Reviewer #2 (Public Review):

Summary:

The ability of cardiac cells to regenerate has been the object of intense (and sometimes controversial) research in biology. While lower organisms can robustly undergo cardiac regeneration by reactivation of the embryonic cardiogenic pathway, this ability is strongly reduced in mice, both temporally and qualitatively. Finding a way to derive precursor cells with regenerative ability from differentiated cells in mammals has been challenging.

Zhou, He, and colleagues hypothesized that ISL-1-positive cells would show regenerative capacity and developed a small molecules screen to dedifferentiate cardiomyocytes (CM) to ISL1-positive precursor cells. Using hESC-derived CM, the authors found that the combination of both, WNT activation (CHIR99021) and p300 acetyltransferase inhibition (A-485) (named 2C protocol) induces CM dedifferentiation to regenerative cardiac cells (RCCs). RCCs are proliferative and re-express embryonic cardiogenic genes while decreasing the expression of more mature cardiac genes, bringing them towards a more precursor-like state. RCCs were able to differentiate into CM, smooth muscle cells, and endothelial cells, highlighting their multipotent property. In vivo, administration of 2C in rats and mice had protective effects on myocardial infarction.

Mechanistically, the authors report that the 2C protocol drives CM-specific transcriptional and epigenetic changes.

Strengths:

The authors made a great effort to validate their data using orthogonal ways, and several hESC lines. The use of lineage tracing convincingly showed a dedifferentiation from CM. They translate their findings into an in vivo model of myocardial injury, and show functional cardiac regeneration post-injury. They also showed that 2C could surprisingly be used as a preventive treatment. Together their data may suggest a regenerative effect of 2C both in vitro and in vivo settings. If confirmed, this study might unlock therapeutic strategy for cardiac regeneration.

Weaknesses:

Several points remain puzzling to me and some aspects of this study need to be clarified and extended:

General comments:

* Experimental design & Interpretation*

1) The main hypothesis (line 50) that Isl1 cells have regenerative properties is not extremely novel (10.1172/jci.insight.80920, doi.org/10.1038/nature03215,10.1016/s1534-5807(03)00363-0).

2) Based on Table S1, concentration of A-485 used in the screen is 10uM but used throughout this study at 0.5um. Could the authors provide a rationale for this 20x reduction of concentration? It would be useful to get a titration of this compound for the effects tested.

3) It is confusing to clearly understand what proportion of CMs dedifferentiate to become RCCs. The lineage tracing data suggests only 0.6%-1.5% of cells undergo this transition. It is difficult to understand how such a small fraction can have wide effects in their different experimental settings. This is specifically true when the author quantified nuclear and cytosolic area on brightfield pictures - would the same effect on nuclear/cytosolic area be observed in Isl1 KO cells?

4) The authors totally disregard the effect of i-BET-762 that gives a very similar percentage of Isl1-positive cells when combined to 2C (Supp. 1E). What is the effect of CHIR + I-BET-762 alone?

5) It is really hard to understand the contradictory effects of A-485 on acetylation status. The authors mentioned that A-485 only has an effect on H3K27Ac and not on H3K9Ac (line 221) to later (line 226) contradict themselves by saying it also has an effect on H3K9Ac. To explain this discrepancy, the authors vaguely mentioned "further analyses" without giving any other details. It would be transparent to explain what led to this radical change in interpretation.

6) The difference in the ChIP peak height is rather minimal for the H3K9Ac data. Were the peaks normalized to the sequencing depth? What does the y-axis represent on these ChIP traces (number of counts?)

7) Would it be possible to test this 2C protocol on mESC and see if similar changes occur? How transcriptionally different would these mouse RCCs be to Isl1+ progenitors isolated from neonatal mice (P1-P5)?

Statistics & Data acquisition

1) The authors mentioned experiments were done at least 3 times and each dot plotted on a graph is an average of technical repeat for one biological repeat. My understanding would be that if I see 9 dots, it means the experiment has been done 9 times - What would be the rationale for such a high number of repeats? It is an "artificial" way to increase the power of a test and might lead to misinterpretation of the data. This becomes relevant for some figures where biological difference is minimal and they still show statistical differences (e.g. Supp 2E, Supp 3A, Supp 9C,...). This is also true for in vivo section (Fig. 4G).

It would help to have a precise clarification between technical and biological repeats in the figure legends (e.g. n=3 biological repeat (aka 3 dots on a graph) obtained from averaging XX technical repeats), as well as the specific test stated the legend in addition to the general paragraph in the methods. Providing raw numerical data so readers can re-test them independently would also be a transparent way to do it.

2) Does the author test for normality before applying a specific test? Please clarify and justify either way.

3) If each dot represents a biological repeat as stated in the method section, why do some datasets have different numbers of repeats between NC and 2C if obtained in parallel? Have repeats been excluded?

Reviewer #3 (Public Review):

Summary:

The manuscript by Zhou and colleagues describes the potential of a two-compound combination (2C), CHIR99021 and A-485, which can generate regenerative cardiac cells (RCCs) from human embryonic stem cell-derived TNNT2+ cardiomyocytes. The authors have also demonstrated this phenomenon in neonatal rats CMs in vitro. Further, the administration of 2C can generate RCCs in adult mouse hearts and significantly improve survival and cardiac function in mice subjected to myocardial infarction. Interestingly, 2C treatment induces global changes in transcription and epigenetic modifications.

Strengths of the study:

1. This study describes the potential of 2C in improving the regeneration of the heart post-MI. The findings may have a translation potential. The idea of promoting the regenerative capacity of the heart by reprogramming CMs into RCCs is interesting.

2. The authors have validated the effect of 2C independently in hESCs, rat CMs, and a model of MI.

3. The authors explored the mechanism by Single-cell RNA-seq and Chip-Seq, which points to the transcriptional and epigenetic activation of genes essential for RCC.

Weaknesses of the study:

1. The mechanism involved in the 2C-mediated generation of RCCs is still unclear. The leads found in the RNA-seq and ChIP-seq were not validated experimentally.

2. Considering the very low number of RCCs (0.6%-1.5% of cells) generated, I cannot comprehend how the heart is protected from MI. Did the author believe 2C would affect the survival or metabolism of existing CM under hypoxia? What percentage of cells were regenerated by 2C treatment post-MI?

3. I would like to know about administering 2C in mice, which could have generated RCCs- dedifferentiated CMs in the heart. Does 2C affect the cardiac functions in mice under basal conditions? Also, does 2C administration affect any physiology in mice? The cardiac structural and functional parameters are required post-2C administration.

4. It is also not tested whether 2C would affect other cell types of the heart, including fibroblasts and endothelial cells, in vitro and in vivo. Assuming the level of protection by 2C in mice, it would affect other cell types.

5. It is still being determined how the authors chose the dose of 2C for in vivo and in vitro studies, although the concentration used for screening is different. Assessing the effect of 2C in a dose-dependent manner is essential.

6. A-485 affects H3K27Ac but not H3K9Ac. However, data show that both H3K27Ac and H3K9Ac are affected. An explanation is required.

7. The authors use "regeneration" even at the screening stage. I am wondering if regeneration could be assessed by the experimental approach they adopted.

Reviewer #4 (Public Review):

Overview:

The present manuscript by Zhou and colleagues investigates the impact of a new combination of compounds termed CHIR99021 and A-485 on stimulating cardiac cell regeneration. This manuscript fits the journal and addresses an important contribution to scientific knowledge. However, the following major revisions need to be addressed as stated below.

Major comments:

-The authors should include more information that clarifies and justifies their hypothesis.<br /> -The story line is not well developed and thus not convincing since the results from different sections are not well connected.<br /> -The main text needs to be improved, and authors should explain their purpose in choosing to study ISL1-CMs. Also, to well argument why they conducted this study and its significance.<br /> -Page 3, row 57-58: Please add the references.<br /> -Page 3-4, row 67-68, authors stated "When CMs resumed contraction, they were treated with individual small molecules from a collection of over 4,000 compounds for 3 days (SI Appendix, Fig. S1C and Table S1), and then fixed and immunostained with ISL1". Please explain better, and show the results of the selected screening compounds.<br /> -Authors must make an effort to discuss their findings in a bold way in order to provide a comprehensive and articulate explanation of their results to the readers. There is much information missing from this section. This should also propose new research avenues and foresee the challenges in future investigations.<br /> -Authors must include a conclusion and future perspectives of this study.<br /> - Page 4, row 73, the authors stated that the unique compound combination 'CHIR99021 and A-485' was found to be the most efficient in promoting ISL1 expression with a healthy cell state. However, the authors should prove that by showing at least the cell viability of these compound combinations at different concentrations and timings as a supplementary figure.<br /> -There is some missing information in the methods part, for example, "Images were captured using a confocal Zeiss LSM710 and Olympus IX83 inverted microscope"; authors should include the objective used and the image size, and should include which method they used to analyze the acquired images.<br /> -Figure S3A shows that the TNNT2 mRNA expression was completely absent after 60 hours of 2C administration. Authors should explain this further.<br /> -Figure 3J, there is high variability in the graph of mCherry cells (%). Please choose a better graph, or increase the independent experiment.<br /> -Authors did not explain/discuss their results of the DNA-binding motif analysis of ISL1 in the cells treated with A-485 or 2C (Figure 7K).<br /> -Figure S1B and D: the image's labeling is not clear. In the exact same figure S1B, how can the authors explain the reduction of ISL cells? Do the authors make the treatment with the compound CHIR99021 as shown in figure S1A? If so, the authors should clarify the ISL reduction in Figure S1B.<br /> -Figure 1H: please improve the immunoblot, the level of B-actin does not match among the different conditions, or provide a relative quantification of the proteins.<br /> -Please indicate further information in the methodology part about the compounds used in this study.<br /> -Figures are not well justified and figure legends are not sufficient enough to explain the figures.<br /> -Please improve the figure legends by including more further information; for example, in Figure 2SH it is highlighted only the "DAPI (4′,6-diamidino-2- phenylindole) staining labeled nuclei as blue" but how about the other markers?<br /> -Figure 2F: the graph shows some high variations in "ns" between NC at 2C and in 60h+3d. I would recommend increasing the independent experiments. Similar observation goes also for figure 2E.<br /> -Authors should provide limitations of this study.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript authored by Stockner and colleagues delves into the molecular simulations of Na+ binding pathway and the ionic interactions at the two known sodium binding sites site 1 and site 2. They further identify a patch of two acidic residues in TM6 that seemingly populate the Na+ ions prior to entry into the vestibule. These results highlight the importance of studying the ion-entry pathways through computational approaches and the authors also validate some of their findings through experimental work. They observe that sodium site 1 binding is stabilized by the presence of the substrate in the s1 site and this is particularly vital as the GABA carboxylate is involved in coordinating the Na+ ion unlike other monoamine transporters and binding of sodium to the Na2 site stabilizes the conformation of the GAT1 by reducing flexibility among the helical bundles involved in alternating access.

Strengths:<br /> The study displays results that are generally consistent with available information from experiments on SLC6 transporters particularly GAT1 and puts forth the importance of this added patch of residues in the extracellular vestibule that could be of importance to the ion permeation in SLC6 transporters. This is a nicely performed study and could be improved if the authors could comment on and fix the following queries.

Weaknesses:<br /> 1. How conserved are the residue pair of D281-E283 in other SLC6 transporters. The authors commented on the presence of these residues in SERT but it would be nice to know how widespread these residues are in other SLC6 transporters like NET, GlyT, and DAT.

2. Further, one would like to see the effect of individual mutations D281A and E283A on transport, surface expression, and EC50 of Na+ to gauge the effect on transport.

3. A clear figure of the S1 site where Na+ tends to stay prior to Na1 site interactions needs to be provided with a clear figure. Further, it is not entirely clear how access to S1 is altered if the transporter is in an outward-occluded conformation if F294 is blocking solvent access. Please comment.

4. The p-value of the EC50 differences between GAT1WT and GAT1double mutant need to be mentioned. The difference in sodium dependence EC50 seems less than twofold and it would be useful to mention how critical the role of the recruitment site is. Since the transport is not affected the site could play a transient role in attracting ions.

5. It would be very nice to know how K+ ions are attracted by this recruitment site. This could further act as a control simulation to test the preference for Na+ ions among SLC6 members.

6. Some of the important figures are not very clear. For instance, there should be a zoomed-in view of the recruitment site. The current one in Fig. 1b and 1c could be made clearer. Similarly as mentioned earlier the Na residence at the S1 site away from the Na1 and Na2 sites needs to be shown with greater clarity by putting side chain information in Fig. 6d.

7. The structural features that comprise the two principle components PC1 and PC2 should be described in greater detail.

Reviewer #2 (Public Review):

Summary:<br /> Starting from an AlphaFold2 model of the outward-facing conformation of the GAT1 transporter, the authors primarily use state-of-the-art MD simulations to dissect the role of the two Na+ ions that are known to be co-transported with the substrate, GABA (and a co-transported Cl- ion). The simulations indicated that Na+ binding to OF GAT depends on the electrostatic environment. The authors identify an extracellular recruiting site including residues D281 and E283 which they hypothesized to increase transport by locally increasing the available Na+ concentration and thus increasing binding of Na+ to the canonical binding sites NA1 and NA2. The charge-neutralizing double mutant D281A-E283A showed decreased binding in simulations. The authors performed GABA uptake experiments and whole-cell patch clamp experiments that taken together validated the hypothesis that the Na+ staging site is important for transport due to its role in pulling in Na+.

Detailed analysis of the MD simulations indicated that Na+ binding to NA2 has multiple structural effects: The binding site becomes more compact (reminiscent of induced fit binding) and there is some evidence that it stabilizes the outward-facing conformation.

Binding to NA1 appears to require the presence of the substrate, GABA, whose carboxylate moiety participates in Na+ binding; thus the simulations predict cooperativity between binding of GABA and Na+ binding to NA1.

Strengths:<br /> - MD simulations were used to propose a hypothesis (the existence of the staging Na+ site) and then tested with a mutant in simulations AND in experiments. This is an excellent use of simulations in combination with experiments.

- A large number of repeat MD simulations are generally able to provide a consistent picture of Na+ binding. Simulations are performed according to current best practices and different analyses illuminate the details of the molecular process from different angles.

- The role of GABA in cooperatively stabilizing Na+ binding to the NA1 site looks convincing and intriguing.

Weaknesses:<br /> - Assessing the effects of Na+ binding on the large-scale motions of the transporter is more speculative because the PCA does not clearly cover all of the conformational space and the use of an AlphaFold2 model may have introduced structural inconsistencies. For example, it is not clear if movements of the inner gate are due to an AF2 model that's not well packed or really a feature of the open outward conformation.

- Quantitative analyses are difficult with the existing data; for example, the tICA "free energy" landscape is probably not converged because unbinding events haven't been observed.

Reviewer #1 (Public Review):

Summary:<br /> Bendzunas, Byrne et al. explore two highly topical areas of protein kinase regulation in this manuscript. Firstly, the idea that Cys modification could regulate kinase activity. The senior authors have published some standout papers exploring this idea of late, and the current work adds to the picture of how active site Cys might have been favoured in evolution to serve critical regulatory functions. Second, BRSK1/2 are understudied kinases listed as part of the "dark kinome" so any knowledge of their underlying regulation is of critical importance to advancing the field.

Strengths:<br /> In this study, the author pinpoints highly-conserved, but BRSK-specific, Cys residues as key players in kinase regulation. There is a delicate balance between equating what happens in vitro with recombinant proteins relative to what the functional consequence of Cys mutation might be in cells or organisms, but the authors are very clear with the caveats relating to these connections in their descriptions and discussion. Accordingly, by extension, they present a very sound biochemical case for how Cys modification might influence kinase activity in cellular environs.

Weaknesses:<br /> I have very few critiques for this study, and my major points are barely major.

Major points<br /> 1. My sense is that the influence of Cys mutation on dimerization is going to be one of the first queries readers consider as they read the work. It would be, in my opinion, useful to bring forward the dimer section in the manuscript.

2. Relatedly, the effect of Cys mutation on the dimerization properties of preparations of recombinant protein is not very clear as it stands. Some SEC traces would be helpful; these could be included in the supplement.

3. Is there any knowledge of Cys mutants in disease for BRSK1/2?

4. In bar charts, I'd recommend plotting data points. Plus it is crucial to report in the legend what error measure is shown, the number of replicates, and the statistical method used in any tests.

5. In Figure 5b, the GAPDH loading control doesn't look quite right.

6. In Figure 7 there is no indication of what mode of detection was used for these gels.

9. Recombinant proteins - more detail should be included on how they were prepared. Was there a reducing agent present during purification? Where did they elute off SEC... consistent with a monomer of higher order species?

Reviewer #2 (Public Review):

Summary:<br /> In this study by Bendzunas et al, the authors show that the formation of intra-molecular disulfide bonds involving a pair of Cys residues near the catalytic HRD motif and a highly conserved T-Loop Cys with a BRSK-specific Cys at an unusual CPE motif at the end of the activation segment function as repressive regulatory mechanisms in BSK1 and 2. They observed that mutation of the CPE-Cys only, contrary to the double mutation of the pair, increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells. Molecular modeling and molecular dynamics simulations indicate that oxidation of the CPE-Cys destabilizes a conserved salt bridge network critical for allosteric activation. The occurrence of spatially proximal Cys amino acids in diverse Ser/Thr protein kinase families suggests that disulfide-mediated control of catalytic activity may be a prevalent mechanism for regulation within the broader AMPK family. Understanding the molecular mechanisms underlying kinase regulation by redox-active Cys residues is fundamental as it appears to be widespread in signaling proteins and provides new opportunities to develop specific covalent compounds for the targeted modulation of protein kinases.

The authors demonstrate that intramolecular cysteine disulfide bonding between conserved cysteines can function as a repressing mechanism as indicated by the effect of DTT and the consequent increase in activity by BSK-1 and -2 (WT). The cause-effect relationship of why mutation of the CPE-Cys only increases catalytic activity in vitro and drives phosphorylation of the BRSK substrate Tau in cells is not clear to me. The explanation given by the authors based on molecular modeling and molecular dynamics simulations is that oxidation of the CPE-Cys (that will favor disulfide bonding) destabilizes a conserved salt bridge network critical for allosteric activation. However, no functional evidence of the impact of the salt-bridge network is provided. If you mutated the two main Cys-pairs (aE-CHRD and A-loop T+2-CPE) you lose the effect of DTT, as the disulfide pairs cannot be formed, hence no repression mechanisms take place, however when looking at individual residues I do not understand why mutating the CPE only results in the opposite effect unless it is independent of its connection with the T+2residue on the A-loop.

Strengths:<br /> This is an important and interesting study providing new knowledge in the protein kinase field with important therapeutic implications for the rationale design and development of next-generation inhibitors.

Weaknesses:<br /> There are several issues with the figures that this reviewer considers should be addressed.

Joint Public Review:

This article is a direct follow-up to the paper published last year in eLife by the same group. In the previous article, the authors discovered a zinc finger protein, Kipferl, capable of guiding the HP1 protein Rhino towards certain genomic regions enriched in GRGGN motifs and packaged in heterochromatin marked by H3K9me3. Unlike other HP1 proteins, Rhino recruitment activates the transcription of heterochromatic regions, which are then converted into piRNA source loci. The molecular mechanism by which Kipferl interacts specifically with Rhino (via its chromodomain) and not with other HP1 proteins remained enigmatic.

In this latest article, the authors go a step further by elucidating the molecular mechanisms important for the specific interaction of Rhino and not other HP1 proteins with Kipferl. A phylogenetic study carried out between the HP1 proteins of 5 Drosophila species led them to study the importance of an AA Glycine at position 31 located in the Rhino chromodomain, an AA different from the AA (aspartic acid) found at the same position in the other HP1 proteins. The authors then demonstrate, through a series of structure predictions, biochemical, and genetic experiments, that this specific AA in the Rhino-specific chromodomain explains the difference in the chromatin binding pattern between Rhino and the other Drosophila HP1 proteins. Importantly, the G31D conversion of the Rhino protein prevents interaction between Rhino and Kipferl, phenocopying a Kipfer mutant.

Strengths:

The authors' effective use of phylogenetic analyses and protein structure predictions to identify a substitution in the chromodomain that allows Rhino's specific interaction with Kipferl is very elegant. Both genetic and biochemical approaches are applied to rigorously probe the proposed explanation. They used a point mutation in the endogenous locus that replaces the Rhino-specific residue with the aspartic acid residue present in all other HP1 family members. This novel allele largely phenocopies the defects in hatch rate, chromatin organization, and piRNA production associated with kipferl mutants, and does not support Kipferl localization to clusters. The data are of high quality, the presentation is clear and concise, and the conclusions are generally well-supported.

Weaknesses:

The reviewers identified potential ways to further strengthen the manuscript.

1) The one significant omission is RNAseq on the rhino point mutant, which would allow direct comparison to cluster, transposon, and repeat expression in kipferl mutants.

2) The manuscript would benefit from adding more evolutionary comparisons. The following or similar analyses would help put the finding into a broader evolutionary perspective: i) Is Kipferl's surface interacting with Rhino also conserved in Kipferl orthologs? In other words, are the Rhino-interacting amino acids of Kipferl under any pressure to be conserved? ii) The remarkable conservation of Rhino's G31 is at odds with the arms race that is proposed to be happening between the fly's piRNA pathway proteins and transposons. Does this mean that Rhino's chromodomain is "untouchable" for such positive selection?

Reviewer #1 (Public Review):

My main concern is the use of the 700K SNP dataset. This set of SNPs suffers from a heavy ascertainment bias, which can be seen in the PCA in the supplementary material where all the aurochs cluster in the center within the variation of cattle. Given the coverage of some of the samples, multiple individuals would have less than 10K SNP covered. The majority of these are unlikely to be informative here given that they would just represent fixed positions between taurine and indicine or SNPs mostly variable in milk cattle breeds. The authors would get a much better resolution (i.e. many more SNPs to work with their very low genome coverage data) using the 1000 bull genome project VCF data set: https://www.ebi.ac.uk/ena/browser/view/PRJEB42783 which based on whole genome resequencing data from many cattle. This will certainly help with improving the resolution of qpAdm and f4 analysis, which have huge confidence intervals in most cases. Right now some individuals have huge confidence intervals ranging from 0 to 80% auroch ancestry...

I agree with the authors that qpAdm is likely to give quite a noisy estimate of ancestry here (likely explain part of the issue I mentioned above). Although qpAdm is good for model testing here for ancestry proportion the authors instead could use an explicit f4 ratio - this would allow them to specify a model which would make the result easier to interpret.

The interpretation of the different levels of allele sharing on X vs autosome being the result of sex-bias admixture is not very convincing. Could these differences simply be due to a low recombination rate on the X chromosome and/or lower effective population size, which would lead to less efficient purifying selection?

The authors suggest that 2 pop model rejection in some domestic population might be due to indicine ancestry, this seems relatively straightforward to test.

The first sentence of the paper is a bit long-winded, also dogs were domesticated before the emergence of farming societies.

It would be good to be specific about the number of genomes and coverage info in the last paragraph of the intro.

Reviewer #2 (Public Review):

Summary:<br /> In this paper, the authors investigated the admixture history of domestic cattle since they were introduced into Iberia, by studying genomic data from 24 ancient samples dated to ~2000-8000 years ago and comparing them to modern breeds. They aimed to (1) test for introgression from (local) wild aurochs into domestic cattle; (2) characterize the pattern of admixture (frequency, extent, sex bias, directionality) over time; (3) test for correlation between genetic ancestry and stable isotope levels (which are indicative of ecological niche); and (4) test for the hypothesized higher aurochs ancestry in a modern breed of fighting bulls.

Strengths:<br /> Overall, this study collects valuable new data that are useful for testing interesting hypotheses, such as admixture between domestic and wild populations, and correlation between genome-wide aurochs ancestry and aggressiveness.

Weaknesses:<br /> Most conclusions are partially supported by the data presented. The presence of admixed individuals in prehistorical periods supports the hypothesized introgression, although this conclusion needs to be strengthened with an analysis of potential contamination. The frequency, sex-bias, and directionality of admixture remain highly uncertain due to limitations of the data or issues with the analysis. There is considerable overlap in stable isotope values between domestic and wild groups, indicating a shared ecological niche, but variation in classification criteria for domestic vs wild groups and in skeletal elements sampled for measurements significantly weakens this claim. Lastly, the authors presented convincing evidence for relatively constant aurochs ancestry across all modern breeds, including the Lidia breed which has been bred for aggressiveness for centuries. My specific concerns are outlined below.

Contamination is a common concern for all ancient DNA studies. Contamination by modern samples is perhaps unlikely for this specific study of ancient cattle, but there is still the possibility of cross-sample contamination. The authors should estimate and report contamination estimates for each sample (based on coverage of autosomes and sex chromosomes, or heterozygosity of Y or MT DNA). Such contamination estimates are particularly important to support the presence of individuals with admixed ancestry, as a domestic sample contaminated with a wild sample (or vice versa) could appear as an admixed individual.

A major limitation of this study is uncertainty in the "population identity" for most sampled individuals (i.e., whether an individual belonged to the domesticated or wild herd when they were alive). Based on chronology, morphology, and genetic data, it is clear the Mesolithic samples from the Artusia and Mendandia sites are bona fide aurochs, but the identities of individuals from the other two sites are much less certain. Indeed, archeological and morphological evidence from El Portalon supports the presence of both domestic animals and wild aurochs, which is echoed by the inter-individual heterogeneity in genetic ancestry. Based on results shown in Fig 1C and Fig 2 it seems that individuals moo017, moo020, and possibly moo012a are likely wild aurochs that had been hunted and brought back to the site by humans. Although the presence of individuals (e.g., moo050, moo019) that can only be explained by two-source models strongly supports that interbreeding happened (if cross-contamination is ruled out), it is unclear whether these admixed individuals were raised in the domestic population or lived in the wild population and hunted.

Such uncertainty in "population identity" limits the authors' ability to make conclusions regarding the frequency, sex bias, and directionality of gene flow between domestic and wild populations. For instance, the wide range of ancestry estimates in Neolithic and Chalcolithic samples could be interpreted as evidence of (1) frequent recent gene flow or (2) mixed practices of herding and hunting and less frequent gene flow. Similarly, the statement about "bidirection introgression" (on pages 8 and 11) is not directly supported by data. As the genomic, morphological, and isotope data cannot confidently classify an individual as belonging to the domesticated or wild population, it seems impossible to conclude the direction of gene flow (if by "bidirection introgression" the authors mean something other than "bidirectional gene flow", they need to clearly explain this before reaching the conclusion.)

The f4 statistics shown in Fig 3B are insufficient to support the claim regarding sex-biased hybridization, as the f4 statistic values are not directly comparable between the X chromosome and autosomes. Because the effective population size is different for the X chromosome and autosomes (roughly 3:4 for populations with equal numbers of males and females), the expected amount of drift is different, hence the fraction of allele sharing (f4) is expected to be different. In fact, the observation that moo004 whose autosomal genome can be modeled as 100% domestic ancestry still shows a higher f4 value for the X chromosome than autosomes hints at this issue. A more robust metric to test for sex-biased admixture is the admixture proportion itself, which can be estimated by qpAdm or f4-ratio (see Patterson et al 2012). However, even with this method, criticism has been raised (e.g., Lazaridis and Reich 2017; Pfennig and Lachance, 2023). In general, detecting sex-bias admixture is a tough problem.

In general, the stable isotope analysis seems to be very underpowered, due to the issues of variation in classification criteria and skeletal sampling location discussed by the authors in supplementary material. The authors claimed a significant difference in stable nitrogen isotope between (inconsistently defined) domestic cattle and wild aurochs, but no figures or statistics are presented to support this claim. Please describe the statistical method used and the corresponding p-values. The authors can consider including a figure to better show the stable isotope results.

Reviewer #3 (Public Review):

Summary:<br /> Günther and colleagues leverage ancient DNA data to track the genomic history of one of the most important farm animals (cattle) in Iberia, a region showing peculiarities both in terms of cultural practices as well as a climatic refugium during the LGM, the latter of which could have allowed the survival of endemic lineages. They document interesting trends of hybridisation with wild aurochs over the last 8-9 millennia, including a stabilisation of auroch ancestry ~4000 years ago, at ~20%, a time coincidental with the arrival of domestic horses from the Pontic steppe. Modern breeds such as the iconic Lidia used in bullfighting or bull running retain a comparable level of auroch ancestry.

Strengths:<br /> The generation of ancient DNA data has been proven crucial to unravel the domestication history of traditional livestock, and this is challenging due to the environmental conditions of the Iberian peninsula, less favourable to DNA preservation. The authors leverage samples unearthed from key archaeological sites in Spain, including the karstic system of Atapuerca. Their results provide fresher insights into past management practices, and permit characterisation of significant shifts in hybridization with wild aurochs.

Weaknesses:<br /> - Treatment of post-mortem damage: the base quality of nucleotide transitions was recalibrated down to a quality score of 2, but for 5bp from the read termini only. In some specimens (e.g. moo022), the damage seems to extend further. Why not use dedicated tools (e.g. mapDamage), or check the robustness by conditioning on nucleotide transversions?

- Their more solid analyses are based on qpAdm, but rely on two single-sample donor populations. As the authors openly discuss, it is unclear whether CPC98 is a good proxy for Iberian aurochs despite possibly forming a monophyletic clade (the number of analysed sites is simply too low to assess this monophyly; Supplementary Table S2). Additionally, it is also unclear whether Sub1 was a fully unadmixed domestic specimen, depleted of auroch ancestry. The authors seem to suggest themselves that sex-biased introgression may have already taken place in Anatolia ("suggesting that sex-biased processes already took place prior to the arrival of cattle to Iberia").

Alternatively, I recommend using Struct-f4 as it can model the ancestry of all individuals together based on their f4 permutations, including outgroups and modern data, and without the need to define pure "right" and "left" populations such as CPC98 and Sub1. It should work with low-coverage data, and allows us to do f4-based MDS plots as well as to estimate ancestry proportions (including from ghost populations).

- In the admixture graph analyses (supplementary results), the authors use population groups based on a single sample. If these samples are pseudohaploidised (or if coverage is insufficient to estimate heterozygosity - and it is at least for moo004 and moo014), f3 values are biased, implying that the fitted graph may be wrong. The graph shown in Fig S7 is in fact hard to interpret. For example, the auroch Gyu2 from Anatolia but not the auroch CPC98 also from Anatolia received 62% of ancestry from North Africa? The Neolithic samples moo004 and moo014 also show the same shocking disparity. I would consider re-doing this analysis with more than a sample per population group.

Reviewer #1 (Public Review):

Summary:<br /> Doxorubincin has long been known to cause bone loss by increasing osteoclast and suppressing osteoblast activities. The study by Wang et al. reports a comprehensive investigation into the off-target effects of doxorubicin on bone tissues and potential mechanisms. They used a tumor-free model with wild-type mice and found that even a single dose of doxorubicin has a major influence by increasing leukopenia, DAMPs, and inflammasomes in macrophages and neutrophils, and inflammation-related cell death (pyroptosis and NETosis). The gene knockout study shows that AIM2 and NLRP3 are the major contributors to bone loss. Overall, the study confirmed previous findings regarding the impact of doxorubicin on tissue inflammation and expanded the research further into bone tissue. The presented data are consistent; however, a major question remains regarding whether doxorubicin drives inflammation and its related events. Most in vitro studies showed that the effect of doxorubincin cannot be demonstrated without LPS priming. This observation raises the question of whether doxorubincin itself could activate the inflammasome and the related events. In vivo study, on the other hand, suggested that it doesn't require LPS. The inconsistency here was not explained further. Moreover, a tumor-free mouse model was used for the study; however, immune responses in tumor-bearing models would likely be distinct from tumor-free ones. The justification for using tumor-free models is not well-established.

Strengths:<br /> The paper includes a comprehensive study that shows the effects of doxorubincin on cytokine levels in serum, the release of DAMPs and NETosis, and leukopenia using both in vivo and in vitro models. Bone marrow cells, macrophages, and neutrophils were isolated from the bone marrow, and the levels of cytokines in serum were also determined.

They employed multiple knockout models with a deficiency in Aim 2, Nlirp3, and double deficiencies to dissect the functional involvement of these two inflammasomes.

The experiments in general are well designed. The paper is also logically written, and the figures were clearly labeled.

Weaknesses:<br /> Most of the data presented are correlative, and there is not much effort to dissect the underlying molecular mechanism.

It is not entirely clear why a tumor-free model is chosen to study immune responses, as immune responses can differ significantly with or without tumor-bearing.

Immune responses in isolated macrophages, neutrophils, and bone marrow cells require priming with LPS, while such responses are not observed in vivo. There is no explanation for these differences.

The band intensities on Western blots in Fig. 4 and Fig. 5 are not quantified, and the numbers of repeats are also not provided.

Many abbreviations are used throughout the text, and some of the full names are not provided.

Fig. 5B needs a label on the X axis.

Reviewer #2 (Public Review):

Summary:<br /> Wang and collaborators have evaluated the impact of inflammation on bone loss induced by Doxorubicin, which is commonly used in chemotherapy to treat various cancers. In mice, they show that a single injection of Doxorubicin induces systemic inflammation, leukopenia, and significant bone loss associated with increased bone-resorbing osteoclast numbers. In vitro, the authors show that Doxorubicin activates the AIM2 and NLRP3 inflammasomes in macrophages and neutrophils. Importantly, they show that the full knockouts (germline deletions) of AIM2 (Aim2-/-) and NLRP3 (Nlrp3-/-) and Caspase 1 (Casp1-/-) limit (but do not completely abolish) bone loss induced 4 weeks after a single injection of Doxorubicin in mice. From these results, they conclude that Doxorubicin activates inflammasomes to cause inflammation-associated bone loss.

Strengths:<br /> While numerous studies have reported that Doxorubicin activates the inflammasome in myeloid cells and various other cell types, that Doxorubicin induces systemic inflammation, and that both the systemic inflammation and Doxorubicin treatment leads to bone loss, functional experiments demonstrating that NRLP3 and/or AIM2 loss-of-functions, and thus the systemic impairment of the inflammatory response, may prevent bone-loss induced by Doxorubicin were lacking. The strength of this manuscript is that it provides these missing data.

Weaknesses:<br /> However, one could argue that most of the conclusions drawn from the data presented here have been previously reported and that it was very much expected that reducing systemic inflammation in treated animals (in Aim2-/- and/or Nlrp3-/- mice) would preserve bone homeostasis to some extent, similarly to what has been reported in the context of cardiotoxicity induced by Doxorubicin.

Since the manuscript focuses on therapeutic considerations aiming to preserve bone homeostasis in animals treated with Doxorubicin, additional experiments evaluating and comparing various therapeutic options could improve the impact of the study. Drugs targeting the inflammasomes could be tested in addition to the genetic mouse models. Since increased osteoclast numbers (and likely bone resorption) are associated with Doxorubicin-induced bone loss, antiresorptive drugs such as Bisphosphonates or anti-RANKL antibodies could be tested and compared to anti-inflammatory drugs. Since autophagy and senescence have been shown to contribute to bone loss induced by Doxorubicin, it would be interesting to use the pharmacologic inhibitors (targeting autophagy or senescence) used in these previous studies to evaluate the relative impact of these different cellular mechanisms, on bone loss induced by Doxorubicin.

Moreover, the cellular and molecular mechanisms by which Doxorubicin induces bone loss in vivo could be further evaluated. Doxorubicin has been reported to directly affect bone-making osteoblasts and bone-resorbing osteoclasts. It would be important to determine the relative importance of the activation of the AIM2 and NLRP3 inflammasomes in these cells compared to macrophages and neutrophils. Floxed mouse lines exist for both Aim2 and Nlrp3, as well as relevant cell-specific Cre lines. Thus, cell-specific conditional knockouts could have been used in the current study, instead of using global knockout animals. Genetic tools also exist to induce the specific ablation of macrophages or neutrophils and could be used. Furthermore, it is unclear whether local inflammation is induced in the bone marrow of Doxorubicin-treated mice, and what is the relative impact of local versus systemic inflammation in bone loss in these mice. Markers of the inflammasomes, pyroptosis, and NETosis could be evaluated on bone sections, and on bone and bone marrow samples. The effect of Doxorubicin on osteoblast numbers in vivo and on bone resorption (not just osteoclast numbers) should be evaluated as well. These mechanistic aspects are important and needed to better understand the cytotoxic mechanisms triggered by Doxorubicin, and define the best therapeutic approaches to preserve bone integrity in chemotherapy.

Finally, it would be important to assess the bone mass of Doxorubicin-treated control, Aim2-/-, Nlrp3-/- and Cas1-/- mice at a later time point than 4 weeks post-injection. Nlrp3 knockout has been reported to increase the density of the cortical and trabecular bones. The bone mass of Aim2-/-, Nlrp3-/- and Cas1-/- mice at baseline may be higher than that of control mice, and it may take slightly longer for Doxorubicin to reduce bone mass to the same extent than in controls. It would be also interesting to do similar experiments using animals treated multiple times with Doxorubicin instead of using a single injection, since patients receive their chemotherapy multiple times.

Reviewer #1 (Public Review):

Summary and strengths:

This is an interesting, timely and informative article. The authors used publicly available data (made available by a funding agency) to examine some of the academic characteristics of the individuals recipients of the National Institutes of Health (NIH) k99/R00 award program during the entire history of this funding mechanism (17 years, total ~ 4 billion US dollars (annual investment of ~230 million USD)). The analysis focuses on the pedigree and the NIH funding portfolio of the institutions hosting the k99 awardees as postdoctoral researchers and the institutions hiring these individuals. The authors also analyze the data by gender, by whether the R00 portion of the awards eventually gets activated and based on whether the awardees stayed/were hired as faculty at their k99 (postdoctoral) host institution or moved elsewhere. The authors further sought to examine the rates of funding for those in systematically marginalized groups by analyzing the patterns of receiving k99 awards and hiring k99 awardees at historically black colleges and universities.

The goals and analysis are reasonable and the limitations of the data are described adequately. It is worth noting that some of the observed funding and hiring traits are in line with the Matthew effect in science (Merton, 1968: https://www.science.org/doi/10.1126/science.159.3810.56) and in science funding (Bol et al., 2018: https://www.pnas.org/doi/10.1073/pnas.1719557115). Overall, the article is a valuable addition to the research culture literature examining the academic funding and hiring traits in the United States. The findings can provide further insights for the leadership at funding and hiring institutions and science policy makers for individual and large-scale improvements that can benefit the scientific community.

Weaknesses:

The authors have addressed my recommendations in the previous review round in a satisfactory way.

Reviewer #2 (Public Review):

Summary and strengths:

Early career funding success has an immense impact on later funding success and faculty persistence, as evidenced by well-documented "rich-get-richer" or "Matthew effect" phenomena in science (e.g., Bol et al., 2018, PNAS). In this study the authors examined publicly available data on the distribution of the National Institutes of Health's K99/R00 awards - an early career postdoc-to-faculty transition funding mechanism - and showed that although 89% of K99 awardees successfully transitioned into faculty, disparities in subsequent R01 grant obtainment emerged along three characteristics: researcher mobility, gender, and institution. Men who moved to a top-25 NIH funded institution in their postdoc-to-faculty transition experienced the shortest median time to receiving a R01 award, 4.6 years, in contrast to the median 7.4 years for women working at less well-funded schools who remained at their postdoc institutions.

Amongst the three characteristics, the finding that researcher mobility has the largest effect on subsequent funding success is key and novel. Other data supplement this finding: for example, although the total number of R00 awards has increased, most of this increase is for awards to individuals moving to different institutions. In 2010, 60% of R00 awards were activated at different institutions compared to 80% in 2022. These findings enhance previous work on the relationship between mobility and ones' access to resources, collaborators, or research objects (e.g., Sugimoto and Larivière, 2023, Equity for Women in Science (Harvard University Press)).

These results empirically demonstrate that even after receiving a prestigious early career grant, researchers with less mobility belonging to disadvantaged groups at less-resourced institutions continue to experience barriers that delay them from receiving their next major grant. This result has important policy implications aimed at reducing funding disparities - mainly that interventions that focus solely on early career or early stage investigator funding alone will not achieve the desired outcome of improving faculty diversity.

The authors also highlight two incredible facts: No postdoc at a historically Black college or university (HBCU) has been awarded a K99 since the program's launch. And out of all 2,847 R00 awards given thus far, only two have been made to faculty at HBCUs. Given the track record of HBCUs for improving diversity in STEM contexts, this distribution of awards is a massive oversight that demands attention.

At no fault of the authors, the analysis is limited to only examining K99 awardees and not those who applied but did not receive the award. This limitation is solely due to the lack of data made publicly available by the NIH. If this data were available, this study would have been able to compare the trajectory of winners versus losers and therefore could potentially quantify the impact of the award itself on later funding success, much like the landmark paper by Bol et al. (PNAS; 2018) that followed the careers of an early career grant scheme in the Netherlands. Such an analysis would also provide new insights that would inform policy.

Although data on applications versus awards for the K99/R00 mechanism are limited, there exists data for applicant race and ethnicity for the 2007-2017 period, which were made available by a Freedom of Information Act request through the now defunct Rescuing Biomedical Research Initiative (https://web.archive.org/web/20180723171128/http://rescuingbiomedicalresearch.org/blog/examining-distribution-k99r00-awards-race/). These results are highly relevant given the discussion of K99 award impacts on the sociodemographic composition of U.S. biomedical faculty. During the 2007-2017 period, the K99 award rate for white applicants was 31% compared to 26.7% for Asian applicants and 16.2% for Black applicants. In terms of award totals, these funding rates amount to 1,384 awards to white applicants, 610 to Asian applicants, and 25 to Black applicants. However, the work required to include these data may be beyond the scope of the study.

The conclusions are well-supported by the data, and limitations of the data and the name-gender matching algorithm are described satisfactorily.

Reviewer #3 (Public Review):

Summary:

The researchers aim add to the literature on faculty career pathways with particular attention to how gender disparities persist in the career and funding opportunities of researchers. The researchers also examine aspects of institutional prestige that can further amplify funding and career disparities. While some factors about individuals' pathways to faculty lines are known, including the prospects of certain K award recipients, the current study provides the only known examination of the K99/R00 awardees and their pathways.

Strengths:

The authors establish a clear overview of the institutional locations of K99 and R00 awardees and the pathways for K99-to-R00 researchers and the gendered and institutional patterns of such pathways. For example, there's a clear institutional hierarchy of hiring for K99/R00 researchers that echo previous research on the rigid faculty hiring networks across fields, and a pivotal difference in the time between awards that can impact faculty careers. Moreover, there's regional clusters of hiring in certain parts of the US where multiple research universities are located. Moreover, documenting the pathways of HBCU faculty is an important extension of the study by Wapman et al. (2022: https://www.nature.com/articles/s41586-022-05222-x), and provides a more nuanced look at the pathways of faculty beyond the oft-discussed high status institutions. (However, there is a need for more refinement in this segment of the analyses). Also, the authors provide important caveats throughout the manuscript about the study's findings that show careful attention to the complexity of these patterns and attempting to limit misinterpretations of readers.

Weaknesses:

The authors have addressed my recommendations in the previous review round in a satisfactory way.

Reviewer #1 (Public Review):

This manuscript deftly combines cryo-EM and electrophysiology to investigate gating mechanisms of human CLC-2. Although another structure of CLC-2 was recently reported, this is the first structure to report density for the absolutely critical gating glutamate, and - an even more exciting result - the first structure to identify the N-terminal gating peptide that is the heart of this manuscript. There has been previous controversy over such a gating peptide in CLC-2, but the combined structural/functional approach appears to establish a role for this peptide in gating, and sets up future experiments to understand why its effects might change under different physiological scenarios. The experiments reported here are thoughtful and well-controlled and the data presentation is excellent. For the electrophysiology experiments, the use of inhibitor AK-42 (developed by the current senior author's lab) to establish a zero current level is a welcome advance and should become standard for electrophysiological studies of CLC-2.

Reviewer #2 (Public Review):

This paper makes important and novel advances that significantly enhance our understanding of the ClC-2 channel. The EM data are of high quality, and the most important argument, concerning the role of the N-terminus of the protein as an occluding inactivation gate, is very well supported by both structural, computational, and functional data (some of which is previously published). The proposal that the "run up" observed in patch clamp experiments represents relief of inactivation is interesting and compelling. The model predicts that mutations at the hairpin binding site should influence this "run up", which should be tested in the near future. Finally, the confirmation of the AK-42 binding site further solidifies evidence that this is a pore-blocking compound; the authors' argument about determinants of specificity is convincing.

Reviewer #3 (Public Review):

Summary<br /> CLC-2 channels play an important role in cellular homeostasis and electrical excitability, and dysfunctions are associated with aldosteronism and leukodystrophy. Structural insights into the functioning of CLC-2 are just emerging. CLC-2 channels are distinct among the members of the CLC family in that they are activated by hyperpolarization. Earlier studies have implicated channel regulation by a "ball-and-chain" type of channel block mechanism which underlies its strong rectification and use-dependent "run-up" properties. Structural insights into these mechanisms are currently lacking. In this manuscript, Xu et al present CryoEM structures of CLC-2 in the apo and inhibitor-bound conformations in the 2.5-2.7 A resolution range. Several novel structural features are presented that lend support to the "ball-and chain" model, identify an interesting role for the c-terminal domain in gating, and establish the interaction pocket for AK-42. Electrophysiology and simulations nicely support the structural work. Overall, an elegant study, with high-quality data, and a well-presented manuscript.

Strengths<br /> 1. The cryoEM data presented reveals that the channel is in a closed conformation at depolarizing potential (0 mv). Structures for the closed state of CLCs were not previously available. A strong density for Glu205, which constitutes the Egate, allows for an unambiguous assignment of its position at the Scen Cl-binding site, thereby establishing the basis for the block in the closed channel.<br /> 2. The apo state particles were sorted into two classes that differ in the conformation of the CTD. A previously unobserved rearrangement of the CBS region in the CTD is reported wherein the CTD is positioned closer to the TM region in one of the subunits, breaking the C2 symmetry. The data implicates a role for the conformational flexibility of CTD in gating.<br /> 3. The most interesting finding of this work, is perhaps, the presence of an additional density, corresponding to a hairpin-like structure, that is seen only at the subunit where the CTD is positioned away from the TMD. The authors propose that the additional density corresponds to a 13 aa stretch in the N-terminal region. The position of the hairpin at the intracellular mouth of the CL-permeation pathway is likely to impede ion conduction, by a mechanism analogous to the "ball-and-chain" proposed in other voltage-gated channels.<br /> 4. The structure of CLC-2 in complex with a selective inhibitor AK-42 is in a conformation very similar to that of the apo state, with a clear additional density for the AK-42 molecule. Binding site interaction provides insights into AK-42 selectivity for CLC-2 vs CLC-1.

Reviewer #1 (Public Review):

In the best genetically and biochemically understood model of eukaryotic DNA replication, the budding yeast, Saccharomyces cerevisiae, the genomic locations at which DNA replication initiates are determined by a specific sequence motif. These motifs, or ARS elements, are bound by the origin recognition complex (ORC). ORC is required for loading of the initially inactive MCM helicase during origin licensing in G1. In human cells, ORC does not have a specific sequence binding domain and origin specification is not specified by a defined motif. There have thus been great efforts over many years to try to understand the determinants of DNA replication initiation in human cells using a variety of approaches, which have gradually become more refined over time.

In this manuscript Tian et al. combine data from multiple previous studies using a range of techniques for identifying sites of replication initiation to identify conserved features of replication origins and to examine the relationship between origins and sites of ORC binding in the human genome. The authors identify a) conserved features of replication origins e.g. association with GC-rich sequences, open chromatin, promoters and CTCF binding sites. These associations have already been described in multiple earlier studies. They also examine the relationship of their determined origins and ORC binding sites and conclude that there is no relationship between sites of ORC binding and DNA replication initiation. While the conclusions concerning genomic features of origins are not novel, if true, a clear lack of colocalization of ORC and origins would be a striking finding. However, the majority of the datasets used do not report replication origins, but rather broad zones in which replication origins fire. Rather than refining the localisation of origins, the approach of combining diverse methods that monitor different objects related to DNA replication leads to a base dataset that is highly flawed and cannot support the conclusions that are drawn, as explained in more detail below.

Methods to determine sites at which DNA replication is initiated can be divided into two groups based on the genomic resolution at which they operate. Techniques such as bubble-seq, ok-seq can localise zones of replication initiation in the range ~50kb. Such zones may contain many replication origins. Conversely, techniques such as SNS-seq and ini-seq can localise replication origins down to less than 1kb. Indeed, the application of these different approaches has led to a degree of controversy in the field about whether human replication does indeed initiate at discrete sites (origins), or whether it initiates randomly in large zones with no recurrent sites being used. However, more recent work has shown that elements of both models are correct i.e. there are recurrent and efficient sites of replication initiation in the human genome, but these tend to be clustered and correspond to the demonstrated initiation zones (Guilbaud et al., 2022).

These different scales and methodologies are important when considering the approach of Tian et al. The premise that combining all available data from five techniques will increase accuracy and confidence in identifying the most important origins is flawed for two principal reasons. First, as noted above, of the different techniques combined in this manuscript, only SNS-seq can actually identify origins rather than initiation zones. It is the former that matters when comparing sites of ORC binding with replication origin sites, if a conclusion is to be drawn that the two do not co-localise.

Second, the authors give equal weight to all datasets. Certainly, in the case of SNS-seq, this is not appropriate. The technique has evolved over the years and some earlier versions have significantly different technical designs that may impact the reliability and/or resolution of the results e.g. in Foulk et al. (Foulk et al., 2015), lambda exonuclease was added to single stranded DNA from a total genomic preparation rather than purified nascent strands), which may lead to significantly different digestion patterns (ie underdigestion). Curiously, the authors do not make the best use of the largest SNS-seq dataset (Akerman et al., 2020) by ignoring these authors separation of core and stochastic origins. By blending all data together any separation of signal and noise is lost. Further, I am surprised that the authors have chosen not to use data and analysis from a recent study that provides subsets of the most highly used and efficient origins in the human genome, at high resolution (Guilbaud et al., 2022).

References

Akerman I, Kasaai B, Bazarova A, Sang PB, Peiffer I, Artufel M, Derelle R, Smith G, Rodriguez-Martinez M, Romano M, Kinet S, Tino P, Theillet C, Taylor N, Ballester B, Méchali M (2020) A predictable conserved DNA base composition signature defines human core DNA replication origins. Nat Commun, 11: 4826

Foulk MS, Urban JM, Casella C, Gerbi SA (2015) Characterizing and controlling intrinsic biases of lambda exonuclease in nascent strand sequencing reveals phasing between nucleosomes and G-quadruplex motifs around a subset of human replication origins. Genome Res, 25: 725-735

Guilbaud G, Murat P, Wilkes HS, Lerner LK, Sale JE, Krude T (2022) Determination of human DNA replication origin position and efficiency reveals principles of initiation zone organisation. Nucleic Acids Res, 50: 7436-7450

Update in response to authors' comments on the original review:

While the authors have clarified their approach to some aspects of their analysis, I believe they and I are just going to have to disagree about the methodology and conclusions of this work. I do not find the authors responses sufficiently compelling to change my mind about the significance of the study or veracity of the conclusions. In my opinion, the method for identification of strong origins is not robust and of insufficient resolution. In addition, the resolution and the overlap of the MCM Chip-seq datasets is poor. While the conclusion of the paper would indeed be striking and surprising if true, I am not at all persuaded that it is based on the presented data.

Reviewer #2 (Public Review):

Tian et al. performed a meta-analysis of 113 genome-wide origin profile datasets in humans to assess the reproducibility of experimental techniques and shared genomics features of origins. Techniques to map DNA replication sites have quickly evolved over the last decade, yet little is known about how these methods fare against each other (pros and cons), nor how consistent their maps are. The authors show that high-confidence origins recapitulate several known features of origins (e.g., correspondence with open chromatin, overlap with transcriptional promoters, CTCF binding sites). However, surprisingly, they find little overlap between ORC/MCM binding sites and origin locations.

Overall, this meta-analysis provides the field with a good assessment of the current state of experimental techniques and their reproducibility, but I am worried about: (a) whether we've learned any new biology from this analysis; (b) how binding sites and origin locations can be so mismatched, in light of numerous studies that suggest otherwise; and (c) some methodological details described below.

-- I understand better the inclusion/exclusion logic for the samples. But I'm still not sure about the fragments. As the authors wrote, there is both noise and stochasticity; the former is not important but the latter is essential to include. How can these two be differentiated, and what may be the expected overlap as a function of different stochasticity rates?

-- Many of the major genomic features analyzed have already been found to be associated with origin sites. For example, the correspondence with TSS has been reported before:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6320713/<br /> https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6547456/

-- Line 250: The most surprising finding is that there is little overlap between ORC/MCM binding sites and origin locations. The authors speculate that the overlap between ORC1 and ORC2 could be low because they come from different cell types. Equally concerning is the lack of overlap with MCM. If true, these are potentially major discoveries that butts heads with numerous other studies that have suggested otherwise.

The key missing dataset is ORC1 and ORC2 CHiP-seq from the same cell type. This shouldn't be too expensive to perform, and I hope someone performs this test soon. Without this, I remain on the fence about how much existing datasets are "junk" vs how much the prevailing hypothesis about replication needs to be revisited. Nonetheless, the authors do perform a nice analysis showing that existing techniques should be carefully used and interpreted.

Reviewer #3 (Public Review):

Summary: The authors present a thought-provoking and comprehensive re-analysis of previously published human cell genomics data that seeks to understand the relationship between the sites where the Origin Recognition Complex (ORC) binds chromatin, where the replicative helicase (Mcm2-7) is loaded, and where DNA replication actually begins (origins). The view that these should coincide is influenced by studies in yeast where ORC binds site-specifically to dedicated nucleosome-free origins where Mcm2-7 can be loaded and remains stably positioned for subsequent replication initiation. However, this is most certainly not the case in metazoans where it has already been reported that chromatin bindings sites of ORC and Mcm2-7 do not necessarily overlap, nor do they always overlap with origins. This is likely due to Mcm2-7 possessing linear mobility on DNA (i.e., it can slide) such that other chromatin-contextualized processes can displace it from the site in which it was originally loaded. Additionally, Mcm2-7 is loaded in excess and thus only a fraction of Mcm2-7 would be predicted to coincide with replication start sites. This study reaches a very similar conclusion of these previous studies: they find a high degree of discordance between ORC, Mcm2-7, and origin positions in human cells.

Strengths: The strength of this work is its comprehensive and unbiased analysis of all relevant genomics datasets. To my knowledge, this is the first attempt to integrate these observations. It also is an important cautionary tale to not confuse replication factor binding sites with the genomic loci where replication actually begins, although this point is already widely appreciated in the field.

Weaknesses: The major weakness of this paper is the lack of novel biological insight and that the comprehensive approach taken failed to provide any additional mechanistic insight regarding how and why ORC, Mcm2-7, and origin sites are selected or why they may not coincide.

Reviewer #1 (Public Review):

The mutation rate and spectrum have been found to differ between populations as well as across individuals within the same population. Hypothesizing that some of the observed variation has a genetic basis, the authors of this paper have made important contributions in the past few years in identifying genetic variants that modify mutation rate or spectrum in natural populations. This paper makes one significant step further by developing a new method for mapping genetic variants associated with the mutation spectrum, which reveals new biological insights.

Using traditional quantitative trait locus (QTL) mapping in the BXD mouse recombinant inbred lines (RILs), the authors of this paper previously identified a genetic locus associated with C>A mutation rate. However, this approach has limited power, as it suffers from multiple testing burden as well as noise in the "observed mutation spectrum phenotype" due to rarity and randomness of mutation events. To overcome these limitations, the authors developed a new method that they named "aggregate mutation spectrum distance" (AMSD), which in short measures the difference in the aggregate mutation spectrum between two groups of individuals with distinct genotypes at a specific genomic locus. With this new approach, they recover the previously reported candidate mutator locus (near Mutyh gene) and identify a new candidate locus that modifies the C>A mutation rate on only the mutator allele genetic background at the Mutyh locus. Using more rigorous statistical testing, the authors show convincingly synergistic epistatic effects between the mutator alleles at the two loci.

Overall, the analyses presented are well done and provide convincing evidence for the major findings, including the new candidate mutator locus and its epistatic interaction with the Mutyh locus. The new AMSD method introduced is innovative and outperforms traditional QTL mapping under most conditions, as demonstrated by extensive simulations. I identify no major issues with this paper and think it is very well written.

One of the major advantages of the AMSD method over QTL mapping is alleviation of the multiple testing burden, as one comparison tests for any changes in the mutation spectrum, including simultaneous, small changes in the relative abundance of multiple mutation types. The flip side of this advantage of AMSD is that, when a significant association is detected, it is not immediately clear which mutation type is driving the signal. To narrow the signal to specific candidate mutation type(s), additional analyses are needed, such as testing for differential proportions of each mutation type between individuals with or without the candidate mutator allele. However, such analysis may be less powerful when the mutator allele leads to small changes in the relative abundance of multiple mutation types. This will be an area of improvement for future studies.

Reviewer #2 (Public Review):

In this paper Sasani, Quinlan and Harris present a new method for identifying genetic factors affecting germline mutation, which is particularly applicable to genome sequence data from mutation accumulation experiments using recombinant inbred lines. These are experiments where laboratory organisms are crossed and repeatedly inbred for many generations, to build up a substantial number of identifiable germline mutations. The authors apply their method to such data from mice, and identify two genetic factors at two separate genetic loci. Clear evidence of such factors has been difficult to obtain, so this is an important finding. They further show evidence of an epistatic interaction between these factors (meaning that they do not act independently in their effects on the germline mutation process). This is exciting because such interactions are difficult to detect and few if any other examples have been studied.

The authors present a careful comparison of their method to another similar approach, quantitative trait locus (QTL) analysis, and demonstrate that in situations such as the one analysed it has greater power to detect genetic factors with a certain magnitude of effect. They also test the statistical properties of their method using simulated data and permutation tests. Overall the analysis is rigorous and well motivated, and the methods explained clearly.

The main limitation of the approach is that it is difficult to see how it might be applied beyond the context of mutation accumulation experiments using recombinant inbred lines. This is because the signal it detects, and hence its power, is based on the number of extra accumulated mutations linked to (i.e. on the same chromosome as) the mutator allele. In germline mutation studies of wild populations the number of generations involved (and hence the total number of mutations) is typically small, or else the mutator allele becomes unlinked from the mutations it has caused (due to recombination), or is lost from the population altogther (due to chance or perhaps selection against its deleterious consequences).

Nevertheless, accumulation lines are a common and well established experimental approach to studying mutation processes in many organisms, so the new method could have wide application and impact on our understanding of this fundamental biological process.

The evidence presented for an epistatic interaction is convincing, and the authors suggest some plausible potential mechanisms for how this interaction might arise, involving the DNA repair machinery and based on previous studies of the proteins implicated. However as with all such findings, given the higher degree of complexity of the proposed model it needs to be treated with greater caution, perhaps until replicated in a separate dataset or demonstrated in follow-up experiments exploring the pathway itself.

Reviewer #3 (Public Review):

Sasani et al. develop and implement a new method for mutator allele discovery in the BXD mouse population. This new method, termed "aggregate mutation spectrum distance" or AMSD, carries several notable strengths, including the ability to aggregate de novo mutations across individuals to reduce data sparsity and to combine mutation rate frequencies across multiple nucleotide contexts into a single estimate. As demonstrated by simulations, this method is better suited to mutator discovery under certain scenarios, as compared to conventional QTL or association mapping. Overall, the theoretical premise of the AMSD method is judged to be both strong and innovative, and the methodology could be extended to other species and populations to enable discovery of additional mutator alleles.

The authors then apply their method to the BXD mouse recombinant inbred mapping population. As proof-of-principle, they first successfully re-identify a known mutator locus in this population on chr4. Next, to assess possible genetic interactions involving this known mutator, Sasani et al. condition on the chr4 mutator genotype and reimplement the AMSD scan. This strategy led them to identify a second locus on chr6 that interacts epistatically with the chr4 locus; mice with "D" alleles at both loci exhibit a significantly increased burden of C>A de novo mutations, even though mice with the D allele at the chr6 locus alone show no appreciable increase in the C>A mutation fraction. This exciting discovery not only adds to the catalog of known mutator alleles, but also reveals key aspects of mutator biology and reinforces the hypothesis that segregating variants in genes associated with DNA repair influence germline mutation spectra.

Despite a high level of overall enthusiasm for this work, there are some limitations to the AMSD method. However, it is my judgement that the authors present a balanced summary of the strengths and weaknesses of their method in the revised manuscript. I also think that the authors' conclusions may actually somewhat undersell the scientific impact of their findings. As the authors note, few mutation rate modifiers have been identified in mammals. This is potentially because large- and moderate-effect modifiers are rapidly selected against due to their deleterious effects, but could also be due to pervasive epistasis wherein modifiers are only expressed on certain "permissive" genetic backgrounds, such as the chr6 locus the authors discover in this paper. The potential background dependence of mutator expression could partially shelter it from the action of selection, allowing the allele persist in populations. This discovery has significant implications for our understanding of mutation rate evolution, but only earns a cursory mention in the paper.

Reviewer #1 (Public Review):

This is an interesting study by Pinos and colleagues that examines the effect of beta carotene on atherosclerosis regression. The authors have previously shown that beta carotene reduces atherosclerosis progress and hepatic lipid metabolism, and now they seek to extend these findings by feeding mice a diet with excess beta carotene in a model of atherosclerosis regression (LDLR antisense oligo plus Western diet followed by LDLR sense oligo and chow diet). They show some metrics of lesion regression are increased upon beta carotene feeding (collagen content) while others remain equal to normal chow diet (macrophage content and lesion size). These effects are lost when beta carotene oxidase (BCO) is deleted. The study adds to the existing literature that beta carotene protects from atherosclerosis in general, and adds new information regarding regulatory T-cells. However, the study does not present significant evidence about how beta-carotene is affecting T-cells in atherosclerosis. For the most part, the conclusions are supported by the data presented, and the work is completed in multiple models, supporting its robustness. However there are a few areas that require additional information or evidence to support their conclusions and/or to align with the previously published work.

Specific additional areas of focus for the authors:<br /> The premise of the story is that b-carotene is converted into retinoic acid, which acts as a ligand of the ROR transcription factor in T-regs. The authors measure hepatic markers of retinoic acid signaling (retinyl esters, Cyp26a1 expression) but none of these are measured in the lesion, which calls into question the conclusion that Tregs in the lesion are responsible for the regression observed with b-carotene supplementation.

There does not appear to be a strong effect of Tregs on the b-carotene induced pro-regression phenotype presented in Figure 5. The only major CD25+ cell dependent b-carotene effect is on collagen content, which matches with the findings in Figure 1 +2. This mechanistically might be very interesting and novel, yet the authors do not investigate this further or add any additional detail regarding this observation. This would greatly strengthen the study and the novelty of the findings overall as it relates to b-carotene and atherosclerosis.

The title indicates that beta-carotene induces Treg 'expansion' in the lesion, but this is not measured in the study.

Revised manuscript:<br /> In the revised manuscript, the authors provide quantification of an RA-responsive gene in the plaque as evidence that RA signalling is indeed elevated upon b-carotene supplementation. It is not reduced upon blocking CD25 (Tregs) which implies that other cells in addition to Tregs are impacted by b-carotene supplementation that favourably remodels the plaque. The authors properly account for this by tempering their conclusions and recognize that Tregs are only partially responsible for the plaque phenotype upon b-carotene supplementation.

The authors chose not to further investigate why b-carotene impacted collagen production, instead including a discussion point. In this reviewer's opinion, it is a missed opportunity but hopefully something that can be investigated further by others.

Reviewer #2 (Public Review):

Pinos et al present five atherosclerosis studies in mice to investigate the impact of dietary supplementation with b-carotene on plaque remodeling during resolution. The authors use either LDLR-ko mice or WT mice injected with ASO-LDLR to establish diet-induced hyperlipidemia and promote atherogenesis during 16 weeks, and then they promote resolution by switching the mice for 3 weeks to a regular chow, either deficient or supplemented with b-carotene. Supplementation was successful, as measured by hepatic accumulation of retinyl esters. As expected, chow diet led to reduced hyperlipidemia, and plaque remodeling (both reduced CD68+ macs and increased collagen contents) without actual changes in plaque size. But, b-carotene supplementation resulted in further increased collagen contents and, importantly, a large increase in plaque regulatory T-cells (TREG). This accumulation of TREG is specific to the plaque, as it was not observed in blood or spleen. The authors propose that the anti-inflammatory properties of these TREG explain the atheroprotective effect of b-carotene, and found that treatment with anti-CD25 antibodies (to induce systemic depletion of TREG) prevents b-carotene-stimulated increase in plaque collagen and TREG.

An obvious strength is the use of two different mouse models of atherogenesis, as well as genetic and interventional approaches. The analyses of aortic root plaque size and contents are rigorous and included both male and female mice (although the data was not segregated by sex). Unfortunately, the authors did not provide data on lesions in en face preparations of the whole aorta.

Overall, the conclusion that dietary supplementation with b-carotene may be atheroprotective via induction of TREG is reasonably supported by the evidence presented. Other conclusions put forth by the authors (e.g., that vitamin A production favors TREG production or that BCO1 deficiency reduces plasma cholesterol), however, will need further experimental evidence to be substantiated.

The authors claim that b-carotene reduces blood cholesterol, but data shown herein show no differences in plasma lipids between mice fed b-carotene-deficient and -supplemented diets (Figs. 1B, 2A, and S3A). Also, the authors present no experimental data to support the idea that BCO1 activity favors plaque TREG expansion (e.g., no TREG data in Fig 3 using Bco1-ko mice).

As the authors show, the treatment with anti-CD25 resulted in only partial suppression of TREG levels. Because CD25 is also expressed in some subpopulation of effector T-cells, this could potentially cloud the interpretation of the results. Data in Fig 4H showing loss of b-carotene-stimulated increase in numbers of FoxP3+GFP+ cells in the plaque should be taken cautiously, as they come from a small number of mice. Perhaps an orthogonal approach using FoxP3-DTR mice could have produced a more robust loss of TREG and further confirmation that the loss of plaque remodeling is indeed due to loss of TREG.

Reviewer #1 (Public Review):

Summary:

The authors demonstrate that the immunosuppressive environment in pancreatic ductal adenocarcinoma (PDAC) can be mitigated by a combination of ionizing radiation (IR), CCR5 inhibition, and PD1 blockade. This combination therapy increases tissue-resident natural killer (trNK) cells that facilitate CD8 T cell activity, resulting in a reduction of E-cadherin positive tumor cells. They identify a specific "hypofunctional" NK cell population in both mouse and human PDAC that supports CD8 T cell involvement. A trNK signature is found to be associated with better survival outcomes in PDAC and other solid tumors.

Strengths:

Overall, I think this is an interesting study that combines testing of therapeutic concepts in mice with bioinformatics analysis of single-cell transcriptome data in primary tumors and exploration of clinical outcomes using signature genes in TCGA data. The key finding is that immunoregulatory properties of tumor-infiltrating/resident CD56-bright NK cells (assumed to be non-cytotoxic) are beneficial for outcome through cross-talk with DC and recruitment of CD8 T cells. The latter is specifically induced by irradiation combined with CCR5i and PD1 blockade.

"These results collectively support the notion that IR/CCR5i/αPD1 combination treatment alters immune infiltration by reducing Tregs and increasing NK and CD8 T cells, thereby resulting in greater local tumor control." I agree with this conclusion.

Weaknesses:

There are a few points to discuss and that the authors may want to address.

1) "Notably, CCR5i significantly reduced Treg infiltration but had no effect on the infiltration of other immune cells, indicating the active recruitment of CCR5+ Tregs in PDAC (Figure 2B)."<br /> CCR5i treatment seems to inhibit infiltration of CD8 T cells and NK cells to a greater extent, in relative terms, compared to Treg, albeit it is not statistically significant. If this visual inspection of the graph does not reflect reality, additional experiments may be needed to verify the selective targeting of Tregs or confirm the fact that also CD8 T cells and NK cells are affected by single agent CCR5i. The reduced recruitment of Treg, NK cells, and CD8T cells was completely reversed when combined with irradiation. In the data shown in Figure 3E it seems as if CCR5i induced infiltration of Tregs along with other immune cells. However, this said, I agree with the conclusion of the authors that this combined treatment leads to an altered immune composition and ratio between Tregs and effector cells (CD8T cells and NK cells). Could this altered composition be displayed more clearly?

2) The definition of active and hypofunctional NK cells based on solely NKG2D expression alone seems like an oversimplification. I realize it is not trivial to test tumor-infiltrating NK cells from these tumors functionally but perhaps scRNAseq of the tumors would allow for characterization of cytotoxicity scores using KEGG or GO analysis or reversed gene set enrichment in responders/non-responders. It seems as if the abstract refers to this phenotype incorrectly since the "hyporesponsive" subset is described as NKG2C-negative.

3) "The NK_C1 cluster correlates best with the hypofunction NK phenotype observed in mice as similarly displayed reduced activation (reduced NKG7, NKp80, GZMA, and PRF1) with additional expression of tissue residency markers CD103, CD49a and, surprisingly, the adaptive activating receptor NKG2C (KLRC2) (Figure 5B, C)."

There is no doubt that NK_C1 represents tumor-infiltrating NK cells with a CD56bright gene signature with a strong tissue resident score. However, the transcriptional expression of KLRC2 on these is not surprising! It is well established that KLRC2 transcripts (but not protein) are highly expressed on conventional CD56bright NK cells. There are several published sources where the authors can find such data for confirmation. Thus, this is not to be confused with adaptive NK cells having an entirely different transcriptional signature and expressing high levels of NKG2C at the cell surface. I strongly recommend re-interpreting the results based on the fact that KLRC2 is expressed at high levels in conventional CD56bright NK cells. If not, it would be important to verify that these tissue-resident NK cells express NKG2C and not NKG2A at the cell surface.

4) NCAM1 transcript alone is not sufficient to deconvolute CD56bright NK cells in TCGA data (Figure 7A). As a single marker, it likely reflects NK cell infiltration without providing further evidence on the contribution of the bright/dim components. Therefore, the use of the bright Tr NK signature described in Table 1 is very important (Figure 7B). Table 1 is not provided. Nor Supplementary Table 1. There is only one supplementary figure in the ppt attached.

Reviewer #2 (Public Review):

Summary:

This work elaborates on a combined therapeutic approach comprising ionizing radiation and CCR5i/αPD1 immunotherapy as a promising strategy in pancreatic cancer. Previous research has established that NK cell-derived CCL5 and XCL1 play a crucial role in recruiting cDC1 cells to the tumor microenvironment, contributing to tumor control. In this study, by using a murine pancreatic cancer model, the authors propose that the addition of radiation therapy to CCR5i and αPD1 immunotherapy could upregulate CD8+ T cells and a subgroup of NK cells within the tumor and result in better tumor control. They further analyzed human single-cell sequencing data from pancreatic cancer patients and identified one subgroup of NK cells (NK C1) with tissue-resident features. Subsequent cell-cell contact analysis reveals the NK-cDC1-CD8 cell axis in pancreatic cancer. By analyzing TCGA data, they found that high NK C1 signature levels were associated with better survival in pancreatic cancer patients. Thus, radiotherapy could benefit the outcome of patients bearing low NK C1 signatures. Importantly, the positive correlation between NK C1 score with survival extends beyond pancreatic cancer, showing potential applicability across various solid cancers.

Strengths:

This study could add new insight into the clinical practice by introducing such novel combined therapy and shed light on the underlying immune cell dynamics. These findings hold potential for more effective and targeted treatment in the future. Mouse experiments nicely confirmed that such combined therapy could significantly reduce tumor volume. The elegant use of single-cell sequencing analysis and human database examination enriches the narrative and strengthens the study's foundation. Additionally, the notion that NK C1 signature correlates with patient survival in various solid cancers is of high interest and relevance.

Weaknesses:

1. The role of CCR5i requires further clarification. While the authors demonstrated its capacity to reduce Treg in murine tumors, its impact on other cell populations, including NK cells and CD8+ T cells, was not observed. Nevertheless, the effect of CCR5i on tumor growth in Figure 2B should be shown. If the combination of radiotherapy and αPD1 already can achieve good outcomes as shown in Figure 3A, the necessity to include CCR5i is questioned. Overall, a more comprehensive elucidation of the roles of CCL5 and CCR5i in this context would be good.

2. In line with this, spatial plots in Figure 4 did not include the group with only radiotherapy and αPD1. This inclusion would facilitate a clearer comparison and better highlight the essential role of CCR5i.

3. NK C1 cells should be also analyzed in the mouse model. The authors suggest that NKNKG2D-ve could be the cell population. Staining of inhibitory markers should be considered, for example, TIGIT and TIM3 as presented in Figure 5B.

4. While the cell-cell contact analysis generated from single-cell sequencing data is insightful, extending this analysis to the mouse model under therapy would be highly informative. NK and CD8 cells in the tumor increased upon the combined therapy. However, cDC1 was not characterized. Analysis regarding cDC1 would provide more information on the NK/cDC1/CD8 axis.

5. Human database analysis showed a positive correlation between NK C1 score and CCL5 in pancreatic cancer. Furthermore, radiotherapy could benefit the outcome of patients bearing low NK C1 scores. It would be interesting to test if radiotherapy could also benefit patients with low CCL5 levels in this cohort.

Reviewer #3 (Public Review):

Summary:

In the submitted manuscript by Go et al, the authors evaluated the tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) and made a number of interesting observations, including the following: 1) CCL5 expression within the tumor microenvironment negatively correlated with clinical outcomes in human patients with PDAC; 2) there were both positive and negative correlations between CCL5 expression and the expression of specific genes (e.g. those encoding CD56 and CD16, respectively) included among gene signature lists for Treg, MDSC, TAM, and NK cells; 3) CCR5 inhibition with the inhibitor, maraviroc, reduced Treg infiltration but not that of other immune cell types in an orthotopic murine model of PDAC; 4) CCR5 inhibition augmented anti-PD1 immunotherapy when combined with ionizing radiation (IR) therapy in the murine model; 5) the above therapy resulted in increased infiltration of CD8+ cytotoxic T cells as well as of a subset of NKG2D-negative, tissue-residency (tr) marker expressing NK cells (deemed Cluster 1 NK in their data sets) that inversely correlated with the number of E-cadherin+ cells (i.e. tumor cells) and showed predicted interactions with cDC1 dendritic cells (including XCL1/XCL2 expressed by the NK and XCR1 expressed by the cDC1); 6) the authors identified a number of putative signals stemming from the trNK (e.g. IL-16, TNFSF14, FASLG, CSF, MIF) as well as incoming from cDC1s to NK (e.g. BAG6-NKp30); 7) these trNK cells positively correlated with good outcomes and with CD8+ T cell infiltrations in human PDAC as well as in many other solid tumor types; and 8) importantly, the benefit of IR therapy was specific to the subset of PDAC patients (represented in the TCGA dataset) that were predicted to have low amounts of trNK cells. The authors used murine experimental models, multiplexed imaging analyses, and a number of publicly available sequencing data sets from human tumor samples to perform their investigations. Based on their findings, the authors proposed that combining IR with CCR5 inhibition and anti-PD1 immunotherapy is a promising strategy to treat solid cancers.

Strengths:

Overall, the collective analyses and conclusions appear to be novel and could be of high and rapid impact on the field, particularly in terms of directing clinical trials to incorporate IR with CCR5 inhibition and immunotherapy. The manuscript is well written; the figures are for the most part clear; and the Discussion is very thoughtful.

Weaknesses:

There were a number of minor typographical errors, missing references, or minor issues with the figures. In general, while many of the observations provided strong suggestive evidence of relationships, phenotypes, and functions, the authors often used language to indicate that such things were confirmed, validated, or proven. In fact, there was a paucity of such functional/confirmatory experiments. This does not necessarily detract from the overall significance, excitement for, and potential impact of the study; but the language could likely be adjusted to be more in keeping with the true nature of the findings. The main title and running title are a bit different; consider making them more similar.

Reviewer #3 (Public Review):

This work by Fleck et al. and colleagues documented the auxin feeding-induced effects in adult flies, since auxin could be used in temporally control gene expression using a modified Gal4/Gal80 system. Overall, the experiments were well designed and carefully executed. The results were quantified with appropriate statistical analyses. The paper was also well written and the results were presented logically. Their findings demonstrate that auxin-fed flies have significantly lower triglyceride levels than the control flies using Ultra High-pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS)-based metabolomics assays. Further transcriptome analyses using the whole flies show changes of genes involved in fatty acid metabolism. However, female oogenesis and fecundity do not seem to be affected, at least using the current assays. These results indicate that auxin may not be used in experiments involving lipid-related metabolism, but could be appropriate to be applied for other biological processes. Researchers need to be careful when applying this strategy in their own experimental design and should perform proper controls.

Reviewer #1 (Public Review):

In recent years, Auxin treatment is frequently used for inducing targeted protein degradation in Drosophila and various other organisms. This approach provides the way to acutely alter the levels of specific proteins. In this manuscript, the authors carefully examine the impact of Auxin treatment and provide strong evidence that Auxin treatment elicits alterations in feeding activity, survival rates, lipid metabolism, and gene expression patterns. Researchers need to be aware of these effects to design experiment/controls and interpret their data.

Strengths:<br /> Regarding widespread usage of Auxin mediated gene manipulation method, it is important to address whether the application of Auxin itself causes any physiological changes. Authors provide evidence of several Auxin effects on lipid metabolism, feeding behavior and gene expression changes. Experiments are suitably designed with appropriate sample size, data analysis methods.

Weaknesses:<br /> Data shown here are limited for certain method of treatment. No time course, dose dependency information is provided, and cell-type-specific responses are unknown. Therefore, this work basically provides the cautionary note for the field for researchers who use this method suggesting the importance that they should thoroughly check the gene expression pattern for their specific tissue of interest under their normal standard or altered food conditions.

Reviewer #2 (Public Review):

In this study, Fleck and colleagues investigate the effects of auxin exposure on Drosophila melanogaster adults, focusing their analysis on feeding behavior, fatty acid metabolism, and oogenesis. The motivation for the study is that auxin-inducible transcription systems are now being used by Drosophila researchers to drive transcription using the Gal4-UAS system as a complement to Gal80ts versions of the system. I found the study to be carefully done. This study will be of interest for researchers using the Drosophila system, especially those focusing on fatty acid metabolism or physiology. The authors have adequately addressed all the minor points I raised in my review of the first submission.

Reviewer #3 (Public Review):

Summary of Work<br /> This paper conducts the largest GWAS study of A. thaliana in response to a viral infection. The paper identifies a 1.5 MB region in the chromosome associated with disease, including SNPs, structural variation, and transposon insertions. Studies further validate the association experimentally with a separate experimental infection procedure with several lines and specific T-DNA mutants. Finally, the paper presents a geographic analysis of the minor disease allele and the major association. The major take-home message of the paper is that structural variants and not only SNPs are important changes associated with disease susceptibility. The manuscript also makes a strong case for negative frequency-dependent selection maintaining a disease susceptibility locus at low frequency.

Strengths and Weaknesses<br /> A major strength of this manuscript is the large sample sizes, careful experimental design, and rigor in the follow-up experiments. For instance, mentioning non-infected controls and using methods to determine if geographic locus associations were due to chance. The strong result of a GWAS-detected locus is impressive given the complex interaction between plant genotypes and strains noted in the results. In addition to the follow-up experiments, the geographic analysis added important context and broadened the scope of the study beyond typical lab-based GWAS studies. I find very few weaknesses in this manuscript.

Support of Conclusions<br /> The support for the conclusions is exceptional. This is due to the massive amount of evidence for each statement and also due to the careful consideration of alternative explanations for the data.

Significance of Work<br /> This manuscript will be of great significance in plant disease research, both for its findings and its experimental approach. The study has very important implications for genetic associations with disease beyond plants.

Reviewer #1 (Public Review):

In this manuscript, Butkovic et al. perform a genome-wide association (GWA) study on Arabidopsis thaliana inoculated with the natural pathogen turnip mosaic virus (TuMV) in laboratory conditions, with the aim to identify genetic associations with virus infection-related parameters. For this purpose, they use a large panel of A. thaliana inbred lines and two strains of TuMV, one naïve and one pre-adapted through experimental evolution. A strong association is found between a region in chromosome 2 (1.5 Mb) and the risk of systemic necrosis upon viral infection, although the causative gene remains to be pinpointed.

This project is a remarkable tour de force, but the conclusions that can be reached from the results obtained are unfortunately underwhelming. Some aspects of the work could be clarified, and presentation modified, to help the reader.

Reviewer #2 (Public Review):

The manuscript presents a valuable investigation of genetic associations related to plant resistance against the turnip mosaic virus (TuMV) using Arabidopsis thaliana as a model. The study infects over 1,000 A. thaliana inbred lines with both ancestral and evolved TuMV and assesses four disease-related traits: infectivity, disease progress, symptom severity, and necrosis. The findings reveal that plants infected with the evolved TuMV strain generally exhibited more severe disease symptoms than those infected with the ancestral strain. However, there was considerable variation among plant lines, highlighting the complexity of plant-virus interactions.

A major genetic locus on chromosome 2 was identified, strongly associated with symptom severity and necrosis. This region contained several candidate genes involved in plant defense against viruses. The study also identified additional genetic loci associated with necrosis, some common to both viral isolates and others specific to individual isolates. Structural variations, including transposable element insertions, were observed in the genomic region linked to disease traits.

Surprisingly, the minor allele associated with increased disease symptoms was geographically widespread among the studied plant lines, contrary to typical expectations of natural selection limiting the spread of deleterious alleles. Overall, this research provides valuable insights into the genetic basis of plant responses to TuMV, highlighting the complexity of these interactions and suggesting potential avenues for improving crop resilience against viral infections.

Overall, the manuscript is well-written, and the data are generally high-quality. The study is generally well-executed and contributes to our understanding of plant-virus interactions.

Reviewer #2 (Public Review):

Summary:

The study demonstrates that deletion of a small cytoplasmic membrane protein, Tmem263, caused severe impairment of longitudinal bone growth and that the impaired bone growth was caused by suppression of expression and/or protein levels of growth hormone receptor in the liver.

Strengths:

The experimental design of the study is sound and the results are in general of supportive of the conclusions.

Weaknesses:

The study lacks mechanistic investigation into how the deletion of a gene corresponding to a small cytoplasmic membrane protein would lead to substantial reduction in the gene expression of growth hormone receptor, which takes place in the nuclei. Accordingly, the manuscript is of largely descriptive nature.

Reviewer #3 (Public Review):

Prior studies in humans and in chickens suggested that TMEM263 could play an important role in longitudinal bone growth, but a definitive assessment of the function and potential mechanism of action of this species-conserved plasma membrane protein has been lacking. Here, the authors create a TMEM263 null mouse model and convincingly show dramatic cessation of post-natal growth, which becomes apparent by day PND21. They report proportional dwarfism, highly significant bone and related phenotypes, as well as notable alterations of hepatic GH signaling to IGF1. A large body of prior work has established an essential role for GH and it's stimulation of IGF1 production in liver and other tissues in post-natal growth. On this basis, the authors conclude that the observed decrease in serum IGF1 seen in TMEM263-KO mice is causal for the growth phenotype, which seems likely. Moreover, they ascribe the low serum IGF1 to the observed decreases in hepatic GH receptor (GHR) expression and GHR/JAK2/STAT5 signaling to IGF1, which is plausible but not proven by the experiments presented.

The finding that TMEM263 is essential for normal hepatic GHR/IGF1 signaling is an important, and unexpected finding, one that is likely to stimulate further research into the underlying mechanisms of TMEM263 action, including the distinct possibility that these effects involve direct protein-protein interactions between GHR and TMEM263 on the plasma membrane of hepatocytes, and perhaps on other mouse cell types and tissues as well, where TMEM263 expression is up to 100-fold higher (Fig. 1C).

An intriguing finding of this study, which is under emphasized and should be noted in the Abstract, is the apparent feminization of liver gene expression in male TMEM263-KO mice, where many male-biased genes are downregulated, and many female-biased genes are upregulated. Further investigation of these liver gene responses by comparison to public datasets could be very useful, as it could help determine: (1) whether the TMEM263 liver phenotype is similar to that of hypophysectomized male mouse liver, where GH and GHR/STAT5/IGF1 signaling are both totally ablated; or alternatively, (2) whether the phenotype is more similar to that of a male mouse given GH as a continuous infusion, which induces widespread feminization of gene expression in the liver, and is perhaps similar to the gene responses seen in the TMEM263-KO mice. Answering this question could provide critical insight into the mechanistic basis for the hepatic effects of TMEM263 gene KO.

Comments on revised version:

The authors have addressed a majority of the concerns raised during the initial review. The evidence supporting the whole-body growth and skeletal phenotypes, as well as the disruption of GH/IGF1 signaling seen in TMEM263-KO mice, is convincing. However, there is insufficient evidence to definitively conclude that the observed alteration of hepatic GH/IGF1 signaling is causative of the body growth and skeletal phenotypes.

Reviewer #1 (Public Review):

Summary<br /> Developing vaccination capable of inducing persistent antibody responses capable of broadly neutralizing HIV strains is of high importance. However, our ability to design vaccines to achieve this is limited by our relative lack of understanding of the role of T-follicular helper (Tfh) subtypes in the responses. In this report Verma et al investigate the effects of different prime and boost vaccination strategies to induce skewed Tfh responses and its relationship to antibody levels. They initially find that live-attenuated measles vaccine, known to be effective at inducing prolonged antibody responses has a significant minority of germinal center Tfh (GC-Tfh) with a Th1 phenotype (GC-Tfh1) and then explore whether a prime and boost vaccination strategy designed to induce GC-Tfh1 is effective in the context of anti-HIV vaccination. They demonstrate that a vaccine formulation referred to as MPLA induces higher GC-Tfh1 and link this to increased antibody production.

Strengths:<br /> While there is a lot of literature on Tfh subtypes in blood, how this related to the germinal centers is not always clear. The strength of this paper is that they use a relevant model to allow some longitudinal insight into the detailed events of the germinal center Tfh (GC-Tfh) compartment across time and how this related to antibody production.

Weaknesses:<br /> The authors focus strongly on the proportion of GC-Tfh1 of GC-Tfh. There seems to be an assumption that since the MPLA vaccine has a higher number of GC-Tfh1 that this explains the higher levels of antibodies. This is not an entirely unreasonable assumption but the mechanistic link between the two is never tested.

Reviewer #2 (Public Review):

Summary:<br /> Anil Verma et al. have performed prime-boost HIV vaccination to enhance HIV-1 Env antibodies in the rhesus macaques model. The authors used two different adjuvants, a cationic liposome-based adjuvant (CAF01) and a monophosphoryl lipid A (MPLA)+QS-21 adjuvant. They demonstrated that these two adjuvants promote different transcriptomes in the GC-TFH subsets. The MPLA+QS-21 adjuvant induces abundant GC TFH1 cells expressing CXCR3 at first priming, while the CAF01 adjuvant predominantly induced GC TFH1/17 cells co-expressing CXCR3 and CCR6. Both adjuvants initiate comparable Env antibody responses. However, MPLA+QS-21 shows more significant IgG1 antibodies binding to gp140 even after 30 weeks.<br /> The enhancement of memory responses by MPLA+QS-21 consistently associates with the emergence of GC TFH1 cells that preferentially produce IFN-γ.

Strengths:<br /> The strength of this manuscript is that all experiments have been done in the rhesus macaques model with great care. This manuscript beautifully indicated that MPLA+QS-21 would be a promising adjuvant to induce the memory B cell response in the HIV vaccine.

Weaknesses:<br /> The authors did not provide clear evidence to indicate the functional relevance of GC TFH1 in IgG1 class-switch and B cell memory responses.

Reviewer #1 (Public Review):

The authors isolated a novel marine Planctomycetes bacterium with unique characteristics using a budding mode of division from the deep-sea cold seep sediment and named it Poriferisphaera heterotrophicis ZRK32. This work demonstrated that strain ZRK32 preferred nutrient-rich medium, moreover, the addition of nitrate or ammonia promoted the growth of strain ZRK32 and further caused the release of bacteriophage without killing the host. These results are interesting, well presented and documented in the revised manuscript.

Reviewer #2 (Public Review):

Summary:<br /> Planctomycetes encompass a group of bacteria with unique biological traits, the compartmentalized cells make them appear to be organisms in between prokaryotes and eukaryotes. However, only few of the Planctomycetes bacteria are cultured thus far, and hampers insight into the biological traits of this evolutionary important organisms.

This work reports the methodology details of how to isolate the deep-sea bacteria that could be recalcitrant to laboratory cultivation, and further reveals the distinct characteristics of the new species of a deep-sea Planctomycetes bacterium, such as the chronic phage release without breaking the host and promote the host and related bacteria in nitrogen utilization. Therefore, the finding of this work is of importance in extending our knowledge on bacteria.

Strengths:

Through combination of microscopic, physiological, genomics and molecular biological approaches, this reports isolation and comprehensively investigation of the first anaerobic representative of the deep-sea Planctomycetes bacterium, in particular in that of the budding division, and release phage without lysis the cells. Most of results and conclusions are supported by the experimental evidences.

Reviewer #1 (Public Review):

In this article, Vardakalis et al. propose a novel model of hippocampal oscillations whereby an external input (emulating the medial septum) can drive theta rhythms. This model displays phase-amplitude coupling of gamma oscillations, as well as theta resetting, which are known features of physiological theta that have been missing in previous models. The end goal proposed by the authors is to have a framework to explore the mechanisms of neurostimulation, which have shown promising applications in pathological conditions, but for which the underlying dynamics remain largely unknown. To reach this objective, the authors implement an existing biophysical model of the hippocampus that is able to generate gamma oscillations, and receives inputs from a set of Kuramoto oscillators to emulate theta drive originating from the medial septum.

Overall, the hypotheses and results are clearly presented and supported by high quality figures. The study is presented in a didactic way, making it easy for a broad audience to understand the significance of the results. The study does present some weaknesses that could easily be addressed by the authors. First, there are some anatomical inaccuracies: line 129 and fig1C, the authors omit medial septum projections to area CA1 (in addition to the entorhinal cortex). Moreover, in addition to CA1, CA3 also provides monosynaptic feedback projections to the medial septum CA3. Finally, an indirect projection from CA1/3 excitatory neurons to the lateral septum, which in turn sends inhibitory projections to the medial septum could be included or mentioned by the authors. This could be of particular relevance to support claims related to effects of neurostimulations, whereby minutious implementation of anatomical data could be key. If not updating their model, the authors could add this point to their limitation section, where they already do a good job of mentioning some limitations of using the EC as a sole oscillatory input to CA1. The authors test conditions of low theta inputs, which they liken to pathological states (line 112). It is not clear what pathology the authors are referring to, especially since a large amount of 'oscillopathies' in the septohippocampal system are associated with decreased gamma/PAC, but not theta oscillations (e.g. Alzheimer's disease conditions). While relevant for the clinical field, there is overall a missed opportunity to explain many experimental accounts with this novel model. Although to this day, clinical use of DBS is mostly restricted to electrical (and thus cell-type agnostic) stimulation, recent studies focusing on mechanisms of neurostimulations have manipulated specific subtypes in the medial septum and observed effects on hippocampal oscillations (e.g. see Muller & Remy, 2017 for review). Focusing stimulations in CA1 is of course relevant for clinical studies but testing mechanistic hypotheses by focusing stimulation on specific cell types could be highly informative. For instance, could the author reproduce recent optogenetic studies (e.g. Bender et al. 2015 for stimulation of fornix fibers; Etter et al., 2019 & Zutshi et al. 2018 for stimulation of septal inhibitory neurons)? Cell specific manipulations should at least be discussed by the authors.

Beyond these weaknesses, this study has a strong utility for researchers wanting to explore hypotheses in the field of neurostimulations. In particular, I see value in such models for exploring more intricate, phase specific effects of continuous, as well as close loop stimulations which are on the rise in systems neuroscience.

Reviewer #2 (Public Review):

Theta-nested gamma oscillations (TNGO) play an important role in hippocampal memory and cognitive processes and are disrupted in pathology. Deep brain stimulation has been shown to affect memory encoding. To investigate the effect of pulsed CA1 neurostimulation on hippocampal TNGO the authors coupled a physiologically realistic model of the hippocampus comprising EC, DG, CA1, and CA3 subfields with an abstract theta oscillator model of the medial septum (MS). Pathology was modeled as weakened theta input from the MS to EC simulating MS neurodegeneration known to occur in Alzheimer's disease. The authors show that if the input from the MS to EC is strong (the healthy state) the model autonomously generates TNGO in all hippocampal subfields while a single neurostimulation pulse has the effect of resetting the TNGO phase. When the MS input strength is weaker the network is quiescent but the authors find that a single CA1 neurostimulation pulse can switch it into the persistent TNGO state, provided the neurostimulation pulse is applied at the peak of the EC theta. If the MS theta oscillator model is supplemented by an additional phase-reset mechanism a single CA1 neurostimulation pulse applied at the trough of EC theta also produces the same effect. If the MS input to EC is weaker still, only a short burst of TNGO is generated by a single neurostimulation pulse. The authors investigate the physiological origin of this burst and find it results from an interplay of CAN and M currents in the CA1 excitatory cells. In this case, the authors find that TNGO can only be rescued by a theta frequency train of CA1 pulses applied at the peak of the EC theta or again at either the peak or trough if the MS oscillator model is supplemented by the phase-reset mechanism.

The main strength of this model is its use of a fairly physiologically detailed model of the hippocampus. The cells are single-compartment models but do include multiple ion channels and are spatially arranged in accordance with the hippocampal structure. This allows the understanding of how ion channels (possibly modifiable by pharmacological agents) interact with system-level oscillations and neurostimulation. The model also includes all the main hippocampal subfields. The other strength is its attention to an important topic, which may be relevant for dementia treatment or prevention, which few modeling studies have addressed.

The work has several weaknesses. First, while investigations of hippocampal neurostimulation are important there are few experimental studies from which one could judge the validity of the model findings. All its findings are therefore predictions. It would be much more convincing to first show the model is able to reproduce some measured empirical neurostimulation effect before proceeding to make predictions. Second, the model is very specific. Or if its behavior is to be considered general it has not been explained why. For example, the model shows bistability between quiescence and TNGO, however what aspect of the model underlies this, be it some particular network structure or particular ion channel, for example, is not addressed. Similarly for the various phase reset behaviors that are found. We may wonder whether a different hippocampal model of TNGO, of which there are many published (for example [1-6]) would show the same effect under neurostimulation. This seems very unlikely and indeed the quiescent state itself shown by this model seems quite artificial. Some indication that particular ion channels, CAN and M are relevant is briefly provided and the work would be much improved by examining this aspect in more detail. In summary, the work would benefit from an intuitive analysis of the basic model ingredients underlying its neurostimulation response properties. Third, while the model is fairly realistic, considerable important factors are not included and in fact, there are much more detailed hippocampal models out there (for example [5,6]). In particular, it includes only excitatory cells and a single type of inhibitory cell. This is particularly important since there are many models and experimental studies where specific cell types, for example, OLM and VIP cells, are strongly implicated in TNGO. Other missing ingredients one may think might have a strong impact on model response to neurostimulation (in particular stimulation trains) include the well-known short-term plasticity between different hippocampal cell types and active dendritic properties. Fourth the MS model seems somewhat unsupported. It is modeled as a set of coupled oscillators that synchronize. However, there is also a phase reset mechanism included. This mechanism is important because it underlies several of the phase reset behaviors shown by the full model. However, it is not derived from experimental phase response curves of septal neurons of which there is no direct measurement. The work would benefit from the use of a more biologically validated MS model.

[1] Hyafil A, Giraud AL, Fontolan L, Gutkin B. Neural cross-frequency coupling: connecting architectures, mechanisms, and functions. Trends in neurosciences. 2015 Nov 1;38(11):725-40.

[2] Tort AB, Rotstein HG, Dugladze T, Gloveli T, Kopell NJ. On the formation of gamma-coherent cell assemblies by oriens lacunosum-moleculare interneurons in the hippocampus. Proceedings of the National Academy of Sciences. 2007 Aug 14;104(33):13490-5.

[3] Neymotin SA, Lazarewicz MT, Sherif M, Contreras D, Finkel LH, Lytton WW. Ketamine disrupts theta modulation of gamma in a computer model of hippocampus. Journal of Neuroscience. 2011 Aug 10;31(32):11733-43.

[4] Ponzi A, Dura-Bernal S, Migliore M. Theta-gamma phase-amplitude coupling in a hippocampal CA1 microcircuit. PLOS Computational Biology. 2023 Mar 23;19(3):e1010942.

[5] Bezaire MJ, Raikov I, Burk K, Vyas D, Soltesz I. Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit. Elife. 2016 Dec 23;5:e18566.

[6] Chatzikalymniou AP, Gumus M, Skinner FK. Linking minimal and detailed models of CA1 microcircuits reveals how theta rhythms emerge and their frequencies controlled. Hippocampus. 2021 Sep;31(9):982-1002.

Joint Public Review:

In this work, Xie et al. developed SCA-seq, which is a multiOME mapping method that can obtain chromatin accessibility, methylation, and 3D genome information at the same time. SCA-seq first uses M.CviPI DNA methyltransferase to treat chromatin, then perform proximity ligation followed by long-read sequencing. This method is highly relevant to a few previously reported long read sequencing technologies. Specifically, NanoNome, SMAC-seq, and Fiber-seq have been reported to use m6A or GpC methyltransferase accessibility to map open chromatin, or open chromatin together with CpG methylation; Pore-C and MC-3C have been reported to use long read sequencing to map multiplex chromatin interactions, or together with CpG methylation. Therefore, as a combination of NanoNome/SMAC-seq/Fiber-seq and Pore-C/MC-3C, SCA-seq is one step forward. The authors tested SCA-seq in 293T cells and performed benchmark analyses testing the performance of SCA-seq in generating each data module (open chromatin and 3D genome). The QC metrics appear to be good and I am convinced that this is a valuable addition to the toolsets of multi-OMIC long-read sequencing mapping.

Reviewer #1 (Public Review):

This research article by Watabe T and colleagues characterizes PKA waves triggered by prostaglandin E2 (PGE2). What the author discovered is that waves of PKA occur both in vitro, in MDCK epithelial monolayers, and in vivo, in the ear epidermis in mice. The PKA waves are the consequence PGE2 discharge, that in turn is triggered by Calcium bursts. Calcium level and ERK activity intensity control that mechanism by acting at different levels.<br /> This article is a technological tour de force using different biosensors and optogenetic actuators. However, what makes this article interesting is the ability of combining these tools together to dissect a complex signaling pathway at the single-cell level and with highly dynamic processes. For this reason, this paper represents the essence of modern cell biology and paves the way for the cell biology of the future.

However, we think that the paper in this stage is still partly descriptive in its nature, and more measurements are needed to increase the strength of the mechanistic insights. Here below the points that we believe that need some improvement.

1)Even though the phenomenon of PGE2 signal propagation is elegantly demonstrated and well described, the whole paper is mostly of descriptive nature - the PGE2 signal is propagated via intercellular communication and requires Ca transients as well as MAPK activity, however function of these RSPAs in dense epithelium is not taken into consideration.<br /> What is the function of these RSPAs in cellular crowding? - Does it promote cell survival or initiate apoptosis? Does it feed into epithelial reorganization during cellular crowding? Still something else? The authors discuss possible roles of this phenomenon in cell competition context, but show no experimental or statistical efforts to answer this question. I believe some additional analysis or simple experiment would help to shed some light on the functional aspect of RSPAs and increase the importance of all the elegant demonstrations and precise experimental setups that the manuscript is rich of. Monolayer experiments using some perturbations that challenge the steady state of epithelial homeostasis - drug treatments/ serum deprivation/ osmotic stress/ combined with live cell imaging and statistical methods that take into account local cell density might provide important answers to these questions. The authors could consider following some of these ideas to improve the overall value of the manuscript.

2) In the line 82-84 the authors claim: "We found that the pattern of cAMP concentration change is very similar to the activity change of PKA, indicating that a Gs protein-coupled receptor (GsPCR) mediates RSPA". In our opinion, this conclusion is not well-supported by the results. The authors should at least show that some measurement of the two patterns show correlation. Are the patterns of cAMP of the same size as the pattern of PKA? Do they have the same size depending on cell density? Do they occur at the same frequency as the PKA patterns, depending on the cell density? Do they have an all or nothing activation as PKA or their activation is shading with the distance from the source?

3) In general, the absolute radius of the waves is not a good measurement for single-cell biology studies, especially when comparing different densities or in vivo vs in vitro experiments. We suggest the authors to add the measurement of the number of the cells involved in the waves (or the radius expressed in number of cells).

4) In 6D, the authors should also show the single-cell trajectories to understand better the correlation between PKA and ERK peaks. Is the huger variability in ERK activity ratio dues to different peak time or different ERK activity levels in different cells? The authors should show both the variability in the time and intensity.

5) In lines 130-132, the authors write, "This observation indicates that the amount of PGE2 secretion is predetermined and that there is a threshold of the cytoplasmic calcium concentration for the triggered PGE2 secretion". How could the author exclude that the amount of PGE2 is not regulated in its intensity as well? For sure, there is a threshold effect regarding calcium, but this doesn't mean that PGE2 secretion can be further regulated, e.g. by further increasing calcium concentration or by other mechanisms.

6) The manuscript shows that not all calcium transients are followed by RSPAs. Does the local cell density/crowding increase the probability of overlap between calcium transients and RSPAs?

The revision of the Watabe T paper provides additional data and analyses in response to the reviewers' comments. On our side, we are satisfied by these improvements.<br /> In the answer to our first question, the authors claim that they did multiple experiments to understand the function of RSPA in MDCK cell, all providing negative results. The authors could consider publishing the negative results as well, as they can be useful for the community.

In sum, we are convinced of the value of this article, and we thank the authors for the work that has been done.

Reviewer #2 (Public Review):

This study visualizes a specific localized form of cell-to-cell communication and conveys very well with what dynamics and sensitivity this biological phenomenon occurs.<br /> Using a FRET-based PKA biosensor, the authors observed that radial localized kinase activity changes spontaneously occur in adjacent cells of certain cell density. This phenomenon of radial propagation of PKA activity changes in groups of cells was further mechanistically elucidated and characterized. Interestingly, the authors found that individual cells in the cell groups form spontaneous Ca2+ transients, which at a certain strength can trigger the biosynthesis and release of prostaglandin E2 (PGE2). PGE2 then acts on the neighboring cells and triggers the increase of cAMP levels and the associated activation of the PKA via G-protein-coupled receptors (EP2 and EP4). In systematic, well-structured experiments, it was then found that the frequency of occurrence of such radial activations depends not only on the cell density but also on the activation state of the ERK MAP kinase pathway.

Strength<br /> In this study, the authors skillfully used various modern genetically encoded biosensors and other tools such as optogenetic tools to visualize and characterize an interesting biological phenomenon of cell-to-cell communication. The insights gained with these investigations produce a better understanding of the dynamics, sensitivity, and spatial extent with which such communications can occur in a cell network. It is also worth noting that the authors have not limited the studies to 2D cell culture in vitro, but were also able to confirm the findings in an animal model.

Weakness<br /> The work is hardly conclusive as to the actual biological significance of the phenomenon. It would be interesting to know more under which physiological and pathological conditions PGE2 triggers such radical PKA activity changes. It is not well explained in which tissues and organs and under what conditions this type of cell-to-cell communication could be particularly important.<br /> The authors also do not explain further why in certain cells of the cell clusters Ca2+ signals occur spontaneously and thus trigger the phenomenon. What triggers these Ca2+ changes? And why could this be linked to certain cell functions and functional changes?<br /> What explains the radius and the time span of the radial signal continuation? To what extent are these factors also related to the degradation of PGE2? The work could be stronger if such questions and their answers would be experimentally integrated and discussed.

Reviewer #1 (Public Review):

Summary:<br /> Here, Boor et al focus on the regulation of daf-7 transcription in the ASJ chemosensory neurons, which has previously shown to be sensitive to a variety of external and internal signals. Interestingly, they find that soluble (but not volatile) signals released by food activate daf-7 expression in ASJ, but that this is counteracted by signals from the ASIC channels del-3 and del-7, previously shown to detect the ingestion of food in the pharynx. Importantly, the authors find that ASJ-derived daf-7 can promote exploration, suggesting a feedback loop that influences locomotor states to promote feeding behavior. They also implicate signals known to regulate exploratory behavior (the neuropeptide receptor PDFR-1 and the neuromodulator serotonin) in the regulation of daf-7 expression in ASJ. Additionally, they identify a novel role for a pathway previously implicated in C. elegans sensory behavior, HEN-1/SCD-2, in the regulation of daf-7 in ASJ, suggesting that the SCD-2 homolog ALK may have a conserved role in feeding and metabolism.

Strengths:<br /> The studies reported here, particularly the quantitation of gene expression and the careful behavioral analysis, are rigorously done and interpreted appropriately. The results suggest that, with respect to food, DAF-7 expression encodes a state of "unmet need" - the availability of nearby food to animals that are not currently eating. This is an interesting finding that reinforces and extends our understanding of the neurobiological significance of this important signaling pathway. The identification of a role for ASJ-derived daf-7 in motor behavior is a valuable advance, as is the finding that SCD-2 acts in the AIA interneurons to influence daf-7 expression in ASJ.

Weaknesses:<br /> A limitation of the work is that some mechanistic relationships between the identified signaling pathways remains unclear, but this provides interesting opportunities for future work. There are some minor concerns about the statistical analysis in the paper, but these are unlikely to affect the authors' interpretation of their results.

Reviewer #2 (Public Review):

In this work, Boor and colleagues explored the role of microbial food cues in the regulation of neuroendocrine controlled foraging behavior. Consistent with previous reports, the authors find that C. elegans foraging behavior is regulated by the neuroendocrine TGFβ ligand encoded by daf-7. In addition to its known role in the neuroendocrine/sensory ASI neurons, Boor and colleagues show that daf-7 expression is dynamically regulated in the ASJ sensory neurons by microbial food cues - and that this regulation is important for exploration/exploitation balance during foraging. They identify at least two independent pathways by which microbial cues regulate daf-7 expression in ASJ: a gustatory pathway that promotes daf-7 expression and an opposing interoceptive pathway, also chemosensory in nature but which requires microbial ingestion to inhibit daf-7 expression via ASIC channels, encoded by del-3/del-7. In contrast, the authors show that the conserved PDF neuropeptide signaling pathway likely functions via the gustatory pathway to promote daf-7 expression. They further identify a novel role for the C. elegans ALK orthologue encoded by scd-2, which acts in interneurons to regulate daf-7 expression and foraging behavior. These results together imply that distinct cues from microbial food are used to regulate the balance between exploration and exploitation via conserved signaling pathways.

Strengths:<br /> The findings that gustatory and interoceptive inputs into foraging behavior are separable and opposing are novel and interesting, which they have shown most clearly in Figure 1 and Figure 3. These data clarify how these parallel chemosensory pathways can be integrated at the level of daf-7 expression.

It is also clear from their results that removal of the interoceptive cue (via transfer to non-digestible food) results in rapid induction of daf-7::gfp in ASJ - suggesting that this pathway is likely chemosensory and not simply nutritive in nature. They have also shown that daf-7 in ASJ plays an important role in the regulation of foraging behavior.

The role of the hen-1/scd-2 pathway in mediating the effects of ingested food is also compelling and well-interpreted, with a few small caveats, described below. This implies that important elements of this food sensing pathway may be conserved in mammals.

Weaknesses:<br /> Although not a weakness of this work per se, the roles of the 5-HT and hen-1/scd-2 pathway remain a bit unclear, likely reflecting their complex genetic contributions to foraging and daf-7 expression. Future work should clarify how these signals are integrated and whether the integration of these pathways improve exploration/exploitation balance to regulate animal fitness.

Reviewer #3 (Public Review):

Summary:<br /> In this interesting study, the authors characterize the mechanisms whereby a C. elegans TGF-beta DAF-7 responds to various forms of food cues to regulate foraging.<br /> Building on their previous findings that characterized the functional role of daf-7 in the ASJ sensory neurons in response to a bacterial pathogen and in regulating searching behaviors, the authors of this manuscript show that ingestion of E. coli OP50, a common laboratory food for the worms, suppresses ASJ expression of daf-7 and secreted water-soluble cues of OP50 increase it. They further show that the level of daf-7 expression in ASJ is positively associated with a higher level of roaming/exploration. The authors identify that the function of a C. elegans ortholog of Anaplastic Lymphoma Kinase in the interneurons AIA regulates ASJ expression of daf-7 in response to food information and the related searching behavior.

Strengths:<br /> The study addresses an important question that appeals to a wide readership. The findings are demonstrated by strong results produced from well designed experiments.

Reviewer #1 (Public Review):

The authors' aim was to test to what extent atypical organization of language is associated with a mirrored brain organization of other cognitive functions. In particular, they focused on the inferior frontal gyri (IFG) by studying the inhibitory control network. This allowed them to directly test support for the Causal hypothesis of hemispheric specialization, arguing for fast sequences of cognitive processes being better performed by a single hemisphere, versus the Statistical hypothesis of lateralization, postulating an independent lateralization of each cognitive function.

Previous studies on this topic did not focus on functions involving homotopic language regions. This limitation is bypassed in this study by assessing inhibition with a Stop-Signal Task which also engages the IFG in the contralateral site to the verb generation task. By studying a combination of structural and functional information, in addition to the activation contrasts, the authors are able to test whether atypical organization is accompanied by stronger interhemispheric connectivity. Although relying mainly on correlations and lacking important methodological information that may be critical to understand the reported effects, the results are quite straightforward. However the bilingual/monolingual status and gender of the participants is not reported which might affect the relationship between language and inhibitory control.

The conclusions of the paper are supported by the data. With their design, the authors observed that, as a group, individuals with atypical organization show a mirror organization of the whole inhibitory network to the contralateral site, supporting the Causal hypothesis at the group level. However, individual data support the Statistical hypothesis, since the segregation between language and inhibition was not observed in all individuals and a variety of configurations in bilateral and bilateral organisation of language and inhibition were also observed.

The results of this study have important implications for our understanding of the independence of different cognitive functions, which is crucial when addressing brain damage and rehabilitation. This aspect also indirectly speaks to researchers interested in evolution and in bilingualism and its relation to cognitive control. These aspects are not discussed but incorporating them would broaden the interest of the paper beyond the current implications mentioned.

Reviewer #2 (Public Review):

Language skills are traditionally associated with a network of brain regions in the left hemisphere. In this intriguing study, Esteban Villar-Rodríguez and collaborators examined whether atypical hemispheric lateralization for language determines the functional and structural organisation of the network for inhibitory control as well as its relationship with schizotypy and autistic spectrum traits. The results suggest that individuals who have atypical lateralisation of the language function have also an atypical (mirrored) lateralisation of the inhibitory control network, compared to the typical group (individuals with left-lateralised language function). Furthermore, the atypical organization of language production is associated with a greater white matter volume of the corpus callosum, and atypical lateralization of inhibitory control is related to a higher interhemispheric functional coupling of the IFC, suggesting a link between atypical functional lateralisation (language and inhibitory control) and structural and functional changes in the brain.

This study also provides interesting evidence on how atypical language lateralisation impacts some aspects of language behaviour (reading), i.e., atypical lateralization predicts worse reading accuracy. Furthermore, the results suggest an association between atypical lateralization and increased schizotypy and autistic traits.

Joint Public Review

In this study, Mitra and coworkers extend their previous analyses of the functional role of Orai in the excitability of central dopaminergic neurons in Drosophila. The authors show that a dominant-negative mutant of Orai (OraiE180A) significantly alters the gene expression profile of flight-promoting dopaminergic neurons (fpDANs), including that of Set2, E(z), and Trl, thereby shifting the level of epigenetic signatures that modulate gene expression. The Orai-Trl-Set2 pathway modulates the expression of voltage gated calcium channels, which, in turn, are involved in dopamine release. The study is generally well-done, is in-depth, and comprehensive. The finding that SOCE regulates a wide range of neuronal genes necessary for neuronal excitability and effector signaling by controlling chromatin remodeling genes is a noteworthy discovery.

The authors have adequately answered the previous concerns.

Joint Public Review:

Summary:

The existence of hox gene complexes conserved in animals with bilateral symmetry and in which the genes are arranged along the chromosome in the same order as the structures they specify along the anteroposterior axis of organisms is one of the most spectacular discoveries of recent developmental biology. In brief, homeotic mutations leads to the transformation of a given body segment of the fly into the copy of the next adjacent segment. For the sake of understanding the main observation of this work, it is important to know that in loss-of-function (LOF) alleles, a given segment develops like a copy of the segment immediately anterior to it, and in gain-of-function mutations (GOF), the affected segment develop like a copy of the immediately posterior segment. Over the last 30 years the molecular lesions associated with GOF alleles led to a model where the sequential activation of the hox genes along the chromosome result from the sequential opening of chromosomal domains. Most of these GOF alleles turned out to be deletions of boundary elements (BE) that define the extend of the segment-specific regulatory domains. The fruit fly Drosophila is a highly specialized insect with a very rapid mode of segmentation. Furthermore, the hox clusters in this lineage have split. Given these specificities it is legitimate to question whether the regulatory landscape of the BX-C we know of in D.melanogaster is the result of very high specialization in this lineage, or whether it reflects a more ancestral organization. In this article, the authors address this question by analyzing the continuous hox cluster in butterflies. They focus on the integenic region between the Antennapedia and the Ubx gene, where the split occurred in D.melanogaster. Hi-C and ATAC-seq data suggest the existence of a boundary element between 2 Topologically-Associated-Domain (TAD) which is also characterized by the presence of CTCF binding sites. Butterflies have 2 pairs of wings originating form T2 (forewing) specified by Antp and T3 specified by Ubx (hindwing). Remarkably, CRISPR mutational perturbation of this boundary leads to the hatching of butterflies with homeotic clones of cells with hindwings identities in the forewing (a posteriorly oriented homeotic transformation). In agreement with this phenotype, the authors observe ectopic expression of Ubx in these clones of cells. In other words, CRISPR mutagenesis of this BE region identified by molecular tool give rise to homeotic transformations directed towards more posterior segment as the boundary mutations that had been 1st identified on the basis of their posterior oriented homeotic transformation in Drosophila. None of the mutant clones they observed affect the hindwing, indicating that their scheme did not affect the nearby Ubx transcription unit. This is a reassuring and important 1st evidence that some of the regulatory paradigm that have been proposed in fruit flies are also at work in the common ancestor to Drosophilae and Lepideptora.

Given the large size of the Ubx transcription unit and its associated regulatory regions it is not surprising that the authors have identified ncRNA that are conserved in 4 species of Nymphalinae butterflies, some of which also present in D.melanogaster. Attempts to target the promoters by CRISPR give rise to clones of cells in both forewings and hindwings, suggesting the generation of regulatory mutations associated with both LOF and GOF transformations. The presence of clones with dual homeosis suggest the targeting of Ubx activator and repression CRMs. Unfortunately, these experiments do not allow us to make further conclusions on the role of these ncRNA or in the identification of specific regulatory elements. To the opinion of this referee, some recent papers addressing the role that these ncRNA may play into boundary function should be taken with caution, and evidences that ncRNA(s) regulate boundaries in the BX-C in a WT context are still lacking.

Strengths: the convincing GOF phenotype resulting from the targeting of the Antp-Ubx_BE

Weaknesses: the lack of comparisons with the equivalent phenotypes obtained in D.melanogaster with for example the Fub mutation

Reviewer #1 (Public Review):

Gametocytes are erythrocytic sexual stages of the malaria-causing parasite Plasmodium, and are essential for parasite transmission and reproduction in the mosquito vector. In this study, Murata et al investigated the mechanisms of gene regulation in female gametocytes in the rodent malaria model parasite Plasmodium berghei. According to current views, gene regulation in Plasmodium parasites is dominated by the family of AP2 transcription factors (TFs), such as the AP2-G TF, which drives sexual commitment. The same authors previously identified one AP2 TF, called AP2-FG, as an essential TF mediating differentiation of female gametocytes. Here, they identified a novel protein, called PFG (for partner of AP2-FG, also described as Fd2 in a recently published study), which cooperates with AP2-FG to regulate a subset of female gametocyte genes.

PFG was identified among AP2-G targets, but possesses no known DNA binding or other characterized domain. The authors show that PFG-knockout P. berghei parasites can form male and female gametocytes yet cannot transmit to mosquitoes, due to a defect in female gametocyte development. Using RNA-seq, they show that many female-specific genes are down-regulated in PFG(-)parasites. Chromatin immunoprecipitation combined with DNA sequencing (ChIP-seq) revealed that PFG colocalizes with AP2-FG on a ten-base motif that is enriched upstream of female-specific genes. Importantly, the ChIP-seq profile of PFG is unchanged in the absence of AP2-FG, suggesting that PFG binds to DNA independently of AP2-FG. Mutation of the ten-base motif in one target gene using CRISPR-Cas9 demonstrates that this motif is required for PFG localization at the gene locus. The data also show that binding of AP2-FG is affected in the absence of PFG, with disruption of AP2-FG interaction with the ten-base motif, but conservation of AP2-FG binding to distinct five-base motifs. Using a recombinant AP2 domain from AP2-FG, the authors demonstrate that the AP2 domain of AP2-FG binds to the five-base motifs. Using CRISPR they show that disruption of the five-base motifs in the genome abrogates AP2-FG binding, and using a reporter expression system they confirm that these motifs act as a cis-activating promoter element.

Through the analysis of target genes based on the presence of the ten- versus five-base motifs, the authors propose a model where AP2-FG can function in two forms, associated or not with PFG, and acting on the ten- or five-base motifs, respectively, to regulate distinct gene subsets during development of female gametocyte development.

The paper is well written, with a clear narrative, and the work is very well performed, relying on robust molecular approaches. Generally the conclusions and the model proposed by the authors are well supported by the data. Nevertheless, the study as it stands raises a number of questions. While the data convincingly show that PFG and AP2-FG cooperate to regulate the expression of a subset of female-specific genes, the paper does not show whether the two proteins actually interact with each other to form a complex. Also, how PFG binds to DNA and whether the protein has transactivating activity remains elusive, as the protein apparently possesses no known DNA-binding or activating domain. These points could be discussed in more detail in the manuscript and/or be the subject of follow up studies.

In summary, this work reveals the essential role of a Plasmodium protein with no known DNA binding or regulatory domain, illustrating that unknown facets remain to be uncovered in this fascinating pathogen.

Reviewer #2 (Public Review):

Murata et al have characterized a transcription activator previously identified in an earlier genetic screen by Russell et al (named Fd2; for female-defective 2), here named PFG. The authors show solid evidence that PFG is a partner of the previously described transcription factor AP2-FG and describe three sets of genes: genes activated by PFG or AP2-FG alone and genes activated by the complex. The authors also show differential binding to the target DNA sequences by AP2-FG to either a 10bp, if in a complex with PFG or a 5bp motif if alone. In all, this is a useful study which further elucidates the underlying regulatory network that drives development of sexual stages and ultimately transmission to mosquitoes. The data presented are clear and solid and the conclusions drawn are mostly supported by the results shown.

A few comments:

Given that the transcriptional programme is so dynamic, the timing of the ChIP-seq experiments is crucial. Could the authors clarify the timings of the different ChIP-seq experiments (AP2-FG, PFG, PFG in AP2-FG-, AP2-FG in PFG-, ...)

Fig 4c is an example of great overlap of peaks, but it would be helpful if the authors could quantify the overlaps between experiments (and describe the overlap parameters used).

It remains unclear if AP2-FG and PFG interact directly or if they bind sequentially in the transcriptional activation process. Perhaps they are part of a larger complex? Immunoprecipitation followed by mass spectrometry of the GFP-tagged version of PFG in the presence and absence of AP2-FG would be highly informative.

Reviewer #3 (Public Review):

This study is well designed and executed and provides new and important insights into the role of two TFs during the maturation of female gametocytes and fertilization in the mosquito midgut. However, it but would benefit from a more thorough characterization of the phenotype to understand at which step of development these factors are required.

Overall the authors have shown only limited willingness to comprehensively address reviewer concerns and incorporate their suggestions.

Joint Public Review:

Xie et al. propose that the asymmetric segregation of the NuRD complex is regulated in a V-ATPase-dependent manner, and plays a crucial role in determining the differential expression of the apoptosis activator egl-1 and thus critical for the life/death fate decision.

While the model is very intriguing, the reviewers raised concerns regarding the rigor of the method. One issue is with statistics (either insufficient information or inadequate use of statistics), and second is the concern that the asymmetry observed may be caused by one cell dying (resulting in protein degradation, RNA degradation etc). We recommend that the authors address these issues.

Major #1:

There are still many misleading statements/conclusions that are not rigorously tested or that are logically flawed. These issues must be thoroughly addressed for this manuscript to be solid.

1. Asymmetry detected by scRNA seq vs. imaging may not represent the same phenomenon, thus should not be discussed as two supporting pieces of evidence for the authors' model, and importantly each method has its own flaw. First, for scRNA seq, when cells become already egl-1 positive, those cells may be already dying, and thus NuRD complex's transcripts' asymmetry may not have any significance. The data presented in FigS1D, E show that there are lots of genes (6487 out of 8624) that are decreased in dying cells. Thus, it is not convincing to claim that NuRD asymmetry is regulated by differential RNA amount.

2. Regarding NuRD protein's asymmetry, there are still multiple issues. Most likely explanation of their asymmetry is purely daughter size asymmetry. Because one cell is much bigger than the other (3 times larger), NuRD components, which are not chromatin associated, would be inherited to the bigger cell 3 times more than the smaller daughter. Then, upon nuclear envelope reformation, NuRD components will enter the nucleus, and there will be 3 times more NuRD components in the bigger daughter cell. It is possible that this is actually the underling mechanism to regulate gene expression differentially, but this possibility is not properly acknowledged. Currently, the authors use chromatin associated protein (Mys-1) as 'symmetric control', but this is not necessarily a fair comparison. For NuRD asymmetry to be meaningful, an example of protein is needed that is non-chromatin associated in mitosis, distributed to daughter cells proportional to daughter cell size, and re-enter nucleus after nuclear envelope formation to show symmetric distribution. And if daughter size asymmetry is the cause of NuRD asymmetry, other lineages that do not undergo apoptosis but exhibit daughter size asymmetry would also show NuRD asymmetry. The authors should comment on this (if such examples exist, it is fine in that in those cell types, NuRD asymmetry may be used for differential gene expression, not necessarily to induce cell death, but such comparison provides the explanation for NuRD asymmetry, and puts the authors finding in a better context).

3. For the analysis of protein asymmetry between two daughters in Fig S4C, the method of calibration is unclear, making it difficult to interpret the results.

4. As for pHluorin experiments, the authors were asked to test the changes in fluorescence observed are due to changes in pH or changes in the amount of pHluorin protein. They need to add a ratio-metric method in this manuscript. A brief mention to Page 12 line 12 is insufficient to clarify this issue.

Major #2:

Some issues surrounding statistics must be resolved.

1. Fig. 1FG, 2D, 3BDEG, 5BD and 6B used either one-sample t-test or unpaired two-tailed parametric t-test for statistical comparison. These t-tests require a verification of each sample fitting to a normal distribution. The authors need to describe a statistical test used to verify a normal distribution of each sample.

2. Fig. 2D, 3D, and 3G have very small sample size (N=3-4, N=6, N=3, respectively), it is possible that a normal distribution cannot be verified. How can the authors justify the use of one-sample t-test and unpaired parametric t-test ?

3. Statistical comparison in Fig. 2D and Fig. 6B should be re-assessed. For Fig. 2D, the authors need to compare the intensity ratio of HDA-1/LIN53 between sister cells dying within 35 min and those over 400 min. For Fig. 6B, they need to compare the intensity ratio of VHA-17 between DMSO- and BafA1- treated cells at the same time point after anaphase.

Reviewer #1 (Public Review):

Huang C-K. and colleagues in this work address the understudied role of environmental conditions and external forces in cell extrusion as a fundamental part of epithelial homeostasis. They suggest that hydrostatic stress plays a significant role in counteracting cell extrusion forces through the indirect regulation of the focal adhesion kinase (FAK) - protein kinase B (AKT) survival pathway. The team nicely exploits their expertise in fabricating cell culture substrates to control hydrostatic stress on a common epithelial cell model from the kidney (i.e., MDCK). This was done by creating waving surfaces with different lengths from 50µm to 200 µm, thus creating a heterogenous distribution of monolayer forces towards the substrate. Finally, using a specific inhibitor for FAK, they suggest that the survivor pathway FAK-AKT is involved in the observed phenomenon.

In conclusion, the presented data underline the importance of considering external forces and tissue geometry in regulating epithelial homeostasis and the selective transport of water and solutes. These results may have a significant impact on understanding the basic mechanisms of epithelial physiology and pathology, such as in the kidney, intestine, or retina.

Comments on the revised version:

Overall, most of my comments were reasonably addressed. Nevertheless, one comment was not convincingly addressed ("Recommendation 5" - reviewer #1).

The authors did not show that the FAK inhibitor directly induced the reduction of AKT phosphorylation but used this experiment to conclude that FAK - AKT survivor pathway is involved in the observed phenomenon (Fig. 4). The authors mentioned that additional immunoblotting experiments are currently underway. This is a minor control for the manuscript message, but I feel it is necessary. The connection between the levels of FAK and p-AKT shown in Fig. 4E is purely correlative and can be caused by ECM adhesion-independent reasons.

Alternatively, the authors could reduce the stress on the FAK - AKT survivor pathway's involvement and conclude only on the involvement of FAK.

Reviewer #2 (Public Review):

The paper by Huan, Yong, et al. studies epithelial cell extrusion in MDCK monolayers grown on sinusoidally wavy surfaces in varying media osmolarities, finding that both curvature and osmolarity-mediated basal hydraulic stress spatially regulate extrusion events. The authors fabricated wavy substrates of varying periods and amplitude out of PDMS (and PA hydrogels) and monitored monolayer evolution and cell extrusion over time, by combining live-cell imaging with a convolutional network-based algorithm for automatic detection of extrusions.

In general, the study has been elegantly designed, starting with convincing evidence for enhanced extrusion rates in concave valleys with respect to convex hills. Next, the authors showed that hyper-osmotic medium reduced cell extrusion rate, which was demonstrated in a variety of different media compositions (e.g. with sucrose, DMSO, or NaCl), while hypo-osmotic medium increased cell extrusion rate. Additionally, the authors applied reflection interference contrast microscopy to reveal fluid spaces between the substrate and the basal side of the monolayer, which were found to grow when media composition was altered from hyper-osmotic to normal osmotic conditions. Using a 3D traction force microscopy approach, the authors demonstrated that cells on convex regions apply a downward pointing force on the substrate, opposite to cells on the concave regions. This was linked to a larger basal separation on the concave valleys as opposed to the convex hills. Finally, the authors focussed on the FAK-Akt pathway to explore the hypothesis that basal hydraulic stress interferes with focal adhesions, leading to differences in cell extrusion rates in media of different osmolarity and on convex or concave surfaces.

Comments on the revised version:

My previous comments were reasonably answered. In response to the comment that "experiments that are currently underway" for "Recommendation 5 - reviewer #1", I would also suggest the authors to either add the additional data or alter the emphasis on the FAK-AKT pathway in the manuscript accordingly if additional data is not presented.

Reviewer #1 (Public Review):

The authors use a combination of structural and MD simulation approaches to characterize phospholipid interactions with the pentameric ligand-gated ion channel, GLIC. By analyzing the MD simulation data using clusters of closed and open states derived previously, the authors also seek to compare lipid interactions between putative functional states. The ultimate goal of this work is to understand how lipids shape the structure and function of this channel.

The strengths of this article include the following:

1) The MD simulation data provide extensive sampling of lipid interactions in GLIC, and these interactions were characterized in putative closed and open states of the channel. The extensive sampling permits confident delineation of 5-6 phospholipid interaction sites per subunit. The agreement in phospholipid binding poses between structures and the all-atom MD simulations supports the utility of MD simulations to examine lipid interactions.

2) The study presents phospholipid binding sites/poses that agree with functionally important lipid binding sites in other pLGICs, supporting the notion that these sites are conserved. For example, the authors identify interactions of POPC at an outer leaflet intersubunit site that is specific for the open state. This result is quite interesting as phospholipids or drugs that positively modulate other pLGICs are known to occupy this site. Also, the effect of mutating W217 in the inner leaflet intersubunit site suggests that this residue, which is highly conserved in pLGICs, is an important determinant of the strength of phospholipid interactions at this site. This residue has been shown to interact with phospholipids in other pLGICs and forms the binding site of potentiating neurosteroids in the GABA(A) receptor.

Comments on the revised version:

We appreciate the authors' thorough response and revisions.

Specifically, the authors address the issue of interaction times by providing measures of the diffusion coefficients and mean displacements of the lipids. These show that there is sufficient movement of lipids within the first shell to indicate that certain residues are forming binding interactions with lipids while others are not. Longer simulation times would be necessary to determine the strength of these interactions and how they may differ between different conformations.

Reviewer #2 (Public Review):

The authors convincingly show multiple inner and outer leaflet non-protein (lipid) densities in a cryo-EM closed state structure of GLIC, a prokaryotic homologue of canonical pentameric ligand-gated ion channels, and observe lipids in similar sites during extensive simulations at both resting and activating pH. The simulations not only corroborate structural observations but also suggest the existence of a state-dependent lipid intersubunit site only occupied in the open state. These important findings will be of considerable interest to the ion channel community and provide new hypotheses about lipid interactions in conjunction with channel gating.

Comments on the revised version:

The authors have addressed all of my comments.

Reviewer #1 (Public Review):

In this study, single neurons were recorded, using tetrodes, from the parahippocampal cortex of 5 rats navigating a double-Y maze (in which each arm of a Y-maze forks again). The goal was located at any one of the 4 branch terminations, and rats were given partial information in the form of a light cue that indicated whether the reward was on the right or left side of the maze. The second decision point was un-cued and the rat had no way of knowing which of the two branches was correct, so this phase of the task was more akin to foraging. Following the outbound journey, with or without reward, the rat had to return (inbound journey) to the maze start, to begin again.

Neuronal activity was assessed for correlations with multiple navigation-relevant variables including location, head direction, speed, reward side, and goal location. The main finding is that a high proportion of neurons showed an increase in firing rate when the animal made a wrong turn at the first branch point (the one in which the correct decision was signalled). This increase, which the authors call rate remapping, persisted throughout the inbound journey as well. It was also found that head direction neurons (assessed by recording in an open field arena) in the same location in the room were more likely to show the rate change. The overall conclusion is that "during goal-directed navigation, parahippocampal neurons encode error information reflective of an animal's behavioral performance" or are "nodes in the transmission of behaviorally relevant variables during goal-directed navigation."

Overall I think this is a well-conducted study investigating an important class of neural representation: namely, the substrate for spatial orientation and navigation. The analyses are very sophisticated - possibly a little too much so, as the basic findings are relatively straightforward and the analyses take quite a bit of work to understand. A difficulty with the study is that it was exploratory (observational) rather than hypothesis-driven. Thus, the findings reveal correlations in the data but do not allow us to infer causal relationships. That said, the observation of increased firing in a subset of neurons following an erroneous choice is potentially interesting. However, the effect seems small. What were the actual firing rate values in Hz, and what was the effect size?

I also feel we are lacking information about the underlying behavior that accompanies these firing rate effects. The authors say "one possibility is that the head-direction signal in the parahippocampal region reflects a behavioral state related to navigational choice or the lack of commitment to a particular navigational route" which is a good thought and raises the possibility that on error trials, rats are more uncertain and turn their heads more (vicarious trial and error) and thus sample the preferred firing direction more thoroughly. Another possibility is that they run more slowly, which is associated with a higher firing rate in these cells. I think we therefore need a better understanding of how behaviour differed between error trials in terms of running speed, directional sampling, etc. A few good, convincing raw-data plots showing a remapping neuron on an error trial and a correct trial on the same arm would also be helpful (the spike plots were too tiny to get a good sense of this: fewer, larger ones would be more helpful). It would be useful to know at what point the elevated response returned to baseline, how - was it when the next trial began, and was the drop gradual (suggesting perhaps a more neurohumoral response) or sudden?

Comments on the revised submission:

The authors have clarified a number of points arising from my original review but some remain.

On the issue of hypotheses: I was really referring, and apologies that I was unclear on this, to the hypothesis about the neural responses predicted in this experiment. The authors aimed to "examine whether spatial representations flexibly adapt to behaviorally relevant factors" but this is not really a hypothesis as such, in the true mechanistic sense so much as "let's see what we can find" which is not an invalid reason to do this type of study. However, no manipulations were made that test causal relationships arising from the study. It thus remains observational. It does however raise testable hypotheses which is valuable. The strongest in my mind is that the rise in firing rates is a catecholamine response to frustration, a conclusion supported by the slow temporal dynamics of the changes.

On the issue of running speed: it needs to be ruled out that this might have been the cause of the altered firing rates since running speeds were different. More generally, the lack of other concurrent behavioral data means we cannot rule out other possible behavioral bases to this effect that are unrelated to error but are related to the motor correlates of the error.

Reviewer #2 (Public Review):

This work recorded neurons in the parahippocampal regions of the medial entorhinal cortex (MEC) and pre- and para-subiculum (PrS, PaS) during a visually guided navigation task on a 'tree maze'. They found that many of the neurons reflected in their firing the visual cue (or the associated correct behavioral choice of the animal) and also the absence of reward in inbound passes (with increased firing rate). Rate remapping explained best these firing rate changes in both conditions for those cells that exhibited place-related firing. This work used a novel task, and the increased firing rate at error trials in these regions is also novel.

The limitation is that cells in these regions were analyzed together.

Comments on the revised submission:

I accept the authors' response that histological differentiation of these regions was not possible.

Reviewer #3 (Public Review):

Summary & Strengths:

This study is useful in revealing the neural correlates of goal-directed navigation in the rodent parahippocampal regions, including the medial entorhinal cortex, presubiculum, and parasubiculum. It shows that task-relevant information represented by the parahippocampus is strongly related to task performance. It also reports the relationships of navigational factors (e.g., head direction signal) recorded during foraging in an open field with task variables.

Gonzalez and Giocomo investigated the neural activities in the parahippocampal cortex modulated by visual cues and error signals while the animal performed a goal-directed navigation task on the tree maze. They confirmed that the firing rates and spatial firing patterns in the parahippocampus were significantly correlated with the animal's task performance and the general navigational coding in the open field arena. The authors have concluded that the parahippocampal neurons encode mismatch-like signals, suggesting the functional role of the parahippocampus as a feedback system in a goal-directed task. However, a few major concerns should be addressed more closely to support the conclusion.

1) Due to the limitations of histological verification, the neural responses in the medial entorhinal cortex, presubiculum, and parasubiculum are analyzed together, and this limits the study from understanding the differential information processing across these regions. Because the medial entorhinal cortex and the pre/parasubiculum are believed to be located in very different positions in the information flow within the rodent medial temporal lobe with different anatomical connections, it would have been more convincing if the distinctive functions between the regions could be identified.

2) The authors should carefully differentiate rate remapping and global remapping in their analysis. Rate remapping generally indicates firing rate modulation with little or no shift of spatial firing fields (Leutgeb et al., 2005; Colgin et al., 2008). Therefore, the neurons exhibiting global remapping should not be included in the analysis suited for rate remapping (e.g., the encoding model that considers the cue-dependent rate-remapping effect).

3) One of the major findings in this study is that the parahippocampal neural responses to a visual cue or reward were correlated with task performance. One can expect that cue representation before the decision point is likely to have a greater impact on task performance. Although the Uz score between the left cue and right cue seemed not significantly different from zero on the stem, it would be beneficial if the authors verify whether the remapping score based on the firing rate maps will still be correlated with the task performance when examined only before the decision point, not for the entire maze.

4) There is a need to set the analytic epoch in more detail. The boundary between outbound and inbound journeys was set as 'last goal well visit.' However, even in a correct trial, if the reward was not received in the first goal well, an error signal could occur before the animal triggered the second goal well which was rewarding. This might have caused the rate remapping between two cue conditions, specifically on the arms. To eliminate this possibility, it is recommended to set the outbound journey from the home well trigger to the first goal well approach or to select only trials where the animal received rewards from the first goal well triggering.

Weaknesses:

Incomplete results could limit support for the arguments of the study and may require more rigorous analytical methods.

Reviewer #1 (Public Review):

The authors set out to determine the causal influence of the rIFG on stop-signal inhibition by using the innovative method of focused ultrasound to modulate this area during a stop-signal task. They report that tFUS during the stop signal only (and not the go) affected the probability of making a stop (only for long SSD) and reduced reaction time. tFUS also looked to affect some ERP components thus lending 'causal' evidence for the role of rIFG in stopping behavior and N200/P300 dynamics. The background and premise seem solid, the experimental design looks appropriate with good controls however, I do not think the authors' conclusions are supported. The methods are difficult to understand, and lack citations (background for performing these analyses/pre-processing) - some are listed but not in the reference list - but also leave out important methodology and detail. Despite the fact that there are many statistical tests in the results there are none for their main conclusions that the P300 latency indexes stop-signal inhibition - this is only descriptive. Individuals with expertise in the field of stop signal inhibition are encouraged to read this pre-print to gauge the veracity of the authors' conclusions and the appropriateness of their methodology.

Reviewer #2 (Public Review):

The authors investigated a central component of adaptive and flexible human behaviour: our ability to stop ongoing action plans. This ability is under prefrontal control, with an important contribution of the right inferior prefrontal gyrus (rIFG). This is a well-studied system, yet providing causal evidence, especially at an electrophysiological level, has proven challenging. In this study the authors use a novel non-invasive brain stimulation technique, transcranial ultrasonic stimulation (TUS), to selectively stimulate the rIFG and record behavioural and electrophysiological changes in the context of a stop-signal task.

The principal finding of this work is that following TUS over rIFG, participants are faster to respond to a stop signal when successfully inhibiting a planned action program. This faster stop-inhibition was reflected both in behaviour and evoked responses as measured with electroencephalography.

The spatial specificity of the TUS stimulation allows strong inferences on selective targeting. The inclusion of two control groups, one receiving stimulation over an active control site, and the other receiving a non-stimulating sham condition, makes the specificity of the observed effect convincing.

The EEG analyses are advanced, exploiting robust data-cleaning and selection approaches to allow strong inferences for analyses in sensor space. Through careful trial-matching and dynamic time-warping, the effects of primary interest - responses evoked by stopping behaviour - could be isolated from those evoked by the go-cue and go-response.

The manuscript focusses on the latency of the electrophysiological response (ERP). Indeed, an earlier P300 ERP is expected considering that TUS over rIFG led to an earlier stop-signal-reaction time (SSRT). However, as the SSRT is inferred from a model fit on the probability of go-responses as a function of the stop-signal delay (more often failing to inhibit go-responses when the stop-signal arrives late), the empirical observation of a latency shift in the closely related P300 ERP is valuable.

It is less clear how the P300 ERP itself relates to the TUS stimulation over rIFG, considering that this ERP has a well-established mid-frontal topology, while rIFG is in the lateral prefrontal cortex. The authors suggest that in the context of stopping control, rIFG is positioned upstream from the mid-frontal regions. However, previous work has revealed an inverse temporal and causal relationship, where rIFG contributions follow those of preSMA (e.g. Neubert et al., 2010, PNAS).

Behavioural changes, especially those dependent on attention and a speeded response, are commonly driven by non-specific cues, such as auditory, somatosensory, or multi-modal cues. This is a major confounding factor for all brain stimulation paradigms. TUS is no exception. Pulsed TUS protocols, such as the 1000 Hz pulsed protocol employed here, are very likely to be accompanied by an auditory confound. In the condition of interest in this experiment, TUS is delivered together with the visual stop-signal, creating a multimodal cue. In the main analyses (figures 3 and 4) this is only contrasted against conditions where the stop-signal is unimodal (visual) only, creating a multi-modal vs. uni-modal contrast.

Indeed, the critical comparison to allow the strongest inference is not between stop-TUS vs. go-TUS, nor between stop-TUS vs. no-TUS, but between the two TUS sites: rIFG-TUS vs rS1-TUS in the stop condition. The inclusion of the S1-TUS condition in this study is therefore highly valuable, although this contrast was implemented as a between-group design, and no assessment of confound matching between rIFG-TUS and S1-TUS is reported. Perhaps more importantly, the main analyses and figures (e.g. figure 3), do not include this comparison. In fact, the data from the TUS control-site group are not included in any analyses of evoked potentials (EEG) at all (e.g. figure 4), even though this is the main focus of the study.

The title of the study is "Transcranial focused ultrasound to rIFG improves response inhibition through modulation of the P300 onset latency". The discussion reads "P300 latency modulation occurred only in the rIFG group". It is not straightforward to see how this conclusion is supported without including a control site in the analyses. Further, the reported difference in onset latency is based on a visual inspection of the data, not on a quantified statistical analysis ("visually contrasting SS-US difference waveforms across tFUS conditions (Fig. 4B, upper right) revealed P300 onsets shifted earlier during Stop-tFUS"). Visual inspection of the same figure might also highlight a clear difference in ERP amplitude, in addition to latency. Lastly, the suggestion of a directional mediation effect ("improves response inhibition through modulation of the P300 onset latency") is only supported by a correlational analysis relating P300 onset latency with the estimated stop-signal-reaction-time.

In summary, by advancing transcranial ultrasonic stimulation to study prefrontal control, this work signifies a paradigm shift towards using interventional tools in cognitive neuroscience. The specificity and precision that ultrasound stimulation provides, with reduced discomfort as compared to TMS, are urgently needed to support a refined and causal understanding of the neural circuits underlying human cognition. The central claims of this study are partially supported by the data presented and might benefit from quantitatively comparing the effects of TUS over the region of interest and the control site.

Reviewer #3 (Public Review):

The paper by Li et al. describes the role of the TOR pathway in Aspergillus flavus. The authors tested the effect of rapamycin in WT and different deletion strains. This paper is based on a lot of experiments and work but remains rather descriptive and confirms the results obtained in other fungi. It shows that the TOR pathway is involved in conidiation, aflatoxin production, pathogenicity, and hyphal growth. This is inferred from rapamycin treatment and TOR1/2 deletions. Rapamycin treatment also causes lipid accumulation in hyphae. The phenotypes are not surprising as they have been shown already for several fungi. In addition, one caveat is in my opinion that the strains grow very slowly and this could cause many downstream effects. Several kinases and phosphatases are involved in the TOR pathway. They were known from S. cerevisiae or filamentous fungi. The authors characterized them as well with knock-out approaches.

Reviewer #1 (Public Review):

Their absolute quantification PCR results with the sumo reference gene led the authors to conclude that A. flavus has two copies of tor and tapA in its genome. However, the the genomic location of the additional copies of tor and tapA are unknown.

I have concerns about the conclusion for the following reasons:

First, the authors should provide more convincing data showing that tor and tapA genes are indeed duplicated genes in A. flavus. The authors appeared to use the A. flavus PTS strain as a parental strain for constructing the tor and tapA mutants. If so, the A. flavus CA14 strain (Hua et al., 2007) should be the parental wild-type strain for the A. flavus PTS strain. I did a BLAST search in NCBI for the torA (AFLA_044350) and tapA (AFLA_092770) genes using the most recent CA14 genome assembly sequence (GCA_014784225.2) and only found one allele for each gene: torA on chromosome 7 and tapA on chromosome 3. I could not find any other parts with similar sequences. Even in another popular A. flavus wild-type strain, NRRL3357, both torA and tapA exist as a single allele. Based on the published genome assembly data for A. flavus, there is no evidence to support the idea that tor and tapA exist as copies of each other. Therefore, the authors could perform a Southern blot analysis to further verify their claim. If torA and tapA indeed exist as duplicate copies in different chromosomal locations, Southern blot data could provide supporting results.

If the tor and tapA genes indeed exist as dual copies, do the duplicate genes have identical DNA and protein sequences? If they have different DNA or protein sequences, they should be named differently as paralogs, such as torA and torB or tapA and tapB.

Second, the authors should consider the possibility of aneuploidy for their constructed mutants. When an essential gene is targeted for deletion, aneuploidy often occurs even in a fungal strain without the "ku" mutation, which results in seemingly dual copies of the gene. As the authors appear to use the A. flavus PTS strain having the "ku" mutation, the parental strain has increased genome instability, which may result in enhanced chromosomal rearrangements. So, it will be necessary to Illumina-sequence their tor and tapA mutants to make sure that they are not aneuploidy.

Furthermore, the genetic nomenclature +/- and -/- should be reserved for heterozygous and homozygous mutants in a diploid strain. As A. flavus is not a diploid strain, this type of description could cause confusion for the readers.

Reviewer #2 (Public Review):

In this study, authors identified the complex TOR, HOG and CWI signaling networks-involved genes that relatively modulate the development, aflatoxin biosynthesis and pathogenicity of A. flavus by gene deletions combined with phenotypic observation.

They also analyzed the specific regulatory process and proposed that the TOR signaling pathway interacts with other signaling pathways (MAPK, CWI, calcineurin-CrzA pathway) to regulate the responses to various environmental stresses. Notably, they found that FKBP3 is involved in sclerotia and aflatoxin biosynthesis and rapamycin resistance in A. flavus, especially found that the conserved site K19 of FKBP3 plays a key role in regulating the aflatoxin biosynthesis. In general, there is heavy workload task carried in this study and the findings are interesting and important for understanding or controlling the aflatoxin biosynthesis. However, findings have not been deeply explored and conclusions are mostly are based on parallel phenotypic observations. In addition, there are some concerns for the conclusions.

Reviewer #1 (Public Review):

Summary:<br /> In their revised manuscript, the authors analyze the evolution of the gasdermin family and observe that the GSDMA proteins from birds, reptiles and amphibians does not form a clade with the mammalian GSDMAs. Moreover, the non-mammalian GSDMA proteins share a conserved caspase-1 cleavage motif at the predicted activation site. The authors provide several series of experiments showing that the non-mammalian GSDMA proteins can indeed be activated by caspase-1 and that this activation leads to cell death (in human cells). They also investigate the role of the caspase-1 recognition tetrapeptide for cleavage by caspase-1 and for the pathogen-derived protease SpeB.

Strengths:<br /> The evolutionary analysis performed in this manuscript appears to use a broader data basis than what has been used in other published work. An interesting result of this analysis is the suggestion that GSDMA is evolutionary older than the main mammalian pyroptotic GSDMD, and that birds, reptiles and amphibians lack GSDMD but use GSDMA for the same purpose. The consequence that bird GSDMA should be activated by an inflammatory caspase (=caspase1) is convincingly supported by the experiments provided in the manuscript.

Weaknesses:<br /> While the cleavability of bird/reptile GSDMA by caspase-1 is well-supported by several experiments, the role of this cleavage for pyroptotic cell killing is addressed more superficially. The experiments performed to this end all use human cells; it is likely - but not guaranteed - that the human model recapitulaes the physiological role of non-mammalian GSDMA proteins. While the data provided in this paper help to understand GSDMA evolution and the activation mechanism of bird/reptile GSDMA, it does not address the still elusive activation mechanism for mammalian GSDMA

As a consequence, the significance of this finding is mostly limited to birds and reptiles.

Reviewer #2 (Public Review):

Summary:

The authors investigated the molecular evolution of members of the gasdermin (GSDM) family. By adding the evolutionary time axis of animals, they created a new molecular phylogenetic tree different from previous ones. The analyzed result verified that non-mammalian GSDMAs and mammalian GSDMAs have diverged into completely different and separate clades. Furthermore, by biochemical analyses, the authors demonstrated non-mammalian GSDMA proteins are cleaved by the host-encoded caspase-1. They also showed mammalian GSDMAs have lost the cleavage site recognized by caspase-1. Instead, the authors proposed that the newly appeared GSDMD is now cleaved by caspase-1.

Through this study, we have been able to understand the changes in the molecular evolution of GSDMs, and by presenting the cleavage of GSDMAs through biochemical experiments, we have become able to grasp the comprehensive picture of this family molecules. However, there are some parts where explanations are insufficient, so supplementary explanations and experiments seem to be necessary.

Strengths:

It has a strong impact in advancing ideas into the study of pyroptotic cell death and even inflammatory responses involving caspase-1.

Weaknesses:

Based on the position of mammalian GSDMA shown in the molecular phylogenetic tree (Figure 1), it may be difficult to completely agree with the authors' explanation of the evolution of GSDMA.

1) Focusing on mammalian GSDMA, this group and mammalian GSDMD diverged into two clades, and before that, GSDMA/D groups and mammalian GSDMC separated into two, more before that, GSDMB, and further before that, non-mammalian GSDMA, when we checked Figure 1. In the molecular phylogenetic tree, it is impossible that GSDMA appears during evolution again. Mammalian GSDMAs are clearly paralogous molecules to non-mammalian GSDMAs in the figure. If they are bona fide orthologous, the mammalian GSDMA group should show a sub-clade in the non-mammalian GSDMA clade. It is better to describe the plausibility of the divergence in the molecular evolution of mammalian GSDMA in the Discussion section.

2) Regarding (1), it is recommended that the authors reconsider the validity of estimates of divergence dates by focusing on mammalian species divergence. Because the validity of this estimation requires recheck of the molecular phylogenetic tree, including alignment.

3) If GSDMB and/or GSDMC between non-mammalian GSDMA and mammalian GSDMD as shown in the molecular phylogenetic tree would be cleaved by caspase-1, the story of this study becomes clearer. The authors should try that possibility.

Reviewer #1 (Public Review):

Summary:<br /> The preprint by Laganowsky and co-workers describes the use of mutant cycles to dissect the thermodynamic profile of specific lipid recognition by the ABC transporter MsbA. The authors use native mass spectrometry with a variable temperature source to monitor lipid binding to the native protein dimer solubilized in detergent. Analysis of the peak intensities (that is, relative abundance) of 1-3 bound lipids as a function of solution temperature and lipid concentration yields temperature-dependent Kds. The authors use these to then generate van't Hoff plots, from which they calculate the enthalpy and entropy contributions to binding of one, two, and in some cases, three lipids to MsbA. The authors have previously demonstrated that MS can indeed extract thermodynamic contributions to lipid binding. The authors then employ mutant cycles, in which basic residues involved in headgroup binding are mutated to alanine. By comparing the thermodynamic signatures of single and double (and in one instance triple) mutants, they aim to identify cooperativity between the different positions. They furthermore use inward and outward locking conditions which should control access to the different binding sites determined previously. The main conclusion is that lipid binding to MsbA is driven mainly by energetically favorable entropy increase upon binding, which stems from the release of ordered water molecules that normally coordinate the basic residues, which helps to overcome the enthalpic barrier of lipid binding. The authors also report an increase in lipid binding at higher temperatures which they attribute to a non-uniform heat capacity of the protein. Although they find that most residue pairs display some degree of cooperativity, particularly between the inner and outer lipid binding sites, they do not provide a structural interpretation of these results.

Strengths:<br /> The use of double mutant cycles and mass spectrometry to dissect lipid binding is novel and interesting. For example, the observation that mutating a basic residue in the inner and one in the outer binding site abolishes lipid binding to a greater extent than the individual mutations is highly informative even without having to break it down into thermodynamic terms. The method and data reported here opens new avenues for the structure/activity relationship of MsbA. The "mutant cycle" approach is in principle widely applicable to other membrane proteins with complex lipid interactions.

Weaknesses:<br /> The use of double mutant cycles to dissect binding energies is well-established, and has, as the authors point out, been employed in combination with mass spectrometry to study protein-protein interactions. Its application to extract thermodynamic parameters is robust in cases where a single binding event is monitored, e.g. the formation of a complex with well-defined stoichiometry, where dissociation constants can be determined with high confidence. It is, however, complicated significantly by the fact that for MsbA-lipid interactions, we are not looking at a single binding event, but a stochastic distribution of lipids across different sites. Even if the protein is locked in a specific conformation, the observation of a single lipid adduct does not guarantee that the one lipid is always bound to a specific site. The authors discuss this issue in the manuscript. As they point out, one can assume that the most high-affinity sites will be populated first. Hence, the Kd values determined by MS likely describe (mostly) lipid binding to these sites, although this does not seem to hold universally true, as seen for example for the two (in principle equivalent) binding sites in the vanadate-locked protein. In addition, mutation of a binding site (which the authors show reduces lipid binding) may instead allow the lipid to bind to a lower-affinity site elsewhere. In summary, the Kds are an approximation.<br /> (Minor comment: The protein concentrations used for MS titration experiments should be stated in the methods.)

The authors conclude that solvation entropy is a major factor driving lipid binding (Figure 6). If the increase in entropy upon lipid binding comes from the release of ordered water molecules around the basic residues, we should see a smaller increase in entropy for proteins where several basic residues have been changed to alanine, which is not the case. The authors explain this by stating that other entropic factors likely are at play. Judging from their data, that is certainly correct, but why then focus on solvation entropy in the discussion if its contribution to the total entropy change cannot be determined?

Reviewer #3 (Public Review):

Summary:<br /> In this paper presented by Liu et al, native MS on the lipid A transporter MsbA was used to obtain thermodynamic insight into protein-lipid interactions. By performing the analyses at different lipid A concentrations and temperatures, dissociation constants for 2-3 lipid A binding sites were determined, as well as enthalpies were calculated using non-linear van't Hoff fitting.

Strengths:<br /> This is an extensive high quality native MS dataset that provides unique opportunities to gain insights into the thermodynamic parameters underlying lipid A binding. In addition, it provides coupling energies between mutations introduced into MsbA, that are implicated in lipid A binding.

Weaknesses:<br /> It remains elusive, which KD values belong to which of the possible lipid A binding sites.

Appraisal:<br /> The authors convincingly addressed the concerns raised by the reviewers.

Joint Public Review:

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

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

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

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

Weaknesses:

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

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

Reviewer #1 (Public Review):

This study delineates an important set of uninjured and injured periosteal snRNAseq data that provides an overview of periosteal cell responses to fracture healing. The authors also took additional steps to validate some of the findings using immunohistochemistry and transplantation assays. This study will provide a valuable publicly accessible dataset to reexamine the expression of the reported periosteal stem and progenitor cell markers.

Strengths:<br /> 1. This is the first single-nuclei atlas of periosteal cells that are obtained without enzymatic cell dissociation or targeted cell purification by FACS. This integrated snRNAseq dataset will provide additional opportunities for the community to revisit the expression of many periosteal cell markers that have been reported to date.

2. The authors delved further into the dataset using cutting-edge algorithms, including CytoTrace, SCENIC, Monocle, STRING, and CellChat, to define the potential roles of identified cell populations in the context of fracture healing. These additional computation analyses generate many new hypotheses regarding periosteal cell reactions.

3. The authors also sought to validate some of the computational findings using immunohistochemistry and transplantation assays to support the conclusion.

Weaknesses:<br /> 1. The current snRNAseq datasets contain only a small number of nuclei (1,189 nuclei at day 0, 6,213 nuclei on day 0-7 combined). It is unclear if the number is sufficient to discern subtle biological processes such as stem cell differentiation.

2. The authors' designation of Sca1+CD34+ cells as SSPCs is not sufficiently supported by experimental evidence. It will be essential to demonstrate stem/progenitor properties of Sca1+CD34+ cells using independent biological approaches such as CFU-F assays. In addition, the putative lineage trajectory of SSPCs toward IIFCs, osteoblasts, and chondrocytes remains highly speculative without concrete supporting data.

3. The designation of POSTN+ clusters as injury-induced fibrogenic cells (IIFCs) is not fully supported by the presented data. The authors' snRNAseq datasets (Figure 1d) demonstrate that there are many POSTN+ cells prior to injury, indicating that POSTN+ cells are not specifically induced in response to injury. It has been widely recognized that POSTN is expressed in the periosteum without fracture. This raises a possibility that the main responder of fracture healing is POSTN+ cells, not SSPCs as they postulate. The authors cannot exclude the possibility that Sca1+CD34+ cells are mere bystanders and do not participate in fracture healing.

4. Detailed spatial organization of Sca1+CD34+ cells and POSTN+ cells in the uninjured periosteum with respect to the cambium layer and the fibrous layer is not demonstrated.

5. Interpretation of transplantation experiments in Figure 5 is not straightforward, as the authors did not demonstrate the purity of Prx1Cre-GFP+SCA1+ cells and Prx1Cre-GFP+CD146- cells to pSSPCs and IIFCs, respectively. It is possible that these populations contain much broader cell types beyond SSPCs or IIFCs.

Reviewer #2 (Public Review):

Summary:<br /> The authors described cell type mapping was conducted for both WT and fracture types. Through this, unique cell populations specific to fracture conditions were identified. To determine these, the most undifferentiated cells were initially targeted using stemness-related markers and CytoTrace scoring. This led to the identification of SSPC differentiating into fibroblasts. It was observed that the fibroblast cell type significantly increased under fracture conditions, followed by subsequent increases in chondrocytes and osteoblasts.

Strengths:<br /> This study presented the injury-induced fibrogenic cell (IIFC) as a characteristic cell type appearing in the bone regeneration process and proposed that the IIFC is a progenitor undergoing osteochondrogenic differentiation.

Weaknesses:<br /> This study endeavored to elucidate the role of IIFC through snRNAseq analysis and in vivo observation. However, such validation alone is insufficient to confirm that IIFC is an osteochondrogenic progenitor, and additional data presentation is required.

Reviewer #3 (Public Review):

In this manuscript, the authors explored the transcriptional heterogeneity of the periosteum with single nuclei RNA sequencing. Without prior enrichment of specific populations, this dataset serves as an unbiased representation of the cellular components potentially relevant to bone regeneration. By describing single-cell cluster profiles, the authors characterized over 10 different populations in combined steady state and post-fracture periosteum, including stem cells (SSPC), fibroblast, osteoblast, chondrocyte, immune cells, and so on. Specifically, a developmental trajectory was computationally inferred using the continuum of gene expression to connect SSPC, injury-induced fibrogenic cells (IIFC), chondrocyte, and osteoblast, showcasing the bipotentials of periosteal SSPCs during injury repair. Additional computational pipelines were performed to describe the possible gene regulatory network and the expected pathways involved in bone regeneration. Overall, the authors provided valuable insights into the cell state transitions during bone repair and proposed sets of genes with possible involvements in injury response.

While the highlights of the manuscript are the unbiased characterization of periosteal composition, and the trajectory of SSPC response in bone fracture response, many of the conclusions can be more strongly supported with additional clarifications or extensions of the analysis.

1. As described in the method section, both the steady-state data and full dataset underwent integration before dimensional reduction and clustering. It would be appreciated if the authors could compare the post-integration landscapes of uninjured cells between steady state and full dataset analysis. Specifically, fibroblasts were shown in Figure 1C and 1E, and such annotations did not exist in Figure 2B. Will it be possible that the original 'fibroblasts' were part of the IIFC population?

2. According to Figure 2, immune cells were taking a significant abundance within the dataset, specifically during days 3 & 5 post-fracture. It will be interesting to see the potential roles that immune cells play during bone repair. For example, what are the biological annotations of the immune clusters (B, T, NK, myeloid cells)? Are there any inflammatory genes or related signals unregulated in these immune cells? Do they interact with SSPC or IIFC during the transition?

3. The conclusion of Notch and Wnt signaling in IIFC transition was not sufficiently supported by the analysis presented in the manuscript, which was based on computational inferences. It will be great to add in references supporting these claims or provide experimental validations examining selected members of these pathways.

Reviewer #1 (Public Review):

In this manuscript Rubin and Aso provide important new tools for the study of learning and memory in Drosophila. In flies, olfactory learning and memory occurs at the Mushroom Body (MB) and is communicated to the rest of the brain through Mushroom Body Output Neurons (MBONs). Previously, typical MBONs were thoroughly studied. Here, atypical MBONs that have dendritic input both within the MB lobes and in adjacent brain regions are studied. The authors describe new cell-type-specific GAL4 drivers for the majority of atypical MBONs (and other MBONs) and using an optogenetic activation screen they examined their ability to drive behaviors and learning.

The experiments in this manuscript were carefully performed and the results are clear. The tools provided in this manuscript are of great importance to the field.

Reviewer #2 (Public Review):

In this study, Aso and Rubin generated new split-GAL4 lines to label Drosophila mushroom body output neurons (MBONs) that previously lacked specific GAL4 drivers. The MBONs represent the output channels for the mushroom body (MB), a computational center in the fly brain. Prior research identified 21 types of typical MBONs whose dendrites exclusively innervate the MB and 14 types of atypical MBONs whose dendrites also innervate brain regions outside the MB. These MBONs transmit information from the MB to other brain areas and form recurrent connections to dopaminergic neurons whose axonal terminals innervate the MB. Investigating the functions of the MBONs is crucial to understanding how the MB processes information and regulates behavior. The authors previously established a collection of split-GAL4 lines for most of the typical MBONs and one atypical MBON. That split-GAL4 collection has been an invaluable tool for researchers studying the MB. This work extends their previous effort by generating additional driver lines labeling the MBON types not covered by the previous split-GAL4 collection. Using these new driver lines, the authors also activated the labeled MBONs using optogenetics and assessed their role in learning, locomotion, and valence coding. The expression patterns of the new split-GAL4 lines and the behavioral analysis presented in this manuscript are convincing. I believe that these new lines will be a valuable resource for the fly community.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript "Drosophila Visuomotor Integration: An Integrative Model and Behavioral Evidence of Visual Efference Copy" provides an integrative model of the visuomotor control in Drosophila melanogaster. This model presents an experimentally derived model based on visually evoked wingbeat pattern recordings of three strategically selected visual stimulus types with well-established behavioral response characteristics. By testing variations of these models, the authors demonstrate that the virtual model behavior can recapitulate the recorded wing beat behavioral results and those recorded by others for these specific stimuli when presented individually. Yet, the novelty of this study and their model is that it allows predictions for natural visual scenes in which multiple visual stimuli occur simultaneously and may have opposite or enhancing effects on behavior. Testing three models that would allow interactions of these visual modalities, the authors show that using a visual efference copy signal allows visual streams to interact, replicating behavior recorded when multiple stimuli are presented simultaneously. Importantly, they validated the prediction of this model in real flies using magnetically tethered flies, e.g., presenting moving bars with varying backgrounds. In conclusion, the presented manuscript presents a commendable effort in developing and demonstrating the validity of a mixture model that allows predictions of the behavior of Drosophila in natural visual environments.

Strengths:<br /> Overall, the manuscript is well-structured and clear in its presentation, and the modeling and experimental research are methodically conducted and illustrated in visually appealing and easy-to-understand figures and their captions.

The manuscript employs a thorough, logical approach, combining computational modeling with experimental behavioral validation using magnetically tethered flies. This iterative integration of simulation and empirical behavioral evidence enhances the credibility of the findings.

The associated code base is well documented and readily produces all figures in the document.

Suggestions:<br /> However, while the experiments provide evidence for the use of a visual efference copy, the manuscript would be even more impressive if it presented specific predictions for the neural implementation or even neurophysiological data to support this model. Or, at the very least, a thorough discussion. Nonetheless, these models and validating behavioral experiments make this a valuable contribution to the field; it is well executed and addresses a significant gap in the modeling of fly behavior and holistic understanding of visuomotor behaviors.

Here are a few points that should be addressed:<br /> 1. The biomechanics block (Figure 2) should be elaborated on, to explain its relevance to behavior and relation to the underlying neural mechanisms.<br /> 2. It is unclear how the three integrative models with different strategies were chosen or what relevance they have to neural implementation. This should be explained and/or addressed.<br /> 3. There should be a discussion of how the visual efference could be represented in the biological model and an evaluation of the plausibility and alternatives.

Reviewer #2 (Public Review):

It has been widely proposed that the neural circuit uses a copy of motor command, an efference copy, to cancel out self-generated sensory stimuli so that intended movement is not disturbed by the reafferent sensory inputs. However, how quantitatively such an efference copy suppresses sensory inputs is unknown. Here, Canelo et al. tried to demonstrate that an efference copy operates in an all-or-none manner and that its amplitude is independent of the amplitude of the sensory signal to be suppressed. Understanding the nature of such an efference copy is important because animals generally move during sensory processing, and the movement would devastatingly distort that without a proper correction. The manuscript is concise and written very clearly. However, experiments do not directly demonstrate if the animal indeed uses an efference copy in the presented visual paradigms and if such a signal is indeed non-scaled. As it is, it is not clear if the suppression of behavioral response to the visual background is due to the act of an efference copy (a copy of motor command) or due to an alternative, more global inhibitory mechanism, such as feedforward inhibition at the sensory level or attentional modulation. To directly uncover the nature of an efference copy, physiological experiments are necessary. If that is technically challenging, it requires finding a behavioral signature that unambiguously reports a (copy of) motor command and quantifying the nature of that behavior.

Reviewer #3 (Public Review):

Summary:<br /> Canelo et al. used a combination of mathematical modeling and behavioral experiments to ask whether flies use an all-or-none EC model or a graded EC model (in which the turn amplitude is modulated by wide-field optic flow). Particularly, the authors focus on the bar-ground discrimination problem, which has received significant attention in flies over the last 50-60 years. First, they use a model by Poggio and Reichardt to model flight response to moving small-field bars and spots and wide-field gratings. They then simulate this model and compare simulation results to flight responses in a yaw-free tether and find generally good agreement. They then ask how flies may do bar-background discrimination (i.e. complex visual environment) and invoke different EC models and an additive model (balancing torque production due to background and bar movement). Using behavioral experiments and simulation supports the notion that flies use an all-or-none EC since flight turns are not influenced by the background optic flow. While the study is interesting, there are major issues with the conceptual framework.

Strengths:<br /> - They ask a significant question related to efference copies during volitional movement.<br /> - The methods are well detailed and the data (and statistics) are presented clearly.<br /> - The integration of behavioral experiments and mathematical modeling of flight behavior.<br /> - The figures are overall very clear and salient.

Weaknesses:<br /> - Omission of saccades: While the authors ask a significant question related to the mechanism of bar-ground discrimination, they fail to integrate an essential component of the Drosophila visuomotor responses: saccades. Indeed, the Poggio and Reichardt model, which was developed almost 50 years ago, while appropriate to study body-fixed flight, has a severe limitation: it does not consider saccades. The authors identify this major issue in the Discussion by citing a recent switched, integrate-and-fire model (Mongeau & Frye, 2017). The authors admit that they "approximated" this model as a smooth pursuit movement. However, I disagree that it is an approximation; rather it is an omission of a motor program that is critical for volitional visuomotor behavior. Indeed, saccades are the main strategy by which Drosophila turn in free flight and prior to landing on an object (i.e. akin to a bar), as reported by the Dickinson group (Censi et al., van Breugel & Dickinson [not cited]). Flies appear to solve the bar-ground discrimination problem by switching between smooth movement and saccades (Mongeau & Frye, 2017; Mongeau et al., 2019 [not cited]). Thus, ignoring saccades is a major issue with the current study as it makes their model disconnected from flight behavior, which has been studied in a more natural context since the work of Poggio.

Critically, recent work showed that a group of columnar neurons (T3) appear specialized for saccadic bar tracking through integrate-and-fire computations, supporting the notion of parallel visual circuits for saccades and smooth movement (Frighetto & Frye, 2023 [not cited]).

A major theme of this work is bar fixation, yet recent work showed that in the presence of proprioceptive feedback, flies do not actually center a bar (Rimniceanu & Frye, 2023). Furthermore, the same study found that yaw-free flies do not smoothly track bars but instead generate saccades. Thus prior work is in direct conflict with the work here. This is a major issue that requires more engagement by the authors.

- Relevance of the EC model: EC-related studies by the authors linked cancellation signals to saccades (Kim et al, 2014 & 2017). Puzzlingly, the authors applied an EC model to smooth movement, when the authors' own work showed that smooth course stabilizing flight turns do not receive cancellation signals (Fenk et al., 2021). Thus, in Fig. 4C, based on the state of the field, the efference copy signal should originate from the torque commands to initiate saccades, and not from torque to generate smooth movement. As this group previously showed, cancellation signals are quantitatively tuned to that of the expected visual input during saccades. Importantly, this tuning would be to the anticipated saccadic turn optic flow. Thus the authors' results supporting an all-or-none model appear in direct conflict with the author's previous work. Further, the addition-only model is not particularly helpful as it has been already refuted by behavioral experiments (Rimneceanu & Frye, Mongeau & Frye).

- Behavioral evidence for all-or-none EC model: The authors state "unless the stability reflex is suppressed during the flies' object evoked turns, the turns should slow down more strongly with the dense background than the sparse one". This hypothesis is based on the fact that the optomotor response magnitude is larger with a denser background, as would be predicted by an EMD model (because there are more pixels projected onto the eye). However, based on the authors' previous work, the EC should be tuned to optic flow and thus the turning velocity (or amplitude). Thus the EC need not be directly tied to the background statistics, as they claim. For instance, I think it would be important to distinguish whether a mismatch in reafferent velocity (optic flow) links to distinct turn velocities (and thus position). This would require moving the background at different velocities (co- and anti-directionally) at the onset of bar motion. Overall, there are alternative hypotheses here that need to be discussed and more fully explored (as presented by Bender & Dickinson and in work by the Maimon group).

Reviewer #1 (Public Review):

The proposed study provides an innovative framework for the identification of muscle synergies taking into account their task relevance. State-of-the-art techniques for extracting muscle interactions use unsupervised machine-learning algorithms applied to the envelopes of the electromyographic signals without taking into account the information related to the task being performed. In this work, the authors suggest to include the task parameters in extracting muscle synergies using a network information framework previously proposed. This allows the identification of muscle interactions that are relevant, irrelevant, or redundant to the parameters of the task executed.

The proposed framework is a powerful tool to understand and identify muscle interactions for specific task parameters and it may be used to improve man-machine interfaces for the control of prostheses and robotic exoskeletons.

With respect to the network information framework recently published, this work added an important part to estimate the relevance of specific muscle interactions to the parameters of the task executed.

It is not clear how the well-known phenomenon of cross-talk during the recording of electromyographic muscle activity may affect the performance of the proposed technique and how it may bias the overall outcomes of the framework.

Reviewer #2 (Public Review):

This paper is an attempt to extend or augment muscle synergy and motor primitive analyses and ideas with addition of task-driven measures. The authors' idea is to use information metrics (mutual information, co-information) in 'synergy' constraint creation that includes task information directly. By using task related information and muscle information sources and then sparsification, the methods construct task relevant network communities among muscles, together with task redundant communities, and task irrelevant communities. This process of creating network communities may then constrain and help to guide subsequent synergy identification using the authors published sNM3F algorithm to detect spatial and temporal synergies. The revised paper is now much clearer and examples are helpful in various ways.

The impact of the information theoretic constraints developed as network communities on subsequent synergy separation are posited to be benign and to improve separation and identification of synergies over other methods (e.g., NNMF). However, not fully addressed are the possible impacts of the methods on the resulting compositionality and its links with physiological bases: the possibility remains that the methods here sometimes will instead lead to modules that represent more descriptive ML frameworks for task description, and resulting 'synergies' that may not support physiological work easily. Accordingly, there is a caveat for users of this framework. This is recognized and acknowledged by the authors in their rebuttal letters responding to prior reviews. It will remain for other work to explore this issue, likely through testing on detailed high degree of freedom artificial neuromechanical models and tasks. This possible issue and caveat with the strategy proposed by the authors likely should be more fully acknowledged in the paper.

The approach of the methods seeks to identify task relevant coordinative couplings. This identification is a meta problem for more classical synergy analyses. Classical/prior analyses seek compositional elements stable across tasks. These elements may then be explored in causal experiments and in generative simulations of coupling and control strategies. However, task-based understanding of synergy roles and functional uses as captured in the proposed methods are significant, and the field is clearly likely to be aided by methods in this study.<br /> Information based separation has been used in muscle synergy analyses previously, by using infomax ICA, to discover physiological primitives. Though linear mixing of sources is assumed in ICA, minimized mutual information among source (synergy) drives is the basis of the separation and can detect low variance synergy contributions (e.g., see Yang, Logan, Giszter, 2019). In the work in the current paper, instead, mutual information approaches are used to cluster muscles and task features into network communities preceding the SNM3F algorithm use for separation, rather than using minimized information in the separation process directly. This contrast of an accretive or agglomerative mutual information strategy in the paper here, which is used to cluster into networks, versus a minimizing mutual information source separation used in infomax ICA epitomizes a key difference in approach. Indeed, physiological causal testing of synergy ideas is neglected in the literature reviews presented in the paper. Although these are only in animal work (e.g., Hart and Giszter, 2010; Takei and Seki, 2017), the clear connection of muscle synergy analysis choices to physiology is important, and eventually these issues need to be better managed and understood in relation to the new methods proposed here, even if not in this paper. Analyses of synergies using the methods the paper has proposed will likely be very much dependent on the number and quality of task variables included and how these are chosen, and the impacts of these on the ensuing sparsification and network communities used prior to SNM3F has already been noted. The authors acknowledge this in their responses. It would be useful in the future to explore the approach described with a range of simulated data to better understand the caveats, and optimizations for best practices in applications of this approach.

A key component of the authors' arguments here is their 'emergentist' view presented in the work, but perhaps not made fully explicit. Through the reductionist lens, which was used in the other physiological work noted above, muscle groupings are the units (primitives or 'building blocks' with informational separations) of coordinated movement and thus the space of these intermuscular unit interactions and controls is of particular interest for understanding movement construction and underlying physiology. This may allow representation of a hierarchy or heterarchy of neural control elements with clear physiological bases at spinal, brainstem and cortical levels. On the other hand, the emergentist view utilized by the authors here suggests that muscle groupings emerge from interactions between many constituent parts in a more freeform fashion with potentially larger task synergy assemblies (also quantified here using information tools). Information methods are applied differently using the two different lenses. The emergentist lens may potentially obscure fundamental neural controls and make them harder to explore in the descriptions resulting. Nonetheless, the different approaches to muscle synergy research, seeking different sorts of explanation and description of 'synergy', can be complementary and beneficial for the field overall going forward, so long as the caveats and concerns noted here are employed by readers in the interpretation of this new method.

Reviewer #3 (Public Review):

In this study, the authors developed and tested a novel framework for extracting muscle synergies. The approach aims at removing some limitations and constrains typical of previous approaches used in the field. In particular, the authors propose a mathematical formulation that removes constrains of linearity and couple the synergies to their motor outcome, supporting the concept of functional synergies and distinguishing the task-related performance related to each synergy. While some concepts behind this work were already introduced in recent work in the field, the methodology provided here encapsulates all these features in an original formulation providing a step forward with respect to the currently available algorithms. The authors also successfully demonstrated the applicability of their method to previously available datasets of multi-joint movements.

Preliminary results positively support the scientific soundness of the presented approach and its potential. The added values of the method should be documented more in future work to understand how the presented formulation relates to previous approaches and what novel insights can be achieved in practical scenarios and confirm/exploit the potential of the theoretical findings.

Reviewer #1 (Public Review):

Gap junction channels establish gated intercellular conduits that allow the diffusion of solutes between two cells. Hexameric connexin26 (Cx26) hemichannels are closed under basal conditions and open in response to CO2. In contrast, when forming a dodecameric gap-junction, channels are open under basal conditions and close with increased CO2 levels. Previous experiments have implicated Cx26 residue K125 in the gating mechanism by CO2, which is thought to become carbamylated by CO2. Carbamylation is a labile post-translational modification that confers negative charge to the K125 side chain. How the introduction of a negative charge at K125 causes a change in gating is unclear, but it has been proposed that carbamylated K125 forms a salt bridge with the side chain at R104, causing a conformational change in the channel. It is also unclear how overall gating is controlled by changes in CO2, since there is significant variability between structures of gap-junction channels and the cytoplasmic domain is generally poorly resolved. Structures of WT Cx26 gap-junction channels determined in the presence of various concentrations of CO2 have suggested that the cytoplasmatic N-terminus changes conformation depending on the concentration of the gas, occluding the pore when CO2 levels are high.

In the present manuscript, Deborah H. Brotherton and collaborators use an intercellular dye-transfer assay to show that Cx26 gap-junction channels containing the K125E mutation, which mimics carbamylation caused by CO2, is constitutively closed even at CO2 concentrations where WT channels are open. Several cryo-EM structures of WT and mutant Cx26 gap junction channels were determined at various conditions and using classification procedures that extracted more than one structural class from some of the datasets. Together, the features on each of the different structures are generally consistent with previously obtained structures at different CO2 concentrations and support the mechanism that is proposed in the manuscript. The most populated class for K125E channels determined at high CO2 shows a pore that is constricted by the N-terminus, and a cytoplasmic region that was better resolved than in WT channels, suggesting increased stability. The K125E structure closely resembles one of the two major classes obtained for WT channels at high CO2. These findings support the hypothesis that the K125E mutation biases channels towards the closed state, while WT channels are in an equilibrium between open and closed states even in the presence of high CO2. Consistently, a structure of K125E obtained in the absence of CO2 appeared to also represent a closed state but at lower resolution, suggesting that CO2 has other effects on the channel beyond carbamylation of K125 that also contribute to stabilizing the closed state. Structures determined for K125R channels, which are constitutively open because arginine cannot be carbamylated, and would be predicted to represent open states, yielded apparently inconclusive results.

A non-protein density was found to be trapped inside the pore in all structures obtained using both DDM and LMNG detergents, suggesting that the density represents a lipid rather than a detergent molecule. It is thought that the lipid could contribute to the process of gating, but this remains speculative. The cytoplasmic region in the tentatively closed structural class of the WT channel obtained using LMNG was better resolved. An additional portion of the cytoplasmic face could be resolved by focusing classification on a single subunit, which had a conformation that resembled the AlphaFold prediction. However, this single-subunit conformation was incompatible with a C6-symmetric arrangement. Together, the results suggest that the identified states of the channel represent open states and closed states resulting from interaction with CO2. Therefore, the observed conformational changes illuminate a possible structural mechanism for channel gating in response to CO2.

Some of the discussion involving comparisons with structures of other gap junction channels are relatively hard to follow as currently written, especially for a general readership. Also, no additional functional experiments are carried out to test any of the hypotheses arising from the data. However, structures were determined in multiple conditions, with results that were consistent with the main hypothesis of the manuscript. No discussion is provided, even if speculative, to explain the difference in behavior between hemichannels and gap junction channels. Also, no attempt was made to measure the dimensions of the pore, which is relevant because of the importance of identifying if the structures indeed represent open or closed states of the channel.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Brotherton et al. describes a structural study of connexin-26 (Cx26) gap junction channel mutant K125E, which is designed to mimic the CO2-inhibited form of the channel. In the wild-type Cx26, exposure to CO2 is presumed to close the channel through carbamylation of the residue K125. The authors mutated K125 to a negatively charged residue to mimic this effect, and they observed by cryo-EM analysis of the mutated channel that the pore of the channel is constricted. The authors were able to observe conformations of the channel with resolved density for the cytoplasmic loop (in which K125 is located). Based on the observed conformations and on the position of the N-terminal helix, which is involved in channel gating and in controlling the size of the pore, the authors propose the mechanisms of Cx26 regulation.

Strengths:<br /> This is a very interesting and timely study, and the observations provide a lot of new information on connexin channel regulation. The authors use the state of the art cryo-EM analysis and 3D classification approaches to tease out the conformations of the channel that can be interpreted as "inhibited", with important implications for our understanding of how the conformations of the connexin channels controlled.

Weaknesses:<br /> My fundamental question to the premise of this study is: to what extent can K125 carbamylation by recapitulated by a simple K125E mutation? Lysine has a large side chain, and its carbamylation would make it even slightly larger. While the authors make a compelling case for E125-induced conformational changes focusing primarily on the negative charge, I wonder whether they considered the extent to which their observation with this mutant may translate to the carbamoylated lysine in the wild-type Cx26, considering not only the charge but also the size of the modified side-chain.

Reviewer #3 (Public Review):

Summary:<br /> The mechanism underlying the well-documented CO2-regulated activity of connexin 26 (Cx26) remains poorly understood. This is largely due to the labile nature of CO2-mediated carbamylation, making it challenging to visualize the effects of this reversible posttranslational modification. This paper by Brotherton et al. aims to address this gap by providing structural insights through cryo-EM structures of a carbamylation-mimetic mutant of the gap junction protein.

Strengths:<br /> The combination of the mutation, elevated PCO2, and the use of LMNG detergent resulted in high-resolution maps that revealed, for the first time, the structure of the cytoplasmic loop between transmembrane helix (TM) 2 and 3.

Weaknesses:<br /> The presented maps merely reinforce their previous findings, wherein wildtype Cx26 favored a closed conformation in the presence of high PCO2. While the structure of the TM2-TM3 loop may suggest a mechanism for stabilizing the closed conformation, no experimental data was provided to support this mechanism. Additionally, the cryo-EM maps were not effectively presented, making it difficult for readers to grasp the message.

Reviewer #1 (Public Review):

Summary:<br /> This study identifies a family of solute transports in the enteric protist, Blastocystis, that may mediate the transport of glycolytic intermediates across the mitochondrial membrane. The study builds on previous observations suggesting that Blastocystis (and other Stramenopiles) are unusual in having a compartmentalized glycolytic pathway with enzymes involved in upper and lower glycolysis being located in the cytosol and mitochondria, respectively. In this study, the authors identified two putative Stamenopile metabolite transporters that are related to plant di/tricarboxylic acid transporters that might mediate the transport of glycolytic intermediates across the mitochondrial membrane. These GIC-transporters were localized to the Blastocystis mitochondrion using specific rabbit antibodies and shown to bind several glycolytic intermediates (including GAP, DHAP, and PEP) based on thermostability shift assays. Direct evidence for transport activity was obtained by reconstituting native proteins in proteoliposomes and measuring the uptake of 14C-malate or 35S-sulphate against unlabelled substrates. This assay showed that GIC-2 transported DHAP, GAP, and PEP. However, significant transport activity was not observed for bGIC-2. Overall, the study provides strong, but not conclusive evidence that bGIC-1 is involved in transporting glycolytic intermediates across the inner membrane of the mitochondria, while the function of GIC-2 remains unclear, despite exhibiting the same metabolite binding properties as bGIC-2 in thermostability assays.

Strengths:<br /> Overall, the findings are of interest in the context of understanding the diversity of core metabolic pathways in evolutionarily diverse eukaryotes, as well as the process by which cytosolic glycolysis evolved in most eukaryotes. The experiments are carefully performed and clearly described.

Weaknesses:<br /> The main weakness of the study is the lack of direct evidence that either bGIC-1 and/or bGIC2 are active in vivo. While it is appreciated that the genetic tools for disrupting GIC genes in Blastocystis are limited/lacking, are there opportunities to ectopically express or delete these genes in other Stamenopiles, such as Phaeodactylum triconuteum, to demonstrate function in vivo?

The authors demonstrate that both bGIC-1 and bGIC-2 are targeted to the mitochondrion, based on immunofluorescence studies. However, the precise localization and topology of these carriers in the inner or outer membrane are not defined. The conclusions of the study would be strengthened if the authors could show that one/both transporters are present in the inner membrane using protease protection experiments following differential solubilization of the outer and inner mitochondrial membranes.

It is not clear why hetero-exchange reactions were not performed for bGIC-1 (only for bGIC-2).

The summary slide depicted in Fig 7 is somewhat simplified and inaccurate. First, the authors show that TPI is located in the mitochondria in this study, while in the summary figure, TPI is shown to be present in both the cytosol and mitochondrial matrix. A cytosolic localization for TPI provides a functional rationale for having a triose-P carrier in the inner membrane - however, this is not supported by the data shown here. Second, if bGIC1/2 uses PEP as a counter ion to import GA3P and DHAP into the mitochondrion, as proposed in Fig 7, the lower glycolytic pathway would be effectively truncated at PEP, removing substrate for pyruvate kinase and formation of pyruvate/ATP. Third, the authors suggest that DHAP may have other functions in the mitochondria although these are not shown in the figure.

Reviewer #2 (Public Review):

In this manuscript, the authors set out to identify transporters that must exist in Stramenophiles due to the fact that the second half of glycolysis appears to be conducted in the mitochondria. They hypothesize that a Stramenophile-specific clade of transporters related to the dicarboxylate carriers is likely the relevant family and then go on to test two proteins from Blastocystis due to the infectious disease relevance of this organism. They show rather convincingly that these two proteins are expressed and are localized to the mitochondria in the native organism. The purified proteins bind to glycolytic intermediates and one of them, GIC-2, transports several glycolytic intermediates in vitro. This is a very solid and well-executed study that clearly demonstrates that bCIC-2 can transport glycolytic intermediates.

1. The major weakness is that the authors aren't able to show that this protein actually has this function in the native organism. This could be impossible due to the lack of genetic tools in Blastocystis, but it leaves us without absolute confidence that bGIC-2 is the important glycolytic intermediate mitochondrial transporter (or even that it has this function in vivo).

2. It's atypical that the figures and figure panels don't really follow the order of their citation in the text. It's not a big deal, but mildly annoying to have to skip around in the figures (e.g. Figure 3D-E are described in the same paragraph as Figure 5). In addition, to facilitate the flow and a proper understanding I would encourage a reordering between figures 5D and 6 since Figure 6 is needed to understand the results shown in panel 5D, which may lead to confusion.

3. My impression is that the authors under-emphasize the fact that the hDIC also binds (and is stabilized by) glycolytic intermediates (G3P and 3PG). In the opinion of this reviewer, this might change the interpretation about the uniqueness of the bGIC proteins. They act on additional glycolytic intermediates, but it's not unique.

Reviewer #3 (Public Review):

Summary:<br /> Unlike most eukaryotes, Blastocystis has a branched glycolysis pathway, which is split between the cytoplasm and the mitochondrial matrix. An outstanding question was how the glycolytic intermediates generated in the 'preparatory' phase' are transported into the mitochondrial matrix for the 'pay off' phase. Here, the authors use bioinformatic analysis to identify two candidate solute carrier genes, bGIC-1, and bGIC-2, and use biochemical and biophysical methods to characterise their substrate specificity and transport properties. The authors demonstrate that bGIC-2 can transport dihydroxyacetone phosphate, glyceraldehyde-3-phosphate, 3-phosphoglycerate, and phosphoenolpyruvate, establishing this protein as the 'missing link' connecting the two split branches of glycolysis in this branch of single-celled eukaryotes. The authors also present their data on bGIC-1, which suggests a role in anion transport and bOGC, which is a close functional homologue of the human oxoglutarate carrier (hOGC, SLC25A11) and human dicarboxylate carrier (hDIC, SLC25A10).

Strengths:<br /> The results are presented in a clear and logical arrangement, which nicely leads the reader through the process of gene identification and subsequent ligand screening and functional reconstitution. The results are compelling and well supported - the thermal stabilisation data is supported by the exchange studies. Caveats, where apparent, are discussed and rational explanations are given.

Weaknesses:<br /> The study does not contain any significant weaknesses in my view. I would like to see the authors include the initial rate plots used in the main figures (possibly as insets), so we can observe the data points used for these calculations. It would also have been interesting to include the AlphaFold models for bGIC-1 and bGIC-2 and a discussion/rationalisation for the substrate specificity discussed in the study.

Reviewer #1 (Public Review):

Summary:<br /> In this study, Yan et al. investigate the molecular bases underlying mating type recognition in Tetrahymena thermophila. This model protist possesses a total of 7 mating types/sexes and mating occurs only between individuals expressing different mating types. The authors aimed to characterize the function of mating type proteins (MTA and MTB) in the process of self- and non-self recognition, using a combination of elegant phenotypic assays, protein studies, and imaging. They showed that the presence of MTA and MTB in the same cell is required for the expression of concavalin-A receptors and for tip transformation - two processes that are characteristic of the costimulation phase that precedes cell fusion. Using protein studies, the authors identify a set of additional proteins of varied functions that interact with MTA and MTB and are likely responsible for the downstream signaling processes required for mating. This is a description of a fascinating self- and non-self-recognition system and, as the authors point out, it is a rare example of a system with numerous mating types/sexes. This work opens the door for the further understanding of the molecular bases and evolution of these complex recognition systems within and outside protists.

The results shown in this study point to the unequivocal requirement of MTA and MTB proteins for mating. Nevertheless, some of the conclusions regarding the mode of functioning of these proteins are not fully supported and require additional investigation.

Strengths:<br /> 1. The authors have established a set of very useful knock-out and reporter lines for MT proteins and extensively used them in sophisticated and well-designed phenotypic assays that allowed them to test the role of these proteins in vivo.

2. Despite their apparent low abundance, the authors took advantage of a varied set of protein isolation and characterization techniques to pinpoint the localization of MT proteins to the cell membrane, and their interaction with multiple other proteins that could be downstream effectors. This opens the door for the future characterization of these proteins and further elucidation of the mating type recognition cascade.

Weaknesses:<br /> The manuscript is structured and written in a very clear and easy-to-follow manner. However, several conclusions and discussion points fall short of highlighting possible models and mechanisms through which MT proteins control mating type recognition:

1. The authors dismiss the possibility of a "simple receptor-ligand system", even though the data does not exclude this possibility. The model presented in Figure 2 S1, and on which the authors based their hypothesis, assumes the independence of MTA and MTB proteins in the generation of the intracellular cascade. However, the results presented in Figure 2 show that both proteins are required to be active in the same cell. Coupled with the fact that MTA and MTB proteins interact, this is compatible with a model where MTA would be a ligand and MTB a receptor (or vice-versa), and could thus form a receptor-ligand complex that could potentially be activated by a non-cognate MTA-MTB receptor-ligand complex, leading to an intracellular cascade mediated by the identified MRC proteins. As it stands, it is not clear what is the proposed working model, and it would be very beneficial for the reader for this to be clarified by having the point of view of the authors on this or other types of models.

2. The presence of MTA/MTB proteins is required for costimulation (Figure 2), and supplementation with non-cognate extracellular fragments of these proteins (MTAxc, or MTBxc) is a positive stimulator of pairing. However, alone, these fragments do not have the ability to induce costimulation (Figure 5). Based on the results in Figures 5 and 6 the authors suggest that MT proteins mediate both self and non-self recognition. Why do MTAxc and MTBxc not induce costimulation alone? Are any other components required? How to reconcile this with the results of Figure 2? A more in-depth interpretation of these results would be very helpful, since these questions remain unanswered, making it difficult for the reader to extract a clear hypothesis on how MT proteins mediate self- and non-self-recognition.

Reviewer #2 (Public Review):

This manuscript reports the discovery and analysis of a large protein complex that controls mating type and sexual reproduction of the model ciliate Tetrahymena thermophila. In contrast to many organisms that have two mating types or two sexes, Tetrahymena is multi-sexual with 7 distinct mating types. Previous studies identified the mating type locus, which encodes two transmembrane proteins called MTA and MTB that determine the specificity of mating type interactions. In this study, mutants are generated in the MTA and MTB genes and mutant isolates are studied for mating properties. Cells missing either MTA or MTB failed to co-stimulate wild-type cells of different mating types. Moreover, a mixture of mutants lacking MTA or MTB also failed to stimulate. These observations support the conclusion that MTA and MTB may form a complex that directs mating-type identity. To address this, the proteins were epitope-tagged and subjected to IP-MS analysis. This revealed that MTA and MTB are in a physical complex, and also revealed a series of 6 other proteins (MRC1-6) that together with MTA/B form the mating type recognition complex (MTRC). All 8 proteins feature predicted transmembrane domains, three feature GFR domains, and two are predicted to function as calcium transporters. The authors went on to demonstrate that components of the MTRC are localized on the cell surface but not in the cilia. They also presented findings that support the conclusion that the mating type-specific region of the MTA and MTB genes can influence both self- and non-self-recognition in mating.

Taken together, the findings presented are interesting and extend our understanding of how organisms with more than two mating types/sexes may be specified. The identification of the six-protein MRC complex is quite intriguing. It would seem important that the function of at least one of these subunits be analyzed by gene deletion and phenotyping, similar to the findings presented here for the MTA and MTB mutants. A straightforward prediction might be that a deletion of any subunit of the MRC complex would result in a sterile phenotype. The manuscript was very well written and a pleasure to read.

Reviewer #3 (Public Review):

The authors describe the role, location, and function of the MTA and MTB mating type genes in the multi-mating-type species T. thermophila. The ciliate is an important group of organisms to study the evolution of mating types, as it is one of the few groups in which more than two mating types evolved independently. In the study, the authors use deletion strains of the species to show that both mating types genes located in each allele are required in both mating individuals for successful matings to occur. They show that the proteins are localized in the cell membrane, not the cilia, and that they interact in a complex (MTRC) with a set of 6 associated (non-mating type-allelic) genes. This complex is furthermore likely to interact with a cyclin-dependent kinase complex. It is intriguing that T. thermophila has two genes that are allelic and that are both required for successful mating. This coevolved double recognition has to my knowledge not been described for any other mating-type recognition system. I am not familiar with experimental research on ciliates, but as far as I can judge, the experiments appear well performed and mostly support the interpretation of the authors with appropriate controls and statistical analyses.

The results show clearly that the mating type genes regulate non-self-recognition, however, I am not convinced that self-recognition occurs leading to the suppression of mating. An alternative explanation could be that the MTA and MTB proteins form a complex and that the two extracellular regions together interact with the MTA+MTB proteins from different mating types. This alternative hypothesis fits with the coevolution of MTA and MTB genes observed in the phylogenetic subgroups as described by Yan et al. (2021 iScience). Adding MTAxc and/or MTBxc to the cells can lead to the occupation of the external parts of the full proteins thereby inhibiting the formation of the complex, which in turn reduces non-self interactions. Self-recognition as explained in Figure 2S1 suggests an active response, which should be measurable in expression data for example. This is in my opinion not essential, but a claim of self-recognition through the MTA and MTB should not be made.

The authors discuss that T. thermophila has special mating-type proteins that are large, while those of other groups are generally small (lines 157-160 and discussion). The complex formed is very large and in the discussion, they argue that this might be due to the "highly complex process, given that there are seven mating types in all". There is no argument given why large is more complex, if this is complex, and whether more mating types require more complexity. In basidiomycete fungi, many more mating types than 7 exist, and the homeodomain genes involved in mating types are relatively small but highly diverse (Luo et al. 1994 PMID: 7914671). The mating types associated with GPCR receptors in fungi are arguably larger, but again their function is not that complex, and mating-type specific variations appear to evolve easily (Fowler et al 2004 PMID: 14643262; Seike et al. 2015 PMID: 25831518). The large protein complex formed is reminiscent of the fusion patches that develop in budding or fission yeasts. In these species, the mating type receptors are activated by ligand pheromones from the opposite mating type that induce polarity patch formation (see Sieber et al. 2023 PMID: 35148940 for a recent review). At these patches, growth (shmooing) and fusion occur, which is reminiscent (in a different order) of the tip transformation in T. thermophilia. The fusion of two cells is in all taxa a dangerous and complex event that requires the evolution of very strict regulation and the existence of a system like the MTRC and cyclin-dependent complex to regulate this process is therefore not unexpected. The existence of multiple mating types should not greatly complicate the process, as most of the machinery (except for the MTA and MTB) is identical among all mating types.

The Tetrahymena/ciliate genetics and lifecycle could be better explained. For a general audience, the system is not easy to follow. For example, the ploidy of the somatic nucleus with regards to the mating type is not clear to me. The MAC is generally considered "polyploid", but how does this work for the mating type? I assume only a single copy of the mating type locus is available in the MAC to avoid self-recognition in the cells. Is it known how the diploid origin reduces to a single mating type? This does not become apparent from Cervantes et al. 2013. Also, the explanation of co-stimulation is not completely clear (lines 49-60). Initially, direct cell-cell contact is mentioned, but later it is mentioned that "all cells become fully stimulated", even when unequal ratios are used. Is physical contact necessary? Or is this due to the "secrete mating-essential factors" (line 601)? These details are essential, for interpretation of the results and need to be explained better.

Abstract and introduction: Sexes are not mating types. In general, mating types refer to systems in which there is no obvious asymmetry between the gametes, beyond the compatibility system. When there is a physiological difference such as size or motility, sexes are used. This distinction is of importance because in many species mating types and sexes can occur together, with each sex being able to have either (when two) or multiple mating types. An example are SI in angiosperms as used as an example by the authors or mating types in filamentous fungi. See Billiard et al. 2011 [PMID: 21489122] for a good explanation and argumentation for the importance of making this distinction.

Reviewer #2 (Public Review):

The current manuscript undoubtedly demonstrates that JAG1 can induce osteogenesis via non-canonical signaling. Using the mouse-calvarial critical defect model, the authors have clearly shown the anabolic regenerative effect of JAG1 via non-canonical pathways. Exploring the molecular mechanisms, the authors have shown that non-canonically JAG1 regulates multiple pathways including STAT5, AKT, P38, JNK, NF-ĸB, and p70 S6K, which together possibly culminate in the activation of p70 S6K. More analysis is required to strongly conclude the role of the JAG1-p70 S6K pathway in the process. In summary, these findings have significant implications for designing new approaches for bone regenerative research.

Reviewer #1 (Public Review):

Summary:

In this manuscript, the authors introduced a compelling study that explored an innovative regenerative treatment for pediatric craniofacial bone loss, with a particular focus on investigating the impacts of JAGGED1 (JAG1) signaling.

Strengths:

Building on their prior research involving the effect of JAG1 on murine cranial neural crest cells, the authors demonstrated successful bone regeneration in an in vivo murine bone loss model with a critically-sized cranial defect, where they delivered JAG1 with pediatric human bone-derived osteoblast-like cells in the hydrogel. Additionally, their findings unveiled a crucial mechanism wherein JAG1 induces pediatric osteoblast commitment and bone regeneration through the phosphorylation of p70 S6K. This discovery offers a promising avenue for potential treatment, involving targeted delivery of JAG1 and activation of downstream p70 s6K, for pediatric craniofacial bone loss. Overall, the experimental design is appropriate, and the results are clearly presented.

Weaknesses:

Several methodology details need to be clearly included and gender differences should be evaluated and discussed.

Reviewer #1 (Public Review):

Summary:<br /> Fita-Torró et al. study the toxic effects of the intermediary lipid degradation product trans-2-hexadecenal (t-2-hex) on yeast mitochondria and suggest a mechanism by which Hfd1 safeguards Tom40 from lipidation by t-2-hex and its consequences, such as mitochondrial protein import inhibition, cellular proteostasis deregulation, and stress-responses.<br /> The authors aimed to dissect a mechanism for t-2-hex' apoptotic consequences in yeast and they suggest it is via lipidation of Tom40 but really under the tested conditions everything seems lipidated. Thus, it is unclear whether Tom40 is the crucial causal target. They also do not provide much biochemical experiments to investigate this phenomenon further functionally. Tom40 is one possible and perhaps, given the cellular consequences, a reasonable candidate but not validated beyond in vitro lipidation by exogenous t-2-hex.

Strengths:<br /> The effects of lipids and their metabolic intermediates on protein function are understudied thus the authors' research contributing to elucidating direct effects of a single lipid is appreciated. It is particularly unknown by which mechanism t-2-hex causes cell death in yeast. The authors elegantly use modulation of the levels of enzyme Hfd1 that endogenously catabolizes t-2-hex as an approach to studying t-2-hex stress. Understanding the cause and consequences of this stress is relevant for understanding fundamental regulation mechanisms, and also to human health since the human homolog of Hfd1, ALDH3A2, is mutated in Sjögren-Larsson Syndrome. The application of a variety of global transcriptomic, functional genomic, and chemoproteomic approaches to study t-2-hex stress targets in the yeast model is laudable.

Weaknesses:<br /> - The extent of the contribution of Tom40 lipidation to the general t-2-hex stress phenotype is unclear. Is Tom40 lipidation alone enough to cause the phenotype? An alteration of the cysteine residue in question could help answer this key question.<br /> - It is unclear whether the exogenously applied amounts of t-2-hex (concentrations chosen between 25-200 uM) are physiologically relevant in yeast cells. For comparison, Chipuk et al. (2012) used at most 1 uM on mitochondria of human cells, while Jarugumilli et al. (2018) considered 25 uM a 'lower dose' on human cells. Since the authors saw responses below 10 uM (Fig. 3B) and at the lowest selected concentration of 25 uM (Fig. 8), why were no lower, likely more specific, concentrations applied for the global transcriptomic and chemoproteomic experiments? Key experiments have to be repeated with the lower concentrations.<br /> - The amount of t-2-hex applied is especially important to consider in light of over 1300 proteins lipidated to an extent equal to or greater than Tom40 (Supp. Table 6). This chemoproteomic experiment (Fig. 8B, Supp. Table 6) is also weakened by the inclusion of only 2 replicates, thus precluding assessment of statistical significance. The selection of targets in Fig. 8B as "among the best hits" is neither immediately comprehensible nor further explained and represents at best cherry-picking. Further evidence based on statistical significance or validation by other means should be provided.<br /> - The authors unfortunately also underuse the possible contribution of mass spectrometry technology to in addition determine the extent and localization of lipidation on a global scale (especially relevant since Cohen et al. (2020) suggest site-specific mechanisms).<br /> - The general novelty of studying t-2-hex stress is lowered in light of existing literature in humans (see e. g. Chipuk et al., 2012; Cohen et al., 2020; Jarugumilli et al., 2018), and in yeast by the same authors (Manzanares-Estreder et al., 2017) and as the authors comment themselves, a significant part of the manuscript may represent rather a confirmation of the already described consequences of t-2-hex stress

Reviewer #2 (Public Review):

This study elucidates the toxic effects of the lipid aldehyde trans-2-hexadecenal (t-2-hex). The authors show convincingly that t-2-hex induces a strong transcriptional response, leads to proteotoxic stress, and causes the accumulation of mitochondrial precursor proteins in the cytosol.<br /> The data shown are of high quality and well controlled. The genetic screen for mutants that are hyper-and hypo-sensitive to t-2-hex is elegant and interesting, even if the mechanistic insights from the screen are rather limited. The last part of the study is less convincing. The authors show evidence that t-2-hex affects subunits of the TOM complex. However, they do not formally demonstrate that the lipidation of a TOM subunit is responsible for the toxic effect of t-2-hex. A t-2-hex-resistant TOM mutant was not identified. Moreover, it is not clear whether the concentrations of t-2-hex in this study are physiological. This is, however, a critical aspect. The literature is full of studies claiming the toxic effects of compounds such as H2O2; even if such studies are technically sound, they are misleading if non-physiological concentrations of such compounds were used.<br /> Nevertheless, this is an interesting study of high quality. A few specific aspects should be addressed.

Reviewer #3 (Public Review):

Summary: The authors investigate the effect of the lipid aldehyde trans-2-hexadecenal (t-2-hex) in yeast using multiple omic analyses that show that a large range of cellular functions across all compartments are affected, e.g. transcriptomic changes affect 1/3 of all genes. The authors provide additional analyses, from which they built a model that mitochondrial protein import caused by modification of Tom40 is blocked.

Strengths: Global analyses (transcriptomic and functional genomics approach) to obtain an unbiased overview of changes upon t-2-hex treatment.

Weaknesses: It is not clear why the authors decided to focus on mitochondria, as only 30 genes assigned to the GO term "mitochondria" are increasing, and also the follow-up analyses using SATAY is not showing a predominance for mitochondrial proteins (only 4 genes are identified as hits). The provided additional experimental data do not support the main claims as neither protein import is investigated nor is there experimental evidence that lipidation of Tom40 occurs in vivo and impacts on protein translocation.

Reviewer #1 (Public Review):

Weber et al. investigated the role of human DDX6 in messenger RNA decay using CRISPR/Cas9 mediated knockout (KO) HEK293T cells. The authors showed that stretches of rare codons or codons known to cause ribosome stalling in reporter mRNAs leads to a DDX6 specific loss of mRNA decay. The authors moved on to show that there is a physical interaction between DDX6 and the ribosome. Using co-immunoprecipitation (co-IP) experiments, the authors determined that the FDF-binding surface of DDX6 is necessary for binding to the ribosome, the same domain which is necessary for binding several decapping factors such as EDC3, LSM14A, and PatL. However, they determine the interaction between DDX6, and the ribosome is independent of the DDX6 interaction with the NOT1 subunit of the CCR4-NOT complex. Interestingly, the authors were able to determine that all known functional domains, including the ATPase activity of DDX6, are required for its effect on mRNA decay. Using ribosome profiling and RNA-sequencing, the authors were able to identify a group of 260 mRNAs that exhibit increased translational efficiency (TE) in DDX6 Knockout cells, suggesting that DDX6 translationally represses certain mRNAs. The authors determined this group of mRNAs has decreased GC content, which has been previously noted to coincide with low codon optimality, the authors thus conclude DDX6 may translationally repress transcripts of low codon optimality. Furthermore, the authors identify 35 transcripts that are both upregulated in DDX6 KO cells and exhibit locally increased ribosome footprints (RBFs), suggestive of a ribosome stalling sequence. Lastly, the authors showed that both endogenous and tethering of DDX6 to reporter mRNAs with and without these translational stalling sequences leads to a relative increase in ribosome association to a transcript. Overall, this work confirms that the role of DDX6 in mRNA decay shares several conserved features with the yeast homolog Dhh1. Dhh1 is known to bind slow-moving ribosomes and lead to the differential decay of non-optimal mRNA transcripts (Radhakrishnan et al. 2016). The novelty of this work lies primarily in the identification of the physical interaction between DDX6 and the ribosome and the breakdown of which domains of DDX6 are necessary for this interaction. This work provides major insight into the role of the human DDX6 in the process of mRNA decay and emphasizes the evolutionary conservation of this process across Eukaryotes.<br /> Strengths: Weber et al. take our knowledge of dhh1, the yeast homolog of the human DDX6, and determine several features that are conserved across eukaryotes. The authors take our understanding of DDX6 a step further by identifying the specific domains involved in the interaction between DDX6 and the ribosome. As well as, differentiating those interactions from other factors known to interact with DDX6, such as NOT1. All of this is necessary and important to understand how mRNA decay plays a role in post-transcriptional gene regulation in humans.<br /> Weaknesses: The authors fail to truly define codon optimality, rare codons, and stalling sequences in their work, all of which are distinct terminologies. They use reporters with rare codon usage but do not mention what metrics they use to determine this, such as cAI, codon usage bias, or tAI. The distinction between the type of codon sequences that DDX6 affects is very important to differentiate and should be done here as certain stretches of codons are known to lead to different quality control RNA decay pathways that are not reliant on canonical mRNA decay factors. Likewise, the authors sort their Ribo-seq data to determine genes that might exhibit a DDX6 specific mRNA decay effect but fail to go into great depth about common features shared among these genes other than GO term analysis, GC content, and coding sequence (CDS) length. The authors then sort out 35 genes that are both upregulated at the mRNA level and have increased local ribosome footprint along the ORF. They are then able to show that 6 out of 9 of those genes had a DDX6-dependent mRNA decay effect. There was no comment or effort as to why 2 out of those 6 genes tested did not show as strong of a DDX6-dependent decay effect relative to the other targets tested. Thus, the efforts to identify mRNA features at a global level that exhibited DDX6-dependent mRNA decay effects are lacking in this analysis.<br /> Overall, the work done by Weber et al. is sound, with the proper controls. The authors expand significantly on the knowledge of what we know about DDX6 in the process of mRNA decay in humans, confirming the evolutionary conservation of the role of this factor across eukaryotes. The analysis of the RNA-seq and Ribo-seq data could be more in-depth, however, the authors were able to show with certainty that some transcripts containing known repetitive sequences or polybasic sequences exhibited a DDX6-mRNA decay effect.

Reviewer #2 (Public Review):

In the manuscript by Weber and colleagues, the authors investigated the role of a DEAD-box helicase DDX6 in regulating mRNA stability upon ribosome slowdown in human cells. The authors knocked out DDX6 KO in HEK293T cells and showed that the half-life of a reporter containing a rare codon repeat is elongated in the absence of DDX6. By analogy to the proposed function of fission yeast Dhh1p (DDX6 homolog) as a sensor for slow ribosomes, the authors demonstrated that recombinant DDX6 interacted with human ribosomes. The interaction with the ribosome was mediated by the FDF motif of DDX6 located in its RecA2 domain, and rescue experiments showed that DDX6 requires the FDF motif as well as its interaction with the CCR4-NOT deadenylase complex and ATPase activity for degrading a reporter mRNA with rare codons. To identify endogenous mRNAs regulated by DDX6, they performed RNA-Seq and ribosome footprint profiling. The authors focused on mRNAs whose stability is increased in DDX6 KO cells with high local ribosome density and validated that such mRNA sequences induced mRNA degradation in a DDX6-dependent manner.

The experiments were well-performed, and the results clearly demonstrated the requirement of DDX6 in mRNA degradation induced by slowed ribosomes. However, in some cases, the authors interpreted their data in a biased way, possibly influenced by the yeast study, and drew too strong conclusions. In addition, the authors should have cited important studies about codon optimality in mammalian cells. This lack of information hinders placing their important discoveries in a correct context.

1) Although the authors concluded that DDX6 acts as a sensor of the slowed ribosome, it is not clear if DDX6 indeed senses the ribosome speed. What the authors showed is a requirement of DDX6 for mRNA decay induced by rare codons, and DDX6 binds to the ribosome to exert this role. For example, DDX6 may bridge the sensor and decay machinery on the ribosome. Without structural or biochemical data on the recognition of the slowed ribosome by DDX6, the role of DDX6 as a sensor remains one of the possible models. It should be described in the discussion section.

2) It is not clear if DDX6 directly binds the ribosome. The authors used ribosomes purified by sucrose cushion, but ribosome-associating and FDF motif-interacting factors might remain on ribosomes, even after RNaseI treatment. Without structural or biochemical data of the direct interaction between the ribosome and DDX6, the authors should avoid description as if DDX6 directly binds to the ribosome.

3) Although the authors performed rigorous reporter assays recapitulating the effect of ribosome-retardation sequences on mRNA stability, this is not the first report showing that codon optimality determines mRNA stability in human cells. The authors did not cite important previous studies, such as Wu et al., 2019 (PMID: 31012849), Hia et al., 2019 (PMID: 31482640), Narula et al., 2019 (PMID: 31527111), and Forrest et al., 2020 (PMID: 32053646). These milestone papers should be cited in the Introduction, Results, and Discussion.

4) While both DDX6 and deadenylation by the CCR4-NOT were required for mRNA decay by the slowed ribosome, whether DDX6 is required for deadenylation was not investigated. Given that the CCR4-NOT deadenylate complex directly interacts with the empty ribosome E-site in yeast and humans (Buschauer et al., 2020 PMID: 32299921 and Absmeier et al., 2023 PMID: 37653243), whether the loss of DDX6 also affected the action of the CCR4-NOT complex is an important point to investigate, or at least should be discussed in this paper.

Reviewer #2 (Public Review):

In this paper the authors present an existing information theoretic framework to assess the ability of single cells to encode external signals sensed through membrane receptors. The main point is to distinguish actual noise in the signaling pathway from cell-cell variability, which could be due to differences in their phenotypic state, and to formalize this difference using information theory. After correcting for this cellular variability, the authors find that cells may encode more information than one would estimate from ignoring it, which is expected. The authors show this using simple models of different complexities, and also by analyzing an imaging dataset of the IGF/FoxO pathway.

I am only partially satisfied by the authors response. To me, the main question that was unanswered, while being at the core of the claim of the paper, was the magnitude of within-cell variability across repetitions of the stimulus.

This can only be done on the IGF/FoxO system because, as the authors acknowledge, the EGF/EGFR system does not have any data to support any claim about single-cell information that's not heavily informed by models, which assume by construction that this variability is small, naturally leading the desired conclusion.

The authors now measure within-cell, across-repetition variability (delta_0) for IGF/FoxO, but:<br /> - they compare it to cell-to-cell variability, finding that it's smaller. That's good and that supports the main claim of the paper that single cells are more precise than a mean cell. However they don't show it in the paper, but only in the response.<br /> - they also don't compare it to within-cell, within-stimulation variability across time. But this latter variability is what they (wrongly) used to estimate information, and still do in this revision. However I think this is approximated by the blue "simulation" violin plot in Reviewer Figure 2. The true variability is clearly larger than previously assumed. So it's strange that they conclude that "our estimates of cell-to-cell variability signaling fidelity are stable and reliable."<br /> - they don't use this delta_0 variability to revise their estimate of the information accordingly.<br /> - since variability is small compared to the differences between distinct stimulations, of which there are only 4, all information quantities they get are around 2 bits, which is not approaching the information capacity but merely a statement that the number of tested doses is small.

I strongly recommend that the authors actually report the figure they provided as Reviewer Figure 2 in the manuscript. In addition, they should not claim that the within-cell variability (captured by the variability across distinct presentations of the stimulus) is well captured by their initial estimate (based on the variance within a single presentation of the stimulus).

Reviewer #3 (Public Review):

Goetz, Akl and Dixit investigated the heterogeneity in the fidelity of sensing the environment by individual cells in a population using computational modeling and analysis of experimental data for two important and well-studied mammalian signaling pathways: (insulin-like growth factor) IGF/FoxO and (epidermal growth factor) EFG/EFGR mammalian pathways. They quantified this heterogeneity using the conditional mutual information between the input (eg. level of IGF) and output (eg. level of FoxO in the nucleus), conditioned on the "state" variables which characterize the signaling pathway (such as abundances of key proteins, reaction rates, etc.) First, using a toy stochastic model of a receptor-ligand system - which constitutes the first step of both signaling pathways - they constructed the population average of the mutual information conditioned on the number of receptors and maximized over the input distribution and showed that it is always greater than or equal to the usual or "cell state agnostic" channel capacity. They constructed the probability distribution of cell state dependent mutual information for the two pathways, demonstrating agreement with experimental data in the case of the IGF/FoxO pathway using previously published data. Finally, for the IGF/FoxO pathway, they found the joint distribution of the cell state dependent mutual information and two experimentally accessible state variables: the response range of FoxO and total nuclear FoxO level prior to IGF stimulation. In both cases, the data approximately follow the contour lines of the joint distribution. Interestingly, high nuclear FoxO levels, and therefore lower associated noise in the number of output readout molecules, is not correlated with higher cell state dependent mutual information, as one might expect. This paper contributes to the vibrant body of work on information theoretic characterization of biochemical signaling pathways, using the distribution of cell state dependent mutual information as a metric to highlight the importance of heterogeneity in cell populations. The authors suggest that this metric can be used to infer "bottlenecks" in information transfer in signaling networks, where certain cell state variables have a lower joint distribution with the cell state dependent mutual information.

The utility of a metric based on the conditional mutual information to quantify fidelity of sensing and its heterogeneity (distribution) in a cell population is supported in the comparison with data. Some aspects of the analysis and claims in the main body of the paper and SI need to be clarified and extended.

Remaining Comments:

- I think Review Figure 2 which is currently in the SI would improve the main body of the paper if moved there. In that case, the discussion of this figure in the main text would have to address more than it currently does, namely "the same cell's FoxO responses to the same input were found to have significantly less variation compared to the variation within the population".

Joint Public Review:

This work by Liu CSC et al. is an extension of the author's previous work on the role of Piezo1 mechano-sensor in human T cell activation. In this study, the authors address whether Piezo1 plays a role in T-cell chemotactic migration.

The authors used CD4+ T cells or Jurkat T cells to test the effects of siRNA-mediated depletion of Piezo1 on chemotactic migration. They establish that Piezo1 is implicated in chemotactic migration, although the effects of depletion are relatively moderate.

They show that Piezo1 is redistributed to the leading edge of T-cells.

They identify that relocation of Piezo1 to the leading edge follows an increase in membrane tension.

In Piezo-1 depleted cells, they observe a moderate reduction of LFA-1 polarity. With the use of specific inhibitors, they propose Piezo1 activation to be downstream of focal adhesion formation and upstream of calpain-mediated LFA-1, integrin alpha L beta 2, or CD11a/CD18 recruitment at the leading edge.

Strengths:

Together with their 2018 paper, this study presents Pieszo1 as a regulator of T-cell activation, implicating it as a player in the coordination of the chemotactic immune response.

Weaknesses:<br /> Most of the effects observed are relatively modest. The authors did not challenge the cells with various physico-mechanical conditions to see when Piezo-1 might become really important. For instance, there are no experiments that expose T cells to varying counter-acting forces to see how piezo1 might affect migration.

Technical weaknesses:

The authors state that "these high tension edges are usually further emphasized at later time points", but after ten minutes the median tension and tension (Figure 2C and Supplementary Figure 2C respectively) reduce down to the pretreatment time point. It would be clearer if the author stated within which timeframe the tension edges are "further emphasized".

Figures 3 and 4 - The author states the number of cells quantified from the images, but it is not clear whether the data is actually from 3 biological replicates.

Some of the data has no representative images or videos included. There is no video in the supplementary for Figures 1 A and B. There are no representative images of transwell migration assay in Figures 1 D and E.

Joint Public Review:

Iske et al. provide experimental data that NAD+ lessens disease severity in bacterial sepsis without impacting on the host pathogen load. They show that in macrophages, NAD+ prevents Il1b secretion potentially mediated by Caspase11.

While the in vivo and in vitro data is interesting and hints towards a crucial role of NAD+ to promote metabolic adaptation in sepsis, the manuscript has shortcomings and would profit from several changes and additional experiments that support the claims.

Conceptually, the definition of sepsis is outdated. Sepsis is not SIRS, as in sepsis-2. Sepsis-3 defines sepsis as infection-associated organ dysfunction. This concept needs to be taken into account for the introduction and when describing the potential effects of NAD+ in sepsis. Also, LPS application cannot be considered an appropriate sepsis model, since it only recapitulates the consequence of TLR-4 activation. It is a model of endotoxemia. Also, the LPS data does not allow to draw conclusions about bacterial clearance (L135).

The authors state that protective effects by NAD were independent of the host pathogen load. This clearly indicates that NAD confers protection via enhancing a disease tolerance mechanism, potentially via reducing immunopathology. This aspect is not considered by the authors. The authors should incorporate the concept of disease tolerance in their work, cite the relevant literature on the topic and discuss it their findings in light of the published evidence for metabolic alteration sand adaptations in sepsis.

For the in vitro data, the manuscript would benefit from additional experiments using in vitro infection models.

The figure legend should not repeat the methods and materials section. The nomenclature for mouse protein and genes needs to be thoroughly revised.

L350. The authors write that they dissect the capacity of NAD+ to dampen auto- and alloimmunity. In this work, no data that supports this statement is shown and experiments with autoantigens or alloantigens are not performed. If this refers to another previous publication by the same group, it needs to be put into this context and appropriately cited.

L163 The authors describe pyroptosis but in the figure legend call it apoptosis (Fig.2D). Specific markers for each cell death should be measured and determined which cell death mechanisms is involved.

Animal data comes from an infection model and LPS application. The RNAseq data is obtained from cells primed with Pam3CSK4 and subsequently subjected to LPS. It is unclear how the cell culture model reflects the animal model. As such the link between IFN signaling and the bacterial infection/LPS model are not convincing and need to be further elaborated.

Further experiments with primary cells from Il10 k.o. and Caspase11 k.o. animals should be provided that support the findings in macrophages.

Joint Public Review:

Summary:

In this manuscript, the authors set out to understand how different TLR4 agonists trigger Myddosome assembly and seek to examine how the potent LPS agonist induces a heightened TLR4 response. A strength of the study is that the authors employ a novel light sheet imaging modality coupled to nanopipette delivery of TLR4 ligands. The authors use this technological innovation to resolve the dynamics of Myddosome formation within the whole cell volume of macrophage cell lines expressing MyD88-YFP. The main finding is that the kinetics of Myddosome formation is slower for the weaker agonist Abeta than LPS. However, Abeta amyloids resulted in the formation of larger MyD88-YFP puncta that persisted for longer. The authors suggest the slower kinetics of formation and larger puncta size reflect how Abeta amyloids are a less efficient TLR4 agonist. Many Toll-like receptors are now known to recognize endogenous produced danger signals and microbially derived molecules. This work is the first to compare the signaling kinetics of endogenous versus microbially derived TLR agonists.

Strengths:

A key strength of this work is the technological achievement of imaging Myddosomes within the entire cell volume and using a nanopipette to administer ligands directly to single cells. The authors also combine this light sheet microscopy with STORM imaging to gain a super-resolved view of the assembly of Myddosomes. These findings suggest that Myddosomes formed in response to Abeta have a more irregular morphology. We conclude that these technological achievements are significant in improving our understanding of the dynamics of TLR4 signaling in response to diverse agonists. Given the limited literature on the molecular dynamics of innate immune signal transduction, this study is an important addition to the field.

Weaknesses:

One limitation of the paper is that a suitable explanation for how larger Myddosomes would contribute to an attenuated downstream signaling response. Do the larger clusters of nucleated MyD88 polymers reflect inefficiency in assembling fully formed Myddosomes that contain IRAK4/2? Could the MyD88-GFP puncta be stained with antibodies against IRAK4 (or IRAK2) to determine the frequency and probably of the two ligands to stimulate signal transduction beyond MyD88 assembly?

A second weakness is the discussion. The authors should explore other explanations for the observed differences in Myddosome formation between TLR4 agonists. For example, could the observed delay in Myddosome assembly in response to Abeta be due to different binding affinity or kinetics to TLR4? Can this be ruled out?

Reviewer #1 (Public Review):

Summary:<br /> Zink et al set out to identify selective inhibitors of the pyridoxal phosphatase (PDXP). Previous studies had demonstrated improvements in cognition upon removal of PDXP, and here the authors reveal that this correlates with an increase in pyridoxal phosphate (PLP; PDXP substrate and an active coenzyme form of vitamin B6) with age. Since several pathologies are associated with decreased vitamin B6, the authors propose that PDXP is an attractive therapeutic target in the prevention/treatment of cognitive decline. Following high throughput and secondary small molecule screens, they identify two selective inhibitors. They follow up on 7, 8 dihydroxyflavone (DHF). Following structure-activity relationship and selectivity studies, the authors then solve a co-crystal structure of 7,8 DHF bound to the active site of PDXP, supporting a competitive mode of PDXP inhibition. Finally, they find that treating hippocampal neurons with 7,8 DHF increases PLP levels in a WT but not PDXP KO context. The authors note that 7,8 DHF has been used in numerous rodent neuropathology models to improve outcomes. 7, 8 DHF activity was previously attributed to activation of the receptor tyrosine kinase TrkB, although this appears to be controversial. The present study raises the possibility that it instead/also acts through modulation of PLP levels via PDXP, and is an important area for future work.

Strengths:<br /> The strengths of the work are in the comprehensive, thorough, and unbiased nature of the analyses revealing the potential for therapeutic intervention in a number of pathologies.

Weaknesses:<br /> Potential weaknesses include the poor solubility of 7,8 DHF that might limit its bioavailability given its relatively low potency (IC50= 0.8 uM), which was not improved by SAR. However, the compound has an extended residence time and the co-crystal structure could aid the design of more potent molecules and would be of interest to those in the pharmaceutical industry. The images related to crystal structure could be improved.

Reviewer #2 (Public Review):

Summary: In this study, the authors performed a screening for PDXP inhibitors to identify compounds that could increase levels of pyridoxal 5'- phosphate (PLP), the co-enzymatically active form of vitamin B6. For the screening of inhibitors, they first evaluated a library of about 42,000 compounds for activators and inhibitors of PDXP and secondly, they validated the inhibitor compounds with a counter-screening against PGP, a close PDXP relative. The final narrowing down to 7,8-DHF was done using PLP as a substrate and confirmed the efficacy of this flavonoid as an inhibitor of PDXP function. Physiologically, the authors show that, by acutely treating isolated wild-type hippocampal neurons with 7,8-DHF they could detect an increase in the ratio of PLP/PL compared to control cultures. This effect was not seen in PDXP KO neurons.

Strengths: The screening and validation of the PDXP inhibitors have been done very well because the authors have performed crystallographic analysis, a counter screening, and mutation analysis. This is very important because such rigor has not been applied to the original report of 7,8 DHF as an agonist for TrkB. Which is why there is so much controversy on this finding.

Weaknesses: As mentioned in the summary report the study may benefit from some in vivo analysis of PLP levels following 7,8-DHF treatment, although I acknowledge that it may be challenging because of the working out of the dosage and timing of the procedure.

Reviewer #3 (Public Review):

This is interesting biology. Vitamin B6 deficiency has been linked to cognitive impairment. It is not clear whether supplements are effective in restoring functional B6 levels. Vitamin B6 is composed of pyridoxal compounds and their phosphorylated forms, with pyridoxal 5-phosphate (PLP) being of particular importance. The levels of PLP are determined by the balance between pyridoxal kinase and phosphatase activities. The authors are testing the hypothesis that inhibition of pyridoxal phosphatase (PDXP) would arrest the age-dependent decline in PLP, offering an alternative therapeutic strategy to supplements. Published data illustrating that ablation of the Pdxp gene in mice led to increases in PLP levels and improvement in learning and memory trials are consistent with this hypothesis.

In this report, the authors conduct a screen of a library of ~40k small molecules and identify 7,8-dihydroxyflavone (DHF) as a candidate PDXP inhibitor. They present an initial characterization of this micromolar inhibitor, including a co-crystal structure of PDXP and 7,8-DHF. In addition, they demonstrate that treatment of cells with 7,8 DHP increases PLP levels. Overall, this study provides further validation of PDXP as a therapeutic target for the treatment of disorders associated with vitamin B6 deficiency and provides proof-of-concept for inhibition of the target with small-molecule drug candidates.

Strengths include the biological context, the focus on an interesting and under-studied class of protein phosphatases that includes several potential therapeutic targets, and the identification of a small molecule inhibitor that provides proof-of-concept for a new therapeutic strategy. Overall, the study has the potential to be an important development for the phosphatase field in general.

Weaknesses include the fact that the compound is very much an early-stage screening hit. It is an inhibitor with micromolar potency for which mechanisms of action other than inhibition of PDXP have been reported. Extensive further development will be required to demonstrate convincingly the extent to which its effects in cells are due to on-target inhibition of PDXP.

Reviewer #1 (Public Review):

Summary:

Makiko Kashio et al aimed to uncover a potential role of exocrine gland-expressing TRPV4 in perspiration. Pharmacological and genetic tools were employed to verify a TRPV4-dependent cytosolic Ca2+ increase, which may contribute to sweat in mice.

Strengths:

(1) The authors identified a functional expression of TRPV4 in sweat glands.<br /> (2) The lower expression of TRPV4 in anhidrotic skin from patients with AIGA suggested a potential role of TRPV4 in perspiration.

Weaknesses:

(1) Measurement of secreted amylase could be seen as direct evidence of sweating, however, how to determine the causal relationship between climbing behavior and sweating? Friction force may also be reduced when there is too much fingertip moisture.

(2) For the human skin immunostaining, did the author use the same TRPV4 antibody as used in the mouse staining? Did they validate the specificity of the antibody for the human TRPV4 channel?

(3) In lines 116-117, the authors tried to determine "the functional interaction of TRPV4 and ANO1 is involved in temperature-dependent sweating", however, they only used the TRPV4 ko mice and did not show any evidence supporting the relationship between TRPV4 and ANO1.

(4) Figure 3-4 is quite confusing. At 25˚C, no sweating difference was observed between TRPV4 and wt mice (Fig 3A-3D), suggesting both Ach-induced sweating and basal sweating are TRPV4-independent at 25˚C, however, the climbing test was done at 26-27 ˚C and the data showed a climbing deficit in TRPV4 ko mice. How to interpret the data is unclear.

(5) Was there any gender differences associated with sweating in mice? In Figure 3, the mouse number for behavior tests should be at least 5.

(8) 8- to 21-week-old mice were used in the immunostaining, the time span is too long.

(6) The authors used homozygous TRPV4 ko mice for all experiments. What are control mice? Are they littermates of the TRPV4 ko mice?

Reviewer #2 (Public Review):

Summary:

In this study, Kashio et al examined the role of TRPV4 in regulating perspiration in mice. They find coexpression of TRPV4 with the chloride channel ANO1 and aquaporin 5, which implies possible coupling of heat sensing through TRPV4 to ion and water excretion through the latter channels. Calcium imaging of eccrine gland cells revealed that the TRPV4 agonist GSK101 activates these cells in WT mice, but not in TRPV4 KO. This effect is reduced with cold-stimulating menthol treatment. Temperature-dependent perspiration in mouse skin, either with passive heating or with ACh stimulation, was reduced in TRPV4 KO mice. Functional studies in mice - correlating the ability to climb a slippery slope to properly regulate skin moisture levels - reveal potential dysregulation of foot pad perspiration in TRPV4 KO mice, which had fewer successful climbing attempts. Lastly, a correlation of TRPV4 to hypohydrosis in humans was shown, as anhidrotic skin showed reduced levels of TRPV4 expression compared to normohidrotic or control skin.

Strengths:

The functional studies of mice climbing slippery slopes is a novel method to determine mechanisms of functional perspiration in mice. Since mice do not perspire for thermoregulation, other functional readouts are needed to study perspiration in mice.

Weaknesses:

1. The coexpression data needs additional controls. In the TRPV4 KO mice, there appears to be staining with the TRPV4 Ab in TRPV4 KO mice below the epidermis. This pattern appears similar to that of the location of the secretory coils of the sweat glands (Fig 1A). Is the co-staining the authors note later in Figure 1 also seen in TRPV4 KOs? This control should be shown, since the KO staining is not convincing that the Ab doesn't have off-target binding.

2. Are there any other markers besides CGRP for dark cells in mice to support the conclusion that mouse secretory cells have clear cell and dark cell properties?

3. The authors utilize menthol (as a cooling stimulus) in several experiments. In the discussion, they interpret the effect of menthol as potentially disrupting TRPV4-ANO1 interactions independent of TRPM8. Yet, the role of TRPM8, such as in TRPM8 KO mice, is not evaluated in this study.

4. Along those lines, the authors suggest that menthol inhibits eccrine function, which might lead to a cooling sensation. But isn't the cooling sensation of sweating from evaporative cooling? In which case, inhibiting eccrine function may actually impair cooling sensations.

5. The climbing assay is interesting and compelling. The authors note performing this under certain temperature and humidity conditions. Presumably, there is an optimal level of skin moisture, where skin that is too dry has less traction, but skin that is too wet may also have less traction. It would bolster this section of the study to perform this assay under hot conditions (perhaps TRPV4 KO mice, with impaired perspiration, would outperform WT mice with too much sweating?), or with pharmacologic intervention using TRPV4 agonists or antagonists to more rigorously evaluate whether this model correlates to TRPV4 function in the setting of different levels of perspiration.

6. There are other studies (PMID 33085914, PMID 31216445) that have examined the role of TRPV4 in regulating perspiration. The presence of TRPV4 in eccrine glands is not a novel finding. Moreover, these studies noted that TRPV4 was not critical in regulating sweating in human subjects. These prior studies are in contradiction to the mouse data and the correlation to human anhidrotic skin in the present study. Neither of these studies is cited or discussed by the authors, but they should be.

Reviewer #3 (Public Review):

Summary:

The authors set out to determine the extent to which the cation channel TRPV4 is expressed in secretory cells of sweat glands and the effect of blocking TRPV4 activity on sweat production, mediated via effects on the chloride channel anoctamin 1.

Strengths:

The study makes use of a diverse array of techniques, including super-resolution microscopy, live-cell calcium imaging, behavioral tests, and immunohistochemistry of human tissues in support of the claim that functional TRPV4 expression is detectable in sweat glands, and that TRPV4-deficient mice do not show respond to stimulation of sweat production (acetylcholine).

Weaknesses:

Figure 2: The calcium imaging-based approach shows average traces from 6 cells per genotype, but it was unclear if all acinar cells tested with this technique demonstrated TRPV4-mediated calcium influx, or if only a subset was presented.

Figure 4: The climbing behavioral test shows a significant reduction in climbing success rate in TRPV4-deficient mice. The authors ascribe this to a lack of hind paw 'traction' due to deficiencies in hind paw perspiration, but important controls and evidence that could rule out other potential confounds were not provided or cited.

In general, the results support the authors' claims that TRPV4 activity is a necessary component of sweat gland secretion, which may have important implications for controlling perspiration as well as secretion from other glands where TRPV4 may be expressed.

Reviewer #1 (Public Review):

Summary:

This work extends previous agent-based models of murine muscle regeneration by the authors (especially Westman et al., 2021) and by others (especially Khuu et al, 2023) by incorporating additional agent rules (altogether now based on over 100 published studies), threshold parameters and interactions with fields of cytokines and growth factors as well as capillaries (dynamically changing through damage and angiogenesis) and lymphatic vessels. The estimation of 52 unknown parameters against three time courses of tissue-scale observables (muscle cross-sectional area recovery, satellite stem cell count and fibroblast cell count) employs the CaliPro algorithm (Joslyn et al., 2021) and sensitivity analysis. The model is validated against additional time courses of tissue-scale observables and qualitative perturbation data, which match for almost all conditions. This model is here used to predict (also non-monotonic) responses of (combinations of) cytokine perturbations but it moreover represents a valuable resource for further analysis of emergent behavior across multiple spatial scales in a physiologically relevant system.

Strengths:

This work (almost didactically) demonstrates how to develop, calibrate, validate and analyze a comprehensive, spatially resolved, dynamical, multicellular model. Testable model predictions of (also non-monotonic) emergent behaviors are derived and discussed. The computational model is based on a widely-used simulation platform and shared openly such that it can be further analyzed and refined by the community.

Weaknesses:

While the parameter estimation approach is sophisticated, this work does not address issues of structural and practical non-identifiability (Wieland et al., 2021, DOI:10.1016/j.coisb.2021.03.005) of parameter values, given just tissue-scale summary statistics, and does not address how model predictions might change if alternative parameter combinations were used. Here, the calibrated model represents one point estimate (column "Value" in Suppl. Table 1) but there is specific uncertainty of each individual parameter value and such uncertainties need to be propagated (which is computationally expensive) to the model predictions for treatment scenarios.<br /> Suggested treatments (e.g. lines 484-486) are modeled as parameter changes of the endogenous cytokines (corresponding to genetic mutations!) whereas the administration of modified cytokines with changed parameter values would require a duplication of model components and interactions in the model such that cells interact with the superposition of endogenous and administered cytokine fields. Specifically, as the authors also aim at 'injections of exogenously delivered cytokines' (lines 578, 579) and propose altering decay rates or diffusion coefficients (Fig. 7), there needs to be a duplication of variables in the model to account for the coexistence of cytokine sub-types. One set of equations would have unaltered (endogenous) and another one have altered (exogenous or drugged) parameter values. Cells would interact with both of them.

This work shows interesting emergent behavior from nonlinear cytokine interactions but the analysis does not provide insights into the underlying causes, e.g. which of the feedback loops dominates early versus late during a time course.

Reviewer #2 (Public Review):

Summary:

In the paper, the authors use a cellular Potts model to investigate muscle regeneration. The model is an attempt to combine many contributors to muscle regeneration into one coherent framework. I believe the resulting model has the potential to be very useful in investigating the complex interplay of multiple actors contributing to muscle regeneration.

Strengths:

The manuscript identified relevant model parameters from a long list of biological studies. This collation of a large amount of literature into one framework has the potential to be very useful to other authors. The mathematical methods used for parameterization and validation are transparent.

Weaknesses:

I have a few concerns which I believe need to be addressed fully.

My main concerns are the following:

1) The model is compared to experimental data in multiple results figures. However, the actual experiments used in these figures are not described. To me as a reviewer, that makes it impossible to judge whether appropriate data was chosen, or whether the model is a suitable descriptor of the chosen experiments. Enough detail needs to be provided so that these judgements can be made.

2) Do I understand it correctly that all simulations are done using the same initial simulation geometry? Would it be possible to test the sensitivity of the paper results to this geometry? Perhaps another histological image could be chosen as the initial condition, or alternative initial conditions could be generated in silico? If changing initial conditions is an unreasonably large request, could the authors discuss this issue in the manuscript?

3) Cytokine knockdowns are simulated by 'adjusting the diffusion and decay parameters' (line 372). Is that the correct simulation of a knockdown? How are these knockdowns achieved experimentally? Wouldn't the correct implementation of a knockdown be that the production or secretion of the cytokine is reduced? I am not sure whether it's possible to design an experimental perturbation which affects both parameters.

4) The premise of the model is to identify optimal treatment strategies for muscle injury (as per the first sentence of the abstract). I am a bit surprised that the implemented experimental perturbations don't seem to address this aim. In Figure 7 of the manuscript, cytokine alterations are explored which affect muscle recovery after injury. This is great, but I don't believe the chosen alterations can be done in experimental or clinical settings. Are there drugs that affect cytokine diffusion? If not, wouldn't it be better to select perturbations that are clinically or experimentally feasible for this analysis? A strength of the model is its versatility, so it seems counterintuitive to me to not use that versatility in a way that has practical relevance. - I may well misunderstand this though, maybe the investigated parameters are indeed possible drug targets.

5) A similar comment applies to Figure 5 and 6: Should I think of these results as experimentally testable predictions? Are any of the results surprising or new, for example in the sense that one would not have expected other cytokines to be affected as described in Figure 6?

6) In figure 4, there were differences between the experiments and the model in two of the rows. Are these differences discussed anywhere in the manuscript?

7) The variation between experimental results is much higher than the variation of results in the model. For example, in Figure 3 the error bars around experimental results are an order of magnitude larger than the simulated confidence interval. Do the authors have any insights into why the model is less variable than the experimental data? Does this have to do with the chosen initial condition, i.e. do you think that the experimental variability is due to variation in the geometries of the measured samples?

8) Is figure 2B described anywhere in the text? I could not find its description.

Reviewer #1 (Public Review):

Summary:

Taking advantage of the Alphafold-multimer program, which predicts the tertiary structure of the macromolecular complex, the authors analyzed the interaction of essential factors involved in sperm-egg fusion. In particular, the authors predicted that the presence of a large complex of the novel factor TMEM81 with IZUMO1, SPACA6, JUNO, and CD9.

Strengths:

The authors postulated that the type I transmembrane sperm protein TMEM81 may be involved in gamete fusion, as predicted by the Alphafold-multimer.

Weaknesses:

All data except Figure 1 are mere predictive models, and their physiological importance is extremely unreliable. In addition, the data lacks experimental validation compared to another group's preprint (https://www.biorxiv.org/content/10.1101/2023.07.27.550750v1).

Reviewer #2 (Public Review):

Summary:

Fertilization is a crucial event in sexual reproduction, but the molecular mechanisms underlying egg-sperm fusion remain elusive. Elofsson et al. used AlphaFold to explore possible synapse-like assemblies between sperm and egg membrane proteins during fertilization. Using a systematic search of protein-protein interactions, the authors proposed a pentameric complex of three sperm (IZUMO1, SPACA6, and TMEM81) and two egg (JUNO and CD9) proteins, providing a new structural model to be used in future structure-function studies.

Strengths:

1. The study uses the AlphaFold algorithm to predict higher-order assemblies. This approach could offer insights into a highly transient protein complex, which is challenging to detect experimentally.<br /> 2. The article predicts a pentameric complex between proteins involved in fertilization, shedding light on the architectural aspects of the egg-sperm fusion synapse.

Weaknesses:

1. The procedures and discriminator scores used to evaluate specific from non-specific complexes were developed previously by the same authors. Therefore, in this manuscript, they are not contributing a new method.<br /> 2. The proposed model, which is a prediction from a modeling algorithm, lacks experimental validation of the identity of the components and the predicted contacts.

It is noteworthy that in an independent study, Deneke et al. provide experimental evidence of the interaction between IZUMO1/SPACA6/TMEM81 in zebrafish. This is an important element that supports the findings presented in this manuscript.

Reviewer #3 (Public Review):

Summary:

Sperm-egg fusion is a critical step in successful fertilization. Although several proteins have been identified in mammals that are required for sperm-egg adhesion and fusion, it is still unclear whether there are other proteins involved in this process and how the reported proteins complex and/or cooperate to complete the fusion process. In this study, the authors first identified TMEM81 as a structural homologue of IZUMO1 and SPACA6, and using AlphaFold-Multimer, a recent advance in protein complex structure prediction, predicted the interactions between human proteins associated with gamete fusion. While the prediction is compelling and well discussed, the experimental evidence to verify this interaction is lacking, so the prediction remains a hypothesis.

Strengths:

The authors present a pentameric complex formation of four previously reported proteins involved in egg/sperm interaction together with TMEM181 using a deep learning tool, AlphaFold-Multimer.

Weaknesses:

While it is intriguing to see that some of the proteins involved in sperm-egg interaction are successfully predicted to be assembled into a single multimeric structure by AlphaFold-Multimer, it is necessary to experimentally validate the interactions. As there are more candidate proteins in the process, it will be necessary to test other possible protein interactions to prove the adequacy of the candidates chosen by the authors, as similar analysis with some other proteins will provide more rationale for further 3D multi-protein modeling. In addition, the lack of biochemical data to support the predicted bindings between proteins limits the proposed complex to remain mainly hypothetical.

Positive Meldungen zu Klima und Umwelt 2023: Rekordzuwachs bei den Erneuerbaren, deutliche Verlangsamung der Entwaldung am Amazonas, Abschluss des High Seas Treaty, Erfolg beim Kampf gegen das Ozonloch und weitgehende Wiederherstellung der französischen Grundwasservorräte durch massive Niederschläge. https://www.liberation.fr/environnement/climat/boom-des-energies-renouvelables-repit-pour-lamazonie-nappes-phreatiques-gonflees-a-bloc-retour-sur-les-quelques-bonnes-nouvelles-environnementales-de-2023-20231230_ADVIREAXPJFJ7DI766HR6GCBJ4/

2022 wurden 12% des elektrischen Stroms mit erneuerbaren Energien produziert - ein Rekordwert, zu dem die russische Invasion der Ukraine im Februar erheblich beigetragen hat. Ember publiziert die Zahlen in seinem vierten Global Electricity Review. https://www.liberation.fr/environnement/nucleaire/le-debut-de-la-fin-de-lage-fossile-jamais-autant-denergies-renouvelables-nont-ete-produites-dans-le-monde-20230412_NBQ2CEVZ7VFV3JZZLL4DJMCWJY/

Reviewer #1 (Public Review):

The manuscript by Singh et al proposes a new theoretical model for the phenomenon of planar cell polarity (PCP). The new model is simulating the emergence of the subcellular polarity of the Fat-Ds pathway, based on the interactions of the protocadherins Fat and Ds at the boundary between cells and in response to external gradients. Several mathematical models for PCP have been previously developed focusing on different aspects of PCP, including non-autonomy domineering (Amonlirdviman et al.), the effect of stochasticity on polarity (Burak et al.), gradient sensing (Mani et al), formation of molecular bridges (Fisher et al.) to name a few. The current modeling approach suggests a new model, based on a relatively simple set of equations for membrane Fat and Ds and their interactions, both in 1D (line of cells) and in 2D (hexagonal array). The equations are relatively simple on one hand, allowing performing tractable computational analysis as well as analytical approximations, while on the other hand allowing tracking membrane protein levels, which is what is measured experimentally. It has been previously shown that achieving polarity requires local feedback that amplify complexes in one orientation at the expense of complexes in the opposite orientation (e.g. Mani et al.). Interestingly, the current manuscript shows that a simple assumption, that Fat-DS complexes are stabilized when bound is sufficient to induce PCP when concentrations are high enough. The authors use the model to show how it captures several experimental observations, as well as to analyze the sensitivity to noise, the response to gradients, and the response to local perturbations (mutant clones). The manuscript is clear and the analysis is mostly coherent and sensible (although some parts need to be clarified, see below). The main issue I have with the manuscript is that it mostly describes how it captures different features that were mostly explained in previous models. I do think the authors should do more with their model to explain features that were not explained by other models, and/or generate non-trivial predictions that can be tested experimentally.

Reviewer #2 (Public Review):

The setting of planar cell polarity in epithelial tissues involves a complex interplay of chemical interactions. While local interactions can spontaneously give rise to cell polarity, planar cell polarity also involves tissue scale gradients whose effects are not clear. To understand their role, the authors built a minimal mechanistic model in considering two atypical cadherins, Fat (Ft) and Dachsous (Ds) which can associate at cell-cell interfaces to form hetero-dimers in which monomers belong to adjacent cells. This association can be seen as a local interaction between cells and is also sensitive to overall concentration gradients. From their model which appears to capture diverse experimental observations, the authors conclude that tissue-scale gradients provide to planar cell polarity a directional cue and some robustness to cellular stochasticity. While this model comes after similar works reaching similar predictions, the quality of this model is in its simplicity, its convenience for experimental testing, and the diversity of experimental observations it recapitulates.

A strength of this work is to recapitulate many experimental observations made on planar cell polarity. It, for example, seems to capture the response of tissues to perturbations such as local downregulation of some important proteins, and the polarity patterns observed in the presence of noise in synthesis or cell-to-cell heterogeneity. It also gives a mechanistic description of planar cell polarity, making its experimental interpretation simple. Finally, the simplicity of the model facilitates its exploration and makes it easily testable because of the reduced amount of free model parameters.

A weakness of this work is that it comes after several models with similar hypotheses and similar predictions. Another weakness is that some conclusions of this work rely on visual appreciation rather than quantification. This is particularly true for what concerns 2D patterns. An argument of the authors is for example that their model reproduces a variety of known spatial patterns, but the comparison with experiments is only visual and would be more convincing in being more quantitative.

Reviewer #3 (Public Review):

Using theory, the authors study mechanisms for establishing planar cell polarity (PCP) through local and global modules. These modules refer to the interaction between neighbouring cells and tissue-wide gradients, respectively. Whereas local interactions alone can lead to tissue-wide alignment PCP, a global gradient can set the direction of PCP and maintain the pattern in presence of noise. In contrast, the authors argue that a global gradient can only generate PCP to an extent that is proportional to the gradient magnitude.

The authors formulate a discrete model in one and two spatial dimensions that describe the assembly dynamics of PCP proteins on membranes. The number of proteins per cell remains constant. Additive noise is introduced to account for stochasticity in the attachment/detachment kinetics of proteins. Furthermore, 'quenched' noise is introduced to account for variations of protein numbers between cells. The authors perform simulations of the stochastic discrete model in various situations. In addition, they derive a continuum description to perform some analytical computations.

The strength of this analysis relies clearly on showing that simple dynamics can lead to tissue-wide PCP even in absence of a gradient in protein expression. A number of phenomena observed in tissues are qualitatively reproduced. In two spatial dimensions, they find swirling patterns that resemble patterns found in tissues when a global gradient is absent. The model also captures qualitative effects due to the down-regulation of one of the PCP proteins in a certain region of the tissue.

The main weak point is that, from a physical point of view, the findings are not particularly surprising. Furthermore, some assumptions underlying the model, need some more justification. This holds notably for the question, of why additive noise is appropriate to account for the effect of stochasticity in the attachment-detachment dynamics of the proteins. Finally, the authors consider a situation that they consider to be one of the most interesting features of PCP, namely, the formation of PCP in presence of a region with a down-regulated PCP protein and in presence of a gradient. Unfortunately, the effect is not very clear and the data provided remains limited.

Reviewer #1 (Public Review):

In this manuscript, the authors seek to investigate the spatiotemporal dynamics of macrophage polarization during Salmonella infection. They undertake intravital microscopy of Salmonella Typhimurium infection in the hindbrain ventricle of zebrafish larvae and couple this with transcriptomic analysis of macrophages from infected tissues. They find that macrophages and neutrophils are rapidly recruited to the site of infection within hours after inoculation. Macrophage abundance is significantly increased in the persistent infection stage at 4 days post-inoculation (dpi), compared to in the early stage, hours post-inoculation. The authors observe that Salmonella bacilli selectively co-localize with aggregates of macrophages, but not neutrophils, during persistent infection. Furthermore, they show that in early infection stage, a markedly higher fraction of macrophages at the site of infection expressed tnfa and exhibits stronger transcriptional signature of pro-inflammatory, M1-like phenotype, compared to macrophages in persistent infection stage. Additionally, the authors find that genes involved in cell-cell adhesion are down-regulated in persistent stage macrophages and these cells have reduced motility. This study's approach, further developing and employing a zebrafish S. Typhimuirum infection model and intravital microscopy of whole living animals, presents an exciting strategy to investigate macrophage responses and their roles during vacuolar intracellular bacterial infection in vivo, complementary to the more commonly utilized murine infection models. The study's findings are useful and largely observational. The data presented have the potential but additional analyses and experiments are needed to clarify and support the conclusions.

Reviewer #2 (Public Review):

In this study, Leiba et al. aim at establishing the developing zebrafish embryo as a suitable infection model to study Salmonella persistence in vivo. Under environmental stress (ex: macrophage phagosomes) a proportion of bacteria switch to a slow/arrested growth state confering increased resistance to antibiotic treatments. Persisters are getting increasingly linked to infection relapses. Understanding how persistent infections emerge and bacteria survive in an organism for long time without replicating before switching back to a replicative state is essential. Zebrafish represents an alternative model to mice offering the possibility to image the whole organism and capture persistency with an amazing spatio-temporal resolution.

In this paper, the authors demonstrate that persistent infections of Salmonella can be reproduced in the developing zebrafish. The kinetics of infection have been well characterized and shows a very nice heterogeneity between animals demonstrating the complex host-pathogen interactions (Fig 1). From the perspective of persistence, the presence of Salmonella survivors to host clearing is reported until 14dpi demonstrating the possibility to induce persistent infection in this model. Through the manuscript, the authors have used a variety of state-of-the-art technics illustrating the flexibility of this model including microscopy and imaging of specific immune populations, various transgenic animals and selective depletion of macrophages or neutrophils to assess their relative contributions. Overall, the conclusions of the authors are well supported by the presented data. This said, the authors should strengthen the conclusions of the paper by providing a better characterization of the infection.

Major comments:<br /> 1- Figure 1: What is the general life-spam of the fish?

2- Figure 2: It would be nice to clearly state what infection scenario we are looking at. Have the authors studied "high proliferation", "infected" or "cleared" zebrafish?

3- Figure 3 and 4: It would be very informative if the authors can tell us what proportion of Salmonella is associated with macrophages and neutrophils. From panel C and D (Figure 3) and Figure 4 C and D and Suppl Fig 1, it seems that a lot of bacteria are extracellular. Maybe an EM image of the tissue would help to understand if the bacteria is "all" intracellular or intracellular.

4- Figure 3 and 4: It would be very useful if the authors can tell us if the intracellular bacteria are mainly found individually (like in Figure 3C) or does host cells harbor many intracellular bacteria. Looking at figure 4G: it is not clear to me how many intracellular bacteria can be counted on this image.

5- Figure 3 and 4: The authors should also perform an experiment with a Salmonella strain harboring a growth reporter to quantify the amount of replicating and non-replicating bacteria. This experiment is not absolutely necessary for the story, but if possible, it would provide a very nice add-up to the story and impact to the paper.

6- Figure 6: The authors should provide in suppl. the flow cytometry scatter plots used to delineate the different subpopulations.

7- Figure 6: A specific characterization of macrophages harboring Salmonella persisters at 4dpi is missing. As shown by the authors in Figure 6, the tnfa- populations of macrophages at 4dpi are very similar for both infected and non-infected larvae. Persisters should indeed reside within tnfa- macrophages but they should also induce a specific signature through the actions of Salmonella effectors. Measuring this signature will allow a direct comparison with published data in mice and assess how accurately the zebrafish model recapitulates the manipulation of macrophages by Salmonella

Reviewer #1 (Public Review):

This paper combines a number of cutting-edge approaches to explore the role of a specific mouse retinal ganglion cell type in visual function. The approaches used include calcium imaging to measure responses of RGC populations to a collection of visual stimuli and CNNs to predict the stimuli that maximally activate a given ganglion cell type. The predictions about feature selectivity are tested and used to generate a hypothesized role in visual function for the RGC type identified as interesting. The paper is impressive; my comments are all related to how the work is presented.

Is the MEI approach needed to identify these cells?<br /> To briefly summarize the approach, the paper fits a CNN to the measured responses to a range of stimuli, extracts the stimulus (over time, space, and color) that is predicted to produce a maximal response for each RGC type, and then uses these MEIs to investigate coding. This reveals that G28 shows strong selectivity for its own MEI over those of other RGC types. The feature of the G28 responses that differentiate it appears to be its spatially-coextensive chromatic opponency. This distinguishing feature, however, should be relatively easy to discover using more standard approaches.<br /> The concern here is that the paper could be read as indicating that standard approaches to characterizing feature selectivity do not work and that the MEI/CNN approach is superior. There may be reasons why the latter is true that I missed or were not spelled out clearly. I do think the MEI/CNN approach as used in the paper provides a very nice way to compare feature selectivity across RGC types - and that it seems very well suited in this context. But it is less clear that it is needed for the initial identification of the distinguished response features of the different RGC types.<br /> What would be helpful for me, and I suspect for many readers, is a more nuanced and detailed description of where the challenges arise in standard feature identification approaches and where the MEI/CNN approaches help overcome those challenges.

Interpretation of MEI temporal structure<br /> Some aspects of the extracted MEIs look quite close to those that would be expected from more standard measurements of spatial and temporal filtering. Others - most notably some of the temporal filters - do not. In many of the cells, the temporal filters oscillate much more than linear filters estimated from the same cells. In some instances, this temporal structure appears to vary considerably across cells of the same type (Fig. S2). These issues - both the unusual temporal properties of the MEIs and the heterogeneity across RGCs of the same type - need to be discussed in more detail.<br /> Related to this point, it would be nice to understand how much of the difference in responses to MEIs in Figure 4d is from differences in space, time, or chromatic properties. Can you mix and match MEI components to get an estimate of that? This is particularly relevant since G28 responds quite well to the G24 MEI.

Explanation of RDM analysis<br /> I really struggled with the analysis in Figure 5b-c. After reading the text several times, this is what I think is happening. Starting with a given RGC type (#20 in Figure 5b), you take the response of each cell in that group to the MEI of each RGC type, and plot those responses in a space where the axes correspond to responses of each RGC of this type. Then you measure euclidean distance between the responses to a pair of MEIs and collect those distances in the RDM matrix. Whether correct or not, this took some time to arrive at and meant filling in some missing pieces in the text. That section should be expanded considerably.

Centering of MEIs<br /> How important is the lack of precise centering of the MEIs when you present them? It would be helpful to have some idea about that - either from direct experiments or using a model.

Reviewer #2 (Public Review):

This paper uses two-photon imaging of mouse ganglion cells responding to chromatic natural scenes along with convolutional neural network (CNN) models fit to the responses of a large set of ganglion cells. The authors analyze CNN models to find the most effective input (MEI) for each ganglion cell as a novel approach to identifying ethological function. From these MEIs they identify chromatic opponent ganglion cells, and then further perform experiments with natural stimuli to interpret the ethological function of those cells. They conclude that a type of chromatic opponent ganglion cell is useful for the detection of the transition from the ground to the sky across the horizon. The experimental techniques, data, and fitting of CNN models are all high quality. However, there are conceptual difficulties with both the use of MEIs to draw conclusions about neural function and the ethological interpretations of experiments and data analyses, as well as a lack of comparison with standard approaches. These bear directly both on the primary conclusions of the paper and on the utility of the new approaches.

1. Claim of feature detection. The color opponent cells are cast as a "feature detector" and the term 'detector' is in the title. However insufficient evidence is given for this, and it seems likely a mischaracterization. An example of a ganglion cell that might qualify as a feature detector is the W3 ganglion cell (Zhang et al., 2012). These cells are mostly silent and only fire if there is differential motion on a mostly featureless background. Although this previous work does not conduct a ROC analysis, the combination of strong nonlinearity and strong selectivity are important here, giving good qualitative support for these cells as participating in the function of detecting differential motion against the sky. In the present case, the color opponent cells respond to many stimuli, not just transitions across the horizon. In addition, for the receiver operator characteristic (ROC) analysis as to whether these cells can discriminate transitions across the horizon, the area under the curve (AUC) is on average 0.68. Although there is not a particular AUC threshold for a detector or diagnostic test to have good discrimination, a value of 0.5 is chance, and values between 0.5 and 0.7 are considered poor discrimination, 'not much better than a coin toss' (Applied Logistic Regression, Hosmer et al., 2013, p. 177). The data in Fig. 6F is also more consistent with a general chromatic opponent cell that is not highly selective. These cells may contribute information to the problem of discriminating sky from ground, but also to many other ethologically relevant visual determinations. Characterizing them as feature detectors seems inappropriate and may distract from other functional roles, although they may participate in feature detection performed at a higher level in the brain.

2. Appropriateness of MEI analysis for interpretations of the neural code. There is a fundamental incompatibility between the need to characterize a system with a complex nonlinear CNN and then characterizing cells with a single MEI. MEIs represent the peak in a complex landscape of a nonlinear function, and that peak may or may not occur under natural conditions. For example, MEIs do not account for On-Off cells, On-Off direction selectivity, nonlinear subunits, object motion sensitivity, and many other nonlinear cell properties where multiple visual features are combined. MEIs may be a useful tool for clustering and distinguishing cells, but there is not a compelling reason to think that they are representative of cell function. This is an open question, and thus it should not be assumed as a foundation for the study. This paper potentially speaks to this issue, but there is more work to support the usefulness of the approach. Neural networks enable a large set of analyses to understand complex nonlinear effects in a neural code, and it is well understood that the single-feature approach is inadequate for a full understanding of sensory coding. A great concern is that the message that the MEI is the most important representative statistic directs the field away from the primary promise of the analysis of neural networks and takes us back to the days when only a single sensory feature is appreciated, now the MEI instead of the linear receptive field. It is appropriate to use MEI analyses to create hypotheses for further experimental testing, and the paper does this (and states as much) but it further takes the point of view that the MEI is generally informative as the single best summary of the neural code. The representation similarity analysis (Fig. 5) acts on the unfounded assumption that MEIs are generally representative and conveys this point of view, but it is not clear whether anything useful can be drawn from this analysis, and therefore this analysis does not support the conclusions about changes in the representational space. Overall this figure detracts from the paper and can safely be removed. In addition, in going from MEI analysis to testing ethological function, it should be made much more clear that MEIs may not generally be representative of the neural code, especially when nonlinearities are present that require the use of more complex models such as CNNs, and thus testing with other stimuli are required.

3. Usefulness of MEI approach over alternatives. It is claimed that analyzing the MEI is a useful approach to discovering novel neural coding properties, but to show the usefulness of a new tool, it is important to compare results to the traditional technique. The more standard approach would be to analyze the linear receptive field, which would usually come from the STA of white noise measurement, but here this could come from the linear (or linear-nonlinear) model fit to the natural scene response, or by computing an average linear filter from the natural scene model. It is important to assess whether the same conclusion about color opponency can come from this standard approach using the linear feature (average effective input), and whether the MEIs are qualitatively different from the linear feature. The linear feature should thus be compared to MEIs for Fig. 3 and 4, and the linear feature should be compared with the effects of natural stimuli in terms of chromatic contrast (Fig. 6b). With respect to the representation analysis (Fig. 5), although I don't believe this is meaningful for MEIs, if this analysis remains it should also be compared to a representation analysis using the linear feature. In fact, a representation analysis would be more meaningful when performed using the average linear feature as it summarizes a wider range of stimuli, although the most meaningful analysis would be directly on a broader range of responses, which is what is usually done.

4. Definition of ethological problem. The ethological problem posed here is the detection of the horizon. The stimuli used do not appear to relate to this problem as they do not include the horizon and only include transitions across the horizon. It is not clear whether these stimuli would ever occur with reasonable frequency, as they would only occur with large vertical saccades, which are less common in mice. More common would be smooth transitions across the horizon, or smaller movements with the horizon present in the image. In this case, cells which have a spatial chromatic opponency (which the authors claim are distinct from the ones studied here) would likely be more important for use in chromatic edge detection or discrimination. Therefore the ethological relevance of any of these analyses remains in question.

It is further not clear if detection is even the correct problem to consider. The horizon is always present, but the problem is to determine its location, a conclusion that will likely come from a population of cells. This is a distinct problem from detecting a small object, such as a small object against the background of the sky, which may be a more relevant problem to consider.

5. Difference in cell type from those previously described. It is claimed that the chromatic opponent cells are different from those previously described based on the MEI analysis, but we cannot conclude this because previous work did not perform an MEI analysis. An analysis should be used that is comparable to previous work, the linear spatiotemporal receptive field should be sufficient. However, there is a concern that because linear features can change with stimulus statistics (Hosoya et al., 2005), a linear feature fit to natural scenes may be different than those from previous studies even for the same cell type. The best approach would likely be presenting a white noise stimulus to the natural scenes model to compute a linear feature, which still carries the assumption that this linear feature from the model fit to a natural stimulus would be comparable to previous studies. If the previous cells have spatial chromatic opponency and the current cells only have chromatic opponency in the center, there should be both types of cells in the current data set. One technical aspect relating to this is that MEIs were space-time separable. Because the center and surround have a different time course, enforcing this separability may suppress sensitivity in the surround. Therefore, it would likely be better if this separability were not enforced in determining whether the current cells are different than previously described cells. As to whether these cells are actually different than those previously described, the authors should consider the following uncited work; (Ekesten Gouras, 2005), which identified chromatic opponent cells in mice in approximate numbers to those here (~ 2%). In addition, (Yin et al., 2009) in guinea pigs and (Michael, 1968) in ground squirrels found color-opponent ganglion cells without effects of a spatial surround as described in the current study.

Reviewer #3 (Public Review):

This study aims to discover ethologically relevant feature selectivity of mouse retinal ganglion cells. The authors took an innovative approach that uses large-scale calcium imaging data from retinal ganglion cells stimulated with both artificial and natural visual stimuli to train a convolutional neural network (CNN) model. The resulting CNN model is able to predict stimuli that maximally excite individual ganglion cell types. The authors discovered that modeling suggests that the "transient suppressed-by-contrast" ganglion cells are selectively responsive to Green-Off, UV-On contrasts, a feature that signals the transition from the ground to the sky when the animal explores the visual environment. They tested this hypothesis by measuring the responses of these suppressed-by-contrast cells to natural movies, and showed that these cells are preferentially activated by frames containing ground-to-sky transitions and exhibit the highest selectivity of this feature among all ganglion cell types. They further verified this novel feature selectivity by single-cell patch clamp recording.

This work is of high impact because it establishes a new paradigm for studying feature selectivity in visual neurons. The data and analysis are of high quality and rigor, and the results are convincing. Overall, this is a timely study that leverages rapidly developing AI tools to tackle the complexity of both natural stimuli and neuronal responses and provides new insights into sensory processing.

Reviewer #2 (Public Review):

This MS reveals that plants that have long been said to push are not, in fact, doing so, but are trapping and killing pests, thereby reducing pest outbreaks. The volatiles data of Desmodium are stable and useful. And the method of showing volatiles data is great.

Reviewer #3 (Public Review):

This study succeeds to highlight and address important gaps in our understanding of plant-insect interactions mediating pest control in a widely known agro-ecological system for sustainable intensification, push-pull agriculture. In particular, the authors present a large amount of data on plant volatile emission, thought to be critical for the functioning of these systems, in reasonable and relevant contexts, as well as on other traits of the plants in the system relevant for pest control. These data come from plants grown both in controlled and field environments, which is unusual. The arguments on mechanism are further supported by insect behavioral assays, which seem to be thoughtfully designed, but also use some non-standard approaches that could be better explained. While most or all of the authors' results pre-date some relevant recent publications in this field, they do incorporate comparisons to current literature in order to better place their findings in the current state of the art.

Reviewer #1 (Public Review):

The author tried to figure out whether neutrophil extracellular traps are involved in aristolochic acid nephropathy. Overall, this study provided some novel findings to support the conclusion. But the generation of knockin mice, IL-19 function in vivo, and the underlying mechanism by which PSTPIP2 influences NF-KB-IL-19 need to be further clarified.

Reviewer #2 (Public Review):

This study by Du et. al addressed the role and regulation of proline-serine-threonine phosphatase interacting protein 2 (PSTPIP2) and neutrophil extracellular traps (NETs) in Aristolochic acid Nephropthathy (AAN) and immune defense. PSTPIP2 expression is downregulated in AAN. Conditional knock-in of PSTPIP2 in mouse kidneys inhibited cell apoptosis, reduced neutrophil infiltration, suppressed the production of inflammatory factors and NETs, and ameliorated renal dysfunction. Reducing the expression of PSTPIP2 to normal levels in knock-in mouse using shRNA promoted kidney injury. Using in vivo model, the role of PSTPIP2 in AAN injury and renal function, apoptosis, neutrophil infiltration and NET formation is established. Using in vitro models, a PSTPIP2/NFkB-mediated NET formation via IL-19-IL20-beta Receptor pathway is shown to induce inflammation and apoptosis in AAN. The studies are well presented.

Reviewer #1 (Public Review):

In this manuscript the authors describe the expression and regulatory function of a self-cleaving ribozyme in the Cpeb3 gene. Cpeb3 knockout is associated with altered memory formation, and there are tempting correlations from the mid-2000s between a human CPEB3 SNP at the ribozyme cleavage site and memory performance, suggesting that regulation of Cpeb3 protein expression could impact memory. Here the authors test the impact of inhibiting Cpeb3 ribozyme self-excision with the hypothesis that this will promote splicing and Cpeb3 protein expression. They study the temporal regulation of ribozyme cleavage and find that it is in sync with transcription. Then they use their in vitro cleavage assay to identify an ASO that blocks cleavage. The validation of the effects of the ASO on ribozyme cleavage, and Cpeb3 mRNA expression and processing in membrane depolarized neurons and in the hippocampus in vivo are rigorous and establish the molecular function of the ribozyme. The authors also show an increase in CPEB3 protein expression and increased expression (and polyadenylation) of known translational targets of CPEB3 in cultures and in vivo with the latter only in the presence of elevated neural activity, consistent with an effect on protein synthesis. The final part of the study assesses the regulation and function of CPEB3 in the context of learning and memory.

The significance of this study lies in the molecular analysis of the ribozyme function. This ribozyme is well established and the gene in which it lies has important links to synaptic plasticity. Gene regulation is known to be important in the context of learning and memory and this is a new mechanism that the authors show has the potential to influence this process.

Reviewer #2 (Public Review):

For about four decades it has been known that RNA molecules can increase the rate of chemical reactions, just like the much more prevalent protein enzymes. Some have suggested that RNA enzymes, also called "ribozymes" were very important at the beginning of life, but that the importance was mostly erased when ribosomal protein synthesis emerged through evolution. The ribosome and spliceosome are two important examples of modern biological functions known to be catalyzed by RNA. In addition to these large RNA machines, the genomes of humans, and all domains of life, also contain a class of small ribozymes that catalyze self-cleavage of the RNA backbone. However, unlike RNA cleaving proteins that are well studied, there exists little evidence that the self-cleaving of RNA by ribozymes has important downstream consequences. This new paper provides evidence that a ribozyme found in all mammals has an important role in memory formation. The authors found a way to block the ribozyme activity and then observe the effect on memory formation in mice, and in the expression of genes in neurons that are known to underly this memory formation process. The authors found that blocking the ribozyme activity in mouse brains actually improved their performance in a memory task. In addition, they found that blocking the ribozyme changed the expression of the gene in which the ribozyme is found (a gene called CPEB3), suggesting that the way the ribozyme effects memory is through controlling the expression of the gene where it is found. The paper confirms the biological importance of this ribozyme, and encourages further investigation into self-cleaving ribozymes in general. Interestingly, the ribozyme found in humans is in fact slower cleaving than most mammals, similar to the blocked ribozyme in these experiments, which brings up the intriguing possibility that the CPEB3 ribozyme is a part of what makes us human!

Reviewer #3 (Public Review):

This manuscript uses ASO to inhibit the self-cleaving ribozyme within CPEB intron 3 and test its effect on CPEB3 expression and memory consolidation. The authors conclude that the intronic ribozyme negatively affects CPEB3 mRNA splicing and expression, and suggests its implications for experience-induced gene expression underlying learning and memory.<br /> The strength of the manuscript is in its exploration of a potentially novel mechanism of regulating CPEB3 expression in learning and memory, a combination of both biochemical and behavioral approaches to gain a wide perspective of this regulatory mechanism, and the application of ASO in this context. The introduction is sufficiently detailed. Statistics are thorough and appropriate. If the results could be more robust, the mechanism would provide a novel target and venue to modify learning and memory paradigm.<br /> The weakness of the manuscript is that the magnitude of the activity-dependent regulation of ribozyme, the effects of ASOs on CPEB3 expression (mRNA and protein) and downstream target gene expression, in vitro and in vivo, are generally weak, raising concerns about the robustness of the result. This may have caused some of the inconsistencies between the data presentation (see below). Also unclear is whether the ribozyme activity is physiologically regulated by experience without ASO interference.<br /> While the statistics tests support corresponding figure panels and their conclusions. The manuscript can be significantly strengthened by additional evidence, clarification of some methodologies, and reconciling some inconsistent results.<br /> The premise of a comparable timescale between transcription and ribozyme activity as the foundation of the whole thesis was based on in vitro measurement of self-scission half-life and a broadly generalized transcription rate (which actually varies significantly between genes). This premise is weak and needs direct experimental support.<br /> The physiological relevance of the proposed mechanism has yet to be demonstrated without ASO interference.<br /> Fig2b: how were total and uncleaved Ribozymes measured by qRT-PCR? Where are the primers' locations? If the two products were amplified using different primers, their subtraction to derive % cleavage would not be appropriate.<br /> Line 400-403: shouldn't ribozyme-blocking ASO prevent ribozyme self-cleavage, and as a result should further increase ribozyme levels? This would contradict the result in fig3a.

Reviewer #2 (Public Review):

The authors examine the use of metformin in the treatment of hepatic ischemia/reperfusion injury (HIRI) and suggest the mechanism of action is mediated in part by the gut microbiota and changes in hepatic ferroptosis. While the concept is intriguing, the experimental approaches are inadequate to support these conclusions.

The histological and imaging studies were considered a strength and reveal a significant impact of metformin post-HIRI.

Weaknesses largely stem from the experimental design. The impact of metformin on the microbiota is profound resulting in changes in bile acid, lipid, and glucose homeostasis. Throughout the manuscript no comparisons are made with metformin alone which would better capture the metformin-specific effects. With the pathology and metabolic disturbances resulting from HIRI, it is important to understand if metformin is providing beneficial effects from reported mechanisms such as changes in bile acid, glucose, and/or lipid metabolism, or are these changes the result of a new unappreciated mechanism. A comparison of the reported and the new pathways is not included.

Overall, while the concept is interesting and has potential to better understand the pleiotropic functions of metformin, the limitations with the experimental design and lack of key controls make it challenging to support the conclusions.

Reviewer #1 (Public Review):

The major strength of this work is its scope, including detailed mouse phenotyping, inter-disciplinary methods, and numerous complementary experiments. The antibiotic depletion and FMT experiments provide support for a role of the gut microbiota in this mouse model.

A major limitation is the lack of studies narrowing down which microbes are responsible. Sequencing data is shown, but no follow-up studies are done with bacterial isolates or defined communities.

The link to GABA is also somewhat tenuous. While it does match the phenotypic data, there are no targeted experiments in which GABA producing microbial communities/strains are compared to a control community/strain. As such, it seems difficult to know how much of the effects in this model are due to GABA vs. other metabolites.

My major recommendation would be to revise the title, abstract, and discussion to provide more qualification and to consider alternative interpretations.

Some key controls are also missing, which could be addressed by repeat experiments in the mouse model. The antibiotic depletion experiment would be improved by testing the effect of antibiotics in the absence of metformin, to see if the effect is just driven by the model itself as opposed to an interaction between metformin and antibiotics. The FMT experiment lacks a control group and suffers from pseudoreplication: multiple donors from metformin treated and untreated mice could be used to colonize separate groups of recipient mice.

Reviewer #1 (Public Review):

The evolution of dioecy in angiosperms has significant implications for plant reproductive efficiency, adaptation, evolutionary potential, and resilience to environmental changes. Dioecy allows for the specialization and division of labor between male and female plants, where each sex can focus on specific aspects of reproduction and allocate resources accordingly. This division of labor creates an opportunity for sexual selection to act and can drive the evolution of sexual dimorphism.

In the present study, the authors investigate sex-biased gene expression patterns in juvenile and mature dioecious flowers to gain insights into the molecular basis of sexual dimorphism. They find that a large proportion of the plant transcriptome is differentially regulated between males and females with the number of sex-biased genes in floral buds being approximately 15 times higher than in mature flowers. The functional analysis of sex-biased genes reveals that chemical defense pathways against herbivores are up-regulated in the female buds along with genes involved in the acquisition of resources such as carbon for fruit and seed production, whereas male buds are enriched in genes related to signaling, inflorescence development and senescence of male flowers. Furthermore, the authors implement sophisticated maximum likelihood methods to understand the forces driving the evolution of sex-biased genes. They highlight the influence of positive and relaxed purifying selection on the evolution of male-biased genes, which show significantly higher rates of non-synonymous to synonymous substitutions than female or unbiased genes. This is the first report (to my knowledge) highlighting the occurrence of this pattern in plants. Overall, this study provides important insights into the genetic basis of sexual dimorphism and the evolution of reproductive genes in Cucurbitaceae.

Reviewer #2 (Public Review):

Summary:

This study uses transcriptome sequence from a dioecious plant to compare evolutionary rates between genes with male- and female-biased expression and distinguish between relaxed selection and positive selection as causes for more rapid evolution. These questions have been explored in animals and algae, but few studies have investigated this in dioecious angiosperms, and none have so far identified faster rates of evolution in male-biased genes (though see Hough et al. 2014 https://doi.org/10.1073/pnas.1319227111).

Strengths:

The methods are appropriate to the questions asked. Both the sample size and the depth of sequencing are sufficient, and the methods used to estimate evolutionary rates and the strength of selection are appropriate. The data presented are consistent with faster evolution of genes with male-biased expression, due to both positive and relaxed selection.

This is a useful contribution to understanding the effect of sex-biased expression in genetic evolution in plants. It demonstrates the range of variation in evolutionary rates and selective mechanisms, and provides further context to connect these patterns to potential explanatory factors in plant diversity such as the age of sex chromosomes and the developmental trajectories of male and female flowers.

Weaknesses:

The presence of sex chromosomes is a potential confounding factor, since there are different evolutionary expectations for X-linked, Y-linked, and autosomal genes. Attempting to distinguish transcripts on the sex chromosomes from autosomal transcripts could provide additional insight into the relative contributions of positive and relaxed selection.

Reviewer #3 (Public Review):

The potential for sexual selection and the extent of sexual dimorphism in gene expression have been studied in great detail in animals, but hardly examined in plants so far. In this context, the study by Zhao, Zhou et al. al represents a welcome addition to the literature.

Relative to the previous studies in Angiosperms, the dataset is interesting in that it focuses on reproductive rather than somatic tissues (which makes sense to investigate sexual selection), and includes more than a single developmental stage (buds + mature flowers).

Reviewer #1 (Public Review):

Summary: Translating discoveries from model organisms to humans is often challenging, especially in neuropsychiatric diseases, due to the vast gaps in the circuit complexities and cognitive capabilities. Kajtor et al. propose to bridge this gap in the fly models of Parkinson's disease (PD) by developing a new behavioral assay where flies respond to a moving shadow by modifying their locomotor activities. The authors believe the flies' response to the shadow approximates their escape response to an approaching predator. To validate this argument, they tested several PD-relevant transgenic fly lines and showed that some of them indeed have altered responses in their assay.

Strengths: This single-fly-based assay is easy and inexpensive to set up, scalable, and provides sensitive, quantitative estimates to probe flies' optomotor acuity. The behavioral data is detailed, and the analysis parameters are well-explained.

Weaknesses: While the abstract promises to give us an assay to accelerate fly-to-human translation, the authors need to provide evidence to show that this is indeed the case. They have used PD lines extensively characterized by other groups, often with cheaper and easier-to-setup assays like negative geotaxis, and do not offer any new insights into them. The conceptual leap from a low-level behavioral phenotype, e.g. changes in walking speed, to recapitulating human PD progression is enormous, and the paper does not make any attempt to bridge it. It needs to be clarified how this assay provides a new understanding of the fly PD models, as the authors do not explore the cellular/circuit basis of the phenotypes. Similarly, they have assumed that the behavior they are looking at is an escape-from-predator response modulated by the central complex- is there any evidence to support these assumptions? Because of their rather superficial approach, the paper does not go beyond providing us with a collection of interesting but preliminary observations.

Reviewer #2 (Public Review):

In this study, Kajtor et al investigated the use of a single-animal trial-based behavioral assay for the assessment of subtle changes in the locomotor behavior of different genetic models of Parkinson's disease of Drosophila. Different genotypes used in this study were Ddc-GAL4>UAS-Parkin-275W and UAS- α-Syn-A53T. The authors measured Drosophila's response to predator-mimicking passing shadow as a threatening stimulus. Along with these, various dopamine (DA) receptor mutants, Dop1R1, Dop1R2 and DopEcR were also tested.<br /> The behavior was measured in a custom-designed apparatus that allows simultaneous testing of 13 individual flies in a plexiglass arena. The inter-trial intervals were randomized for 40 trials within 40 minutes duration and fly responses were defined into freezing, slowing down, and running by hierarchical clustering. Most of the mutant flies showed decreased reactivity to threatening stimuli, but the speed-response behavior was genotype invariant.<br /> These data nicely show that measuring responses to the predator-mimicking passing shadows could be used to assess the subtle differences in the locomotion parameters in various genetic models of Drosophila.

The understanding of the manifestation of various neuronal disorders is a topic of active research. Many of the neuronal disorders start by presenting subtle changes in neuronal circuits and quantification and measurement of these subtle behavior responses could help one delineate the mechanisms involved. The data from the present study nicely uses the behavioral response to predator-mimicking passing shadows to measure subtle changes in behavior. However, there are a few important points that would help establish the robustness of this study.<br /> 1) The visual threat stimulus for measuring response behavior in Drosophila is previously established for both single and multiple flies in an arena. A comparative analysis of data and the pros and cons of the previously established techniques (for example, Gibson et al., 2015) with the technique presented in this study would be important to establish the current assay as an important advancement.<br /> 2) Parkinson's disease mutants should be validated with other GAL-4 drivers along with Ddc-GAL4, such as NP6510-Gal4 (Riemensperger et al., 2013). This would be important to delineate the behavioral differences due to dopaminergic neurons and serotonergic neurons and establish the Parkinson's disease phenotype robustly.<br /> 3) The DopEcR mutant genotype used for behavior analysis is w1118; PBac{PB}DopEcRc02142/TM6B, Tb1. Balancer chromosomes, such as TM6B,Tb can have undesirable and uncharacterised behavioral effects. This could be addressed by removing the balancer and testing the DopEcR mutant in homozygous (if viable) or heterozygous conditions.<br /> 4) The height of the arena is restricted to 1mm. However, for the wild-type flies (Canton-S) and many other mutants, the height is usually more than 1mm. Also, a 1 mm height could restrict the fly movement. For example, it might not allow the flies to flip upside down in the arena easily. This could introduce some unwanted behavioral changes. A simple experiment with an arena of height at least 2.5mm could be used to verify the effect of 1mm height.<br /> 5) The detailed model for Monte Carlo simulation for speed-response simulation is not described. The simulation model and its hyperparameters need to be described in more depth and with proper justification.<br /> 6) The statistical analysis in different experiments needs revisiting. It wasn't clear to me if the authors checked if the data is normally distributed. A simple remedy to this would be to check the normality of data using the Shapiro-Wilk test or Kolmogorov-Smirnov test. Based on the normality check, data should be further analyzed using either parametric or non-parametric statistical tests. Further, the statistical test for the age-dependent behavior response needs revisiting as well. Using two-way ANOVA is not justified given the complexity of the experimental design. Again, after checking for the normality of data, a more rigorous statistical test, such as split-plot ANOVA or a generalized linear model could be used.<br /> 7) The dopamine receptor mutants used in this study are well characterized for learning and memory deficits. In the Parkinson's disease model of Drosophila, there is a loss of DA neurons in specific pockets in the central brain. Hence, it would be apt to use whole animal DA receptor mutants as general DA mutants rather than the Parkinson's disease model. The authors may want to rework the title to reflect the same.

Reviewer #1 (Public Review):

Summary:<br /> The focus of this manuscript was to investigate the role of Cldn9 in the development of the mammalian cochlea. The main rationale of the study is the fact that cochlear hair cells do not regenerate, so when damaged they are lost forever, causing irreparable hearing loss. The authors have attempted to address this problem by inducing the ectopic production of additional hair cells and testing whether they acquire the morphological and functional characteristics of native hair cells. They show that downregulation of Cldn9 using a well-established genetic manipulation of transgenic mice led to the production of extra numerary inner hair cells, which were able to survive for several months. By performing a large battery of experiments, the authors were able to determine that the native and ectopic inner hair cells have comparable morphological and physiological characteristics. There are several conclusions highlighted by the authors in different parts of the manuscript, including the key role of Cldn9 in coordinating embryonic and postnatal development, the differentiation of supporting cells into inner hair cells, and the possible use of Cldn9 to induce inner hair cell differentiation following deafness induced by hair cell loss.

Strengths:<br /> Several of the conclusions in this study are well supported by the experimental work.

Weaknesses:<br /> Some aspects of the data and its interpretation needs better explanation and requires further investigation.

1) The Results section is the most difficult part to read and understand. It contains a very limited, and in some places confusing and repetitive, description of the data. Statistical analysis is missing for some of the key data (e.g., ABRs), and in some places the text contradicts the data presented in the figures (e.g., Figure 8). I am sure a careful revision of the text would clarify some of these issues.

2) One puzzling finding that is not addressed in the manuscript is the lack of functional benefit from these additional inner hair cells. In fact, it appears to be detrimental based on the increased ABR thresholds. Maybe it would be useful to analyze the wave 1 characteristics.

3) It is not clear what direct evidence there is, apart from some immunostaining, indicating that the ectopic inner hair cells derive from the supporting cells. This part would benefit from a more careful consideration and maybe an attempt at a more direct experimental approach.

4) One point that should be made clear throughout the manuscript is that the ectopic inner hair cells are generated in a cochlea that is undergoing normal maturation. Thus, there is no guarantee that modulating the expression levels of Cldn9 in a deaf mouse lacking hair cells would produce the same result as that shown in this study. My guess is that it probably won't, but I am sure this could be tested (maybe in the future) using the excellent experimental approach applied in this study.

Reviewer #2 (Public Review):

Summary:

The generation of functional extranumerary inner hair cells (IHCs) in postnatal mice, particularly with virus-mediated knockdown of Cldn9 mRNA expression in the neonatal cochlear duct, is an important observation. It is significant because not many studies exist that report molecular manipulations of the neonatal organ of Corti that result in the generation of new hair cells that remain functional and appear to be intact for an extended time, here more than one year. Overall, this is a carefully conducted study; the observations are clear, and the methods are solid. Two independent methods for reducing the expression of Cldn9 mRNA were used: a conditional transgenic model and AAV-mediated knockdown with shRNA. The lack of a functional explanation of how the reduced expression of Cldn9 specifically leads to the formation of extranumerary IHCs leaves open questions. For example, it is not clear whether there is indeed a fate change happening and whether Cldn9 reduction affects developmental processes. The discussion of how Cldn9 reduction potentially affects Notch signaling, without hard evidence, is handwaving.

Strengths:

It is a very interesting observation and somewhat unexpected in its specificity for inner hair cells. Using two different approaches to manipulate Cldn9 expression provides a strong experimental foundation. The study is conducted quantitatively and with care.

Weaknesses:

The lack of mechanistic insight results in an open-ended story where at least the potential interaction of Cldn9 reduction with known and well-characterized signaling pathway components should have been investigated. This missed opportunity limits the scope of the study and should be addressed: How does Cldn9 downregulation affect the expression levels of other known genes linked to hair cell production and cell fate decisions? Quantitative RT-PCR is working well for the authors, and a comparison of the expression of Notch or other known pathway components could provide mechanistic insight.

It is unclear how P21 inner hair cells were identified for the patch clamp experiments shown in Fig 4E-H. This is a challenging endeavor without the possibility of using specific markers.

Please also address the numerous minor points outlined below; it will improve the paper's readability.

Please include page numbers and line numbers in a revised manuscript.

Reviewer #3 (Public Review):

This important study by Chen et al help in advancing our knowledge about the regulation of inner hair cell (IHC) development and revealed the role of Cldn9 in IHC embryonic and postnatal induction by transdifferentiation from the supporting cells. The authors developed an inducible doxycycline (dox)-tet-OFF-Cldn9 transgenic mice to regulate expression levels of Cldn9 and show that downregulation of Cldn9 resulted in additional, although incomplete row of IHCs immediately adjacent to the original IHC row. These induced extra IHCs had similar well developed hair bundles, able to mechanotransduce and were innervated by auditory neurons resembling wild-type IHCs. In addition, the authors knock down Cldn9 postnatally using shRNA injections in P1-7 mice with similar induction of extranumerary IHC next to the original row of IHCs. The conclusions of this paper are mostly well supported by the data, but some data analysis needed to be clarified and some crucial controls should be provided to improve the confidence in the presented results. There is a great potential for practical use of these valuable findings and new knowledge on IHC developmental regulation to design Cldn9 gene therapy in the future.<br /> The described by Chen et al mechanisms of extra hair cell generation by suppression of the tight junction protein Cldn9 expression level are very interesting and previously unknown. In particular, the generation of extra IHCs postnatally using downregulation of Cldn9 by shRNA could potentially be very useful as a replacement of HCs lost after noise-induced trauma, ototoxic agents, or other environmental trauma. On the other hand, the replacement of lost hair cells due to various genetic mutations by inducing a supernumerary IHCs with the same abnormalities would not be reasonable.<br /> The authors show that postnatally generated ectopic IHCs are viable and mechanotransducive, but it would be nice to show the maturation steps of ectopic IHC during this postnatal period. For example, stereocilia bundles of the ectopic hair cells should mature later than the original IHCs. A few days after viral delivery of shRNA, you should be able to observe immature IHC bundles that unequivocally will define newly generated IHCs. Unfortunately, the authors show only examples of already mature ectopic IHCs at P21 and in 5-6 weeks old mice and at relatively low resolution. Also, during maturation, IHCs usually have transient axo-somatic synapses that are not present in mature IHCs. It would be great to see if, in 5-6 weeks old mouse, the ectopic IHCs still have axo-somatic synapses or not, and if the majority of the ectopic IHCs have innervation. Some of the data in this study would benefit from showing corresponding controls and some - from higher resolution imaging.<br /> In the mammalian cochlea, each HC is separated from the next by intervening supporting cells, forming an invariant and alternating mosaic along the cochlea's length. Cochlear supporting cells in some conditions can divide and trans-differentiate into HCs, serving as a potential resource for HC differentiation, using transcription and other developmental signaling factors.<br /> However, when ectopic hair cells are generated from supporting cell trans-differentiation, the intricate mosaic of the organ of Corti is altered, which could by itself lead to hearing issues. In case of downregulation of Cldn9, the extra row of IHCs seems to be positioned immediately adjacent to the original IHC row. It is not clear if the newly formed unusual junctions between the ectopic and original IHCs are sufficiently tight to prevent leakage of the endolymph to the basolateral surface of IHCs. Also, it is not clear if the other organ of Corti tight junctions could lose their tightness due to the downregulation of Cldn9, which could over time affect the endocochlear potential as shown by this study and hearing abilities.<br /> Importantly, CLDN9 immunofluorescence staining data that show cytoplasmic staining of supporting cells should be revisited and the organ of Corti schematics showing CLDN9 expression should be corrected, considering that CLDN9 localizes to the tight junctions of the reticular lamina as was shown by immunoEM in this study and described in previous publications (Kitajiri et al., 2004; Nakano et al., 2009, Ramzan et al., 2021).<br /> While the current version of the manuscript will be of interest to scientists working in the inner ear development and regeneration field, it could be more valuable to the hearing researchers outside this immediate field and perhaps developmental biologists and cell biologists after proper revision.

Reviewer #1 (Public Review):

MacDonald et al., investigated the consequence of double knockout of substance P and CGRPα on pain behaviors using a newly created mouse model. The investigators used two methods to confirm knockout of these neuropeptides: traditional immunolabeling and a neat in vitro assay where sensory neurons from either wildtype or double knock are co-cultured with substance P "sniffer cells", HEK cells stably expressing NKR1 (a substance P receptor), GCaMP6s and Gα15. It should be noted that functional assays confirming CGRPα knockout were not performed. Subsequently, the authors assayed double knockout mice (DKO) and wildtype (WT) mice in numerous behavioral assays using different pain models, including acute pain and itch stimuli, intraplanar injection of Complete Freund's Adjuvant, prostaglandin E2, capsaicin, AITC, oxaliplatin, as well as the spared nerve injury model. Surprisingly, the authors found that pain behaviors did not differ between DKO and WT mice in any of the behavioral assays or pain paradigms. Importantly, female and male mice were included in all analyses. These data are important and significant, as both substance P and CGRPα have been implicated in pain signaling, though the magnitude of the effect of a single knockout of either gene has been variable and/or small between studies.

The conclusions of the study are largely supported by the data; however, additional experimental controls and analyses would strengthen the authors claims.

1) The authors note that single knockout models of either substance P or CGRPα have produced variable effects on pain behaviors that are study-dependent. Therefore, it would have strengthened the study if the authors included these single knockout strains in a side-by-side analysis (in at least some of the behavioral assays), as has been done in prior studies in the field when using double- or triple-knockout mouse models (for example, see PMID: 33771873). If in the authors hands, single knockouts of either peptide also show no significant differences in pain behaviors, then the finding that double knockouts also do not show significant differences would be less surprising.

2) It is unclear why the authors only show functional validation of substance P knockout using "sniffer" cells, but not CGRPα. Inclusion of this experiment would have added an additional layer of rigor to the study.

3) The authors should be a bit more reserved in the claims made in the manuscript. The main claim of the study is that "CGRPα and substance P are not required for pain transmission." However, the authors also note that neuropeptides can have opposing effects that may produce a net effect of no change. In my view, the data presented show that double knockout of substance P and CGRPα do not affect somatic pain behaviors, but do not preclude a role for either of these molecules in pain signaling more generally. Indeed, the authors also note that these neuropeptides could be involved in nociceptor crosstalk with the immune or vascular systems to promote headache. The authors only assayed pain responses to glabrous skin stimulation. How the DKO mice would behave in orofacial pain assays, migraine assays, visceral pain assays, or bone/joint pain assays, for example, was not tested. I do not suggest the authors include these experiments, only that they address the limitations/weaknesses of their study more thoroughly.

4) A more minor but important point, the authors do not describe the nature of the WT animals used. Are the littermates or a separately maintained colony of WT animals? The WT strain background should be included in the methods section.

Reviewer #2 (Public Review):

Summary,<br /> The paper aimed to examine the effect of co-ablating Substance P and CGRPα peptides on pain using Tac1 and Calca double knockout (DKO) mice. The authors observed no significant changes in acute, inflammatory, and neuropathic pain. These results suggest that Substance P and CGRPα peptides do not play a major role in mediating pain in mice. Moreover, they reveal that the lack of behavioral phenotype cannot be explained by the redundancy between the two peptides, which are often co-expressed in the same neuron

Strengths,<br /> The paper uses a straightforward approach to address a significant question in the field. The authors confirm the absence of Substance P and CGRPα peptides at the levels of DRG, spinal cord, and midbrain. Subsequently, they employ a comprehensive battery of behavioral tests to examine pain phenotypes, including acute, inflammatory, and neuropathic pain. Additionally, they evaluate neurogenic inflammation by measuring edema and extravasation, revealing no changes in DKO mice. The data are compelling, and the study's conclusions are well-supported by the results. The manuscript is succinct and well-presented.

Reviewer #3 (Public Review):

In this study, the authors were assessing the role of double global knockout of substance P and CGPRα on the transmission of acute and chronic pain. The authors first generated the double knockout (DKO) mice and validated their animal model. This is then followed by a series of acute and chronic pain assessments to evaluate if the global DKO of these neuropeptides are important in modulating acute and chronic pain behaviors. Authors found that these DKO mice Substance P and CGRPα are not required for the transmission of acute and chronic pain although both neuropeptides are strongly implicated in chronic pain. This study does provide more insight into the role of these neuropeptides on chronic pain processing, however, more work still needs to be done. (see the comments below).

1. In assessing the double KO (result #1), why are different regions of the brains shown for substance P and CGRPα (for example, midbrain for substance P and amygdala for CGRPα)? Since the authors mentioned that these peptides co-expressed in the brain (as in the introduction), shouldn't the same brain regions be shown for both IHC? It would be ideal if the authors could show both regions (midbrain and amygdala) in addition to the DRG and spinal cord for both peptides in their findings.<br /> In addition, since this is double KO, the authors should show more representative IHC-stained brain regions (spanning from the anterior to posterior).<br /> 2. It is also unclear as to why the authors only assessed the loss of substance P signaling in the double KO mice. Shouldn't the same be done for CGRPα signaling? Either the authors assess this, or the authors have to provide clear explanations as to why only substance P signaling was assessed.<br /> 3. Has these animal's naturalistic behavior been assessed after the double KO (food intake, sleep, locomotion for example)? I think this is important as changes to these naturalistic behaviors can affect pain processes or outcomes.<br /> 4. Figure 2H: The authors acknowledge that there is a trend to decrease with capsaicin-evoked coping-like responses. However, a close look at the graph suggests that the lack of significance could be driven by 1 mouse. Have the authors run an outlier test? Alternatively, the authors should consider adding more n to these experiments to verify their conclusions.<br /> 5. Similarly, the values for WT in the evoked cFos activity (Figure 2- Suppl Figure 1) are pretty variable. Considering that the n number is low (n = 5), authors should consider adding more n.<br /> Also, since the n number is low in this experiment (eg. 5 vs 4), does this pass the normality test to run a parametric unpaired t-test? Either the authors increase their n numbers or run the appropriate statistical test.<br /> 6. In most of the results, authors ran a parametric test despite the low n number. Authors have to ensure that they are carrying out the appropriate statistical test for their dataset and n number.<br /> 7. Along the same line of comment with the previous, authors should increase the n number for DKO for staining (Figure 4) as n number is only 3 and there is variability in the cFos quantification in the ipsilateral side.<br /> 8. Authors should provide references for statement made in Line 319-321 as authors mentioned that there are accumulating evidence indicating that secretion of these neuropeptides from nociceptor peripheral terminals modulates immune cells and the vasculature in diverse tissues.<br /> 9. Authors state that the sample size used was similar to those from previous studies, but no references were provided. Also, even though the sample sizes used were similar, I believe that the right statistic test should be used to analyze the data.<br /> 10. In the discussion, the authors noted that knocking out of a gene remains the strongest test of whether the molecule is essential for a biological phenomenon. At the same time, it was acknowledged that Substance P infusion into the spinal cord elicits pain, but it is analgesic in the brain. The authors might want to expand more on this discussion, including how we can selectively assess the role of these neuropeptides in areas of interest. For example, knocking out both Substance P and CGRPα in selected areas instead of the global KO since there are reported compensatory effects.

Reviewer #1 (Public Review):

People can perform a wide variety of different tasks, and a long-standing question in cognitive neuroscience is how the properties of different tasks are represented in the brain. The authors develop an interesting task that mixes two different sources of difficulty, and find that the brain appears to represent this mixture on a continuum, in the prefrontal areas involved in resolving task difficulty. While these results are interesting and in several ways compelling, they overlap with previous findings and rely on novel statistical analyses that may require further validation.

Strengths<br /> 1. The authors present an interesting and novel task for combining the contributions of stimulus-stimulus and stimulus-response conflict. While this mixture has been measured in the multi-source interference task (MSIT), this task provides a more graded mixture between these two sources of difficulty.

2. The authors do a good job triangulating regions that encoding conflict similarity, looking for the conjunction across several different measures of conflict encoding. These conflict measures use several best-practice approaches towards estimating representational similarity.

3. The authors quantify several salient alternative hypothesis, and systematically distinguish their core results from these alternatives.

4. The question that the authors tackle is important to cognitive control, and they make a solid contribution.

Concerns<br /> 1. The framing of 'infinite possible types of conflict' feels like a strawman. While they might be true across stimuli (which may motivate a feature-based account of control), the authors explore the interpolation between two stimuli. Instead, this work provides confirmatory evidence that task difficulty is represented parametrically (e.g., consistent with literatures like n-back, multiple object tracking, and random dot motion). This parametric encoding is standard in feature-based attention, and it's not clear what the cognitive map framing is contributing.

2. The representations within DLPFC appear to treat 100% Stoop and (to a lesser extent) 100% Simon differently than mixed trials. Within mixed trials, the RDM within this region don't strongly match the predictions of the conflict similarity model. It appears that there may be a more complex relationship encoded in this region.

3. To orthogonalized their variables, the authors need to employ a complex linear mixed effects analysis, with a potential influence of implementation details (e.g., high-level interactions and inflated degrees of freedom).

Reviewer #2 (Public Review):

Summary<br /> This study examines the construct of "cognitive spaces" as they relate to neural coding schemes present in response conflict tasks. The authors use a novel experimental design in which different types of response conflict (spatial Stroop, Simon) are parametrically manipulated. These conflict types are hypothesized to be encoded jointly, within an abstract "cognitive space", in which distances between task conditions depend only on the similarity of conflict types (i.e., where conditions with similar relative proportions of spatial-Stroop versus Simon conflicts are represented with similar activity patterns). Authors contrast such a representational scheme for conflict with several other conceptually distinct schemes, including a domain-general, domain-specific, and two task-specific schemes. The authors conduct a behavioral and fMRI study to test whether prefrontal cortex activity is correlated to one of these coding schemes. Replicating the authors' prior work, this study demonstrates that sequential behavioral adjustments (the congruency sequence effect) are modulated as a function of the similarity between conflict types. In fMRI data, univariate analyses identified activation in left prefrontal and dorsomedial frontal cortex that was modulated by the amount of Stroop or Simon conflict present, and representational similarity analyses that identified coding of conflict similarity, as predicted under the cognitive space model, in right lateral prefrontal cortex.

Strengths

This study addresses an important question regarding how conflict or difficulty might be encoded in the brain within a computationally efficient representational format. Relative to the other models reported in the paper, the evidence in support of the cognitive space model is solid. The ideas postulated by the authors are interesting and valuable ones, worthy of follow-up work that provides additional necessary scrutiny of the cognitive-space account.

Weaknesses

Future, within-subject experiments will be necessary to disentangle the cognitive space model from confounded task variables. A between-subjects manipulation of stimulus orientation/location renders the results difficult to interpret, as the source and spatial scale of the conflict encoding on cortex may differ from more rigorous (and more typical) within-subject manipulations.

Results are also difficult to interpret because Stroop and Simon conflict are confounded with each other. For interpretability, these two sources of conflict need to be manipulated orthogonally, so that each source of conflict (as well as their interaction) could be separately estimated and compared in terms of neural encoding. For example, it is therefore not clear whether the RSA results are due to encoding of only one type of conflict (Stroop or Simon), to a combination of both, and/or to interactive effects.

Finally, the motivation for the use of the term "cognitive space" to describe results is unclear. Evidence for the mere presence of a graded/parametric neural encoding (i.e., the reported conflict RSA effects) would not seem to be sufficient. Indeed, it is discussed in the manuscript that cognitive spaces/maps allow for flexibility through inference and generalization. Future work should therefore focus on linking neural conflict encoding to inference and generalization more directly.

Reviewer #1 (Public Review):

Summary:<br /> This study is focused on an important aspect of axon guidance at the central nervous system (CNS) midline: how neurons extend axons that either do or do not cross the CNS midline. The authors here address contradictory work in the field relating to how cell surface expression of the slit receptor Robo1 is regulated to generate crossed and non-crossed axon trajectories during Drosophila neural development. They use fly genetics, cell lines, and biochemical assessments to define a complex consisting of the commissureless, Nedd4 and Robo1 proteins necessary for regulating Robo1 protein expression. This work resolves certain remaining questions in the field regarding midline axon guidance, with strengths outweighing weaknesses; however, addressing some of these weaknesses would strengthen this study.

Strengths:<br /> Strengths include:<br /> -The use of well-controlled genetic gain-of-function (overexpression) approaches in vivo in Drosophila to show that phosphorylation sites (there are 2, and this study allows for assessment of the contributions made by each) in the commissureless (Comm) protein are indeed required for Comm function with respect to regulating axon midline guidance via their role in directing Comm-mediated Robo1 ubiquitination and degradation in the lysosome.<br /> -The demonstration that in vitro, and in a sensitized genetic background in vivo, the Nedd4 ubiquitin ligase regulates Robo1 protein cell surface distribution and also midline axon crossing in vivo.<br /> -Important evidence here that serves to resolve many questions raised by previous studies (not from these authors) regarding how Robo1 is regulated by Comm and Nedd4 family ubiquitin ligases. Further, these results are likely to have implications for thinking about the regulation of midline guidance in more complex nervous systems.

Weaknesses:<br /> -The authors in part rely on GOF genetic approaches to infer roles for Comm and Nedd4, and this is understood in light of the lack of phenotypes in certain mutant backgrounds, providing evidence for their capabilities in these GOF paridigms. However, there are a few missed opportunities in some experiments that would allow for conclusions to be drawn regarding endogenous Comm function, some involving relatively simple inclusion of null mutants in the sensitized genetic backgrounds used here.<br /> -A weakness beyond the purview of revision but important to mention is that the authors chose not to complement their GOF experiments with gene editing approaches to generate endogenous PY mutant alleles of Comm that might have been useful in genetic interaction experiments directed toward revealing roles for endogenous Comm in the regulation of Robo1.<br /> -There are very minor concerns regarding protein expression levels in various experiments that should be easy to address.

Reviewer #2 (Public Review):

Summary:<br /> Sullivan and Bashaw delve into the mechanisms that drive neural circuit assembly, and specifically, into the regulation of cell surface proteins that mediate axon pathfinding. During nervous system development, axons must traverse a molecularly and physically complex extracellular milieu to reach their synaptic targets. A fundamental, conserved repulsive signaling pathway is initiated by the Slit-Robo ligand-receptor pair. Robo, expressed on axon growth cones, binds Slit, secreted by midline cells, to prevent "pre-crossing" and "re-crossing" of axons at the midline. To control this repulsion, Robo surface levels are tightly regulated. In Drosophila, Commissureless (Comm) downregulates Robo surface levels and is required for axon crossing at the midline. Several studies suggest that PY motifs in Comm are required to localize Robo to endosomes. PY motifs have been shown to bind WW-domain containing proteins including the ubiquitin ligase Nedd4 family, so the authors propose that Comm may regulate Robo through Nedd4 interactions. Previous studies have hinted at a role for Nedd4-mediated ubiquitination of Comm in the regulation of Robo localization, but there have also been conflicting data. For example, Comm mutants that are unable to be ubiquitinated mimic wild-type Comm, suggesting that ubiquitination of Comm is not required for regulation of Robo. The current study utilizes a suite of genetic analyses in Drosophila to resolve discrepancies pertaining to the mode of Comm-dependent regulation of Robo1 and proposes that Comm acts as an adapter for the Nedd4 ubiquitin ligase to recognize Robo1 as a substrate. The authors also demonstrate that Nedd4 is indeed required for midline crossing.

Strengths:<br /> While this work is more incremental rather than field-shifting, it is nonetheless an excellent example of a rigorous, thorough analysis that culminates in enriching our mechanistic understanding of how neurons regulate cell-surface receptors in a spatiotemporal manner to control fundamental steps of circuit wiring. The experimental approach is thorough, and the manuscript is extremely well-written.

Weaknesses:<br /> Some key experiments (eg. complex formation) were performed in cell culture in an overexpression background. Also, there was a missed opportunity to bolster the model proposed by using Comm PY mutants in several experiments. Finally, Comm PY domains are required for proper Comm localization in neurons, but corresponding Robo localization was not analyzed.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript reports a series of experiments examining category learning and subsequent generalization of stimulus representations across spatial and nonspatial domains. In Experiment 1, participants were first trained to make category judgments about sequences of stimuli presented either in nonspatial auditory or visual modalities (with feature values drawn from a two-dimensional feature manifold, e.g., pitch vs timbre), or in a spatial modality (with feature values defined by positions in physical space, e.g., Cartesian x and y coordinates). A subsequent test phase assessed category judgments for 'rotated' exemplars of these stimuli: i.e., versions in which the transition vectors are rotated in the same feature space used during training (near transfer) or in a different feature space belonging to the same domain (far transfer). Findings demonstrate clearly that representations developed for the spatial domain allow for representational generalization, whereas this pattern is not observed for the nonspatial domains that are tested. Subsequent experiments demonstrate that if participants are first pre-trained to map nonspatial auditory/visual features to spatial locations, then rotational generalization is facilitated even for these nonspatial domains. It is argued that these findings are consistent with the idea that spatial representations form a generalized substrate for cognition: that space can act as a scaffold for learning abstract nonspatial concepts.

Strengths:<br /> I enjoyed reading this manuscript, which is extremely well-written and well-presented. The writing is clear and concise throughout, and the figures do a great job of highlighting the key concepts. The issue of generalization is a core topic in neuroscience and psychology, relevant across a wide range of areas, and the findings will be of interest to researchers across areas in perception and cognitive science. It's also excellent to see that the hypotheses, methods, and analyses were pre-registered.

The experiments that have been run are ingenious and thoughtful; I particularly liked the use of stimulus structures that allow for disentangling of one-dimensional and two-dimensional response patterns. The studies are also well-powered for detecting the effects of interest. The model-based statistical analyses are thorough and appropriate throughout (and it's good to see model recovery analysis too). The findings themselves are clear-cut: I have little doubt about the robustness and replicability of these data.

Weaknesses:<br /> I have only one significant concern regarding this manuscript, which relates to the interpretation of the findings. The findings are taken to suggest that "space may serve as a 'scaffold', allowing people to visualize and manipulate nonspatial concepts" (p13). However, I think the data may be amenable to an alternative possibility. I wonder if it's possible that, for the visual and auditory stimuli, participants naturally tended to attend to one feature dimension and ignore the other - i.e., there may have been a (potentially idiosyncratic) difference in salience between the feature dimensions that led to participants learning the feature sequence in a one-dimensional way (akin to the 'overshadowing' effect in associative learning: e.g., see Mackintosh, 1976, "Overshadowing and stimulus intensity", Animal Learning and Behaviour). By contrast, we are very used to thinking about space as a multidimensional domain, in particular with regard to two-dimensional vertical and horizontal displacements. As a result, one would naturally expect to see more evidence of two-dimensional representation (allowing for rotational generalization) for spatial than nonspatial domains.

In this view, the impact of spatial pre-training and (particularly) mapping is simply to highlight to participants that the auditory/visual stimuli comprise two separable (and independent) dimensions. Once they understand this, during subsequent training, they can learn about sequences on both dimensions, which will allow for a 2D representation and hence rotational generalization - as observed in Experiments 2 and 3. This account also anticipates that mapping alone (as in Experiment 4) could be sufficient to promote a 2D strategy for auditory and visual domains.

This "attention to dimensions" account has some similarities to the "spatial scaffolding" idea put forward in the article, in arguing that experience of how auditory/visual feature manifolds can be translated into a spatial representation helps people to see those domains in a way that allows for rotational generalization. Where it differs is that it does not propose that space provides a *scaffold* for the development of the nonspatial representations, i.e., that people represent/learn the nonspatial information in a spatial format, and this is what allows them to manipulate nonspatial concepts. Instead, the "attention to dimensions" account anticipates that ANY manipulation that highlights to participants the separable-dimension nature of auditory/visual stimuli could facilitate 2D representation and hence rotational generalization. For example, explicit instruction on how the stimuli are constructed may be sufficient, or pre-training of some form with each dimension separately, before they are combined to form the 2D stimuli.

I'd be interested to hear the authors' thoughts on this account - whether they see it as an alternative to their own interpretation, and whether it can be ruled out on the basis of their existing data.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, L&S investigates the important general question of how humans achieve invariant behavior over stimuli belonging to one category given the widely varying input representation of those stimuli and more specifically, how they do that in arbitrary abstract domains. The authors start with the hypothesis that this is achieved by invariance transformations that observers use for interpreting different entries and furthermore, that these transformations in an arbitrary domain emerge with the help of the transformations (e.g. translation, rotation) within the spatial domain by using those as "scaffolding" during transformation learning. To provide the missing evidence for this hypothesis, L&S used behavioral category learning studies within and across the spatial, auditory, and visual domains, where rotated and translated 4-element token sequences had to be learned to categorize and then the learned transformation had to be applied in new feature dimensions within the given domain. Through single- and multiple-day supervised training and unsupervised tests, L&S demonstrated by standard computational analyses that in such setups, space and spatial transformations can, indeed, help with developing and using appropriate rotational mapping whereas the visual domain cannot fulfill such a scaffolding role.

Strengths:<br /> The overall problem definition and the context of spatial mapping-driven solution to the problem is timely. The general design of testing the scaffolding effect across different domains is more advanced than any previous attempts clarifying the relevance of spatial coding to any other type of representational codes. Once the formulation of the general problem in a specific scientific framework is done, the following steps are clearly and logically defined and executed. The obtained results are well interpretable, and they could serve as a good stepping stone for deeper investigations. The analytical tools used for the interpretations are adequate. The paper is relatively clearly written.

Weaknesses:<br /> Some additional effort to clarify the exact contribution of the paper, the link between analyses and the claims of the paper, and its link to previous proposals would be necessary to better assess the significance of the results and the true nature of the proposed mechanism of abstract generalization.

1) Insufficient conceptual setup: The original theoretical proposal (the Tolman-Eichenbaum-Machine, Whittington et al., Cell 2020) that L&S relate their work to proposes that just as in the case of memory for spatial navigation, humans and animals create their flexible relational memory system of any abstract representation by a conjunction code that combines on the one hand, sensory representation and on the other hand, a general structural representation or relational transformation. The TEM also suggests that the structural representation could contain any graph-interpretable spatial relations, albeit in their demonstration 2D neighbor relations were used. The goal of L&S's paper is to provide behavioral evidence for this suggestion by showing that humans use representational codes that are invariant to relational transformations of non-spatial abstract stimuli and moreover, that humans obtain these invariances by developing invariance transformers with the help of available spatial transformers. To obtain such evidence, L&S use the rotational transformation. However, the actual procedure they use actually solved an alternative task: instead of interrogating how humans develop generalizations in abstract spaces, they demonstrated that if one defines rotation in an abstract feature space embedded in a visual or auditory modality that is similar to the 2D space (i.e. has two independent dimensions that are clearly segregable and continuous), humans cannot learn to apply rotation of 4-piece temporal sequences in those spaces while they can do it in 2D space, and with co-associating a one-to-one mapping between locations in those feature spaces with locations in the 2D space an appropriate shaping mapping training will lead to the successful application of rotation in the given task (and in some other feature spaces in the given domain). While this is an interesting and challenging demonstration, it does not shed light on how humans learn and generalize, only that humans CAN do learning and generalization in this, highly constrained scenario. This result is a demonstration of how a stepwise learning regiment can make use of one structure for mapping a complex input into a desired output. The results neither clarify how generalizations would develop in abstract spaces nor the question of whether this generalization uses transformations developed in the abstract space. The specific training procedure ensures success in the presented experiments but the availability and feasibility of an equivalent procedure in a natural setting is a crucial part of validating the original claim and that has not been done in the paper.

2) Missing controls: The asymptotic performance in experiment 1 after training in the three tasks was quite different in the three tasks (intercepts 2.9, 1.9, 1.6 for spatial, visual, and auditory, respectively; p. 5. para. 1, Fig 2BFJ). It seems that the statement "However, our main question was how participants would generalise learning to novel, rotated exemplars of the same concept." assumes that learning and generalization are independent. Wouldn't it be possible, though, that the level of generalization depends on the level of acquiring a good representation of the "concept" and after obtaining an adequate level of this knowledge, generalization would kick in without scaffolding? If so, a missing control is to equate the levels of asymptotic learning and see whether there is a significant difference in generalization. A related issue is that we have no information on what kind of learning in the three different domains was performed, albeit we probably suspect that in space the 2D representation was dominant while in the auditory and visual domains not so much. Thus, a second missing piece of evidence is the model-fitting results of the ⦰ condition that would show which way the original sequences were encoded (similar to Fig 2 CGK and DHL). If the reason for lower performance is not individual stimulus difficulty but the natural tendency to encode the given stimulus type by a combo of random + 1D strategy that would clarify that the result of the cross-training is, indeed, transferring the 2D-mapping strategy.

Reviewer #3 (Public Review):

Summary:<br /> Pesnot Lerousseau and Summerfield aimed to explore how humans generalize abstract patterns of sensory data (concepts), focusing on whether and how spatial representations may facilitate the generalization of abstract concepts (rotational invariance). Specifically, the authors investigated whether people can recognize rotated sequences of stimuli in both spatial and nonspatial domains and whether spatial pre-training and multi-modal mapping aid in this process.

Strengths:<br /> The study innovatively examines a relatively underexplored but interesting area of cognitive science, the potential role of spatial scaffolding in generalizing sequences. The experimental design is clever and covers different modalities (auditory, visual, spatial), utilizing a two-dimensional feature manifold. The findings are backed by strong empirical data, good data analysis, and excellent transparency (including preregistration) adding weight to the proposition that spatial cognition can aid abstract concept generalization.

Weaknesses:<br /> The examples used to motivate the study (such as "tree" = oak tree, family tree, taxonomic tree) may not effectively represent the phenomena being studied, possibly confusing linguistic labels with abstract concepts. This potential confusion may also extend to doubts about the real-life applicability of the generalizations observed in the study and raises questions about the nature of the underlying mechanism being proposed.

Next, the study does not explore whether scaffolding effects could be observed with other well-learned domains, leaving open the question of whether spatial representations are uniquely effective or simply one instance of a familiar 2D space, again questioning the underlying mechanism.

Further doubt on the underlying mechanism is cast by the possibility that the observed correlation between mapping task performance and the adoption of a 2D strategy may reflect general cognitive engagement rather than the spatial nature of the task. Similarly, the surprising finding that a significant number of participants benefited from spatial scaffolding without seeing spatial modalities may further raise questions about the interpretation of the scaffolding effect, pointing towards potential alternative interpretations, such as shifts in attention during learning induced by pre-training without changing underlying abstract conceptual representations.

Conclusions:<br /> The authors successfully demonstrate that spatial training can enhance the ability to generalize in nonspatial domains, particularly in recognizing rotated sequences. The results for the most part support their conclusions, showing that spatial representations can act as a scaffold for learning more abstract conceptual invariances. However, the study leaves room for further investigation into whether the observed effects are unique to spatial cognition or could be replicated with other forms of well-established knowledge, as well as further clarifications of the underlying mechanisms.

Impact:<br /> The study's findings are likely to have a valuable impact on cognitive science, particularly in understanding how abstract concepts are learned and generalized. The methods and data can be useful for further research, especially in exploring the relationship between spatial cognition and abstract conceptualization. The insights could also be valuable for AI research, particularly in improving models that involve abstract pattern recognition and conceptual generalization.

In summary, the paper contributes valuable insights into the role of spatial cognition in learning abstract concepts, though it invites further research to explore the boundaries and specifics of this scaffolding effect.

Reviewer #1 (Public Review):

Summary: The authors explored correlations between taste features of botanical drugs used in ancient times and therapeutic uses, finding some potentially interesting associations between intensity and complexity of flavors and therapeutic potential, plus some more specific associations described in the discussion section. I believe the results could be of potential benefit for the drug discovery community, especially for those scientists working in the field of natural products.

Strengths:

Owing to its eclectic and somehow heterodox nature, I believe the article might be of interest for a general audience. In fact, I have enjoyed reading it and my curiosity was raised by the extensive discussion.

The idea of revisiting a classical vademecum with new scientific perspectives is quite stimulating.

The authors have undertaken a significant amount of work, collecting 700 botanical drugs and exploring their taste and association with known uses via eleven trained panellists.

Weaknesses:

I have some methodological concerns. Robustness in the panelists' perceptions has not been addressed, and not every panellist tasted every drug because of time constrains. The breaks between tasting different samples was not standardized, and depended on the persistence of chemosensory perception, possibly also due to time constraints.

Reviewer #2 (Public Review):

Summary:<br /> This is an unusual, but interesting approach to link the "taste" of plants and plant extracts to their therapeutic use in ancient Graeco-Roman culture. The authors used a panel of 11 trained tasters to test ~700 different medicinal plants and describe them in terms of 22 "taste" descriptors. They correlated these descriptors with the plant's medical use as reported in the De Materia Medica (DMM 1st Century, CE). Correcting for some of the plants' evolutionary phylogenetic relationships, the authors found that taste descriptors along with intensity measures were correlated with the "versatility" and/or a specific therapeutic use of the medicine. For example, simple but intense tastes were correlated with versatility of a medicine. Specific intense tastes were linked to versatility while others were not; intense bitter, starchy, musky, sweet, cooling and soapy were associated with versatility, but sour and woody were negatively associated. Also some specific tastes could be associated with specific uses - both positive and negative associations. Some of these findings make sense immediately, but others are somewhat surprising, and the authors propose some links between taste and medicinal use (both historical and modern use) in the discussion. The authors state that this study allows for a re-evaluation of pre-scientific knowledge, pointing toward a central role for taste in medicine.

Strengths:<br /> The real strength of this study is the novelty of this approach - using modern day tasters to evaluate ancient medicinal plants to understand the potential relationships between taste and therapeutic use, lending some support to the idea that the "taste" of a medicine is linked to its effectiveness as a treatment.

Weaknesses:<br /> Because of the limitations of time and the type of botanicals being tested, there is an inherent difficulty in assessing taste intensity. However, because these botanicals are tested by multiple panelists and sometimes tested repeatedly by individual panelists, this helps support the author's analyses.

Reviewer #1 (Public Review):

Summary:<br /> The authors set out to determine how chemical variation on kinase inhibitors determines selection of Erk2 conformations and how inhibitor binding affects ERk2 structure and dynamics.

Strengths:<br /> The study is beautifully presented both verbally and visually. The NMR experiments and the HDX experiments complement each other for the study of Erk2 solution dynamics. X-ray crystallography of Erk2 complexes with inhibitors show small but distinct structural changes that support the proposed model for the impact of inhibitor binding.

Reviewer #2 (Public Review):

Erk2 is an essential element of the MAP kinase signaling cascade and directly controls cell proliferation, migration, and survival. Therefore, it is one of the most important drug targets for cancer therapy. The catalytic subunit of Erk2 has a bilobal architecture, with the small lobe harboring the nucleotide-binding pocket and the large lobe harboring the substrate-binding cleft. Several studies by the Ahn group revealed that the catalytic domain hops between (at least) two conformational states: active (R) and inactive (L), which exchange in the millisecond time scale based on the chemical shift mapping. The R state is a signature of the double phosphorylated Erk2 (2P-Erk2), while the L state has been associated with the unphosphorylated kinase (0P-Erk2). Interestingly, the X-ray structures reveal only minimal differences between these two states, a feature that led to the conclusion that active and inactive states are structurally similar but dynamically very different. The Ahn group also found that ATP-competitive inhibitors can steer the populations of Erk2 either toward the R or the L state, depending on their chemical nature. The latter opens up the possibility of modulating the activity of this kinase by changing the chemistry of the ATP-competitive inhibitor. To prove this point, the authors present a set of nineteen compounds with diverse chemical substituents. From their combined NMR and HDX-Mass Spec analyses, fourteen inhibitors drive the kinase toward the R state, while four compounds keep the kinase hopping between the R and L states. Based on these data, the authors rationalize the effects of these inhibitors and the importance of the nature of the substituents on the central scaffold to steer the kinase activity. While all these inhibitors target the ATP binding pocket, they display diverse structural and dynamic effects on the kinase, selecting a specific structural state. Although the inhibited kinase is no longer able to phosphorylate substrates, it can initiate signaling events functioning as scaffolds for other proteins. Therefore, by changing the chemistry of the inhibitors it may be possible to affect the MAP cascade in a predictable manner. This concept, recently introduced as proof of principle, finds here its significance and practical implications. The design of the next-generation inhibitors must be taken into account for these design principles.<br /> The research is well executed, and the data support the author's conclusions.

Reviewer #3 (Public Review):

Summary:<br /> Anderson at al utilize an array of orthogonal techniques to highlight the important of protein dynamics for the function and inhibition of the kinase ERK2. ERK2 is important for a large variety of biological functions.

Strengths:<br /> This is a thorough and detailed study that uses a variety of techniques to identify critical molecular/chemical parameters that drive ERK2 in specific states.

Weaknesses:<br /> No details rules were identified so that novel inhibitors could be designed. Nevertheless, the mode of action of these existing inhibitors are much better defined.

Reviewer #1 (Public Review):

Specifically controlling the level of proteins in bacteria is an important tool for many aspects of microbiology, from basic research to protein production. While there are several established methods for regulating transcription or translation of proteins with light, optogenetic protein degradation has so far not been established in bacteria. In this paper, the authors present a degradation sequence, which they name "LOVdeg", based on iLID, a modified version of the blue-light-responsive LOV2 domain of Avena sativa phototropin I (AsLOV2). The authors reasoned that by removing the three C-terminal amino acids of iLID, the modified protein ends in "-E-A-A", similar to the "-L-A-A" C-terminus of the widely used SsrA degradation tag. The authors further speculated that, given the light-induced unfolding of the C-terminal domain of iLID and similar proteins, the "-E-A-A" C-terminus would become more accessible and, in turn, the protein would be more efficiently degraded in blue light than in the dark.

Indeed, several tested LOVdeg-tagged proteins show clearly lower cellular levels in blue light than in the dark. Depending on the nature and expression level of the target protein, protein levels are reduced modestly to strongly (2 to 20x lower levels upon illumination). Accordingly, the authors propose to use their system in combination with other light-controlled expression systems and provide data validating this approach. The LOVdeg system allows to modulate protein levels to a similar degree and with comparable kinetics as optogenetic systems controlling transcription or translation of protein, and can be combined with such systems.

The manuscript and the figures are generally very well-composed and follow a clear structure. The schematics nicely explain the underlying principles. Besides the advantages of the LOVdeg approach, including its complementarity to controlled expression of proteins, the revised version of the manuscript also highlights the limitations of the method more clearly, e.g., (i) the need to attach a C-terminal tag of considerable size to the protein of interest, (ii) the limited efficiency (slightly less efficient and slower than EL222, a light-dependent transcriptional control mechanism), and (iii) the incompletely understood prerequisites for its application. Taken together, this manuscripts describes the LOVdeg system as a valuable addition to the tool box for controlling protein levels in prokaryotic cells.

Reviewer #2 (Public Review):

In this manuscript the authors present and characterize LOVdeg, a modified version of the blue-light sensitive AsLOV2 protein, which functions as a light-inducible degron in Escherichia coli. Light has been shown to be a powerful inducer in biological systems as it is often orthogonal and can be controlled in both space and time. Many optogenetic systems target regulation of transcription, however in this manuscript the authors target protein degradation to control protein levels in bacteria. This is an important advance in bacteria, as inducible protein degradation systems in bacteria have lagged behind eukaryotic systems due to protein targeting in bacteria being primarily dependent on primary amino acid sequence and thus more difficult to engineer. In this manuscript, the authors exploit the fact that the J-alpha helix of AsLOV2, which unwinds into a disordered domain in response to blue light, contains an E-A-A amino acid sequence which is very similar to the C-terminal L-A-A sequence in the SsrA tag which is targeted by the unfoldases ClpA and ClpX. They truncate AsLOV2 to create AsLOV2(543) and combine this truncation with a mutation that stabilizes the dark state to generate AsLOV2*(543) which, when fused to the C-terminus of mCherry, confers light-induced degradation. The authors do not verify the mechanism of degradation due to LOVdeg, but evidence from deletion mutants contained in the supplemental material hints that there is a ClpA dominated mechanism. The LOVdeg is able to target mCherry for protein degradation across different phases of bacterial growth, which is important for regulating processes at stationary phase and a potential additional advantage over transcriptional repression systems. They demonstrate modularity of this LOVdeg by using it to degrade the LacI repressor, CRISPRa activation through degradation of MCP-SoxS, and the AcrB protein which is part of the AcrAB-TolC multidrug efflux pump. In all cases, measurement of the effect of the LOVdeg is indirect as the authors measure reduction in LacI repression, reduction in CRISPRa activation, and drug resistance rather than directly measuring protein levels. Nevertheless the evidence is convincing, although seemingly less effective than in the case of mCherry degradation, although it is hard to compare due to the different endpoints being measured. The authors further modify LOVdeg to contain a known photocycle mutation that slows its reversion time in the dark, so that LOVdeg is more sensitive to short pulses of light which could be useful in low light conditions or for very light sensitive organisms. They also demonstrate that combining LOVdeg with a blue-light transcriptional repression system (EL222) can decrease protein levels an additional 23-fold (relative to 7-fold with LOVdeg alone). Finally, the authors apply LOVdeg to a metabolic engineering task, namely reducing expression of octanoic acid by regulating the enzyme CpFatB1, an acyl-ACP thioesterase. The authors show that tagging CpFatB1 with LOVdeg allows light induced reduction in octanoic acid titer over a 24 hour fermentation. In particular, by comparing control of CpFatB1 with EL222 transcriptional repression alone, LOVdeg, or both the authors show that light-induced protein degradation is more effective than light-induced transcriptional repression. The authors suggest that this is because transcriptional repression is not effective when cells are at stationary phase (and thus there is no protein dilution due to cell division). Overall, the authors have generated a modular, light-activated degron tag for use in Escherichia coli that is likely to be a useful tool in the synthetic biology and metabolic engineering toolkit.

Reviewer #3 (Public Review):

The authors present the mechanism, validation, and modular application of LOVtag, a light-responsive protein degradation tag that is processed by the native degradosome of Escherichia coli. Upon exposure to blue light, the c-terminal alpha helix unfolds, essentially marking the protein for degradation. The authors demonstrate the engineered tag is modular across multiple complex regulatory systems, which shows its potential widespread use throughout the synthetic biology field. The step-by-step rational design of identifying the protein that was most dark-stabilized as well as most light-responsive for degradation, was useful in terms of understanding the key components of this system. The most compelling data shows that the engineered LOVTag can be fused to multiple proteins and achieve light-based degradation, without affecting the original function of the fused protein.

Reviewer #1 (Public Review):

In the manuscript "Mechanistic target of rapamycin (mTOR) pathway in Sertoli cells regulates age-dependent changes in sperm DNA methylation", the authors proposed to test if the balance of mTOR complexes in Sertoli cells may play a significant role in age-dependent changes in the sperm epigenome. The paper could be of interest and has a good scientific aim but there are too many drawbacks that hamper the initial enthusiasm. All sections need extensive revision. The paper is mostly descriptive without a mechanistic-orientated explanation for the observed results.

Specific comments:

1. The abstract is poorly written. There is a lot of unnecessary introduction that does not provide a rationale for the work. It is not possible to understand the experimental approach or the major data just by reading the abstract. It does not clearly represent the work.

2. The introduction is somewhat vague and does not provide a clear rationale for the hypothesis. There should be more focus more on the role of mTOR in Sertoli cells that goes far beyond BTB. That will give more focus on mTOR. Then it is important to focus on BTB and mTOR: what is known? What is the gap and how can it be solved? Several relevant references are missed concerning mTOR and Sertoli cells.

3. The Material and Methods section needs improvement. There is much important information missing. For instance: how many animals were used per group and how was the breeding done? At what age? Statistical analysis should be explained in detail.

4. The results description could be improved. It is vague without highlighting how much difference was detected. The results should be numerically described when possible and the differences should be highlighted. A 10% difference may be significant but not biologically relevant. To correctly evaluate the differences it is important to describe them with some degree of detail.

5. There is no discussion of the data. The authors just summarize their findings without a comprehensive analysis of the literature and how the effects can be mediated. mTOR interacts with different pathways (mTORC1 and mTORC2 are even mediators of distinct pathways). This would be very relevant to discuss. In addition, there are many study limitations not discussed. There is no clear mechanistic explanation of the way by which the mTOR pathway in Sertoli cells regulates age-dependent changes in sperm DNA methylation. The paper seems preliminary.

6. Figure 1 is too simple and does not provide any schematic support for the text.

7. Figure 2 lacks some detail. For instance, how many animals were used for each step?

8. Taking into consideration the roles of mTOR on sperm, particularly mTORC1, it is not clear whether there were any differences in sperm motility.

Reviewer #2 (Public Review):

In this study, the authors hypothesized that the balance of mTOR complexes in Sertoli cells may also play a significant role in age-dependent changes in the sperm epigenome. To test this hypothesis, the authors use transgenic mice with manipulated activity of mTOR complexes in Sertoli cells. These results suggest that the mTOR pathway in Sertoli cells may be used as a novel target of therapeutic interventions to rejuvenate the sperm epigenome in advanced-age fathers.

The authors attempt to demonstrate that the balance of mTOR complexes in Sertoli cells regulates the rate of sperm epigenetic aging. The authors have effectively met their research objectives, and their conclusions are supported by the data presented.

Reviewer #3 (Public Review):

Summary and Strength:

The manuscript by Amir et al. describes that Sertoli-specific inactivation of the mTORC1 and mTORC2 complex by KO of either Raptor or Rictor, respectively, resulted in progressive changes in blood-testis-barrier (BTB) function, testis weight, and sperm parameters, including counts, morphology, mtDNA content and sperm DNA methylation.

The described studies are based on the hypothesis that a decline of BTB function with increasing chronological age of a male contributes to the DNA methylation changes that are known to occur in sperm DNA of old males when compared to sperm DNA from isogenic young males. In order to demonstrate the relevance of a functioning BTB for the maintenance of sperm methylation patterns, the authors generated mice with genetically disrupted mTORC2 complex or mTORC1 complex in Sertoli cells and determined sperm methylation patterns in comparison to isogenic wild-type males. In line with previously published scientific literature (e.g. Mok et al., 2013; Dong et al, 2015; and others), the manuscript corroborates that a Sertoli-cell specific deletion of mTORC2 caused a loss of BTB function and a progressive spermatogenic defect. The authors further show that sperm DNA is differentially methylated (DMRs) as a consequence of either a mTORC2 disruption (associated with a loss of BTB function) or following a mTORC1 disruption (BTB function either increased or not leaky) when compared to their isogenic age-matched wt controls. Those DMRs overlap partially with changes in sperm DNA methylation that were found when comparing sperm from 8-week males with sperm isolated from 22-week-old male mice.

The authors interpret the observed changes as representative of the sperm DNA methylation changes that occur during normal chronological aging of the male. For an aged control group, the authors use sperm DNA of 22-week-old wild-type mates from the mTORC2 and mTORC2 KO breeding and compare the sperm methylation patterns found in sperm from those 22-week males to 8-week young males, that are intended to represent an old and a young cohort, respectively. DNA methylation analysis indicates that a disruption of mTORC2 (& decrease of BTB function) results in increased DNA methylation of sperm DNA, while a disruption of mTORC1 (and proposed increase of BTB tightness, not shown in the manuscript, though) resulted in increased hypomethylation.

Weaknesses:

While the hypothesis and experimental system are interesting and the data demonstrating the relevance of the mTORC2 complex for BTB function is convincing, several open questions limit the evidence that supports the hypothesis that the sperm DNA methylation changes seen in old males are caused by BTB failure following an imbalance of mTOR signaling complexes. The major critique points are the lack of a chronologically old group and the choice of 8 weeks & 22 weeks age of age:

- Data illustrating the degree of BTB decline and sperm DNA methylation changes from chronologically "old" male mice is missing. 22-week-old mice are not considered old but are of good and mature breeding age, equivalent to humans in their mid-late twenties. (In the manuscript, the 22-week-old wildtype mice show no evidence of BTB breakdown (Figure 3), so why are their sperm used to represent "aged" sperm?

- Adding a group of "old" wild-type mice of 12-14 months of age, which is closer to the end of effective reproduction in mice, more equivalent to 45-59 year-old humans) could be used to illustrate that (a) aging causes a marked decrease in BTB function at this time in mouse life, and that this BTB breakdown chronologically aligns with the age-associated DNA hypermethylation seen in old sperm. Age-matched "old" mTORC1 KO, with a (supposedly) tighter BTB barrier, could then be expected to have a sperm DMA methylation profile closer to that of younger wild-type animals. Such data are currently missing. While the progressive testicular decline observed in the mTORC1 KO (Fig.5) could make it difficult to obtain the appropriately aged mTORC1 KO tissues, it is completely feasible to obtain data from chronologically old wild-type males. (The progressive testicular decline further raises the question of what additional defects the KO causes, and how such additional defects would influence the sperm DNA methylation profile.) The addition of data from an old group to the currently included groups could strengthen the interpretation that the observations in the BTB-defective mTORC2 KO mice are modelling an age-related testicular decline, provided that the DMRs seen in the chronologically old group significantly overlap with the BTB-defective changes.

- In the current form, the described differences in sperm DNA methylation are based on comparisons between pubertal mice (8 weeks) and mature but not old adult males (22 weeks), while a chronologically "old" group is missing from the data sets and comparisons. Thus, it appears that the described sperm methylation changes reflect developmental changes associated with normal maturation and not necessarily declining sperm quality due to aging. (Sperm obtained from 8-week-old mice likely were generated, at least in part, during the 1st wave of spermatogenesis, which is known to differ from the continuously proceeding spermatogenesis during the remained of the mature life. During the 1st wave of spermatogenesis, Sertoli cells are known to undergo gene expression changes which could contribute to varying degrees of BTB function, and thus have effects on the sperm DNA methylation profiles of such 1st wave sperm.)

- It is unclear why the aging-related DMRs between the 8 and 22-week-old wild-type mice vary so dramatically between the two wild-type groups derived from the mTORC1 and the mTORC2 breeding (Fig. S4). If the main difference was due to mTORC1 or mTORC2 activity, both wildtype groups should behave very similarly. Changes seen in a truly "old" mouse (e.g. 20 weeks to 56 weeks), changes in "young mTORC1" and in "old mTORC2" are missing. How do those numbers and profiles compare to the shown samples?

Some general comments regarding the chosen age of animals:

- As mentioned, sperm from 8-week-old mice represent many sperm that were produced in the 1st wave of spermatogenesis; 22-week-old mice are not considered chronologically old mice, but mature and "relatively" young animals. 18-24 month-old mice are considered to be equivalent to 56-69 year-old humans, and might be more suitable to detect aging effects. "Old mice" for study purposes should be at least 12-14 months of age, ideally >18 months of age. 22 weeks (5 months of age) are mice at good breeding age, but still considered mature adults, not old males, and therefore are not expected to show typical aging health problems (like declining fertility).

Even the cited reference (Flurkey et al. 2007) defines that "... mice used a reference group for "young mice" should be at least 3 months of age (~ 13 weeks), i.e. fully sexually mature. The authors specifically state: " The young adult group should be at least 3 months old because, although mice are sexually mature by 35 days, relatively rapid maturational growth continues for most biologic processes and structures until about 3 months. The upper age range for the young adult group is typically about 6 months. ... For the middle-aged group, 10 months is typically the lower limit.... The upper age limit for the middle-aged group is typically 14-15 months, because at this age, most biomarkers still have not changed to their full extent, and some have not yet started changing. For the old group, the lower age limit is 18 months because age-related change for almost all biomarkers of aging can be detected by then. The upper limit is 22-26 months, depending on the genotype." According to this reference, mice up to 6 months of age are generally considered "mature adults" (equivalent to humans 20-30 yrs), mice of 10-14 month are "middle-aged adults" (equivalent to ~38-47 human years) and 18-24 month mice are "old" (equivalent to human of 56-69 yrs.).

Going on these commonly used age ranges, it is unclear why the authors used 8-week-old mice (generally considered pubertal to late adolescent age) as young mice and 5-month-old mice as "old mice".

Differences seen between these cohorts most likely do not reflect aging, but more likely reflect changes associated with normal developmental maturation, since testis and epididymides continue to grow until about 10-11 weeks of age.

- The DMRs identified between 8 and 22-week-old animals could represent DMRs that are dependent on developmental maturation more than being changed in an "age-dependent" manner (in the sense of increased chronological age). This interpretation is congruent with the fact that those DMRs are enriched for developmental categories.

Reviewer #1 (Public Review):

The molecular interactions that determine infection (and disease) trajectory following human exposure to Mycobacterium tuberculosis (Mtb) are critical to understanding mycobacterial pathogenicity and tuberculosis (TB), a global public health threat that disproportionately impacts a number of high-burden countries and, owing to the emergence of multidrug-resistant Mtb strains, is a major contributor to antimicrobial resistance (AMR). In this submission, Qin and colleagues extend their own previous work which identified a potential role for host galectin-9 in recognizing the major Mtb cell wall component, arabinogalactan (AG). First, the authors present data indicating that galectin-9 inhibits mycobacterial growth during in vitro culture in liquid and on solid media and that the inhibition depends on carbohydrate recognition by galectin-9. Next, the authors identify anti-AG antibodies in sera of TB patients and use this observation to inform isolation of monoclonal anti-AG antibodies (mAbs) via an in vitro screen. Finally, they apply the identified anti-AG mAbs to inhibit Mtb growth in vitro via a mechanism that proteomic and microscopic analyses suggest is dependent on the disruption of the cell wall structure. In summary, the dual observation of (i) the apparent role of naturally arising host anti-AG antibodies to control infection and (ii) the potential utility of anti-AG monoclonal antibodies as novel anti-Mtb therapeutics is compelling; however, as noted in the comments below, the evidence presented to support these insights is inadequate and the authors should address the following:

1. The experiment that utilizes lactose or glucose supplementation to infer the importance of carbohydrate recognition by galectin-9 cannot be interpreted unequivocally owing to the growth-enhancing effect of lactose supplementation on Mtb during liquid culture in vitro.

2. Similar to the comment above, the apparent dose-independent effect of galectin-9 on Mtb growth in vitro is difficult to reconcile with the interpretation that galectin is functioning as claimed.

3. The claimed differences in galectin-9 concentration in sera from tuberculin skin test (TST)-negative or TST-positive non-TB cases versus active TB patients are not immediately apparent from the data presented.

4. Neither fluorescence microscopy nor electron microscopy analyses are supported by high-quality, interpretable images which, in the absence of supporting quantitative data, renders any claims of anti-AG mAb specificity (fluorescence microscopy) or putative mAb-mediated cell wall swelling (electron microscopy) highly speculative.

5. Finally, the absence of any discussion of how anti-AG antibodies (similarly, galectin-9) gain access to the AG layer in the outer membrane of intact Mtb bacilli (which may additionally possess an extracellular capsule/coat) is a critical omission - situating these results in the context of current knowledge about Mtb cellular structure (especially the mycobacterial outer membrane) is essential for plausibility of the inferred galectin-9 and anti-AG mAb activities.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors work to extend their previous observation that galectin-9 interacts with arabinogalactans of Mtb in their EMBO reports 2021 manuscript. Here they provide evidence that the CARD2 domain of galectin-9 can inhibit the growth of Mtb in culture. In addition, antibodies that also bind to AG appear to inhibit Mtb growth in culture. These data indicate that independent of the common cell-associated responses to galectin-9 and antibodies, the interaction of these proteins with AG of mycobacteria may have consequences for bacterial growth.

Strengths:

The authors provided several lines of evidence in culture media that the introduction of galectin-9 proteins and antibodies inhibits the growth rate of Mtb.

Weaknesses:

In light of other observations that cleaved galectin-9 levels in the plasma is a biomarker for severe infection (Padilla A et al Biomolecules 2021 and Iwasaki-Hozumi H et al. Biomoleucles 2021) it is difficult to reconcile the author's interpretation that the elevated gal-9 in Active TB patients (Figure 1E) contributes to the maintenance of latent infection in humans. The authors should consider incorporating these observations in the interpretation of their own results.

The anti-AG titers were measured only in individuals with active TB (Figure 3C), generally thought to be a less protective immunological state. The speculation that individuals with anti-AG titers have some protection is not founded. Further only 2 mAbs were tested to demonstrate restriction of Mtb in culture. It is possible that clones of different affinities for AG present within a patient's polyclonal AG-antibody responses may or may not display a direct growth restriction pressure on Mtb in culture. The authors should soften the claims about the presence of AG-titers in TB patients being indicative of protection.

Reviewer #1 (Public Review):

Summary:

The authors report on the development of the first cord blood DNA methylation score to capture the epigenetic effects of maternal smoking. The score was built in a White European cohort and tested in White European and South Asian ancestry cohorts. Additionally, epigenome-wide association studies were conducted to quantify the impact of maternal smoking on newborn health.

Strengths:

The main strengths include the use of multiple cohorts of different ancestries. This is also the first study to build a cord blood predictor of maternal smoking.

Weaknesses:

The manuscript could benefit from a more detailed description of methods, especially those used to derive MRS for maternal smoking, which appears to involve overfitting. In particular, the addition of a flow chart would be very helpful to guide the reader through the data and analyses. The FDR correction in the EWAS corresponds to a fairly liberal p-value threshold.

Reviewer #2 (Public Review):

Summary:

The authors generated a DNA methylation score in cord blood for detecting exposure to cigarette smoke during pregnancy. They then asked if it could be used to predict height, weight, BMI, adiposity, and WHR throughout early childhood.

Strengths:

The study included two cohorts of European ancestry and one of South Asian ancestry.

Weaknesses:

1. The number of mothers who self-reported any smoking was very low, much lower than in the general population and practically non-existent in the South Asian population. As a result, all analyses appeared to have been underpowered. It is possibly for this reason that the authors chose to generate their DNA methylation model using previously published summary statistics. The resulting score is not of great value in itself due to the low-powered dataset used to estimate covariance between CpG sites. In fact, a score was generated for a much larger, better-powered dataset several years ago (Reese, EHP, 2017, PMID 27323799).

2. The conclusion that "even minimal smoking exposure in South Asian mothers who were not active smokers showed a DNAm signature of small body size and low birthweight in newborns" is not warranted because no analyses were performed to show that the association between DNA methylation and birth size/weight was driven by maternal smoking.

3. Although it was likely that some mothers were exposed to second-hand smoke and/or pollution, data on this was either non-existent or not included in this study. Including this would have allowed a more novel investigation of the effects of smoke exposure on the pregnancies of non-smoking mothers.

4. One of the European cohorts and half of the South Asian cohort had DNA methylation measured on only 2500 CpG sites. This set of sites included only 125 sites previously linked to prenatal smoking. The resulting model of prenatal smoking was small (only 11 CpG sites). It is possible that a large model may have been more powerful.

5. The health outcomes investigated are potentially interesting but there are other possibly more important outcomes of interest such as birth complications, asthma, and intellectual impairment which are known to be associated with prenatal smoking.

Reviewer #1 (Public Review):

Summary:<br /> Starting from an unbiased search for somatic mutations (from COSMIC) likely disrupting binding of clinically approved antibodies the authors focus on mutations known to disrupt binding between two ERBB2 mutations and Pertuzamab. They use a combined computational and experimental strategy to nominate a position that when mutated could result in restoring the therapeutic activity of the antibody. Using in vitro assays the authors confirm that the engineered antibody binds to the mutant ERBB2 and prevents ERBB3 phosphorylation

Strengths:<br /> 1. In my assessment, the data sufficiently demonstrates that a modified version of Pertuzamab can bind both the wild-type and S310 mutant forms of ERBB2.

2. The engineering strategy employed is rational and effectively combines computational and experimental techniques.

3. Given the clinical activity of HER2-targeting ADCs, antibodies unaffected by ERBB2 mutations would be desired.

Weaknesses:<br /> 1. There is no data showing that the engineered antibody is equally specific as Pertuzamab i.e. that it does not bind to other (non-ERBB2) proteins.

2. There is no data showing that the engineered antibody has the desired pharmacokinetics/pharmacodynamics properties or efficacy in vivo.

3. Computational approaches are only used to design a phage-screen library, but not used to prioritize mutations that are likely to improve binding (e.g. based on predicted impact on the stability of the interaction). A demonstration of how computational pre-screening or lead optimization can improve the time-intensive process would be a welcome advance.

Context:<br /> The conflict of interest statement is inadequate. Most authors of the study (but not the first author) are employees of Biolojic, a company developing multi-specific antibodies, but the statements do not clarify whether the presented antibodies represent Biolojic IP, whether the company sponsored the research, and whether the company is further developing the specific antibodies presented.

Reviewer #2 (Public Review):

Summary:<br /> Peled et al identified HER2 mutations in connection with resistance to the anti-HER2 antibody Pertuzumab-mediated therapy. After constructing a yeast display library of Pertuzumab variants with 3.86×1011 sequences for targeted screening of variant combinations in chosen 6 out of 14 residues, the authors performed experimental screening to obtain the clones that bind to HER2 WT and/or mutants (S310Y and S310F), and then combined new variations to obtain antibodies with a broad spectrum binding to both WT and two HER2 mutants. These are interesting studies of clinical impact and translational potential.

Strengths:<br /> 1. Deep computational analyses of large datasets of clinical data provide useful information about HER2 mutations and their potential relevance to antibody therapy resistance.

2. There is valuable information analyzing the residues within or near the interface between the antigen HER2 and the Pertuzumab antibody (heavy chain). The experimental antibody library screening obtained 90+ clones from 3.86×1011 sequences for further functional validation.

Weaknesses:<br /> 1. There is a lack of assessment for antibody variant functions in cancer cell phenotypes in vitro (proliferation, cell death, motility) or in vivo (tumor growth and animal survival). The only assay was the western blotting of phosphopho-HER3 in Figure 4. However, HER2 levels and phosphor-HER2 were not analyzed.

2. There is a misleading impression from the title of computational engineering of a therapeutic antibody and the statement in the abstract "we designed a multi-specific version of Pertuzumab that retains original function while also bindings these HER2 variants" for a few reasons:<br /> a. The primary method used for variant antibody identification for HER2 mutant binding is rather traditional experimental screening based on yeast display instead of the computational design of a multi-specific version of Pertuzumab.<br /> b. There is insufficient or lack of computational power in the antibody design or prioritization in choosing variant residues for the library construction of 3.86×1011 sequences. It seems random combinations from 6 residues out of 4 groups with 20 amino acid options.<br /> c. The final version of the tri-binding variant is a combination of screened antibody clones instead of computation design from scratch.<br /> d. There is incomplete experimental evidence about the therapeutic values of newly obtained antibody clones.

3. Figures can be improved with better labeling and organization. Some essential pieces of data such as Supplementary Figure 1B on HER2 mutations in S310 that abrogated its binding to Pertuzumab should be placed in the main figures.

4. It is recommended to provide a clear rationale or flowchart overview into the main Figure 1. Figure 2A can be combined with Figure 1 to the list of targeted residues.

5. The quality of Figures such as Figure 2B-C flow data needs to be improved.

Reviewer #1 (Public Review):

The authors put forth the hypothesis that hepatocyte and/or non-parenchymal liver MCT1 may be responsible for physiologic effects (lower body weight gain and less hepatic steatosis) in MCT1 global heterozygote mice. They generate multiple tools to test this hypothesis, which they combine with mouse diets that induce fatty liver, steatohepatitis and fibrosis. Novel findings include that deletion of hepatocyte MCT1 does not change liver lipid content, but increases liver fibrosis. Deletion of hepatic stellate cell (HSC) MCT1 does not substantially affect any liver parameter, but concomitant HSC MCT1 deletion does reverse fibrosis seen with hepatocyte MCT1 knockout or knockdown. In both models, plasma lactate levels do not change, suggesting that liver MCT1 does not substantially affect systemic lactate. In general, the data match conclusions of the manuscript, and the studies are well-conducted and well-described. Further work would be necessary to dissect mechanism of fibrosis with hepatocyte MCT1, and whether this is due to changes in local lactate (as speculated by the authors) or another MCT1 substrate. This would be important to understand this novel potential cross-talk between hepatocytes and HSCs.

A parallel and perhaps more important advance is the generation of new methodology to target HSC in mice, using modified siRNA and by transduction of AAV9-Lrat-Cre. Both methods would reduce the need to cross floxed mice with the Lrat-Cre allele, saving time and resources. These tools were validated to an extent by the authors, but not sufficiently to ensure that there is no cross-reactivity with other liver cell types. For example, AAV9-Lrat-Cre-transduced MCT1 floxed mice show compelling HSC but not hepatocyte Mct1 knockdown, but other liver cell types should be assessed to ensure specificity. This is particularly important as overall liver Mct1 decreased by ~30% in AAV9-Lrat-Cre-transduced mice, which may exceed HSC content of these mice, especially when considering a 60-70% knockdown efficiency. This same issue also affects Chol-MCT1-siRNA, which the authors demonstrate to affect hepatocytes and HSC, but likely affects other cell types not tested. As this is a new and potentially valuable tool, it would be important to assess Mct1 expression across more non-parenchymal cells (i.e. endothelial, cholangiocytes, immune cells) to determine penetration and efficacy.

Reviewer #2 (Public Review):

In this study, the authors seek to answer two main questions: 1) Whether interfering with lactate availability in hepatocytes through depletion of hepatocyte specific MCT-1 depletion would reduce steatosis, and 2) Whether MCT-1 in stellate cells promote fibrogenesis. While the first question is based on the observation that haploinsufficiency of MCT-1 makes mice resistant to steatosis, the rationale behind how MCT-1 could impact fibrogenesis in stellate cells is not clear. A more detailed discussion regarding how lactate availability would regulate two different processes in two different cell types would be helpful. The authors employ several mouse models and in vitro systems to show that MCT1 inhibition in hepatic stellate cells reduces the expression of COL-1.

The authors have sufficiently addressed prior comments and added new experiments to provide details on possible mechanisms.

Reviewer #3 (Public Review):

We commend the authors on addressing our points and do believe that the manuscript is much improved. Even with the added in vitro data (Figure 8, Supplementary Figure 6), however, a clear mechanistic explanation for how MCT1 is modulating/inhibiting fibrosis in hepatic stellate cells is lacking and this represents a key area for future exploration. The authors provide interesting follow up experiments that suggest lactate can potentiate TGF-β1 signaling, a phenomenon that has previously been described in pulmonary fibrosis. Additionally, MCT1 depletion decreased the pSMAD3/SMAD ratio, but this was overcome with higher doses of TGB- β1 ligand. It remains unclear how intracellular versus extracellular lactate is signaling to exert the observed effects, and how the altered metabolism/metabolic flux in NAFLD is contributing to organ level metabolic dysregulation. These will be keys questions to answer going forward potentially using the novel in vivo models that the authors have contributed here.

A major finding of this work is that loss of monocarboxylate transporter 1 (MCT1), specifically in stellate cells, can decrease fibrosis in the liver. However, the underlying mechanism whereby MCT1 influences stellate cells is not addressed. It is unclear if upstream/downstream metabolic flux within different cell types leads to fibrotic outcomes. Ultimately, the paper opens more questions than it answers: why does decreasing MCT1 expression in hepatocytes exacerbate disease, while silencing MCT1 in fibroblasts seems to alleviate collagen deposition? Mechanistic studies in isolated hepatocytes and stellate cells could enhance the work further to show the disparate pathways that mediate these opposing effects. The work highlights the complexity of cellular behavior and metabolism within a disease environment but does little to mechanistically explain it.