This kind of sentence for each feature. i.e. what does each feature enable me to do/give me that I didn't have before.

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the collective creates the greater source from which an power that is beyond oneself stems from

Knowing God isn't about gaining knowledge it's about receiving fuel or gaining resilience

Religion and Science have fundamentally different purposes WE LOVE TO SEE ITTTT

basis of science and religion is not within some far off natural truth-

if it wasn't true it wouldn't make itself apparent and if something contrasts there is a duality

a little too confident in his concept nonsense theory but ok

ummmm no

consciousness of consciousness- understand the world outside of ourselves too see something more fundamental and with stronger continuity across human experience

common collective goals bring people together

time is a commonly established concept

need for classifications to form groups with similar needs

need to understand what others need and see is why concepts were born- proof of social beings

history is a collective memory based in events impact on society

conceptualization exists only alongside collective- does not exist in one persons mind

society is in a sense totality- all things

universe is our concept of it- grounds in society - don't think he actually means the universe as a a physical object with limitations is only in our heads, but the only way we understand and know it is through our societal concepts, confining it to the social space. Do we know the universe outside of our collective conceptualization?

understands existence and changing of world beyond himself but still sees through own experience.

Should establish a working group that identifies their actual threatened status in different areas so that scientists can work together

again, not a life threatening species to citizens, more of a nuisance

stay in concentrated areas

nests would be very hard to remove

Mostly concentrated in either tropical or urban areas-- prime spots for the exotic pet trade

fairly large, could possibly be aggressive if provoked by humans

some sort of solution, but will not fix the more permanent problem. I think the fertility drug would be the best option with the smallest amount of labor

definitely too resource intensive to be effecive

Likely won't help, the birds can just fly to a different area

I think this might work the most: not harmful, does not require too much manual human labor, and does not brutally kill the birds. The EPA should reconsider this method

most success with trapping, and poses least danger to humans

could also be dangerous to people (specifically in residential areas)

this sounds difficult and may not be worth intensive work

This is the key difficulty with all of the solutions: none are practical or cost-effective

relatively successful strategy, could continue to be implemented

further economic consideration: build more of these towers that are difficult to nest on, thereby attempting to alleviate this problem

difficult and does not solve the larger problem of too many birds, but a start

Economic concerns of environmental problems, reflective of people and nature idea

again, still mostly just nuisance and not life-threatening damage, though with increasing bird populations, this could escalate

difficult for humans to remove bird nests, and gives further explanation as to why this method is ineffective

solution, though likely difficult to implement, costly, and may backfire if it goes wrong

Nuisance, but also could be dangerous

sudden population change... I wonder why?

still found it hard to fully understand this, but Edgar put it in the beginning of the story, it should be an important or inspiring idea.

Although the wording is quite complex and difficult throughout the passage, but I think with this explanation makes me understand it better. (a man showing muscles just like analyst solving problems, both have its own happiness)

ok then that's why he can be a detective, I even have no idea about the wording here...literally looking up for the words all the time...

https://www.liberation.fr/environnement/climat/les-emissions-de-gaz-a-effet-de-serre-ont-baisse-de-36-en-france-au-premier-semestre-2024-20240926_6WIUIBXWFBCPXGSATHN7UPWBXA/

Again, we talk about immigrants who arrived. What would America be if no immigrants were never allowed to come here? I wonder

I think once ppl moved to Boston, they felt like they could receive better opportunities somewhere else. It really was for the wealthy that owed possessions and the poor had no reason to stay.

It seems like Immigrants help grow the population, and we are fighting to keep them out now.

It,s amazing how Chicago and some of the other cities hadn't been established yet. The growth by 1850 was amazing.

how would you display these on a topographic map?

What are these?

why do you need special types of levels? cant you just use qa regular level?

Es verdad que los hermanos que nos dirigen, son tan imperfectos como nosotros, tal cómo también lo eran Pablo y Timoteo. Pero al igual que ellos, los ancianos se esfuerzan por aplicar y enseñar, todo lo que él esclavo fiel y prudente les comunica. Son humildes trabajadores y se rigen por las instrucciones los programas de enseñanza que la organización decide, basando toda su enseñanza en la palabra de Dios, la Biblia. Por éso es que Seguír su consejo y dirección, fortalece y hace crecer nuestra fé personal en Jehová y su Organización. Y por añadidura crece y se fortalece toda la congregación.

Su fe creció y se hizo más fuerte, y la predicación daba sus frutos porque el número de creyentes también creció.

Por sus cualidades, que se hicieron tan evidentes, que se reflejaban en su comportamiento, de manera que todos se sentían impulsados a hablar muy bien de él. Y Jehová que ve los corazones, lo bendijo con una hermosa responsabilidad, porque vió su motivación sincera, basada en el amor por lo que aprendía y predicaba.

image qui change du style générale de la page, peu être mettre des feuilles pour que ce soit en accord couleur ?

yep

the real is reasonable not rational

and only the reasonable can be real

rationaility narrowly understood is sheer unreasonableness

good

????

Geographic isolation can lead to the development of distinct dialects, like chiac and acadjonne, even in close regions, which emphasizes the diversity within Acadian linguistic traditions

Lisa's blend of Acadian culture and humor in her music highlights how local, everyday details, like Tim Horton's gossip, can become part of a larger artistic expression, turning regional quirks into something universally joyful and relatable."

This draws attention to the interplay between language, geography, and cultural identity, emphasizing the uniqueness of chiac's evolution.

In the first part of The Game of Chess, the female character is isolated and defined by the lifeless objects surrounding her—perfumes, glass, candle flames, lacquer, and more. Only through these objects, do we get a chance to become acquainted with her. These inanimate items symbolize suffocation and entrapment in her loneliness. The readers can only speculate if it’s the notion of rape that Eliot continuoulsy references that led to this isolation. No matter the cause of it, however, the character strives to get herself out of this situation. She strives for human connection. Her plea, “Speak to me,” reflects this need, but the absence of a question mark in “Why do you never speak to me” suggests that the character already knows the answer. The reader, however, is left to speculate: does she see herself as undesirable because of her trauma? Or is it simply the years of a relationship that deteriorate this connection referencing Eliot’s own troubled marriage? In either case, this emotional disconnect is further demonstrated by the subsequent question, “What are you thinking of?” This time, the question is marked by a question mark, suggesting an actual attempt to break through this emotional barrier. These attempts, however, are ineffective, as the desperation rises and the questions shorten to “what thinking” and “what.” This fragmented monologue mirrors the fragmentation of her emotional state.

In contrast, the second character suffers from the destructive excess of human connection. Shamed for her appearance, she faces the reality of her partner’s potential infidelity, reflected in the statement, “And if you don’t give it to him, there’s others.” The references to abortion intensify this degradation. She justifies her loss of beauty and confidence with the line, “It’s them pills I took, to bring it off.” Instead of finding fulfillment in connection, this character’s relationships strip her of her self-worth.

In these two cases, Eliot presents women trapped at the opposite extremes of human connection: one suffers from its absence, the other from its destructive abundance. Yet, in both cases, external forces define and entrap them. The first woman is reduced to the objects around her, while the second is judged by an external voice—the pronoun “I” suggesting our, as readers, own judgment projected onto the character. We become not simply the judges, but also the victimes of this broken connection. The poem’s fragmented language, which severely affects our understanding of it, mirrors the emotional chaos, invoking feelings rather than rationality, similarly to Ophelia’s “mad” song in Hamlet.

This pattern mirrors the nature of chess, where a single wrong move can drastically alter the entire game. Just as in chess, life’s unpredictability is highlighted in these women’s lives, as one extreme of human connection can quickly shift to another, with equally devastating outcomes. The title of the section, The Game of Chess, thus, reflects this instability —one wrong move leads to extremes of connection. In this case, these characters and we, as readers, are not simply entrapped in this game. Instead, we are playing with an unwinnable position from the very outset: each move only brings the inevitability of loss closer.

Like that association very much

Just to keep the definition open for further use cases?

It is, but it's done already anyway.

Duplicate Address Detection

Duplicate Address Detection

Can be enabled via:

option "Wi-Fi-enhanced MAC randomization" in the developer options.

https://android.stackexchange.com/a/233117

So what did they do?

Mentions some use cases you want to prevent against. (Grocery store tracking its customers)

It's not necessarily a sequence at all. https://www.rfc-editor.org/rfc/rfc8981.html#section-3.1-2.6

eLife assessment

This important study demonstrates a mechanism underlying the sex-dependent regulation of the susceptibility to gut colonization by Methicillin-resistant Staphylococcus aureus (MRSA). The evidence supporting the conclusion is solid, but additional experiments would strengthen the findings. The work will interest biologists who are working on intestinal infection and immunity.

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.

Reviewer #2 (Public review):

The current study by Lejeune et al. investigates factors that allow for persistent MRSA infection in the GI tract. They developed an intriguing model of intestinal MRSA infection that does not use the traditional antibiotic approach, thereby allowing for a more natural infection that includes the normal intestinal microbiota. This model is more akin to what might be expected to be observed in a healthy human host. They find that biological sex plays a clear role in bacterial persistence during infection but only in mice bred at an NYU Facility and not those acquired from Jackson Labs. This clearly indicates a role for the intestinal microbiome in affecting female bacterial persistence but not male persistence which was unaffected by the origin of the mice and thus the microbiome. Through a series of clever microbiome-specific transfer experiments, they determine that the NYU-specific microbiome plays a role in this sexual dimorphism but is not solely responsible. Additional experiments indicate that Th17 cells, estrogen, and neutrophils also participate in the resistance to persistent infection. Notably, they assess the role of sex chromosomes (X/Y) using the established four core genotype model and find that these chromosomes appear to play little role in bacterial persistence.

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.

(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.

(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.

(3) The ovariectomy experiment demonstrates a role for ovarian hormones; however, it lacks a control of adding back ovarian hormones (or at least estrogen) so it is not entirely obvious what is causing the persistence in this experiment. This is especially important considering the experiments demonstrating no role for sex chromosomes thus demonstrating that hormonal effects are highly important. Here it leaves the reader without a conclusive outcome as to the exact hormonal mechanism.

(4) The discussion is underdeveloped and is mostly a rehash of the results. It would greatly enhance the manuscript if the authors would more carefully place the results in the context of the current state of the field including a more enhanced discussion of the role of estrogen, microbiome, and T cells and how the field might predict these all interact and how they might be interacting in the current study as well.

Reviewer #3 (Public review):

Summary:

Using a mouse model of Staphylococcus aureus gut colonization, Lejeune et al. demonstrate that the microbiome, immune system, and sex are important contributing factors for whether this important human pathogen persists in the gut. The work begins by describing differential gut clearance of S. aureus in female B6 mice bred at NYU compared to those from Jackson Laboratories (JAX). NYU female mice cleared S. aureus from the gut but NYU male mice and mice of both sexes from JAX exhibited persistent gut colonization. Further experimentation demonstrated that differences between staphylococcal gut clearance in NYU and JAX female mice were attributed to the microbiome. However, NYU male and female mice harbor similar microbiomes, supporting the conclusion that the microbiome cannot account for the observed sex-dependent clearance of S. aureus gut colonization. To identify factors responsible for female clearance of S. aureus, the authors performed RNAseq on intestinal epithelial cells and cells enriched within the lamina propria. This analysis revealed sex-dependent transcriptional responses in both tissues. Genes associated with immune cell function and migration were distinctly expressed between the sexes. To determine which immune cell types contribute to S. aureus clearance Lejeune et al employed genetic and antibody-mediated immune cell depletion. This experiment demonstrated that CD4+ IL17+ cells and neutrophils promote the elimination of S. aureus from the gut. Subsequent experiments, including the use of the 'four core genotype model' were conducted to discern between the roles of sex chromosomes and sex hormones. This work demonstrated that sex-chromosome-linked genes are not responsible for clearance, increasing the likelihood that hormones play a dominant role in controlling S. aureus gut colonization.

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.

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.

(Jn 3:16; Ro 11:33; Tit 1:2).

(Jer 10:23; 17:9; 2Co 11:13-15; Ef 4:18, 19).

(Is 48:17, 18; Ro 12:2).

.H1

This is the old name. See blame: https://cs.android.com/android/platform/superproject/main/+/main:packages/modules/Wifi/service/java/com/android/server/wifi/WifiConfigManager.java;l=530;drc=0b982af97721be4665bd54b0cf174f82f386c7de

eLife assessment

This valuable manuscript investigated the role of glutamate signaling in the dorsomedial striatum of rats in a treadmill-based task and reported that it differs in goal-trackers compared to sign-trackers in a way that corresponds to differences in behaviour. The evidence supporting these claims is solid but could be further strengthened by adding more analyses and more detailed descriptions of current analyses. These findings will primarily be of interest to behavioural neuroscientists.

Reviewer #1 (Public review):

Summary:

The authors measured glutamate transients in the DMS of rats as they performed an action selection task. They identified diverse patterns of behavior and glutamate dynamics depending on the pre-existing behavioral phenotype of the rat (sign tracker or goal tracker). Using pathway-specific DREADDs, they showed that these behavioral phenotypes and their corresponding glutamate transients were differentially dependent on input from the prelimbic cortex to the DMS.

Strengths:

Overall there are some very interesting results that make an important contribution to the field. Notably, the results seem to point to differential recruitment of the PL-DMS pathway in goal-tracking vs sign-tracking behaviors.

Weaknesses:

There is a lot of missing information and data that should be reported/presented to allow a complete understanding of the findings and what was done. The writing of the manuscript was mostly quite clear, however, there are some specific leaps in logic that require more elaboration, and the focus at the start and end on cholinergic neurons and Parkinson's disease are, at the moment, confusing and require more justification.

Reviewer #2 (Public review):

Summary:

The authors aimed to determine whether goal-directed and cue-driven attentional strategies (goal- and sign-tracking phenotypes) were associated with variation in cued motor responses and dorsomedial striatal (DMS) glutamate transmission. They used a treadmill task in which cues indicated whether rats should turn or stop to receive a reward. They collected and analyzed several behavioral measures related to task performance with a focus on turns (performance, latency, duration) for which there are more measures than for stops. First, they established that goal-trackers perform better than sign-trackers in post-criterion turn performance (cued turns completed) and turn initiation. They used glutamate sensors to measure glutamate transmission in DMS. They performed analyses on glutamate traces that suggest phasic glutamate DMS dynamics to cues were primarily associated with successful turn performance and were more characteristic of goal-trackers (ie. rats with "goal-directed" attentional strategy). Smaller and more frequent DMS glutamate peaks were associated with other task events, cued misses (missed turns), cued stops, and reward delivery and were more characteristic of sign-trackers (i.e. rats with "cue-driven" attentional strategies). Consistent with the reported glutamate findings, chemogenetic inhibition of prelimbic-DMS glutamate transmission had an effect on goal-trackers' turn performance without affecting sign-trackers' performance in the treadmill task.

Strengths:

The power of the sign- and goal-tracking model to account for neurobiological and behavioral variability is critically important to the field's understanding of the heterogeneity of the brain in health and disease. The approach and methodology are sound in their contribution to this important effort.

The authors establish behavioral differences, measure a neurobiological correlate of relevance, and then manipulate that correlate in a broader circuitry and show a causal role in behavior that is consistent with neurobiological measurements and phenotypic differences.

Sophisticated analyses provide a compelling description of the authors' observations.

Weaknesses:

It is challenging to assess what is considered the "n" in each analysis (trial, session, rat, trace (averaged across a session or single trial)). Representative glutamate traces (n = 5 traces (out of hundreds of recorded traces)) are used to illustrate a central finding, while more conventional trial-averaged population activity traces are not presented or analyzed. The latter would provide much-needed support for the reported findings and conclusions. Digging deeper into the methods, results, and figure legends, provides some answers to the reader, but much can be done to clarify what each data point represents and, in particular, how each rat contributes to a reported finding (ie. single trial-averaged trace per session for multiple sessions, or dozens of single traces across multiple sessions).

Representative traces should in theory be consistent with population averages within phenotype, and if not, discussion of such inconsistencies would enrich the conclusions drawn from the study. In particular, population traces of the phasic cue response in GT may resemble the representative peak examples, while smaller irregular peaks of ST may be missed in a population average (averaged prolonged elevation) and could serve as a rationale for more sophisticated analyses of peak probability presented subsequently.

Reviewer #3 (Public review):

Summary:

Avila and colleagues investigate the role of glutamate signaling in the dorsomedial striatum in a treadmill-based task where rats learn to turn or stop their walking based on learning cue-associations that allow them to acquire rewards. Phenotypic variation in Pavlovian conditioned sign and goal-tracking behavior was examined, where behavioral differences in stopping and turning were observed. Glutamate signals in the DMS were recorded during the treadmill task and were related to features of cue-controlled movement, with a stronger relationship seen for goal trackers. Finally, chemogenic inhibition of prelimbic neurons projecting to the DMS (the predicted source of those glutamate signals), preferentially affected cued movement in goal trackers. The authors couch these experiments in the context of cognitive control-attentional mechanisms, movement disorders, and individual differences in cue reactivity.

Strengths:

Overall these studies are interesting and are of general relevance to a number of research questions in neurology and psychiatry. The assessment of the intersection of individual differences in cue-related learning strategies with movement-related questions - in this case, cued turning behavior - is an interesting and understudied question. The link between this work and growing notions of corticostriatal control of action selection makes it timely.

Weaknesses:

The clarity of the manuscript could be improved in several places, including in the graphical visualization of data. It is sometimes difficult to interpret the glutamate results, as presented, in the context of specific behavior, for example.

Author response:

Reviewer #1 (Public Review):

Strengths:

Overall there are some very interesting results that make an important contribution to the field. Notably, the results seem to point to differential recruitment of the PL-DMS pathway in goal-tracking vs sign-tracking behaviors.

Thank you.

Weaknesses:

There is a lot of missing information and data that should be reported/presented to allow a complete understanding of the findings and what was done. The writing of the manuscript was mostly quite clear, however, there are some specific leaps in logic that require more elaboration, and the focus at the start and end on cholinergic neurons and Parkinson's disease are, at the moment, confusing and require more justification.

In the revised paper, we provide additional information in support of results and clarify procedures and findings. Furthermore, we expand the discussion of the proposed interpretational framework that suggests that the contrasts between the cortical-striatal processing of movement cues in sign- versus goal trackers are related to previously established, parallel contrasts in the cortical cholinergic detection of attention-demanding cues.

Reviewer #2 (Public review):

Strengths:

The power of the sign- and goal-tracking model to account for neurobiological and behavioral variability is critically important to the field's understanding of the heterogeneity of the brain in health and disease. The approach and methodology are sound in their contribution to this important effort.

The authors establish behavioral differences, measure a neurobiological correlate of relevance, and then manipulate that correlate in a broader circuitry and show a causal role in behavior that is consistent with neurobiological measurements and phenotypic differences.

Sophisticated analyses provide a compelling description of the authors' observations.

Thank you.

Weaknesses:

It is challenging to assess what is considered the "n" in each analysis (trial, session, rat, trace (averaged across a session or single trial)). Representative glutamate traces (n = 5 traces (out of hundreds of recorded traces)) are used to illustrate a central finding, while more conventional trial-averaged population activity traces are not presented or analyzed. The latter would provide much-needed support for the reported findings and conclusions. Digging deeper into the methods, results, and figure legends, provides some answers to the reader, but much can be done to clarify what each data point represents and, in particular, how each rat contributes to a reported finding (ie. single trial-averaged trace per session for multiple sessions, or dozens of single traces across multiple sessions).

Representative traces should in theory be consistent with population averages within phenotype, and if not, discussion of such inconsistencies would enrich the conclusions drawn from the study. In particular, population traces of the phasic cue response in GT may resemble the representative peak examples, while smaller irregular peaks of ST may be missed in a population average (averaged prolonged elevation) and could serve as a rationale for more sophisticated analyses of peak probability presented subsequently.

Figures 5c-f depict individual data from all rats and trials. For all major analyses, the revised manuscript consolidates information about the number of rats per phenotype and sex, and the number of trials contributed by individual rats, in the result section.

As detailed in the section on statistical methods, and as mentioned by the reviewer under Strengths, we used advanced statistical methods to assure that data from individual animals contribute equally to the overall result, and to minimize the possibility that an inordinate number of trials obtained from just one or a couple of rats biased the overall analysis.

As the reviewer correctly pointed out, we have chosen not to show trial- or subject-averaged traces to illustrate glutamate release dynamics across trials. The present analyses focus on peak glutamate concentrations, the number of peaks, and the timing of peaks relative to a task cue or a behavioral event. Within a response bin, such as the 2-s period following turn cues, glutamate peaks – as defined in Methods - occur at variable times relative to cue onset.  Averaging traces over a population of rats or trials would “wash-out” the phenotype- and task event-dependent patterns of glutamate peaks, yielding, for example, a single, nearly 2-s long plateau for cue-locked glutamate recordings from STs (Figure 5b). Thus, subject- or trial-averaged traces would not illustrate the major findings described in this paper and would rather be uninformative. As already mentioned, individual data from all subjects and trials are shown in Figs 5c-f.

Reviewer #3 (Public review):

Strengths:

Overall these studies are interesting and are of general relevance to a number of research questions in neurology and psychiatry. The assessment of the intersection of individual differences in cue-related learning strategies with movement-related questions - in this case, cued turning behavior - is an interesting and understudied question. The link between this work and growing notions of corticostriatal control of action selection makes it timely.

Thank you.

Weaknesses:

The clarity of the manuscript could be improved in several places, including in the graphical visualization of data. It is sometimes difficult to interpret the glutamate results, as presented, in the context of specific behavior, for example.

We appreciate the reviewer’s concerns about the complexity of some of the graphics, particularly the results from the arguably innovative analysis illustrated in Figure 6. Figure 6 illustrates that the likelihood of a cued turn can be predicted based on single and combined glutamate peak characteristics. The revised legend for this figure provides additional information and examples to ease the readers’ access to this figure.

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eLife assessment

This important study reports the formation of a new organelle, called giant unilocular vacuole (GUVac), in mammary epithelial cells through a macropinocytosis-like process. The evidence supporting conclusions is convincing, using state-of-the-art cell biology techniques. This work will be of interest to cell biologists and contribute to the understanding of cell survival mechanisms against anoikis.

Reviewer #1 (Public review):

The authors found that the loss of cell-ECM adhesion leads to the formation of giant monocular vacuoles in mammary epithelial cells. This process takes place in a macropinocytosis-like process and involves PI3 kinase. They further identified dynamin and septin as essential machinery for this process. Interestingly, this process is reversible and appears to protect cells from cell death.

Strengths: The data are clean and convincing to support the conclusions. The analysis is comprehensive, using multiple approaches such as SIM and TEM. The discussion on lactation is plausible and interesting.

Weaknesses: As the first paper describing this phenomenon, it is adequate. However, the elucidation of the molecular mechanisms is not as exciting as it does not describe anything new. It is hoped that novel mechanisms will be elucidated in the future. Especially the molecules involved in the reversing process could be quite interesting.

Reviewer #2 (Public review):

Summary:

The manuscript describes an interesting observation and provides initial steps towards understanding the underlying molecular mechanism.

The manuscript describes that the majority of non-tumorigenic mammary gland epithelial cells (MCF-10A) in suspension initiate entosis. A smaller fraction of cells form a single giant unilocular vacuole (hereafter referred to as a GUVac). GUVac appeared to be empty and did not contain invading (entotic) cells. The formation of GUVac could be promoted by disrupting actin polymerisation with LatB and CytoD. The formation of GUVacs correlated with resistance to anoikis. GUVac formation was detected in several other epithelial cells from secretory tissues.

The authors then use electron microscopy and super-resolution imaging to describe the biogenesis of GUVac. They find that GUVac formation is initiated by a micropinocytosis-like phenomenon (that is independent of actin polymerisation). This process leads to the formation of large plasma membrane invaginations, that pinch off from the PM to form larger vesicles that fuse with each other into GUVacs.

Inhibition of actin polymerisation in suspended MCF-10a leads to the recruitment of Septin 6 to the PM via its amphipathic helix. Treatment with FCF (a septin polymerisation inhibitor) blocked GUVac biogenesis, as did pharmacological inhibition of dynamin-mediated membrane fission. The fusion of these vesicles in GUVacs required (perhaps not surprisingly) PI3P.

Strengths:

The authors have made an interesting and potentially important observation. They describe the formation of an endo-lysosomal organelle (a giant unilocular vacuole - GUVac) in suspended epithelial cells and correlate the formation of GUVacs with resistance to aniokis.

Comments on revised version:

Additional experiments, including a better characterization of GUVac biogenesis, as well as knockdown and knock out of class II PI3Kα (PI3K-C2α) or class III PI3K (VPS34), have improved the manuscript.

Reviewer #3 (Public review):

Summary:

Loss of cell attachment to extracellular matrix (ECM) triggers aniokis (a type of programmed cell death), and resistance to aniokis plays a role in cancer development. However, mechanisms underlying anoikis resistance, and the precise role of F-actin, are not fully known.

Here authors describe the formation of a new organelle, giant unilocular vacuole (GUVac), in cells whose F-actin is disrupted during loss of matrix attachment. GUVac formation (diameter >500 nm) resulted from a previously unrecognised macropinocytosis-like process, characterized by inwardly curved micron-sized plasma membrane invaginations, dependent on F-actin depolymerization, septin recruitment and PI(3)P. Finally, the authors show GUVac formation after loss of matrix attachment promotes resistance to anoikis.

From these results, authors conclude that GUVac formation promotes cell survival in environments where F-actin is disrupted and conditions of cell stress.

Strengths:

The manuscript is clear and well-written, figures are all presented at a very high level.

A variety of cutting edge cell biology techniques (eg time-lapse imaging, EM, super-resolution microscopy) are used to study the role of cytoskeleton in GUVac formation, discovering (i) a macropinocytosis-like process dependent on F-actin depolymerisation, SEPT6 recruitment and PI(3)P contributes to GUVac formation, and (ii) GUVac formation is associated with resistance to cell death.

Experimental work was advanced in response to reviewers' comments, improving the manuscript message and mechanistic advance.

Weaknesses:

The manuscript is highly reliant on the use of drugs, or combinations of drugs, for long periods of time (6hr, 18hr). However, in the revised manuscript, authors test conclusions drawn from experiments involving drugs using other canonical cell biology approaches.

The molecular characterisation of GUVacs has been advanced, although not fully resolved.

The authors show (mostly using pharmacological inhibition) that F-actin is key for GUVac formation. The precise role of F-actin / GUVac formation in anoikis resistance will be the focus of future work.

Author response:

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

Reviewer #1 (Public Review):

Summary:

The authors found that the loss of cell-ECM adhesion leads to the formation of giant monocular vacuoles in mammary epithelial cells. This process takes place in a macropinocytosis-like process and involves PI3 kinase. They further identified dynamin and septin as essential machinery for this process. Interestingly, this process is reversible and appears to protect cells from cell death.

Strengths:

The data are clean and convincing to support the conclusions. The analysis is comprehensive, using multiple approaches such as SIM and TEM. The discussion on lactation is plausible and interesting.

We thank the reviewer for the summary of our study and the positive comment.

Weaknesses:

As the first paper describing this phenomenon, it is adequate. However, the elucidation of the molecular mechanisms is not as exciting as it does not describe anything new. It is hoped that novel mechanisms will be elucidated in the future. In particular, the molecules involved in the reversing process could be quite interesting.

We agree with the reviewer’s comments and believe that investigating the molecular mechanisms involved in reversing GUVac formation, as illustrated in Figure 5J, would be valuable for future research.

Additionally, the relationship to conventional endocytic compartments, such as early and late endosomes, is not analyzed.

We thank the reviewer for the valuable comment. To determine whether GUVac displays markers of other endomembrane systems, we analyzed several markers, including EEA1, Rab5, LC3B, LAMP1, and Transferrin receptor (TfR). At early time points (1 h), we observed several large vesicles that had taken up 70kDa Dextran and exhibited EEA1 or Rab5, markers of early endosomes. By 6 hours, some of these large vesicles showed lysotracker positivity, indicating a transition from early to late endosomal fate, similar to the maturation process of conventional macropinocytic vesicles (see new Figure 1-figure supplement 2A). However, once the vesicles fused, grew, and became GUVac, these markers did not consistently correspond with the GUVac membrane but were instead unevenly distributed around it (new Figure 1-figure supplement 2B, C). This made it difficult to determine whether they were localized to separate organelles or part of the GUVac membrane. Interestingly, we found that the Transferrin receptor (TfR), which also marks a general membrane population involved in the endocytic pathway (such as PM invagination), was evenly distributed within the GUVac membrane (new Figure 1-figure supplement 2B, D). Therefore, GUVac appears to possess heterogeneous characteristics of the endocytic membrane, mainly with the TfR marker (likely due to PM invagination) and some partial endomembrane system markers. However, further analysis would be required to confirm this.

Reviewer #2 (Public Review):

Summary:

The manuscript "Formation of a giant unilocular vacuole via macropinocytosis-like process confers anoikis resistance" describes an interesting observation and provides initial steps towards understanding the underlying molecular mechanism.

The manuscript describes that the majority of non-tumorigenic mammary gland epithelial cells (MCF-10A) in suspension initiate entosis. A smaller fraction of cells forms a single giant unilocular vacuole (hereafter referred to as a GUVac). GUVac appeared to be empty and did not contain invading (entotic) cells. The formation of GUVac could be promoted by disrupting actin polymerisation with LatB and CytoD. The formation of GUVacs correlated with resistance to anoikis. GUVac formation was detected in several other epithelial cells from secretory tissues.

The authors then use electron microscopy and super-resolution imaging to describe the biogenesis of GUVac. They find that GUVac formation is initiated by a micropinocytosis-like phenomenon (that is independent of actin polymerisation). This process leads to the formation of large plasma membrane invaginations, that pinch off from the PM to form larger vesicles that fuse with each other into GUVacs.

Inhibition of actin polymerisation in suspended MCF-10a leads to the recruitment of Septin 6 to the PM via its amphipathic helix. Treatment with FCF (a septin polymerisation inhibitor) blocked GUVac biogenesis, as did pharmacological inhibition of dynamin-mediated membrane fission. The fusion of these vesicles in GUVacs required (perhaps not surprisingly) PI3P.

Strengths:

The authors have made an interesting and potentially important observation. They describe the formation of an endo-lysosomal organelle (a giant unilocular vacuole - GUVac) in suspended epithelial cells and correlate the formation of GUVacs with resistance to aniokis.

We thank the reviewer for the summary of our study and the positive comment.

Weaknesses:

My major concern is the experimental strategy that is used throughout the paper to induce and study the formation GUVac. Almost every experiment is conducted in suspended cells that were treated with actin depolymerising drugs (e.g. LatB) and thus almost all key conclusions are based on the results of these experiments. I only have a few suggestions that would improve these experiments or change their outcome and interpretation. Yet, I believe it is essential to identify the endogenous pathway leading to the actin depolymerisation that drives the formation of GUVacs in detached epithelial cells (or alternatively to figure out how it is suppressed in most detached cells). A first step in that direction would be to investigate the polymerization status of actin in MCF-10a cells that 'spontaneously' form GUVacs and to test if these cells also become resistant to anoikis.

We thank the reviewer for the valuable comments and fully acknowledge the limitations of our approach. Many detached cells likely tend to contact each other for cell aggregations to suppress GUVac formation. However, it is unclear whether cells that spontaneously form GUVac in suspension have a weakened F-actin structure, which would be valuable to investigate in future studies.

Also, it would be great (and I believe reasonably easy) to better characterise molecular markers of GUVacs (LAMP's, Rab's, Cathepsins, etc....) to discriminate them from other endosomal organelles

In response to a similar comment from Reviewer 1, we analyzed markers of other endocytic compartments, including EEA1, Rab5, Transferrin receptor (TfR), LC3B, and LAMP1. At early time points (1 h), we observed several large vesicles that had taken up 70kDa Dextran and exhibited EEA1 or Rab5, markers of early endosomes. By 6 hours, some of these large vesicles showed lysotracker positivity, indicating a transition from early to late endosomal fate, similar to the maturation process of conventional macropinocytic vesicles (see new Figure 1-figure supplement 2A). However, once the vesicles fused, grew, and became GUVac, these markers did not consistently correspond with the GUVac membrane but were instead unevenly distributed around it (new Figure 1-figure supplement 2B, C). This made it difficult to determine whether they were localized to separate organelles or part of the GUVac membrane. Interestingly, we found that the Transferrin receptor (TfR), which also marks a general membrane population involved in the endocytic pathway (such as PM invagination), was evenly distributed within the GUVac membrane (new Figure 1-figure supplement 2B, D). Therefore, GUVac appears to possess heterogeneous characteristics of the endocytic membrane, mainly with the TfR marker (likely due to PM invagination) and some partial endomembrane system markers. However, further analysis would be required to confirm this.

Reviewer #3 (Public Review):

Summary:

Loss of cell attachment to extracellular matrix (ECM) triggers aniokis (a type of programmed cell death), and resistance to aniokis plays a role in cancer development. However, mechanisms underlying anoikis resistance, and the precise role of F-actin, are not fully known.

Here the authors describe the formation of a new organelle, giant unilocular vacuole (GUVac), in cells whose F-actin is disrupted during loss of matrix attachment. GUVac formation (diameter >500 nm) resulted from a previously unrecognised macropinocytosis-like process, characterized by inwardly curved micron-sized plasma membrane invaginations, dependent on F-actin depolymerization, septin recruitment, and PI(3)P. Finally, the authors show GUVac formation after loss of matrix attachment promotes resistance to anoikis.

From these results, the authors conclude that GUVac formation promotes cell survival in environments where F-actin is disrupted and conditions of cell stress.

Strengths:

The manuscript is clear and well-written, figures are all presented at a very high level.

A variety of cutting-edge cell biology techniques (eg time-lapse imaging, EM, super-resolution microscopy) are used to study the role of the cytoskeleton in GUVac formation. It is discovered that: (i) a macropinocytosis-like process dependent on F-actin depolymerisation, SEPT6 recruitment, and PI(3)P contributes to GUVac formation, and (ii) GUVac formation is associated with resistance to cell death.

We thank the reviewer for the concise summary of our study and positive comments.

Weaknesses:

The manuscript is highly reliant on the use of drugs, or combinations of drugs, for long periods of time (6hr, 18hr..). Wherever possible the authors should test conclusions drawn from experiments involving drugs also using other canonical cell biology approaches (eg siRNA, Crispr). Although suggestive as a first approach, it is not reliable to draw conclusions from experiments where only drug combinations are being advanced (eg LatB + FCF).

We thank the reviewer for the comment and suggestion. As suggested, we employed siRNAs targeting Septin2 and Septin9 in cells treated with LatB as an alternative to the drug combination approach. This genetic approach, combined with chemical treatment, led to a consistent reduction in GUVac formation, similar to the results observed with LatB+FCF treatment (see new Figure 3D-WB and graph).

F-actin is well known to play a wide variety of roles in cell death and other canonical cell death pathways (PMID: 26292640). The authors show using pharmacological inhibition that F-actin is key for GUVac formation. However, especially when testing for physiological relevance, how can these other roles for F-actin be ruled out?

In Figure 5, we investigate the physiological relevance of GUVac, highlighting its role in suppressing apoptosis and enhancing anoikis resistance. As the reviewer correctly noted, F-actin inhibition is known to reduce apoptotic signaling (PMID: 16072039). However, we observed that anoikis resistance is lost when GUVac is suppressed through knockout of either PI3KC2alpha or VPS34 in cells with F-actin disrupted by LatB (Figure 5I). This suggests that GUVac plays a role in suppressing apoptosis independently of F-actin depolymerization-induced apoptosis resistance.

To test the role of septins in GUVac formation only recruitment studies and no direct functional work is performed. A drug forchlofeneuron (FCF) is used, but this is well known to have off-target effects (PMID: 27473917).

We thank the reviewer for the valuable comments. To eliminate potential off-target effects of FCF, as described above, we employed siRNA targeting Septin 2 and Septin 9 and observed similar results (see new Figure 3D).

Cells that possess GUVac are resistant to aniokis, but how are these cells resistant? This report is focused on mechanisms underlying GUVac formation and does not directly test for mechanisms underlying aniokis resistance.

We fully agree with the reviewer’s comments and recognize the importance of uncovering the mechanism behind GUVac-mediated anoikis resistance for future research. It will likely be essential to investigate how prosurvival signaling pathways are activated, like the PI3K-AKT signaling (as shown in Figure 5-Supplement 1) or the YAP/TAZ pathway.

Reviewer #1 (Recommendations For The Authors):

Figure 4 Supplemental 1. What are the faint bands in clones 23, 26, and 29? Are they cross-reacting bands? Or Vps34?

We apologize if the data in our original manuscript were misleading. To clarify the specificity of the VPS34 antibody in the Western blot analysis of VPS34 KO clones, we compared these samples with those from siRNA-mediated VPS34-depleted cells (see new Figure 4-Supplement 1E, which replaces the original Figure). Consistent with the known size of VPS34 at approximately 100 kDa, we observed a clear disappearance of the VPS34 band at around 100 kDa in the sgVPS34 clones, which was comparable to the size observed in siRNA-treated cells.

Reviewer #2 (Recommendations For The Authors):

Figure 2B: Only 4 cells were counted. Please comment.

At the outset of this study, we faced technical difficulties in preparing TEM samples, which limited the number of samples included in Figure 2B. However, subsequent experiments that combined TEM with super-resolution microscopy, as shown in Figure 4D-F, produced similar data on plasma membrane invagination, as depicted in Figure 2B, which is the initial step in the formation of GUVac.

Figure 2C: do cells shrink after treatment with EIPA or LatB? Please comment.

We apologize if the data presented in our original manuscript were misleading. Control cells treated with DMSO display multiple cell-in-cell structures (known as 'entosis'), which typically results in a larger overall cell size compared to EIPA or LatB-treated non-entotic single cells. This might have created the impression that cells shrink relative to the control under EIPA or LatB treatment. We hope this explanation has answered the reviewer’s question.

Figure 3A: The changes in the localization of mCherry-Spetin6 appear to be very dramatic. Are these results properly reflected by the quantification in Figure 3B? Is indeed the entire mCherry-Spetin6 pool recruited to the plasma membrane? Wouldn't that imply that all other septin6-regulated processes are blocked?

Again, we apologize if the data presented in our original manuscript caused any confusion. In Figure 3B, we quantified only the number of filament-like Septin6 structures predominantly observed in LatB-treated cells, rather than measuring changes in the relative fluorescence intensity of Septin6 between the plasma membrane and the cytosol. Although we could not estimate the proportion of total Septin6 recruited to the plasma membrane from the cytosol based solely on Figure 3A-B, conducting plasma membrane fractionation experiments with endogenous Septin6, followed by Western blot analysis, would be valuable for addressing this issue in future studies.

Figure 3D: Please also provide data for the 6h time-point (as in all other experiments).

We apologize for omitting the 6-hour time point, which may have caused confusion. The new Figure 3E (previously Figure 3D) shows that recruitment of wild-type Septin6, but not the amphipathic helix (AH) deletion mutant, occurs at a 6-hour time point.

Figure 3E: Molecular weight for western blot is missing.

We thank the reviewer for pointing this out and have revised the figure accordingly.

Line 188 - Title of subchapter could include dynamin.

We appreciate the reviewer’s helpful suggestion and have updated the revised manuscript to reflect this. The phrase "Recruitment of Septin to the Fluctuating Plasma Membrane Drives Macropinocytosis-like Process" has been revised to "Septin and Dynamin Drive Macropinocytosis-like Process".

Line 450 - please describe how the genotyping of MCF10a gene-engineered cells was performed.

We confirmed the knockout of MCF10A cell lines by Western blot analysis using specific antibodies against VPS34 and PI3KC2α, rather than through genotyping.

Reviewer #3 (Recommendations For The Authors):

(1) The manuscript is highly reliant on the use of drugs, or combinations of drugs, for long periods of time (6hr, 18hr..). Wherever possible authors should test conclusions drawn from experiments involving drugs also using other canonical cell biology approaches (eg siRNA, Crispr). Although suggestive as a first approach, it is not reliable to draw conclusions from experiments where only drug combinations are being advanced (eg LatB + FCF).

We thank the reviewer for the comment. As suggested, we employed siRNAs targeting Septin2 and Septin9 in cells treated with LatB as an alternative to the drug combination approach. This genetic approach, combined with chemical treatment, led to a consistent reduction in GUVac formation, similar to the results observed with LatB+FCF treatment (see new Figure 3D-WB and graph).

(2) SEPT6 is recruited at an inwardly curved plasma membrane. Can the authors better describe what type of structure is being recruited/quantified (filaments, collar-like structures, etc)?

We apologize if the data presented was unclear. As outlined in the Methods section in the original manuscript, we detected puncta-like Septin6 structures using the Find Maxima tool in ImageJ, which could include both filamentous and collar-like structures that were less apparent in the DMSO control. We have added additional explanations in the revised manuscript in the legend of Figure 3B to clarify the recruitment of Septin6.

Previous work has shown that octameric septin complexes are linking actin to the plasma membrane (PMID: 36562751). Tests for the recruitment/function of other key septins such as SEPT7 and SEPT9 to support conclusions.

As previously mentioned, to further explore the role of other septin family members in GUVac formation, we tested the roles of Septin9 and Septin2 using siRNAs and found that they are essential for this process (see new Figure 3D). Unfortunately, we were unable to assess the localization of Septin2 and Septin9 due to the lack of suitable antibodies for detecting endogenous proteins by immunofluorescence.

(3) SEPT6 recruitment is impaired when cells are treated with FCF. FCF is well known to have off-target effects (PMID: 25217460, PMID: 27473917). siRNA for SEPT2, SEPT7 and/or SEPT9 can be used to test phenotypes obtained using FCF.

We thank the reviewer for the comment. As also mentioned above, to eliminate potential off-target effects of FCF, we used siRNA to target Septin2 and Septin9, and obtained similar results (see new Figure 3D).

(4) SEPT6 is recruited to the fluctuating cell membrane via the amphipathic helix (AH) domain (Figure 3D). Are these only representative images? It is not clear what readers should be looking at - can the authors provide arrows to highlight what is the difference +/- AH? Can something be quantified?

We thank the reviewer for the suggestion and have added arrows from the inset of the merge pannel Figure 3E, along with line profile analysis, to emphasize the failure of the AH deletion mutant of Septin6 to recruit to the plasma membrane.

Throughout Figure 3, why use LatB treatment at different times?

We apologize if this was not clearly addressed in our original manuscript. Throughout the study, we primarily used an 18-hour LatB treatment to evaluate GUVac formation, as this longer period allows for gradual vesicle fusion. In contrast, we utilized 6-hour treatments to demonstrate that Septin6 recruitment and subsequent plasma membrane invagination occur at earlier time points, as evidenced by the data in Figure 2G (super-resolution live imaging) and Figure 4D (electron microscopy analysis). This clarification has been incorporated into the revised manuscript.

(5) F-actin is well known to play a wide variety of roles in cell death and other canonical cell death pathways (PMID: 26292640). The authors show using pharmacological inhibition that F-actin is key for GUVac formation. However, especially when testing for physiological relevance, how can these other roles for F-actin be ruled out?

In Figure 5, we investigate the physiological relevance of GUVac, highlighting its role in suppressing apoptosis and enhancing anoikis resistance. As the reviewer correctly noted, F-actin inhibition is known to reduce apoptotic signaling (PMID: 16072039). However, when GUVac is suppressed through knockout of either PI3KC2alpha or VPS34 in cells with F-actin disrupted by LatB, anoikis resistance is lost (see Figure 5H, I). This suggests that GUVac plays a role in suppressing apoptosis independently of F-actin depolymerization-induced apoptosis resistance.

(6) Cells that possess GUVac are resistant to aniokis, but how are these cells resistant? This report is focused on mechanisms underlying GUVac formation and does not directly test for mechanisms underlying aniokis resistance.

We fully agree with the reviewer’s comments and recognize the importance of uncovering the mechanism behind GUVac-mediated anoikis resistance for future research. It will likely be essential to investigate how prosurvival signaling pathways are activated, like the PI3K-AKT signaling (as shown in Figure 5-Supplement 1) or the YAP/TAZ pathway.

(7) In the Discussion, there is a lot of text on involution and speculative relevance of GUVac formation. I would focus the Discussion more on the clear results discovered here.

We thank the reviewer’s feedback and have revised the discussion to reduce its length concerning involution.

(8) Figure 5. GUVac formation promotes cell survival in altered actin and matrix environments. In Figure 5J, it will not be clear to readers outside the field what is being shown here.

We appreciate the reviewer’s suggestion and have added two distinct dotted lines around the vacuole and cell area in the revised figure to emphasize the gradual reduction in its size over time.

cws

Author response:

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

Reviewer #1 (Public Review):

Summary:

SUMO proteins are processed and then conjugated to other proteins via a C-terminal di-glycine motif. In contrast, the N-terminus of some SUMO proteins (SUMO2/3) contains lysine residues that are important for the formation of SUMO chains. Using NMR studies, the N-terminus of SUMO was previously reported to be flexible (Bayer et al., 1998). The authors are investigating the role of the flexible (referred to as intrinsically disordered) N-terminus of several SUMO proteins. They report their findings and modeling data that this intrinsically disordered N-terminus of SUMO1 (and the C. elegans Smo1) regulates the interaction of SUMO with SUMO interacting motifs (SIMs).

Strengths:

Among the strongest experimental data suggesting that the N-terminus plays an inhibitory function are their observations that

(1) SUMO1∆N19 binds more efficiently to SIM-containing Usp25, Tdp2, and RanBp2,<br /> (2) SUMO1∆N19 shows improved sumoylation of Usp25,<br /> (3) changing negatively-charged residues, ED11,12KK in the SUMO1 N-terminus increased the interaction and sumoylation with/of USP25.

The paper is very well-organized, clearly written, and the experimental data are of high quality. There is good evidence that the N-terminus of SUMO1 plays a role in regulating its binding and conjugation to SIM-containing proteins. Therefore, the authors are presenting a new twist in the ever-evolving saga of SUMO, SIMs, and sumoylation.

Weaknesses:

Much has been learned about SUMO through structure-function analyses and this study is another excellent example. I would like to suggest that the authors take some extra time to place their findings into the context of previous SUMO structure-function analyses. Furthermore, it would be fitting to place their finding of a potential role of N-terminally truncated Smo1 into the context of the many prior findings that have been made with regard to the C. elegans SUMO field. Finally, regarding their data modeling/simulation, there are questions regarding the data comparisons and whether manipulations of the N-terminus also have an effect on the 70/80 region of the core.

We thank the reviewer for insightful and constructive comments to improve our manuscript. We have now placed our findings in the context of previous structure-function analyses at several occasions, details of which can be found in our replies to the detailed comments.

We are also placing the C. elegans data into context of previously published findings on the various functions of SMO-1 in controlling development and maintaining genomic stability (lines 510ff). Finally, we addressed all questions and suggestions regarding comparison of MD simulation and NMR data, and addressed the question whether mutations in the N-terminus affected the 70/80 region. We have now clarified in the manuscript that the sum of MD and NMR data does not allow a clear-cut conclusion on the 70/80 interactions. 

Reviewer #2 (Public Review):

Summary:

This very interesting study originated from a serendipitous observation that the deletion of the disordered N-terminal tail of human SUMO1 enhances its binding to its interaction partners. This suggested that the N terminus of SUMO1 might be an intrinsic competitive inhibitor of SUMO-interacting motif (SIM) binding to SUMO1. Subsequent experiments support this mechanism, showing that in humans it is specific to SUMO1 and does not extend to SUMO2 or SUMO3 (except, perhaps, when the N terminus of SUMO2 becomes phosphorylated, as the authors intriguingly suggest - and partially demonstrate). The auto-inhibition of SUMO1 via its N-terminal tail apparently explains the lower binding of SUMO1 compared to SUMO2 to some SIMs and lower SIM-dependent SUMOylation of some substrates with SUMO1 compared to SUMO2, thus adding an important element to the puzzle of SUMO paralogue preference. In line with this explanation, N-terminally truncated SUMO1 was equally efficient to SUMO2 in the studied cases. The inhibitory role of SUMO1's N terminus appears conserved in other species including S. cerevisiae and C. elegans, both of which contain only one SUMO. The study also elucidates the molecular mechanism by which the disordered N-terminal region of SUMO1 can exert this auto-inhibitory effect. This appears to depend on the transient, very highly dynamic physical interaction between the N terminus and the surroundings of the SIM-binding groove based mostly on electrostatic interactions between acidic residues in the N terminus and basic residues around the groove.

Strengths:

A key strength of this study is the interplay of different techniques, including biochemical experiments, NMR, molecular dynamics simulations, and, at the end, in vivo experiments. The experiments performed with these different techniques inform each other in a productive way and strengthen each others' conclusions. A further strength is the detailed and clear text, which patiently introduces, describes, and discusses the study. Finally, in terms of the message, the study has a clear, mechanistic message of fundamental importance for various aspects of the SUMO field, and also more generally for protein biochemists interested in the functional importance of intrinsically disordered regions.

Weaknesses:

Some of the authors' conclusions are similar to those from a recent study by Lussier-Price et al. (NAR, 2022), the two studies likely representing independent inquiries into a similar topic. I don't see it as a weakness by itself (on the contrary), but it seems like a lost opportunity not to discuss at more length the congruence between these two studies in the discussion (Lussier-Price is only very briefly cited). Another point that can be raised concerns the wording of conclusions from molecular dynamics. The use of molecular dynamics simulations in this study has been rigorous and fruitful - indeed, it can be a model for such studies. Nonetheless, parameters derived from molecular dynamics simulations, including kon and koff values, could be more clearly described as coming from simulations and not experiments. Lastly, some of the conclusions - such as enhanced binding to SIM-containing proteins upon N-terminal deletion - could be additionally addressed with a biophysical technique (e.g. ITC) that is more quantitative than gel-based pull-down assays - but I don't think it is a must.

Thank you very much for pointing towards the study of Lussier-Price. We now point out congruent findings in more detail in the discussion.

We also thank the reviewer for the advice to present and discuss the MD findings more clearly, and more explicitly specify which parameters were obtained from MD. We have made changes throughout the Results and Discussion sections.

We agree that it would be a nice addition to use ITC measurements as a more quantitative method to assess differences in binding affinities upon deletion of the SUMO N-terminus. We had tried to measure affinities between SUMO and SIM-containing binding partners by ITC but in our hand, this failed. In the study of Lussier-Price et al., the authors were able to measure differences in SIM binding upon deleting the N-terminus but only when they used phosphorylated SIM peptides. Follow-up studies, e.g., on the effect of SUMO’s N-terminal modifications should certainly include more quantitative measurement such as ITCs, however these studies will have to be picked up by others. The main PI Frauke Melchior and most contributing authors moved on to new challenges.

Reviewing Editor (Recommendations For The Authors):

Both reviewers agreed that your manuscript presents novel results and the key findings including the self-inhibitory role of the N-terminal tail of SUMO proteins in their interaction with SIM are overall well supported by the data. The reviewers also provided constructive suggestions. They pointed out that some simulation results are not clear, which could be strengthened by control analysis and by toning down the related descriptions. In addition, Reviewer 2 suggested that the conclusions from the current biochemical and simulation studies could be further reinforced by more quantitative binding measurements. We hope that these points can be addressed in the revision.

We thank both reviewers for their insightful and constructive comments and the appreciative tone. In our replies above and below we address most of the raised concerns.

We strongly recommend the change of the current title. eLife advises that the authors avoid unfamiliar abbreviations or acronyms, or spell out in full or provide a brief explanation for any acronyms in the title.

We changed the title to “The intrinsically disordered N-terminus of SUMO1 is an intramolecular inhibitor of SUMO1 interactions” to avoid acronyms in the title.

Reviewer #1 (Recommendations For The Authors):

Major:

Lines 190-262: The authors use NMR experiments and all-atom molecular dynamics (MD) simulations. They state that this approach reveals a highly dynamic interaction of the SUMO1 N-terminus with the core and that the SIM binding groove and the 70/80 region are temporarily occupied by the SUMO1 N-terminus (Fig. 3C). After comparing SUMO1, Smt3, SUMO2, and Smo1 by this approach they state that the most striking differences exist for the interaction with the SIM-binding groove, while interactions with the 70/80 region are rather comparable.

The authors then compare the average binding time data of Figure 3C, D, E, F in Figure 3G.

It is not clear which data points are included in the bar graphs of Figure 3G and how the individual data points (there are maybe 8 shown in each bar) correspond to the data shown in 3C, D, E, and F or if they are iterations (n?) of the modeled data. This should be clarified. Also, for comparison, the authors should also graph the average data of the 70/80 region.

We clarified the data shown in Figure 3G as well as 3C-F, and how It relates to each other. Indeed, Figure 3G shows 8 data points for 8 trajectories, and their average. Figure 3C-F are based on the same 8 trajectories, in this case broken down per residue of the protein. The average data of the 70/80 region does not show any significant differences across the proteins, as already pretty well visible from panels 3C-F.

Line 322: More concerning, in Figure 5, the authors model how a ED11,12KK mutations disrupt the interaction between the N-terminus and the SIM-binding groove and state that this mutation leaves interactions with the 70/80 region largely untouched. Again, it is not clear which data points are included in the bar graph 5D and 5G and how many iterations. Furthermore, data of 5B, C (SUMO1) and 5 E, F (smo1) do show clear differences between the WT and mutants affecting both the SIM binding groove and the 70/80 region. The double mutation clearly seems to affect the 70/80 region when comparing 5B, C (SUMO1) and 5 E, F (smo1), but this result is not mentioned. Indeed, the authors state that the double mutants leave the interactions with the 70/80 region largely untouched, but this is not borne out by the data presented.

We improved the clarity of the legend of Figure 5 as suggested. We also thank the reviewer for the comment on the changes in the 70/80 region, to which we point the reader explicitly now in the corresponding Results section. We, however, refrain from drawing conclusions from the MD in this case, as this change is not supported by the NMR measurements (Fig 5a). Charge-charge interactions in the charge-rich double mutants might be overstabilized in the MD simulations, a problem known for the canonical force fields used here, albeit tailoring it for IDPs. We now cite a corresponding reference. Another potential explanation for that the CMPs do not take this change up upon mutation could be a pronounced fuzziness in this region, which however, in turn, is not apparent from the simulations. We would therefore not overinterpret these differences in the 70/80 region. Our key conclusion is the loss of interactions with the SIM-binding groove – and thus of cis-inhibition – by mutations, which is supported by both, MD and NMR.  

341: In their N-termini substitution experiments, the authors show that the SUMO1 core that carries the SUMO2 N-terminus (S2N-S1C) binds USP25 more efficiently than wt SUMO1. However, the SUMO1 core that carries the SUMO2 N-terminus is also reduced in its interaction with Usp25. This is concerning as the SUMO2 N-terminus was not predicted to interfere with SIM binding.

We were excited to see that the inhibitory potential could be partially transplanted by swapping the N-termini of SUMO1 and SUMO2 demonstrating that some important determinants are contained within the N-terminal tail of SUMO proteins. However, the observed effects were partial indicating that also other determinants contribute and that we do not yet understand all aspects. Obviously, the SUMO1 and SUMO2 cores are similar (also in the area comprising the SIM binding groove) but not identical, and as the inhibition arises from dynamic interactions of the N-terminus with the SIM binding area, differences in the SUMO cores and in residues flanking SUMO’s N-terminus are likely to influence the inhibitory potential as well.

Blue bars in 3G, 5D, and 6A look surprisingly similar down to the individual data points - does that mean that the same SUMO1 WT data was recycled for these different experiments? This is concerning to me.

The data displayed in the figures listed above are derived from in silico simulations and indeed display the same data set for the case of SUMO1 WT repeatedly, as we also state in the figure legends (we had done so for 5D “(identical to Fig. 3C)”, and now added the same comment to 6A, thanks for pointing this out). We show the SUMO1 WT data again to facilitate comparing the different SUMO variants in MD simulations.

Line 352 and 496: The authors used phosphomimetic mutants to assess the effect of SUMO2 N-term phosphorylation on interaction with Usp25. The data suggest a mild phenotype (6G) which is borne out by the quantization in 6H. In contrast, the effect of an array of modifications for SUMO1 (Figures 6A - C) was solely analyzed by MD simulation. If possible, this data should be confirmed, at least by using a phosphomimetic at the Ser9 position of SUMO1. Alternatively, a caveat explaining the need to confirm these predictions by actual experiments should be added to the text.

Already now we state in “Limitations of the study” that “While our MD simulations and in vitro studies with selected mutants point in this direction, we have not been able to generate quantitatively acetylated and/or phosphorylated SUMO variants to test this hypothesis.”

We agree that the hypothesis needs experimental validation. Phosphomimetic amino acids can be a useful tool in some cases but fail to mimic a phosphor group in other cases. In the past we had tested whether replacing Ser9 by a potentially phospho-mimicking amino acid (Glu) would further diminish binding of SIM-containing proteins compared to already strongly reduced binding to wt SUMO1 but the effect was too mild to yield a significant difference, at least in our assay. Whether this is due to a lack of Glu in mimicking phosphorylation of Ser9, due to limited sensitivity of our pulldown assay combined with the challenge to detect inhibition compared to an already inhibited state, or a failure in our hypothesis we were not able to clarify so far. We therefore now also added a sentence to the paragraph introducing phosphoSer9 MD simulations (now line 367) stating that this hypothesis needs to be tested experimentally.

Minor:

Line 110: the authors should include references for their summary statement that "A defining feature of SUMO proteins is the intrinsically disordered N-terminus, whose function is only partly understood." Also cite in line 119.

Thank you, we now included some references.

Line 75: Please indicate early on that the N-terminus of some SUMO proteins contains lysines for the formation of SUMO chains. Please list them.

We now list, which of the SUMO proteins used in this study contain lysine residues in their N-termini.

Line 113: Please cite studies that elucidated the sumoylation of lysines in the N-terminus of SUMO2/3 proteins.

Thank you, we now included some references.

Line 153: The authors should include additional references on Smt3 structure function analyses to provide better context. One important detail, for example, is the important finding that Yeast SUMO (Smt3) deletion can be complemented by hsSUMO1 but not hsSUMO2 and hsSUMO3. Additionally, in yeast the entire Smt3 N-terminus can be deleted without detectable effects on growth, underscoring the enigmatic role of the N-terminus (Newman et al., 2017). Caveat also applies to line 266.

Thank you, we now included some additional information and references around line 153 and below.

164: The hypothesis that the SUMO1 N-terminus interferes with SIM binding groove ignores the previous observation that deletion of the SUMO2 N-terminus does not have an effect on binding (in vitro). While this is addressed later, the authors should clarify this e.g. by stating "a unique feature of the SUMO1 N-terminus".
>

We now explicitly mention that this feature appears to be unique to SUMO1.

374 and 499: The authors should discuss the caveat that the deletion of the N-terminus of Smt3 does not have a phenotype in yeast in vivo (Newman et al., 2017).

We now discuss that Smt3’s N-terminus can be deleted without detectable phenotype, both in the results as well as in “Limitations of the study”.

Line 367: I feel this is overstated and I do not see any evidence that post translation modifications of the SUMO core plays a role. Therefore, I suggest: Our data and modeling are consistent with an interpretation that the N-termini of human and C. elegans SUMO1 proteins are inhibitory and that other SUMO N-termini may acquire such a function upon posttranslational modification of the N-terminus.

We agree that this is pure speculation and therefore restrict our hypothesis to modifications of the N-terminus.

Line 374 ff: Since Smo-∆N12 increases sumoylation (Fig. 2I), it is likely that the in vivo defect is due to over-sumoylation in C. elegans. The authors should discuss this possibility and quote appropriate literature e.g.: Rytinki et al., Overexpression of SUMO perturbs the growth and development of Caenorhabditis elegans. Cell Mol Life Sci. 2011 Oct;68(19):3219-32. PMID: 21253676.

In our study, we employ in vitro SUMOylation as a means to assess the SIM binding capability in an in-solution assay. For this, we use USP25 as a specific substrate known to depend on a SIM for its SUMOylation. We cannot exclude that some specific substrates depending on this same mechanism for their modification may be upregulated in modification also in the Smo-1∆N12 worms. In vivo however, the majority of SUMO substrates is not subject to SIM-dependent SUMOylation. We now added a control experiment showing that we neither observe significantly increased SUMO levels nor upregulated steady state levels of SUMOylation in these worms (Supplemental figure 8).

The phenotypes shown in the paper by Rytinki et al. do not resemble the smo-1∆N12 mutants. Rather, we observed a specific defect in the meiotic germ cells at the pachytene stage causing increased apoptosis Moreover, we show by western blot analysis that there is no global over-sumoylation occurring in smo-1∆N12 mutants (Fig. s8). Together, our data point to a germline-specific function of the SMO-1 N-terminus in maintaining genome stability (lines 510ff).

Reviewer #2 (Recommendations For The Authors):

Page2 - "Small Ubiquitin-related modifiers of the SUMO family regulate thousands of proteins in eukaryotic cells" - The authors could consider a more precise statement, e.g. that SUMO modifiers have been detected on thousands of proteins and their regulatory effect on many proteins have been demonstrated.

To be a bit more precise, the sentence now reads: “Ubiquitin-related proteins of the SUMO family are reversibly attached to thousands of proteins”. The summary has a word limit, hence we did not expand further at this place.

Page 4 - "Both events require SUMO-binding motifs (reviewed, e.g. in 7 ." - The end bracket is missing. Also, isn't it too strong a statement that paralogue specificity always requires a SIM? I don't know all the literature sufficiently well, but the authors could double-check if it is correct to say that paralogue-specific SUMOylation always depends on a SIM.

Thank you, we added the missing bracket. We agree that it would not be correct to say that paralogue-specificity always depends on a SIM. One alternative example is Dpp9, which shows a clear preference for SUMO1 without owning a SIM. Instead, Dpp9 harbors an alternative SUMO-binding motif, the E67-interacting loop, with a strong paralogue-preference (Pilla et al., 2012). We never intended to imply that a SIM is required for paralogue preference and we also rather generically wrote “SUMO binding motif” instead of “SIM”. However, in the subsequent paragraph about SUMO binding motifs we only go into details of SIMs as one of three classes of SUMO binding motifs not even mentioning the alternative classes. To make this more obvious, we now list the two other known classes of SUMO binding motifs hoping that it will shed the correct light onto our previous statement about paralogue preference.

Page 4 - In the nice discussion of different types of SIMs, the authors could consider mentioning also the special case of TDP2, which is used later by them as a model binding protein. This could provide an occasion to explain what the unusual "split SIM", mentioned on page 6, but not discussed, is, and what its relation to a normal SIM is. Also, it can perhaps be mentioned that TDP2 contacts SUMO2 not only through the two hydrophobic elements contiguous in space that mimic a SIM but also through a slightly larger interface around these regions on the surface of a folded domain.

Thank you for pointing this out. In the introduction, we extended our section on SUMO binding and now also included TDP2’s “split SIM”.

Page 11-12 - In the section "Interaction between SUMO's disordered N-termini and the SIM binding groove is highly dynamic" (and corresponding figures), it should be stated that the discussed kinetic parameters are derived from molecular dynamics simulations and not experimental measurements. It was not very clear to me. This also applies to this sentence on page 17: "First, we observed a very fast (ns) rate of the binding/unbinding process", which in its current form suggests direct observation rather than simulation.

We thank the reviewer for pointing this out, and in fact, Rev #1 made the same comment. We specified now clearly that the rates were calculated from MD simulations, in the Results and Discussion sections (on page 11-12 and 18 (previously 17)).

Page 16 - The authors could briefly mention that this relatively long disordered N-terminal tail is a specific feature of SUMO proteins that distinguishes them from ubiquitin. I guess it is obvious to people from the SUMO field, but I don't think it is explicitly stated anywhere in the text and it could be interesting for readers who are less familiar with SUMO/ubiquitin differences.

Thank you, we added a short half-sentence pointing out this difference.

Page 17 - "The N-terminal region remains fully disordered in the bound state and is thus a classic example of intrinsic disorder irrespective of the binding state." - it could be added to this sentence that this is suggested by molecular dynamics simulations and not directly observed.

We added the information that this finding is based on the MD simulations.

Page 18 - "(e.g., 41,53 or flanking the SIM binding groove24,42" - the end bracket is missing.

Thanks, we added it.

Page 19 - "Our analysis in C. elegans (Fig. 7) suggests that this N-terminal function is particularly important in DNA damage response, a pathway that is strongly dependent on the SUMO system." - this brief description of the in vivo data seems to overgeneralise them a little bit. Perhaps one can describe what was observed with slightly more nuance.

See changes on p.19, lines 510ff.

eLife assessment

This work demonstrates an important regulatory role of the N-terminal disordered tail of small ubiquitin-like modifier (SUMO) proteins, which modulate the function of various proteins in eukaryotic cells. The authors present convincing evidence that the N-terminal tail of SUMO inhibits SUMO's interaction with downstream effector proteins and SUMOylation targets, and that this regulatory mechanism depends on the SUMO paralogue or the phosphorylation of the N-terminal tail. This discovery significantly advances the field by providing a possible explanation of how SUMO paralogues select their effectors and SUMOylation targets.

Reviewer #2 (Public review):

Summary:

This very interesting study originated from a serendipitous observation that the deletion of the disordered N-terminal tail of human SUMO1 enhances its binding to its interaction partners. This suggested that the N terminus of SUMO1 might be an intrinsic competitive inhibitor of SUMO-interacting motif (SIM) binding to SUMO1. Subsequent experiments support this mechanism, showing that in humans it is specific to SUMO1 and does not extend to SUMO2 or SUMO3 (except, perhaps, when the N terminus of SUMO2 becomes phosphorylated, as the authors intriguingly suggest - and partially demonstrate). The auto-inhibition of SUMO1 via its N-terminal tail apparently explains lower binding of SUMO1 compared to SUMO2 to some SIMs and lower SIM-dependent SUMOylation of some substrates with SUMO1 compared to SUMO2, thus adding an important element to the puzzle of SUMO paralogue preference. In line with this explanation, N-terminally truncated SUMO1 was equally efficient to SUMO2 in the studied cases. The inhibitory role of SUMO1's N terminus appears conserved in other species including S. cerevisiae and C. elegans, both of which contain only one SUMO. The study also elucidates the molecular mechanism by which the disordered N-terminal region of SUMO1 can exert this auto-inhibitory effect. This appears to depend on the transient, very highly dynamic physical interaction between the N terminus and the surroundings of the SIM-binding groove based mostly on electrostatic interactions between acidic residues in the N terminus and basic residues around the groove.

Strengths:

A key strength of this study is the interplay of different techniques, including biochemical experiments, NMR, molecular dynamics simulations, and, at the end, in vivo experiments. The experiments performed with these different techniques inform each other in a productive way and strengthen each others' conclusions. A further strength is the detailed and clear text, which patiently introduces, describes, and discusses the study. Finally, in terms of the message, the study has a clear, mechanistic message of fundamental importance for various aspects of the SUMO field, and also more generally for protein biochemists interested in the functional importance of intrinsically disordered regions. In revision, the authors have further improved the text.

Weaknesses:

In the future, further experimental validation will be required, particularly with regards to the biological importance of the uncovered mechanism. These limitations are satisfactorily pointed out by the authors themselves in the revised manuscript.

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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

eLife assessment

This work aimed at deconstructing how sebaceous gland differentiation is controlled in adult skin. Using monoclonal antibodies designed to inhibit specific Notch ligands or receptors, the authors present convincing evidence that the Jag2/Notch1 signaling axis is a crucial regulator of sebocyte progenitor proliferation and sebocyte differentiation. The valuable findings presented here contribute to the growing evidence that Notch signaling is not only key during the development of the skin and its appendages but also regulates cell fate in adult homeostatic tissues. From a translational perspective, it is intriguing that the effect of Jag2 or Notch1 inhibition, which leads to the accumulation of proliferative stem/progenitor cells in the sebaceous gland and prevents sebocyte differentiation, is reversible.

Reviewer #1 (Public review):

Summary:

In this study, Abidi and colleagues used Notch pathway neutralizing antibodies to inhibit sebaceous glands in the skin. The authors find that blocking either the Notch1 receptor or the Jag2 ligand caused loss of the glands and increased retention of sebaceous progenitor cells. Moreover, these glands began to reappear 14 days after treatment.

Strengths:

Overall, this study definitively identifies the Notch receptor/ligand combination that maintains these glands in the adult. The manuscript is clearly written and the figures are beautifully made.

In this resubmitted manuscript, the authors have adequately addressed all the previous critiques.

Reviewer #2 (Public review):

Summary:

In this report Abidi et al. use an antibody against Jag2, a Notch1 ligand, to inhibit its activity in skin. A single dose of this treatment leads to an impairment of sebocyte differentiation and an accumulation of basal sebocytes. Consistently Notch1 activity, measured as cleaved form of the Notch1 intracellular domain, is detected in basal sebocytes together with the expression of Jag2. Interestingly the phenotype caused by the antibody treatment is reversible.

Strengths:

The quality of the histological data with a clear phenotype, together with the quantification represents a solid base for the authors claims.<br /> This work identifies that the ligand Jag2 is the Notch1 ligand required for sebocyte differentiation.<br /> From a therapeutic point of view, it is interesting that the treatment with the anti-Jag2 is reversible.

Weaknesses:

The authors use a single approach to support their claims.<br /> Future in vitro studies will be needed to understand how Notch signaling induces sebocyte differentiation (i.e. a cell-autonomous mechanism, a mechanism based on cell competition, etc.).

Reviewer #3 (Public review):

Abidi et al. investigated the role of Notch signalling for sebaceous gland differentiation and sebocyte progenitor proliferation in adult mouse skin. By injecting antagonising antibodies against different Notch receptors and ligands into mice, the authors identified that the Notch1 receptor and, to a lesser extent, Notch2 receptor, as well as the Notch ligand Jagged2, contribute to the regulation of sebaceous gland differentiation. In situ hybridisation confirmed that treatment with anti-Jagged2 dramatically reduced the number of basal sebocytes staining for the transcriptionally active intracellular domain of Notch1. Loss of Notch activity in sebocyte progenitors robustly inhibited sebaceous gland differentiation. Under these conditions, the number of sebocyte progenitors marked by Lrig1 was not affected, while the number of proliferating basal sebocytes was increased. Upon recovery of Notch activity, sebaceous gland differentiation could likewise be recovered. By suggesting that Notch activity in sebocyte progenitors is required to balance proliferation and differentiation, these data bring valuable new and relevant findings for the skin field on the sebaceous gland homeostasis.

I fick w this gud vad spännande

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Reply to the reviewers

Reviewer #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Xu, Hörner, Schüle and colleagues is an RNA-seq study focusing characterization of axonal transcriptomes from human iPSC-derived cortical neurons. The authors have differentiated iPSC into neurons, cultured them in microfluidic devices and isolated axonal RNA, comparing this to corresponding cell soma transcriptomes. Second, axonal transcriptomes are compared between wild type and Kif1c knockout axons to determine Kif1c-dependently localized transcripts. Characterization of the latter allows the authors to suggest differentially expressed transcripts in Kif1c-KO axons can be mRNAs relevant for motor neuron degeneration owing to Kif1c mutations in hereditary spastic paraplegias.

Major comments: Overall, his manuscript reads like work in (early) progress. This manuscript provides an interesting dataset, but needs substantial additional experimental and/or bioinformatic work to merit publication. The technical complexity of steps that have led to obtaining axonal transcriptomes can be appreciated, the soundness of generating these data is beyond doubt. However, the study stops at the point of generating axonal transcriptomes from wild type and Kif1c axons. No follow-up experiments are performed to study genes of interest found in RNA-seq. This could be compensated by in-depth bioinformatic analysis (e.g. comparisons with the many different datasets in known in the field), but this is clearly lacking as well. The results section only contains minimal bioinformatic analysis and nothing else. Introduction and discussion are well, clearly written and are in good dialogue with the existing body of work. To improve the manuscript, at minimum these two aspects should be addressed: 1. Characterization of the iPSC-derived neurons is missing (immunostaining with neuronal markers, e.g. Tau, MAP2, exclusion of glial markers, and lack of stem cell markers) 2. Validation of candidates of interest (e.g. FISH analysis in axons vs somata, Kif1c vs wt). Very specific requests from the review are useless at this point, as the authors should have the liberty to focus.

Thank you for the review of our manuscript. We appreciate your recognition of the technical complexity involved in generating axonal transcriptomes and the clarity of our introduction and discussion sections.

__Characterization of iPSC-derived neurons: __We acknowledge the importance of immunostaining with neuronal markers to ensure the purity of our neuronal population. We included this characterization in our revised manuscript and added it into the results and methods section of the paper (Supplementary Figure S1). Additionally, we included RT-qPCR analysis that confirmed the presence of cortical markers and added these to the results and method section of the paper (Supplementary Figure S2).

Additional bioinformatic work: We agree that additional bioinformatic work will greatly benefit this paper. Therefore, we compared our datasets to all additional datasets that we were able to retrieve. This was added to the main text (results and discussion) and supplementary material (Supplementary Figure S5 and S6). We believe this strengthens the merit of our paper, and adds a lot of new unpublished information to the manuscript

__Validation of candidates of interest: __We understand the necessity of validating our RNA-seq findings through experimental approaches such as FISH analysis and comparisons between KIF1C knockout and wild-type neurons. While we appreciate the comment and agree on the importance of high-resolution RNA FISH, we believe it is beyond the scope of this manuscript due to the considerable complexity of these experiments in human iPSC-derived cortical neurons. We will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

Minor comments: 1. Details of RNA seq technicalities are redundant in the results section, e.g. „Our RNA-seq pipeline encompassed read quality control (QC), RNA-seq mapping, and gene quantification" (p. 7) is a trivial description - this and similar details should be skipped or described in methods.

We will ensure that technical details are appropriately placed in the methods section and avoid redundancy in the results. Technical details included in the results section have been moved to the methods.

1. Fig1A: Y axis should start from 0

We adjusted Figure 1A to start the Y-axis from 0.

1. Too much interpretational voice in figure legends (e.g. see Fig. 1, „PC1 clearly distinguishes the soma (blue)"

We revised the interpretational voice in the figure legends to maintain objectivity.

1. PCA analysis seems redundant in Fig. 2C

We removed the PCA analysis in Fig. 2A (2C corresponds to Gene ontology term enrichment analysis).

1. Subheading „Human motor axons show a unique transcription factor profile" is misleading - you are not dealing with motor iPS-derived motoneurons (Isl-1 positive), but cortical neurons (again, no marker information provided to assess this!)

The subheading „Human motor axons show a unique transcription factor profile" was adjusted. Furthermore, validation of neuronal identity has been added to the supplementary figures (Supplementary Figure S1 and S2), as well as main text and methods section.

1. Fig. 3: Just by comparing top expressed factors in axonal samples is not informative - overall high expression of a certain transcript likely makes it easier for it to be picked up in the axonal compartment. Axon/soma ratios would perhaps be more appropriate.

After careful consideration, we decided that we will not change the data presentation in Figure 3. Our aim in this figure was not to compare axon and soma but to see highly expressed transcripts in the axon, regardless of whether they are highly expressed in the soma as well. We think that looking at transcripts present in the axon can give information about axonal function, that we might lose when we only consider transcripts that are upregulated compared to the soma. The fact that 25 out of 50 transcription factor RNAs detected in the axon are actually specific to the axons supports this point of view. The comparison between transcripts expressed in axon and soma are presented in Figure 2.

1. Figure 4 (KIF1C modulates the axonal transcriptome): you should show also data for the same genes in the soma, axonal data only is misleading (is overall expression changed?)

We appreciate your suggestion. This data was already included in Supplementary Figure S6 (now Supplementary Figure S9). To make this easier to find, we've added a section to the results part to more clearly state how transcript expression changes in the soma.

Significance

Axonal transcriptomes have been studied since early 2010s by a number of groups and several datasets exist from different model systems. The authors know these studies well, address their findings and cite them appropriately. Is the dataset in this manuscript novel? Does it contribute to the field? Several axonal transcriptomes have been characterized in thorough studies, and even in the specific niche (human IPS-derived motoneurons) a point of reference exists - as the authors themselves point out, it is the Nijssen 2018 study. With appropriate presentation and follow-up experiments this material could have merit as a replication study.

Audience: specialized

We appreciate the reviewer's suggestion to clarify the differences between our findings and previously published data. In response, we have added a dedicated section to the discussion, where we provide a more detailed comparison of our results with existing research. This includes an in-depth examination of the methodologies, experimental conditions, and biological contexts that may explain the observed discrepancies (e.g., variations in methods, neuronal types, and disease contexts). As prior studies primarily focused on mouse-derived neurons, we have included a new section in both the results (Supplementary Figure S6) and the discussion to highlight the limited overlap in gene expression between the axons of mouse- and human-derived neurons. Furthermore, previous studies on human-derived cells either investigated i3 neurons -induced by transcription factors but not fully representative of human-derived CNS-resident neurons - or neurons of the peripheral nervous system (lower motor neurons). In contrast, our study focuses on human-derived CNS-resident cortical neurons (Supplementary Figure S1, S2; comparison shown in Supplementary Figure S5), emphasizing the greater translatability of our findings.

Moreover, we have expanded our bioinformatic analyses and compared our dataset with additional datasets to further substantiate our conclusions (Supplementary Figure S5, S6)

We believe that these revisions significantly enhance the clarity, quality, and impact of our manuscript. We sincerely thank the reviewer for their constructive feedback.

Reviewer #2

Evidence, reproducibility and clarity

This study seeks to identify axonal transcriptome by RNA-sequencing of the iPSC-derived cortical neuron axons. This is achieved by comparing the RNA expressions between the axonal and soma compartments using microfluid system. The specific expression of axon specific RNAs in the axonal compartment validate the specificity of the approach. Some unique RNAs including TF specific RNAs are identified. Furthermore, this study compared the KIF1C-knockout neurons (which models hereditary spastic paraplegia characterized by axonal degeneration) with wildtype (WT) control neurons, which led to the identification of specific down-regulated RNAs involved in axonal development and guidance, neurotransmission, and synaptic formation.

The data of this study are interesting and clearly presented. The major concerns are the lack of characterization of the neuron identities and the examination of functional deficits in the KIF1C-knockout neurons. For example: 1) are these neurons express layer V/VI markers at protein levels, and the proportion of positive neurons (efficiency of cortical neuron differentiation); 2) What are the phenotypic changes in the KIF1C-knockout neurons; are there change sin axonal growth or transport? 3) Day 58 was selected for collecting RNA for sequencing study: how this time point is selected? And are there phenotypic differences between the WT and knockout neurons at this time point?

We appreciate the favorable review of our manuscript and the insightful comments:

Characterization of neuron identities: We agree on the importance of validating neuron identities and included protein-level characterization of layer V/VI markers and efficiency of cortical neuron differentiation in our revised manuscript: We conducted immunohistochemical staining for layer V/VI and other neuronal markers, as well as qRT-PCR to validate the identity of the neurons, ensuring a comprehensive characterization of our neuronal population.

Functional deficits in KIF1C-knockout neurons: We have conducted phenotypic examinations of the neurons but did not observe gross differences in differentiation, axon growth or axon length. We added a corresponding statement to the results section. Neurons were harvested at DAI 58 because at this time we achieved a nearly confluent chamber that yielded enough material for in-depth RNA-sequencing. We did not observe phenotypic differences between wt and KIF1C-KO neurons at this time point. We added a statement to the method section outlining this.

Some minor comments:1. The protein levels of some critical factors needs to be validated.

We validated neuronal identities on qRT-PCR level (Supplementary Figure S2). While we understand the necessity of validating our RNA-seq findings on protein level, we believe it is beyond the scope of this manuscript. However, we will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

1. Figure 4C, for the list genes, statistical analyses between WT and knockout groups are required.

In Figure 4C we only included differentially expressed genes with a p-value We added a corresponding statement in the main text and figure legend.

1. Page 15, the 5th to last sentence: "nucleus nucleus" (repeat)

The repeat word on page 15 was deleted.

1. The sequencing data requires public links to the deposited library

We will provide public links to the deposited library for the sequencing data once the data is submitted to a journal (depending on journal guidelines).

Significance

The strength of this study is the combinations of iPSC differentiation, gene editing (KIF1C knockout iPSC) and microfluidic system. This allows the identification of specific axonal transcriptomes. Moreover, the comparisons of control and KIF1C knockout neurons at both axon and soma compartments enables the identification of RNAs and pathways caused by the loss of KIF1C.

The limitation is the lack of functional assessment of the iPSC-derived neurons, especially phenotypic changes in the KIF1C-knockout neurons. Only one time point is selected for comparing the WT and KIF1C knockout neurons, and the relationship between this time point and disease phenotypes is unclear.

This study will be of interest to researchers from both basic and translational fields, and in the fields of stem cells, neuroscience, neurology and genetics.

My expertise includes stem cells, iPSC modeling, motor neuron diseases, and nerve degeneration.

We appreciate the favorable significance statement and believe addressing these points will strengthen the scientific rigor and impact of our study. Thank you for your valuable feedback.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):  Using microfluidics chambers and RNA sequencing (RNA-seq) of axons from iPSC-derived human cortical neurons, authors use RNA profiling to investigate the RNAs present in the soma and axons and the impact of KIF1C molecular motor downregulation (KIF1CKO) on the axonal transcriptome. The rationale is that mutations in KIF1C are associated with an autosomal recessive form of hereditary spastic paraplegia, and KIF1C is implicated in the long-range directional transport of APC-dependent mRNAs and RNA-dependent transport of the exon junction complex into neurites.  Employing a well-defined RNA-seq pipeline for analysis, they obtained RNA sequences particular to axonal samples, outperforming previous studies. They detected over 16,000 genes in the soma (which includes axons) and RNA for more than 5,000 genes in axons. A comparison of the list of axonal genes revealed a strong correlation with previous publications, but they detected more genes overall. They identified transcripts enriched in axons compared to somas, notably those for ribosomal and mitochondrial proteins. Indeed, they observed enrichment for ribosomal subunits, respiratory chain complexes, ion transport, and mRNA splicing.  The study also found that human axons exhibit a unique RNA transcription profile of transcription factors (TFs), with TFs such as GTF3A and ATF4 predominant in axons. At the same time, CREB3 was highly expressed in the soma.  Upon analyzing the soma and axon transcriptomes from KIF1CKO cultures, they identified 189 differentially regulated transcripts: 89 downregulated and 100 upregulated in the KIF1CKO condition. Some of these transcripts are critical for synaptic growth and neurotransmission. Notably, only two targets of APC-target RNAs were downregulated, contrary to their expectation. Their data indicates that KIF1C downregulation significantly alters the axonal transcriptome landscape.  Reviewer #3 (Significance (Required)):  The study is well-performed and informative, particularly for researchers interested in the local translation of axonal proteins and the axonal transcriptome. However, the authors did not validate their findings for any transcripts and did not perform any functional assays, so the manuscript lacks mechanistic insight. Interestingly, GTF3A is a transcription factor that stimulates polymerase III transcription of ribosomal proteins, and mRNAs for ribosomal proteins are enriched in human axons. Maybe there is an interesting story there. 

We appreciate the favorable significance statement and the valuable feedback. We have conducted phenotypic examinations of the neurons but did not observe gross differences in differentiation, axon growth or axon length. We added a corresponding statement to the results section. While we understand the necessity of validating our RNA-seq findings on protein level, we believe it is beyond the scope of this manuscript. However, we will focus on incorporating this aspect into future studies and added a corresponding statement outlining the limitations of our study in the discussion stressing the importance of this.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #3

Evidence, reproducibility and clarity

Using microfluidics chambers and RNA sequencing (RNA-seq) of axons from iPSC-derived human cortical neurons, authors use RNA profiling to investigate the RNAs present in the soma and axons and the impact of KIF1C molecular motor downregulation (KIF1CKO) on the axonal transcriptome. The rationale is that mutations in KIF1C are associated with an autosomal recessive form of hereditary spastic paraplegia, and KIF1C is implicated in the long-range directional transport of APC-dependent mRNAs and RNA-dependent transport of the exon junction complex into neurites.

Employing a well-defined RNA-seq pipeline for analysis, they obtained RNA sequences particular to axonal samples, outperforming previous studies. They detected over 16,000 genes in the soma (which includes axons) and RNA for more than 5,000 genes in axons. A comparison of the list of axonal genes revealed a strong correlation with previous publications, but they detected more genes overall. They identified transcripts enriched in axons compared to somas, notably those for ribosomal and mitochondrial proteins. Indeed, they observed enrichment for ribosomal subunits, respiratory chain complexes, ion transport, and mRNA splicing. The study also found that human axons exhibit a unique RNA transcription profile of transcription factors (TFs), with TFs such as GTF3A and ATF4 predominant in axons. At the same time, CREB3 was highly expressed in the soma. Upon analyzing the soma and axon transcriptomes from KIF1CKO cultures, they identified 189 differentially regulated transcripts: 89 downregulated and 100 upregulated in the KIF1CKO condition. Some of these transcripts are critical for synaptic growth and neurotransmission. Notably, only two targets of APC-target RNAs were downregulated, contrary to their expectation. Their data indicates that KIF1C downregulation significantly alters the axonal transcriptome landscape.

Significance

The study is well-performed and informative, particularly for researchers interested in the local translation of axonal proteins and the axonal transcriptome. However, the authors did not validate their findings for any transcripts and did not perform any functional assays, so the manuscript lacks mechanistic insight. Interestingly, GTF3A is a transcription factor that stimulates polymerase III transcription of ribosomal proteins, and mRNAs for ribosomal proteins are enriched in human axons. Maybe there is an interesting story there.

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

This study seeks to identify axonal transcriptome by RNA-sequencing of the iPSC-derived cortical neuron axons. This is achieved by comparing the RNA expressions between the axonal and soma compartments using microfluid system. The specific expression of axon specific RNAs in the axonal compartment validate the specificity of the approach. Some unique RNAs including TF specific RNAs are identified. Furthermore, this study compared the KIF1C-knockout neurons (which models hereditary spastic paraplegia characterized by axonal degeneration) with wildtype (WT) control neurons, which led to the identification of specific down-regulated RNAs involved in axonal development and guidance, neurotransmission, and synaptic formation.

The data of this study are interesting and clearly presented. The major concerns are the lack of characterization of the neuron identities and the examination of functional deficits in the KIF1C-knockout neurons. For example: 1) are these neurons express layer V/VI markers at protein levels, and the proportion of positive neurons (efficiency of cortical neuron differentiation); 2) What are the phenotypic changes in the KIF1C-knockout neurons; are there change sin axonal growth or transport? 3) Day 58 was selected for collecting RNA for sequencing study: how this time point is selected? And are there phenotypic differences between the WT and knockout neurons at this time point?

Some minor comments:

1. The protein levels of some critical factors needs to be validated.
2. Figure 4C, for the list genes, statistical analyses between WT and knockout groups are required.
3. Page 15, the 5th to last sentence: "nucleus nucleus" (repeat)
4. The sequencing data requires public links to the deposited library

Significance

The strength of this study is the combinations of iPSC differentiation, gene editing (KIF1C knockout iPSC) and microfluidic system. This allows the identification of specific axonal transcriptomes. Moreover, the comparisons of control and KIF1C knockout neurons at both axon and soma compartments enables the identification of RNAs and pathways caused by the loss of KIF1C.

The limitation is the lack of functional assessment of the iPSC-derived neurons, especially phenotypic changes in the KIF1C-knockout neurons. Only one time point is selected for comparing the WT and KIF1C knockout neurons, and the relationship between this time point and disease phenotypes is unclear.

This study will be of interest to researchers from both basic and translational fields, and in the fields of stem cells, neuroscience, neurology and genetics.

My expertise includes stem cells, iPSC modeling, motor neuron diseases, and nerve degeneration.

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 #1

Evidence, reproducibility and clarity

Summary:

This manuscript by Xu, Hörner, Schüle and colleagues is an RNA-seq study focusing characterization of axonal transcriptomes from human iPSC-derived cortical neurons. The authors have differentiated iPSC into neurons, cultured them in microfluidic devices and isolated axonal RNA, comparing this to corresponding cell soma transcriptomes. Second, axonal transcriptomes are compared between wild type and Kif1c knockout axons to determine Kif1c-dependently localized transcripts. Characterization of the latter allows the authors to suggest differentially expressed transcripts in Kif1c-KO axons can be mRNAs relevant for motor neuron degeneration owing to Kif1c mutations in hereditary spastic paraplegias.

Major comments:

Overall, his manuscript reads like work in (early) progress. This manuscript provides an interesting dataset, but needs substantial additional experimental and/or bioinformatic work to merit publication. The technical complexity of steps that have led to obtaining axonal transcriptomes can be appreciated, the soundness of generating these data is beyond doubt. However, the study stops at the point of generating axonal transcriptomes from wild type and Kif1c axons. No follow-up experiments are performed to study genes of interest found in RNA-seq. This could be compensated by in-depth bioinformatic analysis (e.g. comparisons with the many different datasets in known in the field), but this is clearly lacking as well.

The results section only contains minimal bioinformatic analysis and nothing else. Indroduction and discussion are well, clearly written and are in good dialogue with the existing body of work. To improve the manuscript, at minimum these two aspects should be addressed:

1. Characterization of the iPSC-derived neurons is missing (immunostaining with neuronal markers, e.g. Tau, MAP2, exclusion of glial markers, and lack of stem cell markers)
2. Validation of candidates of interest (e.g. FISH analysis in axons vs somata, Kif1c vs wt). Very specific requests from the review are useless at this point, as the authors should have the liberty to focus.

Minor comments:

1. Details of RNA seq technicalities are redundant in the results section, e.g. „Our RNA-seq pipeline encompassed read quality control (QC), RNA-seq mapping, and gene quantification" (p. 7) is a trivial description - this and similar details should be skipped or described in methods.
2. Fig1A: Y axis should start from 0
3. Too much interpretational voice in figure legends (e.g. see Fig. 1, „PC1 clearly distinguishes the soma (blue)"
4. PCA analysis seems redundant in Fig. 2C
5. Subheading „Human motor axons show a unique transcription factor profile" is misleading - you are not dealing with motor iPS-derived motoneurons (Isl-1 positive), but cortical neurons (again, no marker information provided to assess this!)
6. Fig. 3: Just by comparing top expressed factors in axonal samples is not informative - overall high expression of a certain transcript likely makes it easier for it to be picked up in the axonal compartment. Axon/soma ratios would perhaps be more appropriate.
7. Figure 4 (KIF1C modulates the axonal transcriptome): you should show also data for the same genes in the soma, axonal data only is misleading (is overall expression changed?)

Significance

Axonal transcriptomes have been studied since early 2010s by a number of groups and several datasets exist from different model systems. The authors know these studies well, address their findings and cite them appropriately. Is the dataset in this manuscript novel? Does it contribute to the field? Several axonal transcriptomes have been characterized in thorough studies, and even in the specific niche (human IPS-derived motoneurons) a point of reference exists - as the authors themselves point out, it is the Nijssen 2018 study. With appropriate presentation and follow-up experiments this material could have merit as a replication study.

Audience: specialized

eLife assessment

In this small study involving patients with a history of myocardial infarction, Fawaz et al. found no significant contribution of clonal hematopoiesis and mosaic loss of the Y chromosome to the incidence of myocardial infarction and atherosclerosis. Although the evidence provided by the study is incomplete due to its small sample size, the findings are valuable for guiding future larger studies that will further investigate this significant and controversial subject.

Reviewer #2 (Public review):

Summary:

The preprint by Fawaz et al. presents the findings of a study that aimed to assess the relationship between somatic mutations associated with clonal hematopoiesis (CHIP) and the prevalence of myocardial infarction (MI). The authors conducted targeted DNA sequencing analyses on samples from 149 MI patients and 297 non-MI controls from a separate cohort. Additionally, they investigated the impact of the loss of the Y chromosome (LOY), another somatic mutation frequently observed in clonally expanded blood cells. The results of the study primarily demonstrate no significant associations, as neither CHIP nor LOY were found to be correlated with an increased prevalence of MI. The null findings regarding CHIP are partly in conflict with several larger studies in the literature. However, it must be noted that the authors did find trends to an association between CHIP and a higher incidence of MI during follow-up among those without a history of MI at baseline, which is more consistent with previous research work. The association with incident MI reached statistical significance in men, particularly in those not showing LOY, suggesting potential interactions between different clonally-expanded somatic mutations.

Strengths:

Overall, this is a useful research work on an emerging risk factor for cardiovascular disease (CVD). The use of a targeted sequencing approach is a strength, as it offers higher sensitivity than the whole exome sequencing approaches used in many previous studies. Reporting null findings is definitely relevant in an emerging field such as the role of somatic mutations in cardiovascular disease.

Weaknesses:

The study suffers from important limitations, which cast some doubts onto the authors' conclusions, as detailed below:

(1) The small sample size of the study population is a critical limitation, particularly when reporting null findings that conflict (partly) with positive findings in much larger studies, totaling hundreds of thousands of individuals (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). The authors claim that they have 90% power to detect an effect size of CHIP on MI comparable to that in previous reports (a hazard ratio of 1.7, mainly based on the findings by Jaiswal et al, NEJM 2014,2017). However, this analysis is simply based on the predicted prevalence of CHIP in MI(+) and MI(-) patients, and it does not consider the complex relationship between age CHIP and atherosclerotic disease. More advanced approaches to calculate statistical power may have provided a more accurate estimation. It must also be noted that recent work in much larger populations suggest that the overall effect of CHIP on atherosclerotic CVD is smaller than 1.7, most likely due to the heterogeneity of effects of different mutated genes (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). In addition, several analyses in the current manuscript are conducted separately in MI(+) (n= 149) and MI(-) (N=297) individuals, further limiting statistical power. Power is even lower in the investigation of the effects of LOY and its interaction with CHIP, as only men are included in these analyses. Overall, I believe the study is underpowered from a statistical point of view, so the authors' findings need to be interpreted with caution.

(2) Related to the above, it is widely accepted that the effects of CHIP on CVD are highly heterogeneous, as some mutated genes appear to have a strong impact on atherosclerosis, whereas the effect of others is negligible (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023, among others). TET2 mutations are frequently considered a "positive control", given the multiple lines of evidence suggesting that these mutations confer a higher risk of atherosclerotic disease. However, no association with MI or related variables was found for TET2 mutations in the current work, which likely reflects the limited statistical power of the study to assess accurately the effects of CHIP mutations on atherosclerotic disease.

(3) One of the most essential features of CHIP is the tight correlation with age. In this study, the effect of age on CHIP (e.g. Supp. Tables S5, S6) is statistically significant, but substantially milder than in previous studies. Given the relatively modest effect size of age on CHIP here, it is not surprising that no association with MI or atherosclerotic disease was found, considering that this association would have a much smaller effect size. It must be considered, however, that the advanced age of the population may have confounded the analysis of these relationships, as acknowledged by the authors.

(4) CHIP represents just one type of clonal hematopoiesis (e.g. see https://doi.org/10.1182/blood.2023022222). In this context, it must be noted that the mutated genes included in the definition of "CHIP" here are markedly different than in most previous studies, particularly when considering specifically the studies that demonstrated an association between CHIP and atherosclerotic CVD. For instance, the definition of CHIP in this manuscript includes genes such as ANKRD26, CALR, CCND2, DDX41... that are not prototypical CHIP genes. This is unlikely to have major impact on the main results, as the vast majority of mutations detected are indeed in bona fide CHIP genes, but it needs to be considered when interpreting the authors' findings. Furthermore, the strategy used here for CHIP variant calling and curation is substantially different than that used in previous studies. This is important, because such differences in the definition of CHIP and the curation of variants are at the basis of most conflicting findings in the literature regarding the effects of this condition. The authors estimate that the effect of these discrepancies on the definition of CHIP is limited, but small differences can have substantial impact in a study with limited sample size.

(5) A major limitation of the current study is the cross-sectional design of most of the analyses. For instance, it is not surprising that no association is found between CHIP and prevalent atherosclerosis burden by ultrasound imaging, considering that many individuals may have developed atherosclerosis years or decades before the expansion of the mutant clones, limiting the possible effect of CHIP on atherosclerosis burden. Similarly, the analysis of the relationship between CHIP and a history of MI may be confounded by the potential effects of MI on the expansion of mutant clones. In this context, it is noteworthy that the only positive results here are found in the analysis of the relationship between CHIP at baseline and incident MI development over follow-up. A larger sample size in these longitudinal analyses would provide deeper insights into the relationship between CHIP and MI.

Author response:

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

Reviewer #1 (Public Review): 

This manuscript examines the individual and dual effects of CHIP and LOY in MI employing a cohort of ~460 individuals. CHIP is assessed by NGS and LOY is assessed by PCR. The threshold for CHIP is set at 2% (an arbitrary cutoff that is often used) and LOY at 9% (according to the Discussion text - this reviewer may have missed the section that describes why this threshold was employed). The investigation assessed whether LOY could modulate inflammation, atherosclerotic burden, or MI risk associated with CHIP. Neither CHIP nor LOY independently affected hsCRP, atherosclerotic burden, or MI incidence, nor did LOY presence diminish these outcomes in CHIP+ male subjects.

This study represents the first dual analysis of CHIP and LOY on CVD outcomes. The results are largely negative, contradictory to other studies (many with much larger sample sizes). I would attribute the limitation of sample size as a major contributor to the negative data. While the negative data are suspect, the "positive" finding that LOY abolishes the prognostic significance of CHIP on MI is of interest (and consistent with what is understood from mechanistic studies).

Overall, I enjoyed reading the paper, and it is of interest to the research community.

However, I disagree with some of the authors' interpretations of the data.

Generally, many conclusions on CHIP interpretation are based on the comparison of findings from very large datasets that have been evaluated by shallow NGS DNA sequencing. These studies lack sensitivity and accuracy, but this is counterbalanced by their very large sample sizes. Thus, they draw conclusions from the sickest individuals (ICD codes) with the largest clones (explaining the 10% VAF threshold). Here, the study has a well-phenotyped cohort, but as far as this reviewer can tell, the DNA sequencing is "shallow" NGS. Typically, to assess smaller datasets, investigators employ an error-correction method (DNA barcodes, duplex sequencing, etc.) for the sensitivity and accuracy of calling variants. Thus, the current study appears to suffer from this limitation (small sample sizes combined with NGS).

We thank the reviewer for his/her positive and open comment. We acknowledge that we did not use error-corrected sequencing method for our study. However, we do not fully agree with the statement that our NGS sequencing technique is “shallow”.

Considering our entire sequencing panel, we achieve a sequencing depth ≥100X and ≥300X for 100% [99%;100%] and 99% [99%;100%] of the targeted regions respectively. This corresponds to a median depth of 2111X [1578;2574] for all regions sequenced. When considering “CHIP genes”, the median depth is 2694X [1875;3785] for patients from the CHAth study and 3455X [2266;4885] for patients from the 3C study. More specifically, for DNMT3A and TET2 genes, the median depths of sequencing are 2531X [1818;3313] and 3710X [2444;4901] for patients from the CHAth and 3C study respectively. These values are far much higher than the 300X recommended for NGS sequencing by capture technology by the French National Institute of Cancer. Coupling this high depth of sequencing with our bioinformatic pipeline that uses 3 different variant callers, a manual curing for all variants by trained hematobiologists and a bioinformatic tool to estimate the background noise allow us to detect somatic mutation with a VAF of 1% with a high accuracy. Noteworthy, our accuracy in detecting mutations in leukemia-associated genes is tested twice a year as part of our quality control program organized by the French Group of Molecular Biologists in Hematology (GBMHM). We added the information about the depth of sequencing in the Supplementary Methods section.

While the "negative" data from this study are inconclusive, the positive data (i.e. CHIP being prognostic for MI in the absence but not presence of MI) is of interest. Thus, the investigators may want to consider a shorter report that largely focuses on this finding.

We thank the reviewer for his/her interest in this result. We also agree that it would be interesting to focus specifically on demonstrating the impact of mLOY in countering the cardiovascular risk associated with CHIP. We performed additional analysis to demonstrate that this effect was independent of age and cardiovascular risk factors and included this information in the results section.

However, we believe that it is also of interest to show negative results that, although probably due to limitation in sample size, suggest that the cardiovascular risk associated with CHIP is not as strong and clinically pertinent as initially suggested. Of note, if CHIP really increase the risk of Myocardial Infarction in a significant manner, they would be more frequently detected in subjects who suffered from a MI compared to those who did not, which was not observed in our cohort. Moreover, we were able to determine that if CHIP increases the risk of MI, they do it to a much lesser extent (HR = 1.03 for CHIP) -than other established cardiovascular risk factors such as hypercholesterolemia or tobacco use HR = 1.47 and HR = 1.86 respectively in our cohort), which questions the pertinence of considering for CHIP in the management of patients with atherothrombosis. These data have been added in the Results and Discussion sections.

We also believe that our study has the merit to assess directly the impact of CHIP on atheroma burden, which has been performed in only a limited number of studies in the context of coronary artery disease. This could not be possible by analyzing only male subjects in our cohort because it would further decrease the statistical power of our analyses.

Reviewer #2 (Public Review):

Summary: 

The preprint by Fawaz et al. presents the findings of a study that aimed to assess the relationship between somatic mutations associated with clonal hematopoiesis (CHIP) and the prevalence of myocardial infarction (MI). The authors conducted targeted DNA sequencing analyses on samples from 149 MI patients and 297 non-MI controls from a separate cohort. Additionally, they investigated the impact of the loss of the Y chromosome (LOY), another somatic mutation frequently observed in clonally expanded blood cells. The results of the study primarily demonstrate no significant associations, as neither CHIP nor LOY were found to be correlated with an increased prevalence of MI. Of note, the null findings regarding CHIP are in conflict with several larger studies in the literature.

Strengths:

Overall, this is a useful research work on an emerging risk factor for cardiovascular disease (CVD). The use of a targeted sequencing approach is a strength, as it offers higher sensitivity than the whole exome sequencing approaches used in many previous studies.

Weaknesses:

Reporting null findings is definitely relevant in an emerging field such as the role of somatic mutations in cardiovascular disease. Nevertheless, the study suffers from severe limitations, which casts doubts on the authors' conclusions, as detailed below:

(1) The small sample size of the study population is a critical limitation, particularly when reporting null findings that conflict (partly) with positive findings in much larger studies, totaling hundreds of thousands of individuals (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024). The authors claim that they have 90% power to detect an effect size of CHIP on MI comparable to that in a previous report (Jaiswal et al, NEJM 2017). However, the methodology used to estimate statistical power is not described.

We thank the reviewer for his/her pertinent and constructive comments. We totally agree that our study presents a substantially smaller sample size as compared to the studies of Zekavat et al, Vlasschaert et al or Zhao et al.

The CHAth study was designed as a prospective study (which is not frequent in CHIP reports) to demonstrate that, if CHIP increase the risk of MI, they would be detected more frequently in patients who suffered from a MI compared to those who did not. To achieve this, we defined eligibility criteria to have a rather high prevalence of CHIP and optimize the statistical power of a study based on a limited number of patients. We thus enrolled patients who suffered from a first MI after the age of 75 years. These patients had to be compared with subjects from the Three-City study who had 65 years or more at inclusion and did not present any cardiovascular event before inclusion.

To determine the number of patients necessary to achieve our objective, we considered a CHIP prevalence of 20% in the general population after the age of 75 years, as estimated when we set up our study (Genovese et al, NEJM 2014, Jaiswal et al, NEJM 2014, Jaiswal et al, NEJM 2017). At this time the relative risk of MI associated with CHIP was shown to be 1.7, leading to an expected prevalence of CHIP of 37% in subjects who presented a MI. Based on these hypotheses, the recruitment of 112 patients in the CHAth would have been sufficient to detect a significant higher prevalence of CHIP in MI(+) patients compared to MI(-) subjects with a power of 0.90 at a type I error rate of 5%. These calculations were performed by the Research Methodology Support Unit of the University Hospital of Bordeaux. These data were added in the Supplementary Methods section to expose more clearly the design and objectives of the CHAth study.

Finally, we recruited 149 patients in the CHAth study and compared them to 297 control subjects. Although recruiting more patients than initially needed, we observed a similar prevalence of CHIP between our 2 cohorts, suggesting that the cardiovascular risk associated with CHIP is lower than the 1.7 increased risk claimed in most publications related to CHIP in the cardiovascular field. We have to notice that our study was not designed to demonstrate the impact of CHIP on the occurrence of MI during follow-up, which could explain our negative results due to a limited number of patients as stated by the reviewers. This statement has been added in the Supplementary Methods section. However, performing such analysis allowed us to confirm that the risk of MI associated with CHIP was lower than 1.7 and lower than the one associated with hypercholesterolemia or smoking.

We would like also to notice that the eligibility criteria for both CHAth and the Three-City study can have led to a selection bias, possibly contributing to the contradiction of our results with other studies. As stated before, in the CHAth study, only patients who experience a first MI after the age of 75 were enrolled. In the Three-City study, all subjects had 65 years or more at inclusion. On the contrary, most of the cohorts showing an association between CHIP and cardiovascular events were composed of younger subjects:

-          Bioimage : median age 70 years (55-80 years)

-          MDC : median age 60 years

-          ATVB : subjects with a MI before 45 years

-          PROMIS : subjects between 30 and 80 years

-          UK Biobank : between 40 and 70 years at inclusion, median age of 58 years in the study of Vlasschaert et al.

-          Zhao et al : median age of 53.83 years (45.35-62.39 years).

This last information was added in the Discussion section (lines 452-454).

Furthermore, the work by Jaiswal et al (NEJM 2017) showed a hazard ratio of approx. 2.0, but more recent work in much larger populations suggests that the overall effect of CHIP on atherosclerotic CVD is smaller, most likely due to the heterogeneity of effects of different mutated genes (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023; Zhao et al, JAMA Cardio 2024).

We thank the reviewer for insisting on the fact that the initial HR of 2.0 observed by Jaiswal et al was shown to be smaller in more recent studies. This corresponds to what we wrote in the introduction (lines 103-109) and discussion (lines 365-370, 465-471).

In addition, several analyses in the current manuscript are conducted separately in MI(+) (n= 149) and MI(-) (N=297) individuals, further limiting statistical power. Power is still lower in the investigation of the effects of LOY and its interaction with CHIP, as only men are included in these analyses. Overall, I believe the study is severely underpowered, which calls into question the validity of the reported null findings.

We agree with the reviewer that the statistical power of our study is lower than the one of other studies, in particular those based on several hundred thousand patients. Whenever possible, we analyzed our data by combining MI(+) and MI(-) subjects. However, for some aspects such as atherosclerosis, we did not have the same parameters available for these 2 groups and had to analyze them separately, leading to a more limited statistical power. We also have to acknowledge that our study was not designed to demonstrate an effect of CHIP on incident MI (as stated before), limiting our statistical power to demonstrate an effect of CHIP +/- mLOY on the incident risk of coronary artery disease.

However, when designing our prospective study (CHAth study), we aimed to address the limitations of a small cohort and obtain rapid, significant results regarding the impact of CHIP. We hypothesized that if CHIP really increases the risk of myocardial infarction (MI), it would be detected more frequently in patients who have experienced a MI compared to those who have not. This study design would demonstrate the importance of CHIP in MI pathophysiology without requiring thousands of patients. However, we did not observe such an association questioning the relevance of detecting CHIP for the management of patients in the field of Cardiology. This was confirmed by the fact that in our cohort, the cardiovascular risk associated with CHIP appears to be low (HR = 1.03 [0.657;1.625] after adjustment on sex, age and cardiovascular risk factors) compared to hypercholesterolemia (HR = 1.474 [0.758;2.866]) or smoking (HR = 1.865 [0.943;3.690]). These data have been added in the Results and Discussion sections.

In addition, we would like to mention that despite the limited number of subjects studied, we do not have only negative results. When studying only men subjects, we were able to show that CHIP accelerate the occurrence of MI, particularly in the absence of mLOY (Figure 2D). This effect was independent of age and cardiovascular risk factors (diabetes, cholesterol and high blood pressure). We added this last information in the results section of the manuscript, although we acknowledge that this has to be confirmed in future work.

(2) Related to the above, it is widely accepted that the effects of CHIP on CVD are highly heterogeneous, as some mutated genes appear to have a strong impact on atherosclerosis, whereas the effect of others is negligible (e.g. Zekavat et al, Nature CVR 2023, Vlasschaert et al, Circulation 2023, among others). TET2 mutations are frequently considered a "positive control", given the multiple lines of evidence suggesting that these mutations confer a higher risk of atherosclerotic disease.

However, no association with MI or related variables was found for TET2 mutations in the current work. Reporting the statistical power specifically for assessing the effect of TET2 mutations would enhance the interpretation of these results.

We thank the reviewer for this pertinent remark. It has indeed been shown that depending on the somatic mutation, the impact of CHIP on inflammation, atherosclerosis and cardiovascular risk is different. The studies cited by the reviewer suggest that DNMT3A mutations have a low impact on atherosclerosis/atherothrombosis while other “non-DNMT3A” mutations, including TET2 mutations, have a greater impact. In particular, Zekavat et al suggested that TP53, PPM1D, ASXL1 and spliceosome mutations have a similar impact on atherosclerosis/atherothrombosis to TET2.

To answer to the reviewer in our cohort, we did not find a clear association between the detection of TET2 mutation with a VAF≥2% and:

-          A history of MI at inclusion (p=0.5339)

-          Inflammation (p=0.440)

-          Atherosclerosis burden :

-   In the CHAth study:

-  p=0.031 for stenosis≥50%

-  p=0.442 fir multitruncular lesions

-  p=0.241 for atheroma volume

-   in the 3C study :

-  p=0.792 for the presence of atheroma

-  p=0.3966 for the number of plaques

-  p=0.876 for intima-media thickness

-          Incidence of MI (p=0.5993)

Similarly we did not find any association between the detection of TET2 mutations with a VAF≥1% and:

-          A history of MI at inclusion (p=0.5339)

-          Inflammation (p=0.802)

-          Atherosclerosis burden :

-   In the CHAth study :

-  p=0.104 for stenosis≥50%

-  p=0.617 fir multitruncular lesions

-  p=0.391 for atheroma volume

-   in the 3c study:

-  p=0.3291 for the presence of atheroma

-  p=0.2060 for the number of plaques

-  p=0.2300 for intima-media thickness

-          Incidence of MI (p=0.195)

However, analyzing the specific effect of TET2 mutations reduces the cohort of CHIP(+) subjects to 61 individuals. In these conditions, considering a prevalence of “TET2-CHIP” of 13.5% (in our cohort) and a hazard ratio of 1.3 (Vlasschaert et al), the statistical power to show an increased risk of MI is only 16%.

(3) One of the most essential features of CHIP is the tight correlation with age. In this study, the effect of age on CHIP (Supplementary Tables S5, S6) seems substantially milder than in previous studies. Given the relatively weak association with age here, it is not surprising that no association with MI or atherosclerotic disease was found, considering that this association would have a much smaller effect size.

We thank the reviewer for highlighting this point. Although the difference of median age between subjects with or without a CHIP is not very important in our cohort, we did observe a significant association of CHIP with age:

-          The differences in age were statistically significant both in the CHAth and 3C study (Supplementary Tables S5 and S6)

-          We observed a significant association between age and CHIP prevalence (p<0.001 for the total cohort, p=0.0197 for the CHAth study, and p=0.0394 for the 3C cohort after adjustment on sex). This association was already shown in the figure 1. We added the significant association between age and CHIP prevalence in the Results section (line 279).

As stated before, we have to remind the reviewer that we enrolled only subjects of ≥75 years and ≥65 years in the CHAth and 3C studies respectively. This led to a median age in our cohort that was substantially higher than in other cohorts (in particular the UK Biobank and the different cohorts studied by Jaiswal et al). This could have contributed to an apparent milder effect of age on CHIP, even if this association was still observed.

In addition, there are previous reports of sex-related differences in the prevalence of CHIP, is there an association between CHIP and age after adjusting for sex? 

The reviewer correctly pointed out that sex has been associated with various aspects of CHIP. While Zekavat et al reported that CHIP carriers were more frequently males, Kar et al (Nature Genetics 2022), and Kamphuis et al (Hemasphere 2023) did not observe a difference in the prevalence of CHIP between males and females, but rather a difference in the mutational spectrum. Male presented more frequently SRSF2, ASXL1, SF3B1, U2AF1, JAK2, TP53 and PPM1D mutations while females had more frequently DNMT3A, CBL and GNB1 mutations.

In our study, the association between CHIP prevalence and age was indeed significant even after adjustment on sex (p<0.001 for the total cohort, p=0.0197 for the CHAth study and p=0.0394 for the 3C).

(4) The mutated genes included in the definition of "CHIP" here are markedly different than those in most previous studies, particularly when considering specifically the studies that demonstrated an association between CHIP and atherosclerotic CVD. For instance, the definition of CHIP in this manuscript includes genes such as ANKRD26, CALR, CCND2, and DDX41... that are not prototypical CHIP genes. This is unlikely to have a major impact on the main results, as the vast majority of mutations detected are indeed in bona fide CHIP genes, but it should be at least acknowledged.

We agree with the reviewer that our gene panel includes genes that are not considered prototypical CHIP genes. This acknowledgment has been added in the Supplementary Methods section. To perform this study, we did not design a specific targeted sequencing panel. We used the one that is used for the diagnosis of myeloid malignancies at the University Hospital of Bordeaux. ANKRD26 and DDX41 are genes that, when mutated, predispose to the development of hematological malignancies. CALR mutations are frequently detected in Myeloproliferative Neoplasms while CCND2 mutation can be detected in acute myeloid leukemia among other diseases. As usually performed in our routine practice, we analyzed all the genes in the panel. However, as stated by the reviewer, most of the mutations we detected involved bona fide CHIP genes.

Furthermore, the strategy used here for the CHIP variant calling and curation seems substantially different than that used in previous studies, which precludes a direct comparison. This is important because such differences in the definition of CHIP and the curation of variants are the basis of most conflicting findings in the literature regarding the effects of this condition. Ideally, the authors should conduct sensitivity analyses restricted to prototypical CHIP genes, using the criteria that have been previously established in the field (e.g. Vlasschaert et al, Blood 2023).

We agree with the reviewer, our strategy for CHIP variant calling and curation was substantially different from what has been used in other studies. We decided to apply the criteria we used in previous studies for the analysis of somatic mutation in myeloid malignancies. Because CHIP are defined by the detection of “somatic mutations in leukemia driver genes”, this appeared to follow the definition of CHIP.

We also acknowledge that this discrepancy with the criteria defined by Vlasschaert et al could contribute to our findings that differ from those of other studies. We thus checked whether the variants detected were in accordance or not with the criteria defined by Vlasschaert et al. Pooling the 2 cohorts, we detected 439 variants, 381 of which were in accordance with the criteria established by Vlasschaert et al, representing a concordance rate of 86.8%. Moreover, the variants “wrongly” retained according to these criteria had an impact on the conclusion on the detection of CHIP in only 15 patients (because these variants were associated with a mutation in a bona fide CHIP gene and/or because its VAF was below 2%). Thus, the impact of CHIP variant calling and curation had only a limited impact on our results. This has been added in the discussion (lines 455-459).

However, we would like to discuss the criteria that have been defined by Vlasschaert et al which are probably too restrictive. For some genes, such as ZRSR2, in addition to frameshift and non-sens mutations that are expected to be associated with a loss of function, only some single nucleotide variations were retained (probably those detected by this group). In our patient 20785, we detected a c.524A>G, p.(Tyr175Cys) mutation that was not reported in the list published by Vlasscheart et al. However, this variant presents a VAF presumptive of a somatic origin (3%), affects the Zn finger domain of the protein and is observed in a male subject. Thus, it presents several criteria to consider it as associated with a loss of function. Similarly, the CBL variant c.1139T>C, p.(Leu380Pro) observed in our patient 21536, although not affecting the residues 381-421 of the protein (the criteria defined by Vlasschaert et al), has been reported in 29 cases of hematological malignancies. It is thus likely to have a significant impact on the behavior of hematopoietic cells. Moreover, in the same patient, a TET2 c.4534G>A, p.(Ala1512Thr) variant was detected. Although not affecting directly the CD1 domain, it has been reported in a case of AML with a VAF suggestive of a somatic origin (Papaemmanuil et al, NEJM 2016). The SH2B3 gene is not considered by Vlasschaert et al as a bona fide CHIP gene, contrary to other genes involved in cell signaling such as JAK2, GNAS, GNB1, CBL. However, inactivating mutations in SH2B3 can be detected in myeloid malignancies and were recently shown to drive the phenotype in some patients with a MPN (Zhang et al, American Journal of Hematology 2024). We could thus expect that this also happens in our patients 22591 and 21998 who harbor mutations of SH2B3 (a SNV in the PH domain and a frameshift mutation respectively).

Regarding BCOR, STAG2, SMC3 and RAD21 genes, although frameshift mutations are the most prevalent, there are several reports on the existence of SNV in the context of hematological malignancies (COSMIC, Blood (2021) 138 (24): 2455–2468, Blood Cancer Journal (2023)13:18 ; https://doi.org/10.1038/s41408-023-00790-1).

We can also add that although Vlasschaert et al did not consider CSF3R and CALR as CHIP-genes, Kessler et al did. Because CHIP are an emerging field, it should be considered that the concepts that define it are expected to evolve, as demonstrated by the recent study of the Jyoti Nangalia’s group (Bernstein et al, Nature Genetics 2024) who showed that 17 additional genes (including SH2B3) should be considered as driver of clonal hematopoiesis.

(5) An important limitation of the current study is the cross-sectional design of most of the analyses. For instance, it is not surprising that no association is found between CHIP and prevalent atherosclerosis burden by ultrasound imaging, considering that many individuals may have developed atherosclerosis years or decades before the expansion of the mutant clones, limiting the possible effect of CHIP on atherosclerosis burden. Similarly, the analysis of the relationship between CHIP and a history of MI may be confounded by the potential effects of MI on the expansion of mutant clones. In this context, it is noteworthy that the only positive results here are found in the analysis of the relationship between CHIP at baseline and incident MI development over follow-up. Increasing the sample size for these longitudinal analyses would provide deeper insights into the relationship between CHIP and MI. 

We agree with the reviewer that increasing the sample size for longitudinal analyses would provide deeper insights into the relationship between CHIP and MI. Unfortunately, for the moment, we do not have access to additional samples of the 3C study and are not able to perform these additional analyses.

(6) The description of some analyses lacks detail, but it seems that statistical analyses were exclusively adjusted for age or age and sex. The lack of adjustment for conventional cardiovascular risk factors in statistical analyses may confound results, particularly given the marked differences in several variables observed between groups.

The reviewer is right when saying that we adjusted our analyses on age and/or sex. This was done because as stated before, our results did not show a lot of significant differences. However, we reanalyzed our data, adjusting further the tests for conventional cardiovascular risk factors, and observed similar results. These data have been added in the results section (lines 286-287, 303, 319, 331-332, 341).

(7) The variant allele fraction (VAF) threshold for identifying clinically relevant clonal hematopoiesis is still a subject of debate. The authors state that subjects without any detectable mutation or with mutations with a VAF below 2% were considered non-CHIP carriers. While this approach is frequent in the field, it likely misses many impactful mutations with lower VAFs. Such false negatives could contribute to the null findings reported here. Ideally, the authors should determine the lower detection limit of their sequencing approach (either computationally or through serial dilution experiments) and identify the threshold of VAF that can be detected reliably with their sequencing assay. The association between CHIP and MI should then be evaluated considering all mutations above this VAF threshold, in addition to sensitivity analyses with other thresholds frequent in the literature, such as 1% VAF, 2% VAF, and 10% VAF.

We agree with the reviewer that the VAF threshold for identifying clinically relevant CH is still debated. As stated in the manuscript and by the reviewer, we used the conventional threshold of 2%. Considering that different studies have shown that the cardiovascular risk is increased in a more important manner for CHIP with a high VAF (Jaiswal et al, NEJM 2017, Kessler et al Nature 2022, Vlasschaert et al, Circulation 2023), it is not sure that considering variant with a very low VAF (below 2%) would help us in finding an impact of CHIP on inflammation, atherosclerosis or atherothrombotic risk.

However, as mentioned by the reviewer, variants with a low VAF could have a clinical impact as recently reported by Zhao et al. In France, the use of biological analysis for medical purposes imposes to demonstrate that all its aspects are mastered, including their performances. In that context, we determined that our NGS strategy allowed us to reliably detect mutation with a VAF down to 1% (data not shown). As stated in the discussion, we also analyzed our results considering variants with a VAF of 1% and found similar results (lines 394-395). The sensitivity analyses were already mentioned in the manuscript, as we also searched for an effect of CHIP with a high VAF (≥5%) and found no effect neither. We did not have a sufficient number of subjects carrying variants with a VAF≥10% to perform analysis with this threshold.

(8) The authors should justify the use of 3D vascular ultrasound imaging exclusively in the supra-aortic trunk. I am not familiar with this technique, but it seems to be most typically used to evaluate atherosclerosis burden in superficial vascular beds such as carotids or femorals. I am concerned about the potential impact of tissue depth on the accurate quantification of atherosclerosis burden in the current study (e.g. https://doi.org/10.1016/j.atherosclerosis.2016.03.002). It is unclear whether the carotids or femorals were imaged in the study population. 

We apologize for the lack of precision in the Methods section. As stated by the reviewer, we evaluated the atherosclerosis burden in superficial vascular beds. We measured atheroma volume at the site of the common carotid (as described by B Lopez-Melgar, in Atheroslerosis, 2016). We did not analyze femoral arteries in this study. The sentence is now corrected in the Methods (lines 176-179).

(9) The specific criteria used to define LOY need to be justified. LOY is stated to be defined based on a "A cut off of 9% of cells with mLOY defined the detection of a mLOY based on the study of 30 men of less than 40 years who had a normal karyotype as assessed by conventional cytogenetic study." As acknowledged by the authors, this definition of LOY is substantially different than that used in recent studies employing the same technique to detect LOY (Mas-Peiro et al, EHJ 2023). In addition, it seems essential to provide more detailed information on the ddPCR assay used to determine LOY, including the operating range and, more importantly, the lower limit of detection (%LOY) of the assay. A dilution series of a control DNA with no LOY would be helpful in this context. 

We apologize if the definition of the threshold for detecting mLOY was unclear. To test the performance of our ddPCR technique, we first determined the background noise by testing DNA obtained from total leukocytes in 30 men of ≤40 years who presented a normal karyotype as assessed by conventional cytogenetic technics. In this control population supposed not to carry mLOY, we detected of proportion of cells with mLOY of 2,34+/-1,98 (see Author response image 1, panel A). We thus considered a threshold above 9% as being different from background noise (mean + 3 times the standard deviation).

We then compared the proportion of cells with mLOY measured by ddPCR and conventional karyotype and observed a rather good correlation between the 2 technics (R2\=0.6430, p=0.0053, see Author response image 1, panel B). Finally, we tested the reliability of our ddPCR assay in detecting different levels of mLOY using a dilution series of control DNA (from an equivalent of 2% of cell with mLOY to 98% of cells with mLOY). We observed a very nice correlation between the theoretical and measured proportions of cells with mLOY (R2\=0.9989, p<0.001, see Author response image 1, panel C). Of note, the proportion of mLOY measured for values ≤10% were concordant with theoretical values. However, considering the background noise determined with control DNA, we were unable to confirm that this “signal” was different from the background noise. Therefore, we set a threshold of 9% to define the detection of mLOY by ddPCR. It is also noteworthy that the 10% cell population with mLOY was consistently detected by the ddPCR technique. This has been added in the Methods section (lines 228-235).

Author response image 1.

(10) Our understanding of the relationship between CHIP and CVD is evolving fast, and the manuscript should be considered in the context of recent literature in the field. For instance, the recent work by Zhao et al (JAMA Cardio 2024, doi:10.1001/jamacardio.2023.5095) should be considered, as it used a similar targeted DNA sequencing approach as the one used here, but found a clear association between CHIP and coronary heart disease (in a population of 6181 individuals). 

We thank the reviewer for this pertinent reference. We did not include it in the first version of our manuscript because it was not published yet when we submitted our work. We included this reference in the discussion (lines 451, 455, 464). We also included the recent study of Heimlich et al (Circ Gen Pre Med 2024, lines 464-468) who studied the association of CHIP with atherosclerosis burden.

(11) The use of subjective terms like "comprehensive" or "thorough" in the title of the manuscript does not align with the objective nature of scientific reporting. 

We removed the terms “comprehensive” and “thorough” from the title and the text.

Recommendations for the authors:

Reviewing Editor:

The Editors believe that in light of the small study the word Comprehensive has to be removed (including from the title and abstract).

We agree and removed the term comprehensive from the title and the text.

Reviewer #1 (Recommendations For The Authors):

Other comments:

It has long been recognized that hsCRP does not adequately address the inflammation associated with CHIP. For example, see Bick et al Nature 2020; 586:763. Through an assessment of a large dataset, the regulation of multiple inflammatory mediators was associated with CHIP but not with CRP. 

We agree that hsCRP is probably not the most sensitive marker for inflammatory state associated with CHIP. However, it is the most commonly used one in medical practise. However, as indicated in the discussion (lines 418-420), we did not observe any association between CHIP and the plasmatic level of different cytokines (IL1ß, IL6, IL18 and TNFα) in patients enrolled in the CHAth study.

Many of the citations lack journal names, volumes, page numbers, etc. 

We apologize for this and corrected the citations.

Please provide more details on the methodology (i.e. is CHIP assessed only through NGS with no error correction?). Specify the rationale for why the 9% LOY threshold was employed. Provide this information in the Methods section.

We added more details on the methodology as demanded in the results section (lines 212-214 and 228-235).

Supplementary Table S3 lacks headings. What are the designations for columns 6-8? 

We apologize for this and corrected the Table. Columns 6-8 correspond to the VAF, coverage of the variants and depth of sequencing, as for Table S4.

eLife assessment

This important study describes the discovery of a mechanism by which multiple species of bacteria synthesize and localize polar flagella via a novel protein, FipA, which interacts with FlhF. The authors use appropriate methodological approaches (biochemistry, molecular microbiology, quantitative microscopy, and bacterial genetics) to obtain and present convincing results and interpretations. This work will particularly interest those studying bacterial motility and bacterial cell biologists.

Reviewer #1 (Public review):

Summary:

Bacteria exhibit species-specific numbers and localization patterns of flagella. How specificity in number and pattern is achieved is poorly understood but often depends on a soluble GTPase called FlhF. Here the authors take an unbiased protein-pulldown approach to identify a protein FipA in V. parahaemolyticus that interacts with FlhF. They show that FipA co-occurs with FlhF in the genomes of bacteria with polarly-localized flagella and study the role of FipA in three different bacteria: V. parahaemolyticus, S. purtefaciens, and P. putida. In each case, they show that FipA contributes to FlhF polar localization, flagellar assembly, flagellar patterning, and motility to different species-specific extents.

Strengths:

The authors perform a comprehensive analysis of FipA, including phenotyping of mutants, protein localization, localization dependence, and domains of FipA necessary for each. Moreover, they perform a time-series analysis indicating that FipA localizes to the cell pole likely prior to, or at least coincident with, flagellar assembly. They also show that the role of FipA appears to differ between organisms in detail but the overarching idea that it is a flagellar assembly/localization factor remains convincing.

Weaknesses:

For me the comparative analysis in the different organism was on balance, a weakness. By mixing the data for each of the organisms together, I found it difficult to read, and take away key points from the results. In its current form, the individual details seem to crowd out the model.

Reviewer #2 (Public review):

Summary:

The authors identify a novel protein, FipA, which facilitates recruitment of FlhF to the membrane at the cell pole together with the known recruitment factor HupB. This finding is key to understanding the mechanism of polar localization. By comparing the role of FipA in polar flagellum assembly in three different species from Vibrio, Shewanella and Pseudomonas, they discover that, while FipA is required in all three systems, evolution has brought different nuances that open avenues for further discoveries.

Strengths:

The discovery of a novel factor for polar flagellum development. A significant contribution to our understanding of flagellar evolution. The solid nature and flow of the experimental work.

Weaknesses:

All my concerns have been addressed. I find no weaknesses. A nice, solid piece of work.

Reviewer #3 (Public review):

Summary:

The authors investigate how polar flagellation is achieved in gamma-proteobacteria. By probing for proteins that interact with the known flagellar placement factor FlhF, they uncover a new regulator (FipA) for flagellar assembly and polar positioning in three flagellated gamma-proteobacteria. They convincingly demonstrate that FipA interacts genetically and biochemically with previously known spatial regulators HubP and FlhF. FipA is a membrane protein with a cytoplasmic DUF2802 and it co-localizes to the flagellated pole with HubP and FlhF. The DUF2802 mediates the interaction between FipA and FlhF and this interaction is required for FipA function. FipA localization depends on HubP and FlhF.

Strengths:

The work is throughly executed, relying on bacterial genetics, cell biology and protein interaction studies. The analysis is deep, beginning with the discovery af a new and conserved factor, to the molecular dissection of the protein and probing localisation and interaction determinants. Finally, they show that these determinants are important for function and they perform these studies in parallel in three model systems.

Weaknesses:

Because some of the phenotypes and localisation dependencies differ somewhat between model systems, the comparison is challenging to the reader because it is sometimes not obvious what these differences mean and why they arise.

Author response:

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

eLife assessment

This important research uses an elegant combination of protein-protein biochemistry, genetics, and microscopy to demonstrate that the novel bacterial protein FipA is required for polar flagella synthesis and binds to FlhF in multiple bacterial species. This manuscript is convincing, providing evidence for the early stages of flagellar synthesis at a cell pole; however, the protein biochemistry is incomplete and would benefit from additional rigorous experiments. This paper could be of significant interest to microbiologists studying bacterial motility, appendages, and cellular biology.

We are very grateful for the very positive and helpful evaluation.

Joint Public Review:

Bacteria exhibit species-specific numbers and localization patterns of flagella. How specificity in number and pattern is achieved in Gamma-proteobacteria needs to be better understood but often depends on a soluble GTPase called FlhF. Here, the authors take an unbiased protein-pulldown approach with FlhF, resulting in identifying the protein FipA in V. parahaemolyticus. They convincingly demonstrate that FipA interacts genetically and biochemically with previously known spatial regulators HubP and FlhF. FipA is a membrane protein with a cytoplasmic DUF2802; it co-localizes to the flagellated pole with HubP and FlhF. The DUF2802 mediates the interaction between FipA and FlhF, and this interaction is required for FipA function. Altogether, the authors show that FipA likely facilitates the recruitment of FlhF to the membrane at the cell pole together with the known recruitment factor HupB. This finding is crucial in understanding the mechanism of polar localization. The authors show that FipA co-occurs with FlhF in the genomes of bacteria with polarly-localized flagella and study the role of FipA in three of these organisms: V. parahaemolyticus, S. purtefaciens, and P. putida. In each case, they show that FipA contributes to FlhF polar localization, flagellar assembly, flagellar patterning, and motility, though the details differ among the species. By comparing the role of FipA in polar flagellum assembly in three different species, they discover that, while FipA is required in all three systems, evolution has brought different nuances that open avenues for further discoveries.

Strengths:

The discovery of a novel factor for polar flagellum development. The solid nature and flow of the experimental work.

The authors perform a comprehensive analysis of FipA, including phenotyping of mutants, protein localization, localization dependence, and domains of FipA necessary for each. Moreover, they perform a time-series analysis indicating that FipA localizes to the cell pole likely before, or at least coincident with, flagellar assembly. They also show that the role of FipA appears to differ between organisms in detail, but the overarching idea that it is a flagellar assembly/localization factor remains convincing.

The work is well-executed, relying on bacterial genetics, cell biology, and protein interaction studies. The analysis is deep, beginning with discovering a new and conserved factor, then the molecular dissection of the protein, and finally, probing localization and interaction determinants. Finally, the authors show that these determinants are important for function; they perform these studies in parallel in three model systems.

Weaknesses:

The comparative analysis in the different organisms was on balance, a weakness. Mixing the data for the organisms together made the text difficult to read and took away key points from the results. The individual details crowded out the model in its current form. Indeed, because some of the phenotypes and localization dependencies differ between model systems, the comparison is challenging to the reader. The authors could more clearly state what these differences mean, why they arise, and (in the discussion) how they might relate to the organism's lifestyle.

More experiments would be needed to fully analyze the effects of interacting proteins on individual protein stability; this absence slightly detracted from the conclusions.

We have tried our best to improve the manuscript according to the insightful suggestions of the reviewers. Please find our answers to the raised issues below.

Reviewer #1 (Recommendations For The Authors):

We are very grateful to this reviewer for the very positive evaluation and the great suggestions to improve the manuscript.

I think there is value to the comparative analysis but how to present it in such a way that the key similarities and differences stand out is the challenge. Perhaps a table that compares the three datasets is sufficient. Or tell the story of V. parahaemolyticus first to establish the model, followed by comparative analysis of the other two organisms highlighting differences and relegating similarities to supplemental?

We agree that the our previous presentation of our comparative analysis made it very hard to follow the major findings and the general role(s) of FipA, and we are very grateful for the suggestions on how to improve this. We have decided to change the presentation as the reviewer recommended. We used V. parahaemolyticus as a ‚lead model‘ to describe the role of FipA, and we then compared the major findings to the other two species. We hope that the story is now easier to follow.

This is not something that needs to be addressed in the text but I wanted to bring the protein SwrB to the authors' attention which may further expand FipA relevance. Bacillus subtilis uses FlhFG to somehow pattern flagella in a peritrichous arrangement and there are a number of striking similarities, in my opinion, between FipA and SwrB. The two proteins have very similar domain architecture/topology, both proteins promote flagellar assembly, and the genetic neighborhood/operon organization is uncannily similar. There are other more minor similarities dependent on the organism in this paper.

Phillips, Kearns. 2021. Molecular and cell biological analysis of SwrB in Bacillus subtilis. J Bacteriol 203:e0022721

Phillips, Kearns. 2015. Functional activation of the flagellar type III secretion export apparatus. PLoS Genet 11:e1005443.

We thank this reviewer for pointing out these intriguing similarities. For this study we have decided to exclusively concentrate on polarly flagellated bacteria. FlhF und FlhG are also present in B. subtilis where they play a role in organizing flagellation, but we feel that this would be out of scope for this manuscript.

Reviewer #2 (Recommendations For The Authors):

We would like to thank this reviewer for the very positive evaluation and for pointing out several issues to strengthen the story.

Figure 3A data are problematic since everything is too small to visualize. Since these are functional GFP fusions (or mCherry for 2E data), why are they not presented in color?

Again - why are color figures not used to help the reader in Fig 4A and 5F & 5G to confirm what is asserted?

Again, it is difficult to see the images presented. It is asserted that FipA is recruited to the cell pole after cell division and before flagellum assembly, but one has to take their word for it.

We fully agree that in some case the localization pattern is hard to see on the micrographs presented. We have, therefore, provided enlarged micrographs in the supplemental part which allow to better see the fluorescent foci within the cells. With respect to presentations in color – we found that this did not improve the visibility of localizations and therefore have decided to use the grayscale images.

Here, what is missing are turnover assays. Do FipA, FlhF, and HubP all co-localize as complex or is the absence of one leading to the protein turnover of other partners? I think this needs to be sorted out before final conclusions can be made.

Thanks for pointing out this important point. We have now provided western analysis which demonstrate that FipA and FlhF are produced and stable in the absence of the other partners (see Supplemental Figure 5). Stability of HubP as a general polar marker not only required for flagellation was not determined.

Minor comments:

Line 58: change "around" to "in timing with"

Line 79: what "signal" is transferred from the C-ring to the MS-ring. Are they not fully connected such that rotation is the entire structure - C-ring-MS-ring-Rod-Hook-Filament. Is it not the change in the relationship to the stator complex where the signal is transferred?

Line 85: change "counting" to "control of flagellar numbers per cell"

Line 110: change "is (co-)responsible for recruiting" to "facilitates recruitment of"

Thanks for pointing this out. We have adjusted the wording according to the reviewer’s suggestions.

Given that motility phenotypes vary on individual plates (volumes and dryness vary), why in Figure 2C are the motility assays for fipA and flhF mutants of P. putida done on different plates?

For better visualisation, we have rearranged the spreading halos for the figure. All strain spreading comparisons on soft agar were always conducted on the same plate due to the reasons this reviewer mentioned.

Reviewer #3 (Recommendations For The Authors):

We thank this reviewer for the very positive evalution and the great suggestions.

One possibility is to describe first all the results relating to FipA in Vibrio and then add the result sections at the end to illustrate the differences between Vibrio and Shewanella, and then Vibrio and Pseudomonas. This may make it easier to follow for the reader.

We agree that the our previous presentation of our comparative analysis made it very hard to follow the major findings and the general role(s) of FipA, and we are very grateful for the suggestions on how to improve this. We have decided to change the presentation as the reviewer recommended. We used V. parahaemolyticus as a ‚lead model‘ to describe the role of FipA, and we then compared the major findings to the other two species. We hope that the story is now easier to follow.

I would have liked to see some TEM analysis of flagella in fipA/hubP double mutants strains and was also wondering if FipA/FlhF/HubP colocalization had been studied in E. coli when all proteins are expressed together, at least with two bearing fluorescent tags.

Thanks for these great suggestions. In this study, we have concentrated on the localization of FlhF by FipA and HubP. HubP has multiple functions in the cell and may also affect flagellar synthesis to some extent in a species-specific fashion. Therefore, any findings would have to be discussed very carefully, so we have decided to leave that out for the time being.

With respect to the FipA/HubP/FlhF production in a heterologous host such as E. coli, this has been partly done (without FipA) in a second parallel story (see reference to Dornes et al (2024) in this manuscript). Rebuilding larger parts of the system in a heterologous host is currently done in an independent study. Therefore, we have decided not to include this already here.

From the Reviewing Editor:

We are grateful for handling the fair reviewing process, for the positive evaluation and the helpful hints.

The microscopy was inconsistent (DIC versus phase) for unclear reasons. Did using different microscopes impact the ability to acquire low-intensity fluorescence signals? Please add a sentence in the Methods section to clarify.

We are sorry for this inconsistency. As the imaging was carried out by different labs (to some part before the projects were joined), the corresponding preferred microscopy settings were used. We have added an explaining sentence to the Methods section.

Also, some subcellular fluorescence localizations were not visible in the selected images (e.g., Figures 3 and 5). The reader had to rely on the authors' statements and analyses. The conclusions could be more robust with fluorescence measurements across the cell body for a subset of cells. The authors could provide this data analysis in the Supplemental; this measurement would more clearly show an accumulation of fluorescence at the cell pole, particularly in low-intensity images.

We fully agree that in some case the localization pattern is hard to see on the micrographs presented. Unfortunately, often the signal is not sufficiently strong to provied proper demographs. We have, therefore, provided enlarged micrographs in the supplemental part, which allow to better see the fluorescent foci within the cells.

hyperpost://hyperpost/search-peergos_dns_settings

hypothesis ex

Author response:

We sincerely thank the reviewers for their thoughtful, critical, and constructive comments, which will help us in further exploring the mechanisms by which LDH regulates glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation future studies. The following is our responses to the reviewers' comments.

Reviewer #1 (Public Review):

Summary:

Zeng et al. have investigated the impact of inhibiting lactate dehydrogenase (LDH) on glycolysis and the tricarboxylic acid cycle. LDH is the terminal enzyme of aerobic glycolysis or fermentation that converts pyruvate and NADH to lactate and NAD+ and is essential for the fermentation pathway as it recycles NAD+ needed by upstream glyceraldehyde-3-phosphate dehydrogenase. As the authors point out in the introduction, multiple published reports have shown that inhibition of LDH in cancer cells typically leads to a switch from fermentative ATP production to respiratory ATP production (i.e., glucose uptake and lactate secretion are decreased, and oxygen consumption is increased). The presumed logic of this metabolic rearrangement is that when glycolytic ATP production is inhibited due to LDH inhibition, the cell switches to producing more ATP using respiration. This observation is similar to the well-established Crabtree and Pasteur effects, where cells switch between fermentation and respiration due to the availability of glucose and oxygen. Unexpectedly, the authors observed that inhibition of LDH led to inhibition of respiration and not activation as previously observed. The authors perform rigorous measurements of glycolysis and TCA cycle activity, demonstrating that under their experimental conditions, respiration is indeed inhibited. Given the large body of work reporting the opposite result, it is difficult to reconcile the reasons for the discrepancy. In this reviewer's opinion, a reason for the discrepancy may be that the authors performed their measurements 6 hours after inhibiting LDH. Six hours is a very long time for assessing the direct impact of a perturbation on metabolic pathway activity, which is regulated on a timescale of seconds to minutes. The observed effects are likely the result of a combination of many downstream responses that happen within 6 hours of inhibiting LDH that causes a large decrease in ATP production, inhibition of cell proliferation, and likely a range of stress responses, including gene expression changes.

Strengths:

The regulation of metabolic pathways is incompletely understood, and more research is needed, such as the one conducted here. The authors performed an impressive set of measurements of metabolite levels in response to inhibition of LDH using a combination of rigorous approaches.

Weaknesses:

Glycolysis, TCA cycle, and respiration are regulated on a timescale of seconds to minutes. The main weakness of this study is the long drug treatment time of 6 hours, which was chosen for all the experiments. In this reviewer's opinion, if the goal was to investigate the direct impact of LDH inhibition on glycolysis and the TCA cycle, most of the experiments should have been performed immediately after or within minutes of LDH inhibition. After 6 hours of inhibiting LDH and ATP production, cells undergo a whole range of responses, and most of the observed effects are likely indirect due to the many downstream effects of LDH and ATP production inhibition, such as decreased cell proliferation, decreased energy demand, activation of stress response pathways, etc.

We appreciate the reviewer’s critical comments. The main argument is whether the inhibition of LDH induces a temporal perturbation in glycolysis, the TCA cycle, and OXPHOS, or if it leads to a shift to a new steady state. We argue that this shift represents a transition between two steady states; specifically, GNE-140 treatment drives metabolism from one steady state to another.

Before conducting the experiment, we performed a time course experiment, measuring glucose consumption and lactate production in cells treated with GNE-140. The results demonstrated a very good linearity, indicating that the glycolytic rate remained constant—thus confirming that glycolysis was at steady state. Given the tight coupling between glycolysis, the TCA cycle, and OXPHOS, we infer that the TCA cycle and OXPHOS were also at steady state. However, this ‘infer’ requires further confirmation.

Multiple published reports have shown that LDH inhibition in cancer cells causes a shift from fermentative ATP production to respiratory ATP production. This notion persists because it is often compared to the well-established Crabtree and Pasteur effects, where cells toggle between fermentation and respiration based on glucose and oxygen availability. However, in the Pasteur or Crabtree effects, the deprivation of oxygen—the terminal electron acceptor—drives the switch, which is fundamentally different from LDH inhibition.

Reviewer #2 (Public Review):

Summary:

Zeng et al. investigated the role of LDH in determining the metabolic fate of pyruvate in HeLa and 4T1 cells. To do this, three broad perturbations were applied: knockout of two LDH isoforms (LDH-A and LDH-B), titration with a non-competitive LDH inhibitor (GNE-140), and exposure to either normoxic (21% O2) or hypoxic (1% O2) conditions. They show that knockout of either LDH isoform alone, though reducing both protein level and enzyme activity, has virtually no effect on either the incorporation of a stable 13C-label from a 13C6-glucose into any glycolytic or TCA cycle intermediate, nor on the measured intracellular concentrations of any glycolytic intermediate (Figure 2). The only apparent exception to this was the NADH/NAD+ ratio, measured as the ratio of F420/F480 emitted from a fluorescent tag (SoNar).

The addition of a chemical inhibitor, on the other hand, did lead to changes in glycolytic flux, the concentrations of glycolytic intermediates, and in the NADH/NAD+ ratio (Figure 3). Notably, this was most evident in the LDH-B-knockout, in agreement with the increased sensitivity of LDH-A to GNE-140 (Figure 2). In the LDH-B-knockout, increasing concentrations of GNE-140 increased the NADH/NAD+ ratio, reduced glucose uptake, and lactate production, and led to an accumulation of glycolytic intermediates immediately upstream of GAPDH (GA3P, DHAP, and FBP) and a decrease in the product of GAPDH (3PG). They continue to show that this effect is even stronger in cells exposed to hypoxic conditions (Figure 4). They propose that a shift to thermodynamic unfavourability, initiated by an increased NADH/NAD+ ratio inhibiting GAPDH explains the cascade, calculating ΔG values that become progressively more endergonic at increasing inhibitor concentrations.

Then - in two separate experiments - the authors track the incorporation of 13C into the intermediates of the TCA cycle from a 13C6-glucose and a 13C5-glutamine. They use the proportion of labelled intermediates as a proxy for how much pyruvate enters the TCA cycle (Figure 5). They conclude that the inhibition of LDH decreases fermentation, but also the TCA cycle and OXPHOS flux - and hence the flux of pyruvate to all of those pathways. Finally, they characterise the production of ATP from respiratory or fermentative routes, the concentration of a number of cofactors (ATP, ADP, AMP, NAD(P)H, NAD(P)+, and GSH/GSSG), the cell count, and cell viability under four conditions: with and without the highest inhibitor concentration, and at norm- and hypoxia. From this, they conclude that the inhibition of LDH inhibits the glycolysis, the TCA cycle, and OXPHOS simultaneously (Figure 7).

Strengths:

The authors present an impressively detailed set of measurements under a variety of conditions. It is clear that a huge effort was made to characterise the steady-state properties (metabolite concentrations, fluxes) as well as the partitioning of pyruvate between fermentation as opposed to the TCA cycle and OXPHOS.

A couple of intermediary conclusions are well supported, with the hypothesis underlying the next measurement clearly following. For instance, the authors refer to literature reports that LDH activity is highly redundant in cancer cells (lines 108 - 144). They prove this point convincingly in Figure 1, showing that both the A- and B-isoforms of LDH can be knocked out without any noticeable changes in specific glucose consumption or lactate production flux, or, for that matter, in the rate at which any of the pathway intermediates are produced. Pyruvate incorporation into the TCA cycle and the oxygen consumption rate are also shown to be unaffected.

They checked the specificity of the inhibitor and found good agreement between the inhibitory capacity of GNE-140 on the two isoforms of LDH and the glycolytic flux (lines 229 - 243). The authors also provide a logical interpretation of the first couple of consequences following LDH inhibition: an increased NADH/NAD+ ratio leading to the inhibition of GAPDH, causing upstream accumulations and downstream metabolite decreases (lines 348 - 355).

Weaknesses:

Despite the inarguable comprehensiveness of the data set, a number of conceptual shortcomings afflict the manuscript. First and foremost, reasoning is often not pursued to a logical conclusion. For instance, the accumulation of intermediates upstream of GAPDH is proffered as an explanation for the decreased flux through glycolysis. However, in Figure 3C it is clear that there is no accumulation of the intermediates upstream of PFK. It is unclear, therefore, how this traffic jam is propagated back to a decrease in glucose uptake. A possible explanation might lie with hexokinase and the decrease in ATP (and constant ADP) demonstrated in Figure 6B, but this link is not made.

We appreciate the reviewer's critical comment. In Figure 3C, there is no accumulation of F6P or G6P, which are upstream of PFK1. This is because the PFK1-catalyzed reaction sets a significant thermodynamic barrier. Even with treatment using 30 μM GNE-140, the ∆GPFK1 (Gibbs free energy of the PFK1-catalyzed reaction) remains -9.455 kJ/mol (Figure 3D), indicating that the reaction is still far from thermodynamic equilibrium, thereby preventing the accumulation of F6P and G6P.

We agree with the reviewer that hexokinase inhibition may play a role, this requires further investigation.

The obvious link between the NADH/NAD+ ratio and pyruvate dehydrogenase (PDH) is also never addressed, a mechanism that might explain how the pyruvate incorporation into the TCA cycle is impaired by the inhibition of LDH (the observation with which they start their discussion, lines 511 - 514).

We agree with the reviewer’s comment. In this study, we did not explore how the inhibition of LDH affects pyruvate incorporation into the TCA cycle. As this mechanism was not investigated, we have titled the study: "Elucidating the Kinetic and Thermodynamic Insights into the Regulation of Glycolysis by Lactate Dehydrogenase and Its Impact on the Tricarboxylic Acid Cycle and Oxidative Phosphorylation in Cancer Cells."

It was furthermore puzzling how the ΔG, calculated with intracellular metabolite concentrations (Figures 3 and 4) could be endergonic (positive) for PGAM at all conditions (also normoxic and without inhibitor). This would mean that under the conditions assayed, glycolysis would never flow completely forward. How any lactate or pyruvate is produced from glucose, is then unexplained.

This issue also concerned me during the study. However, given the high reproducibility of the data, we consider it is true, but requires explanation.

The PGAM-catalyzed reaction is tightly linked to both upstream and downstream reactions in the glycolytic pathway. In glycolysis, three key reactions catalyzed by HK2, PFK1, and PK are highly exergonic, providing the driving force for the conversion of glucose to pyruvate. The other reactions, including the one catalyzed by PGAM, operate near thermodynamic equilibrium and primarily serve to equilibrate glycolytic intermediates rather than control the overall direction of glycolysis, as previously described by us (J Biol Chem. 2024 Aug 8;300(9):107648).

The endergonic nature of the PGAM-catalyzed reaction does not prevent it from proceeding in the forward direction. Instead, the directionality of the pathway is dictated by the exergonic reaction of PFK1 upstream, which pushes the flux forward, and by PK downstream, which pulls the flux through the pathway. The combined effects of PFK1 and PK may account for the observed endergonic state of the PGAM reaction.

However, if the PGAM-catalyzed reaction were isolated from the glycolytic pathway, it would tend toward equilibrium and never surpass it, as there would be no driving force to move the reaction forward.

Finally, the interpretation of the label incorporation data is rather unconvincing. The authors observe an increasing labelled fraction of TCA cycle intermediates as a function of increasing inhibitor concentration. Strangely, they conclude that less labelled pyruvate enters the TCA cycle while simultaneously less labelled intermediates exit the TCA cycle pool, leading to increased labelling of this pool. The reasoning that they present for this (decreased m2 fraction as a function of DHE-140 concentration) is by no means a consistent or striking feature of their titration data and comes across as rather unconvincing. Yet they treat this anomaly as resolved in the discussion that follows.

GNE-140 treatment increased the labeling of TCA cycle intermediates by [13C6]glucose but decreased the OXPHOS rate, we consider the conflicting results as an 'anomaly' that warrants further explanation. To address this, we analyzed the labeling pattern of TCA cycle intermediates using both [13C6]glucose and  [13C5]glutamine. Tracing the incorporation of glucose- and glutamine-derived carbons into the TCA cycle suggests that LDH inhibition leads to a reduced flux of glucose-derived acetyl-CoA into the TCA cycle, coupled with a decreased flux of glutamine-derived α-KG, and a reduction in the efflux of intermediates from the cycle. These results align with theoretical predictions. Under any condition, the reactions that distribute TCA cycle intermediates to other pathways must be balanced by those that replenish them. In the GNE-140 treatment group, the entry of glutamine-derived carbon into the TCA cycle was reduced, implying that glucose-derived carbon (as acetyl-CoA) entering the TCA cycle must also be reduced, or vice versa.

This step-by-step investigation is detailed under the subheading "The Effect of LDHB KO and GNE-140 on the Contribution of Glucose Carbon to the TCA Cycle and OXPHOS" in the Results section in the manuscript.

In the Discussion, we emphasize that caution should be exercised when interpreting isotope tracing data. In this study, treatment of cells with GNE-140 led to an increase labeling percentage of TCAC intermediates by [13C6]glucose (Figure 5A-E). However, this does not necessarily imply an increase in glucose carbon flux into TCAC; rather, it indicates a reduction in both the flux of glucose carbon into TCAC and the flux of intermediates leaving TCAC. When interpreting the data, multiple factors must be considered, including the carbon-13 labeling pattern of the intermediates (m1, m2, m3, ---) (Figure 5G-K), replenishment of intermediates by glutamine (Figure 5M-V), and mitochondrial oxygen consumption rate (Figure 5W). All these factors should be taken into account to derive a proper interpretation of the data. 

Reviewer #3 (Public Review):

Hu et al in their manuscript attempt to interrogate the interplay between glycolysis, TCA activity, and OXPHOS using LDHA/B knockouts as well as LDH-specific inhibitors. Before I discuss the specifics, I have a few issues with the overall manuscript. First of all, based on numerous previous studies it is well established that glycolysis inhibition or forcing pyruvate into the TCA cycle (studies with PDKs inhibitors) leads to upregulation of TCA cycle activity, and OXPHOS, activation of glutaminolysis, etc (in this work authors claim that lowered glycolysis leads to lower levels of TCA activity/OXPHOS). The authors in the current work completely ignore recent studies that suggest that lactate itself is an important signaling metabolite that can modulate metabolism (actual mechanistic insights were recently presented by at least two groups (Thompson, Chouchani labs). In addition, extensive effort was dedicated to understanding the crosstalk between glycolysis/TCA cycle/OXPHOS using metabolic models (Titov, Rabinowitz labs). I have several comments on how experiments were performed. In the Methods section, it is stated that both HeLa and 4T1 cells were grown in RPMI-1640 medium with regular serum - but under these conditions, pyruvate is certainly present in the medium - this can easily complicate/invalidate some findings presented in this manuscript. In LDH enzymatic assays as described with cell homogenates controls were not explained or presented (a lot of enzymes in the homogenate can react with NADH!). One of the major issues I have is that glycolytic intermediates were measured in multiple enzyme-coupled assays. Although one might think it is a good approach to have quantitative numbers for each metabolite, the way it was done is that cell homogenates (potentially with still traces of activity of multiple glycolytic enzymes) were incubated with various combinations of the SAME enzymes and substrates they were supposed to measure as a part of the enzyme-based cycling reaction. I would prefer to see a comparison between numbers obtained in enzyme-based assays with GC-MS/LC-MS experiments (using calibration curves for respective metabolites, of course). Correct measurements of these metabolites are crucial especially when thermodynamic parameters for respective reactions are calculated. Concentrations of multiple graphs (Figure 1g etc.) are in "mM", I do not think that this is correct.

While the roles of lactate as a signaling metabolite and metabolic models are important areas of research, our work focuses on different aspects.

It is true that cell homogenates contain many enzymes that use NAD as a hydride acceptor or NADH as a hydride donor. However, in our assay system, the substrates are pyruvate and NADH, meaning only enzymes that catalyze the conversion of pyruvate + NADH to NAD + lactate can utilize NADH. Other enzymes do not interfere with this reaction. Although some enzymes may also catalyze this reaction, their catalytic efficiency is markedly lower than that of LDH, ensuring the validity of this assay.

Similarly, the assays for glycolytic intermediates are validated by the substrate specificity.

We have developed an LC-MS methodology for some glycolytic intermediates, but the accuracy of quantification remains unsatisfactory due to inherent limitations of this methodology.

eLife assessment

This study presents an assessment of the effect of lactate dehydrogenase (LDH) inhibition on the activity of glycolysis and tricarboxylic acid cycle. The data were collected and analyzed using solid and validated methodology. This paper makes a useful contribution to the field as it considers a control analysis of LDH flux.

Reviewer #1 (Public Review):

Summary:

Zeng et al. have investigated the impact of inhibiting lactate dehydrogenase (LDH) on glycolysis and the tricarboxylic acid cycle. LDH is the terminal enzyme of aerobic glycolysis or fermentation that converts pyruvate and NADH to lactate and NAD+ and is essential for the fermentation pathway as it recycles NAD+ needed by upstream glyceraldehyde-3-phosphate dehydrogenase. As the authors point out in the introduction, multiple published reports have shown that inhibition of LDH in cancer cells typically leads to a switch from fermentative ATP production to respiratory ATP production (i.e., glucose uptake and lactate secretion are decreased, and oxygen consumption is increased). The presumed logic of this metabolic rearrangement is that when glycolytic ATP production is inhibited due to LDH inhibition, the cell switches to producing more ATP using respiration. This observation is similar to the well-established Crabtree and Pasteur effects, where cells switch between fermentation and respiration due to the availability of glucose and oxygen. Unexpectedly, the authors observed that inhibition of LDH led to inhibition of respiration and not activation as previously observed. The authors perform rigorous measurements of glycolysis and TCA cycle activity, demonstrating that under their experimental conditions, respiration is indeed inhibited. Given the large body of work reporting the opposite result, it is difficult to reconcile the reasons for the discrepancy. In this reviewer's opinion, a reason for the discrepancy may be that the authors performed their measurements 6 hours after inhibiting LDH. Six hours is a very long time for assessing the direct impact of a perturbation on metabolic pathway activity, which is regulated on a timescale of seconds to minutes. The observed effects are likely the result of a combination of many downstream responses that happen within 6 hours of inhibiting LDH that causes a large decrease in ATP production, inhibition of cell proliferation, and likely a range of stress responses, including gene expression changes.

Strengths:

The regulation of metabolic pathways is incompletely understood, and more research is needed, such as the one conducted here. The authors performed an impressive set of measurements of metabolite levels in response to inhibition of LDH using a combination of rigorous approaches.

Weaknesses:

Glycolysis, TCA cycle, and respiration are regulated on a timescale of seconds to minutes. The main weakness of this study is the long drug treatment time of 6 hours, which was chosen for all the experiments. In this reviewer's opinion, if the goal was to investigate the direct impact of LDH inhibition on glycolysis and the TCA cycle, most of the experiments should have been performed immediately after or within minutes of LDH inhibition. After 6 hours of inhibiting LDH and ATP production, cells undergo a whole range of responses, and most of the observed effects are likely indirect due to the many downstream effects of LDH and ATP production inhibition, such as decreased cell proliferation, decreased energy demand, activation of stress response pathways, etc.

Reviewer #2 (Public Review):

Summary:

Zeng et al. investigated the role of LDH in determining the metabolic fate of pyruvate in HeLa and 4T1 cells. To do this, three broad perturbations were applied: knockout of two LDH isoforms (LDH-A and LDH-B), titration with a non-competitive LDH inhibitor (GNE-140), and exposure to either normoxic (21% O2) or hypoxic (1% O2) conditions. They show that knockout of either LDH isoform alone, though reducing both protein level and enzyme activity, has virtually no effect on either the incorporation of a stable 13C-label from a 13C6-glucose into any glycolytic or TCA cycle intermediate, nor on the measured intracellular concentrations of any glycolytic intermediate (Figure 2). The only apparent exception to this was the NADH/NAD+ ratio, measured as the ratio of F420/F480 emitted from a fluorescent tag (SoNar).

The addition of a chemical inhibitor, on the other hand, did lead to changes in glycolytic flux, the concentrations of glycolytic intermediates, and in the NADH/NAD+ ratio (Figure 3). Notably, this was most evident in the LDH-B-knockout, in agreement with the increased sensitivity of LDH-A to GNE-140 (Figure 2). In the LDH-B-knockout, increasing concentrations of GNE-140 increased the NADH/NAD+ ratio, reduced glucose uptake, and lactate production, and led to an accumulation of glycolytic intermediates immediately upstream of GAPDH (GA3P, DHAP, and FBP) and a decrease in the product of GAPDH (3PG). They continue to show that this effect is even stronger in cells exposed to hypoxic conditions (Figure 4). They propose that a shift to thermodynamic unfavourability, initiated by an increased NADH/NAD+ ratio inhibiting GAPDH explains the cascade, calculating ΔG values that become progressively more endergonic at increasing inhibitor concentrations.

Then - in two separate experiments - the authors track the incorporation of 13C into the intermediates of the TCA cycle from a 13C6-glucose and a 13C5-glutamine. They use the proportion of labelled intermediates as a proxy for how much pyruvate enters the TCA cycle (Figure 5). They conclude that the inhibition of LDH decreases fermentation, but also the TCA cycle and OXPHOS flux - and hence the flux of pyruvate to all of those pathways. Finally, they characterise the production of ATP from respiratory or fermentative routes, the concentration of a number of cofactors (ATP, ADP, AMP, NAD(P)H, NAD(P)+, and GSH/GSSG), the cell count, and cell viability under four conditions: with and without the highest inhibitor concentration, and at norm- and hypoxia. From this, they conclude that the inhibition of LDH inhibits the glycolysis, the TCA cycle, and OXPHOS simultaneously (Figure 7).

Strengths:

The authors present an impressively detailed set of measurements under a variety of conditions. It is clear that a huge effort was made to characterise the steady-state properties (metabolite concentrations, fluxes) as well as the partitioning of pyruvate between fermentation as opposed to the TCA cycle and OXPHOS.

A couple of intermediary conclusions are well supported, with the hypothesis underlying the next measurement clearly following. For instance, the authors refer to literature reports that LDH activity is highly redundant in cancer cells (lines 108 - 144). They prove this point convincingly in Figure 1, showing that both the A- and B-isoforms of LDH can be knocked out without any noticeable changes in specific glucose consumption or lactate production flux, or, for that matter, in the rate at which any of the pathway intermediates are produced. Pyruvate incorporation into the TCA cycle and the oxygen consumption rate are also shown to be unaffected.

They checked the specificity of the inhibitor and found good agreement between the inhibitory capacity of GNE-140 on the two isoforms of LDH and the glycolytic flux (lines 229 - 243). The authors also provide a logical interpretation of the first couple of consequences following LDH inhibition: an increased NADH/NAD+ ratio leading to the inhibition of GAPDH, causing upstream accumulations and downstream metabolite decreases (lines 348 - 355).

Weaknesses:

Despite the inarguable comprehensiveness of the data set, a number of conceptual shortcomings afflict the manuscript. First and foremost, reasoning is often not pursued to a logical conclusion. For instance, the accumulation of intermediates upstream of GAPDH is proffered as an explanation for the decreased flux through glycolysis. However, in Figure 3C it is clear that there is no accumulation of the intermediates upstream of PFK. It is unclear, therefore, how this traffic jam is propagated back to a decrease in glucose uptake. A possible explanation might lie with hexokinase and the decrease in ATP (and constant ADP) demonstrated in Figure 6B, but this link is not made.

The obvious link between the NADH/NAD+ ratio and pyruvate dehydrogenase (PDH) is also never addressed, a mechanism that might explain how the pyruvate incorporation into the TCA cycle is impaired by the inhibition of LDH (the observation with which they start their discussion, lines 511 - 514).

It was furthermore puzzling how the ΔG, calculated with intracellular metabolite concentrations (Figures 3 and 4) could be endergonic (positive) for PGAM at all conditions (also normoxic and without inhibitor). This would mean that under the conditions assayed, glycolysis would never flow completely forward. How any lactate or pyruvate is produced from glucose, is then unexplained.

Finally, the interpretation of the label incorporation data is rather unconvincing. The authors observe an increasing labelled fraction of TCA cycle intermediates as a function of increasing inhibitor concentration. Strangely, they conclude that less labelled pyruvate enters the TCA cycle while simultaneously less labelled intermediates exit the TCA cycle pool, leading to increased labelling of this pool. The reasoning that they present for this (decreased m2 fraction as a function of DHE-140 concentration) is by no means a consistent or striking feature of their titration data and comes across as rather unconvincing. Yet they treat this anomaly as resolved in the discussion that follows.

Reviewer #3 (Public Review):

Hu et al in their manuscript attempt to interrogate the interplay between glycolysis, TCA activity, and OXPHOS using LDHA/B knockouts as well as LDH-specific inhibitors. Before I discuss the specifics, I have a few issues with the overall manuscript. First of all, based on numerous previous studies it is well established that glycolysis inhibition or forcing pyruvate into the TCA cycle (studies with PDKs inhibitors) leads to upregulation of TCA cycle activity, and OXPHOS, activation of glutaminolysis, etc (in this work authors claim that lowered glycolysis leads to lower levels of TCA activity/OXPHOS). The authors in the current work completely ignore recent studies that suggest that lactate itself is an important signaling metabolite that can modulate metabolism (actual mechanistic insights were recently presented by at least two groups (Thompson, Chouchani labs). In addition, extensive effort was dedicated to understanding the crosstalk between glycolysis/TCA cycle/OXPHOS using metabolic models (Titov, Rabinowitz labs). I have several comments on how experiments were performed. In the Methods section, it is stated that both HeLa and 4T1 cells were grown in RPMI-1640 medium with regular serum - but under these conditions, pyruvate is certainly present in the medium - this can easily complicate/invalidate some findings presented in this manuscript. In LDH enzymatic assays as described with cell homogenates controls were not explained or presented (a lot of enzymes in the homogenate can react with NADH!). One of the major issues I have is that glycolytic intermediates were measured in multiple enzyme-coupled assays. Although one might think it is a good approach to have quantitative numbers for each metabolite, the way it was done is that cell homogenates (potentially with still traces of activity of multiple glycolytic enzymes) were incubated with various combinations of the SAME enzymes and substrates they were supposed to measure as a part of the enzyme-based cycling reaction. I would prefer to see a comparison between numbers obtained in enzyme-based assays with GC-MS/LC-MS experiments (using calibration curves for respective metabolites, of course). Correct measurements of these metabolites are crucial especially when thermodynamic parameters for respective reactions are calculated. Concentrations of multiple graphs (Figure 1g etc.) are in "mM", I do not think that this is correct.

This is very difficult to understand. It would be better to add a paragraph explaining the meaning of the formula

eLife assessment

In this valuable work, Lodhiya et al. provide evidence that excessive ATP underlies the killing of the model organism Mycobacterium smegmatis by two mechanistically-distinct antibiotics. Clarification of the role(s) of reactive oxygen species and ADP, as well as discrepancies with existing literature, would strengthen the model proposed. The data are generally solid as the authors deploy multiple, orthogonal readouts and methods for manipulating reactive oxygen species and ATP. The work will be of interest to those studying antibiotic mechanisms of action.

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.

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.

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.

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.

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. tuberculossi 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.

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.

E-lit refers to works of literature that are born-digital, meaning they are designed and created to exist in a digital environment rather than being transferred from print. These works use digital media to offer unique ways of storytelling, interaction, and meaning-making, incorporating features like hypertext, multimedia elements (audio, video, animation), and interactivity.

The evolution of computers from a big gadget that can only be seen in a specific place and space to what we can comfortably carry around has no doubt give rise to numerous electronic literature that can be access easily. In the same vein, if the move to get imaging to get three dimensions on the screen to immersion in actual three-dimensional spaces see the light of day, more electronic literature and even electronic games will emerged and this in turn will leads to more people having more access to them.

Yes, Ukraine is dependent on Western money, there is neocolonialism here; however this does not deny Ukrainian agency to resist

It's not just Putin doing this. This feels like an oversimplification.

Writing this manifesto from a collective standpoint emphasizes power in numbers.

Sophia Graup

That is a very simplified reasoning. Somehow ironically, weapons do not perpetuate wars because when two countries with equal military might get into a clash, they are more mindful of mutually assured destruction and the rest of their allies take faster action in de-escalating tensions. Ukraine would not be attacked if it had resources anywhere similar to Russia, just like Palestine would not be so helpless in the face of Israeli oppression.

Before talking about the global level and the phantom "imperial blocks" it wouldn't hurt to talk about the exact historical, social, and political context of relations between Ukraine and Russia. Drawing away the attention from Ukraine as a direct subject of war and seeing it as a proxy-war of the "global powers" is dangerous and exclusive

curious about the role of the IMF in Ukraine, and how it is similar or different to their debt and destabiliization strategy in other countries

Saying no, voicing dissent in this case seems like the primary goal of this manifesto. How does voicing dissent via this route prevail over for example direct action / protesting / demos.

who is the actor here?

feminism as inherently peaceful

they do state that Russia is responsible for creating/starting the conflict

how do we fight back with peace?

Weapons also mean protection and armed resistance. What would our solidarity mean if we only supported Ukrainians as they are being annihilated and not when they rise and resist?

supporting anti-war Russians, but again not condemning imperialism, which many of them do not plan on confronting. the highly praised Navalny for example

How should feminists engage with states that utilize militarism? What are the details of navigating this?

deterrence strategy and global militarization, must be differentiated in terms of who is seeking weapons and why

Ukrainians demand cease fire by default, they didn't start the war, but who listens?

another disappointment :'(

ceasefire as a basic step but not the only one

no mention of Ukrainian feminism

:'(((( disappointing

what does this mean? reaction to what?

de-escalation as the only solution. What does this mean for the ukrainian resistance?

any peace or just peace?

Russia's full-scale military invasion seems more fitting. Focusing only on "Putin's regime" makes it look as if he's doing it alone, (as if it was Hitler alone responsible for the Holocaust). Also, the invasion started in 2014?

We here refers to feminists and revolutionaries worldwide that stand with Ukraine against Russian Invasion.

Collective resistance is definitely something that is important when it comes to unity against militarism and the support of peace initiatives

did you listen to the calls launched by Ukrainian feminists? why not respond to them?

are we still in the shperes of influence paradigm? can resistance on the ground not have agency?

What are these "imperialist blocs" exactly? Are we still in the Cold War?

Rosa Luxemburg was vocal against ALL imperialist wars

Russian propaganda loves to abuse this. When did NATO pose a direct threat to Russia? And in what world is it exusable to solve a Russia-NATO conflict preamptively on someone else's soil?

killed, murdered;

condemning Russia and Ukraine equally? what about the right to defend?

I wonder who is making these decisions, then they answer it beneath

euphemism

Death as a uniting force

How is this created?

对于同一个元素，使用相同的散列函数计算出的位数组下标是相同的。这样，在进行交并运算时，才能保证对应位表示的是同一个元素的存在与否。

i completely agree

YES I THINK THIS IS TRUE

AGREE

YES THIS IS TRUE

Das habe ich nicht verstanden.

infl

infl

influence

Defination

eLife assessment

This valuable study discusses a hot topic in post-endoscopic retrograde cholangiopancreatography pancreatitis. The new score for predicting post-ERCP pancreatitis offers an idea about the risk of pancreatitis before the procedure. Although most scores depend on intraprocedural manoeuvres, such as the number of attempts to cannulate the papilla, this is a solid retrospective single-center study in one country. To be validated, this score should be done in many countries and on large numbers of patients, nevertheless, this paper should interest gastrointestinal endoscopists.

Joint Public Review:

Summary:

This work provides a new general tool for predicting post-ERCP pancreatitis before the procedure depending on pancreatic calcification, female sex, intraductal papillary mucinous neoplasm, a native papilla of Vater, or the use of pancreatic duct procedures. Even though it is difficult for the endoscopist to predict before the procedure which case might have post-ERCP pancreatitis, this new model score can help with the maneuver and when the patient is at high risk of pancreatitis, sometimes can be deadly), so experienced endoscopists can do the procedure from the start. This paper provides a model for stratifying patients before the ERCP procedure into low, moderate, and high risk for pancreatitis. To be validated, this score should be done in many countries and on large numbers of patients. Risk factors can also be identified and added to the score to increase rank.

Strengths:

(1) One of the severe complications of endoscopic retrograde cholangiopancreatography procedure is pancreatitis, so investigators try all the time to find a score that can predict which patients will probably have pancreatitis after the procedure. Most scores depend on the intraprocedural maneuver. Some studies discuss the preprocedural score that can predict pancreatitis before the procure. This study discusses a new preprocedural score for post-ERCP pancreatitis.

(2) Depending on this score that identifies low, moderate, and high-risk patients for post-pancreatitis, so from the start, experienced and well-trained endoscopists can do the procedure or can refer patients to tertiary hospitals or use interventional radiology or endoscopic retrograde cholangiopancreatography.

(3) The number of patients in this study is sufficient to analyze data correctly.

Weaknesses:

(1) It is a single-country, retrospective study.

(2) Many cases were excluded, so the score cannot be applied to those patients.

(3) Many other studies, e.g., https://link.springer.com/article/10.1007/s00464-021-08491-1, https://pubmed.ncbi.nlm.nih.gov/36344369/, that have been published before discussing the same issue, so what is the new with this score?

(4) The discussion section needs reformulation to express the study's aim and results.

(5) Why did the authors select these items in their scoring system and did not add more variables?

eLife assessment

This important study combines multiple techniques to investigate how caspase activity regulates non-lethal caspase-dependent processes. Through a combination of various approaches, and the development of new techniques, the authors provide compelling evidence supporting the claim that Fas3G-overexpression promotes non-lethal caspase activation in olfactory receptor neurons.

Reviewer #1 (Public review):

Summary:

In this manuscript, Muramoto and colleagues have examined a mechanism by which the executioner caspase Drice is activated in a non-lethal context in Drosophila. The authors have comprehensively examined this in the Drosophila olfactory receptor neurons using sophisticated techniques. In particular, they had to engineer a new reporter by which non-lethal caspase activation could be detected. The authors conducted a proximity labeling experiment and identified Fasciclin 3 as a key protein in this context. While the removal of Fascilin 3 did not block non-lethal caspase activation (likely because of redundant mechanisms), its overexpression was sufficient to activate non-lethal caspase activation.

Strengths:

While non-lethal functions of caspases have been reported in several contexts, far less is known about the mechanisms by which caspases are activated in these non-lethal contexts. So, the topic is very timely. The overall detail of this work is impressive and the results for the most part are well-controlled and justified.

Weaknesses:

The behavioral results shown in Figure 6 need more explanation and clarification (more details below). As currently shown, the results of Figure 6 seem uninterpretable. Also, overall presentation of the Figures and description in legends can be improved.

Reviewer #2 (Public review):

In this study, the authors investigate the role of caspases in neuronal modulation through non-lethal activation. They analyze proximal proteins of executioner caspases using a variety of techniques, including TurboID and a newly developed monitoring system based on Gal4 manipulation, called MASCaT. They demonstrate that overexpression of Fas3G promotes the non-lethal activation of caspase Dronc in olfactory receptor neurons. In addition, they investigate the regulatory mechanisms of non-lethal function of caspase by performing a comprehensive analysis of proximal proteins of executioner caspase Drice. It is important to point out that the authors use an array of techniques from western blot to behavioral experiments and also that the generated several reagents, from fly lines to antibodies.

This is an interesting work that would appeal to readers of multiple disciplines. As a whole these findings suggest that overexpression of Fas3G enhances a non-lethal caspase activation in ORNs, providing a novel experimental model that will allow for exploration of molecular processes that facilitate caspase activation without leading to cell death.

Reading this part of the article made me realize that this is a good example of growing acceptance of IVF illustrates the concept of punctuated equilibrium in social and policy change. And that changes occur slowly and steadily, but significant shifts can happen rapidly due to various factors.

eLife assessment

This valuable study combines electrophysiology experiments and modeling to investigate the encoding of dynamic patterns of polarized light by identified neurons of the bumblebee central complex. The scientific question and methodology are compelling. However, the evidence supporting the authors' conclusions is incomplete without more comprehensive statistical analyses.

Reviewer #1 (Public review):

Summary:

The authors of this valuable study use linearly polarized UV light rotating at different angular velocities to stimulate photoreceptors in bumblebees and study the response of TL3 neurons to polarized light. Previous work has typically used a single constant rotation velocity of the polarized light, while the authors of this study explore a range of constant rotational velocities spanning from 30deg/s to 1920deg/s. The authors also use linearly polarized UV light rotating at continuously varying velocities following the angular velocity of the head of a flying bumblebee. 

Strengths:

The authors investigate the neuronal responses of TL3 neurons to a variety of rotational velocities. This approach has the potential to reveal the neuronal response to dynamically changing stimuli experienced by the animal as it moves around its environment.

The authors make good use of physiology and modeling to validate their hypotheses and findings.  If done right, this line of investigation has the potential to provide a very useful methodology for utilizing more complex stimuli in studies of the visual pathway and central complex than traditionally. 

Weaknesses: 

The attempt of the authors to use more naturalistic stimuli than previous studies is very important, but the stimulus they use, i.e. linearly polarized UV light projected on the whole dorsal rim of the animal's eyes, is very different from the circular pattern of UV light polarization coming through the sky. In particular, as a bumblebee turns under the sky, the light projected on each ommatidium of the dorsal rim area will not smoothly change like the rotating linearly polarized light used in the experiments. The authors need to discuss this and other limitations of their study. 

The authors should also commend the light intensity confound common in polarized light setups as discussed by Reinhard Wolf et al, J. Comp. Physiol. 1980 and in the thesis of Peter Weir, California Institute of Technology, 2013. It is unclear whether the authors performed measurements to quantify the intensity pattern and if they took measures to compensate and make the polarized light intensity uniform. 

The authors show that the neuronal responses of TL3 neurons depend on the recent history of the polarized light stimulus. They use as evidence, the different neuronal firing rates measured when arriving at the same polarization stimulus by following two different preceding stimulus sequences. It would have been worthwhile to investigate to what extent the difference in neuronal response is due to the history alone and to what extent it is due to spike timing stochasticity inherent in the neurons. According to the raster plots in Figure 2F, there is substantial stochasticity in the timing of the action potential firing events.

The authors appear to base their delay calculations and analysis on the response of one single neuron (Figures 2 and 3) even though they have recorded the responses of several TL3 neurons. There is no reason for the authors not to use all neuron recordings in their calculations and analysis.

Another concern is that while the authors make good use of modeling, like any model, the presented models only partially explain the observed phenomena. However, a discussion about the limitations of their model needs to be provided.  Actually, observing the discrepancies between the model's output and the intracellular recordings reveals what the model is missing. That is, careful consideration of the discrepancies would have led the authors to try adding some noise in their model, which would partially resolve the differences observed at the lower rotational speeds (see stars deviating from the fitted line in Figure 2A) and to consider that introducing an asymmetry between the post-stimulus inhibition and excitation time constants could result in a model not deviating as much at the higher rotation velocities during counter-clockwise rotation of the polarized light (see stars deviating from the fitted line in Figure 2A). 

In the end, the authors use the observation that during saccades, the average activity in their model-with-history increases to claim that when the animal does not turn, it uses less neuronal activity and energy. This is not a convincing line of reasoning. To make a claim about energy efficiency, the authors must instead compare their model with alternatives and show that the neuronal activity of their model during straight flight is indeed lower than those alternative models. Note that such a comparison would be meaningful only if the alternative models compared against capture physiology equally well in all other respects. However, the evident deviations of the presented model from the physiology measurements and the short duration of the test stimulus used would make any such claims difficult to substantiate. 

Finally, for most experiments, the models are stimulated with a single short yaw sequence lasting a few seconds to measure responses. Given the dependence of the model on history, using such a small sample, we cannot see how generalizable the observations are. The authors need to show that the same effect is produced using multiple different trajectories.

Reviewer #2 (Public review):

Summary:

The compass network is a higher-order circuit in insects that integrates sensory cues, like the angle of polarized light, with self-motion information to estimate the animal's angular position in space. This paper by Rother et al. uses share electrode recordings to measure intracellular voltage activity from individual compass neurons while polarization patterns are presented to the bee. They present patterns that rotate with variable speed or simulate the sensory experience created by a flight trajectory. The authors discover that at low rotational speeds, TL neuron responses diverge from the tuning expected from a systematic synaptic delay, suggesting that recent experience (history) impacts TL responses. A population model of 180 TL neurons is then used to argue that having cells that are impacted by spiking history could be advantageous for estimating heading. The model activity showed an anticipation of polarization angle for rapid turns that followed prolonged straight flights or turns in the opposite direction. The model also had reduced spiking activity during translational straight flight.

Strengths:

One strength of this paper is that it focuses on a question that is underexplored in the field: How does the compass network handle the processing delay caused by multi-synaptic relay from the DRA to the sensory input neurons (TL) to the compass network why the insect is turning rapidly and thus sampling distinct polarization angles in rapid succession? Another strength is the fact that they were able to present neurons with both simulated naturalistic polarization patterns that could occur during flight and synthetic stimuli with a range of rotational velocities. This provides an important data set where these responses can be compared. Another strength is the exploration of how adding a history term to a model of a population of TL neurons can lead to the population coding of polarization angle to vary in how delayed it is from changes to the sensory stimuli. They find that angular coding is more anticipatory (shorter delay) following prolonged periods of fixating a single angle, such as what occurs during translation movement, or following turns in the opposite direction of the current turn.

Weaknesses:

A challenge for this experimental approach is the relatively low power for data sets in some of the experimental conditions. Low throughput is expected for this experimental approach, as intracellular recordings are a challenging and time-consuming method. A weakness of the manuscript in its current form is that the data from all cells that were able to be recorded is not always presented or quantified. For example, only a single neuron example is used to show the impact of history on preferred polarization and how this tuning varied with rotation velocity. This is also true for the claim that TL3 neurons exhibit post-inhibitory excitation and post-excitatory inhibition. Another concern is regarding the use of the term "spiking-history" as potentially confusing to readers who might assume this process is cell intrinsic. The authors presented data shows evidence of an effect of stimulus history on the responses of the neurons. However as the authors describe in the discussion this current data set does not distinguish between an effect that occurs in the recorded neurons (e.g. an effect of intrinsic excitability) vs adaptation elsewhere in the circuit or DRA photoreceptors. A final challenge for this approach, shared with other studies that measure neural responses from an insect fixed in place, is that it assumes that these TL neurons are purely sensory and that their response properties (or those upstream of them) do not change when the bee performs a motor action or maneuver. This caveat should be considered when interpreting these data, however these data still represent novel information and important progress in exploring this question.