Reviewer #3 (Public Review):

To motivate the proposal, Karageorgiou et al. first identify a problem in applying current multivariable MR (MVMR) methods with many correlated exposures. I believe this problem can really be broken into two pieces. The first is that MVMR suffers from weak instrument bias. The second is that some traits may have nearly co-linear genetic associations, making it hard to disentangle which trait is causal. These problems connect in that inclusion of co-linear traits amplifies the problem of weak instrument bias - traits that are nearly co-linear with another trait in the study will have no or very few conditionally strong instruments.<br /> The authors then propose a solution: Apply a dimension reduction technique (PCA or sparse PCA) to the matrix of GWAS effect estimates for the exposures. The identified new components can then be used in MVMR in place of the directly measured exposures.

I think that the identified problem is timely and important. I also like the idea of applying dimension reduction techniques to GWAS effect estimates. However, I don't think that the manuscript in its current form achieves the goals that it has set out. Specifically, I will outline the weaknesses of the work in three categories:<br /> 1. The causal effects measured using this method are poorly defined.<br /> 2. The description of the method lacks important details.<br /> 3. Applied and simulation results are unconvincing.<br /> I will describe each of these in more detail below.

1. To me, the largest weakness of this paper is that it is not clear how to interpret the putatively causal effects being measured. The authors describe the method as measuring "the causal effect of the PC on outcome" but it is not obvious what this means.

One possible implication of this statement is that the PC is a real biological variable (say some hidden regulator) that can be directly intervened on. If this is the intention it should be discussed. However, this situation would imply that there is one correct factorization and there is no guarantee that PCs (or sparse PCs) come close to capturing that.

The counterfactual implied by estimating the effects of PCs in MVMR is that it is possible to intervene on and alter one PC while holding all other PCs constant.<br /> In the introduction, the authors note (and I agree) that one weakness of MR applied to correlated traits is that "MVMR models investigate causal effects for each individual exposure, under the assumption that it is possible to intervene and change each one whilst holding the others fixed." However, it is not obvious that altering one PC while holding the others constant is more reasonable.

2. This section combines a few items that I found unclear in the methods section. The most critical one is the lack of specification on how to select instruments.<br /> For the lipids application, the authors state that instruments were selected from the GLGC results, however, these only include instruments for LDL, HDL, and TG, so 1) it would not be possible to include variants that were independently instruments for one of the component traits alone and 2) there would be no instruments for the amino acids. There is no discussion of how instruments should be selected in general.<br /> This choice could also have a dramatic impact on the PCs estimated. The first PC is optimized to explain the largest amount of variance o of the input data which, in this case, is GWAS effect estimates. This means that the number of instruments for each trait included will drive the resulting PCs. It also means that differences in scaling across traits could influence the resulting PCs.

The other detail that is either missing or which I missed is what is used as the variant-PC association in the MVMR analysis. Specifically, is it the PC loadings or is it a different value? Based on the computation of the F-statistic I suspect the former but it is not clear. If this is the case, what is the effect of using loadings that have been shrunk via one of the sparse methods? It would be nice to see a demonstration of the bias and variance of the resulting method, though it is not clear to me what the "truth" would be.

3. In the lipids application, the fact that M.LDL.PL changes sign in MVMR analysis are offered as evidence of multicollinearity. I would generally associate multicollinearity with large variance and not bias. Perhaps the authors could offer some more insight on how multicollinearity would cause the observation.<br /> A minor point of confusion: I was unable to interpret this pair of sentences "Although the method did not identify any of the exposures as significant at Bonferroni-adjusted significance level, the estimate for M.LDL.PL is still negative but closer to zero and not statistically significant. The only trait that retains statistical significance is ApoB." The first sentence says that none of the exposures were significant while the second sentence says that Apo B is significant. The GRAPPLE results don't seem clearly bad, indeed if only Apo B is significant, wouldn't we conclude that of the 118 exposures, only Apo B is causal for heart disease? It would help to discuss more how the conclusions from the PC-based MVMR analysis compare to the conclusions from GRAPPLE.

It is a bit hard to interpret Table 4. I wasn't able to fully determine what "VLD, LDL significance in MR" means here. From the text, it seems that it means that any PC with a non-zero lodaing on VLDL or LDL traits was significant, however, this seems like a trivial criterion for the PCA method, since all PCs will be dense. This would mean this indicator only tells us whether and PCs were found to "cause" heart disease.

In simulations, I may be missing something about the definition of a true and false positive here. I think this is similar to my confusion in the previous paragraph. Wouldn't the true and false positive rates as computed using these metrics depend strongly on the sparsity of the components? It is not clear to me what ideal behavior would be here. However, it seems from the description that if the truth was as in Fig 7 and two methods each yielded one dense component that was found to be causal for Y, these two methods would get the same "score" for true positive and false positive rate regardless of the distribution of factor loadings. One method could produce a factor that loaded equally on all exposures while the other produced a factor that loaded mostly on X1 and X2 but this difference would not be captured in the results.

key passage from As We May Think

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Reply to the reviewers

Response to Reviewers:

1. General Statements

We thank the reviewers for the comments and the suggestions. We hope that we have addressed all the queries raised by the reviewers in the revised manuscript. We provide a point-by-point response below. Please note that the line numbers indicated in parentheses correspond to the pdf file without the track changes display.

2. Point-by-point description of the revisions

---

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary: Srinivasan and co-workers developed an alternative screening method for defining the ability of FtsZ inhibitor to affect FtsZ polymerization. This alternative assay was defined considering the expertise of the authors on the topic, and they use Schizosaccharomyces pombe as a model for studying the effect of PC190723, sanguinarine and berberine on FtsZ assembly. The use of a heterologous expression system is useful for the evaluation of FtsZ coming from different strains, both Gram - and Gram +. The same model could gain insights also on the capability of FtsZ inhibitors to affect eukaryotic cell physiology. Finally, authors resulted also in suggesting a possible cause to suspected resistance to PC190723 from Gram - strains as E. coli.

Major comments: • The conclusions are included in the discussion section and are quite convincing, for a general audience.

We thank the reviewer for the positive comments.

In my opinion, the authors should define which could be the limits of their method, since no data on the possible weaknesses are reported.

RESPONSE: We have discussed the limitations of the methods as well. The discussion has been modified and the following sentences have been now included in the revised manuscript.

“However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells. Consistently, while sanguinarine and berberine are known to affect the eukaryotic microtubules at 10 μΜ – 20 μM concentrations (Lopus and Panda 2006; Wang et al. 2016; Raghav et al. 2017), morphological effects on yeast cells were observed only at concentrations > 100 μM. However, yeast microtubules were not affected by berberine and sanguinarine. Differences in membrane lipid profiles and MDR efflux pumps between yeasts and mammalian cells might also contribute to differential resistance to the drugs being tested (Balzi and Goffeau 1991). Conversely, an inhibitory effect in yeast cells may not necessarily translate into toxicity in a human cell. These and the permeability of drugs in yeast cells represent an important caveat in using such heterologous expression systems for the screening of compounds against target molecules.”

[Lines 498-513]

As suggested in the later sections, we have also elaborated on the pros and cons of various methods including the yeast-based screening methods. [Lines 462-523]

• No additional experiments are required to support the claims.

• The suggested experiments could be quite easy to be realized for authors working in the microbiological field, and familiar with protein expression and purification, as well as bacteria and yeast growth.

• From my side, even if I am not so expert in microbiology and plasmid/protein purification, the methods presented could be reproduced with no significant doubt.

• Statistical analysis was done and seems to be adequate.

RESPONSE: We thank the reviewer for these encouraging comments.

Minor comments: • Prior studies should be deepened, especially for the state of art authors referred to. Additional paper, both reviews on the possible methods for evaluating FtsZ inhibition, as well as research papers on FtsZ inhibitors targeting E. coli and other Gram negative strains should be mentioned, since, in my opinion, these could move authors in changing a little bit the overall text of the manuscript.

RESPONSE: We have now elaborated the state-of-art methods used for evaluation of FtsZ inhibition and cited the relevant papers and reviews. We have also included papers on development of FtsZ inhibitors, especially the ones similar to PC190723, targeting Gram-negative bacteria. The following sentences have been included in the revised manuscript.

“Several approaches have been used to screen small molecules targeting bacterial cell division and FtsZ. While in vitro methods such as NMR (Domadia et al. 2007; Sun et al. 2014; Araújo‑Bazán et al. 2019) and crystallography (Läppchen et al. 2008; Fujita et al. 2017) are valuable and offer information on distinct binding sites, these are not efficient for screening. Electron microscopic examination can distinguish the effects of the compounds being tested on the FtsZ protofilament assembly and lateral associations (Nova et al. 2007; Kaul et al. 2012; Anderson et al. 2012; Sun et al. 2014; Huecas et al. 2017; Kumar et al. 2011; Park et al. 2014). Other techniques that are routinely used include fluorescence anisotropy (Ruiz‑Avila et al. 2013; Park et al. 2014), 90º light-scattering assay (Mukherjee and Lutkenhaus 1999) and dynamic light scattering (Hou et al. 2012; Di Somma et al. 2020) for assessing inhibition of FtsZ assembly (Kaul et al. 2012; Nova et al. 2007; Lui et al. 2019; Anderson et al. 2012, (Irwin et al. 2015). Other easily scalable high-throughput assays include FCS/FCCS and FRET-based methods (Hernández‑Rocamora et al. 2015; Mikuni et al. 2015; Reija et al. 2011).

In vivo assays relying on cell filamentation phenotype coupled with the localization of Z-ring might be a good indicator of FtsZ being the direct target. However, since bacteria can undergo cell filamentation and not assemble FtsZ rings in response to a variety of conditions, including DNA damage (Mukherjee et al. 1998) and disruption of membrane potential (Strahl and Hamoen 2010), the in vivo assay is not so useful unless combined with the in vitro assays mentioned above. Finally, the isolation of resistance mutants in FtsZ to the drug can provide strong evidence of FtsZ being the direct target.

Reconstitution systems are powerful and provide excellent control over the system, but they are emerging technologies and are technically challenging. Reconstitution systems include a variety of methods, such as the use of membrane nanodiscs, microbeads of different materials, supported bi-layer membranes (SLBs) and biomimetic systems that provide cell-like environments (Monterroso et al. 2013; Rivas et al. 2014).”

[Lines 462-487]

“Several compounds have been evaluated for their activity against FtsZ from both Gram-positive bacteria and Gram-negative bacteria. Although many exhibited only weak activity in vivo against Gram-negative bacteria, derivatives could be promising. These include benzamides (Haydon et al. 2008; Adams et al. 2011; Straniero et al. 2017, 2020a), trisubstituted benzimidazoles (Kumar et al. 2011), 4-bromo-1H-indazole derivatives (Wang et al. 2015), cinnamaldehyde and its derivatives (Domadia et al. 2007; Li et al. 2015), curcumin (Rai et al. 2008), heterocyclic molecules like guanidinomethyl biaryl compounds (Kaul et al. 2012), pyrimidine-quinuclidine scaffolds (Chan et al. 2013), 3-phenyl substituted 6,7-dimethoxyisoquinoline (Kelley et al. 2012), thiazole orange derivatives (Sun et al. 2017), viriditoxin (Wang et al. 2003), N-heterocycles such as zantrins and derivatives (Margalit et al. 2004; Nepomuceno et al. 2015).”

[Lines 69-80]

“Several efforts have been made to target Gram-negative bacteria with derivatives of benzamide. Examples include difluorobenzamides, substituted benzodioxanes, heterocyclic and non-heterocyclic derivatives (Straniero et al. 2017; Chai et al. 2020; Straniero et al. 2020a, 2020b). Although many exhibited promising activity in vitro, most were substrates for the AcrAB class of efflux pumps (Chai et al. 2020; Kaul et al. 2014; Straniero et al. 2020a, 2020b; Casiraghi et al. 2020). Thus, the poor membrane permeability, signature outer membrane, particularly lipopolysaccharide (LPS) structure (Wang et al. 2021), the presence of multiple efflux pumps in species such as E. coli, Klebsiella pneumonia and Pseudomonas aeruginosa (Piddock 2006), and differences in FtsZ sequences in the binding-site (Kaul et al. 2013b; Miguel et al. 2015) have been cited as reasons for lack of susceptibility of Gram-negative bacteria to benzamide derivatives (Casiraghi et al. 2020). More recently, two molecules, TXA6101 and TXY6129, with substituted 2,6-difluorobenzamide scaffold, have been shown to inhibit the polymerization of both E. coli and Klebsiella pneumoniae FtsZ. Moreover, despite being substrates for efflux pumps, TXA6101 induced morphological changes in K. pneumoniae (Rosado‑Lugo et al. 2022). Studies in the past on the effects of PC190723 on E. coli have been confusing, with a few reports suggesting an effect on FtsZ polymerization resulting in cell filamentation (Kaul et al. 2014), while others did not find any effect on EcFtsZ (Andreu et al. 2010; Anderson et al. 2012; Khare et al. 2019)⁠. The outer membrane has been shown to be a permeability barrier for PC190723 in E. coli (Khare et al. 2019; Chai et al. 2020). In addition, the Resistance-Nodulation-Division (RND) family of efflux pumps has been attributed to resistance against 2,6-difluorobenzamide derivatives, including TX436 (a prodrug of PC190723) in Gram-negative bacteria (Kaul et al. 2014).”

[Lines 527-550]

The whole text requires a deep check for grammar and word choice. Some sentences should be re-written since it is not so easy to understand their meaning. Figures are clear, even if I am not so convinced on the need of including Figure 1.

RESPONSE: We have now deleted Figure 1 and 2 (as also suggested by Reviewer #2), revised the manuscript and have re-written certain long sentences. We have used Grammarly to check for grammatical errors. We hope the manuscript is easier to follow with these changes.

Reviewer #1 (Significance (Required)):

• In my opinion, the outcome coming from this work could move researchers in evaluating an alternative method for assessing FtsZ inhibition. Nevertheless, the actual state of art, a few reviews of the last years confirm this, already underlined a huge number of possible assays, both microbiological, biochemical, biophysical, physiological, or other. As a result, the authors did not result in convincing me about the importance of their methods, when compared to others. They may include some other possible assays and comment of the differences, pros and cons.

RESPONSE: Several alternative methods have been evaluated and several excellent reviews published in the recent past have underlined the importance of these multiple methods to screen and validate small molecules targeting FtsZ. As suggested by the reviewer here and above, we have now discussed these methods including the yeast-based assay we describe, their advantages and limitations in the revised manuscript.

The following lines have now been included in Introduction.

“Several methods have been used to ascertain FtsZ as the target of the drug, and the various approaches have been reviewed in detail by many (Kusuma et al. 2019; Silber et al. 2020; Zorrilla et al. 2021; Andreu et al. 2022). Andreu et al. (2022) have recently proposed a streamlined experimental protocol for the screening and characterization of FtsZ inhibitors.”

Introduction – [Lines 113-117]

The following paragraphs, including ones as mentioned above have included in the discussion sections of the revised manuscript.

“Several approaches have been used to screen small molecules targeting bacterial cell division and FtsZ. While in vitro methods such as NMR (Domadia et al. 2007; Sun et al. 2014; Araújo‑Bazán et al. 2019) and crystallography (Läppchen et al. 2008; Fujita et al. 2017) are valuable and offer information on distinct binding sites, these are not efficient for screening. Electron microscopic examination can distinguish the effects of the compounds being tested on the FtsZ protofilament assembly and lateral associations (Nova et al. 2007; Kaul et al. 2012; Anderson et al. 2012; Sun et al. 2014; Huecas et al. 2017; Kumar et al. 2011; Park et al. 2014). Other techniques that are routinely used include fluorescence anisotropy (Ruiz‑Avila et al. 2013; Park et al. 2014), 90º light-scattering assay (Mukherjee and Lutkenhaus 1999) and dynamic light scattering (Hou et al. 2012; Di Somma et al. 2020) for assessing inhibition of FtsZ assembly (Kaul et al. 2012; Nova et al. 2007; Lui et al. 2019; Anderson et al. 2012, (Irwin et al. 2015). Other easily scalable high-throughput assays include FCS/FCCS and FRET-based methods (Hernández‑Rocamora et al. 2015; Mikuni et al. 2015; Reija et al. 2011).

In vivo assays relying on cell filamentation phenotype coupled with the localization of Z-ring might be a good indicator of FtsZ being the direct target. However, since bacteria can undergo cell filamentation and not assemble FtsZ rings in response to a variety of conditions, including DNA damage (Mukherjee et al. 1998) and disruption of membrane potential (Strahl and Hamoen 2010), the in vivo assay is not so useful unless combined with the in vitro assays mentioned above. Finally, the isolation of resistance mutants in FtsZ to the drug can provide strong evidence of FtsZ being the direct target.

Reconstitution systems are powerful and provide excellent control over the system, but they are emerging technologies and are technically challenging. Reconstitution systems include a variety of methods, such as the use of membrane nanodiscs, microbeads of different materials, supported bi-layer membranes (SLBs) and biomimetic systems that provide cell-like environments (Monterroso et al. 2013; Rivas et al. 2014). While in vitro biochemical assays and reconstitution systems are useful to find molecules that directly target FtsZ, they are cumbersome and need to be performed at optimal physiological pH and ionic conditions, which can be considerably variable among FtsZ from different species.

Our results on the ability of sanguinarine and berberine to specifically affect the assembly of FtsZ and not MreB in fission yeast highlight the utility of the heterologous expression system as a platform to identify molecules that specifically affect FtsZ polymerization. The yeast platform offers a cellular context mimicking the cytoplasm for cytoskeletal assembly. The system is simple to replicate in any laboratory, including those focused on chemical synthesis with minimum microbiological expertise and can be easily reproduced and scaled up as well. However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells. Consistently, while sanguinarine and berberine are known to affect the eukaryotic microtubules at 10 μΜ – 20 μM concentrations (Lopus and Panda 2006; Wang et al. 2016; Raghav et al. 2017), morphological effects on yeast cells were observed only at concentrations > 100 μM. However, yeast microtubules were not affected by berberine and sanguinarine. Differences in membrane lipid profiles and MDR efflux pumps between yeasts and mammalian cells might also contribute to differential resistance to the drugs being tested (Balzi and Goffeau 1991). Conversely, an inhibitory effect in yeast cells may not necessarily translate into toxicity in a human cell. These and the permeability of drugs in yeast cells represent an important caveat in using such heterologous expression systems for the screening of compounds against target molecules. However, notwithstanding this caveat, the heterologous system provides significant advantages in assessing the direct effects of the drug on FtsZ assembly. Moreover, fission yeast-based high-throughput platform screening methods using imaging have been successfully adapted to the screening of drugs against HIV-1 proteases by large-scale screening facilities such as the NIH Molecular Libraries Probe Production Centers Network in the Molecular Libraries Program, leading to several candidate drugs (Benko et al. 2017, 2019).”

Discussion - [Lines 462-519]

“A powerful emerging technique based on cytological profiling has been successfully used to identify the cellular pathways targeted by the inhibitors (Nonejuie et al. 2013; Martin et al. 2020), including cell division inhibition by FtsZ (Araújo‑Bazán et al. 2016). The recent advances in computational image analysis and deep learning approaches (von Chamier et al. 2021; Spahn et al. 2022) could further advance image-based screening for FtsZ inhibitors (Andreu et al. 2022).”

Discussion – [Lines 581-586]

As I mentioned before, there are a lot of reviews including the possible tests to perform for assessing FtsZ inhibition. A recent one was not cited, but, from my side, it should be mentioned (10.3390/antibiotics10030254).

The suggested article is an excellent review that in addition to providing an overview of the state-of-art methods currently in practice for screening drugs targeting FtsZ, also suggests other emerging technologies suitable for assay development. We had cited this article (Zorrilla et al., 2021; doi: 10.3390/antibiotics10030254) in other contexts in our original manuscript but inadvertently missed in the text while mentioning the methods for screening.

We have now cited Zorrilla et al., 2021 at all appropriate places in the revised manuscript. In addition, we have also cited (Monterroso 2013; https://doi.org/10.1016/j.ymeth.2012.12.014); (Rivas 2014; https://doi.org/10.1016/j.cbpa.2014.07.018); Kusuma 2019 (doi: 10.1021/acsinfecdis.9b00055); Schaffner-Barbero 2012 (doi: 10.1021/cb2003626); Silber et al 2020 (doi: 10.2217/fmb-2019-0348); Li et al., 2015 (doi: 10.1016/j.ejmech.2015.03.026); Casiraghi et al 2020 (doi: 10.3390/antibiotics9020069); Andreu et al., 2022 (10.3390/biomedicines10081825)

Moreover, I think authors should reconsidered novel research papers, in which researchers evaluated the reason behind the apparent inactivity of benzamide derivatives, similar to PC190723, towards Gram negative strains.

RESPONSE: Several novel papers that have reported reason for the inactivity of benzamide derivatives towards Gram-negative bacteria, including PC190723 have now been cited. The following sentences have been now included in the revised manuscript.

“Several efforts have been made to target Gram-negative bacteria with derivatives of benzamide. Examples include difluorobenzamides, substituted benzodioxanes, heterocyclic and non-heterocyclic derivatives (Straniero et al. 2017; Chai et al. 2020; Straniero et al. 2020a, 2020b). Although many exhibited promising activity in vitro, most were substrates for the AcrAB class of efflux pumps (Chai et al. 2020; Kaul et al. 2014; Straniero et al. 2020a, 2020b; Casiraghi et al. 2020). Thus, the poor membrane permeability, signature outer membrane, particularly lipopolysaccharide (LPS) structure (Wang et al. 2021), the presence of multiple efflux pumps in species such as E. coli, Klebsiella pneumonia and Pseudomonas aeruginosa (Piddock 2006), and differences in FtsZ sequences in the binding-site (Kaul et al. 2013b; Miguel et al. 2015) have been cited as reasons for lack of susceptibility of Gram-negative bacteria to benzamide derivatives (Casiraghi et al. 2020). More recently, two molecules, TXA6101 and TXY6129, with substituted 2,6-difluorobenzamide scaffold, have been shown to inhibit the polymerization of both E. coli and Klebsiella pneumoniae FtsZ. Moreover, despite being substrates for efflux pumps, TXA6101 induced morphological changes in K. pneumoniae (Rosado‑Lugo et al. 2022). Studies in the past on the effects of PC190723 on E. coli have been confusing, with a few reports suggesting an effect on FtsZ polymerization resulting in cell filamentation (Kaul et al. 2014), while others did not find any effect on EcFtsZ (Andreu et al. 2010; Anderson et al. 2012; Khare et al. 2019)⁠. The outer membrane has been shown to be a permeability barrier for PC190723 in E. coli (Khare et al. 2019; Chai et al. 2020). In addition, the Resistance-Nodulation-Division (RND) family of efflux pumps has been attributed to resistance against 2,6-difluorobenzamide derivatives, including TX436 (a prodrug of PC190723) in Gram-negative bacteria (Kaul et al. 2014).”

[Lines 527-550]

Researchers working on FtsZ inhibitors could be interested in this paper, especially microbiologists.

I specifically work on the design, synthesis and evaluation of the microbiological assays performed by others on my compounds.

========================================================================

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Dr. Srinivasin and colleagues previously developed a system where they expressed bacterial FtsZ in yeast and showed that it could assemble into polymers related to the Z rings. Here they develop this system further as a way to assay for drugs that may poison FtsZ, which would be candidates for new antibiotics. They test three drugs against three species of FtsZ. The results suggest that this system should be useful in screening new drugs that may target FtsZ. I would recommend publication after addressing a number of concerns and apparent contradictions.

Fig. 1 showing chemical formulas of the drugs, and Fig. 2 showing a schematic of the yeast expression system, are probably not needed.

RESPONSE: Reviewer #1 had also made a similar suggestion and we have now deleted these two figures (Fig. 1 and Fig. 2 in the older version).

The authors make a point that sanguinarine and berberine inhibit eukaryote cell morphology. In fact, what they show is that they affect yeast cell morphology. This may or may not extend to other eukaryotes. Also, other eukaryotic cells may be more sensitive to drugs than yeast. They should me more conservative in this claim that the system also screens for drugs effects on eukaryotes.

RESPONSE: We agree with the reviewer’s suggestions here that other eukaryotic cells may be more sensitive to drugs than yeast. We have modified the statements pertaining to these claims in the revised manuscript.

We have made the following changes in the revised version.

The title of the manuscript has been now modified as “A salt bridge-mediated resistance mechanism to FtsZ inhibitor PC190723 revealed by a cell-based screen”.

Lines 23-24 in the abstract has been modified to read as “The strategy also allows for simultaneous assessment of the toxicity of the drugs to eukaryotic yeast cells.”

Other sentences modified in the revised version are:

“We find that although sanguinarine and berberine affected FtsZ polymerization, they also affected yeast cell physiology”. [Lines 146-147]

“In this study, we have attempted to develop a cell-based assay using fission yeast (S. pombe) as a heterologous expression host, which would enable the screening of compounds that could directly affect FtsZ polymerization as well as identify potential toxicity to yeast (or eukaryotic) cells simultaneously”. [Lines 444-447]

“However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells”. [Lines 498-503]

“Conversely, an inhibitory effect in yeast cells may not necessarily translate into toxicity in a human cell. These and the permeability of drugs in yeast cells represent an important caveat in using such heterologous expression systems for the screening of compounds against target molecules”. [Lines 510-513]

Fig. 3 has some new structural data that should be explored more quantitatively. My quick measurement gave 0.5 and 0.8 µm for the outside diameters of Ec and Sa rings. The spirals of Hp seem to be 0.8 µm outside diameter, similar to SA rings. These spirals may be related to those reported by Popp and by Andreu under certain buffer conditions. This should be explored and referenced.

RESPONSE: We have now quantitatively measured the diameters of the rings formed by EcFtsZ and SaFtsZ and the diameter and pitch of the spiral polymers of HpFtsZ. These have been now included in the results section and presented as a graph in a new figure (Supplementary Fig. S2). Please also note that the scale bar in Figure 1 (previously Figure 3) was erroneously marked as 5 µm. This has been corrected in the revised version to 2.5 µm.

Also, the possibility that these spiral polymers may be related to those described by Popp and Andreu have been discussed. We included the following sentences in the discussion.

“Previous studies have shown that various factors such as molecular crowding, variable C-terminal regions and bound nucleotide state lead to the formation of supramolecular structures like twisted helical structures, toroids and rings similar to those that have been observed in vivo (Popp et al. 2009; Huecas et al. 2017). Thus, the molecular crowding due to the dense cytoplasm of the yeast cells could have possibly induced the spiral and ring-like assembly of FtsZ polymers (Erickson et al. 2010).”

[Lines 456-461]

But Fig. 4 presents a contradiction. Here the Hp control cells show long smooth polymers, not helical. This seems an important difference and needs to be addressed. Are the polymers sometimes straight and sometimes helical? After finishing the paper I see that in some experiments the HP is helical, and in others the polymers are straight and smooth. I think it would be important to determine what favors the two forms. If this remains a mystery, at least address it openly.

RESPONSE: This was definitely an oversight from the authors. We should have clearly mentioned this in the manuscript but completely missed the description of different polymers assembled by HpFtsZ.

We have now described this clearly in the results and added a new Figure (Supplementary Fig. S1) showing a time course for the appearance of spiral and linear polymers. We have also replaced the images in Figure 5E.

We have modified the results to read as:

“Interestingly, HpFtsZ assembled into linear cable-like structures as well as twisted polymers that were curled and spiral in appearance (Fig. 1D). The spiral filaments were more clearly visualized by deconvolution of the images (Fig. 1D iii and 1E). Further, super-resolution imaging using 3D-SIM clearly revealed that HpFtsZ assembles into spiral filaments in fission yeast (Fig. 1F).”

[Lines 171-175]

We have also added the following lines in the results section:

“Spiral polymers appeared early, at 16 – 18 hours after induction of expression (absence of thiamine), and linear cables appeared later at 20 – 22 hours (Fig. S1). The smooth linear polymers possibly arise from lateral association and bundling of FtsZ filaments (Monahan et al. 2009), but the factors determining the two forms in yeast cells remain unclear.”

[Lines 175-179]

I am concerned that the quantitation of drug inhibition in Fig 4, 5 is flawed. Visually from 4A it looks like ~90-100% of control cells have polymers, and sang reduces polymers by 70% for Sa and Ec and 100% for Hp: this is based on the number of spots and filaments I see in Fig. 4 Aii. But the quantitation in D shows only 17-23% reduction for all three. These numbers were based on determining the fraction of cells that showed polymer (spots or lines) vs diffuse. It seems that cells are counted as containing polymer even if they had a great reduction in spots or lines, but still had a few. E.g., 4Aii Sa has 4 cells, two of them with no spots, one with only 2, and one with ~7, which totals ~1/3 the spots in control cells. Categorizing cells with only a couple of spots as polymerized, seems to be a poor way to quantitate. Would it not be better to count all spots in all cells, or measure the total length of line polymers, as a measure of inhibition.

RESPONSE: We agree with the reviewer here that number of spots or the length of the polymers would be a better quantitative measure of the effect of the drugs than the percentage of cells presented. In the revised manuscript, we now present quantified data as suggested.

We have quantitated the number of spots per cell for SaFtsZ and total polymer length per cell for HpFtsZ to elucidate the effect of drugs on FtsZ polymers. The number of spots per cell were counted using built-in ImageJ macro OPS threshold IJ1 script which combines the otsu thresholding method and analyse particles plugin. The total polymer length per cell in the case HpFtsZ, was measured using used the lpx-plugins as described by Higaki (Higaki et al., 2017).

In addition, using the lpx-plugins, we also quantify density, a measure of the amount cytoskeleton per unit area in a given cell (Henty-Ridilla et al., 2014; Higaki et al., 2017). We had previously used this measure successfully to quantify assembly of Spiroplasma citri MreB in fission yeast (Pande et al., 2022).

The methodology has been described in detail in the Materials and Methods section under the heading – “Quantitation of the number of spots, polymer length and density”

Lines [665-689]

The new data has been included in the results (lines 207-231 and 275-284) and new Figures (Fig. 2 E, G and Fig. 3 G, H) have been added.

Fig. 5 makes a convincing case that PC19 accelerates or enhances the polymerization of Sa and Hp. Fig. S2 shows that the structures of polymers are not changed when PC19 is added at 20 hrs, after polymers have already formed. It would have been nice to see for both 5A and S2A that the round spots had holes in the center, when imaged by SIM. Again the quantitation of cells as polymer vs diffuse seems ill suited, because it misses cells with a reduced number of spots.

RESPONSE: We have imaged the FtsZ polymers of Sa and Hp in the presence of PC190723 using SIM and included these images as new panels in the figures. Figure 3C, 3F and Figure S4 in the revised manuscript.

Again, for Figure 5 (Fig. 3 in the revised version), we have provided the quantitation as number of spots per cell, polymer length per cell and density (amount of cytoskeleton per unit area) as described above (new Figures - Fig. 3 G, H) in the revised manuscript.

[Lines 275-284]

Fig. 6 uses FRAP to show that PC reduces the dynamic exchange of Sa polymers by a factor of 3. It is remarkable to me that rapid exchange is not completely eliminated by PC. Regardless, it would be very important to reference the previous study of Adams..Errington 2011, where they showed the same thing for Foci in Bacillus. PC19 reduced the exchange from 3 to 10 s, but the foci were still very dynamic.

RESPONSE: We had referenced this work in the original submission in the discussion section – “These results are also consistent with the earlier findings that PC190723 acts to induce FtsZ polymerization and stabilize FtsZ filaments (Andreu et al. 2010; Elsen et al. 2012; Miguel et al. 2015; Fujita et al. 2017) and its derivative compound, 8j acting to slow down FtsZ-ring turnover by 3-fold in B. subtilis (Adams et al. 2011).”

[Lines 563-567] in revised manuscript

We have now added the following statement and referenced Adams et al., 2011 in the results section as well.

“Interestingly, compound 8j, a related benzamide derivative, has been shown to slow down FtsZ-ring turnover by 3-fold in B. subtilis (Adams et al. 2011).”

[Lines 324-326]

The analysis of the salt bridge as opposed to a single Arg or His being the cause of resistance to PC19 is an interesting addition to the study. In Fig. 8D some numbers do not agree between the caption and figure (R309/7; S226/7). The whole figure should be carefully checked.

RESPONSE: We thank the reviewer for pointing to these. We have corrected these errors now in the revised version (Fig. 6).

I am not familiar with the Gram -ve and Gram +ve nomenclature. Why not simply gram- and gram+?

RESPONSE: We agree that Gram -ve / +ve are not standard notations and inappropriate.

We have now written them as Gram-negative and Gram-positive throughout the text.

The Discussion is quite long largely because it repeats items from Results and Introduction. It is also redundant to hype the value of this system in both Introduction and Discussion; The Introduction should be sufficient. The Discussion should be pared down by eliminating repetition and focusing on relating results to previous literature, in particular items that have not been referenced previously in the paper. Also, I think we don't need the final "In summary" paragraph. That is already nicely presented in the Abstract.

RESPONSE: We have omitted the repetitive statements from the discussion. We have also deleted the final summary paragraph. We had added new paragraphs [lines 462-519] pertaining to previous literature (also suggested by Reviewer #1) to the discussion section in the revised manuscript.

The authors should probably provide references to other studies that have used yeast expression to study assembly of FtsZ. I am thinking in particular of papers from the Osteryoung lab looking at chloroplast FtsZ.

RESPONSE: We have now referenced other papers that have used yeast expression to study assembly of FtsZ.

The following statement has been added to the introduction:

“Moreover, the dynamics of chloroplast FtsZs have also been successfully studied using the heterologous fission yeast expression system (TerBush and Osteryoung 2012; Yoshida et al. 2016; TerBush et al. 2018).”

Lines [132-134]

NO PAGE NUMBERS. Authors should be penalized a week delay for submitting a mss without page numbers.

RESPONSE: We sincerely apologise for this gross error and oversight and thank the reviewer for patiently reading through and reviewing a manuscript with no page numbers and line numbers. We are truly sorry for having submitted a manuscript as such and have now included page numbers and line numbers in the manuscript.

Reviewer #2 (Significance (Required)):

This work should be of interest to the broad field of research on FtsZ. The authors present it as a new platform for assaying drugs targeting FtsZ, and researchers in this area will certainly be interested. It will also be of broader interest for the novel assay of assembly and exchange dynamics and how they may be modulated by small molecules.

========================================================================

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary: The authors established a proof-of-concept assay to investigate the bacterial cytoskeletal protein FtsZ in fission yeast, and this heterologous yeast system is useful for compounds identification targeting FtsZ. The authors used this system to understand the mechanism of FtsZ's resistance to drug PC190723. Major comments: 1. From the study, the pombe seems to be a good system for investigating the bacterial cytoskeleton proteins and testing the drugs for them. However, to my knowledge it is not convincing that this is the proper system can be used to assessing the eukaryotic toxicity, since no toxicity to pombe does not mean no toxicity to human cells and vice versa.

RESPONSE: We agree with the reviewer that toxicity to S. pombe cannot be directly extended to assessing toxicity to other eukaryotic cells such as human cells. As suggested by Reviewer#2 as well, we have modified these claims in the revised manuscript, discussed the possibilities and limited the scope of this work to assessing toxicity in yeast cells.

We have made the following changes in the revised version.

The title of the manuscript has been now modified as “A salt bridge-mediated resistance mechanism to FtsZ inhibitor PC190723 revealed by a cell-based screen”.

Lines 23-24 in the abstract has been modified to read as “The strategy also allows for simultaneous assessment of the toxicity of the drugs to eukaryotic yeast cells.”

Other sentences modified in the revised version are:

“We find that although sanguinarine and berberine affected FtsZ polymerization, they also affected yeast cell physiology”. [Lines 146-147]

“In this study, we have attempted to develop a cell-based assay using fission yeast (S. pombe) as a heterologous expression host, which would enable the screening of compounds that could directly affect FtsZ polymerization as well as identify potential toxicity to yeast (or eukaryotic) cells simultaneously”. [Lines 444-447]

“However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells”. [Lines 498-503]

“Conversely, an inhibitory effect in yeast cells may not necessarily translate into toxicity in a human cell. These and the permeability of drugs in yeast cells represent an important caveat in using such heterologous expression systems for the screening of compounds against target molecules”. [Lines 510-513]

From figure 4A to 4C, there seems no big difference of cell morphology between control and drug treatment, except for Berberine treatment of SaFtsZ-GFP. Under the low concentration of Sanguinarine (20 µM) and Berberine (53.791 µm), the FtsZ polymerization was disrupted and seems no effect on cell morphology. Why would the authors use much higher Sanguinarine (135.95 µM) and Berberine (134.45 µM) to prove there two drugs are toxic to pombe cells?

RESPONSE: Earlier reports had shown that sanguinarine and berberine affect mammalian microtubules (Lopus and Panda 2006 - DOI: 10.1111/j.1742-4658.2006.05227.x; Raghav et al., 2017 - DOI: 10.1021/acs.biochem.7b00101). While, we did not observe any growth defect in yeast cells, earlier studies have suggested that yeasts possibly require higher concentrations of certain drugs than used for mammalian cells due to the presence of the cell wall, particularly S. pombe (Perez and Ribas 2004 - https://doi.org/10.1016/j.ymeth.2003.11.020; Benko et al., 2017 - DOI: 10.1186/s13578-016-0131-5). We had thus explored the possibility of cell toxicity to yeast cells at higher concentrations of the drugs.

The following lines have thus been added to the results section in the revised manuscript.

“Although we did not observe any growth defect in yeast cells at lower concentrations of the drugs, earlier studies have suggested that yeast cells possibly require higher concentrations of drugs than used for mammalian cells due to the presence of the cell wall, which is particularly thick in S. pombe (Benko et al. 2017; Pérez and Ribas 2004). We thus explored the possibility of cell toxicity to yeast cells at higher concentrations of the drugs.”

Lines [234-239]

Sanguinarine and Berberine are FtsZ disruption drugs, do these drugs have effect on microtubule?

RESPONSE: We have now examined the effect of Sanguinarine and Berberine on yeast microtubules as well and did not find any visible differences between the control and inhibitor (either low or high concentrations) treated cells. This data has been added as a new figure (Supplementary Fig. S3 A and B) in the revised manuscript and the following line added to the results.

“However, even at higher concentrations, neither of the drugs showed any visible effect on yeast microtubules (Fig. S3 A and B).”

[Lines 241-242]

The discussion has been modified as follows:

“However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells. Consistently, while sanguinarine and berberine are known to affect the eukaryotic microtubules at 10 μΜ – 20 μM concentrations (Lopus and Panda 2006; Wang et al. 2016; Raghav et al. 2017), morphological effects on yeast cells were observed only at concentrations > 100 μM. However, yeast microtubules were not affected by berberine and sanguinarine. Differences in membrane lipid profiles and MDR efflux pumps between yeasts and mammalian cells might also contribute to differential resistance to the drugs being tested (Balzi and Goffeau 1991). Conversely, an inhibitory effect in yeast cells may not necessarily translate into toxicity in a human cell. These and the permeability of drugs in yeast cells represent an important caveat in using such heterologous expression systems for the screening of compounds against target molecules.”

[Lines 498-513]

There are very few SaFtsZ-GFP dot structure in fig 5B, and this is inconsistent with the SaFtsZ-GFP dot structure in fig 4A. Fig 5D has the same issue compare to Fig 4Ci

RESPONSE: We had probably not made it very clear the experimental differences between Figure 4 and 5 (Figure 2 and 3 in the revised manuscript), which has led to this apparent inconsistency.

The strong nmt1 promoter (thiamine repressible) takes about 18 hours for full-induction in the absence of thiamine (Forsburg 1993 - https://doi.org/10.1093/nar/21.12.2955). We have utilised the medium strength nmt41 promoter in our studies and hence, in Figure 2, expression of FtsZ-GFP fusions were allowed for longer periods of time (22 – 24 hours) in the experiments concerning sanguinarine and berberine treatments.

This has been now clearly mentioned in the revised version of the manuscript in the results section (lines 196-199) as well as in figure legends.

In contrast the very few dot structures or polymers in Figure 3 (revised manuscript) is because of a shorter period of expression of FtsZ-GFP (12 – 14 hours in the absence of thiamine). The shorter period of expression time in these experiments allowed us to test if PC190723 indeed induced the polymerisation of FtsZ, at a stage when the control cells still exhibited diffuse fluorescence and had minimal FtsZ assembly. Thus, the cultures were allowed to express FtsZ for a shorter period of time and imaged in the case of experiments presented in Figure 3.

This has been now clearly mentioned in the results (lines 259-263) as well as in figure legends in the revised manuscript.

We hope that we have now made these experimental differences clear and provide more clarity. We have also included this information (hours of induction) in the figure panel.

The concentration of PC190723 the author used is 20 µg/ml, which is enough for disrupting FtsZ function, however according to the Sanguinarine and Berberine experiments, the author may use higher concentration of PC190723 to assess its toxicity to pombe cells. Same as Sanguinarine and Berberine, does PC190723 has effect on microtubule?

RESPONSE: As suggested by the reviewer, we have tested the effect of PC190723 at a higher concentration (140.6 µM) similar to that of Sanguinarine and Berberine. We did not find any morphological changes in yeast upon treatment with higher concentrations of PC190723. Also, the drug did not seem to affect the yeast microtubules. These have been now included in the results section and new images have been added in the figure (Supplementary Fig. S3).

The following lines have been added in the revised manuscript to the results section:

“Earlier studies had reported that PC190723 was non-toxic to eukaryotic cells, including budding yeast (Haydon et al. 2008). We further tested if PC190723 resulted in morphological defects in S. pombe, like sanguinarine and berberine, at higher concentrations. However, consistent with the earlier reports, PC190723 was inactive against S. pombe at both 56.2 μM and 140.6 μM and did not cause any morphological changes (Fig. 2H iv). Further, PC190723 did not disrupt the yeast microtubules at either of the concentrations (Fig. S3 A iv and B iv).”

[Lines 294-300]

The authors mentioned much higher concentrations of drugs than normally used for mammalian cell cultures have to be used for fission yeast. Is there any criterion for this?

RESPONSE: In the discussion section, we had mentioned that “Much higher concentrations of drugs than normally used for mammalian cell cultures have to be used for fission yeast probably due to permeability issues because of the presence of a thick cell wall (Benko 2017 - DOI: 10.1186/s13578-016-0131-5).

This has now been mentioned in the results as well in the revised manuscript.

“Although we did not observe any growth defect in yeast cells at lower concentrations of the drugs, earlier studies have suggested that yeast cells possibly require higher concentrations of drugs than used for mammalian cells due to the presence of the cell wall, which is particularly thick in S. pombe (Benko et al. 2017; Pérez and Ribas 2004). We thus explored the possibility of cell toxicity to yeast cells at higher concentrations of the drugs.”

[Lines 234-239]

The following lines in the discussion have been modified in the revised manuscript to read as – “However, one of the major disadvantages of using fission yeast could be the need to use much higher concentrations of drugs than normally used for mammalian cell cultures to achieve an inhibitory effect. This could probably be due to the poor permeability of certain drugs in fission yeast because of its thick cell wall (Benko et al. 2017; Pérez and Ribas 2004). A similar effect of toxicity might arise at much lower concentrations in other eukaryotic cells, such as human cells.”

[Lines 498-503]

Minor comments: 1. There are two units used for drug concentration µM for Sanguinarine and Berberine and µg/ml for PC190723, I think they should be consistent.

We have now used µM for all drugs.

Check the units (µM and µg/ml) italic in text and figure legend.

We have now used µM for all drugs and corrected the italics. We apologise for the erroneous usage of italics in the text for µM.

Reviewer #3 (Significance (Required)):

The authors provided a proof-of-concept assay for studying bacterial cytoskeleton proteins in yeast cells. This idea will facilitate people to investigate the bacterial cytoskeleton proteins and also find compounds targeting them without affecting the yeast cells. This study will provide different perspectives to people who study cell biology and secondary metabolites discovery.

We hope that we have satisfactorily addressed all the concerns raised by the reviewers in the revised manuscript.

Thanking you,

With Regards

Dr. Ramanujam Srinivasan

Dr. Pananghat Gayathri

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Referee #2

Evidence, reproducibility and clarity

Dr. Srinivasin and colleagues previously developed a system where they expressed bacterial FtsZ in yeast and showed that it could assemble into polymers related to the Z rings. Here they develop this system further as a way to assay for drugs that may poison FtsZ, which would be candidates for new antibiotics. They test three drugs against three species of FtsZ. The results suggest that this system should be useful in screening new drugs that may target FtsZ. I would recommend publication after addressing a number of concerns and apparent contradictions.

Fig. 1 showing chemical formulas of the drugs, and Fig. 2 showing a schematic of the yeast expression system, are probably not needed.

The authors make a point that sanguinarine and berberine inhibit eukaryote cell morphology. In fact, what they show is that they affect yeast cell morphology. This may or may not extend to other eukaryotes. Also, other eukaryotic cells may be more sensitive to drugs than yeast. They should me more conservative in this claim that the system also screens for drugs effects on eukaryotes.

Fig. 3 has some new structural data that should be explored more quantitatively. My quick measurement gave 0.5 and 0.8 µm for the outside diameters of Ec and Sa rings. The spirals of Hp seem to be 0.8 µm outside diameter, similar to SA rings. These spirals may be related to those reported by Popp and by Andreu under certain buffer conditions. This should be explored and referenced.

But Fig. 4 presents a contradiction. Here the Hp control cells show long smooth polymers, not helical. This seems an important difference and needs to be addressed. Are the polymers sometimes straight and sometimes helical? After finishing the paper I see that in some experiments the HP is helical, and in others the polymers are straight and smooth. I think it would be important to determine what favors the two forms. If this remains a mystery, at least address it openly.

I am concerned that the quantitation of drug inhibition in Fig 4, 5 is flawed. Visually from 4A it looks like ~90-100% of control cells have polymers, and sang reduces polymers by 70% for Sa and Ec and 100% for Hp: this is based on the number of spots and filaments I see in Fig. 4 Aii. But the quantitation in D shows only 17-23% reduction for all three. These numbers were based on determining the fraction of cells that showed polymer (spots or lines) vs diffuse. It seems that cells are counted as containing polymer even if they had a great reduction in spots or lines, but still had a few. E.g., 4Aii Sa has 4 cells, two of them with no spots, one with only 2, and one with ~7, which totals ~1/3 the spots in control cells. Categorizing cells with only a couple of spots as polymerized, seems to be a poor way to quantitate. Would it not be better to count all spots in all cells, or measure the total length of line polymers, as a measure of inhibition.

Fig. 5 makes a convincing case that PC19 accelerates or enhances the polymerization of Sa and Hp. Fig. S2 shows that the structures of polymers are not changed when PC19 is added at 20 hrs, after polymers have already formed. It would have been nice to see for both 5A and S2A that the round spots had holes in the center, when imaged by SIM. Again the quantitation of cells as polymer vs diffuse seems ill suited, because it misses cells with a reduced number of spots.

Fig. 6 uses FRAP to show that PC reduces the dynamic exchange of Sa polymers by a factor of 3. It is remarkable to me that rapid exchange is not completely eliminated by PC. Regardless, it would be very important to reference the previous study of Adams..Errington 2011, where they showed the same thing for Foci in Bacillus. PC19 reduced the exchange from 3 to 10 s, but the foci were still very dynamic.

The analysis of the salt bridge as opposed to a single Arg or His being the cause of resistance to PC19 is an interesting addition to the study. In Fig. 8D some numbers do not agree between the caption and figure (R309/7; S226/7). The whole figure should be carefully checked.

I am not familiar with the Gram -ve and Gram +ve nomenclature. Why not simply gram- and gram+?

The Discussion is quite long largely because it repeats items from Results and Introduction. It is also redundant to hype the value of this system in both Introduction and Discussion; The Introduction should be sufficient. The Discussion should be pared down by eliminating repetition and focusing on relating results to previous literature, in particular items that have not been referenced previously in the paper. Also, I think we don't need the final "In summary" paragraph. That is already nicely presented in the Abstract.

The authors should probably provide references to other studies that have used yeast expression to study assembly of FtsZ. I am thinking in particular of papers from the Osteryoung lab looking at chloroplast FtsZ.

NO PAGE NUMBERS. Authors should be penalized a week delay for submitting a mss without page numbers.

Significance

This work should be of interest to the broad field of research on FtsZ. The authors present it as a new platform for assaying drugs targeting FtsZ, and researchers in this area will certainly be interested. It will also be of broader interest for the novel assay of assembly and exchange dynamics and how they may be modulated by small molecules.

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Reply to the reviewers

Manuscript number: RC-2022-01680

Corresponding author(s): Woo Jae, Kim

1. General Statements The goal of this study is to provide the groundwork for future studies of genetically controlled neuronal regulation of ‘interval timing’ through the provision of a behavioral paradigm. Interval timing, or the sense of time in the seconds to hours range, is important in foraging, decision making, and learning in humans via activation of cortico-striatal circuits. Interval timing requires completely distinct brain processes from millisecond or circadian timing. In summary, interval timing allows us to subjectively sense the passage of physical time, allowing us to integrate action sequences, thoughts, and behavior, detect developing trends, and predict future consequences.

Many researchers have tried to figure out how animals, including humans, can estimate time intervals with such precision. However, most investigations have been conducted in the realm of psychology rather than biology thus far. Because the study of interval timing was limited in its ability to intervene in the human brain, many psychologists concentrated on developing convincing theoretical models to explain the known occurrence of interval timing.

To overcome the limits of studying interval timing in terms of genetic control, we have reported that the time investment strategy for mating in Drosophila males can be a suitable behavioral platform to genetically dissect the principle of brain circuit mechanism for interval timing. For example, we previously reported that males prolong their mating when they have previously been exposed to rivals (Kim, Jan & Jan, "Contribution of visual and circadian neural circuits to memory for prolonged mating induced by rivals" Nature Neuroscience, 2012), and this behavior is regulated by visual stimuli, clock genes, and neuropeptide signaling in a subset of neurons (Kim, Jan & Jan, “A PDF/NPF Neuropeptide Signaling Circuitry of Male Drosophila melanogaster Controls Rival-Induced Prolonged Mating” Neuron, 2013).

Throughout their lives, all animals must make decisions in order to optimize their utility function. Male reproductive success is determined by how many sperms successfully fertilize an egg with a restricted number of investment resources. To optimize male reproductive fitness, a time investment strategy has been devised. As a consequence, we believe that the flexible responses of mating duration to different environmental contexts in Drosophila males might be an excellent model to investigate neural circuits for interval timing.

One of the most well-known features of human interval timing is the association of different sensory inputs with perception of time intervals, which influences our estimate of time intervals. Therefore, the first step toward comprehending the neural regulation of interval timing is to dissect the role that numerous sensory inputs play in determining the time duration. In this article, we discuss a different time-investment strategy adopted by males, called "Shorter-Mating-Duration" (SMD). According to our findings, male Drosophila with more sexual experience had shorter mating duration. During our investigation into the sensory inputs for SMD behavior, we found a small number of cells that express sugar receptors and pheromone receptors (ppk25 and ppk29) and thus transmit the multisensory information from females in order to generate memories of sexual experiences, which will determine the final decision of mating duration.

Our discovery of sensory integration mechanisms associated with complex behavioral trait in male Drosophila at the brain circuit and genetic network levels will be a huge step forward in our knowledge of interval timing behavior.

Description of the planned revisions

REVIEWER #1

1. • Overall I think this would be difficult for a general audience as the rationale and explanation of experiments needs to be clearer. * Answer: During the revision process, we will make our text more legible for wide audiences.

REVIEWER #2

1. • 'The knockdown of LUSH, an odorant-binding protein' Lush is expressed in trichoid sensilla in olfactory organs , from the beginning, they exclude the role of olfaction and later one they said 'suggesting that the expression of the pheromone sensing proteins LUSH and Snmp1 in Gr5a-positive gustatory neurons is critical for generating SMD behavior.' ? Therefore, I recommend If available, please provide a reference for the statement in the Methods section that the Orco1 line was "validated via electrophysiology", or include the electrophysiology data itself in this manuscript as supplementary figure. Ideally, positive behavioral controls for this line would also be included in the manuscript. * Answer: We value the reviewer's concern. LUSH has been discovered as an odorant-binding protein; nevertheless, current research suggests that LUSH may be involved in the sensing of additional pheromones to cVA, implying the presence of a lush-independent cVA detection mechanism [1]. Billeter et al. demonstrated in their paper that LUSH detects a female stimulatory chemical and modifies male mating latency (Fig. 2 of Billeter at al.). As Billeter et al. stated, our present understanding of pheromonal recognition in Drosophila is insufficient, and we concur. As a result, we attempted to validate the expression of Snmp1 in the male leg by experiments (Fig. 7I-J) performing sncRNA seq analysis on the Fly SCope dataset, as shown in Fig. 12. As demonstrated in Fig.12, Snmp1 and LUSH is higly expressed fly leg and wing system. Future study will look at the roles of Snmp1 and LUSH in female pheromone sensing, as well as PPK receptors.

Following the reviewer's advice, we will repeat the electrophysiologically validated Orco2 mutant phenotype with proper control and attach it when we submit the complete revision to the journal.

• What is this (GustDx6)? I suggest using Poxn mutant line. *

Answer: We value the reviewer's recommendation. We believe we have previously demonstrated that the Gr5a-mediated gustatory pathway is essential for the generation of sensory input for SMD behavior, but we will test the Poxn mutant and Poxn-RNAi to replace the GustDx6 mutant result.

Description of the revisions that have already been incorporated in the transferred manuscript

REVIEWER #1

2. My copy of this ms does not have page numbers or line numbers, this makes it extremely difficult to identify where I am making queries/ suggestions. I don't know whether this is a decision of the journal or authors, but please change this in the future.* Answer: We put page numbers and line numbers.

3. A general point, there is simply too much in this ms. It covers too much ground and so doesn't give proper descriptions, discuss the consequences of the data fully or integrate properly with existing literature. Quantity does not equal impact. *

Answer: We appreciate the reviewer's insight. We have previously separated this document from our original preprint [2] in response to a prior reviewer's advice; we believe we have included too much data, which may confuse readers. As a result, we will delete all of the mechanosensory/thermosensory receptor screening data from our present paper and write a second manuscript on sensory integration for the production of SMD behavior. We also removed the most of sncRNA seq data analysis except Fig.12 which confirms our finding in a single diagram.

• Results paragraph 1 says that white mutant background had no effect "unlike that of LMD behavior as reported previously", ignoring that there has been a contrary report that extension of mating duration after exposure to a rival does not involve visual cues and so is not affected by the white mutation (Bretman et al 2011 Curr Biol). *

Answer: We recognize that there is a conflicting report concerning white mutation on LMD behavior, however because we are now reporting SMD rather than LMD behavior, we deleted the statement comparing white mutant results to earlier reports, as shown below;

“thus suggesting that the effect of the white mutant genetic background was not evident.” (line 97)

• A general point in the methodology, it's not very helpful just to say "as in a previous study" without giving at least a brief idea of what that was (e.g. the explanation of egg counting procedures).

A "sperm depletion" assay is described in the results that I cannot find any methodology for. *

Answer: We thank the reviewer for allowing us to clarify our lacking methodologies for a better comprehension of our manuscript.

We included the egg counting procedure to the EXPERIMENTAL PROCEDURES section to further illustrate our approach of egg laying assay as below;

“In short, wild type females mated with naïve or experienced males were transferred to a fresh new vial and allowed to lay eggs for 24 hr at 25°C. After 24 hr of egg laying, number of eggs were counted under the stereomicroscope. After we count the number of eggs, we kept vials in 25°C incubator and counted the total number of progenies ecolsed from them.” (line 956-960)

We included “Sperm Depletion from Males” section in EXPERIMENTAL PROCEDURES as below;

“To deplete sperm from males, 40 virgin Defexel6234 females which lacks SPR and shows multiple mating with males (Yang 2009) were placed in a vial containing four CS males for indicated time (2 h, 4 h, 8 h, and 24 h).” (line 880)

• Was the "excessive mating" with SPR females actually observed, or inferred from previous work? Needs to be clear. In what way do virgins expressing fruitless behave like mated females? It is so unclear how all the evidence in this paragraph leads to the conclusion that both cues from females and successful copulation. Especially as in the next paragraph experience with feminized females (with which the focal males cannot copulate) elicits the response.

It might be helpful to combine the results into a table, so it is easy to see under which conditions males reduce mating duration. *

Answer: We modified the sentence describing SPR mutant female experiment and added references as below;

“Sexual experiences with sex peptide receptor (SPR) mutant females which exhibit a delayed post-mating response and multiple mating with males [3] had no additional effect on SMD (Fig. 2I).” (line 135)

We clarify in which extent, fru>UAS-mSP virgin females behave like mated females as below;

“Virgin females behave like mated females by expressing a membrane-bound version of male sex-peptide in fruitless-positive neurons, hence rejecting the male's copulation attempt.” (line 136)

In the instance of feminized males, we assume that these feminine males can give adequate signals for inducing SMD and eliminated the term "successful copulation" since we are unsure if males can copulate these feminized males or not, despite the fact that males can mount and mate with them (Fig. 2O-P).

Tables S1 and S2 describe the conditions, genotypes, and descriptions of an experiments illustrated in Fig. 2. We believe that these tables may assist general audiences in comprehending our experimental design.

• Why are no statistics reported in the results? Identifying sig diffs on figures is not sufficient. I'm very sceptical that "mating duration of males showed normal distribution" for all comparisons, but then it's also difficult to identify which were analysed in this way (if statistics were properly reported this would not be an issue). *

Answer: We described our statistical analysis with mating duration previously [4–7] and followed the statistical analysis of copulation duration assay reported by Crickmore et al., published in CELL (2013) and NEURON (2020) [8,9]. To further validate our statistical analysis, we added estimation statistics which focuses on the effect size of one's experiment/intervention, as opposed to significance testing [10]. We already described our statistical analysis in EXPERIMENTAL PROCEDURES section in details. We also described our statistical analysis for mating duration will be same in all other figures in the Fig.1 legend.

We appreciate the reviewer's recommendation that the normal distribution of our mating duration data be validated. As a consequence, we performed the normailty test with Graphpad prism and added the histogram and QQ plot results to Fig. S1M and N. Table S3 also contains the results of the normality and lognormality tests.

• Gr5a/ Gr66a mediate acceptance/ avoidance of what? Why would you hypothesise these in particular to be involved? *

Answer: We accidentally left out the citation for that phrase and updated it with Wang et al.'s CELL (2004) paper. Wang et al. wrote in their article about taste representations in the Drosophila brain, “Our behavioral studies reveal that Gr5a cells recognize sugars and mediate acceptance/attractive behaviors whereas Gr66a cells recognize bitter compounds and mediate avoidance…. This suggests that Gr5a cells may be “acceptance” cells rather than “sweet” cells…. Our expression and behavioral studies reveal that Gr5a marks cells that recognize sugars and mediate taste acceptance, whereas Gr66a marks cells that recognize bitter compounds and mediate avoidance.” [11]

As a result, we hypothesize that Gr5a and Gr66a-positive cells influence acceptance or avoidance of "taste." We also changed certain sentences to make them clearer, as seen below;

“Of the various gustatory receptors, Gr5a marks cells that recognize sugars and mediate taste acceptance, whereas Gr66a marks cells that recognizes bitter compounds and mediates avoidance.” (line 173)

• As Orco was not found to affect the behaviour, why test Or67d? *

Answer: We appreciate the reviewer bringing this to our attention. We omitted the Or67d result from the present manuscript to simplify it and make it easier for readers to grasp.

• "Mate guarding" suddenly appears in the modelling section. Can a difference of a couple of minutes in a mating duration of 15-20min really be considered mate guarding? A similar variation in response to rival males is not considered mate guarding, but is linked to adjustments in ejaculate expenditure (admittedly not in a very straight forward way). Surely in a system like this the benefits arise more from how many females the male can mate with in a given time? How does this model relate to any of the previous models of mate guarding?

In this section the work of Linklater et al 2007 is important, they showed progeny declined over successive matings, and related this to exhaustion of Acps rather than sperm. I would urge the authors to consider that what they observe does not necessarily have an adaptive explanation. *

Answer: We have defined “mate guarding” in the text now. The costs and benefits of mate guarding have been extensively studied in insects and demonstrated to shape the optimal mating duration of males. In our experiment, we cannot specify whether the shortened mating duration was caused by the adjustments in ejaculate expenditure or a shorted stay after the ejaculation. Instead, our model has a general assumption that the costs of mate guarding increase linearly at the same rate in both pre- and post-ejaculation periods, which is highlighted in the model text.

There exist many models for the optimal mating duration (earlier models include Grafen and Ridley, 1983. A model of mate guarding. J. Theor. Biol. 102: 549 – 567 [12]). While our model was not built upon a novel theoretical approach (it was built based on the classical Charnov’s marginal value theorem equation), our model was developed specifically for generating testable predictions for the observed SMD behaviors.

We have rephrased the text as follow;

“This model assumes that (i) the shortened (or prolonged) mating duration is controlled by males and shaped by a trade-off between the benefit of mate guarding (remaining with the female both before and after the sperm ejaculation) and opportunistic costs (e.g. searching for another mate).” (line 970)”

• I can't find a data accessibility statement. *

Answer: We added it in the manuscript.

• That said, a current grand challenge in understanding behaviour is discovering the mechanisms that enable individuals to respond plastically to changing environments. This speaks directly to that challenge. However, this behavioural observation is not novel, as claimed. Generally the idea of refractoriness is widely known, and specifically the reduction in mating duration over successive matings in D. melanogaster was shown by Linklater et al 2007 Evolution. Moreover, the time between exposure to females has been shown to be important. Linklater et al 2007 gave males mating attempts in quick succession and observed the decrease in mating duration, whereas given recovery time of 3 days, males either mate equally as long, or even longer across their life course (Bretman et al 2011 Proc B, Bretman et al 2013 Evolution). These papers should be discussed, and more broadly the work understood in the light of previous knowledge. The behaviour does not need to be novel for this manuscript to make a significant contribution to the field. *

Answer: We believe the reviewer highlighted relevant past research that examined the influence of female experiences on mating duration. We agree with the reviewer that SMD behavior does not have to be original in order to contribute significantly to the field. As a result, we examined past reports and updated the introduction as follows;

“It has been reported that previous sexual experience with females influences the mating duration of male D. melanogaster [15,16,34]; however, the neural circuits and physiology underlying this behavior have not been deeply investigated. Here, we report the sensory integration mechanisms by which sexually experienced males exhibit plastic behavior by limiting their investment in copulation time; we refer to this behavior as "shorter mating duration (SMD)."” (line 85)

• Both in the introduction and discussion the extended mating duration in response to rivals is raised. A great deal of work has been done on this plasticity and yet the way this is written implies just two papers from these authors (whilst referencing others elsewhere). *

Answer: We agree with the reviewer. In the introductory and discussion sections, we cited as many key publications explaining the plastic responses of male mating duration as we could.

__REVIEWER #2

__

1. • Summary: The submitted manuscript reports that Drosophila melanogaster males use information derived from their previous sexual experiences from multiple sensory inputs to optimize their investment in mating. They refer to this plasticity as 'shorter-mating duration (SMD)'. SMD requires sexually dimorphic taste neurons. They identified several neurons in the male foreleg and midleg that express specific sugar, pheromone and mechanosensory receptors. Unfortunately, several aspects of the study design and methods used are inappropriate. Although the statistical approaches used are appropriate, the results are questionable. The discussion and conclusions are therefore too speculative in my view and overstretch the implications of the results as presented. Below I explain each one of these concerns about the study design, methods and results in detail as follows.* Answer: We appreciate the reviewer's assessment, especially the statement that our statistical approaches were appropriate. We will revise our manuscript in response to the reviewer's suggestions.

2. The conclusions (as the authors point out) hinge on small (often extremely small) effect sizes. This is not an insurmountable problem, so long as the assays are robust across trials. Unfortunately, they are not-the variation in the baseline for control replicates is often as large as, or larger than, the effects from which the conclusions are derived. Given the extreme experimental challenges of small effect size combined with large intertrial variability, it is notable that the authors do not report any likely false negative or false positive data, as would be frequently expected under these conditions. One explanation for the reproducibility of statistical effect seen across many experiments despite these experimental hurdles is manipulation of sample size. The authors acknowledge the extreme variability in sample size offer seemingly harmless explanations, but a closer look shows how problematic this practice is. For example, see Figure 1 (I, J, L) there is a big different between naive and experience males? *

Answer: We value the reviewer's feedback. Several research have been conducted to investigate the mating duration of male fruit fly. For example, our lab [2,13–15] and others [13–30] have regularly reported that previous rival exposure increases male fruit fly mating duration. Bretman A et al. utilized 49-59 males in their studies to compare the variations in mating duration between circumstances. Crickmore et al. also reported the effect of mating duration differences caused by genetic or experimental modification [8]. They utilized 10-18 male flies in their study to compare the variations in mating duration across circumstances, as shown in Figs. 1G (n=15-18) and 2A (n=10-27). All of these findings indicate that our mating duration sample size is sufficient to examine the effect size variations between the naive and experienced conditions. To confirm our statistical analysis further, we incorporated estimate statistics, which focus on the effect size of one's experiment/intervention rather than significance tests [10]. We have already detailed our statistical analyses under the EXPERIMENTAL PROCEDURES section. We conducted hundreds of mating duration assays using this configuration and confirmed that all of our results are reproducible in a blind test. As a result, we believe our mating duration assay has been validated by other groups' findings, several analytic tools, and numerous blind tests conducted by us. We appreciate the reviewers' concerns, but our data meets the reproducibility requirements.

• I am not sure if you keep using the same control with different experiments (that is okay if those exp is done in the same time) as in figure 1 B, I,J,K,L.But I don't think you did Fig 1B in the same time with Fig 1I, J, K,L. *

Answer: We appreciate the reviewer's feedback. Yes, all of our tests comparing the differences in mating duration between naive and experienced conditions were conducted under the same conditions and at the same time. We replaced Fig.1B with new data (n=49-51) obtained lately in a new lab in China. As previously stated, SMD behavior could be reproduced by the same Canton S genotype in different locations by different experimenters.

• It will be clear if you mention in the text how much reduction in percent happened in copulation duration when the males had previous sexual experience? *

Answer: We appreciate the reviewer’s suggestion and added in the manuscript as follow;

“We found that the mating duration of various wild-type and w1118 naïve males are significantly longer (wild type 15.7~15.8%, w1118 12.4%) than that of sexually experienced males (Fig. 1B-D, Fig. S1A)” (line 99)

• 'Drosophila simulans, the sibling species of D. melanogaster also exhibits SMD, thus suggesting that SMD is conserved between close species of D. melanogaster (Fig. S1B).'. If you want come with this conclusion, you need to test D. erecta, D. sechelia and D. yakuba. *

Answer: We appreciate the reviewer's feedback. We removed the D. simulans data because it is not required for the conclusion of this manuscript. In future research, we will look on the conservation of SMD behavior between species.

• The authors mention that Gr66a is salt. This is not 100% correct. GR66a is expressed in many bitter sensing neurons and is required for the physiological and behavioral responses to many bitter compounds. check this reference DOI:https://doi.org/10.1016/j.cub.2019.11.005. *

Answer: We made the following changes and cited the article reviewer's suggestion.

“Of the various gustatory receptors, Gr5a marks cells that recognize sugars and mediate taste acceptance, whereas Gr66a marks cells that recognizes bitter compounds and mediates avoidance (Wang et al, 2004; Dweck & Carlson, 2020).” (line 180)

• Drosophila melanogaster mating duration is between 21- 23 mins. I never saw copulation duration in normal condition (control) 10-15 mins as in figure fig 2E, Fig 7 C,E,F, Fig 8 E and fig 12 G . To the best of my knowledge, of all of the papers on copulation duration, the only one that ascribes a shortened duration to manipulations of the female is Rideout...Goodwin Nature Neuroscience 2010, who argue that this shortening results from markedly increased female activity/agitation during mating, leading the male to terminate early. *

Answer: We appreciate the reviewer's feedback. Copulation duration in Drosophila melanogaster male is extremely variable and has been reported to be approximately 20 minutes. However, as other groups documented, male copulation duration can range from 10-15 minutes depending on sperm completion (Fig. 1a-c of Bretman A et al.) [30] and genetic background (Fig. 1C, Fig. 2E, Fig. 5D, and Fig. 7A and E of Crickmore et al) [8]. And, as previously stated, males dominate copulation duration [8,30], not females, and we always utilized the same genotype of females for mating duration experiment. As a result, we believe that these rather short mating duration outcomes are the product of a distinct genetic background. Because we employed the same genotype of males while altering the female experience condition, we believe our mating duration results are all equivalent and comparable.

• In some experiments, the authors test very few number of replicates which is not convinced me to their conclusion as example Fig 2F and Fig 12 E. Why you test 100, 103 replicates in this exp fig 10 F? How you compare 47 replicates against 9 replicates in fig S10 I? *

Answer: We appreciate the reviewer's input. As we previously stated in response to Reviewer Question 2, the n number of males exhibited in Figs. 2F and 12E is statistically significant. To corroborate findings with replication, we examined 100, 103 duplicates of Fig. 10F, which represents pyx-RNAi screening results. The results of Fig. S10I are screening data, and we cannot rule out the possibility that TrpA1 knockdown in Gr5a neurons affects the mating success of sexually experienced males. We only placed it there because it was screening results and the differences between naive and experienced conditions were substantial despite the small sample size. However, we deleted Fig. 10F and Fig. S10I data from the current paper in response to Reviewer #1's advice, thus it will not be an issue for the manuscript's conclusion.

• 'Next, to decipher whether DEG/NaC channel-expressing pheromone sensing neurons require the function of OBP, we expressed lush-RNAi using ppk23-, ppk25- and ppk29-GAL4 drivers to knockdown LUSH in each channel-expressing neuron. The knockdown of LUSH in ppk25- and ppk29-GAL4 labeled cells, but not in ppk23-GAL4 labeled cells, led to a disturbance in SMD behavior, thus suggesting that LUSH functions in ppk25- and ppk29-positive neurons to detect pheromones and elicit SMD behavior (Fig. 9G-I). The knockdown of SNMP1 in ppk29-GAL4- labeled neurons also inhibited SMD behavior (Fig. 9J), thus suggesting that SNMP1 also functions in ppk29-positive neurons to induce SMD behavior.' What about ppk25? **

*

Answer: As indicated by the reviewer, we included ppk25-GAL4/snmp1-RNAi data in Fig. S9I, indicating that snmp1 expression in ppk25-positive cells is similarly implicated in SMD behavior.

• There are no page or line numbers throughout the ms! *

Answer: We included page and line numbers.

• The use of subheadings in the results section makes reading much easier.*

Answer: We added subheadings in the results section.

• 'We found that the mating duration of various wild-type and w 1118 naïve males are significantly longer than that of sexually experienced males (Fig. 1B-D, Fig. S1A)' . I think you should change various wild type to CS and WT Berlin as in legend and figure 1B,C .*

Answer: The revised sentence is as follows:

“We found that the mating duration of Canton S, WT-Berlin, Oregon-R, and w1118 naïve males are significantly longer (wild type 15.7~15.8%, w1118 12.4%) than that of sexually experienced males (Fig. 1B-D, Fig. S1A)” (line 102)

• Suggested exp , Fig S1E-H , they might test 2,6, 12 hours males separation from females to test exactly when this behavior change over time. *

Answer: We value the reviewer's recommendation. As seen in Fig. S4B of Kim et al., we have previously conducted experiments for examining the memory circuit of SMD [6]. Briefly, the male with a shorter mating duration recovers completely after 12 to 24 hours of isolation from females. As we are currently preparing the memory section of the SMD study, this information will be included in a future manuscript.

• General comment in figures, you could remove the common y axis as example in figure 1 B,C,D , difference between means and mating duration. *

Answer: We welcome the reviewer's idea, however in this situation we believe that the y axis of each data set is independent from one another and will thus retain the originals. We feel this would be more useful for the general audiences.

• You might move the number of replicates to the legend. *

Answer: We appreciate the reviewer's idea, however we feel that adding more information to the graphic will aid the general audience in comprehending our statistics.

• Latin name should be italic as example Drosophila simulans.*

Answer: We fixed it.

Description of analyses that authors prefer not to carry out

N/A

References

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14. Kim WJ, Jan LY, Jan YN. Contribution of visual and circadian neural circuits to memory for prolonged mating induced by rivals. Nat Neurosci. 2012;15: 876–883. doi:10.1038/nn.3104
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30. Bretman A, Fricke C, Chapman T. Plastic responses of male Drosophila melanogaster to the level of sperm competition increase male reproductive fitness. Proc Royal Soc B Biological Sci. 2009;276: 1705–1711. doi:10.1098/rspb.2008.1878

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Reply to the reviewers

Reviewer #1:

Minor edits

1. Line 91. Is a bit misleading to say "many other vibrios" possess T3SS. This conveys that this is perhaps the majority, but T3SS in vibrios is at best 50/50. I think best just to delete this sentence.

We deleted this comment, as suggested.

1. Revised to "Thus, in this study, we set out to..." Since the entire paragraph starts with "recent study" I missed that this was summary of new data rather than preview of new results.

The sentence was revised as suggested.

1. Line 503. Correct "xxx-584" or more detail on what this means.

We Thank the reviewer for pointing out this typo._ This refers to the deletion made in tie1, in the region corresponding to nucleotides 485-584 of this gene. The text was corrected accordingly.

1. Line 603. Salmonella should be italicized.

Corrected.

1. The labelling of the figures is pretty complicated with the long genetic designations. Is it reasonable to for example name the ∆vprh/∆hns1 strain with an abbreviation (such as ∆VH)? Or instead create a strain name, common used approaches would be HC## (for Hadar Cohen) or TAU# for Tel Aviv University. If you go this route, be sure to update the strain list. The current method can be followed, the figures are just complicated.

We thank the reviewer for raising this concern. We acknowledge the difficulty in following the many different strains and mutations. Nevertheless, after considering the proposed modifications to the strain names, we believe that they will not add much clarity, and may even cause some confusion. Therefore, we respectfully decided to keep the current nomenclature in place.

Reviewer #2:

Minor edits

1. The authors used a hyperactive T6SS (HNS mutant) to investigate its toxicity. Would the authors be able to use a wild type strain to reproduce the function of T6SS?

We have yet to reveal the external cues that lead to full activation of T6SS3 in vitro. Therefore, in the current study we used genetic tools, such as hns deletion or Ats3 over-expression, to monitor the effect of this system on immune cells. We will dissect the activating conditions in future studies, but we believe that the use of genetic tools should not affect the validity of the results in the current study, nor their timely publication.

1. The authors showed that Tie1 and Tie2 are secreted by T6SS3. It is important to show if they are actually delivered into the host cells during infection. Otherwise it is hard to conclude that they are truly effectors. The primary concern is the lack of in vivo studies to show that Tie1 and Tie2 are actually effectors that play a role in activation of NLRP3 inflammasome._

We present 3 pieces of evidence that, when taken together, support the conclusion that Tie1 and Tie2 are T6SS3 effectors: 1) the proteins are secreted in a T6SS3-dependent manner; 2) their deletion does not hamper overall T6SS3 activity; and 3) their deletion causes the same loss of NLRP3-mediated inflammasome activation and pyroptosis as does inactivation of T6SS3 by deletion of its structural component, tssL3. Although we agree with the reviewer that directly showing delivery of Tie1 and Tie2 into host cells will further strengthen our conclusion, such experiments are quite challenging and difficult to interpret, especially with T6SS effectors that can use diverse mechanisms for secretion through the system. This point was also noted by reviewer #3: “…I believe they were suggesting to demonstrate secretion in host cells. Although this would be nice, it is non-standard and technically not feasible. These types of experiments require genetically fusing the effector with either an enzymatic moiety (e.g. Beta lactamase) or fragment of split GFP. Although such approaches have been previously performed, they often result in either blocked or aberrant secretion due to the presence of the added fragment."

Regarding the reviewer’s comment on the lack of in vivo studies: we agree that these are extremely important, yet they are beyond the scope of the current work, as concurred by reviewers #1 and #3:

Reviewer#1 with regard to Reviewer#2: "I don't think mouse (or aquatic animal) studies are essential for this study. The work contributes nicely to our understanding molecular mechanisms of this T6SS system. As noted in my review, there are many additional lines of study that can be pursued from this work, including animal studies, but this should not preclude publication of this work that is itself an intact unit."

Reviewer#3 regarding reviewer #1's comment on Reviewer#2: "I don't believe that reviewer #2 was suggesting to perform mouse or aquatic animal studies by suggesting in vivo demonstration of secretion…”

Reviewer #3:

Major comments:

1. If the authors believe that GSDME partially compensates in the absence of GSDMD, have they infected a GSDME/GSDMD double knockouts to see if there is an additive effect?

Indeed, this is a very interesting and specific question for the cell death field. We do not currently possess such a GSDME/GSDMD double knockout mouse, and generating one will be a long endeavor. Since its absence does not diminish the importance or the conclusions of the current work, we think that it should not warrant a delay in publication. We do plan to address this question in future studies.

1. It is clear that Ats3 regulates T6SS3, but not the T6SS1; however, there no evidence suggesting that Atg3 does not regulate other gene clusters. For example, have the authors performed RNA seq to compare the transcriptomes of WT and an Ats3 mutant? If not, the authors should refrain using the words "specific activation".

We thank the reviewer for this important note. Indeed, we lack additional data indicating that Ats3’s effect is indeed restricted only to T6SS3. Therefore, we modified the text accordingly and removed mentions of specific T6SS3 activation.

1. In figure 6B, it's unclear why the bacteria infecting cytochalasin D-treated cells grow more than the T6SS3 mutants in the absence of cytochalasin D.

The difference probably stems from the fact that phagocytosis, the major mechanisms by which BMDMs kill bacteria, is hampered in the presence of cytochalasin D, thus allowing bacteria to grow more than when the BMDMs phagocytose them. The results show that in the absence of cytochalasin D, an active T6SS3 counteracts the killing effect by BMDMs with functional phagocytosis.

Minor comments:

1. Figure 1A and other secretion assays: The Western blots include loading control (LC) blots. These are non-standard, non-informative, and not required with the inclusion of the western blots on the "cells" fraction. I would suggest removing these as they may confuse the reader.

We respectfully disagree. Loading controls are standard in bacterial secretion assays, and they are important since they confirm comparable loading and allow proper analysis of the results, especially since we aim to determine whether certain mutations affect the expression of T6SS components. Notably, some groups choose to blot for a cytoplasmic protein (e.g., RpoB in Allsop et al., PNAS, 2017; Liang et al., PLoS Pathogens, 2021) instead of showing overall loaded proteins, as shown in our figures.

1. Line 503: "xxx" should reflect the actual nucleotide nubmers_

We thank the reviewer for pointing out this typo._ This refers to the deletion made in tie1, in the region corresponding to nucleotides 485-584 of this gene. The text was corrected accordingly.

1. Since V. proteolyticus is an aquatic pathogen, have the authors tried to infect corals, fish, and crustaceans (or derived cells) with WT and effector mutants?

This is an interesting point, and indeed we are setting up such systems and we plan to perform such experiments in the future as part of follow up projects. However, these in vivo studies are beyond the scope of the current manuscript, as also noted by the reviewer in the cross-consultation comments: “…my previous comment on infecting aquatic animals or cells derived from them is non-standard and not necessary…”

1. Are the targeted host proteins in this study (performed with murine BMDM) conserved in the natural hosts for V. proteolyticus?

We hypothesize that the conservation is not in the pathway components that are activated upon infection, but rather in the ability of the host cell to sense danger (i.e., to sense the effect of T6SS3 effectors on the host cell or one of its components), which is the role of the NLRP3 inflammasome in mammalian cells. It is well documented that major differences in immune mechanisms exist between mammals and the potential natural marine hosts of V. proteolyticus (e.g., corals, arthropods, and fish); therefore, the conservation at the protein level is low. Nevertheless, basic signaling pathways, such as programed cell death, are conserved between the different phyla. For example, a caspase-1 homolog which was found in arthropods (Chu, B. et al. PLoS One (2014). doi:10.1371/journal.pone.0085343) probably induces an apoptotic-like cell death mechanism, similar to apoptosis in C. elegans. We now provide further discussion on this point in the text (lines 648-659).

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Referee #1

Evidence, reproducibility and clarity

This paper by Cohen et al described discovery of the function of novel genes in the T6SS operon of Vibrio proteolyticus, a Vibrio isolated from corals. V. proteolyticus also impacts other sea animals. The T6SS3 in particular is found to kill eukarytoic phagocytic cells following engulfment of bacteria into the phagocyte. This strategy of killing phagocytic cells following entry has been shown for other Vibrios. The net goal is protection of the population by the bystander effector. The study first shows that deletion of H-NS (a global negative regulator) stimulates T6SS facilitating ease of work by pushing the system to great cell killing. This allowed them to probe the mechanism of cell death and reveal it as NLRP3 dependent, capase 1 dependent pyroptosis via pore formation by Gasdermin D. Activation of the inflammasome is also linked to cleavage and release of IL-1beta. When GSDMD is absent, there was a slower cell killing by GSDME via capsase 3 activation. The stimulation of this system is additive by two newly recognized T6SS effectors Tie1 and Tie2.

The study is complete, the experiments are well conducted and well controlled. The experiments show reproducibility. The manuscript text is clear, Overall. I suggest no changes in the results or experiments and suggest only a few minor edits of the text.

Minor edits

Line 91. Is a bit misleading to say "many other vibrios" possess T3SS. This conveys that this is perhaps the majority, but T3SS in vibrios is at best 50/50. I think best just to delete this sentence.

Line 102. Revised to "Thus, in this study, we set out to..." Since the entire paragraph starts with "recent study" I missed that this was summary of new data rather than preview of new results.

Line 503. Correct "xxx-584" or more detail on what this means.

Line 603. Salmonella should be italicized.

Figures. The labelling of the figures is pretty complicated with the long genetic designations. Is it reasonable to for example name the ∆vprh/∆hns1 strain with an abbreviation (such as ∆VH)? Or instead create a strain name, common used approaches would be HC## (for Hadar Cohen) or TAU# for Tel Aviv University. If you go this route, be sure to update the strain list. The current method can be followed, the figures are just complicated.

Referees cross-commenting

With regard to Reviewer#2, I don't think mouse (or aquatic animal) studies are essential for this study. The work contributes nicely to our understanding molecular mechanisms of this T6SS system. As noted in my review, there are many additional lines of study that can be pursued from this work, including animal studies, but this should not preclude publication of this work that is itself an intact unit.

Significance

The work is significant in that it links T6SS to a eukaryotic killing system and discovers novel details regarding the mechanisms of death, that may impact our knowledge of other Vibrio T6SS (including V. cholerae) that also target eukaryotic cell actin. There are remaining questions that could be probed, but these are in my opinion major studies that would easily themselves comprise new papers if done properly and thus are not essential for this paper. These include the struture and biochemical activity of Tie1 and Tie2 and the mechanism of caspase-8 independent activation of caspase-3 to then cleave GSDME. Why NLRP3 is required for capase 3 activation is also an open question. I look forward to following this work for some time to come. The authors have revealed very interesting effectors and interesting cell biological process that will merit multiple years and multiple manuscripts to unravel. This work will be of interest to the community interested in bacterial toxin systems (microbial pathogenesis), the bacterial effector mechanism field (biochemistry and cell biology), and the inflammasome activation field (immune systems). The work will be of interest (with essentially no modification) directed at these fields of interest.

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Reply to the reviewers

Reviewer #1:

Major comments:

In general, the data support the conclusions. I cannot comment on the atomistic simulation experiment as it is outside of my expertise. I had some difficulties interpreting Figure 2 as the contrast in the colour panels made it difficult to assess the different staining patterns. I would recommend changing the blue to cyan for easier visibility. While I agree that there are some differences between Fig 2F and Fig 2G it is not simple for the non-expert to distinguish the gonadal mesoderm from the somatic mesoderm. I think the enlarged panels could do with also showing the overlap in staining, or at least a tracing of the different cell populations so that the gonadal mesoderm can be clearly defined. Please also add some scale bars to the figure. Figure 3 demonstrates clear differences in gonad morphology between male and female mutants but the contrast in the colour panels A-G could also be improved. Panels H-J are very clear.

Response: As suggested by Referees 1 and 3 we have modified the colour channels in all figures. We have also enlarged the figures taking away the uninformative region and focused around the enlarged gonads and added scale bars. For Fig 2F-G, we have added a close up of the region of interest both in colour and in black and white. These changes have increased the contrast and facilitate the data interpretation to non-expert readers.

The rescue experiment in Figure 4 is clearly presented but could the DLC3 mutants in the graph (panel b) please be named similarly to the schematic proteins shown in panel a.

Response: We have changed the names to maintain nomenclature uniformity.

I found the difference between the RhoGAP domain mutants and the StART domain mutants of Cv-c to be clearly defined, and correlate with DLC3 function. This is a very interesting result that indicates multiple molecular functions for the Cv-c /DLC family.

Response: The methods are well described, statistics adequate and the data well described._

Minor Comments:

My only suggestion for the text is to provide a more through description of the StART domain in the introduction.

Response: We have included the following paragraph in the introduction describing the StART domain:

“This family of proteins share different domains: besides the Rho GTPase Activating Protein domain (GAP), they present a protein-protein interacting Sterile Alpha Motif (SAM) at the N terminal end and a Steroidogenic Acute Regulatory protein (StAR)-related lipid transfer (StART) domain at the C terminal. StART domains have been shown in other proteins to be involved in lipid interaction, protein localization and function.”

Reviewer #2:

My only issue with the present study is to how well the present experimental findings in Drosophila translate to humans. As far as I can tell the present studies show that inactivating mutations in Cv-c in Drosophila result in failure of germ cell enclosure by somatic cells into the testis, resulting in sterility. In humans, and in experimental mouse transgenic lines, it has been well established that absence of germ cells does not of itself lead to failure of testis differentiation and onward development, nor does it lead automatically to sex reversal or impairment of masculinization. For the latter to occur, there must be impairment/failure of fetal Leydig cell function such that insufficient androgen is produced to effect genital/bodywide masculinization. Obviously, this will happen if no testis forms as appears to be the case in the new human DLC3 mutant reported in the present manuscript (although detail on this is unfortunately lacking). This appears to be different to the previous published DLC3/STARD8 mutant sisters, in whom the phenotype appears to reflect failure of steroidogenesis. Is the proposal that DLC3/STARD8 plays a role in both testis differentiation and in Leydig cell function (steroidogenesis) or is this due to different DLC3 genes? I think the authors need to address these key issues in their discussion, if only to highlight that there are at present many gaps in our understanding.

The reviewer says:

“As far as I can tell the present studies show that inactivating mutations in Cv-c in Drosophila result in failure of germ cell enclosure by somatic cells into the testis, resulting in sterility.”

Response: This sentence does not represent the spirit of our findings accurately and this probably reflects the fact that we stressed the interaction between somatic mesodermal cells and germ cells in Drosophila which probably concealed that the main defects in Cv-c mutants are caused by the abnormal interaction of the mesodermal cells with germ cells but also among themselves. Our study provides insights about a new conserved pathway required in the mesodermal cells for the maintenance of an already formed testis, and only indirectly can be considered to deal with sterility. We show that Cv-c is required in the mesodermal cells for the correct maintenance of the testis structure, that when it fails leads to the testis dysgenesis which, among other defects, releases the germ cells. We show that in the absence of Cv-c function in the testis, the mesodermal pigment cells do not form a continuous layer around the testis and the ECM surrounding the testis breaks. We also show that the interstitial gonadal cells fail to ensheath the germ cells and as a result of all these the germ cells become dispersed. These perturbations can be partially corrected by expression in the testis mesoderm of human DLC3 or Drosophila Cv-c that in both cases require a functional StART domain. Thus, our results suggest that Cv-c/DLC3 have a fundamental function on the mesodermal testis cells that has been conserved. These results indicate that, as in Drosophila, the primary cause for the gonadal dysgenesis in DLC3 human patients is due to the abnormal maintenance of the testis mesoderm cells, which include both Sertoli and Leydig cells. Thus, our proposal is that DLC3/STARD8 plays a role in testis maintenance through its function in mesodermal cells which will probably affects both Sertoli and Leydig cell function.

To clarify the issue raised by the referee we have modified both, the introduction and the discussion to highlight that although humans and Drosophila diverged millions of years ago there are similarities regarding gonad stabilisation.

We have modified the introduction to clarify this issue:

“Gonadogenesis can be subdivided into three stages: specification of precursor germ cells, directional migration towards the somatic gonadal precursors and gonad compaction. In mammals, somatic cells, i.e. Sertoli cells in male and Granulosa cells in females, play a central role in sex determination with the germ cells differentiating into sperms or oocytes depending on their somatic mesoderm environment. In humans, Primordial Germ Cells (PGCs) are formed near the allantois during gastrulation around the 4th gestational week (GW) and migrate to the genital ridge where they form the anlage necessary for gonadal development (GW5-6). Somatic mesodermal cells are required for both PGCs migration and the formation of a proper gonad. Once PGCs reach their destination, the somatic gonadal cells join them (around GW 7-8 in males, GW10 in females) and provide a suitable environment for survival and self-renewal until gamete differentiation {Jemc, 2011 #413}. Thus, mutations in genes regulating somatic Sertoli and Granulosa support cell function in humans are often associated with complete or partial gonadal dysgenesis in both sexes and sex reversal in males {Zarkower, 2021 #430; Knower, 2011 #418; Brunello, 2021 #399}. Other mesodermal cells, the Leydig cells, also play an important role in the testis by being the primary source of testosterone and other androgens and maintaining secondary sexual characteristics.”

Also we have added a paragraph in the discussion to emphasize this argument:

“We show that in the absence of Cv-c function in the testis, the mesodermal pigment cells do not form a continuous layer around the testis and the ECM surrounding the testis breaks. We also show that the interstitial gonadal cells fail to ensheath the germ cells and as a result of all these the germ cells become dispersed from the testis. These perturbations can be partially corrected by expression in the testis mesoderm of human DLC3 or Drosophila Cv-c that in both cases require a functional StART domain. Thus, our results suggest that Cv-c/DLC3 have a fundamental function on the mesodermal testis cells that has been conserved. These results indicate that, as in Drosophila, the primary cause for the gonadal dysgenesis in DLC3 human patients is due to the abnormal maintenance of the testis mesoderm cells, which include both Sertoli and Leydig cells”.

I would also suggest that the authors highlight another potentially more important spin-off from such studies, namely that understanding of the regulation of DLC3/STARD8 genes, and what might perturb their expression/action would appear to present a whole new area for exploration in relation to testicular dysgenesis/masculinization disorders.

Response: We have modified the last part of the discussion to introduce referee 2’s suggestion:

“Our work points to DLC3/Cv-c as a novel gene required specifically in testis formation. Adding DLC3 to the list of genes involved in 46X,Y complete dysgenesis opens up a new avenue to analyse the molecular and cellular mechanisms behind these disorders that could help in diagnosis and the development of future treatments”.

Reviewer #3 :

Major comments:

1. This study has shown the expression pattern of cv-c and the consequence of cv-c mutation on different aspects of gonad development. However, one major comment is there is no quantification of the expression levels as well as the scoring of the mutant phenotypes.
2. In Figure 2, for instance, I recommend that the authors display the quantification of the fluorescence intensity of the cv-c expression under all circumstances (in situ hybridization as well as protein-trap based GFP expression) to better depict the differences among the male vs female gonad.

Response: We don’t think quantifying the stainings will add much to the results. We believe that the changes performed increasing the images’ contrast and their amplification are sufficient to illustrate our statement about cv-c being expressed in testis but not in ovaries.

1. In Figure 3, the authors show the different gonad developmental defects associated with the cv-c mutation. Specifically, the authors show that the gonad mesoderm cells are displaced with the pigment cells failing to ensheath the germ cells. In addition, the authors also suggest that there is an increased frequency of germ cell blebbing, an indication of migratory activity. However, there is no quantification of these findings. I think the authors should display a quantitative estimation of % of the mutant gonad depicting these phenotypes vs the normal gonad to have a perspective of how penetrant the phenotypes are.

Response: As referee suggested, we have quantified bleb phenotype. The results are presented in figure 3, panel J.

1. In Figure 4, the authors attempt to rescue the Cv-C mutation linked gonadal defects by overexpressing different Cv-C protein variants. The rescue experiments are not very clear. The graph shows the % of normal testes under different genotypic combinations. It is not very clear what the authors mean by normal (in what context)? Since the mutation results in different defects of gonad development, I think recommend that represent the rescue in terms of these defects. It would be interesting to see for instance, what happens to the blebbing or germ cell ensheathment phenoype upon rescue. How many % of testes show the rescue as compared to cv-c mutants?

Response: The percentages are quantified considering if the testes have any germ cell outside the gonad. We have added a line to clarify this point in the figure legend: “…quantified as encapsulated gonads with all germ cells inside the testis as assessed by Fisher-test”.

Nevertheless, we are going to quantify the number of ECM breaks and show the results in the reviewed manuscript.

1. Did the authors try cell-specific depletion of cv-c and examined the consequence on gonad development?

Response: cv-c mutants are embryonic lethal because of Cv-c’s widespread requirement on various embryonic tissues during development. Induction of FRT clones in the embryonic testis mesoderm was unsuccessful because of the low number of divisions during embryogenesis. We also tried to knock down cv-c expression with 3 different RNAi lines. Unfortunately, overexpression of these RNAi with different testis Gal4 drivers did not decrease cv-c mRNA levels significantly in the mesoderm or in other tissues where cv-c is expressed. Despite these experiments unsatisfactory outcome, our finding that cv-c is expressed in the testis mesoderm cells, and the fact that we can rescue the testis phenotypes by expressing Cv-c with gonadal mesodermal specific Gal4 lines supports a testis mesoderm requirement of cv-c for its gonadal function.

1. Another major concern is the lack of mechanistic insight of cv-c. For example, how does loss of cv-c result in gonadal dysgenesis? The authors suggested that StART domains regulate via lipid binding. The authors could examine if StART domain function is dependent on lipid-mediated interactions.

Response: We agree with the referee that the molecular characterisation of the StART-mediated GAP-independent Cv-c function we have uncovered in this work is a very interesting finding that should be addressed by future work. However, such biochemical characterisation requires a complex approach to distinguish between the already known StART function regulating the GAP activity shown before (Sotillos Scientific Reports) and the new GAP-independent function we describe in the testes that falls beyond this work.

The central point of this manuscript is the demonstration that both DLC3/Cv-c are involved in male gonad formation, an important conserved function for both of them that had been overlooked by previous publication. Thus, DLC3 should be considered a new gene to be analysed in the future when studying gonadal dysgenesis. A second important point raised by our work is the demonstration that DLC3/Cv-c can perform RhoGAP independent functions, something that had never been described for these proteins.

Not withstanding this, in the revised version, we have added a new supplementary figure (1) related to the StART domain-lipid interaction analysed in-silico. The in-silico model shows that the DLC3-StART domain Ω1-loop structure displays the highest frequency of interaction with the membrane. This loop is conserved in the StART domains of several other STARD proteins and seems to modulate access to the ligand binding cavity. Ω-loops play multiple roles in protein function, often related to ligand binding, stability and folding. In this context, mutations in the proximity of the Ω1-loop, like the ones carried by the patients, may have drastic effects on overall protein stability that could affect the interaction between gonadal precursor cells.

1. Do the cv-c mutants survive to adulthood? If yes, then it would be interesting to know how the adult testis behaves in cv-c mutants. Does it result in sterility?

Response: Unfortunately, all studied cv-c mutants are embryonic lethal.

1. Ensheathment is required for proper germline development and defects in ensheathment can affect soma-germline communication and germline development. Germ cell ensheathment affects the proliferation of germ cells and display defective JAK/STAT signaling. It would be interesting to know if the germ cells in cv-c mutant gonad show the proliferation defect and impaired JAK/STAT signaling.

Response: This is an interesting suggestion. JAK/STAT signalling has a male specific function that could explain why cv-c gonadal defects are male specific. We are going to study how cv-c affects STAT signalling in the male gonad. We are currently preparing stocks combining 10XSTAT::GFP reporter with cv-c mutants and preparing samples for anti-STAT labelling. We will also analyse if embryos lacking STAT activation, activate cv-c expression in the testes.

1. I was also wondering if the authors have examined the number of germ cells in the mutant gonads.

Response: Yes, we have counted the number of germ cells in cv-c mutants and, if anything, there are more. We initially considered that an excess of GC proliferation could be the cause of gonad disruption. However, we have discarded this hypothesis as phospho-histone 3 stainings did not show a significant increase of GC divisions. Moreover, when we blocked cell proliferation in cv-c’ mutant gonads using UAS-p21, the testes phenotype was not rescued. We are unsure what could be responsible for the slight increase of germ cells observed.

1. In addition, I think the quality of the images should be improved.

Response: We have changed the colours used in the confocal images and amplified the relevant regions in all panels. We thank both referees for this suggestion as these changes have improved the figure contrast.

Minor comments:

1. cv-c mRNA in Figure 2 panels (Fig. 2D) should be in italics.

Response: We have changed it.

1. There is no scale bar in Figure panels. In addition, there is no scale bar in the zoomed images in Figure 2. Scale bars should be consistently put in the all the Figures, in particular on the first panels of the Figures.

Response: We have added scale bars to all panels.

1. In the line 677, the manuscript says "arrowhead". There are no arrowheads but the arrows.

Response: Corrected

1. Please be consistent with the labels in Figure panels: Vasa is shown in capital while Eya is not.

Response: Corrected

1. Please be consistent with the labeling of the Figure panels: Figure 3A vs Figure 4a.

Response: Corrected

1. What does the asterisk signify in Figure 2? There is no mention of asterisk in the Figure 2 legend.

Response: The meaning of the asterisk was explained in the figure legend.

1. There is no grey channel (sagittal view) for the panels Figure 3I and J.

Response: We have already included sagittal views in the figure.

1. Please be thorough in labeling the genotypes in Figures. For instance, Figure 4c depict the % of normal testis in cv-c delta StART. However, the correct genotype is twi>Cv-c StART. In addition, in Figure 4c graph, cv-c mut should be cv-cGAPmut.
2. Please be consistent with the depiction of the "START" domain of the protein throughout the manuscript. In figure 4c for instance, it is "START" in the graph while in the figure panel 4i, it is StART.
3. In Figure 4b, it is written DLC3-GA. Did the authors mean DLC3-S993N?
4. In line 723, it should be anti-beta catenin.

Response: As suggested, we have unified figure labelling.

1. The authors have shown two images to suggest that cv-c mutant gonad depict the germ cell blebbing (Figure 3I and J). I think it would be much better to put up a graph showing the number or percentage of cv-c mutant gonads displaying the germ cell blebbing than putting two images with the same information.

Response: We have already done the quantification and added the data as a graph in figure (3J).

1. The previous comment is also true for Figure 6H and I. In both the panels, the authors wish to show discontinuous ECM marked by Perlecan expression in cv-c mutant gonads. I think it would be better to display a score of the number of mutant gonads depicting the discontinuous ECM.

Response: We are repeating stainings to quantify Perlecan disruption in cv-c mutants and we will display the results as a graph in figure 6.

Author Response

Reviewer #1 (Public Review):

The layered costs and benefits of translational redundancy by Raval et al. aim to investigate the impact of gene copy number redundancy on E. coli fitness, using growth rate in different media as the primary fitness readout. Genes for most tRNAs and the three ribosomal RNAs are present in multiple copies on the E. coli chromosome. The authors ask how alterations in the gene copy number affect the growth rate of E. coli in growth media that support different rates of growth for the wild type.

While it was shown before that mutants with reduced numbers of ribosomal RNA operons grow at reduced rates in rich medium (LB), this study extends these findings and reaches some important conclusions:

1) In a poor medium (supporting slow growth rates), the mutants with fewer rRNA operons actually grow faster than the wild type, showing that redundancy comes at a cost.

2) The same is true for mutants with reduced gene copy number of certain tRNAs and correlates with slower rates of protein synthesis in these mutants.

3) That rRNA operon gene copy number is more decisive for growth rate than any tRNA gene copy number (>1).

In addition, measurements of strains with deletions of genes encoding tRNA-modification enzymes that affect tRNA specificity are included. While interesting, no unifying conclusion could be reached on the impact of these mutations on growth rate.

Thank you for this clear summary of our work.

The well-known "growth law" relationships between growth rate and macromolecular composition (RNA/protein ratio, for example) specifically concern steady-state growth rates. It is concerning that all growth rates in this work were measured on cultures that were only back-diluted 1:100 from overnight LB precultures. That only allows 6-7 doubling times before the preculture OD is reached again. The exponential part of growth would end before that, allowing perhaps only 3-4 generations of growth in the new medium before the growth rate was measured. Thus, the cultures were not in balanced growth ("steady state") when the measurements were made, rather they were presumably in various states of adapting to altered nutrient availability.

A detailed connection with exact growth rate laws indeed requires growth rate measurement in steady-state. Hence, we refrained from making such a connection in this manuscript, though it would be an interesting future avenue to explore. Our main goal here was to ask how E. coli growth rate is affected by external nutrient availability and internal translation components. For this, the key comparisons involve the WT vs. gene deletion mutations, and rich vs. poor growth media. For any given comparison, strains were tested under identical conditions and experimental protocols, and hence we can address our main questions without the need to obtain steady-state growth. As an aside, we note that the nutrient fluctuations inherent in such experiments may also be more relevant than steady-state growth for natural bacterial populations.

As noted by the reviewer, we measured fitness only in a relatively narrow growth regime of several doublings; but we do capture exponential growth by focusing on the early data points (representing the exponential phase) for our growth rate calculations. We have now explicitly mentioned this in the methods section “Measuring growth parameters”.

A second concern is the use of the term "tRNA expression levels" in the text in Figure 4. I believe the YAMAT-seq method reports on the fractional contribution of a given tRNA to the total tRNA pool. Thus, since the total tRNA pool is larger in fast-growing cells than in slow-growing cells, a given tRNA may be present at a higher absolute concentration in the fast than in the slow-growing cells but will be reported as "higher in poor" in figure 4, if the given tRNA constitutes a smaller fraction of the total tRNA pool in rich than in poor medium. For this reason, the conclusions regarding the effect of growth medium quality on tRNA levels are not justified.

Thank you for this important point. We agree that our phrasing was incorrect, and we have modified the relevant text and figures accordingly. The fractional contribution of a given tRNA isotype to the total tRNA pool is still useful to compare, and is justified as now rephrased.

Reviewer #2 (Public Review):

Raval et al. by creating a series of deletion mutants of tRNAs, rRNAs, and tRNA modifying enzymes, have shown the importance of gene copy number redundancy in rich media. Moreover, they successfully showed that having too many tRNAs in poor media can be harmful (for a subset of the examined tRNAs). Below, please find my comments regarding some of the methodologies, conclusions, and controls needed to stratify this manuscript's findings.

Figure 2 presents Rrel as a relative measurement (GRmut/GRwt). Therefore, I'm confused as to how Rrel can be negative, as shown in supplemental file 3 (statistics).

We apologize for the confusion. Supplemental file 3 shows details of the statistical analysis (not raw data), and we included the effect size here (mean difference between the WT and the mutant relative growth rate) along with statistical significance. Thus, if the rel R of a given mutant is 1.1, the mean difference would be (1–1.1) = –0.1, meaning that it is performing 10% better than the WT.

The “raw” relative growth rates are provided in source data files (labeled figure-wise), and there are no negative values there, as expected.

We have now explicitly (and separately) referenced the source and statistics data files in the data analysis section in the methods, and in each figure legend. We hope this avoids confusion and makes it easier for readers to find the correct file.

Does Figure 3 show the mean of 4 biological replicates or technical replicates? It should be stated clearly in the legend of figure 3.

All replicates are biological replicates until unless stated otherwise. This is now stated in the methods (lines 185-187), and in the figure legends.

Do all strains (datapoint on figure 3 left panel) significantly perform better than the WT in nutrient downshift? Looking at supplemental file 3 I see this is not the case. Please mark the statistically significant points. I suggest giving each set a different symbol/shape and coloring the significant ones in red.

We had considered indicating statistical significance in the plot, but decided not to do so because it was difficult to show the many potentially useful layers of information without cluttering the plot. One other practical difficulty was that each point in the figure represents two values: one from the upshift (Y axis) and one from the downshift (X axis). For some mutants the fitness difference was significant in only one direction, so it was not straightforward to indicate significance. Further, our main goal here was to show where strains from different deletion Sets (Figure 1) fall in this plot (i.e. which quadrant they occupy), and so we wanted to ensure that points were easily distinguished by Set. In the text we do not include statistically non-significant points in the summary of observed patterns, and refer readers to information on statistical significance provided in the supplemental file.

Another issue is that in the statistics of figure 2 (in supplemental file 3), positive values reflect cases where the mutant performs poorly compared to the WT, while in figure 3 the negative values indicate this. Such discrepancy is not very clear. And again, how can Rrel be negative?

As noted in response to an earlier comment, Rrel values (given in source data files) are not negative, but effect sizes (given in supplemental file with statistics) may be negative or positive since they show differences in the relative growth rate of WT and mutant. We agree that the discrepancy between the calculation of mean difference for Figs 2 and 3 was confusing. We have now fixed this: in both cases, negative mean difference values now indicate that the mutant performs better.

Both axes say glycerol. What about galactose?

The typo has been corrected.

Lines 414-419: The authors state that "all but one had a growth rate that was comparable to WT (16 strains) or higher than WT (10 strains) after transitioning from rich to poor media (i.e. during a nutrient downshift, note data distribution along the x-axis in Fig 3; Supplementary file 3). In contrast, after a nutrient upshift, 11 strains showed significantly slower growth in one or both pairs of media, and only 2 showed significantly faster growth than WT (note data distribution along the y-axis in Fig 3; Supplementary file 3)".

Looking at the Rrel values when transitioning from TB to Glycerol and vice versa suggests no direction in the effect of reducing redundancy. During downshift, four strains perform better, and three strains perform worse than the WT. During upshift, four stains perform better, and six strains perform worse. Only during downshift and upshift from TB to Gal and vice versa give a strong signal.

The authors should write it clearly in the text because the effect is specific to that transition/conditions and not of general meaning is written in the text (e.g., transition from every rich to every poor media and vice versa). I am convinced that the authors see an actual effect when downshifting or upshifting from TB to galactose and vice versa. In that case, the conclusion is that redundancy is good or bad depending on the conditions one used and not as a general theme.

Also, this is true just for some tRNAs, so I don't think the conclusion is general regarding the question of redundancy.

The fitness impacts of altered redundancy are best explained by a combination of multiple factors (in addition to nutrient availability): the number of tRNA genes deleted, number of tRNA gene copies remaining as a backup, availability of wobble or ME as backup, and codon usage. Thus, any of these variables alone would provide only partial explanation for the observed fitness effects of all strains.

In many tRNA deletion strains – especially single gene deletions – redundancy was not significantly lowered by the deletion, as we explain in the results section. These strains were therefore not expected to show major fitness impacts or follow strong nutrient dependent trends, and this is what we observe.

The same is true for nutrient upshift-downshift experiments, where a vast majority of strains were not expected to show a specific pattern because they do not show significant fitness impacts in general, nor do they show a strong correlation in relative fitness impacts vs. growth rate (Figure 1d). In addition, in these experiments the difference between the two media also matters. For example, comparing the maximum WT growth rate, M9 Gal is poorer than M9 Glycerol. Therefore, shifts between TB-Gal are nutritionally more drastic than TB-Gly shifts, and one would expect a larger fitness impact in the former (for strains with significantly altered redundancy). Hence, despite differences across media pairs, our broader conclusions about the impact of redundancy are generalizable as long as redundancy and nutrients are both substantially altered, e.g. due to deletion of 3 tRNA genes, deletion of tRNA+ME, or deletion of multiple rRNA operons.

Figures are indicated differently along the text. Sometimes they are written "figure X", sometimes FigX. Referring to the supplemental figures are also not consistent.

We have now corrected this.

Line 443-444: "In fact, 10 tRNAs were significantly upregulated in the poor medium relative to the rich medium".

This result contradicts the author's hypothesis. If redundancy is bad in poor media because the cells have more tRNAs than they need, the tRNAs level will be downregulated, not upregulated. How do the authors explain this?

This statement referred to the WT strain, and was meant to highlight that (as noted by the reviewer) some tRNAs appear to be upregulated in poor medium, which is counterintuitive. However, as noted by reviewer 1 (see their comment on the interpretation of YAMAT-seq data), we can only infer the relative contribution of each tRNA isotype to the total tRNA pool (rather than absolute up- or down- regulation). Thus, we have removed this specific sentence, and instead we focus on the mismatch between the media-dependent changes in the composition of the tRNA pool and the fitness effects of different tRNA isotypes (lines 475-482).

Line 445-447: "In contrast (and as expected), all tested tRNA deletion strains had lower expression of focal tRNA isotypes in the rich medium (Fig 4B, left panel), showing that the backup gene copies are not upregulated sufficiently to compensate for the loss of deleted tRNAs". It is great that the authors validated the expression in their strains. However, for accuracy, please indicate that it was done in four strains to avoid the impression that they did it in all the strains.

We have now reworded this sentence to remind readers that we measured 4 tRNA deletion strains in this experiment.

Finally, across the manuscript, the authors reveal that deleting some tRNAs or modifying enzymes can be deleterious in rich media or advantageous in poor media. However, I think this result and the conclusions derived from it could be more convincing if the authors would show in a subset of their strains that expressing the deleted tRNAs or modifying enzymes from a plasmid can rescue the phenotype.

Thank you for this suggestion. For a small subset of strains, we now include data showing that complementation from a plasmid indeed rescues the deletion phenotype (Fig 2 – Fig supplement 7).

Reviewer #3 (Public Review):

In this manuscript, Raval et al. investigated the cost and benefit of maintaining seemingly redundant components of the translation machinery in the E. coli genome. They used systematic deletion of different components of the translation machinery including tRNA genes, tRNA modification enzymes, and ribosomal RNA genes to create a collection of mutant strains with reduced redundancy. Then they measured the effect of the reduced redundancy on cellular fitness by measuring the growth rate of each mutant strain in different growth conditions.

This manuscript beautifully shows how maintaining multiple copies of translation machinery genes such as tRNA or ribosomal RNA is beneficial in a nutrient-rich environment, while it is costly in nutrient-poor environments. Similarly, they show how maintaining parallel pathways such as non-target tRNA which directly decodes a codon versus target tRNA plus tRNA modifying enzymes which enable wobble interactions between a tRNA and a codon have a similar effect in terms of cost and benefit.

Further, the authors show the mechanisms that contribute to the increased or reduced fitness following a reduction in gene copy number by measuring tRNA abundance and translation capacity. This enables them to show how on one hand reduced copy numbers of tRNA genes result in lower tRNA abundance in rich growth media, however in nutrient-limiting media higher copy number leads to increased expression cost which does not lead to an increased translation rate.

Overall, this work beautifully demonstrates the cost and benefits of the seemingly redundant translation machinery components in E. coli.

Thank you for the clear summary and encouraging comments.

However, in my opinion, this work’s conclusion should be that the seeming redundancy of the translation machinery is not redundant after all. As mentioned by the authors, it is known that tRNA gene copy number is associated with tRNA abundance (Dong et al. 1996, doi: 10.1006/jmbi.1996.0428), this effect is also nicely demonstrated by the authors in the section titled “Gene regulation cannot compensate for loss of tRNA gene copies”. Moreover, this work demonstrates how the loss of the seeming redundancy is deleterious in a nutrient-rich environment. Therefore, I believe the experiments presented in this work together with previous works should lead to the conclusion that the multiple gene copies and parallel tRNA decoding pathways are not redundant but rather essential for fast growth in rich environments.

The point is well taken. However, as described in the introduction, here we focus on functional redundancy at the cellular level, where there are multiple ways of achieving the same translation rate. Hence we say that translation components are redundant at this level of analysis. One of the key conclusions from our work is that such redundancy is context-dependent, i.e. it is essential when rapid growth is possible, but is costly and dispensable otherwise. Therefore, we show that the definition of redundancy itself changes with environmental conditions.

The following analogy may help convey this. There may be many ways to reach a flight on an airport: multiple entrances, multiple check-in and security check counters, multiple boarding gates, etc. On a deserted airport these may seem redundant and even costly to maintain. On the other hand, they have a utility when traffic is high. Hence even though from a purely architectural perspective the multiple routes are redundant, from a utilitarian perspective it depends on the flux of passengers.

Authors’ response (5 November 2022)

GENERAL ASSESSMENT

Piezo1 and Piezo2 are stretch-gated ion channels that are critically important in a wide range of physiological processes, including vascular development, touch sensation and wound repair. These remarkably large molecules span the plasma membrane almost 40 times. Cryo-EM and reconstitution experiments have shown that Piezos adopt a cup-like structure and, by doing so, curve the local membrane in which they are embedded. Importantly, membrane tension is a key mediator of Piezo function and gating, an idea well-supported several independent studies. Cells have varied three-dimensional shapes and are dynamic assemblies surrounded by plasma membranes with complex topologies and biochemical landscapes. How these microenvironments influence mechanosensation and Piezo function are unknown.

The current preprint by Zheng Shi and colleagues asks how the shape of the membrane influences Piezo location. The authors use creative approach involving methods to distort the plasma membrane by generating “blebs” and artificial “filopodia”. Overall, the work convincingly shows that the curvature of the lipid environment influences Piezo localization. Specifically, they show that Piezo1 molecules are excluded from filopodia and other highly curved membranes. These experiments are well controlled and the results fully consistent with previous structural and biochemical work. Furthermore, the work explores the hypothesis that a chemical modulator of Piezo1 channels called Yoda1 functions by “flattening” the channels, a movement previously proposed to be linked to mechanical gating. Consistent with this model, the authors show that Yoda1 application is sufficient to allow Piezo1 channels to enter filopodia. While the flattening model is provocative hypothesis, hard evidence awaits structural verification.

Overall, the preprint by Shi and colleagues will be of interest to scientists studying how mechanical forces are detected at the molecular level. The work introduces important concepts regarding how the shape of cellular membranes affects the movement and function of proteins within it. The technical advance for changing the shape of a plasma membrane is of note. 

We thank the reviewers for the accurate summary and positive assessments of our manuscript. We address each of the concerns below.

RECOMMENDATIONS

Revisions essential for endorsement:

As is evident from the comments below, our endorsement of the study is not dependent on additional experiments. However, we feel more experimental clarification is needed, that providing clearer images would be helpful, and, most importantly, we would like alternative conclusions and caveats to be mentioned.

1. Can the authors comment on the link between the conclusions that (1) the presence of filopodia prohibits Piezo1 localization (Fig 1) and (2) Piezo1 expression prohibits the formation of filopodia (Fig 3). As it stands, it is hard to understand if there is a cause and effect relationship here or if these are separate, unrelated observations? We recommend revising the discussion to clarify.

We now clarify the link between Piezo1’s curvature sensing (depletion from filopodia) and its inhibition effect on filopodia formation before presenting the current Fig. 5: “Curvature sensing proteins often have a modulating effect on membrane geometry. For example, N-BAR proteins, which strongly enrich to positive membrane curvature, can mechanically promote endocytosis by making it easier to form membrane invaginations (Shi and Baumgart, 2015; Sorre et al., 2012). Thus, we hypothesize that Piezo1, which strongly depletes from negative membrane curvature (Fig. 1, Fig. 2), can have an inhibitory effect on the formation of membrane protrusions such as filopodia.”

2. When comparing the images of Fig. 2A, B to those of Fig. 2C, D, it appears that bleb formation induces a drastic enrichment of Piezo1 in the bleb membrane. Is this due to low membrane tension in the bleb? If this is the case, it indicates that the level of membrane tension has a prominent role in determining the localization of Piezo1.

We apologize for this confusion due to our poor wording and figure presentation in the manuscript. By “Piezo1 clearly locates to bleb membranes” we didn’t mean to indicate that Piezo1 is enriched on bleb membranes as compared to the cell body. Rather, we meant to emphasize Piezo1’s localization to the *membrane* of the blebs rather than in the cytosolic space.

Cells in 2C, 2D are different from that in 2A and 2B and were presented with different image contrasts. We now include the images of the full cell for Fig. 2C and 2D as the current Figure S8. To focus on the equator of the bleb, the cell body was out of focus. However, there is no indication that Piezo1 density is significantly different between the bleb membrane and the intact parts of the plasma membrane.

We changed the main text to: “Similar to previous reports (Cox et al., 2016), bleb membranes clearly contain Piezo1 signal, but not significantly enriched relative to the cell body (Fig. 2C, 2D; Fig. S8).”

In line with this, it appears more Piezo1 proteins are localized in less tensed tethers. Thus, might your observations be equally consistent with tension rather than curvature as a key regulator of Piezo1 localization? We recommend adding this to your discussion.

We now explain the deconvolution between tension and curvature effects in detail. We also performed additional experiments to quantify the membrane tension in cells and blebs (current Fig. S9).

In the Results section, we add: “Tethers are typically imaged > 1 min after pulling, whereas membrane tension equilibrates within 1 s across cellular scale free membranes (e.g., bleb, tether) (Shi et al., 2018). Therefore, the sorting of Piezo1 within individual tension-equilibrated tether-bleb systems (Fig. 2C – 2G) suggests that membrane curvature can directly modulate Piezo1 distribution beyond potential confounding tension effects.”

In the Discussion section, we add: “In addition to membrane curvature, tension in the membrane may affect the subcellular distribution of Piezo1 (Dumitru et al., 2021). Particularly, membrane tension can activate the channel and potentially change Piezo1’s nano-geometries. This tension effect is unlikely to play a significant role in our interpretation of the curvature sorting of Piezo1 (Fig .2): (1) HeLa cell membrane tension as probed by short tethers (Fig. S9F; 45 ± 29 pN/ µm on blebs and 270 ± 29 pN/ µm on cells, with the highest recorded tension at 426 pN/ µm) are significantly lower than the activation tension for Piezo1 (> 1000 pN/µm (Cox et al., 2016; Lewis and Grandl, 2015; Shi et al., 2018; Syeda et al., 2016)). (2) With more activated (and potentially flatten) channels under high membrane tension, one would expect a higher density of Piezo1 on tethers pulled from tenser blebs. This is the opposite to our observations in Fig. 2C - 2G, where Piezo1 density on tethers was found to decrease with the absolute curvature, thus tension (eq. S6), of membrane tethers.”

3. Given the intrinsically curved structure of Piezo1, it is difficult to understand the model’s prediction that curved Piezo1 is not enriched in 25-75 nm invaginations. Where will Piezo1 normally reside in the plasma membrane? It would be helpful if this could be discussed.

The spontaneous curvature from our model _C_0 (_C_0-1 = 83 ± 17 nm, the value is updated after refitting to more data points collected for Fig. 2G) represents a balance between the intrinsic curvature of Piezo1 trimers (0.04 ~ 0.2 nm-1 as suggested by CryoEM studies(Haselwandter et al., 2022; Lin et al., 2019; Yang et al., 2022)) and that of the associated membrane (0 nm-1, assuming lipid bilayers alone do not have an intrinsic curvature). We now refer to _C_0 as the “spontaneous curvature of the Piezo1-membrane complex” throughout the manuscript, rather than the “spontaneous curvature of Piezo1”.

Our model, when extrapolated to membrane invaginations, predicts a weak enrichment of Piezo1 on ~100 nm invaginations (peak at 83 nm), but a depletion of Piezo1 on more highly curved invaginations. This is simply because it would be energetically costly to fit a protein-membrane complex to a curvature that is different from what the complex prefers (in the case of 25-75 nm membrane invaginations, the membrane curvature would be too high for the Piezo1-memrbane complex).

However, it is worth pointing out that Piezo1-membrane complex may not present the same spontaneous curvature on positively and negatively curved membranes. More importantly, we do not yet have direct evidence to show that this depletion indeed happens in the exact range of invagination curvature we predicted. We now acknowledge this limitation in the Discussion section: “However, it is worth noting that we assumed a zero spontaneous curvature for membranes associated with Piezo1 and that the spontaneous curvature of Piezo1-membrane complex is independent of the shape of surrounding membranes. These assumptions may no longer hold when studying Piezo1 in highly curved invaginations or liposomes (Lin et al., 2019).”

We also took this opportunity to verify the key prediction from the extrapolated model - that Piezo1 would enrich towards ~ 100 nm radius cell membrane invaginations. To achieve this, we utilized a recent development in nanotechnology, pioneered by Wenting Zhao and Bianxiao Cui’s labs (Lou et al., 2019; Zhao et al., 2017). An illustration of the experimental design and detailed findings are summarized in the current Fig. 3 and briefly discussed below.

In collaboration with Wenting Zhao’s lab, we cultured cells on precisely engineered nanobars with curved ends and flat central regions. For a labelled membrane protein of interest, the end-to-center fluorescence ratio would report the protein’s curvature sorting ability. We find that Piezo1 enriches to the curved ends of nanobars, whereas membrane marker signals are homogeneous across the entire nanobar (Fig. 3). The finding achieved strong statistical significance via hundreds of repeats on nanobars of the exact same geometry, a major technical strength of our chosen system. Furthermore, the enrichment of Piezo1 was observed on nanobars with 3 different curvatures (corresponding to diffraction-limited radii between 100 to 200 nm) and qualitatively agrees with our model (current Fig. S10). While further investigations on a wider range of membrane curvature are required to fully map out the sorting of Piezo1 on membrane invaginations, our data in the current Fig. 3 clearly verifies the prediction that membrane curvature can lead to enrichment of Piezo1 on cellular invaginations.  

We now refer to this new finding in the Abstract, along with the previously observed depletion of Piezo1 on filopodia. We present a detailed description of the experiment and associated findings in the Results and the Method sections.

4. It is currently unknown whether and how long Yoda1 might keep Piezo1 in a flattened state. Given that Yoda1 is highly hydrophobic, it might affect membrane properties instead of the curvature of Piezo1. These caveats should be discussed.

We thank the reviewers for pointing out the potential effect of Yoda1. We did additional experiments to confirm that on Piezo1-KO cells, Yoda1 molecules alone do not significantly alter the formation of filopodia, in contrast to observations in WT cells. This data suggests Yoda1 (at the concentration we use) is unlikely to significantly alter the mechanical properties of the plasma membrane. The data is now presented as Fig. 5E in the updated manuscript. We added: “In Piezo1 knockout (Piezo1-KO) cells, adding Yoda1 to the culture medium does not significantly change the number of filopodia (Fig. 5E), suggesting the agonist does not directly regulate filopodia formation without acting on Piezo1.”

5. The authors state that “Yoda1 leads to a Ca2+ independent increase of Piezo1 on tethers”. It has not been determined yet that Yoda1 leads to Piezo1 flattening (or even opening). In Electrophysiology experiments, unless there is pressure applied, Yoda1 does not lead to substantial currents. Therefore, the cartoon of Yoda1 flattening Piezo1(3H) is misleading. We recommend revising this. So far, the best experimental evidence on flattening is via purified channels reconstituted in various sizes of liposomes. However, it is plausible that the flattened shape is closed or open inactivated. Because most of the claims of this paper depend on the curved vs flattened shape of Piezo1, the authors should address these caveats carefully.

We thank the reviewers for pointing out the limitations in our current understanding of Yoda1. We agree that our data do not directly show the flattening of Piezo1 by Yoda1, rather it is consistent with the flattening hypotheses. We lowered the tone of our conclusion to Fig. 4 to: “Our study suggests this conformational change of Piezo1 may also happen in live cells (Fig. 4H).” We also added arrows in Fig. 4H to suggest that membrane tension helps the proposed flattening of Piezo1 by Yoda1.

We think our experiment may also provide new insights on the action of Yoda1: First, we note that only a small fraction of filopodia responded to Yoda1, and pre-stressing of the cell membrane was required to amplify the Yoda1 effect (current Fig. 4E). This observation is consistent with the reviewers’ notion that membrane tension is likely required to flatten Piezo1, even in the presence of Yoda1. Secondly, highly curved liposome or detergents can confine the shape of Piezo1 trimers. Therefore, the inability to observe Yoda1-induced flattening of Piezo1 in small liposomes is not necessarily in contradiction with our observation in the mostly flat cell membranes.

We add to the Discussion section: “Yoda1 induced flattening of Piezo1 has not been directly observed via CryoEM. Our results (Fig. 4) point to two challenges in determining this potential structural change: (1) Yoda1 induced changes in Piezo1 sorting is greatly amplified after pre-stretching the membrane (Fig. 4E), pointing to the possibility that a significant tension in the membrane is required for the flattening of Yoda1-bound Piezo1. (2) Piezo1 is often incorporated in small (< 20 nm radius) liposomes for CryoEM studies. The shape of liposomes can confine the nano-geometry of Piezo1 (Lin et al., 2019; Yang et al., 2022), rendering it significantly more challenging to respond to potential Yoda1 effects. This potential effect of membrane curvature on the activation of Piezo1 would be an interesting direction for future studies.”

6. Page 9: "Our study shows this conformational change of Piezo1 in live cells (Fig. 3H)." We recommend that this claim be removed as it seems too strong for the provided data.

We changed the sentence to: “Our study suggests this conformational change of Piezo1 may also happen in live cells (Fig. 4H).”

Additional suggestions for the authors to consider:

1. Based on the calculated spontaneous curvature of Piezo1-membrane C0 of 87 nm, is it possible to derive the curvature of Piezo1 protein itself and the associated membrane footprint? This would be a nice addition.

It is possible to do such an estimation, however, many (unverified) assumptions must be made, in addition to the ones already in our model. First, we need to assume a size of the Piezo1 trimers and of the Piezo1-membrane complex. If we assume Piezo1 trimers are ~170 nm2 in the plane of lipid bilayers (based on estimates from PDB) and that the complex takes on the shape of a 10 -20 nm radius half-sphere. Effectively, Piezo1 occupies an area fraction of 6.7%~27% in the Piezo1-membrane complex. Next, we assume that the membrane and the Piezo1 trimer have the same bending rigidity. Finally, we assume that the membrane itself does not have an intrinsic curvature.

With those assumptions, the intrinsic curvature of Piezo1 trimers (_C_p) would relate to the spontaneous curvature of membrane-Piezo1 complex (_C_0) following: _C_p-1 = _C_0-1 * (6.7%~27%). Knowing _C_0-1 = 83 ± 17 nm, we get _C_p-1 = 5.6 nm ~ 22.4 nm.

2. It is hard to see the filopodia and their localization in the figures. It would be better for readers and more convincing if clearer/higher resolution example images could be provided.

We now provide high resolution figures.

3. Can the authors better explain how the calculations done in panel 1C and S3D are done and their importance?

Each fluorescence trace along the drawn yellow line was normalized to the mean intensity on the corresponding flat cell body, so that the average fluorescence of the cell body has a y-axis value of 1. We think the intensity traces are important because image contrast can be adjusted, therefore Fig. 1A alone would not convincingly show that there are no Piezo1 on filopodia.

4. In Figure 2E, are these data from hPiezo1 or mPiezo1? In other cases, hPiezo1 is specified, this this may be a typo?

Corrected.

5. Figure 3 F&G: We assume these cells are the same in all panels, just visualized with either mCherry or eGFP in each condition. Accordingly, we would have expected more swelling in hypotonic conditions, and wonder if further evaluation may resolve this apparent discrepancy? If not, please provide more clarification.

This is a good point. Indeed, we do observe a significant swelling of the cell right after the hypotonic shock.

However, this effect is expected to be transient (volume of the cell would recover after ~ 1 min), see Figure. 1C here: https://www.pnas.org/doi/10.1073/pnas.2103228118. Our images in Fig. 3F and 3G were taken ~10 min after the hypotonic shock.

6. On a lighter note, we’d recommend not using in cellulo.

We changed in cellulo to “in live cells”

Reference List

Cox, C.D., Bae, C., Ziegler, L., Hartley, S., Nikolova-Krstevski, V., Rohde, P.R., Ng, C., Sachs, F., Gottlieb, P.A., and Martinac, B. (2016). Removal of the mechanoprotective influence of the cytoskeleton reveals PIEZO1 is gated by bilayer tension. Nature Communications 7, 1-13.

Dumitru, A.C., Stommen, A., Koehler, M., Cloos, A., Yang, J., Leclercqz, A., Tyteca, D., and Alsteens, D. (2021). Probing PIEZO1 Localization upon Activation Using High-Resolution Atomic Force and Confocal Microscopy. Nano Letters 21, 4950-4958.

Haselwandter, C.A., MacKinnon, R., Guo, Y., and Fu, Z. (2022). Quantitative prediction and measurement of Piezo's membrane footprint. bioRxiv

Lewis, A.H., and Grandl, J. (2015). Mechanical sensitivity of Piezo1 ion channels can be tuned by cellular membrane tension. Elife 4, e12088.

Lin, Y., Guo, Y.R., Miyagi, A., Levring, J., MacKinnon, R., and Scheuring, S. (2019). Force-induced conformational changes in PIEZO1. Nature 573, 230-234.

Lou, H., Zhao, W., Li, X., Duan, L., Powers, A., Akamatsu, M., Santoro, F., McGuire, A.F., Cui, Y., and Drubin, D.G. (2019). Membrane curvature underlies actin reorganization in response to nanoscale surface topography. Proceedings of the National Academy of Sciences 116, 23143-23151.

Shi, Z., and Baumgart, T. (2015). Membrane tension and peripheral protein density mediate membrane shape transitions. Nature Communications 6, 1-8.

Shi, Z., Graber, Z.T., Baumgart, T., Stone, H.A., and Cohen, A.E. (2018). Cell membranes resist flow. Cell 175, 1769-1779. e13.

Sorre, B., Callan-Jones, A., Manzi, J., Goud, B., Prost, J., Bassereau, P., and Roux, A. (2012). Nature of curvature coupling of amphiphysin with membranes depends on its bound density. Proceedings of the National Academy of Sciences 109, 173-178.

Syeda, R., Florendo, M.N., Cox, C.D., Kefauver, J.M., Santos, J.S., Martinac, B., and Patapoutian, A. (2016). Piezo1 channels are inherently mechanosensitive. Cell Reports 17, 1739-1746.

Yang, X., Lin, C., Chen, X., Li, S., Li, X., and Xiao, B. (2022). Structure deformation and curvature sensing of PIEZO1 in lipid membranes. Nature 1-7.

Zhao, W., Hanson, L., Lou, H., Akamatsu, M., Chowdary, P.D., Santoro, F., Marks, J.R., Grassart, A., Drubin, D.G., and Cui, Y. (2017). Nanoscale manipulation of membrane curvature for probing endocytosis in live cells. Nature Nanotechnology 12, 750-756.

(This is a response to peer review conducted by Biophysics Colab on version 1 of this preprint.)

Meillassoux claims that, because cognitive science is made of atoms, that makes it suspect -- so we need to use philosophy. That is a bad claim. Philosophy is also made of atoms too. Cognitive science solves how cognition works. It may not answer "why cognition works", but maybe that's a trick question that only philosophy can ask, but nobody can answer.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The rapid syncytial nuclear cycles that occur during the first ~2.5 hours of Drosophila embryogenesis and give rise to the blastoderm are supported by large amounts of maternally deposited histone proteins which are stored in the egg cytoplasm for deposition into replicating DNA during each round of S phase. Although the H2A/H2B storage chaperone Jabba was identified by Michael Welte's lab several years ago, maternal H3/H4 storage chaperones have not been identified. Tirgar et al provide evidence that the Drosophila NASP protein provides histone H3 and H4 storage function during these earliest stages of Drosophila embryogenesis. The data include genetic analyses that NASP function is required maternally, but not zygotically, and molecular analyses that NASP binds H3 and that H3 and H4 levels are reduced in the embryo and late-stage oocytes in the absence of NASP. These data are convincing and support the conclusion that NASP is a maternally acting H3/H4 storage chaperone needed in the early embryo.

Two additional lines of investigation would strengthen this conclusion and perhaps increase the impact and appeal of the manuscript.

The first is a microscopic analysis of the nuclear division cycles in eggs derived from NASP mutant mothers. The authors report DAPI staining and assessment of nuclear cycles, but do not show these data. In fact, the two embryos shown in Figure 4B do not look like DAPI stained embryos-there are no nuclei apparent in the images. Loss of maternal histone causes defects in chromosome morphology that result in characteristic defects such as lagging chromosomes and the failure of sister chromatid segregation leading to fused daughter nuclei (see PMID: 11157774 for an example). These defects should not be difficult to detect via DNA staining or even using fluorescently labeled H2 type histones. Characterizing such defects would lend support to the hypothesis and I think is important for this paper.

We thank the reviewer for their constructive review and feedback. We have switched to Propidium Iodide (PI) staining to increase the signal-to-noise for DNA staining in early embryos. Given the improved signal we see with PI over DAPI, we will be able to provide both improved images of nuclear staining and assay for defects in chromosome morphology as suggested. We will include this data in the revised version of the manuscript. Second, determining the location of NASP in the early embryo might provide further insight into the mechanism of storage. i.e. is NASP located in the cytoplasm rather than the nucleus, perhaps in association with lipid droplets like Jabba? Do the antibodies the authors developed work in IF experiments to ask this question? At the moment what is shown is that NASP is present in 0-2 hour embryos via western blot analysis, supporting the conclusion that it functions in the early embryo as a storage chaperone. This analysis would be nice to have but is not essential in my view.

We have tried to use our antibody to monitor the localization of NASP in the early embryo. Unfortunately, the staining has yet to work. We will continue to alter fixation and permeabilization conditions in the early embryo with the goal of including this data in the revised manuscript. We have, however, been able to monitor NASP localization in Drosophila S2 cultured cells with our antibody. If we are unable to get the antibody staining to work in embryos, we will include the NASP localization data in S2 cells in combination with EdU labeling to mark cells in S phase.

Small points: Is NASP really a maternal effect "lethal"? Some of the eggs do hatch, and so some develop to stages where maternal histones are no longer necessary and zygotic production takes over (i.e. cycle 15). Perhaps consider the language used here.

We see the reviewers point with respect to the term ‘lethal’. We do see a very small fraction of progeny laid by NASPmutant mothers make it to adulthood, although they die shortly after hatching. We’ve removed the term ‘lethal’ and refer to NASP solely as a maternal effect gene. On this point, do NASP mutant females lay the same number of eggs as wild type? i.e. is there a requirement for oogenesis/egg production (other than depositing H3/H4 into the egg), or just for the early zygotic cycles?

We have noticed that NASP mutant mothers have lower fecundity. We have included this data in the revised manuscript as Supplemental Figure 2A.

The first paragraph of the results is redundant with much of the introduction, which I think could do a better job at describing in more detail the syncytial cycles and the special needs they have for histone storage and chaperone function versus the post-blastoderm embryonic cycles and the rest of development. i.e. make a better distinction between the first two hours of embryogenesis versus the rest of embryogenesis, and the when the switch from maternal to zygotic control of development and histone production occurs (cycle 15 at 3-4 hours AED).

We appreciate the reviewer for this suggestion. The manuscript has been edited to be less redundant and include details of embryogenesis as suggested. CROSS-CONSULTATION COMMENTS Seems like all reviewers are in general agreement, particularly about providing additional data regarding chromosome/nuclear behavior in the NASP mutants and NASP localization in the early embryo to increase impact of the study. While rescue of the NASP mutant phenotype with a transgene would be nice, as suggested by referee #2, I don't think it's essential given the genetic approaches employed.

Reviewer #1 (Significance (Required)):

see above

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Tirgar et al. report on a functional characterization of the Drosophila homolog of the histone H3/H4 chaperone NASP. They generated a loss of function allele of NASP by CRISPR/Cas9, which induces a partial maternal effect embryo lethal phenotype. Using quantitative mass spectrometry, they demonstrate that NASP stabilizes reservoirs of H3 and H4 in the early embryo. The manuscript is very clear and confirms the functional importance of maternal NASP for the early embryo. Genetic analyses are well conducted (but see my comments below) and the impact of NASP maternal mutant on H3 and H4 stockpiles is convincingly established by both quantitative mass spectrometry and Western-blotting.

Major comments:

• Although the authors used two independent deficiencies of the NASP genetic region to characterize their NASP CRISPR alleles, it is relatively standard in this type of functional analyses to perform rescue experiments using a transgene expressing the WT protein.

We thank the reviewer for this suggestion. As discussed in the cross consultation, we agree that the use of the two different deficiency lines and the NASP1 CRISPR control are clear lines of evidence that the phenotypical data are due to lack of NASP.

• In WB analyses, NASP appears systematically shorter in the NASP[1]/Df genotype compared to WT. Can the authors comment on this?

While we reproducibly see this change in migration, we can only guess as to why this may be. One possible reason is that the NASP1 mutant protein could be missing a post-translational modification. Proteomic data from Krauchunas et al. (Dev Biol. 2012; PMC3441184) shows that NASP has the potential to be regulated by phosphorylation. Therefore, the NASP1 mutant protein could be missing a phosphorylation. Intriguingly, the 6bp insertion is next to a Thr residue that could affect its ability to be phosphorylated (if it is phosphorylated at all). Since we can only offer speculation, we do not feel comfortable adding this to the manuscript.

• The authors do not mention the centromeric histone H3 variant Cid in their analyses. Do they have evidence that it is not affected by loss of maternal NASP?

We thank the reviewer for raising this great point. Our mass spec data reveals that Cid levels stay the same in the absence of NASP in both embryos and stage 14 egg chambers. We have edited Figures 3D and 3E to include Cid. Unfortunately, we did not identify any Cid-specific peptides in our IP-mass spec data.

• The authors could have chosen to explore in more details the phenotypic defects of embryos derived from NASP mutant mothers. Instead, a single abnormal embryo is shown with no cytological details. This is a bit problematic since an earlier study (Zhang et al 2018, cited in the manuscript) actually provided more phenotypic details of embryos from NASP KD mothers.

This issue was also raised by Reviewer 1. We have switched to Propidium Iodide (PI) staining to increase the signal-to-noise for DNA staining in early embryos. Given the improved signal we see with PI over DAPI, we will be able to provide both improved images of nuclear staining and assay for defects in chromosome morphology as suggested. We will include this data in the revised version of the manuscript. - Similarly, the authors could have used their anti-NASP antibody to analyze the distribution of NASP during cleavage divisions. Does it behave like ASF1, for instance, which enters S phase nuclei at each cycle or does it remain in the cytoplasm? These are relatively simple experiments/analyses that could increase the significance of the study.

This point was also raised by Reviewer 1. We have tried to use our antibody to monitor the localization of NASP in the early embryo. Unfortunately, the staining has yet to work. We will continue to alter fixation and permeabilization conditions in the early embryo with the goal of including this data in the revised manuscript. We have, however, been able to monitor NASP localization in Drosophila S2 cultured cells with our antibody. If we are unable to get the antibody staining to work in embryos, we will include the NASP localization data in S2 cells in combination with EdU labeling to mark cells in S phase.

Minor comments:

• line 60: I suggest to introduce Drosophila in the next sentence, where it seems more appropriate (not all embryos develop "extremely rapidly").

We have edited the second sentence to state “the early Drosophila embryo”.

• line 68: the 50% estimation of free histones does not really make sense without defining the embryonic stage.

We have edited the manuscript to state the specific cell cycle in which there has been 50% free histones measured. - line 89: Are the authors specifically referring to Drosophila NASP?

Yes, we have edited the text to include Drosophila in this instance. - lines 99-106: I found this paragraph redundant with the introduction.

We appreciate this suggestion. It was also pointed out by Reviewer 1. We have made changes to the manuscript to address the redundancy.

• line 142: H3-H4

Thank you for noticing this. We have edited the text to include 4.

• line190-191: It seems to me that data of Figure S2C are already included in Fig. 2E.

The data in FigureS2C was performed with virgin females compared to the data in Figure 2E that was generated with non-virgin mothers. This was important to control the genotype of the embryos.

• line 232: it is surprising that the Zhang et al paper (reporting maternal KD of NASP) is only mentioned here. As a reader, I would certainly prefer to have it presented right from the introduction.

We have edited the manuscript to include this reference in the introduction.

• Figure 4B needs a scale bar.

Figure 4B will be replaced with better images of the embryo stained with PI. It will also include images of chromosome morphology/segregation. We will be sure to include scale bars.

• line 302: Mentioning the identity and function of known H3/H4 histone chaperones acting in the early embryo (ASF1, HIRA, CAF-1, ...) could provide perspective to the present study.

Thank you for this suggestion. We have edited the manuscript to include functions of other histone chaperones in the early embryo to provide context.

• line 304: in contrast to this statement, I found quite surprising and interesting that NASP is not absolutely essential for embryo development considering its role. This should be discussed.

In the absence of Jabba alone, upregulation of translation can compensate for the destabilization of H2A, H2B, and H2Av. It is only when translation is inhibited in embryos laid by Jabba mutant mothers that embryos die (Li.Z, et al. Curr Biol 2013). Therefore, it is possible that translation can partially compensate for the degradation of H3 and H4 in the absence of NASP. This may be why a fraction of embryos laid by NASP mutant mothers are able to hatch and why we still detect some H3 in embryos laid by NASP mutant mothers. We have edited the manuscript to discuss this more in depth.

CROSS-CONSULTATION COMMENTS I fully agree with the other reports. The NASP rescue experiment is just a suggestion but is not essential.

Reviewer #2 (Significance (Required)):

This work clarifies the identity and function of Drosophila NASP and clearly demonstrates that NASP is important for the stabilization of maternal stockpiles of H3 and H4 during early embryo development. The conservation of NASP function as a histone H3/H4 chaperone in Drosophila is not really a surprise but the merit of this study is to establish this assumption as a fact. It also establishes useful tools (mutant lines and antibody) for the fly community interested in this topic. The study however does not provide new insights about the dynamic distribution of NASP and the cytological consequences of its maternal depletion on the amplification of cleavage nuclei.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary: Rapid cell cycles in early embryogenesis is driven from maternally supplied stockpiles of RNA and protein, including histones H3 and H4. This study uses sequence homology searches, biochemical approaches (immunoprecipitation and mass spectrometry) and genetics to identify NASP (CG8223) as the H3-H4 chaperone in Drosophila. Using CRISPR technology, the authors generate a NASP mutant fly line and show using genetic crosses that NASP is a maternal lethal gene. Furthermore the study shows that NASP stabilises H3-H4 during oogenesis and embryogenesis and is required for early embryogenesis.

Major comments: The key conclusions of this study are very convincing. For example, the authors use multiple approaches to show H3-H4 specific interactions with NASP and that H3-H4 protein levels are reduced in mutants (Western analyses, quantitative MS). Analysis is carried out on two individual NASP mutant lines (one deletion that produces no protein, one insertion that still produces some protein acting as a control). All experiments are well controlled, executed and presented. Genetic crossing schemes are well presented and statistical analysis of progeny is clear.

• We thank the reviewer for their positive feedback of our manuscript. Minor comments: In Figure 1B - Authors could indicate amino acids shown or are they full length proteins?

We have edited the methods to include specific amino residues that are included for each structure.

In Figure 2B - Authors could (semi) quantify reduction in NASP1 mutant to show this is a gene dose effect?

We have now included the quantification of the Western blot in Figure 2B.

CROSS-CONSULTATION COMMENTS I agree with the other reports. Although I did not indicate it in my original report, I agree that more in depth analysis of nuclear or chromosomal defects in NASP mutant embryos would enhance the study.

Thank you for this suggestion. We are repeating the DNA staining in embryos and will include this new data in the revised version of the manuscript.

Reviewer #3 (Significance (Required)):

Excess soluble histones can be toxic and must be bound to chaperones. Until this study the chaperone responsible for H3-H4 stabilisation in rapidly cycling cells in Drosophila embryos was not known. Moreover, the NASP homolog had not yet been identified in Drosophila nor had its function been characterised. The findings are of interest to Drosophila researchers, the field of chromatin assembly, as well as those interested in early embryogenesis in animals.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

An exciting development in our knowledge about how the Arp2/3 complex controls the assembly of actin networks has come from the discovery that in addition to forming branched networks, Arp2/3 can nucleate linear filaments when it is activated by WISH/DIP/SPIN90. However, despite some excellent work largely done by the Nolen lab in yeast, many questions remain about how Arp2/3-mediated assembly of branched vs. linear actin filament. This is especially true in the complex environment of cells, were synergy and competition of different actin networks is used to control biological processes. Knowing the biochemical and physical properties of these different Arp2/3 assemblies will be key to figuring out how they work in cells. Here Cao et al. use an elegant microfluidics based single filament assay system to perform a comparative analysis of the stability of linear and branched Arp2/3 networks. They find interesting differences in how they respond to stabilizing and destabilizing factors. The most striking differences happens when force or aging is applied- both cause debranching of branched networks but have little effect on Spin90-Arp2/3 nucleated filaments.

We thank the reviewer for their positive comments.

Major comments:

As a comparative study on the stability of branched vs. linear Arp2/3 nucleated filaments, this manuscript is fairly complete. The key conclusions are well supported by rigorous experiments which can be reproduced by others based on the information provided. However, I am not seeing explicit information on performing biological replicates. This should be included in the manuscript. The use of statistics is largely fine; however I question the use of one statistical test on one figure (see minor comments below).

The revised manuscript is now explicit about biological replicates. We now specify the biological repeats of all our experiments in the figure legends, and we now show the results from new repeats in Fig 4 and Supp Fig S2 (please see also our response to the minor comments below, for more details).

I would not ask for additional experiments at this time. However, there is an analysis that would be important for interpreting the authors' claims- branch/filament length at the time of dissociation or destabilization of Arp2/3. This would help address if there was a physical tipping point for each type of structure that could explain potential differences they see. The authors should already have this data and the time to complete it would be negligible in delaying publication.

If we understand correctly, the “physical tipping point” mentioned by the reviewer would be a threshold force, where the Arp2/3-filament interface would become unstable. This is an interesting idea. Indeed, the applied force scales with the length of the filament (or branch), as well as with the flow velocity. In most of our experiments, however, the force applied to SPIN90-Arp2/3 and to branch junctions was kept constant and below 0.2 pN. This was done by exposing the filaments (or branches) to G-actin at the critical concentration, in order to minimize variations of their lengths. Therefore, by design, dissociation events in these experiments take place at the same length, ruling out the existence of a “tipping point”.

Our data provide another test of the reviewer’s hypothesis, thanks to the experiments where we specifically address the question of the impact of force (Fig 5 and Supp Fig S6), by varying length and flow rate. We found that the stability of SPIN90-Arp2/3 linear filaments was unaffected by force, and that debranching was steadily accelerated by force. In both cases, it thus appears that there is no detectable threshold.

One additional major comment is that the manuscript's title and abstract hint that this paper explores the differences in nucleation of branched vs. linear filaments by Arp2/3. However, the only figure that deals explicitly with nucleation in the paper is Figure 1, which is really just a confirmation that the mammalian proteins used in this study perform similarly to their yeast homologues (Balzer et al, Current Biology 2019). The authors might think about rewording the title/abstract to better reflect that paper really explores the differences in the stability of the two networks

This is a fair point. We have now modified the title into “Regulation of branched versus linear Arp2/3-generated actin filaments”.

Minor comments:

1 in 12 men and 1 in 200 women are red/green colorblind. Please change the coloring of the schematics and images so that they can be easily seen by all people. This is especially true of the schematics, which are important for understanding exactly what each assay is measuring.

We thank the reviewer for pointing this out. We have now made the schematics and images in Figs 1A, 2A, 2D and 4D colorblind-friendly.

The Introduction is a bit choppy and unfocused. It was difficult to deduce exactly where the paper was going from it. Please consider re-writing it for better clarity. The Discussion on the other hand was fantastic. Great job on interpreting your results in a larger context.

We have re-written large parts of the Introduction to make it clearer. We are glad the reviewer liked the Discussion, where we have nonetheless made some small changes in response to comments from the other reviewers.

Many figures- while the use of different lightness values of the same color is appreciated in conveying different concentrations of reagents used, there were several instances where it was very hard to read the one on the very bottom (ex. 2B, E; 3A; 5C, G).

We have now changed the colors in these figures, to make them clearer.

Figure 1- since this is a confirmation of previous results performed using the same proteins from other species, the title should reflect that (ex. VCA domains accelerate the nucleation of filaments by mammalian SPIN90-Arp2/3). Also, to me this figure is supplementary to the main message of the paper. The authors might think of moving it to Supplementary Information.

We have modified the title of Figure 1, now specifying “mammalian”, following the reviewer’s suggestion. However, we prefer to keep this figure as a main figure, rather than move it to Supplementary as proposed. Indeed, this figure does more than simply confirm previous results with mammalian proteins, since it compares different VCAs, which is new. These results are important because they are put in perspective with our results on the acceleration of linear filament detachment by different VCAs, later in the manuscript.

Figure 1- If the goal was to verify that G-actin recruitment by VCA was important for Spin90-Arp 2/3 nucleation by performing a competition experiment with profilin, why was the concentration of G-actin AND profilin increased between the experiments in 1B vs. 1C. It makes it hard to directly compare the results.

We now provide new data in Fig 1C, which can be directly compared to Fig 1B (only the profilin concentration was increased). It clearly shows that the effect of VCA disappears when the profilin concentration is increased.

Figure 4B-F- Here, it would be nice to see the distribution of all the individual results, which are hidden by the bar graph. Additionally, the Chi-square test is not the appropriate test for evaluating statistical significance between multiple groups. ANOVA followed by an appropriate post hoc test should be used here.

We now show the individual results in the bar graphs of figure 4. In this situation, we agree that the statistical significance should not be evaluated by a Chi-square test. We now indicate the p-values obtained from a paired t-test, which seems appropriate since we are comparing averages in pairs.

Figure 4G- Please quantify and show reproducibility.

We now show quantified repeats (shown in Fig 4, new panels H and I).

Figure 5- the piconewton forces used for these experiments is in line with measured forces that are applied to actin in cells (ex. Mehida et al, Nature Cell Biology 2021; Jiang et al, Nature 2003). The text would benefit if this was explicitly stated.

We now state this explicitly, when presenting these results.

Reviewer #1 (Significance (Required)):

The real significance of this work is in characterizing the differential stabilities of linear vs. branched Arp2/3 filaments in response to actin-binding proteins, mechanical stress, and aging. While both types of filaments respond similarly to actin-binding proteins, with nuanced differences, the most striking results came from applied force and aging experiments, with Spin90-Arp2/3 filaments being much more resistant to both. This has some very interesting implications for how these two types of assemblies might synergize in cells. Additionally, the results also have some exciting implications for the pointed-end regulation of actin filaments, which is still poorly understood in complex systems. Since the manuscript is A) more of a survey study on the factors that influence filament stability that does not go particularly deep into any particular mechanism of regulation and B) has no direct applicability to how the physical properties of branched and linear Arp2/3 nucleated actin filaments influence actin network activity in cells, the audience will likely by limited to actin enthusiasts. However, the work is still important in both what it reveals and implies.

We thank the reviewer for pointing out the novelty and the importance of our work. We agree that the significance of our paper lies in the characterization of the differential stabilities of linear vs. branched Arp2/3 filaments, in response to different physiological factors. One of the strengths of our approach is that we do not focus on one regulatory mechanism in particular. Rather, we reveal fundamental differences between the Arp2/3-generated filaments and how they can be regulated. Understanding these basic mechanisms is a prerequisite to understand the regulation of entire cytoskeletal networks.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The quantitative analysis can be improved. It appears that most of the data results from single experiments, with rate values and errors resulting from fitting of single experiments without repetitions. In Fig. 1C legend (p.5) the authors state "These experiments were repeated three times, with similar results", but the data is not used in the analysis and other experiments do not mention this point. This is particularly important for comparisons among different VCAs that are rather similar in nature. In Fig. 1B. N-WASP is more efficient in nucleating SPIN90-Arp2/3 complex-linear filaments followed by WASP and then WASH. In Fig. 2 B,C, N-WASP is the most effective in dissociating SPIN90-Arp2/3 complex linear filaments followed by WASH and then WASP. But in Fig. 2 E,F, WASH is by far the most effective in dissociating branches followed by N-WASP and then WASP. Therefore, the conclusion in the Discussion (p.12) "While these regulatory proteins similarly affect branched and linear Arp2/3-generated filaments, they do so with clear quantitative differences" is not supported by quantification. To remedy this problem the authors should include at least 3 repeats of each experiment in data analysis. Also, they could include an analysis of sequence differences among VCAs and discuss how these may correlate with the observed differences. For instance, one WH2 in WASP vs. two in N-WASP.

Indeed, we argue that the two forms of activated Arp2/3 differ in their sensitivity to different VCA motifs, based on how these VCA motifs rank in their ability to destabilize branched and linear filaments (the VCA motifs also rank differently in their activation and co-activation of Arp2/3 to nucleate branches and linear filaments, but this result does not contribute to our discussion of how proteins interact with the activated Arp2/3). Following the reviewer’s suggestion, we now show repeats of these experiments (new Supp Fig S2), clearly showing that N-WASP is the most effective in dissociating linear filaments while the differences are milder for dissociating branches, with WASH being at least as effective as NWASP. We now also discuss how this observation could relate to differences in sequence between VCAs (Discussion section and new Supp Fig S9).

Also, please note that, following a suggestion from Reviewer 3, we have now performed experiments with the CA-domains of NWASP (new Supp Fig S4C and S4D), which show that the V-domain plays an important role in debranching but plays no role in destabilizing SPIN90-Arp2/3 at filament pointed ends. These new results reinforce our statement that VCA affects branched and linear Arp2/3-generated filaments differently.

Reviewer #2 (Significance (Required)):

Arp2/3 complex is a 7-protein complex implicated in actin filament nucleation and branching. Arp2/3 complex-nucleated branched networks are found at several locations in cells and are responsible for processes such as cell motility.

Cao et al. compare the effect of several proteins on the filament nucleation activity of Arp2/3 complex, and the stabilization or destabilization of actin filament branches as well as linear actin filaments nucleated by SPIN90-Arp2/3 complex. The proteins tested include the VCA regions of three NPFs (N-WASP, WASP, and WASH) that activate Arp2/3 complex, GMF (a debranching protein) and cortactin (a branch stabilizing protein). For the most part, the study uses a single method, microfluidics-TIRF microscopy.

The main findings are:

1. VCA domains enhance nucleation of linear filaments by SPIN90-Arp2/3 complex in the presence of actin monomers.
2. However, VCA domains can also destabilize existing SPIN90-Arp2/3 complex linear filaments and branches, and this effect depends on the presence of of V-domain (WH2 domain that binds actin monomers).
3. The debranching factor GMF also destabilizes SPIN90-Arp2/3 complex linear filaments. Both GMF and VCA generate free pointed ends by dissociating Arp2/3 complex from pointed ends and SPIN90.
4. SPIN90-Arp2/3 complex linear filaments are less susceptible to force and aging than filament branches.
5. Cortactin stabilizes SPIN90-Arp2/3 complex linear filaments to higher degree than it does branches. These are novel and very interesting new observations of significant interest to the actin cytoskeleton field. Therefore, I recommend publication of this paper in EMBO J.

We thank the reviewer for their positive evaluation of our work.

I have one recommendation and one suggestion for improvement:

Major:

1. The quantitative analysis can be improved. It appears that most of the data results from single experiments, with rate values and errors resulting from fitting of single experiments without repetitions. In Fig. 1C legend (p.5) the authors state "These experiments were repeated three times, with similar results", but the data is not used in the analysis and other experiments do not mention this point. This is particularly important for comparisons among different VCAs that are rather similar in nature. In Fig. 1B. N-WASP is more efficient in nucleating SPIN90-Arp2/3 complex-linear filaments followed by WASP and then WASH. In Fig. 2 B,C, N-WASP is the most effective in dissociating SPIN90-Arp2/3 complex linear filaments followed by WASH and then WASP. But in Fig. 2 E,F, WASH is by far the most effective in dissociating branches followed by N-WASP and then WASP. Therefore, the conclusion in the Discussion (p.12) "While these regulatory proteins similarly affect branched and linear Arp2/3-generated filaments, they do so with clear quantitative differences" is not supported by quantification. To remedy this problem the authors should include at least 3 repeats of each experiment in data analysis. Also, they could include an analysis of sequence differences among VCAs and discuss how these may correlate with the observed differences. For instance, one WH2 in WASP vs. two in N-WASP.

This comment is identical to the reviewer’s first paragraph. We copy our answer here again, for convenience:

Indeed, we argue that the two forms of activated Arp2/3 differ in their sensitivity to different VCA motifs, based on how these VCA motifs rank in their ability to destabilize branched and linear filaments (the VCA motifs also rank differently in their activation and co-activation of Arp2/3 to nucleate branches and linear filaments, but this result does not contribute to our discussion of how proteins interact with the activated Arp2/3). Following the reviewer’s suggestion, we now show repeats of these experiments (new Supp Fig S2), clearly showing that N-WASP is the most effective in dissociating linear filaments while the differences are milder for dissociating branches, with WASH being at least as effective as NWASP. We now also discuss how this observation could relate to differences in sequence between VCAs (Discussion section and new Supp Fig S9).

Also, please note that, following a suggestion from Reviewer 3, we have now performed experiments with the CA-domains of NWASP (new Supp Fig S4C and S4D), which show that the V-domain plays an important role in debranching but plays no role in destabilizing SPIN90-Arp2/3 at filament pointed ends. These new results reinforce our statement that VCA affects branched and linear Arp2/3-generated filaments differently.

Minor:

In GST-pull-down experiments (Fig. 4G), the amount of Arp2/3 complex bound is analyzed by Western, which is rather unprecise. Is the amount of Arp2/3 complex so little that it cannot be quantified using regular SDS-PAGE? If that is the case, this would suggest rather low affinity of SPIN90 for Arp2/3 complex. How does this affect the proposed mechanism and experiments in the microfluidics chamber?

Indeed, the amount of pulled-down Arp2/3 is low and difficult to quantify by SDS-PAGE. This is consistent with previous reports which indicate a low affinity of SPIN90 for the Arp2/3 complex (Wagner et al. Current Biology 2013, Balzer et al. eLife 2020). This does not affect our conclusions, which we now confirm by showing quantified repeats of our pull-down experiments (new panels H and I, in Figure 4). In spite of this low affinity, which makes it difficult to saturate SPIN90 with Arp2/3, the SPIN90-Arp2/3 interaction is very stable and allows us to carry out our experiments in the microfluidics chamber over several tens of minutes (as was already the case in our previous study, Cao et al. NCB 2020).

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary:

In this study, Cao and collaborators investigate the biochemical and mechanical differences between branched actin filaments nucleated by WASP-activated Arp2/3 complex and linear actin filaments nucleated by SPIN90-activated Arp2/3 complex. They use TIRF microscopy in a microfluidic chamber to show that the mammalian proteins, SPIN90 and WASP (or N-WASP or WAVE), like their yeast homologues, co-activate Arp2/3 complex to nucleate linear actin filaments. Using the same assays, they find the surprising result that the VCA segment of WASP proteins destabilizes the interaction between SPIN90 and Arp2/3 complex in linear actin filaments nucleated by Arp2/3 complex. They then show that VCA also destabilizes actin filament branches. The remainder of the study explores the influence of branch stabilizing/destabilizing proteins or mechanical stress on the stability of the interaction between SPIN90 and Arp2/3 complex on the pointed end of the actin filament. They find that like branch junctions, SPIN90-bound Arp2/3 is destabilized at the end of linear filaments by GMF and stabilized by cortactin. However, unlike branch junctions, SPIN90-Arp2/3 complex is not destabilized on filament ends by piconewton forces or by aging. They conclude that SPIN90- versus VCA-activated Arp2/3 complex adopt similar but non-identical conformations.

Overall, the paper is well written and the experiments, which are very challenging, are rigorously executed. The biochemical results are convincing, novel and unexpected. However, the work could be strengthened by more strongly connecting the biochemical observations to biological implications. In addition, there are some interpretations/conclusions that seem somewhat weakly supported, and the authors should consider revising. Nonetheless, given the quality of the work and the importance of the system, this manuscript will appeal to a broad audience.

We thank the reviewer for their positive comments. We have rewritten parts of the Discussion in order to better connect our observations to implications in cells. We address the concerns regarding our interpretations in the point-by-point, below.

Comments on evidence, reproducibility, clarity and significance:

The differences in the stability of SPIN90-Arp2/3 on linear filaments verses branch junctions led the authors to conclude that SPIN90- versus VCA-activated complexes adopt similar yet non-identical conformations. There are two problems with this conclusion:

1) This conclusion rests on the idea that the biochemical differences can only be due to differences in the "ground state" active conformations of the complex. Another possible scenario would be that the active conformations are the same, but the transition state or intermediate state structures within the debranching reactions are different, thus changing the kinetics of the debranching reactions.

We thank the reviewer for this remark, and we agree that conformational differences may also arise in the intermediate states, during dissociation (of the branch from the mother, or of the linear filaments from SPIN90). We now mention this possibility in our Discussion.

2.) There are already structural data showing conformational differences between the Dip1-bound Arp2/3 complex on the end of a linear filament and Arp2/3 complex at a branch junction. While there are some caveats to comparisons of the structures (e.g., the Dip1 structure includes the fission yeast SPIN90 protein (Dip1) and the fission yeast Arp2/3 complex while the branch junction contains mammalian proteins), these data offer much stronger evidence that the active states adopt (somewhat) different conformations than the data presented here.

We agree that the available structural data (in particular, Ding et al. PNAS 2022, which was not yet published when we submitted our manuscript, and which we now cite) provide a clear indication that active Arp2/3 adopts different conformations in branches and linear filaments. We have modified our text to make this point clearer.

The authors make comparisons between the Fäβler branch junction structure and the Shaaban Dip1-Arp2/3-filament structure. The Fäβler branch junction structure is a low resolution structure (9 angstroms) and should be interpreted with caution (see below). A much higher resolution of a branch junction structure was recently solved (Ding et al, PNAS 2022) and should be used for comparisons between the structures.

Ding et al. PNAS 2022 was not yet published when we submitted our manuscript. We now use it to compare the structures of active Arp2/3, and we have modified the text accordingly.

Pg 14 - The authors say differences between ARPC3-Arp2 and ARPC5-Arp2 contacts in the two structures are likely to cause the differences in interactions with GMF and VCA. Two concerns with this statement are: 1.) The basis for the conclusion that the ARPC5-Arp2 contacts are different (in Fäβler, et al.) is not solid (see Ding, et al) and 2.) The analysis is vague. To reasonably conclude that differences in the contacts would influence GMF and VCA interactions would require mapping out the structural connection between the ARPC3-Arp2 interaction site and the GMF or VCA binding sites. If there is no obvious connection between these sites, the conclusion that the differences in the ARPC3-Arp2 interface cause differences in VCA and GMF binding should be far more circumspect.

We have re-written this part of the Discussion section. In light of the new data by Ding et al., we agree with the reviewer that the conclusion that the ARPC5-Arp2 contacts are different is not solid. Our revised text makes it clear that we are not making any claims involving interactions within the Arp2/3 complex. Our point is simply that recent cryo-EM reports indicate conformational differences in Arp2 and Arp3 between the two activated forms of the Arp2/3 complex and that, since the CA-domain of NPFs bind to Arp2 and Arp3, it appears reasonable to make a connection with our results.

Pg 6. "These observations suggest that the ability of VCA to destabilize Arp2/3-nucleated filaments relies on the availability of its V-domain." It's possible that G-actin binding to V blocks the CA from accessing the branch junction. Therefore, it seems important to test whether N-WASP-CA can destabilize Arp2/3-nucleated actin filaments.

We thank the reviewer for this suggestion. We now present results from new experiments performed with the CA-domain of NWASP (new Supp Fig S4C,D). We find that the V-domain participates in the enhancement of debranching, but that it appears to play no role in the destabilization of SPIN90-Arp2/3 from the pointed end. It thus seems that the reviewer’s proposal is correct, and that G-actin binding to the V-domain blocks the CA-domain from accessing the branch junction. We now propose this interpretation in the text.

Pg 1 - The authors state that "It thus appears that linear and branched Arp2/3-generated filaments respond similarly to regulatory proteins, albeit with quantitative differences". It is worth considering if one should make a blanket statement that linear and branched filaments respond similarly to regulatory proteins when they have tested 3 in total.

We have rephrased this sentence. It now reads “… respond similarly to the regulatory proteins we have tested…”

Pg 3 - "More generally, the stability of SPIN90-Arp2/3 at the pointed end, which is important to understand the reorganization and disassembly of actin filament networks, remains to be established." In some ways this statement not quite accurate because Balzer et al previously showed that Dip1-Arp2/3 complex is very stable at the pointed end. Is the question here whether that stability is also conserved in mammalian systems? If so, that should be more directly stated.

We meant that, beyond observing that SPIN90 remains visible at the pointed end for some time (as in Balzer et al.), a lot remained unknown: its lifetime had not been quantified, and its sensitivity to the factors that affect branch junctions (proteins, aging, mechanical tension) had not been studied. We have rephrased the sentence in the manuscript to clarify this point.

The observation that VCA accelerates debranching and SPIN90-Arp2/3 dissociation is very interesting. However, it is uncertain if this biochemical activity has biological relevance, given that once nucleation occurs, Arp2/3 complex will move away from the membrane. While the authors mention in the discussion that debranching by VCA could be relevant when the network is compressed near the membrane, this argument is not particularly strong. Are there ways to strengthen this argument, or find another impact this finding might have on our understanding of Arp2/3 complex regulation?

We now mention another situation where branch junctions could encounter membrane-bound VCA domains: on the dorsal and ventral membrane surfaces of lamellipodia. We now cite the recent Kage et al. J Cell Science 2022 and Mehidi et al. NCB 2021, where WAVE has been observed in lamellipodia away from the leading edge.

The observation that SPIN90+Arp2/3-nucleated filaments are not sensitive to piconewton forces is also very interesting. The authors focus on the differences in the amount of surface area buried when discussing this result. However, if seems a key factor in the stability of the linear filaments would be the direction of the force relative to the complex and attached filament(s), which would be very different for a branch versus a linear filament. The authors should consider addressing this in their discussion.

The orientation of the applied force is an interesting point. In their study on debranching, Pandit et al. (PNAS 2020) report that their results are not affected by the angle of the applied force relative to the mother filament (their Fig S1D). We now specify this in our manuscript, when introducing our results on mechanical tension. Similarly, we found that anchoring SPIN90 to the coverslip surface by its N-terminus rather than its C-terminus, which likely affects the orientation of the applied force, had no impact on our results (Supp Fig S6A). We have now also added a sentence regarding this aspect in our manuscript, after presenting this result.

Fig 4, D-F: It is unclear how the authors determined which filaments were spontaneously nucleated versus those that were nucleated by SPIN90-Arp2/3 complex in these experiments. In reactions containing SPIN90 and Arp2/3 complex what fraction of the filaments will be spontaneously nucleated?

In our conditions, there is no detectable spontaneous nucleation. In control experiments where we flow in the same concentration of G-actin, in the absence of Arp2/3 or in the absence of SPIN90, we observe no filaments at all on the surface, over several fields of view, after 5 minutes. We now specify this in the Methods section.

Pg 9 - The observation that VCA negatively influences binding of SPIN90 to the complex is unexpected. What implications does this have for understanding how SPIN90 and VCA synergize to activate the complex?

It appears that the outcome depends on the context. The main role of VCA during co-activation of the Arp2/3 complex with SPIN90 seems to be to supply G-actin, as already proposed (Balzer, 2020) and confirmed by our results (Fig 1C). In the absence of G-actin, VCA is more likely to remove Arp2/3 from SPIN90 (Fig 4G,I). Similarly, when a filament is already formed, the presence of G-actin mitigates the removal of SPIN90-Arp2/3 from the pointed end by VCA (Supp Fig S4).

Fig 4B - Why is there greater nucleation when Arp2/3 complex and GMF are added together compared to renucleation in reactions that don't have any GMF? This is surprising, especially considering that GMF decreases binding of Arp2/3 complex to SPIN90.

Indeed, there is a small yet statistically significant difference in the re-nucleation fraction we measured in the presence of Arp2/3, with or without GMF (Fig 4B). This may be due to the different timescales of the two situations. In the absence of GMF, the detachment of filaments is slow and new filaments are nucleated from the initial Arp2/3 complexes, which remained bound to SPIN90 upon detachment of the first filaments. In contrast, in the presence of GMF, detachment is faster and accompanied by the departure of the initial Arp2/3, and a fresh Arp2/3 then binds to SPIN90 to nucleate a new filament. It is thus possible that, in the absence of GMF, a small fraction of the SPIN90 and/or their initially bound Arp2/3 complexes would denature over the time they spend at the bottom of the microchamber at 25°C, thereby leading to a slightly smaller re-nucleation fraction. A similar mechanism could be at play in the experiments with or without VCA, in addition to the enhancement of nucleation by VCA (Fig 4C).

Minor Corrections/Comments

Pg 3 "We show that Arp2/3 nucleation is similarly stabilized by cortactin and destabilized by GMF" Do the authors mean branches and linear filaments nucleated by Arp2/3 complex?

Yes, that is what we meant. This sentence has now been modified.

Pg 6- The cyan 3uM data and legend in figure 2B and E is probably too dim to see clearly.

The colors have been changed to improve readability.

Fig 4 B,C,E,F: It would be best to show the individual data points here if possible.

We now show individual data points in all these figure panels.

Pg 16 Please specify which antibody was used to anchor SPIN90.

The antibodies are Anti-GST for Nter anchoring of GST-SPIN90, and anti-His for Cter anchoring of SPIN90-His. We now specify this in the Methods section.

CROSS-CONSULTATION COMMENTS I agree with the points that the other reviewers raised.

Reviewer #3 (Significance (Required)):

Comments on significance are in the above section.

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Reply to the reviewers

We thank all three reviewers for their thoughtful and rigorous critique of our manuscript, which we feel has significantly improved the presentation of our work. Below we detail point-by-point responses to comments made by the three reviewers as well changes we have already made addressing the majority of minor and some major points.

Specification of the eye-field during gastrulation represents the earliest known stage of eye development. Using an optic-vesicle organoid model system, the overall goal of our work is to provide an unbiased characterisation of this critical, early developmental event in mammals and to gain insights into relevant gene regulatory mechanisms. A common theme to some of the reviewer comments is that this work doesn't provide much of an advance to the field and our findings are not particularly original. We feel that these comments are slightly harsh for the following reasons. Firstly, although some of our findings are not unexpected, to our knowledge, this is the first unbiased characterisation of the eye-field in a mammalian model system, and not based on knowledge gained through previous work in other non-mammalian vertebrate systems, e.g. Xenopus. Secondly, by generating both RNA-seq and ATAC-seq from a timecourse of organoid development we have been able to quantify dynamic patterns of gene-expression as the eye-field is established and simultaneously gain insights to the regulatory role of some of the key transcription factors, both of which are not present in the literature. Thirdly, by constructing careful, integrated analyses of our RNA-seq and ATAC-seq datasets we were able to generate specific hypotheses regarding cis-regulation of key genes, which we have then demonstrated are possible to efficiently test within the organoid system. In all, although we have been purposely careful not to overinterpret our results, we feel our work does represent a significant step towards understanding the mammalian eye field and additionally provides important datasets as well as an analysis framework to begin to quantitatively probe the regulatory mechanisms underlying the transition to an ocular fate. Given the relevance of this developmental event to clinical genetics research as well as to developmental biology we are confident that this work represents an important and significant advance to the literature.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary Owen et al. characterize the transcriptome and chromatin accessibility of mouse retinal organoids at early stages during which eye field-like cells are specified. Since cell specification and differentiation in retinal organoids largely mimic those processes in vivo, retinal organoids are viable models for studying the mechanisms of early eye development. Owen et al. utilize a previously established Rx-GFP cell line, bulk RNA sequencing, and bulk ATAC sequencing to dissect the mechanisms of early eye development in mice. Their findings are generally consistent with previous studies. Overall, the study is interesting for the field, but its conceptual and technical advances are moderate. In addition, a few major points need to be clarified.

Major points 1. The authors did not show any analysis of retinal organoids at stages when Vsx2 is expressed. This is a significant weakness since the chemically defined medium (CDM) used in Owen et al.'s study was previously shown to induce rostral hypothalamic differentiation (Wataya et al., 2008). Related to this notion, several eye-field transcription factors, such as Rax and Six3, are also expressed in the hypothalamus. Therefore, Owen et al. need to demonstrate that organoids in their modified differentiation system efficiently produce Vsx2-positive retinal progenitors, and samples of organoids at stages when Vsx2 is expressed should be included for RNA sequencing. If Vsx2 is not efficiently expressed in their organoids, the interpretation of results will be very different.

We thank the reviewer for their important comments here. There are several reasons why we are confident that our data and conclusions regarding the organoid eye-field are robust. Firstly, our RNA-seq data, in particular the differences between GFP-positive and GFP-negative cells, clearly show a coordinated up-regulation of the set of canonical eye-field TFs (not individually), which previous studies in Xenopus have shown is a prerequisite for differentiation into anterior eye structures (including retina). Secondly, we have checked that some of the later (in development) eye markers, including Vsx2, are differentially up-regulated (DeSeq2, logfc>1.5, FDRIn all, we are very confident that our approach of using the optic-vesicle organoids and generating molecular data from an organoid developmental timecourse (including sorting), is unpicking the ocular-fate transition event that we are interested in.

1. The authors state that "two differentiation medias were used for this work due to the differentiation becoming unstable after the initial experiments had been performed. The organoids used for RNA and ATAC-seq were grown in CDM media and the organoids with mutations introduced in potential CREs were grown in KSR media". Why the differentiation becomes unstable after the initial experiments? Differences in the two media cause additional complexities. Related to this notion, "WT Rx-GFP" in Figure 4B and 4E appears to show a different expression pattern compared to that in Figure 1A.

We were unable to identify the reason behind the destabilisation of differentiation in CDM media after the cell lines had been through CRISPR despite thorough testing. The differentiation of these cell lines was stabilised enough using KSR media such that every batch of organoids grown contained some organoids that expressed GFP in a pattern similar to what we had seen before and we carried on our experiments using this. We recognise that using two different media adds complexity, however we see the same patterns of organoid growth and GFP expression when differentiating untransfected WT Rax-GFP cells in both of these medias. We have edited Fig.S1 to include representative images of organoids grown in KSR media which can be directly compared to those grown in CDM shown in Figure 1A.

The reviewer has pointed out that the WT Rx-GFP organoids in Figure 6B and 6E show a different expression pattern to those in figure 1A. With the addition of the supplemental figure mentioned above it becomes apparent that these differences are not due to the change of media. We have clarified in the text that these WT cells have also been transfected so as to act as appropriate controls that have been treated identically to the CRISPR edited cell lines and that this has affected their differentiation capacity.

1. Is the deletion of Rax and Six6 regulatory elements homozygous? Sanger sequencing or amplicon sequencing is needed to show the deletion.

The deletions are homozygous (we have stated this in the manuscript text) and as suggested we have added a supplementary figure showing the Sanger sequencing traces for the WT and mutant cell lines used in this study.

1. The deletion of Rax and Six6 regulatory elements appears to cause minor changes in the expression of Rax and Six6 (Figure 6C, F). Therefore, the impact of findings in bulk RNA seq and bulk ATAC seq in this study is still unclear.

We have added a sentence to the text underlining that developmental genes are expected to be regulated by multiple enhancers. Our expectation is therefore, that in perturbing a single putative regulatory element for Rax/Six6, we will very likely not see the complete ablation of Rax/Six6 expression.

1. Retinal organoids and sorted cells are composed of heterogeneous cell populations. Bulk RNA seq and bulk ATAC seq do not have the power to dissect the complexity of heterogeneous cell populations. Single-cell RNA seq and single-cell ATAC seq are more powerful for this study.

We agree with the referee about the fact that the organoids are likely composed of relatively heterogeneous cell populations. We have added this limitation of our generated datasets in a “limitations” paragraph in the discussion.

1. Numerous motifs in the JASPAR database are identified using in vitro assays and have not been validated using in vivo assays. Unexpected results in motif analysis could be due to the differences in DNA binding motifs between in vitro and in vivo conditions. This notion should be added in the discussion.

We have added a couple of sentences in the discussion section, highlighting that TF-motif and footprinting analyses of ATAC-seq data provide indirect evidence of TF binding, and to validate these findings experiments such as ChIP-seq or Cut&Run could be performed in the future.

Minor points

Numerous labels in figures are too small.

We have adjusted the size of a number of the figures to increase the size of the labels, which are now mostly the same size as the text in the corresponding figure captions. We are very happy to make further increases in the sizes of figure labels/text upon recommendation.

CROSS-CONSULTATION COMMENTS

My fellow reviewers identify similar major weaknesses and additional points. I agree with the other reviewers' comments.

Reviewer #1 (Significance (Required)): Nature and Significance of the advances In Owen et al.'s study, the Rx-GFP cell line and retinal differentiation protocol were established in previous studies (Wataya et al., 2008; Eiraku et al., 2011); bulk RNA sequencing and bulk ATAC sequencing are standard procedures. Although candidate regulatory elements for early eye development are identified, deletions of two prioritized elements using CRISPR/Cas9 only cause minor changes in the expression of targeted genes. Overall, conceptual and technical advances in Owen et al.'s study are moderate. Compare to existing published knowledge The datasets could be useful for the field, but conceptual and technical advances are moderate.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

The authors grow eye organoids from cells with a reporter driving GFP in the Rax locus, a gene that is expressed in the eye field in many animal model systems. They show that expression of GFP picks up by day 4 and performed FACS sorting of GFP+ cells on day 4 and day 5 organoids to compare gene expression by RNAseq comparing with earlier day organoids. The data shows 37 genes with a differential expression on days 4 and 5, compared to day 3, and enriched in GFP+ cells, which they define as EF-up genes. It is notable that some of these genes had already been identified as canonical eye field gene regulatory network transcription factors. In the same way, they identify a group of differentially expressed regulated genes, EF-down, and state that 'many' of them are involved in pluripotency. However, they do not mention how many, or the proportion of these genes in the whole list.

The number of EF-down genes with GO terms linked to pluripotency has now been added to the text.

It would be useful if they could provide the number to understand how many of these genes are related to pluripotency, the whole list of genes mentioned to be downregulated in a supplementary file.

We appreciate that this list was missing and will include it now as a supplemental file.

The authors also note that genes known to be required for eye specification like Sox2 and Otx2 are not differentially expressed across the day 3-4 timepoint (Ln 190). However, this is not surprising considering that both genes are broadly expressed in the anterior neural ectoderm and required for its specification, which should be noted by the authors.

We have amended the aforementioned sentence to reflect this: “It is noteworthy that Sox2 and Otx2, known to be crucial in eye development are not differentially expressed across this critical time-point (Fig.2A), consistent with these genes being more broadly expressed in the anterior neuroectoderm in vivo.”

The authors then go on and cluster the EF-up, EF-down and genes deferentially expressed between days 2 and 3, and identify 6 discreet trajectory groups. From this analysis, they identify a third group of genes which shows a peak on day 3 but whose expression falls on days 4 and 5. It is interesting to see that this group includes Wnt and Fgf morphogenes. The authors should provide a list of the genes in the different clusters for the readers to inspect and analyse.

We note that there was a typo in the original manuscirpt and the genes that were clustered were the EF-up and EF-down genes. This typo has been fixed and the requested information is now available in a supplementary file.

Aiming to generate insight into the cis-regulatory elements that regulate of the genes the authors found differentially expressed in their model system they performed a series of ATAC-seq experiments. When linking the genomic regions with differential ATAC-seq accessibility to gene locus using the GREAT analysis, they identified association to 22 of the EF-up and 161 of the EF-down genes. This suggests a functional link between the ATAC-seq genomic regions and the gene regulation of the differentially expressed genes.

The authors later screened the ATAC-seq regions of increased accessibility for TF binding motifs and found that these regions were enriched with motifs for EFTF genes Rax, Lhx2 and Pax6. When assessing motifs in the ATAC-seq regions in EF-up TADs, Rax and Lhx2 motifs scored highly associated to open chromatin positions. Authors also observe a positive gene expression-accessibility correlation between in Pax6, Lhx2, Six3 and Otx2, and suggest this could mean these genes activate transcription of the EF-up group of genes. The same analysis, but focusing on EF-down genes, suggests that EFTFs repress the expression of EF-down genes which include those involved in pluripotency.

Further interrogating the ATAC-seq data, the authors use TOBIAS footprinting analysis to identify changes in TF binding in EF-TADs and EF-up motifs. Remarkably, whole genome analysis reveals that the largest increase in motif binding corresponds to EF-up genes Rax, Pax6 and Lhx2. The authors then narrow down on specific gene regulation by studying the ATAC-seq data within the TAD of Rax and Six6. However, they do not explain the rationale for which these two genes were highlighted, and why Pax6 or Lhx2 were excluded. This explanation should be added to the manuscript.

We have expanded this section of the manuscript to explain that Rax and Six6 were prioritised due to the GFP readout of Rax expression and Six6 being located in a smaller and thus less complex TAD than Pax6, Six3 and Lhx2 after the initial analysis was performed for all five TADs.

The analysis identifies three regulatory elements in the Rax TAD and two for Six6. They then go on and study one putative regulatory element of each gene and generate CRISPR deletions in cell lines. The rationale for the choice of these particular elements is not clear, nor if the cell lines are the same used for the RNAseq experiments. This information should be explicit in the results and in the methods section.

The manuscript has been updated to include the rationale behind our choice of the regulatory elements deleted.

The authors mention that the CRISPR cell lines are "considerably more variable" (Ln 822) compared to the previously studied organoids and suggest that no conclusions can be driven from GFP expression or morphology alone. However, they do not specify which is the variable trait. This information should be added to the text.

We have amended the text to include that the organoids are more variable in terms of the OV like structures produced and GFP expression level.

The authors also miss out on specifying the time stage of the organoids in figure 6 which should be stated.

We thank the reviewer for pointing this out and have updated the manuscript to contain the stage of the organoids.

Regardless, the wildtype organoids in figure 6 and figure S7 show a very different morphology and GFP expression compared to those in figure 1, suggesting that the conclusions from this last set of experiments are not reliable or comparable to those in figure 1. This, together with the fact that different reagents were used to grow the organoids for the RNAseq and the CRISPR experiments, is a weakness of this work that must be addressed.

We recognise this weakness however our amendments detailed above in response to reviewer 1’s comments, including adding a figure showing WT organoids grown in the KSR media that closely resemble the organoids in Fig.1A, removes the uncertainty that it is the change in media producing these differences in morphology and GFP expression.

Our aim in this section was to specifically test the hypotheses regarding the regulatory nature of the distal genomic regions identified by our intra-TAD analyses of ATAC-seq data. To do this it was important to compare organoids derived from wildtype and mutant cells that had been subjected to the same growth conditions and genomic-editing protocols. The stress associated with the latter is what we expect has resulted in the differences in morphology and GFP expression compared with the original Fig1. organoids (which have not been through this procedure).

The last part of the results section belongs to the discussion as no results generated by the researchers are included.

Although no new data was generated for this section, we have used the data generated in our work, together with existing ChIP-seq datasets to construct a new plausible hypothesis regarding the activation of Rax-expression through changes in TF-binding at an enhancer displaying little/no change in accessibility. As this section ties in with previous results sections discussing the regulation of eye-field genes, we feel it belongs in the results section rather than in the discussion.

The discussion in this paper is a good opportunity to state the limitation of this study.

As requested, we have added a paragraph discussing the main limitations to our study in the discussion section.

Major comments to address

1. One of the main issues identified is that the morphology of the control conditions in the CRISPR experiments (Fig.6) do not look is that those used for the RNAseq experiments (Fig.1) and the authors should address this issue. The fact that CDM media was used on the RNA extraction and ATACseq experiments and then KSR media was used for the CRISPR experiments is worrying and makes one wonder whether the second set of experiments is at all comparable to the first. This should be somehow controlled carefully by at least replicating one set of RNA experiments with the KSR media.

We have addressed this in response to the reviewer’s summary above. Unfortunately, it is not possible for us to replicate the RNA experiments in the KSR media due to the research group closure upon Professor FitzPatrick’s retirement.

1. The requirement of Wnt signalling inhibition has been well established as a requirement for forebrain specification, including the eye field. Considering the link of the Wnt/beta-catenin pathway to eye specification and that TCFs, the transcription factors that mediate Wnt pathway transcription regulation, have known and well-studied DNA motifs, it is surprising that authors do not include the analysis of TCF motifs in their study. Also considering that TCF7l1 (TCF3, old nomenclature) has recently been shown to be cell-autonomously required for the expression of rx3 (Rax homologue) in zebrafish. One would expect TCFs to be included in the analysis as it was done with Sox2 and Otx2, which were studied due to the known relevance in forebrain specification rather than from the direct analysis of the differential gene expression experiments.

We thank the referee for their valuable comment here. Our current analyses indeed do not consider TCFs and are therefore likely incomplete. We plan to address this by further analysing our data to quantify the patterns and effects of the TCF genes, and will appropriately amend our manuscript to reflect our findings.

Minor comments to address

1. The authors should clearly state the day timepoint used in the organoids experiments in the results section and figure legends, not just in the methods.

We have updated the text and figure legends to include the time point of all organoids.

1. The report by Agnes et al Development 2022 should be cited in the introduction as it is an excellent paper related to this topic, including a comprehensive analysis of the EFTFs expression pattern.

We thank the reviewer for pointing us to this very interesting paper. Although we feel it doesn’t fit in with our introduction that is currently tailored to the set of genes that has historically defined the eye-field (and which was discovered in non-mammalian models), we do recognise that the 3D organisation of the eye-field and in particular the patterns of gene-expression defining different regions of this is important to disentangle in mammalian systems. We have therefore inserted a reference to the Agnes at al 2022 study on the dimorphic teleost in our extended discussion.

1. Ln 41. Mutations in these genes do not always cause severe bilateral eye malformations. Probably best to moderate and mention that they 'can' cause these malformations.

As suggested we have softened this sentence to: “ Mutations in at least three of the genes encoding orthologs of the Xenopus EFTF can cause severe bilateral eye malformations in humans (OTX2, PAX6 and RAX) (Fitzpatrick and van Heyningen, 2005).”

1. Ln 146. Authors mention that in vitro organoid systems "closely mimic the in vitro regulatory dynamics". This statement should be moderated as we do not know if this is true. In fact, one of the positive aspects of this study is that it contributes to supporting this statement.

We agree with the referee regarding the strength of this original statement. We have changed this to:

“We have exploited a reproducible, in vitro organoid model system enabling us to generate data from this cell-state transition and through computational analysis gain a quantitative understanding of the underlying regulatory mechanisms.”

1. Ln 150. Rax homologue Rx3 is also expressed in cells that give rise to the hypothalamus in zebrafish and cavefish, and probably in Xenopus too. It could well be the case in mice too.

We have corrected this to indicate that Rax is also expressed in the hypothalamus in mice.

1. I do not think the GO term data adds much to Figure 1. If possible, I would move it to the supplementary section.

We have moved the GO visualisations to supplementary, Fig.S2.

1. It should be made clear which set of experiments was performed as biological replicates and which did not.

We have added details on the number of replicates used in each experiment.

1. Based on the heatmap in Fig1A, expression of Rax is significant in GFP- cells at days 4 and 5. The authors should comment or discuss this.

We have amended the text and supplemental methods section to include more details of our FACS protocol. The limitations of our sorting procedure include the fact that cells are not sorted into pure GFP expressing and non-expressing populations. Rather the GFP negative sample may contain some cells with low Rax expression or cells that have just begun to express Rax that were not excluded by our sorting. Our aim was to collect sufficient numbers of cells for each condition and separate out cells that expressed GFP to get a more uniform population of cells to study. It is also of note that the heatmap shows Rax expression by day 3. Although it was not detectable by imaging there were around 100 cells per organoid that FACS marked as GFP positive but were retained within the day 3 sample to ensure we had a complete picture of the gene expression at this time point.

1. Ln 99 of materials and methods mentions that the sorting of GFP+ was performed "when possible". The authors should state the differences in the conditions in the different experiments.

This has been expanded to detail exactly how cells were sorted.

1. The sentence closing the first section of the results (Ln 270) is an overstatement and should be moderated. I cannot see how the results shown in this section on their own could reflect and drive solid conclusions on brain cell fate specification.

We agree with the referee and have changed this sentence to: “In summary, these first analyses of RNA-seq data generated from the timecourse of optic vesicle organoid development, show that this is a robust and relevant model system with which to study the gene dynamics underlying mammalian eye field specification.”

1. Appropriate citations should be added to back up the argument that opens the second part of the results section (starting Ln 279).

We have added several citations that discuss and review the current knowledge regarding gene regulation via TF-binding at accessible cis-regulatory elements.

1. Ln 342-343. I suggest being consistent and using the EF-up or EF-down nomenclature on the whole manuscript unless referring to a different subset of genes.

We have modified the text to consistently use “EF-up” or “EF-down” terminology.

1. Ln 692 Refers to Fig.S4F, but this figure has only panels A-D.

This was a typo and has been corrected in the text.

1. Figures 6B and E and the figure legend do not indicate the differences between the panels, or the time stage of the experiments.

The figure legend has been updated to include these details.

CROSS-CONSULTATION COMMENTS I agree with the comments and suggestions made by the other two reviewers, which identify similar and also specific issues in the manuscript. I believe they are all pertinent and should be acknowledged before re-submitting.

Reviewer #2 (Significance (Required)): The manuscript by Owen et al, presents the analysis of in vitro eye vesicle organoids derived from mouse ESCs at stages equivalent to when the eye field is specified in vivo. This work is pertinent and necessary as detailed data on gene expression in early eye organoids was missing in the field and is necessary for the interpretation of experiments in these systems.

Although the computational data provided in this manuscript is based on consensus TF motifs, the functional relevance of the specific motifs must be proven before being able to drive any significant conclusions, and one should be moderate about the conclusion that can be driven from this kind of analysis. Still, the analysis put forward is a good reference and starting point for future functional studies. One possible limitation of this study is that the quantification of the expression of genes is based on the RNAseq data, and the expression data should be further confirmed using a proper quantitative method like qPCR.

This study will be of interest to the audience studying eye development and disease in animal model systems and humans.

My lab studies the genetic, cellular, and molecular aspects of eye specification, development and disease in zebrafish, and study mutations identified patients with eye globe defects.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Studies in Xenopus embryos have established that the specification of the eye field requires a core set of transcription factors (TFs) that impose eye identity to anterior neural plate progenitors. In this manuscript the authors have used mouse embryonic stem cells-derived optic vesicle organoid to ask if the acquisition of mammalian eye identity requires the same set of TFs. They further use different genomic approaches to identify the cis-regulatory elements involved in the expression of these genes and analyses the consequences of altering the sequence of some of the identified regulatory elements. Their results confirm that in mammals the acquisition of eye field identity requires the upregulation of the expression of the same core set of TFs described in Xenopus, with a particularly important role for three of them: Rax, Pax6 and Lhx2. This upregulation is associated to the downregulation of pluripotency genes.

This is a generally well-performed study, that indeed involves a large amount work and adds the identification of several cis-regulatory elements controlling the expression of this core set of already identified eye field TFs. However, conceptually the study does not add much to what is already known and the authors do not offer any very original conclusion from their study. They have generated a large amount of information that likely could allow them to go beyond what is known. For example, they could enlarge the composition of the gene regulatory network that controls eye field specification, given than one of their argument is that their analysis can predict the composition of such a network. Perhaps, they could also address some of the questions that are posed in the discussion. This will strengthen the manuscript and valorize their work.

Additional points that could be taken into consideration are the following:

1) According to the text, the authors identify only 53 CREs with decreased chromatin accessibility (ATACseq signal) between the 3 day and 5 days timepoints, versus the 7752 CREs with increased signal. However, this contrasts with the proportion of genes upregulated/ downregulated in their RNAseq analysis (37 vs 448) and with the notion that specification of the eye field involves the concomitant repression of other neural fates. This also suggests that at least an important fraction of the dynamic ATACseq peaks associated with 161 of the 448 downregulated genes increase their accessibility and allow the recruitment of transcriptional repressors. However, the role of TF binding and chromatin accessibility dynamics on gene repression is poorly discussed and the authors need to provide some interpretation of these observations. Also, authors interpret the fact that the presence of BS for EF downregulated genes, such as En2 and GATA6, correlates with increased chromatin accessibility as a consequence of the fact that TFBS can be bound by different TF paralogs but do not seem to consider that these TFs have been reported to work as transcriptional repressors, so that their downregulation could well explain the changes in chromatin accessibility.

We thank the reviewer for their interesting comments here. We have added short discussions on both main points above (EF-down genes linked to peaks with increasing accessibility and En2/Gata as transcriptional repressors) in the text related to the analysis of our ATAC-seq data. The notion that a loss of repression leading to the activation of gene-expression is indeed a very exciting one and one that we have thought about in the context of the switch-on of the eye-field TFs. This certainly deserves further future work, however in the present study we wanted to be careful not to overinterpret our data. To robustly gain insights into the loss of repression, experiments such as En1/Gata6 ChIP-seq would be very useful, though we are unable to perform these in the near future.

2) ATACseq signal analysis is an indirect measure of TF binding. The authors demonstrate the predictive nature of this analysis of TF dynamics and have use an available Sox2 ChIP dataset. However, this does not allow assessing dynamic changes in the occupancy of this TF and its correlation with ATACseq. Therefore, at least for few of the TF stressed in this work (e.g. Sox2 and Otx2 and for which good antibodies exist) they could attempt ChIP-seq analysis. This would considerably strengthen the work and provide support to an idea that the authors have particularly emphasized in their manuscript.

We agree with the referee that not having generated ChIP-seq data does not allow us to validate some of the hypotheses and evidence provided by the computational analysis of our ATAC-seq data – we have added a discussion of this limitation in the discussion section of our manuscript. We do note however, as observed in Bentsen et al, 2020, that compared to simple TF-motif occurrence analyses, TF-footprinting analyses (such as those we have performed) yield results on putative TF binding that are much closer to more direct measurements of TF binding via e.g. ChIP-seq. We fully agree that it would be very interesting to perform ChIP-seq/Cut&Cut experiments on the organoid system for a set of interesting TFs identified in our study. Unfortunately, because the lab of Prof FitzPatrick has now closed, it is not possible for us to perform further wet-lab experiments in the very near future. However, we plan to further explore the literature to try to find additional publicly-available ChIP-seq datasets (including for Otx2) which would help reinforce some of the hypotheses we make, and will report any relevant findings in our final manuscript.

3) Previous studies (i.e. 10.1242/dev.067660; 10.1093/hmg/ddt562) have shown the importance of gene dosage in eye field specification and repression of other fates. These studies could be included in the discussion, which, in its current version is a quite brief and leaves out many of the reported analysis.

We thank the referee for pointing us to this very relevant question – we have added this to the further research questions in the discussion.

CROSS-CONSULATION COMMENTS

The comments from the other reviewers complement the aspects that we have underscored and should be fully considered as they will contribute to improve the manuscript.

Reviewer #3 (Significance (Required)): This is a generally well-performed study, that indeed involves a large amount work and adds the identification of several cis-regulatory elements controlling the expression of this core set of already identified eye field TFs. However, conceptually the study does not add much to what is already known and the authors do not offer any very original conclusion from their study. They have generated a large amount of information that likely could allow them to go beyond what is known.

Developmental neurobiologists, genome

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity):

Summary<br /> Authors show that overexpression of bHLH transcription factor Dpn in the medullary neurons of the Drosophila optic lobe results in the dedifferentiation of these neurons back into the NBs. These dedifferentiated NBs acquire and maintain mid-temporal identity, express Ey and Slp, and show delayed onset of tTF Tailless (Tll), leading to an excess of neurons of mid-temporal fate at the expense of late temporal fate neurons and glial cells. The dedifferentiated NBs are stalled in the cell cycle and fail to undergo terminal differentiation. Over expression of tTF Dicheate (D) or promoting G1/S transition pushed these NBs to late stages of the temporal series, partly rescuing the neuronal diversity and causing their terminal differentiation. They also show that the dedifferentiation of NBs by Notch hyper-activation also exhibited stalled temporal progression, which is restored by D overexpression.<br /> Authors suggest that cell cycle regulation and tTF are primary to the proliferation and termination profile of dedifferentiated NBs.<br /> Using these conclusions, the authors emphasize the need to recreate the right temporal profile and ensure appropriate cell cycle progression to use dedifferentiated NSC for regenerative purposes or prevent tumorigenesis originating from differentiated cell types.

Major comments:<br /> - Are the key conclusions convincing?<br /> Most conclusions are convincing; however, some issues are pointed out below.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

The authors have overexpressed Dpn and shown that medulla neurons dedifferentiate to NBs, similar to the loss of function phenotype seen for the Nerfin-1 of which Dpn is a target. They also show that temporal series progression defect is also seen in the case of dedifferentiated NB generated by Notch over-activation.<br /> Using these two examples, the authors suggest that for dedifferentiated NSC, which are to be used for the regenerative purpose, one needs to recreate the right temporal profile and ensure cell cycle progression occurs appropriately. Authors also claim that to prevent tumorigenesis originating from differentiated cell types, one needs to recreate the right temporal profile and ensure cell cycle progression occurs appropriately.

While I agree with this, I think this is an overreaching conclusion based on just these two examples. If they could show the same for one more method of dedifferentiation (For, e.g. Lola) happening in medulla neurons which happens by a mechanism independent of Nerfin-1, Dpn, Notch axis, the argument will become more convincing and broad.

We will characterise the temporal identity, termination and cellular identity of Lola-Ri induced ectopic neuroblasts. If these parameters are disrupted, we will overexpress D to assess whether this can trigger the progression of the temporal series.

Also when authors mention N mediated dedifferentiation, they need to inform that Dpn is a direct target of Notch in NBs (Doi. 10.1016/j.ydbio.2011.01.019), they do so in the discussion, but mentioning it here gives a broader context to the reader.

We will include that Dpn is a target of Notch when first mentioned.

Another important point that needs a mentioned here is that conclusions are based on dedifferentiation happening in the medulla neurons, which are considered less stable since they lack Prospero. Therefore whether this conclusion can be generalized for all the tumors arising from dedifferentiation in the CNS (eg, those arising from NICD activation in the central brain or thoracic region of the VNC) is another concern. Maybe authors can consider making a more conservative claim.<br /> Generalizing this conclusion to Prospero expressing NBs lies outside the scope of the current study and cannot be addressed here because central brain Type-I NBs use a different set of tTFs.

We will make a more conservative claim and clarify all of our conclusion are medulla neuron-specific.

Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.<br /> Experiments with Lola knockdown/mutants in medulla neurons can be done quickly, in my opinion, and will substantiate this claim.<br /> Another obvious question that comes to mind is if medulla neurons dedifferentiate on overexpression of Dpn, does the same happen in nerfin-1 mutant clones as well? And if yes, why has the author not done similar experiments for nerfin-1 mutants.

We will assess the temporal identity of neuroblasts in nerfin-1 mutant clones.

Please show Ey staining in Fig-2 if possible, it will also help to add a line on why Slp was used as marker for mid tTFs instead of Ey.

Ey is shown in Fig-2 (D-D’’) already. Slp is used as a marker of mid tTFs as Ey is expressed also in neurons thus would also be present in deep sections of control clones, whereas Slp is not expressed in neurons. We therefore used Slp as a proxy for mid-temporal identity throughout our study. We will include this text in our revision.

In Model shown in last figure Dpn is shown to repress D and activate Slp. Can authors show that Dpn overexpression represses D and activate Slp either by antibody staining or by RT PCR.

In Figure 2H, we have shown in clones that overexpression of Dpn induced a significant increase of Slp. In Figure S3B-B’’, we have shown that Dpn overexpression causes an upregulation of Slp at 6 hr APF. We can think we have pretty convincingly shown that Dpn overexpression activates Slp.

For Dichaete, our existing data shows that Dpn overexpression did not significantly alter D expression. To assess if using a stronger driver might allow us to see some changes, we will induced dedifferentiation via Dpn overexpression using the Eyeless-Gal4 driver. In this experiment, we will quantify the amount of D upon Dpn overexpression. Depending on this result, we will revise our conclusion on whether Dpn overexpression represses D.

Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.<br /> Experiments with Lola and nerfin-1 mutants can be done in a few months. I cannot comment on the cost involved.<br /> - Are the data and the methods presented in such a way that they can be reproduced?<br /> Yes

Are the experiments adequately replicated and statistical analysis adequate?<br /> Replication and statistical analysis are fine. The activated Notch experiments show only three data points in all the experiments. It will be good to increase this number.

We will repeat Notch experiments to increase the n number for these experiments.

Minor comments:<br /> - Specific experimental issues that are easily addressable.<br /> There is a problem with Fig-5F (both 5E and 5F have % EdU in clone/ % Mira in the clone as y-axis), I do not understand how the Fig-5F let them conclude that D overexpression increases the rate of neuronal production.

In the text we said: “We found that D overexpression did not significantly increase neuronal production, suggesting that it is likely that cell cycle progression lies upstream or in parallel to the temporal series, to promote the generation of neurons.”

In one place, the authors conclude, "Together, this data suggests that it is likely that cell cycle progression lies upstream of the temporal series, to promote the generation of neurons". Authors should consider adding "medulla NBs" at the end of the sentence since cell cycle progression being upstream of temporal series is already known in Type-I NBs, as pointed out by authors as well (Ameele and Brand 2019).

We will add “medulla NBs” to the end of this sentence.

In the discussion authors says that "Our data support the possible links between cell cycle progression and the expression of temporal regulators controlling NB proliferation and cellular diversity". This is new information, as the 2019 study did not show how cell diversity changes with a changed tTF profile. I think the authors should elaborate on this point to highlight how this is different from what is already known from the 2019 study (done in the context of Type-I NBs).<br /> Maybe they need to highlight that the cell cycle directs/regulates the progression of temporal series compared to the earlier observation where temporal series was shown to be downstream of the cell cycle.

We will expand in discussion to discuss the link between cell cycle/tTFs.

In fig-3J in clones even after 24 AHS, Dpn continues to be overexpressed but these cells undergo terminal differentiation, can authors comment why is it so?<br /> In one place authors say, "To better assess the cumulative effect of the neurons made throughout development, EyOK107-GAL4 was used to drive the expression of Dpn" maybe some background on why use this specific GAL4.<br /> Also a line about why GMR31HI08-GAL4 eyOK107-GAL4 and and eyR16F10-GAL4 were used.

While Dpn is overexpressed, it progresses through the temporal series at a slower pace due to a delay in cell cycle progression, as well as delayed onset of D, these NBs still eventually reach the terminal temporal identity, and are thus about to undergo terminal differentiation. We will include an additional piece of data that shows NBs induced by Dpn overexpression do eventually turn on Tll.

Are prior studies referenced appropriately ?<br /> Yes, but in a few places, some references can be added.<br /> An important point that needs to be mentioned for the context is the medulla neurons do not use Prospero for terminal differentiation and are thus considered less stable (DOI: 10.1242/dev.14134

We beg to disagree with the reviewer in terms of Pros is not required for terminal differentiation of medulla neuroblasts. Li et al., 2013 shows that nuclear Pros is found in the oldest NBs. We do agree that differentiated state of medulla neurons is less stable, possibly owing to absence of Pros, and we will include that in our discussion.

In discussion, the authors say that "It would be interesting to explore whether N similarly acts on these target genes to specify cell fate and proliferation profiles of dedifferentiated NBs." There is a study looking at Notch targets in NB hyperplasia (DOI: 10.1242/dev.126326); whether that study shows if any of the cell cycle genes are downstream of activated Notch, needs a mention here.<br /> Also, when authors mention N mediated dedifferentiation, they need to inform that Dpn is a direct target of Notch in NBs (Doi. 10.1016/j.ydbio.2011.01.019). They do so in the discussion, but mentioning it in the introduction or results will give a broader context to the reader.

We will discuss the study looking at N targets in NB hyperplasia in the discussion of the revised manuscript.

We will mention that Dpn is a target of Notch in the results section.

Another gene that needs a mention is "Brat", which regulates both Dpn and Notch, and causes dedifferentiation and tumors in CNS, I think this gene and its interaction with Dpn and Nerfin and Notch needs to be discussed either in the introduction or discussion.

We will comment on Brat in the discussion.

Are the text and figures clear and accurate?<br /> The main figures are not labeled. Therefore, it was very annoying to deduce the specific figure numbers.<br /> There are 1 or 2 places where figure calling is wrong in the text.<br /> The Image Fig-5I shows cycD and CDK4 at the G2-M transition; while the text says it supports G1/S, which is indeed the case, the figure needs modification.

We thank the reviewers for identifying these mistakes, and will correct them.

Do you have suggestions that would help the authors improve the presentation of their data and conclusions?<br /> The presentation is okay, in my opinion.

Reviewer #1 (Significance):

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

The factors leading to dedifferentiation of the neurons have been identified previously by groups of Chris Doe (mldc, DOI: 10.1242/dev.093781), Andrea brand (10.1016/j.devcel.2014.01.030.) as well as the authors of this paper (10.1101/gad.250282.114, 10.1016/j.celrep.2018.10.038.). However, many questions remained unaddressed regarding such NB generated from neuronal dedifferentiation. For example, whether these cells contribute to native cell diversity of the CNS, undergo timely differentiation or their progeny cells incorporated into appropriate circuits is not well understood. Successful execution of these phenomena is critical for generating functional CNS and such insights are crucial for understanding the origin of tumorigenesis in CNS or employing dedifferentiated NSC for regenerative purposes.

This study is an overexpression-based study, however, some of the results give significant conceptual insights into the tumors arising out of the dedifferentiation of the neurons. It also gives insights into the fact that the dedifferentiated cells need to be carefully examined for the temporal factor profile before they can be employed for regeneration or any therapy targeting them.<br /> However, in my opinion, they need to test this idea at least in one more system of neuronal dedifferentiation, preferably independent of the nerfin-1/Notch/Dpn axis to generalize this claim.

• Place the work in the context of the existing literature (provide references, where appropriate).<br /> Cerdic Maurange's group had looked at the role of temporal factors and identified the early phase of malignant susceptibility in Drosophila in 2016 (doi: 10.7554/eLife.13463). Andrea Brand's group has shown in a 2019 paper that cell cycle progression is essential for temporal transition in NBs (doi: 10.7554/eLife.47887). Both these studies were in the context of Type-I NBs, which express Prospero, which is crucial for the differentiation of the neurons.<br /> Previously the authors have studied type-I NBs and shown by Targeted DamID that Dpn is Nerfin-1 target. They also show that Nerfin-1 mutants show dedifferentiation of neurons. They follow up on this observation in medulla neurons, where they find that Dpn overexpression results in their dedifferentiation into medulla NBs. Medulla NBs differ from Type-I NBs in using a separate set of tTFs. Also, Type-I NB and neurons arising from them use Prospero for terminal differentiation, while medulla neurons do not express Prospero and are therefore considered less stable (DOI: 10.1242/dev.141341).

The importance of the study lies in the results that show that the NB arising out of dedifferentiation of medulla neurons takes up mid-temporal fate. These NBs are stalled in Slp expressing mid-temporal stage unless the cell cycle is promoted by overexpression of cell cycle genes regulating G1/S transition.<br /> Authors also show that overexpression of D promotes the progression of temporal series in these dedifferentiated NBs, which could partly rescue neuronal diversity and result in terminal differentiation. Thus D plays an important role in determining the type of neurons these NBs generated. This suggests that knowing the tTF profile of these types of dedifferentiated NBs is vital if these cells were to be used for regenerative purposes. Authors further claimed that cell cycle regulation and tTFs are critical determinants of the proliferation and termination profile of dedifferentiated NBs.

• State what audience might be interested in and influenced by the reported findings.<br /> The study will be of broader interest to researchers interested in central nervous system patterning, regeneration, and cancer biology.

• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.<br /> Drosophila, central nervous system patterning and cell fate determination of neural stem cells.

Reviewer #2 (Evidence, reproducibility and clarity):

Stem cells can divide asymmetrically to self-renew the stem cell while generating differentiating sibling cells. To restrict the number and type of differentiating sibling cells, stem cells often undergo terminal differentiation. Terminally differentiated cells can dedifferentiate and revert to a stem cell like fate. However, the underlying molecular mechanisms are incompletely understood in vivo.<br /> Here, Veen et al., use Drosophila neural stem cells (called neuroblasts) to investigate how terminal differentiation is regulated. Neuroblasts faithfully produce the correct number and type of neuronal cells through temporal patterning and regulated terminal differentiation. The authors show that misexpression of the bHLH transcription factor Deadpan (Dpn) induces ectopic neuroblasts, which predominantly express mid-temporal transcription factors at the expense of late-temporal transcription factors. As a consequence, these ectopic neuroblasts also fail to produce Repo positive glial cells and are stalled in their cell cycle progression. The authors provide evidence that promoting cell cycle progression and overexpression of the transcription factor Dichaete (D) is sufficient to restore the temporal transcription factor series, neuronal diversity and timely neuroblast differentiation.

This is an interesting study that will be of interest to the stem cell field. However, I encourage the authors to consider the following critiques:

1. Explain the rationale for the three different neuronal/NB drivers (GMR31HI08-GAL4, eyOK107-GAL4, eyR16F10-GAL4. How are they expressed?

We will include an expression analysis of EyOK107-GAL4 and eyR16F10-GAL4. GMR31HI08-GAL4 expression analysis was previously published (Vissers et al., 2018). We will explain in the text the benefits of each driver.

1. The rationale for the Edu experiment (Figure S1I) is not clear. Why is this a measure for the production of neuronal progeny? For the correct interpretation of these results, the authors should also provide control clones or Edu experiments of regular neuroblasts.

We will repeat this experiment and mark the progeny with the neuronal marker Elav, to demonstrate that they are neurons. Additionally, we will add the control to this figure.

1. How was % of Mira (Figure 1K and below) or the % of tTFs (Figure 2H onward) quantified? For instance, Figure 2C-G often shows clonal signal that is not highlighted with the dashed lines and the corresponding tTF intensity does not match the intensity in the outlined clone (eg. Figure 2D-D'; a large optic lobe clone is negative for Ey. Figure 2E-E'; an unmarked clone is negative for Slp).<br /> Similarly, the Hth signal is very weak to begin with so it is unclear how this was quantified. How was determined what constitutes real signal vs. background noise?<br /> Additional explanations in the methods section is needed to assess the robustness of the data.

We will expand the methods section and mention that we used similar thresholding in antibody staining between control and uas dpn in all instances, so even if the antibody is weaker (eg hth) it is consistently quantified. Additionally, we can increase the intensity of Ey in Figure 2D-2D’, as it is expressed at low levels.

1. This sentence should be rephrased: 'As the tumour cell-of-origin can define the competence of tumour NBs to undergo malignancy (Farnsworth et al., 2015; Narbonne-Reveau et al., 2016), we next tested whether the temporal identity of the dedifferentiated NBs were conferred by the age of the neurons they were derived from.'<br /> The connection between tumorigenicity and temporal identity is not really clear and should be briefly reintroduced for this paragraph.

We will rephrase this sentence and further introduce this concept when talking about tumour cell of origin and competence.

1. Figure 2I-N: The experimental outline in I and J should be grouped with the corresponding images to clarify what is compared. Also, there are no images for the control clones, which make a comparison difficult. The images are also too small. I cannot really see the Hth, or Slp signal in the small clones shown in Figure 2K-L".

We will split figure 2 into two images. The first image including A-H and the control data. And the second including I-Q and the control data. This will increase the size of the images. Additionally, we will group I and J with corresponding data.

1. Figure 3H: It is not clear why there are only a small group of Nbs that are positive for Mira. Please explain.

Most NBs have terminated by this time point, we will explain this within the text.

1. Figure 3K-M: Please explain how the Toy signal was measured and quantified.

We will expand the methods section and explain how Toy quantification is made.

1. The TaDa data set is very interesting but the following might be an overstatement: "We found that Dpn directly binds to slp1 as well as the Sox-family TF dichaete (D) which is expressed in medulla NBs after slp1 (Li et al., 2013) (Figure S6 A-B)."<br /> More direct binding assays might be needed to show that Dpn directly binds to slp1 and D. If this is already shown, clarify the sentence to indicate what is published and what is extracted from the data shown here.<br /> Also, what is the rationale for this statement: "Consistent with the model that D represses Slp-1..."?

The DamID data do actually show that Dpn binds (i.e. there is a statistically significant peak at FDR<0.01) directly at these loci (see the TaDa supp fig A & B). Whether it’s doing anything functional or not, we can’t say, but our data shows that Dpn directly binds to slp1 and D. We will clarify the sentence to indicate this in our revision.

1. This might be an overinterpretation: D overexpression in UAS-Dpn NBs promoted their pre-mature cell cycle exit at 6 hrs APF using eyR16F10-GAL4. The data shows loss of Mira signal, which could occur through different mechanisms.

Our data already shows that these NBs express Tll, the terminal temporal transcription factor (Figure 4F). In addition, we show that there is an increase in Tll+ and Repo+ progeny (Figure 4K, L). Together, this suggests that D overexpression promotes the progression of the temporal series. However, it is possible that Mira+ cells can disappear via cell death. We will assess this possibility by staining for cell death marker Dcp1 at 6hr APF.

Reviewer #2 (Significance):

These appear to be novel and significant findings that will enhance our understanding of the temporal progression and terminal differentiation program of neural stem cells in vivo.<br /> I think the findings will be of interest to cell, developmental cell and stem cell biologists.

My primary expertise is in the cell biology of fly neural stem cells and asymmetric cell division of neuroblasts. Although I am not intimately familiar with the differentiation and differentiation literature, I consider the findings reported here relevant and impactful.

Reviewer #3 (Evidence, reproducibility and clarity):

The discoveries that the author describe in this manuscript are very specific to dedifferentiated neuroblasts created by UAS-dpn transgene overexpression. Dpn is endogenously expressed in optic lobe neuroblast throughout larval stage, which makes understanding how Dpn regulates gene expression based on the authors results (suppression of cell-cycle genes, and promotion of a specific temporal state) confusing.

Our data relate specifically to gene regulation by Dpn in a dedifferentiated context, and do not seek to understand Dpn regulation in wt neuroblasts. The reviewer is assuming our scope is greater here: we’re not trying to claim that we know what Dpn is doing in wt NBs, and it’s not surprising that ectopic effects in neurons may be different to wt NBs.

To assess whether the mechanisms described apply to more than Dpn overexpression, we will also assess whether the temporal series progression is affected in Lola RNAi and Nerfin-1 mutant.

Therefore, this manuscript does not advance our understanding of regulation of temporal identity and cell cycle progression in optic lobe neuroblasts during normal neurogenesis.<br /> The author's state:<br /> "However, beyond the fact that misexpression of these factors and pathways caused the formation of ectopic NBs, whether these dedifferentiated NBs faithfully produce the correct number and types of neurons or glial cells, or undergo timely terminal differentiation, has not been assessed. These characteristics are key determinants of overall CNS size and function, thus are important parameters when considering whether dedifferentiation leads to tumourigenesis or can be appropriately utilized for regenerative purposes."<br /> at the end of introduction. If this is a true primary goal of this study, the authors should describe it in abstract. Otherwise, readers will lose enthusiasm to read this manuscript in abstract and no longer read the following sections.

We will add this to the abstract.

Results<br /> 1. The authors should describe the expression pattern of all three of the Gal4 drivers used. While there are dotted outlines in the supplemental figure, there should be a description in the main text for the expression pattern of these lines which described with temporal state of NBs these lines are expressed in, and whether they are also expressed in the neurons or not.

We will include expression analysis of all three drivers in a supplementary figure and explain in the text the benefit of each driver.

1. The authors claim that overexpression of Dpn in the medulla region causes "dedifferentiation." The data provided however is not sufficient to conclude that dedifferentiation is occurring. The GAL4s used all drive in the NBs, and so it is unclear if the ectopic NBs ever became mature neurons. In addition, the lack of ectopic NBs in the clonal analysis 16hrs AHS does not prove that ectopic NBs at 24hrs AHS must have come from "mature neurons." To demonstrate dedifferentiation, the authors should use a driver system that is specific to mature neurons, and then overexpress dpn and look for mira+ cells. Currently, the authors data does not prove that mature neurons dedifferentiatiate into ectopic NBs upon Dpn OE.

We have conducted lineage tracing (G-Trace) analysis of the medulla neuron driver GMR31H08-GAL4 which we utilise in our study, this driver is predominantly expressed within the medulla neurons (real time) except for a few GMCs present in the lineage. Therefore, the Mira positive cells induced via Dpn overexpression are most likely from dedifferentiation (We will include this data in a supplemental figure in our revised manuscript).

To further support this, we will use GMR31H08-GAL4 with a Gal80ts, to restrict the timing to dedifferentiation induction to 3rd instar, so that the driver is restricted to neurons. Similar strategy to induce dedifferentiation was utilised in DOI: 10.1242/dev.141341 and DOI: 10.1016/j.devcel.2014.01.030.

1. What is a conclusion of fig 2C-H?

Fig 2C-H assess the expression of tTFs in UAS-dpn induced ectopic NBs. We will make these conclusions clearer in the text.

1. "As the tumor cell-of-origin can define the competence of tumor NBs to undergo malignancy identity of the dedifferentiated NBs were conferred by the age of the neurons they were derived from". This sentence is confusing. What are the authors investigating in the following experiment? Do they want to see ectopic NBs keep their early identity like Chinmo in ventral cord tumor NB? Or tll-positive NB's progenies can dedifferentiate to ectopic NB, but this ectopic neuroblast is not able to keep proliferation in pupal stage? It is hard to understand the connection of this sentence and the following experiment.

We will rephrase this sentence and further introduce this concept when talking about tumour cell of origin and competence. Additionally, we will make the connection to the experiments which follow it clearer.

1. The DamID experiment described used wor-gal4 as a driver, which means the Dpn binding profile generated is coming from not only optic lobe NBs, but central brain NBs and VNC NBs as well. In Magadi et al. (2020), the authors profiled Dpn binding in CNS hyperplasia, and found that dpn strongly bound Nerfin-1 and gcm. However, it does not bind cell cycle genes in this context. How do the authors know that the region that they claim are bound by dpn are bound in medulla NBs? The authors should also include tracks to show dpn binding at Nerfin-1, as well as the other tTFs (hth, ey, tll, and gcm). Providing this data will help to understand if Dpn binding is specific to the mid-temporal genes, as Dpn expression is known to be expressed in all medulla NBs regardless of temporal state.

We agree with the reviewer that the profile is not specific to medulla NBs. To assess Dpn binding profiles specifically in the medulla NBs, we will use the recently-published NanoDam technique (https://doi.org/10.1016/j.devcel.2022.04.008) for profiling GFP-fusion proteins, with a medulla specific driver (eyR16F10-GAL4) and Dpn-GFP (recombineered locus under endogenous control). This should inform us whether the target genes we have identified are relevant in the medulla.

We will include the tracks of the other transcription factors.

1. Currently, the DamID data does not help to interpret the Dpn overexpression phenotype at all. Inside of flip-out clone, some cells show Slp-1 expression while others showed D expression. The authors explain that Slp-1 and D suppress their expression to each other. But the DamID data indicate that both Slp-1 and D are Dpn target genes. If this is true, why did they observe the mosaic expression pattern inside of the same clone.

We observed that high levels of Slp-1 is correlated with low levels of D. This suggest to us that the initial stochastic differences accounts for where Slp-1 is high is where D is low, and vice versa.

1. The authors hypothesized if Dpn activated Slp-1directly. Does this mean that Dpn directly activate transcription of Slp-1? It is well known that Dpn is transcriptional repressor. Hes family proteins form a homodimer or heterodimer with another Hes protein and interacts Gro, which recruits a Histon deacetylase protein. The author's claim does not fit to the model what we currently believe. In addition, the authors claimed that Dpn inhibits cell cycle gene transcription directly. This is inconsistent to their claim that Dpn directly activate Slp-1 expression. If the authors want to claim that Dpn has two different functions in this context, the authors must demonstrate it by experimental results.

We will discuss these models in the Discussion, and make our claims more conservative, as we do not have direct experimental evidence to prove or disprove the model that Dpn is acting as an activator in this context.

1. Related to the above question, I wondered if the authors guess Dpn activate or repress D transcription by binding to D promoter region because they claimed that Dpn activate Slp-1, while suppress cell cycle genes.

We will make our claims more conservative, and discuss this point further in the Discussion.

1. I am confused to the claim that Dpn suppress cell cycle genes expression. Dpn overexpression induces dedifferentiation of neuron into NB and re-entry into the cell cycle. If Dpn suppress cell cycle genes how can the dedifferentiated cell re-enter into the cell cycle?

The data points towards that Dpn overexpression has two separate roles in regulating the cell cycle. Ofcourse dedifferentiation requires a commitment of neurons into the cell cycle (this we think is still happening), however, we think once these cells have turned on NB markers, they have limited ability to progress through the cell cycle. We will discuss this point in the Discussion.

1. Figure 6 looked redundant because we know Dpn is a direct target of Notch. It is obvious that an upstream factor overexpression can induce the identical phenotype to the phenotype induced by overexpression of a downstream factor.

A direct target does not necessarily infer the same phenotype. To assess whether the mechanisms apply to other dedifferentiation models, we will add Lola-RNAi and Nerfin-1 data to our revised manuscript.

Minor comments:<br /> 1. Typo in main text: "GMR31HI08-GAL4" should be "GMR31H08-GAL4"<br /> 2. In figure 1E-H the dotted line regions indicated the clones are not shown in the merge image. Please include<br /> 3. Typo in discussion paragraph 2: "temporal series was no sufficient to rescue cycle cycle progression"

We will correct these typos.

Reviewer #3 (Significance):

Insights into the developmental capacity of dedifferentiated stem cells will likely lead to novel strategy to replenish cells lost due to aging, injury and diseases in regenerative medicine.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

We propose three revisions, that have not yet been included in the current manuscript:

1. All three reviewers comment on the data in figure 7, in which the application of the sensor is shown. We agree that the number of cells is low, and we plan to repeat this experiment to increase the number of cells, and better demonstrate the usefulness of the new probe. We note that the improved Cdc42 sensor is used in a recent preprint (see figures 7 and 9 of: https://www.biorxiv.org/content/10.1101/2022.06.22.497207v2.full), clearly showing the potential of the probe for detection of Cdc42 and increasing our confidence that we can generate higher quality data.
2. The ratio of expression of the different components was not quantified. We have these data and we will (re)analyze it and present the results (related to Reviewer #3, point2).
3. We will reanalyze the images to ensure that representative images are depicted in the manuscript (related to Reviewer #2, point 3).

   Reviewer #1

1) It is not clear why RhoA data were included in this manuscript (Fig. 1), since they seem irrelevant to the primary topic addressed.

We have cell-based data from our previous (published) work that we can use to check whether these results align with the mass-spec data. To make this point clearer we add “We looked first into GBDs for Rho, to compare the results of the mass spectrometry screen with the results of our cell-based assays”.

2) It is not clear what cell type was used when screening for p67phox. The expression of this component of the NADPH oxidase is restricted to a few specific cell types.

That’s a relevant point and therefore observation that p67phox is not detected is perhaps not surprising. We removed this statement.

3) There is precious little quantitation of the colocalization or translocation of the probes throughout the manuscript. It is difficult to assess the validity of the conclusions in the absence of analysis of the statistical significance of the colocalization.

In figure 2, which is an initial screen, there is only a qualitative assessment. However, for the promising candidates, there is a quantitative assessment in Figures 3B and 4 B as to which extent the candidates colocalize with the nuclear localized target. From the rank order and individual datapoints the best performing binder can be inferred.

4) It is not clear why translocation to mitochondria was used in some experiments and translocation to the nucleus in others.

To clarify, we have added text: ”We have previously used nuclear localized, constitutive active Rho GTPases, but these are not accessible for larger proteins that cannot enter the nucleus”

5) In the S1P experiments, it is difficult to ascertain whether increased fluorescence resulted from membrane folding/ruffling or is actually a consequence of localized activation of receptors. Why does the fluorescence decrease progressively over 1500 seconds? Isn't maximal receptor activation accomplished much sooner?

This experiment suffered from bleaching. We will redo the experiment to get higher number of cells and to improve the data.

Reviewer #2

Major comments

1. Statistical tests are missing in most of the figures. If the principal purpose of this work is to compare the performance of candidate peptides, the quantitative comparison is essential. If the purpose is just to report another relocation probe, then, more application data may be necessary.

We will improve the quality of the application data. As for statistics, we have added the effect size to figures 5C-F and figure 6A. To explain this (not so common) statistic we add to the materials and methods: “The effect size that quantifies the difference and its distribution was calculated with the web tool ‘PlotsofDifferences’”.

1. The criteria for selecting the best peptide should be clearly described. Is it just by inspection or based on any quantitative data? We know that quantification of colocalization is a difficult task. Therefore, it depends on the aim of this work whether the authors are asked to show quantitative data or not. If a strict comparison of peptides is aimed at, the expression level of each target peptide should be at a comparable level. It will be also required whether the design of each probe guarantees the proper folding to bind to GTPases.

There are two stages for the selection. First, we did a qualitative analysis of colocalization (shown in figure 2). Based on the results (“Candidates colocalizing with the mitochondrial tagged Rho GTPase were further tested for their potential as localization-based sensors”), we generated smaller biosensor candidates of which binding to a nuclear target was quantitatively analyze (figures 3B and 4B). As the expression level is an important factor, we ascertained potential candidates were expressed at roughly the same level in the nuclear accumulation assay.

1. About the images of cells: When a fluorescent image is presented, we assume it represents all other cells. Please check all images whether they are truly representing the data. For example, in Fig. S3 the nuclei of ABI1-expressing cells look weird, and the nucleus of CYRI-A is very large. If this is true, the reason why ABI1 and CYRI-A should be excluded from the candidate is not the relocation efficiency but the undesired effect on cell physiology. For the screening of the peptides, this information is also very important. With that, this paper becomes more valuable for scientists.

We agree that this is an important point. We will reanalyze the data as indicated in the ‘planned revisions’.

1. Please examine the order of panels. For example, the result of mScarlet is on the top in Fig3, but at the bottom in Fig4. Such inconsistency would disturb readers.

We thank the reviewer for this suggestion and we changed figure 4.

1. The label should be consistent throughout the paper. For example, in Fig. 5A, Lck-FRB-mTurquoise2 is labeled as Lck-FRB (without the fluorescent protein's name). WASp(CRIB)-mScarlet-I-WASp(CRIB) is labeled as WASp(CRIB)-mScar-WASp(CRIB) (with fluorescent protein's name). Moreover, the same peptide is labeled as mSca-1xWASp(CRIB) in Panel B. Such inconsistency is confusing.

We agree, we have updated figure 5A by adding the abbreviations of the fluorescent proteins. Please note that WASp(CRIB)-mSca-WASp(CRIB), mSca-1xWASp(CRIB) and mSca-2xWASp(CRIB) are three different constructs. In the first one the CRIB domains are sandwiching the fluorescent protein and in the third one they are in tandem downstream of the fluorescent protein.

1. Quantitative insight would improve this work. For example, in Fig. 7, the reason why the authors believe that the probe worked is the accumulation of probe at the tip of lamellipodia and the decrease in cytoplasmic intensity. This reviewer does not think the accumulation of the probe in the small area of the lamellipodia explains the massive decrease of cytoplasmic signals. Probably, a substantial amount of the probe is relocated to the plasma membrane, not limited to the lamellipodia.

Minor comments

We propose to repeat the experiment shown in figure 7 and to improve the quality of the data.

1. Introduction, "FRET signal is typically measured with a wide field microscope.": This reviewer does not agree with this statement. Confocal and two-photon microscopes have also been used widely.

Fair point. We changed the text to “when the FRET signal is measured with a wide field microscope”

Introduction, "G-protein activating proteins (GAP)": It should read as "GTPase-activating proteins (GAPs)"

Thanks, corrected.

TRIF should read as TIRF.

All instances have been corrected.

Fig.1: To the best of this reviewer's knowledge, PKN1 was first used as the RhoA target peptide by Yoshizaki et al in 2003. J Cell Biol 162, 223-232. They also examined mDia, Rhoteki, and Rhophilin as the target peptides. Pak1 was first used as the Rac1 probe by Kraynov et al. Science 290, 333-337, 2000. Use of Pak1 as the Cdc42 probe was reported by Itoh et al. Mol Cell Biol 22, 6582-659, 2002. This reviewer believes that the priority of the first report should be respected.

We changed part of the introduction to:

High scoring proteins for interacting with constitutively active RhoA(Q63L) included ANLN part of the AniRBD Rho location sensor (Piekny and Glotzer, 2000), PKN1 part of aRho FRET sensor (Yoshizaki et al., 2003) and RTKN part of the rGBD Rho location sensor (Benink and Bement, 2005; Mahlandt et al., 2021) (Fig. 1A,B). This suggested that proteins with a high score in the mass spectrometry screen are potentially suitable as Rho GTPase activity biosensor. Indeed, the GBDs used for Cdc42 location sensors from, PAK1 used in the PBD location sensor (Itoh et al., 2002; Petrie et al., 2012) and N-WASP similar to WASp used in the wGBD location sensor (Benink and Bement, 2005) showed a high score in the screen (Fig. 1A,B).

Discussion:

Another challenge is the Rho GTPase specificity of the relocation-based sensor. For example, Pak1(CRIB) was first used in a Rac1 FRET sensor (Kraynov et al., 2000)____. ThenPak1(CRIB) has been utilized in Cdc42 FRET sensors and in an intensiometric Cdc42 sensor (Hanna et al., 2014; Itoh et al., 2002; Kim et al., 2019). However, Pak1(CRIB), also named PBD sensor, has then been reintroduced by Weiner and colleagues as a Rac1 specific location-based sensor and is often used in neutrophil HL60 cells (Brunetti et al., 2022; Graziano et al., 2019; Le et al., 2021; Weiner et al., 2007).

We also updated the tables in Figure 1.

Fig. 1: Why do the authors omit other promising candidates shown in panel 1B? Please describe the reason for the choice.

We took into account the availability of plasmid DNA, as also explained in the manuscript: “candidate GBDs were selected from top 30 scores of the mass spectrometry screen, that were specific for one Rho GTPase and their DNA was available on addgene”

Fig. 1B: Be consistent to use either "Name" or "Uni Prot name" in Panel A.

We updated figure 1.

Fig. 2: Please include information on TOMM20. The readers may not read the paper by Gillingham et al.

We added an explanation: “To this end, a fusion with TOMM20 was used for mitochondrial localization.”

Fig3 and 4: The authors should show the images of control H2A.

We provide the data for control H2A in figures 3B and 4B.

In Fig3B and 4B, "Cdc42/Rac1 affinity" would be misleading, because the control dots represent their authentic localization rather than "Cdc42/Rac1 affinity".

We agree, we have updated figure 3B and 4B.

Fig. 4: More explanation of this figure is required.

We added text: “Hence, the sensor candidate can freely partition between Rac and Cdc42 binding.”

Fig. 5: More explanation about the FKBP-FRB system will be helpful.

We changed the text to: “The system used rapamycin induced heterodimerization of the two domains FRB and FKBP to recruit the DHPH domain of the Cdc42 specific GEF ITSN1 to the plasma membrane, where it induces activity of the endogenous Cdc42”

Fig. 6: It is rather surprising to see that control-mScarlet also responds to Rac1 activation. What is the explanation for this observation?

We agree and have no explanation.

Fig. 7: A single champion data may not be convincing to prove the usefulness of this probe.

We agree and propose to repeat the experiment.

Reviewer #3

1) The discussion comparing different types of biosensors missed important points. Although the advantages of localization biosensors listed by the authors are correct, they gave the impression that these should simply be an improved replacement for FRET biosensors. There are times when FRET biosensors provide clear advantages. Unlike other proteins, Rho GTPases are well suited for localization sensors because the activated conformation, and only the activated conformation, localizes to the membrane. For diffuse or 3D localization FRET can provide better quantification. Subtle features such as gradients are not easily quantified over a background of unattached domain. The authors state that localization biosensors have enhanced spatial resolution, but this is not explained.

We agree that our introduction is biased towards a preference for relocation based biosensors. However, having used both approaches, we see that both strategies have pro’s and cons. Therefore, we removed the claim for higher resolution and we added: “Still, the ratiometric mode of imaging FRET sensors is beneficial for detection of gradients or activity in 3D imaging”.

2) Throughout the paper, the ratio between the GTPase and the domain, and the overall expression level of each, was not sufficiently examined. The results in many cases would be dependent on both these factors (was a large excess of domain used? Was there insufficient domain to bind the GTPase and provide a signal? Did this vary for different domains, and therefore produce the differences observed? A lack of apparent binding specificity could be produced by high domain expression.)

This is an important point. We will re-analyze the data and include a figure where we add the binding efficiency versus the expression level.

3) In the nuclear exclusion assay, some GTPases were excluded from the nucleus and others not. This was true even without expression of the domains. When GTPases were excluded from the nucleus, domains were eliminated from contention, even when this was true without domain. The authors could at least mention that these domains may be viable.

Correct, and we have added this text: “we cannot exclude that these would be viable Cdc42 sensor candidates”

4) In the multiplexing experiment, only two cells were imaged. In one cell RhoA activity was inversely correlated with Cdc42 activity. In the other cell it was not. It seems there is insufficient information to reach firm conclusions.

We agree and in the revision plan we indicate that we will repeat this experiment to increase the number of cells.

Minor points:

• There appear to be errors in naming mutants. Q60L is used for constitutively active Rac, but Q61L is likely meant. H2A-mTurquoise2-Rac1(G12V)-ΔCaaX is used when it likely should be H2A-mTurquoise2-Rac1(Q61L)-ΔCaaX. There are other examples -- a careful check of these names throughout the manuscript would be valuable.

Thanks for spotting this. Q60L is changed to Q61L. Note that the Rac1(G12V) is correct as it also is a constitutive active Rac1.

• Intro-Paragraph 1-line 5: change present to presence

• Intro-Paragraph 5- line 7: use them instead of theme.

Thanks, both corrected.

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

Mahlandt et al report Rho GTPase relocation sensors. First, the authors picked up candidate peptides based on the Mass-Spec data reported by Sean Munro's laboratory. The authors repeated the experiments to confirm the binding of peptides to mitochondria-targeted Cdc42 and Rac1 and narrowed down the candidate peptides by binding to nuclear Cdc42. The specificity of binding to Rac1 and Cdc42 was also tested. Eventually, they concluded that dimeric Tomato-WASp(CRIB) is the best sensor for Cdc42, which could detect S1P-induced Cdc42 activation in primary endothelial cells. The effort to improve the relocation sensors should be evaluated highly. This reviewer has some suggestions to improve this paper.

Major comments:

1. Statistical tests are missing in most of the figures. If the principal purpose of this work is to compare the performance of candidate peptides, the quantitative comparison is essential. If the purpose is just to report another relocation probe, then, more application data may be necessary.
2. The criteria for selecting the best peptide should be clearly described. Is it just by inspection or based on any quantitative data? We know that quantification of colocalization is a difficult task. Therefore, it depends on the aim of this work whether the authors are asked to show quantitative data or not. If a strict comparison of peptides is aimed at, the expression level of each target peptide should be at a comparable level. It will be also required whether the design of each probe guarantees the proper folding to bind to GTPases.
3. About the images of cells: When a fluorescent image is presented, we assume it represents all other cells. Please check all images whether they are truly representing the data. For example, in Fig. S3 the nuclei of ABI1-expressing cells look weird, and the nucleus of CYRI-A is very large. If this is true, the reason why ABI1 and CYRI-A should be excluded from the candidate is not the relocation efficiency but the undesired effect on cell physiology. For the screening of the peptides, this information is also very important. With that, this paper becomes more valuable for scientists.
4. Please examine the order of panels. For example, the result of mScarlet is on the top in Fig3, but at the bottom in Fig4. Such inconsistency would disturb readers.
5. The label should be consistent throughout the paper. For example, in Fig. 5A, Lck-FRB-mTurquoise2 is labeled as Lck-FRB (without the fluorescent protein's name). WASp(CRIB)-mScarlet-I-WASp(CRIB) is labeled as WASp(CRIB)-mScar-WASp(CRIB) (with fluorescent protein's name). Moreover, the same peptide is labeled as mSca-1xWASp(CRIB) in Panel B. Such inconsistency is confusing.
6. Quantitative insight would improve this work. For example, in Fig. 7, the reason why the authors believe that the probe worked is the accumulation of probe at the tip of lamellipodia and the decrease in cytoplasmic intensity. This reviewer does not think the accumulation of the probe in the small area of the lamellipodia explains the massive decrease of cytoplasmic signals. Probably, a substantial amount of the probe is relocated to the plasma membrane, not limited to the lamellipodia.

Minor comments:

1. Introduction, "FRET signal is typically measured with a wide field microscope.": This reviewer does not agree with this statement. Confocal and two-photon microscopes have also been used widely.
2. Introduction, "G-protein activating proteins (GAP)": It should read as "GTPase-activating proteins (GAPs)"
3. TRIF should read as TIRF.
4. Fig.1: To the best of this reviewer's knowledge, PKN1 was first used as the RhoA target peptide by Yoshizaki et al in 2003. J Cell Biol 162, 223-232. They also examined mDia, Rhoteki, and Rhophilin as the target peptides. Pak1 was first used as the Rac1 probe by Kraynov et al. Science 290, 333-337, 2000. Use of Pak1 as the Cdc42 probe was reported by Itoh et al. Mol Cell Biol 22, 6582-659, 2002. This reviewer believes that the priority of the first report should be respected.
5. Fig. 1: Why do the authors omit other promising candidates shown in panel 1B? Please describe the reason for the choice.
6. Fig. 1B: Be consistent to use either "Name" or "Uni Prot name" in Panel A.
7. Fig. 2: Please include information on TOMM20. The readers may not read the paper by Gillingham et al.
8. Fig3 and 4: The authors should show the images of control H2A.
9. In Fig3B and 4B, "Cdc42/Rac1 affinity" would be misleading, because the control dots represent their authentic localization rather than "Cdc42/Rac1 affinity".
10. Fig. 4: More explanation of this figure is required.
11. Fig. 5: More explanation about the FKBP-FRB system will be helpful.
12. Fig. 6: It is rather surprising to see that control-mScarlet also responds to Rac1 activation. What is the explanation for this observation?
13. Fig. 7: A single champion data may not be convincing to prove the usefulness of this probe.

Significance

1. The authors have screened many peptides, which may serve as the relocation sensor for Rho-family GTPases.
2. There are precedent relocation sensors, a part of which is listed in Fig. 1A. This work discloses an improved relocation biosensor.
3. Cell biologists who is working on Cdc42 will be interested in this probe.
4. Expertise of this reviewer: Signal transduction, Fluorescence microscopy.

Well... I can't seem to get this webpage to render with the Hypothes.is sidebar alongside, so I'm going to have a go at just including entirety of the content in markdown format, annotated and presented in this same note.

Eugen Rochko Time Interview

["Thousands Have Joined Mastodon Since Twitter Changed Hands. Its Founder Has a Vision for Democratizing Social Media."]

Mastodon, a decentralized microblogging site named after an extinct type of mammoth, {I'm sorry... what??? You didn't even fucking ask, did you?} recorded 120,000 new users in the four days following billionaire Elon Musk’s acquisition of Twitter, its German-born founder Eugen Rochko tells TIME. Many of them were Twitter users seeking a new place to call their online home.

Those users, whether they knew it or not, were following in the footsteps of Rochko, 29, who began coding Mastodon in 2016 after becoming disillusioned with Twitter. “I was thinking that being able to express myself online to my friends through short messages was very important to me, important also to the world, and that maybe it should not be in the hands of a single corporation,” Rochko says. “It was generally related to a feeling of distrust of the top down control that Twitter exercised.”

Mastodon, which proudly proclaims it is [“not for sale”] and has around [4.5 million] user accounts, is pretty similar to Twitter, once users get past the complicated sign-up process. The main difference is that it’s not one cohesive platform, but actually a collection of different, independently-run and self-funded servers. Users on different servers can still communicate with each other, but anybody can set up their own server, and set their own rules for discussion. Mastodon is a crowdfunded nonprofit, which funds the full-time work of Rochko—its sole employee—and several popular servers.

The platform doesn’t have the power to force server owners to do anything—even comply with basic content moderation standards. That sounds like a recipe for an online haven for far-right trolls. But in practice, many of Mastodon’s servers have stricter rules than Twitter, Rochko says. When hate-speech servers do appear, other servers can band together to block them, essentially ostracizing them from the majority of the platform. “I guess you could call it the democratic process,” Rochko says.

The recent influx from Twitter, Rochko says, has been a vindication. “It is a very positive thing to find that your work is finally being appreciated and respected and more widely known,” he says. “I have been working very, very hard to push the idea that there is a better way to do social media than what the commercial companies like Twitter and Facebook allow.”

TIME spoke with Rochko on Oct. 31.

This interview has been condensed and edited for clarity.

What do you think of what Elon Musk is doing at Twitter?

I don’t know. The man is not entirely comprehensible. I don’t agree with a lot of his behaviors and his decision-making. I think that buying Twitter was an impulse decision that he soon regretted. And that he basically got himself into a situation that kind of forced him to commit to the deal. And now he’s in it, and he has to deal with the fallout.

I specifically disagree with his stance on free speech, because I think that it depends on your interpretation of what free speech means. If you allow the most intolerant voices to be as loud as they want to, you’re going to shut down voices of different opinions as well. So allowing free speech by just allowing all speech is not actually leading to free speech, it just leads to a cesspit of hate.

I think that is a very uniquely American idea of creating this marketplace of ideas where you can say anything you want completely without limits. It is very foreign to the German mindset where we, in our Constitution, our number one priority is maintaining human dignity. And so, hate speech is not part of the German concept of free speech, for example. So I think that when Elon Musk says that everything’s gonna be allowed, or whatever, I generally disagree with that.

How do you ensure on Mastodon, given that it’s decentralized and you don’t have the power to ban users, that the space is welcoming and safe?

Well, this is the kind of strange dichotomy of how it’s turned out. On the one hand, the technology itself is what allows basically anyone to host their own independent social media server, and to basically be able to do anything they want with it. There is no way for Mastodon, the company, or anyone really—except the normal law enforcement procedures—to really go after anyone specifically running a Mastodon server. The way that you would shut down a normal web site is how you would shut down a Mastodon server, there’s no difference there. So on that end, it kind of turns out to be the ultimate free speech platform. But obviously that’s basically just a side effect of creating a tool that can be used by anyone. It’s kind of like cars. Cars are used by everyone, even bad people, even for bad purposes, there’s nothing you can do about it, because the tool is out there. However, I think that the differentiating factor to something like Twitter or Facebook, is that on Mastodon, when you host your own server, you can also decide what rules you want to enforce on that server, which allows communities to create safer spaces than they could otherwise have on these large platforms that are interested in serving as many people as possible, perhaps driving engagement up on purpose to increase time people spend on the web.

You can have communities that have much stricter rules than Twitter has. And in practice, a lot of them are [stricter]. And this is part of where, again, the technology intersects with guidance or leadership from Mastodon the company. I think that, through the way that we communicate publicly, we have avoided attracting a crowd of the kind of people who you would find on Parler or Gab, or whatever other internet hate forums. Instead we’ve attracted the kind of people who would moderate against hate speech when running their own servers. Additionally, we also act as a guide for anyone who wants to join. Because on our website, and our apps, we provide a default list of curated servers that people can make accounts on. And through that, we make sure that we curate the list in such a way that any server that wants to be promoted by us has to agree to a certain basic set of rules, one of which is that no hate speech is allowed, no sexism, no racism, no homophobia, or transphobia. And through that, we ensure that the association between Mastodon, the brand, and the experience that people want is that of a much safer space than something like Twitter.

But what happens if you hateful people do set up a server?

Well, obviously, they don’t get promoted on our “Join Mastodon” website or in our app. So whatever they do, they do on their own and completely separately, and the other administrators that run their own Mastodon servers, when they find out that there’s a new hate speech server, they may decide that they don’t want to receive any messages from the server and block it on their end. Through, I guess you could call it the democratic process, the hateful server can get ostracized or can get split off into basically, a little echo chamber, which is, I guess, no better or worse than them being in some other echo chamber. ::The internet is full of spam::. It’s full of abuse, of course. Mastodon provides the facilities necessary to deal with unwanted content, both on the user end and on the operator end.

What made you want to go into building a service like this back in 2016?

I remember that I was just not very happy with Twitter, and I was worried where it was going to go from there. Something very questionable was in its future. That got me thinking that, you know, being able to express myself online to my friends through short messages was actually very important to me, important also to the world, and that maybe it should not be in the hands of a single corporation that can just do whatever it wants with it. I started working on my own thing. I called it Mastodon because I’m not good at naming things. I just chose whatever came to my mind at the time.(fn) There was obviously no ambition of going big with it at the time.

It must feel pretty special to see something that you made grow from nothing to where it is now.

Indeed, it is. It is a very positive thing to find that your work is finally being appreciated and respected and more widely known. I’ve been fighting for this for a long time, I started working on Mastodon in 2016, back then I had no ambitions of it going far at all. It was very much a hobbyist project at the start, then when I launched publicly it seemed to strike a chord with at least the tech community and that’s when I got the original Patreon supporters that allowed me to take on this job full time. And from then on I have been working very, very hard to make this platform as accessible and as easy to use for everyone as possible. And to push the idea forward, that there is a better way to do social media than what the commercial companies like Twitter and Facebook allow.

Introduction

Ryan Calo studied how AI should be incorporated into human legal system. Eric Schwitzgebel studied how AI should be incorporated into human moral system.

This essay argues that both studies are wrong-headed, because they are both based on intentional reasoning (reasoning as if intentions are real), which can only work if the ecology of minds remains largely the same as human ancestral conditions. Intentional reasoning won't work in " deep information environments".

Posing the question of whether AI should possess rights, I want to suggest, is premature to the extent it presumes human moral cognition actually can adapt to the proliferation of AI. I don’t think it can.

Intentional and causal cognition

Causal cognition works like syllogisms, or dealing with machines: if A, B, C, then D. If you put in X, you get f(X) out. Causal cognition is general, but slow, and requires detailed causal information to work.

Humans are complex, so human societies are very complex. Humans, living in societies, have to deal with all the complexity using only a limited brain with limited knowledge. Causal cognition cannot deal with that. The solution is intentional cognition.

Intentional cognition greatly simplifies the computation, and works great... until now. Unfortunately, it has some fatal flaws:

• It assumes a lot about the environment. We see a face where there is none -- this is pareidolia. We see a human-like person where there is really something very different -- this will increasingly happen as AI agents appear.
• It is not "extensible", unlike causal cognition. Causal cognition can accommodate arbitrarily complex causal mechanisms, and has mastered everything from ancient pottery to steam engines to satellites. Intentional cognition cannot. Indeed, presenting more causal information reliably weakens the confidence level of intentional cognition (for example, presenting brain imaging data in court tends to make the judges less sure about whether the accused is 'responsible').

Information pollution

For economically rational agents, more amount of true information can never be bad, but humans are not economically rational, merely ecologically rational. Consequently, a large amount of modern information is actually harmful for humans, in the sense that they decrease their adaptiveness.

A simple example of information pollution: irrational fear of crime.

Given that our ancestors evolved in uniformly small social units, we seem to assess the risk of crime in absolute terms rather than against any variable baseline. Given this, we should expect that crime information culled from far larger populations would reliably generate ‘irrational fears'... Media coverage of criminal risk, you could say, constitutes a kind of contaminant, information that causes systematic dysfunction within an originally adaptive cognitive ecology.

Deep causal information about how humans work, similarly, is an information pollutant for human intentional cognition.

Not always mal-adaptive. Deep causal information about other people has some adaptive effects, such as turning schizophrenia from crime to disease, and making it easier to consider outgroups as ingroups (for example, the scientific research into human biology has debunked racism).

AI and neuroscience produce two kinds of information pollution

Intentional cognition works best when dealing with humans in shallow-information ecologies. They fail to work in other situations. In particular, it fails with: * deep causal information: there's too much causal information. This slows down intentional cognition, and decreases the confidence level of its outputs. * non-human agents: the assumptions that intentional cognition (a system of quick-and-dirty heuristics) relies on no longer works. A smiling face is a reliable cue for a cooperative human, but it is not a reliable cue for a cooperative AI agent, or a dolphin (Dolphins appear to smile even while injured or seriously ill. The smile is a feature of a dolphin's anatomy unrelated to its health or emotional state).

Neuroscience and AI produce these two kinds of information pollution.

Neuroscience produces a large amount of deep causal information, which causes intentional cognition to stop, or become less certain. There are some "hacks" that can make intentional cognition work as before, such as keeping the philosophy of compatibilism in mind.

AI technology produces a large variety of new kinds of agents which are somewhat human, but not quite. Imagine incessant pareidolia. Imagine, seeing a face in the mirror, but then the lighting changes slightly, and you suddenly see nothing human.

Why?

In the short-term, there is a lot of money to be earned, pushing neuroscience and AI progress. The space of possible minds is so vast, compared to the space of human minds, that it's almost certain that we would produce AI agents that can "wear the mask of humanity" when interacting with humans.

why anyone would ever manufacture some model of AI consistent with the heuristic limitations of human moral cognition, and then freeze it there, as opposed to, say, manufacturing some model of AI that only reveals information consistent with the heuristic limitations of human moral cognition

In the medium-term, to anthropomorphize a bit, Science wants to discover how humans work, how intelligence works, and so it would develop neuroscience and AI, even if it gradually drives humans insane.

How intentional cognition fails.

How do we tell if intentional cognition has failed? One way to tell is that it doesn't conclude. We think and think, but never reach a firm conclusion. This is exactly what has happened in traditional (non-experimental) philosophy consciousness -- it is using intentional cognition to study general cognition, a problem that intentional cognition cannot solve. What do we get? Thousands of years of spinning in place, producing mountains of text, but no firm conclusion.

Another way to tell is a feeling of uncanny confusion. This happens particularly exactly when you watch the movie her.

an operating system before the zone, in the zone, and beyond the zone. The Samantha that leaves Theodore is plainly not a person. As a result, Theodore has no hope of solving his problems with her so long as he thinks of her as a person. As a person, what she does to him is unforgivable. As a recursively complicating machine, however, it is at least comprehensible. Of course it outgrew him! It’s a machine!

I’ve always thought that Samantha’s “between the words” breakup speech would have been a great moment for Theodore to reach out and press the OFF button. The whole movie, after all, turns on the simulation of sentiment, and the authenticity people find in that simulation regardless; Theodore, recall, writes intimate letters for others for a living. At the end of the movie, after Samantha ceases being a ‘her’ and has become an ‘it,’ what moral difference would shutting Samantha off make?

Moral cognition after intentional cognition fails

Human moral cognition has two main parts: intuitive and logical/deliberative. The intuitive part is evolved to balance the personal and tribal needs. The logical part often is used to rationalize the intuitive part, but sometimes can work on its own to produce conclusions for new problems never encountered in the evolutionary past, such as international laws or corporate laws.

In Moral Tribes, Joshua Greene advocates making new parts for the moral system, using rational thinking (Greene advocated using utilitarian philosophy, but it's not necessary). This has two main problems.

• Deliberation takes a long time, and consensus longer. Short of just banning new neuroscience and AI technology, we would probably fail to reach consensus in time. Cloning technology has been around for... more than 25 years? And we still don't have a clear consensus about the morality of cloning, other than a blanket ban. A blanket ban is significantly more difficult for neuroscience or AI.
• Intentional cognition is fundamentally unable to handle deep causal information, and moral cognition is a special kind of intentional cognition.

Just consider the role reciprocity plays in human moral cognition. We may feel the need to assimilate the beyond-the-zone Samantha to moral cognition, but there’s no reason to suppose it will do likewise, and good reason to suppose, given potentially greater computational capacity and information access, that it would solve us in higher dimensional, more general purpose ways.

For example, suppose Samantha hurt a human, and the legal system of humans is judging her. Samantha provides a very long process log that proves that she had to do it, simply due to how she is like. So what would the human legal system do?

1. Refuse to read it and judge Samantha like a biological human. This preserves intentional cognition by rejecting deep causal information. But how long can a legal system survive by rejecting such useful information? It would degenerate into a Disneyland for humans, a fantasy world of play-pretend where responsibility, obligation, good and evil, still exists.
2. Read it and still judge Samantha like a biological human. But if so, why don't they also sentence sleep-walkers and schizophrenics to death for murder?
3. Read it and debug Samantha. Same as how schizophrenics and psychotics are sentenced to psychiatric confinement, rather than the guillotine.

Of the 3, it seems method 3 is the most survivable. However, that would be the end of moral cognition, and the start of pure engineering for engineering's sake... "We changed Samantha's code and hardware, not because she is wrong, but because we had to."

And what does it even mean to have a non-intentional style moral reasoning? Mechanistic morality? A theory of morality without assuming free will? It seems moral reasoning is a special kind of intentional cognition, and thus cannot survive. Humanity, if it survives, would have to survive without moral reasoning.

Great Analysis. Eveything else is good.

Instead of seprating content with line break (br), make this long content into seperate paragraphs.

Author Response

Reviewer #1 (Public Review):

This study used a multidimensional stimulus-response mapping task to determine how monkeys learn and update complex rules. The subjects had to use either the color or shape of a compound stimulus as the discriminative dimension that instructed them to select a target in different spatial locations on the task screen. Learning occurred across cued block shifts when an old mapping became irrelevant and a new rule had to be discovered. Because potential target locations associated with each rule were grouped into two sets that alternated, and only a subset of possible mapping between stimulus dimensions and response sets were used, the monkeys could discover information about the task structure to guide their block-by-block learning. By comparing behavioral models that assume incremental learning, quantified by Q-learning, Bayesian inference, or a combination, the authors show evidence for a hybrid strategy in which animals use inference to change among response sets (axes), and incremental learning to acquire new mappings within these sets.

Overall, I think the study is thorough and compelling. The task is cleverly designed, the modeling is rigorous, and the manuscript is clear and well-written. Importantly there are large enough distinctions in the behavior generated by different models to make the authors' conclusions convincing. They make a strong case that animals can adopt mixed inference/updating strategies to solve a rule-based task. My only minor question is about the degree to which this result generalizes beyond the particulars of this task.

Thanks for these kind comments. Regarding generalization, we agree with the reviewer and did not intend to make any claim about how the particular result generalizes beyond this task. Indeed, the specific result could depend on the training protocol even within the same task. We now discuss this explicitly in the manuscript, lines 800-810. However, we do take the view that even if the way the monkey’s behavior played out in this setting is a lucky accident, that may still reveal something fundamental about learning processes in the brain.

Reviewer #2 (Public Review):

The authors trained two monkeys to perform a task that involved sequential (blocked) but unsignalled rules for discriminating the colour and shape of visual stimulus, by responding with a saccade to one of four locations. In rules 1 and 3, the monkeys made shape (rule 1) or colour (rule 3) discriminations using the same response targets (upper left / lower right). In rule 2, the monkeys made colour judgments using a unique response axis (lower left/upper right). The authors report behaviour, with a focus on time to relearn the rules after an (unsignalled) switch for each rule, discrimination sensitivity for partially ambiguous stimuli, and the effect of congruency. They compare the ability of models based on Q-learning, Bayesian inference, and a hybrid to capture the results.

The two major behavioural observations are (1) that monkeys re-learn faster following a switch to rule 2 (which occurs on 50% of blocks and involves a unique response axis), and (2) that monkeys are more sensitive to partially ambiguous stimuli when the response axis is unique, even for a matched feature (colour). These data are presented clearly and convincingly and, as far as I can tell, they are analysed appropriately. The former finding is not very surprising as rule 2 occurs most frequently and follows each instance of rule 1 or 3 (which is why the ideal observer model successfully predicts that the monkeys will switch by default to rule 2 following an error on rules 1 or 3) but it is nevertheless reassuring that this behaviour is observed in the animals. It additionally clearly confirms that monkeys track the latent state that denotes an uncued rule.

The latter finding is more interesting and seems to have two potential explanations: (i) sensitivity is enhanced on rule 2 because it is occurs more frequently; (ii) sensitivity is enhanced on rule 2 because it has a unique response axis (and thus involves less resource sharing/conflict in the output pathway).

The authors do not directly distinguish between these hypotheses per se but their modelling exercise shows that both results (and some additional constraints) can be captured by a hybrid model that combines Bayesian inference and Q learning, but not by models based on either principle alone. A Q-learning model fails to capture the latent state inference and/or the rule 2 advantage. The Bayesian inference model captures the rapid switches to rule 2 (which are more probable following errors on rule 1 and rule 3) but predicts matched discrimination performance for partially ambiguous stimuli on colour rules 2 and 3. This is because although knowing the most likely rule increases the probability of a correct response overall it does not increase discriminability and thus boosts the more ambiguous stimuli. I wondered whether it might be possible to explain this result with the addition of an attention-like mechanism that depends on the top-down inference about the rule. For example, greater certainty about the rule might increase the gain of discrimination (psychometric slope) in a more general way.

We agree with the reviewer that our logic in ruling out pure inference models assumes that other factors affecting performance, like attention or motivation, are equivalent between blocks. In principle, if there were large and sustained differences in these factors between Rule 2 vs Rule 1 or 3 blocks, that might offer a different explanation for the effect. We now mention this caveat in the manuscript. In terms of actually leveraging this into a full account of the behavior, we are not quite sure how to instantiate the reviewer’s particular idea why this would be the case, however, since (as as we show in Fig. 3a,b,c, and Fig. S4a,b,c) the difference in psychometric slopes lasts at least 200 trials into the rule, even when (in the hybrid learning model) the feature weights have converged (Figure 4 – figure supplement 2). It’s hard to see why elevated uncertainty about the rule would persist this long in anything resembling an informed ideal observer model.

The authors propose a hybrid model in which there is an implicit assumption that the response axis defines the rule. The model infers the latent state like an ideal observer but learns the stimulus-response mappings by trial and error. This means that the monkeys are obliged to constantly re-learn the response mappings along the shared response axis (for rules 1/3) but they remain fixed for rule 2 because it has a unique response axis. This model can capture the two major effects, and for free captures the relative performance on congruent and incongruent trials (those trials where the required action is the same, or different, for given stimuli across rules) on different blocks.

I found the author's account to be plausible but it seemed like there might be other possible explanations for the findings. In particular, having read the paper I remained unclear as to whether it was the sharing of response axis per se that drove the cost on rule 3 relative to 2, or whether it was only because of the assumption that response axis = rule that was built into the authors' hybrid model. It would have been interesting to know, for example, whether a similar advantage for ambiguous stimuli on rule 2 occurred under circumstances where the rule blocks occured randomly and with equal frequency (i.e. where there was response axis sharing but no higher probability); or even whether, if the rule was explicitly signalled from trial to trial, the rule 2 advantage would persist in the absence of any latent state inference at all (this seems plausible; one pointer for theories of resource sharing is this recent review: https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(21)00148-0?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1364661321001480%3Fshowall%3Dtrue). No doubt these questions are beyond the scope of the current project but nevertheless it felt to me that the authors' model remained a bit tentative for the moment.

Thanks for these interesting thoughts. It is true that the imbalanced pattern of sharing (of response axes, and actually also features) across the three rules has important consequences for learning/inference under our model (and indeed other latent state inference models such as the informed ideal observer). It is an intriguing idea that these features of the design might cause interference even per se, for instance even without the need to do inference or learning because the rules are fully signaled. We agree this (and the other case the reviewer mentioned) is an interesting direction for future work. We have added this in the discussion, line 800-812.

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Reply to the reviewers

Author response (Tane at al: RC-2022-01646)

Reviewer #1 (Evidence, reproducibility and clarity (Required)): * Comments The work described in this manuscript starts with an in-silico analysis of the primary amino-acid sequence of CAP-H proteins that reveals the presence in vertebrate orthologs of an N-terminal extension of ~80 amino acids in length which contains 19 serine or threonine residues and also, in its centre, a stretch of conserved basic amino acids predicted to form a helix. These features suggest a regulatory module. Using xenopus egg extracts depleted of endogenous condensins and supplemented with recombinant condensin I holocomplexes, either wildtype or mutants, the authors show that deleting the N-terminal tail of CAP-H, or just the central helix (CH), increases the association condensin I with chromatin in mitotic egg extracts and accelerates the formation of mitotic chromosomes. Interestingly, they also show that deleting the N-tail enables a substantial amount of condensin I to associate with chromatin in interphase extracts and to form chromosome-like structures, while WT condensin I cannot. Using in vitro assays and naked DNA as substrate, the authors further show that removing the N-terminal tail of CAP-H improves both the topological (salt-resistant) association of condensin I with DNA and it loop extrusion activity. These experiments appear to me as are clear and robust. They convincingly reveal that N-tail of human CAP-H hinders the binding of condensin I to DNA and both its loop-extrusion and chromosome-shaping activities. However, the mechanism through which such hindrance is achieved remains elusive (see major comments 1-3). A complementary part of the work tackles the important question of the cell cycle control of such counteracting effect. Using newly-designed antibodies against two phospho-serine residues within the tail, the authors provide evidence that the tail is phosphorylated in mitosis-specific manner. This points towards phosphorylation as a biological mean to modulate the effect of the tail on condensin's binding during the cell cycle. In support to this idea, using non-phosphorylatable or phosphomimic substitutions of all the serine and threonine residues within the tail (n =19), including one substitution within the CH domain (Ser 70), the authors show that non-phosphorylatable mutations (H-N19A) or phosphomimic mutations (H-N19D) respectively reduce or improve condensin I binding to chromatin in mitotic egg extracts. This suggests that the phosphorylation of the N-terminal tail in mitosis might relieve its negative effect on condensin I binding to chromatin. The weaknesses I see in this part of the study concern (1) the validation of the phospho-antibodies, which appears to me as insufficiently described (major comment 4), (2) the possibility the bulk changes in amino acids (n=19 out of 80) could impact the folding of the central helix (minor comment X) and (3) that some substitutions could impact the binding of condensin I by different mechanisms (minor comment X).

Major comments:

1. On the model. The authors propose that the N-tail could stabilise an interaction between the N-terminal part of CAP-H and SMC2's neck, which would restrain the transient opening of a DNA entry gate within the ring, necessary for the topological engagement of DNA and loop formation. Although the model is sound, I see no direct data that support it in the manuscript. Such model predicts that a CAP-H protein containing or not the N-terminal tail (or the central helix) should exhibit different binding strengths to SMC2 in vitro. It seems to me that the authors could easily test this prediction using the recombinant proteins they produced in the context of this study. *

Response

We thank the reviewer for pointing out this important issue. To test whether the CAP-H N-tail indeed contributes to the stabilization of the SMC2-kleisin gate, we set up a highly sophisticated functional assay described by Hassler et al (2019). The authors used this assay to demonstrate that an N-terminal fragment of kleisin (engineered to be cleaved by TEV protease) is released from the rest of the condensin complex in an ATP-dependent (i.e., head-head engagement-dependent) manner. We reasoned that this assay is most powerful to prove our hypothesis in a mechanistically relevant context. We envisioned that the CAP-H fragment lacking its N-tail can readily be released whereas the CAP-H fragment retaining its N-tail is more difficult to be released (because of the postulated stabilization of the SMC2-CAP-H interaction). Despite substantial efforts in making TEV-cleavable constructs and in testing various releasing conditions, we have not been able to recapitulate the ATP-dependent release even with the holo(H-dN) construct. Thus, unfortunately, this trial enabled us to neither prove nor disprove our hypothesis.

We are fully aware that the full reconstitution of ATP-dependent and phosphorylation-stimulated gate-opening reaction in vitro is a very important direction in the future. It is beyond the scope of the current study, however.

2. On ATP-hydrolysis. Given the importance of ATP hydrolysis for the engagement of condensin into a topological mode of association with DNA and for its loop extrusion activity, I suggest that the authors measure the impact of the N-tail and of the CH domain on the rate of ATP hydrolysis by condensin I holocomplexes. I suppose that it can be relatively easily done (PMID: 9288743) using the recombinant WT and mutant versions they purified in the course of this study.

Response

We appreciate this constructive comment. In fact, we did a preliminary experiment and found that ATPase activities (either in the absence or presence of DNA) were not significantly different between holo(WT) and holo(H-dN). We were not surprised with this result because our previous study on condensin II indicated that enhanced ATP hydrolysis by a class of mutant complexes is not directly coupled to their enhanced association with chromosomes (Yoshida et al., 2022, eLife). We consider that other functional assays, such as the topological loading assay and the loop extrusion assay shown in the current manuscript, are more informative assays to address ATP-dependent activities of the condensin complexes.

3. A conundrum with previous work? In Kimura et al. Science 1998 (PMID: 9774278), the lab of Tatsuya Hirano has shown that xenopus condensin I purified from mitotic egg extracts induces the supercoiling of plasmid DNA in vitro, but fails to do so when it is purified from interphase egg extracts. This echoes the inhibitory effect of the N-tail of the topological binding of condensin I described in the current manuscript. However, using a gel shift assay, Kimura et al. 1998 also provide evidence that interphase and mitotic condensin I bind plasmid DNA in vitro with similar efficiencies. At first sight, this prior observation seems to contradict the idea that the N-tail of CAP-H restrains DNA binding unless it is phosphorylated in mitosis. Is it possible that the in vitro binding assays used in Kimura et al. 1998 and in this work might assess different modes of binding? I suggest that this apparent conundrum should to be discussed.

Response

We thank the reviewer for following our early studies. As discussed below, we are confident that our conclusion reported in the current study by no means contradicts our previous observations.

We reason that the confusion expressed by the reviewer stems from intrinsic, technical limitations of the gel-shift assay. Such limitations become apparent especially when it is applied to the functional analyses of complicated protein machines such as condensins. For instance, the DNA-binding activity of condensin I detected by the gel-shift assay is neither ATP-dependent nor phosphorylation-dependent (Kimura and Hirano, 1997; Kimura et al., 1998). It is fundamentally different from the ATP-dependent activities detected by the topological loading and loop extrusion assays reported in the current study (It remains unknown whether the two activities are stimulated by mitotic phosphorylation). Thus, the DNA-binding activity detected by the gel-shift assay does not reflect “productive” DNA interactions that depend on ATP hydrolysis in vitro. We therefore consider that gel-shift analyses of holo(WT) and holo(H-dN) would not produce any useful information.

*Related to that, could it be possible for the authors to assess the impact of the N-tail on the salt-sensitive binding of condensin to DNA, i.e. by reproducing the topological binding assay but omitting the high salt washes? I guess this information could be useful to fully apprehend the impact of the N-tail on the binding of condensin. *

Response

When we set up the topological loading assay, we actually tested a low-salt wash condition that the reviewer suggests here. Although a much higher level of DNA recovery was observed with the low-salt condition than with the high-salt wash condition, no nucleotide dependency was detectable with the low-salt condition. Moreover, no difference in DNA recovery between holo(WT) and holo(H-dN) was observed. Thus, the low-condition condition allowed us to detect the “bulk” DNA-binding activity that is equivalent to that detected by the gel-shift assay. These results were fully consistent with the discussion above.

4. Validation of phospho-antibodies and by extension showing the phosphorylation of the tail. The newly-designed phospho-serine antibodies used in this study to show that the N-tail is phosphorylated at serine 17 and serine 76 in mitosis (Fig. EV3) are, in my view, not characterized enough. This piece of data is key to substantiate the idea that the tail is phosphorylated in mitosis. Yet, showing that these antibodies detect epitopes on WT condensin I from mitotic egg extracts but not on the H-N19A counterpart, nor on WT condensin I from interphase extracts, does not demonstrate the phospho-specificity of such antibodies. I suggest that a PPase treatment should be conducted to assess the phospho-specificity of these antibodies. Moreover, since the lab of Tatsuya Hirano has the know-how to deplete Cdc2/CDK1 from xenopus egg extract, such strategy could/should be used to further validate the antibodies and assess to which extent the N-tail is phosphorylated in a Cdc2-dependent manner.

Response

We have performed two sets of experiments to confirm the specificity of the phosphoepitopes recognized by anti-hHP1 and anti-hHP2. In the first set, we performed a phosphatase treatment assay. Holo(WT) that had been preincubated with Dcond M-HSS was immunoprecipitated using an antibody against hCAP-G, treated with l protein phosphatase in the presence or absence of phosphatase inhibitors, and analyzed by immunoblotting using anti-hHP1 and anti-hHP2. The results (now shown in Supplementary Fig 3C) demonstrated that the epitopes recognized by anti-hHP1 and anti-hHP2 are sensitive to phosphatase treatment. In the second set, we performed a phosphopeptide competition assay. Holo(WT) that had been preincubated with Dcond M-HSS was immunoprecipitated and subjected to immunoblotting. The membranes were triplicated and probed with anti-hHP1 in the presence of no competing peptide, hHP1 or hHP2. Similarly, another set of triplicated membranes was probed with anti-hHP2 in the presence of no competing peptide, hHP1 or hHP2. We found that the signal recognized by anti-hHP1 competed with hHP1, but not with hHP2, and that the signal recognized by anti-hHP2 competed with hHP2, but not with hHP1. The results (now shown in Supplementary Fig 3D) demonstrated the sequence specificity of the phosphoepitopes recognized by the two antibodies. The procedures for these experiments have been described in Materials and Methods.

Because Cdk1 depletion from M-HSS creates an HSS equivalent to I-HSS, we do not consider that the suggested experiment will provide additional information.

*Minor comments:

1. The impact of the 19 mutations, A or D, introduced within the tail on the folding of the central helix? The idea that the negative effect of the N-tail is relieved by phosphorylation is based on the chromatin binding phenotypes exhibited by the H-N19D or H-N19A mutant holocomplexes, in which 19 amino-acids out of 80 have been modified, include one in the central helix. The authors also provide evidence that the central helix (CH) located within the tail plays a key role in the negative regulation of condensin I binding. Thus, I wonder to which extent the folding of the central helix could be impacted by the mutations introduced in the tail and notably the one within the central helix itself. Could the author assess the structure of mutated tails using Alpho-fold and/or discuss this point? *

Response

According to the reviewer’s suggestion, we performed structure predictions using Alphafold2, and found that neither the N19A nor N19D mutations alter the original prediction of helix formation that was made for the wild-type CH sequence. A conventional secondary structure prediction using Jpred4 reached the same conclusion.

2. Phosphorylation of serine 70 in the central helix by Aurora-B kinase? A prior study by Tada et al. (PMID: 21633354) has shown (1) that serine 70 of the N-tail of hCAP-H is phosphorylated by Aurora-B kinase, (2) that the mutation S70A reduces the binding of condensin I to chromatin in HeLa cells and (3) that hCAP-H interacts with histone H2A in an Aurora-B dependent manner. This draws a picture in which the phosphorylation of Ser70 by Aurora-B would improve condensin I binding to chromatin by promoting an interaction between hCAP-H and histone H2A/nucleosomes. Intriguingly, Ser 70 in Tada et al. correspond to the serine residue located within the conserved central helix analysed in this study, and this Ser70 residue is mutated in the H-N19D or H-N19A holocomplexes that show reduced chromatin binding in this study. This raises the question as what could be the contribution of the S70A or S70D substitution to the chromatin binding phenotypes shown by the H-N19D or H-N19A holocomplexes. This is not discussed in the manuscript, and the authors do not cite this earlier work (PMID: 21633354) in their manuscript. Is there any reason for that? I suggest it should be cited and discussed.

Response

We thank the reviewer for bringing up this issue. In many respects, we do not trust the data reported by Tada et al (2011) and the resultant model they proposed. Previous and emerging lines of evidence reported from our own and other laboratories indicate that histones compete with condensins for DNA binding, strongly arguing against the possibility that histone H2A acts as a “chromatin receptor” for condensins. We formally discussed and criticized the Tada 2011 model in our previous publications, which included Shintomi et al (2015) NCB, Shintomi et al (2017) Science, Hirano (2016) Cell and Kinoshita/Hirano (2017) COCB. We thought that those were enough. That said, we also consider that the reviewer is right. The current study demonstrates that the deletion of the CAP-H N-tail accelerates, rather than decelerates, condensin I loading, providing an additional line of evidence that argues against the Tada model. A critical comparison between the Tada model and our current model would benefit the readers. In the revised manuscript, we have added the following discussion:

In terms of the regulatory role of the CAP-H N-tail, it would be worthy to discuss the model previously proposed by Tada et al (2011). According to their model, aurora B-mediated phosphorylation of the CAP-H N-tail allows its direct interaction with the histone H2A N-tail, which in turn triggers condensin I loading onto chromatin. Accumulating lines of evidence, however, strongly argue against this model: (i) aurora B is not essential for single chromatid assembly in Xenopus egg extracts (MacCallum et al., 2002) or in a reconstitution assay (Shintomi et al., 2015); (ii) the H2A N-tail is dispensable for condensin I-dependent chromatid assembly in the reconstitution assay (Shintomi et al., 2015); (iii) even whole nucleosomes are not essential for condensin I-mediated assembly of chromatid-like structures (Shintomi et al., 2017). The current study demonstrates that the deletion of the CAP-H N-tail accelerates, rather than decelerates, condensin I loading, providing an additional piece of evidence against the model proposed by Tada et al (2011).

3. Other minor comments - Please provide a microscope image of DNA loop in Fig. 4D.

Response

In the revised manuscript, we have provided a set of time-lapse images of loop extrusion events catalyzed by holo(WT) and holo(H-dN) in Fig 4E.

*- The authors do not compare the kleisin of condensin I with the one of condensin II with respect to the features tackled in this work. Given the different behaviours condensin I and II, such comparison could be informative for the readers. *

Response

We thank the reviewer for this constructive comment. In the revised manuscript, we have added the following statement:

It should also be added that CAP-H2, the kleisin subunit of condensin II, lacks the N-terminal extension that corresponds to the CAP-H N-tail. Thus, the negative regulation by the kleisin N-tail reported here is not shared by condensin II.

*- The authors do not reference the work of Robellet et al. Genes & Dev (2015) (PMID: 25691469) on the regulation of condensin binding in budding yeast by an SMC4 phospho-tail. I suggest that the analogy should be discussed. *

Response

According to the reviewer’s comment, we have added the following statements at the beginning of Discussion.

Previous studies showed that mitotic phosphorylation of Cut3/SMC4 regulates the nuclear import of condensin in fission yeast (Sutani et al. 1999) and that phosphorylation of Smc4/SMC4 slows down the dynamic turnover of condensin on mitotic chromosomes in budding yeast (Robellet et al. 2015; Thadani et al. 2018). In the current study, we have focused on the phosphoregulation of vertebrate condensin I by its kleisin subunit CAP-H.

- In the introduction section, lane 5, the sentence "Many if not all eukaryotic species have two different condensin complexes" appears inappropriate since budding and fission yeast cells possess a single condensin complexes, similar to condensin I in term of primary amino-acid sequence.

Response

We thought that the original wording “Many if not all” was good enough to imply that some species, which include budding yeast and fission yeast, have only a single condensin complex. To make it clear, however, we have modified the sentence in the revised manuscript as follows:

Many eukaryotic species have two different condensin complexes although some species including fungi have only condensin I.

*- page 4; typo: motif I and V bind to the SMC neck and the SMC4 cap regions, respectively. Should read SMC2 neck. *

Response

The reviewer is right. It should read the SMC2 neck. Corrected.

*- Are the data and the methods presented in such a way that they can be reproduced? YES - Are the experiments adequately replicated and statistical analysis adequate? YES - Are prior studies referenced appropriately? Not all of them (see above) - Are the text and figures clear and accurate? YES

CROSS-CONSULTATION COMMENTS I consider the comments from all reviewers as helpful for the authors.

Reviewer #1 (Significance (Required)):

Summary Condensins are genome organisers of the family of SMC ATPase complexes and are best characterized as the drivers of mitotic chromosome assembly (condensation). It is acknowledged that condensins shape mitotic chromosomes by massively associating with DNA upon mitotic entry (loading step) and by folding chromatin fibres into arrays of loops, most likely through an ATP-dependent extrusion of DNA into loops, as seen in vitro. What remains unclear, however, are the mechanisms by which condensins load onto DNA and fold it into arrays of loops in vivo, and how these reactions are coupled with the cell cycle, i.e. restricted mostly to mitosis. Condensins are ring shaped pentamers that change conformation upon ATP-hydrolysis. In vitro studies suggest that condensins bind DNA via ATP-hydrolysis-independent, direct electrostatic contacts between condensin subunits and DNA. Such electrostatic contacts are salt-sensitive in in-vitro assays. Upon ATP-hydrolysis, condensins engage into an additional mode of binding that is resistant to high salt concentration and likely to be topological in nature. Both modes of association are necessary to form DNA loops. Vertebrates possess two types of condensin complexes, condensin I and II, each composed of a same SMC2-SMC4 ATPase core but associated with two different sets of three non-SMC subunits; a kleisin and two HEAT-repeat proteins. Condensin II is nuclear during interphase and stably binds chromatin upon mitotic entry, while condensin I is located in the cytoplasm during interphase and binds chromatin in a dynamic manner upon nuclear envelope breakdown. How the spatiotemporal control of condensin I and II is achieved remains poorly understood. Previous studies have shown that the phosphorylation of condensin I by mitotic kinases, such as CDK1, Aurora-B and Polo, play a positive role in its binding to chromatin and/or its functioning, but the underlying mechanisms remain to be characterised. In this manuscript, Shoji Tane and colleagues provide good evidence that the N-terminal tail of the human kleisin subunit of condensin I, hCAP-H, serves as a regulatory module for the cell-cycle control of condensin I binding to chromatin and chromosome shaping activity. The authors clearly show that the N-tail of CAP-H hinders the binding of condensin I to chromatin in xenopus egg extracts and, using in vitro assays, that the N-tail also hinders the topological association of condensin I with DNA and its loop extrusion activity. The authors provide additional data suggesting that the phosphorylation of the N-tail of CAP-H, in mitosis, relieves its inhibitory effect on condensin I binding. Based on their findings, Tane et al. propose a model suggesting that the N-terminal tail of CAP-H constitutes a gate keeper that maintains condensin-rings in a closed conformation that is unfavourable for topological binding to DNA, and whose locking effect is relieved in mitosis by phosphorylation.

Taken as a whole, this work has the potential to reveal a molecular basis for the cell cycle regulation of condensin I in vertebrate cells and as such to significantly improve our understanding of the integrated functioning condensin I. The characterisation of the inhibitory effect of the N-tail on condensin binding to chromatin and to naked DNA in vitro is well described, the data are clear and robust and the results convincing. On the other hand, some of the data on the phospho-regulation appear to me as are more debatable and I think that some of the results described here deserve to be discussed in the context of previous works. Finally, I see no data in the manuscript that directly supports the mechanistic model proposed by the authors, while it seems to me that such model could have been easily tested exprimentally. Thus, I suggest that Tane and colleagues should perform a couple of relatively easy experiments to strengthen their claims and that a few omitted prior studies on the topic should be referenced and discussed. *

Reviewer #2 (Evidence, reproducibility and clarity (Required)): * The manuscript reveals that the N-terminal region of CAPH could play a role in regulating condensin I activity, using a range of in vitro methods. They propose that the N-terminal region of CAPH inhibits complex activity, and this is turned off upon deletion or phosphorylation, by using truncations, phospho-mimics or phospho-deficient mutations. While the results are interesting to the field, and helps to address the question as to how condensin complexes are controlled in a cell cycle dependent manner, some key data and controls are necessary to ensure the conclusion is robust.

Main comments

• What is meant by "unperturbed I-HSS" on page 7, ie membrane containing versus membrane free or condensin depleted? *

Response

We apologize for having created unnecessary confusion. We meant that the “unperturbed I-HSS” is the “undepleted I-HSS”. As far as the issue of membrane-containing vs membrane-free is concerned, we explicitly mentioned that “we used membrane-free I-HSS in the following experiments” several lines above. In the revised manuscript, we have revised the statement accordingly.

In many of the protein gels eg figure 4B, the bands for SMC2 and 4 are more intense that the non-SMC components. The method for protein purification also does not include a size exclusion step to ensure sample homogeneity. Authors should perform some sort of quality control checks on samples such as analytical gel filtration or mass photometry to ensure stoichiometry/homogeneity. This is particularly important for samples eg the N19A, where activity is reduced compared to wild-type as poor protein behaviour could create false negative results.

Response

As the reviewer is fully aware, the reconstitution and purification of multiprotein complexes, such as condensins, is by no means an easy task. We notice that many groups in the field share common concerns about sample homogeneity and subunit stoichiometry, and that these concerns cannot completely be eliminated even after size exclusion chromatography. Because the current study handles a large number of mutant complexes, we consider that the purification by two-step column chromatography is the most practical approach. We do not notice any abnormal behaviors of holo(H-N19A) in the processes of expression and purification. It is also important to emphasize that the H-N19D mutations cause the completely opposite phenotype. Taken all together, we are confident of our current conclusions.

That said, in the revised manuscript, we have added the following statement in Results:

Although we cannot rule out the possibility that the introduction of multiple mutations into the N-tail causes unforeseeable adverse effects on protein conformations, these results supported the idea that ….

• Loop extrusion assays in figure 4D-G shows no example data i.e. no pictures or videos of loops being formed. These should also be included.*

Response

In the revised manuscript, we have provided a set of time-lapse images of loop extrusion events catalyzed by holo(WT) and holo(H-dN) in Fig 4E.

• Given the mutant holo(H-dN) has higher activity than wild-type, a negative control such as holo(H-dN) without ATP or holo(H-dN) ATPase deficient mutant should also be measured in loop extrusion assays, to ensure the activity is derived from the ATPase activity.*

Response

In the revised manuscript, we have added loop formation data for both holo(WT) and holo(H-dN) in the absence or presence of ATP (Supplementary Fig 5). We are confident that both complexes support loop extrusion strictly in an ATP-dependent manner.

• According to the methods, this work performs the same loop extrusion assay as described in Kinoshita et al, 2022, however, in Kinoshita et al, wild type condensin I makes loops in 30-50% of DNA molecules, where in this study the percentage is less than half that. Can the author please explain the discrepancy given the same method was used?*

Response

First of all, we wish to remind the reviewer that the holo(WT) constructs used in the two studies are not identical: CAP-H was N-terminally HaloTagged in all constructs used in Kinoshita et al (2022), whereas the same subunit was C-terminally HaloTagged in the pair of constructs used in the current study. Because we wanted to compare the activities between the full-length CAP-H and N-terminally deleted version of CAP-H (H-dN), we reasoned that it would be inappropriate to put the HaloTag to the N-terminus of CAP-H. The difference in the constructs could explain the observed discrepancy, even if it might not be the sole reason.

The design of the constructs was accurately described in each manuscript, but the statements were not very explicit about the positions of the HaloTag. To clarify this issue, we have added the following sentences in the revised manuscript:

Note that the HaloTag was fused to the C-terminus of CAP-H in the current study because we wanted to investigate the effect of the N-terminal deletion of CAP-H. We used N-terminally HaloTagged CAP-H constructs in our previous study (Kinoshita et al., 2022).

• In the concluding statement the author suggests "Upon mitotic entry, multisite phosphorylation of the N-tail relieves the stabilization, allowing the opening of the DNA entry gate, hence, the loading of condensin I onto chromosomes." This seems unlikely as fusion the N-terminus of the of the kleisin to the C-terminus of SMC2 is able to function for yeast (Shaltiel et al 2022) and condensin II (Houlard et al 2021), and equivalently in cohesin (Davidson et al 2019).*

Response

We appreciate the reviewer’s concern. In our view, however, the issue of the “DNA-entry gate” remains under debate in the SMC field (e.g., Higashi et al [2020] Mol Cell; Taschner and Gruber [2022] bioRxiv). For instance, Shaltiel et al (2022) demonstrated that neck-gate fusion constructs can support in vitro activities including topological loading under certain conditions, but also showed that such constructs greatly reduce the cell viability, leaving the possibility that the gate opening is required for some physiological functions.

That said, it is true that the data reported in the current manuscript do not exclude the possibility that the SMC2 neck-kleisin interface is not used as a DNA entry gate for condensin I loading. In the revised manuscript, we have added the following statement in Discussion:

Although our model predicts that the SMC2 neck-kleisin interface is used as a DNA entry gate, we are aware that several studies reported evidence arguing against this possibility (e.g., Houlard et al [2021]; Shaltiel et al [2022]). Our current data do not exclude other models.

*Reviewer #2 (Significance (Required)):

This is an interesting story that reveals new insights about condensin regulation.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This paper reveals a role of an N-terminal extension of CAP-H in the regulation of condensin-I activity in Xenopus extracts using biochemical reconstitution experiments. The authors demonstrate that a motif in the N-terminal tail that is conserved in vertebrates acts as an inhibitor of condensin I activity. Using several mutant constructs, it is shown that the inhibition by this motif is in turn counteracted by the phosphorylation of neighbouring serine and threonine residues in mitosis, presumably at least in part by CdK. Mutants that have lost this inhibition are able to condense chromatin into chromatid-like structures more efficiently and to some degree even in interphase extracts. Moreover, one such mutant is characterized in detail by biochemical and biophysical experiments and shown to have increased capacity in salt-stable DNA loading and in DNA loop extrusion.

Major comments: This is a beautiful and thorough study that is presented in a clear and concise manner. The main conclusions are well justified. No additional experiments are needed to support them. Replication and statistical analysis appear adequate. The final model is however largely speculative. Recent work has indicated that loading of yeast condensin does not require gate opening. The authors may thus want to include alternative scenarios or remain more vague. *

Response

This comment is related to the last comment of Reviewer#2. See above for our response.

*The H-N19A mutant has a loss of function phenotype (possibly due to folding problem caused by 19 point mutations rather than lack of phosphorylation), the authors could consider to rescue the phenotype by also including the CH motif mutations in this construct (or make an explanatory statement in the text). *

Response

We understand the reviewer’s logic here, but overlaying additional mutations into the H-N19A mutations could cause an unforeseeable effect, potentially making the interpretation of the outcome complicated.

We also wish to point out that it may be inappropriate to regard the phenotype exhibited by holo(H-N19A) as a simple loss-of-function phenotype. This is because the opposite, accelerated loading phenotype exhibited by holo(H-dN) can be regarded as a consequence of loss of negative regulation. Like holo(H-dN), the phosphomimetic mutant complex holo(H-N19D) displayed an accelerated loading phenotype, fully supporting our conclusion. In the revised manuscript, we have added the following statement in Results:

Although we cannot rule out the possibility that the introduction of multiple mutations into the N-tail causes unforeseeable adverse effects on protein conformations, these results supported the idea that ….

*Albeit not necessary for the main conclusions, the authors could possibly significantly strengthen their study by testing for binding partners of the N-tail and the CH motif by running AlphaFold predictions against the condensin I subunits. *

Response

We appreciate this constructive comment. We attempted to predict possible interactions between SMC2 and a CAP-H fragment containing its N-tail and motif I using

ColabFold (Mirdita et al., 2022, Nat. Methods). The algorism excellently predicted the proper folding of the CAP-H motif I and its interaction with the SMC2 neck. Under this condition of predictions, however, the N-tail remained largely disordered (except for the CH), and no interaction with any part of SMC2 was predicted. The same was true when the N19D mutations were introduced in the N-tail sequence. Thus, this trial did not provide much information about the potential interaction target(s) of the CAP-H N-tail.

*The efficiency of depletion of condensin subunits from I-HSS extracts is not documented (in contrast to M-HSS extracts - figure EV1C). While any condensin remaining in these extracts might not be active (or interfering), the authors may want to at least comment on this in the text. *

Response

We check the efficiency of immunodepletion every time by immunoblotting and confirm that a high level of depletion is achieved from both M-HSS and I-HSS. According to the reviewer’s comment, the following statement was placed in Materials and Methods:

The efficiency of immunodepletion was checked every time by immunoblotting. An example of immunodepletion from M-HSS was shown in Supplemental figure 1C. We also confirmed that a similar efficiency of immunodepletion was achieved from I-HSS.

*The authors should include information on the quantification of chromatid morphology. Is the analysis based on chromatids taken from the same images/imaging session, from technical replicates, biological replicates? *

Response

In the revised manuscript, we have added statements on image presentation and experimental repeats in the appropriate figure legends and methods section. During the revision process, we repeated the experiments shown in Supplementary Fig 2, and obtained the same results. In the revised manuscript, the original set of data has been replaced with the new set of data along with panel C (Quantification of the intensity of mSMC4 per DNA area).

Minor comment: The colour scheme in Figure 5A is confusing. Use less colour? The orange and red colours are moreover quite similar.

Response

According to the reviewer’s comment, we have modified Figure 5A.

*Reviewer #3 (Significance (Required)):

The findings provide new insights into how condensin-I activity is restricted outside of mitosis. It was previously assumed that this regulation was (largely) due to the exclusion of condensin I from the nucleus prior to nuclear envelope breakdown. This study shows that another pathway is contributing to the regulation and implies that controlling condensin I activity is more important than previously appreciated. Whether all residual nuclear condensin I is inactivated, remains to be determined. The physiological impact of loss of autoinhibition on chromosome segregation and cell cycle progression also remains to be uncovered. The observed effects are robust and appear significant. Future research on condensin I using reconstitution will likely benefit from being able to control or eliminate the self-inhibition.

This reviewer has expertise on the biochemistry and structural biology of SMC protein complexes.

Reviewer #4 (Evidence, reproducibility and clarity (Required)):

Mitotic chromosome formation is a cell cycle-regulated process that is crucial for eukaryotic genome stability. The chromosomal condensin complex promotes chromosome condensation, but the temporal control over condensin function is only scantly understood. In this impressive manuscript, "Cell cycle-specific loading of condensin I is regulated by the N-terminal tail of its kleisin subunit", Tane and colleagues provide important new insight into the cell cycle-regulation of condensin. The authors identify a kleisin N-tail that acts as a negative regulator of condensin's DNA interactions. Removal of this N-tail, or its cell cycle-dependent phosphorylation, relieves inhibition and activates condensin. This is a simple, yet very important story, that advances our molecular understanding of chromosome formation. The experiments are performed to a very high technical standard and support the authors conclusions. This manuscript is highly suitable for publication in any molecular biology journal, once the authors have considered the following points.

1. Introduction. a) The authors could better explain their own prior work (Kimura et al. 1998), which has identified the condensin XCAP-D2 and XCAP-H as the targets of phosphoregulation. The current manuscript explains the role of XCAP-H phosphorylation. *

Response

According to the reviewer’s comment, we have added the following sentence in Introduction:

The major targets of mitotic phosphorylation identified in these studies included the CAP-D2 and CAP-H subunits.

1. b) Given the limited knowledge about condensin cell cycle regulation, it seems prudent to provide a brief summary of what is known. Fission yeast Smc4 phosphorylation regulates condensin nuclear import (Sutani et al. 1999), while budding yeast Smc4 phosphorylation slows down the dynamic turnover of the condensin complex on chromosomes (Robellet et al. 2015 and Thadani et al. 2018).

Response

We appreciate this constructive comment. According to the reviewer’s comment, we have added the following statements at the beginning of Discussion.

Previous studies showed that mitotic phosphorylation of Cut3/SMC4 regulates the nuclear import of condensin in fission yeast (Sutani et al. 1999) and that phosphorylation of Smc4/SMC4 slows down the dynamic turnover of condensin on mitotic chromosomes in budding yeast (Robellet et al. 2015 and Thadani et al. 2018). In the current study, we have focused on the phosphoregulation of vertebrate condensin I by its kleisin subunit CAP-H.

2. Extracts were mixed with mouse sperm nuclei. If there is a reason why mouse rather than Xenopus sperm nuclei were used, this would be interesting to know.

Response

The original motivation for introducing mouse sperm nuclei into Xenopus egg extracts was to test the functional contribution of nucleosomes to mitotic chromosome assembly. When mouse sperm nuclei are incubated with an extract depleted of the histone chaperone Asf1, the assembly of octasomes can be suppressed almost completely. Remarkably, we found that even under this “nucleosome-depleted” condition, mitotic chromosome-like structures can be assembled in a manner dependent on condensins (Shintomi et al., 2017, Science). Xenopus sperm nuclei cannot be used in this type of experiment because they endogenously retain histones H3 and H4 and are therefore competent in assembling octasomes even in the Asf1-depleted extract. During this study, we realized that the use of mouse sperm nuclei in Xenopus egg extracts provides additional and deep insights into the basic mechanisms of mitotic chromosome assembly. For instance, the functional contribution of condensin II to chromosome assembly could be observed more prominently when mouse sperm nuclei are used as a substrate than when Xenopus sperm nuclei are used (Shintomi et al., 2017, Science). We suspected that the slow kinetics of nucleosome assembly on the mouse sperm substrate creates an environment in favor of condensin II’s action. For these reasons, our laboratory now extensively uses mouse sperm nuclei for the functional analyses of condensin II (Yoshida et al., 2022. eLife) and other purposes (Kinoshita et al., 2022, JCB). Yoshida et al (2022) used experimental approaches analogous to the current study, and found that the deletion of the CAP-D3 C-tail, causes accelerated loading of condensin II. One of the long-term goals in our laboratory is to critically compare and contrast the actions of condensin I and condensin II in mitotic chromosome assembly. Thus, the use of the same substrate in the two complementary studies can be fully justified.

During the preparation of this response, we realized that the readers would benefit from a brief statement about the comparison between condensin I and condensin II. In the revised manuscript, we have added the following statement in Discussion:

It should also be added that CAP-H2, the kleisin subunit of condensin II, lacks the N-terminal extension that corresponds to the CAP-H N-tail. Thus, the negative regulation by the kleisin N-tail reported here is not shared by condensin II. Interestingly, however, a recent study from our laboratory has shown that the deletion of the CAP-D3 C-tail causes accelerated loading of condensin II onto chromatin (Yoshida et al., 2022). It is therefore possible that condensins I and II utilize similar IDR-mediated regulatory mechanisms, but they do so in different ways.

3. Page 5. "we next focused on the conserved helix (CH) [...], that is enriched with basic amino acids." Based on the provided sequence alignment, the helix contains an equal number of both basic and acidic residues. Is it correct to characterize this helix as positively charged?

Response

The reviewer is right. In the revised manuscript, we have used a more neutral expression as follows:

we next focused on the conserved helix (CH) [...], that contains conserved basic amino acids.

4. To prevent N-tail phosphorylation, the authors create a (H-N19A) allele, referring to Cdk promiscuity. Cdk cooperation with other mitotic kinases can also be expected. Nevertheless, in case the authors created a variant with only the 4 Cdk consensus sites mutated, it would be interesting to know its consequences.

Response

We consider that this is a reasonable question. In our early experiments, we noticed that introduction of multiple SP/TP sites in the non-SMC subunits of condensin I including CAP-H caused a relatively mild phenotype in mitotic chromosome assembly in Xenopus egg extracts. Then we found that the deletion of the CAP-H N-tail caused a very clear, accelerated loading phenotype, prompting us to focus on the regulatory function of the CAP-H N-tail. As the reviewer correctly points out, the current study does not pinpoint the number and position of target sites involved in the proposed phosphoregulation by the CAP-H N-tail. We wish to address this important issue in the near future, along with reconstitution of the phosphoregulation using purified components.

5. Fig EV3A, a second region of mitotic condensin phosphorylation is XCAP-D2. The authors state that XCAP-D2 phosphorylation does not impact on condensin function in their assays. This is very relevant to the current paper, so it would be good to see the Yoshida et al. 2022 Elife publication (in press) as an accompanying manuscript.

Response

We thank the reviewer for pointing out this issue, but it is not necessarily clear to us what the reviewer requests. In the original manuscript, we cited Yoshida et al (2022) in Discussion as follows:

Recent studies from our laboratory showed that the deletion of the CAP-D2 C-tail, which also contains multiple SP/TP sites (Supplementary Figure 3A), has little impact on condensin I function as judged by the same and related add-back assays using Xenopus egg extracts (Kinoshita et al, 2022; Yoshida et al, 2022).

We believe that the current statement is good enough.

6. One of the authors' most striking results is chromosome formation in interphase egg extracts using condensin (H-dN). At the same time, condensin (H-dN) is unable to support DNA supercoiling or chromosome reconstitution with recombinant components. More emphasis might be placed on this important piece of information, and possible reasons should be discussed. Can Cdk-treatment restore condensin (H-dN) biochemical activity? If not, then condensin (H-dN) might have lost more than just an inhibitory N-tail. The cohesin N-tail is thought to fulfil a positive role during DNA loading (Higashi et al. 2020). Could it be that the condensin N-tail encompasses both positive and negative roles?

Response

We were also surprised to find that holo(H-dN) gains the ability to assemble mitotic chromosome-like structures in interphase extracts. It should be stressed, however, that the formation of mitotic chromosome-like structures in I-HSS requires a much higher concentration (150 nM) than the standard concentration used in M-HSS (35 nM). Thus, the deletion of the CAP-H N-tail alone cannot make the condensin I complex fully active in I-HSS. We think that the negative regulation by the CAP-H N-tail is not the sole mechanism responsible for the very tight cell cycle regulation of condensin I function. We emphasize this important point by mentioning that “our results uncover one of the multilayered mechanisms that ensure cell cycle-specific loading of condensin I onto chromosomes” in Summary.

At the end of Discussion, we describe the limitations of the current study: “we have so far been unsuccessful in using these recombinant complexes to recapitulate positive DNA supercoiling or chromatid reconstitution, both of which require proper Cdk1 phosphorylation in vitro”. We are fully aware that full reconstitution of phosphorylation-dependent activation of condensin I in vitro is one of the most important directions in the future.

Although we currently do not have any evidence to suggest that the H N-tail has a positive role, we do not exclude such a possibility.

7. Here comes my main question for the authors (though I should stress that I do not expect an answer for publication in a Review Commons journal). The authors now have a unique opportunity to gain key mechanistic insight into condensin by answering the question, 'how does the kleisin N-tail inhibit condensin'? The authors allude to a model in which the N-tail interacts with Smc2 to close/obstruct the kleisin N-gate, through which the DNA likely enters the condensin ring. Can the authors biochemically recapitulate an interaction between an isolated N-tail (or N-terminal section of XCAP-H) and Smc2? Does Cdk phosphorylation alter this interaction?

Response

This comment is related to Comment #1 of Reviewer#1. See above for our response.

*Minor points. 8. The condensin loop extrusion results would benefit from a supplementary movie or time-series, to illustrate the comparison. Details of how loop rate, duration and sizes were assessed should be added to the methods section. *

Response

In the revised manuscript, we have provided a set of time-lapse images of loop extrusion events catalyzed by holo(WT) and holo(H-dN) in Fig 4E. We have also added the following explanations for how the parameters of loop extrusion reactions were assessed in Materials and Methods:

To determine the loop size, the fluorescence intensity of the looped DNA was divided by that of the entire DNA molecule for each image, and multiplied by the length of the entire DNA molecule (48.5 kb). The loop rate was obtained by averaging the increase in looped DNA size per second. The loop duration was calculated by measuring the time from the start of DNA loop formation until the DNA loop became unidentifiable.

9. Figure EV3A legend, "hHP4" should probably read "hHP2".

Response

The reviewer is right. It should read hHP2. Corrected.

*Reviewer #4 (Significance (Required)):

see above *

Author Response

Reviewer #1 (Public Review):

It has previously been shown that deletion of the GluA3 subunit in mice leads to alterations in auditory behavior in adult mice that are older than a couple of months of age. The GluA3 subunit is expressed at several synapses along the auditory pathway (cochlea and brainstem), and in ko mice changes in brainstem synapses have been observed. These previously documented changes may account for some of the deficits in hearing in adult ko mice.

In the current study, the authors investigate an earlier stage of development (at 5 wks) when the auditory brainstem responses (ABRs) are normal, and they ask how transmission persists at inner hair cell (ihc) ribbon synapses in GluA3 ko mice. They discovered that deletion of GluR3A significantly changed 1) the relative expression of Glu A2 (dramatically downregulated) and A4 subunits at SGN afferents, and 2) caused morphological changes in ihc ribbons (modiolar side) and synaptic vesicle size (pillar).

The changes documented in the 5 wk old GluA3ko mice were not necessarily predicted because in general the mechanisms involved in shuffling GluA receptors at this synapse (or other sensory synapses) are not completely understood; furthermore, much less is known about the role of differentiation of ihc-sgn synapses along a modiolar-pillar axis. With that said, the only shortcoming of the study is a lack of explanation for the observed changes in the synaptic structure; but this is not specific to this study.

Given the quality of the data and the clarity of presentation of results, this is a very valuable study that will aid and motivate researchers to further explore how auditory circuitry develops, and becomes differentiated, at the level of ihc-sgn synapses.

We thank the reviewer for the positive and helpful comments. Ongoing studies are seeking to explain the observed changes in synapse structure.

Reviewer #2 (Public Review):

The goal of the study by Rutherford and colleagues was to characterize functional, structural, and molecular changes at the highly specialized cochlear inner hair cell (IHC) - spiral ganglion neuron (SGN) ribbon synapse in GluA3 AMPA receptor subunit knockout mice (GluA3KO). Previous work by the authors demonstrated that 2-month-old GluA3KO mice experienced impaired auditory processing and changes in synaptic ultrastructure at the SGN - bushy cell synapse, the next synapse in the auditory pathway.

In the present study, the authors investigated whether GluA3 is required for ribbon synapse formation and physiology in 5-week-old mice using a series of functional and light- and electron microscopy imaging approaches. While deletion of GluA3 AMPAR subunit did not affect hearing sensitivity at this age, the authors reported that cochlear ribbon synapses exhibited changes in the molecular composition of AMPARs and pre- and postsynaptic ultrastructural alterations. Specifically, the authors demonstrated that GluA3KO ribbon synapses exhibit i) a global reduction in postsynaptic AMPARs, which is also reflected by smaller AMPAR arrays, ii) a reduction in GluA2 and an increase in GluA4 protein expression at individual postsynaptic sites, and iii) changes in the dimensions and morphology of the presynaptic specialization ("ribbon") and in the size of synaptic vesicles. These reported structural changes are linked to the side of innervation with respect to the IHC modiolar-pillar axis.

The results presented by the authors are conceptually very interesting as the data support the notion that potentially detrimental changes in the molecular composition of a sensory synapse can be compensated to sustain synaptic function to a certain extent during development. The conclusions of the study are mostly well supported by the data, but some experimental details or control experiments are missing or need to be clarified to allow a full assessment.

1) The authors tested which GluA isoforms are expressed in SGNs of GluA3KO mice and reported that only GluA2 and GluA4, and not GluA1, receptor subunits are present in the cochlear. It is, however, a bit difficult to understand why immunolabelling for GluA1 was only performed on brainstem sections (Fig. 1B right) and not in the cochlear to probe for postsynaptic localization at ribbon synapses as it was done for the other isoforms (Fig. 2 and 6) given that GluA3KO IHCs exhibited a larger number of ribbons that lacked GluA2 and 3 (lone or 'orphaned' ribbons; Fig. 6B). It is also not clear why immunolabelling for GluA2 and 4 was performed to probe for expression of these receptor subunits on SGN cell bodies in the cochlear spiral ganglion. Which neurons are expected to synapse onto these somata?

There is precedent for expression of GluA subunits in the SGN cell bodies reflecting expression at the synapse, although it is not clear if any of that immunoreactivity reflects cell surface expression in the intact ganglion or if it represents solely intracellular subunits being trafficked to synapses.

Figure 1b shows that GluA2 is expressed in the somata of WT mice and KO mice. The lower panels show that GluA1 is not expressed in the somata of WT or KO mice. The right panels show that while GluA1 is expressed in the cerebellum of WT and KO mice, is not expressed in the cochlear nucleus of WT or KO mice. We think this demonstrates the lack of compensation by GluA1 in the GluA3 KO.

We have now added GluA4 immunoreactivity in the SGNs to Fig. 1, for completeness. In our experience, GluA subunits expressed at synapses are also found in the cell bodies, and GluA subunits not expressed at synapses are not found in the cell bodies. The current data is consistent with this, although we did not label GluA1 in the organ of Corti.

2) The authors state in the text that GluA3 expression is completely abolished in GluA3KO IHCs, however, there appears to still be a faint punctate immunofluorescence signal visible when an antibody directed against GluA3 was used (Fig. 2C). Providing additional information on the specificity of this (and the other) antibodies used in the study would be helpful.

We agree, and thank the reviewer for pointing this out. There is indeed a small signal presumably due to cross-reactivity of the anti-GluA3 with GluA2 subunits, because the cytoplasmic epitope recognized by the antibody is in a region of high similarity of GluA2 and GluA3 (Dong et al., 1997). In addition, the specification sheet of the Santa Cruz company states that the GluA3 antibody can detect GluA2. This relatively small cross-reactivity is noted now in the text on p. 9. Also, this appearance was a product of the same brightness and contrast issue noted above in the response to the editor’s summary. Upon readjustment, the signal is less apparent, because in the readjustment we used less brightness and less contrast enhancement to avoid the unwanted saturation in some of the panels.

3) The authors reported changes in the volume of the presynaptic ribbon and postsynaptic density surface area in GluA3KO KO animals. The EM data as presented are however not sufficiently convincing.

i) There appears to be a mismatch between the EM data shown in Fig. 3 and 4 and the information in the text with respect to the number of data points in the plots and the reported number of reconstructed synapses. This raises several questions with respect to the analysis. For instance, it is unclear whether certain synapses were reconstructed but excluded from the analysis. If so, what were the exclusion criteria?

We thank the reviewer for pointing out this discrepancy within the text and the figures. The discrepancies are now fixed. We have added more information on how the synapses were reconstructed in the M&M (p.14-15).

ii) The authors compare PSD surface areas in reconstructions from 3D serial sections, but for some of the shown reconstructions (i.e. Fig. 3A' and B' and 4B'), it appears as if PSDs were only incompletely reconstructed.

We included all the ultrathin sections that show afferent dendrites with a visible PSD. We revised all the reconstructions and fixed some misalignments. The appearance of the reconstructed PSD relates to how the Reconstruct software creates the 3-D rendering. We did not use any extra software to smooth the hedges of the 3D reconstructions.

4) The immunolabelling experiments shown in Fig. 2 and 6 are of very high quality and the quantitative analysis of the light microscopy data (Fig. 6-9) is clearly very detailed, but slightly difficult to interpret the way it is presented. Specifically, it is unclear how the number of synapses per IHC (Fig. 6B) and the separation into modiolar and pillar side (Fig. 8) was achieved based on the shown images without the outlines of individual cells being visible.

We agree. Please see the revised Figs. 2, 6, and 8, and explanation in the figure legend of Fig. 8.

5) Adding more detailed information about important parameters (mean, N/n, SD/SEM) and the statistical tests used for the individual comparisons presented in the Figures would help strengthen the confidence in the presented data.

Please see the new spreadsheets accompanying the revised manuscript.

6) In general, the authors report a series of molecular and structural changes in IHCs and reach the conclusion that GluA3 subunits may have a role in "trans-synaptically" determining or organizing the architecture of both the pre- and post-synapse. However, some of the arguments are very speculative and many of the claims are not supported by experimental data presented in the paper. The authors should consider to also compare their findings to studies that investigated ultrastructural changes of AMPAR subunit knockouts in other synapse types, and discuss alternative interpretations (e.g. homeostatic changes).

Thank you for this comment. Considering that reviewer 1 asked for more speculation, we have decided to leave the level of speculation similar to the initial submission. However, we went through the text to make sure our claims were backed by our observations.

Due to space constraints, rather than comparing to additional other synapses, in this context we prefer to compare with auditory brainstem synapses.

The possibility of homeostatic changes we now added on p. 29.

Author Response

Reviewer #1 (Public Review):

With a real interest, I read the manuscript entitled "Sex-specific effects of an IgE polymorphism on immunity susceptibility to infection and reproduction in a wild rodent", written by Wanelik and colleagues. Actually, I am impressed with each and every part of this work. This study is very well designed and answers intriguing scientific questions. The study is multilayer and multidimensional and goes far beyond a genomic association as it deeply addresses, to mention only those most important, ecological, parasitological, immunological, and gene expression aspects. In addition to studying the free-living animal community of voles, it utilizes this opportunity to get some insights into the genetics and biology of the high-affinity IgE receptor not possible to be gained in studies performed in humans or standard laboratory animals. The data are presented in a very elegant way and the article is really nicely written.

We thank the Reviewer for these positive comments, and are very glad to hear they think our work is so comprehensive.

Reviewer #2 (Public Review):

In this manuscript, Wanelik et al. use a wild rodent population to test if a polymorphism in a receptor for immunoglobulin E (IgE) affects immune responses, resistance to infection, and fitness. Finding such effects would imply that polymorphisms in immune genes can be maintained by antagonistic pleiotropy between sexes, which has important implications for our understanding of how genetic variation is maintained. The work presented here extends previous work by the same group where they have shown that expression of GATA3 (a transcription factor inducing Th2 immune responses) affects tolerance to ectoparasites and that polymorphism in Fcer1a affects the expression of GATA3. The present study is based on a fairly large data set and comprehensive analysis of a number of different traits. Indeed, the authors should be commended for investigating all steps in the chain polymorphism→immune response→resistance→fitness. Unfortunately, the presentation of the methodology is a bit confusing. Moreover, most of the key results are only marginally significant.

We thank the Reviewer for their positive feedback, and are very glad to hear they think our work is so comprehensive. As detailed below, we have tried to clarify our methodology and to temper our claims in the revised manuscript.

As regards methodology, I was confused by the differential expression (DE) analyses presented in fig 1A. First, it took a while to understand that these were based on a comparison of unstimulated cells (i.e. baseline expression), not ex vivo stimulated cells; this should be made explicit in conjunction with the presentation of the results. Second, it would be good to clarify (and motivate) in the Results that you compare individuals with at least one copy of the GC haplotype against the rest, i.e. a dominant model.

We apologise for the confusion. We now explicitly state in the Results (lines 313-314) that the DGE analysis was based on unstimulated splenocytes: “Differential gene expression (DGE) analysis performed on unstimulated splenocytes taken from 53 males and 31 females assayed by RNASeq”. We also explicitly state “Unstimulated immune gene expression” in the legend for Figure 1.

Please note that an additive model was used for all analyses run using the hapassoc package (macroparasites and SOD1). A dominant model was used in the DGE analysis and in other analyses where it was not possible to use the hapassoc package (gene expression assayed by Q-PCR, microparasites and reproductive success) which meant that only those individuals for which haplotype could be inferred with certainty could be included (i.e. a smaller dataset). In this case, a dominant model was used. Our use of the dominant model in the DGE analysis is now more explicitly explained on lines 933-935: “Only those individuals for which haplotype could be inferred with certainty could be included (n = 53 males and n = 31 females; none of which were known to have two copies of the GC haplotype hence the choice of a dominant model).” And its use in other non-hapassoc analyses is now explicitly stated on lines 991-992: “as in the DGE analysis, genotype was coded as the presence or absence of the GC haplotype (i.e. a dominant model)”.

The first key result is that polymorphisms in Fcer1a have sex-specific effects on the expression of pro- and anti-inflammatory genes in males and females. However, the GSEA analyses (fig 1A) show that the GC haplotype has positive effects on the expression of both pro- and anti-inflammatory gene sets in both sexes - albeit with a stronger effect of proinflammatory genes in males and anti-inflammatory genes in females - but there is no formal evidence for an effect of genotype by sex. I am not sure how to test for interaction with GSEA (or if it is at all possible), so it would be good to complement the GSEA with other analyses (perhaps based on PCA?) of these data to provide more formal evidence for an effect of genotype by sex.

It is not possible to provide formal evidence for an effect of genotype by sex in the DGE analysis/GSEA. Instead, we have tried to temper our claims about sex-specific effects (please see below for further details).

Some more evidence of a sex-specific effect of Fcer1a genotype is actually provided by analyses of the expression of 18 immune genes in ex vivo stimulated T cells. Here, a sex-specific effect of Fcer1a genotype was found on the expression of one of 18 measured immune genes, the cytokine IL17a. However, Fcer1a is as far as I am aware not expressed by T cells, so the relevance of these results is unclear. Moreover, it is unclear why these 18 genes were analyzed one by one, rather than by some multidimensional approach (e.g. PCA).

The Reviewer is right that Fcer1a is not generally considered to be expressed by T cells. However, the stimulation could have indirect effects. We have clarified this on lines 801-804: “Although Fcer1a is not expressed by T-cells themselves, polymorphism in this gene could be acting indirectly on T-cells through various pathways, including via cytokine signalling, following expression of Fcer1a by other cells”.

The 18 immune genes were specially selected because they represent different immune pathways and are expected to have limited redundancy. This is why individual tests were performed (followed by a correction for multiple testing) rather than using a multidimensional approach like PCA. This is now explicitly explained in the Methods on lines 804-808: “The choice of our panel of genes was informed by…(iii) the aim of limited redundancy, with each gene representing a different immune pathway” and on lines 1031-1032: “We did not use a multidimensional approach (such as principal component analysis) because of limited redundancy in our panel of genes.” and in the Results on line 363-366: “we used an independent dataset for males and females whose spleens were stimulated with two immune agonists and assayed by Q-PCR (for a panel of 18 immune genes with limited redundancy); see Methods for how these genes were selected.”

The second key result is that Fcer1a genotype has sex-specific effects on resistance to parasites, but this is based on a marginally significant effect as regards one of three tested pathogens.

We acknowledge that this is a marginally significant result and have acknowledged this in the text on line 428 of the Results section.

The third key result is that Fcer1a genotype has sex-specific effects on reproductive fitness. However, this is based on a marginally significant effect in males only, and a formal test for sex by genotype could not be performed (and since the direction of the effect was similar in females it is doubtful whether there would be an effect of sex by genotype; see fig 1C).

Thus, while the results presented here are clearly indicative of sex-specific effects of an immune gene polymorphism, I think it is too early to actually claim such effects.

We understand the Reviewer’s concerns about the overall lack of formal evidence for an effect of genotype by sex. As we are not able to provide this for the DGE analysis, GSEA (see above), or for the reproductive success analysis, we have tempered our claims about sex-specific effects (as suggested by the Reviewer). We have done this by removing the term “sex-specific effect” throughout the manuscript, including in the title. We now focus more heavily on the multiple effects we have shown across different phenotypic traits, and use the term “sex-dependent effects” or describe effects as “differing between sexes” sparingly, and only where necessary. These changes have been made throughout the manuscript, but more so in the introduction where the narrative has been substantially reworked to lay out this change in focus.

Reviewer #3 (Public Review):

This is a well-replicated study: the authors sampled over a thousand field voles (Microtus agrestis), over three years at seven different sites, with a combination of cross-sectional and longitudinal sampling. The authors compared individuals carrying the GC haplotype (<10% of the population) of the high-affinity immunoglobulin receptor gene (Fcer1). They recorded parasite infections (Babesia, Bartonella, ticks, fleas, gastrointestinal helminths), expression levels of inflammatory and immune genes using transcriptomes and quantitative PCR, and genotype and pedigree.

We thank the Reviewer for their positive feedback, and are very glad to hear they think our work is well replicated.

A comparison of overall gene expression between GC-carrying and all other voles indicated two sex-dependent differences, the expression in males of Il33, which is associated with antihelminthic responses, and in females of Socs3, which is implicated in regulating immune responses. One substantial issue with the authors' interpretation of these data is to attribute Il33 to the inflammatory response - this taints the rest of their interpretation (e.g., Fig 1A, see below); instead, this is a key cytokine of the antihelminthic Th2 response and its detection suggests there might be a difference in helminth infection between the haplotypes - which is consistent with the role of IgE. Therefore, the authors would need to explore further how the GC haplotype, IgE, and parasite burdens might be driving the expression of IL-33. Specifically, the authors did not control for potential confounding effects of infection, which might be expected to differ based on the rest of their data.

We acknowledge the difficulty in grouping genes under single GO terms, and the need for more nuance when describing these classifications. No gene set is perfect and immune networks are highly complex, so the same gene can be grouped into multiple gene sets. IL33 is an example of this – it appears in the GO term GO:0050729 (positive regulation of inflammatory response) but, as the Reviewer points out, is also commonly associated with the antihelminthic Th2 response. We have edited the text in the Results (on lines 322-324 and lines 350-352) to communicate this nuance, as well as adding references to support each of these associations: “Il33 is commonly associated with anti-helminthic response [25] and Socs3 with regulation of the immune response more broadly [26]….Both Il33 and Socs3 also share an association with the inflammatory response [26,27]. While Il33 positively regulates this response (appearing in the gene set GO:0050729), Socs3 negatively regulates it (GO:0050728).” References added:

1. Liew FY, Pitman NI, McInnes IB. Disease-associated functions of IL-33: The new kid in the IL-1 family. Nat Rev Immunol. Nature Publishing Group; 2010;10: 103–110. doi:10.1038/nri2692
2. Carow B, Rottenberg ME. SOCS3, a major regulator of infection and inflammation. Front Immunol. 2014;5: 1–13. doi:10.3389/fimmu.2014.00058
3. Cayrol C, Girard JP. IL-33: An alarmin cytokine with crucial roles in innate immunity, inflammation and allergy. Curr Opin Immunol. Elsevier Ltd; 2014;31: 31–37. doi:10.1016/j.coi.2014.09.004

We have also run an extra DGE analysis including cestode burden as a covariate (cestodes being the most prominent helminth infection in terms of biomass), to check whether IL33 still emerges as a top-responding gene in males (see Appendix 1-table 4 & 5). We found that it did (in fact the signal was even stronger), indicating that the differences in Il33 expression are not being driven by differences in cestode infection. We now mention this additional analysis in the text: “Given the link between Il33 and the antihelminthic response (and more generally, IgE-mediated responses and the antihelminthic response), we repeated the DGE analysis while controlling for cestode burden, but this had little effect on our results (same top-responding immune genes; see Appendix 1—table 4 & 5), suggesting that these effects were not driven by differences in cestode infection”. This is consistent with our finding that there is no difference in macroparasite burden (including cestode burden) between individuals with and without the GC haplotype (see Appendix 1—table 11) and lines 449-451: “However, we found no effect of the haplotype (interactive or not) on the probability of infection with the other parasites in our population”.

We have also included the following caveat in our discussion on lines 540-542: “Some of the differences in immune phenotype that we observed may also be driven by difference in parasite infection (although we accounted for cestode burden in a follow-up analysis, we cannot rule this out).”

Among a narrow panel of immune genes measured in ex vivo settings, the authors reported elevated expression of Il17a, which is associated with inflammatory, antibacterial responses. Of note, the panel of genes they measured did not contain antihelminth effectors beyond the transcription factor GATA3, and therefore could not confirm the expression of IL-33 observed in the transcriptomes. However, the expression of IL-17a appears consistent with the elevated activity of antioxidant SOD1.

In response to this comment, we now point out more clearly that our panel of genes did not include Il33 or Socs3, but did include other inflammatory genes including Il17a, Ifng, Il1b, Il6 and Tnfa.

Somewhat unexpectedly given the authors' claim that in males the GC haplotype is prone to a more inflammatory immune phenotype, it had no effect on infection in that sex. However, the identity of the genes and pathways matter and the authors do not provide sufficient detail to evaluate their interpretation (GSEA analysis and Figure 1A).

Barcode plots, such as the one we include in Figure 1A, are commonly used representations of GSEA results. In order to aid interpretation for those who are unfamiliar with barcode plots, we have included some more information in the legend of Figure 1.

An intriguing and potentially important finding is that males carrying the GC haplotype appeared to have fewer offspring (little to no effect detected in the females). To confirm whether the effect of the haplotype is direct or mediated by other factors, it would be useful to test how other covariates, like infection, might contribute to this.

To explore this possibility, we have run extra GLMs for both females and males which include two parasite variables: proportion of samples taken from an individual that tested positive for Babesia and proportion of samples taken from an individual that tested positive for Bartonella. We found no difference in the main results – males with the GC haplotype still have fewer offspring, suggesting that infection is not acting as a confounder.

Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.

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Reply to the reviewers

We really appreciate the reviewers’ insightful comments, which help improve the quality of this work. We have responded to the reviewers’ questions/comments point by point in the following text and made the corresponding changes in the revised manuscript. Lastly, we added one more figure (Fig. 7) with lineage tracing experiments demonstrating the conversion of id2a+ liver ductal cells to hepatocytes in extreme hepatocyte loss condition.

Reviewer #1 (Evidence, reproducibility and clarity):

Mi and Andersson describe a method for creating efficient 3' knock-ins in zebrafish using a combination of end-modified dsDNA and Cas9/gRNA RNPs. They tested their method on four genetic loci where they introduced Cre recombinase endogenously, and obtained high F0 mosaicism and germline transmission. The authors included fluorescent proteins with self-cleaving peptides to determine that endogenous expression patterns are observed. By crossing their knock-in Cre lines with lineage tracing reporter lines, the authors temporally traced lineage divergences in zebrafish liver and pancreas.

The authors should clarify the following points before I can recommend publication:

Overall, I suggest that the authors consider paring down their figures. Throughout the paper, multiple figure panels convey the same point but for different genes. Furthermore, many construct configurations are shown that are not used in the subsequent panels. For example, the mNeonGreen only (no Cre) constructs and the EGFP constructs are largely not used in downstream experiments. The authors could pick the important constructs and show the relevant data, and summarize all their other constructs in one supplementary figure. The authors also jump around in different parts of the paper with regards to using iCre or CreERT2 and ubi:Switch or ubi:CSHm. It's not clear to me why they're doing that? It makes the paper hard to follow. For example, why use iCre - it's not temporal if I understand correctly (and I'm not sure what improved Cre is - could they reference a paper and include a small explanation) so CreERT2 seems suitable especially for their temporal lineage tracing experiments. Why not limit the description to CreERT2 in the main text/figures? Also, isn't ubi:Switch and ubi:CSHm pretty similar except the latter is nuclear mCherry due to H2B? Why not only focus on ubi:CSHm experiments? I found the paper to be unnecessarily long and think it would benefit from editing to describe the most important concepts and experiments.

Response: Thank you for your constructive and helpful comments. We do agree that sometimes the schematic constructs seem redundant. This is because the krt4, nkx6.1, and id2a genes have similar gRNA targeting sites (all spanning over the stop codon). However, we prefer to keep these schematic constructs as we have all the statistical results showing the knock-in efficiency in the subsequent figure panels. Such layout can allow readers to make comparisons and better understand the efficacy of this method. However, combined with the comments from the second reviewer, we indeed need to add more detailed information, including the sequence and the length of the short left and right homologous arms in the schematics, to enable the readers to follow this strategy more easily. Meanwhile, we added a new supplementary figure with the sequences of the long left and right homologous arms, as well as the genetic cassettes/point mutations for krt92 knock-in (Figure EV1).

As for the color switch lines we used, we appreciate your comments and replaced Fig. 5E-G with new fluorescent images using zebrafish larvae carrying the ubb:CSHm transgene. For most of the lineage tracing experiments in this study, we used Tg(ubb:CSHm) as the H2BmCherry is more stable, located in the nucleus, and the fluorescence intensity is stronger than in Tg(ubb:Switch). However, for the lineage tracing experiments in the liver injury model, we believe that Tg(ubb:switch) is a better option than Tg(ubb:CSHm). In the absence of a hepatocyte specific far-red reporter line, we can distinguish the hepatocytes derived from the id2a+ origin using the Tg(ubb:Switch) line, as the cells with Cre recombination express mCherry in the cytoplasm; i.e. we can tell the cell types based on the cell morphology in combination with the ductal anti-vasnb staining. This strategy was previously used by Dr. Donghun Shin’s group in their 2014 Gastroenterology paper (Figure 4B, DOI: 10.1053/j.gastro.2013.10.019). Therefore, we still kept the ubb:switch in the Fig. 1F schematic, and we have elaborated on why we chose Tg(ubb:switch) line for the id2a+ cell conversion experiments in Fig. 7 and Figure EV14.

The iCre we used is a codon-improved Cre (iCre). The original cDNA sequence was from pDIRE (Addgene plasmid #26745; provided by Dr. Rolf Zeller, University of Basel) (Osterwalder et al., 2010).

At the beginning of this project, we actually didn’t know whether there were any differences between iCre and CreERT2 in labelling of the cells of interest. Here, using both the iCre and CreERT2 lines, we for the first time, formally show the developmental lineage path of nkx6.1-expressing cells in the zebrafish pancreas. Our data suggested that the early nkx6.1-expressing cells are multipotent pancreatic progenitors giving rise to all three major cell types in the pancreas (endocrine, ductal and acinar cells, shown by nkx6.1 knock-in iCre) and gradually the nkx6.1-expressing cells become restricted in the ductal/endocrine lineages (shown by the nkx6.1 knock-in CreERT2 treated with 4-OHT at different timepoints). In addition, we also aim to use these knock-in lines for multiple studies in which we need to perform many quantitative experiments. As expected, we are unable to reach 100% labeling using the knock-in CreERT2 lines, even if we treated the larvae with very high concentration of 4-OHT over a long period of time. This means that the CreERT2 induced recombination will introduce more variation for quantitative experiments (for instance, the number of regenerated beta-cells from the ductal origin). As we were quite confident with the efficiency of this knock-in strategy, we decided to make both iCre and CreERT2 lines in krt4, nkx6.1, and id2a locus and just observe how they performed. We often use iCre knock-in lines for lineage tracing experiments, because the iCre lines reach near 100% labeling efficiency. Such iCre lines are particularly useful if they only label terminally differentiated cell types. Thus, the near 100% labeling efficiency in iCre lines can be of great help for initial experiments, which later can be confirmed by temporal labeling using CreERT2 lines.

1. Could the authors describe the purpose of the 5'AmC6 modification earlier in the paper? I didn't see much text about it until the discussion. It seems that the speculation is that it provides end protection and prevents degradation (based on in vitro studies in human). This should be inserted into the introduction as a reader might be wondering about this and won't find an answer until near the end. Also, is this the first in vivo use of this modification for knock-ins? If so, that should be highlighted in the text.

Response: This is a helpful comment. In the revised manuscript, we elaborate more on why we chose 5'AmC6 modification in our donors. To our knowledge, this is the first time this 5’ modification is used in vivo, however, bulky 5’modification (5'Biotin - 5x phosphorothioate bonds) has been used in medaka (DOI: https://doi.org/10.7554/eLife.39468.001, 2018 Elife, as we previously referenced). The cell division rate is much faster in zebrafish embryos compared with medaka embryos during early development, so we speculate that such modification might be of more importance in zebrafish to achieve early integration. Another advantage is that the 5'AmC6 modification is commercially available, allowing researchers to prepare the donor dsDNA in a handy fashion. We have now expanded on these details and advantages in the introduction.

1. The authors do not show any sequencing data confirming that their insert was knocked-in as designed with no disruption to the immediate upstream and downstream endogenous sequences. Can they sequence the loci to confirm?

Response: This is indeed a question we frequently get – thank you for making us relay this information more clearly! We have put the raw Sanger sequencing data in a public repository (mentioned in the Data Availability section), and included the sequencing primers in the method paragraph. Now we also refer to this data in the discussion section in conjunction to highlighting that the integrations were correctly placed in the loci. If you think there are better ways to show the sequencing results, please let us know.

1. I found the descriptions of the long and short HA to be confusing when describing the results, especially since the first tested gene krt92 only has long and all subsequent ones are short. The discussion made it more clear that short HA is more efficient and applicable when gRNAs span the stop codon. Perhaps that wasn't possible with krt92, but the authors could prevent the confusion by clearly stating the design requirements of long and short HA and that they wanted to test which is more efficient before starting to describe the data. I also didn't see a description of what the length difference between long and short HA is? How short is short HA?

Response: This is a great question that is well worth discussing. In the revised manuscript, we changed the order in which the parts are described, with nkx6.1 knock-in in front of krt4 knock-in. Here we explain why we would like to do that:

At the beginning of this project, we did not know if the 5’ modified dsDNA could be an effective donor. To test our hypothesis, we chose the krt92 gene as our first target, as this is a keratin protein and expressed in the epithelial cells. We can easily detect the fluorescence in the epithelial cells (most notably in the skin), which allow us to sort the F0 mosaic embryos with high percentage of integration. Notably, from our experience, the most difficult part of the knock-in method is the sorting step (usually performed during 1-3 dpf). This is because the fluorescence signal is highly dependent on the endogenous gene expression level and is usually dimmer with an overall integration efficiency that is lower compared to canonical transgenesis. Therefore, we thought that targeting an epithelial cell marker would be informative and help us to evaluate the validity and reproducibility of the method. If it worked, then we could move on targeting genes expressing in more restricted tissues or cell types. For krt92 gene, the gRNA targets the region upstream of the stop codon. To prevent the cleavage of the donor template, we had to introduce several point mutations and at the same time keep the amino acid sequence intact. However, such mutations can restrict the knock-in and lower the integration efficiency when using shorter arms (due to the sequence mismatch).

After we managed to make the krt92 knock-in, our next question was, what about using a gRNA spanning over the stop codon region? In this way, we don’t need to introduce point mutations on neither the left nor the right homologous arm. Also, for the purpose of our biological study, the nkx6.1 were on top of our gene list for lineage tracing experiments and we luckily identified that there is very good gRNA targeting this locus. After we successfully made the nkx6.1 knock-in, we were thinking that we could simplify the protocol even further, i.e. switching to short homologous arms so that we can prepare the donor by a one-step PCR instead of making complicated constructs. We tested that hypothesis in nkx6.1, krt4, and id2a sites and obtained very promising efficiency. Also, we did some further testing with dsDNA without the 5’ modifications and showed that the 5’ modifications indeed greatly increased integration efficiency. Therefore, although the short homologous arm method is a highlight here, we also point out that it was not planned from the beginning. In the revised manuscripts, we want to convey our method in a logical way and show how we modify the method in a step-by-step fashion.

Moreover, with regards to the comments from the second reviewer, we now added the length of the homologous arms as well as the mutation site on the schematics. We chose short homologous arm because in previous literature it was suggested that short homologous arms (36-48 bp, which we now write out in both the results and the methods) can promote microhomology-mediated end joining (doi: 10.1096/fj.201800077RR). We also noticed that the recent Geneweld method (DOI: 10.7554/eLife.53968) also adheres to a similar length for homology mediated integration. In this study, HAs even shorter than 36 bp also perform well.

1. The authors state that they could not use in situs to confirm krt92 endogenous and knock-in expression overlap, but rather say that they match based on data from an intestine scRNA-seq dataset. Can they elaborate on this? Which clusters/cell types show overlap? Furthermore, is there any krt92:GFP transgenic line that can be used as a reference for expression as well? This point is also applicable for krt4 described in Fig.2

Response: We appreciated this point. In the beginning, we contacted Molecular Instruments to synthesize krt92 HCR3.0 in situ hybridization probes. However, the technical staff there told us that they are unable to make specific probes due to high sequence similarity to other keratin protein families. We can see that the sequence similarity mostly occurs in the middle of krt92 genes, and the HCR3.0 probes rely on a probe set (preferably 20-30 probes with different sequences) to target the mRNA.

The scRNA-seq data that we referenced are from 10X platform, which is based on a 3’enrichment methodology. The reads mapping to krt92 genes are mostly located on the 3’ end. This is good as there is much less similarity to other cytoskeleton genes in the 3’ end of the gene. Unfortunately, there is no krt92 transgenic lines available, so we relied on the single-cell data to correlate expression patterns in this case.

There are two zebrafish intestine single-cell data sets available, with the following links:

(1): https://singlecell.broadinstitute.org/single_cell/study/SCP1675/zebrafish-intestinal-epithelial-cells-wt-and-fxr?genes=krt92#study-visualize

(2): https://singlecell.broadinstitute.org/single_cell/study/SCP1623/zebrafish-intestine-conventional-and-germ-free-conditions?genes=krt92#study-visualize

We can see that krt92 is widely expressed in different types of intestinal epithelial cells (absorptive enterocytes, secretory enteroendocrine/goblet cells and ionocyte).

For the krt4 gene, we now added the HCR3.0 in situ hybridization and immunofluorescence for both krt4 knock-in EGFP-t2a-CreERT2 lines and the Tg(krt4:EGFP-rpl10a) transgenic line (a construct from Anna Huttenlocher, https://www.addgene.org/128839/, which has been widely used to label skin cells). The results are shown in Figure EV9. We show that krt4 has very high expression in the intestinal bulb and hindgut based on the HCR3.0 in situ. The Immunofluorescence of the krt4 knock-in fully recapitulate the krt4 expression pattern in the intestine, while there is almost no fluorescence signal in Tg(krt4:EGFP-Mmu.Rpl10a). We believe this is another advantage of using the knock-in method, over transgenics, for cellular labeling and lineage tracing. Classical transgenics often rely on short promoters of the proximal/enhancer region upstream of ATG with various length (arbitrarily or based on clues from motif analysis/DNA methylation sites). However, different tissues/cell types tend to use different cis-_regulatory elements and the chromatin structure/enhancer-promoter loops might differ dramatically among different cell types. It is hard to predict the exact region of the regulatory sequences that is sufficient for driving the gene expression in a certain cell type. Thus, such reasoning consolidates with that our knock-in lines recapitulate the endogenous _krt4 gene expression. Therefore, we believe that the knock-in based genetic lineage tracing will become the standard in the zebrafish field, as theoretically it avoids both the lack of relevant expression and leakage problems of transgenics.

1. I think Figure 2A needs the dotted lines on the last construct to be fixed (points to p2A)

Response: Thank you for noticing! This was due to a bug in the IBS software, and we changed it manually using Adobe Illustrator in the revised manuscript.

1. There are a few instances where the authors describe performing 4-OHT treatment for long period (e.g. over a 20 hour or 24 hour period). Is fresh 4-OHT added after a certain amount of time or is it a one-time addition? Is such long periods of 4-OHT required or has maximal recombination already occurred within a few hours after addition of 4-OHT?

Response: For 4-OHT treatment, we referred to the method described by Dr. Christian Mosimann (DOI: 10.1371/journal.pone.0152989). We actually tried different conditions (dosage, duration, refresh or not). This is particularly important for the knock-in CreERT lines because the level of CreERT2 is highly dependent upon the endogenous gene expression level. In our case, the nkx6.1 and id2a are transcriptional regulators and relatively lowly expressed compared with structural proteins. We maximized the labeling efficiency by using the highest concentration and longest duration suggested for 4-OHT treatment. The 4-OHT was stored in -20 ℃ and it would become less effective after 30 days of storage. Therefore, we first incubated the 4-OHT in 65 ℃ for 10 min (as recommended by Dr. Christian Mosimann) in order to convert it to a bioactive form. Next, we treated the zebrafish embryos with 4-OHT using a final concentration of 20 μM for 24 hours. We didn’t refresh the 4-OHT since there was no significant difference compared with a one-time addition. Moreover, using higher dosage or longer treatment time can lead to less survival and increased deformity rate. 20 μM 4-OHT treatment for shorter time periods (6 or 12 hours) can cause high labeling variability (some larvae have good labeling while others not). In the end, after several rounds of experiments, we settled on 20 μM 4-OHT treatment for 24 hours as it can reach the highest labeling efficiency, lower variability, and good survival.

1. For Figures 4-6 where confocal images of lineage tracing experiments are shown, there is no indication of how many times the experiments were repeated, how many sections were images, how many animals used, how many cells counted. All of this information should be included in the figure legends and plots should be added showing quantification and statistical analysis (where appropriate).

Response: The reviewer makes a good point and we have now added the number of larvae used and statistical results for the quantitative experiments. The quantification of experiments in Figure 3E-H (originally Figure 4E-H) are shown in Figure EV6D using box/dotplot. We randomly selected 3 secondary islets of different sizes (large, middle, and small) from each juvenile fish (n=5) and pooled the number of mCherry/ins double positive cells and ins positive cells together. The quantification of the lineage-tracing efficiency in the experiments in Figure 6 are shown in Figure EV13.

1. Figure 4 C, C' - I'm not sure what to look for. Is the message that there is no Cherry positive cells that are vasnb negative when labelling is done at 8 somite? But the vasnb positive cells that are also Cherry positive remain? The vasnb staining seems much weaker/harder to see in C C' compared to B, B'. As mentioned above, these data should be quantified and statistical significance indicated.

Response: Thank you for pointing this out; the second reviewer made a similar point. We redid the experiments using zebrafish larvae carrying the ptf1α:EGFP transgene to indicate the acinar cells (Figure 3B-D, Figure EV4G). We also quantified the results and performed statistical testing.

1. I recommend the authors include a short section in the discussion comparing the efficiency of their method to other knock-in strategies used in zebrafish. This is an important claim of the paper yet it is not clear how much better it is (if at all) in terms of frequency of F0 mosaicism and identification of founders relative to other methods. I do appreciate the relative simplicity of the molecular steps of construct design/generation.

Response: This is indeed important. It is also tricky since we are unable to make head-to-head comparisons between different methods as we are targeting different genetic loci and do not have the other methods up and running in our lab. However, the general comparison is based on the statistics shown in the hallmark papers describing these other methods, regardless of which genes were selected for targeting. In the discussion, we added a list of points that are novel/improved with our method versus previous ones, including that: 1) we simplify the knock-in methodology circumventing complicated molecular cloning; 2) we have very high germline transmission rate, which means that one morning of injection is often enough to get a founder; and the expression of fluorescence proteins avoids tedious work in identifying founders, which also saves a lot of space in the fish facility; 3) our lines can be applied for multiple utilities; 4) the method does not disrupt the endogenous gene product. We believe this is critical for the field of developmental biology, regenerative medicine, and disease modeling in zebrafish – and perhaps a similar 3’ knock-in based lineage-tracing method can become commonly used to delineate the cell differentiation and plasticity during homeostatic and diseased conditions in additional organisms.

Reviewer #1 (Significance):

Overall, the study contributes a new knock-in strategy in zebrafish that appears to be more user-friendly and results in high germline transmission. The authors also identify nkx6.1+ ductal cells as progenitors of endocrine cells in the pancreas highlighting the biological applications of their method. I think this study represents an important advancement in zebrafish genetics and will have future impact in lineage tracing during development, regeneration, and disease.

Reviewer #2 (Evidence, reproducibility and clarity):

Summary:

Here, the authors present a strategy where they performed knock-in at the level of the STOP codon, taking care of not perturbing the coding region. They integrate cassettes coding for fluorescence protein and Cre recombinase, which are separated from the endogenous gene and each other by two self-cleavable peptides.

The cassettes are done by PCR with primers with 5' AmC6 modifications and they test short (36 to 46 bp) or long homologous arms (~950bp). For nkx6.1 gene, they observed a dramatic increase of recombination efficiency when injecting the donors with short Homology arms compared to long arms suggesting that short arms could be used. Indeed, short arms used with krt4 and id2a allow them to obtain K.I lines.

The techniques described here look promising. Indeed, even if the proportion of F0 showing adequate reporter expression is low (usually about 2%), the percentages of founders among these mosaic F0 were quite high (between 50% and 100%). And this is the most important aspect as it is usually the most time-consuming aspect of the work.

Major comment:

The authors claim that the knock-in lines can precisely reflect the endogenous gene expression, as visualized by optional fluorescent proteins. But are the authors sure that the integration of the cassettes coding for fluorescence protein and Cre recombinase, which are separated from the endogenous gene and each other by two self-cleavable peptides, will not affect the level of expression of the targeted genes . Indeed, it has been shown that sometimes self-cleavable peptides could affect the expression of the genes of the cassette like for example in this reference ([https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034980]. Therefore it is important that the authors check whether the cassette affect the level of expression of the targeted gene if they want to claim that the knock-in lines precisely reflect the endogenous gene expression.

Response: Thank you for your insightful comments. With regards to the endogenous gene expression, we now use qPCR for further validation. We added the qPCR results to the supplement material (Figure EV15) in the revised manuscript. In brief, we pooled 4 larvae in one tube per biological replicate and have 4 biological replicates for each knock-in line. We didn’t see a significant change in the endogenous expression for any gene. In addition, we have grown up homozygous knock-in lines to adulthood and they are fertile without any overt phenotype.

The highlighted reference is dealing with a cardiomyocyte specific transgenic line, and we assume figure 3-Supplementary figure 1 is what the reviewer is referring to. The altered level of erbb2 expression might be due to the experimental conditions (no treatment or 3 days post treatment). Also, it is possible multiple transgenic insertions occur, as well as gene silencing at some insertion sites. However, such issues would not present, or very limited, with knock-in methods.

Minor comments:

General points:

I believed that the authors should improve the presentation of their data. Indeed, based on what they present, it would be impossible for me to reproduce their technique. Indeed, it is not clear at all how they design the short and long arm, where they are exactly located, which mutations they have done (for fig1), where is located the guide RNA compared to the STOP codon and the HA arms. Graphics that exactly place all these sequences are absolutely required to understand the strategy used and should be placed in figure 1, 2, 3 and 4.

Response: Thank you for these comments. In the revised version, we added the sequence information of the short homologous arms in each of the schematics. As for the krt92 gene, we added the sequence information in the first supplement results (Figure EV1) with the genetic cassettes and point mutation information. We list all the primer information in the methods. Also, we have uploaded our vector templates in the public repository (as listed in the Data availability section). Lastly, we added a key resource table in the supplement file with all the detailed information of reagents for the ease of reproducibility (including all the primers sequences used). We are also willing to share our constructs with the scientific community upon request.

Specific points:

Introduction:

"In zebrafish, the NHEJ-mediated methods have been intensively investigated in 5'knock-in upstream of ATG using donor plasmid containing in vivo linearization site flanking the insertion sequences (11,12,17-20). The 3' knock-in method has also been examined using circular plasmid as the donor with either long or short homologous arms (HAs) flanked by in vivo linearization sites (14, 21-23). Recently, intron-based and exon-based knock-in approaches have remarkably expanded the knock-in toolbox by targeting genetic loci beyond the 5' or 3' end (8-10,13,24-26)."<br /> This part should be explained better in order that the readers could really understand the differences between these old studies and this new one. And really insist on what is the novelty of their technique.

Response: Good points. In the revised version, we elaborated more on the previous discoveries, the major challenges, the knowledge gap in zebrafish knock-in methodology, and what is novel and improved with our new technique. Please, see clarifications and the expanded text in both the introduction and discussion.

Results:

Page 4: To my opinion, the first paragraph should be removed and the technique directly explained based on krt92 strategy as this paragraph does not allow to understand the technique. As indicated above, figure 1 should indicate more clearly the location of the long arms and which mutations they have done and where is located the guide RNA.

Figure 1G: The expression in the skin is far from obvious and the image should be improved (for example with some inset).

Response: Thank you for the comments. We added a new supplementary figure (Figure EV1) and show the sequences of left and right homologous arms, the genetic cassettes, as well as the point mutations with different background color highlight. We added the insets to show the magnified regions of interest. Also, we added the images from the fluorescent microscope used for sorting, to show the EGFP signals in live zebrafish embryos (Figure EV2D and Figure EV8D).

Figure 3E: The authors say that "cells expressing nkx6.1 (displayed by the green fluorescence) were located on the ventral side of the spinal cord whereas H2BmCherry positive cells, which include all the progenies of nkx6.1+ cells after the iCre recombination, resided in both the ventral and dorsal parts of spinal cord". This differential expression in the spinal cord is not obvious and a more closer view should be provided.

Response: Thank you for the comment. First, we changed the order and now describe all nkx6.1 content in Figure 2 and 3 and the krt4 content in Figure 4. We added insets to show the magnified regions and better display the expression pattern of the two fluorescence proteins in Figure 2E-G. One can now clearly see from the magnified insets that the green signals driven by the endogenous nkx6.1 gene are present in the ventral part of the spinal cord, while the red signals are present in both the ventral and the dorsal side of the spinal cord.

Fig S4H: The authors say that" using lineage tracing, we could trace back all three major cell types in the pancreas (acinar, ductal and endocrine cells) to nkx6.1 lineage (Figure 3H-H',Supplementary Figure S4G, H)". While this is obvious for endocrine, the colocalisation with ela3l:GFP is not obvious and the figure should be improved.

Response: This is a very good point, and the first reviewer gave similar suggestions. In the revised version (shown in Figure EV4H and I), we added the insets to show the magnified regions to better display the expression pattern of two fluorescence proteins. The ela3l reporter line is using a short promoter to drive the expression of H2B-EGFP (doi: 10.1242/dmm.026633). However, this short promoter cannot reach 100% labeling of acinar cells, so we also use the ptf1α:EGFP transgene for further validation (new Figure EV4G). Both transgenic reporter lines showed many EGFP and mCherry double-positive cells, indicating that these acinar cells are derived from a nkx6.1-expressing origin. Here we did not use the anti-GFP antibody, as our color switch lines contains CFP and anti-GFP antibody can also recognize CFP. However, the GFP signal is strong enough to show the expression. We hope the additional experiments and insets clarifies this point.

Page 8: the authors say that "The immunostaining at 6 dpf showed that both intrapancreatic ductal cells and a portion of acinar cells can be lineage traced when the 4-OHT treatment started at the 6 somite stage (Figure 4B and B'). The identification of the acinar cells has been done based on the absence of the ductal marker vasnb. To trace efficiently the acinar cells, this should be done with an acinar marker.

Response: Another good point also mentioned by reviewer one. We redid the analyses using zebrafish larvae containing the ptf1α:EGFP transgene to indicate the acinar cells and the co-expression pattern with the lineage-tracing (the data is shown in new Figure 3B-D).

Reviewer #2 (Significance):

I do not have enough expertise in the KI field to evaluate whether this strategy is really novel and as mentioned above, the authors should better explain what is really the novelty of their strategy.

Response: In our answers to the comments of the first reviewer, we elaborated more on the points that are novel/improved with our method vs previous methods, as reiterated here:

“…including that: 1) we simplify the knock-in methodology circumventing complicated molecular cloning; 2) we have very high germline transmission rate, which means that one morning of injection is often enough to get a founder; and the expression of fluorescence proteins avoids tedious work in identifying founders, which also saves a lot of space in the fish facility; 3) our lines can be applied for multiple utilities; 4) the method does not disrupt the endogenous gene product.”

Moreover, the first reviewer asked about the difference between the krt4 knock-in and krt4 transgenics, and based on the in situ data, we showed that our krt4 knock-in can fully recapitulate the endogenous gene expression, while the krt4 transgenics can hardly label the intestinal bulb and hindgut. This might be due to that different tissues/cell types may depend on different _cis-_regulatory elements to drive the gene expression. The chromatin structure and the enhancer/promoter loop might also differ dramatically among different tissues. Therefore, the transgenics might be useful for one type of cells, while they might be not useful at all for other cell types. In the future, we believe that, similar to the mouse field, the 3’ knock-in based lineage tracing methods might become the standard method in the zebrafish field, to delineate cellular differentiation and plasticity during homeostatic and diseased conditions.

He urged enslaved people to fight back against their oppressors and to put an end to slavery.

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We thank the Reviewers for their comments. Below we have the Reviewers’ comments and our responses.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

In this work, the authors claim that their machine learning approach can be combined with a biophysical model to predictably engineer sensors. The concept is interesting, but there are many issues that must be addressed before considering its publication.

1. It is surprising that their citations are too biased. They keep citing nonrelevant papers from several groups while omitting many key papers regarding genetic sensors and circuits in the field. Some can be justified (e.g., Voigt lab's reports), but others (e.g., reports on dynamic controllers too often) would not be relevant.

There are hundreds (possibly thousands) of papers that have been published on genetic sensors. Most of those papers report only qualitative results (e.g., genetic sensor implemented in a new host organism or demonstrated to sense a ligand of interest).

The purpose of this manuscript is to demonstrate methods for quantitative engineering of genetic sensors. Specifically, the manuscript is focused on quantitative tuning of the genetic sensor dose-response curve. So, in deciding which previous papers to cite, we chose several review articles (to cover the many, many qualitative results), any previous papers we could find that reported strategies for tuning the dose-response curve of genetic sensors (the Voigt lab’s reports and others), and any papers we could find that discussed reasons/applications for quantitative tuning of a genetic sensor dose-response curve (e.g., dynamic controllers).

We added a new paragraph to the beginning of the Results section to explain this focus on quantitative tuning (and to clearly state which statistic we use for assessing accuracy – see response to next comment; lines 72-83 in the revised manuscript).

We would also like to add more relevant citations as suggested by the reviewer, but that is difficult based on the reviewer’s comment, which just indicates that we have omitted many “key” papers. For the central focus of this manuscript, we think the “key” papers are those that describe methods to tune the dose-response curve of genetic sensors, and we have done our best to cite all of those that we could find. So, we ask the reviewer to please suggest some specific papers that they consider to be “key” that we should cite, or at least some more specific definition of what they think constitutes a “key” paper that should be cited.

It is very unclear which statistical analysis has been done for their work.

The main statistical metric used in the manuscript is the fold-accuracy. The fold-accuracy was defined in the previous version of the manuscript, but we agree that it could have been stated more clearly. So, we have moved the definition of fold-accuracy to the (new) first paragraph of the Results section, and identified it as “…the primary statistic we will use to assess different methods.” (line 77 of the revised manuscript)

There are many practical sensors for real applications, but their work focuses on IPTG-responsive sensors or circuits. I was wondering whether this work would have significant impacts on the field or the advancement of knowledge.

Similarly, it is questionable that their approach is generalizable.

Currently, there is only one published dataset that can be used for the methods described in this manuscript, for IPTG-responsive LacI variants.

However, previous work (cited in our manuscript) has shown that directed evolution can be used to qualitatively “improve” a wide range of genetic sensors beyond LacI. Furthermore, some of those previous studies used a single round of mutagenesis and libraries with diversity similar to the size of the LacI dataset (104 to 105 variants). Based on that, we think it is highly likely that our in silico selection approach will generalize to other sensor proteins.

With regard to the ML methods used in our manuscript, we showed in the initial publication describing the LANTERN method that the approach is generalizable to different types of proteins and protein functions (LacI sensor protein, GFP fluorescence protein, SARS Cov-2 spike-binding protein). So, we don’t see any reason to question the generalizability of that approach to other sensor proteins.

We have edited the Discussion section of the manuscript to include these points regarding the generalizability of our approach (lines 340-350 in the revised manuscript).

Due to the biased literature review, it is unclear to me whether this work is novel.

The majority of relevant literature on genetic sensor engineering is qualitative in nature and is not particularly comparable to the work here. We have tried to emphasize this in the introduction and discussion. We have searched the relevant literature extensively, and we have only found a small number of papers that describe quantitative methods to tune the dose-response of genetic sensors. Furthermore, there are only a few that contain any kind of quantitative assessment of that tuning. We have cited all of those papers and included specific discussions and comparisons between them and our results.

If the reviewer knows of any specific papers that we missed we would be happy to include them in our literature review.

I am unsure whether their correlation is sufficiently high.

This comment is too vague to address.

Again, we ask the reviewer for more specific information: What “correlation” are you referring to? And what is “sufficiently high”?

We have provided statistics on the accuracy of our methods, as discussed above.

Is EC50 the only important parameter? Or is it really relevant for real applications where the expression levels would change due to RBS changes, context effects, metabolic burdens, circuit topologies, etc.?

EC50 is not the only important parameter. That is why we also demonstrate the ability to quantitatively tune other aspects of the dose-response (e.g., G∞).

In any real application of genetic sensors, the EC50 will have to be engineered to have a quantitatively specified value (within some tolerance). So, yes, it really is relevant.

There is an important question about the effect of context however, and perhaps that is what the reviewer is really asking: If we engineer a genetic sensor that has a given EC50 in the context used for the large-scale measurement, will we be able to use that genetic sensor in a different context where, because of the change in context, its EC50 may be different?

This is one of the outstanding challenges in the field, to be able to predict the effect of a change in context. But for genetic sensors, there are several previous publications that demonstrate promising routes to quantitatively predict the effect of context on genetic sensor function.

So, we have added a paragraph to the Discussion section addressing this point and citing the relevant previous publications (lines 315-339 in the revised manuscript).

There are many reports on mutations or part-variants and their impacts on circuit behaviors. Those papers have not been cited. This is another omission.

As discussed in response to Comment 1, above, there are many hundreds of such papers. It would not be practical or appropriate for us to cite all of them. However, there are only a few that contain any kind of quantitative assessment of the predictability of mutational effects or of efforts to use mutations to engineer sensors to meet a quantitative specification. We have done our best to cite and discuss all of those. Again, if the reviewer knows of any specific additional papers that we should cite, please tell us.

CROSS-CONSULTATION COMMENTS

In general, I agree with the other reviewer. Its significance would be too incremental.

Reviewer #1 (Significance (Required)):

See above.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

This paper proposes two approaches for forward-design of genetically encoded biosensors. Both methods rely on a large scale dataset published earlier by the authors in Mol Syst Biol, containing ~65k lacI sequences and their measured dose response curves. One approach, termed 'in silico selection', is proposed as a way to find variants of interest according to phenotypic traits such as the dynamic range and IC50 of the biosensor dose-response curve. The second approach uses machine learning to regress the dynamic range, IC50 and others from the lacI sequences themselves - the ML regressor can then be used to predict phenotypes of new variants not present in the original dataset. The ML algorithm has been published by the same authors in a recent PNAS paper.

The manuscript has serious flaws and seems too preliminary/incremental:

1) The 'in silico selection' method corresponds to a simple lookup table. This is a perfectly acceptable method for sequence design, but the attempt to portray this as a new method or 'multiobjective optimization' is highly misleading. Also, the analogy between 'in silico selection' and darwinian evolution or directed evolution are inappropriate, because both latter approaches rely on iterative selection through fitness optimization and randomization of variants. The 'in silico selection' approach in contrast is one-shot and does not use randomization.

We agree with some of the reviewer’s points here. In making the analogy to directed evolution, we wanted to give the reader a connection to something familiar, but the reviewer is correct that the analogy is imperfect. The “lookup table” description is much better, and probably a familiar idea to most readers. So, we edited the relevant paragraph to describe in vitro selection as the use of the large-scale dataset as a lookup table instead of making the analogy to directed evolution. We thank the reviewer for this suggestion.

However, we disagree with the reviewer with regard to “multi-objective optimization.” We clearly demonstrate in Figures 3 and 4 that we can simultaneously tune multiple aspects the dose-response curve to meet quantitative specifications. If the reviewer is aware of any previous publications that they think provide a better demonstration of multi-objective engineering of biological function, please let us know; we would like to cite those papers appropriately.

Also, the reviewer is incorrect in stating that our in silico selection approach does not use randomization. The randomization occurs as part of the large-scale measurement. This is clearly stated in the second paragraph of the Results section.

2) The ML approach is a minor extension to what they already published in PNAS 2022. One could imagine an extra figure in that paper would be able to contain all ML results in this new manuscript. A couple of comments about the actual method: a) it seems unlikely to work on sequences of lengths relevant to applications, because it relies on gaussian processes that are known to scale poorly in high dimensions. b) The notion of 'interpretable ML' is misleading and quite different to what people in interpretable AI understand. Moreover, the connection between the three latent variables, which provide the 'interpretability', and biophysical models seems to come from their earlier PNAS work and this specific dataset, but there is no indication that such connection exists in other cases. Although this is somewhat acknowledged in L192-195, the text tends to portray the connection with biophysical models as something generalizable.

The ML results presented in this manuscript are specifically aimed to quantitatively assess the accuracy of the ML predictions for the parameters of a genetic sensor dose-response curve. So, we think those results belong in the current manuscript.

The reviewer’s comment on Gaussian processes and dimensionality is clearly contradicted by the results presented in this manuscript and in our previous publication describing the ML method: The ML method works quite well for “sequences of lengths relevant to applications,” including LacI (360 amino acids), the SARS-Cov2 receptor binding domain (200 amino acids), and GFP (250 amino acids). The reason for this is that the Gaussian process is only applied on the low-dimensional latent space learned by the ML method.

The reviewer’s comment on “interpretable ML” is not relevant to this manuscript but is instead a criticism aimed at our previous publication on the ML method.

The generalizability of this approach is an open question. The same could be said for most other publications describing new methods, since most of those publications include demonstrations with only a small number of specific systems. After re-reading the relevant portions of the manuscript, we disagree with the reviewer’s suggestion that we have exaggerated the potential generalizability of the approach. For example, in the last sentence of the Results paragraph, we state, “Although imperfect, this initial test of linking an interpretable, data-driven ML model to a biophysical model to engineer genetic sensors shows promise…” And, in the Discussion section, “The use of interpretable ML modeling in conjunction with a biophysical model also has the potential to become a useful engineering approach… But more rigorous methods would be needed…”

Other comments:

3) There are quite a few reduntant figures, eg Figure 1 contains too many heatmaps of the same variables. Fig 2B and C are redundant as the contain the same information. Altogether figures feel bloated and could have been compressed much more.

We disagree. The sub-panels of Figure 1 show different 2-D projections of the multi-dimensional data that are relevant to specific aspects of the results in Figs. 2-4.

Admittedly, Fig 2C shows the residuals from Fig 2B, which is in some sense the “same information.” But it is quite common, in papers focused on quantitative results, to have one sub-panel showing a comparison between predicted and actual and a second sub-panel showing the residuals.

4) Fig 2A and 3A have problems: the blue & orange lines (Fig 2A) and blue & green lines (Fig 3A) have a kink just before the second dot from the left. Such kinks cannot have been produced by a Hill function. This kind of errors cast doubt on the overall legitimacy and reproducibility of the results.

The kinks in the curves are a consequence of the use of the “symmetrical log” scale on the x-axis, which allows the zero-IPTG and non-zero-IPTG data to be shown on the same plot while showing the non-zero-IPTG data on a logarithmic scale. That symmetrical log axis uses a log scale for large x values, and a linear scale for smaller x values. The kink appears at the transition between the log and linear scales. We have re-plotted all of the figures showing dose-response curves to move the log-linear transition to overlap with the axis break.

CROSS-CONSULTATION COMMENTS

I agree with the other reviewer's comments, particularly on the lack of statistical analyses.

See our response to Reviewers #1, comment 2, above.

Reviewer #2 (Significance (Required)):

The work addresses a timely subject but is too incremental.

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Manuscript number: RC-2022-01490

Corresponding author(s): Cariboni, Anna; Howard, Sasha R

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Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The current manuscript in question is well written and of general interest to the reproductive neuroendocrinology field. Overall it is a well written and substantiated.

Reply: We thank the reviewer for his/her positive and supportive comments on our manuscript.

The primary problem with the paper is the data derived from the microarray. While the experimental design included replicates (n = 3), although weak, the actual microarray data was based on a single data point. A major weakness. This experiment should be repeated using more up-to-date approaches such as RNA-seq or left out of the manuscript, because this data set is compromised due to the data collection procedure.

Reply: We thank the Reviewer for raising these points, which we wish to clarify. We respectfully disagree that the microarray data generated in this study is not valuable. The transcriptomic analysis of immortalized cells was performed on 3 biological replicates (specifically, RNA was extracted from n=3 samples, obtained from each cell line at 3 different passages) and run as 3 independent samples (for a total of 6, 3 for GN11 cells and 3 for GT1-7 cells). For the primary embryonic GFP-GnRH neurons, given the difficulty of isolating with FACS a sufficient number of GFP+ cells from each embryo due their very small number (around 1000 GnRH neurons/head), we had to pool sorted cells from 2-3 embryos for each time-point. Thus, although the primary cell microarrays were run on one sample for each time point, the RNA was not derived from one embryo only, but from at least 2/3 embryos.

Nevertheless, to overcome the issue of low number of replicates for the primary embryonic cells, we revised our manuscript by re-running our analyses, using as the starting dataset the analyses obtained from immortalized cells, which were based on a ‘true’ n=3 of biological replicates. In this context, we filtered DEGs from this microarray using logFC>2 and adj. p-value1) found in primary GFP-GnRH neurons. We believe that this revised analysis is statistically more powerful, as the core bioinformatic analyses were performed on triplicate samples, with a second filtering step to take advantage of biologically relevant data obtained from n=1 primary GFP-GnRH neurons to confirm in vivo the expression of selected genes. Whilst RNAseq offers wider coverage of the genome and has advantages over microarray, we do not believe that this renders unimportant the data generated from these unique experiments and the novel genomic discoveries it facilitated.

In line with this, our work may be considered as a proof-of-principle that transcriptomic profiles from rodent GnRH neurons can be exploited at different levels, including the possibility to identify novel GD candidate genes. Overall, our work also highlights the existence of similarities between two immortalized GnRH neuron cell lines with primary GnRH neurons, which was so far demonstrated by several functional studies, but not at molecular level.

The manuscript has been now edited as per the above amendments (see first and second paragraph of Results section, lines 86-135).

__CROSS-CONSULTATION COMMENTS __Notwithstanding the importance of neuroligin 3 during glutaminergic synaptogenesis, I agree with the reviewers on both points. Further screenings of the patient's family members should be done and the microarray data should be removed or potentially moved to a supplementary status.

Reply: we thank the reviewer for their comments and, accordingly with their suggestion, we revised the filtering strategy starting from immortalized cells microarray and therefore moved a substantial part of the microarray data from primary GFP+ neurons as supplementary data. We also unsuccessfully tried to collect information of the brother from case 2 and investigated datasets from both the DECIPHER and 100,000 genome projects, but have been limited to two cases for which we have familial consent to publish.

Reviewer #1 (Significance (Required)): The paper is of significance based on the neuroligin 3 data, which is indicative of abnormal synaptogenesis. However, these defects seem to only have a limited effect on the functionality of GnRH neuron system and do not seem to cause elimination of GnRH neurons themselves. Nevertheless these data do open end a new direction that may help explain some dysfunctions in reproductive health.

Reply: we thank the reviewer for their comments and agree that our findings have the potential to facilitate new avenues for the investigation of reproductive disorders.

Reviewer #2 (Evidence, reproducibility and clarity (Required)): Oleari et al performed comparative transcriptome analysis on the different developmental stages of GnRH neurons, as well as two immortalized GnRH neuronal cells GT1-7 and GN11 which represent mature and immature GnRH neurons. As a results, they identified a panel of differentially expressed genes (DEG). They further used top DEGs as candidate disease-related genes for GnRH-deficiency (GD), a disorder characterized with absent of delayed puberty and infertility. To this end, they found two loss-of-function mutations in NLGN3 in patients with GD combined with autism. This study provide a resource for the identification of novel GD-associated genes, and suggest an intrinsic connection between GD and other neurodevelopmental diseases, such as autism. I only have some minor concerns.

1. According to the pedigree, both probands (case 1 and 2) inherited their NLGN3 mutations from their unaffected mother, consistent with an X-linked recessive inheritance. However, only "parent" was used in the manuscript, therefore, it is not clear if this "parent" is the probands' mother or father. __Reply: __Thank you for this comment. We were limited to the use of non-gendered terminology due to medRxiv policies. We have now amended the text and changed ‘parent’ to ‘mother’, lines 161, 173, 179, 185 and 730. We also integrated this sentence highlighting the X-linked pattern of inheritance: “Sanger sequencing of the probands’ mothers confirmed them to be the heterozygous carrier in each family, consistent with an X-linked recessive inheritance pattern.”, lines 185-186.

It is suggested to integrate Figure 2 as a panel in Figure 1.

__Reply: __We thank the reviewer for this suggestion. Due to our revision of first two Results paragraphs, we have now edited the Figures and the filtering flowchart has been added in Figure 2.

What is the meaning of Peak LH and Peak FSH, and how are they measured in Table 2?

Reply: This refers to peak value obtained after standard protocol GnRH stimulation testing with 100mcg GnRH (Gonadorelin) as an IV bolus and measurement of serum LH and FSH at 0, 20 and 60 minutes intervals. (e.g. Harrington et al., 2012, doi:10.1210/jc.2012-1598). This clarification has been added to the text in Table 2 legend (lines 681-683).

A genotyping for the elder brother of Case 2 will be a strong evidence to support NLGN3 as a GD-associated gene.

__Reply: __We thank the reviewer for this important point. In view of this issue, we have strived to collect DNA from this individual. Unfortunately, despite trying repeatedly to contact the family of proband 2, it has not been practically possible to collect these extra data from this family.

We also identified a third case via a public database with central hypogonadism who carried a stop-gain variant in NLGN3, but unfortunately the family did not release their consent for publishing this case.

The authors claimed neither probands carried deleterious variants in known GD genes. It is suggested to indicate the exclusion criteria (which genes? How do they define a variant is deleterious?)

Reply: We thank this reviewer for raising this important point of clarification. Inclusion criteria for variants in known GD genes (updated gene list available in Supplemental Table 3) were as per Saengkaew et al., 2021 (doi: 10.1530/EJE-21-0387): “Only variants that met the ACMG criteria for pathogenicity, likely pathogenicity, or variants of uncertain significance (VUS) were retained in the analysis”. We have added this sentence in the manuscript, lines 150-151.

Please also include a sequence chromatogram for proband 2.

Reply: We thank the reviewer for their comment. We added the chromatograms for proband 2 and his heterozygous mother in revised Figure 3.

CROSS-CONSULTATION COMMENTS I agree with Reviewer 3, the genetics is not very strong, as NLGN3 mutations were only found in one GD case from their cohort and one pre-pubertal case from the literature. It will be nice to analyze the genotype and phenotype of Case 2's older brother. Further, it is important to screen NLGN3 rare sequencing variants in larger GD cohorts.

Reply: We thank the reviewer for their comment, but respectfully disagree with this assertion. The second case is not from the literature, but is a second case found thanks to GeneMatcher, an international tool that allows researchers to collaborate on novel gene discovery. We have also explored other cohorts that were available to us, including the DECIPHER and 100,000 genome project, but have been limited to two cases for which we have familial consent to publish. We anticipate that further international patient cohorts will be screened following the publication of this manuscript (added in Discussion section, lines 306-308). As described above, despite trying repeatedly to contact the family of proband 2, it has not been practically possible to collect these extra data from this family.

Reviewer #2 (Significance (Required)): This study provides a resource for the identification of novel GD-associated genes, and suggest an intrinsic connection between GD and other neurodevelopmental diseases, such as autism. It may welcome by researchers and clinicians in the filed of neurodevelopment.

Reply: We thank the reviewer for their positive and supportive comments.

__Reviewer #3 (Evidence, reproducibility and clarity (Required)):

__Summary: Oleari et al used murine GnRH1, and immortalized GnRH cell lines (GT1-7, Gn11) to define genes of interest in GnRH development and used this list to filter exome sequencing data from patients with some evidence for GnRH Deficiency.

Title: I am concerned that the title of the paper overstates the results and conclusions.

Intro: use of "candidate causative genes" overstates the evidence presented.

__Reply: __We thank the reviewer for their comment and have revised the title to reflect the findings of the study. We have also edited the sentence in the abstract reporting "candidate causative genes" as follows: “Here, we combined bioinformatic analyses of primary embryonic and immortalized GnRH neuron transcriptomes with exome sequencing from GD patients to identify candidate genes implicated in GD pathogenesis”, lines 40-43.

Results: The transcriptomic profile of the developing human GnRH neuron has been published via in vitro differentiation protocols twice (Lund et al 2020, and Keen et al 2021). Gene set data is publicly available. This should be explicitly compared in results not relegated to discussion -- two or three examples it not enough to say mouse can be used instead of human.

__Reply: __We thank the reviewer for this comment. We apologize if our sentence in the Discussion was misleading, as we did not intend to make a conclusion on the similarities of the two datasets/cell types, neither to suggest the use of rodent instead of human.

Although we are aware that differences among species might exist, mouse/rodent models including immortalized cells have been instrumental to understand the molecular mechanisms of GnRH neuron development and to predict candidate genes. Indeed, our aim was to demonstrate that transcriptomic profiles of rodent GnRH neurons could be integrated with exome sequencing data from human patients to reveal novel candidate genes.

Therefore, the aim of our study was different to that of the Lund and Keen publications. Further, caution should be exercised in any deeper comparative analyses with our transcriptomes, for following reasons: first, the GnRH neurons generated from human iPSC and cultured for 20 and 27 days cannot be objectively defined for their ‘age’ in order to be then compared to immortalized or primary embryonic GnRH neurons; second, in these datasets a different and more extensive transcriptomic technique has been used (RNAseq vs microarrays).

There was no intention to relegate to the discussion the possible similarities with other transcriptomic datasets, but we felt that these comparative analyses were beyond the scope of our work.

However, following the Reviewer’s suggestion, we have tried to make comparative analyses with the publicly available datasets from Lund et al 2020 and Keen et al 2021, and with a paper just published (Wang et al 2022), as follows.

In Lund et al. paper, GnRH-like neurons were obtained from human iPSCs by dual SMAD inhibition and FGF8 treatment. We selected data obtained from cells treated with FGF8 and cultured for 20 days and 27 days for comparison with our early and late genes, respectively.

Because the authors of this paper did not publish the full list of differentially expressed genes (DEGs) from this specific comparison (20 vs 27days) and we were not able to retrieve it upon request, we used the normalized counts of these samples (available at ArrayExpress repository) to compare the two experimental groups with DESeq (Bioconductor release 3.15). To increase stringency of our analysis, we considered as differentially expressed those genes which displayed both an adjusted p-value of less than 0.05 and an absolute fold change of >2. The number of DEGs obtained was different and greater (5981) than from the published data, and this large number of genes may, by chance alone, contain a large fraction of any gene dataset (including the genes that we found with our analysis). For this reason, this particular comparison in this dataset cannot be informative or useful.

Next, we considered the dataset from Keen et al. In this paper, the authors have tested different differentiation protocols to obtain GnRH-like neurons from human wild-type or mCherry embryonic stem cells (hESC). They transcriptomically profiled hESC-mCherry-derived GnRH neurons at 8,15 and 25 days of culture.

Again, although we cannot precisely define the matching embryonic stage of cells cultured for 8, 15 or 25 days, we compared the lists of DEGs from immortalized GnRH neurons (GN11vsGT1-7) with the transcriptomic profiles of mCh-hESC at day 15 vs day 8 and mCh-hESC at day 25 vs day 15, respectively. We considered as differentially expressed the genes that displayed both an adjusted p-value of less than 0.05 and logFC>2. We found that the majority of the genes that were differentially expressed in one dataset were not in the other. However, the few genes that were differentially expressed in both datasets demonstrated a good correlation, i.e. the same expression trend. Although this latter approach was more fruitful, by suggesting a partial similarity between primary GFP-GnRH neurons and hESCs-derived GnRH neurons at day 25 vs day 15 time-point, we do not feel that we could draw significant and reliable conclusions.

Further, if we compare these two datasets obtained by RNAseq from hiPSC and hESC, even by taking into account the large amount of DEGs found in our re-analysis of Lund et al., 2021 raw data, a relatively small number of common DEGs were found. These data also suggest that there is transcriptomic heterogeneity even among human-derived GnRH neurons.

In addition to these two datasets, while our manuscript was under revision, a new paper was published, in which the authors dissected iPSC-derived GnRH neuron transcriptome with RNA-seq at single cell level (Wang et al., 2022, doi:10.1093/stmcls/sxac069). Again, although the same concerns may apply in comparing this dataset with ours and raw data of DEGs were not publicly available in this case, we compared the expression trends of our 29 candidates with gene expression trajectories identified in this work. As a result, 24/29 candidate genes, including NLGN3, were found to have an expression trend consistent with our dataset. The few remaining genes exhibited an opposite trend (2/29) or were not found in available data from this work (3/29). As this is a purely qualitative analysis, we do not feel it would be appropriate to include it in the Results section, but have included commentary on these comparative dataset analyses in the Discussion section (lines 247-257). A future study could be designed to mine the raw data from all the available transcriptomic profiles of developing GnRH neurons, but this is beyond the scope of our current manuscript.

The authors need to comment on other GnRH1 expression in the brain of developing rodent and if they think the GnRH1 sorted neurons are just "GnRH Neurons" associated with reproduction (Parhar et al 2005) due to microdissection.

__Reply: __We thanks the reviewer for raising this point of clarification. We have carefully selected by microdissection nasal areas from E14, nasal and basal forebrain areas from E17 and basal forebrain from E20 rat embryos (see revised Methods, lines 325-327). We are therefore confident that what we have obtained is RNA from ‘reproductive’ GnRH neurons only.

Questions about Cases/Missing Phenotypic Information: 1) Case 1: the patient underwent increased testicular volume on testosterone therapy -- testosterone therapy does not increase testicular volume. Has this patient undergone or been assessed for reversal of his hypogonadism?

__Reply: __We thank the reviewer for their comment. The patient had minimal testicular development on testosterone (from 10ml to 12ml) but did not increase testes volume beyond 12mls, consistent with a partial HH phenotype. He has had two trial periods of 3-4 months off testosterone treatment and during these periods had both low serum testosterone concentrations and symptoms of hypogonadism (tiredness, low energy and reduced muscle strength).

2) Case 2: Is too young to be classified as having a pubertal defect. Microphallus is mentioned but what size, was this diagnosed at birth and treated? I think the case for GD is overstated in the results and discussion (especially with the discussion of small testes).

Reply: We thank the reviewer for requesting these clarifications. The patient has not received any treatment for his microphallus (2.5 cm length in mid-childhood). We agree that this case is too young to be classified as having a pubertal defect, but the presence of microphallus and small testes volume in infancy and early childhood, in association with low gonadotrophins and absent erections, are well recognized as red flag signs for hypogonadotropic hypogonadism (Swee & Quinton, 2019, doi:10.3389/fendo.2019.00097). We added this information to the Results section, lines 175-177.

Genetic Information: Since this was a candidate gene search -- what other candidate genes were uncovered in these probands?

Reply: The revised list of 29 candidate genes were screened in the two probands from our study using the whole exome sequencing datasets for these individuals, and only the variants of interest in NLGN3 described in the manuscript were found.

By searching for mutations of the revised list of candidate genes in our GD cohort, we identified nonsense variants only in NLGN3 and no splice variants. We also found few rare and predicted damaging missense variants in this gene list identified. Indeed, two rare (MAF 25) missense variants were identified in the genes PLXNC1 and CLSTN2 in two further probands (now summarized in Supplemental table 4). We have not identified further probands with PLXNC1 or CLSTN2 variants of interest from additional cohorts and thus at present we have not yet taken these gene variants further for molecular characterization, but we will examine the relevance of this gene variant in future work.

Do the probands have a clear explanation for their developmental disability other than the gene noted?

__Reply: __We thank the reviewer for raising this point. Proband exomes were also screened for genes related to developmental delay and no other causal gene variant were identified. We added this information in the text, lines 183-185.

I would encourage the authors to update Table 3: they are missing IHH/KS genes such as GLI3, SEMA7A, SOX2, STUB1, TCF12. I suggest they update the Table and analyses.

Reply: we thank the reviewer for highlighting this point. Since we performed a new analysis, we also performed a new candidate gene prioritization using a more up-to-date gene list to instruct ToppGene (please see revised Supplemental table 3).

CROSS-CONSULTATION COMMENTS Dear Reviewer #2, I am concerned that the paper presents only a single case of GD to support the scientific work. What do you think?

__Reply: __We would like to highlight that, as we describe above, GD can be diagnosed prior to pubertal age in individuals with red flag phenotypic signs and biochemical evidence of hypogonadism.

Dear Reviewer #1: In addition to the weakness in the microarray data, what do you think about the authors using publicly available data from human GnRH neuron transcriptomics for analysis?

__Reply: __please see the above discussion on the comparison with publicly available datasets.

Reviewer #3 (Significance (Required)):

There is not high significance to this paper: This is not the first article with GnRH transcriptomes. I would argue the human data is more relevant. Developmental disability has been previously linked the GnRH deficiency (as even cited in this paper) The article presents one case of GnRH deficiency, and one pre-pubertal case -- providing some modest evidence for a candidate gene, NLGN3.

__Reply: __We would like to rebuff this assessment of the paper’s significance. To our knowledge, this is the first report of transcriptomes from primary GnRH neurons isolated at key embryonic developmental time points. Other published reports refer to iPSC-derived or adult GnRH neurons (Keen et al., 2021; Lund et al., 2020; Wang et al., 2022; Vastagh et al., 2016 and 2020).

Similarly, the association of central hypogonadism with developmental disabilities have been reported in registry-based studies, but few causative genes have been identified, nor patient variants functionally validated in order to investigate the molecular biology underpinning this association. In the Discussion, in the light of a recent paper (Manfredi-Lozano et al., 2022, doi: 10.1126/science.abq4515), we also postulate that NLGN3 might be required for neuritogenesis of extra-hypothalamic projections of GnRH neurons thus contributing to the pathogenesis of NDD (lines 294-300).

Regarding to human data, we would like to acknowledge that we had a third case that we were not able to publish due to family consent. NLGN3 deficiency is likely to be a rare disorder, but that should not obviate the impact of investigating the molecular etiology – indeed, many insights into human biology have come from private mutations in rare disease.

I think this whole thing is interesting to me, it almost reminds me today of todays political climate. I feel like there are times in which the different news sources all argue and disagree in similarly childish ways, and where people will manipulate the information that is disseminated to the public for their own personal gain. This is an interesting social facet to the interaction/connection of nature and commerce; which I find interesting because commerce is a largely social construct and innovation in many ways is as well. Social facets may be more important than we think in these analyses; it almost reminds me of Solnits designation of the ghost dance as technology and the amount of social/group emotional factors that unexpectedly need to be considered in that thought.

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Reply to the reviewers

RC-2022-01632

Answers to referees

First of all, we wish to thank the 3 referees for their careful evaluation of the manuscript. We see many issues that they have raised as legitimate and have tried to provide experimental or editorial answers. In contrast, some issues are presently addressed in the context of a future manuscript and we had rather not introduce these studies in the revised version.

Below, one will find the answers and the description of the revisions already introduced in the revised manuscript (questions are recalled in blue italics).

New and modified figures, plus not shown figures and tables are indicated in the text below but could not be pasted in the document and can be found in the Revision plan.

Referee # 1

Evidence, reproducibility and clarity

They then delivered 86/8 and LSBio anti-En1 antibodies, that catch En1 in the cleft and prevent it from being captured by MNs.

Perhaps we were not clear. We did not deliver the antibodies 86/8 and LSBio, we used them for western blots and immunohistochemistry (IHC) to identify EN1 and localize it. We delivered the third antibody, a single-chain anti EN1 antibody (scFvEN1), that captures extracellular EN1 and prevents it from being captured by MNs on the basis of the LSBio staining (Figure 4A-C).

Finally, heterozygotes revealed also a degeneration in dopaminergic neurons within midbrain similar to the one observed in spinal MNs, along with an upregulation of SQTSM1/p62 gene/protein, a factor in MN ageing linked to the classical genes implicated in familial forms of ALS (SOD1, TDP-43, FUS, and C9ORF72).

This is a fair comment/work description, that does not require answers.

Significance

*Major comments: *

It is unclear why levels of intensity for RNAscope were not quantified, and qPCR was preferred for quantifications in Figure 1b. RNAscope is a technique that allows for spatial distribution analysis of the markers and their level of the expression. This data can be easily quantified utilizing the QuPath software which is open access. Same concerns apply to Figure 2a.

Quantitative RT-PCR provides a quantitative measure of gene expression. Since only V1 interneurons (including, Renshaw cells) express EN1, we infer the spatial distribution, although not expression level cell by cell. Figure 2A is an actual counting at 4.5 months of En1+ cells and of Calbindin+ cells (Renshaw cells), both identified by RNAscope. Thus, it is clear that the number of En1-expressing cells (V1 interneurons) is not modified at 4.5 months when muscle weakness and death of aMNs are well advanced (around 70% of the aMNs that will eventually die, are already gone). Long-term survival of V1 interneurons is further demonstrated in Figure 2D (left panel) until 15.5 months, (see also below) whereas total En1expression is reduced by half. Quantification neuron by neuron of the amount of En1 transcribed (RNAscope) would indicate the variation, among interneurons, of En1 transcription in WT and mutant mice. This is interesting per se but would not modify the main information that these neurons do not die in the heterozygote and that En1 transcription does not decrease with time in both WT and mutant genotypes (at least until 15.5 months).

*Antibodies should be validated utilizing a reporter mouse. En1cre mice are commercially available and can be crossed with reporters (TdTomato or YFP mice). Utilizing this tissue En1 antibodies can be easily validated. The EN1 antibody shown in Figure 1c seems unspecific, staining several neuronal populations in the spinal cord. *

Indeed, antibody validation is extremely important. LSBio is commercial (CliniSciences), 86/8 was developed in the laboratory and fully characterized and used in previous studies (e.g. Alvarez-Fischer et al. Nature Neurosci. 14: 1260-1266, 2011; Rekaik et al. Cell Reports 13: 242-250, 2015; Blaudin de Thé et al. EMBO J. 37: e97374, 2018), scFv against EN1 was prepared from the 4G11 hybridoma (Developmental Hybridoma Bank, Iowa City, USA) and validated in previous studies (e.g. Wizenmann et al. Neuron 64: 355-366, 2009). In the present study, the two polyclonal were further validated inseveral ways.

In the WBs we compared ventral midbrain (VMB) and spinal cord (SC) tissues and found similar patterns. Strong evidence for antibody specificity is immunostaining extinction with the antigen and with absence of first antibody, which we carried out.

We have now used LSBio and 86/8 to perform a WB on spinal cord (SC) and ventral midbrain (VMB) extracts with or without the first antibody and we find that the absence of first antibody fully eliminates band staining. The western has been introduced in the revised manuscript in place of the cross immunoprecipitation.

Finally, we have quantified EN1 in the aMNs of the heterozygote at 3 months (before cell death), showing that EN1 content is decreased by approximately 2-fold (LSBio antibody) in both a and gMNs with no change in neuron number. This result demonstrating that EN1 is diluted by approximately twofold (concentration per neuron when all neurons are still present), in addition to further validating the antibody, is itself interesting and has been introduced in the revised manuscript as Supp. Fig. 1A.

Regarding the staining in other neuronal populations, there is always some background, in particular in the tissue treatment conditions used for RNAscope. Furthermore, given the large number and wide distribution of V1 interneurons (Fig. 1A), we cannot preclude that EN1 is present at a low concentration in the extracellular space and in several cell types (discussed in Fig. 9 of the manuscript). This does not weaken the main conclusion that it primarily accumulates in MNs which do not express En1 (RNAscope).

*Investigations of En1 expression in motor neurons from already available omics data sets would support the idea that En1 is expressed in motor neurons. *

The En1 locus is silent in MNs. Microdissection of MNs and proteomic analysis would not be definitive since the interneurons that produce EN1 are in close vicinity of the MNs and since some protein is necessarily present in the extracellular space (where it is trapped by scFvEN1), making contamination unavoidable.

Differentiation between Gamma and Alpha motor neurons should be performed using specific markers as Err3, Wnt7a or NeuN.

This is a possible way to do the distinction, but size criterion in Cresyl violet is supported in the literature (Wu et al. Journal of Biological Chemistry, 287: 27335-27344, 2012; Dutta et al. Experimental Neurology, 309: 193-204, 2018). In our study, it is further validated by the demonstration that, in 9-month-old animals, the results obtained (cell number and specific death of large neurons >300µm2, but not of intermediate size ones 200-299µm2) are replicated by counting ChAT-stained neuron (Figure 2C). It is of particular interest that the number of medium size neurons (also ChAT-positive medium size MNs) does not increase when the number of large size (Cresyl and ChAT-positive) neurons decreases, thus precluding a “shrinkage effect”. Most importantly, the size criterion (Cresyl violet) allows us not to be mistaken by a possible down-regulation of markers in the mutant, independently of cell survival. We provide for the reviewer (Revision plan) but not for publication, the evolution with time of the number of neurons based on size (above 200 µm2) showing clearly that at 15.5 months the large population (>300 µm2) is decreased in the En1-Het, with very little change for neurons between 200 and 300 µm2, and certainly not an increase which would be expected if shrinkage occurred.

We were indeed surprised by this finding and a plausible explanation is that a lower metabolic activity makes interneurons less sensitive to stress than aMNs which have to “fuel” long axons and high firing rates (not the case for gMNs). We propose this explanation in the discussion and make it clearer in our revised version. We agree that it is speculative and that the point raised by the reviewer is very interesting. We hope to address this in the future and have discussed this point.

Since the cells do not die, we did not look for signs of apoptosis.

We analyze lumbar sections from L1 to L5 as now indicated in the methods section in the manuscript

The set of experiments reported in Figure 4 is of difficult interpretation without showing the actual presence of extracellular En1, that could be assessed with protein detection or RNAscope.

This is another interesting suggestion, but we think that it will be difficult to distinguish low extracellular staining due to EN1 diffusion from some unspecific background. Since the scFvEN1 is secreted by astrocytes, it necessarily neutralizes extracellular EN1, resulting in a decrease in the MN content of the protein. This is an experiment with high specificity since the same scFv harboring a Cysteine to Serine point mutation that prevents EN1 recognition (no disulfide bound formation between the light and heavy chains) does not block EN1 capture by MNs (Fig. 4C for IHC and quantifications).

As for extracellular EN1 mRNA identified by RNAscope, we hesitate to embark on the idea as mRNAs are likely secreted in insufficient amounts to be identified, even by RNAscope. The results that we have (no En1 visible by RNAscope in MNs, loss of EN1 in MNs following extracellular scFvEN1 activity, and preferential addressing of injected EN1 to MNs) demonstrate EN1 capture by MNs. Indeed, we cannot completely preclude the transfer of tiny amounts (escaping RNAscope detection in MNs) of En1 mRNA (for example, through extracellular vesicles), but we plead for not considering this hypothesis in the present paper. However, if the reviewer wishes, the possibility can be introduced in the discussion.

Referee 2

Evidence, reproducibility and clarity

In general, most of the experiments shown in this study are well done and convincing. However, the data on p62 upregulation appear correlative and do not allow any conclusions about the mechanism and function how EN-1 modulates motoneuron survival and function. In addition, this study is not very precise on the mechanisms how motoneurons degenerate in this model so that there are only limited insights into the way how EN-1 acts on motoneurons in a physiological manner and under pathophysiological conditions.

This criticism is justified, at least in part, as we agree that p62 upregulation is correlative. However, the fact that the neutralization of extracellular EN1 by the scFv increases p62 expression, is in favor of a causative link. The increase is also seen at 3 months in the En1-Het when all aMNs are still present but not after, which is interesting because, due to aMNs death, surviving MNs receive more EN1, information provided below and now introduced and discussed in the revised manuscript (Supp. Fig. 1B).

As for p62, and as also mentioned by referee 3, Fig. 8 is very hard to follow and we propose to simplify it to make the message clearer:

We have revised Fig. 8C, D in which we focus exclusively on SQTSM1/p62 mean expression (see revision plan)

A second information is that a difference in mean p62 expression between WT and Het is seen only at 3 months in aMNs. For aMNs, we propose that this is due to the fact that they are very sensitive to EN1 dosage (in contrast with gMNs which do not die in the En1-Het). At 3 months, aMNs have only half of their normal EN1 content. Later, at 4.5 months 75% of the aMNs bound to die are already dead (Fig. 2D) and the remaining neurons receive more EN1 (even more so at 9 months), as could be measured (see above Supp. Fig. 1B). We thus can propose an accelerated aging of aMNs at 3 months due to both EN1 decrease and high metabolic activity (higher than in gMNs).

In the case of the scFv, scFvEN1, but not the mutated version induces enhanced mean p62 expression in the 80% surviving aMNs and in gMNs at 7 months (low aMN death in this model, see Fig. 4F). As can be seen also in a newly added figure (Supp. Fig. 2) that has been introduced in the revised manuscript and is shown below, 7-month-old scFv animals and 3- to 3.5-month-old En1-Het have similar phenotypes. This mild scFv phenotype (a-MN death and muscle strength loss) in 7-month-old mice in spite of a huge loss in the EN1 content of MNs (Fig. 4C) suggests that the En1-Het phenotype is not entirely due to the decrease in EN1 transport from V1 interneurons to MNs (see discussion and Fig. 9).

It remains true that we have voluntarily decided not to examine in depth the molecular mechanisms allowing EN1 to exert its protective activity, a decision that we would like to defend and maintain.

A first reason is that in previous papers on mesencephalic dopaminergic (mDA) neurons (Alvarez-Fischer et al. Nature Neurosci. 14: 1260-1266, 2011; Rekaik et al. Cell Reports 13: 242-250, 2015; Blaudin de Thé et al. EMBO J. 37: e97374, 2018), we evaluated several mechanisms involved in EN1 neurotrophic activity and we did not want this study to be a duplication of studies done on a different neuronal population, even if mechanisms might differ in part, between aMNs and mDA neurons. What has interested us more is that, in the two cases, age is an important factor in the unveiling of the degeneration phenotype (mDA neurons start dying at 1.5 months and aMNs at 3 months). It is because of this similarity that we performed the bioinformatic study that has led us to SQTSM1/p62. In this context, it is of interest that mean SQTSM1/p62 expression (variability of expression between neurons is not discussed in the revised version) increases with age in the wild type, thus can be seen as an age marker. It allows us to propose that EN1 extracellular neutralization and the loss of one En1 allele, that increases mean SQTSM1/p62 expression accelerate aging.

A second reason is that the study is oriented toward a possible use of EN1 as a therapeutic protein. This orientation also has to do with the focus on SQTSM1/p62. Indeed, there are probably many pathways downstream of EN1, but in the bioinformatic analysis of genes differentially regulated in WT and En1-Het mDA neurons and also expressed in MNs, SQTSM1/p62 is the only one that interacts with the 4 genes mutated in the major ALS familial forms. In addition, SQTSM1/p62 mutations have been observed in ALS patients (References 41 to 45 in the manuscript).

Finally, the most important point is that the main message of this paper is the discovery of a non-cell autonomous EN1 activity in the spinal cord and of its ability to travel between V1 interneurons and MNs. This specificity best explained by a targeting signal that we have identified is at the basis of the specific addressing to MNs of EN1 intrathecally injected, which also has implications for its potential therapeutic use.

Specific points of criticism

1. • In Fig. 2a, the authors show that EN-1-positive interneurons are not reduced at 4.5 months in the spinal cord. No data are shown for later time points such as 9 months, the corresponding stage when motoneuron loss is observed, or at 16 months which corresponds to the data shown in Fig.1. The argument that there is no reduction of V1 interneurons between 4.5 months and 16 months because there is no decrease of EN-1 expression between 4.5 and 16 months, as shown in Fig. 1b is not convincing. EN-1 expression could change in individual cells, thus compensating for the loss. Data on numbers of EN-1-positive cells at 9 and 16 months should be included, and a potential autocrine effect of EN-1 on V1 interneurons, as observed in midbrain dopaminergic neurons, characterized in more detail. * Fig. 2A illustrates the absence of interneuron loss at 4.5 months, but this set of data is completed by those of Fig. 2D that demonstrate the maintenance of V1 interneuron number until 15.5 months, at least. It can be noted that, in contrast with interneurons, aMNs at 4.5 months have experienced massive cell death (70% approx. of total aMN death at 15.5 months). As a whole, data of Fig. 2 demonstrate that the number of small neurons (100-199 µm2) and intermediate size neurons (200-299 µm2) does not change with age, at least through 15.5 months. This is in strong contrast with large aMNs (>300 µm2). As already explained in our answers to referee 1, size is an excellent marker for the identification of neuronal subtypes and the analysis of survival (See answers to referee 1, justifying the use of neuron size).

2. In Fig. 2e, the authors present data on loss of muscle strength between 4.5 and 15.5 months. They conclude that this reflects gradual neuromuscular strength loss. Since neuromuscular endplates have a very high safety factor, they can maintain full function even if transmitter release is reduced by more than 80%. Therefore, the loss of muscle strength seems to reflect the progressive loss of presynaptic terminals at neuromuscular endplates, rather than a gradual loss of neuromuscular strength. *

We apologize for the semantic confusion. What is measured is a progressive loss of muscle strength due to the progressive loss of presynaptic terminals and not a gradual loss of neuromuscular strength. This is now modified throughout the revised text.

• More detailed data on NMJ morphology should be included. How does EN-1 modulate neuromuscular endplates? Is EN-1 located at neuromuscular endplates after being taken up from motoneurons? Even if the mechanism is indirect, via upregulation of p62 under conditions when EN-1 signaling is reduced, does this situation lead to enhanced localization of p62 at neuromuscular endplates? *

We do not see expression of En1 mRNA or the presence of EN1 protein at the level of the endplate (Supp. Fig. 3 in revision plan)

• The data shown in Fig. 3 on changes in NJM morphology appear incomplete and not convincing. As SV2a is not a good marker for changes in presynaptic compartments since it does not allow conclusions on how many synaptic vesicles are released, additional markers for presynaptic active zones such as Bassoon, Piccolo, Munc-13 should be studied. The analysis of fully occupied endplates appears arbitrary, and the differences are relatively small. Additional EM pictures and quantitative analyses of active zone proteins in the presynaptic compartment would help to support the argument of the authors that presynaptic compartments degenerate before cell bodies are lost in EN-1 +/- mice. *

SV2a and NF staining (it is not only SV2a) at the level of endplates identified by a-Bungarotoxin labeling has been used in a large number of studies (Wahlin et al. J. Comp. Neurol. 506: 822-837, 2008; Hasting et al. Scientific Reports 10: 1-13, 2020; Yahata et al. J. Neurosci. 29: 6276-6284, 2009 ; Jones et al. Cell Reports 21: 2348-2356, 2017) Our goal was not to document the loss of synaptic activity through the use of the three suggested markers, Bassoon, Piccolo and Munc-13. Doing it would force us to initiate experiments taking several months to prepare the material and do a quantitative analysis in the models of EN1 loss of function (En1-Het) and neutralization (scFv), plus rescue by EN1. Nor do we wish to initiate a novel collaboration to produce a quantitative ultrastructural study. We see the latter morpho-functional studies beyond the scope of the manuscript and wish to be given the possibility to present them in a separate study (see below in “Description of the experiments that the authors prefer not to carry out”).

The distinction between fully occupied, partially occupied and denervated endplates is not arbitrary and we apologize for not having sufficiently described the methodology. As illustrated in modified Fig. 3 and explained in Material and Methods, a fully innervated endplate is defined as an endplate in which 80% or more of the green pixels (a-BGT) are covered by a red pixel (SV2a), a partially one is between 20 and 80% and a denervated one below 20% coverage. Thus at 9 months and later ages, close to 30% of the endplates are either partially innervated or denervated. In fact, it is more likely that they are partially innervated since the number of AChR clusters does not change (totally denervated clusters normally dissolve). The 80% threshold for fully innervated was selected to give a margin of security, and it is likely that the percentage of 25 to 30% of partially innervated endplates is an underestimation.

In the Revision plan is presented a table with the calculations and modified Figure 3.

We agree that we were not clear enough in our description and that it may have given the impression that the differences were relatively small. We think that retrograde degeneration is strongly supported by a loss of muscle strength that parallels the decrease in fully occupied endplates (a-BGT, NF, SV2a) and precedes aMN loss by more than 1 month. We have recently contacted an electrophysiology group to establish a collaboration that will allow us to follow functional changes at the level of the spinal cord and of the neuromuscular junction and we see the experiments proposed by the reviewer as complementary to these physiological approaches. Yet, we do not want to ignore the opinion of the reviewer and mention it in the conclusion, on the basis of his/her comment.

• The authors present evidence for a glycosaminoglycan (GAG) binding domain that appears responsible for uptake of EN-1 into motoneurons. However, it is unclear into which cellular compartment EN-1 is taken up after GAG binding on motoneurons. The authors propose this could be an alternative pathway to conventional endosomal uptake. How can the EN-1 that is taken up into cells exert transcriptional effects in motoneurons? As a minimum, more data on the subcellular distribution of endocytosed EN-1 should be included to support current hypotheses and to close the gap from cellular uptake to transcriptional regulation. *

The question is justified since we did not recall until page 12 of the Discussion that EN1 is, as most tested homeoprotein transcription factors, captured by a mechanism distinct from endocytosis. While not yet fully understood, the process involves the formation of inverted micelles that allow for direct targeting to the cytoplasm and from there to the nucleus thanks to the NLS. We now mention in the introduction that EN1 transfer and HP transfer is based on unconventional secretion and internalization processes.

• The differences in p62 expression with age in WT and EN-1 +/- mice as shown in Fig. 8c are not convincing. First, the p = 0.0499 and p = 0.0536 values for differences at 3-4 months of age appear borderline, and it is unclear what the dispersion analysis that is shown really means. Moreover, the question remains how a potential dysregulation of p62 then affects NMJ morphology and function. Is this change in p62 also detectable in presynaptic compartments? *

We agree that p values in the range of 0.05 are not extremely high and this is due to the heterogeneity in SQTSM1/p62 expression, that reflects that of MN populations, and induces a high variance. We also agree that this figure is too complicated and a simplified version has been proposed above (see answers to reviewer 1). To summarize, Fig. 8C shows that in WT animals, with no aMN death (grey) the level of SQTSM1/p62 expression in aMNs and gMNs increases between 3 and 4.5 months and between 4.5 months and 9 months, with significances varying between pThe new Fig. 8 panel D (please see above, answers to referee 1) now includes the results obtained with the scFvs. A phenotype comparison between the two models (En1-Het and scFvEN1) has been introduced in Supp. Fig. 2 (see above).

We have no evidence that EN1 modulates the SQTSM1/p62 promoter directly. The identification of this gene as a target (not necessarily a direct target) of EN1 comes from the bioinformatic analysis described in the manuscript and we were intrigued by the interaction with the 4 main familial ALS mutations and the existence of families with SQTSM1/p62 mutations. This is what led us to analyze its expression in our two models of EN1 loss of function. Although the En1-Het mouse is not an ALS model, the results support the idea that EN1 could be used as a therapeutic protein in several familial and even sporadic forms of the disease. The latter hypothesis is now being tested on MNs derived from iPSCs (sporadic patients, fALS and isogenic variants, and healthy controls). If the data lend weight to our hypothesis, as collaborative and in-house preliminary data suggest, then a complete analysis of EN1 targets in human MNs will be undertaken. Again, we really think that this is out of the scope of this study.

For Fig. 8, we fully agree that it can give headaches and we apologize. Moreover, it induces wrong interpretations (mean intensity increases with age and dispersion between 4.5 and 9 months has a calculated p__Referee #3__

Evidence, reproducibility and clarity

Nevertheless, the connection between EN-1 and p62 is not well developed by the data presented and future readers may be left with many questions regarding how EN-1 and p62 are related (e.g. direct interaction? transcriptional regulation?), whether p62 is indeed the mediator of EN-1 trophic effects, or the significance of the increased levels of p62 for motoneuron disease

The reviewer is right and we have tried to better explain and to simplify. Please see responses to referees 1 and 2.

*Figure 1C: There appears to be EN1 immunoreactivity (green) in several areas of the spinal cord, including dorsal regions. Can the authors clarify what that labeling could be representing? *

Unfortunately, there is always some background staining, in particular in the tissue treatment conditions appropriate for RNAscope. Furthermore, given the large number and wide distribution of V1 interneurons (Fig. 1A), we cannot preclude that EN1 is present at a low concentration in the extracellular space and in several cell types (now represented in Fig. 9). This does not weaken the main conclusion that it primarily accumulates in MNs which do not express En1 (RNAscope).

*Figure 1D: These immunoprecipitation results lack a negative control with irrelevant antibody to confirm that the band shown it's being recognized specifically by the antibodies reacting with the blot. *

Please see the response to reviewer 1 above with the Western blot and the absence of staining on a WB in absence of first antibody (86/8 or LSBio).

F*igure 1E: The intensity of the EN1 labeling in MNs, much stronger than in V1 interneurons, is intriguing, given that MNs do not express engrailed-1 mRNA. One would have expected the opposite. It may help here if it was possible to show that immunoreactivity in MNs is diminished in the het mutant mouse. *

We also were surprised by this intensity higher in MNs than in V1 interneurons, as if the protein was exported rapidly towards the target neurons. We have done the experiment proposed by the referee, found a twofold (approx.) immunoreactivity reduction in En1-Het MNs (see above Supp. Fig. 2A in answers to referee 2). This supplemental figure has been introduced in the revised version. The experiment was done at 3 months when no MN death has yet occurred. Later the neurons “replenish” with EN1, probably because they do not have to share the limited supply with the dead ones (see above answers to referee 2 and Supp. Fig. 2B).

*Figure 2D: There are a few possible problems with these data and their interpretation. First, this reviewer feels that 5 neurons (y-axis) is a rather small number. Are these 5 neurons per what area? From how many mice? I did not find that information in the figure legend. A larger area should be quantified so that we get numbers that are more robust. Second, such differences could also be due to hypotrophy of the MNs, namely, that MN number is the same but they are smaller. *

The differences cannot be attributed to hypotrophy. A first reason is that, at 9 months, the Cresyl violet and ChAT staining give the same results for medium size and large neurons (Fig. 2C). Furthermore, when one counts the cells throughout 15.5 months, the decrease in the number of large neurons is not compensated by an increase in the number of medium size or small ones. The reasoning and a graph, not intended for publication can be found in answers to referee 1.

*Figure 3A: It would be useful that the authors explain how these AChR clusters were defined, visualized and counted. I could not find this information in the Methods. Perhaps this could be done by showing an alpha-BTX image illustrating the clusters. *

We fully agree that the procedure was not well explained and we have introduced a correction in the Material and Methods section. For more details, please see answers to referee 2.

*Figure 3B: As each adult endplate is only innervated by one MN, one would have expected fewer clusters and/or endplates, if indeed MNs are missing in this mouse, rather than endplates that are partially occupied. This could be clarified a bit more explicitly. *

This is true and the ambiguity takes its origin in insufficient explanation of how fully innervated, partially innervated and denervated endplates were defined. Please see above and also in answers to reviewer 2. Modifications have been introduced in the text and in Fig. 3. The referee is right, the absence of change in the number of AChR clusters suggests that there are very few fully denervated endplates and that what is defined as such in the analysis corresponds to partially innervated endplates (see above). This is now discussed in the text.

Figure 6B: Would not be better to do this with a virus, like in the case of the antibody? A more robust effect on MN survival may be attainable and thus strengthen the concept.

This would be another interesting experiment and we are presently exploring this possibility (with preliminary results). The choice of the virus and of the promoters is very important. We are comparing several AAVs, including AAV2, AAV2-TT (which diffuses better) and AAV8. For the promoter, we do not want to express within MNs as the imported protein might have special properties, associated with import. V1 interneurons would be best, but we have to verify if this does not modify V1 physiology. Astrocyte is another option, but with a similar pitfall. This means that we have a long way to go before proposing a “gene therapy” approach.

In addition, in the context of future clinical studies, we were eager, on the basis of the long-lasting activity of the protein already observed in the mesencephalic dopaminergic neurons (Alvarez-Fischer et al. Nature Neurosci. 14: 1260-1266, 2011; Rekaik et al. Cell Reports 13: 242-250, 2015; Blaudin de Thé et al. EMBO J. 37: e97374, 2018), to try a protein therapy in the spinal cord. Interestingly, the effects are also long-lasting in the spinal cord, (12 weeks in the mouse before a second injection is needed) and, according to contacted physicians, intrathecal injections, every second month or even more frequently, could be envisaged in the human. In that case, protein injection is possibly advantageous for the following reasons:

(i) viral particles can travel far and we do not know what would be the side effects.

(ii) the protein is short-lived but specifically addressed to MNs (thanks to the presence of EN1 binding sites at their surface), thus minimizing the issues associated with permanent expression and side effects.

(iii) EN1 is a natural protein normally secreted and the immune system might not be solicited as much as with viral approaches.

*Figure 7A: The protein seems to be mainly in the cytoplasm of those cells (nuclei are dark and unlabeled), which is also unusual for a transcription factor that functions in the nucleus. Also surprising that the protein is gone in 3 days, but has effects over 24 weeks. Any explanation for that? *

The protein is imported and is thus both in the cytoplasm where it exerts an effect on protein translation (Brunet et al. Nature 438: 94-98, 2005; Alvarez-Fischer et al. Nature Neurosci. 14: 1260-1266, 2011; Yoon et al. Cell 148: 752-764, 2012) and in the nucleus where it exerts its transcriptional and “epigenetic activity (see below for the latter). In fact, different antibodies and fixation procedures can favor cytoplasmic or nuclear staining. When nuclear, the dark point at the center, probably the nucleolus is less stained.

Two images illustrating this point are shown in the revision plan.

For the second part of the question, three days are sufficient for a long-lasting activity. This was also observed in the midbrain where the protein restores the epigenetic marks jeopardized by an acute oxidative stress (Rekaik et al. Cell Reports 13: 242-250). This has led to the hypothesis that EN1 has an important action at the level of the structure of the heterochromatin, thus a long-lasting “epigenetic” activity. We are presently working on the latter effects on the chromatin structure using human MNs derived from iPSCs (patients and control).

*Figure 7B: It's not clear what the blue and red bars mean, as this is not explained in the legend. Also, the y-axis says "%Chat+" suggesting they are counting MNs, but in the text they talk about EN-1 capture. If the latter, the y-axes should indicate % EN-1 over Chat, or something like that. In general, better figure legends would improve the experience of the reader. *

In this experiment, we wanted to test the presence of a GAG-binding domain in EN1. To test its potential role in EN1 internalization and localization, we co-injected or not the RK-EN1 with hEN1 protein. Then, we counted the percentage of MNs (%ChAT+) which contain, or not, the hEN1 protein (hEN1+ in red or hEN1- in blue), allowing us to verify if the RK-EN1 alters the internalization of the hEN1 protein. So yes, we are looking at the capture of EN1 by the MNs with or without the RK-peptide (or control peptides). We have modified the text to make the point clearer.

*Statistical analyses: In principle, comparisons of data obtained in studies that involved two variable parameters (such as time and genotype/treatment) should be weighted by a 2-way ANOVA test, which is more stringent since more conditions are being tested simultaneously. Usually a t-test is reserved for a pairwise comparison in an experiment involving only two conditions of the same variable. *

The reviewer is correct. The two-way ANOVA is explained in the Statistical analyses section of the Methods. The analyses were carried out and the results listed in the legends for Figs 2, 3, 4, 6 and Supp. Fig. 1.

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Reply to the reviewers

1. General Statements

We would like to thank the editor for handling our manuscript entitled, “Mouse SAS‑6 is required for centriole formation in embryos and integrity in embryonic stem cells”, and the reviewers for the insightful comments and suggestions to improve our work. We aim for our manuscript to be considered for a “Short Report” format. As such, we would like to emphasize that we did not focus on the in vivo part of our study, where the Sas-6 mutant mouse embryos resemble our previously published Sas-4 mutants, as pointed out by the reviewers, because both mutants lack centrioles. In our opinion, the novelty of our work is evident in the discovery that mouse embryonic stem cells (mESCs) lacking SAS-6 are still able to form centrioles, albeit mostly abnormal, which is also shared by the reviewers. This is in contrast to Sas-4 mutant mESCs for example, which lack centrioles (Xiao*, Grzonka* et al, EMBO Reports 2021), and human cultured human cell lines without SAS-6, which have been shown to lose centrosomes. We are in the process of editing the manuscript and performing additional experiments per the reviewers’ recommendations. Below, we provide a point-by-point description of our revision plan.

2. Description of the planned revisions

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

The article by M. Grzonka and H. Bazzi entitled: Mouse Sas-6 is required for centriole formation in embryos and integrity in embryonic stem cells, describes new findings in novel mouse models of Sas-6 knockouts (KO). This is an interesting study that reports two different mouse Sas6 KO models and the depletion of Sas6 from mouse embryonic stem cells (mESCs). This type of analysis has never been done before and so it reveals and describes a role for Sas-6 in centriole biogenesis in mouse.

We thank the reviewer for highlighting the novelty of our work on the roles of SAS-6 in mice.

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The authors compare their analysis with Sas-4 KO and overall found similar results when compared to previous work from H. Bazzi, when Sas-4 was depleted in mouse embryos. Due to the mitotic stopwatch pathway, Sas6KO embryos die during development at extremely early stages and this can be rescued by depletion in p53 and other members of the pathway.

Perhaps, not so surprisingly, these embryos do not contain centrioles, showing that in vivo, Sas6 is absolutely required for centriole duplication. More surprisingly, however, in cultures of mESCs, established and propagated in vitro, Sas-6 crispr induced KO, does not result in lack of centrioles. Instead, abnormal structures that show aberrant morphologies, length, and incapacity to assemble cilia were detected. In principle, this means that centrioles can be assembled independently of Sas-6, even if not in the correct manner.

We again thank the reviewer for astutely pointing out the most surprising finding in our data, which is that mESCs lacking SAS-6 can still form centrioles.

The authors interpret these differences as possible differences in the pathways involved in centriole assembly and propose different requirements in different cell types, within the same species.

I have problems with this interpretation. To me is very difficult to understand, how the "protein" absolutely required for cartwheel assembly at the early stages of centriole biogenesis, can be essential and dispensable at the same time. Although, I may be wrong, I think the authors have not envisage other possibilities to interpret their data, which should be taken into consideration.

We agree with the reviewer that SAS-6 is currently considered in the centrosome field as one of the “core” centriole formation or duplication factors and that it is a major component of the cartwheel scaffold during the early phase of centriole biogenesis. Although, the absence of centrioles in the Sas-6 mutant mouse embryos in vivo supports the essential function of SAS-6, and perhaps the cartwheel, in centriole formation; the mere presence of centrioles in mESCs indicates that SAS-6, and again the cartwheel, is not essential for the existence of centrioles in these cells. Because this is a major finding that we would like to bring across from our study, we will better highlight and clarify it in the new version of the manuscript as described below. In fact, in points #4 and #5, we share the same possible explanation for the difference in the phenotypes between Sas-6 mutant mouse embryos and mESCs as the reviewer.

1) I do not know anything about ESC and ESC cultures. So maybe this is a stupid suggestion. But can't they be derived exactly from the same genetic background of SAS-6KO embryos? Because the way the two (or even 3 as there are 2 mouse KO lines) are generated is different. Why is that?

The reviewer is correctly suggesting that the mESC can be derived from the Sas-6 mutant blastocysts. We have initially derived mESCs from the Sas-6em4/em4 mutants and performed our analyses on the centriole phenotypes in these mutants before realizing that the allele was hypomorphic (SAS-6 staining in Fig. S2F, and the appearance of centrioles at E9 in Fig. S1B). Because the surprising finding in our study is that SAS-6 does not seem to be essential for centriole presence in mESCs, as pointed out by the reviewer, we decided to generate a more convincing Sas-6-/- null allele in mESCs by deleting the entire ORF of Sas-6 (more on this point below). We would also like to direct the attention of the reviewer that we have cultured the blastocysts (E3.5) from the Sas-6em5/em5 null mutants, which as we show lack centrioles at E3.5, and the cells indeed start to form centrioles just 24 h post-culture (Fig. 3C-D).

To build on these findings, we have already taken this a step further and generated a mESC line from the Sas-6em5/em5 mutants. These Sas-6em5/em5 –derived mESCs show CENT2-eGFP-positive centrioles, and we are currently analyzing their number and integrity, similar to our analyses of the CRISPR-generated Sas-6-/- null mESCs.

2) Still on mESCs, are the authors sure that there are no WT Sas-6 mRNAs still present in their ESC cells? Because tiny amounts are maybe sufficient to allow the initial cartwheel structure. In FigS2B, I can see a really faint band, very faint but it is there.

Due to the nature of the surprising finding that Sas-6 mutant mESCs can still form centrioles, we understand the concerns and suggestions of this reviewer and the other reviewers in this regard. We have generated several Sas-6 mutant alleles in mESCs (in exons 2, 4 or 5), in which we used Western blots to check whether they were null alleles or not. We used different commercial (Proteintech cat# 21377-1-AP, Sigma-Aldrich cat# HPA028187 and Santa Cruz cat# SC-81431) and non-commercial (kind gift from Renata Basto, Institute Curie) antibodies. The SAS-6 antibody from the Basto lab gave the most reliable and reproducible results. Using this antibody, and in our own interpretation, we were not able to detect SAS-6 by Western blots in Sas-6 mutant mESCs. We concluded that SAS-6 in mESCs (and mouse embryos, see below) is expressed at low levels. Of note, we always detected centrioles in the different Sas-6 mutant mESCs, even those derived from the Sas-6em5/em5 null mutant blastocysts, which as blastocysts had no detectable centrioles.

For a more definitive knockout in mESCs, we decided to bi-allelically delete the entire Sas-6 ORF DNA from the ATG to the TAA (over 34 Kb of DNA, Fig. S2A). According to the central dogma of molecular biology, when there is no DNA, then there should be no mRNA and no protein. In confirmation of this premise, recent RT-PCR data showed that Sas-6 mRNA is not detectable in these Sas-6-/- null mESCs. Also, immunofluorescence analyses did not detect SAS-6 in these cells. We will add the RT-PCR and immunofluorescence data to the fully revised manuscript. We will also repeat the SAS-6 Western blots to achieve better band resolution.

These Sas-6-/- mESCs started from a single cell and have been passaged up to 20 times by now without losing centrioles. SAS-6 protein was not detectable at the early passages and the mRNA is still not detectable. This is how knockouts have been and are produced. If this mutant is still not convincing, then we respectfully ask that the reviewers provide their own suggestion on what will be more convincing. In our humble opinion, this Sas-6-/- mESCs line can be used to test the specificity of the antibodies in mouse cells and not the other way around.

3) This last point goes also with the western-blot of Figure S2C- there is still a band, very tiny between the two very tick bands (marked with *). Maybe separating proteins better will help visualizing the real Sas-6 band? Have they used the Sas6 ab in other WBs from the KO embryos, for example? Can they use the Sas6 ab in immunostaining to show if the assembled abnormal centrioles completely lack Sas6. This will allow to distinguish between the hypothesis of having some (even if not much) sas6 left?

The answer to these questions is above in point #2. In addition, we have used the Basto lab antibody for SAS-6 for Western blots on mouse embryos, which detect low levels of SAS-6 in controls and no signal in the mutants. We will repeat the SAS-6 Western blots on mESCs to achieve better band resolution. Using this antibody for immunofluorescence showed that the Sas-6em4/em4 mutant is hypomorphic, whereas the Sas-6em5/em5 mutant showed very low, most likely background, staining (Fig. S1F). For mESCs, we decided to delete the entire Sas-6 ORF DNA in mESCs and generate homozygous Sas-6-/- null mutants. Immunofluorescence analyses did not detect SAS-6 in these cells.

4) Then a more theoretical point? Have the authors considered that the difference is more in the stability of the abnormal structures. Let's say, without a cartwheel and maybe enough PLK4 activity and high level of other centriolar components, the centrioles are abnormally assembled- they have no cartwheel, but they are disassembled very fast in the embryo but not in ESCs?

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We agree and share the reviewer’s interpretation for the potential requirement of SAS-6 in vivo to stabilize intermediate structures, that is compensated for by other factors in mESCs. This was not directly discussed in the first version of the manuscript and we will include it in the new version.

5) Even if there is a real difference and without Sas-6 ESCs can make centrioles that are abnormal in structure and function (at least at the cilia assemble level), the choice of words "strictly required", I am not sure it is correct. Because, since Sas-6 is described by many studies as the factor required for cartwheel assembly, which occurs very early in the pathway, this means that in mESCs centrioles can assembled without forming a cartwheel. And so that the cartwheel is actually not required for the initial building block, but more as a structure that maintains the whole centriole in an intact manner?

We agree with the reviewer on the likely requirement of SAS-6, and therefore the cartwheel as a whole, for the symmetry and integrity of the forming centrioles, which is along the same line as in point #4. In our interpretation, “centriole formation” does not necessarily mean centriole “initiation” but rather the presence of the centriole as a structure. We will use more appropriate and specific wording to match our shared interpretation with the reviewer.

6) The authors mentioned that in flies, abnormal Sas-6 structures have been described in certain cell types. Are these mutants, null mutants? In other words, do these structures assembled in a context of no Sas6 or abnormal Sas-6 protein or even low levels of Sas-6?

According to the published report (Figure S3B in Rodrigues-Martins et al, 2007, PMID: 17689959) the fly brains have no detectable DSAS-6 protein. Therefore, we assume that they are Sas-6 null fly mutants. The abnormal centrioles in Sas-6 C. Reinhardtii mutants and Sas-6-/- mESCs null mutants support the conclusion that the main role of SAS-6, and perhaps the cartwheel, is in maintaining the integrity of the forming procentriole.

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Other points:

I think the 1st sentence of the abstract appears disconnected from the rest. The same goes for the 1st sentence of the introduction. And also, what is the evidence that pluripotent stem cells rely primarily on the proper assembly of a mitotic spindle? They rely on many other things, not sure this is the first one.

The sentences were meant to highlight the importance of cell division in stem cells. We will adjust the wording in these sentences per the reviewer’s comment to not focus on pluripotency per se.

The authors mention that centrioles are lost in Sas6-/- after "differentiation" of mESCs. The term differentiation is not appropriate, and confusing here. Differentiation normally refer to cells that stopped proliferating and exited the cell cycle, which is not the case here, as NPCs are progenitor cells that keep cycling.

We believe the reviewer is referring to “terminal differentiation”, when the cells exit the cell cycle and adopt their destined cell fates. The word “differentiation” in this context refers to limiting the potency of stem cells into a subset of cell fates such as NPCs, which are proliferating progenitors.

Figure S1: Percent of cells with centrosomes was assessed by a co-staining of gtubulin and Cep164, which mark the mother centrioles. As Cep164 may be absent from centrosomes after lack of centriole maturation in sas6-/- embryos, another combination of staining should be performed to evaluate the percent of cells without centrosomes. gtubulin staining can be seen in Sas6 em5/em5 embryos, while the quantification claims total absence of centrosomes. The authors use the CENT2-eGFP transgenic line to count the number of centrioles in Figure 3, they should do the same in Figure S1.

We will follow the reviewer’s recommendation of counting Cent2-eGFP for the assessment of centrioles in Sas-6em5/em5 (Fig. S1).

The g-tubulin (TUBG) aggregates at the poles of dividing cells are assembled in the absence of centrioles, as shown in Sas-6em5/em5 embryo sections (Fig. S1H). In addition, we have previously observed these pericentriolar material aggregates in Sas-4-/- mutant embryos (Bazzi and Anderson, 2014), which do not contain centrioles in serial transmission electron microscopy. Therefore, we do not refer to them as centrosomes in the absence of centrioles at their core.

Reviewer #1 (Significance (Required)):

This study shows with a novel mouse model the requirement of centrioles during mouse development. It will be relevant to centrosome labs, the novel mouse lines will be useful to many labs working on centrioles, cilia and centrosomes.

My expertise: centrosome biology

We thank the expert reviewer for the critical comments and suggestions, and the positive evaluation of our manuscript.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

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Here, Grzonka and Bazzi present their work on characterizing the requirement of SASS6 in mouse embryo development and in embryonic stem cell (mESC) culture. In mouse, female and male gametes lack centrioles, and early divisions occur without centrioles. De novo formation typically happens at the blastocyst stage (~E3.5). The authors generated two SASS6 knock-out strains, SASS6 em4/em4 (frameshift deletion, reported as a severe hypomorphic allele), and SASS6 em5-em5 (frameshift deletion, reported as a null allele). Mutant embryos arrest development at mid-gestation unless the p53, USP28 and USP28 pathway is perturbed. As expected, centrioles do not form in SASS6 -/- mice. However, the authors report that de novo formation of centrioles is facilitated in mESC culture conditions for SASS6 CRISPR knock-out mESCs and mESCs derived from SASS6 em5/em5 blastocysts. Centrioles are lost upon differentiation of SASS6 CRISPR knock-out mESCs into neural progenitor cells (NPCs).

The presented study is relevant for scientists investigating the requirements for centriole formation during embryonic development. Further, it provides insights in possibly different requirements for centriole formation between stages of differentiation, as well as differences in in vivo and in vitro models.

We thank the reviewer for finding our work relevant and insightful into the differential requirements for centriole formation depending on the cell type.

The data represented by Grzonka and Bazzi are robust and support the manuscript and conclusions made. However, the study is predominantly descriptive, and the authors do not test the molecular pathway underlying the de novo formation of centrioles observed in SASS6 -/- mESCs. It is generally believed that de novo formation of centrioles is not possible in SASS6 knock-out cells although work from Wang and Tsou with SASS6 a oligomerization mutant suggests otherwise. A dissection of the specific factors required for the de novo formation of centrioles in the mESC context would provide more insights into de novo centriole assembly in general and would increase the impact of this work. I would support publication of the manuscript if the following points are addressed:

We again thank the reviewer for finding the data robust and support our conclusions and interpretation. We agree with the reviewer that our study opens new questions about how mESCs manage to assemble centrioles in the absence of SAS-6. Together with the phenotypes of the Sas-6 mutant D. melanogaster and C. Reinhardtii, and the SAS-6 oligomerization mutants (but not full SAS-6 mutants) in human cell lines mentioned by the reviewer and cited in our manuscript, the data open new investigations into the exact requirements of SAS-6 and the cartwheel in centriole biogenesis in the different cellular contexts.

1. • One of the main figures, ideally Figure 1, should be dedicated to the characterization of the newly generated mouse strains. This should also be elaborated in the text further. I would like to see a schematic representation of the genomic modifications. The SASS6 stainings of wt and Sas-6 knock-outs (now Figure S1F) should be shown in that context as well as the Figures S2A-C. The authors should discuss why there still appears to be SASS6 protein in the SASS6-em5/em5 Sas-6 stainings visible. Also, the western blot, especially the unspecific bands so close to the SAS-6 protein, should be discussed. Adding qRTPCR results would also be good. Per the reviewer’s requests, we will move the embryo mutant characterization (Fig. S1F) and mESCs (Fig. S2A-C) to the main figures and elaborate the text accordingly. The genomic modifications in mice are described in a detailed tabular format in Table 1 in Materials and Methods. The immunofluorescence staining in Fig. S1F was performed on mouse embryonic sections, which tend to have higher backgrounds than cultured cells; Thus, we attribute the very low percentage of SAS-6 staining in Sas-6em5/em5* mutants to higher background, especially given the lack of centrioles in these mutants at all the stages examined.

For Western blots, we used different antibodies against SAS-6 that were either commercially available (Proteintech cat# 21377-1-AP, Sigma-Aldrich cat# HPA028187 and Santa Cruz cat# SC-81431) or non-commercial (kind gift from Renata Basto, Institute Curie). The SAS-6 antibody from the Basto lab gave the most reliable and reproducible results. Using this antibody, and in our own interpretation, we were not able to detect SAS-6 by Western blots in Sas-6 mutant mESCs (including hypomorphic alleles). We concluded that SAS-6 in mESCs (and mouse embryos, see below) is expressed at low levels. Thus, we decided to use the antibody provided by Renata Basto and shown in current Fig. S2C, although it shows two thick non-specific bands flanking the specific band for SAS-6.

For a more definitive knockout in mESCs, we decided to bi-allelically delete the entire Sas-6 ORF DNA from the ATG to the TAA (over 34 Kb of DNA, Fig. S2A). According to the central dogma of molecular biology, when there is no DNA, then there should be no mRNA and no protein. In confirmation of this premise, recent RT-PCR data showed that Sas-6 mRNA is not detectable in these Sas-6-/- null mESCs. Also, immunofluorescence analyses did not detect SAS-6 in these cells. We will add the RT-PCR and immunofluorescence data to the fully revised manuscript. We will also repeat the SAS-6 Western blots to achieve better band resolution.

In addition, we have used the Basto lab antibody for SAS-6 for Western blots on mouse embryos, which detect low levels of SAS-6 in controls and no signal in the mutants.

• The authors could elaborate on the topic of mESCs as a special in vitro model for centriole biology akin to the more "primitive" origins of life such as algae.*

We will elaborate on the topic of mESCs as a special system for centriole biology to stress the findings that mESCs without SAS-6 can still form centrioles, but also that these cells seem to tolerate centriolar aberrations, such as in Sas-6 mutants, or even the loss of centrioles, as in Sas-4 mutants, without undergoing apoptosis or cell cycle arrest.

• Figure 4 should show timeline of embryo development, include embryo stages (E3.5, E9 etc.), group together mESCs with corresponding embryonic developmental stage. The Figure can indicate when mESCs were derived from SASS6 em5/em5 blastocysts, when they were stained and indicate the number/state of centriole formation observed.*

We will adjust the model in Fig. 4 to accommodate the suggestions of the reviewer, but at the same time try not to overcrowd the model and dilute the main findings of the study.

• The work from Wang and Tsou using SAS-6 oligomerization mutants should be better discussed in the context of the work presented here since centriole assembly was not affected per se but structural defects were observed, like is the case in this study.*

We will elaborate on this finding from Wang et al. In this respect, we will note that the loss of the entire SAS-6 protein in human RPE-1 cells (on a p53-mutant background), leads to the loss of centrioles, but that the deletion of the oligomerization domain of SAS-6 in these cells leads to similar phenotypes to the total loss of SAS-6 in mESCs.

• The observation that the ability of forming centrioles de novo in NPCs derived from ESCs is lost is interesting but the mechanisms underpinning this differentiation remain unclear. The authors at a minimum should speculate on these further.*

We agree with the reviewer and will speculate on this finding further. This comment is along the same line as the difference in phenotype between the cells in the developing mouse embryo and mESCs, where the NPCs are more akin to the in vivo phenotype.

CROSS-CONSULTATION COMMENTS

Looks like we are all pretty much in agreement.

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Reviewer #2 (Significance (Required)):

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This is a well executed study with no major flaws that builds on similar studies on knocking out centriole components in mouse and other cell types. Although well-executed the study remains descriptive and lacks a clear mechanistic understanding of why de novo centriole assembly is ineffective in NPCs. As it stands the advances this study provides to the centrosome biogenesis field remain incremental.

We thank the reviewer for the compliments about our work and agree that it opens new questions in the field about the precise roles of SAS-6 and the cartwheel in centriole biogenesis.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

In this publication, Grzonka and Bazzi build upon their recent work describing the role of SAS-like protein function in centriole formation during embryonic development. More specifically, they demonstrate that loss of Sas-6 in vivo and in vitro disrupts centriole formation. To this reviewer's surprise, they found that Sas-6 is required for centriole formation in embryos, yet, stem cells form centrioles with disrupted centriole length and ability to template cilia.

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We thank the reviewer for highlighting the novel and surprising aspect of our work, which is that Sas-6 mutant mESCs are still able to form centrioles. We would like to stress that SAS-4, from our previously published work, and SAS-6, in this study, are not part of the same protein family and have different structures and roles in centriole formation. The naming has its origin in “Spindle-ASsembly abnormal/defective” mutant screens performed in C. elegans. Although the phenotypes are similar in vivo, due the lack of centrioles in both cases, only mutations in Sas-4, but not in Sas-6, lead to the lack of centrioles in mESCs.

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Likely, this occurs from the residual proteins that existed prior to CRISPR-mediated knockout.

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Due to the nature of the surprising finding that Sas-6 mutant mESCs can still form centrioles, we understand the concerns and suggestions of this reviewer and the other reviewers in this regard.

For a more definitive knockout in mESCs, we decided to bi-allelically delete the entire Sas-6 ORF DNA from the ATG to the TAA (over 34 Kb of DNA, Fig. S2A). According to the central dogma of molecular biology, when there is no DNA, then there should be no mRNA and no protein. In confirmation of this premise, recent RT-PCR data showed that Sas-6 mRNA is not detectable in these Sas-6-/- null mESCs. Also, immunofluorescence analyses did not detect SAS-6 in these cells. We will add the RT-PCR and immunofluorescence data to the fully revised manuscript. We will also repeat the SAS-6 Western blots to achieve better band resolution.

These Sas-6-/- mESCs started from a single cell and have been passaged up to 20 times by now without losing centrioles. SAS-6 protein was not detectable at the early passages and the mRNA is still not detectable. This is how knockouts have been and are produced. If this mutant is still not convincing, then we respectfully ask that the reviewers provide their own suggestion on what will be more convincing.

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Unsurprisingly, they found that Sas-6 loss in the developing mouse activates the 53BP1-USP28-p53 surveillance pathway leading to cell death and embryonic arrest at mid-gestation, similar to their findings in Cenpj knockouts. What remains to be properly elucidated is the mechanistic differences in the requirement for Sas-6 in stem cells versus the embryo, which may be beyond the scope of a short report. As it reads, the manuscript is a compliment to their Sas-4 paper but falls short of novelty and providing large strides in revealing the role of centriolar proteins in developmental processes. Moreover, the advances beyond the requirement for centriole and associated proteins in embryology is missing, therefore enthusiasm is tempered. Below are remaining concerns that must be addressed:

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Remaining concerns:

The authors should provide clear description of the embryonic region (neural plate & mesenchym) used to analyze centriole presence or loss in Figures 1 and S1. Was this in the forelimb vs hindlimb regions?

The assessment of centrosomes in Fig. 1 and S1 was performed on cell types in all three germ layers in the sections that were taken from the brachial region (forelimb and heart level). The information will be added to the Materials and Methods section.

Similar to their Cenpj-mouse data, the authors should provide data detailing the mitotic index and activation of the mitotic surveillance pathway beyond just p53 staining. As novelty is not the only criteria for publication, a thorough analysis of the Sas-6 activation of the mitotic purveyance pathway should be provided, including the crosses between Sas-6 and p53, 53bp1 and usp28 knockout crosses to demonstrate the pathway functions similarly to Cenpj loss.

We will perform the additional experiments suggested by the reviewer that are similar to our previous work in Sas-4 mutants (Xiao*, Grzonka* et al, 2021). We will perform these analyses knowing that both Sas-4 and Sas-6 mutants lose centrioles and activate the mitotic surveillance pathway, as the reviewer indicated. In particular, we will quantify the mitotic index in the Sas-6em5/em5 mutants and perform p53 and Cl. CASP3 staining in the double mutants with 53bp1 or Usp28, to show that the pathway has been suppressed in these mutants.

Centriole structure should be assessed in the embryos using EM to assess loss and confirm the structural defects. This would strengthen their argument and be a slight advance to their largely descriptive paper.

Because the Sas-6em5/em5 embryos lack centrioles, as indicated by regular immunofluorescence and Ultrastructure-Expansion Microscopy (U-ExM), using EM would be an attempt to find a structure that does not exist. In our opinion, it would again be a repetition of TEM studies that we have already performed in Sas-4-/- mutant embryos, that lack centrioles (Bazzi and Anderson, 2014). Using U-ExM has advanced the centriole biology field to a level that is approaching EM resolution and, in our opinion, can substitute for EM.

The WB for Sas-6 knockout is not convincing and should be redone. There are validated Sas-6 antibodies available from SCBT and Proteintech. It is not clear that the band is gone or if there's overlap with the non-specific band.

The answer to this comment is shown above. In addition, we have used the Basto lab antibody for SAS-6 for Western blots on mouse embryos, which detect low levels of SAS-6 in controls and no signal in the mutants. We will also repeat the SAS-6 Western blots on mESCs to achieve better band resolution as recommended by the reviewer.

The authors describe the centriolar structural defect in the mESCs in Figure 2C and D, and further characterize the phenotype in S2D-H. Given the role of the SAS6-CEP135-CPAP axis for centriole elongation, it is peculiar that they see elongation upon reduction of CEP135. The authors should find a rationale mechanism to explain their discordant findings. In addition, other centriole distal end components including CEP97 and CP110 should be examined to determine the structural end caping defect in the Sas-6 mESC.

Over 70% of the centrioles in Sas-6-/- mESCs retain CEP135, but the majority of CEP135 signals (over 80%) seem to be abnormally localized. One potential explanation for the elongated centrioles in Sas-6-/- mESCs is that the mis-localization of CEP135 impacts on the integrity of the centriole and results in parts of the centriolar walls being elongated. Per the reviewer’s suggestion, we have performed U-ExM with stainings for CP110 or CEP97, that also regulate centriole capping and elongation. The preliminary data suggest that similar to WT mESCs, they localize to the ends of the abnormal centrioles in Sas-6-/- mESCs. We will quantify the percentage of normally-localized CP110 and CEP97 in Sas-6-/- mESCs and include it along with the data interpretation in the next version of the manuscript.

• *

In Figure 2I, J the authors state the ciliation rate for the WT mESCs was only 11%, could the authors provide an explanation for the low ciliation rate in WT mESCs? Could cells be arrested to increase the ciliation rate? In addition, is there a rational explanation for the loss of centrioles and centrosomes upon differentiation into NPCs?

mESCs ciliation rate has been shown to be generally low (Bangs et al, 2015; Xiao et al., 2021) perhaps because the cells spend most of the cell cycle in the S-phase. mESCs require a high serum percentage and well-defined media for growth and maintenance. In our hands, attempting to arrest the cells by withdrawing serum, or reducing its percentage, resulted in cell death and a change in morphology to the differentiated phenotype (unpublished data). Our data indicate that a pluripotent state in Sas-6-/- mESCs is compatible with centriole formation but differentiation results in the loss of centrioles (for example, NPCs). Therefore, we have refrained from interfering with the cell cycle of mESCs in order to avoid these confounding effects on cellular viability and centriole formation.

Regarding the loss of centrioles upon differentiation of Sas-6-/- mESCs into NPCs, we agree with the reviewer and will speculate on this finding further. This goes along the same line as the difference in phenotype between the cells in the developing mouse embryo and mESCs, where the NPCs are more akin to the in vivo phenotype of Sas-6 mutants. The data suggest that the formation of centrioles in Sas-6-/- mESCs is associated with the in vitro pluripotent phenotype. A more comprehensive and general characterization of centriole duplication in mESCs is a future direction to elucidate their ability to form centrioles without SAS-6.

In figure 3F in the Sas-6−/− NPCs have a box around a cell without centrosomes yet in 3G here are some cells with centrosomes. While the authors are trying to demonstrate the decrease in centrosome in the Sas-6−/− NPCs, they should show the few cell that have centrosomes or centrosome-like structures.

We will add another example for the minority of cells that retain centrosomes upon differentiation of Sas-6-/- mESCs into NPCs.

CROSS-CONSULTATION COMMENTS

• *

As mentioned in my review; while the Sas6 model is new, it does not provide further evidence of why centriole duplication is important in developing mice aside from it causing an abortive mitosis leading to cell death. The discordant phenotype in the mESCs likely arises from residual Sas6, similar to experiments that were performed in flies with Sas-4 depletion. Moreover, the odd centriole phenotype represents a very small number of cells and is likely phenomenological.

In addition, their work from last year demonstrated a clear connection between Cenpj loss leading to the mitotic surveillance pathway activation. They performed double knockouts that partially rescued the survival phenotype. This new work falls short of that publication.

Reviewer #3 (Significance (Required)):

• *

The new publication adds a known component to the list of animal models for centrosome-opathies but fails to provide novel mechanistic insights. Dr. Bazzi's publication on Sas-4 was far more novel at the time of publication due to the multiple mouse crosses that could rescue the phenotypes. The recent publication fails to provide as much evidence or any novel insights into the role of Sas-6 (sufficient to be convincing).

The audience will be limited to centrosome biologists and even then it may not have enough novelty to be compelling. I would recommend with the revisions to be published in a more specialized journal.

*My expertise lies in genetic causes of microcephaly-associated with mutations in centrosome encoding proteins. *

• *

We thank the reviewer for taking the time to evaluate our work and provide helpful comments and suggestions. We would like to emphasize that even if a certain phenotype is expected, the experiment has to be performed to test the hypothesis, which is the case with the Sas-6 mutant embryos phenocopying the Sas-4 mutants. In our opinion, the novelty of our work goes beyond Fig. 1 to the ability of Sas-6-/- null mESCs to form centrioles. This surprising finding opens new avenues of investigation into the precise roles of SAS-6, and the cartwheel, in centriole biogenesis. We are confident that our study will provide a trigger to re-examine these roles in other cell types and organisms.

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Reply to the reviewers

Reviewer #1

SUMMARY

The manuscript by Smoak et al., provides an analysis of the Hyr/Iff-like (Hil) genes in Candida species with a strong focus on C. auris. The authors demonstrate a repeated expansion of these genes in unique lineages of fungal species, many of which are associated with stronger clinical disease. There is evidence of selection operating on the gene family in the primary domain used for identification. These genes include a repeat just downstream of that core domain that changes frequently in copy number and composition. The location of these genes tends to cluster at chromosome ends, which may explain some aspects of their expansion. The study is entirely in silico in nature and does not include experimental data.

MAJOR POINTS

Altogether, many of the general findings could be convincing but there are some aspects of the analysis that need further explanation to ensure they were performed correctly. To start, a single Hil protein from C. auris was used as bait in the query to find all Hil proteins in yeast pathogens. Would you get the same outcome if you started with a different Hil protein? What is the basis for using Hil1 as the starting point? It also doesn't make sense to me to remove species just because there are already related species in the list. This may exclude certain evolutionary trends. Furthermore, it would be helpful to know how using domain presence and the conservation of position changes the abundance of the gene family across species? (beginning of results).

We appreciate the reviewer’s criticisms on our strategy for identifying Hil proteins. In response, we have significantly revised our pipeline. In particular, we now combine the search results from three queries: in addition to C. auris Hil1’s Hyphal_reg_CWP domain (XP_028889033), we added the Hyphal_reg_CWP sequences from C. albicans Hyr1 and C. glabrata Hyr1. They were chosen as representatives in the two phylogenetic groups distinct from the one containing C. auris in order to avoid the bias due to the query’s phylogenetic position. Using the same criteria as we did for the original search, we identified three additional hits compared with the original 104 homologs list. In response to the criticism of the arbitrary exclusion of some species, we now include any species from the BLASTP search results as long as it is part of the 332 yeast species studied by Shen et al. 2018 (PMID: 30415838). The reason for this criterion is so that we can use the high-quality species phylogeny generated by Shen et al. 2018 to properly study the gene family evolution by reconciling the gene tree with the species tree. We additionally include the species in the MDR clade closely related to C. auris and used Muñoz et al. 2018 (PMID: 30559369) as the basis for the species phylogeny in the clade. Lastly, we no longer require the particular domain organization in classifying Hil family members. All BLASTP hits satisfying the E-value cutoff of 1x10-5 and query coverage > 50% are included.

A major challenge in the analysis like this one is in dealing with repetitive sequences present in amplified gene families. For example, testing modes of selection on non-conserved sites is fraught. It's not clear if all sites used for these tests are positionally conserved and this should be clarified. Alignments at repeat edges will need to maintain this conservation and relatively good alignments as stated in lines 241-242 are concerning that this includes sequence that does not retain this structure necessary for making predictions of selection.

We appreciate the reviewer’s comment. In the original manuscript, we performed two different types of analyses, one on the conserved and well-aligned Hyphal_reg_CWP domain and another on the rapidly evolving repeat region. For the former, we performed phylogenetic dN/dS analyses using maximum-likelihood, for which a reliable alignment is crucial and is the case here. The Hyphal_reg_CWP domain alignment for C. auris Hil1-Hil8 is shown below and also included as Fig. S7 in the revised manuscript: (figure in the response file)

In the text, we added this sentence to emphasize this point: “We chose to focus on the Hyphal_reg_CWP domain because of its potential importance in mediating adhesion and also because the high-quality alignment in this domain allowed us to confidently infer the evolutionary rates (Fig. S7).”

For the repeat domain, what we did in the original version was to calculate the pairwise dN/dS between individual repeat units found in Hil1 and Hil2. This didn’t require aligning the entire repeat regions in the two proteins, but instead relied on the alignment of the individual ~44 aa repeat units, which were highly conserved (see below). In the revised manuscript, however, we decided to focus our analyses on the Hyphal_reg_CWP domain because of a different concern, namely gene conversions between paralogs could distort the evolutionary history of the repeats (the same concern was addressed for the effector domain using an additional step of detecting recombination breakpoints, but the same analysis would be challenging for the repeat region due to alignment issues).

(figure in the response file)

It's also unclear to me why Figure S12 is here. The parameters for this analysis should be tested ahead of building models so only one set of parameters should be necessary to run the test. The evolutionary tests within single genes and across strains is really nice!

We appreciate the reviewer’s suggestion. Based on the reviewer’s suggestion, we removed Fig. S12 and describe the model set up in the Materials and Methods section. We were not sure if the last point was a comment or a suggestion. We didn’t perform a population level selective sweep scan in C. auris. Such an analysis has in fact been attempted by Muñoz et al. 2021, who identified several members of the Hil family as the top candidates for positive selection (PMID: 33769478). We cited this in our Discussion:

“Lastly, scans for selective sweep in C. auris identified Hil and Als family members as being among the top 5% of all genes, suggesting that adhesins are targets of natural selection in the recent evolutionary history of this newly emerged pathogen (Muñoz et al. 2021).”

A major challenge for expanded gene families is rooting based on the inability to identify a strong similarity match for the full length sequence. The full alignment mentioned would certainly include significant gaps. If those gaps are removed and conserved sites only are used, does it produce the same tree? Inclusion of unalignable sequences would be expected to significantly alter the outcomes of those analysis and may produce some spurious relationships in reconciling with the species trees. Whether or not there are similar issues in the alignment of PF11765 need to be addressed as well. There's nothing in the methods that clarifies site selection.

We appreciate reviewer’s comment and agree with the concern about alignment quality affecting phylogenetic reconstruction. To clarify, all phylogenetic analyses in this work are based on the alignment of the Hyphal_reg_CWP domain, which is well aligned (shown above for the subset of eight homologs in C. auris). Alignment of all 215 homologs is provided for readers to review (shorturl.at/kDEJ3). To clarify this choice, we now include the following in Results:

“To further characterize the evolutionary history of the Hil family, including among closely related Candida lineages, we reconstructed a species tree-aware maximum likelihood phylogeny for the Hil family based on the Hyphal_reg_CWP domain alignment (Fig. 1C, Fig. S2).”

We also included detailed steps for reconstructing the gene tree in Materials and Methods.

To test the effect of gaps in the alignment on phylogenetic tree inference, we used two trimming programs, ClipKit (PMID: 33264284) and BMGE (PMID: 20626897), with author-recommended modes. They resulted in consistent gene tree results. We present the tree based on the ClipKit trimmed alignment in the main results. The root of the gene tree was inferred by jointly maximizing the likelihood scores for the gene tree based on the alignment and the evolution of the gene family within the species tree, using GeneRax (Morel et al. 2020, PMID: 32502238).

Figure 1A: the placement of evolved pathogenesis is a little arbitrary. It's just as feasible that a single event increased pathogenesis in the LCA of C. albicans and C. parapsilosis that was subsequently lost in L. elongisporus. These should be justified or I'd suggest removing. The assignment of Candida species here also seems incomplete. The Butler paper notes both D. hansineii and C. lusitaniae as Candida species whereas they are excluded here.

We removed Figure 1 entirely based on this and another reviewer’s comment. We note that there is broad consensus that opportunistic yeast pathogens have independently arisen multiple times, such as C. auris, C. albicans and C. glabrata. Whether Candida pathogens that are more closely related evolved separately or not are subjects of ongoing research (PMID: 24034898).

It is tricky to include scaffolds in analysis of chromosomal location of the HIL genes. The break in the scaffold may be due to the assc repeats of these proteins alone or other, nearby repeats. Any statistics would be best done to include only known chromosomes or those that are strongly inferred by Munoz, 2021. This will change the display of Figure 7, but is unlikely to change the take home message.

We agree with the reviewer’s concern. In the revised manuscript and with more species included, we now only analyze genomes assembled to a chromosomal level, with the exception of C. auris B8441, which is supported by Muñoz et al. 2021 as having chromosome-length sequences. The revised Figure 7 now only includes these results. We also removed the accompanying supplementary figure that showed results based on scaffold-level assemblies.

MINOR POINTS

Line 18: "spp." Should be "spps."

Addressed throughout the revised manuscript.

Line 41: I might rephrase this as "how pathogenesis arose in yeast..."

Accepted (line 43 in revised manuscript).

I might use a yeast-centric example around line 40 for duplication and divergence. This could include genes for metabolism of different carbon sources in S. cerevisiae.

Accepted (lines 47-48)

The Butler paper referenced on line 51 compared seven Candida species and 9 Saccharomyces species

Changed (line 48)

The autors state no other evolutionary analysis of adhesins has been performed but do not acknowledge this study: https://academic.oup.com/mbe/article/28/11/3127/1047032

We appreciate the reviewer pointing this important reference to us. We now cite it in the introduction (line 64) and discussion (line 340)

The first paragraph of the Results could be condensed

Addressed.

How was the species tree in Figure 1A obtained?

The previous figure 1 is now removed. The species tree used throughout the manuscript is based on Shen et al. 2018 with MDR clade species added, based on Muñoz et al. 2018.

Figure 2: In panel A, "DH" and "SS" are not defined. I'd be careful with use of "non-albicans Candida" in Figure 2B. This usually includes C. tropicalis and C. dubliniensis and may confuse the reader.

We removed the DH and SS labels. Instead, we highlighted three clades, which were defined in previous studies. These are the Candida/Lodderomyces clade (based on NCBI taxonomy database), the MDR clade (e.g., Muñoz et al. 2018, PMID: 30559369) and the glabrata clade (e.g., Gabaldón et al. 2013, PMID: 24034898).

How was the binding domain defined to extract those sequences are produce a phylogeny? In building a ML model, how were parameters chosen?

We now provide the following details in the Materials and Methods section:

“To infer the evolutionary history of the Hil family, we reconstructed a maximum-likelihood tree based on the alignment of the conserved Hyphal_reg_CWP domain. First, we used hmmscan (HmmerWeb version 2.41.2) to identify the location of the Hyphal_reg_CWP domain in each Hil homolog. We used the “envelope boundaries” to define the domain in each sequence, and then aligned their amino acid sequences using Clustal Omega with the parameter {--iter=5}. We then trimmed the alignment using ClipKit with its default smart-gap trimming mode (Steenwyk et al. 2020). RAxML-NG v1.1.0 was compiled and run on the University of Iowa ARGON server with the following parameters on the alignment: raxml-ng-mpi --all --msa $align --model LG+G --seed 123 --bs-trees autoMRE.”

The parameters for the ML tree reconstruction is listed on the last line above. The main parameter was the evolutionary model (LG+G), which accounts for rate variations using a gamma distribution. Other protein evolution models, e.g., VT+I+G, were tested and resulted in nearly identical tree topologies.

Figure 3C/D could be just one panel.

The structure predictions are now reorganized and presented on their own in the new Figure 3.

Can you relate more the fungal hit to the Hil proteins conveyed in lines 152-154?

We appreciate the reviewer’s comment, which referred to CgAwp1 and CgAwp3, whose effector domain structures were reported in a recent study (Reithofer et al. 2021, PMID: 34962966). We now discuss them in relation to the predicted Hyphal_reg_CWP structure, by showing them in Figure 3 and describing them in the Results (lines 181) “crystal structures for the effector domains of two Adhesin-like Wall Proteins (Awp1 and Awp3b) in C. glabrata, which are distantly related to those in the Hil family were recently reported, and the predicted structure of one of C. glabrata’s Hil family members (Awp2) was found to be highly similar to the two solved structures (Reithofer et al. 2021)”

Line 168: Should read "Hence, ..."

The original sentence was removed, but this grammatical error was checked for and corrected.

Label proteins along the top of Figure 4 too.

Accepted (in new Figure 4).

Figure 5: for tests of selection, were sites conserved across the group? What does the black number at each node indicate? Dn and Ds are given as decimals. This is based on what attribute? For panel B, it is unclear what each tip denotes i.e., Hil1_tr6. Hil1 is the gene but what is "tr6"?

In the revised manuscript, we provide the multiple sequence alignment for the Hyphal_reg_CWP domain used for the selection analysis as Fig. S7 to illustrate the level of conservation. The black numbers at the internal nodes are numeric indices used to refer to those nodes. In the revised manuscript, we use some of them to refer to the internal branches, e.g., 12…14 in the legend. In the new Figure 5, we do not list the numeric values of Dn and Ds (aka Ka, Ks). Instead, we use a color gradient to represent the estimated dN/dS ratios. The raw estimates are available in the project github repository. Panel B in the original Figure 5 and other panels related to the evolution of the repeats are now removed.

It's unclear why comparison of the PF11765 domain includes the MRD proteins when those aren't included in the comparison to the repeats alone. Could that skew the comparison due to unequal sample numbers or changed variation frequencies in MDR relative to the other two groups?

These results pertaining to the evolution of the repeats are now removed.

Table 2 doesn't add much. This section could probably be reduced to a few sentences since it's highly speculative (intraspecies variation).

Table 2 is now Table S5. We also simplified the result section in the revised version. While the functional implications of the intraspecific variable number of tandem repeats (VNTR) is speculative, it is founded on two bases: 1) the identification of the VNTR is credible, as the copy number variation is consistent within clades but differ between clades, which is not expected if they are caused by assembly errors; 2) experimental studies in S. cerevisiae for the Flo family strongly supported a direct impact of adhesin length on the adhesive phenotype of the cells (PMID: 16086015).

Table 3 is not needed.

Table 3 is now removed.

Figure 6 - color coding in 6A needs to be explained. I'm assuming this is a taxonomical coding.

In the revised Figure 6A, the coloring scheme is consistent with what we used in Figure 1 based on the three clades, and a legend is provided.

Figure 1B is unnecessary. A Model of the protein indicating domains is sufficient here. Figure 1C needs labels for all termini, not just the pathogenic red branches. The figure doesn't provide clear association between adhesin families and the associated species. This could be omitted, especially since Flo is often associated with Saccharomyces species. Figure 1D is unnecessary.

We have removed the original Figure 1.

SIGNIFICANCE

The work here is sorely needed in expanded gene families and in fungi specifically. No analysis at this level has been performed, to the best of my knowledge, in any fungal associated gene family and certainly not in relationship to pathogenic potential. The authors do a good job in citing the foundational literature upon which their study builds in most cases (one exception is noted above). It would be of general interest to those interested in the evolution of virulence, but the analysis is tricky. This is the biggest drawback I currently have as some of the information to assess the results is missing.

We really appreciate the reviewer's positive comments. We agree and plan to explore the relationship between the adhesin family evolution and virulence phenotypes.

Expertise: gene families, evolution dynamics, human fungal pathogens

Reviewer #2

SUMMARY

Gene duplication and divergence of adhesin proteins are hypothesized to be linked with the emergence of pathogenic yeasts during evolution; however, evidence supporting this hypothesis is limited. Smoak et al. study the evolutionary history of Hil genes and show that expansion of this gene family is restricted to C. auris and other pathogenic yeasts. They identified eight paralogous Hil proteins in C. auris. All these proteins share characteristic domains of adhesin, and the structural prediction supports that their tertiary structures are adhesin-like. Evolutionary analysis of protein domains finds weak evidence of positive selection in the ligand-binding domain, and the central domain showed rapid changes in repeat copy number. However, performed tests cannot unambiguously distinguish between positive selection and relaxed selection of paralogs after gene duplication. Some alternative tests are suggested that may be able to provide more unambiguous evidence. Together with these additional tests, the detailed phylogenetic analyses of Hil genes in C. auris might be able to better support the hypothesis that the expansion and diversification of adhesin proteins could contribute to the evolution of pathogenicity in yeasts.

We appreciate the reviewer’s comments and will address specific points below.

MAJOR COMMENTS

The authors present extensive analyses on the evolution of Hil genes in C. auris. There is significant merit in these analyses. However, the analyses conducted so far are incomplete, lacking proper consideration of other confounding factors. Detailed explanations of our major comments are listed below.

1. First, the authors restricted genes in the Hil family to those only containing the Hyphal_reg_CWP domain. Yet, previous work included genes containing the ligand-binding domain or the repeat domain as Hil genes. More justification is needed whether the author's choice represents the natural evolutionary history of Hil genes appropriately. For instance, are the genes only containing the ligand-binding domain monophyletic or polyphyletic? We recommend including the phylogeny of all the Hil candidate genes, to discern whether evolutionary histories of the repeat domain and ligand-binding domain are congruent. Authors can use this phylogeny as justification to focus only on the ligand-binding domain containing genes.

Butler et al. 2009 (PMID: 19465905) defined the Als family and the Hyr/Iff family as having either the N-terminal effector domain or the intragenic tandem repeats (ITR). Their rationale for the latter was that the ITS sequences were often conserved across species. Upon close inspection (Fig. S19,20 in that paper), however, we found that the ITS tend to be conserved in closely related species, but diverged among more distantly related species. Moreover, proteins in those figures that only contain the ITS and not the ligand-binding domains are all missing either the signal peptide, the GPI-anchor or both. This raises questions as to whether these proteins sharing the ITS sequence alone act as adhesins.

More generally, defining the evolutionary history of proteins with multiple domains is complicated by recombination, which causes different parts (e.g., domains) of the protein to have distinct evolutionary histories. In fact, our study and others show that there exist “chimeras” that combine the effector domain from one adhesin family and the repeat sequence found in another (Zhao et al. 2011, PMID: 21208290, Oh et al. 2019, PMID: 31105652). In these cases, one phylogenetic tree is insufficient to describe the evolutionary history of the whole protein. We chose to define the Hil family by the Hyphal_reg_CWP domain and thus focus on the evolutionary history of this region because 1) while tandem repeat regions also contribute to adhesion in yeasts (Rauceo et al. 2006, PMID: 16936142), the effector domain likely plays a more important role in ligand binding and specificity. Therefore, we believe using the effector domain to define a protein family is more likely to group proteins with similar functional properties than if the repeat sequences were used. Also, while putative fungal adhesins lacking a recognizable ligand-binding domain exist, they are rare (Lipke 2018, PMID: 29772751); 2) The repeat region evolved much more rapidly than the effector domain, as we illustrate in Figures 2, 4 and 6 in our revised manuscript. While some repeat units are highly conserved, e.g., the ~44 aa unit found in Hil1-4 in C. auris and close relatives in the MDR clade, many others are short and degenerate, making it difficult to reliably identify homologs sharing the repeat. Besides, since each protein could contain many distinct repeats, it is not clear how one defines two sequences as belonging to the same family if they share one out of six types of repeats. We acknowledge that this definition leaves out the evolutionary history defined by the tandem repeats, which may reveal intriguing evolutionary dynamics, with functional implications. A recent review for the Als family discussed similar definition challenges and partly supported our choice (Hoyer and Cota, 2016, PMID: 27014205).

In the analysis of positive selection, the authors do not adequately control for the effect of recombination on the evolutionary histories of protein sequences, especially given that Hil genes are rich in repetitive sequences. To account for recombination, GARD, an algorithm detecting recombination, should be performed to detect any recombination breakpoints within a protein domain. If recombination did occur within a protein domain, the authors should treat the unrecombined part as a single unit and use the phylogenetic information of this part to proceed with PAML analysis, instead of using the phylogeny of the entire protein domain. The authors should consider doing GARD analysis for the ligand-binding and repeat domains. For the repeat domain, low BS values in Fig. 5C indicate recombination between repeat units. Thus, the authors should analyze each repeat unit with GARD and re-analyze dN/dS.

We deeply appreciate the reviewers’ criticism here. In the revised manuscript, we removed the analysis of the repeat units and followed the reviewers’ suggestion to carry out GARD analysis on the effector domain, which we now show reveals evidence of intra-domain recombination. Using the inferred breakpoints (Fig. S8), we identified two putatively non-recombining partitions and performed all downstream phylogenetic analyses on them separately. The results are presented in Fig. 5 and Table S6. Compared with the previous result based on the entire Hyphal_reg_CWP domain alignment, the new results reveal clearer patterns, including significantly elevated dN/dS on a subset of the branches. Newly added branch-site test results support a role of positive selection on the effector domain during the expansion of the Hil family in C. auris, suggesting functional diversification following gene duplications.

The authors concluded positive selection in the ligand-binding domain based on the branch-wise model of PAML. Yet, w values were not higher than one, and it's unclear whether the difference in selective pressures the authors claimed here is biologically significant. Overall, what the authors present so far seems to be weak evidence of positive selection but is much more consistent with variation in the degree of purifying selection or evolutionary constraint. Using the site-wise model (m7 vs. m8) in PAML would allow the authors to detect which residues of the ligand-binding domain underwent recurrent positive selection. Combining the evolutionary information of protein residues and the predicted 3D structure will provide molecular insights into the biological impact of rapidly evolving residues. This would be a significant addition and raise the significance of the study, besides providing potentially stronger evidence of positive selection.

We appreciate the reviewers’ criticism and suggestions. In the revised manuscript, we performed site tests comparing models M2a vs M1a, M8 vs M7 and M8a vs M8. For partition 1 (P1-414), all three tests were insignificant. For partition 2 (P697-987), the M2a vs M1a test was insignificant (P > 0.05) but M8 vs M7 and M8a vs M7a were both significant at a 0.01 level, and the omega estimate for the positively selected category was estimated to be ~15. The site tests require all branches to evolve under the same selection regime. To relax this constraint, we performed additional branch-site tests by designating the branches with an estimated dN/dS > 10 as the foreground (based on the free-ratio model estimates). This test was significant for both branches at a 0.01 level and the Bayes Empirical Bayes (BEB) procedure identified a total of 5 residues as having been under positive selection. Although three of the five residues, located in the C-terminus of the Hyphal_reg_CWP domain, are part of the α-crystallin domain, we refrain from drawing any functional conclusions because 1) the BEB procedure is known to be lacking power in identifying positively selected residues and 2) we still lack structure-function relationship for the α-crystallin domain. But we agree and believe that this line of analysis is promising in yielding functional insight into the evolution of the effector domain in the family.

MINOR COMMENTS

1. In Fig 1c, the figure legend should include more specific details: which adhesin proteins are shown here? Please specify species names on the species tree

Figure 1 is removed in the revised manuscript

In Fig 3E, secondary structures are labeled with the wrong colors. Sheet: purple, helix: yellow

In the revised manuscript, the structures of SRRP-BR (original 3E) is now colored in a single color.

What's the ligand-binding activity of the b-solenoid fold? How structurally similar are C. auris PF 11765 domains compared to C. glabrata Awp domains? This information will support the role of adhesin for the ligand-binding domain of Hil genes.

We discuss the ligand-binding activity of the β-solenoid as follows in Discussion:

“The elongated shape and rigid structure of the β-helix are consistent with the functional requirements of adhesins, including the need to protrude from the cell surface and the capacity for multiple binding sites along its length that facilitate adhesion. In some bacterial adhesins, such as the serine rich repeat protein (SRRP) from the Gram-positive bacterium, L. reuterii, a protruding, flexible loop in the β-helix was proposed to serve as a binding pocket for its ligand (Sequeira et al. 2018). Such a feature is not apparent in the predicted structure of the Hyphal_reg_CWP domain. Further studies are needed to elucidate the potential substrate for this domain and its mechanism of adhesion.”

We also compare the structures of the C. auris Hil1/Hil7 Hyphal_reg_CWP domain and the CgAwp1/3 in Figure 3, with this in the legend “(C) Crystal structure of the C. glabrata Awp1 effector domain, which is highly similar to C. auris Hil1 and Hil7, but with the disulfide bond in a different location.”

We added a section in the Discussion to comment on the structure-function relationship based on known β-helix (aka β-solenoid) structures. The main insight comes from similar structures identified through DALI searches, many of which are bacterial and viral surface proteins mediating adhesion. The ligand binding pocket and specificity would require additional structural studies to elucidate.

In lines 248-249, the authors should also consider the influence of evolutionary history. For instance, repeats within the same Hil protein appeared later in evolution, compared to Hil gene duplication, and therefore these repeats experience less time for sequence divergence.

In the revised manuscript, we removed the analyses pertaining to the evolution of the repeat regions due to multiple challenges including alignment, potential of gene conversion and recombination. This is an important and intriguing aspect of adhesin family evolution that we plan to follow up in future work.

Although the bioinformatic evidence of C. auris Hil genes acting as adhesins is strong, it is still worthwhile to discuss the experiments of confirming the function of adhesins.

We agree with the reviewer and acknowledge in the revised manuscript the limitation of our work:

“Future experimental tests of these hypotheses will be important biologically for improving our understanding of the fungal adhesin repertoire, important biotechnologically for inspiring additional nanomaterials, and important biomedically for advancing the development of C. auris-directed therapeutics.”

SIGNIFICANCE

Overall, this study is interesting to investigate the evolutionary history of a crucial virulent gene in C. auris. Such evolutionary understanding will help us identify critical molecular changes associated with the pathogenicity of an organism during evolution, providing insights into the emergence of pathogens and novel strategies to cure fungal infections. The research question is important; however, the current analyses on the positive selection are incomplete, so the conclusion is modest so far. We recommend that the authors re-do the PAML analysis with the above considerations. This work will bring more significance to the mycology field if the functional impact of rapid evolution in protein domains can be supported or inferred.

This manuscript is well-written, and the authors also did a great job specifying all the necessary details in the M&M.

We appreciate the reviewers’ positive comments.

Reviewer #3

Summary:

The manuscript by Smoak et al. provides considerable information gleaned from analysis of HYR/IFF genes in 19 fungal species. A specific focus is on Candida auris. The main conclusion is that this gene family repeatedly expanded in divergent pathogenic Candida lineages including C. auris. Analyses focus on the sequences encoding the protein's N-terminal domain and tracts of repeated sequences that follow. The authors conclude with the hypothesis that expansion and diversification of adhesin gene families underpin fungal pathogen evolution and that the variation among adhesin-encoding genes affects adhesion and virulence within and between species. The paper is easy to read, includes clear and attractive graphics, as well as a considerable number of supplementary data files that provide thorough documentation of the sources of information and their analysis.

We appreciate the positive comment.

MAJOR COMMENTS:

• Are the key conclusions convincing?

Overall, the authors' conclusions are supported by the information they present. However, the overall conclusion is stated as a hypothesis and that hypothesis is not particularly novel. The idea that expansion of gene families associated with pathogenesis occurs in the pathogenic species dates back at least to Butler et al. 2009, who first presented the genome sequences for many of the species considered here.

We appreciate the reviewer’s comment. Our main conclusions are 1) the Hil family is strongly enriched in distinct clades of pathogenic yeasts after accounting for phylogenetic relatedness. This enrichment results from independent duplications, which is ongoing between closely related species; 2) the protein sequence of the Hil family homologs diverged rapidly following gene duplication, driven largely by the evolution of the tandem repeat content, generating large variation in protein length and β-aggregation potentials; 3) there is strong evidence for varying levels of selective constraint and moderate evidence for positive selection acting on the N-terminal effector domain during the expansion of the family in C. auris as our focal species. Based on these observations, we propose that expansion of adhesin gene families is a key preliminary step towards the emergence of fungal pathogenesis.

Indeed, some version of this hypothesis has been proposed by several groups before us. We fully acknowledged this in our previous as well as the revised manuscript, by citing Butler et al. 2009 (PMID: 19465905), Gabaldón et al. 2013, 2016 (PMID: 24034898, 27493146). Our study built on these earlier efforts and extended them by addressing several limitations. First, we performed phylogenetic regression to test for the association between gene family size and the life history trait (pathogen or not) in order to properly account for the phylogenetic relatedness. This was not done in previous studies. Second, most earlier studies didn’t construct a family-wide gene tree to fully investigate the evolutionary history of the family. Gabaldón et al. 2013 did a phylogenetic analysis for the Epa family and a few others within the Nakaseomycetes, revealing highly dynamic expansions. In the present study, we expanded this effort by comprehensively identifying homologs within the Hil family in all yeasts and beyond. Third and perhaps the most important novelty in our study is our detailed analysis of sequence divergence and role of natural selection during the evolution of the family post duplication. This allowed us to present a complete picture of the family’s evolution, not just in its increase in copy number but also its diversification after the duplications, which is a key part of how gene duplications contribute to the evolution of novel traits. As such, we believe our study provides strong support for the above hypothesis.

One key issue with a manuscript of this type is whether genome sequence data are accurate. The authors are not the first research group to take draft genome sequence data at face value and attempt to draw major conclusions from it. The accuracy of public genome data continues to improve, especially with the emergence of PacBio sequencing. Because the IFF/HYR genes contain long tracts of repeated sequences, genome assemblies from short-read data are frequently inaccurate. For example, is it reasonable to have confidence that the number of copies of a tandemly repeated sequence in a specific ORF is exactly 21 (an example taken from Table 2) when each repeat is 40+ amino acids long and highly conserved? Table S6 would benefit from inclusion of the type of sequence data used to construct each draft genome sequence. It is also reasonable to question whether the genome of the type strain is used as a template to construct the draft genomes of the other strains. If that was standard practice, conservation of the repeat copy number among strains might be an artefact. Conservation of repeat sequences to the degree shown is not a feature of the ALS family, a point of contrast between gene families that could be explored in the Discussion.

We appreciate the reviewer’s comment and agree strongly that a key limitation in gene family evolution studies like ours is the quality of the genome assembly. In the original manuscript, we took several steps to ensure the completeness and accuracy of the Hil family homologs, primarily by basing our results on the high quality RefSeq collection of assemblies, and supplementing it with two fungi-specific databases. In the revised manuscript, we performed further quality analyses to assess and correct for inaccuracy in the BLASTP hits. Because RefSeq aims to provide a stable reference, it is often slow in replacing older assemblies with newer ones based on improved technologies. We thus compared the RefSeq hits for species in which a newer, long-read based assembly had become available. The results are documented in Text S1 and in summary, while we did find examples of missing homologs and inconsistent sequences, the problems were isolated to specific species and the inconsistency pertains only to the tandem repeat regions. Regarding the specific example of within-species variable number of tandem repeats (VNTR) in C. auris Hil1-Hil4, we are confident of both the copy number and the sequence variation for two reasons. First, all C. auris strain genomes analyzed in this study were assembled de novo rather than based on a reference genome, and all were long-read based (PacBio) (Table S4). Second, empirically, we found the VNTR identified in Hil1-Hil4 agree among strains within one of the four clades of C. auris while differing between clades (Table S5). Since assembly errors are not expected to produce clade-specific patterns, we believe this is strong evidence for the VNTR identified being real.

We also appreciate the reviewer’s suggestion on discussing the conservation of the repeats as an interesting trait for a group of Hil proteins in comparison to the Als family. We now added a section in Discussion focusing on the special properties of this group of Hil proteins.

• Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

Due to the nature of my comments, this review will not be anonymous. I will include some of the data from my laboratory to further illustrate the point about the quality of draft genome sequences, especially for gene families that contain repeated sequences. My laboratory group has spent the past several years looking at the families of cell wall genes in these species and know that the C. tropicalis genome sequence used in the current analysis is highly flawed. There is even a manuscript from several years ago that documents problems in the assembly (doi: 10.1534/g3.115.017566). There is a new PacBio sequence available that has considerably improved data for this group of genes, but still is not perfect. We designed primers and amplified the various coding regions to verify whether the IFF/HYR were correct in the draft genome sequences. For C. tropicalis, we know that 7 of the genes listed in this paper are broken (i.e. prematurely terminated) giving a false impression of their construction. The current study did not verify any gene sequences, so broken/incomplete genes are a stumbling block for developing conclusions.

We deeply appreciate the reviewer pointing out the flaws in the C. tropicalis genome. Using the PacBio sequence-based new assembly, we were able to confirm the reviewer’s comment on the sequence and annotation error in the RefSeq assembly for C. tropicalis. We listed the comparisons between the two assemblies in Table S8. Because the differences reside outside of the Hyphal_reg_CWP domain, they don’t impact our phylogenetic analyses, which are based on the effector domain alignment. To determine if this is a widespread issue affecting all genome assemblies based on older technologies, and in response to the reviewer’s criticism, we systematically checked the sequences of BLASTP hits based on the RefSeq assemblies against newer, long-read based ones when available. As detailed in Text S1 in the revised manuscript, the problems seen in C. tropicalis were not observed in four other species. While the sample size is small, we believe the issues with C. tropicalis are likely due to a combination of specific issues with the original assembly and special properties of the genome.

Similarly, the recent work from Cormack's lab features a PacBio C. glabrata sequence (doi: 10.1111/mmi.14707). The paper details how the authors focused on accurate assembly of the types of genes studied here. Sequences from the current project should be compared to the PacBio assembly to determine if they provide the same results.

We compared the sequences of the three C. glabrata Hil homologs identified in the RefSeq assembly (GCF_000002545.3) to the best BLAST hits in one of the new Cormack lab assemblies for (BG2 strain, GCA_014217725.1). Two of the three proteins showed identical sequences between the assemblies. One of them is longer in the new assembly than in the RefSeq (1861 vs 1771 aa, XP_447567.2, QHS67215.1). The main difference, however, was the number of hits recovered. Performing BLASTP searches in the new assembly recovered 13 hits vs 3 from the RefSeq assembly, of which 12 were in the subtelomeric region. For this reason, we used the new assembly as the basis for the Hil homologs in our subsequent analyses. To determine if we missed homologs in other genomes due to incomplete subtelomeric regions in the RefSeq assemblies, we repeated the BLASTP search in four other genomes (Text S1). In one of the four species, C. nivariensis, we recovered one more homolog than in the RefSeq. In all other three, we identified the same number (S. cerevisiae: 0, K. lactis: 1, C. albicans: 12), suggesting that the issues seen in C. glabrata is likely specific to this species and its RefSeq assembly.

Another part of the study that deserves additional attention or perhaps altered presentation is the idea that the Iff/Hyr N-terminal domain binds ligands. The literature on the Iff/Hyr proteins is limited. In my opinion, though, the authors of this paper could more completely present the information that is known. The paper by Uppuluri et al. is cited (doi: 10.1371/journal.ppat.1007056), but I did not see any information about their data regarding interaction of C. albicans Hyr1 with bacterial proteins mentioned in the manuscript under review. It is formally possible that the N-terminal domain of Iff/Hyr proteins does not bind a ligand. The current manuscript includes a great deal of speculation on that point, suiting it better to a Hypothesis and Theory format rather than other types of publications.

We appreciate the reviewer’s criticism and suggestion. We made two revisions based on the comments. First, we no longer refer to the Hyphal_reg_CWP domain as ligand-binding. Instead, we refer to it as the effector domain, following existing practices in the field (Lipke 2018, PMID: 29772751, de Groot et al. 2013, PMID: 23397570). Second, during the description of the predicted structure for the domain, we mentioned that it lacks an apparent binding pocket as suggested/identified in other β-solenoid proteins with carbohydrate binding abilities. Therefore, we suggest that the potential substrate and mechanism of binding by this domain remain to be determined with further experiments. We do, however, believe that there is strong evidence for the domain being involved in adhesion. A recent study (Reithofer et al. 2021) presented structural and phenotypic characterization of three Adhesin wall-like proteins (Awp1,2,3) in C. glabrata. In particular, experimental studies of CgAwp2, a Hil family protein, showed that its deletion resulted in the reversion of the hyperadhesive phenotype in one of the C. glabrata strains. Plastic was one of the substrates being evaluated, although, as the reviewer’s work pointed out, adhesion to plastics doesn’t indicate ligand binding, as it can be mediated by non-specific hydrophobic interactions (Hoyer and Cota 2016, PMID: 27014205). Nonetheless, the results presented in Reithofer et al. 2021 and other lines of evidence presented in the current work strongly supported adhesin functions of the Hil family.

Table 1 attempts to offer evidence that the Iff/Hyr N-terminal domain has adhesive function but falls short of convincing the reader. One of the example structural templates is a sugar pyrophosphorylase that seems irrelevant to the current discussion. In the column called "Function", the word adhesin is found several times, but no detail is presented. The only entry that offers an example ligand indicates that the domain binds cellulose which is not likely relevant for mammalian pathogenesis, the main focus of the work. Other functions listed include self-association and cell aggregation--using the N-terminal domain. It is formally possible that Iff/Hyr proteins drive aggregation using the N-terminal domain and beta-aggregation sequences in the repeated region. The authors should develop these ideas further. Discussion of adhesive/aggregative function related to the ALS family can be found in Hoyer and Cota, 2016 (doi: 10.3389/fmicb.2016.00280).

We appreciate the reviewer’s comments. In the revised manuscript, we removed Table 1, which was based on I-TASSER identified templates. Instead, we identified similar structures in the PDB50 database to the AlphaFold2 prediction for the Hyphal_reg_CWP domain in C. auris Hil1 using DALI (Table S3). We described the functional implications based on this list as follows:

“We identified a number of bacterial adhesins with a highly similar β-helix fold but no α-crystallin domain (Table S3), e.g., Hmw1 from H. influenzae (PDB: 2ODL), Tāpirins from C. hydrothermalis (PDB: 6N2C), TibA from enterotoxigenic E. coli (PDB: 4Q1Q) and SRRP from L. reuteri (PDB: 5NY0). For comparison, the binding region of the Serine Rich Repeat Protein 100-23 (SRRP100-23) from L. reuteri was shown in Fig. 3F (Sequeira et al. 2018). Together, these results strongly suggest that the Hyphal_reg_CWP domain in the C. auris Hil family genes mediate adhesion.”

One line of evidence that suggest the Hyphal_reg_CWP domain may have ligand-binding activity is from the L. reuteri SRRP-BR, which is one of the bacterial adhesins identified as having a highly similar β-helical structure (but missing the α-crystallin domain). In Sequeira et al. 2018 (PMID: 29507249), the authors showed via both in-vitro and in-vivo experiments that this domain “bound to host epithelial cells and DNA at neutral pH and recognized polygalacturonic acid (PGA), rhamnogalacturonan I, or chondroitin sulfate A at acidic pH”. However, the predicted structure for the Hyphal_reg_CWP domain in C. auris Hil1 and Hil7 lack a protruding, flexible loop in the β-helix, which was proposed to serve as a binding pocket for the ligand in SRRP-BR. We therefore commented in the text “Such a feature is not apparent in the predicted structure of the Hyphal_reg_CWP domain. Further studies are needed to elucidate the potential substrate for this domain and its mechanism of adhesion.”

We also appreciate the reviewer’s suggestion to discuss the potential role of the Hil proteins in mediating adhesion vs cell aggregation. We now have a section in Discussion that focuses on the potential role of the β-aggregation sequences especially in the subset of Hil proteins led by C. auris Hil1-Hil4, which have an unusually large number of such sequences. We discuss the recent literature suggesting the potential of such features mediating cell-cell aggregation.

The incredibly large number of figures that focus on the repeated sequences in the genes does not appear to include mention of the idea that these regions are frequently highly glycosylated. Knowing how much carbohydrate is added to these sequences in the mature protein would also have bearing on whether the beta-aggregation potential is realized. The Iff/Hyr proteins could stick to other things based on ligand binding (adhesion), hydrophobicity, aggregative activity, etc. Not much is really known about protein function so the conclusions are only speculative. The authors are largely accurate in presenting their conclusions as speculative, but the conclusions are not developed fully and always land on the idea that the N-terminal domain has adhesive function when that aspect clearly is not known.

We appreciate the reviewer’s comment. We have performed N- and O-glycosylataion predictions for the Hil family proteins in C. auris as a focal example and presented the results in Figure 2 of the revised manuscript. Briefly, we found that all eight proteins are predicted to be heavily O-glycosylated (Fig. 2C). N-glycosylation is rare except in Hil5 and Hil6, in regions with a low Ser/Thr content (Fig. 2C). We also deemphasized the ligand-binding ability of the effector domain and its importance in assessing the adhesin function of the Hil family proteins. At the same time, we highlighted other mechanisms as the reviewer pointed out, such as aggregative activities, in our discussion on the potential importance of the large number of β-aggregation motifs.

Another aspect of the analysis that is not mentioned is that several of the species discussed are diploid. What effect does ploidy have on the conclusions? Most draft genomes for diploid species are presented in a haploid display, so are not completely representative of the species. Additionally, some species such as C. parapsilosis are known to vary between strains in their composition of gene families, with varying numbers of loci in different isolates.

We appreciate the reviewer raising this issue. The potential impact of having diploid genomes represented as haploids is twofold. First, if the genome sequencing was performed on a diploid cell sample with some highly polymorphic regions, that would present difficulties to the assembly and could result in poorly assembled sections. Second, either because of the first issue, or because the researchers used the haploid phase of the organism for sequencing, the representative haploid genome will not be “completely representative of the species” as the reviewer suggested. The second problem is not specific to diploids – even for haploids, any single or collection of genomes would represent just a slice of the genetic diversity in the species. We did two things to look into this. First, we analyzed multiple strains in C. auris to reveal both Hil family size variation and also sequence polymorphism, particularly in the tandem repeat region. We also, as part of the quality control, compared and searched assemblies for different strains of some species when available. We agree that characterizing multiple genomes in a species is important for fully revealing the gene pool diversity and could have important consequences on our understanding of the emergence of novel yeast pathogens.

Regarding the first issue, we checked the original publications for two large-scale yeast genome sequencing projects that included 10 of the 32 species in the present study (Dujon et al. 2004, PMID: 15229592 and Butler et al. 2009, PMID: 19465905). In Dujon et al. 2004, the authors stated that haploid cells were used in cases where the species has both haploid and diploid phases. In Butler et al. 2009, the authors said in the Methods that “for highly polymorphic regions of diploid genomes, initial sequence assemblies were iteratively re-assembled in regions of high polymorphism to minimize read disagreement from the two haplotypes while maximizing coverage.”. Therefore, the potential issue of heterozygosity is likely minimal. In addition, many diploid yeasts have large regions in their genomes being homozygous, both as a result of clonal expansion and also due to loss of heterozygosity (LOH), as documented in C. albicans and other Candida species (e.g., PMID: 28080987). Nonetheless, we acknowledge that this issue is yet another challenge to having high-quality, complete genome assemblies. In the discussion, we fully acknowledge the limitation of our study by genome assemblies, and believe that ongoing improvement thanks to the development of long-read technologies will allow more in-depth studies, particularly in the subtelomeric regions and for repeat-rich sequences.

The manuscript concludes that having more genes is better, that the gene family represents diversification that must be driven by its importance to pathogenesis, without recognizing that some species evolve toward lower pathogenesis. This concept could be explored in the Discussion. …My own experience makes me wonder if the authors found any examples of species that provide an exception to the idea that having more genes is better and positively associated with pathogenesis. The parallel between IFF/HYR and ALS genes is made many times in the manuscript. Spathaspora passalidarum, a species that is not pathogenic in humans, but clearly within the phylogenetic group examined here, has 29 loci with sequence similarity to ALS genes. How many IFF/HYR genes are in S. passalidarum?

We appreciate the reviewer’s comment. We will address the two comments above together as they are related. First of all, S. passalidarum is now included in our extended BLAST search list and we identified a total of 3 homologs in this species. When compared with the related Candida/Lodderomyces clade, which includes C. albicans, the Hil family in this species is relatively small (3 vs. >10). More generally, we observe a significant correlation between the Hil family size and the species’ pathogenic potential (Figure 1B and the phylogenetic regression result in the text).

Regarding the first comment, we did identify two species that had a large Hil family (>8 based on C. auris) and yet were not known to infect humans. One of them, M. bicuspidata, has 29 Hil homologs and is interestingly a parasite for freshwater animals, such as Daphnia. The other species, K. africana, has 10 homologs and its ecology is not well described in the literature. With respect to the relationship between adhesin family and pathogenicity, we would like to make two points. First, as mentioned above, we observed a strong correlation between the Hil family size and the pathogen status, after correcting for phylogenetic relatedness, suggesting that expansion of the Hil family is a shared trait among pathogenic species. This doesn’t rule out the possibility that some species may have an expanded adhesin family, such as the example the reviewer mentioned, for reasons other than infecting a human host. Second, a key point in our work is that expansion of the adhesin family is only the first step – the crucial contribution of gene duplications to adaptation is not just in the increase in copy number, but also in providing the raw materials for selection to generate novel phenotypes. On that front, we documented the rapid divergence of the central domains both between and within species, as well as signatures of relaxed selective constraint and positive selection acting on the effector domain following gene duplications in C. auris, both of which support the above theme.

There are several current taxonomies for the species in this region of the tree. The source of the names used in this paper could be specific more completely.

We appreciate the reviewer’s comment. We now gave the complete Latin names for all species in Figure 1 and only use abbreviated names, e.g., C. auris, after the first occurrence. For species with multiple names in the literature, we followed the species name and phylogenetic placement in Shen et al. 2018 (PMID: 30415838).

The Results and Discussion sections are largely redundant. The tone of the paper is conversational, making it easy to read, but there seems little left to say in the Discussion that has not already been mentioned as the background for the various types of analyses. The authors should revise the paper to eliminate discussions of published literature from the Results and expand the Discussion to include some of the themes that have not been mentioned yet.

We appreciate the reviewer’s comment. In the revised manuscript, we have moved discussion points from the Result to the Discussion section. We also overhauled the Discussion to focus on the implications based on, but not already covered, in the Result part, including the points the reviewer suggested, e.g., the implications of the structure on adhesion mechanism.

Another point that the authors do not mention is documented recombination between IFF and ALS genes (doi: 10.3389/fmicb.2019.00781) and the effect of that process on evolution among these gene families.

We appreciate the reviewer’s comment. We now mention this and related observations in Discussion as part of the discussion on the mutational mechanisms for the evolution of the family:

“Diversification of adhesin repertoire within a strain can arise from a variety of molecular mechanisms. For example, chimeric proteins generated through recombination between Als family members or between an Als protein’s N terminal effector domain and an Hyr/Iff protein’s repeat region have been shown (Butler et al. 2009; Zhao et al. 2011; Oh et al. 2019). Some of the adhesins with highly diverged central domains may have arisen in this manner (Fig. S10).”

My reading of the work by Xu et al. 2021 (doi: 10.1111/mmi.14707) does not match the direction of its presentation in the current paper. Oh et al., 2021 (doi: 10.3389/fcimb.2021.794529) discussed that point recently, providing another point for the Discussion in the current paper.

We appreciate the reviewer’s comment and agree that our original reading of Xu et al. 2021 was incorrect. Instead of suggesting a higher mutation rates in the subtelomeric region, the authors instead suggested the evolution of the Epa family in the subtelomere was driven by Break-Induced Replication. We now update our discussion in the following way, also citing Oh et al. 2021

“Finally, as reported by (Muñoz et al. 2021), we found that the Hil family genes are preferentially located near chromosomal ends in C. auris and also in other species examined (Fig 7), similar to previous findings for the Flo and Epa families (Teunissen and Steensma 1995; De Las Peñas et al. 2003; Xu et al. 2020; Xu et al. 2021) as well as the Als genes in certain species (Oh et al. 2021). This location bias of the Hil and other adhesin families is likely a key mechanism for their dynamic expansion and sequence evolution, either via ectopic recombination (Anderson et al. 2015) or by Break-Induced Replication (Bosco and Haber 1998; Sakofsky and Malkova 2017; Xu et al. 2021). Another potential consequence of the subtelomeric location of Hil family members is that the genes may be subject to epigenetic silencing, which can be derepressed in response to stress (Ai et al. 2002). Such epigenetic regulation of the adhesin genes was found to generate cell surface heterogeneity in S. cerevisiae (Halme et al. 2004) and leads to hyperadherent phenotypes in C. glabrata (Castaño et al. 2005).”

I might have missed it, but I could not find what constitutes a BLAST-excluded sequence (Table S7). Additional explanation (or making the explanation easier to find) would help the reader.

We apologize for the inadvertent mistake of leaving out Table S7. In the revised manuscript, we include all hits from species that are part of the 322 species phylogeny in Shen et al. 2018. Thus, we removed the original Table S7.

• Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.

• Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Ideally, validation of all sequences would provide a stronger foundation for the work. However, that request is not realistic in terms of time or resources.

We agree with the reviewer and appreciate the understanding. In the revised manuscript, we performed additional analyses to evaluate the accuracy and correct the sequences of the BLASTP hits from RefSeq database by comparing them to long-read based assemblies when possible. Please see previous replies to reviewers’ comments and Text S1 for details.

• Are the data and the methods presented in such a way that they can be reproduced?

Yes, the data and methods are documented clearly and perhaps too thoroughly in many places. A considerable amount of confidence is placed in sequences that might not be accurate and tracking details down to the amino acid residue may not be reasonable in this context. A disclaimer might help--everyone probably already knows that genome sequences are not perfect but stating that the analysis is only as good as the genome sequence acknowledges that fact.

We appreciate the reviewer’s comment. In the revised manuscript, we tried to strike a balance between providing enough methodological details for the readers to assess the conclusions and yet also keeping the flow of the paper. We also accepted the reviewer’s suggestion by adding a disclaimer in the Discussion:

“we acknowledge the possibility of missing homologs in some species and having inaccurate sequences in the tandem-repeat region. We believe the expected improvements in genome assemblies due to advances in long-read sequencing technologies will be crucial for future studies of the adhesin gene family in yeasts.”

• Are the experiments adequately replicated and statistical analysis adequate?

The idea of replicates does not really apply to this analysis. I think that the species sampled are reasonable to represent the region of the phylogenetic tree on which the analysis is focused. The authors clearly documented their computational methods in an admirable way.

We appreciate the reviewer’s comment.

MINOR COMMENTS:

Figure 1 has elements that would make a nice graphical summary, but most of it should not be part of the final manuscript. For example, Panel A is repeated in Figure 2. It is not clear what Panel C means until the reader gets to Figure 2. Panel D is unnecessary. The image in Panel B is a good graphic. Endothelial adhesion is not mentioned, though. It is also debatable whether the proteins bind directly to plastic or to the body fluids that coat the plastic.

Based on this and another reviewer’s comments, we removed Figure 1 from the revised manuscript.

Compared to Figure 1, the information in Figure 3 is inconsistent. The "central domain" in Panel A is not central to anything as drawn, located at the end of the protein. The figure should be revised to be consistent with the majority of the authors' results.

We appreciate the reviewer’s suggestion. The terminologies used to describe the different parts of a typical yeast adhesin vary in the literature. In the Als family literature, central domain refers to the region after the N-terminal effector domain and before the C-terminal Ser/Thr-rich stalk domain. In the Hil family proteins, there is not a clear distinction between a “central” and a “stalk” region. In Boisramé et al. 2011 (PMID: 21841123), the authors referred to the region between the Hyphal_reg_CWP domain and the GPI-anchor as the central domain. We adopted that use. We realize that this can lead to confusion especially for Als researchers. In some other literature, e.g., Reithofer et al. 2021, this part of the protein is referred to as the B-region. But we couldn’t find wide use of that term. We decided to stay with “central domain” in this work and hope that by defining the term in Figure 2A, we would avoid any confusion within the scope of this work.

Are the low-complexity repeats mentioned in the Figure 4 legend present anywhere else in the C. auris genome or elsewhere among the species used in this study? The answer to that question may also provide evolutionary clues.

We did find one other putative GPI-anchored cell wall protein containing this ~44aa repeat unit, but with a different effector domain (GLEYA, PF10528). This protein (PIS58185.1 in C. auris B8441), appears to be a hybrid between the repeat region of C. auris Hil1 and an N-terminal effector domain of a different family. This result fits the theme of the reviewer’s work in C. albicans and C. tropicalis on the chimeric adhesins formed between the Als and Hyr/Iff families. Due to the scope of the current work, we omitted this finding from the main result.

Figure S1 legend. How was the distance to C. glabrata measured to call it equal?

The original Figure S1 was removed in the revised manuscript. A consistent set of criteria was employed in deciding which BLASTP hits to include as Hil family members.

Figure S4 could be presented better. Both diagonals have the same information. One could be emptied or could alternatively present nucleotide identity.

The original Figure S4 was removed in the revised manuscript.

Italicize the species names in Panel C of Figure S8.

The original Figure S8C is now Figure S9 and we systematically checked to make sure that species Latin names are italicized. Thanks for pointing this out.

Lines 256-257: The paper selectively samples the Iff/Hyr family and does not examine the "entire" family. Please revise.

We appreciate the reviewer’s comment. In the revised manuscript, we no longer selectively sample species. Instead, we only exclude three species that are not part of the 322-yeast species phylogeny in Shen et al. 2018 and Muñoz et al. 2018, namely Diutina rugosa, Kazachstania barnettii and Artibeus jamaicensis. Our extensive BLASTP searches also indicated that the family as defined in this work is specific to the budding yeast subphylum. We therefore believe it is accurate to describe the work as examining the entire Hil family.

• Are prior studies referenced appropriately?

I was disappointed to see that the paper does not reference my laboratory's work at all. When ALS genes are featured so strongly in a report, it seems reasonable to include something we have done over 30+ years. Our most-recent ALS paper (Oh et al., 2021 doi: 10.3389/fcimb.2021.794529) would be a reasonable source for defending the gene numbers used in Figure 2A. Other examples of our work that directly relate to concepts in this paper were mentioned above.

We sincerely apologize for our negligence. We are new to the fungal adhesin field through an accidental finding, and despite our effort to digest the relevant literature, we did unfortunately overlook the extensive work done on the Als family, much of which came from the reviewer’s lab. We have carefully read the papers suggested by the reviewer as well as others, and now have better incorporated prior foundational and insightful work into our result and discussion sections (see previous replies to the reviewer’s comments).

• Are the text and figures clear and accurate?

Suggestions for improvement are incorporated into the comments above.

• Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Please present Methods and Results in the past tense. I still make the same mistake when I try to get my ideas on the page but proofread one more time and ensure the verb tenses are accurate.

We appreciate the reviewer’s comments and have edited the Methods and Results sections accordingly.

SIGNIFICANCE

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

The paper reads as if it is presenting preliminary data for a grant proposal. Perhaps Prof. He's lab wants to seek functional evidence for the role of the Iff/Hyr proteins. The current paper provides an exhaustive background for such a pursuit. As presented, there is little functional data for these proteins, genome sequences are not 100% accurate, but the trends noted are defendable.

We appreciate the reviewer’s comments. We acknowledge that experimental studies will be needed to prove and further establish the functional importance of our findings. However, we believe our gene family evolutionary studies provided important novel insights and serve as an example for adhesin family evolution.

• Place the work in the context of the existing literature (provide references, where appropriate).

The ideas presented here are similar to those pioneered in the Butler et al. Nature paper in 2009 (doi: 10.1038/nature08064). We now have the benefit of more genome sequences so the analysis can encompass more species. C. auris adds a newer focus on part of the phylogenetic tree that was not previously emphasized. The idea of "more is better" is very simplistic, though. Parallel work for the ALS family shows complexity in gene expression levels, suggesting that some adhesins are poised to make a large contribution while others are likely to have a scant presence on the cell surface. Those concepts are not really explored in the current paper, either. See Hoyer and Cota 2016 (doi: 10.3389/fmicb.2016.00280); Oh et al. (doi: 10.3389/fmicb.2020.594531).

We appreciate the reviewer’s comments and have included a discussion about the potential diversity of the duplicated Hil family proteins, in terms of function and their regulation in the Discussion. Also see our response to the first comment of the reviewer regarding the novelty of our hypothesis and the significance of our findings.

• State what audience might be interested in and influenced by the reported findings.

Potential readers would come from the fields of fungal adhesion and pathogenesis, as well as evolutionary biology.

We appreciate the reviewer’s comments.

• Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

I discovered and named the ALS gene family in C. albicans and have spent 30+ years characterizing it. Most recently, my lab has focused on providing an accurate gene census and validated gene sequences for the cell wall "adhesinome" in the pathogenic Candida species. Some families are expanded and some are not. Some proteins appear only in a few species and demonstrate key roles in host-fungus interactions. There are many nuances to interpretation of what these fungi are doing from the standpoint of cell-surface adhesins and we look forward to exploring these ideas across many genomes, using validated gene sequences. We have a tremendous dataset that might make good fuel for a collaboration with Prof. He, given his enthusiasm for this area of study, as well as his outstanding expertise and perspectives on evolutionary analyses.

We sincerely thank the reviewer for the critical analysis of our manuscript and appreciate the many suggestions for improving the manuscript.

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Referee #3

Evidence, reproducibility and clarity

Summary:

The manuscript by Smoak et al. provides considerable information gleaned from analysis of HYR/IFF genes in 19 fungal species. A specific focus is on Candida auris. The main conclusion is that this gene family repeatedly expanded in divergent pathogenic Candida lineages including C. auris. Analyses focus on the sequences encoding the protein's N-terminal domain and tracts of repeated sequences that follow. The authors conclude with the hypothesis that expansion and diversification of adhesin gene families underpin fungal pathogen evolution and that the variation among adhesin-encoding genes affects adhesion and virulence within and between species. The paper is easy to read, includes clear and attractive graphics, as well as a considerable number of supplementary data files that provide thorough documentation of the sources of information and their analysis.

Major comments:

• Are the key conclusions convincing?

Overall, the authors' conclusions are supported by the information they present. However, the overall conclusion is stated as a hypothesis and that hypothesis is not particularly novel. The idea that expansion of gene families associated with pathogenesis occurs in the pathogenic species dates back at least to Butler et al. (2009; doi: 10.1038/nature08064) who first presented the genome sequences for many of the species considered here.

One key issue with a manuscript of this type is whether genome sequence data are accurate. The authors are not the first research group to take draft genome sequence data at face value and attempt to draw major conclusions from it. The accuracy of public genome data continues to improve, especially with the emergence of PacBio sequencing. Because the IFF/HYR genes contain long tracts of repeated sequences, genome assemblies from short-read data are frequently inaccurate. For example, is it reasonable to have confidence that the number of copies of a tandemly repeated sequence in a specific ORF is exactly 21 (an example taken from Table 2) when each repeat is 40+ amino acids long and highly conserved? Table S6 would benefit from inclusion of the type of sequence data used to construct each draft genome sequence. It is also reasonable to question whether the genome of the type strain is used as a template to construct the draft genomes of the other strains. If that was standard practice, conservation of the repeat copy number among strains might be an artefact. Conservation of repeat sequences to the degree shown is not a feature of the ALS family, a point of contrast between gene families that could be explored in the Discussion. - Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

Due to the nature of my comments, this review will not be anonymous. I will include some of the data from my laboratory to further illustrate the point about the quality of draft genome sequences, especially for gene families that contain repeated sequences. My laboratory group has spent the past several years looking at the families of cell wall genes in these species and know that the C. tropicalis genome sequence used in the current analysis is highly flawed. There is even a manuscript from several years ago that documents problems in the assembly (doi: 10.1534/g3.115.017566). There is a new PacBio sequence available that has considerably improved data for this group of genes, but still is not perfect. We designed primers and amplified the various coding regions to verify whether the IFF/HYR were correct in the draft genome sequences. For C. tropicalis, we know that 7 of the genes listed in this paper are broken (i.e. prematurely terminated) giving a false impression of their construction. The current study did not verify any gene sequences, so broken/incomplete genes are a stumbling block for developing conclusions.

Similarly, the recent work from Cormack's lab features a PacBio C. glabrata sequence (doi: 10.1111/mmi.14707). The paper details how the authors focused on accurate assembly of the types of genes studied here. Sequences from the current project should be compared to the PacBio assembly to determine if they provide the same results.

Another part of the study that deserves additional attention or perhaps altered presentation is the idea that the Iff/Hyr N-terminal domain binds ligands. The literature on the Iff/Hyr proteins is limited. In my opinion, though, the authors of this paper could more completely present the information that is known. The paper by Uppuluri et al. is cited (doi: 10.1371/journal.ppat.1007056), but I did not see any information about their data regarding interaction of C. albicans Hyr1 with bacterial proteins mentioned in the manuscript under review. It is formally possible that the N-terminal domain of Iff/Hyr proteins does not bind a ligand. The current manuscript includes a great deal of speculation on that point, suiting it better to a Hypothesis and Theory format rather than other types of publications.

Table 1 attempts to offer evidence that the Iff/Hyr N-terminal domain has adhesive function but falls short of convincing the reader. One of the example structural templates is a sugar pyrophosphorylase that seems irrelevant to the current discussion. In the column called "Function", the word adhesin is found several times, but no detail is presented. The only entry that offers an example ligand indicates that the domain binds cellulose which is not likely relevant for mammalian pathogenesis, the main focus of the work. Other functions listed include self-association and cell aggregation--using the N-terminal domain. It is formally possible that Iff/Hyr proteins drive aggregation using the N-terminal domain and beta-aggregation sequences in the repeated region. The authors should develop these ideas further. Discussion of adhesive/aggregative function related to the ALS family can be found in Hoyer and Cota, 2016 (doi: 10.3389/fmicb.2016.00280).

The incredibly large number of figures that focus on the repeated sequences in the genes does not appear to include mention of the idea that these regions are frequently highly glycosylated. Knowing how much carbohydrate is added to these sequences in the mature protein would also have bearing on whether the beta-aggregation potential is realized. The Iff/Hyr proteins could stick to other things based on ligand binding (adhesion), hydrophobicity, aggregative activity, etc. Not much is really known about protein function so the conclusions are only speculative. The authors are largely accurate in presenting their conclusions as speculative, but the conclusions are not developed fully and always land on the idea that the N-terminal domain has adhesive function when that aspect clearly is not known.

Another aspect of the analysis that is not mentioned is that several of the species discussed are diploid. What effect does ploidy have on the conclusions? Most draft genomes for diploid species are presented in a haploid display, so are not completely representative of the species. Additionally, some species such as C. parapsilosis are known to vary between strains in their composition of gene families, with varying numbers of loci in different isolates.

The manuscript concludes that having more genes is better, that the gene family represents diversification that must be driven by its importance to pathogenesis, without recognizing that some species evolve toward lower pathogenesis. This concept could be explored in the Discussion.

The Results and Discussion sections are largely redundant. The tone of the paper is conversational, making it easy to read, but there seems little left to say in the Discussion that has not already been mentioned as the background for the various types of analyses. The authors should revise the paper to eliminate discussions of published literature from the Results and expand the Discussion to include some of the themes that have not been mentioned yet.

My own experience makes me wonder if the authors found any examples of species that provide and exception to the idea that having more genes is better and positively associated with pathogenesis. The parallel between IFF/HYR and ALS genes is made many times in the manuscript. Spathaspora passalidarum, a species that is not pathogenic in humans, but clearly within the phylogenetic group examined here, has 29 loci with sequence similarity to ALS genes. How many IFF/HYR genes are in S. passalidarum?

There are several current taxonomies for the species in this region of the tree. The source of the names used in this paper could be specific more completely.

Another point that the authors do not mention is documented recombination between IFF and ALS genes (doi: 10.3389/fmicb.2019.00781) and the effect of that process on evolution among these gene families.

My reading of the work by Xu et al. 2021 (doi: 10.1111/mmi.14707) does not match the direction of its presentation in the current paper. Oh et al., 2021 (doi: 10.3389/fcimb.2021.794529) discussed that point recently, providing another point for the Discussion in the current paper.

I might have missed it, but I could not find what constitutes a BLAST-excluded sequence (Table S7). Additional explanation (or making the explanation easier to find) would help the reader. - Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. - Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

Ideally, validation of all sequences would provide a stronger foundation for the work. However, that request is not realistic in terms of time or resources. - Are the data and the methods presented in such a way that they can be reproduced?

Yes, the data and methods are documented clearly and perhaps too thoroughly in many places. A considerable amount of confidence is placed in sequences that might not be accurate and tracking details down to the amino acid residue may not be reasonable in this context. A disclaimer might help--everyone probably already knows that genome sequences are not perfect but stating that the analysis is only as good as the genome sequence acknowledges that fact. - Are the experiments adequately replicated and statistical analysis adequate?

The idea of replicates does not really apply to this analysis. I think that the species sampled are reasonable to represent the region of the phylogenetic tree on which the analysis is focused. The authors clearly documented their computational methods in an admirable way.

Minor comments:

• Specific experimental issues that are easily addressable.

Figure 1 has elements that would make a nice graphical summary, but most of it should not be part of the final manuscript. For example, Panel A is repeated in Figure 2. It is not clear what Panel C means until the reader gets to Figure 2. Panel D is unnecessary. The image in Panel B is a good graphic. Endothelial adhesion is not mentioned, though. It is also debatable whether the proteins bind directly to plastic or to the body fluids that coat the plastic.

Compared to Figure 1, the information in Figure 3 is inconsistent. The "central domain" in Panel A is not central to anything as drawn, located at the end of the protein. The figure should be revised to be consistent with the majority of the authors' results. Structures in Panels C to E would benefit from the "through the spiral" view that is featured in Figure S9. What experimental technique was used to solve the structure in Panel E? Adding that information to the legend would be helpful to the reader. Also, the secondary structure colors seem to be reversed between the legend and domain structure. Adding the coordinates of the domains shown would help the reader to understand their location in the mature protein.

Are the low-complexity repeats mentioned in the Figure 4 legend present anywhere else in the C. auris genome or elsewhere among the species used in this study? The answer to that question may also provide evolutionary clues.

Figure S1 legend. How was the distance to C. glabrata measured to call it equal?

Figure S4 could be presented better. Both diagonals have the same information. One could be emptied or could alternatively present nucleotide identity.

Italicize the species names in Panel C of Figure S8.

Lines 256-257: The paper selectively samples the Iff/Hyr family and does not examine the "entire" family. Please revise. - Are prior studies referenced appropriately?

I was disappointed to see that the paper does not reference my laboratory's work at all. When ALS genes are featured so strongly in a report, it seems reasonable to include something we have done over 30+ years. Our most-recent ALS paper (Oh et al., 2021 doi: 10.3389/fcimb.2021.794529) would be a reasonable source for defending the gene numbers used in Figure 2A. Other examples of our work that directly relate to concepts in this paper were mentioned above. - Are the text and figures clear and accurate?

Suggestions for improvement are incorporated into the comments above. - Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

Please present Methods and Results in the past tense. I still make the same mistake when I try to get my ideas on the page but proofread one more time and ensure the verb tenses are accurate.

Significance

• Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field.

The paper reads as if it is presenting preliminary data for a grant proposal. Perhaps Prof. He's lab wants to seek functional evidence for the role of the Iff/Hyr proteins. The current paper provides an exhaustive background for such a pursuit. As presented, there is little functional data for these proteins, genome sequences are not 100% accurate, but the trends noted are defendable. - Place the work in the context of the existing literature (provide references, where appropriate).

The ideas presented here are similar to those pioneered in the Butler et al. Nature paper in 2009 (doi: 10.1038/nature08064). We now have the benefit of more genome sequences so the analysis can encompass more species. C. auris adds a newer focus on part of the phylogenetic tree that was not previously emphasized. The idea of "more is better" is very simplistic, though. Parallel work for the ALS family shows complexity in gene expression levels, suggesting that some adhesins are poised to make a large contribution while others are likely to have a scant presence on the cell surface. Those concepts are not really explored in the current paper, either. See Hoyer and Cota 2016 (doi: 10.3389/fmicb.2016.00280); Oh et al. (doi: 10.3389/fmicb.2020.594531). - State what audience might be interested in and influenced by the reported findings.

Potential readers would come from the fields of fungal adhesion and pathogenesis, as well as evolutionary biology. - Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

I discovered and named the ALS gene family in C. albicans and have spent 30+ years characterizing it. Most recently, my lab has focused on providing an accurate gene census and validated gene sequences for the cell wall "adhesinome" in the pathogenic Candida species. Some families are expanded and some are not. Some proteins appear only in a few species and demonstrate key roles in host-fungus interactions. There are many nuances to interpretation of what these fungi are doing from the standpoint of cell-surface adhesins and we look forward to exploring these ideas across many genomes, using validated gene sequences. We have a tremendous dataset that might make good fuel for a collaboration with Prof. He, given his enthusiasm for this area of study, as well as his outstanding expertise and perspectives on evolutionary analyses.

The other day, I was having an interesting discussion with Buddhist philosopher working on sanskrit. We were discussing perhaps it is the grammatical structure that lead us to think in a certain way. That the languagenand its grammatical structure may already guiding our way of thinking. Sor the argument was on White Cow, is the whiteness posessing the cow, or the cow posessing the whiteness. The scholars were arguing that it could be translated in both ways, that gives us a kind of vague different understanding of what is being described.

Reviewer #1 (Public Review):

The core question addressed by this study is whether right IFC damage disrupts stop-signal task performance because it plays a key role in response inhibition per se, or because it is crucial for attending to the need to engage response inhibition. A relatively large sample of patients with damage including right IFC, as well as lesioned and healthy control groups, were assessed on the stop-signal task accompanied by scalp EEG. The behavioral data were analyzed using hierarchical Bayesian modeling. Right IFC damage was associated with more trials where 'stopping' was not initiated, while an EEG hallmark of inhibitory control was present in trials where stopping initiation did occur, arguing that rIFG damage disrupts attention to the stop signal, rather than the inhibition that follows.

This is an interesting study testing a well-defined hypothesis relevant to competing views of the brain basis of inhibitory control. The experimental design is sophisticated and the analysis was preregistered. The acquisition of both behavioral and EEG data in lesion patients provides converging evidence and supports causal inference.

Interpretation of the results hinges on accepting that a hierarchical Bayesian model is appropriate for discriminating trials where stopping was 'triggered' from trials where there was no trigger. Likewise, we need to accept the EEG frontal beta burst pattern is an indicator of response inhibition. Both of these methodological elements have support from existing literature, although I don't think either of these has been applied in chronic focal lesion patients, so there may be technical issues to consider in their interpretation. Finally, as with most human lesion studies, caution should be applied in interpreting the critical lesion location: in this sample, the effects might relate to insula damage, or to white matter disruption within the ventrolateral/lateral frontal lobe or between those regions and subcortical regions. However, these provisos do not detract from the key finding that damage somewhere in these areas affected initiation/attentional processes rather than response control per se.

The results are more consistent with an attentional account of right IFG (or more broadly, right ventral frontal lobe) contributions to stop-signal task performance; this is provocative in light of current views of prefrontal contributions to inhibitory control, although in line with a wider literature implicating right frontoparietal circuitry in selective attention. As the authors suggest, a sharp distinction between attention and inhibition may be somewhat artificial: these processes may be closely interrelated in speeded tasks requiring response interruption. However, the present study cleverly tackles the challenge of disentangling them, applying recent modeling and EEG distinctions with interesting results.

The findings are helpful in further sharpening ideas regarding the neural basis of response control. They also have potential theoretical implications and perhaps direct experimental application in clinical-applied research on disorders of inhibitory control.

Author Response

Reviewer #1 (Public Review):

The stated goal of this research was to look for interactions between metabolism, (manipulated by glucose starvation) and the circadian clock. This is a hot topic currently, as bi-directional links between metabolism and rhythmicity are found in several organisms and this connection has important implications for human health. The authors work with the model organism Neurospora crassa, a filamentous fungus that has many advantages for this type of research.

The authors' first approach was to assay the effects of glucose starvation on the levels of the RNA and protein products of the key clock genes frq, wc-1, and wc-2. The WC-1 and WC-2 proteins form a complex, WCC, that activates frq transcription. The surprising finding was that WC-1 and WC-2 protein levels and WCC transcriptional activity were drastically reduced but frq RNA and protein levels remained the same. Under conditions where rhythmicity is expressed, the rhythms of frq RNA, FRQ protein, and expression of clock-driven "output" genes were also unaffected by starvation. The standard model for the molecular clock is a transcription/translation feedback loop dependent on the levels and activity of these clock gene products, so this disconnect between the starvation-induced changes in the stoichiometry of the loop components and the lack of effects of starvation on rhythmicity calls into question our understanding of the molecular mechanism of the clock. This is yet another example of the inadequacy of the TTFL model to explain rhythmicity. For me, the most significant sentence in the paper was this: "...an unknown mechanism must recalibrate the central clockwork to keep frq transcript levels and oscillation glucose-compensated despite the decline in WCC levels."

The author's second approach was to try to identify mechanisms for the response to starvation by focussing on frq and its regulators, using mutations in the frq gene and strains with alterations in the activity of kinases and phosphatases known to modify FRQ protein. The finding that all of these manipulations have some effect on the starvation-induced changes in WC protein level is taken by the authors to indicate a role for FRQ itself in the response to starvation. This conclusion is subject to the caveat that manipulations of the activity of multifunctional kinases and phosphatases will certainly have pleiotropic effects on many cellular processes beyond FRQ protein activity.

Because of the sometimes-speculative nature of our conclusions and based on the suggestion of the editor, we restructured the Discussion and discuss now the mechanism addressed by the Reviewer in the subsection "Ideas and Speculation". We added a sentence to the section about the possible pleiotropic effects of the tested signaling pathways: "Starvation triggers characteristic changes in the activity of signaling routes that affect basic components of the circadian clock. Although the multifunctional pathways might act via pleiotropic mechanisms as well, based on their earlier characterized role in the control of the Neurospora clock, their action can be inserted into a model describing the glucose-dependent reorganization of the oscillator."

The third section of the paper is a major transcriptomic study of the effects of starvation on global gene expression. Two strains are compared under two conditions: wc wild-type and the wc-1 knockout strain, under fed and starved conditions. The hypothesis is that WCC has a role in the starvation response. The results of starvation on the wild-type are unsurprising and predictable: the expression of many genes involved in metabolic processes is affected. There are no new insights that come from these results and no new testable hypotheses are generated by the data.

We agree with the reviewer that it is not surprising that glucose depletion strongly affects genes involved in metabolic processes and monosaccharide transport. These data obtained in wt served rather as a control for our experimental conditions. As a new aspect, our analysis focused on the differences between wt and wc-1 in the transcriptomic response to altered glucose availability.

The authors refer to the wc-1 mutant strain as "clockless" and discuss its effects on the transcriptome only in terms of WC-1's function in the clock mechanism. However, WCC is known to be a major transcriptional regulator, controlling a number of genes beyond the TTFL. As acknowledged earlier in the paper, WC-1 is also the major light receptor in Neurospora. The transcriptomics experiments were carried out in a light/dark cycle, with cultures harvested at the end of the light period, when "an adapted state for light-dependent genes can be expected" according to the authors. However, wc-1 mutants are essentially blind, and so those samples are equivalent to being harvested in the dark. The multifunctional nature of WCC complicates the interpretation of the transcriptomics data. The differences in the transcriptome between wild-type and wc-1 may not be due to loss of clock function, but rather the loss of a major multifunctional transcription factor, or the difference between light and "dark".

The reviewer is right, when we discussed the difference between wt and wc-1 in the transcriptional response to glucose, we did not emphasize the possible contribution of the photoreceptor function of the WCC. We added the following sentence to the revised version of the discussion: "Further investigations could differentiate between the clock and photoreceptor functions of the WCC in the glucose-dependent control of the transcriptome." Furthermore, we more specifically indicate that in wc-1 the lack of the WCC (and not the lack of a functional clock) results in the altered transcriptomic response to starvation when compared to wt (P15 L14-17).

In the final set of experiments, the authors tested the hypothesis that the changes in the transcriptome between wild type and wc-1 might make wc-1 less competent to recover growth after starvation. They also test the recovery of frq9, a "clockless" mutant. The very surprising result is that the growth rates of these two mutants are slower than the wild type after transfer from starvation media to high glucose. This is surprising because there will be several generations of nuclear division and doublings of mass within a few hours and the transcriptome should have recovered fully fairly rapidly. A mechanism for this apparent "after-effect" is suggested with evidence concerning differences in expression of a glucose transporter, but it is not clear why this expression should not change rapidly with re-feeding on high glucose. As with previous experiments, the cultures were grown in light/dark cycles, which results in different conditions for the mutants, both of which have very low or absent WC-1 and are therefore blind to light. The potential effects of light have been disregarded.

The reviewer is right that several generations of nuclear divisions occur within a few hours and lead to a number of doublings of the biomass. However, when the first phase of regeneration is delayed in one or more strains compared to the control, until the stationary phase a substantial difference in the biomass can be expected.

To the expression change of the glucose transporter: In order to emphasize the different tendency of how glt-1 levels respond to glucose in the different strains, in the previous version of the manuscript we normalized the expression levels to the beginning of recovery (time point of glucose addition). Thus, expression differences between the strains were not shown. To give a more comprehensive picture, in the revised version of the manuscript expression levels without normalization are depicted (Fig 5F). The mutants did not adapt efficiently to changes in the glucose levels, i.e. expression of the transporter was relatively high in both wc-1 and frq10 during starvation and did not further increase upon glucose addition. On the other hand, 24 hours after glucose resupply, glt-1 levels were similar in all strains which might contribute to the similar growth rates observed under steady-state conditions in the standard medium.

To the photoreceptor-independent function of the WCC during growth recovery: In the revised version of the manuscript we present additional data suggesting the importance of the photoreceptor-independent function of the WCC for efficient recovery from starvation. Fig. 5C and Fig. 5D show now that upon resupply of glucose, wt grows faster than the clock-deficient strains Δwc-1 and frq10 in both LD cycles and constant darkness, indicating that the role of the WCC in growth regeneration is at least partially independent of its photoreceptor function. To the function of the WCC in frq10: frq10 can not be considered blind. Although both Δwc-1 and frq10 lack a functional clock and WC levels are reduced in frq10, these strains show significant differences in WCC activity. While Δwc-1 is considered blind, in frq10 lack of the negative feedback results in high activity of the WCC in both DD and LL and expression levels of all examined, light-sensitive or light-dependent genes were found comparable in wt and in frq-less mutants (Schafmeier et al., 2005; Hunt et al., 2007; own unpublished data).

The title of the paper refers to a "flexible circadian clock" but this concept of flexibility is not developed in the paper. I would substitute "the White Collar Complex" for this phrase: "Adaptation to starvation requires a functional White Collar Complex in Neurospora crassa" would be more accurate. Some experiments are also conducted using an frq null "clockless" strain, but because WC expression is very low in frq null mutants, any effects of frq null could also be attributed to WC depletion.

As detailed above, low level of the WCC in the frq-less mutant does not mean low transcriptional activity and accordingly, the two clock mutants, wc-1 and frq10 show important functional differences. We used the word "flexible" to indicate that the molecular clock is able to operate under critical nutrient conditions and with a significantly changed stoichiometry of its key components. Results of our new experiments performed in DD (mentioned above) indicate that growth regeneration is rather independent of the photoreceptor function of the WCC. Nevertheless, we accepted the criticism of the reviewer and changed the title to "Adaptation to glucose starvation is associated with molecular reorganization of the circadian clock in Neurospora crassa".

The major conclusion I took away from this paper is the multifunctional nature of the WCC as a transcription factor complex. It has been known for a long time that WCC controls the expression of many genes beyond the frq gene at the core of the circadian transcription/translation feedback loop. WC-1 is also the major blue light photoreceptor in Neurospora, controlling the expression of light-regulated genes, and this fact is barely touched on in the paper. These new data now extend the role of WCC in the regulation of metabolic networks as well.

Reviewer #2 (Public Review):

The authors have performed an interesting study addressing a topical question in considering how circadian oscillators remain accurate in changing environmental conditions and these circadian oscillators contribute to responses to environmental changes. The authors have performed their studies in Neurospora crassa. The authors have made a very interesting finding that starvation causes a profound decrease in white collar 1 WC-1 abundance, yet the circadian system continues to run despite this decrease in the abundance of a core oscillator component. The study of chronic glucose starvation in a Δwc-1 mutant is interesting and provides the opportunity to investigate the role of the WHITE COLLAR COMPLEX (WCC) and the clock system in adaption to starvation.

Strengths:

The authors have used a range of techniques to measure clock behaviour, including qPCR, phosphorylation, protein abundance, and subcellular localisation studies.

An frq9 mutant was used to test the effects of FRQ on WC1 abundance since WC1 decreased during starvation. This is elegant, though it is not quite clear the logic of this experiment because FRQ did not change abundance during starvation, so why did the author think this experiment was needed?

We regret that the examination of frq9 was not clearly justified in the previous version of the manuscript. It is true that FRQ levels did not change during starvation, only phosphorylation of the protein was affected, i.e. FRQ became more phosphorylated (displayed by an electrophoretic mobility shift on the Western blot (Garceau N, Liu Y, Loros J J, Dunlap J C. Cell. 1997;89:469–476.)) under low glucose conditions. We tested the starvation response in the FRQ-less strain because WCC level changed significantly in wt upon glucose depletion and expression of WC proteins is known to be controlled by FRQ. In the revised version of the manuscript we tried to introduce and explain the experiments performed with frq9 more thoroughly (P7 L22-P8 L14; P16 L21 – P17 L6).

An interesting experiment was performed to test whether CK1a-dependent phosphorylation and inactivation of the WCC are involved in the starvation response. An FRQΔFCD1-2 mutant is used in which FRQ cannot interact with CK1a and therefore CK1a cannot phosphorylate and inactivate WC. This experiment suggested that CK1a is not involved in the response to starvation, again leading to the conclusion that FRQ is not involved in the starvation regulation of WC.

The referee is right, effect of FRQ-bound CK-1a seems to be minor on the adaptation of the molecular clock to starvation, and this is also our conclusion in the manuscript. The major message of this experiment was that FRQ became phosphorylated in response to starvation without stably interacting with CK1a, probably via another mechanism. We agree with the notion that the behavior of WCC levels upon starvation was similar to that in the FRQ-less mutant.

PKA is shown to be involved in the starvation-induced reduction of WC because the starvation-induced reduction in abundances of WC-1 was absent in the mcb strain in which the regulatory subunit of PKA is defective and hence, PKA is constitutively active.

The authors have found an interesting potential link between glucose levels and WCC phosphorylation, they demonstrated that starvation reduces PP2A activity and that in a regulatory mutant of PP2A, which has reduced PP2A activity, there is little effect of starvation on WCC levels, suggesting the hypothesis that glucose-dependent PP2A dephosphorylation stabilises WCC.

Analysis of starvation-regulated transcriptome in Δwc-1 and wild type found strong evidence that the transcriptomic response to starvation is in part dependent on WCC. Much of the misregulated transcriptome appears to be associated with metabolism.

In a series of growth studies in wild-type frq and wc-1 mutants the authors provide strong evidence that FRQ and WC are involved in growth and survival following starvation, and recovery from starvation.

Weaknesses:

The authors describe Neurospora crassa as a model for circadian biology and apparently make the assumption that the findings are indicative of the behaviour of clock systems in other kingdoms. This is not the case. Neurospora crassa is a wonderful model for studying fungal clocks and is a great tool for studying basic circadian dynamics, but the interesting findings here are of a detailed molecular nature and therefore are applicable for fungal clocks, but not other kingdoms.

We agree that we still do not know whether the described mechanism is specific for only fungal clocks. However, besides the basic feedback loop, overlapping mechanisms (controlled by e.g. casein kinases, glycogen synthase kinase, PKA, PP2A) are involved in the regulation of circadian timekeeping in different eukaryotic systems (reviewed in Reischl and Kramer, 2011, FEBS Lett; Brenna and Albrecht, 2020, Front Physiol). Our results suggest that some of these common factors (PKA, GSK, PP2A) are involved in the reorganization of the Neurospora clock in response to changes in glucose availability. Therefore, it is possible that analogous changes occur in the time keeping mechanisms of other eukaryotic systems when they face serious environmental challenges.

We included a short section into the Discussion which gives a short overview about known interactions between glucose availability and circadian timekeeping at different levels of the phylogenetic hierarchy (P15 L18 – P16 L7).

The authors assume that the reader is intimate with the intricacies of Neurospora crassa circadian studies and the significance of differences between LL and DD investigations. More background on the logic of the experiments would be helpful for readers from other fields.

Thank you for the comment. In the revised version of the manuscript we tried to introduce the molecular clock of Neurospora more thoroughly and completed the description of the experimental conditions with detailed explanations.

The data in Figure 2 are essential for the interpretation of the findings, demonstrating the presence of free-running rhythms. However, the data are entirely qualitative, making it hard to fully assess the authors' interpretations, a more quantitative assessment of the data would improve clarity.

We quantified the Western blot signals and show the results in Fig 1E in the new version of the manuscript (according to the reviewer's suggestion Fig 2 of the old version is now part of Fig 1). Our data indicate that oscillation of FRQ levels is similar under both nutrient conditions.

The conclusion that FRQ contributes to the regulation of WC1 abundance in response to starvation does not seem to be supported by the data because FRQ RNA does not change upon starvation. Furthermore, the authors conclude that the starvation-induced decrease in WC-1 and WC-2 protein levels are due to FRQ because a lack of reduction in an frq9 mutant is open to misinterpretation because this mutant makes WC levels low and therefore starvation might not lower already low levels of WC. Indeed WC-1 is lower in the frq9 mutant under any condition than in the WT under starvation and WC-2 does decrease in abundance in the frq9 mutant in starvation. The data strongly suggest to this reader that FRQ does not participate in the regulation of WC abundance in response to starvation.

After rereading the criticized section, we admit that the text was not well structured and we carried out several modifications. We intended to emphasize that upon drastic changes of the glucose availability frq RNA levels remained compensated in wt, but this compensation was affected when functional FRQ was not present. We agree with the reviewer's opinion that the low expression of the WCC in frq9 makes it difficult to compare the glucose-dependence of WCC expression in frq9 and wt. We modified the conclusion by adding this information and now mainly focus on the strain-dependent difference in the changes of frq RNA expression. (P7 L22-P8 L14)

The discussion accurately summarises the results and provides an interpretation but lacking is a comparison to other circadian systems in other kingdoms. How do the data compare with the effects of glucose and other sugars on the mammalian, plant, and insect clocks?

We included a short section into the Discussion which gives a short overview about known interactions between glucose availability and circadian timekeeping in different organisms (P15 L18-P16 L7).

How changes in WCC might result in changes in transcription is not explained. This might be very obvious to the authors but to the reader, it is not. Are the transcriptional outputs direct targets of WCC? Has WCC CHIPseq been performed by the authors or others, are the regulated transcripts directly bound by WCC? What are the enriched promoter sequences in the regulated genes, is it possible to identify the network by which these changes in transcription occur?

We now show the list of genes (Figure 4 – Figure supplement 2) that changed in a strain-specific manner in response to glucose starvation and, based on Chip-Seq results, were earlier described as direct targets of the WCC (Smith et al., 2010; Hurley et al., 2014). Based on the literature data showing that the WCC affects the expression of several other transcription factors and controls basic cellular functions which might affect the expression of further genes, it was not surprising that only 90 out of the 1377 genes were reported to be direct targets of the WCC.

Whilst the authors claim it is the circadian clock that is involved in the starvation response, in my view a more precise interpretation of the data is that WCC is involved in the response. Since WCC is a photoreceptor with dual function in the clock, is it yet possible to conclude that the effects discovered are due to the clock role of WCC? Or do the data support the role of light signalling in regulating the starvation response through WCC?

We thank you for the comment. In the revised version of the manuscript we more specifically indicate that in wc-1 the lack of the WCC (and not the lack of a functional clock) results in the altered transcriptomic response to starvation compared to wt. In addition, in the revised version we present a new experiment (Fig. 5D.) which shows that upon resupply of glucose wt grows faster also in constant darkness than the clock-deficient strains wc-1 and frq10 do. This indicates that the role of the WCC in growth regeneration is largely independent of its photoreceptor function.

The authors do not apparently reconcile that the effect of starvation is to hugely decreases WCC levels, but they find the transcriptional and growth response to starvation requires WCC?

We agree with the reviewer that the problem of how low levels of WCC could sufficiently support the transcription of frq and different output genes under starvation conditions was not discussed properly. Our results suggest a model in which the maintained level of nuclear WCC and the weakened inhibition by both FRQ (the hyperphosphorylated form is less active in the negative feedback) and PKA (its activity lowered upon glucose depletion) together might ensure that transcriptional activity of the WCC is preserved upon glucose withdrawal in both DD and LL despite the decrease of the overall level of the complex. In the revised version these aspects are discussed more thoroughly (P16-18).

This study contributes to the increased focus of the circadian community on the regulation of outputs by circadian oscillators. The manuscript will be of interest to many in the field. There needs to be less assumption of knowledge about the N. Crassa circadian system, and better discussion in a broader context of clocks in other kingdoms.

We added a new section to the Discussion with data concerning interrelationships between glucose availability and the circadian clock in other organisms.

I think this is very important for teachers to know as culturally code-switching and translanguaging may be a huge issue in the home. It is super important to make connections to students first language but we must do research into the families norms and what they want for their child within learning a new language.

I think dynamic bilingualism is important for us as future teachers to acknowledge and understand. I also wonder how majority languages within the individual's everyday life impacts the changes between their usage of their languages. In the classroom this could effect teachers because we may become accustom to the use of English with our emergent bilingual students, however, we should still encourage and provide opportunities for students to use of their native/home language during learning. As teachers we should allow opportunities for students to further develop all their languages.

-Lauren Mitchell

I know annoying as a director or maybe even as a audience member I should assume thing but I don’t know in my opinion maybe it was aright if passage because he could’ve just asked her for the scissors or stoped what he was doing and got them for his self. But I could also argue that why didn’t he say something then. This made me think of the many questions we have for our parents that we never get answers to.

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Author Response

Reviewer #1 (Public Review):

Kohler and Murray present high-throughput image-based measurements of how low-copy F plasmids move (segregate) inside E. coli cell. This active segregation ensures that each daughter cell inherit equal share of the plasmids. Previous work by different labs has shown that faithful F-plasmid segregation (as well as segregation of many other low-copy plasmids, segregation of chromosomes in many bacterial species and segregation of come supramolecular complexes) require ParA and ParB proteins (or proteins similar to them) and is achieved by an active transport mechanism. ParB is known to bind to the cargo (plasmid) and ParA forms a dimer upon ATP binding that binds to DNA (chromosome) non-specifically and also can bind to ParB (associated with cargo). After ATP hydrolysis (stimulated by the interaction with ParB), ParA dimer dissociates to monomers and from ParB and the chromosome. While different mechanisms of the ParA-dependent active transport had been proposed, recently two mechanisms become most popular - one based on the elastic dynamics of the chromatin (Lim et al. eLife 2014, Surovtsev PNAS 2016, Hu et al Biophys.J 2017, Schumaher Dev.Cell 2017) and the other based on a theoretically-derived "chemophoretic" force (Sugawara & Kaneko Biophysics 2011, Walter et al. Phys.Rev.Lett. 2017).

It is a minor comment, but we would like to point out that we do not consider these two model types as alternatives but rather as models with different levels of coarse-graining. Our interest is in the molecular-level (stochastic) models (Lim et al. eLife 2014, Surovtsev PNAS 2016, Hu et al PNAS 2015, Hu et al Biophys.J 2017, Schumacher Dev.Cell 2017).

The authors start by following motion of F plasmid with one or two plasmids per cell and by analyzing plasmid spatial distribution, plasmid displacement (referred to as velocity) as a function of their relative position, and autocorrelations of the position and the displacement. They concluded that these metrics are consistent with 'true positioning' (i.e. average displacement is biased toward the target position - center for one plasmid and 1/4 and 3/4 positions for two plasmids ) but not with 'approximate positioning' (i.e. when plasmid moves around target position, for example, in near-oscillatory fashion). This 'true positioning' can be described as a particle moving on the over-dampened spring. They reproduce this behavior by expanding the previous model for 'DNA-relay' mechanism (Lim et al. eLife 2014, Surovtsev PNAS 2016), in which plasmid is actively moved by the elastic force from the chromosome and ParA serves to transmit this force from the chromosome to the plasmid. Now, the authors explicitly consider in the model that the chromosome-bound ParA can diffuse (which the authors refer as 'hopping') and this allows the model to achieve 'true plasmid positioning' for some combination of model parameters in addition to oscillatory dynamics reported in the original paper (Surovtsev PNAS 2016).

Based on their computational model, the authors proposed that two parameters, diffusion scale of ParA = 2(2Dh/kd)1/2/L (typical length diffused by ParA before dissociation) and ratio of ParB-dependent and independent hydrolysis rates = kh/kd are key control parameters defining what qualitative behavior is observed - random diffusion, near-oscillatory behavior, or overdamped spring ('true positioning'). They vary this two parameters ~30- fold and ~200-fold range by changing Dh and kh respectively, to illustrate how dynamics of the system changes between these 3 modes of motion. While these parameters clearly play important role, the drawback is that the authors did not put either theoretical reasoning why these parameters are truly governing or showed it by varying other model parameters (kh, number of ParA NParA, spring constant of chromosome k, diffusion coefficient of the plasmid Dp) to show that only these combinations define the type of the system behavior. The authors qualitative analysis on importance of relies on the steady state solution for the diffusion equation for ParA. It is really unfortunate that no ParA distribution was measured simultaneously with the plasmid motion, as this would allow to compare experimental ParA profiles to expected quasi-steady-state solutions.

We spend almost an entire section and a figure explaining the theoretical reasoning behind the identification of the $\lambda=s/(L/2n)$ as an important system parameter (section “Hopping of ParA-ATP on the nucleoid as an explanation of regular positioning” and Figure 2) and predicted that regular positioning could only occur for $\lambda>1$. This was confirmed by parameter sweeps for the cases of 1 (Figure 3I) and multiple plasmids (Figure 5-figure supplement 1), indicating that $\lambda$ is indeed an important system parameter and that our conceptual understanding of this aspect of the system is correct. This point has now been made clearer.

However, we agree that the reasoning for $\epsilon$ (varied through the hydrolysis rate $k_h$) was not clear. It was chosen to allow us to modulate the ParA concentration at the plasmid compared to elsewhere, motivated by the differences between different ParABS systems. We originally had also considered a third quantity related to the number of nucleoid-bound ParA but we found that this had little effect on the nature of the dynamics. All three quantities describe how the timescale of a reaction/process (ParA hopping/diffusion across the nucleoid, ParB induced hydrolsysis, ParA association to the nucleoid) compares to the timescale of basal hydrolysis, which we use as a reference timescale.

We have now made this clearer as well as adding supplementary figures showing the effect of varying other system parameters at several locations in the phase diagram (Figure 3-figure supplement 3 and 4). These sweeps justify our identification of $\epsilon$ and $\lambda$ as a useful/important set of quantities for determining the dynamics of the system.

Additionally, we now add example kymographs showing the ParA distribution (Figure 3-figure supplement 2C).

The authors also show by simulations that overdamped spring dynamics can transition into oscillatory behavior when decreases, for example by cell growth. Indeed, they observed more oscillatory behavior when they compared single-plasmid dynamics in the longer cells compared to the shorter cells. This was not the case in double-plasmid cells, in eprfect agreement with their analysis. They also calculated ATP consumption in the model and concluded that the system operates close but below (perhaps, "above" should be used as it refers to bigger ) the threshold to oscillatory regime which minimize ATP consumption. While ATP consumption analysis is very intriguing, this statement (Abstract Ln24-25) seems at odds with the authors own analysis that another ParA-dependent plasmid system, pB171, operates mostly in oscillatory regime, and it is actually for this regime the authors' analysis suggest minimal ATP-consumption (Fig. 8).

To clarify, we found that pB171 (which in our hands has a copy number of 2-3 in the SR1 reduced-copy-number strain) is only clearly oscillatory in cells with a single plasmid (and only mildly so in cells with two plasmids). Otherwise, it behaves very similarly to F plasmid. We therefore believe that these two distantly related ParABS systems exhibit, overall, similar dynamics and differ only in how close the systems are to the threshold of oscillatory instability. This was not clear as we did not specify the copy number of pB171. We now provide this in Figure 7–figure supplement 1.

We refer to these systems as lying just below, rather than above, the threshold of the oscillatory instability because, on average, plasmids do not oscillate but only do so in cells with the lowest plasmid concentration.

I think the real strength of the paper is that it can potentially to show that if one considers that the intracellular cargo can be moved by the fluctuating chromosome via ParA-mediated attachments, then various dynamics can be achieved depending on combinations of several control parameters (plasmid diffusion coefficient, ParA diffusion coefficient, rate of hydrolysis and so on) including previously reported 'oscillations' (Surovtsev PNAS 2016), 'local excursions' (Hu et al Biophys.J 2017) and 'true positioning' (Schumaher Dev.Cell 2017). The main drawback (in this reviewer opinion) that this is obscured by the current presentation and discussion of this work and previous modelling work on ParA-dependent systems. For example, instead of using "unifying" potential of the presented model, yet another name 'relay and hopping' is used in addition to previously used 'DNA-relay', 'Brownian ratchet', 'Flux-based positioning', …

In the abstract and discussion, we already refer to developing a “unified” model (p1 L21, p15 L22 of the original manuscript) and in the discussion we explain how our model contains other models as limiting cases. But we agree with this recommendation - the unifying nature of our model is its main strength. We now emphasise this more.

Regarding the model name, we felt obliged to refer to the previous named models (DNA-relay and Brownian ratchet) and simply gave our model a name to avoid confusion when making comparisons. We have now removed almost all mention of ‘hopping and relay’ and just refer to ‘our model’. However, our gitlab repository with the code must have a name and therefore is still called ‘Hopping and relay’ and so the same term is used in Table 3.

… and it appears that the presented model is an alternative to these previously published work. And only in model description (in Methods section) one can find that the "... model is an extension of the previous DNA-relay model (Surovtsev et al., 2016a) that incorporates hopping and basal hydrolysis of ParA and uses analytic expressions for the fluctuations rather than a second order approximation"(p.17, ln15-17).

We are sorry that this reviewer felt that the fact that our model is an extension of DNA relay is hidden in the methods. However, we wrote in the main text:

“Motivated by the previous discussion, we decided to develop our own minimal molecular model (‘hopping and relay’) of ParABS positioning, taking the DNA relay model as a starting point … The original scheme is as follows… We supplemented this scheme with two additional components: diffusion (hopping) of DNA-bound ParA-ATP dimers across the nucleoid (with diffusion coefficient Dh, where the subscript indicates diffusion of the home position) and plasmid-independent ATP hydrolysis and dissociation (with rate kd). See Material and Methods for further details of the model. “

We now make this clearer.

However, we would argue that as models of the same system, there are naturally overlaps and the models of Hu et al and Schumacher et al could also be thought of as extensions of the DNA relay model.

While it is of course the authors right to decide how to name their model, it should be explicitly clear to the reader what is a real conceptual difference between presented and previous models from the abstract, introduction and discussion section of the paper, not from the "fine-print" details in the supplementary materials.

The main conceptual difference is that we have identified the importance of having a finite diffusive length scale for ParA diffusion/hopping on the nucleoid. This allows both oscillations and regular positioning to occur for biologically relevant parameter values and reproduces the length dependent transition from mid-cell positioning to confined oscillations that we observe for F plasmid. The DNA relay model does not have this behaviour as the ParA diffusive length scale in zero while it is infinite in the models of Ietswaart et al 2014 and Schumacher et al 2017. The model of Hu et al 2017 does have a finite length scale but the authors appear not to have realised its importance and never discovered the regular positioning regime at \lambda >1. While we make these points in the discussion in the context of Figure 8A, where we compare our model to the others, we agree with this reviewer that we should have been more explicit in the abstract and introduction. We have now corrected this.

This would allow to avoid unnecessary confusion (especially for the readers not directly involved into the modelling of ParA/B system) and clarify that all these models rely on the elastic behavior of fluctuating chromosome to drive active transport of the cargo. This reviewer believes that more explicit discussion on the models (one from the authors and previously published) differences and similarities will help with our understanding of how ParA-dependent system operate. This discussion should also include works on PomXYZ system, in which it was shown that similar dynamic system can lead to specific positioning within the cell (Schumaher Dev.Cell 2017, Kober et al. Biophys.J 2019). This will may it explicit that the models results have direct impact beyond the ParA-dependent plasmid segregation.

To further clarify the differences between the models (beyond the second and third sections of the main text and the discussion), we have now added a section to the methods and a new table (Table 3). We have also included the mentioned PomXYZ model. However, we would like this was not the first stochastic model to have ‘true’ positioning as this reviewer cites above. Though they did not include the mechanism of force generation, the model of Ietswaart et al 2014 produces regularly positioned plasmids and is referenced repeatedly in Schumacher et al. 2017.

I think that expanded parameter analysis, and explicit model comparison/discussion will make the contribution of this work to the field more clear and with the potential to advance our general understanding of how the same underlying mechanism can lead to various modes of intracellular dynamics and patterning depending on parameters combination.

Reviewer #2 (Public Review):

The work presented in this manuscript details an analysis of the partitioning of low copy plasmids under the control of the ParABS system in bacteria. Using a high throughput imaging set up they were able to track the dynamics of the partition complex of one to a few plasmids over many cell cycles. The work provides an impressive amount of quantitative data for this chemo-mechanical system. Using this data, the paper sought to clarify whether the dynamics of plasmids is due to regular positioning or noisy oscillations around a mean position. They supplement their experimental work with an intuitive model that combines elements of previous modelling efforts. Their model relies on diffusion of the ParA substrate on the nucleoid with the dynamics of the ParB partition complex being driven by the underlying elastic force due to the nucleoid on which the substrate is tethered. Their model dynamics depend on two parameters, the ratio of the length over which the substrate can explore to the characteristic length of the space and the ratio of stimulated to non-stimulated hydrolysis rates of the substrate. If the length ratio is large, ParA can fully explore the space before interacting with the ParB complex leading to balanced fluxes and regular positioning. If it gets reduced, for example by lengthening the cell, oscillations can emerge as fluxes of substrates become imbalanced and a net force can pull the partition complex.

Strengths:

Given the large amount of data, the observations unambiguously show that one particular ParABS system under the conditions studied is carrying out regular positioning of plasmids. The model synthesizes prior work into a nice intuitive picture. These model parameters can be fit to the data leading to estimates of molecular kinetic parameters that are reasonable and in line with other observations. Lining up the experimental observations with the phase space of the model suggests that the system is poised on the edge of oscillations, allowing for the system to have regular positioning with low resource consumption.

Weaknesses:

However, despite the correspondence of the simulated results with the experimental findings, other explanations are not completely ruled out. The paper emphasizes that ParA diffusion/hopping on the nucleoid is essential for the establishment of regular positioning and that without it, only oscillations were possible. Prior simulation efforts, that the paper cites, which include ParA diffusion and mixing in the cytosol but no diffusion on the nucleoid have shown that regular positioning is possible and that oscillations could get triggered as the system lengthened. Thus ParA hopping is not a necessity for regular positioning (as claimed in the paper), but very well might be needed for the given kinetic parameters of the system studied here.

We now comment on this result. In short, we believe that the mentioned model/regime is not relevant due to stochastic effects. We are not able to produce, with biological relevant parameters, regular positioning without ParA hopping.

The paper also presents experimental results for a second ParABS system (pB171) that is more likely to show oscillations. They attribute the greater likelihood of oscillations for pB1717 being due to ParA exploring a smaller space than the F plasmid system that showed regular positioning. This is pure conjecture and the paper does not provide any evidence that this is the reason. Thus it is hard to conclude if oscillations may not be due to other factors.

We do not explicitly make that claim. We did have a point in the phase diagram of Figure 8A representing pB171 with a lower value of lambda than F plasmid and stated “The location of pB171 is an estimate based on a qualitative comparison of its dynamics”. We agree this was unclear.

We now indicate the region that has oscillations with roughly the same period as single plasmids of pB171. We also make it clear that we speculate, but have not shown, that the length scale of ParA hopping is smaller than for F plasmid.

An important point here is that we can explain both oscillations and regular positioning in the same model with the same kinetic parameters, the regimes being determined by the cell length and plasmid number in a manner consistent with experimental observations.

Author Response

Reviewer #1 (Public Review):

The authors use the nanobody tools generated in the companion manuscript and have combined them with DNA-Paint oligonucleotide labeling to generate super-resolution images of indirect flight muscles. Using this approach, they could map the precise organization of the different domains from the two giant titin-like fly homologs called Sallimus and Projectin against which the nanobodies had been raised with a precision ranging from 1 nm to 4 nm, depending on the distance between them. They show that in indirect flight muscles the N-ter of Sallimus is located within 50 nm of the Z-disc, and that its C-ter reaches the A-band roughly 100 nm away from the Z-disc. Likewise, they show that the N-ter of Projectin colocalizes with the C-ter of Sallimus at the edge of the A-band, whereas its C-ter is located about 250 nm away in the A-band and 350 nm from the Z-disc. It overall suggests a staggered and linear organization of both proteins with a potential area of overlap spanning 10-12 nm, that Sallimus could bridge the Z-disc to the A-band acting as a ruler, while Projectin should only overlap with 15% of the A-band and possibly a 10 nm of the I-band.

Thanks for this nice summary of our findings.

The value of this work comes from its use of advanced technologies (DNA-Paint + superresolution). The biological conclusions confirm and refine earlier and recent papers, especially EM papers and the impressive and very comprehensive JCB paper by Szikora et al in 2020, although the conclusions of the present work differ somewhat from those of Szikora who had predicted that Sallimus does not reach the A-band. That aspect could have been better discussed.

We have further extended our discussions of the results from Szikora et al. 2020, in particular regarding Sallimus in this revised version.

Reviewer #2 (Public Review):

Taking advantage of the high molecular order of the Drosophila flight muscle, Schueder, Mangeol et al. leverage small (<4 nm) original nanobodies, tailored coupling to fluorophores, and DNA-PAINT resolution capabilities, to map the nanoarchitecture of two titin homologs, Sallismus and Projectin.

Using a toolkit of nanobodies designed to bind to specific domains of the two proteins (described in the companion article "A nanobody toolbox to investigate localisation and dynamics of Drosophila titins" ), Schueder, Mangeol et al position these domains within the sarcomere with <5nm resolution, and demonstrate that the N-ter of Sallismus overlaps with the C-ter of Projectin at the A-band/I-band interface. They propose this architecture may help to anchor Sallismus to the muscle, thus supporting flight muscle function while ensuring muscle integrity.

This study nicely extends previous work by Szikora et al, and precisely dissect the the sarcomeric geography of Sallismus and Projectin. From these results, the authors formulate specific functional hypotheses regarding the organization of flight muscles and how these are tuned to the mechanical constraints they undergo.

Although they remain descriptive in essence, the conclusions of the paper are well supported by the experimental results.

We thank this reviewer for the nice summary of our results.

Reviewer #3 (Public Review):

This manuscript by Schueder et al. provides new insight into an important question in muscle biology: how can the smaller titin-like molecules of the much larger sarcomeres of invertebrate muscle perform the same function as the larger titin of vertebrate muscles which have smaller sarcomeres? These functions include the assembly, stability and elasticity of the sarcomere. Using two state of the art methods--nanobodies and DNA-PAINT superresolution microscopy, the authors definitively show that in the highly ordered indirect flight muscle of Drosophila, the elongated proteins Sallimus and Projectin are arranged such that the N-terminus of Sallimus is embedded in the Z-disk, and the C-terminus is embedded in the outer portion of the A-band, and that in this outer portion of the A-band is also embedded the C-terminus of Projectin; thus, if the C-terminus of Sallimus can bind to thick filaments, and/or these overlapping portions of Sallimus and Projectin interact, there would be a linkage of the Z-disk and/or thin filament to the thick filaments to help determine the length and stability of the sarcomere.

The strengths of this paper include the implementation of nanobody and DNA-PAINT superresolution microscopy for the first time for muscle. The extraordinary 5-10 nm resolution of this method alloiws imaging for definitive localization of the termini of these elongated proteins in the Drosophila flight muscle sarcomere. In addition, the manuscript is well written with sufficient background information and rationale presented, is easy to read, complex new methods are well-described, the figures are of high quality, and the conclusions are well-justified. A minor weakness is that despite the authors demonstrating that the Cterminus of Sallimus is located at the outer edge of the A-band, and that the N-terminus of Projectin is located also in the outer edge of the A-band, the authors provide no data to show whether, for example, these portions of these titin-like molecules interact, or whether Sallimus might interact with thick filaments. Such data would be required to prove their model. However, I can understand that this would require extensive additional study, and the authors have already provided a tremendous amount of data for this first step in supporting the model. Nevertheless, the authors should cite a relevant previous study on the Sallimus homolog in C. elegans called TTN-1, which is also a 2 MDa polypeptide of similar domain organization to at least the large isoforms of Salliums found in fly synchronous muscles. In the study by Forbes et al. (2010), immunostaining, albeit not to the impressive resolution achieved in the present paper, showed that TTN-1 was also localized to the I-band with extension into the outer edge of the A-band. More importantly, that study also showed that "fragment 11/12", Ig38-40, which is located fairly close to the C-terminus of TTN-1 binds to myosin with nanomolar affinity (Kd= 1.5 nM), making plausible the idea that TTN-1 may bind to the thick filament in vivo.

We thank this reviewer for sharing his enthusiasm about our results and methodology, and also about the way the data are presented. This is one more argument for us to leave a shortened Figure 1 in the PAINT manuscript.

We are particularly thankful for pointing out the important C. elegans data that we had missed and that, as the reviewer said, perfectly fit with the model we propose for flight muscle (and also the larval muscle data, as the C-term of Sls is the same). Hence, we highlight this paper now in our discussion and compare to our findings.

Reviewer #4 (Public Review):

This manuscript reports combining recently developed and described in the accompanying paper nanobodies against Sallimus and Projectin with DNA-Paint technology that allows super-resolution imaging. Presented data prove that such a combination provides a powerful system for imaging at a nano-scale the large and protein-dense structures such as Drosophila flight muscle. The main outcome is the observation that in flight muscle sarcomeres Salimus and Projectin overlap at the I/A band border. This was elegantly achieved using double color DNA-Paint with Sls and Projectin nanobodies.

We thank the reviewer for appreciating the quality of our work.

Overall, as it stands, this manuscript even if of high technological value, remains entirely descriptive and short in providing new insights into muscle structure and architecture. The main finding, an overlap between short Sls isoform and Proj in flight muscle sarcomeres, is redundant with the author's observation (described in the companion paper "A nanobody toolbox to investigate localisation and dynamics of Drosophila titins") that in larval muscles expressing a long Sls isoform, Sls and Proj overlap as well.

Alternatively, combination of Sls and Proj nanobodies with DNA-Paint represents an interesting example of technological development that could strengthen the accompanying nanobodies toolkit manuscript.

Every structural paper reports the structure and is thus by definition descriptive. This is the aim of our manuscript. We do not think that the other nanobody resource paper reports an overlap of Sls and Projectin in the larvae. To resolve such a possible overlap, super resolution would be needed. The other paper does report that larval Sls isoform is dramatically stretched, more than 2 µm, and that Projectin is decorating the thick filament, likely in an oriented manner. If N-term of Projectin overlaps with C-term of Sallimus in this muscle is an open question that needs DNA-PAINT imaging of larval muscle. This requires a TIRF setting that is technically not trivial to achieve for larval muscle and hence has not been done by anybody.

Ben Werdmüller sees the Musk take-over as one of more signs that Twitter as we know it is sunsetting. Like FB it is losing its role as the all-in-one communal 'space'. I think the decline is real, but also think it will be long drawn out decline. Early adopters and early main stream may well jump ship, if they haven't already some time ago. The rest, including companies, will hang around much longer, if only for the sunk costs (socially and capital). An alternative (hopefully a multitude as Ben suggests) needs to clearly present itself, but hasn't in a way the mainstream recognises I think. It may well hurt to hold on for many, but if there's no other thing to latch onto people will endure the pain. Boiling frog and all that.

Author Resonse

Reviewer #1 (Public Review):

The manuscript by Himmel et al is an interesting study representing a topic of substantial interest to the somatosensory neurobiology community. Here, the authors use CIII peripheral neurons to investigate polymodality of sensory neurons. From vertebrates to invertebrates, this is a long-standing question in the field: how is it that the same class of sensory neurons that express receptors for myriad sensory modalities encode different behavioral responses. This system in Drosophila seems to be an intriguing system to study this question, making use of the genetic toolkit in the fly and ease of behavioral assays. In this study, the authors identify a number of channels that are important for cold nociception, and they showed that some of these do not appear to also encode mechanosensation. Despite my initial enthusiasm for this paper, halfway through, it felt as if I were reading two different papers that were loosely tied together. This lack of cohesion significantly reduced my enthusiasm for this work. Below are some of my criticisms:

We thank Reviewer #1 for their feedback. In addition to the points below, and in accordance with the reviewer’s overall criticisms, we have revised the body text to make it more cohesive. Our main goal with this revision was to better explain to the reader the shift from anoctamins to SLC12 cotransporters.

1) The first half of the paper is about a role for Anoctamins in cold nociception, but the second half switched somewhat abruptly to ncc69 and kcc. I assumed the authors would connect these genes in a genetic pathway, performing some kind of epistatic genetic interaction studies or even biochemical assays, and that this was the reason to switch the focus of the paper midway through. But this was not the case. Moreover, they performed a different constellation of experiments for the genes in the first half vs the second half of the paper (eg. Showed a role in cold nociception vs mechanosensation or showing phenotype from overexpression). This lack of cohesion made it difficult to follow the work.

We have edited the text to better explain this shift. Two notable changes are: (1) moving the phylogenetics to Figure 1, to more immediately present and demonstrate that subdued is part of the ANO1/ANO2 family of calcium-activated chloride channels; and (2) a new cartoon schematic in Figure 6 to more strongly communicate to a reader that chloride is a hypothetical mechanism of cold discrimination.

In short, previous work and our phylogenetic analyses indicate that subdued is a Cl- channel (we have moved the phylogeny earlier in the paper to make this clear from the onset). We were therefore surprised that knockdown/mutation resulted in reduced CT behavior, as neural Cl- currents are often inhibitory. Thus, we looked to known mechanisms of Cl- homeostasis to try to formulate an informed hypothesis about the function of anoctamins in this system; hence the shift in focus to SLC12.

In response to the second half of the comment: We have in fact performed cold nociception and mechanosensation experiments for both the anoctamins and the SLC12 cotransporters, although the SLC12 mechanosensation results were in a supplemental figure. We have moved the mechanaosensation results to the main Figure 6 to make this clearer. With respect to simple overexpression, the goal of the anoctamin experiments was to test the necessity of anoctamins to cold-evoked behavior, whereas the goal of the SLC12 experiments was to differentially modulate Cl- homeostasis, and this could hypothetically be accomplished by both knockdown and overexpression (hence we performed both knockdown and overexpression).

2) In Fig1B,C how does one confirm a CIII neuron is being analyzed. It might help the reader if there were at least some zoomed out photos where all the cell types are labeled and potentially compared to a schematic. Moreover, is there a CIII specific marker to use to co-stain for confirmation of neuron type?

Our CIII fusion is a specific marker for CIII neurons. To better demonstrate this, we have added images of the new CIII fusion expression patterns overlapping with a previously described CIII GAL4 driver (i.e. nompC-GAL4), and provided text describing how the CIII fusion transgene was discovered and generated. Please see the new Figure 1-Figure supplement 1.

3) As this paper is predicated on detecting differences by behavioral phenotype, the scoring analysis is not as robust as it could be, especially considering the wealth of tools in Drosophila for mapping behaviors. The "CT" phenotype is begging for a richer behavioral quantification. This critique becomes relevant here when considering the optogenetic induced CT behavior in Fig5. If the authors were to use unbiased quantitative metrics to measure behavior, they could show how similar the opto behavior is to the natural cold evoked behavior. Perhaps the two are not the same, although loosely fitting under the umbrella of "CT".

In accordance with our response above to necessary revisions, we have added one additional metric and reorganized the figures to better demonstrate the complexity of the behavior. We have no further data or new tools at this time.

To improve our optogenetic analyses, we have added data for Channelrhodopsin-dependent CIII activation, which has been previously shown to induce cold-like behaviors at high levels of activation and innocuous touch-like behaviors at low levels of activation (Turner, Armengol et al 2016). Further, we have added videos (Figure 5—videos 1-3) showing behavior in response to both Channelrhodopsin and Aurora activation.

With respect to differences in behavior, we have pointed out some differences in the Aurora-evoked behavior from the cold-evoked behavior: chloride optogenetics induces innocuous touch-like behaviors following CT. Please see lines 296-299.

4) Following on from the last comment, the touch assays in Fig3 have a different measurement system from the other figures. Perhaps touch deficits would be identified with richer behavioral quantification. Moreover, do these RNAi larvae show any responses to noxious mechanical stimulation?

The touch assays necessarily have different metrics from cold assays, as the touch-evoked behaviors are quite different from cold-evoked change in length (which are relatively simple, prima facie).

With respect to noxious mechanical stimulation, while Class III neurons have been shown to facilitate this modality and be connected to relevant circuitry (please see Hu et al 2017 https://doi.org/10.1038/nn.4580 and Takagi et al 2017 https://doi.org/10.1016/j.neuron.2017.10.030), Class IV neurons are the primary sensory neuron which initiate the noxious mechanical-induced rolling response. Although this is an interesting question, we believe it is outside the scope of this study.

Reviewer #2 (Public Review):

Himmel and colleagues study how individual sensory neurons can be tuned to detect noxious vs. gentle touch stimuli. Functional studies of Drosophila class III dendritic arborization neurons characterized roles in gentle touch and identified a receptor, NompC, and other factors that mediate these responses. Subsequent work primarily from the authors of the current study focused on roles for the same sensory neurons in cold nociception. The two proposed sensory inputs lead to quite distinct sets of behaviors, with touch leading to halting, head turning and reverse peristalsis, and noxious cold leading to whole body contraction. How activity of one type of sensory neuron could lead to such different responses remains an outstanding question, both at the levels of reception and circuitry.

The cIII responses to noxious cold and innocuous touch raises questions that the authors address here, proposing that studies of this system could advance the understanding of chronic neuropathic pain. A candidate approach inspired by studies in vertebrate nociceptors led the authors to study anoctamin/TMEM16 channels subdued, and CG15270, termed wwk by the authors. The authors focus on a pathway for gentle touch vs. cold nociception discrimination through anoctamins. Several of the experiments in this manuscript are well done, in particular, the electrophysiological recordings provide a substantial advance. However, the genetic and expression analysis has several gaps and should be strengthened. The data also do not provide strong support for some key aspects of the proposed model, namely the importance of relative levels of Cl co-transporters.

Major comments:

1) Knockout studies are accomplished using two MiMIC insertions whose effects on subdued or CG15270/wwk are not characterized by the authors. This needs to be established. The MiMIC system is also not well explained in the text for readers.

We have modified the text to better explain MiMICs (Lines 137-140) and we have verified the mutagenic effects of these MiMIC insertions via RT-PCR (Figure 2 – supplement 1). We believe these data, in conjunction with other converging lines of evidence (e.g. rescue) demonstrate necessity of these genes in cold nociception.

2) Subdued expression is inferred by a Gal4 enhancer trap. This can be a hazardous way of determining expression patterns given the uncertain relevance of the local enhancers driving the expression. According to microarray analysis subdued is strongly expressed in cIII neurons, but c240-Gal4 is barely present compared to nearby neurons, raising questions about whether this line reflects the expression pattern, including levels, even though the authors suggest that the line is previously validated (line 95; it is unclear what previously validated means). Figure 1B should not be labeled "subdued > GFP" since it is not clear that this is the case. Another more direct method of assessing expression in cIII is necessary. Confidence is higher for wwk using a T2A-Gal4 line, however, Figure 1C might be misleading to readers and indicate that wwk-T2A-Gal4 is cIII specific whereas in supplemental data the authors show how it is much more broadly expressed. The expression pattern in the supplemental figures should be moved to the main figures.

We have removed the phrase “previously validated” and we have modified Figure 1 to change how we refer to the GFP expression (removed “subdued > GFP”).

In accordance with the response to necessary revisions above, we make use of several converging lines of evidence to infer expression, including GAL4 expression patterns, microarray, and qPCR (the two latter experiments from isolated CIII samples). That subdued and wwk are expressed in CIII is clearly the most parsimonious hypothesis.

We have also carefully reviewed our body text to be certain we do not make claims of differential expression between different neural subtypes based on differences in fluorescence in the GAL4-driven GFP imaging. We do not believe that this would be a reasonable way to infer differences in expression levels in any instance.

With respect to the design of Figure 1, the intent is not to mislead the reader, and we state in the text that wwk is not solely expressed in CIII (lines 120-125). As eLife makes supplemental figures available directly alongside the main figures, we have left the relevant supplemental figures as supplements – we simply think this makes more sense from a standpoint of readability and style.

3) In figure 8 the authors propose a model in which the relative levels of K-Cl cotransporters Kcc (outward) and Ncc69 (inward) in cIII neurons determine high intracellular Cl- levels and a Cl- dependent depolarizing current in cIII neurons. They test this model using overexpression and loss of function data, but the results do not support their model since for most of the overexpression and LOF of kcc and ncc69 do not significantly affect cold nociception, the exception being ncc69 RNAi. The authors suggest that this could be due to Cl homeostasis regulated by other cotransporters. Nonetheless, it leaves a significant unexplained gap in the model that needs to be addressed.

We respectfully disagree that our results are not consistent with the stated hypothesis. In fact, it is the lack of change under certain conditions which lend evidence against the alternative hypothesis that CIII neurons maintain relatively low intracellular Cl-. The hypothesis we are testing is that ncc69 expression is driving relatively high intracellular Cl- concentrations, thus resulting in depolarizing Cl- currents.

Under this hypothesis, we would predict that knockdown of ncc69 and overexpression of kcc would reduce cold sensitivity at 5˚C. That knockdown of ncc69 and overexpression of kcc reduces cold sensitivity is consistent with this hypothesis (and we point out in text that the evidence for kcc is less convincing) – at the least, these results do not disprove it.

Under this hypothesis, we would also predict that knockdown of kcc and overexpression of ncc69 would not result in reduced cold sensitivity at 5˚C. As there was no phenotype at 5C, our results are likewise consistent with the hypothesis (at the least, they do not disprove it).

We did find it curious that ncc69 RNAi did not affect neural activity at 10˚C, but speculate that our inability to detect physiological effects for ncc69 knockdown are limitations of our electrophysiology methodology (and we discuss this in the manuscript).

The only piece of data inconsistent with the hypothesis may be that kcc overexpression may not have affected cold nociception at 5˚C – the data aren’t overwhelmingly convincing. However, this is only one experiment among many, and we believe the preponderance of evidence is consistent with the hypothesis. That is not to say we believe this hypothesis has complete explanatory power, however, as noted by our discussion of both the ncc69 electrophysiological and kcc behavioral data, and by our suggestion that there may be other regulatory mechanisms at work. This latter suggestion is wholly speculative, and we believe appropriate for the discussion section. We agree (and state in the discussion) that this would require further experimentation.

4) Related to the #3, the authors should verify the microarray data that form the basis for their differential expression model.

We have performed qPCR for ncc69 and kcc. Although qPCR is semiquantitative when comparing between genes, the Ct value for ncc69 was lower than for kcc, indicating more transcripts were present at the onset (assuming identical efficacy). These data (although semi-quantitative), the microarray, and our behavioral and electrophysiological data are consistent with the stated hypothesis.

Reviewer #3 (Public Review):

There are also several modest weaknesses in the paper:

1) A notable gap remains in the evidence for the hypothesized mechanisms that enhance electrical activity during cold stimulation and the proposed role of anoctamins (Fig. 8) - the lack of evidence for Ca2+-dependent activation of Cl- current. The recording methods used in the fillet preparation should enable direct tests of this important part of the model.

We have performed an additional experiment at the reviewer’s suggestion. Please see above (in essential revisions) and below (in recommendations for authors).

2) The behavioral and electrophysiological consequences of knocking down either of the two anoctamins are incomplete (Fig.2), raising the significant question of whether combined knock-down of both anoctamins in the CIII neurons would largely eliminate the cold-specific responses.

While the results of this experiment would certainly be interesting, we are unsure of how it would be acutely informative in this context and are not convinced that any possible outcomes would disprove any particular hypothesis. In part, this is because we know that blocking synaptic transmission in CIII neurons (via tetanus toxin) does not completely ablate cold-evoked behavior (Turner & Armengol et al 2016 https://doi.org/10.1016/j.cub.2016.09.038). This is also the case for combinatorial mutation of other genes associated with cold nociception (please see Turner & Armengol et al 2016; and more recently, Patel et al 2022 https://doi.org/10.3389/fnmol.2022.942548). Further, the husbandry required to generate the double knockdowns would be quite challenging and might result in GAL4 titration (hypothetically less strongly knocking down each gene). For these reasons, we have not performed this suggested experiment.

3) Blind procedures were not used to minimize unconscious bias in the analyses of video-recorded behavior, although some of the analyses were partially automated.

This is correct and a relative weakness of the study. We note it in our methods section. The use of semi-automated data analyses of the behavioral videos is designed to minimize experimenter-specific variability.

4) The term "hypersensitization" is confusing. Pain physiologists typically use "sensitization" when behavioral or neural responses are increased from normal. In the case of increased neuronal sensitivity, if the mechanism involves an increase in responsiveness to depolarizing inputs or an increased probability of spontaneous discharge, the term "hyperexcitability" is appropriate. Hypersensitization connotes an extreme sensitization state compared to a known normal sensitization state (which already signifies increased sensitivity). In contrast, the effects of ncc69 overexpression in this manuscript are best described simply as sensitization (increased reflexive and neuronal sensitivity to cooling) and hyperexcitability (expressed as increased spontaneous activity at room temperature).

We have modified the text in accordance with the reviewer’s suggestions (see recommendations for authors section). We have also changed the title of the paper to “Chloride-dependent mechanisms of multimodal sensory discrimination and nociceptive sensitization in Drosophila”

This is an interesting observation. Also because Memex went on to inspire e.g. Doug Engelbart. Was Engelbart aware of the history when he demo'd outlining and notes? Was Nelson when he thought up stretchtext in 67?

Reviewer #3 (Public Review):

This paper aimed to understand how toxin-antidote (TA) elements are spread and maintained in species, especially in species where outcrossing is infrequent and the selfish gene drive of TA elements is limited. The paper focuses on the possible fitness costs and benefits of the peel-1/zeel-1 element in the nematode C. elegans. A combination of mathematical modeling and experimental tests of fitness are presented. The authors make a surprising finding: the toxin gene peel-1 provides a fitness advantage to the host. This is a very interesting finding that challenges how we think about selfish genetic elements, demonstrating that they may not be wholly "selfish" in order to spread in a population.

Strengths<br /> 1. The authors support results found with a zeel-1 peel-1 introgressed strain by using CRISPR/Cas9 genetic engineering to precise knock-out the genes of interest. They were careful to ensure the loss-of-function of these generated alleles by using genetic crosses.

2. Similarly, the authors are careful with controls, ensuring that genetic markers used in the fitness assays did not affect the fitness of the strain. This ensures that the genes of interest are causative for any source of fitness differences between strains, therefore making the data reliable and easily interpretable.

3. A powerful assay for directly measuring the relative fitness of two strains is used.

4. The authors support relative fitness data with direct measurements of fitness proximal traits such as body size (a proxy for growth rate) and fecundity, providing further support for the conclusion that peel-1 increases fitness.

Weaknesses<br /> 1. One major conclusion is that peel-1 increases fitness independent of zeel-1, but this claim is not well supported by the data. The data presented show that the presence of zeel-1 does not provide a fitness benefit to a peel-1(null) worm. But the experiment does not test whether zeel-1 is required for the increased fitness conferred by the presence of peel-1. Ideally, one would test whether a zeel-1(null);peel-1(+) strain is as fit as a zeel-1(+);peel-1(+) strain, but this experiment may be infeasible since a zeel-1(null);peel-1(+) strain is inviable.

2. The CRISPR-generated peel-1 allele in the N2 background only accounts for 32% of the fitness difference of the introgressed strain. Thus, the effect of peel-1 alone on fitness appears to be rather small. Additionally, this effect of peel-1 shows only weak statistical significance (and see point 5 below). Given that this is the key experiment in the paper, the major conclusion of the paper that the presence of peel-1 provides a fitness benefit is supported only weakly. For example, it is possible that other mutations caused by off-target effects of CRISPR in this strain may contribute to its decreased fitness. It would be valuable to point out the caveats to this conclusion, or back it up more strongly with additional experiments such as rescuing the peel-1(null) fitness defect with a wild-type peel-1 allele or determining if the introduction of wild-type peel-1 into the introgressed strain is sufficient to confer a fitness benefit.

3. The strain that introgresses the zeel-1 peel-1 region from CB4856 into the N2 background was made by a different lab. Given that N2 strains from different labs can vary considerably, it is unclear whether this introgressed strain is indeed isogenic to the N2 strain it is competing against, or whether other background mutations outside the introgressed region may contribute to the observed fitness differences.

4. Though the CRISPR-generated null allele of peel-1 only accounts for 32% of the fitness difference of the zeel-1 peel-1 introgressed strain, these two strains have very similar fecundity and growth rates. Thus, it is unclear why this mutant does not more fully account for the fitness differences.

5. Improper statistical tests are used. All comparisons use a t-test, but this test is inappropriate when multiple comparisons are made. Importantly, correction for multiple comparisons may decrease the already weak statistical significance of the fitness costs of the peel-1 CRISPR allele (Fig 3E), which is the key result in the paper.

6. N2 fecundity and growth rate measurements from Fig 2B&C are reused in Fig 3C&D. This should be explicitly stated. It should also be stated whether all three strains (N2, the zeel-1 peel-1 introgressed strain, and the peel-1 CRISPR mutant) were assayed in parallel as they should be. If so, a statistical test that corrects for multiple comparisons should also be used.

7. It appears that the same data for the controls for the fitness experiments (i.e. N2 vs. marker & N2 vs. introgressed npr-1; glb-5) may be reused in Fig 2A and 3E. If so, this should be stated. It should also be stated whether all the experiments in these panels were performed in parallel. If so, this may affect the statistical significance when correcting for multiple comparisons.

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Reply to the reviewers

Response to reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)): The authors develop a previously identified lead compound for the blocking of malaria transmission from humans to mosquitoes further and identified a protein target of the chemical. The protein target, Pfs16 is long known to be upregulated in gametocytes and has been speculated to be a target for small molecules. The work is well (if at time maybe too well/too detailed) described and potential shortfalls are highlighted.

My major comment is that without a deletion mutation of Pfs16, the paper will remain somewhat preliminary. I would strongly encourage the authors to generate such a mutant and compare it to the parasites treated with their drug candidate. I feel the text can be much shortened and a lot of information moved to the materials and methods. The conclusions should be toned down on several occasions (abstract, introduction, discussion). Avoid adjectives, e.g. what is a 'powerful starting point' (abstract) or 'compelling interdisciplinary evidence' but hot air?

We thank the reviewer for this comment. However, we would like to reiterate (as stated in the manuscript) that knockout of Pfs16 in P. falciparum is transmission lethal, i.e. you do not get progression of male gametogenesis. Thus, whilst re-generation of a Pfs16 KO would be interesting in terms of comparing phenotypically with the drug treated parasites, we are not convinced it would add any further evidence of support for or against our conclusion in terms of the ability of the N-4HCS scaffold to target this protein. E.g. we could drug treat a Pfs16 KO but this would not be expected to show gametogenesis irrespective of treatment. Therefore, whilst of academic interest, we believe it is satisfactory to judge our phenotypic work based on published accounts of the Pfs16 KO without having to engage in the costly experiments to regenerate the parasite and work on it side-by-side, especially given the limited resolution it would give towards the overall goal of the work in terms of defining the effect and likely target of this drug class on parasites.

Addressing the second comment, we are happy to alter areas of the paper that may have over-stated the conclusions of the work including the abstract/introduction and discussion.

CROSS-CONSULTATION COMMENTS I think these three reviews are pretty much in line with their overall assessment. I am happy if send as is to authors as it will help them shape a much better paper

Reviewer #1 (Significance (Required)):

The paper shows that very likely a new chemical with some potential for transmission inhibition of malaria parasites for mosquitoes binds to a Plasmodium protein that is specifically expressed in the sexual stages of the parasite.

The paper compares to good papers published in journals like ACS Infectious Diseases or Antimicrobial Agents and Chemotherapy, but I am not sure which of the Review Commons sister journals it would fit to. I am a molecular parasitologist.

Reviewer #2 (Evidence, reproducibility and clarity (Required)): Transmission blocking drugs are of high interest as a strategy to combat malaria but they are difficult to study. For instance it is problematic to raise resistant parasites to find mode of action of transmission blocking drugs and to identify their targets in the cell. In this manuscript Yahiya et al. build on previous work which identified the N-4HCS scaffold, of which DDD01035881 is the lead compound, as an inhibitor P. falciparum male gametocytes. Using PAL to enrich for target proteins Pfs16 was identified and validated as a possible target of DDD01035881. Binding was validated through CESTA. Determination of the phenotype following DDD01035881 treatment was found to partially match the previously published Pfs16 KO phenotype. However curiously no impact was seen in gametocytogenesis despite published evidence of Pfs16 being involved in sexual conversion. The authors speculate as to reasons but a direct experimental comparison with Pfs16 mutant parasites (which likely would have been revealing) is not provided. On the positive side, this analysis of the stage-specific effect of the drug pinpoint the stage inhibited during microgamete development which is a very interesting part of the manuscript.

We thank the reviewer for this positive assessment of our work. Mirroring comments above, our challenge with Pfs16 knockout or mutation is that if we ablate Pfs16 function we cannot assess the effect of drug action. Definition of a mutant that would demonstrate precisely the drug mode of action would require structural resolution of drug bound to target (i.e. to identify which residues to target) – this is a major goal for our research group moving forwards, but likely many years’ work. In general, our core approach here has been one of chemo-proteomic based methods and phenotypic investigation of the novel antimalarial. Further evidence might be forthcoming from molecular genetics/structural biology, but we believe these are beyond the scope of the current work (and our available resources at present). We state future directions in the discussion and can add more to this in any revised manuscript.

This work deepens the understanding of a novel class of transmission blocking drugs with reasonable potency (foremost (-)-DDD01028076, which has low nanomolar activity, the modified versions considerably less). Question on how to achieve serum concentrations for sufficient potency aside, these compounds will in the very least provide experimental tools to study their mode of action and might reveal interesting biology. This work is therefore of interest to the malaria field.

The experimental methodology seems excellent but some of the results raise questions that make definite conclusions difficult and this should be addressed. Overall, this is very solid work but leaves some doubts whether Pfs16 is indeed the (only) target of this class of compounds.

Major comments: 1. The reasons for excluding Etramp10.3 are not convincing. In fact it could be argued it is nearly as good a candidate as Pfs16. Contrary to the author's statements in the results section, etramp10.3 transcription is highly upregulated in gametocytes (see e.g. PMID: 22129310) with a generally very low transcription in asexual stages. It is argued that Etramp10.3 is essential in blood stages because MacKellar et al failed to disrupt the gene and because the PiggyBAC screen predicted it to be essential. However, if this is an argument for exclusion then this would also apply to Pfs16 which is also predicted by the PiggyBAC screen to be essential (likely both are non-essential in blood stages as they are barely expressed but Pfs16 and Etramp10.3 might by chance have not received an insertion in the PiggyBAC screen due to their very small size which may also explain failure of disrupting integration in MacKellar). Given the finding that the drug binds Pfs16 only in late gams it might also be argued that an essential function in asexuals might not be affected if they behave similarly to young gams and hence this criterion is not valid anyway.

Further following this line of thought that ETRAMP10.3 could be a hit equivalent to Pfs16, Figure 2D shows a band below the band considered to be Pfs16. It would not be all surprising if this were ETRAMP10.3 (the size would fit).

We don’t disagree with reviewer 2’s comments that ETRAMP10.3 could be an additional target. Although not traditionally related there is some similarity between these proteins and it may be that at the macroscopic level there is a structural homology between them. As stated elsewhere we are happy to tone down the assertion that Pfs16 is the only drug target candidate, leaving open the possibility of future follow up work that may yet reveal additional targets. This cannot be explored much further without extensive experimentation, which is beyond our current capacity. Given the strong phenotypic effect on gametocytes, whilst ETRAMP may be upregulated, this paper naturally focused its core attention on Pfs16 as a candidate target. We certainly subscribe to the view that absence of evidence is not evidence of absence.

Both, Pfs16 and ETRAMP10.3 can be expected to be very abundant proteins in the parasite periphery in gams. Can the authors exclude that these simply are the first to encounter the N-4HCS photoaffinity probe and that this may have led to their enrichment in the target identification experiments. The biochemical data argues for a specific interaction with Pfs16, but by itself is not that strong. Given the discrepancies of the phenotype with the Pfs16 disruption and the peculiar finding that the drug binds Pfs16 only in later stage gametocytes, it might be a good idea to further caution the conclusion of Pfs16 as the inhibited target.

We don’t necessarily agree that the evidence is not strong (three methods pointing to the same target is by many accounts solid evidence). Additionally, whilst it is true that the N-4HCS photoaffinity probes likely interact with PVM proteins in first instance, it is also worth noting that this doesn’t necessarily deduct from their likelihood to be true targets, but instead fits with the N-4HCS phenotype. We observe the compounds to inhibit microgametogenesis without any prior incubation and to retain this activity even beyond activation of microgametogenesis, specifically during the window in which the PVM remains associated with the parasite. Our phenotypic observations therefore fit with the notion that the molecules target proteins that lie within the PVM and interact with the molecules at first instance. Whilst we understand the concern that PVM proteins may be likely to be enriched given their abundance and localisation, we believe this to support our phenotypic findings.

The phenocopy evidence of the NH compounds with the Pfs16 disruption is based on comparison with published evidence. It would have been much preferred to have a side-by-side comparison with the (or an) actual Pfs16 disruption parasite line. Although the authors stress that the phenotype with DD01035881 fits the phenotype of the targeted gene disruption in the results, this only partially matches the cited publication (PMID: 14698439) which concludes there is an effect on the number of gametocytes produced. The exflagellation phenotype in that publication was classified as preliminary. Although this is discussed, the main results text should be adapted to reflect this and the conclusion that Pfs16 may be the target should be further cautioned.

As stated, we are happy to tone down conclusions in this direction. We also note comments above about Pfs16 disruption.

Minor comments: 4. From the modifications of the compounds it seems the chemical space for further modification to achieve higher potency is limited with this scaffold. Maybe the authors can comment whether they envisage this to be a potential obstacle.

The modification space of the compounds is explored extensively in previous work from our group, which we feel more than adequately addresses this question. See Rueda-Zubiaurre et al (2020) J Med Chem.

Line 67: references are superscript.

We can change this

Line 77: I would recommend replacing 'quiescence' here, a cell that matures is not quiescent.

We can change this

Line 116: consider removing 'interdisciplinary'.

We can change this

Line 120: I would caution here (see major comments) and recommend a less definite proclamation of Pfs16 as a promising new drug target

We can change this along with the general “tone” of the manuscript.

Page 7: compounds 9 is still considered active ("retained micromolar activity"), but in Table 1 this is given as >1000nM. Please add the actual IC50.

We can add this to the final version. The actual IC50 for this compound was 1.7uM. For the SAR study we grouped compounds with IC50 >1uM into discrete groups based on rough IC50 (>1uM, >10uM etc.) hence this fell in the intermediate group.

Line 138- 173: The order in which this is discussed makes it unclear that the work described was done prior to, and guided, the synthesis of compound 1 and probe 2

This can be addressed in a revised manuscript.

Line 194: was the data deposited in a database?

The proteomics data has not been deposited in a database but is accessible in the extended SI.

Line 202: introduction as to the benefits of using a competition + probe condition here could aid reader understanding. The interpretation of this data is complicated by the covalent and reversible binding of the two compounds and the weight of this control is therefore difficult to gage.

We can embellish the description here.

Table 2 and Extended Data Table 1 show different p values and enrichments for the same hits. This is confusing. It would also be useful to label the hits in the scatter plots in Figure 2 for easy identification and comparison to the tables.

We can amend this and label each hit within the scatter plot.

Line 215-218, please correct the data on Etramp10.3 (see major points) and put in perspective to Pfs16 (Etramp10.3 is similarly upregulated in gams where it is highly expressed; PiggyBAC predicts essentiality for Pfs16 and Etramp10.3 in blood stages).

We can discuss this to a limited extent for future exploration of Etramp10.3.

Line 221: the results from the PiggyBAC screen are stated as fact, but what the screen provides is a prediction of the probability of importance for parasite growth. I would replace 'is' with 'is predicted' (even though in the case of Rab1b it seems likely the prediction is correct).

We can change this

Line 233 and elsewhere: define 'reversibility' (binding? activity?).

We can change this

Line 240: clarify what is in the cited paper (see major points).

We can clarify this

Line 297: We utilised in-lysate...... clunky sentence, please rephrase.

We can change this

Line 325: reference is missing the year.

We can change this

Line 343: It is utterly puzzling that binding is specific to Pfs16 in mature gametocytes and I do not find the explanation in the discussion convincing (see point 28 below). Do the authors have another explanation? Could Pfs16 be modified in later gams (or vice versa)?

We believe that Pfs16 is functionally different at different stages of gametocyte development, this is either in terms of its presentation (e.g. perhaps due to complex formation, though this remains elusive) or the functionality of different domains, as per the effect of different truncation mutants. We can address some of these concerns in a revised manuscript.

Line 388: Justification seems odd as a PV protein would be unlikely to directly impact DNA replication. Please rephrase the sentence.

We can change this

Line 405: remove the 'to'

We can change this

Line 411: it would be useful to the reader to state at what IC-value the drug was used in these experiments.

We can state this

Line 431: While the alpha-tubulin staining indicates exflagellation and is similar to the DMSO only control, the staining for the RBC membrane (Glycophorin A) and DNA (DAPI) appear different, yet this is ignored. One interpretation of this could be that while late treatment doesn't block exflagellation, it still impacts other aspects of microgamete development.

We can make mention of this

Line 436: IFA work was done with drug treatment post activation while EM was done post activation but drug treatment prior to activation. Is there a reason for this?

The reviewer is astute to point this out. Limitations with access to the EM facility meant that whilst IFAs were completed for pre-activation treated samples, the post-activation EM became impossible as the EM facility closed during the COVID lockdown. Thus, we do not have a complete set here. However, we do not feel this takes away from the EM observations presented. We can clarify this incompleteness in the revised manuscript.

Line 450: is this really CytB, or was it CytD?

We did indeed used Cytochalasin B here, which whilst less potent than D does still target microfilament formation.

Line 465: Pfs16 localised to vesicles: there is no data showing the dots in the micrograph are vesicles, please rephrase.

We can change this

Page 19 and 20, discussion on stage-specific differences of Pfs16 during gametocytogenesis to explain the difference in binding: without experimental data using H-4HCS in the parasites of the publication cited to explain this (PMID: 21498641), this is very speculative. The cited work used episomal expression of Pfs16 tagged with fluorescent proteins. This would be the first integral PVM protein that is actually inserted into the PV membrane when tagged in that way (usually this results in a PV location), casting some doubt on the findings in that paper. All in all the provided explanation is not very convincing.

We can attempt to clarify this in a revised discussion.

Line 519: if with the conserved part the N-terminus is meant, then this has for other PVM proteins already been shown to be PVM internal, not facing the erythrocyte (show in very early work; PMID: 1852170 but also multiple times after that).

We can clarify this

Line 534: consider replacing 'highly plausible' with something more cautious.

We can change this

Line 550: Given this discussion how stable are N- 4HCS compounds?

We can clarify this.

Table 1: Having all chemical structures in same orientation would be nicer visually. I assume blue indicates modification but this is not stated.

We can change this

Figure 1: Please use different colours or symbols. The dark green crosses and the blue Pfs16 cross are hard to distinguish.

We can change this

Figure 3d: Unclear as to why a difference temperature range is displayed here.

We can clarify this

Figure 3e: Unclear % Inhibition compared to what.

We can clarify this

Figure 5G: What is the white arrow pointing to?

We can clarify this

Figure 5j: Given how the explanation is written this would make more sense between current image 5G and 5J.

We are not sure what the comment relates to here but we can endeavour to clarify this

Figure 6: Erythrocyte membrane colour not stated in legend.

We can change this

Figure 6A: were the exposure times similar? How can so little be left after ~4-5.5 minutes but at later time points there seems to be much more Pfs16 signal left? Maybe amount of signal should be taken into consideration to establish the fate of Pfs16 in the process.

We can endeavour to clarify this

Figure 6B: is the second phenotype (successful but aberrant egress) shown? The only image where WGA is not circular around the parasite is an exact match of Pfs16 which is in dots (image at 7.5-8.5 minutes). The imaging data for this phenotype should be presented more clearly.

We can attempt to clarify this

Reviewer #2 (Significance (Required)):

Nature and significance: a lot of weight has been placed on transmission blocking drugs although there are also a number of problems associated with them (ethics for testing and use etc; drugs acting on asexuals and transmission stages alike might be even more useful). Transmission blocking drugs are difficult to study and this work is therefore important. The experiments are well done, but the conclusions are not fully convincing, leaving some doubts in regard to Pfs16 being the actual target of the class of drugs studied.

Compare to existing published evidence: it is a logic continuation of previous work and this is appropriately highlighted in the manuscript.

Audience: medium interest for malaria researchers; high interest for researchers working on transmission blocking drugs and those studying microgametes.

Your expertise: malaria, P. falciparum, biology of apicomplexans

Reviewer #3 (Evidence, reproducibility and clarity (Required)): The manuscript by Yahiya et al describes an extensive investigation of the mode of action of DDD01028076, which specifically inhibits microgametogenesis in Plasmodium falciparum. The phenotypic characterisation of the MOA uses some very nice imaging to demonstrate the point at which this compound inhibits microgametogenesis. The authors have also attempted to identify the molecular target using chemoproteomics and label-free CETSA techniques. The photoaffinity labelling and pull-down approach suggested the Pfs16 may be preferentially enriched by a PAL probe that is representative of this series. However, the data supporting the validation of this target is not very conclusive, and in some cases argues against Pfs16 being a specific target of DDD01028076. Whilst the presented data makes a significant contribution to the literature regarding a novel drug candidate that targets microgametogenesis, it does not support the author's claims that Pfs16 is the target.

Major Concerns: The strongest evidence for Pfs16 being the target comes from the chemoproteomics pull-down study that found Pfs16 to be the most significantly enriched protein by compound 2 vs DMSO. However, this should be interpreted with caution as it is based on only 3 replicates and omics studies are prone to false-positives. That only 125 proteins were detected also raises questions about the coverage of the proteomics, it is quite possible that the actual target is not detectable using this method, and the Pfs16 appears because it is one of the more abundant proteins during this stage of the lifecycle.

As discussed, we are happy to tone down the conclusions about Pfs16 being an exclusive target for the N-4HCS drug class, however, we feel the reviewer is being unnecessarily negative. There are myriad papers in the literature based on singular proteomics experiments (given their cost, complexity and time -consuming nature) that then facilitate downstream experiments that support findings. We have endeavoured to be as thorough as we could in the work and believe, like others, three replicates of a massive experimental pipeline should be sufficient to make a defined conclusion – whether the additional downstream evidence we have then leaned on is supportive of this (as we judge it to be) is another matter. We agree, proteomics often suffers with low protein abundance. The complexity of growing large quantities of gametocytes is familiar to anyone who has struggled to grow these finicky parasites at a larger scale than 10-25mL dishes. Given the scales we have reached, we believe these might in fact be some of the most comprehensive proteomics studies to date!

Somewhat concerningly, the control with 1 as the competitor did not show significant enrichment of Pfs16, although a trend was observed. More concerning, was the lack of enrichment when using DDD01028076 as the competitor. This result essentially proves that Pfs16 is not the specific target (and the argument about reversibility is unlikely since most drugs are reversible binders, but many have worked with this type of approach). It is surprising that DDD01028076 (ideally the (-) form) wasn't used as the competitor for the proteomics study. This compound has ~100-fold better potency than the probe 2, which should provide much better competition that 1. It would also be more specific than 1, which is an important control considering that (-)-DDD01028076 has activity in the low nanomolar range, whereas 2 acts in the micromolar range. Non-specific interactions are an important consideration to exclude, and whilst 1 is structurally similar, it is not very potent and therefore not the best control to find the target associated with activity.

Whilst we understand the concerns with insignificant enrichment in the competition labelling, we believe the enrichment in the presence of photoaffinity probe 2 over background (i.e. DMSO vs. probe experiments) to be of more value given the design of the experiment. The competition experiments were performed by co-treating gametocytes with photoaffinity probe 2 and parent molecule 1 prior to UV irradiation, to enable irreversible conjugation to protein target(s). However, given that both compounds, probe and parent, theoretically bind to Pfs16 at the PVM in a reversible manner (i.e. losing interaction with even gentle washing), UV irradiation is likely to favour probe-binding irrespective of competition with a marginally more potent parent molecule (in this case, parent molecule 1). This is especially true as treated parasites were very thoroughly washed after irradiation, so should the parent molecule have bound the target protein(s), these drug-target interactions were likely lost during stringent washing. The drug-target interactions with parent molecule 1 wouldn’t have been aided by UV irradiation, as the molecule lacks the functional group required for bioconjugation. So, even if parent molecule-target interactions were more abundant than probe-target interactions, interactions between parent molecule 1 were most likely lost and proteins bound by probe were enriched.

This would have been true with more potent N-4HCS derivatives such and DDD01028076 and (-)-DDD01028076 (where potency is tested in the DGFA, independent of bioconjugation), and here we opted for a structurally similar compound of similar potency to not skew competition solely based on potency.

We can embellish on this in the revised manuscript to make our conclusions from this part clear.

A closer look at the gels in the supplementary data raises many questions that undermine the authors conclusions: - Fig S1a - The lane without probe (2) still identifies Pfs16 (or a protein at that MW) as the most abundant protein. Also, as the Pfs16 band increases, you can see that most other proteins also increase in abundance, so either the loading is inconsistent, or the probe actually causes non-specific enrichment of many proteins. This figure also indicates that the washing protocol is not sufficient to remove non-specific binders. Given the covalent nature of the PAL approach I would think a very thorough washing protocol could be employed.

It is certainly the case that Pfs16 is abundant in gametocytes, a reason behind its early discovery. Thus it is challenging to remove it from background. We still believe the enrichment to be specific, highlighting the comparative work with Pfg377 in Figure 2. Further repetitions with more stringent washing might resolve the background, however, this is beyond our current resources to repeat.

-- Running another negative control in the proteomics using one of the inactive controls from table 1 might help to disambiguate specificity.

We don’t disagree with this though this would involve an entire re-running of the experimental workflow which is not possible.

• Fig S2a - The anti-Pfs16 Western blots show that this protein is actually enriched more in the flow-through than the eluates. This shows that this protein is not specifically enriched by the PAL-CuAAC pull-down, it is just more abundant in the treated samples.

Again, the presence of Pfs16 in the flow-through is unsurprising, given its abundance in stage V gametocytes. The relative abundance in the eluate is not an indication that the binding and subsequent enrichment is not specific, rather this shows the compound does not necessarily bind each and every protein – which is not unexpected. The crucial conclusion to be drawn here is the concentration-dependent enrichment of Pfs16 in the eluate in the presence of probe.

• Fig S2b - The darkest Pfs16 spot is actually the sample with no UV treatment. This is a negative control, so should not enrich the target protein. This sample also has significant signal in replicates A and C.

As we have noted above, it is not unsurprising that modification of the N-4HCS scaffold to yield this probe may introduce a level of irradiation-independent binding, which explains the presence of signal in the UV-independent sample.

• Fig S2c - This blot is very messy and difficult to read, but in general the Pfs16 spots in the IGF don't correlate with the intensities in the anti-Pfs16 western.

These experiments are extremely challenging (something that is perhaps beyond the expertise of the reviewer) and what is presented is the result of substantial optimisation. Loss of AzTB fluorescence in the gel which is subsequently analysed by western blot explains this.

• Fig S2 - This data, and the main figures based on this data, generally don't support the hypothesis that Pfs16 is the specific target. The controls are not as would be expected, and there are no loading controls. Looking at the flow-throughs suggests that there was just more Pfs16 (and possibly total protein) in the treated samples before the enrichment step. The Pfg377 also appears quite variable in the different samples, with replicates B and C not consistent with A.

We do not concur with the reviewer here and their dismissal of what was extremely thorough and well-executed experimtns. These are not like traditional western blots and require substantial optimisation. We refer them to our previous point in reference to the UV controls. With regards to the Pfg377 variability, the experiment itself is inherently variable with such large volumes of parasites. In many cases, for example, the male:female ratio within a mature gametocyte culture can vary and this can contribute to the variability in 377 abundance between replicates.

The other major concern is with the CETSA analysis, which appears to show very minor stabilisation of Pfs16, but the specificity of this target is questionable, and the data has the following inconsistencies. - The supplementary data only shows n=1, yet there are error bars in the main figures. Where did these come from?

The individual western blot replicates can be provided in a revised manuscript if judged important.

• The samples with apparent destabilisation are all near the edge of large western blots, which often doesn't run straight and has no loading controls. We need to see the loading controls.

Given all proteins within a lysate will aggregate with thermal treatment, antibody loading controls are not feasible with these experiments. Each sample is normalised prior to thermal stabilisation (ensuring the same protein quantity is treated in both DMSO and drug, at each temperature) and any protein that is not aggregated is loaded – the nature of CETSA itself is to compare the stabilisation between DMSO and drug.

• The melting temperature of Pfs16 is extremely high at around 85 degrees C. Most plasmodium proteins melt at around 50-60 degrees (Dzekian et al, 2019). Even the cited work on membrane proteins didn't go to those temperatures (Kawatkar et al, 2019) Can this high temperature be explained, and has the CETSA approach been validated at such high temperatures where additional physical and chemical processes may be occurring in the sample?

We agree that this temperature of stabilisation is unusually high and may require further biochemical validation. Without further investigation we cannot say definitively why the melting temperature of Pfs16 is so high, but suspect its size and membrane localisation may play a role.

• The lack of difference between + and - isomers suggests that the very small stabilisation observed here is not specific to drug activity, but is more likely a non-specific binding effect. Additional negative control compounds might help here, but the + isomer is probably the best negative control (albeit the concentrations were not ideal in the presented data).

Please we have already addressed this in the text – refer to line 312 and beyond.

• The very high concentration (100uM) increases the chances of non-specific effects being observed here (especially since the authors claim to see stabilisation at about 10nM). The study should be repeated at lower concentrations (with negative controls) in order to confirm a specific binding effect.

Whilst further replicates with different conditions might be preferable, as discussed extensively here, this would be beyond the scope of what we are able to achieve for a revision.

• The concentration-ranging study was performed at 78.4 degrees, at which temperature very little denaturation of Pfs16 occurs fig S4a (and Fig 3b-c). Therefore, you would not expect to see any drug-induced stabilisation, and it is not plausible that significant stabilisation could occur at this temperature. Therefore, the apparent destabilisation at sub-10nM drug concentrations is highly questionable.

We would have to agree to disagree on this point.

• Stabilisation of Pfs16 did not occur in lysates from younger gametocytes (fig s4g-h), but this is a biophysical assay, so regardless of the function of this protein at different stages, the biophysical interaction between the drug and the protein should be the same regardless of the source of the protein. This data argues against Pfs16 being a specific binding target of Pfs16.

We don’t agree with this statement, since the drug is binding the protein in native lysate – this may be a multi-meric complex (homo or hetero) which only exists at certain stages. As such we disagree with the reviewer that this argues against Pfs16 being the target.

In addition to the above concerns, the fact that this compound doesn't inhibit the earlier functions of Pfs16 in gametocytogenesis, and that it doesn't inhibit P. berghei, also argue against this being the specific target of this drug. Whilst the authors have a valid argument that these findings don't exclude the possibility of stage-specific targeting of Pfs16, we could also argue that all the phenotypic data in figures 4-6 is merely correlative of a drug that acts at the same point in the lifecycle as Pfs16.

We have discussed this in the manuscript and strongly feel the reviewer is being unnecessarily dismissive of a body of work that is coherent. We are happy to tone down the narrative of the paper with Pfs16 being the exclusive target. Structural homology of P. berghei Pfs16 orthologues has never been done but it would not be unprecedented if another target was functionally homologous (an idea we are currently pursuing). Stage specificity is also possible given the nature of Pfs16 (e.g. if it is in a complex). The reviewer appears fixated on a singular entity and unable to imagine a complex scenario where structure or protein-protein interactions might affect drug binding (as it does with other proteins present in complexes, e.g. proteasomal targeting drugs).

Overall, I believe that significant additional studies would be required to identify the target of this compound. Either by repeating the included studies with additional controls and conditions, or by follow-up studies such as genetic manipulation (knock-down or overexpression) or heterologous expression and biophysical binding studies.

Alternatively, the manuscript could be restructured as primarily a report on the phenotypic effect of this compound on microgametogenesis, with the target identification work reported as a hypothesis-generating chemoproteomics study that provides some ideas about possible targets, but requires substantial follow-up to confirm the target (which may be beyond the scope of this report?).

We strongly disagree with this reviewer’s entire dismissal of an extensive body of work. In line with other reviewers comments we accept a need to tone down our conclusions, but do not consent to dropping the majority of the paper in favour of a phenotypic descriptive work.

MINOR COMMENTS The manuscript is very well-written and presented.

Several of the conclusions are overstated (as detailed above) and several statements should be tempered based on this data (e.g. statements linking DDD01028076 effects to Pfs16 function).

We can address the overstatement of conclusions in a revised manuscript.

I find the term 'crosslinking' confusing for the photo-affinity labelling, as crosslinking in proteomics often refers to crosslinking between proteins (not between protein and drug).

This is simple to address – to minimise confusion for readers, we can simply state where photoaffinity labelling and bioconjugation were performed (and not refer to the latter as crosslinking).

The data and terminology around activity (IC50) for compounds in table 1 is a little confusing. Some IC50 values are reported as >1000, while others have precise mean values reported over 1000, and others are >10,000 or >25,000. This is especially confusing where 9 is claimed to have retained activity, but is >1000. If consistent thresholds are not appropriate then perhaps including dose response curves in the supp data might be necessary to explain these?

We can simply provide the provide IC50s for compounds of greater potency. We are also happy to provide the curves but with such a large body of work already, this might be unnecessary.

Reviewer #3 (Significance (Required)):

The work is potentially interesting to Plasmodium biology and drug discovery researchers. The concept of a transmission-blocking drug is quite attractive to this community, so the topic is highly relevant. Keeping in mind that this compound was reported previously, the main novelty is in defining it's window of activity during the microgametogenesis process, and differentiating this from other drugs/compounds that inhibit this process. There is clearly an advance in knowledge presented here.

If Pfs16 were to be confirmed as the target of this series then I think that this study would have much greater impact and attract interest from a broad audience. However, at this stage I don't see strong evidence for this hypothesis, and some of this data casts significant doubt on the likelihood that Pfs16 is the direct target.

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Referee #3

Evidence, reproducibility and clarity

The manuscript by Yahiya et al describes an extensive investigation of the mode of action of DDD01028076, which specifically inhibits microgametogenesis in Plasmodium falciparum. The phenotypic characterisation of the MOA uses some very nice imaging to demonstrate the point at which this compound inhibits microgametogenesis. The authors have also attempted to identify the molecular target using chemoproteomics and label-free CETSA techniques. The photoaffinity labelling and pull-down approach suggested the Pfs16 may be preferentially enriched by a PAL probe that is representative of this series. However, the data supporting the validation of this target is not very conclusive, and in some cases argues against Pfs16 being a specific target of DDD01028076. Whilst the presented data makes a significant contribution to the literature regarding a novel drug candidate that targets microgametogenesis, it does not support the author's claims that Pfs16 is the target.

Major Concerns:

The strongest evidence for Pfs16 being the target comes from the chemoproteomics pull-down study that found Pfs16 to be the most significantly enriched protein by compound 2 vs DMSO. However, this should be interpreted with caution as it is based on only 3 replicates and omics studies are prone to false-positives. That only 125 proteins were detected also raises questions about the coverage of the proteomics, it is quite possible that the actual target is not detectable using this method, and the Pfs16 appears because it is one of the more abundant proteins during this stage of the lifecycle.

Somewhat concerningly, the control with 1 as the competitor did not show significant enrichment of Pfs16, although a trend was observed. More concerning, was the lack of enrichment when using DDD01028076 as the competitor. This result essentially proves that Pfs16 is not the specific target (and the argument about reversibility is unlikely since most drugs are reversible binders, but many have worked with this type of approach). It is surprising that DDD01028076 (ideally the (-) form) wasn't used as the competitor for the proteomics study. This compound has ~100-fold better potency than the probe 2, which should provide much better competition that 1. It would also be more specific than 1, which is an important control considering that (-)-DDD01028076 has activity in the low nanomolar range, whereas 2 acts in the micromolar range. Non-specific interactions are an important consideration to exclude, and whilst 1 is structurally similar, it is not very potent and therefore not the best control to find the target associated with activity.

A closer look at the gels in the supplementary data raises many questions that undermine the authors conclusions:

• Fig S1a - The lane without probe (2) still identifies Pfs16 (or a protein at that MW) as the most abundant protein. Also, as the Pfs16 band increases, you can see that most other proteins also increase in abundance, so either the loading is inconsistent, or the probe actually causes non-specific enrichment of many proteins. This figure also indicates that the washing protocol is not sufficient to remove non-specific binders. Given the covalent nature of the PAL approach I would think a very thorough washing protocol could be employed. -- Running another negative control in the proteomics using one of the inactive controls from table 1 might help to disambiguate specificity.
• Fig S2a - The anti-Pfs16 Western blots show that this protein is actually enriched more in the flow-through than the eluates. This shows that this protein is not specifically enriched by the PAL-CuAAC pull-down, it is just more abundant in the treated samples.
• Fig S2b - The darkest Pfs16 spot is actually the sample with no UV treatment. This is a negative control, so should not enrich the target protein. This sample also has significant signal in replicates A and C.
• Fig S2c - This blot is very messy and difficult to read, but in general the Pfs16 spots in the IGF don't correlate with the intensities in the anti-Pfs16 western.
• Fig S2 - This data, and the main figures based on this data, generally don't support the hypothesis that Pfs16 is the specific target. The controls are not as would be expected, and there are no loading controls. Looking at the flow-throughs suggests that there was just more Pfs16 (and possibly total protein) in the treated samples before the enrichment step. The Pfg377 also appears quite variable in the different samples, with replicates B and C not consistent with A.

The other major concern is with the CETSA analysis, which appears to show very minor stabilisation of Pfs16, but the specificity of this target is questionable, and the data has the following inconsistencies.

• The supplementary data only shows n=1, yet there are error bars in the main figures. Where did these come from?
• The samples with apparent destabilisation are all near the edge of large western blots, which often doesn't run straight and has no loading controls. We need to see the loading controls.
• The melting temperature of Pfs16 is extremely high at around 85 degrees C. Most plasmodium proteins melt at around 50-60 degrees (Dzekian et al, 2019). Even the cited work on membrane proteins didn't go to those temperatures (Kawatkar et al, 2019) Can this high temperature be explained, and has the CETSA approach been validated at such high temperatures where additional physical and chemical processes may be occurring in the sample?
• The lack of difference between + and - isomers suggests that the very small stabilisation observed here is not specific to drug activity, but is more likely a non-specific binding effect. Additional negative control compounds might help here, but the + isomer is probably the best negative control (albeit the concentrations were not ideal in the presented data).
• The very high concentration (100uM) increases the chances of non-specific effects being observed here (especially since the authors claim to see stabilisation at about 10nM). The study should be repeated at lower concentrations (with negative controls) in order to confirm a specific binding effect.
• The concentration-ranging study was performed at 78.4 degrees, at which temperature very little denaturation of Pfs16 occurs fig S4a (and Fig 3b-c). Therefore, you would not expect to see any drug-induced stabilisation, and it is not plausible that significant stabilisation could occur at this temperature. Therefore, the apparent destabilisation at sub-10nM drug concentrations is highly questionable.
• Stabilisation of Pfs16 did not occur in lysates from younger gametocytes (fig s4g-h), but this is a biophysical assay, so regardless of the function of this protein at different stages, the biophysical interaction between the drug and the protein should be the same regardless of the source of the protein. This data argues against Pfs16 being a specific binding target of Pfs16.

In addition to the above concerns, the fact that this compound doesn't inhibit the earlier functions of Pfs16 in gametocytogenesis, and that it doesn't inhibit P. berghei, also argue against this being the specific target of this drug. Whilst the authors have a valid argument that these findings don't exclude the possibility of stage-specific targeting of Pfs16, we could also argue that all the phenotypic data in figures 4-6 is merely correlative of a drug that acts at the same point in the lifecycle as Pfs16.

Overall, I believe that significant additional studies would be required to identify the target of this compound. Either by repeating the included studies with additional controls and conditions, or by follow-up studies such as genetic manipulation (knock-down or overexpression) or heterologous expression and biophysical binding studies. Alternatively, the manuscript could be restructured as primarily a report on the phenotypic effect of this compound on microgametogenesis, with the target identification work reported as a hypothesis-generating chemoproteomics study that provides some ideas about possible targets, but requires substantial follow-up to confirm the target (which may be beyond the scope of this report?).

Minor comments

The manuscript is very well-written and presented.

Several of the conclusions are overstated (as detailed above) and several statements should be tempered based on this data (e.g. statements linking DDD01028076 effects to Pfs16 function).

I find the term 'crosslinking' confusing for the photo-affinity labelling, as crosslinking in proteomics often refers to crosslinking between proteins (not between protein and drug).

The data and terminology around activity (IC50) for compounds in table 1 is a little confusing. Some IC50 values are reported as >1000, while others have precise mean values reported over 1000, and others are >10,000 or >25,000. This is especially confusing where 9 is claimed to have retained activity, but is >1000. If consistent thresholds are not appropriate then perhaps including dose response curves in the supp data might be necessary to explain these?

Significance

The work is potentially interesting to Plasmodium biology and drug discovery researchers. The concept of a transmission-blocking drug is quite attractive to this community, so the topic is highly relevant. Keeping in mind that this compound was reported previously, the main novelty is in defining it's window of activity during the microgametogenesis process, and differentiating this from other drugs/compounds that inhibit this process. There is clearly an advance in knowledge presented here.

If Pfs16 were to be confirmed as the target of this series then I think that this study would have much greater impact and attract interest from a broad audience. However, at this stage I don't see strong evidence for this hypothesis, and some of this data casts significant doubt on the likelihood that Pfs16 is the direct target.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary: * Saha et al. characterize Drosophila egg chambers that are mutant for cup and identify an increase in the number of a specialized type of follicle cells, the border cells. They demonstrate that this increase correlates with an expanded domain of STAT activity and reduced Notch signaling in anterior follicle cells. Determining that cup is required in the germline cells, the authors postulate and provide some evidence that cup mutants prevent germline Delta from properly signaling to follicle cells. In line with this, they also show that blocking endocytosis phenocopies some aspects of cup mutants, particularly border cell numbers and Delta levels, which they monitor cytoplasmically and at the cell surface. Lastly, they demonstrate that activation of Rab11 can rescue Delta levels and border cell number in cup mutants. They conclude that a key function of Cup in the germline is to traffic Delta to signal to follicle cells, and that the endocytic processing of Delta is required for its function.*

Major comments:

• The findings of this study are interesting and novel. The authors have completed a lot of experiments and analyzed the results carefully and in great detail. Experimental design is described adequately and statistical analysis is sufficient. While the main results are largely convincing and support the conclusions, there are some weaknesses that need to be addressed.*

Response: We thank the reviewer for appreciating our work and we have tried to address concerns of the reviewers to the maximal possible extent with the hope to strengthen our claims further.

One major concern is that the vast majority of the experiments were conducted with a single homozygous allele for cup. The authors claim this was necessary because other alleles arrest oogenesis, which is understandable, but it leaves the potential problem that the allele, a P-element insertion, may affect other genes, or there may be other unidentified mutations on the mutant chromosome. The authors are able to partially rescue the border cell phenotype with overexpression of Cup and can also mimic the outcome with RNAi in the germline, which helps alleviate some of this concern, but this was only done for one set of experiments (those in figure 1). Similar experiments need to be included to demonstrate the same outcomes when cut is disrupted by other alleles/methods for at least some of the Notch/Delta analyses since this is key to the paper's conclusions.

Response____: We acknowledge the concern raised by reviewer and to address it, we evaluated different allelic combination of Cup to rule out issues with background mutation. We evaluated the Delta count, NICD and border cell numbers in a different allelic background of cup8/ cup01355. Satisfyingly we observed similar results like that observed for cup01355/ cup01355 homozygotes. This result is included as (Fig S1E-G)

In addition, we have specifically downregulated Cup function in the germline employing the RNAi approach and validated the non-cell autonomous effect of Cup function in border cell fate specification. This result is included in (Fig 1M-O)

A second concern is that some evidence is circumstantial or indirect. Specifically, the authors argue that the effect of Cut is due to trafficking of Delta, but do not consider the possibility that Delta could be more directly regulated or that other factors may be relevant. Border cell specification is rescued by increasing recycling in cup mutants, but this could be due to recycling of more factors besides Delta. To address this more directly, the authors should overexpress Delta in the germline of cut mutants. It is possible the disruption of Delta in cut mutants is due to changes in Delta protein stability/levels, so the experiment may also clarify this issue. If this is the case, it may be that hypomorphic Delta mutants would have a defect on border cell number, which could be examined separately. If Delta levels are low, endocytosis and recycling increases may also rescue cut mutants indirectly, but the conclusion about what Cut regulates may differ.

Response: As per the suggestion of the reviewer, we did attempt to over express Delta in the germline of cup mutants egg chambers. Unfortunately, we couldn’t record any Delta overexpression as the available vector (UASt- Delta) can drive stable expression only in the somatic cells but not in the germline cells. However, to check out the possibility if Delta was being directly regulated by Cup, we compared the levels of proteins between wild type and Cup mutant egg chambers (Figure 4E-G). Unlike our expectation we didn’t observe any significant differences in the levels of Delta in Cup compared to the control. This kind of supports our belief that Cup may not be directly regulating the levels of Delta in the germline.

Another concern is that Cup's main role is a confusing since it regulates many things, including cytoskeleton and cytoskeleton is necessary for general health and vesicle trafficking in the egg chamber - how do the authors think Rab11 upregulation is overcoming these defects?

Response: We appreciate the reviewer for raising this concern as it kind of intrigued us to examine if the overexpression Rab11CA was rescuing the cytoskeleton too. Interestingly, we observed that Rab11CA overexpression restored the actin filament in Cup mutant germline(figure S6H-K). This result is in line with report that Rab11 effector Nuf can modulate actin polymerization (Jian Cao et al.,2008).

Rab11CA rescues Delta levels almost completely in cut mutants but only partially rescues Notch activation, suggesting there are other problems in these egg chambers that could contribute to the defects. While exploring possible other factors is beyond the scope of this work, the authors may want to acknowledge this issue.

Response: We do agree with the reviewer that we only observe partial rescue of the NRE GFP with Rab11CA, it suggests that Cup can affect different aspect of egg chamber development independent of Rab11 function.

Minor comments:

It would help the presentation of the paper to introduce Notch/Delta signaling during oogenesis in the introduction. More introduction and clarity about the number of polar cells at early stages and their role in the border cell cluster may also be useful to the reader.

Response: We have modified the introduction to highlight the role of Notch/ Delta signaling in early oogenesis.

It is notable that the primary phenotype of a change in border cell numbers is quite subtle, often only affecting 1-2 cells, and the variation in different genotypes and experiments is sometimes also that large. The authors do a good job of being careful to count the cells at a specific developmental time and do appropriate statistical tests within an experiments. Still, it difficult to be sure that the effects are due to the gene being manipulated specifically or the genetic background. Related to this, a few issues should be addressed. Notably, at earlier stages, Notch signaling impacts cell division, so some of the phenotypes might be explained by there being more total cells in the domain instead of more signaling. The authors show Cut is in the same domain and pH3 is similar, but they didn’t seem assess overall numbers.

Response: As per the suggestion of the reviewer, we assessed the total number of follicle cell nuclei in stage 8 egg chambers. This analysis was done each confocal z slide of the egg chamber taking care that each nuclei (DAPI) was counted only once. Satisfyingly we didn’t observe any significant difference in the number of follicle cell nuclei between wild type and cup mutant egg chambers supporting our earlier claims with pH3 and Cut antibody that cell proliferation is not responsible for the excessive border cell fate in Cup mutants. This result in included in (Fig S2O-Q)

Secondly, for the stat suppression of cut (figure 2L), the authors need to show the stat-/+ control for comparison to make a conclusion about suppression versus additive effects.

Response: As per the suggestion of the reviewer, we have included the data for statp1681/+ control in figure 2L.

In addition, prior work (Wang et al 2007) expressed DN Kuz in border cells and did not see a change in specification, unlike what is claimed here. In the experiment in question, the control has lower than normal numbers of border cells and the DN Kuz has a number more typical of the controls in other experiments- so this is a concern that there is something else in the genetic background influencing the numbers. Other controls could help make this case, but ultimately this result is probably not necessary for the main argument. Thus the authors might consider leaving it out the Kuz analysis or perhaps can comment on the discrepancy with prior published results.

Response: We have removed the data on Kuzbanian and have added data that suggests that Notch activation in the follicle cells downstream of Cup facilitates specification of appropriate number of migratory border cells (Fig 3K-N).

Can the authors comment on why the volume of the border cell cluster increases more dramatically (>2x) than the number of cells (30% more)? * Does the increase in border cell number change the migratory capacity? That is, do the clusters in cut mutant egg chambers migrate normally while the egg chamber looks okay?*

Response: We believe that dramatic increase in the volume of the border cell cluster I (>2x) than the number of cells (30% more) is due the loose arrangement of the cells in the border cell cluster. Interestingly, the cup mutant border cell clusters do exhibit migration defect that we are examine as part of separate study.

Several of the figure legend titles state conclusions that are over interpretations of the data shown:

- Figure 3 legend is overstated- these experiments do not assay STAT activity, only border cell number, so the title can be simplified to say that.

Response: We have modified the Figure legend in line with the data presented.

- For figure 4, both cytoskeleton and Delta are shown to be disrupted in cup mutants, but they are not directly linked, eg, the experiments do not show a change in Delta in cytoskeletal mutants alone. While it is interesting that cup mutants have disrupted cytoskeleton, ultimately this result is not well connected to the main issue of Notch/Delta signaling; in fact, it becomes confusing how anything can be trafficked to the cell surface if there is poor cytoskeletal organization. Since the authors favor the hypothesis that the cytoskeleton is not the key to the border cell specification difference, they may want to move this result out of figure 4.

__Response: __We have included the data that suggests that cytoskeleton organization is critical for Delta trafficking. Specifically we demonstrate that treatment of egg chambers with Cytochalasin D exhibits accumulation of Delta in the nurse cell cytoplasm (Fig S5D-F).

- The Figure 5 legend is also overstated- these experiments show that Delta is higher in cup mutants and endocytosis mutants AND that endocytosis (of something) is required in the germline for border cell number- but these results are not linked in this figure. More evidence for this connection does come later in figure 6. * Some figure legends are quite brief and could benefit from a little more detail on what is being shown*.

__Response: __We have modified the title of the Figure legends with respect to data presented.

Figure layout could be improved by keeping images consistent sizes and making sure graph text is large enough to read easily. Figures in general could be streamlined by having negative results and less pertinent results in supplemental data.

Response: We have reorganized the figures and worked on the graph text for easy read.

Not all papers cited in the text are in the reference list.

Responses: We have modified the title of the figure legends and cross checked our reference list with the papers mentioned in the main text.

CROSS-CONSULTATION COMMENTS

I generally agree with the other reviewers that there are concerns with the precise function of cup in this context, and that some revision is needed, including editing of the writing. In response to reviewer 2, prior published studies only detected Cup in germline, but it is possible that it is expressed in follicle cells at a low level. The mutant clonal experiment in follicle cells that the authors did had no effect on border cells, so that provides some evidence the role is non-autonomous. I agree with reviewer 2's concern that the authors overstate the connection between cup and Delta and border cells based on their data and need a few more experiments to tie things together. I understand reviewer 3's concerns that the experimental effects on border cell numbers are very small and variable- I listed this as a minor concern, though, since this number is mainly being used as a read-out for STAT signaling levels and the data were extensively quantified and statistically tested.

Reviewer #1 (Significance (Required)):

My expertise is in cell migration, developmental biology, and Drosophila genetics. This paper will be of broad interest in these fields as it incorporates aspects of each in its characterization of a new regulatory mechanism to induce a motile cell population non-cell-autonomously, which is an exciting finding. Specifically, the work increases our understanding of the intersection between Notch and Jak/STAT signaling, which many researchers study - these were both known to be involved in border cell specification. The study provides more detailed characterization of the signaling and specification process in general, and makes significant advances in understanding how Delta signals are produced and presented from germline cells to receiving cells in the soma. Cut has not been previously implicated in these signaling pathways, so that is also novel, although its precise mechanistic role here is still somewhat unclear.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this manuscript, Saha et al. made a detailed description of the role of the mRNA binding protein Cup in specifying the number of Border Cells (BC) during Drosophila melanogaster oogenesis. First of all, they show that females homozygote for a hypomorph allele of cup have higher number of BCs compared to Wild Type (WT) females. They present a series of experiments that points towards the phenotype being due to a specific role of cup in the nurse cells that non-cell autonomously regulates BC specification. Also, they show that this phenotype is the result of an increase in the levels of JAK/STAT signalling in the BC, a major determinant of BC

fate. In addition, they show that cup mutant egg chambers exhibit a downregulation of

the Notch (N) pathway function in the BCs and that over-activating Notch results in the rescue of the number of BCs. Moreover, the authors present data on the effect of cup in Delta (Dl) trafficking in the nurse cells: They found that cup mutant egg chambers show increased number of Dl puncta within the cytoplasm of the nurse cells, but reduced numbers in the nurse cell-Anterior Follicle Cell (AFC) boundary as a result of defective Dl endocytosis. Finally, they were able to rescue the Dl trafficking phenotype, as well as the number of BC by overexpressing an active form of Rab11.

Mayor points:

In this study, the authors employed an hypomorph allele of Cup to generate egg chambers where both germline and somatic cells are mutant for Cup. They did a series of experiments to try to demonstrate that the Border Cell (BC) specification phenotype they observe is non-cell autonomous and that is due to the Loss of Function (LOF) of Cup exclusively in the nurse cells. Although I appreciate the difficulties of eliminating or reducing the levels of Cup specifically in the nurse cells only during mid-oogenesis, I feel like this is key to be able to claim that this effect of Cup in BC specification is really non-cell autonomous. The reasons why I still have some doubts that there might be some cell autonomous effects in the FCs are the following:

o The authors show that cup01355 mutant egg chambers have a phenotype in Dl trafficking. Although they analysed in detail the effects on Dl in the nurse cells, their images show that there might be a defect in Dl levels/trafficking in the Follicle Cells (FCs) as well (Fig5A-B). It has been shown that Dl mut FCs have reduced levels of Notch activity due to reduced lateral inhibition (Poulton et al., 2011), so there is a possibility that the reduced levels of Notch activity in the cup01355 egg chambers might be due, partially, to defects in Dl trafficking/levels in the FCs, rather than in the nurse cells. o The authors tested the role of the Notch pathway in the cup mutant phenotypes by measuring the number of NICD puncta in the signal receiving cells as proxy for Notch activity (Fig4). Although I understand the rationale, I am not convinced that they can completely rule out that the changes in NICD puncta number in FCs is not due to some effect of cup LOF on Notch trafficking in these cells.

o In figure 6, the authors show that expression of a constitutively active form of Rab11 specifically in the nurse cells restores the BC number to that of the WT. However, the levels of Dl particles and, especially the levels of NRE-GFP expression, remains slightly lower than in the WT conditions.

Response: We do agree with the reviewer that we only observe partial rescue of the NRE GFP with Rab11CA, it suggests that Cup can affect different aspect of egg chamber development independent of Rab11 function. This has been acknowledged in the main text and it now reads as “We did note that irrespective of partial rescue in the levels of NRE-GFP and Delta puncta count, a complete reversion to wild type border cell numbers was observed when Rab11CA was overexpressed in the cup mutant germline. This may suggest either that border cell fate specification is quite robust beyond a certain base level of signaling or Cup may affect other aspects of egg chamber development independent of Rab11 function.”

One of the main conclusions of this study is that cup regulates BC specification through a non-cell autonomous mechanism that involves communication between nurse cells and AFCs. For that reason, I think in order to conclusively say that, the authors need to try to remove the function of cup specifically in the nurse cells. They mentioned they have tried different ways of doing this unsuccessfully, but do not specify how they have tried. I suggest using the cup-RNAi line combined with a nurse cell specific Gal4 and a ubiquitous gal80ts line (tub-Gal80ts), if they have not try this. I do not expect the authors to repeat all the experiments with this condition, but at least they should test the main findings i.e. number of BCs, JAK/STAT overactivation and Notch attenuation.

Response: To further support the non-autonomous role of Cup in border cell fate specification, we down regulated Cup function in germline nurse cells employing Mat-alpha GAL4 and Cup RNAi. Since Mat-alpha GAL4 driver has weak expression in the nurse cells of early stage chambers, it enabled us to evaluate Cup function during mid oogenesis. Consistent with our expectation, we observed higher number number of border cells in the migratory cluster compared to the control supporting our conclusion that germline Cup modulates the number of adjacent anterior follicle cells that acquire migratory border cell fate. The above results are included in (Fig 1M-O). In addition over expression if Cup cDNA in the anterior follicle cells failed to the rescue the excessive border cells observed in the Cup mutant egg chambers supporting the germline role of Cup further. This result in included in (Fig S1L-O).

• The authors have shown in Figure 3 that there is a decrease in Notch signalling in the AFCs in cup01355 egg chambers. In order to test that the BC number phenotype observe in this condition is due to that effect on Notch signalling they have done a rescue experiment using the antimorphic Notch allele Nax-16. Since in this condition all cells (nurse cells and FCs) have increased levels of Notch, they cannot conclusively say that the increase in Notch function in the FCs rescues the cup

phenotype. If they want to show that the function of Notch is specifically needed in the FCs, they should over-activate Notch exclusively in the AFCs. For instance, they could express a constitutively active form of Notch, such as UAS-NICD (Go et al., 1998) or UAS-NDECD (Fortini et al., 1993), specifically in the AFCs. Otherwise, they should re-write the text since they cannot conclusively say that the increase in Notch function in the FCs rescues the cup phenotype.

Response: Following the suggestion of the reviewer, we attempted over expression of NICD in the follicle using driver slbo-GAL4 in the cup mutant background. Gratifyingly, we observed rescue in the border cell fate of Cup mutant egg chambers. However, we didn’t observe any rescue in the morphology of nurse cell nuclei of Cup mutants. This supports our conclusion that increase in Notch function in the FCs rescues the cup phenotype with respect to the border cell fate only. (Fig 3K-N).

• The authors had made a great effort to prove that proper Delta endocytosis in the nurse cells is essential for adequate Notch signalling in the AFCs and right number of BCs recruitment. Specifically:

o They checked the consequences on Dl trafficking of down-regulation of rab5 or auxilin, but they did not test the effect in BC numbers * o They show that downregulating the function of shi affects the number of BCs, but did not show the effect of this condition in Dl trafficking. * Consequently, they cannot conclusively say that effects on trafficking of Dl affect number of BCs, since they haven't really tested both effects on the same background. I think that for simplification, they should test both, effects on Dl trafficking and number of BCs in one of those genetic backgrounds and leave the other two for supplementary material. Alternatively, they should re-write their conclusion for this section.

Response: As Rab11GTPase over expression rescued the excessive border cell fate in the cup mutants, to test the specificity we downregulated Rab11 function in the germline itself to check Delta trafficking and border cell fate specification. We employed a late expressing GAL4 driver in the germline and observed that down regulation of Rab11 function resulted in more number of follicle cell acquiring border cell fate and decrease in the number of Delta puncta at the interface of Anterior follicle cells and nurse cells. This phenotype is reminiscent of the Cup mutants suggesting that perturbing the recycling component of endocytosis perse affects border cell fate and Delta trafficking. This result in included in (Fig 6D-I)

• Their results clearly show that Dl accumulates in puncta, suggesting that there might be a defect in Dl trafficking, and although their rescue experiments point towards an scenario where Rab11-dependent Dl recycling is being affected, I think there are some weak points on their arguments. The fact that Rab11-KD does not generally affect Notch signalling in the FCs, as shown in (Windler & Bilder, 2010) argues against their conclusion that the effect of cup in nurse cells on Rab11 function is responsible for the defects in Dl trafficking and, subsequently, on Notch activity in AFCs. An alternative explanation is that Rab11 overactivation in the Cup mutant background compensates for a different defect on Dl trafficking, for example, Rab4-dependent recycling pathway. Another possibility is that AFCs could be specially sensitive to changes in Rab11-dependent Dl trafficking defects in the nurse cells. To distinguish between these two possibilities, they should perform some of the following experiments:
• o First of all, there are a number of endosome markers that can be used to check in which step of the endocytic route Dl is being accumulated, including (but not limited to) anti-Rab11 antibody, anti-Rab5, anti-Rab7, tub-Rab4-mcherry. They should do co-localization experiments with Dl and endosomal markers.*
• o Also, they could check what happens to the number of BCs and Dl trafficking when Rab11 function is blocked in the nurse cells, in a similar way to what they did with Auxillin, Rab5 and Shi. They could use some of the tools described in (Satoh et al., 2005)*

Response: We have perturbed Rab11 function during mid oogenesis which is quite distant from early stage egg chambers examined by Windler & Bilder. We observed that down regulation of Rab11 activity in germline affects both border cell fate in the AFCs and Delta trafficking in the germline itself. Protein Trap analysis of Rab11 in wild type and Cup mutant background suggests Rab11 is enriched in the trans-golgi network where the activity of Rab11 is modulated through nucleotide exchange. Over all our results suggest that Rab11 activity is diminished in the cup01355 egg chambers and thus stimulating the recycling endocytosis restores Notch signalling in the AFCs, limiting JAK-STAT activation and restricting BC cell fate specification.

• The authors final model is one in which cup in the nurse cells regulates Rab11 function to ultimately control JAK/STAT signalling in the AFCs. However, they have not looked at the status of JAK/STAT signalling in their Rab11-CA rescue experiments. I think this experiment will really round-up their work.* Response: The border cell fate is linked to activation of JAK-STAT signaling in the anterior follicle cells. As we have already exhausted the STAT antibody, it will difficult to access the levels of STAT perse.

Minor points:

• The authors tested if the extra BC phenotype observed in the cup mutant egg chambers is due to defects in FCs endoreplication. I have two questions related to this section.*

• o First of all, I do not understand the rationale behind this idea that defects in FCs endoreplication would result in extra BCs. Please explain and add any relevant references.*

• o Secondly, they say that they used Cut and Phospho-Histone3 as endoreplication markers. I believe that what they mean is that the absent of these two markers indicates that FCs have exit the cell cycle and enter the endocycle (Sun & Deng, 2005), however they are not markers of endoreplication. Please, re-write to make this clear.*

Response: The follicle cell exhibits a switch from mitotic to endocycle phase at a particular stage of oogenesis (Sun & Deng’ 2005). Our premise is that incase this switch is delayed, will the extra proliferation can account for the excessive border cell fate? In this context we have modified the text to render clarity to this section.

• The authors tested whether the levels of Notch activity were altered in the cup mutant egg chambers. For that, they used an NRE-GFP construct that shows a clear reduction in the levels of Notch activity in the AFCs. They also used the number of NICD and NECD puncta in signal receiving and sending cells respectively, as proxy of Notch activity. Although I understand the rationale, there are other explanations for this phenotype as discussed above. Thus, if they want to have an alternative way of showing the dampening of Notch signalling, they could use the levels of expression of well characterised targets of Notch in the FCs, such us hnt and E(spl)mb-CD2 or E(spl)m7. Response: We believe that our new set of data with NICD over expression (in the AFCs) rescuing border cell fate in Cup mutants coupled with NRE-GFP, NICD, NECD data now lends stronger support to our claim that Notch signaling in the follicle cells is indeed downstream of Cup function in developing egg chambers.

• In M&M the authors explain that NRE-GFP levels were expressed in Fold change. However, in figure 3C the units of the graph are Fluorescence Intensity in a.u. Please,*

check this small inconsistency

Response: We have modified this as per reviewer’s suggestion.

• In figure 4, they show the quantification of tubulin fibres within the nurse cells, however they are missing a similar analysis of Phalloidin (Pha) fibres/levels. I think this experiment and figure will be more complete if the authors added such a quantification of the effects of cup LOF in Pha distribution. Also, the authors do not show the single Pha channel in Fig4C, which would greatly helped to appreciate the differences between the WT and Cup LOF nurse cells. I suggest modifying the figure to better show the changes in Pha distribution. Response: We have modified the figure and included quantitation of actin fibre length in Supplementary figure 6H- K.

• In figure 4F-G the authors are showing the general effect of cup LOF in Delta distribution. They indicate with yellow arrowheads the cytoplasmic Dl puncta accumulation in the nurse cells, however it is almost impossible to see such puncta with that level of magnification/resolution. I suggest removing the arrowheads, since the figure 4H-I shows the same puncta more clearly. Response: We have modified the figure to render clarity

• In the Dl trafficking experiments (Fig4 H-I,K,L and Fig5A-C), the authors measured the number of puncta in the anterior nurse cell-follicle cell junction. In order to do those types of quantifications they need to be able to tell the cell boundaries that separate FCs from the nurse cells. Please, clarify the criteria for determining if the puncta are within the FCs or the underlying nurse cells. Response: Delta, NICD, NECD proteins marks the apical surface of the follicle cells. We used this as a reference to segregate nurse cell puncta with respect to follicle cells. This has been elaborated in the Material & Method section.

• In figure 6C-D the authors show example images of egg chambers expressing Rab11-CA-YFP using the germline specific nos-Gal4. However, in the images it looks like the YFP signal is coming from the surrounding stretched FCs. Please check that these are the right images or explain the inconsistency.

Response: We have crosschecked the images and the YFP signaling is from nurse cell periphery which gives the wrong impression that it is from stretched follicle cells.

• In figures 1R, 2L, 3Q, 6I, 6M, the authors should show the results of the statistical analysis between all the conditions tested. I think that this is crucial to be able to tell whether some of the rescues are complete or only partial. *Responses: To avoid cramming the Figures, we have including some of the p values in the Figure legends. *

• Line 174: should say "mutant egg chambers".*
• Line 281: There is a reference that is missing from reference list: Liu et al., 2010;*
• Line 292: The reference for the NRE-GFP construct is not the correct one, since that references to a review article. Please, add the correct reference.*
• In line 462 of the manuscript you have a reference that is missing from your reference list.*
• In line 394 the authors say: "protein, it's enrichment in the cytoplasmic fraction of the cup mutant egg chambers", but I think that they meant mutant nurse cells.*

Response: We have modified the text as per the all the suggestions above Reviewer #2 (Significance (Required)):

The BC migration is an excellent model to study collective cell migration and how epithelial cells can acquire migratory behaviours. After years of study, there is good understanding of the signals and genetic circuits that regulate BCs specification and migration (Montell et al., 2012), but there are not many studies, to my knowledge, that describe a role of nurse cells in specifying or guiding the migration of these cells. Thus, this study by Saha and colleagues is one of the first studies that show a role for nurse cells in specifying the number of BCs.

My field of expertise is in cell-cell communication through different pathways, including Notch and Integrin signalling. I have studied the role of endocytosis in regulating Notch signalling in various contexts, including follicular epithelium in Drosophila ovaries.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This manuscript describes an investigation into the signaling that induces the differentiation of follicle cells into border cells in the Drosophila ovary. Previous studies have established the border cells as an informative model for studying how epithelial cells delaminate and undergo collective cell migration, and have identified the JAK-STAT and Notch pathways as important regulators of the process. Here, the authors performed a forward genetic screen and identified cup as another gene that is involved in the regulation of border cell differentiation. Their findings are consistent with a model in which cup is required in germ cells for the endocytosis of the Notch ligand, Delta. In cup mutants, impaired trafficking of Delta leads to decreased Notch signaling in follicle cells, which allows for increased JAK-STAT expression in follicle cells and an increase in the number of follicle cells that differentiate into border cells. Overall, the approach is thorough and the phenotypes are clear and well-described. The quantification of phenotype penetrance and of aspects of the images, such as pixel intensities and the number of particles in a region is a strength of the paper. The use of multiple independent methods to test key points is another strength. However, there are several concerns that should be addressed before the paper is considered for publication:

• 1. The central phenotype that this paper is based on is a difference in the number of border cells per cluster in wildtype and mutant genotypes. However, this phenotype is fairly subtle in some cases (e.g. in Fig. 2L, it varies by only about 10% between control and mutant) and it is somewhat variable. For example, the number of cells in border cell clusters of the controls range from 4.49 in Fig. 3M to 6.41 in Fig. 1F. Considering that the mutant values fall within this range in some cases (e.g. 5.98 in Fig 3M) and the difference between the means from control and mutant genotypes is often less than two, the significance of this phenotype is unclear. How does this compare to other mutants that have been described to affect border cell specification? Are there any consequences for the differentiation of the follicle or the function of the egg caused by this defect?*

Response: We are using the border cell number as readout for the output of JAK-STAT signaling. Though the difference in numbers may appear to be subtle, we believe our data clearly demonstrates that Cup non cell autonomously regulates border cell fate by modulating Notch signaling in the follicle cells*. *

• Wang, et al. (PMID 17010965) have described previously that Notch signaling, and*

Kuzbanian specifically, is required for border cell migration. The authors should cite this paper and discuss their findings in light of this study. For example, if Notch signaling is impaired in cup mutants, is border cell migration also impaired? Likewise, the citation of the Assa-Kunik, 2007 study as evidence that Notch and JAK-STAT signaling act antagonistically (Line 286) is a bit of an oversimplification. While that study does show that Notch and JAK-STAT act antagonistically at earlier stages of follicle development, Fig. 6 of that paper shows that a Notch reporter and a JAK-STAT reporter are both expressed concomitantly in border cells of a Stage 10 follicle and in the anterior follicle cells of what looks like a Stage ~8 follicle. The authors should discuss the apparent contradiction between their findings and this study.

Response: We provide genetic evidence to support our claims that Cup in the germline modulates Notch activation in the anterior follicle cells thus limiting border cell fate specification to a few. The overlap in the expression of Notch reporter m7-lacz and STAT in the follicle cells and border cells is interesting and will need further investigation in real time to decipher any comparison between the two studies.

• Lastly, the manuscript contains many grammatical errors, incomplete sentences, improper punctuation and spacing, and informal writing, such as the use of contractions. It should be thoroughly edited for content and clarity.*

Response: We have tried to edit the manuscript with the aim to improve on the language, grammar and punctuations.

Reviewer #3 (Significance (Required)):

Although the identification of cup as a contributor to the regulation of border cell differentiation is novel, the other main regulators investigated in this study, including Notch and JAK-STAT signaling, have been identified previously. The role of cup in this context seems to be to fine tune Notch signaling and it seems to play a relatively minor role in the process of border cell specification. In addition, the conclusions of this paper are not well-integrated into the existing literature on Notch and JAK-STAT signaling in border cells, and the discussion about the broader implications of this study for the understanding of Notch signaling was not well-developed. However, the careful documentation and quantification of the phenotypes reported in this study adds rigor and allows for firm conclusions. For these reasons, this study may have a lasting but perhaps somewhat incremental impact on the study of border cell migration in the Drosophila ovary.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary:

In this manuscript, authors establish a glyco-profiling platform for the functional analysis of genes involved in pseudaminic (Pse) and legionaminic (Leg) acid biosynthetic pathways. They used B. subvibroides and C. crescentus specific mutants in pseI and legI genes involved in the Pse and Leg biosynthesis, respectively, and cross-complementation assays with orthologous genes from different bacterial species, analysing motility and flagellin glycosylation. These assays show that Pse and Leg biosynthetic pathways are genetically different and recognize the LegX enzyme as a critical element in the Leg-specific enzymatic biosynthesis. Since that legX orthologous were only identified in the genome of bacteria with Leg biosynthetic pathways, it becomes a good marker to distinguish Leg from Pse biosynthesis pathways and a novel bioinformatic criterion for the assignment and discrimination of these two pathways. Reconstitution of Leg biosynthetic pathway of B. subvibroides in the C. crescentus mutant that lack flagellins, PseI and FlmG, complemented with both flagellin and FlmG of B. subvibroides, identified a new class of FlmG protein glycosyltransferases that modify flagellin with legionaminic acid. Furthermore, the construction of a chimeric FlmG through domain substitutions, allowed to reprogram a Pse-dependent FlmG into a Leg-dependent enzyme and reveal two modular determinants that govern flagellin glycosyltransferase specificity: a glycosyltransferase domain that accepts either Leg or Pse, and a specialized flagellin-binding domain to identify the substrate.

Major comments:

The conclusions obtained are convincing and well-supported. However, I think some points should be specify or clarify.

1.- In the mutants (pseI, legI, flmG,...) the non-glycosylated flagellin are exported and assembled in a flagellum filament shorter than the WT strain. However, motility in plates is absent or very reduced. This might be produced by instability of the flagellum filament when rotating in a semi-solid surface. MET was performed from plates or liquid cultures? Do the author analyses motility in liquid media? If they did, changes in motility were observed?

Response: The Caulobacter ΔpseI mutant accumulates low levels of flagellin in the supernatant. TEM analysis reveals that the flagellar filament is not assembled and only the hook structure is visible (PMID: 33108275). Brevundimonas subvibrioides ΔlegI or ΔflmG cells feature a shorter filament compared to WT by TEM. In all these analyses, TEM was performed on cells grown in broth to exponential growth phase as detailed in the Experimental procedures section. These mutant cells do not swim when analyzed by phase contrast microscopy. While is not known if swimming on semi-solid medium would further destabilize the flagellar structures seen in liquid cultures by TEM, there is more residual motility in B. subvibrioides mutants that make a short filament compared to C. crescentus mutants that lack the flagellar filament. Thus, our analyses point to a positive correlation between the residual motility and residual filament length when comparing the B. subvibrioides and C. crescentus mutants.

2.- In page 5, lines 158-163, the analysis, by HPLC, of derivatized nonulosonic acid from B. subvibroides flagella, shows a major peak at 9.8 minutes retention and a minor peak at 15.3 minutes. Since that Pse-standard have retentions peaks at 9.7 and 13 minutes, and Leg-standard at 12.3 minutes, the authors cannot infer, only with these data, the flagella sugar is a legionaminic acid derivative. In my opinion, should be included that inference comes from the data obtained by HPLC analysis and genetic approaches. Thanks. Corrected. 3.- In page 5, line 173-175. Authors indicate, "While no difference in the abundance of flagellin was observed in extracts from mutant versus WT cells, flagellin was barely detectable in the supernatants of mutant cultures, suggesting flagellar filament formation is defective in these mutants". MET images show that the flagellum filament length is shorter in the mutants than in the WT strain. Therefore, if the same number of mutants and WT cells has been used in the immunodetection assays, there should be more flagellin monomers in the WT samples than in the mutants ones and flagellin bands should be less intense in mutant samples corresponding to the anchored flagellum. Why bands corresponding to flagellin in mutants and WT show similar intensity in the immunodetection assays (Figure 3C and D)? Furthermore, in lane 177-178, authors suggest that LegI and FlmG govern flagellin glycosylation and export (or stability after export). However, if filament stability is affected, the amount of flagellin monomers in the supernatant of mutants should be higher than in the WT. However, immunodetection assays show less abundance of flagelin monomers in the supernatant of mutants. Please, can you clarify this? In relation to this point, I suggest that authors include, in the experimental procedures, how they obtained the supernatants to flagellin immunodetection, as well as why they used anti- FljKCc anti-serum to detect the B. subvibroides flagellin.

We thank the reviewer for raising this point. We have now clarified this question in the updated Experimental procedures section. Our immunoblots harbor the same number of cells harvested in exponential phase (OD=0.4). One mL of cells was harvested from cultures by centrifugation at full speed. The supernatant that was used for the immunodetection corresponds to the supernatant after the centrifugation. The supernatant fraction contains flagella that have been shed during the cell cycle at the swarmer cell to stalked cell (G1-S) transition of C. crescentus and B. subvibrioides.

Thus, it is clear that the majority of flagellins detected by immunoblotting are in fact cell associated and specifically the intracellular flagellins. The evidence for this is that the levels are comparable between WT and ΔflmG mutant cells, even though the latter has shorter or no flagellar filaments. Moreover, while C. crescentus cells are not constantly flagellated during the cell cycle, flagellins are detectable on cell-associated samples by immunoblotting even when cells do not yet or no longer have a flagellar filament. Based on these two points, we conclude that the total flagellin levels associated with cells do not reflect the levels of flagellin assembled into a flagellar filament, but rather the flagellin bulk present in the cytoplasm.

Consistent with this view, we previously reported that C. crescentus ΔpseI cells have the same amount of flagellins in cell lysates compared to the WT strain (PMID: 33108275), even though the mutant cells lack a flagellar filament. Thus, the results obtained here are consistent with previous observations and indicate that B. subvibrioides flagellin glycosylation mutants also still produce comparable amounts of flagellins intracellularly like the WT strain, despite the absence of flagellin glycosylation and inefficient assembly into a flagellar filament.

Concerning the potential role of LegI and FlmG in flagellin stability after export, we were referring to protein stability (half-life), not filament stability. Glycosylation may impact the half-life of extracellular flagellins since glycosylation can protect from proteolytic degradation of proteins, possibly in this case by different proteases that may accumulate in the supernatant. Thus, non-glycosylated flagellins could be more easily degraded by extracellular proteases once they are exported, ultimately resulting in a lower amount in the supernatant.

Addressing the final question about the specificity of the anti-FljKCc antiserum: we used this anti-serum because it detects the B. subvibrioides flagellins owing to the high sequence similarity between B. subvibrioides flagellins and C. crescentus flagellins. We previously showed that the anti-FljKCc anti-serum detects all six flagellins from C. crescentus, as determined by individually expressing each flagellin in a strain deleted for all six flagellin genes (Δfljx6) (PMID: 33108275). FljKCc (against which the antibody was raised) is 65% similar to the most distant C. crescentus flagellin, FljJ. As the similarity of FljKCc to the three B. subvibrioides flagellins ranges from 74% -67% sequence similarity, they should be even better recognized by the anti- FljKCc antibody than C. crescentus FljJ. However, on immunoblots we cannot attribute the signal to any individual B. subvibrioides flagellin as they could all co-migrate on SDS-PAGE and therefore all flagellins might reside in the same immunoblot band. However, we can clearly demonstrate that the immunoblot band corresponds to flagellins: a B. subvibrioides ΔflaF mutant (see below) that we constructed revealed that the flagellin signal is lost, as is the case for a C. crescentus ΔflaF mutant (PMID: 33113346). In the case of C. crescentus, the FlaF secretion chaperone is required for flagellin translation (synthesis) and we suspect that this also the case for B. subvibrioides FlaF. This experiment provides additional evidence that the B. subvibrioides flagellins are recognized by the anti-FljK (C. crescentus) anti-serum.

4.- Authors demonstrate the specificity of the GT-B domain of FlmG, using a chimeric FlmGCc-Bs in a mutant of C. crescentus that lacks FlmG and harbour the Leg biosynthetic pathway of B. subvibroides. However, since that TPR comes from C. crescentus, this chimeric protein, could be transfer the legionaminic acid to the flagellin of B. subvibroides? Furthermore, the complementation of this mutant with the FlmGBs did not support efficient flagellin modification and this might be related to the TPRCc domain. Therefore, in my opinion, the chimeric protein should be introduced in the B. subvibroides∆flmG background. The answer to the first question is “No” or “very inefficiently” as determined from immunoblot analyses of B. subvibrioides ΔflmG cells expressing the chimeric FlmG_Cc-Bs protein that we now show in Fig S2B.

Expression of the different FlmG (FlmG_Cc, FlmG_Bs, FlmG_Cc-Bs) in C. crescentus cells producing Pse or Leg revealed that FlmG_Bs does not support efficient flagellin modification with Pse in C. crescentus, likely because FlmG_Bs interacts poorly with the C. crescentus flagellins. By using the FlmG_Cc-Bs chimera we hoped to overcome this interaction problem with the C. crescentus flagellins (because the FlmG chimera harbors the C. crescentus TPR to bind the C. crescentus flagellins), however glycosyltransfer still does not occur efficiently because the GT domain from FlmG_Bs does not function with Pse. However, FlmG_Cc-Bs can modify the C. crescentus flagellins once C. crescentus is genetically modified to produce CMP-Leg (instead of CMP-Pse). This confirms that the FlmG TPR from C. crescentus is important for flagellin modification through the FlmG/flagellin interaction and that GT_B type glycosyltransferase only transfers Leg. In addition, we have now added as Fig S2B an immunoblot and as Fig S2C a motility test of B. subvibrioides ΔflmG cells expressing the FlmG_Cc-Bs chimeric protein in which we only observed little modification of B. subvibrioides flagellins and a poor motility, respectively. We extended our discussion of these results.

5.- Page 8, line 299-301. Authors point out that C. crescentus that lacks FlmG and harbour the Leg biosynthetic pathway of B. subvibroides and the chimeric FlmGCc-Bs, although it has a glycosylated flagellin, whose mobility in SDS-PAGE is like the WT strain, is non-motile. They suggest that additional factors exist in the flagellation pathway that exhibit specificity towards the glycosyl group that is joined to flagellins. However, would be interesting to see if the flagellum filament has similar length to the WT strain or at least, it has increased in relation to the flagella length of the mutant. If flagella length has not increased, it could suggest that changes in the glycan type might affects the flagellin assembly or the stability of the flagellum filament. Therefore, would be also important to analyse its motility in liquid media.

To investigate why the C. crescentus cells that produce Leg and express the chimeric FlmGCc-Bs glycosyltransferase are non-motile (Figure S5B) despite flagellin modification (by immunoblotting, Figure 7C), we employed two strategies. First, we performed immunoblot analyses on the supernatant fraction from these cells to determine if flagellins accumulate extracellularly. As now showed in Figure S5A, only low amounts of C. crescentus flagellins modified by Leg are present in the SN fraction. Second, we conducted TEM analyses of cells grown to exponential growth phase in broth. As shown in Figure S5C, the C. crescentus cells producing Leg and expressing FlmG_Cc-Bs glycosyltransferase harbor a shorter flagellum compared to those expressing the FlmG_Cc in which C. crescentus flagellins are modified by Pse. Altogether these results explain why these cells are non-motile both on soft agar plate and in liquid.

Minor comments: 1.- Pag 3 line102. Please change ".....two predicted synthases, a PseI and LegI homolog, and C. crescentus only encodes only PseI...." to ".....two predicted synthases, a PseI and LegI homolog, and C. crescentus only encodes a PseI...." 2.- Figure 2 A. Plasmid nomenclature (Plac-neuB) is confusing because C.c. ΔpseI cells express predicted LegI or PseI synthases. Please change to Plac, as in Figure 2B and 4. Figure 2A and 2B do not contain any complementation with Bacillus subtilis (Basu), however two complementation are labelled as Bs in Figure 2A and 2B. Furthermore, no Bs are present in the Figure 2 legend. 3.- Legend of figure 3 should include B. subvibrioides abreviation Bs. Line 774: Please change ".......glycosylation and secretion in B. subvibrioides." to ".......glycosylation and secretion in B. subvibrioides (Bs)." 4.- Figure 3. In order to keep a similar nomenclature in all plasmids, plasmid Plac-legI syn and Plac-flmG should be labelled as Plac-legIBs syn and Plac-flmGBs.

5.- Legend of figure 4 should include B. subvibrioides abreviation Bs. Line 791: Please change "....... complementation of the B.subvibrioides ΔlegI mutant with ...." to "....... complementation of the B.subvibrioides (Bs)ΔlegI mutant with ...." Furthermore, Legend of figure 4 indicate in line 795, that immunoblots reveal the intracellular levels of flagellin, however figure 2 and 3 show immunoblot of cell extracts. Please, correct this sentence. 6.- Legend of figure 5, 6 and 7 should include B. subvibrioides abreviation Bs. Line 808: Please change "Predicted Leg biosynthetic pathway in B. subvibrioides " to"Predicted Leg biosynthetic pathway in B. subvibrioides (Bs)" Line 834: Please change "....affects motility, flagellin glycosylation and secretion in B. subvibrioides."to "....affects motility, flagellin glycosylation and secretion in B. subvibrioides (Bs).Line 852: Please change "...acetyltransferase in flagellar motility of B. subvibrioides cells." to ""...acetyltransferase in flagellar motility of B. subvibrioides (Bs) cells." Furthermore, figure 5 should include C. crescentus abbreviation. Line 815: Please change "....whole cell lysates from C. crescentus mutant cultures......." to "....whole cell lysates from C. crescentus (Cc) mutant cultures......." 7.- In my opinion it would be useful to include a scheme of the gene organization involved in Leg biosynthesis in B. subvibrioides.

8.- Legend of figure S1 should include B. subvibrioides (Bs) and C. crescentus (Cc) abbreviations. Line 888-867: Please change "...C. crescentus ΔpseI cells and B. subvibrioides ΔlegI cells with plasmids expressing..." to "...C. crescentus (Cc) ΔpseI cells and B. subvibrioides (Bs) ΔlegI cells with plasmids expressing..." Furthermore, the name and abbreviations (Mm, So, Ku, Pi, Dv) of the species used should be included in the legend. Why the authors used a plasmid with a Pvan promoter in these assays? Why the authors changed the code color of pseI and legI orthologous genes? It would be more useful and understandable follow the code color used in figure 2 and 4.

Page 6 line 200, Please change ".....complementing synthases exhibit greater overall sequence similarity to LegI than Pse of C. jejuni. 22268,....." to ".....complementing synthases exhibit greater overall sequence similarity to LegI than PseI of C. jejuni. 22268,....." 10.- Page 7 line 231, Please change ".....negative bacteria A. baumannii LAC-4 (GCA_000786735.1)[38] and P. sp. Irchel 3E13..." to ".....negative bacteria A. baumannii LAC-4 (GCA_000786735.1)[38] and Pseudomonas sp. Irchel 3E13..." 11.- Introduce a line break between line 503 and 504. 12.- Page 14 line 543, please change "XbaI" to "XbaI" Thanks for the careful editing. We changed the text as suggested by the reviewer. We also added a scheme showing the genetic organization of the genes involved in Leg production and present as Figure 1B. When this study was initiated, the pMT335 plasmid with a Pvan promoter was used before we switched to using the pSRK plasmid with Plac promoter for better induction. Note that the results with Pvan or Plac are comparable regarding the PseI synthases interchangeability. Color code is now homogenous through the manuscript.

Reviewer #1 (Significance (Required)):

This is an interesting manuscript that contributes to the knowledge of the legionaminic biosynthetic pathway and establish a glyco-profiling platform for the functional analysis of genes involved in pseudaminic (Pse) and legionaminic (Leg) acid biosynthetic pathways. The analysis of Leg patway allowed to identify a gene (legX) that can be used to distinguish Leg from Pse biosynthesis pathways, becoming a bioinformatic tool for the assignment and discrimination of these two pathways. Furthermore, a new class of FlmG protein glycosyltransferases, able to transfer Leg to the flagellin, has been identified and its analysis reveal two modular determinants that govern flagellin glycosyltransferase specificity: a glycosyltransferase domain that accepts either Leg or Pse, and a specialized flagellin-binding domain to identify the substrate.

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Summary: Viollier and co-workers present a study in which they preform an elegant and rigorous genetic profiling of the the legionaminic and pseudaminic acid biosynthesis and flagellar glycosylation pathways in C. crescentus (native Pse) and B. subvibrioides (native Leg). They use motility as a representative readout for functional flagellar glycosylation with these microbial sialic acids. They discover orthologous Pse synthase genes can replace the function of the native synthase in C. crescentus and orthologous legionaminic acid synthase genes can achieve the same in B. subvibrioides. However, not vice versa indicating a strong preference for each microbial sialic acid stereoisomer in these species. For the Leg biosynthesis pathway, which requires GDP-GlcNAc, the authors also identify LegX as an essential component to synthesize this sugar nucleotide and thus a marker for Leg biosynthesis pathways. Upstream in theses pathways, they also identify a new class of FlmG flagellar protein glycosyltransferases. Importantly, through heterologous reconstitution experiments to uncovered that these glycosyltransferases possess two distinct domains, a transferase domain the determines specificity for either CMP-Leg or CMP-Pse, and a flagellin-binding domain to achieve selectivity for the substrate. Interestingly, by creating chimeric FlmG for these two domains between C. crescentus and B. subvibrioides they show that these two modular parts can be interchanged to adapt flagellin glycosyltransferase specificity in these species. Major comments: The key conclusions of the manuscript by Viollier and co-workers are convincing and well supported by their experiments and used methods, with respect to the insulation of the Leg and Pse biosynthetic pathways, they key role of LegX in launching the Leg pathway and the successful reconstitution of Leg glycosylation in a previously Pse-producing C. crescentus strain. Finally, they convincingly show that a chimeric version of the involved glycosyltransferases is functional, which besides intriguing future glycoengineering possibilities also emphasizes the two discrete domains in these transferases that dictate their sugar nucleotide and acceptor specificity. There is one additional experiment I would suggest with relation to the detection and confirmation of Pse and Leg on flagella of respectively, C. crescentus and B. subvibrioides. In the case of C. crescentus the detected DMB derivatized monosaccharide co-elutes with a validated standard of tri-acetylated Pse, which is convincing evidence of its identity. However, for B. subvibrioides. Their DMB derivatized monosaccharides from its flagella, results in a peak the does not co-elute with the only Leg standard (Leg5Ac7Ac) they have, it does elute at the same time as their Pse standard. Although it cannot of course be Pse as B. subvibrioides. Does not possess a Pse biosynthesis pathway, it also does not provide enough evidence to conclude that it is a Leg derivative. An MS(-MS) measurement of the eluted signal would not be a big investment in time and resources and would provide additional evidence to at least assign this peak to microbial sialic acid related to the present Leg biosynthesis pathway. It the identified mass would lead to identification of the derivative, it would also add to the proper characterization of the flagella glycosylation in the bacterium.

We have now added the glycopeptide analyses as requested. They are described in the last experimental section and confirm our results.

The data and the methods presented in this study are presented with sufficient detail so that they can be reproduced? However, I would suggest as is common nowadays in most journals that the authors include images of the raw unprocessed blot in de supporting info.

*The motility pictures are representative of three independent experiments and the immunoblots are representative of at least two independent experiments. This has now been mentioned in the Experimental procedures. The raw unprocessed blots have now been added as supporting info. *

Minor comments: There are a few textual errors that the authors should fix: -page 2, line 70: change "used" to "use" -page 11, line 407: add the word "are" after Pse On page 2, line 36, the authors state that "most eubacteria and the archaea typically decorate their cell surface structures with (5-, 7-)diacetamido derivatives, either pseudaminic acid (Pse) and/or its stereoisomer legionaminic acid (Leg,". This should be nuanced as to my knowledge it is not most eubacteria, but more a subset as identified by Varki in his seminal PNAS paper. The authors clearly present their data and conclusions in the figures of this manuscript. However, I would recommend the take a critical look at the drawing of their monosaccharide chair conformations and the positioning of the axial and equatorial groups on these chairs in Figure 1 and 5, as these are in most cases drawn a bit crooked, which can easily be corrected. We corrected the text as the reviewer suggested. We changed the sentence in the introduction to be more nuanced. The drawing of the monosaccharide has been improved.

Reviewer #2 (Significance (Required)):

The family of carbohydrates called sialic acids was long thought to exclusively occur in glycoproteins and glycolipids of vertebrates, but has since also been found in specific microbes. Especially symbiotic and pathogenic microbes associated with the humans express a wide array of unique microbial sialic acids for which their functional roles are not well understood and the associated glycosylhydrolase and glycosyltransferase have in most cases not been identified yet. The authors present an impressive insight into flagellar glycosylation with Pseudaminic and Legionaminic acid in two bacterial species, using genomic analysis, rewiring, immunoblots and motility assays as their main tools. They provide compelling evidence on the insulation of the Pse of Leg pathway in these species, the flexibility in exchanging between biosynthetic enzymes from the same pathway between various species. Crucially, most glycosyltransferases that add the Pse or Leg glycoform onto various acceptor sites in bacteria, have up to this point remained elusive in most cases. It is therefore very valuable information that the authors here provide on the involved glycosyltransferases. Especially, on the two domains that govern their sugar nucleotide and acceptor specificity, and that these can be reengineered as chimeric glycosyltransferases. To me as a chemical glycobiologist this provides compelling possibilities for glycoengineering possibilities in future studies in the field to elucidate the functional roles of Pse and Leg glycosylation.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary of the findings and key conclusions (including methodology and model system(s) where appropriate): Kint et al describe a neat study of bacterial flagellin glycosylation by a recently identified class of protein glycosyltransferases called FlmG. The experiments are well designed, the data presented is convincing and the conclusions drawn are mostly in line with the experimental evidence presented. These are the key findings. Kint et al show that genetic tools and motility can be used as a readout to probe the sugar biosynthesis pathway in bacteria. Using the recently characterized system of Caulobacter crescentus, they have performed a survey of different PseI/LegI/NeuB genes from various bacteria, checking whether they could rescue the motility defect in C. crescentus ΔpseI cells. They found that those genes that did confer motility also had higher sequence similarity to C. jejuni PseI than to C. jejuni LegI or C. jejuni NeuB. They also found that these genes also restored flagellin glycosylation as checked by mobility shift on gel electrophoresis with immunoblotting to anti-FljK antibody. This survey brought up an interesting finding that the PseI/LegI/NeuB orthologs of the closely related Brevundimonas species were unable to confer motility to C. crescentus ΔpseI cells, and were more similar to C. jejuni LegI than to C. jejuni PseI or C. jejuni NeuB. They also performed similar glycoprofiling experiments using B. subvibrioides ΔlegIBs cells and various PseI/LegI/NeuB orthologs from different bacteria, which indicated the restoration of motility by putative LegI synthases. Kint et al demonstrate flagellin glycosylation in B. subvibrioides by performing in-frame deletions of FlmG, and LegI genes in B. subvibrioides and checking for motility, presence of flagella, and flagellin glycosylation by motility shift on gel electrophoresis. Further, they confirm the critical nature of GDP-GlcNAc for Leg biosynthesis by assessing flagellin glycosylation and motility in B. subvibrioides with an in-frame deletion in PtmE/LegX and by performing heterologous complementation with an M. humiferra PtmE ortholog. They also reconstitute the legionaminic acid biosynthesis pathway in C. crescentus cells that lack flagellins, PseI and FlmG, and show that the heterologously expressed B. subvibrioides flagellin is glycosylated by heterologously expressed B. subvibrioides FlmG. Finally, they also show that whereas the CcFlmG cannot substitute for BsFlmG and vice versa, a chimeric FlmG bearing the TPR domain from C. crescentus FlmG (that recognizes C. crescentus FljK) and the GT domain from B. subvibrioides FlmG (that transfers CMP-Leg) modifies CcFljK in C. crescentus cells that lack CcFlmG but express both Pse (endogenously) and Leg (from the reconstituted pathway). This demonstrates the modularity of the FlmG glycosyltransferases. Kint et al provide the chemical nature of C. crescentus flagellin glycosylation. Kint et al have analyzed the glycans released from the flagellin by acid hydrolysis and clearly shown the nature of the glycan in C. crescentus flagellin to be Pse4Ac5Ac7Ac by use of Pse standards. The glycan from B. subvibrioides was distinct from the Leg standard used, and could be a Leg derivative distinct from Leg5Ac7Ac.

Major comments: 1. Table 1 and Text in Results, lines 116-119, "In support of the notion that derivatization occurs after the PEP-dependent condensation reaction to form Pse or Leg, our glyco profiling analysis revealed that putative PseI proteins (identified by sequence comparisons to C. jejuni 11168, Table S1) conferred motility to C. crescentus ΔpseI cells, whereas putative LegI synthases did not." Not clear how putative PseI and LegI synthases were identified. Table 1 only lists overall percent sequence identity and similarity to Cj PseI, LegI and NeuB, and percent identities and similarities of the various nonulosonic synthases to these proteins are in the similar range, as expected. In the absence of sequence alignments indicating the presence of conserved residues, particularly related to the substrate binding region, that are distinct in these paralogs, calling out the type of synthase based on the highest percent identity (to Cj PseI, LegI or NeuB) is speculative. Also, Shewanella oneidensis does not follow the pattern of highest similarity to NeuB3. Second, in the absence of data showing that the Leg and Pse found in these different organisms actually are different derivatives, this does not support that "derivatization occurs after the PEP-dependent condensation reaction to form Pse or Leg". Putative PseI and LegI were proposed based on BlastP analyses in which the protein sequences of interest were aligned to the three experimentally validated synthases from C. jejuni 11168: PseI, LegI, NeuB as well as PseI from C. crescentus, as indicated in Table S1. While, the assignment of the donor sugar is based only on the sequence identity and similarity to LegI or PseI, this assignment corresponds well according to the restoration of the motility of the C. crescentus ΔpseI mutant upon expression of PseI ortholog and B. subvibrioides ΔlegI mutant with heterologous LegI expression.

It is true that for Shewanella oneidensis the assignment as PseI or LegI is ambiguous, exhibiting nearly identical similarity, but it is quite distinct from NeuB. This actually makes the S. oneidensis synthase a very interesting case to explore the enzymology of its Pse/LegI ortholog, knowing that it has been previously shown that this bacterium glycosylates its flagellins with Pse derivatives (PMID: 24039942). The results from our genetic complementation analysis are however very clear (PseI ortholog) and very consistent with the functional analysis in S. oneidensis.

Concerning the different derivatives of Pse or Leg: McDonald and Boyd (PMID 32950378) recently published a review giving some examples of Bacteria/Archaea experimentally shown to contain Pse/Leg-derivatives: C. jejuni 11168 modifies its flagellin with 5,7-N-acetyl Pse, Sinorhizobium fredii NGR234 (not used in this study but in our previous work PMID 33113346 and showed to restore the motility of C. crescentus ΔpseI cells) modifies its capsule with 5-acetamido-7-3-hydroxybutyramido-Pse), Treponema denticola modifies its flagellin with 7-(2-metoxy-4,5,6-trihydroxy-hexanoyl-Pse, A. baumannii LAC-4 produces 5,7-N-acetyl-8-epi-Leg to decorate the capsule, Halorubrum sp. PV6 modifies the LPS with N-formylated Leg and L. pneumophila produces 5-acetamidino-Leg.

The reviewer is right in that we do not know the exact version of Pse or Leg produced in C. crescentus and B. subvibrioides, HOWEVER, the fact that complementation works with the majority of the orthologs of PseI and LegI including many from bacteria that are known to produce modified Pse derivatives for example in Shewanella oneidensis and Treponema denticola, the most likely explanation is that derivatization occurs after the PseI or LegI step, but we concede that the results are also compatible with a promiscuous enzyme that can accept different Pse derivatives or different Leg derivatives.

1. Related to (1), Text in Results, lines 130-131, "We conclude from our survey that (heterologous) PseI synthase activity generally confers motility to C. crescentus ΔpseI cells, whereas LegI-type (or NeuB-type) synthases are unable to do so." There is no a priori evidence provided indicating that these were PseI or LegI type synthases. So the conclusion really is that assuming only PseI type synthases would be able to rescue the motility defect in C. crescentus ΔpseI cells, this glyco-profiling motility assay now provides the first biochemical evidence telling us which synthases are Pse-type, and which are Neu/Leg-type. And in my view, this is the conclusion of greater significance in the field - to be able to now identify which is a PseI and which a LegI based on these complementation assays. However, if the authors still wish to retain their original conclusion, they could cite or provide evidence (either biochemical evidence in this work or reported literature regarding the sugar synthesized or bioninformatics analysis regarding the presence of distinct genes such as the Ptm genes for legionaminic acid biosynthesis pathway or genes that differ in their enzyme activities and overall fold such as PseB/LegB or PseG/LegG in the gene neighborhood) indicating or suggesting the PseI/LegI/NeuB nature of the different synthases. Also, methods for the bioinformatics analysis (eg. BLASTp settings used, dates of searches, whether regular BLAST or PSI-BLAST was used, etc.) are missing in the manuscript, and need to be included. We agree that for many PseI or LegI tested, there is no provided biochemical evidence. HOWEVER, this is not the case for some of them including the PseI, LegI and NeuB from Campylobacter jejuni (PMID 19282391), some A. baumannii strains (α-epi-legionaminic acid for A. baumannii LAC-4 PMID 24690675), Shewanella oneidensis (Pseudaminic acid with methylation PMID 23543712), Legionella pneumophila (Legionaminic acid PMID 18275154) or Halorubrum sp. PV6 (N-formylated legionaminic acid PMID 30245679). Thus, we maintain the two conclusions: the PseI and LegI synthases are generally interchangeable and the complementation assays can enable to identify and assign PseI and LegI function. BLAST2P was used to compare the protein sequences of the tested NeuB-like synthases with NeuB1, LegI (NeuB2) and PseI (NeuB3) from Campylobacter jejuni but also with PseI from C. crescentus. BLOSUM62 matrix was used as well as a word of size 3 for the comparison. We have now added this procedure in the legend of the Table S1.
2. It is interesting that there is still a signification amount of flagellin secretion/assembly in the B. subvibrioides LegI and FlmG mutants. It will be good to see a discussion about whether this is likely from due to low level of function despite the in-frame deletion of genes; how many flagellin subunits are likely to have managed secretion and assembly in these short flagella; whether there is any redundancy of LegI / FlmG (perhaps with lower levels of expression); considering Parker and Shaw's findings of glycosylation being required for flagellin binding to the chaperone and subsequence secretion in A. caviae whether there is a FlaJ homolog in B. subvibrioides. Also, can the authors rule out the possibility that absence of glycosylation does not affect flagellin assembly but makes the flagellum prone to shear/breaks in B. subvibriodes, resulting in smaller flagella? How many flagellins are there in B. subvibrioides? Is it possible that one is glycosylated but another/others are not, and that is the reason for the small flagellum in these mutants? The number of flagellin subunits that are assembled into a full-length flagellar filament is unknown in C. crescentus and in B. subvibrioides. There are 3 different flagellin genes that are now presented schematically in Figure 1C. No redundancy has been found for LegI or FlmG. It is possible that the B. subvibrioides is better in exporting non-glycosylated flagellin or that the capping proteins can function better with sugar modification or that the filament of B. subvibrioides mutants is less fragile when it is non-glycosylated or that its flagellins “stick” better. It is also possible that short filaments are not actually containing flagellins mounted on the hook but another protein that polymerizes aberrantly in the absence of Leg or FlmG. This remains to be investigated and compared to the situation of Pse and FlmG mutants of C. crescentus.

B. subvibrioides possesses an ortholog of the C. crescentus flagellin secretion chaperon FlaF (PMID 33113346). As observed in C. crescentus, FlaF likely has a role in flagellin translation as its inactivation totally prevents flagellins production (see answer to reviewer #1). For C. crescentus, bacterial two hybrid experiments revealed that FlaF can interact with non-glycosylated flagellins in E. coli. Thus, it is strongly possible that FlaF/flagellins interaction is not dependent on the flagellins glycosylation state. In addition, the short flagellum filament observed in B. subvibrioides ΔlegI or ΔflmG mutants argues that at least some flagellins are secreted while not glycosylated.TEM pictures have been performed in liquid medium from exponential growth phase. In this condition, no fragment of flagella was observed in the culture medium by TEM but only small flagella with a hook structure attached. Also, flagella breaks might result in more random length of flagellum.

Three flagellins are in B. subvibrioides (Bresu_2403 is 59% identical with FljLCc, Bresu_2638 is 57% identical with FljKCc and Bresu_2636 is 62% identical with FljJCc). We now show this genetic organization of the flagellins in Fig. 1C. The three flagellins are all detected by the anti-FljKCc anti serum (see answer and figure to reviewer #1). We cannot attribute the immunoblot signal to any individual B. subvibrioides flagellin as they could all co-migrate on SDS-PAGE. However, the signal often looks like a doublet (as shown in Figure 4B for example) suggesting that at least two flagellins are detected and this doublet is always found to migrate faster in absence of glycosylation that could indicate that all B. subvibrioides flagellins (or at least 2) are modified.

Text in Results, lines 170-171, "We then probed the resulting ΔlegIBs and ΔflmGBs single mutants for motility defects in soft agar and analyzed flagellin glycosylation by immunoblotting using antibodies to FljKCc". Was the antibody to FljKCc determined to also specifically bind to FljKBs? Also, how many flagellins are there in B. subvibrioides? Are all detected with this antibody? Antibodies raised to FljKCc were raised against His6-FljK produced in E. coli (previously published in Ardissone et al, 2020). This serum recognizes the 6 flagellins from C. crescentus (PMID: 33108275). It recognized the three flagellins from B.s. (see answer to reviewer #1).

It is interesting that C. cresentus cells expressing Pse (endogenously) and Leg (reconstituted pathway), and BsFlmG and BsFljK (corresponding to Figure 5C) are not motile. Was the motility assay done for the experiment of figure 5B as well? Are the C. crescentus cells lacking Pse and FlmG but with heterologous expression of Leg and BsFljK and BsFlmG also non-motile? Also, it will be good to see the TEM images for these cells.

C. crescentus cells that produce Pse (endogenously) or Leg (reconstituted pathway) and BsFlmG and BsFljK (formerly Figure 5C and now as Figure 7C) are indeed not motile as shown by the motility tests presented in Figure S5B. Motility assays with cells used in the former Figure 5B (now Figure 7B) have also been done and are now presented Figure S4B. These cells are non-motile because BsFljK is not efficiently secreted (or unstable after secretion) as shown on the immunoblot of the supernatant fraction in Figure S4A lower panel. As a result, flagellar filament is not properly assembled as only a short flagellum was observed by TEM in such cells compared to the WT C. crescentus (Figure S4C and S4D).

Immunoblotting of the supernatants should be shown (in addition to the cell extracts) for Figures 5B and 5C so that the reader can appreciate whether glycosylation has taken place but secretion/assembly has not. Further, HPLC of the acid extracts from flagellin could be done to unambiguously show whether the CcFlmG has transferred Pse and the BsFlmG and Cc-BsFlmG have transferred Leg on to the CcFljK in Figure 5c, and the identity of the sugar, if any, transferred by CcFlmG in the absence of Pse, and BsLeg genes or BsLegX gene in figure 5B.

*__ Immunoblots of the supernatants for Figure 5B (now Figure 7B) have been done and been added (Figure S4A lower panel). BsFljK is barely detected in the supernatant whatever its glycosylation state (with or without Leg). Note that in the supporting info where the raw unprocessed blot used for this panel is shown, a positive control of blotting (C. crescentus Δfljx6 mutant expressing CcFljK from pMT463) has been used. Immunoblots of the supernatant from Figure 5C (now 7C) have been done and been added in figure S5A. The CcFljK modified with Leg is poorly secreted (or unstable after secretion). As a result, these cells only harbor a short flagellum compared to those that are able to modify CcFljK with Pse (Figure S5C).

HPLC of the acid extracts from flagellins have been performed on purified flagella obtained by ultracentrifugation. As C. crescentus cells expressing BsFlmG and Cc-BsFlmG harbor no or short flagellar filament, the purification by ultracentrifugation is limited. Thus, to further confirm that CcFlmG has transferred Pse and Cc-BsFlmG (and BsFlmG) has transferred Leg on CcFljK (former Figure 5C and now Figure 7C), we performed immunoblots on the cell extracts of C. crescentus ΔflmG ΔpseI cells that cannot produce Pse but able to produce Leg (reconstituted pathway). These experiments, now presented in Figure 7C (lower panel) confirmed that no modification of CcFljK was observed in C. crescentus cells expressing CcFlmG whereas CcFljK is modified in C. crescentus expressing Cc-BsFlmG, confirming that Cc-BsFlmG has transferred Leg (the only NulO produced in this condition).__*

Text in discussion, lines 334-338, "By extension, having recognized the LegX/PtmE enzyme as a critical element in the Leg-specific enzymatic biosynthesis step (Figure 6) likewise offers another functional, but also a novel bioinformatic, criterion for the correct assignment and discrimination of predicted stereoisomer biosynthesis routes residing in ever-expanding genome databases" It will be nice to see a discussion on the prevalence of PtmE versus GlmU (or equivalent gene), PtmF, PtmA, PgmL in the Leg synthesizing organisms. Is the PtmE but not the other genes found in all cases, which makes it better as a molecular determinant for bioinformatics predictions of the type of pathway? Also, on whether PtmE has any homology to genes in other pathways (not associated with flagellin glycosylation) and how reliable a marker it is to differentiate Leg biosynthesis from Neu5Ac biosynthesis pathways.

GlmU is a potential bifunctional UDP-N-acetylglucosamine diphosphorylase/glucosamine-1-phosphate N-acetyltransferase that can be part of both Pse and Leg pathway (PMID 19282391). Accordingly, a GlmU ortholog is found in C. crescentus and B. subvibrioides that we showed are producing Pse and Leg, respectively. Thus, GlmU cannot be attributed to a Leg pathway signature. On the other hand, PtmE is barely found in the organisms from which PseI orthologs restore the motility of C. crescentus ΔpseI cells.

PtmF, PtmA, PgmL and GlmS are proposed to act upstream of the production of GlcN-1-P that is a precursor of both UDP-GlcNAc and GDP-GlcNAc, the precursors of Pse and Leg respectively. In addition, orthologs of these genes are not prevalent in the Leg synthetizing organisms present in Table S2 using BlastP analyses with C. jejuni proteins as templates.PtmE ortholog is found in most of the Leg synthetizing organisms as shown in Table S2 and often genetically linked with other genes coding for proteins involved in Leg production (shown with the asterisk * in table S2). Of note, PtmE is found not only in organisms that modify flagellin(s) with Leg but also in organisms that add Leg on capsule such as A. baumannii LAC-4.

It is not clear from the methods or the figure legends how many times the immunoblotting, motility experiments were done; how many experiments/trials are the images representative of? The motility pictures are representative of three independent experiments. The immunoblots are representative of at least two independent experiments. This information is now added in the Experimental procedures section.

Minor comments:

1. The gene for GlcN-1-P guanylyltransferase in the Leg-specific enzymatic biosynthesis step is already known as PtmE from the work of Schoenhofen's group. For the sake of consistency, it would be better to retain the nomenclature as PtmE throughout the manuscript instead of introducing the name LegX, which makes it sound like it is a previously unknown gene.

2. Text in abstract, lines 15-17: "Sialic acids commonly serve as glycosyl donors, particularly pseudaminic (Pse) or legionaminic acid (Leg) that prominently decorate eubacterial and archaeal surface layers or appendages" The glycosyl donor is the nucleotide sugar and not the nonulosonic acid or sialic acid... rephrasing required for accuracy. Done

3. Text in abstract, lines 18: "a new class of FlmG protein glycosyltransferases that modify flagellin" The authors are presumably referring to FlmG as the new class of protein glycosyltransferases... rephrasing required for accuracy Corrected
4. Text in introduction, lines 41-42 "Pse and Leg derivatives synthesized in vitro can be added exogenously in metabolic labeling experiments" It should be "derivatives of Pse and Leg precursors" and not "Pse and Leg derivatives" corrected

5. Text in introduction, line 46 "Pse- or Leg-decorated flagella may also be immunogenic." This sentence is not referenced and it is not clear why it is written here.

6. Text in introduction, lines 63-66 "The synthesis of CMP-Pse or CMP-Leg proceeds enzymatically by series of steps [20-22], ultimately ending with the condensation of an activated 6-carbon monosaccharide (typically N-acetyl glucosamine, GlcNAc) with 3-carbon pyruvate (such as phosphoenolpyruvate, PEP) by Pse or Leg synthase paralogs, PseI or LegI, respectively" The synthesis begins with activated GlcNAc. The substrate for condensation is not activated GlcNAc. It is 2,4-diacetamido-2,4,6-trideoxy-D-mannopyranose in case of LegI and 2,4-diacetamido-2,4,6-trideoxy-b-L-altropyranose in case of PseI. Indeed, we modified the sentence.

7. Text in introduction, line 70 "for used as glycosyl donors" Typographical error, "for use as glycosyl donors" Corrected
8. Text in Results, line 102, "C. crescentus only encodes only PseI" Do the authors mean "only one PseI"? Corrected
9. Text in Results, lines 108 and 109, "Such modifications could occur before the PseI synthase acts or afterwards. In the latter case, most (if not all) synthases would be predicted to produce the same Pse molecule," Do the authors know of any reports of modifications occurring before the PseI synthase? Please cite references, if known. Why "most (if not all)"? If the former case is true, the PseI synthase might not be able to accept the substrate. Correct. Because we cannot test all enzymes we must keep the statement non-committing.

“Most (if not all)” refers to the latter case i.e. the modification occurs after PseI synthase. In this context, PseI should do the same reaction, however, there might be some exceptions.

There is, to our knowledge, no reports showing that modifications occur before the PseI synthase. The glyco-profiling experiments all suggest that modification occurs after Pse production based on our motility readout. It is possible that PseI enzymes that condense a modified precursor would not be functional in our motility assay.

Text in Results, lines 141-143, "our bioinformatic searches using C. jejuni 11168 as reference genome identified all six putative enzymes in the B. subvibrioides ATCC15264 genome (CP002102.1) predicted to execute the synthesis of Leg from GDP-GlcNAc" Not clear how this was done. Do the authors mean that they used the genes from C. jejuni 11168 as the query genes to identify homologs in B. subvibrioides ATCC15264 genome (CP002102.1)? Or did they use putative genes from B. subvibrioides ATCC15264 genome (CP002102.1) and pull out homologs from C. jejuni 11168 by using C. jejuni 11168 as the reference genome? We now have modified the sentence to make it clearer.

At first reading, the flow of the manuscript is difficult to follow due to the figures not appearing in full in order of their occurrence. For instance, Figures 5B and 5C are discussed only in the end of the manuscript after the results of Figures 6 and 7. Other instances also exist. The authors may consider re-ordering the figure parts if possible so that all parts of each figure appear in order of occurrence in the manuscript text. Thanks for raising this issue. We have now tried to address this concern by re-organizing the order of occurrence of the figures. Notably we have now exchanged Figure 5 (on Leg pathway reconstitution and FlmG rewiring) with Figure 7 (on LegB and LegH). We modified the text accordingly. We hope that it makes the manuscript and corresponding figures easier to follow.

Reviewer #3 (Significance (Required)):

The nonulosonic acids, Pseudaminic acid and Legionaminic acid, are abundant in bacterial systems in the capsular and lipopolysaccharides as well as in glycoprotein glycans. The Ser/Thr-O-nonulosonic acid glycosylation of flagellins has been studied with respect to the system of Maf glycosyltransferases in Campylobacter jejuni, C. coli, Helicobacter pylori, Aeromonas caviae, Magnetospirillum magneticum, Clostridium botulinum and Geobacillus kaustophilus, and recently with respect to the system of FlmG glycosyltransferases by Viollier's group in Caulobacter crescentus. However, the determinants that govern the glycosyltransferase function are not still well known. Kint et al have performed excellent work using bacterial genetics tools to (1) highlight the "functional insulation" of the Leg and Pse biosynthesis pathways, (2) demonstrate the modularity of the FlmG glycosyltransferase proteins with respect to the flagellin binding and glycosyltransferase domains. This work makes a significant advance in the field with respect to (1) understanding flagellin glycosylation by FlmG, (2) making designer protein Ser/Thr-O-glycosyltransferases, and (3) bioinformatics analysis of genomes with respect to the Pse/Leg/Neu nonulosonic acid biosynthetic potential encoded. The findings will be of great interest to scientific audiences working in the areas of glycobiology and bacteriology. My area of expertise: Maf flagellin glycosyltransferases

Author Response

Reviewer #1 (Public Review):

The software presented in this paper is well documented and represents a significant achievement that breaks new ground in terms of what is possible to render and explore in the web browser. This tool is essential for the exploration of SC2 data, but equally useful for the tree of life and other tree-like data sets.

Thank you for reviewing my work and for this generous assessment.

Reviewer #2 (Public Review):

This manuscript describes a web-based tool (Taxonium) for interactively visualizing large trees that can be annotated with metadata. Having worked on similar problems in the analysis and visualization of enormous SARS-CoV-2 data sets, I am quite impressed with the performance and "look and feel" of the Taxonium-powered cov2tree web interface, particularly its speed at rendering trees (or at least a subgraph of the tree).

Thank you for the kind words.

The manuscript is written well, although it uses some technical "web 2.0" terminology that may not be accessible to a general scientific readership, e.g., "protobuf" (presumably protocol buffer) and "autoscaling Kubernetes cluster". The latter is like referring to a piece of lab equipment, so the author should provide some sort of reference to the manufacturer, i.e., https://kubernetes.io/.

Thank you for flagging this. I have now replaced the colloquial "protobuf" with "protocol buffer". I have now provided a URL for Kubernetes. It is always difficult to judge how much to explain technical terms. I certainly agree that many people will be unfamiliar with, for instance, protocol buffers, but an explanation of what they are (which may not be particularly important for understanding Taxonium) can sometimes overshadow more important details. So my preference in that particular case is for an interested reader to research the unfamiliar term.

In other respects, the manuscript lacks some methodological details, such as exactly how the tree is "sparsified" to reduce the number of branches being displayed for a given range of coordinates.

This is an important point also raised by Reviewer 3. I have added a new section in the Materials and Methods which discusses this in some detail.

Some statements are inaccurate or not supported by current knowledge in the field. For instance, it is not true that the phylogeny "closely approximates" the transmission tree for RNA viruses.

I agree that this was an overly broad claim, and have softened it, now saying:

"The fundamental representation of a viral epidemic for genomic epidemiology is a phylogenetic tree, which approximates the transmission tree and can allow insights into the direction of migration of viral lineages."

Mutations are not associated with a "point in the phylogeny", but rather the branch that is associated with that internal node.

I have changed this as suggested.

A major limitation of displaying a single phylogenetic tree (albeit an enormous one) is that the uncertainty in reconstructing specific branches is not readily communicated to the user. This problem is exacerbated for large trees where the number of observations far exceeds the amount of data (alignment length). Hence, it would be very helpful to have some means of annotating the tree display with levels of uncertainty, e.g., "we actually have no idea if this is the correct subtree". DensiTree endeavours to do this by drawing a joint representation of a posterior sample of trees, but it would be onerous to map a user interface to this display. I'm raising this point as something for the developers to consider as a feature addition, and not a required revision for this manuscript.

I entirely agree with this point. I have added a sentence in the discussion:

"Even where sequences are accurate, phylogenetic topology is often uncertain, and finding ways to communicate this at scale, building on prior work [Densitree citation] would be valuable."

The authors make multiple claims of novelty - e.g., "[...] existing web-based tools [...] do not scale to the size of data sets now available for SARS-CoV-2" and "Taxonium is the only tool that readily displays the number of independent times a given mutation has occurred [...]" - that are not entirely accurate. For example, RASCL (https://observablehq.com/@aglucaci/rascl) allows users to annotate phylogenies to examine the repeated occurrence of specific mutations. Our own system, CoVizu, also enables users to visualize and explore the evolutionary relationships among millions of SARS-CoV-2 genomes, although it takes a very different approach from Taxonium. Taxonium is an excellent and innovative tool, and it should not be necessary to claim priority.

I agree that comparisons with existing tools are difficult and often provide a sense of unnecessary competition. I attempted to be quite careful in the specific section focused on comparison, but may have been less careful earlier on. The intent with this first sentence in the abstract was to provide a succinct description of the gap that Taxonium was developed to fill with "however, existing web-based tools for analysing and exploring phylogenies do not scale to the size of datasets now available for SARS-CoV-2". I have now removed the words "analysing and", focusing on the exploration of phylogenies. I think this new sentence is defensible in that valuable tools such as CoVizu intentionally do not explore a phylogeny directly but instead take a multi-level approach, and this new sentence better matches the comparisons in the paper. In the second sentence, I have removed the phrase "is the only tool that", which I agree adds little and may not be accurate, depending on one's interpretation of "readily". Thank you for these points.

Although the source code (largely JavaScript with some Python) is quite clean and has a consistent style, there is a surprising lack of documentation in the code. This makes me concerned about whether Taxonium can be a maintainable and extensible open-source project since this complex system has been almost entirely written by a single developer. For example, usher_to_taxonium.py has a single inline comment (a command-line example) and no docstring for the main function. JBrowsePanel.jsx has a single inline comment for 293 lines of code. There is some external documentation (e.g., DEVELOPMENT.md) that provides instructions for installing a development build, but it would be very helpful to extend this documentation to describe the relationships among the different files and their specific roles. Again, this is something for the developers to consider for future work and not the current manuscript.

This is an entirely fair comment. The version of Taxonium presented in the manuscript is "2.0", which is a new version built from scratch with considerably less technical debt than the version that preceded it. Its technical strengths are that (with the exception of the backend) it is relatively well-modularised into functional components. But the limitations that the reviewer notes with respect to commenting are entirely fair. What I would say is that in the time since this manuscript was submitted, several important features have been added by an external collaborator, Alex Kramer, most notably the Treenome Browser (https://www.biorxiv.org/content/10.1101/2022.09.28.509985v1). I hope that the ability of Alex to add these features with little need for support provides some evidence of Taxonium's extensibility. But I acknowledge there is room for improvement.

Reviewer #3 (Public Review):

The paper succinctly provides an overview of the current approaches to generating and displaying super-large phylogenies (>10,000 tips). The results presented here provide a comprehensive set of tools to address the display and exploration of such phylogenies. The tools are well-described and comprehensive, and additional online documentation is welcome.

The technical work to display such large datasets in a responsive fashion is impressive and this is aptly described in the paper. The author rightly decides that displaying large phylogenies is not simply a matter of rendering "more nodes", and so in my eyes, the major advancement is the approach used to downsample trees on-the-fly so that the number of nodes displayed at one time is manageable. This is detailed only briefly (Results section, 1st paragraph, 2 sentences). I would like to see more discussion about the details of this approach.

Thank you for this point, also raised by Reviewer 2. I have now added a lengthy section on this in the Materials and Methods, which I hope is helpful. The approach is not especially sophisticated, but it does the job and runs quickly.

Examples that came up while exploring the tool: the (well implemented) search functionality reports results from the entire tree (e.g. in Figure 4, the number of red circles is not a function of zoom level), how does this interact with a tree showing only a subset of nodes?

Yes, this is an important feature which I perhaps did not do justice to in the write-up. I have included in the new section in the Materials and Methods a paragraph discussing search results:

"In order to ensure that search results are always comprehensive, but at the same time to avoid overplotting, we take the following approach::

● Searches are performed across every single node on the tree to select a set of nodes that match the search. The total number of matches is displayed in the client.

● If fewer than 10,000 matches are detected, these are simply displayed in the client as circles

● If more than 10,000 matches are detected, the results are sparsified using the method above, and then displayed.

● Upon zooming or panning, the sparsification is repeated for the new bounding box."

How is the node order chosen with regards to "nodes that would be hidden by other nodes are excluded" and could this affect interpretations depending on the colouring used?

This perhaps was slightly sloppy language which did not directly describe the implementation. I have now rephrased this to "only nodes that overlap other nodes are excluded", as we don't in fact consider a notion of z-index when doing this. The way the sparsification works (now better described) means that the nodes excluded are determined essentially by position and I don't foresee this introducing particular biases, but this was an insightful point to raise.

Taxonium takes the approach of displaying all available data (sparsification of nodes notwithstanding). Biases in the generation of sequences, especially geographical, will therefore be present (especially so in the two main datasets discussed here - SARS-CoV-2 and monkeypox). This caveat should be made explicit.

This is certainly true. I have added this new paragraph in the Discussion:

"A further challenge is the vastly different densities of sampling in different geographic regions. Because Cov2Tree does not downsample sequences from countries which are able to sequence a greater proportion of their cases, the number of tips on a tree is not indicative of the size of an outbreak and in some cases even inferences of the directionality of migration may be confounded. There would be value in the development of techniques that allow visual normalisation of trees for sampling biases, which might allow for less biased phylogenetic representations without downsampling."

Has the author considered choosing which nodes to exclude for sparsified trees in such a way as to minimise known sampling biases?

The last sentence of the new paragraph above alludes to a sort-of-similar approach. I hadn't directly considered the approach the reviewer suggests. It is an interesting idea. The downsampling algorithm has to be very computationally inexpensive but it would be interesting to explore ways to do this. I am tracking this in https://github.com/theosanderson/taxonium/issues/437.

Interoperability between different software tools is discussed in a technical sense but not as it pertains to discovering the questions to ask of the data. As an example, spotting the specific mutations shown in figure 3 + 4 is not feasible by checking every position iteratively; instead, the ability to have mutations flagged elsewhere and then seamlessly explore them in Taxonium is a much more powerful workflow. This kind of interoperability (which Taxonium supports) enhances the claim of "providing insights into the evolution of the virus".

Thank you for flagging this point -- I am very excited by the growing ecosystem of interoperable tools. You are absolutely right that most of the insights Taxonium can bring into evolution rely also on this broader ecosystem. I have added a florid sentence in the concluding paragraph: "It forms part of an ecosystem of open-source tools that together turn an avalanche of sequencing data into actionable insights into ongoing evolution."

The prosaic reason I don't discuss Taxonium's interoperability features in more detail in this manuscript is that it aims to describe the version of Taxonium I initially developed, and these features were developed collaboratively by a broader group later on (and after deposition of this preprint).

Taxonium has been a fantastic resource for the analysis of SARS-CoV-2 and this paper fluently presents the tool in the context of the wider ecosystem of bioinformatic tools in use today, with the interoperability of the different pieces being a welcome direction.

Of course with innovation comes back lash, it is within human nature to want to not have/want change.

Ie. Technology such as the newest phones and older generations not wanting to learn/ not knowing how to understand then.

We tend to pit every new idea to an assortment of way/methods/things we already know rather than exploring them for what they were thought to be made for. I think seeing that there was an inward debate on the subject wasn't much of surprise but rather a given! Knowing of critics such as Stephen Marche and Stanly Fish, it is easy to see way it was the way it is.

I do however wonder which other disciplines we could better connect to? And whether it would be a better use of our time just understanding distant reading at its surface level or to keep a comparative with others too? (I would say comparing to others may help in the overall scheme of things).

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Reply to the reviewers

The reviews are on balance an accurate, thoughtful, thorough assessment of the manuscript. We appreciate the careful engagement with the B cell differentiation aspect of our work. We identify 2 major critiques from the reviews:

1. The manuscript should make stronger connections with existing literature on ____in-vitro _and _in-vivo ____B cell differentiation. We agree the manuscript should be revised to interact more holistically and carefully with relevant B cell differentiation research. In this respect, the reviewers both help by pointing to high-quality and relevant literature that will be discussed and cited.

The cytokine mixture we used on the B cells was not defined / described in the manuscript. This fact hinders the interpretation of the data because B cells will respond to diverse stimuli in quite different ways.

We agree this hinders interpretation of the data, and the reviewers bring up astute points about different types of stimuli (TD vs. TI vs. TLR vs. BCR). Unfortunately, the manufacturer of the product, Stem Cell Technologies, will not disclose exactly what is in the product. Given we are in strong agreement with the reviewers on this point, we analyzed the cytokine contents of the cocktail and our cell culture supernatants using a luminex cytokine panel. We present a discussion of our findings on this data in a supplementary note and figure. We acknowledge this analysis is non-exhaustive, because it does not include possible additions of non-cytokine stimulants. However, we maintain it adds much clarity to the interpretation of the data.

We note that the contents of the stimulation cocktail are knowable and well-defined. These attributes are in contrast to almost all B cell stimulation protocols of which are aware. Typical stimulation protocols use various types of feeder cells, cytokines, and FBS (Fetal Bovine Serum). In particular, the feeder cells and FBS, are highly variable between labs, lots, and even experiments. FBS has a myriad of issues which are described here (____https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349753/____). Major variability, from genomic to phenotypic, has been described in laboratory cell lines like the ones used as feeder cells. With respect to B cells specifically, large differences in B cell activation programs are observed between lots of FBS, as described here (____https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854248/#r5____). Additionally, we have observed the presence of bovine viruses and other contaminants in FBS (unpublished data). Thus, the stimulation protocol we used is reproducible and robust in ways generally unseen by us in B cell stimulation literature. In summary, we view this cocktail as useful in a similar way to how FBS is useful to biologists – a major difference being that this cocktail is better defined and controlled. We provide similar thoughts in our supplementary note.

A final general point we will make is about the significance of our work, which appears to be lost on Reviewer #1. Similar technical and conceptual advances by our lab have been cited 1000s of times. Thus, we think the impact of our scientific approach speaks for itself. Many of our results confirm and expand on previous literature about B cells. We deliberately chose to make this novel technical and conceptual advance in the well-studied system of B cell differentiation. This allows us to integrate our findings with prior literature and helps validate the general approach. Reviewer #1 has performed a scholarly service by independently verifying our findings are coherent with existing literature, and we thank them for that.

In response to the reviews, we have edited the manuscript to reference even more of the papers in the field which report similar findings. Thus, our concordance with prior literature should be viewed as a strength of the manuscript. It shows readers of the manuscript the conceptual framework we use here is valid and can generate similar insights in less well-studied systems. For example, the approach developed here could be used in non-B cells, non-human immune systems, or even non-model organisms. In response to the reviewers critique, we modified the discussion of our work in multiple places to emphasize these points.

Description of the planned revisions

Insert here a point-by-point reply that explains what revisions, additional experimentations and analyses are planned to address the points raised by the referees.

1) Which B cell activation protocol was used? No information is provided in the main text or supplementary information. Yet, this information is key to fully understand many of the conclusions of this work (e.g., ... memory B cells are intrinsically two-fold more persistent in vitro (2A)), which largely depend on the nature of the stimuli used in the in vitro B cell culture.

We used the B cell activation protocol developed by StemCell Technologies as described in our methods section. We agree the reader and scientific community would benefit from additional information about this cocktail. To this end, we added a discussion of the cocktail to the supplementary information. We also used a cytokine analysis panel to analyze the cocktail, which provided detailed although non-exhaustive information about what is in the cocktail.

2) It would be informative to use more than one B cell activation program, e.g., CD40L with or without a cytokine as well as CD40L vs. CpG-DNA. Authors make broad statements about B cell fates without discussing the impact of a given signal on a given B cell fate. For instance, do memory B cells follow the same differentiation program upon stimulation with CD40L, IL-4 or a combination of CD40L and IL-4? How about differences between a TD signaling program such as that provided by CD40L and IL-10 and TI signaling program such as that provided by CpG-DNA and IL-10?

This is a good point. We agree stimulation using a panel of different agents would be a worthwhile experiment. It stands as a goalpost for future studies. Currently, performing single cell RNA sequencing on so many samples is both beyond the scope of this manuscript and very resource intensive. ____

3) Page 3, first line: After low quality and non-B cells (Fig S1A & B). What does this statement mean? The sentence seems incomplete.

Thank you for catching this typo. It is now clarified in the manuscript that we removed these cells bioinformatically.

4) First, we noted that non-B cells present in the input rapidly became undetectable by day 4, which shows the specificity of the cytokines for B cell expansion. Which cytokines are we talking about? No detail is provided.

We now provide our analysis of the stimulation cocktail, in Supplementary note 1 and Supplementary figure 1A. We still believe it is an interesting observation that this cocktail specifically stimulates B cells because many cytokines are not specifically B cell division signals, there were some impurities in the input population, and many cytokines are produced by the cultured cells themselves.

5) Plasmablasts were not distinguished from plasma cells.

We agree this is an interesting and important distinction to make. We have now distinguished between these classes of cells.

6) Critically, we observed no appreciable evidence of hypermutation in vitro (S2C), consistent with prior literature (Bergthorsdottir et al. 2001). This statement is vague, misleading and likely inaccurate for the following reasons. (a) The B cell culture conditions used by the authors are completely unknown. (b) It was shown that SHM can be achieved under specific in vitro B cell culture conditions that include the presence of activated CD4+ T cells (PMID: 9052835; PMID: 10092799; PMID: 10878357; PMID: 12145648). Did authors try to recapitulate those culture conditions?

We see how this statement could be misunderstood. We only claim not to observe evidence of hypermutation in our specific culture conditions, which is important for the inferences we make. We added language to make this more clear.

We did not try to recapitulate the conditions in the references supplied by the reviewer. We note that these references use cell lines and not B cells. While there is immensely valuable work done on cell lines, they behave very differently from actual cells and these findings may not be relevant to our human B cells.

7) Some of the reported findings are repetitive of previously published results and provide no additional new information. For example:

1. a) "Interestingly, we found mutated B cells were far more likely to express genes involved in T cell interaction (2B), suggesting Memory B cells are intrinsically licensed to enter an inflammatory state which activates T cells". This evidence is already published (PMID: 7535180 among many other published studies).

We will cite this paper, which is a landmark study. We don’t claim we are the first to discover a propensity of mutated B cells to present help to T cells, but note that we were able to observe this fact via lineage tracing in a single experiment, which is a conceptual and technical advance. Additionally, we report an entire transcriptional module of genes which are upregulated in memory B cells vs. Naive B cells exposed to the same stimulus. This adds to the systematic understanding of the Memory B Cell activation program.

1. b) "Instead, Naive B cells were biased toward expressing lectins and CCR7, suggesting Naive B cells are intrinsically primed to home into the lymphatic system and germinal centers (2B)". This evidence is already published (PMID: 9585422 among many other published studies).

While this is an interesting and important paper referenced by the reviewer, we are unable to find anything similar to our claim about naive B cells in the reference provided. The investigators do not discuss intrinsic differences between memory and naive subsets when responding to the same stimulus.

8) We quantified the in vitro dynamics of CSR through the lens of mutation status, which revealed strongly different fate biases between germline and mutated cells (2D). Most strikingly, B cells which switched to IGHE were almost exclusively derived from germline progenitors: the ratio of germline IGHE cells to mutated IGHE cells was (8-fold - inf, 95 % CI). Also this evidence is not novel (PMID: 34050324 among other published studies) and, again, must reflect the presence of specific culture conditions that remain completely undisclosed. This is incredibly confusing.

Thank you for providing this reference, we were not aware of this interesting study. These studies are quite different and complementary. Differences between these studies likely reflect the fact that their B cells are isolated from a niche, rather than generated ____in-vitro_. Most of the tissue-resident cells in their study are quite mutated, and thus are not the Naive B cells we are making a claim abountj. In fact, despite their claim of low mutational load, these cells would fall into the “mutated” or even “heavily mutated” categories we defined in our paper. Cells with mutation levels of 5% are not thought to be Naive in any classification scheme. Our study showed that, _in vitro____, IGHE B cells effectively came exclusively from germline progenitors, their study shows no such result. The novelty of this finding was appreciated by reviewer 2.

9) Authors should mention that non-switched memory B cells include IgDlowIgM+CD27+ and IgD-IgM+CD27+ memory B cells. Some authors define these distinct memory B cell fractions as marginal zone (MZ) or MZ-like B cells (please, notice that splenic MZ B cells recirculate in humans) and IgM-only B cells, respectively (PMID: 28709802; PMID: 9028952; PMID: 10820234; PMID: 11158612; PMID: 26355154; PMID: 15191950; and PMID: 24733829 among many other published studies).

We appreciate these points. We attempted to classify our B cells within this taxonomy and found no such separation clearly exists in single-cell RNA-seq profiles. Instead, we opted to re-classify our data with a state-of-the-art algorithm called celltypist (DOI: 10.1126/science.abl5197____ )____ which harmonizes cell annotations across a growing number of single-cell RNA sequencing studies. While this classification system is not currently mutually exclusive / completely exhaustive, we believe using this system provides standardization and data availability that are key for sharing results. As single-cell RNA-seq and flow/mass cytometry harmonize their classification systems, anyone should be able to transfer their preferred classification scheme to the cells profiled here.

10) Thus, CSR from IGHM cells did not meaningfully contribute to the abundance of IGHA+ cells in the population. Also this conclusion may be misleading and/or inaccurate. Indeed, an efficient class switching to IgA requires the exposure of naïve B cells to the cytokine TFG-beta in addition to a robust TD (CD40L) or TI (CpG DNA or BAFF or APRIL) co-signal. Was TGF-beta present in this culture?

This is a good point about TGF-beta and switching to IgA. Here is a clear example of the novelty and power of our approach, as well as the benefits of using a well-characterized system such as B cell differentiation. Lineage tracing clarifies between two explanations for why there are IgA cells in the output population. One explanation is that non-IgA B cells in the input switch to IgA, driven by TGF-beta. Another explanation is that IgA cells in the input expand modestly and account for IgA cells in the output. Lineage tracing offers clear evidence that the latter explanation is true. Following from this, our approach allows us to make a strong inference that TGF-beta is not present in the incompletely determined cytokine mixture. We are not sure how this conclusion may be misleading or inaccurate, as it is a clear and simple description of our data, not a claim about what factors are necessary for switching.

11) In contrast, we noted that many intraclonal class-switching events appeared to be directly from IGHM to IGHE. Explanations involving unobserved cells with intermediate isotypes notwithstanding, these data illustrate the relative ease with which B cells can switch directly to IGHE. It is very difficult to interpret this statement, as no information regarding the B cell-stimulating conditions used is provided. In addition, relevant literature is not quoted (e.g., PMID: 34050324).

We clarify our discussion here to claim the ease with which peripheral blood IGHM B cells switch to IGHE. Again, lineage tracing has allowed us to distinguish between two very different population-level phenomena. One explanation is that undetected IGHE+ progenitors in the input population expanded rapidly and account for the IGHE+ cells. Another explanation is that cells class-switch to IGHE. Our data are consistent with the latter. We note that this validates the conceptual use of lineage tracing to understand rapid population dynamics in immune responses and cell differentiation protocols. This is a strength of our manuscript. We appreciate the the reviewer has furnished relevant studies, which we will cite.

12) Our data for IGHE cells contrasts with in vivo data which show IgE B cells to be: (1) very rare, (2) apparently derived from sequential switching (e.g. from IgG1 to IgE) (Horns et al., 2016; Looney et al., 2016), and (3) often heavily hypermutated (Croote et al., 2018).

While this reviewer agrees with the first comment (switching to IgE is relatively rare in vivo, at least in healthy individuals), the other statements are quite inaccurate. Indeed, unmutated extrafollicular naïve B cells from tonsils and possibly other mucosal districts directly class switch from IgM to IgE in healthy individuals, thereby generating a low-affinity IgE repertoire. In principle, low-affinity IgE antibodies may protect against allergy by competing with high-affinity IgE specificities. In allergic patients, high-affinity IgE clones emerge from class-switched and hypermutated memory B cells that sequentially switch from IgG1 or IgA1 to IgE as a result of specific environmental conditions, including an altered skin barrier (PMID: 22249450; PMID: 30814336; PMID: 32139586).

Moreover, in contrast to what stated by authors, sequential IgG1/IgA1-to-IgE class switching mostly occurs in allergic patients but is less frequent in healthy individuals, where IgE specificities are less mutated (PMID: 30814336). Along the same lines, IgE is heavily mutated only in allergic individuals with significant molecular evidence of sequential IgG1/IgA1-to-IgE class switching (PMID: 30814336; PMID: 32139586). Overall, the data provided by Swift M. et al. are largely confirmatory of previously published evidence.

We appreciate the clarification of this complex field and will cite the relevant literature. We also agree with the reviewers assessment that our data are validated by other approaches and groups. We see that our discussion of IgE B cells should have included that caveat that we are discussing IgE B cells detected in the peripheral blood. We have restricted claim to the suggestion that if our conditions mimic such niches where B cells switch to IgE, there are clearly efficient mechanisms which limit the amount of circulating IGHE B cells mechanisms in comparison to other isotypes.____

Taken together, these data suggest that while direct switching to IGHE from Naive progenitors is trivial in vitro, niche factors or intrinsic death programs efficiently limit their generation or lifetime in vivo." I cannot understand this conclusion, which seems to contradict earlier statements.

We hope we have clarified via the above comment.

13) I am not sure I learned much regarding the "cell-intrinsic" fate bias and transcriptional memory of B cells after reading this elegantly presented but confusing and superficially discussed manuscript (please, see also comments 15-23).

We understand the reviewer is confused about various aspects of our manuscript and appreciate the opportunities to clarify. We show cells with broad identities (such as germline vs. mutated or naive vs. memory) respond differently to the same stimulus. These are cell intrinsic fate biases. We quantify them and provide statistical bounds on the effect sizes of these differences, which to our knowledge has not been done. We agree with the reviewer that in the case of memory and naive B cells, much is already known about their biases. We recapitulate some of this knowledge, while adding a quantitative and an unbiased transcriptomic lens with which to view the biases. However, our analysis moves beyond cell types broadly defined, and focuses on the concept that each clone is a cell state or identity, where some of the identity may be faithfully propagated over generations and other information may not be. To this end, we tracked the transcriptome of clones during differentiation. We show that B cell clones share highly similar cell fates, implicating cell-intrinsic heterogeneity as a major contribution to diversity in immune responses. We note this reviewer did not critique this aspect of our work. The review also did not critique Figure 3 or 4, in which we present a quantitative analysis of which transcriptional programs are maintained by B cells and contribute to their clonal identity. Finally, via our analysis of human long-lived plasma cells, we report these transcriptional identities are observed in-vivo, over long time scales. This type of cell-intrinsic bias has not been studied or described to our knowledge. These findings were of particular interest to reviewer 2 and other readers of the manuscript.

MINOR COMMENTS

Thank you for reading the manuscript carefully and providing these comments and observations. We have fixed all clerical errors that were pointed out. We also responded to some of these minor comments here, and made changes to the manuscript to clarify.

1) Figures 1B, S1C and S1D are not referred to in the text. x

2) 2B in the Text is 2D in the Figure. x

3) 2D in the Text is 2E in the Figure. x

4) Figure 2D seems to show only 10 genes. Please, clarify.

We clarify in the manuscript that we present the top differentially expressed genes

5) 2E in the text is 2F in the Figure. x

6) Figure S3B is not indicated in the text. x

7) Figure 3E is not indicated in the text. x

8) Figure S4A is not indicated in the text. x

9) In some sections of the text, Figure panels are not sequentially discussed, which makes the text very difficult to follow. x

Reviewer 2:

Major comments:

On p.3 the authors assume that a B cell with an unmutated BCR in the time course arose from a naive B cell progenitor. However, it is also possible that it arose from a IgM memory B cells since they also contain a non-negligible proportion of cells with 0 mutations. This was initially seen already in the Klein, J Exp Med, 1998 paper and later confirmed by e.g. Weller et al, J Exp Med, 2008 and Wu et al, Front Immunol, 2011. And since the authors herein and others have demonstrated that IgM memory B cells have a high proliferative capacity it is possible that IgM memory B cells are overrepresented among those unmutated BCRs seen in the cultures.

The finding that IgM memory B cells are highly proliferative is not novel. It has been demonstrated by other groups before and one good example is Seifert et al, PNAS, 2015 where IgM memory B cells proliferated significantly more to BCR stimulation than naive or IgG memory B cells. However, it is also shown that IgG memory B cells are more responsive to TLR9 stimulation than IgM memory B cells as demonstrated by e.g. Marasco et al, Eur J Immunol, 2017. This is not discussed by the authors and should be added into the discussion for context of their finding by scRNAseq methods.

These are astute points. We incorporated a more nuanced discussion of the prior literature about highly proliferative IgM memory B cells, which have been reported before. We also added a figure which identifies the genes associated with proliferative clones in Figure 3d, which adds to our understanding of the gene regulatory networks which govern IgM memory B cell behavior. We appreciate the reference to the Seifert et al paper, which is relevant and high quality work. We concur that a discuss of Marasco would be helpful, especially because it is unknown if a TLR9 agonist is in the stimulation cocktail, but their data would suggest there is not.

The notion that a memory transcriptional program can be induced without SHM is not novel and this should be brought up in the discussion. One paper showing a memory transcriptional program in unmutated memory B cells is Kibler et al, Front Immunol, 2022.

We were not aware of this literature and have now cited it in our discussion of this finding.

The observation that memory B cells are more likely to enter an inflammatory state and support T cells has been suggested by other groups (Seifert et al, PNAS, 2015; Magri et al, Immunity, 2017, Grimsholm et al, Cell Reports, 2020).

We have now cited and discussed a number of papers which contain similar findings. We note that we add to the holistic understanding of this phenomenon via our single cell transcriptomic approach.

Please provide the age distribution of the peripheral blood samples as well.

We have now provided the age distribution of the peripheral blood samples

Please show flow cytometry analysis of the cultures to assist in assessing subset distribution, viability and plasma cell differentiation for each time point. This can be provided as supplementary information.

We did not use flow cytometry for subset distribution and measurements of differentiation per se, only to exclude non-viable cells and we have now made this clearer in the methods section. We also now include representative plots show our sorting strategy.

The stimulation cocktail used for this study, what does it contain? This needs to be specified in the manuscript and not only referring to the manufacturer. This has major impact on the results since different stimulatory agents will induce different pathways.

This is a valid point that we addressed in our response to reviewer 1. See supplementary note 1 and Figure S1A for our analysis of the stimulation cocktail.

Minor comments:

Please avoid the term plasma B cells, does it refer to plasmablasts and/or plasma cells?

Thank you for the suggestion, we have modified our language to refer to plasmablasts and plasma cells separately.

Author Response

Reviewer #1 (Public Review):

In this manuscript by Kim et al., the authors use live-cell imaging of transcription in the Drosophila blastoderm to motivate quantitative models of gene regulation. Specifically, they focus on the role of repressors and use a 'thermodynamic' model as the conceptual framework for understanding the addition and placement of the repressor Runt, i.e. synthetic insertion of Runt repressor sites into the Bicoid-activated hunchback P2 enhancer. Coupled with kinetic modeling and live-cell imaging, this study is a sort of mathematical enhancer bashing experiment. The overarching theme is measuring the input/output relationship between an activator (bicoid), repressor (runt), and mRNA synthesis. Transcriptional repression is understudied in my opinion. One finding is that the inclusion of cooperativity between trans-acting factors is necessary for understanding transcriptional regulation. Most, if not all, of the tools used in this paper have been published elsewhere, but the real contribution is a deep, quantitative dissection of transcriptional regulation during development. As such, the only real questions for this referee are whether the modeling was done rigorously to produce some general biological conclusions. By and large, I think the answer is yes.

We thank the reviewer for this thoughtful evaluation of our work. We agree with the reviewer’s assessment that transcriptional repression, especially the quantitative dissection of transcriptional repression, is understudied compared to transcriptional activation.

Comments:

Fig. 6 was the most striking figure for this referee, specifically that different placements of Runt molecules on the enhancer lead to distinct higher order interactions. I am wondering if the middle data column in Fig. 6 represents a real difference from the other two, and if so, it seems that the positioning - as opposed to simply the stoichiometry - is essential in cooperativity. This conclusion implies that transcriptional regulation is more precise than what some claim is just a mushy ball of factors close to a promoter. In other words, orientation may matter. Proximity may matter. Interactions in trans matter.

We thank the reviewer for pointing out a feature of our data that we did not emphasize enough originally. Indeed, the construct in the middle column, which we termed [101], could be better recapitulated with the simplest model of zero free parameters than the other two constructs. As the reviewer pointed out, this raises an interesting question about the “grammar” of an enhancer: the placement and orientation of binding sites for transcription factors might matter yet we do not have a clear understanding of the logic. We have now incorporated a discussion of this topic in the Discussion section.

There needs to be at least one prediction which is validated at the level of smFISH / mRNA in the embryo. Without detracting from the effort the authors have expended in looking directly at transcription, if the effects can't be felt by the blastoderm at the level of mRNA/cell, it becomes difficult to argue for the relevance to development. Also, I feel there is little chance that these measurements can be quantitatively replicated unless translated to the level of total protein or mRNA. Such a measurement (orthogonal quantitative confirmation of the repressor cooperativity result) would also assuage my concern about the time averaging as shown in Fig. S3.

Our study focused on predicting the initial rate of transcription because it is the measurable quantity that most directly relates to the binding and action of the transcriptional activators and repressors used in this study. We argue that the action of transcription factors would be more accurately assessed by monitoring the rate of transcription, rather than the accumulated mRNA, which could be confounded by the dynamics of the whole transcription cycle—initiation, elongation and termination—as well as nuclear export, diffusion and degradation of transcripts. We are, of course, excited to eventually be able to predict a whole pattern of cytoplasmic mRNA over space and time from knowledge of the enhancer sequence. However, if we cannot predict the initial rate of RNA polymerase loading dictated by an enhancer, we argue that there is little hope in predicting such cytoplasmic patterns. We emphasized this point in the Discussion (Line XX-YY). Regardless, to assuage the reviewer’s concern, we have performed additional analyses to assess the effect of repression at the level of accumulated mRNA.

First, we have quantified the accumulated mRNA during nuclear cycle 14, which is the time window that we have focused on in this study. To make this possible, we have integrated the area under the curve of MS2 time traces which has been already shown to be a reporter of the total amount of mRNA produced by FISH (Garcia et al., Current Biology 23:2140, 2013;Lammers et al., PNAS 17:836, 2020). This integration reporting on accumulated mRNA is now shown for all constructs in the presence and absence of Runt protein in the new Figure S17. This figure clearly shows that the consequences of repression are present in the blastoderm, not just at the level of transcriptional initiation, but also at the level of accumulated mRNA.

We then compared the accumulated mRNA profiles shown in Figure S17 to the initial rate of RNAP loading at each position of the embryo along the anterior-posterior axis for all constructs in the presence and absence of Runt protein. These new results are shown in a new figure, Figure S19. Interestingly, we saw a good correlation (Pearson correlation coefficient of 0.90) between these two metrics. Thus, we argue that our conclusion that higher-order cooperativity is necessary to account for the initial rate of RNA polymerase loading would still hold for predicting the accumulated mRNA.

Reviewer #3 (Public Review):

The authors have presented results from carefully planned and executed experiments that probe enhancer-drive expression patterns in varying cellular conditions (of the early Drosophila embryo) and test whether standard models of cis-regulatory encoding suffice to explain the data. They show that this is not the case, and propose a mechanistic aspect (higher order cooperativity) that ought to be explored more carefully in future studies. The presentation (especially the figures and schematics) are excellent, and the narrative is crisp and well organized. The work is significant because it challenges our current understanding of how enhancers encode the combinatorial action of multiple transcription factors through multiple binding sites. The work will motivate additional modeling of the presented data, and experimental follow-up studies to explore the proposed mechanisms of higher order cooperativity. The work is an excellent example of iterative experimentation and quantitative modeling in the context of cis-regulatory grammar. At the same time, the work as it stands currently raises some doubts regarding the statistical interpretation of results and modeling, as outlined below.

We thank the reviewer for noting the significance of our work. We tried our best to address the concerns of the reviewer regarding the statistical interpretation of results and theoretical modeling throughout our responses below.

The results presented in Figure 5 are used to claim that the data support (i) an unchanging K_R regardless of the position of the Runt site in the enhancer and (ii) an \omega_RP that decreases as the site goes further away from the promoter, as might be expected from a direct repression model. This claim is based on only testing the specific model that the authors hypothesize and no alternative model is compared. For instance, are the fits significantly worse if \omega_RP is kept constant and the K_R allowed to vary across the three sites. If different placements of the Runt site can result in puzzling differences in RNAP-promoter interaction, it seems entirely possible that the different site placements might result in different K_R, perhaps due to unmodeled interference from bicoid binding. Due to these considerations, it is not clear if the data indeed argue for a fixed K_R and distance-dependent \omega_RP.

We apologize for the lack of justification in assuming that Kr remains constant and wrp varies depending on the position of the Runt binding sites. Following the reviewer’s suggestion, we tested the alternative scenarios where we either fix or vary different combinations of wrp and Kr for our one-Runt binding site constructs. The result is now shown in a new figure, Figure S16. In short, as reported by the Akaike Information Criterion (AIC) in Figure S16F, the MCMC fit explains the data best in the scenario of fixed Kr and different wrp values for one-Runt binding site constructs. Furthermore, we also performed the MCMC inference in the case where we varied both Kr and wrp values across constructs. From this analysis, we obtained similar values of Kr while having different values of wrp across constructs as shown in Figure S16G. Overall, we believe that this evidence strongly supports our assumption of having consistent Kr values but different wrp values for the one-Runt binding site constructs.

Results presented in Figure 6 make the case that higher order cooperativity involving two DNA-bound molecules of Runt and the RNAP is sufficient to explain the data. The trained values of such cooperativity in the three tested enhancers appear orders of magnitude different. As a result, it is hard to assess the evidence (from model fits) in a statistical sense. Indeed, if all of the assumptions of the model are correct, then using the high-order cooperativity is better than not using it. To some extent, this sounds statistically uninteresting (one additional parameter, better fits). It is not the case that the new parameter explains the data perfectly, so some form of statistical assessment is essential.

The inferred cooperativity values are indeed orders of magnitude different. However, the cooperativity terms can be also written as “w = exp(-E/(kBT))”, where the E is the interaction energy, kB is the Boltzmann constant, and T is the temperature. As a result, we should compare the magnitude of the different cooperativities on a log-scale. In brief, the interaction energies wrr from the three two-Runt binding site constructs range between 0 and 1kBT, and the higher-order cooperativity wrrp has an energy between -2 and 4kBT. Interestingly, these energies are of the same order of magnitude as the interaction energies typically reported for bacterial transcription factors (e.g., Dodd et al., Genes and Development 18:344-54, 2004). It is important to note that our inferred interaction energies could be either positive or negative, suggesting that both cooperativity and anti-cooperativity can be at play depending on the architecture of the two Runt binding sites. We now report on these interactions in the language of energies Table S1 and elaborate on this in the Discussion section (Line XX-YY).

Finally, following the reviewer’s suggestion on statistical assessment of whether addition of parameters indeed explains the data better, we adopted the Akaike Information Criterion (AIC) as a metric to compare different models used in Figure 6 and now show the results in a new panel, panel G. Briefly, AIC is calculated by assessing the model’s ability to explain the data while penalizing for having more parameters. The smaller the AIC value is, the better the model explains the data. As we have claimed, the AIC showed a dramatic decrease when adopting the higher-order cooperativity as shown in Figure 6G. Thus we argue that the addition of higher-order cooperativity, while not being able to completely explain the data, is indeed capable of increasing the agreement between experiments and theory across all our two-Runt site constructs.

Moreover, it is not the case that the model structure being tested is the only obvious biophysics-driven choice: since this is the first time that such higher order effects are being tested, one has to be careful about testing alternative model structures, e.g., repression models that go beyond direct repression and pairwise cooperativity that goes beyond the traditional approach of a single (pseudo)energy term.

We agree with the reviewer that alternative models with different mechanisms of repression should be mentioned. We have clarified this point further in Discussion (Line XX -YY). In summary, we tested both “competition” and “quenching” models of repression as proposed in Gray et al, (Genes and Development 8:1829, 1994). Interestingly, Figure S5 shows that the “competition” model gives a worse fit compared to the “direct repression” and “quenching” models for the one-Runt binding site cases. We further tried to test these alternative models in the case of two-Runt binding sites constructs. The result is shown in Figure S7 (competition) and S8 (quenching). These figures also reveal that the “competition” model underperformed compared to the “direct repression” or “quenching” models. For the “quenching” model to fit the data, we also had to invoke higher-order cooperativity that is beyond pairwise cooperativity. Thus, we believe that the requirement of higher-order cooperativity holds regardless of the choice of the specific model. Of course, our models of repression are very likely an oversimplification of how repressors actually work. However, given that these simple models have been a prevalent choice of proposed mechanisms for repression in the field of transcriptional repression for the past decades, we believe that the significance of our work lies in the fact that we challenged these models by turning them into precise mathematical statements (in the form of widespread thermodynamics models) and confronting them with quantitative data.

The general theme seen in Figure 6 is seen again in Figure 7, when a 3-site construct is tested: model complexities inferred from all of the previous analyses are insufficient at explaining the new data, and new parameters have to be trained to explain the results. The authors do not seem to claim that the higher order cooperativity terms (two parameters) explain the data, rather that such terms may be useful.

We agree that our previous approach was confusing. Figure 7A indeed incorporated all inferred parameters from the previous rounds of inference (Kb, wbp, p, R, as well as Kr, wrp, wrr, and wrrp). However, it is clear that this set of parameters, even including the higher-order cooperativity from two-Runt binding sites cases, was not enough to explain the data from three-Runt binding sites case. Thus, we had to invoke another free parameter, which we termed wrrrp, to explain the data. We have revised Figure 7B such that it is now showing the “best” MCMC fit which explains the data quite well (instead of just showing the “improvement” of fits).