Reviewer #1 (Public Review):

This manuscript describes identification of influential organisms on rice growth and an attempt of validation. The analysis of eDNA on rice pot and mimic field provides rice growth promoting organisms. This approach is novel for plant ecology field. However current results did not fully support whether eDNA analysis-based detection of influencing organism.

The strength of this manuscript is to attempt application of eDNA analysis-based plant growth differentiation. The weakness is too preliminary data and experimental set-up to make any conclusion. The trials of authors experiments are ideal. However, the process of data analysis did not meet certain level. For example, eDNA analysis of different time points on rice growth stages resulted two influential organisms for rice growth. Then they cultivate two species and applied rice seedlings. Without understanding of fitness and robustness, how we can know the effect of the two species on rice growth.

The authors did not check the fate of two species after introducing into rice. If this is true, it is difficult to link between the rice gene expression after treatments and the effectiveness of two species. I think the validation experiment in 2019 needs to be re-conducted.

As authorized gave answered, no strong rationale to select the two species was found. However, I insist that the method has enough novelty to present to general audiences.

Reviewer #2 (Public Review):

Most farming is done by subtracting or adding what people want based in nature. However, in nature, crops interact with various objects, and mostly we are unaware of their effects. In order to increase agricultural productivity, finding useful objects is very important. However, in an uncontrolled environment, it coexists with so many biological objects that it is very inefficient to verify them all experimentally. It is therefore necessary to develop an effective screening method to identify external environmental factors that can increase crop productivity. This study identified factors presumed to be important to crop growth based on metabarcoding analysis, field sampling, and non-linear analysis/information theory, and conducted a mesocosm experiment to verify them experimentally. In conclusion, the object proposed by the author did not increase rice yield, but rather rice growth rate.

The authors responded to my general concerns and all of my specific comments. The manuscript has significantly improved. The flow of aims and approaches is more understandable. Extra supplementary material -especially the visual ones, is useful.

I agree with the other reviewers that the study needs more data and evidence. However, this study aims to introduce ecological concepts and advanced statistical methods to the field. Also, most time series analyses require absolute abundance data, but the manuscript provides solutions for the sequencing data.

Reviewer #1 (Public Review):

Previous experimental studies demonstrated that membrane association drives avidity for several potent broadly HIV-neutralizing antibodies and its loss dramatically reduces neutralization. In this study, the authors present a tour de force analysis of molecular dynamics (MD) simulations that demonstrate how several HIV-neutralizing membrane-proximal external region (MPER)-targeting antibodies associate with a model lipid bilayer.

First, the authors compared how three MPER antibodies, 4E10, PGZL1, and 10E8, associated with model membranes, constructed with a lipid composition similar to the native virion. They found that the related antibodies 4E10 and PGZL1 strongly associate with a phospholipid near heavy chain loop 1, consistent with prior crystallographic studies. They also discovered that a previously unappreciated framework region between loops 2-3 in the 4E10/PGZL1 heavy chain contributes to membrane association. Simulations of 10E8, an antibody from a different lineage, revealed several differences from published X-ray structures. Namely, a phosphatidylcholine binding site was offset and includes significant interaction with a nearby framework region.

Next, the authors simulate another MPER-targeting antibody, LN01, with a model HIV membrane either containing or missing an MPER antigen fragment within. Of note, LN01 inserts more deeply into the membrane when the MPER antigen is present, supporting an energy balance between the lowest energy conformations of LN01, MPER, and the complex. Additional contacts and conformational restraints imposed by ectodomain regions of the envelope glycoprotein, however, remain unaddressed-the size of such simulations likely runs into technical limitations including sampling and compute time.

The authors next established course-grained (CG) MD simulations of the various antibodies with model membranes to study membrane embedding. These simulations facilitated greater sampling of different initial antibody geometries relative to membrane. Distinct geometries derived from CG simulations were then used to initialize all-atom MD simulations to study insertion in finer detail (e.g., phospholipid association), which largely recapitulate their earlier results, albeit with more unbiased sampling. The multiscale model of an initial CG study with broad geometric sampling, followed by all-atom MD, provides a generalized framework for such simulations.

Finally, the authors construct velocity pulling simulations to estimate the energetics of antibody membrane embedding. Using the multiscale modelling workflow to achieve greater geometric sampling, they demonstrate that their model reliably predicts lower association energetics for known mutations in 4E10 that disrupt lipid binding. However, the model does have limitations: namely, its ability to predict more subtle changes along a lineage-intermediate mutations that reduce lipid binding are indistinguishable from mutations that completely ablate lipid association. Thus, while large/binary differences in lipid affinity might be predictable, the use of this method as a generative model are likely more limited.

The MD simulations conducted throughout are rigorous and the analysis are extensive. However, given the large amount of data presented within the manuscript, the text would benefit from clearer subsections that delineate discrete mechanistic discoveries, particularly for experimentalists interested in antibody discovery and design. One area the paper does not address involves the polyreactivity associated with membrane binding antibodies-MD simulations and/or pulling velocity experiments with model membranes of different compositions, with and without model antigens, would be needed. Finally, given the challenges in initializing these simulations and their limitations, the text regarding their generalized use for discovery, rather than mechanism, could be toned down.

Overall, these analyses provide an important mechanistic characterization of how broadly neutralizing antibodies associate with lipids proximal to membrane-associated epitopes to drive neutralization.

Reviewer #2 (Public Review):

In this study, Maillie et al. have carried out a set of multiscale molecular dynamics simulations to investigate the interactions between the viral membrane and four broadly neutralizing antibodies that target the membrane proximal exposed region (MPER) of the HIV-1 envelope trimer. The simulation recapitulated in several cases the binding sites of lipid head groups that were observed experimentally by X-ray crystallography, as well as some new binding sites. These binding sites were further validated using a structural bioinformatics approach. Finally, steered molecular dynamics was used to measure the binding strength between the membrane and variants of the 4E10 and PGZL1 antibodies.

The conclusions from the paper are mostly well supported by the simulations, however, they remain very descriptive and the key findings should be better described and validated. In particular:

It has been shown that the lipid composition of HIV membrane is rich in cholesterol [1], which accounts for almost 50% molar ratio. The authors use a very different composition and should therefore provide a reference. It has been shown for 4E10 that the change in lipid composition affects dynamics of the binding. The robustness of the results to changes of the lipid composition should also be reported.

The real advantage of the multiscale approach (coarse grained (CG) simulation followed by a back-mapped all atom simulation) remains unclear. In most cases, the binding mode in the CG simulations seem to be an artifact.

The results reported in this study should be better compared to available experimental data. For example how does the approach angle compare to cryo-EM structure of the bnAbs engaging with the MPER region, e.g. [2-3]? How do these results from this study compare to previous molecular dynamics studies, e.g.[4-5]?

References<br /> 1. Brügger, Britta, et al. "The HIV lipidome: a raft with an unusual composition." Proceedings of the National Academy of Sciences 103.8 (2006): 2641-2646.<br /> 2. Rantalainen, Kimmo, et al. "HIV-1 envelope and MPER antibody structures in lipid assemblies." Cell Reports 31.4 (2020).<br /> 3. Yang, Shuang, et al. "Dynamic HIV-1 spike motion creates vulnerability for its membrane-bound tripod to antibody attack." Nature Communications 13.1 (2022): 6393.<br /> 4. Carravilla, Pablo, et al. "The bilayer collective properties govern the interaction of an HIV-1 antibody with the viral membrane." Biophysical Journal 118.1 (2020): 44-56.<br /> 5. Pinto, Dora, et al. "Structural basis for broad HIV-1 neutralization by the MPER-specific human broadly neutralizing antibody LN01." Cell host & microbe 26.5 (2019): 623-637.

Reviewer #1 (Public Review):

The authors of the manuscript "High-resolution kinetics of herbivore-induced plant volatile transfer reveal tightly clocked responses in neighboring plants" assessed the effects of herbivory-induced maize volatiles on receiver plants over a period of time in order to assess the dynamics of the responses of receiver plants. Different volatile compound classes were measured over a period of time using PTR-ToF-MS and GC-MS, under both natural light:dark conditions, and continuous light. They also measured gene expression of related genes as well as defense-related phytohormones. The effects of a secondary exposure to GLVs on primed receiver plants were also measured.

The paper addresses some interesting points, however, some questions arise regarding some of the methods employed. Firstly, I am wondering why VOCs (as measured by GC-MS) were not quantified. While I understand that quantification is time-consuming and requires more work, it allows for comparisons to be made between lines of the same species, as well as across other literature on the subject. As experiments with VOC dispensers were also used in this experiment, I find it even more baffling that the authors didn't confirm the concentration of the emission from the plants they used to make sure they matched. The references cited justifying the concentration used (saying it was within the range of GLVs emitted by their plants) to prepare the dispenser were for either a different variety of maize (delprim versus B73) or arabidopsis. Simply relying on the area under the curve and presenting results using arbitrary units is not enough for analyses like these.

With regards to the correlation analyses shown in Figure 6, the results presented in many of the correlation plots are not actually informative. By blindly reporting the correlation coefficient important trends are being ignored, as there are clearly either bimodal relationships (e.g. upper left panel, HAC/TMTT, HAC/MNT) or even stranger relationships (e.g. upper left panel, IND/SQT, IND/MNT) that are not being well explained by a correlation plot. It is not appropriate to discuss the correlation factors presented here and to draw such strong conclusions on emission kinetics. The comparison between plants under continuous light and normal light:dark conditions is interesting, but I think there are better ways to examine these relationships, for example, multivariate analysis might reveal some patterns.

In Figure 2, the elevated concentrations of beta-caryophyllene found in the control plants at 8h and 16.75h measurement timepoints are curious. Is this something that is commonly seen in B73? While there can be discrepancies between emissions and compounds actually present within leaf tissue, it is a little bit odd that such high levels of b-caryophyllene were found at these timepoints, however, this is not reflected in the PTR-ToF-MS measurements of sesquiterpenes. It would be beneficial to include an overview of the mechanism of production and storage of sesquiterpenes in maize leaves, which would clarify why high amounts were found only in the GC-MS analysis and not the PTR-ToF-MS analysis, which is a more sensitive analytical tool. It is possible that the amounts of b-caryophyllene present in the leaf are actually extremely low, however as the values are not given as a concentration but rather arbitrary units, it is not possible to tell. I would include a line explaining what is seen with b-caryophyllene. Additionally, it seems like the amounts of TMTT within the leaf are extraordinarily high (judging only by the au values given for scale), far higher than one would expect from maize.

Reviewer #2 (Public Review):

The exact dynamics of responses to volatiles from herbivore-attacked neighbouring plants have been little studied so far. Also, we still lack evidence of whether herbivore-induced plant volatiles (HIPVs) induce or prime plant defences of neighbours. The authors investigated the volatile emission patterns of receiver plants that respond to the volatile emission of neighbouring sender plants which are fed upon by herbivorous caterpillars. They applied a very elegant approach (more rigorous than the current state-of-the-art) to monitor temporal response patterns of neighbouring plants to HIPVs by measuring volatile emissions of senders and receivers, senders only and receivers only. Different terpenoids were produced within 2 h of such exposure in receiver plants, but not during the dark phase. Once the light turned on again, large amounts of terpenoids were released from the receiver plants. This may indicate a delayed terpene burst, but terpenoids may also be induced by the sudden change in light. A potential caveat exists with respect to the exact timing and the day-night cycle. The timing may be critical, i.e. at which time-point after onset of light herbivores were placed on the plants and how long the terpene emission lasted before the light was turned off. If the rhythm or a potential internal clock matters, then this information should also be highly relevant. Moreover, light on/off is a rather arbitrary treatment that is practical for experiments in the laboratory but which is not a very realistic setting. Particularly with regard to terpene emission, the sudden turning on of light instead of a smooth and continuous change to lighter conditions may trigger emission responses that are not found in nature. As one contrasting control, the authors also studied the time-delay in volatile emission when plants were just kept under continuous light (just for the experiment or continuously?). Here they also found a delayed terpenoid production, but this seemed to be lower compared to the plants exposed to the day-night-cycle. Another helpful control would be to start the herbivory treatment in the evening hours and leave the light on. If then again plants only release volatiles after a 17 h delay, the response is indeed independent of the diurnal clock of the plant.

Interestingly, internal terpene pools of one of the leaves tested here remained more comparable between night and day, indicating that their pools stay higher in plants exposed to HIPVs. In contrast, terpene synthases were only induced during the light-phase, not in the dark-phase. Moreover, jasmonates were only significantly induced 22 h after the onset of the volatile exposure and thus parallel with the burst of terpene release.

An additional experiment exposing plants to the green leaf volatile (glv) (Z)-3-hexenyl acetate revealed that plants can be primed by this glv, leading to a stronger terpene burst. The results are discussed with nice logic and considering potential ecological consequences. Some data are not discussed, e.g. the jasmonate and gene induction pattern.

Overall, this study provides intriguing insights into the potential interplay between priming and induction, which may co-occur, enhancing (indirect and direct) plant defence. Follow-up studies are suggested that may provide additional evidence.

Reviewer #1 (Public Review):

In this paper, the authors show that disruption of calcineurin, which is encoded by tax-6 in C. elegans, results in increased susceptibility to P. aeruginosa, but extends lifespan. In exploring the mechanisms involved, the authors show that disruption of tax-6 decreases the rate of defecation leading to intestinal accumulation of bacteria and distension of the intestinal lumen. The authors further show that the lifespan extension is dependent on hlh-30, which may be involved in breaking down lipids following deficits in defecation, and nhr-8, whose levels are increased by deficits in defecation. The authors propose a model in which disruption of the defecation motor program is responsible for the effect of calcineurin on pathogen susceptibility and lifespan, but do not exclude the possibility that calcineurin affects these phenotypes independently of defecation.

Reviewer #2 (Public Review):

The manuscript titled "Calcineurin Inhibition Enhances Caenorhabditis elegans Lifespan by Defecation Defects-Mediated Calorie Restriction and Nuclear Hormone Signaling" by Priyanka Das, Alejandro Aballay, and Jogender Singh reveals that inhibiting calcineurin, a conserved protein phosphatase, in C. elegans affects the defecation motor program (DMP), leading to intestinal bloating and increased susceptibility to bacterial infection. This intestinal bloating mimics calorie restriction, ultimately resulting in an enhanced lifespan. The research identifies the involvement of HLH-30 and NHR-8 proteins in this lifespan enhancement, providing new insights into the role of calcineurin in C. elegans DMP and mechanisms for longevity.

The authors present novel findings on the role of calcineurin in regulating the defecation motor program in C. elegans and how its inhibition can lead to lifespan enhancement. The evidence provided is solid with multiple experiments supporting the main claims.

Strengths:<br /> The manuscript's strength lies in the authors' use of genetic and biochemical techniques to investigate the role of calcineurin in regulating the DMP, innate immunity, and lifespan in C. elegans. Moreover, the authors' findings provide a new mechanism for calcineurin inhibition-mediated longevity extension, which could have significant implications for understanding the molecular basis of aging and developing interventions to promote healthy aging.

1. The study uncovers a new role for calcineurin in the regulation of C. elegans DMP and a potential novel pathway for enhancing lifespan via calorie restriction involving calcineurin, HLH-30, and NHR-8 in C. elegans.<br /> 2. Multiple signaling pathways involved in lifespan enhancement were investigated with fairly strong experimental evidence supporting their claims.

Weaknesses:<br /> The manuscript's weaknesses include the lack of mechanistic details regarding how calcineurin inhibition leads to defects in the DMP and induces calorie restriction-like effects on lifespan.

The exact site of calcineurin action, i.e., whether in the intestine or enteric muscles (Lee et al., 2005), and the possible molecular mechanisms linking calcineurin inhibition, DMP defects, and lifespan were not adequately explored. Although characterization of the full mechanism is probably beyond the scope of this paper, given the relative simplicity and advantages of using C. elegans as a model organism for this study, some degree of rigor is expected with additional straightforward control experiments as listed below:

The authors state that tax-6 knockdown animals had drastically reduced expulsion events (Figure 2G), leading to irregular DMP (Lines 144-145), but did not describe the nature of DMP irregularity. For example, did the reduced expulsion events still occur with regular intervals but longer cycle lengths? Or was the rhythmicity completely abolished? The former would suggest the intestine clock is still intact, and the latter would indicate that calcineurin is required for the clock to function. Therefore, ethograms of DMP in both wild-type and tax-6 mutant animals are warranted to be included in the manuscript. Along the same line, besides the cycle length, the three separable motor steps (aBoc, pBoc, EMC) are easily measurable, with each step indicating where the program goes wrong, hence the site of action, which is precisely the beauty of studying C. elegans DMP. Unfortunately, the authors did not use this opportunity to characterize the exact behavior phenotypes of the tax-6 mutant to guide future investigations. Furthermore, it is interesting that about 64% of tax-6 (p675) animals had normal DMP. The authors attributed this to p675 being a weak allele. It would be informative to further examine tax-6 RNAi as in other experiments or to make a tax-6 null mutant with CRISPR. In addition, in one of the cited papers (Lee et al., 2005), the exact calcineurin loss-of-function strain tax-6(p675) was shown to have normal defecation, including normal EMC, while the gain-of-function mutant of calcineurin tax-6(jh107) had abnormal EMC steps. It wasn't clear from Lee et al., 2005, if the reported "normal defecation" was only referring to the expulsion step or also included the cycle length. Nevertheless, this potential contradiction and calcineurin gain-of-function mutant is highly relevant to the current study and should be further explored as a follow-up to previously reported results. For some of the key experiments, such as tax-6's effects on susceptibility to PA14, DMP, intestinal bloating, and lifespan, additional controls, as the norm of C. elegans studies, including second allele and rescue experiments, would strengthen the authors' claims and conclusions.

The second weakness of this manuscript is the data presentation for all survival rate curves. The authors stated that three independent experiments or biological replicates were performed for each group but only showed one "representative" curve for each plot. Without seeing all individual datasets or the averaged data with error bars, there is no way to evaluate the variability and consistency of the survival rate reported in this study.

Overall, the authors' claims and conclusions are justified by their data, but further experiments are needed to confirm their findings and establish the detailed mechanisms underlying the observed effects of calcineurin inhibition on the DMP, calorie restriction, and lifespan in C. elegans.

Reviewer #1 (Public Review):

In this study the authors first perform global knockout of the gene coding for the polarity protein Crumbs 3 (CRB3) in the mouse and show that this leads to perinatal lethality and anopthalmia. Next, they create a conditional knockout mouse specifically lacking CRB3 in mammary gland epithelial cells and show that this leads to ductal epithelial hyperplasia, impaired branching morphogenesis and tumorigenesis. To study the mechanism by which CRB3 affects mammary epithelial development and morphogenesis the authors turn to MCF10A cells and find that CRB3 shRNA-mediated knockdown in these cells impairs their ability to form properly polarized acini in 3D cultures. Furthermore, they find that MCF10A cells lacking CRB3 display reduced primary ciliation frequency compared to control cells, which is supported by rescue experiments and is in agreement with previous studies implicating CRB3 in primary cilia biogenesis. Using a combination of biochemical, molecular- and imaging approaches the authors then provide evidence indicating that CRB3 promotes ciliogenesis by mediating Rab11-dependent recruitment of gamma-tubulin ring complex (gamma-TuRC) component GCP6 to the centrosome/ciliary base, and they also show that CRB3 itself is localized to the base of primary cilia. Finally, to assess the functional consequences of CRB3 loss on ciliary signaling function, the authors analyze the effect of CRB3 loss on Hedgehog and Wnt signaling using cell-based assays or a mouse model.

Overall, the described findings are interesting and in agreement with previous studies showing an involvement of CRB3 in epithelial cell biology, tumorigenesis and ciliogenesis. The results showing a role for CRB3 in mammary epithelial development and morphogenesis in vivo seem convincing. Although the authors provide evidence that CRB3 promotes ciliogenesis via (indirect) physical association with Rab11 and gamma-TuRC, the precise mechanism by which CRB3 promotes ciliogenesis remains to be clarified.

Reviewer #1 (Public Review):

Summary:<br /> This manuscript provides some valuable findings concerning the hippocampal circuitry and the potential role of adult-born granule cells in an interesting long-term social memory retrieval. The behavior experiments and strategy employed to understand how adult-born granule cells contribute to long-term social discrimination memory are interesting.

I have a few concerns, however with the strength of the evidence presented for some of the experiments. The data presented and the method described is incomplete in describing the connection between cell types in CA2 and the projections from abGCs. Likewise, I worry about the interpretation of the data in Figures 1 and 2 given the employed methodology. I think that the interpretation should be broadened. This second concern does not impact the interest and significance of the findings.

Strengths:<br /> The behavior experiments are beautifully designed and executed. The experimental strategy is interesting.

Weaknesses:<br /> The interpretation of the results may not be justified given the methods and details provided.

Reviewer #2 (Public Review):

Summary:<br /> Laham et al. investigate how the projection from adult-born granule cells into CA2 affects the retrieval of social memories at various developmental points. They use chemogenetic manipulations and electrophysiological recordings to test how this projection affects hippocampal network properties during behavior. I find the study to be very interesting, the results are important for our understanding of how social memories of different natures (remote or immediate) are encoded and supported by the hippocampal circuitry. I have some points that I added below that I think could help clarify the conclusions:<br /> - My major concern with the manuscript was that making the transitions between the different experiments for each result section is not very smooth. Maybe they can discuss a bit in a summary conclusion sentence at the end of each result section why the next set of experiments is the most logical step.<br /> - In line 113, the authors say that "the DG is known to influence hippocampal theta-gamma coupling and SWRs". Another recent study Fernandez-Ruiz et al. 2021, examined how various gamma frequencies in the dentate gyrus modulate hippocampal dynamics.<br /> - Having no single cells in the electrophysiological recordings makes it difficult to interpret the ephys part. Perhaps having a discussion on this would help interpret the results. If more SWRs are produced from the CA2 region (perhaps aided by projections from abGC), more CA2 cells that respond to social stimuli (Oliva et al. 2020) would reactivate the memories, therefore making them consolidate faster/stronger. On the other hand, the projections from abGC that the authors see, also target a great deal of PV+ interneurons, which have been shown to pace the SWRs frequency (Stark et al 2014, Gan et al 2017), which further suggests that this projection could be involved in SWRs modulation.<br /> - The authors should cite and discuss Shuo et al., 2022 (A hypothalamic novelty signal modulates hippocampal memory).<br /> - I think the authors forgot to refer to Fig 3a-f, maybe around lines 163-168.<br /> - Are the SWRs counted only during interaction time or throughout the whole behavior session for each condition?<br /> - Figure 3t shows a shift in the preferred gamma phase within theta cycles as a result of abGC projections to CA2 ablation with CNO, especially during Mother CNO condition. I think this result is worth mentioning in the text.<br /> - Figure 3u in the legend mention "scale bars = 200um", what does this refer to?<br /> - What exactly is calculated as SWR average integral? Is it a cumulative rate? Please clarify.<br /> - Alexander et al 2017, "CA2 neuronal activity controls hippocampal oscillations and social behavior", examined some of the CA2 effects in the hippocampal network after CNO silencing, and the authors should cite it.

Strengths:<br /> Behavioral experiments after abGC projections to CA2 are compelling as they show clearly distinct behavioral readout.

Weaknesses:<br /> Electrophysiological experiments are difficult to interpret without additional quantifications (single-cell responses during interactions etc.)

Reviewer #3 (Public Review):

Laham et al. present a manuscript investigating the function of adult-born granule cells (abGCs) projecting to the CA2 region of the hippocampus during social memory. It should be noted that no function for the general DG to CA2 projection has been proposed yet. The authors use targeted ablation, chemogenetic silencing, and in vivo ephys to demonstrate that the abGCs to CA2 projection is necessary for the retrieval of remote social memories such as the memory of one's mother. They also use in vivo ephys to show that abGCs are necessary for differential CA2 network activity, including theta-gamma coupling and sharp wave-ripples, in response to novel versus familiar social stimuli.

The question investigated is important since the function of DG to CA2 projection remained elusive a decade after its discovery. Overall, the results are interesting but focused on the social memory of the mother, and their description in the manuscript and figures is too cursory. For example, raw interaction times must be shown before their difference. The assumption that mice exhibit social preference between familiar or novel individuals such as mother and non-mother based on social memory formation, consolidation, and retrieval should be better explained throughout the manuscript. Thus, when describing the results, the authors should comment on changes in preference and how this can be interpreted as a change in social memory retrieval. Several critical experimental details such as the total time of presentation to the mother and non-mother stimulus mice are also lacking in the manuscript. The in vivo e-phys results are interesting as well but even more succinct with no proposed mechanism as to how abGCs could regulate SWR and PAC in CA2.

The manuscript is well-written with the appropriate references. The choice of the behavioral test is somewhat debatable, however. It is surprising that the authors chose to use a direct presentation test (presentation of the mother and non-mother in alternation) instead of the classical 3-chamber test which is particularly appropriate to investigate social preference. Since the authors focused exclusively on this preference, the 3-chamber test would have been more adequate in my opinion. It would greatly strengthen the results if the authors could repeat a key experiment from their investigation using such a test. In addition, the authors only impaired the mother's memory. An additional experiment showing that disruption of the abGCs to CA2 circuit impairs social memory retrieval would allow us to generalize the findings to social memories in general. As the manuscript stands, the authors can only conclude the importance of this circuit for the memory of the mother. Developmental memory implies the memory of familiar kin as well.

The in vivo ephys section (Figure 3) is interesting but even more minimalistic and it is unclear how abGCs projection to CA2 can contribute to SWR and theta-gamma PAC. In Figure 1, the authors suggest that abGCs project preferentially to PV+ neurons in CA2. At a minimum, the authors should discuss how the abGCs to PV+ neurons to CA2 pyramidal neurons circuit can facilitate SWR and theta-gamma PAC.

Finally, proposing a function for 4-6-week-old abGCs projecting to CA2 begs two questions: What are abGCs doing once they mature further, and more generally, what is the function of the DG to CA2 projection? It would be interesting for the authors to comment on these questions in the discussion.

Reviewer #1 (Public Review):

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

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

There are, however, parts of the manuscript that are not clearly described or could be otherwise improved.

- The number of denovo-assembled unigenes seems large and I would like to know how it compares to the number of genes in other Cucurbitaceae species. The presence of alternatively assembled isoforms or assembly artifacts may be still high in the final assembly and inflate the numbers of identified sex-biased genes.

- It is interesting that the majority of sex-biased genes are present in the floral buds but not in the mature flowers. I think this pattern could be explored in more detail, by investigating the expression of male and female sex-biased genes throughout the flower development in the opposite sex. It is also not clear how the expression of the sex-biased genes found in the buds changes when buds and mature flowers are compared within each sex.

- The statistical analysis of evolutionary rates between male-biased, female-biased, and unbiased genes is performed on samples with very different numbers of observations, therefore, a permutation test seems more appropriate here.

- The impact of pleiotropy on the evolutionary rates of male-biased genes is speculative since only two tissue samples (buds and mature flowers) are used. More tissue types need to be included to draw any meaningful conclusions here.

Reviewer #2 (Public Review):

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

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

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

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

Reviewer #3 (Public Review):

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

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

The main limitation of the study is the very low number of samples analyzed, with only three replicate individuals per sex (i.e. the whole study is built on six individuals only). This provides low power to detect differential expression. Along the same line, only three species were used to evaluate the rates of non-synonymous to synonymous substitutions, which also represents a very limited dataset, in particular when trying to fit parameter-rich models such as those implemented here.

A third limitation relates to the absence of a reference genome for the species, making the use of a de novo transcriptome assembly necessary, which is likely to lead to a large number of incorrectly assembled transcripts. Of course, the production of a reference transcriptome in this non-model species is already a useful resource, but this point should at least be acknowledged somewhere in the manuscript.

Each of these shortcomings is relatively important, and together they strongly limit the scope of the conclusions that can be made, and they should at least be acknowledged more prominently. The study is valuable in spite of these limitations and the topic remains grossly understudied, so I think the study will be of interest to researchers in the field, and hopefully inspire further, more comprehensive analyses.

Reviewer #1 (Public Review):

Summary:<br /> The manuscript of Zhao et al. aimed at investigating the relationships between type 2 diabetes, bone mineral density (BMD) and fracture risk using Mendelian Randomization (MR) approach.<br /> The authors found that genetically predicted T2D was associated with higher BMD and lower risk of fracture, and suggested a mediated effect of RSPO3 level. Moreover, when stratified by the risk factors secondary to T2D, they observed that the effect of T2D on the risk of fracture decreased when the number of risk factors secondary to T2D decreased.

Strengths:<br /> - Important question<br /> - Manuscript is overall clear and well-written<br /> - MR analyses have been conducted properly, which include the usage of various MR methods and sensitivity analyses, and likely meet the criteria of the MR-strobe checklist to report MR results.

Weaknesses:<br /> - Previous MR studies on that topic have not been discussed<br /> - Multivariable MR could have been used to better assessed the mediative effect of BMI or RSPO3 on the relationships between T2D and fracture risk.

Reviewer #2 (Public Review):

The authors employed the Mendelian Randomization method to analyze the association between type 2 diabetes (T2D) and fracture using the UK Biobank data. They found that "genetically predicted T2D was associated with higher BMD and lower risk of fracture". Additionally, they identified 10 loci that were associated with both T2D and fracture risk, with the SNP rs4580892 showing the highest signal. While the negative relationship between T2D and fracture has been previously observed, the discovery of these 10 loci adds an intriguing dimension to the findings, although the clinical implications remain uncertain.

Reviewer #1 (Public Review):

In this manuscript, the authors investigate differences between Tibetans and Han Chinese at altitude in terms of placental transcriptomes during full-term pregnancy. Most importantly, they found that the inter-population differentiation is mostly male-specific and the observed direction of transcriptional differentiation seems to be adaptive at high altitude. In general, it is of great importance and provides new insights into the functional basis of Tibetan high-altitude adaptations, which so far have been mostly studied via population genetic measures only. More specifically, I firmly believe that we need more phenotype data (including molecular phenotypes such as gene expression data) to fully understand Tibetan adaptations to high altitude, and this manuscript is a rare example of such a study. I have a few suggestions and/or questions with which I hope to improve the manuscript further, especially in terms of 1) testing if the observed DEG patterns are truly adaptive, and 2) how and whether the findings in this study can be linked to EPAS1 and EGLN1, the signature adaptation genes in Tibetans.

Major Comments:

1. The DEG analysis is the most central result in this manuscript, but the discrepancy between sex-combined and sex-specific DEGs is quite mind-boggling. For those that were differentially expressed in the sex-specific sets but not in the sex-combined one, the authors suggest an opposite direction of DE as an explanation (page 11, Figure S5). But Figure S5A does not show such a trend, showing that down-regulated genes in males are mostly not at all differentially expressed in females. Figure S6B does show such a trend, but it doesn't seem to be a dominant explanation. I would like to recommend the authors test alternative ways of analysis to boost statistical power for DEG detection other than simply splitting data into males and females and performing analysis in each subset. For example, the authors may consider utilizing gene-by-environment interaction analysis schemes here biological sex as an environmental factor.

2. Please clarify how the authors handled multiple testing correction of p-values.

3. The "natural selection acts on the placental DEGs ..." section is potentially misleading readers to assume that the manuscript reports evidence for positive selection on the observed DEG pattern between Tibetans and Han, which is not.<br /> a) Currently the section simply describes an overlap between DEGs and a set of 192 genes likely under positive selection in Tibetans (TSNGs). The overlap is quite small, leading to only 13 genes in total (Figure 6). The authors are currently not providing any statistical measure of whether this overlap is significantly enriched or at the level expected for random sampling.<br /> b) The authors are describing sets of DEGs that seem to affect important phenotypic changes in a consistent and adaptive direction. A relevant form of natural selection for this situation may be polygenic adaptation while the authors only consider strong positive selection at a single variant/gene level.<br /> c) The manuscript is currently providing no eQTL information that can explain the differential expression of key genes. The authors can actually do this based on the genotype and expression data of the individuals in this study. Combining eQTL info, they can set up a test for polygenic adaptation (e.g. Berg and Coop; https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1004412). This will provide a powerful and direct test for the adaptiveness of the observed DEG pattern.

4. The manuscript is currently only minimally discussing how findings are linked to EPAS1 and EGLN1 genes, which show the hallmark signature of positive selection in Tibetans. In fact, the authors' group previously reported male-specific association between EPAS1 SNPs and blood hemoglobin level. Many readers will be intrigued to see a discussion about this point.

Reviewer #2 (Public Review):

In this manuscript, the authors use newly-generated, large-scale transcriptomic data along with histological data to attempt to dissect the mechanisms by which individuals with Tibetan ancestry are able to mitigate the negative effects of high elevation on birth weight. They present detailed analyses of the transcriptomic data and find significant sex differences in the placenta transcriptome.

I have significant concerns about the conclusions that are presented. The analyses also lack the information necessary to evaluate their reliability.

The experimental design does not include a low elevation comparison and thus cannot be used to answer questions about how ancestry influences hypoxia responses and thus birthweight at high elevations. Importantly, because the placenta tissues (and trophoblasts specifically) are quickly evolving, there are a priori good reasons to expect to find population differences irrespective of adaptive evolution that might contribute to fetal growth protection. There are also significant details missing in the analyses that are necessary to substantiate and replicate the analyses presented.

Although the datasets are ultimately valuable as reference sets, the absence of low elevation comparisons for Tibetans and Han Chinese individuals undermines the ability of the authors to assess whether differences observed between populations are linked to hypoxia responses or variation in the outcomes of interest (i.e., hypoxia-dependent fetal growth restriction).

The authors attempt to tackle this phenotypic association by looking for correlations between gene networks (WGCNA) and individual genes with birthweight and other measurements collected at birth. I have some reservations about this approach with only two groups (i.e., missing the lowland comparison), but it is further problematic that the authors do not present data demonstrating that there are differences in birthweight or any other traits between the populations in the samples they collected.

Throughout, I thus find conclusions about the adaptive value and hypoxia-responses made by the authors to be unsubstantiated and/or the data to be inadequate. There are also a gratuitous number of speculative statements about mechanisms by which differential gene expression leads to the protection of birthweight that are not evaluated and thus cannot be substantiated by the data presented.

As currently presented and discussed, these results thus can only be used to evaluate population differences and tissue-specific variation therein.

There is also some important methodological information missing that makes it difficult or impossible to assess the quality of the underlying data and/or reproduce the analyses, further limiting the potential impact of these data:<br /> 1. Transcriptome data processing and analyses: RNA quality information is not mentioned (i.e., RIN). What # of reads are mapped to annotated regions? How many genes were expressed in each tissue (important for contextualizing the # of DE genes reported - are these a significant proportion of expressed genes or just a small subset?).<br /> 2. The methods suggest that DE analyses were run using data that were normalized prior to reading them into DESeq2. DESeq2 has an internal normalization process and should not be used on data that was already normalized. Please clarify how and when normalization was performed.<br /> 3. For enrichment analyses, the background gene set (all expressed genes? all genes in the genome? or only genes expressed in the tissue of interest?) has deterministic effects on the outcomes. The background sets are not specified for any analyses.<br /> 4. In the WGCNA analysis, P-values for correlations of modules with phenotype data (birthweight etc.) should be corrected for multiple testing (i.e., running the module correlation for each outcome variables) and p.adjust used to evaluate associations to limit false positives given the large number of correlations being run.<br /> 6. The plots for umbilical histological data (Fig 5 C) contain more than 5 points, but the use of replicate sections is not specified. If replicate sections were used, the authors should control for non-independence of replicate sections in their analyses (i.e., random effects model).

On more minor notes:<br /> There is significant and relevant published data on sex differences and hypoxia in rodents (see Cuffe et al 2014, "Mid- to late-term hypoxia in the mouse alters placental morphology, glucocorticoid regulatory pathways, and nutrient transporters in a sex-specific manner" and review by Siragher and Sferuzzi-Perro 2021, "Placental hypoxia: What have we learnt from small animal models?"), and historical work reporting sex differences in placental traits associated with high elevation adaptation in Andeans (series of publications by Moira Jackson in the late 1980s, reviewed in Wilsterman and Cheviron 2021, "Fetal growth, high altitude, and evolutionary adaptation: A new perspective").

Reviewer #3 (Public Review):

More than 80 million people live at high altitude. This impacts health outcomes, including those related to pregnancy. Longer-lived populations at high altitudes, such as the Tibetan and Andean populations show partial protection against the negative health effects of high altitude. The paper by Yue sought to determine the mechanisms by which the placenta of Tibetans may have adapted to minimise the negative effect of high altitude on fetal growth outcomes. It compared placentas from pregnancies from Tibetans to those from the Han Chinese. It employed RNAseq profiling of different regions of the placenta and fetal membranes, with some follow-up of histological changes in umbilical cord structure and placental structure. The study also explored the contribution of fetal sex in these phenotypic outcomes.

A key strength of the study is the large sample sizes for the RNAseq analysis, the analysis of different parts of the placenta and fetal membranes, and the assessment of fetal sex differences.

A main weakness is that this study, and its conclusions, largely rely on transcriptomic changes informed by RNAseq. Changes in genes and pathways identified through bioinformatic analysis were not verified by alternate methods, such as by western blotting, which would add weight to the strength of the data and its interpretations. There is also a lack of description of patient characteristics, so the reader is unable to make their own judgments on how placental changes may link to pregnancy outcomes. Another weakness is that the histological analyses were performed on n=5 per group and were rudimentary in nature.

Reviewer #1 (Public Review):

The authors report a new bioinformatics pipeline ("SPICE") to predict pairwise cooperative binding-sites based on input ChIP-seq data for transcription factor (TF)-of-interest, analyzed against DNA-binding sites (DNA motifs) in a database (HOCOMOCO). The pipeline also predicts the optimal distance between the paired binding sites. The pipeline correctly predicted known/reported transcription factor cooperations, and also predicted new cooperations, not yet reported in literature. The authors choose to follow up on the predicted interaction between Ikaros and Jun. Using ChIP-seq in mouse B cells, they show extensive overlap in binding regions between Ikaros and Jun in LPS+IL21 stimulated cells. In a human B-lineage cell line (MINO) they show that anti-Ikaros Ab can co-immunoprecipitate Jun protein, and that the MINO cell extracts contain protein(s) that can bind to the CNS9 probe (conserved region upstream of IL10 gene), and that binding is lost upon mutation of two basepairs in the AP1 binding motif, and reduced upon mutation of two basepairs in the non-canonical Ikaros binding motif. Part of this protein complex is super-shifted with an anti-Jun antibody, and more DNA is shifted with addition of an anti-Ikaros antibody.

The authors perform EMSA showing that recombinant Jun can bind to the tested DNA-region (IL10 CNS9) and that addition of recombinant Ikaros (or anti-Ikaros antibody in Fig 3E) can enhance binding (increase amount of DNA shifted). The authors lastly show that the IL10 CNS9 DNA region can enhance transcription in B- and T-cells with a luciferase reporter assay, and that 2 bp mutation of the Ikaros or Jun DNA motifs greatly reduce or abolish this activity.

This is interesting work, with two main contributions: The SPICE pipeline (if made available to the scientific community), and the report of interaction between Ikaros and Jun. However, the distinction between DNA motifs, and the proteins actually binding and having a biological function, should be made clear consistently throughout the manuscript. The same DNA motifs can be bound by multiple factors, for instance within transcription factor families with highly homology in the DNA-binding regions of the proteins.

Some specific points:

SPICE: It is unclear if this is uploaded somewhere to be available to the scientific community.

It was unclear if Ikaros-Jun interaction was initially found from primary Jun ChIP-seq (and secondary Ikaros motif from HOCOMOCO) or from primary Ikaros CHIP-seq (and secondary Jun motif from HOCOMOCO). And - what were the two DNA motifs (primary and secondary, and their distance) from the SPICE analysis?

Authors have mostly careful considerations and statements. One additional comment is that binding does not equal function (Fig 2D), and that opening of chromatin (by any other factor(s)) can give DNA-binding factors (like Ikaros and Jun) the opportunity to bind, without functional consequence for the biological process studied.

Figure 2E: Ikaros is reported to be expressed at baseline in murine B cells, yet the Ikaros ChIP-seq in unstimulated cells had what looks to be no significant or low peaks. LPS stimulation induced strong Ikaros ChIP-seq signal. A western blot showing the Ikaros protein levels in the 3 conditions could help understand if the binding pattern is due to protein expression level induction. Similar for Jun (western in the 3 conditions), which seemed to mainly bind in the LPS+IL21 condition. Furthermore, as also suggested below, tracks showing Ikaros and Jun binding from all conditions (unstimulated, LPS only and LPS+IL21 stimulated cells), at select genomic loci, would be helpful in illustrating this difference in signal between the different cell conditions. This is relevant in regards to the point of cooperativity of binding.

ChIP-seq in mouse B cells showed that Ikaros bound strongly in LPS stimulated cells, in the (relative) absence of Jun binding (Fig. 2C). However, in EMSA (Fig 3C), there is no binding when the AP1 site is mutated, and the authors describe this as Ikaros binding site. What does the Ikaros binding look like at this genomic location in LPS (only) stimulated cells? The authors could show the same figure as in Fig 2F but show Ikaros and Jun ChIP-seq tracks at IL10 CNS9 locus from all conditions to compare binding in unstimulated, LPS and LPS+IL21 cells.

Also: How does this reconcile with the luciferase assay in Fig 4E, where LPS (only) stimulation is used, which in Fig 2E only/mainly induced Ikaros, and not Jun ChIP-seq signal (while EMSA indicate Ikaros cannot bind the site alone, but can enhance Jun-dependent binding).

Comment on statements in results section: The luciferase assays in B and T cells do not demonstrate the role of the proteins Ikaros or Jun directly (page 10, lines 208 and surrounding text). The assay measures an effect of the DNA sequences (implying binding of some transcription factor(s)), but does not identify which protein factors bind there.

Lastly, the authors only discuss Ikaros (using the term IKZF1 which is the gene symbol for the Ikaros protein). There are other Ikaros family members that have high homology and that are reported to bind similar DNA sequences (for instance Aiolos and Helios), which are expressed in B-cells and T-cells. A discussion of this is of relevance, as these are different proteins, although belonging to the same family (the Ikaros-family) of transcription factors. For instance, western for Aiolos and Helios will likely detect Aiolos in the B cells used, and Helios in the T cells used.

Reviewer #2 (Public Review):

In this manuscript, Xie and colleagues investigate the contribution of osteocytes to bone metastasis of non-small cell lung carcinoma (NSCLC) using a combination of clinical samples and in vitro and in vivo data. They find that metastatic NSCLC cells exhibit lower levels of the proliferation marker Ki-67 when located in areas adjacent to the bone surface in both NSCLC patients and an intraosseous animal model of NSCLC. Using in vitro approaches, they show that osteocyte-like cells inhibit the proliferation of NSCLC cells through the secretion of small extracellular vesicles (sEVs). They identify miR-99b-3p as a component of sEVs and demonstrate that miR-99b3p inhibits the proliferation of NSCLC cells by targeting the transcription factor MDM2. Interestingly, the data also shows that mechanical stimulation of osteocytes enhances the inhibitory effect of osteocytes on NSCLC cell proliferation via increasing sEVs release. By performing different in vivo studies, the authors show that tibial loading and moderate exercise (treadmill running), before and after tumor cell inoculation, suppress tumor progression in bone and protect bone mass. Intriguingly, the moderate exercise regime shows additive/synergistic effects with the co-administration of anti-resorptive therapy. These data add to the growing evidence pointing towards osteocytes as important cells of the tumor microenvironment capable of influencing the progression of tumors in bone.

The conclusions of the paper, however, are not well supported by the data, and some critical aspects of image analysis and data analysis need to be clarified and extended.

1) The histological images are analyzed in a qualitative manner, with no description of the methodology used. In bone metastases, cancer cells are frequently mixed with bone marrow cells. The lack of cell markers to identify NSCLC cells versus bone marrow cells makes the interpretation of the imaging data difficult. The authors rely on KI-67 as a marker of proliferation. Yet, it is intriguing that some osteocytes, non-proliferating cells by definition, are often positive for this marker, which questions the specificity of the staining. To make these results more solid, the authors should have provided the proper immunostaining controls to check for specificity and use additional markers of proliferation.

2) Adding control groups to fully assess the impact of the in vivo interventions (tibial loading, moderate exercise, anti-resorptive therapy) on bone mass would be needed. The authors should have used naive mice or analyzed the bones from the non-injected contralateral legs. Further, validating the in vivo work with other osteocyte-like cells or primary osteocytes would have strengthened the results.

3) The data on miRNA99b-3p on NSCLC in Supplementary Figure 3 is not convincing. The positive cells are difficult to see and most of the osteocyte lack nuclei. Better data, in humans and the mouse model, would have helped to confirm that osteocytes produce miRNA99b-3p.

4) The conclusions of the paper are not fully supported by the data provided. Osteocytes, as well as other bone cells, can respond to mechanical stimulation and thus could virtually be responsible for the protective effects of mechanical loading or moderate exercise. In vivo experiments demonstrating a direct role of osteocytes-produced miRNA99b-3p are needed to support the notion that osteocytes maintain tumor dormancy in NSCLC bone metastasis. Further, the authors solely rely on Ki-67 as a marker of dormancy. Completing this analysis with an assessment of a dormant gene expression signature or in vivo studies assessing tumor dormancy directly would be needed to confirm this notion.

Reviewer #1 (Public Review):

Xie and Colleagues propose here to investigate the mechanism by which exercise inhibits bone metastasis progression. The authors describe that osteocyte, sensing mechanical stimulation generated by exercise, inhibit NSCLC cell proliferation and sustain the dormancy thereof by releasing sEVs with tumor suppressor microRNAs. Furthermore, mechanical loading of the tibia inhibited the bone metastasis progression of NSCLC. Interestingly, exercise preconditioning effectively suppressed bone metastasis progression.

Reviewer #1 (Public Review):

In this manuscript, the authors explored the benefits of intermittent fasting on the cardiac physiology through a multi-omics approach and compared different fasting times (IF12; IF 16 and EOD) for a duration of 6 months. Combining the RNA-sequencing, proteomics and phosphor-proteomics analysis, the authors have made an interesting observation that different fasting times would lead to different changes that could be important for the cardiac physiology. Moreover, the changes observed at transcriptional level are different from protein level, suggesting a post-transcriptional regulation mechanism. Using western blot, the authors have confirmed the key signaling pathways, including AMPK, IRS pathway to be significantly altered upon intermittent fasting for 16hrs. Lastly, as a proof of concept for better cardiac function, the animals were challenged with dobutamine and echocardiography was performed to show the mice subjected to intermittent fasting have better cardiac systolic function.

The impact of intermittent fasting on cardiovascular health has been well characterized in several studies. This report appears to be the first one utilizing a multi-omics approach and provided an interesting dataset at transcriptome, proteome and phosphor-proteome levels, and would serve as a valuable data resource for the field. I have the following concerns:

Major concerns:

1) The rationale for choosing the intermittent fasting pattern and timing<br /> While the 16:8 intermittent fasting is relatively standard, what is the rationale to test IF 12 hours? As a 4 hour fasting difference might not cause dramatic changes in transcriptome and proteome. Also, what is the rationale to perform 6 months study? The dobutamine stress test is not a terminal procedure, have the authors examined the cardiac function prior to 6 months to see whether there is a difference?

2) Lack of validation study<br /> One interesting observation from this study is the changes of transcriptome does not reflect all the changes at protein level and there is a differential gene expression pattern in IF12, IF16 and EOD. If this is the case, the authors should select a few important targets and provide both mRNA and protein level analysis, as a proof of concept for the bioinformatics analysis accuracy.

3) Poor western blot image quality<br /> The quality of the western blot has several issues: a. the change of pAMPK/AMPK appears to be a decrease of total AMPK instead of change at p-AMPK level. Same with GSK3a/b. There appears to be an increase of total GSK3a/b. The AKT should also be blotted and quantified at phosphorylation level. The western blot should be clearly labeled, for the ones with double bands, including GSK3a/b, the author should clearly label which is GSK3a and which is GSK3b. For the IRS with non-specific band, the author should point out IRS-1 band itself.

Reviewer #2 (Public Review):

Summary:

This work presents a previously undescribed neuroanatomical and neurophysiological analog between mammals and songbirds. Juvenile zebra finches learn to sing by memorizing an adult song and then, through practice, converging to a close copy of the stored template. Previous work identified pathways emanating from the avian auditory cortical regions (AIV) and basal ganglia that, through ventral pallium (VP), and the subthalamic nucleus, innervate the finches' ventral tegmental area (VTA). As in mammals, the dopaminergic projections of the VTA onto the avian striatopallidal nucleus, area X, deliver a prediction error signal. This signal encodes a surprisingly better or worse performance of the ongoing song and therefore allows the birds to improve.

In mammals, lateral Habenula (LHb) neurons contribute to learning by signaling disappointing trial outcomes or aversive stimuli. Using viral tract tracing Roesner et al. identify projections from the zebra finch VP and AIV to the LHb as well as from the LHb to the VTA. The authors use functional mapping to show that the VP activates the LHb and that the LHb suppresses the Area X-projecting VTA neurons. Then, the authors show that lesioning the LHb in juvenile finches does not prevent them from copying their tutor's song but still leads to worse performance than controls due to the production of highly abnormal vocalizations, peppered in both lone and female-directed songs. In contrast, lesioning the LHb in adult finches has no effect on the song. Together, these findings suggest that the LHb may be part of a song evaluation system and may participate in learning by signaling vocalizations that deviate from the desired tutor template.

The LHb is an evolutionarily conserved structure that connects the forebrain and midbrain with the epithalamus in vertebrates. By identifying the LHb as a component in song learning, the authors lay the grounds for a trove of new research into the various emotional, biophysical, memory, and sensory processes that contribute to learning within and through the LHb. Most conclusions of this paper are well supported by data, but some conceptual and analytic aspects require framing with respect to methodological limitations.

Strengths:<br /> The use of both anatomical tracing and functional circuit mapping is a uniquely-powerful approach to addressing the main line of inquiry in this work. Specifically, collision testing and antidromic identification allow identifying LHb-->VTA and VTA-->X projecting neurons and therefore testing the response of these specific learning-related projections to stimulation in VP and LHb (respectively).

The evaluation of abnormal vocalizations using a variational autoencoder (VAE) is a particularly strong approach that is immune to observer biases. By training this artificial neural network model with sham or pre-lesion animals, the authors clearly distinguish abnormal syllables because of their significantly poorer reconstruction through the VAE. This approach allowed the authors to provide strong quantitative support to the effect of LHb lesion in juvenile finches on their adult song.

Weaknesses:<br /> The lesions in juveniles, as the authors discuss, were histologically examined at the end of the song development, months after their creation. The authors mention not being able to rule out damage to the medial part of the Hb. But the effect of the lesions could perhaps be mediated by damage to other brain regions, such as DLM, or passing fibers (when using electrolytic lesions).

Additionally, the effect on learning could also be mediated indirectly. In mammals, the outputs of the LHb target dopaminergic regions, serotonergic regions, and a cholinergic region. In birds, the LHb may also have a diverse impact on neuromodulators and therefore an impact on behavior states and on sleep. Disrupted behavior states may lead to poorer or less frequent practice and indirectly to abnormal results that do not stem from erroneous performance evaluation.

Reviewer #1 (Public Review):

Reinforcement mechanisms play a central role in learning structured behaviors, and recent studies in the songbird have shown that reinforcement learning is also integral to the imitation of the internally motivated singing behavior of songbirds. In this study, Roeser, Teoh et al. investigate the role of the lateral habenula in this process. The lateral habenula is thought to signal unexpected aversive outcomes, like reward omission, and inhibit dopaminergic neurons in the ventral tegmental area (VTA) via direct synaptic projections. Thus, the lateral habenula could logically play a key role in the trial-and-error learning of song by signaling worse performance outcomes (as evaluated by comparing to a memory of the tutor song) as birds practice copying their father's song.

The authors show that both the anatomical and functional connectivity of the lateral habenula in songbirds resembles what has been described in other vertebrates, including in afferent inputs from the ventral pallidum and efferent projections to the VTA that suppresses activity of putative dopaminergic neurons. Additionally, they show the lateral habenula circuits appear to be integrated with circuits known to be important for learning song, including receiving input from an auditory region, AIV, thought to be important in relaying song evaluation signals and providing inputs to VTA that overlap with neurons projecting to areas of the striatum essential for vocal learning (VTA-Area X neurons). They conclude that lesions of the lateral habenula early in song development do not disrupt a bird's ability to accurately imitate the song of their tutor but result in either the retention or development of unusual vocalizations that have qualities observed in the songs of zebra finches that have been experimentally raised without having access to a song tutor. The analysis of the adult song behavior is particularly compelling and provides novel approaches for identifying outlier vocalizations. Lastly, the authors show that birds will include these isolate-like syllables during courtship behaviors and that lesions of the lateral habenula do lead to disruptions in adult birds.

The conclusions stemming from the analysis of habenula connectivity require stronger support, and incomplete evidence is provided to link lesions of the lateral habenula to the observed disruptions in song learning.

This study has several strengths. First, the goal of understanding the role of the lateral habenula in natural learning of a complex behavior, like birdsong, is a valuable research avenue that can ultimately better link how natural learning of intrinsically rewarded behaviors may (or may not) harness similar learning mechanisms that have been well delineated in laboratory trained and externally reinforced behaviors. Second, the computational approaches brought to bear on the analysis of song, including variational autoencoders to help define the range of control song syllables from abnormal song syllables and anomaly scores, help provide a good framework for examining and conveying disruptions in behavior that might be associated with lesions of the lateral habenula. Lastly, the manuscript is well-written and clearly presented, and the authors do acknowledge some of the weaknesses mentioned below.

The major weakness of the article is that the authors do not verify the completeness (i.e., how much of the lateral habenula is lesioned in individual animals) or the extent (if neuronal regions adjacent to the lateral habenula neural are also lesioned) of their lesions. It is argued that this is not possible because of the timeframe (long survival times) of the experiments. However, there are standard ways of addressing this technical hurdle. One simple approach would be to first examine the correlation in the number of retrogradely labeled neurons in LHb, VP, and Area X following injections of tracer into VTA. For convergent anatomical pathways, there is typically a strong positive correlation across input circuits. Therefore, given the number of retrogradely labeled neurons in VP and Area X following VTA injections, one can make reasonable predictions for how many retrogradely labeled neurons would be expected in LHb. Using tracer injections at the end of the experiments and quantification of the retrograde labeling would allow the authors to reasonably estimate the completeness of their lesions.

This unfortunate problem with the design of the experiments significantly weakens any interpretations for the role of the lateral habenula in song learning. This is particularly important because the lateral habenula is a small area that has several adjacent brain structures that could also play significant roles in song development, most of which have not been well studied in this context. These include the medial habenula, the thalamic nuclei DMP and UVA, and forebrain axons from RA, as well as axons flowing into, out of, and interconnecting the structures previously mentioned. Additional tracer injections with different color tracers could be used to provide reasonable assurance that these other adjacent circuits are still intact at the end of each lesion experiment.

There are two weaknesses with the assessment of the functional connectivity of the lateral habenula. First, the anatomical tracing experiments are not particularly compelling. Very little data is shown and there is no quantification of any of the results. In the inset for retrograde labeling of VP-LHb and VP-VTA neurons, it is unclear that neurons of either population are shown in that image. Likewise, terminals from LHb in VTA are very sparse and it is not clear how well they overlap with VTA-X neurons which are intermingled with dopaminergic neurons projecting to other areas of the brain. The images shown seem out of focus and blurry. Although the electrophysiological experiments provide better assurance of these pathways, the sample sizes in these neurophysiology experiments seem preliminary. Stronger evidence in both regards would provide better assurance of LHb circuitry.

The interpretations and theoretical implications of these results are unclear. This is in part because it is not possible to fully tie behavioral outcomes specifically to lesions of the lateral habenula, but also because, albeit interesting, the behavioral results are somewhat confusing. The developmental lesions did not impact the ability of zebra finches to learn how to copy the song of their tutor over development, indicating, in a strict sense, this circuit is not needed for vocal imitation of a social model. However, birds clearly exhibit unusual song syllables that they throw into their song bouts, even when singing in courtship displays. What this may reflect is not addressed in this study. It could be that lesions disrupt a bird's ability to prune away poor syllables over development, and/or that lesions result in birds being unable to suppress unwanted vocal behaviors during performances. Analysis of song over development could provide insights into these possibilities and help provide a better understanding of what the lateral habenula contributes to the song-learning process.

Reviewer #1 (Public Review):

The manuscript focused on roles of a key fatty-acid synthesis enzyme, acetyl-coA-carboxylase 1 (ACC1), in the metabolism, gene regulation and homeostasis of invariant natural killer T (NKT_ cells and impact on these T cells' roles during asthma pathogenesis. The authors presented data showing that the acetyl-coA-carboxylase 1 enzyme regulates the expression of PPARg then the function of NKT cells including the secretion of Th2-type cytokines to impact on asthma pathogenesis. The results are clearcut and data were logically presented.

Reviewer #2 (Public Review):

In this study the authors sought to investigate how the metabolic state of iNKT cells impacts their potential pathological role in allergic asthma. The authors used two mouse models, OVA and HDM-induced asthma, and assessed genes in glycolysis, TCA, B-oxidation and FAS. They found that acetyl-coA-carboxylase 1 (ACC1) was highly expressed by lung iNKT cells and that ACC1 deficient mice failed to develop OVA-induced and HDM-induced asthma. Importantly, when they performed bone marrow chimera studies, when mice that lacked iNKT cells were given ACC1 deficient iNKT cells, the mice did not develop asthma, in contrast to mice given wildtype NKT cells. In addition, these observed effects were specific to NKT cells, not classic CD4 T cells. Mechanistically, iNKT cell that lack AAC1 had decreased expression of fatty acid-binding proteins (FABPs) and peroxisome proliferator-activated receptor (PPAR)γ, but increased glycolytic capacity and increased cell death. Moreover, the authors were able to reverse the phenotype with the addition of a PPARg agonist. When the authors examined iNKT cells in patient samples, they observed higher levels of ACC1 and PPARG levels, compared to healthy donors and non-allergic-asthma patients.

Reviewer #1 (Public Review):

Summary: A well-executed series of experiments that will likely be of immense interest to (a) vector-borne disease researchers and (b) gram-negative sepsis/bacteremia researchers. The study uses comparative transcriptomics to begin probing what makes Peromyscus leucopus a unique host for numerous pathogens. Most issues with the paper are trivial, relating to descriptions of statistical cutoffs. While the paper does not provide mechanistic insight into how P. leucopus restrains its immune response to LPS or other microbial invaders, it is likely that this paper will be frequently consulted by researchers trying to understand that phenomenon.

Strengths:

o Use of outbred M. musculus is a commendable choice for the studies here.<br /> o Excellent decision by the authors to use their published dataset (with appropriate statistical normalization) to improve their statistical power to examine sex-biased gene expression. Is it possible to go one step further and briefly incorporate their prior BALB/c data to see how the BALB/c compare to the outbred mice. This could perhaps be just a PCA plot to see if they cluster with the outbred mice and/or Peromyscus, or are separate.<br /> o The correlations and ratios used to try to understand immune cell dynamics are clever and likely reflect interesting biology, but caution should be used when interpreting these indirect measures. As there are no tools for cell separation in P. leucopus, the authors should continue to include these data to stimulate ideas in the field, but readers should understand the "conclusions" are hypotheses due to the nature of the bulk RNAseq.

Weaknesses:

o Supplemental Table 1 only lists genes that passed the authors statistical thresholds. The full list of genes detected in their analysis should be included with read counts, statistics, etc. as supplemental information<br /> o While P. leucopus is a critical reservoir for B. burgdorferi, caution should be taken in directly connecting the data presented here and the Lyme disease spirochete. While it's possible that P. leucopus have a universal mechanism for limiting inflammation in response to PAMPs, B. burgdorferi lack LPS and so it is also possible the mechanisms that enable LPS tolerance and B. burgdorferi tolerance may be highly divergent.<br /> o Statistical significance is binary and p-values should not be used as the primary comparator of groups (e.g. once a p-value crosses the deigned threshold for significance, the magnitude of that p-value no longer provides biological information). For instance, in comparing GO-terms, the reason for using of high p-value cutoffs ("None of these were up-regulated gene GO terms with p values < 1011 for M. musculus.") to compare species is unclear. If the authors wish to compare effect sizes, comparing enrichment between terms that pass a cutoff would likely be the better choice. Similarly, comparing DEG expression by p-value cutoff and effect size is more meaningful than analyses based on exclusively on p-value: "Of the top 100 DEGs for each species by ascending FDR p value." Description in later figures (e.g. Figure 4) is favored.<br /> o The ability to use of CD45 to normalize data is unclear. Authors should elaborate both on the use of the method and provide some data how the data change when they are normalized. For instance, do correlations between untreated Mus and Peromyscus gene expression improve? The authors seem to imply this should be a standard for interspecies comparison and so it would be helpful to either provide data to support that or, if applicable, use of the technique in literature should be referenced.<br /> o Regarding the ISG data-is a possible conclusion not that Peromyscus don't upregulate the antiviral response because it's already so high in untreated rodents? It seems untreated Peromyscus have ISG expression roughly equivalent to the LPS mice for some of the genes. This could be compared more clearly if genes were displayed as bar plots/box and whisker plots rather than in scatter plots. It is unclear why the linear regression is the key point here rather than normalized differences in expression.<br /> o Some sections of the discussion are under supported:<br />  The claim that low inflammation contributes to increased lifespan is stated both in the introduction and discussion. Is there justification to support this? Do aged pathogen-free mice show more inflammation than aged Peromyscus?<br />  The claim that reduced Peromyscus responsiveness could lead to increased susceptibility to infection is prominently proposed but not supported by any of the literature cited.<br />  References to B. burgdorferi, which do not have LPS, in the discussion need to ensure that the reader understands this and the potential that responses could be very different.

Reviewer #2 (Public Review):

Milovic, Duong, and Barbour investigate the inflammatory response of three species of small mammals (P. leucopus, M. musculus, and R. norvegicus) to endotoxin lipopolysaccharide (LPS) injection via genome-wide transcriptomics from blood samples. Understanding the inflammation response of P. leucopus is of importance as they are a reservoir for several pathogens. The study is a thorough, controlled, well researched analysis that will be valuable for designing and interpreting future studies. The authors discuss the limitations of the data and the potential directions. Clearly P. leucopus respond differently to the LPS exposure which is very interesting and opens the door for numerous other comparative studies.

The conclusions of the manuscript are thoughtful and mostly supported by the data, but there are a couple of points for clarification.

1) How were the number of animals for each experiment selected? Was a power analysis conducted?

2) The authors conducted a cursory evaluation of sex differences of P. leucopus and reported no difference in response except for Il6 and Il10 expression being higher in the males than the females in the exposed group. The data was not presented in the manuscript. Nor was sex considered for the other two species. A further discussion of the role that sex could play and future studies would be appreciated.

3) The ratio of Nos2 and Arg1 copies for LPS treated and control P. leucopus and M.musculus in Table 3 show that in P. leucopus there is not a significant difference but in M.musculus there is an increase in Nos2 copies with LPS treatment. The authors then used a targeted RNA-seq analysis to show that in P. leucopus the number of Arg1 reads after LPS treatment is significantly higher than the controls. These results are over oversimplified in the text as an inverse relationship for Nos2/Arg1 in the two species.

Reviewer #1 (Public Review):

The article by Reversade and colleagues reports new mutations in the PYCR1 in a progeroid disease associated with premature skin aging. Using human cell culture and a newly generated mouse model of PYCR1deficiency they identify a role for this factor in maintaining dermal homeostasis and ECM production. I have some minor concerns about the role of PYCR1 in fibroblast survival vs function and the quantification of western blots.

Reviewer #2 (Public Review):

Summary:<br /> Sotiropoulou et al. present an interesting study of an incredibly rare premature aging disease (De Barsy syndrome), examining both the underlying mechanisms at play behind the condition as well as how that biology may have a larger role in understanding features of normal aging, and in particular, human skin aging. The authors link one of the underlying genetic defects in De Barsy syndrome (PYCR1 mutations) to its phenotypic manifestations and then extrapolate those findings to present more preliminary data to suggest that a loss of PYCR1 may be a biomarker of normal human skin aging.

Strengths:<br /> - The study is important as De Barsy syndrome is challenging to study given its rarity, thus making it an understudied condition. Here the authors combine both human patient samples and murine models to offer a nice contribution to further understanding the pathophysiology of this disease.

- The authors are able to link some of the observed features in De Barsy syndrome preliminarily to more common aging models and processes (senescence, human skin dermal aging). They nicely show that the loss of Pycr1 in mice can provoke thinning of the dermis of mice while not affecting the epidermis. Furthermore, they present compelling data to suggest that Pycr2 may be compensating in mice (while not in humans) and this may contribute to the differences in lifespan observed between the mice and humans.

- Should these results be further verified, this could suggest that further study of Pycr1 and Pycr2 biology may offer new insights into aging and senescence in other tissues.

Weaknesses:<br /> - Some of the data appears preliminary and seems like it needs further analysis as described further below in my suggestions for the authors:

1) While the authors report that there is no difference in the lifespan of the Pycr1-KO mice, can they report whether there was overall weight loss or any size differences between the mice? This is helpful particularly when comparing the dermal thickness as well as considering how the global loss of Pycr1 may affect overall systemic health.

2) In Figure S2E, the comparison "pairs" seems somewhat arbitrarily chosen and it seems from the quantifications of these pairs that depending upon which young sample you compare to which old sample, you may end up with differing results. I think the more appropriate way to make this quantitative comparison would be to average the young samples and average the old samples and then compare them and perform statistics. This seems critical to really assess whether PYCR1 loss would be a consistent marker of human skin dermal aging. Additionally, it would be helpful to also look at Pycr2 expression in the normal young versus old dermis to see if the reported difference in Pycr1 is really something specific for Pycr1 and not something more general.

3) Are the labels mixed up in Figures 1J and 1K or am I reading it incorrectly? From what I can see the graph is showing that the dermal thickness and collagen intensity is higher in the Pycr1-/- mice. Similarly, the authors state that there is "significantly less collagen fiber staining", although in Figure S1G neither the quantification of collagen I or collagen III are shown to be significant. These discrepancies need to be discussed or corrected.

4) Can the authors speculate further on why Pycr2 is also diminished in human patients (while it clearly remains present in the mice).

5) Can the authors comment on whether other canonical senescence features are seen in De Barsy syndrome (p16 positivity, senescence associated secretory phenotype, etc.)? Along these lines, there is an abundance of publicly available RNA-seq datasets from various forms of senescent cells. It would be interesting to examine these and see whether there is any loss of expression of PYCR1 or PYCR2 in these data, or is the loss of PYCR1 only seen at the protein level?

Reviewer #1 (Public Review):

Summary:

In this excellent manuscript by Egan et al., the authors very carefully dissect the roles of inflammasome components in restricting Salmonella Typhimurium (STm) replication in human macrophages. They show that caspase-1 is essential to mediating inflammasome responses and that caspase-4 contributes to bacterial restriction at later time points. The authors show very clear roles for the host proteins that mediate terminal lysis, gasdermin D and ninjurin-1. The unique finding in this study is that in the absence of inflammasome responses, Salmonella hypereplicates within the cytosol of macrophages. These findings suggest that caspase-1 and possibly caspase-4 play roles in restricting the replication of Salmonella in the cytosol as well as in the Salmonella containing vacuole.

Strengths:

1) The genetic and biochemical approaches have shown for the first time in human macrophages that the caspase-1-GSDMD-NINJ1 axis is very important for restricting intracellular STm replication. In addition, they demonstrate a later role for Casp4 in control of intracellular bacterial replication.

2) In addition, they show that in macrophages deficient in the caspase-1-GSDMD-NINJ1 axis that STm are found replicating in the cytosol, which is a novel finding. The electron microscopy is convincing that STm are in the cytosol.

3) The authors go on to use a chloroquine resistance assay to show that inflammasome signaling also restricts STm within SCVs in human macrophages.

4) Finally, they show that the Type 3 Secretion System encoded on Salmonella Pathogenicity Island 1 contributes to STm's cytosolic access in human macrophages.

Weaknesses:

1) Their results with human macrophages suggest that there are differences between murine and human macrophages in inflammasome-mediated restriction of STm growth. For example, Thurston et al. showed that in murine macrophages that inflammasome activation controls the replication of mutant STm that aberrantly invades the cytosol, but only slightly limits replication of WT STm. In contrast, here the authors found that primed human macrophages rely on caspase-1, gasdermin D and ninjurin-1 to restrict WT STm. I wonder if the priming of the human macrophages in this study could account for the differences in these studies. Along those lines, do the authors see the same results presented in this study in the absence of priming the macrophages with Pam3CSK4. I think that determining whether the control of intracellular STm replication is dependent on priming is very important. Another difference with the Thurston et al. paper is the way that the STm inoculum was prepared - stationary phase bacteria that were opsonized. Could this also account for differences between the two studies rather than differences between murine and human macrophages in inflammasome-dependent control of STm?<br /> 2) The authors show that the pore-forming proteins GSDMD and Ninj1 contribute to control of STm replication in human macrophages. Is it possible that leakage of gentamicin from the media contributes to this control?

3) One major question that remains to be answered is whether casp-1 plays a direct role in the intracellular localization of STm. If the authors quantify the percentage of vacuolar vs. cytosolic bacteria at early time points in WT and casp-1 KO macrophages, would that be the same in the presence and absence of casp-1? If so, then this would suggest that there is a basal level of bacterial-dependent lysis of the SCV and in WT macrophages the presence of cytosolic PAMPS trigger cell death and bacteria can't replicate in the cytosol. However, in the inflammasome KO macrophages, the host cell remains alive and bacteria can replicate in the cytosol.

Reviewer #2 (Public Review):

Summary:

This work addresses the question of how human macrophages restrict intracellular replication of Salmonella.

Strengths:

Through a series of genetic knockouts and using specific inhibitors, Egan et al. demonstrated that the inflammasome components caspase-1, caspase-4, gasdermin D (GSDMD), and the final lytic death effector ninjurin-1 (NINJ1) are required for control of Salmonella replication in human macrophages. Interestingly, caspase-1 proved crucial in restricting Salmonella early during infection, whereas caspase-4 was essential in the later stages of infection. Furthermore, using a chloroquine resistance assay and state-of-the-art microscopy, the authors found that NAIP receptor and caspase-1 mostly regulate replication of cytosolic bacteria, with smaller, yet significant, impact on the vacuolar bacteria.

The finding that inflammasomes are critical in the restriction of replication of intracellular Salmonella in human macrophages contrasts with the published minimal role of inflammasomes in restriction of replication of intracellular Salmonella in murine macrophages. These findings demonstrate yet another example of interspecies and intercellular differences in regulation of bacterial infections by the immune system.

Weaknesses: none.

Reviewer #3 (Public Review):

The manuscript by Egan and coworkers investigates how Caspase-1 and Caspase-4 mediated cell death affects replication of Salmonella in human THP-1 macrophages in vitro.

Overall evaluation:

Strength of the study include the use of human cells, which exhibit notable differences (e.g., Caspase 11 vs Caspase-4/5) compared to commonly used murine models. Furthermore, the study combines inhibitors with host and bacterial genetics to elucidate mechanistic links.

The main weaknesses of the study are the inherent limitations of tissue culture models. For example, to study interaction of Salmonella with host cells in vitro, it is necessary to kill extracellular bacteria using gentamicin. However, since Salmonella-induced macrophage cell death damages the cytosolic membrane, gentamicin can reach intracellular bacteria and contribute to changes in CFU observed in tissue culture models (major point 1). This can result in tissue culture "artefacts" (i.e., observations/conclusions that cannot be recapitulated in vivo). For example, intracellular replication of Salmonella in murine macrophages requires T3SS-2 in vitro, but T3SS-2 is dispensable for replication in macrophages of the spleen in vivo (Grant et al., 2012).

Major comments:

In Figure 1: are increased CFU in WT vs CASP1-deficient THP-1 cells due to Caspase 1 restricting intracellular replication or due to Caspase-1 causing pore formation to allow gentamicin to enter the cytosol thereby restricting bacterial replication? The same question arises about Caspase-4 in Figure 2, where differences in CFU are observed only at 24h when differences in cell death also become apparent. The idea that gentamicin entering the cytosol through pores is responsible for controlling intracellular Salmonella replication is also consistent with the finding that GSDMD-mediated pore formation is required for restricting intracellular Salmonella replication (Figure 3). Similarly, the finding that inflammasome responses primarily control Salmonella replication in the cytosol could be explained by an intact SCV membrane protecting Salmonella from gentamicin (Figure 5).

Reviewer #1 (Public Review):

The manuscript by Sun and colleagues followed their previous findings on the tumor-suppressive role of PDLIM2 in lung cancer. They further investigated various mechanisms, including epigenetic modification, copy number variation, and LOH, that led to the decreased expression of PDLIM2 in human lung cancer. Next, they used a nanoparticle-based approach to specifically restore the expression in mouse lung tumors. They showed that over-expression of PDLIM2 in lung cancer repressed its progression in vivo. Also, this treatment could synergize with chemotherapy and checkpoint inhibitor anti-PD-1. Overall, the results were quite promising and convincing, using a treatment combination that would appear to have the potential for clinical implementation.

Reviewer #2 (Public Review):

Summary: The authors have previously demonstrated that the E3 ligase PDLIM2 inhibits NF-kB and STAT3 and is epigenetically repressed in human lung cancers (Sun et al. Nat. Comm. 2019 10: 5324); therefore, PDLIM2 is a tumor suppressor in lung cancer. In this manuscript, they follow up on their previous findings and show that expression of PDLIM2 is downregulated in human lung cancers by both genetic deletion and promoter methylation. They further describe a novel approach to restore the expression of PDLIM2 in mouse lung tumors by systemically administering PDLIM2 plasmids encapsulated in nanoparticles (termed "nanoPDLIM2"). The nanoPDLIM2 approach was shown to exhibit efficacy with low toxicity in a urethane-induced mouse lung cancer model. The authors further demonstrated the synergy of nanoPDLIM2 with chemotherapy and PD-1 blockade immunotherapy. The combination therapy of nanoPDLIM2, chemotherapy, and immunotherapy proved most effective with complete tumor remission in 60% of mice. Mechanistically, nanoPDLIM2 upregulated MHC-I expression, enhanced CD4/CD8 T cell activation and tumor infiltration, and suppressed MDR1 induction and nuclear expression of STAT3, RelA and prosurvival genes in tumors. Overall, this study is important because it reinforces the critical roles of PDLIM2 in suppressing lung cancer, and also identifies a potential approach to restoring PDLIM2 expression in lung tumors. The experiments were well executed; the data are convincing and support the conclusions made by the authors.

Reviewer #3 (Public Review):

Strengths:

NanoPDLIM2, nanotechnologies that efficiently deliver lentivirus overcomes resistance to chemotherapy and anti-PD-1 immunotherapy. This is a new strategy for enhancing the efficiency of immune checkpoint inhibitors. This finding is important from a clinical translation perspective, but I have several minor concerns.

Weaknesses:

1. Please describe the mechanism of increased MHC class I and PD-L1 by PDLIM2.<br /> 2. Please describe the mechanism of decreased MDR1, nuclear RelA and STAT3 by PDLIM2.<br /> 3. Please determine whether PDLIM2 expression directly impacts immune cells (function and number)?<br /> 4. What is the efficiency of PDLIM2 delivery? Does delivery efficiency determine anti-tumor effect?<br /> 5. Authors used a non-immunogenic tumor model. Can you demonstrate the combination effect with PDLIM2 in immunogenic lung cancer models to determine whether the combination of PDLIM2 with anti-PD-1 Ab confers a synergistic effect without chemotherapy?<br /> 6. On page 11, % change can make one over-interpret data.<br /> 7. In Figure 5, what is the difference between 5A and 5D?<br /> 8. It is unclear whether PDLIM2 confers an additive or a synergistic effect with anti-PD-1/chemo.<br /> 9. Have the authors tested any toxicity in normal lungs?

Reviewer #1 (Public Review):

In this manuscript, the authors demonstrated that YAP/TAZ promotes P-body formation in a series of cancer cell lines. YAP/TAZ modulates the transcription of multiple P-body-related genes, especially repressing the transcription of the tumor suppressor proline-rich nuclear receptor coactivator 1 (PNRC1) through cooperation with the NuRD complex. PNRC1 functions as a critical repressor in YAP-induced biogenesis of P-bodies and tumorigenesis in colorectal cancer (CRC). Reexpression of PNRC1 or disruption of P-bodies attenuated the protumorigenic effects of YAP. Overall, these findings are interesting and the study was well conducted.

Major concerns:

1. RNAseq data indicated that Yap has the capacity to suppress the expression of numerous genes. In addition to PNRC1, could there be additional Yap targeting factors involved in Yap-mediated the formation of P-bodies?<br /> 2. It is still not clear how PNRC1 regulates P-bodies. Knockdown of PNRC1 prevented the reduction of P-bodies caused by Yap knockdown. How do the genes related to P-bodies that are positively regulated by Yap, such as SAMD4A, AJUBA, and WTIP, change in this scenario? Given that the expression of Yap can differ considerably among various cell types, is it possible for P-bodies to be present in tumor cells lacking Yap expression?<br /> 3. The authors demonstrated that CHD4 can bind to Yap target genes, such as CTGF, AJUBA, SAMD4A (Figure 4 - Figure Supplement 1D). Does the NuRD complex repress the expression of these genes? the NuRD complex could prevent the formation of P-bodies?<br /> 4. YAP/TAZ promotes the formation of P-bodies which contradicts the previous study's conclusion (PMID: 34516278). Please address these inconsistent findings.

Reviewer #2 (Public Review):

In a study by Shen et al., the authors investigated YAP/TAZ target genes that play a role in the formation of processing bodies (P-bodies). P-bodies are membraneless cytoplasmic granules that contain translationally repressed mRNAs and components of mRNA turnover. GO enrichment analysis of the RNA-Seq data of colorectal cancer cells (HCT116) after YAP/TAZ knockdown showed that the downregulated genes were enriched in P-body resident proteins. Overexpression, knockdown, and ChIP-qPCR analyses showed that SAMD4A, PNRC1, AJUBA, and WTIP are YAP-TEAD target genes that also play a role in P-body biogenesis. Using P-body markers such as DDX6 and DCP1A, the authors showed that the knockdown of YAP in the HCT116 cell line causes a reduction in the number of P-bodies. Similarly, overexpression of constitutively active YAP (YAP 5SA) increased the P-body number. The YAP-TEAD target genes SAMD4A and AJUBA positively regulate P-body formation, because lowering their expression levels using siRNA reduces the number of P-bodies. The other YAP target gene, PNRC1, is a negative regulator of P-body biogenesis and consistently YAP suppresses its expression through the recruitment of the NuRD complex. YAP target genes that modulate P-body formation play prominent roles in oncogenesis. PNRC1 suppression is key to YAP-mediated proliferation, colony formation, and tumorigenesis in HCT116 xenografts. Similarly, SAMD4 and AJUBA knockdown abrogated cell viability. In summary, this study demonstrated that SAMD4, AJUBA, WTIP, and PNRC1 are bona fide YAP-TEAD target genes that play a role in P-body formation, which is also linked to the oncogenesis of colon cancer cells.

Major Strengths:

The majority of the experiments were appropriately planned so that the generated data could support the conclusions drawn by the authors. The phenotype observed with YAP/TAZ knockdown correlated inversely with YAP5SA overexpression, which is complementary. Where possible, the authors also used point mutations that selectively disrupt protein-protein interactions, such as YAP S94A and PNRC1 W300A. The CRC cell line HCT116 was used throughout the study; additionally, data from other cancer cell lines were used to support the generality of the findings.

Weaknesses:

The authors did not elucidate the mechanistic link between P-body formation and oncogenesis; therefore, it is unclear why an increase in the number of P-bodies is pro-tumorigenic. AJUBA and SAMD4 may have housekeeping functions and reduce the proliferation of YAP-independent cell lines. Figure 6 - Figure Supplement 4 shows a reduction in cell viability and migration in control HCT116 cell lines upon AJUBA/SAMD4 knockdown. Therefore, it is unclear whether their tumor suppressive role is YAP-dependent. The authors extrapolated and suggested that their findings could be exploited therapeutically, without providing much detail. How do they plan to stimulate the expression of PNRC1? It is not necessary for every scientific finding to lead to a therapeutic benefit; therefore, they can tone down such statements if therapeutic exploitation is not realistic. The authors elucidated a mechanism for PNRC1 repression and one wonders why no attempts were made to understand the mechanism of activation of SAMD4, AJUBA, and WTIP expression.

Reviewer #1 (Public Review):

This is a technically sound paper focused on a useful resource around the DRGP phenotypes which the authors have curated, pooled, and provided a user-friendly website. This is aimed to be a crowd-sourced resource for this in the future.

The authors should make sure they coordinate as well as possible with the NC datasets and community and broader fly community. It looks reasonable to me but I am not from that community.

I have only one major concern which in a more traditional review setting I would be flagging to the editor to insist the authors did on resubmission. I also have some scene setting and coordination suggestions and some minor textual / analysis considerations.

The major concern is that the authors do not comment on the distribution of the phenotypes; it is assumed it is a continuous metric and well-behaved - broad gaussian. This is likely to be more true of means and medians per line than individual measurements, but not guaranteed, and there could easily be categorical data in the future. The application of ANOVA tests (of the "covariates") is for example fragile for this.

The simplest recommendation is in the interface to ensure there is an inverse normalisation (rank and then project on a gaussian) function, and also to comment on this for the existing phenotypes in the analysis (presumably the authors are happy). An alternative is to offer a kruskal test (almost the same thing) on covariates, but note PLINK will also work most robustly on a normalised dataset.

Minor points:<br /> On the introduction, I think the authors would find the extensive set of human GWAS/PheWAS resources useful; widespread examples include the GWAS Catalog, Open Targets PheWAS, MR-base, and the FinnGen portal. The GWAS Catalog also has summary statistics submission guidelines, and I think where possible meta-data harmonisation should be similar (not a big thing). Of course, DRGP has a very different structure (line and individuals) and of course, raw data can be freely shown, so this is not a one-to-one mapping.

For some authors coming from a human genetics background, they will be interpreting correlations of phenotypes more in the genetic variant space (eg LD score regression), rather than a more straightforward correlation between DRGP lines of different individuals. I would encourage explaining this difference somewhere.

This leads to an interesting point that the inbred nature of the DRGP allows for both traditional genetic approaches and leveraging the inbred replication; there is something about looking at phenotype correlations through both these lenses, but this is for another paper I suspect that this harmonised pool of data can help.

I was surprised the authors did not crunch the number of transcript/gene expression phenotypes and have them in. Is this because this was better done in other datasets? Or too big and annoying on normalisation? I'd explain the rationale to leave these out.

I think 25% FDR is dangerously close to "random chance of being wrong". I'd just redo this section at a higher FDR, even if it makes the results less 'exciting'. This is not the point of the paper anyway.

I didn't buy the extreme line piece as being informative. Something has to be on the top and bottom of the ranks; the phenotypes are an opportunity for collection and probably have known (as you show) and cryptic correlations. I think you don't need this section at all for the paper and worry it gives an idea of "super normals" or "true wild types" which ... I just don't think is helpful.

I'd say "well-established inversion genotypes and symbiot levels" rather than generic covariates. Covariates could mean anything. You have specific "covariates" which might actually be the causal thing.

I wouldn't use the adjective tedious about curation. It's a bit of a value judgement and probably places the role of curation in the wrong way. Time-consuming due to lack of standards and best practice?

Reviewer #2 (Public Review):

Summary:<br /> ​In the present study, Gardeux et al provide a web-based tool for curated association mapping results from DRP studies. The tool lets users view association results for phenotypes and compare mean phenotype ~ phenotype correlations between studies. In the manuscript, the authors provide several example utilities associated with this new resource, including pan-study summary statistics for sex, traits, and loci. They highlight cross-trait correlations by comparing studies focused on longevity with phenotypes such as oxphos and activity.

Strengths:<br /> -Considerable efforts were dedicated toward curating the many DRG studies provided.<br /> -Available tools to query large DRP studies are sparse and so new tools present appeal

Weaknesses:<br /> The creation of a tool to query these studies for a more detailed understanding of physiologic outcomes seems underdeveloped. These could be improved by enabling usages such as more comprehensive queries of meta-analyses, molecular information to investigate given genes or pathways, and links to other information such as in mouse rat or human associations.

Reviewer #1 (Public Review):

General comments:<br /> This paper investigates the pH-specific enzymatic activity of mouse acidic mammalian chitinase (AMCase) and aims to elucidate its function's underlying mechanisms. The authors employ a comprehensive approach, including hydrolysis assays, X-ray crystallography, theoretical calculations of pKa values, and molecular dynamics simulations to observe the behavior of mouse AMCase and explore the structural features influencing its pH-dependent activity.

The study's key findings include determining kinetic parameters (Kcat and Km) under a broad range of pH conditions, spanning from strong acid to neutral. The results reveal pH-dependent changes in enzymatic activity, suggesting that mouse AMCase employs different mechanisms for protonation of the catalytic glutamic acid residue and the neighboring two aspartic acids at the catalytic motif under distinct pH conditions.

The novelty of this research lies in the observation of structural rearrangements and the identification of pH-dependent mechanisms in mouse AMCase, offering a unique perspective on its enzymatic activity compared to other enzymes. By investigating the distinct protonation mechanisms and their relationship to pH, the authors reveal the adaptive nature of mouse AMCase, highlighting its ability to adjust its catalytic behavior in response to varying pH conditions. These insights contribute to our understanding of the pH-specific enzymatic activity of mouse AMCase and provide valuable information about its adaptation to different physiological conditions.

Overall, the study enhances our understanding of the pH-dependent activity and catalytic properties of mouse AMCase and sheds light on its adaptation to different physiological pH environments.

Reviewer #2 (Public Review):

Summary: In this study of the mouse homolog of acidic mammalian chitinase, the overall goal is to provide a mechanistic explanation for the unusual observation of two pH optima for the enzyme. The study includes biochemical assays to establish kinetic parameters at different solution pH, structural studies of enzyme/substrate complexes, and theoretical analysis of amino acid side chain pKas and molecular dynamics.

Strengths: The biochemical assays are rigorous and nicely complemented by the structural and computational analysis. The mechanistic proposal that results from the study is well rationalized by the observations in the study.

Weaknesses: The overall significance of the work could be made more clear. Additional details could be provided about the limitations of prior biochemical studies of mAMC that warranted the kinetic analysis. The mouse enzyme seems unique in terms of its behavior at high and low pH, so it remains unclear how the work will enhance broader understanding of this enzyme class. It was also not clear can the findings be used for therapeutic purposes, as detailed in the abstract, if the human enzyme works differently.

Reviewer #1 (Public Review):

Summary:<br /> This study focuses on the defining cellular pathways critical for tRNA export from the nucleus. While a number of these pathways have been identified, the observation that the primary transport receptors identified thus far (Los1 and Msn5) are not essential and that cells are viable even when both the genes are deleted supports the idea that there are as yet unidentified mediators of tRNA export from the nucleus. This study implicates the helicase Dbp5 in one of these parallel pathways arguing that Dbp5 works in a pathway that is independent of Los1 and/or Msn5. The authors present genetic data to support this conclusion. At least one result suggests that the idea of these pathways in parallel may be too simplistic as deletion of the LOS1 gene, which is not essential decreases the interaction of tRNA export substrate with Dbp5 (Figure 2A). If the two pathways were working in parallel, one might have expected removing one pathway to lead to an increase in the use of the other pathway and hence the interaction with a receptor in that pathway. The authors provide solid evidence that Dbp5 interacts with tRNA directly and that the addition of the factor Gle1 together with the previously identified co-factor InsP6 can trigger helicase activity and release of tRNA. The combination of in vivo studies and biochemistry provides evidence to consider how Dbp5 contributes to the export of tRNA and more broadly adds to the conversation about how coding and non-coding RNA export from the nucleus might be coordinated to control cell physiology.

Strengths and weaknesses:<br /> A major strength of this manuscript is the multi-pronged approach to explore a potential role for the helicase Dbp5 in one of the multiple export pathways for tRNA from the nucleus.

The obvious missing experiment here with respect to genetics is the test of whether deletion of the MSN5 gene in the cells, which combines deletion of LOS1 and the dbp5_R423A allele, shown in Figure 1D would be lethal. This key experiment would lend substance to the argument that Dbp5 functions in a tRNA export pathway that is parallel to the Los1 and Msn5 pathways.

While some of the binding assays show rather modest band shifts (Figure 4B for example), the data in Figure 4A showing that there is no binding detected unless a non-hydrolyzable ATP analogue is employed, argues for specificity in nucleic acid binding. The question that does arise is whether the binding is specific for tRNA.

With the exception of the binding studies, which also employ a mixture of yeast tRNAs, this study relies primarily on a single tRNA species to come to the conclusions drawn. Many other studies have used multiple tRNAs to explore whether pathways characterized are generalizable to other tRNAs.

The authors provide evidence of a model where the helicase Dbp5 plays a role in tRNA export from the nucleus. Further evidence is required to determine whether Dbp5 could function in the same pathway as the previously defined tRNA export receptors, Los1 and Msn5. There are genetic tests that could be performed to explore this question. Some of the biochemistry presented would show when Los1 is absent that the interaction of Dbp5 with tRNA decreases, which could support a model where Dbp5 plays a role in coordination with Los1.

This work allows insight into key questions which still remain about the multiple pathways that are required for tRNA trafficking as well as how transport pathways for coding and non-coding RNAs might be coordinated. These questions are important as many of these pathways may be regulated in response to cellular conditions or during development and defining the fundamental pathways will be critical to understanding these dynamic processes.

Reviewer #2 (Public Review):

This submission is about the role of Dbp5/Gle1 in tRNA export. The manuscript provides data showing that Dbp5/Gle1 are involved in tRNA export from the nucleus which is an essential process critical to translation. The authors provide data that largely supports conclusions, however, there are some pieces of data that are misinterpreted. (Figure 1A and B look the same; in Fig 1E, the DAPI staining is abnormal; in Fig 4 the bands can't be seen.)

Additionally, the methods used are fairly standard so the article does not contain any new technical achievements.

Reviewer #1 (Public Review):

The authors present a study focused on addressing the key challenge in drug discovery, which is the optimization of absorption and affinity properties of small molecules through in silico methods. They propose active learning as a strategy for optimizing these properties and describe the development of two novel active learning batch selection methods. The methods are tested on various public datasets with different optimization goals and sizes, and new affinity datasets are curated to provide up-to-date experimental information. The authors claim that their active learning methods outperform existing batch selection methods, potentially reducing the number of experiments required to achieve the same model performance. They also emphasize the general applicability of their methods, including compatibility with popular packages like DeepChem.

Strengths:

Relevance and Importance: The study addresses a significant challenge in the field of drug discovery, highlighting the importance of optimizing the absorption and affinity properties of small molecules through in silico methods. This topic is of great interest to researchers and pharmaceutical industries.

Novelty: The development of two novel active learning batch selection methods is a commendable contribution. The study also adds value by curating new affinity datasets that provide chronological information on state-of-the-art experimental strategies.

Comprehensive Evaluation: Testing the proposed methods on multiple public datasets with varying optimization goals and sizes enhances the credibility and generalizability of the findings. The focus on comparing the performance of the new methods against existing batch selection methods further strengthens the evaluation.

Weaknesses:

Lack of Technical Details: The feedback lacks specific technical details regarding the developed active learning batch selection methods. Information such as the underlying algorithms, implementation specifics, and key design choices should be provided to enable readers to understand and evaluate the methods thoroughly.

Evaluation Metrics: The feedback does not mention the specific evaluation metrics used to assess the performance of the proposed methods. The authors should clarify the criteria employed to compare their methods against existing batch selection methods and demonstrate the statistical significance of the observed improvements.

Reproducibility: While the authors claim that their methods can be used with any package, including DeepChem, no mention is made of providing the necessary code or resources to reproduce the experiments. Including code repositories or detailed instructions would enhance the reproducibility and practical utility of the study.

Suggestions for Improvement:

Elaborate on the Methodology: Provide an in-depth explanation of the two active learning batch selection methods, including algorithmic details, implementation considerations, and any specific assumptions made. This will enable readers to better comprehend and evaluate the proposed techniques.

Clarify Evaluation Metrics: Clearly specify the evaluation metrics employed in the study to measure the performance of the active learning methods. Additionally, conduct statistical tests to establish the significance of the improvements observed over existing batch selection methods.

Enhance Reproducibility: To facilitate the reproducibility of the study, consider sharing the code, data, and resources necessary for readers to replicate the experiments. This will allow researchers in the field to validate and build upon your work more effectively.

Conclusion:

The authors' study on active learning methods for optimizing drug discovery presents an important and relevant contribution to the field. The proposed batch selection methods and curated affinity datasets hold promise for improving the efficiency of drug discovery processes. However, to strengthen the study, it is crucial to provide more technical details, clarify evaluation metrics, and enhance reproducibility by sharing code and resources. Addressing these limitations will further enhance the value and impact of the research.

Reviewer #2 (Public Review):

The authors presented a well-written manuscript describing the comparison of active-learning methods with state-of-art methods for several datasets of pharmaceutical interest. This is a very important topic since active learning is similar to a cyclic drug design campaign such as testing compounds followed by designing new ones which could be used to further tests and a new design cycle and so on. The experimental design is comprehensive and adequate for proposed comparisons. However, I would expect to see a comparison regarding other regression metrics and considering the applicability domain of models which are two essential topics for the drug design modelers community.

Reviewer #1 (Public Review):

The authors developed an extension to the pairwise sequentially Markov coalecent model that allows to simultaneously analyze multiple types of polymorphism data. In this paper, they focus on SNPs and DNA methylation data. Since methylation markers mutate at a much faster rate than SNPs, this potentially gives the method better power to infer size history in the recent past. Additionally, they explored a model where there are both local and regional epimutational processes.

Integrating additional types of heritable markers into SMC is a nice idea which I like in principle. However, a major caveat to this approach seems to be a strong dependence on knowing the epimutation rate. In Fig. 6 it is seen that, when the epimutation rate is known, inferences do indeed look better; but this is not necessarily true when the rate is not known. A roughly similar pattern emerges in Supp. Figs. 4-7; in general, results when the rates have to be estimated don't seem that much better than when focusing on SNPs alone. This carries over to the real data analysis too: the interpretation in Fig. 7 appears to hinge on whether the rates are known or estimated, and the estimated rates differ by a large amount from earlier published ones.

Overall, this is an interesting research direction, and I think the method may hold more promise as we get more and better epigenetic data, and in particular better knowledge of the epigenetic mutational process. At the same time, I would be careful about placing too much emphasis on new findings that emerge solely by switching to SNP+SMP analysis.

Reviewer #2 (Public Review):

A limitation in using SNPs to understand recent histories of genomes is their low mutation frequency. Tellier et al. explore the possibility of adding hypermutable markers to SNP based methods for better resolution over short time frames. In particular, they hypothesize that epimutations (CG methylation and demethylation) could provide a useful marker for this purpose. Individual CGs in Arabidopsis tends to be either close to 100% methylated or close to 0%, and are inherited stably enough across generations that they can be treated as genetic markers. Small regions containing multiple CGs can also be treated as genetic markers based on their cumulative methylation level. In this manuscript, Tellier et al develop computational methods to use CG methylation as a hypermutable genetic marker and test them on theoretical and real data sets. They do this both for individual CGs and small regions. My review is limited to the simple question of whether using CG methylation for this purpose makes sense at a conceptual level, not at the level of evaluating specific details of the methods. I have a small concern in that it is not clear that CG methylation measurements are nearly as binary in other plants and other eukaryotes as they are in Arabidopsis. However, I see no reason why the concept of this work is not conceptually sound. Especially in the future as new sequencing technologies provide both base calling and methylating calling capabilities, using CG methylation in addition to SNPs could become a useful and feasible tool for population genetics in situations where SNPs are insufficient.

Reviewer #3 (Public Review):

I very much like this approach and the idea of incorporating hypervariable markers. The method is intriguing, and the ability to e.g. estimate recombination rates, the size of DMRs, etc. is a really nice plus. I am not able to comment on the details of the statistical inference, but from what I can evaluate it seems sound and reasonable. This is an exciting new avenue for thinking about inference from genomic data. I have a few concerns about the presentation and then also questions about the use of empirical methylation data sets.

I think a more detailed description of demographic accuracy is warranted. For example, in L245 MSMC2 identifies the bottleneck (albeit smoothed) and only slightly overestimates recent size. In the same analysis the authors' approach with unknown mu infers a nonexistent population increase by an order of magnitude that is not mentioned.

Similarly, it seems problematic that (L556) the approach requiring estimation of site and region parameters (as would presumably be needed in most empirical systems like endangered nonmodel species mentioned in the introduction) does no better than using only SNPs. Overall, I think a more objective and perhaps quantitative comparison of approaches is warranted.

The authors simulate methylated markers at 2% (and in some places up to 20%). In many plant genomes a large proportion of cytosines are methylated (e.g. 70% in maize: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8496265/). I don't know what % of these may be polymorphic, but this leads to an order of magnitude more methylated cytosines than there are SNPs. Couldn't this mean that any appreciable error in estimating methylation threatens to be of a similar order of magnitude to the SNP data? I would welcome the authors' thoughts here.

A few points of discussion about the biology of methylation might be worth including. For example, methylation can differ among cell types or cells within a tissue, yet sequencing approaches evaluate a pool of cells. This results in a reasonable fraction of sites having methylation rates not clearly 0 or 1. How does this variation affect the method? Similarly, while the authors cite literature about the stable inheritance of methylation, a sentence or so more about the time scale over which this occurs would be helpful. Finally, in some species methylated cytosines have mutation rates an order of magnitude higher than other nucleotides. The authors mention they assume independence, but how would violation of this assumption affect their inference?

Reviewer #1 (Public Review):

Summary:<br /> The precise mechanism of how tetraspanin proteins engage in the generation of discs is still an open question in the field of photoreceptor biology. This question is of significance as the lack of photoreceptor discs or defects in disc morphogenesis due to mutations in tetraspanin proteins is a known cause of vision loss in humans. The authors of this study combine TEM and mouse models to tease out the role of tetraspanin proteins, peripherin, and Rom1 in the genesis of the photoreceptor discs. They show that the absence of Rom1 leads to an increase in peripherin and changes in disc morphology. Further rise in peripherin alleviates some of the defects observed in Rom1 knockout animals leading to the conclusion that peripherin can substitute for the absence of Rom1.

Strengths:<br /> A mouse model of Rom1 generated by the McInnes group in 2000 predicted a role for Rom1 in rim closure. They also showed enlarged discs in the absence of Rom1. This study confirmed this finding and showed the compensatory changes in peripherin, maintaining the total levels of tetraspanin proteins. Lack of Rom1 leads to excessive open disks demonstrated by darkly stained tannic acid-accessible areas in TEM. Interestingly, increased peripherin expression can rescue some morphological defects, including maintaining normal disc diameters and incisures. Overall, these observations lead authors to propose a model that ROM1 can be replaced by peripherin.

Weaknesses:<br /> The compensatory increase in peripherin and morphological rescue in the absence of ROM1 is expected, given the previous work from authors showing i) absence of peripherin showing increased ROM1 and ii) "Eliminating Rom1 also increased levels of Prph2/RRCT: mean Prph2/RRCT levels in P30 Prph2+/R retinas were 34% of WT, while levels in Prph2+/R/Rom1−/− retinas were 59% of WT" from Conley, 2019. The current study provides a comprehensive quantitative analysis. However, the mechanism behind the mechanism is unclear and warrants discussion.

Photoreceptor morphology appears better when peripherin is overexpressed. Is there a rescue of rod function (assessed by ERG or equivalent measures) in peripherin OE/Rom1-/- mice? Given the extensive work in this area and the implications the authors allude to at the end, it is important to investigate this aspect.

Reviewer #2 (Public Review):

In this study, Lewis et al seek to further define the role of ROM1. ROM1 is a tetraspanin protein that oligomerizes with another tetraspanin, PRPH2, to shape the rims of the membrane discs that comprise the light-sensitive outer segment of vertebrate photoreceptors. ROM1 knockout mice and several PRPH2 mutant mice are reexamined. The conclusion reached is that ROM1 is redundant to PRPH2 in regulating the size of newly forming discs, although excess PRPH2 is required to compensate for the loss of ROM1.

This replicates earlier findings while adding rigor using a mass spectrometry-based approach to quantitate the ratio of ROM1 and PRPH2 to rhodopsin (the protein packed in the body of the disc membranes) and careful analysis of tannic acid labeled newly forming discs using transmission electron microscopy.

In ROM1 knockout mice PRPH2 expression was found to be increased so that the level of PRPH2 in those mice matches the combined amount of PRPH2 and ROM1 in wildtype mice. Despite this, there are defects in disc formation that are resolved when the ROM1 knockout is crossed to a PRPH2 overexpressing line. A weakness of the study is that the molar ratios between ROM1, PRPH2 and rhodopsin were not measured in the PRPH2 overexpressing mice. This would have allowed the authors to be more precise in their conclusion that a 'sufficient' excess of PRPH2 can compensate for defects in ROM1.

Reviewer #3 (Public Review):

In this manuscript, Lewis et al. investigate the role of tetraspanins in the formation of discs - the key structure of vertebrate photoreceptors essential for light reception. Two tetraspanin proteins play a role in this process: PRPH2 and ROM1. The critical contribution of PRPH2 has been well established and loss of its function is not tolerated and results in gross anatomical pathology and degeneration in both mice and humans. However, the role of ROM1 is much less understood and has been considered somewhat redundant. This paper provides a definitive answer about the long-standing uncertainty regarding the contribution of ROM1 firmly establishing its role in outer segment morphogenesis. First, using an ingenious quantitative proteomic technique the authors show PRPH2 compensatory increase in ROM1 knockout explaining the redundancy of its function. Second, they uncover that despite this compensation, ROM1 is still needed, and its loss delays disc enclosure and results in the failure to form incisures. Third, the authors used a transgenic mouse model and show that deficits seen in ROM1 KO could be completely compensated by the overexpression of PRPH2. Finally, they analyzed yet another mouse model based on double manipulation with both ROM1 loss and expression of PRPH2 mutant unable to form dimerizing disulfide bonds further arguing that PRPH2-ROM1 interactions are not required for disc enclosure. To top it off the authors complement their in vivo studies by a series of biochemical assays done upon reconstitution of tetraspanins in transfected cultured cells as well as fractionations of native retinas. This report is timely, addresses significant questions in cell biology of photoreceptors, and pushes the field forward in a classical area of photoreceptor biology and mechanics of membrane structure as well. The manuscript is executed at the top level of technical standard, exceptionally well written, and does not leave much more to desire. It also pushes standards of the field- one such domain is the quantitative approach to analysis of the EM images which is notoriously open to alternative interpretations - yet this study does an exceptional job unbiasing this approach.

According to my expertise in photoreceptor biology, there is nothing wrong with this manuscript either technically or conceptually and I have no concerns to express.

Reviewer #1 (Public Review):

In this study, the authors investigated the role of MAM and the Notch signaling pathway in the onset of the atrophic phenotype in both in vivo and in vitro models. The rationale used to obtain the data is one of the main strengths of the study. Already from the reading, the reasoning scheme used by the authors in setting up the study and evaluating the data obtained is clear. Using both cellular and mouse models in vivo consolidates the data obtained. The authors also methodologically described all the choices made in the supplementary section. A weakness, on the other hand, is the failure to include averages and statistical data in the results that would give a quantifiable idea of the data obtained. To complete the picture, the authors could also investigate the possible involvement of the intrinsic apoptosis pathway as well as describe probable metabolic shifts to muscle cells in atrophic conditions. The rationale used by the authors to obtain the result is linear. The data obtained are useful for understanding the onset and characterization of the atrophic phenotype under disuse and microgravity conditions. The methods used are in line with those used in the field and can be a starting point for other studies. The cellular models are well described in the materials and methods section. The selected mouse models followed a logical rationale and were in line with the intended aim.

Reviewer #2 (Public Review):

In this study, the authors examined how the maintenance of mitochondrial-associated endoplasmic reticulum membranes (MAM) is critical for the prevention of muscle atrophy under microgravity conditions. They observed, a reduction in MAM in myotubes placed in a microgravity condition; in addition, MFN2-deficient human iPS cells showed a decrease in the number of MAM, similar to in myotubes differentiated under microgravity conditions, in addition to the activation of the Notch signaling pathway. The authors, moreover, observed that treatment with the gamma-secretase inhibitor with DAPT preserved the atrophic phenotype of differentiated myotubes in microgravity and improve the regenerative capacity of Mfn2-deficient muscle stem cells in dystrophic mice.

The entire study was well conducted, bringing an interesting analysis in vitro and in vivo of aging conditions. In my opinion, it is necessary to improve the analysis of both genes and proteins to better support the conclusions

The study can contribute to a better understanding of one of the major problems of aging, such as muscle atrophy and inhibition of muscle regeneration, emphasizing the importance of the NOTCH pathway in these pathological situations. The work will be of interest to all scientists working on aging.

Reviewer #1 (Public Review):

Summary:

Sender et al describe a model to estimate what fraction of DNA becomes cell-free DNA in plasma. This is of great interest to the community, as the amount of DNA from a certain tissue (for example, a tumor) that becomes available for detection in the blood has important implications for disease detection.

However, the authors' methods do not consider important variables related to cell-free DNA shedding and storage, and their results may thus be inaccurate. At this stage of the paper, the methods section lacks important detail. Thus, it is difficult to fully assess the manuscript and its results.

Strengths:

The question asked by the authors has potentially important implications for disease diagnosis. Understanding how genomic DNA degrades in the human circulation can guide towards ways to enrich for DNA of interest or may lead to unexpected methods of conserving cell-free DNA. Thus, the question "how much genomic DNA becomes cfDNA" is of great interest to the scientific and medical community. Once the weaknesses of the manuscript are addressed, I believe this manuscript has the potential to be a widely used resource.

Weaknesses:

There are two major weaknesses in how the analysis is presented. First, the methods lack detail. Second, the analysis does not consider key variables in their model.

Issues pertaining to the methods section.<br /> The current manuscript builds a flux model, mostly taking values and results from three previous studies:

1- The amount of cellular turnover by cell type, taken from Sender & Milo, 2021<br /> 2- The fractions of various tissues that contribute DNA to the plasma, taken from Moss et al, 2018 and Loyfer et al, 2023

My expertise lies in cell-free DNA, and so I will limit my comments to the manuscripts in (2).

Paper by Loyfer et al (additional context):

Loyfer et al is a recent landmark paper that presents a computational method for deconvoluting tissues of origin based on methylation profiles of flow-sorted cell types. Thus, the manuscript provides a well-curated methylation dataset of sorted cell-types. The majority of this manuscript describes the methylation patterns and features of the reference methylomes (bulk, sorted cell types), with a smaller portion devoted to cell-free DNA tissue of origin deconvolution.

I believe the data the authors are retrieving from the Loyfer study are from the 23 healthy plasma cfDNA methylomes analyzed in the study, and not the re-analysis of the 52 COVID-19 samples from Cheng et al (MED 2021).

Paper by Moss et al (additional context):

Moss et al is another landmark paper that predates the Loyfer et al manuscript. The technology used in this study (methylation arrays) is outdated but is an incredible resource for the community. This paper evaluates cfDNA tissues of origin in health and different disease scenarios. Again, I assume the current manuscript only pulled data from healthy patients, although I cannot be sure as it is not described in the methods section.

This manuscript:

The current manuscript takes (I think) the total cfDNA concentration from males and females from the Moss et al manuscript (pooled cfDNA; 2 young male groups, 2 old male groups, 2 young female groups, 2 old female groups, Supplementary Dataset; "total_cfDNA_conc" tab). I believe this is the data used as total cfDNA concentration. It would be beneficial for all readers if the authors clarified this point.

The tissues of origin, in the supplemental dataset ("fraction" tab), presents the data from 8 cell types (erythrocytes, monocytes/macrophages, megakaryocytes, granulocytes, hepatocytes, endothelial cells, lymphocytes, other). The fractions in the spreadsheet do not match the Loyfer or Moss manuscripts for healthy individuals. Thus, I do not know what values the supplementary dataset represents. I also don't know what the deconvolution values are used for the flux model.

The integration of these two methods lack detail. Are the authors here using yields (ie, cfDNA concentrations) from Moss et al, and tissue fractions from Loyfer et al? If so, why? There are more samples in the Loyfer manuscript, so why are the samples from Moss et al. being used? The authors are also selectively ignoring cell-types that are present in healthy individuals (Neurons from Moss et al, 2018). Why?

Appraisal:

At this stage of the manuscript, I think additional evidence and analysis is required to confirm the results in the manuscript.

Impact:

Once the authors present additional analysis to substantiate their results, this manuscript will be highly impactful on the community. The field of liquid biopsies (non-invasive diagnostics) has the potential to revolutionize the medical field (and has already in certain areas, such as prenatal diagnostics). Yet, there is a lack of basic science questions in the field. This manuscript is an important step forward in asking more "basic science" questions that seek to answer a fundamental biological question.

Reviewer #2 (Public Review):

Summary:

Cell-free DNA (cfDNA) are short DNA fragments released into the circulation when cells die. Plasma cfDNA level is thought to reflect the degree of cell-death or tissue injury. Indeed, plasma cfDNA is a reliable diagnostic biomarker for multiple diseases, providing insights into disease severity and outcomes. In this manuscript, Dr. Sender and colleagues address a fundamental question: What fraction of DNA released from cell death is detectable as plasma cfDNA? The authors use public data to estimate the amount of DNA produced from dying cells. They also utilize public data to estimate plasma cfDNA levels. Their calculations showed that <10% of DNA released is detectable as plasma cfDNA, the fraction of detectable cfDNA varying by tissue sources. The study demonstrates new and fundamental principles that could improve disease diagnosis and treatment via cfDNA.

Strengths:

1. The experimental approach is resource-mindful taking advantage of publicly available data to estimate the fraction of detectable cfDNA in physiological states. The authors did not assess if the fraction of detectable cfDNA changes in disease conditions. Nonetheless, their pioneering study lays the foundation and provides the methods needed for a similar assessment in disease states.<br /> 2. The findings of this study potentially explain discrepancies in measured versus expected tissue-specific cfDNA from some tissues. For example, the gastrointestinal tract is subject to high cell turnover and release of DNA. Yet, only a small fraction of that DNA ends up in plasma as gastrointestinal cfDNA.<br /> 3. The study proposes potential mechanisms that could account for the low fraction of detectable cfDNA in plasma relative to DNA released. This includes intracellular or tissue machinery that could "chew up" DNA released from dying cells, allowing only a small fraction to escape into plasma as cfDNA. Could this explain why the gastrointestinal track with an elaborate phagosome machinery contributes a small fraction of plasma cfDNA? Given the role of cfDNA as damage-associated molecular pattern in some diseases, targeting such a machinery may provide novel therapeutic opportunities.

Weaknesses: In vitro and in vivo studies are needed to validate these findings and define tissue machinery that contribute to cfDNA production. The validation studies should address the following limitations of the study design: -

1. Align the cohorts to estimate DNA production and plasma cfDNA levels. Cellular turnover rate and plasma cfDNA levels vary with age, sex, circadian clock, and other factors (Madsen AT et al, EBioMedicine, 2019). This study estimated DNA production using data abstracted from a homogenous group of healthy control males (Sender & Milo, Nat Med 2021). On the other hand, plasma cfDNA levels were obtained from datasets of more diverse cohort of healthy males and females with a wide range of ages (Loyfer et al. Nature, 2023 and Moss et al., Nat Commun, 2018).<br /> 2. "cfDNA fragments are not created equal". Recent studies demonstrate that cfDNA composition vary with disease state. For example, cfDNA GC content, fraction of short fragments, and composition of some genomic elements increase in heart transplant rejection compared to no-rejection state (Agbor-Enoh, Circulation, 2021). The genomic location and disease state may therefore be important factors to consider in these analyses.<br /> 3. Alternative sources of DNA production should be considered. Aside from cell death, DNA can be released from cells via active secretion. This and other additional sources of DNA should be considered in future studies. The distinct characteristics of mitochondrial DNA to genomic DNA should also be considered.

Reviewer #1 (Public Review):

The association of vitamin D supplementation in reducing Asthma risk is well studied, although the mechanistic basis for this remains unanswered. In the presented study, Kilic and co-authors aim to dissect the pathway of Vitamin D mediated amelioration of allergic airway inflammation. They use initial leads from bioinformatic approaches, which they then associate with results from a clinical trial (VDAART) and then validate them using experimental approaches in murine models. The authors identify a role of VDR in inducing the expression of the key regulator Ikzf3, which possibly suppresses the IL-2/STAT5 axis, consequently blunting the Th2 response and mitigating allergic airway inflammation.

Strengths:<br /> The major strength of the paper lies in its interdisciplinary approach, right from hypothesis generation, and linkage with clinical data, as well as in the use of extensive ex vivo experiments and in vivo approaches using knock-out mice.

The study presents some interesting findings including an inducible baseline absence/minimal expression of VDR in lymphocytes, which could have physiological implications and needs to be explored in future studies.

Weaknesses:<br /> The core message of the study relies on the role of vitamin D and its receptor in suppressing the Th2 response. However, there is scope for further dissection of relevant pathophysiological parameters in the in vivo experiments, which would enable stronger translation to allergic airway diseases like Asthma.

To a large extent, the authors have been successful in validating their results, although a few inferences could be reinforced with additional techniques, or emphasised in the discussion section (possibly utilising the ideas and speculative section offered by the journal).

The study inferences also need to be read in the context of the different sub-phenotypes and endotypes of Asthma, where the Th2 response may not be predominant. Moreover, the authors have referenced vitamin D doses for the murine models from the VDAART trials and performed the experiments in the second generation of animals. While this is appreciated, the risk of hypervitaminosis-D cannot be ignored, in view of its lipid solubility. Possibly comparison and justification of the doses used in murine experiments from previous literature, as well as the incorporation of an emphasised discussion about the side effects and toxicity of Vitamin D, is an important aspect to consider.

In no way do the above considerations undermine the importance of this elegant study which justifies trials for vitamin D supplementation and its effects on Asthma. The work possesses tremendous potential.

Reviewer #2 (Public Review):

Summary:<br /> This study seeks to advance our knowledge of how vitamin D may be protective in allergic airway disease in both adult and neonatal mouse models. The rationale and starting point are important human clinical, genetic/bioinformatic data, with a proposed role for vitamin D regulation of 2 human chromosomal loci (Chr17q12-21.1 and Chr17q21.2) linked to the risk of immune-mediated/inflammatory disease. The authors have made significant contributions to this work specifically in airway disease/asthma. They link these data to propose a role for vitamin D in regulating IL-2 in Th2 cells implicating genes associated with these loci in this process.

Strengths:<br /> Here the authors draw together evidence from multiple lines of investigation to propose that amongst murine CD4+ T cell populations, Th2 cells express high levels of VDR, and that vitamin D regulates many of the genes on the chromosomal loci identified to be of interest, in these cells. The bottom line is the proposal that vitamin D, via Ikfz3/Aiolos, suppresses IL-2 signalling and reduces IL-2 signalling in Th2 cells. This is a novel concept and whilst the availability of IL-2 and the control of IL-2 signalling is generally thought to play a role in the capacity of vitamin D to modulate both effector and especially regulatory T cell populations, this study provides new data.

Weaknesses:<br /> Overall, this is a highly complicated paper with numerous strands of investigation, methodologies etc. It is not "easy" reading to follow the logic between each series of experiments and also frequently fine detail of many of the experimental systems used (too numerous to list), which will likely frustrate immunologists interested in this. There is already extensive scientific literature on many aspects of the work presented, much of which is not acknowledged and largely ignored. For example, reports on the effects of vitamin D on Th2 cells are highly contradictory, especially in vitro, even though most studies agree that in vivo effects are largely protective. Similarly, other reports on adult and neonatal models of vitamin D and modulation of allergic airway disease are not referenced. In summary, the data presentation is unwieldy, with numerous supplementary additions, which makes the data difficult to evaluate and the central message lost. Whilst there are novel data of interest to the vitamin D and wider community, this manuscript would benefit from editing to make it much more readily accessible to the reader.

Wider impact: Strategies to target the IL-2 pathway have long been considered and there is a wealth of knowledge here in autoimmune disease, transplantation, GvHD etc - with some great messages pertinent to the current study. This includes the use of IL-2, including low dose IL-2 to boost Treg but not effector T cell populations, to engineered molecules to target IL-2/IL-2R.

Reviewer #1 (Public Review):

Hwang et al., report that LRRC23 is required for RS3 head assembly and sperm motility, and the truncating LRRC23 is associated with asthenozoospermia in humans. They identified an LRRC23 variant in a consanguineous Pakistani family with infertile males diagnosed as asthenozoospermia and found this variant leads to early termination of LRRC23 translation with loss of 136 amino acids at the C-terminus. They generated Lrrc23 mutant mice that mimic the predicted outcome in human patients and found the truncated LRRC23 specifically disorganizes RS3 and the junctional structure between RS2 and RS3 in the sperm axoneme, which causes sperm motility defects and male infertility. These dates try to elucidate the pathogenicity of LRRC23 in asthenozoospermia. The conclusions of this paper are mostly well supported by data, but many aspects of data analyses and data interpretations need to be improved.

1) The pathogenesis of truncating LRRC23 in asthenozoospermia needs to be further considered. The molecular mechanism of LRRC23 demonstrated in mice should be tested in patients with the LRRC23 variant. As it may be difficult to determine the structures of RS3 in the infertile male sperm, the LRRC23 localization should be observed in the sperm from patients with the LRRC23 variant.<br /> 2) The absence of the RS3 head in LRRC23Δ/Δ mouse sperm is not sufficient to support the specific localization of LRRC23 in RS3 head. Although LRRC23 might bind to RS head protein RSPH9, the authors state that "RSPH9 is a head component of RS1 and RS2 like in C. reinhardtii (Gui et al, 2021), but not of RS3" as the protein level and the localization of RSPH9 is not altered in LRRC23Δ/Δ sperm. Thus, the specific localization of LRRC23 in RS3 head should be further confirmed.<br /> 3) The interaction between LRRC23 and RSPH9 needs to be defined. AlphaFold models could help determine the likelihood of a direct interaction. In addition, the structure of the 96-nm modular repeats of axonemes from the flagella of human respiratory cilia has been determined (PMID: 37258679), and the localization of LRRC23 in RS could be further predicted.<br /> 4) The ortholog of the RSP15 may also be predicted or confirmed by using the reported structure in human respiratory cilia (PMID: 37258679). Whether the LRCC34 in RS2 is LRRC34?

Reviewer #2 (Public Review):

Summary:<br /> The present study explores the molecular function of LRRC23 in male fertility, specifically in the context of the regulation of spermiogenesis. The author initiates the investigation by identifying LRRC23 mutations as a potential cause of male sterility based on observations made in closely related individuals affected by asthenozoospermia (ASZ). To further investigate the function of LRRC23 in spermatogenesis, mutant mice expressing truncated LRRC23 proteins are created, aligning with the identified mutation site. Consequently, the findings confirm the deleterious effects of LRRC23 mutations on sperm motility in these mice while concurrently observing no significant abnormalities in the overall flagella structure. Furthermore, the study reveals LRRC23's interaction with the RS head protein RSPH9 and its active involvement in the assembly of the axonemal RS. Notably, LRRC23 mutations result in the loss of the RS3 head structure and disruption of the RS2-RS3 junction structure. Therefore, the author claimed that LRRC23 is an indispensable component of the RS3 head structure and suggests that mutations in LRRC23 underlie sterility in mice.

Strengths:<br /> The key contribution of this article lies in confirming LRRC23's involvement in assembling the RS3 head structure in sperm flagella. This finding represents a significant advancement in understanding the complex architecture of the RS3 structural complex, building upon previous studies. Moreover, the article's topic is interesting and originates from clinical research, which holds significant implications for potential clinical applications.

Weaknesses:<br /> 1. While the author generated mutant mice expressing truncated LRRC23 proteins, the expression of these truncated proteins was not detected in sperm. This implies that, in terms of sperm structure, the mutant LRRC23 protein behaves similarly to the complete knockout of the LRRC23 protein, which has been previously reported and characterized (Zhang et al., 2021).

2. This reviewer questions the proposal that LRRC23 is an integral component of RS3, as the results indicate not only the loss of the RS3 head structure but also an incomplete RS2-RS3 junction structure. In addition, the interaction of LRRC23 with RSPH9 alone does not fully explain its involvement solely in RS3 assembly. Additional evidence is required to examine the influence of LRRC23 on the RS2-RS3 junction.

3. The article does not explore how these mutations affect the flagella structure in human sperm, which needs further study. Expanding the study to include human sperm structure would undoubtedly enhance the quality of the article.

Reviewer #1 (Public Review):

Summary: This impressive study by Bandet and Winship uses 2-photon imaging in awake-behaving mice to examine long-term changes in neural activity and functional connectivity after focal ischemic stroke. The authors discover that there are long-lasting perturbations in neural activity and functional connectivity, specifically within peri-infarct cortex but not more distant cortical regions. Overall I thought the study provided important new findings that were supported by compelling data.

Strengths: This is a technically challenging study to perform and the authors show high-quality data. The manuscript was well-written, and the figures were clearly presented. I really like the analytic tools they applied, which were rigorous and provided some novel insights regarding neural activity patterns during movement or rest. The discovery of long-lasting impairments in neural activity/functional connectivity is an important one as it is important for future stroke studies to recognize what problems need to be rectified in the post-stroke brain, even many weeks after injury. They also suggest there is a much more nuanced relationship between macroscopic changes in somatosensory maps and single-cell activity. Overall, I think this is a well-executed study whose primary conclusions were justified by the data presented.

Weaknesses: I found very little in the way of weaknesses. The statistics were notably conservative and are appropriate.

Reviewer #2 (Public Review):

This study investigates the excitability of neurons in the peri-infarct cortex during recovery from ischemic stroke. The excitability of neurons in the peri-infarct cortex during stroke recovery has produced contradictory findings: some studies suggest hyper-excitability to direct-brain stimulation, while others indicate diminished responsiveness to physical stimuli. However, most studies have used anesthetized animals, which can disrupt cortical activity and functional connectivity. The present study used two-photon Ca2+ imaging after focal photothrombotic stroke to examine neural activity patterns in awake mice. The authors found reduced neuronal spiking in the peri-infarct cortex that was strongly correlated with motor performance deficits. Additionally, the authors found disruptions in neural activation, functional connectivity, and assembly architecture in the immediate peri-infarct region but not in the distal cortex regions.

The findings of this study are very important as they show that there is no measurable change in terms of neuronal activation and reorganization in distal regions of remapped cortical response areas after stroke.

However, cortical response areas are calculated using a threshold of 95% peak activity within a trial. The threshold is presumably used to discriminate between the sensory-evoked response and collateral activation / less "relevant" response (noise). Since the peak intensity is lower after stroke, the "response" area is larger - lower main signal results in less noise exclusion. Predictably, areas that show a higher response before stroke than after are excluded from the response area before the stroke and included after.

We suggest a reinterpretation of the findings: much of the non-remapped areas are included when using a within-trial threshold as a criterion, and the absence of increased neuronal activation and reorganization is evidence for this claim. The take-home message of this study should be that we need a much better criterion for what we consider remapping.

Reviewer #1 (Public Review):

Existing literature suggests that brain structures implicated in memory such as the hippocampus, and reward/punishment processing such as the striatal regions are also engaged in learning and value-based decision-making. However, how the contributions of these regions to learning and value-based decision-making change over time, particularly in children where these neural systems show protracted maturation was not studied systematically. This is the question the authors are aiming to address in this work in which children 6-to-7-years-old were recruited for a neuroimaging study that involves taking structural scans from this cohort to investigate how they correlate with changes in the way children approach a reinforcement learning task in which they learn to identify the better shape between 2 options through trial-and-error.

Particular strengths of the paper are longitudinally following up a cohort of small children and engaging them in a value-based decision-making task so that the relationship between neural maturation and improvements in reinforcement learning can be studied reliably. Towards this end, the authors make use of well-established computational modelling approaches to extract key parameters such as learning rates (which designate the speed of learning from expected versus actual outcomes) or choice stochasticity (which designate the inherent variation in people's decisions and the tendency to explore between the options) from children's choices so that their structural neural correlates can be established. As a part of this endeavour, the authors rely on methodological choices which do not warrant much criticism. Their data visualization choices are particularly spot-on and highly informative about the details of the raw data.

Also considering the importance of the hippocampal system in human memory, the key contribution of the paper is that the volumetric increases in hippocampus size between 2 assessment points correlated selectively with the delayed, but not immediate, learning score which refers to the learning condition in which the outcome feedback is given to the children after a 5-seconds delay. Although the authors also demonstrate evidence to suggest that changes in the striatal volume are also implicated in learning performance, this was more general as associations were found for both immediate and delayed feedback conditions. Thus, the paper makes an important contribution to the fields of developmental and decision neuroscience. An important question arising from the authors' findings could be that, whether the hippocampus maintains this selective role in value-based learning during the course of neuronal development, for example, whether a similar association would be found in children 8-to-9 years old. A better understanding of how these developmental trajectories map onto changes in learning and decision-making can inform fields outside neuroscience, for example tailoring educational approaches onto neural development pathways to boost learning efficiency in young children.

Reviewer #2 (Public Review):

Summary:<br /> This is an interesting and impressive study that provides a rare opportunity to learn about brain-behaviour links of learning systems at a relatively early stage of development.

Strengths:<br /> The main strengths are that the authors followed a relatively large group of children over 2 years and used a reinforcement learning task aimed at assessing learning that depends on both the striatum and the hippocampus. The authors also included a thorough overview of the computational models and the choices they made. I think this paper would be of considerable interest and contributes to knowledge about how learning and memory systems change with development.

Weaknesses:<br /> There were a few things that I thought would be helpful to clarify. First, what exactly are the anatomical regions included in the striatum here? Second, it was mentioned that for the reduced dataset, object recognition memory focused on "sure" ratings. This seems like the appropriate way to do it, but it was not clear whether this was also the case for the full analyses in the main text. Third, the children's fitted parameters were far from optimal; is it known whether adults would be closer to optimal on the task?

The main thing I would find helpful is to better integrate the differences between the main results reported and the many additional results reported in the supplement, for example from the reduced dataset when excluding non-learners. I found it a bit challenging to keep track of all the differences with all the analyses and parameters. It might be helpful to report some results in tables side-by-side in the two different samples. And if relevant, discuss the differences or their implication in the Discussion. For example, if the patterns change when excluding the poor learners, in particular for the associations between delayed feedback and hippocampal volume, and those participants were also those less well fit by the value-based model, is that something to be concerned about and does that affect any interpretations? What was not clear to me is whether excluding the poor learners at one extreme simply weakens the general pattern, or whether there is a more qualitative difference between learners and non-learners. The discussion points to the relevance of deficits in hippocampal-dependent learning for psychopathology and understanding such a distinction may be relevant.

Reviewer #1 (Public Review):

The aim of this study is to test the overarching hypothesis that plasticity in BNST CRF neurons drives distinct behavioral responses to unpredictable threat in males and females. The manuscript provides evidence for a possible sex-specific role for CRF-expressing neurons in the BNST in unpredictable aversive conditioning and subsequent hypervigilance across sexes. As the authors note, this is an important question given the high prevalence of sex differences in stress-related disorders, like PTSD, and the role of hypervigilance and avoidance behaviors in these conditions. The study includes in vivo manipulation, bulk calcium imaging, and cellular resolution calcium imaging, which yield important insights into cell-type specific activity patterns. However, it is difficult to generate an overall conclusion from this manuscript, given that many of the results are inconsistent across sexes and across tests and there is an overall lack of converging evidence. For example, partial conditioning yields increased startle in males but not females, yet, CRF KO only increases startle response in males after full conditioning, not partial, and CRF neurons show similar activity patterns between partial and full conditioning across sexes. Further, while the study includes a KO of CRF, it does not directly address the stated aim of assessing whether plasticity in CRF neurons drives the subsequent behavioral<br /> effects unpredictable threat.

A major strength of this manuscript is the inclusion of both males and females and attention to possible behavioral and neurobiological differences between them throughout. However, to properly assess sex-differences, sex should be included as a factor in ANOVA (e.g. for freezing, startle, and feeding data in Figure 1) to assess whether there is a significant main effect or interaction with sex. If sex is not a statistically significant factor, both sexes should be combined for subsequent analyses. See, Garcia-Sifuentes and Maney, eLife 2021 https://elifesciences.org/articles/70817. There are additional cases where t-tests are used to compare groups when repeated measures ANOVAs would be more appropriate and rigorous.

Additionally, it's unclear whether the two sexes are equally responsive to the shock during conditioning and if this is underlying some of the differences in behavioral and neuronal effects observed. There are some reports that suggest shock sensitivity differs across sexes in rodents, and thus, using a standard shock intensity for both males and females may be confounding effects in this study.

The data does not rule out that BNST CRF activity is not purely tracking the mobility state of the animal, given that the differences in activity also track with differences in freezing behavior. The data shows an inverse relationship between activity and freezing. This may explain a paradox in the data which is why males show a greater suppression of BNST activity after partial conditioning than full conditioning, if that activity is suspected to drive the increased anxiety-like response. Perhaps it reflects that activity is significantly suppressed at the end of the conditioning session because animals are likely to be continuously freezing after repeated shock presentations in that context. It would also explain why there is less of a suppression in activity over the course of the recall session, because there is less freezing as well during recall compared with conditioning.

A mechanistic hypothesis linking BNST CRF neurons, the behavioral effects observed after fear conditioning, and manipulation of CRF itself are not clearly addressed here.

Reviewer #2 (Public Review):

This study examined the role of CRF neurons in the BNST in both phasic and sustained fear in males and females. The authors first established a differential fear paradigm whereby shocks were consistently paired with tones (Full) or only paired with tones 50% of the time (Part), or controls who were exposed to only tones with no shocks. Recall tests established that both Full and Part conditioned male and female mice froze to the tones, with no difference between the paradigms. Additional studies using the NSF and startle test, established that neither fear paradigm produced behavioral changes in the NSF test, suggesting that these fear paradigms do not result in an increase in anxiety-like behavior. Part fear conditioning, but not Full, did enhance startle responses in males but not females, suggesting that this fear paradigm did produce sustained increases in hypervigilance in males exclusively. Photometry studies found that while undifferentiated BNST neurons all responded to shock itself, only Full conditioning in males lead to a progressive enhancement of the magnitude of this response. BNST neurons in males, but not females, were also responsive to tone onset in both fear paradigms, but only in Full fear did the magnitude of this response increase across training. Knockdown of CRF from the BNST had no effect on fear learning in males or females, nor any effect in males on fear recall in either paradigm, but in females enhanced both baseline and tone-induced freezing only in Part fear group. When looking at anxiety following fear training, it was found in males that CRF knockdown modulated anxiety in Part fear trained animals and amplified startle in Fully trained males but had no effect in either test in females. Using 1P imaging, it was found that CRF neurons in the BNST generally decline in activity across both conditioning and recall trials, with some subtle sex differences emerging in the Part fear trained animals in that in females BNST CRF neurons were inhibited after both shock and omission trials but in males this only occurred after shock and not omission trials. In recall trials, CRF BNST neuron activity remained higher in Part conditioned mice relative to Full conditioned mice.

Overall, this is a very detailed and complex study that incorporates both differing fear training paradigms and males and females, as well as a suite of both state of the art imaging techniques and gene knockdown approaches to isolate the role and contributions of CRF neurons in the BNST to these behavioral phenomena. The strengths of this study come from the thorough approach that the authors have taken, which in turn helped to elucidate nuanced and sex specific roles of these neurons in the BNST to differing aspects of phasic and sustained fear. More so, the methods employed provide a strong degree of cellular resolution for CRF neurons in the BNST. In general, the conclusions appropriately follow the data, although the authors do tend to minimize some of the inconsistencies across studies (discussed in more depth below), which could be better addressed through discussion of these in greater depth. As such, the primary weakness of this manuscript comes largely from the discussion and interpretation of mixed findings without a level of detail and nuance that reflects the complexity, and somewhat inconsistency, across the studies. These points are detailed below:

-Given the focus on CRF neurons in the BNST, it is unclear why the photometry studies were performed in undifferentiated BNST neurons as opposed to CRF neurons specifically (although this is addressed, to some degree, subsequently with the 1P studies in CRF neurons directly). This does limit the continuity of the data from the photometry studies to the subsequent knockdown and 1P imaging studies. The authors should address the rationale for this approach so it is clear why they have moved from broader to more refined approaches.

-The CRF KD studies are interesting, but it remains speculative as to whether these effects are mediated locally in the BNST or due to CRF signaling at downstream targets. As the literature on local pharmacological manipulation of CRF signaling within the BNST seems to be largely performed in males, the addition of pharmacological studies here would benefit this to help to resolve if these changes are indeed mediated by local impairments in CRF release within the BNST or not. While it is not essential to add these experiments, the manuscript would benefit from a more clear description of what pharmacological studies could be performed to resolve this issue.

-While I can appreciate the authors perspective, I think it is more appropriate to state that startle correlates with anxiety as opposed to outright stating that startle IS anxiety. Anxiety by definition is a behavioral cluster involving many outputs, of which avoidance behavior is key. Startle, like autonomic activation, correlates with anxiety but is not the same thing as a behavioral state of anxiety (particularly when the startle response dissociates from behavior in the NSF test, which more directly tests avoidance and apprehension). Throughout the manuscript the use of anxiety or vigilance to describe startle becomes interchangeable, but then the authors also dissociate these two, such as in the first paragraph of the discussion when stating that the Part fear paradigm produces hypervigilance in males without influencing fear or anxiety-like behaviors. The manuscript would benefit from harmonization of the language used to operationally define these behaviors and my recommendation would be to remain consistent with the description that startle represents hypervigilance and not anxiety, per se.

-The interpretation of the anxiety data following CRF KD is somewhat confusing. First, while the authors found no effect of fear training on behavior in the NSF test in the initial studies, now they do, however somewhat contradictory to what one would expect they found that Full fear trained males had reduced latency to feed (indicative of an anxiolytic response), which was unaltered by CRF KD, but in Part fear (which appeared to have no effect on its own in the NSF test), KD of CRF in these animals produced an anxiolytic effect. Given that the Part fear group was no different from control here it is difficult to interpret these data as now CRF KD does reduce latency to feed in this group, suggesting that removal of CRF now somehow conveys an anxiolytic response for Part fear animals. In the discussion the authors refer to this outcome as CRF KD "normalizing" the behavior in the NSF test of Part fear conditioned animals as now it parallels what is seen after Full fear, but given that the Part fear animals with GFP were no different then controls (and neither of these fear training paradigms produced any effect in the NSF test in the first arm of studies), it seems inappropriate to refer to this as "normalization" as it is unclear how this is now normalized. Given the complexity of these behavioral data, some greater depth in the discussion is required to put these data in context and describe the nuance of these outcomes, in particular a discussion of possible experimental factors between the initial behavioral studies and those in the CRF KD arm that could explain the discrepancy in the NSF test would be good (such as the inclusion of surgery, or other factors that may have differed between these experiments). These behavioral outcomes are even more complex given that the opposite effect was found in startle whereby CRF KD amplified startle in Full trained animals. As such, this portion of the discussion requires some reworking to more adequately address the complexity of these behavioral findings.

Reviewer #3 (Public Review):

Hon et al. investigated the role of BNST CRF signaling in modulating phasic and sustained fear in male and female mice. They found that partial and full fear conditioning had similar effects in both sexes during conditioning and during recall. However, males in the partially reinforced fear conditioning group showed enhanced acoustic startle, compared to the fully reinforced fear conditioning group, an effect not seen in females. Using fiber photometry to record calcium activity in all BNST neurons, the authors show that the BNST was responsive to foot shock in both sexes and both conditioning groups. Shock response increased over the session in males in the fully conditioned fear group, an effect not observed in the partially conditioned fear group. This effect was not observed in females. Additionally, tone onset resulted in increased BNST activity in both male groups, with the tone response increasing over time in the fully conditioned fear group. This effect was less pronounced in females, with partially conditioned females exhibiting a larger BNST response. During recall in males, BNST activity was suppressed below baseline during tone presentations and was significantly greater in the partially conditioned fear group. Both female groups showed an enhanced BNST response to the tone that slowly decayed over time. Next, they knocked CRF in the BNST to examine its effect on fear conditioning, recall and anxiety-like behavior after fear. They found no effect of the knockdown in either sex or group during fear conditioning. During fear recall, BNST CRF knockdown lead to an increase in freezing in only the partially conditioned females. In the anxiety-like behavior tasks, BNST CRF knockdown lead to increased anxiolysis in the partially reinforced fear male, but not in females. Surprisingly, BNST CRF knockdown increased startle response in fully conditioned, but not partially conditioned males. An effect not observed in either female group. In a final set of experiments, the authors single photon calcium imaging to record BNST CRF cell activity during fear conditioning and recall. Approximately, 1/3 of BNST CRF cells were excited by shock in both sexes, with the rest inhibited and no differences were observed between sexes or group during fear conditioning. During recall, BNST CRF activity decreased in both sexes, an effect pronounced in male and female fully conditioned fear groups.

Overall, these data provide novel, intriguing evidence in how BNST CRF neurons may encode phasic and sustained fear differentially in males and females. The experiments were rigorous.

Reviewer #1 (Public Review):

This work by Gonzalez-Segarra et al. greatly extends previous research from the same group that identified ISNs as a key player in balancing nutrition and water ingestion. Using well-balanced sets of exploratory anatomical analyses and rigorous functional experiments, the authors identify and compile various peptidergic circuits that modulate nutrient and/or water ingestion. The findings are convincing and the experiments rigorous.

Strengths:<br /> - The authors complement anatomically-reconstructed and functionally-validated neuronal connectivity with extensive and intensive morphological and synaptic reconstruction.

- Neurons and genes involved in specific components of feeding control are undoubtedly challenging, because numerous neurons and circuits redundantly and reciprocally regulate the same components of feeding behavior. This work dissociates how multiple, parallel and interconnected, peptidergic circuits (dilp3, CCHa2, CCAP) modulate sucrose and water ingestion, in tandem and in parallel.

- The authors address some of the incongruencies/discrepancies in current literature (IPCs) and try to provide explanations, rather than ignoring inconsistent findings.

Weaknesses:<br /> - The authors have addressed several weaknesses of the paper in the revised text.

Reviewer #2 (Public Review):

In this manuscript, González-Segarra et al. investigated how ISNs regulate sugar and water ingestion in Drosophila. In their previous paper, authors have shown that inhibiting neurotransmission in ISNs has opposite effects on sugar and water ingestion. In this manuscript, the authors first identified the effector molecules released by ISNs. Their RNAi screen found that, surprisingly, ISNs use ilp3 as a neuromodulator. Next, using light and electron microscopy, they investigated the downstream neural circuits ISNs connect with to regulate water or sugar ingestion. These analyses identified a new group of neurons named Bilateral T-shaped neurons (BiT) as the main output of ISNs, and several other peptidergic neurons as downstream effectors of ISNs. While BiT activity regulated both sugar and water ingestion, BiT downstream neurons, such as CCHa2R, only impacted water ingestion. These results suggested that ISNs might interact with distinct neural circuits to control sugar or water ingestion. The authors also investigated other ISN downstream neurons, such as ilp2 and CCAP, and revealed that their activity also contributes to ingestive behaviors in flies.

Major strengths:<br /> 1. This manuscript presents a comprehensive investigation of the downstream neurons connected to ISNs.

2. The authors have identified and characterized a diverse set of peptidergic neurons that regulate ingestive behaviors in the fly brain.

Weaknesses:<br /> 1. Only one RNAi hairpin is used to knock down Ilp3 in ISNs? There is a concern about off-targeting effects without the presence of another hairpin or mutant data. Do ilp3 mutants also have similar defects in sugar/water ingestion compared to ISN ilp3 knockdown?

2. Throughout the paper, authors use either voltage or calcium sensors without explaining why they choose to use either method to determine the functional connectivity between neurons.

3. How these diverse sets of peptidergic neurons interact to regulate ingestive behaviors is unclear and requires further investigation.

Reviewer #1 (Public Review):

Summary:<br /> In this study, the authors provide a new computational platform called Vermouth to automate topology generation, a crucial step that any biomolecular simulation starts with. Given a wide arrange of chemical structures that need to be simulated, varying qualities of structural models as inputs obtained from various sources, and diverse force fields and molecular dynamics engines employed for simulations, automation of this fundamental step is challenging, especially for complex systems and in case that there is a need to conduct high-throughput simulations in the application of computer-aided drug design (CADD). To overcome this challenge, the authors develop a programming library composed of components that carry out various types of fundamental functionalities that are commonly encountered in topological generation. These components are intended to be general for any type of molecules and not to depend on any specific force field and MD engines. To demonstrate the applicability of this library, the authors employ those components to re-assemble a pipeline called Martinize2 used in topology generation for simulations with a widely used coarse-grained model (CG) MARTINI. This pipeline can fully recapitulate the functionality of its original version Martinize but exhibit greatly enhanced generality, as confirmed by the ability of the pipeline to faithfully generate topologies for two high-complexity benchmarking sets of proteins.

Strengths:<br /> The main strength of this work is the use of concepts and algorithms associated with induced subgraph in graph theory to automate several key but non-trivial steps of topology generation such as the identification of monomer residue units (MRU), the repair of input structures with missing atoms, the mapping of topologies between different resolutions, and the generation of parameters needed for describing interactions between MRUs.

Weaknesses:<br /> Although the Vermouth library appears promising as a general tool for topology generation, there is insufficient information in the current manuscript and a lack of documentation that may allow users to easily apply this library. More detailed explanation of various classes such as Processor, Molecule, Mapping, ForceField etc. that are mentioned is still needed, including inputs, output and associated operations of these classes. Some simple demonstration of application of these classes would be of great help to users. The formats of internal databases used to describe reference structures and force fields may also need to be clarified. This is particularly important when the Vermouth needs to be adapted for other AA/CG force fields and other MD engines.

The successful automation of the Vermouth relies on the reference structures that need to be pre-determined. In case of the study of 43 small ligands, the reference structures and corresponding mapping to MARTINI-compatible representations for all these ligands have been already defined in the M3 force field and added into the Vermouth library. However, the authors need to comment on the scenario where significantly more ligands need to be considered and other force fields need to be used as CG representations with a lack of reference structures and mapping schemes.

Reviewer #2 (Public Review):

Summary:

This manuscript by Kroon, Grunewald, Marrink and coworkers present the development of Vermouth library for coarse grain assignment and parameterization and an updated version of python script, the Martinize2 program, to build Martini coarse grained (CG) models, primarily for protein systems.

Strengths:

In contrast to many mature and widely used tools to build all-atom (AA) models, there are few well-accepted programs for CG model constructions and parameterization. The research reported in this manuscript is among the ongoing efforts to build such tools for Martini CG modeling, with a clear goal of high-throughput simulations of complex biomolecular systems and, ultimately, whole-cell simulations. Thus, this manuscript targets a practical problem in computational biophysics. The authors see such an effort to unify operations like CG mapping, parameterization, etc. as a vital step from the software engineering perspective.

Weaknesses:

However, the manuscript in this shape is unclear in the scientific novelty and appears incremental upon existing methods and tools. The only "validation" (more like an example application) is to create Martini models with two protein structure sets (I-TASSER and AlphaFold). The success rate in building the models was only 73%, while the significant failure is due to incomplete AA coordinates. This suggests a dependence on the input AA models, which makes the results less attractive for high-throughput applications (for example, preparation/creation of the AA models can become the bottleneck). There seems to be an improvement in considering the protonation state and chemical modification, but convincing validation is still needed. Besides, limitations in the existing Martini models remain (like the restricted dynamics due to the elastic network, the electrostatic interactions or polarizability).

Reviewer #3 (Public Review):

Summary:<br /> The manuscript Kroon et al. described two algorithms, which when combined achieve high throughput automation of "martinizing" protein structures with selected protonation states and post-translational modifications.

Strengths:<br /> A large scale protein simulation was attempted, showing strong evidence that authors' algorithms work smoothly.

The authors described the algorithms in detail and shared the open-source code under Apache 2.0 license on GitHub. This allows both reproducibility of extended usefulness within the field. These algorithms are potentially impactful if the authors can address some of the issues listed below.

Weaknesses:<br /> One major caveat of the manuscript is that the authors claim their algorithms aim to "process any type of molecule or polymer, be it linear, cyclic,<br /> branched, or dendrimeric, and mixtures thereof" and "enable researchers to prepare simulation input files for arbitrary (bio)polymers". However, the examples provided by the manuscript only support one type of biopolymer, i.e. proteins. Despite the authors' recommendation of using polyply along with martinize2/vermouth, no concrete evidence has been provided to support the authors' claim. Therefore, the manuscript must be modified to either remove these claims or include new evidence.

Method descriptions on Martinize2 and graph algorithms in SI should be core content of the manuscript. I argue that Figure S1 and Figure S2 are more important than Figure 3 (protonation state). I recommend the authors can make a workflow chart combining Figure S1 and S2 to explain Martinize2 and graph algorithms in main text.

In Figure 3 (protonation state), the figure itself and the captions are ambiguous about whether at the end the residue is simply renamed from HIS to HIP, or if hydrogen is removed from HIP to recover HIS.

In "Incorporating a Ligand small-molecule Database", the authors are calling for a community effort to build a small-molecule database. Some guidance on when the current database/algorithm combination does or does not work will help the community in contributing.

A speed comparison is needed to compare Martinize2 and Martinize.

Reviewer #1 (Public Review):

The authors investigated the function of BATF in hepatic lipid metabolism. They found BATF alleviated high-fat diet (HFD)-induced hepatic steatosis. In addition, BATF could inhibit programmed cell death protein (PD)1 expression induced by HFD. By using over expression and transcriptional activity analysis, this study confirmed that BATF regulates fat accumulation by inhibiting PD1 expression and promoting energy metabolism. Then, they found PD1 antibodies alleviated hepatic lipid deposition. These data identified the regulatory role of BATF in hepatic lipid metabolism and that PD1 is a target for alleviation of NAFLD. The conclusions of this manuscript are supported by the data.

Reviewer #2 (Public Review):

In this manuscript, authors firstly investigated the role of a transcriptional factor BATF in hepatic lipid metabolism both in vivo and in vitro. By using a AAV transfection to overexpress BATF in liver, the mice with overexpression of BATF resisted the high fat diets induced obesity and attenuated the hepatic steatosis. Mechanically, the PD1 mediated its effect on lipid accumulation in hepatocyte and IL-27 mediated its effect on adiposity reduction in vivo.

Strengths:

1) This work found the transcription factor BATF was positive to reduce hepatic lipid accumulation and offered a potential target to treat NAFLD.<br /> 2) PD1 antibody is always used to treat cancer, authors here have developed its new function in metabolic disease. PD1 antibody could help mice to combat obesity and hepatic steatosis induced by high fat diets.<br /> 3) Overexpression of BATF in the liver not only decreased the lipid accumulation in the liver but also reduced the fat mass. IL-27 secretion in the liver was enhanced to affect the adipose tissue. The cross talk in liver and adipose tissue was also validated in this paper.

Reviewer #1 (Public Review):

A typical path from preprocessed data to findings in systems neuroscience often includes set of analyses that often share common components. For example, an investigator might want to generate plots that relating one time series (e.g., a set of spike times) to another (measurements of a behavioral parameter such as pupil diameter or running speed). In most cases, each individual scientist writes their own code to carry out these analyses, and thus the same basic analysis is coded repeatedly. This is problematic for several reasons, including the inefficiency of different people writing the same code over and over again.

This paper presents Pynapple, a python package that aims to address those problems.

Strengths:

The authors have identified a key need in the community - well written analysis routines that carry out a core set of functions and can import data from multiple formats. In addition, they recognized that there are some common elements of many analyses, particularly those involving timeseries, and their object-oriented architecture takes advantage of those commonalities to simplify the overall analysis process.

The package is separated into a core set of applications and another with more advanced applications, with the goal of both providing a streamlined base for analyses and allowing for implementations/inclusion of more experimental approaches.

Weaknesses:

The revised version of the paper does a very good job of addressing previous concerns. It would be slightly more accurate in the Highlights section to say "A lightweight and standalone package facilitating long-term backward compatibility" but this is a very minor issue.

Reviewer #2 (Public Review):

The manuscript by G. Viejo et al. describes a new open-source toolbox called Pynapple, for data analysis of electrophysiological recordings, calcium imaging, and behavioral data. It is an object-oriented python package, consisting of 5 main object types: timestamps (Ts), timestamped data (Tsd), TsGroup, TsdFrame, and IntervalSet. Each object has a set of built-in core methods and import tools for common data acquisition systems and pipelines.

Pynapple is a low-level package that uses NWB as a file format, and further allows for other more advanced toolsets to build upon it. One of these is called Pynacollada which is a toolset for data analysis of electrophysiological, imaging, and behavioral data.

Pynapple and Pynacollada have the potential to become very valuable and foundational tools for the analysis of neurophysiological data. NWB still has a steep learning curve and Pynapple offers a user-friendly toolset that can also serve as a wrapper for NWB.

Reviewer #1 (Public Review):

This manuscript addresses the important and understudied issue of circuit-level mechanisms supporting habituation, particularly in pursuit of the possible role of increases in the activity of inhibitory neurons in suppressing behavioral output during long-term habituation. The authors make use of many of the striking advantages of the larval zebrafish to perform whole brain, single neuronal calcium imaging during repeated sensory exposure, and high throughput screening of pharmacological agents in freely moving, habituating larvae. Notably, several blockers/antagonists of GABAA(C) receptors completely suppress habituation of the O-bend escape response to dark flashes, suggesting a key role for GABAergic transmission in this form of habituation. Other substances are identified that strikingly enhance habituation, including melatonin, although here the suggested mechanistic insight is less specific. To add to these findings, a number of functional clusters of neurons are identified in the larval brain that have divergent activity through habituation, with many clusters exhibiting suppression of different degrees, in line with adaptive filtration during habituation, and a single cluster that potentiates during habituation. Further assessment reveals that all of these clusters include GABAergic inhibitory neurons and excitatory neurons, so we cannot take away the simple interpretation that the potentiating cluster of neurons is inhibitory and therefore exerts an influence on the other adapting (depressing) clusters to produce habituation. Rather, a variety of interpretations remain in play.

Overall, there is great potential in the approach that has been used here to gain insight into circuit-level mechanisms of habituation. There are many experiments performed by the authors that cannot be achieved currently in other vertebrate systems, so the manuscript serves as a potential methodological platform that can be used to support a rich array of future work. While there are several key observations that one can take away from this manuscript, a clear interpretation of the role of GABAergic inhibitory neurons in habituation has not been established. This potential feature of habituation is emphasized throughout, particularly in the introduction and discussion sections, meaning that one is obliged as a reader to interrogate whether the results as they currently stand really do demonstrate a role for GABAergic inhibition in habituation. Currently, the key piece of evidence that may support this conclusion is that picrotoxin, which acts to block some classes of GABA receptors, prevents habituation. However, there are interpretations of this finding that do not specifically require a role for modified GABAergic inhibition. For instance, by lowering GABAergic inhibition, an overall increase in neural activity will occur within the brain, in this case below a level that could cause a seizure. That increase in activity may simply prevent learning by massively increasing neural noise and therefore either preventing synaptic plasticity or, more likely, causing indiscriminate synaptic strengthening and weakening that occludes information storage. Sensory processing itself could also be disrupted, for instance by altering the selectivity of receptive fields. Alternatively, it could be that the increase in neural activity produced by the blockade of inhibition simply drives more behavioral output, meaning that more excitatory synaptic adaptation is required to suppress that output. The authors propose two specific working models of the ways in which GABAergic inhibition could be implemented in habituation. An alternative model, in which GABAergic neurons are not themselves modified but act as a key intermediary between Hebbian assemblies of excitatory neurons that are modified to support memory and output neurons, is not explored. As yet, these or other models in which inhibition is not required for habituation, have not been fully tested.

This manuscript describes a really substantial body of work that provides evidence of functional clusters of neurons with divergent responses to repeated sensory input and an array of pharmacological agents that can influence the rate of a fundamentally important form of learning.

Reviewer #2 (Public Review):

In this study, Lamire et al. use a calcium imaging approach, behavioural tests, and pharmacological manipulations to identify the molecular mechanisms behind visual habituation. They show a valuable drug screen paradigm to assess the impact of pharmacological compounds on the behaviour of larval zebrafish.

The pharmacological screen identifies an expected suppression of habituation by GABA receptor antagonists. More interestingly, it identifies potentially new contributions of melatonin receptor agonists, and oestrogen receptor agonists to habituation, as they seem to increase the rate of habituation.

The volumetric calcium imaging of habituation to dark flashes is valuable, but the mix of responses to visual cues that are not relevant to the dark flash escape, such as the slow increase back to baseline luminosity, lowers the clarity of the results. The link between the calcium imaging results and free-swimming behaviour is not especially convincing, however, that is a common issue of head-restrained imaging with larval zebrafish. The identification of a cluster of neurons with potentiating responses, which could drive the habituation is intriguing, but more characterizations of these neurons would be needed to fully understand their function in habituation. The pharmacological manipulation of the habituation circuits mapped in the first part does not arrive at any satisfying conclusion, which is acknowledged by the authors.

Overall, the authors did identify interesting new molecular pathways that may be involved in habituation to dark flashes. Their screening approach, while not novel, will be a powerful way to interrogate other behavioural profiles. The authors identified circuit loci apparently involved in habituation to dark flashes, and the potentiation and no adaptation clusters have not been previously observed and are interesting targets for future work. This work suggests that the circuits and mechanisms underlying habituation are likely more complex than anticipated. The data will be useful to guide follow-up experiments by the community on the new pathway candidates that this screen has uncovered, including behaviours beyond dark flash habituation.

Reviewer #3 (Public Review):

To analyze the circuit mechanisms leading to the habituation of the O-bed responses upon repeated dark flashes (DFs), the authors performed 2-photon Ca2+ imaging in larvae expressing nuclear-targeted GCaMP7f pan-neuronally panning the majority of the midbrain, hindbrain, pretectum, and thalamus. They found that while the majority of neurons across the brain depress their responsiveness during habituation, a smaller population of neurons in the dorsal regions of the brain, including the torus longitudinalis, cerebellum, and dorsal hindbrain, showed the opposite pattern, suggesting that motor-related brain regions contain non-depressed signals, and therefore likely contribute to habituation plasticity.

Further analysis using affinity propagation clustering identified 12 clusters that differed both in their adaptation to repeated DFs, as well as the shape of their response to the DF.

Next by the pharmacological screening of 1953 small molecule compounds with known targets in conjunction with the high-throughput assay, they found that 176 compounds significantly altered some aspects of measured behavior. Among them, they sought to identify the compounds that 1) have minimal effects on the naive response to DFs, but strong effects during the training and/or memory retention periods, 2) have minimal effects on other aspects of behaviors, 3) show similar behavioral effects to other compounds tested in the same molecular pathway, and identified the GABAA/C Receptor antagonists Bicuculline, Amoxapine, and Picrotoxinin (PTX). As partial antagonism of GABAAR and/or GABACR is sufficient to strongly suppress habituation but not generalized behavioral excitability, they concluded that GABA plays a very prominent role in habituation. They also identified multiple agonists of both Melatonin and Estrogen receptors, indicating that hormonal signalling may also play a prominent role in habituation response.

To integrate the results of the Ca2+ imaging experiments with the pharmacological screening results, the authors compared the Ca2+ activity patterns after treatment with vehicle, PTX, or Melatonin in the tethered larvae. The behavioral effects of PTX and Melatonin were much smaller compared with the very strong behavioral effects in freely-swimming animals, but the authors assumed that the difference was significant enough to continue further experiments. Based on the hypothesis that Melatonin and GABA cooperate during habituation, they expected PTX and Melatonin to have opposite effects. This was not the case in their results: for example, the size of the 12(Pot, M) neuron population was increased by both PTX and Melatonin, suggesting that pharmacological manipulations that affect habituation behavior manifest in complex functional alterations in the circuit, making capturing these effects by a simple difficult.

Since the 12(𝑃𝑜𝑡, 𝑀) neurons potentiate their responses and thus could act to progressively depress the responses of other neuronal classes, they examined the identity of these neurons with GABA neurons. However, GABAergic neurons in the habituating circuit are not characterized by their Adaptation Profile, suggesting that global manipulations of GABAergic signalling through PTX have complex manifestations in the functional properties of neurons.

Overall, the authors have performed an admirably large amount of work both in whole-brain neural activity imaging and pharmacological screening.

Reviewer #1 (Public Review):

In this manuscript, the authors aimed to compare, from testis tissues at different ages from mice in vivo and after culture, multiple aspects of Leydig cells. These aspects included mRNA levels, proliferation, apoptosis, steroid levels, protein levels, etc. A lot of work was put into this manuscript in terms of experiments, systems, and approaches. The technical aspects of this work may be of interest to labs working on the specific topics of in vitro spermatogenesis for fertility preservation.

Second review:

The authors should be commended for substantial improvement in their manuscript for resubmission.

Reviewer #3 (Public Review):

Moutard, Laura, et al. investigated the gene expression and functional aspects of Leydig cells in a cryopreservation/long-term culture system. The authors found that critical genetic markers for Leydig cells were diminished when compared to the in-vivo testis. The testis also showed less androgen production and androgen responsiveness. Although they did not produce normal testosterone concentrations in basal media conditions, the cultured testis still remained highly responsive to gonadotrophin exposure, exhibiting a large increase in androgen production. Even after the hCG-dependent increase in testosterone, genetic markers of Leydig cells remained low, which means there is still a missing factor in the culture media that facilitates proper Leydig cell differentiation. Optimizing this testis culture protocol to help maintain proper Leydig cell differentiation could be useful for future human testis biopsy cultures, which will help preserve fertility and child cancer patients.

Overall, the authors addressed most comments and questions from the previous review. The additional data regarding the necrotic area is helpful for interpreting the quality of the cultures.

The authors did not conduct a multiple comparison tests although there are multiple comparisons conducted on for a single dependent variable (Fig 2J, Fig 3F, among many others), however, the addition of this multiple comparison is unlikely to change the conclusions of the paper or the figure and, thus is a minor technical detail in this case.

Reviewer #3 (Public Review):

In this paper, Toschi et al. performed dMRI to in vivo estimate axon diameter in the brain and demonstrated that multi-compartmental modeling (AxCaliber) is sensitive to microstructural axonal damage in rats and axon caliber increase in demyelinating lesions in MS patients, suggesting that axon diameter mapping provides a potential biomarker to bridge the gap between medical imaging contrasts and biological microstructure. In particular, authors injected ibotenic acid (IBO) and saline in the left and right rat hippocampus, respectively, and compared in vivo estimated axon diameter and ex vivo neurofilament staining in left and right fimbria. The axon size estimation was larger in the fimbria of IBO injection side, where the neurofilament intensity is higher. Correlation of axon size estimation and neurofilament intensity was observed in both injection sides. Further, higher axon diameter estimation was observed in normal appearing white matter (NAWM) of MS patients, compared with the healthy subjects. The axon size estimation increased in hypointense lesions of T1 weighted contrast, but not in isointense lesions. Through the comparison of dMRI-estimated axon size and histology-based fluorescence intensity, authors indirectly validated the sensitivity of axon diameter mapping to the tissue microstructure in the rat brain, and further explored the axon size change in the brain of MS patients. However, the dMRI protocol and biophysical modeling in this study were not fully optimized to maximize the sensitivity to axon size estimation, and the dMRI-estimated axon size (4.4-5.4 micron) was much larger than values reported in previous histological studies (0.5-3 micron) [Barazany et al., Brain 2009]. Finally, although the modified AxCaliber model incorporated two fiber bundles in different directions, the fiber dispersion in each bundle was not considered (c.f. fiber dispersion ~20-30 degree in corpus callosum), potentially leading to overestimated axon diameter.

The conclusions in this study are supported by experimental results. However, the dMRI protocol and biophysical model could be further optimized and validated:<br /> 1. To in vivo estimate the axon diameter ~1 micron using dMRI, strong diffusion weighting (b-value) should be applied to maximize the signal decay due to intra-axonal restricted diffusion and minimize the signal contribution of extra-cellular hindered diffusion. However, authors only applied maximal b-value = 4000 s/mm2, much smaller than values ~15,000-20,000 s/mm2 in previous studies [Assaf et al., MRM 2008; Huang et al., BSAF 2020, 225:1277]. The use of low diffusion weighting in this study leads to a lower bound ~4-6 micron for accurate diameter estimation, the so-called resolution limit in [Nilsson et al., NMR Biomed 2017, 30:e3711]. In other words, the estimated axon diameter is potentially overestimated and related with the imaging protocol and image quality, confounding the biological interpretation.<br /> 2. In this study, the positive correlation of dMRI-estimated axon size and neurofilament fluorescence intensity is indeed an encouraging result, and yet this validation is indirect since it relies on the positive correlation between neurofilament intensity and axon diameter in histology.<br /> 3. Authors did not consider the fiber dispersion in the proposed dMRI model. This can lead to overestimated axon diameter, even in the highly aligned WM, such as corpus callosum with ~20-30 degree dispersion in histology [Ronen et al., BSAF 2014, 219:1773; Leergaard et all, PLoS One 2010, 5(1), e8595] and MRI [Dhital et al., NeuroImage 2019, 189, 543; Novikov et al., NeuroImage 2018, 174:518].

Reviewer #1 (Public Review):

1. My primary concern relates to how meaningful the human-rodent comparisons are, and whether these comparisons really advance our understanding of AxCaliber estimates in MS.

I applaud the aim to conduct "matched" experiments in both rodent models and human disease. It is a strength that the experiments are aligned with respect to the MRI measurements (although there are some caveats to this mentioned below). But beyond that, the overlap is not what one might hope for: the pathology would seem to be very distinct in humans and rodents, and the histological validation is not specific to what the MRI measurements claim to estimate.

To summarize the main findings: (i) in a rat model of general axonal degeneration, axon calibre estimates correlate with neurofilaments; (ii) in MS in humans, axon calibre estimates correlate with demyelinating lesions. This gives a picture of AxCalibre estimates correlating with neuropathology, but is this something that has not already been established in the literature?

If the aim is to validate AxCaliber, then there is a logic in using a rodent model that isolates alterations to axonal radius, but what then does this add to the existing literature in that space? If the aim is to study MS (for which AxCaliber results have been previously reported in Huang et al), then why not use a rodent model of MS?

2. I appreciate that both rodent and patient studies are time intensive, major endeavors. Neverthless, the number of subjects is very low in both rodent (n=9) and human (MS=10, control=6) studies. At the very least, this should be more openly acknowledged. But I'm concerned that this is a major weakness of the paper. Related to this, I find it hard to tell how carefully multiple comparison correction was performed throughout. It seems reasonably clear for the TBSS analyses, but then other analyses were performed in ROIs. Are these multiple comparisons corrected as well? Similarly, in Methods, I am confused by the statement that: "post hoc t tests corrected for multiple comparisons whenever a significant effect was detected". What does this mean?

3. While I do not think the text is in any sense deliberately misleading, I think the authors would do well to either tone down their claims or consider more carefully the implications of the text in many places. Some that stuck out for me are:

(a) Throughout, language in the paper (e.g., "Paired t tests were used to assess differences in the axonal diameter") presumes that the AxCaliber estimates specifically reflect axon diameter. I think the jury is out over whether this is true, particularly for measurements conducted with limited hardware specs. At the very least, I would encourage the author to refer to these measurements throughout as "estimates" of axon diameter.

(b) The authors suggest that their results provide "new tools for patient stratification" based on differences in lesion type, but it isn't clear what new information these markers would confer given that the lesions are differentiated based on T1w hypo/hyperintensities. In other words, these lesions are by definition already differentiable from a much simpler MRI marker.

(c) The authors note in the Discussion that: "sensitive to early stages of axonal degeneration, even before alterations in the myelin sheet are detected". Whether intentional or not, the implication in the context of this study is that this would hold for MS (that these markers would detect axonal degeneration preceding demyelination). While there is some discussion of alterations to axonal diameter in MS, the authors do not discuss whether these are the same mechanisms thought to occur in the IBO intervention used here.

(d) In the Discussion, the authors note the lack of evidence for a relationship with disability or disease duration, but nevertheless, go on to interpret the "trends" they do observe. I would advise strongly against this: the authors acknowledge that their numbers are low, so I would avoid the temptation to speculate here.

(e) In the Discussion state that "the use of neurofilaments has also been well validated in MS". Well validated for what? MS is a complex disease with a broad range of pathology, so this statement could be read to mean "neurofilaments are known to be altered in MS". However, in the context of this paragraph, the implication would seem to be that neurofilaments are a well-established proxy for axonal diameter. Is that the implication, and if so what general evidence is there for this?

Reviewer #2 (Public Review):

Diffusion MRI is sensitive to the brain microstructure, and it has been used to assess the integrity of white matter for nearly 3 decades. Its main limitation is the limited specificity, which makes it difficult to link changes in diffusion parameters to a given pathological substrate. Recently methods based on diffusion MRI that enable the estimation of axonal diameter, non invasively, have become available. This paper aims at validating one of such methods using an experimental model of neurodegeneration. The authors found a significant correlation between axonal diameter estimated by MRI and an histological marker of neurodegeneration. Although this is of great interest, as it demonstrates that this method is sensitive to neurodegeneration, a direct validation would require a measurement of axonal diameter using electron or confocal microscopy, rather than a correlation with a measure of axonal degeneration not directly related to axonal diameter. So, although these data are compelling, they do not prove that the increase in axonal diameter suggested by diffusion MRI corresponds to actual axonal swelling. The Authors also apply the same method to compare the white matter of patients with multiple sclerosis (MS) and healthy controls, showing widespread increases in axonal diameter in the patients. These data are compelling, but again, not conclusive. Other factors such as gloss could bias the MRI measurement and lead to an apparent increase in axonal diameter.

Reviewer #3 (Public Review):

This study examined the changes in fear response, as measured by the flight initiation distances (FID), of birds living in urban areas. The authors examined the FIDs of birds during the pandemic (COVID-19 lockdown restrictions) compared to FIDs measured before the pandemic (mostly in 2018 & 2019). The main study justification was that human presence changed drastically during the pandemic lockdowns and the change in human presence might have influenced the fear response of birds as a result of changing the "landscape of fear". Human presence was quantified using a 'stringency' index (government-mandated restrictions). Urban areas were selected from within five different cities, which included four European cities (Czech Republic - Prague, Finland - Rovaniemi, Hungary - Budapest, Poland - Poznan), and one city in the global south (Australia - Melbourne). Using 6369 flight initiation distances across 147 different bird species, the authors found that FIDs were not significantly different before the pandemic versus during the pandemic, nor was the variation in FID explained by the level of 'stringency'.

Major strengths: There are several strengths to this study that allows for understanding the variety of factors that influence a bird's response to fear (measured as flight initiation distances). This study also demonstrates that FIDs are highly variable between species and regions.<br /> Specifically,<br /> 1) One of the major strengths of this paper is the focus on birds living in urban areas, a habitat type that is hypothesized to have changed drastically in the 'landscape of fear' experienced by animals during the pandemic lockdown restrictions (due to the presumed decrease in human presence and densities). Maintaining the focus on urban birds allowed for a deeper examination of the effect of human behaviour changes on bird behaviour in urban habitats, which are at the interface of human-wildlife interactions.<br /> 2) This study accounted for several variables that are predicted to influence flight initiation distances in birds including species, genus, region (country), variability between years, pandemic year (pre- versus during), the strictness of government-mandated lockdown measures, and ecological factors such as the human observer starting distance, flock size, species-specific body size, ambient air temperature (also a proxy of the timing during the breeding season), time of day, date of data collection (timing within the regional [Europe or Australia] breeding season), and categorization of urban site type (e.g. park, cemetery, city centre).<br /> 3) This study examined FIDs in two years previous to the pandemic (mostly 2018 and 2019, one site was 2014) which would account for some of the within- and between-year FID variation exhibited prior to the pandemic.<br /> 4) This study uses strong statistical approaches (mixed effect models) which allows for repeat sampling, and a post hoc analysis testing for a phylogenetic signal.

Major weaknesses: The authors used government 'stringency' as a proxy for human presence and densities, however, this may not have been an accurate measure of actual human presence at the study sites and during measurements of FIDs. Furthermore, although the authors accounted for many factors that are predicted to influence fear response and FIDs in birds, there are several other factors that may have contributed to the high level of variation and patterns in FIDS observed during this study, thus resulting in the authors' conclusion that FIDs did not vary between pre- and during pandemic years.<br /> Specifically,<br /> 1) The authors used "government stringency" as a measure of change in human activity, which makes the assumption that the higher the level of 'stringency', the fewer humans in urban areas where birds are living. However, the association between "stringency" and actual human presence at the study sites was not measured, nor was 'stringency' compared to other measures of human presence such as human mobility.<br /> 2) There was considerable variation in FID measurements, which can be seen in the figures, indicating that most of the variation in FID was not accounted for in the authors' models. Factors that may have contributed to variation in FIDs that were not accounted for in this study are as follows:<br /> a. The authors accounted for the date of data collection using the 'day' since the start of the general region's breeding season (Europe: Day 1 = 1 April; Australia: Day 1 = 15 August). Using 'day' since the breeding season started probably was an attempt to quantify the effect of the breeding stage (e.g. territory establishment, nest young, fledgling) on FIDs. However, breeding stages vary both within- and between species, as well as between sub-regions (e.g. Finland vs. Hungary). As different species respond to predation or human presence differently depending on the stage during their breeding cycle, more specificity in the breeding cycle stage may allow for explaining the observed variation and patterns in FID.<br /> b. Variation in species-specific FIDs may also vary with habitat features within urban sites, such as the proximity of trees and other protective structures (e.g. perches and cover), the openness of the area, and the level of stressors present (e.g. noise pollution, distance to roads). Perhaps accounting for this habitat heterogeneity would account for the FID variation measured in this study.<br /> c. The authors accounted for species and genus within their models, however, FIDs may vary with other species-specific (or even specific populations of a species) characteristics such as whether the species/population is neophobic versus neophilic, precocial versus altricial, and the level of behavioural plasticity exhibited. These variables were not accounted for in the analysis.<br /> d. Three different methods of measuring the distances between flight and the observer location were used, and FIDs were only measured once per bird, such that there were no measures of repeatability for a test subject. Thus, variation surrounding the measurement of FIDs would have contributed to the variation in FIDs seen during this study.<br /> 3) The sample design of this study may have influenced the FID variability associated with specific species, and specific populations of species. A different number of species were sampled across the time periods of interest; 68 species were sampled before the pandemic versus 135 species after the pandemic. However, the authors do not appear to have directly compared the FIDs for the same species before the pandemic compared to during the pandemic (e.g. the FIDs of Eurasian blackbirds before the pandemic versus during the pandemic). Furthermore, within the same country-city, it is unclear whether the species observed before the pandemic were observed at the same location (e.g. same habitat type such as the same park) during the pandemic. As a species' FID response may be influenced by population characteristics and features specific to each site (e.g. habitat openness), these factors may have influenced the variability in FID measurements in this study.<br /> 4) The models in this study accounted for many factors predicted to affect FIDs (see the section on major strengths), however, the number of fixed and random factors are large in number compared to the total sample size (N =6369), such that models may have been over-extended.

Overarching main conclusion<br /> Overall, this study examines factors influencing FIDs in a variety of bird species and concludes that FIDs did not differ during the pandemic lockdowns compared to before the pandemic (2019 and earlier). Furthermore, FIDs were not influenced by the strictness of government-mandated restrictions. Although the authors accounted for many factors influencing the measurement of FIDs in birds, the authors did not achieve their aim of disentangling the effects of pandemic-specific ecological effects from ecological effects unrelated to the pandemic (such as habitat heterogeneity). Their findings indicate that FIDs are highly variable both within- and between- species, but do not strongly support the conclusion that FIDs did not change in urban species during the pandemic lockdown. Therefore, this study is of limited impact on our understanding of how a drastic change in human behaviour may impact bird behaviour in urban habitats. Overall, the study demonstrates the challenges in using FIDs as a general fear response in birds, even during a pandemic lockdown when fewer humans are presumably present, and this study illustrates the large degree of variation in FIDs in response to a human observer.

Reviewer #1 (Public Review):

This paper uses a series of flight initiation "challenges" conducted both prior to and during COVID-19-related restrictions on human movement to estimate the degree to which avian escape responses to humans changed during the "anthropause". This technique is suitable for understanding avian behavioral responses with a high degree of repeatability. The study collects an impressive dataset over multiple years across five cities on two continents. Overall the study finds no effect of lockdown on avian escape distance (the distance at which the "target" individual flees the approaching observer). The study considers the variable of interest as both binary (during lockdown or prior to lockdown) and continuous, using the Oxford Stringency Index (with neither apparently affecting escape distance).

Overall this paper presents interesting results which may suggest that behavioral responses to humans are rather inflexible over "short" (~2 year) timespans. The anthropause represents a unique opportunity to disentangle the mechanistic drivers of myriad hypothesized impacts humans have on the behavior, distribution, and abundance of animals. Indeed, this finding would provide important context to the larger body of literature aimed at these ends. However, the paper could do more to carefully fit this finding into the broader literature and, in so doing, be a bit more careful about the conclusions they are able to draw given the study design and the measures used. Taking some of these points (in no particular order):

1) Oxford Stringency Index is a useful measure of governmental responses to the pandemic and it's true that in some scenarios (including the (Geng et al. 2021) study cited by this paper) it can correlate with human mobility. However, it is far from a direct measure of human mobility (even in the Geng study, to my reading, the index only explained a minority of the variation). Moreover, particular sub-components of the index are wholly unrelated to human mobility (e.g., would changes to a country's public information campaign lead to concomitant changes in urban human mobility?). Finally, compliance with government restrictions can vary geographically and over time (i.e., we might expect lower compliance in 2021 than in 2020) and the index is calculated at the scale of entire countries and may not be very reflective of local conditions. Overall this paper could do more to address the potential shortcomings of the Oxford Stringency Index as a measure of human mobility including attempting to validate the effect on human mobility using other datasets (e.g., the google dataset and/or those discussed in (Noi et al. 2022). This is of critical importance since the fundamental logic of the experimental design relies on the assumption that stringency ~ mobility.

2) The interpretation of the primary finding (that behavioral responses to humans are inflexible) could use a bit more contextualization within the literature. Specifically, the study offers three potential explanations for the observed invariance in escape response: 1) these behaviors are consistent within individuals and this study provides evidence that there was no population turnover as a result of lockdowns; 2) escape response is linked to other urban adaptations such that to be an urban-dwelling species dictates escape response; and/or 3) these populations already exhibit maximum habituation and the reduction in human mobility would only have increased that habituation but that trait is already at a boundary condition. Some comments on each of these respectively:

a) Even had these populations turned over as a result of a massive rural-to-urban dispersal event, it's not clear that the escape distance in those individuals would be different because this paper does not establish that these hypothetical rural birds have a different behavioral response which would be constant following dispersal. Thus the evidence gathered here is insufficient to tell us about possible relocations of the focal species. Additionally, the paper cites several papers that found no changes in abundance or movements of animals in response to lockdowns but ignore others that do. For example: (Wilmers et al. 2021), (Warrington et al. 2022) (though this may have been published after this was submitted...), and (Schrimpf et al. 2021). There is a missed opportunity to consider the drivers of some of these results - the findings in this paper are interesting in light of studies that *did* observe changes in space use or abundance - i.e., changes in space use could arise precisely *because* responses to humans are non-plastic but the distribution and activities of humans changed. To wit, the primary finding here would imply that the reaction norm to human presence is apparently fixed over such timescales - however, and critically, the putative reduction in human activity/mobility combined with fixed responses at the individual level might then imply changes in avian abundance/movement/etc.

b) If this were the case, wouldn't this be then measurable as a function of some measure of urbanity (e.g. Human Footprint Index) that varies across the cities included here? Site accounted for ~15% of the total variation in escape distance but was treated as a random effect - perhaps controlling for the nature of the urban environment using some e.g., remotely sensed variable would provide additional context here.

c) Because it's not clear the extent to which the populations tested had turned over between years, the paper could do with a bit more caution in interpreting these results as behavioral. This study spans several years so any response (or non-response) is not necessarily a measure of behavioral change because the sample at each time point could (likely does) represent different individuals. In fact, there may be an opportunity here to leverage the one site where pre-pandemic measures were taken several years prior to the pandemic. How much variance in the change in escape distance is observed when the gap between time points far exceeds the lifetime of the focal taxa versus measures taken close in time?

d) Finally, I think there are a few other potential explanations not sufficiently accounted for here:

i) These behaviors might indeed be plastic, but not over the timescales observed here.<br /> ii) Time of year - this study took place during the breeding season. The focal behavior here varies with the time of year, for example, escape distance for many of these species could be tied up in nest defense behaviors, tradeoffs between self-preservation and e.g., nest provisioning, etc.<br /> iii) Escape behaviors from humans are adaptively evolved, strongly heritable, and not context dependent - thus we would only expect these behaviors to change on evolutionary timescales.<br /> iv) See point one above - it's possible that the lockdown didn't modify human activity sufficiently to trigger a behavioral response or that the reaction norm to human behavior is non-linear (e.g. a threshold effect).

LITERATURE CITED<br /> Geng DC, Innes J, Wu W, Wang G. 2021. Impacts of COVID-19 pandemic on urban park visitation: a global analysis. J For Res 32:553-567. doi:10.1007/s11676-020-01249-w

Noi E, Rudolph A, Dodge S. 2022. Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework. Int J Geogr Inf Sci.

Schrimpf MB, Des Brisay PG, Johnston A, Smith AC, Sánchez-Jasso J, Robinson BG, Warrington MH, Mahony NA, Horn AG, Strimas-Mackey M, Fahrig L, Koper N. 2021. Reduced human activity during COVID-19 alters avian land use across North America. Sci Adv 7:eabf5073. doi:10.1126/sciadv.abf5073

Warrington MH, Schrimpf MB, Des Brisay P, Taylor ME, Koper N. 2022. Avian behaviour changes in response to human activity during the COVID-19 lockdown in the United Kingdom. Proc Biol Sci 289:20212740. doi:10.1098/rspb.2021.2740

Wilmers CC, Nisi AC, Ranc N. 2021. COVID-19 suppression of human mobility releases mountain lions from a landscape of fear. Curr Biol 31:3952-3955.e3. doi:10.1016/j.cub.2021.06.050

Reviewer #2 (Public Review):

Mikula et al. have a large experience studying the escape distances of birds as a proxy of behavioral adaptation to urban environments. They profited from the exceptional conditions of social distance and reduced mobility during the covid-19 pandemic to continue sampling urban populations of birds under exceptional circumstances of low human disturbance. Their aim was to compare these new data with data from previous "normal" years and check whether bird behavior shifted or not as a consequence of people's lockdown. Therefore, this study would add to the growing body of literature assessing the effect of the covid-19 shutdown on animals. In this sense, this is not a novel study. However, the authors provide an interesting conclusion: birds have not changed their behavior during the pandemic shutdown. This lack of effects disagrees with most of the previously published studies on the topic. I think that the authors cannot claim that urban birds were unaffected by the covid-19 shutdown. I think that the authors should claim that they did not find evidence of covid-19-shutdown effects. This point of view is based on some concerns about data collection and analyses, as well as on evolutionary and ecological rationale used by the authors both in their hypotheses and results interpretation. I will explain my criticisms point by point:

1) The authors used ambivalent, sometimes contradictory, reasoning in their predictions and results interpretation. Some examples:<br /> 1.1) The authors claimed that urban birds perceive humans as harmless (L224), but birds actually escape from us, when we approach them... Furthermore, they escape usually 5 to 20 m away. This is more distance that would be necessary just to be not trampled.<br /> 1.2) If we are harmless, why birds should spend time monitoring us as a potential threat (L102)? Indeed, I disagree with the second prediction of the authors. I could argue that reduced human activity should increase animal vigilance because real bird predators (e.g., raptors) may increase their occurrence or activity in empty cities. If birds should increase their vigilance because the invisible shield of human fear of their predators is no longer available, then I would expect longer escape distances.<br /> 1.3) To justify the same escape behavior shown by birds in pre- and pandemic conditions from an adaptive point of view, the authors argued a lack of plasticity and a strong genetic determination of such behavior. This contravenes the plasticity proposed in the previous point or the expected effect of the stringency index (L112). In my opinion, some degree of plasticity in the escape behavior would be really favorable for individuals from an adaptive perspective, as they may face quite different fear landscapes during their lives. Looking at the figures, one can see notable differences in the escape distance of the same species between sites in the same city. As I can hardly imagine great genetic differences between birds sampled in a park or a cemetery in Rovaniemi, for instance, I would expect a major role of plasticity to explain the observed variability. Furthermore, if escape behavior would not be plastic, I would not expect date or hour effects. By including them in their models, the authors are accepting implicitly some degree of plasticity.

2) Looking at the figures I do not see the immense stochasticity (L156, Fig. S3, S5) claimed by the authors. Instead, I can see that some species showed an obvious behavioral change during the shutdown. For instance, Motacilla alba, Larus ridibundus, or Passer domesticus clearly reduced their escape distances, while others like the Dendrocopos major, Passer montanus, or Turdus merula tended to increase it. On the other hand, birds in Poland tended to have larger escape distances during the shutdown for most species, while in Rovaniemi there was an apparent reduction of escape distances in most cases. The multispecies and multisite approach is a strength of this study, but it is an Achilles' heel at the same time. The huge heterogeneity in bird responses among species and sites counterbalanced and as a result, there was an apparent lack of shutdown effects overall. Furthermore, as most data comes from a few (European) species (i.e., Columba, Passer, Parus, Pica, Turdus, Motacilla) I would say that the overall results are heavily influenced (or biased) by them. The authors realize that results are often area- or species-specific (L203), therefore, does a whole approach make sense?

3) The previous point is worsened by the heterogeneity of cities and periods sampled. For instance:<br /> 3.1) I can hardly imagine any common feature between a small city in northern Finland (Rovaniemi) and a megacity in Australia (Melbourne). Thus, I would not be surprised to find different results between them.<br /> 3.2) Prague baseline data was for 2014 and 2018, while for the rest of the study sites were for 2018 and 2019. If study sites used a different starting point, you cannot compare differences at the final point.<br /> 3.3) Due to the obvious seasonal differences between the northern and southern hemispheres, data collection in Australia began five months later than in the rest of the sites (Aug vs Mar 2020). There, urban birds faced already too many months of reduced human disturbances, while European birds were sampled just at the beginning of the lockdown.<br /> 3.4) Some cities were sampled by a single observer, while others by many of them. Even if all of them are skilled birders, they represent different observers from a statistical point of view and consequently, observer identity was an extra source of noise in your data that you did not account for.

4) Although I liked the stringency index as a variable, I am not sure if it captured effectively the actual human activity every day. Even if restrictive measures were similar between countries, their actual accomplishment greatly depended on people's commitment and authorities' control and sanctions. I would suggest using a more realistic measure of human activity, such as google mobility reports.

5) The authors used escape trials from birds on the ground and perched birds. I think that they are not comparable, as birds on the ground probably perceive a greater risk than those placed some meters above the ground, i.e. I would expect shorter escape distances for perched birds. As this can be strongly dependent on the species preferences or sampling site (i.e, more or less available perches), I wonder how this mixture of observations from birds on the ground and perched birds could be affecting the results.

6) The authors did not sample the same location in the same breeding season to avoid repeated sampling of the same individuals (L331). This precaution may help, but it does not guarantee a lack of pseudoreplication. Birds are highly mobile organisms and the same individuals may be found in different places in the same city. This pseudoreplication seems particularly plausible for Rovaniemi, where sampling points must be necessarily close due to the modest size of this city.

7) An intriguing result was that the authors collected data for 135 species during the shutdown, while they collected data only for 68 species before the pandemic. Such a two-fold increase in bird richness would not be expected with a 36% increase in sampling effort during 2020-21. I wonder if this could be reflecting an actual increase in bird richness in urban areas as a positive result of the shutdown and reduced human presence.

8) The authors dismissed the multicollinearity problem of explanatory variables unjustifiably (L383). However, looking at fig. S1, I can see strong correlations between some of them. For instance, period and stringency index were virtually identical (r=0.95), while temperature and date were also strongly correlated.

9) The random structure of the models is a key element of the statistical analyses but those random factors are poorly explained and justified. I needed to look up the supplementary tables to fully understand the complex architecture of the random part of the models. To the best of my knowledge, random variables aim to account for undesirable correlations in the covariance matrix, which is expected in hierarchical designs, such as the present one. However, the theoretical violation of data independence may happen or not. As the random structure is usually of little interest, you should keep it as simple as necessary, otherwise random factors may be catching part of data variability that you would like to explain by fixed variables. I think that this is what is happening (at least, in part) here, as the authors included a too-complex random structure. For instance, if you include the year as a random factor, I think that you are leaving little room for the period effect. The authors simplified the random structure of the models (L387), but they did not explain how. Nevertheless, this model selection was not important at all, as the authors showed the results for several models. I assume, consequently, that the authors are considering all these models equally valid. This approach seems quite contradictory.

Reviewer #1 (Public Review):

The authors managed to show the broad botanical landscape and not only the main crops. This unique achievement is based on decades of establishing an excellent collection of a full comparative seed collection of the current flora. This allows the identification of species that usually are not identifiable. The authors were able to compare the crops that were grown there and identify the contribution of the Roman period with that of the Arab one. This excellent study is a landmark in how such studies should be done. The list of identified species will be used for many other studies on this subject.

Reviewer #2 (Public Review):

Fuks et al. provide extensive paleobotanical data from several sites in the Negev desert to address hypotheses regarding the relative importance of the Roman Agricultural Diffusion (RAD) and the Islamic Green Revolution (IGR) in the dispersal of crops across Eurasia.

While the overall claims from the authors are convincing, I found the presentation of the data somewhat difficult to follow.<br /> Graphical visualization of the data with respect to the proposed hypotheses would go a long way towards making the argument clearer for a non-specialist audience.

The authors apply appropriate caveats in the discussion about their ability to assess IGR given their timeline only incorporates the first few hundred years and some IGR plants may not leave macrobotanical remains. Yet I think more could be done to explain how the data they do find provides positive evidence for RAD. Many of their findings are inferred to be RAD introductions not because of the timing in their sites, but because of previous evidence of introductions at other sites. It would thus be helpful to be more explicit about what additional evidence these findings provide beyond previously published data of introductions of many of these crops into the Levant.

Reviewer #3 (Public Review):

A big open question in evolutionary biology is how single cells become multicellular organisms, capable of adaptation as a collective. Many cells form groups, but adaptation at the level of the group tends to be inefficient (especially in comparison to cells). Theoretically, it has been proposed that groups formed by clonal development (cells remain attached to each other after division) can more readily lead to group-level adaptation than groups coming together through the aggregation of different cells post-division. To evaluate empirically the plausibility of this hypothesis, the authors compared adaptation in two lines of yeast that differ only in a couple of mutations determining their mechanism of group formation. Ace2 mutants develop through staying together, and Floc mutants through aggregation. They performed a form of size selection (through settling) as a way to select for multicellularity (this selection regime has been used before to obtain multicellular phenotypes). This selective regime has two components: growing (largely due to differences between cells) and settling (largely due to differences between groups). Thus, the authors assume that increases in fitness through growth are due mostly to adaptation at the single-cell level, whereas increases in fitness through settling are mostly due to adaptation at the multicellular level. They find that adaptation in clonal groups is mostly through settling and that aggregative groups adapt more through growth (despite getting bigger).

Overall this assumption makes sense (especially in a positive way) but growth, in this case, is also selecting against groups in the snowflake case and less strongly so in the floc case in which cells aggregate and disaggregate with some probability, and therefore cells can keep growing. That is, in addition to assortment the result is somewhat expected because there is less of a trade-off between growth and settling in floc: having a higher density in floc probably leads to higher aggregation and indirectly benefits settling, whereas in the clonal case, larger groups mean that a larger proportion of cells is not growing.

The main result of the paper holds true: clonal development favors multicellular adaptation relative to aggregative multicellularity, but the reason is not exclusively a difference in the distribution of variation, but a difference in the trade-off between single cell and multicellular traits.

In the second part of the paper, the authors beautifully show that the mechanisms of group formation affect evolutionary processes. Clonal aggregation leads to a decrease in the effective population size (because the descendants of mutants are likely to be in the same group, and therefore be selected together). This result shows that the mode of development can affect evolution!

Reviewer #1 (Public Review):

The paper proposes a novel approach, named ModCRE, which utilizes structure-based learning to predict the DNA binding preferences of transcription factors (TFs). The authors integrate both experimental knowledge of the structures of TF-DNA complexes and large amounts of high-throughput TF-DNA interaction data. Additionally, the authors have developed a server that automatically produces these characteristics for other TFs and their complexes with co-factors.

Strengths: The paper's integration of experimental knowledge and high-throughput data to develop statistical knowledge-based potentials to score the binding capability of TFs in cis-regulatory elements is a powerful strategy. The proposed approach can be applied to more than 80% of TF sequences, making it a general method for characterizing binding preferences.

Weaknesses: The paper is difficult to follow, as it contains many technical details and implementation details. The method applied is not always clear, and the paper focuses on implementation rather than the message. The results indicate that the nearest neighbors approach in Figure 4 outperforms the proposed method in many cases, and the proposed method seems to perform better only when similarity with the target is low. The same applies in Fig. 5 when using normalized ranked scores.

It appears that the authors have successfully developed a structure-based learning approach for predicting DNA binding preferences of transcription factors. However, the paper's technical language and implementation focus make it challenging to follow at times.

It seems the authors have successfully achieved most of their aims in improving predictions for TF-DNA interaction, and the results support their conclusions.

This work has the potential to significantly impact the field of TF-DNA binding and gene regulation, particularly for those interested in predicting PWMs for TFs with limited or unreliable experimental data.

Reviewer #1 (Public Review):

Summary:<br /> Rai1 encodes the transcription factor retinoic acid-induced 1 (RAI1), which regulates expression of factors involved in neuronal development and synaptic transmission. Rai1 haploinsufficiency leads to the monogenic disorder Smith-Magenis syndrome (SMS), which is associated with excessive feeding, obesity and intellectual disability. Consistent with findings in human subjects, Rai1+/- mice and mice with conditional deletion of Rai1 in Sim+ neurons, which are abundant in the paraventricular nucleus (PVN), exhibit hyperphagia, obesity and increased adiposity. Furthermore, RAI1-deficient mice exhibit reduced expression of brain-derived neurotrophic factor (BDNF), a satiety factor essential for the central control of energy balance. Notably, overexpression of BDNF in PVN of RAI1-deficient mice mitigated their obesity, implicating this neurotrophin in the metabolic dysfunction these animals exhibit. In this follow up study, Javed et al. interrogated the necessity of RAI1 in BDNF+ neurons promoting metabolic health.

Consistent with previous reports, the authors observed reduced BDNF expression in the hypothalamus of Rai1+/- mice. Moreover, proteomics analysis indicated impairment in neurotrophin signaling in the mutants. Selective deletion of Rai1 in BDNF+ neurons in the brain during development resulted in increased body weight, fat mass and reduced locomotor activity and energy expenditure without changes in food intake. There was also a robust effect on glycemic control, with mutants exhibiting glucose intolerance. Selective depletion of RAI1 in BDNF+ neurons in PVN in adult mice also resulted in increased body weight, reduced locomotor activity, and glucose intolerance without affecting food intake. Blunting RAI1 activity also leads to increases and decreases in the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN.

Strengths:<br /> Overall, the experiments are well designed and multidisciplinary approaches are employed to demonstrate that RAI1 deficits in BDNF+ neurons diminish hypothalamic BDNF signaling and produce metabolic dysfunction. The most significant advance relative to previous reports is the finding from electrophysiological studies showing that blunting RAI1 activity leads to increases and decreases the inhibitory tone and intrinsic excitability, respectively, of BDNF+ neurons in the PVN. Furthermore, that intact RAI1 function is required in BDNF+ neurons for the regulation of glucose homeostasis.

Weaknesses:<br /> Some of the data need to be reconciled with previous findings by others. For example, the authors report that more than 50% of BDNF+ neurons in PVN also express pTrkB whereas about 20% of pTrkB+ cells contain BDNF, raising the possibility that autocrine mechanisms might be at play. This is in conflict with a previous study by An et al, (2015) showing that these cell populations are largely non-overlapping in the PVN.

Another issue that deserves more in depth discussion is that diminished BDNF function appears to play a minor part driving deficits in energy balance regulation. Accordingly, both global central depletion of Rai1 in BDNF+ neurons during development and deletion of Rai1 in BDNF+ neurons in the adult PVN elicited modest effects on body weight (less than 18% increase) and did not affect food intake. This contrasts with mice with selective Bdnf deletion in the adult PVN, which are hyperphagic and dramatically obese (90% heavier than controls). Therefore, the results suggest that deficits in RAI1 in PVN or the whole brain only moderately affect BDNF actions influencing energy homeostasis and that other signaling cascades and neuronal populations play a more prominent role driving the phenotypes observed in Rai1+/- mice, which are hyperphagic and 95% heavier than controls. The results from the proteomic analysis of hypothalamic tissue of Rai1 mutant mice and controls could be useful in generating alternative hypotheses.

Depleting RAI1 in BDNF+ neurons had a robust effect compromising glycemic control. However, as the approach does not necessarily impact BDNF exclusively, there should be a larger discussion of alternative mechanisms.

Reviewer #3 (Public Review):

Summary:<br /> Smith-Magenis syndrome (SMS) is associated with obesity and is caused by deletion or mutations in one copy of the Rai1 gene which encodes a transcriptional regulator. Previous studies have shown that Bdnf gene expression is reduced in the hypothalamus of Rai1 heterozygous mice. This manuscript by Javed et al. further links SMS-associated obesity with reduced Bdnf gene expression in the PVH.

Strengths:<br /> The authors show that deletion of the Rai1 gene in all BDNF-expressing cells or just in the PVH BDNF neurons postnatally caused obesity. Interestingly, mutant mice displayed sexual dimorphism in the cause for the obesity phenotype. Overall, the data are well presented and convincing except the data from LM22A-4.

Weaknesses:<br /> 1. The most serious concern is about data from LM22A-4 administration experiments (Figure 5 and associated supplemental figures). A rigorous study has demonstrated that LM22A-4 does not activate TrkB (Boltaev et al., Science Signaling, 2017), which is consistent with unpublished results from many labs in the neurotrophin field. It is tricky to interpret body weight data from pharmacological studies because compounds always have some side effects, which can reduce body weight non-specifically.

2. The resolution of all figures are poor, and thus I could not judge the quality of the micrographs.

3. Citation of the literature is not precise. The study by An et al. (2015) shows that deletion of the Bdnf gene in the PVH leads to obesity due to increased food intake and reduced energy expenditure (not just hyperphagic obesity; Line 72). Furthermore, the study by Unger et al. (2017) carried out Bdnf deletion in the VMH and DMH using AAV-Cre and did not discuss SF1 neurons at all (Line 354). The two studies by Yang et al. (Mol Endocrinol, 2016) and Kamitakahara et al. (Mol Metab, 2015) did use SF1-Cre to delete the Bdnf gene and did not observe any obesity phenotype.

4. Animal number is not described in many figure legends.

Reviewer #2 (Public Review):

Understanding disease conditions often yields valuable insights into the physiological regulation of biological functions, as well as potential therapeutic approaches. In previous investigations, the author's research group identified abnormal expression of brain-derived neurotrophic factor (BDNF) in the hypothalamus of a mouse model exhibiting Smith-Magenis syndrome (SMS), which is caused by heterozygous mutations of the Rai1 gene. Human SMS is associated with distinct facial characteristics, sleep disturbances, behavioral issues, and intellectual disabilities, often accompanied by obesity. Conditional knockout (cKO) of the Bdnf gene from the paraventricular hypothalamus (PVH) in mice led to hyperphagic obesity, while overexpression of the Bdnf gene in the PVH of Rai1 heterozygous mice restored the SMS-like obese phenotype. Based on these preceding findings, the authors of the present study discovered that homozygous Rai1 cKO restricted to Bdnf-expressing cells, or Rai1 gene knockdown solely in Bdnf-positive neurons in the PVH, induced obesity along with intricate alterations in adipose tissue composition, energy expenditure, locomotion, feeding patterns, and glucose tolerance, some of which varied between sexes. Additionally, the authors demonstrated that a brain-penetrating drug capable of activating the TrkB pathway, a downstream signaling pathway of BDNF, partially alleviated the SMS-like obesity phenotype in female mice with Rai1 heterozygous mutations. Although the specific (neural) cell type responsible for this TrkB signaling remains an open question, the present study unequivocally highlights the importance of Rai1 gene function in PVH Bdnf neurons for the obesity phenotype, providing valuable insights into potential therapeutic strategies for managing obesity associated with SMS.

In the proteomic analysis (Fig. 1), the authors elucidated that multiple phospho-protein signaling pathways, including Akt and mTOR pathways, exhibited significant attenuation in the SMS model mice. Of significance, the manifestation of haploinsufficiency of the Rai1 gene exclusively within the BDNF+ cells demonstrated negligible impact on body weight (Fig. 2-supple 3D), despite observing a reduction in BDNF levels in the heterozygous Rai1 mutant (Fig. 1A). Conversely, the homozygous Rai1 cKO in the BDNF+ cells prominently displayed an obesity phenotype, suggesting substantial dissimilarities in the gene expression profiles between Rai1 heterozygous and homozygous conditions within the BDNF+ cell population. It would be advantageous to precisely identify the responsible differentially expressed genes, possibly including Bdnf itself, in the homozygous cKO model. The observed reduction in the excitability of PVH BDNF+ cells (Fig. 3) is presumably attributed to aberrant gene expression other than Bdnf itself, which may serve as a prospective target for gene expression analysis. Notably, the Rai1 homozygous cKO mice in BDNF+ cells exhibited some sexual dimorphisms in feeding and energy expenditures, as evidenced by Fig. 2 and related figures. Exploring the potential relevance of these sexual differences to human SMS cases and investigating the underlying cellular/molecular mechanisms in the future would provide valuable insights.

Although the CRISPR-mediated knockdown of the Rai1 gene (Fig. 4) appears to be highly effective, given the broad transduction of AAV serotype 9, it may be helpful to exclude the possibility of other brain regions adjacent to the PVH, such as the DMH or VMH, being affected by this viral procedure. If the PVH-specificity is established, the majority of Rai1 cKO effects in Bdnf+ cells are primarily attributed to PVH-Bdnf+ cells based on the similarity of phenotypes observed. With regards to the apparent rescue of the body weight phenotype in Rai1 heterozygous mutants using a selective TrkB activator, the specific biological processes, and neurons responsible for this effect remain unclear to this reviewer. Elucidating these aspects would be significant when considering potential applications to human SMS cases.

Overall, the present study represents a valuable addition to the authors' series of high-quality molecular genetic investigations into the in vivo functions of the Rai1 gene. This reviewer particularly commends their diligent efforts to enhance our comprehension of SMS and contribute to the future development of more effective therapies for this syndrome.

Reviewer #1 (Public Review):

Summary:<br /> This paper reported a protocol of using human-induced pluripotent stem cells to generate cells expressing microglia-enriched genes and responding to LPS by drastic upregulation of proinflammatory cytokines. Upon subretinal transplantation in mice, hiPSC-derived cells integrated into the host retina and maintained retinal homeostasis, while they responded to RPE injury by migration, proliferation and phagocytosis. The findings revealed the potential of using hiPSC-derived cell transplantation for microglia replacement as a therapeutic strategy for retinal diseases.

Strengths:<br /> The paper demonstrates a method of consistently generating a significant quantity of hiPSC-derived microglia-like cells for in vitro study or for in vivo transplantation. RNAseq analysis offers an opportunity for comprehensive transcriptome profiling of the derived cells. It is impressive that following transplantation, these cells integrated into the retina well, migrated to the corresponding layers, adopted microglia-like morphologies, and survived long term without generating apparent harm. The work has laid a foundation for future utilization of hiPSC-derived microglia in lab and clinical applications.

Weaknesses:<br /> 1. The primary weakness of the paper concerns its conclusion of having generated "homogenous mature microglia", partly based on the RNAseq analysis. However, the comparison of gene profiles was carried out only between "hiPSC-derived mature microglia" and the proliferating myeloid progenitors. While the transcriptome profiles revealed a trend of enrichment of microglia-like gene expression in "hiPSC-derived mature microglia" compared to proliferating myeloid progenitors, this is not sufficient to claim they are "mature microglia". It is important that one carries out a comparative analysis of the RNAseq data with those of primary human microglia, which may be done by leveraging the public database. To convincingly claim these cells are mature microglia, questions need to be addressed including how similar the molecular signatures of these cells are compared with the fully differentiated primary microglia cell or if they remain progenitor-like or take on mosaic properties, and how they distinguish from macrophages.

2. While the authors attempted to demonstrate the functional property of "hiPSC-derived mature microglia" in culture, they used LPS challenge, which is an inappropriate assay. This is because human microglia respond poorly to LPS alone but need to be activated by a combination of LPS with other factors, such as IFNγ. Their data that "hiPSC-derived mature microglia" showed robust responses to LPS indeed implicates that these cells do not behave like mature human microglia.

3. The resolution of Figs. 4 - 6 is so low that even some of the text and labels are hardly readable. Based on the morphology shown in Fig. 4 and the statement in line 147, these hiPSC-derived "cells altered their morphology to a rounded shape within an hour of incubation and rapidly internalized the fluorescent-labeled particles". This is a peculiar response. Usually, microglia do not respond to fluorescent-labeled zymosan by turning into a rounded shaped within an hour when they internalize them. Such a behavior usually implicates weak phagocytotic capacity.

4. Data presented in Fig. 5 are not very convincing to support that transplanted cells were immunopositive for "human CD11b (Fig.5C), as well as microglia signature markers P2ry12 and TMEM119 (Fig.5D)" (line 167). The resolution and magnification of Fig. 5D is too low to tell the colocalization of tdT and human microglial marker immunolabeling. In the flat-mount images (C, I), hCD11b immunolabeling is not visible in the GCL or barely visible in the IPL. This should be discussed.

5. Microglia respond to injury by becoming active and lose their expression of the resting state microglial marker, such as P2ry12, which is used in Fig. 6 for detection of migrated microglia. To confirm that these cells indeed respond to injury like native microglia, one should check for activated microglial markers and induction of pro-inflammatory cytokines in the sodium iodate-injury model.

Reviewer #2 (Public Review):

Summary:<br /> Ma et al. employed a myeloid progenitor/microglia differentiation protocol to produce human-induced pluripotent stem cell (hiPSC)-derived microglia in order to examine the potential of microglial cell replacement as a treatment for retinal disorders. They characterized the iPSC-derived microglia by gene expression and in vitro assay analysis. By evaluating xenografted microglia in the partly microglia-depleted retina, the function of the microglia was further assessed.

Strengths:

Overall, the study and the data are convincing, and xenografted microglia were also tested in a RPE injury paradigm.

Weaknesses:

Gene expression analysis of mature microglia cells should be better interpreted and it would be beneficial to compare the iPSC-derived microglia gene set to a human microglial cell line (for example, HMC3) instead of myeloid progenitor cells.<br /> The way that the manuscript has been written, unfortunately, is not optimal. I recommend that the entire manuscript be edited and proofread in English. The text contains spelling and grammar mistakes, and the manuscript is inconsistent in several parts. The manuscript should also be revised for a scientific paper format.

Reviewer #1 (Public Review):

The inferior colliculus (IC) is the central auditory system's major hub. It integrates ascending brainstem signals to provide acoustic information to the auditory thalamus. The superficial layers of the IC ("shell" IC regions as defined in the current manuscript) also receive a massive descending projection from the auditory cortex. This auditory cortico-collicular pathway has long fascinated the hearing field, as it may provide a route to funnel "high-level" cortical signals and impart behavioral salience upon an otherwise behaviorally agnostic midbrain circuit.

Accordingly, IC neurons can respond differently to the same sound depending on whether animals engage in a behavioral task (Ryan and Miller 1977; Ryan et al., 1984; Slee & David, 2015; Saderi et al., 2021; De Franceschi & Barkat, 2021). Many studies also report a rich variety of non-auditory responses in the IC, far beyond the simple acoustic responses one expects to find in a "low-level" region (Sakurai, 1990; Metzger et al., 2006; Porter et al., 2007). A tacit assumption is that the behaviorally relevant activity of IC neurons is inherited from the auditory cortico-collicular pathway. However, this assumption has never been tested, owing to two main limitations of past studies:

1) Prior studies could not confirm if data were obtained from IC neurons that receive monosynaptic input from the auditory cortex.

2) Many studies have tested how auditory cortical inactivation impacts IC neuron activity; the consequence of cortical silencing is sometimes quite modest. However, all prior inactivation studies were conducted in anesthetized or passively listening animals. These conditions may not fully engage the auditory cortico-collicular pathway. Moreover, the extent of cortical inactivation in prior studies was sometimes ambiguous, which complicates interpreting modest or negative results.

Here, the authors' goal is to directly test if auditory cortex is necessary for behaviorally relevant activity in IC neurons. They conclude that surprisingly, task relevant activity in cortico-recipient IC neuron persists in absence of auditory cortico-collicular transmission. To this end, a major strength of the paper is that the authors combine a sound-detection behavior with clever approaches that unambiguously overcome the limitations of past studies.

First, the authors inject a transsynaptic virus into the auditory cortex, thereby expressing a genetically encoded calcium indicator in the auditory cortex's postsynaptic targets in the IC. This powerful approach enables 2-photon Ca2+ imaging from IC neurons that unambiguously receive monosynaptic input from auditory cortex. Thus, any effect of cortical silencing should be maximally observable in this neuronal population. Second, they abrogate auditory cortico-collicular transmission using lesions of auditory cortex. This "sledgehammer" approach is arguably the most direct test of whether cortico-recipient IC neurons will continue to encode task-relevant information in absence of descending feedback. Indeed, their method circumvents the known limitations of more modern optogenetic or chemogenetic silencing, e.g. variable efficacy.

I also see three weaknesses which limit what we can learn from the authors' hard work, at least in the current form. I want to emphasize that these issues do not reflect any fatal flaw of the approach. Rather, I believe that their datasets likely contain the treasure-trove of knowledge required to completely support their claims.

1. The conclusion of this paper requires the following assumption to be true: That the difference in neural activity between Hit and Miss trials reflects "information beyond the physical attributes of sound." The data presentation complicates asserting this assumption. Specifically, they average fluorescence transients of all Hit and all Miss trials in their detection task. Yet, Figure 3B shows that mice's d' depends on sound level, and since this is a detection task the smaller d' at low SPLs presumably reflects lower Hit rates (and thus higher Miss rates). As currently written, it is not clear if fluorescence traces for Hits arise from trials where the sound cue was played at a higher sound level than on Miss trials. Thus, the difference in neural activity on Hit and Miss trials could indeed reflect mice's behavior (licking or not licking). But in principle could also be explained by higher sound-evoked spike rates on Hit compared to Miss trials, simply due to louder click sounds. Indeed, the amplitude and decay tau of their indicator GCaMP6f is non-linearly dependent on the number and rate of spikes (Chen et al., 2013), so this isn't an unreasonable concern.

2. The authors' central claim effectively rests upon two analyses in Figures 5 and 6. The spectral clustering algorithm of Figure 5 identifies 10 separate activity patterns in IC neurons of control and lesioned mice; most of these clusters show distinct activity on averaged Hit and Miss trials. They conclude that although the proportions of neurons from control and lesioned mice in certain clusters deviates from an expected 50/50 split, neurons from lesioned mice are still represented in all clusters. A significant issue here is that in addition to averaging all Hits and Miss trials together, the data from control and lesioned mice are lumped for the clustering. There is no direct comparison of neural activity between the two groups, so the reader must rely on interpreting a row of pie charts to assess the conclusion. It's unclear how similar task relevant activity is between control and lesioned mice; we don't even have a ballpark estimate of how auditory cortex does or does not contribute to task relevant activity. Although ideally the authors would have approached this by repeatedly imaging the same IC neurons before and after lesioning auditory cortex, this within-subjects design may be unfeasible if lesions interfere with task retention. Nevertheless, they have recordings from hundreds to thousands of neurons across two groups, so even a small effect should be observable in a between-groups comparison.

3. In Figure 6, the authors show that logistic regression models predict whether the trial is a Hit or Miss from their fluorescence data. Classification accuracy peaks rapidly following sound presentation, implying substantial information regarding mice's actions. The authors further show that classification accuracy is reduced, but still above chance in mice with auditory cortical lesions. The authors conclude from this analysis task relevant activity persists in absence of auditory cortex. In principle I do not disagree with their conclusion.

The weakness here is in the details. First, the reduction in classification accuracy of lesioned mice suggests that auditory cortex does nevertheless transmit some task relevant information, however minor it may be. I feel that as written, their narrative does not adequately highlight this finding. Rather one could argue that their results suggest redundant sources of task-relevant activity converging in the IC. Secondly, the authors conclude that decoding accuracy is impaired more in partially compared to fully lesioned mice. They admit that this conclusion is at face value counterintuitive, and provide compelling mechanistic arguments in the Discussion. However, aside from shaded 95% CIs, we have no estimate of variance in decoding accuracy across sessions or subjects for either control or lesioned mice. Thus we don't know if the small sample sizes of partial (n = 3) and full lesion (n = 4) groups adequately sample from the underlying population. Their result of Figure 6B may reflect spurious sampling from tail ends of the distributions, rather than a true non-monotonic effect of lesion size on task relevant activity in IC.

Reviewer #1 (Public Review):

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder leading to the loss of innervation of skeletal muscles, caused by the dysfunction and eventual death of lower motor neurons. A variety of approaches have been taken to treat this disease. With the exception of three drugs that modestly slow progression, most therapeutics have failed to provide benefit. Replacing lost motor neurons in the spinal cord with healthy cells is plagued by a number of challenges, including the toxic environment, inhibitory cues that prevent axon outgrowth to the periphery, and proper targeting of the axons to the correct muscle groups. These challenges seem to be well beyond our current technological approaches. Avoiding these challenges altogether, Bryson et al. seek to transplant the replacement motor neurons into the peripheral nerves, closer to their targets. The current manuscript addresses some of the challenges that will need to be overcome, such as immune rejection of the allograft and optimizing maturation of the neuromuscular junction.

Bryson et al. begin by examining the survival of mESC-derived motor neurons allografted into SOD1 mice. The motor neurons, made on a 129S1/SvImJ, were transplanted into the tibial nerve of SOD1 mice on a C57BL/6J background. Without immunosuppression, most cells were lost between 14 and 35 days, suggesting an immune response had eliminated them. Tacrolimus prevented cell loss, but it also inhibited innervation of the muscle. It also uncovered the tumorigenic potential of contaminating pluripotent cells. In contrast, immunosuppression using H57-597, an antibody targeting T-cell receptor beta, prevented graft rejection while permitting some innervation of muscle. Pretreatment of the cells with mitomycin-C eliminated pluripotent cells, preventing tumor formation. The authors noted that this combination only innervated ~10% of endplates, likely due to the fact that the implanted motor neurons are not active.

The authors then began the process of optimizing the cells themselves, using measurements taken in late-stage SOD1 mice. Fast-firing and slow-firing populations of neurons were first compared. Using optical stimulation, these two cell types appeared to be similar. The authors opted to use slow-firing neurons in the subsequent experiments. Recognizing that neuromuscular junction (NMJ) innervation and maintenance are dependent on motor neuron activity, implantable optical stimulators were also evaluated. 14 days after transplanting the cells, optical stimulation training was initiated for one hour each day. This training led to a nearly 13-fold increase in force generation, although this still remained well below the force generated by electrical stimulation. The enhanced innervation also prevented the atrophy of muscle fibers caused by denervation.

Overall, the data for the function of the implanted cells are convincing. The dCALMS technique that the authors have developed is quite interesting and will likely be applicable to analyze muscles for other therapeutics. The identification of calcineurin inhibitors as inhibitors of reinnervation will also be important for the development of other cell-based therapeutics for ALS.

However, there are some issues that should be addressed. These include some common misconceptions about ALS. While ALS is split into familial and sporadic forms based on the presence or absence of a family history of the disease, mutations in the known ALS-associated genes are found in both forms. The authors also state that exercise programs are likely to accelerate degeneration in ALS. This is incorrect. Moderate exercise is part of the current guidelines for treating ALS, and mouse studies have demonstrated a therapeutic effect of moderate exercise. Regarding the experimental design, there are some important details missing. The animals do not appear to have been operated on at the same age, and the criteria for when to perform the operation were not described. A similar problem exists for when the animals were determined to reach endpoint. The authors also do not seem to address a potential pitfall of this approach: acceleration of the disease process. Indeed, some of the data comparing the ipsilateral side to the contralateral side suggest that the implantation of the cells and/or the light source increase the denervation of the muscle. Finally, there is a fairly large difference between the motor output provided by optical stimulation relative to electrical stimulation. It is currently unclear what level needs to be reached to provide an effective response in the intact animal. Thus, it is difficult to determine if the level of reinnervation that this study has achieved will be sufficient to improve a patient's quality of life.

Reviewer #2 (Public Review):

The authors provide convincing evidence that optogenetic stimulation of ChR2-expressing motor neurons implanted in muscles effectively restores innervation of severely affected skeletal muscles in the aggressive SOD1 mouse model of ALS, and conclude that this method can be applied to selectively control the function of implicated muscles. This was supported by convincing data presented in the paper.

This is an interesting paper providing new/improved optogenetic methods to restore or improve muscle strength in ALS. In general, it is of high significance in both the techniques and concept, and the paper was well written. The evidence supporting the conclusions is convincing, with rigorous muscle tension physiological analysis, and nerve and muscle histology and image analysis. The work will be of broad interest to medical biologists on muscle disorders.

One weak point is that proper control experiments were not clearly presented - these could be shown in the paper. For example, one control experiment with only YFP but no ChR2 expression with optogenetic stimulation should be performed, following similar procedures and analysis applied to the ChR2-transduced animals.

Reviewer #1 (Public Review):

This is a key paper examining the evolution of an important structure (pillars) in the shell architecture of organo-phosphatic brachiopods. The advantages of these structures are adequately discussed and the evolution of the pillars is described and illustrated. There is much that is of fundamental significance here in understanding the ecology and evolution of these groups as a whole.

1) In several places the biological control on the development of the pillars is noted. This is explained in terms of their relationship to the growth and evolution of epithelial cells. It would be useful and make the paper more understandable if this link was mentioned early on in the paper and developed during the narrative.

2) The Cambrian Explosion is mentioned a number of times. Are these changes driven by the Cambrian Explosion, i.e. the expansion of major new body plans, or are the changes merely coincident with the long duration of the 'Explosion'?

3) I have no doubt the process is one of adaptive innovation but it would be useful to expand on this. Why is it adaptive?

4) Are pillars present in living Lingula?

Reviewer #2 (Public Review):

Summary: Two early Cambrian taxa of linguliform brachiopods are assigned to the family Eoobolidae. The taxa exhibit a columnar shell structure and the phylogenetic implications of this shell structure in relation to other early Cambrian families are discussed.

Strengths: Interesting idea regarding the evolution of shell structure.

Weaknesses: The early record of shell structures of linguliform brachiopods is incomplete and partly contradictory. The authors maintain silence regarding contradictory information throughout the article to the extent that information is cited wrongly.<br /> The structure and language of the article need reworking in my opinion, the systematic part can be in the appendix but the main results and the results relevant for the discussion should be in the main article. A critical revision of the family Eoobolidae and Lingulellotretidae including a revision of the type species of Eoobolus and Lingulellotreta is needed.

Reviewer #1 (Public Review):

The present study examines whether one can identify kinematic signatures of different motor strategies in both humans and non-human primates (NHP). The Critical Stability Task (CST) requires a participant to control a cursor with complex dynamics based on hand motion. The manuscript includes datasets on performance of NHPs collected from a previous study, as well as new data on humans performing the same task. Further human experiments and optimal control models highlight how different strategies lead to different patterns of hand motion. Finally, classifiers were developed to predict which strategy individuals were using on a given trial. There are several strengths to this manuscript. I think the CST task provides a useful behavioural task to explore the neural basis of voluntary control. While reaching is an important basic motor skill, there is much to learn by looking at other motor actions to address many fundamental issues on the neural basis of voluntary control. I also think the comparison between human and NHP performance is important as there is a common concern that NHPs can be overtrained in performing motor tasks leading to differences in their performance as compared to humans. The present study highlights that there are clear similarities in motor strategies of humans and NHPs. While the results are promising, I would suggest that the actual use of these paradigms and techniques likely need some improvement/refinement. Notably, the threshold or technique to identify which strategy an individual is using on a given trial needs to be more stringent given the substantial overlap in hand kinematics between different strategies.

The most important goal of this study is to set up future studies to examine how changes in motor strategies impact neural processing. I have a few concerns that I think need to be considered. First, a classifier was developed to identify whether a trial reflected Position Control with success deemed to be a probability of >70% by the classifier. In contrast, a probability of <30% was considered successfully predicting Velocity Control (Uncertain bandwidth middle 40%). While this may be viewed as acceptable for purposes of quantifying behaviour, I'm not sure this is strict enough for interpreting neural data. Figure 7A displays the OFC Model results for the two strategies and demonstrates substantial overlap for RMS of Cursory Position and Velocity at the lowest range of values. In this region, individual trials for humans and NHP are commonly identified as reflecting Position Control by the classifier although this region clearly also falls within the range expected for Velocity Control, just a lower density of trials. The problem is that neural data is messy enough, but having trials being incorrectly labelled will make it even messier when trying to quantify differences in neural processing between strategies. A further challenge is that trials cannot be averaged as the patterns of kinematics are so different from trial-to-trial. One option is to just move up the threshold from >70%/<30% to levels where you have a higher confidence that performance only reflects one of the two strategies (perhaps 95/5% level). Another approach would be to identify the 95% confidence boundary for a given strategy and only classify a trial as reflecting a given strategy when it is inside its 95% boundary, but outside the other strategies 95% boundary (or some other level separation). A higher threshold would hopefully also deal with the challenge of individuals switching strategies within a trial. Admittedly, this more stringent separation will likely drop the number of trials prohibitively, but there is a clear trade-off between number of trials and clean data. For the future, a tweak to the task could be to lengthen the trial as this would certainly increase separation between the two conditions.

While the paradigm creates interesting behavioural differences, it is not clear to me what one would expect to observe neurally in different brain regions beyond paralleling kinematic differences in performance. Perhaps this could be discussed. One extension of the present task would be to add some trials where visual disturbances are applied near the end of the trial. The prediction is that there would be differences in the kinematics of these motor corrections for different motor strategies. One could then explore differences in neural processing across brain regions to identify regions that simply reflect sensory feedback (no differences in the neural response after the disturbance), versus those involved in different motor strategies (differences in neural responses after the disturbance).

It seems like a mix of lambda values are presented in Figure 5 and beyond. There needs to be some sort of analysis to verify that all strategies were equally used across lambda levels. Otherwise, apparent differences between control strategies may simply reflect changes in the difficulty of the task. It would also be useful to know if there were any trends across time? Strategies used for blocks of trials or one used early when learning and then changing later.

Figure 2 highlights key features of performance as a function of task difficulty. Lines 187 to 191 highlight similarities in motor performance between humans and NHPs. However, there is a curious difference in hand/cursor Gain for Monkey J. Any insight as to the basis for this difference?

Reviewer #3 (Public Review):

This paper considers a challenging motor control task - the critical stability task (CST) - that can be performed equally well by humans and macaque monkeys. This task is of considerable interest since it is rich enough to potentially yield important novel insights into the neural basis of behavior in more complex tasks that point-to-point reaching. Yet it is also simple enough to allow parallel investigation in humans and monkeys, and is also easily amenable to computational modeling. The paper makes a compelling argument for the importance of this type of parallel investigation and the suitability of the CST for doing so.

Behavior in monkeys and in human subjects suggests that behavior seems to cluster into different regimes that seem to either oscillate about the center of the screen, or drift more slowly in one direction. The authors show that these two behavioral regimes can be reliably reproduced by instructing human participants to either maintain the cursor in the center of the screen (position control objective), or keep the cursor still anywhere in the screen (velocity control objective) - as opposed to the usual 'instruction' to just not let the cursor leave the screen. A computational model based on optimal feedback control can similarly reproduce the two control regimes when the costs are varied

Overall, this is a creative study that successfully leverages experiments in humans and computational modeling to gain insight into the nature of individual differences in behavior across monkeys (and people). The approach does work and successfully solves the core problem the authors set out to address. I do think that more comprehensive approaches might be possible that might involve, e.g. using a richer set of behavioral features to classify behavior, fitting a parametric class of control objectives rather than assuming a binary classification, and exploring the reliability of the inference process in more detail.

In addition, the authors do fully establish that varying control objectives is the only way to obtain the different behavioral phenotypes observed. It may, for instance, be possible that some other underlying differences (e.g. the sensitivity to effort costs or the extent of signal-dependent noise) might also lead to a similar range of behaviors as varying the position versus velocity costs.

Specific Comments:<br /> The simulations convincingly show that varying the control objective via the cost function can reproduce the different observed behavioral regimes. However, in principle, the differences in behavior among the monkeys and among the humans in Experiment 1 might not necessarily be due to difference in other aspects of the model. For instance, for a fixed cost function, differences in motor execution noise might perhaps lead the model to favor a position-like strategy or a velocity-like strategy. Or differences in the relative effort cost might alter the behavioral phenotype. Given that the narrative is about inferring control objectives, it seems important to rule out more systematically that some other factor might not potentially dictate each individual's style of performing the task. One approach to rule this out might be to try to formally fit the parameters of the model (or at least a subset of them) under a fixed cost function (e.g. velocity-based), and check whether the model might still recover the different regimes of behavior when parameters *other than the cost function* are varied.

The approach to the classification problem is somewhat ad hoc and based on fairly simplistic, hand-picked features (RMS position and RMS velocity). I do wonder whether a more comprehensive set of behavioral features might enable a clearer separation between strategies, or might even reveal that the uninstructed subjects were doing something qualitatively different still from the instructed groups. Different control objectives ought to predict meaningfully different control policies - that is, different ways of updating hand position based on current state of the cursor and hand - e.g. the hand/cursor gain, which does clearly differ across instructed strategies. Would it be possible to distinguish control strategies more accurately based on this level of analysis, rather than based on gross task metrics? Might this point to possible experimental interventions (e.g. target jumps) that might validate the inferred objective?

It seems that the classification problem cannot be solved perfectly, at least on a single-trial level. Although it works out that the classification can recover which participants were given which instructions, it's not clear how robust this classification is. It should be straightforward to estimate the reliability of the strategy classification by simulating participants and deriving a "confusion matrix", i.e. calculating how often e.g. data generated under a velocity-control objective gets mis-classified as following a position-control objective. It's not clear how this kind of metric relates to the decision confidence outputted by the classifier.

The problem of inferring the control objective is framed as a dichotomy between position control and velocity control. In reality, however, it may be a continuum of possible objectives, based on the relative cost for position and velocity. How would the problem differ if the cost function is framed as estimating a parameter, rather than as a classification problem?

Reviewer #1 (Public Review):

This paper falls in a long tradition of studies on the costs of reproduction in birds and its contribution to understanding individual variation in life histories. Unfortunately, the meta-analyses only confirm what we know already, and the simulations based on the outcome of the meta-analysis have shortcomings that prevent the inferences on optimal clutch size, in contrast to the claims made in the paper.

There was no information that I could find on the effect sizes used in the meta-analyses other than a figure listing the species included. In fact, there is more information on studies that were not included. This made it impossible to evaluate the data-set. This is a serious omission, because it is not uncommon for there to be serious errors in meta-analysis data sets. Moreover, in the long run the main contribution of a meta-analysis is to build a data set that can be included in further studies.

The main finding of the meta-analysis of the brood size manipulation studies is that the survival costs of enlarging brood size are modest, as previously reported by Santos & Nakagawa on what I suspect to be mostly the same data set. The paper does a very poor job of critically discussing whether we should take this at face value or whether instead there may be short-comings in the general experimental approach. A major reason why survival cost estimates are barely significantly different from zero may well be that parents do not fully adjust their parental effort to the manipulated brood size, either because of time/energy constraints, because it is too costly and therefore not optimal, or because parents do not register increased offspring needs. Whatever the reason, as a consequence, there is usually a strong effect of brood size manipulation on offspring growth and thereby presumably their fitness prospects. In the simulations (Fig.4), the consequences of the survival costs of reproduction for optimal clutch size were investigated without considering brood size manipulation effects on the offspring. Effects on offspring are briefly acknowledged in the discussion, but otherwise ignored. Assuming that the survival costs of reproduction are indeed difficult to discern because the offspring bear the brunt of the increase in brood size, a simulation that ignores the latter effect is unlikely to yield any insight in optimal clutch size. It is not clear therefore what we learn from these calculations.

There are other reasons why brood size manipulations may not reveal the costs of reproduction animals would incur when opting for a larger brood size than they produced spontaneously themselves. Firstly, the manipulations do not affect the effort incurred in laying eggs (which also biases your comparison with natural variation in clutch size). Secondly, the studies by Boonekamp et al on Jackdaws found that while there was no effect of brood size manipulation on parental survival after one year of manipulation, there was a strong effect when the same individuals were manipulated in the same direction in multiple years. This could be taken to mean that costs are not immediate but delayed, explaining why single year manipulations generally show little effect on survival. It would also mean that most estimates of the fitness costs of manipulated brood size are not fit for purpose, because typically restricted to survival over a single year.

Details of how the analyses were carried out were opaque in places, but as I understood the analysis of the brood size manipulation studies, manipulation was coded as a covariate, with negative values for brood size reductions and positive values for brood size enlargements (and then variably scaled or not to control brood or clutch size). This approach implicitly assumes that the trade-off between current brood size (manipulation) and parental survival is linear, which contrasts with the general expectation that this trade-off is not linear. This assumption reduces the value of the analysis, and contrasts with the approach of Santos & Nakagawa.

The observational study selection is not complete and apparently no attempt was made to make it complete. This is a missed opportunity - it would be interesting to learn more about interspecific variation in the association between natural variation in clutch size and parental survival.

Reviewer #2 (Public Review):

I have read with great interest the manuscript entitled "The optimal clutch size revisited: separating individual quality from the costs of reproduction" by LA Winder and colleagues. The paper consists in a meta-analysis comparing survival rates from studies providing clutch sizes of species that are unmanipulated and from studies where the clutch sizes are manipulated, in order to better understand the effects of differences in individual quality and of the costs of reproduction. I find the idea of the manuscript very interesting. However, I am not sure the methodology used allows to reach the conclusions provided by the authors (mainly that there is no cost of reproduction, and that the entire variation in clutch size among individuals of a population is driven by "individual quality").

I write that I am not sure, because in its current form, the manuscript does not contain a single equation, making it impossible to assess. It would need at least a set of mathematical descriptions for the statistical analysis and for the mechanistic model that the authors infer from it.<br /> The texts mixes concepts of individual vs population statistics, of within individual vs among-individuals measures, of allocation trade-offs and fitness trade-offs, etc ....which means it would also require a glossary of the definitions the authors use for these various terms, in order to be evaluated.

This problem is emphasised by the following sentence to be found in the discussion "The effect of birds having naturally larger clutches was significantly opposite to the result of increasing clutch size through brood manipulation". The "effect" is defined as the survival rate (see Fig 1). While it is relatively easy to intuitively understand what the "effect" is for the unmanipulated studies: the sensitivity of survival to clutch size at the population level, this should be mentioned and detailed in a formula. Moreover, the concept of effect size is not at all obvious for the manipulated ones (effect of the manipulation? or survival rate whatever the manipulation (then how could it measure a trade-off ?)? at the population level? at the individual level ?) despite a whole appendix dedicated to it. This absolutely needs to be described properly in the manuscript.

Despite the lack of information about the underlying mechanistic model tested and the statistical model used, my impression is still that the interpretation in the introduction and discussion is not granted by the outputs of the figures and tables. Let's use a model similar to that of (van Noordwijk and de Jong, 1986): imagine that the mechanism at the population level is<br /> a.c_(i,q)+b.s_(i,q)=E_q<br /> Where c_(i,q) are s_(i,q) are respectively the clutch size for individual i which is of quality q, and E_q is the level of "energy" that an individual of quality q has available during the given time-step (and a and b are constants turning the clutch size and survival rate into energy cost of reproduction and energy cost of survival, and there are both quite "high" so that an extra egg (c_(i,q) is increased by 1) at the current time-step, decreases s_(i,q) markedly (E_q is independent of the number of eggs produced), that is, we have strong individual costs of reproduction). Imagine now that the variance of c_(i,q) (when the population is not manipulated) among individuals of the same quality group, is very small (and therefore the variance of s_(i,q) is very small also) and that the expectation of both are proportional to E_q. Then, in the unmanipulated population, the variance in clutch size is mainly due to the variance in quality. And therefore, the larger the clutch size c_(i,q) the higher E_q, and the higher the survival s_(i,q).<br /> In the manipulated populations however, because of the large a and b, an artificial increase in clutch size, for a given E_q, will lead to a lower survival s_(i,q). And the "effect size" at the population level may vary according to a,b and the variances mentioned above. In other words, the costs of reproduction may be strong, but be hidden by the data, when there is variance in quality; however there are actually strong costs of reproduction (so strong actually that they are deterministic and that the probability to survive is a direct function of the number of eggs produced)

Moreover, it seems to me that the costs of reproduction are a concept closely related to generation time. Looking beyond the individual allocative (and other individual components of the trade-off) cost of reproduction and towards a populational negative relationship between survival and reproduction, we have to consider the intra-population slow fast continuum (some types of individuals survive more and reproduce less (are slower) than other (which are faster)). This continuum is associated with a metric: the generation time. Some individuals will produce more eggs and survive less in a given time-period because this time-period corresponds to a higher ratio of their generation time (Gaillard and Yoccoz, 2003; Gaillard et al., 2005). It seems therefore important to me, to control for generation time and in general to account for the time-step used for each population studied when analysing costs of reproduction. The data used in this manuscript is not just clutch size and survival rates, but clutch size per year (or another time step) and annual (or other) survival rates.

Finally, it is important to relate any study of the costs of reproduction in a context of individual heterogeneity (in quality for instance), to the general problem of the detection of effects of individual differences on survival (see, e.g., Fay et al., 2021). Without an understanding of the very particular statistical behaviour of survival, associated to an event that by definition occurs only once per life history trajectory (by contrast to many other traits, even demographic, where the corresponding event (production of eggs for reproduction, for example) can be measured several times for a given individual during its life history trajectory).

References:<br /> Fay, R. et al. (2021) 'Quantifying fixed individual heterogeneity in demographic parameters: Performance of correlated random effects for Bernoulli variables', Methods in Ecology and Evolution, 2021(August), pp. 1-14. doi: 10.1111/2041-210x.13728.<br /> Gaillard, J.-M. et al. (2005) 'Generation time: a reliable metric to measure life-history variation among mammalian populations.', The American naturalist, 166(1), pp. 119-123; discussion 124-128. doi: 10.1086/430330.<br /> Gaillard, J.-M. and Yoccoz, N. G. (2003) 'Temporal Variation in Survival of Mammals: a Case of Environmental Canalization?', Ecology, 84(12), pp. 3294-3306. doi: 10.1890/02-0409.<br /> van Noordwijk, A. J. and de Jong, G. (1986) 'Acquisition and Allocation of Resources: Their Influence on Variation in Life History Tactics', American Naturalist, p. 137. doi: 10.1086/284547.

Reviewer #1 (Public Review):

The authors present a scRNAseq study describing the transcriptomes of the tendon enthesis during postnatal development. This is an important topic that has major implication for the care of common clinical problems such as rotator cuff repair. The results are a valuable addition to the literature, providing a descriptive data set reinforcing other, more comprehensive studies. There are weaknesses, however, in the scRNAseq analyses.

1.The authors should provide additional rationale for the PCA analysis shown in Fig 1d. It is uncommon to use PCA for histomorphologic parameters. These results do not convincingly demonstrate that P7 is as a critical developmental timepoint.

2. According to the methods, it appears that the entire humeral head-supraspinatus tendon was used for cell isolation for scRNAseq. This results in the inclusion of cells from a variety of tissues, including bone, growth plate, enthesis and tendon. As such, only a very small percentage of cells in the analysis came from the enthesis. Inclusion of such a wide range of cells makes interpretation of enthesis cells difficult.

3. The differentiation/pseudotime analysis described in Fig 3 is difficult to follow. This map includes cell transcriptomes from vastly different tissues. Presumably, embedded in these maps are trajectories for osteoblast differentiation, chondrocyte differentiation, tenocyte differentiation, etc. With so many layers of overlapping information, it is difficult to (algorithmically) deduce a differentiation path of a particular cell type.

4. The authors uses the term "function" throughout the paper (e.g., "functional definition of fibrocartilage subpopulations"). However, this is a descriptive scRNAseq study, and "function" can therefore only theoretically be inferred from the algorithms used to analyze the data. A functional role for any of the identified pathways or processes can only be defined with gain- and/or loss-of-function studies.

5. "C2 highly expressed biomineralization-related genes (Clec3a, Tnn, Acan)". The three example genes are not related to biomineralization.

6. The functional characterization of the three enthesis cell clusters is not convincing. For example, activation of metabolism-related processes can mean a lot of things (including changes in differentiation), yet the authors interpret it very specifically as "role in postnatal fibrochondrocyte formation and growth".

7. The pseudotime analysis of the enthesis cell clusters is not convincing. The three clusters are quite close and overlapping on the UMAP. Furthermore, the authors focus on Tnn as a novel and unique gene, yet the expression pattern shown in Fig 5g implies even expression of this gene across all three clusters.

8. The TC1 markers (Ly6a, Dlk3, Clec3b) imply a non-tendon-specific cell population. Perhaps a tendon progenitor pool or an endothelial cell phenotype is more appropriate.

9. Pseudotime analyses assume that your data set includes cells from progenitor through mature cell populations. It is unclear that the timepoints studied here included cells from early progenitor states.

10. The CellChat analysis is difficult to follow, as the authors included 18 cell types. The number of possible interactions among so many cell types is enormous, and deducing valid connections between any two cell types in this case should be justified. Is the algorithm robust to so many possible interactions?

Reviewer #2 (Public Review):

To reveals cellular and molecular heterogeneity in enthesis, the authors established a single-cell temporal atlas during development. This study provides a transcriptional resource for further investigation of fibrocartilage development.

Reviewer #2 (Recommendations for the authors):

1. As known, Fei Fang et al. have established single-cell transcriptomes of mouse supraspinatus tendon enthesis cells (Cell Stem Cell, 2022). It is suggested that the authors introduced Fei Fang et al.'s work in Introduction and emphasize the significant novelty compared with Fei Fang et al.'s work.<br /> 2. In Fig1, the authors highlighted P7 was a critical stage for enthesis differentiation. But this section was less associated with the following content. The authors should link these results with the scRNASeq data. Is there any time-dependent change/signaling in scRNASeq data at this critical time point?<br /> 3. In the H&E staining of Fig1a, the tendon structure was separated and random. It is suggested that the authors provide high-quality staining figures.<br /> 4. Fig2 showed that the Scx+ or Sox9+ cells was decreased in enthesis over time. At least it should be co-staining to show the distribution and frequency of double positive and single positive cell populations. However, a previous study has demonstrated this finding (PLOS ONE, 2020). It is suggested to verify some new findings by IF or IHC staining.<br /> 5. There are some conflicts about trajectory analysis. In Fig3c, RNA velocity showed that the arrow flowed from BTJ to MTJ and CTFb. However, in Fig3d, PAGA plot indicated that BTJ cells is independent of other cells. Furthermore, in supplementary figure S3, RNA velocity showed that the trajectory flowed from TC to BTJ. These figures were inconsistent with the described results. Please provide detailed explanation to avoid misleading readers.<br /> 6. Fig5 showed that C1 was the original cluster, and whether C1 cluster expressed canonical progenic/stem cell markers.<br /> 7. The authors performed cell-cell interaction based on cellchat analysis. But the cell-cell interaction was not actively examined.

Reviewer #3 (Public Review):

This manuscript describes the use of scRNA-seq to decipher the cellular heterogeneity, molecular dynamics and signaling interactions during fibrocartilaginous enthesis formation. They delineate the enthesis growth and the temporal atlas from embryonic stage to postnatal stage by scRNA-seq, compared the development pattern of enthesis origins with tendon and articular cartilage, then demonstrated the cellular complexity and heterogeneity of postnatal enthesis growth and revealed the molecular dynamics and signaling networks during enthesis formation.

This manuscript used appropriate and validated methodology in line with current state-of-the-art, and the conclusions of this paper are mostly well supported by data, more in vitro or in vivo experiments are encouraged to verify the key molecular dynamics and signaling networks revealed by scRNA-seq during enthesis formation.

This manuscript facilitates better understand of the enthesis development, which will benefit the important field of enthesis research.

Reviewer #1 (Public Review):

This study examines the factors underlying the assembly of MreB, an actin family member involved in mediating longitudinal cell wall synthesis in rod-shaped bacteria. Required for maintaining rod shape and essential for growth in model bacteria, single molecule work indicates that MreB forms treadmilling polymers that guide the synthesis of new peptidoglycan along the longitudinal cell wall. MreB has proven difficult to work with and the field is littered with artifacts. In vitro analysis of MreB assembly dynamics has not fared much better as helpfully detailed in the introduction to this study. In contrast to its distant relative actin, MreB is difficult to purify and requires very specific conditions to polymerize that differ between groups of bacteria. Currently, in vitro analysis of MreB and related proteins has been mostly limited to MreBs from Gram-negative bacteria which have different properties and behaviors from related proteins in Gram-positive organisms.

Here, Mao and colleagues use a range of techniques to purify MreB from the Gram-positive organism Geobacillus stearothermophilus, identify factors required for its assembly, and analyze the structure of MreB polymers. Notably, they identify two short hydrophobic sequences-located near one another on the 3-D structure-which are required to mediate membrane anchoring.

With regard to assembly dynamics, the authors find that Geobacillus MreB assembly requires both interactions with membrane lipids and nucleotide binding. Nucleotide hydrolysis is required for interaction with the membrane and interaction with lipids triggers polymerization. These experiments appear to be conducted in a rigorous manner, although the salt concentration of the buffer (500mM KCl) is quite high relative to that used for in vitro analysis of MreBs from other organisms. The authors should elaborate on their decision to use such a high salt buffer, and ideally, provide insight into how it might impact their findings relative to previous work.

Additionally, this study, like many others on MreB, makes much of MreB's relationship to actin. This leads to confusion and the use of unhelpful comparisons. For example, MreB filaments are not actin-like (line 58) any more than any polymer is "actin-like." As evidenced by the very beautiful images in this manuscript, MreB forms straight protofilaments that assemble into parallel arrays, not the paired-twisted polymers that are characteristic of F-actin. Generally, I would argue that work on MreB has been hindered by rather than benefitted from its relationship to actin (E.g early FP fusion data interpreted as evidence for an MreB endoskeleton supporting cell shape or depletion experiments implicating MreB in chromosome segregation) and thus such comparisons should be avoided unless absolutely necessary.

Reviewer #2 (Public Review):

The paper "Polymerization cycle of actin homolog MreB from a Gram-positive bacterium" by Mao et al. provides the second biochemical study of a gram-positive MreB, but importantly, the first study examines how gram-positive MreB filaments bind to membranes. They also show the first crystal structure of a MreB from a Gram-positive bacterium - in two nucleotide-bound forms, finally solving structures that have been missing for too long. They also elucidate what residues in Geobacillus MreB are required for membrane associations. Also, the QCM-D approach to monitoring MreB membrane associations is a direct and elegant assay.

While the above findings are novel and important, this paper also makes a series of conclusions that run counter to multiple in vitro studies of MreBs from different organisms and other polymers with the actin fold. Overall, they propose that Geobacillus MreB contains biochemical properties that are quite different than not only the other MreBs examined so far but also eukaryotic actin and every actin homolog that has been characterized in vitro. As the conclusions proposed here would place the biochemical properties of Geobacillus MreB as the sole exception to all other actin fold polymers, further supporting experiments are needed to bolster these contrasting conclusions and their overall model.

1. (Difference 1) - The predominant concern about the in vitro studies that makes it difficult to evaluate many of their results (much less compare them to other MreB/s and actin homologs) is the use of a highly unconventional polymerization buffer containing 500(!) mM KCL. As has been demonstrated with actin and other polymers, the high KCl concentration used here (500mM) is certain to affect the polymerization equilibria, as increasing salt increases the hydrophobic effect and inhibits salt bridges, and therefore will affect the affinity between monomers and filaments. For example, past work has shown that high salt greatly changes actin polymerization, causing: a decreased critical concentration, increased bundling, and a greatly increased filament stiffness(Kang et al., 2013, 2012). Similarly, with AlfA, increased salt concentrations have been shown to increase the critical concentration, decrease the polymerization kinetics, and inhibit the bundling of AlfA filaments (Polka et al., 2009). A more closely related example comes from the previous observation that increasing salt concentrations increasingly slow the polymerization kinetics of B. subtilis MreB (Mayer and Amann, 2009). Lastly, These high salt concentrations might also change the interactions of MreB(Gs) with the membrane by screening charges and/or increasing the hydrophobic effect.

Given that 500mM KCl was used throughout this paper, many (if not all) of the key experiments should be repeated in more standard salt concentration (~100mM), similar to those used in most previous in vitro studies of polymers. This would test if the many divergent properties of MreB(Gs) reported here arise from some difference in MreB(Gs) relative to other MreBs (and actin homologs), or if they arise from the 400mM difference in salt concentration between the studies. Critically, it would also allow direct comparisons to be made relative to previous studies of MreB (and other actin homologs) that used much lower salt, thereby allowing them to definitively demonstrate whether MreB(Gs) is indeed an outlier relative to other MreB and actin homologs. I would suggest using 100mM KCL, as historically, all polymerization assays of actin and numerous actin homologs have used 50-100mM KCL: 50mM KCl (for actin in F buffer) or 100mM KCl for multiple prokaryotic actin homologs and MreB (Deng et al., 2016; Ent et al., 2014; Esue et al., 2006, 2005; Garner et al., 2004; Polka et al., 2009; Rivera et al., 2011; Salje et al., 2011) Likewise, similar salt concentrations are standard for tubulin (80 mM K-Pipes) and FtsZ (100 mM KCl or 100mM KAc in HMK100 buffer).

2. (Difference 2) - One of the most important differences claimed in this paper is that MreB(Gs) filaments are straight, a result that runs counter to the curved T. Maritima and C. crescentus filaments detailed by the Löwe group (Ent et al., 2014; Salje et al., 2011). Importantly, this difference could also arise from the difference in salt concentrations used in each study (500mM here vs. 100mM in the Löwe studies), and thus one cannot currently draw any direct comparisons between the two studies.

One example of how high salt could be causing differences in filament geometry: high salts are known to greatly increase the bending stiffness of actin filaments, making them more rigid (Kang et al., 2013). Likewise, increasing salt is known to change the rigidity of membranes. As the ability of filaments to A) bend the membrane or B) Deform to the membrane depends on the stiffness of filaments relative to the stiffness of the membrane, the observed difference in the "straight vs. curved" conformation of MreB filaments might simply arise from different salt concentrations.

Thus, in order to draw several direct comparisons between their findings and those of other MreB orthologs (as done here), the studies of MreB(GS) confirmations on lipids should be repeated at the same buffer conditions as used in the Löwe papers, then allowing them to be directly compared.

3. (Difference 3) - The next important difference between MreB(Gs) and other MreBs is the claim that MreB polymers do not form in the absence of membranes.

A) This is surprising relative to other MreBs, as MreBs from 1) T. maritime (multiple studies), E.coli (Nurse and Marians, 2013), and C. crescentus (Ent et al., 2014) have been shown to form polymers in solution (without lipids) with electron microscopy, light scattering, and time-resolved multi-angle light scattering. Notably, the Esue work was able to observe the first phase of polymer formation and a subsequent phase of polymer bundling (Esue et al., 2006) of MreB in solution. 2) Similarly, (Mayer and Amann, 2009) demonstrated B. subtilis MreB forms polymers in the absence of membranes using light scattering.

B) The results shown in figure 5A also go against this conclusion, as there is only a 2-fold increase in the phosphate release from MreB(Gs) in the presence of membranes relative to the absence of membranes. Thus, if their model is correct, and MreB(Gs) polymers form only on membranes, this would require the unpolymerized MreB monomers to hydrolyze ATP at 1/2 the rate of MreB in filaments. This high relative rate of hydrolysis of monomers compared to filaments is unprecedented. For all polymers examined so far, the rate of monomer hydrolysis is several orders of magnitude less than that of the filament. For example, actin monomers are known to hydrolyze ATP 430,000X slower than the monomers inside filaments (Blanchoin and Pollard, 2002; Rould et al., 2006).

C) Thus, there is a strong possibility that MreB(Gs) polymers are indeed forming in solution in addition to those on the membrane, and these "solution polymers" may not be captured by their electron microscopy assay. For example, high salt could be interfering with the absorption of filaments to glow discharged lacking lipids.<br /> In order to definitively prove that MreB(Gs) does not have polymers in solution, the authors should:

i) conduct orthogonal experiments to test for polymers in solution. The simplest test of polymerization might be conducting pelleting assays of MreB(Gs) with and without lipids, sweeping through the concentration range as done in 2B and 5a.

ii) They also could examine if they see MreB filaments in the absence of lipids at 100mM salt (as was seen in both Löwe studies), as the high salt used here might block the charges on glow discharged grids, making it difficult for the polymer to adhere.

iii) Likewise, the claim that MreB lacking the amino-terminus and the α2β7 hydrophobic loop "is required for polymerization" is questionable as if deleting these resides blocks membrane binding, the lack of polymers on the membrane on the grid is not unexpected, as these filaments that cannot bind the membrane would not be observable. Given these mutants cannot bind the membrane, mutant polymers could still indeed exist in solution, and thus pelleting assays should be used to test if non-membrane associated filaments composed of these mutants do or do not exist.

A final note, the results shown in "Figure 1 - figure supplement 2, panel C" appear to directly refute the claim that MreB(Gs) requires lipids to polymerize. As currently written, it appears they can observe MreB(Gs) filaments on EM grids without lipids. If these experiments were done in the presence of lipids, the figure legend should be updated to indicate that. If these experiments were done in the absence of lipids, the claim that membrane association is required for MreB polymerizations should be revised.

4. (Difference 4) - The next difference between this study and previous studies of MreB and actin homologs is the conclusion that MreB(Gs) must hydrolyze ATP in order to polymerize. This conclusion is surprising, given the fact that both T. Maritima (Salje · 2011, Bean 2008) and B. subtilis MreB (Mayer 2009) have been shown to polymerize in the presence of ATP as well as AMP-PNP. Likewise, MreB polymerization has been shown to lag ATP hydrolysis in not only T. maritima MreB (Esue 2005), eukaryotic actin, and all other prokaryotic actin homologs whose polymerization and phosphate release have been directly compared: MamK (Deng et al., 2016), AlfA (Polka et al., 2009), and two divergent ParM homologs (Garner et al., 2004; Rivera et al., 2011).

Currently, the only piece of evidence supporting the idea that MreB(Gs) must hydrolyze ATP in order to polymerize comes from 2 observations: 1) using electron microscopy, they cannot see filaments of MreB(Gs) on membranes in the presence of AMP-PNP or ApCpp, and 2) no appreciable signal increase appears testing AMPPNP- MreB(Gs) using QCM-D. This evidence is by no means conclusive enough to support this bold claim: While their competition experiment does indicate AMPPNP binds to MreB(Gs), it is possible that MreB(Gs) cannot polymerize when bound to AMPPNP. For example, it has been shown that different actin homologs respond differently to different non-hydrolysable analogs: Some, like actin, can hydrolyze one ATP analog but not the other, while others are able to bind to many different ATP analogs but only polymerize with some of one of them. Thus, to further verify their "hydrolysis is needed for polymerization" conclusion, they should:<br /> A. Test if a hydrolysis deficient MreB(Gs) mutant (such as D158A) is also unable to polymerize by EM.<br /> B. They also should conduct an orthogonal assay of MreB polymerization aside from EM (pelleting assays might be the easiest). They should test if polymers of ATP, AMP-PNP, and MreB(Gs)(D158A) form in solution (without membranes) by conducting pelleting assays. These could also be conducted with and without lipids, thereby also addressing the points noted above in point 3.<br /> C. Polymers may indeed form with ATP-gamma-S, and this non-hydrolysable ATP analog should be tested.<br /> D. They could also test how the ADP-Phosphate bound MreB(Gs) polymerizes in bulk and on membranes, using beryllium phosphate to trap MreB in the ADP-Pi state. This might allow them to further refine their model.<br /> E. Importantly, the Mayer study of B. subtilis MreB found the same results in regard to nucleotides, "In polymerization buffer, MreB produced phosphate in the presence of ATP and GTP, but not in ADP, AMP, GDP or AMP-PNP, or without the readdition of any nucleotide". Thus this paper should be referenced and discussed

5. (Difference 5) - The introduction states (lines 128-130) "However, the need for nucleotide binding and hydrolysis in polymerization remains unclear due to conflicting results, in vivo and in vitro, including the ability of MreB to polymerize or not in the presence of ADP or the non-hydrolyzable ATP analog AMP-PNP."

A) While this is a great way to introduce the problem, the statement is a bit vague and should be clarified, detaining the conflicting results and appropriate references. For example, what conflicting in vivo results are they referring to? Regarding "MreB polymerization in AMP-PNP", multiple groups have shown the polymerization of MreB(Tm) in the presence of AMP-PNP, but it is not clear what papers found opposing results.

B) The statement "However, the need for nucleotide binding and hydrolysis in polymerization remains unclear due to conflicting results, in vivo and in vitro, including the ability of MreB to polymerize or not in the presence of ADP or the non-hydrolyzable ATP analog AMP-PNP" is technically incorrect and should be rephrased or further tested.

i. For all actin (or tubulin) family proteins, it is not that a given filament "cannot polymerize" in the presence of ADP but rather that the ADP-bound form has a higher critical concentration for polymer formation relative to the ATP-bound form. This means that the ADP polymers can indeed polymerize, but only when the total protein exceeds the ADP critical concentration. For example, many actin-family proteins do indeed polymerize in ADP: ADP actin has a 10-fold higher critical concentration than ATP actin, (Pollard, 1984) and the ADP critical concentrations of AlfA and ParM are 5X and 50X fold higher (respectively) than their ATP-bound forms(Garner et al., 2004; Polka et al., 2009)

ii. Likewise, (Mayer and Amann, 2009) have already demonstrated that B. subtilis MreB can polymerize in the presence of ADP, with a slightly higher critical concentration relative to the ATP-bound form.

Thus, to prove that MreB(Gs) polymers do not form in the presence of ADP would require one to test a large concentration range of ADP-bound MreB(Gs). They should test if ADP- MreB(Gs) polymerizes at the highest MreB(Gs) concentrations that can be assayed. Even if this fails, it may be the MreB(Gs) ADP polymerizes at higher concentrations than is possible with their protein preps (13uM). An even more simple fix would be to simply state MreB(Gs)-ADP filaments do not form beneath a given MreB(Gs) concentration.

Other Points to address:

1. There are several points in this paper where the work by Mayer and Amann is ignored, not cited, or readily dismissed as "hampered by aggregation" without any explanation or supporting evidence of that fact.

A) Lines 100-101 - While the irregular 3-D formations seen formed by MreB in the Dersch 2020 paper could be interpreted as aggregates, stating that the results from specifically the Gaballah and Meyer papers (and not others) were "hampered by aggregation" is currently an arbitrary statement, with no evidence or backing provided. Overall, these lines (and others in the paper) dismiss these two works without giving any evidence to that point. Thus, they should provide evidence for why they believe all these papers are aggregation, or remove these (and other) dismissive statements.

One important note - There are 2 points indicating that dismissing the Meyer and Amann work as aggregation is incorrect: 1) the Meyer work on B. subtilis MreB shows both an ATP and a slightly higher ADP critical concentration. As the emergence of a critical concentration is a steady-state phenomenon arising from the association/dissociation of monomers (and a kinetically limiting nucleation barrier), an emergent critical concentration cannot arise from protein aggregation, critical concentrations only arise from a dynamic equilibrium between monomer and polymer. 2) Furthermore, Meyer observed that increased salt slowed and reduced B. subtilis MreB light scattering, the opposite of what one would expect if their "polymerization signal" was only protein aggregation, as higher salts should increase the rate of aggregation by increasing the hydrophobic effect.

B) Lines 113-137 -The authors reference many different studies of MreB, including both MreB on membranes and MreB polymerized in solution (which formed bundles). However, they again neglect to mention or reference the findings of Meyer and Amann (Mayer and Amann, 2009), as it was dismissed as "aggregation". As B. subtilis is also a gram-positive organism, the Meyer results should be discussed.

2. Lines 387-391 state the rates of phosphate release relative to past MreB findings: "These rates of Pi release upon ATP hydrolysis (~ 1 Pi/MreB in 6 min at 53{degree sign}C) are comparable to those observed for MreBTm and MreB(Ec) in vitro". While the measurements of Pi release AND ATP hydrolysis have indeed been measured for actin, this statement does not apply to MreB and should be corrected: All MreB papers thus far have only measured Pi release alone, not ATP hydrolysis at the same time. Thus, it is inaccurate to state "rates of Pi release upon ATP hydrolysis" for any MreB study, as to accurately determine the rate of Pi release, one must measure: 1. The rate of polymer over time, 2) the rate of ATP hydrolysis, and 3) the rate of phosphate release. For MreB, no one has, so far, even measured the rates of ATP hydrolysis and phosphate release with the same sample.

3. The interpretation of the interactions between monomers in the MreB crystal should be more carefully stated to avoid confusion. While likely not their intention, the discussions of the crystal packing contacts of MreB can appear to assume that the monomer-monomer contacts they see in crystals represent the contacts within actual protofilaments. One cannot automatically assume the observations of monomer-monomer contacts within a crystal reflect those that arise in the actual filament (or protofilament).

A) They state, "the apo form of MreBGs forms less stable protofilaments than its G- homologs ." Given filaments of the Apo form of MreB(GS) or b. subtilis have never been observed in solution, this statement is not accurate: while the contacts in the crystal may change with and without nucleotide, if the protein does not form polymers in solution in the apo state, then there are no "real" apo protofilaments, and any statements about their stability become moot. Thus this statement should be rephrased or appropriately qualified.

B) Another example: while they may see that in the apo MreB crystal, the loop of domain IB makes a *single* salt bridge with IIA and none with IIB. This contrasts with every actin, MreB, and actin homolog studied so far, where domain IB interacts with IIB. This might reflect the real contacts of MreB(Gs) in the solution, or it may be simply a crystal-packing artifact. Thus, the authors should be careful in their claims, making it clear to the reader that the contacts in the crystal may not necessarily be present in polymerized filaments.

4. lines 201-202 - "Polymers were only observed at a concentration of MreB above 0.55 μM (0.02 mg/mL)". Given this concentration dependence of filament formation, which appears the same throughout the paper, the authors could state that 0.55 μM is the critical concentration of MreB on membranes under their buffer conditions. Given the lack of critical concentration measurement in most of the MreB literature, this could be an important point to make in the field.

5. Both mg/ml and uM are used in the text and figures to refer to protein concentration. They should stick to one convention, preferably uM, as is standard in the polymer field.

6. Lines 77-78 - (Teeffelen et al., 2011) should be referenced as well in regard to cell wall synthesis driving MreB motion.

7. Line 90 - "Do they exhibit turnover (treadmill) like actin filaments?". This phrase should be modified, as turnover and treadmilling are two very different things. Turnover is the lifetime of monomers in filaments, while treadmilling entails monomer addition at one end and loss at the other. While treadmilling filaments cause turnover, there are also numerous examples of non-treadmilling filaments undergoing turnover: microtubules, intermediate filaments, and ParM. Likewise, an antiparallel filament cannot directionally treadmill, as there is no difference between the two filament ends to confer directional polarity.

8. Throughout the paper, the term aggregation is used occasionally to describe the polymerization shown in many previous MreB studies, almost all of which very clearly showed "bundled" filaments, very distinct entities from aggregates, as a bundle of polymers cannot form without the filaments first polymerizing on their own. Evidence to this point, polymerization has been shown to precede the bundling of MreB(Tm) by (Esue et al., 2005).

9. lines 106-108 mention that "The N-terminal amphipathic helix of E. coli MreB (MreBEc) was found to be necessary for membrane binding. " This is not accurate, as Salje observed that one single helix could not cause MreB to mind to the membrane, but rather, multiple amphipathic helices were required for membrane association (Salje et al., 2011). The Salje results imply that dimers (or further assemblies) of MreB drive membrane association, a point that should be discussed in regard to the question "What prompts the assembly of MreB on the inner leaflet of the cytoplasmic membrane?" posed on lines 86-87.

10. On lines 414-415, it is stated, "The requirement of the membrane for polymerization is consistent with the observation that MreB polymeric assemblies in vivo are membrane-associated only." While I agree with this hypothesis, it must be noted that the presence or absence of MreB polymers in the cytoplasm has not been directly tested, as short filaments in the cytoplasm would diffuse very quickly, requiring very short exposures (<5ms) to resolve them relative to their rate of diffusion. Thus, cytoplasmic polymers might still exist but have not been tested.

11. lines 429-431 state, "but polymerization in the presence of ADP was in most cases concluded from light scattering experiments alone, so the possibility that aggregation rather than ordered polymerization occurred in the process cannot be excluded."

A) If an increased light scattering signal is initiated by the addition of ADP (or any nucleotide), that signal must come from polymerization or multimerization. What the authors imply is that there must be some ADP-dependent "aggregation" of MreB, which has not been seen thus far for any polymer. Furthermore, why would the addition of ADP initiate aggregation?

B) Likewise, the statement "Differences in the purity of the nucleotide stocks used in these studies could also explain some of the discrepancies" is unexplained and confusing. How could an impurity in a nucleotide stock affect the past MreB results, and what is the precedent for this claim?

12. lines 467-469 state, "Thus, for both MreB and actin, despite hydrolyzing ATP before and after polymerization, respectively, the ADP-Pi-MreB intermediate would be the long-lived intermediate state within the filaments."

A) For MreB, this statement is extremely speculative and unbiased, as no one has measured 1) polymerization, 2) ATP hydrolysis, and 3) phosphate release. For example, it could be that ATP hydrolysis is slow, while phosphate release is fast, as is seen in the actin from Saccharomyces cerevisiae.

B) For actin, the statement of hydrolysis of ATP of monomer occurring "before polymerization" is functionally irrelevant, as the rate of ATP hydrolysis of actin monomers is 430,000 times slower than that of actin monomers inside filaments(Blanchoin and Pollard, 2002; Rould et al., 2006).

13. Lines 442-444. "On the basis of our data and the existing literature, we propose that the requirement for ATP (or GTP) hydrolysis for polymerization may be conserved for most MreBs." Again, this statement both here (and in the prior text) is an extremely bold claim, one that runs contrary to a large amount of past work on not just MreB, but also eukaryotic actin and every actin homolog studied so far. They come to this model based on 1) one piece of suggestive data (the behavior of MreB(GS) bound to 2 non-hydrolysable ATP analogs in 500mM KCL), and 2) the dismissal (throughout the paper) of many peer-reviewed MreB papers that run counter to their model as "aggregation" or "contaminated ATP stocks ." If they want to make this bold claim that their finding invalidates the work of many labs, they must back it up with further validating experiments.

References cited.

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Dersch S, Reimold C, Stoll J, Breddermann H, Heimerl T, Soufo HJD, Graumann PL. 2020. Polymerization of Bacillus subtilis MreB on a lipid membrane reveals lateral co-polymerization of MreB paralogs and strong effects of cations on filament formation. Bmc Mol Cell Biology 21:76. doi:10.1186/s12860-020-00319-5

Ent F van den, Izoré T, Bharat TA, Johnson CM, Lowe J. 2014. Bacterial actin MreB forms antiparallel double filaments. eLife 3:e02634. doi:10.7554/elife.02634

Esue O, Cordero M, Wirtz D, Tseng Y. 2005. The Assembly of MreB, a Prokaryotic Homolog of Actin. J Biol Chem 280:2628-2635. doi:10.1074/jbc.m410298200

Esue O, Wirtz D, Tseng Y. 2006. GTPase Activity, Structure, and Mechanical Properties of Filaments Assembled from Bacterial Cytoskeleton Protein MreB. J Bacteriol 188:968-976. doi:10.1128/jb.188.3.968-976.2006

Garner EC, Campbell CS, Mullins RD. 2004. Dynamic instability in a DNA-segregating prokaryotic actin homolog. Science (New York, NY) 306:1021-1025. doi:10.1126/science.1101313

Kang H, Bradley MJ, Elam WA, De La Cruz EM. 2013. Regulation of Actin by Ion-Linked Equilibria. Biophys J 105:2621-2628. doi:10.1016/j.bpj.2013.10.032

Kang H, Bradley MJ, McCullough BR, Pierre A, Grintsevich EE, Reisler E, Cruz EMDL. 2012. Identification of cation-binding sites on actin that drive polymerization and modulate bending stiffness. Proc National Acad Sci 109:16923-16927. doi:10.1073/pnas.1211078109

Mayer JA, Amann KJ. 2009. Assembly properties of the Bacillus subtilis actin, MreB. Cell Motil Cytoskel 66:109-118. doi:10.1002/cm.20332

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Polka JK, Kollman JM, Agard DA, Mullins RD. 2009. The Structure and Assembly Dynamics of Plasmid Actin AlfA Imply a Novel Mechanism of DNA Segregation. J Bacteriol 191:6219-6230. doi:10.1128/jb.00676-09

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Reviewer #3 (Public Review):

The major claim from the paper is the dependence of two factors that determine the polymerization of MreB from a Gram-positive, thermophilic bacteria 1) The role of nucleotide hydrolysis in driving the polymerization. 2) Lipid bilayer as a facilitator/scaffold that is required for hydrolysis-dependent polymerization. These two conclusions are contrasting with what has been known until now for the MreB proteins that have been characterized in vitro. The experiments performed in the paper do not completely justify these claims as elaborated below.

Major comments:

1. No observation of filaments in the absence of lipid monolayer can also be accounted due to the higher critical concentration of polymerization for MreBGS in that condition. It is seen that all the negative staining without lipid monolayer condition has been performed at a concentration of 0.05 mg/mL. It is important to check for polymerization of the MreBGS at higher concentration ranges as well, in order to conclusively state the requirement of lipids for polymerization.

2. The absence of filaments for the non-hydrolysable conditions in the lipid layer could also be because the filaments that might have formed are not binding to the planar lipid layer, and not necessarily because of their inability to polymerize.

3. Given the ATPase activity measurements, it is not very convincing that ATP rather than ADP will be present in the structure. The ATP should have been hydrolysed to ADP within the structure. The structure is now suggestive that MreB is not capable of hydrolysis, which is contradictory to the ATP hydrolysis data.

Reviewer #1 (Public Review):

In this paper, the authors tried to elucidate specific neuronal microRNAs which play an important role in the assembly of hippocampal networks. Using expression screening, they narrowed down on the microRNA miR-218, which is abundantly expressed at early postnatal stages of hippocampal development. Using different loss-of-function tools (antisense oligonucleotides, conditional microRNA knockout mice), they found that miR-218 inhibition early in life leads to a higher susceptibility of mice to develop epileptic seizures, as well as subtle behavioural alterations. These phenotypes were accompanied by disruption of early depolarizing GABAergic signaling, structural defects in dendritic spines, and altered intrinsic membrane excitability. An important role for miR-218 specifically in GABAergic interneurons is supported by the use of mice with an interneuron-specific loss of miR-218. However, the authors do not directly address which of the cellular phenotypes is causally involved in seizure susceptibility and behavioural alterations. Moreover, the authors describe molecular changes in interneurons and pyramidal neurons which are resulting from miR-218 inhibition in the mouse hippocampus. However, the identity of molecular pathways downstream of miR-218 in the context of epileptic seizures and behaviour remains unexplored.

Altogether, this study has a potentially high impact on the field of neuronal microRNA research and more specifically neuronal circuit assembly. The methods will be of high relevance for the microRNA community studying microRNA function in the context of early neural circuit development in mice in vivo. From a clinical point of view, these results could also increase our knowledge about the mechanisms of epileptic seizure development.

Reviewer #2 (Public Review):

The current study by Taylor and colleagues investigated the role of microRNA-218 in hippocampal development and discover that disturbances in miR-218 during a key developmental window can lead to persistent changes in network excitability which could have implications for neurodevelopmental and neurological diseases. They found that miR-218 is developmentally regulated in the mouse hippocampus and resides in both excitatory pyramidal neurons and interneurons. Using antagomirs (inhibitors) specifically targeted to miR-218 they find that persistent inhibition of miR-218 elevates network activity and renders mice more susceptible to seizures when challenged with a chemoconvulsant. Additionally antagomir treated mice displayed altered cognitive processing when compared to control-treated mice. Taylor and colleagues then identified potential pathways and targets through which miR-218 may exert control over network formation and stabilisation and identified cell-type-specific targets through which it may function. Overall they find that the activity of miR-218 and its effects on network development may be mediated through its activity in interneurons.

The conclusions of this paper are mostly excellently supported by extensive and advanced experimentation.

The data on miR-218 is the least convincing element of the paper but there are inherent difficulties in assessing miR-mediated targeting which the authors may have encountered. Firstly the justification for performing gene ontology on genes with an FC of greater than 0 must be included. Similarly, the use of p values of less than 0.2 lacks stringency and authors should specify why these parameters were chosen. Otherwise, the gene ontology data is difficult to interpret. Protein data may add to this section also.

The authors state they do not analyse known developmental miRs such as miR-124. But the reasoning behind this is not explained. As known developmental miRNAs, analysing their expression would add confidence to the data. Furthermore, the statistical significance of Fig 1B is unclear.

Reviewer #1 (Public Review):

The authors design a peptide, PITCR, that is similar to the transmembrane domain of the TCR zeta, but is rendered soluble by adding an additionally charged residue to the TM domain and changing basic residues in the cytoplasmic juxtamembrane sequence to acidic residues. Some other bulky hydrophobic resides were made smaller. The strategy was based on earlier work with EphA2 sequences reported in elife in 2018. The TCRzeta conditional TM peptide was then tested for effects on T cell receptor signalling, co-localisation, and effects on TCR stability in biochemical assays. Significant effects were detected and these were eliminated by a strong helix-breaking mutation. There are currently some limitations with the interpretation of the signaling and co-localization studies. The results will be of interest to those studying the TCR as well as those seeking to use the TCR or its derivatives in synthetic biology studies and immunotherapy.

Reviewer #2 (Public Review):

The authors present findings on a designed peptide, PITCR, and its role in inhibiting TCR activation through an extensive series of experiments. These include the measurement of phosphorylation in the TCR zeta chain and a number of associated signaling proteins such as Zap70, LAT, PLCg1, and SLP76. In addition, the authors measure the impact of PITCR on the TCR intracellular calcium response and examine the peptide-induced inhibition of TCR activation by antigen-presenting cells. They also present data indicating that the fluorescently labeled PITCR co-localizes with TCR in Jurkat cells and with ligand-bound TCR in primary murine cells.

Overall the experiments provide useful insights into the mechanism of T cell activation and generally support an allosteric model of activation, while not necessarily excluding alternative models.

However, some aspects of the study do need clarification.

1) The authors do not provide a clear structural basis for their peptide design, which makes it difficult to understand the rationale for choosing this particular peptide. The use of a structural model based on the TCR zeta domain, for example, and how it becomes modified to generate PITCR would provide some clarity on what types of putative interactions are being engineered.

2) The inhibitory effects of PITCR are not large. Measurement of dose dependence might improve confidence in the results.

3) Use of control peptides is not uniform. Control peptides similar to PITCR in Figure 1 and Figure 2 studies, for example, could strengthen the authors' arguments.

Reviewer #3 (Public Review):

In this study, Ye et al investigated how a peptide that binds to the transmembrane (TM) domain of the T cell receptor (TCR) subunits affects TCR activation. The objective was to test the allosteric relaxation model of TCR activation. To this end, the authors leveraged their previously established strategy of designing TM-targeting peptides and studied how such peptide alters the TCR activation and downstream signaling cascades in Jurkat T cells. The authors found that the TM-targeting peptide inhibited phosphorylation of the TCR submits, phosphorylation of downstream signaling proteins such as ZAP70, and calcium influx in T cells. Using immunoprecipitation experiments, the authors proposed that the peptide binds into the membrane gap between CD3 and CD3 subunits in the TCR complex. The authors conclude that their data support the allosteric TCR activation model, in which allosteric changes in the TM bundle in the TCR complex determine the receptor signaling.

The use of pH-responsive TM-targeting peptides, which the authors previously developed, is a novel aspect of this study. Those peptides can be quite powerful for understanding molecular mechanisms of receptor signaling, such as the allosteric activation model as tested in this study. The manuscript contains several interesting approaches and observations, but there are concerns about the experimental design and interpretation of the results. More importantly, the authors' primary conclusion that the allosteric changes in the TM bundles determine TCR activation is not fully supported by the data presented. For example:

1. The authors provided confocal fluorescence images showing the colocalization of fluorescently labeled peptides and TCR subunits. Based on the data, they concluded that "PITCR is able to bind to TCR". This is misleading, because given the spatial resolution of the imaging technique, "colocalization" does not indicate binding or interaction between molecules. Because the peptide binding to the TM region is the pillar of the primary finding of this study, direct evidence supporting the peptide-TM binding or interaction is essential.<br /> 2. In calcium response experiments, the authors compared calcium influx (indicated by Indo-1 ratio) under different cell activation conditions (Figure 2). There are some concerns about how the authors interpreted the data: (1) The calcium plots from OKT3 activation in A-C panels are inconsistent. The plot in (A) showed a calcium peak after activation, which is not present in the plots shown in (B) and (C). There is no explanation or discussion on this inconsistency. (2) What is more concerning is that this prominent calcium peak in (A) was used to draw the conclusion that the designer peptide inhibitor effectively reduces calcium response. However, inconsistent with that conclusion, the calcium plots are indistinguishable for the three conditions: with PITCR (peptide inhibitor), with PITCRG41P (negative control that should not affect TCR activation), or no peptide. All three plots have similar magnetite and fluctuations. This does not support the authors' conclusion that the PITCR (peptide inhibitor) reduces calcium response in T cells.<br /> 3. Different types of T cells were used for separate measurements: E6-1 Jurkat T cells were used for calcium influx experiments, J. OT.hCD8+ Jurkat cells were used for CD69 measurements, and primary murine CD4+ T cells were used for colocalization imaging experiments. Rationales for the choices of cells in different measurements are also unclear. This is different from the common practice where different cell types are used in repeated experiments to test the generality of a finding. Here, they were used for different experiments, and findings were lumped together as "T cells", without further evidence/discussion on how translatable the findings from different cell types are.<br /> 4. The authors set out to test the model that TCR activation by pMHC occurs through allosteric changes in the TM region, but in most experiments, they activated Jurkat T cells by anti-CD3 antibody, not by antigen peptides. The anti-CD3 antibody activates TCR signaling through clustering. It is unclear whether TCR activation by anti-CD3 leads to the same allosteric changes in the TM region as activation by pMHC.

As such, the main claim of the paper, namely that the designer peptide affects TCR signaling by disrupting the allosteric changes in the TM region, remains insufficiently supported by the data presented.

Reviewer #1 (Public Review):

This paper accomplishes the authors' goal of using two complementary CRISPR approaches to identify novel determinants of CTL killing in vitro. Through these screens, the authors identify two new genes, ILKAP and ICAM1, that both modulate CTL killing across different cancer cell types. The dissection of how different ICAM1 proteins (membrane-bound and secreted) was also performed in a rigorous fashion. The use of multiple unrelated cancer cell lines greatly increases the strength of the findings and potential future applicability. Major weaknesses of the manuscript first include how ILKAP is connected to the control of ICAM1, which is unclear from the data presented in the paper. Secondly, while the authors use many different mutational variants of ICAM1 to dissect its function, the specific role of each of these mutations is not well described. A rigorous examination of secreted ICAM1 on CTL killing is not presented, and since membrane-bound and secreted ICAM1 have opposing functions on CTL killing, the clinical relevance of modulating ICAM1 is unclear. Finally, the authors do not consider how ICAM1 may affect antigen-presenting cells and other myeloid cells in the tumor which are critical intermediaries in the antitumor immune response. Overall, once these points of weakness are addressed, this work is expected to have a high impact in the field, as it presents new targets outside the PD-L1 / PD-1 axis that may aid in CTL killing of tumors across multiple cancer types.

Reviewer #2 (Public Review):

Mattes et al. used a CRISPR screen to determine tumor-intrinsic factors modulating the efficacy of T cell-mediated cell lysis. For this purpose, colon carcinoma cell lines were modified with gain-of-function (CRISPRa) and loss-of-function (CRISPRi) sgRNA libraries. Modified colon cancer cells were subsequently exposed to antigen-specific tumor cell lysis by CD8+ cytotoxic T cells and surviving colon cancer cells were analyzed for over- and underrepresented genes. The screen replicated findings from previous studies showing the importance of IFNy, TNFa, and autophagy pathways for T cell-mediated lysis of cancer cells. In addition, the authors identified two genes involved in cell adhesion that modulate T cell-mediate cell lysis: ILKAP and ICAM1. Subsequently, the authors validate their findings in in-vitro experiments and show that a soluble form of ICAM1 is negatively affecting tumor cell lysis. Finally, they analyze publicly available gene expression data from cancer patient cohorts and show that high ICAM1 expression, in combination with high expression of genes associated with soluble ICAM1 generation, has a negative impact on patient survival. Beyond these findings, the CRISPR screening dataset from this study serves as a comprehensive resource for other researchers in the onco-immunology space.

The conclusions of this paper are well supported by data, but some aspects of the role of soluble ICAM1 in T cell-mediated tumor cell lysis and the limitations of the employed experimental system should be clarified and extended.

1. For their screening, the authors use an in-vitro model of antigen-specific tumor cell lysis based on expanded CMV-specific CD8+ T cells and CMV peptide-pulsed colon cancer cells. While this model allows for the efficient induction of cellular cytotoxicity by expanded primary T cells, it has one critical caveat: pulsing colon cancer cells with CMV peptide adds the antigen artificially to the MHC complex on the cell surface. Cell-intrinsic factors of antigen processing and presentation are not required for tumor cell recognition in this system. However, antigen processing and presentation pathways represent important targets of tumor evasion in cancer patients. Factors affecting these processes won't be detected in this study. To consider antigen processing and presentation as well, the authors could, for instance, have used an additional model with T cells containing a transgenic TCR specific for an antigen typically expressed on colon cancer cells (or another cancer cell line).

2. The authors demonstrate the negative impact of soluble ICAM1 on T cell-mediated cytotoxicity in their co-culture assay. However, they lack to provide evidence on how this is facilitated. One option, as the authors speculate in their discussion and cartoon, could be that soluble ICAM1 occupies LFA1 on T cells thereby preventing the binding of T cells to ICAM1 on the surface of tumor cells. To demonstrate that this is indeed the case, the authors could, for instance, have used microscopy and measured T cell and tumor cell interaction duration and frequency under conditions with and without soluble ICAM1 present.

3. Regarding the analysis of clinical relevance, the authors show that patients with high levels of ICAM1 expression in combination with high levels of protease expression have poor survival. The rationale behind this is that the proteases cleave ICAM1 off the membrane leading to high levels of soluble ICAM1 that then negatively affects T cell-mediate tumor cell lysis. To demonstrate that indeed the combination of both factors, ICAM1 expression, and protease expression, is responsible for poor survival, the authors should also have analyzed the impact of each of these factors alone on patient survival. If their hypothesis is true, the combination of high ICAM1 and protease expression should have a worse impact on survival than each factor alone.

Reviewer #1 (Public Review):

Blanch-Lombarte and colleagues demonstrated that the expression of certain inhibitory receptors (IRGs) on CD8 T cells is elevated in people living with HIV (PLWH) and they remain elevated despite years of viral suppression on antiretroviral therapy (ART). A comprehensive single-cell analysis by multiparametric flow cytometry demonstrated that TGIT+ CD8 T cells have a skewed phenotype following HIV infection. Blocking of TGIT partially restores the ability of CD8 T cells to produce CD107a but not the other functions.

Strengths of the current study include the comprehensive analysis of IRGs on CD8 T cells of a well-characterized group of individuals with and without HIV. Additionally, they have confirmed that blocking of TGIT should be evaluated further as a potential therapy for PLWH. The conclusions seem well justified from the presented data.

Weaknesses include the cross-sectional data and minor confusion stemming in part from the lack of clarity and rationale for some of the experiments.

Reviewer #2 (Public Review):

Antiretroviral therapy (ART) can control HIV replication and improve the quality of life for people living with HIV (PLWH); however, it does not cure infection, nor does it revert T cell exhaustion. Inhibitory receptor expression is a characteristic of CD8+ T cell exhaustion and a better understanding of the differences in receptor expression dynamics between healthy donors and PLWH on ART is of interest. In this comparative study, Blanch-Lombarte et al. use single-cell analysis of flow cytometric PBMC profiling to examine inhibitory receptor expression (IR) and functional markers in CD8+ T cells derived from PLWH on ART and healthy donors.

The authors first perform a mix of cross-sectional and longitudinal characterization of IR expression and memory differentiation markers in donors who are healthy controls, are in the early stages of HIV infection, PLWH on ART for ~ 2 years, and PLWH on ART for ~10 years. They conduct both supervised and unsupervised analyses of the phenotypic results. The authors use three experimental conditions (unstimulated, SEB stimulation, HIV Gag peptide pool stimulation) to perform cluster analyses. The longitudinal paired samples allow determination of the persistence of the alterations observed early after initiation of ART. The analyses show inverse correlations between frequencies of TIGIT+ and TIGIT+ TIM+ CD8 subsets and CD4 counts. However, findings for HIV-specific CD8 were different, with a selective reduction of TIGIT+ clusters whose functionality in terms of CD107 expression was recovered by anti-TIGIT blockade.

The authors conclude that TIGIT could be a therapeutic target to revive exhausted T cells (Tex) at all ART stages.

Strengths:<br /> - The study addressed relevant questions for the field.<br /> - The is a logical sequence of experiments and analyses.<br /> - The authors investigate interesting samples - longitudinal time points on ART several years apart are a significant asset.<br /> - Assessment of CD8 T cell populations as bulk unstimulated cells, broad stimulation with a superantigen (SEB), and HIV-specific responses (Gag peptide pool stimulation).<br /> - Complementary use of supervised and detailed unsupervised analyses of flow cytometry data.<br /> - The analyses are overall detailed and carefully presented, except for minor issues in color coding and font size.<br /> - Functional assays to assess the functional impact of TIGIT upregulation on CD8 T cell function.<br /> -<br /> Weaknesses:<br /> - While the paper reads overall well, the hypotheses and concepts should be clarified in several instances. For example, the authors speak of T cell exhaustion, which in principle is understood as antigen-specific T dysfunction associated with antigen persistence. However, a good part of the paper is focused on total CD8 T cells, and the links between findings in the different populations of CD8 examined (total, SEB-stimulated, Gag-stimulated) are hard to understand.<br /> - Upregulation of IRs can be associated with the state of T cell differentiation and also modulated by chronic inflammation independently of TCR signaling (eg, common gamma-chain cytokines upregulate PD-1), so defining these cells as univocally Tex is not correct.<br /> - The study mostly focuses on descriptive phenotypic analyses of CD8 T cells rather than dynamics studies which would imply more in-depth investigations of T cell evolution and fate.<br /> - HIV-specific CD8 T cells can be both quantitatively and quantitatively impaired, but the quantitative aspects are not considered, nor shifts in phenotype. For example, HIV-specific TIGIT+ CD8 responding to blockade proportionally over time - It is unclear if this is compensated by other subsets.<br /> - The functional assays with TIGIT blockade are limited and do not include other markers of cytotoxic cells (perforin, granzyme B expression...). It is not clear how do these subsets compare to the other clusters in terms of CD107 expression.<br /> - The statistical analyses do apparently not include correction for multiple comparisons.

Reviewer #3 (Public Review):

Here the authors use high-parameter flow cytometry to address expression patterns of inhibitory receptors and concordant functional responses in CD8+ T cells from people living with HIV (PLWH) during early vs. long-term ART treatment in order to understand the potential evolution of exhausted T cells in HIV infection. High-dimensional bioinformatic analysis is employed to uncover different subsets of CD8+ T cells expressing TIM-3, TIGIT, PD1, LAG3, and CD39. Stimulation assays were further conducted to assess polyclonal T cell responses (superantigen) or HIV-gag-specific CD8+ T cells, and whether the responding cells displayed inhibitory receptors. Finally, inhibitory receptor blockade was used (focusing on TIGIT and TIM-3 only) to examine the potential reversal of exhaustion. The authors found that CD107a+ degranulating central memory T cells apparently were sensitive to TIGIT blockade, yielding increased responses in cells from ART-treated PLWH.

Methods and Results Major Strengths: Sample size and data density. Longitudinal samples from long-term treated PLWH. Mechanistic studies to assess inhibitory receptor blockade.

Methods and Results Major Weaknesses: Lack of clarity on flow cytometric analysis and statistical methodology, including correction for multiple comparisons. Clustering density in tSNE analysis is unjustified, leading to potentially spurious outcomes. Insufficient raw flow cytometry data presented on inhibitory receptor expression in the various contexts of the study to allow determination of whether the subsequent bioinformatic analysis was merited due to the very low expression of 3/5 markers examined. Unclear whether differences observed are biologically meaningful (despite statistical differences). Finally, although the longitudinal samples are a distinct strength of the study, changes over time within individuals are unfortunately not assessed.

Aims and conclusions: The authors do find differences between the cohorts as described in the manuscript; however, the biological relevance of the findings is questionable due to an absence of direct studies on the cell populations found to be different. The use of unbiased clustering analysis is both a strength and a weakness. Specifically, the algorithm uncovers potential cell clusters that might be missed; however, the clustering program requires pre-set inputs on the expected number of clusters to be found, leading to possible irrelevant subsets being identified. The conclusions of the study are appropriately limited in scope.

Impact: There have been numerous studies of CD8+ T cell inhibitory receptor expression and T cell exhaustion in the context of HIV infection. It is well-accepted that T-cell exhaustion is a hallmark of progressive infection. This study contributes to the current knowledge in this area specifically through the examination of very long-term ART-treated PLWH. Unfortunately, it is not clear that several of the examined inhibitory receptors could be adequately detected, limiting the interpretation of the findings. Finally, it is unclear that this study justifies the potential use of TIGIT blockade to improve T cell function given the unclear biological relevance of the differential populations of CD8+ T cells observed.

Reviewer #2 (Public Review):

Summary:<br /> In the paper from Hartman, Vandenberg, and Hill entitled "assessing drug safety, by identifying the access of arrhythmia and cardio, myocytes, electro physiology", the authors, define a new metric, the axis of arrhythmia" that essentially describes the parameter space of ion channel conductance combinations, where early after depolarization can be observed.

Strengths:<br /> There is an elegance to the way the authors have communicated the scoring system. The method is potentially useful because of its simplicity, accessibility, and ease of use. I do think it adds to the field for this reason - a number of existing methods are overly complex and unwieldy and not necessarily better than the simple parameter regime scan presented here.

Weaknesses:<br /> The method described in the manuscript suffers from a number of weaknesses that plague current screening methods. Included in these are the data quality and selection used to inform the drug-blocking profile. It's well known that drug measurements vary widely, depending on the measurement conditions.

There doesn't seem to be any consideration of pacing frequency, which is an important consideration for arrhythmia triggers, resulting from repolarization abnormalities, but also depolarization abnormalities. Extremely high doses of drugs are used to assess the population risk. But does the method yield important information when realistic drug concentrations are used? In the discussion, the comparison to conventional approaches suggests that the presented method isn't necessarily better than conventional methods.

In conclusion, I have struggled to grasp the exceptional novelty of the new metric as presented, especially when considering that the badly needed future state must include a component of precision medicine.

Reviewer #1 (Public Review):

Summary:<br /> Heitmann et al introduce a novel method for predicting the potential of drug candidates to cause Torsades de Pointes using simulations. Despite the fact that a multitude of such methods have been proposed in the past decade, this approach manages to provide novelty in a way that is potentially paradigm-shifting. The figures are beautiful and manage to convey difficult concepts intuitively.

Strengths:<br /> (1) Novel combination of detailed mechanistic simulations with rigorous statistical modeling

(2) A method for predicting drug safety that can be used during drug development

(3) A clear explication of difficult concepts.

Weaknesses:<br /> (1) In this reviewer's opinion, the most important scientific issue that can be addressed is the fact that when a drug blocks multiple channels, it is not only the IC50 but also the Hill coefficient that can differ. By the same token, two drugs that block the same channel may have identical IC50s but different Hill coefficients. This is important to consider since concentration-dependence is an important part of the results presented here. If the Hill coefficients were to be significantly different, the concentration-dependent curves shown in Figure 6 could look very different.

(2) The curved lines shown in Figure 6 can initially be difficult to comprehend, especially when all the previous presentations emphasized linearity. But a further issue is obscured in these plots, which is the fact that they show a two-dimensional projection of a 4-dimensional space. Some of the drugs might hit the channels that are not shown (INaL & IKs), whereas others will not. It is unclear, and unaddressed in the manuscript, how differences in the "hidden channels" will influence the shapes of these curves. An example, or at least some verbal description, could be very helpful.

Reviewer #3 (Public Review):

Henault et al. address the important open question of whether hybridization could trigger TE mobilization. To do this they analysed MA lines derived from crosses of Saccharomyces paradoxus and Saccharomyces cerevisiae using long-read sequencing. These MA lines were already analysed in a previous publication using Illumina short-read data but the novelty of this work is the long-read sequencing data, which may reveal previously missed information. It is an interesting message of this study that hybridization between the two species did not lead to much TE activity. Due to this low activity, the authors performed an additional TE activity assay in vivo to measure transposition rates in hybrid backgrounds. The study is well written and I cannot spot any major problems. The study provides some important messages (like the influence of the genotype and mitochondrial DNA on transposition rates).

Major comments<br /> - What I miss the most in this work is the perspective of the host defence against TEs in Saccharmoces. Based on such a mechanistic perspective, why do the authors think that hybridization could lead to a TE reactivation? For example, in Drosophila small RNAs important for the defence against a TE, are solely maternally transmitted. Hybrid offspring will thus solely have small-RNAs complementary to the TEs of the mother but not to the TEs of the father, therefore a reactivation of the paternal TEs may be expected. I was thus wondering, what is the situation in yeast. Why would we expect an upregulation of TEs? Without such a mechanistic explanation the hypothesis that TEs should be upregulated in hybrids is a bit vague, based on a hunch.

Reviewer #1 (Public Review):

Henault et al build on their own previous work investigating the longstanding hypothesis that hybridization between divergent populations can activate transposable element mobilization (transposition). Previously they created crosses of increasing sequence divergence, using both intra- and inter-species hybrids, and passaged them neutrally for hundreds of generations. Their previous work showed that neither hybrids isolated from natural environments nor hybrids from their mutation accumulation lines showed consistent evidence of increased transposable element content. Here, they sequence and assemble long-read genomes of 127 of their mutation-accumulation lines and annotate all existing and de novo transposable elements. They find only a handful of de novo transposition events, and instead demonstrate that structural variation (ploidy, aneuploidy, loss of heterozygosity) plays a much larger role in the transposable element load in a given strain. They then created transposable element reporter constructs using two different Ty1 elements from S. paradoxus lineages and measured the transposition rate in a number of intraspecific crosses. They demonstrate that the transposition rate is dependent on both the Ty1 sequence and the copy number of genomic transposable elements, the latter of which is consistent with what has been observed in the literature on transposable element copy number control in Saccharomyces. To my knowledge, others have not directly tested the effect of Ty1 sequence itself (have not created diverse Ty1 reporter constructs), and so this is an interesting advance. Finally, the authors show that mitotype has a moderate effect on transposition rate, which is an intriguing finding that will be interesting to explore in future work.

This study represents a large effort to investigate how genetic background can influence transposable element load and transposition rate. The long read sequencing, assembly, and annotation, and the creation of these reporter constructs are non-trivial. Their results are straightforward, well supported, and a nice addition to the literature.

The authors state that the results from their current work support results taken from their previous study using short-read sequencing data of the same lines. The argument that follows is whether the authors gained anything novel from long-read sequencing. I would like to see the authors make a stronger argument for why this new work was necessary, and a more detailed view of similarities or differences from their previous study (when should others choose to do long read vs. short read of evolved lines?). Relatedly, the authors should report the rates of structural variants that they observe. How are these results similar/different from other mutation-accumulation work in S. cerevisiae?

Since the authors show a small, but consistent influence of mitotype on transposition rates, adding further evidence for the role of mtDNA in regulating transposition, I'm curious what the transposition rate of a p0 strain is. I think including these results could make this observation more compelling.

Reviewer #2 (Public Review):

This is an interesting follow-up study that uses long-read sequencing to examine previously constructed mutation accumulation lines between wild populations of S. cerevisiae and S. paradoxus. They also complement this work with reporter assays in hybrid backgrounds. The authors are attempting to test the hypothesis that hybridization leads to genome shock and unrestrained transposition. The paper largely confirms previous results (suggesting hybridization does not increase transposition) that are well cited and discussed in the paper, both from this group and from the Smukowski Heil/Dunham group but extends them to a new set of species/hybrids and with some additional resolution via the long read sequencing. The paper is well written and clear and I have no serious complaints.

In the abstract, the authors make three primary claims:

Structural variation plays a strong role in TE load.<br /> Transposition plays only a minor role in shaping the TE landscape in MA lines.<br /> Transposition rates are not increased by hybridization but are affected by genotype-specific factors.

I found all three claims supported, albeit with some minor questions below:

Structural variation plays a strong role in TE load.<br /> Convinced of this result. However:<br /> Line 185-187/Figure 3C: I'm curious given that the changes in Ty count are so often linked to changes in gross DNA sequence whether the count per total DNA sequence is actually changing on average in these genomes. Ie., does hybridization tend to increase TE count via CNV or does hybridization tend to increase DNA content in the MA lines and TEs come along for the ride?

One question about ploidy (lines 175-177):

Both aneuploidy and triploidy seem easy to call from this data. A 3:1 tetraploidy as well. However, in Figure 2B there are tetraploids that are around the 1:1 line. How are the authors calling ploidy for these strains? This was not clear to me from the text.

Reviewer #1 (Public Review):

Anderson, Henikoff, Ahmad et al. performed a series of genomics assays to study Drosophila spermatogenesis. Their main approaches include (1) Using two different genetic mutants that arrest male germ cell differentiation at distinct stages, bam and aly mutant, they performed CUT&TAG using H3K4me2, a histone modification for active promoters and enhancers; (2) Using FACS sorted pure spermatocytes, they performed CUT&TAG using antibodies against RNA PolII phosphorylated Ser 2, H4K16ac, H3K9me2, H3K27me3, and ubH2AK118. They also compare these chromatin profiling results with the published single-cell and single-nucleus RNA-seq data. Their analyses are across the genome but the major conclusions are about the chromatin features of the sex chromosomes. For example, the X chromosome is lack of dosage compensation as well as inactivation in spermatocytes, while Y chromosome is activated but enriched with ubH2A in spermatocytes. Overall, this work provides high-quality epigenome data in testes and in purified germ cells. The analyses are very informative to understand and appreciate the dramatic chromatin structure change during spermatogenesis in Drosophila. Some new analyses and a few new experiments are suggested here, which hopefully further take advantage of these data sets and make some results more conclusive.

Major comments:

1). The step-wise accumulation of H3K4me2 in bam, aly and wt testes are interesting. Is it possible to analyse the cis-acting sequences of different groups of genes with distinct H3K4me2 features, in order to examine whether there is any shared motif(s), suggesting common trans-factors that potentially set up the chromatin state for activating gene expression in a sequential manner?

2). Pg. 4, line 141-142: "we cannot measure H3K4me2 modification at the bam promoter in bam mutant testes or at the aly promoter in aly mutant testes", what are the allelic features of the bam mutant and aly mutant? Are the molecular features of these mutations preventing the detection of H3K4me2 at the endogenous genes' promoters? Also, the references cited (Chen et al., 2011) and (Laktionov et al., 2018) are not the original research papers where these two mutants were characterized.

3). The original paper that reported the Pc-GFP line and its localization is: Chromosoma 108, 83 (1999). The Pc-GFP is ubiquitously expressed and almost present in all cell types. In Figure 6B, there is no Pc-GFP signals in bam and aly mutant cells. According to the Method "one testis was dissected", does it mean that only one testis was prepared for immunostaining and imaging? If so, definitely more samples should be used for a more confident conclusion. Also, why use 3rd instar larval testes instead of adult testes? Finally, it is better to compare fixed tissue and live tissue, as the Pc-GFP signal could be lost during fixation and washing steps. Please refer to the above paper [Chromosoma 108, 83 (1999)] for Pc-GFP in spermatogonial cells and Development 138, 2441-2450 (2011) for Pc-GFP localization in aly mutant.

4). Ubiquitinylation of histone H2A is typically associated with gene silencing, here it has been hypothesized that ubH2A contributes to the activation of Y chromosome. This conclusion is strenuous, as it entirely depends on correlative results. For example, the lack of co-localization of ubH2A immunostaining and Pc-GFP are not convincing evidence that ubH2A is not resulting from PRC1 dRing activity. It would be a lot stronger conclusion by using genetic tools to show this. For example, if dRing is knocked down (using RNAi driven by a late-stage germline driver such as bam-Gal4) or mutated in spermatocytes (using mitotic clonal analysis), would they detect changes of ubH2A levels?

5). Regarding "X chromosome of males is thought to be upregulated in early germline cells", it has been shown that male-biased genes are deprived on the X chromosome [Science 299:697-700 (2003); Genome Biol 5:R40 (2004); Nature 450:238-241 (2007)], so are the differentiation genes of spermatogenesis [Cell Research 20:763-783 (2010)]. It would be informative to discuss the X chromatin features identified in this work with these previous findings. For example, the lack of RNAPII on X chromosome in spermatocytes could be due to a few differentiation genes expressed in spermatocytes located on the X chromosome.

Reviewer #2 (Public Review):

Anderson et al profiled chromatin features, including active chromatin marks, RNA polymerase II distribution, and histone modifications in the sex chromosomes of spermatogenic cells in Drosophila. The results are new and the experiments and analyses look well done, including with appropriate numbers of replicates. Results were parsed by comparing them among two arrest mutants and wildtype, as well as in FACS-sorted spermatocytes. The authors also profiled larval wing discs to serve as reference-somatic cells, which allowed them to focus only on features in their testis data that were associated with germ cells. Their results were further refined by categorizing the genes of interest based on available single nucleus RNA seq expression profiles. The authors document interesting phenomena, such as differences in the distribution of RNAPIIS2p on some genes in germ cells vs somatic cells, the presence of a uH2A body beginning in early spermatocytes, and high levels of uH2A on the Y chromosome and little or none on the X. The former is intriguing because this modification is usually associated with silencing, yet the Y chromosome is active in spermatogenic cells. The authors interpret some of their data as implying a lack of dosage compensation of the X chromosome in spermatocytes.

The data are believable and new, but it is not fully clear how to interpret them. The paper's interpretations rely on subtractive logic to parse results from mixtures of cells down to cell type, extracting spermatogonia, spermatocyte, etc. features by comparing bam mutants (only spermatogonia) to aly mutants (spermatogonia and early spermatocytes but no later stages) to wildtype (all spermatogenic stages), and extracting testis germline data by comparison to wing disc soma; their FACS sorted spermatocytes also have heterogeneity. I recognize that the present paper was a lot of work and am not suggesting that the authors redo their study using methods that give more purity and precision of stage (https://doi.org/10.1126/science.aal3096, https://doi.org/10.1101/gad.335331.119), but they should be aware of them and of their results.

The conclusions about dosage compensation are indirect, but are consistent with the current model documented in the studies cited by the authors, as well as earlier studies (doi: 10.1186/jbiol30).

Reviewer #1 (Public Review):

This is an intriguing and creative paper that examines whole brain cfos induction, a measure of brain activity, during mating and the formation of pair bonding. This contrasts with the classical reductionistic approach of focusing on a few individual brain regions in the monogamous and pair-bonding prairie vole. By taking this whole-brain approach following mating and then bond formation, several findings are revealed. (1) Using hierarchical cluster analysis some clusters were consistent with previously well-identified brain regions/circuits involved in bonding. The bed nucleus of the stria terminalis was identified as an important hub for bonding behavior but, importantly, the study also identified newer brain circuits likely involved in pair bond maintenance. (2) Rates of ejaculation best predicted the consistency of cfos activation that characterized a pair. (3) once the pair bond has stabilized, an amygdala cluster emerged potentially representing the coordination of a new cluster of brain regions that allow for pair bond maintenance. (4) There was a surprising lack of sexual dimorphism in active brain clusters identified during mating and pair bonding, but perhaps characteristic of a monogamous species.

While the approach used in this study cannot identify cause and effect, the whole brain approach identified clusters representing circuits of potential importance and a series of new hypotheses to explore.

The importance of the role of sexual behavior, specifically ejaculation rates, is worth emphasizing for the formation of pair bonds in prairie voles. It suggests that the role of sexual behavior in contributing to the strength of pair bonds should be explored more. It is also important to add that males and females in the study were screened for sexual receptivity. It would therefore be important to identify characteristics of animals that did not mate under the laboratory conditions used that may add depth and complexity to what was identified in the current study. The identification of brain regions for pair bond maintenance centered around the amygdala was also intriguing.

The issue of the lack of a strong presence of the reward circuitry (nucleus accumbens) in the final models is also worth more discussion. Perhaps it has been overly emphasized in the past, but there are strong results from other studies pointing to the importance of reward circuitry.

The design involved a nice time series for collecting behavioral and neural data at four time points: 0 hr (mating), 2.5 hr (mating huddling, investigation). 6 (early unstable bond) and 22 hours after mating.

Please discuss the consequences of creating the behavioral data for pair bond formation by subtracting same-sex pairs interactions from the opposite-sex interactions. What sources of information are removed by using this approach?

Time 0 is when the barrier is removed after a two-hour exposure. Please speculate on what is going on during the two-hour exposure. Time zero is potentially more than the time of mating. Is it possible that aggression is being decreased during this time point that represents mating? Could it also be a measure of the outcome of an initial compatibility assessment by the male and female?

Reviewer #2 (Public Review):

In this manuscript, the authors generate an annotated brain atlas for the prairie vole, which is a widely studied organism. This species has a suite of social behaviors that are difficult or impossible to study in conventional rodents, and has attracted a large community of researchers. The atlas is impressive and will be a fantastic resource. The authors use this atlas to examine brain-wide c-fos expression in prairie voles that were paired with same-sex or opposite-sex voles across multiple time points. In some sense, the design resembles PET studies done in primates that take whole brain scans after an important behavioral experience. The authors observed increased c-fos expression across a network of brain regions that largely corresponds with the previous literature. The study design captured several novel observations including that c-fos expression in some regions correlates strongly between males and females during pair bond formation and mating, suggesting synchrony in neural activity. An important caveat to this study not mentioned by the authors is that c-fos provides a snapshot of neural activity and that important populations of neurons could be active and not express c-fos. Thus observed correlations are likely to be robust, but the absence of differences (in say accumbens) may just reflect the limits of c-fos estimation of neural activity. Similarly, highly coordinated neural activity between males and females might still be driven by different mechanisms if different cell types were activated within a specific region. Nonetheless, the creation of this resource and its use in a well-designed study is an important accomplishment.

Reviewer #3 (Public Review):

In this manuscript, Gustison et al., describe the development of an automated whole-brain mapping pipeline, including the first 3D histological atlas of the prairie vole, and then use that pipeline to quantify Fos immunohistochemistry as a measure of neural activity during mating and pair bonding in male and female prairie voles. Prairie voles have become a useful animal model for examining the neural bases of social bonding due to their socially monogamous mating strategy. Prior studies have focused on identifying the role of a few neuromodulators (oxytocin, vasopressin, dopamine) acting in a limited number of brain regions. The authors use this unbiased approach to determine which areas become activated during mating, cohabitation, and pair bonding in both sexes to identify 68 brain regions clustered in seven brain-wide neuronal circuits that are activated over the course of pair bonding. This is an important study because i) it generates a valuable tool and analysis pipeline for other investigators in the prairie vole research community and ii) it highlights the potential involvement of many brain regions in regulating sexual behavior, social engagement, and pair bonding that have not been previously investigated.

Strengths of the study include the unbiased assessment of neural activity using the automated whole brain activity mapped onto the 3D histological atlas. The design of the behavioral aspect of the study is also a strength. Brains were collected at baseline and 2.5, 6 and 22 hrs after cohabitation with either a sibling or opposite-sex partner. These times were strategically chosen to correspond to milestones in pair bond development. Behavior was also quantified during epochs over the 22 hr period providing useful information on the progression of behaviors (e.g. mating) during pair bonding and relating Fos activation to specific behaviors (e.g. sex vs bonding). The sibling co-housed group provided an important control, enabling the identification of areas specifically activated by sex and bond formation. The analyses of the data were rigorous, resulting in convincing conclusions. While there was nothing particularly surprising in terms of the structures that were identified to be active during the mating and cohabitation, the statistical analysis revealed interesting relationships in terms of interactions of the various clusters, and also some level of synchrony in brain activation between partners. Furthermore, ejaculation was found to be the strongest predictor of Fos activation in both males and females. The sex differences identified in the study were subtle and less than the authors expected, which is interesting.

While the study provides a potentially useful tool and approach that may be of general use to the prairie vole community and identifies in an anatomically precise manner areas that may be important for mating or pair bond formation, there are some weaknesses as well. The study is largely descriptive. It is impossible to determine whether the activated areas are simply involved in sex or in the pair bond process itself. In other words, the authors did not use the Fos data to inform functional testing of circuits in pair bonding or mating behaviors. However, that is likely beyond the scope of this paper in which the goal was more to describe the automated, unbiased approach. This weakness is offset by the value of the comprehensive and detailed analysis of the Fos activation data providing temporal and precise anatomical relationships between brain clusters and in relation to behavior. The manuscript concludes with some speculative interpretations of the data, but these speculations may be valuable for guiding future investigations.

Reviewer #1 (Public Review):

The manuscript by Maio and colleagues looks at the impact of the heightened glycolytic activity induced by Mtb in monocytes, and its impact on Hif1- dependent migration of DCs.

Data concerning the biological significance of the impact of enhanced glycolysis on DC migration is strong and convincing. While Hif1-a is obviously a key factor, the evidence that it is a linear component in the cascade falls a little short as the main inhibitor used PX-478 does not have a clear, single mode of action. Additional characterization with the alternative inhibitor (Echinomycin) would make the argument more convincing.

Reviewer #2 (Public Review):

The manuscript by Maio et al attempts to examine the bioenergetic mechanisms involved in the delayed migration of DC's during Mtb infection. The authors performed a series of in vitro infection experiments including bioenergetic experiments using the Agilent Seahorse XF, and glucose uptake and lactate production experiments. This is a well-written manuscript and addresses an important question in the TB field. A major weakness is the use of dead Mtb in virtually all the experiments. Unfortunately, the authors did not attempt to address this critical confounding factor. As a result, data was interpreted, and conclusions were made as if live Mtb was used. Also, previous studies (PMID: 30444490 and PMID: 31914380) have shown that live Mtb suppresses glycolysis, which contradicts findings in this study, perhaps because dead Mtb was used here. For these reasons, obtaining any pertinent conclusions from the study is not possible, which diminishes the significance of the work.

Reviewer #1 (Public Review):

Summary:<br /> The article written by Kazdaghli et al. proposes a modification of imputation methods, to better account for and exploit the variability of the data. The aim is to reduce the variability of the imputation results. The authors propose two methods, one that still includes some imputation variability, but accounts for the distribution of the data points to improve the imputation. The other one proposes a determinantal sampling, that presents no variation in the imputation data, at least no variation in the classification task. As these methods grow easily in computation requirements and time, they also propose an algorithm to run these methods in quantum processors.

Strengths:<br /> The sampling method for imputing missing values that accounts for the variability of the data seems to be accurate.

Weaknesses:<br /> While the proposed method seems accurate and should improve the imputation task, I think that the authors must explain a little better some parts of the algorithm that they are using. Although I think the authors could have evaluated the imputations directly, as they mention in the introduction, I understand that the final goal in the task is to have a better classification. The problem is that they do not explain what the classification is, or how is it trained. In a real situation, they would have data that would be used for training the algorithm, and then new data that needs to be imputed and classified. In this article, I do not see any train, plus test or validation data. I wonder if there could be some interaction between the imputation and the classification methods, that leads to overfitting the data; in particular when the deterministic DPP is used.

In its current state, I do not think this article brings not very much value to the community that could benefit from it. I did not find an implementation of the method available to other scientists, nor the data used to evaluate it (while one data set is public, the simulated data is not available). This not only hinders the use of the method by the scientific community, but also makes it impossible to reproduce the results or test the algorithm in similar databases.

Reviewer #2 (Public Review):

In this work, the authors address the problem of missing data imputation in the life sciences domain and propose several new algorithms which improve on the current state-of-the-art. In particular (i) they modify two existing Random Forest-based imputation methods -- MissForest and miceRanger -- to use either determinantal sampling or deterministic determinantal sampling, and show slightly improved classification performance on two datasets (one synthetic, one real); in addition, (ii) the authors present a quantum circuit for performing the determinantal sampling which scales asymptotically better than the best-known classical methods, and perform small scale experiments using both a (noiseless) quantum simulator as well as a 10 qubit IBM quantum computer to validate that the approach works in principle.

The problem of data imputation is important in practice, and results that improve on existing methods should be of interest to those in the field. The use of determinantal sampling for applications beyond data imputation should also be of broader interest, and the connection to quantum computing warrants further investigation and analysis.

The use of classification accuracy (as measured by AUC) as a measure of success is well-motivated, and the authors use both real and synthetic datasets to evaluate their methods, which consistently (if only marginally) outperform the existing state-of-the-art. The results obtained here motivate the further study of this approach to a wider class of datasets, and to areas beyond life sciences.

As it stands, in my opinion, two points need addressing.

1. Additional clarity is required on what is novel:

While the application of determinantal and deterministic determinantal sampling to the specific case of data imputation appears to be novel, the authors should make it more clear that both of these methods themselves are not new, and have been directly lifted from the literature. As it stands, the current wording in the main body of the paper gives the impression that the deterministic determinantal algorithm is novel, e.g. "this motivated us to develop a deterministic version of determinantal sampling" (p.2), and it is only in the methods section that a reference is made to the paper of Schreurs et al. which proposed the algorithm.

Similarly, in the abstract and main body of the text, the wording gives the impression that the quantum circuits presented here are new (e.g., "We also develop quantum circuits for implementing determinantal point processes") whereas they have been previously proposed (although one of the authors of the current paper was also an author of the original paper proposing the quantum circuits for determinantal sampling).

2. Additional analysis is needed to support the claims of potential for quantum advantage:

The authors claim that the quantum algorithm for implementing determinantal point processes provides a computational advantage over classical ones, in that the quantum circuits scale linearly in the number of features compared with cubic scaling classically. While this may be true asymptotically, in my opinion, more discussion is required about the utility and feasibility of this method in practice, as well as the realistic prospects of this being a potential area of application for quantum computing.

For example, the authors mention that a quantum computer of 150 qubits capable of running circuits of depth 400 is needed to perform the determinantal sampling for the MIMIC-III dataset considered, and say "while [such hardware is] not available right now, it seems quite possible that they will be available in the not so far future". The authors also state "This suggests that with the advent of next-generation quantum computers... one could expect a computational speedup in performing determinantal sampling" and "it is expected that next-generation quantum computers will provide a speedup in practice". These are strong assertions (even if 'next generation' is not clearly defined), and in my opinion, are not sufficiently backed by evidence to date. Given that datasets of the size of MIMIC-III (and presumably much larger) can be handled efficiently classically, the authors should clarify whether one expects a quantum advantage by this approach in the "NISQ" (pre-error-corrected) era of quantum computing. This seems unlikely, and any argument that this is the case should include an analysis accounting for the absolute operation speeds and absolute times required to perform such computations, including any time required for inputting data, resetting quantum circuits etc. On the other hand, if by 'next generation' the authors mean quantum computers beyond the NISQ era (i.e., assuming fault-tolerant quantum computers and logical qubits), then the overhead costs of quantum error correction (both in terms of physical qubit numbers as well as computational time) should be analyzed, and the crossover regime (i.e., data size where a quantum computation takes less absolute time than classical) estimated in order to assess the prospects of a practical quantum advantage, especially in light of recent analyses e.g., [1,2] below.

[1] Hoefler, Haner, Troyer. Communicatios of the ACM, 66.5 (2023):82-87<br /> [2] Babbush et al., PRX Quantum 2.1 (2021):010103

Other comments and suggestions:<br /> The authors measure "running time [as] the depth of the necessary quantum circuits." While circuit depth may indeed correspond to wall-clock time, quantum circuit size (i.e. number of gates) is the fairer complexity metric for comparison with classical running time. If depth is used, then a fair comparison to classical methods should be to compare with classical parallel processing time using N processors. However, if circuit size is used, then the quantum complexity is Nd, which contrasts with the classical value of Nd^2 (pre-processing) + d^3 (per sample). This yields a subquadratic quantum speedup over classical, as opposed to a qubic speedup.

The results (e.g Table 1) show that the new algorithms consistently outperform the original miceRanger and MissForest methods, although the degree of improvement is small, typically of order 1% or less. Some discussion is therefore warranted on the practical benefits of this method, and any tradeoff in terms of efficiency. In particular, while Table 1 compares the classification accuracy (as measured by AUC) of the newly proposed methods vs the existing state-of-the-art, a discussion on the scalability and efficiency would be welcome. The determinantal sampling takes time Nd^2, how does this compare with the original methods? For what dataset and feature sizes are the determinantal methods feasible (which will determine the scale at which other approaches, e.g. those based on quantum computing may be required).

A discussion (or at least mention) of the algorithmic complexity of the classical deterministic determinantal sampling (which seems to also be Nd^2) in the main body of the text would be welcome.

The final paragraph of the Methods section discusses sampling many times from the quantum circuits to estimate the most probable outcome, and hence perform the deterministic determinantal sampling. A more careful analysis of the number of samples needed (for bounded variance/error) and the impact on the running time (and whether one still expects an advantage over classical (although one must define some bounded error version of the deterministic algorithm to do so) or performance of the algorithm would be welcome.

A discussion on the absolute running time required for the quantum experiments performed (and how they compare to classical) would be interesting.

A mention of which quantum simulator was used would be welcome.

In the introduction, three kinds of data missingness (MCAR, MAR, MNAR) are mentioned, although experiments are only performed for MCAR and MNAR. Can some explanation for excluding MAR be given?

Reference 24 (Shadbar et al., the study that demonstrated the effectiveness of miceRanger and MissForest) used 4 datasets: MIMIC-III, Simulated, Breast Cancer, and NHSX COVID-19. Of these, MIMIC-III is used in the current paper, and Simulated appears similar (although with 1000 instead of 2000 rows) to the synthetic dataset of the current paper. An analysis of the determinantal sampling methods applied to the Breast Cancer and NHSX COVID-19 datasets (which have naturally occurring missingness), and a comparison to the results of Shadbar et al. would be interesting.

Reviewer #1 (Public Review):

Shoemaker and Grilli analyze publicly available sequencing data to quantify how the microbial diversity of ecosystems changes with the taxonomic scale considered (e.g., diversity of genera vs diversity of families). This study builds directly on Grilli's 2020 paper which used this data to show that for many different microbial species, the distribution of abundances of the species across sampling sites belongs to a simple one-parameter family of gamma distributions. In this work, they show that the gamma distribution also describes the distribution of abundances of higher taxonomic levels. The distribution now requires two parameters, but the second parameter can be approximately derived by treating the distributions of lower-level taxonomic units as being independent. The difference between the species-level result and the result at higher taxonomic levels suggests that in some sense microbial species are ecologically meaningful units.

While the higher-level taxon abundance distributions can be well-approximated assuming independence of the constituent species, this approach substantially underestimates variation in community richness and diversity among sampling sites. Much of this extra variability appears to be driven by variability in sample size across sites. It is not clear to me how much this variation in sample size is itself due to variation in sampling effort versus variation in overall microbial densities. This variation in sample size also produces correlations between taxon richness at lower and higher taxonomic levels. For instance, sites with large samples are likely to have both many species within a genus and many genera. The authors also consider taxon diversity (Shannon index, i.e. entropy), which is constructed from frequencies and is therefore less sensitive to sample size. In this case, correlations between diversity across taxonomic scales instead appear to depend on the idiosyncratic correlations among species abundances.

This paper's results are presented in a fairly terse manner, even when they are describing summary statistics that require a lot of thought to interpret. I don't think it would make sense to try to understand it without having first worked through the 2020 paper. But everyone interested in a general understanding of microbial ecology should read the 2020 paper, and once one has done that, this paper is worth reading as well simply for seeing how the major pattern in that paper shifts as one moves up in the taxonomic scale.

Reviewer #2 (Public Review):

Summary<br /> In this research advance, the authors purport to show that the unified neutral theory of biodiversity (UNTB) is not a suitable null model for exploring the relationship between macroecological quantities, and additionally that the stochastic logistic growth model (SLM) is a viable replacement. They do this by citing other studies where UNTB was unable to capture individual macroecological quantities and then demonstrating SLM's strength at modeling macroecological diversity metrics. They extend this analysis to show SLM's modeling capability at multiple scales of coarse-graining. Finally, the authors conduct a similar analysis to Madi et al. (2020) by investigating the relationship between diversity measures within a group and across coarse-grained groups (e.g. genera diversity in one family compared to diversity of families). The authors show that choosing SLM as a null model reveals some previously reported relationships to be no longer "novel", in the sense that the patterns can be adequately captured by the null model.

Strengths<br /> 1. The authors make a strong argument that UNTB is not a good null model of macroecological observables and especially relationships between them. The authors convincingly argue that a SLM is a better null since the gamma distribution it predicts is a better description of the empirical Abundance Fluctuation Distributions (AFD).<br /> 2. The authors show that the gamma distribution predicted by SLM is a good fit for the AFD's at many different scales of coarse-graining, not just the OTU level as was previously demonstrated.<br /> 3. The authors convincingly demonstrate how SLM can be used to test the relevance of interactions to macroecological relationships.

Weaknesses<br /> 1. Use of the word "predict" with the SLM in this advance is confusing, and to this reviewer seems to make a stronger claim than shown by the authors. For example, in their abstract, the authors state "We found that measures of biodiversity at a given scale can be consistently predicted using predictions (sic) derived from a minimal model of ecology." This appears to imply that a minimal model predicted the behavior of a system when in reality it accurately described the data it was trained on. This potential for confusion extends throughout the text and obscures what was actually achieved.<br /> 2. More generally, to my mind the presentation in the manuscript could benefit from a clearer delineation between the question of "what patterns are explainable by a noninteracting model vs require interactions" (which could be assessed with no reference to SLM, but by a simple randomization test), and whether specifically, SLM is a good null model / better than UNTB.

Overall Impact<br /> The authors achieve their aims, even though the text is at times dense. The use of SLM as a non-interacting null model for macroecological quantities and relationships is well supported by the text, and SLM should be used as a null model for these types of phenomena going forward.

Joint Public Review:

Previous findings by authors show that heliomycin induces autophagy to inhibit cancer progression, while its water-soluble analogs induce apoptosis. Here, they show that one of the analogs, 4-dmH, binds to tNOX, a NADH oxidase which supports SirT1 activity, in addition to SirT1, while heliomycin only binds to SirtT1 but not tNOX, using CETSA and in silico molecular docking studies, in human oral cancer cells. The additional binding activity of 4-dmH to tNOX might explain the different biological outcome from heliomycin. 4-dmH induces ubiquitination and degradation of tNOX protein, in dependent of p53 status. The tumor suppressive effect of 4-dmH (by intra-tumoral injections) is better than heliomycin. TCGA data base analysis suggests that high tNOX mRNA expression is correlated with poor prognosis of oral cancer patients.

This group has been a leading lab of chemical and biological characterization of heliomycin and its analogs. Although their findings are interesting and advance their previous findings, they arbitrarily focus on tNOX as a potential new target of 4-dmH without clear rationale. Moreover, it remains unclear if the different biological outcomes caused by heliomycin and 4-dmH are indeed due to 4-dmH's ability to bind to tNOX in addition to SirT1. Moreover, molecular biological analyses to establish the proposed tNOX-SirT1 axis on inducing autophagy vs apoptosis are insufficiently performed.

Comments on the current version:

1. The rationale of selecting tNOX/ENOX2 as a potential target of 4-dmH, but not heliomycin, is unclear by taking a biased approach. Thus, there is high possibility that 4-dmH binds to other proteins involved in apoptosis inhibition. An unbiased screen to identify 4-dmH-binding proteins would be a better approach unless there is a clear and logical rationale.

2. The authors should show whether heliomycin indeed does not induce apoptosis, while 4-dmH cannot induce autophagy.

3. They should demonstrate whether genetic knockdown of tNOX, SirT1, or both tNOX and SirT1 induces apoptosis or autophagy and also reduces malignant properties of oral cancer cells.

4. The authors should examine whether overexpression of SirT1 or tNOX in cells treated with heliomycin or 4-dmH could nullify heliomycin-induced autophagy and 4-dmH-induced apoptosis. Also, instead of overexpressing tNOX, they can supplement NAD into cells treated with 4-dmH.

5. Related to Fig. 5C and 6a, the authors should examine the effects of heliomycin and 4-dmH on the cell cycle profiles, Annexin V positivity, and colony formation.

6. They should also examine whether either or both heliomycin and 4-dmH induce reactive oxygen species (ROS).

7. Related to Fig. 9d, they should mutate amino acid residue(s) in tNOX that are crucial for the 4-dmH-tNOX binding, including Ile 90, Lys98, Pro111, Pro113, Leu115, Pro117, and Pro118, to examine whether these mutants lose the binding to 4-dmH and fail to rescue 4-dmH-induced apoptosis, unlike wild-type tNOX.

8. Related to Fig. 10a, heliomycin appears to also reduce tNOX levels (although the extent is not as robust as 4-dmH), which is not expected since heliomycin does not bind to tNOX. They should compare the effects of heliomycin and 4-dmH on reducing the protein levels of tNOX. If heliomycin does not change the tNOX protein levels, then they need to discuss why heliomycin reduces tNOX levels in vivo.

9. Related to Fig. 10F, if tNOX is an upstream regulator of SirT1 and both heliomycin and 4-dmH ultimately target SirT1, it is unclear why heliomycin and 4-dmH cause different biological outcomes. One explanation is that tNOX has apoptosis-inhibiting function other than supporting (or independent of) SirT1 and hence 4-dmH-mediated tNOX inhibition causes apoptosis rather than autophagy. They should explain and discuss more about whether tNOX-inhibiting/binding function of 4-dmH is sufficient to explain the different biological outcomes from heliomycin.

10. They should examine the effects of heliomycin and 4-dmH on cell viability of non-tumor cells to examine their toxicities.

11. They should consistently use either tNOX or ENOX2 to avoid confusion.

Reviewer #1 (Public Review):

This manuscript conducts a classic QTL analysis to identify the molecular basis of natural variation in disease resistance. This identifies a pair of glycosyltransferases that contribute to steroidal glycoalkaloid production. Specifically altering the final hexose structure of the compound. This is somewhat similar to the work in tomatine showing that the specific hexose structure mediates the final potential bioactivity. Using the resulting transgenic complementation lines that show that the gene leads to a strong resistance phenotype to one isolate of Alternaria solani and the Colorado potato beetle. This is solid work showing the identification of a new gene and compound influencing plant biotic interactions. The authors have improved the introduction and discussion to better show the breadth of knowledge in pathogen-defense metabolite interactions involving plants.

Reviewer #2 (Public Review):

The study focuses on a mechanism of pest/pathogen resistance identified in Solanum commersonii, which appears to offer dominant resistance to Alternaria solani (potato early blight) through the activity of specific glycosyltransferases which facilitate the production of tetraose glycoalkaloids in leaf tissue. The authors demonstrated that these glycoalkaloids are suppressive to the growth of multiple pathogenic ascomycetes and furthermore, that transgenic plants expressing these glycosyltransferases in susceptible S. commersonii clones demonstrate improved resistance to specific strains of A. solani and a genotype of Colorado Potato Beetle. The study design is straightforward, yet thorough, and does a good job demonstrating the importance of these genes in resistance. This work is significant because it demonstrates the mechanism behind resistance to a necrotrophic pathogen. Resistance to this group of pathogens has historically relied on mechanisms that do not include the use of typical dominant resistance gene products (nucleotide-binding, leucine-rich repeat proteins). The identification of these glycosyltransferases and their role in resistance will give potato breeders options for the development of markers associated with resistance to this group of pathogens. However, this may demonstrate an important battle to balance between production traits (like disease resistance) and quality traits (like glycoalkaloid content), as the two may be mutually exclusive in the development of new varieties.

Reviewer #1 (Public Review):

The work in this paper is in general done carefully. Reconstructions are done appropriately and the effects of statistical uncertainty are quantified properly. My only slight complaint is that I couldn't find statistics about posterior probabilities anywhere and that the sequences and trees do not seem to be deposited. I would also have preferred to have the actual phylogeny in the main text. This is a crucial piece of data that the reader needs to see to understand what exactly is being reconstructed.<br /> The paper identifies which mutations are crucial for the functional differences between the ancestors tested. This is done quite carefully - the authors even show that the same substitutions also work in extant proteins. My only slight concern was the authors' explanation of what these substitutions do. They show that these substitutions lower the affinity of the C-terminal peptide to the alpha-crystallin domain - a key oligomeric interaction. But the difference is very small - from 4.5 to 7 uM. That seems so small that I find it a bit implausible that this effect alone explains the differences in hydrodynamic radius shown in Figure S8. From my visual inspection, it seems that there is also a noticeable change in the cooperativity of the binding interaction. The binding model the authors use is a fairly simple logarithmic curve that doesn't appear to consider the number of binding sites or potential cooperativity. I think this would have been nice to see here.

Lastly, the authors use likelihood methods to test for signatures of selection. This reviewer is not a fan of these methods, as they are easily misled by common biological processes (see PMID 37395787 for a recent critique). Perhaps these pitfalls could simply be acknowledged, as I don't think the selection analysis is very important to the impact of the work.

Reviewer #2 (Public Review):

This was an interesting study, and I enjoyed seeing different experimental approaches used to compare the properties of the different native proteins, the ancestral reconstructions, and the other mutants. I think it provides convincing mechanistic evidence as to how these small heat shock proteins have evolved. Thus, I think it represents a valuable contribution to the field. However, to a certain extent, I think the authors have at times over-interpeted their results, and over-simplified their explanations, as the differences between the ancestral proteins, and the changes induced by the two mutations, only partially explain the differences between IbpA proteins from the two different species. Furthermore, in some places, I found this difficult to follow and figures were not properly explained or labelled. If these issues were addressed, I think the paper would be considerably more accessible to readers.

Reviewer #3 (Public Review):

Summary:<br /> The study by Karaś et al. reveals how multi-protein systems can evolve into single-protein equivalents, shedding light on the molecular events enabling gene loss during evolution. This work is valuable for researchers in evolutionary fields and offers potential applications in protein and organism engineering. While the findings lack broader appeal and societal implications, the evidence presented supports the proposed molecular mechanism. Using computational methods and biochemical analysis, the authors traced the evolutionary simplification of bacterial small heat shock proteins, linking specific mutations to functional changes. The study's strength lies in its vertical approach, identifying functional residues, but it does not introduce new techniques, limiting its novelty and significance.

Strengths:<br /> 1) Experimental Approach<br /> The research question was clearly outlined and the author's approach to answering it was systematic. In particular, their model system was highly suitable to address the research question. The authors employed appropriate experimental and computational techniques, and their 'vertical approach' was beneficial in that it allowed them to discover functional residues in the sHsp system which may not have been possible otherwise. Overall, their approach to this study was solid.

2) Reproducibility<br /> The results were presented well. The number of experimental repeats was suitable, as well as their analysis of the data. The values for standard deviation were reasonable, and their results using the alternative ancestors for the substrate aggregation assays helped support the robustness of their observations.

Weaknesses:<br /> During the mutational experiments, the authors examined seven potential substitutions identified through ASR and measured their impact on protein disaggregation activity. Positions 66 and 109 exhibited a significant decrease in luciferase refolding stimulation. To explore the combined effect of these mutations, the authors created the double mutant AncA0. However, predicting the most impactful combination of mutations due to epistatic effects is challenging. A more effective strategy would be to test various combinations of mutations to identify the double mutant with the greatest decrease in luciferase refolding stimulation and/or alternatively perform a co-evolutionary study to try to understand any epistatic effects between the mutations.

Reviewer #1 (Public Review):

Summary:<br /> This study develops and applies a coarse-grained model for nucleosomes with explicit ions. The authors perform several measurements to explore the utility of a coarse-grained simulation method to model nucleosomes and nucleosome arrays with explicit ions and implicit water. 'Explicit ions' means that the charged ions are modeled as particles in simulation, allowing the distributions and dynamics of ions to be measured. Since nucleosomes are highly charged and modulated by charge modifications, this innovation is particularly relevant for chromatin simulation.

Strengths:<br /> This simulation method produces accurate predictions when compared to experiments for the binding affinity of histones to DNA, counterion interactions, nucleosome DNA unwinding, nucleosome binding free energies, and sedimentation coefficients of arrays. The variety of measured quantities makes both this work and the impact of this coarse-grained methodology compelling.

The comparison between the contributions of sodium and magnesium ions to nucleosome array compaction, presented in Figure 3, was exciting and a novel result that this simulation methodology can assess.

Weaknesses:<br /> The presentation of experimental data as representing in vivo systems is a simplification that may misrepresent the results of the simulation work. In vivo, in this context, typically means experimental data from whole cells. What one could expect for in vivo experimental data is measurements on nucleosomes from cell lysates where various and numerous chemical modifications are present. On the contrary, some of the experimental data used as a comparison are from in vitro studies. In vitro in this context means nucleosomes were formed 'in a test tube' or under controlled conditions that do not represent the complexity of an in vivo system. The simulations performed here are more directly compared to in vitro conditions. This distinction likely impacts to what extent these simulation results are biologically relevant. In vivo and in vitro differences could be clarified throughout and discussed.

Reviewer #2 (Public Review):

In this manuscript, the authors introduced an explicit ion model using the coarse-grained modelling approach to model the interactions between nucleosomes and evaluate their effects on chromatin organization. The strength of this method lies in the explicit representation of counterions, especially divalent ions, which are notoriously difficult to model. To achieve their aims and validate the accuracy of the model, the authors conducted coarse-grained molecular dynamics simulations and compared predicted values to the experimental values of the binding energies of protein-DNA complexes and the free energy profile of nucleosomal DNA unwinding and inter-nucleosome binding. Additionally, the authors employed umbrella sampling simulations to further validate their model, reproducing experimentally measured sedimentation coefficients of chromatin under varying salt concentrations of monovalent and divalent ions.

The significance of this study lies in the authors' coarse-grained model which can efficiently capture the conformational sampling of molecules while maintaining a low computational cost. The model reproduces the scale and, in some cases, the shape of the experimental free energy profile for specific molecule interactions, particularly inter-nucleosome interactions. Additionally, the authors' method resolves certain experimental discrepancies related to determining the strength of inter-nucleosomal interactions. Furthermore, the results from this study support the crucial role of intrinsic physicochemical interactions in governing chromatin organization within the nucleus.

The method is simple but can be useful, given the authors can provide more details on their ion parameterization. The paper says that parameters in their "potentials were tuned to reproduce the radial distribution functions and the potential of mean force between ion pairs determined from all-atom simulations." However, no details on their all-atom simulations were provided; at some point, the authors refer to Reference 67 which uses all-atom simulations but does not employ the divalent ions. Also, no explanation is given for their modelling of protein-DNA complexes.

Overall, the paper is well-written, concise and easy to follow but some statements are rather blunt. For example, the linker histone contribution (Figure 5D) is not clear and could be potentially removed. The result on inter-nucleosomal interactions and comparison to experimental values from Ref#44 is the most compelling. It would be nice to see if the detailed shape of the profile for restrained inter-nucleosomal interactions in Figure 4B corresponds to the experimental profile. Including the dependence of free energy on a vertex angle would also be beneficial.

Another limitation of this study is that the authors' model sacrifices certain atomic details and thermodynamic properties of the modelled systems. The potential parameters of the counter ions were derived solely by reproducing the radial distribution functions (RDFs) and potential of mean force (PMF) based on all-atom simulations (see Methods), without considering other biophysical and thermodynamic properties from experiments. Lastly, the authors did not provide any examples or tutorials for other researchers to utilize their model, thus limiting its application.

Reviewer #2 (Public Review):

Summary:<br /> The major purpose of this manuscript is to examine whether leucine treatment would be a potential strategy to treat cytokine storm syndrome (CSS). CSS is a common symptom in multiple infectious diseases in clinic, which gradually leads to multiple organ failure and high mortality. Strategies to treat CSS including pulse steroid therapy normally lead to severe side effects. Therefore, it is still required to develop a safe strategy with high efficacy to treat CSS. In clinic, sepsis is well characterized to exhibit CSS and therefore multiple studies utilized a LPS-induced sepsis model to evaluate CSS symptoms. In this study, the authors examined whether leucine, an essential amino acid that has been absorbed daily in our body, could ameliorate CSS symptoms in the LPS-induced sepsis mouse model. They found a potential protective effect of leucine in terms of the survival rate and inflammatory responses.

Strengths:<br /> The study is overall well designed and the results are well analyzed with only minor issues. The methods utilized are appropriate.

Weaknesses:<br /> The mechanistic insights are not sufficient and could not fully explain the phenotype they found. Considering the importance of this study is to identify the potential protective role of leucine in CSS, the authors could also consider investigator-initiated clinical trials to further expand the significance of this study.

Reviewer #1 (Public Review):

The authors aimed to determine the mechanisms that underpin metabolic influences, particularly via the use of leucine which has been implicated in protection in lipopolysaccharide-induced cytokine storm syndrome.

The strength of the work is in establishing the clear relationship between the macrophage subtype and the severity of cytokine storm syndrome which occurs in severe inflammation and infection. They have undertaken a solid analysis of the cellular polarization of macrophage subtypes, identifying leucine suppresses M1 polarization and promotes M2 polarization. Subsequently, the authors confirmed this polarization via examination of signal transduction was mediated through the mTORC1 pathway. Pharmacological manipulation of mTORC was shown to influence arginase 1, a hallmark of M2 polarization. In addition, the authors show that leucine promoted the expression of LXRa required for arginase induction. While these studies identify how leucine might shape M2 cellular metabolism and polarization, the studies were all performed in vitro and do not examine other cellular or molecular changes that might influence the level of cytokine storm that might occur. Thus the specific contributions in cytokine storm syndrome are correlative requiring further analysis in the disease setting. These include features such as localization influencing other immune or stromal cells that might release cytokines and contribute to the syndrome, or molecular pathways not previously described. The statistical reporting and representation of data should be provided in greater detail. The data provides an interesting direction for consideration of the manipulation of immune cells in the context of inflammation and opens further discussion on how this might be practically applied in the clinical setting.

Reviewer #1 (Public Review):

Summary:<br /> This paper by Schommartz and colleagues investigates the neural basis of memory reinstatement as a function of both how recently the memory was formed (recent, remote) and its development (children, young adults). The core question is whether memory consolidation processes as well as the specificity of memory reinstatement differ with development. A number of brain regions showed a greater activation difference for recent vs. remote memories at the long versus shorter delay specifically in adults (cerebellum, parahippocampal gyrus, LOC). A different set showed decreases in the same comparison, but only in children (precuneus, RSC). The authors also used neural pattern similarity analysis to characterize reinstatement, though I have substantive concerns about how this analysis was performed and as such will not summarize the results. Broadly, the behavioural and univariate findings are consistent with the idea that memory consolidation differs between children and adults in important ways, and takes a step towards characterizing how.

Strengths:<br /> The topic and goals of this paper are very interesting. As the authors note, there is little work on memory consolidation over development, and as such this will be an important data point in helping us begin to understand these important differences. The sample size is great, particularly given this is an onerous, multi-day experiment; the authors are to be commended for that. The task design is also generally well controlled, for example as the authors include new recently learned pairs during each session.

Weaknesses:<br /> As noted above, the pattern similarity analysis for both item and category-level reinstatement was performed in a way that is not interpretable given concerns about temporal autocorrelation within the scanning run. Below, I focus my review on this analytic issue, though I also outline additional concerns.

1. The pattern similarity analyses were not done correctly, rendering the results uninterpretable (assuming my understanding of the authors' approach is correct).

a. First, the scene-specific reinstatement index: The authors have correlated a neural pattern during a fixation cross (delay period) with a neural pattern associated with viewing a scene as their measure of reinstatement. The main issue with this is that these events always occurred back-to-back in time. As such, the two patterns will be similar due simply to the temporal autocorrelation in the BOLD signal. Because of the issues with temporal autocorrelation within the scanning run, it is always recommended to perform such correlations only across different runs. In this case, the authors always correlated patterns extracted from the same run, which moreover have temporal lags that are perfectly confounded with their comparison of interest (i.e., from Fig 4A, the "scene-specific" comparisons will always be back-to-back, having a very short temporal lag; "set-based" comparisons will be dispersed across the run, and therefore have a much higher lag). The authors' within-run correlation approach also yields correlation values that are extremely high - much higher than would be expected if this analysis was done appropriately. The way to fix this would be to restrict the analysis to only cross-run comparisons, but I don't believe this is possible unfortunately given the authors' design; I believe the target (presumably reinstated) scene only appears once during scanning, so there is no separate neural pattern during the presentation of this picture that they can use. For these reasons, any evidence for "significant scene-specific reinstatement" and the like is completely uninterpretable and would need to be removed from the paper.

b. From a theoretical standpoint, I believe the way this analysis was performed considering the fixation and the immediately following scene also means that the differences between recent and remote could have to do with either the reactivation (processes happening during the fixation, presumably) or differences in the processing of the stimulus itself (happening during the scene presentation). For example, people might be more engaged with the more novel scenes (recent) and therefore process those scenes more; such a difference would be interpreted in this analysis as having to do with reinstatement, but in fact could be just related to the differential scene processing/recognition, etc. It would be important when comparing scene-specific neural patterns as templates for reinstatement across conditions that, at the time of scene presentation itself, the two conditions are equal (e.g., no difference in familiarity and so on); otherwise, we do not know which trial period (and therefore which underlying process) is driving the differences.

c. For the category-based neural reinstatement: (1) This suffers from the same issue of correlations being performed within the run. Again, to correct this the authors would need to restrict comparisons to only across runs (i.e., patterns from run 1 correlated with patterns for run 2 and so on). With this restriction, it may or may not be possible to perform this analysis, depending upon how the same-category scenes are distributed across runs. However, there are other issues with this analysis, as well. (2) This analysis uses a different approach of comparing fixations to one another, rather than fixations to scenes. The authors do not motivate the reason for this switch. Please provide reasoning as to why fixation-fixation is more appropriate than fixation-scene similarity for category-level reinstatement, particularly given the opposite was used for item-level reinstatement. Even if the analyses were done properly, it would remain hard to compare them given this difference in approach. (3) I believe the fixation cross with itself is included in the "within category" score. Is this not a single neural pattern correlated with itself, which will yield maximal similarity (pearson r=1) or minimal dissimilarity (1-pearson r=0)? Including these comparisons in the averages for the within-category score will inflate the difference between the "within-category" and "between-category" comparisons. These (e.g., forest1-forest1) should not be included in the within-category comparisons considered; rather, they should be excluded, so the fixations are always different but sometimes the comparisons are two retrievals of the same scene type (forest1-forest2), and other times different scene types (forest1-field1). (4) It is troubling that the results from the category reinstatement metric do not seem to conceptually align with past work; for example, a lot of work has shown category-level reinstatement in adults. Here the authors do not show any category-level reinstatement in adults (yet they do in children), which generally seems extremely unexpected given past work and I would guess has to do with the operationalization of the metric.

2. I did not see any compelling statistical evidence for the claim of less robust consolidation in children. Specifically in terms of the behavioural results of retention of the remote items at 1 vs 14 days, shown in Figure 2B, the authors conclude that memory consolidation is less robust in children (line 246). Yet they do not report statistical evidence for this point, as there was no interaction of this effect with the age group. Children had worse memory than adults overall (in terms of a main effect - i.e. across recent and remote items). If it were consolidation-specific, one would expect that the age differences are bigger for the remote items, and perhaps even most exaggerated for the 14-day-old memories. Yet this does not appear to be the case based on the data the authors report. Therefore, the behavioural differences in retention do not seem to be consolidation specific, and therefore might have more to do with differences in encoding fidelity or retrieval processes more generally across the groups. This should be taken into account when interpreting the findings.

3. Please clarify which analyses were restricted to correct retrievals only. The univariate analyses states that correct and incorrect trials were modelled separately, but does not say which were considered in the main contrast (I assume correct only?). The item specific reinstatement analysis states that only correct trials were considered, but the category-level reinstatement analysis does not say. Please include this detail.

4. To what extent could performance differences be impacting the differences observed across age groups? I think (see prior comment) that the analyses were probably limited to correct trials, which is helpful, but still yields pretty big differences across groups in terms of the amount of data going into each analysis. In general, children showed more attenuated neural effects (e.g., recent/remote or session effects); could this be explained by their weaker memory? Specifically, if only correct trials are considered that means that fewer trials would be going into the analysis for kids, especially for the 14-day remote memories, and perhaps pushing the remove > recent difference for this condition towards 0. The authors might be able to address this analytically; for example, does the remote > recent difference in the univariate data at day 14 correlate with day 14 memory?

5. Some of the univariate results reporting is a bit strange, as they are relying upon differences between retrieval of 1- vs. 14-day memories in terms of the recent vs. report difference, and yet don't report whether the regions are differently active for recent and remote retrieval. For example in Figure 3A, neither anterior nor posterior hippocampus seem to be differentially active for recent vs. remote memories for either age group (i.e., all data is around 0). This difference from zero or lack thereof seems important to the message - is that correct? If so, can the authors incorporate descriptions of these findings?

6. Please provide more details about the choices available for locations in the 3AFC task. (1) Were they different each time, or always the same? If they are always the same, could this be a motor or stimulus/response learning task? (2) Do the options in the 3AFC always come from the same area - in which case the participant is given a clue as to the gist of the location/memory? Or are they sometimes randomly scattered across the image (in which case gist memory, like at a delay, would be sufficient for picking the right option)? Please clarify these points and discuss the logic/impact of these choices on the interpretation of the results.

7. Often p values are provided but test statistics, effect sizes, etc. are not - please include this information. It is at times hard to tell whether the authors are reporting main effects, interactions, pairwise comparisons, etc.

8. There are not enough methodological details in the main paper to make sense of the results. For example, it is not clear from reading the text that there are new object-location pairs learned each day.

9. The retrieval task does not seem to require retrieval of the scene itself, and as such it would be helpful for the authors to both explain their reasoning for this task to measure reinstatement. Strictly speaking, participants could just remember the location of the object on the screen. Was it verified that children and adults were recalling the actual scene rather than just the location (e.g. via self-report)? It's possible that there may be developmental differences in the tendency to reinstate the scene depending on e.g., their strategy.

10. In general I found the Introduction a bit difficult to follow. Below are a few specific questions I had.

a. At points findings are presented but the broader picture or take-home point is not expressed directly. For example, lines 112-127, these findings can all be conceptualized within many theories of consolidation, and yet those overarching frameworks are not directly discussed (e.g., that memory traces go from being more reliant on the hippocampus to more on the neocortex). Making these connections directly would likely be helpful for many readers.

b. Lines 143-153 - The comparison of the Tompary & Davachi (2017) paper with the Oedekoven et al. (2017) reads like the two analyses are directly comparable, but the authors were looking at different things. The Tompary paper is looking at organization (not reinstatement); while the Oedekoven et al. paper is measuring reinstatement (not organization). The authors should clarify how to reconcile these findings.

c. Line 195-6: I was confused by the prediction of "stable involvement of HC over time" given the work reviewed in the Introduction that HC contribution to memory tends to decrease with consolidation. Please clarify or rephrase.

d. Lines 200-202: I was a bit confused about this prediction. Firstly, please clarify whether immediate reinstatement has been characterized in this way for kids versus adults. Secondly, don't adults retain gist more over long delays (with specific information getting lost), at least behaviourally? This prediction seems to go against that; please clarify.

Reviewer #3 (Public Review):

Summary:<br /> This study aimed to understand the neural correlates of memory recall over short (1-day) and long (14-days) intervals in children (5-7 years old) relative to young adults. The results show that children recall less than young adults and that this is accompanied by less activation (relative to young adults) in brain networks associated with memory retrieval.

Strengths:<br /> This paper is one of few investigating long-term memory (multiple days) in a developmental population, an important gap in the field. Also, the authors apply a representational similarity analysis to understand how specific memories evolve over time. This analysis shows how the specificity of memories decreases over time in children relative to adults. This is an interesting finding.

Weaknesses:<br /> Overall, these results are consistent with what we already know: recall is worse in children relative to adults (e.g., Cycowicz et al., 2001) and children activate memory retrieval networks to a lesser extent than adults (Bauer et al, 2017).

It seems that the reduced activation in memory recall networks is likely associated with less depth of memory encoding in children due to inattentiveness, reduced motivation, and documented differences in memory strategies. In regards to this, there was consideration of IQ, sex, and handedness but these were not included as covariates as they were not significant although I note p<.16 suggests there was some level of association nonetheless. Also, IQ is measured differently for the children and adults so it's not clear these can be directly contrasted. The authors suggest the instructed elaborative encoding strategy is effective for children and adults but the reference in support of this (Craik & Tulving, 1975) does not seem to support this point.

Reviewer #2 (Public Review):

Schommartz et al. present a manuscript characterizing neural signatures of reinstatement during cued retrieval of middle-aged children compared to adults. The authors utilize a paradigm where participants learn the spatial location of semantically related item-scene memoranda which they retrieve after short or long delays. The paradigm is especially strong as the authors include novel memoranda at each delayed time point to make comparisons across new and old learning. In brief, the authors find that children show more forgetting than adults, and adults show greater engagement of cortical networks after longer delays as well as stronger item-specific reinstatement. Interestingly, children show more category-based reinstatement, however, evidence supports that this marker may be maladaptive for retrieving episodic details. The question is extremely timely both given the boom in neurocognitive research on the neural development of memory, and the dearth of research on consolidation in this age group. Also, the results provide novel insights into why consolidation processes may be disrupted in children. Despite these strengths, there are quite a few important design and analytical choices that derail my enthusiasm for the paper. If the authors could address these concerns, this manuscript would provide a solid foundation to better understand memory consolidation in children.

Reviewer #2 (Public Review):

In this paper, Boi et al. thoroughly classified the electrophysiological and morphological characteristics of serotonergic and dopaminergic neurons in the DRN and examined the alterations of these neurons in the 6-OHDA-induced mouse PD model. Using whole-cell patch clamp recording, they found that 5-HT and dopamine (DA) neurons in the DRN are electrophysiologically well-distinguished from each other. In addition, they characterized distinct morphological features of 5-HT and DA neurons in the DRN. Notably, these specific features of 5-HT and DA neurons in the DRN exhibited different changes in the 6-OHDA-induced PD model. Then the authors utilized desipramine (DMI) to separate the effects of nigrostriatal DA depletion and noradrenalin (NA) depletion which are induced by 6-OHDA. Interestingly, protection from NA depletion by DMI pretreatment reversed the changes in 5-HT neurons, while having a minor impact on the changes in DA neurons in the DRN. These data indicate that the role of NA lesion in the altered properties of DRN 5-HT neurons by 6-OHDA is more critical than the one of DA lesion.

Overall, this study provides foundational data on the 5-HT and DA neurons in the DRN and their potential involvement in PD symptoms. Given the defects of the DRN in PD, this paper may offer insights into the cellular mechanisms that may underlie non-motor symptoms associated with PD. Despite the importance of the primary claim proposed by the authors, however, several weaknesses undermine the significance of the data.

Reviewer #1 (Public Review):

Summary:<br /> People with Parkinson's disease often experience a variety of nonmotor symptoms, the biological bases of which remain poorly understood. Johansson et al began to study the potential roles of the dorsal raphe nucleus (DRN) degeneration in the pathophysiology of neuropsychiatric symptoms in PD.

Strengths:<br /> Johansson et al validated a transgenic reporter mouse line that can reliably label dopaminergic neurons in the DRN. This brain region shows severe neurodegeneration and has been proposed to contribute to the manifestation of neuropsychiatric symptoms in PD. Using this mouse line (and others), Johansson and colleagues characterized electrophysiological and morphological phenotypes of dopaminergic and serotoninergic neurons in the raphe nucleus. This study involved very careful topographical registration of recorded neurons to brain slices for post hoc immunohistochemical validation of cell identification, making it an elegant and thorough piece of work.

In relevance to PD pathophysiology, the authors evaluated the physiological and morphological changes of DRN serotoninergic and dopaminergic neurons after a partial loss of nigrostriatal dopamine neurons, which serves as a mouse model of early parkinsonian pathology. Importantly, the authors identified a series of physiological and morphological changes of subtypes of DRN neurons that depend on nigral dopaminergic neurodegeneration, LC adrenergic neurodegeneration, or both.

Overall, the study was well-designed, and the data were well-presented in this well-written manuscript.

Weaknesses:<br /> Caveats that should be mentioned include:

1) While desipramine experiments provide clues about the potential role of adrenaline loss in electrophysiological and morphological changes in the Figs. 3-5, a complementary set of experiments is needed to confirm these findings. For example, how might selective LC adrenergic neurodegeneration affect cellular physiology and morphology in the DRN? Can the observed phenotypes in Figs 3-4 be rescued by adrenergic receptor agonists?

2) It should be kept in mind that the key experiments of this study were conducted using mouse models of parkinsonism. Thus, these models cannot recapitulate the complexity of PD pathology and circuit dysfunction.

Reviewer #3 (Public Review):

Summary:<br /> Using ex vivo electrophysiology and morphological analysis, Boi et al. investigate the electrophysiological and morphological properties of serotonergic and dopaminergic subpopulations in the dorsal raphe nucleus (DRN). They performed labor-intensive and rigorous electrophysiology with posthoc immunohistochemistry and neuronal reconstruction to delineate the two major cell classes in the DRN: DRN-DA and DRN-5HT, named according to their primary neurotransmitter machinery. They find that the dopaminergic (DRN-DA) and serotonergic (DRN-5HT) neurons are electrophysiologically and morphologically distinct, and are altered following striatal injection of the toxin 6-OHDA. However, these alterations were largely prevented in DRN-5HT neurons by pre-treatment with desipramine. These findings suggest an important interplay between catecholaminergic systems in healthy and parkinsonian conditions, as well as a relationship between neuronal structure and function.

Strengths:<br /> A large, well-validated dataset that will be a resource for others.<br /> Complementary electrophysiological and anatomical characterizations.<br /> Conclusions are justified by the data.<br /> Relevant for basic scientists interested in DRN cell types and physiology.<br /> Relevant for those interested in serotonin and/or DRN neurons in Parkinson's Disease.

Weaknesses:<br /> Given the scope of the author's questions and hypotheses, I did not identify any major weaknesses.

Reviewer #1 (Public Review):

Koumoundourou et al., identify a pathway downstream of Bcl11b that controls synapse morphology and plasticity of hippocampal mossy fiber synapses. Using an elegant combination of in vivo, ex vivo, and in vitro approaches, the authors build on their previous work that indicated C1ql2 as a functional target of Bcl11b (De Bruyckere et al., 2018). Here, they examine the functional implications of C1ql2 at MF synapses in Bcl11b cKO mice and following C1ql2 shRNA. The authors find that Bcl11b KO and shRNA against C1ql2 significantly reduces the recruitment of synaptic vesicles and impairs LTP at MF synapses. Importantly, the authors test a role for the previously identified C1ql2 binding partner, exon 25b-containing Nrxn3 (Matsuda et al., 2016), as relevant at MF synapses to maintain synaptic vesicle recruitment. To test this, the authors developed a K262E C1ql2 mutant that disrupts binding to Nrxn3. Curiously, while Bcl11b KO and C1ql2 KD largely phenocopy (reduced vesicle recruitment and impaired LTP), only vesicle recruitment is dependent on C1ql2-Nrxn3 interactions. These findings provide new insight into the functional role of C1ql2 at MF synapses. While the authors convincingly demonstrate a role for C1ql2-Nrxn3(25b+) interaction for vesicle recruitment and a Nrxn3(25b+)-independent role for C1ql2 in LTP, the underlying mechanisms remain inconclusive. Additionally, a discussion of how these findings relate to previous work on C1ql2 at mossy fiber synapses and how the findings contribute to the biology of Nrxn3 would increase the interpretability of this work.

Reviewer #2 (Public Review):

This manuscript describes experiments that further investigate the actions of the transcription factor Bcl11b in regulating mossy fiber (MF) synapses in the hippocampus. Prior work from the same group had demonstrated that loss of Bcl11b results in loss of MF synapses as well as a decrease in LTP. Here the authors focus on a target of Bcl11b a secreted synaptic organizer C1ql2 which is almost completely lost in Bcl11b KO. Viral reintroduction of C1ql2 rescues the synaptic phenotypes, whereas direct KD of C1ql2 recapitulates the Bcl1 phenotype. C1ql2 itself interacts directly with Nrxn3 and replacement with a binding deficient mutant C1q was not able to rescue the Bcl11b KO phenotype. Overall there are some interesting observations in the study, however there are also some concerns about the measures and interpretation of data.

The authors state that they used a differential transcriptomic analysis to screen for candidate targets of Bcl11b, yet they do not present any details of this screen. This should be included and at the very least a table of all DE genes included. It is likely that many other genes are also regulated by Bcl11b so it would be important to the reader to see the rationale for focusing attention on C1ql2 in this study.

All viral-mediated expression uses AAVs which are known to ablate neurogenesis in the DG (Johnston DOI: 10.7554/eLife.59291) through the ITR regions and leads to hyperexcitability of the dentate. While it is not clear how this would impact the measurements the authors make in MF-CA3 synapses, this should be acknowledged as a potential caveat in this study.

The authors claim that the viral re-introduction "restored C1ql2 protein expression to control levels. This is misleading given that the mean of the data is 2.5x the control (Figure 1d and also see Figure 6c). The low n and large variance are a problem for these data. Moreover, they are marked ns but the authors should report p values for these. At the least, this likely large overexpression and variability should be acknowledged. In addition, the use of clipped bands on Western blots should be avoided. Please show the complete protein gel in primary figures of supplemental information.

Measurement of EM micrographs: As prior work suggested that MF synapse structure is disrupted the authors should report active zone length as this may itself affect "synapse score" defined by the number of vesicles docked. More concerning is that the example KO micrographs seem to have lost all the densely clustered synaptic vesicles that are away from the AZ in normal MF synapses e.g. compare control and KO terminals in Fig 2a or 6f or 7f. These terminals look aberrant and suggest that the important measure is not what is docked but what is present in the terminal cytoplasm that normally makes up the reserve pool. This needs to be addressed with further analysis and modifications to the manuscript.

The study also presents correlated changes in MF LTP in Bcl11b KO which are rescued by C1ql2 expression. It is not clear whether the structural and functional deficits are causally linked and this should be made clearer in the manuscript. It is also not apparent why this functional measure was chosen as it is unlikely that C1ql2 plays a direct role in presynaptic plasticity mechanisms that are through a cAMP/ PKA pathway and likely disrupted LTP is due to dysfunctional synapses rather than a specific LTP effect. The authors should consider measures that might support the role of Bcl11b targets in SV recruitment during the depletion of synapses or measurements of the readily releasable pool size that would complement their findings in structural studies.<br /> Bcl11b KO reduces the number of synapses, yet the I-O curve reported in Supp Fig 2 is not changed. How is that possible? This should be explained.

Matsuda et al DOI: 10.1016/j.neuron.2016.04.001 previously reported that C1ql2 organizes MF synapses by aligning postsynaptic kainate receptors with presynaptic elements. As this may have consequences for the functional properties of MF synapses including their plasticity, the authors should report whether they see deficient postsynaptic glutamate receptor signaling in the Bcl11b KO and rescue in the C1ql2 re-expression.

Reviewer #3 (Public Review):

Overall, this is a strong manuscript that uses multiple current techniques to provide specific mechanistic insight into prior discoveries of the contributions of the Bcl11b transcription factor to mossy fiber synapses of dentate gyrus granule cells. The authors employ an adult deletion of Bcl11b via Tamoxifen-inducible Cre and use immunohistochemical, electron microscopy, and electrophysiological studies of synaptic plasticity, together with viral rescue of C1ql2, a direct transcriptional target of Bcl11b or Nrxn3, to construct a molecular cascade downstream of Bcl11b for DG mossy fiber synapse development. They find that C1ql2 re-expression in Bcl11b cKOs can rescue the synaptic vesicle docking phenotype and the impairments in MF-LTP of these mutants. They also show that C1ql2 knockdown in DG neurons can phenocopy the vesicle docking and plasticity phenotypes of the Bcl11b cKO. They also use artificial synapse formation assays to suggest that C1ql2 functions together with a specific Nrxn3 splice isoform in mediating MF axon development, extending these data with a C1ql2-K262E mutant that purports to specifically disrupt interactions with Nrxn3. All of the molecules involved in this cascade are disease-associated and this study provides an excellent blueprint for uncovering downstream mediators of transcription factor disruption. Together this makes this work of great interest to the field. Strengths are the sophisticated use of viral replacement and multi-level phenotypic analysis while weaknesses include the linkage of C1ql2 with a specific Nrxn3 splice variant in mediating these effects.

Here is an appraisal of the main claims and conclusions:

1. C1ql2 is a downstream target of Bcl11b which mediates the synaptic vesicle recruitment and synaptic plasticity phenotypes seen in these cKOs. This is supported by the clear rescue phenotypes of synapse anatomy (Fig.2) and MF synaptic plasticity (Fig.3). One weakness here is the absence of a control assessing over-expression phenotypes of C1ql2. It's clear from Fig.1D that viral rescue is often greater than WT expression (totally expected). In the case where you are trying to suppress a LoF phenotype, it is important to make sure that enhanced expression of C1ql2 in a WT background does not cause your rescue phenotype. A strong overexpression phenotype in WT would weaken the claim that C1ql2 is the main mediator of the Bcl11b phenotype for MF synapse phenotypes.

2. Knockdown of C1ql2 via 4 shRNAs is sufficient to produce the synaptic vesicle recruitment and MF-LTP phenotypes. This is supported by clear effects in the shRNA-C1ql2 groups as compared to nonsense-EGFP controls. One concern (particularly given the use of 4 distinct shRNAs) is the potential for off-target effects, which is best controlled for by a rescue experiment with RNA-insensitive C1ql2 cDNA as opposed to nonsense sequences, which may not elicit the same off-target effects.

3. C1ql2 interacts with Nrxn3(25b+) to facilitate MF terminal SV clustering. This claim is theoretically supported by the HEK cell artificial synapse formation assay (Fig.5), the inability of the K262-C1ql2 mutation to rescue the Bcl11b phenotype (Fig.6), and the altered localization of C1ql2 in the Nrxn1-3 deletion mice (Fig.7). Each of these lines of experimental evidence has caveats that should be acknowledged and addressed. Given the hypothesis that C1ql2 and Nrxn3b(25b) are expressed in DG neurons and work together, the heterologous co-culture experiment seems strange. Up till now, the authors are looking at pre-synaptic function of C1ql2 since they are re-expressing it in DGNs. The phenotypes they are seeing are also pre-synaptic and/or consistent with pre-synaptic dysfunction. In Fig.5, they are testing whether C1ql2 can induce pre-synaptic differentiation in trans, i.e. theoretically being released from the 293 cells "post-synaptically". But the post-synaptic ligands (Nlgn1 and and GluKs) are not present in the 293 cells, so a heterologous synapse assay doesn't really make sense here. The effect that the authors are seeing likely reflects the fact that C1ql2 and Nrxn3 do bind to each other, so C1ql2 is acting as an artificial post-synaptic ligand, in that it can cluster Nrxn3 which in turn clusters synaptic vesicles. But this does not test the model that the authors propose (i.e. C1ql2 and Nrxn3 are both expressed in MF terminals). Perhaps a heterologous assay where GluK2 is put into HEK cells and the C1ql2 and Nrxn3 are simultaneously or individually manipulated in DG neurons?

4. K262-C1ql2 mutation blocks the normal rescue through a Nrxn3(25b) mechanism (Fig.6). The strength of this experiment rests upon the specificity of this mutation for disrupting Nrxn3b binding (presynaptic) as opposed to any of the known postsynaptic C1ql2 ligands such as GluK2. While this is not relevant for interpreting the heterologous assay (Fig.5), it is relevant for the in vivo phenotypes in Fig.6. Similar approaches as employed in this paper can test whether binding to other known postsynaptic targets is altered by this point mutation.

5. Altered localization of C1ql2 in Nrxn1-3 cKOs. These data are presented to suggest that Nrx3(25b) is important for localizing C1ql2 to the SL of CA3. Weaknesses of this data include both the lack of Nrxn specificity in the triple a/b KOs as well as the profound effects of Nrxn LoF on the total levels of C1ql2 protein. Some measure that isn't biased by this large difference in C1ql2 levels should be attempted (something like in Fig.1F).

Reviewer #3 (Public Review):

This study demonstrates that from fish to mammals CIB2/3 is required for hearing, revealing the high degree of conservation of CIB2/3 function in vertebrate sensory hair cells. The modeling data reveal how CIB2/3 may affect the conductance of the TMC1/2 channels that mediate mechanotransduction, which is the process of converting mechanical energy into an electrical signal in sensory receptors. This work will likely impact future studies of how mechanotransduction varies in different hair cell types.

One caveat is that the experiments with the mouse mutants are confirmatory in nature with regard to a previous study by Wang et al., and the authors use lower resolution tools in terms of function and morphological changes. Another is that the modeling data is not supported by electrophysiological experiments, however, as mentioned above, future experiments may address this weakness.

Reviewer #1 (Public Review):

This reviewed preprint is a bit of Frankenstein monster, as it crams together three quite different sets of data. It is essentially three papers combined into one-one paper focused on the role of CIB2/CIB3 in VHCs, one on the role of CIB2/CIB3 in zebrafish, and one on structural modeling of a CIB2/3 and TMC1/2 complex. The authors try to combine the three parts with the overarching theme of demonstrating that CIB2/3 play a functionally conserved role across species and hair cell types, but given the previous work on these proteins, especially Liang et al. (2021) and Wang et al. (2023), this argument doesn't work very well. My sense is that the way the manuscript is written now, the sum is less than the individual parts, and the authors should consider whether the work is better split into three separate papers.

The most important shortcoming is the novelty of the work presented here. In line 89 of the introduction the authors state "However, whether CIB2/3 can function and interact with TMC1/2 proteins across sensory organs, hair-cell types, and species is still unclear." They make a similar statement in the first sentence of the discussion and generally use this claim throughout the paper as motivation for why they performed the experiments. Given the data presented in the Liang et al. (2021) and Wang et al. (2023 papers), however, this statement is not well supported. Those papers clearly demonstrate a role for CIB2/CIB3 in auditory and vestibular cells in mice. Moreover, there is also data in Riazuddin et al. (2012) paper that demonstrates the importance of CIB2 in zebrafish and Drosophila. I think the authors are really stretching to describe the data in the manuscript as novel. Conceptually, it reads more as solidifying knowledge that was already sketched out in the field in past studies.

There is one exception, however, and that is the last part of the manuscript. Here structural studies (AlphaFold 2 modeling, NMR structure determination, and molecular dynamics simulations) bring us closer to the structure of the mammalian TMCs, alone and in complex with the CIB proteins. Moreover, the structural work supports the assignment of the TMC pore to alpha helices 4-7.

Reviewer #2 (Public Review):

The paper 'Complexes of vertebrate TMC1/2 and CIB2/3 proteins 1 form hair-cell mechanotransduction cation channels' by Giese and coworkers is quite an intense reading. The manuscript is packed with data pertaining to very different aspects of MET apparatus function, scales, and events. I have to praise the team that combined molecular genetics, biochemistry, NMR, microscopy, functional physiology, in-vivo tests for vestibulo-ocular reflexes, and other tests for vestibular dysfunction with molecular modeling and simulations. The authors nicely show the way CIBs are associated with TMCs to form functional MET channels. The authors clarify the specificity of associations and elucidate the functional effects of the absence of specific CIBs and their partial redundancy.

Joint Public Review:

The authors report the first use of the bacterial Tus-Ter replication block system in human cells. A single plasmid containing two divergently oriented five-fold TerB repeats was integrated on chromosome 12 of MCF7 cells. ChIP and PLA experiments convincingly demonstrate the occupancy of Tus at the Ter sites in cells. Using an elegant Single Molecule Analysis of Replicated DNA (SMARD) assay, compelling data demonstrate the replication block at Ter sites dependent on the presence of the protein. As an orthogonal method to demonstrate fork stalling, ChIP data show the accumulation of the replicative helicase component MCM3 and the repair protein FANCM around the Ter sites. Previous published work from the Scully and Hickson laboratories showed that Ter sites do not perturb replication fork progression and consistently the data show that the observed effects are dependent on expression of the Tus protein. The SMARD data reveal that about one third of the forks are arrested at Tus/Ter but it is unclear for how long forks remain stalled. Fork stalling led to a highly localized gammaH2AX response, as monitored by ChIP using primer pairs spread along the integrated plasmid carrying the Ter sites. This response was shown to be dependent on ATR using the ATR inhibitor VE-822. This contrasts with a single Cas9-induced DSB between the two Ter sites, which causes a more spread gammaH2AX response measured at two sites flanking the DSB. The difference between the DSB and the Tus-induced stall is very significant. Interestingly, despite evidence for ATR activation through the gammaH2AX response, no evidence for phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 could be found under fork stalling conditions. The global replication inhibitor hydroxyurea (HU) elicited phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33. In this context, it would have been of interest to examine if a single DSB in the Ter region leads to phosphorylation of ATR-T1989, CHK1-S345, or RPA2-S33 and cell cycle arrest. The replication inhibitor HU led to an increase in gamma H2AX foci consistent with a global replication stress response. Overall, this is a well written manuscript, and the data provide convincing evidence that the Tus-Ter system poses a site-specific replication fork block in MCF7 cells leading to a localized ATR-dependent DNA damage checkpoint response that is distinct from the more global response to HU or DSBs.

Joint Public Review:

Summary:<br /> Cook, Watt, and colleagues previously reported that a mouse model of Spinocerebellar ataxia type 6 (SCA6) displayed defects in BDNF and TrkB levels at an early disease stage. Moreover, they have shown that one month of exercise elevated cerebellar BDNF expression and improved ataxia and cerebellar Purkinje cell firing rate deficits. In the current work, they attempt to define the mechanism underlying the pathophysiological changes occurring in SCA6. For this, they carried out RNA sequencing of cerebellar vermis tissue in 12-month-old SCA6 mice, a time when the disease is already at an advanced stage, and identified widespread dysregulation of many genes involved in the endo-lysosomal system. Focusing on BDNF/TrkB expression, localization, and signaling they found that, in 7-8 month-old SCA6 mice early endosomes are enlarged and accumulate BDNF and TrkB in Purkinje cells. Curiously, TrkB appears to be reduced in the recycling endosomes compartment, despite the fact that recycling endosomes are morphologically normal in SCA6. In addition, the authors describe a reduction in the Late endosomes in SCA6 Purkinje cells associated with reduced BDNF levels and a probable deficit in late endosome maturation.

Strengths:<br /> The article is well written, and the findings are relevant for the neuropathology of different neurodegenerative diseases where dysfunction of early endosomes is observed. The authors have provided a detailed analysis of the endo-lysosomal system in SCA6 mice. They have shown that TrkB recycling to the cell membrane in recycling endosomes is reduced, and the late endosome transport of BDNF for degradation is impaired. The findings will be crucial in understanding underlying pathology. Lastly, the deficits in early endosomes are rescued by chronic administration of 7,8-DHF.

Weaknesses:<br /> The specificity of BDNF and TrkB immunostaining requires additional controls, as it has been very difficult to detect immunostaining of BDNF. In addition, in many of the figures, the background or outside of Purkinje cell boundaries also exhibits a positive signal.

One important concern about the conclusions is that the RNAseq experiment was conducted in 12-month-old SCA6 mice suggesting that the defects in the endo-lysosomal system may be caused by other pathophysiological events and, likewise, the impairment in BDNF signaling may also be indirect, as also noted by the authors. Indeed, Purkinje cells in SCA6 mice have an impaired ability to degrade other endocytosed cargo beyond BDNF and TrkB, most likely because of trafficking deficits that result in a disruption in the transport of cargo to the lysosomes and lysosomal dysfunction. Moreover, the beneficial effects of 7,8-DHF treatment on motor coordination may be caused by 7,8-DHF properties other than the putative agonist role on TrkB. Indeed, many reservations have been raised about using 7,8-DHF as an agonist of TrkB activity. Several studies have now debunked (Todd et al. PlosONE 2014, PMID: 24503862; Boltaev et al. Sci Signal 2017, PMID: 28831019) or at the very least questioned (Lowe D, Science 2017: see Discussion: https://www.science.org/content/blog-post/those-compounds-aren-t-what-you-think-they-are Wang et al. Cell 2022 PMID: 34963057). Another interpretation is that 7,8-DHF possesses antioxidant activity and neuroprotection against cytotoxicity in HT-22 and PC12 cells, both of which do not express TrkB (Chen et al. Neurosci Lett 201, PMID: 21651962; Han et al. Neurochem Int. 2014, PMID: 24220540). Thus, while this flavonoid may have a beneficial effect on the pathophysiology of SCA6, it is most unlikely that mechanistically this occurs through a TrkB agonistic effect considering the potent anti-oxidant and anti-inflammatory roles of flavonoids in neurodegenerative diseases (Jones et al. Trends Pharmacol Sci 2012, PMID: 22980637).

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Overall, the authors have significantly improved the manuscript, but there is still an unclarified point. In response to the inquiry in the initial review on how extent E80A KI mice function as a pathological model of dominant CoRD, the authors add data (Figures S7) and described the sixth section in the discussion. However, the authors mentioned that it is technically too challenging because of a small number of cones. The point is not clear to me, but it is possible to analyze cone differentiation and degeneration by immunostaining at multiple stages even though cone number is small. Cone arrestin and S- and M-opsins become positive at early postnatal stages in the mouse retina. Cone arrestin seems earlier than cone opsins. Cones seem born by detecting RXRg at P0, but are cone arrestin and/or cone opsins expressed in early postnatal E80A/+ retina? If positive, how about an apoptosis marker? If negative, it seems to be a cone development phenotype rather than cone degeneration phenotype. If so, authors should modify the expression to say that the E80A retina underlies CoRD-like phenotype. It seems an overstatement.

Reviewer #1 (Public Review):

The manuscript by Zheng et al. examined the disease-causing mechanisms of two missense mutations within the homeodomain (HD) of CRX protein. Both mutations were found in humans and can produce severe dominant retinopathy. The authors investigated the two CRX HD mutants via in vitro DNA-binding assay (Spec-seq), in vivo chromatin-binding assay (ChIP-seq), in vivo expression assay of downstream target genes (RNA-seq), and retinal histological and functional assays. They concluded that p.E80A increased the transactivation activity of CRX and resulted in precocious photoreceptor differentiation, whereas p.K88N significantly changed the binding specificity of CRX and led to defects in photoreceptor differentiation and maintenance. The authors performed a significant amount of analyses. The claims are sufficiently supported by the data. The results not only uncovered the underlying disease-causing mechanisms, but also can significantly improve our understanding of the interaction between HD-TF and DNA during development.

Reviewer #2 (Public Review):

Zheng et al., investigated the molecular and functional mechanisms of two homeodomain missense mutations causing human retinal photoreceptor degeneration diseases in photoreceptor development regulated by the CRX transcription factor. They analyzed the E80A mutation associated with dominant cone-rod dystrophy (CRD) and the K88N mutation associated with dominant Leber Congenital Amaurosis (LCA). The authors found that E80A CRX binds to the same target DNA sites as WT CRX, but the binding specificity of K88N CRX is altered from that of WT in an in vitro assay. They generated Crx(E80A) and Crx(K88N) KI mice and performed ChIP assay and observed that K88N CRX binds to novel genomic regions from the WT-binding sites, while E80A binds to the WT sites. In addition, using the KI mice, they found that E80A and K88N differently affect the expression of Crx target genes. The authors may want to provide explicit clarification on whether CRX E80A mice exhibit cone development and/or degeneration defects.

This study is well executed with proper and solid methodologies, and the manuscript is clearly written. This study gives us the insights into how single missense CRX mutations lead to different types of human retinal photoreceptor degeneration diseases.

Reviewer #3 (Public Review):

Ghasemahmad et al. examined behavioral and neurochemical responses of male and female mice to vocalizations associated with mating and restraint. The authors made two significant and exciting discoveries. They revealed that the affective content of vocalizations modulated both behavioral responses and the release of acetylcholine (ACh) and dopamine (DA) but not serotonin (5-HIAA) in the basolateral amygdala (BLA) of male and female mice. Moreover, the results show sex-based differences in behavioral responses to vocalizations associated with mating. The authors conclude that behavior and neurochemical responses in male and female mice are experience-dependent and are altered by vocalizations associated with restraint and mating. The findings suggest that ACh and DA release may shape behavioral responses to context-dependent vocalizations. The study has the potential to significantly advance our understanding of how neuromodulators provide internal-state signals to the BLA while an animal listens to social vocalizations; however, multiple concerns must be addressed to substantiate their conclusions.

Major concerns:

1. The authors normalized all neurochemical data to the background level obtained from a single pre-stimulus sample immediately preceding playback. The percentage change from the background level was calculated based on a formula, and the underlying concentrations were not reported. The authors should report the sample and background concentrations to make the results and analyses more transparent. The authors stated that NE and 5-HT had low recovery from the mouse brain and hence could not be tracked in the experiment. The authors could be more specific here by relating the concentrations to ACh, DA, and 5-HIAA included in the analyses.

2. For the EXP group, the authors stated that each animal underwent 90-min sessions on two consecutive days that provided mating and restraint experiences. Did the authors record mating or copulation during these experiments? If yes, what was the frequency of copulation? What other behaviors were recorded during these experiences? Did the experiment encompass other courtship behaviors along with mating experiences? Was the female mouse in estrus during the experience sessions?

3. For the mating playback, the authors stated that the mating stimulus blocks contained five exemplars of vocal sequences emitted during mating interactions. The authors should clarify whether the vocal sequences were emitted while animals were mating/copulating or when the male and female mice were inside the test box. If the latter was the case, it might be better to call the playback "courtship playback" instead of "mating playback".

4. Since most differences that the authors reported in Figure 3 were observed in Stim 1 and not in Stim 2, it might be better to perform a temporal analysis - looking at behaviors and neurochemicals over time instead of dividing them into two 10-minute bins. The temporal analysis will provide a more accurate representation of changes in behavior and neurochemicals over time.

5. In Figures 2 and 3, the authors show the correlation between Flinching behavior and ACh concentration. The authors should report correlations between concentrations of all neurochemicals (not just ACh) and all behaviors recorded (not just Flinching), even if they are insignificant. The analyses performed for the stim 1 data should also be performed on the stim 2 data. Reporting these findings would benefit the field.

6. The mice used in the study were between p90 - p180. Although CBA/CaJ mice display normal hearing, sexual behaviors, and social behaviors for at least 1 year (Ohlemiller, Dahl, and Gagnon, JARO 11: 605-623, 2010), the age of the mice covers a range of 90 days. It would strengthen the authors' argument that the affective content of vocalizations modulated both behavioral responses and the release of acetylcholine (ACh) and dopamine (DA) but not serotonin (5-HIAA) in the basolateral amygdala (BLA) of male and female mice if there were no correlations between the magnitude of the neural responses and age.

7. The authors reported neurochemical levels estimated as the animals listened to the sounds played back. What about the sustained effects of changes in neurochemicals? Are there any potential long-term effects of social vocalizations on behavior and neurochemical levels? The authors might consider discussing long-term effects.

8. Histology from a single recording was shown in supplementary figure 1. It would benefit the readers if additional histology was shown for all the animals, not just the colored schematics summarizing the recording probe locations. Further explanation of the track location is also needed to help the readers. Make it clear for the readers which dextran-fluorescein labeling image is associated with which track in the schematic.

9. The authors did not control for the sounds being played back with a speaker. This control may be necessary since the effects are more pronounced in Stim 1 than in Stim 2. Playing white noise rather than restraint or courtship vocalizations would be an excellent control. However, the authors could perform a permutation analysis and computationally break the relationship between what sound is playing and the neurochemical data. This control would allow the authors to show that the actual neurochemical levels are above or below chance.

10. The authors indicated that each animal's post-vocalization session was also recorded. No data in the manuscript related to the post-vocalization playback period was included. This omission was a missed opportunity to show that the neurochemical levels returned to baseline, and the results were not dependent on the normalization process described in major concern #1. The data should be included in the manuscript and analyzed. It would add further support for the model described in Figure 6.

11. The authors could use a predictive model, such as a binary classifier trained on the CSF sampling data, to predict the type of vocalizations played back. The predictive model could support the conclusions and provide additional support for the model in Figure 6.

Reviewer #3 (Public Review):

Using the zebrafish model, this paper by Kraus A. et al., described the anti-virus response in the Olfactory bulb (OB) neurons and microglia. This paper used the behavioral test, neuron calcium imaging, and single-cell transcriptomic analysis. Importantly, this paper discovered that following IHNV infection, the OB neuron increased Pacap expression, which likely protects the neuron cells and mediates the anti-viral defense response. Overall, the findings presented in this paper are quite interesting.

Major strength:<br /> (1) The author demonstrated for the first time that zebrafish OSN neurons sense the IHNV viruses and transmit the viral signal to OB neurons. The zebrafish can be used as a new system to investigate the viral-neuron interaction and understand the mechanisms of how the neurons in the CNS to viral infection through the peripheral chemosensory system.

(2) This paper generated the first zebrafish OB sc-RNA sequencing data. The sc-RNA sequencing data generated in this paper will also help other zebrafish researchers who study the OB neurons.

Major weakness:<br /> The experiment results presented in this paper are not well-integrated. For example, it is unclear how the behavioral phenotype is connected to the neuronal calcium phenotype. It is also unclear how the behavioral or neuronal calcium imaging results is connected to the scRNA sequencing result.

Reviewer #1 (Public Review):

Kraus et al. investigated transcriptional responses to transient exposure to infectious hematopoietic necrosis virus in the brain of adult zebrafish using single cell RNA-Seq methods. The authors discovered valuable evidence for immune responses in microglial clusters within minutes of viral exposure, and longer term changes in neuronal populations one day after viral treatment. The strength of the study is the RNA-Seq data which will act as a valuable resource for the zebrafish community. Their discoveries from the RNA-Seq studies are convincing, where they find a neuropeptide called PACAP enriched in neuronal populations a day after viral exposure, which exhibit antiviral activity. 

The authors select the 1 day time point post-infection based on initial behavioral experiments, the evidence for which is modest at best. While the experiments with larval animals are more substantiated, they use adults for their RNA-Seq experiments. The behavioral phenotype in adults is a marginal decrease in velocity 1 day after infection. The authors could have performed other tests associated with sickness behaviors, or even characterized the locomotion in the open field experiment with more in-depth analysis (for example, the larval experiments had more information regarding turning angles).

Reviewer #2 (Public Review):

Kraus, Aurora et al. investigated the potential immune response of the olfactory bulb after exposure of the infectious hematopoietic necrosis virus (IHNV), via the olfactory epithelia. Specifically, they show that a) viral-specific neuronal activation of "OSNs" (Crypt cells), b) changes in behaviour of both adult and larval zebrafish after viral exposure, c) Pituitary adenylate-cyclase-activating polypeptide (PACAP), was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV

Although the paper does have strengths in principle, the weaknesses of the manuscript are that these strengths are not directly demonstrated and the referencing of the manuscript omits many references important for the understanding of the questions and the results of the study. Furthermore, the data presented are not sufficient to fully support the key claims in the manuscript. In particular:

a) Viral-specific neuronal activation of OSNs:<br /> What type of neurons? The authors are a bit elusive and do not clearly state that the neurons are crypt cells (Sepahi et al.: rainbow trout) which have a very specific axonal projection to the brain and whose response characteristics are not well characterized (see work of Korsching lab). Crypt cells are not present in the olfactory epithelia of mammals. Furthermore, in their previous work the crypt cells die; so how do they think the (inflammatory) virus response is transmitted to the olfactory bulbs in order to protect the brain?<br /> The authors state from previous work that they never detected virus in the brain, but why would they? Does INHV move trans-synaptically?<br /> The neuronal activity was monitored using a pan-neuronal marker thus these data are of limited use when trying to understand the role of neuronal activity (crypt cells) in the IHNV-triggered activity: the authors may be looking at a generalized inflammation response, and the image presented is not particularly informative it is difficult to decipher the results. The authors assume IHNV is an odorant without carefully ruling out the possibility of a generalized inflammation response.<br /> b) Changes in behaviour of both adult and larval zebrafish after viral exposure:<br /> What is the motivating question for looking at behaviour of the virus infected animals? Do we know the effects of crypt cell loss on the behaviour in any fish species? Authors need to build a better conceptual framework for the behaviour experiments.

c) Pituitary adenylate-cyclase-activating polypeptide (PACAP) was enriched when assayed by single cell transcriptomic profiling of cells in the OB after OSNs are exposed to IHNV. Authors draw many generous conclusions from limited data. Authors seem to have forgotten to cite papers previously published showing that PACAP-38 has anti-viral activities in fish (VHSV: trout) such as: Velasquez et al 2020, First in vivo evidence of pituitary adenylate cyclase-activating polypeptide antiviral activity in teleost.<br /> The histology for PACAP presented in the manuscript is not convincing. The antibody is against the human form of PACAP thus any labelling should be treated with caution (and called PACAP-38-like).

Summary: The authors need to better develop their model (perhaps a diagram would be helpful) explaining exactly which neurons are transmitting the information. Because of the elusive nature of some referencing and the skirting of important issues such as clearly stating which neurons are affected (crypt cells), what the point of the behaviour is (relate to neuronal type infected by virus), and, the lack of an antibody specific to the zebrafish protein, the model appears to be built on an unstable base.

Joint Public Review:

In this manuscript, the authors challenge the fundamental concept that all neurons are derived from ectoderm. The key points of the authors argument are as follows:

1) Roughly half of the cells in the small intestinal longitudinal muscle-myenteric plexus (LM-MP) that express a pan-neuronal marker do not, by lineage tracing, appear to be derived from the neural crest.

2) Lineage tracing and marker gene imaging suggest that these non-neural crest derived neurons originate in the mesoderm, leading to their designation as mesodermal-derived enteric neurons (MENs).

3) Single-cell sequencing of LM-MP tissues confirms the mesodermal origin of MENs.

4) MENs progressively replace neural crest derived enteric neurons as mice age, eventually representing the bulk of the EN population.

There is broad agreement among the reviewers that the identification and description of this cell population is important, and that the failure of these cells to be labeled by neural crest lineage tracers is not artifactual. The work with transgenic lines is convincing that some presumptive neurons in the enteric nervous system (ENS) likely originate from an alternative source in the postnatal intestine and that this population increases in aging mice.

There is, however, ongoing disagreement between the authors and reviewers about whether the authors' provocative and potentially paradigm-changing proposal that these are neurons of mesodermal origin has been established. While the authors believe they have addressed the reviewers' concerns in multiple rounds of review (much of this prior to submission), the reviewers remain unconvinced and continue to request additional data and analyses.

A key premise of the preprint review system is that the best interests of science are not served by endlessly litigating disagreements around papers by either compelling the authors to do extensive and expensive additional experiments that they do not believe to be necessary or by treating the authors' claim as established in the face of continued skepticism. Accordingly the editor believes it is time to present this work, which everyone agrees contains important observations and valuable data, along with the following editor's synthesis of the reviewers' concerns and author responses about the question of these cells' origins. We encourage anyone interested in the details to review the already posted reviews and authors' response.

The following key issues have been raised during review:

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin?

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments?

* Does the genomic data establish that the sub-population of cells the authors focus on are of mesodermal origin?

* Are there alternative explanations for the lineage tracing and genomic observations than a mesodermal origin?

* Is the lineage tracing and marker gene expression data definitive as to mesodermal origin? *

The proximal evidence that the authors present for a mesodermal origin of the non-NC derived cells is presented in Figure 2, which establishes the presence, via lineage tracing of Tek+ and Mesp1+ (and therefore mesoderm derived) and Hu+ (and therefore neuronal) cells. The fraction of lineage labeled cells in each case (~50%) corresponds roughly to the fraction of cells that do not appear to be NC derived.

The reviewers raise several technical questions about the lineage tracing experiments, including issues of incomplete labeling, ectopic labeling and toxicity. The authors have addressed each of these with data and/or citations, and the editor believes they have demonstrated, subject to the broader limits of lineage tracing experiments, that there are Hu+ cells in the tissue that are derived from cells that do not express NC markers and that do express mesodermal markers.

One reviewer raised the question of whether these cells are neurons. This appears to the editor to be a valid question, in that specific neuronal activity of these cells has not been established. But the authors' argument is persuasive that their Hu+ state would have led them to be designated neurons and that changing that designation based on not being derived from NC is circular. However the possibility that, despite this accepted designation, these cells are not functionally neurons should be noted by readers.

* Are the cells analyzed in the genomic experiments the same as those identified in the lineage tracing experiments, and does this data establish mesodermal origin? *

To provide orthogonal evidence for the presence of mesodermally derived enteric neurons, the authors carried out single-cell sequencing of dissociated cells from hand-dissected longitudinal muscle - myenteric plexus (LM-MP) tissue. They use standard methods to identify clusters of cells with similar transcriptomes, and designate, based on marker gene expression, two clusters to be neural crest derived enteric neurons (NENs) and mesoderm derived enteric neurons (MENs). However the reviewers raised several issues about the designation of the cells MENs, and therefore their equation with the cells identified in lineage tracing.

While the logic behind specific choices made in the single-cell analysis is not always clear in the manuscript, such as why genes not-specific to MENs were used to identify the MEN cluster and how genes were selected for subsequent analysis (although both issues are explained better in the authors' response to reviewers), they in the end identify a single large cluster that has the characteristics of MENs (it expresses both neuronal and mesodermal markers) that is (by immunohistochemistry) broadly associated with the previously described tissue MENs.

The standard methods for the delineation of clusters in single-cell sequencing data (which the authors use) are stochastic and defy statistical interpretation, and the way these data and analyses are used is often subjective. The editor shares the reviewers' confusion about aspects of the analysis, but also finds the authors' assertions that they have described a cluster of cells that express both neuronal and mesodermal genes, and that this cluster corresponds to the tissue MENs described in lineage tracing, to be broadly sound.

The biggest weakness in the single-cell data and analysis - identified by all reviewers - is the massive overrepresentation of MENs relative to NENs. The authors' explanation - that some cells are more sensitive to manipulations required to prepare cells for sequencing - is certainly well-represented in the literature and is therefore plausible. But it isn't fully satisfactory, especially because it undermines the notion that the MENs and NENs are functionally equivalent (though one could argue in response that increased fragility of NENs is why they are progressively replaced by MENs).

There are many additional questions about the single cell analysis that are difficult to resolve with the data in hand. I think everyone would agree that an ideal analysis would have more cells, deeper sequencing, and comprehensive validation of the identity of each cluster of cells. But given the time and expense required to carry out such experiments, we cannot demand them, and must take the data for what they are rather than what they could be. And in the end, it is the editors' view that these data and analyses bolster the authors' claims, without conclusively establishing them. That is, these data should neither be dismissed nor, on their own, considered definitive.

* Are there alternative explanations for the data than that they are mesodermally derived neurons? *

As discussed above, the reviewers generally agree that the lineage tracing experiments are careful and well-executed, and the authors have provided data that demonstrates that the data are highly unlikely to be due to either incomplete or ectopic lineage marking. The reviewers raise several possible alternative hypotheses, some based on the literature and some based on the genomic data. The authors discuss each in detail in their response. The editor would note that, at this stage in the history of single-cell analysis, the criteria for using single cell sequencing data to establish cell type and cell origin is are not well established, and that neither the presence nor absence of specific sets of genes in single cells should not, for both technical and biological reasons, be considered dispositive as to identity.

* Additional aspects of paper: *

There are additional intriguing aspects of the paper, especially the increase in the number of MENs relative to NENs over time, suggesting functional replacement of one population with the other, and some evidence for and speculation about what might be regulating this evolution. However these are somewhat secondary points relative to the central question at hand of whether the authors have discovered a population of mesodermally derived neurons.

* Editor's summary and comment: *

The editor believes it is a fair summary to say that the authors believe they have gone to great lengths to provide multiple lines of evidence that support their hypothesis, but that these reviewers, while appreciating the potential importance of the authors' discovery of an unusual cell type, are not yet convinced of its origin.

In an ideal world, the authors, reviewers and editor would all ultimately agree on what claims the data presented in a paper supports, and indeed this is what the traditional journal publishing system tries to achieve. But the system fails in cases like this where no consensus between authors and reviewers can be reached, as it neither makes sense to "accept" the paper and imply that it has been endorsed by the reviewers, nor to "reject" it and keep the work in peer review limbo.

There is certainly enough here to warrant the idea and the data and arguments behind it being digested and considered by people in the field. It may very well be that the authors - who have spent years working on this problem and likely know more about this population of cells than anyone on Earth - are right that they have discovered something that changes how we think about the development of the nervous system. To the extent the reviewers are representative, people are likely to need additional data to be convinced. But it is time to put that to the test.