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    1. Reviewer #3 (Public Review):

      The authors delved into an important aspect of abortifacient diseases of livestock in Tanzania. The thoughts of the authors on the topic and its significance are implied, and the methodological approach needs further clarity. The number of wards in the study area, statistical selection of wards, type of questionnaire ie open or close-ended. Statistical analyses of outcomes were not clearly elucidated in the manuscript. Fifteen wards were mentioned in the text but 13 used what were the exclusion criteria. Observations were from pastoral, agropastoral, and smallholder agroecological farmers. No sample numbers or questionnaires were attributed to the above farming systems to correlate findings with management systems. The impacts of the research investigation output are not clearly visible as to warrant intervention methods. What were the identified pathogens from laboratory investigation, particularly with the use of culture and PCR not even mentioning the zoonotic pathogens encountered if any? The public health importance of any of the abortifacient agents was not highlighted.

      In conclusion, based on the intent of the authors and the content of this research, and the weight of the research topic, there are obvious weaknesses in the critical data analysis to demonstrate cause, effect, and impact.

    2. Reviewer #2 (Public Review):

      The paper "The Value of Livestock Abortion Surveillance in Tanzania: Identifying Disease Priorities and Informing Interventions" provides a comprehensive analysis of the importance of livestock abortion surveillance in Tanzania. The authors aim to highlight the significance of this surveillance system in identifying disease priorities and guiding interventions to mitigate the impact of livestock abortions on both animal and human health.

      Summary:

      The paper begins by discussing the context of livestock farming in Tanzania and the significant economic and social impact of livestock abortions. The authors then present a detailed overview of the livestock abortion surveillance system in Tanzania, including its objectives, methods, and data collection process. They analyze the data collected from this surveillance system over a specific period to identify the major causes of livestock abortions and assess their public health implications.

      Evaluation:

      Overall, this paper provides valuable insights into the importance of livestock abortion surveillance as a tool for disease prioritization and intervention planning in Tanzania. The authors effectively demonstrate the utility of this surveillance system in identifying emerging diseases, monitoring disease trends, and informing evidence-based interventions to control and prevent livestock abortions.

      Strengths:

      (1) Clear Objective: The paper clearly articulates its objective of highlighting the value of livestock abortion surveillance in Tanzania.

      (2) Comprehensive Analysis: The authors provide a thorough analysis of the surveillance system, including its methodology, data collection process, and findings as seen in the supplementary files.

      (3) Practical Implications: The paper discusses the practical implications of the surveillance system for disease control and public health interventions in Tanzania.

      (4) Well-Structured: The paper is well-organized, with clear sections and subheadings that facilitate understanding and navigation.

      Suggestions for Improvement:

      (1) Data Presentation: While the analysis is comprehensive, the presentation of data could be enhanced with the use of more visual aids such as tables, graphs, or charts to illustrate key findings.

      (2) Discussion Section: The paper could benefit from a more in-depth discussion of the implications of the findings for disease control strategies and policy formulation in Tanzania.

      (3) Future Directions: Including recommendations for future research or areas for further investigation would add depth to the paper.

      Summary:

      This paper contains thorough analysis and valuable insights. Overall, it makes a significant contribution to the literature on livestock abortion surveillance and its implications for disease control in Tanzania.

    3. Reviewer #1 (Public Review):

      Summary:

      The paper examined livestock abortion, as it is an important disease syndrome that affects productivity and livestock economies. If livestock abortion remains unexamined it poses risks to public health.

      Several pathogens are associated with livestock abortions across Africa however the livestock disease surveillance data rarely include information from abortion events, little is known about the aetiology and impacts of livestock abortions, and data are not available to inform prioritisation of disease interventions. Therefore the current study seeks to examine the issue in detail and proposes some solutions.

      The study took place in 15 wards in northern Tanzania spanning pastoral, agropastoral, and smallholder agro-ecological systems. The key objective is to investigate the causes and impacts of livestock abortion.

      The data collection system was set up such that farmers reported abortion cases to the field officers of the Ministry of Livestock and Fisheries livestock.

      The reports were made to the investigation teams. The team only included abortion of those that the livestock field officers could attend to within 72 hours of the event occurring.

      Also, a field investigation was carried out to collect diagnostic samples from aborted materials. In addition, aborting dams and questionnaires were administered to collect data on herd/flock management. Laboratory diagnostic tests were carried out for a range of abortigenic pathogens

      Over the period of the study, 215 abortion events in cattle (n=71), sheep 48 (n=44), and goats (n=100) were investigated. All 49 investigated cases varied widely across wards. The aetiological attribution, achieved for 19.5% of cases through PCR-based diagnostics, was significantly affected by delays in the field investigation.

      The result also revealed that vaginal swabs from aborting dams provided a practical and sensitive source of diagnostic material for pathogen detection.

      Livestock abortion surveillance can generate valuable information on causes of zoonotic disease outbreaks, and livestock reproductive losses and can identify important pathogens that are not easily captured through other forms of livestock disease surveillance. The study demonstrated the feasibility of establishing an effective reporting and investigation system that could be implemented across a range of settings, including remote rural areas,

      Strengths:

      The paper combines both science and socio-economic methodology to achieve the aim of the study. The methodology was well presented and the sequence was great. The authors explain where and how the data was collected. Figure 2 was used to describe the study area which was excellently done. The section on the investigation of cases was well written. The sample analysis was also well-written. The authors devoted a section to summarizing the investigated cases and description of the livestock 221-study population. The logit model was well-presented.

    1. Reviewer #1 (Public Review):

      In this manuscript, Naseri et al. present a new strategy for identifying human genetic variants with recessive effects on disease risk by the genome-wide association of phenotype with long runs-of-homozygosity (ROH). The key step of this approach is the identification of long ROH segments shared by many individuals (termed "shared ROH diplotype clusters" by the authors), which is computationally intensive for large-scale genomic data. The authors circumvented this challenge by converting the original diploid genotype data to (pseudo-)haplotype data and modifying the existing positional Burrow-Wheeler transformation (PBWT) algorithms to enable an efficient search for haplotype blocks shared by many individuals. With this method, the authors identified over 1.8 million ROH diplotype clusters (each shared by at least 100 individuals) and 61 significant associations with various non-cancer diseases in the UK Biobank dataset.

      Overall, the study is well-motivated, highly innovative, and potentially impactful. Previous biobank-based studies of recessive genetic effects primarily focused on genome-wide aggregated ROH content, but this metric is a poor proxy for homozygosity of the recessive alleles at causal loci. Therefore, searching for the association between phenotype and specific variants in the homozygous state is a key next step towards discovering and understanding disease genes/alleles with recessive effects. That said, I have some concerns regarding the power and error rate of the methods, for both identification of ROH diplotype clusters and subsequent association mapping. In addition, some of the newly identified associations need further validation and careful consideration of potential artifacts (such as cryptic relatedness and environment sharing).

      (1) Identification of ROH diplotype clusters.<br /> The practice of randomly assigning heterozygous sites to a homozygous state is expected to introduce errors, leading to both false positives and false negatives. An advantage that the authors claim for this practice is to reduce false negatives due to occasional mismatch (possibly due to genotyping error, or mutation), but it's unclear how much the false positive rate is reduced compared to traditional ROH detection algorithm. The authors also justified the "random allele drawing" practice by arguing that "the rate of false positives should be low" for long ROH segments, which is likely true but is not backed up with quantitative analysis. As a result, it is unclear whether the trade-off between reducing FNs and introducing FPs makes the practice worthwhile (compared to calling ROHs in each individual with a standard approach first followed by scanning for shared diplotypes across individuals using BWT). I would like to see a combination of back-of-envelope calculation, simulation (with genotyping errors), and analysis of empirical data that characterize the performance of the proposed method.

      In particular, I find the high number of ROH clusters in MHC alarming, and I am not convinced that this can be fully explained by a high density of SNPs and low recombination rate in this region. The authors may provide further support for their hypothesis by examining the genome-wide relationship between ROH cluster abundance and local recombination rate (or mutation rate).

      (2) Power of ROH association. Given that the authors focused on long segments only (which is a limitation of the current method), I am concerned about the power of the association mapping strategy, because only a small fraction of causal alleles are expected to be present in long, homozygous haplotypes shared by many individuals. It would be useful to perform a power analysis to estimate what fraction of true causal variants with a given effect size can be detected with the current method. To demonstrate the general utility of this method, the authors also need to characterize the condition(s) under which this method could pick up association signals missed by standard GWAS with recessive effects considered. I suspect some variants with truly additive effects can also be picked up by the ROH association, which should be discussed in the manuscript to guide the interpretation of results.

      (3) False positives of ROH association. GWAS is notoriously prone to confounding by population and environmental stratification. Including leading principal components in association testing alleviates this issue but is not sufficient to remove the effects of recent demographic structure and local environment (Zaidi and Mathieson 2020 eLife). Similar confounding likely applies to homozygosity mapping and should be carefully considered. For example, it is possible that individuals who share a lot of ROH diplotypes tend to be remotely related and live near each other, thus sharing similar environments. Such scenarios need to be excluded to further support the association signals.

      (4) Validation of significant associations. It is reassuring that some of the top associations are indirectly corroborated by significant GWAS associations between the same disease and individual SNPs present in the ROH region (Tables 1 and 2). However, more sanity checks should be done to confirm consistency in direction of effect size (e.g., risk alleles at individual SNPs should be commonly present in risk-increasing ROH segment, and vice versa) and the presence of dominance effect.

    2. Reviewer #2 (Public Review):

      The authors have proposed a computational algorithm to identify runs of homozygosity (ROH) segments in a generally outbred population and then study the association of ROH with self-reported disorders in the UK biobank. The algorithm certainly identifies such segments. However, more work is needed to justify the importance of ROH.

    3. Reviewer #3 (Public Review):

      A classic method to detect recessive disease variants is homozygosity mapping, where affected individuals in a pedigree are scanned for the presence of runs of homozygosity (ROH) intersecting in a given region. The method could in theory be extended to biobanks with large samples of unrelated individuals; however, no efficient method was available (to the best of my knowledge) for detecting overlapping clusters of ROH in such large samples. In this paper, the authors developed such a method based on the PBWT data structure. They applied the method to the UK biobank, finding a number of associations, some of them not discovered in single SNP associations.

      Major strengths:<br /> • The method is innovative and algorithmically elegant and interesting. It achieves its purpose of efficiently and accurately detecting ROH clusters overlapping in a given region. It is therefore a major methodological advance.<br /> • The method could be very useful for many other researchers interested in detecting recessive variants associated with any phenotype.<br /> • The statistical analysis of the UK biobank data is solid and the results that were highlighted are interesting and supported by the data.

      Major weaknesses:<br /> • The positions and IDs of the ROH clusters in the UK biobank are not available for other researchers. This means that other researchers will not be able to follow up on the results of the present paper.<br /> • The vast majority of the discoveries were in regions already known to be associated with their respective phenotypes based on standard GWAS.<br /> • The running time seems rather long (at least for the UK biobank), and therefore it will be difficult for other researchers to extensively experiment with the method in very large datasets. That being said, the method has a linear running time, so it is already faster than a naïve algorithm.

    1. Reviewer #1 (Public Review):

      Summary:

      For many years, there has been extensive electrophysiological research investigating the relationship between local field potential patterns and individual cell spike patterns in the hippocampus. In this study, using state-of-the-art imaging techniques, they examined spike synchrony of hippocampal cells during locomotion and immobility states. In contrast to conventional understanding of the hippocampus, the authors demonstrated that hippocampal place cells exhibit prominent synchronous spikes locked to theta oscillations.

      Strengths:

      The voltage imaging used in this study is a highly novel method that allows recording not only suprathreshold-level spikes but also subthreshold-level activity. With its high frame rate, it offers time resolution comparable to electrophysiological recordings. Moreover, it enables the visualization of actual cell locations, allowing for the examination of spatial properties (e.g., Figure 4G).

      Weaknesses:

      There is a notable deviation from several observations obtained through conventional electrophysiological recordings. Particularly, as mentioned below in detail, the considerable differences in baseline firing rates and no observations of ripple-triggered firing patterns raise some concerns about potential artifacts from imaging and analsyis, such as cell toxicity, abnormal excitability, and false detection of spikes. While these findings are intriguing if the validity of these methods is properly proven, accepting the current results as new insights is challenging.

    2. Reviewer #2 (Public Review):

      Summary:

      This study employed voltage imaging in the CA1 region of the mouse hippocampus during the exploration of a novel environment. The authors report synchronous activity, involving almost half of the imaged neurons, occurred during periods of immobility. These events did not correlate with SWRs, but instead, occurred during theta oscillations and were phased-locked to the trough of theta. Moreover, pairs of neurons with high synchronization tended to display non-overlapping place fields, leading the authors to suggest these events may play a role in binding a distributed representation of the context.

      Strengths:

      Technically this is an impressive study, using an emerging approach that allows single-cell resolution voltage imaging in animals, that while head-fixed, can move through a real environment. The paper is written clearly and suggests novel observations about population-level activity in CA1.

      Weaknesses:

      The evidence provided is weak, with the authors making surprising population-level claims based on a very sparse data set (5 data sets, each with less than 20 neurons simultaneously recorded) acquired with exciting, but less tested technology. Further, while the authors link these observations to the novelty of the context, both in the title and text, they do not include data from subsequent visits to support this. Detailed comments are below:

      (1) My first question for the authors, which is not addressed in the discussion, is why these events have not been observed in the countless extracellular recording experiments conducted in rodent CA1 during the exploration of novel environments. Those data sets often have 10x the neurons simultaneously recording compared to these present data, thus the highly synchronous firing should be very hard to miss. Ideally, the authors could confirm their claims via the analysis of publicly available electrophysiology data sets. Further, the claim of high extra-SWR synchrony is complicated by the observation that their recorded neurons fail to spike during the limited number of SWRs recorded during behavior- again, not agreeing with much of the previous electrophysiological recordings.

      (2) The authors posit that these events are linked to the novelty of the context, both in the text, as well as in the title and abstract. However, they do not include any imaging data from subsequent days to demonstrate the failure to see this synchrony in a familiar environment. If these data are available it would strengthen the proposed link to novelty if they were included.

      (3) In the discussion the authors begin by speculating the theta present during these synchronous events may be slower type II or attentional theta. This can be supported by demonstrating a frequency shift in the theta recording during these events/immobility versus the theta recording during movement.

      (4) The authors mention in the discussion that they image deep-layer PCs in CA1, however, this is not mentioned in the text or methods. They should include data, such as imaging of a slice of a brain post-recording with immunohistochemistry for a layer-specific gene to support this.

    3. Reviewer #3 (Public Review):

      Summary:

      In the present manuscript, the authors use a few minutes of voltage imaging of CA1 pyramidal cells in head-fixed mice running on a track while local field potentials (LFPs) are recorded. The authors suggest that synchronous ensembles of neurons are differentially associated with different types of LFP patterns, theta and ripples. The experiments are flawed in that the LFP is not "local" but rather collected in the other side of the brain, and the investigation is flawed due to multiple problems with the point process analyses. The synchrony terminology refers to dozens of milliseconds as opposed to the millisecond timescale referred to in prior work, and the interpretations do not take into account theta phase locking as a simple alternative explanation.

      Weaknesses:

      The two main messages of the manuscript indicated in the title are not supported by the data. The title gives two messages that relate to CA1 pyramidal neurons in behaving head-fixed mice: (1) synchronous ensembles are associated with theta (2) synchronous ensembles are not associated with ripples.

      There are two main methodological problems with the work: (1) experimentally, the theta and ripple signals were recorded using electrophysiology from the opposite hemisphere to the one in which the spiking was monitored. However, both signals exhibit profound differences as a function of location: theta phase changes with the precise location along the proximo-distal and dorso-ventral axes, and importantly, even reverses with depth. And ripples are often a local phenomenon - independent ripples occur within a fraction of a millimeter within the same hemisphere, let alone different hemispheres. Ripples are very sensitive to the precise depth - 100 micrometers up or down, and only a positive deflection/sharp wave is evident. (2) The analysis of the point process data (spike trains) is entirely flawed. There are many technical issues: complex spikes ("bursts") are not accounted for; differences in spike counts between the various conditions ("locomotion" and "immobility") are not accounted for; the pooling of multiple CCGs assumes independence, whereas even conditional independence cannot be assumed; etc.

      Beyond those methodological issues, there are two main interpretational problems: (1) the "synchronous ensembles" may be completely consistent with phase locking to the intracellular theta (as even shown by the authors themselves in some of the supplementary figures). (2) The definition of "synchrony" in the present work is very loose and refers to timescales of 20-30 ms. In previous literature that relates to synchrony of point processes, the timescales discussed are 1-2 ms, and longer timescales are referred to as the "baseline" which is actually removed (using smoothing, jittering, etc.).

    1. Reviewer #1 (Public Review):

      In this study, the authors offer a fresh perspective on how visual working memory operates. They delve into the link between anticipating future events and retaining previous visual information in memory. To achieve this, the authors build upon their recent series of experiments that investigated the interplay between gaze biases and visual working memory. In this study, they introduce an innovative twist to their fundamental task. Specifically, they disentangle the location where information is initially stored from the location where it will be tested in the future. Participants are tasked with learning a novel rule that dictates how the initial storage location relates to the eventual test location. The authors leverage participants' gaze patterns as an indicator of memory selection. Intriguingly, they observe that microsaccades are directed towards both the past encoding location and the anticipated future test location. This observation is noteworthy for several reasons. Firstly, participants' gaze is biased towards the past encoding location, even though that location lacks relevance to the memory test. Secondly, there's a simultaneous occurrence of an increased gaze bias towards both the past and future locations. To explore this temporal aspect further, the authors conduct a compelling analysis that reveals the joint consideration of past and future locations during memory maintenance. Notably, microsaccades biased towards the future test location also exhibit a bias towards the past encoding location. In summary, the authors present an innovative perspective on the adaptable nature of visual working memory. They illustrate how information relevant to the future is integrated with past information to guide behavior.

    2. Reviewer #2 (Public Review):

      Summary:

      The manuscript by Liu et al. reports a task that is designed to examine the extent to which "past" and "future" information is encoded in working memory that combines a retrocue with rules that indicate the location of an upcoming test probe. An analysis of microsaccades on a fine temporal scale shows the extent to which shifts of attention track the location of the encoded item (past) and the location of the future item (test probe). The location of the encoded grating and test probe were always on orthogonal axes (horizontal, vertical) so that biases in microsaccades could be used to track shifts of attention to one or the other axis (or mixtures of the two). The overall goal here was then to (1) create a methodology that could tease apart memory for the past and future, respectively, (2) to look at the time-course attention to past/future, and (3) to test the extent to which microsaccades might jointly encode past and future memoranda. Finally, some remarks are made about the plausibility of various accounts of working memory encoding/maintenance based on the examination of these time-courses.

      Strengths:

      This research has several notable strengths. It has a clear statement of its aims, is lucidly presented, and uses a clever experimental design that neatly orthogonalized "past" and "future" as operationalized by the authors. Figure 1b-d shows fairly clearly that saccade directions have an early peak (around 300ms) for the past and a "ramping" up of saccades moving in the forward direction. This seems to be a nice demonstration that the method can measure shifts of attention at a fine temporal resolution and differentiate past from future oriented saccades due to the orthogonal cue approach. The second analysis shown in Figure 2, reveals a dependency in saccade direction such that saccades toward the probe future were more likely also to be toward the encoded location than away from the encoded direction. This suggests saccades are jointly biased by both locations "in memory". The "central contribution" (as the authors characterize it) is that "the brain simultaneously retains the copy of both past and future-relevant locations in working memory, and (re)activates each during mnemonic selection", and that: "... while it is not surprising that the future location is considered, it is far less trivial that both past and future attributes would be retained and (re)activated together. This is our central contribution." The authors provide a nuanced analysis that offers persuasive evidence that past and future representations are jointly maintained in memory.

    1. Reviewer #1 (Public Review):

      Using A. carterae as a model system, this work investigates the properties of the trans-spliced SL leader sequences and the dinoflagellate eIF4E protein family members.

      Analysis was performed to identify the 5' cap type of the SL leader. Variation in the SL leader sequence and an abundance of modified bases was documented.

      Various aspects of the sequence and expression of the eIF4E family members were examined. This included phylogeny, mRNA, and protein expression levels in A. carterae, and the ability of eIF4E proteins to bind cap structures. Differences in expression levels and cap-binding capacity were characterized, leading to the proposition that eIF4E-1a serves as the major cap-binding protein in A. carterae.

      A major discussion point is the potential for differential eIF4E binding to specific SL leader sequences as a regulatory mechanism, which is an exciting prospect. However, despite indications of sequence variability and the presence of various nucleotide modifications in the SL, and the several eIF4E variants, direct evidence to support this hypothesis is lacking.

      It is an extensive and highly descriptive study. The work is presented clearly, although it is rather lengthy and contains repetition across the introduction, results, and discussion sections. Its style leans more towards a review format. As a non-expert in the field, I appreciated the extensive background however I do believe the paper would benefit from a more concise format.

    2. Reviewer #2 (Public Review):

      Summary:

      Jones et al. extend their previous work on the translation machinery in Dinoflagellate. In particular, they study the species Amphidium carterae. They characterize the type of cap structure mRNAs possess in this species, as well as the eight eIF4E family members A. carterae possesses and their affinity to the mRNA cap. They also establish the leader sequences of the transpliced mRNAs that A. carterae generates during gene expression.

      Strengths:

      The authors performed a solid phylogenetic and biochemical study to understand the structure of Dinoflagellate mRNAs at the 5'-UTR as well as the divergence and biochemical features of eIF4Es across Dinoflagellate. They also establish eIF4E-1a as the prototypical paralog of the eIF4E family of proteins. The scientific questions they ask are very relevant to the gene expression field across eukaryotes. The experiments and the phylogenetic analysis are performed with a very high quality. They perform a wide spectrum of experimental approaches and techniques to answer the questions.

      Weaknesses:

      The authors assume all eIF4E from Dinoflagellate are involved in translation, i.e., mRNA recruitment to the ribosome. Indeed, they think that the diverse biochemical features of all eIF4E in A. carterae have to do with the possible recruitment of different subsets of mRNAs to the ribosome for translation. I think that the biochemical differences among all paralogs also might be due to the involvement of some of them in different processes of RNA metabolism, other than translation. For instance, some of them could be involved only in RNA processing in the nucleus or mRNA storage in cytoplasmic foci.

    3. Reviewer #3 (Public Review):

      Summary:

      In this article, the authors provide an inventory of the 5' spliced leader sequences, cap structures, and eIF4E isoforms present in the model dinoflagellate species A. carterae. They provide evidence that the 5' cap structure is m7G, as it is in most characterized eukaryotes that do not employ trans-splicing for mRNA maturation, and that there are additional methylated nucleotides throughout the spliced leader RNAs. They then show that of the 8 different eIF4E species in A. carterae, only a subset of eIF4E1 and eIF4E2 proteins are detected and that the levels change according to time of day. Interestingly, while the eIF4E1 proteins bind a canonical cap nucleotide and are able to complement eIF4E-deficiency in yeast, an eIF4E2 paralog does not bind the traditional cap.

      Strengths:

      A strength of the article is that the authors have clearly presented the findings and by straying away from traditional model organisms, they have highlighted unique and interesting features of an understudied system for translational control. They provide complementary evidence for most findings using multiple techniques. E.g. the evidence that eIF4E1A binds m7GTP is supported by both pulldowns using m7GTP sepharose as well as SPR experiments to directly monitor binding of recombinant protein with affinity measurements. The methods are extremely detailed noting cell numbers, volumes, concentrations, etc. used in the experiments to be easily replicated.

      Weaknesses:

      While not necessary to support the author's conclusions, the significance of the work would be further enhanced by additional experiments to gain insights into mechanisms for translational control and to link specific SLs to organismal functions or mechanisms of mRNA recruitment.

      -Monitoring diel expression of SLs and direct sequencing of mature mRNA would yield insights into whether there is regulated expression of RNAs with different SLs or the SLs themselves. This would also allow the authors to perform gene ontology to link SL expression at different points in the diel cycle to related functions, e.g. photosynthesis.

      -In addition, the work would be strengthened by polysome sequencing or ribosome profiling as a function of the diel cycle, with analyses of when various spliced leader sequences are recruited to ribosomes in parallel with western blotting of polysome fractions to determine when various eIF4E isoforms are present on polysomes. This is a substantial expansion though from what the authors focused on in this manuscript, and not having these experiments does not undermine the findings presented. Alternatively, they could attempt to make bioinformatic comparisons with existing ribosome profiling datasets from a related dinoflagellate, Lingulodinium polyedrum, discussed briefly, if there were sufficient overlap between SL RNAs in these organisms.

    1. Reviewer #1 (Public Review):

      Summary:

      The authors want to determine the role of the sperm hook of the house mouse sperm in movement through the uterus. The authors are trying to distinguish between two hypotheses put forward by others on the role of the sperm hook: (1) the sperm cooperation hypothesis (the sperm hook helps to form sperm trains) vs (2) the migration hypothesis (that the sperm hook is needed for sperm movement through the uterus). They use transgenic lines with fluorescent labels to sperm proteins, and they cross these males to C57BL/6 females in pathogen-free conditions. They use 2-photon microscopy on ex vivo uteri within 3 hours of mating and the appearance of a copulation plug. There are a total of 10 post-mating uteri that were imaged with 3 different males. They provide 10 supplementary movies that form the basis for some of the quantitative analysis in the main body figures. Their data suggest that the role of the sperm hook is to facilitate movement along the uterine wall.

      Strengths:

      Ex vivo live imaging of fluorescently labeled sperm with 2-photon microscopy is a powerful tool for studying the behavior of sperm.

      Weaknesses:

      The paper is descriptive and the data are correlations.

      The data are not properly described in the figure legends.

      When statistical analyses are performed, the authors do not comment on the trend that sperm from the three males behave differently from each other. This weakens confidence in the results. For example, in Figure 1 the sperm from male 3613 (blue squares) look different from male 838 (red circles), but all of these data are considered together. The authors should comment on why sperm across males are considered together when the individual data points appear to be different across males.

      Movies S8-S10 are single data points and no statistical analyses are performed. Therefore, it is unclear how penetrant the sperm movements are.

      Movies S1B - did the authors also track the movement of sperm located in the middle of the uterus (not close to the wall)? Without this measurement, they can't be certain that sperm close to the uterus wall travels faster.

      Movie S5A - is of lower magnitude (200 um scale bar) while the others have 50 and 20 uM scale bars. Individual sperm movement can be observed in the 20 uM (Movie 5SC). If the authors went to prove that there is no upsucking movement of sperm by the uterine contractions, they need to provide a high magnification image.

      Movie S8 - if the authors want to make the case that clustered sperm do not move faster than unclustered sperm, then they need to show Movie S8 at higher magnification. They also need to quantify these data.

      Movie S9C - what is the evidence that these sperm are dead or damaged?

      MovIe S10 - both slow- and fast-moving sperm are seen throughout the course of the movie, which does not support the authors' conclusion that sperm tails beat faster over time.

    2. Reviewer #2 (Public Review):

      Summary:

      The specific objective of this study was to determine the role of the large apical hook on the head of mouse sperm (Mus musculus) in sperm migration through the female reproductive tract. The authors used a custom-built two-photon microscope system to obtain digital videos of sperm moving within the female reproductive tract. They used sperm from genetically modified male mice that produce fluorescence in the sperm head and flagellar midpiece to enable visualization of sperm moving within the tract. Based on various observations, the authors concluded that the hook serves to facilitate sperm migration by hooking sperm onto the lining of the female reproductive tract, rather than by hooking sperm together to form a sperm train that would move them more quickly through the tract. The images and videos are excellent and inspirational to researchers in the field of mammalian sperm migration, but interpretations of the behaviors are highly speculative and not supported by controlled experimentation.

      Strengths:

      The microscope system developed by the authors could be of interest to others investigating sperm migration.

      The new behaviors shown in the images and videos could be of interest to others in the field, in terms of stimulating the development of new hypotheses to investigate.

      Weaknesses:

      The authors stated several hypotheses about the functions of the sperm behaviors they saw, but the hypotheses were not clearly stated or tested experimentally.

      The hypothesis statements were weakened by the use of hedge words, such as "may".

    1. Reviewer #1 (Public Review):

      The authors have performed all-atom MD simulations to study the working mechanism of hsPepT2. It is widely accepted that conformational transitions of proton-coupled oligopeptide transporters (POTs) are linked with gating hydrogen bonds and salt bridges involving protonatable residues, whose protonation triggers gate openings. Through unbiased MD simulations, the authors identified extra-cellular (H87 and D342) and intra-cellular (E53 and E622) triggers. The authors then validated these triggers using free energy calculations (FECs) and assessed the engagement of the substrate (Ala-Phe dipeptide). The linkage of substrate release with the protonation of the ExxER motif (E53 and E56) was confirmed using constant-pH molecular dynamics (CpHMD) simulations and cell-based transport assays. An alternating-access mechanism was proposed. The study was largely conducted properly, and the paper was well-organized. However, I have a couple of concerns for the authors to consider addressing.

      (1) As a proton-coupled membrane protein, the conformational dynamics of hsPepT2 are closely coupled to protonation events of gating residues. Instead of using semi-reactive methods like CpHMD or reactive methods such as reactive MD, where the coupling is accounted for, the authors opted for extensive non-reactive regular MD simulations to explore this coupling. Note that I am not criticizing the choice of methods, and I think those regular MD simulations were well-designed and conducted. But I do have two concerns.

      a) Ideally, proton-coupled conformational transitions should be modelled using a free energy landscape with two or more reaction coordinates (or CVs), with one describing the protonation event and the other describing the conformational transitions. The minimum free energy path then illustrates the reaction progress, such as OCC/H87D342-  OCC/H87HD342H  OF/H87HD342H as displayed in Figure 3. Without including the protonation as a CV, the authors tried to model the free energy changes from multiple FECs using different charge states of H87 and D342. This is a practical workaround, and the conclusion drawn (the OCCOF transition is downhill with protonated H87 and D342) seems valid. However, I don't think the OF states with different charge states (OF/H87D342-, OF/H87HD342-, OF/H87D342H, and OF/H87HD342H) are equally stable, as plotted in Figure 3b. The concern extends to other cases like Figures 4b, S7, S10, S12, S15, and S16. While it may be appropriate to match all four OF states in the free energy plot for comparison purposes, the authors should clarify this to ensure readers are not misled.

      b) Regarding the substrate impact, it appears that the authors assumed fixed protonation states. I am afraid this is not necessarily the case. Variations in PepT2 stoichiometry suggest that substrates likely participate in proton transport, like the Phe-Ala (2:1) and Phe-Gln (1:1) dipeptides mentioned in the introduction. And it is not rigorous to assume that the N- and C-termini of a peptide do not protonate/deprotonate when transported. I think the authors should explicitly state that the current work and the proposed mechanism (Figure 8) are based on the assumption that the substrates do not uptake/release proton(s).

      (2) I have more serious concerns about the CpHMD employed in the study.

      a) The CpHMD in AMBER is not rigorous for membrane simulations. The underlying generalized Born model fails to consider the membrane environment when updating charge states. In other words, the CpHMD places a membrane protein in a water environment to judge if changes in charge states are energetically favorable. While this might not be a big issue for peripheral residues of membrane proteins, it is likely unphysical for internal residues like the ExxER motif. As I recall, the developers have never used the method to study membrane proteins themselves. The only CpHMD variant suitable for membrane proteins is the membrane-enabled hybrid-solvent CpHMD in CHARMM. While I do not expect the authors to redo their CpHMD simulations, I do hope the authors recognize the limitations of their method.

      b) It appears that the authors did not make the substrate (Ala-Phe dipeptide) protonatable in holo-simulations. This oversight prevents a complete representation of ligand-induced protonation events, particularly given that the substrate ion pairs with hsPepT2 through its N- & C-termini. I believe it would be valuable for the authors to acknowledge this potential limitation.

    2. Reviewer #2 (Public Review):

      Summary:

      This is an interesting manuscript that describes a series of molecular dynamics studies on the peptide transporter PepT2 (SLC15A2). They examine, in particular, the effect on the transport cycle of protonation of various charged amino acids within the protein. They then validate their conclusions by mutating two of the residues that they predict to be critical for transport in cell-based transport assays. The study suggests a series of protonation steps that are necessary for transport to occur in Petp2. Comparison with bacterial proteins from the same family shows that while the overall architecture of the proteins and likely mechanism are similar, the residues involved in the mechanism may differ.

      Strengths:

      This is an interesting and rigorous study that uses various state-of-the-art molecular dynamics techniques to dissect the transport cycle of PepT2 with nearly 1ms of sampling. It gives insight into the transport mechanism, investigating how the protonation of selected residues can alter the energetic barriers between various states of the transport cycle. The authors have, in general, been very careful in their interpretation of the data.

      Weaknesses:

      Interestingly, they suggest that there is an additional protonation event that may take place as the protein goes from occluded to inward-facing but they have not identified this residue. Some things are a little unclear. For instance, where does the state that they have defined as occluded sit on the diagram in Figure 1a? - is it truly the occluded state as shown on the diagram or does it tend to inward- or outward-facing? The pKa calculations and their interpretation are a bit unclear. Firstly, it is unclear whether they are using all the data in the calculations of the histograms, or just selected data and if so on what basis was this selection done. Secondly, they dismiss the pKa calculations of E53 in the outward-facing form as not being affected by peptide binding but say that E56 is when there seems to be a similar change in profile in the histograms.

    3. Reviewer #3 (Public Review):

      Summary:

      Lichtinger et al. have used an extensive set of molecular dynamics (MD) simulations to study the conformational dynamics and transport cycle of an important member of the proton-coupled oligopeptide transporters (POTs), namely SLC15A2 or PepT2. This protein is one of the most well-studied mammalian POT transporters that provides a good model with enough insight and structural information to be studied computationally using advanced enhanced sampling methods employed in this work. The authors have used microsecond-level MD simulations, constant-PH MD, and alchemical binding free energy calculations along with cell-based transport assay measurements; however, the most important part of this work is the use of enhanced sampling techniques to study the conformational dynamics of PepT2 under different conditions.

      The study attempts to identify links between conformational dynamics and chemical events such as proton binding, ligand-protein interactions, and intramolecular interactions. The ultimate goal is of course to understand the proton-coupled peptide and drug transport by PepT2 and homologous transporters in the solute carrier family.

      Some of the key results include<br /> (1) Protonation of H87 and D342 initiate the occluded (Occ) to the outward-facing (OF) state transition.

      (2) In the OF state, through engaging R57, substrate entry increases the pKa value of E56 and thermodynamically facilitates the movement of protons further down.

      (3) E622 is not only essential for peptide recognition but also its protonation facilitates substrate release and contributes to the intracellular gate opening. In addition, cell-based transport assays show that mutation of residues such as H87 and D342 significantly decreases transport activity as expected from simulations.

      Strengths:

      (1) This is an extensive MD-based study of PepT2, which is beyond the typical MD studies both in terms of the sheer volume of simulations as well as the advanced methodology used. The authors have not limited themselves to one approach and have appropriately combined equilibrium MD with alchemical free energy calculations, constant-pH MD, and geometry-based free energy calculations. Each of these 4 methods provides a unique insight regarding the transport mechanism of PepT2.

      (2) The authors have not limited themselves to computational work and have performed experiments as well. The cell-based transport assays clearly establish the importance of the residues that have been identified as significant contributors to the transport mechanism using simulations.

      (3) The conclusions made based on the simulations are mostly convincing and provide useful information regarding the proton pathway and the role of important residues in proton binding, protein-ligand interaction, and conformational changes.

      Weaknesses:

      (1) Some of the statements made in the manuscript are not convincing and do not abide by the standards that are mostly followed in the manuscript. For instance, on page 4, it is stated that "the K64-D317 interaction is formed in only ≈ 70% of MD frames and therefore is unlikely to contribute much to extracellular gate stability." I do not agree that 70% is negligible. Particularly, Figure S3 does not include the time series so it is not clear whether the 30% of the time where the salt bridge is broken is in the beginning or the end of simulations. For instance, it is likely that the salt bridge is not initially present and then it forms very strongly. Of course, this is just one possible scenario but the point is that Figure S3 does not rule out the possibility of a significant role for the K64-D317 salt bridge.

      (2) Similarly, on page 4, it is stated that "whether by protonation or mutation - the extracellular gate only opens spontaneously when both the H87 interaction network and D342-R206 are perturbed (Figure S5)." I do not agree with this assessment. The authors need to be aware of the limitations of this approach. Consider "WT H87-prot" and "D342A H87-prot": when D342 residue is mutated, in one out of 3 simulations, we see the opening of the gate within 1 us. When D342 residue is not mutated we do not see the opening in any of the 3 simulations within 1 us. It is quite likely that if rather than 3 we have 10 simulations or rather than 1 us we have 10 us simulations, the 0/3 to 1/3 changes significantly. I do not find this argument and conclusion compelling at all.

      (3) While the MEMENTO methodology is novel and interesting, the method is presented as flawless in the manuscript, which is not true at all. It is stated on Page 5 with regards to the path generated by MEMENTO that "These paths are then by definition non-hysteretic." I think this is too big of a claim to say the paths generated by MEMENTO are non-hysteretic by definition. This claim is not even mentioned in the original MEMENTO paper. What is mentioned is that linear interpolation generates a hysteresis-free path by definition. There are two important problems here: (a) MEMENTO uses the linear interpolation as an initial step but modifies the intermediates significantly later so they are no longer linearly interpolated structures and thus the path is no longer hysteresis-free; (b) a more serious problem is the attribution of by-definition hysteresis-free features to the linearly interpolated states. This is based on conflating the hysteresis-free and unique concepts. The hysteresis in MD-based enhanced sampling is related to the presence of barriers in orthogonal space. For instance, one may use a non-linear interpolation of any type and get a unique pathway, which could be substantially different from the one coming from the linear interpolation. None of these paths will be hysteresis-free necessarily once subjected to MD-based enhanced sampling techniques.

    1. Reviewer #2 (Public Review):

      Summary:

      In this article, Kumar et al., report on a previously unappreciated mechanism of translational regulation whereby p130Cas induces LLPS condensates that then traffic out from focal adhesion into the cytoplasm to modulate mRNA translation. Specifically, the authors employed EGFP-tagged p130Cas constructs, endogenous p130Cas, and p130Cas knockouts and mutants in cell-based systems. These experiments in conjunction with various imaging techniques revealed that p130Cas drives assembly of LLPS condensates in a manner that is largely independent of tyrosine phosphorylation. This was followed by in vitro EGFP-tagged p130Cas-dependent induction of LLPS condensates and determination of their composition by mass spectrometry, which revealed enrichment of proteins involved in RNA metabolism in the condensates. The authors excluded the plausibility that p130Cas-containing condensates co-localize with stress granules or p-bodies. Next, the authors determined mRNA compendium of p130Cas-containing condensates which revealed that they are enriched in transcripts encoding proteins implicated in cell cycle progression, survival, and cell-cell communication. These findings were followed by the authors demonstrating that p130Cas-containing condensates may be implicated in the suppression of protein synthesis using puromycylation assay. Altogether, it was found that this study significantly advances the knowledge pertinent to the understanding of molecular underpinnings of the role of p130Cas and more broadly focal adhesions on cellular function, and to this end, it is likely that this report will be of interest to a broad range of scientists from a wide spectrum of biomedical disciplines including cell, molecular, developmental and cancer biologists.

      Strengths:

      Altogether, this study was found to be of potentially broad interest inasmuch as it delineates a hitherto unappreciated link between p130Cas, LLPS, and regulation of mRNA translation. More broadly, this report provides unique molecular insights into the previously unappreciated mechanisms of the role of focal adhesions in regulating protein synthesis. Overall, it was thought that the provided data sufficiently supported most of the authors' conclusions. It was also thought that this study incorporates an appropriate balance of imaging, cell and molecular biology, and biochemical techniques, whereby the methodology was found to be largely appropriate.

      Weaknesses:

      Two major weaknesses of the study were noted. The first issue is related to the experiments establishing the role of p130Cas-driven condensates in translational suppression, whereby it remained unclear whether these effects are affecting global mRNA translation or are specific to the mRNAs contained in the condensates. Moreover, some of the results in this section (e.g., experiments using cycloheximide) may be open to alternative interpretation. The second issue is the apparent lack of functional studies, and although the authors speculate that the described mechanism is likely to mediate the effects of focal adhesions on e.g., quiescence, experimental testing of this tenet was lacking.

    2. Reviewer #1 (Public Review):

      Summary:

      The authors demonstrated the phenomenon of p130Cas, a protein primarily localized at focal adhesions, and its formation of condensates. They identified the constituents within the condensates, which include other focal adhesion proteins, paxillin, and RNAs. Furthermore, they proposed a link between p130Cas condensates and translation.

      Strengths:

      Adhesion components undergo rapid exchange with the cytoplasm for some unclear biological functions. Given that p130Cas is recognized as a prominent mechanical focal adhesion component, investigating its role in condensate formation, particularly its impact on the translation process, is intriguing and significant.

      Weaknesses:

      The authors identified the disordered region of p130Cas and investigated the formation of p130Cas condensate. They attempted to demonstrate that p130Cas condensates inhibit translation, but the results did not fully support this assertion. There are several comments below:

      (1) Despite isolating p130Cas-GFP protein using GFP-trap beads, the authors cannot conclusively eliminate the possibility of isolating p130Cas from focal adhesions. While the characterization of the GFP-tagged pulls can reveal the proteins and RNAs associated with p130Cas, they need to clarify their intramolecular mechanism of localization within p130Cas droplets. Whether the protein condensates retain their liquid phase or these GFP-p130Cas pulls represent protein aggregate remains uncertain.

      (2) The authors utilized hexanediol and ammonium acetate to highlight the phenomenon of p130Cas condensates. Although hexanediol is an inhibitor for hydrophobic interactions and ammonium acetate is a salt, a more thorough explanation of the intramolecular mechanisms underlying p130Cas protein-protein interaction is required. Additionally, given that the size of p130Cas condensates can exceed >100um2, classification is needed to differentiate between p130Cas condensates and protein aggregation.

      (3) The connection between p130Cas condensates and translation inhibition appears tenuous. The data only suggests a correlation between p130Cas expression and translation inhibition. Further evidence is required to bolster this hypothesis.

    1. Reviewer #1 (Public Review):

      Summary:

      The manuscript focuses on the role of the deubiquitinating enzyme UPS-50/USP8 in endosome maturation. The authors aimed to clarify how this enzyme drives the conversion of early endosomes into late endosomes. Overall, they did achieve their aims in shedding light on the precise mechanisms by which UPS-50/USP8 regulates endosome maturation. The results support their conclusions that UPS-50 acts by disassociating RABX-5 from early endosomes to deactivate RAB-5 and by recruiting SAND-1/Mon1 to activate RAB-7. This work is commendable and will have a significant impact on the field. The methods and data presented here will be useful to the community in advancing our understanding of endosome maturation and identifying potential therapeutic targets for diseases related to endosomal dysfunction. It is worth noting that further investigation is required to fully understand the complexities of endosome maturation. However, the findings presented in this manuscript provide a solid foundation for future studies.

      Strengths:

      The major strengths of this work lie in the well-designed experiments used to examine the effects of UPS-50 loss. The authors employed confocal imaging to obtain a picture of the aftermath of the USP-50 loss. Their findings indicated enlarged early endosomes and MVB-like structures in cells deficient in USP-50/USP8.

      Weaknesses:

      Specifically, there is a need for further investigation to accurately characterize the anomalous structures detected in the ups-50 mutant. Also, the correlation between the presence of these abnormal structures and ESCRT-0 is yet to be addressed, and the current working model needs to be revised to prevent any confusion between enlarged early endosomes and MVBs.

    2. Reviewer #2 (Public Review):

      Summary:

      In this study, the authors study how the deubiquitinase USP8 regulates endosome maturation in C. elegans and mammalian cells. The authors have isolated USP8 mutant alleles in C. elegans and used multiple in vivo reporter lines to demonstrate the impact of USP8 loss-of-function on endosome morphology and maturation. They show that in USP8 mutant cells, the early endosomes and MVB-like structures are enlarged while the late endosomes and lysosomal compartments are reduced. They elucidate that USP8 interacts with Rabx5, a guanine nucleotide exchange factor (GEF) for Rab5, and show that USP8 likely targets specific lysine residue of Rabx5 to dissociate it from early endosomes. They also find that the localization of USP8 to early endosomes is disrupted in Rabx5 mutant cells. They observe that in both Rabx5 and USP8 mutant cells, the Rab7 GEF SAND-1 puncta which likely represents late endosomes are diminished, although Rabex5 is accumulated in USP8 mutant cells. The authors provide evidence that USP8 regulates endosomal maturation in a similar fashion in mammalian cells. Based on their observations they propose that USP8 dissociates Rabex5 from early endosomes and enhances the recruitment of SAND-1 to promote endosome maturation.

      Strengths:

      The major highlights of this study include the direct visualization of endosome dynamics in a living multi-cellular organism, C. elegans. The high-quality images provide clear in vivo evidence to support the main conclusions. The authors have generated valuable resources to study mechanisms involved in endosome dynamics regulation in both the worm and mammalian cells, which would benefit many members of the cell biology community. The work identifies a fascinating link between USP8 and the Rab5 guanine nucleotide exchange factor Rabx5, which expands the targets and modes of action of USP8. The findings make a solid contribution toward the understanding of how endosomal trafficking is controlled.

      Weaknesses:

      - The authors utilized multiple fluorescent protein reporters, including those generated by themselves, to label endosomal vesicles. Although these are routine and powerful tools for studying endosomal trafficking, these results cannot tell whether the endogenous proteins (Rab5, Rabex5, Rab7, etc.) are affected in the same fashion.

      - The authors clearly demonstrated a link between USP8 and Rabx5, and they showed that cells deficient in both factors displayed similar defects in late endosomes/lysosomes. However, the authors didn't confirm whether and/or to which extent USP8 regulates endosome maturation through Rabx5. Additional genetic and molecular evidence might be required to better support their working model.

    3. Reviewer #3 (Public Review):

      Summary:

      The authors were trying to elucidate the role of USP8 in the endocytic pathway. Using C. elegans epithelial cells as a model, they observed that when USP8 function is lost, the cells have a decreased number and size in lysosomes. Since USP8 was already known to be a protein linked to ESCRT components, they looked into what role USP8 might play in connecting lysosomes and multivesicular bodies (MVB). They observed fewer ESCRT-associated vesicles but an increased number of "abnormal" enlarged vesicles when USP8 function was lost. At this specific point, it's not clear what the objective of the authors was. What would have been their hypothesis addressing whether the reduced lysosomal structures in USP8 (-) animals were linked to MVB formation? Then they observed that the abnormally enlarged vesicles, marked by the PI3P biosensor YFP-2xFYVE, are bigger but in the same number in USP8 (-) compared to wild-type animals, suggesting homotypic fusion. They confirmed this result by knocking down USP8 in a human cell line, and they observed enlarged vesicles marked by YFP-2xFYVE as well. At this point, there is quite an important issue. The use of YFP-2xFYVE to detect early endosomes requires the transfection of the cells, which has already been demonstrated to produce differences in the distribution, number, and size of PI3P-positive vesicles (doi.org/10.1080/15548627.2017.1341465). The enlarged vesicles marked by YFP-2xFYVE would not necessarily be due to the loss of UPS8. In any case, it appears relatively clear that USP8 localizes to early endosomes, and the authors claim that this localization is mediated by Rabex-5 (or Rabx-5). They finally propose that USP8 dissociates Rabx-5 from early endosomes facilitating endosome maturation.

      Weaknesses:

      The weaknesses of this study are, on one side, that the results are almost exclusively dependent on the overexpression of fusion proteins. While useful in the field, this strategy does not represent the optimal way to dissect a cell biology issue. On the other side, the way the authors construct the rationale for each approximation is somehow difficult to follow. Finally, the use of two models, C. elegans and a mammalian cell line, which would strengthen the observations, contributes to the difficulty in reading the manuscript.

      The findings are useful but do not clearly support the idea that USP8 mediates Rab5-Rab7 exchange and endosome maturation, In contrast, they appear to be incomplete and open new questions regarding the complexity of this process and the precise role of USP8 within it.

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

      As the first paper describing this phenomenon, it is adequate. However, the elucidation of the molecular mechanisms is not as exciting as it does not describe anything new. It is hoped that novel mechanisms will be elucidated in the future. In particular, the molecules involved in the reversing process could be quite interesting. Additionally, the relationship to conventional endocytic compartments, such as early and late endosomes, is not analyzed.

    2. Reviewer #2 (Public Review):

      Summary:

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

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

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

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

      Strengths:

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

      Weaknesses:

      My major concern is the experimental strategy that is used throughout the paper to induce and study the formation GUVac. Almost every experiment is conducted in suspended cells that were treated with actin depolymerising drugs (e.g. LatB) and thus almost all key conclusions are based on the results of these experiments. I only have a few suggestions that would improve these experiments or change their outcome and interpretation.

      Yet, I believe it is essential to identify the endogenous pathway leading to the actin depolymerisation that drives the formation of GUVacs in detached epithelial cells (or alternatively to figure out how it is suppressed in most detached cells). A first step in that direction would be to investigate the polymerization status of actin in MCF-10a cells that 'spontaneously' form GUVacs and to test if these cells also become resistant to anoikis.

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

    3. Reviewer #3 (Public Review):

      Summary:

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

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

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

      Strengths:

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

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

      Weaknesses:

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

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

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

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

    1. Reviewer #1 (Public Review):

      The paper 'Structural Analysis of the Dynamic Ribosome-Translocon Complex,' authored by Lewis et al., meticulously explores various conformations and states of the ribosome-translocon complex. Employing advanced techniques such as cryoEM structural determination and AlphaFold modeling, the study delves into the dynamic nature of the ribosome-translocon complex. The findings from these analyses unveil crucial insights, significantly advancing our understanding of the co-translational translocation process in cellular mechanisms.

      To begin with, the authors employed a construct comprising the first two transmembrane domains of rhodopsin as a model for studying protein translocation. They conducted in vitro translation, followed by the purification of the ribosome-translocon complex, and determined its cryoEM structures. An in-depth analysis of their ribosome-translocon complex structure revealed that the nascent chain can pass through the lateral gate of translocon Sec61, akin to the behavior of a Signaling Peptide. Additionally, Sec61 was found to interact with 28S rRNA helix 24 and the ribosomal protein uL24. In summary, their structural model aligns with the through-pore model of insertion, contradicting the sliding model.

      Secondly, the authors successfully identified RAMP4 in their ribosome-translocon complex structure. Notably, the transmembrane domain of RAMP4 mimics the binding of a Signaling Peptide at the lateral gate of Sec61, albeit without unplugging. Intriguingly, RAMP4 is exclusively present in the non-multipass translocon ribosome-translocon complex, not in those containing multipass translocon. This observation suggests that co-translational translocation specifically occurs in the Sec61 channel that includes bound RAMP4. Additionally, the authors discovered an interaction between the C-tail of ribosomal proteins uL22 and the translocon Sec61, providing valuable insights into the nascent chain's behavior.

      Moving on to the third point, the focused classification unveiled TRAP complex interactions with various components. The authors propose that the extra density observed in their novel ribosome-translocon complex can be attributed to calnexin, a major binder of TRAP according to previous studies. Furthermore, the new structure reveals a TRAP-OSTA interaction. This newly identified TRAP-OSTA interaction offers a potential explanation for why patients with TRAP delta defects exhibit congenital disorders of glycosylation.

      In conclusion, this paper presents a robust contribution to the field with its thorough structural and modeling analyses. The significance of the findings is evident, providing valuable insights into the intricate mechanisms of protein co-translational translocation. The well-crafted writing, meticulous analyses, and clear figures collectively contribute to the overall strength of the paper.

      Major points:

      (1) The identification of RAMP4 is a pivotal discovery in this paper. The sophisticated AlphaFold prediction, de novo model building of RAMP4's RBD domain, and sequence analyses provide strong evidence supporting the inclusion of RAMP4 in the ribosome-translocon complex structure.

      However, it is crucial to ensure the presence of RAMP4 in the purified sample. Particularly, a validation step such as western blotting for RAMP4 in the purified samples would strengthen the assertion that the ribosome-translocon complex indeed contains RAMP4. This is especially important given the purification steps involving stringent membrane solubilization and affinity column pull-down.

      (2) Despite the comprehensive analyses conducted by the authors, it is challenging to accept the assertion that the extra density observed in TRAP class 1 corresponds to calnexin. The additional density in TRAP class 1 appears to be less well-resolved, and the evidence for assigning it as calnexin is insufficient. The extra density there can be any proteins that bind to TRAP. It is recommended that the authors examine the density on the ER lumen side. An investigation into whether calnexin's N-globular domain and P-domain are present in the ER lumen in TRAP class 1 would provide a clearer understanding.

      (3) In the section titled 'TRAP competes and cooperates with different translocon subunits,' the authors present a compelling explanation for why TRAP delta defects can lead to congenital disorders of glycosylation. To enhance this explanation, it would be valuable if the authors could provide additional analyses based on mutations mentioned in the references. Specifically, examining whether these mutations align with the TRAP delta-OSTA structure models would strengthen the link between TRAP delta defects and the observed congenital disorders of glycosylation.

    2. Reviewer #2 (Public Review):

      Summary:

      In the manuscript 'Structural analysis of the dynamic ribosome-translocon complex' Lewis and Hegde present a structural study of the ribosome-bound multipass translocon (MPT) based on re-analysis of cryo-EM single particle data of ribosome-MPTs processing the multipass transmembrane substrate RhoTM2 from a previous publication (Smalinskaité et al, Nature 2022) and AlphaFold2 multimer modeling. Detailed analysis of the laterally open Sec61 is obtained from PAT-less particles.

      The following major claims are made:

      - TMs can bind similarly to the Sec61 lateral gate as signal peptides.

      - Ribosomal H59 is in immediate proximity to basic residues of TMs and signal peptides, suggesting it may contribute to the positive-inside rule.

      - RAMP4/SERP1 binds to the Sec61 lateral gate and the ribosome near 28S rRNA's helices 47, 57, and 59 as well as eL19, eL22, and eL31.

      - uL22 C-terminal tail binds H24/47 blocking a potential escape route for nascent peptides to the cytosol.

      - TRAP and BOS compete for binding to Sec61 hinge.

      - Calnexin TM binds to TRAPg.

      - NOMO wedges between TRAP and MPT.

      Strengths:

      The manuscript contains numerous novel new structural analyses and their potential functional implications. While all findings are exciting, the highlight is the discovery of RAMP4/SERP1 near the Sec61 lateral gate. Overall, the strength is the thorough and extensive structural analysis of the different high-resolution RTC classes as well as the expert bioinformatic evolutionary analysis.

      Weaknesses:

      A minor downside of the manuscript is the sheer volume of analyses and mechanistic hypotheses, which makes it sometimes difficult to follow. The authors might consider offloading some analyses based on weaker evidence to the supplement to maximize impact.

    1. Joint Public Review:

      Summary:

      This study presents an immunotherapeutic strategy for treating mouse cutaneous squamous cell carcinoma (mCSCC) using serum from mice inoculated with mCSCC. The author hypothesizes that antibodies in the generated serum could aid the immune system in tumor volume reduction. The study results showed a reduction in tumor volume and altered expression of several cancer markers (p53, Bcl-xL, NF-κB, Bax) suggesting the potential effectiveness of this approach.

      Strengths:

      The approach shows potential effect on preventing tumor progression, from both the tumor size and the cancer biomarker expression levels bringing attention to the potential role of antibodies and B cell responses in cancer therapy.

      Weaknesses:

      These are some of the specific things that the author could consider to strengthen the evidence supporting the claims in their study.

      (1) The study fails to provide evidence of the specific effect of mCSCC-antibodies on mCSCC. The study utilized serum which also contains many immune response factors like cytokines that could contribute to tumor reduction. There is no information on serum centrifugation conditions, which makes it unclear whether immune components like antigen-specific T cells, activated NK cells, or other immune cells were removed from the serum. The study does not provide evidence of neutralizing antibodies through isolation, analysis of B cell responses, or efficacy testing against specific cancer epitopes. To affirm the specific antibodies' role in the observed immune response, isolating antibodies rather than employing whole serum could provide more conclusive evidence. Purifying the serum to isolate mCSCC-binding antibodies, such as through protein A purification, and ELISA would have been more useful to quantify the immune response. It would be interesting to investigate the types of epitopes targeted following direct tumor cell injection. A more thorough characterization of the antibodies, including B cell isolation and/or hybridoma techniques, would strengthen the claim.

      (2) In the study design, the control group does not account for the potential immunostimulatory effects of serum injection itself. A better control would be tumor-bearing mice receiving serum from healthy non-mCSCC-exposed mice. Additionally, employing a completely random process for allocating the treatment groups would be preferable. Also, the study does not explain why intravenous injection of tumor cells would produce superior antibodies compared to those naturally generated in mCSCC-bearing mice.

      (3) In Figure 2B, it would be more helpful if the author could provide raw data/figures of the tumor than just the bar graph. Similarly in Figure 3, the author should show individual data points in addition to the error bar to visualize the actual distribution.

      (4) The author mentioned that different stages of tumor cells have different surface biomarkers. Therefore, experimenting with injecting tumor cells at various stages could reveal the most immunogenic stage. Such an approach would allow for a comparative analysis of immune responses elicited by tumor cells at different stages of development.

      (5) In the abstract the author mentioned that using mCSCC is a proof-of-concept for this potential cancer treatment strategy. The discussion session should extend to how this strategy might apply to other cancer types beyond carcinoma.

    1. Reviewer #2 (Public Review):

      Summary:

      The authors provide strong evidence that bacteria, such as E. coli, compete with tumor cells for iron resources and consequently reduce tumor growth. When sequestration between LCN2 and bacterobactin is blocked by upregulating CDG(DGC-E. coli) or salmochelin(IroA-E.coli), E. coli increase iron uptake from the tumor microenvironment (TME) and restrict iron availability for tumor cells. Long-term remission in IroA-E.coli treated mice is associated with enhanced CD8+ T cell activity. Additionally, systemic delivery of IroA-E.coli shows a synergistic effect with chemotherapy reagent oxaliplatin to reduce tumor growth.

      Strengths:

      It is important to identify the iron-related crosstalk between E. coli and TME. Blocking lcn2-bacterobactin sequestration by different strategies consistently reduce tumor growth.

      Weaknesses:

      As engineered E.coli upregulate their function to uptake iron, they may increase the likelihood of escaping from nutritional immunity (LCN2 becomes insensitive to sequester iron from the bacteria). Would this raise the chance of developing sepsis? Do authors think that it is safe to administrate these engineered bacteria in mice or humans?

    2. Reviewer #3 (Public Review):

      Summary:

      Based on their observation that tumor has an iron-deficient microenvironment, and the assumption that nutritional immunity is important in bacteria-mediated tumor modulation, the authors postulate that manipulation of iron homeostasis can affect tumor growth. This paper uses straightforward in vitro and in vivo techniques to examine a specific and important question of nutritional immunity in bacteria-mediated tumor therapy. They are successful in showing that manipulation of iron regulation during nutritional immunity does affect the virulence of the bacteria, and in turn the tumor. These findings open future avenues of investigation, including the use of different bacteria, different delivery systems for therapeutics, and different tumor types. The authors were also successful in addressing the reviewer's concerns adequately.

    3. Reviewer #1 (Public Review):

      In this manuscript, Huang and colleagues explored the role of iron in bacterial therapy for cancer. Using proteomics, they revealed the upregulation of bacterial genes that uptake iron, and reasoned that such regulation is an adaptation to the iron-deficient tumor microenvironment. Logically, they engineered E. Coli strains with enhanced iron-uptake efficiency, and showed that these strains, together with iron scavengers, suppress tumor growth in a mouse model. Lastly, they reported the tumor suppression by IroA-E. Coli provides immunological memory via CD8+ T cells. In general, I find the findings in the manuscript novel and the evidence convincing.

      (1) Although the genetic and proteomic data are convincing, would it be possible to directly quantify the iron concentration in (1) E. Coli in different growth environments, and (2) tumor microenvironment? This will provide functional consequence of upregulating genes that import iron into the bacteria.

      (2) Related to 1, the experiment to study the synergistic effect of CDG and VLX600 (lines 139-175) is very nice and promising, but one flaw here is a lack of the measurement of iron concentration. Therefore, a possible explanation could be that CDG acts in another manner, unrelated to iron uptake, that synergizes with VLX600's function to deplete iron from cancer cells. Here, a direct measurement of iron concentration will show the effect of CDG on iron uptake, thus complementing the missing link.

      (3) Lines 250-268: Although statistically significant, I would recommend the authors characterize the CD8+ T cells a little more, as the mechanism now seems quite elusive. What signals or memories do CD8+ T cells acquire after IroA-E. Coli treatment to confer their long-term immunogenicity?

      (4) Perhaps this goes beyond the scope of the current manuscript, but how broadly applicable is the observed iron-transport phenomenon in other tumor models? I would recommend the authors to either experimentally test it in another model, or at least discuss this question.

    1. Reviewer #2 (Public Review):

      Summary:

      This combined experimental-theoretical paper introduces a novel two-domain statistical thermodynamic model (primarily Equation 1) to study allostery in generic systems but focusing here on the tetracycline repressor (TetR) family of transcription factors. This model, building on a function-centric approach, accurately captures induction data, maps mutants with precision, and reveals insights into epistasis between mutations.

      Strengths:

      The study contributes innovative modeling, successful data fitting, and valuable insights into the interconnectivity of allosteric networks, establishing a flexible and detailed framework for investigating TetR allostery. The manuscript is generally well-structured and communicates key findings effectively.

      Comments on revised version:

      I am happy with the changes made by the authors

    2. Reviewer #1 (Public Review):

      Summary:

      The authors' earlier deep mutational scanning work observed that allosteric mutations in TetR (the tetracycline repressor) and its homologous transcriptional factors are distributed across the structure instead of along the presumed allosteric pathways as commonly expected. Especially, in addition, the loss of the allosteric communications promoted by those mutations, was rescued by additional distributed mutations. Now the authors develop a two-domain thermodynamic model for TetR that explains these compelling data. The model is consistent with the in vivo phenotypes of the mutants with changes in parameters, which permits quantification. Taken together their work connects intra- and inter-domain allosteric regulation that correlate with structural features. This leads the authors to suggest broader applicability to other multidomain allosteric proteins.

      Here the authors follow their first innovative observations with a computational model that captures the structural behavior, aiming to make it broadly applicable to multidomain proteins. Altogether, an innovative and potentially useful contribution.

      Weaknesses:

      None that I see, except that I hope that in the future, if possible, the authors would follow with additional proteins to further substantiate the model and show its broad applicability. I realize however the extensive work that this would entail.

    1. Reviewer #1 (Public Review):

      Original review:<br /> The authors report here interesting data on the interactions mediated by the SH3 domain of BIN1 that expand our knowledge on the role of the SH3 domain of BIN1 in terms of mediating specific interactions with a potentially high number of proteins and how variants in this region alter or prevent these protein-protein interactions. These data provide useful information that will certainly help to further dissect the networks of proteins that are altered in some human myopathies as well as the mechanisms that govern the correct physiological activity of muscle cells.

      The work is mostly based on improved biochemical techniques to measure protein-protein interaction and provide solid evidence that the SH3 domain of BIN1 can establish an unexpectedly high number of interactions with at least a hundred cellular proteins, among which the authors underline the presence of other proteins known to be causative of skeletal muscle diseases and not known to interact with BIN1. This represents an unexpected and interesting finding relevant to better define the network of interactions established among different proteins that, if altered, can lead to muscle disease. An interesting contribution is also the detailed identification of the specific sites, namely the Proline-Rich Motifs (PRMs) that in the interacting proteins mediate binding to the BIN1 SH3 domain. Less convincing, or too preliminary in my opinion, are the data supporting BIN1 co-localization with PRC1. Indeed, the affinity of PRC1 is significantly lower than that of DNM2, an established BIN1 interacting protein. Thus, this does not provide compelling evidence to support PRC1 as a significant interactor of BIN1. Similarly, the localization data appears somewhat preliminary to substantiate a role of BIN1 in mitotic processes. These findings may necessitate additional experimental work to be more convincing.

      Comments on revision:<br /> I acknowledge the significant changes made by the authors in the revised manuscript. However, I remain puzzled by the data concerning the interaction between BIN1 and PRC1. While I agree with the authors that even weak interactions among proteins can be significant, I am hesitant to accept a priori that the lack of clear evidence of colocalization between proteins can be justified solely by their low affinity.

      Moreover, the possibility that other mitotic proteins may be potential partners of BIN1 does not inherently support an interaction between BIN1 and PRC1. I suggest that the authors present the interaction with PRC1 as a potential event and emphasize that further studies are needed to definitively establish it.

    2. Reviewer #2 (Public Review):

      Original review:<br /> Summary:<br /> In this paper, Zambo and coworkers use a powerful technique, called native holdup, to measure the affinity of the SH3 domain of BIN1 for cellular partners. Using this assay, they combine data using cellular proteins and proline-containing fragments in these proteins to identify 97 distinct direct binding partners of BIN1. They also compare the binding interactome of the BIN1 SH3 domain to the interactome of several other SH3 domains, showing varying levels of promiscuity among SH3 domains. The authors then use pathway analysis of BIN1 binding partners to show that BIN1 may be involved in mitosis. Finally, the authors examine the impact of clinically relevant mutations of the BIN1 SH3 domain on the cellular interactome. The authors were able to compare the interactome of several different SH3 domains and provide novel insight into the cellular function of BIN1. Generally, the data supports the conclusions, although the reliance on one technique and the low number of replicates in each experiment is a weakness of the study.

      Strengths:<br /> The major strength of this paper is the use of holdup and native holdup assays to measure the affinity of SH3 domains to cellular partners. The use of both assays using cell-derived proteins and peptides derived from identified binding partners allows the authors to better identify direct binding partners. This assay has some complexity but does hold the possibility of being used to measure the affinity of the cellular interactome of other proteins and protein domains. Beyond the utility of the technique, this study also provides significant insight into the cellular function of BIN1. The authors have strong evidence that BIN1 might have an undiscovered function in cellular mitosis, which potentially highlights BIN1 as a drug target. Finally, the study provides outstanding data on the cellular binding properties and partners of seven distinct SH3 domains, showing surprising differences in the promiscuity of these proteins.

      Weaknesses:<br /> There are three major weaknesses of the study. First, the authors rely completely on a single technique to measure the affinity of the cellular interactome. The native holdup is a relatively new technique that is powerful yet relatively unproven. However, it appears to have the capacity to measure the relative affinity of proteins. Second, the authors appear to use a relatively small number of replicates for the holdup assays. There is no information in the legends about the number of replicates but the materials and methods suggest the native holdup data is from a single experimental replicate with multiple technical replicates. Finally, the authors' data using cellular proteins and fragments show that the affinity of the whole proteins is 5-20 fold lower than individual proline-containing fragments. The authors state that this difference suggests that there is cooperativity between different proline-rich sites of the binding partners of BIN1, yet BIN1 only has one SH3 domain. It is unclear what the molecular mechanism of the cooperative interaction would be exactly since there would be only one SH3 domain to bind the partner. An alternative interpretation would be that the BIN 1 SH3 domain requires sequences outside of the short proline-rich regions for high-affinity interactions with cellular partners, a hypothesis that is supported by other studies.

      Comments on revision:<br /> I thank the authors for their thoughtful response. I have additional comments.

      I appreciate that this is not a techniques paper and that the authors have done more detailed work in a separate publication. It would be helpful to readers not familiar with this new method to more fully describe this technique in this manuscript.

      I also thank the authors for their description of why they performed only 1 biological replicate of the experiment. However, I still believe that multiple biological replicates will provide more rigorous and reproducible data. The data the authors provide actually argues for the inclusion of more biological replicates. They state they performed 2 separate nHU replicates using different mass spectrometers. It is unclear if this data uses the same lysates and protein preparations, but by the data, the two methods detected a total of 207 distinct binding partners. Only 29 of these were significant binders in both replicates and only 90 were detected binders in both replicates. 117 binding partners were found in only one replicate suggesting a significant differences between replicates. Different batches of SH3 domains can have different activities and different replicates of cell lysates can vary, even when made from the same cell line. Thus, there can still be significant differences between replicates in this method. I appreciate the difficulty of performing and analyzing multiple biological replicates, but it is the most rigorous way to identify potential cellular partners.

      I also thank the author for including the mechanistic discussion about the differences between peptides and whole proteins. There is literature showing that regions outside of the short PxxP regions drive binding to SH3 domains, especially for the GRB2 family of adaptor proteins.

    1. Joint Public Review:

      Zhang et. al. presents compelling results that support the identification of epigenetically mediated control for the recognition of dihydropyrimidine dehydrogenase (DPYD) gene expression that is linked with cancer treatment resistance 5-fluorouracil. The experimental approach was developed and pursued with in vitro and in vivo strategies. Combining molecular, cellular, and biochemical approaches, the authors identify a germline variant with compromised enhancer control. Several lines of evidence were presented that are consistent with increased CEBP recruitment to the DPYD regulatory domain with consequential modifications in promoter-enhancer interactions that are associated with compromised 5-fluorouracil resistance. Functional identification of promoter and enhancer elements was validated by CRISPRi and CRISPRa assays. ChIP and qPCR documented histone marks that can account for the control of DPYD gene expression were established. Consistency with data from patient-derived specimens and direct assessment of 5-fluorouracil sensitivity provides confidence in the proposed mechanisms. The model is additionally supported by genome data from a population with high "compromised allele frequency". It can be informative to directly demonstrate DPYD promoter-enhancer interactions. However, the genetic variants support the integration of regulatory activities.

    1. 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 a 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.

    2. Reviewer #2 (Public Review):

      Summary:

      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 redeye K125. The authors mutated K125 to a negatively charged residue to mimic this effect and 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:

      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:

      The revised version of the manuscript is improved, and the authors have addressed the review comments/criticisms in a satisfactory manner.

    3. Reviewer #3 (Public Review):

      Summary:

      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.

      Strength:

      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:

      While the structure of the TM2-TM3 loop may suggest a mechanism for stabilizing the closed conformation, the EM density is not strong enough to support direct interaction with carbamylated or mutated K125.

      Overall, the cryo-EM structures presented in this study support their proposing mechanism in which carbamylation at K125 promotes Cx26 gap junction closure. Through careful control of the pH and PCO2 for each cryo-EM sample, the current study substantiated that the more closed conformation observed in high PCO2 is independent of pH but likely triggered by carbamylation. This was unclear from their prior cryo-EM map of wildtype Cx26 at high PCO2.

      While the new structures successfully visualize the TM2-TM3 loop, which likely plays significant roles in CO2-regulated Cx26 activity, further studies are necessary to understand the underlying mechanism. For instance, the current study lacks explanation regarding what propels the movement of the N-terminal helix, how carbamylated K125 interacts with the TM2-TM3 loop, the importance of the lipids visualized in the map, or the reason why gap junctions are constitutively open while hemichannels are closed under normal PCO2 levels

    1. Reviewer #1 (Public Review):

      Muscle models are important tools in the fields of biomechanics and physiology. Muscle models serve a wide variety of functions, including validating existing theories, testing new hypotheses, and predicting forces produced by humans and animals in health and disease. This paper attempts to provide an alternative to Hill-type muscle models that includes contributions of titin to force enhancement over multiple time scales. Due to the significant limitations of Hill-type models, alternative models are needed and therefore the work is important and timely.

      The effort to include a role for titin in muscle models is a major strength of the methods and results. The results clearly demonstrate the weaknesses of Hill models and the advantages of incorporating titin into theoretical treatments of muscle mechanics. Another strength is to address muscle mechanics over a large range of time scales.

      The authors succeed in demonstrating the need to incorporate titin in muscle models, and further show that the model accurately predicts in situ force of cat soleus (Kirsch et al. 1994; Herzog & Leonard, 2002) and rabbit posts myofibrils (Leonard et al. 2010). However, it remains unclear whether the model will be practical for use with data from different muscles or preparations. Several ad hoc modifications were described in the paper, and the degree to which the model requires parameter optimization for different muscles, preparations and experiment types remains unclear.

      I think the authors should state how many parameters require fitting to the data vs the total number of model parameters. It would also be interesting for the authors to discuss challenges associated with modeling ex vivo and in vivo data sets, due to differences in means of stimulation vs. model inputs.

    2. Reviewer #2 (Public Review):

      This model of skeletal muscle includes springs and dampers which aim to capture the effect of crossbridge and titin stiffness during the stretch of active muscle. While both crossbridge and titin stiffness have previously been incorporated, in some form, into models, this model is the first to simultaneously include both. The authors suggest that this will allow for the prediction of muscle force in response to short-, mid- and long-range stretches. All these types of stretch are likely to be experienced by muscle during in vivo perturbations, and are known to elicit different muscle responses. Hence, it is valuable to have a single model which can predict muscle force under all these physiologically relevant conditions. In addition, this model dramatically simplifies sarcomere structure to enable this muscle model to be used in multi-muscle simulations of whole-body movement.

      In order to test this model, its force predictions are compared to 3 sets of experimental data which focus on short-, mid- and long-range perturbations, and to the predictions of a Hill-type muscle model. The choice of data sets is excellent and provide a robust test of the model's ability to predict forces over a range of length perturbations. However, I find the comparison to a Hill-type muscle model to be somewhat limiting. It is well established that Hill-type models do not have any mechanism by which they can predict the effect of active muscle stretch. Hence, that the model proposed here represents an improvement over such a model is not a surprise. Many other models, some of which are also simple enough to be incorporated into whole-body simulations, have incorporated mechanistic elements which allow for the prediction of force responses to muscle stretch. And it is not clear from the results presented here that this model would outperform such models.

      The paper begins by outlining the phenomenological vs mechanistic approaches taken to muscle modelling, historically. It appears, although is not directly specified, that this model combines these approaches. A somewhat mechanistic model of the response of the crossbridges and titin to active stretch is combined with a phenomenological implementation of force-length and force-velocity relationships. This combination of approaches may be useful improving the accuracy of predictions of muscle models and whole-body simulations, which is certainly a worthy goal. However, it also may limit the insight that can be gained. For example, it does not seem that this model could reflect any effect of active titin properties on muscle shortening. In addition, it is not clear to me, either physiologically or in the model, what drives the shift from the high stiffness in short-range perturbations to the somewhat lower stiffness in mid-range perturbations.

    1. Reviewer #2 (Public Review):

      In this revised manuscript Aguillon and collaborators convincingly demonstrating that CLK is required for free-running behavioral rhythms under constant conditions in the Cnidarian Nematostella. The results also convincingly show that CLK impacts rhythmic gene expression in this organism. This original work thus demonstrate that CLK was recruited very early during animal evolution in the circadian clock mechanism to optimize behavior and gene expression with the time-of-day. The manuscript could still benefit from some improvements so that it is more accessible for a wide readership.

    1. Reviewer #1 (Public Review):

      Summary:

      In this manuscript, Ruichen Yang et al. investigated the importance of BMP signaling in preventing microtia. Authors showed that Cre recombinase mediated deletion of Bmpr1a using skeletal stem specific Cre Prx1Cre leads to microtia in adult and young mice. In these mice, distal auricle is more affected than middle and proximal. In these Bmpr1a floxed Prx1Cre mice, auricle chondrocyte start to differentiate into osteoblasts through increase in PKA signaling. The authors showed human single-cell RNA-Seq data sets where they observed increased PKA signaling in microtia patient which resembles their animal model experiments.

      Strengths:

      Although the importance of BMP signaling in skeletal tissues has been previously reported, the importance of its role in microtia prevention is novel and very promising to study in detail. The authors satisfied the experimental questions by performing correct methods and explaining the results in detail.

    2. Reviewer #2 (Public Review):

      The authors (Yang et al.) present a well-executed study of a mouse model of Bmpr1a focusing on microtia development and pathogenesis.

      The authors report that the generation of the Bmpr1a in Prrx1+ cells in adult mice helps characterize the developmental progression of the external ear.

      The authors explain how auricular chondrocytes differ from growth plates or other chondrocytes and BMP-Smd1/5/9 activation, which is required to maintain chondrocyte fate in the distal part of the ear. The authors explain with evidence how BMP signaling actively maintains auricle cartilage in the post-developmental stage.

      Elegant immunofluorescence staining, excellent histology preparations and dissections, excellent microscopy, sufficient experimental sample size, and good statistical analyses support the results. The study is well grounded in extensively reviewed and cited existing literature. This report sets the stage for a comprehensive interrogation of Bmpr1a deficiency and ear defects.

    1. Reviewer #1 (Public Review):

      In this study, the authors address a fundamental unresolved question in cerebellar physiology: do synapses between granule cells (GCs) and Purkinje cells (PCs) made by the ascending part of the axon (AA) have different synaptic properties from those made by parallel fibers? This is an important question, as GCs integrate sensorimotor information from numerous brain areas with a precise and complex topography.

      Summary:<br /> The authors argue that CGs located close to PCs essentially contact PC dendrites via the ascending part of their axons. They demonstrate that joint high-frequency (100 Hz) stimulation of distant parallel fibers and local CGs potentiates AA-PC synapses, while parallel fiber-PC synapses are depressed. On the basis of paired-pulse ratio analysis, they concluded that evoked plasticity was postsynaptic. When individual pathways were stimulated alone, no LRP was observed. This associative plasticity appears to be sensitive to timing, as stimulation of parallel fibers first results in depression, while stimulation of the AA pathway has no effect. NMDA, mGluR1 and GABAA receptors are involved in this plasticity.

      Strengths:<br /> Overall, the associative modulation of synaptic transmission is convincing, and the experiments carried out support this conclusion. However, weaknesses limit the scope of the results.

      Weaknesses:<br /> One of the main weaknesses of this study is the suggestion that high-frequency parallel-fiber stimulation cannot induce long term potentiation unless combined with AA stimulation. Although we acknowledge that the stimulation and recording conditions were different from those of other studies, according to the literature (e.g. Bouvier et al 2016, Piochon et al 2016, Binda et al, 2016, Schonewille et al 2021 and others), high-frequency stimulation of parallel fibers leads to long-term postsynaptic potentiation under many different experimental conditions (blocked or unblocked inhibition, stimulation protocols, internal solution composition). Furthermore, in vivo experiments have confirmed that high-frequency parallel fibers are likely to induce long-term potentiation (Jorntell and Ekerot, 2002; Wang et al, 2009). This article provides further evidence that long-term plasticity (LTP and LTD) at this connection is a complex and subtle mechanism underpinned by many different transduction pathways. It would therefore have been interesting to test different protocols or conditions to explain the discrepancies observed in this dataset.<br /> Another important weakness is the lack of evidence that the AAs were stimulated. Indeed, without filling the PC with fluorescent dye or biocytin during the experiment, and without reconstructing the anatomical organization, it is difficult to assess whether the stimulating pipette is positioned in the GC cluster that is potentially in contact with the PC with the AAs. According to EM microscopy, AAs account for 3% of the total number of synapses in a PC, which could represent a significant number of synapses. Although the idea that AAs repeatedly contact the same Purkinje cell has been propagated, to the best of the review author's knowledge, no direct demonstration of this hypothesis has yet been published. In fact, what has been demonstrated (Walter et al 2009; Spaeth et al 2022) is that GCs have a higher probability of being connected to nearby PCs, but are not necessarily associated with AAs.

    2. Reviewer #2 (Public Review):

      Summary:

      The authors describe a form of synaptic plasticity at synapses from granule cells onto Purkinje cells in the mouse cerebellum, which is specific to synapses proximal to the cell body but not to distal ones. This plasticity is induced by the paired or associative stimulation of the two types of synapses because it is not observed with stimulation of one type of synapse alone. In addition, this form of plasticity is dependent on the order in which the stimuli are presented, and is dependent on NMDA receptors, metabotropic glutamate receptors and to some degree on GABAA receptors. However, under all experimental conditions described, there is a progressive weakening or run-down of synaptic strength. Therefore, plasticity is not relative to a stable baseline, but relative to a process of continuous decline that occurs whether or not there is any plasticity-inducing stimulus.

      Strengths:

      The focus of the authors on the properties of two different synapse-types on cerebellar Purkinje cells is interesting and relevant, given previous results that ascending and parallel fiber synapses might be functionally different and undergo different forms of plasticity. In addition, the interaction between these two synapse types during plasticity is important for understanding cerebellar function. The demonstration of timing and order-dependent potentiation of only one pathway, and not another, after associative stimulation of both pathways, changes our understanding of potential plasticity mechanisms. In addition, this observation opens up many new questions on underlying intracellular mechanisms as well as on its relevance for cerebellar learning and adaptation.

      Weaknesses and suggested improvements:

      A concern with this study is that all recordings demonstrate "rundown", a progressive decrease in the amplitude of the EPSC, starting during the baseline period and continuing after the plasticity-induction stimulus. In the absence of a stable baseline, it is hard to know what changes in strength actually occur at any set of synapses. Moreover, the issues that are causing rundown are not known and may or may not be related to the cellular processes involved in synaptic plasticity. This concern applies in particular to all the experiments where there is a decrease in synaptic strength.<br /> The authors should consider changes in the shape of the EPSC after plasticity induction, as in Fig 1 (orange trace) as this could change the interpretation.<br /> In addition, the inconsistency with previous results is surprising and is not explained; specifically, that no PF-LTP was induced by PF-alone repeated stimulation.<br /> The authors test the role of NMDARs, GABAARs and mGluRs in the phenotype they describe. The data suggest that the form of plasticity described here is dependent on any one of the three receptors. However, the location of these receptors varies between the Purkinje cells, granule cells and interneurons. The authors do not describe a convincing hypothetical model in which this dependence can be explained. They suggest that there is crosstalk between AA and PF synapses via endocannabinoids downstream of mGluR or NO downstream of NMDARs. However, it is not clear how this could lead to the long-term potentiation that they describe. Also, there is no long-lasting change in paired-pulse ratio, suggesting an absence of changes in presynaptic release.<br /> Is the synapse that undergoes plasticity correctly identified? In this study, since GABAergic inhibition is not blocked for most experiments, PF stimulation can result in both a direct EPSC onto the Purkinje cell and a disynaptic feedforward IPSC. The authors do address this issue with Supplementary Fig 3, where the impact of the IPSC on the EPSC within the EPSC/IPSC sequence is calculated. However, a change in waveform would complicate this analysis. An experiment with pharmacological blockade will make the interpretation more robust. The observed dependence of the plasticity on GABAA receptors is an added point in favor of the suggested additional experiments.<br /> A primary hypothesis of this study is that proximal, or AA, and distal, or PF, synapses are different and that their association is specifically what drives plasticity. The alternative hypothesis is that the two synapse-types are the same. Therefore, a good control for pairing AA with PF would be to pair AA with AA and PF with PF, thereby demonstrating that pairing with each other is different from pairing with self.<br /> It is hypothesized that the association of a PF input with an AA input is similar to the association of a PF input with a CF input. However, the two are very different in terms of cellular location, with the CF input being in a position to directly interact with PF-driven inputs. Therefore, there are two major issues with this hypothesis: 1) how can sub-threshold activity at one set of synapses affect another located hundreds of micrometers away on the same dendritic tree? 2) There is evidence that the CF encodes teaching/error or reward information, which is functionally meaningful as a driver of plasticity at PF synapses. The AA synapse on one set of Purkinje cells is carrying exactly the same information as the PF synapses on another set of Purkinje cells further up and down the parallel fiber beam. It is suggested that the two inputs carry sensory vs. motor information, which is why this form of plasticity was tested. However, the granule cells that lead to both the AA and PF synapses are receiving the same modalities of mossy fiber information. Therefore, one needs to presuppose different populations of granule cells for sensory and motor inputs or receptive field and contextual information. As a consequence, which granule cells lead to AA synapses and which to PF synapses will change depending on which Purkinje cell you're recording from. And that's inconsistent with there being a timing dependence of AA-PF pairing in only one direction. Overall, it would be helpful to discuss the functional implications of this form of plasticity.

    3. Reviewer #3 (Public Review):

      Granule cells' axons bifurcate to form parallel fibers (PFs) and ascending axons (AAs). While the significance of PFs on cerebellar plasticity is widely acknowledged, the importance of AAs remains unclear. In the current paper, Conti and Auger conducted electrophysiological experiments in rat cerebellar slices and identified a new form of synaptic plasticity in the AA-Purkinje cell (PC) synapses. Upon simultaneous stimulation of AAs and PFs, AA-PC EPSCs increased, while PFs-EPSCs decreased. This suggests that synaptic responses to AAs and PFs in PCs are jointly regulated, working as an additional mechanism to integrate motor/sensory input. This finding may offer new perspectives in studying and modeling cerebellum-dependent behavior. Overall, the experiments are performed well. However, there are two weaknesses. First, the baseline of electrophysiological recordings is influenced significantly by run-down, making it difficult to interpret the data quantitatively. The amplitude of AA-EPSCs is relatively small and the run-down may mask the change. The authors should carefully reexamine the data with appropriate controls and statistics. Second, while the authors show AA-LTP depends on mGluR, NMDA receptors, and GABA-A receptors, which cell types express these receptors and how they contribute to plasticity is not clarified. The recommended experiments may help to improve the quality of the manuscript.

    1. Reviewer #1 (Public Review):

      Summary:

      The manuscript proposes a series of steps using the FIJI environment, the authors have created a plugin for the initial steps of the process, merging images into an RGB stack, conversion to HSV, and then using brightness for reference and hue to distinguish the phases of the cycle. Then, the well-known Trackmate plugin was used to identify single cells and extract intensities. The data was further post-processed in R, where a series of steps, smoothing, scaling, and addressing missing frames were used to train a random forest. Hard-coded values of hue were used to distinguish G1, S, and G2/M. The process was validated with a score comparing the quality of the tracks and the authors reported the successful measure of the cell cycles.

      Strengths:

      The implementation of the pipeline seems easy, although it requires two separate platforms: Fiji and R. A similar approach could be implemented in a single programming environment like Python or Matlab and there would not be any need to export from one to the other. However, many labs have similar setups and that is not necessarily a problem.

      Weaknesses:

      I found two important weaknesses in the proposal:

      (1) The pipeline relies on a large number of hard-coded conditions: size of Gaussian blur (Gaussian should be written in uppercase), values of contrast, size of filters, levels of intensity, etc. Presumably, the authors followed a heuristic approach and tried values of these and concluded that the ones proposed were optimal. A proper sensitivity analysis should be performed. That is, select a range of values of the variables and measure the effect on the output.

      (2) Linked to the previous comments. Other researchers that want to follow the pipeline would have either to have exactly the same acquisition conditions as the manuscript or start playing with values and try to compensate for any difference in their data (cell diameter, fluorescent intensity, etc.) to see if they can match the results of the manuscript.

    2. Reviewer #2 (Public Review):

      Summary:

      This paper presents an automated method to track individual mammalian cells as they progress through the cell cycle using the FUCCI system and applies the method to look at different tumor cell lines that grow in suspension and determine their cell cycle profile and the effect of drugs that directly affect the cell cycles, on progression through the cell cycle for a 72 hour period.

      Strengths:

      This is a METHODS paper. The one potentially novel finding is that they can identify cells that are at the G1-S transition by the change in color as one protein starts to go up and the other one goes down, similar to the change seen as cells enter G2/M.

      Weaknesses:

      They did not clearly indicate whether the G1/S cells are identified automatically or need to be identified by the person reviewing the data. In Figures 1 and S1, the movie shows cells with no color at a time corresponding to what is about the G1/S transition. Their assigned cell cycle phase is shown in Figure 1 but not in Figure S1. None of these pictures show the G1/S cells that they talk about being able to detect with a different color.

    1. Reviewer #2 (Public Review):

      In this study, Wang et al., report the significance of XAP5L and XAP5 in spermatogenesis, involved in transcriptional regulation of the ciliary gene in testes. In previous studies, the authors demonstrate that XAP5 is a transcription factor required for flagellar assembly in Chlamydomonas. Continuing from their previous study, the authors examine the conserved role of the XAP5 and XAP5L, which are the orthologue pair in mammals.

      XAP5 and XAP5L express ubiquitously and testis specifically, respectively, and their absence in the testes causes male infertility with defective spermatogenesis. Interestingly, XAP5 deficiency arrests germ cell development at the pachytene stage, whereas XAP5L absence causes impaired flagellar formation. RNA-seq analyses demonstrated that XAP5 deficiency suppresses ciliary gene expression including Foxj1 and Rfx family genes in early testis. By contrast, XAP5L deficiency abnormally remains Foxj1 and Rfx genes in mature sperm. From the results, the authors conclude that XAP5 and XAP5L are the antagonistic transcription factors that function upstream of Foxj1 and Rfx family genes.

      This reviewer thinks the overall experiments are performed well and that the manuscript is clear. However, the current results do not directly support the authors' conclusion. For example, the transcriptional function of XAP5 and XAP5L requires more evidence. In addition, this reviewer wonders about the conserved XAP5 function of ciliary/flagellar gene transcription in mammals - the gene is ubiquitously expressed despite its functional importance in flagellar assembly in Chlamydomonas. Thus, this reviewer thinks authors are required to show more direct evidence to clearly support their conclusion with more descriptions of its role in ciliary/flagellar assembly.

    2. Reviewer #1 (Public Review):

      Summary:

      Wang et al. generate XAP5 and XAP5L knockout mice and find that they are male infertile due to meiotic arrest and reduced sperm motility, respectively. RNA-Seq was subsequently performed and the authors concluded that XAP5 and XAP5L are antagonistic transcription factors of cilliogenesis (in XAP5-KO P16 testis: 554 genes were unregulated and 1587 genes were downregulated; in XAP5L-KO sperm: 2093 genes were unregulated and 267 genes were downregulated).

      Strengths:

      Knockout mouse models provided strong evidence to indicate that XAP5 and XAP5L are critical for spermatogenesis and male fertility.

      Weaknesses:

      The key conclusions are not supported by evidence. First, the authors claim that XAP5 and XAP5L transcriptionally regulate sperm flagella development; however, detailed molecular experiments related to transcription regulation are lacking. How do XAP5 and XAP5L regulate their targets? Only RNA-Seq is not enough. Second, the authors declare that XAP5 and XAP5L are antagonistic transcription factors; however, how do XAP5 and XAP5L regulate sperm flagella development antagonistically? Only RNA-Seq is not enough. Third, I am concerned about whether XAP5 really regulates sperm flagella development. XAP5 is specifically expressed in spermatogonia and XAP5-cKO mice are in meiotic arrest, indicating that XAP5 regulates meiosis rather than sperm flagella development.

    1. Reviewer #1 (Public Review):

      • A summary of what the authors were trying to achieve.

      The authors cultured pre- and Post-vaccine PBMCs with overlapping peptides encoding S protein in the presence of IL-2, IL-7, and IL-15 for 10 days, and extensively analyzed the T cells expanded during the culture; by including scRNAseq, scTCRseq, and examination of reporter cell lines expressing the dominant TCRs. They were able to identify 78 S epitopes with HLA restrictions (by itself represents a major achievement) together with their subset, based on their transcriptional profiling. By comparing T cell clonotypes between pre- and post-vaccination samples, they showed that a majority of pre-existing S-reactive CD4+ T cell clones did not expand by vaccinations. Thus, the authors concluded that highly-responding S-reactive T cells were established by vaccination from rare clonotypes.

      • An account of the major strengths and weaknesses of the methods and results.

      Strengths

      • Selection of 4 "Ab sustainers" and 4 "Ab decliners" from 43 subjects who received two shots of mRNA vaccinations.<br /> • Identification of S epitopes of T cells together with their transcriptional profiling. This allowed the authors to compare the dominant subsets between sustainers and decliners.

      Weaknesses were adequately addressed in the revised manuscript, and I do not have any additional concerns.

    2. Reviewer #3 (Public Review):

      The paper aims to investigate the relationship between anti-S protein antibody titers with the phenotypes & clonotypes of S-protein-specific T cells in people who receive SARS-CoV2 mRNA vaccines. The paper recruited a cohort of COVID-19 naive individuals who received the SARS-CoV2 mRNA vaccines and collected sera and PBMCs samples on different time points. Then, three sets of data were generated: 1). Anti-S protein antibody titers on all time points. 2) Single-cell RNAseq/TCRseq analysis for divided T cells after in vitro stimulation by S-protein. 3) Peptide epitopes for each expanded TCR clone. Based on these, the paper reports two major findings: A) Individuals having more sustained anti-S protein antibody response also have more Tfh-featured S-specific cells in their blood after 2nd-dose vaccination. B). S-specific cross-reactive T cells exist in COVID-19 naive individuals, but most of these T cell clones are not expanded after SARS-CoV-2 vaccination.

      The paper's strength is that it uses a very systemic strategy trying to dissect the relationship between antibody titers, T cell phenotypes, TCR clonotypes and corresponding epitopes. The conclusion is solid in general. However, the weaknesses include the relatively small sample size (4 sustainers vs. 4 decliners) and the use of in vitro stimulated cells for analysis, which may 'blur' the classification of T cell subsets. Nevertheless, it may have great impact on future vaccine design because it demonstrated that promoting Tfh differentiation is crucial for the longevity of antibody response. Additionally, this paper nicely showed that most cross-reactive clones that are specific to environmental/symbiotic microbes did not expand post- vaccination, providing important fundamental insights into the establishment of T-cell responses after SARS-CoV-2 vaccination.

    1. Reviewer #2 (Public Review):

      Summary:

      This work follows previous work from the group where they have demonstrated the role of TASK1 in the regulation of glucose stimulated insulin secretion. Moreover, a recent study links a mutation in KCNK16, the gene encoding TALK-1 channels to MODY. Here the authors have constructed a mouse model with the specific mutation (TALK-1 L114P mutation) and investigated the phenotype. They have to perform a couple of breeding tricks to find a model that is lethal in adult which might complicate the conclusions, however, the phenotype of the heterozygote model used have a MODY-like phenotype. The study is convincing and solid.

      Strengths:

      (1) The work is a natural follow-up from previous studies from the groups.<br /> (2) The authors present convincing and solid data that in the long perspective will help patients with this mutations.<br /> (3) Both in vivo and in vitro data are presented to give the full picture of the phenotype.<br /> (4) Data from both female and male mice are presented.

      Weaknesses:

      The authors have answered all my comments in the revised version and I find no more weaknesses. Some questions still remain but have been clearly discussed in the new version of the manuscript.

    2. Reviewer #1 (Public Review):

      Summary:

      This paper focuses on the effects of a L114P mutation in the TALK-1 channel on islet function and diabetes. This mutation is clinically relevant and a cause of MODY diabetes. This work employs a mouse model with heterozygous and homozygous mutants. The homozygous mice are homozygous lethal from severe hyperglycemia. The work shows that the mutation increases K+ currents and inhibits insulin secretion. This is a very nice paper with mechanistic insight and clear clinical importance. It is generally well written and the data is well presented.

      Comments on revision:

      I have no further comments to add at this time. The authors have adequately addressed my concerns.

    3. Reviewer #3 (Public Review):

      Summary

      The L114P gain of function mutation in the K2P channel TALK-1 encoded by KCNJ16 has been associated with maturity-onset diabetes of the young (MODY). In this study, Nakhe et al. generated mice carrying L114P TALK-1 and evaluated the impact of the mutation on pancreatic islet functions and glucose homeostasis. The authors report that the mutation increases neonatal lethality, owing to hyperglycemia caused by a lack of glucose-stimulated Ca2+ influx and insulin secretion. Adult mutant mice showed glucose intolerance and fasting hyperglycemia, which is attributed to blunted glucose-stimulated insulin secretion as well as increased glucagon secretion. Interestingly, male mice were more affected than female mice. Islets from adult mutant mice were found to have reduced Ca2+ entry upon glucose stimulation but also enhanced IP3-induced ER Ca2+ release, consistent with previous studies from the group showing a role of TALK-1 in ER Ca2+ homeostasis. Finally, comparison of bulk RNA sequencing results from WT and mutant islets revealed altered expression of genes involved in β-cell identify, function and signaling, which also contributes to the observed islet dysfunction.

      Strengths

      This is a well-executed and rigorous study that will be of great interest to the diabetes and islet biology communities. The findings provide convincing evidence supporting a causal role of the L114P gain of function TALK-1 mutation in glucose-stimulated insulin secretion defects and diabetes. The neonatal diabetes phenotype and the gender difference uncovered by the study have important clinical implications. The complexity of TALK-1 expression and hormone secretion in different endocrine cell types and how it impacts glucose homeostasis is elegantly illustrated in the L114P TALK-1 mouse model. The authors carefully and thoroughly addressed limitations of their study and discussed future directions. The importance of TALK-1 in β-cell and islet function demonstrated by this study will prompt future efforts targeting this important channel for diabetes treatment.

    1. Reviewer #1 (Public Review):

      Summary:

      Babosha et al. deeply investigate the N-terminal region of the Drosophila dosage compensation protein MSL1. Much of the prior research into the dosage compensation complex has focused on the male-specific MSL2 protein. However, the authors point out prior evidence that the N-terminus of MSL1 is important for protein function, including interaction with MSL2. Through a series of transgenic deletions and substitutions, the authors pinpoint two regions: N-terminal amino acids 3-7 and 41-65, which are critical for the binding of MSL1 to the X-chromosome and recruitment of MSL2. To deepen these observations, the authors perform well-controlled immunoprecipitation experiments to test the interaction of mutant MSL1 proteins with the lncRNA roX2, which is critical for the stability and localization of the dosage compensation complex. Through immunoprecipitation, the authors discover that the interaction of their mutant MSL1 proteins with roX2 is compromised. They suggest that the roX-MSL1 interaction is mediated by the N-terminal amino acids and is also critical for interaction with MSL2 and X-specific localization. This agrees with previous models that MSL1 and MSL2 directly interact through other regions.

      This work lays the foundation for future investigations into the overall structure of the dosage compensation machinery, which allows this unique complex to specifically target the X-chromosome through still unclear mechanisms.

      Strengths:

      The data provided by the authors is of high quality and supports the authors' conclusions, which are nicely contextualized in the text with previous models. The novelty of this study is specifically pinpointing the amino acid regions of MSL1 that interact with roX. The authors point out that, surprisingly, the N-terminal region of MSL1 is not particularly well conserved, indicating that the interactions outlined in this study might be Drosophila/Diptera-specific.

      The major strength of this study is that the authors find agreement between multiple dimensions of experimentation: the regions of MSL1 that are required for roX2 interaction (immunoprecipitation experiments) are also the regions that are critical for MSL1 localization to polytene chromosomes in an artificial female in vivo system, which are also critical for male-specific survival. The authors later suggest that it is the roX2 interaction that is responsible for the latter observations, although there is no direct evidence for this suggestion.

      Weaknesses:

      A minor weakness of the study is that it largely supports, and incrementally expands, the existing model in the field: that roX RNAs mediate the assembly of the complex on chromatin. I hesitate to call this a weakness, as supporting an existing model is still strong scientifically. However, the current study does not dramatically push the model forward.

    2. Reviewer #2 (Public Review):

      Summary:

      A deletion analysis of the MSL1 gene to assess how different parts of the protein product interact with the MSL2 protein and roX RNA to affect the association of the MSL complex with the male X chromosome of Drosophila was performed.

      Strengths:

      The deletion analysis of the MSL1 protein and the tests of interaction with MSL2 are adequate.

      Weaknesses:

      This reviewer does not adhere to the basic premise of the authors that the MSL complex is the primary mediator of dosage compensation of the X chromosome of Drosophila. Several lines of evidence from various laboratories indicate that it is involved in sequestering the MOF histone acetyltransferase to the X chromosome but there is a constraint on its action there. When the MSL complex is disrupted, there is no overall loss of compensation but there is an increase in autosomal expression. Sun et al (2013, PNAS 110: E808-817) showed that ectopic expression of MSL2 does not increase expression of the X and indeed inhibits the effect of acetylation of H4Lys16 on gene expression. Aleman et al (2021, Cell Reports 35: 109236) showed that dosage compensation of the X chromosome can be robust in the absence of the MSL complex. Together, these results indicate that the MSL complex is not the primary mediator of X chromosome dosage compensation. The authors use sex-specific lethality as a measure of disruption of dosage compensation, but other modulations of gene expression are the likely cause of these viability effects.

      A detailed explanation was provided by Birchler and Veitia (2021, One Hundred Years of Gene Balance: How stoichiometric issues affect gene expression, genome evolution, and quantitative traits. Cytogenetics and Genome Research 161: 529-550). The relevant portions of that article that pertain to Drosophila are quoted below. The cited references can be found in that publication.

      "In Drosophila, the sex chromosomes consist of an X and a Y. The Y in this species contains only a few genes required for male fertility (Zhang et al., 2020). The X consists of approximately 20% of the genome. Thus, females have two X chromosomes and males have one. Muller (1932) found that the expression of genes between the two sexes was similar but when individual genes on the X were varied in dosage they exhibited a proportional dosage effect. Each copy in a male was expressed at about twice the level as each copy in a female. Females with three X chromosomes are highly inviable but when they do survive to the adult stage, Stern (1960) found that they too exhibited dosage compensation in that the expression in the triple X genotype was similar to normal females and males. Studies in triploid flies found that dosage compensation also occurred among X; AAA, XX; AAA, and XXX; AAA genotypes via upregulation of the Xs, where X indicates the dosage of the X and A indicates the triploid nature of the autosomes (see Birchler, 2016 for further discussion). Diploid and triploid females have a similar per-gene expression but the other five genotypes each must modulate gene expression by different amounts equivalent to an inverse relationship between the X versus autosomal dosage to achieve a balanced expression between the X and the A (Birchler, 1996).

      Some years ago, mutations were sought in Drosophila that were lethal to males but viable in females. A number of such mutations were found and termed Male Specific Lethal (MSL) loci (Belote and Lucchesi, 1980). Once the products of these genes were identified, they were found to be at high concentrations on the male X chromosome (Kuroda et al., 1991). One of these genes encodes a histone acetyltransferase that acetylates Lysine16 of Histone H4 (Bone et al., 1994; Hilfiker et al., 1997). The recognition of the MSL complex and its association with the male X was an important set of contributions to an understanding of sex chromosome evolution in Drosophila (Kuroda et al., 2016). Thus, the hypothesis arose that the MSL complex accumulated this chromatin modifier on the male X to activate the expression about two-fold to bring about dosage compensation. Other data that contributed to this hypothesis were that when autoradiography of nascent transcription on salivary gland polytene chromosomes was examined in the MSL maleless mutation, the ratio of the number of grains over the X versus an autosomal region was reduced compared to the normal ratio (Belote and Lucchesi, 1980).

      It has been pointed out (Hiebert and Birchler, 1994; Bhadra et al., 1999; Pal Bhadra et al., 2005; Sun et al., 2013a; Birchler, 2016), however, that the grain counts over the X and the autosomes when considered in absolute terms rather than as a ratio show that the X more or less retained dosage compensation and the autosomal numbers are about doubled, i.e. exhibit an inverse dosage effect. The same situation occurs with the msl3 mutation (Okuno et al., 1984), another MSL gene, in that the autoradiographic grain numbers as an absolute measure show retention of X dosage compensation and an autosomal increase. The data treatment to produce an X to A ratio seemed reasonable in the context of the time when all regulation in eukaryotes was considered positive. However, when studies were conducted in such a manner as to assay the absolute effect on gene expression in the maleless mutation, in adults (Hiebert and Birchler, 1994), larvae (Hiebert and Birchler, 1994; Bhadra et al., 1999; 2000; Pal Bhadra et al., 2005), and embryos (Pal Bhadra et al., 2005), the trend was for retention of dosage compensation of X linked genes and an increase in expression of autosomal genes.

      In global studies, if the X to autosomal expression does not change between mutant and normal, one can conclude that dosage compensation is operating. However, a lower X to A ratio could be a loss of compensation or an increased transcriptome size from the increase of the autosomes, as suggested by the absolute data of Belote and Lucchesi (1980) and Okuno et al (1984) and was visualized directly in embryos (Pal Bhadra et al., 2005). The transcriptome size in aneuploids can change, which cannot be detected in RNA-seq analyses alone (Yang et al., 2021), so it is an important consideration for studies of dosage compensation. It was recently acknowledged that in MSL2 knockdowns the relative X expression is decreased and a moderate autosomal increase is found (Valsecchi et al., 2021b). A similar trend is evident in the microarray data on MSL2 knockdown in SL2 tissue culture cells (Hamada et al., 2005) and in the roX RNA (noncoding RNAs essential for MSL localization on the male X) mutants (Deng and Meller, 2006). This trend is in fact consistent with the absolute data that suggest an increase in the transcriptome size (Figure 7). A global change in transcriptome size can cause a generalized dosage compensation of a single chromosome to appear as a proportional dosage effect (loss of compensation) to some degree (Figure 7).

      Examination of expression in triple X metafemales, where there is no MSL complex, found that X-linked genes generally show dosage compensation but there is a generalized inverse effect on the autosomes, which could account for the detrimental effects of metafemales (Birchler et al., 1989; Sun et al., 2013b). An examination in metafemales of alleles of the white eye color gene that do or do not exhibit dosage compensation in males, showed the same response, namely, increased expression if there was no dosage compensation in males and no difference from normal females for the male dosage-compensated alleles (Birchler, 1992). This experiment demonstrated a relationship between the mechanism of dosage compensation in males and metafemales and implicated the inverse dosage effect in both. An involvement of the inverse effect in Drosophila dosage compensation provides an explanation for how the five levels of gene expression can be explained (Birchler, 1996), whereas an all-or-none presence of a complex on the X does not. The stoichiometric relationship of regulatory gene products provides a means to read the relative dosage at multiple doses to produce the appropriate inverse level.

      What then is the function of the MSL complex? It was discovered that the MSL complex will actually constrain the effect of H4 lysine16 acetylation to prevent it from causing overexpression of genes (Bhadra et al., 1999; 2000; Pal Bhadra et al., 2005; Sun and Birchler 2009; Sun et al., 2013a). Indeed, in the chromatin remodeling Imitation Switch (ISWI) mutants, the male X chromosome was specifically overexpressed suggesting that its normal function is needed for the constraint to occur (Pal Bhadra et al., 2005). Independently, the Mtor nuclear pore component shows a similar specific male X upregulation when Mtor is knocked down and this effect was shown to operate on the transcriptional level (Aleman et al., 2021). Interestingly, the increased expression of the X in the Mtor knockdown is accompanied by an inverse modulation of a substantial subset of autosomal genes, illustrating why the constraining process evolved to counteract male X overexpression. The constraining effect might involve a number of gene products (Birchler, 2016) and is an interesting direction for further study.

      Furthermore, when the H4Lys16 acetylase was individually targeted to reporter genes, there was an increase in expression (Sun et al., 2013a). However, when other members of the MSL complex were present in normal males or ectopically expressed, this increase did not occur (Sun et al., 2013a). It thus appears that the function of the MSL complex is to sequester the acetylase from the autosomes and constrain it on the X (Bhadra et al., 1999; 2000; Pal Bhadra et al., 2005; Sun and Birchler, 2009; Sun et al., 2013a). Indeed, in the Mtor knockdowns, the X-linked genes with the greatest upregulation were those with the greatest association with the acetylase and the H4K16ac histone mark (Aleman et al 2021), supporting the idea of a constraining activity that becomes released in the Mtor knockdown. When the MSL complex is disrupted, there is an inverse effect on the autosomes that occurs but in normal circumstances the sequestration mutes this effect. The MSL complex disruption releases the acetylase to be uniformly distributed across all chromosomes as determined cytologically (Bhadra et al., 1999) or via ChIPseq for H4Lys16ac (Valsecchi et al., 2021a). Indeed, the quantity of the H4Lys16ac mark only has a proportional effect on gene expression when the constraining activity is disrupted (Aleman et al., 2021) or when the MSL complex is not present (Sun et al., 2013a). Thus, in normal flies, there is a more or less equalized expression of the X and autosomes despite the monosomy for 20% of the genome.

      The component of the complex that is expressed in males and thought to organize the complex to the male X, MSL2, was recently found to also be associated with autosomal dosage-sensitive regulatory genes (Valsecchi et al., 2018). MSL2 was found to modulate these autosomal dosage-sensitive genes in various directions, which illustrates that MSL2 has a role in dosage balance that goes beyond the X chromosome. This finding is consistent with the evolutionary scenario that the initial attraction of the complex to the X chromosome was to upregulate dosage-sensitive genes in hemizygous regions as the progenitor Y became deleted for them, with the constraining activity evolving to prevent an overexpression as the amount of acetylase on the male X increased with time (Birchler, 2016).

      The MSL hypothesis takes an X-centric view that does not accommodate what is now known about dosage effects across the whole genome. The idea that dissolution of the MSL complex would cause a reduction in expression of the male X-linked genes without any consequences for the autosomes is not consistent with current knowledge of gene regulatory networks and their dosage sensitivity. Indeed, the finding of dosage compensation in large autosomal aneuploids that operates on the transcriptional level (Devlin et al., 1982; 1984; Birchler et al., 1990; Sun et al., 2013c), as well as a predominant inverse effect by the same (Devlin, et al., 1988; Birchler et al., 1990), argues that one must consider the inverse effect for an understanding of the evolution of dosage compensation in Drosophila (and other species). Further discussion of models of Drosophila compensation has been published (Birchler, 2016).

      What is likely to be the most critical issue with sex chromosome evolution is the consequences for dosage-sensitive regulatory genes. This fact is nicely illustrated by the retention of these types of genes in different independent vertebrate sex chromosome evolutions (Bellott and Page, 2021). In Drosophila, by contrast, dosage compensation is more of a blanket effect on most but not all X-linked genes despite the fact that many genes on the X are unlikely to have dosage detrimental effects, although dosage-sensitive genes might have played a role as noted above. The particularly large size of the X in Drosophila compared to the whole genome is potentially a contributing factor because such a large genomic imbalance is likely to modulate most genes across the genome. Also, there is no evidence of a WGD in Drosophila as there is in other species for which the inverse effect has been documented (maize, Arabidopsis, yeast, mice, human). These other species have various numbers of retained duplicate dosage-sensitive regulatory genes from WGDs. Thus, the relative change of regulatory genes in aneuploids in these species will not be as great compared to some of their interactors in the remainder of the genome, which could result in lesser magnitudes of some trans-acting effects, similar to how aneuploids in ascending ploidies have fewer effects as described above. The absence of duplicate regulatory genes in Drosophila would predict a stronger inverse effect in general and that could have been capitalized upon to produce dosage compensation of most genes on the X chromosome despite many of them not being dosage critical. While sex chromosome evolution must accommodate dosage-sensitive genes for proper development and viability, it could also be capitalized upon to evolve sexual dimorphisms in expression (Sun et al., 2013c)."

    1. Reviewer #1 (Public Review):

      Summary:

      In this study the authors demonstrated that ablation of astrocytes in lumbar spinal cord not only reduced neuropathic pain but also caused microglia activation. Furthermore, RNA sequencing and bioinformatics revealed an activation of STING/type I IFNs signal pathway in spinal cord microglia after astrocyte ablation.

      Strengths:

      The findings are novel and interesting and provide new insights into astrocyte-microglia interaction in neuropathic pain. This study may also offer a new therapeutic strategy for the treatment of debilitating neuropathic pain in patients with SCI.

      Weaknesses:

      More details are needed to justify the sample size, statistics, and sex of animals.

    2. Reviewer #2 (Public Review):

      Summary:

      In the manuscript, Zhao et al. have carried out a thorough examination of the effects of targeted ablation of resident astrocytes on behavior, cellular responses, and gene expression after spinal cord injury. Employing transgenic mice models alongside pharmacogenetic techniques, the authors have successfully achieved the selective removal of these resident astrocytes. This intervention led to a notable reduction in neuropathic pain and induced a shift in microglial cell reactivation states within the spinal cord, significantly altering transcriptome profiles predominantly associated with interferon (IFN) signaling pathways.

      Strengths:

      The findings presented add considerable value to the current understanding of the role of astrocyte elimination in neuropathic pain, offering convincing evidence that supports existing hypotheses and valuable insights into the interactions between astrocytes and microglial cells, likely through IFN-mediated mechanisms. This contribution is highly relevant and suggests that further exploration in this direction could yield meaningful results.

      Weaknesses:

      The methodology and evidence underpinning the study are solid, yet some areas would benefit from further clarification, particularly concerning methodological details and the choice of statistical analyses. Additionally, the manuscript's organization and clarity could be improved, as certain figures and schematics appear inconsistent or misleading.

    1. Reviewer #1 (Public Review):

      Summary:

      This work revealed an important finding that the blood-brain barrier (BBB) functionality changes with age and is more pronounced in males. The authors applied a non-invasive, contrast-agent-free approach of MRI called diffusion-prepared arterial spin labeling (DP-pCASL) to a large cohort of healthy human volunteers. DP-pCASL works by tracking the movement of magnetically labeled water (spins) in blood as it perfuses brain tissue. It probes the molecular diffusion of water, which is sensitive to microstructural barriers, and characterizes the signal coming from fast-moving spins as blood and slow-moving spins as tissue, using different diffusion gradients (b-values). This differentiation is then used to assess the water exchange rates (kw) across the BBB, which acts as a marker for BBB functionality. The main finding of the authors is that kw decreases with age, and in some brain regions, kw decreases faster in males. The neuroprotective role of the female sex hormone, estrogen, on BBB function is discussed as one of the explanations for this finding, supported by literature. The study also shows that BBB function remains stable until the early 60s and remarkably decreases thereafter.

      Strengths:

      The two main strengths of the study are the MRI method used and the amount of data. The authors employed a contrast-agent-free MRI method called ASL, which offers the opportunity to repeat such experiments multiple times without any health risk - a significant advantage of ASL. Since ASL is an emerging field that requires further exploration and testing, a study evaluating blood-brain barrier functionality is of great importance. The authors utilized a large dataset of healthy humans, where volunteer data from various studies were combined to create a substantial pool. This strategy is effective for statistically evaluating differences in age and gender.

      Weaknesses:

      Gender-related differences are only present in some brain regions, not in the whole brain or gray matter - which is usually the assumption unless stated otherwise. From the title, this was not clear. Including simulations could increase readers' understanding related to model fitting and the interdependence of parameters, if present. The discussion follows a clear line of argument supported by literature; however, focusing solely on AQP4 channels and missing a critical consideration of other known/proven changes in transport mechanisms through the BBB and their effects substantially weakens the discussion.

    2. Reviewer #2 (Public Review):

      Summary:

      This study used a novel diffusion-weighted pseudo-continuous arterial spin labelling (pCASL) technique to simultaneously explore age- and sex-related differences in brain tissue perfusion (i.e., cerebral blood flow (CBF) & arterial transit time (ATT) - a measure of CBF delivery to brain tissue) and blood-brain barrier (BBB) function, measured as the water exchange (kw) across the BBB. While age- and sex-related effects on CBF are well known, this study provides new insights to support the growing evidence of these important factors in cerebrovascular health, particularly in BBB function. Across the brain, the decline in CBF and BBB function (kw) and elevation in ATT were reported in older adults, after the age of 60, and more so in males compared to females. This was also evident in key cognitive regions including the insular, prefrontal, and medial temporal regions, stressing the consideration of age and sex in these brain physiological assessments.

      Strengths:

      Simultaneous assessment of CBF with BBB along with transit time and at the voxel-level helped elucidate the brain's vulnerability to age and sex-effects. It is apparent that the investigators carefully designed this study to assess regional associations of age and sex with attention to exploring potential non-linear effects.

      Weaknesses:

      It appears that no brain region showed concurrent CBF and BBB dysfunction (kw), based on the results reported in the main manuscript and supplemental information. Was an association analysis between CBF and kw performed? There is a potential effect of the level of formal education on CBF (PMID: 12633147; 15534055), which could have been considered and accounted for as well, especially for a cohort with stated diversity (age, race, sex).

    1. Reviewer #1 (Public Review):

      Updated summary:

      Glenn et al. present solid evidence that both lab and clinical Salmonella enterica serovars rapidly migrate towards human serum using an exciting approach that combines microfluidics, structural biology and genotypic analysis. The authors succeed in bringing to light a novel context for the role of serine as a bacterial chemoattractant as well as documenting what is likely to be a key step in bloodstream entry for some of the main sepsis-associated pathogens during gastrointestinal bleeding. They illustrate the generality of their findings through phylogenetic analysis, testing additional species within the Enterobacteriaceae family and showing attraction towards swine and equine serum. Their interdisciplinary approach here greatly increases the scope of their findings.<br /> I would also like to note that, whilst I enjoyed the interdisciplinary scope of this study, I am personally not well placed to review the protein structural aspects of this work.

      Additional strengths of the revised manuscript:

      All weaknesses raised in my review of the original manuscript have been satisfactorily addressed in the revised manuscript. It is interesting to note that the accumulation pattern of the bacteria 50-75 um from the source of serum could, as the author's now note, be due to the avoidance of bactericidal serum elements. Alternative explanations, however, could include chemoreceptor saturation (i.e. close to the serum source, high ligand concentrations could saturate chemoreceptors preventing further chemotaxis) or Weber's Law considerations (cell's ability to detect a given change in chemical concentrations diminishes with increasing background concentrations - thus, as cells get closer to the serum source, their ability to chemotax decreases).

      The authors have also added new experimental data and analyses and these constitute major new strengths of the revised manuscript:<br /> - The authors show that the competitive advantage of WT cells relative to a tsr mutant is removed when serum is treated with serine-racemase and this provides strong evidence that chemotaxis towards serine is responsible for the reduced attraction of the tsr mutant towards serum (i.e. rather than any possible pleiotropic effects).<br /> - New experimental data showing Salmonella enterica is also attracted to swine and equine serum (including an ex vivo swine model) is a useful addition that hints at the potential generality of the response reported here.<br /> - The authors now include additional data to back up the intriguing lack of a movement response towards norepinephrine and DHMA reported here.

      Additional weaknesses of the revised manuscript:

      - The addition of an ex vivo swine model is an exciting new inclusion in the updated manuscript. However, information regarding biological and technical replication here is currently unclear or missing.

    2. Reviewer #3 (Public Review):

      Summary:

      This manuscript characterizes a chemoattractant response to human serum by pathogenic bacteria, focusing on pathogenic stratins of Salmonella enterica Se. The researchers conduct the chemotaxis assays using a micropipette injection method that allows real-time tracking of bacterial population densities. They found that clinical isolates of several Se strains present a chemoattractant response to human serum. The specific chemoattractant within the serum is identified as L-serine, a highly characterized and ubiquitous chemoattractant, that is sensed by the Tsr receptor. They further show that chemoattraction to serum is impaired with a mutant strain devoid of Tsr. X-ray crystallography is then used to determine the structure of L-serine in the Se Tsr ligand binding domain, which differs slightly from a previously determine structure of a homologous domain. They went on to identify other pathogens that have a Tsr domain through a bioinformatics approach and show that these identified species also present a chemoattractant response to serum.

      Strengths and Weaknesses:

      This study is well executed and the experiments are clearly presented. These novel chemotaxis assays provide advantages in terms of temporal resolution and ability to detect responses from small concentrations. That said, it is perhaps not surprising these bacteria respond to serum as it is known to contain high levels of known chemoattractants, serine certainly, but also aspartate. In fact, the bacteria are shown to respond to aspartate and the tsr mutant is still chemotactic. The authors do not adequately support their decision to focus exclusively on the Tsr receptor. Tsr is one of the chemoreceptors responsible for observed attraction to serum, but perhaps, not the receptor. Furthermore, the verification of chemotaxis to serum is a useful finding, but the work does not establish the physiological relevance of the behavior or associate it with any type of disease progression. I would expect that a majority of chemotactic bacteria would be attracted to it under some conditions. Hence the impact of this finding on the chemotaxis or medical fields is uncertain.

      The authors also state that "Our inability to substantiate a structure-function relationship for NE/DHMA signaling indicates these neurotransmitters are not ligands of Tsr." Both norepinephrine (NE) and DHMA have been shown previously by other groups to be strong chemoattractants for E. coli (Ec), and that this behavior was mediated by Tsr (e.g. single residue changes in the Tsr binding pocket block the response). Given the 82% sequence identity between the Se and Ec Tsr, this finding is unexpected (and potentially quite interesting). To validate this contradictory result the authors should test E. coli chemotaxis to DHMA in their assay. It may be possible that Ec responds to NE and DHMA and Se doesn't. However, currently the data is not strong enough to rule out Tsr as a receptor to these ligands in all cases. At the very least the supporting data for Tsr being a receptor for NE/DHMA needs to be discussed.

      The authors also determine a crystal structure of the SeTsr periplasmic ligand binding domain bound to L-Ser and note that the orientation of the ligand is different than that modeled in a previously determined structure of lower resolution. I agree that the SeTsr ligand binding mode in the new structure is well-defined and unambiguous, but I think it is too strong to imply that the pose of the ligand in the previous structure is wrong. The two conformations are in fact quite similar to one another and the resolution of the older structure, is, in my view, insufficient to distinguish them. It is possible that there are real differences between the two structures. The domains do have different sequences and, moreover, the crystal forms, and cryo-cooling conditions are different in each case. It's become increasingly apparent that temperature, as manifested in differential cooling conditions here, can affect ligand binding modes. It's also notable that full-length MCPs show negative cooperativity in binding ligands, which is typically lost in the isolated periplasmic domains. Hence ligand binding is sensitive to the environment of a given domain. In short, the current data is not convincing enough to say that a previous "misconception" is being corrected.

    1. Reviewer #1 (Public Review):

      Summary:

      The presented study by Centore and colleagues investigates the inhibition of BAF chromatin remodeling complexes. The study is well-written, and includes comprehensive datasets, including compound screens, gene expression analysis, epigenetics, as well as animal studies. This is an important piece of work for the uveal melanoma research field, and sheds light on a new inhibitor class, as well as a mechanism that might be exploited to target this deadly cancer for which no good treatment options exist.

      Strengths:

      This is a comprehensive and well-written study.

      Weaknesses:

      There are minimal weaknesses.

    2. Reviewer #2 (Public Review):

      Summary:

      The authors generate an optimized small molecule inhibitor of SMARCA2/4 and test it in a panel of cell lines. All uveal melanoma (UM) cell lines in the panel are growth-inhibited by the inhibitor making the focus of the paper. This inhibition is correlated with the loss of promoter occupancy of key melanocyte transcription factors e.g. SOX10. SOX10 overexpression and a point mutation in SMARCA4 can rescue growth inhibition exerted by the SMARCA2/4 inhibitor. Treatment of a UM xenograft model results in growth inhibition and regression which correlates with reduced expression of SOX10 but not discernible toxicity in the mice. Collectively the data suggest a novel treatment of uveal melanoma.

      Strengths:

      There are many strengths of the study including the strong challenge of the on-target effect, the assays used, and the mechanistic data. The results are compelling as are the effects of the inhibitor. The in vivo data is dose-dependent and doses are low enough to be meaningful and associated with evidence of target engagement.

      Weaknesses:

      The authors introduce the field stating that SMARCA4 inhibitors are more effective in SMARCA2 deficient cancers and the converse. Since the desirable outcome of cancer therapy would be synthetic lethality it is not clear why a dual inhibitor is desirable. Wouldn't this be associated with more side effects? It is not known how the inhibitor developed here impacts normal cells, in particular T cells which are essential for any durable response to cancer therapies in patients. Another weakness is that the UM cell lines used do not molecularly resemble metastatic UM. These UM most frequently have mutations in the BAP1 tumor suppressor gene. It is not clear if the described SMARCA2/4 inhibitor is efficacious in BAP1 mutant UM cell lines in vitro or BAP1 mutant patient-derived xenografts in vivo.

    3. Reviewer #3 (Public Review):

      Summary:

      This manuscript reports the discovery of new compounds that selectively inhibit SMARCA4/SMARCA2 ATPase activity that work through a different mode as previously developed SMARCA4/SMARCA2 inhibitors. They also demonstrate the anti-tumor effects of the compounds on uveal melanoma cell proliferation and tumor growth. The findings indicate that the drugs exert their effects by altering chromatin accessibility at binding sites for lineage-specific transcription factors within gene enhancer regions. In uveal melanoma, altered expression of the transcription factor, SOX10, and SOX10 target gene underlies the anti-proliferative effects of the compounds. This study is significant because the discovery of new SMARCA4/SMARCA2 inhibitory compounds that can abrogate uveal melanoma tumorigenicity has therapeutic value. In addition, the findings provide evidence for the therapeutic use of these compounds in other transcription factor-dependent cancers.

      Strengths:

      The strengths of this manuscript include biochemical evidence that the new compounds are selective for SMARCA4/SMARCA2 over other ATPases and that the mode of action is distinct from a previously developed compound, BRM014, which binds the RecA lobe of SMARCA2. There is also strong evidence that FHT1015 suppresses uveal melanoma proliferation by inducing apoptosis. The in vivo suppression of tumor growth without toxicity validates the potential therapeutic utility of one of the new drugs. The conclusion that FHT1015 primarily inhibits SMARCA4 activity and thereby suppresses chromatin accessibility at lineage-specific enhancers is substantiated by ATAC-seq and ChIP-seq studies.

      Weaknesses:

      The weaknesses include a lack of more precise information on which SMARCA4/SMARCA2 residues the drugs bind. Although the I1173M/I1143M mutations are evidence that the critical residues for binding reside outside the RecA lobe, this site is conserved in CHD4, which is not affected by the compounds. Hence, this site may be necessary but not sufficient for drug binding or specifying selectivity. A more precise evaluation of the region specifying the effect of the new compounds would strengthen the evidence that they work through a novel mode and that they are selective. Another concern is that the mechanisms by which FHT1015 promotes apoptosis rather than simply cell cycle arrest are not clear. Does SOX10 or another lineage-specific transcription factor underlie the apoptotic effects of the compounds?

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, the authors investigate the potential therapeutic effects of the PEGylated PDZ peptide, derived from the ZO-1 protein, in suppressing LPS-induced systemic inflammation. The authors found that the pretreatment of PEGylated PDZ peptide led to a restoration of tissue injuries in the kidney, liver, and lung, and diminished alterations in biochemical plasma markers induced by LPS. This was accompanied by decreased production of pro-inflammatory cytokines in the plasma and lung BALF of the PDZ-administered mice.

      Strengths:

      - The data presented here is solid and the results provide the groundwork for developing novel anti-inflammatory therapeutic strategies.<br /> - The authors employ various cells and in vivo models to test the efficacy of the peptide.

      Weaknesses:<br /> The mechanism of action remains largely unknown.

    2. Reviewer #2 (Public Review):

      Summary:

      The authors investigated systemic inflammation induced by LPS in various tissues and also examined immune cells of the mice using tight junction protein-based PDZ peptide. They explored the mechanism of anti-systemic inflammatory action of PDZ peptides, which enhanced M1/M2 polarization and induced the proliferation of M2 macrophages. Additionally, they insisted on the physiological mechanism that inhibited the production of ROS in mitochondria, thereby preventing systemic inflammation.

      Strengths:<br /> In the absence of specific treatments for septic shock or sepsis, the study demonstrating that tight junction-based PDZ peptides inhibit systemic inflammation caused by LPS is highly commendable. Whereas previous research focused on antibiotics, this study proves that modifying parts of intracellular proteins can significantly suppress symptoms caused by septic shock. The authors expanded the study of localized inflammation caused by LPS or PM2.5 in the respiratory tract, to systemic inflammation, presenting promising results. They not only elucidated the physiological mechanism by identifying the transcriptome through RNA sequencing but also demonstrated that PDZ peptides inhibit the production of ROS in mitochondria and prevent mitochondrial fission. This research is highly regarded as an excellent study with potential as a treatment for septic shock or sepsis.

      Weaknesses<br /> (1) The authors focused intensively on acute inflammation for a short duration instead of chronic inflammation.<br /> (2) LPS was used to induce septic shock, but administrating actual microbes such as E.coli would yield more accurate results.<br /> (3) The authors used pegylated peptides, but future research should utilize the optimized peptides to derive the optimal peptide, and further, PK/PD studies are also necessary.

    1. Reviewer #2 (Public Review):

      Summary:

      This work proposes a synaptic plasticity rule that explains the generation of learned stochastic dynamics during spontaneous activity. The proposed plasticity rule assumes that excitatory synapses seek to minimize the difference between the internal predicted activity and stimulus-evoked activity, and inhibitory synapses try to maintain the E-I balance by matching the excitatory activity. By implementing this plasticity rule in a spiking recurrent neural network, the authors show that the state-transition statistics of spontaneous excitatory activity agree with that of the learned stimulus patterns, which are reflected in the learned excitatory synaptic weights. The authors further demonstrate that inhibitory connections contribute to well-defined state transitions matching the transition patterns evoked by the stimulus. Finally, they show that this mechanism can be expanded to more complex state-transition structures including songbird neural data.

      Strengths:

      This study makes an important contribution to computational neuroscience, by proposing a possible synaptic plasticity mechanism underlying spontaneous generations of learned stochastic state-switching dynamics that are experimentally observed in the visual cortex and hippocampus. This work is also very clearly presented and well-written, and the authors conducted comprehensive simulations testing multiple hypotheses. Overall, I believe this is a well-conducted study providing interesting and novel aspects of the capacity of recurrent spiking neural networks with local synaptic plasticity.

      Weaknesses:

      This study is very well-thought-out and theoretically valuable to the neuroscience community, and I think the main weaknesses are in regard to how much biological realism is taken into account. For example, the proposed model assumes that only synapses targeting excitatory neurons are plastic, and uses an equal number of excitatory and inhibitory neurons.

      The model also assumes Markovian state dynamics while biological systems can depend more on history. This limitation, however, is acknowledged in the Discussion.<br /> Finally, to simulate spontaneous activity, the authors use a constant input of 0.3 throughout the study. Different amplitudes of constant input may correspond to different internal states, so it will be more convincing if the authors test the model with varying amplitudes of constant inputs.

    2. Reviewer #1 (Public Review):

      In the presented manuscript, the authors investigate how neural networks can learn to replay presented sequences of activity. Their focus lies on the stochastic replay according to learned transition probabilities. They show that based on error-based excitatory and balance-based inhibitory plasticity networks can self-organize towards this goal. Finally, they demonstrate that these learning rules can recover experimental observations from song-bird song learning experiments.

      Overall, the study appears well-executed and coherent, and the presentation is very clear and helpful. However, it remains somewhat vague regarding the novelty. The authors could elaborate on the experimental and theoretical impact of the study, and also discuss how their results relate to those of Kappel et al, and others (e.g., Kappel et al (doi.org/10.1371/journal.pcbi.1003511)). Overall, the work could benefit if there was either (A) a formal analysis or derivation of the plasticity rules involved and a formal justification of the usefulness of the resulting (learned) neural dynamics; and/or (B) a clear connection of the employed plasticity rules to biological plasticity and clear testable experimental predictions. Thus, overall, this is a good work with some room for improvement.

    3. Reviewer #3 (Public Review):

      Summary:

      Asabuki and Clopath study stochastic sequence learning in recurrent networks of Poisson spiking neurons that obey Dale's law. Inspired by previous modeling studies, they introduce two distinct learning rules, to adapt excitatory-to-excitatory and inhibitory-to-excitatory synaptic connections. Through a series of computer experiments, the authors demonstrate that their networks can learn to generate stochastic sequential patterns, where states correspond to non-overlapping sets of neurons (cell assemblies) and the state-transition conditional probabilities are first-order Markov, i.e., the transition to a given next state only depends on the current state. Finally, the authors use their model to reproduce certain experimental songbird data involving highly-predictable and highly-uncertain transitions between song syllables.

      Strengths:

      This is an easy-to-follow, well-written paper, whose results are likely easy to reproduce. The experiments are clear and well-explained. The study of songbird experimental data is a good feature of this paper; finches are classical model animals for understanding sequence learning in the brain. I also liked the study of rapid task-switching, it's a good-to-know type of result that is not very common in sequence learning papers.

      Weaknesses:

      While the general subject of this paper is very interesting, I missed a clear main result. The paper focuses on a simple family of sequence learning problems that are well-understood, namely first-order Markov sequences and fully visible (no-hidden-neuron) networks, studied extensively in prior work, including with spiking neurons. Thus, because the main results can be roughly summarized as examples of success, it is not entirely clear what the main point of the authors is.

      Going into more detail, the first major weakness I see in this paper is the heuristic choice of learning rules. The paper studies Poisson spiking neurons (I return to this point below), for which learning rules can be derived from a statistical objective, typically maximum likelihood. For fully-visible networks, these rules take a simple form, similar in many ways to the E-to-E rule introduced by the authors. This more principled route provides quite a lot of additional understanding on what is to be expected from the learning process. For instance, should maximum likelihood learning succeed, it is not surprising that the statistics of the training sequence distribution are reproduced. Moreover, given that the networks are fully visible, I think that the maximum likelihood objective is a convex function of the weights, which then gives hope that the learning rule does succeed. And so on. This sort of learning rule has been studied in a series of papers by David Barber and colleagues [refs. 1, 2 below], who applied them to essentially the same problem of reproducing sequence statistics in recurrent fully-visible nets. It seems to me that one key difference is that the authors consider separate E and I populations, and find the need to introduce a balancing I-to-E learning rule.

      Because the rules here are heuristic, a number of questions come to mind. Why these rules and not others - especially, as the authors do not discuss in detail how they could be implemented through biophysical mechanisms? When does learning succeed or fail? What is the main point being conveyed, and what is the contribution on top of the work of e.g. Barber, Brea, et al. (2013), or Pfister et al. (2004)?

      The use of a Poisson spiking neuron model is the second major weakness of the study. A chief challenge in much of the cited work is to generate stochastic transitions from recurrent networks of deterministic neurons. The task the authors set out to do is much easier with stochastic neurons; it is reasonable that the network succeeds in reproducing Markovian sequences, given an appropriate learning rule. I believe that the main point comes from mapping abstract Markov states to assemblies of neurons. If I am right, I missed more analyses on this point, for instance on the impact that varying cell assembly size would have on the findings reported by the authors.

      Finally, it was not entirely clear to me what the main fundamental point in the HVC data section was. Can the findings be roughly explained as follows: if we map syllables to cell assemblies, for high-uncertainty syllable-to-syllable transitions, it becomes harder to predict future neural activity? In other words, is the main point that the HVC encodes syllables by cell assemblies?

      (1) Learning in Spiking Neural Assemblies, David Barber, 2002. URL: https://proceedings.neurips.cc/paper/2002/file/619205da514e83f869515c782a328d3c-Paper.pdf

      (2) Correlated sequence learning in a network of spiking neurons usingmaximum likelihood, David Barber, Felix Agakov, 2002. URL: http://web4.cs.ucl.ac.uk/staff/D.Barber/publications/barber-agakov-TR0149.pdf

    1. Reviewer #1 (Public Review):

      In this study, Alejandro Rosell et al. uncovers the immunoregulation functions of RAS-p110α pathway in macrophages, including the extravasation of monocytes from the bloodstream and subsequent lysosomal digestion. Disrupting RAS-p110α pathway by mouse genetic tools or by pharmacological intervention, hampers the inflammatory response, leading to delayed resolution and more severe acute inflammatory reactions. The authors proposed that activating p110α using small molecules could be a promising approach for treating chronic inflammation. This study provides insights into the roles and mechanisms of p110α on macrophage function and the inflammatory response, while some conclusions are still questionable because of several issues described below.

      (1) Fig. 1B showed that disruption of RAS-p110α causes the decrease in the activation of NF-κB, which is a crucial transcription factor that regulates the expression of proinflammatory genes. However, the authors observed that disruption of RAS-p110α interaction results in an exacerbated inflammatory state in vivo, in both localized paw inflammation and systemic inflammatory mediator levels. Also, the authors introduced that "this disruption leads to a change in macrophage polarization, favouring a more proinflammatory M1 state" in introduction according to reference 12. The conclusions drew from the signaling and the models seemed contradictory and puzzling. Besides, it is not clear why the protein level of p65 was decreased at 10' and 30'. Was it attributed to the degradation of p65 or experimental variation?

      (2) In Fig 3, the authors used bone-marrow derived macrophages (BMDMs) instead of isolated monocytes to evaluate the ability of monocyte transendothelial migration, which is not sufficiently convincing. In Fig. 3B, the authors evaluated the migration in Pik3caWT/- BMDMs, and Pik3caWT/WT BMDMs treated with BYL-719'. Given that the dose effect of gene expression, the best control is Pik3caWT/- BMDMs treated with BYL-719.

      (3) In Fig. 4E-4G, the authors observed that elevated levels of serine 3 phosphorylated Cofilin in Pik3caRBD/- BMDMs both in unstimulated and in proinflammatory conditions, and phosphorylation of Cofilin at Ser3 increase actin stabilization, it is not clear why disruption of RAS-p110α binding caused a decrease in the F-actin pool in unstimulated BMDMs?

    2. Reviewer #2 (Public Review):

      Summary:

      Cell intrinsic signaling pathways controlling the function of macrophages in inflammatory processes, including in response to infection, injury or in the resolution of inflammation are incompletely understood. In this study, Rosell et al. investigate the contribution of RAS-p110α signaling to macrophage activity. p110α is a ubiquitously expressed catalytic subunit of PI3K with previously described roles in multiple biological processes including in epithelial cell growth and survival, and carcinogenesis. While previous studies have already suggested a role for RAS-p110α signaling in macrophages function, the cell intrinsic impact of disrupting the interaction between RAS and p110α in this central myeloid cell subset is not known.

      Strengths:

      Exploiting a sound previously described genetically mouse model that allows tamoxifen-inducible disruption of the RAS-p110α pathway and using different readouts of macrophage activity in vitro and in vivo, the authors provide data consistent with their conclusion that alteration in RAS-p110α signaling impairs the function of macrophages in a cell intrinsic manner. The study is well designed, clearly written with overall high-quality figures.

      Weaknesses:

      My main concern is that for many of the readouts, the difference between wild-type and mutant macrophages in vitro or between wild-type and Pik3caRBD mice in vivo is rather modest, even if statistically significant (e.g. Figure 1A, 1C, 2A, 2F, 3B, 4B, 4C). In other cases, such as for the analysis of the H&E images (Figure 1D-E, S1E), the images are not quantified, and it is hard to appreciate what the phenotype in samples from Pik3caRBD mice is or whether this is consistently observed across different animals. Also, the authors claim there is a 'notable decrease' in Akt activation but 'no discernible chance' in ERK activation based on the western blot data presented in Figure 1A. I do not think the data shown supports this conclusion.

      To further substantiate the extent of macrophage function alteration upon disruption of RAS-p110α signaling, the manuscript would benefit from testing macrophage activity in vitro and in vivo across other key macrophage activities such as bacteria phagocytosis, cytokine/chemokine production in response to titrating amounts of different PAMPs, inflammasome function, etc. This would be generally important overall but also useful to determine whether the defects in monocyte motility or macrophage lysosomal function are selectively controlled downstream of RAS-p110α signaling.

      Furthermore, given the key role of other myeloid cells besides macrophages in inflammation and immunity it remains unclear whether the phenotype observed in vivo can be attributed to impaired macrophage function. Is the function of neutrophils, dendritic cells or other key innate immune cells not affected?

      Compelling proof of concept data that targeting RAS-p110α signalling constitutes indeed a putative approach for modulation of chronic inflammation is lacking. Addressing this further would increase the conceptual advance of the manuscript and provide extra support to the authors' suggestion that p110α inhibition or activation constitute promising approaches to manage inflammation.

      Finally, the analysis by FACS should also include information about the total number of cells, not just the percentage, which is affected by the relative change in other populations. On this point, Figure S2B shows a substantial, albeit not significant (with less number of mice analysed), increase in the percentage of CD3+ cells. Is there an increase in the absolute number of T cells or does this apparent relative increase reflect a reduction in myeloid cells?

    1. Reviewer #1 (Public Review):

      Summary:

      This paper reports a number of somewhat disparate findings on a set of colorectal tumour and infiltrating T-cells. The main finding is a combined machine-learning tool which combines two previous state-of-the-art tools, MHC prediction, and T-cell binding prediction to predict immunogenicity. This is then applied to a small set of neoantigens and there is a small-scale validation of the prediciton at the end.

      Strengths:

      The prediction of immunogenic neoepitopes is an important and unresolved question.

      Weaknesses:

      The paper contains a lot of extraneous material not relevant to the main claim. Conversely, it lacks important detail on the major claim.

      (1) The analysis of T cell repertoire in Figure 2 seems irrelevant to the rest of the paper. As far as I could ascertain, this data is not used further.

      (2) The key claim of the paper rests on the performance of the ML algorithm combining NETMHC and pmtNET. In turn, this depends on the selection of peptides for training. I am unclear about how the negative peptides were selected. Are they peptides from the same databases as immunogenic petpides but randomised for MHC ? It seems as though there will be a lot of overlap between the peptides used for testing the combined algorithm, and the peptides used for training MHCNet and pmtMHC. If this is so, and depending on the choice of negative peptides, it is surely expected that the tools perform better on immunogenic than on non-immunogenic peptides in Figure 3. I don't fully understand panel G, but there seems very little difference between the TCR ranking and the combined. Why does including the TCR ranking have such a deleterious effect on sensitivity?

      (3) The key validation of the model is Figure 5. In 4 patients, the authors report that 6 out 21 neo-antigen peptides give interferon responses > 2 fold above background. Using NETMHC alone (I presume the tool was used to rank peptides according to bding to the respecitve HLAs in each individual, but this is not clear), identified 2; using the combined tool identified 4. I don't think this is significant by any measure. I don't understand the score shown in panel E but I don't think it alters the underlying statistic.

      In conclusion, the paper demonstrates that combining MHCNET and pmtMHC results in a modest increase in the ability to discriminate 'immunogenic' from 'non-immunogenic' peptide; however, the strength of this claim is difficult to evaluate without more knowledge about the negative peptides. The experimental validation of this approach in the context of CRC is not convincing.

    2. Reviewer #2 (Public Review):

      Summary:

      This paper introduces a novel approach for improving personalized cancer immunotherapy by integrating TCR profiling with traditional pHLA binding predictions, addressing the need for more precise neoantigen CRC patients. By analyzing TCR repertoires from tumor-infiltrating lymphocytes and applying machine learning algorithms, the authors developed a predictive model that outperforms conventional methods in specificity and sensitivity. The validation of the model through ELISpot assays confirmed its potential in identifying more effective neoantigens, highlighting the significance of combining TCR and pHLA data for advancing personalized immunotherapy strategies.

      Strengths:

      (1) Comprehensive Patient Data Collection: The study meticulously collected and analyzed clinical data from 27 CRC patients, ensuring a robust foundation for research findings. The detailed documentation of patient demographics, cancer stages, and pathology information enhances the study's credibility and potential applicability to broader patient populations.

      (2) The use of machine learning classifiers (RF, LR, XGB) and the combination of pHLA and pHLA-TCR binding predictions significantly enhance the model's accuracy in identifying immunogenic neoantigens, as evidenced by the high AUC values and improved sensitivity, NPV, and PPV.

      (3) The use of experimental validation through ELISpot assays adds a practical dimension to the study, confirming the computational predictions with actual immune responses. The calculation of ranking coverage scores and the comparative analysis between the combined model and the conventional NetMHCpan method demonstrate the superior performance of the combined approach in accurately ranking immunogenic neoantigens.

      (4) The use of experimental validation through ELISpot assays adds a practical dimension to the study, confirming the computational predictions with actual immune responses.

      Weaknesses:

      (1) While multiple advanced tools and algorithms are used, the study could benefit from a more detailed explanation of the rationale behind algorithm choice and parameter settings, ensuring reproducibility and transparency.

      (2) While pHLA-TCR binding displayed higher specificity, its lower sensitivity compared to pHLA binding suggests a trade-off between the two measures. Optimizing the balance between sensitivity and specificity could be crucial for the practical application of these predictions in clinical settings.

      (3) The experimental validation was performed on a limited number of patients (four), which might affect the generalizability of the findings. Increasing the number of patients for validation could provide a more comprehensive assessment of the model's performance

    3. Reviewer #3 (Public Review):

      Summary:

      This study presents a new approach of combining two measurements (pHLA binding and pHLA-TCR binding) in order to refine predictions of which patient mutations are likely presented to and recognized by the immune system. Improving such predictions would play an important role in making personalized anti-cancer vaccinations more effective.

      Strengths:

      The study combines data from pre-existing tools pVACseq and pMTNet and applies them to a CRC patient population, which the authors show may improve the chance of identifying immunogenic, cancer-derived neoepitopes. Making the datasets collected publicly available would expand beyond the current datasets that typically describe caucasian patients.

      Weaknesses:

      It is unclear whether the pNetMHCpan and pMTNet tools used by the authors are entirely independent, as they appear to have been trained on overlapping datasets, which may explain their similar scores. The pHLA-TCR score seems to be driving the effects, but this not discussed in detail.

      Due to sample constraints, the authors were only able to do a limited amount of experimental validation to support their model; this raises questions as to how generalisable the presented results are. It would be desirable to use statistical thresholds to justify cutoffs in ELISPOT data.

      Some of the TCR repertoire metrics presented in Figure 2 are incorrectly described as independent variables and do not meaningfully contribute to the paper. The TCR repertoires may have benefitted from deeper sequencing coverage, as many TCRs appear to be supported only by a single read.

    1. Joint Public Review:

      Summary:

      In their paper Li et al. investigate the transcriptome of satellite cells obtained from different muscle types including hindlimb, diaphragm and extraocular muscles (EOM) from wild type and G93A transgenic mice (end stage ALS) in order to identify potential factors involved in the maintenance of the neuromuscular junction. The underlying hypothesis being that since EOMs are largely spared from this debilitating disease, they may secrete NMJ-protective factors. The results of their transcriptome analysis identified several axon guidance molecules including the chemokine Cxcl12, which are particularly enriched in EOM-derived satellite cells. Transduction of hindlimb-derived satellite cells with AAV encoding Cxcl12 reverted hindlimb-derived myotubes from the G93A mice into myotubes sharing phenotypic characteristics similar to those of EOM-derived satellite cells. Additionally, the authors were able to demonstrate that EOM-derived satellite cell myotube cultures are capable of enhancing axon extensions and innervation in co-culture experiments.

      Strengths:

      The strength of the paper is that the authors successfully isolated and purified different populations of satellite cells, compared their transcriptomes, identified specific factors release by EOM-derived satellite cells, overexpressed one of these factors (the chemokine Cxcl12) by AAV-mediated transduction of hindlimb-derived satellite cells. The transduced cells were then able to support axon guidance and NMJ integrity. They also show that administration of Na butyrate to mice decreased NMJ denervation and satellite cell-depletion of hind limbs. Furthermore, addition of Na Butyrate to hindlimb derived satellite cell myotube cultures increased Cxcl12 expression. These are impressive results providing important insights for the development of therapeutic targets to slow the loss on neuromuscular function characterizing ALS.

      Comments on latest version:

      The authors have sufficiently acknowledged and discussed the limitations of experiments involving NaBu treatment. The authors have also addressed the use of AAV-mediated delivery of Cxcl12.

    1. Reviewer #1 (Public Review):

      In this manuscript, Ngo et al. report a peculiar effect where a single base mismatch (CC) can enhance the mechanical stability of a nucleosome. In previous studies, the same group used a similar state-of-the-art fluorescence-force assay to study the unwrapping dynamics of 601-DNA from the nucleosome and observed that force-induced unwrapping happens more slowly for DNA that is more bendable because of changes in sequence or chemical modification. This manuscript appears to be a sequel to this line of projects, where the effect of CC is tested. The authors confirmed that CC is the most flexible mismatch using the FRET-based cyclization assay and found that unwrapping becomes slower when CC is introduced at three different positions in the 601 sequence. The CC mismatch only affects the local unwrapping dynamics of the outer turn of nucleosomal DNA.

    2. Reviewer #2 (Public Review):

      Mismatches occur as a result of DNA polymerase errors, chemical modification of nucleotides, during homologous recombination between near-identical partners, as well as during gene editing on chromosomal DNA. Under some circumstances, such mismatches may be incorporated into nucleosomes but their impact on nucleosome structure and stability is not known. The authors use the well-defined 601 nucleosome positioning sequence to assemble nucleosomes with histones on perfectly matched dsDNA as well as on ds DNA with defined mismatches at three nucleosomal positions. They use the R18, R39, and R56 positions situated in the middle of the outer turn, at the junction between the outer turn and inner turn, and in the middle of the inner turn, respectively. Most experiments are carried out with CC mismatches and Xenopus histones. Unwrapping of the outer DNA turn is monitored by single-molecule FRET in which the Cy3 donor is incorporated on the 68th nucleotide from the 5'-end of the top strand and the Cy5 acceptor is attached to the 7th nucleotide from the 5' end of the bottom strand. Force is applied to the nucleosomal DNA as FRET is monitored to assess nucleosome unwrapping. The results show that a CC mismatch enhances nucleosome mechanical stability. Interestingly, yeast and Xenopus histones show different behaviors in this assay. The authors use FRET to measure the cyclization of the dsDNA substrates to test the hypothesis that mismatches enhance the flexibility of the 601 dsDNA fragment and find that CC, CA, CT, TT, and AA mismatches decrease looping time, whereas GA, GG, and GT mismatches had little to no effect. These effects correlate with the results from DNA buckling assays reported by Euler's group (NAR 41, 2013) using the same mismatches as an orthogonal way to measure DNA kinking. The authors discuss that substitution rates are higher towards the middle of the nucleosome, suggesting that mismatches/DNA damage at this position are less accessible for repair, consistent with the nucleosome stability results.

    3. Reviewer #3 (Public Review):

      The mechanical properties of DNA wrapped in nucleosomes affect the stability of nucleosomes and may play a role in the regulation of DNA accessibility in eukaryotes. In this manuscript, Ngo and coworkers study how the stability of a nucleosome is affected by the introduction of a CC mismatched base pair, which has been reported to increase the flexibility of DNA. Previously, the group has used a sophisticated combination of single-molecule FRET and force spectroscopy with an optical trap to show that the more flexible half of a 601 DNA segment provides for more stable wrapping as compared to the other half. Here, it is confirmed with a single-molecule cyclization essay that the introduction of a CC mismatch increases the flexibility of a DNA fragment. Consistent with the previous interpretation, it also increased the unwrapping force for the half of the 601 segment in which the CC mismatch was introduced, as measured with single-molecule FRET and force spectroscopy. Enhanced stability was found up to 56 bp into the nucleosome. The intricate role of mechanical stability of nucleosomes was further investigated by comparing force-induced unwrapping profiles of yeast and Xenopus histones. Intriguingly, asymmetric unwrapping was more pronounced for yeast histones.

      Note from Reviewing Editor:

      The authors addressed the points in the reviews by making appropriate text additions and clarifications.

    1. Reviewer #1 (Public Review):

      Summary:

      In this manuscript, Ketaren, Mast, Fridy et al. assessed the ability of a previously generated llama nanobody library (Mast, Fridy et al. 2021) to bind and neutralize SARS-CoV-2 delta and omicron variants. The authors identified multiple nanobodies that retain neutralizing and/or binding capacity against delta, BA.1 and BA.4/5. Nanobody epitope mapping on spike proteins using structural modeling revealed possible mechanisms of immune evasion by viral variants as well as mechanisms of cross-variant neutralization by nanobodies. The authors additionally identified two nanobody pairs involving non-neutralizing nanobodies that exhibited synergy in neutralization against the delta variant. These results enabled the refinement of target epitopes of the nanobody repertoire and the discovery of several pan-variant nanobodies for further preclinical development.

      Strengths:

      Overall, this study is well executed and provides a valuable framework for assessing the impact of emerging SARS-CoV-2 variants on nanobodies using a combination of in vitro biochemical and cellular assays as well as computational approaches. There are interesting insights generated from the epitope mapping analyses, which offer possible explanations for how delta and omicron variants escape nanobody responses, as well as how some nanobodies exhibit cross-variant neutralization capacity. These analyses laid out a clear path forward for optimizing these promising next-gen therapeutics, particularly in the face of rapidly emerging SARS-CoV-2 variants. This work will be of interest to researchers in the fields of antibody/nanobody engineering, SARS-CoV-2 therapeutics, and host-virus interaction.

      Weaknesses:

      A main weakness of the study is that the efficacy statement is not thoroughly supported. While the authors comprehensively characterized the neutralizing ability of nanobodies in vitro, there is no animal data involving mice or hamsters to demonstrate the real protective efficacy in vivo. Yet, in the title and throughout the manuscript, the authors repeatedly used phrases like "retains efficacy" or "remains efficacious" to describe the nanobodies' neutralization or binding capacities. This claim is not well supported by the data and underestimates the impact of variants on the nanobodies, especially the omicron sublineages. For example, the authors showed that S1-RBD-15 had a ~100-fold reduction in neutralization titer against Omicron, with an IC50 at around 1 uM. This is much higher than the IC50 value of a typical anti-ancestral RBD nanobody reported in the previous study (Mast, Fridy et al. 2021). In fact, the authors themselves ascribe nanobodies with an IC50 above 1 uM as weak neutralizers. And there were many in the range of 0.1-1 uM. Furthermore, many nanobodies selected for affinity measurement against BA.4/5 had no detectable binding. Without providing in vivo protection data or including monoclonal antibodies that are known to be efficacious against variants in the in vitro assays as a benchmark, it is difficult to evaluate the efficacy just with the IC50 values.

      Comments post revision:

      The authors are to be commended for their comprehensive response to the referees' comments. In the revised manuscript, the authors made extensive changes throughout the texts and added new figures that greatly improved their clarity. While the manuscript is still limited in solely relying on in vitro data for efficacy assessment, it nicely demonstrates how the combination of experimental and computational techniques could lead to the discovery of broadly neutralizing nanobody candidates for further lead optimization.

    2. Reviewer #2 (Public Review):

      Summary:

      Interest in using nanobodies for therapeutic interventions in infectious diseases is growing due to their ability to bind hidden or cryptic epitopes that are inaccessible to conventional immunoglobulins. In the presented study, authors posed to characterize nanobodies derived the library produced earlier with Wuhan strain of SARS-CoV-2, map their epitopes on SARS-CoV-2 spike protein and demonstrate that some nanobodies retain binding and even neutralization against antigenically distant, newly emerging Variants of Concern (VOCs).

      Strengths:

      Authors demonstrate that some nanobodies despite being obtained against ancestral virus strain retain high affinity binding to antigenically distant SARS-CoV-2 strains despite majority of the repertoire loses binding. Despite being limited to only two nanobody combinations, demonstration of synergy in virus neutralization between nanobodies targeting different epitopes is compelling. The ability of nanobodies to bind emerging virus strains has been demonstrated and the possible effect of mutations within epitopes has been thoroughly discussed.

    1. Reviewer #1 (Public Review):

      Summary:

      The Roco proteins are a family of GTPases characterized by the conserved presence of an ROC-COR tandem domain. How GTP binding alters the structure and activity of Roco proteins remains unclear. In this study, Galicia C et al. took advantage of conformation-specific nanobodies to trap CtRoco, a bacterial Roco, in an active monomeric state and determined its high-resolution structure by cryo-EM. This study, in combination with the previous inactive dimeric CtRoco, revealed the molecular basis of CtRoco activation through GTP-binding and dimer-to-monomer transition.

      Strengths:

      The reviewer is impressed by the authors' deep understanding of the CtRoco protein. Capturing Roco proteins in a GTP-bound state is a major breakthrough in the mechanistic understanding of the activation mechanism of Roco proteins and shows similarity with the activation mechanism of LRRK2, a key molecule in Parkinson's disease. Furthermore, the methodology the authors used in this manuscript - using conformation-specific nanobodies to trap the active conformation, which is otherwise flexible and resistant to single-particle average - is highly valuable and inspiring.

    2. Reviewer #2 (Public Review):

      Summary

      The manuscript by Galicia et al describes the structure of the bacterial GTPyS-bound CtRoco protein in the presence of nanobodies. The major relevance of this study is in the fact that the CtRoco protein is a homolog of the human LRRK2 protein with mutations that are associated with Parkinson's disease. The structure and activation mechanisms of these proteins are very complex and not well understood. Especially lacking is a structure of the protein in the GTP-bound state. Previously the authors have shown that two conformational nanobodies can be used to bring/stabilize the protein in a monomer-GTPyS-bound state. In this manuscript, the authors use these nanobodies to obtain the GTPyS-bound structure and importantly discuss their results in the context of the mammalian LRRK2 activation mechanism and mutations leading to Parkinson's disease. The work is well performed and clearly described. In general, the conclusions on the structure are reasonable and well-discussed in the context of the LRRK2 activation mechanism.

      Strengths:

      The strong points are the innovative use of nanobodies to stabilize the otherwise flexible protein and the new GTPyS-bound structure that helps enormously in understanding the activation cycle of these proteins.

    1. Reviewer #1 (Public Review):

      Summary:

      The aim of the present work is to evaluate the role of BMP9 and BMP10 in liver by depleting Bmp9 and Bmp10 from the main liver cell types (endothelial cells (EC), hepatic stellate cells (HSC), Kupffer cells (KC) and hepatocytes (H)) using cell-specific cre recombinases. They show that HSCs are the main source of BMP9 and BMP10 in the liver. Using transgenic ALK1 reporter mice, they show that ALK1, the high affinity type 1 receptor for BMP9 and BMP10, is expressed on KC and EC. They have also performed bulk RNAseq analyses on whole liver, and cell-sorted EC and KC, and showed that loss of Bmp9 and Bmp10 decreased KC signature and that KC are replaced by monocyte-derived macrophages. EC derived from these Bmp9fl/flBmp10fl/flLratCre mice also lost their identity and transdifferentiated into continuous ECs. Liver iron metabolism and metabolic zonation were also affected in these mice. In conclusion, this work supports that BMP9 and BMP10 produced by HSC play a central role in mediating liver cell-cell crosstalk and liver homeostasis.

      Strengths:

      This work further supports the role of BMP9 and BMP10 in liver homeostasis. Using a specific HSC-Cre recombinase, the authors show for the first time that it is the BMP9 and BMP10 produced by HSC that play a central role in mediating liver cell-cell crosstalk to maintain a healthy liver. Although the overall message of the key role of BMP9 in liver homeostasis has been described by several groups, the role of hepatic BMP10 has not been studied before. Thus, one of the novelties of this work is to have used liver cell specific Cre recombinase to delete hepatic Bmp9 and Bmp10. The second novelty is the demonstration of the role of BMP9 and BMP10 in KC Differentiation/homeostasis which has already been slightly addressed by this group by knocking out ALK1, the high affinity receptor of BMP9 and BMP10 (Zhao et al. JCI, 2022).

      Weaknesses:

      This work remains rather descriptive and the molecular mechanisms are barely touched upon and could have been more explored.<br /> Some references should be added; In particular, a work that has already demonstrated, using a different approach (in situ hybridization RNAscope), that in the liver BMP9 and BMP10 are expressed by HSC (Tillet et al., J Biol Chem 2018). Another publication (Bouvard et al., Cardiovasc Res, 2021) has previously showed that deletion of Bmp9 and Bmp10 leads to liver fibrosis and could have thus been cited. There is also a reference that is not correctly cited. Ref 26 (Herrera et al., 2014) does not say that "BMP10 is mostly expressed in the heart, followed by the liver" or that "BMP9 and BMP10 also bind to ALK2" as cited in the manuscript.<br /> The gating strategies for cell sorting which is used for bulk RNAseq and FACS analyses should be better described in order to better follow the manuscript. This point is particularly important for KC gating as the authors show that Tim4 is very strongly decreased in Bmp9fl/flBmp10fl/flLratCre (Fig 2c), yet, it seems that this marker is used for gating macrophages (Suppl fig4). Same question with F4/80 which is strongly decreased in Bmp9fl/flBmp10fl/flLratCre (Fig 2d) and also used for gating. It is important to show the gating strategy for both Control and Bmp9fl/flBmp10fl/flLratCre mice.<br /> The authors should explain how they selected the genes shown on each heatmaps and add references that can justify the choice of the genes.<br /> Quantifications of Immunostaining and FACS data should be added as well as statistical analyses.

    2. Reviewer #2 (Public Review):

      Summary:

      The authors characterized the contribution of BMP9/BMp10 expression/secretion from all different hepatic cell types and analysed their impact on the other cell types. They are able to show that HSC derived BMP9/BMP10 controls Kupffer cell and EC differentiation and functions.

      Strengths:

      This is the first study to my knowledge to comprehensively analyze the contribution of BMP9/BMP10 expression in such systematic fashion in vivo. This study therefore is a significant contribution to the field and further supports previous studies that have already implied BMP9 and BMP10 in Kupffer cell and EC functions but did not unravel the intercellular cross talk in such detailed fashion.

      Weaknesses:

      Several findings such as the impact of BMP9/10 on Kupffer cells and EC were already known. So these findings are not innovative, however I still believe that the elucidation of the cellular crosstalk makes this publication highly interesting to a broad scientific community.

      Overall the authors achieved their aims and the results are well supporting the conclusions and discussion.

    1. Reviewer #1 (Public Review):

      This study holds significant importance as it assessed antibody levels arising from both COVID-19 vaccination and natural infection in a representative population-based sample. The analysis was conducted with thoughtfulness and rigor. The sampling methodology ensured the representation of the broader Canadian population, including minorities and indigenous communities. Findings suggest, that despite a substantial number of individuals having been previously infected, especially following the first omicron wave, repeat booster vaccination is essential to ensure that individuals develop an optimal antibody response against new exposures to infection, given the waning of antibodies over time. The study findings carry global significance as it informs decisions about the relevance of booster vaccination for reducing infection incidence amid the ongoing challenge of vaccine hesitancy and the continual emergence of new variants.

      Among the weaknesses of the study, from my perspective, is the lack of explicit clarification that one objective of achieving repeat booster vaccination is to impart a robust level of protection against acquiring infections. Previous studies have demonstrated that the effectiveness of even only primary-series vaccination against COVID-19 severe disease was high, with slow waning over time. However, even when effectiveness against severity is high, infections may still present a risk for progression to severe COVID-19 among older individuals and those with comorbidities. Another limitation is that the study did not investigate whether there were variations in spike levels based on the last vaccine type administered. Furthermore, it is important to comment on the generalizability of the findings considering that individuals who participated in the research may have been different from those who did not participate and therefore residual confounding cannot be eliminated.

    2. Reviewer #2 (Public Review):

      Strengths<br /> (1) The study benefits from a Large sample size, encompassing serial assessments of 4000-9000 adults over an extended period. This large cohort enhances the reliability and generalizability of the findings.<br /> (2) The study employs a rigorous methodology, including serial assessments, self-collected dried blood spots, and highly sensitive antibody assays. The use of multiple measures ensures a robust evaluation of hybrid immunity and SARS-CoV-2 incidence within the Canadian population.<br /> (3) The manuscript provides detailed analyses of antibody levels, vaccination history, infection rates, and demographic factors. The inclusion of stratified analyses by age, sex, and ethnicity enhances the understanding of population-level immunity dynamics.<br /> (4) The study's findings contribute valuable insights into the dynamics of hybrid immunity and SARS-CoV-2 incidence, particularly during the emergence of the Omicron variant. The observed decline in COVID-19 death rates amidst rising infection rates underscores the potential protective role of hybrid immunity against severe outcomes.

      Weaknesses<br /> (1) Sampling Limitations: While the study claims to be representative of the Canadian population, there are potential limitations in sampling methods, particularly reliance on an online polling platform. This approach may introduce selection bias and limit the generalizability of findings to certain demographic groups.<br /> (2) Assay Limitations: The study acknowledges limitations associated with antibody assays and the potential for assay saturation, the reliance on self-reported vaccination history and infection status may introduce recall bias and affect the accuracy of estimates.<br /> (3) Data Interpretation: While the study presents compelling data on hybrid immunity and SARS-CoV-2 incidence, some interpretations may be speculative. The assertion of a causal relationship between hybrid immunity and reduced COVID-19 mortality warrants cautious interpretation, given the complexity of factors influencing disease outcomes.<br /> (4) Lack of inclusion and exclusion criteria: The manuscript does not have specific inclusion and exclusion criteria for participants and the methods used for data analysis.<br /> (5) The protocol does not include disaggregated data, this is only available on page 25 as an annex.

    1. Reviewer #1 (Public Review):

      Authors investigated the role of OBOX4 in the zygotic genome activation (ZGA) in mice. Obox4 genes form an array of duplicated genes they were identified as a candidate ZGA factor based on expression patterns during early development. The role of OBOX4 was subsequently studied in embryonic stem cells and early embryos. It was found that transcriptional activation mediated by OBOX4 has similar features as that of DUX, which was previously identified as a zygotic transcription factor involved in ZGA and a major activator of the zygotic expression program. It was, however, unexpected that Dux knock-out did not impair embryonic development. The work by Guo et al. provides several lines of evidence that OBOX4-mediated activation of gene expression considerably overlaps with that of DUX and this redundancy might explain the loss of early developmental phenotype in Dux mutants. Consistent with this model, double mutants of Obox4 and Dux show impaired development. Given the difficulties with investigating details of the genetic model in double mutants at the preimplantation embryo stage, authors not only crossed genetic mutants, but also used (1) nuclear transfer of mutated nuclei of ESCs, which could be characterized on their own in separate experiments, and (2) antisense oligonucleotides (ASO) microinjection, which included a rescue control demonstrating that reintroducing OBOX4 is sufficient to rescue the phenotype caused by blocking both, Dux and Obox4.

      This work is important for the field because it reveals functional redundancy and plasticity of the zygotic genome activation in mammals, where the mouse model stands as a remarkable example of genome activation, which massively integrated long terminal repeat (LTR)-derived enhancers from retrotransposons and now two of the key activating zygotic factors appear to be encoded by tandemly duplicated clusters of different phylogenetic age. Identification of OBOX4 as a second factor partially redundant with DUX now allows us to decipher what constitutes the essential part of the ZGA program.

    2. Reviewer #2 (Public Review):

      In this study, Guo et al., screened a few homeobox transcription factors and identified that Obox4 can induce the 2-cell like state in mouse embryonic stem cells (mESCs) (Fig. 1 and 2). The authors also compared in detail how Obox4 vs. Dux in activating 2C repeats and genes in mESCs (Fig. 3). Compared to Dux, Obox4 activates fewer 2C genes (Fig. 2). In addition, although both Obox4 and Dux bind to MERVL elements, Obox4 additionally binds to ERVK (Fig. 3). The authors then used three different approaches (i.e., SCNT-mediated KO, ASO-mediated KD, and genetic KO) to study how Obox4 and Dux regulates zygotic genome activation in embryos. Although there are some inconsistencies among different approaches, the authors were able to show that loss of both Obox4 and Dux causes more severe consequences than loss of single protein in embryonic development and zygotic genome activation (Fig. 4 and 5).

      Overall, this is a comprehensive study that addresses an important question that puzzles the community. However, some comparisons to the recent work by Ji et al (PMID: 37459895) are highly recommended. Ji et al knocked out the entire Obox cluster (including Obox4) in mice and found that Obox cluster KO causes 2-4 cell arrest without affecting Dux. That said, Obox proteins seem more critical than Dux in regulating ZGA, and Obox cluster KO cannot be compensated by Dux. Ji et al., also reported that maternal (Obox1, 2, 5, 7) and zygotic (Obox3, 4) Obox proteins redundantly regulate embryogenesis because loss of either is compatible to development. Consistent with Ji's work, Obox4 KO embryos generated in this study can develop to adulthood and are fertile. Since these two studies are highly relevant, some comparisons of Obox4 KO and Obox4/Dux DKO with the previous Obox cluster KO will greatly benefit the community.

    1. Reviewer #2 (Public Review):

      Summary:

      In the manuscript "Representational drift as a result of implicit regularization" the authors study the phenomenon of representational drift (RD) in the context of an artificial network which is trained in a predictive coding framework. When trained on a task for spatial navigation on a linear track, they found that a stochastic gradient descent algorithm led to a fast initial convergence to spatially tuned units, but then to a second very slow, yet directed drift which sparsified the representation while increasing the spatial information. They finally show that this separation of time-scales is a robust phenomenon and occurs for a number of distinct learning rules.

      This is a very clearly written and insightful paper, and I think people in the community will benefit from understanding how RD can emerge in such artificial networks. The mechanism underlying RD in these models is clearly laid out and the explanation given is convincing.

      It still remains unclear how this mechanism may account for the learning of multiple environments, although this is perhaps a topic for future study. The non-stationarity of the drift in this framework would seem, at first blush, to contrast with what one sees experimentally, but the authors provide compelling evidence that there are continuous changes in network properties during learning and that stationarity may be the hallmark of overfamiliarized environments. Future experimental work may further shed light on differences in RD between novel and familiar environments.

    2. Reviewer #1 (Public Review):

      The authors start from the premise that neural circuits exhibit "representational drift" -- i.e., slow and spontaneous changes in neural tuning despite constant network performance. While the extent to which biological systems exhibit drift is an active area of study and debate (as the authors acknowledge), there is enough interest in this topic to justify the development of theoretical models of drift.

      The contribution of this paper is to claim that drift can reflect a mixture of "directed random motion" as well as "steady state null drift." Thus far, most work within the computational neuroscience literature has focused on the latter. That is, drift is often viewed to be a harmless byproduct of continual learning under noise. In this view, drift does not affect the performance of the circuit nor does it change the nature of the network's solution or representation of the environment. The authors aim to challenge the latter viewpoint by showing that the statistics of neural representations can change (e.g. increase in sparsity) during early stages of drift. Further, they interpret this directed form of drift as "implicit regularization" on the network.

      The evidence presented in favor of these claims is concise, but on balance I find their evidence persuasive, at least in artificial network models. This paper includes a brief analysis of four independent experiments in Figure 3, which corroborates the main claims of the paper. Future work should dig deeper into the experimental data to provide a finer grained characterization. For example, in addition to quantifying the overall number of active units, it would be interesting to track changes in the signal-to-noise ratio of each place field, the widths of the place fields, et cetera.

      To establish the possibility of implicit regularization in artificial networks, the authors cite convincing work from the machine learning community (Blanc et al. 2020, Li et al., 2021). Here the authors make an important contribution by translating these findings into more biologically plausible models and showing that their core assumptions remain plausible. The authors also develop helpful intuition in Figure 5 by showing a minimal model that captures the essence of their result.

    3. Reviewer #3 (Public Review):

      Summary:

      Single unit neural activity tuned to environmental or behavioral variables gradually changes over time. This phenomenon, called representational drift, occurs even when all external variables remain constant, and challenges the idea that stable neural activity supports the performance of well-learned behaviors. While a number of studies have described representational drift across multiple brain regions, our understanding of the underlying mechanism driving drift is limited. Ratzon et al. propose that implicit regularization - which occurs when machine learning networks continue to reconfigure after reaching an optimal solution - could provide insights into why and how drift occurs in neurons. To test this theory, Ratzon et al. trained a recurrent neural network (RNN) trained to perform the oft-utilized linear track behavioral paradigm and compare the changes in hidden layer units to those observed in hippocampal place cells recorded in awake, behaving animals.

      Ratzon et al. clearly demonstrate that hidden layer units in their model undergo consistent changes even after the task is well-learned, mirroring representational drift observed in real hippocampal neurons. They show that the drift occurs across three separate measures: the active proportion of units (referred to as sparsification), spatial information of units, and correlation of spatial activity. They continue to address the conditions and parameters under which drift occurs in their model to assess the generalizability of their findings to non-spatial tasks. Last, they investigate the mechanism through which sparsification occurs, showing that flatness of the manifold near the solution can influence how the network reconfigures. The authors suggest that their findings indicate a three stage learning process: 1) fast initial learning followed by 2) directed motion along a manifold which transitions to 3) undirected motion along a manifold.

      Overall, the authors' results support the main conclusion that implicit regularization in machine learning networks mirrors representational drift observed in hippocampal place cells. Their findings promise to open new fields of inquiry into the connection between machine learning and representational drift in other, non-spatial learning paradigms, and to generate testable predictions for neural data.

      Strengths:

      (1) Ratzon et al. make an insightful connection between well-known phenomena in two separate fields: implicit regularization in machine learning and representational drift in the brain. They demonstrate that changes in a recurrent neural network mirror those observed in the brain, which opens a number of interesting questions for future investigation.

      (2) The authors do an admirable job of writing to a large audience and make efforts to provide examples to make machine learning ideas accessible to a neuroscience audience and vice versa. This is no small feat and aids in broadening the impact of their work.

      (3) This paper promises to generate testable hypotheses to examine in real neural data, e.g., that drift rate should plateau over long timescales (now testable with the ability to track single-unit neural activity across long time scales with calcium imaging and flexible silicon probes). Additionally, it provides another set of tools for the neuroscience community at large to use when analyzing the increasingly high-dimensional data sets collected today.

      Weaknesses:

      The revised manuscript addresses all the weaknesses outlined in my initial review. However, there is one remaining (minor) weakness regarding how "sparseness" is used and defined.

      Sparseness can mean different things to different fields. For example, for engram studies, sparseness could be measured at the population level by the proportion of active cells, whereas for a physiology study, sparseness might be measured at the neuron level by the change in peak firing rate of each cell as an animal enters that cell's place field. In this manuscript, the idea of "sparseness" is introduced indirectly in the last paragraph of the introduction as "...changes in activity statistics (sparseness)...", but it is unclear from the preceding text if the referenced "activity statistics" used to define sparseness are the "fraction of active units," or their "tuning specificity," or both. While sparseness is clearly defined in the Methods section for the RNN, there is no mention of how it is defined for neural data, and spatial information is not mentioned at all. For clarity, I suggest explicitly defining sparseness for both the RNN and real neural data early in the main text, e.g. "Here, we measure sparseness in neural data by A and B, and by the analogous metric(s) of X and Y in our RNN..." This is a small but important nuance that will enhance the ease of reading for a broad neuroscience audience.

    1. Reviewer #2 (Public Review):

      Summary:

      This significant research explored how the PHOX2B transcription factor functions within neurons located in the retrotrapezoid nucleus (RTN), a crucial brainstem chemosensory area, to sustain appropriate CO2 chemoreflex reactions related to breathing in adult rats when observed in a living state. By applying a viral shRNA technique to selectively suppress PHOX2B in RTN neurons, the authors present compelling evidence of deteriorating ventilatory reactions to increased CO2 levels. This impairment progresses over a four-week period in vivo, hinting at disruptions in RTN neuron transcriptional processes and a consequent dulling of CO2-induced breathing responses. The data on RTN neuronal mRNA expression indicates that the weakened hypercapnic ventilatory response may stem from reduced levels of crucial proton sensors within the RTN. This research holds relevance for neuroscientists focused on the neurobiology of respiration and the neurodevelopmental regulation of motor functions.

      Strengths:

      The authors employed a shRNA viral strategy to systematically reduce PHOX2B protein levels, targeting RTN neurons specifically, to assess the importance of PHOX2B for the survival and chemosensory capabilities of adult RTN neurons in a living organism. The findings of this research underscore that beyond its developmental role, PHOX2B remains essential for sustaining accurate CO2 chemoreflex reactions in the adult brain. Furthermore, its diminished presence in Congenital Central Hypoventilation Syndrome (CCHS) could be a factor in the respiratory deficiencies observed in the condition. This study highlights the critical ongoing function of PHOX2B in adult physiology and its potential impact on respiratory health, offering valuable insights for the scientific and medical communities involved in treating and understanding respiratory disorders.

      Weaknesses:

      N/A

    2. Reviewer #1 (Public Review):

      Summary:

      This important study investigated the role of the PHOX2B transcription factor in neurons in the key brainstem chemosensory structure, the retrotrapezoid nucleus (RTN), for maintaining proper CO2 chemoreflex responses of breathing in the adult rat in vivo. PHOX2B has an important transcriptional role in neuronal survival and/or function, and mutations of PHOX2B severely impair the development and function of the autonomic nervous system and RTN, resulting in the developmental genetic disease congenital central hypoventilation syndrome (CCHS) in neonates, where the RTN may not form and is functionally impaired. The function of the wild-type PHOX2B protein in adult RTN neurons that continue to express PHOX2B is unknown. By utilizing a viral PHOX2B-shRNA approach for the knockdown of PHOX2B specifically in RTN neurons, the authors' solid results show impaired ventilatory responses to elevated inspired CO2, measured by whole-body plethysmography in freely behaving adult rats, that develop progressively over a four-week period in vivo, indicating effects on RTN neuron transcriptional activity and associated blunting of the CO2 ventilatory response. The RTN neuronal mRNA expression data presented suggests the impaired hypercapnic ventilatory response is possibly due to the decreased expression of key proton sensors in the RTN. This study will be of interest to neuroscientists studying respiratory neurobiology as well as the neurodevelopmental control of motor behavior.

      Strengths:

      (1) The authors used a shRNA viral approach to progressively knock down the PHOX2B protein, specifically in RTN neurons, to determine whether PHOX2B is necessary for the survival and/or chemosensory function of adult RTN neurons in vivo.

      (2) To determine the extent of PHOX2B knockdown in RTN neurons, the authors combined RNAScope® and immunohistochemistry assays to quantify the subpopulation of RTN neurons expressing PHOX2B and Neuromedin B (Nmb), which has been proposed to be key chemosensory neurons in the RTN.

      (3) The authors demonstrate that knockdown efficiency is time-dependent, with a progressive decrease in the number of Nmb-expressing RTN neurons that co-express PHOX2B over a four-week period.

      (4) Their results convincingly show hypoventilation, particularly in 7.2% CO2 only, for PHOX2B-shRNA RTN-injected rats after four weeks compared to naïve and non-PHOX2B-shRNA targeted (NT-shRNA) RTN-injected rats, suggesting a specific impairment of chemosensitive properties in RTN neurons with PHOX2B knockdown.

      (5) Analysis of the association between PHOX2B knockdown in RTN neurons and the<br /> attenuation of the hypercapnic ventilatory response (HCVR), by evaluating the correlation between the number of Nmb+/PHOX2B+ or Nmb+/PHOX2B- cells in the RTN and the resulting HCVR, showed a significant correlation between HCVR and number of Nmb+/PHOX2B+ and Nmb+/PHOX2B- cells, suggesting that the number of PHOX2B-expressing cells in the RTN is a predictor of the chemoreflex response and the reduction of PHOX2B protein impairs the CO2-chemoreflex.

      (6) The data presented indicate that PHOX2B knockdown reduces the HCVR and the expression of Gpr4 and Task2 mRNAs. This suggests that PHOX2B knockdown affects RTN neurons' transcriptional activity and decreases the CO2 response, possibly by reducing the expression of key proton sensors in the RTN.

      (7) This study's results show that independent of its role during development, PHOX2B is still required to maintain proper CO2 chemoreflex responses in the adult brain, and its reduction in CCHS may contribute to the respiratory impairment in this disorder.

      Weaknesses:

      (1) The authors found a significant decrease in the total number of Nmb+ RTN neurons (i.e., Nmb+/PHOX2B+ plus Nmb+/ PHOX2B-) in NT-shRNA rats at two weeks post viral injection, and also at the four-week period where the impairment of the chemosensory function of the RTN became significant, suggesting some inherent cell death possibly due to off-target toxic effects associated with shRNA procedures.

      (2) The tissue sampling procedures for quantifying numbers of cells expressing proteins/mRNAs throughout the extended RTN region bilaterally have not been completely validated to accurately represent the full expression patterns in the RTN under the experimental conditions.

      (3) The inferences about RTN neuronal expression of NMB, GPR4, or TASK2 are based on changes in mRNA levels, so it remains speculation that the observed reduction in Gpr4 and Task2 mRNA translates to a reduction in the protein levels and associated reduction of RTN neuronal chemosensitive properties.

    3. Reviewer #3 (Public Review):

      A brain region called the retrotrapezoid nucleus (RTN) regulates breathing in response to changes in CO2/H+, a process termed central chemoreception. A transcription factor called PHOX2B is important for RTN development and mutations in the PHOX2B gene result in a severe type of sleep apnea called Congenital Central Hypoventilation Syndrome. PHOX2B is also expressed throughout life, but its postmitotic functions remain unknown. This study shows that knockdown of PHOX2B in the RTN region in adult rats decreased expression of Task2 and Gpr4 in Nmb-expressing RTN chemoreceptors and this corresponded with a diminished ventilatory response to CO2 but did not impact baseline breathing or the hypoxic ventilatory response. These results provide novel insight regarding postmitotic functions of PHOX2B in RTN neurons.

      I have two main concerns and several points of clarification.

      Main issues:<br /> (1) The experimental approach was not targeted to Nmb+ neurons and since other cells in the area also express Phox2b, conclusions should be tempered to focus on Phox2b expressing parafacial neurons NOT specifically RTN neurons

      (2) It's not clear whether PHOX2B is important for transcription of pH sensing machinery, cell health or both. If knockdown of PHOX2B knockdown results in loss of RTN neurons this is also expected to decrease Task2 and Gpr4 levels, albeit by a transcription-independent mechanism.

      Other points:

      (3) All individual data points should be visible in floating bar graphs in Figs 1 and 4. For example, I don't see any dots for naïve animals in any of the panels in Fig. 1.

      (4) the C1 and facial partly overlap with the RTN at this level of the medulla and these cells should appear as Phox2b+/Nmb- cells so it is not clear to me why these cells are not evident in the control tissue in figs 2B and 3B. Also, some of the bregma levels shown in Fig. 5A overlap with Figs 2-3 so again it's not clear to me how this non-cell type specific viral approach was targeted to Nmb cells but not near by TH+ cells. Please clarify.

      (5) How do you get a loss of Nmb+ neurons (Figs 2-3) with no change in Nmb fluorescence (Fig. 5B)? In the absence of representative images these results are not compelling and should be substantiated by more readily quantifiable approaches like qPCR.

    1. Reviewer #2 (Public Review):

      Summary:

      In this study, Mu Qiao employs a bilinear modelling approach, commonly utilised in the recommendation systems, to explore the intricate neural connections between different pre- and post-synaptic neuronal types. This approach involves projecting single-cell Transcriptomic datasets of pre- and post-synaptic neuronal types into a latent space through transformation matrices. Subsequently, the cross-correlation between these projected latent spaces is employed to estimate neuronal connectivity. To facilitate the model training, Connectomic data is used to estimate the ground-truth connectivity map. This work introduces a promising model for the exploration of neuronal connectivity and its associated molecular determinants. In the revised version of the manuscript, the author has applied and validated the model in both C. elegans gap junction connectivity and the retina neuron connectivity conditions.

      Strengths:

      This study introduces a succinct yet promising computational model for investigating connections between neuronal types. The model, while straightforward, effectively integrates single-cell transcriptomic and connectomic data to produce a reasonably accurate connectivity map, particularly within the context of retinal connectivity. Furthermore, it successfully recapitulates connectivity patterns and helps uncover the genetic factors that underlie these connections.

      Weaknesses:

      (1) When compared with the previous method - SCM, the new model shows a similar performance level. This may be due to the limitation of the dataset itself, as it only has the innexin expression data. Is it possible to apply the SCM model to the more complete retina dataset and compare the performance with the proposed bilinear modelling approach?

      Minor Weakness:

      (1) The study lacks experimental validation of the model's prediction results.

    2. Reviewer #1 (Public Review):

      Summary:

      In this study, the author aimed to develop a method for estimating neuronal-type connectivity from transcriptomic gene expression data. They sought to develop an interpretable model that could be used to characterize the underlying genetic mechanisms of circuit assembly and connectivity in various neuronal systems.

      Strengths:

      Many of the proposed suggestions were addressed by the author from the initial review. In general the claims made by the author are more strongly supported by the data and better situated in the literature. A major improvement includes the application of the model to the C. elegans gap junction neuronal system. Despite several key differences in the dataset as compared to the mouse retina data, the proposed model performs comparably to the SCM model currently considered state of the art in the literature (the author should remain cautious about claiming better performance given extremely marginal differences). In section 7.2, the author clearly outlines additional advantages of the proposed model including superior time and space complexity. The overall model performance remains modest, but it learns the same rules as the SCM model as well as other candidate patterns.

      As in the initial submission, the bilinear model recapitulates key connectivity motifs for the mouse dataset. The algorithm is shown to converge across several runs affirming its stability/replicability. The model is also extended to predict connectivity on unknown RGC-BC cell type pairs. Without ground truth, the author posits how it should perform based on known functional properties of the RGC type. The hypotheses are confirmed for 8/10 neuronal types with unknown connectivity. The author more clearly describes how this model can be used experimentally for hypothesis testing and presents a more comprehensive future roadmap regarding validation, avenues for improving the model, and incorporation of growing datasets.

      Weaknesses:

      While the C Elegans dataset is useful because it enables benchmarking to existing models, the dataset is quite different. The gene expression dimensionality is 18 genes as opposed to over 3000 genes in the mouse dataset. It is a strength that the model still works as intended, but a weakness that the bilinear model could not be tested on a similar mouse dataset. This distinction matters because it remains an open question if the PCA methodology would hold up in a dataset with varied distributions of gene expression. Variations of the PCA methodology could be evaluated further with the present dataset to make the generalizability of the model more convincing.

      The Gene Ontology analysis requires more methodological explanation. The author claims, "(the linear nature of the model) enables the direct interpretation of gene expressions by examining their associated weights in the model. These weights signify the importance of each gene in determining the connectivity motifs between the BC and RGC types." If I am correctly understanding the methods, the model weights in each dimension are indexing the importance of a gene expression feature as opposed to the importance of a single gene alone, "the gene expression of the BCs in X and the RGCs in Y were featurized by their respective PCs, resulting in matrices of dimensions 22453 × 11323 and 3779 × 3142, respectively." It would be helpful to explain how gene weights are extracted from a gene expression feature once highlighted.

      There could be a more rigorous analysis of the predictive capacity of the model even with the current data. The model recapitulates connectivity patterns from the full dataset and a prediction is demonstrated for unknown data. The model is thus championed as a useful tool for predicting how genetic modifications will influence connectivity, but this is not empirically evaluated.

      Appraisal of whether the author achieved their aims, and whether results support their conclusions:

      In line with the aims of the paper, the author proposed an interpretable bilinear model to learn a shared latent feature space derived from gene expression profiles to predict synaptic connectivity between various neuron types. The model was shown to generalize to two distinct neuronal systems with varying levels of genomic and cellular resolution. While the performance remains modest, the model performs comparably to the existing state of the art despite improved computational complexity.

      Discussion of likely impact of the work on the field, and utility of methods and data to the community:

      The author has elaborated substantially on the impact of this work, particularly how it could be leveraged in experimental settings. The clear methodology could be implemented by other researchers to test the model on new datasets and for benchmarking novel methods.

    1. Reviewer #2 (Public Review):

      Summary:

      Replacing linezolid (L) with the preclinical development candidate spectinamide 1599, administered by inhalation, in the BPaL standard of care regimen achieves similar efficacy, and reduces hematological changes and pro-inflammatory responses.

      Strengths:

      The authors not only measure efficacy but also quantify histological changes, hematological responses, and immune responses, to provide a comprehensive picture of treatment response and the benefits of the L to S substitution.

      The authors generate all data in two mouse models of TB infection, each reproducing different aspects of human histopathology.

      Extensive supplementary figures ensure transparency.

      Weaknesses:

      The articulation of objectives and hypotheses could be improved.

    2. Reviewer #3 (Public Review):

      Summary:

      In this paper, the authors sought to evaluate whether the novel TB drug candidate, spectinamide 1599 (S), given via inhalation to mouse TB models, and combined with the drugs B (bedaquiline) and Pa (pretomanid), would demonstrate similar efficacy to that of BPaL regimen (where L is linezolid). Because L is associated with adverse events when given to patients long-term, and one of those is associated with myelosuppression (bone marrow toxicity) the authors also sought to assess blood parameters, effects on bone marrow, immune parameters/cell effects following treatment of mice with BPaS and BPaL. They conclude that BPaL and BPaS have equivalent efficacy in both TB models used and that BPaL resulted in weight loss and anemia (whereas BPaL did not) under the conditions tested, as well as effects on bone marrow.

      Strengths:

      The authors used two mouse models of TB that are representative of different aspects of TB in patients (which they describe well), intending to present a fuller picture of the activity of the tested drug combinations. They conducted a large body of work in these infected mice to evaluate efficacy and also to survey a wide range of parameters that could inform the effect of the treatments on bone marrow and on the immune system. The inclusion of BPa controls (in most studies) and also untreated groups led to a large amount of useful data that has been collected for the mouse models per se (untreated) as well as for BPa - in addition to the BPaS and BPaL combinations which are of particular interest to the authors. Many of these findings related to BPa, BPaL, untreated groups, etc corroborate earlier findings and the authors point this out effectively and clearly in their manuscript. To go further, in general, it is a well-written and cited article with an informative introduction.

      Weaknesses:

      The authors performed a large amount of work with the drugs given at the doses and dosing intervals started, but at present, there is no exposure data available in the paper. It would be of great value to understand the exposures achieved in plasma at least (and in the lung if more relevant for S) in order to better understand how these relate to clinical exposures that are observed at marketed doses for B, Pa, and L as well as to understand the exposure achieved at the doses being evaluated for S. If available as historical data this could be included/cited. Considering the great attempts made to evaluate parameters that are relevant to clinical adverse events, it would add value to understand what exposures of drug effects such as anemia, weight loss, and bone marrow effects, are being observed.

      It would also be of value to add an assessment of whether the weight loss, anemia, or bone marrow effects observed for BPaL are considered adverse, and the extent to which we can translate these effects from mouse to patient (i.e. what are the limitations of these assessments made in a mouse study?). For example, is the small weight loss seen as significant, or is it reversible? Is the magnitude of the changes in blood parameters similar to the parameters seen in patients given L?

      In addition, it is always challenging to interpret findings for combinations of drugs, so the addition of language to explain this would add value: for example, how confident can we be that the weight loss seen for only the BPaL group is due to L as opposed to a PK interaction leading to an elevated exposure and weight loss due to B or Pa?

      Turning to the evaluations of activity in mouse TB models, unfortunately, the evaluations of activity in the BALB/c mouse model as well as the spleens of the Kramnik model resulted in CFU below/at the limit of detection and so, to this reviewer's understanding of the data, comparisons between BPaL and BPaS cannot be made and so the conclusion of equivalent efficacy in BALB/c is not supported with the data shown. There is no BPa control in the BALB/c study, therefore it is not possible to discern whether L or S contributed to the activity of BPaL or BPaS; it is possible that BPa would have shown the same efficacy as the 3 drug combinations. It would be valuable to conduct a study including a BPa control and with a shorter treatment time to allow comparison of BPa, BPaS, and BPaL. In the Kramnik lungs, as the authors rightly note, the studies do not support any contribution of S or L to BPa - i.e. the activity observed for BPa, BPaL, and BPaS did not significantly differ. Although the conclusions note equivalency of BPaL and BPaS, which is correct, it would be helpful to also include BPa in this statement; it would be useful to conduct a study dosing for a longer period of time or assessing a relapse endpoint, where it is possible that a contribution of L and/or S may be seen - thus making a stronger argument for S contributing an equivalent efficacy to L. The same is true for the assessment of lesions - unfortunately, there was no BPa control meaning that even where equivalency is seen for BPaL and BPaS, the reader is unable to deduce whether L or S made a contribution to this activity.

    3. Reviewer #1 (Public Review):

      Summary:

      This manuscript is an extension of previous studies by this group looking at the new drug spectinamide 1599. The authors directly compare therapy with BPaL (bedaquiline, pretomanid, linezolid) to a therapy that substitutes spectinamide for linezolid (BPaS). The Spectinamide is given by aerosol exposure and the BPaS therapy is shown to be as effective as BPaL without adverse effects. The work is rigorously performed and analyses of the immune responses are consistent with curative therapy.

      Strengths:

      (1) This group uses 2 different mouse models to show the effectiveness of the BPaS treatment.

      (2) Impressively the group demonstrates immunological correlates associated with Mtb cure with the BPaS therapy.

      (3) Linezolid is known to inhibit ribsomes and mitochondria whereas spectinaminde does not. The authors clearly demonstrate the lack of adverse effects of BPaS compared to BPaL.

      Weaknesses:

      (1) Although this is not a weakness of this paper, a sentence describing how the spectinamide would be administered by aerosolization in humans would be welcomed.

    1. Reviewer #3 (Public Review):

      Summary:

      The article by Huang et.al. presents an in-depth study on the role of DNA methylation in regulating virulence and metabolism in Pseudomonas syringae, a model phytopathogenic bacterium. This comprehensive research utilized single-molecule real-time (SMRT) sequencing to profile the DNA methylation landscape across three model pathovars of P. syringae, identifying significant epigenetic mechanisms through the Type-I restriction-modification system (HsdMSR), which includes a conserved sequence motif associated with N6-methyladenine (6mA). The study provides novel insights into the epigenetic mechanisms of P. syringae, expanding the understanding of bacterial pathogenicity and adaptation. The use of SMRT sequencing for methylome profiling, coupled with transcriptomic analysis and in vivo validation, establishes a robust evidence base for the findings

      Strengths:

      The results are presented clearly, with well-organized figures and tables that effectively illustrate the study's findings.

      Weaknesses:

      It would be helpful to add more details, especially in the methods, which make it easy to evaluate and enhance the manuscript's reproducibility.

    2. Reviewer #1 (Public Review):

      Summary:

      In this work, Huang et al used SMRT sequencing to identify methylated nucleotides (6mA, 4mC, and 5mC) in Pseudomonas syringae genome. They show that the most abundant modification is 6mA and they identify the enzymes required for this modification as when they mutate HsdMSR they observe a decrease of 6mA. Interestingly, the mutant also displays phenotypes of change in pathogenicity, biofilm formation, and translation activity due to a change in gene expression likely linked to the loss of 6mA.

      Overall, the paper represents an interesting set of new data that can bring forward the field of DNA modification in bacteria.

      Major Concerns:

      • Most of the authors' data concern Psph pathovar. I am not sure that the authors' conclusions are supported by the two other pathovars they used in the initial 2 figures. If the authors want to broaden their conclusions to Pseudomonas synringae and not restrict it to Psph, the authors should have stronger methylation data using replicates. Additionally, they should discuss why Pss is so different than Pst and Psph. Could they do a blot to confirm it is really the case and not a sequencing artefact? Is the change of methylation during bacterial growth conserved between the pathovar? The authors should obtain mutants in the other pathovar to see if they have the same phenotype. The authors have a nice set of data concerning Psph but the broadening of the results to other pathovar requires further investigation.

      • The authors should include proper statistical analysis of their data. A lot of terms are descriptive but not supported by a deeper analysis to sustain the conclusions. For example, in Figure 4E, we do not know if the overlap is significant or not. Are DEGs more overlapping to 6mA sites than non-DEGs? Here is a non-exhaustive list of terms that need to be supported by statistics: different level (L145), greater conservation (L162), significant conservation (L165), considerable similarity (L175), credible motifs (L189), Less strong (L277) and several "lower" and "higher" throughout the text.

      • The authors performed SMRT sequencing of the delta hsdMSR showing a reduction of 6mA. Could they include a description of their results similar to Figures 1-2. How reduced is the 6mA level? Is it everywhere in the genome? Does it affect other methylation marks? This analysis would strengthen their conclusions.

      • In Figure 6E to conclude that methylation is required on both strands, the authors are missing the control CAGCN6CGC construct otherwise the effect could be linked to the A on the complementary strand.

    3. Reviewer #2 (Public Review):

      In the present manuscript, Huang et.al. revealed the significant roles of the DNA methylome in regulating virulence and metabolism within Pseudomonas syringae, with a particular focus on the HsdMSR system in this model strain. The authors used SMRT-seq to profile the DNA methylation patterns (6mA, 5mC, and 4mC) in three P. syringae strains (Psph, Pss, and Psa) and displayed the conservation among them. They further identified the type I restriction-modification system (HsdMSR) in P. syringae, including its specific motif sequence. The HsdMAR participated in the process of metabolism and virulence (T3SS & Biofilm formation), as demonstrated through RNA-seq analyses. Additionally, the authors revealed the mechanisms of the transcriptional regulation by 6mA. Strictly from the point of view of the interest of the question and the work carried out, this is a worthy and timely study that uses third-generation sequencing technology to characterize the DNA methylation in P. syringae. The experimental approaches were solid, and the results obtained were interesting and provided new information on how epigenetics influences the transcription in P. syringae. The conclusions of this paper are mostly well supported by data, but some aspects of data analysis and discussion need to be clarified and extended.

    1. Reviewer #1 (Public Review):

      Summary:

      This study examines how blood vessels exposed to the cytokine VEGF respond to vascular leakage when the VEGF receptor NRP1 is targeted. This study compares results in in two different body sites of the dermis and in a different organ, the trachea. The authors refer to the two different sites of the dermis as two different organs, but the dermis is one organ. The authors report that vascular leakage is differentially affected by NRP1 targeting in the ear skin compared to the trachea and back skin. They attribute these differences to NRP1 presence in cells other than the vascular endothelium, especially in the ear skin, where they observe higher perivascular NRP1 staining.

      The manuscript states that the aim was to uncover the role of NRP1 in VEGF-mediated vascular permeability. This was misleading, because a lot is already known on NRP1 in this pathway, as is evidenced by a large number of publications the authors themselves quote (and sometimes misquote). The main information they wish to add is the possibility that NRP1 may also play a role in other cells to regulate permeability, as they previously suggested for blood vessel growth. Several technical issues and experimental limitations call into question whether the above conclusion can be reached with the data provided.

      Strengths:

      It is an interesting concept that NRP1 regulates vascular permeability by acting in perivascular cells.

      Weaknesses:

      (A) Technical limitations due to assay type:

      A direct comparison of the skin in two body sites is not warranted given that the authors used different methods to study the two sites. Below is a list of differences reported in their methods section:

      (A1) Different tracers were used to visualize VEGF165-induced leakage in different sites.<br /> Ear skin assay: 2 kDa FITC and two different dextrans, 10 kDa TRITC dextran, and another dextran whose molecular weight is not specified. It is not explained why 3 different tracers were used. Figures 1 and 2 report data with 2 kDa TRITC dextran.<br /> Back skin assay: They describe the Miles assay using Evans Blue, which binds to albumin, making it a 67 kDa tracer. However, Figure 1 suggests that 2 kDa dextran was used, and perhaps Evans Blue was only used for the supplemental data. This is relevant because current knowledge suggests that small dyes use the junctional pathway, whereas larger proteins such as albumin can use vesicular transport. The former is thought to be a fast pathway (hence, the authors measured dye extravasation 3 min after VEGF165 injection). The latter pathway is a slower one (hence, measured 30 min after VEGF165 injection in the Miles assay).

      Quantification: For ear skin, the number of leakage sites and lag period is quantified, as well as leakage over time. For back skin, the amount of extravasated dye is quantified at a fixed time point. Such different measurements do not allow for direct comparison.

      (A2) Mice were prepared in different ways for the different body sites studied:<br /> Ear skin assay: general anesthesia with ketamine-xylazine.<br /> Back skin assay: No anesthesia is described for the back skin Miles assay. This would be a concern because intradermal injections are considered to be painful. For back skin histology, they do report to have used isoflurane anesthesia before perfusion fixation. However, it is not advisable to use used isoflurane anesthesia for perfusion fixation if this has been done via the conventional cardiac route, because opening the chest cavity to access the heart for perfusion causes lung collapse, meaning that the mice cannot breathe the anaesthetic, and there is a risk of them regaining consciousness. The authors should clarify what exactly they have done, for ethical reasons and also because the type of anesthesia can affect vascular studies, for example, see PMID 36418078.

      (A3) Differential histamine use:<br /> Back skin assay: uses anti-histamine, as is advised with intradermal injections to minimize vascular leakage due to histamine release after local trauma.<br /> Ear skin assay: no anti-histamine was used, so histamine-induced background leakage might have been present, independently of VEGF165. The authors suggest that the ear skin injection does not cause trauma, but it is unclear how this is possible, given that skin needs to be disrupted for the needle to enter the tissue.

      (A4) Different VEGF165 concentration used:<br /> The ear skin assay uses 10 ng VEGF per injection, and the back skin assay 80 ng.

      Given all these differences in experimental protocols, as well as different knockdown efficiency (see below), the results for the different sites are not directly comparable. Hence it cannot presently be concluded that the role of NRP1 in both sites is different, and further work is required to make a firm conclusion. In addition, the conflicts between the reported methods and figures need to be resolved.

      (B) It is unclear whether appropriate controls were used:

      (B1) What genotype and treatment are the control mice for NRP1 targeting? The ideal control would be wild-type mice with the same CreER, injected with tamoxifen according to the same timeline, to account for vehicle, tamoxifen, and tamoxifen-induced CreER toxicity (https://doi.org/10.1038/s44161-022-00125-6). This could be a littermate mouse or, alternatively, a separate experiment should be shown comparing wild-type mice carrying the same CreER as used for the ablation studies and injected with tamoxifen, versus wild-type mice injected with tamoxifen, to demonstrate that the induction regime does not in itself cause phenotypes.

      (B2) Has a PBS injection been performed to compare baseline leakage between genotypes, independently of VEGF165 injections? This is an essential control.

      (B3) The experimental protocol assays 4 days after 5 consecutive tamoxifen injections, which does not allow much time for drug washout. Moreover, this is a lot of tamoxifen (80 mg x 5 = 400 mg tamoxifen per kg). Due to the possibility that tamoxifen-induced effects might still be present and cause sex-differential effects, the corresponding sex for each individual data point should be indicated in all graphs.

      (B4) i.p. peanut oil is used in undefined volumes; this vehicle was shown to cause inflammation if administered i.p. (PMID 33139505). Therefore, inflammation might be present, which might affect different body sites differently.

      (C) Validation of NRP1 targeting:<br /> The authors have not performed an NRP1 knockout in the endothelium, as they repeatedly claim. In the lung, there is a good knockdown of around 75%; this may or may not be due to complete EC knockdown with preservation of NRP1 in other cell types. In the trachea, ear skin, and back skin, knockdown was not quantified, although qualitative comparisons by NRP1 immunostaining in Supplementary Figure 1 suggest that the back skin targeting worked better than the ear skin targeting, which would confound results, but in any case, it was neither a knockdown nor knockout. The staining for global targeting looks fainter than for the other genotypes, and the single-channel images seem to have different intensities than the overlays in Supplementary Figure 1 A.

      (D) Systemic permeability studies:<br /> Organs have very different baseline permeability, due to the properties of the vascular barrier, i.e. tight barriers in the brain and retina and permeable endothelium in the liver and kidney. In this assay, VEGF is not delivered from the tissue side, as would be typical during inflammation but is delivered through the circulation, which has been shown to differentially affect the VEGF response, at least in some tissues (PMID 25175707). Nevertheless, this is a helpful readout, especially given that PBS controls appear not to have been performed above to establish baseline leakage between genotypes and tissues.

      Figure Supplement 3 shows that VEGF induces vascular leakage in all body sites examined, independently of the size of the tracer used, and agreeing with current literature. An additional set of panels should be included with data shown without calculating the fold change relative to the control, set to 1, to account for the endothelium in different organs having different baseline vascular permeability. How do the authors explain that VEGF has the same effect in the ear and back skin in this assay, when NRP1 is present, given that they claim a role for perivascular NRP1 in the ear, but not back skin, for reducing VEGF/VEGFR2 signalling?

      (E) Comparing results obtained with different tools:

      - The endothelial NRP1 knockdown yielded different results for ear and back skin.<br /> - Anti-NRP1 yielded similar results for ear and back skin.<br /> - The global NRP1 ko yielded similar results for ear and back skin.<br /> Because anti-NRP1 and the global NRP1 knockdown gives similar results for all tissues, the authors deduce that the NRP1 acts in cell types other than endothelial cells to regulate permeability. This is an interesting idea, based on the lab's prior work in angiogenesis. In their trans-interaction scenario, NRP1 would have the same role in ECs in all sites, but non-endothelial NRP1 can override the function of the endothelial NRP1 function depending on its expression levels.

      Confidence in this conclusion would require additional experiments:<br /> - Show that the endothelial knockdown works equally well in different body sites, via NRP1 staining and/or by checking recombination efficiency with a reporter.<br /> - Using an analogous assay to measure permeability in different body sites.<br /> - Perform a non-endothelial knockdown, i.e. in pericytes, which is hypothesized to be the source of NRP1 that affects vascular leakage signalling in endothelial cells in trans.

      (F) Abstract, introduction, and references:<br /> The authors suggest controversy with regard to NRP1's roles in permeability. However, NRP1's function in VEGF signalling has been defined as being an accessory to VEGFR2, with a role in promoting SFK activation. This function relies on the NRP1 cytoplasmic domain, which mediates VEGFR2 trafficking and signalling; the relevant literature for the NRP1 cytoplasmic domain is mentioned for arteriogenesis (PMID 23639442), but not permeability (PMID 28289053). Another paper is mentioned which describes a VEGFR2-independent pathway for a CendR ligand, but this prior study did NOT make the claim that VEGF signalling is NRP1-independent or promotes it (PMID 27117252). In the eye, NRP1 has been implicated in both SEMA3A and VEGF165-induced permeability, which was also corroborated by the Miles assay in two prior studies (PMID 18180379, PMID 28289053). The last sentence in the abstract is incorrect, because differences in ear versus back skin do not constitute organotypic difference (as the organ is the dermis), and the potential role of perivascular cells is only inferred from the global endothelial NRP1 knockdown, which gives the same result as reported for the endothelial NRP1 knockdown in the literature.

      (1) Lines 5/.53: The references for VEGF-NRP1 signalling in age-related macular degeneration are not helpful: Raimondi investigated VEGF-independent NRP1 pathways in angiogenesis, Fernandez-Robredo investigated NRP1 pathways in angiogenesis and showed that fewer vessels correlated with less leakage but did not test VEGF signaling specifically. A more suitable reference would have been PMID 28289053.

      (2) Lines 63/64 and repeated in 84-89: The references quoted all showed that NRP1 inhibition reduces vascular permeability, and therefore do not provide evidence for the idea that NRP1 inhibition promotes permeability, as the authors report here for the ear skin; the only study supporting them is one using arterial endothelial cells, which are not permeability-relevant.

      (3) Lines 106/107: The references used to underpin organ-specific barrier properties are correct, but as stated above, the dermis is the dermis, and therefore, these references would not be useful to provide support for the idea that the ear and back skin behave differently after NRP1 knockdown.

      (G) Additional comments on the figures:<br /> Figure 4: The authors show that VEGFR2 is essential for permeability, and VEGF164 effects are VEGFR2 dependent - this is well established for VEGF164 in the Miles assay, including the accessory role of NRP1 (e.g. PMID 28289053). As the proposed trans function of NRP1 cannot make a difference in VEGFR2 signaling when VEGFR2 is not there, this experiment is only confirmatory of prior VEGFR2 knowledge.

    2. Reviewer #2 (Public Review):

      The paper by Pal et al. examines the role of Nrp1 in organ-specific permeability response to VEGF. The subject is certainly interesting, but there are a number of significant methodological problems that make data evaluation rather problematic. In particular, lung endothelial cells are used to assess the effectiveness of Nrp1 knockout when experiments focus on different organs; small number of data points (as small as 2 or 3) are used to claim statistically significant differences; obvious data scatter is not commented on and seems ignored; key reagents (anti-Nrp1 Ab) are not well characterized, a proposed model is not verified in vitro, etc. Some of these issues are outlined in detail below, but the list of problems is much longer than this.

      (1) Intradermal injection of anti-Nrp1 Ab: I am puzzled by this experiment: Will Ab presence be limited locally or is there a systemic distribution? This needs to be verified.

      (2) What does anti-Nrp1 Ab actually do? Does it block VEGF binding? Induces Nrp1 and VEGFR2 endocytosis?

      (3) How does i.v. injection of anti-Nrp1 Ab affect permeability in different organs?

      (4) Effect of endothelial Nrp1KO: Since the authors examine organ-specific effects of Nrp1, it seems illogical to assess its expression in the lung as a measure of KO as KO efficiency may differ organ by organ. Immunocytochemistry is not particularly quantitative and prone to selection bias. I'd suggest using EC bulk RNAseq from different organs to confirm the magnitude of the knockout in different beds.

      (5) Figures 1B and 2B show profoundly different levels of Nrp1 KO in lung ECs. Were different mouse strains used in Figure 1 and Figure 2 experiments? This may well explain the differences the authors have observed.

      (6) Supplementary Figure 2: why is there no leakage of 10kD dextran in the heart in response to VEGF when there is an increase in the 70kD dextran leakage? That does not seem possible. Further, the authors observed no significant increase in 70kD dextran leakage after VEGF in the skeletal muscle. That also seems very unlikely and flies against experience of many labs in the field.

      (7) Since the authors think that peri-vascular cell Nrp1 expression accounts for organ-specific Nrp1 effects, this should be studied and examined in an in vitro co-culture model.

      (8) Quantification: a lot of quantifications- of Nrp1 expression level, VE-cadherin Y685 phosphorylation, etc. are done on the basis of immunocytochemistry. This really is not a quantitative technique and is prone to numerous artifacts. The data should be at least confirmed by whole-tissue Westerns. I am also puzzled by small numbers of samples. If each dot on a graph represents an individual data point, how do authors get a p<0.5 value with an N of 3? (for example Figure 5B, but there are other examples). Also, in Figure 4F data scatter is quite enormous. This is either an experimental problem or, more likely, there is a biological message here - the tissue is not uniform. In any case, I do not see how one gets a significant result here. Figures 5B and 5C have a similar problem while Figure 5D seems to be based on only two data points?

    3. Reviewer #3 (Public Review):

      Summary:

      Pal et al. provide valuable evidence supporting distinct vascular bed-specific VEGF-A mediated vascular permeability function of Neuropilin-1 (NRP1) in adult mice. Using a suite of genetic mice models and state-of-the-art vascular permeability assays the authors demonstrate that ear skin vasculature of EC-specific NRP1 adult knockout mice is hypersensitive to VEGF-A mediated high-molecular weight dye leakage from venules, as opposed to back skin and tracheal vasculature where EC-specific NRP1 loss had a more classical negative effect on permeability. Interestingly, both whole organism KO of NRP1 and a blocking antibody treatment, attenuated VEGF-A mediated permeability in ear skin and had the usual attenuation of permeability phenotype in back skin and tracheal vasculature. Using a pericyte promoter specific reporter mice line, the authors characterize NRP1 expression in the vascular beds of the ear dermis and back skin and conclude that NRP1 expression is higher in perivascular cells in the ear dermis as opposed to back skin vasculature, thus indicating a juxtracrine NRP1-VEGFR2 signaling model in adult mice. Further, they use a Vegfr2 phosphosite mutant homozygous mice model in the background of NRP1 iECKO to find the hypersensitivity to VEGF-A stimulation in ear skin is abrogated and therefore, prove the juxtracrine NRP1 control of VEGFR2 mediated downstream signaling leading to vascular permeability. Further, they successfully show distinctive vascular bed-specific results as above using a well-characterized VE-Cadherin Y685 antibody staining which corresponds to vascular leakage downstream of VEGF-A/VEGFR2 signaling in ear dermis and back skin vascular beds.

      Strengths:

      The question of the in vivo role of NRP1 in VEGF-A-induced hyper-permeability is an unresolved one and the elegant use of genetic mice models to demonstrate the phenotypes is valuable to the field. The organotypic differences observed in vascular permeability upon VEGF-A treatment in ear skin versus back skin and tracheal vasculature are solid. The subsequent investigation to validate heightened VEGFR2 signaling in ear dermis downstream of VEGF-A stimulation using Vegfr2 Y949F mice, VEC Y685 antibody, and pPLCγ antibody is also very convincing.

      Weaknesses:

      The mechanism proposed by the authors by which EC-specific loss of NRP1 caused hypersensitivity to VEGF-A in ear dermis is through elevated juxtracrine signaling of NRP1 expressed in pericytes in trans binding and retaining VEGFR2 on the cell surface of ECs to sustain downstream signaling for longer time, in corroboration to earlier findings in Koch et al., 2014, where NRP1 was studied in the context of tumor angiogenesis. To support their claim, the authors stain the ear dermis and back skin vasculature of Pdgfrb-GFP reporter mice, with NRP1 and CD31 antibodies and find out that ear skin vasculature has higher perivascular cells as opposed to back skin vasculature. While this is a good experiment to prove the above point, there are no functional experiments to support this model.

      Overall, although the paper presents very useful findings in the field of NRP1-VEGFR2 biology, and most of the conclusions are well supported by the data, there are a few points if addressed can significantly substantiate the model of juxtracrine signaling proposed by the authors. They are:

      (1) It will be important to know if the perivascular to vascular NRP1 expression (such as in Figure 3B) increases further in ear skin vasculatures of NRP1 iECKO mice compared to otherwise WT mice.

      (2) Does knocking out NRP1 in pericytes attenuate the VEGF-A mediated hyperpermeability observed in ear skin of NRP1 iECKO mice (similar to experiments in 1C, 2C)?

      (3) What is the status of VEGFR2 expression in ECs of ear skin and back skin of NRP1 iECKO and NRP1 iKO mice? This experiment is a proof-of-concept and is not essential to prove the point of juxtracrine NRP1 signaling since downstream readouts - pPLCγ and VEC Y685 staining have already been shown to correlate in the ear dermis.

    1. Reviewer #1 (Public Review):

      Summary:

      In this article, Kremser et al set off to explore how local interactions between cells can drive pattern formation by focusing on the French flag problem whereby an initially homogeneous system breaks axial symmetry to form three distinct regions of different cell fates. The authors use a cellular automata model together with evolution searches on possible rules that determine cell state and tissue level patterning. It is assumed that three cell states are possible and that at each time iteration each cell updates its fate according to the current state of itself and its neighbours. The authors use a computational procedure based on evolution algorithms to identify "fit" update rules that can successfully drive patterning into three distinct domains and go on to provide insights with regards to the function of these rules as well as their properties such as robustness and patterning dynamics. The article is generally well-written, the results seem solid, and the analysis and methods are thorough and generally well-explained. A main concern is the lack of connection between the biology that motivated the analysis and the results, this could be improved in the discussion by making the methods somewhat more concise to allow space to make links back to potential biological mechanisms when the results are presented. We raise some general points and some more specific questions and suggestions for clarification below that we hope will help improve the MS and make it more accessible to a wider audience.

      General points:

      • Although the authors motivate their work on the premise that biological patterns at the tissue level often are driven by local cell-cell interactions, by the end of the analysis any possible connection to the underlying biology is lost. For example, it would have been useful to discuss how the rules that evolved to dominate the patterning process in the results section could be implemented by cells. Is there a connection that could be made back to Notch signalling and its multiple ligands or to morphogens that diffuse only locally? Would the large number of rules possible in the cellular automata context reflect transcriptional feedback? This is an important point to bring the work "home". At the moment, it feels like a nice computational analysis of cellular automata but the links to the systems that motivate the work are lost in the process.

      • When growth is considered (p.14-15) a discussion of timescales seems pertinent. Often patterning takes place at a timescale faster than cell division so the system could be allowed to reach a steady state before a new division event takes place. What are the time scales of updating the phenotype compared with the time scales of division in the model and in relevant biological systems? How would different limiting cases impact conclusions, e.g. new cells added and pattern allowed to reach steady state before more growth versus cells added while patterning dynamics are still updating?

      • An interesting question is whether certain elements of rules (out of the 27 possible elements for the system with 3 states) are more or less likely to appear together in an evolved final rule. This may give a mechanistic understanding of what combinations of elements are likely to drive the optimal pattern and which combinations are avoided altogether.

    2. Reviewer #2 (Public Review):

      Summary:

      In this paper, the authors seek to identify strategies that can be used to generate robust one-dimensional large-scale patterns through the sequential application of only local, unchanging, space-independent rules. This is an important general question in developmental biology.

      Strengths:

      The authors do a nice job of laying out the problem, which they explore through cellular automaton (CA) modeling. The modeling framework is well described, as are the methods used for computational identification of effective (most "fit") strategies. As many biologists are unfamiliar with CA models, the clarity of description offered by these authors is especially important, as is the attention that was paid to useful visualization of results.

      Ultimately, the authors use their approach to converge on certain generic strategies for achieving robust patterns. In the case when there are only three states (no hidden or transient states) available to cells, they rationalize the consensus strategy that emerges to involve a combination of "sorting" and "bulldozer" modules, which are relatively easy to rationalize. In cases involving a fourth state, a more complicated set of strategies arise and are considered.

      As a pure modeling paper, I find the work to be very well done, and the conclusions are well supported by the data and analyses. In terms of the long-term importance of this approach to biologists studying pattern formation, I see this paper as primarily laying a foundation for taking the next step, which is moving into two (or three dimensions). Clearly, the complexity of rules becomes much greater, but one may expect some big qualitative differences to show up in higher dimensions, where simple strategies like sorting and bulldozing cannot work quite as simply. It will be interesting to see where this leads.

      Weaknesses:

      Ultimately, the relevance of this work to biology rests with its ability to provide insight into important biological problems. In terms of explaining the challenging nature of generating long-range patterns using short-range rules, I think the authors do a good job. However, they could do a better job of relating the results of the work back to biology. For example, are there examples of "sorting module" and "bulldozer module" behavior in biology? Could they be involved in explaining actual biological patterns?

      It also would have been helpful for the authors to generalize more about the way in which their CA rules achieve global patterns with other patterning mechanisms. For example, in a Wolpert positional information model, patterning information is distributed over space in a steady-state gradient. In the CA model, no information spreads more than one cell at any one time point, but over time information still spreads, so in a sense a stationary spatial gradient has been traded for a moving spatial discontinuity. Because the discontinuity moves without decrement, any stationary state ends up being determined by the boundaries of the system, which goes a long way to explaining the robustness they observe, as well as why the result is quite sensitive to growth (which keeps changing the boundary).

    1. Reviewer #2 (Public Review):

      In this study, Torcq and colleagues make carefull observations of the cellular morphology of haemogenic endothelium undergoing endothelial to haematopoietic transition (EHT) to become stem cells, using the zebrafish model. To achieve this, the used an extensive array of transgenic lines driving fluorescent markers, markers of apico-basal polarity (podocalixin-FP fusions) or tight junction markers (jamb-FP fusions). The use of the runx truncation to block native Runx1 only in endothelial cells is an elegant tool to achieve something akin to tissue-specific deletion of Runx1. Overall, the imaging data is of excellent quality. They demonstrate that differences in apico-basal polarity are strongly associated with different cellular morphologies of cells undergoing EHT from HE (EHT pol- and EHT pol+) which raises the exciting possibility that these morphological differences reflect heterogeneity of HE (and potentially HSCs, but this is not addressed in this manuscript) at a very early stage. They then overexpress a truncated form of Runx1 (just the runt domain) to block Runx1 function and show that more HE cells abort EHT and remain associated with the embryonic dorsal aorta. The revised version identifies pard3ab as differentially distributed in dtRunx mutants and correlates that distribution with a potential regulatory role on cell polarity. No direct evidence for their role in EHT is presented.

      The manuscript has now been streamlined and reference to figures made much clearer. It provides for a clearer reading, and clearly a well thought out discussion of HE, polarity and the regulation of the EHT process. The evidence for the different cellular morphologies of cells undergoing EHT is strong, and the main claim that tuning apico-basal polarity and junctional recycling underlie morphological complexity of EHT (rather than of HSCs) is well supported by the data.

    1. Reviewer #1 (Public Review):

      Summary

      The authors investigated the antigenic diversity of recent (2009-2017) A/H3N2 influenza neuraminidases (NAs), the second major antigenic protein after haemagglutinin. They used 27 viruses and 43 ferret sera and performed NA inhibition. This work was supported by a subset of mouse sera. Clustering analysis determined 4 antigenic clusters, mostly in concordance with the genetic groupings. Association analysis was used to estimate important amino acid positions, which were shown to be more likely close to the catalytic site. Antigenic distances were calculated and a random forest model used to determine potential important sites.

      This revision has addressed many of my concerns of inconsistencies in the methods, results and presentation. There are still some remaining weaknesses in the computational work.

      Strengths

      (1) The data cover recent NA evolution and a substantial number (43) of ferret (and mouse) sera were generated and titrated against 27 viruses. This is laborious experimental work and is the largest publicly available neuraminidase inhibition dataset that I am aware of. As such, it will prove a useful resource for the influenza community.

      (2) A variety of computational methods were used to analyse the data, which give a rounded picture of the antigenic and genetic relationships and link between sequence, structure and phenotype.

      (3) Issues raised in the previous review have been thoroughly addressed.

      Weaknesses:

      Some concerns regarding the robustness of the machine learning model and potential overfitting remain.

    2. Reviewer #2 (Public Review):

      Summary:

      The authors characterized the antigenicity of N2 protein of 43 selected A(H3N2) influenza A viruses isolated from 2009-2017 using ferret and mice immune sera. Four antigenic groups were identified, which the authors claimed to be correlated with their respective phylogenic/ genetic groups. Among 102 amino acids differed by the 44 selected N2 proteins, the authors identified residues that differentiate the antigenicity of the four groups and constructed a machine-learning model that provides antigenic distance estimation. Three recent A(H3N2) vaccine strains were tested in the model but there was no experimental data to confirm the model prediction results.

      Strengths:

      This study used N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 and generated corresponding panels of ferret and mouse sera to react with the selected strains. The amount of experimental data for N2 antigenicity characterization is large enough for model building.

      Weaknesses:

      One weakness is the use of double-immune ferret sera (post-infection plus immunization with recombinant NA protein) or mouse sera (immunized twice with recombinant NA protein) to characterize the antigenicity of the selected A(H3N2) viruses. Conventionally, NA antigenicity is characterized using ferret sera after a single infection. Repeated influenza exposure in ferrets has been shown to enhance antibody binding affinity and may affect the cross-reactivity to heterologous strains (PMID: 29672713). The increased cross-reactivity is supported by the NAI titers shown in Table S3, as many of the double immune ferret sera showed the highest reactivity not against its own homologous virus but to heterologous strains. In response to the reviewer's comment, the authors agreed the use of double-immune ferret sera may be a limitation of the study.

      Another weakness is that the authors used the newly constructed a model to predict antigenic distance of three recent A(H3N2) viruses but there is no experimental data to validate their prediction (eg. if these viruses are indeed antigenically deviating from group 2 strains as concluded by the authors). Leaving out data from some strains for testing is a useful check, but due to phylogenetic correlations in the data the generalizability of the machine learning is not guaranteed.

    3. Reviewer #3 (Public Review):

      Summary:

      This paper by Portela Catani et al examines the antigenic relationships (measured using monotypic ferret and mouse sera) across a panel of N2 genes from the past 14 years, along with the underlying sequence differences and phylogenetic relationships. This is a highly significant topic given the recent increased appreciation of the importance of NA as a vaccine target, and the relative lack of information about NA antigenic evolution compared with what is known about HA. Thus, these data will be of interest to those studying the antigenic evolution of influenza viruses. The methods used are generally quite sound, though there are a few addressable concerns that limit the confidence with which conclusions can be drawn from the data/analyses.

      Strengths:

      -The significance of the work, and the (general) soundness of the methods.<br /> -Explicit comparison of results obtained with mouse and ferret sera

      Weaknesses:

      - Machine learning analyses neither experimentally validated nor shown to be better than simple, phylogenetic-based inference.

    1. Reviewer #2 (Public Review):

      Summary:

      The manuscript by Kandoi et al. describes a new 3D retinal organoid model of a mono-allelic copy number variant of the rhodopsin gene that in a patient led to autosomal dominant retinitis pigmentosa. The evidence provided here is relatively strong that the rod photoreceptor phenotype observed in an adult patient with RP in vivo is similar to that phenotype observed in human stem cell-derived retinal organoids. Increases in RHO expression were detected by qPCR, RNA-seq, and IHC support this phenotype. Importantly, the amelioration of photoreceptor rhodopsin mislocalization and related defects using the small molecule drug photoregulin demonstrates an important potential clinical application.

      Strengths:<br /> - Retinal organoids derived from patient with adRP.<br /> - RHO mislocalization could explain the phenotype in patients.

      Weaknesses:

      - Organoids at 300 days do not show PR loss.

      Additional minor weaknesses

      - Bulk RNAseq methods require greater detail, particularly with respect to how total or mRNA was purified, how was it quantified for concentration and integrity (i.e. Nanodrop, Tape station, Bioanalyzer), what reagents were used for library preparation and how many reads were analyzed per sample.

      - Fig. 4. The levels of RHO visualized in tissue sections (panels A-C) does not seem to match the general levels shown for the western blots (panel D) which appear to be far higher in RM western blot samples than in the IHC images. Please clarify why there is such a difference.

      - Line 186: by what criteria are the authors able to state that " there were no clear visible anatomical changes in apical-basal retinal cell type distribution (data not shown)". Was this based on histological staining with antibodies, nuclear counter-staining or some other evaluation?

    2. Reviewer #3 (Public Review):

      This manuscript reports a novel pedigree with four intact copies of RHO on a single chromosome which appears to lead to overexpression of rhodopsin and a corresponding autosomal dominant form of RP. The authors generate retinal organoids from patient- and control-derived cells, characterize the phenotypes of the organoids, and then attempt to 'treat' aberrant rhodopsin expression/mislocalization in the patient organoids using a small molecule called photoregulin 3 (PR3). While this novel genetic mechanism for adRP is interesting, the organoid work is not compelling. There are multiple problems related to the technical approaches, the presentation of the results, and the interpretations of the data. I will present my concerns roughly in the order in which they appear in the manuscript and will separate them into 'major' and 'minor' categories:

      Major concerns:<br /> (1) Individual human retinal organoids in culture can show a wide range of differentiation phenotypes with respect to the expression of specific markers, percentages of given cell types, etc. For this reason, it can be very difficult to make rigorous, quantitative comparisons between 'wild-type' and 'mutant' organoids. Despite this difficulty, the author of the present manuscript frequently present results in an impressionistic manner without quantitation. Furthermore, there is no indication that the investigator who performed the phenotypic analyses was blind with respect to the genotype. In my opinion, such blinding is essential for the analysis of phenotypes in retinal organoids.

      To give an example, in lines 193-194 the authors write "we observed that while the patient organoids developing connecting cilium and the inner segments similar to control organoids, they failed to extend outer segments". Outer segments almost never form normally in human retinal organoids, even when derived from 'wild-type' cells. Thus, I consider it wholly inadequate to simply state that outer segment formation 'failed' without a rigorous, quantitative, and blinded comparison of patient and control organoids.

      (2) The presentation of qPCR results in Fig. 3A in very confusing. First, the authors normalize expression to that of CRX, but they don't really explain why. In lines 210-211 they write "CRX, a ubiquitously expressing photoreceptor gene maintained from development to adulthood." Several parts of this sentence are misleading or incomplete. First, CRX is not 'ubiquitously expressed' (which usually means 'in all cell types') nor is it photoreceptor-specific: CRX is expressed in rods, cones, and bipolar cells. Furthermore, CRX expression levels are not constant in photoreceptors throughout development/adulthood. So, for these reasons alone, CRX is a poor choice for normalization of photoreceptor gene expression.

      Second, the authors' interpretation of the qPCR results (lines 216-218) is very confusing. The authors appear to be saying that there is a statistically significant increase in RHO levels between D120 and D300. However, the same change is observed in both control and patient organoids and is not unexpected, since the organoids are more mature at D300. The key comparison is between control and patient organoids at D300. At this time point, there appears to be no difference control and patient. The authors don't even point this out in the main text.

      Third, the variability in number of photoreceptor cells in individual organoids makes a whole-organoid comparison by qPCR fraught with difficulty. It seems to me that what is needed here is a comparison of RHO transcript levels in isolated rod photoreceptors.

      (3) I cannot understand what the authors are comparing in the bulk RNA-seq analysis presented in the paragraph starting with line 222 and in the paragraph starting with line 306. They write "we performed bulk-RNA sequencing on 300-days-old retinal organoids (n=3 independent biological replicates). Patient retinal organoids demonstrated upregulated transcriptomic levels of RHO... comparable to the qRT-PCR data." From the wording, it suggests that they are comparing bulk RNA-seq of patient and control organoids at D300. However, this is not stated anywhere in the main text, the figure legend, or the Methods. Yet, the subsequent line "comparable to the qRT-PCR data" makes no sense, because the qPCR comparison was between patient samples at two different time points, D120 and D300, not between patient and control. Thus, the reader is left with no clear idea of what is even being compared by RNA-seq analysis.

      Remarkably, the exact same lack of clarity as to what is being compared plagues the second RNA-seq analysis presented in the paragraph starting with line 306. Here the authors write "We further carried out bulk RNA-sequencing analysis to comprehensively characterize three different groups of organoids, 0.25 μM PR3-treated and vehicle-treated patient organoids and control (RC) organoids from three independent differentiation experiments. Consistent with the qRT-PCR gene expression analysis, the results showed a significant downregulation in RHO and other rod phototransduction genes." Here, the authors make it clear that they have performed RNA-seq on three types of sample: PR3-treated patient organoids, vehicle-treated patient organoids, and control organoids (presumably not treated). Yet, in the next sentence they state "the results showed a significant downregulation in RHO", but they don't state what two of the three conditions are being compared! Although I can assume that the comparison presented in Fig. 6A is between patient vehicle-treated and PR3-treated organoids, this is nowhere explicitly stated in the manuscript.

      (4) There are multiple flaws in the analysis and interpretation of the PR3 treatment results. The authors wrote (lines 289-2945) "We treated long-term cultured 300-days-old, RHO-CNV patient retinal organoids with varying concentrations of PR3 (0.1, 0.25 and 0.5 μM) for one week and assessed the effects on RHO mRNA expression and protein localization. Immunofluorescence staining of PR3-treated organoids displayed a partial rescue of RHO localization with optimal trafficking observed in the 0.25 μM PR3-treated organoids (Figure 5B). None of the organoids showed any evidence of toxicity post-treatment."

      There are multiple problems. First, the results are impressionistic and not quantitative. Second, it's not clear that the investigator was blinded with respect to treatment condition. Third, in the sections presented, the organoids look much more disorganized in the PR3-treated conditions than in the control. In particular, the ONL looks much more poorly formed. Overall, I'd say the organoids looked considerably worse in the 0.25 and 0.5 microM conditions than in the control, but I don't know whether or not the images are representative. Without rigorously quantitative and blinded analysis, it is impossible to draw solid conclusions here. Lastly, the authors state that "none of the organoids showed any evidence of toxicity post-treatment," but do not explain what criteria were used to determine that there was no toxicity.

      (5) qPCR-based quantitation of rod gene expression changes in response to PR3 treatment is not well-designed. In lines 294-297 the authors wrote "PR3 drove a significant downregulation of RHO in a dose-dependent manner. Following qRT-PCR analysis, we observed a 2-to-5 log2FC decrease in RHO expression, along with smaller decreases in other rod-specific genes including NR2E3, GNAT1 and PDE6B." I assume these analyses were performed on cDNA derived from whole organoids. There are two problems with this analysis/interpretation. First, a decrease in rod gene expression can be caused by a decrease in the number of rods in the treated organoids (e.g., by cell death) or by a decrease in the expression of rod genes within individual rods. The authors do not distinguish between these two possibilities. Second, as stated above, the percentage of cells that are rods in a given organoid can vary from organoid to organoid. So, to determine whether there is downregulation of rod gene expression, one should ideally perform the qPCR analysis on purified rods.

      (6) In Fig. 4B 'RM' panels, the authors show RHO staining around the somata of 'rods' but the inset images suggest that several of these cells lack both NRL and OTX2 staining in their nuclei. All rods should be positive for NRL. Conversely, the same image shows a layer of cells sclerad to the cells with putative RHO somal staining which do not show somal staining, and yet they do appear to be positive for NRL and OTX2. What is going on here? The authors need to provide interpretations for these findings.

      Minor concerns:

      (1) The writing is poor in many places. Problems include: poor word choice (e.g., 'semi-occasional' is used three times where 'occasional' or 'infrequent' would be better); superfluous use of the definite article in many places (e.g., lines 189-190 "by the light microscopy" should be "by light microscopy"); awkward sentence structures (e.g., lines 208-209: "To equilibrate the data to equivalent the number of photoreceptors in organoids"), opaque expressions (e.g., line 217 "there was a significant ~3 log2 fold change (log2FC)"; why not just say "an ~8-fold change"?); poor proof-reading (Abstract says that 40% of adRP cases are due to mutation in RHO, then the Introduction says the figure is 25%) etc.

      (2) The figures are not numbered, which makes it painful for the reviewer to correlate main text call-outs, figure legends, and actual figures. I had to repeatedly count down the list of figures to determine which figure I should be looking at.

      (3) In the abstract, the authors suggest that the patient's disease "develops from a dominant negative gain of function" mechanism. I don't agree with this interpretation. Typically 'dominant-negative' refers to an aberrant protein which directly interferes with the function of the normal protein, for example by forming non-functional heterodimers. In the present patient, the disease can be explained by a simple overexpression mechanism, as it has been previously demonstrated in mice that even minimal overexpression of rhodopsin (e.g., ~25% more than normal levels) can led to progressive rod degeneration: PMID: 11222515.

      (4) In line 85 the word 'Morphologically' is superfluous and can be deleted.

      (5) In the Introduction the authors should more clearly articulate the rationale for using PR3 to treat this patient: because it leads to downregulation of multiple rod genes including RHO. This isn't clearly explained until the Discussion.

      (6) The authors mention in several places that PR3 may act via inhibition of NR2E3. Although this was the conclusion of the original publication, the evidence that PR3 acts via Nr2e3 in mice is not solid. The original study (PMID: 29148976) showed that the main effect of PR3 application on mouse retinas is downregulation of numerous rod genes. However, knockout of Nr2e3 in mouse has been shown to have very little effect on rod gene expression, and Nr2e3 mutant rods have largely preserved rod function as demonstrated by scotopic ERGs PMIDs: 15634773, 16110338, 15689355). The primary gene expression defect in Nr2e3 mutant mouse rods is upregulation of a subset of cone genes, a change not observed upon application of PR3 to mouse retinas. For these reasons, I am skeptical that PR3 acts via inhibition of Nr2e3 activity, and I would suggest that the present authors qualify that interpretation.

      (7) This mechanistic speculation presented in lines 274-278 is not warranted. Ectopic localization of opsin to the cytoplasmic membrane occurs in a wide range of genetic forms of rod degeneration.

    1. Reviewer #1 (Public Review):

      Valk and Engert et al. examined the potential relations between three different mental training modules, hippocampal structure and functional connectivity, and cortisol levels (stress) over a 9-month period. They found that among the three types of mental training: Presence (attention and introspective awareness), Affect (socio-emotional - compassion and prosocial motivation), and Perspective (socio-cognitive - metacognition and perspective taking) modules; Affect training most robustly related to changes in hippocampal structure and function - specifically, CA1-3 subfields of the hippocampus. Moreover, change in intrinsic functional connectivity related to changes in diurnal cortisol release and long-term cortisol exposure. These changes are proposed to result from a combination of factors, which is supported by multivariate analyses showing changes across subfields and training content relate to cortisol changes.

      The authors demonstrate that mindfulness training programs are a potential avenue for stress interventions that impact hippocampal structure and cortisol, providing a promising approach to improve health. The data contribute to the literature on plasticity of hippocampal subfields during adulthood, the impact of mental training interventions on the brain, and the link between CA1-3 and both short- and long-term stress changes.

      The authors thoughtfully approached the study of hippocampal subfields, utilizing a method designed for T1w images that outperformed Freesurfer 5.3 and that produced comparable results to an earlier version of ASHS. The authors note the limitations of their approaches and provide detailed information on the data used and analyses conducted. The results provide a strong basis from which future studies can expand using computational approaches or more fine-grained investigations of the impact of mindfulness training on cortisol levels and the hippocampus.

    1. Reviewer #1 (Public Review):

      The manuscript considers a hierarchical network of neurons, of the type that can be found in sensory cortex, and assumes that they aim to constantly predict sensory inputs that may change in time. The paper describes the dynamics of neurons and rules of synaptic plasticity that minimize the integral of prediction errors over time.

      The manuscript describes and analyses the model in great detail, and presents multiple and diverse simulations illustrating the model's functioning. However, the manuscript could be made more accessible and easier to read. The paper may help to understand the organization of cortical neurons, their properties, as well as the function of its particular components (such as apical dendrites).

    2. Reviewer #2 (Public Review):

      Neuroscientists often state that we have no theory of the brain. The example of theoretical physics is often cited, where numerous and quite complex phenomena are explained by a compact mathematical description. Lagrangian and Hamiltonian pictures provide such powerful 'single equation'. These frameworks are referred to as 'energy', an elegant way to turn numerous differential equations into a single compact relationship between observable quantities (state variables like position and speed) and scaling constants (like the gravity constant or the Planck constant). Such energy pictures have been used in theoretical neuroscience since the 1980s.

      The manuscript "neuronal least-action principle for real-time learning in cortical circuits" by Walter Senn and collaborators describes a theoretical framework to link predictive coding, error-based learning, and neuronal dynamics. The central concept is that an energy function combining self-supervised and supervised objectives is optimized by realistic neuronal dynamics and learning rules when considering the state of a neuron as a mixture of the current membrane potential and its rate of change. As compared with previous energy functions in theoretical neuroscience, this theory captures a more extensive range of observations while satisfying normative constraints. Particularly, no theory had to my knowledge related adaptive dynamics widely observed in the brain (referred to as prospective coding in the text, but is sometimes referred to as adaptive coding or redundancy reduction) with the dynamics of learning rules.

      The manuscript first exposes the theory of two previously published papers by the same group on somato-dendritic error with apical and basal dendrites. These dynamics are then related to an energy function, whose optimum recovers the dynamics. The rest of the manuscript illustrates how features of this model fits either normative or observational constraints. Learning follows a combination of self-supervised learning (learning to predict the next step) and supervised learning (learning to predict an external signal). The credit assignment problem is solved by an apical-compartment projecting set of interneurons with learning rules whose role is to align many weight matrices to avoid having to do multiplexing. An extensive method section and supplementary material expand on mathematical proofs and make more explicit the mathematical relationship between different frameworks.

      Experts would say that much of the article agglomerates previous theoretical papers by the same authors that have been published recently either in archival servers or in conference proceedings. A number of adaptations to previous theoretical results were necessary, so the present article is not easily reduced to a compendium of previous pre-prints. However, the manuscript is by no means easy to read. Also, there remain a few thorny assumptions (unobserved details of the learning rules or soma-dendrites interactions), but the theory is likely going to be regarded as an important step towards a comprehensive theory of the brain.

    1. Reviewer #1 (Public Review):

      In this manuscript, Nagel et al. sought to characterize the composition of urinary compounds, some of which are putative chemosignals. They used urines from adult males and females in three different strains, including one wild-derived strain. By performing mass spectrometry of two classes of compounds: volatile organic compounds and proteins, they found that urines from inbred strains are qualitatively similar to those of a wild strain. This finding is significant because there is a high degree of diversity in different inbred strains and wild mice, with respect to the polymorphisms of chemosensory receptor genes and expression of vomeronasal ligands previously identified. Notably, their study did not characterize steroids, which represent a major class of urinary chemosignals activating vomeronasal neurons. Therefore, important future studies should address the strain dependence of steroid composition in urines.

      In the second part of this work, the authors used calcium imaging to monitor the pattern of vomeronasal neuron responses to these urines. By performing pairwise comparisons, the authors found a large degree of strain-specific response and a relatively minor response to sex-specific urinary stimuli. This is a finding generally in agreement with previous calcium imaging work by Ron Yu and colleagues in 2008. The authors extend the previous work by using urines from wild mice. They further report that the concentration diversity of urinary compounds in different urine batches is largely uncorrelated with the activity profiles of these urines. In addition, the authors found that the patterns of vomeronasal neuron response to urinary cues are not identical when measured using different recipient strains.

      The pitfalls of this study are the omission of steroids for the mass spectrometry experiments and the indirect (correlational) nature of their mass spectrometry data and activity data. Whether the urinary compounds identified in this study activate vomeronasal neurons were not tested.

      Nevertheless, the major contribution of this work is the identification of specific molecules in mouse urines. This work is likely to be of significant interest to researchers in chemosensory signaling in mammals and could provide a systematic avenue to exhaustively identify additional pheromones in mice.

    2. Reviewer #2 (Public Review):

      This manuscript by Nagel et al provides a comprehensive examination of the chemical composition of mouse urine (an important source of semiochemicals) across strain and sex, and correlates these differences with functional responses of vomeronasal sensory neurons (an important sensory population for detecting chemical social cues). The strength of the work lies in the careful and comprehensive imaging and chemical analyses, the rigor of quantification of functional responses, and the insight into the relevance of olfactory work on lab-derived vs wild-derived mice.

      With regards to the chemical analysis, the reader should keep in mind (and the authors acknowledge) that a difference in the concentration of a chemical across strain or sex does not necessarily mean that that chemical is used for chemical communication. In the most extreme case, the animals may be completely insensitive to the chemical. Thus, the fact that the repertoire of proteins and volatiles could potentially allow sex and/or strain discrimination, it is unclear to what degree both are used in different situations.

    3. Reviewer #3 (Public Review):

      Summary:

      The manuscript by Nagel, et al. describes studies of mouse vomeronasal sensory neuron (VSN) tuning to mouse urine samples across different sexes and strains, including wild mice, alongside mass spectrometry analysis of the same samples. The authors performed live Ca2+ imaging (CAL520 dye) of VSNs in acute vomeronasal organ (VNO) slices to determine how VSNs are tuned to pairs of stimuli that differ in their origin (e.g. male C57BL/6 versus male BALB/c urine, male C57BL/6 versus female C57BL/6, etc.). For each pair of tested odorants, the results measure the proportion of VSNs that respond to both stimuli ("generalists") or just one of the two ("specialists"), as well as metrics of tuning preference and response reliability. The authors find in most cases that generalists make up a larger proportion of responsive VSNs than specialists, but several pairwise comparisons showed a high degree of strain selectivity. Notably, the authors evaluated VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding strain-dependent differences in the representation of mouse urine. Alongside these measurements of VSN tuning, the authors report results of mass spectrometry analyses of volatiles and proteins in the same urine samples. These analyses indicated a number of molecules in each category that vary across sex and strain, and therefore represent candidate vomeronasal ligands. However, this study did not directly test whether any of these candidate molecules drives VSN activity. Overall, this work provides solid information related to mouse vomeronasal chemosensation.

      Strengths:

      A strength of the current study is its focus on characterizing the neural responses of the VNO to urine derived from wild mice. The majority of existing vomeronasal system research has relied on the use of inbred strains for both neural response recordings and investigations of candidate vomeronasal system ligands. Inbreeding in laboratory environments may alter the chemical composition of bodily secretions, thereby potentially changing the information they contain. Moreover, the more homogeneous nature of inbred strains could be critical when studying the AOS mediated social aspects. If there exist noticeable differences in the chemical composition of secretions from wild animals compared to inbred strains, this would suggest that future research must consider natural sources of candidate ligands outside of inbred strains. This work identifies some intriguing differences, worthy of further exploration, between the urine composition of wild mice versus inbred mice, as well as disparities in how the VNO responds to urine from these different sources. However, the molecular composition and VNO responsiveness to wild mouse urine was found to be highly overlapping with inbred mouse urine, supporting the continued investigation of candidate ligands found in inbred mouse urine.

      Another positive aspect of this work is its use of the same set of stimuli as a previous study by the same authors (Bansal et al., 2021) in the downstream accessory olfactory bulb. The consistency in stimulus selection facilitates a comparison of information processing of sex and strain information from the sensory periphery to the brain. Although comparisons between the two connected regions are not a focus of this work, and methodological differences (e.g., Ca2+ imaging versus electrophysiology) may introduce caveats into comparisons, the support of "apples to apples" comparisons across connected circuits is critical to progress in the field.

      Finally, this study directly measured VSN tuning in both male C57BL/6 and male BALB/c VNOs, finding subtle but important differences in the representation of mouse urine in these two recipient strains. Given that there is a long history of behavioral research into strain-specific differences in social behavior, this research paves the way for future studies into how different mouse strains detect and process social chemosignals.

      Weaknesses:

      One of the primary objectives in this study is to ascertain the extent to which the response profiles of VSNs are specific to sex and strain. The design of these Ca2+ imaging experiments uses a simple stimulus design, using two interleaved bouts of stimulation with pairs of urine (e.g., male versus female C57BL/6, male C57BL/6 versus male BALB/c) at a single dilution factor (1:100). This introduces two significant limitations: (1) the "generalist" versus "specialist" descriptors pertain only to the specific pairwise comparisons made and (2) there is no information about the sensitivity/concentration-dependence of the responses.

      The functional measurements of VSN tuning to various pairs of urine stimuli are presented alongside mass spectrometry-based comparisons. However, the mass spectrometry-based analysis was performed separately from VSN tuning experiments/analysis. The juxtaposition of these measurements may give some readers the impression that VSN tuning measurements were integrated with molecular profiling (i.e., that the molecular diversity was causally related physiological responses). This is a hypothesis raised by the parallel studies, but not a supported conclusion of the current work.

      The impact of mass spectrometry findings is acknowledged to be limited to nonvolatile organic compounds and proteins/peptides, and that it is possible that few of these candidate molecules are active in the VNO. Moreover, it remains possible that the VSN responses are driven mostly by small nonvolatiles (e.g., polar steroids), a class of strong VSN ligands that were excluded from molecular analysis.

    1. Reviewer #1 (Public Review):

      Summary:

      The aim of the study described in this paper was to test whether visual stimuli that pulse synchronously with the systole phase of the cardiac cycle are suppressed compared with stimuli that pulse in the diastole phase. To this end, the authors employed a binocular rivalry task and used the duration of the perceived image as the metric of interest. The authors predicted that if there was global suppression of the visual stimulus during systole then the durations of the stimulus that were pulsing synchronously with systole should be of shorter duration than those pulsing in diastole. However, the results observed were the opposite of those predicted. The authors speculate on what this facilitation effect might mean for the baroreceptor suppression hypothesis.

      Strengths:

      This is an interesting and timely study that uses a clever paradigm to test the baroreceptor suppression hypothesis in vision. This is a refreshingly focussed paper with interesting and seemingly counterintuitive results.

      Weaknesses:

      The paper could benefit from a clearer explanation of the predicted results. For those not experts in binocular rivalry, it would be useful to explain the predicted results. Does pulsing stimuli in this way change durations in such a task? If there is global suppression of visual stimuli why would this lead to shorter/longer durations in the systole compared to the diastole conditions? In addition, the duration lengths in both conditions seem to be longer than one cardiac cycle. If the cardiac cycle modulates duration it would be interesting to discuss why this occurs on some cycles but not on others. If there is a facilitation effect why does it only occur on some cycles?

    2. Reviewer #2 (Public Review):

      Summary:

      This is a binocular rivalry study that uses electrocardiogram events to modulate visual stimuli in real-time, relative to participants' heartbeats. The main finding is that modulations during the period around when the heart has contracted (systole) increase rivalry dominance durations. This is a really neat result, that demonstrates the link between interoception and vision. I thought the Bayesian mixture modelling was a really smart way to identify cardiac non-perceivers, and the finding that the main result is preserved in this group is compelling. Overall, the study has been conducted to a high standard, is appropriately powered, and reported clearly. I have one suggestion about interpretation, which concerns the explanation of increased dominance durations with reference to contemporary models of binocular rivalry, and a few minor queries. However, I think this paper is a worthwhile addition to the literature.

    3. Reviewer #3 (Public Review):

      Summary:

      The manuscript addresses a question inspired by the Baroceptor Hypothesis and its links to visual awareness and interoception. Specifically, the reported study aimed to determine if the effects of cardiac contraction (systole) on binocular rivalry (BR) are facilitatory or suppressive. The main experiment - relying on a technically challenging procedure of presenting stimuli synchronised with the heartbeats of participants - has been conducted with great care, and numerous manipulation checks the authors report convincingly show that the methods they used work as intended. Moreover, the control experiment allows for excluding alternative explanations related to participants being aware of their heartbeats. Therefore, the study convincingly shows the effect of cardiac activity on BR - and this is an important finding. The results, however, do not allow for unambiguously determining if this effect is facilitatory or suppressive (see details below), which renders the study not as informative as it could be.

      While the authors strongly focus on interoception and awareness, this study will be of interest to researchers studying BR as such. Moreover, the code and the data the authors share can facilitate the adoption of their methods in other labs.

      Strengths:

      (1) The study required a complex technical setup and the manuscript both describes it well and demonstrates that it was free from potential technical issues (e.g. in section 3.3. Manipulation check).

      (2) The sophisticated statistical methods the authors used, at least for a non-statistician like me, appear to be well-suited for their purpose. For example, they take into account the characteristics of BR (gamma distributions of dominance durations). Moreover, the authors demonstrate that at least in one case their approach is more conservative than a more basic one (Binomial test) would be.

      (3) Finally, the control experiment, and the analysis it enabled, allow for excluding a multitude of alternative explanations of the main results.

      (4) The authors share all their data and materials, even the code for the experiment.

      (5) The manuscript is well-written. In particular, it introduces the problem and methods in a way that should be easy to understand for readers coming from different research fields.

      Weaknesses:

      (1) The interpretation of the main result in the context of the Baroceptor hypothesis is not clear. The manuscript states: The Baroreceptor Hypothesis would predict that the stimulus entrained to systole would spend more time suppressed and, conversely, less time dominant, as cortical activity would be suppressed each time that stimulus pulses. The manuscript does not specify why this should be the case, and the term 'entrained' is not too helpful here (does it refer to neural entrainment? or to 'being in phase with'?). The answer to this question is provided by the manuscript only implicitly, and, to explain my concern, I try to spell it out here in a slightly simplified form.

      During systole (cardiac contraction), the visual system is less sensitive to external information, so it 'ignores' periods when the systole-synchronised stimulus is at the peak of its pulse. Conversely, the system is more sensitive during diastole, so the stimulus that is at the peak of its pulse then should dominate for longer, because its peaks are synchronised with the periods of the highest sensitivity of the visual system when the information used to resolve the rivalry is sampled from the environment. This idea, while indeed being a clever test of the hypothesis in question, rests on one critical assumption: that the peak of the stimulus pulse (as defined in the manuscript) is the time when the stimulus is the strongest for the visual system. The notion of 'stimulus strength' is widely used in the BR literature (see Brascamp et al., 2015 for a review). It refers to the stimulus property that, simply speaking, determines its tendency to dominate in the BR. The strength of a stimulus is underpinned by its low-level visual properties, such as contrast and spatial frequency content. Coming back to the manuscript, the pulsing of the stimuli affected at least spatial frequency (and likely other low-level properties), and it is unknown if it was in phase with the pulsing of the stimulus strength, or not. If my understanding of the premise of the study is correct, the conclusions drawn by the authors stand only if it was.

      In other words, most likely the strength of one of the stimuli was pulsating in sync with the systole, but is it not clear which stimulus it was. It is possible that, for the visual system, the stimulus meant to pulse in sync with the systole was pulsing strength-wise in phase with the diastole (and the one intended to pulse with in sync with the diastole strength-wise pulsed with the systole). If this is the case, the predictions of the Baroceptor Hypothesis hold, which would change the conclusion of the manuscript.

      (2) Using anaglyph goggles necessitates presenting stimuli of a different colour to each eye. The way in which different colours are presented can impact stimulus strength (e.g. consider that different anaglyph foils can attenuate the light they let through to different degrees). To deal with such effects, at least some studies on BR employed procedures of adjusting the colours for each participant individually (see Papathomas et al., 2004; Patel et al., 2015 and works cited there). While I think that counterbalancing applied in the study excludes the possibility that colour-related effects influenced the results, the effects of interest still could be stronger for one of the coloured foils.

      (3) Several aspects of the methods (e.g. the stimuli), are not described at the level of detail some readers might be accustomed to. The most important issue here is the task the participants performed. The manuscript says that they pressed a button whenever they experienced a switch in perception, but it is only implied that there were different buttons for each stimulus.

      Brascamp, J. W., Klink, P. C., & Levelt, W. J. M. (2015). The 'laws' of binocular rivalry: 50 years of Levelt's propositions. Vision Research, 109, 20-37. https://doi.org/10.1016/j.visres.2015.02.019<br /> Papathomas, T. V., Kovács, I., & Conway, T. (2004). Interocular grouping in binocular rivalry: Basic attributes and combinations. In D. Alais & R. Blake (Eds.), Binocular Rivalry (pp. 155-168). MIT Press<br /> Patel, V., Stuit, S., & Blake, R. (2015). Individual differences in the temporal dynamics of binocular rivalry and stimulus rivalry. Psychonomic Bulletin and Review, 22(2), 476-482. https://doi.org/10.3758/s13423-014-0695-1

    1. Reviewer #1 (Public Review):

      Summary:

      Pham and colleagues provide an illuminating investigation of aquaporin-4 water flux in the brain utilizing ex vivo and in vivo techniques. The authors first show in acute brain slices, and in vivo with fiber photometry, SRB-loaded astrocytes swell after inhibition of AQP4 with TGN-020, indicative of tonic water efflux from astrocytes in physiological conditions. Excitingly, they find that TGN-020 increases the ADC in DW-MRI in a region-specific manner, potentially due to AQP4 density. The resolution of the DW-MRI cannot distinguish between intracellular or extracellular compartments, but the data point to an overall accumulation of water in the brain with AQP4 inhibition. These results provide further clarity on water movement through AQP4 in health and disease.

      Overall, the data support the main conclusions of the article, with some room for more detailed treatment of the data to extend the findings.

      Strengths:

      The authors have a thorough investigation of AQP4 inhibition in acute brain slices. The demonstration of tonic water efflux through AQP4 at baseline is novel and important in and of itself. Their further testing of TGN-020 in hyper- and hypo-osmotic solutions shows the expected reduction of swelling/shrinking with AQP4 blockade.

      Their experiment with cortical spreading depression further highlights the importance of water efflux from astrocytes via AQP4 and transient water fluxes as a result of osmotic gradients. Inhibition of AQP4 increases the speed of tissue swelling, pointing to a role in the efflux of water from the brain.

      The use of DW-MRI provides a non-invasive measure of water flux after TGN-020 treatment.

      Weaknesses:

      The authors specifically use GCaMP6 and light sheet microscopy to image their brain sections in order to identify astrocytic microdomains. However, their presentation of the data neglects a more detailed treatment of the calcium signaling. It would be quite interesting to see whether these calcium events are differentially affected by AQP4 inhibition based on their cellular localization (ie. processes vs. soma vs. vascular end feet which all have different AQP4 expressions).

      The authors show the inhibition of AQP4 with TGN-020 shortens the onset time of the swelling associated with cortical spreading depression in brain slices. However, they do not show quantification for many of the other features of CSD swelling, (ie. the duration of swelling, speed of swelling, recovery from swelling).

      Significance:

      AQP4 is a bidirectional water channel that is constitutively open, thus water flux through it is always regulated by local osmotic gradients. Still, characterizing this water flux has been challenging, as the AQP4 channel is incredibly water-selective. The authors here present important data showing that the application of TGN-020 alone causes astrocytic swelling, indicating that there is constant efflux of water from astrocytes via AQP4 in basal conditions. This has been suggested before, as the authors rightfully highlight in their discussion, but the evidence had previously come from electron microscopy data from genetic knockout mice.

      AQP4 expression has been linked with the glymphatic circulation of cerebrospinal fluid through perivascular spaces since its rediscovery in 2012 [1]. Further studies of aging[2], genetic models[3], and physiological circadian variation[4] have revealed it is not simply AQP4 expression but AQP4 polarization to astrocytic vascular endfeet that is imperative for facilitating glymphatic flow. Still, a lingering question in the field is how AQP4 facilitates fluid circulation. This study represents an important step in our understanding of AQP4's function, as the basal efflux of water via AQP4 might promote clearance of interstitial fluid to allow an influx of cerebrospinal fluid into the brain. Beyond glymphatic fluid circulation, clearly, AQP4-dependent volume changes will differentially alter astrocytic calcium signaling and, in turn, neuronal activity.

      (1) Iliff, J.J., et al., A Paravascular Pathway Facilitates CSF Flow Through the Brain Parenchyma and the Clearance of Interstitial Solutes, Including Amyloid β. Sci Transl Med, 2012. 4(147): p. 147ra111.<br /> (2) Kress, B.T., et al., Impairment of paravascular clearance pathways in the aging brain. Ann Neurol, 2014. 76(6): p. 845-61.<br /> (3) Mestre, H., et al., Aquaporin-4-dependent Glymphatic Solute Transport in the Rodent Brain. eLife, 2018. 7.<br /> (4) Hablitz, L., et al., Circadian control of brain glymphatic and lymphatic fluid flow. Nature Communications, 2020. 11(1).

    2. Reviewer #2 (Public Review):

      Summary:

      The paper investigates the role of astrocyte-specific aquaporin-4 (AQP4) water channel in mediating water transport within the mouse brain and the impact of the channel on astrocyte and neuron signaling. Throughout various experiments including epifluorescence and light sheet microscopy in mouse brain slices, and fiber photometry or diffusion-weighted MRI in vivo, the researchers observe that acute inhibition of AQP4 leads to intracellular water accumulation and swelling in astrocytes. This swelling alters astrocyte calcium signaling and affects neighboring neuron populations. Furthermore, the study demonstrates that AQP4 regulates astrocyte volume, influencing mainly the dynamics of water efflux in response to osmotic challenges or associated with cortical spreading depolarization. The findings suggest that AQP4-mediated water efflux plays a crucial role in maintaining brain homeostasis, and indicates the main role of AQP4 in this mechanism. However authors highlight that the report sheds light on the mechanisms by which astrocyte aquaporin contributes to the water environment in the brain parenchyma, the mechanism underlying these effects remains unclear and not investigated. The manuscript requires revision.

      Strengths:

      The paper elucidates the role of the astrocytic aquaporin-4 (AQP4) channel in brain water transport, its impact on water homeostasis, and signaling in the brain parenchyma. In its idea, the paper follows a set of complimentary experiments combining various ex vivo and in vivo techniques from microscopy to magnetic resonance imaging. The research is valuable, confirms previous findings, and provides novel insights into the effect of acute blockage of the AQP4 channel using TGN-020.

      Weaknesses:

      Despite the employed interdisciplinary approach, the quality of the manuscript provides doubts regarding the significance of the findings and hinders the novelty claimed by the authors. The paper lacks a comprehensive exploration or mention of the underlying molecular mechanisms driving the observed effects of astrocytic aquaporin-4 (AQP4) channel inhibition on brain water transport and brain signaling dynamics. The scientific background is not very well prepared in the introduction and discussion sections. The important or latest reports from the field are missing or incompletely cited and missconcluded. There are several citations to original works missing, which would clarify certain conclusions. This especially refers to the basis of the glymphatic system concept and recently published reports of similar content. The usage of TGN-020, instead of i.e. available AER-270(271) AQP4 blocker, is not explained. While employing various experimental techniques adds depth to the findings, some reasoning behind the employed techniques - especially regarding MRI - is not clear or seemingly inaccurate. Most of the time the number of subjects examined is lacking or mentioned only roughly within the figure captions, and there are lacking or wrongly applied statistical tests, that limit assessment and reproducibility of the results. In some cases, it seems that two different statistical tests were used for the same or linked type of data, so the results are contradictory even though appear as not likely - based on the figures. Addressing these limitations could strengthen the paper's impact and utility within the field of neuroscience, however, it also seems that supplementary experiments are required to improve the report.

    3. Reviewer #3 (Public Review):

      Summary:

      In this manuscript, the authors propose that astrocytic water channel AQP4 represents the dominant pathway for tonic water efflux without which astrocytes undergo cell swelling. The authors measure changes in astrocytic sulforhodamine fluorescence as the proxy for cell volume dynamics. Using this approach, they perform a technically elegant series of ex vivo and in vivo experiments exploring changes in astrocytic volume in response to AQP4 inhibitor TGN-020 and/or neuronal stimulation. The key finding is that TGN-020 produces an apparent swelling of astrocytes and modifies astrocytic cell volume regulation after spreading depolarizations. Additionally, systemic application of TGN-020 produced changes in diffusion-weighted MRI signal, which the authors interpret as cellular swelling. This study is perceived as potentially significant. However, several technical caveats should be strongly considered and perhaps addressed through additional experiments.

      Strengths:

      (1) This is a technically elegant study, in which the authors employed a number of complementary ex vivo and in vivo techniques to explore functional outcomes of aquaporin inhibition. The presented data are potentially highly significant (but see below for caveats and questions related to data interpretation).

      (2) The authors go beyond measuring cell volume homeostasis and probe for the functional significance of AQP4 inhibition by monitoring Ca2+ signaling in neurons and astrocytes (GCaMP6 assay).

      (3) Spreading depolarizations represent a physiologically relevant model of cellular swelling. The authors use ChR2 optogenetics to trigger spreading depolarizations. This is a highly appropriate and much-appreciated approach.

      Weaknesses:

      (1) The main weakness of this study is that all major conclusions are based on the use of one pharmacological compound. In the opinion of this reviewer, the effects of TGN-020 are not consistent with the current knowledge on water permeability in astrocytes and the relative contribution of AQP4 to this process.

      Specifically: Genetic deletion of AQP4 in astrocytes reduces plasmalemmal water permeability by ~two-three-fold (when measured a 37oC, Solenov et al., AJP-Cell, 2004). This is a significant difference, but it is thought to have limited/no impact on water distribution. Astrocytic volume and the degree of anisosmotic swelling/shrinkage are unchanged because the water permeability of the AQP4-null astrocytes remains high. This has been discussed at length in many publications (e.g., MacAulay et al., Neuroscience, 2004; MacAulay, Nat Rev Neurosci, 2021) and is acknowledged by Solenov and Verkman (2004).

      Keeping this limitation in mind, it is important to validate astrocytic cell volume changes using an independent method of cell volume reconstruction (diameter of sulforhodamine-labeled cell bodies? 3D reconstruction of EGFP-tagged cells? Else?)

      (2) TGN-020 produces many effects on the brain, with some but not all of the observed phenomena sensitive to the genetic deletion of AQP4. In the context of this work, it is important to note that TGN-020 does not completely inhibit AQP4 (70% maximal inhibition in the original oocyte study by Huber et al., Bioorg Med Chem, 2009). Thus, besides not knowing TGN-020 levels inside the brain, even "maximal" AQP4 inhibition would not be expected to dramatically affect water permeability in astrocytes.

      This caveat may be addressed through experiments using local delivery of structurally unrelated AQP4 blockers, or, preferably, AQP4 KO mice.

      (3) This reviewer thinks that the ADC signal changes in Figure 5 may be unrelated to cellular swelling. Instead, they may be a result of the previously reported TGN-020-induced hyphemia (e.g., H. Igarashi et al., NeuroReport, 2013) and/or changes in water fluxes across pia matter which is highly enriched in AQP4. To amplify this concern, AQP4 KO brains have increased water mobility due to enlarged interstitial spaces, rather than swollen astrocytes (RS Gomolka, eLife, 2023). Overall, the caveats of interpreting DW-MRI signal deserve strong consideration.

    1. Reviewer #1 (Public Review):

      Yun et al. examined the molecular and neuronal underpinnings of changes in Drosophila female reproductive behaviors in response to social cues. Specifically, the authors measure the ejaculate-holding period, which is the amount of time females retain male ejaculate after mating (typically 90 min in flies). They find that female fruit flies, Drosophila melanogaster, display shorter holding periods in the presence of a native male or male-associated cues, including 2-Methyltetracosane (2MC) and 7-Tricosene (7-T). They further show that 2MC functions through Or47b olfactory receptor neurons (ORNs) and the Or47b channel, while 7-T functions through ppk23 expressing neurons. Interestingly, their data also indicates that two other olfactory ligands for Or47b (methyl laurate and palmitoleic acid) do not have the same effects on the ejaculate-holding period. By performing a series of behavioral and imaging experiments, the authors reveal that an increase in cAMP activity in pC1 neurons is required for this shortening of the ejaculate-holding period and may be involved in the likelihood of remating. This work lays the foundation for future studies on sexual plasticity in female Drosophila.

      The conclusions of this paper are mostly supported by the data, but aspects of the lines used for individual pC1 subtypes and visual contributions as well as the statistical analysis need to be clarified.

      (1) The pC1 subtypes (a - e) are delineated based on their morphology and connectivity. While the morphology of these neurons is distinct, they do share a resemblance that can be difficult to discern depending on the imaging performed. Additionally, genetic lines attempting to label individual neurons can easily be contaminated by low-level expression in off-target neurons in the brain or ventral nerve cord (VNC), which could contribute to behavioral changes following optogenetic manipulations. In Figures 5C - D, the authors generated and used new lines for labeling pC1a and pC1b+c. The line for pC1b+c was imaged as part of another recent study (https://doi.org/10.1073/pnas.2310841121). However, similar additional images of the pC1a line (i.e. 40x magnification and VNC expression) would be helpful in order to validate its specificity.

      (2) The author's experiments examining olfactory and gustatory contributions to the holding period were well controlled and described. However, the experiments in Figure 1D examining visual contributions were not sufficiently convincing as the line used (w1118) has previously been shown to be visually impaired (Wehner et al., 1969; Kalmus 1948). Using another wild-type line would have improved the authors' claims.

      (3) When comparisons between more than 2 groups are shown as in Figures 1E, 3D, and 5E, the comparisons being made were not clear. Adding in the results of a nonparametric multiple comparisons test would help for the interpretation of these results.

    2. Reviewer #2 (Public Review):

      The work by Yun et al. explores an important question related to post-copulatory sexual selection and sperm competition: Can females actively influence the outcome of insemination by a particular male by modulating the storage and ejection of transferred sperm in response to contextual sensory stimuli? The present work is exemplary for how the Drosophila model can give detailed insight into the basic mechanism of sexual plasticity, addressing the underlying neuronal circuits on a genetic, molecular, and cellular level.

      Using the Drosophila model, the authors show that the presence of other males or mated females after mating shortens the ejaculate-holding period (EHP) of a female, i.e. the time she takes until she ejects the mating plug and unstored sperm. Through a series of thorough and systematic experiments involving the manipulation of olfactory and chemo-gustatory neurons and genes in combination with exposure to defined pheromones, they uncover two pheromones and their sensory cells for this behavior. Exposure to the male-specific pheromone 2MC shortens EHP via female Or47b olfactory neurons, and the contact pheromone 7-T, present in males and on mated females, does so via ppk23 expressing gustatory foreleg neurons. Both compounds increase cAMP levels in a specific subset of central brain receptivity circuit neurons, the pC1b,c neurons. By employing an optogenetically controlled adenyl cyclase, the authors show that increased cAMP levels in pC1b and c neurons increase their excitability upon male pheromone exposure, decrease female EHP, and increase the remating rate. This provides convincing evidence for the role of pC1b,c neurons in integrating information about the social environment and mediating not only virgin but also mated female post-copulatory mate choice.

      Understanding context and state-dependent sexual behavior is of fundamental interest. Mate behavior is highly context-dependent. In animals subjected to sperm competition, the complexities of optimal mate choice have attracted a long history of sophisticated modelling in the framework of game theory. These models are in stark contrast to how little we understand so far about the biological and neurophysiological mechanisms of how females implement post-copulatory or so-called "cryptic" mate choice and bias sperm usage when mating multiple times.

      The strength of the paper is decrypting "cryptic" mate choice, i.e. the clear identification of physiological mechanisms and proximal causes for female post-copulatory mate choice. The discovery of peripheral chemosensory nodes and neurophysiological mechanisms in central circuit nodes will provide a fruitful starting point to fully map the circuits for female receptivity and mate choice during the whole gamut of female life history.

    1. Reviewer #1 (Public Review):

      Summary:

      Olfactory sensory neurons (OSNs) in the olfactory epithelium detect myriads of environmental odors that signal essential cues for survival. OSNs are born throughout life and thus represent one of the few neurons that undergo life-long neurogenesis. Until recently, it was assumed that OSN neurogenesis is strictly stochastic with respect to subtype (i.e. the receptor the OSN chooses to express).

      However, a recent study showed that olfactory deprivation via naris occlusion selectively reduced birthrates of only a fraction of OSN subtypes and indicated that these subtypes appear to have a special capacity to undergo changes in birthrates in accordance with the level of olfactory stimulation. These previous findings raised the interesting question of what type of stimulation influences neurogenesis, since naris occlusion does not only reduce the exposure to potentially thousands of odors but also to more generalized mechanical stimuli via preventing airflow.

      In this study, the authors set out to identify the stimuli that are required to promote the neurogenesis of specific OSN subtypes. Specifically, they aim to test the hypothesis that discrete odorants selectively stimulate the same OSN subtypes whose birthrates are affected. This would imply a highly specific mechanism in which exposure to certain odors can "amplify" OSN subtypes responsive to those odors suggesting that OE neurogenesis serves, in part, an adaptive function.

      To address this question, the authors focused on a family of OSN subtypes that had previously been identified to respond to musk-related odors and that exhibit higher transcript levels in the olfactory epithelium of mice exposed to males compared to mice isolated from males. First, the authors confirm via a previously established cell birth dating assay in unilateral naris occluded mice that this increase in transcript levels actually reflects a stimulus-dependent birthrate acceleration of this OSN subtype family. In a series of experiments using the same assay, they show that one specific subtype of this OSN family exhibits increased birthrates in response to juvenile male exposure while a different subtype shows increased birthrates to adult mouse exposure. In the core experiment of the study, they finally exposed naris occluded mice to a discrete odor (muscone) to test if this odor specifically accelerates the birth rates of OSN types that are responsive to this odor. This experiment reveals a complex relationship between birth rate acceleration and odor concentrations showing that some muscone concentrations affect birth rates of some members of this family and do not affect two unrelated OSN subtypes.

      Strengths:

      The scientific question is valid and opens an interesting direction. The previously established cell birth dating assay in naris occluded mice is well performed and accompanied by several control experiments addressing potential other interpretations of the data.

      Weaknesses:

      (1) The main research question of this study was to test if discrete odors specifically accelerate the birth rate of OSN subtypes they stimulate, i.e. does muscone only accelerate the birth rate of OSNs that express muscone-responsive ORs, or vice versa is the birthrate of muscone-responsive OSNs only accelerated by odors they respond to?

      This question is only addressed in Figure 5 of the manuscript and the results only partially support the above claim. The authors test one specific odor (muscone) and find that this odor (only at certain concentrations) accelerates the birth rate of some musk-responsive OSN subtypes, but not two other unrelated control OSN subtypes. This does not at all show that musk-responsive OSN subtypes are only affected by odors that stimulate them and that muscone only affects the birthrate of musk-responsive OSNs, since first, only the odor muscone was tested and second, only two other OSN subtypes were tested as controls, that, importantly, are shown to be generally stimulus-independent OSN subtypes (see Figure 2 and S2).

      As a minimum the authors should have a) tested if additional odors that do not activate the three musk-responsive subtypes affect their birthrate b) choose 2-3 additional control subtypes that are known to be stimulus-dependent (from their own 2020 study) and test if muscone affects their birthrates.

      (2) The finding that Olfr1440 expressing OSNs do not show any increase in UNO effect size under any muscone concentration (Figure 5D, no significance in line graph for UNO effect sizes, middle) seems to contradict the main claim of this study that certain odors specifically increase birthrates of OSN subtypes they stimulate. It was shown in several studies that olfr1440 is seemingly the most sensitive OR for muscone, yet, in this study, muscone does not further increase birthrates of OSNs expressing olfr1440. The effect size on birthrate under muscone exposure is the same as without muscone exposure (0%).

      In contrast, the supposedly second most sensitive muscone-responsive OR olfr235 shows a significant increase in UNO effect size between no muscone exposure (0%) and 0.1% as well as 1% muscone.

      (3) The authors introduce their choice to study this particular family of OSN subtypes with first, the previous finding that transcripts for one of these musk-responsive subtypes (olfr235) are downregulated in mice that are deprived of male odors. Second, musk-related odors are found in the urine of different species. This gives the misleading impression that it is known that musk-related odors are indeed excreted into male mouse urine at certain concentrations. This should be stated more clearly in the introduction (or cited, if indeed data exist that show musk-related odors in male mouse urine) because this would be a very important point from an ethological and mechanistic point of view.

      In addition, this would also be important information to assess if the chosen muscone concentrations fall at all into the natural range.

      Related: If these are male-specific cues, it is interesting that changes in OR transcripts (Figure 1) can already be seen at the age of P28 where other male-specific cues are just starting to get expressed. This should be discussed.

      (4) Figure 5: Under muscone exposure the number of newborn neurons on the closed sides fluctuates considerably. This doesn't seem to be the case in other experiments and raises some concerns about how reliable the naris occlusion works for strong exposure to monomolecular odors or what other potential mechanisms are at play.

      (5) In contrast to all other musk-responsive OSN types, the number of newborn OSNs expressing olfr1437 increases on the closed side of the OE relative to the open in UNO-treated male mice (Figure 1). This seems to contradict the presented theory and also does not align with the bulk RNAseq data (Figure S1).

      (6) The authors hypothesize in relation to the accelerated birthrate of musk-responsive OSN subtypes that "the acceleration of the birthrates of specific OSN subtypes could selectively enhance sensitivity to odors detected by those subtypes by increasing their representation within the OE". However, for two other OSN subtypes that detect male-specific odors, they hypothesize the opposite "By contrast, Olfr912 (Or8b48) and Olfr1295 (Or4k45), which detect the male-specific non-musk odors 2-sec-butyl-4,5-dihydrothiazole (SBT) and (methylthio)methanethiol (MTMT), respectively, exhibited lower representation and/or transcript levels in mice exposed to male odors, possibly reflecting reduced survival due to overstimulation."

      Without any further explanation, it is hard to comprehend why exposure to male-derived odors should, on one hand, accelerate birthrates in some OSN subtypes to potentially increase sensitivity to male odors, but on the other hand, lower transcript levels and does not accelerate birth rates of other OSN subtypes due to overstimulation.

    2. Reviewer #2 (Public Review):

      In their paper entitled "In mice, discrete odors can selectively promote the neurogenesis of sensory neuron subtypes that they stimulate" Hossain et al. address lifelong neurogenesis in the mouse main olfactory epithelium. The authors hypothesize that specific odorants act as neurogenic stimuli that selectively promote biased OR gene choice (and thus olfactory sensory neuron (OSN) identity). Hossain et al. employ RNA-seq and scRNA-seq analyses for subtype-specific OSN birthdating. The authors find that exposure to male and musk odors accelerates the birthrates of the respective responsive OSNs. Therefore, Hossain et al. suggest that odor experience promotes selective neurogenesis and, accordingly, OSN neurogenesis may act as a mechanism for long-term olfactory adaptation.

      The authors follow a clear experimental logic, based on sensory deprivation by unilateral naris occlusion, EdU labeling of newborn neurons, and histological analysis via OR-specific RNA-FISH. The results reveal robust effects of deprivation on newborn OSN identity. However, the major weakness of the approach is that the results could, in (possibly large) parts, depend on "downregulation" of OR subtype-specific neurogenesis, rather than (only) "upregulation" based on odor exposure. While, in Figure 6, the authors show that the observed effects are, in part, mediated by odor stimulation, it remains unclear whether deprivation plays an "active" role as well. Moreover, as shown in Figure 1C, unilateral naris occlusion has both positive and negative effects in a random subtype sample.

      Another weakness is that the authors build their model (Figure 8), specifically the concept of selectivity, on a receptor-ligand pair (Olfr912 that has been shown to respond, among other odors, to the male-specific non-musk odors 2-sec-butyl-4,5-dihydrothiazole (SBT)) that would require at least some independent experimental corroboration. At least, a control experiment that uses SBT instead of muscone exposure should be performed. In this context, it is somewhat concerning that some results, which appear counterintuitive (e.g., lower representation and/or transcript levels of Olfr912 and Olfr1295 in mice exposed to male odors) are brushed off as "reflecting reduced survival due to overstimulation." The notion of "reduced survival" could be tested by, for example, a caspase3 assay.<br /> Important analyses that need to be done to better be able to interpret the findings are to present (i) the OR+/EdU+ population of olfactory sensory neurons not just as a count per hemisection, but rather as the ratio of OR+/EdU+ cells among all EdU+ cells; and (ii) to the ratio of EdU+ cells among all nuclei (UNO versus open naris). This way, data would be normalized to (i) the overall rate of neurogenesis and (ii) any broad deprivation-dependent epithelial degeneration.

      Finally, the paper will benefit from improved data presentation and adequate statistical testing. Images in Figures 2 - 7, showing both EdU labeling of newborn neurons and OR-specific RNA-FISH, are hard to interpret. Moreover, t-tests should not be employed when data is not normally distributed (as is the case for most of their samples).

    3. Reviewer #3 (Public Review):

      Summary:

      Neurogenesis in the mammalian olfactory epithelium persists throughout the life of the animal. The process replaces damaged or dying olfactory sensory neurons. It has been tacitly that replacement of the OR subtypes is stochastic, although anecdotal evidence has suggested that this may not be the case. In this study, Santoro and colleagues systematically test this hypothesis by answering three questions: is there enrichment of specific OR subtypes associated with neurogenesis? Is the enrichment dependent on sensory stimulus? Is the enrichment the result of differential generation of the OR type or from differential cell death regulated by neural activity? The authors provide some solid evidence indicating that musk odor stimulus selectively promotes the OR types expressing the musk receptors. The evidence argues against a random selection of ORs in the regenerating neurons.

      Strengths:

      The strength of the study is a thorough and systematic investigation of the expression of multiple musk receptors with unilateral naris occlusion or under different stimulus conditions. The controls are properly performed. This study is the first to formulate the selective promotion hypothesis and the first systematic investigation to test it. The bulk of the study uses in situ hybridization and immunofluorescent staining to estimate the number of OR types. These results convincingly demonstrate the increased expression of musk receptors in response to male odor or muscone stimulation.

      Weaknesses:

      A major weakness of the current study is the single-cell RNASeq result. The authors use this piece of data as a broad survey of receptor expression in response to unilateral nasal occlusion. However, several issues with this data raise serious concerns about the quality of the experiment and the conclusions. First, the proportion of OSNs, including both the immature and mature types, constitutes only a small fraction of the total cells. In previous studies of the OSNs using the scRNASeq approach, OSNs constitute the largest cell population. It is curious why this is the case. Second, the authors did not annotate the cell types, making it difficult to assess the potential cause of this discrepancy. Third, given the small number of OSNs, it is surprising to have multiple musk receptors detected in the open side of the olfactory epithelium whereas almost none in the closed side. Since each OR type only constitutes ~0.1% of OSNs on average, the number of detected musk receptors is too high to be consistent with our current understanding and the rest of the data in the manuscript. Finally, unlike the other experiments, the authors did not describe any method details, nor was there any description of quality controls associated with the experiment. The concerns over the scRNASeq data do not diminish the value of the data presented in the bulk of the study but could be used for further analysis.

      A weakness of the experiment assessing musk receptor expression is that the authors do not distinguish immature from mature OSNs. Immature OSNs express multiple receptor types before they commit to the expression of a single type. The experiments do not reveal whether mature OSNs maintain an elevated expression level of musk receptors.

      There are also two conceptual issues that are of concern. The first is the concept of selective neurogenesis. The data show an increased expression of musk receptors in response to male odor stimulation. The authors argue that this indicates selective neurogenesis of the musk receptor types. However, it is not clear what the distinction is between elevated receptor expression and a commitment to a specific fate at an early stage of development. As immature OSNs express multiple receptors, a likely scenario is that some newly differentiated immature OSNs have elevated expression of not only the musk receptors but also other receptors. The current experiments do not distinguish the two alternatives. Moreover, as pointed out above, it is not clear whether mature OSNs maintain the increased expression. Although a scRNASeq experiment can clarify it, the authors, unfortunately, did not perform an in-depth analysis to determine at which point of neurogenesis the cells commit to a specific musk receptor type. The quality of the scRNASeq data unfortunately also does not lend confidence for this type of analysis.

      A second conceptual issue, the idea of homeostasis in regeneration, which the authors presented in the Introduction, needs clarification. In its current form, it is confusing. It could mean that a maintenance of the distribution of receptor types, or it could mean the proper replacement of a specific OR type upon the loss of this type. The authors seem to refer to the latter and should define it properly.

    1. Reviewer #1 (Public Review):

      The work by Debashish U. Menon, Noel Murcia, and Terry Magnuson brings important knowledge about histone H3.3 dynamics involved in meiotic sex chromosome inactivation (MSCI). MSCI is unique to gametes and failure during this process can lead to infertility. Classically, MSCI has been studied in the context of DNA Damage repair pathways and little is known about the epigenetic mechanisms behind maintenance of the sex body as a silencing platform during meiosis. One of the major strengths of this work is the evidence provided on the role of ARID1A, a BAF subunit, in MSCI through the regulation of H3.3 occupancy in specific genic regions.

      Using RNA seq and CUT&RUN and ATAC-seq, the authors show that ARID1A regulates chromatin accessibility of the sex chromosomes and XY gene expression. Loss of ARID1A increases promoter accessibility of XY linked genes with concomitant influx of RNA pol II to the sex body and up regulation of XY-linked genes. This work suggests that ARID1A regulates chromatin composition of the sex body since in the absence of ARID1A, spermatocytes show less enrichment of H3.3 in the sex chromosomes and stable levels of the canonical histones H3.1/3.2. By overlapping CUT&RUN and ATAC-seq data, authors show that changes in chromatin accessibility in the absence of ARID1A are given by redistribution of occupancy of H3.3. Gained open chromatin in mutants corresponds to up regulation of H3.3 occupancy at transcription start sites of genes mediated by ARID1A.

      Interestingly, ARID1A loss caused increased promoter occupancy by H3.3 in regions usually occupied by PRDM9. PRDM9 catalyzes histone H3 lysine 4 trimethylation during meiotic prophase I, and positions double strand break (DSB) hotspots. Lack of ARID1A causes reduction in occupancy of DMC1, a recombinase involved in DSB repair, in non-homologous sex regions. These data suggest that ARID1A might indirectly influence DNA DSB repair on the sex chromosomes by regulating the localization of H3.3. This is very interesting given the recently suggested role for ARID1A in genome instability in cancer cells. It raises the question of whether this role is also involved in meiotic DSB repair in autosomes and/or how this mechanism differs in sex chromosomes compared to autosomes.

      The fact that there are Arid1a transcripts that escape the Cre system in the Arid1a KO mouse model might difficult the interpretation of the data. The phenotype of the Arid1a knockout is probably masked by the fact that many of the sequencing techniques used here are done on a heterogeneous population of knockout and wild type spermatocytes. In relation to this, I think that the use of the term "pachytene arrest" might be overstated, since this is not the phenotype truly observed. Nonetheless, the authors provide evidence showing that the spermatids observed in cKO testes that progress in spermatogenesis are the ones expressing Arid1a. This work presents enough evidence to include the BAF complex as part of the MSCI process, which increases our knowledge on specific regulation of the sex chromatin during meiosis.

    2. Reviewer #2 (Public Review):

      The authors tried to characterize the function of the SWI/SNF remodeler family, BAF, in spermatogenesis. The authors focused on ARID1A, a BAF-specific putative DNA binding subunit, based on gene expression profiles.

      The authors disagreed with my previous assessments. I disagree with their response.

    3. Reviewer #3 (Public Review):

      In this manuscript, Magnuson and colleagues investigate the meiotic functions of ARID1A, a putative DNA binding subunit of the SWI/SNF chromatin remodeler BAF. The authors develop a germ cell specific conditional knockout (cKO) mouse model using Stra8-cre and observe that ARID1A-deficient cells fail to progress beyond pachytene, although due to inefficiency of the Stra8-cre system the mice retain ARID1A-expressing cells that yield sperm and allow fertility. Because ARID1A was found to accumulate at the XY body late in Prophase I, the authors suspected a potential role in meiotic silencing and by RNAseq observe significant misexpression of sex-linked genes that typically are silenced at pachytene. They go on to show that ARID1A is required for exclusion of RNA PolII from the sex body and for limiting promoter accessibility at sex-linked genes, consistent with a meiotic sex chromosome inactivation (MSCI) defect in cKO mice. The authors proceed to investigate the impacts of ARID1A on H3.3 deposition genome-wide. H3.3 is known be regulated by ARID1A and is linked to silencing, and here the authors find that upon loss of ARID1A, overall H3.3 enrichment at the sex body as measured by IF failed to occur, but H3.3 was enriched specifically at transcriptional start sites of sex-linked genes that are normally regulated by ARID1A. The results suggest that ARID1A normally prevents H3.3 accumulation at target promoters on sex chromosomes and based on additional data, restricts H3.3 to intergenic sites. Finally, the authors present data implicating ARID1A and H3.3 occupancy in DSB repair, finding that ARID1A cKO leads to a reduction in focus formation by DMC1, a key repair protein. Overall the paper provides new insights into the process of MSCI from the perspective of chromatin composition and structure, and raises interesting new questions about the interplay between chromatin structure, meiotic silencing and DNA repair.

      In general the data are convincing. The conditional KO mouse model has some inherent limitations due to incomplete recombination and the existence of 'escaper' cells that express ARID1A and progress through meiosis normally. This reviewer feels that the authors have addressed this point thoroughly and have demonstrated clear and specific phenotypes using the best available animal model. The data demonstrate that the mutant cells fail to progress past pachytene, although it is unclear whether this specifically reflects pachytene arrest, as accumulation in other stages of Prophase also is suggested by the data in Table 1.

      The revised manuscript more appropriately describes the relationship between ARID1A and DNA damage response (DDR) signaling. The authors don't see defects in a few DDR markers in ARID1A CKO cells (including a low resolution assessment of ATR), suggesting that ARID1A may not be required for meiotic DDR signaling. However, as previously noted the data do not rule out the possibility that ARID1A is downstream of DDR signaling, and the authors note the possibility of a role for DDR signaling upstream of ARID1A.

      A final comment relates to the impacts of ARID1A loss on DMC1 focus formation and the interesting observation of reduced sex chromosome association by DMC1. The authors additionally assess the related recombinase RAD51 and suggest that it is unaffected by ARID1A loss. However, only a single image of RAD51 staining in the cKO is provided (Fig. S11) and there are no associated quantitative data provided. The data are suggestive and conclusions about the impacts of ARID1A loss on RAD51 must be considered as preliminary until more rigorously assessed.

    1. Reviewer #1 (Public Review):

      Summary:

      Asymptomatic malaria infections are frequent during the dry season and have been associated with lower cytoadherence of P. falciparum parasites and lower expression of variant surface antigens. The mechanisms underlying parasite adaptation during the low transmission season remain poorly understood. The authors previously established that members of the non-coding RNA RUF6 gene family, transcribed by RNA pol III, are required for expression of the main variant surface antigens in P. falciparum, PfEMP1, which drive parasite cytoadherence and pathogenicity. In this study, the authors investigated the contribution of RNA pol III transcription in the regulation of PfEMP1 expression in different clinical states, either symptomatic malaria cases during the wet season or asymptomatic infections during the dry season.

      By reanalyzing RNAseq data from a previous study in Mali, complemented with RT-qPCR on new samples collected in The Gambia, the authors first report the down-regulation of RNA pol III genes (tRNAs, RUF6) in P. falciparum isolates collected from asymptomatic individuals during the dry season, as compared to isolates from symptomatic (wet season) individuals. They also confirm the down-regulation of var (DBLalpha) gene expression in asymptomatic infection as compared to symptomatic malaria. Plasma analysis in the two groups in the Gambian study reveals higher Magnesium levels in dry season as compared to wet season samples, pointing at a possible role of external factors. The authors tested the effect of MgCl2 supplementation on cultured parasites, as well as three other stimuli (temperature, low glucose, Ile deprivation), and show that Ile deprivation and MgCl2 both induce down-regulation of RNA pol III transcription but not pol I or pol II (except the active var gene). Using RNAseq, they show that MgCl2 supplementation predominantly inhibits RNA pol III-transcribed genes, including the entire RUF6 family. Conditional depletion of Maf1 leads to the up-regulation of RNA pol III gene transcription, confirming that Maf1 is a RNA pol III inhibitor in P. falciparum, as described in other organisms. Quantitative mass spectrometry shows that Maf1 interacts with RNA pol III complex in the nucleus, and with distinct proteins including two phosphatases in the cytoplasm. Using the Maf1 cKD parasites, the authors document that down-regulation of RNA pol III by MgCl2 is dependent on Maf1. Finally, they show that MgCl2 results in decreased cytoadherence of infected erythrocytes, associated with reduced PfEMP1 expression.

      Strengths:

      -The work is very well performed and presented.<br /> -The study uncovers a novel regulatory mechanism relying on RNA pol III-dependent regulation of variant surface antigens in response to external signals, which could contribute to parasite adaptation during the low transmission season.<br /> -Potential regulators of Maf1 were identified by mass spectrometry, including phosphatases, paving the way for future mechanistic studies.

      Weaknesses:

      -The signaling pathway upstream of Maf1 remains unknown. In eukaryotes, Maf1 is a negative regulator of RNA pol III and is regulated by external signals via the TORC pathway. Since TORC components are absent in the apicomplexan lineage, one central question that remains open is how Maf1 is regulated in P. falciparum. Magnesium is probably not the sole stimulus involved, as suggested by the observation that Ile deprivation also down-regulates RNA pol III activity.<br /> -The study does not address why MgCl2 levels vary depending on the clinical state. It is unclear whether plasma magnesium is increased during asymptomatic malaria or decreased during symptomatic infection, as the study does not include control groups with non-infected individuals. Along the same line, MgCl2 supplementation in parasite cultures was done at 3mM, which is higher than the highest concentrations observed in clinical samples.<br /> -Although the study provides biochemical evidence of Maf1 accumulation in the parasite nuclear fraction upon magnesium addition, this is not fully supported by the immunofluorescence experiments.

    2. Reviewer #2 (Public Review):

      The study by Diffendall et al. set out to establish a link between the activity of RNA polymerase III (Pol III) and its inhibitor Maf1 and the virulence of Plasmodium falciparum in vivo. Having previously found that knockdown of the ncRNA ruf6 gene family reduces var gene expression in vitro, they now present experimental evidence for the regulation of ruf6 and subsequently, var gene expression by Pol III using a commercially available inhibitor. They confirm their findings with samples from a previously published Gambian cohort study using asymptomatic dry season and mildly symptomatic wet season samples, showing that higher levels of Pol III-dependent transcripts and var transcripts as well as lower MgCl2 plasma concentrations are present in wet season samples. From this, they hypothesize that the external stimuli heat, reduced glucose and essential amino acid supply, and increased MgCl2 levels are sensed by the parasite through the only known Pol III inhibitor Maf1 and result in lower Pol III activity and fewer ruf6 transcripts, which in turn reduces var gene expression, leading to reduced cytoadherence and virulence of P. falciparum. In their in vitro experiments they focus on investigating higher MgCl2 levels and their impact on Pol III and Maf1 activity as well as var gene expression and parasites adherence to purified CD36, thereby successfully confirming their hypothesis for MgCl2. Nicely, MgCl2-induced down-regulation of Pol III activity was shown to be dependent on Maf1 using a knock-down cell line. Additionally, they show that the Maf1-KD cell line displays a slower growth rate with fewer merozoites per schizonts and Maf1 interacts with RNA pol III subunits and some kinases/phosphatases.

      Comments on latest version:

      It is understandable that the RNA samples from the Gambian cohort were limited, but for all in vitro analyses a larger panel of qPCR primers or RNAseq would have been feasible. I also understand the rationale for using the general var primer pair (DBLa) for field isolates, but since the authors were working with a clonal parasite line (3D7) in vitro, qPCR with specific 3D7/NF54 primer pairs or RNAseq, which would also allow inferences about ruf6 regulation of specific (neighboring?) var genes and other Pol III-regulated genes, would have been a far better option.

      As far as I could see from the resubmitted manuscript, the authors did not correct the statistical analyses. For example, they continue to apply a t-test to fold-change values (which must be transformed to log2), many t-test based analyses rely on only 2-3 replicates (a non-parametric test would be more appropriate), they have not corrected for multiple testing, and it is unclear how the authors handle technical and biological replicates in their plots. Therefore, I still suspect that more appropriate statistical analyses might have an impact on the significance of their results.

      I agree that CD36 binding is associated with mild malaria, but since the authors only make a link between Pol III and CD36 binding in vitro, I think it is an overstatement to claim something like "Our study reveals a regulatory mechanism in P. falciparum involving RNA Polymerase III, which plays a pivotal role in the parasite's virulence."

      Finally, if the authors have checked all the relevant literature on MgCl2, it should be easy for them to give a brief explanation why they included only one study and ignored all the other contradictory results.

    3. Reviewer #3 (Public Review):

      Summary:

      This work describes a new pathway by which malaria parasites, P. falciparum, may regulate their growth and virulence (i.e. their expression of virulence-linked cytoadhesins). This is a topic of considerable interest in the field - does this important parasite sense factor(s) in its host bloodstream and regulate itself accordingly? Several fragments of evidence have come out on this topic in the past decade, showing, for example, reduced parasite growth under calorie restriction (in mice); parasite dormancy in response to amino acid starvation (in culture and in mice), and also reduced virulence in dry-season, low-parasitaemia infections in humans. The molecular mechanisms that may underlie this interesting biology remain only poorly understood.

      Here, the authors show that dry-season P. falciparum parasites have reduced expression of Pol3-transcribed tRNAs and ncRNAs that positively regulate virulence gene expression. They link the level of Pol3 activity to PfMaf1, a remnant of the largely-absent nutrient-sensing TOR pathway in this parasite. They propose that in the dry season, human hosts may be calorie-restricted, leading to Maf1 moving to the nucleus and suppressing Pol3, thus downregulated growth and virulence of parasites. The evidence is intriguing and the idea is conceptually elegant.

      Strengths:

      The use of dry/wet-season field samples from The Gambia is a strength, showing potential real-world relevance. The generation of an inducible knockdown of Maf1 in lab-cultured parasites is also a strength, allowing this pathway to be studied somewhat in isolation.

      Weaknesses:

      (1) The signals upstream of Maf1 remain rather a black box. 4 are tested - heatshock and low-glucose, which seem to suppress ALL transcription; low-Isoleucine and high magnesium, which suppress Pol3. Therefore the authors use Mg supplementation throughout as a 'starvation type' stimulus. They do not discuss why they didn't use amino acid limitation, which could be more easily rationalised physiologically. It may for experimental simplicity (no need for dropout media) but this should be discussed, and ideally sample experiments with low-IsoLeu should be done too, to see if the responses (e.g. cytoadhesion) are all the same.

      (2) The proteomics, conducted to seek partners of Maf1, is probably the weakest part. From Fig S4 it is clear that the proteins highlighted in the text are highly selected (as ones that might be relevant, e.g. phosphatases), but many others are more enriched. It would be good to see a) the top hits from the whole list provided as a short table within the main proteomics figure, along with the GO terms that actually came top in enrichment; b) the whole list provided as a supp. spreadsheet for easy re-analysis, rather than a PDF which cannot be easily re-used.

      (3) Fig 3 shows the Maf1-low line has very poor growth after only 5 days but it is stated that no dead parasites are seen even after 8 cycles and the merozoites number is down only ~18 to 15... is this too small to account for such poor growth (~5-fold reduced in a single cycle, day 3-5)? It would additionally be interesting to see a cell-cycle length assessment and invasion assay, to see of Maf1-low parasite have further defects in growth.

      Other weaknesses, which are more restricted but were not addressed in revision, are highlighted below:

      Fig S1B - The downregulation of RNAPol3 transcripts caused by a commercial Pol3 inhibitor is pretty weak - mostly non-significant. The authors might comment on why they think this is, when interfering with PfMaf1 evidently has a greater effect.

      Fig 2D: the legend states ' Expressed transcripts from three replicates between control and addition of MgCl2 that are significantly up-regulated are highlighted in red while significantly down-regulated RNA Pol III genes are highlighted in blue (FDR corrected p-value of <0.05) and a FC {greater than or equal to}{plus minus} 1.95) with examples listed as text'. This isn't very clear. The authors could clarify whether they took ALL (Pol3 or not) upregulated genes to show in red, but only putative Pol3-regulated genes to show in blue? If so, why? Or did they take all significantly downregulated genes, and found they were all annotated as pol3 transcribed? (I cannot see any dots that are not blue. If there are some, a clearer figure is needed?)

      Line 227: 'PfMaf1 levels were shown to decrease by approximately 57% in total extracts after one cycle' - the provenance of this very precise percentage isn't clear (it does not appear on the figure). Is it densitometry of a western blot? And if so, is it an average of the 3 replicates that are stated in the legend (but not shown), or from the single example blot shown in Figure 3?

      Fig 4A: the western blot, as shown, lacks controls, both for loading and for completeness of cyto/nuclear fractionation. To avoid confusion, these should be shown in the main figure, as is standard in the field, rather than separately in a supp figure. Ideally, 3 repeats should be done, with densitiometry quantification.

    1. Reviewer #1 (Public Review):

      Bian et al showed that biomarker-informed PhenoAgeAccel was consistently related to an increased risk of site-specific cancer and overall cancer within and across genetic risk groups. The results showed that PhenoAgeAccel and genetic liability of a bunch of cancers serve as productive tools to facilitate the identification of cancer-susceptible individuals under an additive model. People with a high genetic risk for cancer may benefit from PhenoAgeAccel-imformed interventions.

      As the authors pointed out, the large sample size, the prospective design UK Biobank study, and the effective application of PhenoAgeAccel in predicting the risk of overall cancer are the major strengths of the study. Meanwhile, the CPRS seems to be a solid and comprehensive score based on incidence-weighted site-specific polygenic risk scores across 20 well-powered GWAS for cancers.

    2. Reviewer #2 (Public Review):

      Bian et al. calculated Phenotypic Age Acceleration (PhenoAgeAccel) via a linear model regressing Phenotypic Age on chronological age. They examined the associations between PhenoAgeAccel and cancer incidence using 374,463 individuals from the UK Biobank and found that older PhenoAge was consistently related to an increased risk of incident cancer, even among each risk group defined by genetics.

      The study is well-designed, and uses a large sample size from the UK biobank.

      Comments on revised version:

      The authors have addressed all my concerns.

    1. Reviewer #1 (Public Review):

      Summary:

      The manuscript presents a compelling model to explain the impact of mosaicism in preimplantation genetic testing for aneuploidies.

      Strengths:

      A new view of mosaicism is presented with a computational model, that brings new insights into an "old" debate in our field. It is a very well-written manuscript.

      Weaknesses:

      Although the manuscript is very well written, this is in a way that assumes that the reader has existing knowledge about specific terms and topics. This was apparent through a lack of definitions and minimal background/context to the aims and conclusions for some of the author's findings.

      There is a need for some examples to connect real evidence and scenarios from clinical reports with the model.

    2. Reviewer #2 (Public Review):

      Summary:

      Although an oversimplification of the biological complexities, this modeling work does add, in a limited way, to the current knowledge on the theoretical difficulties of detecting mosaicism in human blastocysts from a single trophectoderm biopsy in PGT. However, many of the premises that the modeling was built on are theoretical and based on unproven biological and clinical assumptions that could yet lead to be untrue. Therefore, the work should be considered only as a simplified model that could assist in further understanding of the complexities of preimplantation embryo mosaicism, but assumptions of real-world application are, at this stage, premature and should not be considered as evidence in favour of any clinical strategies.

      Strengths:

      The work has presented an intriguing theoretical model for elaborating on the interpretation of complex and still unclear biological phenomena such as chromosomal mosaicism in preimplantation embryos.

      Weaknesses:

      Lines 134-138: The spatial modeling of mitotic errors in the embryo was oversimplified in this manuscript. There is only limited (and non-comprehensive) evidence that meiotic errors leading to chromosome mosaicism arise from chromosome loss or gain only (e.g. anaphase lag). This work did not take into account the (more recognised) possibility of mitotic nondisjunction where following the event there would be clones of cells with either one more or one less of the same chromosome. Although addressed in the discussion (lines 572-574), not including this in the most basic of modeling is a significant oversight that, based on the simple likelihood, could significantly affect results.

      General comment: the premise of the manuscript is that an embryologist (embryology laboratory) is aware of and can accurately quantify the number of cells in a blastocyst or TE biopsy. The reality is that it is not possible to accurately do this without the destruction of the sample which is obviously not clinically applicable. Based on many assumptions the findings show that taking small biopsies poorly classifies mosaic embryos, which is not disputed. However, extrapolating this to the clinic and making suggestions to biopsy a certain amount of cells (lines 539-540) is careless and potentially harmful by suggesting the introduction of potential change in clinical practice without validation. Additionally, no embryologist in the field can tell how many cells are present in a clinical TE biopsy, making this suggestion even more impractical.

      On a more general clinical consideration, the authors should acknowledge that when reporting findings of unproven clinical utility and unknown predictive values this inevitably results in negative consequences for infertile couples undergoing IVF. It is proven and established that when couples face the decision on how to manage a putative mosaicism finding, the vast majority decide on embryo disposal. It was recently reported in an ESHRE survey that about 75% of practitioners in the field consider discarding or donating to research embryos with reported mosaicism. A prospective clinical trial showed that about 30% live birth rate reduction can be expected if mosaic embryos are not considered (Capalbo et al., AJHG 2021). The real-world experience is that when mosaicism is reported, embryos with almost normal reproductive potential are discarded. The authors should be more careful with the clinical interpretation and translation of these theoretical findings.

      There is a robust consensus within the field of clinical genetics and genomics regarding the necessity to exclusively report findings that possess well-established clinical validity and utility. This consensus is grounded in the imperative to mitigate misinterpretation and ineffective actions in patient care. However, the clinical framework delineated in this manuscript diverges from the prevailing consensus in clinical genetics. Clinical genetics and genomics prioritize the dissemination of findings that have undergone rigorous validation processes and have demonstrated clear clinical relevance and utility. This emphasis is crucial for ensuring accurate diagnosis, prognosis, and therapeutic decision-making in patient care. By adhering to established standards of evidence and clinical utility, healthcare providers can minimize the potential for misinterpretation and inappropriate interventions. The framework proposed in this manuscript appears to deviate from the established principles guiding clinical genetics practice. It is imperative for clinical frameworks to align closely with the consensus guidelines and recommendations set forth by professional organizations and regulatory bodies in the field. This alignment not only upholds the integrity and reliability of genetic testing and interpretation but also safeguards patient well-being and clinical outcomes.

      References:<br /> ACMG Board of Directors. (2015). Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genetics in Medicine, 17(6), 505-507. https://doi.org/10.1038/gim.2014.194.<br /> Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., ... ACMG Laboratory Quality Assurance Committee. (2015). Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine, 17(5), 405-424. https://doi.org/10.1038/gim.2015.30

      Line 61: "Self correction" - This terminology is unfortunately indiscriminately used in the field for PGT when referring to mosaicism and implies that the embryo can actively correct itself from a state of inherent abnormality. Apart from there being no evidence to suggest that there is an active process by which the embryo itself can correct chromosomal errors, most presumed euploid/aneuploid mosaic embryos will have been euploid zygotes and therefore "self-harm" may be a better explanation. True self-correction in the form of meiotic trisomy/monosomy rescue is of course theoretically possible but not at all clinically significant. The concept being conveyed in this part of the manuscript is not disputed but it is strongly suggested that the term "self correction" is not used in this context, nor in the rest of the manuscript, to prevent the perpetuation of misinformation in the field and instead use a better description.

      Lines 69-73: The ability to quantify aneuploidy in known admixtures of aneuploid cells is indeed well established. However, the authors claim that the translation of this to embryo biopsy samples is inferred with some confidence and that if a biopsy shows an intermediate chromosome copy number (ICN), that the biopsy and the embryo are mosaic. There are no references provided here and indeed the only evidence in the literature relating to this is to the contrary. Multifocal biopsy studies have shown that an ICN result in a single biopsy is often not seen in other biopsies from the same embryo (Capalbo et al 2021; Kim et al., 2022; Girardi et al., 2023; Marin, Xu, and Treff 2021). Multifocal biopsies showing reciprocal gain and loss which would provide stronger validation for the presence of true mosaicism are also rare. In this work, the entire manuscript is based on the accuracy of ICN in a biopsy being reflective of mosaicism in the embryo. The evidence however points to a large proportion of ICN detected in embryo biopsy potentially being technical artifacts (misdiagnosing both constitutionally normal and abnormal (meiotic aneuploid) embryos as mosaic. Therefore, although results from the modelling provide insight into theoretical results, these can not be used to inform clinical decision-making at all.

      Lines 87-89: The authors make the claim that emerging evidence is suggestive that the majority of embryos are mosaic to some degree. If in fact, mosaicism is the norm, the clinical importance may be limited.

      Line 102-103: The statement that data shows that the live birth rate per ET is generally lower in mosaic embryos than euploid embryos is from retrospective cohort studies that suffer from significant selection bias. The authors have ignored non-selection study results (Capalbo et al, ajhg 2021) that suggest that putative mosaicism has limited predictive value when assessed prospectively and blinded.

      Lines 94-98: The authors have misrepresented the works they have presented as evidence for biopsy result accuracy (Kim et al., 2023; Victor et al 2019; Capalbo et al., 2021; Girardi et al., 2023, and any others). These studies show that a mosaic biopsy is not representative of the whole embryo and can actually be from embryos where the remainder of the embryo shows no evidence of mosaicism. There is also a missing key reference of Capalbo et al, AJHG 2021, and Girardi et al., HR 2023 where multifocal biopsies were taken.

      Lines 371-372: "Selecting the embryo with the lowest number of aneuploid cells in the biopsy for transfer is still the most sensible decision". Where is the evidence for this other than the modeling which is affected by oversimplification and unproven assumptions? Although the statement seems logical at face value, there is no concrete evidence that the proportion of aneuploid cells within a biopsy is valuable for clinical outcomes, especially when co-evaluated with other more relevant clinical information.

      Lines 431-463: In this section, the authors discuss clinical outcome data from the transfer of putative mosaic embryos and make conclusions about the relationship between ICN level in biopsy and successful pregnancy outcomes. The retrospective and selective nature of the data used in forming the results has the potential to lead to incorrect conclusions when applied to prospective unselected data.

    3. Reviewer #3 (Public Review):

      Unfortunately, this study fails to incorporate the most important variable impacting the ability to predict mosaicism, the accuracy of the test. The fact is that most embryos diagnosed as mosaic are not mosaic. There may be 4 cases out of thousands and thousands of transfers where a confirmation was made. Mosaicism has become a category of diagnosis in which embryos with noisy NGS profiles are placed. With VeriSeq NGS it is not possible to routinely distinguish true mosaicism from noise. An analysis of NGS noise levels (MAPD) versus the rate of mosaics by clinic using the registry will likely demonstrate this is the case. Without accounting for the considerable inaccuracy of the method of testing the proposed modeling is meaningless.

      Recent data using more accurate methods of identifying mosaicism indicate that the prevalence of true preimplantation embryonic mosaicism is only 2%, which is also consistent with findings made post-implantation. This model fails to account for the possibility that, because so few embryos are actually mosaic, there is actually no relevance to clinical care whatsoever. In fact, differences in clinical outcomes of embryos designated as mosaic could be entirely attributed to poor embryo quality resulting in noise levels that make NGS results fall into the "mosaic" category.

      Additional comments:

      Indeed, as more data emerges, it appears that the majority of embryos from both healthy and infertile couples are mosaic to some degree (Coticchio et al., 2021; Griffin et al., 2022).

      This statement should be softened as all embryos will be considered mosaic when a method with a 10% false positive rate is applied to 10 more parts of the same embryo. The distinction between artifact and true mosaicism cannot be made with nearly all current methods of testing. When virtually no embryos display uniform aneuploidy in a rebiopsy study, there should be great concern over the accuracy of the testing used. The vast majority of aneuploidy is meiotic in origin.

      Experimental data provides strong evidence that, for the most part, the biopsy result obtained accurately represents the chromosome constitution of the rest of the embryo (Kim 96 et al., 2022; Navratil et al., 2020; Victor et al., 2019).

      This statement is incorrect given published systematic review of the literature indicates a 10% false positive rate based on rebiopsy results.

      This shows that accurately classifying a mosaic embryo based on a single biopsy is not robust.

      This is exactly why the practice of designating embryo mosaics with intermediate copy numbers should not exist.

    1. Reviewer #1 (Public Review):

      Summary:

      This study by Park and colleagues uses longitudinal saliva viral load data from two cohorts (one in the US and one in Japan from a clinical trial) in the pre-vaccine era to subset viral shedding kinetics and then use machine learning to attempt to identify clinical correlates of different shedding patterns. The stratification method identifies three separate shedding patterns discriminated by peak viral load, shedding duration, and clearance slope. The authors also assess micro-RNAs as potential biomarkers of severity but do not identify any clear relationships with viral kinetics.

      Strengths:

      The cohorts are well developed, the mathematical model appears to capture shedding kinetics fairly well, the clustering seems generally appropriate, and the machine learning analysis is a sensible, albeit exploratory approach. The micro-RNA analysis is interesting and novel.

      Weaknesses:

      The conclusions of the paper are somewhat supported by the data but there are certain limitations that are notable and make the study's findings of only limited relevance to current COVID-19 epidemiology and clinical conditions.

      (1) The study only included previously uninfected, unvaccinated individuals without the omicron variant. It has been well documented that vaccination and prior infection both predict shorter duration shedding. Therefore, the study results are no longer relevant to current COVID-19 conditions. This is not at all the authors' fault but rather a difficult reality of much retrospective COVID research.

      (2) The target cell model, which appears to fit the data fairly well, has clear mechanistic limitations. Specifically, if such a high proportion of cells were to get infected, then the disease would be extremely severe in all cases. The authors could specify that this model was selected for ease of use and to allow clustering, rather than to provide mechanistic insight. It would be useful to list the AIC scores of this model when compared to the model by Ke.

      (3) Line 104: I don't follow why including both datasets would allow one model to work better than the other. This requires more explanation. I am also not convinced that non-linear mixed effects approaches can really be used to infer early model kinetics in individuals from one cohort by using late viral load kinetics in another (and vice versa). The approach seems better for making population-level estimates when there is such a high amount of missing data.

      (4) Along these lines, the three clusters appear to show uniform expansion slopes whereas the NBA cohort, a much larger cohort that captured early and late viral loads in most individuals, shows substantial variability in viral expansion slopes. In Figure 2D: the upslope seems extraordinarily rapid relative to other cohorts. I calculate a viral doubling time of roughly 1.5 hours. It would be helpful to understand how reliable of an estimate this is and also how much variability was observed among individuals.

      (5) A key issue is that a lack of heterogeneity in the cohort may be driving a lack of differences between the groups. Table 1 shows that Sp02 values and lab values that all look normal. All infections were mild. This may make identifying biomarkers quite challenging.

      (6) Figure 3A: many of the clinical variables such as basophil count, Cl, and protein have very low pre-test probability of correlating with virologic outcome.

      (7) A key omission appears to be micoRNA from pre and early-infection time points. It would be helpful to understand whether microRNA levels at least differed between the two collection timepoints and whether certain microRNAs are dynamic during infection.

      (8) The discussion could use a more thorough description of how viral kinetics differ in saliva versus nasal swabs and how this work complements other modeling studies in the field.

      (9) The most predictive potential variables of shedding heterogeneity which pertain to the innate and adaptive immune responses (virus-specific antibody and T cell levels) are not measured or modeled.

      (10) I am curious whether the models infer different peak viral loads, duration, expansion, and clearance slopes between the 2 cohorts based on fitting to different infection stage data.

    2. Reviewer #2 (Public Review):

      Summary:

      This study argues it has found that it has stratified viral kinetics for saliva specimens into three groups by the duration of "viral shedding"; the authors could not identify clinical data or microRNAs that correlate with these three groups.

      Strengths:

      The question of whether there is a stratification of viral kinetics is interesting.

      Weaknesses:

      The data underlying this work are not treated rigorously. The work in this manuscript is based on PCR data from two studies, with most of the data coming from a trial of nelfinavir (NFV) that showed no effect on the duration of SARS-CoV-2 PCR positivity. This study had no PCR data before symptom onset, and thus exclusively evaluated viral kinetics at or after peak viral loads. The second study is from the University of Illinois; this data set had sampling prior to infection, so has some ability to report the rate of "upswing." Problems in the analysis here include:

      -- The PCR Ct data from each study is treated as equivalent and referred to as viral load, without any reports of calibration of platforms or across platforms. Can the authors provide calibration data and justify the direct comparison as well as the use of "viral load" rather than "Ct value"? Can the authors also explain on what basis they treat Ct values in the two studies as identical?

      -- The limit of detection for the NFV PCR data was unclear, so the authors assumed it was the same as the University of Illinois study. This seems a big assumption, as PCR platforms can differ substantially. Could the authors do sensitivity analyses around this assumption?

      -- The authors refer to PCR positivity as viral shedding, but it is viral RNA detection (very different from shedding live/culturable virus, as shown in the Ke et al. paper). I suggest updating the language throughout the manuscript to be precise on this point.

      -- Eyeballing extended data in Figure 1, a number of the putative long-duration infections appear to be likely cases of viral RNA rebound (for examples, see S01-16 and S01-27). What happens if all the samples that look like rebound are reanalyzed to exclude the late PCR detectable time points that appear after negative PCRs?

      -- There's no report of uncertainty in the model fits. Given the paucity of data for the upslope, there must be large uncertainty in the up-slope and likely in the peak, too, for the NFV data. This uncertainty is ignored in the subsequent analyses. This calls into question the efforts to stratify by the components of the viral kinetics. Could the authors please include analyses of uncertainty in their model fits and propagate this uncertainty through their analyses?

      -- The clinical data are reported as a mean across the course of an infection; presumably vital signs and blood test results vary substantially, too, over this duration, so taking a mean without considering the timing of the tests or the dynamics of their results is perplexing. I'm not sure what to recommend here, as the timing and variation in the acquisition of these clinical data are not clear, and I do not have a strong understanding of the basis for the hypothesis the authors are testing.

      It's unclear why microRNAs matter. It would be helpful if the authors could provide more support for their claims that (1) microRNAs play such a substantial role in determining the kinetics of other viruses and (2) they play such an important role in modulating COVID-19 that it's worth exploring the impact of microRNAs on SARS-CoV-2 kinetics. A link to a single review paper seems insufficient justification. What strong experimental evidence is there to support this line of research?

    3. Reviewer #3 (Public Review):

      The article presents a comprehensive study on the stratification of viral shedding patterns in saliva among COVID-19 patients. The authors analyze longitudinal viral load data from 144 mildly symptomatic patients using a mathematical model, identifying three distinct groups based on the duration of viral shedding. Despite analyzing a wide range of clinical data and micro-RNA expression levels, the study could not find significant predictors for the stratified shedding patterns, highlighting the complexity of SARS-CoV-2 dynamics in saliva. The research underscores the need for identifying biomarkers to improve public health interventions and acknowledges several limitations, including the lack of consideration of recent variants, the sparsity of information before symptom onset, and the focus on symptomatic infections.

      The manuscript is well-written, with the potential for enhanced clarity in explaining statistical methodologies. This work could inform public health strategies and diagnostic testing approaches. However, there is a thorough development of new statistical analysis needed, with major revisions to address the following points:

      (1) Patient characterization & selection: Patient immunological status at inclusion (and if it was accessible at the time of infection) may be the strongest predictor for viral shedding in saliva. The authors state that the patients were not previously infected by SARS-COV-2. Was Anti-N antibody testing performed? Were other humoral measurements performed or did everything rely on declaration? From Figure 1A, I do not understand the rationale for excluding asymptomatic patients. Moreover, the mechanistic model can handle patients with only three observations, why are they not included? Finally, the 54 patients without clinical data can be used for the viral dynamics fitting and then discarded for the descriptive analysis. Excluding them can create a bias. All the discarded patients can help the virus dynamics analysis as it is a population approach. Please clarify. In Table 1 the absence of sex covariate is surprising.

      (2) Exact study timReviewer #3 (Public Review):eline for explanatory covariates: I understand the idea of finding « early predictors » of long-lasting viral shedding. I believe it is key and a great question. However, some samples (Figure 4A) seem to be taken at the end of the viral shedding. I am not sure it is really easier to micro-RNA saliva samples than a PCR. So I need to be better convinced of the impact of the possible findings. Generally, the timeline of explanatory covariate is not described in a satisfactory manner in the actual manuscript. Also, the evaluation and inclusion of the daily symptoms in the analysis are unclear to me.

      (3) Early Trajectory Differentiation: The model struggles to differentiate between patients' viral load trajectories in the early phase, with overlapping slopes and indistinguishable viral load peaks observed in Figures 2B, 2C, and 2D. The question arises whether this issue stems from the data, the nature of Covid-19, or the model itself. The authors discuss the scarcity of pre-symptom data, primarily relying on Illinois patients who underwent testing before symptom onset. This contrasts earlier statements on pages 5-6 & 23, where they claim the data captures the full infection dynamics, suggesting sufficient early data for pre-symptom kinetics estimation. The authors need to provide detailed information on the number or timing of patient sample collections during each period.

      (4) Conditioning on the future: Conditioning on the future in statistics refers to the problematic situation where an analysis inadvertently relies on information that would not have been available at the time decisions were made or data were collected. This seems to be the case when the authors create micro-RNA data (Figure 4A). First, when the sampling times are is something that needs to be clarified by the authors (for clinical outcomes as well). Second, proper causal inference relies on the assumption that the cause precedes the effect. This conditioning on the future may result in overestimating the model's accuracy. This happens because the model has been exposed to the outcome it's supposed to predict. This could question the - already weak - relation with mir-1846 level.

      (5) Mathematical Model Choice Justification and Performance: The paper lacks mention of the practical identifiability of the model (especially for tau regarding the lack of early data information). Moreover, it is expected that the immune effector model will be more useful at the beginning of the infection (for which data are the more parsimonious). Please provide AIC for comparison, saying that they have "equal performance" is not enough. Can you provide at least in a point-by-point response the VPC & convergence assessments?

      (6) Selected features of viral shedding: I wonder to what extent the viral shedding area under the curve (AUC) and normalized AUC should be added as selected features.

      (7) Two-step nature of the analysis: First you fit a mechanistic model, then you use the predictions of this model to perform clustering and prediction of groups (unsupervised then supervised). Thus you do not propagate the uncertainty intrinsic to your first estimation through the second step, ie. all the viral load selected features actually have a confidence bound which is ignored. Did you consider a one-step analysis in which your covariates of interest play a direct role in the parameters of the mechanistic model as covariates? To pursue this type of analysis SCM (Johnson et al. Pharm. Res. 1998), COSSAC (Ayral et al. 2021 CPT PsP), or SAMBA ( Prague et al. CPT PsP 2021) methods can be used. Did you consider sampling on the posterior distribution rather than using EBE to avoid shrinkage?

      (8) Need for advanced statistical methods: The analysis is characterized by a lack of power. This can indeed come from the sample size that is characterized by the number of data available in the study. However, I believe the power could be increased using more advanced statistical methods. At least it is worth a try. First considering the unsupervised clustering, summarizing the viral shedding trajectories with features collapses longitudinal information. I wonder if the R package « LongituRF » (and associated method) could help, see Capitaine et al. 2020 SMMR. Another interesting tool to investigate could be latent class models R package « lcmm » (and associated method), see Proust-Lima et al. 2017 J. Stat. Softwares. But the latter may be more far-reached.

      (9) Study intrinsic limitation: All the results cannot be extended to asymptomatic patients and patients infected with recent VOCs. It definitively limits the impact of results and their applicability to public health. However, for me, the novelty of the data analysis techniques used should also be taken into consideration.

      Strengths are:<br /> - Unique data and comprehensive analysis.<br /> - Novel results on viral shedding.

      Weaknesses are:<br /> - Limitation of study design.<br /> - The need for advanced statistical methodology.

    1. Reviewer #3 (Public Review):

      Summary:

      This manuscript by Liu et al. presents a case that CAPSL mutations are a cause of familial exudative vitreoretinopathy (FEVR). Attention was initially focused on the CAPSL gene from whole exome sequence analysis of two small families. The follow-up analyses included studies in which CAPSL was manipulated in endothelial cells of mice and multiple iterations of molecular and cellular analyses. Together, the data show that CAPSL influences endothelial cell proliferation and migration. Molecularly, transcriptomic and proteomic analyses suggest that CAPSL influences many genes/proteins that are also downstream targets of MYC and may be important to the mechanisms.

      Strengths:

      This multi-pronged approach found a previously unknown function for CAPSLs in endothelial cells and pointed at MYC pathways as high-quality candidates in the mechanism.

      Weaknesses:

      Two issues shape the overall impact for me. First, the unreported population frequency of the variants in the manuscript makes it unclear if CAPSL should be considered an interesting candidate possibly contributing to FEVR, or possibly a cause. Second, it is unclear if the identified variants act dominantly, as indicated in the pedigrees. The studies in mice utilized homozygotes for an endothelial cell-specific knockout, leaving uncertainty about what phenotypes might be observed if mice heterozygous for a ubiquitous knockout had instead been studied.

      In my opinion, the following scientific issues are specific weaknesses that should be addressed:

      (1) Please state in the manuscript the number of FEVR families that were studied by WES. Please also describe if the families had been selected for the absence of known mutations, and/or what percentage lack known pathogenic variants.

      (2) A better clinical description of family 3104 would enhance the manuscript, especially the father. It is unclear what "manifested with FEVR symptoms, according to the medical records" means. Was the father diagnosed with FEVR? If the father has some iteration of a mild case, please describe it in more detail. If the lack of clinical images in the figure is indicative of a lack of medical documentation, please note this in the manuscript.

      (3) The TGA stop codon can in some instances also influence splicing (PMID: 38012313). Please add a bioinformatic assessment of splicing prediction to the assays and report its output in the manuscript.

      (4) More details regarding utilizing a "loxp-flanked allele of CAPSL" are needed. Is this an existing allele, if so, what is the allele and citation? If new (as suggested by S1), the newly generated CAPSL mutant mouse strain needs to be entered into the MGI database and assigned an official allele name - which should then be utilized in the manuscript and who generated the strain (presumably a core or company?) must be described.

      (5) The statement in the methods "All mice used in the study were on a C57BL/6J genetic background," should be better defined. Was the new allele generated on a pure C57BL/6J genetic background, or bred to be some level of congenic? If congenic, to what generation? If unknown, please either test and report the homogeneity of the background, or consult with nomenclature experts (such as available through MGI) to adopt the appropriate F?+NX type designation. This also pertains to the Pdgfb-iCreER mice, which reference 43 describes as having been generated in an F2 population of C57BL/6 X CBA and did not designate the sub-strain of C57BL/6 mice. It is important because one of the explanations for missing heritability in FEVR may be a high level of dependence on genetic background. From the information in the current description, it is also not inherently obvious that the mice studied did not harbor confounding mutations such as rd1 or rd8.

      (6) In my opinion, more experimental detail is needed regarding Figures 2 and 3. How many fields, of how many retinas and mice were analyzed in Figure 2? How many mice were assessed in Figure 3?

      (7) I suggest adding into the methods whether P-values were corrected for multiple tests.

    2. Reviewer #1 (Public Review):

      Summary:

      The author presents the discovery and characterization of CAPSL as a potential gene linked to Familial Exudative Vitreoretinopathy (FEVR), identifying one nonsense and one missense mutation within CAPSL in two distinct patient families afflicted by FEVR. Cell transfection assays suggest that the missense mutation adversely affects protein levels when overexpressed in cell cultures. Furthermore, conditionally knocking out CAPSL in vascular endothelial cells leads to compromised vascular development. The suppression of CAPSL in human retinal microvascular endothelial cells results in hindered tube formation, a decrease in cell proliferation, and disrupted cell polarity. Additionally, transcriptomic and proteomic profiling of these cells indicates alterations in the MYC pathway.

      Strengths:

      The study is nicely designed with a combination of in vivo and in vitro approaches, and the experimental results are good quality.

      Weaknesses:

      My reservations lie with the main assertion that CAPSL is associated with FEVR, as the genetic evidence from human studies appears relatively weak. Further careful examination of human genetics evidence in both patient cohorts and the general population will help to clarify. In light of human genetics, more caution needs to be exercised when interpreting results from mice and cell models and how is it related to the human patient phenotype.

    3. Reviewer #2 (Public Review):

      Summary:

      This work identifies two variants in CAPSL in two-generation familial exudative vitreoretinopathy (FEVR) pedigrees, and using a knockout mouse model, they link CAPSL to retinal vascular development and endothelial proliferation. Together, these findings suggest that the identified variants may be causative and that CAPSL is a new FEVR-associated gene.

      Strengths:

      The authors' data provides compelling evidence that loss of the poorly understood protein CAPSL can lead to reduced endothelial proliferation in mouse retina and suppression of MYC signaling in vitro, consistent with the disease seen in FEVR patients. The study is important, providing new potential targets and mechanisms for this poorly understood disease. The paper is clearly written, and the data generally support the author's hypotheses.

      Weaknesses:

      (1) Both pedigrees described appear to suggest that heterozygosity is sufficient to cause disease, but authors have not explored the phenotype of Capsl heterozygous mice. Do these animals have reduced angiogenesis similar to KOs? Furthermore, while the p.R30X variant protein does not appear to be expressed in vitro, a substantial amount of p.L83F was detectable by western blot and appeared to be at the normal molecular weight. Given that the full knockout mouse phenotype is comparatively mild, it is unclear whether this modest reduction in protein expression would be sufficient to cause FEVR - especially as the affected individuals still have one healthy copy of the gene. Additional studies are needed to determine if these variants alter protein trafficking or localization in addition to expression, and if they can act in a dominant negative fashion.

      (2) The manuscript nicely shows that loss of CAPSL leads to suppressed MYC signaling in vitro. However, given that endothelial MYC is regulated by numerous pathways and proteins, including FOXO1, VEGFR2, ERK, and Notch, and reduced MYC signaling is generally associated with reduced endothelial proliferation, this finding provides little insight into the mechanism of CAPSL in regulating endothelial proliferation. It would be helpful to explore the status of these other pathways in knockdown cells but as the authors provide only GSEA results and not the underlying data behind their RNA seq results, it is difficult for the reader to understand the full phenotype. Volcano plots or similar representations of the underlying expression data in Figures 6 and 7 as well as supplemental datasets showing the differentially regulated genes should be included. In addition, while the paper beautifully characterizes the delayed retinal angiogenesis phenotype in CAPSL knockout mice, the authors do not return to that model to confirm their in vitro findings.

      (3) In Figure S2D, the result of this vascular leak experiment is unconvincing as no dye can be seen in the vessels. What are the kinetics for biocytin tracers to enter the bloodstream after IP injection? Why did the authors choose the IP instead of the IV route for this experiment? Differences in the uptake of the eye after IP injection could confound the results, especially in the context of a model with vascular dysfunction as here.

      (4) In Figure 5, it is unclear how filipodia and tip cells were identified and selected for quantification. The panels do not include nuclear or tip cell-specific markers that would allow quantification of individual tip cells, and in Figure 5C it appears that some filipodia are not highlighted in the mutant panel.

    1. Reviewer #2 (Public Review):

      Summary:

      An article with lots of interesting ideas and questions regarding the evolution of timing of dormancy, emphasizing mammalian hibernation but also including ectotherms. The authors compare selective forces of constraints due to energy availability versus predator avoidance and requirements and consequences of reproduction in a review of between and within species (sex) differences in the seasonal timing of entry and exit from dormancy.

      Strengths:

      The multispecies approach including endotherms and ectotherms is ambitious. This review is rich with ideas if not in convincing conclusions. Limitations are discussed yet are impactful, namely that differences among and within species are contrast only for ecological hibernation (the duration of remaining sequestered) and not for "heterothermic hibernation" the period between first and last torpor. Differences between the two can have significant energetic consequences, especially for mammals returning to euthermic levels of body temperature whilst remaining in their cold burrows before emerging, eg. reproductively developing males in spring.

      Weaknesses:

      The differences between physiological requirements for gameatogenesis between sexes that affect the timing of heterothermy and need for euthermy during mammalian hibernator are significant issues that underlie, but are under discussed, in this contrast of selective pressures that determine seasonal timing of dormancy. Some additional discussion of the effects of rapid rapid climate change on between and within species phenologies of dormancy would have been interesting.

    1. Reviewer #2 (Public Review):

      Summary:

      This work by Cloarec-Ung et al. sets out to uncover strategies that would allow for the efficient and precision editing of primitive human hematopoietic stem and progenitor cells (HSPCs). Such effective editing of HSPCs via homology directed repair has implications for the development of tractable gene therapy approaches for monogenic hematopoietic disorders as well as precise engineering of these cells for clinical regenerative and/or cell therapy strategies. In the setting of experimental hematology, precision introduction of disease relevant mutations would also open the door to more robust disease modeling approaches. It has been recognized that to encourage HDR, NHEJ as the dominant mode of repair in quiescent HSPCs must be inhibited. Testing editing of human cord blood HSPCs the authors first incorporate a prestimulation phase then identify optimal RNP amounts and donor types/amounts using standard editing culture conditions identifying optimal concentrations of AAV and short single-stranded oligonucleotide donors (ssODNs) that yield minimal impacts to cell viability while still enabling heightened integration efficiency. They then demonstrate the superiority of AZD7648, an inhibitor of NHEJ-promoting DNA-PK, in allowing for much increased HDR with toxicities imparted by this compound reduced substantially by siRNAs against p53 (mean targeting efficiencies at 57 and 80% for two different loci). Although AAV offered the highest HDR frequencies, differing from ssODN by a factor by ~2-fold, the authors show that spacer breaking sequence mutations introduced into the ssODN to better mimic the disruption of the spacer sequence provided by the synthetic intron in the AAV backbone yielded ssODN HDR frequencies equal to that attained by AAV. By examining editing efficiency across specific immunophenotypically identified subpopulations they further suggest that editing efficiency with their improved strategy is consistent across stem and early progenitors and use colony assays to quantify an approximate 4-fold drop in total colony numbers but no skewing in the potentiality of progenitors in the edited HSPC pool. Finally, the authors provide a strategy using mutation-introducing AAV mixed with different ratios of silent ssODN repair templates to enable tuning of zygosity in edited CD34+ cells.

      Strengths:

      The methods are clearly described and the experiments for the most part also appropriately powered. In addition to using state-of-the-art approaches, the authors also provided useful insights into optimizing the practicalities of the experimental procedures that will aid bench scientists in effectively carrying out these editing approaches, for example avoiding longer handling times inherent when scaling up to editing over multiple conditions.

      The sum of the adjustments to the editing procedure have yielded important advances towards minimizing editing toxicity while maximizing editing efficiency in HSPCs. In particular, the significant increase in HDR facilitated by the authors' described application of AZD7648 and the preservation of a pool of targeted progenitors is encouraging that functionally valuable cell types can be effectively edited.

      The discovery of the effectiveness of spacer breaking changes in ssODNs allowing for substantially increased targeting efficiency is a promising advance towards democratizing these editing strategies given the ease of designing and synthesizing ssODNs relative to the production of viral donors.

      The ability to zygosity tune was convincingly presented and provides a valuable strategy to modify this HDR procedure towards more accurate disease modelling.

      Weaknesses:

      Despite providing convincing evidence that functional progenitors can be successfully edited by their procedure, as the authors acknowledge it remains to be verified to what degree the survival/self-renewal capacity and in vivo regenerative potential of the more primitive fractions is maintained with their strategy. That said the inclusion of LTC-IC assays that verify the lack of effect on these quite primitive cells is encouraging that functionality of stem cells will be similarly spared.

    1. Reviewer #1 (Public Review):

      Summary: The type I ABC importer OpuA from Lactococcus lactis is the best studied transporter involved in osmoprotection. In contrast to most ABC import systems, the substrate binding protein is fused via a short linker to the transmembrane domain of the transporter. Consequently, this moiety is called the substrate binding domain (SBD). OpuA has been studied in the past in great detail and we have a very detailed knowledge about function, mechanisms of activation and deactivation as well as structure.

      Strengths: Application of smFRET to unravel transient interactions of the SBDs. The method is applied at a superb quality and the data evaluation is excellent.

      Weaknesses: The proposed model is not directly supported by experimental data. Rather alternative models are excluded as they do not fit to the obtained data. However, this is now clearly stated in the manuscript

    2. Reviewer #2 (Public Review):

      Summary:<br /> In this report the authors used solution-based single-molecule FRET and low resolution cryo-EM to investigate the interactions between the substrate-binding domains of the ABC-importer OpuA from Lactococcus lactis. Based on their results, the authors suggest that the SBDs interact in an ionic strength-dependent manner.

      Strengths:<br /> The strength of this manuscript is the uniqueness and importance of the scientific question, the adequacy of the experimental system (OpuA), and the combination of two very powerful and demanding experimental approaches.

      Weaknesses:<br /> A demonstration that the SBDs physically interact with one another, and that this interaction is important for the transport mechanism will greatly strengthen the claims of the authors. The relation to cooperativity is also unclear.

    1. Reviewer #1 (Public Review):

      Building on previous work from the Tansey lab, here Howard et al. characterize transcriptional and translational changes upon WIN site inhibition of WDR5 in MLL-rearranged cancer cells. They first analyze whether C16, a newer generation compound, has the same cellular effects as C6, an early generation compound. Both compounds reduce the expression of WDR5-bound RPGs in addition to the unbound RPG RPL22L1. They then investigate differential translation by ribo-seq and observe that WIN site inhibition reduces the translational RPGs and other proteins related to biomass accumulation (spliceosome, proteasome, mitochondrial ribosome). Interestingly, this reduction adds to the transcriptional changes and is not limited to RPGs whose promoters are bound by WDR5. Quantitative proteomics at two time points confirmed the downregulation of RPGs. Interestingly, the overall effects are modest, but RPL22LA is strongly affected. Unexpectedly, most differentially abundant proteins seem to be upregulated 24 h after C6 (see below). A genetic screen showed that loss of p53 rescues the effect of C6 and C16 and helped the authors to identify pathways that can be targeted by compounds together with WIN site inhibitors in a synergistic way. Finally, the authors elucidated the underlying mechanisms and analyzed the functional relevance of the RPL22, RPL22L1, p53 and MDM4 axis.

      Comments on revised version:

      The authors have answered my points satisfactorily and the manuscript has become clearer and more meaningful as a result. In particular, the measurement of global translation rate is important and validates the upregulation of a number of proteins following WDR5 inhibitor treatment.

    2. Reviewer #2 (Public Review):

      Summary:

      The manuscript by Howard et al reports the development of high affinity WDR5-interaction site inhibitors (WINi) that engage the protein to block the arginine-dependent engagement with its partners. Treatment of MLL-rearranged leukemia cells with high-affinity WINi (C16) decreases the expression of genes encoding most ribosomal proteins and other proteins required for translation. Notably, although these targets are enriched for WDR5-ChIP-seq peaks, such peaks are not universally present in the target genes. High concordance was founded between the alterations in gene expression due to C16 treatment and the changes resulting from treatment with an earlier, lower affinity WINi (C6). Besides protein synthesis, genes involved in DNA replication or MYC responses are downregulated, while p53 targets and apoptosis genes are upregulated. Ribosome profiling reveals a global decrease in translational efficiency due to WINi with overall ribosome occupancies of mRNAs ~50% of control samples. The magnitude in the decrements of translation for most individual mRNAs exceeds the respective changes in mRNA levels genome-wide. From these results and other considerations, the authors hypothesize that WINi results in ribosome depletion. Quantitative mass spec documents the decrement in ribosomal proteins following WINi treatment along with increases in p53 targets and proteins involved in apoptosis occurring over 3 days. Notably RPL22L1 is essentially completely lost upon WINi treatment. The investigators next conduct a CRISPR screen to find moderators and cooperators with WINi. They identify components of p53 and DNA repair pathways as mediators of WINi inflicted cell death (so gRNAs against these genes permit cell survival). Next, WINi are tested in combination with a variety of other agents to explore synergistic killing to improve their expected therapeutic efficacy. The authors document loss of the p53 antagonist MDM4 (in combination with splicing alterations of RPL22L1), an observation that supports the notion that WINi killing is p53-mediated.

      This is a scientifically very strong and well-written manuscript that applies a variety of state-of-the art molecular approaches to interrogate the role of the WDR5 interaction site and WINi. They reveal that the effects of WINi seem to be focused on the overall synthesis of protein components of the translation apparatus, especially ribosomal proteins-even those that do not bind WDR5 by ChIP (a question left unanswered is how such the WDR5-less genes are nevertheless WINi targeted). They convincingly show that disruption of the synthesis of these proteins occurs upon activation of p53 dependent apoptosis, likely driven by unbalanced ribosomal protein synthesis leading to MDM2 inhibition. This apoptosis is subsequently followed, as expected by ɣH2AX-activation. Pathways of possible WINi resistance and synergies with other anti-neoplastic approaches are explored. These experiments are all well-executed and strongly invite more extensive pre-clinical and translational studies of WINi in animal studies. The studies also may anticipate the use of WINi as probes of nucleolar function and ribosome synthesis though this was not really explored in the current manuscript. The current version of the manuscript documents ribosomal stress revealed by leakage of NPM1 into the nucleoplasm while nucleolar integrity is preserved. A progressive loss of rRNA synthesis occurs upon drug treatment that is presumably secondary to the decrement in ribosomal protein production.

      Comments on revised version:

      (1) The authors to my mind, have quite nicely and professionally addressed the comments of the reviewers and are to be congratulated on an important contribution to the elucidation of WDR5 biology and pathology.

    1. Reviewer #1 (Public Review):

      Summary:

      The authors use truncations, fragments, and HCN2/4 chimeras to narrow down the interaction and regulatory domains for LRMP inhibition of cAMP-dependent shifts in the voltage dependence of activation of HCN4 channels. They identify the N-terminal domain of HCN4 as a binding domain for LRMP, and highlight two residues in the C-linker as critical for the regulatory effect. Notably, whereas HCN2 is normally insensitive to LRMP, putting the N-terminus and 5 additional C-linker and S5 residues from HCN4 into HCN2 confers LRMP regulation in HCN2.

      Strengths:

      The work is excellent, the paper well written, and the data convincingly support the conclusions which shed new light on the interaction and mechanism for LRMP regulation of HCN4, as well as identifying critical differences that explain why LRMP does not regulate other isoforms such as HCN2.

    2. Reviewer #2 (Public Review):

      Summary:

      HCN-4 isoform is found primarily in sino-atrial node where it contributes to the pacemaking activity. LRMP is an accessory subunit which prevents cAMP-dependent potentiation of HCN4 isoform but does not have any effect on HCN2 regulation. In this study, the authors combine electrophysiology, FRET with standard molecular genetics to determine the molecular mechanism of LRMP action on HCN4 activity. Their study shows parts of N- and C-termini along with specific residues in C-linker and S5 of HCN4 are crucial for mediating LRMP action on these channels. Furthermore, they show that the initial 224 residues of LRMP are sufficient to account for most of the activity. In my view, the highlight of this study is Fig. 7 which recapitulates LRMP modulation on HCN2-HCN4 chimera. Overall, this study is an excellent example of using time-tested methods to probe the molecular mechanisms of regulation of channel function by an accessory subunit.

      The authors adequately addressed my earlier concerns.

    3. Reviewer #3 (Public Review):

      Summary:

      Using patch clamp electrophysiology and Förster resonance energy transfer (FRET), Peters and co-workers showed that the disordered N-terminus of both LRMP and HCN4 are necessary for LRMP to interact with HCN4 and inhibit the cAMP-dependent potentiation of channel opening. Strikingly, they identified two HCN4-specific residues, P545 and T547 in the C-linker of HCN4, that are close in proximity to the cAMP transduction centre (elbow Clinker, S4/S5-linker, HCND) and account for the LRMP effect.

      Strengths:

      Based on these data, the Authors propose a mechanism in which LRMP specifically binds to HCN4 via its isotype-specific Nterminal sequence and thus prevents the cAMP transduction mechanism by acting at the interface between the elbow Clinker, the S4S5-linker, the HCND.

      Weaknesses:

      Although the work is interesting, there are some discrepancies between data that need to be addressed.

      - I suggest inserting in Table 1 and in the text, the Δ shift values (+cAMP; + LRMP; +cAMP/LRMP). This will help readers.

      - Figure 1 is not clear, the distribution of values is anomalously high. For instance, in 1B the distribution of values of V1/2 in the presence of cAMP goes from - 85 to -115. I agree that in the absence of cAMP, HCN4 in HEK293 cells shows some variability in V1/2 values, that nonetheless cannot be so wide (here the variability spans sometimes even 30 mV) and usually disappears with cAMP (here not).<br /> This problem is spread throughout the ms, and the measured mean effects indeed always at the limit of statistical significance. Why so? Is this a problem with the analysis, or with the recordings?<br /> There are several other problems with Figure 1 and in all figures of the ms: the Y scale is very narrow while the mean values are marked with large square boxes. Moreover, the exemplary activation curve of Fig 1A is not representative of the mean values reported in Figure 1B, and the values of 1B are different from those reported in Table 1.<br /> On this ground it is difficult to judge the conclusions and it would also greatly help if exemplary current traces would also be shown.

      - "....HCN4-P545A/T547F was insensitive to LRMP (Figs. 6B and 6C; Table 1), indicating that the unique HCN4 C-linker is necessary for regulation by LRMP. Thus, LRMP appears to regulate HCN4 by altering the interactions between the C-linker, S4-S5 linker, and N-terminus at the cAMP transduction centre."

      Although this is an interesting theory, there are no data supporting it. Indeed, P545 and T547 at the tip of the C-linker elbow (fig 6A) are crucial for LRMP effect, but these two residues are not involved in the cAMP transduction centre (interface between HCND, S4S5 linker and Clinker elbow), at least for the data accumulated till now in the literature. Indeed, the hypothesis that LRMP somehow inhibits the cAMP transduction mechanism of HCN4 given the fact that the two necessary residues P545 and T547 are close to the cAMP transduction centre, awaits to be proven.

      Moreover, I suggest analysing the putative role of P545 and T547 in the light of the available HCN4 structures. In particular, T547 (elbow) point towards the underlying shoulder of the adjacent subunit and, therefore, it is in a key position for the cAMP transduction mechanism. The presence of bulky hydrophobic residues (very different nature compared to T) in the equivalent position of HCN1 and HCN2 is also favouring this hypothesis. In this light, it will also be interesting to see whether single T547F mutation is sufficient to prevent LRMP effect.

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, Pan DY et al. discovered that the clearance of senescent osteoclasts can lead to a reduction in sensory nerve innervation. This reduction is achieved through the attenuation of Netrin-1 and NGF levels, as well as the regulation of H-type vessels, resulting in a decrease in pain-related behavior. The experiments are well-designed. The results are clearly presented, and the legends are also clear and informative. Their findings represent a potential treatment for spine pain utilizing senolytic drugs.

      Strengths:

      Rigorous data, well-designed experiments as well as significant innovation make this manuscript stand out.

      Weaknesses:

      All my concerns have been well addressed, no further comments.

    2. Reviewer #2 (Public Review):

      Summary:

      This manuscript examined the underlying mechanisms between senescent osteoclasts (SnOCs) and lumbar spine instability (LSI) or aging. They first showed that greater numbers of SnOCs are observed in mouse models of LSI or aging, and these SnOCs are associated with induced sensory nerve innervation, as well as the growth of H-type vessels, in the porous endplate. Then, the deletion of senescent cells by administration of the senolytic drug Navitoclax (ABT263) results in significantly less spinal hypersensitivity, spinal degeneration, porosity of the endplate, sensory nerve innervation, and H-type vessel growth in the endplate. Finally, they also found that there is greater SnOC-mediated secretion of Netrin-1 and NGF, two well-established sensory nerve growth factors, compared to non-senescent OCs. The study is well conducted and data strongly support the idea.

    3. Reviewer #3 (Public Review):

      Summary:

      This research article reports that a greater number of senescent osteoclasts (SnOCs), which produce Netrin-1 and NGF, are responsible for innervation in the LSI and aging animal models.

      Strengths:

      The research is based on previous findings in the authors' lab and the fact that the IVD structure was restored by treatment with ABT263. The logic is clear and clarifies the pathological role of SnOCs, suggesting the potential utilization of senolytic drugs for the treatment of LBP. Generally, the study is of good quality and the data is convincing.

      Weaknesses:

      All my concerns have been well addressed, no further comments.

    1. Reviewer #1 (Public Review):

      Here, using an organoid system, Wong et al generated a new model of hereditary diffuse leukoencephalopathy with axonal spheroids, with which they investigated how CSF1R-mutaions affect the phenotypes of microglia/macrophages, and revealed metabolic changes in microglia/macrophages associated with a proinflammatory phenotype.

      In general, this paper is interesting and well-written, and tackles important issues to be addressed.

      This study suffers from several major concerns and limitations that dampen the value of the study. As the authors also mentioned, models that perfectly recapitulate the complexity of the HDLS brain the models would be required to better understand the molecular mechanisms of the disease. In this regard, it is unclear how nicely the organoid system in this study can recapitulate the condition in patients with HDLS (e.g. reduced microglia density, downregulated expression of P2YR12, pathological alterations). In addition, the authors used two different models with distinct mutations that could produce different readouts in CSF1R-mediated cellular responses.

      Although the reviewer does understand the importance of providing several options/tools to study rare diseases like HDLS and the difficulty of generating stable organoids with less variation, it is unclear if the different outcomes between HD1 and HD2 are generated through different mutations or simply due to different differentiation efficiency from iMacs (e.g. Figure 2B), which needs to be confirmed. Lastly, there is an over-interpretation regarding the results in Figure 6A. There is no difference between isoHD1 iMac control and HD1 Mut iMac.

    2. Reviewer #2 (Public Review):

      Summary:

      This paper investigates a rare and severe brain disease called Hereditary Diffuse Leukoencephalopathy with Axonal Spheroids (HDLS). The authors aimed to understand how mutations in the gene CSF-1R affect microglia, the resident immune cells in the brain, and which alterations and factors lead to the specific pathophysiology. To model the human brain with the pathophysiology of HDLS, they used the human-specific model system of induced pluripotent stem cell (iPSC)-derived forebrain organoids with integrated iPSC-derived microglia (iMicro) from patients with the HDLS-causing mutation and an isogenic cell line with the corrected genome. They found that iPSC-derived macrophages (iMac) with HDLS mutations showed changes in their response, including increased inflammation and altered metabolism. Additionally, they studied these iMacs in forebrain organoids, where they differentiate into iMicro, and showed transcriptional differences in isolated iMicro when carrying the HDLS mutation. In addition, the authors described the influence of the mutation within iMicro on the transcriptional level of neurons and neural progenitor cells (NPCs) in the organoid. They observed that the one mutation showed implications for impaired development of neurons, possibly contributing to the progression of the disease.

      Overall, this study provides valuable insights into the mechanisms underlying HDLS and emphasizes the importance of studying diseases like these with a suitable model system. These findings, while promising, represent only an initial step towards understanding HDLS and similar neurodegenerative diseases, and thus, their direct translation into new treatment options remains uncertain.

      Strengths:

      The strength of the work lies in the successful reprogramming of two HDLS patient-derived induced pluripotent stem cells (iPSCs) with different mutations, which is crucial for the study of HDLS using human forebrain organoid models. The use of corrected isogenic iPSC lines as controls increases the validity of the mutation-specific observations. In addition, the model effectively mimics HDLS, particularly concerning deficits in the frontal lobe, mirroring observations in the human brain. Obtaining iPSCs from patients with different CSF1R mutations is particularly valuable given the limitations of rodent and zebrafish models when studying adult-onset neurodegenerative diseases. The study also highlights significant metabolic changes associated with the CSF1R mutation, particularly in the HD2 mutant line, which is confirmed by the HD1 line. In addition, the work shows transcriptional upregulation of the proinflammatory cytokine IL-1beta in cells carrying the mutation, particularly when they phagocytose apoptotic cells, providing further insight into disease mechanisms.

      Weaknesses:

      The authors have not elucidated the significance of the increased CSF1 dosage in Figure 2F, aside from its effect on cell viability, lacking a thorough discussion of this result. Additionally, while transcriptomic and metabolic alterations related to the mutation were demonstrated in iMac models, similar investigations in iMicros are absent, necessitating further experiments to validate the findings across cell models. The conclusion drawn regarding cytokine levels lacks robust support from the data, particularly considering the varied responses observed in different mutant lines. Further analysis of the secretome (e.g. via ELISA) could provide additional insights. Moreover, the characterization of iMicros is incomplete, with limited protein-level analysis (e.g. validate RNA-seq via flow cytometry). Additionally, the claim of microglial-like morphology lacks adequate evidence, as the provided image is insufficient for such an assessment. RNA-seq experiments should be represented better, it is not possible to read the legends or gene names in the figures. Maybe the data sets can be combined into PCAone and one overall analysis, e.g. via WGCNA-like analyses? This would make it easier for the reader to compare the two cell lines side by side. Furthermore, inaccuracies and omissions in the figure legends compromise the clarity of data representation. Statistical test information is missing. Finally, inconsistent terminology usage throughout the paper may confuse readers (iMac versus iMicros).

    1. Reviewer #2 (Public Review):

      Summary:

      Fertilization is a crucial event in sexual reproduction, but the molecular mechanisms underlying egg-sperm fusion remain elusive. Elofsson A 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 are 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:

      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. provides experimental evidence of the interaction between IZUMO1/SPACA6/TMEM81 in zebrafish. This is an important element that supports the findings presented in this manuscript

      Regarding the authors response on the question of a global search:<br /> I understand that a global search might be difficult to interpret because a large number of putative false positives. But it is this type of information that is needed to assess the validity of the model and the scoring power in the absence of any experimental validation. At minimum, the search should include a negative control set of proteins known to be unrelated to sperm fertilization or homologous egg-sperm fusion complexes from incompatible species to account for species-specific interactions.

      I acknowledge that experimentally validating highly transient complexes presents technical hurdles. However, a high-confidence structural model could enable the design of point mutations specifically disrupting the predicted interactions. Subsequent rescue experiments could then validate the directionality of these interactions. Ultimately, such experiments are crucial for robust model validation.

    2. 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 co-operate to complete the fusion process. In this study, the authors first identified TMEM81 as a structural homologue of IZUMO1 and SPACA6, and predicted the interactions with a pool of human proteins associated with gamete fusion, using AlphaFold-Multimer, a recent advance in protein complex structure prediction. The prediction is compelling and well discussed, and the experimental evidence to verify this interaction is lacking in this study but supported by a complementary and independent study by another group.

      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:

      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. The experimental validation of the interactions is not directly supported in this study. As there are more candidate proteins in the process, testing other possible protein interactions more comprehensively will provide more rationale for the current 3D multi-protein modeling.

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, the authors generated a novel transgenic mouse line OpalinP2A-Flpo-T2A-tTA2 to specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small but lasting contribution to the cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study provides a revised and more comprehensive view on the embryonic origins of cortical oligodendrocytes. To specifically label mature oligodendrocytes, and at the same time their embryonic origins by crossing with a progenitor cre mouse line. With this clever approach, they found that LGE/CGE-derived OLs make minimum contributions to the neocortex, whereas MGE/POA-derived OLs make a small-but-lasting contribution to to cortex. These findings are contradictory to the current belief that LGE/CGE-derived OPCs make a sustained contribution to cortical OLs, whereas MGE/POA-derived OPCs are completely eliminated. Thus, this study has provided a revised and updated view on the embryonic origins of cortical oligodendrocytes.

      Strengths:

      The authors have generated a novel transgenic mouse line to specifically label mature differentiated oligodendrocytes, which is very useful for tracing the final destiny of mature myelinating oligodendrocytes. Also, the authors carefully compared the distribution of three progenitor cre mouse lines and suggested that Gsh-cre also labeled dorsal OLs, contrary to the previous suggestion that it only marks LGE-derived OPCs. In addition, the author also analyzed the relative contributions of OLs derived from three distinct progenitor domains in other forebrain regions (e.g. Pir, ac). Finally, the new transgenic mouse lines and established multiple combinatorial genetic models will facilitate future investigations of the developmental origins of distinct OL populations and their functional and molecular heterogeneity.

      Weaknesses:

      Since OpalinP2A-Flpo-T2A-tTA2 only labels mature oligodendrocytes but not OPCs, the authors can not suggest that the lack of LGE/CGE-derived-OLs in the neocortex is less likely caused by competitive postnatal elimination, but more likely due to limited production and/or allocation (line 118-9). It remains possible that LGE/CGE-derived OPCs migrate into the cortex but are later eliminated.

    2. Reviewer #2 (Public Review):

      Summary:

      In this manuscript, Cai et al use a combination of mouse transgenic lines to re-examine the question of the embryonic origin of telencephalic oligodendrocytes (OLs). Their tools include a novel Flp mouse for labelling mature oligodendrocytes and a number of pre-existing lines (some previously generated by the last author in Josh Huang's lab) that allowed combinatorial or subtractive labelling of oligodendrocytes with different origins. The conclusion is that cortically-derived OLs are the predominant OL population in the motor and somatosensory cortex and underlying corpus callosum, while the LGE/CGE generates OLs for the piriform cortex and anterior commissure rather than the cerebral cortex. Small numbers of MGE-derived OLs persist long-term in the motor, somatosensory and piriform cortex.

      Strengths:

      The strength and novelty of the manuscript lies in the elegant tools generated and used and which have the potential to elegantly and accurately resolve the issue of the contribution of different progenitor zones to telencephalic regions.

      Weaknesses:

      (1) Throughout the manuscript (with one exception, lines 76-78), the authors quantified OL densities instead of contributions to the total OL population (as a % of ASPA for example). This means that the reader is left with only a rough estimation of the different contributions.

      (2) All images and quantifications have been confined to one level of the cortex and the potential of the MGE and the LGE/CGE to produce oligodendrocytes for more anterior and more posterior cortical regions remains unexplored.

      (3) Hence, the statement that "In summary, our findings significantly revised the canonical model of forebrain OL origins (Figure 4A) and provided a new and more comprehensive view (Figure 4B )." (lines 111, 112) is not really accurate as the findings are neither new nor comprehensive. Published manuscripts have already shown that (a) cortical OLs are mostly generated from the cortex [Tripathi et al 2011 (https://doi.org/10.1523/JNEUROSCI.6474-10.2011), Winker et al 2018 (https://doi.org/10.1523/JNEUROSCI.3392-17.2018) and Li et al (https://doi.org/10.1101/2023.12.01.569674)] and (b) MGE-derived OLs persist in the cortex [Orduz et al 2019 (https://doi.org/10.1038/s41467-019-11904-4) and Li et al 2024 (https://doi.org/10.1101/2023.12.01.569674)]. Extending the current study to different rostro-caudal regions of the cortex would greatly improve the manuscript.

    3. Reviewer #3 (Public Review):

      In the manuscript entitled "Embryonic Origins of Forebrain Oligodendrocytes Revisited by Combinatorial Genetic Fate Mapping," Cai et al. used an intersectional/subtractional strategy to genetically fate-map the oligodendrocyte populations (OLs) generated from medial ganglionic eminence (NKX2.1+), lateral ganglionic eminences, and dorsal progenitor cells (EMX1+). Specifically, they generated an OL-expressing reporter mouse line OpalinP2A-Flpo-T2A-tTA2 and bred with region-specific neural progenitor-expressing Cre lines EMX1-Cre for dOL and NKX2.1-Cre for MPOL. They used a subtractional strategy in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line to predict the origins of OLs from lateral/caudal ganglionic eminences (LC). With their genetic tools, the authors concluded that neocortical OLs primarily consist of dOLs. Although the populations of OLs (dOLs or MP-OLs) from Emx1+ or Nkx2.1+ progenitors are largely consistent with previous findings, they observed that MP-OLs contribute minimally but persist into adulthood without elimination as in the previous report (PMID: 16388308).

      Intriguingly, by using an indirect subtraction approach, they hypothesize that both Emx1-negative and Nkx2.1-negative cells represent the progenitors from lateral/caudal ganglionic eminences (LC), and conclude that neocortical OLs are not derived from the LC region. This is in contrast to the previous observation for the contribution of LC-expressing progenitors (marked by Gsx2-Cre) to neocortical OLs (PMID: 16388308). The authors claim that Gsh2 is not exclusive to progenitor cells in the LC region (PMID: 32234482). However, Gsh2 exhibits high enrichment in the LC during early embryonic development. The presence of a small population of Gsh2-positive cells in the late embryonic cortex could originate/migrate from Gsh2-positive cells in the LC at earlier stages (PMID: 32234482). Consequently, the possibility that cortical OLs derived from Gsh2+ progenitors in LC could not be conclusively ruled out. Notably, a population of OLs migrating from the ventral to the dorsal cortical region was detected after eliminating dorsal progenitor-derived OLs (PMID: 16436615).

      The indirect subtraction data for LC progenitors drawn from the OpalinFlp-tdTOM reporter in Emx1-negative and Nkx2.1-negative cells in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line present some caveats that could influence their conclusion. The extent of activity from the two Cre lines in the OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mice remains uncertain. The OpalinFlp-tdTOM expression could occur in the presence of either Emx1Cre or Nkx2.1Cre, raising questions about the contribution of the individual Cre lines. To clarify, the authors should compare the tdTOM expression from each individual Cre line, OpalinFlp::Emx1Cre::RC::FLTG or OpalinFlp::Nkx2.1Cre::RC::FLTG, with the combined OpalinFlp::Emx1Cre::Nkx2.1Cre::RC::FLTG mouse line. This comparison is crucial as the results from the combined Cre lines could appear similar to only one Cre line active.

      Overall, the authors provided intriguing findings regarding the origin and fate of oligodendrocytes from different progenitor cells in embryonic brain regions. However, further analysis is necessary to substantiate their conclusion about the fate of LC-derived OLs convincingly.

  2. Apr 2024
    1. Reviewer #1 (Public Review):

      This is an interesting, informative, and well-designed study that combines theoretical and experimental methodologies to tackle the phenomenon of higher-resolution structures/substructures in model biomolecular condensates. However, there is significant room for improvement in the presentation and interpretation of the results. As it stands, the precise definition of "frustration," which is a main theme of this manuscript (as emphasized in the title), is not sufficiently well articulated. This situation should be rectified to avoid "frustration" becoming a "catch-all" term without a clear perimeter of applicability rather than a precise, informative description of the physical state of affairs. There are also a few other concerns, e.g., regarding interpretation of correlation of phase-separation critical temperature and transfer free energy of amino acid residues as well as the difference between critical temperature and onset temperature, and the way the simulated configurations are similar to that of gyroids. Accordingly, the manuscript should be revised to address the following:

      (1) It is accurately pointed out on p.4 that elastin-like polypeptides (ELPs) undergo heat-induced phase separation and therefore exhibit lower critical solution temperatures (LCSTs). But it is not entirely clear how this feature is reproduced by the authors' simulation. A relationship between simulated surface tension and "transition temperature" is provided in Fig.1C; but is the "transition temperature" (authors cited ref.41 by Urry) the same as critical temperature? Apparently, Urry's Tt is "critical onset temperature", the temperature when phase separation happens at a given polymer concentration. This is different from the (global) critical temperature LCST - though the two may be correlated-or not-depending on the shape of the phase boundary. Moreover, is the MOFF coarse-grained forcefield (first step in the multi-scale simulation), by itself, capable of reproducing heat-induced phase separation in a way similar to the forcefield of Dignon et al., ACS Cent Sci 5, 821-230 (2019)? Or, is this temperature-dependent effect appearing only subsequently, after the implementation of the MARTINI and/or all-atom steps? Clarification is needed. To afford a more informative context for the authors' introductory discussion, the aforementioned Dignon et al. work and the review by Cinar et al. [Chem Eur J 25, 13049-13069 (2019)], both touching upon the physical underpinning of the LCST feature of elastin, should also be cited along with refs.41-43.

      (2) "Frustration" and "frustrated" are used prominently in the manuscript to characterize certain observed molecular configurations (11 times total, in both the title and in the abstract). Apparently, it is the most significant conceptual pronouncement of this work, hence its precise meaning is of central importance to the authors' thesis. Whereas one should recognize that the theoretical and experimental observations are striking without invocation of the "frustration" terminology, usage of the term can be useful if it offers a unifying conceptual framework. However, as it stands, a clear definition of the term "frustration" is lacking, leaving readers to wonder what molecular configurations are considered "frustrated" and what are not (i.e.,is the claim of observation of frustration falsifiable?). For instance, "frustrated microphase separation" appears in both the title and abstract. A logical question one may ask is: "Are all microphase separations frustrated"? If the answer is in the affirmative, does invocation of the term "frustration" add anything to our physical insight? If the answer is not in the affirmative, then how does one distinguish between microphase separations that are frustrated from those that are not frustrated? Presumably all simulated and experimental molecular configurations in the present study are those of lowest free energy for the given temperature. In other words, they are what they are. In the discussion about frustrated phase separation on p.13, for example, the authors appear to refer to the fact that chain connectivity is preventing hydrophobic residues to come together in a way to achieve the most favorable interactions as if there were no chain connectivity (one may imagine in that case all the hydrophobic residues will form a large cluster without microphase separation). Is this what the authors mean by "frustration"? If that's true, isn't that merely stating the obvious, at least for the observed microphase separation? In general, does "frustration" always mean deviation of actual, physical molecular configurations from certain imagined/hypothetical/reference molecular configurations, and therefore dependent upon the choice of the imagined reference configuration? If this is how the authors apply the term "frustration" in the present work, what is the zero-frustration reference state/configuration for microphase separation? And, similarly, what is the zero-frustration reference state/configuration when frustrated EPS-water interactions are discussed (~p.14-p.15, Fig.5)? How do non-frustrated water-protein interactions look like? Is the classic clathrate-like organization of water hydrogen bonds around small nonpolar solute "frustrated"?

      (3) In the discussion about the correlation of various transfer free energy scales for amino acids and Urry's critical onset temperature (ref.41) on p.11 and Fig.4, is there any theoretical relationship to be expected between the interactions among amino acids of ELPs and their critical onset temperatures? While a certain correlation may be intuitively expected if the free energy scale "is working", is there any theoretical insight into the mathematical form of this relationship? A clarifying discussion is needed because it bears logically on whether the observed correlation or lack thereof for different transfer energy scales is a good indication of the adequacy of the energy scales in describing the actual physical interactions at play. This question requires some prior knowledge of the expected mathematical relationship between interaction parameters and onset temperature.

      (4) To provide a more comprehensive context for the present study, it is useful to compare the microphase separation seen in the authors' simulation with the micelle-like structures observed in recent simulated condensed/aggregated states of hydrophobic-polar (HP) model sequences in Statt et al., J Chem Phys 152, 075101 (2020) [see esp. Fig.6] and Wessén et al., J Phys Chem B 126, 9222-9245 (2022) [see, e.g., Fig.10].

      (5) "Gyroid-like morphology" is mentioned several times in the manuscript (p.4, p.8, p.17, Fig.S3). This is apparently an interesting observation but a clear explanation is lacking. A more detailed and specific discussion, perhaps with additional graphical presentations, should be provided to demonstrate why the simulated condensed-phase ELP configurations are similar to the classical description of gyroid as in, e.g., Terrones & Mackay, Chem Phys Lett 207, 45-50 (1993) and Lambert et al., Phil Trans R Soc A 354, 2009-2023 (1996).

      Comments on the revised manuscript:

      The authors have adequately addressed my previous concerns.

    2. Reviewer #2 (Public Review):

      Summary:

      Latham A.P. et al. apply simulations and FLIM to analyse several di-block elastin-like polypetides and connect their sequence to the micro-structure of coacervates resulting from their phase-separation.

      Strengths:

      Understanding the molecular grammar of phase separating proteins and the connection with mesoscale properties of the coacervates is highly relevant. This work provides insights into micro-structures of coacervates resulting from di-block polypetides.

      Weaknesses:

      The results apply to a very specific architecture (di-block polypetides) with specific sequences.

    1. Reviewer #1 (Public Review):

      Most amino acids are stereoisomers in the L-enantiomer, but natural D-serine has also been detected in mammals and its levels shown to be connected to a number of different pathologies. Here, the authors convincingly show that D-serine is transported in the kidney by the neutral amino acid transporter ASCT2 and as a non-canonical substrate for the sodium-coupled monocarboxylate transporter SMCTs. Although both transport D-serine, this important study further shows in a mouse model for acute kidney injury that ASCT2 has the dominant role.

      Strengths:

      The paper combines proteomics, animal models, ex vivo transport analyses and in vitro transport assays using purified components. The exhaustive methods employed provide compelling evidence that both transporters can translocate D-serine in the kidney.

      Weakness:

      In the model for acute kidney injury the SMCTs proteins were not showing a significant change in expression levels and were rather analysed based on other, circumstantial evidence. Although its clear SMCTs can transport D-serine its physiological role is less obvious compared to ASCT2.

    2. Reviewer #2 (Public Review):

      Summary:

      The manuscript "A multi-hierarchical approach reveals D-1 serine as a hidden substrate of sodium-coupled monocarboxylate transporters" by Wiriyasermkul et al. is a resubmission of a manuscript, which focused first on the proteomic analysis of apical membrane isolated from mouse kidney with early ischemia- reperfusion injury (IRI), a well-known acute kidney injury (AKI) model. In a second part, the transport of D-serine by Asct2, Smct1, and Smct2 has been characterized in detail in different model systems, such as transfected cells and proteoliposomes.

      Strengths:

      A major problem with the first submission was the explanation of the link between the two parts of the manuscript: it was not very clear why the focus on Asct2, Smct1 and Smct2 was a consequence of the proteomic analysis. In the present version of the manuscript, the authors have focused on the expression of membrane transporters in the proteome analysis, thus making the reason for studying Asct2, Smct1 and Smct2 transporters more clear. In addition, the authors used 2D-HPLC to measure plasma and urinary enantiomers of 20 amino acids in plasma and urine samples from sham and ischaemia-reperfusion injury (IRI) mice. The results of this analysis demonstrated the value of D-serine as a potential marker of renal injury. These changes have greatly improved the manuscript and made it more convincing.

      Weaknesses:

      More than weakness I would speak of discussion points: I have a few suggestions that may help to make the paper more accessible to a general audience.<br /> (1) In the Introduction, when the authors introduce the term "micromolecules", it would be beneficial to provide a precise definition or clarification of what they mean by this term. Adding a brief explanation may help the reader to better understand the context.<br /> (2) In line 91, I suggest specifying that this is a renal IRI model.<br /> (3) Lines 167-168 state that Asct2 is localised to the apical side of the renal proximal tubules. Is there any expression of Asct2 in other nephron segments?<br /> (4) Lines 225-226: Have the authors expressed the candidate genes in HEK293 cells with ASCT2 knockdown?<br /> (5) lines 254-255: why was D-serine transport enhanced by ASCT2 knockdown in FlpInTR-SMCT1 or 2 cells?<br /> (6) line 265: The low affinity of SMCT1 for D-serine alone makes it an unlikely transporter for urinary D-serine.<br /> (7) line 316: The authors state that there is a high tubular D-serine reabsorption in IRI and in line 424 that there is an inactivation of DAAO during the pathology. This suggests that there is a reabsorption of D-serine mediated by a transport system in the basolateral membrane domain of proximal tubular cells. Do the authors have any information about this transporter?<br /> (8) in lines 462-463, the authors state: "It is suggested that PAT1 is less active at the apical membrane where the luminal pH is neutral". However, the pH of urine in the proximal tubules is normally acidic due to the high activity of NH3. I suggest rewording this sentence.

    3. Reviewer #3 (Public Review):

      Summary:

      The main objective of this work has been to delve into the mechanisms underlying the increment of D-serine in serum, as a marker of renal injury.

      Strengths:

      With a multi-hierarchical approach, the work shows that Ischemia reperfusion injury in kidney causes a specific increment in renal reabsorption of D-serine that, at least in part, is due to the increased expression of the apical transporter ASCT2. In the way, the authors revealed that SMCT1 also transports D-serine.

      The manuscript also supports that increased expression of ASCT2, even together with the parallel decreased expression of SMCT1, in renal proximal tubules underlies the increased reabsorption of D-serine responsible of the increment of this enantiomer in serum in a murine model of ischemia reperfusion injury.

      Weaknesses:

      Remains to be clarified whether ASCT2 has substantial stereospecificity in favor of D- versus L-serine to sustain a ~10-fold decreased in the ratio D-serine/L-serine in the urine of mouse under ischemia reperfusion injury (IRI).<br /> It is not clear how the increment in the expression of ASCT2, in parallel with the decreased expression of SMCT1, results in increased renal reabsorption of D-serine in IRI.

      I am satisfied with the changes the authors have introduced in the text of the revised version of their manuscript.

    1. Reviewer #1 (Public Review):

      Summary:

      LRRK2 protein is familially linked to Parkinson's disease by the presence of several gene variants that all confer a gain-of-function effect on LRRK2 kinase activity.

      The authors examine the effects of BDNF stimulation in immortalized neuron-like cells, cultured mouse primary neurons, hIPSC-derived neurons, and synaptosome preparations from the brain. They examine an LRRK2 regulatory phosphorylation residue, LRRK2 binding relationships, and measures of synaptic structure and function.

      Strengths:

      The study addresses an important research question: how does a PD-linked protein interact with other proteins, and contribute to responses to a well-characterized neuronal signalling pathway involved in the regulation of synaptic function and cell health?

      They employ a range of good models and techniques to fairly convincingly demonstrate that BDNF stimulation alters LRRK2 phosphorylation and binding to many proteins. Some effects of BDNF stimulation appear impaired in (some of the) LRRK2 knock-out scenarios (but not all). A phosphoproteomic analysis of PD mutant Knock-in mouse brain synaptosomes is included.

      Weaknesses:

      The data sets are disjointed, conclusions are sweeping, and not always in line with what the data is showing. Validation of 'omics' data is very light. Some inconsistencies with the major conclusions are ignored. Several of the assays employed (western blotting especially) are likely underpowered, findings key to their interpretation are addressed in only one or other of the several models employed, and supporting observations are lacking.

      As examples to aid reader interpretation:

      (a) pS935 LRRK2 seems to go up at 5 minutes but goes down below pre-stimulation levels after (at times when BDNF-induced phosphorylation of other known targets remains very high). This is ignored in favour of discussion/investigation of initial increases, and the fact that BDNF does many things (which might indirectly contribute to initial but unsustained changes to pLRRK2) is not addressed.

      (b) Drebrin coIP itself looks like a very strong result, as does the increase after BDNF, but this was only demonstrated with a GFP over-expression construct despite several mouse and neuron models being employed elsewhere and available for copIP of endogenous LRRK2. Also, the coIP is only demonstrated in one direction. Similarly, the decrease in drebrin levels in mice is not assessed in the other model systems, coIP wasn't done, and mRNA transcripts are not quantified (even though others were). Drebrin phosphorylation state is not examined.

      (c) The large differences in the CRISPR KO cells in terms of BDNF responses are not seen in the primary neurons of KO mice, suggesting that other differences between the two might be responsible, rather than the lack of LRRK2 protein.

      (d) No validation of hits in the G2019S mutant phosphoproteomics, and no other assays related to the rest of the paper/conclusions. Drebrin phosphorylation is different but unvalidated, or related to previous data sets beyond some discussion. The fact that LRRK2 binding occurs, and increases with BDNF stimulation, should be compared to its phosphorylation status and the effects of the G2019S mutation.

    2. Reviewer #2 (Public Review):

      Taken as a whole, the data in the manuscript show that BDNF can regulate PD-associated kinase LRRK2 and that LRRK2 modifies the BDNF response. The chief strength is that the data provide a potential focal point for multiple observations across many labs. Since LRRK2 has emerged as a protein that is likely to be part of the pathology in both sporadic and LRRK2 PD, the findings will be of broad interest. At the same time, the data used to imply a causal throughline from BDNF to LRRK2 to synaptic function and actin cytoskeleton (as in the title) are mostly correlative and the presentation often extends beyond the data. This introduces unnecessary confusion. There are also many methodological details that are lacking or difficult to find. These issues can be addressed.

      (1) The writing/interpretation gets ahead of the data in places and this was confusing. For example, the abstract highlights prior work showing that Ser935 LRRK2 phosphorylation changes LRRK2 localization, and Figure 1 shows that BDNF rapidly increases LRRK2 phosphorylation at this site. Subsequent figures highlight effects at synapses or with synaptic proteins. So is the assumption that LRRK2 is recruited to (or away from) synapses in response to BDNF? Figure 2H shows that LRRK2-drebrin interactions are enhanced in response to BDNF in retinoic acid-treated SH-SY5Y cells, but are synapses generated in these preps? How similar are these preps to the mouse and human cortical or mouse striatal neurons discussed in other parts of the paper (would it be anticipated that BDNF act similarly?) and how valid are SH-SY5Y cells as a model for identifying synaptic proteins? Is drebrin localization to synapses (or its presence in synaptosomes) modified by BDNF treatment +/- LRRK2? Or do LRRK2 levels in synaptosomes change in response to BDNF? The presentation requires re-writing to stay within the constraints of the data or additional data should be added to more completely back up the logic.

      (2) The experiments make use of multiple different kinds of preps. This makes it difficult at times to follow and interpret some of the experiments, and it would be of great benefit to more assertively insert "mouse" or "human" and cell type (cortical, glutamatergic, striatal, gabaergic) etc.

      (3) Although BDNF induces quantitatively lower levels of ERK or Akt phosphorylation in LRRK2KO preps based on the graphs (Figure 4B, D), the western blot data in Figure 4C make clear that BDNF does not need LRRK2 to mediate either ERK or Akt activation in mouse cortical neurons and in 4A, ERK in SH-SY5Y cells. The presentation of the data in the results (and echoed in the discussion) writes of a "remarkably weaker response". The data in the blots demand more nuance. It seems that LRRK2 may potentiate a response to BDNF that in neurons is independent of LRRK2 kinase activity (as noted). This is more of a point of interpretation, but the words do not match the images.

      (4) Figure 4F/G shows an increase in PSD95 puncta per unit length in response to BDNF in mouse cortical neurons. The data do not show spine induction/dendritic spine density/or spine morphogenesis as suggested in the accompanying text (page 8). Since the neurons are filled/express gfp, spine density could be added or spines having PSD95 puncta. However, the data as reported would be expected to reflect spine and shaft PSDs and could also include some nonsynaptic sites.

      (5) Experimental details are missing that are needed to fully interpret the data. There are no electron microscopy methods outside of the figure legend. And for this and most other microscopy-based data, there are few to no descriptions of what cells/sites were sampled, how many sites were sampled, and how regions/cells were chosen. For some experiments (like Figure 5D), some detail is provided in the legend (20 segments from each mouse), but it is not clear how many neurons this represents, where in the striatum these neurons reside, etc. For confocal z-stacks, how thick are the optical sections and how thick is the stack? The methods suggest that data were analyzed as collapsed projections, but they cite Imaris, which usually uses volumes, so this is confusing. The guide (sgRNA) sequences that were used should be included. There is no mention of sex as a biological variable.

      (6) For Figures 1F, G, and E, how many experimental replicates are represented by blots that are shown? Graphs/statistics could be added to the supplement. For 1C and 1I, the ANOVA p-value should be added in the legend (in addition to the post hoc value provided).

      (7) Why choose 15 minutes of BDNF exposure for the mass spec experiments when the kinetics in Figure 1 show a peak at 5 mins?

      (8) The schematic in Figure 6A suggests that iPSCs were plated, differentiated, and cultured until about day 70 when they were used for recordings. But the methods suggest they were differentiated and then cryopreserved at day 30, and then replated and cultured for 40 more days. Please clarify if day 70 reflects time after re-plating (30+70) or total time in culture (70). If the latter, please add some notes about re-differentiation, etc.

      (9) When Figures 6B and 6C are compared it appears that mEPSC frequency may increase earlier in the LRRK2KO preps than in the WT preps since the values appear to be similar to WT + BDNF. In this light, BDNF treatment may have reached a ceiling in the LRRK2KO neurons.

      (10) Schematic data in Figures 5A and C and Figures 5B and E are too small to read/see the data.

    1. Reviewer #1 (Public Review):

      Amason et al. investigated the formation of granulomas in response to Chromobacterium violaceum infection, aiming to uncover the cellular mechanisms governing the granuloma response. They identify spatiotemporal gene expression of chemokines and receptors associated with the formation and clearance of granulomas, with a specific focus on those involved in immune trafficking. By analyzing the presence or absence of chemokine/receptor RNA expression, they infer the importance of immune cells in resolving infection. Despite observing increased expression of neutrophil-recruiting chemokines, treatment with reparixin (an inhibitor of CXCR1 and CXCR2) did not inhibit neutrophil recruitment during infection. Focusing on monocyte trafficking, they found that CCR2 knockout mice infected with C. violaceum were unable to form granulomas, ultimately succumbing to infection.

      The spatial transcriptomics data presented in the figures could be considered a valuable resource if shared, with the potential for improved and clarified analyses. The primary conclusion of the paper, that C. violaceum infection in the liver cannot be contained without macrophages, would benefit from clarification.

      While the spatial transcriptomic data generated in the figures are interesting and valuable, they could benefit from additional information. The manual selection of regions of granulomas for analysis could use additional context - was the rest of the liver not sequenced, or excluded for other reasons? Including a healthy liver in the analysis could serve as a control for any lasting effects at the final time point of 21 days. Providing more context for the scalebars throughout the spatial analyses, such as whether the data are raw counts or normalized based on the number of reads per spatial spot, would be helpful for interpretation, as changes in expression could signal changes in the numbers of cells or changes in the gene expression of cells.

      In Figure 4, qualitative measurements are valuable, but having an idea of the raw data for a few of the pursued chemokines/receptors would aid interpretation. It would also be beneficial to clarify whether the reported values are across all clusters and consider focusing on clusters with the greatest change in expression. Figures 5E and F would benefit from clarification regarding the x-axis units and whether the expression levels are summed across all clusters for each time point. Additionally, information on the sequencing depth of the samples would be helpful, particularly as shallow sequencing of RNA can result in poor capture of low-expression transcripts.

      Regarding the conclusion of the essentiality of macrophages in granuloma formation, it may be prudent to further investigate the role of macrophages versus CCR2. Analyzing total cell counts in the liver after infection could provide insight into whether the decrease in the fraction of macrophages is due to decreased numbers or infiltration of other cell types. Consideration of experiments deleting macrophages directly, instead of CCR2, could provide more definitive evidence of the necessity of macrophage migration in containing infections.

    2. Reviewer #2 (Public Review):

      Summary:

      In this study, Amason et al employ spatial transcriptomics and intervention studies to probe the spatial and temporal dynamics of chemokines and their receptors and their influence on cellular dynamics in C. violaceum granulomas. As a result of their spatial transcriptomic analysis, the authors narrow in on the contribution of neutrophil- and monocyte-recruiting pathways to host response. This results in the observation that monocyte recruitment is critical for granuloma formation and infection control, while neutrophil recruitment via CXCR2 may be dispensable.

      Strengths:

      Since C. violaceum is a self-limiting granulomatous infection, it makes an excellent case study for 'successful' granulomatous inflammation. This stands in contrast to chronic, unproductive granulomas that can occur during M. tuberculosis infection, sarcoidosis, and other granulomatous conditions, infectious or otherwise. Given the short duration of C. violaceum infection, this study specifically highlights the importance of innate immune responses in granulomas.

      Another strength of this study is the temporal analysis. This proves to be important when considering the spatial distribution and timing of cellular recruitment. For example, the authors observe that the intensity and distribution of neutrophil- and monocyte-recruiting chemokines vary substantially across infection time and correlate well with their previous study of cellular dynamics in C. violaceum granulomas.

      The intervention studies done in the last part of the paper bolster the relevance of the authors' focus on chemokines. The authors provide important negative data demonstrating the null effect of CXCR1/2 inhibition on neutrophil recruitment during C. violaceum infection. That said, the authors' difficulty with solubilizing reparixin in PBS is an important technical consideration given the negative result. On the other hand, monocyte recruitment via CCR2 proves to be indispensable for granuloma formation and infection control. I would hesitate to agree with the authors' interpretation that their data proves macrophages are serving as a physical barrier from the uninvolved liver. It is possible and likely that they are contributing to bacterial control through direct immunological activity and not simply as a structural barrier.

      Weaknesses:

      There are several shortcomings that limit the impact of this study. The first is that the cohort size is very limited. While the transcriptomic data is rich, the authors analyze just one tissue from one animal per time point. This assumes that the selected individual will have a representative lesion and prevents any analysis of inter-individual variability. Granulomas in other infectious diseases, such as schistosomiasis and tuberculosis, are very heterogeneous, both between and within individuals. It will be difficult to assert how broadly generalizable the transcriptomic features are to other C. violaceum granulomas. Furthermore, this undermines any opportunity for statistical testing of features between time points, limiting the potential value of the temporal data.

      Another caveat to these data is the limited or incompletely informative data analysis. The authors use Visium in a more targeted manner to interrogate certain chemokines and cytokines. While this is a great biological avenue, it would be beneficial to see more general analyses considering Visum captures the entire transcriptome. Some important questions that are left unanswered from this study are:

      What major genes defined each spatial cluster?

      What were the top differentially expressed genes across time points of infection?

      Did the authors choose to focus on chemokines/receptors purely from a hypothesis perspective or did chemokines represent a major signature in the transcriptomic differences across time points?

      In addition to the absence of deep characterization of the spatial transcriptomic data, the study lacks sufficient quantitative analysis to back up the authors' qualitative assessments. Furthermore, the authors are underutilizing the spatial information provided by Visium with no spatial analysis conducted to quantify the patterning of expression patterns or spatial correlation between factors.

      Impact:

      The author's analysis helps highlight the chemokine profiles of protective, yet host protective granulomas. As the authors comment on in their discussion, these findings have important similarities and differences with other notable granulomatous conditions, such as tuberculosis. Beyond the relevance to C. violaceum infection, these data can help inform studies of other types of granulomas and hone candidate strategies for host-directed therapy strategies.

    1. Reviewer #1 (Public Review):

      Pineda et al investigate the association of the hypothesis that Dux4, an embryonic transcription factor, expression in tumor cells is associated with immune evasion and resistance to immunotherapy. They analyze existing cohorts of bulk RNAseq sequenced tumors across cancer types to identify Dux4 expression and association with survival. They find that Dux4 expression is detected in a higher proportion of metastatic tumors compared to primary tumors, is associated with decreased immune infiltrate and a variety of immune metrics and previously nominated immune signatures, and do an in depth evaluation of a cohort of metastatic urothelial cell carcinoma, finding that Dux4 expression is associated with a more immunodeficient tumor microenvironment (desert or excluded microenvironment) and worse survival in this aPDL1 treated cohort. They then find that Dux4 expression is a major independent predictor of survival in this cohort using different types of survival analyses (KM, Cox PH, and random survival forests). With prior existing biological data supporting the hypothesis (in prior work, the senior author has demonstrated Dux4 expression causally suppresses MHC-I expression in interferon-gamma treated cell lines), the current work links Dux4 expression with less immune activity in clinical tumor samples and with survival in ICI treated urothelial carcinomas, and demonstrates that Dux4 expression provides independent information towards survival including other molecular and clinical characteristics (TMB, ECOG PS as the other strongest markers), and provides interesting resolution on landmark analyses with TMB and Dux4 expression providing greater informativeness at later survival landmarks (e.g. 1 year and later), while ECOG PS has strong informativeness already at earlier time points. This work provides impetus towards more mechanistic and functional dissection of the mechanism of Dux4-associated changes with the tumor microenvironment (e.g. in vivo mouse studies) as well as potential interventional studies (e.g. Dux4 as a target in combination therapies). What the work does not provide is additional resolution on the mechanism of how Dux4 may be associated with a more immunodeficient microenvironment.

      The conclusions are generally well supported, but there are issues that would benefit from clarification and extension:

      - The finding that Dux4 expression is detected in a higher proportion of metastatic tumors and at higher levels compared to TCGA samples (Fig 1BC) is striking. However, at least for one tumor type (melanoma), the TCGA cohort is comprised of mostly locoregional metastatic (n=81 primary and 367 metastatic tumors in the PanCan Atlas). Since there are annotations for primary and (locoregional) metastatic samples in TCGA, an analysis of the primary vs. locoregional metastasis vs distant metastatic samples seems reasonable and likely informative. The analysis of tumors with matched FFPE and flash frozen samples with hybrid probe capture and polyA sequencing, respectively is a nice validation to show that the difference in Dux4 expression is not due to differences in preservation of starting material/sequencing in the metastatic samples vs TCGA samples (S1BC).<br /> - The findings that Dux4 expression in the metastatic urothelial carcinoma setting is associated with a more immunodeficient microenvironment (Figure 2) is clear and unambiguous using multiple lines of data and analyses (bulk RNAseq, DUX4-positive vs DUX4-negative tumors, different immune cell and cytokine signatures; IHC showing an association with immune deserts and immune excluded phenotypes). However, this is an association and does not demonstrate causality.<br /> - The survival analyses (Fig 3,4,5) show fairly convincingly that Dux4 provide independent predictive information beyond clinical variables and TMB towards survival in the aPDL1 treated metastatic urothelial carcinoma cohort. However, the choice to split the cohort into Dux4 negative (defined as < 0.25 TPM) and Dux4 positive (> 1 TPM) while excluding a large number of patients (n=126 pts) that fall in between has significant impact on the rigor of conclusions. This would benefit from showing all the data (e.g. including the 3rd group of in-betweens in the survival analyses as a separate group).<br /> - The authors demonstrate that adding Dux4 to clinical markers and TMB results in an improved predictive model for survival, but there are a few questions regarding this model as a clinical biomarker<br /> o Is Dux4 expression better than other correlated immune signatures/markers (e.g. interferon gamma, T effector signature, overall immune infiltrate) in providing additional information?<br /> - The use of random survival forests to quantify the (predictive) marginal effect of Dux4+ vs Dux4- expression on survival in a non-parametric model as well as shed light on association with survival at different landmark times using Shapley values is quite interesting and well conducted.

    2. Reviewer #2 (Public Review):

      Summary:

      This article takes an expansive look at the potential role of DUX4 in cancer treatment and prognosis, including its correlation with other key biomarkers, the potential for cancer to be resistant to treatment, and risk prediction.

      Strengths:

      The primary strength of this work is the breadth of the analyses. The authors have linked DUX4 to not just one but multiple points in the trajectory of cancer, which increases the face validity of their conclusion that DUX4 is meaningfully related to the course of a cancer as well as the prognosis for a patient.

      Statistically, the authors have taken care to properly validate their findings using appropriate bootstrapping and testing strategies.

      Weaknesses:

      Several weaknesses are noted. First, there is little-to-no description of the underlying sample population. It is only stated that "several large cohorts of patients with different metastatic cancers" were analyzed, and that a cohort of patients with advanced urothelial cancer was used for estimating associations with clinical outcomes. Lacking is information on the sampling mechanism, inclusion/exclusion criteria, treatment modalities, the definition of 'time = 0', the number of events observed, or even the sample size. Knowledge about the underlying study design would help explain some counterintuitive results, e.g. that the hazard of death among patients with Stage IV cancer is half that of those with Stage I cancer (Table 1); presumably this is not because Stage IV is actually protective but rather an artifact of the sampling scheme for these data. Second, the definition of negative versus positive DUX4 expression varies throughout the paper. In Figure 2B, Figure 3A, and Figure 3C, it is defined as >1 TPM vs. <= 1 TPM; in Figure 4A and Figure 5A, it is defined as >1 TPM vs. < 0.25 TPM; in Figure S1C it is partitioned into four groups, with boundaries defined at 0.25 TPM, 1 TPM, and 5 TPM. If categorization is needed, a rationale should be provided (ideally prospectively and not based upon the observed data, so as to avoid the perception of forking paths analyses), and it should be consistently applied. Third and finally, data seem to be occasionally excluded without rationale. For example, as mentioned above, the Cox model presented in Figure 4A seems to exclude all patients with DUX4 TPM between 0.25 and 1. Figure 3C excludes patients with TMB in the lowest quartile (although the decision was ostensibly to control for TMB confounding, there are more appropriate ways to do so that don't result in loss of data, e.g. a stratified KM plot). Excluding patients based upon a particular region of the covariate space makes interpreting the resulting model awkward.

    1. Reviewer #1 (Public Review):

      The authors have made a novel and important effort to distinguish and include different sources of active deformations for fitting C elegans embryo development: cyclic muscle contractions and actomyosion circumferential stresses. The combination and synchronisation of both contributions are, according to the model, responsible for different elongation rates, and can induce bending and torsion deformations, which are a priori not expected from purely contractile forces. The model can be applied to other growth processes in initially cylindrical shapes.

      The tilt of the fibers is an important assumption of the model. However, fiber direction in Figure 3B is not fully clear for explaining the tilting. The fiber in 3B has not very much in common with the fibers in the color part of the figure. Also, is vector m supposed to be tangent to the fiber? In the figure does not seem to be so. It should be expected that alpha is a consequence of the deformation, not as an input parameter, as it seems in the tests of Figure 6A. How is the value of alpha chosen? According to Figure 6, torsion is expected for alpha>0, but for beta=pi/2 and alpha>0 no torsion may be obtained. In fact, it seems that torsion should appear when cos(beta)*sin(alpha)>0. As a consequence, value of beta should be given in Figure 6. Can the amount of torsion be tested as a function of alpha and beta?

      The transfer of energy and deformation is a very interesting aspect of the paper, and also crucial for the model and predicting elongation. However, the modelling of this transfer remains very obscure and only explained in the Appendix. Some more details on how the transfer is selected should be given in the main text. Can the transfer of energy interpreted as a change of the relaxed reference configuration? Once a ratio of the energy transferred is fixed, the assumption on elongation distribution should be stated. (Uniformly? ) The authors should also define in the main text the factor g_a1, and explain how this value is computed from condition W_c=W_r .

      Given the convoluted shape of the embryo in the egg, contact may be a crucial mechanism for determining growth and torsion. The model does not include this contact, and this limitation should be reflected in the article.

      Minor comment:<br /> -Line 300: "we determine the optimal values for the activation parameters". the optimal with respect to which objective? Norm of difference between experimental and computational displacements? How this is quantified needs to be specified.

    2. Reviewer #2 (Public Review):

      Summary:

      During C. elegans development, embryos undergo elongation of their body axis in absence of cell proliferation or growth. This process relies in an essential way on periodic contractions of two pairs muscles that extend along the embryo's main axis. How contraction can lead to extension along the same direction is unknown.

      To address this question, the authors use a continuum description of a multicomponent elastic solid. The various components are the interior of the animal, the muscles, and the epidermis. The different components form separate compartments and are described as hyperelastic solids with different shear moduli. For simplicity, a cylindrical geometry is adopted. The authors consider first the early elongation phase, which is driven by contraction of the epidermis, and then late elongation, where contraction of the muscles injects elastic energy into the system, which is then transferred into elongation. The authors get elongation that can be successfully fitted to the elongation dynamics of wild type worms and two mutant strains.

      Strengths:

      The work proposes a physical mechanism underlying a puzzling biological phenomenon. The framework developed by the authors could be used to explain phenomena in other organisms and could be exploited in the design of soft robots.

      Weaknesses:

      (1) The manuscript is hard to read without being very familiar with continuum descriptions of elastic media. This might make the work difficult to access for biologists. This is a real pity because the findings are potentially of great interest to developmental biologists and engineers alike.

      (2) The discussion of the worm's mechanical properties could go deeper. The authors hardly justify their assumptions.

    1. Reviewer #1 (Public Review):

      Summary:

      This study presents careful biochemical experiments to understand the relationship between LRRK2 GTP hydrolysis parameters and LRRK2 kinase activity. The authors report that incubation of LRRK2 with ATP increases the KM for GTP and decreases the kcat. From this they suppose an autophosphorylation process is responsible for enzyme inhibition. LRRK2 T1343A showed no change, consistent with it needing to be phosphorylated to explain the changes in G-domain properties. The authors propose that phosphorylation of T1343 inhibits kinase activity and influences monomer-dimer transitions.

      Strengths:

      Strengths of the work are the very careful biochemical analyses and interesting result for wild type LRRK2.

      Weaknesses:

      The conclusions related to involvement of a monomer-dimer transition are to this reviewer, premature and an independent method needs to be utilized to bolster this aspect of the story.

    2. Reviewer #2 (Public Review):

      As discussed in the original review, this manuscript is an important contribution to a mechanistic understanding of LRRK2 kinase. Kinetic parameters for the GTPase activity of the ROC domain have been determined in the absence/presence of kinase activity. A feedback mechanism from the kinase domain to GTP/GDP hydrolysis by the ROC domain is convincingly demonstrated through these kinetic analyses. However, a regulatory mechanism directly linking the T1343 phospho-site and a monomer/dimer equilibrium is not fully supported. The T1343A mutant has reduced catalytic activity and can form similar levels of dimer as WT. The revised manuscript does point out that other regulatory mechanisms can also play a role in kinase activity and GTP/GDP hydrolysis (Discussion section). The environmental context in cells cannot be captured from the kinetic assays performed in this manuscript, and the introduction contains some citations regarding these regulatory factors. This is not a criticism, the detailed kinetics here are rigorous, but it is simply a limitation of the approach. Caveats concerning effects of membrane localization, Rab/14-3-3 proteins, WD40 domain oligomers, etc... should be given more prominence than a brief (and vague) allusion to 'allosteric targeting' near the end of the Discussion.

      Specific comments

      (1) The revised version is better organized with respect to the significance of monomer/dimer equilibrium and the relevance of the GTP-binding region of ROC domain that encompasses the T1343 phospho-site. The relevance of monomers/dimers of LRRK2 from previous studies is better articulated and readers are able to follow the reasoning for the various mutations.

      (2) As a suggestion I would change the following on page 6 to clarify for readers:<br /> "...would show no change in kcat and KM values upon in vitro ATP treatment" to:<br /> "...would show no change in kcat and KM values for GTP hydrolysis upon in vitro ATP treatment"

      (3) The levels of dimer in WT (+ATP) and T1343A (+/- ATP) are the same, about 40-45%. These data are cited when the authors state that ATP-induced monomerization is 'abolished' (page 6). My suggestion is to re-phrase this conclusion for consistency with data (Fig 5). For example, one can state that 'ATP incubation does not affect the percentage of dimer for the T1343A variant of LRRK2'. This would be similar to the authors' description of these data on page 8 - 'no difference in dimer formation upon ATP treatment'.

    1. Reviewer #1 (Public Review):

      The author studies a family of models for heritable epigenetic information, with a focus on enumerating and classifying different possible architectures. The key aspects of the paper are:

      - Enumerate all 'heritable' architectures for up-to 4 constituents.<br /> - A study of whether permanent ("genetic") or transient ("epigenetic") perturbations lead to heritable changes<br /> - Enumerated the connectivity of the "sequence space" formed by these heritable architectures<br /> - Incorporating stochasticity, the authors explore stability to noise (transient perturbations)<br /> - A connection is made with experimental results on C elegans.

      The study is timely, as there is a renewed interest in the last decade in non-genetic, heritable heterogeneity (e.g., from single-cell transcriptomics). Consequently, there is a need for a theoretical understanding of the constraints on such systems. There are some excellent aspects of this study: for instance, the attention paid to how one architecture "mutates" into another. Unfortunately, the manuscript as a whole does not succeed in formalising nor addressing any particular open questions in the field. Aside from issues in presentation and modelling choices (detailed below), it would benefit greatly from a more systematic approach rather than the vignettes presented.

      ## Terminology

      The author introduces a terminology for networks of interacting species in terms of "entities" and "sensors" -- the former being nodes of a graph, and the latter being those nodes that receive inputs from other nodes. In the language of directed graphs, "entities" would seem to correspond to vertices, and "sensors" those vertices with positive indegree and outdegree. Unfortunately, the added benefit of redefining accepted terminology from the study of graphs and networks is not clear.

      ## Model

      The model seems to suddenly change from Figure 4 onwards. While the results presented here have at least some attempt at classification or statistical rigour (i.e. Fig 4 D), there are suddenly three values associated with each entity ("property step, active fraction, and number"). Furthermore, the system suddenly appears to be stochastic. The reader is left unsure what has happened, especially after having made the effort to deduce the model as it was in Figs 1 through 3. No respite is to be found in the SI, either, where this new stochastic model should have been described in sufficient detail to allow one to reproduce the simulation.

      ## Perturbations

      Inspired especially by experimental manipulations such as RNAi or mutagenesis, the author studies whether such perturbations can lead to a heritable change in network output. While this is naturally the case for permanent changes (such as mutagenesis), the author gives convincing examples of cases in which transient perturbations lead to heritable changes. Presumably, this is due the the underlying multistability of many networks, in which a perturbation can pop the system from one attractor to another.

      Unfortunately, there appears to be no attempt at a systematic study of outcomes, nor a classification of when a particular behaviour is to be expected. Instead, there is a long and difficult-to-read description of numerical results that appear to have been sampled at random (in terms of both the architecture and parameter regime chosen). The main result here appears to be that "genetic" (permanent) and "epigenetic" (transient) perturbations can differ from each other -- and that architectures that share a response to genetic perturbation need not behave the same under an epigenetic one. This is neither surprising (in which case even illustrative evidence would have sufficed) nor is it explored with statistical or combinatorial rigour (e.g. how easy is it to mistake one architecture for another? What fraction share a response to a particular perturbation?)

      As an additional comment, many of the results here are presented as depending on the topology of the network. However, each network is specified by many kinetic constants, and there is no attempt to consider the robustness of results to changes in parameters.

      ## DNA analogy

      At two points, the author makes a comparison between genetic information (i.e. DNA) and epigenetic information as determined by these heritable regulatory architectures. The two claims the author makes are that (i) heritable architectures are capable of transmitting "more heritable information" than genetic sequences, and (ii) that, unlike DNA, the connectivity (in the sense of mutations) between heritable architectures is sparse and uneven (i.e. some architectures are better connected than others).

      In both cases, the claim is somewhat tenuous -- in essence, it seems an unfair comparison to consider the basic epigenetic unit to be an "entity" (e.g., an entire transcription factor gene product, or an organelle), while the basic genetic unit is taken to be a single base-pair. The situation is somewhat different if the relevant comparison was the typical size of a gene (e.g., 1 kb).

    1. Reviewer #1 (Public Review):

      Summary:

      This describes the molecular identity of the intermediate status of cranial neural crest cells (NCCs) during the initial delamination process. Taking advantage of single-cell RNA seq, the authors identify new populations of cells during EMT characterized by a specific set of gene expressions, including Dlc1. Promigratory cranial NCCs differentiate through different trajectories depending on their cell cycle phases but converge into a common progenitor, then differentiate into mesenchymal cells expressing region-specific genes.

      Strengths:

      Single-cell RNA seq data convincingly support what the authors claim. This is the first time to identify intermediate states between premigratory and migratory cranial NCCs. Silencing one of the marker genes, Dlc1, reduces the migratory activity of cranial NCCs. These findings deepen our understanding of the mechanism of EMT in general.

      Comments on revised version:

      Weaknesses:

      None after substantial revision.

    2. Reviewer #2 (Public Review):

      Zhao et al., focus on mechanisms through which cells convert from epithelium to mesenchyme and become migratory. This phenomenon of epithelial-to-mesenchymal transition (EMT) occurs during both embryonic development and cancer progression. During cancer progression, EMT seemingly includes cells at intermediate states as defined by the combinatorial expression of epithelial and mesenchymal markers. But the importance of these markers and the role of these intermediate states remains unclear. Moreover, whether EMT during development also involves equivalent intermediate cell states is not known. To address this gap in knowledge, the authors devise a strategy to identify and characterize changes that an embryonic population of cells called the cranial neural crest undergo as they delaminate from the neuroepithelium and become a highly migratory population of mesenchymal cells that ultimately give rise to a broad range of derivatives.

      To isolate and study the neural crest, the authors use embryos collected at E8.5 from two transgenic mouse lines. Wnt1-Cre;RosaeYFP labels Wnt1-positive neuroepithelial cells in the dorsolateral neural plate, which includes pre-migratory neural crest that reside in the dorsal neuroectoderm and neural plate border before induction (as well as some other lineages). Mef2c-F10N-LacZ leverages a neural crest cell-specific enhancer of Mef2c to control LacZ expression in predominantly migratory neural crest. This dual genetic approach that allows the authors to distinguish and compare pre-migratory and migratory neural crest cells is a strength of the work.

      To assay for the differential expression of genes involved in the EMT and migration of cranial neural crest, the authors perform single cell RNA sequencing (scRNA-seq) using current methods. A strength is a large sample size per mouse line, and relatively high numbers of single cells analyzed. The authors identify six major cell/tissue types present in mouse E8.5 cranial tissues using known markers, which they then segregate into a cranial neural crest cluster using a well-reasoned bioinformatic strategy. The cranial neural crest cluster contains pre-migratory and migratory cells that they partition further into five subclusters and then characterize using the differential expression and combinatorial patterns of neural crest specifier genes, markers of pre-migratory neural crest, markers of early versus late migratory neural crest, markers of undifferentiated versus differentiated neural crest, tissue-specific markers, and region-specific markers. One weakness is that there is little attempt to map potential novel genes and/or pathways that also distinguish these clusters.

      The authors then go on to subdivide the five cranial neural crest subclusters into almost two dozen smaller subclusters, again using the combinatorial expression of known markers (e.g., neural crest genes, cell junction genes, and cell cycle genes). A weakness is that the marker analysis and accompanying interpretation of the results relies heavily on the purported roles of different genes as described in the published work of others, which potentially introduces some untested assumptions and a bit of hand-waving into the study. Moreover, the limited correlation between mRNA and protein abundance for cell cycle markers is well documented in the literature but the authors rely heavily on gene expression to determine cell cycle status. Even though the authors add a compelling Edu/pHH3 double-labeling experiment and cell cycle inhibition studies, the work would be strengthened by including some analysis of protein expression to see if the cell cycle correlations hold up. Nonetheless, the subcluster and cell cycle analyses lead the authors to conclude that there are a series of intermediate cell states between neural crest EMT and delamination, and that cell cycle regulation is a defining feature and necessary component of those states. These novel findings are generally well supported by the data.

      To test if there are spatiotemporal differences in the localization of neural crest cells during EMT in vivo, the authors apply a cutting-edge technique called signal amplification by exchange reaction for multiplexed fluorescent in situ hybridization (SABER-FISH), which they validate using standard in situ hybridization. The authors select specific marker genes that seem justified based on their scRNA-seq dataset, and they generate a series of convincing images and quantitative data that add valuable depth to the story.

      As a functional test of their hypothesis that one of the genes indicative of an EMT intermediate stage (i.e., Dlc1) is essential for neural crest migration, the authors use a lentivirus-mediated knockdown strategy. A strength is that the authors include appropriate scramble and cell death controls as part of their experimental design.

      The authors use Sox10 as a marker to count neural crest cells, but Sox10 may only label a subset of neural crest cells and thus some unaffected lineages may not have been counted. Although the data are persuasive, a second marker for counting neural crest cells following knockdown would make the analysis more robust.

      Overall, this is a first-rate study with many more strengths than weaknesses. The authors generate high quality data, and their interpretations are reasonable and balanced. Another strength is the writing, which is clear and well organized, and the figures (including supplemental), which are excellent and provide unambiguous visualization of some very complex data sets. The methods are state-of the art and are effectively executed, and they will be useful to the broader cell and developmental biology community. The work contains well-substantiated findings and supports the conclusion that EMT is a highly dynamic, multi-step process, which was previously thought to be more-or-less binary. Such findings will alter the way the field thinks about EMT in neural crest and the work will likely serve as an important example alongside cancer metastasis.

    3. Reviewer #3 (Public Review):

      Summary:

      Zhao et al. address the question of whether intermediate states of the epithelial-to-mesenchymal transition (EMT) exist in a natural developmental context as well as in cancer cells. This is important not only for our understanding of these developmental systems but also for their development as resources for new anti-cancer approaches. Guided by single-cell RNA sequencing analysis of delaminating mouse cranial neural crest cells, they identify two distinct populations with transcriptional signatures intermediate between neuroepithelial progenitors and migrating crest. Both clusters are also spatially intermediate and are actively cycling, with one in S-phase and one in G2/M. They show that blocking progression through S phase prior to the onset of delamination and knockdown of intermediate state marker Dlc1 both reduce the number of migratory cells that have completed EMT. Overall, the work provides a modern take and new insights into the classical developmental process of neural crest delamination.

      Strengths:

      • Deep analysis of the scRNAseq dataset revealed previously unappreciated cell populations intermediate between premigratory and migratory crest.<br /> • The observation that delaminating/intermediate neural crest cells appear to be in S or G2/M phase is interesting and worth reporting, though the ultimate significance remains unclear, given that they do not make distinct derivatives depending on their cycle state.<br /> • The authors employ new methods for multiplex spatial imaging to more accurately define their populations of interest and their relative positions.<br /> • The authors present evidence that intermediate state gene Dlc1 (a Rho GAP) is not just a marker but functionally required for neural crest delamination in mouse, as previously shown in chicken.

      Weaknesses:

      • Similar experiments involving blockade of cell cycle progression and Dlc1 dose manipulation were previously performed in chick models, as noted in the discussion. The newly-defined intermediate states give added context to the results, but they are not entirely novel.

    1. Reviewer #1 (Public Review):

      In this manuscript, the authors report a molecular mechanism for recruiting syntaxin 17 (Syn17) to the closed autophagosomes through the charge interaction between enriched PI4P and the C-terminal region of Syn17. How to precisely control the location and conformation of proteins is critical for maintaining autophagic flux. Particularly, the recruitment of Syn17 to autophagosomes remains unclear. In this paper, the author describes a simple lipid-protein interaction model beyond previous studies focusing on protein-protein interactions. This represents conceptual advances.

    2. Reviewer #2 (Public Review):

      Summary:

      Syntaxin17 (STX17) is a SNARE protein that is recruited to mature (i.e., closed) autophagosomes, but not to immature (i.e., unclosed) ones, and mediates the autophagosome-lysosome fusion. How STX17 recognizes the mature autophagosome is an unresolved interesting question in the autophagy field. Shinoda and colleagues set out to answer this question by focusing on the C-terminal domain of STX17 and found that PI4P is a strong candidate that causes the STX17 recruitment to the autophagosome.

      Strengths:

      The main findings are: 1) Rich positive charges in the C-terminal domain of STX17 are sufficient for the recruitment to the mature autophagosome; 2) Fluorescence charge sensors of different strengths suggest that autophagic membranes have negative charges and the charge increases as they mature; 3) Among a battery of fluorescence biosensors, only PI4P-binding biosensors distribute to the mature autophagosome; 4) STX17 bound to isolated autophagosomes is released by treatment with Sac1 phosphatase; 5) By dynamic molecular simulation, STX17 TM is shown to be inserted to a membrane containing PI4P but not to a membrane without it. These results indicate that PI4P is a strong candidate that STX17 binds to in the autophagosome.

      Weaknesses:

      • It was not answered whether PI4P is crucial for the STX17 recruitment in cells because manipulation of the PI4P content in autophagic membranes was not successful for unknown reasons.<br /> • The question that the authors posed in the beginning, i.e., why is STX17 recruited to the mature (closed) autophagosome but not to immature autophagic membranes, was not answered. The authors speculate that the seemingly gradual increase of negative charges in autophagic membranes is caused by an increase in PI4P. However, this was not supported by the PI4P fluorescence biosensor experiment that showed their distribution to the mature autophagosome only. Here, there are at least two possibilities: 1) The increase of negative charges in immature autophagic membranes is derived from PI4P. However the fluorescence biosensors do not bind there for some reason; for example, they are not sensitive enough to recognize PI4P until it reaches a certain level, or simply, their binding does not occur in a quantitative manner. 2) The negative charge in immature membranes is not derived from PI4P, and PI4P is generated abundantly only after autophagosomes are closed. In either case, it is not easy to explain why STX17 is recruited to the mature autophagosome only. For the first scenario, it is not clear how the PI4P synthesis is regulated so that it reaches a sufficient level only after the membrane closure. In the second case, the mechanism that produces PI4P only after the autophagosome closure needs to be elucidated (so, in this case, the question of the temporal regulation issue remains the same).

    3. Reviewer #3 (Public Review):

      Summary:

      In this study, the authors set out to address the question of how the SNARE protein Syntaxin 17 senses autophagosome maturation by being recruited to autophagosomal membranes only once autophagosome formation and sealing is complete. The authors discover that the C-terminal region of Syntaxin 17 is essential for its sensing mechanism that involves two transmembrane domains and a positively charged region. The authors discover that the lipid PI4P is highly enriched in mature autophagosomes and that electrostatic interaction with Syntaxin 17's positively charged region with PI4P drives recruitment specifically to mature autophagosomes. The temporal basis for PI4P enrichment and Syntaxin 17 recruitment to ensure that unsealed autophagosomes do not fuse with lysosomes is a very interesting and important discovery. Overall, the data are clear and convincing, with the study providing important mechanistic insights that will be of broad interest to the autophagy field, and also to cell biologists interested in phosphoinositide lipid biology. The author's discovery also provides an opportunity for future research in which Syntaxin 17's c-terminal region could be used to target factors of interest to mature autophagosomes.

      Strengths:

      The study combines clear and convincing cell biology data with in vitro approaches to show how Syntaxin 17 is recruited to mature autophagosomes. The authors take a methodical approach to narrow down the critical regions within Syntaxin 17 required for recruitment and use a variety of biosensors to show that PI4P is enriched on mature autophagosomes.

      Weaknesses:

      There are no major weaknesses, overall the work is highly convincing. It would have been beneficial if the authors could have shown whether altering PI4P levels would affect Syntaxin 17 recruitment. However, this is understandably a challenging experiment to undertake and the authors outlined their various attempts to tackle this question.

    1. Reviewer #1 (Public Review):

      The authors investigated how global brain activity varied during reward-based motor learning. During early learning, they found increased covariance between the sensorimotor and dorsal attention networks, coupled with reduced covariance between the sensorimotor and default mode networks; during late learning, they found the opposite pattern. Individual learning performance varied only with changes in the dorsal attention network. The authors certainly used a wide variety of valuable, state-of-the-art techniques to interrogate whole-brain networks and extract the key components of learning behavior. However, the findings are incomplete, tempered by potential confounds in the experimental design. As such, the underlying claim regarding how these networks jointly support reward-based motor learning is unclear.

    2. Reviewer #2 (Public Review):

      This useful investigation of learning-driven dynamics of cortical and some subcortical structures combines a novel in-scanner learning paradigm with interesting analysis approaches. The new task for reward-based motor learning is highly compelling and goes beyond the current state-of-the-art, but it is incomplete with respect to examining different signatures of learning, clarifying probed learning processes, and investigating changes in all relevant subcortical structures is incomplete and would benefit from more rigorous approaches. With the rationale and data presentation strengthened this paper would be of interest to neuroscientists working on motor control and reward-based learning.

    3. Reviewer #3 (Public Review):

      The manuscript of Nick and colleagues addresses the intriguing question of how brain connectivity evolves during reward-based motor learning. The concept of quantifying connectivity through changes in extraction and contraction across lower-dimensional manifolds is both novel and interesting and the presented results are clear and well-presented. Overall, the manuscript is a valuable addition to the field. The evidence supporting the presented findings is strong, though at times lacking rigorous statistical quantification. Nevertheless, there are several issues that require attention and clarification.

    1. Reviewer #1 (Public Review):

      Li et al report that upon traumatic brain injury (TBI), Pvr signalling in astrocytes activates the JNK pathway and up-regulates the expression of the well-known JNK target MMP1. The FACS sort astrocytes, and carry out RNAseq analysis, which identifies pvr as well as genes of the JNK pathway as particularly up-regulated after TBI. They use conventional genetics loss of function, gain of function and epistasis analysis with and without TBI to verify the involvement of the JNK-MMP1 signalling pathway downstream of PVR. They also show that blocking endocytosis prolongs the involvement of this pathway in the TBI response.

      The strengths are that multiple experiments are used to demonstrate that TBI in their hands damaged the BBB, induced apoptosis and increased MMP1 levels. The RNAseq analysis on FACS sorted astrocytes is nice and will be valuable to scientists beyond the confines of this paper. The functional genetic analysis is conventional, yet sound, and supports claims of JNK and MMP1 functioning downstream of Pvr in the TBI context.

      For this revised version the authors have removed all the unsupported claims. This renders their remaining claims more solid. However, it has resulted in the loss of important cellular aspects of the response to TBI, limiting the scope and value of the work.

      The main weakness is that novelty and insight are both rather limited. Others had previously published that both JNK signalling and MMP1 were activated upon injury, in multiple contexts (as well as the articles cited by the authors, they should also see Losada-Perez et al 2021). That Pvr can regulate JNK signalling was also known (Ishimaru et al 2004). The authors claim that the novelty was investigating injury responses in astrocytes in Drosophila. However, others had investigated injury responses by astrocytes in Drosophila before. It had been previously shown that astrocytes - defined as the Prospero+ neuropile glia, and also sharing evolutionary features with mammalian NG2 glia - respond to injury both in larval ventral nerve cords and in adult brains, where they proliferate regenerating glia and induce a neurogenic response (Kato et al 2011; Losada-Perez et al 2016; Harrison et al 2021; Simoes et al 2022). The authors argue that the novelty of the work is the investigation of the response of astrocytes to TBI. However, this is of somewhat limited scope. The authors mention that MMP1 regulates tissue remodelling, the inflammatory process and cancer. Exploring these functions further would have been an interesting addition, but the authors did not investigate what consequences the up-regulation of MMP1 after injury has in repair or regeneration processes.

      The statistical analysis is incorrect in places, and this could affect the validity of some claims.

      Altogether, this is an interesting and valuable addition to the repertoire of articles investigating neuron-glia communication and glial responses to injury in the Drosophila central nervous system (CNS). It is good and important to see this research area in Drosophila grow. This community together is building a compelling case for using Drosophila and its unparalleled powerful genetics to investigate nervous system injury, regeneration and repair, with important implications. Thus, this paper will be of interest to scientists investigating injury responses in the CNS using Drosophila, other model organisms (eg mice, fish) and humans.

    2. Reviewer #3 (Public Review):

      In this study, authors used the Drosophila model to characterize molecular details underlying traumatic brain injury (TBI). Authors used the transcriptomic analysis of astrocytes collected by FACS sorting of cells derived from Drosophila heads following brain injury and identified upregulation of multiple genes, such as Pvr receptor, Jun, Fos, and MMP1. Additional studies identified that Pvr positively activates AP-1 transciption factor (TF) complex consisting of Jun and Fos, of which activation leads to the induction of MMP1. Finally, authors found that disruption of endocytosis and endocytotic trafficking facilitates Pvr signaling and subsequently leads to induction of AP-1 and MMP1.

      Overall, this study provides important clues to understanding molecular mechanisms underlying TBI. The identified molecules linked to TBI in astrocytes could be potential targets for developing effective therapeutics. The obtained data from transcriptional profiling of astrocytes will be useful for future follow-up studies. The manuscript is well-organized and easy to read.

      However, the connection suggested by the authors between Pvr and AP-1, potentially mediated through the JNK pathway, lacks strong experimental support in my view. It's important to recognize that AP-1 activity is influenced by multiple upstream signaling pathways, not just the JNK pathway, which is the most well-characterized among them. Therefore, assuming that AP-1 transcriptional activity solely reflects the activity of the JNK pathway without additional direct evidence is unwarranted. To strengthen their argument, the study could benefit from direct evidence implicating the JNK pathway in linking Pvr to AP-1. This could be achieved through genetic studies involving mutants or transgenes targeting key components of the JNK pathway, such as Bsk and Hep, the Drosophila homologues of JNK and JNKK, respectively. Alternatively, employing p-JNK antibody-based techniques like Western blotting, while considering the potential challenges associated with p-JNK immunohistochemistry, could provide further validation. This important criticism regarding the molecular link between Pvr and AP-1 has been overlooked.

    1. Reviewer #1 (Public Review):

      Dasguta et al. have dissected the role of Sema7a in fine tuning of a sensory microcircuit in the posterior lateral line organ of zebrafish. They attempt to also outline the different roles of a secreted verses membrane-bound form of Sema7a in this process. Using genetic perturbations and axonal network analysis, the authors show that loss of both Sema7a isoforms causes abnormal axon terminal structure with more bare terminals and fewer loops in contact with presynaptic sensory hair cells. Further, they show that loss of Sema7a causes decreased number and size of both the pre- and post-synapse. Finally, they show that overexpression of the secreted form of Sema7a specifically can elicit axon terminal outgrowth to an ectopic Sema7a expressing cell. Together, the analysis of Sema7a loss of function and overexpression on axon arbor structure is fairly thorough and revealed a novel role for Sema7a in axon terminal structure. However, the connection between different isoforms of Sema7a and the axon arborization needs to be substantiated. Furthermore, the effect of loss of Sema7a on the presynaptic cell is not ruled out as a contributing factor to the synaptic and axon structure phenotypes. These issues weaken the claims made by the authors including the statement that they have identified dual roles for the GPI-anchored verses secreted forms of Sema7a on synapse formation and as a chemoattractant for axon arborization respectively.

    2. Reviewer #2 (Public Review):

      In this work, Dasgupta et al. investigates the role of Sema7a in the formation of peripheral sensory circuit in the lateral line system of zebrafish. They show that Sema7a protein is present during neuromast maturation and localized, in part, to the base of hair cells (HCs). This would be consistent with pre-synaptic Sema7a mediating formation and/or stabilization of the synapse. They use sema7a loss-of-function strain to show that lateral line sensory terminals display abnormal arborization. They provide highly quantitative analysis of the lateral line terminal arborization to show that a number of specific topological parameters are affected in mutants. Next, they ectopically express a secreted form of Sema7a to show that lateral line terminals can be ectopically attracted to the source. Finally, they also demonstrate that the synaptic assembly is impaired in the sema7a mutant. Overall, the data are of high quality and properly controlled. The availability of Sema7a antibody is a big plus, as it allows to address the endogenous protein localization as well to show the signal absence in the sema7a mutant. The quantification of the arbor topology should be useful to people in the field who are looking at the lateral line as well as other axonal terminals. I think some results are overinterpreted though. The authors state: "Our findings demonstrate that Sema7A functions both as a juxtracrine and as a secreted cue to pattern neural circuitry during sensory organ development." However, they have not actually demonstrated which isoform functions in HCs (also see comments below). In addition, they have to be careful in interpreting their topology analysis, as they cannot separate individual axons. Thus, such analysis can generate artifacts. They can perform additional experiments to address these issues or adjust their interpretations.