatical Texts, p. 123. 35 So also in Sumerian (Zimmern, Sumerische Kultlieder aus altbabylonischer Zeit, No. 196, rev. 14 and 16.) 36 The sign used, LUM (Brünnow No. 11183), could have the value ḫu as well as ḫum. 37 The addition “father-in-law of Moses” to the name Ḫobab b. Re’uel in this passage must refer to Re’uel, and not to Ḫobab. In Judges 4, 11, the gloss “of the Bene Ḫobab, the father-in-law of Moses” must be separated into two: (1) “Bene Ḫobab,” and (2) “father-in-law of Moses.” The latter addition rests on an erroneous tradition, or is intended as a brief reminder that Ḫobab is identical with the son of Re’uel. 38 See his List of Personal Names from the Temple School of Nippur, p. 122. Ḫu-um-ba-bi-tu and ši-kin ḫu-wa-wa also occur in Omen Texts (CT XXVII, 4, 8–9 = Pl. 3, 17 = Pl. 6, 3–4 = CT XXVIII, 14, 12). The contrast to ḫuwawa is ligru, “dwarf” (CT XXVII, 4, 12 and 14 = Pl. 6, 7.9 = Pl. 3, 19). See Jastrow, Religion Babyloniens und Assyriens, II, p. 913, Note 7. Ḫuwawa, therefore, has the force of “monster.” 39 Ungnad-Gressmann, Das Gilgamesch-Epos, p. 111 seq. 40 Ungnad, 1. c. p. 77, called attention to this name, but failed to draw the conclusion that Ḫu(m)baba therefore belongs to the West and not to the East. 41 First pointed out by Ungnad in OLZ 1910, p. 306, on the basis of CT XVIII, 30, 10, where En-gi-dú appears in the column furnishing phonetic readings. 42 See Clay Amurru, pp. 74, 129, etc. 43 Tablet I, 2, 39–40; 3, 6–7 and 33–34; 4, 3–4. 44 Tablet I, 2, 1 and IX, 2, 16. Note also the statement about Gilgamesh that “his body is flesh of the gods” (Tablet IX, 2, 14; X, 1, 7). 45 BOR IV, p. 264. 46 Lewin, Die Scholien des Theodor bar Koni zur Patriarchengeschichte (Berlin, 1905), p. 2. See Gressmann in Ungnad-Gressmann, Das Gilgamesch-Epos, p. 83, who points out that the first element of גלמגוס compared with the second of גמיגמוס gives the exact form that we require, namely, Gilgamos. 47 Tablet I, col. 2, is taken up with this episode. 48 See Poebel, Historical and Grammatical Texts, p. 123. 49 See Poebel, Historical Texts No. 2, col. 2, 26. 50 Hilprecht, Old Babylonian Inscriptions I, 1 No. 26. 51 Delitzsch, Assyrische Lesestücke, p. 88, VI, 2–3. Cf. also CT XXV, 28(K 7659) 3, where we must evidently supply [Esigga]-tuk, for which in the following line we have again Gish-bil-ga-mesh as an equivalent. See Meissner, OLZ 1910, 99. 52 See, e.g., Barton, Haverford Collection II No. 27, Col. I, 14, etc. 53 Deimel, Pantheon Babylonicum, p. 95. 54 CT XII, 50 (K 4359) obv. 17. 55 See Barton, Origin and Development of Babylonian Writing, II, p. 99 seq., for various explanations, though all centering around the same idea of the picture of fire in some form. 56 See the passages quoted by Poebel, Historical and Grammatical Texts, p. 126. 57 E.g., Genesis 4, 20, Jabal, “the father of tent-dwelling and cattle holding;” Jubal (4, 21), “the father of harp and pipe striking.” 58 See particularly the plays (in the J. Document) upon the names of the twelve sons of Jacob, which are brought forward either as tribal characteristics, or as suggested by some incident or utterance by the mother at the birth of each son. 59 The designation is variously explained by Arabic writers. See Beidhawi’s Commentary (ed. Fleischer), to Súra 18, 82. 60 The writing Gish-gi-mash as an approach to the pronunciation Gilgamesh would thus represent the beginning of the artificial process which seeks to interpret the first syllable as “hero.” 61 See above, p. 27. 62 Poebel, Historical Texts, p. 115 seq. 63 Many years ago (BA III, p. 376) I equated Etana with Ethan in the Old Testament—therefore a West Semitic name. 64 See Clay, The Empire of the Amorites, p. 80. 65 Professor Clay strongly favors an Amoritic origin also for Gilgamesh. His explanation of the name is set forth in his recent work on The Empire of the Amorites, page 89, and is also referred to in his work on Amurru, page 79, and in his volume of Miscellaneous Inscriptions in the Yale Babylonian Collection, page 3, note. According to Professor Clay the original form of the hero’s name was West Semitic, and was something like Bilga-Mash, the meaning of which was perhaps “the offspring of Mash.” For the first element in this division of the name cf. Piliḳam, the name of a ruler of an early dynasty, and Balaḳ of the Old Testament. In view of the fact that the axe figures so prominently in the Epic as an instrument wielded by Gilgamesh, Professor Clay furthermore thinks it reasonable to assume that the name was interpreted by the Babylonian scribe as “the axe of Mash.” In this way he would account for the use of the determinative for weapons, which is also the sign Gish, in the name. It is certainly noteworthy that the ideogram Gish-Tún in the later form of Gish-Tún-mash = pašu, “axe,” CT XVI, 38:14b, etc. Tun also = pilaḳu “axe,” CT xii, 10:34b. Names with similar element (besides Piliḳam) are Belaḳu of the Hammurabi period, Bilaḳḳu of the Cassite period, etc. It is only proper to add that Professor Jastrow assumes the responsibility for the explanation of the form and etymology of the name Gilgamesh proposed in this volume. The question is one in regard to which legitimate differences of opinion will prevail among scholars until through some chance a definite decision, one way or the other, can be reached. 66 me-iḫ-rù (line 191). 67 Tablet I, 5, 23. Cf. I, 3, 2 and 29. 68 Tablet IV, 4, 7 and I, 5, 3. 69 Assyrian version, Tablet II, 3b 34, in an address of Shamash to Enkidu. 70 So Assyrian version, Tablet VIII, 3, 11. Also supplied VIII, 5, 20 and 21; and X, 1, 46–47 and 5, 6–7. 71 Tablet XII, 3, 25. 72 Ward, Seal Cylinders of Western Asia, Chap. X, and the same author’s Cylinders and other Ancient Oriental Seals—Morgan collection Nos. 19–50. 73 E.g., Ward No. 192, Enkidu has human legs like Gilgamesh; also No. 189, where it is difficult to say which is Gilgamesh, and which is Enkidu. The clothed one is probably Gilgamesh, though not infrequently Gilgamesh is also represented as nude, or merely with a girdle around his waist. 74 E.g., Ward, Nos. 173, 174, 190, 191, 195 as well as 189 and 192. 75 On the other hand, in Ward Nos. 459 and 461, the conflict between the two heroes is depicted with the heroes distinguished in more conventional fashion, Enkidu having the hoofs of an animal, and also with a varying arrangement of beard and hair. 76 See Jastrow, Religion of Babylonia and Assyria (Boston, 1898), p. 468 seq. 77 Ungnad-Gressmann, Das Gilgamesch-Epos, p. 90 seq. 78 Pennsylvania tablet, l. 198 = Assyrian version, Tablet IV, 2, 37. 79 “Enkidu blocked the gate” (Pennsylvania tablet, line 215) = Assyrian version Tablet IV, 2, 46: “Enkidu interposed his foot at the gate of the family house.” 80 Pennsylvania tablet, lines 218 and 224. 81 Yale tablet, line 198; also to be supplied lines 13–14. 82 Yale tablet, lines 190 and 191. 83 PSBA 1914, 65 seq. = Jensen III, 1a, 4–11, which can now be completed and supplemented by the new fragment. 84 I.e., Enkidu will save Gilgamesh. 85 These two lines impress one as popular sayings—here applied to Enkidu. 86 King’s fragment, col. I, 13–27, which now enables us to complete Jensen III, 1a, 12–21. 87 Yale tablet, lines 252–253. 88 Yale tablet, lines 143–148 = Assyrian version, Tablet IV, 6, 26 seq. 89 Assyrian version, Tablet III, 2a, 13–14. 90 Lines 215–222. 91 Assyrian version, Tablet V, Columns 3–4. We have to assume that in line 13 of column 4 (Jensen, p. 164), Enkidu takes up the thread of conversation, as is shown by line 22: “Enkidu brought his dream to him and spoke to Gilgamesh.” 92 Assyrian version, Tablet VI, lines 146–147. 93 Lines 178–183. 94 Lines 176–177. 95 Tablet VII, Column 6. 96 Assyrian version, Tablet VI, 200–203. These words are put into the mouth of Gilgamesh (lines 198–199). It is, therefore, unlikely that he would sing his own praise. Both Jensen and Ungnad admit that Enkidu is to be supplied in at least one of the lines. 97 Lines 109 and 112. 98 Assyrian version, Tablet IX, 1, 8–9. 99 Tablet VIII, 5, 2–6. 100 So also Gressmann in Ungnad-Gressmann, Das Gilgamesch-Epos, p. 97, regards Enkidu as the older figure. 101 See Jastrow, Adam and Eve in Babylonian Literature, AJSL, Vol. 15, pp. 193–214. 102 Assyrian version, Tablet I, 2, 31–36. 103 It will be recalled that Enkidu is always spoken of as “born in the field.” 104 Note the repetition ibtani “created” in line 33 of the “man of Anu” and in line 35 of the offspring of Ninib. The creation of the former is by the “heart,” i.e., by the will of Aruru, the creation of the latter is an act of moulding out of clay. 105 Tablet I, Column 3. 106 Following as usual the enumeration of lines in Jensen’s edition. 107 An analogy does not involve a dependence of one tale upon the other, but merely that both rest on similar traditions, which may have arisen independently. 108 Note that the name of Eve is not mentioned till after the fall (Genesis 3, 20). Before that she is merely ishsha, i.e., “woman,” just as in the Babylonian tale the woman who guides Enkidu is ḫarimtu, “woman.” 109 “And he drank and became drunk” (Genesis 9, 21). 110 “His heart became glad and his face shone” (Pennsylvania Tablet, lines 100–101). 111 That in the combination of this Enkidu with tales of primitive man, inconsistent features should have been introduced, such as the union of Enkidu with the woman as the beginning of a higher life, whereas the presence of a hunter and his father shows that human society was already in existence, is characteristic of folk-tales, which are indifferent to details that may be contradictory to the general setting of the story. 112 Pennsylvania tablet, lines 102–104. 113 Line 105. 114 Tablet I, 1, 9. See also the reference to the wall of Erech as an “old construction” of Gilgamesh, in the inscription of An-Am in the days of Sin-gamil (Hilprecht, Old Babylonian Inscriptions, I, No. 26.) Cf IV R² 52, 3, 53. 115 The invariable designation in the Assyrian version as against Uruk ribîtim, “Erech of the plazas,” in the old Babylonian version. 116 In Ungnad-Gressmann, Das Gilgamesch-Epos, p. 123 seq. 117 See Jensen, p. 266. Gilgamesh is addressed as “judge,” as the one who inspects the divisions of the earth, precisely as Shamash is celebrated. In line 8 of the hymn in question, Gilgamesh is in fact addressed as Shamash. 118 The darkness is emphasized with each advance in the hero’s wanderings (Tablet IX, col. 5). 119 This tale is again a nature myth, marking the change from the dry to the rainy season. The Deluge is an annual occurrence in the Euphrates Valley through the overflow [50n]of the two rivers. Only the canal system, directing the overflow into the fields, changed the curse into a blessing. In contrast to the Deluge, we have in the Assyrian creation story the drying up of the primeval waters so that the earth makes its appearance with the change from the rainy to the dry season. The world is created in the spring, according to the Akkadian view which is reflected in the Biblical creation story, as related in the P. document. See Jastrow, Sumerian and Akkadian Views of Beginnings (JAOS, Vol 36, p. 295 seq.). 120 Aš-am in Sumerian corresponding to the Akkadian Šabaṭu, which conveys the idea of destruction. 121 The month is known as the “Mission of Ishtar” in Sumerian, in allusion to another nature myth which describes Ishtar’s disappearance from earth and her mission to the lower world. 122 Historical Texts No. 1. The Sumerian name of the survivor is Zi-ū-gíd-du or perhaps Zi-ū-sū-du (cf. King, Legends of Babylon and Egypt, p. 65, note 4), signifying “He who lengthened the day of life,” i.e., the one of long life, of which Ut-napishtim (“Day of Life”) in the Assyrian version seems to be an abbreviated Akkadian rendering, [n]with the omission of the verb. So King’s view, which is here followed. See also CT XVIII, 30, 9, and Langdon, Sumerian Epic of Paradise, p. 90, who, however, enters upon further speculations that are fanciful. 123 See the translation in Ungnad-Gressmann, Das Gilgamesch-Epos, pp. 69, seq. and 73. 124 According to Professor Clay, quite certainly Amurru, just as in the case of Enkidu. 125 Gressmann in Ungnad-Gressmann, Das Gilgamesch-Epos, p. 100 seq. touches upon this motif, but fails to see the main point that the companions are also twins or at least brothers. Hence such examples as Abraham and Lot, David and Jonathan, Achilles and Patroclus, Eteokles and Polyneikes, are not parallels to Gilgamesh-Enkidu, but belong to the enlargement of the motif so as to include companions who are not regarded as brothers. 126 Or Romus. See Rendell Harris, l. c., p. 59, note 2. 127 One might also include the primeval pair Yama-Yami with their equivalents in Iranian mythology (Carnoy, Iranian Mythology, p. 294 seq.). 128 Becoming, however, a triad and later increased to seven. Cf. Rendell Harris, l. c., p. 32. 129 I am indebted to my friend, Professor A. J. Carnoy, of the University of Louvain, for having kindly gathered and placed at my disposal material on the “twin-brother” motif from Indo-European sources, supplemental to Rendell Harris’ work. 130 On the other hand, Uruk mâtum for the district of Erech, i.e., the territory over which the city holds sway, appears in both versions (Pennsylvania tablet, 1. 10 = Assyrian version I, 5, 36). 131 “My likeness” (line 27). It should be noted, however, that lines 32–44 of I, 5, in Jensen’s edition are part of a fragment K 9245 (not published, but merely copied by Bezold and Johns, and placed at Jensen’s disposal), which may represent a duplicate to I, 6, 23–34, with which it agrees entirely except for one line, viz., line 34 of K 9245 which is not found in column 6, 23–34. If this be correct, then there is lacking after line 31 of column 5, the interpretation of the dream given in the Pennsylvania tablet in lines 17–23. 132 ina šap-li-ki, literally, “below thee,” whereas in the old Babylonian version we have ana ṣi-ri-ka, “towards thee.” 133 Repeated I, 6, 28. 134 ul-tap-rid ki-is-su-šú-ma. The verb is from parâdu, “violent.” For kissu, “strong,” see CT XVI, 25, 48–49. Langdon (Gilgamesh Epic, p. 211, note 5) renders the phrase: “he shook his murderous weapon!!”—another illustration of his haphazard way of translating texts. 135 Shown by the colophon (Jeremias, Izdubar-Nimrod, Plate IV.) 136 Lines 42–43 must be taken as part of the narrative of the compiler, who tells us that after the woman had informed Enkidu that Gilgamesh already knew of Enkidu’s coming through dreams interpreted by Ninsun, Gilgamesh actually set out and encountered Enkidu. 137 Tablet I, col. 4. See also above, p. 19. 138 IV, 2, 44–50. The word ullanum, (l.43) “once” or “since,” points to the following being a reference to a former recital, and not an original recital. 139 Only the lower half (Haupt’s edition, p. 82) is preserved. 140 “The eyes of Enkidu were filled with tears,” corresponding to IV, 4, 10. 141 Unless indeed the number “seven” is a slip for the sign ša. See the commentary to the line. Pennsylvania Tablet The 240 lines of the six columns of the text are enumerated in succession, with an indication on the margin where a new column begins. This method, followed also in the case of the Yale tablet, seems preferable to Langdon’s breaking up of the text into Obverse and Reverse, with a separate enumeration for each of the six columns. In order, however, to facilitate a comparison with Langdon’s edition, a table is added: Obverse Col. I, 1 = Line 1 of our text. ,, I, 5 = ,, 5 ,, ,, ,, ,, I, 10 = ,, 10 ,, ,, ,, ,, I, 15 = ,, 15 ,, ,, ,, ,, I, 20 = ,, 20 ,, ,, ,, ,, I, 25 = ,, 25 ,, ,, ,, ,, I, 30 = ,, 30 ,, ,, ,, ,, I, 35 = ,, 35 ,, ,, ,, Col. II, 1 = Line 41 ,, ,, ,, ,, II, 5 = ,, 45 ,, ,, ,, ,, II, 10 = ,, 50 ,, ,, ,, ,, II, 15 = ,, 55 ,, ,, ,, ,, II, 20 = ,, 60 ,, ,, ,, ,, II, 25 = ,, 65 ,, ,, ,, ,, II, 30 = ,, 70 ,, ,, ,, ,, II, 35 = ,, 75 ,, ,, ,, Col. III, 1 = Line 81 ,, ,, ,, ,, III, 5 = ,, 85 ,, ,, ,, ,, III, 10 = ,, 90 ,, ,, ,, ,, III, 15 = ,, 95 ,, ,, ,, ,, III, 26 = ,, 100 ,, ,, ,, ,, III, 25 = ,, 105 ,, ,, ,, ,, III, 30 = ,, 110 ,, ,, ,, ,, III, 35 = ,, 115 ,, ,, ,, Reverse Col. I, 1 (= Col. IV) = Line 131 of our text. ,, I, 5 = ,, 135 ,, ,, ,, ,, I, 10 = ,, 140 ,, ,, ,, ,, I, 15 = ,, 145 ,, ,, ,, ,, I, 20 = ,, 150 ,, ,, ,, ,, I, 25 = ,, 155 ,, ,, ,, ,, I, 30 = ,, 160 ,, ,, ,, ,, II, 1 (= Col. V) = Line 171 ,, ,, ,, ,, II, 5 = ,, 175 ,, ,, ,, ,, II, 10 = ,, 180 ,, ,, ,, ,, II, 15 = ,, 185 ,, ,, ,, ,, II, 20 = ,, 190 ,, ,, ,, ,, II, 25 = ,, 195 ,, ,, ,, ,, II, 30 = ,, 200 ,, ,, ,, ,, III, 1 (= Col. VI) = Line 208 ,, ,, ,, ,, III, 5 = ,, 212 ,, ,, ,, ,, III, 10 = ,, 217 ,, ,, ,, ,, III, 15 = ,, 222 ,, ,, ,, ,, III, 20 = ,, 227 ,, ,, ,, ,, III, 25 = ,, 232 ,, ,, ,, ,, III, 30 = ,, 237 ,, ,, ,, ,, III, 33 = ,, 240 ,, ,, ,, [62] Pennsylvania Tablet. Transliteration. Col. I. 1it-bi-e-ma dGiš šú-na-tam i-pa-áš-šar 2iz-za-kàr-am a-na um-mi-šú 3um-mi i-na šá-at mu-ši-ti-ia 4šá-am-ḫa-ku-ma at-ta-na-al-la-ak 5i-na bi-ri-it it-lu-tim 6ib-ba-šú-nim-ma ka-ka-bu šá-ma-i 7[ki]-iṣ-rù šá A-nim im-ḳu-ut a-na ṣi-ri-ia 8áš-ši-šú-ma ik-ta-bi-it e-li-ia 9ú-ni-iš-šú-ma nu-uš-šá-šú ú-ul il-ti-’i 10Urukki ma-tum pa-ḫi-ir e-li-šú 11it-lu-tum ú-na-šá-ku ši-pi-šú 12ú-um-mi-id-ma pu-ti 13i-mi-du ia-ti 14áš-ši-a-šú-ma ab-ba-la-áš-šú a-na ṣi-ri-ki 15um-mi dGiš mu-di-a-at ka-la-ma 16iz-za-kàr-am a-na dGiš 17mi-in-di dGiš šá ki-ma ka-ti 18i-na ṣi-ri i-wa-li-id-ma 19ú-ra-ab-bi-šú šá-du-ú 20ta-mar-šú-ma [kima Sal(?)] ta-ḫa-du at-ta 21it-lu-tum ú-na-šá-ku ši-pi-šú 22tí-iṭ-ṭi-ra-áš-[šú tu-ut]-tu-ú-ma 23ta-tar-ra-[as-su] a-na ṣi-[ri]-ia 24[uš]-ti-nim-ma i-ta-mar šá-ni-tam[63] 25[šú-na]-ta i-ta-wa-a-am a-na um-mi-šú 26[um-mi] a-ta-mar šá-ni-tam 27[šú-na-tu a-ta]-mar e-mi-a i-na su-ḳi-im 28[šá Uruk]ki ri-bi-tim 29ḫa-aṣ-ṣi-nu na-di-i-ma 30e-li-šú pa-aḫ-ru 31ḫa-aṣ-ṣi-nu-um-ma šá-ni bu-nu-šú 32a-mur-šú-ma aḫ-ta-du a-na-ku 33a-ra-am-šú-ma ki-ma áš-šá-tim 34a-ḫa-ab-bu-ub el-šú 35el-ki-šú-ma áš-ta-ka-an-šú 36a-na a-ḫi-ia 37um-mi dGiš mu-da-at [ka]-la-ma 38[iz-za-kàr-am a-na dGiš] 39[dGiš šá ta-mu-ru amêlu] 40[ta-ḫa-ab-bu-ub ki-ma áš-šá-tim el-šú] Col. II. 41áš-šum uš-[ta]-ma-ḫa-ru it-ti-ka 42dGiš šú-na-tam i-pa-šar 43dEn-ki-[dũ wa]-ši-ib ma-ḫar ḫa-ri-im-tim 44ur-[šá ir]-ḫa-mu di-da-šá(?) ip-tí-[e] 45[dEn-ki]-dũ im-ta-ši a-šar i-wa-al-du 46ûm, 6 ù 7 mu-ši-a-tim 47dEn-[ki-dũ] ti-bi-i-ma 48šá-[am-ka-ta] ir-ḫi 49ḫa-[ri-im-tum pa-a]-šá i-pu-šá-am-ma 50iz-za-[kàr-am] a-na dEn-ki-dũ 51a-na-tal-ka dEn-ki-dũ ki-ma ili ta-ba-áš-ši 52am-mi-nim it-ti na-ma-áš-te-e 53ta-at-ta-[na-al]-ak ṣi-ra-am[64] 54al-kam lu-úr-di-ka 55a-na libbi [Urukki] ri-bi-tim 56a-na bît [el]-lim mu-šá-bi šá A-nim 57dEn-ki-dũ ti-bi lu-ru-ka 58a-na Ê-[an]-na mu-šá-bi šá A-nim 59a-šar [dGiš gi]-it-ma-[lu] ne-pi-ši-tim 60ù at-[ta] ki-[ma Sal ta-ḫa]-bu-[ub]-šú 61ta-[ra-am-šú ki-ma] ra-ma-an-ka 62al-ka ti-ba i-[na] ga-ag-ga-ri 63ma-a-ag-ri-i-im 64iš-me a-wa-as-sa im-ta-ḫar ga-ba-šá 65mi-il-[kum] šá aššatim 66im-ta-ḳu-ut a-na libbi-šú 67iš-ḫu-ut li-ib-šá-am 68iš-ti-nam ú-la-ab-bi-iš-sú 69li-ib-[šá-am] šá-ni-a-am 70ši-i it-ta-al-ba-áš 71ṣa-ab-tat ga-as-su 72ki-ma [ili] i-ri-id-di-šú 73a-na gu-up-ri šá-ri-i-im 74a-šar tar-ba-ṣi-im 75i-na [áš]-ri-šú [im]-ḫu-ruri-ia-ú 76[ù šú-u dEn-ki-dũ i-lit-ta-šú šá-du-um-ma] 77[it-ti ṣabâti-ma ik-ka-la šam-ma] 78[it-ti bu-lim maš-ḳa-a i-šat-ti] 79[it-ti na-ma-áš-te-e mê i-ṭab lib-ba-šú] (Perhaps one additional line missing.) Col. III. 81ši-iz-ba šá na-ma-áš-te-e 82i-te-en-ni-ik 83a-ka-lam iš-ku-nu ma-ḫar-šú 84ib-tí-ik-ma i-na-at-tal 85ù ip-pa-al-la-as[65] 86ú-ul i-di dEn-ki-dũ 87aklam a-na a-ka-lim 88šikaram a-na šá-te-e-im 89la-a lum-mu-ud 90ḫa-ri-im-tum pi-šá i-pu-šá-am-ma 91iz-za-kàr-am a-na dEn-ki-dũ 92a-ku-ul ak-lam dEn-ki-dũ 93zi-ma-at ba-la-ṭi-im 94šikaram ši-ti ši-im-ti ma-ti 95i-ku-ul a-ak-lam dEn-ki-dũ 96a-di ši-bi-e-šú 97šikaram iš-ti-a-am 987 aṣ-ṣa-am-mi-im 99it-tap-šar kab-ta-tum i-na-an-gu 100i-li-iṣ libba-šú-ma 101pa-nu-šú [it]-tam-ru 102ul-tap-pi-it [lùŠÚ]-I 103šú-ḫu-ra-am pa-ga-ar-šú 104šá-am-nam ip-ta-šá-áš-ma 105a-we-li-iš i-we 106il-ba-áš li-ib-šá-am 107ki-ma mu-ti i-ba-áš-ši 108il-ki ka-ak-ka-šú 109la-bi ú-gi-ir-ri 110uš-sa-ak-pu re’ûti mu-ši-a-tim 111ut-tap-pi-iš šib-ba-ri 112la-bi uk-ta-ši-id 113it-ti-[lu] na-ki-[di-e] ra-bu-tum 114dEn-ki-dũ ma-aṣ-ṣa-ar-šú-nu 115a-we-lum giš-ru-um 116iš-te-en it-lum 117a-na [na-ki-di-e(?) i]-za-ak-ki-ir (About five lines missing.) Col. IV. (About eight lines missing.) 131i-ip-pu-uš ul-ṣa-am 132iš-ši-ma i-ni-i-šú 133i-ta-mar a-we-lam[66] 134iz-za-kàr-am a-na ḫarimtim 135šá-am-ka-at uk-ki-ši a-we-lam 136a-na mi-nim il-li-kam 137zi-ki-ir-šú lu-uš-šú 138ḫa-ri-im-tum iš-ta-si a-we-lam 139i-ba-uš-su-um-ma i-ta-mar-šú 140e-di-il e-eš ta-ḫi-[il-la]-am 141lim-nu a-la-ku ma-na-aḫ-[ti]-ka 142e-pi-šú i-pu-šá-am-ma 143iz-za-kàr-am a-na dEn-[ki-dũ] 144bi-ti-iš e-mu-tim ik …… 145ši-ma-a-at ni-ši-i-ma 146tu-a-(?)-ar e-lu-tim 147a-na âli(?) dup-šak-ki-i e-ṣi-en 148uk-la-at âli(?) e-mi-sa a-a-ḫa-tim 149a-na šarri šá Urukki ri-bi-tim 150pi-ti pu-uk epiši(-ši) a-na ḫa-a-a-ri 151a-na dGiš šarri šá Urukki ri-bi-tim 152pi-ti pu-uk epiši(-ši) 153a-na ḫa-a-a-ri 154áš-ša-at ši-ma-tim i-ra-aḫ-ḫi 155šú-ú pa-na-nu-um-ma 156mu-uk wa-ar-ka-nu 157i-na mi-il-ki šá ili ga-bi-ma 158i-na bi-ti-iḳ a-bu-un-na-ti-šú 159ši-ma-as-su 160a-na zi-ik-ri it-li-im 161i-ri-ku pa-nu-šú (About three lines missing.) [67] Col. V. (About six lines missing.) 171i-il-la-ak [dEn-ki-dũ i-na pa-ni] 172u-šá-am-ka-at [wa]-ar-ki-šú 173i-ru-ub-ma a-na libbi Urukki ri-bi-tim 174ip-ḫur um-ma-nu-um i-na ṣi-ri-šú 175iz-zi-za-am-ma i-na su-ḳi-im 176šá Urukki ri-bi-tim 177pa-aḫ-ra-a-ma ni-šú 178i-ta-wa-a i-na ṣi-ri-šú 179a-na ṣalam dGiš ma-ši-il pi-it-tam 180la-nam šá-pi-il 181si-ma …. [šá-ki-i pu]-uk-ku-ul 182............. i-pa-ka-du 183i-[na mâti da-an e-mu]-ki i-wa 184ši-iz-ba šá na-ma-aš-te-e 185i-te-en-ni-ik 186ka-a-a-na i-na [libbi] Urukki kak-ki-a-tum 187it-lu-tum ú-te-el-li-lu 188šá-ki-in ur-šá-nu 189a-na itli šá i-šá-ru zi-mu-šú 190a-na dGiš ki-ma i-li-im 191šá-ki-iš-šum me-iḫ-rù 192a-na dIš-ḫa-ra ma-a-a-lum 193na-di-i-ma 194dGiš it-[ti-il-ma wa-ar-ka-tim] 195i-na mu-ši in-ni-[ib-bi]-it 196i-na-ag-šá-am-ma 197it-ta-[zi-iz dEn-ki-dũ] i-na sûḳim 198ip-ta-ra-[aṣ a-la]-ak-tam 199šá dGiš 200[a-na e-pi-iš] da-na-ni-iš-šú (About three lines missing.) [68] Col. VI. (About four lines missing.) 208šar(?)-ḫa 209dGiš … 210i-na ṣi-ri-[šú il-li-ka-am dEn-ki-dũ] 211i-ḫa-an-ni-ib [pi-ir-ta-šú] 212it-bi-ma [il-li-ik] 213a-na pa-ni-šú 214it-tam-ḫa-ru i-na ri-bi-tum ma-ti 215dEn-ki-dũ ba-ba-am ip-ta-ri-ik 216i-na ši-pi-šú 217dGiš e-ri-ba-am ú-ul id-di-in 218iṣ-ṣa-ab-tu-ma ki-ma li-i-im 219i-lu-du 220zi-ip-pa-am ’i-bu-tu 221i-ga-rum ir-tu-tu 222dGiš ù dEn-ki-dũ 223iṣ-ṣa-ab-tu-ú-ma 224ki-ma li-i-im i-lu-du 225zi-ip-pa-am ’i-bu-tu 226i-ga-rum ir-tu-tú 227ik-mi-is-ma dGiš 228i-na ga-ag-ga-ri ši-ip-šú 229ip-ši-iḫ uz-za-šú-ma 230i-ni-iḫ i-ra-as-su 231iš-tu i-ra-su i-ni-ḫu 232dEn-ki-dũ a-na šá-ši-im 233iz-za-kàr-am a-na dGiš 234ki-ma iš-te-en-ma um-ma-ka 235ú-li-id-ka 236ri-im-tum šá su-pu-ri 237dNin-sun-na 238ul-lu e-li mu-ti ri-eš-ka 239šar-ru-tú šá ni-ši 240i-ši-im-kum dEn-lil 241 duppu 2 kam-ma 242šú-tu-ur e-li ………………… 243 4 šú-ši [62] Translation. Col. I. 1Gish sought to interpret the dream; 2Spoke to his mother: 3“My mother, during my night 4I became strong and moved about 5among the heroes; 6And from the starry heaven 7A meteor(?) of Anu fell upon me: 8I bore it and it grew heavy upon me, 9I became weak and its weight I could not endure. 10The land of Erech gathered about it. 11The heroes kissed its feet.1 12It was raised up before me. 13They stood me up.2 14I bore it and carried it to thee.” 15The mother of Gish, who knows all things, 16Spoke to Gish: 17“Some one, O Gish, who like thee 18In the field was born and 19Whom the mountain has reared, 20Thou wilt see (him) and [like a woman(?)] thou wilt rejoice. 21Heroes will kiss his feet. 22Thou wilt spare [him and wilt endeavor] 23To lead him to me.” 24He slept and saw another[63] 25Dream, which he reported to his mother: 26[“My mother,] I have seen another 27[Dream.] My likeness I have seen in the streets 28[Of Erech] of the plazas. 29An axe was brandished, and 30They gathered about him; 31And the axe made him angry. 32I saw him and I rejoiced, 33I loved him as a woman, 34I embraced him. 35I took him and regarded him 36As my brother.” 37The mother of Gish, who knows all things, 38[Spoke to Gish]: 39[“O Gish, the man whom thou sawest,] 40[Whom thou didst embrace like a woman]. Col II. 41(means) that he is to be associated with thee.” 42Gish understood the dream. 43[As] Enki[du] was sitting before the woman, 44[Her] loins(?) he embraced, her vagina(?) he opened. 45[Enkidu] forgot the place where he was born. 46Six days and seven nights 47Enkidu continued 48To cohabit with [the courtesan]. 49[The woman] opened her [mouth] and 50Spoke to Enkidu: 51“I gaze upon thee, O Enkidu, like a god art thou! 52Why with the cattle 53Dost thou [roam] across the field?[64] 54Come, let me lead thee 55into [Erech] of the plazas, 56to the holy house, the dwelling of Anu, 57O, Enkidu arise, let me conduct thee 58To Eanna, the dwelling of Anu, 59The place [where Gish is, perfect] in vitality. 60And thou [like a wife wilt embrace] him. 61Thou [wilt love him like] thyself. 62Come, arise from the ground 63(that is) cursed.” 64He heard her word and accepted her speech. 65The counsel of the woman 66Entered his heart. 67She stripped off a garment, 68Clothed him with one. 69Another garment 70She kept on herself. 71She took hold of his hand. 72Like [a god(?)] she brought him 73To the fertile meadow, 74The place of the sheepfolds. 75In that place they received food; 76[For he, Enkidu, whose birthplace was the mountain,] 77[With the gazelles he was accustomed to eat herbs,] 78[With the cattle to drink water,] 79[With the water beings he was happy.] (Perhaps one additional line missing.) Col. III. 81Milk of the cattle 82He was accustomed to suck. 83Food they placed before him, 84He broke (it) off and looked 85And gazed.[65] 86Enkidu had not known 87To eat food. 88To drink wine 89He had not been taught. 90The woman opened her mouth and 91Spoke to Enkidu: 92“Eat food, O Enkidu, 93The provender of life! 94Drink wine, the custom of the land!” 95Enkidu ate food 96Till he was satiated. 97Wine he drank, 98Seven goblets. 99His spirit was loosened, he became hilarious. 100His heart became glad and 101His face shone. 102[The barber(?)] removed 103The hair on his body. 104He was anointed with oil. 105He became manlike. 106He put on a garment, 107He was like a man. 108He took his weapon; 109Lions he attacked, 110(so that) the night shepherds could rest. 111He plunged the dagger; 112Lions he overcame. 113The great [shepherds] lay down; 114Enkidu was their protector. 115The strong man, 116The unique hero, 117To [the shepherds(?)] he speaks: (About five lines missing.) Col. IV. (About eight lines missing.) 131Making merry. 132He lifted up his eyes, 133He sees the man.[66] 134He spoke to the woman: 135“O, courtesan, lure on the man. 136Why has he come to me? 137His name I will destroy.” 138The woman called to the man 139Who approaches to him3 and he beholds him. 140“Away! why dost thou [quake(?)] 141Evil is the course of thy activity.”4 142Then he5 opened his mouth and 143Spoke to Enkidu: 144”[To have (?)] a family home 145Is the destiny of men, and 146The prerogative(?) of the nobles. 147For the city(?) load the workbaskets! 148Food supply for the city lay to one side! 149For the King of Erech of the plazas, 150Open the hymen(?), perform the marriage act! 151For Gish, the King of Erech of the plazas, 152Open the hymen(?), 153Perform the marriage act! 154With the legitimate wife one should cohabit. 155So before, 156As well as in the future.6 157By the decree pronounced by a god, 158From the cutting of his umbilical cord 159(Such) is his fate.” 160At the speech of the hero 161His face grew pale. (About three lines missing.) [67] Col. V. (About six lines missing.) 171[Enkidu] went [in front], 172And the courtesan behind him. 173He entered into Erech of the plazas. 174The people gathered about him. 175As he stood in the streets 176Of Erech of the plazas, 177The men gathered, 178Saying in regard to him: 179“Like the form of Gish he has suddenly become; 180shorter in stature. 181[In his structure high(?)], powerful, 182.......... overseeing(?) 183In the land strong of power has he become. 184Milk of cattle 185He was accustomed to suck.” 186Steadily(?) in Erech ..... 187The heroes rejoiced. 188He became a leader. 189To the hero of fine appearance, 190To Gish, like a god, 191He became a rival to him.7 192For Ishḫara a couch 193Was stretched, and 194Gish [lay down, and afterwards(?)] 195In the night he fled. 196He approaches and 197[Enkidu stood] in the streets. 198He blocked the path 199of Gish. 200At the exhibit of his power, (About three lines missing.) [68] Col. VI. (About four lines missing.) 208Strong(?) … 209Gish 210Against him [Enkidu proceeded], 211[His hair] luxuriant. 212He started [to go] 213Towards him. 214They met in the plaza of the district. 215Enkidu blocked the gate 216With his foot, 217Not permitting Gish to enter. 218They seized (each other), like oxen, 219They fought. 220The threshold they demolished; 221The wall they impaired. 222Gish and Enkidu 223Seized (each other). 224Like oxen they fought. 225The threshold they demolished; 226The wall they impaired. 227Gish bent 228His foot to the ground,8 229His wrath was appeased, 230His breast was quieted. 231When his breast was quieted, 232Enkidu to him 233Spoke, to Gish: 234“As a unique one, thy mother 235bore thee. 236The wild cow of the stall,9 237Ninsun, 238Has exalted thy head above men. 239Kingship over men 240Enlil has decreed for thee. 241Second tablet, 242enlarged beyond [the original(?)]. 243240 lines. [69] 1 I.e., paid homage to the meteor. 2 I.e., the heroes of Erech raised me to my feet, or perhaps in the sense of “supported me.” 3 I.e., Enkidu. 4 I.e., “thy way of life.” 5 I.e., the man. 6 I.e., an idiomatic phrase meaning “for all times.” 7 I.e., Enkidu became like Gish, godlike. Cf. col. 2, 11. 8 He was thrown and therefore vanquished. 9 Epithet given to Ninsun. See the commentary to the line. Commentary on the Pennsylvania Tablet. Line 1. The verb tibû with pašâru expresses the aim of Gish to secure an interpretation for his dream. This disposes of Langdon’s note 1 on page 211 of his edition, in which he also erroneously speaks of our text as “late.” Pašâru is not a variant of zakâru. Both verbs occur just as here in the Assyrian version I, 5, 25. Line 3. ina šât mušitia, “in this my night,” i.e., in the course of this night of mine. A curious way of putting it, but the expression occurs also in the Assyrian version, e.g., I, 5, 26 (parallel passage to ours) and II, 4a, 14. In the Yale tablet we find, similarly, mu-ši-it-ka (l. 262), “thy night,” i.e., “at night to thee.” Line 5. Before Langdon put down the strange statement of Gish “wandering about in the midst of omens” (misreading id-da-tim for it-lu-tim), he might have asked himself the question, what it could possibly mean. How can one walk among omens? Line 6. ka-ka-bu šá-ma-i must be taken as a compound term for “starry heaven.” The parallel passage in the Assyrian version (Tablet I, 5, 27) has the ideograph for star, with the plural sign as a variant. Literally, therefore, “The starry heaven (or “the stars in heaven”) was there,” etc. Langdon’s note 2 on page 211 rests on an erroneous reading. Line 7. kiṣru šá Anim, “mass of Anu,” appears to be the designation of a meteor, which might well be described as a “mass” coming from Anu, i.e., from the god of heaven who becomes the personification of the heavens in general. In the Assyrian version (I, 5, 28) we have kima ki-iṣ-rù, i.e., “something like a mass of heaven.” Note also I, 3, 16, where in a description of Gilgamesh, his strength is said to be “strong like a mass (i.e., a meteor) of heaven.” Line 9. For nuššašu ûl iltê we have a parallel in the Hebrew phrase נלְַפָסֵתִי נשַׂפָס (Isaiah 1, 14). Line 10. Uruk mâtum, as the designation for the district of Erech, occurs in the Assyrian version, e.g., I, 5, 31, and IV, 2, 38; also to be supplied, I, 6, 23. For paḫir the parallel in the Assyrian version has iz-za-az (I, 5, 31), but VI, 197, we find paḫ-ru and paḫ-ra. Line 17. mi-in-di does not mean “truly” as Langdon translates, but “some one.” It occurs also in the Assyrian version X, 1, 13, mi-in-di-e ma-an-nu-ṵ, “this is some one who,” etc. [70] Line 18. Cf. Assyrian version I, 5, 3, and IV, 4, 7, ina ṣiri âlid—both passages referring to Enkidu. Line 21. Cf. Assyrian version II, 3b, 38, with malkê, “kings,” as a synonym of itlutum. Line 23. ta-tar-ra-as-sú from tarâṣu, “direct,” “guide,” etc. Line 24. I take uš-ti-nim-ma as III, 2, from išênu (יָשֵׁן), the verb underlying šittu, “sleep,” and šuttu, “dream.” Line 26. Cf. Assyrian version I, 6, 21—a complete parallel. Line 28. Uruk ri-bi-tim, the standing phrase in both tablets of the old Babylonian version, for which in the Assyrian version we have Uruk su-pu-ri. The former term suggests the “broad space” outside of the city or the “common” in a village community, while supûri, “enclosed,” would refer to the city within the walls. Dr. W. F. Albright (in a private communication) suggests “Erech of the plazas” as a suitable translation for Uruk ribîtim. A third term, Uruk mâtum (see above, note to line 10), though designating rather the district of which Erech was the capital, appears to be used as a synonym to Uruk ribîtim, as may be concluded from the phrase i-na ri-bi-tum ma-ti (l. 214 of the Pennsylvania tablet), which clearly means the “plaza” of the city. One naturally thinks of רְחֹבֹת עִיר in Genesis 10, 11—the equivalent of Babylonian ri-bi-tu âli—which can hardly be the name of a city. It appears to be a gloss, as is הִיַפָס הָעִיּר הַגְּדֹלָה at the end of v. 12. The latter gloss is misplaced, since it clearly describes “Nineveh,” mentioned in v. 11. Inasmuch as רְחֹבֹת עִיר immediately follows the mention of Nineveh, it seems simplest to take the phrase as designating the “outside” or “suburbs” of the city, a complete parallel, therefore, to ri-bi-tu mâti in our text. Nineveh, together with the “suburbs,” forms the “great city.” Uruk ribîtim is, therefore, a designation for “greater Erech,” proper to a capital city, which by its gradual growth would take in more than its original confines. “Erech of the plazas” must have come to be used as a honorific designation of this important center as early as 2000 B. C., whereas later, perhaps because of its decline, the epithet no longer seemed appropriate and was replaced by the more modest designation of “walled Erech,” with an allusion to the tradition which ascribed the building of the wall of the city to Gilgamesh. At all [71]events, all three expressions, “Erech of the plazas,” “Erech walled” and “Erech land,” are to be regarded as synonymous. The position once held by Erech follows also from its ideographic designation (Brünnow No. 4796) by the sign “house” with a “gunufied” extension, which conveys the idea of Unu = šubtu, or “dwelling” par excellence. The pronunciation Unug or Unuk (see the gloss u-nu-uk, VR 23, 8a), composed of unu, “dwelling,” and ki, “place,” is hardly to be regarded as older than Uruk, which is to be resolved into uru, “city,” and ki, “place,” but rather as a play upon the name, both Unu + ki and Uru + ki conveying the same idea of the city or the dwelling place par excellence. As the seat of the second oldest dynasty according to Babylonian traditions (see Poebel’s list in Historical and Grammatical Texts No. 2), Erech no doubt was regarded as having been at one time “the city,” i.e., the capital of the entire Euphrates Valley. Line 31. A difficult line for which Langdon proposes the translation: “Another axe seemed his visage”!!—which may be picturesque, but hardly a description befitting a hero. How can a man’s face seem to be an axe? Langdon attaches šá-ni in the sense of “second” to the preceding word “axe,” whereas šanî bunušu, “change of his countenance” or “his countenance being changed,” is to be taken as a phrase to convey the idea of “being disturbed,” “displeased” or “angry.” The phrase is of the same kind as the well-known šunnu ṭêmu, “changing of reason,” to denote “insanity.” See the passages in Muss-Arnolt, Assyrian Dictionary, pp. 355 and 1068. In Hebrew, too, we have the same two phrases, e.g., וַיְשַׁנֹּו ַפָסֶת־טַעְמֹו (I Sam. 21, 14 = Ps. 34, 1), “and he changed his reason,” i.e., feigned insanity and מְשַׁנֶּה פָּנָיו (Job 14, 20), “changing his face,” to indicate a radical alteration in the frame of mind. There is a still closer parallel in Biblical Aramaic: Dan. 3, 19, “The form of his visage was changed,” meaning “he was enraged.” Fortunately, the same phrase occurs also in the Yale tablet (l. 192), šá-nu-ú bu-nu-šú, in a connection which leaves no doubt that the aroused fury of the tyrant Ḫuwawa is described by it: ”Ḫuwawa heard and his face was changed” precisely, therefore, as we should say—following Biblical usage—“his countenance fell.” Cf. also the phrase pânušu arpu, “his countenance [72]was darkened” (Assyrian version I, 2, 48), to express “anger.” The line, therefore, in the Pennsylvania tablet must describe Enkidu’s anger. With the brandishing of the axe the hero’s anger was also stirred up. The touch was added to prepare us for the continuation in which Gish describes how, despite this (or perhaps just because of it), Enkidu seemed so attractive that Gish instantly fell in love with him. May perhaps the emphatic form ḫaṣinumma (line 31) against ḫaṣinu (line 29) have been used to indicate “The axe it was,” or “because of the axe?” It would be worth while to examine other texts of the Hammurabi period with a view of determining the scope in the use and meaning of the emphatic ma when added to a substantive. Line 32. The combination amur ù aḫtadu occurs also in the El-Amarna Letters, No. 18, 12. Line 34. In view of the common Hebrew, Syriac and Arabic חָבַב “to love,” it seems preferable to read here, as in the other passages in the Assyrian versions (I, 4, 15; 4, 35; 6, 27, etc.), a-ḫa-ab-bu-ub, aḫ-bu-ub, iḫ-bu-bu, etc. (instead of with p), and to render “embrace.” Lines 38–40, completing the column, may be supplied from the Assyrian version I, 6, 30–32, in conjunction with lines 33–34 of our text. The beginning of line 32 in Jensen’s version is therefore to be filled out [ta-ra-am-šú ki]-i. Line 43. The restoration at the beginning of this line En-ki-[dũ wa]-ši-ib ma-ḫar ḫa-ri-im-tim enables us to restore also the beginning of the second tablet of the Assyrian version (cf. the colophon of the fragment 81, 7–27, 93, in Jeremias, Izdubar-Nimrod, plate IV = Jensen, p. 134), [dEn-ki-dũ wa-ši-ib] ma-ḫar-šá. Line 44. The restoration of this line is largely conjectural, based on the supposition that its contents correspond in a general way to I, 4, 16, of the Assyrian version. The reading di-da is quite certain, as is also ip-ti-[e]; and since both words occur in the line of the Assyrian version in question, it is tempting to supply at the beginning ur-[šá] = “her loins” (cf. Holma, Namen der Körperteile, etc., p. 101), which is likewise found in the same line of the Assyrian version. At all events the line describes the fascination exercised [73]upon Enkidu by the woman’s bodily charms, which make him forget everything else. Lines 46–47 form a parallel to I, 4, 21, of the Assyrian version. The form šamkatu, “courtesan,” is constant in the old Babylonian version (ll. 135 and 172), as against šamḫatu in the Assyrian version (I, 3, 19, 40, 45; 4, 16), which also uses the plural šam-ḫa-a-ti (II, 3b, 40). The interchange between ḫ and k is not without precedent (cf. Meissner, Altbabylonisches Privatrecht, page 107, note 2, and more particularly Chiera, List of Personal Names, page 37). In view of the evidence, set forth in the Introduction, for the assumption that the Enkidu story has been combined with a tale of the evolution of primitive man to civilized life, it is reasonable to suggest that in the original Enkidu story the female companion was called šamkatu, “courtesan,” whereas in the tale of the primitive man, which was transferred to Enkidu, the associate was ḫarimtu, a “woman,” just as in the Genesis tale, the companion of Adam is simply called ishshâ, “woman.” Note that in the Assyrian parallel (Tablet I, 4, 26) we have two readings, ir-ḫi (imperf.) and a variant i-ri-ḫi (present). The former is the better reading, as our tablet shows. Lines 49–59 run parallel to the Assyrian version I, 4, 33–38, with slight variations which have been discussed above, p. 58, and from which we may conclude that the Assyrian version represents an independent redaction. Since in our tablet we have presumably the repetition of what may have been in part at least set forth in the first tablet of the old Babylonian version, we must not press the parallelism with the first tablet of the Assyrian version too far; but it is noticeable nevertheless (1) that our tablet contains lines 57–58 which are not represented in the Assyrian version, and (2) that the second speech of the “woman” beginning, line 62, with al-ka, “come” (just as the first speech, line 54), is likewise not found in the first tablet of the Assyrian version; which on the other hand contains a line (39) not in the Babylonian version, besides the detailed answer of Enkidu (I 4, 42–5, 5). Line 6, which reads “Enkidu and the woman went (il-li-ku) to walled Erech,” is also not found in the second tablet of the old Babylonian version. Line 63. For magrû, “accursed,” see the frequent use in Astrological texts (Jastrow, Religion Babyloniens und Assyriens II, page [74]450, note 2). Langdon, by his strange error in separating ma-a-ag-ri-im into two words ma-a-ak and ri-i-im, with a still stranger rendering: “unto the place yonder of the shepherds!!”, naturally misses the point of this important speech. Line 64 corresponds to I, 4, 40, of the Assyrian version, which has an additional line, leading to the answer of Enkidu. From here on, our tablet furnishes material not represented in the Assyrian version, but which was no doubt included in the second tablet of that version of which we have only a few fragments. Line 70 must be interpreted as indicating that the woman kept one garment for herself. Ittalbaš would accordingly mean, “she kept on.” The female dress appears to have consisted of an upper and a lower garment. Line 72. The restoration “like a god” is favored by line 51, where Enkidu is likened to a god, and is further confirmed by l. 190. Line 73. gupru is identical with gu-up-ri (Thompson, Reports of the Magicians and Astrologers, etc., 223 rev. 2 and 223a rev. 8), and must be correlated to gipâru (Muss-Arnolt, Assyrian Dictionary, p. 229a), “planted field,” “meadow,” and the like. Thompson’s translation “men” (as though a synonym of gabru) is to be corrected accordingly. Line 74. There is nothing missing between a-šar and tar-ba-ṣi-im. Line 75. ri-ia-ú, which Langdon renders “shepherd,” is the equivalent of the Arabic riʿy and Hebrew רְעִי “pasturage,” “fodder.” We have usually the feminine form ri-i-tu (Muss-Arnolt, Assyrian Dictionary, p. 990b). The break at the end of the second column is not serious. Evidently Enkidu, still accustomed to live like an animal, is first led to the sheepfolds, and this suggests a repetition of the description of his former life. Of the four or five lines missing, we may conjecturally restore four, on the basis of the Assyrian version, Tablet I, 4, 2–5, or I, 2, 39–41. This would then join on well to the beginning of column 3. Line 81. Both here and in l. 52 our text has na-ma-áš-te-e, as against nam-maš-ši-i in the Assyrian version, e.g., Tablet I, 2, 41; 4, 5, etc.,—the feminine form, therefore, as against the masculine. Langdon’s note 3 on page 213 is misleading. In astrological texts we also find nam-maš-te; e.g., Thompson, Reports of the Magicians and Astrologers, etc., No. 200, Obv. 2. [75] Line 93. zi-ma-at (for simat) ba-la-ṭi-im is not “conformity of life” as Langdon renders, but that which “belongs to life” like si-mat pag-ri-šá, “belonging to her body,” in the Assyrian version III, 2a, 3 (Jensen, page 146). “Food,” says the woman, “is the staff of life.” Line 94. Langdon’s strange rendering “of the conditions and fate of the land” rests upon an erroneous reading (see the corrections, Appendix I), which is the more inexcusable because in line 97 the same ideogram, Kàš = šikaru, “wine,” occurs, and is correctly rendered by him. Šimti mâti is not the “fate of the land,” but the “fixed custom of the land.” Line 98. aṣ-ṣa-mi-im (plural of aṣṣamu), which Langdon takes as an adverb in the sense of “times,” is a well-known word for a large “goblet,” which occurs in Incantation texts, e.g., CT XVI, 24, obv. 1, 19, mê a-ṣa-am-mi-e šú-puk, “pour out goblets of water.” Line 18 of the passage shoves that aṣammu is a Sumerian loan word. Line 99. it-tap-šar, I, 2, from pašâru, “loosen.” In combination with kabtatum (from kabitatum, yielding two forms: kabtatum, by elision of i, and kabittu, by elision of a), “liver,” pašâru has the force of becoming cheerful. Cf. ka-bit-ta-ki lip-pa-šir (ZA V., p. 67, line 14). Line 100, note the customary combination of “liver” (kabtatum) and “heart” (libbu) for “disposition” and “mind,” just as in the standing phrase in penitential prayers: “May thy liver be appeased, thy heart be quieted.” Line 102. The restoration [lùŠÚ]-I = gallabu “barber” (Delitzsch, Sumer. Glossar, p. 267) was suggested to me by Dr. H. F. Lutz. The ideographic writing “raising the hand” is interesting as recalling the gesture of shaving or cutting. Cf. a reference to a barber in Lutz, Early Babylonian Letters from Larsa, No. 109, 6. Line 103. Langdon has correctly rendered šuḫuru as “hair,” and has seen that we have here a loan-word from the Sumerian Suḫur = kimmatu, “hair,” according to the Syllabary Sb 357 (cf. Delitzsch, Sumer. Glossar., p. 253). For kimmatu, “hair,” more specifically hair of the head and face, see Holma, Namen der Körperteile, page 3. The same sign Suḫur or Suḫ (Brünnow No. 8615), with Lal, i.e., “hanging hair,” designates the “beard” (ziḳnu, cf. Brünnow, No. 8620, and Holma, l. c., p. 36), and it is interesting to [76]note that we have šuḫuru (introduced as a loan-word) for the barbershop, according to II R, 21, 27c (= CT XII, 41). Ê suḫur(ra) (i.e., house of the hair) = šú-ḫu-ru. In view of all this, we may regard as assured Holma’s conjecture to read šú-[ḫur-ma-šú] in the list 93074 obv. (MVAG 1904, p. 203; and Holma, Beiträge z. Assyr. Lexikon, p. 36), as the Akkadian equivalent to Suḫur-Maš-Ḫa and the name of a fish, so called because it appeared to have a double “beard” (cf. Holma, Namen der Körperteile). One is tempted, furthermore, to see in the difficult word שכירה (Isaiah 7, 20) a loan-word from our šuḫuru, and to take the words ַפָסֶת־הָרַֹפָסשׁ וְשַׂעַר הָרַגְלַיִם “the head and hair of the feet” (euphemistic for the hair around the privates), as an explanatory gloss to the rare word שכירה for “hair” of the body in general—just as in the passage in the Pennsylvania tablet. The verse in Isaiah would then read, “The Lord on that day will shave with the razor the hair (השכירה), and even the beard will be removed.” The rest of the verse would represent a series of explanatory glosses: (a) “Beyond the river” (i.e., Assyria), a gloss to יְגַלַּח (b) “with the king of Assyria,” a gloss to בְּתַעַר “with a razor;” and (c) “the hair of the head and hair of the feet,” a gloss to השכירה. For “hair of the feet” we have an interesting equivalent in Babylonian šu-ḫur (and šú-ḫu-ur) šêpi (CT XII, 41, 23–24 c-d). Cf. also Boissier, Documents Assyriens relatifs aux Présages, p. 258, 4–5. The Babylonian phrase is like the Hebrew one to be interpreted as a euphemism for the hair around the male or female organ. To be sure, the change from ה to כ in השכירה constitutes an objection, but not a serious one in the case of a loan-word, which would aim to give the pronunciation of the original word, rather than the correct etymological equivalent. The writing with aspirated כ fulfills this condition. (Cf. šamkatum and šamḫatum, above p. 73). The passage in Isaiah being a reference to Assyria, the prophet might be tempted to use a foreign word to make his point more emphatic. To take השכירה as “hired,” as has hitherto been done, and to translate “with a hired razor,” is not only to suppose a very wooden metaphor, but is grammatically difficult, since השכירח would be a feminine adjective attached to a masculine substantive. Coming back to our passage in the Pennsylvania tablet, it is to [77]be noted that Enkidu is described as covered “all over his body with hair” (Assyrian version, Tablet I, 2, 36) like an animal. To convert him into a civilized man, the hair is removed. Line 107. mutu does not mean “husband” here, as Langdon supposes, but must be taken as in l. 238 in the more general sense of “man,” for which there is good evidence. Line 109. la-bi (plural form) are “lions”—not “panthers” as Langdon has it. The verb ú-gi-ir-ri is from gâru, “to attack.” Langdon by separating ú from gi-ir-ri gets a totally wrong and indeed absurd meaning. See the corrections in the Appendix. He takes the sign ú for the copula (!!) which of course is impossible. Line 110. Read uš-sa-ak-pu, III, 1, of sakâpu, which is frequently used for “lying down” and is in fact a synonym of ṣalâlu. See Muss-Arnolt, Assyrian Dictionary, page 758a. The original has very clearly Síb (= rê’u, “shepherd”) with the plural sign. The “shepherds of the night,” who could now rest since Enkidu had killed the lions, are of course the shepherds who were accustomed to watch the flocks during the night. Line 111. ut-tap-pi-iš is II, 2, napâšu, “to make a hole,” hence “to plunge” in connection with a weapon. Šib-ba-ri is, of course, not “mountain goats,” as Langdon renders, but a by-form to šibbiru, “stick,” and designates some special weapon. Since on seal cylinders depicting Enkidu killing lions and other animals the hero is armed with a dagger, this is presumably the weapon šibbaru. Line 113. Langdon’s translation is again out of the question and purely fanciful. The traces favor the restoration na-ki-[di-e], “shepherds,” and since the line appears to be a parallel to line 110, I venture to suggest at the beginning [it-ti]-lu from na’âlu, “lie down”—a synonym, therefore, to sakâpu in line 110. The shepherds can sleep quietly after Enkidu has become the “guardian” of the flocks. In the Assyrian version (tablet II, 3a, 4) Enkidu is called a na-kid, “shepherd,” and in the preceding line we likewise have lùNa-Kid with the plural sign, i.e., “shepherds.” This would point to nakidu being a Sumerian loan-word, unless it is vice versa, a word that has gone over into the Sumerian from Akkadian. Is perhaps the fragment in question (K 8574) in the Assyrian version (Haupt’s ed. No. 25) the parallel to our passage? If in line 4 of this fragment we could read šú for sa, i.e., na-kid-šú-nu, “their shepherd, we would have a [78]parallel to line 114 of the Pennsylvania tablet, with na-kid as a synonym to maṣṣaru, “protector.” The preceding line would then be completed as follows: [it-ti-lu]-nim-ma na-kidmeš [ra-bu-tum] (or perhaps only it-ti-lu-ma, since the nim is not certain) and would correspond to line 113 of the Pennsylvania tablet. Inasmuch as the writing on the tiny fragment is very much blurred, it is quite possible that in line 2 we must read šib-ba-ri (instead of bar-ba-ri), which would furnish a parallel to line 111 of the Pennsylvania tablet. The difference between Bar and Šib is slight, and the one sign might easily be mistaken for the other in the case of close writing. The continuation of line 2 of the fragment would then correspond to line 112 of the Pennsylvania tablet, while line 1 of the fragment might be completed [re-e]-u-ti(?) šá [mu-ši-a-tim], though this is by no means certain. The break at the close of column 3 (about 5 lines) and the top of column 4 (about 8 lines) is a most serious interruption in the narrative, and makes it difficult to pick up the thread where the tablet again becomes readable. We cannot be certain whether the “strong man, the unique hero” who addresses some one (lines 115–117) is Enkidu or Gish or some other personage, but presumably Gish is meant. In the Assyrian version, Tablet I, 3, 2 and 29, we find Gilgamesh described as the “unique hero” and in l. 234 of the Pennsylvania tablet Gish is called “unique,” while again, in the Assyrian version, Tablet I, 2, 15 and 26, he is designated as gašru as in our text. Assuming this, whom does he address? Perhaps the shepherds? In either case he receives an answer that rejoices him. If the fragment of the Assyrian version (K 8574) above discussed is the equivalent to the close of column 3 of the Pennsylvania tablet, we may go one step further, and with some measure of assurance assume that Gish is told of Enkidu’s exploits and that the latter is approaching Erech. This pleases Gish, but Enkidu when he sees Gish(?) is stirred to anger and wants to annihilate him. At this point, the “man” (who is probably Gish, though the possibility of a third personage must be admitted) intervenes and in a long speech sets forth the destiny and higher aims of mankind. The contrast between Enkidu and Gish (or the third party) is that between the primitive [79]savage and the civilized being. The contrast is put in the form of an opposition between the two. The primitive man is the stronger and wishes to destroy the one whom he regards as a natural foe and rival. On the other hand, the one who stands on a higher plane wants to lift his fellow up. The whole of column 4, therefore, forms part of the lesson attached to the story of Enkidu, who, identified with man in a primitive stage, is made the medium of illustrating how the higher plane is reached through the guiding influences of the woman’s hold on man, an influence exercised, to be sure, with the help of her bodily charms. Line 135. uk-ki-ši (imperative form) does not mean “take away,” as Langdon (who entirely misses the point of the whole passage) renders, but on the contrary, “lure him on,” “entrap him,” and the like. The verb occurs also in the Yale tablet, ll. 183 and 186. Line 137. Langdon’s note to lu-uš-šú had better be passed over in silence. The form is II. 1, from ešû, “destroy.” Line 139. Since the man whom the woman calls approaches Enkidu, the subject of both verbs is the man, and the object is Enkidu; i.e., therefore, “The man approaches Enkidu and beholds him.” Line 140. Langdon’s interpretation of this line again is purely fanciful. E-di-il cannot, of course, be a “phonetic variant” of edir; and certainly the line does not describe the state of mind of the woman. Lines 140–141 are to be taken as an expression of amazement at Enkidu’s appearance. The first word appears to be an imperative in the sense of “Be off,” “Away,” from dâlu, “move, roam.” The second word e-eš, “why,” occurs with the same verb dâlu in the Meissner fragment: e-eš ta-da-al (column 3, 1), “why dost thou roam about?” The verb at the end of the line may perhaps be completed to ta-ḫi-il-la-am. The last sign appears to be am, but may be ma, in which case we should have to complete simply ta-ḫi-il-ma. Taḫîl would be the second person present of ḫîlu. Cf. i-ḫi-il, frequently in astrological texts, e.g., Virolleaud, Adad No. 3, lines 21 and 33. Line 141. The reading lim-nu at the beginning, instead of Langdon’s mi-nu, is quite certain, as is also ma-na-aḫ-ti-ka instead of what Langdon proposes, which gives no sense whatever. Manaḫtu in the sense of the “toil” and “activity of life” (like עָמָל throughout the Book of Ecclesiastes) occurs in the introductory lines to [80]the Assyrian version of the Epic I, 1, 8, ka-lu ma-na-aḫ-ti-[šu], “all of his toil,” i.e., all of his career. Line 142. The subject of the verb cannot be the woman, as Langdon supposes, for the text in that case, e.g., line 49, would have said pi-šá (“her mouth”) not pi-šú (“his mouth”). The long speech, detailing the function and destiny of civilized man, is placed in the mouth of the man who meets Enkidu. In the Introduction it has been pointed out that lines 149 and 151 of the speech appear to be due to later modifications of the speech designed to connect the episode with Gish. Assuming this to be the case, the speech sets forth the following five distinct aims of human life: (1) establishing a home (line 144), (2) work (line 147), (3) storing up resources (line 148), (4) marriage (line 150), (5) monogamy (line 154); all of which is put down as established for all time by divine decree (lines 155–157), and as man’s fate from his birth (lines 158–159). Line 144. bi-ti-iš e-mu-ti is for bîti šá e-mu-ti, just as ḳab-lu-uš Ti-a-ma-ti (Assyrian Creation Myth, IV, 65) stands for ḳablu šá Tiamti. Cf. bît e-mu-ti (Assyrian version, IV, 2, 46 and 48). The end of the line is lost beyond recovery, but the general sense is clear. Line 146. tu-a-ar is a possible reading. It may be the construct of tu-a-ru, of frequent occurrence in legal texts and having some such meaning as “right,” “claim” or “prerogative.” See the passages given by Muss-Arnolt, Assyrian Dictionary, p. 1139b. Line 148. The reading uk-la-at, “food,” and then in the wider sense “food supply,” “provisions,” is quite certain. The fourth sign looks like the one for “city.” E-mi-sa may stand for e-mid-sa, “place it.” The general sense of the line, at all events, is clear, as giving the advice to gather resources. It fits in with the Babylonian outlook on life to regard work and wealth as the fruits of work and as a proper purpose in life. Line 150 (repeated lines 152–153) is a puzzling line. To render piti pûk epši (or epiši), as Langdon proposes, “open, addressing thy speech,” is philologically and in every other respect inadmissible. The word pu-uk (which Langdon takes for “thy mouth”!!) can, of course, be nothing but the construct form of pukku, which occurs in the Assyrian version in the sense of “net” (pu-uk-ku I, 2, 9 and 21, and also in the colophon to the eleventh tablet furnishing the [81]beginning of the twelfth tablet (Haupt’s edition No. 56), as well as in column 2, 29, and column 3, 6, of this twelfth tablet). In the two last named passages pukku is a synonym of mekû, which from the general meaning of “enclosure” comes to be a euphemistic expression for the female organ. So, for example, in the Assyrian Creation Myth, Tablet IV, 66 (synonym of ḳablu, “waist,” etc.). See Holma, Namen der Körperteile, page 158. Our word pukku must be taken in this same sense as a designation of the female organ—perhaps more specifically the “hymen” as the “net,” though the womb in general might also be designated as a “net” or “enclosure.” Kak-(ši) is no doubt to be read epši, as Langdon correctly saw; or perhaps better, epiši. An expression like ip-ši-šú lul-la-a (Assyrian version, I, 4, 13; also line 19, i-pu-us-su-ma lul-la-a), with the explanation šipir zinništi, “the work of woman” (i.e., after the fashion of woman), shows that epêšu is used in connection with the sexual act. The phrase pitî pûk epiši a-na ḫa-a-a-ri, literally “open the net, perform the act for marriage,” therefore designates the fulfillment of the marriage act, and the line is intended to point to marriage with the accompanying sexual intercourse as one of the duties of man. While the general meaning is thus clear, the introduction of Gish is puzzling, except on the supposition that lines 149 and 151 represent later additions to connect the speech, detailing the advance to civilized life, with the hero. See above, p. 45 seq. Line 154. aššat šimâtim is the “legitimate wife,” and the line inculcates monogamy as against promiscuous sexual intercourse. We know that monogamy was the rule in Babylonia, though a man could in addition to the wife recognized as the legalized spouse take a concubine, or his wife could give her husband a slave as a concubine. Even in that case, according to the Hammurabi Code, §§145–146, the wife retained her status. The Code throughout assumes that a man has only one wife—the aššat šimâtim of our text. The phrase “so” (or “that”) before “as afterwards” is to be taken as an idiomatic expression—“so it was and so it should be for all times”—somewhat like the phrase maḫriam ù arkiam, “for all times,” in legal documents (CT VIII, 38c, 22–23). For the use of mûk see Behrens, Assyrisch-Babylonische Briefe, p. 3. Line 158. i-na bi-ti-iḳ a-bu-un-na-ti-šú. Another puzzling line, for which Langdon proposes “in the work of his presence,” which [82]is as obscure as the original. In a note he says that apunnâti means “nostrils,” which is certainly wrong. There has been considerable discussion about this term (see Holma, Namen der Körperteile, pages 150 and 157), the meaning of which has been advanced by Christian’s discussion in OLZ 1914, p. 397. From this it appears that it must designate a part of the body which could acquire a wider significance so as to be used as a synonym for “totality,” since it appears in a list of equivalent for Dur = nap-ḫa-ru, “totality,” ka-lu-ma, “all,” a-bu-un-na-tum e-ṣi-im-tum, “bony structure,” and kul-la-tum, “totality” (CT XII, 10, 7–10). Christian shows that it may be the “navel,” which could well acquire a wider significance for the body in general; but we may go a step further and specify the “umbilical cord” (tentatively suggested also by Christian) as the primary meaning, then the “navel,” and from this the “body” in general. The structure of the umbilical cord as a series of strands would account for designating it by a plural form abunnâti, as also for the fact that one could speak of a right and left side of the appunnâti. To distinguish between the “umbilical cord” and the “navel,” the ideograph Dur (the common meaning of which is riksu, “bond” [Delitzsch, Sumer. Glossar., p. 150]), was used for the former, while for the latter Li Dur was employed, though the reading in Akkadian in both cases was the same. The expression “with (or at) the cutting of his umbilical cord” would mean, therefore, “from his birth”—since the cutting of the cord which united the child with the mother marks the beginning of the separate life. Lines 158–159, therefore, in concluding the address to Enkidu, emphasize in a picturesque way that what has been set forth is man’s fate for which he has been destined from birth. [See now Albright’s remarks on abunnatu in the Revue d’Assyriologie 16, pp. 173–175, with whose conclusion, however, that it means primarily “backbone” and then “stature,” I cannot agree.] In the break of about three lines at the bottom of column 4, and of about six at the beginning of column 5, there must have been set forth the effect of the address on Enkidu and the indication of his readiness to accept the advice; as in a former passage (line 64), Enkidu showed himself willing to follow the woman. At all events the two now proceed to the heart of the city. Enkidu is in front [83]and the woman behind him. The scene up to this point must have taken place outside of Erech—in the suburbs or approaches to the city, where the meadows and the sheepfolds were situated. Line 174. um-ma-nu-um are not the “artisans,” as Langdon supposes, but the “people” of Erech, just as in the Assyrian version, Tablet IV, 1, 40, where the word occurs in connection with i-dip-pi-ir, which is perhaps to be taken as a synonym of paḫâru, “gather;” so also i-dip-pir (Tablet I, 2, 40) “gathers with the flock.” Lines 180–182 must have contained the description of Enkidu’s resemblance to Gish, but the lines are too mutilated to permit of any certain restoration. See the corrections (Appendix) for a suggested reading for the end of line 181. Line 183 can be restored with considerable probability on the basis of the Assyrian version, Tablet I, 3, 3 and 30, where Enkidu is described as one “whose power is strong in the land.” Lines 186–187. The puzzling word, to be read apparently kak-ki-a-tum, can hardly mean “weapons,” as Langdon proposes. In that case we should expect kakkê; and, moreover, to so render gives no sense, especially since the verb ú-te-el-li-lu is without much question to be rendered “rejoiced,” and not “purified.” Kakkiatum—if this be the correct reading—may be a designation of Erech like ribîtim. Lines 188–189 are again entirely misunderstood by Langdon, owing to erroneous readings. See the corrections in the Appendix. Line 190. i-li-im in this line is used like Hebrew Elohîm, “God.” Line 191. šakiššum = šakin-šum, as correctly explained by Langdon. Line 192. With this line a new episode begins which, owing to the gap at the beginning of column 6, is somewhat obscure. The episode leads to the hostile encounter between Gish and Enkidu. It is referred to in column 2 of the fourth tablet of the Assyrian version. Lines 35–50—all that is preserved of this column—form in part a parallel to columns 5–6 of the Pennsylvania tablet, but in much briefer form, since what on the Pennsylvania tablet is the incident itself is on the fourth tablet of the Assyrian version merely a repeated summary of the relationship between the two heroes, leading up to the expedition against Ḫu(m)baba. Lines 38–40 of [84]column 2 of the Assyrian version correspond to lines 174–177 of the Pennsylvania tablet, and lines 44–50 to lines 192–221. It would seem that Gish proceeds stealthily at night to go to the goddess Ishḫara, who lies on a couch in the bît êmuti , the “family house” Assyrian version, Tablet IV, 2. 46–48). He encounters Enkidu in the street, and the latter blocks Gish’s path, puts his foot in the gate leading to the house where the goddess is, and thus prevents Gish from entering. Thereupon the two have a fierce encounter in which Gish is worsted. The meaning of the episode itself is not clear. Does Enkidu propose to deprive Gish, here viewed as a god (cf. line 190 of the Pennsylvania tablet = Assyrian version, Tablet I, 4, 45, “like a god”), of his spouse, the goddess Ishḫara—another form of Ishtar? Or are the two heroes, the one a counterpart of the other, contesting for the possession of a goddess? Is it in this scene that Enkidu becomes the “rival” (me-iḫ-rù, line 191 of the Pennsylvania tablet) of the divine Gish? We must content ourself with having obtained through the Pennsylvania tablet a clearer indication of the occasion of the fight between the two heroes, and leave the further explanation of the episode till a fortunate chance may throw additional light upon it. There is perhaps a reference to the episode in the Assyrian version, Tablet II, 3b, 35–36. Line 196. For i-na-ag-šá-am (from nagâšu), Langdon proposes the purely fanciful “embracing her in sleep,” whereas it clearly means “he approaches.” Cf. Muss-Arnolt, Assyrian Dictionary, page 645a. Lines 197–200 appear to correspond to Tablet IV, 2, 35–37, of the Assyrian version, though not forming a complete parallel. We may therefore supply at the beginning of line 35 of the Assyrian version [ittaziz] Enkidu, corresponding to line 197 of the Pennsylvania tablet. Line 36 of IV, 2, certainly appears to correspond to line 200 (dan-nu-ti = da-na-ni-iš-šú). Line 208. The first sign looks more like šar, though ur is possible. Line 211 is clearly a description of Enkidu, as is shown by a comparison with the Assyrian version I, 2, 37: [pi]-ti-ik pi-ir-ti-šú uḫ-tan-na-ba kima dNidaba, “The form of his hair sprouted like wheat.” We must therefore supply Enkidu in the preceding line. Tablet IV, 4, 6, of the Assyrian version also contains a reference to the flowing hair of Enkidu. [85] Line 212. For the completion of the line cf. Harper, Assyrian and Babylonian Letters, No. 214. Line 214. For ribîtu mâti see the note above to line 28 of column 1. Lines 215–217 correspond almost entirely to the Assyrian version IV, 2, 46–48. The variations ki-ib-su in place of šêpu, and kima lîm, “like oxen,” instead of ina bâb êmuti (repeated from line 46), ana šurûbi for êribam, are slight though interesting. The Assyrian version shows that the “gate” in line 215 is “the gate of the family house” in which the goddess Ishḫara lies. Lines 218–228. The detailed description of the fight between the two heroes is only partially preserved in the Assyrian version. Line 218. li-i-im is evidently to be taken as plural here as in line 224, just as su-ḳi-im (lines 27 and 175), ri-bi-tim (lines 4, 28, etc.), tarbaṣim (line 74), aṣṣamim (line 98) are plural forms. Our text furnishes, as does also the Yale tablet, an interesting illustration of the vacillation in the Hammurabi period in the twofold use of im: (a) as an indication of the plural (as in Hebrew), and (b) as a mere emphatic ending (lines 63, 73, and 232), which becomes predominant in the post-Hammurabi age. Line 227. Gilgamesh is often represented on seal cylinders as kneeling, e.g., Ward Seal Cylinders Nos. 159, 160, 165. Cf. also Assyrian version V, 3, 6, where Gilgamesh is described as kneeling, though here in prayer. See further the commentary to the Yale tablet, line 215. Line 229. We must of course read uz-za-šú, “his anger,” and not uṣ-ṣa-šú, “his javelin,” as Langdon does, which gives no sense. Line 231. Langdon’s note is erroneous. He again misses the point. The stem of the verb here as in line 230 (i-ni-iḫ) is the common nâḫu, used so constantly in connection with pašâḫu, to designate the cessation of anger. Line 234. ištên applied to Gish designates him of course as “unique,” not as “an ordinary man,” as Langdon supposes. Line 236. On this title “wild cow of the stall” for Ninsun, see Poebel in OLZ 1914, page 6, to whom we owe the correct view regarding the name of Gilgamesh’s mother. Line 238. mu-ti here cannot mean “husband,” but “man” in [86]general. See above note to line 107. Langdon’s strange misreading ri-eš-su for ri-eš-ka (“thy head”) leads him again to miss the point, namely that Enkidu comforts his rival by telling him that he is destined for a career above that of the ordinary man. He is to be more than a mere prize fighter; he is to be a king, and no doubt in the ancient sense, as the representative of the deity. This is indicated by the statement that the kingship is decreed for him by Enlil. Similarly, Ḫu(m)baba or Ḫuwawa is designated by Enlil to inspire terror among men (Assyrian version, Tablet IV, 5, 2 and 5), i-šim-šú dEnlil = Yale tablet, l. 137, where this is to be supplied. This position accorded to Enlil is an important index for the origin of the Epic, which is thus shown to date from a period when the patron deity of Nippur was acknowledged as the general head of the pantheon. This justifies us in going back several centuries at least before Hammurabi for the beginning of the Gilgamesh story. If it had originated in the Hammurabi period, we should have had Marduk introduced instead of Enlil. Line 242. As has been pointed out in the corrections to the text (Appendix), šú-tu-ur can only be III, 1, from atâru, “to be in excess of.” It is a pity that the balance of the line is broken off, since this is the first instance of a colophon beginning with the term in question. In some way šutûr must indicate that the copy of the text has been “enlarged.” It is tempting to fill out the line šú-tu-ur e-li [duppi labiri], and to render “enlarged from an original,” as an indication of an independent recension of the Epic in the Hammurabi period. All this, however, is purely conjectural, and we must patiently hope for more tablets of the Old Babylonian version to turn up. The chances are that some portions of the same edition as the Yale and Pennsylvania tablets are in the hands of dealers at present or have been sold to European museums. The war has seriously interfered with the possibility of tracing the whereabouts of groups of tablets that ought never to have been separated. [87] Yale Tablet. Transliteration. (About ten lines missing.) Col. I. 11.................. [ib]-ri(?) 12[mi-im-ma(?) šá(?)]-kú-tu wa(?)-ak-rum 13[am-mi-nim] ta-aḫ-ši-iḫ 14[an-ni]-a-am [e-pi]-šá-am 15...... mi-im[-ma šá-kú-tu(?)]ma- 16di-iš 17[am-mi]-nim [taḫ]-ši-iḫ 18[ur(?)]-ta-du-ú [a-na ki-i]š-tim 19ši-ip-ra-am it-[ta-šú]-ú i-na [nišê] 20it-ta-áš-šú-ú-ma 21i-pu-šú ru-ḫu-tam 22.................. uš-ta-di-nu 23............................. bu 24............................... (About 17 lines missing.) 40.............. nam-........ 41.................... u ib-[ri] ..... 42.............. ú-na-i-du ...... 43[zi-ik]-ra-am ú-[tí-ir]-ru 44[a-na] ḫa-ri-[im]-tim 45[i]-pu(?)-šú a-na sa-[ka]-pu-ti Col. II. (About eleven lines missing.) 57... šú(?)-mu(?) ............... 58ma-ḫi-ra-am [šá i-ši-šú] 59šú-uk-ni-šum-[ma] ............... 60la-al-la-ru-[tu] .................. 61um-mi d-[Giš mu-di-a-at ka-la-ma] 62i-na ma-[ḫar dŠamaš i-di-šá iš-ši][88] 63šá ú 64i-na- an(?)-[na am-mi-nim] 65ta-[aš-kun(?) a-na ma-ri-ia li-ib-bi la] 66ṣa-[li-la te-mid-su] 67............................. (About four lines missing.) 72i-na [šá dEn-ki-dũ im-la-a] di-[im-tam] 73il-[pu-ut li]-ib-ba-šú-[ma] 74[zar-biš(?)] uš-ta-ni-[iḫ] 75[i-na šá dEn]-ki-dũ im-la-a di-im-tam 76[il-pu-ut] li-ib-ba-šú-ma 77[zar-biš(?)] uš-ta-ni-[iḫ] 78[dGiš ú-ta]-ab-bil pa-ni-šú 79[iz-za-kar-am] a-na dEn-ki-dũ 80[ib-ri am-mi-nim] i-na-ka 81[im-la-a di-im]-tam 82[il-pu-ut li-ib-bi]-ka 83[zar-biš tu-uš-ta]-ni-iḫ 84[dEn-ki-dũ pi-šú i-pu-šá]-am-ma 85iz-za-[kàr-am] a-na dGiš 86ta-ab-bi-a-tum ib-ri 87uš-ta-li-pa da-1da-ni-ia 88a-ḫa-a-a ir-ma-a-ma 89e-mu-ki i-ni-iš 90dGiš pi-šú i-pu-šá-am-ma 91iz-za-kàr-am a-na dEn-ki-dũ (About four lines missing.) Col. III. 96..... [a-di dḪu]-wa-wa da-pi-nu 97.................. ra-[am(?)-ma] 98................ [ú-ḫal]- li-ik 99[lu-ur-ra-du a-na ki-iš-ti šá] iserini[89] 100............ lam(?) ḫal-bu 101............ [li]-li-is-su 102.............. lu(?)-up-ti-šú 103dEn-ki-dũ pi-šú i-pu-šá-am-ma 104iz-za-kàr-am a-na dGiš 105i-di-ma ib-ri i-na šadî(-i) 106i-nu-ma at-ta-la-ku it-ti bu-lim 107a-na ištên(-en) kas-gíd-ta-a-an nu-ma-at ki-iš-tum 108[e-di-iš(?)] ur-ra-du a-na libbi-šá 109d[Ḫu-wa]-wa ri-ig-ma-šú a-bu-bu 110pi-[šú] dBil-gi-ma 111na-pi-iš-šú mu-tum 112am-mi-nim ta-aḫ-ši-iḫ 113an-ni-a-am e-pi-šá-am 114ga-[ba]-al-la ma-ḫa-ar 115[šú]-pa-at dḪu-wa-wa 116(d)Giš pi-šú i-pu-šá-am-ma 117[iz-za-k]àr-am a-na dEn-ki-dũ 118....... su(?)-lu-li a-šá-ki2-šá 119............. [i-na ki-iš]-tim 120............................... 121ik(?) ......................... 122a-na .......................... 123mu-šá-ab [dḪu-wa-wa] ....... 124ḫa-aṣ-si-nu ................. 125at-ta lu(?) ................. 126a-na-ku lu-[ur-ra-du a-na ki-iš-tim] 127dEn-ki-dũ pi-šú i-pu-[šá-am-ma] 128iz-za-kàr-am a-na [dGiš] 129ki-i ni[il]-la-ak [iš-te-niš(?)] 130a-na ki-iš-ti [šá iṣerini] 131na-ṣi-ir-šá dGiš muḳ-[tab-lu] 132da-a-an la ṣa[-li-lu(?)] 133dḪu-wa-wa dpi-ir-[ḫu ša (?)][90] 134dAdad iš .......... 135šú-ú .................. Col. IV. 136áš-šúm šú-ul-lu-m[u ki-iš-ti šáiṣerini] 137pu-ul-ḫi-a-tim 7 [šú(?) i-šim-šú dEnlil] 138dGiš pi-šú i-pu [šá-am-ma] 139iz-za-kàr-am a-na [dEn-ki-dũ] 140ma-an-nu ib-ri e-lu-ú šá-[ru-ba(?)] 141i-ṭib-ma it-ti dŠamaš da-ri-iš ú-[me-šú] 142a-we-lu-tum ba-ba-nu ú-tam-mu-šá-[ma] 143mi-im-ma šá i-te-ni-pu-šú šá-ru-ba 144at-ta an-na-nu-um-ma ta-dar mu-tam 145ul iš-šú da-na-nu ḳar-ra-du-ti-ka 146lu-ul-li-ik-ma i-na pa-ni-ka 147pi-ka li-iš-si-a-am ṭi-ḫi-e ta-du-ur 148šum-ma am-ta-ḳu-ut šú-mi lu-uš-zi-iz 149dGiš mi3-it-ti dḪu-wa-wa da-pi-nim 150il(?)-ḳu-ut iš-tu 151i-wa-al-dam-ma tar-bi-a i-na šam-mu(?) Il(?) 152iš-ḫi-it-ka-ma la-bu ka-la-ma ti-di 153it- ku(?) ..... [il(?)]-pu-tu-(?) ma ..... 154.............. ka-ma 155.............. ši pi-ti 156............ ki-ma re’i(?) na-gi-la sa-rak-ti 157.... [ta-šá-s]i-a-am tu-lim-mi-in li-ib-bi 158[ga-ti lu]-uš-ku-un-ma 159[lu-u-ri]-ba-am iṣerini[91] 160[šú-ma sá]-ṭa-ru-ú a-na-ku lu-uš-ta-ak-na 161[pu-tu-ku(?)] ib-ri a-na ki-iš-ka-tim lu-mu-ḫa 162[be-le-e li-iš-]-pu-ku i-na maḫ-ri-ni 163[pu-tu]-ku a-na ki-iš-ka-ti-i i-mu-ḫu 164wa-áš-bu uš-ta-da-nu um-mi-a-nu 165pa-ši iš-pu-ku ra-bu-tim 166ḫa-aṣ-si-ni 3 biltu-ta-a-an iš-tap-ku 167pa-aṭ-ri iš-pu-ku ra-bu-tim 168me-še-li-tum 2 biltu-ta-a-an 169ṣi-ip-ru 30 ma-na-ta-a-an šá a-ḫi-ši-na 170išid(?) pa-aṭ-ri 30 ma-na-ta-a-an ḫuraṣi 171[d]Giš ù [dEn-ki-]dũ 10 biltu-ta-a-an šá-ak-nu] 172.... ul-la . .[Uruk]ki 7 i-di-il-šú 173...... iš-me-ma um-ma-nu ib-bi-ra 174[uš-te-(?)]-mi-a i-na sûḳi šá Urukki ri-bi-tim 175...... [u-še(?)]-ṣa-šú dGis 176[ina sûḳi šá(?) Urukki] ri-bi-tim 177[dEn-ki-dũ(?) ú]-šá-ab i-na maḫ-ri-šú 178..... [ki-a-am(?) i-ga]-ab-bi 179[........ Urukki ri]-bi-tim 180 [ma-ḫa-ar-šú] Col. V. 181dGiš šá i-ga-ab-bu-ú lu-mu-ur 182šá šú-um-šú it-ta-nam-ma-la ma-ta-tum 183lu-uk-šú-su-ma i-na ki-iš-ti iṣerini 184ki-ma da-an-nu pi-ir-ḫu-um šá Urukki[92] 185lu-ši-eš-mi ma-tam 186ga-ti lu-uš-ku-un-ma lu-uk-[šú]4-su-ma iṣerini 187šú-ma šá-ṭa-ru-ú a-na-ku lu-uš-tak-nam 188ši-bu-tum šá Urukki ri-bi-tim 189zi-ik-ra ú-ti-ir-ru a-na dGiš 190ṣi-iḫ-ri-ti-ma dGiš libbi-ka na-ši-ka 191mi-im-ma šá te-te-ni-pu-šú la ti-di 192ni-ši-im-me-ma dḪu-wa-wa šá-nu-ú bu-nu-šú 193ma-an-nu-um [uš-tam]-ḫa-ru ka-ak-ki-šú 194a-na ištên(-en) [kas-gíd-ta-a]-an nu-ma-at kišti 195ma-an-nu šá [ur-ra]-du a-na libbi-šá 196dḪu-wa-wa ri-ig-ma-šú a-bu-bu 197pi-šú dBil-gi-ma na-pi-su mu-tum 198am-mi-nim taḫ-ši-iḫ an-ni-a-am e-pi-šá 199ga-ba-al-la ma-ḫa-ar šú-pa-at dḪu-wa-wa 200iš-me-e-ma dGiš zi-ki-ir ma-li-[ki]-šú 201ip-pa-al-sa-am-ma i-ṣi-iḫ a-na ib-[ri-šú] 202i-na-an-na ib-[ri] ki-a-am [a-ga-ab-bi] 203a-pa-al-aḫ-šú-ma a-[al-la-ak a-na kišti] 204[lu]ul-[lik it-ti-ka a-na ki-iš-ti iṣerini(?)] (About five lines missing.) 210........................ -ma 211li ............... -ka[93] 212ilu-ka li(?) ..............-ka 213ḫarrana li-šá-[tir-ka a-na šú-ul-mi] 214a-na kar šá [Urukki ri-bi-tim] 215ka-mi-is-ma dGiš [ma-ḫa-ar dŠamaš(?)] 216a-wa-at i-ga-ab- [bu-šú-ma] 217a-al-la-ak dŠamaš katâ-[ka a-ṣa-bat] 218ul-la-nu lu-uš-li-ma na-pi-[iš-ti] 219te-ir-ra-an-ni a-na kar i-[na Urukki] 220ṣi-il-[la]m šú-ku-un [a-na ia-a-ši(?)] 221iš-si-ma dGiš ib-[ri.....] 222te-ir-ta-šú .......... 223is(?) .............. 224tam ................ 225........................ 226i-nu(?)-[ma] .................. (About two lines missing.) Col. VI. 229[a-na-ku] dGiš [i-ik]-ka-di ma-tum 230........... ḫarrana šá la al-[kam] ma-ti-ma 231.... a-ka-lu ..... la(?) i-di 232[ul-la-nu] lu-uš-li-[mu] a-na-ku 233[lu-ud-lul]-ka i-na [ḫ]u-ud li-ib-bi 234...... [šú]-ḳu-ut-[ti] la-li-ka 235[lu-še-šib(?)] - ka i-na kussêmeš 236....................... ú-nu-su 237[bêlêmeš(?)ú-ti-ir]-ru ra-bu-tum 238[ka-aš-tum] ù iš-pa-tum 239[i-na] ga-ti iš-ku-nu 240[il-]te-ki pa-ši 241....... -ri iš-pa-as-su[94] 242..... [a-na] ili šá-ni-tam 243[it-ti pa(?)] - tar-[šú] i-na ši-ip-pi-šú 244........ i-ip-pu-šú a-la-kam 245[ša]-niš ú-ga-ra-bu dGiš 246[a-di ma]-ti tu-ut-te-ir a-na libbi Urukki 247[ši-bu]-tum i-ka-ra-bu-šú 248[a-na] ḫarrani i-ma-li-ku dGiš 249[la t]a-at-kal dGiš a-na e-[mu]-ḳi-ka 250[a-]ka-lu šú-wa-ra-ma ú-ṣur ra-ma-an-ka 251[li]-il-lik dEn-ki-dũ i-na pa-ni-ka 252[ur-ḫa]-am a-we-ir a-lik ḫarrana(-na) 253[a-di] šá kišti ni-ri-bi-tim 254[šá(?)] [d]Ḫu-wa-wa ka-li-šú-nu ši-ip-pi-iḫ(?)-šú 255[ša(?)a-lik] maḫ-ra tap-pa-a ú-šá-lim 256[ḫarrana](-na)-šú šú-wa-ra-[ma ú-ṣur ra-ma-na-ka] 257[li-šak-šid]-ka ir-[ni-ta]-ka dŠamaš 258[ta]-ak-bi-a-at pi-ka li-kal-li-ma i-na-ka 259li-ip-ti-ḳu pa-da-nam pi-ḫi-tam 260ḫarrana li-iš-ta-zi-ik a-na ki-ib-si-ka 261šá-di-a li-iš-ta-zi-ik a-na šêpi-ka 262mu-ši-it-ka aw-a-at ta-ḫa-du-ú 263li-ib-la-ma dLugal-ban-da li-iz-zi-iz-ka[95] 264i-na ir-ni-ti-ka 265ki-ma ṣi-iḫ-ri ir-ni-ta-ka-ma luš-mida(-da) 266i-na na-ri šá dḪu-wa-wa šá tu-ṣa-ma-ru 267mi-zi ši-pi-ka 268i-na bat-ba-ti-ka ḫi-ri bu-ur-tam 269lu-ka-a-a-nu mê ellu i-na na-di-ka 270[ka-]su-tim me-e a-na dŠamaš ta-na-di 271[li-iš]ta-ḫa-sa-as dLugal-ban-da 272[dEn-ki-]dũ pi-su i-pu-šá-am-ma, iz-za-kàr a-na dGiš 273[is(?)]-tu(?) ta-áš-dan-nu e-pu-uš a-la-kam 274[la pa]la-aḫ libbi-ka ia-ti tu-uk-la-ni 275[šú-ku-]un i-di-a-am šú-pa-as-su 276[ḫarrana(?)]šá dḪu-wa-wa it-ta-la-ku 277.......... ki-bi-ma te-[ir]-šú-nu-ti (Three lines missing.) L.E. 281.............. nam-ma-la 282............... il-li-ku it-ti-ia 283............... ba-ku-nu-ši-im 284......... [ul]-la(?)-nu i-na ḫu-ud li-ib-bi 285[i-na še-me-e] an-ni-a ga-ba-šú 286e-diš ḫarrana(?) uš-te-[zi-ik] 287a-lik dGiš lu-[ul-lik a-na pa-ni-ka] 288li-lik il-ka .......... 289li-šá-ak-lim-[ka ḫarrana] ...... 290dGiš ù[dEn-ki-dũ] ....... 291mu-di-eš .......... 292bi-ri-[su-nu] ........ [87] Translation. (About ten lines missing.) Col. I. 11.................. (my friend?) 12[Something] that is exceedingly difficult, 13[Why] dost thou desire 14[to do this?] 15.... something (?) that is very [difficult (?)], 16[Why dost thou] desire 17[to go down to the forest]? 18A message [they carried] among [men] 19They carried about. 20They made a .... 21.............. they brought 22.............................. 23.............................. (About 17 lines missing.) 40............................. 41................... my friend 42................ they raised ..... 43answer [they returned.] 44[To] the woman 45They proceeded to the overthrowing Col. II. (About eleven lines missing.) 57.......... name(?) ............. 58[The one who is] a rival [to him] 59subdue and ................ 60Wailing ................ 61The mother [of Gišh, who knows everything] 62Before [Shamash raised her hand][88] 63Who 64Now(?) [why] 65hast thou stirred up the heart for my son, 66[Restlessness imposed upon him (?)] 67............................ (About four lines missing.) 72The eyes [of Enkidu filled with tears]. 73[He clutched] his heart; 74[Sadly(?)] he sighed. 75[The eyes of En]kidu filled with tears. 76[He clutched] his heart; 77[Sadly(?)] he sighed. 78The face [of Gišh was grieved]. 79[He spoke] to Enkidu: 80[“My friend, why are] thy eyes 81[Filled with tears]? 82Thy [heart clutched] 83Dost thou sigh [sadly(?)]?” 84[Enkidu opened his mouth] and 85spoke to Gišh: 86“Attacks, my friend, 87have exhausted my strength(?). 88My arms are lame, 89my strength has become weak.” 90Gišh opened his mouth and 91spoke to Enkidu: (About four lines missing.) Col. III. 96..... [until] Ḫuwawa, [the terrible], 97........................ 98............ [I destroyed]. 99[I will go down to the] cedar forest,[89] 100................... the jungle 101............... tambourine (?) 102................ I will open it. 103Enkidu opened his mouth and 104spoke to Gišh: 105“Know, my friend, in the mountain, 106when I moved about with the cattle 107to a distance of one double hour into the heart of the forest, 108[Alone?] I penetrated within it, 109[To] Ḫuwawa, whose roar is a flood, 110whose mouth is fire, 111whose breath is death. 112Why dost thou desire 113To do this? 114To advance towards 115the dwelling(?) of Ḫuwawa?” 116Gišh opened his mouth and 117[spoke to Enkidu: 118”... [the covering(?)] I will destroy. 119....[in the forest] 120.................... 121.................... 122To ................. 123The dwelling [of Ḫuwawa] 124The axe .......... 125Thou .......... 126I will [go down to the forest].” 127Enkidu opened his mouth and 128spoke to [Gish:] 129“When [together(?)] we go down 130To the [cedar] forest, 131whose guardian, O warrior Gish, 132a power(?) without [rest(?)], 133Ḫuwawa, an offspring(?) of ....[90] 134Adad ...................... 135He ........................ Col. IV. 136To keep safe [the cedar forest], 137[Enlil has decreed for it] seven-fold terror.” 138Gish [opened] his mouth and 139spoke to [Enkidu]: 140“Whoever, my friend, overcomes (?) [terror(?)], 141it is well (for him) with Shamash for the length of [his days]. 142Mankind will speak of it at the gates. 143Wherever terror is to be faced, 144Thou, forsooth, art in fear of death. 145Thy prowess lacks strength. 146I will go before thee. 147Though thy mouth calls to me; “thou art afraid to approach.” 148If I fall, I will establish my name. 149Gish, the corpse(?) of Ḫuwawa, the terrible one, 150has snatched (?) from the time that 151My offspring was born in ...... 152The lion restrained (?) thee, all of which thou knowest. 153........................ 154.............. thee and 155................ open (?) 156........ like a shepherd(?) ..... 157[When thou callest to me], thou afflictest my heart. 158I am determined 159[to enter] the cedar forest.[91] 160I will, indeed, establish my name. 161[The work(?)], my friend, to the artisans I will entrust. 162[Weapons(?)] let them mould before us.” 163[The work(?)] to the artisans they entrusted. 164A dwelling(?) they assigned to the workmen. 165Hatchets the masters moulded: 166Axes of 3 talents each they moulded. 167Lances the masters moulded; 168Blades(?) of 2 talents each, 169A spear of 30 mina each attached to them. 170The hilt of the lances of 30 mina in gold 171Gish and [Enki]du were equipped with 10 talents each 172.......... in Erech seven its .... 173....... the people heard and .... 174[proclaimed(?)] in the street of Erech of the plazas. 175..... Gis [brought him out(?)] 176[In the street (?)] of Erech of the plazas 177[Enkidu(?)] sat before him 178..... [thus] he spoke: 179”........ [of Erech] of the plazas 180............ [before him] Col. V. 181Gish of whom they speak, let me see! 182whose name fills the lands. 183I will lure him to the cedar forest, 184Like a strong offspring of Erech.[92] 185I will let the land hear (that) 186I am determined to lure (him) in the cedar (forest)5. 187A name I will establish.” 188The elders of Erech of the plazas 189brought word to Gish: 190“Thou art young, O Gish, and thy heart carries thee away. 191Thou dost not know what thou proposest to do. 192We hear that Huwawa is enraged. 193Who has ever opposed his weapon? 194To one [double hour] in the heart of the forest, 195Who has ever penetrated into it? 196Ḫuwawa, whose roar is a deluge, 197whose mouth is fire, whose breath is death. 198Why dost thou desire to do this? 199To advance towards the dwelling (?) of Ḫuwawa?” 200Gish heard the report of his counsellors. 201He saw and cried out to [his] friend: 202“Now, my friend, thus [I speak]. 203I fear him, but [I will go to the cedar forest(?)]; 204I will go [with thee to the cedar forest]. (About five lines missing.) 210.............................. 211May ................... thee[93] 212Thy god may (?) ........ thee; 213On the road may he guide [thee in safety(?)]. 214At the rampart of [Erech of the plazas], 215Gish kneeled down [before Shamash(?)], 216A word then he spoke [to him]: 217“I will go, O Shamash, [thy] hands [I seize hold of]. 218When I shall have saved [my life], 219Bring me back to the rampart [in Erech]. 220Grant protection [to me ?]!” 221Gish cried, ”[my friend] ...... 222His oracle .................. 223........................ 224........................ 225........................ 226When (?) (About two lines missing.) Col. VI. 229”[I(?)] Gish, the strong one (?) of the land. 230...... A road which I have never [trodden]; 231........ food ...... do not (?) know. 232[When] I shall have succeeded, 233[I will praise] thee in the joy of my heart, 234[I will extol (?)] the superiority of thy power, 235[I will seat thee] on thrones.” 236.................. his vessel(?) 237The masters [brought the weapons (?)]; 238[bow] and quiver 239They placed in hand. 240[He took] the hatchet. 241................. his quiver.[94] 242..... [to] the god(?) a second time 243[With his lance(?)] in his girdle, 244......... they took the road. 245[Again] they approached Gish! 246”[How long] till thou returnest to Erech?” 247[Again the elders] approached him. 248[For] the road they counselled Gis: 249“Do [not] rely, O Gish, on thy strength! 250Provide food and save thyself! 251Let Enkidu go before thee. 252He is acquainted with the way, he has trodden the road 253[to] the entrance of the forest. 254of Ḫuwawa all of them his ...... 255[He who goes] in advance will save the companion. 256Provide for his [road] and [save thyself]! 257(May) Shamash [carry out] thy endeavor! 258May he make thy eyes see the prophecy of thy mouth. 259May he track out (for thee) the closed path! 260May he level the road for thy treading! 261May he level the mountain for thy foot! 262During thy night6 the word that wilt rejoice 263may Lugal-banda convey, and stand by thee[95] 264in thy endeavor! 265Like a youth may he establish thy endeavor! 266In the river of Ḫuwawa as thou plannest, 267wash thy feet! 268Round about thee dig a well! 269May there be pure water constantly for thy libation 270Goblets of water pour out to Shamash! 271[May] Lugal-banda take note of it!” 272[Enkidu] opened his mouth and spoke to Gish: 273”[Since thou art resolved] to take the road. 274Thy heart [be not afraid,] trust to me! 275[Confide] to my hand his dwelling(?)!” 276[on the road to] Ḫuwawa they proceeded. 277....... command their return (Three lines missing.) L.E. 281............... were filled. 282.......... they will go with me. 283............................... 284.................. joyfully. 285[Upon hearing] this word of his, 286Alone, the road(?) [he levelled]. 287“Go, O Gish [I will go before thee(?)]. 288May thy god(?) go ......... 289May he show [thee the road !] ..... 290Gish and [Enkidu] 291Knowingly .................... 292Between [them] ................ [96]Lines 13–14 (also line 16). See for the restoration, lines 112–13. Line 62. For the restoration, see Jensen, p. 146 (Tablet III, 2a,9.) Lines 64–66. Restored on the basis of the Assyrian version, ib. line 10. Line 72. Cf. Assyrian version, Tablet IV, 4, 10, and restore at the end of this line di-im-tam as in our text, instead of Jensen’s conjecture. Lines 74, 77 and 83. The restoration zar-biš, suggested by the Assyrian version, Tablet IV, 4, 4. Lines 76 and 82. Cf. Assyrian version, Tablet VIII, 3, 18. Line 78. (ú-ta-ab-bil from abâlu, “grieve” or “darkened.” Cf. uš-ta-kal (Assyrian version, ib. line 9), where, perhaps, we are to restore it-ta-[bil pa-ni-šú]. Line 87. uš-ta-li-pa from elêpu, “exhaust.” See Muss-Arnolt, Assyrian Dictionary, p. 49a. Line 89. Cf. Assyrian version, ib. line 11, and restore the end of the line there to i-ni-iš, as in our text. Line 96. For dapinu as an epithet of Ḫuwawa, see Assyrian version, Tablet III, 2a, 17, and 3a, 12. Dapinu occurs also as a description of an ox (Rm 618, Bezold, Catalogue of the Kouyunjik Tablets, etc., p. 1627). Line 98. The restoration on the basis of ib. III, 2a, 18. Lines 96–98 may possibly form a parallel to ib. lines 17–18, which would then read about as follows: “Until I overcome Ḫuwawa, the terrible, and all the evil in the land I shall have destroyed.” At the same time, it is possible that we are to restore [lu-ul]-li-ik at the end of line 98. Line 101. lilissu occurs in the Assyrian version, Tablet IV, 6, 36. Line 100. For ḫalbu, “jungle,” see Assyrian version, Tablet V, 3, 39 (p. 160). Lines 109–111. These lines enable us properly to restore Assyrian version, Tablet IV, 5, 3 = Haupt’s edition, p. 83 (col. 5, 3). No doubt the text read as ours mu-tum (or mu-u-tum) na-pis-su. Line 115. šupatu, which occurs again in line 199 and also line 275.šú-pa-as-su (= šupat-su) must have some such meaning as [97]“dwelling,” demanded by the context. [Dhorme refers me to OLZ 1916, p. 145]. Line 129. Restored on the basis of the Assyrian version, Tablet IV, 6, 38. Line 131. The restoration muḳtablu, tentatively suggested on the basis of CT XVIII, 30, 7b, where muḳtablu, “warrior,” appears as one of the designations of Gilgamesh, followed by a-lik pa-na, “the one who goes in advance,” or “leader”—the phrase so constantly used in the Ḫuwawa episode. Line 132. Cf. Assyrian version, Tablet I, 5, 18–19. Lines 136–137. These two lines restored on the basis of Jensen IV, 5, 2 and 5. The variant in the Assyrian version, šá niše (written Ukumeš in one case and Lumeš in the other), for the numeral 7 in our text to designate a terror of the largest and most widespread character, is interesting. The number 7 is similarly used as a designation of Gilgamesh, who is called Esigga imin, “seven-fold strong,” i.e., supremely strong (CT XVIII, 30, 6–8). Similarly, Enkidu, ib. line 10, is designated a-rá imina, “seven-fold.” Line 149. A difficult line because of the uncertainty of the reading at the beginning of the following line. The most obvious meaning of mi-it-tu is “corpse,” though in the Assyrian version šalamtu is used (Assyrian version, Tablet V, 2, 42). On the other hand, it is possible—as Dr. Lutz suggested to me—that mittu, despite the manner of writing, is identical with miṭṭú, the name of a divine weapon, well-known from the Assyrian creation myth (Tablet IV, 130), and other passages. The combination miṭ-ṭu šá-ḳu-ú-, “lofty weapon,” in the Bilingual text IV, R², 18 No. 3, 31–32, would favor the meaning “weapon” in our passage, since [šá]-ḳu-tu is a possible restoration at the beginning of line 150. However, the writing mi-it-ti points too distinctly to a derivative of the stem mâtu, and until a satisfactory explanation of lines 150–152 is forthcoming, we must stick to the meaning “corpse” and read the verb il-ḳu-ut. Line 152. The context suggests “lion” for the puzzling la-bu. Line 156. Another puzzling line. Dr. Clay’s copy is an accurate reproduction of what is distinguishable. At the close of the line there appears to be a sign written over an erasure. Line 158. [ga-ti lu-]uš-kun as in line 186, literally, “I will place my hand,” i.e., I purpose, I am determined. [98] Line 160. The restoration on the basis of the parallel line 187. Note the interesting phrase, “writing a name” in the sense of acquiring “fame.” Line 161. The kiškattê, “artisans,” are introduced also in the Assyrian version, Tablet VI, 187, to look at the enormous size and weight of the horns of the slain divine bull. See for other passages Muss-Arnolt Assyrian Dictionary, p. 450b. At the beginning of this line, we must seek for the same word as in line 163. Line 162. While the restoration belê, “weapon,” is purely conjectural, the context clearly demands some such word. I choose belê in preference to kakkê, in view of the Assyrian version, Tablet VI, 1. Line 163. Putuku (or putukku) from patâku would be an appropriate word for the fabrication of weapons. Line 165. The rabûtim here, as in line 167, I take as the “master mechanics” as contrasted with the ummianu, “common workmen,” or journeymen. A parallel to this forging of the weapons for the two heroes is to be found in the Sumerian fragment of the Gilgamesh Epic published by Langdon, Historical and Religious Texts from the Temple Library of Nippur (Munich, 1914), No. 55, 1–15. Lines 168–170 describe the forging of the various parts of the lances for the two heroes. The ṣipru is the spear point Muss-Arnolt, Assyrian Dictionary, p. 886b; the išid paṭri is clearly the “hilt,” and the mešelitum I therefore take as the “blade” proper. The word occurs here for the first time, so far as I can see. For 30 minas, see Assyrian version, Tablet VI, 189, as the weight of the two horns of the divine bull. Each axe weighing 3 biltu, and the lance with point and hilt 3 biltu we would have to assume 4 biltu for each pašu, so as to get a total of 10 biltu as the weight of the weapons for each hero. The lance is depicted on seal cylinders representing Gilgamesh and Enkidu, for example, Ward, Seal Cylinders, No. 199, and also in Nos. 184 and 191 in the field, with the broad hilt; and in an enlarged form in No. 648. Note the clear indication of the hilt. The two figures are Gilgamesh and Enkidu—not two Gilgameshes, as Ward assumed. See above, page 34. A different weapon is the club or mace, as seen in Ward, Nos. 170 and 173. This appears also to be the weapon which Gilgamesh holds in his hand on the colossal figure from the palace of Sargon (Jastrow, Civilization of [99]Babylonia and Assyria, Pl. LVII), though it has been given a somewhat grotesque character by a perhaps intentional approach to the scimitar, associated with Marduk (see Ward, Seal Cylinders, Chap. XXVII). The exact determination of the various weapons depicted on seal-cylinders merits a special study. Line 181. Begins a speech of Ḫuwawa, extending to line 187, reported to Gish by the elders (line 188–189), who add a further warning to the youthful and impetuous hero. Line 183. lu-uk-šú-su (also l. 186), from akâšu, “drive on” or “lure on,” occurs on the Pennsylvania tablet, line 135, uk-ki-ši, “lure on” or “entrap,” which Langdon erroneously renders “take away” and thereby misses the point completely. See the comment to the line of the Pennsylvania tablet in question. Line 192. On the phrase šanû bunu, “change of countenance,” in the sense of “enraged,” see the note to the Pennsylvania tablet, l.31. Line 194. nu-ma-at occurs in a tablet published by Meissner, Altbabyl. Privatrecht, No. 100, with bît abi, which shows that the total confine of a property is meant; here, therefore, the “interior” of the forest or heart. It is hardly a “by-form” of nuptum as Muss-Arnolt, Assyrian Dictionary, p. 690b, and others have supposed, though nu-um-tum in one passage quoted by Muss-Arnolt, ib. p. 705a, may have arisen from an aspirate pronunciation of the p in nubtum. Line 215. The kneeling attitude of prayer is an interesting touch. It symbolizes submission, as is shown by the description of Gilgamesh’s defeat in the encounter with Enkidu (Pennsylvania tablet, l. 227), where Gilgamesh is represented as forced to “kneel” to the ground. Again in the Assyrian version, Tablet V, 4, 6, Gilgamesh kneels down (though the reading ka-mis is not certain) and has a vision. Line 229. It is much to be regretted that this line is so badly preserved, for it would have enabled us definitely to restore the opening line of the Assyrian version of the Gilgamesh Epic. The fragment published by Jeremias in his appendix to his Izdubar-Nimrod, Plate IV, gives us the end of the colophon line to the Epic, reading ……… di ma-a-ti (cf. ib., Pl. I, 1. … a-ti). Our text evidently reproduces the same phrase and enables us to supply ka, as well as [100]the name of the hero Gišh of which there are distinct traces. The missing word, therefore, describes the hero as the ruler, or controller of the land. But what are the two signs before ka? A participial form from pakâdu, which one naturally thinks of, is impossible because of the ka, and for the same reason one cannot supply the word for shepherd (nakidu). One might think of ka-ak-ka-du, except that kakkadu is not used for “head” in the sense of “chief” of the land. I venture to restore [i-ik-]ka-di, “strong one.” Our text at all events disposes of Haupt’s conjecture iš-di ma-a-ti (JAOS 22, p. 11), “Bottom of the earth,” as also of Ungnad’s proposed [a-di pa]-a-ti, “to the ends” (Ungnad-Gressmann, Gilgamesch-Epos, p. 6, note), or a reading di-ma-a-ti, “pillars.” The first line of the Assyrian version would now read šá nak-ba i-mu-ru [dGis-gi(n)-maš i-ik-ka]-di ma-a-ti, i.e., “The one who saw everything, Gilgamesh the strong one (?) of the land.” We may at all events be quite certain that the name of the hero occurred in the first line and that he was described by some epithet indicating his superior position. Lines 229–235 are again an address of Gilgamesh to the sun-god, after having received a favorable “oracle” from the god (line 222). The hero promises to honor and to celebrate the god, by erecting thrones for him. Lines 237–244 describe the arming of the hero by the “master” craftsman. In addition to the pašu and paṭru, the bow (?) and quiver are given to him. Line 249 is paralleled in the new fragment of the Assyrian version published by King in PSBA 1914, page 66 (col. 1, 2), except that this fragment adds gi-mir to e-mu-ḳi-ka. Lines 251–252 correspond to column 1, 6–8, of King’s fragment, with interesting variations “battle” and “fight” instead of “way” and “road,” which show that in the interval between the old Babylonian and the Assyrian version, the real reason why Enkidu should lead the way, namely, because he knows the country in which Ḫuwawa dwells (lines 252–253), was supplemented by describing Enkidu also as being more experienced in battle than Gilgamesh. Line 254. I am unable to furnish a satisfactory rendering for this line, owing to the uncertainty of the word at the end. Can it [101]be “his household,” from the stem which in Hebrew gives us מִשְׁפָּחָה “family?” Line 255. Is paralleled by col. 1, 4, of King’s new fragment. The episode of Gišh and Enkidu proceeding to Ninsun, the mother of Gish, to obtain her counsel, which follows in King’s fragment, appears to have been omitted in the old Babylonian version. Such an elaboration of the tale is exactly what we should expect as it passed down the ages. Line 257. Our text shows that irnittu (lines 257, 264, 265) means primarily “endeavor,” and then success in one’s endeavor, or “triumph.” Lines 266–270. Do not appear to refer to rites performed after a victory, as might at a first glance appear, but merely voice the hope that Gišh will completely take possession of Ḫuwawa’s territory, so as to wash up after the fight in Ḫuwawa’s own stream; and the hope is also expressed that he may find pure water in Ḫuwawa’s land in abundance, to offer a libation to Šhamašh. Line 275. On šú-pa-as-su = šupat-su, see above, to l. 115. [Note on Sabitum (above, p. 11) In a communication before the Oriental Club of Philadelphia (Feb. 10, 1920), Prof. Haupt made the suggestion that sa-bi-tum (or tu), hitherto regarded as a proper name, is an epithet describing the woman who dwells at the seashore which Gilgamesh in the course of his wanderings reaches, as an “innkeeper”. It is noticeable that the term always appears without the determinative placed before proper names; and since in the old Babylonian version (so far as preserved) and in the Assyrian version, the determinative is invariably used, its consistent absence in the case of sabitum (Assyrian Version, Tablet X, 1, 1, 10, 15, 20; 2, 15–16 [sa-bit]; Meissner fragment col. 2, 11–12) speaks in favor of Professor Haupt’s suggestion. The meaning “innkeeper”, while not as yet found in Babylonian-Assyrian literature is most plausible, since we have sabū as a general name for ’drink’, though originally designating perhaps more specifically sesame wine (Muss-Arnolt, Assyrian Dictionary, p. 745b) or distilled brandy, according to Prof. Haupt. Similarly, in the Aramaic dialects, sebha is used for “to drink” and in the Pael to “furnish drink”. Muss-Arnolt in [102]his Assyrian Dictionary, 746b, has also recognized that sabitum was originally an epithet and compares the Aramaic sebhoyâthâ(p1) “barmaids”. In view of the bad reputation of inns in ancient Babylonia as brothels, it would be natural for an epithet like sabitum to become the equivalent to “public” women, just as the inn was a “public” house. Sabitum would, therefore, have the same force as šamḫatu (the “harlot”), used in the Gilgamesh Epic by the side of ḫarimtu “woman” (see the note to line 46 of Pennsylvania Tablet). The Sumerian term for the female innkeeper is Sal Geštinna “the woman of the wine,” known to us from the Hammurabi Code §§108–111. The bad reputation of inns is confirmed by these statutes, for the house of the Sal Geštinna is a gathering place for outlaws. The punishment of a female devotee who enters the “house of a wine woman” (bît Sal Geštinna §110) is death. It was not “prohibition” that prompted so severe a punishment, but the recognition of the purpose for which a devotee would enter such a house of ill repute. The speech of the sabitum or innkeeper to Gilgamesh (above, p. 12) was, therefore, an invitation to stay with her, instead of seeking for life elsewhere. Viewed as coming from a “public woman” the address becomes significant. The invitation would be parallel to the temptation offered by the ḫarimtu in the first tablet of the Enkidu, and to which Enkidu succumbs. The incident in the tablet would, therefore, form a parallel in the adventures of Gilgamesh to the one that originally belonged to the Enkidu cycle. Finally, it is quite possible that sabitum is actually the Akkadian equivalent of the Sumerian Sal Geštinna, though naturally until this equation is confirmed by a syllabary or by other direct evidence, it remains a conjecture. See now also Albright’s remarks on Sabitum in the A. J. S. L. 36, pp. 269 seq.] [103] 1 Scribal error for an. 2 Text apparently di. 3 Hardly ul. 4 Omitted by scribe. 5 Kišti omitted by scribe. 6 I.e., at night to thee, may Lugal-banda, etc. Corrections to the Text of Langdon’s Edition of the Pennsylvania Tablet.1 Column 1. 5. Read it-lu-tim (“heroes”) instead of id-da-tim (“omens”). 6. Read ka-ka-bu instead of ka-ka-’a. This disposes of Langdon’s note 2 on p. 211. 9 Read ú-ni-iš-šú-ma, “I became weak” (from enêšu, “weak”) instead of ilam iš-šú-ma, “He bore a net”(!). This disposes of Langdon’s note 5 on page 211. 10. Read Urukki instead of ad-ki. Langdon’s note 7 is wrong. 12. Langdon’s note 8 is wrong. ú-um-mid-ma pu-ti does not mean “he attained my front.” 14. Read ab-ba-la-áš-šú instead of at-ba-la-áš-šú. 15. Read mu-di-a-at instead of mu-u-da-a-at. 20. Read ta-ḫa-du instead of an impossible [sa]-ah-ḫa-ta—two mistakes in one word. Supply kima Sal before taḫadu. 22. Read áš-šú instead of šú; and at the end of the line read [tu-ut]-tu-ú-ma instead of šú-ú-zu. 23. Read ta-tar-ra-[as-su]. 24. Read [uš]-ti-nim-ma instead of [iš]-ti-lam-ma. 28. Read at the beginning šá instead of ina. 29. Langdon’s text and transliteration of the first word do not tally. Read ḫa-aṣ-ṣi-nu, just as in line 31. 32. Read aḫ-ta-du (“I rejoiced”) instead of aḫ-ta-ta. Column 2. 4. Read at the end of the line di-da-šá(?) ip-tí-[e] instead of Di-?-al-lu-un (!). 5. Supply dEn-ki-dū at the beginning. Traces point to this reading. 19. Read [gi]-it-ma-[lu] after dGiš, as suggested by the Assyrian version, Tablet I, 4, 38, where emûḳu (“strength”) replaces nepištu of our text. 20. Read at-[ta kima Sal ta-ḫa]-bu-[ub]-šú. 21. Read ta-[ra-am-šú ki-ma]. [104] 23. Read as one word ma-a-ag-ri-i-im (“accursed”), spelled in characteristic Hammurabi fashion, instead of dividing into two words ma-a-ak and ri-i-im, as Langdon does, who suggests as a translation “unto the place yonder(?) of the shepherd”(!). 24. Read im-ta-ḫar instead of im-ta-gar. 32. Supply ili(?) after ki-ma. 33. Read šá-ri-i-im as one word. 35. Read i-na [áš]-ri-šú [im]-ḫu-ru. 36. Traces at beginning point to either ù or ki (= itti). Restoration of lines 36–39 (perhaps to be distributed into five lines) on the basis of the Assyrian version, Tablet I, 4, 2–5. Column 3. 14. Read Kàš (= šikaram, “wine”) ši-ti, “drink,” as in line 17, instead of bi-iš-ti, which leads Langdon to render this perfectly simple line “of the conditions and the fate of the land”(!). 21. Read it-tam-ru instead of it-ta-bir-ru. 22. Supply [lùŠú]-I. 29. Read ú-gi-ir-ri from garû (“attack), instead of separating into ú and gi-ir-ri, as Langdon does, who translates “and the lion.” The sign used can never stand for the copula! Nor is girru, “lion!” 30. Read Síbmeš, “shepherds,” instead of šab-[ši]-eš! 31. šib-ba-ri is not “mountain goat,” nor can ut-tap-pi-iš mean “capture.” The first word means “dagger,” and the second “he drew out.” 33. Read it-ti-[lu] na-ki-[di-e], instead of itti immer nakie which yields no sense. Langdon’s rendering, even on the basis of his reading of the line, is a grammatical monstrosity. 35. Read giš instead of wa. 37. Read perhaps a-na [na-ki-di-e i]- za-ak-ki-ir. Column 4. 4. The first sign is clearly iz, not ta, as Langdon has it in note 1 on page 216. 9. The fourth sign is su, not šú. 10. Separate e-eš (“why”) from the following. Read ta-ḫi-[il], followed, perhaps, by la. The last sign is not certain; it may be ma. [105] 11. Read lim-nu instead of mi-nu. In the same line read a-la-ku ma-na-aḫ-[ti]-ka instead of a-la-ku-zu(!) na-aḫ … ma, which, naturally, Langdon cannot translate. 16. Read e-lu-tim instead of pa-a-ta-tim. The first sign of the line, tu, is not certain, because apparently written over an erasure. The second sign may be a. Some one has scratched the tablet at this point. 18. Read uk-la-at âli (?) instead of ug-ad-ad-lil, which gives no possible sense! Column 5. 2. Read [wa]-ar-ki-šú. 8. Read i-ta-wa-a instead of i-ta-me-a. The word pi-it-tam belongs to line 9! The sign pi is unmistakable. This disposes of note 1 on p. 218. 9. Read Mi = ṣalmu, “image.” This disposes of Langdon’s note 2 on page 218. Of six notes on this page, four are wrong. 11. The first sign appears to be si and the second ma. At the end we are perhaps to supply [šá-ki-i pu]-uk-ku-ul, on the basis of the Assyrian version, Tablet IV, 2, 45, šá-ki-i pu-[uk-ku-ul]. 12. Traces at end of line suggest i-pa(?)-ka-du. 13. Read i-[na mâti da-an e-mu]-ki i-wa. 18. Read ur-šá-nu instead of ip-šá-nu. 19. Read i-šá-ru instead of i-tu-ru. 24. The reading it-ti after dGiš is suggested by the traces. 25. Read in-ni-[ib-bi-it] at the end of the line. 28. Read ip-ta-ra-[aṣ a-la]-ak-tam at the end of the line, as in the Assyrian version, Tablet IV, 2, 37. 30. The conjectural restoration is based on the Assyrian version, Tablet IV, 2, 36. Column 6. 3. Read i-na ṣi-ri-[šú]. 5. Supply [il-li-ik]. 21. Langdon’s text has a superfluous ga. 22. Read uz-za-šú, “his anger,” instead of uṣ-ṣa-šú, “his javelin” (!). 23. Read i-ni-iḫ i-ra-as-su, i.e., “his breast was quieted,” in the sense of “his anger was appeased.” 31. Read ri-eš-ka instead of ri-eš-su. [106] In general, it should be noted that the indications of the number of lines missing at the bottom of columns 1–3 and at the top of columns 4–6 as given by Langdon are misleading. Nor should he have drawn any lines at the bottom of columns 1–3 as though the tablet were complete. Besides in very many cases the space indications of what is missing within a line are inaccurate. Dr. Langdon also omitted to copy the statement on the edge: 4 šú-ši, i.e., “240 lines;” and in the colophon he mistranslates šú-tu-ur, “written,” as though from šaṭâru, “write,” whereas the form is the permansive III, 1, of atâru, “to be in excess of.” The sign tu never has the value ṭu! In all, Langdon has misread the text or mistransliterated it in over forty places, and of the 204 preserved lines he has mistranslated about one-half. 1 The enumeration here is according to Langdon’s edition. Plates Plate I. The Yale Tablet. Plate II. The Yale Tablet. Plate III. The Yale Tablet. Plate IV. The Yale Tablet. Plate V. The Yale Tablet. Plate VI. The Yale Tablet. Plate VII. The Yale Tablet.

      Compared to the other versions focusing on the epic of Gilgamesh, this version looks more into Gilgamesh's cure for immortality after Enkidu's death. The "us" in this instance would be Gilgamesh and his search for a cure while the "them" would be the enemies which are trying stop him which include the forces he come along. The text is able to create this distinction by describing Gilgamesh as the main character as the one who is need of a cure because struggles to come to terms that he will die one day. Not to mention, Enkidu as a being was able to turn Gilgamesh into a noble figure who used his power for good turning him into a more likeable figure which is why the reader also roots for him to find a cure. Gilgamesh as a figure shows that in his time period, males were the ones who were seen as leaders who have strength because the other females in all versions of the text do not carry dynamic roles that showcase their personality or even their endearing qualities. There are more political and nationalistic themes compared to the Sumerian versions which illustrate how linguistics and language can play a role in how a culture might be perceived. By using the strong characteristics of Gilgamesh, the text is ultimately able to show the civilization of Uruk and create a sense of identity as a result. CC BY Ajey Sasimugunthan (contact)

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC-2024-02555

      __Corresponding author(s): __Maurizio Molinari

      [Please use this template only if the submitted manuscript should be considered by the affiliate journal as a full revision in response to the points raised by the reviewers.

      • *

      If you wish to submit a preliminary revision with a revision plan, please use our "Revision Plan" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]

      1. General Statements [optional]

      We thank the 3 reviewers for the positive and constructive comments to our manuscript.

      Please see below the point-by-point responses to their suggestions.

      2. Point-by-point description of the revisions

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      The paper proposes an interesting role for ERp44 in TMX5 retention. The authors identified a list of proposed TMX5 clients which include many Golgi localised proteins but do not discuss the role for TMX for instance in protein folding. In this context it is not absolutely clear whether TMX5 acts as a trafficking chaperone? are clients functionally engaged in the Golgi or ER or both?

      This work focuses on the crosstalk between a member of the PDI superfamily lacking a conventional cytosolic ER retention motif (TMX5), and ERp44, a PDI family member previously reported to retrieve in the ER proteins that lack the ER retention motif (ERp44). To support our conclusions on the involvement of ERp44 in control of TMX5’s intracellular distribution, we have added new data obtained by characterization of a cell line lacking ERp44, where more than 50% of TMX5 escapes ER retention (new Fig. 6).

      __We agree with the referee that the assessment of the biological role of TMX5 is of interest. We mention in this manuscript that there is a follow-up study (ongoing in the lab) on TMX5 clients and TMX5 function. More specifically, we are monitoring the action of TMX5 on the biogenesis and intracellular trafficking of class I HLA molecules, which are, besides PDI, ERp57 and ERp44, major interactors (clients) of TMX5 (please also refer to the initial and final parts of the new discussion). __

      The defining criteria for the client proteins were not included. At last, it might be of interest to evaluate for how long TMX5 clients are retained on the protein, whether it is temporary (as for instance a folding sensor) or more permanent.

      The list of interacting proteins is now available (__Data are available via ProteomeXchange with identifier PXD054716."), their selection for presentation in Figure 3B is now explained more clearly (Results, page 6). Also better explained is that we define as “clients of TMX5” those endogenous proteins that associate with TMX5, covalently, via the catalytic Cys220. The mutation of the TMX5 active site cysteine residue does not impact the covalent association of PDI, ERp57 and ERp44 with TMX5. For this reason, we do not consider these PDI family members clients of TMX5. In this submission, we explore the covalent association of ERp44 and its consequences on TMX5 subcellular distribution. Interacting via non-catalytic Cysteine residues 114 and 124 with the catalytic cysteine 29 of ERp44, we identify TMX5 as a client of the latter.__

      The preparation of figures could be greatly improved and there is some inconsistency among similar gels.


      Please refer to the point-by-point answers below.


      The proposed model of ERp44, ER retention vs ER retrieval, is unclear. Overall, there is more room for improved discussion beyond the conclusions from experiments.

      __We thank the referee for these comments. We have improved the description of the results, and we separated the Discussion (written de novo) from the Results section. __

      The ERp44 interaction is interesting especially since the protein contains an incomplete thioredoxin domain (such as ERp29, PDIA17 and 18), would the interaction between Erp44 and TMX5 be involved in some holdase/competitor role thereby allowing for client selectivity (or kinetics)? In addition, all the experiments were carried out in Hek293T or MEF cells, would the authors anticipate some interactions of TMX5 with PDIA17/18 in cells where those proteins are highly expressed? Testing whether the observation is a general mechanism occurring between TMX5 and PDI family members with incomplete thioredoxin sites would be an asset.

      __We thank the referee for this comment that we implemented in the new discussion. __

      Major comments Fig 2 - avoid labels on the blots that might obscure information and impede clarity and interpretation. o The % of resistant protein can be otherwise placed.


      __This has been modified, thank you. __

      • What does the asterix in 2B signify? This should be included in the legend.

      We have now specified in the legend of figures that asterisks show cross-reacting polypeptide bands.

      • A label for 'deglycosylated' proteins could be included.

      __We added a label for de- and for glycosylated proteins in the EndoH essays in Figs. 2A, 2B and 5B. __

      • Consider treating with PNGase.

      This is now showy in panel 2A, lane 5.

      • There is a change in EndoH resistance of about 3-4% among wt, C220A & C114A, is this significant?

      We do not consider significant these variations. Our data show that the mutation of TMX5 Cys 114 or of Cys124 to alanine substantially reduce (without abolishing) the co-IP with ERp44. This means that the proteins interact less, or that the interaction is more short living. The EndoH experiment shown in Fig. 2B and the CLSM analyses in Figs. 2D-2O fail to reveal significant differences showing that these reduced or more short living associations with ERp44 are sufficient to control TMX5 distribution.

      In the previous submission, the function of ERp44 in retaining TMX5 in the ER was supported by data showing that the co-expression of ERp44 retains TMX5 in the ER, but co-expression of ERp44C29S that cannot bind TMX5 fails to retain TMX5 in the ER. These model is further supported in this new submission by the release of 50% of TMX5 from the ER in cells lacking ERp44, which is substantially inhibited to the levels measured in wild type cells upon back-transfection of ERp44, but not upon the co-transfection of the ERp44C29S mutant (new Figure 6).


      • Equivalent inputs (cell lysates) for the IPs should be included.

      __ These have now been added in Figs. 4, 5 6, and 7.__

      Fig 3A - Indicate the specific bands that were subject to MS. How did the authors correct for non-specific interactors and false positives? Perhaps a more specifically targeted approach could be utilised.

      • How do the authors explain the absence of bands representing the reduced form of interacting TMX5 interactors?

      • What was the inclusion and exclusion criteria used to determine which of the proteins listed were clients?

      The endogenous proteins present in the entire region of the gel labeled with the red and blue rectangles have been sequenced (see methods section and this is now also better explained in the results section, page 6). Only the proteins that disappear from the corresponding region of the gel when the samples have been reduced are listed in the table. This is also better explained in the text (page 6). These experiments have been repeated few times with a series of controls (e.g., mock-transfected cells and cells transfected with other members of the TMX family (shown to capture and to impact on the fate of other endogenous polypeptides in previous publications from our lab)). An in parallel analysis of mock, TMX3, TMX4 and TMX5 interactors has been published in (Kucinska et al Nature Comm 2023), where we focused on the biological function of TMX4. The references referring to the TMX1 study (Brambilla et al 2015) and the TMX4 study (Kucinska et al) are given in the text.

      The Table in Fig. 3B only lists the interacting polypeptides that have a MW __- It might be useful to perform MS on the C220A mutant and compare those results to the WT.

      __To validate few interactions with endogenous proteins detected in MS, and to compare the interactions of TMX5 and TMX5C220A, we have used the specifically targeted approach suggested above by the referee (i.e., co-IP validated by WB, Figs. 3C-3F).

      __

      Fig 4 - Equivalent inputs (cell lysates) for the IPs should be included.

      __This is now shown as panel A in Fig. 4.____

      __

      Fig 5 - Equivalent inputs (cell lysates) for the IPs should be included.

      This is now Figure 7, see new panel 7A

      Fig 6 - A loading control should be included.

      __This is now Fig. 5. Both panels A and B in Fig. 5 show total cell extracts____

      __

      • Blot using anti-HA to identify ERp44 should be included to substantiate claims.

      The ERp44 and TMX5 components of the ERp44-s-s-TMX5 mixed disulfides are detected upon IP:HA followed by WB:V5 (to show the TMX5 component) and upon IP:V5 followed by WB:HA to show the ERp44 component) in Figs. 4B-4E and 7B-7C.

      • How do the authors account for the huge difference in TMX5 associated complexes shown in Fig 6A compared to Fig 3A.

      Fig. 6 is now Fig. 5. As specified in the legends of the figures, Fig. 3A shows a gel, where the complexes are stained with silver, Fig. 5A is a WB, where the complexes are stained with an antibody. The intensities of the signals cannot be compared.

      • Inappropriate marking on the gel area.
      • Inconsistencies in protein standard labeling

      This has carefully been checked and corrected where needed. Please note that we used two different MW standards for our figures (200, 117, 97, 66, 45, 31 kDa and 270, 175, 130, 95, 66, 53, 37 kDa)

      • It might be useful to demonstrate the colocalisation of ERp44 and ERp44C29S with Giantin and with TMX5 considering that ERp44 is known to cycle between the Golgi and ER.

      These data are shown in Fig. 5D-5I.

      Reviewer #1 (Significance (Required)):

      This work provides an additional understanding on how the regulation of Erp44 trafficking might occur (and perhaps additional PDIs), and lead to the characterization of kinetic value that might explain better productive protein folding in the early secretory pathway. This represents a significant advance in the field and may in turn unveil uncharacterized pathophysiological functions in various diseases. This is a serious study well conducted and original by an expert in the field that desserves publication.

      Field of expertise: ER homeostasis control

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      The manuscript by Solda et al, investigates TMX5, a poorly understood member of the PDI family that lacks an ER-retrieval motif. They find that it localizes to the ER and the Golgi and that it interacts with ERp44. This interaction requires formation of a mixed disulfide and they identify the cysteine residues in both proteins that mediate this interaction. Overall, this is a well written manuscript that is easy to follow and the story is compact and straight-forward. It provides some new and solid insight into the biology of TMX5 without going into depth of what the cellular role of TMX5 is or might be. I have only very few comments and suggestions:

      1- The authors conclude that ERp44 associates only with ER-localized TMX5. I am not sure that this is a valid conclusion based on the data. EndoH sensitivity just means that the protein has not gone to the medial Golgi. The pool of TMX5 could therefore be an ERGIC-based pool, or it could interact with a TMX5 that is recycled directly from the first Golgi cisterna, where complex glycosylation is unlikely to occur. Can this be validated using another type of experiment? Alternatively, the wording could be changed.

      We thank the reviewer. We agree with this insightful comment that led us to change the wording used in some part of the text.

      2- Is the trafficking of TMX5 dependent on its glycosylation?

      This is another insightful comment that we report in the ____new discussion, where we write, page 14 “____It should be noted that in the case of TMX5 the extensive N-glycosylation could engage____ leguminous L-type lectins located in the ER (VIPL), cycling between the ER and the intermediate compartment (ERGIC) (ERGIC-53) or between the ERGIC and the cis-Golgi (VIP36)_33-36_ and have an impact on the subcellular distribution and activity of TMX5.____”

      3- Figure 6: The data are not really convincing. Just because the color turns yellow, it does not mean that there is colocalization. The green channel is overexposed in this area of the cell, and anything will produce a yellow color, even if there is no genuine colocalization. Maybe the authors could provide a different example and even better would be a quantification of the colocalization.

      __We thank the referee for this comment. We show images of better quality, where the black/white channels clearly show the co-localization (or lack thereof) of TMX5 with the Golgi marker Giantin in cells mock-transfected (co-localization TMX5:Giantin, Fig. 5D), co-transfected with ERp44 (no co-localization TMX5:Giantin, Fig. 5E), or co-transfected with ERp44C29S, co-localization TMX5:Giantin, Fig. 5F). Figs. 5G-5I show the corresponding results for the co-localization or lack thereof between TMX5C220A and Giantin. Importantly, the IF data match the data shown in Fig. 5B, where release from the ER (or arrival in the medial Golgi, see text of the manuscript and comment 1 by the referee) is assessed by monitoring complex glycosylation. __

      Reviewer #2 (Significance (Required)):

      This is a solid story that will be of interest of scientists working on various aspects of the secretory pathway and protein quality control. The advance is rather incremental, because there are no experiments that provide insight into the cellular roles of TMX5.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)):

      Solda et al have assembled data on the transmembrane redox enzyme TMX5, on which currently very little information is available. TMX5 does not contain any obvious targeting signal, unlike the other TMX family proteins, which localize to the ER. TMX5 has 5 glycosylation sites, which can be used to determine its intracellular localization biochemically. Indeed, about 20% of TMX5 is found as endoH-resistant, indicating Golgi localization. This is confirmed with beautiful IF imagery and giantin co-localization. The Golgi localization requires two luminal cysteines (C212, 177), which likely form a disulfide bond. TMX5 acts as a natural cysteine-trapping protein, allowing for easy assessment of its interactors. Within its interactome, the authors found multiple members of the thioredoxin family. Many of these interactions occur within the CXXS motif, but notably ERp44 does not require this motif to interact, indicating this and other interactions are not of a catalytic nature. Instead, the authors found this interaction to be essential for ER retention or retrieval and depends on the cysteine within the ERp44 "active" site. The study provides critical first insight about the potential functions and sites of activity of TMX5.

      Specific Points: 1. The results are very convincing and of high quality. 2. The cytosolic tail of TMX5 contains an LI motif, which could act as a post-ER localization signal. Since the protein might play a role in ciliogenesis, this motif could be critical. In this context, I am wondering which mutations are known to lead to the disease spectrum.


      The position of disease-related TMX5 mutations identified so far are given in Xu H, et al (2024) Mol Genet Genomic Med 12: e2340 _https://www.ncbi.nlm.nih.gov/pubmed/38073519_ and in ____Deng T, Xie Y (2024) Mol Genet Genomic Med 12: e2343 https://www.ncbi.nlm.nih.gov/pubmed/38156946____.

      They are all distributed in the luminal part of the protein____.


      Mutation of C114 and C124 abrogates interaction with ERp44. Therefore, I would expect these mutations to increase endoH resistance and Golgi staining. This should be investigated by the authors.

      __The mutations C114 and C124 reduce (or make short-living), without abrogating the covalent association between TMX5 and ERp44. The EndoH experiment shown in Fig. 2B and the IF in Figs. 2D-2O fail to reveal significant differences showing that these reduced or more short living associations with ERp44 are sufficient to control TMX5 distribution. To strengthen our conclusion that ERp44 is involved in regulation of the intracellular TMX5 distribution, we have now added data in ERp44 cell (50% of TMX5 displays complex glycans as symptom of traffic to the medial Golgi compartment), back-transfection of ERp44 (but not of the ERp44C29S mutant that does not associate with TMX5) restores the complex glycan fraction to the level measured in wild type cells (Fig. 6). __

      Minor Points: 1. The position of the % endoH resistance in Figures 1B and 6B is not ideal, as it obstructs a visual inspection of TMX5 resistance to endoH.

      This has been modified, thank you.

      Reviewer #3 (Significance (Required)):

      Given that no information about TMX5 is currently available, the study provides critical first insight that should allow researchers to tackle the disease relevance of TMX5 in the future.

    1. Author response:

      Reviewer #1 (Public Review):

      In this manuscript, Yang et al. conduct a comprehensive investigation to demonstrate the role of adipose tissue Mir802 in obesity-associated inflammation and metabolic dysfunction. Using multiple models and techniques, they propose a mechanism where elevated levels of Mir802 in adipose tissue (both in mouse models and humans) trigger fat accumulation and inflammation, leading to increased adiposity and insulin resistance. They suggest that increased Mir802 levels in adipocytes during obesity result in the downregulation of TRAF3, a negative regulator of canonical and non-canonical NF-κB pathways. This downregulation induces inflammation through the production of cytokines/chemokines that attract and polarize macrophages. Concurrently, the NF-κB pathway induces the lipogenic transcriptional factor SREBP1, which promotes fat accumulation and further recruits pro-inflammatory macrophages. While the proposed model is supported by multiple experiments and consistent data, there are areas where the manuscript could be improved. Some improvements can be addressed in the text, while others require additional controls, experiments, or analyses.

      1) The manuscript should provide measurements of lipid droplet/adipocyte size for all models, both in vitro and in vivo. In vivo studies should also include fat weight measurements. This is crucial to determine whether Mir802, TRAF3, and SREBP1 promote adiposity/fat accumulation across all models.

      Thank you for your careful reviewing. As suggested, we have measured the size of lipid droplet and adipocyte (1J, 2A, S2I, 3F, 3L, S3L, 5I), this modification can make you and other readers understand our manuscript more clearly. In vivo studies have included fat weight measurements (Figure 2K, L; Figure 3C, D; Figure 5N). Our results determined that adipose-selective overexpression Mir802 induced adipogenesis during high fat diet induced.

      2) The rationale for co-culture experiments using WAT SVF is unclear, given that Mir802 is upregulated by obesity in adipocytes, not in the stromal-vascular fraction. These experiments would be more relevant if performed using isolated adipocytes or differentiated WAT SVF.

      Thank you for this important point. We are sorry for our inaccurate expression. In our study, we used differentiated WAT SVF to co-culture with primary macrophage, we illustrated it in the methods of Migration and invasion assays. We have revised it in the Flowchart of the co-culture experiments (Figure 4A). We hope that this modification will enhance readers' comprehension of our manuscript.

      3) Figures 1G and 1H lack a control group (time 0 or NCD). Without this control, it is impossible to determine if inflammation precedes Mir802 upregulation.

      Thank you for this insightful comment. In the previous study, we have tested the 0 weeks high fed diet treatment group of the Figures 1I and 1J, now we have added this data in the manuscript, we hope this modification can enhance our conclusion that inflammation precedes Mir802 upregulation.

      4) The statement, "The knockout of Mir802 in adipose tissue did not alter food intake, body weight, glucose level, and adiposity (data not shown)," needs more detail regarding the age and sex of the animals. These data are important and should be reported, perhaps in a supplementary figure.

      Thank you for your careful reviewing. To enhance our conclusions, we have added the data of food intake, body weight, glucose level, and adiposity about Mir802 KO mice treated with normal chow diet (NCD, Supplementary Figure 3E-I).

      ….The knockout of Mir802 in adipose tissue did not alter food intake, body weight, glucose levels, and adiposity compared with their WT littermates in both males and females when they were fed with NCD (Figure S3E-I)……

      5) The terms "KO" (knockout) and "KI" (knock-in) are misleading for AAV models, as they do not modify the genome. "KD" (knockdown) and "OE" (overexpression) are more accurate.

      Thank you for your good advice. We are sorry for our inaccurate expression. According to your advice, we have rewritten it. AAV models for Mir802 knockdown (Figure 3) and Traf3 overexpression (Figure 5) have changed to KD and OE respectively.

      6) The statement, "Mir802 expression was unaffected in other organs (Figure S3O)," should clarify that this is except for BAT.

      We appreciate the you for this insightful comment. We have clarified that Mir802 expression was unaffected in other organs except for BAT (Figure S3T, revised manuscript).

      By addressing these points, the manuscript would present a more robust and clear demonstration of the role of Mir802 in obesity-associated inflammation and metabolic dysfunction.

      Thanks for your positive comments. As suggested, we have modified all point.

      Reviewer #2 (Public Review):

      Yang et al. investigated the role of Mir802 in the development of adipose tissue (AT) inflammation during obesity. The authors found Mir802 levels are up-regulated in the AT of mouse models of obesity and insulin resistance as well as in the AT of humans. They further demonstrated that Mir802 regulates the intracellular levels of TRAF3 and downstream activation of the NF-kB pathway. Ultimately, controlling AT inflammation by manipulating Mir802 affected whole-body glucose homeostasis, highlighting the role of AT inflammatory status in whole-body metabolism. The study provides solid evidence on the role of adipocyte Mir802 in controlling inflammation and macrophage recruitment. However, how lipid mobilization from adipocytes and how engulfment of lipid droplets by macrophages control inflammatory phenotype in these cells could be better explored. The findings of this study will have a great impact in the field, contributing to the growing body of evidence on how microRNAs control the inflammatory microenvironment of AT and whole-body metabolism in obesity.

      Thanks for your positive comments.

      Reviewer #3 (Public Review):

      Mir802 appears to accumulate before macrophage numbers increase in adipose tissue in both mice and humans. The phenotype of Mir802 overexpression and deletion in vivo is sticking and novel. Deletion of Mir802 in adipose tissue after obesity onset also attenuated Adipose inflammation and improved systemic glucose homeostasis. Understanding how Mir802 affects the crosstalk between macrophage and adipocyte is a major point. For example, does Mir802 change the inflammatory of macrophages as it increases Traf3 expression in adipocytes? This is important because macrophages are the input if inflammatory mediators that will activate the TNFR receptor signaling pathway, potentially Traf3, resulting in impaired insulin stimulated Glut4 translocation and glucose uptake. Also, modulation of Mir802 levels in vivo leads to alterations in adiposity. Here, what is a direct effect of Mir802 and what is a result of simply reduced adiposity? One point that os ket is what triggers Mir802 expression, especially in obesity.

      Thanks for your important suggestions. According to your suggestions, we have addressed additional data in the revised manuscript to enhance our conclusion.

    1. Author response:

      The following is the authors’ response to the original reviews.

      We extend our sincere gratitude to the reviewers for their constructive feedback and valuable suggestions, which have significantly contributed to enhancing the quality of our work. In response to the comments, we have meticulously revised our manuscript with the following updates:

      (1) New Data Inclusion: We have incorporated new immunofluorescent staining images, FACS analysis of monocytes, and single-cell RNA sequencing (scRNAseq) expression analysis focusing on genes related to IFNGR, as well as T cell memory subsets (Trm, Tcm, and Tem).

      (2) Comparative Analysis: We have conducted a comparative analysis between the active vitiligo dFBs and the ACD pAd (r5) identified in our study, which provides further insight into the immune response mechanisms.

      (3) Discussion Expansion: We have expanded the discussion to include the role of tissue-resident memory (Trm) T cells in our model and have addressed the limitations of our animal model and in vitro studies.

      (4) Supplemental Material: As requested by the reviewers, we have provided four new supplemental tables (Table S2 ~ S5) and specific information for antibodies used in our study.

      Please see our Point-to-Point Responses to Reviewers' comments below:

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this manuscript, Liu et al. used scRNA-seq to characterize cell type-specific responses during allergic contact dermatitis (ACD) in a mouse model, specifically the hapten-induced DNFB model. Using the scRNA-seq data, they deconvolved the cell types responsible for the expression of major inflammatory cytokines such as IFNG (from CD4 and CD8 T cells), IL4/13 (from basophils), IL17A (from gd T cells), and IL1B from neutrophils and macrophages. They found the highest upregulation of a type 1 inflammatory response, centering around IFNG produced by CD4 and CD8 T cells. They further identified a subpopulation of dermal fibroblasts that upregulate CXCL9/10 during ACD and provided functional genetic evidence in their mouse model that disrupting IFNG signaling to fibroblasts decreases CD8 T cell infiltration and overall inflammation. They identify an increase in IFNG-expressing CD8 T cells in human patient samples of ACD vs. healthy control skin and co-localization of CD8 T cells with PDGFRA+ fibroblasts, which suggests this mechanism is relevant to human ACD. This mechanism is reminiscent of recent work (Xu et al., Nature 2022) showing that IFNG signaling in dermal fibroblasts upregulates CXCL9/10 to recruit CD8 T cells in a mouse model of vitiligo. Overall, this is a very wellpresented, clear, and comprehensive manuscript. The conclusions of the study are mostly well supported by data, but some aspects of the work could be improved by additional clarification of the identity of the cell types shown to be involved, including the exact subpopulation discovered by scRNA-seq and the subtype of CD8 T cell involved. The study was limited by its use of one ACD model (DNFB), which prevents an assessment of how broadly relevant this axis is. The human sample validation is slightly circumstantial and limited by the multiplexing capacity of immunofluorescence markers.

      Strengths:

      Through deep characterization of the in vivo ACD model, the authors were able to determine which cell types were expressing the major cytokines involved in ACD inflammation, such as IFNG, IL4/13, IL17A, and IL1B. These analyses are well-presented and thoughtful, showing first that the response is IFNG-dominant, then focusing on deeper characterization of lymphocytes, myeloid cells, and fibroblasts, which are also validated and complemented by FACS experiments using canonical markers of these cell types as well as IF staining. Crosstalk analyses from the scRNA-seq data led the authors to focus on IFNG signaling fibroblasts, and in vitro experiments demonstrate that CXCL9 and CXCL10 are expressed by fibroblasts stimulated by IFNG. In vivo functional genetic evidence demonstrates an important role for IFNG signaling in fibroblasts, as KO of Ifngr1 using Pdgfra-Cre Ifngr1 fl/fl mice, showed a reduction in inflammation and CD8 T cell recruitment.

      Weaknesses:

      (1) The use of one model limits an understanding of how broad this fibroblast-T cell axis is during ACD. However, the authors chose the most commonly employed model and cited additional work in a vitiligo model (another type 1 immune response).

      We thanks the reviewer for pointing out this limitation. Although the DNFB-elicited ACD model is the most commonly used animal model for ACD, our study is limited by the use of only one type 1 immune response model. We have now added new data (Figure 5-figure supplement 1A) showing that the active ACD pAd (r5) and the active IFNγ-responsive vitiligo dFBs (Xu et al., 2022) are enriched with a highly similar panel of IFNγ-inducible genes. Future studies are still needed to determine whether this fibroblast-T cell axis may be broadly applied to other ACD models or to other type-1 immune response-related inflammatory skin diseases.

      (2) The identity of the involved fibroblasts and T cells in the mouse model is difficult to assess as scRNA-seq identified subpopulations of these cell types, but most work in the Pdgfra-Cre Ifngr1 fl/fl mice used broad markers for these cell types as opposed to matched subpopulation markers from their scRNA-seq data.

      Thanks for the reviewer's constructive comments. To better showcase the dWAT layer where PDGFRA+ pAds are enriched, we have included new histological staining and PLIN1 (adipocyte marker) in new Figure 4 - figure supplement 1F-G. As shown in Figure 4 - figure supplement 1G, the PLIN1+ dWAT layer is located in the lower dermis right above the cartilage layer.  In Figure 4-figure supplement 1I and J, we have shown that phosphor-STAT1 (pSTAT1), a key signaling molecule activated by IFNγ, was detected primarily in PDGFRA+Ly6A+ pAds in the lower dermis where dWAT is located. In addition, we have now included new data showing that the pAd (dFB_r5) cluster preferentially expressed the highest levels of both Ifngr1 and Ifngfr2 among all dFB subclusters (new Figure 5 - figure supplement 1B). Furthermore, we have included new co-staining data showing that CXCL9 largely co-localized with ICAM1(new Figure 4 - figure supplement 1K), a marker for committed pAds (Merrick et al., 2019), in the reticular dermis and dWAT region of the ACD skin, further confirming that CXCL9 is specifically induced in the pAd subset of dFBs. Additionally, we included new staining data showing that ACD-mediated induction of CXCL9 in ICAM1+ dFBs were largely suppressed upon targeted deletion of Ifngr1 in Pdgfra+ dFBs (new Figure 6 - figure supplement 1D-E).

      (3) Human patient samples of ACD were co-stained with two markers at a time, demonstrating the presence of CD8+IFNG+ T cells, PDGFRA+CXCL10+ fibroblasts, and co-localization of PDGFRA+ fibroblasts and CD8+ T cells. However, no IF staining demonstrates co-expression of all 4 markers at once; thus, the human validation of co-localization of CD8+IFNG+ T cells and PDGFRA+CXCL10+ fibroblasts is ultimately indirect, although not a huge leap of faith. Although n=3 samples of healthy control and ACD samples are used, there is no quantification of any results to demonstrate the robustness of differences.

      Thanks for the reviewer’s constructive comments. We have shown that PDGFRA colocalizes with CXCL10, in the dermal micro-vascular structures, where CD8+ T cells infiltrate around PDGFRA+ dFBs. We are sorry that due to technical issues (antibody compatibility), we cannot provide the four color co-staining as suggested by the reviewers. In order to demonstrate the robustness and reproducibility of the staining presented, we have now supplemented 4 independent images for both Fig. 7A and Fig. 7E in the updated Figure 7-figure supplement 1A-B.

      Reviewer #2 (Public Review):

      Summary:

      The investigators apply scRNA seq and bioinformatics to identify biomarkers associated with DNFB-induced contact dermatitis in mice. The bioinformatics component of the study appears reasonable and may provide new insights regarding TH1-driven immune reactions in ACD in mice. However, the IF data and images of tissue sections are not clear and should be improved to validate the model.

      Strengths:

      The bioinformatics analysis.

      Weaknesses:

      The IF data presented in 4H, 6H, 7E and 7F are not convincing and need to be correlated with routine staining on histology and different IF markers for PDGFR. Some of the IF staining data demonstrates a pattern inconsistent with its target.

      We are sorry for the confusion, because 4H and 6H are staining on mouse skin sections, and 7E and 7F are staining on human skin sections, therefore the patterns of PDGFRA+ dFBs appeared inconsistent between species. As shown in Fig. 4H, in mouse skin, PDGFRA+CXCL9/10+ dFBs are located between the lower reticular dermis and dWAT region, where preadipocytes are located (Sun et al., 2023). To better showcase the dWAT layer where PDGFRA+ pAds are enriched, we have included new histological staining and PLIN1 (adipocyte marker) in new Figure 4 - figure supplement 1F-G. As shown in Figure 4 - figure supplement 1G, the PLIN1+ dWAT layer is located in the lower dermis right above the cartilage layer. Furthermore, we have included new co-staining data showing that CXCL9 largely co-localized with ICAM1(new Figure 4 - figure supplement 1K), a marker for committed pAds (Merrick et al., 2019), in the reticular dermis and dWAT region of the ACD skin, further confirming that CXCL9 is specifically induced in the pAd subset of dFBs.   

      As shown in Fig. 7E, in human skin, PDGFRA+CXCL10+ dFBs are located within the microvascular structures located at the dermal-epidermal junction (DEJ) region, where mesenchymal stem cells are enriched (Russell-Goldman & Murphy, 2020). We have included the corresponding HE histological staining image for Fig. 4H in new Figure 4-supplement 1F. Histological staining for Fig. 6H is the HE staining image in Fig. 6F. The histological staining for Fig. 7E and 7F is shown by Masson’s trichrome staining shown in Fig. 7C (a three-colour histological staining).

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Major comments:

      (1) While the focus on fibroblast and T cell interactions and overall biological findings regarding these interactions (IFNG - CXCL9/10 - CXCR3) is sound, it is slightly confusing about which exact subpopulations of these cells are involved in ACD pathogenesis as both scRNA-seq and IF are used but very broad markers are used for IF. Regarding fibroblasts, the scRNA-seq identifies the pAd (r5) cluster of fibroblasts as the main producer of CXCL9/10. However, the expression of IFNGR1 was not shown for this subpopulation as well as for other fibroblast subpopulations. Figure 6C shows IFNGR1 staining in the Ifngr1 fl/fl control mice which appears quite broad. With the seemingly broad expression of IFNGR1, why is it that only a subpopulation of fibroblasts upregulate CXCL9/10? Is there a specific location of these pAd fibroblasts that help drive this IFNG response? Please show the expression of Ifngr1 in the fibroblast scRNA-seq data.

      Thanks for the reviewer’s constructive comments. We have now included new data showing that the pAd (dFB_r5) cluster preferentially expressed higher levels of both Ifngr1 and Ifngfr2 among all dFB subclusters (new Figure 5 - figure supplement 1B). In addition, we included new co-staining data showing that CXCL9 largely co-localized with ICAM1, a marker for committed pAds (Merrick et al., 2019), in the reticular dermis and dWAT region of the ACD skin, further confirming that CXCL9 is specifically induced in the pAd subset of dFBs.

      (2) Regarding T cells, it is slightly confusing regarding what role the fibroblast-produced CXCL9/10 plays on T cell migration vs. activation. This is mainly because in vitro work focuses on T cell activation, while in vivo work seems to mainly assess T cell migration into the tissue. The in vivo studies have nicely shown that CD8 T cells are the main cell type affected by Ifngr1 iKO (i.e., a reduction of these cells), but T cell activity in vivo is not assessed (in the form of IFNG production). I have the following related questions:

      a. Authors do not discuss whether T cells involved in ACD in their model are tissue-resident memory T cells (Trm) or whether these are recruited from circulation. This may be possible to assess via additional analysis of the scRNA-seq data (looking for expression of Trm markers). 

      Thanks for the reviewer’s constructive comments. We have now included new data showing the expression of marker genes of various memory T cells in various T cell subclusters (new Figure 2 - figure supplement 1C-D). Antigen-specific CD8 or CD4 memory T cells can be classified into CD62hi/CCR7hi/CD28hi/CD27hi/CX3CR1lo central memory T cells (Tcm), CX3CR1hi/Cd28hi/Cd27lo/CD62lo/CCR7lo effector memory T cells (Tem), and CD49ahi/CD103hi/ CD69hi/BLIMP1hi tissue-resident memory T cells (Trm) (Benichou, Gonzalez, Marino, Ayasoufi, & Valujskikh, 2017; Cheon, Son, & Sun, 2023; Mackay et al., 2013; Martin & Badovinac, 2018; Park et al., 2023). We observed that in ACD skin, CD4+ and CD8+ T cells predominantly expressed marker genes associated with Tcm including Cd28, Cd27, Ccr7, and S1pr1/Cd62l. In contrast, marker genes associated with Tem (Cx3cr1) and Trm (Itga1/Cd49a, Itgae/Cd103, Cd69 and Prdm1/Blimp1, Cd127/Il7r) were only scarcely expressed in these αβ T cells, suggesting that ACD predominantly triggers a central memory T cell response in the skin.

      Furthermore, this hypothesis is supported by new lymph node gene expression results. We showed that the expression of Ifng, but not Il4 or Il17a, was rapidly induced in skin draining lymph nodes at 24 hours after ACD elicitation (new Figure 1-figure supplement 1H). This suggests a robust and systemic activation of type 1 memory T cell response in the early stage of ACD, and the migration of these lymphatic memory T cells to the skin may contribute to the exacerbation of skin inflammation.

      b. Authors have focused on CXCR3 axis involvement in IFNG production (Figures 5G-H) without assessing the presumed migratory role of this axis. Presumably, CD8 T cells are recruited to the skin via the CXCL9/10-CXCR3 axis, but this would be important to clarify given other work that has demonstrated Trm involvement in ACD. Authors should at least discuss how their model and findings support, refine, or even contradict the current paradigm of Trm involvement in ACD (Lefevre et al., 2021; PMID: 34155157).

      We are grateful for the constructive feedback provided by the reviewer. CXCR3 is a chemokine receptor on T cells and not only plays a pivotal role in the trafficking of type 1 T cells, but also is required for optimal generation of IFNG-secreting type 1 T cells in vivo (Groom et al., 2012). Our in vitro study is limited by only focusing on CXCL9/10-CXCR3 axis involvement in IFNγ production without studying its role in driving T cell migration. We have now addressed this limitation in the discussion section.

      In the murine model of ACD, the initial sensitization phase involves exposing mouse skin to a high dose of DNFB to prime effector T cells in lymphoid organs, and this is followed by a later challenge/elicitation phase, during which the mice are re-exposed to a lower dose of DNFB in a different area of the skin, distal from the original sensitization site (Manresa, 2021; Vocanson, Hennino, Rozieres, Poyet, & Nicolas, 2009). Our updated analysis of the expression of marker genes associated with central memory T cells (Tcm), effector memory T cells (Tem), and tissue-resident memory T cells (Trm), as presented in the revised Figure 2-figure supplement 1C-D, indicates that indicate that the type-1 inflammation observed upon ACD elicitation is predominantly driven by memory T cells recruited from lymphoid organs, rather than by skin resident memory T cells. We have read the reference provided by the reviewer along with a few other related studies indicating that Trm is involved in ACD. We found that these studies performed the elicitation phase on the same skin area where the initial sensitization is conducted, and only when it results in a rapid allergen-induced skin inflammatory response, that is primarily mediated by IL17A-producing and IFNγ-producing CD8+ skin resident memory T cells (Gadsboll et al., 2020; Murata & Hayashi, 2020; Schmidt et al., 2017; Wongchang et al., 2023). These studies suggest that Trm cells establish a long-lasting local memory during the initial sensitization, and upon re-exposure to the hapten in the same skin area, these site-specific Trm cells can rapidly contribute to a robust type-1 skin inflammatory response. Therefore, a robust involvement of Trm in ACD requires a repeated exposure of the same hapten to the same skin area. We have now added related discussion in the discussion section.

      c. While it may be difficult to assess given reduced numbers of CD8 T cells in the Ifngr1 iKO, is the CXCL9/10-CXCR3 axis affecting IFNG production by T cells in vivo?

      Yes, we have shown in Fig. 6G that ACD-mediated induction of Ifng was significantly suppressed in the Ifngr1-iKO mice compared to the control mice.

      (3) The authors cite prior work (Xu et al. Nature 2022) that demonstrated a similar mechanism for fibroblasts in recruiting vitiligo-inducing T cells. Are the pAd (r5) cluster of fibroblasts similar to the fibroblast subpopulation that drives vitiligo?

      The study on mouse model of vitiligo (Xu et al. Nature 2022) did not perform single-cell RNAseq of the vitiligo mouse skin. Instead, they conducted RNAseq analysis on the sorted PDGFRA+ dFBs. Therefore, we cannot directly compare our pAd (r5) cluster with the fibroblast subpopulation that drives vitiligo. Nevertheless, by utilizing a Venn diagram to compare the top 100 lFNγ signaling dependent genes upregulated in the active vitiligo mouse dFBs and the top 100 genes enriched in our ACD pAd (dFB_r5) cells, we identified 29 commonly upregulated genes between the two conditions (Figure 5-figure supplement 1A). Furthermore, all these 29 genes were among the top IFNγ-inducible genes in primary dFBs. These shared genes include CXCL9, CXCL10, and several other downstream targets of IFNγ signaling, such as B2M, BST2, CD274, as well as the GBP family members GBP3, GBP4, GBP5, GBP7, and additional genes like H2-K1, H2-Q4, H2-Q7, H2-T23, IFIT3, ISG15, and STAT1. This result suggests that the pAd (dFB_r5) cells possess a common IFNγ-pathway gene signature with the active vitiligo mouse dFBs, indicating a potential overlap in molecular pathways.

      (4) The authors should include bulk RNA-seq data from fibroblast stimulation (Figure 5b) at a minimum in the GEO submission. They should ideally include the differentially expressed genes in a supplementary table.

      Thanks for the reviewer’s constructive comments. We have now included the raw FPKM file for the bulk RNAseq data shown in Fig. 5 in Supplemental Table S3, and the list for differentially expressed genes in Supplemental Table S4.

      (5) The authors state that human sample stainings were n = 3 per group for healthy control and ACD (Figure 7), but no quantification or statistical testing is provided to demonstrate significant differences in findings such as co-localization of fibroblasts and T cells, IFNG+CD8+ T cells, etc.

      Thanks for the reviewer’s constructive comments. We have now supplemented 4 independent images for both Fig. 7A and Fig. 7E in the new Figure 7-figure supplement 1A-B to demonstrate the robustness and reproducibility of the staining presented.

      Minor comments:

      (1) Figure 1G, possible typos, Il14 and Il11b are on the violin plots when I believe authors meant Il4 and Il1b.

      Thank a lot for pointing out these typos. We have now made the correction in the updated manuscript figure 1.

      (2) The authors label cluster 27 as neutrophils based on the expression of Ly6g and S100a8. These markers are also expressed by Cd14+ inflammatory monocytes. I believe the authors need to additionally validate that these cells are neutrophils (via staining or additional analyses). Neutrophils are notoriously difficult to capture in scRNA-seq given low RNA content. Later, they are quantified by FACS using CD11b+Ly6G+ markers, but I do not believe this would distinguish them from CD14+ monocytes. As this is a relatively minor aspect of the manuscript, I consider this a minor concern, but a finding that should be as accurate as possible as Il1b is likely important, and identifying its accurate source likewise.

      Thanks a lot for reviewer’s constructive comments. According to the reviewer’s suggestion, we have now added Cd14 expression in Figure 1C, and found that indeed cluster 27 express not only expressed Ly6G but also expressed Cd14. Based on literatures, the expression of Ly6G in circulating blood, spleen, and peripheral tissues is limited to neutrophils, whereas monocytes, macrophages, and lymphocytes are negative of Ly6G (Ikeda et al., 2023; Lee, Wang, Parisini, Dascher, & Nigrovic, 2013). Therefore, Ly6G can be used as a marker to distinguish neutrophils and monocytes. Although CD14 is highly expressed in monocytes, neutrophils can also express CD14 at lower level (Antal-Szalmas, Strijp, Weersink, Verhoef, & Van Kessel, 1997). Therefore, the cluster 27 is likely a mixed population of neutrophils and monocytes. So we have changed the definition of this cluster as NEU/Mon in the updated manuscript.

      To confirm the presence of neutrophils and monocytes in ACD, we have included new FACS analysis of inflammatory monocytes, which are gated as CD11B+Ly6G-F4/80-CD11C-Ly6Chi, according to published FACS protocol(Rose, Misharin, & Perlman, 2012). We found that elicitation of ACD led to a transient influx of monocytes at 24 hrs post treatment, whereas the percentage of neutrophils continued to increase by 60 hours post-treatment (Figure 3L, and Figure 3-figure supplement 1G). In addition, at 60 hrs, the percentage of neutrophils (~5%) was > 10 times greater than the percentage of monocytes (~0.4%), indicating that neutrophils are the dominant granulocytes at 60 hours post ACD elicitation.

      (3) The authors should include a cluster marker table as a supplementary file to accompany Figure 1C. Only top cluster markers are shown in 1C.

      Thanks a lot for reviewer’s constructive comments. We have now included the top 5 enriched genes in each cell clusters shown in Fig. 1C in supplementary Table S2.

      (4) Figures 2A/B have mismatched labels. There is a gdT/ILC2 label in the 2B, but not in 2A. Please match these. Along these lines, which gdT cluster is the IL17A expressing cluster as shown in 1D? Matching these labels will clarify which population is doing what.

      Thanks a lot for reviewer to point out this mistake. To avoid confusion about the T cell clusters, we have added a specific recluster# for the T cell clusters as r0~r7 (Figure 2A-B). The r4 cluster is a mixed population of δγT and ILC2, therefore termed as δγT/ILC2. As shown in Figure 2-figure supplement 1E, IL17A is primarily expressed in the δγT cell (r5). We have now corrected δγT2 to δγT/ILC2 throughout the manuscript. To avoid confusion, we have now added cluster # in updated Figure 2D.

      (5) In Figure 3E, the authors used CD11B as a distinguishing marker for basophils (CD11B+) vs. mast cells (CD11B-). Mcpt8 is a better distinguishing marker, so I am wondering why the authors chose CD11B.

      Thanks a lot for reviewer’s comments. In scRNAseq, we did use Mcpt8 as a basophil specific marker to distinguish basophils and mast cells (see Figure 1C). However, Mcpt8 is not a surface receptor that can be used in FACS analysis. Therefore, to distinguish basophils from mast cells by FACS, we have to choose surface markers expressed on these cells. FcεR1a is a highly specific markers expressed exclusively on basophils and mast cells, and CD11B is expressed on basophils but not in mature mast cells (Hamey et al., 2021). As a result, FACS analysis of the surface expression of CD11B and FceR1a can distinguish basophils (CD11B+ FcεR1a+) from mast cells (CD11B- FcεR1a+). The use of CD11B and FcεR1a to distinguish basophils and mast cells can also been see in a published reference study (Arinobu et al., 2005).

      (6) Antibody information is missing for IF studies. No clones, catalog numbers, vendors, RRIDs, or dilutions are included in the Methods section for any of the IF data.

      Thanks a lot for reviewer’s constructive comments. We have now added related information for all the antibodies we used for FACS or IF data in the method section.

      (7) Figure 3 supplement E and F appear to be reversed based on legend descriptions.

      Thank a lot for pointing this out. We have now made the correction in the updated Supplementary file.

      References:

      Antal-Szalmas, P., Strijp, J. A., Weersink, A. J., Verhoef, J., & Van Kessel, K. P. (1997). Quantitation of surface CD14 on human monocytes and neutrophils. J Leukoc Biol, 61(6), 721-728. doi:10.1002/jlb.61.6.721

      Arinobu, Y., Iwasaki, H., Gurish, M. F., Mizuno, S., Shigematsu, H., Ozawa, H., . . . Akashi, K. (2005). Developmental checkpoints of the basophil/mast cell lineages in adult murine hematopoiesis. Proc Natl Acad Sci U S A, 102(50), 18105-18110. doi:10.1073/pnas.0509148102

      Benichou, G., Gonzalez, B., Marino, J., Ayasoufi, K., & Valujskikh, A. (2017). Role of Memory T Cells in Allograft Rejection and Tolerance. Front Immunol, 8, 170. doi:10.3389/fimmu.2017.00170

      Cheon, I. S., Son, Y. M., & Sun, J. (2023). Tissue-resident memory T cells and lung immunopathology. Immunol Rev, 316(1), 63-83. doi:10.1111/imr.13201

      Gadsboll, A. O., Jee, M. H., Funch, A. B., Alhede, M., Mraz, V., Weber, J. F., . . . Bonefeld, C. M. (2020). Pathogenic CD8(+) Epidermis-Resident Memory T Cells Displace Dendritic Epidermal T Cells in Allergic Dermatitis. J Invest Dermatol, 140(4), 806-815 e805. doi:10.1016/j.jid.2019.07.722

      Groom, J. R., Richmond, J., Murooka, T. T., Sorensen, E. W., Sung, J. H., Bankert, K., . . . Luster, A. D. (2012). CXCR3 chemokine receptor-ligand interactions in the lymph node optimize CD4+ T helper 1 cell differentiation. Immunity, 37(6), 1091-1103. doi:10.1016/j.immuni.2012.08.016

      Hamey, F. K., Lau, W. W. Y., Kucinski, I., Wang, X., Diamanti, E., Wilson, N. K., . . . Dahlin, J. S. (2021). Single-cell molecular profiling provides a high-resolution map of basophil and mast cell development. Allergy, 76(6), 1731-1742. doi:10.1111/all.14633

      Ikeda, N., Kubota, H., Suzuki, R., Morita, M., Yoshimura, A., Osada, Y., . . . Asano, K. (2023). The early neutrophil-committed progenitors aberrantly differentiate into immunoregulatory monocytes during emergency myelopoiesis. Cell Rep, 42(3), 112165. doi:10.1016/j.celrep.2023.112165

      Lee, P. Y., Wang, J. X., Parisini, E., Dascher, C. C., & Nigrovic, P. A. (2013). Ly6 family proteins in neutrophil biology. J Leukoc Biol, 94(4), 585-594. doi:10.1189/jlb.0113014

      Mackay, L. K., Rahimpour, A., Ma, J. Z., Collins, N., Stock, A. T., Hafon, M. L., . . . Gebhardt, T. (2013). The developmental pathway for CD103(+)CD8+ tissue-resident memory T cells of skin. Nat Immunol, 14(12), 1294-1301. doi:10.1038/ni.2744

      Manresa, M. C. (2021). Animal Models of Contact Dermatitis: 2,4-Dinitrofluorobenzene-Induced Contact Hypersensitivity. Methods Mol Biol, 2223, 87-100. doi:10.1007/978-1-0716-1001-5_7

      Martin, M. D., & Badovinac, V. P. (2018). Defining Memory CD8 T Cell. Front Immunol, 9, 2692. doi:10.3389/fimmu.2018.02692

      Merrick, D., Sakers, A., Irgebay, Z., Okada, C., Calvert, C., Morley, M. P., . . . Seale, P. (2019). Identification of a mesenchymal progenitor cell hierarchy in adipose tissue. Science, 364(6438). doi:10.1126/science.aav2501

      Murata, A., & Hayashi, S. I. (2020). CD4(+) Resident Memory T Cells Mediate Long-Term Local Skin Immune Memory of Contact Hypersensitivity in BALB/c Mice. Front Immunol, 11, 775. doi:10.3389/fimmu.2020.00775

      Park, S. L., Christo, S. N., Wells, A. C., Gandolfo, L. C., Zaid, A., Alexandre, Y. O., . . . Mackay, L. K. (2023). Divergent molecular networks program functionally distinct CD8(+) skin-resident memory T cells. Science, 382(6674), 1073-1079. doi:10.1126/science.adi8885

      Rose, S., Misharin, A., & Perlman, H. (2012). A novel Ly6C/Ly6G-based strategy to analyze the mouse splenic myeloid compartment. Cytometry A, 81(4), 343-350. doi:10.1002/cyto.a.22012

      Russell-Goldman, E., & Murphy, G. F. (2020). The Pathobiology of Skin Aging: New Insights into an Old Dilemma. Am J Pathol, 190(7), 1356-1369. doi:10.1016/j.ajpath.2020.03.007

      Schmidt, J. D., Ahlstrom, M. G., Johansen, J. D., Dyring-Andersen, B., Agerbeck, C., Nielsen, M. M., . . . Bonefeld, C. M. (2017). Rapid allergen-induced interleukin-17 and interferon-gamma secretion by skin-resident memory CD8(+) T cells. Contact Dermatitis, 76(4), 218-227. doi:10.1111/cod.12715

      Sun, L., Zhang, X., Wu, S., Liu, Y., Guerrero-Juarez, C. F., Liu, W., . . . Zhang, L. J. (2023). Dynamic interplay between IL-1 and WNT pathways in regulating dermal adipocyte lineage cells during skin development and wound regeneration. Cell Rep, 42(6), 112647. doi:10.1016/j.celrep.2023.112647

      Vocanson, M., Hennino, A., Rozieres, A., Poyet, G., & Nicolas, J. F. (2009). Effector and regulatory mechanisms in allergic contact dermatitis. Allergy, 64(12), 1699-1714. doi:10.1111/j.1398-9995.2009.02082.x

      Wongchang, T., Pluangnooch, P., Hongeng, S., Wongkajornsilp, A., Thumkeo, D., & Soontrapa, K. (2023). Inhibition of DYRK1B suppresses inflammation in allergic contact dermatitis model and Th1/Th17 immune response. Sci Rep, 13(1), 7058. doi:10.1038/s41598-023-34211-x

      Xu, Z., Chen, D., Hu, Y., Jiang, K., Huang, H., Du, Y., . . . Chen, T. (2022). Anatomically distinct fibroblast subsets determine skin autoimmune patterns. Nature, 601(7891), 118-124. doi:10.1038/s41586-021-04221-8

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      As adult-born granule neurons have been shown to play diverse roles, both positive and negative, to modulate hippocampal circuitry and function in epilepsy, understanding the mechanisms by which altered neurogenesis contributes to seizures is important for future therapeutic strategies. The work by Jain et al. demonstrates that increasing adult neurogenesis before status epilepticus (SE) leads to a suppression of chronic seizures in the pilocarpine model of temporal lobe epilepsy. This work is potentially interesting because previous studies showed suppressing neurogenesis led to reduced chronic seizures.

      To increase neurogenesis, the authors conditionally delete the pro-apoptotic gene Bax using a tamoxifen-inducible Nestin-CreERT2 which has been previously published to increase proliferation and survival of adult-born neurons by Sahay et al. After 6 weeks of tamoxifen injection, the authors subjected male and female mice to pilocarpine-induced SE. In the first study, at 2 hours after pilocarpine, the authors examine latency to the first seizure, severity and total number of acute seizures, and power during SE. In the second study in a separate group of mice, at 3 weeks after pilocarpine, the authors examine chronic seizure number and frequency, seizure duration, postictal depression, and seizure distribution/cluster seizures. Overall, the study concludes that increasing adult neurogenesis in the normal adult brain can reduce epilepsy in females specifically. However, important BrdU birthdating experiments in both male and female mice need to be included to support the conclusions made by the authors. Furthermore, speculative mechanisms lacking direct evidence reduce enthusiasm for the findings.

      There are two suggestions. First, BrdU birthdating of newborn neurons is important to add to the paper so that there is support for the conclusions. Second, speculative text reduced enthusiasm. In response, we clarified the conclusions. We do not think that the clarified conclusions require BrdU birthdating (discussed further below). We also removed two schematics (and associated text) that we think the reviewer was referring to when speculation was mentioned.

      We also want to point out something minor -that the times of injections listed above are not correct.

      a. Seizures were not measured 2 hrs after pilocarpine; that is when the anticonvulsant diazepam was administered to males. 

      b. Seizures were not measured 3 weeks after pilocarpine; the duration of recording was 3 weeks.  

      (1) BrdU birthdating is required for conclusions.

      We think that the Reviewer was suggesting birthdating because we were not clear about our conclusions, and we apologize for the confusion. The Reviewer stated that we concluded: “conditionally deleting Bax in Nestin-Cre+ cells leads to increased neurogenesis and hilar ectopic granule cells, thereby reducing chronic seizures.”  (Note this is a quote from the review).

      However, we did not intend to conclude that. We intended to conclude that conditionally deleting Bax in Nestin-Cre+ mice reduced chronic seizures in the mouse model of epilepsy that we used. Also, that conclusion only pertained to females. Please note we did not conclude that hilar ectopic granule cells led to reduced seizures. We also concluded that Bax deletion increased neurogenesis in female mice. We have revised the text to make the conclusions clear.

      Abstract, starting on line 67:

      The results suggest that selective Bax deletion to increase adult neurogenesis can reduce experimental epilepsy, and the effect shows a striking sex difference.

      Results, starting on line 448:

      Because Cre+ epileptic females had increased numbers of immature neurons relative to Cre- females at the time of SE, and prior studies show that Cre+ females had less neuronal damage after SE (Jain et al., 2019), female Cre+ mice might have had reduced chronic seizures because of high numbers of immature neurons. However, the data do not prove a causal role.

      Starting on line 477:

      ...we hypothesized that female Cre+ mice would have fewer hilar ectopic GCs than female Cre- mice. However, that female Cre+ mice did not have fewer hilar ectopic GCs.

      Discussion, starting on line 563:

      The chronic seizures, measured 4-7 weeks after pilocarpine, were reduced in frequency by about 50% in females. Therefore, increasing young adult-born neurons before the epileptogenic insult can protect against epilepsy. However, we do not know if the protective effect was due to the greater number of new neurons before SE or other effects. Past data would suggest that increased numbers of newborn neurons before SE leads to a reduced SE duration and less neuronal damage in the days after SE. That would be likely to lessen the epilepsy after SE. However, there may have been additional effects of larger numbers of newborn neurons prior to SE.

      Conclusions, starting on line 745:

      In the past, suppressing adult neurogenesis before SE was followed by fewer hilar ectopic GCs and reduced chronic seizures. Here, we show that the opposite - enhancing adult neurogenesis before SE and increased hilar ectopic GCs - do not necessarily reduce seizures. We suggest instead that protection of the hilar neurons from SE-induced excitotoxicity was critical to reducing seizures. The reason for the suggestion is that the survival of hilar neurons would lead to persistence of the normal inhibitory functions of hilar neurons, protecting against seizures. However, this is only a suggestion at the present time because we do not have data to prove it. Additionally, because protection was in females, sex differences are likely to have played an important role. Regardless, the results show that enhancing neurogenesis of young adult-born neurons in Nestin-Cre+ mice had a striking effect in the pilocarpine model, reducing chronic seizures in female mice.

      The Reviewer is correct that it would be interesting to know when the increase in adult neurogenesis occurred that was critical to the effect. For example, was it the initial increase following Bax deletion but before pilocarpine-induced SE, or the increase in neurogenesis following SE, or increased adult neurogenesis in the chronic stage of epilepsy. It also might be that related aspects of neurogenesis played a role such as the degree that maturation was normal in adult-born neurons. We have not pursued the experiments to identify these aspects of neurogenesis because of how much work it would entail. Also, approaches to conclude cause-effect relationships are going to be difficult. 

      (2) Speculation.

      We removed the text and supplemental figures with schematics that we think were the overly speculative parts of the paper the Reviewer mentioned.

      Strengths:

      (1) The study is sex-matched and reveals differences in response to increasing adult neurogenesis in chronic seizures between males and females.

      (2) The EEG recording parameters are stringent, and the analysis of chronic seizures is comprehensive. In two separate experiments, the electrodes were implanted to record EEG from the cortex as well as the hippocampus. The recording was done for 10 hours post pilocarpine to analyze acute seizures, and for 3 weeks continuous video EEG recording was done to analyze chronic seizures.

      Weaknesses:

      (1) Cells generated during acute seizures have different properties to cells generated in chronic seizures. In this study, the authors employ two bouts of neurogenesis stimuli (Bax deletion dependent and SE dependent), with two phases of epilepsy (acute and chronic). There are multiple confounding variables to effectively conclude that conditionally deleting Bax in Nestin-Cre+ cells leads to increased neurogenesis and hilar ectopic granule cells, thereby reducing chronic seizures.

      As mentioned above, with a clarification of our conclusions we think we have addressed the concern. We believe that we conditionally deleted Bax in Nestin-expressing cells. We believe we found that female mice had reduced loss of hilar mossy cells and somatostatin-expressing neurons after SE, and fewer chronic seizures after SE. While it makes sense that increased neurogenesis caused the reduced seizures, we acknowledge it was not proved.

      We do not make conclusions about the role of hilar ectopic granule cells. However, we note that they appear to have been similar in number across groups, which suggests they played no role in the results. This is very surprising and therefore adds novelty.

      (2) Related to this is the degree of neurogenesis between Cre+ and Cre- mice and the nature of the sex differences. It is crucial to know the rate/fold change of increased neurogenesis before pilocarpine treatment and whether it is different between male and female mice.

      We agree that if sex differences in adult neurogenesis could be shown by a sex difference in rate, fold change, maturation, and other characteristics.  However, sex differences can also be shown by a change in doublecortin (DCX), which is what we did. We respectfully submit that we do not see an exhaustive study is critical.

      As a result, we have clarified DCX was studied either before SE or in the period of chronic seizures:

      Results, starting on line 406:

      III. Before and after epileptogenesis, Cre+ female mice exhibited more immature neurons than Cre- female mice but that was not true for male mice.

      Starting on line 446:

      Therefore, elevated DCX occurred after chronic seizures had developed in Cre+ mice but the effect was limited to females.

      Discussion, starting on line 592:

      This study showed that conditional deletion of Bax from Nestin-expressing progenitors increased young adult-born neurons in the DG when studied 6 weeks after deletion and using DCX as a marker of immature neurons.

      (3) The authors observe more hilar Prox1 cells in Cre+ mice compared to Cre- mice. The authors should confirm the source of the hilar Prox1+ cells.

      This is an excellent question but it is unclear that it is critical to the seizures since both sexes showed more hilar Prox1 cells in Cre+ mice but only the females had fewer seizures than Cre- mice. This is the additional text to describe the results (starting on Line 493):

      In past studies, hilar ectopic GCs have been suggested to promote seizures (Scharfman et al., 2000; Jung et al., 2006; Cho et al., 2015). Therefore, we asked if the numbers of hilar ectopic GCs correlated with the numbers of chronic seizures. When Cre- and Cre+ mice were compared (both sexes pooled), there was a correlation with numbers of chronic seizures (Fig. 6D1) but it suggested that more hilar ectopic GCs improved rather than worsened seizures. However, the correlation was only in Cre- mice, and when sexes were separated there was no correlation (Fig. 6D3).

      When seizure-free interval was examined with sexes pooled, there was a correlation for Cre+ mice (Fig. 6D2) but not Cre- mice. Strangely, the correlations of Cre+ mice with seizure-free interval (Fig. 6D2, D4) suggest ectopic GCs shorten the seizure-free interval and therefore worsen epilepsy, opposite of the correlative data for numbers of chronic seizures. In light of these inconsistent results it seems that hilar ectopic granule cells had no consistent effect on chronic seizures.

      (4) The biggest weakness is the lack of mechanism. The authors postulate a hypothetical mechanism to reconcile how increasing and decreasing adult-born neurons in GCL and hilus and loss of hilar mossy and SOM cells would lead to opposite effects - more or fewer seizures. The authors suggest the reason could be due to rewiring or no rewiring of hilar ectopic GCs, respectively, but do not provide clear-cut evidence.

      As we mention above, we removed the supplemental figures with schematics because they probably were what seemed overly speculative.

      We acknowledge that mechanism is not proven by our study. However, we would like to mention that in our view, showing preservation of hilar mossy cells and SOM cells, but not PV cells, does add mechanistic data to the paper. We understand more experiments are necessary.

      Reviewer #2 (Public Review):

      Summary:

      In this manuscript, Jain et al explore whether increasing adult neurogenesis is protective against status epilepticus (SE) and the development of spontaneous recurrent seizures (chronic epilepsy) in a mouse pilocarpine model of TLE. The authors increase adult neurogenesis via conditional deletion of Bax, a pro-apoptotic gene, in Nestin-CreERT2Baxfl/fl mice. Cre- littermates are used as controls for comparisons. In addition to characterizing seizure phenotypes, the authors also compare the abundance of hilar ectopic granule cells, mossy cells, hilar SOM interneurons, and the degree of neuronal damage between mice with increased neurogenesis (Cre+) vs Cre- controls. The authors find less severe SE and a reduction in chronic seizures in female mice with pre-insult increased adult-born neurons. Immunolabeling experiments show these females also have preservation of hilar mossy cells and somatostatin interneurons, suggesting the pre-insult increase in adult neurogenesis is protective.

      Strengths:

      (1) The finding that female mice with increased neurogenesis at the time of pilocarpine exposure have fewer seizures despite having increased hilar ectopic granule cells is very interesting.

      (2) The work builds nicely on the group's prior studies.

      (3) Apparent sex differences are a potentially important finding.

      (4) The immunohistochemistry data are compelling.

      (5) Good controls for EEG electrode implantation effects.

      (6) Nice analysis of most of the SE EEG data.

      Weaknesses:

      (1) In addition to the Cre- littermate controls, a no Tamoxifen treatment group is necessary to control for both insertional effects and leaky expression of the Nestin-CreERT2 transgene.

      About “leaky” expression, we have not found expression to be leaky. We checked by injecting a Cre-dependent virus so that mCherry would be expressed in those cells that had Cre.  The results were published as Supplemental Figure 9 in Jain et al. (2019).

      In the revised manuscript we also mention a study that examined three Nestin-CreERT2 mouse lines (Sun et al., 2014). One of the mouse lines was ours. The leaky expression was not in the mouse line we use. We have added these points to the revised manuscript:

      Methods, section II starting on line 791:

      Although Nestin-Cre-ERT2 mouse lines have been criticized because  they can have leaky expression, the mouse line used in the present study did not (Sun et al., 2014), which we confirmed (Jain et al., 2019).

      (2) The authors suggest sex differences; however, experimental procedures differed between male and female mice (as the authors note). Female mice received diazepam 40 minutes after the first pilocarpine-induced seizure onset, whereas male mice did not receive diazepam until 2 hours post-onset. The former would likely lessen the effects of SE on the female mice. Therefore, sex differences cannot be accurately assessed by comparing these two groups, and instead, should be compared between mice with matching diazepam time courses.

      We agree that a shorter delay between pilocarpine and diazepam would be likely to lead to less damage. However, the latency from pilocarpine to SE varied, making the time from the onset of SE to diazepam variable. Most of the variability was in females. By timing the diazepam injection differently in males and females, we could make the time from the onset of SE to diazepam similar between females and males. We had added a supplemental figure to show that our approach led to no significant differences between females and males in the latency to SE, time between SE and diazepam injection, and time between pilocarpine and diazepam injection. We also show that Cre+ females and Cre- females were not different in these times, so it could not be related to the neuroprotection of Cre+ females.

      Additionally, the authors state that female mice that received diazepam 2 hours post-onset had severe brain damage. This is concerning as it would suggest that SE is more severe in the female than in the male mice.

      We regret that our language was misleading. We intended to say females had more morbidity and mortality than males (lack of appetite and grooming, death in the days after SE) when we gave DZP 2 hrs after Pilo. We actually don’t know why because there were no differences in severity of SE. We think the females had worse outcome when they had a short latency to SE.  These females had a longer period of SE before DZP than males, probably leading to worse outcome. To correct this we gave DZP to females sooner. Then morbidity and mortality was improved in females. 

      Interestingly, after we did this we saw females did not always have a short latency to SE. We maintained the same regimen however, to be consistent. As the new supplemental figure (above) shows, there were significant sex differences in the latency to SE, time between SE and DZP, and time between pilocarpine and DZP.

      (3) Some sample sizes are low, particularly when sex and genotypes are split (n=3-5), which could cause a type II statistical error.

      We agree and have noted this limitation in the Discussion:

      Additional considerations, starting on line 739:

      This study is limited by the possibilities of type II statistical errors in those instances where we divided groups by genotype and sex, leading to comparisons of 3-5 mice/group.

      (4) Several figures show a datapoint in the sex and genotype-separated graphs that is missing from the corresponding male and female pooled graphs (Figs. 2C, 2D, 4B).

      We are very grateful to the Reviewer for pointing out the errors. They are corrected.

      (5) In Suppl Figs. 1B & 1C, subsections 1c and 2c, the EEG trace recording is described as the end of SE; however, SE appears to still be ongoing in these traces in the form of periodic discharges in the EEG.

      The Reviewer is correct.  It is a misconception that SE actually ends completely. The most intense seizure activity may, but what remains is abnormal activity that can last for days. Other investigators observe the same and have suggested that it argues against the concept of a silent period between SE and chronic epilepsy. We had discussed this in our prior papers and had referenced how we define SE.  In the revised manuscript we add the information to the Methods section instead of referencing a prior study:

      Methods, starting on line 899:

      SE duration was defined in light of the fact that the EEG did not return to normal after the initial period of intense activity. Instead, intermittent spiking occurred for at least 24 hrs, as we previously described (Jain et al., 2019) and has been described by others (Mazzuferi et al., 2012; Bumanglag and Sloviter, 2018; Smith et al., 2018). We therefore chose a definition that captured the initial, intense activity. We defined the end of this time as the point when the amplitude of the EEG deflections were reduced to 50% or less of the peak deflections during the initial hour of SE. Specifically, we selected the time after the onset of SE when the EEG amplitude in at least 3 channels had dropped to approximately 2 times the amplitude of the EEG during the first hour of SE, and remained depressed for at least 10 min (Fig. S2 in (Jain et al., 2019). Thus, the duration of SE was defined as the time between the onset and this definition of the "end" of SE.

      (6) In Results section II.D and associated Fig.3, what the authors refer to as "postictal EEG depression" is more appropriately termed "postictal EEG suppression". Also, postictal EEG suppression has established criteria to define it that should be used.

      We find suppression is typical in studies of ECT or humans (Esmaeili et al., 2023; Gascoigne et al., 2023; Hahn et al., 2023; Kavakbasi et al., 2023; Langroudi et al., 2023; Karl et al., 2024; Vilan et al., 2024; Zhao et al., 2024) and animal research uses the term postictal depression(Kanner et al., 2010; Krishnan and Bazhenov, 2011; Riljak et al., 2012; Singh et al., 2012; Carballosa-Gonzalez et al., 2013; Kommajosyula et al., 2016; Smith et al., 2018; Uva and de Curtis, 2020; Medvedeva et al., 2023). Therefore we think depression is a more suitable term.

      The example traces in Fig. 3A and B should also be expanded to better show this potential phenomenon.

      We expanded traces in Fig. 3 as suggested. They are in Fig 3A.

      (7) In Fig.5D, the area fraction of DCX in Cre+ female mice is comparable to that of Cre- and Cre+ male mice. Is it possible that there is a ceiling effect in DCX expression that may explain why male Cre+ mice do not have a significant increase compared to male Cre- mice?

      We thank the Reviewer for the intriguing possibility. We now mention it in the manuscript:

      Results, starting on line 456:

      It is notable that the Cre+ male mice did not show increased numbers of immature neurons at the time of chronic seizures but Cre+ females did. It is possible that there was a “ceiling” effect in DCX expression that would explain why male Cre+ mice did not have a significant increase in immature neurons relative to male Cre- mice.

      (8) In Suppl. Fig 6, the authors should include DCX immunolabeling quantification from conditional Cre+ male mice used in this study, rather than showing data from a previous publication.

      We have made this revision.

      (9) In Fig 8, please also include Fluorojade-C staining and quantification for male mice.

      The additional data for males have been added to part D.

      (10) Page 13: Please specify in the first paragraph of the discussion that findings were specific to female mice with pre-insult increases in adult-born neurogenesis.

      This has been done.

      Minor:

      (11) In Fig. 1 and suppl. figure 1, please clarify whether traces are from male or female mice.

      We have clarified.

      (12) Please be consistent with indicating whether immunolabeling images are from female or male mice.

      a. Fig 5B images labeled as from "Cre- Females" and "Cre+ Females".

      b. Suppl. Fig 8: Images labeled as "Cre- F" and "Cre+ F".

      c. Fig 6: sex not specified.

      d. Fig. 7: sex only specified in the figure legend.

      e. Fig 8: only female mice were included in these experiments, but this is not clear from the figure title or legend.

      We revised all figures according to the comments.

      (13) Page 4: the last paragraph of the introduction belongs within the discussion section.

      We recognize there is a classic view that any discussion of Results should not be in the Introduction. However, we find that view has faded and more authors make a brief summary statement about the Results at the end of the Introduction. We would like to do so because it allow Readers to understand the direction of the study at the outset, which we find is helpful.

      (14) Page 6: The sentence "The data are consistent with prior studies..." is unnecessary.

      We have removed the text.

      (15) Suppl. Fig 6A: Please include representative images of normal condition DCX immunolabeling.

      We have added these data. There is an image of a Cre- female, Cre+ female, Cre- male and Cre+ male in the new figure, Supplemental Figure 6. All mice had tamoxifen at 6 weeks of age and were perfused 6 weeks later. None of the mice had pilocarpine.

      (16) In Suppl. Fig 7C, I believe the authors mean "no loss of hilar mossy and SOM cells" instead of "loss of hilar mossy and SOM cells".

      This Figure was removed because of the input from Reviewer 1 suggesting it was too speculative.

      Reviewer #1 (Recommendations For The Authors):

      (1) The main claim of the study is that increasing adult neurogenesis decreases chronic seizures. However, to quantify adult-born neurons, DCX immunoreactivity is used as the sole metric to determine neurogenesis. This is insufficient as changes in DCX-expressing cells could also be an indicator of altered maturation, survival, and/or migration, not proliferation per se. To claim that increasing adult neurogenesis is associated with a reduction of chronic seizures, the authors should perform a pulse/chase (birth dating) experiment with BrdU and co-labeling with DCX.

      We think that increased DCX does reflect increased adult neurogenesis. However, we agree that one does not know if it was due to increased proliferation, survival, etc. We also note that this mouse line has been studied thoroughly to show there was increased neurogenesis with BrdU, Ki67 and DCX. We mention that paper in the revised text:

      Methods, starting on line 786:

      It was shown that after tamoxifen injection in adult mice there is an increase in dentate gyrus neurogenesis based on studies of bromo-deoxyuridine, Ki67, and doublecortin (Sahay et al., 2011).

      (2) As mentioned above, analysis of DCX staining alone months after TAM injections is limited. Instead, the cells could be labelled by BrdU prior to TAM injection, following which quantification of BrdU+/Prox1+ cells at 6 weeks post TAM injection should be performed in Cre+ and Cre- mice (males and females) to yield the rate of neurogenesis increase.

      We respectfully disagree that birthdating cells is critical. Using DCX staining just before SE, we know the size of the population of cells that are immature at the time of SE. This is what we think is most important because these immature neurons are those that appear to affect SE, as we have already shown.

      (3) To confirm the source of the hilar Prox1+ cells, a dual BrdU/EdU labeling approach would be beneficial. BrdU injection could be given before TAM injection and EdU injection before pilocarpine to label different cohorts of neural stem cells. Co-staining with Prox1 at different time points will help in identifying the origin of hilar ectopic cells.

      We are grateful for the ideas of the Reviewer. We hesitate to do these experiments now because it seems like a new study to find out where hilar granule cells come from.

      REFERENCES

      Bumanglag AV, Sloviter RS (2018) No latency to dentate granule cell epileptogenesis in experimental temporal lobe epilepsy with hippocampal sclerosis. Epilepsia 59:2019-2034.

      Carballosa-Gonzalez MM, Munoz LJ, Lopez-Alburquerque T, Pardal-Fernandez JM, Nava E, de Cabo C, Sancho C, Lopez DE (2013) EEG characterization of audiogenic seizures in the hamster strain gash:Sal. Epilepsy Res 106:318-325.

      Cho KO, Lybrand ZR, Ito N, Brulet R, Tafacory F, Zhang L, Good L, Ure K, Kernie SG, Birnbaum SG, Scharfman HE, Eisch AJ, Hsieh J (2015) Aberrant hippocampal neurogenesis contributes to epilepsy and associated cognitive decline. Nat Commun 6:6606.

      Esmaeili B, Weisholtz D, Tobochnik S, Dworetzky B, Friedman D, Kaffashi F, Cash S, Cha B, Laze J, Reich D, Farooque P, Gholipour T, Singleton M, Loparo K, Koubeissi M, Devinsky O, Lee JW (2023) Association between postictal EEG suppression, postictal autonomic dysfunction, and sudden unexpected death in epilepsy: Evidence from intracranial EEG. Clin Neurophysiol 146:109-117.

      Gascoigne SJ, Waldmann L, Schroeder GM, Panagiotopoulou M, Blickwedel J, Chowdhury F, Cronie A, Diehl B, Duncan JS, Falconer J, Faulder R, Guan Y, Leach V, Livingstone S, Papasavvas C, Thomas RH, Wilson K, Taylor PN, Wang Y (2023) A library of quantitative markers of seizure severity. Epilepsia 64:1074-1086.

      Hahn T et al. (2023) Towards a network control theory of electroconvulsive therapy response. PNAS Nexus 2:pgad032.

      Jain S, LaFrancois JJ, Botterill JJ, Alcantara-Gonzalez D, Scharfman HE (2019) Adult neurogenesis in the mouse dentate gyrus protects the hippocampus from neuronal injury following severe seizures. Hippocampus 29:683-709.

      Jung KH, Chu K, Lee ST, Kim J, Sinn DI, Kim JM, Park DK, Lee JJ, Kim SU, Kim M, Lee SK, Roh JK (2006) Cyclooxygenase-2 inhibitor, celecoxib, inhibits the altered hippocampal neurogenesis with attenuation of spontaneous recurrent seizures following pilocarpine-induced status epilepticus. Neurobiol Dis 23:237-246.

      Kanner AM, Trimble M, Schmitz B (2010) Postictal affective episodes. Epilepsy Behav 19:156-158.

      Karl S, Sartorius A, Aksay SS (2024) No effect of serum electrolyte levels on electroconvulsive therapy seizure quality parameters. J ECT 40:47-50.

      Kavakbasi E, Stoelck A, Wagner NM, Baune BT (2023) Differences in cognitive adverse effects and seizure parameters between thiopental and propofol anesthesia for electroconvulsive therapy. J ECT 39:97-101.

      Kommajosyula SP, Randall ME, Tupal S, Faingold CL (2016) Alcohol withdrawal in epileptic rats - effects on postictal depression, respiration, and death. Epilepsy Behav 64:9-14.

      Krishnan GP, Bazhenov M (2011) Ionic dynamics mediate spontaneous termination of seizures and postictal depression state. J Neurosci 31:8870-8882.

      Langroudi ME, Shams-Alizadeh N, Maroufi A, Rahmani K, Rahchamani M (2023) Association between postictal suppression and the therapeutic effects of electroconvulsive therapy: A systematic review. Asia Pac Psychiatry 15:e12544.

      Mazzuferi M, Kumar G, Rospo C, Kaminski RM (2012) Rapid epileptogenesis in the mouse pilocarpine model: Video-EEG, pharmacokinetic and histopathological characterization. Exp Neurol 238:156-167.

      Medvedeva TM, Sysoeva MV, Sysoev IV, Vinogradova LV (2023) Intracortical functional connectivity dynamics induced by reflex seizures. Exp Neurol 368:114480.

      Riljak V, Maresova D, Jandova K, Bortelova J, Pokorny J (2012) Impact of chronic ethanol intake of rat mothers on the seizure susceptibility of their immature male offspring. Gen Physiol Biophys 31:173-177.

      Sahay A, Scobie KN, Hill AS, O'Carroll CM, Kheirbek MA, Burghardt NS, Fenton AA, Dranovsky A, Hen R (2011) Increasing adult hippocampal neurogenesis is sufficient to improve pattern separation. Nature 472:466-470.

      Scharfman HE, Goodman JH, Sollas AL (2000) Granule-like neurons at the hilar/CA3 border after status epilepticus and their synchrony with area CA3 pyramidal cells: Functional implications of seizure-induced neurogenesis. J Neurosci 20:6144-6158.

      Singh B, Singh D, Goel RK (2012) Dual protective effect of passiflora incarnata in epilepsy and associated post-ictal depression. J Ethnopharmacol 139:273-279.

      Smith ZZ, Benison AM, Bercum FM, Dudek FE, Barth DS (2018) Progression of convulsive and nonconvulsive seizures during epileptogenesis after pilocarpine-induced status epilepticus. J Neurophysiol 119:1818-1835.

      Sun MY, Yetman MJ, Lee TC, Chen Y, Jankowsky JL (2014) Specificity and efficiency of reporter expression in adult neural progenitors vary substantially among nestin-creer(t2) lines. J Comp Neurol 522:1191-1208.

      Uva L, de Curtis M (2020) Activity- and ph-dependent adenosine shifts at the end of a focal seizure in the entorhinal cortex. Epilepsy Res 165:106401.

      Vilan A, Grangeia A, Ribeiro JM, Cilio MR, de Vries LS (2024) Distinctive amplitude-integrated EEG ictal pattern and targeted therapy with carbamazepine in kcnq2 and kcnq3 neonatal epilepsy: A case series. Neuropediatrics 55:32-41.

      Zhao C, Tang Y, Xiao Y, Jiang P, Zhang Z, Gong Q, Zhou D (2024) Asymmetrical cortical surface area decrease in epilepsy patients with postictal generalized electroencephalography suppression. Cereb Cortex 34.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Summary Responses: Besides the WT allele, equivalent to the mouse TMEM173 gene, the human TMEM173 gene has two common alleles: the HAQ and AQ alleles carried by billions of people. The main conclusions and interpretation, summarized in the Title and Abstract, are i) Different from the WT TMEM173 allele, the HAQ or AQ alleles are resistant to STING activation-induced cell death; ii) STING residue 293 is critical for cell death; iii) HAQ, AQ alleles are dominant to the SAVI allele; iv) One copy of the AQ allele rescues the SAVI disease in mice. We propose that STING research and STING-targeting immunotherapy should consider human TMEM173 heterogeneity. These interpretations and conclusions were based on Data and Logic. We welcome alternative, logical interpretations and collaborations to advance the human TMEM173 research.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This manuscript by Aybar-Torres et al investigated the effect of common human STING1 variants on STING-mediated T cell phenotypes in mice. The authors previously made knock-in mice expressing human STING1 alleles HAQ or AQ, and here they established a new knock-in line Q293. The authors stimulated cells isolated from these mice with STING agonists and found that all three human mutant alleles resist cell death, leading to the conclusion that R293 residue is essential for STING-mediated cell death (there are several caveats with this conclusion, more below). The authors also bred HAQ and AQ alleles to the mouse Sting1-N153S SAVI mouse and observed varying levels of rescue of disease phenotypes with the AQ allele showing more complete rescue than the HAQ allele. The Q293 allele was not tested in the SAVI model. They conclude that the human common variants such as HAQ and AQ have a dominant negative effect over the gain-of-function SAVI mutants.

      Strengths:

      The authors and Dr. Jin's group previously made important observations of common human STING1 variants, and these knock-in mouse models are essential for understanding the physiological function of these alleles.

      Weaknesses:

      However, although some of the observations reported here are interesting, the data collectively does not support a unified model. The authors seem to be drawing two sets of conclusions from in vitro and in vivo experiments, and neither mechanism is clear. Several experiments need better controls, and these knock-in mice need more comprehensive functional characterization.

      (1) In Figure 1, the authors are trying to show that STING agonist-induced splenocytes cell death is blocked by HAQ, AQ and Q alleles. The conclusion at line 134 should be splenocytes, not lymphocytes. Most experiments in this figure were done with mixed population that may involve cell-to-cell communication. Although TBK1-dependence is likely, a single inhibitor treatment of a mixed population is not sufficient to reach this conclusion.

      We greatly appreciate Reviewer 1's insights. We changed the “lymphocytes” to “splenocytes” (line 133) as suggested. We respectfully disagree with Reviewer 1’s comments on TBK1. First, we used two different TBK1 inhibitors: BX795 and GSK8612. Second, because BX795 also inhibits PDK1, we used a PDK1 inhibitor GSK2334470; Third, both BX795 and GSK8612 completely inhibited diABZI-induced splenocyte cell death (Figure 1B) (lines 128 – 133). The logical conclusion is “TBK1 activation is required for STING-mediated mouse spleen cell death ex vivo”. (line 117).

      Our discovery that the common human TMEM173 alleles are resistant to STING activation-induced cell death is a substantial finding. It further strengthens the argument that the HAQ and AQ alleles are functionally distinct from the WT allele 1-3. We wish to underscore the crucial message of this study-that 'STING research and STING-targeting immunotherapy should consider TMEM173 heterogeneity in humans' (line 37), which has been largely overlooked in current STING clinical trials 4.

      Regarding STING-Cell death, as we stated in the Introduction (lines 65-77). i) STING-mediated cell death is cell type-dependent 5-7 and type I IFNs-independent 5,7,8. ii) The in vivo biological significance of STING-mediated cell death is not clear 7,8. iii) The mechanisms of STING-Cell death remain controversial. Multiple cell death pathways, i.e., apoptosis, necroptosis, pyroptosis, ferroptosis, and PANoptosis, are proposed 7,9,10. SAVI/HAQ, SAVI/AQ prevented lymphopenia and alleviated SAVI disease in mice. Thus, the manuscript provides some answers to the biological significance of STING-cell death in vivo, which is new. Regarding the molecular mechanism, splenocytes from Q293/Q293 mice are resistant to STING cell death. The logical conclusion is that the amino acid 293 is critical for STING cell death (line 29).

      Extensive studies are needed, beyond the scope of this manuscript, on how aa293 and TBK1 mediates STING-Cell death to resolve the controversies in the STING-cell death fields (e.g. apoptosis, necroptosis, pyroptosis, ferroptosis, and PANoptosis).

      (2) Q293 knock-in mouse needs to be characterized and compared to HAQ and AQ. Is this mutant expressed in tissues? Does this mutant still produce IFN and other STING activities? Does the protein expression level altered on Western blot? Is the mutant protein trafficking affected? In the authors' previous publications and some of the Western blot here, expression levels of each of these human STING1 protein in mice are drastically different. HAQ and AQ also have different effects on metabolism (pmid: 36261171), which could complicate interoperation of the T cell phenotypes.

      These are very important questions that require rigorous investigations that are beyond the scope of this manuscript. This manuscript, titled “The common TMEM173 HAQ, AQ alleles rescue CD4 T cellpenia, restore T-regs, and prevent SAVI (N153S) inflammatory disease in mice” does not focus on Q293 mice. We have been investigating the common human TMEM173 alleles since 2011 from the discovery 11 , mouse model 1,3, human clinical trial 2, and human genetics studies 3. This manuscript is another step towards understanding these common human TMEM173 alleles with the new discovery that HAQ, AQ alleles are resistant to STING cell death.

      (3) HAQ/WT and AQ/WT splenocytes are protected from STING agonist-induced cell death equally well (Figure 1G). HAQ/SAVI shows less rescue compared to AQ/SAVI. These are interesting observations, but mechanism is unclear and not clearly discussed. E.g., how does AQ protect disease pathology better than HAQ (that contains AQ)? Does Q293 allele also fully rescue SAVI?

      In this manuscript, Figure 6 shows AQ/SAVI had more T-regs than HAQ/SAVI (lines 251 – 261). In our previous publication on HAQ, AQ knockin mice, we showed that AQ T-regs have more IL-10 than HAQ T-regs 3. Thus, increased IL-10+ Tregs in AQ mice may contribute to an improved phenotype in AQ/SAVI compared to HAQ/SAVI. However, we are not excluding other contributions (e.g. metabolic difference) (lines 332-335). We are exploring these possibilities.  

      (4) Figure 2 feels out of place. First of all, why are the authors using human explant lung tissues? PBMCs should be a better source for lymphocytes. In untreated conditions, both CD4 and B cells show ~30% dying cells, but CD8 cells show 0% dying cells. This calls for technical concerns on the CD8 T cell property or gating strategy because in the mouse experiment (Figure 1A) all primary lymphocytes show ~30% cell death at steady-state. Second, Figure 2C, these type of partial effect needs multiple human donors to confirm. Three, the reconstitution of THP1 cells seems out of place. STING-mediated cell death mechanism in myeloid and lymphoid cells are likely different. If the authors want to demonstrate cell death in myeloid cells using THP1, then these reconstituted cell lines need to be better validated. Expression, IFN signaling, etc. The parental THP1 cells is HAQ/HAQ, how does that compare to the reconstitutions? There are published studies showing THP1-STING-KO cells reconstituted with human variants do not respond to STING agonists as expected. The authors need to be scientifically rigorous on validation and caution on their interpretations.

      Figure 2 is necessary because it reveals the difference between mouse and human STING cell death, which is critical to understand STING in human health and diseases (lines 160-161). Figure 2A-2B showed that STING activation killed human CD4 T cells, but not human CD8 T cells or B cells. This observation is different from Figure 1A, where STING activation killed mouse CD4, CD8 T cells, and CD19 B cells, revealing the species-specific STING cell death responses. Regarding human CD8 T cells, as we stated in the Discussion (lines 323-325), human CD8 T cells (PBMC) are not as susceptible as the CD4 T cells to STING-induced cell death 8. We used lung lymphocytes that showed similar observations (Figure 2A). For Figure 2C, we used 2 WT/HAQ and 3 WT/WT individuals (lines 738-739). We generate HAQ, AQ THP-1 cells in STING-KO THP-1 cells (Invivogen,, cat no. thpd-kostg) (lines 380-387).

      A recent study found that a new STING agonist SHR1032 induces cell death in STING-KO THP-1 cells expressing WT(R232) human STING 10 (line 182). SHR1032 suppressed THP1-STING-WT(R232) cell growth at GI50: 23 nM while in the parental THP1-STING-HAQ cells, the GI50 of SHR1032 was >103 nM 10. Cytarabine was used as an internal control where SHR1032 killed more robustly than cytarabine in the THP1-STING-WT(R232) cells but much less efficiently than cytarabine in the THP-1-STING-HAQ cells 10. 

      Our manuscript rigorously uses mouse splenocytes, human lung lymphocytes, THP-1 reconstituted with HAQ, AQ, and HAQ/SAVI, AQ/SAVI mice, to demonstrate that the common human HAQ, AQ alleles are resistant to STING cell death in vitro and in vivo.

      We agree with Reviewer 1 that STING-mediated cell death mechanisms in myeloid and lymphoid cells may be different and likely contribute to the different mechanisms proposed in STING cell death research 7,9,10. Our study focuses on the in vivo STING-mediated T cellpenia.

      (5) Figure 2G, H, I are confusing. AQ is more active in producing IFN signaling than HAQ and Q is the least active. How to explain this?

      We stated in the Introduction that “AQ responds to CDNs and produce type I IFNs in vivo and in vitro 3,12,13 ”(line 92-93). We reported that the AQ knock in mice responded to STING activation 3. We previously showed that there was a negative natural selection on the AQ allele in individuals outside of Africa 3. 28% of Africans are WT/AQ but only 0.6% East Asians are WT/AQ 3. In contrast, the HAQ allele was positively selected in non-Africans 3. Investigation to understand the mechanisms and biological significance of these naturally selected human TMEM173 alleles has been ongoing in the lab.

      (6) The overall model is unclear. If HAQ, AQ and Q are loss-of-function alleles and Q is the key residue for STING-mediated cell death, then why AQ is the most active in producing IFN signaling and AQ/SAVI rescues disease most completely? If these human variants act as dominant negatives, which would be consistent with the WT/het data, then how do you explain AQ is more dominant negative than HAQ?

      In this manuscript, Figure 6 shows AQ/SAVI had more T-regs than HAQ/SAVI (lines 251 – 261). In our previous publication on HAQ, AQ knockin mice, we showed that AQ T-regs have more IL-10 and mitochondria activity than HAQ T-regs 3. Nevertheless, we are not excluding other contributions (e.g. metabolic difference) by the AQ allele (lines 332-335). Last, we used modern human evolution to discover the dominance of these common human STING alleles. In modern humans outside Africans, HAQ was positively selected while AQ was negatively selected 3. However, AQ is likely dominant to HAQ because there is no HAQ/AQ individuals outside Africa. The genetic dominance of common human TMEM173 allele is a new concept. More investigation is ongoing.

      (7) As a general note, SAVI disease phenotypes involve multiple cell types. Lymphocyte cell death is only one of them. The authors' characterization of SAVI pathology is limited and did not analyze immunopathology of the lung.

      Both radioresistant parenchymal and/or stromal cells and hematopoietic cells influence SAVI pathology in mice 14,15. Nevertheless, the lack of CD 4 T cells, including the anti-inflammatory T-regs, likely contributes to the inflammation in SAVI mice and patients 16. We characterized lung function, lung inflammation (Figure 4), lung neutrophils, and inflammatory monocyte infiltration (Figure S5) (lines 232-235).

      (8) Line 281, the discussion on HIV T cell death mechanism is not relevant and over-stretching. This study did not evaluate viral infection in T cells at all. The original finding of HAQ/HAQ enrichment in HIV/AIDS was 2/11 in LTNP vs 0/11 in control, arguably not the strongest statistics.

      Several publications have linked STING to HIV pathogenesis 17-22  (line 271). CD4 T cellpenia is a hallmark of AIDS. The manuscript studies STING activation-induced T cellpenia in vivo. It is not stretching to ask, for example, does preventing STING T cell death (e.g HAQ, AQ alleles) can restore CD4 T cell counts and improve care for AIDS patients?

      Reviewer #2 (Public Review):

      Aybar-Torres and colleagues utilize common human STING alleles to dissect the mechanism of SAVI inflammatory disease. The authors demonstrate that these common alleles alleviate SAVI pathology in mice, and perhaps more importantly use the differing functionality of these alleles to provide insight into requirements of SAVI disease induction. Their findings suggest that it is residue A230 and/or Q293 that are required for SAVI induction, while the ability to induce an interferon-dependent inflammatory response is not. This is nicely exemplified by the AQ/SAVI mice that have an intact inflammatory response to STING activation, yet minimal disease progression. As both mutants seem to be resistant STING-dependent cell death, this manuscript also alludes to the importance of STING-dependent cell death, rather than STING-dependent inflammation, in the progression of SAVI pathology. While I have some concerns, I believe this manuscript makes some important connections between STING pathology mouse models and human genetics that would contribute to the field.

      Some points to consider:

      (1) While the CD4+ T cell counts from HAQ/SAVI and AQ/SAVI mice suggest that these T cells are protected from STING-dependent cell death, an assay that explores this more directly would strengthen the manuscript. This is also supported by Fig 2C, but I believe a strength of this manuscript is the comparison between the two alleles. Therefore, if possible, I would recommend the isolation of T cells from these mice and direct stimulation with diABZI or other STING agonist with a cell death readout.

      Please see the new Figure S3 for cell death by diABZI, DMXAA in Splenocytes from WT/WT, WT/HAQ, HAQ/SAVI, AQ/SAVI mice. The HAQ/SAVI and AQ/SAVI splenocytes showed similar partial resistance to STING activation-induced cell death (lines 214-216).

      (2) Related to the above point - further exemplifying that the Q293 locus is essential to disease, even in human cells, would also strengthen the paper. It seems that CD4 T cell loss is a major component of human SAVI. While not co_mpletely necessary, repeating the THP1 cell death experiments from Fig 2 with a human T cell line would round out the study nicely._

      We examined HAQ, AQ mouse splenocytes, HAQ human lung lymphocytes, THP-1 reconstituted with HAQ, AQ, and HAQ/SAVI, AQ/SAVI mice, to demonstrate that the common human HAQ, AQ alleles are resistant to STING cell death in vitro and in vivo. Additional human T cell line work does not add too much. We hope to conduct more human PBMC or lung lymphocytes STING cell death experiments from HAQ, AQ individuals as we continue the human STING alleles investigation.

      (3) While I found the myeloid cell counts and BMDM data interesting, I think some more context is needed to fully loop this data into the story. Is myeloid cell expansion exemplified by SAVI patients? Do we know if myeloid cells are the major contributors to the inflammation these patients experience? Why should the SAVI community care about the Q293 locus in myeloid cells?

      This is likely a misunderstanding. We use BMDM for the purpose of comparing STING signaling (TBK1, IRF3, NFkB, STING activation) by WT/SAVI, HAQ/SAVI, AQ/SAVI. Ideally, we would like to compare STING signaling in CD4 T cells from WT/SAVI to HAQ/SAVI, AQ/SAVI mice. However, WT/SAVI has no CD4 T cells. Doing so, we are making the assumption that the basic STING signaling (TBK1, IRF3, NFkB, STING activation) is conserved between T cells and macrophages.

      (4) The functional assays in Figure 4 are exciting and really connect the alleles to disease progression. To strengthen the manuscript and connect all the data, I would recommend additional readouts from these mice that address the inflammatory phenotype shown in vitro in Figure 5. For example, measuring cytokines from these mice via ELISA or perhaps even Western blots looking for NFkB or STING activation would be supportive of the story. This would also allow for some tissue specificity. I believe looking for evidence of inflammation and STING activation in the lungs of these mice, for example, would further connect the data to human SAVI pathology.

      Reviewer 2 suggests looking for evidence of inflammation and STING activation in the lungs of HAQ/SAVI, AQ/SAVI. We would like to elaborate further. First, anti-inflammatory treatments, e.g. steroids, DMARDs, IVIG, Etanercept (TNF), rituximab, Nifedipine, amlodipine, et al., all failed in SAVI patients 23. JAK inhibitors on SAVI had mixed outcomes (lines 55-58). Second, Figure S5 examined lung neutrophils and inflammatory monocyte infiltration. Interestingly, while AQ/SAVI mice had a better lung function than HAQ/SAVI mice (Figure 4D, 4E vs 4H, 4I), HAQ/SAVI and AQ/SAVI lungs had comparable neutrophils and inflammatory monocyte infiltration (Figure S5). Last, SAVI is classified as type I interferonopathy 23, but the lung diseases of SAVI are mainly independent of type I IFNs 24-27. The AQ allele suppresses SAVI in vivo.  Understanding the mechanisms by which AQ rescues SAVI may lead to curative care for SAVI patients.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      One suggestion is to streamline this study by focusing on STING-mediated cell death only in CD4 T cells. The authors can use in vitro PBMC isolated human T cells, ex vivo T cells from the knock-in mice, and in vivo T cells from the SAVI breeding. The current manuscript includes myeloid cell death, Tregs, complex SAVI disease pathology, which is too confusing and too complex to explain with the varying effect from the three human STING1 variants.

      We sincerely appreciate Reviewer 1’s suggestion. The goal of our human STING alleles research has always been translational, i.e. improving human health. Even as a monogenetic disease, the SAVI pathology is still complex. For example, thought as a type I Interferonopathy, SAVI is largely independent of type I IFNs. Similarly, STING-activation-induced cell death, while contribute to SAVI, is not the whole story, as the Reviewer pointed out in the Comment 3 & 6 &7. HAQ/SAVI mice still died early and had lung dysfunction (Figure 4). In contrast, AQ/SAVI mice restore lifespan and lung function. We had Figure 6 show different T-regs between AQ/SAVI and HAQ/SAVI mice. In addition, AQ mice had more IL-10+ T-regs than HAQ mice 3. Therefore, we are excited about developing AQ-based curative therapy for SAVI patients (preventing cell death and inducing immune tolerance).  Again, we thank the Reviewer for the suggestion. Additional research is ongoing.

      Reviewer #2 (Recommendations For The Authors):

      Minor points

      (1) Generation of THP1 cells with the human STING alleles is missing from methods.

      We added the protocol in the methods (lines 380-387). THP-1 KO line stable expressing WT STING was first described by Weikang Tao’s group 10.

      (2) Some abbreviations are not expanded (CDA).

      CDA is expanded as cyclic di-AMP (e.g. line 375).

      References.

      (1) Patel, S. et al. The Common R71H-G230A-R293Q Human TMEM173 Is a Null Allele. J Immunol 198, 776-787 (2017).

      (2) Sebastian, M. et al. Obesity and STING1 genotype associate with 23-valent pneumococcal vaccination efficacy. JCI Insight 5 (2020).

      (3) Mansouri, S. et al. MPYS Modulates Fatty Acid Metabolism and Immune Tolerance at Homeostasis Independent of Type I IFNs. J Immunol 209, 2114-2132 (2022).

      (4) Sivick, K. E. et al. Comment on "The Common R71H-G230A-R293Q Human TMEM173 Is a Null Allele". J Immunol 198, 4183-4185 (2017).

      (5) Gulen, M. F. et al. Signalling strength determines proapoptotic functions of STING. Nat Commun 8, 427 (2017).

      (6) Kabelitz, D. et al. Signal strength of STING activation determines cytokine plasticity and cell death in human monocytes. Sci Rep 12, 17827 (2022).

      (7) Murthy, A. M. V., Robinson, N. & Kumar, S. Crosstalk between cGAS-STING signaling and cell death. Cell Death Differ 27, 2989-3003 (2020).

      (8) Kuhl, N. et al. STING agonism turns human T cells into interferon-producing cells but impedes their functionality. EMBO Rep 24, e55536 (2023).

      (9) Li, C., Liu, J., Hou, W., Kang, R. & Tang, D. STING1 Promotes Ferroptosis Through MFN1/2-Dependent Mitochondrial Fusion. Front Cell Dev Biol 9, 698679 (2021).

      (10) Song, C. et al. SHR1032, a novel STING agonist, stimulates anti-tumor immunity and directly induces AML apoptosis. Sci Rep 12, 8579 (2022).

      (11) Jin, L. et al. Identification and characterization of a loss-of-function human MPYS variant. Genes Immun 12, 263-269 (2011).

      (12) Yi, G. et al. Single nucleotide polymorphisms of human STING can affect innate immune response to cyclic dinucleotides. PLoS One 8, e77846 (2013).

      (13) Patel, S. et al. Response to Comment on "The Common R71H-G230A-R293Q Human TMEM173 Is a Null Allele". J Immunol 198, 4185-4188 (2017).

      (14) Gao, K. M. et al. Endothelial cell expression of a STING gain-of-function mutation initiates pulmonary lymphocytic infiltration. Cell Rep 43, 114114 (2024).

      (15) Gao, K. M., Motwani, M., Tedder, T., Marshak-Rothstein, A. & Fitzgerald, K. A. Radioresistant cells initiate lymphocyte-dependent lung inflammation and IFNgamma-dependent mortality in STING gain-of-function mice. Proc Natl Acad Sci U S A 119, e2202327119 (2022).

      (16) Hu, W. et al. Regulatory T cells function in established systemic inflammation and reverse fatal autoimmunity. Nat Immunol 22, 1163-1174 (2021).

      (17) Monroe, K. M. et al. IFI16 DNA sensor is required for death of lymphoid CD4 T cells abortively infected with HIV. Science 343, 428-432 (2014).

      (18) Doitsh, G. et al. Cell death by pyroptosis drives CD4 T-cell depletion in HIV-1 infection. Nature 505, 509-514 (2014).

      (19) Jakobsen, M. R., Olagnier, D. & Hiscott, J. Innate immune sensing of HIV-1 infection. Curr Opin HIV AIDS 10, 96-102 (2015).

      (20) Silvin, A. & Manel, N. Innate immune sensing of HIV infection. Curr Opin Immunol 32, 54-60 (2015).

      (21) Altfeld, M. & Gale, M., Jr. Innate immunity against HIV-1 infection. Nat Immunol 16, 554-562 (2015).

      (22) Krapp, C., Jonsson, K. & Jakobsen, M. R. STING dependent sensing - Does HIV actually care? Cytokine Growth Factor Rev 40, 68-76 (2018).

      (23) Liu, Y. et al. Activated STING in a vascular and pulmonary syndrome. N Engl J Med 371, 507-518 (2014).

      (24) Luksch, H. et al. STING-associated lung disease in mice relies on T cells but not type I interferon. J Allergy Clin Immunol 144, 254-266 e258 (2019).

      (25) Stinson, W. A. et al. The IFN-gamma receptor promotes immune dysregulation and disease in STING gain-of-function mice. JCI Insight 7 (2022).

      (26) Warner, J. D. et al. STING-associated vasculopathy develops independently of IRF3 in mice. J Exp Med 214, 3279-3292 (2017).

      (27) Fremond, M. L. et al. Overview of STING-Associated Vasculopathy with Onset in Infancy (SAVI) Among 21 Patients. J Allergy Clin Immunol Pract 9, 803-818 e811 (2021).

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      In this work, the authors provide a comprehensive description of transcriptional regulation in Pseudomonas syringae by investigating the binding characteristics of various transcription factors. They uncover the hierarchical network structure of the transcriptome by identifying top-, middle-, and bottom-level transcription factors that govern the flow of information in the network. Additionally, they assess the functional variability and conservation of transcription factors across different strains of P. syringae by studying DNA-binding characteristics. These findings notably expand our current knowledge of the P. syringae transcriptome.

      The findings associated with crosstalk between transcription factors and pathways, and the diversity of transcription factor functions across strains provide valuable insights into the transcriptional regulatory network of P. syringae. However, these results are at times underwhelming as their significance is unclear. This study would benefit from a discussion of the implications of transcription factor crosstalk on the functioning of the organism as a whole. Additionally, the implications of variability in transcription factor functions on the phenotype of the strains studied would further this analysis.<br /> Overall, this manuscript serves as a key resource for researchers studying the transcriptional regulatory network of P. syringae.

      Thank you for your positive comments.

      Reviewer #2 (Public Review):

      Summary:

      The phytopathogenic bacterium Pseudomonas syringae is comprised of many pathovars with different host plant species and has been used as a model organism to study bacterial pathogenesis in plants. Transcriptional regulation is key to plant infection and adaptation to host environments by this bacterium. However, researchers have focused on a limited number of transcription factors (TFs) that regulate virulence-related pathways. Thus, a comprehensive, systems-level understanding of regulatory interactions between transcription factors in P. syringae has not been achieved.

      This study by Sun et al performed ChIP-seq analysis of 170 out of 301 TFs in P. syringae pv. syringae 1448A and used this unique dataset to infer transcriptional regulatory networks in this bacterium. The network analyses revealed hierarchical interactions between TFs, various network motifs, and co-regulation of target genes by TF pairs, which collectively mediate information flow. As discussed, the structure and properties of the P. syringae transcriptional regulatory networks are somewhat different from those identified in humans, yeast, and E. coli, highlighting the significance of this study. Further, the authors made use of the P. syringae transcriptional regulatory networks to find TFs of unknown functions to be involved in virulence-related pathways. For some of these TFs, their target specificity and biological functions, such as motility and biofilm formation, were experimentally validated. Of particular interest is the finding that despite conservation of TFs between P. syringae pv. syringae 1448A, P. syringae pv. tomato DC3000, P. syringae pv. syringae B728a, and P. syringae pv. actinidiae C48, some of the conserved TFs show different repertoires of target genes in these four P. syringae strains.

      Thank you for your positive comments.

      Strengths:

      This study presents a systems-level analysis of transcriptional regulatory networks in relation to P. syringae virulence and metabolism, and highlights differences in transcriptional regulatory landscapes of conserved TFs between different P. syringae strains, and develops a user-friendly database for mining the ChIP-seq data generated in this study. These findings and resources will be valuable to researchers in the fields of systems biology, bacteriology, and plant-microbe interactions.

      Thank you for your positive comments.

      Weaknesses:

      No major weaknesses were found, but some of the results may need to be interpreted with caution. ChIP-seq was performed with bacterial strains overexpressing TFs. This may cause artificial binding of TFs to promoters which may not occur when TFs are expressed at physiological levels. Another caution is applied to the interpretation of the biological functions of TFs. The biological roles of the tested TFs are based on in vitro experiments. Thus, functional relevance of the tested TFs during plant infection and/or survival under natural environmental conditions remains to be demonstrated.

      Thank you for your comments, and we agree with the reviewer. To eliminate the artificial binding of TFs, we performed EMSA to verify the analyzed targets. Our EMSA results confirmed the analyzed binding peaks.

      For the verification experiments of the biological functions of TFs, we also performed in vivo motility assay and biofilm production assay (Figures 3b-d). To further detect the biological functions of TFs, we performed plant infection assay of TF PSPPH2193 under natural environmental condition (bean leaves). As shown in Figures S6c and g, both the motility and the virulence of P. syringae in ∆PSPPH2193 strain was significantly reduced compared with WT strain. These results showed that TF PSPPH2193 positively regulated the pathogenicity of P. syringae via modulating the bacterial motility.

      Reviewer #3 (Public Review):

      Summary:

      This study aims to understand gene regulation of the plant bacterial pathogen Pseudomonas syringae. Although the function of some TFs has been characterized in this strain, a global picture of the gene regulatory network remains elusive. The authors conducted a large-scale ChIP-seq analysis, covering 170 out of 301 TFs of this strain, and revealed gene regulatory hierarchy with functional validation of some previously uncharacterized TFs.

      Thank you for your positive comments.

      Strengths:

      - This study provides one of the largest ChIP-seq datasets for a single bacterial strain, covering more than half of its TFs. This impressive resource enabled comprehensive systems-level analysis of the TF hierarchy.

      - This study identified novel gene regulation and function with validations through biochemical and genetic experiments.

      - The authors attempted on broad analyses including comparisons between different bacterial strains, providing further insights into the diversity and conservation of gene regulatory mechanisms.

      Thank you for your positive comments.

      Weaknesses:

      (1) Some conclusions are not backed by quantitative or statistical analyses, and they are sometimes overinterpreted.

      Thank you for your comments. We used hypergeometric test in this analysis. Although only one gene was enriched in some pathways, the adjusted p-value was less than 0.05. We added the details in the revised manuscript.

      (2) Some figures and analyses are not well explained, and I was not able to understand them.

      Thank you for your comments, and we are sorry for the confusion. We defined ‘indirect interaction’ as ‘co-association’ and ‘cooperativity’ as ‘if the common target of two TFs is from a TF’. We added the definition of "indirect interaction" and "cooperativity" in the revised legend.

      For Figure S3a, the low co-association scores and large peak numbers of these top-level TFs indicated that top-level TFs preferred to solely regulate target genes, but not to co-regulate with other top-level TFs. PSPPH4700 was an example to show that top-level TFs with low co-association scores and large peak numbers tend to solely regulate target genes, but not to co-regulate with other top-level TFs. We revised the sentence to ‘For example, the top-level TF PSPPH4700 yielded over 1,700 peaks but cooperated with only 24 top-level TFs with low co-association scores about 0.05 (Supplementary Table 2b).’.

      We analyzed high co-association scores of 125 TFs in three levels and further determined the co-association patterns. To identify the tendency of co-association of all these 125 TFs, the co-association patterns were classified into 4 clusters. Bottom-level TFs tend to co-regulate target genes with other TFs. We revised the sentence in the revised manuscript.

      For Figure 2b, in C1, C2 and C4, many bottom-level TFs performed co-association pattern with other TFs, especially bottom TFs (showed in C4). To explore the regulatory pattern in C3, the peak locations in target genes of MexT were analyzed with those of TFs in C3. Seven top-level TFs (PSPPH1435, PSPPH1758, PSPPH2193, PSPPH2454, PSPPH4638, PSPPH4998 and PSPPH3411), three middle-level TFs (PSPPH1100, PSPPH5132 and PSPPH5144) and four bottom-level TFs (PSPPH0700, PSPPH2300, PSPPH2444 and PSPPH2580) were compared with MexT. MexT showed higher co-association scores (more than 60 scores) with more top-level-TFs. Therefore, we demonstrated that MexT performed closer co-association relationships with top-level TFs. We added the statement in the revised manuscript.

      For Figure 1a, the hierarchical network showed different number of TFs in three levels (54 top-level TFs, 62 middle-level TFs and 147 bottom-level TFs), which indicated that more than half of TFs (bottom-level TFs) tend to be regulated by other TFs and then directly bound to target genes. This finding showed a downward regulatory direction of transcription regulation in P. syringae. We revised the statement in the revised manuscript.

      (3) The Method section lacks depth, especially in data analyses. It is strongly recommended that the authors share their analysis codes so that others can reproduce the analyses.

      Thank you for your comments, and we defined the intergenic region before each TF sequence as the promoter region. As pHM1 plasmid carries its own constitutive promoter (lacZ promoter), we amplified the TF-coding sequence and cloned into site following the promoter. The TF protein expression was activated by the promoter of plasmid. Psph 1448A was used for our main ChIP-seq. We added the details in the revised manuscript.

      For Figure S3, we performed GO analysis on genes that were co-bound by TF pairs. We added the details in the revised manuscript.

      We shared our analysis codes on the website (https://github.com/dengxinb2315/PS-PATRnet-code) in the Data Availability.

      Recommendations for the authors

      Reviewer #1 (Recommendations For The Authors):

      (1) The specific strain of Pseudomonas syringae used in the study outside of the evolutionary analysis should be specified in the abstract and main text.

      Thank you for your suggestion. We revised the statements in abstract and main text to specific strains.

      (2) The language used throughout the manuscript should be revised for clarity, conciseness, and readability.

      Thank you for your suggestion. We have revised the language used throughput the manuscript by a scientific editor who is a native speaker of English.

      (2) Line 688: Replace "80C" with "-80C".

      Thank you for your correction. We revised ‘80℃’ to ‘-80℃’. Please see Line 713.

      (3) Line 172 - 173: The abbreviations TT, MM, BB, TM, TB, and MB need to be expanded in the main text before their use.

      Thank you for your suggestion. We added the abbreviations TT, MM, BB, TM, TB, and MB in the manuscript. Please see Lines 172-174.

      Reviewer #2 (Recommendations For The Authors):

      Major points

      (1) The name of the P. syringae strains used in each experiment/analysis should be explicitly stated (most experiments were carried out with P. syringae strain 1448A). This should also be applied to the introduction where many papers on P. syringae are cited without clear indication of strain names. I think this amendment is essential because target genes and thus biological functions of TFs could be different between P. syringae strains, as shown in the present study.

      Thank you for your suggestion. We revised the P. syringae strains in the citations throughout the manuscript.

      (2) How many TFs were analyzed throughout the study? Most sentences including line 22 in the abstract say 170, but I also found some say 270 (for example, line 106 and line 149). The legend of Figure 1 says 262. More detailed information is required regarding the datasets used for each analysis.

      Thank you for your suggestion. The number of TFs analyzed by ChIP-seq in this research is 170, the number of TFs analyzed by HT-SELEX in our previous research is 100. Hierarchical analysis integrated data from ChIP-seq and HT-SELEX which included 270 TFs. As 8 TFs did not show hierarchical characteristic, the legend of Figure 1 said 262 TFs. We added the data source in the revised manuscript. Please see Lines 104, 147, 160 and 1082.

      (3) Figure 1b: Please define "indirect interaction" and "cooperativity" in the legend as well as in the text. I only found the definition of "direct interaction".

      Sorry for the missing information. We defined ‘indirect interaction’ and ‘cooperativity’ as ‘co-association’ and ‘if the common target of two TFs is from a TF’, respectively. We added the definition of "indirect interaction" and "cooperativity" in the revised legend. Please see Lines 174-176, 1084-1086.

      (4) I found it very interesting that conserved TFs show different repertoires of target genes in different P. syringae strains. This suggests the rewiring of transcriptional regulatory networks in P. syringae strains, but the underlying mechanism is not explored in the current manuscript. It can be easily tested whether these conserved TFs bind to similar or different motifs by motif enrichment analysis. If they bind to similar motifs, it is possible that the promoter sequences of their target genes have diversified. Addressing or at least discussing these points would provide molecular insights into the diversification of the transcriptional regulatory networks in P. syringae. Similarly, functional enrichment analysis of target genes can be used to test whether the conserved TFs regulate different biological processes.

      Thank you for your suggestion. We added the motif analysis and functional enrichment analysis of target genes of TFs (PSPPH3122 and PSPPH4127) in different P. syringae strains. We found two different motifs (AGACN4GATCAA and CGGACGN3GATCA) in 1448A and DC3000 strains, respectively. We also performed the GO analysis and found the specific functions of PSPPH3122 in Psph 1448A compared with Pst DC3000 and Pss B728a strains, including recombinase activity and DNA recombination. For PSPPH4127, we found four different motifs in four P. syringae strains. GO analysis showed its relationship with recombinase activity in Psph 1448A strain, and RNA binding, structural constituent of ribosome, translation and ribosome in Pss B728a strain. These results indicated the highly functional diversity of TFs in P. syringae. We added these points in the Results part, and Figure S9-S10 in the revised manuscript. Please see Lines 497-509.

      (5) Related to point 4, it would be quite useful if a list of orthologous genes of 1448A TFs in the other tested P. syringae strains were provided. Such information may also enhance the utility of the database developed in this study.

      Thank you for your suggestion. We added the list of orthologous genes of 301 Psph 1448A TFs in the other tested P. syringae strains in the Supplementary Table 5. Please see Lines 467 and Supplementary Table 5.

      (6) Lines 243-246: It is unclear how these functional enrichment analyses were performed. Did you use target genes regulated by individual TFs or those coregulated by pairs of TFs? Please add more information for the sake of readers.

      Thank you for your suggestion. We performed the functional enrichment analyses by hypergeometric test (BH-adjusted p < 0.05) via using target genes regulated by individual TFs. We added the details in the Results part. Please see Lines 248-252, 270, 1194-1195, 1199-1200 and 1205-1206.

      Minor points

      (1) Lines 167-168: I may not understand correctly, but you might want to say "downward-pointing edges" instead of "upward-pointing edges".

      Thank you for correction. We revised the ‘upward-pointing edges’ to ‘downward-pointing edges’. Please see Line 166.

      (2) Line 174: "physical interactions" should be amended to "direct interactions".

      Thank you for correction. We revised the ‘physical interactions’ to ‘direct interactions’. Please see Line 177.

      (3) Line 224: Could you please explain why bacterial growth in plant tissues is considered an example of "multi-stability"?

      Thank you for your suggestion. We are sorry for the incorrect statement. We showed ‘plant intercellular spaces’ as ‘multi-stability’. We revised the sentence to ‘These auto-regulators are important and always act as repressors in scenarios of multi-stability, such as plant intercellular spaces’. Please see Lines 224-226.

      (4) Line 254-257: Here, the definition of "tether binding" is introduced, but it is not very clear to me. In my understanding, tethered binding is an indirect binding of a TF to a target gene through protein-protein interaction with other TF that directly binds to the promoter of the target gene.

      Thank you for your suggestion, and we agree with you. We referred to the paper published in 2012 (Wang et al., 2012) and revised the statement of ‘tether binding’ to ‘This finding suggested that these TFs indirectly regulated target genes through protein-protein interaction with other TFs that directly binds to the promoters of target genes, a phenomenon defined as tethered binding’. Please see Lines 259-262.

      (5) Lines 341-343: Figure 3b shows qRT-PCR of hopAE1, not hrpR.

      Thank you for your correction. We revised ‘hrpR’ to ‘hopAE1’. Please see Line 349.

      (6) Lines 500 and Figure 6b: It is hard to see edges from module 12 to others. So, it would be better to provide numeric information (number of TFs and target genes) in the text.

      Thank you for your suggestion. Module 12 includes 22 TFs and 318 target genes. We added the statement of numeric information about Module 12 in the revised manuscript. Please see Lines 536-537.

      (7) Line 519: Figure S4b is not the EMSA data for PSPPH3798. Should it be Figure S4e?

      Thank you for your correction. We revised to ‘Figure S4e’. Please see Line 545.

      (8) Line 522: Figure S6b is not relevant to the statement here.

      Thank you for your correction. We deleted the ‘Figure S6b’ here. Please see Line 547.

      (9) Line 593: prokaryotic transcriptional regulatory networks -> eukaryotic transcriptional regulatory networks?

      Thank you for your correction. We revised ‘prokaryotic transcriptional regulatory networks’ to ‘eukaryotic transcriptional regulatory networks’. Please see Line 618.

      (10) Figure S3 requires images of higher resolution. Especially, values for the color codes are not readable or very hard to see.

      Thank you for your suggestion. To make the images clearer, we enlarged the images, change the color codes, and divided it into three figures. Please see the revised Figures S3-S5 and corresponding Figure legends at Lines 1191-1206.

      Reviewer #3 (Recommendations For The Authors):<br /> (1) Some conclusions are not backed by quantitative or statistical analyses, and they are sometimes overinterpreted.

      L221: "Taken together, the simplest and most effective submodule M1 and the coregulatory submodule M13 played crucial roles in the transcriptional regulation of TFs in P. syringae."

      The authors did not provide any evidence supporting the functional importance of any of these submodules. M13 is most enriched within the locked loop, but its size is much smaller than simple loops. What evidence supports the importance of this particular submodule?

      Thank you for your suggestion. In eukaryote (Saccharomyces cerevisiae) and prokaryote (Escherichia coli) which have the best characterized transcriptional regulation networks, the feed-forward loop (called M13 in this article) appear numerous times in the networks and perform different biological functions. M1 appeared most frequently by an order of magnitude than other modules. We revised the sentence to ‘Taken together, the most numerous but simplest submodule M1 played a crucial role in the transcriptional regulation of TFs in P. syringae.’ Please see Lines 222-224.

      L223: "...we found 92 auto-regulators...These auto-regulators are important and always act as repressors in scenarios of multi-stability, such as in plant intercellular spaces where bacteria grow (Figure 1d)(Alon, 2007). These regulators are regarded as bistable switches that further influence the expression of downstream genes."<br /> Are these claims supported by any evidence?

      Thank you for your suggestion. We referred to the following articles:

      (1) Alon. Nature Reviews Genetics. 2007(Alon, 2007).

      That transcription factors repress the transcription of their target genes was considered as negative regulation. These negative autoregulators account for half of the repressors in E. coli and occur in many eukaryotes. The repressors controlled the concentration of the target production through suppressing its expression, which accelerated back to the steady state of cells.

      (2) Becskei. et al. Nature. 2000; Rosenfeld et al. Journal of Molecular Biology. 2002 (Becskei & Serrano, 2000; Rosenfeld, Elowitz, & Alon, 2002).

      Fluorescent assay confirmed that the negative autoregulatory module (negative autoregulator TetR) spent less time to the log phase than unregulated group, which reduced cell-to-cell fluctuations in the steady-state level of the transcription factor. Some negative autoregulators were showed here, such as LexA, CysB and SrlA-D.

      In our research, we also identified many autoregulators including CysB and LexA2 (annotated as LexA repressor). We revised the sentence to ‘In addition, we found 92 auto-regulators in our hierarchy network. These auto-regulators are important and always act as repressors in scenarios of multi-stability, such as plant intercellular spaces (Figure 1d) (Alon, 2007). For example, LexA and CysB as negative autoregulators were indicated to reduce cell-to-cell fluctuations in the steady-state level of the transcription factor (Becskei & Serrano, 2000; Rosenfeld et al. 2002).’. Please see Lines 224-229.

      L265: "This finding indicated that the bottom-level TFs, which were more easily regulated, tended to cooperate with downstream genes and other intra-level TFs."<br /> Could the authors provide more explanation to reach this conclusion from the data? Analyzing the number of highly co-accessing TFs does not sufficiently support this conclusion. The clustering of TFs (C1-C4) is incomplete, and each TF level (Top/Middle/Bottom) contains different numbers of TFs. Since the authors calculated all-by-all co-association scores for these 125 TFs, they can group these scores into 6 possible combinations (TT, TM, TB, MM, MB, BB) and show the distribution of co-association scores.

      Thank you for your suggestion. We indicated that the bottom-level TFs preferred to regulate the target genes through the cooperation with other TFs. To further support the claim, we analyzed the proportion of the bottom TF interaction in all the TF pairs interactions and direct interaction based on results in Figure 1B. The interactions of bottom TFs were 43% and 49%, respectively. However, the interactions of top TFs and middle TFs were only 20% and 28%, respectively. We revised the statement ‘Based on the analysis in Figure 1B, we found that the proportions of bottom-level TF interaction in all the TF pair interactions and direct interaction were 43% and 49%. These results indicated that the bottom-level TFs tended to regulate downstream genes through cooperating with other level TFs.’ in the revised manuscript. Please see Lines 269-272.

      As not every TF performed co-association with other TFs, we only collected 125 TFs with co-association scores. For the numbers of TF in each level, we divided TFs into three levels according to hierarchy height. Hierarchy height from -1 to -0.3 represented bottom level; hierarchy height from -0.3 to 0.3 represented middle level ; hierarchy height from 0.3 to 1 represents top level. Each level was equally divided by height scores. We suggested that different numbers of TFs in three levels indicated the characteristic of transcriptional regulation in P. syringae.

      Thank you for your suggestion. As the co-association patterns were determined by co-association scores of the same TFs, we first grouped the co-association scores into 3 possible TF pairs (TT, MM, and BB, in Figures S3a, S4a and S5a). Our results indicated that higher co-association scores preferred to occur in bottom-level TFs. We revised the statement in the revised manuscript. Please see Lines 244-252.

      (2) Some figures and analyses are not well explained, and I was not able to understand them.

      Figure 1b: The terms "direct," "indirect," and "cooperativity" require further clarification as their definitions in the text (L169-183) are unclear to me. This ambiguity hampers the evaluation of the authors' discussion regarding TF-TF interactions (L561-584), an important theme of this study. The figure includes concepts discussed in later sections (e.g., cooperativity), making it difficult to understand. A diagram explaining these concepts would be highly helpful for readers to understand.

      Sorry for the missing information. We defined ‘indirect interaction’ as ‘co-association’, ‘cooperativity’ as ‘if the common target of two TFs is from a TF’. We added the definition of "indirect interaction" and "cooperativity" in the revised manuscript and legend. Please see Lines 174-176 and 1085-1087.

      L253: "Notably, we found that TFs at the top level, without cooperating TFs, exhibited a large number of binding peaks (Figure S3a)."

      I could not understand this sentence. Did the authors mean that top-level TFs with a large number of peaks showed a low level of co-association? If so, does this data suggest that these TFs do not tend to cooperate with other TFs? I was confused by the discussion in L253-L261.

      Thank you for your comment, and we agree with you. The low co-association scores and large peak numbers of these top-level TFs indicated that top-level TFs preferred to solely regulate target genes, but not to co-regulate with other top-level TFs.

      Thank you for your comment. From L253-256, PSPPH4700 was an example to show that top-level TFs with low co-association scores and large peak numbers tend to solely regulate target genes, but not to co-regulate with other top-level TFs. We revised the sentence to ‘For example, the top-level TF PSPPH4700 yielded over 1,700 peaks, but cooperated with only 24 top-level TFs with low co-association scores about 0.05 (Supplementary Table 2b).’.

      From L257-261, we analyzed high co-association scores of 125 TFs in three levels and further determined the co-association patterns. To identify the tendency of co-association of all these 125 TFs, the co-association patterns were classified into 4 clusters. Bottom-level TFs tend to co-regulate target genes with other TFs. We revised the sentence. Please see Lines 262-264, 265-266 and 269-272.

      L287: "The analysis of the peak locations of MexT demonstrated that MexT showed closer co-association relationships with top-level TFs (Figure 2b)."

      I could reach this conclusion by seeing Figure 2b. Additional explanation and/or data visualization would be appreciated.

      Thank you for your suggestion. In C1, C2 and C4, many bottom-level TFs performed co-association pattern with other TFs, especially bottom TFs (showed in C4). To explore the regulatory pattern in C3, the peak locations in target genes of MexT were analyzed with those of TFs in C3. Seven top-level TFs (PSPPH1435, PSPPH1758, PSPPH2193, PSPPH2454, PSPPH4638, PSPPH4998 and PSPPH3411), three middle-level TFs (PSPPH1100, PSPPH5132 and PSPPH5144) and four bottom-level TFs (PSPPH0700, PSPPH2300, PSPPH2444 and PSPPH2580) were compared with MexT. MexT showed higher co-association scores (more than 60 scores) with more top-level-TFs. Therefore, we demonstrated that MexT performed closer co-association relationships with top-level TFs. We added the statement in the revised manuscript. Please see Lines 291-296.

      Figure 6cd: What kind of enrichment analysis did the authors perform? Was any statistical test used? The figure only shows the number of genes, and sometimes the number is only 1 for a functional category. Can it be considered as significant enrichment?

      Thank you for your comment. We used hypergeometric test in this analysis. Although only one gene was enriched in some pathways, the adjusted p-value was less than 0.05. We added the details in the revised manuscript. Please see Lines 533-534.

      L169: "The hierarchical network revealed a downward information flow, suggesting the prioritization of collaboration between different hierarchy levels."<br /> Can the authors please explain the logic behind this statement more in detail?

      Thank you for your comment. The hierarchical network showed different number of TFs in three levels (54 top-level TFs, 62 middle-level TFs and 147 bottom-level TFs), which indicated that more than half of TFs (bottom-level TFs) tend to be regulated by other TFs and then directly bound to target genes. This finding showed a downward regulatory direction of transcription regulation in P. syringae. We revised the statement in the revised manuscript. Please see Lines 167-170.

      (3) The Method section lacks depth, especially on data analyses.

      How did the authors define promoter regions of each gene? How were operons treated in their analyses? Was P. syringae 1448A used for their main ChIP-seq?

      Thank you for your comment. We defined the intergenic region before each TF sequence as the promoter region.

      As pHM1 plasmid carries its own constitutive promoter (lacZ promoter), we amplified the TF-coding sequence and cloned into the site following the promoter. The TF protein expression was activated by the promoter of plasmid.

      P. syringae 1448A was used for our main ChIP-seq. We added the details in the revised manuscript. Please see Lines 705 and 727-730.

      Figure S3: I am not sure how the GO analyses were done. For example, in the case of the top-level TF PSPPH4700, did the authors perform GO analysis on genes that are co-bound by PSPPH4700 and any other top-level TFs?

      Thank you for your comment and we agree with you. We performed GO analysis on genes that were co-bound by TF pairs in the same level. We added the details in the revised manuscript. Please see Lines 248-252.

      The analysis presented in Figure 6a needs more explanation of the methodology employed by the authors.

      Thank you for your comment. We added more details for the analysis in Figure 6a. Please see Lines 514-522.

      It is strongly recommended that the authors share their analysis codes so that others can reproduce the analyses.

      Thank you for your comment. We shared our analysis codes on the website (https://github.com/dengxinb2315/PS-PATRnet-code) in the Data Availability. Please see Lines 800-801.

      (4) Other:

      Figure 3: I suggest putting additional panel labels to facilitate the interpretation of the figure.

      Thank you for your suggestion. We added detailed labels in the revised Figures 3 and 4. Please see in the revised Figures 3 and 4.

      I spotted several potential errors:

      L106: 170 TFs?

      Thank you for your comment, and we are sorry for the missing details. For the hierarchical network, we integrated the DNA-binding data of 170 TFs in this study and 100 TFs in our previous SELEX research. We added the details in the revised manuscript. Please see Lines 104, 147 and 159-160.

      L592: P. syringae not E. coli?

      Thank you for your comment. Here we discussed the hierarchical characteristics in E. coli. We revised the statement in the revised manuscript. Please see Line 618.

      L593: eukaryotic not prokaryotic?

      Thank you for your correction. Here we discussed the feedforward loops in our study. We revised the statement in the revised manuscript. Please see Line 618.

      References

      Alon, U. (2007). Network motifs: theory and experimental approaches. Nature Reviews Genetics, 8(6), 450-461.

      Becskei, A., & Serrano, L. (2000). Engineering stability in gene networks by autoregulation. Nature, 405(6786), 590-593.

      Rosenfeld, N., Elowitz, M. B., & Alon, U. (2002). Negative autoregulation speeds the response times of transcription networks. Journal of molecular biology, 323(5), 785-793.

      Wang, J., Zhuang, J., Iyer, S., Lin, X., Whitfield, T. W., Greven, M. C., . . . Cheng, Y. (2012). Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors. Genome research, 22(9), 1798-1812.

    1. 如果步行,亲友步行进入园可在“J区边城、F区六号门门岗、H区三家巷、L区柳堡、M区康 桥、D区南门、B区南门”门岗进入;

      步行 游览

    1. Author response:

      The following is the authors’ response to the original reviews.

      eLife assessment

      In this useful study, the authors report the efficacy, hematological effects, and inflammatory response of the BPaL regimen (containing bedaquiline, pretomanid, and linezolid) compared to a variation in which Linezolid is replaced with the preclinical development candidate spectinamide 1599, administered by inhalation in tuberculosis-infected mice. The authors provide convincing evidence that supports the replacement of Linezolid in the current standard of care for drug-resistant tuberculosis. However, a limitation of the work is the lack of control experiments with bedaquiline and pretomanid only, to further dissect the relevant contributions of linezolid and spectinamide in efficacy and adverse effects.

      We acknowledge a limitation in our study due to lack of groups with monotherapy of bedaquiline and pretomanid however, similar studies to understand contribution of bedaquiline and pretomanid to the BPaL have been published already (references #4 and #60 in revised manuscript).  Our goal was to compare the BPaS versus the BPaL with the understanding that TB treatment requires multidrug therapy.   We omitted monotherapy groups to reduce complexity of the studies because the multidrug groups require very large number of animals with very intensive and complex dosing schedules. Even if B or Pa by themselves have better efficacy than the BPa or BPaL combination, patients will not be treated with only B or Pa because of very high risk of developing drug resistance to B or/and PA. If drug resistance is developed for B or Pa, the field will lose very effective drugs against TB. 

      Although the manuscript is well written overall, a re-formulation of some of the stated hypotheses and conclusions, as well as the addition of text to contextualize translatability, would improve value.

      Manuscript has been edited to address these critiques.  Answers to individual critiques are below.

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This manuscript is an extension of previous studies by this group looking at the new drug spectinamide 1599. The authors directly compare therapy with BPaL (bedaquiline, pretomanid, linezolid) to a therapy that substitutes spectinamide for linezolid (BPaS). The Spectinamide is given by aerosol exposure and the BPaS therapy is shown to be as effective as BPaL without adverse effects. The work is rigorously performed and analyses of the immune responses are consistent with curative therapy.

      Strengths:

      (1) This group uses 2 different mouse models to show the effectiveness of the BPaS treatment.

      (2) Impressively the group demonstrates immunological correlates associated with Mtb cure with the BPaS therapy.

      (3) Linezolid is known to inhibit ribosomes and mitochondria whereas spectinaminde does not. The authors clearly demonstrate the lack of adverse effects of BPaS compared to BPaL.

      Weaknesses:

      (1) Although this is not a weakness of this paper, a sentence describing how the spectinamide would be administered by aerosolization in humans would be welcomed.

      We already reported on the aerodynamic properties of dry powder spectinamide 1599 within #3 HPMC capsules and its delivery from a RS01 Plastiape inhaler device (reference #59 in revised manuscript).  To address this critique, we added a last paragraph in discussion “It is proposed that human use of spectinamides 1599 will be administered using a dry powder formulation delivered by the RS01 Plastiape dry powder inhaler" (reference #59 in revised manuscript).  

      Reviewer #2 (Public Review):

      Summary:

      Replacing linezolid (L) with the preclinical development candidate spectinamide 1599, administered by inhalation, in the BPaL standard of care regimen achieves similar efficacy, and reduces hematological changes and proinflammatory responses.

      Strengths:

      The authors not only measure efficacy but also quantify histological changes, hematological responses, and immune responses, to provide a comprehensive picture of treatment response and the benefits of the L to S substitution.

      The authors generate all data in two mouse models of TB infection, each reproducing different aspects of human histopathology.

      Extensive supplementary figures ensure transparency. 

      Weaknesses:

      The articulation of objectives and hypotheses could be improved.

      We edited to "The AEs were associated with the long-term administration of the protein synthesis inhibitor linezolid. Spectinamide 1599 (S) is also a protein synthesis inhibitor of Mycobacterium tuberculosis with an excellent safety profile, but which lacks oral bioavailability. Here, we propose to replace L in the BPaL regimen with spectinamide administered via inhalation and we demonstrate that inhaled spectinamide 1599, combined with BPa ––BPaS regimen––has similar efficacy to that of BPaL regimen while simultaneously avoiding the L-associated AEs.

      Reviewer #3 (Public Review):

      Summary:

      In this paper, the authors sought to evaluate whether the novel TB drug candidate, spectinamide 1599 (S), given via inhalation to mouse TB models, and combined with the drugs B (bedaquiline) and Pa (pretomanid), would demonstrate similar efficacy to that of BPaL regimen (where L is linezolid). Because L is associated with adverse events when given to patients long-term, and one of those is associated with myelosuppression (bone marrow toxicity) the authors also sought to assess blood parameters, effects on bone marrow, immune parameters/cell effects following treatment of mice with BPaS and BPaL. They conclude that BPaL and BPaS have equivalent efficacy in both TB models used and that BPaL resulted in weight loss and anemia (whereas BPaL did not) under the conditions tested, as well as effects on bone marrow.

      Strengths:

      The authors used two mouse models of TB that are representative of different aspects of TB in patients (which they describe well), intending to present a fuller picture of the activity of the tested drug combinations. They conducted a large body of work in these infected mice to evaluate efficacy and also to survey a wide range of parameters that could inform the effect of the treatments on bone marrow and on the immune system. The inclusion of BPa controls (in most studies) and also untreated groups led to a large amount of useful data that has been collected for the mouse models per se (untreated) as well as for BPa - in addition to the BPaS and BPaL combinations which are of particular interest to the authors. Many of these findings related to BPa, BPaL, untreated groups, etc corroborate earlier findings and the authors point this out effectively and clearly in their manuscript. To go further, in general, it is a well-written and cited article with an informative introduction.

      Weaknesses:

      The authors performed a large amount of work with the drugs given at the doses and dosing intervals started, but at present, there is no exposure data available in the paper. It would be of great value to understand the exposures achieved in plasma at least (and in the lung if more relevant for S) in order to better understand how these relate to clinical exposures that are observed at marketed doses for B, Pa, and L as well as to understand the exposure achieved at the doses being evaluated for S. If available as historical data this could be included/cited. Considering the great attempts made to evaluate parameters that are relevant to clinical adverse events, it would add value to understand what exposures of drug effects such as anemia, weight loss, and bone marrow effects, are being observed. It would also be of value to add an assessment of whether the weight loss, anemia, or bone marrow effects observed for BPaL are considered adverse, and the extent to which we can translate these effects from mouse to patient (i.e. what are the limitations of these assessments made in a mouse study?). For example, is the small weight loss seen as significant, or is it reversible? Is the magnitude of the changes in blood parameters similar to the parameters seen in patients given L? In addition, it is always challenging to interpret findings for combinations of drugs, so the addition of language to explain this would add value: for example, how confident can we be that the weight loss seen for only the BPaL group is due to L as opposed to a PK interaction leading to an elevated exposure and weight loss due to B or Pa?

      We totally agree with this critique but the studies suggested by the reviewer are very expensive and

      logistically/resource intensive. Data reported in this manuscript was used as preliminary data in a RO1 application to NIH-NIAID that included studies proposed above by this reviewer. The authors are glad to report that the application got a fundable score and is currently under consideration for funding by NIH-NIAID.   The summary of proposed future studies is included in the last paragraph of the discussion in this revised manuscript. 

      Turning to the evaluations of activity in mouse TB models, unfortunately, the evaluations of activity in the BALB/c mouse model as well as the spleens of the Kramnik model resulted in CFU below/at the limit of detection and so, to this reviewer's understanding of the data, comparisons between BPaL and BPaS cannot be made and so the conclusion of equivalent efficacy in BALB/c is not supported with the data shown. There is no BPa control in the BALB/c study, therefore it is not possible to discern whether L or S contributed to the activity of BPaL or BPaS; it is possible that BPa would have shown the same efficacy as the 3 drug combinations. It would be valuable to conduct a study including a BPa control and with a shorter treatment time to allow comparison of BPa, BPaS, and BPaL. 

      We agree with the reviewer these studies need to be done.  Some of them were recently published by our colleague Dr. Lyons (reference #60 in revised manuscript). The studies proposed by the reviewer will be performed under a new award under consideration for funding by the NIH-NIAID, the summary of future studies is included in the last paragraph of the discussion in this revised manuscript. 

      In the Kramnik lungs, as the authors rightly note, the studies do not support any contribution of S or L to BPa - i.e. the activity observed for BPa, BPaL, and BPaS did not significantly differ. Although the conclusions note equivalency of BPaL and BPaS, which is correct, it would be helpful to also include BPa in this statement;

      We edited and now included in lines #191 as requested 

      It would be useful to conduct a study dosing for a longer period of time or assessing a relapse endpoint, where it is possible that a contribution of L and/or S may be seen - thus making a stronger argument for S contributing an equivalent efficacy to L. The same is true for the assessment of lesions - unfortunately, there was no BPa control meaning that even where equivalency is seen for BPaL and BPaS, the reader is unable to deduce whether L or S made a contribution to this activity.

      Added in the future plans in the last paragraph of discussion

      “Future studies are already under consideration for funding by NIH-NIAID to understand the pharmacokinetics of mono, binary and ternary combinations of BPaS. These studies also aim to identify the optimal dose level and dosing frequency of each regimen along with their efficacy and relapse free-sterilization potential. Studies are also planned using a model-based pharmacokinetic-pharmacodynamic (PKPD) framework, guided by an existing human BPa PKPD model (reference #61 in revised manuscript), to find allometric human dose levels, dosing frequencies and treatment durations that will inform the experimental design of future clinical studies. 

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Although this is not a weakness of this paper, a sentence describing how the spectinamide would be administered by aerosolization in humans would be welcomed.

      Last paragraph of discussion was added “It is proposed that human use of spectinamides 1599 will be administered using a dry powder formulation delivered by the RS01 Plastiape dry powder inhaler". We already reported on the aerodynamic properties of dry powder spectinamide 1599 within #3 HPMC capsules and delivered from a RS01 Plastiape inhaler device (reference #59 in revised manuscript)

      Reviewer #2 (Recommendations For The Authors):

      Major comments

      The Abstract lacks focus and could more clearly convey the key messages.

      Edited as requested 

      The two mouse models and why they were chosen need to be described earlier. Currently, it's covered in the first section of the Discussion, but the reader needs to understand the utility of each model in answering the questions at hand before the first results are described, either in the introduction or in the opening section of the results.

      Thank you for suggestion, we agree.  We moved the first paragraph in discussion to last paragraph in Introduction. 

      Line 130: Please justify the doses and dosing frequency for S. A reference to a published manuscript could suffice if compelling.

      The dosing and regimens were previously reported by our groups in ref 21 and 22 in revised manuscript.- 

      (21) Robertson GT, Scherman MS, Bruhn DF, Liu J, Hastings C, McNeil MR, et al. Spectinamides are effective partner agents for the treatment of tuberculosis in multiple mouse infection models. J Antimicrob Chemother.

      2017;72(3):770–7. 

      (22) Gonzalez-Juarrero M, Lukka PB, Wagh S, Walz A, Arab J, Pearce C, et al. Preclinical Evaluation of Inhalational Spectinamide-1599 Therapy against Tuberculosis. ACS Infect Dis. 2021;7(10):2850–63. 

      Figures 1 E to H: several "ns" are missing, please add them.

      Edited as requested 

      Line 184 to 190: suggest moving the body weight plots to a Supplemental Figure, and at least double the size of the histology images to convey the message of lines 192-203.

      Please include higher magnification insets to illustrate the histopathological findings. In that same section, please add a sentence or two describing the lesion scoring concept/method. It is a nice added feature, not widespread in the field, and deserves a brief description.

      Edited as requested.  We added detailed description for scoring method in M&M under histopathology and lesion scoring

      Line 206: please add an introductory sentence explaining why one would expect S to cause (or not) hematological disruption, and why MCHC and RDW were chosen initially (they are markers of xyz). The first part of Figure 3 legend belongs to the Methods.

      To address this critique we added in #225-226 “The effect of L in the blood profile of humans and mouse has been reported (references #38-42 in revised manuscript) but the same has not been reported for S” . In line #229-230 we added “Of 20-blood parameters evaluated, two blood parameters were affected during treatment”. 

      The first part of Figure 3 legend belongs to the Methods.

      We edited Figure 3 to “During therapy of mice in Figure 1, the blood was collected at 1, 2- and 4-weeks posttreatment. The complete blood count was collected in VETSCAN® HM5 hematology analyzer (Zoetis)”.

      Line 218: please explain why the 4 blood parameters that are shown were selected, out of the 20 parameters surveyed.

      We added an explanation in line 239-240 “out 20-blood parameters evaluated, a total of four blood parameters were affected at 2 and 4-weeks-of treatment”.

      Line 243 and again Line 262 (similar to comment Line 206): please add an introductory paragraph explaining the motivation to conduct this analysis and the objective. Can the authors put the experiment in the context of their hypothesis?

      To address this critique, we added in line #235-237 “The Nix-TB trial associated the long-term administration of L within the BPaL regimen as the causative agent resulting in anemia in patients treated with the BPaL regimen (5).”

      Figure 4C (and the plasma and lung equivalent in the SI). This figure needs adequate labeling of axes: X axis = LOG CFU? Please add tick marks for all plots since log CFU is only shown for the bottom line. Y axes have no units: pg/mL as in B?

      Figure legend were edited to add (Y axis:pg/ml) and (X axis; log10CFU).  

      Line 255-256: please remove "pronounced" and "profound". There is a range of CFU reduction and cytokine reduction, from minor to major. The correlation trend is clear and those words are not needed.

      Edited as requested 

      Line 277-289, Figure 6: given the heterogeneity of a C3HeB/FeJ mouse lung (TB infected), and the very heterogeneous cell population distribution in these lungs (Fig. 6A), the validity of whole lung analysis on 2 or 3 mice (the legend should state what 1, 2 and 3 means, individual mice?) is put into question. "F4/80+ cells were observed significantly higher in BPaS compared to UnRx control": Figure S14 suggests a statistically significant difference, but nothing is said about the other cell type, which appears just as much reduced in BPaS compared to UnRx as F4/80+. Overall, sampling the whole lung for these analyses should be mentioned as a limitation in the Discussion.

      We agree with the reviewer that "visually" it appears as other populations in addition to F4/80 have statistical significance.  We run again the two way Anova with Tukey test and only the BPaS and UnRx for F4/80 is significant. 

      We edited figure S16 (previously S14) to add ns for every comparation.  

      In Figure 6A was edited ;  N=2 are 2 mice for Unrx and n=3 mice for BPaL/BPaS each.

      Line 355-360: "The BPa and BPaL regimens altered M:E in the C3HeB/FeJ TB model by suppressing myeloid and inducing erythroid lineages" This suggests that altered M:E is not associated with L, putting into question the comparison between BPaS, BPaL, and UnRx. Can the authors comment on how M:E is altered in BPa and not in BPaS?

      Our interpretation to this result was that addition of S in our regimen BPsS was capable of restoring the M:E ratio altered by the BPa and BPaL. This interpretation was included in main text in line #263-264 and is also now added to abstract

      Line 379: discuss the limitations of working with whole lungs.

      Sorry we cannot understand this request. In our studies we always work with whole lungs if the expected course of histopathology/infection among lung lobes is very variable (as is the case of C3HeB/Fej TB model)

      Concluding paragraph: "Here we present initial results that are in line with these goals." If such a bold claim is made, there needs to be a discussion on the translatability of the route of administration and the dose of S. Otherwise, please rephrase.

      We added the following last paragraph to discussion:

      To conclude, the TB drug development field is working towards developing shorter and safer therapies with a common goal of developing new multidrug regimens of low pill burden that are accessible to patients, of short duration (ideally 2-3 months) and consist of 3-4 drugs of novel mode-of-action with proven efficacy, safety, and limited toxicity. Here we present initial results for new multidrug regimens containing inhaled spectinamide 1599 that are in line with these goals. It is proposed that human use of spectinamides 1599 will be administered using a dry powder formulation delivered by the RS01 Plastiape dry powder inhaler.  We already reported on the aerodynamic properties of dry powder spectinamide 1599 within #3 HPMC capsules and delivered from a RS01 Plastiape inhaler device (reference #59 in revised manuscript). Future studies are already under consideration for funding by NIHNIAID to understand the pharmacokinetics of mono, binary and ternary combinations of BPaS. These studies also aim to identify the optimal dose level and dosing frequency of each regimen along with their efficacy and relapse free-sterilization potential. Studies are also planned using a model-based pharmacokinetic-pharmacodynamic (PKPD) framework, guided by an existing human BPa PKPD model (references #60 and 61 in revised manuscript) , to find allometric human dose levels, dosing frequencies and treatment durations that will inform the experimental design of future clinical studies.

      Minor edits

      Adverse events, not adverse effects (side effects)

      Edited as requested

      BALB/c (not Balb/c, please change throughout).

      Edited as requested

      Line 92: replace 'efficacy' with potency or activity.

      Edited as requested

      "Live" body weight: how is that different from "body weight"? Suggest deleting "live" throughout, or replace with "longitudinally recorded" if that's what is meant, although this is generally implied.

      Edited as requested

      The last line of Figure 2 legend is disconnected. 

      Line 331: delete "human".

      Edited as requested

      Reviewer #3 (Recommendations For The Authors):

      We thank the reviewer for these suggestions.  The data presented in this manuscript with 4 weeks of treatment along with monitoring of effects of therapy in blood, bone marrow and immunity have been submitted for a RO1 application to NIH-NIAID, which have received a fundable score and is under funding consideration. All the points suggested by the reviewer(s) here are included in the research proposed in the RO1 application including manufacturing and physico-chemically characterize larger scale of dry powders of spectinmides and evaluation of their aerodynamic performance for human or animal use; Pharmacokinetics and efficacy studies to determine the optimal dose level and dosing frequency for new multidrug regimens containing spectinamides. These studies include mono, binary and ternary combinations of each multidrug regimen along with their efficacy and relapse free- sterilization potential. These studies will also develop PK/PD simulation-based allometric scaling to aid in human dose projections inhalation. We hope the reviewer will understand all together these studies will last 4-5 years.  

      Although I truly appreciate the great efforts of the authors, I suggest that in order to better evaluate the contribution of S versus L to BPa in these models, repeat studies be run that:

      (a) include BPa groups to allow the contribution of S and L to be assessed. Included in research proposed RO1 application mentioned above

      (b) use shorter treatment times in BALB/c to allow comparisons at end of Tx CFU above the LOD. We have added new data for 2 weeks treatment with BPaL and BPaS in Balb/c mice infected with MTb that was removed from previous submission of this manuscript

      (c) use longer treatment times and ideally a relapse endpoint in Kramnik to allow

      assessment of L and S as contributors to BPa (i.e. give a chance to see better efficacy of BPaL or BPaS versus BPa) and also measure plasma exposures of all drugs (or lung levels if this is the translatable parameter for S) to allow detection of any large DDI and also understand the translation to the clinic. Related to the safety parameters, it would be really great to understand whether or not the observations for BPaL would be labeled adverse in a toxicology study/in a clinical study, and it would be useful to include information on the magnitude of observations seen here versus in the clinic (eg for the hematological parameters).

      The research proposed in the RO1 application mentioned above included extensive PK, extended periods of treatment beyond 1 month of treatment (2-5 months as needed to reach negative culturable bacterial from organs) and of course relapse studies. 

      Minor point: I suggest rewording "high safety profile" when describing spectinomides in the intro - or perhaps qualify the length of dosing where the drug is well tolerated

      "high safety profile" was replaced by “an acceptable safety profile”

    2. Reviewer #3 (Public Review):

      Summary:<br /> In this paper, the authors sought to evaluate whether the novel TB drug candidate, spectinamide 1599 (S), given via inhalation to mouse TB models, and combined with the drugs B (bedaquiline) and Pa (pretomanid), would demonstrate similar efficacy to that of BPaL regimen (where L is linezolid). Because L is associated with adverse events when given to patients longterm, and one of those is associated with myelosuppression (bone marrow toxicity) the authors also sought to assess blood parameters, effects on bone marrow, immune parameters/cell effects following treatment of mice with BPaS and BPaL. They conclude that BPaL and BPaS have equivalent efficacy in both TB models used and that BPaL resulted in weight loss and anemia (whereas BPaS did not) under the conditions tested, as well as effects on bone marrow.

      Strengths:<br /> The authors used two mouse models of TB that are representative of different aspects of TB in patients (which they describe well), intending to present a fuller picture of the activity of the tested drug combinations. They conducted a large body of work in these infected mice to evaluate efficacy and also to survey a wide range of parameters that could inform the effect of the treatments on bone marrow and on the immune system. The inclusion of BPa controls (in most studies) and also untreated groups led to a large amount of useful data that has been collected for the mouse models per se (untreated) as well as for BPa - in addition to the BPaS and BPaL combinations which are of particular interest to the authors. Many of these findings related to BPa, BPaL, untreated groups etc corroborate earlier findings and the authors point this out effectively and clearly in their manuscript. To go further, in general, it is a well written and cited article with an informative introduction.

      Weaknesses:<br /> The authors performed a large amount of work with the drugs given at the doses and dosing intervals stated, but there is no exposure data available at this time. The authors intend to evaluate exposure-effect relationships in future work. An understanding of the exposures at which the efficacy and adverse effects are seen will assist in the translation of these findings to the clinic.<br /> In addition, it is always challenging to interpret findings for combinations of drugs and for now, the data available cannot attribute confidence to the weight loss seen for only the BPaL group to L specifically, as opposed to a PK interaction leading to an elevated exposure and weight loss due to B or Pa. It is not yet possible, then to state that what is seen are "L-associated AEs" - this is assumed only.<br /> The evaluations of activity in the BALB/c mouse model as well as the spleens of the Kramnik model resulted in CFU below/at the limit of detection so comparisons between BPaL and BPaS cannot be made and so the conclusion of equivalent efficacy in BALB/c is not supported with the data shown. There is no BPa control in the BALB/c study, therefore it is not possible to discern whether L or S contributed to the activity of BPaL or BPaS. The same is true for the assessment of lesions - unfortunately, there was no BPa control meaning that even where equivalency is seen for BPaL and BPaS, the reader is unable to deduce whether L or S made a contribution to this activity.<br /> Although these weaknesses limit what we can learn from the current body of data, the authors note that further studies will be done to increase understanding of the points above.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      This manuscript dissects the contribution of the CaBP 1 and 2 on the calcium current in the cochlear inner hair cells. The authors measured the calcium current inactivation from the double knock-out CaBP1 and 2 and showed that both proteins contribute to voltage-dependent and calcium-dependent inactivation. Synaptic release was reduced in the double KO. As a consequence, the authors observed a depressed activity within the auditory nerve. Taken together, this study identifies a new player that regulates the stimulation-secretion coupling in the auditory sensory cells. 

      Strengths: 

      In this study, the authors bring compelling evidence that CaBP 1 and 2 are both involved in the inactivation of the calcium current, from cellular up to system level, and by taking care to probe different experimental conditions such as different holding potentials and by rescuing the phenotype with the re-expression of CaBP2. Indeed, while changing the holding potential worsens the secretion, it completely changes the kinetics of the inactivation recovery. It alerts the reader that probing different experimental conditions that may be closer to physiology is better suited to uncovering any deleterious phenotype. This gave pretty solid results. 

      Weaknesses: 

      Although this study clearly points out that CaBP1 is involved in the calcium current inactivation, it is not clear how CaBP1 and CaBP2 act together (but this is probably beyond the scope of the study). Another point is that the authors re-express CaBP2 to largely rescue the phenotype in the double KO but no data are available to know whether the re-expression of both CaBP1 and CaBP2 would achieve a full recovery and what would be the effect of the sole re-expression of CaBP1 in the double KO.

      We would like to thank the reviewer for the appreciation of our work. We agree that the effect of the sole re-expression of CaBP1 in the double KO remains elusive and have planned to address this question in a follow-up study. 

      Reviewer #2 (Public Review): 

      Summary: 

      In the manuscript by Oestreicher et al, the authors use patch-clamp electrophysiology, immunofluorescent imaging of the cochlea, auditory function tests, and single-unit recordings of auditory afferent neurons to probe the unique properties of calcium signaling in cochlear hair cells that allow rapid and sustained neurotransmitter release. The calcium-binding proteins (CaBPs) are thought to modify the inactivation of the Cav1.3 calcium channels in IHCs that initiate vesicle fusion, reducing the calcium-dependent inactivation (CDI) of the channels to allow sustained calcium influx to support neurotransmitter release. The authors use knockout mice of Cabp1 and Cabp2 in a double knockout (Cabp1/2 DKO) to show that these molecules are required for enabling sustained calcium currents by reducing CDI and enabling proper IHC neurotransmitter release. They further support their evidence by re-introducing Cabp2 using an injection of AAV containing the Cabp2 sequence into the cochlea, which restores some of the auditory function and reduces CDI in patch-clamp recordings. 

      Strengths: 

      Overall the data is convincing that Cabp1/2 is required for reducing CDI in cochlear hair cells, allowing their sustained neurotransmitter release and sound encoding. Figures are well-prepared, recordings are careful and stats are appropriate, and the manuscript is well-written. The discussion appropriately considers aspects of the data that are not yet explained and await further experimentation.

      Weaknesses: 

      There are some sections of the manuscript that pool data from different experiments with slightly different conditions (wt data from a previous paper, different calcium concentrations, different holding voltages, tones vs clicks, etc). This makes the work harder to follow and more complicated to explain. However, the major conclusion, that cabp1 and 2 work together to reduce calcium-dependent inactivation of L-type calcium channels in cochlear inner hair cells, still holds. 

      Another weakness is that the authors used injections of AAV-containing sequences for Cabp2, but do not present data from sham surgeries. In most cases, the improvement of hearing function with AAV injection is believable and should be attributed to the cabp2 function. However, in at least one instance (Figure 4B), the results of the AAV injection experiments may be overinterpreted - the authors show that upon AAV injection, the hair cells have a much longer calcium current recovery following a large, long depolarization to inactivate the calcium channels. Without comparison to sham surgery, it is not known if this result could be a subtle result of the surgery or indeed due to the Cabp2 expression.  It would be great to see the auditory nerve recordings in AAV-injected animals that have a recovery of ABRs. However, this is a challenging experiment that requires considerable time and resources, so is not required.

      We would like to thank the reviewer for the appreciation of our work. We agree with the reviewer that sham surgery may convey more information that might benefit the interpretation of our data. The recovery experiments were very tedious and these long patch-clamp paradigms required extremely stable recordings. Based on our observations, we plan to address the recovery kinetics into more detail in the follow-up study. However, we would consider off-side effects of the surgery (as it may mainly affect middle ear function) and of the empty AAV-vector on inner hair cell calcium current recovery rather unlikely, but we cannot exclude them. We thus added a sentence in the discussion to alert to that. Based on previously published data of the effect of PHP.eB-Cabp2eGFP in WT animals we expect some (mild) adverse effects on hearing from overexpression of CaBP2 and/or eGFP in the inner ear. In the future, we thus plan to further optimize the treatment. In terms of the in vivo recordings from the auditory nerve fibers of the rescued mice, we could not agree more. That is in plan for the follow-up study.

      Reviewer #3 (Public Review): 

      Summary: 

      The authors attempted to unravel the role of the Ca2+-binding proteins CaBP1 and CaBP2 for the hitherto enigmatic lack of Ca2+-dependent inactivation of Ca2+ currents in sensory inner hair cells (IHCs). As Ca2+ currents through Cav1.3 channels are crucial for exocytosis, the lack of inactivation of those Ca2+ currents is essential for the indefatigable sound encoding by IHCs. Using a deaf mouse model lacking both CaBP1 and CaBP2, the authors convincingly demonstrate that both CaBP1 and CaBP2 together confer a lack of inactivation, with CaBP2 being far more effective. This is surprising given the mild phenotype of the single knockouts, which has been published by the authors before. Readmission of CaBP2 through viral gene transfer into the inner ear of double-knockout mice largely restored hearing function, normal Ca2+ current properties, and exocytosis. 

      Strengths: 

      (1) In vitro electrophysiology: perforated patch-clamp recordings of Ca2+/Ba2+ currents of inner hair cells (IHCs) from 3-4 week-old mice - very difficult recordings - necessary to not interfere with intracellular Ca2+ buffers, including CaBP1 and CaBP2. 

      (2) Capacitance (exocytosis) recordings from IHCs in perforated patch mode. 

      (3) The insight that a negative holding potential might underestimate the impact of lack of CaBP1/2 on the inactivation of ICa in IHCs. As the physiological holding potential is much more positive than a preferred holding potential in patch clamp experiments it has a strong impact on inactivation in the pauses between depolarization mimicking receptor potentials. This truly advances our thinking about the stimulation of IHCs and accumulating inactivation of the Cav1.3 channels. 

      (4) Insight that the voltage sine method with usual voltage excursions (35 mV) to determine the membrane capacitance (for exocytosis measurements) also favors the inactivated state of Cav1.3 channels 

      (5) Use of double ko mice (for both CaBP1 and CaBP2, DKO) and use of DKO with virally injected CaBP2eGFP into the inner ear. 

      (6) Use of DKO animals/IHCs/SGNs after virus-mediated CaBP2 gene transfer shows a great amount of rescue of the normal ICa inactivation phenotype.

      (7) In vivo measurements of SGN AP responses to sound, which is highly demanding. 

      (8) In vivo measurements of hearing thresholds, DPOAE characteristics, and ABR wave I amplitudes/latencies of DKO mice and DKO+injected mice compared to WT mice. 

      Very thorough analysis and presentation of the data, excellent statistical analysis.

      The authors achieved their aims. Their results fully support their conclusions. The methods used by the authors are state-of-the-art. 

      The impacts on the field are the following:

      Regulation of inactivation of Cav1.3 currents is crucial for the persistent functioning of Cav1.3 channels in sensory transduction. 

      The findings of the authors better explain the phenotype of the human autosomal recessive DFNB93, which is based on the malfunction of CaBP2. 

      Future work - by the authors or others - should address the molecular mechanisms of the interaction of CaBP1 and 2 in regulating Cav1.3 inactivation. 

      Weaknesses: 

      I do not see weaknesses. 

      What is not explained (but was not the aim of the authors) is how the CaBPs 1 and 2 interact with the Cav1.3 channels and with each other to reduce CDI. Also, why DFNB93, which is based on mutation of the CaBP2 gene, lead to a severe phenotype in humans in contrast to the phenotype of the CaBP2 ko mouse.

      We would like to thank the reviewer for the appreciation of our work and the amount of effort that went into these experiments. These are the questions that we are posing ourselves as well and would like to address them in the future.   

      Recommendations for the authors:

      Reviewing editor: 

      In the Introduction, the authors may also mention that Ca2+-dependent and voltage-dependent inactivation of L-type Ca channels has been reported at ribbon synapses of retinal bipolar cells (see von Gersdorff & Mathtews, J Neurosci. 1996, 16(1):115-122). These are critical retinal interneurons involved in the continuous exocytosis of synaptic vesicles onto retinal ganglion cells. 

      We would like to thank the reviewing editor for pointing that out, we have added the reference in the revised version of the manuscript.

      Reviewer #1 (Recommendations For The Authors): 

      Conditions worsen with age but no numbers regarding the threshold shift are provided. 

      For better readability, we now included click threshold values for both genotypes and age groups in the MS text, results section.   

      Do the authors correlate the re-expression level of CaBP2 using GFP to the rescuing phenotype (for exocytosis or BK channels immunostaining)?

      The restoration of BK expression in the virus-treated IHC was a side observation of our study, which was not performed in sufficient replicates for proper quantification. In the future, we will address this question into greater detail, possibly with improved viral constructs. In a previous study, we attempted to correlate eGFP fluorescence intensity with residual depolarization-evoked calcium current in CaBP2-injected IHC of Cabp2 single KO animals. At that time, we were unable to establish a convincing correlation. This could be related to (i) large variability in the data, possibly requiring much larger datasets to observe potential correlation above the noise, (ii) variable imaging conditions from prep to prep, or (iii) additional parameters that could influence the outcome of the current rescue, e.g. uncontrolled expression of the transgene. However, we did analyse the correlation between ABR click thresholds and mean IHC eGFP fluorescence in another, preliminary set of data that included different viruses at different titres. There, we were able to observe a relatively good correlation. Interestingly, some of the highest expression levels resulted in poorer threshold recovery, which could indicate harmful overexpression. Moreover, the correlation was only detected when the difference of the mean eGFP expression levels per organ was large. Furthermore, significantly less efficient ABR threshold recovery was observed in the non-injected contralateral ears, which showed a significantly lower viral expression of the transgene. In our follow-up study, we will investigate the question of dose dependence of rescue in more detail.  

      Reviewer #2 (Recommendations For The Authors): 

      -  There are two paragraphs in the results text about supplemental figure #2, which suggests that it should be moved to the main figures. 

      We would like to thank the reviewer for this suggestion. Figure S2 has now been moved to the main figures (as current Figure 5) and has been modified to accommodate the BK cluster analysis panel. The histogram with the number of ribbon synapses was removed as the data was redundant with the numbers given in the MS text.  

      -  Overall it is hard to distinguish between dark blue and black in many figures, including the dual-color asterisks.

      To improve the readability and clarity of the figures, we exchanged dark blue with magenta.  Dual-color asterisks in Fig. 3 were changed to single-color asterisks and what they refer to is explain in the figure legend.  

      -  Figure 4 legend - there is a mis-spelling of cabp in the fourth line from the bottom. 

      -  Figure 4 legend - the last line does not make sense - describes recovery as being both 'much faster' and 'slowest'.

      -  Figure 6 title - consider removing 'nearly blocked' and replacing it with 'impaired'.

      We would like to thank the reviewer for noticing these mistakes that have been corrected in the revised version, as suggested.

      -  The calculations of VDI and CDI could be better explained, specifically detailing that VDI is calculated first from currents using barium as a divalent, followed by the calculation of CDI. 

      We included an explanatory sentence in the results section as suggested and are additionally referring the readers to the methods section for the mathematical formulas.

      -  Why were two different tests (one parametric and one non-parametric) used for the Figure 3B data? 

      We performed a point-by-point-comparison of data. The choice of test was made based on the distribution and the variance of the data points. We now opted for a unified test, t test with Welch correction, which assumes that samples come from populations with normal distribution, but does not make assumption about equal variances. The outcome of these tests were similar. 

      -  The much broader tuning of the auditory nerve fibers is interesting, consider including this in a figure. 

      For recording tuning curves, we use an automated algorithm which adapts the tone burst intensity and frequency depending on the preceding results. The threshold criterion is an increase of spiking by 20Hz above spontaneous rate. This routine works fairly well in wild-type animals. However, DKO SGNs typically had very high thresholds at >80 dB across all frequencies, which can partly be explained by the fact that they had very low spike rates and did not reach that criterion. Besides tuning curve runs, we also tried systematic frequency sweeps and manual frequency control to determine a best frequency, followed by a rate intensity function at that frequency to determine “best threshold”. 

      All this was difficult, because in the DKO SGNs, sound threshold detection was challenged by the strong dependence of spiking on the duration of the preceding silent interval. A preceding stimulus outside the frequency response area or below the activation threshold of the SGN would thus improve spiking by allowing for longer recovery, while a preceding efficient stimulus would reduce it. Thus, the sound threshold determined in a rate level sweep varied depending on the interstimulus interval and possibly even on the (randomized) order at which the intensities were played. 

      A meaningful threshold measure would require long silent interstimulus intervals, i.e. a long recording time. As tuning curves require multiple threshold measures, it seemed impossible to obtain a useful dataset at high quality. As we deemed the spike rate dependence on interstimulus intervals more important than the tuning we rather focused on tone burst responses acquired at frequency/intensity combinations at which the hair cells and their synapses were maximally activated. In wild-types, these would be tone bursts at characteristic frequency or noise bursts in the saturated part of the rate intensity function, which typically has a dynamic range of 10-25dB. As we assume (based on DPOAE) that cochlear micromechanics and amplification are mostly normal in the DKOs, we hypothesize that the sensitivity and dynamic range of basilar membrane motion and  inner hair cell transduction are normal and that the increase in single unit thresholds and loss of sharp tuning are another readout of synaptic dysfunction. 

      - Figure S2 - please show separate panels for each channel, it is very difficult to make out the changes by eye in the merged panels. 

      Done.  

      - Figure S2 G - the results text stated that the BK channel clusters 'appeared' smaller - why was this not measured? 

      We have performed additional experiments to enable proper analysis of the BK channel clusters. The analysed data shows that the BK clusters are considerably larger and more abundant in the WT as compared to CaBP1/2-deficient IHCs of approx. 4-week-old mice. The results of the analysis are included in the immunohistochemistry figure (now Fig. 5) and are further commented in the results section.  

      Reviewer #3 (Recommendations For The Authors): 

      I have only a few minor points on the MS: 

      (1) Some labels in Figure 1 are too small and hard to read, e.g. y-axis in B-F. Wherever you use subscripts on the axes, the labeling needs to be larger.

      (2) Fig. 1A: the colors for CaM and CaBP1.2 are too similar, at least on my printout. Please use more distant colors.

      (3) Reference 24 should be corrected (no longer in press).

      These points have been addressed in the revised version of the MS.

    1. Author response:

      The following is the authors’ response to the previous reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      The present study provides a phylogenetic analysis of the size prefrontal areas in primates, aiming to investigate whether relative size of the rostral prefrontal cortex (frontal pole) and dorsolateral prefrontal cortex volume vary according to known ecological or social variables.

      I am very much in favor of the general approach taken in this study. Neuroimaging now allows us to obtain more detailed anatomical data in a much larger range of species than ever before and this study shows the questions that can be asked using these types of data. In general, the study is conducted with care, focusing on anatomical precision in definition of the cortical areas and using appropriate statistical techniques, such as PGLS.

      I have read the revised version of the manuscript with interest. I agree with the authors that a focus on ecological vs laboratory variables is a good one, although it might have been useful to reflect that in the title.

      I am happy to see that the authors included additional analyses using different definitions of FP and DLPFC in the supplementary material. As I said in my earlier review, the precise delineation of the areas will always be an issue of debate in studies like this, so showing the effects of different decisions in vital.

      We thank the reviewer for these positive remarks and for these very useful suggestions on the previous version of this article.

      I am sorry the authors are so dismissive of the idea of looking the models where brain size and area size are directly compared in the model, rather preferring to run separate models on brain size and area size. This seems to me a sensible suggestion.

      We agree with the reviewer 1 and the response of reviewer 3 also made it clear to us of why it was an important issue. We have therefore addressed it more thoroughly this time.

      First, we have added a new analysis, with whole brain volume included as covariate in the model accounting for regional volumes, together with the socio-ecological variables of interest. As expected given the very strong correlation across all brain measures (>90%), the effects of all socio-ecological factors disappear for both FP and DLPFC volumes when ‘whole brain’ is included as covariate. This is coherent with our previous analysis showing that the same combination of socio-ecological variables could account for the volume of FP, DLPFC and the whole brain. Nevertheless, the interpretation of these results remains difficult, because of the hidden assumptions underlying the analysis (see below).

      Second, we have clarified the theoretical reasons that made us choose absolute vs relative measures of brain volumes. In short, we understand the notion of specificity associated with relative measures, but 1) the interpretation of relative measures is confusing and 2) we have alternative ways to evaluate the specificity of the effects (which are complementary to the idea of adding whole brain volume as covariate). 

      Our goal here was to evaluate the influence of socio-ecological factors on specific brain regions, based on their known cognitive functions in laboratory conditions (working memory for the DLPFC and metacognition for the frontal pole). Thus, the null hypothesis is that socio-ecological challenges supposed to mobilize working memory and metacognition do not affect the size of the brain regions associated with these functions (respectively DLPFC and FP). This is what our analysis is testing, and from that perspective, it seems to us that direct measures are better, because within regions (across species), volumes provide a good index of neural counts (since densities are conserved), which are indicative fo the amount of computational resources available for the region. It is not the case when using relative measures, or when using the whole brain as covariate, since densities are heterogenous across brain regions (e.g. Herculano-Houzel, 2011; 2017, but see below for further details on this).

      Quantitatively, the theoretical level of specificity of the relation between brain regions and socio-ecological factors is difficult to evaluate, given that our predictions are based on the cognitive functions associated with DLPFC and FP, namely working memory and metacognition, and that each of these cognitive functions also involved other brain regions. We would actually predict that other brain regions associated with the same cognitive functions as DLPFC or FP also show a positive influence of the same socioecological variables. Given that the functional mapping of cognitive functions in the brain remains debated, it is extremely difficult to evaluate quantitatively how specific the influence of the socio-ecological factors should be on DLPFC and FP compared to the rest of the brain, in the frame of our hypothesis.

      Critically, given that FP and DLPFC show a differential sensitivity to population density, a proxy for social complexity, and that this difference is in line with laboratory studies showing a stronger implication of the FP in social cognition, we believe that there is indeed some specificity in the relation between specific regions of the PFC and socioecological variables. Thus, our results as a whole seem to indicate that the relation between prefrontal cortex regions and socio-ecological variables shows a small but significant level of specificity. We hope that the addition of the new analysis and the corresponding modifications of the introduction and discussion section will clarify this point.

      Similarly, the debate about whether area volume and number of neurons can be equated across the regions is an important one, of which they are a bit dismissive.

      We are sorry that the reviewer found us a bit dismissive on this issue, and there may have been a misunderstanding.

      Based on the literature, it is clearly established that for a given brain region, area volume provides a good proxy for the number of neurons, and it is legitimate to generalize this relation across species if neuronal densities are conserved for the region of interest (see for example Herculano-Houzel 2011, 2017 for review). It seems to be the case across primates because cytoarchitectonic maps are conserved for FP and DLPFC, at least in humans and laboratory primates (Petrides et al, 2012; Sallet et al, 2013; Gabi et al, 2016; Amiez et al, 2019). But we make no claim about the difference in number of neurons between FP and DLPFC, and we never compared regional volumes across regions (we only compared the influence of socio-ecological factors on each regional volume), so their difference in cellular density is not relevant here. As long as the neuronal density is conserved across species but within a region (DLPFC or FP), the difference in volume for that region, across species, does provide a reliable proxy for the influence of the socioecological regressor of interest (across species) on the number of neurons in that region.

      Our claims are based on the strength of the relation between 1) cross-species variability in a set of socio-ecological variables and 2) cross-species variability in neural counts in each region of interest (FP or DLPFC). Since the effects of interest relate to inter-specific differences, within a region, our only assumption is that the neural densities are conserved across distinct species for a given brain region. Again (see previous paragraph), there is reasonable evidence for that in the literature. Given that assumption, regional volumes (across species, for a given brain region) provide a good proxy for the number of neurons. Thus, the influence of a given socio-ecological variable on the interspecific differences in the volume of a single brain region provides a reliable estimate of the influence of that socio-ecological variable on the number of neurons in that region (across species), and potentially of the importance of the cognitive function associated with that region in laboratory conditions. None of our conclusions are based on direct comparison of volumes across regions, and we only compared the influence of socioecological factors (beta weights, after normalization of the variables).

      Note that this is yet another reason for not using relative measures and not including whole brain as covariate in the regression model: Given that whole brain and any specific region have a clear difference in density, and that this difference is probably not conserved across species, relative measures (or covariate analysis) cannot be used as proxies for neuronal counts (e.g. Herculano-Houzel, 2011). In other words, using the whole brain to rescale individual brain regions relies upon the assumption that the ratios of volumes (specific region/whole brain) are equivalent to the ratios of neural counts, which is not valid given the differences in densities.

      Nevertheless, I think this is an important study. I am happy that we are using imaging data to answer more wider phylogenetic questions. Combining detailed anatomy, big data, and phylogenetic statistical frameworks is a important approach.

      We really thank the reviewer for these positive remarks, and we hope that this study will indeed stimulate others using a similar approach.

      Reviewer #2 (Public Review):

      In the manuscript entitled "Linking the evolution of two prefrontal brain regions to social and foraging challenges in primates" the authors measure the volume of the frontal pole (FP, related to metacognition) and the dorsolateral prefrontal cortex (DLPFC, related to working memory) in 16 primate species to evaluate the influence of socio-ecological factors on the size of these cortical regions. The authors select 11 socio-ecological variables and use a phylogenetic generalized least squares (PGLS) approach to evaluate the joint influence of these socio-ecological variables on the neuro-anatomical variability of FP and DLPFC across the 16 selected primate species; in this way, the authors take into account the phylogenetic relations across primate species in their attempt to discover the the influence of socio-ecological variables on FP and DLPF evolution.

      The authors run their studies on brains collected from 1920 to 1970 and preserved in formalin solution. Also, they obtained data from the Mussée National d´Histoire Naturelle in Paris and from the Allen Brain Institute in California. The main findings consist in showing that the volume of the FP, the DLPFC, and the Rest of the Brain (ROB) across the 16 selected primate species is related to three socio-ecological variables: body mass, daily traveled distance, and population density. The authors conclude that metacognition and working memory are critical for foraging in primates and that FP volume is more sensitive to social constraints than DLPFC volume.

      The topic addressed in the present manuscript is relevant for understanding human brain evolution from the point of view of primate research, which, unfortunately, is a shrinking field in neuroscience. But the experimental design has two major weak points: the absence of lissencephalic primates among the selected species and the delimitation of FP and DLPFC. Also, a general theoretical and experimental frame linking evolution (phylogeny) and development (ontogeny) is lacking.

      We are sorry that the reviewer still believes that these two points are major weaknesses.

      - We have added a point on lissencephalic species in the discussion. In short, we acknowledge that our work may not be applied to lissencephalic species because they cannot be studied with our method, but on the other hand, based on laboratory data there is no evidence showing that the functional organization of the DLPFC and FP in lissencephalic primates is radically different from that of other primates (Dias et al, 1996; Roberts et al, 2007; Dureux et al, 2023; Wong et al, 2023). Therefore, there is no a priori reason to believe that not including lissencephalic primates prevents us from drawing conclusions that are valid for primates in general. Moreover, as explained in the discussion, including lissencephalic primates would require using invasive functional studies, only possible in laboratory conditions, which would not be compatible with the number of species (>15) necessary for phylogenetic studies (in particular PGLS approaches). Finally, as pointed out by the reviewer, our study is also relevant for understanding human brain evolution, and as such, including lissencephalic species should not be critical to this understanding.

      - In response to the remarks of reviewer 1 on the first version of the manuscript, we had included a new analysis in the previous version of the manuscript, to evaluate the validity of our functional maps given another set of boundaries between FP and DLPFC. But one should keep in mind that our objective here is not to provide a definitive definition of what the regions usually referred to as DLPFC and FP should be from an anatomical point of view. Rather, as our study aims at taking into account the phylogenetic relations across primate species, we chose landmarks that enable a comparison of the volume of cortex involved in metacognition (FP) and working memory (DLPFC) across species. We have also updated the discussion accordingly.

      We agree that this is a difficult point and we have always acknowledged that this was a clear limitation in our study. In the light of the functional imaging literature in humans and non-human primates, as well as the neurophysiological data in macaques, defining the functional boundary between FP and DLPFC remains a challenging issue even in very well controlled laboratory conditions. As mentioned by reviewer 1, “the precise delineation of the areas will always be an issue of debate in studies like this, so showing the effects of different decisions in vital”. Again, an additional analyses using different boundaries for FP and DLPFC was included in the supplementary material to address that issue. Now, we are not aware of solid evidence showing that the boundaries that we chose for DLPFC vs FP were wrong, and we believe that the comparison between 2 sets of measures as well as the discussion on this topic should be sufficient for the reader to assess both the strength and the limits of our conclusion. That being said, if the reviewer has any reference in mind showing better ways to delineate the functional boundary between FP and DLPFC in primates, we would be happy to include it in our manuscript.

      - The question of development, which is an important question per se,  is neither part of the hypothesis nor central for the field of comparative cognition in primates. Indeed, major studies in the field do not mention development (e.g. Byrne, 2000; Kaas, 2012; Barton, 2012). De Casien et al (2022) even showed that developmental constraints are largely irrelevant (see Claim 4 of their article): [« The functional constraints hypothesis […] predicts more complex, ‘mosaic’ patterns of change at the network level, since brain structure should evolve adaptively and in response to changing environments. It also suggests that ‘concerted’ patterns of brain evolution do not represent conclusive evidence for developmental constraints, since allometric relationships between developmentally linked or unlinked brain areas may result from selection to maintain functional connectivity. This is supported by recent computational modeling work [81], which also suggests that the value of mosaic or concerted patterns may fluctuate through time in a variable environment and that developmental coupling may not be a strong evolutionary constraint. Hence, the concept of concerted evolution can be decoupled from that of developmental constraints »].

      Finally, when studies on brain evolution and cognition mention development, it is generally to discuss energetic constraints rather than developmental mechanisms per se (Heldstab et al 2022 ; Smaers et al, 2021;  Preuss & Wise, 2021; Dunbar & Schutz, 2017; MacLean et al, 2012. Mars et al, 2018; 2021). Therefore, development does not seem to be a critical issue, neither for our article nor for the field.

      Reviewer #3 (Public Review):

      This is an interesting manuscript that addresses a longstanding debate in evolutionary biology - whether social or ecological factors are primarily responsible for the evolution of the large human brain. To address this, the authors examine the relationship between the size of two prefrontal regions involved in metacognition and working memory (DLPFC and FP) and socioecological variables across 16 primate species. I recommend major revisions to this manuscript due to: 1) a lack of clarity surrounding model construction; and 2) an inappropriate treatment of the relative importance of different predictors (due to a lack of scaling/normalization of predictor variables prior to analysis).

      We thank the reviewer for his/her remarks, and for the clarification of his /her criticism regarding the use of relative measures. We are sorry to have missed the importance of this point in the first place. We also thank the reviewer for the cited references, which were very interesting and which we have included in the discussion. As the reviewer 1 also shared these concerns, we wrote a detailed response to explain how we addressed the issue above.

      First, we did run a supplementary analysis where whole brain volume was added as covariate, together with socio-ecological variables, to account for the volume of FP or DLPFC. As expected given the very high correlation across all 3 brain measures, none of the socio-ecological variables remained significant. We have added a long paragraph in the discussion to tackle that issue. In short, we agree with the reviewer that the specificity of the effects (on a given brain region vs the rest of the brain) is a critical issue, and we acknowledge that since this is a standard in the field, it was necessary to address the issue and run this extra-analysis. But we also believe that specificity could be assessed by other means: given the differential influence of ‘population density’ on FP and DLPFC, in line with laboratory data, we believe that some of the effects that we describe do show specificity. Also, we prefer absolute measures to relative measures because they provide a better estimate of the corresponding cognitive operation, because standard allometric rules (i.e., body size or whole brain scaling) may not apply to the scaling and evolution of FP and DLPFC in primates.. Indeed, given that we use these measures as proxies of functions (metacognition for FP and working memory for DLPFC), it is clear that other parts of the brain should show the same effect since these functions are supported by entire networks that include not only our regions of interest but also other cortical areas in the parietal lobe. Thus, the extent to which the relation with socio-ecological variables should be stronger in regions of interest vs the whole brain depends upon the extent to which other regions are involved in the same cognitive function as our regions of interest, and this is clearly beyond the scope of this study. More importantly, volumetric measures are taken as proxies for the number of neurons, but this is only valid when comparing data from the same brain region (across species), but not across brain regions, since neural densities are not conserved. Thus, using relative measures (scaling with the whole brain volume) would only work if densities were conserved across brain regions, but it is not the case. From that perspective, the interpretation of absolute measures seems more straightforward, and we hope that the specificity of the effects could be evaluated using the comparison between the 3 measures (FP, DLPFC and whole brain) as well as the analysis suggested by the reviewer. We hope that the additional analysis and the updated discussion will be sufficient to cover that question, and that the reader will have all the information necessary to evaluate the level of specificity and the extent to which our findings can be interpreted.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      In my previous review of the present manuscript, I pointed out the fact that defining parts, modules, or regions of the primate cerebral cortex based on macroscopic landmarks across primate species is problematic because it prevents comparisons between gyrencephalic and lissencephalic primate species. The authors have rephrased several paragraphs in their manuscript to acknowledge that their findings do apply to gyrencephalic primates.

      I also said that "Contemporary developmental biology has showed that the selection of morphological brain features happens within severe developmental constrains. Thus, the authors need a hypothesis linking the evolutionary expansion of FP and DLPFC during development. Otherwise, the claims form the mosaic brain and modularity lack fundamental support". I insisted that the author should clarify their concept of homology of cerebral cortex parts, modules, or regions cross species (in the present manuscript, the frontal pole and the dorsolateral prefrontal cortex). Those are not trivial questions because any phylogenetic explanation of brain region expansion in contemporary phylogenetic and evolutionary biology must be rooted in evolutionary developmental biology. In this regard, the authors could have discussed their findings in the frame of contemporary studies of cerebral cortex evolution and development, but, instead, they have rejected my criticism just saying that they are "not relevant here" or "clearly beyond the scope of this paper".

      The question of development, which is an important question per se, is neither part of the hypothesis nor central for the field of comparative cognition in primates. Indeed, the major studies in the field do not mention development and some even showed that developmental constraints were not relevant (see De Casien et al., 2022 and details in our response to the public review). When studies on brain evolution and cognition mention development, it is generally to discuss energetic constraints rather than developmental mechanisms per se (Heldstab et al 2022 ; Smaers et al, 2021;  Preuss & Wise, 2021; Dunbar & Schutz, 2017;  MacLean et al, 2012. Mars et al, 2018; 2021).

      If the other reviewers agree, the authors are free to publish in eLife their correlations in a vacuum of evolutionary developmental biology interpretation. I just disagree. Explanations of neural circuit evolution in primates and other mammalian species should tend to standards like the review in this link: https://royalsocietypublishing.org/doi/full/10.1098/ rstb.2020.0522

      In this article, Paul Cizek (a brilliant neurophysiologist) speculates on potential evolutionary mechanisms for some primate brain functions, but there is surprisingly very little reference to the existing literature on primate evolution and cognition. There is virtually no mention of studies that involve a large enough number of species to address evolutionary processes and/or a comparison with fossils and/or an evaluation of specific socio-ecological evolutionary constraints. Most of the cited literature refers to laboratory studies on brain anatomy of a handful of species, and their relevance for evolution remains to be evaluated. These ideas are very interesting and they could definitely provide an original perspective on evolution, but they are mostly based on speculations from laboratory studies, rather than from extensive comparative studies. This paper is interesting for understanding developmental mechanisms and their constraints on neurophysiological processes in laboratory conditions, but we do not think that it would fit it in the framework of our paper as it goes far beyond our main topic.

      Reviewer #3 (Recommendations For The Authors):

      Yes, I am suggesting that the authors also include analyses with brain size (rather than body size) as a covariate to evaluate the effects of other variables in the model over and above the effect on brain size. In a very simplified theoretical scenario: two species have the same body sizes, but species A has a larger brain and therefore a larger FP. In this case, species A has a larger FP because of brain allometric patterns, and models including body size as a covariate would link FP size and socioecological variables characteristic of species A (and others like it). However, perhaps the FP of species A is actually smaller than expected for its brain size, while the FP of species B is larger than expected for its brain size.

      As explained in our response to the public review, we did run this analysis and we agree with the reviewer’s point from a practical point of view: it is important to know the extent to which the relation with a set of socio-ecological variables is specific of the region of interest, vs less specific and present for other brain regions. Again, we are sorry to not have understood that earlier, and we acknowledge that since it is a standard in the field, it needs to be addressed thoroughly.

      We understand that the scaling intuition, and the need to get a reference point for volumetric measures, but here the volume of each brain region is taken as a proxy for the number of neurons and therefore for the region’s computational capacities. Since, for a given brain region (FP or DLPFC) the neural densities seem to be well conserved across species, comparing regional volumes across species provides a good proxy for the contrast (across species) in neural counts for that region. All we predicted was that for a given brain region, associated with a given cognitive operation, the volume (number of neurons) would be greater in species for which socio-ecological constraints potentially involving that specific cognitive operation were greater. We do not understand how or why the rest of the brain would change this interpretation (of course, as discussed just above, beyond the question of specificity). And using whole brain volume as a scaling measure is problematic because the whole brain density is very different from the density of these regions of the prefrontal cortex (see above for further details). Again, we acknowledge that allometric patterns exist, and we understand how they can be interpreted, but we do not understand how it could prove or disprove our hypothesis (brain regions involved in specific cognitive operations are influenced by a specific set of socio-ecological variables). When using volumes as a proxy for computational capacities, the theoretical implications of scaling  procedures might be problematic. For example, it implies that the computational capacities of a given brain region are scaled by the rest of the brain. All other things being equal, the computational capacities of a given brain region, taken as the number of neurons, should decrease when the size of the rest of the brain increases. But to our knowledge there is no evidence for that in the literature. Clearly these are very challenging issues, and our position was to take absolute measures because they do not rely upon hidden assumptions regarding allometric relations and their consequence on cognition.

      But since we definitely understand that scaling is a reference in the field, we have not only completed the corresponding analysis (including the whole brain as a covariate, together with socio-ecological variables) but also expended the discussion to address this issue in detail. We hope that between this new analysis and the comparison of effects between non-scaled measures of FP, DLPFC and the whole brain, the reader will be able to judge the specificity of the effect.

      Models including brain (instead of body) size would instead link FP size and socioecological variables characteristic of species B (and others like it). This approach is supported by a large body of literature linking comparative variation in the relative size of specific brain regions (i.e., relative to brain size) to behavioral variation across species - e.g., relative size of visual/olfactory brain areas and diurnality/nocturnality in primates (Barton et al. 1995), relative size of the hippocampus and food caching in birds (Krebs et al. 1989).

      Barton, R., Purvis, A., & Harvey, P. H. (1995). Evolutionary radiation of visual and olfactory brain systems in primates, bats and insectivores. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 348(1326), 381-392.

      Krebs, J. R., Sherry, D. F., Healy, S. D., Perry, V. H., & Vaccarino, A. L. (1989). Hippocampal specialization of food-storing birds. Proceedings of the National Academy of Sciences, 86(4), 1388-1392. 

      We are grateful to the reviewer for mentioning these very interesting articles, and more generally for helping us to understand this issue and clarify the related discussion. Again, we understand the scaling principle but the fact that these methods provide interesting results does not make other approaches (such as ours) wrong or irrelevant. Since we have used both our original approach and the standard version as requested by the reviewer, the reader should be able to get a clear picture of the measures and of their theoretical implications. We sincerely hope that the present version of the paper will be satisfactory, not only because it is clearer, but also because it might stimulate further discussion on this complex question.

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, Setogawa et al. employ an auditory discrimination task in freely moving rats, coupled with small animal imaging, electrophysiological recordings, and pharmacological inhibition/lesioning experiments to better understand the role of two striatal subregions: the anterior Dorsal Lateral Striatum (aDLS) and the posterior Ventrolateral Striatum (pVLS), during auditory discrimination learning. Attempting to better understand the contribution of different striatal subregions to sensory discrimination learning strikes me as a highly relevant and timely question, and the data presented in this study are certainly of major interest to the field. The authors have set up a robust behavioral task and systematically tackled the question about a striatal role in learning with multiple observational and manipulative techniques. Additionally, the structured approach the authors take by using neuroimaging to inform their pharmacological manipulation experiments and electrophysiological recordings is a strength.

      However, the results as they are currently presented are not easy to follow and could use some restructuring, especially the electrophysiology. Also, the main conclusion that the authors draw from the data, that aDLS and pVLS contribute to different phases of discrimination learning and influence the animal's response strategy in different ways, is not strongly supported by the data and deserves some additional caveats and limitations of the study in the discussion.

      Strengths:

      See above. In addition, the electrophysiology data is a major strength.

      Weaknesses:

      (1) The authors have rigorously used PET neuroimaging, which is an interesting non-invasive method to track brain activity during behavioral states. However, in the case of a freely moving behavior where the scans are performed ~30 minutes after the behavioral task, it is unclear what conclusions can be drawn about task-specific brain activity. The study hinges on the neuroimaging findings that both areas of the lateral striatum (aDLS and pVLS) show increased activity during acquisition, but the DMS shows a reduction in activity during the late stages of behavior, and some of these findings are later validated with complementary experiments. However, the limitations of this technique can be further elaborated on in the discussion and the conclusions.

      a) In commenting on the unilateral shifts in brain striatal activity during behavior, the authors use the single lever task as a control, where many variables affecting neuronal activity might be different than in the discriminatory task. The study might be better served using Day 2 measurements as a control against which to compare activity of all other sessions since the task structures are similar.<br /> b) From the plots in J, K, and L, it seems that shifts in activity in the different substructures are not unilateral but consistently bilateral, in contrast to what is mentioned in the text. Possibly the text reflects comparisons to the single lever task, and here again, I would emphasize comparing within the same task.

      (2) In Figure 2, the authors present compelling data that chronic excitotoxic lesions with ibotenic acid in the aDLS, pVLS, and DMS produce differential effects on discrimination learning. However, the significant reduction in success rate of performance happens as early as Day 6 in both IBO groups in both aDLS and pVLS mice. This would seem to agree with conclusions drawn about the role of aDLS in the middle stages of learning in Figure 2, but not the pVLS, which only shows an increased activity during the late stages of the behavior.

      (3) In Figure 4, the authors show interesting data with transient inactivation of subregions of the striatum with muscimol, validating their findings that the aDLS mediates the middle and the pVLS the late stages of learning, and the function of each area serves different strategies. However, the inference that aDLS inactivation suppresses the WSW strategy "moderately" is not reflected in the formal statistical value p=0.06. While there still may be a subtle effect, the authors would need to revise their conclusions appropriately to reflect the data. In addition, the authors could try a direct comparison between the success rate during muscimol inhibition in the mid-learning session between the aDLS and pVLS-treated groups in Figure 4C (middle) and 4D (middle). If this comparison is not significant, the authors should be careful to claim that inhibition of these two areas differentially affects behavior.

      (4) The authors have used in-vivo electrophysiological techniques to systematically investigate the roles of the aDLS and the pVLS in discriminatory learning, and have done a thorough analysis of responses with each phase of behavior over the course of learning. This is a commendable and extremely informative dataset and is a strength of the study. However, the result could be better organized following the sequence of events of the behavioral task to give the reader an easier structure to follow. Ideally, this would involve an individual figure to compare the responses in both areas to Cue, Lever Press, Reward Sound, and First Lick (in this order).

      (5) An important conceptual point presented in the study is that the aDLS neurons, with learning, show a reduction in firing rates and responsiveness to the first lick as well as the behavioral outcome, and don't play a role in other task-related events such as cue onset. However, the neuroimaging data in Figure 2 seems to suggest a transient enhancement of aDLS activity in the mid-stage of discriminatory learning, that is not reflected in the electrophysiology data. Is there an explanation for this difference?

      (6) A significant finding of the study is that CO-HR and CO-LL responses are strikingly obvious in the pVLS, but not in the aDLS, in line with the literature that the posterior (sensory) striatum processes sound. This study also shows that responses to the high-frequency tone indicating a correct right-lever choice increase with learning in contrast to the low-frequency tone responses. To further address whether this difference arises from the task contingency, and not from the frequency representation of the pVLS, an important control would be to switch the cue-response association in a separate group of mice, such that high-frequency tones require a left lever press and vice versa. This would also help tease apart task-evoked responses in the aDLS, as I am given to understand all the recording sites were in the left striatum.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Recommendations For The Authors): 

      The authors should perform experiments to answer this question: does Cav3 transcription increase in the G369i-KI, or is there instead some post-transcriptional modulation that permits surface expression of functional Cav3-containing channels in the absence of typical HVA Ca conductances? Also, the authors should determine whether G369i-KI can mediate Ca2+ release from intracellular stores and whether release from stores is upregulated as Cav3-containing channel expression (or function) is increased. 

      We performed transcriptomic (drop-seq) analysis to test whether a Cav3 subtype is upregulated in cones of G369i KI mice. These experiments show that, consistent with previous studies (PMID 35803735, 26000488), Cacna1h appears to be the primary Cav3 subtype expressed mouse cones. However, as shown in new Supp.Fig.S3, there was no significant difference in the levels of Cacna1h transcripts in WT and G369i KI cones. Therefore, we propose that there may be some post-transcriptional modification, or alteration in a pathway that regulates channel availability, that enables the contribution Cav3 channels to the whole-cell Ca2+ current in the absence of functional Cav1.4 channels cones.

      We also performed Ca2+ imaging experiments in WT vs G369i KI cone terminals to assess whether the diminutive Cav3 current in G369i KI cone terminals may be compensated by upregulation of a Ca2+ signal such as from intracellular stores. Arguing against this possibility, depolarization-evoked Ca2+ signals in G369i KI cones were dramatically reduced compared to WT cones (new Fig.9). 

      Reviewer #2 (Recommendations For The Authors): 

      Major points- 

      (1) It is stated in too many places that cone features in the Cav1.4 knock-in are "intact", preserved, or spared, but this representation is not accurate. There are two instances in this study that qualify as intact when comparing KI to WT: 1) the photopic a-waves in the Cav1.4 knock-in (also demonstrated in Maddox et al 2020) and 2) latency to the platform (current MS, Figure 7f). However, in the numerous instances listed below, the authors compared the Cav1.4 knock-in to the Cav1.4 knock-out, and then referred to the KI as exhibiting intact responses. The reference point for intactness needs to be wildtype, as appropriately done for Figures 2 and 3, and when comparing the KI to the KO the phrasing should be altered; for example: "the KI was spared from the extensive degeneration witnessed in the KO....". 

      In most cases, we clearly note that there are key differences in the WT and the G369i KI cone synapses, which highlight the importance of Cav1.4-specific Ca2+ signals for certain aspects of the cone synapse. We disagree with the reviewer on the point that we did not often use the WT as a reference since most of our experiments involved comparisons of only WT and G369i KI (Figs. 3-6) or WT, G369i KI, and Cav1.4 KO (Figs.1,7—and in these cases comparisons specifically between WT and G369i KI mice were included). We used “intact” as a descriptor for G369i KI cone synapses since these are actually present, albeit abnormal in the G369i KI retina, whereas cone synapses are completely absent in the Cav1.4 KO retina. To avoid confusion, we modified our use of “intact” and “preserved” where appropriate.

      A. Abstract, line 34 to 35: ".......preserved in KI but not in KO.". 

      Abstract was rewritten and this line was removed.

      B. Line 36: "....synaptogenesis remains intact". The MS documents many differences in the morphology of KI and WT cones (immunofluorescence and electron microscopy data), which is counter to an intact phenotype. 

      The sentence was: “In CSNB2, we propose that Cav3 channels maintain cone synaptic output provided that the Ca2+-independent role of Cav1.4 in cone synaptogenesis remains intact.”

      Here the meaning of “intact” refers to the Ca2+ -independent role of Cav1.4, not synapses. Thus, we have left the sentence unchanged.

      C. This strikes the right balance, lines 67 to 68: "....although greatly impaired.....". 

      D. Line 149, "Cone signaling to a postsynaptic partner is intact in G369i KI mice". This description is inaccurate. Here there is only WT and KI, and the text reads as follows in line 162: "terminals (Figure 6b). The ON and OFF components of EPSCs in G369i KI HCs were measurable, although lower in amplitude than in WT (Figure 6a,b)." Neither "measurable" nor "lower in amplitude" meet the definition of "intact", and actual numerical values are lacking in the text. 

      We have added results showing that there are no light responses in the Cav1.4 KO horizontal cells and have modified the sentence to: “Cone synaptic responses are present in horizontal cells of G369i KI but not Cav1.4 KO mice”. 

      We have modified discussion of these results as (line 210-213): “Consistent with the lack of mature ribbons and abnormal cone pedicles (Fig.1), HC light responses were negligible in Cav1.4 KO mice (Fig.8a,b). In contrast, the ON and OFF responses were present in G369i KI HCs although significantly lower in amplitude than in WT HCs (Fig. 8a,b).”

      E. Please add a legend to Figure 6a to indicate the intensities. The shape of the KI responses is different from the control which is worthy of discussion: i) there is no clear cessation of HC EPSCs in the KI during the light ON period (when release stops, Im fluctuations should be minimal), and ii) the "peaked" appearances of the initial 500ms of the On and Off periods are very similar in shape for the KI (hard to interpret in the same fashion as a control response). How were the On and Off amplitudes analyzed? Furthermore, the OFF current is not summarized in Figure 6D, but should not this be when Cav3 should be opening and triggering release: Off response-EPSC? Lastly, Figure 6b,d shows a ~70% reduction in On-current in the KI, and the KI example of 6b an 80% reduction in Off current compared to WT. Yet, the only place asterisks are used to indicate sig diff is the DNQX data within each genotype in Fig 6d. These data cannot be described as showing "intact" KI responses, and the absence of numerical and statistical values needs to be addressed. 

      New Fig.8a depicting the horizontal cell light responses has been modified to include the legend indicating light intensities. The ON and OFF amplitudes were analyzed as the peak current amplitudes. This information has been added to the legend.

      The reviewer is correct in that the OFF response represents the EPSC whereas the ON response represents the decrease in the EPSC with light. To avoid confusion, we changed the y axis label for the averaged data to read ON or OFF “response” rather than “current” in new Fig.8b.

      As the reviewer suggests, the more transient nature of the KI response during the light ON period could result from aberrant continuation of vesicular release during the light-induced hyperpolarization of cones in the KI mice, in contrast to the prolonged suppression of release by light which is evident in the WT responses. We speculated on this difference as follows (lines 237-241):

      “In addition to its smaller amplitude, the transient nature of the ON response in G369i KI HCs suggested inadequate cessation of cone glutamate release by light (Fig.8b). Slow deactivation of Cav3 channels and/or their activation at negative voltages20 could give rise to Ca2+ signals that support release following light-induced hyperpolarization of G369i KI cones.”

      We added astericks to new Fig.8b,d indicating statistical differences and description of the tests in the legend.

      F. line 168 the section titled "Light responses of bipolar cells and visual behavior is spared in G369i KI but not Cav1.4 KO mice". 

      Changed to: “Light responses of bipolar cells and visual behavior are present in G369i KI but not Cav1.4 KO mice”

      Last sentence of erg results, 189-190: "These results suggest that cone-to-CBC signaling is intact in G369i KI mice.". "Spared and intact" are not accurate descriptions. The ERG data presented here shows massive differences between WT and the KI, except in the instance of awaves. 

      This sentence was removed.

      As for Figure 6, the results text related to Figure 7a-d does not present real numbers for ERG responses, and there is no indication of significant differences there or in the Figure panels. For instance, in Figure 7b, b-waves are KI are comparable to KO, except at the two highest-intensity flashes that show KI responses ~20% the amplitude of WT. Presentation of KI and KO data on a 6- to 10-fold expanded scale higher than WT can be misleading: a quick read of these Figure panels might make one incorrectly conclude that the KI is intact while the KO is impaired when compared to WT. The Methods section needs more details on the ERG analysis (e.g. any filtering out of oscillatory potentials when measuring b-wave, and what was the allowable range of time-to-peak for b-wave amplitude, etc..). 

      The vertical scaling of the ERG results in new Fig.10c,d has been changed so as to reflect clearly diminished responses of the KO and KI vs the WT. Further details regarding the ERG analysis was added to the Methods section.

      G. Can you point to other studies that have used the "visible platform swim test" used in Figure 7e, f, and specify further how mice were dark/light adapted prior to the recordings? 

      As referenced in the Methods, original line 674, the methods we used for the swim test were described in our previous study (PMID 29875267). Other studies that have used this assay include PMIDs: 28262416, 26402607.

      (2) The Maddox et al 2020 study does not safely address whether rods have a residual T-type Ca2+ current in the Cav 1.4 KO or KI. The study showed that membrane currents measured from rods in the KI and KO retina were distinct from WT, supporting their claim that L-type Ca2+ current is absent in the KI and KO. However, the recordings had shortcomings that challenge the analysis of Ca2+ currents: i) collected at room temp (22-24{degree sign}C), ii) at an unknown distance from the terminal (uncertain voltage clamp), iii) with a very slow voltage ramp rate that is not suitable for probing T-type currents (Figure 1d Maddox 2020, 140 mV over 1 sec: 7msec/1mV), and iv) at a signal-to-noise that does not allow to resolve a membrane current under 1 pA (avg wt rod Ca2+ current was -3.5 pA, and line noise ~1pA peak-to-peak in Maddox 2020). Suggestion: say T-type currents were not probed in Maddox et al 2020, but Davison et al 2022 did not find PCR signal for Cav3.2 in rods. 

      We disagree that recordings in the Maddox 2020 study were not sufficient to uncover a T-type current. The voltage ramps in that study were not much slower than that of the Davison et al. 2022 study (they used 0.19 mV/ms). Moreover, in new Supp. Fig.S1, we show that like the slower voltage ramp (0.15 mV/ms) used in the prior study of G369i KI rods, the voltage ramps we used in the present study (0.5 mV/ms), which clearly evoke currents with T-type properties in G369i KI cones (Fig.2a,b, Fig.3a,b) do not evoke currents in WT or G369i KI rods.  

      Minor comments. 

      (1) Suggestion: add an overview panel to Figure 1 that shows the rod terminals in the KI. The problem is that cropping out the ribbon and active zone signals from rods, to highlight cones, can give the impression that the cones are partially spared in the KI, and the rods are not spared at all. (yet you nicely clarify this in Figure 4 and in the legend and text, etc.). 

      We chose to modify the legend with this information as in Fig.4 rather than modify the figure.

      (2) Mouse wt cone Ca2+ currents look like L-type currents, as do your monkey and squirrel cone recordings, and also much like those of mouse rods (see Figure S5, Hagiwara et al., 2018 or Grabner and Moser 2021). Your pharm data from mice and squirrels further supports your conclusion, and certainly took much effort. Davison et al 2022 J Neurosci showed PCR results that support their claim that a Cav3 current exists in wt cones. Questions: 1) have you tried PCR? 2) Can you offer more details on what Cav3 KO you tried and what antibodies failed to confirm the KO? As the authors know, one complication is that the deletion of one Cav can be compensated for by the expression of a new Cav. There are 3 types of Cav3s and removal of one type may be compensated for by another Cav3. 

      We have included drop-seq data (new Supp.Fig.S3) implicating Cav3.2 as the main Cav3 subtype in cones and have modified our discussion of these results accordingly. These experiments did not reveal any changes in Cav3 subtype expression in G369i KI vs WT cones.

      (3) Lines 95/96- onward, spend more time telling the story. When working out the biophysical and pharmacological behavior of the Ca2+ currents, you might want to initially refer to the membrane current as a membrane current, and then state how your voltage protocols, intra- and extra-cell solutions, and drugs helped you verify 1) L-type and 2) T-type Ca2+ currents. 

      We have modified the text with more detail.

      (4) If data is in hand, add a ramp I-V to Figure S2, which shows the response of the ground squirrel cone. The steps in S2a are excellent for making your point that a transient current is missing, and the bipolar is a great control to illustrate ML218 works. However, a comparison of a squirrel cone ramp to a bipolar ramp response could complete the figure. 

      See Reponse to #5 below.

      (5) Consider moving Supplementary Figures S2 and S3 to the main text; these are highly relevant to the story, novel, and well-executed. 

      Fig.S2 and S3 were added as new Figs.4,5. The new Fig.4 includes voltage ramps in ground squirrel cones (panel a) to compare with the bipolar data (panel f).

      (6) The nice electron microscopy reconstructions are not elaborated on in any detail, and there is no mention of ribbon size. Is the resolution sufficient to estimate ribbon size, the number of synaptic vesicles around the ribbon and in the adjacent cytosol? The images indicate major changes in the morphology of the terminals. Is the glial envelope similar in WT and KI? 

      Since ribbons were quantified extensively in the confocal analyses in Fig.6, we felt it unnecessary to add this to the EM analysis which focused mainly on aspects of 3D structure (i.e., arrangement of ribbons, postsynaptic wiring, cone pedicle morphology). We added further discussion of the change in morphology of the G369i KI cone pedicle (lines 200-203): “Compared to WT, ribbons in G369i KI pedicles appeared disorganized and were often parallel rather than perpendicular to the presynaptic membrane (Fig.7a-c). Consistent with our confocal analyses (Fig.1), G369i KI cone pedicles extended telodendria in multiple directions rather than just apically (Fig. 7a).”

      While we did not opt to characterize the glial envelope in WT cones, we did add an analysis of synaptic vesicles around ribbons to Table 2.

      (7) Discussion line 250: "we found no evidence for a functional contribution of Cav3 in our recordings of cones in WT mice (Figures. 2,3), ground squirrels, or macaque (Supplementary Figures S2 and S3).". I would not use "functional" in this context because when comparing your work to Davison et al 2022, they defined functional as a separate response component driven by Cav3. For instance, they examined the influence of their T-type current on exocytosis (by membrane capacitance) and other features like spiking Ca2+ transients. Suggestion: substitute functional with "detectable", and say "we found no detectable Cav currents". Or if you had Ttype staining, but not T-type Ca2+ currents, then say "no functional current even though there is staining...". 

      We have modified the text as (lines 336-338): “However, in contrast to recordings of WT mouse cone pedicles in a previous study21, we found no evidence for Cav3-mediated currents in somatic recordings of cones in WT mice (Figs.2,3).”

      We propose an alternative interpretation of the results in the Davison et al study concerning the conclusion that Cav3 channels contribute to Ca2+ spikes and exocytosis. That study used 100 µM Ni2+ to block a “T-type” contribution to spike activity in cones. In their Figs.4,5, the spikes are suppressed by 100 µM Ni2+ and 10 µM nifedipine, a Cav1 antagonist, and spared by the T-type selective drug Z944. This is problematic for several reasons. First, as shown by the authors

      (their Fig.2A1,A2) and others (PMID: 15541900), 100 µM Ni2+ inhibits Cav1-type currents in photoreceptors. Second, Z944 potentiates Cav1 current in their mouse cones (their Fig.2C1,C2). Thus, both reagents are suboptimal for dissecting the contribution of either Cav subtype to spiking activity. With respect to Cav3 channels and exocytosis, these authors interpreted a reduction in exocytosis upon holding at -39 mV compared to at -69 mV as indicating a loss of a T-type driven component of release. However, Cav1 channel inactivation (PMID: 12473074) could lead to the observed reduction in exocytosis at -30 mV.

      (8) Additional literature related to your Intro and Discussion. Regarding CSNB2, related mutations of active zone proteins, and what happens to Ca2+ currents when ribbons are deleted, you might want to consider the following studies that measure Ca2+ currents from rods: conditional KO of RIM1/2 (Grabner et al 2015 JN), KO of ELKS1/2 (Hagiwara et al, 2018 JCB), and KO of Ribeye (Grabner and Moser eLife 2021). In these studies, the Cav currents were absent in rods of the ELKS1/2 DKO, strongly reduced (80%) in the RIM1/2DKO, but altered in more subtle ways (activation-inactivation) without significantly changing steady-state Ca2+ current in the Ribeye KO. This does not seem to support some of the arguments you have made in the Introduction and Discussion regarding ribbon size and Ca2+ currents, yet the suggested literature is related to the topic at hand. 

      A description of these synaptic proteins as potential mediators of the effect of Cav1.4 on ribbon morphogenesis was added to the Discussion, lines 325-327.

      (9) Line 129: "Along with the major constituents of the ribbon, CtBP2, and RIBEYE", for clarity Ribeye has two domains, one that is identical to CtBP2 (B-domain) and the unique Ribeye domain (A-domain) that is only expressed at ribbon synapses. And, Piccolino is also embedded in the ribbon (Brandstaetter lab, Wichmann/Moser labs). In other words, Ribeye and Piccolino are the major constituents of the ribbon. 

      To avoid confusion, we simply mention Ctbp2 and RIBEYE in the context of the corresponding antibodies that were used to label ribbons.

      (10) Abstract: consider to rephrase "Ca2+-independent role of Cav1.4" by "Ca2+-permeationindependent role of Cav1.4" or alike 

      Sentence changed to: “In CSNB2, we propose that Cav3 channels maintain cone synaptic output provided that the nonconducting role of Cav1.4 in cone synaptogenesis remains intact.”

      Reviewer #3 (Recommendations For The Authors): 

      Cav1.4 voltage-gated calcium channels play an important role in neurotransmission at mammalian photoreceptor synapses. Mutations in the CACNA1f gene lead to congenital stationary night blindness that particularly affects the rod pathway. Mouse Cav1.4 knockout and Cav1.4 knockin models suggest that Cav1.4 is also important for the cone pathway. Deletion of Cav1.4 in the knockout models leads to signaling malfunctions and to abundant morphological re-arrangements of the synapse suggesting that the channel not only has a role in the influx of Ca2+ but also in the morphological organization of the photoreceptor synapse. Of note, also additional Cav-channels have been previously detected in cone synapses by different groups, including L-type Cav1.3 (Wu et al., 2007; pmid; Kersten et al., 2020; pmid), and also T-type Cav3.2 (Davison et al., 2021; pmid 35803735). 

      In order to study a conductivity-independent role of Cav1.4 in the morphological organization of photoreceptor synapses, the authors generated the knockin (KI) mouse Cav1.4 G369i in a previous study (Maddox et al., eLife 2020; pmid 32940604). The Cav1.4 G369i KI channel no longer works as a Ca2+-conducting channel due to the insertion of a glycine in the pore-forming unit (Madox et al. elife 2020; pmid 32940604). In this previous study (Madox et al. elife 2020; pmid 32940604), the authors analyzed Cav1.4 G369i in rod photoreceptor synapses. In the present study, the authors analyzed cone synapses in this KI mouse. 

      For this purpose, the authors performed a comprehensive set of experimental methods

      including immunohistochemistry with antibodies (also with quantitative analyses), electrophysiological measurements of presynaptic Ca2+ currents from cone photoreceptors in the presence/absence of inhibitors of L-type- and T-type- calcium channels, electron microscopy (FIB-SEM), ERG recordings and visual behavior tests of the Cav G369i KI in comparison to the Cav1.4 knockout and wild-type control mice. 

      The authors found that the non-conducting Cav channel is properly localized in cone synapses and demonstrated that there are no gross morphological alterations (e.g., sprouting of postsynaptic components that are typically observed in the Cav1.4 knockout). These findings demonstrate that cone synaptogenesis relies on the presence of Cav1.4 protein but not on its Ca2+ conductivity. This result, obtained at cone synapses in the present study, is similar to the previously reported results observed for rod synapses (Maddox et al., eLife 2020, pmid 32940604). No further mechanistic insights or molecular mechanisms were provided that demonstrated how the presence of the Cav channels could orchestrate the building of the cone synapse. 

      We respectfully disagree regarding the mechanistic advance of our study. As indicated by Reviewer 2, a major advance of our study is in providing a mechanism that can explain the longstanding conundrum that congenital stationary night blindness type 2 mutations that would be expected to severely compromise Cav1.4 function do not produce complete blindness. Our study provides an important contrast to the Maddox et al 2020 study in showing that rods and cones respond differentially to loss of Cav1.4 function, which is also relevant to the visual phenotypes of CSNB2. How the presence of Cav1.4 orchestrates cone synaptogenesis is an important topic that is outside the scope of our present study.

      In the present study, the authors also propose a homeostatic switch from L-type to (newly occurring) T-type calcium channels in the Cav1.4 G369i KI mouse as a consequence of the deficient calcium channel conductivity in the Cav1.4 G369i Cav1.4 KI mouse. In cones of the Cav1.4 G369i, the high-voltage activated, L-type Ca2+-entry was abolished, in agreement with their previous paper (Maddox et al., eLife 2020, pmid 32940604). The authors found a lowvoltage activated Ca2+ current instead that they assigned to T-type Ca2+-currents based on pharmacological inhibitor experiments. T-type Ca2+-currents/channels were already previously identified in other studies by independent groups and independent techniques

      (electrophysiology, RT-PCR, single-cell sequencing) in cones of wild-type mice (Davison et al.,

      2021, pmid 35803735; Macosko et al., 2015, pmid 26000488; Williams et al., 2022, pmid 35650675). In the present manuscript (Figures 3a/b), the authors also observed a low-voltage activated, T-type like current in cones of wild-type mice, that is isradipine-resistant and affected by the T-type inhibitor ML218. This finding appears compatible with a T-type-like current in wildtype cones and is consistent with the published data mentioned above, although the authors interpret this data in a different way in the discussion. 

      Due to the noise inherent in whole cell voltage clamp measurements and some crossover effects in the pharmacology, we cannot completely exclude the presence of a T-type current in WT mouse cones. However, our results very clearly support a conclusion opposite to that stated by the reviewer. Namely, if WT mouse cones have T-type Ca currents, then they are far smaller than those in the Cav1.4 G369i KI and KO cones. In particular, while we identified message for Cav3.2 in WT mouse cones, we were unable to identify a functional T-type current by either voltage clamp measurements or pharmacology. See below for a detailed rebuttal.

      This proposal of a homeostatic switch is not convincingly supported in this reviewer's opinion

      (for further details, please see below). Furthermore, no data on possible molecular mechanisms were provided that would support such a proposal of a homeostatic switch of calcium channels. No mechanistic/molecular insights were provided for a proposed homeostatic switch between Ltype to T-type channels that the authors propose to occur between wild-type and Cav1.4 G369i as a consequence of conduction-deficient Cav1.4 G369i channels. Is this e.g. based on posttranslational modifications that switch on T-type channels or regulation at the transcriptional level inducing expression of T-type calcium channel or on other mechanisms? The authors remain descriptive with their central hypotheses. No molecular mechanisms/signaling pathways were provided that would support the idea of such a homeostatic switch. 

      Homeostatic plasticity refers to the maintenance of neuronal function in response to some perturbation in neuronal activity and can result from changes in the expression of ion channel genes (PMID: 36377048, 32747440, 19778903) or regulatory pathways that modulate ion channels (PMID: 15051886, 32492405). We present multiple lines of evidence showing that Cav3 currents appear in cones upon genetically induced Cav1.4 loss of function and can support cone synaptic responses and visual behavior if cone synapse structure is maintained. Our new transcriptomic studies show no difference between levels of Cav3 channel transcripts in WT and G369i KI cones, suggesting that the appearance of the Cav3 currents in G369i KI cones does not result from an increase in Cav3 gene expression. We are currently investigating our transcriptomic dataset to determine if Cav3 regulatory pathways are upregulated in G369i KI cones and will present this in a follow-up study.

      The authors show residual photopic signaling in the non-conducting Cav1.4 G369i KI mouse as judged by the recording of postsynaptic currents, ERG recordings and visual behavior tests though in a reduced manner. The residual cone-based signaling could be based on the nonaffected T-type Ca2+ channel conductivity in cone synapses. Given that the L-type current through Cav1.4 is gone in the Cav1.4 G369i KI as previously shown (Maddox et al., 2020, pmid 32940604), the T-type calcium current will remain. However as discussed above, this does not necessarily support the idea of a homeostatic switch. 

      A major point which we highlighted with new results is that despite the expression of Cav3 transcripts in WT mouse cones, Cav3 channels do not contribute to the cone Ca2+ current. This is at odds with the Davison et al study (PMID: 35803735, see our response to Reviewer 2, pt 7 for caveats of this study), but our results convincingly show that the Cav3 current appears only when Cav1.4 is genetically inactivated. Pharmacological or electrophysiological methods that should reveal the presence of Cav3 currents do not change the properties of the Ca2+ current in cones of WT mice, ground squirrel, or macaque:

      • Figs.2-4: Voltage steps to -40 mV (Fig 2e) that activate a sizeable T-current in G369i KI mouse cones produce a negligible transient at pulse onset in WT mouse cones. Similarly, transient currents that are obvious in G369i KI mouse cones during the final step to -30 mV are absent in WT cones.  When we block Cav1.4 with isradipine either in cones of WT mice or ground squirrel, the current that remains does not resemble a Cav3 current but rather a scaled down version of the L-type current. ML218, which readily blocks Cav3 channels in HEK293T cells and in G369i KI cones, has only minor effects in cones of WT mice and ground squirrel; these effects of ML218 can be attributed to non-specific actions on Cav1.4 (new Supp.Fig.S2). New Fig.4 (moved from the supplementary data to the main article) clearly shows that the ML218-sensitive current in ground squirrel cones exhibits properties of Cav1.4 not Cav3 channels. 

      • Figs.2,5: Holding voltages that inactivate Cav3 channels have no effect on the Ca2+ current in cones of WT mice or macaque (recordings of macaque cones were moved from the supplement to the main article as new Fig.5).

      In Figure 4 the authors measured an increase in the size of the active zone (as judged by the size of the bassoon cluster) and of the synaptic ribbons in the Cav1.4 G369i. A mechanistic explanation for this phenomenon was not provided and the underlying molecular mechanisms were not unraveled. 

      The FIB-SEM data uncover some ultrastructural alteration/misalignments of the synaptic ribbons and misalignments of the regular arrangement of the postsynaptic dendrites in the G369i KI mice. Also concerning this observation, the study remains descriptive and does not reveal the underlying mechanisms as it would be expected for eLife. 

      We respectfully disagree on the descriptive nature of our study and the need for a full characterization of the molecular mechanism underlying the cone synaptic defects in the G369i KI mouse.   

      An important study in the field (Zanetti et al., Sci. Rep. 2021; pmid 33526839) should be also cited that used a gain-of-function mutation of Cav1.4 to analyze its functional and structural role in the cone pathway. 

      We have added citation of this paper to the Discussion (lines 354-356).

      In conclusion, the study has been expertly performed but remains descriptive without deciphering the underlying molecular mechanisms of the observed phenomena, including the proposed homeostatic switch of synaptic calcium channels. Furthermore, a relevant part of the data in the present paper (presence of T-type calcium channels in cone photoreceptors) has already been identified/presented by previous studies of different groups (Macosko et al., 2015; pmid 26000488; Davison et al., 2021; pmid 35803735; Williams et al., 2022; pmid 35650675). The degree of novelty of the present paper thus appears limited. I think that the study might be better suited in a more specialized journal than eLife. 

      We thank the reviewer for acknowledging the rigor of our study but disagree with their evaluation regarding the novelty of our work as outlined in our responses above.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Rebuttal_ Preprint- #RC-2023-02144

      First of all we would like to thank the three reviewers for their constructive and positive comments and suggestions, and the time spent in reviewing our manuscript. Their suggestions and comments had contributed to improve our manuscript. We feel the manuscript is much strengthened by this revision.

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      __Summary:____ __The manuscript by Dabsan et al builds on earlier work of the Igbaria lab, who showed that ER-luminal chaperones can be refluxed into the cytosol (ERCYS) during ER stress, which constitutes a pro-survival pathway potentially used by cancer cells. In the current work, they extent these observations and a role for DNAJB12&14 in ERCYS. The work is interesting and the topic is novel and of great relevance for the proteostasis community. I have a number of technical comments:

      We thank the reviewer for his/her positive comments on our manuscript.


      __Major and minor comments: __

      1- In the description of Figure 2, statistics is only show to compare untreated condition with those treated with Tg or Tm, but no comparison between condition and different proteins. As such, the statement made by the authors "...DNAJB14-silenced cells were only affected in AGR2 but not in DNAJB11 or HYOU1 cytosolic accumulation" cannot be made.

      Answer: We totally agree with the reviewer#1. The aim of this figure is to show that during ER stress, a subset of ER proteins are refluxed to the cytosol. This is happening in cells expressing DNAJB12 and DNAJB14. We are not comparing the identity of the expelled proteins between DNAJB12-KD cells and DNAJB14-KD cells, This is not the scoop of this paper as such the statement was removed.

      2- Figure S2C: D11 seems to increase in the cytosolic fraction after Tm and Tg treatment. However, this is not reflected in the text. The membrane fraction also increases in the DKO. Is the increase of D11 in both cytosol and membrane and indication for a transcriptional induction of this protein by Tm/Tg? Again, the authors are not reflecting on this in their text.

      Answer: We performed qPCR experiments in control, DNAJB12-KD, DNAJB14-KD and in the DNAJB12/DNAJB14 double knock down cells (in both A549 and PC3 cells) to follow the mRNA levels of DNAJB11. As shown in (Figure S2F-S2N), there is no increase in the mRNA levels of DNAJB11, AGR2 or HYOU1 in the different cells in normal (unstressed conditions). Upon ER stress with tunicamycin or thapsigargin there is a little increase in the mRNA levels of HYOU1 and AGR2 but not in DNAJB11 mRNA levels. On the other hand, we also performed western blot analysis and we did not detect any difference between the different knockdown cells when we analyzed the levels of DNAJB11 compared to GAPDH. Those data are now added as (Figure S2F-S2N).

      We must note that although AGR2 and HYOU1 are induced at the mRNA as a result of ER stress, the data with the overexpression of DNAJB12 and DNAJB14 are important as control experiments because when DNAJB12 is overexpressed it doesn’t inducing the ER stress (Figure S3C-S3D). In those conditions there is an increase of the cytosolic accumulation of AGR2, HYOU1 and DNAJB11 despite that there was no induction of AGR2, HYOU1 or DNAJB11 (Figure 3C and Figure 3E, Figure S3, Figure 4, and Figure S4) . Those results argue against the idea that the reflux is a result of protein induction and an increase in the total proteins levels.

      3- Figure 2D: Only p21 is quantified. phospho-p53 and p53 levels are not quantified.


      Answer: We added the quantification of phospho-p53 and the p53 levels to (Figure 2E-G). Additional blots of the P21, phosphor-p53 and p53 now added to FigureS2O.

      4- Figure 2D: There appears to be a labelling error

      Answer: Yes, the labelling error was corrected.

      5- Are there conditions where DNAJB12 would be higher?

      Answer: In some cancer types there is a higher DNAJB12, DNAJB14 and SGTA expression levels that are associated with poor prognosis and reduced survival (New Figure S6E-M). The following were added to the manuscript: “Finally, we tested the effect of DNAJB12, DNAJB14, and SGTA expression levels on the survival of cancer patients. A high copy number of DNAJB12 is an unfavorable marker in colorectal cancer and in head and neck cancer because it is associated with poor prognosis in those patients (Figure S6E). A high copy number of DNAJB12, DNAJB14, and SGTA is associated with poor prognosis in many other cancer types, including colon adenocarcinoma (COAD), acute myeloid leukemia (LAML), adrenocortical carcinoma (ACC), mesothelioma (MESO), and Pheochromocytoma and paraganglioma (PCPG) (Figure S6F-M). In uveal melanoma (UVM), a high copy number of the three tested genes, DNAJB12, DNAJB14, and SGTA, are associated with poor prognosis and poor survival (Figure S6I, S6J, and S6M). The high copy number of DNAJB12, DNAJB14, and SGTA is also associated with poor prognosis in many other cancer types but with low significant scores. More data is needed to make significant differences (TCGA database). We suggest that the high expression of DNAJB12/14 and SGTA in those cancer types may account for the poor prognosis by inducing ERCYS and inhibiting pro-apoptotic signaling, increasing cancer cells' fitness.

      6- What do the authors mean by "just by mass action"?

      Answer: Mass action means increasing the amount of the protein (overexpression). We corrected this in the main text to overexpression.

      7- Figure 3C: Should be labelled to indicate membrane and cytosolic fraction. The AGR2 blot in the left part is not publication quality and should be replaced.

      Answer: We added the labelling to indicate cytosolic and membrane fractions to Figure 3C. We re-blotted the AGR2, new blot of AGR2 was added.

      8- What could be the reason for the fact that DNAJB12 is necessary and sufficient for ERCYS, while DNAJB14 is only necessary?

      Answer: Because of their very high homology, we speculate that the two proteins have partial redundancy. Partial because we believe that some of the roles of DNAJB12 cannot be carried by DNAJB14 in its absence. Although they are highly homologous, we expect that they probably have different affinities in recruiting other factors that are necessary for the reflux of proteins.

      We further developed around this point in the discussion and the main text.

      9- Figure 5A: Is the interaction between SGTA and JB12 UPR-independent?HCS70 seems to show only background binding. The interaction of JB12 with SGTA is not convincing. A better blot is needed.

      Answer: In the conditions of Figure 5A, we did not observe any induction of the UPR (Figure S3C-D). Thus, we concluded that in those condition of overexpression, DNAJB12 interacts with SGTA in UPR independent manner.

      We repeated this experiment another 3 times with very high number of cells (2X15cm2 culture dishes for each condition) and instead of coimmunoprecipitating with DNAJB12 antibodies we IP-ed with FLAG-beads, the results are very clear as shown in the new Figure 5A compared to Figure S5A.

      10- Figure 5B: the expression of DNAJB14 was induced by Tg50, but not by Tg25 or Tm. However, the authors have not commented on this. This should be mentioned in the text and discussed.

      Answer: In most of the experiments we did not see an increase in DNAJB14 upon ER stress except in this replicate. To be sure we looked at the DNAJB14 levels upon ER stress by protein and qPCR experiment as shown in new (in the Input of Figure 5 and Figure S5) and (Figure S5H-I). We also added new IP experiments in Figure 5 and Figure S5.

      11- Figure 6A: Why is a double knockdown important at all? DNAJB14 does not seem to do much at all (neither in overexpression nor with single knockdown).

      Answer: the data shows that DNAJB12 can compensate for the lack of DNAJB14 while DNAJB14 can only partially compensate for some of the DNAJB12 functions. DNAJB12 could have higher affinity to recruit other factor needed for the reflux process and thus the impact of DNAJB12 is higher. In summary, neither DNAJB12 or DNAJB14 is essential in the single knockdown which means that they compensate for each other. In the overexpression experiment, it is enough to have the endogenous DNAJB14 for the DNAJB12 activity. When DNAJB14 is overexpressed at very high levels, we believe that it binds to some factors that are needed for proper DNAJB12 activity (Figure 4 showing that the WT-DNAJB14 inhibits ER-stress induced ER protein reflux when overexpressed). We believe that DNAJB14 is important because only when we knock both DNAJB12 and DNAJB14 we see an effect on the ER-protein reflux. DNAJB14 is part of a complex of DNAJB12/HSC70 and DSGTA.

      (DNAJB12 is sufficient while DNAJB14 is not- please refer to point #8 above).

      **Referees cross-commenting**

      I agree with the comments raised by reviewer 1 about the manuscript. I also agree with the points written in this consultation session. In my opinion, the comments of reviewer 2 are phrased in a harsh tone and thus the reviewer reaches the conclusion that there are "serious" problems with this manuscript. However, I think that the authors could address many of the points of this reviewer in a matter of 3 months easily. For instance, it is easy to control for the expression levels of exogenous wild type and mutant D12 and compare it to the endogenous one (point 3). This is a very good point of this reviewer and I agree with this experiment. Likewise, it is easy to provide data about the levels of AGR2 to address the concern whether its synthesis is affected by D12 and D14 overexpression. Again, an excellent suggestion, but no reason for rejecting the story. As for not citing the literature, I think this can also easily be addressed and I am sure that this is just an oversight and no ill intention by the authors. __Overall, I am unable to see why the reviewer reaches such a negative verdict about this work. With proper revisions that might take 3 months, I think the points of all reviewers can be addressed. __

      Reviewer #1 (Significance (Required)):

      Significance: The strength of the work is that it provides further mechanistic insight into a novel cellular phenomenon (ERCYS). The functions for DNAJB12&14 are unprecedented and therefore of great interest for the proteostasis community. Potentially, the work is also of interest for cancer researchers, who might capitalize of the ERCYS to establish DNAJB12/14 as novel therapeutic targets. The major weaknesses are as follows: (i) the work is limited to a single cell line. To better probe the cancer relevance, the work should have used at least a panel of cell lines from one (or more) cancer entity. Ideally even data from patient derived samples would have been nice. Having said this, I also appreciate that the work is primarily in the field of cell biology and the cancer-centric work could be done by others. Certainly, the current work could inspire cancer specialists to explore the relevance of ERCYS. (ii) No physiological or pathological condition is shown where DNAJB12 is induced or depleted.

      Answer: We previously showed that ERCYS is conserved in many different cell lines including A549, MCF7, GL-261, U87, HEK293T, MRC5 and others and is also conserved in murine models of GBM (GL-261 and U87 derived tumors) and human patients with GBM (Sicari et al. 2021). Here, we tested the reflux process and the IP experiments in many different cell lines including A549, MCF-7, PC3 and Trex-293 cells. We also added new fractionation experiment in DNAJB12 and DNAJB14 -depleted MCF-7, PC3 and A549 cells. We added all those data to the revised version.

      We also added survival curves from the TCGA database showing that high copy number of DNAB12, DNAJB14 and SGTA are associated with poor prognosis compared to conditions where DNAJB12, DNAJB14, and SGTA are at low copy number (Figure S6E-M). Finally, we included immunofluorescent experiment to show that the interaction between the refluxed AGR2 and the cytosolic SGTA occurs in tumors collected from patients with colorectal cancer patients (Figure S5F-G) compared to non-cancerous tissue.

      This study is highly significant and is relevant not only to cancer but for other pathways that may behave in similar manner. For instance, DNAJB12 and DNAJB14 are part of the mechanism that is used by non-envelope viruses to escape the ER to the cytosol. Thus, the role of those DNAJB proteins seems to be mainly in the reflux of functional (not misfolded) proteins from the ER to the cytosol. We reported earlier that the UDP-Glucose-Glucosyl Transferase 1 (UGGT1) is also expelled during ER stress. UGGT1 is important because it is redeploy to the cytosol during enterovirus A71 (EA71) infection to help viral RNA synthesis (Huang et al, 2017). This redeployment of EAA71 is similar to what happens during the reflux process because on one hand, UGGT1 exit the ER by an ER stress mediated process (Sicari et al. 2021) and it is also a functional in the cytosol as a proteins which help viral RNA synthesis ((Huang et al, 2017). All those data showing that there is more of DNAJB12, DNAJB14, DNAJC14, DNAJC30 and DNAJC18 that still needs to be explored in addition to what is published. Thus, we suggest that viruses hijacked this evolutionary conserved machinery and succeeded to use it in order to escape the ER to the cytosol in a manner that depends on all the component needed for ER protein reflux.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      The authors present a study in which they ascribe a role for a complex containing DNAJB12/14-Hsc70-SGTA in facilitating reflux of a AGR2 from the ER to cytosol during ER-stress. This function is proposed to inhibit wt-P53 during ER-stress.

      Concerns: 1. The way the manuscript is written gives the impression that this is the first study about mammalian homologs of yeast HLJ1, while there are instead multiple published papers on mammalian orthologs of HLJ1. Section 1 and Figure 1 of the results section is redundant with a collection of previously published manuscripts and reviews. The lack of proper citation and discussion of previous literature prevents the reader from evaluating the results presented here, compared to those in the literature.

      Answer: We highly appreciate the reviewer’s comments. This paper is not to show that DNAJB12 and DNAJB14 are the orthologues of HLJ-1 but rather to show that DNAJB12 and DNAJB14 are part of a mechanism that we recently discovered and called ERCYS that cause proteins to be refluxed out of the ER. A mechanism that is regulated in by HLJ-1 in yeast. ERCYS is an adaptive and pro-survival mechanism that results in increased chemoresistance and survival in cancer cells. The papers that reviewer #2 refer to are the ones that report DNAJB12 can replace some of the ER-Associated Degradation (ERAD) functions of HLJ-1 in degradation of membranal proteins such as CFTR. These two mechanism are totally different and the role of the yeast HLJ-1 in degradation of CFTR is not needed for ERCYS. This is because we previously showed that the role of the yeast HLJ-1 and probably its orthologues in ERCYS is independent of their activity in ERAD(Igbaria et al. 2019). Surprisingly, the role of HLJ-1 in refluxing the ER proteins is not only independent of the reported ERAD-functions of HLJ1 and the mammalian DNAJBs but rather proceeds more rigorously when the ERAD is crippled (Igbaria et al. 2019). This role of DNAJBs is unique in cancer cells and is responsible in regulating the activity of p53 during the treatment of DNA damage agents.

      In our current manuscript we show by similarity, functionality, and topological orientation, that DNAJB12 and DNJB14 may be part of a well conserved mechanism to reflux proteins from the ER to the cytosol. A mechanism that is independent of DNAJB12/14’s reported activity in ERAD(Grove et al. 2011; Yamamoto et al. 2010; Youker et al. 2004). In addition, DNAJB12 and DNAJB14 facilitate the escape of non-envelope viruses from the ER to the cytosol in similar way to the reflux process(Goodwin et al. 2011; Igbaria et al. 2019; Sicari et al. 2021). All those data show that HLJ-1 reported function may be only the beginning of our understanding on the role that those orthologues carry and that are different from what is known about their ERAD function.

      Action: We added the references to the main text and discussed the differences between the reported DNAJB12 and HLJ-1 functions to the function of DNAJB12, DNAJB14 and the other DNAJ proteins in the reflux process. We also developed around this in the discussion.

      The conditions used to study DNAJB12 and DNAJ14 function in AGR2 reflux from the ER do not appear to be of physiological relevance. As seen below they involve two transfections and treatment with two cytotoxic drugs over a period of 42 hours. The assay for ERCY is accumulation of lumenal ER proteins in a cytosolic fraction. Yet, there is no data or controls that describe the path taken by AGR2 from the ER to cytosol. It seems like pleotropic damage to the ER due the experimental conditions and accompanying cell death could account for the reported results?

      Transfection of cells with siRNA for DNAJB12 or DNAJB14 with a subsequent 24-hour growth period.

      Transfection of cells with a p53-lucifease reporter.

      Treatment of cells with etoposide for 2-hours to inhibit DNA synthesis and induce p53. D. Treatment of cells for 16 hours with tunicamycin to inhibit addition of N-linked glycans to secretory proteins and cause ER-stress.

      Subcellular fractionation to determine the localization of AGR2, DNAJB11, and HYOU1

      KD of DNAJB12 or DNAJB14 have modest if any impact on AGR2 accumulation in the cytosol. There is an effect of the double KD of DNAJB12 or DNAJB14 on AGR2 accumulation in the cytosol. Yet there are no western blots showing AGR2 levels in the different cells, so it is possible that AGR2 is not synthesized in cells lacking DNAJB12 and DNAKB14. The lack of controls showing the impact of single and double KD or DNAJB12 and DNAJB14 on cell viability and ER-homeostasis make it difficult to interpret the result presented. How many control versus siRNA KD cells survive the protocol used in these assays?


      Answer: Despite the long protocol we see differences between the control cells and the DNAJB-silenced cells in terms of the quantity of the refluxed proteins to the cytosol. The luciferase construct was used to assess the activity of p53 so the step of the second transfection was used only in experiments were we assayed the p53-luciferase activity. The rest of the experiments especially those where we tested the levels of p53 and P21 levels, were performed with one transfection. Moreover, all the experiments with the subcellular protein fractionation were performed after one transfection without the second transfection of the p53-Luciferase reporter. Finally, the protocol of the subcellular protein fractionation requires first to trypsinize the cells to lift them up from the plates, at the time of the experiment the cells were almost at 70-80% confluency and in the right morphology under the microscope.

      Here, we performed XTT assay and Caspase-3 assay to asses cell death at the end of the experiment and before the fractionation assay. We did not observe any differences at this stage between the different cell lines (Figure-RV1 for reviewers Only). This can be explained by the fact that we use low concentrations of Tm and Tg for short time of 16 hour after the pulse of etoposide.

      Finally, the claim that and ER-membrane damage result in a mix between the ER and cytosolic components is not true for the following reasons: (1) In case of mixing we would expect that GAPDH levels in the membrane fraction will be increased and that we do not see, and (2) we used our previously described transmembrane-eroGFP (TM-eroGFP) that harbors a transmembrane domain and is attached to the ER membrane facing the ER lumen. The TM-eroGFP was found to be oxidized in all conditions tested. Those data argue against a rupture of the ER membrane which can results in a mix of the highly reducing cytosolic environment with the highly oxidizing ER environment by the passage of the tripeptide GSH from the cytosol to the ER. All those data argue against (1) cell death, and (2) rupture of the ER membrane. Figure RV1 Reviewers Only.

      Moreover, as it is shown in Figure S2, AGR2 is found in the membrane fraction in all the four different knock downs, thus it is synthesized in all of them. Moreover, we assayed the mRNA levels of AGR2 in all the knockdowns and we so that they are at the same levels in all the 4 different conditions and still AGR2 mRNA levels increase upon ER stress in all of the 4 knockdown cells in different backgrounds (Figure S2F-N).

      In Figure 3 the authors overexpress WT-D12 and H139Q-D12 and examine induction of the p53-reporter. There are no western blots showing the expression levels of WT-D12 and H139Q-D12 relative to endogenous DNAJB12. HLJ1 stands for high-copy lethal DnaJ1 as overexpression of HLJ1 kills yeast. The authors present no controls showing that WT-D12 and H139-D12 are not expressed at toxic levels, so the data presented is difficult to evaluate.

      Answer: The expression levels of the overexpression of DNAJB12 and DNAJB14 were present in the initial submission of the manuscript as Figure S3A and S3B. The data showing the relationship between the expression degree and the viability were also included in the initial submission as Figure S3C (Now S3H).

      There is no mechanistic data used to help explain the putative role DNAJB12 and DNAJB14 in ERCY? In Figure 4, why does H139Q JB12 prevent accumulation of AGR2 in the cytosol? There are no westerns showing the level to which DNAJB12 and DNAJB14 are overexpressed.


      Answer: The data showing the levels of DNAJB12 compared to the endogenous were present in the initial submission as Figure S3A and S3B.

      We suggest a mechanism by which DNAJB12 and DNAJB14 interact (Figure 5 and Figure S5) and oligomerize to expel those proteins in similar way to expelling non-envelope viruses to the cytosol. Thus, when expressing the mutant DNAJB12 H139Q may indicate that the J-domain dead-mutant can still be part of the complex but affects the J-domain activity in this oligomer and thus inhibit ER-protein reflux. In other words, we showed that the H139Q exhibits a dominant negative effect when overexpressed. Moreover, here we added another IP experiment in the D12/D14-DKD cells to show that in the absence of DNAJB12 and DNAJB14, SGTA cannot bind the ER-lumenal proteins because they are not refluxed (Figure 5 and Figure S5). Those data indicate that in order for SGTA bind the refluxed proteins they have to go through the DNAJB12 and DNAJB14 and their absence this interaction does not occur. This explanation was also present in the discussion of the initial submission.

      Mechanistically, we show that AGR2 interacts with DNAJB12/14 which are necessary for its reflux. This mechanism involves the functionality of cytosolic HSP70 chaperones and their cochaperones (SGTA) proteins that are recruited by DNAJB12 and 14. This mechanism is conserved from yeast to mammals. Moreover, by using the alpha-fold prediction tools, we found that AGR2 is predicted to interact with SGTA in the cytosol by the interaction between the cysteines of SGTA and AGR2 in a redox-dependent manner.

      **Referees cross-commenting**

      __ __ I appreciate the comments of the other reviewers. I agree that the authors could revise the manuscript. Yet, based on my concerns about the physiological significance of the process under study and lack of scholarship in the original draft, I would not agree to review a revised version of the paper.

      Answer: Regards the physiological relevance, we showed in our previous study (Sicari et al. 2021) how relevant is ERCYS in human patients of GBM and murine model of GBM. ERCYS is conserved from yeast to human and is constitutively active in GL-261 GBM model, U87 GBM model and human patients with GBM (Sicari et al. 2021). Here, extended that to other tumors and showed that DNAJB12, DNAJB14 and SGTA high levels are associated with poor prognosis in many cancer types (Figure S6). We also show some data from to show the relevance and added data showing the interaction of SGTA with AGR2 in CRC samples obtained from human patients compared to healthy tissue (Figure S5). This study is highly significant and is relevant not only to cancer but for other pathways that may behave in similar manner. For instance, DNAJB12 and DNAJB14 are part of the mechanism that is used by non-envelope viruses to escape the ER to the cytosol. Thus, the role of those DNAJB proteins seems to be mainly in the reflux of functional (not misfolded) proteins from the ER to the cytosol. We reported earlier that the UDP-Glucose-Glucosyl Transferase 1 (UGGT1) is also expelled during ER stress. UGGT1 is important because it is redeploy to the cytosol during enterovirus A71 (EA71) infection to help viral RNA synthesis (Huang et al, 2017). This redeployment of EAA71 is similar to what happens during the reflux process because on one hand, UGGT1 exit the ER by an ER stress mediated process (Sicari et al. 2021) and it is also a functional in the cytosol as a proteins which help viral RNA synthesis ((Huang et al, 2017). All those data showing that there is more of DNAJB12, DNAJB14, DNAJC14, DNAJC30 and DNAJC18 that still needs to be explored in addition to what is published. We suggest that viruses hijacked this evolutionary conserved machinery and succeeded to use it in order to escape.

      We appreciate the time spent to review our paper and we are sorry that the reviewer reached such verdict that is also not understood by the other reviewers. Most of the points raised by reviewer 2 were already addressed and explained in the initial submission, anyways we appreciate the time and the comments of reviewer #2 on our manuscript.

      Reviewer #2 (Significance (Required)):

      Overall, there are serious concerns about the writing of this paper as it gives the impression that it is the first study on higher eukaryotic and mammalian homologs of yeast HLJ1. The reader is not given the ability to compare the presented data to related published work. There are also serious concerns about the quality of the data presented and the physiological significance of the process under study. In its present form, this work does not appear suitable for publication.

      Answer: Again we thank reviewer #2 for giving us the opportunity to explain how significant is this manuscript especially for people who are less expert in this field. The significance of this paper (1) showing a the unique role of DNAJB12 and DNAJB14 in the molecular mechanism of the reflux process in mammalian cells (not their role in ERAD), (2) showing the implication of other cytosolic chaperones in the process including HSC70 and SGTA (3), our alpha-fold prediction show that this process may be redox dependent that implicate the cysteines of SGTA in extracting the ER proteins, (4) overexpression of the WT DNAJB12 is sufficient to drive this process, (5) mutation in the HPD motif prevent the reflux process probably by preventing the binding to the cytosolic chaperones, and (6) we need both DNAJB12 and DNAJB14 in order to make the interaction between the refluxed ER-proteins and the cytosolic chaperones occur.

      In Summary, this study is highly significant in terms of physiology, we previously reported that ERCYS is conserved in mammalian cells and is constitutively active in human and murine tumors (Sicari et al. 2021). Moreover, DNAJB12 and DNAJB14 are part of the mechanism that is used by non-envelope viruses to escape the ER to the cytosol in a mechanism that is similar to reflux process (Goodwin et al. 2011; Goodwin et al. 2014). Thus, the role of those DNAJB proteins seems to be mainly in the reflux of functional proteins from the ER to the cytosol, viruses used this evolutionary conserved machinery and succeeded to use in order to escape. This paper does not deal with the functional orthologues of the HLJ-1 in ERAD but rather suggesting a mechanism by which soluble proteins exit the ER to the cytosol.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)):____ __

      Summary: Reflux of ER based proteins to the cytosol during ER stress inhibits wt-p53. This is a pro-survival mechanism during ER stress, but as ER stress is high in many cancers, it also promotes survival of cancer cells. Using A549 cells, Dabsan et al. demonstrate that this mechanism is conserved from yeast to mammalian cells, and identify DNAJB12 and DNAJB14 as putative mammalian orthologues of yeast HLJ1.

      This paper shows that DNAJB12 and 14 are likely orthologues of HLJ1 based on their sequences, and their behaviour. The paper develops the pathway of ER-stress > protein reflux > cytosolic interactions > inhibition of p53. The authors demonstrate this nicely using knock downs of DNAJB12 and/or 14 that partially blocks protein reflux and p53 inhibition. Overexpression of WT DNAJB12, but not the J-domain inactive mutant, blocks etoposide-induced p53 activation (this is not replicated with DNAJB14) and ER-resident protein reflux. The authors then show that DNAJB12/14 interact with refluxed ER-resident proteins and cytosolic SGTA, which importantly, they show interacts with the ER-resident proteins AGR2, PRDX4 and DNAJB11. Finally, the authors show that inducing ER stress in cancer cell lines can increase proliferation (lost by etoposide treatment), and that this is partially dependent on DNAJB12/14.

      This is a very interesting paper that describes a nice mechanism linking ER-stress to inhibition of p53 and thus survival in the face of ER-stress, which is a double edged sword regarding normal v cancerous cells. The data is normally good, but the conclusions drawn oversimplify the data that can be quite complex. The paper opens a lot of questions that the authors may want to develop in more detail (non-experimentally) to work on these areas in the future, or alternatively to develop experimentally and develop the observations further. There are only a few experimental comments that I make that I think should be done to publish this paper, to increase robustness of the work already here, the rest are optional for developing the paper further.

      We thank the reviewer for his/her positive comments His/her comments contributed to make our manuscript stronger.

      __Major comments:____ __

      1. Number of experimental repeats must be mentioned in the figure legends. Figures and annotations need to be aligned properly

      __Answer____: __All experiments were repeated at least 3 times. We added the number of repeats on each figure in the figures legends

      Results section 2:

      No intro to the proteins you've looked at for relocalization. Would be useful to have some info on why you chose AGR2. Apart from them being ER-localized, do they all share another common characteristic? Does ability to inhibit p53 vary in potency?

      Answer: We previously showed that AGR2 is refluxed from the ER to the cytosol to bind and inhibit wt-p53 (Sicari et al. 2021). Here, we used AGR2 because, (1) we know that AGR2 is refluxed from the ER to the cytosol, and (2) we know which novel functions it gains in the cytosol so we are able to measure and provide a physiological significance of those novel functions when the levels of DNAJB12 and DNAJB14 are altered. Moreover, we used DNAJB11 (41 kDa) and HYOU1 (150 kDa) proteins to show that alteration in DNAJB12 or DNAJB14 prevent the reflux small, medium and large sized proteins. We added a sentence in the discussion stating that DNAJB12/14 are responsible for the reflux of ER-resident proteins independently of their size. We also added in the result section that we are looking at proteins of different sizes and activities.


      What are the roles of DNAJB12/14 if overexpression can induce reflux? Does it allow increased binding of an already cytosolic protein, causing an overall increase in an interaction that then causes inhibition of p53? What are your suggested mechanisms?

      Answer: Previously it was reported that over-expression of DNAJB12 and DNAJB14 tend to form membranous structures within cell nuclei, which was designate as DJANGOS for DNAJ-associated nuclear globular structures(Goodwin et al. 2014). Because those structures which contain both DNAJB12 and DNAJB14 also form on the ER membrane (Goodwin et al. 2014), we speculate that during stress DNAJB12/14 overexpression may facilitate ERCYS. Interestingly, those structures contain Hsc70 and markers of the ER lumen, the nuclear and ER and nuclear membranes (Goodwin et al. 2014).

      The discussion was edited accordingly to further strengthen and clarify this point

      Fig3: A+B show overexpression of individual DNAJs but not combined. As you go on to discuss the effect of the combination on AGR2 reflux, it would be useful to include this experimentally here.

      Answer: This is a great idea, we tried to do it for long time. Unfortunately when we used cells overexpress DNAJB12 under the doxycycline promoter and transfect with DNAJB14 plasmid expressing DNAJB14 under the CMV promoter, most of the cells float within 24 hours compared to cells transfected with the empty vector alone or with DNAJB14-H136Q. We also did overexpression of DNAJB14 in cells with DNAJB12 conditional expression and also were lethal in Trex293T cells and A549-cells.

      Fig 3C: Subfractionation of cells shows AGR2 in the cytosol of A549 cells. The quality of the data is good but the bands are very high on the blot. For publication is it possible to show this band more centralized so that we are sure that we are not missing bands cut off in the empty and H139Q lanes?

      Also, you have some nice immunofluorescence in the 2021 EMBO reports paper, is it possible to show this by IF too? It is not essential for the story, but it would enrich the figure and support the biochemistry nicely. Also it is notable that the membrane fraction of the refluxed proteins doesn't appear to have a decrease in parallel (especially for AGR2). Is this because the % of the refluxed protein is very small? Is there a transcriptional increase of any of them (the treatments are 12+24 h so it would be enough time)? This could be a nice opportunity to discuss the amount of protein that is refluxed, whether this response is a huge emptying of the ER or more like a gentle release, and also the potency of the gain of function and effect on p53 vs the amount of protein refluxed. This latter part isn't essential but it would be a nice element to expand upon.

      Answer: We re-blotted the AGR2 again, new blot of AGR2 was added. More blots also are added in Figure S2, the text is edited accordingly.

      In new Figure S5 we added immunofluorescence experiment from tumors and non-tumors tissues obtained from Colorectal cancer (CRC) patients showing that the interaction between SGTA and the refluxed AGR2 also occurs in more physiological settings. It is also to emphasize that the suggested mechanism that implicates SGTA is also valid in CRC tumors.

      We performed qPCR experiments in control, DNAJB12-KD, DNAJB14-KD and in the DNAJB12/DNAJB14 double knock down cells (in both A549 and PC3 cells) to follow the mRNA levels of DNAJB11. As shown in the Figure S2F-N, there is no increase in the mRNA levels of DNAJB11, AGR2 or HYOU1 in the different cells in normal (unstressed conditions). Upon ER stress with tunicamycin or thapsigargin there is a little increase in the mRNA levels of HYOU1 and AGR2 but in DNAJB11 mRNA levels. On the other hand, we also performed western blot analysis and we did not detect any difference between the different knockdown cells when we analyzed the levels of DNAJB11 compared to GAPDH. Those data are now added to Figure S2F-N. We must note that in AGR2 and HYOU1 are induced at the mRNA as a result of ER stress. The data with the overexpression of DNAJB12 and DNAJB14 are important control experiment where we show a reflux when DNAJB12 is overexpressed without inducing the ER stress (Figure 3, Figure 4, and Figure S3). In those conditions no induction of AGR2, HYOU1 or DNAJB11 were observed. Those results argue against the reflux as a result of protein induction and the increase in the proteins levels.

      The overall protein levels in steady state are function of how much proteins are made, degraded and probably secreted outside the cell. We do see in Figure S2 under ER stress there are some differences in the levels of the mRNA, moreover, from our work in yeast we showed that the expelled proteins have very long half-life in the cytosol (Igbaria et al. 2019). Because it is difficult to assay how many of the mRNA is translated and how much of it is stable/degraded and the stability of the cytosolic fraction vs the ER, it is hard to interpret on the stability and the levels of the proteins.

      Those data are now added to the manuscript, the text is edited accordingly.

      You still mention DNAJB12 and 14 as orthologues, even though DNAJB14 has no effect on p53 activity when overexpressed. Do you think that this piece of data diminishes this statement?

      Answer: The fact that DNAJB12 and DNAJB14 are highly homologous and that only the double knockdown has a great effect on the reflux process may indicate that they are redundant. Moreover, because only DNAJB12 is sufficient may indicate that some of DNAJB12 function cannot be carried by DNAJB14. In one hand they share common activities as shown in the double knock down and on the other hand DNAJB12 has a unique function that may not be compensated by DNAJB14 when overexpressed.

      __ __ Fig 3D/F: Overexpression of DNAJB14 induces reflux of DNAJB11 at 24h, what does this suggest? Does this indicate having the same role as DNAJB12 but less potently? What's your hypothesis?

      Answer: ERCYS is new and interesting phenomenon and the redistribution of proteins to the cytosol has been documented lately by many groups. Despite that we still do not know what is the specificity of DNAJB12 and DNAJB14 to the refluxed proteins. DNAJB11 is glycosylated protein and now we are testing whether other glycosylated proteins prefer the DNAJB14 pathway or not. This data is beyond the scope of this paper

      "This suggests that the two proteins may have different functions when overexpressed, despite their overlapping and redundant functions" What does it suggest about their dependence on each other? If overexpression of WT DNAJB12 inhibits Tg induced reflux, is it also blocking the ability of DNAJB14 to permit flux?

      Answer: We hypothesize that it is all about the stichometry and the ratios between proteins. When we overexpress DNAJB14 (the one that is not sufficient to cause reflux it may hijack common components and factor by non-specifically binding to them. Those factors may be needed for DNAJB12 to function properly (Like the dominant negative effect of the DNAJB12-HPD mutant for instance). On the other hand, DNAJB12 may have higher affinity for some cytosolic partner and thus can do the job when overexpressed. Here, we deal with the DNAJB12/DNAJB14 as essential components of the reflux process, yet we need to identify the interactome of each of the proteins during stress and the role of the other DNAJ proteins that also share some of the topological and structural similarity to DNAJB12, DNAJB14 and HLJ-1 (DNAJC30, DNAJC14, and DNAJC18). We edited the text accordingly and integrated this in the discussion.

      __ __ Fig 4: PDI shown in blots but not commented on in text. Then included in the schematics. Please comment in the text.

      Answer: We commented PDI in the text.

      Fig 4F: Although the quantifications of the blots look fine, the blot shown does not convincingly demonstrate this data for AGR2. The other proteins look fine, but again it could be useful to see the individual means for each experiment, or the full gels for all replicates in a supplementary figure.

      Answer: the other two repeats are in Figure S4

      __ __Results section 3

      Fig 5A, As there is obviously a difference between DNAJB12/14 it would be useful to do the pulldown with DNAJB14 too. Re. HSC70 binding to DNAJB12 and 14, the abstract states that DNAJB12/14 bind HSC70 and SGTA through their cytosolic J domains. Fig 5 shows pulldowns of DNAJB12 with an increased binding of SGTA in FLAG-DNAJB12 induced conditions, but the HSC70 band does not seem to be enriched in any of the conditions, including after DNAJB12 induction. This doesn't support the statement that DNAJB12 binds HSC70. In fact, in the absence of a good negative control, this would suggest that the HSC70 band seen is not specific. There is also no data to show that DNAJB14 binds HSC70. I recommend including a negative condition (ie beads only) and the data for DNAJB14 pulldown.

      Answer: In Figure 5A we used the Flp-In T-REx-293 cells as it is easier to control and to tune up and down the expression levels of DNAJB12 and DNAJB14. According to new Figure S5A, DNAJB12 binds at the basal levels to HSC70 all the time. It was also surprising for us not to see the differences in the overexpression and we relate that to the fact that all the HSC70 are saturated with DNAJB12. In order to better assay that we repeated the IP in Figure 5A but instead of the IP with DNAJB12, we IP-ed with FLAG antibodies to selectively IP the transfected DNAJB12. As shown in the new Fig 5A, the increase of DNAJB12-FLAG is accompanied with an increase in the binding of HSC70.

      We further tested the interaction between DNAJB12, DNAJB14 and HSC70 during ER stress in cancer cells. In those cells we found that DNAJB12 and DNAJB14 bind to HSC70 and they recruit SGTA upon stress. We also tested the binding between DNAJB12 and DNAJB14, in unstressed conditions, there was a basal binding between both, this interaction was stronger during ER stress. Those data are now added to Figure 5 and Figure S5 and the discussion was edited accordingly.

      The binding of DNAJB12 to SGTA under stress conditions in Fig5B looks much more convincing than SGTA to DNAJB12 in Fig 5A. Bands in all blots need to be quantified from 3 independent experiments, and repeated if not already n=3. If this is solely a technical difference, please explain in the text.

      The conclusions drawn from this interaction data are important and shold be elaborated upon to support th claims made in the paper. The authors may also chose to expand the pulldowns to demonstrate their claims made on olidomerisation of DNAJB12 and 14 here. It is also clear that the interaction data of the SGTA with ER-resident proteins AGR2, PRDX4 and DNAJB11 is strong. The authors may want to draw on this in their hypotheses of the mechanism. I would imagine a complex such as DNAJB14/DNAJB12 - SGTA - AGR2/PRDX4/DNAJB11 would be logical. Have any experiments been performed to prove if complexes like this would form?

      Answer: In Figure 5A we used the Flp-In T-REx-293 cells as it is easier to control and to tune up and down the expression levels of DNAJB12 and DNAJB14. T-REx-293 are highly sensitive to ER stress, they do not die (as we did not observe apoptosis markers to be elevated) but they float and can regrow after the stress is gone. In Figure 5B we are using ER stress without the need to express DNAJB12 in A549 cell line. In order to further verify those data, we repeated the IP in another cell line as well to confirm the data in 5B. We also repeated the IP in 5A with anti-FLAG antibody to improve the IP and to specifically map he interaction with the overexpressed FLAG-DNAJB12 (discussed above). All experiments were done in triplicates and added to Figure 5 and Figure S5.

      We agree with the reviewer on the complex between the refluxed proteins and SGTA. We believed that SGTA may form a complex with other refluxed ER-proteins but we were unable to see an interaction between AGR2-DNAJB11 in the cytosolic fraction or between AGR2-PRDX4 in the conditions tested in the cytosolic fraction. We could not do this in the whole cell lysate because those proteins bind each other in the ER. Finally, our structural prediction using Alpha-fold suggests that the interaction between SGTA and the refluxed AGR2 (and probably others) is redox depending and that it requires disulfide bridge between cysteine 81 on AGR2 and cysteine 153 on SGTA. Thus, we hypothesize that SGTA binds one refluxed protein at the time.

      We repeated the figure with improvement: (1) using more cells in order to increase the amount of IP-ed proteins and to overcome the problem of the faint bands, (2) performing the IP with the FLAG antibodies instead of the DNAJB12 endogenous antibodies.

      Fig 5B: It is clear that DNAJB12 interacts with SGTA. The authors state that DNAJB14 also interacts with SGTA under normal and stress conditions, but the band in 25/50 Tg is very feint. Why would there be stronger binding at the 2 extremes than during low stress induction? In the input, there is a much higher expression of DNAJB14 in 50 Tg. What does this say about the interaction? Is there an effect of ER stress on DNAJB14 expression? A negative control should be included to show any background binding, such as a "beads only" control

      __Answer: __DNAJB14 does not change with ER stress as shown in the Ips (Input) and in the qPCR experiment in Figure S5I. We added beads only control, we also added new Ips to assess the binding between DNAJB14 and DNAJB12, and between DNAJB14-SGTA. All the new Ips and controls now added as Figure 5 and Figure S5.

      Fig 5C data is sound, although a negative control should be included.

      Answer: Negative control was added in Figure S5.

      __Results section 4____ __

      Fig 6A-B: Given that there is the complexity of overexpression v KD of DNAJB12 v 14 causing similar effects on p53 actvity (Fig 2 v 3), it would be interesting to see whether the effect of overexpression mirrors the results in Fig 6A. Is it known what SGTA overexpression does (optional)?

      Answer: In the overexpression system, cells overexpressing DNAJB12 start to die between 24-48 hours as shown in Figure S3C. Thus, it is difficult to assay the proliferation of these cells in those conditions. On the other hand, overexpression of Myc-tagged SGTA in A549 cells, MCF7 or T-ReX293 did not show any reflux of ER-proteins to the cytosol and it didn’t show any significant changes in the proliferation index (Figure Reviewers only RV2).

      Fig 6D: resolution very low

      Answer: Figure 6D was changed

      __ __ Fig 6C-D: There is an interesting difference though between the proposed cytosolic actions of the refluxed proteins. You show that AGR2, PRDX4 and DNAJB11 all bind to SGTA in stress conditions, but in the schematics you show: DNAJB11 binding to HSC70 through SGTA (not shown in the paper), then also PDIA1, PDIA3 binding to SGTA and AGR2 binding to SGTA. What role does SGTA have in these varied reactions? Sometimes it is depicted as an intermediate, sometimes a lone binder, what is its role as a binder? It should be clarified which interactions are demonstrated in the paper (or before) and which are hypothesized in a graphical way (eg. for hypotheses dotted outlines or no solid fill etc). The schematics also suggest that DNAJB14 binding to HSC70 and SGTA is inducible in stress conditions, as is PDIA3, which is not shown in the paper. Discussion "In cancer cells, DNAJB12 and DNAJB14 oligomerize and recruit cytosolic chaperones and cochaperones (HSC70 and SGTA) to reflux AGR2 and other ER-resident proteins and to inhibit wt-p53 and probably different proapoptotic signaling pathways (Figure 5, and Figure 6C-6D)." You havent shown oligomerisation between DNAJB12/14. Modify the text to make it clear that it is a hypothesis.

      Answer: We removed “oligomerize” from the text and added that it as a hypothesis. Figure (C-D) also were changed to be compatible with the text.

      Minor comments:

      __ __ It would be useful to have page or line numbers to help with document navigation, please include them. Typos and inconsistency in how some proteins are named throughout the manuscript

      Answer: Page numbers and line numbers are added. Typos are corrected

      Title: Include reference to reflux. Suggest: "chaperone complexes (?proteins) reflux from the ER to cytosol..." I presume it would be more likely that the proteins go separately rather than in complex. Do you have any ideas on the size range of proteins that can undergo this process?

      Answer: this is true, proteins may cross the ER membrane separately and then be in a complex with cytosolic chaperones. The title is changed accordingly. As discussed earlier, the protein we chose were of different sizes to show that they are refluxed independently of their size. Moreover, our previous work showed that the proteins that were refluxed are of different sizes. Most importantly UGGT1 (around 180 Kda) which is reported to deploy to the cytosol upon viral infection (Huang et al. 2017; Sicari et al. 2020). In this study we used AGR2 (around 19 Kda) and HYOU1 (150Kda).

      ERCY in abstract, ERCYS in intro. There are typos throughout, could be a formatting problem, please check

      Answer: Checked and corrected

      What about the selection of refluxed proteins? Is this only a certain category of proteins? Could it be anything? Have you looked at other cargo / ER resident proteins?

      __ ____Answer: __in our previous study by (Sicari, Pineau et al. 2020) we looked at many other proteins especially glycoproteins from the ER. In (Sicari, Pineau et al. 2020) we used mass spectrometry in order to identify new refluxed proteins and we found 26 new glycoprotein that are refluxed from cells treated with ER stressor and from human tissues obtained from GBM patients (Sicari, Pineau et al. 2020).

      We previously showed that AGR2 is refluxed from the ER to the cytosol to bind and inhibit p53 (Sicari, Pineau et al. 2020). Here, we selected AGR2 because we know that (1) it is refluxed, and (2) we know which novel functions it acquires in the cytosol so we are able to measure and provide a physiological significance of those novel functions when the levels of DNAJB12 and DNAJB14 are altered. Moreover, we selected DNAJB11 (41 kDa) and HYOU1 (150 kDa) proteins to show that alteration in DNAJB12 or DNAJB14 prevent the reflux small, medium and large protein (independently of their size). We also showed earlier by mass spectrometry analysis that the refluxed proteins range from small to very large proteins such as UGGT1, thus we believe that soluble ER-proteins can be substrates of ERCYS independently of their size. In the discussion, we added a note that the reflux by the cytosolic and ER chaperones operates on different proteins independently of their size.

      "Their role in ERCYS and cells' fate determination depends..." Suggest change to "Their role in ERCYS and determination of cell fate..."

      Answer: changed and corrected

      I think that the final sentence of the intro could be made stronger and more concise. There's a repeat of ER and cytosol. Instead could you comment on the reflux permitting new interactions between proteins otherwise spatially separated, then the effect on wt-p53 etc.

      Answer: The sentence was rephrased as suggested to “ In this study, we found that HLJ1 is conserved through evolution and that mammalian cells have five putative functionality orthologs of the yeast HLJ1. Those five DNAJ- proteins (DNAJB12, DNAJB14, DNAJC14, DNAJC18, and DNAJC30) reside within the ER membrane with a J-domain facing the cytosol (Piette et al. 2021; Malinverni et al. 2023). Among those, we found that DNAJB12 and DNAJB14, which are strongly related to the yeast HLJ1 (Grove et al. 2011; Yamamoto et al. 2010), are essential and sufficient for determining cells' fate during ER stress by regulating ERCYS. Their role in ERCYS and determining cells' fate depends on their HPD motif in the J-domain. Downregulation of DNAJB12 and DNAJB14 increases cell toxicity and wt-p53 activity during etoposide treatment. Mechanistically, DNAJB12 and DNAJB14 interact and recruit cytosolic chaperones (HSC70/SGTA) to promote ERCYS. This later interaction is conserved in human tumors including colorectal cancer.

      In summary, we propose a novel mechanism by which ER-soluble proteins are refluxed from the ER to the cytosol, permitting new inhibitory interactions between spatially separated proteins. This mechanism depends on cytosolic and ER chaperones and cochaperones, namely DNAJB12, DNAJB14, SGTA, and HSC70. As a result, the refluxed proteins gain new functions to inhibit the activity of wt-p53 in cancer cells. “

      __Figure legends: __

      In some cases the authors state the number of replicates, but this should be stated for all experiments. If experiments don't already include 3 independent repeats, this should be done. Check text for typos, correct letter capitalisation, spaces and random bold text (some of this could be from incompatability when saving as PDF)

      Answer: all experiments were repeated at least three times. The number of repeats is now indicated in the figure legends of each experiment. Typos and capitalization is corrected as well.

      Fig2E: scrambled not scramble siRNA

      Answer: corrected

      Fig 3: "to expel" is a term not used in the rest of the paper for reflux. Useful to remain consistent with terminology where possible

      Answer: Rephrased and corrected

      Results section 1:

      "Protein alignment of the yeast HLJ1p showed high amino acids similarity to the mammalian..."

      Answer: Rephrased to “ Comparing the amino acid sequences revealed significant similarity between the yeast protein HLJ1p and the mammalian proteins DNAJB12 and DNAJB14”

      __ __ Fig 1C: state in legend which organism this is from (presumably human)

      Answer: in Figure 1C legends it is stated that: “ the HPD motif within the J-domain is conserved in HLJ-1 and its putative human orthologs DNAJB12, DNAJB14, DNAJC14, DNAJC18, and DNAJC30.”

      Results Section 2

      "Test the two strongest hits DNAJB12/14" Add reference to previous paper showing this

      Answer: the references were added.

      __ __ "In the WT and J-protein-silenced A549 cells, there were no differences in the cytosolic enrichment of the three ER resident proteins AGR2, DNAJB11, and HYOU1 in normal and unstressed conditions (Figure 2A-C and Figure S2C)." I think that this is an oversimplification, and in your following discussion, you show this it's more subtle than this.

      Answer: We expanded on this both in the discussion and the results section.

      __ __ The text here isn't so clear: normal and unstressed conditions? Do you mean stressed? Please be careful in your phrases: "DNAJB12-silenced cells are slightly affected in AGR2 and DNAJB11 cytosolic accumulation but not HYOU1." This is the wrong way around. DNAJB12 silencing effects AGR2, not that AGR2 effects the cells (which is how you have written it). This also occurs agan in the next para:

      Answer: Normal cells are non-cancer cells. Unstressed conditions= without ER stress. The sentence was rephrased to: In the absence of ER stress, the cytosolic levels of the three ER-resident proteins (AGR2, DNAJB11, and HYOU1) were similar in wild-type and J-protein-silenced A549 cells.

      "During stress, DNAJB12/DNAJB14 double knockdown was highly affected in the cytosolic..." I think you mean it highly affected the cytosolic accumulation, not that it was affected by the cytosolic accumulation. Please change in the text

      Answer: the sentence is now rephrased to” During stress, double knockdown of DNAJB12 and DNAJB14 highly affected the cytosolic accumulation of all three tested proteins”

      __ __ "DNAJB12 and DNAJB14 are strong hits of the yeast HLJ1" Not clear, I presume you mean they are likely orthologues? Top candidates for being closest orthologues?

      Answer: this is correct, the sentence is rephrased and corrected

      __ __ Fig 2D: typos in WB labelling? I think Tm should be - - +, not - + +as it is now (if it's not a typo, you need more controls, eto alone.

      Answer: the labeling is now corrected

      Fig 2D-E-F typos for DKD? D12/D12 or D12/14?

      Answer: This is correct, thank you for pointing this out. The labeling in corrected

      __ __ "We assayed the phosphorylation state of wt- p53 and p21 protein expression levels (a downstream target of p53 signaling) during etoposide treatment." What are the results of this? Explain what Fig 2D-E shows, then build on this with the +Tm results. Results should be explained didactically to be clear.

      Answer: The paragraph was edited and we explained the results: In these conditions, we saw an increase in the phosphorylation of wt-p53 in the control cells and in cells knocked-down with DNAJB12, DNAJB14 or both. This phosphorylation increased the protein levels of p21 as well (Figure 2D-G). Tm addition to cells treated with etoposide resulted in a reduction in wt-p53 phosphorylation, and as a consequence, the p21 protein levels were also decreased (Figure 2D-G and Figure S2O). Cells lacking DNAJB12 or DNAJB14 have partial protection in wt-p53 phosphorylation and p21 protein levels. Silencing both proteins in A549 and MCF7 cells rescued wt-p53 phosphorylation and p21 levels (Figure 2D-G and Figure S2D). Moreover, similar results were obtained when we assayed the transcriptional activity of wt-p53 in cells transfected with a luciferase reporter under the p53-DNA binding site (Figure 2H). These data confirm that DNAJB12 and DNAJB14 are involved in ER protein reflux and the inhibition of wt-p53 activity during ER stress.


      "(Figure 2D- E). Cells lacking DNAJB12 and or DNAJB14 have partial protection in wt-p53 phosphorylation and p21 protein levels."

      Answer: This sentence is now removed

      You comment on p53 phosphorylation, but you haven't quantified this. This should be done, normalized to p53 levels, if you want to draw these conclusions, especially as total p53 varies between condition. Does Eto increase p53 txn? Does Tm alone increase p53 activity/phospho-p53? These are shown in the Sicari EMBO reports paper in 2021, you should briefly reference those.

      Answer: The blots are now quantified and new blot is added to Figure S2D. The Paragraph was edited and referenced to our previous paper (Sicari et al. 2021). “We then wanted to examine whether the gain of function of AGR2 and the inhibition of wt-p53 depends on the activity of DNAJB12 and DNJAB14. We assayed the phosphorylation state of wt-p53 and p21 protein expression levels (a downstream target of wt-p53 signaling) during etoposide treatment. In these conditions, there was an increase in the phosphorylation of wt-p53 in the control cells and in cells knocked down with DNAJB12, DNAJB14, or both. This phosphorylation also increases protein levels of p21 (Figure 2D-G and Figure S2O). Tm addition to cells treated with etoposide resulted in a reduction in wt-p53 phosphorylation, and as a consequence, the p21 protein levels were also decreased (Figure 2D-G and Figure S2O). Silencing DNAJB12 and DNAJB14 in A549 and MCF-7 cells rescued wt-p53 phosphorylation and p21 levels (Figure 2D-G and Figure S2O). Moreover, similar results were obtained when we assayed the transcriptional activity of wt-p53 in cells transfected with a luciferase reporter under the p53-DNA binding site (Figure 2H). In the latter experiment, etoposide treatment increased the luciferase activity in all the cells tested. Adding ER stress to those cells decreased the luciferase activity except in cells silenced with DNAJB12 and DNAJB14.

      These data confirm that DNAJB12 and DNAJB14 are involved in the reflux of ER proteins in general and AGR2 in particular. Inhibition of DNAJB12 and DNAJB14 prevented the inhibitory interaction between AGR2 and wt-p53 and thus rescued wt-p53 phosphorylation and its transcriptional activity as a consequence. “

      Fig3A: overexpression of DNAJB12 decreases Eto induced p53 but not at steady state. Is this because at steady state the activity is already basal? Or is there another reason?

      Answer: yes, at steady state the activity is already basal

      Switch Figs S3D and S3C as they are not referred to in order. Also Fig S3C: vary colour (or add pattern) on bars more between conditions

      Answer: The Figures now are called by their order in the new version. Colors are now added to Figure S3C.

      Need to define HLJ1 at first mention

      Answer: defined as” HLJ1 - High copy Lethal J-protein -an ER-resident tail-anchored HSP40 cochaperone.

      Results section 3

      HSC70 cochaperone (SGTA) defined twice

      Answer: the second one was removed

      "These data are important because SGTA and the ER-resident proteins (PRDX4, AGR2, and DNAJB11) are known to be expressed in different compartments, and the interaction occurs only when those ER-resident proteins localize to the cytosol." Is there a reference for this?

      Answer: Peroxireoxin 4 is the only peroxerodin that is expressed in the ER. AGR2 and DNAJB11 are also ER luminal proteins that are known to be solely expressed in the ER. SGTA is part of the cytosolic quality control system and is expressed in the cytosol. The references are added in the main text.

      Results section 4

      "by almost two folds"

      Answer: corrected

      Fig 6A: It seems strange that the difference between purple and blue bars in scrambled, and D14-KD are very significant but D12-KD is only significant. Why is this? The error bars don't look that different. It would be interesting to see the individual means for each different replicate.

      Answer: Thank you for pointing this, the two asterixis were aligned in the middle as one during figure alignments. In D14 the purple one has a lower error bar thus this changes the significance when compared to the blue while in D12-KD, the error bars in the eto treatment and the eto-Tm both are slightly higher. Graphs of the three different replicates are now added in Figure S6. Each one of the three biological replicates was repeated in three different technical repeats (averaged in the graphs).

      Figures: Fig 6A: Scale bars not well placed. Annotation on final set should be D12/D14 DKD?

      Answer: both were Corrected

      __Discussion __47. The authors mention that they want to use DNAJB12/4-HSC70/SGTA axis to impair cancer cell fitness: What effect would this have though in a non cancer model? Would this be a viable approach Although it is obviously early days, which approach would the authors see as potentially favorable?


      Answer: In our previous study we used an approach to target AGR2 in the cytosol because the reflux of AGR2 occurs only in cancer cells and not in normal cells. In that study we targeted AGR2 with scFv that targets AGR2 and is expressed in the cytosol, in this case it will target AGR2 in the cytosol which only occurs in cancer. Here, we suggest to target the interaction between the refluxed proteins and their new partners in the cytosol or to target the mechanism that causes their reflx to the cytosol by inhibiting for instance the interaction between SGTA and DNAJB proteins.


      __ __ Second para: Should be "Here we present evidences"

      Answer: we replaced with “Here we present evidences”

      "DNAJB12 overexpression was also sufficient to promote ERCYS by refluxing AGR2 and inhibit wt-p53 signaling in cells treated with etoposide" Suggest:

      Answer: DNAJB12 overexpression is also sufficient to promote ERCYS by refluxing AGR2 and inhibit wt-p53 signaling in cancer cells treated with etoposide (Figure 3). This suggests that it is enough to increase the levels of DNAJB12 without inducing the unfolded protein response in order to activate ERCYS. Moreover, the downregulation of DNAJB12 and DNAJB14 rescued the inhibition of wt-p53 during ER stress (Figure 2). Thus, wt-p53 inhibition is independent of the UPR activation but depends on the inhibitory interaction of AGR2 with wt-p53 in the cytosol.

      .

      DNAJB12 overexpression was also sufficient to promote ERCYS by increasing reflux of AGR2 and inhibition of wt-p53 signaling in cells treated with etoposide

      Answer: This sentence is repeated twice and was removed

      "Moreover, DNAJB12 was sufficient to promote this phenomenon and cause ER protein reflux by mass action without causing ER stress (Figure 3, Figure 4, and Figure S3)." You dont look at induction of ER stress here, please change the text or explain in more depth with refs if suitable

      Answer: In the initial submission and in the revised version we assayed the activation of the UPR by looking at the levels of spliced Xbp1 and Bip in the different conditions when DNAJB12 and DNAJB14 are overexpressed (Figure S3C and S3D). Our data show that although DNAJB12 overexpression induces ERCYS, there was no UPR activation.

      The mention of viruses is sparse in this paper. If it is a main theory, put it more centrally to the concept, and explain in more detail. As it is, its appearance in the final sentence is out of context.

      Answer: DNAJB12 and DNAJB14 were reported to facilitate the escape of non-envelope viruses from the endoplasmic reticulum to the cytosol. The mechanism of non-envelope penetration is highly similar to the reflux of proteins from the ER to the cytosol. Interestingly, this mechanism takes place when the DNAJB12 and DNAJB14 form a complex with chaperones from both the ER and the cytosol including HSC70, SGTA and BiP (Walczak et al. 2014; Goodwin et al. 2011; Goodwin et al. 2014)..

      Moreover, the UGGT1 that was independently found in our previous mass spectrometry analysis of the digitonin fraction obtained from HEK293T cells treated with the ER stressor thapsigargin and from isolated human GBM tumors (Sicari et al. 2020), is known to deploy to the cytosol upon viral infection (Huang et al. 2017; Sicari et al. 2020). We therefore hypothesized that the same machinary that is known to allow viruses to escape the ER to penetrate the cytosol may play an important role in the reflux of ER proteins to the cytosol.

      Because ER protein reflux and the penetration of viruses from the ER to the cytosol behave similarly, we speculate that viruses hijacked an evolutionary conserved machinery -ER protein reflux- to penetrate to the cytosol. This is key because it was also reported that during the process of nonenveloped viruses penetration, large, intact and glycosylated viral particles are able to penetrate the ER membrane on their way to the cytosol (Inoue and Tsai 2011).

      Action: we developed the discussion around this point and clarified it better because we believe it central to show that viruses hijacked this conserved mechanism.

      **Referees cross-commenting**

      I agree with the comments from Reviewer 1.

      Reviewer 2 also is correct in many ways, but I think that they have somewhat overlooked the relevance of the ER-stress element and treatments. The authors do need to reference past papers more to give a full story, as this includes the groups own papers, I don't think that it is an ethical problem but rather an oversight in the writing. Regarding reviewer 2's concerns about overexpression levels and cell death, the authors do use an inducible cell line and show the levels of DNAJB12 induced (could CRISPR also be considered?). This could be used to further address reviewer 2's concerns. It would also be useful to see data on cell death in the conditions used in the paper. Re concerns about ER integrity, this could be addressed by using IF (or EM) to show a secondary ER marker that remains ER-localised, and this would also be of interest regarding my comment on which categories of proteins can undergo reflux. If everything is relocalised, then reviewer 2's point would be validated.

      Reviewer #3 (Significance (Required)):

      Significance

      General assessment: This paper robustly shows that the yeast system of ER to cytosol reflux of ER-resident proteins is conserved in mammalian cells, and it describes clearly the link between ER stress, protein reflux and inhibition of p53 in mammalian cells. The authors have the tools to delve deeper into this mechanism and robustly explore this pathway, however the mechanistic elements - where not instantly clear from the results - have been over interpreted somewhat The results have been oversimplified in their explanations and some points and complexities of the study need to be addressed further to make the most of them - these are often some of the more interesting concepts of the paper, for example the differences in DNAJB12/14 and how the proteins orchestrate in the cytosol to play their cytosol-specific effects. I think that many points can be addressed in the text, by the authors being clear and concise with their reporting, while other experiments would turn this paper from an observational one, into a very interesting mechanistic one.

      Advance: This paper is based on previous nice papers from the group. It is a nice progressions from yeast, to basic mechanism, to physiological model. But as mentioned, without a strong mechanistic improvement, the paper would remain observatory.

      Audience: This paper is interesting to cell biologists (homeostasis, quality control and trafficking) as well as cancer cell biologists (fitness of cancer cells and homeostasis) and it is a very interesting demonstration of a process that is a double edged sword, depending on the environment of the cells.

      My expertise: cell biology, trafficking, ER homeostasis

      Answer: We would like to thank the reviewer for his/her positive feedback on our manuscript. All the comments of the three reviewers are now addressed and the manuscript has been strengthen. We put more emphasis on the mechanistic aspect with more Ips and knockdowns. We also added data to show that it is physiologically relevant. We hope that after that the revised version addressed all the concerns raised by the reviewers.

      Goodwin, E. C., A. Lipovsky, T. Inoue, T. G. Magaldi, A. P. Edwards, K. E. Van Goor, A. W. Paton, J. C. Paton, W. J. Atwood, B. Tsai, and D. DiMaio. 2011. 'BiP and multiple DNAJ molecular chaperones in the endoplasmic reticulum are required for efficient simian virus 40 infection', MBio, 2: e00101-11.

      Goodwin, E. C., N. Motamedi, A. Lipovsky, R. Fernandez-Busnadiego, and D. DiMaio. 2014. 'Expression of DNAJB12 or DNAJB14 causes coordinate invasion of the nucleus by membranes associated with a novel nuclear pore structure', PLoS One, 9: e94322.

      Grove, D. E., C. Y. Fan, H. Y. Ren, and D. M. Cyr. 2011. 'The endoplasmic reticulum-associated Hsp40 DNAJB12 and Hsc70 cooperate to facilitate RMA1 E3-dependent degradation of nascent CFTRDeltaF508', Mol Biol Cell, 22: 301-14.

      Huang, P. N., J. R. Jheng, J. J. Arnold, J. R. Wang, C. E. Cameron, and S. R. Shih. 2017. 'UGGT1 enhances enterovirus 71 pathogenicity by promoting viral RNA synthesis and viral replication', PLoS Pathog, 13: e1006375.

      Igbaria, A., P. I. Merksamer, A. Trusina, F. Tilahun, J. R. Johnson, O. Brandman, N. J. Krogan, J. S. Weissman, and F. R. Papa. 2019. 'Chaperone-mediated reflux of secretory proteins to the cytosol during endoplasmic reticulum stress', Proc Natl Acad Sci U S A, 116: 11291-98.

      Inoue, T., and B. Tsai. 2011. 'A large and intact viral particle penetrates the endoplasmic reticulum membrane to reach the cytosol', PLoS Pathog, 7: e1002037.

      Malinverni, D., S. Zamuner, M. E. Rebeaud, A. Barducci, N. B. Nillegoda, and P. De Los Rios. 2023. 'Data-driven large-scale genomic analysis reveals an intricate phylogenetic and functional landscape in J-domain proteins', Proc Natl Acad Sci U S A, 120: e2218217120.

      Piette, B. L., N. Alerasool, Z. Y. Lin, J. Lacoste, M. H. Y. Lam, W. W. Qian, S. Tran, B. Larsen, E. Campos, J. Peng, A. C. Gingras, and M. Taipale. 2021. 'Comprehensive interactome profiling of the human Hsp70 network highlights functional differentiation of J domains', Mol Cell, 81: 2549-65 e8.

      Sicari, D., F. G. Centonze, R. Pineau, P. J. Le Reste, L. Negroni, S. Chat, M. A. Mohtar, D. Thomas, R. Gillet, T. Hupp, E. Chevet, and A. Igbaria. 2021. 'Reflux of Endoplasmic Reticulum proteins to the cytosol inactivates tumor suppressors', EMBO Rep: e51412.

      Sicari, Daria, Raphael Pineau, Pierre-Jean Le Reste, Luc Negroni, Sophie Chat, Aiman Mohtar, Daniel Thomas, Reynald Gillet, Ted Hupp, Eric Chevet, and Aeid Igbaria. 2020. 'Reflux of Endoplasmic Reticulum proteins to the cytosol yields inactivation of tumor suppressors', bioRxiv.

      Walczak, C. P., M. S. Ravindran, T. Inoue, and B. Tsai. 2014. 'A cytosolic chaperone complexes with dynamic membrane J-proteins and mobilizes a nonenveloped virus out of the endoplasmic reticulum', PLoS Pathog, 10: e1004007.

      Yamamoto, Y. H., T. Kimura, S. Momohara, M. Takeuchi, T. Tani, Y. Kimata, H. Kadokura, and K. Kohno. 2010. 'A novel ER J-protein DNAJB12 accelerates ER-associated degradation of membrane proteins including CFTR', Cell Struct Funct, 35: 107-16.

      Youker, R. T., P. Walsh, T. Beilharz, T. Lithgow, and J. L. Brodsky. 2004. 'Distinct roles for the Hsp40 and Hsp90 molecular chaperones during cystic fibrosis transmembrane conductance regulator degradation in yeast', Mol Biol Cell, 15: 4787-97.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC-2023-02306

      Corresponding author(s): John, Yates

      [Please use this template only if the submitted manuscript should be considered by the affiliate journal as a full revision in response to the points raised by the reviewers.

      • *

      If you wish to submit a preliminary revision with a revision plan, please use our "Revision Plan" template. It is important to use the appropriate template to clearly inform the editors of your intentions.]

      1. General Statements [optional]

      We greatly appreciate the reviewers taking time from their busy scientific careers to evaluate our manuscript. We were elated to read all the positive comments, such as “the conclusions are well-supported and convincing”, “should contribute to a more nuanced understanding of SCZ pathogenesis”; “The potential implications for drug development underscore the broader significance of the study in advancing our knowledge of neurobiology and its relevance to neurological disorders like schizophrenia”, and “The study is informative, and has great potential to enrich the specific literature of this field”. We also found the constructive criticism very helpful for improving our manuscript. We performed additional experiments and bioinformatic analyses, as requested. We modified the manuscript to answer the reviewers’ questions. Due to its complexity, it is difficult to describe the different and sometimes conflicting hypotheses of SCZ pathogenesis in a single manuscript. This complexity is reflected in the conflicting requests from the reviewers. One reviewer requested we investigate and highlight the role of non-neuronal cells in SCZ while another reviewer suggested we did not focus enough on synaptic proteins. We believe we have achieved a balance to represent the intricacy of SCZ biology and the different opinions of the reviewers.

      Thanks again.

      2. Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      • *

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      Summary: Provide a short summary of the findings and key conclusions (including methodology and model system(s) where appropriate). In this manuscript, McClatchy and colleagues used a conventional approach combining immunoprecipitation (IP) of endogenous target proteins (baits) followed by liquid chromatography mass spectrometry (MS) analysis of the co-immunoprecipitating proteins to map protein-protein interaction (PPI). This interaction network is centered around baits that had been annotated as susceptibility factors for schizophrenia (SCZ). A variety of previous studies have identified thousands of such SCZ susceptibility factors. Mostly based on the availability of antibodies, 8 bait proteins were selected in this study. The authors reasoned that immunoprecipitating endogenous proteins from tissues using specific antibodies was a more accurate view of physiological conditions than epitope tagging followed by affinity purification (AP) from cells in culture. The model system from which proteins were extracted was the hippocampus dissected from mice that had been treated or not by phencyclidine (PCP), a drug that has been shown to induce SCZ symptoms in humans and animals. By comparing the proteins identified and quantified from the PCP-treated samples against control IPs and/or saline-injected mouse controls, a large number of PPI were deemed statistically significant. Most of these potential interactors were not present in PPI databases (BioGRID), most likely because such databases are populated with large-scale APMS datasets from cell cultures, with very few studies using brain tissue. Strikingly, many of the co-immunoprecipitated proteins were also known as SCZ susceptibility factors, which lend weight to the hypothesis that these factors form a large protein interaction network, localized at the synapses.

      Major comments: - Are the key conclusions convincing? Overall, the conclusions drawn from the experimental design, data analysis, and corroboration with existing literature are well-supported and convincing. When selecting the SCZ susceptibility factors, the authors clearly state their goal, the databases used for gene selection, and the rationale for choosing proteins with synaptic localization. The inclusion of evidence from genetic studies and previous publications strengthens the credibility of the selected genes. The methodology used to establish the novel SCZ PPI network is mostly well-described (see minor comments below). The use of an 15N internal standard also adds rigor to the quantitation of PPI. The GO enrichment analysis provides valuable insights into the biological functions and cellular components associated with the SCZ PPI network. The annotation of identified proteins using the SynGo synaptic database and the distribution of annotated synaptic proteins among different baits further support the biological relevance of this PPI network. The cross-referencing of the PPI network with published genetic studies on SCZ susceptibility genes adds robustness to the findings. Specifically, the observation that 68% of protein interactors have evidence of being potential SCZ risk factors is a strong corroboration of the prevailing hypothesis in the field. Finally, the significant changes induced by PCP that were identified for all baits except Syt1, along with the comparison of altered proteins with SAINT-identified PPI, add depth to the understanding of PCP modulation.

      - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? No, but note that APMS/IPMS has been around for more than a decade (Introduction page 3).

      We agree and did not mean to imply that IP-MS is new technology. We tried to convey that IP-MS is not new technology, but the number of IP-MS studies employed to study the PPI of endogenous proteins in brain tissue is a small percentage of all the published PPI MS studies.

      We added the following to the Conclusions to clarify this point: “Although IP-LC-MS technology has been employed for more than a decade, quantitation of proteins using this strategy in mammalian tissue is scarce in the literature.”

      - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. One piece of data that is missing are Western blots using the 8 selected antibodies against the proteins extracted from their experimental samples to validate the antibodies recognize 1 protein of the expected size from these tissue extracts.

      We took your suggestion and performed immunoblots with our 8 IP antibodies using the starting material (i.e. rat brain hippocampus). All antibodies recognized a single band of the approximate molecular weight of the target except for the Gsk3b, which produced a doublet instead of a single band. This image is similar to what has been observed with the phosphorylation of Gsk3b(Krishnankutty, Kimura et al. 2017, Vainio, Taponen et al. 2021). To provide evidence that the additional band observed for Gsk3b is the phosphorylated target protein, we searched our Gsk3b IP dataset for a differential phosphorylation (i.e. 79.9663) on S,T, or Y. Even though we did not perform phosphorylation enrichment, we identified S389 as abundantly phosphorylated in all Sal and PCP samples consistent with our immunoblot. Images of these immunoblots are now Supplementary Figure 1.

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. Running SDS-PAGE and Western blotting should be straightforward and cheap.

      - Are the data and the methods presented in such a way that they can be reproduced? Yes

      - Are the experiments adequately replicated and statistical analysis adequate? Yes

      Minor comments: - Specific experimental issues that are easily addressable. The rationale for the short duration between PCP injection and animal sacrifice is only explained in the discussion section (page 17). The fact that this short treatment of less than 30 min should prevent any change in transcription or translation should be introduced earlier (in the experimental procedures).

      We agree this is an important aspect of the study and that it suggests that the effect of PCP is independent of changes in transcription and translation as stated in the Discussion.

      We added the following to the Introduction:

      “PCP was administered for less than 30min., which precluded any changes in transcription or translation and allowed us to focus on PPI.*” *

      Note that the duration is written as 26 min on page 4 and 25 min on page 9. Please reconcile these numbers*. *

      We have corrected this typo. It was 26min.<br /> Is there any biological significance for this SCZ study that the mice were maintained on a reverse day-night cycle?

      Rats are nocturnal animals, i.e. active at night and sleep during the day. In this study, rats were housed on a reverse day-night cycle so that assessment of the response to PCP could be evaluated during their active phase. This is not specific SCZ research and is the routine protocol for behavioral testing in the Powell laboratory. It is not clear from reading Experimental Procedures/Bioinformatic Analysis section (page 6) if normalized N14/N15 protein ratios measured in the bait-IPs and control-IPs were used for the SAINT analysis? Or did the authors used label-free quantitation with spectral counts?

      We apologize for not making the methods clearer. In the results, it is stated that the N14 identifications are used in the SAINT analysis, and we state in the Discussion that SAINT uses spectral counts. We modified the Experimental Procedures/Bioinformatic Analysis section (page 6) to state: The input for SAINT was only the 14N identifications.

      *- Are prior studies referenced appropriately? Yes

      • Are the text and figures clear and accurate? *Fig1C: The workflow is a little too simple, the authors might want to add more details.

      We revised Fig1C with more details as suggested.

      FigS1C: Please add x-axis title (spectral counts) directly to the figure.

      “Spectral counts” was added to the x-axis. FigS1C is now FigS2C ,with the addition of the immunoblots you suggested. Fig2B-D: The color scale bar should have number values to denote lower and upper limits in % (as opposed to "lowest" and "highest"). Numerical values were added to replace the upper and lower limits. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions? No * *

      Reviewer #1 (Significance (Required)):

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. In this study, the authors have drastically expanded the protein interaction landscape around 8 known SCZ susceptibility factors by using a conventional IPMS approach. Performing the IPs on protein extracted from hippocampus dissected from mice treated with phencyclidine to model SCZ increases the biological significance of such lists of proteins. Furthermore, the co-immunoprecipitation of many other SCZ susceptibility factors along with the 8 selected baits supports the hypothesis that these proteins of varied functions are part of large interaction networks. Overall, the integration of experimental data with in silico networks, along with the quantification of PPI changes in response to PCP, should contribute to a more nuanced understanding of SCZ pathogenesis. The potential implications for drug development underscore the broader significance of the study in advancing our knowledge of neurobiology and its relevance to neurological disorders like schizophrenia.

      • Place the work in the context of the existing literature (provide references, where appropriate). Overall, this study contributes to the existing literature by providing experimental data on in vivo PPI networks related to SCZ risk factors. Not only do the authors validate 124 known interactions but also they identify many novel PPI, due to a gap in the existing literature regarding the comprehensive mapping of PPI directly from tissue extracts, especially brain tissue. The authors advocate for more IPMS studies in mammalian tissues to generate robust tissue-specific in silico networks, which agrees with the growing understanding of the importance of tissue-specific networks for identifying disease mechanisms and potential drug targets. Furthermore, the SCZ PPI network reported here is enriched in proteins previously associated with SCZ, which aligns with the existing literature emphasizing the involvement of certain proteins and pathways in the pathogenesis of SCZ [References: 78-85]. The authors also investigate the response of the SCZ network to PCP treatment, hence providing insights into the potential effects of post-translational modifications, protein trafficking, and PPI alterations in a model of schizophrenia, which adds to existing knowledge about the impact of PCP on the molecular processes associated with SCZ [References: 88, 89, 92].

      • State what audience might be interested in and influenced by the reported findings. Overall, the findings reported in this manuscript have implications for both basic research in molecular biology and potential translational applications in the development of targeted therapies for neurological disorders, particularly schizophrenia. The study delves into in vivo protein-protein interaction (PPI) networks related to genes implicated in schizophrenia (SCZ) risk factors. Researchers in neuroscience, molecular biology, and psychiatry would find the information valuable for understanding the molecular basis of SCZ. The study highlights the potential for identifying disease "hubs" that could be drug targets. Pharmacologists and drug developers interested in targeting protein complexes for drug development, especially in the context of neurological disorders, may find the study relevant.

      • Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. Technical Expertise | biochemistry, liquid chromatography mass spectrometry, proteomics, computational biology, protein engineering, protein interaction networks, post-translational modifications, protein crosslinking, proximity labeling, limited proteolysis, thermal shift assay, label-free and isotope-labeled quantitation. Biological Applications | human transcriptional complexes, apicomplexan parasites, viruses, nuclear envelope, ubiquitin ligases, non-model organisms.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      Summary: McClatchy, Powell and Yates aimed at identifying a protein interactome associated to schizophrenia. For that, they treated rats (N14 and N15) with PCP, which disturbs gutamatergic transmission, as a model for the disease and co-immunoprecipitated hippocampi proteins, which were further analyzed by standard LC-MS.

      The study is new, considering not much has been done in this direction in the field of schizophrenia. This justifies its publication. On the other hand, a major flaw of the is the lack of information on the level of interaction of the so called protein interactome. Meaning, we cannot distinguish, as the study was performed, which proteins are directly interacting with the targets of interest from proteins which are interacting with targets´ interactors. The different shells of interaction are crucial information in protein interactomics.

      Major: most of I am pointing below must be at least discussed or better presented in the paper, as It may not be solvable considering how the study has been conducted.

      1) The study fails in defining the level of interaction of the protein interactome with the considered targets. This has been shortly mentioned in the discussion, but must be more explicit to readers, for instance, in the abstract, introduction and in the methods sections. We agree this is crucial information that is absent from our dataset. As we explained in the Discussion, we cannot distinguish between PPI that are direct interactors with the target protein and PPI that reside in a multi-protein complex that includes the protein (i.e. indirect). This is an inherent problem with any IP-MS study. We amended the Introduction to highlight the ambiguity of the interaction data produced by the IP-MS approach, as you suggested.

      Text added to the Introduction:

      “Regardless of whether Ab or tagged proteins are employed to identify PPI from a biological sample, it cannot be determined if the identified interactor binds directly to the target protein or reside in a complex of proteins that includes the target protein (i.e. indirect).”

      Since this important information is routinely missing from IP-MS studies, we decided to try to determine the level of interaction by using the artificial intelligence algorithm AlphaFold3(AF3). We believe it is not yet optimized for PPI, but AF3 is a big leap forward in the field of structural biology. For example, we observed AF3 did not predict high confident structures for our large membrane target proteins and was unable to validate known direct PPI of these targets. In addition, analyzing data with AF3 is currently not automated or streamlined so with ~1600 PPI identified in our dataset, we chose to look at one target protein, Ppp1ca. AF3 identified many known direct binding proteins in our Ppp1ca PPI dataset, which gives high confidence to the novel PPI predicted to be direct interactors. The AF3 data is encompassed in an additional Figure 6.

      The following was added to the Results Section:

      “A disadvantage of IP-MS studies is that it cannot distinguish between a PPI that binds directly to the target protein, and a PPI in which the interactor and target protein reside the same multiprotein complex (i.e. indirect). We sought to predict which PPI may be directly interacting with its target protein by using the artificial intelligence algorithm AlphaFold3(AF3) (Abramson, Adler et al. 2024). First, we analyzed the predicted AF3 structure of the targets using the pTM score and the fraction of each structure calculated to be disordered (Figure 6A and Supplementary Table7). Our reasoning was that if targets have a poorly resolved structures, it will be difficult to screen them for direct PPI. A pTM score >0.5 suggests that the structure may be correct (the highest confidence score is 1). Undefined or disordered regions hinder the accuracy of the prediction. All targets possessed a pTM score > 0.5 except Syt1. The disordered fraction negatively correlated with the pTM score, as expected. Gsk3b, Ppp1ca, and Map2k1 had the highest pTM scores and were also the smallest of our target proteins (Figure 6B). Ppp1ca had the most confident structure (i.e. pTM 0.9) and the smallest disordered fraction (i.e. 0.07). Next, we determined the AF3 prediction of previously reported direct interactions of the targets. We used the iPTM score to determine interaction confidence. An iPTM score >0.8 is considered a highly confident direct interaction, whereas 0.8. These eight PPI have all previously been reported to form a direct interaction with Ppp1ca, except Phactr3 (Zhang, Zhang et al. 1998, Terrak, Kerff et al. 2004, Hurley, Yang et al. 2007, Marsh, Dancheck et al. 2010, Ragusa, Dancheck et al. 2010, Ferrar, Chamousset et al. 2012, Choy, Srivastava et al. 2024, Xu, Sadleir et al. 2024)*. Phactr3 is structurally similar to, but less studied than, the reported direct interactor Phactr1. These interactors are all inhibitors of PP1 except Ppp1r9b which targets Ppp1ca to specific subcellular compartments. Nine PPI were assigned a score The following has been added to the Discussion:

      Our SCZ PPI network consists of two types of PPI: direct physical interactions and “co-complex” or indirect interactions. Typically, the nature of the interaction can be distinguished in IP-MS studies. We decided to employ the new AF3 algorithm to screen the PPI of Ppp1ca to provide evidence for direct interactors. We chose to examine the PPI assigned to Ppp1ca, because its structure was the most confident among our target proteins and AF3 correctly predicted a known direct interactor with high confidence. Ppp1ca is a catalytic subunit of the phosphatase PP1, which is required to associate with regulatory subunits to create holoenzymes (Li, Wilmanns et al. 2013). Eighteen PPI were predicted to be directly interacting with Ppp1ca using a 0.6 or higher iPTM filter. This filter may be too conservative and generate false negatives, because another study employed a 0.3 filter followed by additional interrogation to screen for direct PPI (Weeratunga, Gormal et al. 2024). Forty-four percent of these predictions were confirmed by previous publications. Most of the validated direct interactions are inhibitors of the phosphatase, but one, Ppp1r9b (aka spinophilin), is known to target Ppp1ca to dendrite spines to enhance its activity to specific substrates (Allen, Ouimet et al. 1997, Salek, Claeboe et al. 2023). This high correlation with the literature provides substantial confidence in the novel PPI predicted to be direct Ppp1ca interactors. The AF3 screen predicted that NDRG2 directly interacts with Ppp1ca. This protein is known to regulate many phosphorylation dependent signaling pathways by directly interacting with other phosphatases including Pp1ma and PP2A (Feng, Zhou et al. 2022, Lee, Lim et al. 2022). Actin binding protein Capza1 was also predicted to directly interact with Ppp1ca and Ppp1ca interacts with actin and its binding proteins to maintain optimal localization for efficient activity to specific substrates (Foley, Ward et al. 2023). Hsp1e is a heat shock protein predicted to directly interact with Ppp1ca. Although there is no direct connection to Ppp1ca, other heat shock proteins have been reported to regulate Ppp1ca (Mivechi, Trainor et al. 1993, Flores-Delgado, Liu et al. 2007, Qian, Vafiadaki et al. 2011). We also observed that many of these direct PPI were altered with PCP treatment. One direct interactor, Ppp1r1b (aka DARPP-32), is phosphorylated at Thr34 by PKA in the brain upon PCP treatment. This phosphorylation event converts Ppp1rb to a potent inhibitor of Ppp1ca(Svenningsson, Tzavara et al. 2003). Importantly, manipulation of Thr34 attenuated the behavioral effects of PCP. Consistent with this report, Ppp1r1b-Ppp1ca interaction was only observed with PCP in our study. Further investigation is needed to determine if our novel direct interactors regulate the PCP phenotype. We conclude that AF3 can provide important structural insights into the nature of PPI obtained from large scale IP-MS studies.

      2) Considering the protein extraction protocol, it is fair to mention that only the most soluble proteins are being considered here. I am bringing this up since the importance of membrane receptors is clear in the studied context. This is an interesting point. It has been predicted that transmembrane proteins constitute 25-30% of the proteome(Dobson, Remenyi et al. 2015). Thus, we would predict our dataset will have more soluble proteins than membrane proteins. Half of our target proteins were transmembrane proteins, so in designing the protocol for this study we ensured that these membrane proteins could be significantly enriched compared to the control IPs (Supplementary Figure 2C). In addition, compared to soluble proteins, membrane proteins are notoriously difficult to identify by bottom-up proteomics (Savas, Stein et al. 2011). We decided to investigate how many of our protein interactors were transmembrane proteins. Using Uniprot, 199 (20%) of our protein interactors were determined to have a transmembrane domain. Therefore, this data does not support the statement that only the most soluble proteins are being considered in our study. We added this percentage of transmembrane proteins in our network to the text of the Results section.

      3) It is not clear from the methods description if antibodies from all 8 targets were all together in one Co-IP or have been incubated separately in 8 different hippocampi samples. It seems the first, given how results have been presented. If so, this maximizes the major issue raised above (in 1). We apologize for not clearly describing our experimental design. All the targets were immunoprecipitated separately and analyzed separately on the mass spectrometer. With all the biological replicates and two conditions (i.e. Saline and PCP), we performed 48 individual, separate IPs. There were an additional 48 individual, separate IPs run in parallel that were the control IPs.

      We modified the schematic of our experimental design in Figure 1C to clarify that the 8 targets IPs were analyzed separately. In addition, we modified the Results to read:

      “In total, 96 (48 bait and 48 control) IPs were performed, and each was analyzed separately by LC-MS analysis.”

      4) Definitely, results here are not representing a "SCZ PPI network". PCP-treated animals, as any other animal model, are rather limited models to schizophrenia. As a complex multifactorial disease, synaptic deficits, which is the focus of this study, can no longer be considered "the pivot" of the disease. Synaptic dysfunction is only one among many other factors associated to schizophrenia.

      We do agree that synaptic dysfunction is only one factor associated with SCZ and we will discuss this more in our response to your next comment.

      We understand the limitations of PCP as an animal model of SCZ. It is quite difficult to model a specific human complex multifactorial neurological disease in rodents and we would contend that there is no single universal SCZ model that everyone agrees with. We addressed this by adding the following to the Introduction:

      Since many SCZ symptoms are uniquely human, this is no single animal model that truly replicates all the complex human SCZ phenotypes(Winship, Dursun et al. 2019). In this respect, all SCZ animal models can be considered limited.* “ *

      We respectfully disagree, however, with the term SCZ PPI network. This study is focused on SCZ by choosing proteins implicated in SCZ, quantitating how the PPI changes in a SCZ model, and discussing how our findings are relevant to SCZ pathogenesis. So, it seems logical to call our dataset a SCZ PPI network. We do concede that without further experimentation we do not know if these PPI play a causal role in SCZ. Furthermore, our novel PPI may involve biological pathways unrelated to SCZ and that have relevance to other biological conditions.

      We added the following statement to the Discussion to address this comment:

      “Even though our network was constructed in the context of SCZ, our dataset has relevance to other neurological diseases where our targets have been implicated in the pathogenesis.

      5) Authors should look for protein interactions that might be happening also in glial cells. They are not the majority in hippocampus, but are present in the type of tissue analyzed here. Thus, some of the interactions observed might be more abundantly present in those cells. Maybe enriching using bioinformatics tools the PPI network to different cell types.

      As mentioned above, we agree that synaptic dysfunction is just one of the hypotheses of SCZ pathogenesis and emerging evidence suggests that dysfunction in astrocytes and microglia are factors. Since these non-neuronal cells can regulate synapses, these hypotheses are not mutually exclusively and suggests that at the cellular level SCZ etiology involves multiple cell types.

      We addressed your query by comparing our PPI network to an RNA-seq analysis of different cell types in the rodent brain(Zhang, Chen et al. 2014). First, we analyzed our target proteins, and found that they were expressed in all cell types to varying degrees except Syngap which was not in the RNA-seq database. This data is now represented in Figure 3E. We then determined the RNA abundance distribution of all the protein interactors, which is represented in Figure 3D as a heatmap. From a bird’s eye view, it suggests that some PPI exist in non-neuronal cells. Next, we determine how many of our protein interactors were enriched in one cell type, which is shown in Figure 3F. We defined an enriched protein as having >50% of the RNA signal in one cell type. We identified 175 proteins that were enriched in one cell type compared to the entire RNA-seq dataset which had 4008 enriched proteins. In the entire RNA-seq dataset, 24% of the enriched proteins were in neurons whereas 47% of our protein interactors were enriched in neurons. This is consistent with the enrichment of synaptic proteins in our network. There was also an increased percentage of astrocytes (19%) and oligodendrocytes (6%) in our network compared to the entire database (i.e. astrocytes-11% and oligodendrocytes-4%). In other cell types, such as microglia, there was less protein enrichment in our network compared to the database. We have amended this cell type analysis to our manuscript and concluded that a portion of our PPI network may occur in non-neuronal cells. We also created a supplementary table of our network with its associated RNA-seq data.

      Text added to the Results:

      “Non-synaptic proteins represented 59% of our network suggesting that some PPI may occur in non-neuronal cells. To investigate this possibility, we annotated our network with a transcriptome rodent brain database of eight cell types(Zhang, Chen et al. 2014). All the targets were detected in all cell types but there was obvious enrichment in specific cell types for some targets (Figure 3E). Syngap1 was not in the database. We also observed a large variation of cellular distributions for the interactors (Figure 3D). Next, we sought to determine how many interactors are enriched in a particular cell type by defining cell enrichment as a protein having >50% RNA signal in one cell type. We identified 175 protein interactors enriched in one cell type, whereas the entire database had 4008 proteins enriched (Figure 3F). Consistent with our synaptic enrichment, 47% of the enriched protein interactors were in neurons whereas only 24% of the enriched protein in the entire database were in neurons. We also observed an increase in protein interactors enriched in astrocytes compared to the database. Overall, this analysis provides evidence that our identified PPI may occur in non-neuronal cells.”

      Text added to the Discussion:

      “The exact etiology of SCZ, however, remains unclear and synaptic dysfunction is only one hypothesis (Misir and Akay 2023). There is evidence for the involvement of non-neuronal cell types, including endothelial cells, astrocytes, and microglia(Tarasov, Svistunov et al. 2019, Rodrigues-Neves, Ambrosio et al. 2022, Stanca, Rossetti et al. 2024). Although we observed an enrichment of synaptic proteins in our SCZ network, we provided evidence that a portion of our network may occur in non-neuronal cells. Since non-neuronal cells can regulate synapses(Vilalta and Brown 2018, Bauminger and Gaisler-Salomon 2022), synaptic dysfunction and perturbations in non-neuron cells in SCZ etiology are not mutually exclusive. Our data corresponds with emerging evidence that pathogenesis is multifaceted, involving dysfunction in multiple cell types.

      Minor: 1) in the abstract, it is not clear if 90% of the PPI are novel to brain tissue in general or specifically schizophrenia. We apologize for the confusing sentence. 90% are novel meaning the PPI have not been reported in any study. We changed the abstract to read:

      “Over 90% of the PPI have not been previously reported.”

      2) authors refer to LC-MS-based proteomics as "MS" all across the text. Who am I to say this to Yates et al, but I think it is rather simplified use "Mass Spectrometry Analysis", when this is a typical LC-MS type of analysis We agree with you. We have replaced MS analysis with LC-MS analysis in the manuscript.

      3) Several references used to construct the hypothesis of the paper are rather outdated: several from 10-15 years ago. It would be interesting to provide to the reader up to date references, given the rapid pace science has been progressing. We agree many of the references are 10-15 years old. Many of the hypotheses and biological mechanisms we discussed can be supported by too many studies to cite them all, due to space. If we could, we would. We also agree that there are many more recent studies that have confirmed and added more details to the original discovery or hypothesis cited. We cite the first study to support our conclusions because it deserves the most credit.

      4) "UniProt rat database". Please, state the version and if reviewed or unreviewed.

      This information was added to the Methods section. UniProt reviewed rat database with isoforms 03-25-2014.

      Reviewer #2 (Significance (Required)):

      The study is informative, and has great potential to enrich the specific literature of this field. But should tone down some arguments, given the experimental limitations of the PPI network (as described above) and should state PCP-treated rats as a limited model to schizophrenia.

      Reviewer #3 (Evidence, reproducibility and clarity (Required)):

      Summary

      It is now widely accepted that schizophrenia is polygenic disorder in which a large fraction of the genetic risk is in variants affecting the expression of synaptic proteins. Moreover, it is known that these synaptic proteins are found in multiprotein complexes and that many proteins encoded by schizophrenia risk genes interact directly or indirectly in these complexes. It is also known that some drugs including phencyclidine, which binds to NMDA receptors and to Dopamine D2 receptors (not mentioned by the authors) can induce schizophreniform psychosis. The authors have set out to advance on this position by performing proteomic mass spectrometry studies on proteins identified as encoded by schizophrenia risk genes. They target 8 proteins for immunoprecipitation from rat brain and identify coisolated proteins and perform various network analyses. In the most interesting part of the paper they ask if PCP-treatment altered protein interactions and report various changes.

      Major comments:

      1. Choice of target proteins. It was not until the first paragraph of the results section that the authors first name the 8 synaptic proteins that have chosen to study. This information should be in the abstract.

      This information was added to the abstract as requested.

      The authors then use figure 1A and 1B as evidence that these 8 "baits" are schizophrenia-relevant proteins. Figure 1A does not provide any evidence at all and Figure 1B is about as weak a line of evidence imaginable - a histogram of the number of papers that have the search term "schizophrenia" and the protein name. I tried this search for Grin2B and almost immediately found papers that reported no association between Grin2B and schizophrenia (e.g. PMID: 33237434). Figure 1B should be scrapped.

      The purpose of Figure 1A was not to demonstrate that there is evidence that our proteins are involved in SCZ. The purpose of this figure is to show that these proteins are diverse in function and structure (blue = membrane proteins; yellow = soluble proteins), and that there are published studies reporting physical and functional interactions between these 8 proteins. This suggests that a more extensive network may exist.

      We agree that Figure 1B does not specifically describe how each protein is related to SCZ but demonstrates how many papers investigating their connection to SCZ have been published. We understand how by itself, this can be considered weak. We still think it is important to show that multiple laboratories have published papers connecting these proteins to SCZ. Instead of scrapping this figure, we have moved it to the Supplementary Figure 2A.

      We read PMID: 33237434 and interpret their findings quite differently than you. This report examined whether one single nucleotide mutation (SNV) in Grin2b is associated with the cognitive dysfunction in SCZ but did not examine if this mutation is associated with the other major SCZ phenotypes (i.e. psychotic and emotional). Specifically, the study selected 117 “patients in whom cognitive dysfunctions are present despite effective antipsychotic treatment of other schizophrenia symptoms.” The study concluded that Grin2B SNV was not associated with this subset of patients but concluded that they need to search for other NMDAR variants and study their association with SCZ. We would argue that the only reason this group performed these experiments was the well-known association between Grin2b and SCZ. Many studies have found SNVs in Grin2B that are associated with SCZ, but there are conflicting reports. It is unclear if the discrepancies are connected to different cohorts, complexity of SCZ phenotype, or small sample sizes. Regardless of Grin2B mutations significantly associated with SCZ, there are several lines of evidence that Grin2B is involved in SCZ. Most importantly, Grin2b is a component of the NMDAR, which is a key player to the SCZ hypo-glutamate hypothesis and the receptor that binds PCP. By immunoprecipitating Grin2b, we are analyzing the PPI network of NMDAR, which is arguably the most studied complex in SCZ research.

      The remaining part of paragraph 1 of the results does not provide an adequate, let alone systematic, justification for the use of the 8 baits. It would be appropriate to construct a table with the 8 proteins and cite relevant papers and identify the basis for why they are implicated in schizophrenia (is it a direct mutation or some other evidence?). What makes these 8 proteins better than many others that are cited as synaptic schizophrenia relevant proteins?

      We apologize for not clearly and thoroughly describing the reasons for choosing our baits. As stated in the first paragraph of the Results, we chose the proteins that had evidence of being a SCZ risk factor in SCZ databases that included a plethora of human genomic studies. This criterion by itself results in ~5000 genes. To further narrow our candidates, we chose targets that were synaptic and were observed to have phosphorylation changes in response to PCP in an SCZ animal model. Since protein-protein interactions (PPI) are often dependent on phosphorylation, we believe this is an important criterion for quantitation of PPI in response to PCP. These requirements still resulted in a list of hundreds of proteins. So, what makes these better than any other SCZ relevant protein? As stated in the manuscript, the major limiting criterion was identifying commercial antibodies that can efficiently immunoprecipitate their target in brain tissue. Since there are many reports associating our targets with SCZ, we directed the reader to SCZ databases that compile large genomic association studies. We understand, however, the request for more specific information regarding the biological connection between these proteins and SCZ. We took your suggestion and constructed a table with our 8 targets, and it is now Figure 1A. In this table, we selected references to indicate if the target has reported changes in expression and/or activity in SCZ samples (i.e. human and animal model) or genetic association with SCZ in human studies.

      The methods of protein extraction are particularly concerning. The postsynaptic density of excitatory synapses (which contains several of the target proteins in this study) has been notoriously difficult to solubilise unless one uses high pH (9) and harsh detergent extraction (1% deoxycholate). The authors use pH 7 and weak detergent conditions, which are likely to be inefficient for solubilising at least several of the target proteins. Nowhere do the authors report how much of the total of their target protein is being solubilised. Indeed, there are no figures showing biochemical conditions at all. What if only a small percentage of the target protein is being immunoprecipitated - what does this mean for the interaction data? How do we know if the fraction being immunoprecipitated is from the synapse? (why did they not use synaptosomes).

      How do we know if the fraction being immunoprecipitated is from the synapse? (why did they not use synaptosomes). The absence of this kind of data undermines the reader's confidence in the findings.

      We apologize for not clearly explaining our experimental design We were not interested in identifying the PPI of the PSD. All these proteins have been localized to the synapse, but they are also localized to other neuronal compartments and non-neuronal cell types. Synaptic dysfunction is one hypothesis of SCZ pathogenesis, but there is evidence of other cell types, including astrocytes, microglia, and oligodendrocytes(Kerns, Vong et al. 2010, Ma, Abazyan et al. 2013, Goudriaan, de Leeuw et al. 2014, Park, Noh et al. 2020). For these reasons, we chose an unbiased approach to identifying PPI.

      The Results have been amended to read: “All the targets are localized to the synapse, but also localized to non-synaptic compartments and expressed in non-neuronal cells. Thus, since there is also evidence for non-synaptic perturbations contributing to SCZ pathogenesis, we chose to perform an unbiased analysis in unfractionated brain tissue (Tarasov, Svistunov et al. 2019, Rodrigues-Neves, Ambrosio et al. 2022, Stanca, Rossetti et al. 2024). “

      Why do we choose a specific solubilization strategy? Harsh detergents can disrupt PPI and prevent efficient enrichment of the target by disrupting the target-antibody interaction(Pankow, Bamberger et al. 2015). To identify protein interactions, mild detergent conditions are typically employed in PPI studies. We used a combination of “weak” detergents (i.e. 0.5% NP-40, 0.5% Triton, and 0.01% Deoxycholate) to help prevent non-specific PPI, but still allowing efficient enrichment of the target proteins. We do agree that with our conditions the targets were not completely solubilized. It is a balancing act to find the correct conditions for IP-MS analysis. Since we are unable to immunoprecipitate all the target protein, we did not identify all the PPI for each target, and we did not make this claim. Importantly, we did identify known interactions for all our targets. Our mild detergent protocol is similar to other PPI studies and our results validates results reported in previous studies. It is more important to significantly enrich the target protein over control than to achieve complete solubilization (Supplementary Figure 2D). This allows us to use control IPs to successfully employ the SAINT algorithm to determine which proteins are confident PPI using a 5% FDR.

      How do we know protein are being immunoprecipitated from the synapse? As we show in Figures 2B and 3A, multiple proteins are annotated to the synapse with different databases, Gene ontology and SynGO. Well-known synaptic PPI were also observed, such as Grin2B-Dlg4(i.e. PSD-95), providing further evidence for proteins being immunoprecipitated for the synapses. Besides validating over a hundred published PPI interactions, we also identified many reciprocal interactions between the target datasets demonstrating the reproducibility of our protocol. Thus, we respectfully disagree with you and assert that our PPI network is very confident.

      The immunoprecipitation protocol is unusual in that the homogenates were incubated overnight (twice), which is a very long period compared to most published protocols. This is a concern because spurious protein interactions could form during this long incubation.

      There are many different immunoprecipitation protocols in the literature. The IP conditions depend upon the target protein and the antibody employed. Specifically, the abundance of the target and the affinity of the antibody to the target will dictate the IP conditions. We routinely perform overnight incubation for our IP-MS studies(Pankow, Bamberger et al. 2016, McClatchy, Yu et al. 2018). In our experience with brain tissue, this results in the highest enrichment of the target protein and the best reproducibility between biological replicates compared to IP protocols with shorter incubation times. Many other laboratories use overnight incubations(Lin and Lai 2017, Iqbal, Akins et al. 2018, Lagundzin, Krieger et al. 2022), so we do not consider our protocol unusual. We do find that IPs with tagged proteins in cell culture are more amenable to short incubation times. We have no evidence that overnight incubation causes spurious protein interactions nor could find any in the literature. Non-specific interactions are a concern with IP-MS experiments regardless of the incubation time. We took multiple steps to reduce the non-specific PPI from affecting our dataset. The first overnight incubation was incubating the brain lysate with agarose beads linked to IgGs to preclear the lysate from “sticky” non-specific interactors binding to IgGs and the beads. In addition, control IPs with IgG crosslinked to beads were incubated with brain lysate in parallel to each target IP. We computationally compared the non-specific control IPs with the target IPs using the SAINT algorithm to generate a confident list of PPI with a stringent 5% FDR. Therefore, our pipeline is specifically designed to prevent spurious PPI.

      In the section "Biological interpretation of scz PPI network". Surprisingly the authors found that synaptic proteins that are exclusively postsynaptic (Grin2B, SynGAP) or exclusively presynaptic (Syt1) show very high percentages of their interacting proteins are from the synaptic compartments where the target protein is not expressed. The authors offer no explanation for this paradox. One explanation for this could be that spurious PPIs have formed in the protein extraction/immunoprecipitation protocol. These findings need validation by biochemical fractionation of synapses into pre and post synaptic fractions and immunohistochemistry to demonstrate the subsynaptic localisation of the proteins. Grin2b is traditionally described as exclusively post-synaptic, but there is evidence for other localizations, including presynaptic(Berretta and Jones 1996, Sjostrom, Turrigiano et al. 2003, Bouvier, Larsen et al. 2018) and expression in astrocytes(Serrano, Robitaille et al. 2008, Lee, Ting et al. 2010, Lalo, Koh et al. 2021, Kim, Choi et al. 2024). Syngap has been localized to non-synaptic sites and glia expression in addition to its heavily studied role at the post synapse(Moon, Sakagami et al. 2008, Araki, Zeng et al. 2015, Birtele, Del Dosso et al. 2023). Syt1 is commonly used as a presynaptic marker, but along with other proteins previously reported to be exclusively presynaptic (such as SNAP-25), it has been localized to the postsynapse (Selak, Paternain et al. 2009, Tomasoni, Repetto et al. 2013, Hussain, Egbenya et al. 2017, Madrigal, Portales et al. 2019, Sumi and Harada 2023). Similarly, SynGo database assigns both post-synaptic and pre-synaptic localizations to Grin2b as stated in the manuscript. Thus, our data is not paradoxical, but supports the emerging evidence against the canonical exclusivity of the pre- and post-synaptic compartments. Determining subsynaptic localization of a protein is a huge undertaking and requires expertise we do not possess. This is why we relied on synaptic databases and the literature for our interpretation of our data, as other publications have done.

      We added the following to the Discussion to address this issue:

      “Using the SynGo database, 418 proteins (i.e. 41% of our network) were identified as synaptic proteins consistent with the targets having a synaptic localization. Defining the synaptic proteome is inherently difficult because the synapse is an “open organelle”, and many synaptic proteins also have non-synaptic localizations and are expressed in non-neuronal cells. We further attempted to define our synaptic PPI by differentiating between pre- and post- synaptic compartments via SynGo. Half of our targets were annotated to both compartments and all targets had PPI that were annotated to both. This data supports the emerging evidence against the canonical localization exclusivity of the pre and post synapse(Bouvier, Larsen et al. 2018, Madrigal, Portales et al. 2019).”

      My concerns about spurious interactions are raised again because the authors say that 92% of their interactions are novel (I note that they authors have not compared their interaction data of the NMDA receptor with published datasets from Dr Seth Grant's laboratory). BioGrid itself is good but not enough for comparison, maybe at this point it worth taking String, which accumulates several sources of PPIs, just select the direct PPIs.

      Since the MS-IP experiments in our study have never been performed before, we are not surprised by the extent of novel data we produced. As described above, we took many steps to prevent spurious PPI from entering our final dataset, including the use of detergents, preclearing and stringent bioinformatic filtering. Our entire dataset is very large, so the 8% of PPI that we replicated from other studies represents 124 interactions. We believe this to be an impressive number which correlates to the confidence of our data. Providing more confidence, we identified many reciprocal PPI where shared protein interactors between target proteins were identified in both target protein datasets.

          The PPI described for our targets in BioGrid encompassed 713 publications.  Two of the BioGrid datasets that were compared to our Grin2b PPI data were from the laboratory of Seth Grant.  Arbuckle et al (2010) is a low-throughout paper that describes a Grin2b and DLG4 PPI (that we also identified) and Husi et al (__2000__) is a seminal paper using high-throughput LC-MS to identify PPI in the PSD of mouse brain.  There were many differences between Husi et al and our pipeline.  Husi et al employed the C-terminal Grin2b peptide to pull down interactors from the PSD fraction whereas we employed Grin2b antibody to enrich Grin2b and its interactors from unfractionated brain tissue.  Despite these differences, our studies found 8 proteins in common.
      

      We took your suggestion and compared our data to String which includes direct PPI and functional PPI. Our input was the high confidence PPI identified by SAINT with 5% FDR as with the BioGrid comparison. The PPI network for each target protein had a more significant enrichment (p We think the problem you suggest with SynGO is more of an inherent problem with characterizing the synaptic proteome. The synaptic proteome is difficult to define since it is an “open organelle” with proteins transporting in and out. In addition, most synaptic proteins, such as mitochondrial and translational proteins, also have non-synaptic localizations. It is not possible to isolate a contaminant-free “pure” synaptic preparation by biochemical fractionation. Recently, SynGO was used in a meta-analysis of previously published PSD datasets(Kaizuka, Hirouchi et al. 2024). Kaizuka et al. found 123 proteins identified in 20 PSD datasets. SynGo annotated proteins with post-synaptic localization from this list. To a lesser extent they also identified presynaptic localizations, but it is unclear if the presynaptic proteins are novel localizations. Kaizuka et al. continued the investigation and identified a novel PSD protein, thus demonstrating that our knowledge of pre- and post- synaptic proteomes is incomplete.

      Minor comments

      1. A number of papers have reported protein interactions of native NMDA receptor complexes and their associated proteins isolated from rodent brain and are neither referenced in this paper. It would be relevant to compare these published datasets with the Grin2B IP datasets.

      We employed BioGrid as a reference of reported PPI for each of our target proteins. For Grin2B, the PPI came from 142 different publications. For eight target proteins, we decided *BioGrid * was the best resource for determining the novelty of our PPI because it is routinely used for large-scale unbiased PPI analysis. To determine the novelty of our network, we compared our PPI network to 713 publications via BioGrid. We are unsure whether the papers you are referring to are included in the BioGrid database. To make it easier for readers with similar queries, we added an additional supplementary table (TableS4) including all the publications (i.e. PMID numbers) included in BioGrid comparison for each target protein.

      We amended the Results with the following sentence, so the readers realized the extensiveness of the Biogrid comparison analysis:

      “There were 713 publications in BioGrid that describe at least one interaction with one of our targets (Supplementary Table4).”

      The use of the term "bait" in purification experiments typically refers to a protein and not an antibody. I suggest removing the word bait to avoid ambiguity and simply use the word target. We took your suggestion and used “target” instead of “bait” to avoid ambiguity.

      26 mins of treatment gives completely different set of PPIs between PCP and saline which is very interesting, so both networks should be included in Supplementary. Also, it would be useful to have a list of modulated (phosphorylated in their case, but also ubiquitinated etc) proteins, which is not presented. Table S1 lists the PPI for each target, and we designated whether the interactors were for Sal, PCP, or both. Phosphorylated and ubiquitinated proteins are very hard to reproducibly identify without an additional enrichment step. Since we did not perform this enrichment step, we did not search for these modifications and do not have any modified proteins to report.

      As they say their final network is composed of "direct physical and "co-complex" interactors and they cannot distinguish between them. This is particularly bad for the postsynapse, where all the PSD components can be co-IP-ed in different combinations. It can explain the Figure 5C, where most of the proteins have FDR = 1, which means they do not reproduce. Figure 5C represents the intersection of 15N quantification and SAINT analysis. The x-axis is the FDR reported for SAINT analysis, and the y-axis is the significant proteins from the N15 analysis. This figure demonstrates that some proteins that were significantly different with PCP via N15 quantification also were annotated as PPI by SAINT (i.e. 5%. As stated in the Discussion, we concluded that the SAINT analysis and N15 quantitation are complementary in identifying PPI and that the quantification of a biological perturbation may aid the identification of PPI. Figure 5C is not related to whether our PPI are direct physical or "co-complex" interactors. Distinguishing between direct physical and co-complex interactors is an inherent problem for all IP studies. Since another reviewer also highlighted this deficit in our manuscript, we decided to analyze our PPI dataset with the artificial intelligence algorithm AlphaFold 3(AF3). The AF3 data is encompassed in Figure 6.

      The following AF3 data was added to the Results Section:

      “A disadvantage of IP-MS studies is that it cannot distinguish between a PPI that binds directly to the target protein, and a PPI in which the interactor and target protein reside in the same multiprotein complex (i.e. indirect). We sought to predict which PPI may be directly interacting with its target protein by using the artificial intelligence algorithm AlphaFold3(AF3) (Abramson, Adler et al. 2024). First, we analyzed the predicted AF3 structure of the targets using the pTM score, and determined the fraction of each structure that was calculated to be disordered (Figure 6A and Supplementary Table7). Our reasoning was that if our targets have a poorly resolved structures then it will be difficult to screen for direct PPI. A pTM score >0.5 suggests that the structure may be correct, with the highest confidence equaling 1. Undefined or disordered regions hinder the accuracy of the prediction, and all our targets possessed a pTM score > 0.5 except Syt1. The fraction of disordered negatively correlated with the pTM score, as expected. Gsk3b, Ppp1ca, and Map2k1 were the target proteins with the highest pTM scores and were also the smallest of our targets (Figure 6B). Ppp1ca had the most confident structure (i.e. pTM 0.9) and the least fraction disordered (i.e. 0.07). Next, we determined the AF3 prediction of previously reported direct interactions of the targets. We used the iPTM score to determine an interaction confidence. An iPTM score >0.8 is a highly confident direct interaction, whereas 0.8. These eight PPI have all previously been reported to form a direct interaction with Ppp1ca, except Phactr3 (Zhang, Zhang et al. 1998, Terrak, Kerff et al. 2004, Hurley, Yang et al. 2007, Marsh, Dancheck et al. 2010, Ragusa, Dancheck et al. 2010, Ferrar, Chamousset et al. 2012, Choy, Srivastava et al. 2024, Xu, Sadleir et al. 2024)*. Phactr3 is structurally similar to, but less studied than, the reported direct interactor, Phactr1. These interactors are all inhibitors of PP1 except for Ppp1r9b which targets Ppp1ca to specific subcellular compartments. Nine PPI were assigned a score The following AF3 interpretation was added to the Discussion:

      “Our SCZ PPI network consists of two types of PPI: direct physical interactions and “co-complex” or indirect interactions. Typically, the nature of the interaction cannot be distinguished in IP-MS studies. We decided to employ the new AF3 algorithm to screen the PPI of Ppp1ca to provide evidence for direct interactors. We chose to examine the PPI assigned to Ppp1ca, because its structure was the most confident among our target proteins and AF3 correctly predicted a known direct interactor with high confidence. Ppp1ca is a catalytic subunit of the phosphatase PP1, which is required to associate with regulatory subunits to create holoenzymes (Li, Wilmanns et al. 2013). Eighteen PPI were predicted to be directly interacting with Ppp1ca using a 0.6 or higher iPTM filter. This filter may be too conservative and may generate false negatives, because another study employed a 0.3 filter followed by additional interrogation to screen for direct PPI (Weeratunga, Gormal et al. 2024). Forty-four percent of these predictions were confirmed by previous publications. Most of these validated direct interactions are inhibitors of the phosphatase, but one, Ppp1r9b (aka spinophilin), is known to target Ppp1ca to dendritic spines (Allen, Ouimet et al. 1997, Salek, Claeboe et al. 2023). This high correlation with the literature provides substantial confidence to the novel PPI predicted to be direct Ppp1ca interactors. The AF3 screen predicted that NDRG2 directly interacts with Ppp1ca. This protein is known to regulate many phosphorylation dependent signaling pathways by directly interacting with other phosphatases including Pp1ma and PP2A (Feng, Zhou et al. 2022, Lee, Lim et al. 2022). Actin binding protein Capza1 was also predicted to directly interact with Ppp1ca and Ppp1ca interacts with actin and its binding proteins to maintain optimal localization for efficient activity to specific substrates (Foley, Ward et al. 2023). Hsp1e is a heat shock protein predicted to directly interact with Ppp1ca. Although there is no direct connection to Ppp1ca, other heat shock proteins have been reported to regulate Ppp1ca (Mivechi, Trainor et al. 1993, Flores-Delgado, Liu et al. 2007, Qian, Vafiadaki et al. 2011). We also observed that many of the direct PPI were altered with PCP treatment. One direct interactor, Ppp1r1b (aka DARPP-32), is phosphorylated at Thr34 by PKA in the brain upon PCP treatment. This phosphorylation event converts Ppp1rb to a potent inhibitor of Ppp1ca(Svenningsson, Tzavara et al. 2003). Importantly, the manipulation of Thr34 attenuated the behavioral effects of PCP. Consistent with this report, Ppp1r1b-Ppp1ca interaction was only observed with PCP in our study. Further investigation is needed to determine if our novel direct interactors regulate the PCP phenotype. We conclude that AF3 can provide important structural insights into the nature of PPI obtained from large scale IP-MS studies.”

      The way PPI data is reported can be improved so that I does not have to be extracted from Table 1 and 2. It would be good if they provide just two columns PPI list, with names or IDs, plus PSP/saline/both conditions in third column, for ease of comparison with other sources and building the graph. They can add it as another spreadsheet to Table 2. We generated this table (TableS2) as you requested.

      Is Figure 2 built for Sal or PCP conditions? as they have only 23% interactions in common (Figure 4A) the Figure 2 should be pretty different for two conditions. Are the 1007 interactors combined from SAL and PCP?

      Figure 2 contains ALL the unique PPI for each target regardless of Sal or PCP conditions. The 1007 protein interactors shown in Figure 2Awhere Sal and PCP were combined to generate a non-redundant list of proteins for each target.

      We amended the Results to make this clearer:

      “When the PCP and SAL datasets were combined, there were 1007 unique proteins.”

      This sentence was added to Figure 2A:

      “For this comparison, Sal and PCP PPI were combined into a unique PPI list for each target.”

      Figure 1F is mentioned but no figure is shown. We apologize for this oversight, and we have corrected the manuscript. 8. Overall the paper could be edited and made more concise, especially the introduction and discussion. We extensively edited the manuscript to be more concise.

      Reviewer #3 (Significance (Required)):

      General assessment

      Proteomic mass spectrometry of immunoprecipitated complexes from synapses has been extensively studied since Husi et al (2000) first study of NMDA receptor and AMPA receptor complexes. Since then, a wide variety of methods have been employed to purify synaptic protein complexes including peptide affinity, tandem-affinity purification of endogenous proteins tagged with FLAG and Histine-affinity tags amongst other methods. Purification of protein complexes and the postsynaptic density from the postsynaptic terminal of mammalian excitatory synapses have been crucial for establishing that schizophrenia is a polygenic disorder affecting synapses (e.g. Fernandez et al, 2009; Kirov et al, 2012; Purcell et al, 2014, Fromer et al, 2014 etc). Network analyses of the postsynaptic proteome have described networks of schizophrenia interacting proteins (e.g. Pocklington et al, 2006; Fernandez et al, 2009) and other neuropsychiatric disorders.

      Hundreds of synaptic protein complexes have been identified (Frank et al, 2016), but very few have been characterised using proteomic mass spectrometry. This paper has chosen 8 protein targets for such analysis and identified many proteins that a putative interactors of the target protein. At this level the current manuscript does not represent a conceptual advance and the value of the data lies in its utility as a resource that may be used in future studies.

      The findings from the 8 target proteins from normal adult rat brain were used for a secondary study that describes the effects that PCP has on the interaction networks. Interestingly, this work shows that 26 minutes of drug treatment leads to considerable changes in the interactomes of the target proteins. These descriptive data could be used in future studies to understand the cell biological mechanisms that mediate these rapid changes in the proteome. PCP and drugs that interact with NMDA receptors are known to induce changes in synaptic proteome phosphorylation including modifications in protein-protein interaction sites, which may explain the PCP effects.

      The study would benefit from validation of experimental protocols for solubilisation and immunoprecipitation and validation of described interactions using orthogonal biochemical or localisation experiments.

      Audience Specialists in synapse proteins and mechanisms of schizophrenia.

      Expertise

      The reviewers' expertise is in molecular biology of synapses including synapse proteomics, protein interaction and network analysis, and genetics of schizophrenia and other brain disorders.

      Abramson, J., J. Adler, J. Dunger, R. Evans, T. Green, A. Pritzel, O. Ronneberger, L. Willmore, A. J. Ballard, J. Bambrick, S. W. Bodenstein, D. A. Evans, C. C. Hung, M. O'Neill, D. Reiman, K. Tunyasuvunakool, Z. Wu, A. Zemgulyte, E. Arvaniti, C. Beattie, O. Bertolli, A. Bridgland, A. Cherepanov, M. Congreve, A. I. Cowen-Rivers, A. Cowie, M. Figurnov, F. B. Fuchs, H. Gladman, R. Jain, Y. A. Khan, C. M. R. Low, K. Perlin, A. Potapenko, P. Savy, S. Singh, A. Stecula, A. Thillaisundaram, C. Tong, S. Yakneen, E. D. Zhong, M. Zielinski, A. Zidek, V. Bapst, P. Kohli, M. Jaderberg, D. Hassabis and J. M. Jumper (2024). "Accurate structure prediction of biomolecular interactions with AlphaFold 3." Nature 630(8016): 493-500.

      Allen, P. B., C. C. Ouimet and P. Greengard (1997). "Spinophilin, a novel protein phosphatase 1 binding protein localized to dendritic spines." Proc Natl Acad Sci U S A 94(18): 9956-9961.

      Anschuetz, A., K. Schwab, C. R. Harrington, C. M. Wischik and G. Riedel (2024). "A Meta-Analysis on Presynaptic Changes in Alzheimer's Disease." J Alzheimers Dis 97(1): 145-162.

      Araki, Y., M. Zeng, M. Zhang and R. L. Huganir (2015). "Rapid dispersion of SynGAP from synaptic spines triggers AMPA receptor insertion and spine enlargement during LTP." Neuron 85(1): 173-189.

      Bauminger, H. and I. Gaisler-Salomon (2022). "Beyond NMDA Receptors: Homeostasis at the Glutamate Tripartite Synapse and Its Contributions to Cognitive Dysfunction in Schizophrenia." Int J Mol Sci 23(15).

      Berretta, N. and R. S. Jones (1996). "Tonic facilitation of glutamate release by presynaptic N-methyl-D-aspartate autoreceptors in the entorhinal cortex." Neuroscience 75(2): 339-344.

      Birtele, M., A. Del Dosso, T. Xu, T. Nguyen, B. Wilkinson, N. Hosseini, S. Nguyen, J. P. Urenda, G. Knight, C. Rojas, I. Flores, A. Atamian, R. Moore, R. Sharma, P. Pirrotte, R. S. Ashton, E. J. Huang, G. Rumbaugh, M. P. Coba and G. Quadrato (2023). "Non-synaptic function of the autism spectrum disorder-associated gene SYNGAP1 in cortical neurogenesis." Nat Neurosci 26(12): 2090-2103.

      Bouvier, G., R. S. Larsen, A. Rodriguez-Moreno, O. Paulsen and P. J. Sjostrom (2018). "Towards resolving the presynaptic NMDA receptor debate." Curr Opin Neurobiol 51: 1-7.

      Choy, M. S., G. Srivastava, L. C. Robinson, K. Tatchell, R. Page and W. Peti (2024). "The SDS22:PP1:I3 complex: SDS22 binding to PP1 loosens the active site metal to prime metal exchange." J Biol Chem 300(1): 105515.

      Dobson, L., I. Remenyi and G. E. Tusnady (2015). "The human transmembrane proteome." Biol Direct 10: 31.

      Feng, D., J. Zhou, H. Liu, X. Wu, F. Li, J. Zhao, Y. Zhang, L. Wang, M. Chao, Q. Wang, H. Qin, S. Ge, Q. Liu, J. Zhang and Y. Qu (2022). "Astrocytic NDRG2-PPM1A interaction exacerbates blood-brain barrier disruption after subarachnoid hemorrhage." Sci Adv 8(39): eabq2423.

      Ferrar, T., D. Chamousset, V. De Wever, M. Nimick, J. Andersen, L. Trinkle-Mulcahy and G. B. Moorhead (2012). "Taperin (c9orf75), a mutated gene in nonsyndromic deafness, encodes a vertebrate specific, nuclear localized protein phosphatase one alpha (PP1alpha) docking protein." Biol Open 1(2): 128-139.

      Flores-Delgado, G., C. W. Liu, R. Sposto and N. Berndt (2007). "A limited screen for protein interactions reveals new roles for protein phosphatase 1 in cell cycle control and apoptosis." J Proteome Res 6(3): 1165-1175.

      Foley, K., N. Ward, H. Hou, A. Mayer, C. McKee and H. Xia (2023). "Regulation of PP1 interaction with I-2, neurabin, and F-actin." Mol Cell Neurosci 124: 103796.

      Goudriaan, A., C. de Leeuw, S. Ripke, C. M. Hultman, P. Sklar, P. F. Sullivan, A. B. Smit, D. Posthuma and M. H. Verheijen (2014). "Specific glial functions contribute to schizophrenia susceptibility." Schizophr Bull 40(4): 925-935.

      Hemmings, H. C., Jr., P. Greengard, H. Y. Tung and P. Cohen (1984). "DARPP-32, a dopamine-regulated neuronal phosphoprotein, is a potent inhibitor of protein phosphatase-1." Nature 310(5977): 503-505.

      Hurley, T. D., J. Yang, L. Zhang, K. D. Goodwin, Q. Zou, M. Cortese, A. K. Dunker and A. A. DePaoli-Roach (2007). "Structural basis for regulation of protein phosphatase 1 by inhibitor-2." J Biol Chem 282(39): 28874-28883.

      Hussain, S., D. L. Egbenya, Y. C. Lai, Z. J. Dosa, J. B. Sorensen, A. E. Anderson and S. Davanger (2017). "The calcium sensor synaptotagmin 1 is expressed and regulated in hippocampal postsynaptic spines." Hippocampus 27(11): 1168-1177.

      Iqbal, H., D. R. Akins and M. R. Kenedy (2018). "Co-immunoprecipitation for Identifying Protein-Protein Interactions in Borrelia burgdorferi." Methods Mol Biol 1690: 47-55.

      Kaizuka, T., T. Hirouchi, T. Saneyoshi, T. Shirafuji, M. O. Collins, S. G. N. Grant, Y. Hayashi and T. Takumi (2024). "FAM81A is a postsynaptic protein that regulates the condensation of postsynaptic proteins via liquid-liquid phase separation." PLoS Biol 22(3): e3002006.

      Kaizuka, T., T. Suzuki, N. Kishi, K. Tamada, M. W. Kilimann, T. Ueyama, M. Watanabe, T. Shimogori, H. Okano, N. Dohmae and T. Takumi (2024). "Remodeling of the postsynaptic proteome in male mice and marmosets during synapse development." Nat Commun 15(1): 2496.

      Kerns, D., G. S. Vong, K. Barley, S. Dracheva, P. Katsel, P. Casaccia, V. Haroutunian and W. Byne (2010). "Gene expression abnormalities and oligodendrocyte deficits in the internal capsule in schizophrenia." Schizophr Res 120(1-3): 150-158.

      Kim, H., S. Choi, E. Lee, W. Koh and C. J. Lee (2024). "Tonic NMDAR Currents in the Brain: Regulation and Cognitive Functions." Biol Psychiatry.

      Koopmans, F., P. van Nierop, M. Andres-Alonso, A. Byrnes, T. Cijsouw, M. P. Coba, L. N. Cornelisse, R. J. Farrell, H. L. Goldschmidt, D. P. Howrigan, N. K. Hussain, C. Imig, A. P. H. de Jong, H. Jung, M. Kohansalnodehi, B. Kramarz, N. Lipstein, R. C. Lovering, H. MacGillavry, V. Mariano, H. Mi, M. Ninov, D. Osumi-Sutherland, R. Pielot, K. H. Smalla, H. Tang, K. Tashman, R. F. G. Toonen, C. Verpelli, R. Reig-Viader, K. Watanabe, J. van Weering, T. Achsel, G. Ashrafi, N. Asi, T. C. Brown, P. De Camilli, M. Feuermann, R. E. Foulger, P. Gaudet, A. Joglekar, A. Kanellopoulos, R. Malenka, R. A. Nicoll, C. Pulido, J. de Juan-Sanz, M. Sheng, T. C. Sudhof, H. U. Tilgner, C. Bagni, A. Bayes, T. Biederer, N. Brose, J. J. E. Chua, D. C. Dieterich, E. D. Gundelfinger, C. Hoogenraad, R. L. Huganir, R. Jahn, P. S. Kaeser, E. Kim, M. R. Kreutz, P. S. McPherson, B. M. Neale, V. O'Connor, D. Posthuma, T. A. Ryan, C. Sala, G. Feng, S. E. Hyman, P. D. Thomas, A. B. Smit and M. Verhage (2019). "SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse." Neuron 103(2): 217-234 e214.

      Krishnankutty, A., T. Kimura, T. Saito, K. Aoyagi, A. Asada, S. I. Takahashi, K. Ando, M. Ohara-Imaizumi, K. Ishiguro and S. I. Hisanaga (2017). "In vivo regulation of glycogen synthase kinase 3beta activity in neurons and brains." Sci Rep 7(1): 8602.

      Lagundzin, D., K. L. Krieger, H. C. Law and N. T. Woods (2022). "An optimized co-immunoprecipitation protocol for the analysis of endogenous protein-protein interactions in cell lines using mass spectrometry." STAR Protoc 3(1): 101234.

      Lalo, U., W. Koh, C. J. Lee and Y. Pankratov (2021). "The tripartite glutamatergic synapse." Neuropharmacology 199: 108758.

      Lee, B. H., F. Schwager, P. Meraldi and M. Gotta (2018). "p37/UBXN2B regulates spindle orientation by limiting cortical NuMA recruitment via PP1/Repo-Man." J Cell Biol 217(2): 483-493.

      Lee, K. W., S. Lim and K. D. Kim (2022). "The Function of N-Myc Downstream-Regulated Gene 2 (NDRG2) as a Negative Regulator in Tumor Cell Metastasis." Int J Mol Sci 23(16).

      Lee, M. C., K. K. Ting, S. Adams, B. J. Brew, R. Chung and G. J. Guillemin (2010). "Characterisation of the expression of NMDA receptors in human astrocytes." PLoS One 5(11): e14123.

      Li, X., M. Wilmanns, J. Thornton and M. Kohn (2013). "Elucidating human phosphatase-substrate networks." Sci Signal 6(275): rs10.

      Lin, J. S. and E. M. Lai (2017). "Protein-Protein Interactions: Co-Immunoprecipitation." Methods Mol Biol 1615: 211-219.

      Ma, T. M., S. Abazyan, B. Abazyan, J. Nomura, C. Yang, S. Seshadri, A. Sawa, S. H. Snyder and M. V. Pletnikov (2013). "Pathogenic disruption of DISC1-serine racemase binding elicits schizophrenia-like behavior via D-serine depletion." Mol Psychiatry 18(5): 557-567.

      Madrigal, M. P., A. Portales, M. P. SanJuan and S. Jurado (2019). "Postsynaptic SNARE Proteins: Role in Synaptic Transmission and Plasticity." Neuroscience 420: 12-21.

      Marsh, J. A., B. Dancheck, M. J. Ragusa, M. Allaire, J. D. Forman-Kay and W. Peti (2010). "Structural diversity in free and bound states of intrinsically disordered protein phosphatase 1 regulators." Structure 18(9): 1094-1103.

      McClatchy, D. B., N. K. Yu, S. Martinez-Bartolome, R. Patel, A. R. Pelletier, M. Lavalle-Adam, S. B. Powell, M. Roberto and J. R. Yates (2018). "Structural Analysis of Hippocampal Kinase Signal Transduction." ACS Chem Neurosci 9(12): 3072-3085.

      Misir, E. and G. G. Akay (2023). "Synaptic dysfunction in schizophrenia." Synapse 77(5): e22276.

      Mivechi, N. F., L. D. Trainor and G. M. Hahn (1993). "Purified mammalian HSP-70 KDA activates phosphoprotein phosphatases in vitro." Biochem Biophys Res Commun 192(2): 954-963.

      Moon, I. S., H. Sakagami, J. Nakayama and T. Suzuki (2008). "Differential distribution of synGAP alpha1 and synGAP beta isoforms in rat neurons." Brain Res 1241: 62-75.

      Pankow, S., C. Bamberger, D. Calzolari, A. Bamberger and J. R. Yates, 3rd (2016). "Deep interactome profiling of membrane proteins by co-interacting protein identification technology." Nat Protoc 11(12): 2515-2528.

      Pankow, S., C. Bamberger, D. Calzolari, S. Martinez-Bartolome, M. Lavallee-Adam, W. E. Balch and J. R. Yates, 3rd (2015). "∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis." Nature 528(7583): 510-516.

      Park, G. H., H. Noh, Z. Shao, P. Ni, Y. Qin, D. Liu, C. P. Beaudreault, J. S. Park, C. P. Abani, J. M. Park, D. T. Le, S. Z. Gonzalez, Y. Guan, B. M. Cohen, D. L. McPhie, J. T. Coyle, T. A. Lanz, H. S. Xi, C. Yin, W. Huang, H. Y. Kim and S. Chung (2020). "Activated microglia cause metabolic disruptions in developmental cortical interneurons that persist in interneurons from individuals with schizophrenia." Nat Neurosci 23(11): 1352-1364.

      Partiot, E., A. Hirschler, S. Colomb, W. Lutz, T. Claeys, F. Delalande, M. S. Deffieu, Y. Bare, J. R. E. Roels, B. Gorda, J. Bons, D. Callon, L. Andreoletti, M. Labrousse, F. M. J. Jacobs, V. Rigau, B. Charlot, L. Martens, C. Carapito, G. Ganesh and R. Gaudin (2024). "Brain exposure to SARS-CoV-2 virions perturbs synaptic homeostasis." Nat Microbiol.

      Qian, J., E. Vafiadaki, S. M. Florea, V. P. Singh, W. Song, C. K. Lam, Y. Wang, Q. Yuan, T. J. Pritchard, W. Cai, K. Haghighi, P. Rodriguez, H. S. Wang, D. Sanoudou, G. C. Fan and E. G. Kranias (2011). "Small heat shock protein 20 interacts with protein phosphatase-1 and enhances sarcoplasmic reticulum calcium cycling." Circ Res 108(12): 1429-1438.

      Ragusa, M. J., B. Dancheck, D. A. Critton, A. C. Nairn, R. Page and W. Peti (2010). "Spinophilin directs protein phosphatase 1 specificity by blocking substrate binding sites." Nat Struct Mol Biol 17(4): 459-464.

      Rodrigues-Neves, A. C., A. F. Ambrosio and C. A. Gomes (2022). "Microglia sequelae: brain signature of innate immunity in schizophrenia." Transl Psychiatry 12(1): 493.

      Salek, A. B., E. T. Claeboe, R. Bansal, N. F. Berbari and A. J. Baucum, 2nd (2023). "Spinophilin-dependent regulation of GluN2B-containing NMDAR-dependent calcium influx, GluN2B surface expression, and cleaved caspase expression." Synapse 77(3): e22264.

      Savas, J. N., B. D. Stein, C. C. Wu and J. R. Yates, 3rd (2011). "Mass spectrometry accelerates membrane protein analysis." Trends Biochem Sci 36(7): 388-396.

      Selak, S., A. V. Paternain, M. I. Aller, E. Pico, R. Rivera and J. Lerma (2009). "A role for SNAP25 in internalization of kainate receptors and synaptic plasticity." Neuron 63(3): 357-371.

      Serrano, A., R. Robitaille and J. C. Lacaille (2008). "Differential NMDA-dependent activation of glial cells in mouse hippocampus." Glia 56(15): 1648-1663.

      Sjostrom, P. J., G. G. Turrigiano and S. B. Nelson (2003). "Neocortical LTD via coincident activation of presynaptic NMDA and cannabinoid receptors." Neuron 39(4): 641-654.

      Stanca, S., M. Rossetti, L. Bokulic Panichi and P. Bongioanni (2024). "The Cellular Dysfunction of the Brain-Blood Barrier from Endothelial Cells to Astrocytes: The Pathway towards Neurotransmitter Impairment in Schizophrenia." Int J Mol Sci 25(2).

      Sumi, T. and K. Harada (2023). "Muscarinic acetylcholine receptor-dependent and NMDA receptor-dependent LTP and LTD share the common AMPAR trafficking pathway." iScience 26(3): 106133.

      Svenningsson, P., E. T. Tzavara, R. Carruthers, I. Rachleff, S. Wattler, M. Nehls, D. L. McKinzie, A. A. Fienberg, G. G. Nomikos and P. Greengard (2003). "Diverse psychotomimetics act through a common signaling pathway." Science 302(5649): 1412-1415.

      Tarasov, V. V., A. A. Svistunov, V. N. Chubarev, S. S. Sologova, P. Mukhortova, D. Levushkin, S. G. Somasundaram, C. E. Kirkland, S. O. Bachurin and G. Aliev (2019). "Alterations of Astrocytes in the Context of Schizophrenic Dementia." Front Pharmacol 10: 1612.

      Terrak, M., F. Kerff, K. Langsetmo, T. Tao and R. Dominguez (2004). "Structural basis of protein phosphatase 1 regulation." Nature 429(6993): 780-784.

      Tokizane, K., C. S. Brace and S. I. Imai (2024). "DMH(Ppp1r17) neurons regulate aging and lifespan in mice through hypothalamic-adipose inter-tissue communication." Cell Metab 36(2): 377-392 e311.

      Tomasoni, R., D. Repetto, R. Morini, C. Elia, F. Gardoni, M. Di Luca, E. Turco, P. Defilippi and M. Matteoli (2013). "SNAP-25 regulates spine formation through postsynaptic binding to p140Cap." Nat Commun 4: 2136.

      Vainio, L., S. Taponen, S. M. Kinnunen, E. Halmetoja, Z. Szabo, T. Alakoski, J. Ulvila, J. Junttila, P. Lakkisto, J. Magga and R. Kerkela (2021). "GSK3beta Serine 389 Phosphorylation Modulates Cardiomyocyte Hypertrophy and Ischemic Injury." Int J Mol Sci 22(24).

      van Oostrum, M., T. M. Blok, S. L. Giandomenico, S. Tom Dieck, G. Tushev, N. Furst, J. D. Langer and E. M. Schuman (2023). "The proteomic landscape of synaptic diversity across brain regions and cell types." Cell 186(24): 5411-5427 e5423.

      Vilalta, A. and G. C. Brown (2018). "Neurophagy, the phagocytosis of live neurons and synapses by glia, contributes to brain development and disease." FEBS J 285(19): 3566-3575.

      Weeratunga, S., R. S. Gormal, M. Liu, D. Eldershaw, E. K. Livingstone, A. Malapaka, T. P. Wallis, A. T. Bademosi, A. Jiang, M. D. Healy, F. A. Meunier and B. M. Collins (2024). "Interrogation and validation of the interactome of neuronal Munc18-interacting Mint proteins with AlphaFold2." J Biol Chem 300(1): 105541.

      Winship, I. R., S. M. Dursun, G. B. Baker, P. A. Balista, L. Kandratavicius, J. P. Maia-de-Oliveira, J. Hallak and J. G. Howland (2019). "An Overview of Animal Models Related to Schizophrenia." Can J Psychiatry 64(1): 5-17.

      Xu, Z., L. Sadleir, H. Goel, X. Jiao, Y. Niu, Z. Zhou, G. de Valles-Ibanez, G. Poke, M. Hildebrand, N. Lieffering, J. Qin and Z. Yang (2024). "Genotype and phenotype correlation of PHACTR1-related neurological disorders." J Med Genet 61(6): 536-542.

      Zhang, J., L. Zhang, S. Zhao and E. Y. Lee (1998). "Identification and characterization of the human HCG V gene product as a novel inhibitor of protein phosphatase-1." Biochemistry 37(47): 16728-16734.

      Zhang, Y., K. Chen, S. A. Sloan, M. L. Bennett, A. R. Scholze, S. O'Keeffe, H. P. Phatnani, P. Guarnieri, C. Caneda, N. Ruderisch, S. Deng, S. A. Liddelow, C. Zhang, R. Daneman, T. Maniatis, B. A. Barres and J. Q. Wu (2014). "An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex." J Neurosci 34(36): 11929-11947.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Reviewer 1

      R1 Cell profiling is an emerging field with many applications in academia and industry. Finding better representations for heterogeneous cell populations is important and timely. However, unless convinced otherwise after a rebuttal/revision, the contribution of this paper, in our opinion, is mostly conceptual, but in its current form - not yet practical. This manuscript combined two concepts that were previously reported in the context of cell profiling, weakly supervised representations. Our expertise is in computational biology, and specifically applications of machine learning in microscopy.

      In our revised manuscript, we have aimed to better clarify the practical contributions of our work by demonstrating the effectiveness of the proposed concepts on real-world datasets. We hope that these revisions and our detailed responses address your concerns and highlight the potential impact of our approach.

      R1.1a. CytoSummaryNet is evaluated in comparison to aggregate-average profiling, although previous work has already reported representations that capture heterogeneity and self-supervision independently. To argue that both components of contrastive learning and sets representations are contributing to MoA prediction we believe that a separate evaluation for each component is required. Specifically, the authors can benchmark their previous work to directly evaluate a simpler population representation (PMID: 31064985, ref #13) - we are aware that the authors report a 20% improvement, but this was reported on a separate dataset. The authors can also compare to contrastive learning-based representations that rely on the aggregate (average) profile to assess and quantify the contribution of the sets representation.

      We agree that evaluating the individual contributions of the contrastive learning framework and single-cell data usage is important for understanding CytoSummaryNet's performance gains.

      To assess the impact of the contrastive formulation independently, we applied CytoSummaryNet to averaged profiles from the cpg0004 dataset. This isolated the effect of contrastive learning by eliminating single-cell heterogeneity. The experiment yielded a 32% relative improvement in mechanism of action retrieval, compared to the 68% gain achieved with single-cell data. These findings suggest that while the contrastive formulation contributes significantly to CytoSummaryNet's performance, leveraging single-cell information is crucial for maximizing its effectiveness. We have added a discussion of this experiment to the Results section:

      “We conducted an experiment to determine whether the improvements in mechanism of action retrieval were due solely to CytoSummaryNet's contrastive formulation or also influenced by the incorporation of single-cell data. We applied the CytoSummaryNet framework to pre-processed average profiles from the 10 μM dose point data of Batch 1 (cpg0004 dataset). This approach isolated the effect of the contrastive architecture by eliminating single-cell data variability. We adjusted the experimental setup by reducing the learning rate by a factor of 100, acknowledging the reduced task complexity. All other parameters remained as described in earlier experiments.

      This method yielded a less pronounced but still substantial improvement in mechanism of action retrieval, with an increase of 0.010 (32% enhancement - Table 1). However, this improvement was not as high as when the model processed single-cell level data (68% as noted above). These findings suggest that while CytoSummaryNet's contrastive formulation contributes to performance improvements, the integration of single-cell data plays a critical role in maximizing the efficacy of mechanism of action retrieval.”

      We don't believe comparing with PMID: 31064985 is useful: while the study showcased the usefulness of modeling heterogeneity using second-order statistics, its methodology is limited in scalability due to the computational burden of computing pairwise similarities for all perturbations, particularly in large datasets. Additionally, the study's reliance on similarity network fusion, while expedient, introduces complexity and inefficiency. We contend that this comparison does not align with our objective of testing the effectiveness of heterogeneity in isolation, as it primarily focuses on capturing second and first-order information. Thus, we do not consider this study a suitable baseline for comparison.

      R1.1b. The evaluation metric of mAP improvement in percentage is misleading, because a tiny improvement for a MoA prediction can lead to huge improvement in percentage, while a much larger improvement in MoA prediction can lead to a small improvement in percentage. For example, in Fig. 4, MEK inhibitor mAP improvement of ~0.35 is measured as ~50% improvement, while a much smaller mAP improvement can have the same effect near the origins (i.e., very poor MoA prediction).

      We agree that relying solely on percentage improvements can be misleading, especially when small absolute changes result in large percentage differences.

      However, we would like to clarify two key points regarding our reporting of percentage improvements:

      • We calculate the percentage improvement by first computing the average mAP across all compounds for both CytoSummaryNet and average profiling, and then comparing these averages. This approach is less susceptible to the influence of outlier improvements compared to calculating the average of individual compound percentage improvements.
      • We report percentage improvements alongside their corresponding absolute improvements. For example, the mAP improvement for Stain4 (test set) is reported as 0.052 (60%). To further clarify this point, we have updated the caption of Table 1 to explicitly state how the percentage improvements are calculated:

      The improvements are calculated as mAP(CytoSummaryNet)-mAP(average profiling). The percentage improvements are calculated as (mAP(CytoSummaryNet)-mAP(average profiling))/mAP(average profiling).

      R1.1b. (Subjective) visual assessment of this figure does not show a convincing contribution of CytoSummaryNet representations of the average profiling on the test set (3.33 uM). This issue might also be relevant for the task of replicate retrieval. All in all, the mAP improvement reported in Table 1 and throughout the manuscript (including the Abstract), is not a proper evaluation metric for CytoSummaryNet contribution. We suggest reporting the following evaluations:

      1. Visualizing the results of cpg0001 (Figs. 1-3) similarly to cpg0004 (Fig. 4), i.e., plotting the matched mAP for CytoSummaryNet vs. average profile.

      2. In Table 1, we suggest referring to the change in the number of predictable MoAs (MoAs that pass a mAP threshold) rather than the improvement in percentages. Another option is showing a graph of the predictability, with the X axis representing a threshold and Y-axis showing the number of MoAs passing it. For example see (PMID: 36344834, Fig. 2B) and (PMID: 37031208, Fig. 2A), both papers included contributions from the corresponding author of this manuscript.

      Regarding the suggestion to visualize the results for compound group cpg0001 similarly to cpg0004, unfortunately, this is not feasible due to the differences in data splitting between the two datasets. In cpg0001, an MoA might have one compound in the training set and another in the test or validation set. Reporting a single value per MoA would require combining these splits, which could be misleading as it would conflate performance across different data subsets.

      However, we appreciate the suggestion to represent the number of predictable MoAs that surpass a certain mAP threshold, as it provides another intuitive measure of performance. To address this, we have created a graph that visualizes the predictability of MoAs across various thresholds, similar to the examples provided in the referenced papers (PMID: 36344834, Figure 2B and PMID: 37031208, Figure 2A). This graph, with the x-axis depicting the threshold and the y-axis showing the number of MoAs meeting the criterion, has been added to Supplementary Material K.

      R1.1c.i. "a subset of 18 compounds were designated as validation compounds" - 5 cross-validations of 18 compounds can make the evaluation complete. This can also enhance statistical power in figures 1-3.

      We appreciate your suggestion and acknowledge the potential benefits of employing cross-validation, particularly in enhancing statistical power. While we understand the merit of cross-validation for evaluating model performance and generalization to unseen data, we believe the results as presented already highlight the generalization characterics of our methods.

      Specifically, (the new) Figure 3 demonstrates the model's improvement over average profiling in both training and validation plates, supporting its ability to generalize to unseen compounds (but not to unseen plates).

      While cross-validation could potentially enhance our analysis, retraining five new models solely for different validation set results may not substantially alter our conclusions, given the observed trends in Suppl Figure A1 and (the new) Figure 4, both of which show results across multiple stain sets (but a single train-test-validation split).


      R1.1c.ii. Clarify if the MoA results for cpg0001 are drawn from compounds from both the training and the validation datasets. If so, describe how the results differ between the sets in text and graphs.

      We confirm that the Mechanism of Action (MoA) retrieval results for cpg0001 are derived from all available compounds. It's important to note that the training and validation dataset split for the replicate retrieval task is different from the MoA prediction task. For replicate retrieval, we train using all available compounds and validate on a held-out set (see Figure 2). For MoA prediction, we train using the replicate retrieval task as the objective on all available compounds but validate using MoA retrieval, which is a distinct task. We have added a brief clarification in the main text to highlight the distinction between these tasks and how validation is performed for each:

      “We next addressed a more challenging task: predicting the mechanism of action class for each compound at the individual well level, rather than simply matching replicates of the exact same compound (Figure 5). It's also important to note that mechanism of action matching is a downstream task on which CytoSummaryNet is not explicitly trained. Consequently, improvements observed on the training and validation plates are more meaningful in this context, unlike in the previous task where only improvements on the test plate were meaningful. For similar reasons, we calculate the mechanism of action retrieval performance on all available compounds, combining both the training and validation sets. This approach is acceptable because we calculate the score on so-called "sister compounds" only—that is, different compounds that have the same mechanism of action annotation. This ensures there is no overlap between the mechanism of action retrieval task and the training task, maintaining the integrity of our evaluation. ”

      R1.1c.iii. "Mechanism of action retrieval is evaluated by quantifying a profile's ability to retrieve the profile of other compounds with the same annotated mechanism of action.". It was unclear to us if the evaluation of mAP for MoA identification can include finding replicates of the same compound. That is, whether finding a close replicate of the same compound would be included in the AP calculation. This would provide CytoSummaryNet with an inherent advantage as this is the task it is trained to do. We assume that this was not the case (and thus should be more clearly articulated), but if it was - results need to be re-evaluated excluding same-compound replicates.

      The evaluation excludes replicate wells of the same compound and only considers wells of other compounds with the same MoA. This methodology ensures that the model's performance on the MoA prediction task is not inflated by its ability to find replicates of the same compound, which is the objective of the replicate retrieval task. Please see the explanation we have added to the main text in our response to R1.1c.ii. Additionally, we have updated the Methods section to clearly describe this evaluation procedure:

      “Mechanism of action retrieval is evaluated by quantifying a profile’s ability to retrieve the profile of different compounds with the same annotated mechanism of action.”



      __R1.2a. __The description of Stain2-5 was not clear for us at first (and second) read. The information is there, but more details will greatly enhance the reader's ability to follow. One suggestion is explicitly stating that these "stains" partitioning was already defined in ref 26. Another suggestion is laying out explicitly a concrete example on the differences between two of these stains. We believe highlighting the differences between stains will strengthen the claim of the paper, emphasizing the difficulty of generalizing to the out-of-distribution stain.

      We appreciate your feedback on the clarity of the Stain2-5 dataset descriptions; we certainly struggled to balance detail and concepts in describing these. We have made the following changes:

      • Explicitly mentioned that the partitioning of the Stain experiments was defined in https://pubmed.ncbi.nlm.nih.gov/37344608/: “The partitioning of the Stain experiments have been defined and explained previously [21].”
      • Moved an improved version of (now) Figure 2 from the Methods section to the main text to help visually explain how the stratification is done early on.
      • Added a new section in the Experimental Setup: Diversity of stain sets, which includes a concrete example highlighting the differences between Stain2, and Stain5 to emphasize the diversity in experimental setups within the same dataset: “Stain2-5 comprise a series of experiments which were conducted sequentially to optimize the experimental conditions for image-based cell profiling. These experiments gradually converged on the most optimal set of conditions; however, within each experiment, there were significant variations in the assay across plates. To illustrate the diversity in experimental setups within the dataset, we will highlight the differences between Stain2 and Stain5.

      Stain2 encompasses a wide range of nine different experimental protocols, employing various imaging techniques such as Widefield and Confocal microscopy, as well as specialized conditions like multiplane imaging and specific stains like MitoTracker Orange. This subset also includes plates acquired with strong pixel binning instead of default imaging and plates with varying concentrations of dyes like Hoechst. As a result, Stain2 exhibits greater variance in the experimental conditions across different plates compared to Stain5.

      In contrast, Stain5, the last experiment in the series, follows a more systematic approach, consistently using either confocal or default imaging across three well-defined conditions. Each condition in Stain5 utilizes a lower cell density of 1,000 cells per well compared to Stain2's 2,500 cells per well. Being the final experiment in the series, Stain5 had the least variance in experimental conditions.

      For training the models, we typically select the data containing the most variance to capture the broadest range of experimental variation. Therefore, we chose Stain2-4 for training, as they represented the majority of the data and captured the most experimental variation. We reserved Stain5 for testing to evaluate the model's ability to generalize to new experimental conditions with less variance.

      All StainX experiments were acquired in different passes, which may introduce additional batch effects.”

      These changes aim to provide a clearer understanding of the dataset's complexity and the challenges associated with generalizing to out-of-distribution data.

      R1.2b. What does each data point in Figures 1-3 represent? Is it the average mAP for the 18 validation compounds, using different seeds for model training? Why not visualize the data similarly to Fig. 4 so the improvement per compound can be clearly seen?

      The data points in (the new) Figures 3,4,5 represent the average mAP for each plate, calculated by first computing the mAP for each compound and then averaging across compounds to obtain the average mAP per plate. We have updated the figure captions to clarify this:

      "... (each data point is the average mAP of a plate) ..."

      While visualizing the mAP per compound, similar to (the new) Figure 6 for cpg0004, could provide insights into compound-level improvements, it would require creating numerous additional figures or one complex figure to adequately represent all the stratifications we are analyzing (plate, compound, Stain subset). By averaging the data per plate across different stratifications, we aim to provide a clearer and more comprehensible overview of the trends and improvements while allowing us to draw conclusions about generalization.

      Please note: this comment is related to the comment R1.1b (Subjective)

      R1.2.c [On the topic of enhancing clarity and readability:] Justification and interpretation of the evaluation metrics.

      Please refer to our response to comment R1.1b, where we have addressed your concerns regarding the justification and interpretation of the evaluation metrics.

      R1.2d. Explicitly mentioning the number of MoAs for each datasets and statistics of number of compounds per MoA (e.g., average\median, min, max).

      We have added the following to the Experimental Setup: Data section:

      “A subset of the data was used for evaluating the mechanism of action retrieval task, focusing exclusively on compounds that belong to the same mechanism class. The Stain plates contained 47 unique mechanisms of action, with each compound replicated four times. Four mechanisms had only a single compound; the four mechanisms (and corresponding compounds) were excluded, resulting in 43 unique mechanisms used for evaluation. In the LINCS dataset, there were 1436 different mechanisms, but only 661 were used for evaluation because the remaining had only one compound.”

      R1.2e. The data split in general is not easily understood. Figure 8 is somewhat helpful, however in our view, it can be improved to enhance understanding of the different splits. Specifically, the training and validation compounds need to be embedded and highlighted within the figure.

      Thank you for highlighting this. We have completely revised the figure, now Figure 2 which we hope more clearly conveys the data split strategy.

      Please note: this comment is related to the comment R1.2a.





      R1.3a. Why was stain 5 used for the test, rather than the other stains?

      Stain2-5 were part of a series of experiments aimed at optimizing the experimental conditions for image-based cell profiling using Cell Painting. These experiments were conducted sequentially, gradually converging on the most optimal set of conditions. However, within each experiment, there were significant variations in the assay across plates, with earlier iterations (Stain2-4) having more variance in the experimental conditions compared to Stain5. As Stain5 was the last experiment in the series and consisted of only three different conditions, it had the least variance. For training the models, we typically select the data containing the most variance to capture the broadest range of experimental variation. Therefore, Stain2-4 were chosen for training, while Stain5 was reserved for testing to evaluate the model's ability to generalize to new experimental conditions with less variance.

      We have now clarified this in the Experimental Setup: Diversity of stain sets section. Please see our response to comment R1.2a. for the full citation.

      R1.3b How were the 18 validation compounds selected?

      20% of the compounds (n=18) were randomly selected and designated as validation compounds, with the remaining compounds assigned to the training set. We have now clarified this in the Results section:

      “Additionally, 20% of the compounds (n=18) were randomly selected and designated as validation compounds, with the remaining compounds assigned to the training set (Supplementary Material H).”

      R1.3c. For cpg0004, no justification for the specific doses selected (10uM - train, 3.33 uM - test) for the analysis in Figure 4. Why was the data split for the two dosages? For example, why not perform 5-fold cross validation on the compounds (e.g., of the highest dose)?

      We chose to use the 10 μM dose point as the training set because we expected this higher dosage to consist of stronger profiles with more variance than lower dose points, making it more suitable for training a model. We decided to use a separate test set at a different dose (3.33 μM) to assess the model's ability to generalize to new dosages. While cross-validation on the highest dose could also be informative, our approach aimed to balance the evaluation of the model's generalization capability with its ability to capture biologically relevant patterns across different dosages.

      This explanation has been added to the text:

      “We chose the 10 μM dose point for training because we expected this high dosage to produce stronger profiles with more variance than lower dose points, making it more suitable for model training.”

      “The multiple dose points in this dataset allowed us to create a separate hold-out test set using the 3.33 μM dose point data. This approach aimed to evaluate the model's performance on data with potentially weaker profiles and less variance, providing insights into its robustness and ability to capture biologically relevant patterns across dosages. While cross-validation on the 10 μM dose could also be informative, focusing on lower dose points offers a more challenging test of the model's capacity to generalize beyond its training conditions, although we do note that all compounds’ phenotypes would likely have been present in the 10 μM training dataset, given the compounds tested are the same in both.”

      R1.3d. A more detailed explanation on the logic behind using a training stain to test MoA retrieval will help readers appreciate these results. In our first read of this manuscript we did not grasp that, we did in a second read, but spoon-feeding your readers will help.

      This comment is related to the rationale behind training on one task and testing on another, which is addressed in our responses to comments R1.1.cii and R1.1.ciii.

      R1.4 Assessment of interpretability is always tricky. But in this case, the authors can directly confirm their interpretation that the CytoSummaryNet representation prioritizes large uncrowded cells, by explicitly selecting these cells, and using their average profile re

      We progressively filtered out cells based on a quantile threshold for Cells_AreaShape features (MeanRadius, MaximumRadius, MedianRadius, and Area), which were identified as important in our interpretability analysis, and then computed average profiles using the remaining cells before determining the replicate retrieval mAP. In the exclusion experiment, we gradually left out cells as the threshold increased, while in the inclusion experiment, we progressively included larger cells from left to right.

      The results show that using only the largest cells does not significantly increase the performance. Instead, it is more important to include the large cells rather than only including small cells. The mAP saturates after a threshold of around 0.4, indicating that larger cells define the profile the most, and once enough cells are included to outweigh the smaller cell features, the profile does not change significantly by including even larger cells.

      These findings support our interpretation that CytoSummaryNet prioritizes large, uncrowded cells. While this approach could potentially be used as a general outlier removal strategy for cell profiling, further investigation is needed to assess its robustness and generalizability across different datasets and experimental conditions.

      We have created Supplementary Material L to report these findings and we additionally highlight them in the Results:

      “To further validate CytoSummaryNet's prioritization of large, uncrowded cells, we progressively filtered cells based on Cells_AreaShape features and observed the impact on replicate retrieval mAP (Supplementary Material L). The results support our interpretation and highlight the key role of larger cells in profile strength.”

      __R1.5. __Placing this work in context of other weakly supervised representations. Previous papers used weakly supervised labels of proteins / experimental perturbations (e.g., compounds) to improve image-derived representations, but were not discussed in this context. These include PMID: 35879608, https://www.biorxiv.org/content/10.1101/2022.08.12.503783v2 (from the same research groups and can also be benchmarked in this context), https://pubs.rsc.org/en/content/articlelanding/2023/dd/d3dd00060e , and https://www.biorxiv.org/content/10.1101/2023.02.24.529975v1. We believe that a discussion explicitly referencing these papers in this specific context is important.

      While these studies provide valuable insights into improving cell population profiles using representation learning, our work focuses specifically on the question of single-cell aggregation methods. We chose to use classical features for our comparisons because they are the current standard in the field. This approach allows us to directly assess the performance of our method in the context of the most widely used feature extraction pipeline in practice. However, we see the value in incorporating them in future work and have mentioned them in the Discussion:

      “Recent studies exploring image-derived representations using self-supervised and self-supervised learning [35][36] could inspire future research on using learned embeddings instead of classical features to enhance model-aggregated profiles.”

      R1.minor1. "Because the improved results could stem from prioritizing certain features over others during aggregation, we investigated each cell's importance during CytoSummaryNet aggregation by calculating a relevance score for each" - what is the relevance score? Would be helpful to provide some intuition in the Results.

      We have included more explanation of the relevance score in the Results section, following the explanation of sensitivity analysis (SA) and critical point analysis (CPA):

      “SA evaluates the model's predictions by analyzing the partial derivatives in a localized context, while CPA identifies the input cells with the most significant contribution to the model's output. The relevance scores of SA and CPA are min-max normalized per well and then combined by addition. The combination of the two is again min-max normalized, resulting in the SA and CPA combined relevance score (see Methods for details).”

      R1.minor2. Figure 1:

      1. Colors of the two methods too similar
      2. The dots are too close. It will be more easily interpreted if they were further apart.
      3. What do the dots stand for?
      4. We recommend considering moving this figure to the supp. material (the most important part of it is the results on the test set and it appears in Fig.2).
      1. We chose a lighter and darker version of the same color as a theme to simplify visualization, as this theme is used throughout (the new) Figures 3,4,5.
      2. We agree; we have now redrawn the figure to fix this.
      3. Each data point is the average mAP of a plate. Please see our answer for R1.2b as well.
      4. We believe that (the new) Figures 3,4,5 serve distinct purposes in testing various generalization hypotheses. We have added the following text to emphasize that the first figures are specifically about generalization hypothesis testing: “We first investigated CytoSummaryNet’s capacity to generalize to out-of-distribution data: unseen compounds, unseen experimental protocols, and unseen batches. The results of these investigations are visualized in Figures 3, 4, and 5, respectively.”

      R1.minor3 Figure 4: It is somewhat misleading to look at the training MoAs and validation MoAs embedded together in the same graph. We recommend showing only the test MoAs (train MoAs can move to SI).

      We addressed this comment in R1.1c.ii. To reiterate briefly, there are no training, validation, or test MoAs because these are not used as labels during the training process. There is an option to split them based on training and validation compounds, which is addressed in R1.1c.ii.


      R1.minor4 Figure 5

      1. Why only Stain3? What happens if we look at Stains 2,3 and 4 together? Stain 5?

      2. Should validation compounds and training compounds be analyzed separately?

      3. Subfigure (d): it is expected that the data will be classified by compound labels as it is the training task, but for this to be persuasive I would like to see this separately on the training compounds first and then and more importantly on the validation compounds.

      4. For subfigures (b) and (d): it appears there are not enough colors for d, which makes it partially not understandable. For example, the pink label in (d) shows a single compound which appears to represent two different MoAs. This is probably not the case, and it has two different compounds, but it cannot be inferred when they are represented by the same color.

      5. For the Subfigure (e) - only 1 circle looks justified (in the top left). And for that one, is it not a case of an outlier plate that would perhaps need to be removed from analysis? Is it not good that such a plate will be identified?

      We have addressed this point in the text, stating that the results are similar for Stain2 and Stain4. Stain5 represents an out-of-distribution subset because of a very different set of experimental conditions (see Experimental Setup: Diversity of stain sets). To improve clarity, we have revised the figure caption to reiterate this information:

      “... Stain2 and Stain4 yielded similar results (data not shown). …”

      1. For replicate retrieval, analyzing validation and training compounds separately is appropriate. However, this is not the case for MoA retrieval, as discussed in our responses to R1.1c.ii and R1.1c.i.
      2. We have created the requested plot (below) but ultimately decided not to include it in the manuscript because we believe that (the new) Figures 3 and 4 are more effective for making quantitative comparative claims.

      [Please see the full revision document for the figures]

      Top: training compounds (validation compounds grayed out); not all compounds are listed in the legend.

      *Bottom: validation compounds (training compounds grayed out). *

      Left: average profiling; Right: CytoSummaryNet

      1. We agree with your observation and have addressed this issue by labeling the center mass as a single class (gray) and highlighting only the outstanding pairs in color. Please refer to the updated figure and our response to R3.6 for more details.

      2. In the updated figure, we have revised the figure caption to focus solely on the annotation of same mechanism of action profile clusters, as indicated by the green ellipses. The annotation of isolated plate clusters has been removed (Figures 7e and 7f) to maintain consistency and avoid potential confusion. Despite being an outlier for Stain3, the plate (BR00115134bin1) clusters with Stain4 plates (Supplementary Figure F1, green annotated square inside the yellow annotated square), indicating it is not merely a noisy outlier and can provide insights into the out-of-sample performance of our model.

      R1.minor5a. Discussion: "perhaps in part due to its correction of batch effects" - is this statement based on Fig. 5F - we are not convinced.

      We appreciate the reviewer's scrutiny regarding our statement about batch effect correction. Upon reevaluation, we agree that this claim was not adequately substantiated by empirical data. We quantified the batch effects using comparison mean average precision for both average profiles and CytoSummaryNet profiles, and the statistical analysis revealed no significant difference between these profiles in terms of batch effect correction. Therefore, we have removed this theoretical argument from the manuscript entirely to ensure that all claims are strongly supported by the data presented.

      R1.minor5b. "Overall, these results improve upon the ~20% gains we previously observed using covariance features" - this is not the same dataset so it is hard to reach conclusions - perhaps compare performance directly on the same data?

      We have now explicitly clarified this is a different dataset. Please see our response to R1.1a for why a direct comparison was not performed. The following clarification can be found in the Discussion:

      “These results improve upon the ~20% gains previously observed using covariance features [13] albeit on a different dataset, and importantly, CytoSummaryNet effectively overcomes the challenge of recomputation after training, making it easier to use.”

      Reviewer 2

      R2.1 The authors present a well-developed and useful algorithm. The technical motivation and validation are very carefully and clearly explained, and their work is potentially useful to a varied audience.

      That said, I think the authors could do a better job, especially in the figures, of putting the algorithm in context for an audience that is unfamiliar with the cell painting assay. (a) For example, a figure towards the beginning of the paper with example images might help to set the stage. (b) Similarly a schematic of the algorithm earlier in the paper would provide a graphical overview. (c) For the sake of a biologically inclined audience, I would consider labeling the images in the caption by cell type and label.

      Thank you for your valuable suggestions on improving the accessibility of our figures for readers unfamiliar with the Cell Painting assay. We have made the following changes to address your comments:

      1. and b. To provide visual context and a graphical overview of the algorithm, we have moved the original Figure 7 to Figure 1. This figure now includes example images that help readers new to the Cell Painting assay.
      2. We have added relevant details to the example images in (the new) Figure 1

        R2.2 The interpretability results were intriguing. The authors might consider further validating these interpretations by removing weakly informative cells from the dataset and retraining. Are the cells so uninformative that the algorithm does better without them, or are they just less informative than other cells?

      Please see our responses to R1.4 and R3.0

      R2.3 As far as I can tell, the authors only oblique state whether the code associated with the manuscript is openly available. Posting the code is needed for reproducibility. I would provide not only a github, but a doi linked to the code, or some other permanent link.

      We have now added a Code Availability and Data Availability section, clearing stating that the code and data associated with the manuscript are openly available.

      R2.4 Incorporating biological heterogeneity into machine-learning driven problems is a critical research question. Replacing means/modes and such with a machine learning framework, the authors have identified a problem with potentially wide significance. The application to cell painting and related assays is of broad enough significance for many journals, However, the authors could further broaden the significance by commenting on other possible cell biology applications. What other applications might the algorithm be particularly suited for? Are there any possible roadblocks to wider use. What sorts of data has the code been tested on so far?

      We have added the following paragraph to discuss the broader applicability of CytoSummaryNet:

      “The architecture of CytoSummaryNet holds significant potential for broader applications beyond image-based cell profiling, accommodating tabular, permutation-invariant data and enhancing downstream task performance when applied to processed population-level profiles. Its versatility makes it valuable for any omics measurements where downstream tasks depend on measuring similarity between profiles. Future research could also explore CytoSummaryNet's applicability to genetic perturbations, expanding its utility in functional genomics.”

      Reviewer 3

      R3.0 The authors have done a commendable job discussing the method, demonstrating its potential to outperform current models in profiling cell-based features. The work is of considerable significance and interest to a wide field of researchers working on the understanding of cell heterogeneity's impact on various biological phenomena and practical studies in pharmacology.

      One aspect that would further enhance the value of this work is an exploration of the method's separation power across different modes of action. For instance, it would be interesting to ascertain if the method's performance varies when dealing with actions that primarily affect size, those that affect marker expression, or compounds that significantly diminish cell numbers.

      Thank you for encouraging comments!

      We have added the following to Results: Relevance scores reveal CytoSummaryNet's preference for large, isolated cells:

      “Statistical t-tests were conducted to identify the features that most effectively differentiate mechanisms of action from negative controls in average profiles, focusing on the three mechanisms of action where CytoSummaryNet demonstrates the most significant improvement and the three mechanisms where it shows the least. Consistent with our hypothesis that CytoSummaryNet emphasizes larger, more sparse cells, the important features for the CytoSummaryNet-improved mechanisms of action (Supplementary Material I1) often involve the radial distribution for the mitochondria and RNA channels. These metrics capture the fraction of those stains near the edge of the cell versus concentric rings towards the nucleus, which are more readily detectable in larger cells compared to small, rounded cells.

      In contrast, the important features for mechanisms of action not improved by CytoSummaryNet (Supplementary Material I) predominantly include correlation metrics between brightfield and various fluorescent channels, capturing spatial relationships between cellular components. Some of these mechanisms of action included compounds that were not individually distinguishable from negative controls, and CytoSummaryNet did not overcome the lack of phenotype in these cases. This suggests that while CytoSummaryNet excels in identifying certain cellular features, its effectiveness is limited when dealing with mechanisms of action that do not exhibit pronounced phenotypic changes.”

      We have also added supplementary material to support (I. Relevant features for CytoSummaryNet improvement).

      R3.0 Another test on datasets that are not concerned with chemical compounds, but rather genetic perturbations would greatly increase the reach of the method into the functional genomics community and beyond. This additional analysis could provide valuable insights into the versatility and applicability of the proposed method.

      We agree that testing the method's behavior on genetic perturbations would be interesting and could provide insights into its versatility. However, the efficacy of the methodology may vary depending on the specific properties of different genetic perturbation types.

      For example, the penetrance of phenotypes may differ between genetic and chemical perturbations. In some experimental setups, a selection agent ensures that nearly all cells receive a genetic perturbation (though not all may express a phenotype due to heterogeneity or varying levels of the target protein). Other experiments may omit such an agent. Additionally, different patterns might be observed in various classes of reagents, such as overexpression, CRISPR-Cas9 knockdown (CRISPRn), CRISPR-interference (CRISPRi), and CRISPR-activation (CRISPRa).

      We believe that selecting a single experiment with one of these technologies would not adequately address the question of versatility. Instead, we propose future studies that may conclusively assess the method's performance across a variety of genetic perturbation types. This would provide a more comprehensive understanding of CytoSummaryNet's applicability in functional genomics and beyond. We have update the Discussion section to reflect this:

      “Future research could also explore CytoSummaryNet's applicability to genetic perturbations, expanding its utility in functional genomics.”

      R3.1. The datasets were stratified based on plates and compounds. It would be beneficial to clarify the basis for data stratification applied for compounds. Was the data sampled based on structural or functional similarity of compounds? If not, what can be expected from the model if trained and validated using structurally or functionally diverse and non-diverse compounds?

      Thank you for raising the important question of data stratification based on compound similarity. In our study, the data stratification was performed by randomly sampling the compounds, without considering their structural or functional similarity.

      This approach may limit the generalizability of the learned representations to new structural or functional classes not captured in the training set. Consequently, the current methodology may not fully characterize the model’s performance across diverse compound structures.

      In future work, it would be valuable to explore the impact of compound diversity on model performance by stratifying data based on structural or functional similarity and comparing the results to our current random stratification approach to more thoroughly characterize the learned representations.

      R3.2. Is the method prioritizing a particular biological reaction of cells toward common chemical compounds, such as mitotic failure? Could this be oncology-specific, or is there more utility to it in other datasets?

      Our analysis of CytoSummaryNet's performance in (the new) Figure 6 reveals a strong improvement in MoAs targeting cancer-related pathways, such as MEK, HSP, MDM, dehydrogenase, and purine antagonist inhibitors. These MoAs share a common focus on cellular proliferation, survival, and metabolic processes, which are key characteristics of cancer cells.

      Given the composition of the cpg0004 dataset, which contains 1,258 unique MoAs with only 28 annotated as oncology-related, the likelihood of randomly selecting five oncology-related MoAs that show strong improvement is extremely low. This suggests that the observed prioritization is not due to chance.

      Furthermore, the prioritization cannot be solely attributed to the frequency of oncology-related MoAs in the dataset. Other prevalent disease areas, such as neurology/psychiatry, infectious disease, and cardiology, do not exhibit similar improvements despite having higher MoA counts.

      While these findings indicate a potential prioritization of oncology-related MoAs by CytoSummaryNet, further research is necessary to fully understand the extent and implications of this bias. Future work should involve conducting similar analyses across other disease areas and cell types to assess the method's broader utility and identify areas for refinement and application. However, given the speculative nature of these observations, we have chosen not to update the manuscript to discuss this potential bias at this time.

      R3.3 Figures 1 and 2 demonstrate that the CytoSummaryNet profiles outperform average-aggregated profiles. However, the average profiling results seem more consistent when compared to CytoSummaryNet profiling. What further conditions or approaches can help improve CytoSummaryNet profiling results to be more consistent?

      The observed variability in CytoSummaryNet's performance is primarily due to the intentional technical variance in our datasets, where each plate tested different staining protocol variations. It's important to note that this level of technical variance is not typical in standard cell profiling experiments. In practice, the variance across plates would be much lower. We want to emphasize that while a model capable of generalizing across diverse experimental conditions might seem ideal, it may not be as practically useful in real-world scenarios. This is because such non-uniform conditions are uncommon in typical cell profiling experiments. In normal experimental settings, where technical variance is more controlled, we expect CytoSummaryNet's performance to be more consistent.

      R3.4 Can the poor performance on unseen data (in the case of stain 5) be overcome? If yes, how? If no, why not?

      We believe that the poor performance on unseen data, such as Stain 5, can be overcome depending on the nature of the unseen data. As shown in Figure 4 (panel 3), the model improves upon average profiling for unseen data when the experimental conditions are similar to the training set.

      The issue lies in the different experimental conditions. As explained in our response to R3.3, this could be addressed by including these experimental conditions in the training dataset. As long as CytoSummaryNet is trained (seen) and tested (unseen) on data generated under similar experimental conditions, we are confident that it will improve or perform as well as average profiling.

      It's important to note that the issue of generalization to vastly different experimental conditions was considered out of scope for this paper. The main focus is to introduce a new method that improves upon average profiling and can be readily used within a consistent experimental setup.

      R3.5 It needs to be mentioned how the feature data used for CytoSummaryNet profiling was normalized before training the model. What would be the impact of feature data normalization before model training? Would the model still outperform if the skewed feature data is normalized using square or log transformation before model training?

      We have clarified in the manuscript that we standardized the feature data on a plate-by-plate basis to achieve zero mean and unit variance across all cells per feature within each plate. We have added the following statement to improve clarity:

      “The data used to compute the average profiles and train the model were standardized at the plate-level, ensuring that all cell features across the plate had a zero mean and unit variance. The negative control wells were then removed from all plates."

      We chose standardization over transformations like squaring or logging to maintain a balanced scale across features while preserving the biological and morphological information inherent in the data. While transformations can reduce skewness and are useful for data spanning several orders of magnitude, they might distort biological relevance by compressing or expanding data ranges in ways that could obscure important cellular variations.

      Regarding the potential impact of square or log transformations on skewed feature data, these methods could improve the model's learning efficiency by making the feature distribution more symmetrical. However, the suitability and effectiveness of these techniques would depend on the specific data characteristics and the model architecture.

      Although not explored in this study, investigating various normalization techniques could be a valuable direction for future research to assess their impact on the performance and adaptability of CytoSummaryNet across diverse datasets and experimental setups.

      R3.6. In Figure 5 b and c, MoAs often seem to be represented by singular compounds and thus, the test (MoA prediction) is very similar to the training (compound ID). Given this context, a discussion about the extent this presents a circular argument supported by stats on the compound library used for training and testing would be beneficial.

      Clusters in (the new) Figure 7 that contain only replicates of a single compound would not yield an improved performance on the MoA task unless they also include replicates of other compounds sharing the same MoA in close proximity. Please see our response to R1.1c.iii. for details. To improve visual clarity and avoid misinterpretation, we have recomputed the colors for (the new) Figure 7 and grayed out overlapping points.

      R3.7 Can you estimate the minimum amount of supervision (fuzzy/sparse labels, often present in mislabeled compound libraries with dirty compounds and polypharmacology being present) that is needed for it to be efficiently trained?

      It's important to note that the metadata used by the model is only based on identifying replicates of the same compound. Mechanism of action (MoA) annotations, which can be erroneous due to dirty compounds, polypharmacology, and incomplete information, are not used in training at all. MoA annotations are only used in our evaluation, specifically for calculating the mAP for MoA retrieval.

      We have successfully trained CytoSummaryNet on 72 unique compounds with 4 replicates each. This is the current empirical minimum, but it is possible that the model could be trained effectively with even fewer compounds or replicates.

      Determining the absolute minimum amount of supervision required for efficient training would require further experimentation and analysis. Factors such as data quality, feature dimensionality, and model complexity could influence the required level of supervision.

      R3.minor1 Figure 5: The x-axis and y-axis tick values are too small, and image resolution/size needs to be increased.

      We have made the following changes to address the concerns:

      • Increased the image resolution and size to improve clarity and readability.
      • Removed the x-axis and y-axis tick values, as they do not provide meaningful information in the context of UMAP visualizations. We believe these modifications enhance the visual presentation of the data and make it easier for readers to interpret the results.

      R3.minor2 The methods applied to optimize hyperparameters in supplementary data need to be included.

      We added the following to Supplementary Material D:

      “We used the Weights & Biases (WandB) sweep suite in combination with the BOHB (Bayesian Optimization and HyperBand) algorithm for hyperparameter sweeps. The BOHB algorithm [47] combines Bayesian optimization with bandit-based strategies to efficiently find optimal hyperparameters.

      Additionally Table D1 provides an overview of all tunable hyperparameters and their chosen values based on a BOHB hyperparameter optimization.”

      R3.minor3 Figure 5(c, d): The names of compound 2 and Compound 5 need to be included in the labels.

      These compounds were obtained from external companies and are proprietary, necessitating their anonymization in our study. This has now been added in the caption of (the new) Figure 7:

      “Note that Compound2 and Compound5 are intentionally anonymized.”

      R3.minor4 Table C1: Plate descriptions need to be included.

      *Table C1: The training, validation, and test set stratification for Stain2, Stain3, Stain4, and Stain5. Five training, four validation, and three test plates are used for Stain2, Stain3, and Stain4. Stain5 contains six test set plates only. *

      __Stain2 __

      Stain3

      Stain4

      Stain5

      Training plates

      Test plates

      BR00113818

      BR00115128

      BR00116627

      BR00120532

      BR00113820

      BR00115125highexp

      BR00116631

      BR00120270

      BR00112202

      BR00115133highexp

      BR00116625

      BR00120536

      BR00112197binned

      BR00115131

      BR00116630highexp

      BR00120530

      BR00112198

      BR00115134

      200922_015124-Vhighexp

      BR00120526

      Validation plates

      BR00120274

      BR00112197standard

      BR00115129

      BR00116628highexp

      BR00112197repeat

      BR00115133

      BR00116629highexp

      BR00112204

      BR00115128highexp

      BR00116627highexp

      BR00112201

      BR00115127

      BR00116629

      Test plates

      BR00112199

      BR00115134bin1

      200922_044247-Vbin1

      BR00113819

      BR00115134multiplane

      200922_015124-V

      BR00113821

      BR00115126highexp

      BR00116633bin1

      We have added a reference to the metadata file in the description of Table C1: https://github.com/carpenter-singh-lab/2023_Cimini_NatureProtocols/blob/main/JUMPExperimentMasterTable.csv

      R3.minor5 Figure F1: Does the green box (stain 3) also involve training on plates from stain 4 (BR00116630highexp) and 5 (BR00120530) mentioned in Table C1? Please check the figure once again for possible errors.

      We have carefully re-examined Figure F1 and Table C1 to ensure their accuracy and consistency. Upon double-checking, we can confirm that the figure is indeed correct. We intentionally omitted the training and validation plates from Figure F1 to maintain clarity and readability, as including them resulted in a cluttered and difficult-to-interpret figure.

      Regarding the specific plates mentioned:

      • BR00116630highexp (Stain4) is used for training, as correctly stated in Table C1. This plate is considered an outlier within the Stain4 dataset and happens to cluster with the Stain3 plates in Figure F1.
      • BR00120530 (Stain5) is part of the test set only and correctly falls within the Stain5 cluster in Figure F1. To improve the clarity of the training, validation, and test split in Table C1, we have added a color scheme that visually distinguishes the different data subsets. This should make it easier for readers to understand the distribution of plates across the various splits.
    1. Author response:

      The following is the authors’ response to the previous reviews.

      Public Reviews

      Reviewer 1 summarized that: In this revised version of the manuscript, the authors have made important modifications in the text, inserted new data analyses, and incorporated additional references, as recommended by the reviewers. These modifications have significantly improved the quality of the manuscript.

      We are grateful for the reviewer's positive recognition of our revisions.

      Reviewer 2 noted that:

      (1) The authors do not show if the PVT mediates dPAG to BLA communication with any functional behavioral assay.

      We appreciate the reviewer’s suggestion to include a functional assay to investigate the role of the PVT in mediating communication between the dPAG and BLA. Our primary objective was to confirm the upstream role of the dPAG in processing and relaying naturalistic predatory threat information to the BLA, thereby broadening our current understanding of the dPAG-BLA relationship based on Pavlovian fear conditioning paradigms.

      Given previous anatomical findings indicating the absence of direct monosynaptic projections from the dPAG to the BLA (Cameron et al. 1995, McNally, Johansen, and Blair 2011, Vianna and Brandao 2003), we employed both anterograde and retrograde tracers, supplemented by c-Fos expression analysis following predatory threats, to explore possible routes through which threat signals may be conveyed from the dPAG to the BLA. Our findings indicated significant activity within the midline thalamic regions, particularly the PVT as a mediator of dPAG-BLA interactions, corroborating the possibility of dPAGàBLA information flow.

      Investigating the PVT's functional role appropriately would require single-unit recordings, correlation analysis of PVT neuronal responses with dPAG and BLA neuronal responses, and pathway-specific causal techniques, involving other midline thalamic regions for controls. This comprehensive study would represent an independent study.

      In response to previous feedback, we have carefully revised our manuscript to moderate the emphasis on the PVT's role. Both the Abstract, Results, and Discussion refer more broadly to "midline thalamic regions" and “The midline thalamus” (subheading) rather than specifically to the PVT. In the Introduction, we mention that the PVT "may be part of a network that conveys predatory threat information from the dPAG to the BLA." Our conclusions about the functional interaction between the dPAG and BLA, which broaden the view of Pavlovian fear conditioning, are not contingent on confirming a specific intermediary role for the PVT.

      (2) The author also do not thoroughly characterize the activity of BLA cells during the predatory assay.

      Our previous studies have extensively detailed BLA cell firing characteristics, including their responsiveness to food and/or a robot predator during the predatory assay (Kim et al. 2018, Kong et al. 2021), and compared these findings to other predator studies (Amir et al. 2019, Amir et al. 2015). In the current study, out of 85 BLA cells, 3 were food-specific and 4 responded to both the pellet and the robot, with none of these 7 cells responding to dPAG stimulation.

      Given our earlier findings of the immediate responses of BLA neurons to robot activation, we specifically examined whether robot-responsive BLA neurons receive signals from the dPAG. For this analysis, we excluded all food-related cells (pellet cells and BOTH cells) and focused on the time window immediately after robot activation (within 500 ms after robot onset). This approach enabled us to avoid potential confounds from residual effects of robot-induced immediate BLA responses during the animals’ flight and nest entry behaviors.

      Furthermore, as previously described, the robot is programmed to move forward a fixed distance and then return, repeatedly triggering foraging behavior. This setup facilitates the analysis of neural changes during food approach and predator avoidance conflicts. However, animals quickly adapt to the robot, reducing freezing and stretch-attend behaviors, making time-stamped analysis of these behaviors unfeasible.

      We would like to highlight that the present study explicitly focused on demonstrating whether BLA neurons that responded to intrinsic dPAG optogenetic stimulation also responded to extrinsic predatory robot activation, and compared their firing characteristics to those BLA neurons that did not respond to dPAG stimulation (Figure 3). This targeted analysis provides insights into the responsiveness of BLA neurons to both intrinsic and extrinsic stimuli, furthering our understanding of the dPAG-BLA interaction in the context of predatory threats.

      Reviewer 3 also raised no concerns and stated that: The series of experiments provide a compelling case for supporting their conclusions. The study brings important concepts revealing dynamics of fear-related circuits particularly attractive to a broad audience, from basic scientists interested in neural circuits to psychiatrists.

      We sincerely thank the reviewer for the positive feedback on our revisions.

      Recommendations for the Authors

      Reviewer 1: There are a few minor concerns that the authors may want to fix:

      (1) Point 5) The sentence: "The complexity of targeting the dPAG, which includes its dorsomedial, dorsolateral, lateral, and ventrolateral subdivisions" is hard to follow because the ventrolateral subdivision is not part of the dPAG. The authors may want to say specific subregions of the PAG instead. It is also unclear why transgenic animals would be needed for this projection-defined manipulations. The combination of retrograde Cre-recombinase virus with inhibitory opsin or chemogenetic approach may be sufficient.

      We appreciate the reviewer’s insightful feedback regarding our description of the dPAG and the use of transgenic mice in future studies. As suggested, we have corrected the manuscript to exclude the 'ventrolateral' subdivision from the dPAG description, now accurately aligning with pioneering studies (Bandler, Carrive, and Zhang 1991, Bandler and Keay 1996, Carrive 1993) that designated dPAG as including the dorsomedial (dmPAG), dorsolateral (dlPAG) and lateral (lPAG) regions, as cited in our revised manuscript.

      We acknowledge the reviewer’s helpful suggestion regarding the use of retrograde Cre-recombinase virus with inhibitory opsins or chemogenetic approaches as viable alternatives. These methods have been incorporated into our discussion (pages 14-15): “While our findings demonstrate that opto-stimulation of the dPAG is sufficient to trigger both fleeing behavior and increased BLA activity, we have not established that the dPAG-PVT circuit is necessary for the BLA’s response to predatory threats. To establish causality and interregional relationships, future studies should employ methods such as pathway-specific optogenetic inhibition (using retrograde Cre-recombinase virus with inhibitory opsins; Lavoie and Liu 2020, Li et al. 2016, Senn et al. 2014) or chemogenetics (Boender et al. 2014, Roth 2016) in conjunction with single unit recordings to fully characterize the dPAG-PVT-BLA circuitry’s (as opposed to other midline thalamic regions for controls) role in processing predatory threat-induced escape behavior. If inactivating the dPAG-PVT circuits reduces the BLA's response to threats, this would highlight the central role of the dPAG-PVT pathway in this defense mechanism. Conversely, if the BLA's response remains unchanged despite dPAG-PVT inactivation, it could suggest the existence of multiple pathways for antipredatory defenses.”

      This revision addresses the critique by clarifying the anatomical description of the dPAG and emphasizing the feasibility of using targeted viral approaches without the necessity for transgenic animals.

      (2) Point 6e) The authors mentioned that "pellet retrieval" was indicated by the animal entering a designated zone 19 cm from the pellet, driven by hunger. Entering the area 19cm of distance should be labeled as food approaching rather then food retrieval because in many occasions the animals may be some seconds away of grabbing the pellet.

      We agree and incorporate the change (pg. 22).

      (3) Point 11) We would strongly recommend the authors to replace the terminology "looming" by "approaching" to avoid confusion with several previous studies looking at defensive behaviors in responses to looming induced by the shadow of an object moving closer to the eyes.

      Done.

      (4) Point 17) The authors mentioned that "A total of three rats were utilized for the robot testing experiments depicted in Fig. 2 G-J." However, the figure indicates a total of 9 ChR2 and 4 controls.

      We apologize for the confusion in our previous author responses. To examine the optical stimulation effects on behavior in Fig. 2G-J, we used a total of 9 ChR2 and 4 EYFP rats. The experimental sequence is detailed in the previously revised manuscript (pg. 20): “For optical stimulation and behavioral experiments, the procedure included 3 baseline trials with the pellet placed 75 cm away, followed by 3 dPAG stimulation trials with the pellet locations sequentially set at 75 cm, 50 cm, and 25 cm. During each approach to the pellet, rats received 473-nm light stimulation (1-2 s, 20-Hz, 10-ms width, 1-3 mW) through a laser (Opto Engine LLC) and a pulse generator (Master-8; A.M.P.I.). Additional testing to examine the functional response curves was conducted over multiple days, with incremental adjustments to the stimulation parameters (intensity, frequency, duration) after confirming that normal baseline foraging behavior was maintained. For these tests, one parameter was adjusted incrementally while the others were held constant (intensity curve at 20 Hz, 2 s; frequency curve at 3 mW, 2 s; duration curve at 20 Hz, 3 mW). If the rat failed to procure the pellet within 3 min, the gate was closed, and the trial was concluded.”

      This clarification ensures that the actual number of animals used is accurately reflected and aligns with the figure data, addressing the reviewer's concern.

      Reviewer 2: The authors made important changes in the text to address study limitations, including citations requested by the Reviewers and additional discussions about how this work fits into the existing literature. These changes have strengthened the manuscript.

      (1) However, the authors did not perform new experiments to address any of the issues raised in the previous round of reviews. For example, they did not make optogenetic manipulations of the pathway including the PVT, and did not add any loss of function experiments. The justification that these experiments are better suited for future reports using mice is not convincing, because hundreds of papers performing these types of circuit dissection assays have been performed in rats.

      We appreciate the reviewer's comments regarding the experimental scope of our study. Our study’s primary objective was to explore the dPAG’s upstream functional role in processing and conveying naturalistic predatory threat information to the BLA, extending our current understanding of the dPAG-BLA relationship based on Pavlovian fear conditioning paradigms. We believe that our findings effectively address this goal.

      Our use of anterograde and retrograde tracers, supplemented by c-Fos expression analysis in response to predatory threats, was primarily conducted to verify the possibility of the dPAGàBLA information flow during predator encounters. This involved exploring potential routes through which threat signals might be conveyed from the dPAG to the BLA, given the lack of direct monosynaptic projections from the dPAG to BLA neurons (Cameron et al. 1995, McNally, Johansen, and Blair 2011, Vianna and Brandao 2003). This methodology helped us identify a potential structure, PVT, for more in-depth future studies. A thorough examination of the PVT's role would require single-unit recordings and causal techniques, incorporating other midline thalamic regions as controls, representing a significant and separate study on its own.

      In response to prior feedback, we have carefully revised our manuscript to generally address the role of "midline thalamic regions" rather than focusing specifically on the PVT. We wish to emphasize that our findings, which illustrate unique functional interactions between the dPAG and BLA in response to a predatory imminence, remain compelling and informative even without definitive evidence of the PVT’s involvement.

      Reviewer 3: In the revised version of the manuscript, the authors addressed adequately all the concerns raised by the reviewers. 

      We thank the reviewer for the thoughtful feedback on the earlier version of our manuscript and for reexamining the revisions we have made.

      References

      Amir, A., P. Kyriazi, S. C. Lee, D. B. Headley, and D. Pare. 2019. "Basolateral amygdala neurons are activated during threat expectation." J Neurophysiol 121 (5):1761-1777.

      Amir, A., S. C. Lee, D. B. Headley, M. M. Herzallah, and D. Pare. 2015. "Amygdala Signaling during Foraging in a Hazardous Environment." J Neurosci 35 (38):12994-3005.

      Bandler, R., P. Carrive, and S. P. Zhang. 1991. "Integration of somatic and autonomic reactions within the midbrain periaqueductal grey: viscerotopic, somatotopic and functional organization." Prog Brain Res 87:269-305.

      Bandler, R., and K. A. Keay. 1996. "Columnar organization in the midbrain periaqueductal gray and the integration of emotional expression." Prog Brain Res 107:285-300.

      Boender, A. J., J. W. de Jong, L. Boekhoudt, M. C. Luijendijk, G. van der Plasse, and R. A. Adan. 2014. "Combined use of the canine adenovirus-2 and DREADD-technology to activate specific neural pathways in vivo." PLoS One 9 (4):e95392.

      Cameron, A. A., I. A. Khan, K. N. Westlund, and W. D. Willis. 1995. "The efferent projections of the periaqueductal gray in the rat: a Phaseolus vulgaris-leucoagglutinin study. II. Descending projections." J Comp Neurol 351 (4):585-601.

      Carrive, P. 1993. "The periaqueductal gray and defensive behavior: functional representation and neuronal organization." Behav Brain Res 58 (1-2):27-47.

      Kim, E. J., M. S. Kong, S. G. Park, S. J. Y. Mizumori, J. Cho, and J. J. Kim. 2018. "Dynamic coding of predatory information between the prelimbic cortex and lateral amygdala in foraging rats." Sci Adv 4 (4):eaar7328.

      Kong, M. S., E. J. Kim, S. Park, L. S. Zweifel, Y. Huh, J. Cho, and J. J. Kim. 2021. "'Fearful-place' coding in the amygdala-hippocampal network." Elife 10.

      Lavoie, A., and B. H. Liu. 2020. "Canine Adenovirus 2: A Natural Choice for Brain Circuit Dissection." Front Mol Neurosci 13:9.

      Li, Y., L. Hickey, R. Perrins, E. Werlen, A. A. Patel, S. Hirschberg, M. W. Jones, S. Salinas, E. J. Kremer, and A. E. Pickering. 2016. "Retrograde optogenetic characterization of the pontospinal module of the locus coeruleus with a canine adenoviral vector." Brain Res 1641 (Pt B):274-90.

      McNally, G. P., J. P. Johansen, and H. T. Blair. 2011. "Placing prediction into the fear circuit."  Trends Neurosci 34 (6):283-92.

      Roth, B. L. 2016. "DREADDs for Neuroscientists." Neuron 89 (4):683-94.

      Senn, V., S. B. Wolff, C. Herry, F. Grenier, I. Ehrlich, J. Grundemann, J. P. Fadok, C. Muller, J. J. Letzkus, and A. Luthi. 2014. "Long-range connectivity defines behavioral specificity of amygdala neurons." Neuron 81 (2):428-37.

      Vianna, D. M., and M. L. Brandao. 2003. "Anatomical connections of the periaqueductal gray: specific neural substrates for different kinds of fear." Braz J Med Biol Res 36 (5):557-66.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Reviewer #1 (Public Review): 

      Summary: 

      The author presents the discovery and characterization of CAPSL as a potential gene linked to Familial Exudative Vitreoretinopathy (FEVR), identifying one nonsense and one missense mutation within CAPSL in two distinct patient families afflicted by FEVR. Cell transfection assays suggest that the missense mutation adversely affects protein levels when overexpressed in cell cultures. Furthermore, conditionally knocking out CAPSL in vascular endothelial cells leads to compromised vascular development. The suppression of CAPSL in human retinal microvascular endothelial cells results in hindered tube formation, a decrease in cell proliferation, and disrupted cell polarity. Additionally, transcriptomic and proteomic profiling of these cells indicates alterations in the MYC pathway. 

      Strengths: 

      The study is nicely designed with a combination of in vivo and in vitro approaches, and the experimental results are good quality. 

      We thank the reviewer for the conclusion and positive comments.

      Weaknesses: 

      My reservations lie with the main assertion that CAPSL is associated with FEVR, as the genetic evidence from human studies appears relatively weak. Further careful examination of human genetics evidence in both patient cohorts and the general population will help to clarify. In light of human genetics, more caution needs to be exercised when interpreting results from mice and cell models and how is it related to the human patient phenotype. 

      We thank the reviewer for careful reading and constructive suggestion. we added several experiments to address the concern of reviewer are as follows:

      (1) The pLI score of LOF allele of CAPSL is based of general population, among which Europeans account for ~77% and East Asians make up less than 3%. Since the FEVR families in this article all come from China, the pLI score may not be accurate. Of course, we will continue to collect FEVR pedigrees.

      (2) We evaluated the phenotype of Capsl heterozygous mice at P5, and the results showed no overt difference in vascular progression, vessel density and branchpoints with littermate wildtype controls (Fig.S4). The lack of pronounced phenotype in FEVR heterozygous mice may be due to different sensitivity between human and mice. A similar example is LRP5 mutations associated with FEVR. Heterozygous mutations in LRP5 were reported in FEVR patients in multiple populations (PMID: 16929062, 33302760, 27486893, 35918671, 36411543). However, heterozygous Lrp5 knockout mice exhibited no visible angiogenic phenotype (PMID: 18263894). Corresponding description was added in the manuscript at page 6.

      (3) We further assessed the angiogenic phenotype when angiogenesis almost complete at P21, and the resulted revealed no difference observed between Ctrl and CapsliECKO/iECKO mice (Fig.S5). And corresponding description was added in the manuscript at page 7.

      (4) We evaluated the expression of MYC downstream genes in vivo using lung tissue form P35 Ctrl and _Capsl_iECKO/iECKO mice (Fig.S8). Consistent with the results from in vitro HRECs, _Capsl_iECKO/iECKO mice showed downregulated expression of MYC targets. And corresponding description was added in the manuscript at page 11.

      Reviewer #2 (Public Review): 

      Summary: 

      This work identifies two variants in CAPSL in two-generation familial exudative vitreoretinopathy (FEVR) pedigrees, and using a knockout mouse model, they link CAPSL to retinal vascular development and endothelial proliferation. Together, these findings suggest that the identified variants may be causative and that CAPSL is a new FEVR-associated gene. 

      Strengths: 

      The authors' data provides compelling evidence that loss of the poorly understood protein CAPSL can lead to reduced endothelial proliferation in mouse retina and suppression of MYC signaling in vitro, consistent with the disease seen in FEVR patients. The study is important, providing new potential targets and mechanisms for this poorly understood disease. The paper is clearly written, and the data generally support the author's hypotheses. 

      We thank the reviewer for the conclusion and positive comments.

      Weaknesses: 

      (1) Both pedigrees described appear to suggest that heterozygosity is sufficient to cause disease, but authors have not explored the phenotype of Capsl heterozygous mice. Do these animals have reduced angiogenesis similar to KOs? Furthermore, while the p.R30X variant protein does not appear to be expressed in vitro, a substantial amount of p.L83F was detectable by western blot and appeared to be at the normal molecular weight. Given that the full knockout mouse phenotype is comparatively mild, it is unclear whether this modest reduction in protein expression would be sufficient to cause FEVR - especially as the affected individuals still have one healthy copy of the gene. Additional studies are needed to determine if these variants alter protein trafficking or localization in addition to expression, and if they can act in a dominant negative fashion. 

      We thank the reviewer for the suggestion. We evaluated the phenotype of Capsl heterozygous mice at P5 (Fig.S4), and the results showed no overt difference in angiogenesis compared with littermate control mice.

      We transfected CAPSL wild-type plasmid, p.R30X mutant plasmid and p.L83F mutant plasmid into 293T cells to assess the intracellular localization change of CAPSL mutant proteins (Fig.S1). The result showed that the point mutation did not affect the localization of the mutated protein, and corresponding description was added in the manuscript at page 5.

      (2) The manuscript nicely shows that loss of CAPSL leads to suppressed MYC signaling in vitro. However, given that endothelial MYC is regulated by numerous pathways and proteins, including FOXO1, VEGFR2, ERK, and Notch, and reduced MYC signaling is generally associated with reduced endothelial proliferation, this finding provides little insight into the mechanism of CAPSL in regulating endothelial proliferation. It would be helpful to explore the status of these other pathways in knockdown cells but as the authors provide only GSEA results and not the underlying data behind their RNA seq results, it is difficult for the reader to understand the full phenotype. Volcano plots or similar representations of the underlying expression data in Figures 6 and 7 as well as supplemental datasets showing the differentially regulated genes should be included. In addition, while the paper beautifully characterizes the delayed retinal angiogenesis phenotype in CAPSL knockout mice, the authors do not return to that model to confirm their in vitro findings. 

      We thank the reviewer for the suggestion. Although endothelial MYC can be regulated by FOXO1, VEGFR2, ERK, and Notch signaling pathway, these pathways are not enriched in the RNA seq data of CAPSL-depleted HRECs. This suggests that the down regulated MYC targets may not be influenced by the signaling pathway mentioned above. RNA-seq raw data have been uploaded to the Genome Sequence Archive (https://ngdc.cncb.ac.cn/gsa/browse/HRA010305) and proteomic profiling raw data have been uploaded to the Genome Sequence Archive (https://www.ebi.ac.uk/pride/archive), and the assigned accession number was PXD051696. Corresponding description was added in the manuscript at page 20-21. The datasets represent the differentially regulated genes in Figure 6 and 7 were listed at Dataset S1 and S2.

      (3) In Figure S2D, the result of this vascular leak experiment is unconvincing as no dye can be seen in the vessels. What are the kinetics for biocytin tracers to enter the bloodstream after IP injection? Why did the authors choose the IP instead of the IV route for this experiment? Differences in the uptake of the eye after IP injection could confound the results, especially in the context of a model with vascular dysfunction as here. 

      We thank the reviewer for suggestion. In Figure S2D (now Fig.S6D), we used a non-representative image to show vascular leakage. We replaced the images with more representative ones. We are sorry that we are not clear about the kinetics for biocytin tracers to enter the bloodstream after IP injection. Since the experiment was carried out on mice at P5, it is not feasible to do IV injection in P5 neonatal mice. We followed the methods described in the previous study involving mice of same age (PMID:35361685).

      (4) In Figure 5, it is unclear how filipodia and tip cells were identified and selected for quantification. The panels do not include nuclear or tip cell-specific markers that would allow quantification of individual tip cells, and in Figure 5C it appears that some filipodia are not highlighted in the mutant panel. 

      We thank the reviewer for the comments. In Figure 5, we used HRECs to examine the cell proliferation, migration and polarity in vitro, and therefore there is no distinction between tip cells and stalk cells. The quantification of filopodia/lamellipodia was performed as previous studies (PMID: 30783090, PMID: 28805663). In briefly, wound scratch was performed on confluent layers of transfected HRECs, and 9 hours after initiating cell migration by scratch, cells were fixed and stained with phalloidin. Cells at the edge of wound were considered as leader cells and quantified for number of filopodia/lamellipodia.

      Reviewer #3 (Public Review): 

      Summary: 

      This manuscript by Liu et al. presents a case that CAPSL mutations are a cause of familial exudative vitreoretinopathy (FEVR). Attention was initially focused on the CAPSL gene from whole exome sequence analysis of two small families. The follow-up analyses included studies in which CAPSL was manipulated in endothelial cells of mice and multiple iterations of molecular and cellular analyses. Together, the data show that CAPSL influences endothelial cell proliferation and migration. Molecularly, transcriptomic and proteomic analyses suggest that CAPSL influences many genes/proteins that are also downstream targets of MYC and may be important to the mechanisms. 

      Strengths: 

      This multi-pronged approach found a previously unknown function for CAPSLs in endothelial cells and pointed at MYC pathways as high-quality candidates in the mechanism. 

      Weaknesses: 

      Two issues shape the overall impact for me. First, the unreported population frequency of the variants in the manuscript makes it unclear if CAPSL should be considered an interesting candidate possibly contributing to FEVR, or possibly a cause. Second, it is unclear if the identified variants act dominantly, as indicated in the pedigrees. The studies in mice utilized homozygotes for an endothelial cell-specific knockout, leaving uncertainty about what phenotypes might be observed if mice heterozygous for a ubiquitous knockout had instead been studied. 

      In my opinion, the following scientific issues are specific weaknesses that should be addressed: 

      (1) Please state in the manuscript the number of FEVR families that were studied by WES. Please also describe if the families had been selected for the absence of known mutations, and/or what percentage lack known pathogenic variants. 

      We thank the reviewer for thoughtful comments. 120 FEVR families were studied by WES and we added corresponding description in the manuscript at page 4.

      (2) A better clinical description of family 3104 would enhance the manuscript, especially the father. It is unclear what "manifested with FEVR symptoms, according to the medical records" means. Was the father diagnosed with FEVR? If the father has some iteration of a mild case, please describe it in more detail. If the lack of clinical images in the figure is indicative of a lack of medical documentation, please note this in the manuscript. 

      We thank the reviewer for thoughtful comments. The father of family 3104 has also been identified as a carrier of this heterozygous variant, manifested with FEVR symptoms, according to the medical records. Nevertheless, clinical examination images are presently unavailable. We added corresponding description in the manuscript at page 5.

      (3) The TGA stop codon can in some instances also influence splicing (PMID: 38012313). Please add a bioinformatic assessment of splicing prediction to the assays and report its output in the manuscript. 

      We thank the reviewer for thoughtful comments. We predicted the splicing of c.88C>T variant of CAPSL using MaxEntScan (http://hollywood.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html) and SpliceTool (https://rddc.tsinghua-gd.org/ai) (Fig.S2). MaxEntScan and SpliceTool were used to predict the impact of TGA stop codon of c.88C>T variant on the formation of a cryptic donor splice site.

      (4) More details regarding utilizing a "loxp-flanked allele of CAPSL" are needed. Is this an existing allele, if so, what is the allele and citation? If new (as suggested by S1), the newly generated CAPSL mutant mouse strain needs to be entered into the MGI database and assigned an official allele name - which should then be utilized in the manuscript and who generated the strain (presumably a core or company?) must be described. 

      We added detailed description of Capsl flxoed allele to Method section on page 14-15: “Capslloxp/+ model was generated using the CRISPR/Cas9 nickase technique by Viewsolid Biotechology (Beijing, China) in C57BL/6J background and named Capslem1zxj. The genomic RNA (gRNA) sequence was as follows: Capsl-L gRNA: 5’-CTATCCCAA TTGTGCTCCTGG-3’; Capsl-R gRNA: 5’-TGGGACTCATGGTTCTAGAGG-3’. ”

      (5) The statement in the methods "All mice used in the study were on a C57BL/6J genetic background," should be better defined. Was the new allele generated on a pure C57BL/6J genetic background, or bred to be some level of congenic? If congenic, to what generation? If unknown, please either test and report the homogeneity of the background, or consult with nomenclature experts (such as available through MGI) to adopt the appropriate F?+NX type designation. This also pertains to the Pdgfb-iCreER mice, which reference 43 describes as having been generated in an F2 population of C57BL/6 X CBA and did not designate the sub-strain of C57BL/6 mice. It is important because one of the explanations for missing heritability in FEVR may be a high level of dependence on genetic background. From the information in the current description, it is also not inherently obvious that the mice studied did not harbor confounding mutations such as rd1 or rd8. 

      We thank the reviewer for suggestion. We added the following description to “Mouse model and genotyping” method section on page 14. “Capslloxp/+ model was generated using the CRISPR/Cas9 nickase technique by Viewsolid Biotechology (Beijing, China) in C57BL/6J background and named Capslem1zxj. The genomic RNA (gRNA) sequence was as follows: Capsl-L gRNA: 5’-CTATCCCAA TTGTGCTCCTGG-3’; Capsl-R gRNA: 5’-TGGGACTCATGGTTCTAGAGG-3’. Pdgfb-iCreER[43] transgenic mice on a mixed background of C57BL/6 and CBA was obtainted from Dr. Marcus Fruttiger and backcrossed to background for 6 generations. Capslloxp/+ mice were bred with Pdgfb-iCreER[43] transgenic mice to generate Capslloxp/loxp, Pdgfb-iCreER mice.” Sanger sequencing was performed on experimental mice to identify whether they harbor confounding mutations such as Pde6b or Crb1. The results showed the mice did not harbor confounding mutations (Fig.S9) and corresponding description was added in the manuscript at page 15.

      (6) In my opinion, more experimental detail is needed regarding Figures 2 and 3. How many fields, of how many retinas and mice were analyzed in Figure 2? How many mice were assessed in Figure 3? 

      We thank the reviewer for thoughtful comments. We have already presented the detailed information in the manuscript, please refer to the “Methods-Quantification of retinal parameters” section for experimental details.

      (7) I suggest adding into the methods whether P-values were corrected for multiple tests. 

      We thank the reviewer for suggestion. Actually, the statistical analysis was performed using unpaired Student’s t-test for comparison between two groups or one-way ANOVA followed by Dunnett multiple comparison test for comparison of multiple groups. The above description was added to “Methods-Image acquisition and statistical analysis” section to make it clear.

      Recommendations for the authors:

      Reviewing Editor (Recommendations For The Authors): 

      In summary, the following concerns should addressing reviewers' concerns as outlined below could bolster the evidence from "solid" to "convincing" and further strengthen the study's impact. 

      (1) Analysis of the phenotype in CAPSLheterozygous mice, as highlighted by all 3 reviews. 

      We thank the editor for thoughtful comments. The phenotype analysis of Capsl heterozygous mice was added to Fig.S4, with the corresponding description provided at page 6.

      (2) Analysis of Capsl KO mice to determine if the pathways identified in vitro are modified (as suggested by reviewers 1 & 2). 

      We thank the editor for suggestion. In Fig.S7, RT-qPCR was performed on lung tissues from Capsl Ctrl and KO mice to validate the expression of MYC targets in vivo. And the result indicated that the downstream targets of MYC signaling were also downregulated in vivo, consistent with the in vitro findings.

      (3) Additional description of the genetic pedigrees and variants to address the points raised by reviewer #3. 

      We thank the editor for suggestion. The father of family 3104 has also been identified as a carrier of this heterozygous variant, manifested with FEVR symptoms, according to the medical records. Nevertheless, clinical examination data are presently unavailable. We added corresponding description in the manuscript page 5.

      (4) Validation of the identified protein variants, especially L83F which appears to be expressed at a near normal level. Are these proteins mislocalized, do the variants to interfere with sites of known or predicted protein-protein interactions, could they act in a dominant-negative fashion by aggregation with co-expressed WT protein etc. Given the comparatively weak genetic data, additional validation is required to establish plausibility of CAPSL as a FEVR gene. 

      We thank the editor for suggestion. As substantial amount of p.L83F was detectable at normal molecular weight, we further investigated whether this variant affects protein localization. Fig.S1, immunocytochemistry results indicated that this variant does not affect the subcellular localization of the protein.

      (5) Improved description of experimental details and statistical analyses as outlined by reviewer #3. 

      We thank the editor for suggestion. The more detailed information about Capsl mice was added in the manuscript at page 14-15. The experimental details regarding Figure 2 and Figure 3 have already presented in the “Methods-Quantification of retina parameters” section in the manuscript at page 19-20. And the statistical analysis was performed using unpaired Student’s t-test for comparison between two groups or one-way ANOVA followed by Dunnett multiple comparison test for comparison of multiple groups. The above description was added to “Methods-Image acquisition and statistical analysis” section at page 21 to make it clear.

      Reviewer #1 (Recommendations For The Authors): 

      My reservations lie with the main assertion that CAPSL is associated with FEVR, as the genetic evidence from human studies appears relatively weak. My concerns are as follows: 

      (1) The molecular characterization of the identified mutations suggests a loss of function (LOF). Notably, in one family, both the father and son exhibit the FEVR phenotype and share the LOF mutation, suggesting a dominant mode of inheritance. However, the prevalence of the LOF allele of CAPSL in the general population is high, and its pLI score is 0, according to the GNOMAD database. This raises doubts about the LOF variant of CAPSL being causative for FEVR. 

      We thank the reviewer for recommendation. The pLI score of LOF allele of CAPSL is based of general population, among which Europeans account for ~77% and East Asians make up less than 3%. Since the FEVR families in this article all come from China, the pLI score may not be accurate. Of course, we will continue to collect FEVR pedigrees and screen for CAPSL mutations.

      (2) In the conditional knockout study, a delay in vascular development is observed in the retina up to P14. What the phenotype looks like in adult mice and whether it replicates the human FEVR phenotype? 

      We thank the reviewer for recommendation. We further assessed the phenotype when angiogenesis almost complete at P21, the resulted showed no difference in Ctrl and CapsliECKO/iECKO mice (Fig.S5). And corresponding description was added in the manuscript at page 7.

      (3) The conditional knockout mice lack both alleles of CAPSL. The phenotype resulting from the knockout of a single allele needs investigation to align with observed human phenotypes and genetic data. 

      We thank the reviewer for recommendation. The phenotype of Capsl heterozygous mice at P5 showed no overt difference in vascular progression, vessel density and branchpoints with littermate wildtype controls (Fig.S4). The lack of pronounced phenotype in FEVR heterozygous mice may be due to different sensitivity between human and mice. A similar example is LRP5 mutations associated with FEVR. Heterozygous mutations in LRP5 were reported in FEVR patients in multiple populations. However, heterozygous Lrp5 mice exhibited no visible angiogenic phenotype (PMID: 18263894).

      (4) The MYC pathway has been identified as influenced by CAPSL. Whether MYC downregulation is observed in the mouse model in vivo? 

      We thank the reviewer for recommendation. MYC expression was identified at both mRNA and protein level in Figure S8, and corresponding description was added in the manuscript at page 11.

      Reviewer #2 (Recommendations For The Authors): 

      Minor comments: 

      (1) While authors note that little is known about CAPSL protein function, more introductory detail about the protein (structure, domains intracellular localization etc) and additional discussion on potential mechanisms would aid the reader in interpreting the findings and model.

      We thank the reviewer for recommendation. The subcellular localization of the CAPSL protein is distributed in both the nucleus and cytoplasm (https://www.proteinatlas.org/). The immunochemistry analysis confirmed that CAPSL protein is expressed in both the cell nucleus and cytoplasm (Fig.S1). And corresponding description was added in the manuscript at page 5.

      (2) Pg 7 states that Capsl knockout mainly leads to "...defects in retinal vascular ECs rather than other vascular cells.". Consider rephrasing to describe "other vasculature-associated cells", as no vascular cells outside the retina were examined in the manuscript. 

      We thank the reviewer for recommendation. We rephrased the "...defects in retinal vascular ECs rather than other vascular cells." into "...defects in retinal vascular ECs rather than other vasculature-associated cells" at page 8.

      (3) The manuscript is well written but contains numerous typos. E.g. "" (Pg 14), "MCY signaling axis" (figure 6 legend), "shCAPAL" (figure 5 K). Please correct these, and search carefully for others. 

      We are sorry for the careless mistakes we made, and we have checked the manuscript and correct these mistakes.

      Reviewer #3 (Recommendations For The Authors): 

      The following are somewhat grammatical, but significant issues, that I feel should be addressed before making the pre-print final: 

      (1) Perhaps the largest issue with the manuscript to me is whether CAPSL is an interesting candidate (as stated repeatedly) or causative of FEVR. Within the scope of what is feasible, this is a challenging problem. Since the publication of the pre-print, it would be great if another group independently reported the detection of mutations specifically in FEVR patients. That lacking, meaningful additions to the manuscript that I'd recommend are the inclusion of a paragraph on caveats of the study and reporting the allele frequencies based on public databases. As the authors know the data better than anyone and will have invested thought into the implications, they are the ones best positioned to alert the field to the study's limitations - amongst them- the factors that might practically distinguish whether CAPSL is a candidate or cause.

      We thank the reviewer for recommendation. We will collect more samples from FEVR families and screen for other mutation sites within the CAPSL gene in further studies.

      (2) It is unclear why the modeling with mice did not attempt to recapitulate the observations in humans, i.e., why were heterozygotes for a ubiquitous knockout not studied? Any data with heterozygotes, or ubiquitous alleles (which would be easier to generate than the strain studied) should be shared in the manuscript. If no such data exists, this reviewer would find it a worthwhile new experiment to add, but it is appreciated that new experiments are sometimes beyond the scope of what is possible. At the least, this would be worthwhile to discuss in the requested caveats paragraph of the discussion. 

      We thank the reviewer for recommendation. We evaluated the phenotype of Capsl heterozygous mice at P5, and the results showed no overt difference in vascular progression, vessel density and branchpoints with littermate wildtype controls (Fig.S4). The lack of pronounced phenotype in FEVR heterozygous mice may be due to different sensitivity between human and mice. For example, heterozygous Lrp5 mice exhibited no visible angiogenic phenotype (PMID: 18263894). Corresponding description was added in the manuscript at page 6.

      (3) The statement in the Abstract "which provides invaluable information for genetic counseling and prenatal diagnosis of FEVR" should be toned down, better supported, or rephrased. This appears to be the 18th disease-associated gene for FEVR, with variants identified in 4 patients of the same ethnicity. In my opinion, the word "invaluable" is currently overstated. 

      We thank the reviewer for recommendation. We have changed "which provides invaluable information for genetic counseling and prenatal diagnosis of FEVR" into "which provides valuable information for genetic counseling and prenatal diagnosis of FEVR" in the abstract.

      (4) The transcriptomic and proteomic data should be deposited into a public repository and accession numbers added to the manuscript. 

      We thank the reviewer for recommendation. We have uploaded the raw data of transcriptomic and proteomic to the Genome Sequence Archive (https://ngdc.cncb.ac.cn/gsa/browse/HRA010305) and the Genome Sequence Archive (https://www.ebi.ac.uk/pride/archive), respectively.

      (5) The links to MYC are over-stated in the title "through the MYC axis", the abstract "CAPSL function causes FEVR through MYC axis", and the discussion "we demonstrated that the defects in CAPSL affect EC function by down-regulating the MYC signaling cascade". The links to MYC are entirely by association, there were no experiments testing that the transcriptomic and proteomic changes observed were determinative of the CAPSL-mediated phenotype. It seems appropriate to conjecture that these changes are important, but the above statements all need to be altered and conjectures need to be clearly identified as such. 

      We are sorry to overstate the link between CAPSL-mediated phenotype and MYC axis in the abstract and discussion sections, and we have altered the statements in these sections to make it more logical. For example, we changed “This study also reveals that compromised CAPSL function causes FEVR through MYC axis, shedding light on the potential involvement of MYC signaling in the pathogenesis of FEVR.” into “This study also reveals that compromised CAPSL function causes FEVR may through MYC axis, shedding light on the potential involvement of MYC signaling in the pathogenesis of FEVR.” in the abstract. And in the discussion we changed “…cause FEVR through inactivating MYC signaling, expanding FEVR-involved signaling pathway and providing a potential therapeutic target for the intervention of FEVR” to “…cause FEVR may through inactivating MYC signaling, expanding FEVR-involved signaling pathway and providing a potential therapeutic target for the intervention of FEVR”.

      (6) Finally, I suggest that the following grammatical issues in the pre-print be corrected before making the pre-print final: 

      We have checked the manuscript and correct these mistakes.

      (a) p2. Suggest rewriting the sentence "Nevertheless, the molecular mechanisms by which CAPSL regulates cell processes and signaling cascades have yet to be elucidated." The preceding sentences only state that CASPL is a candidate in another disease - the word "nevertheless" seems to reflect a logic that isn't described. 

      We have checked the manuscript and correct these mistakes.

      (b) p5. Please correct the grammar "We, generated an inducible" 

      We corrected this mistake.

      (c) p5. Suggest rephrasing "impairing CAPSL expression." The word "expression" is often used in reference to transcription. To avoid confusion, something such as "eliminating or reducing protein abundance" might be better. 

      We corrected this mistake.

      (d) p6. Please correct the grammar "As expected, the radial vascular growth, as well as vessel density and vascular branching, are dramatically reduced in..." - note subject-verb agreement issue 

      We corrected this mistake.

      (e) Figure 3 legend - correct "(A) Hyloaid vessels"

      We corrected this mistake.

  6. Jul 2024
    1. Author response:

      We thank you for the opportunity to provide a concise response. The criticisms are accurately summarized in the eLife assessment:

      the study fails to engage prior literature that has extensively examined the impact of variance in offspring number, implying that some of the paradoxes presented might be resolved within existing frameworks.

      The essence of our study is to propose the adoption of the Haldane model of genetic drift, based on the branching process, in lieu of the Wright-Fisher (WF) model, based on sampling, usually binomial.  In addition to some extensions of the Haldane model, we present 4 paradoxes that cannot be resolved by the WF model. The reviews suggest that some of the paradoxes could be resolved by the WF model, if we engage prior literature sufficiently.

      We certainly could not review all the literature on genetic drift as there must be thousands of them. Nevertheless, the literature we do not cover is based on the WF model, which has the general properties that all modifications of the WF model share.  (We should note that all such modifications share the sampling aspect of the WF model. To model such sampling, N is imposed from outside of the model, rather than self-generating within the model.  Most important, these modifications are mathematically valid but biologically untenable, as will be elaborated below. Thus, in concept, the WF and Haldane models are fundamentally different.)

      In short, our proposal is general with the key point that the WF model cannot resolve these (and many other) paradoxes.  The reviewers disagree (apparently only partially) and we shall be specific in our response below.

      We shall first present the 4th paradox, which is about multi-copy gene systems (such as rRNA genes and viruses, see the companion paper). Viruses evolve both within and between hosts. In both stages, there are severe bottlenecks.  How does one address the genetic drift in viral evolution? How can we model the effective population sizes both within- and between- hosts?  The inability of the WF model in dealing with such multi-copy gene systems may explain the difficulties in accounting for the SARS-CoV-2 evolution. Given the small number of virions transmitted between hosts, drift is strong which we have shown by using the Haldane model (Ruan, Luo, et al. 2021; Ruan, Wen, et al. 2021; Hou, et al. 2023). 

      As the reviewers suggest, it is possible to modify the WF model to account for some of these paradoxes. However, the modifications are often mathematically convenient but biologically dubious. Much of the debate is about the progeny number, K.  (We shall use haploid model for this purpose but diploidy does not pose a problem as stated in the main text.) The modifications relax the constraint of V(k) = E(k) inherent in the WF sampling.  One would then ask how V(k) can be different from E(k) in the WF sampling even though it is mathematically feasible (but biologically dubious)?  Kimura and Crow (1963) may be the first to offer a biological explanation.  If one reads it carefully, Kimura's modification is to make the WF model like the Haldane model. Then, why don't we use the Haldane model in the first place by having two parameters, E(k) and V(k), instead of the one-parameter WF model?

      The Haldane model is conceptually simpler. It allows the variation in population size, N, to be generated from within the model, rather than artificially imposed from outside of the model.  This brings us to the first paradox, the density-dependent Haldane model. When N is increasing exponentially as in bacterial or yeast cultures, there is almost no drift when N is very low and drift becomes intense as N grows to near the carrying capacity.  We do not see how the WF model can resolve this paradox, which can otherwise be resolved by the Haldane model.

      The second and third paradoxes are about how much mathematical models of population genetic can be detached from biological mechanisms. The second paradox about sex chromosomes is rooted in the realization of V(k) ≠ E(k).  Since E(k) is the same between sexes but V(k) is different, how does the WF sampling give rise to V(k) ≠ E(k)? We are asking a biological question that troubled Kimura and Crow (1963) alluded above. The third paradox is acknowledged by two reviewers. Genetic drift manifested in the fixation probability of an advantageous mutation is 2s/V(k).  It is thus strange that the fundamental parameter of drift in the WF model, N (or Ne), is missing.  In the Haldane model, drift is determined by V(k) with N being a scaling factor; hence 2s/V(k) makes perfect biological sense,

      We now answer the obvious question: If the model is fundamentally about the Haldane model, why do we call it the WF-Haldane model? The reason is that most results obtained by the WF model are pretty good approximations and the branching process may not need to constantly re-derive the results.  At least, one can use the WF results to see how well they fit into the Haldane model. In our earlier study (Chen, et al. (2017); Fig. 3), we show that the approximations can be very good in many (or most) settings.

      We would like to use the modern analogy of gas-engine cars vs. electric-motor ones. The Haldane model and the WF model are as fundamentally different concepts as the driving mechanisms of gas-powered vs electric cars.  The old model is now facing many problems and the fixes are often not possible.  Some fixes are so complicated that one starts thinking about simpler solutions. The reservations are that we have invested so much in the old models which might be wasted by the switch. However, we are suggesting the integration of the WF and Haldane models. In this sense, the WF model has had many contributions which the new model gratefully inherits. This is true with the legacy of gas-engine cars inherited by EVs.

      The editors also issue the instruction: while the modified model yields intriguing theoretical predictions, the simulations and empirical analyses are incomplete to support the authors' claims. 

      We are thankful to the editors and reviewers for the thoughtful comments and constructive criticisms. We also appreciate the publishing philosophy of eLife that allows exchanges, debates and improvements, which are the true spirits of science publishing.

      References for the provisional author responses

      Chen Y, Tong D, Wu CI. 2017. A New Formulation of Random Genetic Drift and Its Application to the Evolution of Cell Populations. Mol. Biol. Evol. 34:2057-2064.

      Hou M, Shi J, Gong Z, Wen H, Lan Y, Deng X, Fan Q, Li J, Jiang M, Tang X, et al. 2023. Intra- vs. Interhost Evolution of SARS-CoV-2 Driven by Uncorrelated Selection-The Evolution Thwarted. Mol. Biol. Evol. 40.

      Kimura M, Crow JF. 1963. The measurement of effective population number. Evolution:279-288.

      Ruan Y, Luo Z, Tang X, Li G, Wen H, He X, Lu X, Lu J, Wu CI. 2021. On the founder effect in COVID-19 outbreaks: how many infected travelers may have started them all? Natl. Sci. Rev. 8:nwaa246.

      Ruan Y, Wen H, He X, Wu CI. 2021. A theoretical exploration of the origin and early evolution of a pandemic. Sci Bull (Beijing) 66:1022-1029.

      Review comments

      eLife assessment 

      This study presents a useful modification of a standard model of genetic drift by incorporating variance in offspring numbers, claiming to address several paradoxes in molecular evolution.

      It is unfortunate that the study fails to engage prior literature that has extensively examined the impact of variance in offspring number, implying that some of the paradoxes presented might be resolved within existing frameworks.

      We do not believe that the paradoxes can be resolved.

      In addition, while the modified model yields intriguing theoretical predictions, the simulations and empirical analyses are incomplete to support the authors' claims. 

      Public Reviews: 

      Reviewer #1 (Public Review): 

      Summary: 

      The authors present a theoretical treatment of what they term the "Wright-Fisher-Haldane" model, a claimed modification of the standard model of genetic drift that accounts for variability in offspring number, and argue that it resolves a number of paradoxes in molecular evolution. Ultimately, I found this manuscript quite strange.

      The notion of effective population size as inversely related to the variance in offspring number is well known in the literature, and not exclusive to Haldane's branching process treatment. However, I found the authors' point about variance in offspring changing over the course of, e.g. exponential growth fairly interesting, and I'm not sure I'd seen that pointed out before.

      Nonetheless, I don't think the authors' modeling, simulations, or empirical data analysis are sufficient to justify their claims. 

      Weaknesses: 

      I have several outstanding issues. First of all, the authors really do not engage with the literature regarding different notions of an effective population. Most strikingly, the authors don't talk about Cannings models at all, which are a broad class of models with non-Poisson offspring distributions that nonetheless converge to the standard Wright-Fisher diffusion under many circumstances, and to "jumpy" diffusions/coalescents otherwise (see e.g. Mohle 1998, Sagitov (2003), Der et al (2011), etc.). Moreover, there is extensive literature on effective population sizes in populations whose sizes vary with time, such as Sano et al (2004) and Sjodin et al (2005).

      Of course in many cases here the discussion is under neutrality, but it seems like the authors really need to engage with this literature more. 

      The most interesting part of the manuscript, I think, is the discussion of the Density Dependent Haldane model (DDH). However, I feel like I did not fully understand some of the derivation presented in this section, which might be my own fault. For instance, I can't tell if Equation 5 is a result or an assumption - when I attempted a naive derivation of Equation 5, I obtained E(K_t) = 1 + r/c*(c-n)*dt. It's unclear where the parameter z comes from, for example. Similarly, is equation 6 a derivation or an assumption? Finally, I'm not 100% sure how to interpret equation 7. I that a variance effective size at time t? Is it possible to obtain something like a coalescent Ne or an expected number of segregating sites or something from this? 

      Similarly, I don't understand their simulations. I expected that the authors would do individual-based simulations under a stochastic model of logistic growth, and show that you naturally get variance in offspring number that changes over time. But it seems that they simply used their equations 5 and 6 to fix those values. Moreover, I don't understand how they enforce population regulation in their simulations---is N_t random and determined by the (independent) draws from K_t for each individual? In that case, there's no "interaction" between individuals (except abstractly, since logistic growth arises from a model that assumes interactions between individuals). This seems problematic for their model, which is essentially motivated by the fact that early during logistic growth, there are basically no interactions, and later there are, which increases variance in reproduction. But their simulations assume no interactions throughout! 

      The authors also attempt to show that changing variance in reproductive success occurs naturally during exponential growth using a yeast experiment. However, the authors are not counting the offspring of individual yeast during growth (which I'm sure is quite hard). Instead, they use an equation that estimates the variance in offspring number based on the observed population size, as shown in the section "Estimation of V(K) and E(K) in yeast cells". This is fairly clever, however, I am not sure it is right, because the authors neglect covariance in offspring between individuals. My attempt at this derivation assumes that I_t | I_{t-1} = \sum_{I=1}^{I_{t-1}} K_{i,t-1} where K_{i,t-1} is the number of offspring of individual i at time t-1. Then, for example, E(V(I_t | I_{t-1})) = E(V(\sum_{i=1}^{I_{t-1}} K_{i,t-1})) = E(I_{t-1})V(K_{t-1}) + E(I_{k-1}(I_{k-1}-1))*Cov(K_{i,t-1},K_{j,t-1}). The authors have the first term, but not the second, and I'm not sure the second can be neglected (in fact, I believe it's the second term that's actually important, as early on during growth there is very little covariance because resources aren't constrained, but at carrying capacity, an individual having offspring means that another individuals has to have fewer offspring - this is the whole notion of exchangeability, also neglected in this manuscript). As such, I don't believe that their analysis of the empirical data supports their claim. 

      Thus, while I think there are some interesting ideas in this manuscript, I believe it has some fundamental issues:

      first, it fails to engage thoroughly with the literature on a very important topic that has been studied extensively. Second, I do not believe their simulations are appropriate to show what they want to show. And finally, I don't think their empirical analysis shows what they want to show. 

      References: 

      Möhle M. Robustness results for the coalescent. Journal of Applied Probability. 1998;35(2):438-447. doi:10.1239/jap/1032192859 

      Sagitov S. Convergence to the coalescent with simultaneous multiple mergers. Journal of Applied Probability. 2003;40(4):839-854. doi:10.1239/jap/1067436085 

      Der, Ricky, Charles L. Epstein, and Joshua B. Plotkin. "Generalized population models and the nature of genetic drift." Theoretical population biology 80.2 (2011): 80-99 

      Sano, Akinori, Akinobu Shimizu, and Masaru Iizuka. "Coalescent process with fluctuating population size and its effective size." Theoretical population biology 65.1 (2004): 39-48 

      Sjodin, P., et al. "On the meaning and existence of an effective population size." Genetics 169.2 (2005): 1061-1070 

      Reviewer #2 (Public Review): 

      Summary: 

      This theoretical paper examines genetic drift in scenarios deviating from the standard Wright-Fisher model. The authors discuss Haldane's branching process model, highlighting that the variance in reproductive success equates to genetic drift. By integrating the Wright-Fisher model with the Haldane model, the authors derive theoretical results that resolve paradoxes related to effective population size. 

      Strengths: 

      The most significant and compelling result from this paper is perhaps that the probability of fixing a new beneficial mutation is 2s/V(K). This is an intriguing and potentially generalizable discovery that could be applied to many different study systems. 

      The authors also made a lot of effort to connect theory with various real-world examples, such as genetic diversity in sex chromosomes and reproductive variance across different species. 

      Weaknesses: 

      One way to define effective population size is by the inverse of the coalescent rate. This is where the geometric mean of Ne comes from. If Ne is defined this way, many of the paradoxes mentioned seem to resolve naturally. If we take this approach, one could easily show that a large N population can still have a low coalescent rate depending on the reproduction model. However, the authors did not discuss Ne in light of the coalescent theory. This is surprising given that Eldon and Wakeley's 2006 paper is cited in the introduction, and the multiple mergers coalescent was introduced to explain the discrepancy between census size and effective population size, superspreaders, and reproduction variance - that said, there is no explicit discussion or introduction of the multiple mergers coalescent. 

      The Wright-Fisher model is often treated as a special case of the Cannings 1974 model, which incorporates the variance in reproductive success. This model should be discussed. It is unclear to me whether the results here have to be explained by the newly introduced WFH model, or could have been explained by the existing Cannings model. 

      The abstract makes it difficult to discern the main focus of the paper. It spends most of the space introducing "paradoxes". 

      The standard Wright-Fisher model makes several assumptions, including hermaphroditism, non-overlapping generations, random mating, and no selection. It will be more helpful to clarify which assumptions are being violated in each tested scenario, as V(K) is often not the only assumption being violated. For example, the logistic growth model assumes no cell death at the exponential growth phase, so it also violates the assumption about non-overlapping generations. 

      The theory and data regarding sex chromosomes do not align. The fact that \hat{alpha'} can be negative does not make sense. The authors claim that a negative \hat{alpha'} is equivalent to infinity, but why is that? It is also unclear how theta is defined. It seems to me that one should take the first principle approach e.g., define theta as pairwise genetic diversity, and start with deriving the expected pair-wise coalescence time under the MMC model, rather than starting with assuming theta = 4Neu. Overall, the theory in this section is not well supported by the data, and the explanation is insufficient. 

      {Alpha and alpha' can both be negative.  X^2 = 0.47 would yield x = -0.7}

      Reviewer #3 (Public Review): 

      Summary: 

      Ruan and colleagues consider a branching process model (in their terminology the "Haldane model") and the most basic Wright-Fisher model. They convincingly show that offspring distributions are usually non-Poissonian (as opposed to what's assumed in the Wright-Fisher model), and can depend on short-term ecological dynamics (e.g., variance in offspring number may be smaller during exponential growth). The authors discuss branching processes and the Wright-Fisher model in the context of 3 "paradoxes": (1) how Ne depends on N might depend on population dynamics; (2) how Ne is different on the X chromosome, the Y chromosome, and the autosomes, and these differences do match the expectations base on simple counts of the number of chromosomes in the populations; (3) how genetic drift interacts with selection. The authors provide some theoretical explanations for the role of variance in the offspring distribution in each of these three paradoxes. They also perform some experiments to directly measure the variance in offspring number, as well as perform some analyses of published data. 

      Strengths: 

      (1) The theoretical results are well-described and easy to follow. 

      (2) The analyses of different variances in offspring number (both experimentally and analyzing public data) are convincing that non-Poissonian offspring distributions are the norm. 

      (3) The point that this variance can change as the population size (or population dynamics) change is also very interesting and important to keep in mind. 

      (4) I enjoyed the Density-Dependent Haldane model. It was a nice example of the decoupling of census size and effective size. 

      Weaknesses: 

      (1) I am not convinced that these types of effects cannot just be absorbed into some time-varying Ne and still be well-modeled by the Wright-Fisher process. 

      (2) Along these lines, there is well-established literature showing that a broad class of processes (a large subset of Cannings' Exchangeable Models) converge to the Wright-Fisher diffusion, even those with non-Poissonian offspring distributions (e.g., Mohle and Sagitov 2001). E.g., equation (4) in Mohle and Sagitov 2001 shows that in such cases the "coalescent Ne" should be (N-1) / Var(K), essentially matching equation (3) in the present paper. 

      (3) Beyond this, I would imagine that branching processes with heavy-tailed offspring distributions could result in deviations that are not well captured by the authors' WFH model. In this case, the processes are known to converge (backward-in-time) to Lambda or Xi coalescents (e.g., Eldon and Wakely 2006 or again in Mohle and Sagitov 2001 and subsequent papers), which have well-defined forward-in-time processes. 

      (4) These results that Ne in the Wright-Fisher process might not be related to N in any straightforward (or even one-to-one) way are well-known (e.g., Neher and Hallatschek 2012; Spence, Kamm, and Song 2016; Matuszewski, Hildebrandt, Achaz, and Jensen 2018; Rice, Novembre, and Desai 2018; the work of Lounès Chikhi on how Ne can be affected by population structure; etc...) 

      (5) I was also missing some discussion of the relationship between the branching process and the Wright-Fisher model (or more generally Cannings' Exchangeable Models) when conditioning on the total population size. In particular, if the offspring distribution is Poisson, then conditioned on the total population size, the branching process is identical to the Wright-Fisher model. 

      (6) In the discussion, it is claimed that the last glacial maximum could have caused the bottleneck observed in human populations currently residing outside of Africa. Compelling evidence has been amassed that this bottleneck is due to serial founder events associated with the out-of-Africa migration (see e.g., Henn, Cavalli-Sforza, and Feldman 2012 for an older review - subsequent work has only strengthened this view). For me, a more compelling example of changes in carrying capacity would be the advent of agriculture ~11kya and other more recent technological advances. 

      Recommendations for the authors: 

      Reviewing Editor Comments: 

      The reviewers recognize the value of this model and some of the findings, particularly results from the density-dependent Haldane model. However, they expressed considerable concerns with the model and overall framing of this manuscript.

      First, all reviewers pointed out that the manuscript does not sufficiently engage with the extensive literature on various models of effective population size and genetic drift, notably lacking discussion on Cannings models and related works.

      Second, there is a disproportionate discussion on the paradoxes, yet some of the paradoxes might already be resolved within current theoretical frameworks. All three reviewers found the modeling and simulation of the yeast growth experiment hard to follow or lacking justification for certain choices. The analysis approach of sex chromosomes is also questioned. 

      The reviewers recommend a more thorough review of relevant prior literature to better contextualize their findings. The authors need to clarify and/or modify their derivations and simulations of the yeast growth experiment to address the identified caveats and ensure robustness. Additionally, the empirical analysis of the sex chromosome should be revisited, considering alternative scenarios rather than relying solely on the MSE, which only provides a superficial solution. Furthermore, the manuscript's overall framing should be adjusted to emphasize the conclusions drawn from the WFH model, rather than focusing on the "unresolved paradoxes", as some of these may be more readily explained by existing frameworks. Please see the reviewers' overall assessment and specific comments. 

      Reviewer #2 (Recommendations For The Authors): 

      In the introduction -- "Genetic drift is simply V(K)" -- this is a very strong statement. You can say it is inversely proportional to V(K), but drift is often defined based on changes in allele frequency. 

      Page 3 line 86. "sexes is a sufficient explanation."--> "sex could be a sufficient explanation" 

      The strongest line of new results is about 2s/V(K). Perhaps, the paper could put more emphasis on this part and demonstrate the generality of this result with a different example. 

      The math notations in the supplement are not intuitive. e.g., using i_k and j_k as probabilities. I also recommend using E[X] and V[X]for expectation and variance rather than \italic{E(X)} to improve the readability of many equations. 

      Eq A6, A7, While I manage to follow, P_{10}(t) and P_{10} are not defined anywhere in the text. 

      Supplement page 7, the term "probability of fixation" is confusing in a branching model. 

      E.q. A 28. It is unclear eq. A.1 could be used here directly. Some justification would be nice. 

      Supplement page 17. "the biological meaning of negative..". There is no clear justification for this claim. As a reader, I don't have any intuition as to why that is the case.

    2. Reviewer #1 (Public Review):

      Summary:

      The authors present a theoretical treatment of what they term the "Wright-Fisher-Haldane" model, a claimed modification of the standard model of genetic drift that accounts for variability in offspring number, and argue that it resolves a number of paradoxes in molecular evolution. Ultimately, I found this manuscript quite strange. The notion of effective population size as inversely related to the variance in offspring number is well known in the literature, and not exclusive to Haldane's branching process treatment. However, I found the authors' point about variance in offspring changing over the course of, e.g. exponential growth fairly interesting, and I'm not sure I'd seen that pointed out before. Nonetheless, I don't think the authors' modeling, simulations, or empirical data analysis are sufficient to justify their claims.

      Weaknesses:

      I have several outstanding issues. First of all, the authors really do not engage with the literature regarding different notions of an effective population. Most strikingly, the authors don't talk about Cannings models at all, which are a broad class of models with non-Poisson offspring distributions that nonetheless converge to the standard Wright-Fisher diffusion under many circumstances, and to "jumpy" diffusions/coalescents otherwise (see e.g. Mohle 1998, Sagitov (2003), Der et al (2011), etc.). Moreover, there is extensive literature on effective population sizes in populations whose sizes vary with time, such as Sano et al (2004) and Sjodin et al (2005). Of course in many cases here the discussion is under neutrality, but it seems like the authors really need to engage with this literature more.

      The most interesting part of the manuscript, I think, is the discussion of the Density Dependent Haldane model (DDH). However, I feel like I did not fully understand some of the derivation presented in this section, which might be my own fault. For instance, I can't tell if Equation 5 is a result or an assumption - when I attempted a naive derivation of Equation 5, I obtained E(K_t) = 1 + r/c*(c-n)*dt. It's unclear where the parameter z comes from, for example. Similarly, is equation 6 a derivation or an assumption? Finally, I'm not 100% sure how to interpret equation 7. I that a variance effective size at time t? Is it possible to obtain something like a coalescent Ne or an expected number of segregating sites or something from this?

      Similarly, I don't understand their simulations. I expected that the authors would do individual-based simulations under a stochastic model of logistic growth, and show that you naturally get variance in offspring number that changes over time. But it seems that they simply used their equations 5 and 6 to fix those values. Moreover, I don't understand how they enforce population regulation in their simulations---is N_t random and determined by the (independent) draws from K_t for each individual? In that case, there's no "interaction" between individuals (except abstractly, since logistic growth arises from a model that assumes interactions between individuals). This seems problematic for their model, which is essentially motivated by the fact that early during logistic growth, there are basically no interactions, and later there are, which increases variance in reproduction. But their simulations assume no interactions throughout!

      The authors also attempt to show that changing variance in reproductive success occurs naturally during exponential growth using a yeast experiment. However, the authors are not counting the offspring of individual yeast during growth (which I'm sure is quite hard). Instead, they use an equation that estimates the variance in offspring number based on the observed population size, as shown in the section "Estimation of V(K) and E(K) in yeast cells". This is fairly clever, however, I am not sure it is right, because the authors neglect covariance in offspring between individuals. My attempt at this derivation assumes that I_t | I_{t-1} = \sum_{I=1}^{I_{t-1}} K_{i,t-1} where K_{i,t-1} is the number of offspring of individual i at time t-1. Then, for example, E(V(I_t | I_{t-1})) = E(V(\sum_{i=1}^{I_{t-1}} K_{i,t-1})) = E(I_{t-1})V(K_{t-1}) + E(I_{k-1}(I_{k-1}-1))*Cov(K_{i,t-1},K_{j,t-1}). The authors have the first term, but not the second, and I'm not sure the second can be neglected (in fact, I believe it's the second term that's actually important, as early on during growth there is very little covariance because resources aren't constrained, but at carrying capacity, an individual having offspring means that another individuals has to have fewer offspring - this is the whole notion of exchangeability, also neglected in this manuscript). As such, I don't believe that their analysis of the empirical data supports their claim.

      Thus, while I think there are some interesting ideas in this manuscript, I believe it has some fundamental issues: first, it fails to engage thoroughly with the literature on a very important topic that has been studied extensively. Second, I do not believe their simulations are appropriate to show what they want to show. And finally, I don't think their empirical analysis shows what they want to show.

      References:

      Möhle M. Robustness results for the coalescent. Journal of Applied Probability. 1998;35(2):438-447. doi:10.1239/jap/1032192859

      Sagitov S. Convergence to the coalescent with simultaneous multiple mergers. Journal of Applied Probability. 2003;40(4):839-854. doi:10.1239/jap/1067436085

      Der, Ricky, Charles L. Epstein, and Joshua B. Plotkin. "Generalized population models and the nature of genetic drift." Theoretical population biology 80.2 (2011): 80-99

      Sano, Akinori, Akinobu Shimizu, and Masaru Iizuka. "Coalescent process with fluctuating population size and its effective size." Theoretical population biology 65.1 (2004): 39-48

      Sjodin, P., et al. "On the meaning and existence of an effective population size." Genetics 169.2 (2005): 1061-1070

    1. D EAR D R A U P A D I, BEC O N S O L E D . Y O U RH U M IL IA T IO N SWILL B E AVENF O U R T E E NY E A R S FR O MN O W .

      Filled with anger and anguish, the Pandavas are forced to live away from the comforts that they are used to and must face the harsh realities of existence. Krishna's presence after they have been exiled and gives a sense of assurance for them and makes them feel secure as they are in new territory that they are not accustomed to. He is a symbol of hope for their people. In a way, the exile helps bring the Pandavas closer as they have a common enemy that they all hate and want to avenge creating an even strong unity among them. While the exile does not compare to the moment when Draupadi was gambled away, this marks another low point in the story as the moral is still low for the Pandavas and they know it will be many years before they can inflict any type of pain or suffering onto the Kauravas. CC BY Ajey Sasimugunthan (contact)

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      This study is convincing because they performed time-resolved X-ray crystallography under different pH conditions using active/inactive metal ions and PpoI mutants, as with the activity measurements in solution in conventional enzymatic studies. Although the reaction mechanism is simple and may be a little predictable, the strength of this study is that they were able to validate that PpoI catalyzes DNA hydrolysis through "a single divalent cation" because time-resolved X-ray study often observes transient metal ions which are important for catalysis but are not predictable in previous studies with static structures such as enzyme-substrate analog-metal ion complexes. The discussion of this study is well supported by their data. This study visualized the catalytic process and mutational effects on catalysis, providing new insight into the catalytic mechanism of I-PpoI through a single divalent cation. The authors found that His98, a candidate of proton acceptor in the previous experiments, also affects the Mg2+ binding for catalysis without the direct interaction between His98 and the Mg2+ ion, suggesting that "Without a proper proton acceptor, the metal ion may be prone for dissociation without the reaction proceeding, and thus stable Mg2+ binding was not observed in crystallo without His98". In future, this interesting feature observed in I-PpoI should be investigated by biochemical, structural, and computational analyses using other metal-ion dependent nucleases. 

      We appreciate the reviewer for the positive assessment as well as all the comments and suggestions.

      Reviewer #2 (Public Review): 

      Summary: 

      Most polymerases and nucleases use two or three divalent metal ions in their catalytic functions. The family of His-Me nucleases, however, use only one divalent metal ion, along with a conserved histidine, to catalyze DNA hydrolysis. The mechanism has been studied previously but, according to the authors, it remained unclear. By use of a time resolved X-ray crystallography, this work convincingly demonstrated that only one M2+ ion is involved in the catalysis of the His-Me I-PpoI 19 nuclease, and proposed concerted functions of the metal and the histidine. 

      Strengths: 

      This work performs mechanistic studies, including the number and roles of metal ion, pH dependence, and activation mechanism, all by structural analyses, coupled with some kinetics and mutagenesis. Overall, it is a highly rigorous work. This approach was first developed in Science (2016) for a DNA polymerase, in which Yang Cao was the first author. It has subsequently been applied to just 5 to 10 enzymes by different labs, mainly to clarify two versus three metal ion mechanisms. The present study is the first one to demonstrate a single metal ion mechanism by this approach. 

      Furthermore, on the basis of the quantitative correlation between the fraction of metal ion binding and the formation of product, as well as the pH dependence, and the data from site-specific mutants, the authors concluded that the functions of Mg2+ and His are a concerted process. A detailed mechanism is proposed in Figure 6. 

      Even though there are no major surprises in the results and conclusions, the time-resolved structural approach and the overall quality of the results represent a significant step forward for the Me-His family of nucleases. In addition, since the mechanism is unique among different classes of nucleases and polymerases, the work should be of interest to readers in DNA enzymology, or even mechanistic enzymology in general. 

      Thank you very much for your comments and suggestions.

      Weaknesses: 

      Two relatively minor issues are raised here for consideration: 

      p. 4, last para, lines 1-2: "we next visualized the entire reaction process by soaking I-PpoI crystals in buffer....". This is a little over-stated. The structures being observed are not reaction intermediates. They are mixtures of substrates and products in the enzyme-bound state. The progress of the reaction is limited by the progress of the soaking of the metal ion. Crystallography has just been used as a tool to monitor the reaction (and provide structural information about the product). It would be more accurate to say that "we next monitored the reaction progress by soaking....". 

      We appreciate the clarification regarding the description of our experimental approach. We agree that our structures do not represent reaction intermediates but rather mixtures of substrate and product states within the enzyme-bound environment. We have revised the text accordingly to more accurately reflect our methodology.

      p. 5, the beginning of the section. The authors on one hand emphasized the quantitative correlation between Mg ion density and the product density. On the other hand, they raised the uncertainty in the quantitation of Mg2+ density versus Na+ density, thus they repeated the study with Mn2+ which has distinct anomalous signals. This is a very good approach. However, there is still no metal ion density shown in the key Figure 2A. It will be clearer to show the progress of metal ion density in a figure (in addition to just plots), whether it is Mg or Mn. 

      Thank you for your insightful comments. We recognize the importance of visualizing metal ion density alongside product density data. To address this, we included in Figure S4 to present Mg2+/Mn2+ and product densities concurrently.

      Reviewer #1 (Recommendations For The Authors): 

      (1) Figure 6. I understand that pre-reaction state (left panel) and Metal-binding state (two middle panels) are in equilibrium. But can we state that the Metal-binding state (two middle panels) and the product state (right panel) are in equilibrium and connected by two arrows? 

      Thank you for your comments. We agree that the DNA hydrolysis reaction process may not be reversible within I-Ppo1 active site. To clarify, we removed the backward arrows between the metal-binding state and product state. In addition, we thank the reviewer for giving a name for the middle state and think it would be better to label the middle state. We added the metal-binding state label in the revised Figure 6 and also added “on the other hand, optimal alignment of a deprotonated water and Mg2+ within the active site, labeled as metal-binding state, leads to irreversible bond breakage (Fig. 6a)” within the text.

      (2) The section on DNA hydrolysis assay (Materials and Methods) is not well described. In this section, the authors should summarize the methods for the experiments in Figure 4 AC, Figure 5BC, Figure S3C, Figure S4EF, and Figure S6AB. The authors presented some graphs for the reactions. For clarity, the author should state in the legends which experiments the results are from (in crystallo or in solution). Please check and modify them. 

      Thank you for the suggestion. We have added four paragraphs to detail the experimental procedures for experiments in these figures. In addition, we have checked all of the figure legends and labeled them as “in crystallo or in solution.” To clarify, we also added “in crystallo” or “solution” in the corresponding panels.

      (3) The authors showed the anomalous signals of Mn2+ and Tl+. The authors should mention which wavelength of X-rays was used in the data collections to calculate the anomalous signals. 

      Thank you for the suggestion. We have included the wavelength of the X-ray in the figure legends that include anomalous maps, which were all determined at an X-ray wavelength of 0.9765 Å.

      (4) The full names of "His-Me" and "HNH" are necessary for a wide range of readers. 

      Thank you for the suggestion. We have included the full nomenclature for His-Me (histidine-metal) nucleases and HNH (histidine-asparagine-histidine) nuclease.

      (5) The authors should add the side chain of Arg61 in Figure 1E because it is mentioned in the main text. 

      Thank you for the suggestion. We have added Arg61 to Figure 1E.

      (6) Figure 5D. For clarity, the electron densities should cover the Na+ ion. The same request applies to WatN in Figure S3B.

      Thank you for catching this detail. We have added the electron density for the Na+ ion in Figure 5D and WatN in Figure S3B.

      (7) At line 269 on page 8, what is "previous H98A I-PpoI structure with Mn2+"? Is the structure 1CYQ? If so, it is a complex with Mg2+. 

      Thank you for catching this detail. We have edited the text to “previous H98A I-PpoI structure with Mg2+.”

      (8) At line 294 on page 9, "and substrate alignment or rotation in MutT (66)." I think "alignment of the substrate and nucleophilic water" is preferred rather than "substrate alignment or rotation". 

      Thank you for the suggestion. We have edited the text to “alignment of the substrate and nucleophilic water.”

      (9) At line 305 on page 9, "Second, (58, 69-71) single metal ion binding is strictly correlated with product formation in all conditions, at different pH and with different mutants (Figure 3a and Supplementary Figure 4a-c) (58)". The references should be cited in the correct positions. 

      Thank you for catching this typo. We have removed the references.

      (10) At line 347 on page 10, "Grown in a buffer that contained (50 g/L glucose, 200 g/L α-lactose, 10% glycerol) for 24 hrs." Is this sentence correct? 

      Thank you for catching this detail. We have corrected the sentence.

      (11) At line 395 on page 11, "The His98Ala I-PpoI crystals of first transferred and incubated in a pre-reaction buffer containing 0.1M MES (pH 6.0), 0.2 M NaCl, 1 mM MgCl2 or MnCl2, and 20% (w/v) PEG3350 for 30 min." In the experiments using this mutant, does a pre-reaction buffer contain MgCl2 or MnCl2? 

      Thank you for bringing this to our attention. We have performed two sets of experiments: 1) metal ion soaking in 1 mM Mn2+, which is performed similarly as WT and does not have Mn2+ in the pre-reaction buffer; 2) imidazole soaking, 1 mM Mn2+ was included in the pre-reaction buffer. We reasoned that the Mn2+ will not bind or promote reaction with His98Ala I-PpoI, but pre-incubation may help populate Mn2+ within the lattice for better imidazole binding. However, neither Mn2+ nor imidazole were observed. We have added experimental details for both experiments with His98Ala I-PpoI.

      (12) In the figure legends of Figure 1, is the Fo-Fc omit map shown in yellow not in green? Please remove (F) in the legends. 

      We have changed the Fo-Fc map to be shown in violet. We have also removed (f) from the figure legends.

      (13) I found descriptions of "MgCl". Please modify them to "MgCl2". 

      Thank you for catching these details. We have modified all “MgCl” to “MgCl2.”

      (14) References 72 and 73 are duplicated. 

      We have removed the duplicated reference.

      Reviewer #2 (Recommendations For The Authors): 

      p. 9, first paragraph, last three lines: "Thus, we suspect that the metal ion may play a crucial role in the chemistry step to stabilize the transition state and reduce the electronegative buildup of DNA, similar to the third metal ion in DNA polymerases and RNaseH." This point is significant but the statement seems a little uncertain. You are saying that the single metal plays the role of two metals in polymerase, in both the ground state and the transition state. I believe the sentence can be stronger and more explicit. 

      Thank you for raising this point. We suspect the single metal ion in I-PpoI is different from the A-site or B-site metal ion in DNA polymerases and RNaseH, but similar to the third metal ion in DNA polymerases and nucleases. As we stated in the text,

      (1) the metal ion in I-PpoI is not required for substrate alignment. The water molecule and substrate can be observed in place even in the presence of the metal ion. In contrast, the A-site or B-site metal ion in DNA polymerases and RNaseH are required for aligning the substrates.

      (2) Moreover, the appearance of the metal ion is strictly correlated with product formation, similar as the third metal ion in DNA polymerase and RNaseH.

      To emphasize our point, we have revised the sentence as

      “Thus, similar to the third metal ion in DNA polymerases and RNaseH, the metal ion in I-PpoI is not required for substrate alignment but is essential for catalysis. We suspect that the single metal ion helps stabilize the transition state and reduce the electronegative buildup of DNA, thereby promoting DNA hydrolysis.”

      Minor typos: 

      p. 2, line 4 from bottom: due to the relatively low resolution... 

      Thank you for catching this. We have edited the text to “due to the relatively low resolution.”

      Figure 4F: What is represented by the pink color? 

      The structures are color-coded as 320 s at pH 6 (violet), 160 s at pH 7 (yellow), and 20 s at pH 8 (green). We have included the color information in figure legend and make the labeling clearer in the panel.

      p. 9, first paragraph, last line: ...similar to the third... 

      Thank you for catching this. We have edited the text.

    1. Author response:

      The following is the authors’ response to the original reviews.

      Public Reviews: 

      Reviewer #1 (Public Review): 

      We thank the reviewer for the time and effort in reviewing our revised manuscript and are grateful for their constructive comments and for acknowledging the significance of our work.

      Summary: 

      Their findings elucidate the mechanisms underlying 2-AA-mediated reduction of pyruvate transport into mitochondria, which impairs the interaction between ERRα and PGC1α, consequently suppressing MPC1 expression and reducing ATP production in tolerized macrophages. While the data presented is intriguing and the paper is well-written, there are several points that warrant consideration. The authors should enhance the clarity, relevance, and impact of their study. 

      Strengths: 

      This paper presents a novel discovery regarding the mechanisms through which PA regulates the bioenergetics of tolerized macrophages. 

      Weaknesses: 

      The relevance of the in vivo model to support the conclusions is questionable. Further clarification is needed on this point. 

      We appreciate the reviewer’s comment. Our conclusion that 2-AA decreases bioenergetics while sustains bacterial burden is further supported by additional in vivo data we present now in Fig. S5. To strengthen the relevance of our in vivo data, we performed additional in vivo experiments. In this set of in vivo studies, mice received the first exposure to 2-AA by injecting 2-AA only and the 2nd exposure through infection with PA14 or ΔmvfR four days post-2-AA injection.  As shown in the supplementary Figure S5 the levels of ATP and acetyl-CoA in the spleen of infected animals and the enumeration of the bacterial counts were the similar between PA14 or ΔmvfR receiving the 1st 2-AA exposure and agree with the “one-shot infection” findings presented in Figure 5 with the PA14 or ΔmvfR+2-AA infected mice or those receiving 2-AA only. These results are consistent with our previous findings showing that 2-AA impedes the clearance of PA14 (Bandyopadhaya et al. 2012; Bandyopadhaya et al. 2016; Tzika et al. 2013) and provide compelling evidence that the metabolic alterations identified may favor PA persistence in infected tissues.

      Reviewer #2 (Public Review): 

      We thank the reviewer for the time and effort in reviewing our revised manuscript and are grateful for their constructive comments and for acknowledging the significance of our work.

      Summary: 

      The study tries to connect energy metabolism with immune tolerance during bacterial infection. The mechanism details the role of pyruvate transporter expression via ERRalpha-PGC1 axis, resulting in pro-inflammatory TNF alpha signalling responsible for acquired infection tolerance. 

      Strengths: 

      Overall, the study is an excellent addition to the role of energy metabolism during bacterial infection. The mechanism-based approach in dissecting the roles of metabolic coactivator, transcription factor, mitochondrial transporter, and pro-inflammatory cytokine during acquired tolerance towards infections indicates a detailed and well-written study. The in vivo studies in mice nicely corroborate with the cell line-based data, indicating the requirement for further studies in human infections with another bacterial model system. 

      Weaknesses:

      The authors have involved various mechanisms to justify their findings. However, they have missed out on certain aspects which connect the mechanism throughout the paper. For example, they measured ATP and acetyl COA production linked with bacterial re-exposures and added various targets like MCP1, EER alpha, PGC1 alpha, and TNF alpha. However, they skipped PGC1 alpha levels, ATP and acetyl COA in various parts of the paper. Including the details would make the work more comprehensive. 

      We appreciate the reviewer’s comments and apologize for omitting the PGC-1α levels.  Per the reviewer’s suggestion, we have added the PGC-1α transcript levels (Figure 4C) in the section describing 2-AA-mediated dysregulation of the ERRα and MPC1 transcription (lines 243-252). Moreover, we have added Figure S5, which shows additional ATP and acetyl CoA levels in vivo. In our view, ATP and acetyl-CoA levels are shown in all appropriate settings, interrogating the bioenergetics, including in the presence of bacteria and in their absence, where only 2-AA is added. Please see Figures 1 and 5 and the newly added Figure S5.

      The use of public data sets to support their claim on immune tolerance is missing. Including various data sets of similar studies will strengthen the findings independently. 

      Suppose we understand correctly the reviewer’s comment regarding public data sets on immune tolerance. In that case, we are referring to our data since there are no published data from other groups on 2-AA tolerization and because the outcome of the 2-AA effect on the bacterial burden differs from that of LPS. Therefore, this study did not consider comparing with published data from LPS.

      Reviewer #1 (Recommendations For The Authors): 

      (1) Animal model: The authors appropriately initiated the study with an in vitro tolerization model involving 2-AA re-exposure, providing foundational insights for further investigation. However, the rationale for the one-shot injection in the in vivo model lacks clarity. To strengthen the relevance of the in vivo data, the authors should consider establishing a model involving bacterial re-exposure, such as a two-challenge paradigm with antibiotic treatment in between. This approach would allow for the examination of peritoneal macrophages harvested from mice, assessing ATP levels, acetyl CoA, TNF production, and bacterial counts. Such an approach would better align the in vivo findings with the in vitro experiments, confirming the role of tolerized macrophages in controlling PA infection in the presence of 2-AA. 

      We thank the reviewer for this comment.  Indeed, we have performed a similar two-challenge paradigm study in which first exposure to 2-AA is achieved by injecting 2-AA, and 2nd exposure through infection with PA14 or ΔmvfR four days post -2-AA injection.  The results of Figure S5 can be directly compared with those in Fig 5 in vivo studies. As shown in supplementary Figure S5 the levels of ATP and acetyl-CoA in the spleen of infected animals and the enumeration of the bacterial counts agree with the “one-shot infection” presented in Fig 5 (PA14 or ΔmvfR+2-AA).  Figure S5 study although not included initially to simplify data presentation, it was performed in parallel with Fig 5 and thus they can be directly compared. 

      (2) Exogenous ATP treatment: It is crucial to explore whether 2-AA re-exposure suppresses inflammasome activation and whether this suppression can be reversed by exogenous ATP treatment. Specifically, the authors should investigate whether NLRP3 inflammasome activation is inhibited in tolerized macrophages and whether such activation is necessary for host defense. Clarifying these points would provide valuable insights into the mechanisms underlying macrophage tolerization induced by 2-AA. 

      Excellent point. We agree, indeed, this is planned in the near future.

      (3) Figures 4C and D: The authors should exercise care in describing these figures. For instance, line 263 states that "UK5099 had no effect on the PA14 burden in macrophages," which requires correction for accuracy. 

      We apologize and rephrase this sentence and other sentences referring to Fig 4D and 4E in this section. Please see the highlighted sentences in the results section referring to Fig 4. For example, “The addition of the UK5099 inhibitor strongly enhanced the bacterial intracellular burden in ΔmvfR infected macrophages compared to the non-inhibited ΔmvfR infected cells, reaching a similar burden to those infected with PA14 (Fig. 4D)”.

      (4) ERRα expression: While the study intriguingly demonstrates a decrease in ERRα levels in tolerized macrophages following exposure to 2-AA, the discussion of this finding is lacking. It is worth exploring the possibility of increasing ERRα expression to counteract the tolerization induced by 2-AA and enhance clearance of PA infection. This avenue should be thoroughly discussed in the manuscript's Discussion section, offering insights into potential therapeutic strategies to mitigate the effects of 2-AA on macrophage function. 

      Thank you so much for this additional comment.  We have now included this point in the discussion section (lines 373-376).

      Reviewer #2 (Recommendations For The Authors): 

      Overall, the study is an excellent addition to the role of energy metabolism during bacterial infection. The mechanism-based approach in dissecting the roles of metabolic coactivator, transcription factor, mitochondrial transporter, and pro-inflammatory cytokine during acquired tolerance indicates a detailed and well-written study. However, connecting the mechanisms often was not reflected in some of the experiments, and answering a few concerns/suggestions will undoubtedly improve the study's readability, appeal, and overall impact on a broader audience. 

      (1) The authors should rephrase the title if possible. The title indicates 2AA as a bacterial quorum sensing signal; however, throughout the manuscript, there are no studies associated with actual quorum sensing in bacteria. 

      Thank you for this comment. However, the title indicates 2-AA as a quorum sensing molecule because the synthesis of this signaling molecule is uniquely regulated by quorum sensing. Because of its importance in the virulence of Pseudomonas aeruginosa and its regulation by quorum sensing, we feel that it is appropriate to refer to it as such.

      (2) The authors generalised immunotolerance and memory of 2AA-exposed cells to broad-spectrum microbial exposure by just testing with LPS exposure. I would suggest they test at least 2 more heterologous microbial products known to illicit response and confirm their claim from Figure 1. 

      We appreciate the reviewer’s comment. We intend not to generalize immunotolerance and memory of 2-AA exposed cells to broad-spectrum microbial exposure. Moreover, since the manuscript is not focused on comparing other bacterial molecules to 2-AA and multiple studies have focused on LPS tolerance, we tested LPS only in the manuscript.

      (3) LPS triggers ATP production through glycolysis in nitric oxide (NO) dependent mechanisms in various immune and non-immune cells. The authors should study the concentrations of NO, Glucose, and Pyruvate levels to clarify the mechanism of energy dynamics and the source of ATP and Acetyl CoA generated/scavenged during primary and secondary exposures to both 2AA and LPS. 

      We agree that a cross-tolerization experiment using 2-AA and LPS would reveal interesting insights into immune response during PA infections.  However, this is out of the scope of this article. Please notice that the mechanism of 2-AA and LPS tolerization is mechanistically distinct, e.g. they rely on different HDAC enzymes, and LPS tolerization predominantly involves changes in H3K27 acetylation (Lauterbach et al. 2019). In contrast, 2-AA tolerization involves H3K18 modifications (Bandyopadhaya, Tsurumi, and Rahme 2017). For this reason, the complexity of such interactions would require a comprehensive set of experiments that are not part of the focus of this study.

      (4) Immunogenic triggers often rapidly alter mitochondrial membrane potential, which alters oxygen consumption rates. However, the authors tend to generalize energy homeostasis and claim the deregulation of OXPHOS-inducing quiescent phenotype depending upon OCR measurements from Figure 1D. The authors must evaluate mitochondrial health and membrane potential during first and second exposure in a time-dependent manner to strengthen their theory of mitochondrial dysfunction. The authors should also check the phenomena in vivo (mice exposed to infection) if possible. 

      Thank you for this suggestion. We now include electron microscopy images of mitochondria isolated from macrophages exposed to 2-AA. Results revealed that 2-AA alters mitochondrial morphology and cristae, supporting the mitochondrial dysfunctionality caused by 2-AA. These results are shown in Figure S4 and lines 185-188.

      (5) Since both MCP1 and MCP2 transporters are known to transport pyruvate to mitochondria, checking both MCP1 and 2 at transcript and protein levels in exposed cells will be essential. I suggest authors use MCP inhibitors or use RNA interference against MCPs to check the effect on tolerance of the cells exposed for a second time. 

      To our understanding, mitochondrial pyruvate carrier proteins, MPC1 and MPC2, form a hetero-oligomeric complex in the inner mitochondrial membrane to facilitate pyruvate import into mitochondria (McCommis and Finck 2015). We also used UK5099 an MPC carrier inhibitor for enumeration of bacterial load in macrophages in Figure 4 and observed a similar effect as 2-AA suggesting a similar mechanism of action.

      (6) The pyruvate levels of mitochondria in Figure 2A are shallow, and the authors claim statistical significance within a 1.5-fold change. The authors should cross-check the number of mitochondria they are isolating while estimating pyruvate from only mitochondrial fractions. Another point is, correlating mitochondrial pyruvate with the burst of ATP during first exposure in comparison to second exposure, one can argue that the number of mitochondria is variable between the exposures leading to a change in pyruvate amount (mitochondria number increases to compensate for the first exposure and decreases quickly to maintain homeostasis and remains quiescent during a second exposure due to activation of compensatory immune mechanism towards primary exposure). How do authors address the issue? 

      Our electron microscopic studies indicate that although after 2-AA exposure, no reduction in mitochondrial numbers is observed in macrophages, alterations in mitochondrial morphology and cristae are observed. Please also see our answer to point # 4.

      (7) The authors claim that ERR alpha regulates MCP1 transcription via activation of ERRalpha-PGC1 alpha axis and tolerization in cells to second exposure is due to impairment of the axis (Figure 3). PGC1 alpha is known to be induced during various metabolic, physiological, and immune-challenge-related stress in a tissue-dependent manner. In this context, one should expect changes in transcript and protein levels of PGC1 alpha. The authors must study PGC1 alpha levels with time-dependent exposures. LPS was shown to induce oscillations in PGC1 alpha levels in a tissue-specific manner. In experiments, authors should verify if such oscillations persist during time-dependent exposure, emphasising mitochondrial uncoupling that might get dampened during re-exposures to microbial challenges. 

      We appreciate the suggestion. We have now included PGC-1α (Figure 4C) transcript levels, which show the same profile as the transcript levels of ERRα and MPC1. Please note that PGC-1α is only one of several ERRα co-activators; therefore, the amount of ERRα protein is the most relevant assessment regarding the activation of the MPC1 transcription.

      (8) The authors claim that ERRalpha induces MCP1 through ChIP data in Figure 3. However, the physical verifications at mRNA levels and mutational/inhibitor-based experiments are missing. The authors should study the alterations of MCP1 mRNA in relation to exposures and inhibitors of ERRalpha and PGC1 alpha to strengthen their work. 

      This is an interesting approach; however, this experiment exceeds the scope of our manuscript. We will certainly consider this suggestion in our future experiments. Thank you.

      (9) Publicly available data sets with LPS exposures should be analyzed for gene sets pertaining to mitochondrial OXPHOS, metabolism, immune response, etc. This will support the authors' work and provide a global overview of transcriptome associated with immune tolerance. 

      We appreciate the reviewer’s comment. For the reasons explained in #3 point and because the bacterial burden outcome of the 2-AA effect is different from that of LPS, comparison with LPS published data was not considered in this study.  We agree that in the future, a comprehensive comparison of whole genome transcriptome studies between LPS and 2-AA may reveal important insights that may also help better understand and potentially classify the immune tolerance triggered by 2-AA.

      (10) In Figure 4, the authors study the role of MCP1 and associated pyruvate-dependent bacterial clearance during tolerization and associate them with a decrease in TNF alpha. I would suggest the addition of an ERR alpha inhibitor in these experiments. It is not clear as to why (mechanism) TNF alpha transcription was affected via pyruvate transport during bacterial exposure. I would suggest that the authors clarify the mechanism of TNF alpha activation/inactivation and its association with energy metabolism during acquired tolerance. 

      This is an excellent suggestion, given that a similar effect of ERRα on TNF-α was observed by other researchers (Chaltel-Lima et al. 2023).  Here, to clarify the mechanism of TNF alpha activation/inactivation and its association with energy metabolism, we elaborate on this aspect in the discussion section.

      Lines 388-393. The text reads:

      Previously, we reported that 2-AA tolerization induces histone deacetylation via HDAC1, reducing H3K18ac at the TNF-α promoter (Bandyopadhaya et al. 2016). The findings with acetyl-CoA reduction, the primary substrate of histone acetylation, and the TNF-α transcription  using UK5099 and ATP in 2-AA treated macrophages are in support of the bioenergetics disturbances observed in macrophages and their link to epigenetic modifications we have shown to be promoted by 2-AA (Bandyopadhaya et al. 2016)

      (11) It is surprising that authors specifically target TNF alpha as a pro-inflammatory cytokine during tolerance. Various reports of cytokines and immune modulatory factors play a vital role in immune tolerance upon bacterial exposure. I would suggest authors perform cytokine profiling or check public data sets to specify their reason for choosing TNF alpha. 

      The choice of TNF-α is based on the results obtained in our previous study  (Bandyopadhaya et al. 2016).

      Bandyopadhaya, A., M. Kesarwani, Y. A. Que, J. He, K. Padfield, R. Tompkins, and L. G. Rahme. 2012. 'The quorum sensing volatile molecule 2-amino acetophenon modulates host immune responses in a manner that promotes life with unwanted guests', PLoS pathogens, 8: e1003024.

      Bandyopadhaya, A., A. Tsurumi, D. Maura, K. L. Jeffrey, and L. G. Rahme. 2016. 'A quorum-sensing signal promotes host tolerance training through HDAC1-mediated epigenetic reprogramming', Nat Microbiol, 1: 16174.

      Bandyopadhaya, A., A. Tsurumi, and L. G. Rahme. 2017. 'NF-kappaBp50 and HDAC1 Interaction Is Implicated in the Host Tolerance to Infection Mediated by the Bacterial Quorum Sensing Signal 2-Aminoacetophenone', Front Microbiol, 8: 1211.

      Chaltel-Lima, L., F. Domínguez, L. Domínguez-Ramírez, and P. Cortes-Hernandez. 2023. 'The Role of the Estrogen-Related Receptor Alpha (ERRa) in Hypoxia and Its Implications for Cancer Metabolism', Int J Mol Sci, 24.

      Lauterbach, M. A., J. E. Hanke, M. Serefidou, M. S. J. Mangan, C. C. Kolbe, T. Hess, M. Rothe, R. Kaiser, F. Hoss, J. Gehlen, G. Engels, M. Kreutzenbeck, S. V. Schmidt, A. Christ, A. Imhof, K. Hiller, and E. Latz. 2019. 'Toll-like Receptor Signaling Rewires Macrophage Metabolism and Promotes Histone Acetylation via ATP-Citrate Lyase', Immunity, 51: 997-1011 e7.

      McCommis, K. S., and B. N. Finck. 2015. 'Mitochondrial pyruvate transport: a historical perspective and future research directions', Biochem J, 466: 443-54.

      Tzika, A. A., C. Constantinou, A. Bandyopadhaya, N. Psychogios, S. Lee, M. Mindrinos, J. A. Martyn, R. G. Tompkins, and L. G. Rahme. 2013. 'A small volatile bacterial molecule triggers mitochondrial dysfunction in murine skeletal muscle', PloS one, 8: e74528.

    1. Author response:

      The following is the response to the original reviews.

      Public Reviews:

      Reviewer #1 (Public Review):

      Nitta et al, in their manuscript titled, "Drosophila model to clarify the pathological significance of OPA1 in autosomal dominant optic atrophy." The novelty of this paper lies in its use of human (hOPA1) to try to rescue the phenotype of an OPA1 +/- Drosophilia DOA model (dOPA). The authors then use this model to investigate the differences between dominant-negative and haploinsufficient OPA1 variants. The value of this paper lies in the study of DN/HI variants rather than the establishment of the drosophila model per se as this has existed for some time and does have some significant disadvantages compared to existing models, particularly in the extra-ocular phenotype which is common with some OPA1 variants but not in humans. I judge the findings of this paper to be valuable with regards to significance and solid with regards to the strength of the evidence.

      Suggestions for improvements:

      (1) Stylistically the results section appears to have significant discussion/conclusion/inferences in section with reference to existing literature. I feel that this information would be better placed in the separate discussion section. E.g. lines 149-154.

      We appreciate the reviewer’s suggestion to relocate the discussion, conclusions, and inferences, particularly those that reference existing literature, to a separate discussion section. For lines 149–154, we placed them in the discussion section (lines 343–347) as follows. “Our established fly model is the first simple organism to allow observation of degeneration of the retinal axons. The mitochondria in the axons showed fragmentation of mitochondria. Former studies have observed mitochondrial fragmentation in S2 cells (McQuibban et al., 2006), muscle tissue (Deng et al., 2008), segmental nerves (Trevisan et al., 2018), and ommatidia (Yarosh et al., 2008) due to the LOF of dOPA1.”

      For lines 178–181, we also placed them in the discussion section (lines 347–351) as follows. “Our study presents compelling evidence that dOPA1 knockdown instigates neuronal degeneration, characterized by a sequential deterioration at the axonal terminals and extending to the cell bodies. This degenerative pattern, commencing from the distal axons and progressing proximally towards the cell soma, aligns with the paradigm of 'dying-back' neuropathy, a phenomenon extensively documented in various neurodegenerative disorders (Wang et al., 2012). ”

      For lines 213–217, 218–220, and 222–223, we also placed them in the discussion section (lines 363– 391) as follows. “To elucidate the pathophysiological implications of mutations in the OPA1 gene, we engineered and expressed several human OPA1 variants, including the 2708-2711del mutation, associated with DOA, and the I382M mutation, located in the GTPase domain and linked to DOA. We also investigated the D438V and R445H mutations in the GTPase domain and correlated with the more severe DOA plus phenotype. The 2708-2711del mutation exhibited limited detectability via HA-tag probing. Still, it was undetectable with a myc tag, likely due to a frameshift event leading to the mutation's characteristic truncated protein product, as delineated in prior studies (Zanna et al., 2008). Contrastingly, the I382M, D438V, and R445H mutations demonstrated expression levels comparable to the WT hOPA1. However, the expression of these mutants in retinal axons did not restore the dOPA1 deficiency to the same extent as the WT hOPA1, as evidenced in Figure 5E. This finding indicates a functional impairment imparted by these mutations, aligning with established understanding (Zanna et al., 2008). Notably, while the 2708-2711del and I382M mutations exhibited limited functional rescue, the D438V and R445H mutations did not show significant rescue activity. This differential rescue efficiency suggests that the former mutations, particularly the I382M, categorized as a hypomorph (Del Dotto et al., 2018), may retain partial functional capacity, indicative of a LOF effect but with residual activity. The I382M missense mutation within the GTPase domain of OPA1 has been described as a mild hypomorph or a disease modifier. Intriguingly, this mutation alone does not induce significant clinical outcomes, as evidenced by multiple studies (Schaaf et al., 2011; Bonneau et al., 2014; Bonifert et al., 2014; Carelli et al., 2015). A significant reduction in protein levels has been observed in fibroblasts originating from patients harboring the I382M mutation. However, mitochondrial volume remains unaffected, and the fusion activity of mitochondria is only minimally influenced (Kane et al., 2017; Del Dotto et al., 2018). This observation is consistent with findings reported by de la Barca et al. in Human Molecular Genetics 2020, where a targeted metabolomics approach classified I382M as a mild hypomorph. In our current study, the I382M mutation preserves more OPA1 function compared to DN mutations, as depicted in Figures 5E and F. Considering the results from our Drosophila model and previous research, we hypothesize that the I382M mutation may constitute a mild hypomorphic variant. This might explain its failure to manifest a phenotype on its own, yet its contribution to increased severity when it occurs in compound heterozygosity.

      (2) I do think further investigation as to why a reduction of mitochondria was noticed in the knockdown. There are conflicting reports on this in the literature. My own experience of this is fairly uniform mitochondrial number in WT vs OPA1 variant lines but with an increased level of mitophagy presumably reflecting a greater turnover. There are a number of ways to quantify mitochondrial load e.g. mtDNA quantification, protein quantification for tom20/hsp60 or equivalent. I feel the reliance on ICC here is not enough to draw conclusions. Furthermore, mitophagy markers could be checked at the same time either at the transcript or protein level. I feel this is important as it helps validate the drosophila model as we already have a lot of experimental data about the number and function of mitochondria in OPA+/- human/mammalian cells.

      We thank the reviewer for the insightful comments and suggestions regarding our study on the impact of mitochondrial reduction in a knockdown model. We concur with the reviewer’s observation that our initial results did not definitively demonstrate a decrease in the number of mitochondria in retinal axons. Furthermore, we measured mitochondrial quantity by conducting western blotting using antiCOXII and found no reduction in mitochondrial content with the knockdown of dOPA1 (Figure S4A and B). Consequently, we have revised our manuscript to remove the statement “suggesting a decreased number of mitochondria in retinal axons. However, whether this decrease is due to degradation resulting from a decline in mitochondrial quality or axonal transport failure remains unclear.” Instead, we have refocused our conclusion to reflect our electron microscopy findings, which indicate reduced mitochondrial size and structural abnormalities. The reviewer’s observation of consistent mitochondrial numbers in WT versus mutant variant lines and elevated mitophagy levels prompted us to evaluate mitochondrial turnover as a significant factor in our study. Regarding verifying mitophagy markers, we incorporated the mito-QC marker in our experimental design. In our experiments, mito-QC was expressed in the retinal axons of Drosophila to assess mitophagy activity upon dOPA1 knockdown. We observed a notable increase in mCherry positive but GFP negative puncta signals one week after eclosion, indicating the activation of mitophagy (Figure 2D–H). This outcome strongly suggests that dOPA1 knockdown enhances mitophagy in our Drosophila model. The application of mito-QC as a quantitative marker for mitophagy, validated in previous studies, offers a robust approach to analyzing this process. Our findings elucidate the role of dOPA1 in mitochondrial dynamics and its implications for neuronal health. These results have been incorporated into Figure 2, with the corresponding text updated as follows (lines 159–167): “Given that an increase in mitophagy activity has been reported in mouse RGCs and nematode ADOA models (Zaninello et al., 2022; Zaninello et al., 2020), the mitoQC marker, an established indicator of mitophagy activity, was expressed in the photoreceptors of Drosophila. The mito-QC reporter consists of a tandem mCherry-GFP tag that localizes to the outer membrane of mitochondria (Lee et al., 2018). This construct allows the measurement of mitophagy by detecting an increase in the red-only mCherry signal when the GFP is degraded after mitochondria are transported to lysosomes. Post dOPA1 knockdown, we observed a significant elevation in mCherry positive and GFP negative puncta signals at one week, demonstrating an activation of mitophagy as a consequence of dOPA1 knockdown (Figure 2D–H).”  

      (3) Could the authors comment on the failure of the dOPA1 rescue to return their biomarker, axonal number to control levels. In Figure 4D is there significance between the control and rescue. Presumably so as there is between the mutant and rescue and the difference looks less.

      As the reviewer correctly pointed out, there is a significant difference between the control and rescue groups, which we have now included in the figure. Additionally, we have incorporated the following comments in the discussion section (lines 329–342) regarding this significant difference: “In our study, expressing dOPA1 in the retinal axons of dOPA1 mutants resulted in significant rescue, but it did not return to control levels. There are three possible explanations for this result. The first concerns gene expression levels. The Gal4-line used for the rescue experiments may not replicate the expression levels or timing of endogenous dOPA1. Considering that the optimal functionality of dOPA1 may be contingent upon specific gene expression levels, attaining a wild-type-like state necessitates the precise regulation of these expression levels. The second is a nonautonomous issue. Although dOPA1 gene expression was induced in the retinal axons for the rescue experiments, many retinal axons were homozygous mutants, while other cell types were heterozygous for the dOPA1 mutation. If there is a non-autonomous effect of dOPA1 in cells other than retinal axons, it might not be possible to restore the wild-type-like state fully. The third potential issue is that only one isoform of dOPA1 was expressed. In mouse OPA1, to completely restore mitochondrial network shape, an appropriate balance of at least two different isoforms, lOPA1 and s-OPA1, is required (Del Dotto et al., 2017). This requirement implies that multiple isoforms of dOPA1 are essential for the dynamic activities of mitochondria.”

      (4) The authors have chosen an interesting if complicated missense variant to study, namely the I382M with several studies showing this is insufficient to cause disease in isolation and appears in high frequency on gnomAD but appears to worsen the phenotype when it appears as a compound het. I think this is worth discussing in the context of the results, particularly with regard to the ability for this variant to partially rescue the dOPA1 model as shown in Figure 5.

      As the reviewer pointed out, the I382M mutation is known to act as a disease modifier. However, in our system, as suggested by Figure 5, I382M appears to retain more activity than DN mutations. Considering previous studies, we propose that I382M represents a mild hypomorph. Consequently, while I382M alone may not exhibit a phenotype, it could exacerbate severity in a compound heterozygous state. We have incorporated this perspective in our revised discussion (lines 375-391).

      “Notably, while the 2708-2711del and I382M mutations exhibited limited functional rescue, the D438V and R445H mutations did not show significant rescue activity. This differential rescue efficiency suggests that the former mutations, particularly the I382M, categorized as a hypomorph (Del Dotto et al., 2018), may retain partial functional capacity, indicative of a LOF effect but with residual activity. The I382M missense mutation within the GTPase domain of OPA1 has been described as a mild hypomorph or a disease modifier. Intriguingly, this mutation alone does no induce significant clinical outcomes, as evidenced by multiple studies (Schaaf et al., 2011; Bonneau et al., 2014; Bonifert et al., 2014; Carelli et al., 2015). A significant reduction in protein levels has been observed in fibroblasts originating from patients harboring the I382M mutation. However, mitochondrial volume remains unaffected, and the fusion activity of mitochondria is only minimally influenced (Kane et al., 2017; Del Dotto et al., 2018). This observation is consistent with findings reported by de la Barca et al. in Human Molecular Genetics 2020, where a targeted metabolomics approach classified I382M as a mild hypomorph. In our current study, the I382M mutation preserves more OPA1 function compared to DN mutations, as depicted in Figures 5E and F. Considering the results from our Drosophila model and previous research, we hypothesize that the I382M mutation may constitute a mild hypomorphic variant. This might explain its failure to manifest a phenotype on its own, yet its contribution to increased severity when it occurs in compound heterozygosity.”

      (5) I feel the main limitation of this paper is the reliance on axonal number as a biomarker for OPA1 function and ultimately rescue. I have concerns because a) this is not a well validated biomarker within the context of OPA1 variants b) we have little understanding of how this is affected by over/under expression and c) if it is a threshold effect e.g. once OPA1 levels reach <x% pathology develops but develops normally when opa1 expression is >x%. I think this is particularly relevant when the authors are using this model to make conclusions on dominant negativity/HI with the authors proposing that if expression of a hOPA1 transcript does not increase opa1 expression in a dOPA1 KO then this means that the variant is DN. The authors have used other biomarkers in parts of this manuscript e.g. ROS measurement and mito trafficking but I feel this would benefit from something else particularly in the latter experiments demonstrated in figure 5 and 6.

      The reviewer raised concerns regarding the adequacy of axonal count as a validated biomarker in the context of OPA1 mutants. In response, we corroborated its validity using markers such as MitoSOX, Atg8, and COXII. Experiments employing MitoSOX revealed that the augmented ROS signals resulting from dOPA1 knockdown were mitigated by expressing human OPA1. Conversely, the mutant variants 2708-2711del, D438V, and R445H did not ameliorate these effects, paralleling the phenotype of axonal degeneration observed. These findings are documented in Figure 5F, and we have incorporated the following text into section lines 248–254 of the results:

      “Furthermore, we assessed the potential for rescuing ROS signals. Similar to its effect on axonal degeneration, wild-type hOPA1 effectively mitigated the phenotype, whereas the 2708-2711del, D438V, and R445H mutants did not (Figure 5F). Importantly, the I382M variant also reduced ROS levels comparably to the wild type. These findings demonstrate that both axonal degeneration and the increase in ROS caused by dOPA1 downregulation can be effectively counteracted by hOPA1. Although I382M retains partial functionality, it acts as a relatively weak hypomorph in this experimental setup.”

      Moreover, utilizing mito-QC, we observed elevated mitophagy in our Drosophila model, with these results now included in Figure 2D–H. Given the complexity of the genetics involved and the challenges in establishing lines, autophagy activity was quantified by comparing the ratio of Atg8-1 to Atg8-2 via Western blot analysis. However, no significant alterations were detected across any of the genotypes. Additionally, mitochondrial protein levels derived from COXII confirmed consistent mitochondrial quantities, showing no considerable variance following knockdown. These insights affirm that retinal axon degeneration and mitophagy activation are present in the Drosophila DOA model, although the Western blot analysis revealed no significant changes in autophagy activation. Such findings necessitate caution as this model may not fully replicate the molecular pathology of the corresponding human disease. These Western blot findings are presented in Figure S4, with the following addition made to section lines 255–263 of the results:

      “We also conducted Western blot analyses using anti-COXII and anti-Atg8a antibodies to assess changes in mitochondrial quantity and autophagy activity following the knockdown of dOPA1. Mitochondrial protein levels, indicated by COXII quantification, were evaluated to verify mitochondrial content, and the ratio of Atg8a-1 to Atg8a-2 was used to measure autophagy activation. For these experiments, Tub-Gal4 was employed to systemically knockdown dOPA1. Considering the lethality of a whole-body dOPA1 knockdown, Tub-Gal80TS was utilized to repress the knockdown until eclosion by maintaining the flies at 20°C. After eclosion, we increased the temperature to 29°C for two weeks to induce the knockdown or expression of hOPA1 variants. The results revealed no significant differences across the genotypes tested (Figure S4A–D).”

      In assessing the effects of dominant negative mutations, measurements including ROS levels, the ratio of Atg8-1 to Atg8-2, and the quantity of COXII protein were conducted, yet no significant differences were observed (Figure S6). This limitation of the fly model is mentioned in the results, noting the observation of the axonal degeneration phenotype but not alterations in ROS signaling, autophagy activity, or mitochondrial quantity as follows (line 287–290):

      “We investigated the impacts of dominant negative mutations on mitochondrial oxidation levels, mitochondrial quantity, and autophagy activation levels; however, none of these parameters showed statistical significance (Figure S6).”

      The reviewer also inquired about the effects of overexpressing and underexpressing OPA1 on axonal count and whether these effects are subject to a threshold. In response, we expressed both wild-type and variant forms of human OPA1 in Drosophila in vivo and assessed their protein levels using Western blot analysis. The results showed no significant differences in expression levels between the wild-type and variant forms in the OPA1 overexpression experiments, suggesting the absence of a variation threshold effect. These findings have been newly documented as quantitative data in Figure 5C. Furthermore, we have included a statement in the results section for Figure 6A, clarifying that overexpression of hOPA1 exhibited no discernible impact, as detailed on lines 274–276.

      “The results presented in Figure 5C indicate that there are no significant differences in the expression levels among the variants, suggesting that variations in expression levels do not influence the outcomes.”

      (6) Could the authors clarify what exons in Figure 5 are included in their transcript. My understanding is transcript NM_015560.3 contains exon 4,4b but not 5b. According to Song 2007 this transcript produces invariably s-OPA1 as it contains the exon 4b cleavage site. If this is true, this is a critical limitation in this study and in my opinion significantly undermines the likelihood of the proposed explanation of the findings presented in Figure 6. The primarily functional location of OPA1 is at the IMM and l-OPA1 is the primary opa1 isoform probably only that localizes here as the additional AA act as a IMM anchor. Given this is where GTPase likely oligomerizes the expression of s-OPA1 only is unlikely to interact anyway with native protein. I am not aware of any evidence s-OPA1 is involved in oligomerization. Therefore I don't think this method and specifically expression of a hOPA1 transcript which only makes s-OPA1 to be a reliable indicator of dominant negativity/interference with WT protein function. This could be checked by blotting UAS-hOPA1 protein with a OPA1 antibody specific to human OPA1 only and not to dOPA1. There are several available on the market and if the authors see only s-OPA1 then it confirms they are not expressing l-OPA1 with their hOPA1 construct.

      As suggested by the reviewer, we performed a Western blot using a human OPA1 antibody to determine if the expressed hOPA1 was producing the l-OPA1 isoform, as shown in band 2 of Figure 5D. The results confirmed the presence of both l-OPA1 and what appears to be s-OPA1 in bands 2 and 4, respectively. These findings are documented in the updated Figure 5D, with a detailed description provided in the manuscript at lines 224-226. Additionally, the NM_015560.3 refers to isoform 1, which includes only exons 4 and 5, excluding exons 4b and 5b. This isoform can express both l-OPA1 and s-OPA1 (refer to Figure 1 in Song et al., J Cell Biol. 2007). We have updated the schematic diagram in the figure to include these exons. The formation of s-OPA1 through cleavage occurs at the OMA1 target site located in exon 5 and the Yme1L target site in exon 5b of OPA1. Isoform 1 of OPA1 is prone to cleavage by OMA1, but a homologous gene for OMA1 does not exist in Drosophila. Although a homologous gene for Yme1L is present in Drosophila, exon 5b is missing in isoform 1 of OPA1, leaving the origin of the smaller band resembling s-OPA1 unclear at this point.

      Reviewer #2 (Public Review):

      The data presented support and extend some previously published data using Drosophila as a model to unravel the cellular and genetic basis of human Autosomal dominant optic atrophy (DOA). In human, mutations in OPA1, a mitochondrial dynamin like GTPase (amongst others), are the most common cause for DOA. By using a Drosophila loss-of-function mutations, RNAi- mediated knockdown and overexpression, the authors could recapitulate some aspects of the disease phenotype, which could be rescued by the wild-type version of the human gene. Their assays allowed them to distinguish between mutations causing human DOA, affecting the optic system and supposed to be loss-of-function mutations, and those mutations supposed to act as dominant negative, resulting in DOA plus, in which other tissues/organs are affected as well. Based on the lack of information in the Materials and Methods section and in several figure legends, it was not in all cases possible to follow the conclusions of the authors.

      We appreciate the reviewer's constructive feedback and the emphasis on enhancing clarity in our manuscript. We recognize the concerns raised about the lack of detailed information in the Materials and Methods section and several figure legends, which may have obscured our conclusions. In response, we have appended the detailed genotypes of the Drosophila strains used in each experiment to a supplementary table. Additionally, we realized that the description of 'immunohistochemistry and imaging' was too brief, previously referenced simply as “immunohistochemistry was performed as described previously (Sugie et al., 2017).” We have now expanded this section to include comprehensive methodological details. Furthermore, we have revised the figure legends to provide clearer and more thorough descriptions.

      Similarly, how the knowledge gained could help to "inform early treatment decisions in patients with mutations in hOPA1" (line 38) cannot be followed.

      To address the reviewer's comments, we have refined our explanation of the clinical relevance of our findings as follows. We believe this revision succinctly articulates the practical application of our research, directly responding to the reviewer’s concerns about linking the study's outcomes to treatment decisions for patients with hOPA1 mutations. By underscoring the model’s value in differential diagnosis and its influence on initiating treatment strategies, we have clarified this connection explicitly, within the constraints of the abstract’s word limit. The revised sentence now reads: "This fly model aids in distinguishing DOA from DOA plus and guides initial hOPA1 mutation treatment strategies."

      Reviewer #3 (Public Review):

      Nitta et al. establish a fly model of autosomal dominant optic atrophy, of which hundreds of different OPA1 mutations are the cause with wide phenotypic variance. It has long been hypothesized that missense OPA1 mutations affecting the GTPase domain, which are associated with more severe optic atrophy and extra-ophthalmic neurologic conditions such as sensorineural hearing loss (DOA plus), impart their effects through a dominant negative mechanism, but no clear direct evidence for this exists particularly in an animal model. The authors execute a well-designed study to establish their model, demonstrating a clear mitochondrial phenotype with multiple clinical analogs including optic atrophy measured as axonal degeneration. They then show that hOPA1 mitigates optic atrophy with the same efficacy as dOPA1, setting up the utility of their model to test disease-causing hOPA1 variants. Finally, they leverage this model to provide the first direct evidence for a dominant negative mechanism for 2 mutations causing DOA plus by expressing these variants in the background of a full hOPA1 complement.

      Strengths of the paper include well-motivated objectives and hypotheses, overall solid design and execution, and a generally clear and thorough interpretation of their results. The results technically support their primary conclusions with caveats. The first is that both dOPA1 and hOPA1 fail to fully restore optic axonal integrity, yet the authors fail to acknowledge that this only constitutes a partial rescue, nor do they discuss how this fact might influence our interpretation of their subsequent results.

      As the reviewer rightly points out, neither dOPA1 nor hOPA1 achieve a complete recovery. Therefore, we acknowledge that this represents only a partial rescue and have added the following explanations regarding this partial rescue in the results and discussion sections.

      Result:

      Significantly —> partially (lines 207 and 228) Discussion (lines 329–342):

      In our study, expressing dOPA1 in the retinal axons of dOPA1 mutants resulted in significant rescue, but it did not return to control levels. There are three possible explanations for this result. The first concerns gene expression levels. The Gal4-line used for the rescue experiments may not replicate the expression levels or timing of endogenous dOPA1. Considering that the optimal functionality of dOPA1 may be contingent upon specific gene expression levels, attaining a wild-type-like state necessitates the precise regulation of these expression levels. The second is a non-autonomous issue. Although dOPA1 gene expression was induced in the retinal axons for the rescue experiments, many retinal axons were homozygous mutants, while other cell types were heterozygous for the dOPA1 mutation. If there is a non-autonomous effect of dOPA1 in cells other than retinal axons, it might not be possible to restore the wild-type-like state fully. The third potential issue is that only one isoform of dOPA1 was expressed. In mouse OPA1, to completely restore mitochondrial network shape, an appropriate balance of at least two different isoforms, l-OPA1 and s-OPA1, is required (Del Dotto et al., 2017). This requirement implies that multiple isoforms of dOPA1 are essential for the dynamic activities of mitochondria.

      The second caveat is that their effect sizes are small. Statistically, the results indeed support a dominant negative effect of DOA plus-associated variants, yet the data show a marginal impact on axonal degeneration for these variants. The authors might have considered exploring the impact of these variants on other mitochondrial outcome measures they established earlier on. They might also consider providing some functional context for this marginal difference in axonal optic nerve degeneration.

      In response to the reviewer’s comment regarding the modest effect sizes observed, we acknowledge that the magnitude of the reported changes is indeed small. To explore the impact of these variants on additional mitochondrial outcomes as suggested, we employed markers such as MitoSOX, Atg8, and COXII for validation. However, we could not detect any significant effects of the DOA plus-associated variants using these methods. We apologize for the redundancy, but to address Reviewer #1's fifth question, we present experimental results showing that while the increased ROS signals observed upon dOPA1 knockdown were rescued by expressing human OPA1, the mutant variants 2708-2711del, D438V, and R445H did not ameliorate this effect. This outcome mirrors the axonal degeneration phenotype and is documented in Figure 5F. The following text has been added to the results section lines 248–254:

      “Furthermore, we assessed the potential for rescuing ROS signals. Similar to its effect on axonal degeneration, wild-type hOPA1 effectively mitigated the phenotype, whereas the 2708-2711del, D438V, and R445H mutants did not (Figure 5F). Importantly, the I382M variant also reduced ROS levels comparably to the wild type. These findings demonstrate that both axonal degeneration and the increase in ROS caused by dOPA1 downregulation can be effectively counteracted by hOPA1. Although I382M retains partial functionality, it acts as a relatively weak hypomorph in this experimental setup.”

      Moreover, utilizing mito-QC, we observed elevated mitophagy in our Drosophila model, with these results now included in Figure 2D–H. Given the complexity of the genetics involved and the challenges in establishing lines, autophagy activity was quantified by comparing the ratio of Atg8-1 to Atg8-2 via Western blot analysis. However, no significant alterations were detected across any of the genotypes. Additionally, mitochondrial protein levels derived from COXII confirmed consistent mitochondrial quantities, showing no considerable variance following knockdown. These insights affirm that retinal axon degeneration and mitophagy activation are present in the Drosophila DOA model, although the Western blot analysis revealed no significant changes in autophagy activation. Such findings necessitate caution as this model may not fully replicate the molecular pathology of the corresponding human disease. These Western blot findings are presented in Figure S4, with the following addition made to section lines 255–263 of the results:

      “We also conducted Western blot analyses using anti-COXII and anti-Atg8a antibodies to assess changes in mitochondrial quantity and autophagy activity following the knockdown of dOPA1. Mitochondrial protein levels, indicated by COXII quantification, were evaluated to verify mitochondrial content, and the ratio of Atg8a-1 to Atg8a-2 was used to measure autophagy activation. For these experiments, Tub-Gal4 was employed to systemically knockdown dOPA1. Considering the lethality of a whole-body dOPA1 knockdown, Tub-Gal80TS was utilized to repress the knockdown until eclosion by maintaining the flies at 20°C. After eclosion, we increased the temperature to 29°C for two weeks to induce the knockdown or expression of hOPA1 variants. The results revealed no significant differences across the genotypes tested (Figure S4A–D).”

      In assessing the effects of dominant negative mutations, measurements including ROS levels, the ratio of Atg8-1 to Atg8-2, and the quantity of COXII protein were conducted, yet no significant differences were observed (Figure S6). This limitation of the fly model is mentioned in the results, noting the observation of the axonal degeneration phenotype but not alterations in ROS signaling, autophagy activity, or mitochondrial quantity as follows (line 287–290):

      “We investigated the impacts of dominant negative mutations on mitochondrial oxidation levels, mitochondrial quantity, and autophagy activation levels; however, none of these parameters showed statistical significance (Figure S6).”

      Despite these caveats, the authors provide the first animal model of DOA that also allows for rapid assessment and mechanistic testing of suspected OPA1 variants. The impact of this work in providing the first direct evidence of a dominant negative mechanism is under-stated considering how important this question is in development of genetic treatments for DOA. The authors discuss important points regarding the potential utility of this model in clinical science. Comments on the potential use of this model to investigate variants of unknown significance in clinical diagnosis requires further discussion of whether there is indeed precedent for this in other genetic conditions (since the model is nevertheless so evolutionarily removed from humans).

      As suggested by the reviewer, we have expanded the discussion in our study to emphasize in greater detail the significance of the fruit fly model and the MeDUsA software we have developed, elaborating on the model's potential applications in clinical science and its precedents in other genetic disorders. Our text is as follows (lines 299–318):

      “We have previously utilized MeDUsA to quantify axonal degeneration, applying this methodology extensively to various neurological disorders. The robust adaptability of this experimental system is demonstrated by its application in exploring a wide spectrum of genetic mutations associated with neurological conditions, highlighting its broad utility in neurogenetic research. We identified a novel de novo variant in Spliceosome Associated Factor 1, Recruiter of U4/U6.U5 Tri-SnRNP (SART1). The patient, born at 37 weeks with a birth weight of 2934g, exhibited significant developmental delays, including an inability to support head movement at 7 months, reliance on tube feeding, unresponsiveness to visual stimuli, and development of infantile spasms with hypsarrhythmia, as evidenced by EEG findings. Profound hearing loss and brain atrophy were confirmed through MRI imaging. To assess the functional impact of this novel human gene variant, we engineered transgenic Drosophila lines expressing both wild type and mutant SART1 under the control of a UAS promoter.

      Our MeDUsA analysis suggested that the variant may confer a gain-of-toxic-function (Nitta et al.,  2023). Moreover, we identified heterozygous loss-of-function mutations in DHX9 as potentially causative for a newly characterized neurodevelopmental disorder. We further investigated the pathogenic potential of a novel heterozygous de novo missense mutation in DHX9 in a patient presenting with short stature, intellectual disability, and myocardial compaction. Our findings indicated a loss of function in the G414R and R1052Q variants of DHX9 (Yamada et al., 2023). This experimental framework has been instrumental in elucidating the impact of gene mutations, enhancing our ability to diagnose how novel variants influence gene function.”

      Recommendations for the Authors:

      Reviewer #1 (Recommendations For The Authors):

      Overall I enjoyed reading this paper. It is well presented and represents a significant amount of well executed study. I feel it further characterizes a poorly understood model of OPA1 variants and one which displays significant differences with the human phenotype. However I feel the use of this model with the author's experiments are not enough to validate this model/experiment as a screening tool for dominant negativity. I have therefore suggested the above experiments as a way to both further validate the mitochondrial dysfunction in this model and to ensure that the expressed transcript is able affect oligomerization as this is a pre-requisite to the authors conclusions.

      We assessed the extent to which our model reflects mitochondrial dysfunction using COXII, Atg8, and MitoSOX markers. Unfortunately, neither COXII levels nor the ratio of Atg8a-1 to Atg8a-2 showed significant variations across genotypes that would clarify the impact of dominant negative mutations. Nonetheless, MitoSOX and mito-QC results revealed that mitochondrial ROS levels and mitophagy are increased in Drosophila following intrinsic knockdown of dOPA1. These findings are documented in Figures 2, 5, and S6.

      Regarding oligomer formation, the specifics remain elusive in this study. However, the expression of dOPA1K273A, identified as a dominant negative variant in Drosophila, significantly disrupted retinal axon organization, as detailed in Figure S7. From these observations, we hypothesize that oligomerization of wild-type and dominant negative forms in Drosophila results in axonal degeneration. Conversely, co-expression of Drosophila wild-type with human dominant negative forms does not induce degeneration, suggesting that they likely do not interact.

      Reviewer #2 (Recommendations For The Authors):

      Materials and Methods:

      The authors used GMR-Gal4 to express OPA1-RNAi. I) GMR is expressed in most cells in the developing eye behind the morphogenetic furrow. So the defects observed can be due to knock- down in support cells rather than in photoreceptor cells.

      We have added the following sentences in the result (lines 194–196)."The GMR-Gal4 driver does not exclusively target Gal4 expression to photoreceptor cells. Consequently, the observed retinal axonal degeneration could potentially be secondary to abnormalities in support cells external to the photoreceptors.”

      OPA1-RNAi: how complete is the knock-down? Have the authors tested more than one RNAi line?

      We conducted experiments with an additional RNAi line, and similarly observed degeneration in the retinal axons (Figure S2 A and B; lines 178–179).

      The loss-of-function allele, induced by a P-element insertion, gives several eye phenotypes when heterozygous (Yarosh et al., 2008). Does RNAi expression lead to the same phenotypes?

      A previous report indicated that the compound eyes of homozygous mutations of dOPA1 displayed a glossy eye phenotype (Yarosh et al., 2008). Upon knocking down dOPA1 using the GMR-Gal4 driver, we also observed a glossy eye-like rough eye phenotype in the compound eyes. These findings have been added to Figure S3 and lines 192–194.

      There is no description on the way the somatic clones were generated. How were mutant cells in clones distinguished from wild-type cells (e. g. in Fig. 4).

      In the Methods section, we described the procedure for generating clones and their genotypes as follows (lines 502–505): "The dOPA1 clone analysis was performed by inducing flippase expression in the eyes using either ey-Gal4 with UAS-flp or ey3.5-flp, followed by recombination at the chromosomal location FRT42D to generate a mosaic of cells homozygous for dOPA1s3475." Furthermore, we have created a table detailing these genotypes. In these experiments, it was not possible to differentiate between the clone and WT cells. Accordingly, we have noted in the Results section (lines 201–203): "Note that the mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them.”

      Why were flies kept at 29{degree sign}C? this is rather unusual.

      Increased temperature was demonstrated to induce elevated expression of GAL4 (Kramer and Staveley, Genet. Mol. Res., 2003), which in turn led to an enhanced expression of the target genes. Therefore, experiments involving knockdown assays or Western blotting to detect human OPA1 protein were exclusively conducted at 29°C. However, all other experiments were performed at 25°C, as described in the methods sections: “Flies were maintained at 25°C on standard fly food. For knockdown experiments (Figures 1C–E, 1F–H, 2A–H, 3B–K, 5F, S1, S2 A and B, and S6A), flies were kept at 29°C in darkness.” Furthermore, “We regulated protein expression temporally across the whole body using the Tub-Gal4 and Tub-GAL80TS system. Flies harboring each hOPA1 variant were maintained at a permissive temperature of 20°C, and upon emergence, females were transferred to a restrictive temperature of 29°C for subsequent experiments.”

      Legends:

      It would be helpful to have a description of the genotypes of the flies used in the different experiments. This could also be included as a table.

      We have created a table detailing the genotypes. Additionally, in the legend, we have included a note to consult the supplementary table for genotypes.

      Results:

      Line 141: It is not clear what they mean by "degradation", is it axonal degeneration? And if so, what is the argument for this here?

      In the manuscript, we addressed the potential for mitochondrial degradation; however, recognizing that the expression was ambiguous, the following sentence has been omitted: "Nevertheless, the degradation resulting from mitochondrial fragmentation may have decreased the mitochondrial signal.”

      Fig. 2: Axons of which photoreceptors are shown?

      We have added "a set of the R7/8 retinal axons" to the legend of Figure 2.

      Line 167: The authors write that axonal degeneration is more severe after seven days than after eclosion. Is this effect light-dependent? The same question concerns the disappearance of the rhabdomere (Fig. 3G–J).

      We conducted the experiments in darkness, ensuring that the observed degeneration is not light- dependent. This condition has been added to the methods section to clarify the experimental conditions.

      Line 178/179: Based on what results do they conclude that there is degeneration of the "terminals" of the axons?

      Quantification via MeDUsA has enabled us to count the number of axonal terminals, and a noted decrease has led us to conclude axonal terminal degeneration. We have published two papers on these findings. We have added the following description to the results section to clarify how we defined degeneration (lines 174–176): "We have assessed the extent of their reduction from the total axonal terminal count, thereby determining the degree of axonal terminal degeneration (Richard JNS 2022; Nitta HMG 2023).

      Line 189: They write: ".. we observed dOPA1 mutant axons...". How did they distinguish es mutant from the controls?

      Fig. 5 and Fig. 6: How did they distinguish genetically mutant cells from genetically control cells in the somatic clones?

      Mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them. Accordingly, this point has been added to lines 201–203, “Note that the mutant clone analysis was conducted in a context where mutant and heterozygous cells coexist as a mosaic, and it was not possible to distinguish between them.” and the text in the results section has been modified as follows:

      (Before “To determine if dOPA1 is responsible for axon neurodegeneration, we observed the dOPA1 mutant axons by expressing full- length versions of dOPA1 in the photoreceptors at one day after eclosion and found that dOPA1 expression significantly rescued the axonal degeneration” —>

      (After “To determine if dOPA1 is responsible for axon neurodegeneration, we quantify the number of the axons in the dOPA1 eye clone fly with the expression of dOPA1 at one day after eclosion and found that dOPA1 expression partially rescued the axonal degeneration”

      Line 225/226: It is not clear to me how their approach "can quantitatively measure the degree of LOF".

      To address the reviewer's question and clarify how our approach quantitatively measures the degree of loss of function (LOF), we revised the statement (lines 238–247):

      "Our methodology distinctively facilitates the quantitative evaluation of LOF severity by comparing the rescue capabilities of various mutations. Notably, the 2708-2711del and I382M mutations demonstrated only partial rescue, indicative of a hypomorphic effect with residual activity. In contrast, the D438V and R445H mutations failed to show significant rescue, suggesting a more profound LOF. The correlation between the partial rescue by the 2708-2711del and I382M mutations and their classification as hypomorphic is significant. Moreover, the observed differences in rescue efficacy correspond to the clinical severities associated with these mutations, namely in DOA and DOA plus disorders. Thus, our results substantiate the model’s ability to quantitatively discriminate among mutations based on their impact on protein functionality, providing an insightful measure of LOF magnitude.”

      Discussion:

      Line 251, 252 and line 358: What is "the optic nerve" in the adult Drosophila?

      In humans, the axons of retinal ganglion cells (RGCs) are referred to as the optic nerve, and we posit that the retinal axons in flies are similar to this structure. In the introduction section, where it is described that the visual systems of flies and humans bear resemblance, we have appended the following definition (lines 107–108): “In this study, we defined the retinal axons of Drosophila as analogous to the human optic nerve.”

      Line 344: These bands appear only upon overexpression of the hOPA1 constructs, so this part of the is very speculative.

      Confirmation was achieved using anti-hOPA1, demonstrating that myc is not nonspecific. These results have been added to Figure 5D. Furthermore, the phrase “The upper band was expected as” has been revised to “From a size perspective, the upper band was inferred to represent the full-length hOPA1 including the mitochondria import sequence (MIS).” (lines 464–465)

      I was missing a discussion about the increase of ROS upon loss/reduction of dOPA1 observed by others and described here. Is there an increase of ROS upon expression of any of the constructs used?

      We demonstrated that not only axonal degeneration but also ROS can be suppressed by expressing human OPA1 in the genetic background of dOPA1 knockdown. Additionally, rescue was not possible with any variants except for I382M. Furthermore, we assessed whether there were changes in ROS in the evaluation of dominant negatives, but no significant differences were observed in this experimental system. These findings have been added to the discussion section as follows (lines 318–328). “Our research established that dOPA1 knockdown precipitates axonal degeneration and elevates ROS signals in retinal axons. Expression of human OPA1 within this context effectively mitigated both phenomena; it partially reversed axonal degeneration and nearly completely normalized ROS levels. These results imply that factors other than increased ROS may drive the axonal degeneration observed post-knockdown. Furthermore, while differences between the impacts of DN mutations and loss-of- function mutations were evident in axonal degeneration, they were less apparent when using ROS as a biomarker. The extensive use of transgenes in our experiments might have mitigated the knockdown effects. In a systemic dOPA1 knockdown, assessments of mitochondrial quantity and autophagy activity revealed no significant changes, suggesting that the cellular consequences of reduced OPA1 expression might vary across different cell types.”

      Reviewer #3 (Recommendations For The Authors):

      Consider being more explicit regarding literature that has or has failed to test a direct dominant negative effect by expressing a variant in question in the background of a full OPA1 complement. My understanding is that this is the first direct evidence of this widely held hypothesis. This lends to the main claim promoting the utility of fly as a model in general. The authors might also outline this in the introduction as a knowledge gap they fill through this study.

      In the introduction, we have incorporated a passage that highlights precedents capable of distinguishing between LOF and DN effects, and we note the absence of models capable of dissecting these distinctions within an in vivo organism. This study aims to address this gap, proposing a model that elucidates the differential impacts of LOF and DN within the context of a living model organism, thereby contributing to a deeper understanding of their roles in disease pathology. We added the following sentences in the introduction (lines 71–80).

      “In the quest to differentiate between LOF and DN effects within the context of genetic mutations, precedents exist in simpler systems such as yeast and human fibroblasts. These models have provided valuable insights into the conserved functions of OPA1 across species, as evidenced by studies in yeast models (Del Dotto et al., 2018) and fibroblasts derived from patients harboring OPA1 mutations (Kane et al., 2017). However, the ability to distinguish between LOF and DN effects in an in vivo model organism, particularly at the structural level of retinal axon degeneration, has remained elusive. This gap underscores the necessity for a more complex model that not only facilitates molecular analysis but also enables the examination of structural changes in axons and mitochondria, akin to those observed in the actual disease state.”

      The authors should clarify the language used in the abstract and introduction on the effect of hOPA1 DOA and DOA plus on the dOPA1- phenotype. Currently written as "none of the previously reports mutations known to cause DOA or DOA plus were rescued, their functions seems to be impaired." but presumably the authors mean that these variants failed to rescue to the dOPA1 deficient phenotype.

      We thank the reviewer for the constructive feedback. We acknowledge the need for clarity in our description of the effects of hOPA1 DOA and DOA plus mutations on the dOPA1- phenotype in both the abstract and the introduction. The current phrasing, "none of the previously reported mutations known to cause DOA or DOA plus were rescued, their functions seem to be impaired," may indeed be confusing. To address your concern, we have revised this statement to more accurately reflect our findings: "Previously reported mutations failed to rescue the dOPA1 deficiency phenotype." For Abstract site, we have changed as following. "we could not rescue any previously reported mutations known to cause either DOA or DOA plus.”→ “mutations previously identified did not ameliorate the dOPA1 deficiency phenotype.”

      DOA plus is associated with a multiple sclerosis-like illness; as written it suggests that the pathogenesis of sporadic multiple sclerosis and that associated with DOA plus share and underlying pathogenic mechanism. Please use the qualifier "-like illness." 

      We have added the term “multiple sclerosis-like illness” wherever “multiple sclerosis” is mentioned.

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC- 2024-02497

      Corresponding author(s): Tourriere, Hélene and Maraver, Antonio

      1. General Statements [optional]

      We sincerely thank the Editors and Reviewers for the time devoted to our manuscript. We found their critiques interesting and very helpful. After careful examination and thanks to a large collaborative effort, we will be able to answer to all the reviewers’ comments by adding significantly new experimental data.

      We are also encouraged by the positive comments of the Reviewers:

      “This manuscript will likely engage oncologists who investigate the chemotherapy-resistant mechanisms of platinum compounds in NSCLC treatment” (Reviewer 1);

      “Overall, the authors have conducted experiments that sufficiently elucidate their claims, and the description of the experiments is detailed.”; and “Overall, this work unveils a novel mechanism for Notch activation in response to platinum chemotherapy, providing a renewed outlook on overcoming chemotherapy resistance in NSCLC” (Reviewer 2).

      We are also aware that both reviewers agreed that there is room for improvement, and we are sure that upon accomplishment of all proposed experiments both reviewers will be fully satisfied.

      Please bear in mind that although it was known that platinum-based chemotherapy induced the Notch pathway in lung cancer cells, the underlying molecular mechanism was largely unknown. Thanks to the molecular dissection we performed in our study, we propose an innovative treatment for patients with lung cancer, the main cause of death by cancer in the world. Hence, we agree with both reviewers that our study will be appealing for a large number of cancer researchers, and we feel it will be also the case for those interested in DNA damage, Notch and MDM2 pathways.

      2. Description of the planned revisions

      Reviewer #1 (Evidence, reproducibility and clarity (Required)):

      Summary: This manuscript from Maraver and co-authors investigates the putative resistance mechanisms that hinder the efficacy of platinum-based therapies (e.g., carboplatin) against non-small cell lung carcinoma (NSCLC). Using in vitro lung cancer cell lines, shRNA-based knockdown, and exogenous overexpression systems, the research describes a DNA damage-induced resistance mechanism involving the NOTCH signaling pathway and the E3 ligase MDM2. The authors show that carboplatin treatment induces DNA damage and promotes ATM activation, which in turn activates the NOTCH signaling pathway via ubiquitination and stabilization of the Notch Intracellular Domain (NICD). New findings include the MDM2-mediated ubiquitination and stabilization of NICD. Using in vivo NSCLC-PDX models, they demonstrate that combining carboplatin with Notch and MDM2 inhibitors can enhance tumor killing, suggesting that targeting the MDM2/NICD axis in conjunction with carboplatin may be a viable therapeutic alternative. Furthermore, they show that NICD and MDM2 levels are elevated among tumor samples from chemo-resistant patients. Consistent with these findings, high MDM2 levels correlate with poor progression-free survival (PFS) in NSCLC patients.

      [Authors] We thank this reviewer for her/his fair summary of our work that highlights our new findings.

      Major comments:

      Some of the key conclusions may not be convincing.

      [Authors] We understand the concerns that reviewer might have and we are sure that upon accomplishment of all experiments detailed below, she/he will be convinced that the manuscript will be ready for publication.

      1. One significant weakness of the manuscript is the lack of exploration into the underlying mechanism of how MDM2 mediates the stabilization of NICD. While the observation of MDM2-mediated NICD stabilization is intriguing, it is important to provide a more convincing explanation for the reviewers. This could be achieved by offering a detailed molecular mechanism, especially considering that MDM2 typically targets proteins for degradation.

      [Authors] After reading this reviewer’s comment, we realize we did a poor job discussing better the previous study demonstrating that MDM2 induced ubiquitination on NICD but not for degradative purposes (Pettersson et al., 2013). In particular, they performed it using a mutated form of ubiquitin in lysine 48, i.e., the K48R mutant. Like this, the authors of this seminal study demonstrated that MDM2 was still able to induce ubiquitination in NICD, and hence it was not degradative.

      Still, and to confirm that this is the case also upon DNA damage, we will perform experiments using same K48R mutant to formally prove that MDM2 upon DNA damage does not ubiquitinate NICD via lysine 48-linked polymers, and hence it is not degradative. Even more, upon discussion with Laetitia Linares, author of our study and long-lasting expert in ubiquitination (for instance see (Riscal et al., 2016) and (Arena et al., 2018)), we will use another ubiquitin mutant in lysine 63. This different type of ubiquitination does not mark proteins for degradation but promote an association of the targeted protein with DNA helping for DNA repair (Liu et al., 2018). Using a ubiquitin mutated in this lysine, i.e., K63R, this type of ubiquitination cannot occur. Taking into account that we observe NICD increase ubiquitination upon DNA damage, the use of K63R will be very informative.

      Hence, we will repeat experiments of current Figure 3A with the same WT ubiquitin as before, and now also with K48R and K63R mutants. Even more, we will also include mutant forms of ubiquitin which can only form ubiquitin chains on lysine 48 (K48 only) or lysine 63 (K63 only) and we anticipate that in the presence of K48 only mutant, NICD will not be ubiquitinated upon DNA damage, while the use of K63 only mutant will be very useful. All these data will be part of the new Figure 3A.

      Of note, Dr Linares has all tools required to perform these experiments and hence we will start them soon.

      Another weakness lies in the unclear role and the underlying mechanism of ATM in the MDM2-mediated NICD stabilization. While the data presented (Fig. 3B, 3C) suggest that carboplatin could elevate MDM2 levels for NICD stabilization, a more precise method to induce MDM2 overexpression specifically for targeting NICD is required. It appears that ATM plays a crucial role in this regulatory process. The following questions must be addressed: Does ATM induce the phosphorylation of MDM2 for its protein stabilization and/or E3 ligase activity?

      [Authors] There are several points here.

      For the first one, the use of a more precise method to induce MDM2 overexpression, it is exactly what we did in Figure 4A, i.e., ectopic expression of MDM2 to demonstrate that MDM2 is sufficient to increase NICD levels.

      For the second one, i.e., the phosphorylation status of MDM2 by ATM in our system, we will perform different experiments. There are up to six proposed residues in MDM2 to be phosphorylated by ATM upon DNA damage: S386, S395, S407, T419, S425, and S429 (Cheng et al., 2011). Among all of them, S395 is the most well-known and again Dr Linares has interesting tools we will use to answer to this specific reviewer’s point. We will use an MDM2 mutant harboring an aspartate instead of the serine in this position, i.e., S395D, that mimics the serine 395 phosphorylation induced by ATM upon DNA damage. We will use this mutant together with the WT and 464A MDM2 proteins already used, and if this residue is important in our phenotype, total levels of NICD will be even higher and/or localize more in the nuclei when compared with WT MDM2. All these new data will appear as the new Figure 4A __and new Figure 4B__.

      Furthermore, we will also use an antibody that recognizes this phosphorylation site by WB after carboplatin treatment and it will be part of the new Figure 3B.

      Finally, we will also express WT MDM2 and purify it by immunoprecipitation in different experimental conditions: steady state, upon carboplatin treatment and also in combination of carboplatin and ATM inhibitor, to perform phospho-proteomics analysis upon all these conditions. Of note, and to show the feasibility of this approach, the proteomic platform at Biocampus in Montpellier has experience using this technique (Kassouf et al., 2019).

      The combination therapy of carboplatin with MDM2 and NICD inhibitors may lack compelling rationale (see below).

      [Authors] This is a very important point but we discuss it below, where more information is provided by the reviewer. Still, we anticipate we will perform a new in vivo experiment to answer to this point.

      In lines 275-276, the authors stated that their preclinical data establish the enhancement of carboplatin's therapeutic effect in NSCLC in vivo through MDM2-NICD axis inhibition. However, it's important to note that this finding remains preliminary at this stage.

      [Authors] We consider that our statement is not exaggerated, but we will tone down the message as proposed by the reviewer in the next submission.

      Minor comments:

      1. The observed loss of NICD during ATMi + carboplatin treatment in Figures 2A and 2B raises the question of whether ATM regulates the gene transcription of NOTCH. In addition to the CHX assay conducted in Figures 2C and 2D, quantifying NOTCH mRNA upon ATM inhibition could provide further insights. Alternatively, referencing relevant studies on this topic may strengthen the discussion.

      [Authors] This is an interesting experiment and we will perform it.

      In Figures 4A and 4B, the noticeable discrepancy between the exogenous expression of wild-type (WT) MDM2 and catalytically inactive MDM2-464A raises concerns. It is essential to consider if the reduced ubiquitination and stability of NICD might be attributed to varying levels of MDM2-464A in the cells rather than its catalytic inactivity. While p53 ubiquitination was utilized as a control, ensuring comparable levels of MDM2 and MDM2-464A expression could enhance the experimental rigor. Compared to the smear poly-ubiquitination bands observed for MDM2 in Figure 4B, the ubiquitination of NICD appears simpler. What distinguishes the feature of MDM2-mediated NICD ubiquitination? Could it potentially involve mono-ubiquitination?

      [Authors] The point of the reviewer is well taken, and importantly, as mentioned above in main point 2, we will repeat these experiments and will appear as new Figure 4A and new Figure 4B.

      Regarding the type of ubiquitination, as explained in detail in major point 1 to same reviewer, we will fully characterize the type of ubiquitination on NICD induced by DNA damage, and we will confirm that MDM2 is required for this specific ubiquitination in future new Figure 4C where we will overexpress the required ubiquitin forms and WT MDM2.

      In Figure 5A, the authors need to consider conducting additional NOTCH-associated factors to definitively demonstrate the activation of NOTCH signaling beyond HES1. Alternatively, in Figure 5B, the NICD Western blot could be complemented by detecting HES1 or other NOTCH-associated factors.

      [Authors] To answer to this particular point, we will test for other downstream targets of Notch as NRARP and it will appear as part of new Figure 5C.

      In Figures 5C and 5D, crucial control groups are missing, specifically mice treated solely with SP141+DBZ, carboplatin+SP141, and SP141+DBZ. It is essential to include these groups to demonstrate that the enhanced tumor killing results from the combination of carboplatin with SP141 and/or DBZ, rather than from SP141 and DBZ alone. Furthermore, in addition to the currently used NSCLC-PDX model harboring the p53 (P151R) mutation, it would be informative to include a NSCLC-PDX model expressing WT p53.

      [Authors] This is a crucial point in this rebuttal as mentioned before in major point 3 and we detail it in here.

      We did only 3 groups because preliminary data indicated that SP141 in combination with carboplatin was not showing any benefit compared to carboplatin alone while upon combination of carboplatin with Notch inhibition there was only a slight increase in therapeutic carboplatin benefit but otherwise not very potent, and for simplicity we preferred to don’t show these data. But, after reading this point from Reviewer 1, even if we will propose later only the triple combination for patients, we clearly need to demonstrate that the other combinations are not potent enough or not at all.

      The reviewer asked to include: “SP141+DBZ, carboplatin+SP141, and SP141+DBZ”. We imagine that she/he meant: SP141+DBZ, carboplatin+SP141, and carboplatin +DBZ, that together with the vehicle, carboplatin and carboplatin+SP141+DBZ makes 6 groups of treatments. Putting together the 8 mice devoted for tumor growth and survival, plus 4 mice for the acute treatment for IHC and WB purposes (for current Figures 5A and 5B) makes a total of 72, that is a substantial number of mice. Of note, since we performed the in vivo experiment presented in the current manuscript, a new Notch inhibitor called nirogacestat, appear in the market being the first in class Notch inhibitor to treat solid cancer patients (desmoid tumors) after demonstrating a significant therapeutic effect in clinical trials (Gounder et al., 2023).

      Hence, we will take advantage of the repetition of this experiment to substitute this new molecule instead of DBZ, that is an interesting molecule for preclinical research, but without any clinical relevance. Therefore, the use of nirogacestat will further increase the medical impact of our data. Importantly, nirogacestat is better tolerated than DBZ, meaning that mice can be treated for longer periods of time and we propose in here to treat up to 12 weeks. Finally, after discussion with Quentin Thomas, author of the manuscript and clinical researcher in the lab, we will provide 4 carboplatin cycles as it is proposed today to NSCLC patients in an attempt of getting closer to the clinical setting. In particular we will provide carboplatin to mice on weeks 1, 4, 7 and 10, while treating with MDM2 inhibitor (SP141) and Notch inhibitor (nirogacestat) from Monday to Friday for the 12 weeks.

      This experiment will be long and will require an important use of resources both human and financial, but we are sure that the effect in tumor growth and survival will be more dramatic than the one presented now.

      On the contrary and as explained in the 4th subheading part of this “revision plan”, including another 72 mice to treat a p53 proficient NSCLC PDX, when we already demonstrated in vitro that p53 is not required for the phenotype described in this study, for us it is totally unfeasible by ethical reasons, i.e., the use of animals in research (please see below for further details).

      All the new data will appear as new Figure 5 (B to E). For new Figure 5A please see below the major comment 2 of Reviewer 2.

      Though beyond the current study's scope, in the discussion section, the authors may want to propose or hypothesize on how MDM2-mediated NICD stabilization contributes to carboplatin resistance. This could provide valuable insights for future research directions.

      [Authors] We will discuss this part as proposed by the reviewer.

      In the Western blot results, the total ATM and ATR controls were absent.

      [Authors] The reviewer is totally right and we will repeat experiments to include all the totals as requested.

      Authors may choose to include a graphical abstract at the end of their study to visually illustrate the mechanisms they have described.

      [Authors] Very good idea thanks, we will do it.

      Reviewer #1 (Significance (Required)):

      Advance: The authors aim to present a novel perspective on the resistance mechanisms to platinum compounds in NSCLC therapy. They explore platinum compounds-induced DNA damage, ATM activation, and MDM2-mediated stabilization of the active form of NOTCH (NICD). However, to strengthen their claims, they must provide more conclusive results.

      Audience: This manuscript will likely engage oncologists who investigate the chemotherapy-resistant mechanisms of platinum compounds in NSCLC treatment, as well as scientists specializing in NOTCH and MDM2 pathways. However, the manuscript's central claims lack robust support from the available data, and the current approaches employed are not sufficiently thoughtful and rigorous; there is room for improvement.

      My expertise is molecular medicine, cancer biology, and epigenetics.

      [Authors] We want to thank again this reviewer for her/his helpful comments that will increase the impact and the relevance of our study while keeping the original message.

      We are also very satisfied when she/he said: “This manuscript will likely engage oncologists who investigate the chemotherapy-resistant mechanisms of platinum compounds in NSCLC treatment”.

      Reviewer #2 (Evidence, reproducibility and clarity (Required)):

      In this manuscript, Sara Bernardo et al. investigated the molecular mechanisms underlying the activation of the Notch signaling in response to DNA damage induced by platinum-based chemotherapeutic agents in non-small cell lung cancer (NSCLC). They demonstrated that carboplatin treatment induces DNA double-strand breaks (DSBs) and stabilizes NICD, a process dependent on ATM and mediated by MDM2. In vivo experiments in patient-derived xenografts (PDX) showed that inhibition of NICD and MDM2 enhanced platinum effectiveness. Furthermore, clinical analysis revealed a correlation between MDM2 expression and poor prognosis in NSCLC patients treated with platinum compounds, emphasizing the clinical relevance of the MDM2-NICD axis in platinum resistance.

      [Authors] We thank this reviewer for her/his nice synopsis of our study.

      Major comments:

      Overall, the authors have conducted experiments that sufficiently elucidate their claims, and the description of the experiments is detailed. However, there is still room for the improvement.

      [Authors] We are very pleased that reviewer finds our experimental work “…sufficiently elucidate their claims, and the description of the experiments is detailed.” And we are sure that after all the new experiments we are proposing in here, she/he will be fully satisfied.

      1.The finding that MDM2 promoted NICD stability through non degradative ubiquitination is interesting and in line with a previous study. As it is also known that NICD is regulated by various post-translational modifications, including ubiquitination that promotes NICD degradation. It is unclear what's the potential difference between these two types of ubiquitination. For example, do these two differ in specific ubiquitination sites? Can the authors provide some discussion?

      [Authors] We agree with the reviewer and hence we will perform a new set of experiments to determine the role of 2 key lysine residues in the ubiquitin protein promoting either degradation or DNA binding. As explained in detail in major point 1 from reviewer 1, we will determine if DNA damage promotes ubiquitination in position 48, i.e., to degrade, or in position 63, i.e., to facilitate the binding to DNA for repairing upon DNA damage, or in any of these 2 positions. And as mentioned above, we will then confirm that MDM2 is responsible of the specific ubiquitination type we will uncover. We are sure that the reviewer will be satisfied by these new data once is generated.

      As for the specific ubiquitination sites in NICD, there are up to 17 lysine residues susceptible of being ubiquitinated. Hence unveiling what residues are targeted by MDM2 and if they differ from others inducing degradation as those promoted by the E3 ligase FBXW7, we feel is out of the scope of the current manuscript. Still, we will discuss all this part as kindly proposed by the reviewer.

      Could the overexpression of MDM2 or NICD lead to carboplatin resistance in A549 or H358 cells?

      [Authors] This is a very interesting experiment and prompted by the reviewer’s comment we started the subcloning of inducible NICD into lentiviral vectors to generate stable cells and test the carboplatin sensitivity in presence of different levels of NICD. These new data will be the new Figure 5A.

      The trends observed in the western blot data within the manuscript appear inconsistent. While the authors propose that NICD levels increased upon incubation with carboplatin, the discrepancy arises when considering the NICD levels without cycloheximide (CHX) treatment in Figure 1E, where no significant elevation is observed (Lane 6 vs. Lane 1).

      [Authors] The point of the reviewer is well taken. Please bear in mind that in here we are handling several signaling pathways that interact among them while having each one different kinetics. Our finding of increased NICD upon carboplatin treatment is highly consistent in vitro and in vivo, but it is true that in the experiment mentioned by the reviewer is not obvious, probably due to some kinetic issue. We are repeating this experiment to have the increased in NICD upon carboplatin as it is in the rest of the manuscript (up to 9 times only in main figures).

      The quality of western blots needs to be improved, especially Fig. 1C and S1C, also Figure 3B. Moreover, the NICD western blot sometimes appears as one band and sometimes as two bands. Please provide an explanation. If possible, please quantify the bands in western blots.

      [Authors] We agree with the reviewers that not all WB have the same quality and we will repeat some of them to homogenize the quality all over the manuscript, and particularly, we will repeat the ones kindly pointed out by the reviewer.

      The two bands it is something we also noticed and we will pay attention while reproducing the WB, since it might be related to discrepancies in the percentage of acrylamide. If this is not the case, i.e., upon repetition we still observe in some conditions and not in others, we will provide explanations for this in the new submission as kindly proposed by the reviewer.

      Finally, and also as proposed by the reviewer we will quantify the WB bands.

      Please provide a necessary discussion on whether the targeted treatment approach towards the MDM2-NICD axis is applicable to all patients or only to those with high expression of MDM2/NICD.

      [Authors] In the discussion of the current manuscript, we focused into the MDM2 high expression subset of patients for this issue, but in the next submission we will enlarge to patients with high levels of NICD also.

      How to interpret the significance of the simultaneous increase in NICD ubiquitination and stability mediated by MDM2? Please provide a relevant discussion.

      [Authors] We will provide strong experimental data to go beyond discussion (please see above the experiments with ubiquitin mutants), but we will also provide discussion of this particular point.

      In Figure 5B, please also check the level of MDM2. In Figure 5C, carboplatin appears to have little impact on tumor growth. How to explain the increase of Ki-67 in the carboplatin treatment group in Figure 5A?

      [Authors] We will measure also levels of MDM2 in the future new Figure 5C as requested by the reviewer.

      As for the interesting observation of the Ki67, since we will repeat the whole experiment, we will pay special attention to this point if ever it is repeated. Should be this the case, we will elaborate an explanation.

      Minor comments:

      1.Please include scale bars in Figure 1B and Supplemental Figure 1B.

      [Authors] We thank the reviewer for this comment. We will include the scale bars where required.

      2.Figure 5D, the P values of the survival curve should be indicated in the figures.

      [Authors] We will include the P values in the future new Figure 5E.

      3.The presentation of survival curve data in Figures 5D and 6A should be consistent.

      [Authors] The point of the reviewer is well taken and we will use Prism to draw the PFS for patients in Figure 6A as we did for the mice in current Figure 5D.

      4.It seems that supplemental figure 2 is missing.

      [Authors] We actually jumped from supplemental figure 1 to 3 because we do not have any associated supplemental figure to main Figure 2. We will clarify this point in the next submission.

      5.Please carefully check the spelling of the entire text, for example, on page 20, line 426 it should be 'western'. Also, please spell out the abbreviations DDR and ATM.

      [Authors] We will double check all spelling and provide the abbreviations kindly suggested by the reviewer.

      6.The abbreviation for Cleaved caspase 3 should be CC3.

      [Authors] We thank the reviewer for this information, we will use CC3 in the next submission.

      Reviewer #2 (Significance (Required)):

      Notch signaling is associated with the occurrence and development of non-small cell lung cancer (NSCLC). Previous study indicates that the expression of Notch protein is significantly higher in NSCLC tissues compared to normal tissues (PMID: 31170211). Additionally, the upregulation of Notch1 is correlated with higher tumor grades, lymph node metastasis, tumor-node-metastasis (TNM) staging, and poor prognosis (PMID: 25996086). Abnormal activation of Notch signaling pathway is frequently observed in chemotherapy-resistant NSCLC, and some studies have aimed to address NSCLC drug resistance via modulating Notch signaling (PMID: 30087852, 38301911). This manuscript firstly proposes that MDM2-mediated stabilization of NICD upon DNA damage plays a major role in NSCLC response to platinum chemotherapy. It further suggests that targeting the MDM2-NICD axis could prove to be an effective therapeutic strategy. Overall, this work unveils a novel mechanism for Notch activation in response to platinum chemotherapy, providing a renewed outlook on overcoming chemotherapy resistance in NSCLC. This manuscript will attract those interested in the mechanisms of chemotherapy resistance and novel treatment approaches.

      [Authors] We sincerely thank the reviewer for finding that our “…work unveils a novel mechanism for Notch activation in response to platinum chemotherapy, providing a renewed outlook on overcoming chemotherapy resistance in NSCLC”. We are also very satisfied when she/he says: “This manuscript will attract those interested in the mechanisms of chemotherapy resistance and novel treatment approaches.”

      Finally, we are convinced that the reviewer will appreciate all the new proposed experimental data, and also that upon finishing all experiments, she/he will think that the manuscript will be suitable for publication.

      3. Description of the revisions that have already been incorporated in the transferred manuscript

      For simplicity, we decided to introduce all changes in next submission upon conclusion of all experimental approaches proposed above.

      4. Description of analyses that authors prefer not to carry out

      While we will perform almost all experiments proposed by reviewers, there is one we feel is not possible to do due to ethical reasons. Reviewer 1 wanted us to perform a new in vivo experiment with the same PDX using up to 6 treatment groups. We use 8 mice per condition (for tumor growth and survival) plus 4 for the “acute” treatment for WB and IHC purposes, hence 12 mice x 6 groups = 72 mice, and we will perform this experiment as indicated above and proposed by the reviewer.

      On the contrary, the reviewer asked us also to repeat the same experiment with a PDX p53 proficient. While we understand the possible interest, since we demonstrated in vitro that p53 is not required for the protective phenotype of MDM2 and Notch upon DNA damage, we honestly believe that using another 72 mice to confirm this aspect in vivo, is against the rational use of animals in research going against the 3Rs rule. Hence, we will not perform this experiment unless Editors believe is strictly required.

      REFERENCES

      Arena, G., Cisse, M. Y., Pyrdziak, S., Chatre, L., Riscal, R., Fuentes, M., Arnold, J. J., Kastner, M., Gayte, L., Bertrand-Gaday, C., et al. (2018). Mitochondrial MDM2 Regulates Respiratory Complex I Activity Independently of p53. Mol Cell 69, 594-609 e598.

      Cheng, Q., Cross, B., Li, B., Chen, L., Li, Z., and Chen, J. (2011). Regulation of MDM2 E3 ligase activity by phosphorylation after DNA damage. Mol Cell Biol 31, 4951-4963.

      Gounder, M., Ratan, R., Alcindor, T., Schoffski, P., van der Graaf, W. T., Wilky, B. A., Riedel, R. F., Lim, A., Smith, L. M., Moody, S., et al. (2023). Nirogacestat, a gamma-Secretase Inhibitor for Desmoid Tumors. N Engl J Med 388, 898-912.

      Kassouf, T., Larive, R. M., Morel, A., Urbach, S., Bettache, N., Marcial Medina, M. C., Merezegue, F., Freiss, G., Peter, M., Boissiere-Michot, F., et al. (2019). The Syk Kinase Promotes Mammary Epithelial Integrity and Inhibits Breast Cancer Invasion by Stabilizing the E-Cadherin/Catenin Complex. Cancers (Basel) 11.

      Liu, P., Gan, W., Su, S., Hauenstein, A. V., Fu, T. M., Brasher, B., Schwerdtfeger, C., Liang, A. C., Xu, M., and Wei, W. (2018). K63-linked polyubiquitin chains bind to DNA to facilitate DNA damage repair. Sci Signal 11.

      Pettersson, S., Sczaniecka, M., McLaren, L., Russell, F., Gladstone, K., Hupp, T., and Wallace, M. (2013). Non-degradative ubiquitination of the Notch1 receptor by the E3 ligase MDM2 activates the Notch signalling pathway. Biochem J 450, 523-536.

      Riscal, R., Schrepfer, E., Arena, G., Cisse, M. Y., Bellvert, F., Heuillet, M., Rambow, F., Bonneil, E., Sabourdy, F., Vincent, C., et al. (2016). Chromatin-Bound MDM2 Regulates Serine Metabolism and Redox Homeostasis Independently of p53. Mol Cell 62, 890-902.

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, Gu et al. employed novel viral strategies, combined with in vivo two-photon imaging, to map the tone response properties of two groups of cortical neurons in A1. The thalamocortical recipient (TR neurons) and the corticothalamic (CT neurons). They observed a clear tonotopic gradient among TR neurons but not in CT neurons. Moreover, CT neurons exhibited high heterogeneity of their frequency tuning and broader bandwidth, suggesting increased synaptic integration in these neurons. By parsing out different projecting-specific neurons within A1, this study provides insight into how neurons with different connectivity can exhibit different frequency response-related topographic organization.

      Strengths:

      This study reveals the importance of studying neurons with projection specificity rather than layer specificity since neurons within the same layer have very diverse molecular, morphological, physiological, and connectional features. By utilizing a newly developed rabies virus CSN-N2c GCaMP-expressing vector, the authors can label and image specifically the neurons (CT neurons) in A1 that project to the MGB. To compare, they used an anterograde trans-synaptic tracing strategy to label and image neurons in A1 that receive input from MGB (TR neurons).

      Weaknesses:

      - Perhaps as cited in the introduction, it is well known that tonotopic gradient is well preserved across all layers within A1, but I feel if the authors want to highlight the specificity of their virus tracing strategy and the populations that they imaged in L2/3 (TR neurons) and L6 (CT neurons), they should perform control groups where they image general excitatory neurons in the two depths and compare to TR and CT neurons, respectively. This will show that it's not their imaging/analysis or behavioral paradigms that are different from other labs.  

      - Figures 1D and G, the y-axis is Distance from pia (%). I'm not exactly sure what this means. How does % translate to real cortical thickness? 

      - For Figure 2G and H, is each circle a neuron or an animal? Why are they staggered on top of each other on the x-axis? If the x-axis is the distance from caudal to rostral, each neuron should have a different distance? Also, it seems like it's because Figure 2H has more circles, which is why it has more variation, thus not significant (for example, at 600 or 900um, 2G seems to have fewer circles than 2H).  

      - Similarly, in Figures 2J and L, why are the circles staggered on the y-axis now? And is each circle now a neuron or a trial? It seems they have many more circles than Figure 2G and 2H. Also, I don't think doing a correlation is the proper stats for this type of plot (this point applies to Figures 3H and 3J).

      - What does the inter-quartile range of BF (IQRBF, in octaves) imply? What's the interpretation of this analysis? I am confused as to why TR neurons show high IQR in HF areas compared to LF areas, which means homogeneity among TR neurons (lines 213 - 216). On the same note, how is this different from the BF variability?  Isn't higher IQR equal to higher variability?

      - Figure 4A-B, there are no clear criteria on how the authors categorize V, I, and O shapes. The descriptions in the Methods (lines 721 - 725) are also very vague.

    1. because chatGPT said it was "El and the Royal Navy of Australia"

      ((( literally, literally, literally, that is how I read, and when I read things, it's important, because this is all about

      Arnutet

      which you might call Ultima Thule, or Elseum or ... "Far Points Station;" or if you are up on the new lingo, you might be calling it the military outpost related to the Venutian Alexandria, which I apparently have still failed to sell rights of name to from Jessup to Virgin, or we'd be calling it the Virgin Alexandria by now.

      Who is Nathan Jessup?

      Alex?

      [

      Ernutet Crater - Enhanced Color - Jet Propulsion Laboratory

      NASA Jet Propulsion Laboratory (.gov)

      https://www.jpl.nasa.gov › images › pia21419-ernutet-c...

      ](https://www.jpl.nasa.gov/images/pia21419-ernutet-crater-enhanced-color)

      [

      ceres arnutet from www.jpl.nasa.gov

      ](https://www.jpl.nasa.gov/images/pia21419-ernutet-crater-enhanced-color)

      Feb 16, 2017 --- ... aboard NASA's Dawn spacecraft, shows the area around Ernutet crater. The bright red portions appear redder with respect to the rest of Ceres.

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      People also ask

      Why does Ceres have bright spots?

      What is the structure and composition of Ceres?

      Feedback

      [

      Organics on Ceres may be more abundant than originally ...

      Brown University

      https://www.brown.edu › news › ceres

      ](https://www.brown.edu/news/2018-06-13/ceres)

      [

      ceres arnutet from www.brown.edu

      ](https://www.brown.edu/news/2018-06-13/ceres)

      Jun 13, 2018 --- A new analysis of data from NASA's Dawn mission suggests that organic matter may exist in surprisingly high concentrations on the dwarf ...

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      [

      Scientists dig into the origin of organics on Ceres

      Phys.org

      https://phys.org › Astronomy & Space › Space Exploration

      ](https://phys.org/news/2017-10-scientists-ceres.html)

      [

      ceres arnutet from phys.org

      ](https://phys.org/news/2017-10-scientists-ceres.html)

      Oct 18, 2017 --- "The discovery of a locally high concentration of organics close to the Ernutet crater poses an interesting conundrum," said Dr. Simone Marchi, ...

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      [

      The composition and structure of Ceres' interior

      ScienceDirect.com

      https://www.sciencedirect.com › article › abs › pii

      ](https://www.sciencedirect.com/science/article/abs/pii/S0019103519300508)

      by MY Zolotov - 2020 - Cited by 21 --- Ceres is modeled as a chemically uniform mixture of CI-type carbonaceous chondritic rocks and 12--29 vol% of macromolecular organic matter. Water ...

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      [

      Organic Material on Ceres: Insights from Visible and ...

      MDPI

      https://www.mdpi.com › ...

      ](https://www.mdpi.com/2075-1729/11/1/9)

      by A Raponi - 2020 - Cited by 19 --- In the present work, we focus on the average spectrum of Ceres. We also revise local spectra from the Ernutet and Occator crater regions, where ...

      [

      Ceres Community Project

      Ceres Community Project

      https://www.ceresproject.org

      ](https://www.ceresproject.org/)

      [

      ceres arnutet from www.ceresproject.org

      ](https://www.ceresproject.org/)

      Ceres client enjoying meal. We provide beautiful, delicious and medically tailored meals made with love for those facing a serious illness like cancer ...

      Contact - ‎Ceres Volunteer - ‎Meals for Myself or a Loved One - ‎Job Openings

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      Images

      Ernutet Crater - Enhanced Color

      [

      Ernutet Crater - Enhanced Color

      Jet Propulsion Laboratory - NASA

      ](https://www.jpl.nasa.gov/images/pia21419-ernutet-crater-enhanced-color)

      Organics on Ceres may be more abundant than originally ...

      [

      Organics on Ceres may be more abundant than originally ...

      Brown University

      ](https://www.brown.edu/news/2018-06-13/ceres)

      Scientists dig into the origin of organics on Ceres

      [

      Scientists dig into the origin of organics on Ceres

      Phys.org

      ](https://phys.org/news/2017-10-scientists-ceres.html)

      Feedback


      6 more images

      [

      Home | Ceres: Sustainability is the bottom line

      ](https://www.ceres.org/)

      [

      ceres.org

      https://www.ceres.org

      ](https://www.ceres.org/)

      Ceres Accelerator for Sustainable Capital Markets. Our center for excellence within Ceres aims to transform the practices and policies that govern capital ...

      About - ‎Support Ceres - ‎Ceres Accelerator - ‎Investor Network

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      [

      Ceres (mythology)

      Wikipedia

      https://en.wikipedia.org › wiki › Ceres_(mythology)

      ](https://en.wikipedia.org/wiki/Ceres_(mythology))

      She is usually depicted as a mature woman. Ceres. Goddess of agriculture, fertility, grains, the harvest, motherhood, the earth, and cultivated crops.

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      [

      Ceres Imaging: Risk insights for sustainable agriculture

      Ceres Imaging

      https://www.ceresimaging.net

      ](https://www.ceresimaging.net/)

      Ceres Imaging is the world's most advanced data analytics platform for agriculture.

      Careers - ‎About us - ‎Ceres for sustainability - ‎Ceres for agribusiness

      Missing: ~~arnutet~~ ‎| Show results with: arnutet

      Elizabeth Rosa Landau is an American science writer and communicator. She is a Senior Communications Specialist at NASA Headquarters.^[1]^ She was a Senior Storyteller at the NASA Jet Propulsion Laboratory previously.

      Education

      Landau grew up in Bryn Mawr, Pennsylvania. As a child, she watched Carl Sagan's TV series Cosmos, which helped inspire her love of space.^[2]^

      She earned a bachelor's degree in anthropology at Princeton University (magna cum laude) in 2006. As a Princeton student, she completed study-abroad programs at University of Seville and Universidad de León.^[3]^ During her junior year in Princeton, she was the editor-in-chief of Innovation, the university's student science magazine.^[2]^ In the summer of 2004, she became a production intern at CNN en Español in New York.^[3]^ She earned a master's in journalism from Columbia University, where she focused on politics.^[4]^

      Career

      Landau began to write and produce for CNN's website in 2007 as a Master's Fellow, and returned full-time in 2008.^[5]^ Here she co-founded the CNN science blog, Light Years.^[6]^ She covered a variety of topics including Pi Day.^[7]^^[8]^^[9]^ In 2012, Landau interviewed Scott Maxwell about the Curiosity rover at the NASA Jet Propulsion Laboratory.^[10]^

      NASA career

      In 2014, she became a media relations specialist at the NASA Jet Propulsion Laboratory, where she led media strategy for Dawn (spacecraft), Voyager, Spitzer, NuSTAR, WISE, Planck and Hershel.^[11]^^[12]^^[13]^^[14]^^[15]^^[16]^ She led NASA's effort to share the TRAPPIST-1 exoplanet system with the world on February 22, 2017.^[17]^^[18]^ In January 2018, she was appointed a Senior Storyteller at the Jet Propulsion Laboratory.^[2]^ In February 2020, she became a Senior Communications Specialist at NASA Headquarters.^[1]^

    1. Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

      Learn more at Review Commons


      Reply to the reviewers

      Manuscript number: RC-2024-02394

      Corresponding author(s): Altman, Brian J

      1. General Statements [optional]

      We thank all three Reviewers for their insightful and helpful feedback and suggestions. We strongly believe that addressing these comments has now resulted in a much-improved manuscript. We appreciate that the Reviewers found the manuscript "interesting" with "valuable insights and... obvious novelty", "an important study that is well-done", and "an important understanding of the crosstalk between cancer cells and immune cells as well as the understanding of how the TME disrupts circadian rhythms". All three Reviewers requested a significant revision, which we provide here. We carefully and completely responded to each Reviewer question or suggestion, in most cases with new experiments and text, and in a very few cases with changes or additions to the Discussion section. This includes new data in seven of the original Figures and Supplementary Figures, and one new main Figure and three new Supplementary Figures. Highlights of these new data include testing the role of low pH in cancer cell supernatant on macrophage rhythms, and analysis of single-cell RNA-sequencing data for heterogeneity in macrophage circadian gene expression. Additional experiments were also performed that were not included in the manuscript, and these data are presented in this Response. A detailed point-by-point response to each comment is included below with excerpts of the data and updated text for the reviewers. Please note that the PDF version of this Response includes images of the new Figures inserted in to the manuscript.

      2. Point-by-point description of the revisions

      __Reviewer #1 __

      Evidence, reproducibility and clarity

      The manuscript by Knudsen-Clark et al. investigates the novel topic of circadian rhythms in macrophages and their role in tumorigenesis. The authors explore how circadian rhythms of macrophages may be influenced by the tumor microenvironment (TME). They utilize a system of bone marrow-derived macrophages obtained from transgenic mice carrying PER2-Luciferase (PER2-Luc), a trackable marker of rhythmic activity. The study evaluates how conditions associated with the TME, such as polarizing stimuli (to M1 or M2 subtype), acidic pH, and elevated lactate, can each alter circadian rhythms in macrophages. The authors employ several approaches to explore macrophage functions in cancer-related settings. While the manuscript presents interesting findings and may be the first to demonstrate that tumor stimuli alter circadian rhythms in macrophages and impact tumor growth, it lacks a clear conclusion regarding the role of altered circadian rhythms in suppressing tumor growth. Several discrepancies need to be addressed before publication, therefore, the manuscript requires revision before publication, addressing the following comments:

      We thank Reviewer #1 for the comments regarding the quality of our work and are pleased that the Reviewer finds that this manuscript "presents interesting findings and may be the first to demonstrate that tumor stimuli alter circadian rhythms in macrophages and impact tumor growth". We have addressed all comments and critiques from Reviewer #1 below. To summarize, we added new data on how different macrophage polarization states affect media pH (Supplementary Figure 4), further characterized gene expression in our distinct macrophage populations (Supplementary Figure 1), provided clarity in the data and text on the universal nature of Clock Correlation Distance (CCD) across macrophage populations (Figure 6), included human tumor-associated macrophage (TAM) data for CCD (Figure 7) analyzed single-cell RNA-sequencing data of TAMs to demonstrate heterogeneity in circadian gene expression (Figure 9), and used tumor-conditioned media to show that low pH still affects macrophage rhythms in this context *Supplementary Figure 5". Thanks to the helpful suggestions of the Reviewer, we also made numerous clarifications and fixed a critical referencing error that the Reviewer identified.

      Major comments: 1. It is well known that pro-inflammatory macrophages primarily rely on glycolysis during inflammation, exhibiting dysregulated tricarboxylic acid (TCA) cycle activity. These pro-inflammatory macrophages are commonly referred to as 'M1' or pro-inflammatory, as noted in the manuscript. In contrast, M2 macrophages, or pro-resolution macrophages, are highly dependent on active mitochondrial respiration and oxidative phosphorylation (OXPHOS). Given that M1 macrophages favor glycolysis, they create an acidic environment due to elevated lactate levels and other acidifying metabolites. However, the study does not address this effect. The authors' hypothesis revolves around the acidic environment created by glycolytic tumors, yet they overlook the self-induced acidification of media when culturing M1 macrophages. This raises the question of how the authors explain the reduced circadian rhythms observed in pro-inflammatory macrophages in their study, while low pH and higher lactate levels enhance the amplitude of circadian rhythms. I would encourage the authors to incorporate the glycolytic activity of pro-inflammatory macrophages into their experimental setup. Otherwise the data look contradictory and misleading in some extent.

      We appreciate the important point Reviewer #1 made that macrophages polarized toward a pro-inflammatory phenotype such as those stimulated with IFNγ and LPS (M1 macrophages) prioritize metabolic pathways that enhance glycolytic flux, resulting in increased release of protons and lactate as waste products from the glycolysis pathway. In this way, polarization of macrophages toward the pro-inflammatory phenotype can lead to acidification of the media, which may influence our observations given that we are studying the effect of extracellular pH on rhythms in macrophages. To address this point, we have performed additional experiments in which we measured pH of the media to capture changes in media pH that occur during the time in which we observe changes in rhythms of pro-inflammatory macrophages.

      In line with the documented enhanced glycolytic activity of pro-inflammatory macrophages, the media of pro-inflammatory macrophages is acidified over time, in contrast to media of unstimulated or pro-resolution macrophages. Notably, while pH decreased over time in the pro-inflammatory group, the pH differential between the pH7.4, pH6.8, and pH6.5 sample groups was maintained over the period in which we observe and measure changes in circadian rhythms of pro-inflammatory macrophages. Additionally, media that began at pH 7.4 was acidified only to pH 7 by day 2, above the acidic pH of 6.8 or 6.5. As a result, there remained a difference in pH between the two groups (pH 7.4 and pH 6.5) out to 2 days consistent with the changes in rhythms that we observe between these two groups. This indicates that the difference in circadian rhythms observed in pro-inflammatory macrophages cultured at pH 7.4 compared to pH 6.5 were indeed due to the difference in extracellular pH between the two conditions. We have incorporated these data, shown below, into Supplementary Figure 4 and added the following discussion of these data to the Results section:

      "In line with their documented enhanced glycolytic capacity, pro-inflammatory macrophages acidified the media over time (Supplementary Figure 4C). Notably, while pH of the media the pro-inflammatory macrophages were cultured in decreased over time pH, the pH differential between the pH 7.4, pH 6.8, and pH 6.5 samples groups of pro-inflammatory macrophages was maintained out to 2 days, consistent with the changes in rhythms that we observe and measure between these groups."

      The article examines the role of circadian rhythms in tumor-associated macrophages, yet it lacks sufficient compelling data to support this assertion. Two figures, Figure 7 and Figure 9, are presented in relation to cancer. In Figure 7, gene expression analysis of Arg1 (an M2 marker) and Crem (a potential circadian clock gene) is conducted in wild-type macrophages, BMAL1-knockout macrophages with dysregulated circadian rhythms, and using publicly available data on tumor-associated macrophages from a study referenced as 83. However, it is noted that this referenced study is actually a review article by Geeraerts et al. (2017) titled "Macrophage Metabolism as Therapeutic Target for Cancer, Atherosclerosis, and Obesity" published in Frontiers in Immunology. This raises concerns about the reliability of the results. Furthermore, comparing peritoneal macrophages from healthy mice with macrophages isolated from lung tumors is deemed inaccurate. It is suggested that lung macrophages from healthy mice and those from mice with lung tumors should be isolated separately for a more appropriate comparison. Consequently, Figure 7B is further questioned regarding how the authors could compare genes from the circadian rhythm pathway between these non-identical groups. As a result, the conclusion drawn from these data, suggesting that tumor-associated macrophages exhibit a gene expression pattern similar to BMAL1-KO macrophages, is deemed incorrect, affecting the interpretation of the data presented in Figure 8.

      We thank Reviewer #1 for pointing out our error in the reference provided as the source of the TAM data used for CCD in Figure 7. While we took care to provide the GEO ID for the data set (GSE188549) in the Methods section, we mistakenly cited Geeraerts (2017) Front Immunol when we should have cited Geeraerts (2021) Cell Rep. We have corrected this citation error in the main text.

      We also appreciate Reviewer #1's concern that we are comparing circadian gene expression of peritoneal macrophages to tumor-associated macrophages derived from LLC tumors, which are grown ectopically in the flank for the experiment from which the data set was produced. To ensure an accurate comparison of gene expression, we downloaded the raw FASTQ files from each dataset and processed them in identical pipelines. Our main comparison between these cell types is Clock Correlation Distance (CCD), which compares the pattern of co-expression of circadian genes (Shilts et al PeerJ 2018). CCD was built from multiple mouse and human tissues to be a "universal" tool to compare circadian rhythms, and designed to compare between different tissues and cell types. Each sample is compared to a reference control built from these multiple tissues. To better convey this concept to readers to give confidence the suitability of CCD for comparing data sets across different tissues, we have added the reference control to Figure 7 (now Figure 6B), We have also expanded our analysis to include bone marrow-derived macrophages, to further demonstrate that the organization of clock gene co-expression is not specific to peritoneal macrophages; we have added this data to Figure 7 (now Figure 6C,D). Finally, we have included an abbreviated explanation of the points made above in the results section.

      Due to the universal nature of the CCD tool, we disagree with Reviewer #1's assertion that "the conclusion drawn from these data, suggesting that tumor-associated macrophages exhibit a gene expression pattern similar to BMAL1-KO macrophages, is deemed incorrect". Indeed, this finding mirrors findings in the original CCD paper, which showed that tumor tissues universally exhibit a disordered molecular clock as compared to normal tissue. Notably, the original CCD paper also compared across cell and tumor types.

      As an additional note to the review, we would like to clarify that nowhere in the manuscript do we propose that Crem is a potential circadian clock gene. We are clear throughout the manuscript that we are using Crem as a previously established biomarker for acidic pH-sensing in macrophages. Please see below for the modified Figure and text.

      "To understand the status of the circadian clock in TAMs, we performed clock correlation distance (CCD) analysis. This analysis has previously been used to assess functionality of the circadian clock in whole tumor and in normal tissue[102]. As the circadian clock is comprised of a series of transcription/translation feedback loops, gene expression is highly organized in a functional, intact clock, with core clock genes existing in levels relative to each other irrespective of the time of day. In a synchronized population of cells, this ordered relationship is maintained at the population level, which can be visualized in a heatmap. CCD is designed to compare circadian clock gene co-expression patterns between different tissues and cell types. To accomplish this, CCD was built using datasets from multiple different healthy tissues from mouse and human to be a universal tool to compare circadian rhythms. Each sample is compared to a reference control built from these multiple tissues (Figure 6B)[102]. To validate the use of this analysis for assessing circadian disorder in macrophages, we performed CCD analysis using publicly available RNA-sequencing data from bone marrow-derived macrophages and wild type peritoneal macrophages, as a healthy control for functional rhythms in a synchronized cell population, and BMAL1 KO peritoneal macrophages, as a positive control for circadian disorder[44]."

      And in the Discussion:

      "Interestingly, analysis of TAMs by clock correlation distance (CCD) presents evidence that rhythms are disordered in bulk TAMs compared to other macrophage populations (Figure 6). CCD is one of the most practical tools currently available to assess circadian rhythms due to its ability to assess rhythms independent of time of day and without the need for a circadian time series, which is often not available in publicly available data from mice and humans[102]."

      If the authors aim to draw a clear conclusion regarding the circadian rhythms of tumor-associated macrophages (TAMs), they may need to analyze single-sorted macrophages from tumors and corresponding healthy tissues. Such data are publicly available (of course not in #83)

      We agree with Reviewer #1 that while our interpretation of the data is that there may be heterogeneity in circadian rhythms of tumor-associated macrophages, we cannot prove this without assessing circadian rhythms at the single cell level. While single-cell RNA-sequencing data of freshly isolated tumor associated macrophages of sufficient read depth for circadian gene expression analysis has historically been unavailable, fortunately a dataset was released recently (May 2024) which we were able to use to address this point. We have analyzed publicly available single-cell RNAseq data of tumor-associated macrophages (GSE260641, Wang 2024 Cell) to determine whether there are differences in expression of circadian clock genes between different TAM populations. We have added these data as a new Figure 9. Please see the figure and updated text below.

      "Tumor-associated macrophages exhibit heterogeneity in circadian clock gene expression.

      __ Our findings suggested that heterogeneity of the circadian clock may lead to disorder in bulk macrophage populations, but did not reveal if specific gene expression changes exist in tumor-associated macrophages at the single-cell level. To determine whether heterogeneity exists within the expression of circadian clock genes of the tumor-associated macrophage population, we analyzed publicly available single-cell RNA sequencing data of macrophages isolated from B16-F10 tumors[107]. To capture the heterogeneity of macrophage subsets within the TAM population, we performed unbiased clustering (Figure 9A). We then performed differential gene expression to determine if circadian clock genes were differentially expressed within the TAM subpopulations. The circadian clock genes Bhlhe40 (DEC1), Bhlhe41 (DEC2), Nfil3 (E4BP4), Rora (RORα), Dbp (DBP), and Nr1d2 (REV-ERBβ) were significantly (adj.p We next sought to determine whether differences in circadian clock gene expression between TAM subpopulations were associated with exposure to acidic pH in the TME. To this end, we first assessed Crem expression in the TAM subpopulations that were identified by unbiased clustering. Crem expression was significantly higher in TAM clusters 4, 5, and 6 compared to TAM clusters 1-3 and 7-9 (Figure 9C). Clusters were subset based on Crem expression into Crem high (clusters 4-6) and Crem low (clusters 1-3, 7-9) (Figure 9D), and differential gene expression analysis was performed. The circadian clock genes Nfil3, Rora, Bhlhe40, and Cry1 (CRY1) were significantly (adj.p __And in the Discussion:

      "Supporting the notion that population-level disorder may exist in TAMs, we used scRNA-sequencing data and found evidence of heterogeneity between the expression of circadian clock genes in different TAM subpopulations (Figure 9A, B). Phenotypic heterogeneity of TAMs in various types of cancer has previously been shown[20, 21, 125, 126], and we have identified distinct TAM subpopulations by unbiased clustering (Figure 9A). Within those TAM subpopulations, we identified differential expression of circadian clock genes encoding transcription factors that bind to different consensus sequences: DEC1 and DEC2 bind to E-boxes, NFIL3 and DBP binds to D-boxes, and RORα and REV-ERBβ binds to retinoic acid-related orphan receptor elements (ROREs)[127, 128]. While little is known about regulation of macrophages by E-box and D-box elements beyond the circadian clock, aspects of macrophage function have been shown to be subject to transcriptional regulation through ROREs[129, 130]. Thus, we speculate that variations in these transcription factors may exert influence on expression of genes to drive diversity between TAM subpopulations. Differential expression of circadian clock genes between TAM subpopulations was also associated with Crem expression (Figure 9C-E), suggesting that exposure of TAMs to acidic pH within the TME can alter the circadian clock. However, there remained significant variation in expression of circadian clock genes within the Crem high and Crem low groups (Figure 9B), suggesting that acidic pH is not the only factor in the TME that can alter the circadian clock. Together, these data implicate the TME in driving heterogeneity in TAM circadian rhythms just as it drives heterogeneity in TAM phenotype.

      Interestingly, in contrast to our observations of circadian disorder in TAMs isolated from LLC tumors (Figure 6), rhythmicity in expression of circadian genes was observed in bulk TAMs isolated from B16 tumors[107]. This suggests that circadian rhythms of TAMs are maintained differently in different types of cancer. Notably, both of these observations were at the population level. Upon separation of the B16 TAM population into subsets by unbiased clustering of single-cell RNA sequencing data, we measured differences in expression of circadian clock genes between TAM subpopulations (Figure 9A,B). This suggests that even within a rhythmic TAM population, there is heterogeneity in the circadian clock of TAM subpopulations."

      Additionally, it is widely acknowledged that human and mouse macrophages exhibit distinct gene expression profiles, both in vitro and in vivo. While assuming that genes involved in circadian rhythms are conserved across species, the authors could consider extending their funding to include analyses of single-sorted macrophages from cancer patients, such as those with lung cancer or pancreatic ductal adenocarcinoma (PDAC). These experiments would provide relevant insights into TAM biology.

      We agree that with Reviewer #1 that ultimately, being able to relate findings in mice to humans is critical. It is important to assess if circadian disorder is observed in TAMs in human cancers as it is for LLC tumor-derived macrophages in mice. To address this point, we have performed CCD using a human data set (GSE116946; Garrido 2020 J Immunother Cancer) suitable for use with CCD (wherein macrophages were isolated from bulk tumor in humans, with a high enough samples size, and not cultured prior to sequencing). We have added these data as a new Figure 7, shown below. Please see the added data and updated text below.

      "We next assessed the status of the circadian clock in human TAMs from NSCLC patients. We performed CCD with publicly available RNA-seq data of tumor-adjacent macrophages and tumor-associated macrophages from NSCLC patients, using alveolar macrophages from healthy donors as a control[104, 105]. To assess the contribution of the acidic TME to circadian disorder, we subset TAM NSCLC patient samples into groups (Crem high TAMs and Crem low TAMs) based on median Crem expression. Notably, in macrophages from human NSCLC there was a trend toward disorder in Crem low but not Crem high TAM samples (Figure 7A,B). Additionally, the co-variance among core clock genes observed in alveolar macrophages from healthy donors was absent within Crem low and Crem high TAM samples (Figure 7C). In all, these data indicate that there is population-level disorder in the circadian rhythms of tumor-associated macrophages in humans and mice, suggesting that circadian rhythms are indeed altered in macrophages within the TME."

      And in the Discussion:

      "Indeed, we observed differences in the circadian clock of Crem low human TAM samples compared to Crem high human TAM samples, suggesting that acidic pH influences circadian disorder in TAMs (Figure 7). Interestingly, Crem low TAM samples exhibited a trend toward disorder while Crem high TAM samples did not. This is of particular interest, as we have observed that acidic pH can enhance circadian rhythms in macrophages, raising the question of whether acidic pH promotes or protects against circadian disorder."

      Minor comments: 1. Figure 2C needs clarification. It's unclear why pro-inflammatory macrophages treated with lactic acid would have a shorter amplitude and period, while acidic pH would increase amplitude and period in M2 macrophages.

      We thank Reviewer #1 for this important observation. Based on the comment, it is our understanding that the Reviewer is referring to the data in Figure 2 (low pH) compared to Figure 4 (lactate). We also find it very interesting that lactate alters rhythms in a manner distinct from the way in which acidic pH alters rhythms. Reviewer 3 asked for clarification on how lactate affected circadian gene expression in pH 7.4 or 6.5. We have added these data as Figure 4C (data and text below). It is notable that lactate opposing effects on circadian gene expression in pH 6.5, enhancing the effects of low pH in some cases (Nr1d1) while blunting them in other cases (Cry1). This is mentioned in the text.

      "Lactate was also observed to alter expression of the circadian clock genes Per2, Cry1, and Nr1d1 over time in BMDMs cultured at pH 6.5, while having more subtle effects at pH 7.4 (Figure 4C). Notably, lactate blunted the effect of pH 6.5 on Cry1 expression, while enhancing the effect of low pH on Nr1d1 expression."

      Why these two stimuli alter rhythms differently remains an open question that is discussed in the Discussion section and is prime to be a topic of future investigation. We have added to the Discussion section potential reasons why these conditions may alter rhythms differently, such as the different pathways downstream of sensing these two different conditions. Please see the updated text, below.

      "Although lactate polarizes macrophages toward a pro-resolution phenotype similar to acidic pH[30, 93], exposure to lactate had different effects on circadian rhythms - and in some cases, circadian clock gene expression - than exposure to acidic pH (Figure 4). Sensing of lactate occurs through different pathways than acid-sensing, which may contribute to the different ways in which these two stimuli modulate circadian rhythms of macrophages[111]. One previously published finding that may offer mechanistic insight into how phenotype can influence circadian rhythms is the suppression of Bmal1 by LPS-inducible miR-155[54]. It has also been observed that RORα-mediated activation of Bmal1 transcription is enhanced by PPARγ co-activation[112]. In macrophages, PPARγ expression is induced upon stimulation with IL-4 and plays a key role in alternative activation of macrophages, promoting a pro-resolution macrophage phenotype, and supporting resolution of inflammation[113-115]. Such observations prompt the question of whether there are yet-unidentified factors induced downstream of various polarizing stimuli that can modulate expression of circadian genes at the transcriptional and protein levels. Further work is required to understand the interplay between macrophage phenotype and circadian rhythms."

      The scale in Figure 2C should be equal for all conditions (e.g., -200).

      We appreciate Reviewer #1's preference for the axes to be scaled similarly to enable cross-comparison between graphs. However, due to the different amplitude of pro-inflammatory macrophages compared to the others, we feel that making all axes the same will make it hard to see the rhythms of pro-inflammatory macrophages, hindering the reader's ability to observe the data. Thus, we have put the matched-axis plots, shown below, in Supplementary Figure 4A.

      Absolute values of amplitude, damping, and period differ between Figure 1 and Figure 2A, B, C. The authors should explain these discrepancies.

      As with many experimental approaches, there is slight variation in absolute values between independent experiments, which Reviewer #1 correctly notes. However, while the absolute values vary slightly, the relationship between the values in each of these conditions remains the same across the panels mentioned by Reviewer #1.

      The authors should consider modulating the acidic environment of macrophages in settings more representative of cancer. For example, by adding conditioned media from tumor cells with pronounced glycolysis.

      We appreciate Reviewer #1's desire to more closely mimic the tumor microenvironment. To address Reviewer #1's point, we cultured macrophages in RPMI or cancer cell (KCKO) supernatant at pH 6.5 or pH-adjusted to pH 7.4 and assessed rhythms by measuring rhythmic activity of Per2-Luc with LumiCycle analysis. We then compared changes in rhythms between macrophages cultured normal media to cancer cell supernatant in pH-matched conditions to assess how cancer cell-conditioned media may influence circadian rhythms of macrophages, and the contribution of acidic pH. We have added these data, shown below, as a new Supplementary Figure 5, and included a discussion of these data in the manuscript. Please see the new Figure and updated text below.

      "Cancer cell supernatant alters circadian rhythms in macrophages in a manner partially reversed by neutralization of pH.

      We have observed that polarizing stimuli, acidic pH, and lactate can alter circadian rhythms. However, the tumor microenvironment is complex. Cancer cells secrete a variety of factors and deplete nutrients in the environment. To model this, we cultured BMDMs in RPMI or supernatant collected from KCKO cells, which are a murine model of pancreatic ductal adenocarcinoma (PDAC)[94, 95], at pH 6.5 or neutralized to pH 7.4 (Supplementary Figure 5). Circadian rhythms of BMDMs cultured in cancer cell supernatant at pH 7.4 or pH 6.5 exhibited increased amplitude and lengthened period compared to RPMI control at pH 7.4 or 6.5, respectively, indicating that cancer cell supernatant contains factors that can alter circadian rhythms of BMDMs. Notably, BMDMs cultured in cancer cell supernatant at pH 6.5 had increased amplitude and shortened period compared to BMDMs cultured in cancer cell-conditioned media at pH7.4, indicating that pH-driven changes in rhythms were maintained in BMDMs cultured in cancer cell supernatant. When the pH of cancer cell supernatant was neutralized to pH7.4, the increased amplitude was decreased, and the shortened period was lengthened, indicating that neutralizing acidic pH partially reverses the changes in rhythms observed in macrophages cultured in cancer cell supernatant at pH 6.5. These data further support our observations that acidic pH can alter circadian rhythms of macrophages both alone and in combination with various factors in the TME."

      And, in the Discussion:

      "We have shown that various stimuli can alter rhythms of macrophages in a complex and contributing manner, including polarizing stimuli, acidic pH, and lactate. TGFβ is produced by a variety of cells within the TME, and was recently identified as a signal that can modulate circadian rhythms[123, 124]. Additionally, when we exposed macrophages to cancer cell-conditioned media, rhythms were modulated in a manner distinct from acidic pH or lactate, with these changes in rhythms partially reversed by neutralization of the cancer cell-conditioned media pH (Supplementary Figure 5). It is conceivable that, in addition to acidic pH, other stimuli in the TME are influencing circadian rhythms to drive population-level disorder that we observed by CCD."

      Arg1 alone is not sufficient as an M2 polarization marker. The authors should include additional markers.

      We thank Reviewer #1 for bringing up this critical point in experimental rigor. While Arg1 is a commonly-used marker for M2 polarization, Reviewer #1 points out that polarization of macrophages is typically assessed by a full panel of markers characteristic of the M2 state. To address this point, we have expanded our panel to include several other markers of M2 polarization in mice such as Retnla, Ym1, MGL1, and CD206. In response to Reviewer 2's major point 2 and Reviewer 3's major point 4 below, we have also expanded our panel of markers used to assess the M1 polarization state with Tnfa, Il1b. and Il6. We have added these data, shown below, to Supplementary Figure 1 and updated the text appropriately. Please see the new Figure and updated text below.

      "Consistent with previous studies, we found that genes associated with anti-inflammatory and pro-resolution programming characteristic of IL-4 and IL-13-stimulated macrophages such as Arg1, Retnla, Chil3 (Ym1), Clec10a (MGL1), and Mrc1 (CD206) were induced in IL-4 and IL-13-stimulated macrophages, but not IFNγ and LPS-stimulated macrophages. In contrast, genes associated with pro-inflammatory activity characteristic of IFNγ and LPS-stimulated macrophages such as Nos2 (iNOS), Tnfa, Il1b, and Il6 were induced in IFNγ and LPS-stimulated macrophages, but not IL-4 and IL-13-stimulated macrophages (Supplementary Figure 1)[28, 30, 65, 71, 74, 75]. This indicates that macrophages stimulated with IL-4 and IL-13 were polarized toward a pro-resolution phenotype, while macrophages stimulated with IFNγ and LPS were polarized toward a pro-inflammatory phenotype."

      __ Significance__

      While the manuscript provides valuable insights and has obvious novelty, it requires a significant revision

      We thank Reviewer #1 for their deep read of our manuscript, and their helpful feedback and suggestions. As shown by the comments above, we are confident we have fully addressed each of the points that were made to result in a much-improved revised manuscript.

      __ Reviewer #2 __

      Evidence, reproducibility and clarity

      Knudsen-Clark et al. showed that the circadian rhythm of bone marrow-derived macrophages (BMDM) can be affected by polarization stimuli, pH of the microenvironment, and by the presence of sodium-lactate. Mechanistically, the acidic pH of cell microenvironment is partly regulated by intracellular cAMP-mediated signaling events in BMDM. The authors also showed that the circadian clock of peritoneal macrophages is also modified by the pH of the cell microenvironment. Using publicly available data, the authors showed that the circadian rhythm of tumor-associated macrophages is similar to that of Bmal1-KO peritoneal macrophages. In a murine model of pancreatic cancer, the authors showed that the tumor growth is accelerated in C57BL/6 mice co-injected with cancer cells and Bmal1-KO BMDM as compared to mice co-injected with cancer cell and wild type BMDM.

      We thank Reviewer #2 for their insightful and helpful comments and feedback. Their Review guided key clarifying experiments and additions to the Discussion and Methods. To summarize, we added new data to Supplementary Figure 1 to characterize distinct gene expression in our different polarized macrophage populations, showed in Supplementary Figure 2 that serum shock independently induces cAMP and Icer, discussed the limitations of the artificial polarization models more clearly, and updated our Methods to better explain how macrophages were isolated from the peritoneum. We also quantified multiple immunoblots of pCREB, provided clarity in the Methods and Reviewer-only data on how our protein-extraction protocol isolates nuclear protein, better introduced the BMAL1-KO mouse model, and showed in Supplementary Figure 6 that low pH can induce oscillations in the absence of a serum shock.

      Major points of criticism: 1. Nine main figures include different experimental models on a non-systematic manner in the manuscript, and only literature-based correlation is used to link the results each other. The authors used in vitro BMDM and peritoneal cell-based model systems to study the effects of IL4+IL13, IFNg+LPS, low pH, sodium-lactate, adenylate cyclase inhibitors on the circadian clock of macrophages. The link between these microenvironment conditions of the cells is still correlative with the tumor microenvironment: publicly available data were used to correlate the increased expression level of cAMP-activated signaling events with the presence of acidic pH of tumor microenvironment. Notably, the cell signaling messenger molecule cAMP is produced by not only low extracellular pH by activated GPCRs, but also starvation of the cell. The starvation is also relevant to this study, since the BMDM used in the in vitro culture system were starving for 24 hours before the measurement of Per2-Luc expression to monitor circadian rhythm.

              We agree with the important point that Reviewer #2 makes that our synchronization protocol of serum starvation followed by serum shock can impact the cAMP signaling pathway. Indeed, it has previously been shown that serum shock induces phosphorylation of CREM in rat fibroblasts, which is indicative of signaling through the cAMP pathway. To address this point, we have added a schematic of our synchronization protocol to Supplementary Figure 2B for additional clarity. We have also performed additional experiments to test whether cAMP signaling is induced in macrophages by our synchronization protocol. For this, we assessed downstream targets of the cAMP signaling pathway, Icer and pCREB, after serum starvation but before serum shock, and at several time points post-treatment with serum shock (Supplementary Figures 2D,E). We observed that Icer and phosphorylation of Creb are induced rapidly in macrophages upon exposure to serum shock, as early as 10 minutes for pCREB and 1 hour post-exposure for Icer. Notably, this signaling is transient and rapidly returns to baseline, with pCREB levels fully returned to baseline by 2 hours post-treatment, at which time media is replaced and the experiment begins (CT 0). These data, shown below, have been added to Supplementary Figure 2 and a discussion of these data has been added to the manuscript - please see the modified text below.
      

      "The synchronization protocol we use to study circadian rhythms in BMDMs involves a 24-hour period of serum starvation followed by 2 hours of serum shock. It has previously been shown that serum shock can induce signaling through the cAMP pathway in rat fibroblasts[98]. To determine whether the synchronization protocol impacts cAMP signaling in macrophages, we harvested macrophages before and after serum shock. We then assessed Icer expression and phosphorylation of cyclic AMP-response element binding protein (CREB), which occur downstream of cAMP and have been used as readouts to assess induction of cAMP signaling in macrophages[29, 96, 100]. Serum shock of macrophages following serum starvation led to rapid phosphorylation of CREB and Icer expression that quickly returned to baseline (Supplementary Figure 2D,E). This indicates that serum starvation followed by serum shock in the synchronization protocol we use to study circadian rhythms in BMDMs induces transient signaling through the cAMP signaling pathway. "

      The definition of pre-resolution macrophages (MF) used across the manuscript could be argued. The authors defined BMDM polarized with IL-4 and IL-13 as pre-resolution MF. Resolution is followed by inflammation, but the IL-4 secretion does not occur in every inflammatory setting. Moreover, IL-4 and IL-13 are secreted during specific tissue environment and immunological settings involving type 2 inflammation or during germinal center reactions of the lymph nodes. • What are the characteristics of pre-resolution macrophages (MF)? The authors indicated that IL-4 and IL-13 cytokines were used to model the pre-resolution macrophages. In which pathological context are these cytokines produced and induce pre-resolution macrophages? IL-4 polarized BMDM can also produce pro-inflammatory protein and lipid mediators as compared to LPS-stimulated BMDM, and IL-4 polarized BMDM still have potent capacity to recruit immune cells and to establish type 2 inflammation.

      • The authors showed Arg1 and Vegfa qPCR data from BMDM only. Based on the literature, these MFs are anti-inflammatory cells particularly. Resolution-related MFs followed by acute inflammation are a specific subset of MFs, and the phenotype of pre-resolution MF should be described, referred, and measured specifically.

      We thank Reviewer #2 for bringing up this important point that clarity is required in describing our in vitro macrophage models. We chose the most commonly used models of in vitro macrophage polarization in the tumor immunology field, M2 (IL-4+IL-13) and M1 (IFNγ+LPS). These polarization conditions have been used for over two decades in the field, and have been well-characterized to drive a pro-inflammatory (for M1) and pro-resolution or anti-inflammatory (for M2) macrophage phenotype (Murray 2017 Annu Rev Phys). Each of these cell states have similarities in phenotype to pro-inflammatory and pro-resolution (pro-tumorigenic) macrophages found in tumors. In fact, in the literature, pro-inflammatory and pro-resolution TAMs will frequently be categorized as "M1" or "M2", respectively, even though this is a gross oversimplification (Ding 2019 J Immunol, Garrido-Martin 2020 J Immunother Cancer).

      As Reviewer #2 points out, IL-4 and IL-13 play a role in inflammatory settings, mediating protective responses to parasites and pathological responses to allergens. Importantly, IL-4 and IL-13 are also key regulators and effectors of resolution and wound repair (Allen 2023 Annu Rev Immunol). In line with this, M2 macrophages show many of the characteristics of pro-resolution programming in their gene expression profile, expressing genes associated with wound healing (ex. Vegf) and immunoregulation (ex. Arg1) (Mantovani 2013 J Pathol). These cells have frequently been used as a model for studying TAMs in vitro, due to the similarity in pro-resolution programming that is dysregulated/hijacked in TAMs (Biswas 2006 Blood). M2 macrophages have also been referred to as anti-inflammatory, and this is in line with their role in the type 2 response driven by IL-4 and IL-13, as this is primarily a response induced by allergy or parasites where tissue damage drives an anti-inflammatory and pro-resolution phenotype in macrophages (Pesce 2009 Plos Pathogens and Allen 2023 Annu Rev Immunol).

      We do not assert that these in vitro models recapitulate the macrophage polarization cycle that Reviewer #2 astutely describes, and indeed, stimuli polarizing macrophages in tumor are much more diverse and complex (Laviron 2022 Cell Rep). We also fully agree with Reviewer #2 that, while IL4 and IL13 may exist in the tumor and be secreted by Th2 CD4 T cells (see Shiao 2015 Cancer Immunol Res), there may be multiple reasons why macrophages may be polarized to a pro-resolution, M2-like state in a tumor (in fact, exposure to low pH and lactate each independently do this, as we show in Supplementary Figure 2 and Figure 4, and was previously shown in Jiang 2021 J Immunol and Colegio 2014 Nature). Nonetheless, using the well-described M1 and M2 in vitro models allows our findings to be directly comparable to the vast literature that also uses these models, and to understand how distinct polarization states respond to low pH.

      We fully agree with Reviewer #2 that these cells must be defined more clearly in the text. We have taken care to discuss the limitations of using in vitro polarization models to study macrophages in our Limitations of the Study section. To better address Reviewer #2's concern, we have more thoroughly introduced the M2 macrophages as a model, and are clear that that these are type 2-driven macrophages that share characteristics of pro-resolution macrophages. We have also added additional citations to the manuscript, including those highlighted above in our response. Finally, we have expanded our panel to better characterize the IL-4/IL-13 stimulated macrophages using more markers that have been characterized in the literature, in line with both Reviewer #2's comments and that of Reviewer #1 and Reviewer #3. Please see the updated data and text, below.

      "As macrophages are a phenotypically heterogeneous population in the TME, we first sought to understand whether diversity in macrophage phenotype could translate to diversity in circadian rhythms of macrophages. To this end, we used two well-established in vitro polarization models to study distinct macrophage phenotypes[5, 60-63]. For a model of pro-inflammatory macrophages, we stimulated macrophages with IFNγ (interferon γ) and LPS (lipopolysaccharide) to elicit a pro-inflammatory phenotype[60, 64]. These macrophages are often referred to as 'M1' and are broadly viewed as anti-tumorigenic, and we will refer to them throughout this paper as pro-inflammatory macrophages[65, 66]. For a model at the opposite end of the phenotypic spectrum, we stimulated macrophages with IL-4 and IL-13[60, 67]. While these type 2 stimuli play a role in the response to parasites and allergy, they are also major drivers of wound healing; in line with this, IL-4 and IL-13-stimulated macrophages have been well-characterized to adopt gene expression profiles associated with wound-healing and anti-inflammatory macrophage phenotypes[68-71]. As such, these macrophages are often used as a model to study pro-tumorigenic macrophages in vitro and are often referred to as 'M2' macrophages; throughout this paper, we will refer to IL-4 and IL-13-stimulated macrophages as pro-resolution macrophages[66, 72, 73]. Consistent with previous studies, we found that genes associated with anti-inflammatory and pro-resolution programming characteristic of IL-4 and IL-13-stimulated macrophages such as Arg1, Retnla, Chil3 (Ym1), Clec10a (MGL1), and Mrc1 (CD206) were induced in IL-4 and IL-13-stimulated macrophages, but not IFNγ and LPS-stimulated macrophages. In contrast, genes associated with pro-inflammatory activity characteristic of IFNγ and LPS-stimulated macrophages such as Nos2 (iNOS), Tnfa, Il1b, and Il6 were induced in IFNγ and LPS-stimulated macrophages, but not IL-4 and IL-13-stimulated macrophages (Supplementary Figure 1)[28, 30, 65, 71, 74, 75]. This indicates that macrophages stimulated with IL-4 and IL-13 were polarized toward a pro-resolution phenotype, while macrophages stimulated with IFNγ and LPS were polarized toward a pro-inflammatory phenotype.

      In the Limitations of the Study section, we now write the following:

      "Our observations of rhythms in macrophages of different phenotypes are limited by in vitro polarization models. It is important to note that while our data suggest that pro-inflammatory macrophages have suppressed rhythms and increased rate of desynchrony, it remains unclear the extent to which these findings apply to the range of pro-inflammatory macrophages found in vivo. We use IFNγ and LPS co-treatment in vitro to model a pro-inflammatory macrophage phenotype that is commonly referred to as 'M1', but under inflammatory conditions in vivo, macrophages are exposed to a variety of stimuli that result in a spectrum of phenotypes, each highly context-dependent. The same is true for for 'M2'; different tissue microenvironment are different and pro-resolution macrophages exist in a spectrum."

      The authors used IFNg and LPS, or IL-4 and IL-13 and co-treatments to polarize BMDM in to type 1 (referred as pro-inflammatory MF) and type 2 (referred as pre-resolution MF) activation state. The comparison between these BMDM populations has limitations, since LPS induces a potent inflammatory response in MF. The single treatment with MF-polarizing cytokines enable a more relevant comparison to study the circadian clock in classically and alternatively activated MF.

      We thank Reviewer #2 for bringing up this important point to provide additional clarity on our polarization conditions. The use of IFNγ and LPS to polarize macrophages toward a pro-inflammatory, M1 phenotype, and the use of IL-4 an IL-13 to polarize macrophages toward a pro-resolution, M2 phenotype have been commonly used for over two decades, and thus are well-characterized in the literature (please see Murray 2017 Annu Rev Phys for an extensive review on the history of these polarization models, as well as Hörhold 2020 PLOS Computational Biology, Binger 2015 JCI, McWhorter 2013 PNAS, Ying 2013 J Vis Exp for more recent studies using these models). The use of LPS alone or in combination with IFNγ, and IL-13 along with IL-4, was introduced in 1998 (Munder 1998 J Immunol). This approach was originally designed to mimic what could happen when macrophages were exposed to CD4+ Th1 cells, which produce IFNγ, or Th2 cells, which produce IL-4 and IL-13 (Munder 1998 J Immunol, Murray 2017 Annu Rev Phys). As Reviewer #2 points out, these stimuli induce potent responses, driving macrophages to adopt pro-inflammatory or pro-resolution/anti-inflammatory phenotypes that are two extremes at opposite ends of the spectrum of macrophage phenotypes (Mosser 2008 Nat Rev Immunol). Since our goal was to study rhythms of distinct macrophage phenotypes in vitro, and how TME-associated conditions such as acidic pH and lactate affect their rhythms, these cell states were appropriate for our questions. Thus, the polarization models used in this paper allowed us to achieve this goal. We include a section in the Discussion on the limitations of in vitro polarization models.

      "A critical question in understanding the role of circadian rhythms in macrophage biology is determining how different polarization states of macrophages affect their internal circadian rhythms. This is especially important considering that tumor-associated macrophages are a highly heterogeneous population. Our data indicate that compared to unstimulated macrophages, rhythms are enhanced in pro-resolution macrophages, characterized by increased amplitude and improved ability to maintain synchrony; in contrast, rhythms are suppressed in pro-inflammatory macrophages, characterized by decreased amplitude and impaired ability to maintain synchrony (Figure 1). These agree with previously published work showing that polarizing stimuli alone and in combination with each other can alter rhythms differently in macrophages[80, 81]. In a tumor, macrophages exist along a continuum of polarization states and phenotypes[18-21, 24]. Thus, while our characterizations of rhythms in in vitro-polarized macrophages provide a foundation for understanding how phenotype affects circadian rhythms of macrophages, further experiments will be needed to assess macrophages across the full spectrum of phenotypes. Indeed, alteration of rhythms may be just as highly variable and context-dependent as phenotype itself."

      There are missing links between the results of showing the circadian rhythm of polarized BMDM, sodium-lactate treated BMDM, and tumor growth. Specifically, do the used pancreatic ductal adenocarcinoma cells produce IL-4 and sodium-lactate? In the LLC-based experimental in silico analysis of tumors, the LLC do not produce IL-4.

      Reviewer #2 raises important points about the source of lactate and IL-4 in tumors as relevance for our investigation of how these factors can alter rhythms in macrophages. Tumor-infiltrating Th2 CD4 T cells are potential sources of IL-4 and IL-13 in the tumor (see Shiao 2015 Cancer Immunol Res). Various cells in the tumor can produce lactate. We discuss this in both the Introduction and the Results: poor vascularization of tumors results in hypoxia areas, where cells are pushed toward glycolysis to survive and thus secrete increased glycolytic waste products such as protons and lactate. As lactate is lactic acid, ionized it is sodium l-lactate.

      How can the circadian rhythm affect the function of BMDM? The Authors should provide evidence that circadian rhythm affects the function of polarized MF.

      We agree with Reviewer #2 that the next step is to determine how altered rhythms influence function of macrophages. This will be the topic of future work, but is outside the scope of this paper. Our contribution with this paper is providing the first evidence that rhythms are altered in the TME and the TME-associated conditions can alter rhythms in macrophages. We have added what is currently known about how circadian rhythms influence macrophages function to the discussion section to facilitate a conversation about this important future direction. Please see the updated text below.

      "Considering our observations that conditions associated with the TME can alter circadian rhythms in macrophages, it becomes increasingly important to understand the relevance of macrophage rhythms to their function in tumors. It has been shown that acidic pH and lactate can each drive functional polarization of macrophages toward a phenotype that promotes tumor growth, with acidic pH modulating phagocytosis and suppressing inflammatory cytokine secretion and cytotoxicity[28, 30, 93]. However, how the changes in circadian rhythms of macrophages driven by these conditions contributes to their altered function remains unknown. Current evidence suggests that circadian rhythms confer a time-of-day-dependency on macrophage function by gating the macrophage response to inflammatory stimuli based on time-of-day. As such, responses to inflammatory stimuli such as LPS or bacteria are heightened during the active phase while the inflammatory response is suppressed during the inactive phase. An important future direction will be to determine how changes in circadian rhythms of macrophages, such as those observed under acidic pH or high lactate, influences the circadian gating of their function."

      In Figure 3, the authors show data from peritoneal cells. The isolated peritoneal cells are not pure macrophage populations. Based on the referred article in the manuscript, the peritoneal cavity contains more then 50% of lymphocytes, and the myeloid compartment contains 80% macrophages.

      Reviewer #2 raises important concerns about the purity of the peritoneal population used in our experiments. We enrich for peritoneal macrophages from the peritoneal exudate cells by removing non-adherent cells in culture. This is described in our Methods section and is a method of isolation that is commonly used in the field, as lymphocytes are non-adherent. In addition to the source cited in the paper within our Methods section (Goncalves 2015 Curr Prot Immunol), please see Layoun 2015 J Vis Exp, de Jesus 2022 STAR Protocols, and Harvard HLA Lab protocol - macrophages enriched in this manner have been shown to be over 90% pure. We have modified our Methods section to make this clear, and added the additional references in this response to this section of our Methods. Please see the modified text below.

      "Peritoneal exudate cells were harvested from mice as previously published[137]. To isolate peritoneal macrophages, peritoneal exudate cells were seeded at 1.2*106 cells/mL in RPMI/10% HI FBS supplemented with 100U/mL Penicillin-Streptomycin and left at 37⁰C for 1 hour, after which non-adherent cells were rinsed off[136]. Isolation of peritoneal macrophages using this method has been shown to yield a population that is over 90% in purity[138, 139]. Peritoneal macrophages were then cultured in Atmospheric Media at pH 7.4 or 6.5 with 100μM D-luciferin, and kept at 37⁰C in atmospheric conditions."

      The figure legend of Figure 3 describes the effects of pH on the circadian rhythm of bone marrow-derived macrophages ex vivo. Peritoneal macrophages involve tissue resident peritoneal macrophages with yolk sac and fetal liver origin, and also involve small peritoneal MF with bone marrow origin. The altered description of results and figure legends makes confusion.

      We are very grateful to Reviewer #2 for pointing out our typo. We have fixed the caption of Figure 3 to properly describe the data as "peritoneal macrophages ex vivo".

      In Figure 6C, one single Western blot is shown with any quantification. The authors should provide data of the relative protein level of p-CREB from at least 3 independent experiments. In the Western-blot part of the methods, the authors described that the pellet was discarded after cell lysis. The p-CREB is the activated form of the transcription factor CREB and there is increased binding to the chromatin to regulate gene expression. By discarding the pellet after cell lysis, the chromatin-bond p-CREB could be also removed at the same time.

      We thank Reviewer 2 for bringing up this point. We agree that quantification is an important aspect of western blot. We have repeated the experiment again for n=3 and provide quantification of pCREB normalized to total protein. We have added these data, shown below, to Figure 5.

      Reviewer #2 also expressed concern that we may not be capturing all of the CREB due to nuclear localization and chromatin binding. We specifically chose the lysis buffer M-Per, which is formulated to lyse the nucleus and solubilize nuclear and chromatin-bound proteins. To demonstrate this, we show in the below Figure to the Reviewer that the nuclear protein p85 is solubilized and readily detectable by western blot using our protein extraction method.

      We have also added an additional sentence in the Methods section for clarity - please see the modified text below.

      "Cells were lysed using the M-Per lysis reagent (Thermo Scientific, CAT#78501), supplemented with protease and phosphatase inhibitor cocktail (1:100; Sigma, CAT#PPC1010) and phosphatase inhibitor cocktail 2 (1:50; Sigma, CAT#P5726), with 200μM deferoxamine (Sigma, CAT#D9533). M-Per is formulated to lyse the nucleus and solubilize nuclear and chromatin-bound proteins, allowing isolation of nuclear proteins as well as cytosolic proteins. Lysates were incubated on ice for 1 hour, then centrifuged at 17,000 xg to pellet out debris; supernatant was collected."

      It is confusing that adenylate-cyclase inhibitor MDL-12 elevated the phospho-CREB levels in BMDM. How can the authors exclude any other inducers of CREB phosphorylation?

      We agree with Reviewer #2 that it is surprising pCREB was elevated with MDL-12 treatment alone, and we do indeed think that there are other pathways contributing to this. We have addressed this point in the Discussion - please see the text below.

      "The mechanism through which acidic pH can modulate the circadian clock in macrophages remains unclear. Evidence in the literature suggests that acidic pH promotes a pro-resolution phenotype in macrophages by driving signaling through the cAMP pathway[29]. It has previously been shown that cAMP signaling can modulate the circadian clock[99]. However, our data indicated that cAMP signaling was not fully sufficient to confer pH-mediated changes in circadian rhythms of macrophages (Figure 5A,B). Treatment with MDL-12, commonly known as an inhibitor of adenylyl cyclase[29, 117], resulted in suppression of pH-induced changes in amplitude of circadian rhythms but did not inhibit signaling through the cAMP signaling pathway (Figure 5C,D). While MDL-12 is commonly used as an adenylyl cyclase inhibitor, it has also been documented to have inhibitory activity toward phosphodiesterases (PDEs) and the import of calcium into the cytosol through various mechanisms[118, 119]. This is of particular interest, as calcium signaling has also been shown to be capable of modulating the circadian clock[120]. Furthermore, while acid-sensing through GPCRs have been the most well-characterized pathways in macrophages, there remain additional ways in which acidic pH can be sensed by macrophages such as acid-sensing ion channels[121, 122]. Further work is required to understand the signaling pathways through which pH can influence macrophage phenotype and circadian rhythms."

      It is described in the methods that BMDM were starving for 24 hours in serum-free culture media followed by serum shock (50% FBS). The cAMP production can be induced during cell starvation which should be considered for the data representation.

      We appreciate that Reviewer #2 points out that our synchronization protocol of serum starvation followed by serum shock may impact the cAMP signaling pathway in macrophages, as serum shock has been shown to induce pCREB, a downstream mediator of cAMP signaling, in rat fibroblasts. Indeed, we show in additional experiments performed (in response to Reviewer #2's major comment 1) evidence that cAMP signaling is induced in macrophages following the serum shock phase of our synchronization protocol, as indicated by elevation of Icer and pCREB. As we note above, this induction is transient and returns to baseline by 2 hours post-serum shock, the time at which we replace media and begin our experiments (CT 0).

      Despite the transient nature of cAMP induction by our synchronization protocol, we agree wholeheartedly with Reviewer #2 that this must be considered in light of our experimental system in which we are studying the effect of acidic pH on circadian rhythms of macrophages, which in itself induces signaling through the cAMP signaling pathway. To address Reviewer #2's point, we have performed experiments in which we culture unstimulated BMDMs in neutral pH 7.4 or acidic pH 6.5, without prior serum starvation and serum shock (i.e. we do not submit these BMDMs to the synchronization protocol). We then observed circadian rhythms of Per2-Luc by LumiCycle to determine whether acidic pH alters circadian rhythms of BMDMs in the absence of prior serum starvation followed by serum shock. Similar to our observations in Figure 2, circadian rhythms of macrophages at pH 6.5 had increased amplitude and shortened period compared to rhythms of macrophages at pH 7.4. This indicates that pH-driven changes in circadian rhythms observed in our system are not due to the synchronization protocol. The data, shown below, have been placed in a new Supplementary Figure 6, and a discussion of these results has been added to the Results section - please see the updated text below.

      "As acidic pH induces signaling through the cAMP pathway, we sought to determine whether acidic pH independently contributed to the pH-driven changes in circadian rhythms we observe in BMDMs. To test this, we omitted the synchronization step and observed BMDM rhythms by LumiCycle when cultured in neutral pH 7.4 or acidic pH 6.8 or pH 6.5 (Supplementary Figure 6). Circadian rhythms of BMDMs cultured at pH 6.5 exhibited similar changes as previously observed, with enhanced amplitude and shortened period relative to BMDMs at pH 7.4. This indicates pH-driven changes observed in circadian rhythms of BMDMs occur in the absence of prior serum starvation and serum shock. "As acidic pH independently induces signaling through the cAMP pathway, we sought to determine whether acid pH could also independently contribute to the pH-driven changes in circadian rhythms we observe in BMDMs. To test this, we omitted the synchronization step and observed BMDM rhythms by LumiCycle when cultured in neutral pH 7.4 or acidic pH 6.8 or pH 6.5 (Supplementary Figure 6). Circadian rhythms of BMDMs cultured at pH 6.5 exhibited similar changes as previously observed, with enhanced amplitude and shortened period relative to BMDMs at pH 7.4. This indicates pH-driven changes observed in circadian rhythms of BMDMs occur in the absence of prior serum starvation and serum shock."

      How can the authors explain and prove that the wild type and Bmal1-KO BMDM co-injected with pancreatic cancer cells subcutaneously survive, present, and have effector functions at the same extent in the subcutaneous tissue, before and during tumor growth (Figure 9)? In other words, what kind of MF-derived parameters could be modified by disrupting the circadian rhythm of MF during tumor development? The production of MF-derived regulatory enzymes, cytokines, growth factors are affected by the disrupted circadian clock in MF?

              Review #2 poses the very important question of why we see differences in tumor growth in our co-injection model, and what might be driving it. Of note, co-injection models of tumor growth are commonly used to determine macrophage-specific roles in tumor growth (Colegio 2014 Nature, Mills 2019 Cell Rep, Lee 2018 Nat Comm). We observed that tumor growth is altered when macrophages with disrupted circadian rhythms (BMAL1 KO) are co-injected compared to when macrophages with intact circadian rhythms (WT) are co-injected in a murine model of pancreatic cancer using KCKO cells. Our observation is supported by a previously published paper in which they used a co-injection model of melanoma, which we cite in the manuscript(Alexander 2020 eLife). What drives this difference in tumor growth remains an open question that is the subject of future work and is outside the scope of this paper, which focuses on our discovery that factors associated with the tumor microenvironment can alter circadian rhythms in macrophages. We have included a discussion on what is currently known about how circadian rhythms alter macrophage function, acknowledging that we have yet to answer these important questions and identifying it as interest for future work. Please see the text below.
      

      "Considering our observations that conditions associated with the TME can alter circadian rhythms in macrophages, it becomes increasingly important to understand the relevance of macrophage rhythms to their function in tumors. It has been shown that acidic pH and lactate can each drive functional polarization of macrophages toward a phenotype that promotes tumor growth, with acidic pH modulating phagocytosis and suppressing inflammatory cytokine secretion and cytotoxicity[28, 30, 93]. However, how the changes in circadian rhythms of macrophages driven by these conditions contributes to their altered function remains unknown. Current evidence suggests that circadian rhythms confer a time-of-day-dependency on macrophage function by gating the macrophage response to inflammatory stimuli based on time-of-day. As such, responses to inflammatory stimuli such as LPS or bacteria are heightened during the active phase while the inflammatory response is suppressed during the inactive phase. An important future direction will be to determine how changes in circadian rhythms of macrophages, such as those observed under acidic pH or high lactate, influences the circadian gating of their function. Data from our lab and others suggest that disruption of the macrophage-intrinsic circadian clock accelerates tumor growth, indicating that circadian regulation of macrophages is tumor-suppressive in models of PDAC (our work) and melanoma [109]. This agrees with complementary findings that behavioral disruption of circadian rhythms in mice (through chronic jetlag) disrupts tumor macrophage circadian rhythms and accelerates tumor growth[56]. It remains unclear whether this is through the pro-tumorigenic functions of macrophages such as extracellular matrix remodeling or angiogenesis, through suppression of the anti-tumor immune response, or a combination of both functions. Further work will be needed to tease apart these distinctions."

      Minor points of criticism: 1. The figure legends of the graphs and diagrams are missing in Figure 2D,E,F

      We thank Reviewer #2 for pointing out that figure legends were missing. We have added legends for Figure 2D,E,F.

      The BMAL1-based in vivo murine model of circadian rhythm is not introduced in the manuscript.

      We thank Reviewer #2 for bringing to our attention that the BMAL1 KO macrophage model was not well-introduced in the manuscript. To address this point, we have modified the text to better introduce this model. Please see the modified text below.

      "As a positive control for circadian clock disruption, we used data from BMAL1 KO peritoneal macrophages [44]. BMAL1 KO macrophages have a genetic disruption of the circadian clock due to the loss of Bmal1, the central clock gene. As a result, circadian rhythms of BMAL1 KO macrophages are disrupted, lacking rhythmicity and downstream circadian regulation of macrophage function (Supplementary Figure 8)[45, 54]. "As a positive control for circadian clock disruption, we used data from BMAL1 KO peritoneal macrophages [44]. BMAL1 KO macrophages have a genetic disruption of the circadian clock due to the loss of Bmal1, the central clock gene. As a result, circadian rhythms of BMAL1 KO macrophages are disrupted, lacking rhythmicity and downstream circadian regulation of macrophage function (Supplementary Figure 8)[45, 54]."__ __

      Significance

      Knudsen-Clark et al. showed that the circadian rhythm of bone marrow-derived macrophages (BMDM) can be affected by polarization stimuli, pH of the microenvironment, and by the presence of sodium-lactate. Mechanistically, the acidic pH of cell microenvironment is partly regulated by intracellular cAMP-mediated signaling events in BMDM. The authors also showed that the circadian clock of peritoneal macrophages is also modified by the pH of the cell microenvironment. Using publicly available data, the authors showed that the circadian rhythm of tumor-associated macrophages is similar to that of Bmal1-KO peritoneal macrophages. In a murine model of pancreatic cancer, the authors showed that the tumor growth is accelerated in C57BL/6 mice co-injected with cancer cells and Bmal1-KO BMDM as compared to mice co-injected with cancer cell and wild type BMDM.

      We are grateful to Reviewer #2 for their very helpful comments and suggestions, which we believe have greatly enhanced the clarity and reproducibility of this manuscript.

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      Review for Knudsen-Clark et al.

      "Circadian rhythms of macrophages are altered by the acidic pH of the tumor microenvironment"

      Knudsen-Clark and colleagues explore the impact of TME alterations on macrophage circadian rhythms. The authors find that both acidic pH and lactate modulate circadian rhythms which alter macrophage phenotype. Importantly, they define circadian disruption of tumor-associated macrophages within the TME and show that circadian disruption in macrophages promotes tumor growth using a PDAC line. This represents an important understanding of the crosstalk between cancer cells and immune cells as well as the understanding of how the TME disrupts circadian rhythms. The study is well-done, however, authors need to address several important points below.

      We thank Reviewer #3 for their in-depth and insightful comments and suggestions, which have resulted in a much-improved manuscript. We were pleased that Reviewer #3 found the work to be "an important study that is well-done" and that it "represents an important understanding of the crosstalk between cancer cells and immune cells as well as the understanding of how the TME disrupts circadian rhythms.". In response to Reviewer #3's comments, we have added several new key experiments and changes to the text. To summarize, we added new data to Supplementary Figure 1 to better characterize our macrophage polarization states, showed in Figure 3 that low pH affects peritoneal macrophage circadian gene expression in a similar fashion as bone marrow-derived macrophages, added new data in Figure 4 to show how lactate and low pH affect circadian gene expression over time, and new computational analysis to Figures 6, 7, and Supplementary Figure 9 to probe circadian gene covariance from publicly available data. We also made several key additions to the Discussion to discuss the functional implications of macrophage circadian rhythm disruption by low pH and potential mechanisms of this disruption. Finally, at the request of Reviewer #3, we consolidated several existing Figures and added new data, where appropriate, to existing figures, and we worked to describe new findings succinctly.

      Major comments:

      • In Figures 3 and 4, the authors can include additional clock genes that can be run by qPCR. This was done in Figure 2 and was a nice addition to the data.

      We agree with Reviewer #3's suggestion that an analysis of clock gene expression at the mRNA level would enhance our data in Figures 3 and 4. To address this point, we have performed short time course experiments to assess circadian clock gene expression over time in BMDMs cultured with or without lactate at neutral or acidic pH (for Figure 4). In line with the difference in circadian rhythms of Per2-Luc levels between BMDMs cultured in the presence or absence of lactate which we observed by Lumicycle analysis, we measured changes in expression of the circadian clock genes Per2, Nr1d1, and Cry1 between macrophages cultured with 25 mM sodium-L-lactate compared to those cultured with 0 mM sodium-L-lactate at pH 6.5. We have added these data, shown below, to Figure 4, and updated the manuscript accordingly to discuss these results. Please see below for the new Figure Panel and modified text.

      "Lactate was also observed to alter expression of the circadian clock genes Per2, Cry1, and Nr1d1 over time in BMDMs cultured at pH 6.5, while having more subtle effects at pH 7.4 (Figure 4C). Notably, lactate blunted the effect of pH 6.5 on Cry1 expression, while enhancing the effect of low pH on Nr1d1 expression. In all, these data indicate that concentration of lactate similar to that present in the TME can influence circadian rhythms and circadian clock gene expression of macrophages."

      As an additional measure to address Reviewer #3's point about Figure 3 (peritoneal macrophages), we have compared expression of circadian clock genes in peritoneal macrophages cultured at neutral pH 7.4 or acidic pH 6.8 for 24 hours using a publicly available RNA-seq data set from Jiang 2021 J Immunol (GSE164697). In line with previous observations in macrophages cultured under acidic compared to neutral pH conditions, including the clock gene expression data from Figure 2 in BMDMs and the Per2-Luc levels observed in peritoneal macrophages in Figure 3, we found that peritoneal macrophages exhibited differences in expression of circadian clock genes when cultured at acidic pH 6.8 compared to neutral pH 7.4. We have added these data, shown below, as Figure 3B, and have updated the manuscript accordingly - please see below for the new Figure panel and modified text.

      "To test whether pH-driven changes in circadian rhythms of peritoneal macrophages were reflected at the mRNA level, we compared expression of circadian clock genes in peritoneal macrophages cultured at neutral pH 7.4 or acidic pH 6.8 for 24 hours using publicly available RNA-sequencing data [30]. In line with altered circadian rhythms observed by Lumicycle, peritoneal macrophages cultured at pH 6.8 expressed different levels of circadian clock genes than peritoneal macrophages culture at pH 7.4 (Figure 3B). The trends in changes of gene expression in peritoneal macrophages cultured at pH 6.8 matched what we observed in BMDMs, where low pH generally led to higher levels of circadian clock gene expression (Figure 2D-F). These data support our observations by LumiCycle and indicate that acidic pH drives transcriptional changes in multiple components of the circadian clock. In all, these data are evidence that pH-dependent changes in circadian rhythms are relevant to in vivo-differentiated macrophages."

      We have also updated the Methods section appropriately

      "FASTQ files from a previously published analysis of peritoneal macrophages cultured under neutral pH 7.4 or acidic pH 6.8 conditions were downloaded from NCBI GEO (accession #GSE164697) [30]."

      2) There are far too many figures with minimal data in each. Please consolidate the figures. For example, Figures 1-3 can be fully combined, Figures 4-6 can be combined, and Figures 7-8 can be combined. Additionally, it is unclear if Figure 5 needs to be in the main, it can be moved to the supplement.

      We appreciate the preference of Reviewer #3 to see some of the figures consolidated. We have combined Figures 5 and 6 into a single new Figure 5. Additionally, we have added new data from revisions to current figures to increase the amount of data in each figure and minimize the amount of new figures generated. In all, despite the large amount of new data added to the paper in response to Reviewer comments and suggestions (including additional data in Figure 4 and new Figures 6 and 8), our manuscript now contains 10 main Figures, only one more than the initial submission.

      3) The observation that conditions like pH and lactate alter macrophage phenotype and rhythmicity are important. However, macrophage phenotype via gene expression does not always correlate to function. It is important for authors to demonstrate the effect of pH or lactate on macrophage function. This can be done using co-culture assays with cancer cells. If these experiments cannot be performed, it is suggested that authors discuss these limitations and consideration in the discussion.

      Reviewer #3 correctly points out that changes in phenotype does not always correlate to changes in function. Others have shown that acidic pH and lactate can each alter macrophage phenotype, and also alter macrophage function and the ability to promote tumor growth (please see El-Kenawi 2019 Br J Cancer, Jiang 2021 J Immunol, Colegio 2014 Nature). How changes in rhythms influence macrophage function remains unknown and we agree with Reviewer #3 that this is an important future direction, We have added a section in the Discussion to facilitate the discussion of this important future direction. Please see the text below.

      "Considering our observations that conditions associated with the TME can alter circadian rhythms in macrophages, it becomes increasingly important to understand the relevance of macrophage rhythms to their function in tumors. It has been shown that acidic pH and lactate can each drive functional polarization of macrophages toward a phenotype that promotes tumor growth, with acidic pH modulating phagocytosis and suppressing inflammatory cytokine secretion and cytotoxicity[28, 30, 93]. However, how the changes in circadian rhythms of macrophages driven by these conditions contributes to their altered function remains unknown. Current evidence suggests that circadian rhythms confer a time-of-day-dependency on macrophage function by gating the macrophage response to inflammatory stimuli based on time-of-day. As such, responses to inflammatory stimuli such as LPS or bacteria are heightened during the active phase while the inflammatory response is suppressed during the inactive phase. An important future direction will be to determine how changes in circadian rhythms of macrophages, such as those observed under acidic pH or high lactate, influences the circadian gating of their function."

      4) On line 119-122, authors describe a method for polarization of macrophages. They then reference one gene to confirm each macrophage polarization state. To more definitively corroborate proper macrophage polarization, authors should perform qPCR for additional target genes that are associated with each phenotype. For example, Socs3, CD68, or CD80 for M1, and CD163 or VEGF for M2. Alternatively, the authors should cite previous literature validating this in vitro polarization model.

      We appreciate Reviewer #3's suggestion to better the phenotypic identity of our polarization models with additional canonical markers. To address this point, we have expanded our panel using transcriptional markers commonly used in the murine polarization model for M1 macrophages such as Tnfa, Il6, and Il1b. As discussed in the response to Reviewer #1's minor point 5 and Reviewer #2's major point 2, we have also expanded our panel to include additional markers for M2 such as Vegf, Retnla, Ym1, Mgl1, and CD206. We have added these new data to Supplementary Figure 1. Finally, we have added additional citations for the in vitro polarization models. Please see the modified text and new data, below.

      "As macrophages are a phenotypically heterogeneous population in the TME, we first sought to understand whether diversity in macrophage phenotype could translate to diversity in circadian rhythms of macrophages. To this end, we used two well-established in vitro polarization models to study distinct macrophage phenotypes[5, 60-63]. For a model of pro-inflammatory macrophages, we stimulated macrophages with IFNγ (interferon γ) and LPS (lipopolysaccharide) to elicit a pro-inflammatory phenotype[60, 64]. These macrophages are often referred to as 'M1' and are broadly viewed as anti-tumorigenic, and we will refer to them throughout this paper as pro-inflammatory macrophages[65, 66]. For a model at the opposite end of the phenotypic spectrum, we stimulated macrophages with IL-4 and IL-13[60, 67]. While these type 2 stimuli play a role in the response to parasites and allergy, they are also major drivers of wound healing; in line with this, IL-4 and IL-13-stimulated macrophages have been well-characterized to adopt gene expression profiles associated with wound-healing and anti-inflammatory macrophage phenotypes[68-71]. As such, these macrophages are often used as a model to study pro-tumorigenic macrophages in vitro and are often referred to as 'M2' macrophages; throughout this paper, we will refer to IL-4 and IL-13-stimulated macrophages as pro-resolution macrophages[66, 72, 73]. Consistent with previous studies, we found that genes associated with anti-inflammatory and pro-resolution programming characteristic of IL-4 and IL-13-stimulated macrophages such as Arg1, Retnla, Chil3 (Ym1), Clec10a (MGL1), and Mrc1 (CD206) were induced in IL-4 and IL-13-stimulated macrophages, but not IFNγ and LPS-stimulated macrophages. In contrast, genes associated with pro-inflammatory activity characteristic of IFNγ and LPS-stimulated macrophages such as Nos2 (iNOS), Tnfa, Il1b, and Il6 were induced in IFNγ and LPS-stimulated macrophages, but not IL-4 and IL-13-stimulated macrophages (Supplementary Figure 1)[28, 30, 65, 71, 74, 75]. This indicates that macrophages stimulated with IL-4 and IL-13 were polarized toward a pro-resolution phenotype, while macrophages stimulated with IFNγ and LPS were polarized toward a pro-inflammatory phenotype.

      5) Several portions of the manuscript are unnecessarily long, including the intro and discussion. Please consolidate the text. The results section is also very lengthy, please consider consolidation.

      We appreciate Reviewer #3's preference for a shorter manuscript. The revised manuscript, in response to the many Reviewer comments and requests, contains many new pieces of data, and we have taken care to describe these new data as briefly and simply as possible. In preparation for this Revision, we also removed and shortened several sections of the Results and Discussion where we felt extra explanation was not necessary. We will work with the editor of the journal we submit to ensure the length of the manuscript sections is compliant with the journal's guidelines.

      6) The authors find that macrophage phenotype impacts rhythmicity. However, there is no mechanistic understanding of why this occurs. The authors should provide some mechanistic insight on this topic in the discussion.

      We agree with Reviewer #3 that while the mechanism by which macrophage phenotype alters rhythms remains unknown, this is an important topic of discussion. While there is some literature on how circadian rhythms modulate inflammatory response (and hints at how it may influence phenotype) in macrophages, there is very little on the converse: how phenotype may influence circadian rhythms. We address this point by expanding on our Discussion - please see the modified text below.

      "Elucidating the role of circadian rhythms in regulation of macrophage biology necessitates a better understanding of the crosstalk between phenotype and circadian rhythms. Although lactate polarizes macrophages toward a pro-resolution phenotype similar to acidic pH[30, 93], exposure to lactate had different effects on circadian rhythms - and in some cases, circadian clock gene expression - than exposure to acidic pH (Figure 4). Sensing of lactate occurs through different pathways than acid-sensing, which may contribute to the different ways in which these two stimuli modulate circadian rhythms of macrophages[111]. One previously published finding that may offer mechanistic insight into how phenotype can influence circadian rhythms is the suppression of Bmal1 by LPS-inducible miR-155[54]. It has also been observed that RORα-mediated activation of Bmal1 transcription is enhanced by PPARγ co-activation[112]. In macrophages, PPARγ expression is induced upon stimulation with IL-4 and plays a key role in alternative activation of macrophages, promoting a pro-resolution macrophage phenotype, and supporting resolution of inflammation[113-115]. Such observations prompt the question of whether there are yet-unidentified factors induced downstream of various polarizing stimuli that can modulate expression of circadian genes at the transcriptional and protein levels. Further work is required to understand the interplay between macrophage phenotype and circadian rhythms."

      7) The data presented in Figure 9 is very intriguing and arguably the strongest aspect of the paper. To strengthen the point, the authors could repeat this experiment with an additional cell model, another PDAC line or a different cancer line.

      We appreciate Reviewer #3's comment about the impact of tumor growth data. Indeed, our finding that deletion of Bmal1 in co-injected macrophages accelerated PDAC growth has been recapitulate by others in different cancer models. This lends strength to our observations. We discuss and cite complementary work on macrophage rhythms and tumor growth in other models of cancer the Discussion, please see below.

      "Data from our lab and others suggest that disruption of the macrophage-intrinsic circadian clock accelerates tumor growth, indicating that circadian regulation of macrophages is tumor-suppressive in models of PDAC (our work) and melanoma [109]. This agrees with complementary findings that behavioral disruption of circadian rhythms in mice (through chronic jetlag) disrupts tumor macrophage circadian rhythms and accelerates tumor growth[56]."

      Minor Comments:

      1) Data is Figure 2 is interesting and the impact on circadian rhythms is clear based on changes in amplitude and period. However, though the impact on period and amplitude is clear from Figures 2A-C, the changes in circadian gene expression are less clear. For instance, though amplitude is up in 2B, amplitude is suppressed in 2C. However, that does not appear to be reflected in the gene expression data in Figures 2E and F. The authors should comment on this.

      Reviewer #3 correctly points out that there appear to be discrepancies between the LumiCycle data in Figure 2 and the circadian gene expression data in Figure 2. This discrepancy is perhaps unsurprising given that the gene expression data is only a short time course over 12 hours, while the LumiCycle data are collected over a course of 3 days. The gene expression data do not allow us to determine changes in period or rhythm. Another point of interest is that it's been shown that circadian regulation occurs on many different levels (transcriptional, post-transcriptional, translational, post-translational). As result of this, circadian patterns observed in gene transcripts don't always match those of their encoded proteins; just the same, circadian patterns of proteins aren't always reflected in their encoding gene transcripts (Collins 2021 Genome Res). Due to this multi-level regulation, we propose that the results of the LumiCycle analysis, which measures PER2-Luc levels, are a more robust readout of rhythms because they are further downstream of the molecular clock than transcriptional readouts. That said, observing changes at both the protein (by Lumicycle) and transcriptional level confirm that all components of the clock are altered by acidic pH, even if the way in which they are altered appears to differ. We have incorporated the points we raised above into the Results section.

      Please see the modified text below.

      "Low pH was also observed to alter the expression of the circadian clock genes Per2, Cry1, and Nr1d1 (REV-ERBα) over time across different macrophage phenotypes, confirming that multiple components of the circadian clock are altered by acidic pH (Figure 2D-F). Notably, the patterns in expression of circadian genes did not always match the patterns of PER2-Luc levels observed by LumiCycle. This is perhaps unsurprising, as circadian rhythms are regulated at multiple levels (transcriptional, post-transcriptional, translational, post-translational); as a result, circadian patterns observed in circadian proteins such as PER2-Luc do not always match those of their gene transcripts[77]."

      2) On line 156-158, authors describe damping rate. I believe the authors are trying to say that damping rate increases as the time it takes cells to desynchronize decreases and vice versa. However, this point needs to be better explained.

      We thank Reviewer #3 for bringing to our attention that this was not communicated clearly in the text. We have adjusted our explanation to be clearer. Please see the modified text below.

      "Damping of rhythms in most free-running cell populations (defined as populations cultured in the absence of external synchronizing stimuli) occurs naturally as the circadian clocks of individual cells in the population become desynchronized from each other; thus, damping can be indicative of desynchrony within a population[84]. The damping rate increases as the time it takes for rhythms to dissipate decreases; conversely, as damping rate decreases as the time it takes for rhythms to dissipate increases."

      3) Data presented in Figures 3 and 4 are different in terms of the impact of changing the pH. The source of the macrophages is different, but the authors could clarify this further.

      We thank Reviewer #3 for this comment. Our conclusion is that the impact of low pH is largely similar in Figure 3 (peritoneal macrophages) and Figure 4 (BMDMs exposed to low pH and lactate). In both Figures 3 and 4, exposure to acidic pH by culturing macrophages at pH 6.5 increased amplitude, decreased period, and increased damping rate compared to macrophages cultured at neutral pH 7.4.

      4) For heatmaps shown in Figures 7 and 8, please calculate covariance and display asterisks where P We thank Reviewer #3 for the excellent suggestion to use an additional approach to asses circadian clock status in samples by measuring co-variance in the circadian clock gene network. To address this point, we have performed weighted gene co-expression network analysis (WGCNA) to calculate covariance, as was originally performed in Chun and Fortin et al Science Advances 2022. For the samples analyzed in Figure 7 (now Figure 6), we have added these data to the figure. We have applied this analysis to a new set of human data that we analyzed and added it to the new Figure 7. Finally, for the samples analyzed in Figure 8, we have added these data as a new Supplementary Figure 9. Please see the data and modified text below.

      Figure 6

      "Weighted gene co-expression network analysis (WGCNA) has been used as an alternate approach to measure the co-variance between clock genes and thus assess bi-directional correlations among the core clock gene network in healthy tissue and tumor samples [103]. In line with the circadian disorder observed by CCD, while many bi-directional correlations among the core clock gene network were significant and apparent in wild type peritoneal macrophages, these relationships were altered or abolished within BMAL1 KO peritoneal macrophages and TAM samples, and in some cases replaced by new relationships (Figure 6E). This indicates that there is population-level disorder in the circadian rhythms of tumor-associated macrophages in murine lung cancer."

      Figure 7

      "We next assessed the status of the circadian clock in human TAMs from NSCLC patients. We performed CCD with publicly available RNA-seq data of tumor-adjacent macrophages and tumor-associated macrophages from NSCLC patients, using alveolar macrophages from healthy donors as a control[104, 105]. To assess the contribution of the acidic TME to circadian disorder, we subset TAM NSCLC patient samples into groups (Crem high TAMs and Crem low TAMs) based on median Crem expression. Notably, in macrophages from human NSCLC there was a trend toward disorder in Crem low but not Crem high TAM samples (Figure 7A,B). Additionally, the co-variance among core clock genes observed in alveolar macrophages from healthy donors was absent within Crem low and Crem high TAM samples (Figure 7C). In all, these data indicate that there is population-level disorder in the circadian rhythms of tumor-associated macrophages in humans and mice, suggesting that circadian rhythms are indeed altered in macrophages within the TME."

      Supplementary Figure 9

      "CCD score worsened as populations became increasingly desynchronized, with the 12hr desynchronized population having a significantly worse CCD score than synchronized, homogenous macrophage population (Figure 8C). This indicates that as circadian rhythms of individual macrophages within a population become more different from each other, circadian disorder increases at the population-level. This is further supported by WGCNA, which revealed that the significant co-variance of circadian clock genes in the synchronized population was progressively altered and lost as the population is increasing desynchronized to 12 hours (Supplementary Figure 9)."

      Reviewer #3 (Significance (Required)):

      This is an important study that is well-done. It is the feeling of the reviewer that the study warrants a revision, at the discretion of the editor. The study represents an important understanding of the crosstalk between cancer cells and immune cells as well as the understanding of how the TME disrupts circadian rhythms.

      We thank Reviewer #3 for their comments regarding the impact and significance of our work. As shown by the comments above, we are confident we have fully addressed each of the points that were made to result in a much-improved revised manuscript.




    1. Author response:

      The following is the authors’ response to the original reviews.

      Editors’ recommendations for the authors

      The reviewers recommend the following: 

      (a) Digging deeper into the discussion of the density-dependent dispersal. 

      (b) Clarifying the microfluidic setup.  

      (c) Clarifying the description and interpretation of the transcriptomic evidence. 

      (d) Toning down carbon cycle connections (some reviewers felt the evidence did not fully support the claims). 

      We would like to thank the editors for their thoughtful evaluation of our manuscript and their clear suggestions. We have revised the manuscript in the light of these comments, as we outline below and address in detail in the point-by-point response to the reviewers’ comments that follows. 

      (a) We have expanded the discussion of density-dependent dispersal and revised Figure 2C to improve clarity. 

      (b) We have also added further information concerning the microfluidic setup in the results section and provide an illustration of the setup in a new figure panel, Figure 1A.

      (c) Addressing the reviewers’ comments on the transcriptomic analysis, we have added more information in the description and interpretation of the results. 

      (d) We have rephrased the text describing the role of degradation-dispersal cycles for carbon cycling to highlight it as the motivation of this study and emphasize the link to literature on foraging, without creating expectations of direct measurements of global carbon cycling.

      Public Reviews:

      Reviewer #1 (Public Review):

      [...]

      Weaknesses: 

      Much of the genetic analysis, as it stands, is quite speculative and descriptive. I found myself confused about many of the genes (e.g., quorum sensing) that pop up enriched during dispersal quite in contrast to my expectations. While the authors do mention some of this in the text as worth following up on, I think the analysis as it stands adds little insight into the behaviors studied. However, I acknowledge that it might have the potential to generate hypotheses and thus aid future studies. Further, I found the connections to the carbon cycle and marine environments in the abstract weak --- the microfluidics setup by the authors is nice, but it provides limited insight into naturalistic environments where the spatial distribution and dimensionality of resources are expected to be qualitatively different. 

      We thank the reviewer for their suggestions to improve our manuscript. We agree that the original manuscript would have benefitted from more detailed interpretation of the observed changes in gene expression. We have revised the manuscript to elaborate on the interpretation of the changes in expression of quorum sensing genes (see response to reviewer 1, comment 3), motility genes (see response to reviewer 1, comment 6), alginate lyase genes (see response to reviewer 1, comment 7 and reviewer 2, comment 2), and ribosomal and transporter genes (see response to reviewer 2, comment 2).

      In general, we think that the gene expression study not only supports the phenotypic observations that we made in the microfluidic device, such as the increased swimming motility when exposed to digested alginate medium, but  also adds further insights. Our reasoning for studying the transcriptomes in well mixed-batch cultures was the inability to study gene expression dynamics to support the phenotypic observations about differential motility and chemotaxis in our microfluidics setup. The transcriptomic data clearly show that even in well-mixed environments, growth on digested alginate instead of alginate is sufficient to increase the expression of motility and chemotaxis genes. In addition, the finding that expression of alginate lyases and metabolic genes is increased during growth on digested alginate was revealed through the analysis of transcriptomes, something which would not have been possible in the microfluidic setup. We agree with the reviewer that our analyses implicate further, perhaps unexpected, mechanisms like quorum sensing in the cellular response to breakdown products, and that this represents an interesting avenue for further studies.

      Finally, we  also agree with the reviewer that it would be good to be more explicit in the text that our microfluidic system cannot fully capture the complex dynamics of natural environments. Our approach does, however, allow the characterization of cellular behaviors at spatial and temporal scales that are relevant to the interactions of bacteria, and thus provides a better understanding of colonization and dispersal of marine bacteria in a manner that is not possible through in situ experiments. We have edited our manuscript to highlight this and modified our statements regarding carbon cycling towards emphasizing the role degradation-dispersal cycles in remineralization of polysaccharides (see response to reviewer 1, comment 2).  

      Reviewer #2 (Public Review):

      [...]

      Weaknesses: 

      The explanation of the microfluidics measurements is somewhat confusing but I think this could be easily remedied. The quantitative interpretation of the dispersal data could also be improved and I'm not clear if the data support the claim made. 

      We thank the reviewer for their comments and helpful suggestions. We have revised the manuscript with these suggestions in mind and believe that the manuscript is improved by a more detailed explanation of the microfluidic setup. We have added more information in the text (detailed in response to reviewer 2, comments 1 and 2) and have added a depiction of the microfluidic setup (Fig. 1A). We have also modified the presentation and discussion of the dispersal data (Fig. 2C), as described in detail below in response to reviewer 2, comment 4, and argue that they clearly show density-dependent dispersal. We believe that this modification of how the results are presented provides a more convincing case for our main conclusion, namely that the presence of degradation products controls bacterial dispersal in a density-dependent manner.  

      Reviewer #3 (Public Review):

      [...]

      Weaknesses: 

      I find this paper very descriptive and speculative. The results of the genetic analyses are quite counterintuitive; therefore, I understand the difficulty of connecting them to the observations coming from experiments in the microfluidic device. However, they could be better placed in the literature of foraging - dispersal cycles, beyond bacteria. In addition, the interpretation of the results is sometimes confusing. 

      We thank the reviewer for their suggestions to improve the manuscript. We have edited the manuscript to interpret the results of this study more clearly, in particular with regard to the fact that breakdown products of alginate cause cell dispersal (see response to reviewer 2, comment 1), gene expression changes of ribosomal proteins and transporters (see response to reviewer 2, comment 2), as well as genes relating to alginate catabolism (see response to reviewer 2, comment 3).

      To provide more context for the interpretation of our results we now also embed our findings in more detail in the previous work on foraging strategies and dispersal tradeoffs.

      Recommendations For The Authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) The authors should clarify in more detail what they mean by density dependence in Figure 2. Usually density dependence refers to a per capita dependence, but here it seems that the per capita rate of dispersal might be roughly independent of density (Figure 2c; if you double the number of cells it doubles the number of cells leaving). Rather it seems the dispersal is such that the density of remaining cells falls below a threshold (~300 cells). 

      We thank the reviewer for raising this important point. To analyze the data more explicitly in terms of per capita dependence and so make the density dependence in the dispersal from the microfluidic chambers more clear, we have modified Figure 2C and edited the text. 

      In the modified Figure 2C, we computed the fraction of dispersed cells for each chamber (i.e the change in cell number divided by the cell number at the time of the nutrient switch). This quantity directly reveals the per-capita dependence, as mentioned by reviewer 1, and is now represented on the y-axis of Figure 2C instead of the absolute change in cell number. 

      These data demonstrate that the fraction of dispersed cells increases with increasing numbers of cells present in the chamber at the time of switching, with more highly populated chambers showing a higher fraction of dispersed cells. These findings indicate that there is a strong density dependence in the dispersal process.

      As pointed out by reviewer 1, another interesting aspect of the data is the transition at low cell number. The fraction of dispersed cells is negative in the case of the chamber with approximately 70 cells, consistent with no dispersal at this low density, and a moderate density increase as a function of continued growth.  

      In addition to the new analysis presented in Figure 2C, we have modified the paragraph that discusses this result as follows (line 208):

      “We indeed found that the nutrient switch caused a few or no cells to disperse from small cell groups (Fig. 2B), whereas a large fraction of cells from large cell groups dispersed (Fig. 2C). In fact, the e fraction of cells that dispersed upon imposition of the nutrient switch showed a strong positive relationship with the number of cells present, meaning that cells in chambers with many cells were more likely to disperse than cells in chambers with fewer cells (Fig. 2C).”

      (2) The authors should tone down their claims about the carbon cycle in the abstract. I do not believe the results as they stand could be used to understand degradation-dispersal cycles in marine environments relevant to the carbon cycle, since these behaviors have been studied in microfluidic environments which in my understanding are quite different. As such, statements such as "degradation-dispersal cycles are an integral part in the global carbon cycle, we know little about how cells alternate between degradation and motility" and "Overall, our findings reveal the cellular mechanisms underlying bacterial degradation-dispersal cycles that drive remineralization in natural environments" are overstated in the abstract. 

      We appreciate the reviewer’s comments regarding the connections of our work with the carbon cycle. We have now rephrased these statements in our manuscript to describe a potential connection between our work and the marine carbon cycle. The colonization of polysaccharides particles by bacteria and subsequent degradation has been widely acknowledged to play a significant role in controlling the carbon flow in marine ecosystems. (Fenchel, 2002; Preheim et al., 2011; Yawata et al., 2014, 2020). We still refer to carbon flow in the revised manuscript, though cautiously, as microbial remineralization of biomass, which is recognized as an important factor in the marine biological carbon pump (e.g., (Chisholm, 2000; Jiao et al., 2024). As stated in the previous version of the manuscript, the main motivation of our work was to study the growth behaviors of marine heterotrophic bacteria during polysaccharide degradation, especially to understand when bacteria depart already colonized and degraded particles and find novel patches to grow and degrade, a process that is poorly understood. Therefore, it is conceivable that degradation-dispersal cycles do play a role in the flow of carbon in marine ecosystems. However, we acknowledge that the carbon cycle is influenced by a multitude of biological and chemical processes, and the bacterial degradation-dispersal cycle might not be the sole mechanism at play. 

      We also appreciate the reviewer’s comments highlighting that the complexity of natural environments is not fully captured in our microfluidics system. However, our microfluidics setup does allow us to quantify responses and behaviors of microbial groups at high spatial and temporal resolution, especially in the context of environmental fluctuations. Microbes in nature interact at small spatial scales and have to respond to changes in the environment, and the microfluidics setup enables the quantification of these responses. Moreover, dispersal of the bacterium V. cyclitrophicus that we use in our study, has been previously observed even during growth on particulate alginate (Alcolombri et al., 2021), but the cues and regulation controlling dispersal behaviors have been unclear.  Microfluidic experiments have now allowed us to study this process in a highly quantitative manner, and align well with observations from experiments from more nature-like settings. These quantitative experiments on bacterial strains isolated from marine particles are expected to constrain quantitative models of carbon degradation in the ocean (Nguyen et al., 2022).

      We have now adjusted our statements throughout our manuscript to reflect the knowledge gaps in understanding the triggers of degradation-dispersal cycles and their links with carbon flow in marine ecosystems. The revised manuscript, especially, contains the following statements (line 47 and line 60):

      “Even though many studies indicate that these degradation-dispersal cycles contribute to the carbon flow in marine systems, we know little about how cells alternate between polysaccharide degradation and motility, and which environmental factors trigger this behavioral switch.”

      “Overall, our findings reveal cellular mechanisms that might also underlie bacterial degradation-dispersal cycles, which influence the remineralization of biomass in marine environments.”

      (3) The authors should clarify why they think quorum-sensing genes are increased in expression on digested alginate. The authors currently mention that QS could be used to trigger dispersal, but given the timescales of dispersal in Figure 2 (~half an hour), I find it hard to believe that these genes are expressed and have the suggested effect on those timescales. As such I would have expected the other way round - for QS genes to be expressed highly during alginate growth, so that density could be sensed and responded to. Please clarify. 

      We have now clarified this point in the revised manuscript. While the triggering of dispersal by quorum-sensing genes may indeed appear counterintuitive, and the response is rapid (we see dispersal of cells within 30-40 minutes), both observations are in line with previous studies in another model organism Vibrio cholerae. The dispersal time is similar to the dispersal time of V. cholerae cells from biofilms, as described by Singh and colleagues, (Figure 1E of Ref. Singh et al., 2017). In that case, induction of the quorum sensing dispersal regulator HapR was observed during biofilm dispersal within one hour after switch of condition (Fig. 2, middle panel of Ref. Singh et al., 2017). Even though the specific quorum sensing signaling molecules are probably different in our strain (there is no annotated homolog of the hapR gene in V. cyclitrophicus), we observed that the full set of quorum sensing genes was enriched in cells growing on digested alginate (as reported in line 314 and Fig. 4A).

      We have added this information in the manuscript (line 317): 

      “The set of quorum sensing genes was also positively enriched in cells growing on digested alginate (Fig. 4A and S4F, Table S13). This role in dispersal is in agreement with a previous study that showed induction of the quorum sensing master regulator in V. cholerae cells during dispersal from biofilms on a similar time scale as here (less than an hour) [28].”

      Reviewer #2 (Recommendations For The Authors):

      (1) Around line 144 - I don't really understand how you flow alginate through the microfluidic platform. It seems if the particles are transiently going through the microfluidic chamber then the flow rate and hence residence time of the alginate particles will matter a lot by controlling the time the cells have to colonize and excrete enzymes for alginate breakdown. Or perhaps the alginate is not particulate but is instead a large but soluble polymer? I think maybe a schematic of the microfluidic device would help -- there is an implicit assumption that we are familiar with the Dal Co et al device, but I don't recall its details and maybe a graphic added to Figure 1 would help. 

      a. In reviewing the Dal Co paper I see that cells are trapped and the medium flows through channels and the plane where the cells are held. I am still a little confused about the size of the polymeric alginate -- large scale (>1um) particles or very small polymers? 

      We have now provided a detailed description of our microfluidic experimental system. At the start of the experiments, cells are in fact not trapped within the microfluidic device, but grow and can move freely within a chamber designed with dimensions (sub-micron heights) so that growth occurs only as a monolayer. Cells were exposed to nutrients, either alginate or alginate digestion products, both in soluble form (not particles). These compounds were flowed into the device through a main channel, but entered the flowfree growth chambers by diffusion. To make these aspects of our experiments clearer, we have added further information on this in the Materials & Methods section (line 556), added this information in the abstract (line 51), and in the results (line123).

      To make our microfluidic setup clearer, we have followed this advice and added a schematic as Figure 1A and have added more information on the setup to the main text (line 153):

      “In brief, the microfluidic chips are made of an inert polymer (polydimethylsiloxane) bound to a glass coverslip. The PDMS layer contains flow channels through which the culture medium is pumped continuously. Each channel is connected to several growth chambers that are laterally positioned. The dimensions of these growth chambers (height: 0.85 µm, length: 60 µm, width: 90-120 µm) allow cells to freely move and grow as monolayers. The culture medium, containing either alginate or digested alginate in their soluble form, is constantly pumped through the flow channel and enters the growth chambers primarily through diffusion [15,16,4,17,8]. Therefore, the number of cells and their positioning within microfluidic chambers is determined by the cellular growth rate as well as by cell movement4. This setup combined with time-lapse microscopy allowed us to follow the development of cell communities over time.”

      (2) What makes this confusing is the difference between Figure 1C and Figure S2A -- the authors state that the difference in Figure 1C is due to dispersal, but is there flow through the microfluidic device? So what role does that flow through the device have in dispersal? Is the adhesion of the cell groups driven at all by a physical interaction with high molecular weight polymers in the microfluidic devices or is this purely a biological effect? Could this also be explained by different real concentrations of nutrients in the two cases? 

      We realize from this comment that the role of flow of the medium in the microfluidic setup was not clearly addressed in our manuscript. In fact, cells were not exposed to flow, and nutrients were provided to the growth chambers by diffusion. We have added a clearer explanation of this point on line 158:

      “The culture medium, containing either alginate or digested alginate in their soluble form, is constantly pumped through the flow channel and enters the growth chambers primarily through diffusion [15,16,4,17,8]. Therefore, the number of cells and their positioning within microfluidic chambers is determined by the cellular growth rate as well as by cell movement4.“

      One purely physical effect that we anticipate is that a high viscosity of the medium could immobilize cells. To address this point, we measured the viscosity of both alginate and digested alginate and conclude that the increase in viscosity is not strong enough to immobilize cells. We added a statement in the text (line 170)

      “To test the role of increased viscosity of polymeric alginate in causing the increased aggregation of cells, we measured the viscosity of 0.1% (w/v) alginate or digested alginate dissolved in TR media. For alginate, the viscosity was 1.03±0.01 mPa·s (mean and standard deviation of three technical replicates) whereas the viscosity of digested alginate in TR media was found to be 0.74±0.01 mPa·s. Both these values are relatively close to the viscosity of water at this temperature (0.89 mPa·s18) and, while they may affect swimming behavior [19], they are insufficient to physically restrain cell movement [20].”

      as well as a section in the Materials and Methods (line 594):

      “Viscosity of the alginate and digested alginate solution

      We measured the viscosity of alginate solutions using shear rheology measurements. We use a 40 mm cone-plate geometry (4° cone) in a Netzsch Kinexus Pro+ rheometer. 1200 uL of sample was placed on the bottom plate, the gap was set at 150 um and the sample trimmed. We used a solvent trap to avoid sample evaporation during measurement. The temperature was set to 25°C using a Peltier element. We measure the dynamic viscosity over a range of shear rates  = 0.1 – 100 s-1. We report the viscosity of each solution as the average viscosity measured over the shear rates 10 – 100 s-1, where the shear-dependence of the viscosity was low.

      We measured the viscosity of 0.1% (w/V) alginate dissolved in TR media, which was 1.03 +/- 0.01 mPa·s (reporting the mean and standard deviation of three technical replicates.). The viscosity of 0.1% digested alginate in TR media was found to be 0.74+/-0.01 mPa·s. This means that the viscosity of alginate in our microfluidic experiments is 36% higher than of digested alginate, but the viscosities are close to those expected of water (0.89 mPa·s at 25 degree Celsius according to Berstad and colleagues [18]).”

      While our microfluidic setup allows us to track the position and movement of cells in a spatially structured setting, these observations do not allow us to distinguish directly whether the differences in dispersal are a result of purely physical effects of polymers on cells or are a result of them triggering a biological response in cells that causes them to become sessile. It is known that bacterial appendages like pili interact with polysaccharide residues (Li et al., 2003). Therefore, it is quite plausible that cross-linking by polysaccharides can contribute growth behaviors on alginate. However, our analysis of gene expression demonstrates that flagellum-driven motility is decreased in the presence of alginate compared to digested alginate, alongside other major changes in gene expression. In addition, our measures of dispersal show that dispersal of cells when exposed to digested alginate is density dependent. Both observations suggest that the patterns in dispersal are governed by decision-making processes by cells resulting in changes in cell motility, rather than being a product of purely physical interactions with the polymer. 

      The finding that viscosities of both alginate and digested alginate are similar to that of water, suggests that diffusion of nutrients in the growth chambers should be similar. Therefore, we think that the differences in real concentrations of nutrients is likely not contributing to the observed differences in behavior. 

      (3) Why is Figure S1 arbitrary units? Does this have to do with the calibration of LC-MS? It would be better, it seems, to know the concentrations in real units of the monomer at least. 

      We agree with the reviewer that it would have been better to have absolute concentrations for these compounds. However, to calibrate the mass spectrometer signals (ion counts) to absolute concentrations for the different alginate compounds, we would need an analytical standard of known concentration. We are not aware of such a standard and thus report only relative concentrations. We agree that the y-axis label of Figure S1 should not contain ‘arbitrary’ units, as it shows a ratio (of measurements in the same arbitrary units). We have edited the labels of Figure S1 accordingly and the figure legend in line 26 of the Supplemental Material (“Relative concentrations…”).

      (4) Line 188 - density-dependent dispersal. The claim here is that "cells in chambers with many cells were more likely to disperse than cells in chambers with less cells." (my emphasis). Looking at the data in Figure 2C it appears that about 40% of the cells disperse irrespective of the density, before the switch to digested alginate. So it would seem that there is not a higher likelihood of dispersal at higher cell densities. For the very highest cell density, it does appear that this fraction is larger, but I'd be concerned about making this claim from what I understand to be a single experiment. To support the claim made should the authors plot Change in Cell number/Starting Cell number on the y-axis of Fig. 2C to show that the fraction is increasing? It would seem some additional data at higher starting cell densities would help support this claim more strongly. 

      We thank the reviewer for this comment, which is in line with a remark made by reviewer 1 in their comment 1. In response to these two comments (and as described above), we have edited Figure 2C and now have plotted the change in cell number relative to starting cell number at the y axis to directly show the density dependence. We observe a positive (approximately linear) relationship between the fraction of dispersed cells with the number of cells present in the chamber at the time of switching. This indicates that there is a density dependence in the dispersal process, with highly populated chambers showing a higher fraction of dispersed cells. 

      In addition to the change in Figure 2C, we have modified the paragraph around line 208: “We indeed found that the nutrient switch caused a few or no cells to disperse from small cell groups (Fig. 2B), whereas a large fraction of cells from large cell groups dispersed (Fig. 2C). In fact, the e fraction of cells that dispersed upon imposition of the nutrient switch showed a strong positive relationship with the number of cells present, meaning that cells in chambers with many cells were more likely to disperse than cells in chambers with fewer cells (Fig. 2C).”

      The highest cell number at the start of the switch that we include is about 800 cells. The maximum number of cells that can fit into a chamber are ca. 1000 cells. Thus, 800 resident cells are close to the maximal density.

      (5) A comment -- I find the result of significant chemotaxis towards alginate but not the monomers of alginate to be quite surprising. The ecological relevance of this (line 219) seems like an important result that is worth expanding on a bit at least in the discussion. For now, my question is whether the authors know of any mechanism by which chemotaxis receptors could respond to alginate but not the monomer. How can a receptor distinguish between the two? 

      We agree that this result is surprising, given that oligomers can be more easily transported into the periplasm where sensing takes place, and they also provide an easier accessible nutrient source. Indeed, in case of the insoluble polymer chitin it has been shown that chemotaxis towards chitin is mediated by chitin oligomers (Bassler et al., 1991), which was suggested as a general motif to locate polysaccharide nutrient sources (Keegstra et al., 2022). However, a recent study has changed this perspective by showing widespread chemotaxis of marine bacteria towards the glucose-based marine polysaccharide laminarin, but not towards laminarin oligomers or glucose (Clerc et al., 2023). Together with our results on chemotaxis towards alginate (but not significantly toward alginate oligomers) this suggests that chemotaxis towards soluble polysaccharides can be mediated by direct sensing of the polysaccharide molecules.

      As recommended, we expanded the discussion of the ecological relevance and also added more information on possible mechanisms of selective sensing of alginate and its breakdown products (around line 479).:

      “Direct chemotaxis towards polysaccharides may facilitate the search for new polysaccharide sources after dispersal. We found that the presence of degradation products not only induces cell dispersal but also increases the expression of chemotaxis genes. Interestingly, we found that V. cyclitrophicus ZF270 cells show chemotaxis towards polymeric alginate but not digested alginate. This contrasts with previous findings for bacterial strains degrading the insoluble marine polysaccharide chitin, where chemotaxis was strongest towards chitin oligomers53, suggesting that oligomers may act as an environmental cue for polysaccharide nutrient sources55. However, recent work has shown that certain marine bacteria are attracted to the marine polysaccharide laminarin, and not laminarin oligomers56. Together with our results, this indicates that chemotaxis towards soluble polysaccharides may be mediated by the polysaccharide molecules themselves. The mechanism of this behavior is yet to be identified, but could be mediated by polysaccharide-binding proteins as have been found in Sphingomonas sp. A1 facilitating chemotaxis towards pectin57. Direct polysaccharide sensing adds complexity to chemosensing as polysaccharides cannot freely diffuse into the periplasm, which can lead to a trade-off between chemosensing and uptake58. Furthermore, most polysaccharides are not immediately metabolically accessible as they require degradation. But direct polysaccharide sensing can also provide certain benefits compared to using oligomers as sensory cues. First, it could enable bacterial strains to preferably navigate to polysaccharide nutrients sources that are relatively uncolonized and hence show little degradation activity. Second, strong chemotaxis towards degradation products could hinder a timely dispersal process as the dispersal then requires cells to travel against a strong attractant gradient formed by the degradation products. Overall, this strategy allows cells to alternate between degradation and dispersal to acquire carbon and energy in a heterogeneous world with nutrient hotspots [44,59–61].”

      (6) Comment on lines 287-8 -- that the "positive enrichment of the gene set containing bacterial motility proteins matched the increase in motile cells that we observe in Fig 3E." I'm confused about what is meant by the word "matched" here. Is the implication that there is some quantitative correspondence between increased motility in Figure 3 and the change in expression in Figure 4? Or is the statement a qualitative one -- that motility genes are upregulated in the presence of digested alginate? Table S12 didn't help me answer this question. 

      We thank the reviewer for their helpful comment. Our original statement was a qualitative one - observing that gene expression enrichment in genes associated with bacterial motility aligned with our expectations based on the previous observation of an increase in motile cells. We have now changed the wording to highlight the qualitative nature of this statement (line 315):

      “The positive enrichment of the gene set containing bacterial motility proteins aligned with our expectations based on the increase in motile cells that we observed in Figure 3E (Fig. 4A, Table S12).”

      (7) Line 326 - what is the explanation for the production of public enzymes in the presence of digest? How does this square with the previous narrative about cells growing on alginate digest expressing motility genes and chemotaxing towards alginate? It seems like the story is a bit tenuous here in the sense that digested alginates stimulate both motility - which is hypothesized to drive the discovery of new alginate particles - and lyase enzymes which are used to degrade alginate. So do the high motility cells that are chemotaxing towards alginate also express lyases en route? I'm of the opinion that constructing narratives like these in the absence of a more quantitative understanding of the colonization and degradation dynamics of alginate particles presents a major challenge and may be asking more of the data than the data can provide. 

      a. I noted later that this is addressed later around lines 393 in the Discussion section.

      Indeed, the notion that the presence of breakdown products triggers motility and also increases the expression of alginate lyases and other metabolic genes for alginate catabolism seems counterintuitive. We have now expanded our discussion of these results to contextualize these findings (around line 443):

      "One reason for this observation may be that cells primarily rely on intracellular monosaccharide levels to trigger the upregulation of genes associated with polysaccharide degradation and catabolism, as has previously been observed for E. coli across various carbon sources [50,51]. In fact, the majority of carbon sources are sensed by prokaryotes through one‑component sensors inside the cell50. In the one‑component internal sensing scheme, the enzymes and transporters for the use of various carbon sources are expressed at basal levels, which leads to an increase in pathway intermediates upon nutrient availability. The pathway intermediates are sensed by an internal sensor, usually a transcription factor, and lead to the upregulation of transporter and enzyme expression [50,51]. This results in a positive feedback loop, which enables small changes in substrate abundance to trigger large transcriptional responses [50,52]. Thus, the presence of alginate breakdown products may likely result in increased expression of all components of the alginate degradation pathway, including the expression of degrading enzymes. As the gene expression analysis was performed on well-mixed cultures in culture medium containing alginate breakdown products, we therefore expect a strong stimulation of alginate catabolism. In a natural scenario, where cells disperse from a polysaccharide hotspot before its exhaustion, the expression of alginate catabolism genes may likely decrease again once the local concentration of breakdown products decreases. However, continued production of alginate lyases could also provide an advantage when encountering a new alginate source and continued production of alginate lyases may thus help cells to prepare for likely future environments. Further investigations of bacterial enzyme secretion in changing nutrient environments and at relevant spatial scales are required to improve our understanding of the regulation of enzyme secretion along nutrient gradients."

      (8) I like Figure 6, and I think this hypothesis is a good result from this paper, but I think it would be important to emphasize this as a proposal that needs further quantitative analysis to be supported. 

      We have now edited the manuscript to make this point more clear. While both degradation and dispersal are well-appreciated parts of microbial ecology, the transitions and underlying mechanisms are unclear. We have edited the discussion to improve the clarity (line 419): 

      “This cycle of biomass degradation and dispersal has long been discussed in the context of foraging e.g., [44,45,13,46,47], but the cellular mechanisms that drive the cell dispersal remain unclear.”

      Also, we have updated Figure 6 to indicate more clearly which new findings this work proposes (now bold font) and which previous findings that were made in different bacterial taxa and carbon sources that aligns with our  work (now light font). We edited the figure legend accordingly (line 503):

      "By integrating our results with previous studies on cooperative growth on the same system, as well as results on dispersal cycles in other systems, we highlight where the specific results of this work add to this framework (bold font)."

      Minor comments 

      (1) Is there any growth on the enzyme used for alginate digestion? E.g. is the enzyme used to digest the alginate at sufficiently high concentrations that cells could utilize it for a carbon/nitrogen source? 

      We thank the reviewer for raising this point. We added the following paragraph as Supplemental Text to address it (line 179):

      “Protein amount of the alginate lyases added to create digested alginate

      Based on the following calculation, we conclude that the amount of protein added to the growth medium by the addition of alginate lyases is so small that we consider it negligible. In our experiment we used 1 unit/ml of alginate lyases in a 4.5 ml solution to digest the alginate. As the commercially purchased alginate lyases are 10,000 units/g, our 4.5 ml solution contains 0.45 mg of alginate lyase protein. The digested alginate solution diluted 45x when added to culture medium. This means that we added 0.18 µg alginate lyase protein to 1 ml of culture medium.

      As a comparison, for 1ml of alginate medium, 1000µg of alginate is added or for 1 ml of Lysogeny broth (LB) culture medium, 3,500 µg of LB are added.  Thus, the amount of alginate lyase protein that we added is ca. 5000 - 20,000 times smaller than the amount of alginate or LB that one would add to support cell growth. Therefore, we expect the growth that the digestion of the added alginate lyases would allow to be negligible.”

      (2) The lines in Figure 2B are very hard to see. 

      We have addressed this comment by using thicker lines in Figure 2B.

      (3) The black background and images in Figure 3A and B are hard to see as well. 

      We have now replaced Figure 3A and B, now using a white background.

      (4) Typo at the beginning of line 251? 

      Unfortunately we failed to find the typo referred to. We are happy to address it if it still exists in the revised manuscript.

      Reviewer #3 (Recommendations For The Authors):

      (1) I think there is not enough experimental evidence to conclude that the underlying cause of increased motility is the accumulation of digested alginate products. To conclusively show that this is the cause and not just some signal linked to cell density, perhaps the experiment should be repeated with a different carbon source. 

      We thank the reviewer for their comment, which made us realize that we did not make the nature of the dispersal cue clear. The gene expression data was obtained from batch cultures and measured at the same approximate bacterial densities in batch, which indeed shows that the digested alginate is a sufficient signal for an increase in motility gene expression. This agrees very well with our observation that cells growing on digested alginate in microfluidic chambers have an increased fraction of motile cells in comparison with cells exposed to alginate (Fig 3E). However, we did not mean to suggest that the observed dispersal by bacterial motility is not influenced by cell density, in fact, we see that dispersal (and hence the increase in cell motility) in microfluidic chambers that are switched from polymeric to digested alginate depends on the bacterial density in the chamber, with higher bacterial densities showing increased dispersal. This shows that the presence of alginate oligomers does trigger dispersal through motility, but this signal affects bacterial groups in a cell density dependent manner.

      Similar observations have been made in Caulobacter crescentus, which was found to form cell groups on the polymer xylan while cells disperse when the corresponding monomer xylose becomes available (D’Souza et al., 2021). We reference the additional work in lines 179 and 230. Taken together, these observations indicate a more general phenomenon in dispersal from polysaccharide substrates.

      (2) About the expression data: 

      • Ribosomal proteins and ABC transporters are enriched in cells grown on digested alginate and the authors discuss that this explains the difference in max growth rate between alginate and digested alginate. However, in Figure S2E the authors report no statistical difference between growth rates. 

      We have now edited the manuscript to clarify this point. We found that cells grown on degradation products reached their maximal growth rate around 7.5 hours earlier (Fig. S2D) and showed increased expression of ribosomal biosynthesis and ABC transporters in late-exponential phase (Fig. 4A). We consider this shorter lag time as a sign of a different growth state and therefore a possible reason for the difference in ribosomal protein expression.

      As the reviewer correctly points out, the maximum growth rates that were computed from the two growth curves were not significantly different (Fig. S2E). However, for our gene expression analysis, we harvested the transcriptome of cells that reached OD 0.39-0.41 (mid- to late-exponential phase). At this time point, the cell cultures may have differed in their momentary growth rate.

      We edited the manuscript to make this clearer (line 287):

      “Both observations likely relate to the different growth dynamics of V. cyclitrophicus ZF270 on digested alginate compared to alginate (Fig. S2A), where cells in digested alginate medium reached their maximal growth rate 7.5 hours earlier and thus showed a shorter lag time (Fig. S2D). As a consequence, the growth rate at the time of RNA extraction (mid-to-late exponential phase) may have differed, even though the maximum growth rate of cells grown in alginate medium and digested alginate medium were not found to be significantly different (Fig. S2E).”

      • The increased expression of transporters for lyases in cells grown on digested alginate (lines 273-274 and 325-328) is very confusing and the explanation provided in lines 412-420 is not very convincing. My two cents on this: Expression of more enzymes and induction of motility might be a strategy to be prepared for more likely future environments (after dispersal, alginate is the most likely carbon source they will find). This would be in line with observed increased chemotaxis towards the polymer rather than the monomer (Similar to C. elegans). 

      This comment is in line with reviewer 2, comment 7. In response to these two comments (and as described above), we expanded our discussion of these results to contextualize these findings (around line 443):

      “One reason for this observation may be that cells primarily rely on intracellular monosaccharide levels to trigger the upregulation of genes associated with polysaccharide degradation and catabolism, as has previously been observed for E. coli across various carbon sources [50,51]. In fact, the majority of carbon sources are sensed by prokaryotes through one‑component sensors inside the cell [50]. In the one‑component internal sensing scheme, the enzymes and transporters for the use of various carbon sources are expressed at basal levels, which leads to an increase in pathway intermediates upon nutrient availability. The pathway intermediates are sensed by an internal sensor, usually a transcription factor, and lead to the upregulation of transporter and enzyme expression [50,51]. This results in a positive feedback loop, which enables small changes in substrate abundance to trigger large transcriptional responses [50,52]. Thus, the presence of alginate breakdown products may likely result in increased expression of all components of the alginate degradation pathway, including the expression of degrading enzymes. As the gene expression analysis was performed on well-mixed cultures in culture medium containing alginate breakdown products, we therefore expect a strong stimulation of alginate catabolism. In a natural scenario, where cells disperse from a polysaccharide hotspot before its exhaustion, the expression of alginate catabolism genes may likely decrease again once the local concentration of breakdown products decreases. However, continued production of alginate lyases could also provide an advantage when encountering a new alginate source and continued production of alginate lyases may thus help cells to prepare for likely future environments. Further investigations of bacterial enzyme secretion in changing nutrient environments and at relevant spatial scales are required to improve our understanding of the regulation of enzyme secretion along nutrient gradients.”

      Additionally, we agree with the intriguing comment that continued expression of alginate lyases may also prepare cells for likely future environments. Further studies that aim to answer whether marine bacteria are primed by their growth on one carbon source towards faster re-initiation of degradation on a new particle will be an interesting research question. We now address this point in our manuscript (line 458):

      “However, continued production of alginate lyases could also provide an advantage when encountering a new alginate source and continued production of alginate lyases may thus help cells to prepare for likely future environments. Further investigations of bacterial enzyme secretion in changing nutrient environments and at relevant spatial scales are required to improve our understanding of the regulation of enzyme secretion along nutrient gradients.“

      (3) The yield reached by Vibrio on alginate is significantly higher than the yield in digested alginate, not similar, as stated in lines 133-134. Only cell counts are similar. Perhaps the author can correct this statement and speculate on the reason leading to this discrepancy: perhaps cells tend to aggregate in alginate despite the fact that these are well-mixed cultures. 

      We have edited the description of the OD measurements accordingly and agree with the reviewer that aggregation is indeed a possible reason for the discrepancy (line 141):

      “We also observed that the optical density at stationary phase was higher when cells were grown on alginate (Fig. S2B and C). However, colony counts did not show a significant difference in cell numbers (Fig. S3), suggesting that the increased optical density may stem from aggregation of cells in the alginate medium, as observed for other Vibrio species [7].”

      (4) I suggest toning down the importance of the results presented in this study for understanding global carbon cycling. There is a link but at present it is too much emphasized. 

      We have edited our statements regarding the carbon cycle. In the revised manuscript we stress the lack of direct quantifications of carbon cycling. . We still refer to carbon flow in the revised manuscript, as we would argue that microbial remineralization of biomass is recognized as an important factor in the marine biological carbon pump (e.g., Chisholm, 2000) and research on marine bacterial foraging investigates how bacterial cells manage to find and utilize this biomass.

      Our revised manuscript contains the following modified statements (line 47 and line 60): “Even though many studies indicate that these degradation-dispersal cycles contribute to the carbon flow in marine systems, we know little about how cells alternate between polysaccharide degradation and motility, and which environmental factors trigger this behavioral switch.”

      “Overall, our findings reveal cellular mechanisms that might also underlie bacterial degradation-dispersal cycles, which influence the remineralization of biomass in marine environments.”

      References

      • Alcolombri, U., Peaudecerf, F. J., Fernandez, V. I., Behrendt, L., Lee, K. S., & Stocker, R. (2021). Sinking enhances the degradation of organic particles by marine bacteria. Nature Geoscience, 14(10), 775–780. https://doi.org/10.1038/s41561-021-00817-x
      • Bassler, B. L., Gibbons, P. J., Yu, C., & Roseman, S. (1991). Chitin utilization by marine bacteria. Chemotaxis to chitin oligosaccharides by Vibrio furnissii. Journal of Biological Chemistry, 266(36), 24268–24275. https://doi.org/10.1016/S0021-9258(18)54224-1
      • Chisholm, S. W. (2000). Stirring times in the Southern Ocean. Nature, 407(6805), 685–686. https://doi.org/10.1038/35037696
      • Chubukov, V., Gerosa, L., Kochanowski, K., & Sauer, U. (2014). Coordination of microbial metabolism. Nature Reviews. Microbiology, 12(5), 327–340. https://doi.org/10.1038/nrmicro3238
      • Clerc, E. E., Raina, J.-B., Keegstra, J. M., Landry, Z., Pontrelli, S., Alcolombri, U., Lambert, B. S., Anelli, V., Vincent, F., Masdeu-Navarro, M., Sichert, A., De Schaetzen, F., Sauer, U., Simó, R., Hehemann, J.-H., Vardi, A., Seymour, J. R., & Stocker, R. (2023). Strong chemotaxis by marine bacteria towards polysaccharides is enhanced by the abundant organosulfur compound DMSP. Nature Communications, 14(1), 8080. https://doi.org/10.1038/s41467-023-43143z
      • Dal Co, A., van Vliet, S., Kiviet, D. J., Schlegel, S., & Ackermann, M. (2020). Shortrange interactions govern the dynamics and functions of microbial communities. Nature Ecology and Evolution, 4(3), 366–375. https://doi.org/10.1038/s41559-019-1080-2
      • D’Souza, G., Ebrahimi, A., Stubbusch, A., Daniels, M., Keegstra, J., Stocker, R., Cordero, O., & Ackermann, M. (2023). Cell aggregation is associated with enzyme secretion strategies in marine polysaccharide-degrading bacteria. The ISME Journal. https://doi.org/10.1038/s41396-023-01385-1
      • D’Souza, G. G., Povolo, V. R., Keegstra, J. M., Stocker, R., & Ackermann, M. (2021). Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations. The ISME Journal, 15(9), 2614–2626. https://doi.org/10.1038/s41396-021-00953-7
      • D’Souza, G., Schwartzman, J., Keegstra, J., Schreier, J. E., Daniels, M., Cordero, O. X., Stocker, R., & Ackermann, M. (2023). Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities. Proceedings of the National Academy of Sciences of the United States of America, 120(44), e2305198120. https://doi.org/10.1073/pnas.2305198120
      • Fenchel, T. (2002). Microbial Behavior in a Heterogeneous World. Science, 296(5570), 1068–1071. https://doi.org/10.1126/science.1070118
      • Jiao, N., Luo, T., Chen, Q., Zhao, Z., Xiao, X., Liu, J., Jian, Z., Xie, S., Thomas, H., Herndl, G. J., Benner, R., Gonsior, M., Chen, F., Cai, W.-J., & Robinson, C. (2024). The microbial carbon pump and climate change. Nature Reviews Microbiology. https://doi.org/10.1038/s41579-024-01018-0
      • Keegstra, J. M., Carrara, F., & Stocker, R. (2022). The ecological roles of bacterial chemotaxis. Nature Reviews Microbiology, 20(8), 491–504. https://doi.org/10.1038/s41579-022-00709-w
      • Konishi, H., Hio, M., Kobayashi, M., Takase, R., & Hashimoto, W. (2020). Bacterial chemotaxis towards polysaccharide pectin by pectin-binding protein. Scientific Reports, 10(1), 3977. https://doi.org/10.1038/s41598-020-60274-1
      • Li, Y., Sun, H., Ma, X., Lu, A., Lux, R., Zusman, D., & Shi, W. (2003). Extracellular polysaccharides mediate pilus retraction during social motility of Myxococcus xanthus. Proceedings of the National Academy of Sciences, 100(9), 5443–5448. https://doi.org/10.1073/pnas.0836639100
      • Martínez-Antonio, A., Janga, S. C., Salgado, H., & Collado-Vides, J. (2006). Internal sensing machinery directs the activity of the regulatory network in Escherichia coli. Trends in Microbiology, 14(1), 22–27. https://doi.org/10.1016/j.tim.2005.11.002
      • McDougald, D., Rice, S. A., Barraud, N., Steinberg, P. D., & Kjelleberg, S. (2012). Should we stay or should we go: Mechanisms and ecological consequences for biofilm dispersal. Nature Reviews Microbiology, 10(1), 39–50. https://doi.org/10.1038/nrmicro2695
      • Nguyen, T. T. H., Zakem, E. J., Ebrahimi, A., Schwartzman, J., Caglar, T., Amarnath, K., Alcolombri, U., Peaudecerf, F. J., Hwa, T., Stocker, R., Cordero, O. X., & Levine, N. M. (2022). Microbes contribute to setting the ocean carbon flux by altering the fate of sinking particulates. Nature Communications, 13(1), 1657. https://doi.org/10.1038/s41467-022-29297-2
      • Norris, N., Alcolombri, U., Keegstra, J. M., Yawata, Y., Menolascina, F., Frazzoli, E., Levine, N. M., Fernandez, V. I., & Stocker, R. (2022). Bacterial chemotaxis to saccharides is governed by a trade-off between sensing and uptake. Biophysical Journal, 121(11), 2046–2059. https://doi.org/10.1016/j.bpj.2022.05.003
      • Povolo, V. R., D’Souza, G. G., Kaczmarczyk, A., Stubbusch, A. K., Jenal, U., & Ackermann, M. (2022). Extracellular appendages govern spatial dynamics and growth of Caulobacter crescentus on a prevalent biopolymer. bioRxiv, 2022.06.13.495907. https://doi.org/10.1101/2022.06.13.495907
      • Preheim, S. P., Boucher, Y., Wildschutte, H., David, L. A., Veneziano, D., Alm, E. J., & Polz, M. F. (2011). Metapopulation structure of Vibrionaceae among coastal marine invertebrates. Environmental Microbiology, 13(1), 265–275. https://doi.org/10.1111/j.1462-2920.2010.02328.x
      • Schwartzman, J. A., Ebrahimi, A., Chadwick, G., Sato, Y., Orphan, V., & Cordero, O. X. (2021). Bacterial growth in multicellular aggregates leads to the emergence of complex lifecycles. bioRxiv, 2021.11.01.466752. https://doi.org/10.1101/2021.11.01.466752
      • Singh, P. K., Bartalomej, S., Hartmann, R., Jeckel, H., Vidakovic, L., Nadell, C. D., & Drescher, K. (2017). Vibrio cholerae Combines Individual and Collective Sensing to Trigger Biofilm Dispersal. Current Biology, 27(21), 3359-3366.e7. https://doi.org/10.1016/j.cub.2017.09.041
      • Ulrich, L. E., Koonin, E. V., & Zhulin, I. B. (2005). One-component systems dominate signal transduction in prokaryotes. Trends in Microbiology, 13(2), 52–56. https://doi.org/10.1016/j.tim.2004.12.006
      • Wall, M. E., Hlavacek, W. S., & Savageau, M. A. (2004). Design of gene circuits: Lessons from bacteria. Nature Reviews Genetics, 5(1), 34–42. https://doi.org/10.1038/nrg1244
      • Yawata, Y., Carrara, F., Menolascina, F., & Stocker, R. (2020). Constrained optimal foraging by marine bacterioplankton on particulate organic matter. Proceedings of the National Academy of Sciences, 117(41), 25571–25579. https://doi.org/10.1073/pnas.2012443117
      • Yawata, Y., Cordero, O. X., Menolascina, F., Hehemann, J.-H., Polz, M. F., & Stocker, R. (2014). Competition–dispersal tradeoff ecologically differentiates recently speciated marine bacterioplankton populations. Proceedings of the National Academy of Sciences, 111(15), 5622–5627. https://doi.org/10.1073/pnas.1318943111
      • Zöttl, A., & Yeomans, J. M. (2019). Enhanced bacterial swimming speeds in macromolecular polymer solutions. Nature Physics, 15(6), 554–558. https://doi.org/10.1038/s41567-019-0454-3