7,348 Matching Annotations
  1. Jan 2024
    1. Joint Public Review:

      Summary:

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

      Strengths:

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

      Weaknesses:

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

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

    1. Reviewer #1 (Public Review):

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

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

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

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

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

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

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

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

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

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

    1. Reviewer #1 (Public Review):

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

    1. Reviewer #1 (Public Review):

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

    1. Reviewer #2 (Public Review):

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

    1. Reviewer #1 (Public Review):

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

    1. Reviewer #1 (Public Review):

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

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

  2. Dec 2023
    1. 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.

    1. Reviewer #1 (Public Review):

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

      Strengths:

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

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

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

      Weaknesses:

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

    1. Reviewer #1 (Public Review):

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

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

    1. Reviewer #1 (Public Review):

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

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

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

    1. Reviewer #1 (Public Review):

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

      Specific comments:

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

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

      Summary:

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

      Strengths:

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

      Weaknesses:

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

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

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

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

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

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

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

    1. Reviewer #1 (Public Review):

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

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

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this paper, the authors investigate the impact of fecal microbiota transfer (FMT) on intestinal recovery from enterotoxigenic E. coli infection following antibiotic treatment. Using a piglet model of intestinal infection, the authors demonstrate that FMT reduces weight loss and diarrhea and enhances the expression of tight junction proteins. Sequencing analysis of the intestinal microbiota following FMT showed significant increases in Akkermansia muciniphila and Bacteroides fragilis. Using additional mouse and organoid models, the authors examine the impact of these microbes on intestinal recovery and modulation of the Wnt signaling pathway. Overall, the data support the notion that FMT following ETEC infection is beneficial, however, additional investigation is required to fully elucidate the mechanisms involved.

      Strengths:<br /> Initial experiments used a piglet model of infection to test the value of FMT on recovery from E. coli. The FMT treatment was beneficial and the authors provide solid evidence that the treatment increased the diversity of the microbiota and enhanced the recovery of the intestinal epithelium. Sequencing data highlighted an increase in Akkermansia muciniphila and Bacteroides fragilis after FMT.

      The mouse data are consistent with the observations in pigs, and reveal that daily gavage with A. muciniphila or B. fragilis enhances intestinal recovery based on histological analysis, expression of tight junction proteins, and analysis of intestinal barrier function.

      The authors demonstrate the benefit of probiotic treatment following infection using a range of model systems.

      Weaknesses:<br /> Without sequencing the pre-infection pig microbiota or the FMT input material itself, it's challenging to firmly say that the observed bloom in Akkermansia muciniphila and Bacteroides fragilis stemmed from the FMT.

      The lack of details for the murine infection model, such as weight loss and quantification of bacterial loads over time, make it challenging for a reader to fully appreciate how treatment with Akkermansia muciniphila and Bacteroides fragilis is altering the course of infection. Bacterial loads of E. coli were only quantified at one time point, and the mice that received A. muciniphila and B. fragilis had very low levels of E. coli. Therefore, it is not clear if all mice were subjected to the same level of infection in the first place. The reduced translocation of E. coli to the organs and enhanced barrier function may just reflect the low level of infection in these mice. Further, the authors' conclusion that the effect is specific to A. muciniphila or B. fragilis would be more convincing if the experiments included an inert control bacterium, to demonstrate that gavage with any commensal microbe would not elicit a similar effect.

      Many of the conclusions in the study are drawn from the microscopy results. However, the methods describing both light microscopy and electron microscopy lack sufficient detail. For example, it is not clear how many sections and fields of view were imaged or how the SEM samples were prepared and dehydrated. The mucus layer does not appear to be well preserved, which would make it challenging to accurately measure the thickness of the mucus layer.

      Gene expression data appears to vary across the different models, for example, Wnt3 expression in mice versus organoids. Additional experiments may be required to clarify the mechanisms involved. Considering that both of the bacteria tested elicited similar changes in Wnt signaling, this pathway might be broadly modulated by the microbiota.

      The unconventional choice to not include references in the results section makes it challenging for the reader to put the results in context with what is known in the field. Similarly, there is a lack of discussion acknowledging that B. fragilis is a potential pathogen, associated with intestinal inflammation and cancer (Haghi et al. BMC Cancer 19, 879 (2019) ), and how this would impact its utility as a potential probiotic.

    1. Reviewer #1 (Public Review):

      Tiedje et al. investigated the transient impact of indoor residual spraying (IRS) followed by seasonal malaria chemoprevention (SMC) on the plasmodium falciparum parasite population in a high transmission setting. The parasite population was characterized by sequencing the highly variable DBL$\alpha$ tag as a proxy for var genes, a method known as varcoding. Varcoding presents a unique opportunity due to the extraordinary diversity observed as well as the extremely low overlap of repertoires between parasite strains. The authors also present a new Bayesian approach to estimating individual multiplicity of infection (MOI) from the measured DBL$\alpha$ repertoire, addressing some of the potential shortcomings of the approach that have been previously discussed. The authors also present a new epidemiological endpoint, the so-called "census population size", to evaluate the impact of interventions.

      This study provides a nice example of how varcoding technology can be leveraged, as well as the importance of using diverse genetic markers for characterizing populations, especially in the context of high transmission. The data are robust and clearly show the transient impact of IRS in a high transmission setting, however, some aspects of the analysis are confusing.

      1) Approaching MOI estimation with a Bayesian framework is a well-received addition to the varcoding methodology that helps to address the uncertainty associated with not knowing the true repertoire size. It's unfortunate that while the authors clearly explored the ability to estimate the population MOI distribution, they opted to use only MAP estimates. Embracing the Bayesian methodology fully would have been interesting, as the posterior distribution of population MOI could have been better explored.

      2) The "census population size" endpoint has unclear utility. It is defined as the sum of MOI across measured samples, making it sensitive to the total number of samples collected and genotyped. This means that the values are not comparable outside of this study, and are only roughly comparable between strata in the context of prevalence where we understand that approximately the same number of samples were collected. In contrast, mean MOI would be insensitive to differences in sample size, why was this not explored? It's also unclear in what way this is a "census". While the sample size is certainly large, it is nowhere near a complete enumeration of the parasite population in question, as evidenced by the extremely low level of pairwise type sharing in the observed data.

      3) The extraordinary diversity of DBL$\alpha$ presents challenges to analyzing the data. The authors explore the variability in repertoire richness and frequency over the course of the study, noting that richness rapidly declined following IRS and later rebounded, while the frequency of rare types increased, and then later declined back to baseline levels. The authors attribute this to fundamental changes in population structure. While there may have been some changes to the population, the observed differences in richness as well as frequency before and after IRS may also be compatible with simply sampling fewer cases, and thus fewer DBL$\alpha$ sequences. The shift back to frequency and richness that is similar to pre-IRS also coincides with a similar total number of samples collected. The authors explore this to some degree with their survival analysis, demonstrating that a substantial number of rare sequences did not persist between timepoints and that rarer sequences had a higher probability of dropping out. This might also be explained by the extreme stochasticity of the highly diverse DBL$\alpha$, especially for rare sequences that are observed only once, rather than any fundamental shifts in the population structure.

    1. Reviewer #1 (Public Review):

      Summary: TRAIL (Tumor necrosis factor (TNF)-related apoptosis-inducing ligand) is a potent inducer of apoptosis in tumor cells. Initially, this finding raised high expectations on the possibility to induce tumor-specific apoptosis by activation of TRAIL-receptors DR4 and DR5. However, attempted TRAIL-based anti-tumor therapies failed so far, and several tumor types were found to resist TRAIL-induced apoptosis. Yin Luo and colleagues provide an explanation for these observations with the potential to provide a new important biomarker for future TRAIL-based anti-tumor therapies and to reduce resistance. The authors reveal that sensitivity towards TRAIL correlates inversely with heparan sulfate (HS) expression levels at the surface of tumor cells, suggesting that HS functions as a tumor suppressor. These observations are explained by two two mechanisms: First, HS induces the assembly of higher-order oligomers from soluble TRAIL trimers, and second, TRAIL and HS form a ternary complex with DR5 to promote its cellular internalization. Therefore, this timely and important work provides a better mechanistic understanding of TRAIL-induced apoptosis and TRAIL resistance of some tumor types, with the potential to improve therapy.

      Strengths: The major novel finding of this study is that extracellular heparan sulfate (HS) acts as a positive regulator of TRAIL-induced tumor cell apoptosis, and that HS expression of different tumor cell lines correlates with their capacity to induce cell death. The authors first show by affinity chromatography and SPR that murine and human TRAIL bind strongly to heparin (heparin is a highly sulfated, and thus strongly negatively charged form of HS that is derived from connective tissue type mast cells), and identify three basic amino acids on the TRAIL N-terminus that are required for the interaction. Size exclusion chromatography (SEC) and multiangle light scattering (MALS) revealed that TRAIL exists as a trimer that requires a minimum heparin length of 8 sugar residues for binding, and small angle X-ray scattering (SAXS) showed that TRAIL interaction with longer oligosaccharides induced higher order multimerization of TRAIL. Consistent with these biochemical and biophysical analyses, HS on tumor cells contributes to TRAIL-binding to their cell surface and subsequent apoptosis. The study also describes domain swapping observed by TRAIL trimer crystallization, and demonstrates different degrees of HS core protein and DR receptor expression in different tumor cell types. These findings are well supported and together with the advanced and established methodology used by the authors are the strengths of this paper. The paper will be of great interest to medical biologists studying TRAIL-resistance of tumors, to biologists interested in DR4 and DR5 receptor function and the effects of receptor internalization, and to glycobiologists aiming to understand the multiple important roles that HS plays in development and disease. The authors also raise the important point (and support it well) that routine heparin treatment of cancer patients potentially interferes with TRAIL-based therapies, providing one possible reason for their failure.

      Weaknesses: Despite the importance and the clear strengths of the paper, some of its aspects could have been developed further. First, the authors findings that HS at the tumor surface promotes TRAIL binding, and that HS promotes TRAIL-induced breast cancer and myeloma cell apoptosis, are based on pre-treatment of cells with heparinase to remove surface HS prior to TRAIL-treatment, or on the addition of soluble heparin to compete with cell-surface HS for TRAIL binding. A more direct way to establish such new HS function could have been the genetic manipulation of cancer cells to overexpress HS or to express less or undersulfated HS. Changed susceptibility of these cells to TRAIL-induced apoptosis would have greatly underlined the physiological significance of the authors findings. Second, the mechanistics of TRAIL-induced, HS-modulated tumor cell apoptosis could have been more clearly defined. For example, the authors demonstrate convincingly that cell surface HS is essential for TRAIL-induced apoptosis in MDA-MB-453 breast cancer cells, and show that a tumor cell line (IM-9 cells) that expresses HS and the core protein to which HS is attached to only limited degrees is the most resistant to TRAIL-induced apoptosis. However, Indeed, the authors later also report that cell surface HS promotes TRAIL-induced myeloma cell apoptosis regardless of the sensitivity levels, and that other factors - the degree of TRAIL multimerization or DR4/DR5 receptor internalization - are also important. Therefore, HS levels do not play a sole determining role in TRAIL-induced apoptosis. Along the same line, the authors show that RPMI-8226 cell-surface HS promotes DR5 internalization despite the absence of direct DR5/heparin interactions. This suggests that HS at the cell surface may also affect apoptosis indirectly. To test this hypothesis, it would have been worthwhile to include the binding characteristics and HS-dependent internalization of DR4 into the study.

    1. Reviewer #1 (Public Review):

      The idea is that inversions capture genetic variants that have antagonistic effects on male sexual success (via some display traits) and survival of females (or both sexes) until reproduction. A series of simulations are presented and show that the scenario works at least under some conditions. While a polymorphism at a single locus with large antagonistic effects can be maintained for a certain range of parameters, a second such variant with somewhat smaller effects tends to be lost unless closely linked. It becomes much more likely for genomically distant variants that add to the antagonism to spread if they get trapped in an inversion; the model predicts this should drive the accumulation of sexually antagonistic variants on the inversion versus standard haplotype, leading to the evolution of haplotypes with very strong cumulative antagonistic pleiotropic effects. This idea has some analogies with one of the predominant hypotheses for the evolution of sex chromosomes, and the authors discuss these similarities. To provide empirical support for this idea, the authors study the dynamics of inversions in population cages over one generation, tracking their frequencies through amplicon sequencing, from the parental generation through embryos to aged adults of either sex. Out of four inversions included in the experiment, two show patterns consistent with antagonistic effects on male sexual success (competitive paternity) and the survival of offspring, especially females, until old age, which the authors interpret as consistent with their theory.

      This is an interesting idea, and the authors should be praised for combining a model with experimental data. However, in addition to the potential for improvement of presentation (details below), the study has some substantial weaknesses that could be addressed with additional simulations and additional experiments.

      (1) The authors claim that the negative frequency dependence that maintains polymorphism in their model results from a non-linear relationship between the display trait and sexual success. I am not convinced about that. It seems to me that the "best of n" female choice implemented in the model (l. 741ff and Figure 2) does not lead to negative frequency dependence. Let p be the frequency of the competitively inferior male genotype. Assuming no noise in the male display, a female will mate with an inferior male only if all males among the n males sampled by the female are of the inferior genotype, which will be the fraction p^n, the remaining 1-p^n matings will go to the superior males. Thus, per capita, the inferior males will achieve (p^n)/p or p^(n-1) matings while the per-capita matings per superior male will be (1-p^n)/(1-p). Thus, the ratio of the mating success of the inferior to the superior males will be (1-p) p^(n-1) / (1- p^n). For the range of p from 0 to 1, this is an increasing function of p. E.g., with n = 2, the sexual fitness of the inferior genotype relative to that of the superior phenotype is p/(1+p). Thus, at least in the absence of noise in the mate choice, this generates positive rather than negative frequency dependence. Maybe I missed something, but the authors do not provide support for their claim about the negative frequency-dependence of sexual selection in their simulations. To do so they could (1) extract the relationship between the relative mating success of the two male types from the simulations and (2) demonstrate that polymorphism is not maintained if the relationship between male display trait and mating success is linear.

      (2) The authors only explore versions of the model where the survival costs are paid by females or by both sexes. We do not know if polymorphism would be maintained or not if the survival cost only affected males, and thus if sexual antagonism is crucial.

      (3) The authors assume no cost to aneuploidy, with no justification. Biologically, investment in aneuploid eggs would not be recoverable by Drosophila females and thus would potentially act against inversions when they are rare.

      (4) The authors appear to define balanced polymorphism as a situation in which the average allele frequency from multiple simulation runs is intermediate between zero and one (e.g., Figure 3). However, a situation where 50% of simulation runs end up with the fixation of allele A and the rest with the fixation of allele B (average frequency of 0.5) is not a balanced polymorphism. The conditions for balanced polymorphism require that selection favors either variant when it is rare.

      (5) Possibly the most striking result of the experiment is the fact that for 14 out of 16 combinations of inversion x maternal background, the changes in allele frequencies between embryo and adult appear greater in magnitude in females than in males irrespective of the direction of change, being the same in the remaining two combinations. The authors interpret this as consistent with sexually antagonistic pleiotropy in the case of In(3L)Ok and In(3R)K. The frequencies of adult inversion frequencies were, however, measured at the age of 2 months, at which point 80% of flies had died. For all we know, this may have been 90% of females and 70% of males that died at this point. If so, it might well be that the effects of inversion on longevity do not systematically differ between the ages and the difference in Figure 9B results from the fact that the sample includes 30% longest-lived males and 10% longest-lived females.

      (6) Irrespective of the above problem, survival until the age of 2 months is arguably irrelevant from the viewpoint of fitness consequences and thus maintenance of inversion polymorphism in nature. It would seem that trade-offs in egg-to-adult survival (as assumed in the model), female fecundity, and possibly traits such as females resistance to male harm would be much more relevant to the maintenance of inversion polymorphisms.

      (7) The experiment is rather minimalistic in size, with four cages in total; given that each cage contains a different female strain, it essentially means N=1. The lack of replication makes statements like " In(2L)t and In(2R)NS each showed elevated survival with all maternal strains except ZI418N" (l. 493) unsubstantiated because the claimed special effect of ZI418N is based on a single cage subject to genetic drift and sampling error. The same applies to statements on inversion x female background interaction (e.g., l. 550), as this is inseparable from residual variation. It is fortunate that the most interesting effects appear largely consistent across the cages/female backgrounds. Still, I am wondering why more replicates had not been included.

    1. Reviewer #1 (Public Review):

      This manuscript presents a model in which combined action of the transporter-like protein DISP and the sheddases ADAM10/17 promote shedding of a mono-cholesteroylated Sonic Hedgehog (SHH) species following cleavage of palmitate from the dually lipidated precursor ligand. The authors propose that this leads to transfer of the cholesterol-modified SHH to HDL for solubilization. The minimal requirement for SHH release by this mechanism is proposed to be the covalently linked cholesterol modification because DISP could promote transfer of a cholesteroylated mCherry reporter protein to serum HDL. The authors used an in vitro system to demonstrate dependency on DISP/SCUBE2 for release of the cholesterol modified ligand. These results confirm previously published results from other groups (PMC3387659 and PMC3682496).

      A strength of the work is the use of a bicistronic SHH-Hhat system to consistently generate dually-lipidated ligand to determine the quantity and lipidation status of SHH released into cell culture media.

      Key shortcomings include the unusual normalization strategies used for many experiments and the lack of quantification/statistical analyses for several experiments. Due to these omissions, it is difficult to conclude that the data justify the conclusions. The significance of the data provided is overstated because many of the presented experiments confirm/support previously published work. The study provides a modest advance in understanding of the complex issue of SHH membrane extraction.

    1. Reviewer #1 (Public Review):

      The authors have previously employed micrococcal nuclease tethered to various Mcm subunits to the cut DNA to which the Mcm2-7 double hexamers (DH) bind. Using this assay, they found that Mcm2-7 DH are located on many more sites in the S. cerevisiae genome than previously shown. They then demonstrated that these sites have characteristics consistent with origins of DNA replication, including the presence of ARS consensus sequences, the location of very inefficient sites of initiation of DNA replication in vivo, and for the most part are free of nucleosomes. They contain a G-C skew and they locate to intergenic regions of the genome. The authors suggest, consistent with published single molecule results, that there are many more potential origins in the S. cerevisiae genome than previously annotated, but also conclude that many of the newly discovered Mcm2-7 DH are very infrequently used as active origins of DNA replication.

      The results are convincing and are consistent with prior observations. The analysis of the origin associated features is informative.

    1. Joint Public Review:

      This study provides evidence on the ability of sublethal imidacloprid doses to affect growth and development of honeybee larva. While checking the effect of doses that do not impact survival or food intake, the authors found changes in the expression of genes related to energy metabolism, antioxidant response, and P450 metabolism. The authors also identified cell death in the alimentary canal, and disturbances in levels of ROS markers, molting hormones, weight, and growth ratio. The study strengths come from employing these different approaches to investigate the impacts of imidacloprid exposure. The study weaknesses come from the lack of a in depth investigation and drawing many conclusions solely from punctual gene expression, that are not representative of complete biological processes. Though relevant to understand the impacts on neonicotinoid contamination on insect pollinators, the study conclusions should be carefully weighted as they are often not fully substantiated. Follow up studies using in-depth investigation and more robust methodological design testing whether the impacts observed lead to post-metamorphosis effects and impacts in the colony would have a significant impact.

    1. Reviewer #1 (Public Review):

      Precision guided sterile insect technology (pgSIT) is a means of mosquito vector control that aims to simultaneously kill females while generating sterile males for field release. These sterile males are expected to mate with 'wild' females resulting in very few eggs being laid or low hatching rates. Repeated releases are expected to result in the suppression of the mosquito population. This method avoids cumbersome sex-sorting while generating the sterile males. Importantly, until release, the two genetic elements that bring about female lethality and male sterility - the Cas9 and the gRNA carrying mosquitoes - are maintained as separate lines. They are crossed only prior to release, and therefore, this approach is considered to be more safe than gene drives.

      The authors had made a version of this pgSIT in their 2021 paper where they targeted *β-Tubulin 85D*, which is only expressed in the male testes and its loss-of-function results in male sterility. In that pgSIT, they did not have female lethality, but generated flightless females by simultaneously targeted *myosin heavy chain,* which is expressed only in the female wings. Here the authors argue, that the survival of females is not ideal, and so modify their 2021 approach to achieve female lethality/sterility.

      To do this, they target two genes - the female specific isoform of Dsx and intersex. They use multiple gRNAs against these genes and validate their ability to cause female lethality/sterility. Having verified that these do indeed affect female fertility, they combine gRNAs against Dsx and ix to generate female lethality/sterility and use *β-Tubulin 85D* to generate male sterility (previously validated). When these gRNA mosquitoes are crossed to Cas9 and the progeny crossed to WT (the set-up for pgSIT), they find that very few eggs are laid, larval death is high, and what emerges are males or intersex progeny that are sterile.

      As this is the requirement for pgSIT, the authors then test if it is able to induce population suppression. To do this, they conduct cage trials and find that only when they use 20:1 or 40:1 ratio of pgSIT:WT cages, does the population crash in 4-5 generations. They model this pgSIT's ability to suppress a population in the wild. Unfortunately, I was not able to assess what parameters from their pgSIT were used in the model and therefore the predicted efficacy of their pgSIT, (though the range of 0-.1 is not great, given that the assessment is between 0-0.15).

      Finally, they also develop a SENSR with a rapid fluorescence read-out for detecting the transgene in the field. They show that this sensor is specific and sensitive, detecting low copy numbers of the transgene. This would be important for monitoring any release.

      Overall, the data are clear and well presented.

      Comments on revised version:

      The authors have addressed the major issues raised by reviewers related to off target effects, writing and figures, and comparisons with other vector control methods and claims made in passing.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In an era of increasing antibiotic resistance, there is a pressing need for the development of novel sustainable therapies to tackle problematic pathogens. In this study, the authors hypothesize that pyoverdines - metal-chelating compounds produced by fluorescent pseudomonads - can act as antibacterials by locking away iron, thereby arresting pathogen growth. Using biochemical, growth, and virulence assays on 12 opportunistic pathogens strains, the authors demonstrate that pyoverdines induce iron starvation, but this effect was highly context-dependent. This same effect has been demonstrated for plant pathogens, but not for human opportunistic pathogens exposed to natural siderophores. Only those pathogens lacking (1) a matching receptor to take up pyoverdine-bound iron and/or (2) the ability to produce strong iron chelators themselves experienced strong growth arrest. This would suggest that pyoverdines might not be effective against all pathogens, thereby potentially limiting the utility of pyoverdines as global antibacterials.

      Strengths:<br /> The work addresses an important and timely question - can pyoverdines be used as an alternative strategy to deal with opportunistic pathogens? In general, the work is well conducted with rigorous biochemical, growth, and virulence assays. The work is clearly written and the findings are supported by high-quality figures.

      Weaknesses:<br /> I do not think there are any 'weaknesses' as such. However, it is well known that siderophore production is highly plastic, typically being upregulated in response to metal limitation (as well as toxic metal stress). Did the authors quantify whether pyoverdine supplementation altered siderophore production in the focal pathogens (either through phenotypic assays / transcriptomics)? Could such a phenotypic plastic response result in an increased capacity to scavenge iron from the environment? Importantly, increased expression of siderophores has been shown to enhance pathogen virulence (e.g. Lear et al 2023: increased pyoverdine production is linked with increased virulence in Pseudomonas aeruginosa). I really appreciate the amount of work the authors have put into this study, but I would suggest expanding the discussion a bit to include a few sentences on (1) unintentional consequences of pyoverdine treatment (e.g. changes in gene expression and non-siderophore-related mutations (e.g. biofilm formation)) on disease dynamics/pathogen virulence , and (2) the efficacy of siderophore treatment under more natural conditions, i.e. when the pathogens have to compete with other species in the resident community (i.e. any other effects than resistance evolution through HGT of pyoverdine receptors as mentioned).

    1. Reviewer #1 (Public Review):

      Summary:<br /> The nuclease protein TnpB is ubiquitous across microorganisms. It is associated with the stabilization of transposable genetic elements and is a putative precursor of the RNA-guided endonuclease Cas9 from the CRISPR system. Despite its potential as a gene-editing tool, TnpB is not well understood. In this study, the authors use a fluorescence-based construct to individually quantify the transposable-element excision rate and the abundance of the two ancillary proteins TnpA and TnpB. They develop a mathematical model describing the role of TnpB in transposable-element stabilization.

      Strengths:<br /> The methodology (with schematic shown in Figure 1A) is powerful and sophisticated. The authors are able to de-convolve excision events from the individual abundances of TnpA and TnpB.

      Weaknesses:<br /> The claim that TnpB expression level correlates positively (and significantly) with the probability of a growth-disrupting integration (called 'b') is not well-supported by the data shown in Fig. 3D. The modelling of results shown in Figure 4 are not tied directly to the experimental data shown in Figures 1-3.

    1. Reviewer #1 (Public Review):

      Summary<br /> In this manuscript, Hagihara et al. characterized the relationship between the changes in lactate and pH and the behavioral phenotypes in different animal models of neuropsychiatric disorders at a large-scale level. The authors have previously reported that increased lactate levels and decreased pH are commonly observed in the brains of five genetic mouse models of schizophrenia (SZ), bipolar disorder (BD), and autism spectrum disorder (ASD). In this study, they expanded the detection range to 109 strains or conditions of animal models, covering neuropsychiatric disorders and neurodegenerative disorders. Through statistical analysis of the first 65 strains/conditions of animal models which were set as exploratory cohort, the authors found that most strains showed decreased pH and increased lactate levels in the brains. There was a significant negative correlation between pH and lactate levels both at the strain/condition level and the individual animal level. Besides, only working memory was negatively correlated with brain lactate levels. These results were successfully duplicated by studying the confirmative cohort, including 44 strains/conditions of animal models. In all strains/conditions, the lactate levels were not correlated with age, sex, or storage duration of brain samples.

      Strengths<br /> 1. The manuscript is well-written and structured. In particular, the discussion is really nice, covering many potential mechanisms for the altered lactate levels in these disease models.<br /> 2. Tremendous efforts were made to recruit a huge number of various animal models, giving the conclusions sufficient power.

      Weaknesses<br /> 1. The biggest concern of this study is the limited novelty. The point of "altered pH and/or lactate levels in the brains from human and rodent animals of neuropsychiatric disorders" has been reported by the same lab and other groups in many previous papers.<br /> 2. This study is mostly descriptive, lacking functional investigations. Although a larger cohort of animal models were studied which makes the conclusion more solid, limited conceptual advance is contributed to the relevant field, as we are still not clear about what the altered levels of pH and lactate mean for the pathogenesis of neuropsychiatric disorders.<br /> 3. The experiment procedure is also a concern. The brains from animal models were acutely collected without cardiac perfusion in this study, which suggests that resident blood may contaminate the brain samples. The lactate is enriched in the blood, making it a potential confounded factor to affect the lactate levels as well as pH in the brain samples.<br /> 4. The lactate and pH levels may also be affected by other confounded factors, such as circadian period, and locomotor activity before the mice were sacrificed. This should also be discussed in the paper.<br /> 5. Another concern is the animal models. Although previous studies have demonstrated that dysfunctions of these genes could cause related phenotypes for certain disorders, many of them are not acknowledged by the field as reliable disease models. Besides, gene deficiency could also cause many known or unknown unrelated phenotypes, which may contribute to the altered levels of lactate and pH, too. In this circumstance, the conclusion "pH and lactate levels are transdiagnostic endophenotype of neuropsychiatric disorders" is somewhat overstated.<br /> 6. The negative correlationship between pH and lactate is rather convincing. However, how much the contribution of lactate to pH is not tested. In addition, regarding pH and lactate, which factor contributes most to the pathogenesis of neuropsychiatric disorders is also unclear. These questions may need to be addressed in the future study.<br /> 7. The authorship is open to question. Most authors listed in this paper may only provide mice strains or brain samples. Maybe it is better just to acknowledge them in the acknowledgements section.<br /> 8. The last concern is about the significance of this study. Although the majority of strains showed increased lactate, some still showed decreased lactate levels in the brains. These results suggested that lactate or pH is an endophenotype for neuropsychiatric disorders, but it is hard to serve as a good diagnostic index as the change is not unidirectional in different disorders. In other words, the relationship between lactate level and neuropsychiatric disorders is not exclusive.

    1. Reviewer #1 (Public Review):

      Loss of skeletal muscle tissue from traumatic injury is debilitating. Restoring muscle mass and function remains a challenge. Using a mouse model, the authors performed punch biopsy injuries of the tibialis anterior in which the volume of muscle loss was varied to result in either successful muscle regeneration with a smaller injury or the unsuccessful outcome of fibrosis with a larger injury. For both conditions, a novel lipidomic profiling approach was used to evaluate pro-inflammatory and anti-inflammatory lipids at key time points post-injury with respect to collagen deposition, macrophage infiltration, muscle fiber regeneration, and force produced during isometric contractions. A key finding was that while all lipids increased at 3 days post-injury (dpi) and then declined through 14 dpi, pro-inflammatory lipids remained elevated during recovery from greater muscle loss which led to fibrosis. Maresin 1 was identified as an anti-inflammatory lipid that, when injected into injured muscle, reduced fibrosis, improved muscle regeneration, and partially restored the strength of contraction.

      Strengths: The metabolipidomic profiling demonstrated here represents a novel approach to identifying pro-inflammatory and anti-inflammatory mediators of successful vs unsuccessful skeletal muscle regeneration. These findings may translate into a new therapeutic approach for promoting successful regeneration following volumetric muscle loss.

      Weaknesses: Certain aspects of the data are overinterpreted; while some measures appear to have an adequate sample size to make sound conclusions, other measures are likely to lack sufficient statistical power given their variability. Presentation of the results would be strengthened by adhering to consistent terminology and labeling of figures throughout; specific examples are identified in recommendations to the authors. Several of the images used to illustrate differences between treatments are unconvincing because differences are not readily.

    1. Reviewer #1 (Public Review):

      In this work George et al. describe RatInABox, a software system for generating surrogate locomotion trajectories and neural data to simulate the effects of a rodent moving about an arena. This work is aimed at researchers that study rodent navigation and its neural machinery.

      Strengths:<br /> + The software contains several helpful features. It has the ability to import existing movement traces and interpolate data with lower sampling rates. It allows varying the degree to which rodents stay near the walls of the arena. It appears to be able to simulate place cells, grid cells, and some other features.<br /> + The architecture seems fine and the code is in a language that will be accessible to many labs.<br /> + There is convincing validation of velocity statistics. There are examples shown of position data, which seem to generally match between data and simulation.

      Weaknesses:<br /> + There is little analysis of position statistics. I am not sure this is needed, but the software might end up more powerful and the paper higher impact if some position analysis was done. Based on the traces shown, it seems possible that some additional parameters might be needed to simulate position/occupancy traces whose statistics match the data.<br /> + The overall impact of this work is somewhat limited. It is not completely clear how many labs might use this, or have a need for it. The introduction could have provided more specificity about examples of past work that would have been better done with this tool.<br /> + Presentation: Some discussion of case studies in Introduction might address the above point on impact. It would be useful to have more discussion of how general the software is, and why the current feature set was chosen. For example, how well does RatInABox deal with environments of arbitrary shape? T-mazes? It might help illustrate the tool's generality to move some of the examples in supplementary figure to main text - or just summarize them in a main text figure/panel.

    1. Reviewer #1 (Public Review):

      This article proposes a new statistical approach to identify which of several experimenter-defined strategies best describes a biological agent's decisions when such strategies are not fully observable by choices made in a given trial. The statistical approach is described as Bayesian but can be understood instead as computing a smoothed running average (with decay) of the strategies' success at matching choices, with a winner-take-all inference across the rules. The article tests the validity of this statistical approach by applying it to both simulated agents and real data sets in mice and humans. It focuses on dynamically changing environments, where the strategy best describing a biological agent may change rapidly.

      The paper asks an important question, and the analysis is well conducted; the paper is well-written and easy to follow. However, there are several concerns that limit the strength of the contribution. Major concerns include the framing of the method, considerations around the strategy space, limitations in how useful the technique may be, and missing details in analyses.

    1. Reviewer #1 (Public Review):

      Farhat-Younis and colleagues demonstrate tumor-specific IgM's capacity to induce tumor cell death in monocyte-derived dendritic cell cultures. They subsequently designed a chimeric receptor based on high-affinity FcRI. However, the authors found that the transfection process was more efficient when either the variable light or heavy chain was transfected individually rather than the entire scFv. This scFv construct led to an endoplasmic reticulum (ER) stress response and scFv degradation. A considerable portion of the manuscript is dedicated to the negative scFv expression results. The authors pivoted to a modified FcgRI capable of transmitting IgM signals. This represents a tremendous amount of work in the development of this chimeric receptor, the critical experiment showing efficacy in vivo was not presented, and instead various in vitro assays are shown. Thus, this manuscript will markedly benefit from showing improved responses to tumors in vivo when macrophages express FcgRI-IgM.

      1. In a mouse tumor model, the authors demonstrated that monocyte-derived dendritic cells (MoDCs) treated with IgG immune complexes (ICs) were more effective at preventing tumor growth compared to those treated with IgM ICs (as shown in Figure 1B). In Figure 1C, their in vitro experiments revealed that IgM resulted in tumor cell death, as well as increased production of nitric oxide (NO) and granzyme B.<br /> How do the authors reconcile IgG IC-treated MoDCs performing better in preventing tumors in vivo than IgM IC-treated MoDCs, despite the in vitro results with IgM-ICs. The authors speculate that IgG IC-treated MoDCs might trigger T cell immunity but do not show T cell involvement.

      2. The authors report distinct functional consequences of MoDCs incubated with tumor-IgG complexes and tumor IgM complexes. Tumor growth was inhibited and T cell immunity induced with the former. The latter, however, elicited robust anti-tumor killing. What happens if MoDCs are incubated with both IgG and IgM complexes? If this combined treatment induces effective killing and T cell memory, would this impact the design of the chimeric receptor to include IgG responsiveness as well?

      3. In Figure 5H, the authors demonstrate the ability of the chimeric receptor construct to deplete tumor cells in vitro. The ms would improve if the authors could show the chimeric receptor construct results in tumor cell death and/or prevention in an in vivo model. Similarly, if combined stimulation with IgG and IgM complexes enhances tumor response, this should be incorporated into the therapeutic strategy.

    1. Reviewer #1 (Public Review):

      This paper aims to explain recent experimental results that showed deactivating the PPC in rats reduced both the contraction bias and the recent history bias during working memory tasks. The authors propose a two-component attractor model, with a slow PPC area and a faster WM area (perhaps mPFC, but unspecified). Crucially, the PPC memory has slow adaptation that causes it to eventually decay and then suddenly jump to the value of the last stimulus. These discrete jumps lead to an effective sampling of the distribution of stimuli, as opposed to a gradual drift towards the mean that was proposed by other models. Because these jumps are single-trial events, and behavior on single events is binary, various statistical measures are proposed to support this model. To facilitate this comparison, the authors derive a simple probabilistic model that is consistent with both the mechanistic model and behavioral data from humans and rats. The authors show data consistent with model predictions: longer interstimulus intervals (ISIs) increase biases due to a longer effect over the WM, while longer intertrial intervals (ITIs) reduce biases. Finally, they perform new experiments using skewed or bimodal stimulus distributions, in which the new model better fits the data compared to Bayesian models.

      The mechanistic proposed model is simple and elegant, and it captures both biases that were previously observed in behavior, and how these are affected by the ISI and ITI (as explained above). Their findings help rethink whether our understanding of contraction bias is correct.

      On the other hand, the main proposal - discrete jumps in PPC - is only indirectly verified. The majority of the behavioral predictions stem from the probabilistic model, which is consistent with the mechanistic one, but does not necessitate it.<br /> The revised submission uses the self-paced nature of the experiments to confirm the systematic change in bias with inter-trial-interval, as predicted by the model. This analysis strengthens the hypothesis.

    1. Reviewer #1 (Public Review):

      Schmid et al. investigate the question of how sensory learning in animals and artificial networks is driven both by passive exposure to the environment (unsupervised) and from reinforcing feedback (supervised) and how these two systems interact. They first demonstrate in mice that passive exposure to the same auditory stimuli used in a discrimination task modify learning and performance in the task. Based on this data, they then tested how the interaction of supervised and unsupervised learning in an artificial network could account for the behavioural results.

      The clear behavioural impact of the passive exposure to sounds on accelerating learning is a major strength of the paper. Moreover, the observation that passive exposure had a positive impact on learning whether it was prior to the task or interleaved with learning sessions provides interesting constraints for modelling the interaction between supervised and unsupervised learning. A practical fallout for labs performing long training procedures is that the periods of active learning that require water-restriction could be reduced by using passive sessions. This could increase both experimental efficiency and animal well-being.

      The modelling section clearly exhibits the differences between models and the step-by-step presentation building to the final model provides the reader with a lot of intuition about how supervised and unsupervised learning interact. In particular the authors highlight situations in which the task-relevant discrimination does not align with the directions of highest variance, thus reinforcing the relevance of their conclusions for the complex structure of sensory stimuli. A great strength of these models is that they generate clear predictions about how neural activity should evolve during the different training regimes that would be exciting to test.

      As the authors acknowledge, the experimental design presented cannot clearly show that the effect of passive exposure was due to the specific exposure to task-relevant stimuli since there is no control group exposed to irrelevant stimuli. Studies have shown that exposure to a richer sensory environment, even in the adult, swiftly (ie within days) enhances responses even in the adult and even when the stimuli are different from those present in the task (1-3). Clearly distinguishing between these two options would require further experiments and could be a possible direction for future research.

      1. Mandairon, N., Stack, C. & Linster, C. Olfactory enrichment improves the recognition of individual components in mixtures. Physiol. Behav. 89, 379-384 (2006).<br /> 2. Alwis, D. S. & Rajan, R. Environmental enrichment and the sensory brain: The role of enrichment in remediating brain injury. Front. Syst. Neurosci. 8, 1-20 (2014).<br /> 3. Polley, D. B., Kvašňák, E. & Frostig, R. D. Naturalistic experience transforms sensory maps in the adult cortex of caged animals. Nature 429, 67-71 (2004).

    1. Reviewer #1 (Public Review):

      In this manuscript, the authors describe an improved miniscope they name "E-scope" combining in vivo calcium imaging with electrophysiological recording and use it to examine neural correlates of social interactions with respect to cerebellar and cortical circuits. Through correlations between electrophysiological single units of Purkinje cells and dentate nucleus neurons as well as with calcium signals imaging of neurons from the anterior cingulate cortex, the authors provide correlative data supporting the view that intracerebellar circuits and cerebello-cortical communications take part in the modulation of social behavior. In particular, the electrophysiological dataset reflects the PC-DN connection and strongly suggests its involvement in social interactions. Cross-correlations analyses between PC / DN single units and ACC calcium signals suggest that the recorded cerebellar and cortical structures both take part in the brain networks at play in social behavior.

      Comments on revised submission:

      While the authors have, to some extent, replied to most of my comments, they seem to have chosen not to respond to the part concerning the different types of social interactions that are not addressed in the manuscript, as also pointed out by reviewer 3. However, I feel that given the scope of the paper, which aims at demonstrating the value of the E-scope new device, this should not preclude the current study from being published.

    1. Reviewer #1 (Public Review):

      This is a clear and rigorous study of intracranial EEG signals in the prefrontal cortex during a visual awareness task. The results are convincing and worthwhile, and strengths include the use of several complementary analysis methods and clear results. The only methodological weakness is relatively small sample size of only 6 participants compared to other studies in the field. Interpretation weaknesses are claims that their task removes the confound of report (it does not), and claims of primacy in showing early prefrontal cortical involvement in visual perception using intracranial EEG (several studies already have shown this). Also the shorter reaction times for perceived vs not perceived stimuli (confident vs not confident responses) has been described many times previously and is not a new result.

    1. Reviewer #1 (Public Review):

      In the manuscript by Urban et al., the authors attempt to further delineate the role with which non-neuronal CNS cells play in the development of ALS. Towards this goal, the transmembrane signaling molecule ephrinB2 was studied. It was found that there is an increased expression of ephrinB2 in astrocytes within the cervical ventral horn of the spinal cord in a rodent model of ALS. Moreover, reduction of ephrinB2 reduced motoneuron loss and prevented respiratory dysfunction at the NMJ. Further driving the importance of ephrinB2 is an increased expression in the spinal cords of human ALS individuals. Collectively, these findings present compelling evidence implicating ephrinB2 as a contributing factor towards the development of ALS.

    1. Reviewer #1 (Public Review):

      In this study, Nuria Martin-Flores, Marina Podpolny and colleagues investigate the role of Dickkopf-3 (DKK3), a Wnt antagonist in synaptic dysfunction in Alzheimer's disease. Loss of synapses is a feature of Alzheimer's and other forms of dementia such as frontotemporal dementia and linked amyotrophic lateral sclerosis (FTD). The authors utilise a broad range of experimental approaches. They show that DKK3 levels are increased in Alzheimer's disease and that this occurs early in disease. This is an important finding since early disease changes are believed to be the most important. They also show increases in DKK3 in transgenic mouse models of Alzheimer's disease and that DKK3 knockdown restores synapse number and memory in one such model. Finally, they link these DKK3 increases to loss of excitatory synapses via the blockade of the Wnt pathway and subsequent activation of GSK3B; GSK3B is strongly linked to both Alzheimer's disease and FTD. The quality of the data is good and the conclusions well supported by these data. There are no major weaknesses. The findings support studies that target the Wnt pathway as a potential therapeutic for Alzheimer's disease.

    1. Reviewer #1 (Public Review):

      Jafarinia et al. have made an interesting contribution to unravel the molecular mechanisms underlying pathological phenotypes of repeat expansion of the C9orf72 gene.

      The repeat expression leads to expression of polyPR proteins. Using coarse-grained molecular dynamics simulations, the authors identify putative binding partners involved in nucleocytoplasmic transport (NCT), and conjecture that polyPR affects essential processes by binding to NCT-related proteins.

      The results are well-reported, but only putative, and need experimental support to be more conclusive. Also, comparison with results from all-atom MD simulations in explicit water could help verify the results. But even without these, the work is very useful as a first step to unravel the role of polyPR and related peptides.

    1. Joint Public Review:

      Summary:<br /> Guma and colleagues set out to compare to what extent differences in total and regional brain volumes, as measured by structural magnetic resonance imaging (MRI) are conserved or not, between humans and mice. The rationale for this work is to inform the best use of the mouse as a model system to carry out mechanistic studies of how sex differences arise in brain volumes, based on convergence to humans. This has practical implications for multiple fields in neuroscience. The authors find a modest convergence on these measures highlighting important areas for further mechanistic study.

      Strengths:<br /> The main strengths of the study lie in the use of a cross-species technology, i.e. structural MRI, using tools and methods that have been extensively validated.

      Weaknesses:<br /> Limitations of the study include, as acknowledged by the authors, the focus on a specific age range in mice and humans (which may not be congruent) and the lack of information regarding sex differences earlier or later in life. This has relevance with regard to the ages of onset for psychiatric and neurological disorders for example, which show apparent sex differences in prevalence. The paper also does provide data for an intermediate phylogenic level of analysis, such as data from primates. Lastly, these data do not provide any evidence as to the mechanisms underlying sex differences, when they arise, and to what extent they impact behavior.

    1. Reviewer #1 (Public Review):

      Summary: Using a cross-modal sensory selection task in head-fixed mice, the authors attempted to characterize how different rules reconfigured representations of sensory stimuli and behavioral reports in sensory (S1, S2) and premotor cortical areas (medial motor cortex or MM, and ALM). They used silicon probe recordings during behavior, a combination of single-cell and population-level analyses of neural data, and optogenetic inhibition during the task.

      Strengths: A major strength of the manuscript was the clarity of the writing and motivation for experiments and analyses. The behavioral paradigm is somewhat simple but well-designed and well-controlled. The neural analyses were sophisticated, clearly presented, and generally supported the authors' interpretations. The statistics are clearly reported and easy to interpret. In general, my view is that the authors achieved their aims. They found that different rules affected preparatory activity in premotor areas, but not sensory areas, consistent with dynamical systems perspectives in the field that hold that initial conditions are important for determining trial-based dynamics.

      Weaknesses: The manuscript was generally strong. The main weakness in my view was in interpreting the optogenetic results. While the simplicity of the task was helpful for analyzing the neural data, I think it limited the informativeness of the perturbation experiments. The behavioral read-out was low dimensional -a change in hit rate or false alarm rate- but it was unclear what perceptual or cognitive process was disrupted that led to changes in these read-outs. This is a challenge for the field, and not just this paper, but was the main weakness in my view. I have some minor technical comments in the recommendations for authors that might address other minor weaknesses.

      I think this is a well-performed, well-written, and interesting study that shows differences in rule representations in sensory and premotor areas and finds that rules reconfigure preparatory activity in the motor cortex to support flexible behavior.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This manuscript provides potentially important new information about ipsilateral cortical impact on locomotion. A number of issues need to be addressed.

      Strengths:<br /> The primary appeal and contribution of this manuscript are that it provides a range of different measures of ipsilateral cortical impact on locomotion in the setting of impaired contralateral control. While the pathways and mechanisms underlying these various measures are not fully defined and their functional impacts remain uncertain, they comprise a rich body of results that can inform and guide future efforts to understand cortical control of locomotion and to develop more effective rehabilitation protocols.

      Weaknesses:

      1. The authors state that they used a cortical stimulation location that produced the largest ankle flexion response (lines 102-104). Did other stimulation locations always produce similar, but smaller responses (aside from the two rats that showed ipsilateral neuromodulation)? Was there any site-specific difference in response to stimulation location?

      2. Figure 2: There does not appear to be a strong relationship between the percentage of spared tissue and the ladder score. For example, the animal with the mild injury (based on its ladder score) in the lower left corner of Figure 2A has less than 50% spared tissue, which is less spared tissue than in any animal other than the two severe injuries with the most tissue loss. Is it possible that the ladder test does not capture the deficits produced by this spinal cord injury? Have the authors looked for a region of the spinal cord that correlates better with the deficits that the ladder test produces? The extent of damage to the region at the base of the dorsal column containing the corticospinal tract would be an appropriate target area to quantify and compare with functional measures.

      3. Lines 219-221: The authors state that "phase-coherent stimulation reinstated the function of this muscle, leading to increased burst duration (90{plus minus}18% of the deficit, p=0.004, t-test, Fig. 4B) and total activation (56{plus minus}13% of the deficit, p=0.014, t-test, Fig. 3B). This way of expressing the data is unclear. For example, the previous sentence states that after SCI, burst duration decreased by 72%. Does this mean that the burst duration after stimulation was 90% higher than the -72% level seen with SCI alone, i.e., 90% + -72% = +18%? Or does it mean that the stimulation recovered 90% of the portion of the burst duration that had been lost after SCI, i.e., -72% * (100%-90%)= -7%? The data in Figure 4 suggests the latter. It would be clearer to express both these SCI alone and SCI plus stimulation results in the text as a percent of the pre-SCI results, as done in Figure 4.

      4. Lines 227-229: The authors claim that the phase-dependent stimulation effects in SCI rats are immediate, but they don't say how long it takes for these effects to be expressed. Are these effects evident in the response to the first stimulus train, or does it take seconds or minutes for the effects to be expressed? After the initial expression of these effects, are there any gradual changes in the responses over time, e.g., habituation or potentiation?

      5. Awake motor maps (lines 250-277): The analysis of the motor maps appears to be based on measurements of the percentage of channels in which a response can be detected. This analytic approach seems incomplete in that it only assesses the spatial aspect of the cortical drive to the musculature. One channel could have a just-above-threshold response, while another could have a large response; in either case, the two channels would be treated as the same positive result. An additional analysis that takes response intensity into account would add further insight into the data, and might even correlate with the measures of functional recovery. Also, a single stimulation intensity was used; the results may have been different at different stimulus intensities.

      6. Lines 858-860: The authors state that "All tests were one-sided because all hypotheses were strictly defined in the direction of motor improvement." By using the one-sided test, the authors are using a lower standard for assessing statistical significance that the overwhelming majority of studies in this field use. More importantly, ipsilateral stimulation of particular kinds or particular sites might conceivably impair function, and that is ignored if the analysis is confined to detecting improvement. Thus, a two-sided analysis or comparable method should be used. This appropriate change would not greatly modify the authors' current conclusions about improvements.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Rook et al examined the role of BMP signaling in cerebellum development, using chick as a model alongside human tissue samples. They first examined p-SMADs and found differences between the species, with human samples retaining high p-SMAD after foliation, while in chick, BMP signaling appears to decrease following foliation. To understand the role of BMP during early development, they then used early chick embryos to modulate BMP, using either a constitutively active BMP regulator to increase BMP signaling or overexpressing the negative intracellular BMP regulator to decrease BMP signaling. After validating the constructs in ovo, the authors then examined GNP morphology and migration. They then determined whether the effects were cell autonomous.

      Strengths:<br /> The experiments were well-designed and well-controlled. The figures were extremely clear and convincing, and the accompanying drawings help orient the reader to easily understand the experimental set up. These studies also help clarify the role of BMP at different stages of cerebellum development, suggesting early BMP signaling is required for dorsalization, not rhombic lip induction, and that later BMP signaling is needed to regulate the timing of migration and maturation of granule neurons.

      Weaknesses:<br /> Given the species-specific differences in pSmad localization and abundance in human and chick cerebellum, caution is warranted when making the link to the treatment of human medulloblastoma through modulation BMP signaling. While these studies certainly hint that BMP modulation may affect tumor growth, this was not explicitly tested here. Future studies are required to generalize the functional role of BMP signaling in normal cerebellum development to malignant growth.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This paper sets out to achieve a deeper understanding of the effects of hydrogen sulfide on C. elegans behavior and physiology, with a focus on behavior, detection mechanism(s), physiological responses, and detoxification mechanisms.

      Strengths:<br /> The paper takes full advantage of the experimental tractability of C. elegans, with thorough, well-designed genetic analyses.<br /> Some evidence suggests that H2S may be directly detected by the ASJ sensory neurons.<br /> The paper provides interesting and convincing evidence for complex interactions between responses to different gaseous stimuli, particularly an antagonistic role between H2S and O2 detection/response.<br /> Intriguing roles for mitochondria and iron homeostasis are identified, opening the door to future studies to better understand the roles of these components and processes.

      Weaknesses:<br /> The claim that worms' behavioral responses to H2S are mediated by direct detection is incompletely supported. While a role for the chemosensory neuron ASJ is implicated, it remains unclear whether this reflects direct detection. Other possibilities, including indirect effects of ASJ and the guanylyl cyclase daf-11 on O2 responses, are also consistent with the authors' data.

      The role of H2S-mediated damage in behavioral responses, particularly when detoxification pathways are disrupted, remains unclear.

      The findings of the paper are somewhat disjointed, such that a clear picture of the relationships between H2S detection, detoxification mechanisms, mitochondria, and iron does not emerge from these studies. Most importantly, the relative roles of H2S detection and integration, vs. general and acute mitochondrial crisis, in generating behavioral responses are not convincingly resolved.

    1. Reviewer #1 (Public Review):

      Summary<br /> General Comments<br /> The authors present an interesting study that aims to resolve the contribution of the sodium-activated potassium channel (KNa1.1) to acquired, trauma-induced epilepsy. To this end, the authors first aim to develop a mouse model that consistently generates seizures. Using controlled cortical impact (CCI) methods to induce traumatic brain injuries (TBIs) that range from mild to severe, the authors demonstrate that behavioral deficits correlate with the extent of brain damage. Interestingly, despite the differences in behavioral scores, the spontaneous seizure phenotype was similar across mice with a range of TBI-associated tissue loss. However, when challenged with the chemoconvulsant pentylenetetrazol (PTZ), mice with more severe TBI exhibited more severe seizures.

      After establishing a model of moderate TBI, the authors then show that moderate brain injury transiently upregulates the perilesional expression of KNa1.1. Moreover, the authors provide some evidence that the expression of inhibitory neuron markers is downregulated in the perilesional region following moderate TBI, whereas the expression of excitatory neuron markers is unchanged. Consistent with this finding is the functional observation that neurons receive less inhibitory signaling following TBI, whereas excitatory signaling is unchanged. Inhibitory neurons also fire less robustly following moderate TBI.

      The authors then show that deletion of KNa1.1 in mice provides a moderate level of protection against pharmacologically induced seizures following TBI. In aggregate, the authors propose a model wherein inhibitory neuron-specific upregulation of KNa1.1 following TBI selectively reduces the excitability of inhibitory neurons. In turn, this reduced excitability of inhibitory neurons promotes perilesional tissue hyperexcitability and, ultimately, seizures. Although this model is compelling, readers should be aware that the authors only utilized PTZ-induced seizures following TBI to resolve differences between WT and KO animals. It remains unclear whether WT mice have a robust spontaneous seizure phenotype 14 days after moderate TBI, and whether deleting KNa1.1 reduces this spontaneous seizure phenotype. In general, the combined use of TBI and a chemoconvulsant to evaluate epileptic phenotypes diminishes this reviewer's enthusiasm for the clinical impact of the author's conclusions; although, I appreciate that "capturing [spontaneous] seizures is challenging in terms of animal numbers and long-term recording, which hinders high-throughput studies" (line 302).

      Finally, the authors seemed to have missed an opportunity to determine if the electrophysiological changes observed in WT mice following TBI (i.e., Figure 5) are eliminated in the KNa1.1 KO mouse. That is, the authors show that KNa1.1 contributes to the intrinsic firing properties of uninjured tissue (Figure 6). But does deleting KNa1.1 also restore inhibitory neuron excitability associated with TBI? The inclusion of such data would strengthen the conclusion that the reduced inhibitory neuron excitability following TBI is indeed the result of changes in KNa1.1 expression.

      Strengths:<br /> (1) The development of a TBI model with a range of behavioral phenotypes.

      (2) The inclusion of knockout mouse.

      (3) The inclusion of functional data regarding the intrinsic and synaptic properties of neurons following TBI.

      Weaknesses:<br /> (1) A missed opportunity to better utilize the knockout animal to test the hypothesis that KNa1.1 drives changes in intrinsic excitability following TBI.

      (2) The combined use of TBI and chemoconvulsants to suss out differences in seizure phenotypes.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Using concurrent in vivo whole-cell patch clamp and dendritic calcium imaging, the authors characterized how functional synaptic inputs across dendritic arborizations of mouse primary visual cortex layer 2/3 neurons emerge during the second postnatal week. They were able to identify spatially and functionally separated domains of clustered synapses in these neurons even before eye-opening and characterize how the clustering changes from P8 to P13.

      Strengths:<br /> The work is technically challenging and the findings are novel. The results support previous EM and immunostaining studies but provide in vivo evidence on the time course and the trajectory of how functional synaptic input develops.

      Weaknesses:<br /> There are some missing details about how the experiments were performed, and I also have some questions about the analyses.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Tobón and Moser reveal a remarkable amount of presynaptic diversity in the fundamental Ca dependent exocytosis of synaptic vesicles at the afferent fiber bouton synapse onto the pilar or mediolar sides of single inner hair cells of mice. These are landmark findings with profound implications for understanding acoustic signal encoding and presynaptic mechanisms of synaptic diversity at inner hair cell ribbon synapses. The paper will have an immediate and long-lasting impact in the field of auditory neuroscience.

      Main findings: 1) Synaptic delays and jitter of masker responses are significantly shorter (synaptic delay: 1.19 ms) at high SR fibers (pilar) than at low SR fibers (mediolar; 2.57 ms). 2) Masked evoked EPSC are significantly larger in high SR than in low SR. 3) Quantal content and RRP size are 14 vesicles in both high and low SR fibers. 4) Depression is faster in high SR synapses suggesting they have a higher release probability and tighter Ca nanodomain coupling to docked vesicles. 5) Recovery of master-EPSCs from depletion is similar for high and low SR synapses, although there is a slightly faster rate for low SR synapses that have bigger synaptic ribbons, which is very interesting. 6) High SR synapses had larger and more compact (monophasic) sEPSCs, well suited to trigger rapidly and faithfully spikes. 7) High SR synapses exhibit lower voltage (~sound pressure in vivo) dependent thresholds of exocytosis.

      Strengths:<br /> Great care was taken to use physiological external pH buffers and physiological external Ca concentrations. Paired recordings were also performed at higher temperatures with IHCs at physiological resting membrane potentials and in more mature animals than previously done for paired recordings. This is extremely challenging because it becomes increasingly difficult to visualize bouton terminals when myelination becomes more prominent in the cochlear afferents. In addition, perforated patch recordings were used in the IHC to preserve its intracellular milieu intact and thus extend the viability of the IHCs. The experiments are tour-de-force and reveal several novel aspects of IHC ribbon synapses. The data set is rich and extensive. The analysis is detailed and compelling.

      Weaknesses:<br /> 1) Materials and Methods: Please provide whole-cell Rs (series resistance ) and Cm (membrane capacitance) average +/- S.E.M. (or SD) values for IHC and afferent fiber bouton recordings. The Cm values for afferents have been estimated to be about 0.1 pF (Glowatzki and Fuchs, 2002) and it would be interesting to know if there are differences in these numbers for high and low SR afferents. Is it possible to estimate Cm from the capacitative transient time constant? Minimal electronic filtering would be required for that to work, so I realize the authors may not have this data and I also realize that the long cable of the afferents do not allow accurate Cm measurements, but some first order estimate would be very interesting to report, if possible.

      2) Page 20, 26 and Figure 4: With regard to synaptic delays at auditory hair cell synapses: please see extensive studies done in Figure 11 of Chen and von Gersdorff (JNeurosci., 2019); this showed that synaptic delays are 1.26 ms in adult bullfrog auditory hair cells at 31oC, which is very similar to the High SR fibers (1.19 ms; Fig.4B and page 20). During ongoing depolarizations (e.g. during a sustained sine wave) the synaptic delay can be reduced to just 0.72 ms for probe EPSCs, which is a more usual number for mature fast synapses. This paper should, thus, be cited and briefly discussed in the Discussion. So a significant shortening of delay occurs for the probe response and this is also observed in young rat IHC synapses (see Goutman and Glowatzki, 2011).

      3) Gaussian-like (and/or multi-peak) EPSC amplitude distributions were obtained in more mature rat IHCs by Grant et al. (see their Figure 4G; JNeurosci. 2010; postnatal day 19-21). The putative single quanta peak was at 50 pA and the main peak was at 375 pA. The large mean suggests a low CV (probably < 0.4). However, Fig. 2F shows a mean of about 100 pA and CV = 0.7 for spontaneous EPSCs. This major difference deserves some more discussion. I suppose that one possible explanation may be that the current paper holds the IHC membrane potential fixed at -58 mV, whereas Grant et al. (2010) did not control the IHC membrane potential and spontaneous fluctuations in the Vm may have depolarized the IHC, thus producing larger evoked EPSCs that are triggered by Ca channel openings. Some discussion that compares these differences and possible explanations would be quite useful for the readers.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this manuscript, Sang et al. proposed a pair of IR60b-expressing pharyngeal neurons in Drosophila use IR25a, IR76b, and IR60b channels to detect high Na+ and limit its consumption. Some of the key findings that support this thesis are: 1) animals that lacked any one of these channels - or with their IR60b-expressing neurons selectively silenced - showed much reduced rejection of high Na+, but restored rejection when these channels were reintroduced back in the IR60b neurons; 2) animals with TRPV artificially expressed in their IR60b neurons rejected capsaicin-laced food whereas WT did not; 3) IR60b-expressing neurons exhibited increased Ca2+ influx in response to high Na+ and such response went away when animals lacked any of the three channels.

      Strengths:<br /> The experiments were thorough and well designed. The results are compelling and support the main claim. The development and the use of the DrosoX two-choice assay put forward for a more quantitative and automatic/unbiased assessment for ingestion volume and preference.

      Weaknesses:<br /> There are a few inconsistencies with respect the the exact role by which IR60b neurons limit high salt consumption and the contribution of external (labellar) high-salt sensors in regulating high salt consumption. These weaknesses do not significantly impact the main conclusion, however.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors set up a pipeline for automated high-throughput single-molecule fluorescence imaging (htSMT) in living cells and analysis of molecular dynamics.

      Strengths:<br /> htSMT reveals information on the diffusion and bound fraction of molecules, dose-response curves, relative estimates of binding rates, and temporal changes of parameters. It enables the screening of thousands of compounds in a reasonable time and proves to be more sensitive and faster than classical cell-growth assays. If the function of a compound is coupled to the mobility of the protein of interest, or affects an interaction partner, which modulates the mobility of the protein of interest, htSMT allows identifying the modulator and getting the first indication of the mechanism of action or interaction networks, which can be a starting point for more in-depth analysis.

      Weaknesses:<br /> While elegantly showcasing the power of high-throughput measurements, the authors disclose little information on their microscope setup and analysis procedures. Thus, reproduction by other scientists is limited. Moreover, a critical discussion about the limits of the approach in determining dynamic parameters, the mechanism of action of compounds, and network reconstruction for the protein of interest is missing. In addition, automated imaging and analysis procedures require implementing sensitive measures to assure data and analysis quality, but a description of such measures is missing.

    1. Reviewer #1 (Public Review):

      Summary:

      In this manuscript, the authors performed single nucleus RNA-seq for perirenal adipose tissue (PRAT) at different ages. They concluded a distinct subpopulation of adipocytes arises through brown-to-white conversion and can convert to a thermogenic phenotype upon cold exposure.

      Strengths:

      PRAT adipose tissue has been reported as an adipose tissue that undergoes browning. This study confirms that brown-to-white and white-to-beige conversions also exist in PRAT, as previously reported in the subcutaneous adipose tissue.

      Weaknesses:

      1. There is overall a disconnection between single nucleus RNA-seq data and the lineage chasing data. No specific markers of this population have been validated by staining.<br /> 2. It would be nice to provide more evidence to support the conclusion shown in lines 243 to 245 "These results indicated that new BAs induced by cold exposure were mainly derived from UCP1- adipocytes rather than de novo ASPC differentiation in puPRAT". Pdgfra-negative progenitor cells may also contribute to these new beige adipocytes.<br /> 3. The UCP1Cre-ERT2; Ai14 system should be validated by showing Tomato and UCP1 co-staining right after the Tamoxifen treatment.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors have presented data showing that there is a greater amount of spontaneous differentiation in human pluripotent cells cultured in suspension vs static and have used PKCβ and Wnt signaling pathway inhibitors to decrease the amount of differentiation in suspension culture.

      Strengths:<br /> This is a very comprehensive study that uses a number of different rector designs and scales in addition to a number of unbiased outcomes to determine how suspension impacts the behaviour of the cells and in turn how the addition of inhibitors counteracts this effect. Furthermore, the authors were also able to derive new hiPSC lines in suspension with this adapted protocol.

      Weaknesses:<br /> The main weakness of this study is the lack of optimization with each bioreactor change. It has been shown multiple times in the literature that the expansion and behaviour of pluripotent cells can be dramatically impacted by impeller shape, RPM, reactor design, and multiple other factors. It remains unclear to me how much of the results the authors observed (e.g. increased spontaneous differentiation) was due to not having an optimized bioreactor protocol in place (per bioreactor vessel type). For instance - was the starting seeding density, RPM, impeller shape, feeding schedule, and/or any other aspect optimized for any of the reactors used in the study, and if not, how were the values used in the study determined?

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors develop a method to fluorescently tagged peptides loaded onto dendritic cells using a three step method. These include a pre blocking step to block endogenous cysteine motifs on the DC surface, loading a tetracystein motif modified peptide on surface MHC and a labelling step done on the surface of live DC using a dye with high affinity for the added motif. The results are convincing in demonstrating in vitro and in vivo T cell activation and efficient label transfer to specific T cells in vivo. The label transfer technique will be useful to identify T cell that have recognised a DC presenting a specific peptide antigen to allow the isolation of the T cell and cloning of its TCR subunits, for example. It may also be useful as a general assay for in vitro or in vivo T-DC communication that can allow detection of genetic or chemical modulators.

      Strengths:<br /> The study include both in vitro and in vivo analysis including flow cytometry and two photon laser scanning microscopy. The results are convincing and the level of T cell labelling with the fluorescent pMHC is surprisingly robust and suggests that the approach is potentially revealing something about fundamental mechanisms beyond the state of the art. They also provide practical information about the challenges of the method and discuss limitations.

      Weaknesses:<br /> The method is demonstrated only at high pMHC density and it would need to be re-optimised to determine if it can be used at lower densities that may often be encountered physiologically.

    1. Reviewer #1 (Public Review):

      In this manuscript, Shimonty and colleagues study the effects of FNDC5/irisin deletion on osteocytes in a sex-specific manner using models of lactation-induced bone loss and bone loss due to low calcium diet (LCD). Consistent with the previous findings of Kim et al. (2018), the authors report 'protective' effects of irisin deficiency in lactating female FNDC5-null mice due to reduced osteocytic osteolysis. Interestingly, FNDC5 null mice show distinct changes when placed on LCD, with mutant females showing some protection from hyperparathyroidism-induced bone loss, while mutant males (which have more cortical bone at baseline) show increased LCD-induced bone loss. Furthermore, new insights into irisin's role in osteocytes regarding cellular energetic metabolism were provided by sex and gene-dependent transcriptomic datasets. Strengths of the well-written manuscript include a clear description of sex-dependent effects, strong transcriptomic datasets, and a focus on cortical bone changes using microCT, histomorphometry, BSEM, and serum analysis. Despite these strengths, important weaknesses are noted (below) which could be addressed to improve the impact of the work for a broad audience.

      Major comments:

      1. Overall, the magnitude of the effect size due to FNDC5 deficiency in both male and female mice is rather modest. Looking at the data from a qualitative perspective, it is clear that knockout females still lose bone during lactation and on the low calcium diet (LCD). It is difficult to assess the physiologic consequence of the modest quantitative 'protection' seen in FNDC5 mutants since the mutants still show clear and robust effects of lactation and LCD on all parameters measured. Similarly, the magnitude of the 'increased' cortical bone loss in FNDC5 mutant males is also modest and perhaps could be related to the fact that these mice are starting with slightly more cortical bone. Since the authors do not provide a convincing molecular explanation for why FNDC5 deficiency causes these somewhat subtle changes, I would like to offer a suggestion for the authors to consider (below, point #2) which might de-emphasize the focus of the manuscript on FNDC5. If the authors chose not to follow this suggestion, the manuscript could be strengthened by addressing the consequences of the modest changes observed in WT versus FNDC5 KO mice.

      2. The bone RNA-seq findings reported in Figures 4-6 are quite interesting. Although Youlten et al previously reported that the osteocyte transcriptome is sex-dependent, the work here certainly advances that notion to a considerable degree and likely will be of high interest to investigators studying skeletal biology and sexual dimorphism in general. To this end, one direction for the authors to consider might be to refocus their manuscript toward sexually-dimorphic gene expression patterns in osteocytes and the different effects of LCD on male versus female mice. This would allow the authors to better emphasize these major findings, and to then use FNDC5 deficiency as an illustrative example of how sexually-dimorphic osteocytic gene expression patterns might be affected by deletion of an osteocyte-acting endocrine factor. Ideally, the authors would confirm RNA-seq data comparing male versus female mice in osteocytes using in situ hybridization or immunostaining.

      3. Along the lines of point #2 (above), the presentation of the RNA-seq studies in Figures 4-6 is somewhat confusing in that the volcano plot titles seem to be reversed. For example, Figure 4A is titled "WT M: WT F", but the genes in the upper right quadrant appear to be up-regulated in female cortical bone RNA samples. Should this plot instead be titled "WT F: WT M"? If so, then all other volcano plots should be re-titled as well.

      4. Have the authors compared male versus female transcriptomes of LCD mice?

      5. It would be appreciated if the authors could provide additional serum parameters (if possible) to clarify incomplete data in both lactation and low-calcium diet models: RANKL/OPG ratio, Ctx, PTHrP, and 1,25-dihydroxyvitamin D levels.

      6. Lastly, the data that overexpressing irisin improved bone properties in Fig 2G was somewhat confusing. Based on Kim et al.'s (2018) work, irisin injection increased sclerostin gene expression and serum levels, thus reducing bone formation. Were sclerostin levels affected by irisin overexpression in this study? Was irisin's role in modulating sclerostin levels attenuated with additional calcium deficiency?

    1. Review #1 (Public Review)

      Watanuki et al used metabolomic tracing strategies of U-13C6-labeled glucose and 13C-MFA to quantitatively identify the metabolic programs of HSCs during steady-state, cell-cycling, and OXPHOS inhibition. They found that 5-FU administration in mice increased anaerobic glycolytic flux and decreased ATP concentration in HSCs, suggesting that HSC differentiation and cell cycle progression are closely related to intracellular metabolism and can be monitored by measuring ATP concentration. Using the GO-ATeam2 system to analyze ATP levels in single hematopoietic cells, they found that PFKFB3 can accelerate glycolytic ATP production during HSC cell cycling by activating the rate-limiting enzyme PFK of glycolysis. Additionally, by using Pfkfb3 knockout or overexpressing strategies and conducting experiments with cytokine stimulation or transplantation stress, they found that PFKFB3 governs cell cycle progression and promotes the production of differentiated cells from HSCs in proliferative environments by activating glycolysis. Overall, in their study, Watanuki et al combined metabolomic tracing to quantitatively identify metabolic programs of HSCs and found that PFKFB3 confers glycolytic dependence onto HSCs to help coordinate their response to stress.

    1. Joint Public Review:

      This study used ATAC-Seq to characterize chromatin accessibility during stages of GABAergic neuron development in induced pluripotent stem cells (iPSCs) derived from both Dravet Syndrome (DS) patients and healthy donors. The authors report accelerated GABAergic maturation to a point, followed by further differentiation into a perturbed chromatin profile, in the cells from patients. In a preliminary analysis, valproic acid, an anti-seizure medication commonly used in patients with DS, increased open chromatin in both patient and control iPSCs in a nonspecific manner, and to different degrees in cultures derived from different patients. These findings provide new information about DS-associated changes in chromatin, and provide further evidence for developmental abnormalities in interneurons with DS.

      Strengths:

      This is a novel study that aims to investigate the epigenetic changes that occur in a sodium channel model of epilepsy; these changes are often ignored but may be an interesting area for future therapeutics. In general, the flow of the paper is good, and the figures are well-designed.

      Weaknesses:

      The most substantial weakness relates to the observation that DS is often viewed as a monogenic form of epilepsy. It is directly linked to SCN1A gene haploinsufficiency (Yu et al, 2006; Ogiwara et al, 2007). The gene product is Nav1.1, the alpha subunit of voltage-gated sodium channel type I that regulates neuronal excitability. Yet, analysis was conducted at time points of GABAergic interneuron differentiation in which SCN1A is likely not expressed. The paper would be strengthened if SCN1A expression and Nav1.1 protein were examined across the experimental time course. If SCN1A is not yet expressed, this would complicate any explanation of how the observed epigenetic changes might arise. It also seems counterintuitive that the absence of a sodium channel can accelerate differentiation, when, a priori, one might expect the opposite (a 'less neuronal' signal).

      Related to this, another important limitation of the study is that the controls are cells derived from healthy individuals and not from isogenic lines. The usage of isogenic lines is extremely relevant for every study in which iPSC-derived somatic cells are used to model a disease, but specifically in diseases like DS, in which the genetic background has an ascertained impact on disease phenotype (Cetica et al, 2017 and others). This serious limitation should be considered. In addition, the authors should provide data on variability across cell lines and differentiations to help convince the reader that the results can be attributed to genetic defects, rather than variability across individuals.

      Additionally, the authors acknowledge the variability of the differentiations and cell lines, which is commendable, and they attribute this to "possibly reflecting cell line specific and endogenous differences reported previously", but could also have to do with cell death. This is a large confounding factor for ATAC-seq. Certainly, Sup Fig 1C shows lower FrIP scores, consistent with cell death, and there seems to be a lot of death in the representative images. Moreover, the iGABA neurons are very difficult to keep alive, especially to 65 days, without co-culturing with glia and/or glutamatergic neurons. The authors should comment on how much these factors may have influenced their results.

      Finally, changes in gene expression are only inferred, as no RNA levels were measured. If RNA-seq was not possible it would have been good to see at least some of the key genes/findings corroborated with RNA/protein levels vs chromatin accessibility alone, particularly given that these molecular readouts do not always correlate.

      Additional Points:

      1. Representative images for cell-identity markers for only D65 are shown, and not D0, D19, and D35 though it is stated in the text that this was performed. At a minimum, these representative images should be shown for all lines.<br /> 2. What QC was performed on iPSC lines, i.e. karyotype/CNV analysis and confirmation of genotypes?<br /> 3. Were all experiments performed on a single differentiation? Or multiples? Were the differentiations performed with the same type? If not, was batch considered in the analysis? I also assume that technical replicates were merged, and then all three biological replicates were kept for each analysis and outliers were not removed, e.g. Control_D19_8F seems like an example of an outlier.<br /> 4. In Figure 1C, it is intriguing that the ATACseq signal gets stronger in imN. One might expect it to be strongest in the iPSCs which are undifferentiated and have the highest levels of open chromatin. Is this a function of sequencing depth, or are all the Y-axes normalized across all time points?<br /> 5. In Figure 1F, are these all enriched terms, or were they prioritized somehow?<br /> 6. In Figure 1G (also the same plots in Fig 2/3), are all these images normalized i.e. there is no scale bar for each track, and do they represent and aggregate BAM/bigwig? It would be good to show in supplement the variability across cell lines/diffs - particularly given the variability in the heatmap/PCA - and demonstrate the rigor/reproducibility of these results. This comment applies to all these plots across the 3 figures, particularly as in some instances the samples appear to cluster by individual first and then time point (Sup Fig 3B). How confident are the authors that these effects are driven by genotype and not a single cell line? In the Fig 3D representation of NANOG, it is very difficult to see any difference between patient and control.<br /> 7. For the changes in occupancy annotation (UTR/exon/intron etc), are these differences still significant after correcting for variability from cell line to cell line at each time point? I.e. rather than average across all three samples, what is the range?<br /> 8. The VPA timepoint is not well-justified. Given that VPA would be administered in patients with fully mature inhibitory neurons, it is difficult to determine the biological relevance. I appreciate that this is a limitation of the model, but this should at least be addressed in the manuscript.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors provide mechanistic insights into how the loss of function of MBOAT7 promotes alcohol-associated liver disease. They showed that hepatocyte-specific genetic deletion of Mboat7 enhances ethanol-induced hepatic steatosis and increased ALT levels in a murine model of ethanol-induced liver disease. Through lipidomic profiling, they showed that mice with Mboat7 deletion demonstrated augmented ethanol-induced endosomal and lysosomal lipids, together with impaired transcription factor EB (TFEB)-mediated lysosomal biogenesis and accumulation of<br /> autophagosomes.

      Strengths:<br /> -Alcohol-induced liver disease (ALD) and metabolic-associated steatotic liver disease (MASLD) are major global health problems, and polymorphism near the gene encoding MBOAT7 has been associated with these conditions. This paper is timely as it is important to gain insights on how loss of MBOAT function contributes to liver disease as this may eventually lead to therapeutic strategies.<br /> -The conclusions of the paper are mostly well supported by data.

      Weaknesses:<br /> 1) In regards to circulating levels of MBOAT7 products, a comparison of heavy drinkers with ALD versus heavy drinkers without ALD would be more clinically relevant.<br /> 2) A few typos need to be addressed. For Figure 1 - figure supplement 1, should the second column heading be "Heavy drinkers" instead of "Healthy drinkers"? Also, in the same figure, it is unclear what the "healthy" subcategory under MELD means.<br /> 3) Some of the data in the tables need to be addressed/discussed. For instance, the white blood cell count (WBC) in Figure 1 - figure supplement 1 for "healthy controls" is 34, compared to 13.51 for drinkers. A WBC of 34 is not at all healthy and should be explained. The vast difference between BMI and also between racial distribution within the two cohorts should also be explained. Is it possible that some of these differences contributed to the different levels of circulating MBOAT7 products that were measured?<br /> 4) The representation of the statistical difference between the bars in the results figures by using alphabets is a bit confusing. For instance, in figure 2C, does that mean all the bars labelled A are significantly different from B? The solid black bar seems to be very similar to the open red bar; please double check.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The extra macrochaetae (emc) gene encodes the only Inhibitor of DNA binding protein (Id protein) in Drosophila. Its best-known function is to inhibit proneural genes during development. However, the emc mutants also display non-proneural phenotypes. In this manuscript, the authors examined four non-proneural phenotypes of the emc mutants and reported that they are all caused by inappropriate non-apoptotic caspase activity. These non-neuronal phenotypes are: reduced growth of imaginal discs, increased speed of the morphogenetic furrow, and failure to specify R7 photoreceptor neurons and cone cells during eye development. Double mutants between emc and either H99 (which deletes the three pro-apoptotic genes reaper, grim, and hid) or the initiator caspase dronc suppress these mutant phenotypes of emc suggesting that the cell death pathway and caspase activity are mediating these emc phenotypes. In previous work, the authors have shown that emc mutations elevate the expression of ex which activates the SHW pathway (aka the Hippo pathway). One known function of the SHW pathway is to inhibit Yorkie which controls the transcription of the inhibitor of apoptosis, Diap1. Consistently, in emc clones the levels of Diap1 protein are reduced which might explain why caspase activity is increased in emc clones giving rise to the four non-neural phenotypes of emc mutants. However, this increased caspase activity is not causing ectopic apoptosis, hence the authors propose that this is non-apoptotic caspase activity. In the last part of the manuscript, the authors ruled out that Wg, Dpp, and Hh signaling are the target of caspases, but instead identified Notch signaling as the target of caspases, specifically the Notch ligand Delta. Protein levels of Delta are increased in emc clones in an H99- and dronc-dependent manner. The authors conclude that caspase-dependent non-apoptotic signaling underlies multiple roles of emc that are independent of proneural bHLH proteins.

      Strengths:<br /> Overall, this is an interesting manuscript and the findings are intriguing. It adds to the growing number of non-apoptotic functions of apoptotic proteins and caspases in particular. The manuscript is well written and the data are usually convincingly presented.

      Weaknesses:<br /> 1. One major concern I have is the observation by the authors in Figure 3C in which protein levels of Diap1 are still reduced in emc H99 double mutant clones. If Diap1 is still reduced in these clones, shouldn't caspases still be de-repressed? Given that emc H99 double mutants rescue all emc phenotypes examined, the observation that Diap1 levels are still reduced in emc H99 clones is inconsistent with the authors' model. The authors need to address this inconsistency.

      2. Are Diap1 protein levels reduced in all emc clones, including clones anterior to the furrow? This is difficult to see in Figure 3B. it is also recommended to look in emc mosaic wing discs.

      3. The authors speculate that Delta may be a direct target of caspase cleavage (Figure 9B), but then rule it out for a good reason. However, I assume that the increased protein levels of Delta in emc clones (Figure 7) are the results of increased transcription. In that case, shouldn't caspases control the transcriptional machinery leading to Delta expression?

      4. How does caspase activity in emc clones cause reduced growth? Is this also mediated through Delta signaling?

      5. Figure 1M: Is there a similar result with emc dronc mosaics?

    1. La inteligencia artificial (IA) está revolucionando la investigación y el mundo académico, facilitando desde la redacción del manuscrito hasta el análisis de datos. Pero, la IA no “pisa la calle”. La IA sigue confinada al ámbito digital y es incapaz de involucrarse en interacciones humanas para indagar sobre dinámicas interpersonales o comprender el contexto. Ante este panorama, ¿se debería aceptar que la IA revise artículos de investigación enviados a una revista? ¿Cómo debe adaptarse la academia ante el auge de la IA generativa? El presente artículo reflexiona sobre el impacto de la IA en la investigación y el mundo académico, ofreciendo una definición y caracterización de la IA generativa, presentando herramientas de IA que asisten en la investigación, y analizando cuatro escenarios futuros posibles: democratización de la investigación, desaprovechamiento de la IA, aumento de la desigualdad y rezagados digitales. Se concluye sugiriendo estrategias de acción como mayor formación en herramientas de IA, fomento de una educación basada en investigación, y necesidad de abrir un debate sobre el uso de la IA en la gestión de las revistas científicas.

      Comentario 21/12/2023 público

    1. La inteligencia artificial (IA) está revolucionando la investigación y el mundo académico, facilitando desde la redacción del manuscrito hasta el análisis de datos. Pero, la IA no “pisa la calle”.

      Comentario 21/12/2023 público

    1. Joint Public Review:

      Roget et al. build on their previous work developing a simple theoretical model to examine whether ageing can be under natural selection, challenging the mainstream view that ageing is merely a byproduct of other biological and evolutionary processes. The authors propose an agent-based model to evaluate the adaptive dynamics of a haploid asexual population with two independent traits: fertility timespan and mortality onset. Through computational simulations, their model demonstrates that ageing can give populations an evolutionary advantage. Notably, this observation arises from the model without invoking any explicit energy tradeoffs, commonly used to explain this relationship.

      Additionally, the theoretical model developed here indicates that mortality onset is generally selected to start before the loss of fertility, irrespective of the initial values in the population. The selected relationship between the fertility timespan and mortality onset depends on the strength of fertility and mortality effects, with larger effects resulting in the loss of fertility and mortality onset being closer together. By allowing for a trans-generational effect on ageing in the model, the authors show that this can be advantageous as well, lowering the risk of collapse in the population despite an apparent fitness disadvantage in individuals. Upon closer examination, the authors reveal that this unexpected outcome is a consequence of the trans-generational effect on ageing increasing the evolvability of the population (i.e., allowing a more effective exploration of the parameter landscape), reaching the optimum state faster.

      The simplicity of the proposed theoretical model represents both the major strength and weakness of this work. On one hand, with an original and rigorous methodology, the logic of their conclusions can be easily grasped and generalised, yielding surprising results. Using just a handful of parameters and relying on direct competition simulations, the model qualitatively recapitulates the negative correlation between lifespan and fertility without requiring energy tradeoffs. This alone makes this work an important milestone for the rapidly growing field of adaptive dynamics, opening many new avenues of research, both theoretically and empirically.

      On the other hand, the simplicity of the model also makes its relationship with living organisms difficult to gauge, leaving open questions about how much the model represents the reality of actual evolution in a natural context. In particular, a more explicit discussion of how the specifics of the model can impact the results and their interpretation is needed. For example, the lack of mechanistic details on the trans-generational effect on ageing makes the results difficult to interpret. Even if analytical results are obtained, most of the observations appear derived from simulations as they are currently presented. Also, the choice of parameters for the simulations shown in the paper and how they relate to our biological knowledge are not fully addressed by the authors. Finally, the conclusions of evolvability are insufficiently supported, as the authors do not show if the wider genotypic variability in populations with the ageing trans-generational effect is, in fact, selected.

    1. Reviewer #1 (Public Review):

      Summary:

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

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

      Weaknesses:

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

    1. Reviewer #1 (Public Review):

      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 taxonomic scale.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This study examined the impact of exogenous microapplication of acetylcholine (Ach) on metrics of novelty detection in the anesthetized rat auditory cortex. The authors found that the majority of units showed some degree of modulation of novelty detection, with roughly similar numbers showing enhanced novelty detection, suppressed novelty detection or no change. Enhanced novelty responses were driven by increases in repetition suppression. Suppressed novelty responses were driven by deviance suppression. There were no compelling differences seen between auditory cortical subfields or layers, though there was heterogeneity in the Ach effects within subfields. Overall, these findings are important because they suggest that fluctations in cortical Ach, which are known to occur during changes in arousal or attentional states, will likely influence the capacity for individual auditory cortical neurons to respond to novel stimuli.

      Strengths:<br /> The work addresses an important problem in auditory neuroscience. The main strengths of the study are that the work appears to be systematically done with appropriate controls (cascaded stimuli) and utilizes a classical approach that ensures that drug application is isolated to the micro-environment of the recorded neuron. In addition, the authors do not isolate their study to only primary auditory cortex, but examine the impact of Ach across all known auditory cortical subfields.

      Weaknesses:<br /> 1. As acknowledged by the authors, this study explicitly examines a phenomenon of high relevance to active listening, but is done in anesthetized animals, limiting its applicability to the waking state.<br /> 2. The authors do not make any attempt to determine, by spike shape/duration, if their units are excitatory or inhibitory, which may explain some of the variance of the data.<br /> 3. The application of exogenous Ach, potentially in supra-physiological amounts, makes this study hard to extrapolate to a behaving animal. A more compelling design would be to block Ach, particularly at particular receptor types, to determine the effect of endogenous Ach

    1. Reviewer #1 (Public Review):

      Summary:

      The manuscript by Heyndrickx et al describes protein crystal formation and function that bears similarity to Charcot-Leyden crystals made of galectin 10, found in humans under similar conditions. Therefore, the authors set out to investigate CLP crystal formation and their immunological effects in the lung. The authors reveal the crystal structure of both Ym1 and Ym2 and show that Ym1 crystals trigger innate immunity, activated dendritic cells in the lymph node, enhancing antigen uptake and migration to the lung, ultimately leading to induction of type 2 immunity.

      Strengths:

      We know a lot about expression levels of CLPs in various settings in the mouse, but still know very little about the functions of these proteins, especially in light of their ability to form crystal structures. As such data presented in this paper is a major advance to the field.

      Resolving the crystal structure of Ym2 and the comparison between native and recombinant CLP crystals is a strength of this manuscript that will be a very powerful tool for further evaluation and understanding of receptor, binding partner studies including ability to aid mutant protein generation.

      The ability to recombinantly generate CLP crystals and study their function in vivo and ex vivo has provided a robust dataset whereby CLPs can activate innate immune responses, aid activation and trafficking of antigen presenting cells from the lymph node to the lung and further enhances type 2 immunity. By demonstrating these effects the authors directly address the aims for the study. A key apoint of this study is the generation of a model in which crystal formation/function an important feature of human eosinophilic diseases, can be studied utilising mouse models. Excitingly, using crystal structures combined with understanding the biochemistry of these proteins will provide a potential avenue whereby inhibitors could be used to dissolve or prevent crystal formation in vivo.

      Generation of the crystal structure for Ym2 is a particular strength of the authors work and highlights the similarities between Ym1 and Ym2. Whilst the authors did not specifically examine Ym2 function, they have provided a discussion on this and speculate that Ym2 will function in a similar manner to Ym1.

      The data presented flows logically and formulates a well constructed overall picture of exactly what CLP crystals could be doing in an inflammatory setting in vivo. Leaves open a clear and exciting future avenue (currently beyond the scope of this work) for determining whether targeting crystal formation in vivo could limit pathology.

      Weaknesses:

      It would have been nice for the authors to confirm whether Ym2 has similar functions to Ym1 using the in vivo and in vitro systems. However, they have discussed these points and raised it as a potential for future studies.

    1. Reviewer #1 (Public Review):

      Summary:

      This manuscript describes the development of an oral THC consumption model in mice where THC is added to a chocolate flavored gelatin. The authors compared the effects of THC consumed in this highly palatable gelatin (termed E-gel) to THC dissolved in a less palatable gelatin (CTR-gel), and to i.p. injections of multiple doses of THC, on the classic triad of CB1R dependent behaviors (hypolocomotion, antinociception, and body temperature).

      The authors found that they could achieve consumption of higher concentrations of THC in the E-gel than the CTR-gel, and that this led to larger total dose exposure and decreases in locomotor activity, antinociception, and body temperature reductions similar to 3-4 mg/kg THC when tested after 2 hour consumption and roughly 10 mg/kg if tested immediately after 1 hour consumption. The majority of THC E-gel consumption was found to occur in the first hour on the first exposure day. THC E-gel consumption was lower than VEH E-gel consumption and this persisted on a subsequent consumption day, suggesting that the animals may form a taste aversion and that THC at the dose consumed likely has aversive properties, consistent with the literature on i.p. dosing. The authors also report the pharmacokinetics in brain and plasma of THC and metabolites after 1 or 2 hour consumption, finding high levels of THC in the brain that begins to dissipate at 2.5 hours is gone 24 hours later. Finally, the authors tested THC effects on the acoustic startle response and found an inverted dose response that was more pronounced in males than females after i.p. dosing and a greater startle response in males after E-gel dosing.

      Overall, the authors find that voluntary oral consumption of THC can achieve levels of intake that are consistent with the present and prior reported literature on i.p. dosing.

      Strengths:

      The strengths of the article include a direct comparison of voluntary oral THC consumption to noncontingent i.p. administration, the use of multiple THC doses and oral THC formulations, the inclusion of multiple assays of cannabinoid agonist effects, and the inclusion of males and females. Additional strengths include monitoring intake over 10 minute intervals and validating that effects are CB1R dependent via antagonist studies.

      Weaknesses:

      1. The abstract does not discuss the reduction of E-gel consumption that occurs after multiple days of exposure to the THC formulation, but rather implies that a new model for chronic oral self-administration has been developed. Given that only two days of consumption was assessed, it is not clear if the model will be useful to determine THC effects beyond the acute measures presented here. The abstract should clarify that there was evidence of reduced consumption/aversive effects with repeated exposures.<br /> 2. In the results section, the authors sometimes describe effects in terms of the concentration of gel as opposed to the dose consumed in mg/kg, which can make interpretation difficult. For example, the text describing Figure 1i states that significant effects on body temperature were achieved at 4 mg CTR-gel and 5 mg THC-gel, but were essentially equivalent doses consumed? It would be helpful to describe what average dose of THC produced effects given that consumption varied within each group of mice assigned to a particular concentration.<br /> 3. The description of the PK data in Figure 3 did not specify if sex differences were examined. Prior studies have found that males and females can exhibit stark differences in brain and plasma levels of THC and metabolites, even when behavioral effects are similar. However, this does depend on species, route, timing of tissue collection. It would be helpful to describe the PK profile of males and females separately.<br /> 4. In Figure 5, it is unclear how the predicted i.p. THC dose could be 30 mg/kg when 30 mg/kg was not tested by the i.p. route according to the figure, and if it had been it would have likely been almost zero acoustic startle, not the increased startle that was observed in the 2 hr gel group. It seems more likely that it would be equivalent to 3 mg/kg i.p. Could there be an error in the modeling, or was it based on the model used for the triad effects? This should be clarified.

    1. Reviewer #1 (Public Review):

      This study investigates the structuring of long calls in orangutans. The authors demonstrate long calls are structured around full pulses, repeated following a regular tempo (isochronic rhythm). These full pulses are themselves structured around different sub-pulses, themselves repeated following an isochronic rhythm. The authors argue this patterning is evidence for self-embedded, recursive structuring in orangutang long calls.

      The analyses conducted are robust and compelling and they support the rhythmicity the authors argue is present in the long calls. Furthermore, the authors went above and beyond and confirmed acoustically the sub-categories identified were accurate.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this work, the authors study whether the human brain uses long-term priors (acquired during our lifetime) regarding the statistics of auditory stimuli to make predictions respecting auditory stimuli. This is an important open question in the field of predictive processing.

      To address this question, the authors cleverly profit from the naturally existing differences between two linguistic groups. While speakers of Spanish use phrases in which function words (short words like articles and prepositions) are followed by content words (longer words like nouns, adjectives, and verbs), speakers of Basque use phrases in the opposite order. Because of this, speakers of Spanish usually hear phrases in which short words are followed by longer words, and speakers of Basque experience the opposite. This difference in the order of short and longer words is hypothesized to result in a long-term duration prior that is used to make predictions regarding the likely durations of incoming sounds, even if they are not linguistic in nature.

      To test this, the authors used MEG to measure the mismatch responses (MMN) elicited by the omission of short and long tones that were presented in alternation. The authors report an interaction between the language background of the participants (Spanish, Basque) and the type of omission MMN (short, long), which goes in line with their predictions. They supplement these results with a source-level analysis.

      Unfortunately, serious concerns regarding the predictions put forward by the authors, and the interaction effect found, make the interpretation of these results difficult.

      Strengths:<br /> This work has many strengths. To test the main question, the authors profit from naturally occurring differences in the everyday auditory experiences of two linguistic groups, which allows them to test the effect of putative auditory priors consolidated over years. This is a direct way of testing the effect of long-term priors.

      The fact that the priors in question are linguistic, and that the experiment was conducted using non-linguistic stimuli (i.e. simple tones), allows for testing of whether these long-term priors generalize across auditory domains.

      The experimental design is elegant and the analysis pipeline is appropriate. This work is very well written. In particular, the introduction and discussion sections are clear and engaging. The literature review is complete.

      Weaknesses:<br /> There are two main issues in this work. The first one pertains to the predictions put forward by the researchers, and the second with the interaction effect reported.

      1) With respect to the predictions, the authors propose that the subjects, depending on their linguistic background and the length of the tone in a trial, can put forward one or two predictions. The first is a short-term prediction based on the statistics of the previous stimuli and identical for both groups (i.e. short tones are expected after long tones and vice versa). The second is a long-term prediction based on their linguistic background. According to the authors, after a short tone, Basque speakers will predict the beginning of a new phrasal chunk, and Spanish speakers will predict it after a long tone.

      In this way, when a short tone is omitted, Basque speakers would experience the violation of only one prediction (i.e. the short-term prediction), but Spanish speakers will experience the violation of two predictions (i.e. the short-term and long-term predictions), resulting in a higher amplitude MMN. The opposite would occur when a long tone is omitted. So, to recap, the authors propose that subjects will predict the alternation of tone durations (short-term predictions) and the beginning of new phrasal chunks (long-term predictions).

      The problem with this is that subjects are also likely to predict the completion of the current phrasal chunk. In speech, phrases are seldom left incomplete. In Spanish is very unlikely to hear a function-word that is not followed by a content-word (and the opposite happens in Basque). On the contrary, after the completion of a phrasal chunk, a speaker might stop talking and a silence might follow, instead of the beginning of a new phrasal chunk.

      Considering that the completion of a phrasal chunk is more likely than the beginning of a new one, the prior endowed to the participants by their linguistic background should make us expect a pattern of results actually opposite to the one reported here.

      2) The authors report an interaction effect that modulates the amplitude of the omission response, but caveats make the interpretation of this effect somewhat uncertain. The authors report a widespread omission response, which resembles the classical mismatch response (in MEG) with strong activations in sensors over temporal regions. Instead, the interaction found is circumscribed to four sensors that do not overlap with the peaks of activation of the omission response. Furthermore, the boxplot in Figure 2E suggests that part of the interaction effect might be due to the presence of two outliers (if removed, the effect is no longer significant). Overall, it is possible that the reported interaction is driven by a main effect of omission type which the authors report, and find consistently only in the Basque group (showing a higher amplitude omission response for long tones than for short tones).

      Because of these points, it is difficult to interpret this interaction as a modulation of the omission response. It should also be noted that in the source analysis, the interaction only showed a trend in the left auditory cortex, but in its current version the manuscript does not report the statistics of such a trend.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The global decline of amphibians is primarily attributed to deadly disease outbreaks caused by the chytrid fungus, Batrachochytrium dendrobatidis (Bd). It is unclear whether and how skin-resident immune cells defend against Bd. Although it is well known that mammalian mast cells are crucial immune sentinels in the skin and play a pivotal role in the immune recognition of pathogens and orchestrating subsequent immune responses, the roles of amphibian mast cells during Bd infections are largely unknown. The current study developed a novel way to enrich X. laevis skin mast cells by injecting the skin with recombinant stem cell factor (SCF), a KIT ligand required for mast cell differentiation and survival. The investigators found an enrichment of skin mast cells provides X. laevis substantial protection against Bd and mitigates the inflammation-related skin damage resulting from Bd infection. Additionally, the augmentation of mast cells leads to increased mucin content within cutaneous mucus glands and shields frogs from the alterations to their skin microbiomes caused by Bd.

      Strengths:<br /> This study underscores the significance of amphibian skin-resident immune cells in defenses against Bd and introduces a novel approach to examining interactions between amphibian hosts and fungal pathogens.

      Weaknesses:<br /> The main weakness of the study is the lack of functional analysis of X. laevis mast cells. Upon activation, mast cells have the characteristic feature of degranulation to release histamine, serotonin, proteases, cytokines, and chemokines, etc. The study should determine whether X. laevis mast cells can be degranulated by two commonly used mast cell activators IgE and compound 48/80 for IgE-dependent and independent pathways. This can be easily done in vitro. It is also important to assess whether in vivo these mast cells are degranulated upon Bd infection using avidin staining to visualize vesicle releases from mast cells. Figure 3 only showed rSCF injection caused an increase in mast cells in naïve skin. They need to present whether Bd infection can induce mast cell increase and rSCF injection under Bd infection causes a mast cell increase in the skin. In addition, it is unclear how the enrichment of mast cells provides protection against Bd infection and alternations to skin microbiomes after infection. It is important to determine whether skin mast cells release any contents mentioned above.

    1. Reviewer #1 (Public Review):

      Summary: This study brings new information about the function of serotonin-gated ion channels 5-HT3AR, by describing the conformational changes undergoing during ligands binding. These results can be potentially extrapolated to other members of the Cys-loop ligand-gated ion channels. By combining fluorescence microscopy with electrophysiological recordings, the authors investigate structural changes inside and outside the orthosteric site elicited by agonists, partial agonists, and antagonists. The results are convincing and correlate well with the observations from cryo-EM structures. The work will be of important significance and broad interest to scientists working on channel biophysics but also drug development targeting ligand-gated ion channels.

      Strengths: The authors present an elegant and well-designed study to investigate the conformational changes on 5-HT3AR where they combine electrophysiological and fluorometry recordings. They determined four positions suitable to act as sensors for the conformational changes of the receptor: two inside and two outside the agonist binding site. They make a strong point showing how antagonists produce conformational changes inside the orthosteric site similarly as agonists do but they failed to spread to the lower part of the ECD, in agreement with previous studies and Cryo-EM structures. They also show how some loss-of-function mutant receptors elicit conformational changes (changes in fluorescence) after partial agonist binding but failed to produce measurable ionic currents, pointing to intermediate states that are stabilized in these conditions. The four fluorescence sensors developed in this study may be good tools for further studies on characterizing drugs targeting the 5-HT3R.

      Weaknesses: Although the major conclusions of the manuscript seem well justified, some of the comparison with the structural data may be vague. The claim that monitoring these silent conformational changes can offer insights into the allosteric mechanisms contributing to signal transduction is not unique to this study and has been previously demonstrated by using similar techniques with other ion channels.

    1. Reviewer #1 (Public Review):

      In their revised manuscript, the authors have addressed all the concerns raised earlier (written below for completeness).

      Summary:

      These types of analyses use many underlying assumptions about the data, which are not easy to verify. Hence, one way to test how the algorithm is performing in a task is to study its performance on synthetic data in which the properties of the variable of interest can be apriori fixed. For example, for burst detection, synthetic data can be generated by injected bursts of known durations, and checking if the algorithm can pick it up. Burst detection is difficult in the spectral domain since direct spectral estimators have high variance (see Subhash Chandran et al., 2018, J Neurophysiol). Therefore, detected burst lengths are typically much lower than injected burst lengths (see their Figure 3). This problem can be solved by doing burst estimation in the time domain itself, for example, using Matching Pursuit (MP). I think the approach presented in this paper would also work since this model is also trained on data in the time domain. Indeed, the synthetic data can be made more "challenging" by injecting multiple oscillatory bursts that are overlapping in time, for which a greedy approach like MP may fail. It would be very interesting to test whether this method can "keep up" as the data is made more challenging. While showing results from brain signals directly (e.g., Figure 7) is nice, it will be even more impactful if it is backed up with results obtained from synthetic data with known properties.

      I was wondering about what kind of "synthetic data" could be used for the results shown in Figure 8-12 but could not come up with a good answer. Perhaps data in which different sensory systems are activated (visual versus auditory) or sensory versus movement epochs are compared to see if the activation maps change as expected? We see similarities between states across multiple runs (reproducibility analysis) and across tasks (e.g. Figure 8 vs 9) and even methods (Figure 8 vs 10), which is great. However, we should also expect emergence of new modes specific to sensory activation (say auditory cortex for an auditory task). This will allow us to independently check the performance of this method.

      The authors should explain the reproducibility results (variational free energy and best run analysis) in the Results section itself, to better orient the reader on what to look for.

      Page 15: the comparison across subjects is interesting, but it is not clear why sensory-motor areas show a difference and the mean lifetime of the visual network decreases. Can you please explain this better? The promised discussion in section 3.5 can be expanded as well.

    1. Reviewer #1 (Public Review):

      Batra, Cabrera, Spence et al. present a model which integrates histone posttranslational modification (PTM) data across cell models to predict gene expression with the goal of using this model to better understand epigenetic editing. This gene expression prediction model approach is useful if a) it predicts gene expression in specific cell lines b) it predicts expression values rather than a rank or bin, c) it helps us to better understand the biology of gene expression, or d) it helps us to understand epigenome editing activity. Problematically for points a) and b) it is easier to directly measure gene expression than to measure multiple PTMs and so the real usefulness of this approach mostly relates to c) and d).

      Other approaches have been published that use histone PTM to predict expression (e.g. 27587684, 36588793). Is this model better in some way? No comparisons are made. The paper does not seem to have substantial novel insights into understanding the biology of gene expression. The approach of using this model to predict epigenetic editor activity on transcription is interesting and to my knowledge novel but I doubt given the variability of the predictions (Figures 6 and S7&8) that many people will be interested in using this in a practical sense. As the authors point out, the interpretation of the epigenetic editing data is convoluted by things like sgRNA activity scoring and to fully understand the results likely would require histone PTM profiling and maybe dCas9 ChIP-seq for each sgRNA which would be a substantial amount of work.

      Furthermore from the model evaluation of H3K9me3 it seems the model is not performing well for epigenetic or transcriptional editing- e.g. we know for the best studied transcriptional editor which is CRISPRi (dCas9-KRAB) that recruitment to a locus is associated with robust gene repression across the genome and is associated with H3K9me3 deposition by recruitment of KAP1/HP1/SETDB1 (PMID: 35688146, 31980609, 27980086, 26501517). However, it seems from Figures 2&4 that the model wouldn't be able to evaluate or predict this.

      The model seems to predict gene expression for endogenous genes quite well although the authors sometimes use expression and sometimes use rank (e.g. Figure 6) - being clearer with how the model predicts expression rather than using rank or fold change would be very useful.

      One concern overall with this approach is that dCas9-p300 has been observed to induce sgRNA-independent off-target H3K27Ac (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349887/ see Figure S5D) which could convolute interpretation of this type of experiment for the model.

      Figure 2<br /> It seems this figure presents known rather than novel findings from the authors' description. Please comment on whether there are any new findings in this figure. Please comment on differences in patterns of repressive and activating histone PTMs between cell lines (e.g. H1-Esc H3K27me3 green 25-50% is more enriched than red 0-25%).

      Figure 3&4<br /> There are a number of approaches including DeepChrome and TransferChrome that predict endogenous gene expression from histone PTMs. I appreciate that the authors have not used the histone PTM data to predict gene expression levels of an "average cell" but rather that they are predicting expression within specific cell types or for unseen cell types. But from what is presented it isn't clear that the author's model is better or enabling beyond other approaches. The authors should show their model is better than other approaches or make clear why this is a significant advance that will be enabling for the field. For example is it that in this approach they are actually predicting expression levels whereas previous approaches have only predicted expressed or not expressed or a rank order or bin-based ranking?

      Figure 5<br /> From the methods, it seems gene activation is measured by qpcr in hek293 transfected with individual sgRNAs and dCas9-p300. The cells aren't selected or sorted before qPCR so how are we sure that some of the variability isn't due to transfection efficiency associated with variable DNA quality or with variable transfection efficiency?

      Figure 6<br /> The use of rank in 6D and 6E is confusing. In 6D a higher rank is associated with higher expression while in 6E a higher rank seems to mean a lower fold change e.g. CYP17A1 has a low predicted fold-change rank and qPCR fold-change rank but in Figure 5 a very high qPCR fold change. Labeling this more clearly or explaining it in the text further would be useful.

    1. Reviewer #1 (Public Review):

      Summary:

      Glenn et al. present solid evidence that both lab and clinical Enterobacteriaceae strains rapidly migrate towards human serum using an exciting approach that combines microfluidics, structural biology, and genotypic analysis. The authors succeed in bringing to light a novel context for the role of serine as a bacterial chemoattractant as well as documenting what is likely to be a key step in bloodstream entry for some of the main sepsis-associated pathogens during gastrointestinal bleeding. They aim to expand their conclusions from a single lab serovar of Salmonella enterica to a range of clinical serovars and other species within the Enterobacteriaceae family. This is a powerful approach that greatly increases the scope of their findings but I find that some of their conclusions here are not always supported by strong evidence.

      I would also like to note that, while I enjoyed the interdisciplinary scope of this study, I am personally not well positioned to review the protein structural aspects of this work.

      Strengths:<br /> - The authors first characterise migration towards serum in detail using a well-characterised lab strain but one of the main strengths of this study is that they then expand their scope to observe equivalent behaviours in several clinical serovars. This strongly supports the clinical relevance of the key behaviours that they document.

      - The interdisciplinary nature of this study is a real strength and greatly increases the scope of the conclusions presented. Working from a structural understanding of chemoreceptor-ligand binding through to a larger-scale genetic analysis of chemoreceptor phylogeny allows the authors to draw important (although I find not always definitive) conclusions about bacterial migration towards human serum across a wide range of bacterial species (including many important pathogens). This is a very exciting approach and I was particularly interested to see the authors follow this up with observations of migration in C. koseri (a clinical isolate with little known about its chemotactic capabilities).

      - The authors use experiments that compete migrating strains against each other and these offer an exciting glimpse into how bacterial movement and navigation could play out in multi-species environments like the human gut.

      - The authors successfully identify a single component of human serum (i.e. serine) as one specific attractant driving the bacterial migration response seen here. Teasing apart the response of bacteria to complex stimuli like human serum is an important step here.

      Weaknesses:<br /> There are several issues that I would personally like to see addressed in this study:

      1) The authors refer to human serum as a chemoattractant numerous times throughout the study (including in the title). As the authors acknowledge, human serum is a complex mixture and different components of it may act as chemoattractants, chemo-repellents (particularly those with bactericidal activities), or may elicit other changes in motility (e.g. chemokinesis). The authors present convincing evidence that cells are attracted to serine within human serum - which is already a well-known bacterial chemoattractant. Indeed, their ability to elucidate specific elements of serum that influence bacterial motility is a real strength of the study. However, human serum itself is not a chemoattractant and this claim should be re-phrased - bacteria migrate towards human serum, driven at least in part by chemotaxis towards serine.

      2) Linked to the previous point, several bacterial species (including E. coli - one of the bacterial species investigated here) are capable of osmotaxis (moving up or down gradients in osmolality). Whilst chemotaxis to serine is important here, could movement up the osmotic gradient generated by serum injection play a more general role? It could be interesting to measure the osmolality of the injected serum and test whether other solutions with similar osmolality elicit a similar migratory response. Another important control here would be to treat human serum with serine racemase and observe how this impacts bacterial migration.

      3) The inference of the authors' genetic analysis combined with the migratory response of E. coli and C. koseri to human serum shown in Fig. 6 is that Tsr drives movement towards human serum across a range of Enterobacteriaceae species. The evidence for the importance of Tsr here is currently correlative - more causal evidence could be presented by either studying the response of tsr mutants in these two species (certainly these should be readily available for E. coli) or by studying the response of these two species to serine gradients.

      4) The migratory response of E. coli looks striking when quantified (Fig. 6C), but is really unclear from looking at Panel B - it would be more convincing if an explanation was offered for why these images look so much less striking than analogous images for other species (E.g. Fig. 6A).

      5) It is unclear why the fold-change in bacterial distribution shows an approximately Gaussian shape with a peak at a radial distance of between 50 -100 um from the source (see for example Fig. 2H). Initially, I thought that maybe this was due to the presence of the microcapillary needle at the source, but the CheY distribution looks completely flat (Fig. 3I). Is this an artifact of how the fold-change is being calculated? Certainly, it doesn't seem to support the authors' claim that cells increase in density to a point of saturation at the source. Furthermore, it also seems inappropriate to apply a linear fit to these non-linear distributions (as is done in Fig. 2H and in the many analogous figures throughout the manuscript).

      6) The authors present several experiments where strains/ serovars competed against each other in these chemotaxis assays. As mentioned, these are a real strength of the study - however, their utility is not always clear. These experiments are useful for studying the effects of competition between bacteria with different abilities to climb gradients. However, to meaningfully interpret these effects, it is first necessary to understand how the different bacteria climb gradients in monoculture. As such, it would be instructive to provide monoculture data alongside these co-culture competition experiments.

      7) Linked to the above point, it would be especially instructive to test a tsr mutant's response in monoculture. Comparing the bottom row of Fig. 3G to Fig. 3I suggests that when in co-culture with a cheY mutant, the tsr mutant shows a higher fold-change in radial distribution than the WT strain. Fig. 4G shows that a tsr mutant can chemotax towards aspartate at a similar, but reduced rate to WT. This could imply that (like the trg mutant), a tsr mutant has a more general motility defect (e.g. a speed defect), which could explain why it loses out when in competition with the WT in gradients of human serum, but actually seems to migrate strongly to human serum when in co-culture with a cheY mutant. This should be resolved by studying the response of a tsr mutant in monoculture.

      8) In Fig. 4, the response of the three clinical serovars to serine gradients appears stronger than the lab serovar, whilst in Fig. 1, the response to human serum gradients shows the opposite trend with the lab serovar apparently showing the strongest response. Can the authors offer a possible explanation for these slightly confusing trends?

      9) In Fig. S2, it seems important to present quantification of the effect of serine racemase and the reported lack of response to NE and DHMA - the single time-point images shown here are not easy to interpret.

      10) Importantly, the authors detail how they controlled for the effects of pH and fluid flow (Line 133-136). Did the authors carry out similar controls for the dual-species experiments where fluorescent imaging could have significantly heated the fluid droplet driving stronger flow forces?

    1. Reviewer #1 (Public Review):

      Strengths:<br /> The authors first perform several important controls to show that the expressed mutant actin is properly folded, and then show that the Arp2/3 complex behaves similarly with WT and mutant actin via a TIRF microscopy assay as well as a bulk pyrene-actin assay. A TIRF assay showed a small but significant reduction in the rate of elongation of the mutant actin suggesting only a mild polymerization defect.

      Based on in silico analysis of the close location of the actin point mutation and bound cofilin, cofilin was chosen for further investigation. Faster de novo nucleation by cofilin was observed with mutant actin. In contrast, the mutant actin was more slowly severed. Both effects favor the retention of filamentous mutant actin. In solution, the effect of cofilin concentration and pH was assessed for both WT and mutant actin filaments, with a more limited repertoire of conditions in a TIRF assay that directly showed slower severing of mutant actin.

      Lastly, the mutated residue in actin is predicted to interact with the cardiomyopathy loop in myosin and thus a standard in vitro motility assay with immobilized motors was used to show that non-muscle myosin 2A moved mutant actin more slowly, explained in part by a reduced affinity for the filament deduced from transient kinetic assays. By the same motility assay, myosin 5A also showed impaired interaction with the mutant filaments.

      The Discussion is interesting and concludes that the mutant actin will co-exist with WT actin in filaments, and will contribute to altered actin dynamics and poor interaction with relevant myosin motors in the cellular context. While not an exhaustive list of possible defects, this is a solid start to understanding how this mutation might trigger a disease phenotype.

      Weaknesses:<br /> Potential assembly defects of the mutant actin could be more thoroughly investigated if the same experiment shown in Fig. 2 was repeated as a function of actin concentration, which would allow the rate of disassembly and the critical concentration to also be determined.

      The more direct TIRF assay for cofilin severing was only performed at high cofilin concentration (100 nM). Lower concentrations of cofilin would also be informative, as well as directly examining by the TIRF assay the effect of cofilin on filaments composed of a 50:50 mixture of WT:mutant actin, the more relevant case for the cell.

      The more appropriate assay to determine the effect of the actin point mutation on class 5 myosin would be the inverted assay where myosin walks along single actin filaments adhered to a coverslip. This would allow an evaluation of class 5 myosin processivity on WT versus mutant actin that more closely reflects how Myo5 acts in cells, instead of the ensemble assay used appropriately for myosin 2.

    1. Joint Public Review:

      The authors are trying to distinguish between four models of the role of glypicans (HSPGs) on the Dpp/BMP gradient in the Drosophila wing, schematized in Fig. 1: (1) "Restricted diffusion" (HSPGs transport Dpp via repetitive interaction of HS chains with Dpp); (2) "Hindered diffusion" (HSPGs hinder Dpp spreading via reversible interaction of HS chains with Dpp); (3) "Stabilization" (HSPGs stabilize Dpp on the cell surface via reversible interaction of HS chains with Dpp that antagonizes Tkv-mediated Dpp internalization); and (4) "Recycling" (HSPGs internalize and recycle Dpp).

      To distinguish between these models, the authors generate new alleles for the glypicans Dally and Dally-like protein (Dlp) and for Dpp: a Dally knock-out allele, a Dally YFP-tagged allele, a Dally knock-out allele with 3HA-Dlp, a Dlp knock-out allele, a Dlp allele containing 3-HA tags, and a Dpp lacking the HS-interacting domain. Additionally, they use an OLLAS-tag Dpp (OLLAS being an epitope tag against which extremely high affinity antibodies exist). They examine OLLAS-Dpp or HA-Dpp distribution, phospho-Mad staining, adult wing size.

      They find that over-expressed Dally - but not Dlp - expands Dpp distribution in the larval wing disc. They find that the Dally[KO] allele behaves like a Dally strong hypomorph Dally[MH32]. The Dally[KO] - but not the Dlp[KO] - caused reduced pMad in both anterior and posterior domains and reduced adult wing size (particularly in the Anterior-Posterior axis). These defects can be substantially corrected by supplying an endogenously tagged YFP-tagged Dally. By contrast, they were not rescued when a 3xHA Dlp was inserted in the Dally locus. These results support their conclusion that Dpp interacts with Dally but not Dlp.

      They next wanted to determine the relative contributions of the Dally core or the HS chains to the Dpp distribution. To test this, they over-expressed UAS-Dally or UAS-Dally[deltaHS] (lacking the HS chains) in the dorsal wing. Dally[deltaHS] over-expression increased the distribution of OLLAS-Dpp but caused a reduction in pMad. They do a critical experiment, making the Dally[deltaHS] allele, they find that loss of the HS chains is nearly as severe as total loss of Dally (i.e., Dally[KO]). These results indicate that the HS are critical for Dally's role in Dpp distribution and signaling.

      Prior work has shown that a stretch of 7 amino acids in the Dpp N-terminal domain is required to interact with heparin but not with Dpp receptors (Akiyama, 2008). The authors generated an HA-tagged Dpp allele lacking these residues (HA-dpp[deltaN]). It is an embryonic lethal allele, but they can get some animals to survive to larval stages if they also supply a transgene called "JAK" containing dpp regulatory sequences. In the JAK; HA-dpp[deltaN] mutant background, they find that the distribution and signaling of this Dpp molecule is largely normal. While over-expressed Dally can increase the distribution of HA-dpp[deltaN], over-expression of Dally[deltaHS] cannot. These latter results support the model that the HS chains in Dally are required for Dpp function but not because of a direct interaction with Dpp.

      In the last part of the results, they attempt to determine if the Dpp receptor Thickveins (Tkv) is required for Dally-HS chains interaction. The 2008 (Akiyama) model posits that Tkv activates pMad downstream of Dpp and also internalizes and degrades Dpp. A 2022 (Romanova-Michaelides) model proposes that Dally (not Tkv) internalizes Dpp. To distinguish between these models, the authors deplete Tkv from the dorsal compartment of the wing disc and found that extracellular Dpp increased and expanded in that domain. These results support the model that Tkv is required to internalize Dpp. They then tested the model that Dally antagonizes Tkv-mediated Dpp internalization by determining whether the defective extracellular Dpp distribution in Dally[KO] mutants could be rescued by depleting Tkv. Extracellular Dpp did increase in the D vs V compartment, potentially providing some support for their model. The results are statistically significant but the statistics are buried in an excel file without a read-me page. The code for the statistics is available from Github. These p values should be made more readily accessible and/or intelligible to the reader.

      Strengthens:<br /> 1. New genomically-engineered alleles<br /> A considerable strength of the study is the generation and characterization of new Dally, Dlp and Dpp alleles. These reagents will be of great use to the field.

      2. Surveying multiple phenotypes<br /> The authors survey numerous parameters (Dpp distribution, Dpp signaling (pMad) and adult wing phenotypes) which provides many points of analysis.

      Weaknesses (minor):<br /> 1. The results are statistically significant but the statistics are buried in a dense excel file without a read-me page. The code for the statistics is available from Github. These p values should be made more readily accessible to the reader.

      An appraisal of whether the authors achieved their aims, and whether the results support their conclusions.<br /> The authors' model is that Dally (not Dlp) is required for Dpp distribution and signaling but that this is not due to a direct interaction with Dpp. Rather, they posit that Dally-HS antagonize Tkv-mediated Dpp internalization. Currently the results of the experiments could be considered consistent with their model. Finally, their results support the idea that one or more as-yet unidentified proteins interact with Dally-HS chains to control Dpp distribution and signaling in the wing disc.

      There is much debate and controversy in the Dpp morphogen field. The generation of new, high quality alleles in this study will be useful to Drosophila community, and the results of this study support the concept that Tkv but not Dally regulate Dpp internalization. Thus the work could be impactful and fuel new debates among the morphogen researchers.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors perform a multidisciplinary approach to describe the conformational plasticity of P-Rex1 in various states (autoinhibited, IP4 bound, and PIP3 bound). Hydrogen-deuterium exchange (HDX) is used to reveal how IP4 and PIP3 binding affect intramolecular interactions. While IP4 is found to stabilize autoinhibitory interactions, PIP3 does the opposite, leading to deprotection of autoinhibitory sites. Cryo-EM of IP4 bound P-Rex1 reveals a structure in the autoinhibited conformation, very similar to the unliganded structure reported previously (Chang et al. 2022). Mutations at observed autoinhibitory interfaces result in a more open structure (as shown by SAXS), reduced thermal stability, and increased GEF activity in biochemical and cellular assays. Together their work portrays a dynamic enzyme that undergoes long-range conformational changes upon activation on PIP3 membranes. The results are technically sound (apart from a few points mentioned below) and the conclusions are justified. The main drawback is the limited novelty due to the recently published structure of unliganded P-Rex1, which is virtually identical to the IP4 bound structure presented here. Novel aspects suggest a regulatory role for IP4, but the exact significance and mechanism of this regulation have not been explored.

      Strengths:<br /> The authors use a multitude of techniques to describe the dynamic nature and conformational changes of P-Rex1 upon binding to IP4 and PIP3 membranes. The different approaches together fit well with the overall conclusion that IP4 binding negatively regulates P-Rex1, while binding to PIP3 membranes leads to conformational opening and catalytic activation. The experiments are performed very thoroughly and are technically sound (apart from a few comments mentioned below). The results are clear and support the conclusions.

      Weaknesses:<br /> 1) The novelty of the study is compromised due to the recently published structure of unliganded P-Rex1 (Chang et al. 2022). The unliganded and IP4-bound structure of P-Rex1 appear virtually identical, however, no clear comparison is presented in the manuscript. In the same paper, a very similar model of P-Rex1 activation upon binding to PIP3 membranes and Gbeta/gamma is presented.

      2) The authors demonstrate that IP4 binding to P-Rex1 results in catalytic inhibition and increased protection of autoinhibitory interfaces, as judged by HDX. The relevance of this in a cellular setting is not clear and is not experimentally demonstrated. Further, mechanistically, it is not clear whether the biochemical inhibition by IP4 of PIP3 activated P-Rex1 is due to competition of IP4 with activating PIP3 binding to the PH domain of P-Rex1, or due to stabilizing the autoinhibited conformation, or both.

      3) It is difficult to judge the error in the HDX experiments presented in Sup. data 1 and 2. In the method section, it is stated that the results represent the average from two samples. How is the SD error calculated in Fig.1B-C?

    1. Reviewer #1 (Public Review):

      Summary:<br /> During the last decades, extensive studies (mostly neglected by the authors), using in vitro and in vivo models, have elucidated the five-step mechanism of intoxication of botulinum neurotoxins (BoNTs). The binding domain (H chain) of all serotypes of BoNTs binds polysialogangliosides and the luminal domain of a synaptic vesicle protein (which varies among serotypes). When bound to the synaptic membrane of neurons, BoNTs are rapidly internalized by synaptic vesicles (SVs) via endocytosis. Subsequently, the catalytic domain (L chain) translocates, a process triggered by the acidification of these organelles. Following translocation, the disulfide bridge connecting the H chain with the L chain is reduced by the thioredoxin reductase/thioredoxin system, and it is refolded by the chaperone Hsp90 on SV's surface. Once released into the cytosol, the L chains of different serotypes cleave distinct peptide bonds of specific SNARE proteins, thereby disrupting neurotransmission.

      In this study, Yeo et al. extensively revise the neuronal intoxication model, suggesting that BoNT/A follows a more complex intracellular route than previously thought. The authors propose that upon internalization, BoNT/A-containing endosomes are retro-axonally trafficked to the soma. At the level of the neuronal soma, this serotype then traffics to the endoplasmic reticulum (ER) via the Golgi apparatus. The ER SEC61 translocon complex facilitates the translocation of BoNT/A's LC from the ER lumen into the cytosol, where the thioredoxin reductase/thioredoxin system and HSP complexes release and refold the catalytic L chain. Subsequently, the L chain diffuses and cleaves SNAP25 first in the soma before reaching neurites and synapses.

      Strengths:<br /> I appreciate the authors' efforts to confirm that the newly established methods somehow recapitulate aspects of the BoNTs mechanism of action, such as toxin binding and uptake occurring at the level of active synapses. Furthermore, even though I consider the SNAPR approach inadequate, the genome-wide RNAi screen has been well executed and thoroughly analyzed. It includes well-established positive and negative controls, making it a comprehensive resource not only for scientists working in the field of botulinum neurotoxins but also for cell biologists studying endocytosis more broadly.

      Weaknesses:<br /> I have several concerns about the authors' main conclusions, primarily due to the lack of essential controls and validation for the newly developed methods used to assess toxin cleavage and trafficking into neurons. Furthermore, there is a significant discrepancy between the proposed intoxication model and existing studies conducted in more physiological settings. In my opinion, the authors have omitted over 20 years of work done in several labs worldwide (Montecucco, Montal, Schiavo, Rummel, Binz, etc.). I want to emphasize that I support changes in biological dogma only when these changes are supported by compelling experimental evidence, which I could not find in the present manuscript.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This study examines the spatial and temporal patterns of occurrence and the interspecific associations within a terrestrial mammalian community along human disturbance gradients. They conclude that human activity leads to a higher incidence of positive associations.

      Strengths:<br /> The theoretical framework of the study is brilliantly introduced. Solid data and sound methodology. This study is based on an extensive series of camera trap data. Good review of the literature on this topic.

      Weaknesses:<br /> The authors use the terms associations and interactions interchangeably. It is not clear what the authors mean by "associations". A brief clarification would be helpful. Also, the authors do not delve into the different types of association found in the study. A more ecological perspective explaining why certain species tend to exhibit negative associations and why others show the opposite pattern (and thus, can be used as indicator species) is missing. Also, the authors do not distinguish between significant (true) non-random associations and random associations. In my opinion, associations are those in which two species co-occur more or less than expected by chance. This is not well addressed in the present version of the manuscript.

      The obtained results support the conclusions of the study.

      Anthropogenic pressures can shape species associations by increasing spatial and temporal co-occurrence, but above a certain threshold, the positive influence of human activity in terms of species associations could be reverted. This study can stimulate further work in this direction.

    1. Reviewer #1 (Public Review):

      The manuscript has helped address a long-standing mystery in splicing regulation: whether splicing occurs co- or post-transcriptionally. Specifically, the authors (1) uniquely combined smFISH, expansion microscopy, and live cell imaging; (2) revealed the ordering and spatial distribution of splicing steps; and (3) discovered that nascent, not-yet-spliced transcripts move more slowly around the transcription site and undergo splicing as they move through the clouds. Based on the experimental results, the authors suggest that the observation of co-transcriptional splicing in previous literature could be due to the limitation of imaging resolution, meaning that the observed co-transcriptional splicing might actually be post-transcriptional splicing occurring in proximity to the transcription site. Overall, the work presented here clearly provides a comprehensive picture of splicing regulation.

    1. Reviewer #1 (Public Review):

      Summary<br /> While DNA sequence divergence, differential expression, and differential methylation analysis have been conducted between humans and the great apes to study changes that "make us human", the role of lncRNAs and their impact on the human genome and biology has not been fully explored. In this study, the authors computationally predict HSlncRNAs as well as their DNA Binding sites using a method they have developed previously and then examine these predicted regions with different types of enrichment analyses. Broadly, the analysis is straightforward and after identifying these regions/HSlncRNAs the authors examined their effects using different external datasets.

      I no longer have any concerns about the manuscript as the authors have addressed my comments in the first round of review.

    1. Reviewer #1 (Public Review):

      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 ejaculations rates, is worth emphasizing for the formation of pair bonds. 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. The identification of brain regions for pair bond maintenance centered around the amygdala was also intriguing.

    1. Reviewer #1 (Public Review):

      In this article, different machine learning models (pan-specific, peptide-specific, pre-trained, and ensemble models) are tested to predict TCR-specificity from a paired-chain peptide-TCR dataset. The data consists of 6,358 positive observations across 26 peptides (as compared to six peptides in NetTCR version 2.1) after several pre-processing steps (filtering and redundancy reduction). For each positive sample, five negative samples were generated by swapping TCRs of a given peptide with TCRs binding to other peptides. The weighted loss function is used to deal with the imbalanced dataset in pan-specific models.

      The results demonstrate that the redundant data introduced during training did not lead to performance gain; rather, a decrease in performance was observed for the pan-specific model. The removal of outliers leads to better performance.<br /> <br /> To further improve the peptide-specific model performance, an architecture is created to combine pan-specific and peptide-specific models, where the pan-specific model is trained on pan-specific data while keeping the peptide-specific part of the model frozen, and the peptide-specific model is trained on a peptide-specific dataset while keeping the pan-specific part of the model frozen. This model surpassed the performance of individual pan-specific and peptide-specific models. Finally, sequence similarity-based predictions of TCRbase are integrated into the pre-trained CNN model, which further improved the model performance (mostly due to the better discrimination of binders and non-binders).<br /> <br /> The prediction for unseen peptides is still low in a pan-specific model; however, an improvement in prediction is observed for peptides with high similarity to the ones in the training dataset. Furthermore, it is shown that 15 observations show satisfactory performance as compared to the ~150 recommended in the literature.<br /> <br /> Models are evaluated on the external dataset (IMMREP benchmark). Peptide-specific models performed competitively with the best models in the benchmark. The pre-trained model performed worst, which the authors suggested could be because of positive and negative sample swapping across training and testing sets. To resolve this issue, they applied the redundancy removal technique to the IMMER dataset. The results agreed with the earlier conclusion that the pre-trained models surpassed peptide-specific models and the integration of similarity-based methods leads to performance boost. It highlights the need for the creation of a new benchmark without data redundancy or leakage problems.

      The manuscript is well-written, clear, and easy to understand. The data is effectively presented. The results validate the drawn conclusions.

    1. Joint Public Review:

      Here, the authors compare how different operationalizations of adverse childhood experience exposure related to patterns of skin conductance response during a fear conditioning task. They use a large dataset to definitively understand a phenomenon that, to date, has been addressed using a range of different definitions and methods, typically with insufficient statistical power. Specifically, the authors compared the following operationalizations: dichotomization of the sample into "exposed" and "non-exposed" categories, cumulative adversity exposure, specificity of adversity exposure, and dimensional (threat versus deprivation) adversity exposure. The paper is thoughtfully framed and provides clear descriptions and rationale for procedures, as well as package version information and code. The authors' overall aim of translating theoretical models of adversity into statistical models, and comparing the explanatory power of each model, respectively, is an important and helpful addition to the literature. However, the analysis would be strengthened by employing more sophisticated modelling techniques that account for between-subjects covariates and the presentation of the data needs to be streamlined to make it clearer for the broad audience for which it is intended.

      Strengths<br /> Several outstanding strengths of this paper are the large sample size and its primary aim of statistically comparing leading theoretical models of adversity exposure in the context of skin conductance response. This paper also helpfully reports Cohen's d effect sizes, which aid in interpreting the magnitude of the findings. The methods and results are generally thorough.

      Weaknesses<br /> The largest concern is that the paper primarily relies on ANOVAs and pairwise testing for its analyses and does not include between-subjects covariates. Employing mixed-effects models instead of ANOVAs would allow more sophisticated control over sources of random variance in the sample (especially important for samples from multi-site studies such as the present study), and further allow the inclusion of potentially relevant between-subjects covariates such as age (e.g. Eisenstein et al., 1990) and gender identity or sex assigned at birth (e.g. Kopacz II & Smith, 1971) (perhaps especially relevant due to possible to gender or sex-related differences in ACE exposure; e.g. Kendler et al., 2001). Also, proxies for socioeconomic status (e.g. income, education) can be linked with ACE exposure (e.g. Maholmes & King, 2012) and warrant consideration as covariates, especially if they differ across adversity-exposed and unexposed groups. On a related methodological note, the authors mention that scores representing threat and deprivation were not problematically collinear due to VIFs being <10; however, some sources indicate that VIFs should be <5 (e.g. Akinwande et al., 2015).

      Additionally, the paper reports that higher trait anxiety and depression symptoms were observed in individuals exposed to ACEs, but it would be helpful to report whether patterns of SCR were in turn associated with these symptom measures and whether the different operationalizations of ACE exposure displayed differential associations with symptoms. Given the paper's framing of SCR as a potential mechanistic link between adversity and mental health problems, reporting these associations would be a helpful addition. These results could also have implications for the resilience interpretation in the discussion (lines 481-485), which is a particularly important and interesting interpretation.

      Given that the manuscript criticizes the different operationalizations of childhood adversity, there should be greater justification of the rationale for choosing the model for the main analyses. Why not the 'cumulative risk' or 'specificity' model? Related to this, there should also be a stronger justification for selecting the 'moderate' approach for the main analysis. Why choose to cut off at moderate? Why not severe, or low? Related to this, why did they choose to cut off at all? Surely one could address this with the continuous variable, as they criticize cut-offs in Table 2.

      In the Introduction, the authors predict less discrimination between signals of danger (CS+) and safety (CS-) in trauma-exposed individuals driven by reduced responses to the CS+. Given the potential impact of their findings for a larger audience, it is important to give greater theoretical context as to why CS discrimination is relevant here, and especially what a reduction in response specifically to danger cues would mean (e.g. in comparison to anxiety, where safety learning is impacted).

    1. Joint Public Review:

      The present work establishes 14-3-3 proteins as binding partners of spastin and suggests that this binding is positively regulated by phosphorylation of spastin. The authors show evidence that 14-3-3 - spastin binding prevents spastin ubiquitination and final proteasomal degradation. By using drugs and peptides that separately inhibit 14-3-3 binding or spastin activity, they show that both proteins are necessary for axon regeneration in cell culture and in vivo models in rats.

      Major strengths<br /> -The data establishing 14-3-3 and spastin as binding partners is convincing, as is its regulation by phosphorylation and its impact on protein levels related to the activity of the ubiquitin-proteasome system.

      -The effects of FC-A on locomotor recovery after spinal cord contusion is very interesting.

      Major weaknesses<br /> -Given that spastazoline has a major impact on neurite outgrowth suggests that cells simply cannot grow in the presence of the inhibitor and raises serious questions about any selectivity for the concomitant effect FC-A - dependent growth.

      -The histological data and analyses following spinal cord injury are not convincing. For example, the colabeling of NF and 5-HT is not convincingly labeling fibers. Also, the quality, resolution and size of the images is insufficient to support the quantitative data and it is hence difficult to interpret the data. Reviewers recognize that during the review process, efforts were made to improve the quality of the images.

      -Reviewers also observed that the data to infer Spastin actions on Microtubules across different experimental models is weak and that claims about "MT severing" and "microtubules dynamics" were wrongly used given the provided evidence.

      -The manuscript lacks direct evidence that a 14-3-3 and spastin function as a complex in the same pathway to promote regeneration. It is recognized, however, that the authors had made changes in the manuscript title and claims not to imply that the current evidence is sufficient in that matter.

    1. Reviewer #1 (Public Review):

      Summary:

      The paper by Majeed et al has a valuable and worthwhile aim: to provide a set of tools to standardize the quantification of synapses using fluorescent markers in the nematode C. elegans. Using current approaches, the identification of synapses using fluorescent markers is tedious and subject to significant inter-experimenter variability. Majeed et al successfully develop and validate a computational pipeline called "WormPsyQi" that overcomes some of these obstacles and will be a powerful resource for many C. elegans neurobiologists.

      Strengths:

      The computational pipeline is rigorously validated and shown to accurately quantitate fluorescent puncta, at least as well as human experimenters. The inclusion of a mask - a region of interest defined by a cytoplasmic marker - is a powerful and useful approach. Users can take advantage of one of four pre-trained neural networks, or train their own. The software is freely available and appears to be user-friendly. A series of rigorous experiments demonstrates the utility of the pipeline for measuring differences in the number of synaptic puncta between sexes and across developmental stages. Neuron-to-neuron heterogeneity in patterns of synaptic growth during development are convincingly demonstrated. Weaknesses and caveats are realistically discussed.

    1. Reviewer #1 (Public Review):

      The authors developed computational models that capture the electrical and Ca2+ signaling behavior in mesenteric arterial cells from male and female mice. Sex-specific differences in the L-type calcium channel and two voltage-gated potassium channels were carefully tuned based on experimental measurements. To incorporate the stochasticity of ion channel openings seen in smooth muscle cells under physiological conditions, noise was added to the membrane potential and the sarcoplasmic Ca2+ concentration equations. Finally, the models were assembled into 1D vessel representations and used to investigate the tissue-level electrical response to an L-type calcium channel blocker. This comprehensive computational framework helped provide nuanced insight into arterial myocyte function difficult to achieve through traditional experimental methods and can be further expanded into tissue-level studies that incorporate signaling pathways for blood pressure control.

      Throughout the paper, model behavior was both validated by experimental recordings and well supported by previously published data. The main findings from the models suggested that sex-specific differences in membrane potential regulation and Ca2+ handling are attributable to variability in the gating of a small number of voltage-gated potassium channels and L-type calcium channels. This variability contributes to a higher Ca2+ channel blocker sensitivity in female arterial vessels. Overall, the study successfully presented novel sex-specific computational models of mesenteric arterial myocytes and demonstrated their use in drug-testing applications.

    1. Reviewer #1 (Public Review):

      Summary:

      Otarigho et al. presented a convincing study revealing that in C. elegans, the neuropeptide Y receptor GPCR/NPR-15 mediates both molecular and behavioral immune responses to pathogen attack. Previously, three npr genes were found to be involved in worm defense. In this study, the authors screened mutants in the remaining npr genes against P. aeruginosa-mediated killing and found that npr-15 loss-of-function improved worm survival. npr-15 mutants also exhibited enhanced resistance to other pathogenic bacteria but displayed significantly reduced avoidance to S. aureus, independent of aerotaxis, pathogen intake and defecation. The enhanced resistance in npr-15 mutant worms was attributed to upregulation of immune and neuropeptide genes, many of which were controlled by the transcription factors ELT-2 and HLH-30. The authors found that NPR-15 regulates avoidance behavior via the TRPM gene, GON-2, which has a known role in modulating avoidance behavior through the intestine. The authors further showed that both NPR-15-dependent immune and behavioral responses to pathogen attack were mediated by the NPR-15-expressing neurons ASJ. Overall, the authors discovered that the NPR-15/ASJ neural circuit may regulate distinct defense mechanisms against pathogens under different circumstances. This study provides novel and useful information to researchers in the fields of neuroimmunology and C. elegans research.

      Strengths:

      1. This study uncovered specific molecules and neuronal cells that regulate both molecular immune defense and behavior defense against pathogen attack and indicate that the same neural circuit may regulate distinct defense mechanisms under different circumstances. This discovery is significant because it not only reveals regulatory mechanisms of different defense strategies but also suggests how C. elegans utilize its limited neural resources to accomplish complex regulatory tasks.

      2. The conclusions in this study are supported by solid evidence, which are often derived from multiple approaches and/or experiments. Multiple pathogenic bacteria were tested to examine the effect of NPR-15 loss-of-function on immunity; the impacts of pharyngeal pumping and defecation on bacterial accumulation were ruled out when evaluating defense; RNA-seq and qPCR were used to measure gene expression; gene inactivation was done in multiple strains to assess gene function.

      3. Gene differential expression, gene ontology and pathway analyses were performed to demonstrate that NPR-15 controls immunity through regulating immune pathways.

      4. Elegant approaches were employed to examine avoidance behavior (partial lawn, full lawn, and lawn occupancy) and the involvement of neurons in regulating immunity and avoidance (the use of a diverse array of mutant strains).

      5. Statistical analyses were appropriate and adequate.

    1. Reviewer #1 (Public Review):

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

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

      Weaknesses:<br /> There are minor concerns like typo mistakes and missing control data histology pictures which should be corrected.

    1. Joint Public Review:

      Summary:

      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, gradually leads to multiple organ failure and high mortality. Strategies to treat CSS including pulse steroid therapy normally leads to severe side effects. Therefore, it is still required to develop safe strategy with high efficacy to treat CSS. In clinic, sepsis is well characterized to exhibit CSS and therefore multiple studies utilized LPS-induced sepsis model to evaluate CSS symptom. In this study, the authors examined whether leucine, an essential amino acid that has been absorbed daily in our body, could ameliorate CSS symptom 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:

      The study is overall well designed and the results are well analyzed with only minor issues. The methods they utilized is appropriate.

      Weaknesses:

      The mechanistical 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.

    1. Reviewer #2 (Public Review):

      Summary:<br /> Seignette et al. investigated the potential roles of axo-axonic (chandelier) cells (ChCs) in a sensory system, namely visual processing. As introduced by the authors, the axo-axonic cell type has remained (and still is) somehow mysterious in its function. Seignette and colleagues leveraged the development of a transgenic mouse line selective for ChC, and applied a very wide range of techniques: transsynaptic rabies tracing, optogenetic input activation, in vitro electrophysiology, 2-photon recording in vivo, behavior and chemogenetic manipulations, to precisely determine the contribution of ChCs to the primary visual cortex network.

      The main findings are 1) the identification of synaptic inputs to ChC, with a majority of local, deep layer principal neurons (PN), 2) the demonstration that ChC is strongly and synchronously activated by visual stimuli with low specificity in naive animals, 3) the recruitment of ChC by arousal/visuomotor mismatch, 4) the induction of functional and structural plasticity at the ChC-PN module, and, 5) the weak disinhibition of PNs induced by ChCs silencing. All these findings are strongly supported by experimental data and thoroughly compared to available evidence.

      Strengths:<br /> This article reports an impressive range of very demanding experiments, which were well executed and analyzed, and are presented in a very clear and balanced manner. Moreover, the manuscript is well-written throughout, making it appealing to future readers. It has also been a pleasure to review this article.

      In sum, this is an impressive study and an excellent manuscript, that presents no major flaws.

      Notably, this study is one of the first studies to report on the activities and potential roles of axo-axonic cells in an active, integrated brain process, beyond locomotion as reported and published in V1. This type of research was much awaited in the fields of interneuron and vision research.

      Weaknesses:<br /> There are no fundamental weaknesses; the latter mainly concern the presentation of the main results.

      The main weakness may be that the different sections appear somehow disconnected conceptually.

      Additionally, some parts deserve a more in-depth clarification/simplification of concepts and analytic methods for scientists outside the subfield of V1 research. Indeed, this paper will be of key interest to researchers of various backgrounds.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this paper, the authors show that the degree of pigmentation for RPE cells is not correlated with a level of maturation and function. They suggest that this status could be different in vitro than in vivo but do not provide proper experiments to validate this hypothesis. However, it is the first time that the absence of a correlation between pigmentation and function has been studied.

      Strengths:<br /> The methods are good and the experiments are very rigorous.

      Weaknesses:<br /> Demonstration of in vitro but no in vivo data.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This work describes a simple mechanical model of worm locomotion, using a series of rigid segments connected by damped torsional springs and immersed in a viscous fluid. It uses this model to simulate forward crawling movement, as well as omega turns.

      Strengths:<br /> The primary strength is in applying a biomechanical model to omega-turn behaviors. The biomechanics of nematode turning behaviors are relatively less well described and understood than forward crawling. The model itself may be a useful implementation to other researchers, particularly owing to its simplicity.

      Weaknesses:<br /> The strength of the model presented in this work relative to prior approaches is not well supported, and in general, the paper would be improved with a better description of the broader context of existing modeling literature related to undulatory locomotion. This paper claims to improve on previous approaches to taking body shapes as inputs. However, the sole nematode model cited aims to do something different, and arguably more significant, which is to use experimentally derived parameters to model both the neural circuits that induce locomotion as well as the biomechanics and to subsequently compare the model to experimental data. Other modeling approaches do take experimental body kinematics as inputs and use them to produce force fields, however, they are not cited or discussed. Finally, the overall novelty of the approach is questionable. A functionally similar approach was developed in 2012 to describe worm locomotion in lattices (Majmudar, 2012, Roy. Soc. Int.), which is not discussed and would provide an interesting comparison and needed context.

      The idea of applying biomechanical models to describe omega turns in C. elegans is a good one, however, the kinematic basis of the model as used in this paper (the authors do note that the control angle could be connected to a neural model, but don't do so in this work) limits the generation of neuromechanical control hypotheses. The model may provide insights into the biomechanics of such behaviors, however, the results described are very minimal and are purely qualitative. Overall, direct comparisons to the experiments are lacking or unclear. Furthermore, the paper claims the value of the model is to produce the force fields from a given body shape, but the force fields from omega turns are only pictured qualitatively. No comparison is made to other behaviors (the force experienced during crawling relative to turning for example might be interesting to consider) and the dependence of the behavior on the model parameters is not explored (for example, how does the omega turn change as the drag coefficients are changed). If the purpose of this paper is to recapitulate the swim-to-crawl transition with a simple model, and then apply the model to new behaviors, a more detailed analysis of the behavior of the model variables and their dependence on the variables would make for a stronger result. In some sense, because the model takes kinematics as an input and uses previously established techniques to model mechanics, it is unsurprising that it can reproduce experimentally observed kinematics, however, the forces calculated and the variation of parameters could be of interest.

      Relatedly, a justification of why the drag coefficients had to be changed by a factor of 100 should be explored. Plate conditions are difficult to replicate and the rheology of plates likely depends on a number of factors, but is for example, changes in hydration level likely to produce a 100-fold change in drag? or something more interesting/subtle within the model producing the discrepancy?

      Finally, the language used to distinguish different modeling approaches was often unclear. For example, it was unclear in what sense the model presented in Boyle, 2012 was a "kinetic model" and in many situations, it appeared that the term kinematic might have been more appropriate. Other phrases like "frictional forces caused by the tension of its muscles" were unclear at first glance, and might benefit from revision and more canonical usage of terms.

    1. Reviewer #1 (Public Review):

      With genephys, the author provides a generative model of brain responses to stimulation. This generative model allows to mimic specific parameters of a brain response at the sensor level, to test the impact of those parameters on critical analytic methods utilized on real M/EEG data. Specifically, they compare the decoding output for differently set parameters to the decoding pattern observed in a classical passive viewing study in terms of the resulting temporal generalization matrix (TGM). They identify that the correspondence between the mimicked and the experimental TGM to depend on an oscillatory component that spans multiple channels, frequencies, and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory, faster component.

      A strength of the article is that it considers the complexity of neural data that contribute to the findings obtained in stimulation experiments. An additional strength is the provision of a Python package that allows scientists to explore the potential contribution of different aspects of neural signals to obtained experimental data and thereby to potentially test their theoretical assumptions critical parameters that contribute to their experimental data.

      A weakness of the paper is that the power of the model is illustrated for only one specific set of parameters, added in a stepwise manner and the comparison to on specific empirical TGM, assumed to be prototypical; And that this comparison remains descriptive. (That is could a different selection of parameters lead to similar results and is there TGM data which matches these settings less well.) It further remained unclear to me, which implications may be drawn from the generative model, following from the capacities to mimic this specific TGM (i) for more complex cases, such as the comparison between experimental conditions, and (ii) about the complex nature of neural processes involved.

      Towards this end I would appreciate (i) a more profound explanation of the conclusions that can be drawn from this specific showcase, including potential limitations, as well as wider considerations of how scientists may empower the generative model to (ii) understand their experimental data better and (iii) which added value the model may have in understanding the nature of underlaying brain mechanism (rather than a mere technical characterization of sensor data).

    1. Reviewer #1 (Public Review):

      Force sensing and gating mechanisms of the mechanically activated ion channels is an area of broad interest in the field of mechanotransduction. These channels perform important biological functions by converting mechanical force into electrical signals. To understand their underlying physiological processes, it is important to determine gating mechanisms, especially those mediated by lipids. The authors in this manuscript describe a mechanism for mechanically induced activation of TREK-1 (TWIK-related K+ channel. They propose that force induced disruption of ganglioside (GM1) and cholesterol causes relocation of TREK-1 associated with phospholipase D2 (PLD2) to 4,5-bisphosphate (PIP2) clusters, where PLD2 catalytic activity produces phosphatidic acid that can activate the channel. To test their hypothesis, they use dSTORM to measure TREK-1 and PLD2 colocalization with either GM1 or PIP2. They find that shear stress decreases TREK-1/PLD2 colocalization with GM1 and relocates to cluster with PIP2. These movements are affected by TREK-1 C-terminal or PLD2 mutations suggesting that the interaction is important for channel re-location. The authors then draw a correlation to cholesterol suggesting that TREK-1 movement is cholesterol dependent. It is important to note that this is not the only method of channel activation and that one not involving PLD2 also exists. Overall, the authors conclude that force is sensed by ordered lipids and PLD2 associates with TREK-1 to selectively gate the channel.

      The proposed mechanism is solid and the authors have revised the manuscript to address previous issues with the first version

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors posed a research question about how an animal integrates sensory information to optimize its behavioral outputs and how this process evolved. Their data (behavioral output analysis with detailed categories in response to the different odors in different concentrations by comparing surface and cave populations and their hybrid) partially answer this tough question. They built a new low-disturbance system to answer the question. They also found that the personality of individual fish is a good predictor of behavioral outputs against odor response. They concluded that cavefish evolved to specialize their response to alanine and histidine while surface fish are more general responders, which was supported by their data.

      Strengths:<br /> With their new system, the authors could generate clearer results without mechanical disturbances. The authors characterize multiple measurements to score the odor response behaviors, and also brought a new personality analysis. Their conclusion that cavefish evolved as a specialist to sense alanine and histidine among 6 tested amino acids was well supported by their data.

      Weaknesses:<br /> The authors posed a big research question: How do animals evolve the processes of sensory integration to optimize their behavioral outputs? I personally feel that, to answer the questions about how sensory integration generates proper (evolved) behavior, the authors at least need to show the ecological relevance of their response. For the alanine/histidine preference in cavefish, they need data for the alanine and other amino acid concentrations in the local cave water and compare them with those of surface water.

      Also, as for "personality matters", I read that personality explains a large variation in surface fish. Also, thigmotaxis or wall-following cavefish individuals are exceeded to respond well to odorants compared with circling and random swimming cavefish individuals. However, I failed to understand the authors' point about how much percentages of the odorant-response variations are explained (PVE) by personality. Association (= correlation) was good to show as the authors presented, but showing proper PVE or the effect size of personality to predict the behavioral outputs is important to conclude "personality is matter"; otherwise, the conclusion is not so supported.

      From the above, I recommend the authors reconsider the title also their research questions well. At this moment, I feel that the authors' conclusions and their research questions are a little too exaggerated, with less supportive evidence.

      Also, for the statistical method, Fisher's exact test is not appropriate for the compositional data (such as Figure 2B). The authors may quickly check it at https://en.wikipedia.org/wiki/Compositional_data or https://www.annualreviews.org/doi/pdf/10.1146/annurev-statistics-042720-124436.

      The authors may want to use centered log transformation or other appropriate transformations (R-package could be: https://doi.org/10.1016/j.cageo.2006.11.017). According to changing the statistical tests, the authors' conclusion may not be supported.

    1. Reviewer #1 (Public Review):

      Establishing direct links between the neuronal connectivity information of connectomics datasets with circuit physiology and behavior and exciting current research area in neurobiology. Until recently, studies of aggression in Drosophila had been conducted largely in males, and many of the neurons involved in this behavior are male-specific clusters. Since the currently available fly brain connectomes come from female brains, their applicability for the study of the circuitry underlying aggressive behavior is very limited.

      The authors have previously used the Janelia hemibrain connectome paired with behavior analysis to show that activating either the aIPg or pC1d cell types can induce short term aggression in females, while activation of other PC1 clusters (a-c and e) does not. Here they expand on those findings, showing that optogenetic stimulation of aIPg neurons was sufficient to promote an aggressive internal state lasting at least 10 minutes following a 30 second activation. In addition, authors show that while stimulation of PC1d alone is not sufficient to induce this persistent aggressive state, simultaneous activation of PC1d + PC1e is, suggesting a synergistic effect. Connectomics analysis performed in the authors' previous study had shown that PC1d and aIPg are interconnected. However, silencing pC1d neuronal activity did not reduce aIPg-evoked persistent aggression, indicating that the aggressive state did not depend on pC1d-aIPg recurrent connectivity.

      The conclusions are well supported by the data, and the results presented in this manuscript represent an important contribution to our understanding of the neuronal circuitry underlying female aggression.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In the paper by Choi et al., the authors aimed to develop base editing strategies to convert CAG repeats to CAA repeats in the huntingtin gene (HTT), which causes Huntington's disease (HD). They hypothesized that this conversion would delay disease onset by shortening the uninterrupted CAG repeat. Using HEK-293T cells as a model, the researchers employed cytosine base editors and guide RNAs (gRNAs) to efficiently convert CAG to CAA at various sites within the CAG repeat. No significant indels, off-target edits, transcriptome alterations, or changes in HTT protein levels were detected. Interestingly, somatic CAG repeat expansion was completely abolished in HD knock-in mice carrying CAA-interrupted repeats.

      Strengths:<br /> This study represents the first proof-of-concept exploration of the cytosine base editing technique as a potential treatment for HD and other repeat expansion disorders with similar mechanisms.

      Weaknesses:<br /> Given that HD is a neurodegenerative disorder, it is crucial to determine the efficiency of the base editing strategies tested in this manuscript and their feasibility in relevant cells affected by HD and the brain, which needed to be improved in this manuscript.

    1. Reviewer #1 (Public Review):

      The authors took advantage of a large dataset of transcriptomic information obtained from parasites recovered from 35 patients. In addition, parasites from 13 of these patients were reared for 1 generation in vivo, 10 for 2 generations, and 1 for a third generation. This provided the authors with a remarkable resource for monitoring how parasites initially adapt to the environmental change of being grown in culture. They focused initially on var gene expression due to the importance of this gene family for parasite virulence, then subsequently assessed changes in the entire transcriptome. Their goal was to develop a more accurate and informative computational pipeline for assessing var gene expression and secondly, to document the adaptation process at the whole transcriptome level.

      Overall, the authors were largely successful in their aims. They provide convincing evidence that their new computational pipeline is better able to assemble var transcripts and assess the structure of the encoded PfEMP1s. They can also assess var gene switching as a tool for examining antigenic variation. They also documented potentially important changes in the overall transcriptome that will be important for researchers who employ ex vivo samples for assessing things like drug sensitivity profiles or metabolic states. These are likely to be important tools and insights for researchers working on field samples.

      Interestingly, the conclusions about changes in var gene expression due to the transition to in vitro culture (one of the primary goals of the paper) were somewhat difficult to assess. The authors found that in most instances, var gene expression patterns changed only modestly. However, in a few cases, more substantial changes were observed. Thus, it is difficult to make firm conclusions about how one should interpret var gene expression profiles in parasites recently placed in culture. Changes in the core transcriptome however were more pronounced, justifying the authors recommendation for caution when interpreting the results of such experiments.

    1. Reviewer #1 (Public Review):

      The contribution of Klughammer et al reports on the fabrication and functionalization of zero-mode waveguides of different diameters as a mimic system for nuclear pore complexes. Moreover, the researchers performed molecular transport measurements on these mimic systems (together with molecular dynamic simulations) to assess the contribution of pore diameter and Nsp functionalization on the translocation rates of BSA, the nuclear transport protein Kap95 and finally the impact of different Kap95 concentrations on BSA translocation and overall selectivity of the mimicked pores as function of their diameter. In order to assess the effect of the Nsp1 on the coated pores to the translocation rates and molecular selectivity they also conducted separated experiments on bare nano-pores, i.e., without coating, and of different diameters. One of the most novel aspects of this contribution is the detection scheme used to assess the translocation rates & selectivity, i.e., the use of an optical scheme based on single molecule fluorescence detection as compared to previous works that have mostly relied on conductance measurements. The results are convincing, the experiments carefully performed and the procedures explained in detail.

      Importantly, this study provides new insights on the mechanisms of nuclear transport contributing to further our understanding on how real nuclear-pore complexes (i.e., in living cell) can regulate molecular transport. The recent findings that the nuclear pore complexes are sensitive to mechanical stimulation by modulating their effective diameters, adds an additional level of interest to the work reported here, since the authors thoroughly explored different nano-pore diameters and quantified their impact on translocation and selectivity. There are multiple avenues for future research based the system developed here, including higher throughput detection, extending to truly multicolor schemes or expanding the range of FG-Nups, nuclear transport proteins or cargos that need to be efficiently transported to the nucleus through the nuclear pore complexes. As a whole, this is an important contribution to the field.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Shibl et al., studied the possible role of dicarboxylate metabolite azelaic acid (Aze) in modulating the response of different bacteria, it was used as a carbon source by Phycobacter and possibly toxic for Alteromonas. The experiments were well conducted using transcriptomics, transcriptional factor coexpression networks, uptake experiments, and chemical methods to unravel the uptake, catabolism, and toxicity of Aze on these two bacteria. They identified a putative Aze TRAP transporter in bacteria and showed that Aze is assimilated through fatty acid degradation in Phycobacter. Meanwhile, in Alteromonas it is suggested that Aze inhibits the ribosome and/or protein synthesis, and that efflux pumps shuttles Aze outside the cytoplasm. Further on, they demonstrate that seawater amended with Aze selects for microbes that can catabolize Aze.

      Major strengths:<br /> The manuscript is well written and very clear. Through the combination of gene expression, transcriptional factor co-expression networks, uptake experiments, and chemical methods Shibl et al., showed that Aze has a different response in two bacteria.

      Major weakness:<br /> There is no phenotype confirmation of the Aze TRAP transporters through mutagenesis.

      Impact on the field:<br /> Metabolites exert a significant influence on microbial communities in the ocean, playing a crucial role in their composition, dynamics, and biogeochemical cycles. This research highlights the intriguing capacity of a single metabolite to induce contrasting responses in distinct bacterial species, underscoring its role in shaping microbial interactions and ecosystem functions.

    1. Reviewer #1 (Public Review):

      Peng et al develop a computational method to predict/rank transcription factors (TFs) according to their likelihood of being pioneer transcription factors--factors that are capable of binding nucleosomes--using ChIP-seq for 225 human transcription factors, MNase-seq and DNase-seq data from five cell lines. The authors developed relatively straightforward, easy to interpret computational methods that leverage the potential for MNase-seq to enable relatively precise identification of the nucleosome dyad. Using an established smoothing approach and local peak identification methods to estimate positions together with identification of ChIP-seq peaks and motifs within those peaks which they referred to as "ChIP-seq motifs", they were able to quantify "motif profiles" and their density in nucleosome regions (NRs) and nucleosome depleted regions (NDRs) relative to their estimated nucleosome dyad positions. Using these profiles, they arrived at an odd-ratio based motif enrichment score along with a Fisher's exact test to assess the odds and significance that a given transcription factor's ChIP-seq motifs are enriched in NRs compared to NDRs, hence, its potential to be a pioneer transcription factor. They showed that known pioneer transcription factors had among the highest enrichment scores, and they could identify a number of relatively novel pioneer TFs with high enrichment scores and relatively high expression in their corresponding cell line. They used multiple validation approaches including (1) calculating the ROC-AUC and Matthews correlation coefficient (MCC) and generating ROC and precision-recall curves associated with their enrichment score based on 32 known pioneer TFs among their 225 TFs which they used as positives and the remaining TFs (among the 225) as negatives; (2) use of the literature to note that known pioneer TFs that acted as key regulators of embryonic stem cell differentiation had a highest enrichment scores; (3) comparison of their enrichment scores to three classes of TFs defined by protein microarray and electromobility shift assays (1. strong binder to free and nucleosomal DNA, 2. weak binder to free and nucleosomal DNA, 3. strong binding to free but not nucleosomal DNA); and (4) correlation between their calculated TF motif nucleosome end/dyad binding ratio and relevant data from an NCAP-SELEX experiment. They also characterize the spatial distribution of TF motif binding relative to the dyad by (1) correlating TF motif density and nucleosome occupancy and (2) clustering TF motif binding profiles relative to their distance from the dyad and identifying 6 clusters.

      The strengths of this paper are the use of MNase-seq data to define relatively precise dyad positions and ChIP-seq data together with motif analysis to arrive at relatively accurate TF binding profiles relative to dyad positions in NRs as well as in NDRs. This allowed them to use a relatively simple odds ratio based enrichment score which performs well in identifying known pioneer TFs. Moreover, their validation approaches either produced highly significant or reasonable, trending results.

      The weaknesses of the paper are relatively minor, and the authors do a good job of describing the limitations of the data and approach.

    1. Reviewer #1 (Public Review):

      Summary:

      This revised study follows up on previous work showing a female-specific enhancer region of PAX1 is associated with adolescent idiopathic scoliosis (AIS). This new analysis combines human GWAS analysis from multiple countries to identify a new AIS-associated coding variant in the COL11A1 gene (COL11A1P1335L). Using a Pax1 knockout mouse they go on to find that PAX1 and Collagen XI protein are expressed in the intervertebral discs (IVDs) and robustly in the growth plate, showing that COL11A1 expression is reduced in Pax1 mutant growth plate. Moreover, other AIS-associated genes, Gpr126 and Sox6, were also reduced in Pax1 mutant mice, suggesting a common pathway is involved in AIS.

      Using SV40 immortalized costal cartilage cells, derived from floxed Col11a1 mice primary rib cage cartilage, they go to show that removal of Col11a1 leads to reduction of Mmp3 expression. In this context, the expression of wild-type Col11a1 restored regular levels of Mmp3 expression, while expression of the AIS-associated Col11a1P1335L allele failed to restore normal Mmp3 expression. This supports a model that the AIS-associated Col11a1P1335L allele leads to the dysregulation of ECM in vivo.

      Using this culture system, they go on to test the role of the estrogen receptor ESR2, showing that loss of this receptor leads to reduced Mmp3 and Pax1 expression, and increased Col11a1 expression. They support this by showing similar gene expression changes and estrogen receptor function in Rat cartilage endplate cell culture.

      Altogether, this study nicely brings together an impressive number of human genetic data from multi-ethnic AIS cohorts and controls from across the globe and functionally tests these findings in cell culture and animal models. This study wonderfully integrates other findings from other human and mouse work in AIS and supports a new molecular mechanism by which estrogen can interact and synergize with COL11A1/PAX1/MMP3 signaling to change ECM development and dynamics, thus providing a tangible model for mutations and dysregulation of this pathway can increase the susceptibility of scoliosis.

      Strengths:

      This work integrates a large cohort of human genetic data from AIS patient and control from diverse ethnic backgrounds, across the globe. This work attempts to functionally test their findings in vivio and by use of cell culture.

      Weaknesses:

      Many of the main functional work was done in cell culture and not in vivo.

    1. Reviewer #1 (Public Review):

      Over the last decade, numerous studies have identified adaptation signals in modern humans driven by genomic variants introgressed from archaic hominins such as Neanderthals and Denisovans. One of the most classic signals comes from a beneficial haplotype in the EPAS1 gene in Tibetans that is evidently of Denisovan origin and facilitated high altitude adaptation (HAA). Given that HAA is a complex trait with numerous underlying genetic contributions, in this paper Ferraretti et al. asked whether additional HAA-related genes may also exhibit a signature of adaptive introgression. Specifically, the authors considered that if such a signature exists, they most likely are only mild signals from polygenic selection, or soft sweeps on standing archaic variation, in contrast to a strong and nearly complete selection signal like in the EPAS1. Therefore, they leveraged two methods, including a composite likelihood method for detecting adaptive introgression and a biological network-based method for detecting polygenic selection, and identified two additional genes that harbor plausible signatures of adaptive introgression for HAA.

      Strengths:<br /> The study is well motivated by an important question, which is, whether archaic introgression can drive polygenic adaptation via multiple small effect contributions in genes underlying different biological pathways regulating a complex trait (such as HAA). This is a valid question and the influence of archaic introgression on polygenic adaptation has not been thoroughly explored by previous studies

      The authors reexamined previously published high-altitude Tibetan whole genome data and applied a couple of the recently developed methods for detecting adaptive introgression and polygenic selection.

      Weaknesses:<br /> My main concern with this paper is that I am not too convinced that the reported genomic regions putatively under polygenic selection are indeed of archaic origin. Other than some straightforward population structure characterizations, the authors mainly did two analyses with regard to the identification of adaptive introgression: First, they used one composite likelihood-based method, the VolcanoFinder, to detect the plausible archaic adaptive introgression and found two candidate genes (EP300 and NOS2). Next, they attempted to validate the identified signal using another method that detects polygenic selection based on biological network enrichments for archaic variants.

      In general, I don't see in the manuscript that the choice of methods here are well justified. VolcanoFinder is one among the several commonly used methods for detecting adaptive introgression (eg. the D, RD, U, and Q statistics, genomatnn, maldapt etc.). Even if the selection was mild and incomplete, some of these other methods should be able to recapitulate and validate the results, which are currently missing in this paper. Besides, some of the recent papers that studied the distribution of archaic ancestry in Tibetans don't seem to report archaic segments in the two gene regions. These all together made me not sure about the presence of archaic introgression, in contrast to just selection on ancestral variation.

      Furthermore, the authors tried to validate the results by using signet, a method that detects enrichments of alleles under selection in a set of biological networks related to the trait. However, the authors did not provide sufficient description on how they defined archaic alleles when scoring the genes in the network. In fact, reading from the method description, they seemed to only have considered alleles shared between Tibetans and Denisovans, but not necessarily exclusively shared between them. If the alleles used for scoring the networks in Signet are also found in other populations such as Han Chinese or Africans, then that would make a substantial difference in the result, leading to potential false positives.

      Overall, given the evidence provided by this article, I am not sure they are adequate to suggest archaic adaptive introgression. I recommend additional analyses for the authors to consider for rigorously testing their hypothesis. Please see the details in my review to the authors.

    1. Reviewer #1 (Public Review):

      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 results 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 pathways 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 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 provide evidence to consider how Dbp5 contributes to 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.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors present a detailed study of a nearly complete Entomophthora muscae genome assembly and annotation, along with comparative analyses among related and non-related entomopathogenic fungi. The genome is one of the largest fungal genomes sequenced, and the authors document the proliferation and evolution of transposons and the presence/absence of related genetic machinery to explore how this may have occurred. There has also been an expansion in gene number, which appears to contain many "novel" genes unique to E. muscae. Functionally, the authors were interested in CAZymes, proteases, circadian clock related genes (due to entomopathogenicity/ host manipulation), other insect pathogen-specific genes, and secondary metabolites. There are many interesting findings including expansions in trahalases, unique insulinase, and another peptidase, and some evidence for RIP in Entomophthoralean fungi. The authors performed a separate study examining E. muscae species complex and related strains. Specifically, morphological traits were measured for strains and then compared to the 28S+ITS-based phylogeny, showing little informativeness of these morpho characters with high levels of overlap.

      This work represents a big leap forward in the genomics of non-Dikarya fungi and large fungal genomes. Most of the gene homologs have been studied in species that diverged hundreds of millions of years ago, and therefore using standard comparative genomic approaches is not trivial and still relatively little is known. This paper provides many new hypotheses and potential avenues of research about fungal genome size expansion, entomopathogenesis in zygomycetes, and cellular functions like RIP and circadian mechanisms.

      Strengths:<br /> There are many strengths to this study. It represents a massive amount of work and a very thorough functional analysis of the gene content in these fungi (which are largely unsequenced and definitely understudied). Too often comparative genomic work will focus on one aspect and leave the reader wondering about all the other ways genome(s) are unique or different from others. This study really dove in and explored the relevant aspects of the E. muscae genome.

      The authors used both a priori and emergent properties to shape their analyses (by searching for specific genes of interest and by analyzing genes underrepresented, expanded, or unique to their chosen taxa), enabling a detailed review of the genomic architecture and content. Specifically, I'm impressed by the analysis of missing genes (pFAMs) in E. muscae, none of which are enriched in relatives, suggesting this fungus is really different not by gene loss, but by its gene expansions.

      Analyzing species-level boundaries and the data underlying those (genetic or morphological) is not something frequently presented in comparative genomic studies, however, here it is a welcome addition as the target species of the study is part of a species complex where morphology can be misleading and genetic data is infrequently collected in conjunction with the morphological data.

      Weaknesses:<br /> The conclusions of this paper are mostly well supported by data, but a few points should be clarified.

      In the analysis of Orthogroups (OGs), the claim in the text is that E. muscae "has genes in multi-species OGs no more frequently than Enotomophaga maimaiga. (Fig. 3F)" I don't see that in 3F. But maybe I'm really missing something.

      Also related, based on what is written in the text of the OG section, I think portions of Figure 3G are incorrect/ duplicated. First, a general question, related to the first two portions of the graph. How do "Genes assigned to an OG" and "Genes not assigned to an OG" not equal 100% for each species? The graph as currently visualized does not show that. Then I think the bars in portion 3 "Genes in species-specific OG" are wrong (because in the text it says "N. thromboides had just 16.3%" species-specific OGs, but the graph clearly shows that bar at around 50%. I think portion 3 is just a duplicate of the bars in portion 4 - they look exactly the same - and in addition, as stated in the text portion 4 "Potentially species-specific genes" should be the simple addition of the bars in portion 2 and portion 3 for each species.

      In the introduction, there is a name for the phenomenon of "clinging to or biting the tops of plants," it's called summit disease. And just for some context for the readers, summit disease is well-documented in many of these taxa in the older literature, but it is often ignored in modern studies - even though it is a fascinating effect seen in many insect hosts, caused by many, many fungi, nematodes (!), etc. This phenomenon has evolved many times. Nice discussions of this in Evans 1989 and Roy et al. 2006 (both of whom cite much of the older literature).

    1. Reviewer #1 (Public Review):

      The authors set out to illuminate how legumes promote symbiosis with beneficial nitrogen-fixing bacteria while maintaining a general defensive posture towards the plethora of potentially pathogenic bacteria in their environment. Intriguingly, a protein involved in plant defence signalling, RIN4, is implicated as a type of 'gatekeeper' for symbiosis, connecting symbiosis signalling with defence signalling. Although questions remain about how exactly RIN4 enables symbiosis, the work opens an important door to new discoveries in this area.

      Strengths:<br /> The study uses a multidisciplinary, state-of-the-art approach to implicate RIN4 in soybean nodulation and symbiosis development. The results support the authors' conclusions.

      Weaknesses:<br /> No serious weaknesses, although the manuscript could be improved slightly from technical and communication standpoints.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors demonstrated that carbon depletion triggers the autophagy-dependent formation of Rubisco Containing Bodies, which contain chloroplast stroma material, but exclude thylakoids. The authors show that RCBs bud directly from the main body of chloroplasts rather than from stromules and that their formation is not dependent on the chloroplast fission factor DRP5. The authors also observed a transient engulfment of the RBCs by the tonoplast during delivery to the vacuolar lumen.

      Strengths:<br /> The authors demonstrate that autophagy-related protein 8 (ATG8) co-localizes to the chloroplast demarking the place for RCB budding. The authors provide good-quality time-lapse images and co-localization of the markers corroborating previous observations that RCBs contain only stroma material and do not include thylakoid. The text is very well written and easy to follow.

      Weaknesses:<br /> A significant portion of the results presented in the study comes across as a corroboration of the previous findings made under different stress conditions: autophagy-dependent formation of RCBs was reported by Ishida et all in 2009. Furthermore, some included results are not of particular relevance to the study's aim. For example, it is unclear what is the importance of the role of SA in the formation of stromules, which do not serve as an origin for the RCBs. Similarly, the significance of the transient engulfment of RCBs by the tonoplast remained elusive. Although it is indeed a curious observation, previously reported for peroxisomes, its presentation should include an adequate discussion maybe suggesting the involved mechanism. Finally, some conclusions are not fully supported by the data: the suggested timing of events poorly aligns between and even within experiments mostly due to high variation and low number of replicates. Most importantly, the discussion does not place the findings of this study into the context of current knowledge on chlorophagy and does not propose the significance of the piece-meal vs complete organelle sequestration into the vacuole under used conditions, and does not dwell on the early localization of ATG8 to the future budding place on the chloroplast.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors recently reported a scRNA-seq-based study focused on synovial fibroblasts using a mouse model of post-traumatic OA (Ref. 21). In the present manuscript, they reanalyzed the scRNA-seq data to investigate the diversity and roles of macrophages. In addition to their original scRNA-seq data (Ref. 21), they utilized the deposited data of other OA or RA models (Ref. 25-27) and compared cell types in the synovium. The authors extracted the macrophage/monocyte group, compared differentially expressed genes (DEGs) between OA and RA synovium, and analyzed macrophage subsets, including trajectory analysis. They further estimated the crosstalk between stromal and immune cells via M-CSF signaling, and transcription factors for monocyte differentiation.

      Strengths:<br /> The descriptions are comprehensive, based on the scRNA-seq data including the original and other independent studies.

      Weaknesses:<br /> Meanwhile, methods of sample preparation must be different, for example, the extent and location of excised synovium. The comparison with other studies is meaningful and informative; however, caution should be exercised regarding the potentially significant impact of methodological differences on the analysis results.

      The various data obtained from these technologies are comprehensive and useful; however, they are just estimates. Without confirmation by experiments, it is impossible to determine how much of it can be believed. This issue is not limited to this paper.

      Most of all signaling pathways and molecules described in the latter part of this study are previously known.

    1. Reviewer #1 (Public Review):

      Summary: The goal of this study was to develop and validate novel molecules to selectively activate a cell signaling pathway, the Wnt pathway in this case, in target cells expressing a specific receptor. This was achieved through a two-component system that the authors call BRAID, where each component simultaneously binds the target cell-specific marker BKlotho and a Wnt co-receptor. These components, called SWIFT molecules, bring together the Wnt co-receptors LRP and FZD, activating the pathway specifically in cells that express BKlotho.

      Results presented in the study demonstrate the desired activity of SWIFT molecules; the binding assays support simultaneous association of SWIFT with BKlotho and a Wnt co-receptor, and the Wnt reporter and qPCR assays support pathway activation in cell lines and primary cells in a BKlotho-dependent manner. In the future, the BRAID approach could be applied to activate Wnt signaling or another pathway initiated by a co-receptor complex in a cell type-specific manner, and/or in a FZD subtype-specific manner to activate distinct branches of Wnt signaling.

      Strengths:

      • This study successfully demonstrates a novel way to activate Wnt signaling in target cells expressing a specific marker. Given the role of the Wnt signaling pathway in key processes such as cell proliferation and tissue renewal and the value of modulating cell signaling in a cell type-specific manner, the cell targeting system developed here holds great therapeutic and research potential. It will be curious to see whether the BRAID design can be applied to other cell surface markers for Wnt activation, or for activation of other signaling pathways that require co-receptor association.

      • Octet assay results show simultaneous binding of SWIFT molecules to both the Wnt co-receptor FZD/LRP and BKlotho, while negative control molecules without the FZD/LRP or BKlotho-binding module show neither receptor binding nor Wnt pathway activation. These results indicate that SWIFT molecules function through the intended mechanism.

      • Exposure of two cell types simultaneously exposed to the SWIFT molecules in 2-layer cell culture demonstrated the ability of the molecules to activate Wnt signaling in a cell type- and BKlotho expression-specific manner.

      Weaknesses:

      • The study does not address whether the targeted cells express FGFR1c/2c/3c and whether the FGF21 full length moiety or the 39F7 IgG moiety of SWIFT molecules could unintentionally activate FGF signaling in these cells.

    1. Reviewer #1 (Public Review):

      Summary:<br /> "Expanding the Drosophila toolkit for dual control of gene expression" by Zirin et al. aims to develop resources for simultaneous independent manipulation of multiple genes in Drosophila. The authors use CRISPR knock-ins to establish a collection of T2A-LexA and T2A-QF2 transgenes with expression patterns in a number of commonly studied organs and tissues. In addition to the transgenic lines that are established, the authors describe a number of plasmids that can be used to generate additional transgenes, including a plasmid to generate a dual insert of LexA and QF that can be resolved into a single insert using FLP/FRT-mediated recombination, and plasmids to generate RNAi reagents for the LexA and QF systems. Finally, the authors demonstrate that a subset of the LexA and QF lines that they generated can induce RNAi phenotypes when paired with LexAop or QUAS shRNA lines. In general, the claims of the paper are well supported by the evidence and the authors do a thorough job of validating the transgenic lines and characterizing their expression patterns.

      Strengths:<br /> -Numerous Gal4 lines allow for highly specific genetic manipulation in a wide range of organs and tissues, however, similar tissue-specific drivers using alternative binary expression systems are not currently well developed. This study provides a large number of tissue and organ-specific LexA and QF2 driver lines that should be broadly useful for the Drosophila community.<br /> -While a minority of the driver lines do not express the expected pattern (likely due to cryptic regulatory elements in the LexA or QF2 sequences), the ability to generate drivers using two different Gal4 alternatives mitigates this issue (as in nearly all cases at least one of the two systems produces a clean driver line with the expected expression pattern).<br /> -The use of LexA-GAD provides an additional degree of control as it is subject to Gal80 repression. This could prove to be particularly useful in cases where a researcher wishes to manipulate multiple genes using Gal4 and LexA-GAD drivers as the Gal80(ts) system could be used for simultaneous temporal control of both constructs.<br /> -The use of Fly Cell Atlas information to generate novel oenocyte-specific driver lines provides a useful proof-of-concept for constructing additional highly tissue-specific drivers.

      Weaknesses:<br /> -Since these reagents will most commonly be paired with existing Gal4 lines, adding information about corresponding Gal4 lines targeting these tissues and how faithfully the LexA and QF2 lines recapitulate these Gal4 patterns would be highly beneficial.<br /> -It is not stated in the manuscript if these transgenic lines and plasmids are currently publicly available. Information about how to obtain these reagents through Bloomington, Addgene, or TRiP should be added to the manuscript.

    1. Reviewer #1 (Public Review):

      The findings in this paper can be split into three parts.

      1) Processing of ITS2

      Firstly, the authors identify two sites on ITS2 which are cleaved by the ScLas1-Grc3 complex, as part of 25S ribosomal RNA maturation.

      For a smaller segment of ITS2 (33nt), the two sites separate out 3 parts with sizes of 10nt, 14nt, and 9nt (Figure 1C). However, bands in mass spec. occur at 23nt (14nt+9nt) and 14nt, but not 9nt alone. Additional bands can be seen at 22nt and 21nt. Hence the evidence for these two specific sites seems somewhat uncertain. It is not clear if there is an experimental limitation in terms of accuracy, or that the cleavage is perhaps somewhat approximate at the two sites. The authors may try to clarify these results a bit further.

      For a larger ITS2 (81nt), similar support is found for the two cleavage sites, but now the possible fragments are 14nt, 30nt, 37nt, and 44nt (14nt+30nt) (Figure 1E). The observed bands match these fragments at 44nt, 37nt, 30nt, but again there are additional bands at 36nt, 28nt, and 13nt, which are not fully explained. It may be useful for explain or discuss these discrepancies.

      Another useful result of these experiments is to confirm that Las1 alone has only weak activity against ITS2, but very strong activity when it is part of the Las1-Grc3 complex.

      2) Structure of Las1, and Las1-Grc3 complexes

      A second important contribution of this work are X-ray and cryoEM structures of Las1-Grc3 from Sc and Cj. It is interesting that even though the complexes are very similar, CjGrc3 shows weak activation of CjLas1, whereas ScGrc3 more strongly activates ScLas1. The X-ray and cryoEM structures are very similar. However, the X-ray structures also show an additional (CC) domain from Las1 not resolved in the cryoEM map. This difference is significant, because it suggests the CC domain may remain more flexible in solution, but stabilizes in the crystal. Also interestingly, the CC domains have different structures and are in different positions in ScLas1-Grc3 vs CjLas1-Grc3, again hinting that they are more dynamic. Further experiments described by the authors confirm the CC domain is indeed important in RNA binding and activity. Whether they are only implicated in binding RNA or both binding and cleavage is somewhat unclear.

      The structure of Las1-Grc3 is described as resembling a butterfly, with Las1 being the body and Grc3 the wings. While this is a useful description, it may be a bit misleading. The complex has C2 symmetry, with one Las1-Grc3 unit related to the other by about ~180 rotation around a vertical axis parallel to the body of the butterfly as proposed. To use the butterfly analogy, one half of the body and one wing faces the opposite way as the other, not a mirror symmetry as a real butterfly would have.

      Both Cj and Sc structures show the C-terminal of Grc3 binding to the active pocket of Las1, explaining its effect on activity. Mutation experiments also further show the importance of these residues on activity. Reciprocally, a region in Las1, LCT, inserts into Grc3, forming a stable complex. Again mutating these residues affects activity, strengthening their importance and the evidence for how the stable complex forms.

      Finally, an X-ray structure of dimeric Las1 in Cj, without Grc3 is presented. Truncating CC and LCT appeared to be necessary to allow the dimer to crystallize. Superposition with Las1 dimer in Las1-Grc3 shows a conformational difference, and different distances between residues in the active pocket, explaining the change in activity with and without Grc3. Interestingly, the Las1 domains themselves do not change too much, i.e. both domains can be matched with less than 1Å Ca-RMSD, so the difference may be more of a repositioning of the two domains for the active conformation.

      One notable strength of this study is the use of both X-ray and cryoEM to obtain structures of the Las1-Grc3 and dimeric Las1 complexes. Typically structures of cryoEM at ~3Å are sufficient for reliable modeling; for example, the backbone and side chains of residues in the active site are well resolved. However, in this case, a cryoEM model of the Las1 dimer was not obtained, so it was important to show first that the Las1-Las1 conformation in the Las1-Grc3 complex is the same in both X-ray and cryoEM models. Otherwise, there may remain doubt whether the X-ray model of Las1 dimer could be compared to the cryoEM map of Las1-Grc3, as crystallization conditions could potentially influence conformation and arrangement. It would be interesting to know whether a cryoEM structure of the Las1 dimer alone was attempted - perhaps it was too small to be reliably seen in micrographs. Having had such a model could avoid the need of X-ray structures, although of course more experimental data are always useful.

      3) Mechanism of ITS2 cleavage

      The proposed mechanism shown in Figure 8 seems to be well supported by the obtained structures and biochemical experiments. A question that remains is why it is proposed that both C2 and C2' cleavage can be performed upon a single binding of the ITS2 RNA, i.e. seeming to suggest there are two binding sites. This would seem to directly generate 3 fragments, without any other intermediate products. Mass spec. seemed to show the intermediate products, perhaps indicating two binding events for each cleavage process. Perhaps the authors could discuss this more. Also perhaps can be good to discuss whether it would be possible to obtain a structure with the bound RNA, further giving structural information of how the exact cleavage process is performed.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Ellis et al. investigated the functional and topographical organization of the visual cortex in infants and toddlers, as evidenced by movie-viewing data. They build directly on prior research that revealed topographic maps in infants who completed a retinotopy task, claiming that even a limited amount of rich, naturalistic movie-viewing data is sufficient to reveal this organization, within and across participants. Generating this evidence required methodological innovations to acquire high-quality fMRI data from awake infants (which have been described by this group, and elsewhere) and analytical creativity. The authors provide evidence for structured functional responses in infant visual cortex at multiple levels of analyses; homotopic brain regions (defined based on a retinotopy task) responded more similarly to one another than to other brain regions in visual cortex during movie-viewing; ICA applied to movie-viewing data revealed components that were identifiable as spatial frequency, and to a lesser degree, meridian maps, and shared response modeling analyses suggested that visual cortex responses were similar across infants/toddlers, as well as across infants/toddlers and adults. These results are suggestive of fairly mature functional response profiles in the visual cortex in infants/toddlers and highlight the potential of movie-viewing data for studying finer-grained aspects of functional brain responses, but further evidence is necessary to support their claims and the study motivation needs refining, in light of prior research.

      Strengths:<br /> - This study links the authors' prior evidence for retinotopic organization of visual cortex in human infants (Ellis et al., 2021) and research by others using movie-viewing fMRI experiments with adults to reveal retinotopic organization (Knapen, 2021).

      - Awake infant fMRI data are rare, time-consuming, and expensive to collect; they are therefore of high value to the community. The raw and preprocessed fMRI and anatomical data analyzed will be made publicly available.

      Weaknesses:<br /> - The Methods are at times difficult to understand and in some cases seem inappropriate for the conclusions drawn. For example, I believe that the movie-defined ICA components were validated using independent data from the retinotopy task, but this was a point of confusion among reviewers. In either case: more analyses should be done to support the conclusion that the components identified from the movie reproduce retinotopic maps (for example, by comparing the performance of movie-viewing maps to available alternatives (anatomical ROIs, group-defined ROIs). Also, the ROIs used for the homotopy analyses were defined based on the retinotopic task rather than based on movie-viewing data alone - leaving it unclear whether movie-viewing data alone can be used to recover functionally distinct regions within the visual cortex.

      - The authors previously reported on retinotopic organization of the visual cortex in human infants (Ellis et al., 2021) and suggest that the feasibility of using movie-viewing experiments to recover these topographic maps is still in question. They point out that movies may not fully sample the stimulus parameters necessary for revealing topographic maps/areas in the visual cortex, or the time-resolution constraints of fMRI might limit the use of movie stimuli, or the rich, uncontrolled nature of movies might make them inferior to stimuli that are designed for retinotopic mapping, or might lead to variable attention between participants that makes measuring the structure of visual responses across individuals challenging. This motivation doesn't sufficiently highlight the importance or value of testing this question in infants. Further, it's unclear if/how this motivation takes into account prior research using movie-viewing fMRI experiments to reveal retinotopic organization in adults (e.g., Knapen, 2021). Given the evidence for retinotopic organization in infants and evidence for the use of movie-viewing experiments in adults, an alternative framing of the novel contribution of this study is that it tests whether retinotopic organization is measurable using a limited amount of movie-viewing data (i.e., a methodological stress test). The study motivation and discussion could be strengthened by more attention to relevant work with adults and/or more explanation of the importance of testing this question in infants (is the reason to test this question in infants purely methodological - i.e., as a way to negate the need for retinotopic tasks in subsequent research, given the time constraints of scanning human infants?).

    1. Reviewer #1 (Public Review):

      Summary:

      The paper of Mao et al. expands the genetic toolset that was previously developed by the Rao lab (Denfg et al 2019) to introduce the conditional KO or downregulation of neurotransmission components in Drosophila. The authors then use these tools to investigate neurotransmission in the clock neurons of the Drosophila brain. They first test some known components and then analyze the contribution of the CNMa neuropeptide and its receptor to the circadian behavior. The results indicate that CNMA acts from a subset of DN1ps (dorsal clock neurons) to set the phase of the morning peak of locomotor activity in light:dark cycles, with an advanced morning activity in the absence of the neuropeptide. Interestingly, the receptor for the PDF neuropeptide appears to be acting in some of the CNMa neurons to control morning activity.

      Strengths/weaknesses:

      This is clearly a very useful new set of tools to restrict the manipulation of these components to specific neuronal populations, and overall (see specific points below), the paper is convincing to show that the tools indeed allow to efficiently and specifically eliminate neuropeptides/receptors from subsets of neurons. The analysis of the CNMa function in the clock network reveals a new and interesting function for CNMa. but this part needs to be improved. Some of the behavioral data (PDF/PDFR) do not fit with published work with the mutants. This should be clarified by providing more data comparing the described genotypes with the classical mutants. Some conclusions also need to be toned down.

    1. Reviewer #1 (Public Review):

      Characterizing gene-by-environment interactions has been of great interest for quite some time, as these effects are believed (based on plausible hypotheses and some data) to have importance for the interpretation of complex disease risk. Here, a major class of variants of interest is genetic regulatory variants where e.g. binding of context-specific regulators (TFs, etc) provides a plausible mechanism. However, these variants have been difficult to identify in eQTL and other studies.

      This study leverages the MPRA approach to screen for many thousands of constructs of putative regulatory variants for their effects on vascular endothelial cells with and without caffeine. They identify thousands of sequences that are differentially regulated between the conditions, and with motif enrichment approaches and comparisons to prior studies, identify some TFs (including novel ones) that may have a role in how these cells respond to caffeine. Next, by allele-specific expression analysis, they identify thousands of variants that are not only regulatory (having a different activity from the two allelic versions of the construct) but also a major subset that has different regulatory activity following the caffeine treatment. Again, motif analysis indicates potential mechanisms, and the eQTL comparison nicely demonstrates the value of these discoveries. The MRPA approach is clearly fruitful and informative, and identifying many context-specific regulatory variants is informative for people working on genetic regulatory variation.

      The part of the paper that felt underwhelming and not so well-founded was the link to complex disease. I was somewhat surprised to see caffeine experiments in vascular endothelial cells being so strongly framed in terms of CAD. This cell type (and potentially also caffeine) is relevant in many biological processes and diseases. More importantly, given the strongly disease-focused framing, I was surprised to find few results that would actually link the regulatory variant data here to CAD via GWAS overlap or other analyses. Maybe the results were slim here with little overlap, but the results provided do not really justify the implications that disease-relevant findings are being made.

      Specifically, the evidence of PIP4K2B let alone the studied cASE variant having a causal role in CAD is weak. This is based on a previously published pTWAS paper, but the variant itself is not a significant GWAS variant. TWAS is known to easily suffer from non-causal hits due to LD and other complications, and hence this link should be taken with a heavy grain of salt. I would be more convinced if the variant was a significant GWAS hit, and even more so if it was a fine-mapped variant, but it is neither of them. As such, the language (Discussion) is not justified by the data: "By studying different environmental contexts, we can identify that, in this instance, caffeine can reduce the risk of poor cardiovascular health outcomes. If the environmental context was not considered and this work was conducted solely in the control condition, the decreased risk induced by caffeine would not have been observed." the decreased [CAD] risk induced by caffeine would not have been observed." Has to be softened. Furthermore, Figure 5 is an illustration but very little data (cASE p-values, etc) is provided here and in the text.

      Furthermore, I find some of the suggested links to CAD via lipid biology and related TFs quite speculative; are these processes really taking place in vascular endothelian cells? The paper that is being referred to seems to focus on the liver.

      Finally, the analyses seem carefully done, but in Figure 2A the systematic inflation of p-values seems concerning. This could be the real biology of broadly distributed response to caffeine, but it's also consistent with a bias that is unaccounted for and inflates p-values across the board. And do we really expect all these elements to respond to caffeine (more or less)? It is difficult to say what exactly this might be, but the caffeine libraries seem to have a higher sequencing coverage (SFig 5). How does this affect the results? Can it bias the DE results via different overdispersion, or the ASE or cASE estimation when the caffeine condition is a higher power (which ASE analysis is typically sensitive to)?

      The library included negative controls of variants that are not believed to be regulatory variants, but I don't see a systematic presentation of the null obtained from these presented in the paper.

    1. Reviewer #1 (Public Review):

      In this manuscript, the authors investigate whether the effects of the BCG vaccine on immunity to Mtb infection could be improved by inhibiting amidation of the peptidoglycan sidechains to allow for recognition by NOD-1. This is a very important area and an interesting new approach to improve vaccination for TB. The authors find that CRISPRi knockdown of murT-gatD causes rather dramatic cell wall defects, more accessible cell wall labeling, and results in attenuated growth in macrophages and mice. There is some data presented to support that the murT-gatD KD strain may be more protective in the animal model, but most comparisons made are not significant and some interpretations stated in the results section do not reflect the data in the figures. It seems that the most important comparisons are between WT BCG+Dox and rBCG+Dox, and the manuscript would be clearer if this comparison was focused on specifically.

    1. Reviewer #1 (Public Review):

      Predator-prey interactions often involve one predator and one prey. Where more than one predator hunts a single prey, a key question is whether the predators involved are cooperating in some manner. Where this has been observed in biology, it has been suggested that complex cognitive processes may be needed to support the cooperation, such as each predator representing the intention of other predators. In this study the authors ask whether cooperation can emerge in a highly idealized scenario with little more than a basic reinforcement learning approach. Due to the size of the resulting state space, computing the value function becomes computationally cumbersome, so a function approximation method using a variant of a deep Q-network (DQN) is used. The authors have successfully shown that cooperation, here operationalized as a higher success rate with two predators in the context of sharing of the reward (prey that's captured), can emerge in this context. Further, they show that a cluster-based analysis of the DQN can guide the generation of a short description length rule-based approach that they also test and show qualitative agreement with the original DQN results.

      Strengths of the work include providing a demonstration proof that cooperation can emerge with simple rules in a predator-prey context, suggesting that its emergence over phylogenetic time within certain clades of animals may not require the complex cognitive processes that prior work has suggested may be needed. Given the simplicity of the rules, one possible outcome could be a widening of investigation into cooperative hunting beyond the usual small number of species in which this has been observed, such as chimpanzees, seals, dolphins, whales, wild dogs, and big cats. The authors have done well to show how, with a variety of adjustments, a DQN network can be used to gain insights into a complex ethological phenomena.

      One weakness of the work is the simplicity of the environment, a 2D plane that is 10 body lengths in each dimension, with full observability and no limitations to movement besides the boundaries of the space. Recent literature suggests that more complex phenomena such as planning may only evolve in the context of partial observability in predator-prey interactions. Thus the absence of more advanced tactics on the part of the predator agents may reflect limitations due to the simplicity of the behavioral arena, or limitations of associative learning alone to drive the emergence of these tactics. Another is that although correlations between network activity are discussed, and used to generate a rule-based approach that succeeds in replicating some of the results, there is no further analysis that may go beyond correlation to a causal analysis.

    1. Joint Public Review:

      LD Score regression (LDSC) is a software tool widely used in the field of genome-wide association studies (GWAS) for estimating heritabilities, genetic correlations, the extent of confounding, and biological enrichment. LDSC is for the most part not regarded as an accurate estimator of \emph{absolute} heritability (although useful for relative comparisons). It is relied on primarily for its other uses (e.g., estimating genetic correlations). The authors propose a new method called \texttt{i-LDSC}, extending the original LDSC in order to estimate a component of genetic variance in addition to the narrow-sense heritability---epistatic genetic variance, although not necessarily all of it. Epistasis in quantitative genetics refers to the component of genetic variance that cannot be captured by a linear model regressing total genetic values on single-SNP genotypes. \texttt{i-LDSC} seems aimed at estimating that part of the epistatic variance residing in statistical interactions between pairs of SNPs. To simplify, the basic model of \texttt{i-LDSC} for two SNPs $X_1$ and $X_2$ is<br /> \begin{equation}\label{eq:twoX}<br /> Y = X_1 \beta_1 + X_2 \beta_2 + X_1 X_2 \theta + E,<br /> \end{equation}<br /> and estimation of the epistatic variance associated with the product term proceeds through a variant of the original LD Score that measures the extent to which a SNP tags products of genotypes (rather than genotypes themselves). The authors conducted simulations to test their method and then applied it to a number of traits in the UK Biobank and Biobank Japan. They found that for all traits the additive genetic variance was larger than the epistatic, but for height the absolute size of the epistatic component was estimated to be non-negligible. An interpretation of the authors' results that perhaps cannot be ruled out, however, is that pairwise epistasis overall does not make a detectable contribution to the variance of quantitative traits.

      Major Comments

      This paper has a lot of strong points, and I commend the authors for the effort and ingenuity expended in tackling the difficult problem of estimating epistatic (non-additive) genetic variance from GWAS summary statistics. The mere possibility of the estimated univariate regression coefficient containing a contribution from epistasis, as represented in the manuscript's Equation~3 and elsewhere, is intriguing in and of itself.

      Is \texttt{i-LDSC} Estimating Epistasis?

      Perhaps the issue that has given me the most pause is uncertainty over whether the paper's method is really estimating the non-additive genetic variance, as this has been traditionally defined in quantitative genetics with great consequences for the correlations between relatives and evolutionary theory (Fisher, 1930, 1941; Lynch & Walsh, 1998; Burger, 2000; Ewens, 2004).

      Let us call the expected phenotypic value of a given multiple-SNP genotype the \emph{total genetic value}. If we apply least-squares regression to obtain the coefficients of the SNPs in a simple linear model predicting the total genetic values, then the partial regression coefficients are the \emph{average effects of gene substitution} and the variance in the predicted values resulting from the model is called the \emph{additive genetic variance}. (This is all theoretical and definitional, not empirical. We do not actually perform this regression.) The variance in the residuals---the differences between the total genetic values and the additive predicted values---is the \emph{non-additive genetic variance}. Notice that this is an orthogonal decomposition of the variance in total genetic values. Thus, in order for the variance in $\mathbf{W}\bm{\theta}$ to qualify as the non-additive genetic variance, it must be orthogonal to $\mathbf{X} \bm{\beta}$.

      At first, I very much doubted whether this is generally true. And I was not reassured by the authors' reply to Reviewer~1 on this point, which did not seem to show any grasp of the issue at all. But to my surprise I discovered in elementary simulations of Equation~\ref{eq:twoX} above that for mean-centered $X_1$ and $X_2$, $(X_1 \beta_1 + X_2 \beta_2)$ is uncorrelated with $X_1 X_2 \theta$ for seemingly arbitrary correlation between $X_1$ and $X_2$. A partition of the outcome's variance between these two components is thus an orthogonal decomposition after all. Furthermore, the result seems general for any number of independent variables and their pairwise products. I am also encouraged by the report that standard and interaction LD Scores are ``lowly correlated' (line~179), meaning that the standard LDSC slope is scarcely affected by the inclusion of interaction LD Scores in the regression; this behavior is what we should expect from an orthogonal decomposition.

      I have therefore come to the view that the additional variance component estimated by \texttt{i-LDSC} has a close correspondence with the epistatic (non-additive) genetic variance after all.

      In order to make this point transparent to all readers, however, I think that the authors should put much more effort into placing their work into the traditional framework of the field. It was certainly not intuitive to multiple reviewers that $\mathbf{X}\bm{\beta}$ is orthogonal to $\mathbf{W}\bm{\theta}$. There are even contrary suggestions. For if $(\mathbf{X}\bm{\beta})^\intercal \mathbf{W} \bm{\theta} = \bm{\beta}^\intercal \mathbf{X}^\intercal \mathbf{W} \bm{\theta} $ is to equal zero, we know that we can't get there by $\mathbf{X}^\intercal \mathbf{W}$ equaling zero because then the method has nothing to go on (e.g., line~139). We thus have a quadratic form---each term being the weighted product of an average (additive) effect and an interaction coefficient---needing to cancel out to equal zero. I wonder if the authors can put forth a rigorous argument or compelling intuition for why this should be the case.

      In the case of two polymorphic sites, quantitative genetics has traditionally partitioned the total genetic variance into the following orthogonal components:<br /> \begin{itemize}<br /> \item additive genetic variance, $\sigma^2_A$, the numerator of the narrow-sense heritability;<br /> \item dominance genetic variance, $\sigma^2_D$;<br /> \item additive-by-additive genetic variance, $\sigma^2_{AA}$;<br /> \item additive-by-dominance genetic variance, $\sigma^2_{AD}$; and<br /> \item dominance-by-dominance genetic variance, $\sigma^2_{DD}$.<br /> \end{itemize}<br /> See Lynch and Walsh (1998, pp. 88-92) for a thorough numerical example. This decomposition is not arbitrary or trivial, since each component has a distinct coefficient in the correlations between relatives. Is it possible for the authors to relate the variance associated with their $\mathbf{W}\bm{\theta}$ to this traditional decomposition? Besides justifying the work in this paper, the establishment of a relationship can have the possible practical benefit of allowing \texttt{i-LDSC} estimates of non-additive genetic variance to be checked against empirical correlations between relatives. For example, if we know from other methods that $\sigma^2_D$ is negligible but that \texttt{i-LDSC} returns a sizable $\sigma^2_{AA}$, we might predict that the parent-offspring correlation should be equal to the sibling correlation; a sizable $\sigma^2_D$ would make the sibling correlation higher. Admittedly, however, such an exercise can get rather complicated for the variance contributed by pairs of SNPs that are close together (Lynch & Walsh, 1998, pp. 146-152).

      I would also like the authors to clarify whether LDSC consistently overestimates the narrow-sense heritability in the case that pairwise epistasis is present. The figures seem to show this. I have conflicting intuitions here. On the one hand, if GWAS summary statistics can be inflated by the tagging of epistasis, then it seems that LDSC should overestimate heritability (or at least this should be an upwardly biasing factor; other factors may lead the net bias to be different). On the other hand, if standard and interaction LD Scores are lowly correlated, then I feel that the inclusion of interaction LD Score in the regression should not strongly affect the coefficient of the standard LD Score. Relatedly, I find it rather curious that \texttt{i-LDSC} seems increasingly biased as the proportion of genetic variance that is non-additive goes up---but perhaps this is not too important, since such a high ratio of narrow-sense to broad-sense heritability is not realistic.

      How Much Epistasis Is \texttt{i-LDSC} Detecting?

      I think the proper conclusion to be drawn from the authors' analyses is that statistically significant epistatic (non-additive) genetic variance was not detected. Specifically, I think that the analysis presented in Supplementary Table~S6 should be treated as a main analysis rather than a supplementary one, and the results here show no statistically significant epistasis. Let me explain.

      Most serious researchers, I think, treat LDSC as an unreliable estimator of narrow-sense heritability; it typically returns estimates that are too low. Not even the original LDSC paper pressed strongly to use the method for estimating $h^2$ (Bulik-Sullivan et al., 2015). As a practical matter, when researchers are focused on estimating absolute heritability with high accuracy, they usually turn to GCTA/GREML (Evans et al., 2018; Wainschtein et al., 2022).

      One reason for low estimates with LDSC is that if SNPs with higher LD Scores are less likely to be causal or to have large effect sizes, then the slope of univariate LDSC will not rise as much as it ``should' with increasing LD Score. This was a scenario actually simulated by the authors and displayed in their Supplementary Figure~S15. [Incidentally, the authors might have acknowledged earlier work in this vein. A simulation inducing a negative correlation between LD Scores and $\chi^2$ statistics was presented by Bulik-Sullivan et al. (2015, Supplementary Figure 7), and the potentially biasing effect of a correlation over SNPs between LD Scores and contributed genetic variance was a major theme of Lee et al. (2018).] A negative correlation between LD Score and contributed variance does seem to hold for a number of reasons, including the fact that regions of the genome with higher recombination rates tend to be more functional. In short, the authors did very well to carry out this simulation and to show in their Supplementary Figure~S15 that this flaw of LDSC in estimating narrow-sense heritability is also a flaw of \texttt{i-LDSC} in estimating broad-sense heritability. But they should have carried the investigation at least one step further, as I will explain below.

      Another reason for LDSC being a downwardly biased estimator of heritability is that it is often applied to meta-analyses of different cohorts, where heterogeneity (and possibly major but undetected errors by individual cohorts) lead to attenuation of the overall heritability (de Vlaming et al., 2017).

      The optimal case for using LDSC to estimate heritability, then, is incorporating the LD-related annotation introduced by Gazal et al. (2017) into a stratified-LDSC (s-LDSC) analysis of a single large cohort. This is analogous to the calculation of multiple GRMs defined by MAF and LD in the GCTA/GREML papers cited above. When this was done by Gazal et al. (2017, Supplementary Table 8b), the joint impact of the improvements was to increase the estimated narrow-sense heritability of height from 0.216 to 0.534.

      All of this has at least a few ramifications for \texttt{i-LDSC}. First, the authors do not consider whether a relationship between their interaction LD Scores and interaction effect sizes might bias their estimates. (This would be on top of any biasing relationship between standard LD Scores and linear effect sizes, as displayed in Supplementary Figure~S15.) I find some kind of statistical relationship over the whole genome, induced perhaps by evolutionary forces, between \emph{cis}-acting epistasis and interaction LD Scores to be plausible, albeit without intuition regarding the sign of any resulting bias. The authors should investigate this issue or at least mention it as a matter for future study. Second, it might be that the authors are comparing the estimates of broad-sense heritability in Table~1 to the wrong estimates of narrow-sense heritability. Although the estimates did come from single large cohorts, they seem to have been obtained with simple univariate LDSC rather than s-LDSC. When the estimate of $h^2$ obtained with LDSC is too low, some will suspect that the additional variance detected by \texttt{i-LDSC} is simply additive genetic variance missed by the downward bias of LDSC. Consider that the authors' own Supplementary Table~S6 gives s-LDSC heritability estimates that are consistently higher than the LDSC estimates in Table~1. E.g., the estimated $h^2$ of height goes from 0.37 to 0.43. The latter figure cuts quite a bit into the estimated broad-sense heritability of 0.48 obtained with \texttt{i-LDSC}.

      Here we come to a critical point. Lines 282--286 are not entirely clear, but I interpret them to mean that the manuscript's Equation~5 was expanded by stratifying $\ell$ into the components of s-LDSC and this was how the estimates in Supplementary Table~S6 were obtained. If that interpretation is correct, then the scenario of \texttt{i-LDSC} picking up missed additive genetic variance seems rather plausible. At the very least, the increases in broad-sense heritability reported in Supplementary Table~S6 are smaller in magnitude and \emph{not statistically significant}. Perhaps what this means is that the headline should be a \emph{negligible} contribution of pairwise epistasis revealed by this novel and ingenious method, analogous to what has been discovered with respect to dominance (Hivert et al., 2021; Pazokitoroudi et al., 2021; Okbay et al., 2022; Palmer et al., 2023).

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      Burger, R. (2000). The mathematical theory of selection, recombination, and mutation. Wiley.

      de Vlaming, R., Okbay, A., Rietveld, C. A., Johannesson, M., Magnusson, P. K. E., Uitterlinden, A. G., van Rooij, F. J. A., Hofman, A., Groe- nen, P. J. F., Thurik, A. R., & Koellinger, P. D. (2017). Meta-GWAS Accuracy and Power (MetaGAP) calculator shows that hiding heritability is partially due to imperfect genetic correlations across studies. PLoS Genetics, 13, e1006495.

      Evans, L. M., Tahmasbi, R., Vrieze, S. I., Abecasis, G. R., Das, S., Gazal, S., Bjelland, D. W., de Candia, T. R., Haplotype Reference Consortium, Goddard, M. E., Neale, B. M., Yang, J., Visscher, P. M., & Keller, M. C. (2018). Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits. Nature Genetics, 50, 737-745.

      Ewens, W. J. (2004). Mathematical population genetics I. Theoretical introduction (2nd ed.). Springer.

      Fisher, R. A. (1930). The genetical theory of natural selection. Oxford University Press.

      Fisher, R. A. (1941). Average excess and average effect of a gene substitution. Annals of Eugenics, 11, 53-63.

      Gazal, S., Finucane, H. K., Furlotte, N. A., Loh, P.-R., Palamara, P. F., Liu, X., Schoech, A., Bulik-Sullivan, B., Neale, B. M., Gusev, A., & Price, A. L. (2017). Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nature Genetics, 49, 1421-1427.

      Hivert, V., Sidorenko, J., Rohart, F., Goddard, M. E., Yang, J., Wray, N. R., Yengo, L., & Visscher, P. M. (2021). Estimation of non-additive genetic variance in human complex traits from a large sample of unrelated individuals. American Journal of Human Genetics, 108, 786- 798.

      Lee, J. J., McGue, M., Iacono, W. G., & Chow, C. C. (2018). The accuracy of LD Score regression as an estimator of confounding and genetic correlations in genome-wide association studies. Genetic Epidemiology, 42, 783-795.

      Lynch, M., & Walsh, B. (1998). Genetics and the analysis of quantitative traits. Sinauer.

      Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., ... Young, A. I. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individu- als. Nature Genetics, 54, 437-449.

      Palmer, D. S., Zhou, W., Abbott, L., Wigdor, E. M., Baya, N., Churchhouse, C., Seed, C., Poterba, T., King, D., Kanai, M., Bloemendal, A., & Neale, B. M. (2023). Analysis of genetic dominance in the UK Biobank. Science, 379, 1341-1348.

      Pazokitoroudi, A., Chiu, A. M., Burch, K. S., Pasaniuc, B., & Sankararaman, S. (2021). Quantifying the contribution of dominance deviation effects to complex trait variation in biobank-scale data. American Journal of Human Genetics, 108, 799-808.

      Wainschtein, P., Jain, D., Zheng, Z., TOPMed Anthropometry Working Group, NHLBI Trans-Omics for Precision Medicine Consoritum, Cupples, L. A., Shadyab, A. H., McKnight, B., Shoemaker, B. M., Mitchell, B. D., Psaty, B. M., Kooperberg, C., Liu, C.-T., Albert, C. M., Roden, D., Chasman, D. I., Darbar, D., Lloyd-Jones, D. M., Arnett, D. K., . . . Visscher, P. M. (2022). Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data. Nature Genetics, 54, 263-273.

    1. Reviewer #1 (Public Review):

      In this work, 40 healthy volunteers underwent a placebo followed by a ketamine infusion during a resting state fMRI scan. The authors use principal components analysis (PCA) of the difference in global brain connectivity (GBC) between the ketamine and placebo infusions as their summary neural measure. First, a GBC map is computed after processing with the HCP minimal pipeline and removal of the global brain signal for each scan (~4.5 min, TR=700ms). Then the significant PCA components of difference between ketamine and placebo GBC maps are taken as the neural effect of interest and compared to the mean delta GBC. The first two principal components account for 24.5% of the variance of the data and had correlations with SST and PVALB cortical gene expression patterns that were above chance. No significant correlations were found between mean change in GBC and these genes. Additionally, in comparison with the mean GBC the PCs were found to better correlate with behavioral measures.

      To further support their aim to establish the multi-dimensionality of the ketamine response using their neural measure, the PCA dimensionality was estimated in external datasets that used psilocybin and LSD with sample size matching using identical processing and found lower dimensionality in these datasets.

      Effective dimensionality was calculated using the participation ratio and dataset re-sampling was used to control for sample size in this calculation, but dimensionality is also affected by motion within the sample among other noise sources, which are not well discussed. In particular, each drug may affect physiological noise in different ways and this may in turn affect their dimensionality measurement.

      A PCA decomposition of the changes (ketamine-placebo) in 31 measured behavioral variables was also performed which resulted in two major PCs which accounted for 41.4% of the variance. Following prior work, behavioral PCs were mapped onto the neural PCs to create neuro-behavioral PCs. The weighing of the PCs at the individual level was explored to compare inter-individual variability.

      In an earlier fMRI study of the timeseries response to ketamine (De Simoni, 2013) it was clear that there are both individual and regional brain response differences. Behaviorally, there is known individual variability in the response to ketamine insofar as only about 60% of depressed people will experience symptom improvement and even then to varying levels. Thus, it is good to see that the compound summary measure of the PCA of the change in GBC after ketamine follows this pattern and shows inter-individual differences.

      A strength of this paper is that it brings together multimodal and external datasets and combines them in a linked analysis to support their investigational aims. Several sets of analyses are used to draw relations between fMRI results, genetics, and behavioral measures but the range of conclusions is limited by the understandably small sample size for this kind of drug challenge study. A weakness is that the chosen summary measure (delta GBC of ketamine-placebo, followed by a group-level PCA) that has been principally developed by this lab and has not seen wide replication. The presentation of the analyses could be simplified to increase readability and impact. Nevertheless, this study provides informative steps toward the development of markers for individualized drug response.

    1. Reviewer #1 (Public Review):

      This thorough study expands our understanding of BMP signaling, a conserved developmental pathway, involved in processes diverse such as body patterning and neurogenesis. The authors applied multiple, state-of-art strategies to the anthozoan Nematostella vectensis in order to first identify the direct BMP signaling targets - bound by the activated pSMAD1/5 protein - and then dissect the role of a novel pSMAD1/5 gradient modulator, zwim4-6. The list of target genes features multiple developmental regulators, many of which are bilaterally expressed, and which are notably shared between Drosophila and Xenopus. The analysis identified in particular zswim4-6 a novel nuclear modulator of the BMP pathway conserved also in vertebrates. A combination of both loss-of-function (injection of antisense morpholino oligonucleotide, CRISPR/Cas9 knockout, expression of dominant negative) and gain-of-function assays, and of transcriptome sequencing identified that zwim acts as a transcriptional repression of BMP signaling. Functional manipulation of zswim5 in zebrafish shows a conserved role in modulating BMP signaling in a vertebrate.<br /> The particular strength of the study lies in the careful and thorough analysis performed. This is solid developmental work, where one clear biological question is progressively dissected, with the most appropriate tools. The functional results are further validated by alternative approaches. Data is clearly presented and methods are detailed.

      I have a couple of comments.<br /> 1) I was intrigued - as the authors - by the fact that the ChiP-Seq did not identify any known BMP ligand bound by pSMAD1/5. Are these genes found in the published ChiP-Seq data of the other species used for the comparative analysis? One hypothesis could be that there is a change in the regulatory interactions and that the initial set-up of the gradient requires indeed a feedback loop, which is then turned off at later gastrula. In this case, immunoprecipitation at early gastrula, prior to the set-up of the pSMAD1/5 gradient, could reveal a different scenario. Alternately, the regulation could be indirect, for example, through RGM, an additional regulator of BMP signaling expressed on the side of lower BMP activity, which is among the targets of the ChiP-Seq. This aspect could be discussed. Additionally, even if this is perhaps outside the scope of this study, I think it would be informative to further assess the effect of ZSWIM manipulation on RGM (and vice versa).<br /> 2) I do not fully understand the rationale behind the choice of performing the comparative assays in zebrafish: as the conservation was initially identified in Xenopus, I would have expected the experiment to be performed in frog. Furthermore, reading the phylogeny (Figure 4A), it is not obvious to me why ZSWIM5 was chosen for the assay (over the other paralog ZSWIM6). Could the Authors comment on this experiment further?

    1. Reviewer #1 (Public Review):

      In several developmental systems, the core Planar Cell Polarity (PCP) pathway organises the dynamics of cellular behaviours underlying morphogenesis. During pupal stages, the Drosophila wing undergoes a complex morphogenetic process that results in the simultaneous elongation and narrowing of the wing blade along the proximal-distal and anterior-posterior axes, respectively. It was proposed that this dynamic process is driven by mechanical stress that results in cell deformations and cell rearrangements. However, prior work by Etournay et al. (eLife 2015) shows that mutants that reduce of mechanical stresses do not completely eliminate oriented cell rearrangements. Here, Piscitello-Gomez et al. use imaging techniques previously developed by them and others, combined with a computational analysis of a rheological model, to evaluate the role of the core-PCP pathway as a possible patterning cue that could orient cell rearrangements in this system. Surprisingly, the authors found that core-PCP mutants only affect an early retraction velocity upon laser ablation, but do not seem to drive overall morphogenesis in this system. Therefore, the original question of the work, namely, identifying the patterning cues that establish oriented cell rearrangements in this system, remains unanswered.

      The work exemplifies how the integration of mechanical perturbations, image analysis, and computational modelling could be used to investigate the contribution of a specific patterning cue in morphogenesis. While the conclusions of the manuscript are solid and the data support the conclusion that core-PCP pathway mutants do not display an altered cell dynamic or cell elongation phenotype relative to wild-type controls, one challenge of the approach is that the time-lapse imaging technique is done only in a handful of pupal wings. This does not permit to conclude whether subtle changes in cell elongation or cell rearrangements could account for observed changes in the shape of adult wings (that are more round in these mutants). Other patterning and polarity cues such as Fat-Daschous or Toll-like signalling are suggested by the authors, but their examination is left for future studies.

    1. Reviewer #1 (Public Review):

      This study uses electrophysiological techniques in vitro to address the role of the Na+ leak channel NALCN in various physiological functions in cartwheel interneurons of the dorsal cochlear nucleus. Comparing wild type and glycinergic neuron-specific knockout mice for NALCN, the authors show that these channels 1) are required for spontaneous firing, 2) are modulated by noradrenaline (NA, via alpha2 receptors) and GABA (through GABAB receptors), 3) how the modulation by NA enhances IPSCs in these neurons.

      This work builds on previous results from the Trussell's lab in terms of the physiology of cartwheel cells, and from other labs in terms of the role of NALCN channels, that have been characterized in more and more brain areas somewhat recently; for this reason, this study could be of interest for researchers that work in other preparations as well. The general conclusions are strongly supported by results that are clearly and elegantly presented.

      In this revised submission, the authors addressed all my questions. This is very interesting work that could be of interest for researchers working in other brain areas as well.

    1. Reviewer #1 (Public Review):

      In the manuscript "Long‐read single‐cell sequencing reveals expressions of hypermutation clusters of isoforms in human liver cancer cells", S. Liu et al present a protocol combining 10x Genomics single-cell assay with Element LoopSeq synthetic long-read sequencing to study single nucleotide variants (SNVs) and gene fusions in Hepatocellular carcinoma (HCC) at single‐cell level. The authors were the first to combine LoopSeq synthetic long‐read sequencing technology and 10x Genomics barcoding for single cell sequencing. For each cell and each somatic mutation, they obtain fractions of mutated transcripts per gene and per each transcript isoform. The manuscript states that these values (as well as gene fusion information) provide better features for tumor-normal classification than gene expression levels. The authors identified many SNVs in genes of the human major histocompatibility complex (HLA) with up to 25 SNVs in the same molecule of HLA‐DQB1 transcript. The analysis shows that most mutations occur in HLA genes and suggests evolution pathways that led to these hypermutation clusters.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The paper investigates the physiological and neural processes that relate to infants' attention allocation in a naturalistic setting. Contrary to experimental paradigms that are usually employed in developmental research, this study investigates attention processes while letting the infants be free to play with three toys in the vicinity of their caregiver, which is closer to a common, everyday life context. The paper focuses on infants at 5 and 10 months of age and finds differences in what predicts attention allocation. At 5 months, attention episodes are shorter and their duration is predicted by autonomic arousal. At 10 months, attention episodes are longer, and their duration can be predicted by theta power. Moreover, theta power predicted the proportion of looking at the toys, as well as a decrease in arousal (heart rate). Overall, the authors conclude that attentional systems change across development, becoming more driven by cortical processes.

      Strengths:<br /> I enjoyed reading the paper, I am impressed with the level of detail of the analyses, and I am strongly in favour of the overall approach, which tries to move beyond in-lab settings. The collection of multiple sources of data (EEG, heart rate, looking behaviour) at two different ages (5 and 10 months) is a key strength of this paper. The original analyses, which build onto robust EEG preprocessing, are an additional feat that improves the overall value of the paper. The careful consideration of how theta power might change before, during, and in the prediction of attention episodes is especially remarkable. However, I have a few major concerns that I would like the authors to address, especially on the methodological side.

      Points of improvement<br /> 1. Noise<br /> The first concern is the level of noise across age groups, periods of attention allocation, and metrics. Starting with EEG, I appreciate the analysis of noise reported in supplementary materials. The analysis focuses on a broad level (average noise in 5-month-olds vs 10-month-olds) but variations might be more fine-grained (for example, noise in 5mos might be due to fussiness and crying, while at 10 months it might be due to increased movements). More importantly, noise might even be the same across age groups, but correlated to other aspects of their behaviour (head or eye movements) that are directly related to the measures of interest. Is it possible that noise might co-vary with some of the behaviours of interest, thus leading to either spurious effects or false negatives? One way to address this issue would be for example to check if noise in the signal can predict attention episodes. If this is the case, noise should be added as a covariate in many of the analyses of this paper.<br /> Moving onto the video coding, I see that inter-rater reliability was not very high. Is this due to the fine-grained nature of the coding (20ms)? Is it driven by differences in expertise among the two coders? Or because coding this fine-grained behaviour from video data is simply too difficult? The main dependent variable (looking duration) is extracted from the video coding, and I think the authors should be confident they are maximising measurement accuracy.

      2. Cross-correlation analyses<br /> I would like to raise two issues here. The first is the potential problem of using auto-correlated variables as input for cross-correlations. I am not sure whether theta power was significantly autocorrelated. If it is, could it explain the cross-correlation result? The fact that the cross-correlation plots in Figure 6 peak at zero, and are significant (but lower) around zero, makes me think that it could be a consequence of periods around zero being autocorrelated. Relatedly: how does the fact that the significant lag includes zero, and a bit before, affect the interpretation of this effect?

      A second issue with the cross-correlation analyses is the coding of the looking behaviour. If I understand correctly, if an infant looked for a full second at the same object, they would get a maximum score (e.g., 1) while if they looked at 500ms at the object and 500ms away from the object, they would receive a score of e.g., 0.5. However, if they looked at one object for 500ms and another object for 500ms, they would receive a maximum score (e.g., 1). The reason seems unclear to me because these are different attention episodes, but they would be treated as one. In addition, the authors also show that within an attentional episode theta power changes (for 10mos). What is the reason behind this scoring system? Wouldn't it be better to adjust by the number of attention switches, e.g., with the formula: looking-time/(1+N_switches), so that if infants looked for a full second, but made 1 switch from one object to the other, the score would be .5, thus reflecting that attention was terminated within that episode?

      3. Clearer definitions of variables, constructs, and visualisations<br /> The second issue is the overall clarity and systematicity of the paper. The concept of attention appears with many different names. Only in the abstract, it is described as attention control, attentional behaviours, attentiveness, attention durations, attention shifts and attention episode. More names are used elsewhere in the paper. Although some of them are indeed meant to describe different aspects, others are overlapping. As a consequence, the main results also become more difficult to grasp. For example, it is stated that autonomic arousal predicts attention, but it's harder to understand what specific aspect (duration of looking, disengagement, etc.) it is predictive of. Relatedly, the cognitive process under investigation (e.g., attention) and its operationalization (e.g., duration of consecutive looking toward a toy) are used interchangeably. I would want to see more demarcation between different concepts and between concepts and measurements.

      General Remarks<br /> In general, the authors achieved their aim in that they successfully showed the relationship between looking behaviour (as a proxy of attention), autonomic arousal, and electrophysiology. Two aspects are especially interesting. First, the fact that at 5 months, autonomic arousal predicts the duration of subsequent attention episodes, but at 10 months this effect is not present. Conversely, at 10 months, theta power predicts the duration of looking episodes, but this effect is not present in 5-month-old infants. This pattern of results suggests that younger infants have less control over their attention, which mostly depends on their current state of arousal, but older infants have gained cortical control of their attention, which in turn impacts their looking behaviour and arousal.

    1. Reviewer #1 (Public Review):

      In this study, authors performed multiple sets of mesoscale chromatin simulations at nucleosome resolution to study the effects of TF binding on chromatin structures. Through simulations at various conditions, authors performed systemically analysis to investigate how linker histone, tail acetylation, and linker DNA length can operate together with TFs to regulate chromatin architecture. Using gene Eed as one example, authors found that binding of Myc:Max could repress the gene expression by increasing fiber folding and compaction and this repression can be reversed by the linker histone. Understanding how transcription factors bind to regulatory DNA elements and modulate chromatin structure and accessibility is an essential question in epigenetics. Through modelling of TF binding to chromatin structures at nucleosome levels, authors demonstrated that TF binding could create microdomains that are visible in the ensemble-based contact maps and short DNA linkers prevent the formation microdomains. It has also been shown that tail acetylation and TF binding have opposite effects on chromatin compaction and linker histone can compete for the linker DNA with TF binding to impair the effect of TF binding. This study improves our knowledge on how TFs collaborate with different epigenetic marks and chromatin features to regulate chromatin structure and accessibility, which will be of broad interest to the community.

    1. Reviewer #1 (Public Review):

      In this very strong and interesting paper the authors present a convincing series of experiments that reveal molecular mechansism of neuronal cell type diversification in the nervous system of Drosophila. The authors show that a homeodomain transcription factor, Bsh, fulfills several critical functions - repressing an alternative fate and inducing downstream homeodomain transcription factors with whom Bsh may collaborate to induce L4 and L5 fates (the author's accompanying paper reveals how Bsh can induce two distinct fates). The authors make elegant use of powerful genetic tools and an arsenal of satisfying cell identity markers.

      I believe that this is an important study because it provides some fundamental insights into the conservation of neuronal diversification programs. It is very satisfying to see that similar organizational principles apply in different organism to generate cell type diversity. The authors should also be commended for contextualizing their work very well, giving a broad, scholarly background to the problem of neuronal cell type diversification.

      My one suggestion for the authors is to perhaps address in the Discussion (or experimentally address if they wish) how they reconcile that Bsh is on the one hand: (a) continuously expressed in L4/L4, (b) binding directly to a cohort of terminal effectors that are also continuously expressed but then, on the other hand, is not required for their maintaining L4 fate? A few questions: Is Bsh only NOT required for maintaining Ap expression or is it also NOT required for maintaining other terminal markers of L4? The former could be easily explained - Bsh simply kicks of Ap, Ap then autoregulates, but Bsh and Ap then continuously activate terminal effector genes. The second scenario would require a little more complex mechanism: Bsh binding of targets (with Notch) may open chromatin, but then once that's done, Bsh is no longer needed and Ap alone can continue to express genes. I feel that the authors should be at least discussing this. The postmitotic Bsh removal experiment in which they only checked Ap and depression of other markers is a little unsatisfying without further discussion (or experiments, such as testing terminal L4 markers). I hasten to add that this comment does not take away from my overall appreciation for the depth and quality of the data and the importance of their conclusions.

    1. Reviewer #1 (Public Review):

      Like the "preceding" co-submitted paper, this is again a very strong and interesting paper in which the authors address a question that is raised by the finding in their co-submitted paper - how does one factor induce two different fates. The authors provide an extremely satisfying answer - only one subset of the cells neighbors a source of signaling cells that trigger that subset to adopt a specific fate. The signal here is Delta and the read-out is Notch, whose intracellular domain, in conjunction with, presumably, SuH cooperates with Bsh to distinguish L4 from L5 fate (L5 is not neighbored by signal-providing cells). Like the back-to-back paper, the data is rigorous, well-presented and presents important conclusions. There's a wealth of data on the different functions of Notch (with and without Bsh). All very satisfying.

      I have again one suggestion that the authors may want to consider discussing. I'm wondering whether the open chromatin that the author convincingly measure is the CAUSE or the CONSEQUENCE of Bsh being able to activate L4 target genes. What I mean by this is that currently the authors seem to be focused on a somewhat sequential model where Notch signaling opens chromatin and this then enables Bsh to activate a specific set of target genes. But isn't it equally possible that the combined activity of Bsh/Notch(intra)/SuH opens chromatin? That's not a semantic/minor difference, it's a fundamentally different mechanism, I would think. This mechanism also solves the conundrum of specificity - how does Notch know which genes to "open" up? It would seem more intuitive to me to think that it's working together with Bsh to open up chromatin, with chromatin accessibility than being a "mere" secondary consequence. If I'm not overlooking something fundamental here, there is actually also a way to distinguish between these models - test chromatin accessibility in a Bsh mutant. If the author's model is true, chromatin accessibility should be unchanged.

      I again finish by commending the authors for this terrific piece of work.

    1. Reviewer #1 (Public Review):

      Summary:

      This study aims to provide imaging methods for users of the field of human layer-fMRI. This is an emerging field with 240 papers published so far. Different than implied in the manuscript, 3T is well represented among those papers. E.g. see the papers below that are not cited in the manuscript. Thus, the claim on the impact of developing 3T methodology for wider dissemination is not justified. Specifically, because some of the previous papers perform whole brain layer-fMRI (also at 3T) in more efficient, and more established procedures.

      The authors implemented a sequence with lots of nice features. Including their own SMS EPI, diffusion bipolar pulses, eye-saturation bands, and they built their own reconstruction around it. This is not trivial. Only a few labs around the world have this level of engineering expertise. I applaud this technical achievement. However, I doubt that any of this is the right tool for layer-fMRI, nor does it represent an advancement for the field. In the thermal noise dominated regime of sub-millimeter fMRI (especially at 3T), it is established to use 3D readouts over 2D (SMS) readouts. While it is not trivial to implement SMS, the vendor implementations (as well as the CMRR and MGH implementations) are most widely applied across the majority of current fMRI studies already. The author's work on this does not serve any previous shortcomings in the field.

      The mechanism to use bi-polar gradients to increase the localization specificity is doubtful to me. In my understanding, killing the intra-vascular BOLD should make it less specific. Also, the empirical data do not suggest a higher localization specificity to me.

      Embedding this work in the literature of previous methods is incomplete. Recent trends of vessel signal manipulation with ABC or VAPER are not mentioned. Comparisons with VASO are outdated and incorrect.

      The reproducibility of the methods and the result is doubtful (see below).

      I don't think that this manuscript is in the top 50% of the 240 layer-fmri papers out there.

      3T layer-fMRI papers that are not cited:<br /> Taso, M., Munsch, F., Zhao, L., Alsop, D.C., 2021. Regional and depth-dependence of cortical blood-flow assessed with high-resolution Arterial Spin Labeling (ASL). Journal of Cerebral Blood Flow and Metabolism. https://doi.org/10.1177/0271678X20982382

      Wu, P.Y., Chu, Y.H., Lin, J.F.L., Kuo, W.J., Lin, F.H., 2018. Feature-dependent intrinsic functional connectivity across cortical depths in the human auditory cortex. Scientific Reports 8, 1-14. https://doi.org/10.1038/s41598-018-31292-x

      Lifshits, S., Tomer, O., Shamir, I., Barazany, D., Tsarfaty, G., Rosset, S., Assaf, Y., 2018. Resolution considerations in imaging of the cortical layers. NeuroImage 164, 112-120. https://doi.org/10.1016/j.neuroimage.2017.02.086

      Puckett, A.M., Aquino, K.M., Robinson, P.A., Breakspear, M., Schira, M.M., 2016. The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex. NeuroImage 139, 240-248. https://doi.org/10.1016/j.neuroimage.2016.06.019

      Olman, C.A., Inati, S., Heeger, D.J., 2007. The effect of large veins on spatial localization with GE BOLD at 3 T: Displacement, not blurring. NeuroImage 34, 1126-1135. https://doi.org/10.1016/j.neuroimage.2006.08.045

      Ress, D., Glover, G.H., Liu, J., Wandell, B., 2007. Laminar profiles of functional activity in the human brain. NeuroImage 34, 74-84. https://doi.org/10.1016/j.neuroimage.2006.08.020

      Huber, L., Kronbichler, L., Stirnberg, R., Ehses, P., Stocker, T., Fernández-Cabello, S., Poser, B.A., Kronbichler, M., 2023. Evaluating the capabilities and challenges of layer-fMRI VASO at 3T. Aperture Neuro 3. https://doi.org/10.52294/001c.85117

      Scheeringa, R., Bonnefond, M., van Mourik, T., Jensen, O., Norris, D.G., Koopmans, P.J., 2022. Relating neural oscillations to laminar fMRI connectivity in visual cortex. Cerebral Cortex. https://doi.org/10.1093/cercor/bhac154

      Strengths:

      See above. The authors developed their own SMS sequence with many features. This is important to the field. And does not leave sequence development work to view isolated monopoly labs. This work democratises SMS.<br /> The questions addressed here are of high relevance to the field: getting tools with good sensitivity, user-friendly applicability, and locally specific brain activity mapping is an important topic in the field of layer-fMRI.

      Weaknesses:

      1. I feel the authors need to justify why flow-crushing helps localization specificity. There is an entire family of recent papers that aim to achieve higher localization specificity by doing the exact opposite. Namely, MT or ABC fRMRI aims to increase the localization specificity by highlighting the intravascular BOLD by means of suppressing non-flowing tissue. To name a few:

      Priovoulos, N., de Oliveira, I.A.F., Poser, B.A., Norris, D.G., van der Zwaag, W., 2023. Combining arterial blood contrast with BOLD increases fMRI intracortical contrast. Human Brain Mapping hbm.26227. https://doi.org/10.1002/hbm.26227.

      Pfaffenrot, V., Koopmans, P.J., 2022. Magnetization Transfer weighted laminar fMRI with multi-echo FLASH. NeuroImage 119725. https://doi.org/10.1016/j.neuroimage.2022.119725

      Schulz, J., Fazal, Z., Metere, R., Marques, J.P., Norris, D.G., 2020. Arterial blood contrast ( ABC ) enabled by magnetization transfer ( MT ): a novel MRI technique for enhancing the measurement of brain activation changes. bioRxiv. https://doi.org/10.1101/2020.05.20.106666

      Based on this literature, it seems that the proposed method will make the vein problem worse, not better. The authors could make it clearer how they reason that making GE-BOLD signals more extra-vascular weighted should help to reduce large vein effects.

      The empirical evidence for the claim that flow crushing helps with the localization specificity should be made clearer. The response magnitude with and without flow crushing looks pretty much identical to me (see Fig, 6d).<br /> It's unclear to me what to look for in Fig. 5. I cannot discern any layer patterns in these maps. It's too noisy. The two maps of TE=43ms look like identical copies from each other. Maybe an editorial error?

      The authors discuss bipolar crushing with respect to SE-BOLD where it has been previously applied. For SE-BOLD at UHF, a substantial portion of the vein signal comes from the intravascular compartment. So I agree that for SE-BOLD, it makes sense to crush the intravascular signal. For GE-BOLD however, this reasoning does not hold. For GE-BOLD (even at 3T), most of the vein signal comes from extravascular dephasing around large unspecific veins, and the bipolar crushing is not expected to help with this.

      2. The bipolar crushing is limited to one single direction of flow. This introduces a lot of artificial variance across the cortical folding pattern. This is not mentioned in the manuscript. There is an entire family of papers that perform layer-fmri with black-blood imaging that solves this with a 3D contrast preparation (VAPER) that is applied across a longer time period, thus killing the blood signal while it flows across all directions of the vascular tree. Here, the signal cruising is happening with a 2D readout as a "snap-shot" crushing. This does not allow the blood to flow in multiple directions.<br /> VAPER also accounts for BOLD contaminations of larger draining veins by means of a tag-control sampling. The proposed approach here does not account for this contamination.

      Chai, Y., Li, L., Huber, L., Poser, B.A., Bandettini, P.A., 2020. Integrated VASO and perfusion contrast: A new tool for laminar functional MRI. NeuroImage 207, 116358. https://doi.org/10.1016/j.neuroimage.2019.116358

      Chai, Y., Liu, T.T., Marrett, S., Li, L., Khojandi, A., Handwerker, D.A., Alink, A., Muckli, L., Bandettini, P.A., 2021. Topographical and laminar distribution of audiovisual processing within human planum temporale. Progress in Neurobiology 102121. https://doi.org/10.1016/j.pneurobio.2021.102121

      If I would recommend anyone to perform layer-fMRI with blood crushing, it seems that VAPER is the superior approach. The authors could make it clearer why users might want to use the unidirectional crushing instead.

      3. The comparison with VASO is misleading.<br /> The authors claim that previous VASO approaches were limited by TRs of 8.2s. The authors might be advised to check the latest literature of the last years.<br /> Koiso et al. performed whole brain layer-fMRI VASO at 0.8mm at 3.9 seconds (with reliable activation), 2.7 seconds (with unconvincing activation pattern, though), and 2.3 (without activation).<br /> Also, whole brain layer-fMRI BOLD at 0.5mm and 0.7mm has been previously performed by the Juelich group at TRs of 3.5s (their TR definition is 'fishy' though).

      Koiso, K., Müller, A.K., Akamatsu, K., Dresbach, S., Gulban, O.F., Goebel, R., Miyawaki, Y., Poser, B.A., Huber, L., 2023. Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset. Aperture Neuro 34. https://doi.org/10.1101/2022.08.19.504502

      Yun, S.D., Pais‐Roldán, P., Palomero‐Gallagher, N., Shah, N.J., 2022. Mapping of whole‐cerebrum resting‐state networks using ultra‐high resolution acquisition protocols. Human Brain Mapping. https://doi.org/10.1002/hbm.25855

      Pais-Roldan, P., Yun, S.D., Palomero-Gallagher, N., Shah, N.J., 2023. Cortical depth-dependent human fMRI of resting-state networks using EPIK. Front. Neurosci. 17, 1151544. https://doi.org/10.3389/fnins.2023.1151544

      The authors are correct that VASO is not advised as a turn-key method for lower brain areas, incl. Hippocampus and subcortex. However, the authors use this word of caution that is intended for inexperienced "users" as a statement that this cannot be performed. This statement is taken out of context. This statement is not from the academic literature. It's advice for the 40+ user base that wants to perform layer-fMRI as a plug-and-play routine tool in neuroscience usage. In fact, sub-millimeter VASO is routinely being performed by MRI-physicists across all brain areas (including deep brain structures, hippocampus etc). E.g. see Koiso et al. and an overview lecture from a layer-fMRI workshop that I had recently attended: https://youtu.be/kzh-nWXd54s?si=hoIJjLLIxFUJ4g20&t=2401

      Thus, the authors could embed this phrasing into the context of their own method that they are proposing in the manuscript. E.g. the authors could state whether they think that their sequence has the potential to be disseminated across sites, considering that it requires slow offline reconstruction in Matlab?<br /> Do the authors think that the results shown in Fig. 6c are suggesting turn-key acquisition of a routine mapping tool? In my humble opinion, it looks like random noise, with most of the activation outside the ROI (in white matter).

      4. The repeatability of the results is questionable.<br /> The authors perform experiments about the robustness of the method (line 620). The corresponding results are not suggesting any robustness to me. In fact, the layer profiles in Fig. 4c vs. Fig 4d are completely opposite. The location of peaks turns into locations of dips and vice versa.<br /> The methods are not described in enough detail to reproduce these results.<br /> The authors mention that their image reconstruction is done "using in-house MATLAB code" (line 634). They do not post a link to github, nor do they say if they share this code.

      It is not trivial to get good phase data for fMRI. The authors do not mention how they perform the respective coil-combination.<br /> No data are shared for reproduction of the analysis.

      5. The application of NODRIC is not validated.<br /> Previous applications of NORDIC at 3T layer-fMRI have resulted in mixed success. When not adjusted for the right SNR regime it can result in artifactual reductions of beta scores, depending on the SNR across layers. The authors could validate their application of NORDIC and confirm that the average layer-profiles are unaffected by the application of NORDIC. Also, the NORDIC version should be explicitly mentioned in the manuscript.

      Akbari, A., Gati, J.S., Zeman, P., Liem, B., Menon, R.S., 2023. Layer Dependence of Monocular and Binocular Responses in Human Ocular Dominance Columns at 7T using VASO and BOLD (preprint). Neuroscience. https://doi.org/10.1101/2023.04.06.535924

      Knudsen, L., Guo, F., Huang, J., Blicher, J.U., Lund, T.E., Zhou, Y., Zhang, P., Yang, Y., 2023. The laminar pattern of proprioceptive activation in human primary motor cortex. bioRxiv. https://doi.org/10.1101/2023.10.29.564658

    1. Reviewer #1 (Public Review):

      Summary:<br /> Based on a "dichoptic-background-movie" paradigm that modulates ocular dominance, the present study combines fMRI and TMS to examine the role of the frontoparietal attentional network in ocular dominance shifts. The authors claimed a causal role of FEF in generating the attention-induced ocular dominance shift.

      Strengths:<br /> A combination of fMRI, TMS, and "dichoptic-background-movie" paradigm techniques is used to reveal the causal role of the frontoparietal attentional network in ocular dominance shifts. The conclusions of this paper are mostly well supported by data.

      Weaknesses:<br /> The relationship between eye dominance, eye-based attention shift, and cortical functions remains unclear and merits further delineation. The rationale of the experimental design related to the hemispheric asymmetry in the FEF and other regions should be clarified.

      Theoretically, how the eye-related functions in this area could be achieved, and how it interacts with the ocular representation in V1 warrant further clarification.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors of this study investigated the development of interoceptive sensitivity in the context of cardiac and respiratory interoception in 3-, 9-, and 18-month-old infants using a combination of both cross-sectional and longitudinal designs. They utilised the cardiac interoception paradigm developed by Maister et al (2017) and also developed a new paradigm to investigate respiratory interoception in infants. The main findings of this research are that 9-month-old infants displayed a preference for stimuli presented synchronously with their own heartbeat and respiration. The authors found less reliable effects in the 18-month-old group, and this was especially true for the respiratory interoceptive data. The authors replicated a visual preference for synchrony over asynchrony for the cardiac domain in 3-month-old infants, while they found inconclusive evidence regarding the respiratory domain. Considering the developmental nature of the study, the authors also investigated the presence of developmental trajectories and associations between the two interoceptive domains. They found evidence for a relationship between cardiac and respiratory interoceptive sensitivity at 18 months only and preliminary evidence for an increase in respiratory interoception between 9 and 18 months.

      Strengths: The conclusions of this paper are mostly well supported by data, and the data analysis procedures are rigorous and well-justified. The main strengths of the paper are:<br /> - A first attempt to explore the association between two different interoceptive domains. How different organ-specific axes of interoception relate to each other is still open and exploring this from a developmental lens can help shed light into possible relationships. The authors have to be commended for developing novel interoceptive tasks aimed at assessing respiratory interoceptive sensitivity in infants and toddlers, and for trying to assess the relationship between cardiac and respiratory interoception across developmental time.<br /> - A thorough justification of the developmental ages selected for the study. The authors provide a rationale behind their choice to examine interoceptive sensitivity at 3, 9, and 18 months of age. These are well justified based on the literature pertaining to self- and social development. Sometimes, I wondered whether explaining the link between these self and social processes and interoception would have been beneficial as a reader not familiar with the topics may miss the point.<br /> - An explanation of the direction of looking behaviour using latent curve analysis. I found this additional analysis extremely helpful in providing a better understanding of the data based on previous research and analytical choices (though see comment under weaknesses). As the authors explain in the manuscript, it is often difficult to interpret the direction of infant-looking behaviour as novelty and familiarity preferences can also be driven by hidden confounders (e.g. task difficulty). The authors provide some evidence that analytical choices can explain some of these effects. Beyond the field of interoception, these findings will be relevant to development psychologists and will inform future studies using looking time as a measure of infants' ability to discriminate among stimuli.<br /> - The use of simulation analysis to account for the small sample size. The authors acknowledge that some of the effects reported in their study could be explained by a small sample size (i.e. the 3-month-olds and 18-month-olds data). Using a simulation approach, the authors try to overcome some of these limitations and provide convincing evidence of interoceptive abilities in infancy and toddlerhood (but see also my next point).

      Weaknesses:<br /> - The authors should carefully address the potential confounding of not counterbalancing the conditions of the first trial in both interoceptive tasks for the 9-month and 18-month age groups. The results of these groups could indeed be driven by having seen the synchronous trial first.<br /> - The conclusion that cardiac interoception remains stable across infancy is not fully warranted by the data. Given the small sample size of 18-month-old toddlers included in the final analyses, it might be misleading to state this without including the caveat that the study may be underpowered. In other words, the small sample size could explain the direction of the results for this age group.

    1. Reviewer #1 (Public Review):

      This study examined a universal fractal primate brain shape. However, the paper does not seem well structured and is not well written. It is not clear what the purpose of the paper is. And there is a lack of explanation for why the proposed analysis is necessary. As a result, it is challenging to clearly understand what novelty in the paper is and what the main findings are. Additionally, several terms are introduced without adequate explanation and contextualization, further complicating comprehension. Does the second section, "2. Coarse-graining procedure", serve as an introduction or a method? Moreover, the rationale behind the use of the coarse-graining procedure is not adequately elucidated. Overall, it is strongly recommended that the paper undergoes significant improvements in terms of its structure, explanatory depth, and overall clarity to enhance its comprehensibility.

    1. Reviewer #1 (Public Review):

      The major aim of the paper was a method for determining genetic associations between two traits using common variants tested in genome-wide association studies. The work includes a software implementation and application of their approach. The results of the application of their method generally agree with what others have seen using similar AD and UKB data.

      The paper has several distinct portions. The first is a method for testing genetic associations between two or more traits using genome-wide association tests statistics. The second is a python implementation of the method. The last portion is the results of their method using GWAS from AD and UK Biobank.

      Regarding the method, it seems like it has similarities to LDSC, and it is not clear how it differs from LDSC or other similar methods. The implementation of the method used python 2.7 (or at least was reportedly tested using that version) that was retired in 2020. The implementation was committed between Wed Oct 3 15:21:49 2018 to Mon Jan 28 09:18:09 2019 using data that existed at the time so it was a bit surprising it used python 2.7 since it was initially going to be set for end-of-life in 2015. Anyway, trying to run the package resulted in unmet dependency errors, which I think are related to an internal package not getting installed. I would expect that published software could be installed using standard tooling for the language, and, ideally, software should have automated testing of key portions.

      Regarding the main results, they find what has largely been shown by others using the same data or similar data, which add prima facie validity to the work The portions of the work dealing with AD subgroups, pathology, biomarkers, and cognitive traits of interest. I was puzzled why the authors suggested surprise regarding parental history and high cholesterol not associated with MCI or cognitive composite scores since the this would seem like the likely fallout of selection of the WRAP cohort. The discussion paragraph that started "What's more, environmental factors may play a big role in the identified associations." confused me. I think what the authors are referring to are how selection, especially in a biobank dataset, can induce correlations, which is not what I think of as an environmental effect.

      Overall, the work has merit, but I am left without a clear impression of the improvement in the approach over similar methods. Likewise, the results are interesting, but similar findings are described with the data that was used in the study, which are over 5 years old at the time of this review.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Frey et al. report the structures of aSyn fibrils that were obtained under a variety of conditions. These include the generation of aSyn fibrils without seeds, but in different buffers and at different pH values. These also include the generation of aSyn fibrils in the presence of seeding fibrils, again performed in different buffers and at different pH values, while the seeds were generated at different conditions. The authors find that fibril polymorphs primarily correlate with fibril growth buffer conditions, and not such much with the type of seed. However, the presence of a seed is still required, likely because fibrils can also seed along their lateral surfaces, not only at the blunt ends.

      Strengths:<br /> The manuscript includes an excellent review of the numerous available structures of aSyn. As the authors state, "it seems that there are about as many unique atomic-resolution structures of these aggregates as there are publications describing them."

      The text is interesting to read, figures are clear and not redundant.

      Weaknesses:<br /> The manuscript is excellently written, but sometimes a few commas are lacking.

    1. Reviewer #1 (Public Review):

      Summary:<br /> UGGTs are involved in the prevention of premature degradation for misfolded glycoproteins, by utilizing UGGT-KO cells and a number of different ERAD substrates. They proposed a concept by which the fate of glycoproteins can be determined by a tug-of-war between UGGTs and EDEMs.

      Strengths:<br /> The authors provided a wealth of data to indicate that UGGT1 competes with EDEMs, which promotes glycoprotein degradation.

      Weaknesses:<br /> Less clear, though, is the involvement of UGGT2 in the process. Also, to this reviewer, some data do not necessarily support the conclusion.

      Major criticisms:

      1. One of the biggest problems I had on reading through this manuscript is that, while the authors appeared to generate UGGTs-KO cells from HCT116 and HeLa cells, it was not clearly indicated which cell line was used for each experiment. I assume that it was HCT116 cells in most cases, but I did not see that it was clearly mentioned. As the expression level of UGGT2 relative to UGGT1 is quite different between the two cell lines, it would be critical to know which cells were used for each experiment.

      2. While most of the authors' conclusion is sound, some claims, to this reviewer, were not fully supported by the data. Especially I cannot help being puzzled by the authors' claim about the involvement of UGGT2 in the ERAD process. In most of the cases, KO of UGGT2 does not seem to affect the stability of ERAD substrates (ex. Fig. 1C, 2A, 3D). When the author suggests that UGGT2 is also involved in the ERAD, it is far from convincing (ex. Fig. 2D/E). Especially because now it has been suggested that the main role of UGGT2 may be distinct from UGGT1, playing a role in lipid quality control (Hung, et al., PNAS 2022), it is imperative to provide convincing evidence if the authors want to claim the involvement of UGGT2 in a protein quality control system.

      In fact, it was not clear at all whether even UGGT1 is also involved in the process in Fig. 2D/E, as the difference, if any, is so subtle. How the authors can be sure that this is significant enough? While the authors claim that the difference is statistically significant (n=3), this may end up with experimental artifacts. To say the least, I would urge the authors to try rescue experiments with UGGT1 or 2, to clarify that the defect in UGGT-DKO cells can be reversed. It may also be interesting to see that the subtle difference the authors observed is indeed N-glycan-dependent by testing a non-glycosylated version of the protein (just like NHK-QQQ mutants in Fig. 2C).

      To this reviewer, it is still possible that the involvement of UGGT1 (or 2, if any) could be totally substrate-dependent, and the substrates used in Fig 2D or E happen not to be dependent to the action of UGGTs. To the reviewer, without the data of Fig. 2D and E the authors provide enough evidence to demonstrate the involvement of UGGT1 in preventing premature degradation of glycoprotein ERAD substrates. I am just afraid that the authors may have overinterpreted the data, as if the UGGTs are involved in stabilization of all glycoproteins destined for ERAD.

      3. I am a bit puzzled by the DNJ treatment experiments. First, I do not see the detailed conditions of the DNJ treatment (concentration? Time?). Then, I was a bit surprised to see that there were so little G3M9 glycans formed, and there was about the same amount of G2M9 also formed (Figure 1 Figure supplement 4B-D), despite the fact that glucose trimming of newly syntheized glycoproteins are expected to be completely impaired (unless the authors used DNJ concentration which does not completely impair the trimming of the first Glc). Even considering the involvement of Golgi endo-alpha-mannosidase, a similar amount of G3M9 and G2M9 may suggest that the experimental conditions used for this experiment (i.e. concentration of DNJ, duration of treatment, etc) is not properly optimized.

    1. Reviewer #1 (Public Review):

      It is known that aberrant habit formation is a characteristic of obsessive-compulsive disorder (OCD). Habits can be defined according to the following features (Balleine and Dezfouli, 2019): rapid execution, invariant response topography, action 'chunking' and resistance to devaluation.<br /> The extent to which OCD behavior is derived from enhanced habit formation relative to deficits in goal-directed behavior is a topic of debate in the current literature. This study examined habit-learning specifically (cf. deficits in goal-directed behavior) by regularly presenting, via smartphone, sequential learning tasks to patients with OCD and healthy controls. Participants engaged in the tasks every day over the course of a month. Automaticity, including the extent to which individual actions in the sequence become part of a unified 'chunk', was an important outcome variable. Following the 30 days of training, in-laboratory tasks were then administered to examine 1) if performing the learned sequences themselves had become rewarding 2) differences in goal-directed vs. habitual behavior.

      Several hypotheses were tested, including:<br /> Patients would have impaired procedural learning vs. healthy volunteers (this was not supported, possibly because there were fewer demands on memory in the task used here)<br /> Once the task had been learned, patients would display automaticity faster (unexpectedly, patients were slower to display automaticity)<br /> Habits would form faster under a continuous (vs. variable) reinforcement schedule

      Exploratory analyses were also conducted: an interesting finding was that OCD patients with higher self-reported symptoms voluntarily completed more sessions with the habit-training app and reported a reduction in symptoms.

      Strengths

      This paper is well situated theoretically within the habit learning/OCD literature.<br /> Daily training in a motor-learning task, delivered via smartphone, was innovative, ecologically valid and more likely to assay habitual behaviors specifically. Daily training is also more similar to studies with non-humans, making a better link with that literature. The use of a sequential-learning task (cf. tasks that require a single response) is also more ecologically valid.<br /> The in-laboratory tests (after the 1 month of training) allowed the researchers to test if the OCD group preferred familiar, but more difficult, sequences over newer, simpler sequences.

      Weaknesses

      The authors were not able to test one criterion of habits, namely resistance to devaluation, due to the nature of the task.<br /> The sample size was relatively small. Some potentially interesting individual differences within the OCD group could have been examined more thoroughly with a bigger sample (e.g., preference for familiar sequences). A larger sample may have allowed the statistical testing of any effects due to medication status.

      The authors achieved their aims in that two groups of participants (patients with OCD and controls) engaged with the task over the course of 30 days. The repeated nature of the task meant that 'overtraining' was almost certainly established, and automaticity was demonstrated. This allowed the authors to test their hypotheses about habit learning. The results are supportive of the author's conclusions.

      This article is likely to be impactful -- the delivery of a task across 30 days to a patient group is innovative and represents a new approach for the study of habit learning that is superior to an in-laboratory approach.

      An interesting aspect of this manuscript is that it prompts a comparison with previous studies of goal-directed/habitual responding in OCD that used devaluation protocols, and which may have had their effects due to deficits in goal-directed behavior and not enhanced habit learning per se.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Ger and colleagues address an issue that often impedes computational modeling: the inherent ambiguity between stochasticity in behavior and structural mismatch between the assumed and true model. They propose a solution to use RNNs to estimate the ceiling on explainable variation within a behavioral dataset. With this information in hand, it is possible to determine the extent to which "worse fits" result from behavioral stochasticity versus failures of the cognitive model to capture nuances in behavior (model misspecification). The authors demonstrate the efficacy of the approach in a synthetic toy problem and then use the method to show that poorer model fits to 2-step data in participants with low IQ are actually due to an increase in inherent stochasticity, rather than systemic mismatch between model and behavior.

      Strengths:<br /> Overall I found the ideas conveyed in the paper interesting and the paper to be extremely clear and well-written. The method itself is clever and intuitive and I believe it could be useful in certain circumstances, particularly ones where the sources of structure in behavioral data are unknown. In general, the support for the method is clear and compelling. The flexibility of the method also means that it can be applied to different types of behavioral data - without any hypotheses about the exact behavioral features that might be present in a given task.

      Weaknesses:<br /> That said, I have some concerns with the manuscript in its current form, largely related to the applicability of the proposed methods for problems of importance in computational cognitive neuroscience. This concern stems from the fact that the toy problem explored in the manuscript is somewhat simple, and the theoretical problem addressed in it could have been identified through other means (for example through the use of posterior predictive checking for model validation), and the actual behavioral data analyzed were interpreted as a null result (failure to reject that the behavioral stochasticity hypothesis), rather than actual identification of model-misspecification. I expand on these primary concerns and raise several smaller points below.

      A primary question I have about this work is whether the method described would actually provide any advantage for real cognitive modeling problems beyond what is typically done to minimize the chance of model misspecification (in particular, post-predictive checking). The toy problem examined in the manuscript is pretty extreme (two of the three synthetic agents are very far from what a human would do on the task, and the models deviate from one another to a degree that detecting the difference should not be difficult for any method). The issue posed in the toy data would easily be identified by following good modeling practices, which include using posterior predictive checking over summary measures to identify model insufficiencies, which in turn would call for the need for a broader set of models (See Wilson & Collins 2019). Thus, I am left wondering whether this method could actually identify model misspecification in real world data, particularly in situations where standard posterior predictive checking would fall short. The conclusions from the main empirical data set rest largely on a null result, and the utility of a method for detecting model misspecification seems like it should depend on its ability to detect its presence, not just its absence, in real data.

      Beyond the question of its advantage above and beyond data- and hypothesis-informed methods for identifying model misspecification, I am also concerned that if the method does identify a model-insufficiency, then you still would need to use these other methods in order to understand what aspect of behavior deviated from model predictions in order to design a better model. In general, it seems that the authors should be clear that this is a tool that might be helpful in some situations, but that it will need to be used in combination with other well-described modeling techniques (posterior predictive checking for model validation and guiding cognitive model extensions to capture unexplained features of the data). A general stylistic concern I have with this manuscript is that it presents and characterizes a new tool to help with cognitive computational modeling, but it does not really adhere to best modeling practices (see Collins & Wilson, eLife), which involve looking at data to identify core behavioral features and simulating data from best-fitting models to confirm that these features are reproduced. One could take away from this paper that you would be better off fitting a neural network to your behavioral data rather than carefully comparing the predictions of your cognitive model to your actual data, but I think that would be a highly misleading takeaway since summary measures of behavior would just as easily have diagnosed the model misspecification in the toy problem, and have the added advantage that they provide information about which cognitive processes are missing in such cases.

      As a more minor point, it is also worth noting that this method could not distinguish behavioral stochasticity from the deterministic structure that is not repeated across training/test sets (for example, because a specific sequence is present in the training set but not the test set). This should be included in the discussion of method limitations. It was also not entirely clear to me whether the method could be applied to real behavioral data without extensive pretraining (on >500 participants) which would certainly limit its applicability for standard cases.

      The authors focus on model misspecification, but in reality, all of our models are misspecified to some degree since the true process-generating behavior almost certainly deviates from our simple models (ie. as George Box is frequently quoted, "all models are wrong, but some of them are useful"). It would be useful to have some more nuanced discussion of situations in which misspecification is and is not problematic.

    1. Reviewer #1 (Public Review):

      The authors present a model for multisensory correlation detection that is based on the neurobiologically plausible Hassenstein Reichardt detector. It modifies their previously reported model (Parise & Ernst, 2016) in two ways: a bandpass (rather than lowpass) filter is initially applied and the filtered signals are then squared. The study shows that this model can account for synchrony judgment, temporal order judgment, etc in two new data sets (acquired in this study) and a range of previous data sets.

      Strengths:<br /> 1. The model goes beyond descriptive models such as cumulative Gaussians for TOJ and differences in cumulative Gaussians for SJ tasks by providing a mechanism that builds on the neurobiologically plausible Hassenstein-Reichardt detector.<br /> 2. This modified model can account for results from two new experiments that focus on the detection of correlated transients and frequency doubling. The model also accounts for several behavioural results from experiments including stochastic sequences of A/V events and sinewave modulations.

      Additional thoughts:<br /> 1. The model introduces two changes: bandpass filtering and squaring of the inputs. The authors emphasize that these changes allow the model to focus selectively on transient rather than sustained channels. But shouldn't the two changes be introduced separately? Transients may also be detected for signed signals.

      2. Because the model is applied only to rather simple artificial signals, it remains unclear to what extent it can account for AV correlation detection for naturalistic signals. In particular, speech appears to rely on correlation detection of signed signals. Can this modified model account for SJ or TOJ judgments for naturalistic signals?

      Even Nidiffer et al. (2018) which is explicitly modelled by the authors report a significant difference in performance for correlated and anti-correlated signals. This seems to disagree with the results of study 1 which is reported in the current paper and the model's predictions. How can these contradicting results be explained? In case the brain performs correlation detection on signed and unsigned signals, is a more complex mechanism needed to arbitrate between those two mechanisms?

      3. The number of parameters seems quite comparable for the authors' model and descriptive models (e.g. PSF models). This is because time constants require refitting (at least for some experimental data sets) and the correlation values need to be passed through a response mode (i.e. probit function) to account for behavioural data. It remains unclear how the brain adjusts the time constants to different sensory signals.

      4. Fujisaki and Nishida (2005, 2006) proposed mechanisms for AV correlation detection based on the Hassenstein-Reichardt motion detector (though not formalized as a computational model).

    1. Reviewer #1 (Public Review):

      Summary:<br /> This paper identifies GABA cells in the preoptic hypothalamus which are involved in REM sleep rebound (the increase in REM sleep) after selective REM sleep deprivation. By calcium photometry, these cells are most active during REM, and show more claim signals during REM deprivation, suggesting they respond to "REM pressure". Inhibiting these cells ontogenetically diminishes REM sleep. The optogenetic and photometry work is carried out to a high standard, the paper is well-written, and the findings are interesting.

      Points that could be addressed or discussed:<br /> 1. The circuit mechanism for REM rebound is not defined. How do the authors see REM rebound as working from the POAGAD2 cells? Although the POAGAD2 does project to the TMN, the actual REM rebound could be mediated by a projection of these cells elsewhere. This could be discussed.

      2. The "POAGAD2 to TMN" name for these cells is somewhat confusing. The authors chose this name because they approach the POAGAD2 cells via retrograde AAV labelling (rAAV injected into the TMN). However, the name also seems to imply that neurons (perhaps histamine neurons) in the TMN are involved in the REM rebound, but there is no evidence in the paper that this is the case. Although it is nice to see from the photometry studies that the histamine cells are selectively more active (as expected) in NREM sleep (Fig. S2), I could not logically see how this was a relevant finding to REM rebound or the subject of the paper. There are many other types of cells in the TMN area, not just histamine cells, so are the authors suggesting that these non-histamine cells in the TMN could be involved?

      3. It is a puzzle why most of the neurons in the POA seem to have their highest activity in REM, as also found by Miracca et al 2022, yet presumably some of these cells are going to be involved in NREM sleep as well. Could the same POAGAD2-TMN cells identified by the authors also be involved in inducing NREM sleep-inhibiting histamine neurons (Chung et al). And some of these POA cells will also be involved in NREM sleep homeostasis (e.g. Ma et al Curr Biol)? Is NREM sleep rebound necessary before getting REM sleep rebound? Indeed, can these two things (NREM and REM sleep rebound) be separated?

      4. Is it possible to narrow down the POA area where the GAD2 cells are located more precisely?

      5. It would be ideal to further characterize these particular GAD2 cells by RT-PCR or RNA seq. Which other markers do they express?

    1. Reviewer #1 (Public Review):

      Summary:<br /> The study by Liff et al significantly advances our understanding of transgenerational olfactory changes resulting from fear conditioning, particularly in revealing elevated odor-encoding neurons in both conditioned mice (F0) and their progeny (F1). The authors attribute F0 increases to biased stem cell receptor selection, building upon the seminal work of Dias and Ressler (2014). While the dedication and use of novel histological techniques add strength to the study, there are notable weaknesses, including the need for clarification on discrepancies with previous findings, the decision to modify paradigms, and the presentation of behavioral data in supplementary materials.

      Overall, the manuscript has strong potential but would benefit from addressing these weaknesses and minor recommendations to enhance its quality and contribution to the field.

      Strengths:<br /> - Significant contribution to understanding transgenerational olfactory changes induced by fear conditioning.<br /> - Use of novel histological techniques and exploration of stem cell involvement adds depth to the study.

      Weaknesses:<br /> Discrepancies with previous findings need clarification, especially regarding the absence of similar behavioral effects in F1. Lack of discussion on the decision to modify paradigms instead of using the same model. Presentation of behavioral data in supplementary materials, with a recommendation to include behavioral quantification in main figures. Absence of quantification for freezing behavior, a crucial measure in fear conditioning.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors examined whether archerfish have the capacity for motor adaptation in response to airflow perturbations. Through two experiments, they demonstrated that archerfish could adapt. Moreover, when the fish flipped its body position with the perturbation remaining constant, it did not instantaneously counteract the error. Instead, the archerfish initially persisted in correcting for the original perturbation before eventually adapting, consistent with the notion that the archerfish's internal model has been adapted in egocentric coordinates.

      Evaluation:<br /> The results of both experiments were convincing, given the observable learning curve and the clear aftereffect. The ability of these fish to correct their errors is also remarkable. Nonetheless, certain aspects of the experiment's motivation and conclusions temper my enthusiasm.

      1. The authors motivated their experiments with two hypotheses, asking whether archerfish can adapt to light refractions using an innate look-up table as opposed to possessing a capacity to adapt. However, the present experiments are not designed to arbitrate between these ideas. That is, the current experiments do not rule out the look-up table hypothesis, which predicts, for example, that motor adaptation may not generalize to de novo situations with arbitrary action-outcome associations. Such look-up table operations may also show set-size effects, whereas other mechanisms might not. Whether their capacity to adapt is innate or learned was also not directly tested, as noted by the authors in the discussion. Could the authors clarify how they see their results positioned in light of the two hypotheses noted in the Introduction?

      2. The authors claim that archerfish use egocentric coordinates rather than allocentric coordinates. However, the current experiments do not make clear whether the archerfish are "aware" that their position was flipped (as the authors noted, no visual cues were provided). As such, for example, if the fish were "unaware" of the switch, can the authors still assert that generalization occurs in egocentric coordinates? Or simply that, when archerfish are ostensibly unaware of changes in body position, they continue with previously successful actions.

      3. The experiments offer an opportunity to examine whether archerfish demonstrate any savings from one session to another. Savings are often attributed to a faster look-up table operation. As such, if archerfish do not exhibit savings, it might indicate a scenario where they do not possess a refined look-up table and must rely on implicit mechanisms to relearn each time.

      4. The authors suggest that motor adaptation in response to wind may hint at mechanisms used to adapt to light refraction. However, how strong of a parallel can one draw between adapting to wind versus adapting to light refraction? This seems important given the claims in this paper regarding shared mechanisms between these processes. As a thought experiment, what would the authors predict if they provided a perturbation more akin to light refraction (e.g., a film that distorts light in a new direction, rather than airflow)?

      5. The number of fish excluded was greater than those included. This raises the question as to whether these fish are merely elite specimens or representative of the species in general.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Huang and Luo investigated whether regularities between stimulus features can be exploited to facilitate the encoding of each set of stimuli in visual working memory, improving performance. They recorded both behavioural and neural (EEG) data from human participants during a sequential delayed response task involving three items with two properties: location and colour. In the key condition ('aligned trajectory'), the distance between locations of successively presented stimuli was identical to their 'distance' in colour space, permitting a compression strategy of encoding only the location and colour of the first stimulus and the relative distance of the second and third stimulus (as opposed to remembering 3 locations and 3 colours, this would only require remembering 1 location, 1 colour, and 2 distances). Participants recalled the location and colour of each item after a delay.

      Consistent with the compression account, participants' location and colour recall errors were correlated and were overall lower compared to a non-compressible condition ('misaligned trajectory'). Multivariate analysis of the neural data permitted decoding of the locations and colours during encoding. Crucially, the relative distance could also be decoded - a necessary ingredient for the compression strategy.

      Strengths:<br /> The main strength of this study is a novel experimental design that elegantly demonstrates how we exploit stimulus structure to overcome working memory capacity limits. The behavioural results are robust and support the main hypothesis of compressed encoding across a number of analyses. The simple and well-controlled design is suited to neuroimaging studies and paves the way for investigating the neural basis of how environmental structure is detected and represented in memory. Prior studies on this topic have primarily studied behaviour only (e.g., Brady & Tenenbaum, 2013).

      Weaknesses:<br /> The main weakness of the study is that the EEG results do not make a clear case for compression or demonstrate its neural basis. If the main aim of this strategy is to improve memory maintenance, it seems that it should be employed during the encoding phase. From then on, the neural representation in memory should be in the compressed format. The only positive evidence for this occurs in the late encoding phase (the re-activation of decoding of the distance between items 1 and 2, Fig. 5A), but the link to behaviour seems fairly weak (p=0.068). Stronger evidence would be showing decoding of the compressed code during memory maintenance or recall, but this is not presented. On the contrary, during location recall (after the majority of memory maintenance is already over), colour decoding re-emerges, but in the un-compressed item-by-item code (Fig. 4B). The authors suggest that compression is consolidated at this point, but its utility at this late stage is not obvious.

      Impact:<br /> This important study elegantly demonstrates that the use of shared structure can improve capacity-limited visual working memory. The paradigm and approach explicitly link this field to recent findings on the role of replay in structure learning and will therefore be of interest to neuroscientists studying both topics.

    1. Reviewer #1 (Public Review):

      Padamsey et al. followed up on their previous study in which they found that male mice sacrifice visual cortex computation precision to save energy in periods of food restriction (Padamsey et al. 2021, Neuron). In the present study, the authors find that female mice show much lower levels of adaptation in response to food restriction on the level of metabolic signaling and visual cortex computation. This is an important finding for understanding sex differences in adaptation to food scarcity and also impacts the interpretation of studies employing food restriction in behavioral analyses and learning paradigms.

      The manuscript is, in general, very clear and the conclusions are straightforward. The main limitation, that the number of experiments is insufficient to compare the effects of food restriction in males and females directly, is discussed by the authors: to address this point they use Bayes factor analysis to provide an estimate of the likelihood that females and males indeed differ in terms of energy metabolism and sensory processing adaptions during food restriction.

      The following points are not entirely clear yet.<br /> 1. For a number of experiments the authors use their new data set on females and compare that with the data set previously published on males. In how far are these data sets comparable? Have they been performed originally in parallel for example using siblings of different sexes or have the experiments been conducted several years apart from each other? What is the expected variability, if one repeated these experiments with the same sex considering the differences/similarities between experimental setups, housing conditions, interindividual differences, etc.?

      2. Energy consumption and visual processing may differ between periods in which animals are in different behavioral states. Is there a possibility that male and female mice differed in behavioral state during measurements? Were animals running or resting during visual stimulation and during ATP measurements?

      3. Related to the previous point: the authors show that ATP consumption was reduced in male mice during visual stimulation. What about visual cortex ATP consumption in the absence of visual stimulation? Do food-deprived males and/or females show lower ATP consumption in the visual cortex e.g. during sleep?

    1. Reviewer #1 (Public Review):

      Summary:<br /> Zhang et al. provide valuable data for understanding molecular features of the human spinal cord. The authors made considerable efforts to acknowledge and objectively address the limitations of Visium while attempting to overcome them by utilizing single-nucleus RNA sequencing (snRNA-seq) from the same tissue. By mapping snRNA-seq clusters to Visium data, they offer spatial information, complemented by RNA-ISH and immunofluorescence (IF) validation. They also discuss gender-related differences and the similarities between human and mouse data, aiming to establish a crucial foundation for experimental research. However, I have some comments below.

      1. The observation of gender-related differences is interesting. The authors reported that SCN10A, associated with nociceptos, exhibited stronger expression in females. While they intend to validate this finding through IF, the quantitative difference is not clearly observed in the IF data (Figure 5f). It would be essential to provide validation through DAPI-based cell counts, demonstrating the difference in CHAT/SCNA10A co-expression.

      2. It is meritorious that in novel features of the transcriptomic study, the authors considered gender-related differences and similarities between humans and mice. Nevertheless, despite the extensive bioinformatics-based analyses performed, the results mostly confirm what has been previously reported (Nguyen et al. 2021; Yadav et al. 2023; Jung et al. 2023).

      3. The study did not perform snRNA-seq in the DRG. The limitations of Visium in cell type separation are acknowledged, and the authors are aware that Visium alone has limitations in describing cell expression patterns. The authors need to validate their findings via analyses of public DRG snRNA-seq data (Jung et al. 2023 Ncom; Nguyen et al. 2021eLife) before drawing broad conclusions.

      4. Figure 7's comparison between human Visium spot data and Renthal et al.'s mouse snRNA-seq may have limitations as Visium spot data could not provide a transcriptional profile at the single cell resolution. The authors need to clarify this point.

      5. Recent findings indicate that type 2 cytokines can directly stimulate sensory neurons. This includes the expression of IL-4RA, IL31RA, and IL13RA in DRG. These findings support the role of JAK kinase inhibitors in mediating chronic itch. Demonstrating the expression of these itch receptors in DRG would be valuable.

      6. Given that juxtacrine and paracrine signals operate from 0 to 200 um, spatial information is vital to understanding intercellular communication. The presentation of spatial information using Visium is meaningful, and more comprehensive analyses of potential interaction based on distance should be provided, beyond the top 10 interactions (Figure 8).

      7. The gender-related differences are interesting and, if possible, it would be interesting to explore whether age-related differences or degeneration-related factors exist. Using public data could allow the examination of age-related changes.

    1. Reviewer #1 (Public Review):

      Summary and strengths<br /> The authors tried to address why only a subset of genes are highlighted in many publications. Is it because these highlighted genes are more important than others? Or is it because there are non-genetic reasons? This is a critical question because in the effort to discover new genes for drug targets and clinical benefit, we need to expand a pool of genes for deep analyses. So I appreciate the authors' efforts in this study, as it is timely and important. They also provided a framework called FMUG (short for Find My Understudied Gene) to evaluate genes for a number of features for subsequent analyses.

      Weaknesses<br /> Many of the figures are hard to comprehend, and the figure legends do not sufficiently explain them.<br /> # For example, what was plotted in Fig 1b? The number of articles increased from results -> write-ups -> follow-ups in all four categories with different degrees. But it does not seem to match what the authors meant to deliver.<br /> # Fig 4 is also confusing. It appears that the genes were clustered by many features that the authors developed. But does it have any relationship with genes being under- or over-studied?

    1. deux jours ouvrables correspondantau délai accordé à l’élève pour présenter sa défense (art. R. 421-10-1 du code del’éducation) dans le cadre du respect du principe du contradictoire.
    1. Reviewer #1 (Public Review):

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

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

      Weaknesses:<br /> The proposed model is not directly supported by experimental data. Rather all alternative models are excluded as they do not fit the obtained data.

    1. Reviewer #1 (Public Review):

      This is an interesting manuscript that extends prior work from this group identifying that a chemovar of Cannabis induces apoptosis of T-ALL cells by preventing NOTCH1 cleavage. Here the authors isolate specific components of the chemovar responsible for this effect to CBD and CBDV. They identify the mechanism of action of these agents as occurring via the integrated stress response. Overall the work is well performed but there are two lingering questions that would be helpful to address as follows:

      -Exactly how CBD and CBDV result in the upregulation of the TRPV1/integrated stress response is unclear. What is the most proximal target of these agents that results in these changes?

      -Related to the above, all experiments to confirm the mechanism of action of CBD/CBDV rely on chemical agents, whose precise targets are not fully clear in some cases. Thus, some use of genetic means (such as by knockout of TRPV1, ATF4) to confirm the dependency of these pathways on drug response and NOTCH cleavage would be very helpful.

    1. Joint Public Review:

      Summary:

      The manuscript of Heydasch et al. addresses the spatiotemporal regulation of Rho GTPase signaling in living cells and its coupling to the mechanical state of the cell. They focus on a GAP of RhoA, the Rho-specific GAP Deleted in Liver Cancer 1 (DLC1). They first show that removing DLC1 either by a CRISPR KO or by downregulation using siRNA leads to increased contractility and globally elevated RhoA activity, as revealed by a FRET biosensor. This result was expected, since DLC1 is deactivating RhoA its absence should lead to increasing amounts of active RhoA. To go beyond global and steady levels of RhoA activity, the authors developed an acute optogenetic system to study transient RhoA activity dynamics in different genetic and subcellular contexts. In WT cells, they found that pulses of activation lead to an increased RhoA activity at focal adhesions (FA) compared to plasma membrane (PM), which suggests that FAs contain less RhoA GAPs, more RhoA, or that FAs involve positive feedback implying other GEFs for example. In DLC1 KO cells, they found that the RhoA response upon pulses of optogenetic activation was increased (higher peak) both at FA and PM, which could be expected since less GAP should increase the amount of active RhoA. But surprisingly, they observed a higher rate of RhoA deactivation in DLC1 KO cells, which is counterintuitive: less GAP should result in a slower rate of deactivation. Less GAP should also lead to a lower rate of observed RhoA activation (smaller koff) and delayed peak. From the data, it seems hard to conclude on these two expectations since the initial rates (slopes right after the activation) and times at peak appear similar in both WT and DLC1 KO cells. Further on, the authors study the dynamics of DLC1 on FAs depending on the mechanical state and nicely show a causal decrease of DLC1 enrichment at FA upon FA reinforcement, hereby probing a positive feedback where RhoA activation is further amplified as the force exerted at FA is increasing.

      Strengths:

      - Experiments are precise and well done.<br /> - Technically, the work brings original and interesting data. The use of transient optogenetic activation within focal adhesions together with a biosensor of activity is new and elegant.<br /> - The link between DLC1 and global contractility/RhoA activity is clear and convincing.<br /> - The surprisingly higher rate of RhoA deactivation in DLC1 KO cells is convincing, as well as the differences in the dynamics of RhoA between focal adhesions and plasma membrane.<br /> - The correlation between DLC1 enrichment and focal adhesion dynamics is very clear.

      Weaknesses:

      - There is no explanation for the higher rate of RhoA deactivation in DLC1 KO cells.<br /> - For the optogenetic experiments, it is not clear if we are looking at the actual RhoA dynamics of the activity or at the dynamics of the optogenetic tool itself.<br /> - There is no model to analyze transient RhoA responses, however, the quantitative nature of the data calls for it. Even a simple model with linear activation-deactivation kinetics fitted on the data would be of benefit for the conclusions on the observed rates and absolute amounts.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This study uses whole genome sequencing to characterise the population structure and genetic diversity of a collection of 58 isolates of E. coli associated with neonatal meningitis (NMEC) from seven countries, including 52 isolates that the authors sequenced themselves and a further 6 publicly available genome sequences. Additionally, the study used sequencing to investigate three case studies of apparent relapse. The data show that in all three cases, the relapse was caused by the same NMEC strain as the initial infection. In two cases they also found evidence for gut persistence of the NMEC strain, which may act as a reservoir for persistence and reinfection in neonates. This finding is of clinical importance as it suggests that decolonisation of the gut could be helpful in preventing relapse of meningitis in NMEC patients.

      Strengths:<br /> The study presents complete genome sequences for n=18 diverse isolates, which will serve as useful references for future studies of NMEC. The genomic analyses are high quality, the population genomic analyses are comprehensive and the case study investigations are convincing.

      Weaknesses:<br /> The NMEC collection described in the study includes isolates from just seven countries. The majority (n=51/58, 88%) are from high-income countries in Europe, Australia, or North America; the rest are from Cambodia (n=7, 12%). Therefore it is not clear how well the results reflect the global diversity of NMEC, nor the populations of NMEC affecting the most populous regions.

      The virulence factors section highlights several potentially interesting genes that are present at apparently high frequency in the NMEC genomes; however, without knowing their frequency in the broader E. coli population it is hard to know the significance of this.

    1. Joint Public Review:

      Summary:

      Cincotta et al set out to investigate the presence of glucocorticoid receptors in the male and female embryonic germline. They further investigate the impact of tissue specific genetically induced receptor absence and/or systemic receptor activation on fertility and RNA regulation. They are motivated by several lines of research that report inter and transgenerational effects of stress and or glucocorticoid receptor activation and suggest that their findings provide an explanatory mechanism to mechanistically back parental stress hormone exposure induced phenotypes in the offspring.

      Strengths:

      - A chronological immunofluorescent assessment of GR in fetal and early life oocyte and sperm development.<br /> - RNA seq data that reveal novel cell type specific isoforms validated by q-RT PCR E15.5 in the oocyte.<br /> - 2 alternative approaches to knock out GR to study transcriptional outcomes. Oocytes: systemic GR KO (E17.5) with low input 3-tag seq and germline specific GR KO (E15.5) on fetal oocyte expression via 10X single cell seq and 3-cap sequencing on sorted KO versus WT oocytes - both indicating little impact on polyadenylated RNAs -<br /> - 2 alternative approaches to assess the effect of GR activation in vivo (systemic) and ex vivo (ovary culture): here the RNA seq did show again some changes in germ cells and many in the soma.<br /> - They exclude oocyte specific GR signaling inhibition via beta isoforms<br /> - Perinatal male germline shows differential splicing regulation in response to systemic Dex administration, results were backed up with q-PCR analysis of splicing factors.

      Weaknesses:

      - Sequencing techniques used are not Total RNA but either are focused on all polyA transcripts (10x) - effects on non-polyA-transcripts are left unexplored.<br /> The number of replicates in the low input seq is very low and hence this might be underpowered. Since Dex treatment showed some (modest) changes in oocyte RNA effects of GR depletion might only become apparent upon Dex treatment as an interaction. Meaning GR activation in the presence of GR shows changes, upon GR depletion those changes are abolished --> statistically speaking an interaction --> conclusion: there are germline GR effects that get abolished when there is no GR hinting on germline GR autonomous effects.<br /> - Effects in oocytes following systemic Dex might be indirect due to GR activation in the soma. The changes observed might be irrelevant to meiosis and thus in the manuscript are deemed irrelevant, but they could still lead to settle consequences. in other terms.

      Even though ex vivo culture of ovaries shows GR translocation to nucleus it is not sure whether the in vivo systemic administration does the same. The authors argue in their rebuttal that GR is already nuclear in fetal oocytes hence the<br /> conclusion that fetal oocytes are resistant to GR manipulation is understandable, at least for the readouts that were considered. Yet the question arises: If GR is already nuclear (active) in the absence of additional Dex treatment why does GR knock out not elicit any changes in the considered readouts -> what are we missing.

      This work is a good reference point for researchers interested in glucocorticoid hormone signaling fertility and RNA splicing. It might spark further studies on germline-specific GR functions and the impact of GR activation on alternative splicing.<br /> The study provides a characterization of GR and some aspects of GR perturbation, and the negative findings in this study do help to rule out a range of specific roles of GR in the germline. This will help the study of unexplored options. The authors do acknowledge the unexplored options in their discussion.<br /> The intro of the study eludes to implications for intergenerational effects via epigenetic modifications in the germline and points out additional potential indirect effects of reproductive tissue GR signaling on the germline. Future studies might hence focus on further exploration of epigenetic modifications and/or indirect effects.

    1. Reviewer #1 (Public Review):

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

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

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

      The fact that there are Arid1a transcripts that escape the Cre system in the Arid1a KO mouse model might difficult the interpretation of the data. The phenotype of the Arid1a knockout is probably masked by the fact that many of the sequencing techniques used here are done on a heterogeneous population of knockout and wild type spermatocytes. In relation to this, I think that the use of the term "pachytene arrest" might be overstated, since this is not the phenotype truly observed. Knockout mice produce sperm, and probably litters, although a full description of the subfertility phenotype is lacking, along with identification of the stage at which cell death is happening by detection of apoptosis.<br /> It is clear from this work that ARID1a is part of the protein network that contribute to silencing of the sex chromosomes. However, it is challenging to understand the timing of the role of ARID1a in the context of the well-known DDR pathways that have been described for MSCI. Staining of chromosome spreads with Arid1a antibody showed localization at the sex chromosomes by diplonema, however, analysis of gene expression in Arid1a ko was performed on pachytene spermatocytes. Therefore, is not very clear how the chromatin remodeling activity of Arid1a in diplonema is affecting gene expression of a previous stage. CUTnRUN showed that ARID1a is present at the sex chromatin in earlier stages, leading to hypothesize that immunofluorescence with ARID1a antibody might not reflect ARID1a real localization.

    1. Reviewer #1 (Public Review):

      In the submitted manuscript, Port et al. investigated the host and viral factors influencing the airborne transmission of SARS-CoV-2 Alpha and Delta variants of concern (VOC) using a Syrian hamster model. The authors analyzed the viral load profiles of the animal respiratory tracts and air samples from cages by quantifying gRNA, sgRNA, and infectious virus titers. They also assessed the breathing patterns, exhaled aerosol aerodynamic profile, and size distribution of airborne particles after SARS-CoV-2 Alpha and Delta infections. The data showed that male sex was associated with increased viral replication and virus shedding in the air. The relationship between co-infection with VOCs and the exposure pattern/timeframe was also tested. This study appears to be an expansion of a previous report (Port et al., 2022, Nature Microbiology). The experimental designs were rigorous, and the data were solid. These results will contribute to the understanding of the roles of host and virus factors in the airborne transmission of SARS-CoV-2 VOCs.

    1. Reviewer #1 (Public Review):

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

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

      Weaknesses<br /> The authors have addressed my recommendations in the previous review round in a satisfactory way.

    1. This dangerous framing is compounded by a generally supine media owned or controlled by the 1%
      • for: 1% - media control
    2. This 1% of humanity uses its awesome power to manipulate societal aspirations and the narratives around climate change.
      • for: quote - Kevin Anderson, quote - 1% manipulation

      • quote

        • This 1% of humanity uses its awesome power to manipulate
          • societal aspirations and
          • the narratives around climate change.
        • These extend from
          • well-funded advertising to
          • pseudo-technical solutions,
          • the financialisation of carbon emissions (and increasingly, nature) to
          • labelling extreme any meaningful narrative that questions inequality and power.
    1. Reviewer #1 (Public Review):

      Summary:

      This study by He, Liu, and He et al. investigated the fundamental role of microglia in modulating general anesthesia. While microglia have been previously shown to regulate neuronal network activity, their role in the induction of (i.e., LORR) and emergence from (i.e., RORR) anesthesia has only recently been explored. Recently published work by Cao et al. reported that microglia modulate general anesthesia via P2Y12 receptor. The present study largely reproduces those findings and does so using an impressive array of techniques and clever approaches. Following the serendipitous discovery that microglia-depleted mice exhibit increased LORR and decreased RORR, the authors go on to demonstrate that microglia regulate neuronal activity in a region-specific manner during anesthesia via purinergic receptor-mediated calcium signaling. The manuscript is well written and the data are convincing, elegantly validated using several different methods and controls, and largely complete. Nevertheless, this Reviewer has a few minor comments and suggestions to further strengthen the manuscript.

      Strengths:

      Impressive number of genetic mouse models, techniques, controls, and methods of validation.

      Weaknesses:

      Some of the novelty of these findings may be reduced based on the recent publication of a similar study.

    1. Reviewer #1 (Public Review):

      Summary:

      Given knowledge of the amino acid sequence and of some version of the 3D structure of two monomers that are expected to form a complex, the authors investigate whether it is possible to accurately predict which residues will be in contact in the 3D structure of the expected complex. To this effect, they train a deep learning model that takes as inputs the geometric structures of the individual monomers, per-residue features (PSSMs) extracted from MSAs for each monomer, and rich representations of the amino acid sequences computed with the pre-trained protein language models ESM-1b, MSA Transformer, and ESM-IF. Predicting inter-protein contacts in complexes is an important problem. Multimer variants of AlphaFold, such as AlphaFold-Multimer, are the current state of the art for full protein complex structure prediction, and if the three-dimensional structure of a complex can be accurately predicted then the inter-protein contacts can also be accurately determined. By contrast, the method presented here seeks state-of-the-art performance among models that have been trained end-to-end for inter-protein contact prediction.

      Strengths:

      The paper is carefully written and the method is very well detailed. The model works both for homodimers and heterodimers. The ablation studies convincingly demonstrate that the chosen model architecture is appropriate for the task. Various comparisons suggest that PLMGraph-Inter performs substantially better, given the same input than DeepHomo, GLINTER, CDPred, DeepHomo2, and DRN-1D2D_Inter. As a byproduct of the analysis, a potentially useful heuristic criterion for acceptable contact prediction quality is found by the authors: namely, to have at least 50% precision in the prediction of the top 50 contacts.

      Weaknesses:

      My biggest issue with this work is the evaluations made using *bound* monomer structures as inputs, coming from the very complexes to be predicted. Conformational changes in protein-protein association are the key element of the binding mechanism and are challenging to predict. While the GLINTER paper (Xie & Xu, 2022) is guilty of the same sin, the authors of CDPred (Guo et al., 2022) correctly only report test results obtained using predicted unbound tertiary structures as inputs to their model. Test results using experimental monomer structures in bound states can hide important limitations in the model, and thus say very little about the realistic use cases in which only the unbound structures (experimental or predicted) are available. I therefore strongly suggest reducing the importance given to the results obtained using bound structures and emphasizing instead those obtained using predicted monomer structures as inputs.

      In particular, the most relevant comparison with AlphaFold-Multimer (AFM) is given in Figure S2, *not* Figure 6. Unfortunately, it substantially shrinks the proportion of structures for which AFM fails while PLMGraph-Inter performs decently. Still, it would be interesting to investigate why this occurs. One possibility would be that the predicted monomer structures are of bad quality there, and PLMGraph-Inter may be able to rely on a signal from its language model features instead. Finally, AFM multimer confidence values ("iptm + ptm") should be provided, especially in the cases in which AFM struggles.

      Besides, in cases where *any* experimental structures - bound or unbound - are available and given to PLMGraph-Inter as inputs, they should also be provided to AlphaFold-Multimer (AFM) as templates. Withholding these from AFM only makes the comparison artificially unfair. Hence, a new test should be run using AFM templates, and a new version of Figure 6 should be produced. Additionally, AFM's mean precision, at least for top-50 contact prediction, should be reported so it can be compared with PLMGraph-Inter's.

      It's a shame that many of the structures used in the comparison with AFM are actually in the AFM v2 training set. If there are any outside the AFM v2 training set and, ideally, not sequence- or structure-homologous to anything in the AFM v2 training set, they should be discussed and reported on separately. In addition, why not test on structures from the "Benchmark 2" or "Recent-PDB-Multimers" datasets used in the AFM paper?

      It is also worth noting that the AFM v2 weights have now been outdated for a while, and better v3 weights now exist, with a training cutoff of 2021-09-30.

      Another weakness in the evaluation framework: because PLMGraph-Inter uses structural inputs, it is not sufficient to make its test set non-redundant in sequence to its training set. It must also be non-redundant in structure. The Benchmark 2 dataset mentioned above is an example of a test set constructed by removing structures with homologous templates in the AF2 training set. Something similar should be done here.

      Finally, the performance of DRN-1D2D for top-50 precision reported in Table 1 suggests to me that, in an ablation study, language model features alone would yield better performance than geometric features alone. So, I am puzzled why model "a" in the ablation is a "geometry-only" model and not a "LM-only" one.

    1. Reviewer #1 (Public Review):

      Summary:<br /> This paper uses a high-throughput assay of transcription levels to (i) assess the potential of large numbers of Escherichia coli genomic sequences to function as promoters, and (ii) identify regulatory sequences in some of those promoters. This is a substantial undertaking, and while much of the work supports principles of transcription and transcription regulation described by many prior studies, there is considerable value in assessing promoters on such a large scale. The identification of putative regulatory sequences in larger numbers of promoters will likely be valuable to other groups studying transcription regulation in E. coli. And the analysis of antisense promoters provides some interesting new insight that goes beyond previous anecdotal studies.

      Strengths:<br /> - The presentation of the work is very clear, and the conclusions are mostly well supported by the data.<br /> - The assays are rigorously controlled and analyzed.<br /> - Conclusions regarding the impact of antisense transcription on sense transcript levels provide new insight. While these data are consistent with previous anecdotal studies, to my knowledge this is the first large-scale analysis supporting a negative regulatory role for antisense transcription.<br /> - The putative regulatory elements mapped in the high-throughput mutagenesis experiments will be a valuable resource for the scientific community.

      Weaknesses:<br /> (all minor)<br /> - There are some parts where the authors could clarify their arguments.<br /> - I'm not convinced that intragenic promoters impact codon usage rather than the other way around.<br /> - The authors should present a more nuanced discussion of promoters that avoids making yes/no calls (i.e., characterize sequences by promoter strength rather than a binary yes/no call of being a promoter).<br /> - Data relating to intragenic promoters should be presented and discussed for sense and antisense promoters separately.

    1. Reviewer #1 (Public Review):

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

      The revised manuscript addressed most of my questions except my concern about Fig. S9. This figure is about a theory that a chromatin region can become open due to interaction with other regions, and the author propose a mathematic model to compute such effects. I was concerned about the errors in the model of Fig. S9a, and I was also concerned about the lack of evidence or validation. In their responses, the authors admitted that they cannot provide biological evidence or validations but still chose to keep the figure and the text.

      The revised Fig. S9a now uses a symmetric genome interaction matrix as I suggested. But Figure S9a still have a lot of problems. Firstly, the diagonal of the matrix in Fig. S9a still has many 0's, which I asked in my previous comments without an answer. The legend mentioned that the contacts were defined as 2, 0 or -2 but the revised Fig. S9a only shows 1,0, or -1 values. Furthermore, Fig. S9b,9c,9d all added a panel of CTCF+/- but there is no explanation in text or figure legend about these newly added panels. Given many unaddressed problems, I would still suggest deleting this figure.

      In my opinion, this paper does not need Fig. S9 to support its major story. The model in this figure is independent of SCA-seq. I think it should be spinoff as an independent paper if the authors can provide more convincing analysis or experiments. I understand eLife lets authors to decide what to include in their paper. If the authors insist to include Fig. S9, I strongly suggest they should at least provide adequate explanation about all the figure panels. At this point, the Fig. S9 is not solid and clearly have many errors. The readers should ignore this part.

    1. Reviewer #1 Public Review

      Anobile and colleagues present a manuscript detailing an account of numerosity processing with an appeal to a two-channel model. Specifically, the authors propose that the perception of numerosity relies on (at least) two distinct channels for small and large numerosities, which should be evident in subject reports of perceived numerosity. To do this, the authors had subjects reproduce visual dot arrays of numerosities ranging from 8 to 32 dots, by having subjects repetitively press a response key at a pre-instructed rate (fast or slow) until the number of presses equaled the number of perceived dots. The subjects performed the task remarkably well, yet with a general bias to overestimate the number of presented dots. Further, no difference was observed in the precision of responses across numerosities, providing evidence for a scalar system. No differences between fast and slow tapping were observed. For behavioral analysis, the authors examined correlations between the Weber fractions for all presented numerosities. Here, it was found that the precision at each numerosity was similar to that at neighboring numerosities, but less similar to more distant ones. The authors then went on to conduct PCA and clustering analyses on the weber fractions, finding that the first two components exhibited an interaction with the presented numerosity, such that each was dominant at distinct lower and upper ranges and further well-fit by a log-Gaussian model consistent with the channel explanation proposed at the beginning.

      Overall, the authors provide compelling evidence for a two-channel system supporting numerosity processing that is instantiated in sensorimotor processes. A strength of the presented work is the principled approach the authors took to identify mechanisms, as well as the controls put in place to ensure adequate data for analysis. Some questions do remain in the data, and there are aspects of the presentation that could be adjusted.

      -The use of a binary colormap for the correlation matrix seems unnecessary. Binary colormaps between two opposing colors (with white in the middle) are best for results spanning positive and negative values (say, correlation values between -1 and +1), but the correlations here are all positive, so a uniform colormap should be applied. I can appreciate that the authors were trying to emphasize that a 2+ channel system would lead to lower correlations at larger ratios, but that's emphasized better in the numerical ratio line plots.

      -In Figure 1, the correlation matrices in Figure 1 appear blurred out. I am not sure if this was intentional but suspect it was not, and so they should appear like those presented in Figure 3.

      -It's notable that the authors also collected data on a timing task to rule out a duration-based strategy in the numerosity task. If possible, it would be great to have the author also conduct the rest of the analyses on the duration task as well; that is, to look at WF correlation matrices/ratios as well as PCA. There is evidence that duration processing is also distinctly sensorimotor, and may also rely on similar channels. Evidence either for or against this would likely be of great interest.

      -For the duration task, there was no fast tapping condition. Why not? Was this to keep the overall task length short?

      -The number of subjects/trials seems a bit odd. Why did some subjects perform both and not others? The targets say they were presented "between 25 and 30 times", but why was this variable at all?

      -For the PCA analysis, my read of the methods and results is that this was done on all the data, across subjects. If the data were run on individual subjects and the resulting PCA components averaged, would the same results be found?

      -For the data presented in Figure 2, it would be helpful to also see individual subject data underlaid on the plots to get a sense of individual differences. For the reproduced number, these will likely be clustered together given how small the error bars are, but for the WF data it may show how consistently "flat" the data are. Indeed, in other magnitude reproduction tasks, it is not uncommon to see the WF decrease as a function of target magnitude (or even increase). It may be possible that the reason for the observed findings is that some subjects get more variable (higher WFs) with larger target numbers and others get less variable (lower WFs).

      -Regarding the two-channel model, I wonder how much the results would translate to different ranges of numerosities? For example, are the two channels supported here specific to these ranges of low and high numbers, or would there be a re-mapping to a higher range (say, 32 to 64 dots) or to a narrower range (say 16 to 32 dots). It would be helpful to know if there is any evidence for this kind of remapping.

    1. Reviewer #1 (Public Review):

      The study presents an extensive computational approach to identify the motor neuron input from the characteristics of single motor neuron discharge patterns during a ramp up/down contraction. This reverse engineering approach is relevant due to limitations in our ability to estimate this input experimentally. Using well-established models of single motor neurons, a (very) large number of simulations were performed that allowed identification of this relation. In this way, the results enable researchers to measure motor neuron behavior and from those results determine the underlying neural input scheme. Overall, the results are very convincing and represent an important step forward in understanding the neural strategies for controlling movement.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this study, Basha and colleagues aim to test whether the thalamic nucleus reuniens can facilitate the hippocampus/prefrontal cortex coupling during sleep. Considering the importance of sleep in memory consolidation, this study is important to understand the functional interaction between these three majorly involved regions. This work suggests that the thalamic nucleus reuniens has a functional role in synchronizing the hippocampus and prefrontal cortex.

      Strengths:<br /> The authors performed recordings in naturally sleeping cats, and analysed the correlation between the main slow wave sleep oscillatory hallmarks: slow waves, spindles, and hippocampal ripples, and with reuniens' neurons firing. They also associated intracellular recordings to assess the reuniens-prefrontal connectivity, and computational models of large networks in which they determined that the coupling of oscillations is modulated by the strength of hippocampal-thalamic connections.

      Weaknesses:<br /> The authors' main claim is made on slow waves and spindle coupling, which are recorded both in the prefrontal cortex and surprisingly in reuniens. Known to be generated in the cortex by cortico-thalamic mechanisms, the slow waves and spindles recorded in reuniens show no evidence of local generation in the reuniens, which is not anatomically equipped to generate such activities. Until shown differently, these oscillations recorded in reuniens are most likely volume-conducted from nearby cortices. Therefore, such a caveat is a major obstacle to analysing their correlation (in time or frequency domains) with oscillations in other regions.

      Finally, the choice of the animal model (cats) is the best suited one, as too few data, particularly anatomical ones regarding reuniens connectivity, are available to support functional results.

    1. Reviewer #1 (Public Review):

      Summary: By elevating Ca influx and inducing PTP, the authors have maximised the release probability. In this condition, the release probability is nearly one. Under such a condition, the release site can release another vesicle in a short time. By analyzing mean, variance and covariance, the authors propose a release model that each release site contains a docking site and a replacement site. They excluded the LS-TS model (Neher and Brose) based on discrepancy between model and the data (mean and covariance).

      Strengths: The authors have used a minimal stimulation and modelling nicely to look into stochastic nature of release sites with good resolution. This cannot be done at other synapses. Overall conclusions are reasonable and convincing.

      Weaknesses: The interpretation is somewhat model-dependent, and it is unclear if the interpretation is unique. For example, it is unclear if the heterogeneous release probability among sites, silent sites, can explain the results. However, the authors discuss these potential caveats in a fair manner and argue that their model is very likely to be the best so far.

    1. Reviewer #1 (Public Review):

      Activity has effects on the development of neural circuitry during almost any step of neuronal differentiation. In particular during specific time periods of circuit development, so called critical periods (CP), altered neural activity can induce permanent changes of neuronal and network excitability. In complex neural networks it is often difficult to pinpoint the specific network components that are permanently altered by activity, and it often remains unclear how activity is integrated during the CP to set mature network excitability. This study combines electrophysiology with pharmacological and optogenetic manipulation in the Drosophila genetic model system to pinpoint the neural substrate that is influenced by altered activity during a critical period (CP) of larval locomotor circuit development. Moreover, it is then tested whether and how different manipulations of synaptic input are integrated during the CP to tune network excitability.

      Strengths: Based on previous work, during the CP network activity is increased by feeding the GABA-AR antagonist PTX. This results in permanent network activity changes as highly convincingly assayed by a prolonged recovery period following induced seizure and by altered intersegmental locomotor network coordination. This is then used to provide two important findings: First, compelling electro- and optophysiological as well as anatomical experiments track the site of network change down to the level of single neurons and pre- versus postsynaptic specializations. In short, increased activity during the CP increases both, the magnitude of excitatory and inhibitory synaptic transmission to the aCC motoneuron, but excitation is affected more strongly. This results in altered excitation inhibition ratios. Fine electrophysiology shows that excitatory synapse strengthening occurs postsynaptically. High quality anatomy shows that dendrite size and numbers of synaptic contacts remain unaltered. It is a major accomplishment to track the tuning of network excitability during the CP down to the physiology of specific synapses at identified neurons.<br /> Second, additional experiments with single neuron resolution demonstrate that during the CP different forms of activity manipulation are integrated so that opposing manipulations can rescue altered setpoints. This provides novel insight into how developing neural network excitability is tuned, and it indicates that during the CP training can rescue the effects of hyperactivity.

      Weaknesses: There are no major weaknesses to the findings presented, but the molecular cause that underlies increased motoneuron postsynaptic responsiveness as well as the mechanism that integrates different forms of activity during the CP remain unknown. However, the discussion addresses this point adequately.

    1. Reviewer #1 (Public Review):

      Summary:<br /> Peterson et al., present a series of experiments in which the Pavlovian performance (i.e. time spent at a food cup/port) of male and female rats is assessed in various tasks in which context/cue/outcome relationships are altered. The authors find no sex differences in context-irrelevant tasks and no such differences in tasks in which the context signals that different cues will earn different outcomes. They do find sex differences, however, when a single outcome is given and context cues must be used to ascertain which cue will be rewarded with that outcome (Ctx-dep O1 task). Specifically, they found that males acquired the task faster, but that once acquired, the performance of the task was more resilient in female rats against exposure to a stressor. Finally, they show that these sex differences are reflected in differential rates of c-fos expression in all three subregions of rat OFC, medial, lateral, and ventral, in the sense that it is higher in females than males, and only in the animals subject to the Ctx-dep O1 task in which sex differences were observed.

      Strengths:<br /> • Well-written.<br /> • Experiments elegantly designed.<br /> • Robust statistics.<br /> • Behaviour is the main feature of this manuscript, rather than any flashy techniques or fashionable lab methodologies, and luckily the behaviour is done really well.<br /> • For the most part I think the conclusions were well supported, although I do have some slightly different interpretations to the authors in places.

      Weaknesses:<br /> 1. With regards to the claim (page 4 of pdf), I think I can see what the authors are getting at when they claim "Only Ctx-dep.01 engages context-gated reward predictions", because the same reward is available in each context, and the animal must use contextual information to determine which cue will be rewarded. In other words, it has a discriminative purpose. In Ctx-dep.O1/O2, however, although the context doesn't serve a discriminative purpose in the sense that one cue will always earn a unique outcome, regardless of context, the fact that these cues are differentially rewarded in the different context means that animals may well form context-gated cue-outcome associations (e.g. CtxA-(CS1-O1), CtxnoA-(CS2-O2)). Moreover, the context is informative in this group in telling the animal which cue will be rewarded, even prior to outcome delivery, such that I don't think contextual information will fade to the background of the association and attention be lost to it in the way, say Mackintosh (1975) might predict. Therefore, I don't think this statement is correct.

      2. I think the results shown in Figure 1 are very interesting, and well supported by the statistics. It's so nice to see a significant interaction, as so many papers try to report these types of effects without it. However, I do wonder how specific the results are to contextual modulation. That is, should a discriminative discrete cue be used instead of each context (e.g. CS1 indicates CS2 earns O1, CS3 indicates CS4 earns O1), would female rats still be as slow to learn the discrimination?

      3. Pages 8-9 of pdf, where the biological basis or the delayed acquisition of contextual control in females is considered, I find this to be written from a place of assuming that what is observed in the males is the default behaviour. That is, although the estrous cycle and its effects on synaptic plasticity/physiology may well account for the results, is there not a similar argument to be made for androgens in males? Perhaps the androgens also somehow alter synaptic plasticity/physiology, leading to their faster speed, reduced performance stability, and increased susceptibility to stress.

      4. In addition, the OFC - which is the brain region found to have differential expression of c-fos in males and females in Figure 5 - is not explicitly discussed with regard to the biological mechanisms of differences, which seems odd.

    1. Reviewer #1 (Public Review):

      The authors presented a new MNase-based proximity ligation method called MChIP-C, allowing for the measurement of protein-mediated chromatin interactions at single-nucleosome resolution on a genome-wide scale. With improved resolution and sensitivity, they explored the spatial connectivity of active promoters and identified the potential candidates for establishing/maintaining E-P interactions. Finally, with published CRISPRi screens, they found that most functionally verified enhancers do physically interact with their cognate promoters, supporting the enhancer-promoter looping model.

      The study's experimental approach and findings are interesting. However, several issues need to be addressed.

      1. The authors described that "the lack of interaction between experimentally-validated enhancers and their cognate promoters in some studies employing C-methods has raised doubts regarding the classical promoter-enhancer looping model", so it's intriguing to see whether the MChIP-C could indeed detect the E-P interactions which were not identified by C-methods as they mentioned (Benabdallah et al., 2019; Gupta et al., 2017). I agree that they identified more E-P interactions using MChIP-C, but specifically, they should show at least 2-3 cases. It's important since this is the main conclusion the authors want to draw.

      2. The authors compared their data to those of Chen et al. (Chen et al., 2022), who used PLAC-seq with anti-H3K4me3 antibodies in K562 cells and standard Micro-C data previously reported for K562, concluding that "MChIP-C achieves superior sensitivity and resolution compared to C-methods based on standard restriction enzymes.". This is not convincing since they only compared their data to one dataset. More datasets from other cell lines should be included.

      3. The reasons for choosing Chen's data (Chen et al., 2022) and CRISPRi screens (Fulco et al., 2019; Gasperini et al., 2019) should be provided since there are so many out there.

      4. The authors identify EP300 histone acetyltransferase and the SWI/SNF remodeling complex as potential candidates for establishing and/or maintaining enhancer-promoter interactions, but not RNA polymerase II, mediator complex, YY1, and BRD4. More explanation is needed for this point since they're previously suggested to be associated with E-P interactions.

      5. The limitations of the method should be discussed.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The manuscript considers a mechanistic extension of MacArthur's consumer-resource model to include chasing down food and potential encounters between the chasers (consumers) that lead to less efficient feeding in the form of negative feedback. After developing the model, a deterministic solution and two forms of stochastic solutions are presented, in agreement with each other. Finally, the model is applied to explain observed coexistence and rank-abundance data.

      Strengths:<br /> - The application of the theory to natural rank-abundance curves is impressive.<br /> - The comparison with the experiments that reject the competitive exclusion principle is promising. It would be fascinating to see if in, e.g. insects, the specific interference dynamics could be observed and quantified and whether they would agree with the model.<br /> - The results are clearly presented; the methods adequately described; the supplement is rich with details.<br /> - There is much scope to build upon this expansion of the theory of consumer-resource models. This work can open up new avenues of research.

      Weaknesses:<br /> - I am questioning the use of carrying capacity (Eq. 4) instead of using nutrient limitation directly through Monod consumption (e.g. Posfai et al. who the authors cite). I am curious to see how these results hold or are changed when Monod consumption is used.

      - Following on the previous comment, I am confused by the fact that the nutrient consumption term in Eq. 1 and how growth is modeled (Eq. 4) are not obviously compatible and would be hard to match directly to experimentally accessible quantities such as yield (nutrient to biomass conversion ratio). Ultimately, there is a conservation of mass ("flux balance"), and therefore the dynamics must obey it. I don't quite see how conservation of mass is imposed in this work.

      - These models could be better constrained by more data, in principle, thereby potential exists for a more compelling case of the relevance of this interference mechanism to natural systems.

      - The underlying frameworks, B-D and MacArthur are not properly exposed in the introduction, and as a result, it is not obvious what is the specific contribution in this work as opposed to existing literature. One needs to dig into the literature a bit for that. The specific contribution exists, but it might be more clearly separated and better explained. In the process, the introduction could be expanded a bit to make the paper more accessible, by reviewing key features from the literature that are used in this manuscript.

    1. Joint Public Review:

      This paper explores how minimal active matter simulations can model tissue rheology, with applications to the in vivo situation of zebrafish morphogenesis. The authors explore the idea of active noise, particle softness and size heterogeneity cooperating to give rise to surprising features of experimental tissue rheologies (in particular an increase and then a plateau in viscosity with fluid fraction). In general, the paper is interesting from a theoretical standpoint, by providing a bridge between concepts from jamming of particulate systems and experiments in developmental biology. The idea of exploring a free space picture in this context is also interesting. It will be interesting in the future to see whether and how the findings change when considering 3D tissues with less size heterogeneity or how viscosity is impacted by the time scale of measurements.

    1. Reviewer #1 (Public Review):

      Gazula and co-workers presented in this paper a software tool for 3D structural analysis of human brains, using slabs of fixed or fresh brains. This tool will be included in Freesurfer, a well-known neuroimaging processing software. It is possible to reconstruct a 3D surface from photographs of coronal sliced brains, optionally using a surface scan as a model. A high-resolution segmentation of 11 brain regions is produced, independent of the thickness of the slices, interpolating information when needed. Using this method, the researcher can use the sliced brain to segment all regions, without the need for ex vivo MRI scanning.

      The software suite is freely available and includes 3 modules. The first accomplishes preprocessing steps, for correction of pixel sizes and perspective. The second module is a registration algorithm that registers a 3D surface scan obtained prior to sectioning (reference) to the multiple 2D slices. It is not mandatory to scan the surface - a probabilistic atlas can also be used as a reference - however, the accuracy is lower. The third module uses machine learning to perform the segmentation of 11 brain structures in the 3D reconstructed volume. This module is robust, dealing with different illumination conditions, cameras, lenses, and camera settings. This algorithm ("Photo-SynthSeg") produces isotropic smooth reconstructions, even in high anisotropic datasets (when the in-plane resolution of the photograph is much higher than the thickness), interpolating the information between slices.

      To verify the accuracy and reliability of the toolbox, the authors reconstructed 3 datasets, using real and synthetic data. Real data of 21 postmortem confirmed Alzheimer's disease cases from the Massachusetts Alzheimer's Disease Research Center (MADRC) and 24 cases from the AD Research at the University of Washington (who were MRI scanned prior to processing) were employed for testing. These cases represent a challenging real-world scenario. Additionally, 500 subjects of the Human Connectome project were used for testing error as a continuous function of slice thickness. The segmentations were performed with the proposed deep-learning new algorithm ("Photo-SynthSeg") and compared against MRI segmentations performed to "SAMSEG" (an MRI segmentation algorithm, computing Dice scores for the segmentations. The methods are sound and statistically showed correlations above 0.8, which is good enough to allow volumetric analysis. The main strengths of the methods are the datasets used (real-world challenging and synthetic) and the statistical treatment, which showed that the pipeline is robust and can facilitate volumetric analysis derived from brain sections and conclude which factors can influence the accuracy of the method (such as using or not 3D scan and using constant thickness).

      Although very robust and capable of handling several situations, the researcher has to keep in mind that processing has to follow some basic rules in order for this pipeline to work properly. For instance, fiducials and scales need to be included in the photograph, and the slabs must be photographed against a contrasting background. Also, only coronal slices can be used, which can be limiting for certain situations.

      The authors achieved their aims, and the statistical analysis confirms that the machine learning algorithm performs segmentations comparable to the state-of-the-art of automated MRI segmentations.

      Those methods will be particularly interesting to researchers who deal with post-mortem tissue analysis and do not have access to ex vivo MRI. Quantitative measurements of specific brain areas can be performed in different pathologies and even in the normal aging process. The method is highly reproducible, and cost-effective since it allows the pipeline to be applied by any researcher with small pre-processing steps.

      The paper is very interesting and well structured, adding an important tool for fixed and fresh brain analysis. The software tool is robust and demonstrated good and consistent results in the hard task of managing automated segmentation from brain slices. In the future, segmentation of the histological slices could be developed and histological structures added (such as small brainstem nuclei, for instance). Also, dealing with axial and sagittal planes can be useful to some labs.

    1. Reviewer #1 (Public Review):

      Gumaste et al studied if a parameter of odor plumes, the intermittency can be detected by an animal species, such as mice that heavily rely on olfaction to navigate and search for food and mates, among other behaviors. They also ask if the animals can extract information from this to gain knowledge about the odor source. Intermittency is defined as the fraction of time an odorant is present at a sampled point within the odor plume space. Their findings could be summarized as follows: they found that animals are capable of detecting differences in intermittency levels and suggest that this parameter of odor plumes is important for odor-based navigation in mammals, as it has been seen in other animals such as flying insects. The authors used a combination of behavioral training while concomitantly performing calcium imaging of olfactory receptor neurons (input to the olfactory bulb) and also mitral cells (output of the olfactory bulb). They found that mice are able to behaviorally discriminate between odor plumes of high and low intermittency. Interestingly, they found that the response of both input and output neurons of the olfactory bulb is capable to encode the intermittency experienced by the animals. The methods utilized in this work are very well suited for the kind of questions that the authors are asking. The combination of behavior and imaging, as opposed to only anesthetized imaging gives the authors a lot of power to interpret their data. A very relevant point is the generation of the olfactory stimuli that will be used to test the animals. The authors go to great lengths to generate more naturalistic odorant stimulations, as opposed to the typically used square pulses. Although there are some issues that can be addressed, the authors succeeded in answering the questions they set at the beginning of this work, and their conclusions are supported by their experiments. This work would generate interest among a relatively broad audience because the issue presented here (how the temporal structure of the odor plume affects the detection and encoding of an odorant) is novel in mice olfactory research.

    1. Reviewer #1 (Public Review):

      With MERGEseq, the authors sought to develop a scalable and accessible method for getting both projectome and transcriptome information at the single-cell level from multiple projection targets within a single animal. MERGEseq uses a retro rAAV2 to deliver a 15-nucleotide barcode driven by a CAG promoter with co-expression of eGFP to enrich barcoded cells using FACS. Injection of this rAAV2 in distinct regions (with each injection region distinguished by a unique barcode that is specific to the virus used) allows retrograde trafficking and expression of the barcodes in cells that project to the injected region. In this manuscript, rAAVs harboring 5 unique barcodes were stereotactically delivered to 5 targets of the mouse: dorsomedial striatum (DMS), mediodorsal thalamic nucleus (MD), basal amygdala (BLA), lateral hypothalamus (LH), and agranular insular cortex (AI). After a 6-week period to allow for viral transduction and expression, the ventromedial prefrontal cortex (vmPFC) was harvested for scRNAseq. vmPFC scRNAseq data were validated against previously published PFC datasets, demonstrating that MERGEseq does not disrupt transcript expression and identifies the same principal cell types as annotated in previous studies. Importantly, MERGEseq enabled the identification of cell types in the vmPFC that project to distinct areas, with separation occurring largely based on cell type and cortical layer. The application of stringent criteria for barcode index determination is rigorous and improves confidence that barcoded cells are correctly identified. The observation that all barcoded cells were excitatory is consistent with prior work, although it is not clear if viral tropism contributes to this in some way. In a parallel experiment, FAC-sorted cells (vmPFC cells expressing EGFP) were isolated as a comparison. Notably, EGFP+ cells were exclusively excitatory neurons, consistent with literature showing PFC projection neurons are excitatory. Next, barcode analysis was combined with transcriptional identification of neuronal subtypes to define general projection patterns and single-cell projection patterns, which were validated by the DMS and MD in situ using retrograde tracing in combination with RNA FISH. MERGEseq data were also used to identify transcriptional differences between neurons with dedicated and bifurcated projections. DMS+LH and DMS+MD projecting neurons had distinct transcriptional profiles, unlike cells with other targets. RNA FISH for marker gene Pou3f and retrograde tracing from DMS+LH projecting cells demonstrate enrichment of this gene in this projection population. Finally, machine-learning was used to predict projection targets based on transcriptional profiles. In this dataset, 50 highly variable genes (HVGs) were optimal for predicting projection patterns, though this might vary in different circuits. Overall, the results of this manuscript are well presented and include rigorous validation for select vmPFC targets with in situ techniques. The application of unique barcodes for retro-AAV delivery is an accessible tool that other labs can implement to study other brain circuits.

      Ultimately, MERGEseq is a subtle conceptual advancement over VECTORseq (retro-AAV delivered transgenes rather than barcodes, in combination with scRNAseq) that offers higher confidence in the described projectome diversity in comparison. The use of a retrograde AAV inherently limits the number of projection areas that can be assessed, a weakness compared to anterograde approaches such as MAPseq/BARseq. However, BARseq demands more time and resources; further, the use of the highly toxic Sindbis virus limits the application of this technique. This manuscript builds upon previous work by utilizing machine learning to predict projection targets. BARseq2 could be used to rigorously validate predicted projectomes and gain single-cell information regarding target neurons. Overall, MERGEseq is an accessible technique that can be used across many animal models and serve as an important starting point to define circuits at the single-cell level.

    1. Reviewer #1 (Public Review):

      This study characterized the role of the Drosophila odorant-binding protein Obp56g in mediating post-mating responses in females. The authors show that this Obp56g is expressed in the male ejaculatory bulb, use genetic approaches to disrupt Obp56g, and show that males with disrupted Obp56g fail to form mating plugs in their mates.

      Despite the fact that Obp56g deficient males generate and transfer sperm normally, the lack of formation of a functional mating plug leads to sperm loss in females mated to these males and thus a failure to induce normal post-mating responses.

      This study identifies an unexpected role for an Obp and raises new questions about the function of this class of protein and the variety of roles that they may play in sensory function and reproduction.

    1. Reviewer #1 (Public Review):

      In this paper, the authors develop new models of sequential effects in a simple Bernoulli learning task. In particular, the authors show evidence for both a "precision-cost" model (precise posteriors are costly) and an "unpredictability-cost" model (expectations of unpredictable outcomes are costly). Detailed analyses of experimental data partially support the model predictions.

      Strengths:<br /> - Well-written and clear.<br /> - Addresses a long-standing empirical puzzle.<br /> - Rigorous modeling.

      Weaknesses:<br /> - No model adequately explains all of the data.<br /> - New empirical dataset is somewhat incremental.<br /> - Aspects of the modeling appear weakly motivated (particularly the unpredictability model).<br /> - Missing discussion of some relevant literature.

    1. Reviewer #1 (Public Review)

      This work challenges previously published results regarding the presence and abundance of 6mA in Drosophila genome, as well as the claim that the TET or DMAD enzyme serves as the "eraser" of this DNA methylation mark and its roles in development. This information is needed to clarify these questions in the field. Generally speaking, the methods for fly husbandry and treatment seem to be in accordance with those established ones in the field.

      Here are a couple of suggestions that could be discussed with the current work and addressed in the future, in order to better understand the roles of 6mA and TET.

      1. Regarding the estimated "200 to 400 methylated adenines per haplogenome", some insights regarding where they are enriched in the genome could inform the potential target sites regulated by 6mA.

      2. The TET-GFP and TET-CD-GFP knock-in lines give proper nuclear localization and could be used to identify genomic regions bound with full-length TET and TET-CD using anti-GFP for ChIP-seq or CUT&RUN (or CUT&TAG).

    1. Reviewer #1 (Public Review):

      Summary:

      Using chromaffin cells as powerful model systems for studying secretion, the authors study the regulatory role of complexin in secretion. Complexin is still enigmatic in its regulatory role, as it both provides inhibitory and facilitatory functions in release. The authors perform an extensive structure-function analysis of both the C- and N-terminal regions of complexin. There are several interesting findings that significantly advance our understanding of cpx/SNARe interactions in regulating release. C-terminal amphipathic helix interferes with SNARE complex assembly and thus clamps fusion. There are acidic residues in the C-term that may be seen as putative interaction partners for Synaptotagmin. The N-terminus of Complexin promoting role may be associated with an interaction with Syt1. In particular, the putative interaction with Syt1 is of high interest and supported by quite strong functional and biochemical evidence. The experimental approaches are state-of-the-art, and the results are of the highest quality and convincing throughout. They are adequately and intelligently discussed in the rich context of the standing literature. Whilst there are some concerns about whether the facilitatory actions of complexion have to be tightly linked to Syt1 interactions, the proposed model will significantly advance the field by providing new directions in future research.

      I have only minor comments related to the interpretation of the data:

      Fig 5 While the data very nicely show that CPX and Syt1 have interdependent interactions in the chromaffin neurons, this seems to be not the case in neurons, where the loss of complexins and synaptotagmins have additive effects, suggesting independent mechanisms (eg Xue et al., 2010). This would be a good opportunity to discuss some possible differences between secretion in endocrine cells vs neurons.

      Fig 8 Shows an apparent shift in Ca sensitivity in N-terminal mutants suggesting a modification of Ca sensitivity of Syt1. Could there be also an alternative mechanism, that explains this phenotype which is based on a role of the n-term lowering the energy barrier for fusion, that in turn shifts corresponding fusion rates to take place at lower Ca saturation levels?

    1. Reviewer #1 (Public Review):

      Summary:<br /> Yang et al combine high-speed video tracking of the limbs of freely moving mice with in vivo electrophysiology to demonstrate how striatal neurons encode single-limb gait. They also examine encoding other well-known aspects of locomotion, such as movement velocity and the initiation/termination of movement. The authors show that striatal neurons exhibit rhythmic firing phase-locked with mouse gait, while mice engage in spontaneous locomotion in an open field arena. Moreover, they describe gait deficits induced by severe unilateral dopamine neuron degeneration and associate these deficits with a relative strengthening of gait-modulation in the firing of D2-expressing MSNs. Although the source and function of this gait-modulation remain unclear, this manuscript uncovers an important physiological correlate of striatal activity with gait, which may have implications for gait deficits in Parkinson's Disease.

      Strengths:<br /> While some previous work has looked at the encoding of gait variables in the striatum and other basal ganglia nuclei, this paper uses more careful quantification of gait with video tracking. In addition, few if any papers do this in combination with optically-labeled recordings as were performed here.

      Weaknesses:<br /> The data collected has a great richness at the physiological and behavioral levels, and this is not fully described or explored in the manuscript. Additional analysis and display of data would greatly expand the interest and interpretability of the findings.

      There are also some caveats to the interpretation of the analyses presented here, including how to compare encoding of gait variables when animals have markedly different behaviors (eg comparing sham and unilaterally 6-OHDA treated mice), or how to interpret the loss of gait modulation when single unit activity is overall very low.

      1. The authors use circular analysis to quantify the degree to which striatal neurons are phase-locked to individual limbs during gait. The result of this analysis is shown as the proportion of units phase-locked to each limb, vector length, and vector angle (Fig 2H-K; Fig 4E-F; Fig 6E-F). Given that gait is a cyclic oscillation of the trajectories of all four limbs, one could expect that if one unit is phase-locked to one limb, it will also be phase-locked to the other three limbs but at a different phase. Therefore, it is not clear in the manuscript how the authors determine to which limb each unit is locked, and how some units are locked to more than one limb (Fig 2H). More methodological/analytical detail would be especially helpful.

      2. In Figures 2 and 3, the authors describe the modulation of striatal neurons by gait, velocity, and movement transitions (start/end), with most of their examples showing firing rates compatible with rates typical of striatal interneurons, not MSNs. In order to have a complete picture of the relationship between striatal activity and gait, a cell type-specific analysis should be performed. This could be achieved by classifying units into putative MSN, FS interneurons, and TANs using a spike waveform-based unit classification, as has been done in other papers using striatal single-unit electrophysiology. An example of each cell type's modulation with gait, as well as summary data on the % modulation, would be especially helpful.

      3. By normalizing limb trajectories to the nose-tail axis, the analysis ignores whether the mouse is walking straight, or making left/right turns. Is the gait-modulation of striatal activity shaped by ipsi- and contralateral turning? This would be especially important to understand changes in the unilateral disease model, given the imbalance in turning of 6-OHDA mice.

      4. It looks like the data presented in Figure 4 D-F comes from all opto-identified D1- and D2-MSNs. How many of these are gait-modulated? This information is missing (line 110). Pooling all units may dilute differences specific to gait-modulated units, therefore a similar analysis only on gait-modulated units should be performed.

      5. Since 6-OHDA lesions are on the right hemisphere, we would expect left limbs to be more affected than right limbs (although right limbs may also compensate). It is therefore surprising that RF and RR strides seem slightly shorter than LF and LR (Fig 5G), and no differences in other stride parameters (Fig 5H-J). Could the authors comment on that? It may be that this is due to rotational behavior. One interesting analysis would be to compare activity during similar movements in healthy and 6-OHDA mice, eg epochs in which mice are turning right (which should be present in both groups) or walking a few steps straight ahead (which are probably also present in both groups).

      6. Multiple publications have shown that firing rates of D1-MSN and D2-MSN are dramatically changed after dopamine neuron loss. Is it possible that changes observed in gait-modulation might be biased by changes in firing rates? For example, dMSNs have exceptionally low overall activity levels after dopamine depletion (eg Parker...Schnitzer, 2018; Ryan...Nelson, 2018; Maltese...Tritsch, 2021); this might reduce the ability to detect modulation in the firing of dMSNs as compared to iMSNs, which have similar or increased levels of activity in dopamine depleted mice. Does vector length correlate with firing rate? In addition, the normalization method used (dividing firing rate by minimum) may amplify very small changes in absolute rates, given that the firing rates for MSN are very low. The authors could show absolute values or Z-score firing rates (Figure 6 A, D).

      7. The analysis shown in Fig 3C should also be done for opto-identified D1- and D2-MSNs (and for waveform-based classified units as noted above).

      8. Discussion: the origin of the gait-modulation as well as the possible mechanisms driving the alterations observed in 6-OHDA mice should be discussed in more detail.

    1. Reviewer #1 (Public Review):

      The brain's code is not static. Neuronal activity patterns change as a result of learning, aging, and disease. Reliable tracking of activity from individual neurons across long time periods would enable detailed studies of these important dynamics. For this reason, the authors' efforts to track electrophysiological activity across days without relying on matching neural receptive fields (which can change due to learning, aging, and disease) are very important.

      By utilizing the tightly-spaced electrodes on Neuropixels probes, they are able to measure the physical distance and the waveform shape 'distance' between sorted units recorded on different days. To tune the matching algorithm and validate the results, they used the visual receptive fields of neurons in the mouse visual cortex (which tend to change little over time) as ground truth. Their approach performs quite well, with a high proportion of neurons accurately matched across multiple weeks. This suggests that the method may be useable in other cases where the receptive fields can't be used as ground truth to validate the tracking. This potential extendibility to tougher applications is where this approach holds the most promise.

      The main caveat (and disappointment) is that this paper does not address generalizability to other experimental conditions. Because it only looks at one brain area (visual cortex), in one species (mouse), using one type of spike sorter (Kilosort), and one type of behavioral prep (head-fixed), it is not clear if this approach is overfit to those conditions or if it will perform equally well in other conditions. Most importantly, in brain areas where neuronal receptive fields are more dynamic and can't be used as a ground truth diagnostic, it isn't clear how to apply the technique outlined in this study, since many of the parameters are tuned to a very specific set of conditions using visual receptive fields as ground truth.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The authors have nicely demonstrated the efficiency of the HCR v.3.0 using hr38 mRNA expression as a marker of neuronal activity. This is very important in the Drosophila neuroscience field as in situ hybridization in adult Drosophila brains has been so far very challenging to do and replicate. However, this method has been described before [Choi et al., (2018)] and, if I understand correctly, is now the property of the non-profit organization molecular Technologies, who are the ones responsible for designing the probes (the sequences are not provided). Here the authors present their work as a description of a new method, called HI-FISH. However, I do not consider this as a new method but rather an application, a "proof of principle" that HCR v.3.0 can be done even on challenging tissues such as the adult Drosophila brain. Hence, if HCR v3.0 is sensitive enough and powerful enough to be used as a marker of neuronal activity, we can use it, for other neurobiological purposes, using other gene probes.<br /> To demonstrate the efficiency of HI-FISH, the authors have addressed two biological questions. The first one addressed whether specific groups of neurons, known to trigger specific behaviours (here courtship and/or aggression) are indeed activated by the behavioural context they can promote. In other words: is the behavioural output of these neurons also a trigger for their activation? The second question addressed whether this method is powerful enough to distinguish two subgroups of a class of neurons called P1 known to be involved in the two behaviours considered. In other words, are the same P1 neurons that promote aggression and courtship?

      Strengths: The demonstration of the efficiency of the method is very convincing and well-performed. It gives the will for the reader to apply the method to their own subject.

      Weakness: The pictures provided for HI-FISH and catFISH do not corroborate with the quantification and therefore I am not convinced about the author's biological interpretation of their data. See below for details.

      Previously, using a split-gal4 line to restrict the Gal4 expression to a subset of P1 neurons, the authors have shown that these particular neurons when activated can trigger both aggressivity and courtship behaviour [Hoopfer et al., 2015]. The P1 neurons are composed of about 20 FruM neurons/hemibrain but are part of a bigger group that comprises about the same number of Fru- neurons that seem to be exclusively aggression-promoting neurons [Koganezawa et al., 2016]. Hence, this group of 40 neurons (pC1 neurons) contains aggressive-promoting neurons, courtship-promoting neurons, and perhaps neurons that can do both. Therefore, to address the first question, the authors compared hr38 expression in different groups of neurons, with a focus on subgroups, under different social contexts. While there is no ambiguity concerning the function of the Tk neurons as being exclusively aggressive-promoting neurons [Asahina et al., 2014], it is less clear when we look at the pC1 neurons. This is particularly evident for the P1a neurons which have been shown to be ambiguous as they can promote both aggression and courtship. For example, while optogenetic activation of these neurons promotes hr38 expression (Fig. 3D and fig sup. 4), it is less clear in the pictures to determine whether these specific P1a neurons labeled by the split-gal4 line are specifically activated by an aggressive behavioural context or a courtship behavioural context (Fig1, supp. 2 and fig. 4). Furthermore, the pictures chosen do not reflect the reality of the quantification (Fig. 2 B-D compared to sup. 2 or fig. 4C compared to fig. 4D) and therefore the authors conclusion. Because the drivers used are only expressed by a small subset of a larger population, I believe it would be more informative to separate in the quantification between the Gal4-expressing neurons and the non-expressing ones. Notably, based on the pictures provided, it looks like more P1 neurons (or rather pC1 neurons) are activated by a male-male encounter than by a male-female encounter. On the other hand, the splitGal4+ P1a seem to be more responsive to a courtship behavioural context (2/6 P1a neurons express hr38 in a courtship behavioural context while 0/9 _if we mentally abstract the increase of the background signal compared to the control picture_ seem to express hr38 in an aggression behavioural context). Hence, while activation of this P1asplit-Gal4 can promote both aggressive behaviour and courtship behaviour [Hoopfer et al., 2015], the authors didn't provide clear evidence (pictures not corroborating the quantification) that these specific small subpopulation of neurons are activated by one or the other or both behavioural conditions. Therefore my suggestion of differentiating in the quantification between the Gal4+ neurons from the others in the same local area.

      Fig. 3, suppl. 3: In this section the authors addressed the question of whether the HI-FISH can be used to identify the downstream targets of this subpopulation. As positive controls of known downstream targets, the authors looked at the pCd population which they recently published as being an indirect downstream target of the P1a neurons [Jung et al., Neuron 2020]. They identified the Kenyon cells and a group of dopaminergic neurons, the PAM neurons as being activated by the P1a neurons. To confirm the increase of hr38 expression is indeed the result of a neuronal response of these neurons to the P1a activation, the authors used a different strategy used by them and others before. Using Gcamp signal to monitor the neuronal response of the presumably downstream targets the authors activated the P1a neurons using optogenetic (chrimson). It is important to note that they have previously shown that depending on the frequency of the light pulses activation of the P1a neurons can trigger only aggression, both aggression and wing extension or only wing extension [Hoopfer et al., eLife 2015]. Here the authors use 50Hz which is a frequency that leads to wing extension during the stimulation and aggressive behaviour at the offset of the stimulus [Hoopfer et al., eLife 2015]. Interestingly, the Gcamp experiment shows activation of the Kenyon cells and the PAM neurons but this activity is not maintained when the stimulus is turned off, suggesting that these neurons are activated during a courtship context rather than an aggressive behavioural context. I think it would be nice to see in which behavioural context the Kenyon cells and PAM neurons are activated (hr38 expression in the different behavioural context using the corresponding Gal4).<br /> Fig.4 and supp.4: The demonstration that the catFISH can now be done in Drosophila brain with a new in situ method was nicely performed. Notably, the intronic Hr38 probe appears to be an excellent marker for recent neuronal activation. However, while the optogenetic activation of the P1a neurons used to quantify the time lapse for both probes nicely distinguishes between nuclear and cytoplasmic exonic hr38, it is very difficult to use the localization of this probe in the experimental setup the authors used. Also, With their setup, I would simply use the frequency of intronic hr38 as a marker of recent activation correlating or not with the frequency of exonic hr38 marker (present in both conditions first and second encounter). This is important as this experiment addresses the second biological question. Once again, the pictures chosen absolutely do not corroborate the quantification. For example, the picture of the double encounter with the same gender male-male context clearly shows a higher number of cells that are hr38INT positive (and therefore nuclear) than the picture of the female-female context (Fig. 4C), and thus even if we only considered the P1asplit-Gal4 positive cells. In the male-male picture, 5/6 P1a cells have the Hr38INT marker while the presence of this marker is debatable in the female-female context. Especially, in some of the cells these magenta dots appear to be localized in the cytoplasm, suggesting a non-specific signal. Therefore, I would suggest to quantify the percentage of Hr38INT positive cells as the only marker for recent activation and the relative level of Hr38EXN immunostaining, and this among the P1asplit-Gal4 positive cells and the gal4- ones. A high Hr38EXN level associated with the presence of hr38INT would indicate that the cell has been activated during both encounters, while a lower hr38EXN with no hr38INT would suggest only an activation during the 1st behavioural context. Finally, a lower hr38EXN associated with the presence of hr38INT would suggest the opposite, an activation only during the 2nd behaviour.<br /> Overall, by only looking at the pictures provided, I would conclude that the HCR applied with the hr38 probes seems to efficiently work and is usable to address the question of whether a specific group of neurons are indeed activated by a specific social behavioural context. However, I would also conclude that this technique nicely demonstrated that flies are not robots and that even in a "simple" organism model such as Drosophila melanogaster individual variability is present among a group of neurons. Hence, only the quantification of the gal4-expressing neurons in comparison with their neighbor neurons known to belong to the same functional group, would allow a conclusion toward a specificity of contextual response. Therefore, although activation of a small group of neurons can be enough to trigger a specific behaviour that shouldn't happen under a certain environmental context [Hoopfer et al., eLife 2015], the results presented here suggest that we should, using this method, considering the response of the neighbour cells of the Gal4+ ones. Although currently, the quantification of the author's data does not allow such analysis, to strengthen the author's argumentation, I would distinguish in their quantification between gal4+ from the others (Fig. 2 and 4). Furthermore, I am not certain that the distinction between cytoplasmic and nuclear hr38EXN is 100% feasible (based on the pictures provided). I would instead for the hr38EXN marker only use the relative intensity (Fig. 4D).

    1. Reviewer #1 (Public Review):

      Bischoff et al present a carefully prepared study on a very interesting and relevant topic: the role of ion channels (here a Ca2+-activated K+ channel BK) in regulating mitochondrial metabolism in breast cancer cells. The potential impact of these and similar observations made in other tumor entities has only begun to be appreciated. That being said, the authors pursue in my view an innovative approach to understanding breast cancer cell metabolism.

      Considering the following points would further strengthen the manuscript:

      Methods:

      1. The authors use an extracellular Ca2+ concentration (2 mM) in their Ringer's solutions that is almost twice as high as the physiologically free Ca2+ concentration (ln 473). Moreover, the free Ca2+ concentration of their pipette solution is not indicated (ln 487).

      2. Ca2+I measurements: The authors use ATP to elicit intracellular Ca2+ signals. Is this then a physiological stimulus for Ca2+ signaling in breast cancer? What is the rationale for using ATP? Moreover, it would be nice to see calibrated baseline values of Ca2+i.

      3. Membrane potential measurements: It would be nice to see a calibration of the potential measurements; this would allow us to correlate the IV relationship with membrane potential. Without calibration, it is hard to compare unless the identical uptake of the dye is shown.

      Does paxilline or IbTx also induce depolarization?

      4. Mito-potential measurements: Why did the authors use such a long time course and preincubate cells with channel blockers overnight? Why did they not perform paired experiments and record the immediate effect of the BK channel blockers in the mito potential?

      5. MTT assays are also based on mitochondrial function - since modulation of mito function is at the core of this manuscript, an alternative method should be used.

      Results:

      1. Fig. 5G: The number of BK "positive" mitoplasts is surprisingly low - how does this affect the interpretation? Did the authors attempt to record mitoBK current in the "whole-mitoplast" mode? How does the mitoBK current density compare with that of the plasma membrane? Is it possible to theoretically predict the number of mitoBK channels per mitochondrion to elicit the observed effects? Can these results be correlated with the immuno-localization of mitoBK channels?

      2. There are also reports about other mitoK channels (e.g. Kv1.3, KCa3.1, KATP) playing an important role in mitochondrial function. Did the authors observe them, too? Can the authors speculate on the relative importance of the different channels? Is it known whether they are expressed organ-/tumor-specifically?

    1. Reviewer #1 (Public Review):

      Summary:

      In this study, the authors showed that activation of RelA and Stat3 in hepatocytes of DSS-treated mice induced CYPs and thereby produced primary bile acids, particularly CDCA, which exacerbated intestinal inflammation.

      Strengths:

      This study reveals the RelA/Stat3-dependent gene program in the liver influences intestinal homeostasis.

      Weaknesses:

      Additional evidence will strengthen the conclusion.

      1. In Fig. 1C, photos show that phosphorylation of RelA and Stat3 was induced in only a few hepatocytes. The authors conclude that activation of both RelA and Stat3 induces inflammatory pathways. Therefore, the authors should show that phosphorylation of RelA and Stat3 is induced in the same hepatocytes during DSS treatment.

      2. In Fig. 5, the authors treated mice with CDCA intraperitoneally. In this experiment, the concentration of CDCA in the colon of CDCA-treated mice should be shown.

    1. Reviewer #1 (Public Review):

      Summary:

      Ravichandran et al investigate the regulatory panels that determine the polarization state of macrophages. They identify regulatory factors involved in M1 and M2 polarization states by using their network analysis pipeline. They demonstrate that a set of three regulatory factors (RFs) i.e., CEBPB, NFE2L2, and BCL3 can change macrophage polarization from the M1 state to the M2 state. They also show that siRNA-mediated knockdown of those 3-RF in THP1-derived M0 cells, in the presence of M1 stimulant increases the expression of M2 markers and showed decreased bactericidal effect. This study provides an elegant computational framework to explore the macrophage heterogeneity upon different external stimuli and adds an interesting approach to understanding the dynamics of macrophage phenotypes after pathogen challenge.

      Strengths:

      This study identified new regulatory factors involved in M1 to M2 macrophage polarization. The authors used their own network analysis pipeline to analyze the available datasets. The authors showed 13 different clusters of macrophages that encounter different external stimuli, which is interesting and could be translationally relevant as in physiological conditions after pathogen challenge, the body shows dynamic changes in different cytokines/chemokines that could lead to different polarization states of macrophages. The authors validated their primary computational findings with in vitro assays by knocking down the three regulatory factors-NCB.

      Weaknesses:

      One weakness of the paper is the insufficient analysis performed on all the clusters. They used macrophages treated with 28 distinct stimuli, which included a very interesting combination of pro- and anti-inflammatory cytokines/factors that can be very important in the context of in vivo pathogen challenge, but they did not characterize the full spectrum of clusters. Although they mentioned that their identified regulatory panels could determine the precise polarization state, they restricted their analysis to only the two well-established macrophage polarization states, M1 and M2. Analyzing the other states beyond M1 and M2 could substantially advance the field. They mentioned the regulatory factors involved in individual clusters but did not study the potential pathway involving the target genes of these regulatory factors, which can show the importance of different macrophage polarization states. Importantly, these findings were not validated in primary cells or using in vivo models.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this paper, the authors provide a characterisation of auditory responses (tones, noise, and amplitude-modulated sounds) and bimodal (somatosensory-auditory) responses and interactions in the higher-order lateral cortex (LC) of the inferior colliculus (IC) and compare these characteristics with the higher order dorsal cortex (DC) of the IC - in awake and anaesthetised mice. Dan Llano's group has previously identified gaba'ergic patches (modules) in the LC distinctly receiving inputs from somatosensory structures, surrounded by matrix regions receiving inputs from the auditory cortex. They here use 2P calcium imaging combined with an implanted prism to - for the first time - get functional optical access to these subregions (modules and matrix) in the lateral cortex of IC in vivo, in order to also characterise the functional difference in these subparts of LC. They find that both DC and LC of both awake and anaesthetised mice appear to be more responsive to more complex sounds (amplitude-modulated noise) compared to pure tones and that under anesthesia the matrix of LC is more modulated by specific frequency and temporal content compared to the gabaergic modules in LC. However, while both LC and DC appear to have low-frequency preferences, this preference for low frequencies is more pronounced in DC. Furthermore, in both awake and anesthetized mice, somatosensory inputs are capable of driving responses on their own in the modules of LC, but very little (possibly not at all) in the matrix. However, bimodal interactions may be different under awake and anesthesia in LC, which warrants deeper investigation by the authors: They find, under anesthesia, more bimodal enhancement in modules of LC compared to the matrix of LC and bimodal suppression dominating the matrix of LC. In contrast, under awake conditions bimodal enhancement is almost exclusively found in the matrix of LC, and bimodal suppression dominates both matrix and modules of LC.

      The paper provides new information about how subregions with different inputs and neurochemical profiles in the higher-order auditory midbrain process auditory and multisensory information, and is useful for the auditory and multisensory circuits neuroscience community.

      Strengths:<br /> The major strength of this study is undoubtedly the fact that the authors for the first time provide optical access to a subcortical region (the lateral cortex of the inferior colliculus (i.e. higher order auditory midbrain)) which we know (from previous work by the same group) have optically identifiable subdivisions with unique inputs and neurotransmitter release, and plays a central role in auditory and multisensory processing. A description of basic auditory and multisensory properties of this structure is therefore very useful for understanding auditory processing and multisensory interactions in subcortical circuits.

      Weaknesses:<br /> I have divided my comments about weaknesses and improvements into major and minor comments. All of which I believe are addressable by the reviewers to provide a more clear picture of their characterisation of the higher-order auditory midbrain.

      Major comment:<br /> 1. The differences between multisensory interactions in LC in anaesthetised and awake preparations appear to be qualitatively different, though the authors claim they are similar (see also minor comment related to figure 10H for further explanation of what I mean). However, the findings in awake and anaesthetised conditions are summarised differently, and plotting of similar findings in the awake figures and anaesthetised figures are different - and different statistics are used for the same comparisons. This makes it very difficult to assess how multisensory integration in LC is different under awake and anaesthetised conditions. I suggest that the authors plot (and test with similar statistics) the summary plots in Figure 8 (i.e. Figure 8H-K) for awake data in Figure 10, and also make similar plots to Figures 10G-H for anaesthetised data. This will help the readers understand the differences between bimodal stimulation effects on awake and anaesthetised preparations - which in its current form, looks very distinct. In general, it is unclear to me why the awake data related to Figures 9 and 10 is presented in a different way for similar comparisons. Please streamline the presentation of results for anaesthetised and awake results to aid the comparison of results in different states, and explicitly state and discuss differences under awake and anaesthetised conditions.

      2. The claim about the degree of tonotopy in LC and DC should be aided by summary statistics to understand the degree to which tonotopy is actually present. For example, the authors could demonstrate that it is not possible/or is possible to predict above chance a cell's BF based on the group of other cells in the area. This will help understand to what degree the tonotopy is topographic vs salt and pepper. Also, it would be good to know if the gaba'ergic modules have a higher propensity of particular BFs or tonotopic structure compared to matrix regions in LC, and also if general tuning properties (e.g. tuning width) are different from the matrix cells and the ones in DC.

      3. Throughout the paper more information needs to be given about the number of cells, sessions, and animals used in each panel, and what level was used as n in the statistical tests. For example, in Figure 4 I can't tell if the 4 mice shown for LC imaging are the only 4 mice imaged, and used in the Figure 4E summary or if these are just examples. In general, throughout the paper, it is currently not possible to assess how many cells, sessions, and animals the data shown comes from.

      4. Throughout the paper, to better understand the summary maps and plots, it would be helpful to see example responses of the different components investigated. For example, given that module cells appear to have more auditory offset responses, it would be helpful to see what the bimodal, sound-only, and somatosensory responses look like in example cells in LC modules. This also goes for just general examples of what the responses to auditory and somatosensory inputs look like in DC vs LC. In general example plots of what the responses actually look like are needed to better understand what is being summarised.

    1. Joint Public Review:

      This study sought to characterize the influence of acute stress on prosocial behavior, combining an effort-based task with neuroimaging, neuroendocrinological measures, and computational cognitive modeling. Two major results are reported: 1) Compared to controls, participants who experienced acute stress were less willing to exert effort for others, with more prominent effects for those who were more selfish; 2) More stressed participants exhibited an increase in activation in the dorsal anterior cingulate cortex and anterior insula, which are implicated in self-benefiting behavior. The approach is sophisticated and the findings are informative. Concerns regarding potential confounds and data reporting were addressed in a revised submission.

    1. Reviewer #1 (Public Review):

      This paper studies the effects of tACS on detection of silence gaps in an FM modulated noise stimulus. Both FM modulation of the sound and the tACS are at 2Hz, and the phase of the two is varied to determine possible interactions between the auditory and electric stimulation. Additionally, two different electrode montages are used to determine if variation in electric field distribution across the brain may be related to the effects of tACS on behavioral performance in individual subjects.

      Major strengths and weaknesses of the methods and results.

      The study appears to be well powered to detect modulation of behavioral performance with N=42 subjects. There is a clear and reproducible modulation of behavioral effects with the phase of the FM sound modulation. The study was also well designed and executed in terms of fMRI, current flow modeling, montage optimization targeting, and behavioral analysis. A particular merit of this study is to have repeated the sessions for most subjects in order to test repeat-reliability, which is so often missing in human experiments. The results and methods are generally well described and well conceived. The portion of the analysis related to behavior alone is excellent. The analysis of the tACS results are also generally well described, candidly highlighting how variable results are across subjects and sessions. The figures are all of high quality and clear. One weakness of the experimental design is that no effort was made to control for sensation effects. tACS at 2Hz causes prominent skin sensations which could have interacted with auditory perception and thus, detection performance.

      The central claim is that tACS modulates behavioral detection performance across the 0.5s  cycle of stimulation. Statistical analysis with randomize relative phase (between audio and tACS) show that detection performance is modulated by tACS. Neither the relative phase or the strength of this effect reproduces across subjects or sessions, which makes the interpretation of these results difficult. These result could be of interest to investigators in the field of tACS.

      The claim that the variation in the strength of the effect can be explained by variation of electric fields is not compelling.

      The following are more detailed comments to specific sections of the paper, including details on the concerns with the statistical analysis of the tACS effects.<br /> The introduction is well balanced, discussing the promise and limitations of previous results with tACS. The objectives are well defined.

      The analysis surrounding behavioral performance and its dependence on phase of the FM modulation (Figure 3) is masterfully executed and explained. It appears that it reproduces previous studies and points to a very robust behavioral task that may be of use in other studies.

      The definition of tACS(+) vs tACS(-) phase is adjusted to each subject/session, which seems unconventional.  For argument sake, let's assume the curves in Fig. 3E are random fluctuations. Then aligning them to best-fitting cosine will trivially generate a FM-amplitude fluctuation with cosine shape as shown in Fig. 4a. Selecting the positive and negative phase of that will trivially be larger and smaller than sham, respectively, as shown in Fig 4b.

      "Data from the optimal tACS lag and its opposite lag (corresponding trough) were excluded to avoid any artificial bias in estimating tACS effects induced by the alignment procedure (33)." The delay was found by fitting a cosine, so removing just the peaks of that cosine does little to avoid this problem.

      To demonstrate that this is not a trivial result of the definition, the analysis compares this to the same analysis but with a randomize alignment to the two stimuli (audio and tACS) in Figure 4d. Assuming this shuffle was done correctly, this shows that the modulation observed in 4b is not just a result of the analysis procedure.

      The authors are to be commended for analyzing the robustness of their observation across subjects and across sessions in Fig. 5. The lack of consistency in the optimal time delay between the two stimuli is hard to reconcile with the common theory that tACS entrains brain function.

      "To better understand what factors might be influencing inter-session variability in tACS effects, we estimated multiple linear models ..." "Inter-individual variability in the simulated E-field predicts tACS effects" Authors here are attempting to predict a property of the subjects that was just shown to not be a reliable property of the subject. Authors are picking 9 possible features for this, testing 33 possible models with N=34 data points. With these circumstances it is not hard to find something that correlates by chance. And some of the models tested had interaction terms, possibly further increasing the number of comparisons. In the absence of multiple comparison correction, what is happening here is that multiple models are fit to the data, and a statistical test is performed for the best model on the same (training) data. The corresponding claim that variations are explained by variations in electric field is not persuasive.

      "Can we reduce inter-individual variability in tACS effects ..." This section seems even more speculative and with mixed results.

      Given the concerns with the statistical analysis above, there are concerns about the following statements in the summary of the Discussion:

      "4) individual variability in tACS effect size was partially explained by two interactions: between the normal component of the E-field and the field focality, and between the normal component of the E-field and the distance between the peak of the electric field and the functional target ROIs."

      The complexity of this statement alone may be a good indication that this could be the result of false discovery due to multiple comparisons.

      For the same reason as stated above, the following statements in the Abstract do not appear to have adequate support in the data:

      "Inter-individual variability of tACS effects was best explained by the strength of the inward electric field, depending on the field focality and proximity to the target brain region. Although additional evidence is necessary, our results<br /> 42 also provided suggestive insights that spatially optimizing the electrode montage could be a promising tool to reduce inter-individual variability of tACS effects."

    1. Joint Public Review:

      This manuscript tackles an important question, namely how K+ affects substrate transport in the SLC6 family. K+ effects have previously been reported for DAT and SERT, but the prototypical SLC6-fold transporter LeuT was not known to be sensitive to the K+ concentration. In this manuscript, the authors demonstrate convincingly that K+ inhibits Na+ binding, and Na+-dependent amino acid binding at high concentrations, and that K+ inside of vesicles containing LeuT increases the transport rate. However, outside K+ apparently had very little effect. Uptake data are supplemented with binding data, using the scintillation proximity assay, and transition metal FRET, allowing the observation of the distribution of distinct conformational states of the transporter.

      Overall, the data are of high quality. I was initially concerned about the use of solutions of very high ionic strength (the Km for K+ is in the 200 mM range), however, the authors performed good controls with lower ionic strength solutions, suggesting that the K+ effect are specific and not caused by artifacts from the high salt concentrations.

    1. Reviewer #1 (Public Review):

      Summary:<br /> In this study, Nandy and colleagues examine neural and behavioral correlates of perceptual variability in monkeys performing a visual change detection task. They used a laminar probe to record from area V4 while two macaque monkeys detected a small change in stimulus orientation that occurred at a random time in one of two locations, focusing their analysis on stimulus conditions where the animal was equally likely to detect (hit) or not-detect (miss) a briefly presented orientation change (target). They discovered two behavioral measures that are significantly different between hit and miss trials - pupil size tends to be slightly larger on hits vs. misses, and monkeys are more likely to miss the target on trials in which they made a microsaccade shortly before target onset. They also examined multiple measures of neural activity across the cortical layers and found some measures that are significantly different between hits and misses.

      Strengths:<br /> Overall the study is well executed and the analyses are appropriate (though multiple issues do need to be addressed).

      Weaknesses:<br /> My main concern with this study is that with the exception of the pre-target microsaccades, the physiological and behavioral correlates of perceptual variability (differences between hits and misses) appear to be very weak and disconnected. Some of these measures rely on complex analyses that are not hypothesis-driven and where statistical significance is difficult to assess. The more intuitive analysis of the predictive power of trial outcomes based on the behavioral and neural measures is only discussed at the end of the paper. This analysis shows that some of the significant measures have no predictive power, while others cannot be examined using the predictive power analysis because these measures cannot be estimated in single trials. Given these weak and disconnected effects, my overall sense is that the current results do not significantly advance our understanding of the neural basis of perceptual variability.

    1. Reviewer #1 (Public Review):

      Zhu, et al present a genome-wide histone modification analysis comparing patients with schizophrenia (on or off antipsychotics) to non-psychiatric controls. The authors performed analyses across the dorsolateral prefrontal cortex and tested for enrichment of nearby genes and pathways. The authors performed an analysis measuring the effect of age on the epigenomic landscape as well. While this paper provides a unique resource around SCZ and its epigenetic correlates, and some potentially intriguing findings in the antipsychotic response dataset there were some potential missed opportunities - related to the integration of outside datasets and genotypes that could have strengthened the results and novelty of the paper.

      Major Comments

      1. Is there genotype data available for this cohort of donors or can it be generated? This would open several novel avenues of investigation for the authors. First the authors can test for enrichment of heritability for SCZ or even highly comorbid disorders such as bipolar. Second, it would allow the authors to directly measure the genetic regulation of histone markers by calculating QTLs (in this case histone hQTLs). The authors assert that although interesting, ATAC-seq approach does not provide the same chromatin state information as histone mods mapped by ChiP. Why do the authors not test this? There are several ATAC-seq datasets available for SCZ [https://pubmed.ncbi.nlm.nih.gov/30087329/]and an additional genomic overlap could help tease apart genetic regulation of the changes observed.

      2. Can the authors theorize why their analysis found significant effects for H3K27Ac for antipsychotic use when a recent epigenomic study of SCZ using a larger cohort of samples and including the same histone modifications did not [https://pubmed.ncbi.nlm.nih.gov/30038276/]? Given the lower n and lower number of cells in this group, it would be helpful if the authors could speculate on why they see this. Do the authors know if there is any overlap with the Girdhar study donors or if there are other phenotypic differences that could account for this?

      3. The reviewer is concerned about the low concordance between bulk nuclei RNA-seq and single-cell RNA-seq for SCZ (236 of 802 DEGs in NeuN+ and 63 of 1043 NEuN-). While it is not surprising for different cohorts to have different sets of DEGs these seem to be vastly different. Was there a particular cell type(s) that enriched for the authors' DEGs in the single-cell dataset? Do the authors know if any donors overlapped between these cohorts?

      4. Functional enrichment analyses: details are not provided by the authors and should be added. The authors need to consider a) providing a gene universe, ie only considering the sets of genes with nearby H3K4me3/ H3K27ac levels, to such pathway tools, and b) should take into account the fact that some genes have many more peaks with data. There are known biases in seemingly just using the best p-value per gene in other epigenetic analysis (ie. DNA methylation data) and software is available to run correct analyses: https://pubmed.ncbi.nlm.nih.gov/23732277.

    1. Reviewer #1 (Public Review):

      Summary:<br /> The circuit mechanism underlying the formation of grid cell activity and the organization of grid cells in the medial entorhinal cortex (MEC) is still unclear. To understand the mechanism, the current study investigated synaptic interactions between stellate cells (SC) and PV+ interneurons (IN) in layer 2 of the MEC by combing optogenetic activations and paired patch-clamp recordings. The results convincingly demonstrated highly structured interactions between these neurons: specific and direct excitatory-inhibitory interactions existed at the scale of grid cell phase clusters, and indirect interactions occurred at the scale of grid modules.

      Strengths:<br /> Overall, the manuscript is very well written, the approaches used are clever, and the data were thoroughly analyzed. The study conveyed important information for understanding the circuit mechanism that shapes grid cell activity. It is important not only for the field of MEC and grid cells, but also for broader fields of continuous attractor networks and neural circuits.

      Weaknesses:<br /> (1) The study largely relies on the fact that ramp-like wide-field optogenetic stimulation and focal optogenetic activation both drove asynchronous action potentials in SCs, and therefore, if a pair of PV+ INs exhibited correlated activity, they should receive common inputs. However, it is unclear what criteria/thresholds were used to determine the level of activity asynchronization, and under these criteria, what percentage of cells actually showed synchronized or less asynchronized activity. A notable percentage of synchronized or less asynchronized SCs could complicate the results, i.e., PV+ INs with correlated activity could receive inputs from different SCs (different inputs), which had synchronized activity. More detailed information/statistics about the asynchronization of SC activity is necessary for interpreting the results.

      (2) The hypothesis about the "direct excitatory-inhibitory" synaptic interactions is made based on the GABAzine experiments in Figure 4. In the Figure 8 diagram, the direct interaction is illustrated between PV+ INs and SCs. However, the evidence supporting this "direct interaction" between these two cell types is missing. Is it possible that pyramidal cells are also involved in this interaction? Some pieces of evidence or discussions are necessary to further support the "direction interaction".

    1. Reviewer #1 (Public Review):

      The authors used mathematical models to explore the mechanism(s) underlying the process of polar tube extrusion and the transport of the sporoplasm and nucleus through this structure. They combined this with experimental observations of the structure of the tube during extrusion using serial block face EM providing 3 dimensional data on this process. They also examined the effect of hyperosmolar media on this process to evaluate which model fit the predicted observed behavior of the polar tube in these various media solutions. Overall, this work resulted in the authors arriving at a model of this process that fit the data (model 5, E-OE-PTPV-ExP). This model is consistent with other data in the literature and provides support for the concept that the polar tube functions by eversion (unfolding like a finger of a glove) and that the expanding polar vacuole is part of this process. Finally, the authors provide important new insights into the bucking of the spore wall (and possible cavitation) as providing force for the nucleus to be transported via the polar tube. This is an important observation that has not been in previous models of this process.

    1. Reviewer #1 (Public Review):

      In this study, the authors investigated the role of MAM and the Notch signalling 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.