Reviewer #2 (Public Review):

Hagihara et al. conducted a study investigating the correlation between decreased brain pH, increased brain lactate, and poor working memory. They found altered brain pH and lactate levels in animal models of neuropsychiatric and neurodegenerative disorders. Their study suggests that poor working memory performance may predict higher brain lactate levels.

However, the study has some significant limitations. One major concern is that the authors examined whole-brain pH and lactate levels, which might not fully represent the complexity of disease states. Different brain regions and cell types may have distinct protein and metabolite profiles, leading to diverse disease outcomes. For instance, certain brain regions like the hippocampus and nucleus accumbens exhibit opposite protein/signaling pathways in neuropsychiatric disease models.

Moreover, the memory tests used in the study are specific to certain brain regions, but the authors did not measure lactate levels in those regions. Without making lactate measurements in brain-regions and cell types involved in these diseases, any conclusions regarding the role of lactate in CNS diseases is premature.

Additionally, evidence suggests that exogenous treatment with lactate has positive effects, such as antidepressant effects in multiple disease models (Carrard et al., 2018, Carrard et al., 2021, Karnib et al., 2019, Shaif et al., 2018). It also promotes learning, memory formation, neurogenesis, and synaptic plasticity (Suzuki et al., 2011, Yang et al., 2014, Weitian et al., 2015, Dong et al., 2017, El Hayek et al. 2019, Wang et al., 2019, Lu et al., 2019, Lev-Vachnish et a.l, 2019, Descalzi G et al., 2019, Herrera-López et al., 2020, Ikeda et al., 2021, Zhou et al., 2021,Roumes et al., 2021, Frame et al., 2023, Akter et al., 2023).

In conclusion, the relevance of total brain pH and lactate levels as indicators of the observed correlations is controversial, and evidence points towards lactate having more positive rather than negative effects. It is important that the authors perform studies looking at brain-region-specific concentrations of lactate and that they modulate lactate levels (decrease) in animal models of disease to validate their conclusions. It is also important to consider the above-mentioned studies before concluding that "altered brain pH and lactate levels are rather involved in the underlying pathophysiology of some patients with neuropsychiatric disorders" and that "lactate can serve as a potential therapeutic target for neuropsychiatric disorders".

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.

Reviewer #2 (Public Review):

The study is novel and valuable to the field and provides new and important insights into the role of lipid mediators in VML injuries. By expanding our understanding of the mechanisms that regulate muscle regeneration following VML injuries, the study has the potential to guide the development of novel therapeutic interventions that promote tissue repair and recovery. The data presented in the manuscript is of good quality. The findings and conclusions are supported by a variety of different analyses (e.g., gene expression, histology, flow cytometry).

Despite the strengths of the study, some limitations are identified. Specifically, the impact of maresin 1 on macrophage phenotypes (M1/M2) could have been explored in more detail using histological or protein expression analysis. Moreover, additional data are needed to substantiate the claims about increased muscle regeneration. Lastly, the study does not address myofiber innervation, myofiber-type transitions, or motor unit remodeling.

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.

Reviewer #3 (Public Review):

George et al. present a convincing new Python toolbox that allows researchers to generate synthetic behavior and neural data specifically focusing on hippocampal functional cell types (place cells, grid cells, boundary vector cells, head direction cells). This is highly useful for theory-driven research where synthetic benchmarks should be used. Beyond just navigation, it can be highly useful for novel tool development that requires jointly modeling behavior and neural data. The code is well organized and written and it was easy for us to test.

We have a few constructive points that they might want to consider.

- Right now the code only supports X,Y movements, but Z is also critical and opens new questions in 3D coding of space (such as grid cells in bats, etc). Many animals effectively navigate in 2D, as a whole, but they certainly make a large number of 3D head movements, and modeling this will become increasingly important and the authors should consider how to support this.

- What about other environments that are not "Boxes" as in the name - can the environment only be a Box, what about a circular environment? Or Bat flight? This also has implications for the velocity of the agent, etc. What are the parameters for the motion model to simulate a bat, which likely has a higher velocity than a rat?

- Semi-related, the name suggests limitations: why Rat? Why Not Agent? (But its a personal choice)

- A future extension (or now) could be the ability to interface with common trajectory estimation tools; for example, taking in the (X, Y, (Z), time) outputs of animal pose estimation tools (like DeepLabCut or such) would also allow experimentalists to generate neural synthetic data from other sources of real-behavior.

- What if a place cell is not encoding place but is influenced by reward or encodes a more abstract concept? Should a PlaceCell class inherit from an AbstractPlaceCell class, which could be used for encoding more conceptual spaces? How could their tool support this?

- This a bit odd in the Discussion: "If there is a small contribution you would like to make, please open a pull request. If there is a larger contribution you are considering, please contact the corresponding author3" This should be left to the repo contribution guide, which ideally shows people how to contribute and your expectations (code formatting guide, how to use git, etc). Also this can be very off-putting to new contributors: what is small? What is big? we suggest use more inclusive language.

- Could you expand on the run time for BoundaryVectorCells, namely, for how long of an exploration period? We found it was on the order of 1 min to simulate 30 min of exploration (which is of course fast, but mentioning relative times would be useful).

- Regarding the Geometry and Boundary conditions, would supporting hyperbolic distance might be useful, given the interest in alternative geometry of representations (ie, https://www.nature.com/articles/s41593-022-01212-4)?

- In general, the set of default parameters might want to be included in the main text (vs in the supplement).

- It still says you can only simulate 4 velocity or head directions, which might be limiting.

- The code license should be mentioned in the Methods.

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.

Reviewer #2 (Public Review):

In this study, the goal is to leverage the power of Bayesian inference to estimate online the probability that any given arbitrarily chosen strategy is being used by the decision-maker. By computing the trial-by-trial MAP and variance of the posterior distribution for each candidate strategy, the authors can not only see which strategy is primarily being used at every given time during the task and when strategy changes occur but also detect when the target rule of a learning task becomes the front-running strategy, i.e., when successful learning occurs.

Strengths:<br /> 1. The proposed approach adds to recent methods for capturing the dynamics of decision-making at finer temporal resolution (trials) (Roy et al., 2021; Ashwood et al., 2022) but it is novel and differs from these in that it is suited especially well for analyzing when learning occurs, or when a rule switches and learning must recommence, and it does not necessitate large numbers of trials.

2. The manuscript starts with a validation of the approach using synthetic data and then is applied to datasets of trial-based two-alternative forced choice tasks ranging from rodent to non-human primate to human, providing solid evidence of its utility.

3. Compared to classic procedures for identifying when an animal has learned a contingency which typically needs to be conservative in favor of better accuracy, this method retrieves signs of learning happening earlier (~30 trials earlier on average). This is achieved by identifying the moment (trial) when the posterior probability of the correct "target" rule surpasses the probability of all other strategies. Having greater temporal precision in detecting when learning happens may have a very significant impact on studies of the neural mechanisms of learning.

4. This approach seems amenable to testing many different strategies depending on the purpose of the analysis. In the manuscript, the authors test target versus non-target strategies (correct versus incorrect) and also in another version of the analysis, they test what they call "exploratory" strategies.

5. One of the main appeals of this method is its apparent computational simplicity. It necessitates only updating on every trial the parameters of a beta distribution (prior distribution for a given strategy) with the evidence that the behavior on trial was either consistent or inconsistent with the strategy. Two scalars, the mode of the posterior (MAP) and the inverse of the variance, are all that are required for identifying the decision criterion (highest MAP and if tied lowest variance) and the learning criterion (first trial where MAP for target strategy is higher than chance).

Weaknesses:<br /> 1. It seems like a limitation of this approach is that the candidate strategies to arbitrate between must be known ex-ante. It is not clear how this approach could be applied to uncover latent strategies that are not mixtures of the strategies selected.

2. Different strategies may be indistinguishable from each other and thus it may not be possible to distinguish between them. Similarly, the fact that two strategies seem to be competing for the highest MAP doesn't necessarily mean that those are correct strategies and perhaps interchangeable as the manuscript seems to suggest.

3. The decay parameter is a necessary component to make the strategy selection non-stationary and accommodate data sets where the rules are changing throughout the task. However, the choice of the decay parameter value bounds does not seem very principled. Having this parameter as a free-parameter adds a flexibility that seems to have significant effects on when the strategy switch is detected and how stable the detected switch is.

4. This method is a useful approach for arbitrating between strategies and describing the behavior with a temporal precision that may prove important for studies attempting to tie these precise events to changes in neural activity. However, it seems limited in its explanatory power. In its current form, this method does not provide a prediction of the probability to transition from one strategy to another. And, because the MAP of different strategies may be close at any given moment, it is hard to imagine using this approach to tease out the different "mental states" that represent each strategy being at play.

Reviewer #3 (Public Review):

Summary:<br /> The authors aim to demonstrate the effectiveness of their developed methodology, which utilizes super-resolution microscopy and single-molecule tracking in live cells on a high-throughput scale. Their study focuses on measuring the diffusion state of a molecule target, the estrogen receptor, in both ligand-bound and unbound forms in live cells. By showcasing the ability to screen 5067 compounds and measure the diffusive state of the estrogen receptor for each compound in live cells, they illustrate the capability and power of their methodology.

Strengths:<br /> Readers are well introduced to the principles in the initial stages of the manuscript with highly convincing video examples. The methods and metrics used (fbound) are robust. The authors demonstrate high reproducibility of their screening method (R2=0.92). They also showcase the great sensitivity of their method in predicting the proliferation/viability state of cells (R2=0.84). The outcome of the screen is sound, with multiple compounds clustering identified in line with known estrogen receptor biology.

Weaknesses:<br /> - Potential overstatement on the relationship of low diffusion state of ER bound to compound and chromatin state without any work on chromatin level.<br /> - Could the authors clarify if the identified lead compound effects are novel at any level?<br /> - More video example cases on the final lead compounds identified would be a good addition to the current data package.

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.

Reviewer #2 (Public Review):

Summary:<br /> McSwiggen et al present a high throughput platform for SPT that allows them to identify pharmaceutics interactions with the diffusional behavior of receptors and in turn to identify potent new ligands and cellular mechanisms. The manuscript is well written, it provides a solid new mentor and a proper experimental foundation

Strengths:<br /> The method capitalizes and extends to existing high throughput toolboxes and is directly applied to multiple receptors and ligands. The outcomes are important and relevant for society. 10^6 cells and >400 ligands per is a significant achievement.

The method can detect functionally relevant changes in transcription factor dynamics and accurately differentiate the ligand/target specificity directly within the cellular environment. This will be instrumental in screening libraries of compounds to identify starting points for the development of new therapeutics. Identifying hitherto unknown networks of biochemical signaling pathways will propel the field of single-particle live cell and quantitative microscopy in the area of diagnostics. The manuscript is well-written and clearly conveys its message.

Weaknesses:<br /> There are a few elements, that if rectified would improve the claims of the manuscript.

The authors claim that they measure receptor dynamics. In essence, their readout is a variation in diffusional behavior that correlates to ligand binding. While ligand binding can result in altered dynamics or /and shift in conformational equilibrium, SPT is not recording directly protein structural dynamics, but their effect on diffusion. They should correct and elaborate on this.

L 148 What do the authors mean 'No correlation between diffusion and monomeric protein size was observed, highlighting the differences between cellular protein dynamics versus purified systems'. This is not justified by data here or literature reference. How do the authors know these are individual molecules? Intensity distributions or single bleaching steps should be presented.

Along the same lines, the data in Figs 2 and 4 show that not only the immobile fraction is increased but also that the diffusion coefficient of the fast-moving (attributed to free) is reduced. The authors mention this and show an extended Fig 5 but do not provide an explanation. How do potential transient ligand binding and the time-dependent heterogeneity in motion (see comment above) contribute to this? Also, in line 216 the authors write "with no evidence" of transient diffusive states. How do they define transient diffusive states? While there are toolboxes to directly extract the existence and abundance of these either by HMM analysis or temporal segmentation, the authors do not discuss or use them.

The authors discuss the methods for extracting kinetic information of ligand binding by diffusion. They should consider the temporal segmentation of heterogenous diffusion. There are numerous methods published in journals or BioRxiv based on analytical or deep learning tools to perform temporal segmentation. This could elevate their analysis of Kon and Koff.

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.

Reviewer #2 (Public Review):

Summary:

While a significant portion of immunotherapy research has focused on the pivotal role of T cells in tumor immunity, their effectiveness may be limited by the suppressive nature of the tumor environment. On the other hand, myeloid cells are commonly found within tumors and can withstand these adverse conditions. However, these cells often adopt an immunosuppressive phenotype when infiltrating tumors. Therefore, manipulating myeloid cells could potentially enhance the anti-tumor potential of immunotherapy.

In this manuscript, Farhat-Younes and colleagues have demonstrated that activating the IgM receptor signaling in myeloid cells induces an oxygen burst, the secretion of Granzyme B, and the lysis of adjacent tumor cells. Furthermore, they have outlined a strategy to utilize these features to generate CAR macrophages. However, they have identified a limitation: the expression of scFv in myeloid cells induces ER stress and the degradation of misfolded proteins. To address this issue, chimeric receptors were designed based on the high-affinity FcγRI for IgG. When macrophages transfected with these receptors were exposed to tumor-binding IgG, extensive tumor cell killing, and the release of reactive oxygen species and Granzyme B were observed.

Strengths:<br /> In general, I consider this work to be significant, and the results are compelling. It emphasizes the specific considerations and requirements for successful manipulation in myeloid cells, which could further advance the field of cellular engineering for the benefit of immunotherapy

Weaknesses:

Nevertheless, there are several minor issues that should be addressed:

1- TCR fragments are commonly used to induce ER stress in non-immune cells. Therefore, it would be interesting to investigate whether TCR fragments can be expressed in myeloid cells and if they induce ER stress. Addressing this issue would support the notion that these cells lack the ER chaperones required for folding immunoglobulin variable chains.<br /> 2- It would be valuable to determine whether, after the degradation of scFv fragments by myeloid cells, they are presented on MHC-I and MHC-II.<br /> 3- Some methodological details, such as the vaccination protocol and high-resolution microscopy procedures, are missing from the text.

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.

Reviewer #2 (Public Review):

Working memory is not error free. Behavioral reports of items held in working memory display several types of bias, including contraction bias and serial dependence. Recent work from Akrami and colleagues demonstrates that inactivating rodent PPC reduces both forms of bias, raising the possibility of a common cause.

In the present study, Boboeva, Pezotta, Clopath, and Akrami introduce circuit and descriptive variants of a model in which the contents of working memory can be replaced samples from recent sensory history. This volatility manifests as contraction bias and serial dependence in simulated behavior, parsimoniously explaining both sources of bias. The authors validate their model by showing that it can recapitulate previously published and novel behavioral results in rodents and neurotypical and atypical humans.

Both the modeling and the experimental work is rigorous, providing convincing evidence that a model of working memory in which reports sometimes sample past experience can produce both contraction bias and serial dependence, and that this model is consistent with behavioral observations across rodents and humans in the parametric working memory (PWM) task.

These efforts constitute an admirable initial validation of the proposed model, and the authors present several novel predictions that will allow for further tests in future experiments. First, the authors note that their circuit model predicts a bimodal error distribution in delayed estimation paradigms (due to noisy sampling of sensory history on a subset of trials) that merges into a unimodal distribution when recent sensory history and the current to-be-reported stimulus have very similar values (Fig. 5c). Analysis of extent delayed estimation datasets (e.g., https://osf.io/jmkc9/) or new experiments will provide the opportunity for a straightforward test of this hypothesis.

Second, the bulk of the modeling efforts presented here are devoted to a circuit-level description of how putative posterior parietal cortex (PPC) and working-memory (WM) related networks may interact to produce such volatility and biases in memory. This effort is extremely useful because it allows the model to be constrained by neural observations and manipulations in addition to behavior, and the authors begin this line of inquiry here (by showing that the circuit model can account for effects of optogenetic inactivation of rodent PPC). As the authors note, population electrophysiology in PPC and WM-related areas and single-trial analyses will play an important role in the ultimate validation of this model.

Finally, it is noteworthy that, in the spirit of moving away from an overreliance on p-values (e.g., Amrhein et al., PeerJ 2017), the authors eschew conventional hypothesis testing when reporting their experimental results. The p-values aren't missed, in large part thanks to excellent visualizations and apparently large effect sizes. It's unclear how well this approach would generalize to other questions and datasets; nevertheless, this study provides an interesting data point in the ongoing conversation around reproducibility and rigor.

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).

Reviewer #2 (Public Review):

Schmid et al present a lovely study looking at the effect of passive auditory exposure on learning a categorization task.<br /> The authors utilize a two-alternative choice task where mice have to discriminate between upward and downward moving frequency sweeps. Once mice learn to discriminate easy stimuli, the task is made psychometric and additional intermediate stimuli are introduced (as is standard in the literature). The authors introduce an additional two groups of animals, one that was passively exposed to the task stimuli before any behavioral shaping, and one that had passive exposure interleaved with learning. The major behavioral finding is that passive exposure to sounds improves learning speed. The authors show this in a number of ways through linear fits to the learning curves. Additionally, by breaking down performance based on the "extreme" vs "psychometric" stimuli, the authors show that passive exposure can influence responses to sounds that were not present during the initial training period. One limitation here is that the presented analysis is somewhat simplistic, does not include any detailed psychometric analysis (bias, lapse rates etc), and primarily focuses on learning speed. Ultimately though, the behavioral results are interesting and seem supported by the data.

To investigate the neural mechanisms that may underlie their behavioral findings, the authors turn to a family of artificial neural network models and evaluate the consequences of different learning algorithms and schedules, network architectures, and stimulus distributions, on the learning outcomes. The authors work through five different architectures that fail to recapitulate the primary behavior findings before settling on a final model, utilizing a combination of supervised and unsupervised learning, that was capable of reproducing the key aspects of the experiments. Ultimately, the behavioral results presented are consistent with network models that build latent representations of task-relevant features that are determined by statistical properties of the input distribution.

Reviewer #3 (Public Review):

Summary of Author's Results/Intended Achievements<br /> The authors were trying to ascertain the underlying learning mechanisms and network structure that could explain their primary experimental finding: passive exposure to a stimulus (independent of when the exposure occurs) can lead to improvements in active (supervised) learning. They modeled their task with 5 progressively more complex shallow neural networks classifying vectors drawn from multi-variate Gaussian distributions.

Account of Major Strengths:<br /> Overall, the experimental findings were interesting. The modelling was also appropriate, with a solid attempt at matching the experimental condition to simplified network models.

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.

Reviewer #2 (Public Review):

This report by Hur et al. examines simultaneous activity in the cerebellum and anterior cingulate cortex (ACC) to determine how activity in these regions is coordinated during social behavior. To accomplish this, the authors developed a recording device named the E-scope, which combines a head-mounted mini-scope for in vivo Ca2+ imaging with an extracellular recording probe (in the manuscript they use a 32-channel silicon probe). Using the E-scope, the authors find subpopulations of cerebellar neurons with social-interaction-related activity changes. The activity pattern is predominantly decreased firing in PCs and increases in DNs, which is the expected reciprocal relationship between these populations. They also find social-interaction-related activity in the ACC. The authors nicely show the absence of locomotion onset and offset activity in PCs and DNs ruling out that is movement driven. Analysis showed high correlations between cerebellar and ACC populations (namely, Soc+ACC and Soc+DN cells). The finding of correlated activity is interesting because non-motor functions of the cerebellum are relatively little explored. However, the causal relationship is far from established with the methods used, leaving it unclear if these two brain regions are similarly engaged by the behavior or if they form a pathway/loop. Overall, the data are presented clearly, and the manuscript is well written, however the biological insight gained is rather limited.

Reviewer #3 (Public Review):

Complex behavior requires complex neural control involving multiple brain regions. The currently available tools to measure neural activity in multiple brain regions in small animals are limited and often involve obligatory head-fixation. The latter, obviously, impacts the behaviors under study. Hur and colleagues present a novel recording device, the E-Scope, that combines optical imaging of fluorescent calcium imaging in one brain region with high-density electrodes in another. Importantly, the E-Scope can be implanted and is, therefore, compatible with usage in freely moving mice. The authors used their new E-Scope to study neural activity during social interactions in mice. They demonstrate the presence of neural correlates of social interaction that happen simultaneously in the cerebellum and the anterior cingulate cortex.

The major accomplishment of this study is the development and introduction of the E-Scope. The evaluation of this part can be short: it works, so the authors succeeded.

The authors managed to reduce the weight of the implant to 4.5 g, which is - given all functionality - quite an accomplishment in my view. However, a mouse weighs between 20 and 40 g, so that an implant of 4.5 g is still quite considerable. It can be expected that this has an impact on the behavior and, possibly, the well-being of the animals. Whether this is the case or not, is not really addressed in this study. The authors suffice with the statement that "Recorded animals made more contact with the other mouse than with the object (Figure 2A), suggesting a normal preference for social contact with the E-Scope attached." A direct comparison between mice before and after implant, or between mice with and without an implant would provide more insight into the putative impact of the E-Scope on (social) behavior.

In Figure 1 D-G, the authors present raw data from the neurophysiological recordings. In panel D, we see events with vastly different amplitudes. It would be very insightful if the authors would describe which events they considered to be action potentials, and which not. Similarly, indicating the detected complex spikes in the raw traces of Figure 1E would provide more insight into the interpretation of the data. Although the authors mention to consider the occurrence of complex spikes and simple spikes, a clear definition of what is considered a single unit recording is lacking. As there is quite a wide range in reported firing rates in Figure 2 - figure supplement 3, more clarity on this aspect would be insightful. Furthermore, in their text, the authors state that the pause in simple spike firing following a complex spike normally lasts until around 40 ms, and for this statement they refer to Figure 1G that shows a pause of less than 10 ms.

The number of Purkinje cells recorded during social interactions is quite low: only 11 cells showed a modulation in their spiking activity (unclear whether in complex spikes, simple spikes or both. During object interaction, only 4 cells showed a significant modulation. Unclear is whether the latter 4 are a subset of the former 11, or whether "social cells" and "object cells" are different categories. Having so few cells, and with these having different types of modulation, the group of cells for each type of modulation is really small, going down to 2 cells/group. The small group sizes complicate the interpretation of the data - in particular also on the analysis of movement-related activity that is now very noisy (Figure 2 - figure supplement 4).

In conclusion, the authors present a novel method to record neural activity with single cell-resolution in two brain regions in freely moving mice. Given the challenges associated with understanding of complex behaviors, this approach can be useful for many neuroscientists. The authors demonstrate the potential of their approach by studying social interactions in mice. Clearly, there are correlations in activity of neurons in the anterior cingulate cortex and the cerebellum related to social interactions. To bring our understanding of these patterns to a higher level, more detailed analyses (and probably also larger group sizes of cerebellar neurons) are required, though.

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.

Reviewer #2 (Public Review):

The authors attempt to address a long-standing controversy in the study of the neural correlates of visual awareness, namely whether neurons in prefrontal cortex are necessarily involved in conscious perception. Several leading theories of consciousness propose a necessary role for (at least some sub-regions of) PFC in basic perceptual awareness (e.g., global neuronal workspace theory, higher order theories), while several other leading theories posit that much of the previously reported PFC contributions to perceptual awareness may have been confounded by task-based cognition that co-varied between the aware and unaware reports (e.g., recurrent processing theory, integrated information theory). By employing intracranial EEG in human patients and a threshold detection task on low-contrast visual stimuli, the authors assessed the timing and location of neural populations in PFC that are differentially activated by stimuli that are consciously perceived vs. not perceived. Overall, the reported results support the view that certain regions of PFC do contribute to visual awareness, but at time-points earlier than traditionally predicted by GNWT and HOTs.

Major strengths of this paper include the straightforward visual threshold detection task including the careful calibration of the stimuli and the separate set of healthy control subjects used for validation of the behavioral and eye tracking results, the high quality of the neural data in six epilepsy patients, the clear patterns of differential high gamma activity and temporal generalization of decoding for seen versus unseen stimuli, and the authors' interpretation of these results within the larger research literature on this topic. This study appears to have been carefully conducted, the data were analyzed appropriately, and the overall conclusions seem warranted given the main patterns of results.

Weaknesses include the saccadic reaction time results and the potential flaws in the design of the reporting task. As the authors acknowledge, this is not a "no report" paradigm, rather, it's a paradigm aimed at balancing the post-perceptual cognitive and motor requirements between the seen and unseen trials. On each trial, subjects/patients either perceived the stimulus or not, and had to briefly maintain this "yes/no" judgment until a fixation cross changed color, and the color change indicated how to respond (saccade to the left or right). Differences in saccadic RTs (measured from the time of the fixation color change to moving the eyes to the left or right response square) were evident between the seen and unseen trials (faster for seen). In the discussion, the authors summarize several alternative explanations of the saccade results and limitations of their report paradigm that will help guide future research.

The current results help advance our understanding of the contribution of PFC to visual awareness. These results, when situated within the larger context of the rapidly developing literature on this topic provide converging evidence that some sub-regions of PFC contribute to visual awareness, but at latencies earlier than originally predicted by proponents of, especially, global neuronal workspace theory. Three recent studies that used "no report paradigms", but with clearly visible stimuli, reported very similar results in PFC (Vishne et al., 2023; Broday-Dvir et al., 2023; Cogitate et al., 2023). The current study uses a report paradigm, but with consciously seen vs. unseen conditions, to fill the gap left by these previous studies, i.e., it remained unclear whether the PFC results from the previous studies were related to conscious or unconscious processing. Taken as a whole, evidence appears to be converging for a limited and early-in-time (200-300ms) contribution of PFC to visual awareness, after task and motor confounds are minimized.

Reviewer #3 (Public Review):

The authors report a study in which they use intracranial recordings to dissociate subjectively aware and subjectively unaware stimuli, focusing mainly on prefrontal cortex.

The authors have dealt successfully with some of my previous concerns, especially the more direct link to the Gaillard et al., (2009) paper, and the associated analyses, has improved the manuscript. Some of my other concerns regarding the theoretical embedding of the findings have only been partially mitigated and some interesting results derived from suggestions for additional analyses will be used for future papers.

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.

Reviewer #2 (Public Review):

The contribution of glial cells to the pathogenesis of amyotrophic lateral sclerosis (ALS) is of substantial interest and the investigators have contributed significantly to this emerging field via prior publications. In the present study, authors use a SOD1G93A mouse model to elucidate the role of astrocyte ephrinB2 signaling in ALS disease progression. Erythropoietin-producing human hepatocellular receptors (Ephs) and the Eph receptor-interacting proteins (ephrins) signaling is an important mediators of signaling between neurons and non-neuronal cells in the nervous system. Recent evidence suggests that dysregulated Eph-ephrin signaling in the mature CNS is a feature of neurodegenerative diseases. In the ALS model, upregulated Eph4A expression in motor neurons has been linked to disease pathogenesis. In the present study, authors extend previous findings to a new class of ephrinB2 ligands. Urban et al. hypothesize that upregulated ephrinB2 signaling contributes to disease pathogenesis in ALS mice. The authors successfully test this hypothesis and their results generally support their conclusion.

Major strengths of this work include a robust study design, a well-defined translational model, and complementary biochemical and experimental methods such that correlated findings are followed up by interventional studies. Authors show that ephrinB2 ligand expression is progressively upregulated in the ventral horn of the cervical and lumbar spinal cord through pre-symptomatic to end stages of the disease. This novel association was also observed in lumbar spinal cord samples from post-mortem samples of human ALS donors with a SOD1 mutation. Further, they use a lentiviral approach to drive knock-down of ephrinB2 in the central cervical region of SOD1G93A mice at the pre-symptomatic stage. Interestingly, in spite of using a non-specific promoter, authors note that the lentiviral expression was preferentially driven in astrocytes.

Since respiratory compromise is a leading cause of morbidity in the ALS population, the authors proceed to characterize the impact of ephrinB2 knockdown on diaphragm muscle output. In mice approaching the end stage of the disease, electrophysiological recordings from the diaphragm muscle show that animals in the knock-down group exhibited a ~60% larger amplitude. This functional preservation of diaphragm function was also accompanied with the preservation of diaphragm neuromuscular innervation. However, it must be noted that this cervical ephrinB2 knockdown approach had no impact on disease onset, disease duration, or animal survival. Furthermore, there was no impact of ephrinB2 knockdown on forelimb or hindlimb function. This is an expected result, given the fairly focal approach of ephrinB2 knockdown in C3-C5 spinal segments.

The major limitation of the study is the conclusion that the preservation of diaphragm output following ephrinB2 knockdown in SOD1 mice is mediated primarily (if not entirely) by astrocytes. The authors present convincing evidence that a reduction in ephrinB2 is observed in local astrocytes (~56% transduction) following the intraspinal injection of the lentivirus. However, the proportion of cell types assessed for transduction with the lentivirus in the spinal cord was limited to neurons, astrocytes, and oligodendrocyte lineage cells. Microglia comprise a large proportion of the glial population in the spinal grey matter and have been shown to associate closely with respiratory motor pools. This cell type, amongst the many other that comprise the ventral gray matter, have not been investigated in this study. Nonetheless, there is convincing evidence to suggest astrocytes play a significant role, as compared to oligodendrocytes in promoting ALS pathogenesis.

In summary, this study by Urban et al. provides a valuable framework for Eph-Ephrin signaling mechanisms imposing pathological changes in an ALS mouse model. The role of glial cells in ALS pathology is a very exciting and upcoming field of investigation. The current study proposes a novel astrocyte-mediated mechanism for the propagation of disease that may eventually help to identify potential therapeutic targets.

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.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript by Martin-Flores et al. examines the role of DKK3 in Alzheimer's disease, focusing on the regulation of synaptic number. Using human AD brain databases and tissue samples, the authors demonstrate increased levels of DKK3 protein and mRNA in the brains of AD patients. DKK3 is expressed in excitatory neurons in WT mouse brains and accumulates at atrophic neurites around amyloid plaques in AD mouse brains. Interestingly, the secretion of DKK3 appears to be regulated by NMDAR antagonists, as well as chemical LTD. Through gain and loss of function studies, the authors reveal that DKK3 regulates the number of both excitatory and inhibitory synapses with distinct downstream pathways. Finally, the authors investigate the contribution of DKK3 to synaptic changes in AD and find that DKK3 loss of function rescues both excitatory and inhibitory synaptic defects, resulting in improved memory function in J20 mice.

Strengths:<br /> Overall, the data is clearly presented and deals with the novel roles of DKK3 in controlling excitatory and inhibitory synapses. The finding that shRNA expression of DKK3 in AD model mice rescues synaptic phenotypes and memory impairment is potentially interesting and may provide a new strategy for AD treatment.

Weaknesses:<br /> There are no major weaknesses.

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.

Reviewer #3 (Public Review):

Summary:<br /> Onck and co-workers present in this work the identification of binding partners and sites of polyPR on various nuclear transport components and elucidate how polyPR might potentially influence the transport process. It's interesting to note that some interaction sites on transport components also serve as their inherent/functional binding sites (Figure 3). The difference in the effects between short polyPR (PR7) and long polyPR (PR50) is also evident, although the authors might need to clarify the mechanisms better. Overall, I find this manuscript well organized and concisely written, and it would greatly enhance our understanding of the toxicity induced by polyPR.

Strengths:<br /> The 1-bead per atom force field model used in the study is well-tuned for studying the interactions between polyPR and proteins, as the essential cation-pi interactions (between Arg and Phe/Tyr/Trp) was included using a 8-6 LJ model.

Weaknesses:<br /> To cite the author's response: "At the moment, accurately capturing the binding of NCT components to their native binding targets and the competition with polyPR are best resolved by all-atom molecular dynamics simulations, which come with significant computational demands. This level of detail and computation-intensive analyses is beyond the scope of the current study."

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.

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.

Reviewer #2 (Public Review):

Summary:<br /> Chang et al. investigate neuronal activity firing patterns across various cortical regions in an interesting context-dependent tactile vs visual detection task, developed previously by the authors (Chevee et al., 2021; doi: 10.1016/j.neuron.2021.11.013). The authors report the important involvement of a medial frontal cortical region (MM, probably a similar location to wM2 as described in Esmaeili et al., 2021 & 2022; doi: 10.1016/j.neuron.2021.05.005; doi: 10.1371/journal.pbio.3001667) in mice for determining task rules.

Strengths:<br /> The experiments appear to have been well carried out and the data well analysed. The manuscript clearly describes the motivation for the analyses and reaches clear and well-justified conclusions. I find the manuscript interesting and exciting!

Weaknesses:<br /> I did not find any major weaknesses.

Reviewer #3 (Public Review):

This study examines context-dependent stimulus selection by recording neural activity from several sensory and motor cortical areas along a sensorimotor pathway, including S1, S2, MM, and ALM. Mice are trained to either withhold licking or perform directional licking in response to visual or tactile stimulus. Depending on the task rule, the mice have to respond to one stimulus modality while ignoring the other. Neural activity to the same tactile stimulus is modulated by task in all the areas recorded, with significant activity changes in a subset of neurons and population activity occupying distinct activity subspaces. Recordings further reveal a contextual signal in the pre-stimulus baseline activity that differentiates task context. This signal is correlated with subsequent task modulation of stimulus activity. Comparison across brain areas shows that this contextual signal is stronger in frontal cortical regions than in sensory regions. Analyses link this signal to behavior by showing that it tracks the behavioral performance switch during task rule transitions. Silencing activity in frontal cortical regions during the baseline period impairs behavioral performance.

Overall, this is a superb study with solid results and thorough controls. The results are relevant for context-specific neural computation and provide a neural substrate that will surely inspire follow-up mechanistic investigations. We only have a couple of suggestions to help the authors further improve the paper.

1. We have a comment regarding the calculation of the choice CD in Fig S3. The text on page 7 concludes that "Choice coding dimensions change with task rule". However, the motor choice response is different across blocks, i.e. lick right vs. no lick for one task and lick left vs. no lick for the other task. Therefore, the differences in the choice CD may be simply due to the motor response being different across the tasks and not due to the task rule per se. The authors may consider adding this caveat in their interpretation. This should not affect their main conclusion.

2. We have a couple of questions about the effect size on single neurons vs. population dynamics. From Fig 1, about 20% of neurons in frontal cortical regions show task rule modulation in their stimulus activity. This seems like a small effect in terms of population dynamics. There is somewhat of a disconnect from Figs 4 and S3 (for stimulus CD), which show remarkably low subspace overlap in population activity across tasks. Can the authors help bridge this disconnect? Is this because the neurons showing a difference in Fig 1 are disproportionally stimulus selective neurons?

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.

Reviewer #2 (Public Review):

Summary:<br /> The authors' long-term goals are to understand the utility of precisely phased cortex stimulation regimes on recovery of function after spinal cord injury (SCI). In prior work, the authors explored the effects of contralesion cortex stimulation. Here, they explore ipsilesion cortex stimulation in which the corticospinal fibers that cross at the pyramidal decussation are spared. The authors explore the effects of such stimulation in intact rats and rats with a hemisection lesion at the thoracic level ipsilateral to the stimulated cortex. The appropriately phased microstimulation enhances contralateral flexion and ipsilateral extension, presumably through lumbar spinal cord crossed-extension interneuron systems. This microstimulation improves weight bearing in the ipsilesion hindlimb soon after injury, before any normal recovery of function would be seen. The contralateral homologous cortex can be lesioned in intact rats without impacting the microstimulation effect on flexion and extension during gait. In two rats ipsilateral flexion responses are noted, but these are not clearly demonstrated to be independent of the contralateral homologous cortex remaining intact.

Strengths:<br /> This paper adds to prior data on cortical microstimulation by the laboratory in interesting ways. First, the strong effects of the spared crossed fibers from the ipsi-lesional cortex in parts of the ipsi-lesion leg's step cycle and weight support function are solidly demonstrated. This raises the interesting possibility that stimulating the contra-lesion cortex as reported previously may execute some of its effects through callosal coordination with the ipsi-lesion cortex tested here. This is not fully discussed by the authors but may represent a significant aspect of these data. The authors demonstrate solidly that ablation of the contra-lesional cortex does not impede the effects reported here. I believe this has not been shown for the contra-lesional cortex microstimulation effects reported earlier, but I may be wrong.

Effects and neuroprosthetic control of these effects are explored well in the ipsi-lesion cortex tests here.

Weaknesses:<br /> Some data is based on very few rats. For example (N=2) for ipsilateral flexion effects of microstimulation. N=3 for homologous cortex ablation, and only ipsi extension is tested it seems. There is no explicit demonstration that the ipsilateral flexion effects in only 2 rats reported can survive the contra-lateral cortex ablation.

Some improvements in clarity and precision of descriptions are needed, as well as fuller definitions of terms and algorithms.

Likely Impacts:<br /> This data adds in significant ways to prior work by the authors, and an understanding of how phased stimulation in cortical neuroprosthetics may aid in recovery of function after SCI, especially if a few ambiguities in writing and interpretation are fully resolved.

Reviewer #3 (Public Review):

Summary:<br /> This article aims to investigate the impact of neuroprosthesis (intracortical microstimulation) implanted unilaterally on the lesion side in the context of locomotor recovery following unilateral thoracic spinal cord injury.

Strength:<br /> The study reveals that stimulating the left motor cortex, on the same side as the lesion, not only activates the expected right (contralateral) muscle activity but also influences unexpected muscle activity on the left (ipsilateral) side. These muscle activities resulted in a substantial enhancement in lift during the swing phase of the contralateral limb and improved trunk-limb support for the ipsilateral limb. They used different experimental and stimulation conditions to show the ipsilateral limb control evoked by the stimulation. This outcome holds significance, shedding light on the engagement of the "contralateral projecting" corticospinal tract in activating not only the contralateral but also the ipsilateral spinal network.

The experimental design and findings align with the investigation of the stimulation effect of contralateral projecting corticospinal tracts. They carefully examined the recovery of ipsilateral limb control with motor maps. They also tested the effective sites of cortical stimulation. The study successfully demonstrates the impact of electrical stimulation on the contralateral projecting neurons on ipsilateral limb control during locomotion, as well as identifying important stimulation spots for such an effect. These results contribute to our understanding of how these neurons influence bilateral spinal circuitry. The study's findings contribute valuable insights to the broader neuroscience and rehabilitation communities.

Weakness:<br /> The term "ipsilateral" lacks a clear definition in the title, abstract, introduction, and discussion, potentially causing confusion for the reader.

The unexpected ipsilateral (left) muscle activity is most likely due to the left corticospinal neurons recruiting not only the right spinal network but also the left spinal network. This is probably due to the joint efforts of the neuroprosthesis and activation of spinal motor networks which work bilaterally at the spinal level.

However, in my opinion, readers can easily link the ipsilateral cortical network to the ipsilateral-projecting corticospinal tract, which is less likely to play a role in ipsilateral limb control in this study since this tract is disrupted by the thoracic spinal injury.

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.

Reviewer #2 (Public Review):

Summary:<br /> This is a fundamental and elegant study showing the role of BMP signaling in cerebellar development. This is an important question because there are multiple diseases, including aggressive childhood cancers, which involve granule cell precursors. Thus understanding of the factors that govern the formation of the granule cell layer is important both from a basic science and a disease perspective.

Overall, the manuscript is clear and well-written. The figures are extremely clear, wonderfully informative, and overall quite beautiful.

Figures 1-3 show the experimental design and report how BMP activity is altered over development in both the chick and the human developing cerebellum. Both data are very impressive and convincing.

They then go on to modulate BMP activity in the developing chick, using a complex electroporation paradigm that allows them to label cells with GFP as well as with cell-specific reporters of BMP activity levels. They bidirectionally modulate BMP levels and then can look at both cell-specific and non-specific alterations in the formation of the external and internal granule cell layer, across different developmental timepoints. These are really elegant and rigorous experiments, as they look at both sagittal and transverse sections to collect this data. This makes the data extremely compelling. With these rigorous techniques, they show that BMP signaling serves more than one function across development: it is involved in the initial tangential migration from the rhombic lip, but at a later time, both up- and down-regulation of BMP activity reduces the density of amplifying cells in the external granule cell layer.

Strengths:<br /> Overall, I think the paper is interesting and important and the data is strong. The use of both chick and human tissue strengthens the findings. They are extremely rigorous, analyzing data from multiple planes at multiple ages, which also really strengthens their findings. The dual electroporation approach is extremely elegant, providing beautiful visual representations of their findings.

Weaknesses:<br /> I find no significant weaknesses.

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.

Reviewer #2 (Public Review):

Summary:

H2S is a gas that is toxic to many animals and causes avoidance in animals such as C. elegans. The authors show that H2S increases the frequency of turning and the speed of locomotion. The response was shown to be modulated by a number of neurons and signaling pathways as well as by ambient oxygen concentrations. The long-term adaptation involved gene expression changes that may be related to iron homeostasis as well as the homeostasis of mitochondria.

Strengths:

Overall, the authors provide many pieces that will be important for solving how H2S signals through neuronal circuits to change gene expression and physiological programs. The experiments rely mostly on a behavioral assay that measures the increase of locomotion speed upon exposure to H2S. This assay is then combined with manipulations of environmental factors, different wild-type strains, and mutants. The mutants analyzed were obtained as candidates from the literature and from transcriptional profiling that the authors carried out in worms that were exposed to H2S. These studies imply several genetic signaling pathways, some neurons, and metabolism-related factors in the response to H2S. Hence the data provided should be useful for the field.

Weaknesses:

On the other hand, many important aspects of the underlying mechanisms remain unsolved and the reader is left with many loose ends. For example, it is not clear how H2S is actually sensed, how sensory neurons are activated and signal to downstream circuits, and what the role of ciliated and RMG neurons is in this circuit. It remains unclear how signals lead to gene expression and physiological changes such as metabolic rewiring. Solving all this would clearly be beyond the scope of a single manuscript. Yet, the manuscript also does not focus on understanding one of these central aspects and rather is all over the place, which makes it harder to understand for readouts that are not in this core field. Multiple additional methods and approaches exist to dig deeper into these mechanisms in the future, such as neuronal calcium imaging, optogenetics, and metabolic analysis. To generate a story that will be interesting to a broad readership substantial additional experimentation would be required. Further, in the current manuscript, it is often difficult to understand the rationales of the experiments, why they were carried out, and how to place them into a context. This could be improved in terms of documentation, narration/explanation, and visualization.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript explores the behavioral responses of C. elegans to hydrogen sulfide, which is known to exert remarkable effects on animal physiology in a range of contexts. The possibility of genetic and precise neuronal dissection of responses to H2S motivates the study of responses in C. elegans. The manuscript is well-written in communicating the complex physiology around C. elegans behavioral responses to H2S and in appropriately citing prior and related relevant work.

There are three parts to the manuscript.

In the first, an immediate behavioral response-increased locomotory rate-upon exposure to H2S is characterized. The experimental conditions are critical, and data are obtained from exposure of animals to 150ppm H2S at 7% O2. The authors provide evidence that this is a chemosensory response to H2S, showing a requirement for genes encoding components of the cilia apparatus and implicating a role for tax-4 and daf-11. Neuron-specific rescue in the ASJ neurons suggests the ASJ neurons contribute to the response to H2S. One caveat is that previous work has shown that the dauer-constitutive phenotype of daf-11 mutants can be suppressed by ASJ ablation, suggesting that there may be pervasive changes in animal nervous system signaling that are ASJ-dependent in daf-11 mutants, which may indirectly alter chemosensory responses to H2S. More direct methods to assess whether ASJ senses H2S, e.g. using calcium imaging, would better assess a direct role for the ASJ neurons in a behavioral response to H2S. The authors also point out interesting parallels between the response to H2S and CO2 though provide some genetic data separating the two responses. Importantly, the authors note that when aerotaxis (O2-sensing and movement) in the presence of bacterial food is intact, as in npr-1 215F animals, the response to H2S is abrogated. Mutation in gcy-35 in the npr-1 215F background restores the H2S chemosensory response.

There is a second part of the paper that conducts transcriptional profiling of the response to H2S that corroborates and extends prior work in this area.

The final part of the paper is the most intriguing, but for me, also the most problematic. The authors examine how H2S-evoked locomotory behavioral responses are affected in mutants defective in the stress and detoxification response to H2S, most notably hif-1. Prior genetic studies have established the pathways leading to HIF-1 activation/stabilization, as well as potential downstream mechanisms. The authors conduct logical genetic analysis to complement studies of the hif-1 mutant and in part motivated by their transcriptional profiling studies, examine the role of iron sequestration/free iron in the locomotory response to H2S, and further speculate on how the behavior of mutants defective in mitochondrial function might be affected by exposure to H2S.

In some regard, this part of the manuscript is interesting because the analysis begins to connect how the behavior of an animal to a toxic compound is affected by mutations that affect sensitivity to the toxic compound. However, what is unclear is what is being studied at this point. In the context, of noting that H2S at 150ppm is known to be lethal, its addition to mutants clearly sensitized to its effects would be anticipated to have pervasive effects on animal physiology and nervous system function. The authors note that the continued increased locomotion of wild-type animals upon H2S exposure might be due to the byproducts of detoxification or the detrimental effects of H2S. The latter explanation seems much more likely, in which case what one may be observing is the effects of general animal sickness, or even a bit more specifically, neuronal dysfunction in the presence of a toxic compound, on locomotion. As such, what is unclear is what conclusions can be taken away from this part of the work.

Strengths:<br /> 1. Characterization of a motor behavior response to H2S<br /> 2. Transcriptional profiling of the response to H2S corroborating prior work.

Weaknesses:<br /> Unclear significance and experimental challenges regarding the study of locomotory responses to animals sensitized to the toxic effects of H2S under exposure to H2S.

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.

Reviewer #2 (Public Review):

Summary:<br /> Authors hypothesized that modulation of KNa1.1 channel specifically in inhibitory interneurons contributes to the hyperactivity of neurons in the peripheral cortex at the lesion site, enhances seizure susceptibility to PTZ-induced seizures, and promotes the occurrence of PTE. They test this hypothesis in a mouse model of TBI induced by controlled cortical impact in wild-type and kcnt1 knock-out (KO) mice. The authors performed a series of experiments including behavioral assessment, electrographic recordings in vivo and in vitro, western blotting, and immunofluorescence imaging with the goal of investigating the contributory role of KNa1.1 channel to post-traumatic epileptogenesis.

Strengths:<br /> The hypothesis is innovative, focusing on the specific role of the KNa1.1 channel in the development of PTE post-TBI. The use of a comprehensive set of techniques, including EEG, whole cell patch clamp, western blot, immunofluorescence imaging, and behavioral assessments, provides a diverse data set. The study makes initial steps in correlating specific molecular changes with functional outcomes in TBI models, offering potential pathways for therapeutic intervention.

Weaknesses:<br /> 1) The study presents interesting findings on early changes in protein expression and electrophysiological properties following TBI. However, I would like to draw attention to the timeline of EEG and cellular assessments that require further clarification or consideration. The patch clamp recordings and other assays were conducted within 14 days post-TBI, while EEG recordings with or without PTZ testing were performed at 3 months post-injury. This temporal gap leaves a period where changes in electrophysiological properties and PTE status are not accounted for. Since epileptogenesis post-TBI involves a dynamic process spanning from hyperacute and acute phases to chronic development, capturing these changes continuously or at least at more frequent intervals (on and off bi-weekly) could provide a more comprehensive understanding of this progression. In the current study design, the one-week duration of EEG recordings at the 3-month timepoint raises the possibility that some seizures might have occurred undetected between the early post-injury phase and the EEG recording period. This gap could potentially affect the interpretation of results, especially when correlating early post-injury cellular changes with later seizure activity and thresholds and hence is a significant limitation to data interpretation. Experiments using western blots, immunofluorescence, and patch clamp were done at an early timepoint hence the relevance of these datasets to PTE status outcome is not established.

2) While referencing Nichols et al., 2015, to justify the 14-day timeline for characterizing seizures is understandable, it is important to consider differences in animal models (juvenile rats in Nichols vs. adult mice in the present study) which might influence the generalizability of the findings.

3) Behavior: Authors performed behavioral assays using the rotarod technique evaluating the hanging time of mice with different severity of TBI (mild, moderate, severe). The purpose of the testing is explained as 'to sort out an appropriate TBI model'. The authors also measured mortality rates 'to attain a stable model'. It is not clear what is assumed by the terms 'appropriate' or 'stable' model. Furthermore, the relevance of this to post-traumatic epileptogenesis is unclear. Additionally, the mortality in the Sham group within 2 weeks of craniectomy is not explained.

4) Seizure assessment: authors report seizure severity in PTZ-induced seizures but no mention about the severity of spontaneous seizures between different TBI severity modalities. When characterizing the PTZ-induced seizures, the mild TBI group does not have generalized seizures. Does this mean that al all 6 tested animals in the mild TBI group had exclusively focal seizures? What about the spontaneous seizure occurrence: were all seizures generalized or were any focal too? Did that differ between mild, moderate, and severe TBI?

5) Experiments with KCNT1 KO mice: in all experiments with a mutant mouse line, authors only used them in TBI group. Without the Sham group, it is difficult to discern whether any observed changes in seizure susceptibility in the KCNT1 KO TBI group are due to gene deletion, the TBI, or a combination of both. This group would provide a crucial comparison point to isolate the effects of the KCNT1 knockout from those of TBI. This limits the ability to make comprehensive conclusions about the role of the KCNT1 gene in seizure susceptibility following TBI.

6) While the current study showed interesting data about the KNa1.1 changes early after TBI, the study design and disconnect between early and late electrophysiology experiments timeline, does not establish a correlative or causative link between KNa1.1 and post-traumatic epileptogenesis since it remained unresolved whether KCNT1 KO mice developed no PTE (or less severe/ less frequent seizures at 3 months) compared with WT mice and what are the seizure properties of KCNT1 KO Sham mice compared to WT TBI and Sham groups. The hypothesis was that modulation of KNa1.1 channel specifically in inhibitory interneurons contributes to the hyperactivity of neurons in the peripheral cortex at the lesion site, enhances seizure susceptibility to PTZ-induced seizures, and promotes the occurrence of PTE. The part about 'promotes the occurrence of PTE' was not established.

7) NeuN is not the best marker of neurons in the context of TBI since TBI affects its expression patterns which will influence the interpretation of co-localization results. Unlike NeuN, Nissl staining is less likely to be affected by factors that alter protein expression, such as TBI. Therefore, it can be a more stable marker for identifying neurons in injured brain tissue.

8) Statistics: Authors report only SEM, which shows the precision of the mean and it will decrease as the sample size increases and does not reflect the data variability.

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.

Reviewer #2 (Public Review):

In this study, Leighton et al performed remarkable experiments by combining in-vivo patch-clamp recording with two-photon dendritic Ca2+ imaging. The voltage-clamp mode is a major improvement over the pioneer versions of this combinatorial experiment that has led to major breakthroughs in the neuroscience field for visualizing and understanding synaptic input activities in single cells in-vivo (sharp electrodes: Svoboda et al, Nature 1997, Helmchen et al, Nature Neurosci 1999; whole-cell current-clamp: Jia et al, Nature 2010, Chen et al, Nature 2011. I suggest that these papers would be cited). This is because in voltage-clamp mode, despite the full control of membrane voltage in-vivo not being realistic, is nevertheless most effective in preventing back-propagation action potentials, which would severely confound the measurement of individual synaptically-induced Ca2+ influx events. Furthermore, clamping the cell body at a strongly depolarized potential (here the authors did -30mV) also facilitates the detection of synaptically-induced Ca2+ influx. As a result, the authors successfully recorded high-quality Ca2+ imaging data that can be used for precise analysis. To date, even in view of the rapid progress of voltage-sensitive indicators and relevant imaging technologies in recent years, this very old 'art' of combining single-cell electrophysiology and two-photon imaging (ordinary, raster-scanned, video-rate imaging) of Ca2+ signals still enables measurements of the best-level precision.

On the other hand, the interpretation of data in this study is a bit narrow-minded and lacks a comprehensive picture. Some suggestions to improve the manuscript are as follows:

1. The authors made a segregation of 'spine synapse' and 'shaft synapse' based solely on the two-photon images in-vivo. However, caution shall be taken here, because the optical resolution under in-vivo imaging conditions like this cannot reliably tell apart whether a bright spot within or partially overlapping a segment of the dendrite is a spine on top of (or below) it. Therefore, what the authors consider as a 'shaft synapse' (by detecting Ca2+ hotspots) has an unknown probability of being just a spine on top or below the dendrite. If there is other imaging data of higher axial resolution to validate or calibrate, the authors shall take some further considerations or analysis to check the consistency of their data, as the authors do need such a segregation between spine and shaft synapses to show how they evolve over the brain development stages.

2. The use of terminology 'bursts of spontaneous inputs' for describing voltage-clamp data seems improper. Conventionally, 'burst' refers to suprathreshold spike firing events, but here, the authors use 'burst' to refer to inward synaptic currents collected at the cell body. Not every excitatory synaptic input (or ensemble of inputs) activation will lead to spike firing under naturalistic conditions, therefore, these two concepts are not equivalent. It is recommended to use 'barrage of inputs' instead of 'burst of inputs'. Imagine a full picture of the entire dendritic tree, the fact that the authors could always capture spontaneous Ca2+ events here and there within a few pieces of dendrites within an arbitrary field-of-view suggests that, the whole dendritic tree must have many more such events going on as a barrage while the author's patch electrode picks up the summed current flow from the whole dendritic tree.

3. Following the above issue, an analysis of the temporal correlation between synaptic (not segregating 'spine' or 'shaft') Ca2+ events and EPSCs is absent. Again, the authors drew arbitrary time windows to clump the events for statistical analysis. However, the demonstrated example data already shows that the onset times of individual synaptic Ca2+ events do not necessarily align with the beginning of a 'barrage' inward current event.

4. The authors claim that "these observations indicate that the activity patterns investigated here are not or only slightly affected by low-level anesthesia". It would be nice to show some of the recordings in this work without any anesthesia to support this claim.

Reviewer #3 (Public Review):

Summary:<br /> There is a growing body of literature on the clustering of co-active synapses in adult mice, which has important implications for understanding dendritic integration and sensory processing more broadly. However, it has been unclear when this spatial organization of co-active synapses arises during development. In this manuscript, Leighton et al. investigate the emergence of spatially organized, co-active synapses on pyramidal dendrites in the mouse visual cortex before eye-opening. They find that some dendrite segments contain highly active synapses that are co-active with their neighbors as early as postnatal day (P) 8-10, and that these domains of co-active synapses increase their coverage of the dendritic arbor by P12-13. Interestingly, Leighton et al. demonstrate that synapses co-active with their neighbors are more likely to increase their activity across a single recording session, compared to synapses that are not co-active with their neighbors, suggesting local plasticity driven by coincident activity before eye-opening.

The current manuscript includes some replication of earlier results from the same research group (Winnubst et al., 2015), including the presence of clustered, co-active synapses in the visual cortex of mouse pups, and the finding that synapses co-active with their neighbors show an increase in transmission frequency during a recording session. The main novelty in the current study compared to Winnubst et al. (2015) is the inclusion of younger animals (P8-13 in the current study compared to P10-15 in Winnubst et al., 2015). The current manuscript is the first demonstration that active synapses are clustered on specific dendrite segments as early as P8-10 in the mouse visual cortex, and the first to show the progression in active synapse distribution along the dendrite during the 2nd postnatal week. These results from the visual cortex may help inform our understanding of sensory development more broadly.

Strengths:<br /> The authors ask a novel question about the emergence of synaptic spatial organization, and they use well-chosen techniques that directly address their questions despite the challenging nature of these techniques. To capture both structural and functional information from dendrites simultaneously, the authors performed a whole-cell voltage clamp to record synaptic currents arriving at the soma while imaging calcium influx at individual synaptic sites on dendrites. The simultaneous voltage clamp and calcium imaging allowed the authors to isolate individual synaptic inputs without their occlusion by widespread calcium influx from back-propagating action potentials. Achieving in vivo dendrite imaging in live mice that are as young as P8 is challenging, and the resulting data provides a unique view of synaptic activity along individual dendrites in the visual cortex at an early stage in development that is otherwise difficult to assess.

The authors provide convincing evidence that synapses are more likely to be co-active with their neighbors compared to synapses located farther away (Fig. 6F-H), and that synapses co-active with their neighbors increase their transmission frequency during a recording session (Figure 7C). These findings are particularly interesting given that the recordings occur before eye-opening, suggesting a relationship between co-activity and local synaptic plasticity even before the onset of detailed visual input. These results replicate previously published findings from P10-15 pups (Winnubst et al., 2015), increasing confidence in the reproducibility of the data.

The authors also provide novel data documenting for the first time spatially organized, co-active synapses in pups as young as P8. Comparing the younger (P8-10) and older (P12-13) pups, provides insight into how clusters of co-active synapses might emerge during development.

Weaknesses:<br /> This manuscript provides insufficient detail for assessing the rigor and reproducibility of the methods, particularly for age comparisons. The P8-10 vs P12-13 age comparisons are the primary novel finding in this manuscript, and it is, therefore, critical to avoid systematic age differences in the methods and analysis whenever possible. Specific concerns related to the age comparisons are listed below:

• Given that the same research group previously published P12-13 data (Winnubst et al., 2015), it is unclear whether both age groups in the current study were imaged/analyzed in parallel by the same researcher(s), or whether previous data was used for the P12-13 group.

• The authors mention that they used 2 different microscopes, and used a fairly wide range of imaging frame rates (5-15 Hz). It is unclear from the current manuscript whether the same imaging parameters were used across the two age groups. If data for the two experimental groups was collected separately, perhaps at different times, by a different person, or on a different microscope, there is a concern that some differences between the groups may not necessarily be due to age.

• It is unclear whether the image analysis was performed blind to age. Blinding to age during analysis is particularly important for this study, in which it was not possible to blind to age during imaging due to visible differences in size and developmental stage between younger and older pups.

• The relatively low N (where N is the number of dendrites or the number of mice) in this study is acceptable due to the challenging nature of the techniques used, but unintentional sampling bias is a concern. For example, if higher-order dendrites from the apical tuft were imaged at P12-13, while more segments of the apical trunk were imaged at P8-10, this could inadvertently create apparent age differences that were in fact due to dendrite location on the arbor or dendrite depth.

Additional general methodological concerns, which are not specifically related to the age comparisons, are listed below:

• The authors assert that clustered, co-active synapses emerge in the visual cortex before eye-opening, which is an important finding in that it suggests this phenomenon is driven by spontaneous activity rather than visual input. However, this finding hinges on the imaged cells being reliably located in the visual cortex, which is difficult to identify with certainty in animals that have not yet opened their eyes and therefore cannot undergo intrinsic signal imaging to demarcate the boundaries of the visual cortex. If the imaged cells were in, for example, nearby somatosensory cortex, then the observed spatial organization could be due to sensory input rather than spontaneous activity.

• It is unclear how the authors defined a synaptic transmission event in the GCaMP signal (e.g. whether there was a quantitative deltaF/F threshold).

• The authors' division of synapses into spine vs shaft is unconvincing due to the difficulty of identifying Z-projecting spines in images from 2-photon microscopy, where the Z resolution is insufficient to definitively identify Z-projecting spines, and the fact that spines in young animals may be thin and dim. The authors' examples of spine synapses (e.g. in Fig. 2A) are convincing, but some of the putative shaft synapses may in fact be on spines.

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.

Reviewer #2 (Public Review):

Summary: The study by Jaime-Tobon & Moser is a truly major effort to bridge the gap between classical observations on how auditory neurons respond to sounds and the synaptic basis of these phenomena. The so-called spiral ganglion neurons (SGNs) are the primary auditory neurons connecting the brain with hair cells in the cochlea. They all respond to sounds increasing their firing rates, but also present multiple heterogeneities. For instance, some present a low threshold to sound intensity, whereas others have high threshold. This property inversely correlates with the spontaneous rate, i.e., the rate at which each neuron fires in the absence of any acoustic input. These characteristics, along with others, have been studied by many reports over the years. However, the mechanisms that allow the hair cells-SGN synapses to drive these behaviors are not fully understood.

Strengths:<br /> The level of experimental complexity described in this manuscript is unparalleled, producing data that is hardly found elsewhere. The authors provide strong proof for heterogeneity in transmitter release thresholds at individual synapses and they do so in extremely complex experimental settings. In addition, the authors found other specific differences such as in synaptic latency and max EPSCs. A reasonable effort is put into bridging these observations with those extensively reported in in vivo SGNs recordings. Similarities are many and differences are not particularly worrying as experimental conditions cannot be perfectly matched, despite the authors' efforts in minimizing them.

Weaknesses:<br /> Some concern surges in relation to mismatches with previous reports of IHC-SGN synapses function. EPSCs at these synapses present a peculiar distribution of amplitudes, shapes, and rates. These characteristics are well-established and some do not seem to be paralleled in this study. Here, amplitude distributions are drastically shifted to smaller values, and rates of events are very low, all compared with previous evidence. The reasons for these discrepancies are unclear. The rate at which spontaneous EPSCs appear is an especially sensitive matter. A great part of the conclusions relies on the definition of which of the SGNs (or should say synapses) belong to the low end and which to the high end in the spectrum of spontaneous rates. The data presented by the authors seem a bit off and the criteria used to classify recordings are not well justified. The authors should clarify the origin of these differences since they do not seem to come from obvious reasons such as animal ages, recording techniques, mouse strain, or even species.

Reviewer #3 (Public Review):

Summary:

"Bridging the gap between presynaptic hair cell function and neural sound encoding" by Jaime Tobon and Moser uses patch-clamp electrophysiology in cochlear preparations to probe the pre- and post-synaptic specializations that give rise to the diverse activity of spiral ganglion afferent neurons (SGN). The experiments are quite an achievement! They use paired recordings from pre-synaptic cochlear inner hair cells (IHC) that allow precise control of voltage and therefore calcium influx, with post-synaptic recordings from type I SGN boutons directly opposed to the IHC for both presynaptic control of membrane voltage and post-synaptic measurement of synaptic function with great temporal resolution.

Strengths<br /> Any of these techniques by themselves are challenging, but the authors do them in pairs, at physiological temperatures, and in hearing animals, all of which combined make these experiments a real tour de force. The data is carefully analyzed and presented, and the results are convincing. In particular, the authors demonstrate that post-synaptic features that contribute to the spontaneous rate (SR) of predominantly monophasic post-synaptic currents (PSCs), shorter EPSC latency, and higher PSC rates are directly paired with pre-synaptic features such as a lower IHC voltage activation and tighter calcium channel coupling for release to give a higher probability of release and subsequent increase in synaptic depression. Importantly, IHCs paired with Low and High SR afferent fibers had the same total calcium currents, indicating that the same IHC can connect to both low and high SR fibers. These fibers also followed expected organizational patterns, with high SR fibers primarily contacting the pillar IHC face and low SR fibers primarily contacting the modiolar face. The authors also use in vivo-like stimulation paradigms to show different RRP and release dynamics that are similar to results from SGN in vivo recordings. Overall, this work systematically examines many features giving rise to specializations and diversity of SGN neurons.

Weaknesses / Comments / edits:<br /> 1) The careful analysis of calcium coupling and EPSC metrics is especially nice. Can the authors speculate as to why different synapses (likely in the same IHC) would have different calcium cooperativity?

2) On the bottom of page 6 it would be helpful to mention earlier how many pillar vs modiolar fibers were recorded from, otherwise the skewness of SRs (figure 2H could be thought to be due to predominantly recordings from modiolar fibers. As is, it reads a bit like a cliff-hanger.

3) The contrasts for some of the data could be used to point out that while significant differences occur between low and high SR fibers, some of these differences are no longer apparent when comparing modiolar vs pillar fibers (eg by contrasting Figure 2C and 2K). This can indicate that indeed there are differences between the fiber activity, but that the activity likely exists in a gradient across the hair cell faces. Pointing this out at the top of page 10 (end of the first paragraph) would be helpful, it would make the seemingly contradictory voltage-dependence data easier to understand on first read (voltage-dependence of release is significantly different between different SR fibers (figure 3) but is not significantly different between fibers on different HC faces (figure S3).

4) It should be acknowledged that although the use of post-hearing animals here (P14-23) ensures that SGN have begun to develop more mature activity patterns (Grant et al 2010), the features of the synapses and SGN activity may not be completely mature (Wu et al 2016 PMID: 27733610). Could this explain some of the 'challenges' (authors' section title) detailed on page 28, first full paragraph?

5) In the discussion on page 24, the authors compare their recorded SR of EPSCs to measure values in vivo which are higher. Could this indicate that in vivo, the resting membrane potential of IHCs is more depolarized than is currently used for in vitro cochlear experiments?

6) The results showing lower calcium cooperativity of high SR fibers are powerful, but do the authors have an explanation for why the calcium cooperativity of < 2 is different from that (m = 3-4) observed in other manuscripts?

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.

Reviewer #2 (Public Review):

Summary:

In this paper, Sang et al. set out to identify gustatory receptors involved in salt taste sensation in Drosophila melanogaster. In a two-choice assay screen of 30 Ir mutants, they identified that Ir60b is required for avoidance of high salt. In addition, they demonstrate that activation of Ir60b neurons is sufficient for gustatory avoidance using either optogenetics or TRPV1 to specifically activate Ir60b neurons. Then, using tip recordings of labellar gustatory sensory neurons and proboscis extension response behavioral assays in Ir60b mutants, the authors demonstrate that Ir60b is dispensable for labellar taste neuron responses to high salt and the suppression of proboscis extension by high salt. Since external gustatory receptor neurons (GRNs) are not implicated, they look at Poxn mutants, which lack external chemosensory sensilla but have intact pharyngeal GRNs. High salt avoidance was reduced in Poxn mutants but was still greater than Ir60b mutants, suggesting that pharyngeal gustatory sensory neurons alone are sufficient for high salt avoidance. The authors use a new behavioral assay to demonstrate that Ir60b mutants ingest a higher volume of sucrose mixed with high salt than control flies do, suggesting that the action of Ir60b is to limit high salt ingestion. Finally, they identify that Ir60b functions within a single pair of gustatory sensory neurons in the pharynx, and that these neurons respond to high salt but not bitter tastants.

Strengths:

A great strength of this paper is that it rigorously corroborates previously published studies that have implicated specific Irs in salt taste sensation. It further introduces a new role for Ir60b in limiting high salt ingestion, demonstrating that Ir60b is necessary and sufficient for high salt avoidance and convincingly tracing the action of Ir60b to a particular subset of gustatory receptor neurons. Overall the authors have achieved their aim by identifying a new gustatory receptor involved in limiting high salt ingestion. They use rigorous genetic, imaging, and behavioral studies to achieve this aim, often confirming a given conclusion with multiple experimental approaches. They have further done a great service to the field by replicating published studies and corroborating the roles of a number of other Irs in salt taste sensation. An aspect of this study that merits further investigation is how the same gustatory receptor neurons and Ir in the pharynx can be responsible for regulating the ingestion of both appetitive (sugar) and aversive tastants (high salt).

Weaknesses:

There are several weaknesses that, if addressed, could greatly improve this work.<br /> 1) The authors combine the results and discussion but provide a very limited interpretation of their results. More discussion of the results would help to highlight what this paper contributes, how the authors interpret their results, and areas for future study.<br /> 2) The authors rename previously studied populations of labellar GRNs to arbitrary letters, which makes it difficult to understand the experiments and results in some places. These GRN populations would be better referred to according to the gustatory receptors they are known to express.<br /> 3) The conclusion that GRNs responsible for high salt aversion may be inhibited by those that function in low salt attraction is not well substantiated. This conclusion seems to come from the fact that overexpression of Ir60b in salt attraction and salt aversion sensory neurons still leads to salt aversion, but there need not be any interaction between these two types of sensory neurons if they act oppositely on downstream circuits.<br /> 4) The authors rely heavily on a new Droso-X behavioral apparatus that is not sufficiently described here or in the previous paper the authors cite. This greatly limits the reader's ability to interpret the results.

Reviewer #3 (Public Review):

Summary:<br /> Sang et al. successfully demonstrate that a set of single sensory neurons in the pharynx of _Drosophila_ promotes avoidance of food with high salt concentrations, complementing previous findings on Ir7c neurons with an additional internal sensing mechanism. The experiments are well-conducted and presented, convincingly supporting their important findings and extending the understanding of internal sensing mechanisms. However, a few suggestions could enhance the clarity of the work.

Strengths:<br /> The authors convincingly demonstrate the avoidance phenotype using different behavioral assays, thus comprehensively analyzing different aspects of the behavior. The experiments are straightforward and well-contextualized within existing literature.

Weaknesses:<br /> Discussion<br /> While the authors effectively relate their findings to existing literature, expanding the discussion on the surprising role of Ir60b neurons in both sucrose and salt rejection would add depth. Additionally, considering Yang et al. 2021's (https://doi.org/10.1016/j.celrep.2021.109983) result that Ir60b neurons activate feeding-promoting IN1 neurons, the authors should discuss how this aligns with their own findings.

Lines 187ff: The discussion primarily focuses on taste sensillae outside the labellum, neglecting peg-type sensillae on the inner surface. Clarification on whether these pegs contribute to the described behaviors and if the Poxn mutants described also affect the pegs would strengthen the discussion.

In line 261 the authors state: "We attempted to induce salt activation in the I-type sensilla by ectopically expressing Ir60b, similar to what was observed with Ir56b 8; however, this did not generate a salt receptor (Figures S6A)"<br /> An obvious explanation would be that these neurons are missing the identified necessary co-receptors Ir76b and Ir25a. The authors should discuss here if the Gr33a neurons they target also express these co-receptors, if yes this would strengthen their conclusion that an additional receptor might be missing.

Methods<br /> The description of the Droso-X assay seems to be missing some details. Currently, it is not obvious how the two-choice is established. Only one capillary is mentioned, I assume there were two used? Also, the meaning of the variables used in the equation (DrosoX and DrosoXD) are not explained.

The description of the ex-vivo calcium imaging prep. is unclear in several points:<br /> 1. It is lacking information on how the stimulus was applied (was it manually washed in? If so how was it removed?).<br /> 2. The authors write: "A mild swallow deep well was prepared for sample fixation." I assume they might have wanted to describe a "shallow well"?<br /> 3. "...followed by excising a small portion of the labellum in the extended proboscis region to facilitate tastant access to pharyngeal organs." It is not clear to me how one would excise a small portion of the labellum, the labellum depicts the most distal part of the proboscis that carries the sensillae and pegs. Did the authors mean to say that they cut a part of the proboscis?

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.

Reviewer #2 (Public Review):

Summary:

In the present manuscript, Zhang et al utilize single-nuclei RNA-Seq to investigate the heterogeneity of perirenal adipose tissue. The perirenal depot is interesting because it contains both brown and white adipocytes, a subset of which undergo functional "whitening" during early development. While adipocyte thermogenic transdifferentiation has been previously reported, there remain many unanswered questions regarding this phenomenon and the mechanisms by which it is regulated.

Strengths:

The combination of UCP1-lineage tracing with the single nuclei analysis allowed the authors to identify four populations of adipocytes with differing thermogenic potential, including a "whitened" adipocyte (mPRAT-ad2) that retains the capacity to rapidly revert to a brown phenotype upon cold exposure. They also identify two populations of white adipocytes that do not undergo browning with acute cold exposure.

Anatomically distinct adipose depots display interesting functional differences, and this work contributes to our understanding of one of the few brown depots present in humans.

Weaknesses:

The most interesting aspect of this work is the identification of a highly plastic mature adipocyte population with the capacity to switch between a white and brown phenotype. The authors attempt to identify the transcriptional signature of this ad2 subpopulation, however, the limited sequencing depth of single nuclei somewhat lessens the impact of these findings. Furthermore, the lack of any form of mechanistic investigation into the regulation of mPRAT whitening limits the utility of this manuscript. However, the combination of well-executed lineage tracing with comprehensive cross-depot single-nuclei presented in this manuscript could still serve as a useful reference for the field.

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?

Reviewer #2 (Public Review):

This study by Matsuo-Takasaki et al. reported the development of a novel suspension culture system for hiPSC maintenance using Wnt/PKC inhibitors. The authors showed elegantly that inhibition of the Wnt and PKC signaling pathways would repress spontaneous differentiation into neuroectoderm and mesendoderm in hiPSCs, thereby maintaining cell pluripotency in suspension culture. This is a solid study with substantial data to demonstrate the quality of the hiPSC maintained in the suspension culture system, including long-term maintenance in >10 passages, robust effect in multiple hiPSC lines, and a panel of conventional hiPSC QC assays. Notably, large-scale expansion of a clinical grade hiPSC using a bioreactor was also demonstrated, which highlighted the translational value of the findings here. In addition, the author demonstrated a wide range of applications for the IWR1+LY suspension culture system, including support for freezing/thawing and PBMC-iPSC generation in suspension culture format. The novel suspension culture system reported here is exciting, with significant implications in simplifying the current culture method of iPSC and upscaling iPSC manufacturing.

Another potential advantage that perhaps wasn't well discussed in the manuscript is the reported suspension culture system does not require additional ECM to provide biophysical support for iPSC, which differentiates from previous studies using hydrogel and this should further simplify the hiPSC culture protocol.

Interestingly, although several hiPSC suspension media are currently available commercially, the content of these suspension media remained proprietary, as such the signaling that represses differentiation/maintains pluripotency in hiPSC suspension culture remained unclear. This study provided clear evidence that inhibition of the Wnt/PKC pathways is critical to repress spontaneous differentiation in hiPSC suspension culture.

I have several concerns that the authors should address, in particular, it is important to benchmark the reported suspension system with the current conventional culture system (eg adherent feeder-free culture), which will be important to evaluate the usefulness of the reported suspension system. Also, the manuscript lacks a clear description of a consistent robust effect in hiPSC maintenance across multiple cell lines. There are also several minor comments that should be addressed to improve readability, including some modifications to the wording to better reflect the results and conclusions.

Reviewer #3 (Public Review):

In the current manuscript, Matsuo-Takasaki et al. have demonstrated that the addition of PKCβ and WNT signaling pathway inhibitors to the suspension cultures of iPSCs suppresses spontaneous differentiation. These conditions are suitable for large-scale expansion of iPSCs. The authors have shown that they can perform single-cell cloning, direct cryopreservation, and iPSC derivation from PBMCs in these conditions. Moreover, the authors have performed a thorough characterization of iPSCs cultured in these conditions, including an assessment of undifferentiated stem cell markers and genetic stability. The authors have elegantly shown that iPSCs cultured in these conditions can be differentiated into derivatives of three germ layers. By differentiating iPSCs into dopaminergic neural progenitors, cardiomyocytes, and hepatocytes they have shown that differentiation is comparable to adherent cultures. This new method of expanding iPSCs will benefit the clinical applications of iPSCs.

Recently, multiple protocols have been optimized for culturing human pluripotent stem cells in suspension conditions and their expansion. Additionally, a variety of commercially available media for suspension cultures are also accessible. However, the authors have not adequately justified why their conditions are superior to previously published protocols (indicated in Table 1) and commercially available media. They have not conducted direct comparisons. Additionally, the authors have not adequately addressed the observed variability among iPSC lines. While they claim in the Materials and Methods section to have tested multiple pluripotent stem cell lines, they do not clarify in the Results section which line they used for specific experiments and the rationale behind their choices. There is a lack of comparison among the different cell lines. It would also be beneficial to include testing with human embryonic stem cell lines. Additionally, there is a lack of information regarding the specific role of the two small molecules in these conditions. The authors have not attempted to elucidate the underlying mechanism other than RNA expression analysis.

For these reasons some aspects of the manuscript need to be extended:

1. It is crucial for authors to specify the culture media used for suspension cultures. In the Materials and Methods section, the authors mentioned that cells in suspension were cultured in either StemFit AK02N medium, 415 StemFit AK03N (Cat# AK03N, Ajinomoto, Co., Ltd., Tokyo, Japan), or StemScale PSC416 suspension medium (A4965001, Thermo Fisher Scientific, MA, USA). The authors should clarify in the text which medium was used for suspension cultures and whether they observed any differences among these media.

2. In the Materials and Methods section, the authors mentioned that they used multiple cell lines for this study. However, it is not clear in the text which cell lines were used for various experiments. Since there is considerable variation among iPSC lines, I suggest that the authors simultaneously compare 2 to 3 pluripotent stem cell lines for expansion, differentiation, etc.

3. Single-cell sorting can be confusing. Can iPSCs grown in suspensions be single-cell sorted? Additionally, what was the cloning efficiency? The cloning efficiency should be compared with adherent cultures.

4. The authors have not addressed the naïve pluripotent state in their suspension cultures, even though PKC inhibition has been shown to drive cells toward this state. I suggest the authors measure the expression of a few naïve pluripotent state markers and compare them with adherent cultures

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.

Reviewer #2 (Public Review):

Summary:

The authors have developed novel Ovalbumin model (OTII) peptide that can be labeled with a site-specific FlAsH dye to track agonist peptides both in vitro and in vivo. The utility of this tool could allow better tracking of activated polyclonal T cells particularly in novel systems. The authors have provided solid evidence that peptides are functional, capable of activating OTII T cells, and these peptides can undergo trogocytosis by cognate T cells only.

Strengths:<br /> -An extensive array of in vitro and in vivo studies are used to assess peptide functionality.<br /> -Nice use of cutting edge intravital imaging,<br /> -internal controls such as multiple non-cogate T cells were used to improve robustness of the results<br /> -One of the strengths is the direct labeling of the peptide, and the potential utility in other systems.

Weaknesses:<br /> -Peptide labeling specificity and efficiency is not clear. High levels of background labeling. While it was sufficient for demonstrating the system works, it may pose problems depending on the peptide sequence, and/or use at lower dose.<br /> -Only one peptide system was tested, namely OVA323-339 region.<br /> -Limited novel biological findings. This study mostly describes a new tool that may have exciting potential.

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?

Reviewer #2 (Public Review):

Summary:

The goal of this study was to examine the role of FNDC5 in the response of the murine skeleton to either lactation or a calcium-deficient diet. The authors find that female FNDC5 KO mice are somewhat protected from bone loss and osteocyte lacunar enlargement caused by either lactation or a calcium-deficient diet. In contrast, male FNDC5 KO mice lose more bone and have a greater enlargement of osteocyte lacunae than their wild-type controls. Based on these results, the authors conclude that in males irisin protects bone from calcium deficiency but that in females it promotes calcium removal from bone for lactation.

While some of the conclusions of this study are supported by the results, it is not clear that the modest effects of FNDC5 deletion have an impact on calcium homeostasis or milk production.

Specific comments:

1. The authors sometimes refer to FNDC5 and other times to irisin when describing causes for a particular outcome. Because irisin was not measured in any of the experiments, the authors should not conclude that lack of irisin is responsible. Along these lines, is there any evidence that either lactation or a calcium-deficient diet increases the production of irisin in mice?

2. The results of the irisin-rescue experiment shown in figure 2G cannot be appropriately interpreted without normal diet controls. In addition, some evidence that the AAV8-irisin virus actually increased irisin levels in the mice would strengthen the conclusion.

3. There is insufficient evidence to support the idea that the effect of FNDC5 on bone resorption and osteocytic osteolysis is important for the transfer of calcium from bone to milk. Previous studies by others have shown that bone resorption is not required to maintain milk or serum calcium when dietary calcium is sufficient but is critical if dietary calcium is low (Endo. 156:2762-73, 2015). To support the conclusions of the current study, it would be necessary to determine whether FNDC5 is required to maintain calcium levels when lactating mice lack sufficient dietary calcium.

4. The amount of cortical bone loss due to lactation is very similar in both WT and FNDC5 KO mice. The results of the statistical analysis of the data presented in figure 1B are surprising given the very similar effect size of lactation. The key result from the 2-way ANOVA is whether there is an effect of genotype on the effect size of lactation (genotype-lactation interaction). The interaction terms were not provided. Similar concerns are noted for the results shown in figure 1G and H.

5. It is not clear what justifies the term 'primed' or 'activated' for resorption. Is there evidence that a certain level of TRAP expression lowers the threshold for osteocytic osteolysis in response to a stimulus?

Reviewer #3 (Public Review):

Summary: Irisin has previously been demonstrated to be a muscle-secreted factor that affects skeletal homeostasis. Through the use of different experimental approaches, such as genetic knockout models, recombinant Irisin treatment, or different cell lines, the role of Irisin on skeletal homeostasis has been revealed to be more complex than previously thought and this warrants further examination of its role. Therefore, the current study sought to rigorously examine the effects of global Irisin knockout (KO) in male and female mouse bone. Authors demonstrated that in calcium-demanding settings, such as lactation or low-calcium diet, female Irisin KO mice lose less bone compared to wild-type (WT) female mice. Interestingly male Irisin KO mice exhibited worse skeletal deterioration compared to WT male mice when fed a low-calcium diet. When examined for transcriptomic profiles of osteocyte-enriched cortical bone, authors found that Irisin KO altered the expression of osteocytic osteolysis genes as well as steroid and fatty acid metabolism genes in males but not in females. These data support the authors' conclusion that Irisin regulates skeletal homeostasis in sex-dependent manner.

Strengths: The major strength of the study is the rigorous examination of the effects of Irisin deletion in the settings of skeletal maturity and increased calcium demands in female and male mice. Since many of the common musculoskeletal disorders are dependent on sex, examining both sexes in the preclinical setting is crucial. Had the investigators only examined females or males in this study, the conclusions from each sex would have contradicted each other regarding the role of Irisin on bone. Also, the approaches are thorough and comprehensive that assess the functional (mechanical testing), morphological (microCT, BSEM, and histology), and cellular (RNA-seq) properties of bone.

Weaknesses: One of the weaknesses of this study is a lack of detailed mechanistic analysis of why Irisin has a sex-dependent role on skeletal homeostasis. This absence is particularly notable in the osteocyte transcriptomic results where such data could have been used to further probe potential candidate pathways between LC females vs. LC males.

Another weakness is authors did not present data that convincingly demonstrate that Irisin secretion is altered in the skeletal muscle between female vs. male WT mice in response to calcium restriction. The supplement skeletal muscle data only present functional and electrophysiolgical outcomes. Since Itgav or Itgb5 were not different in any of the experimental groups, it is assumed that the changes in the level of Irisin is responsible for the phenotypes observed in WT mice. Assessing Irisin expression will further strengthen the conclusion based on observing skeletal changes that occur in Irisin KO male and female mice.

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.

Review #2 (Public Review)

In the manuscript Watanuki et al. define the metabolic profile of HSCs in stress/proliferative (myelosuppression with 5-FU), and mitochondrial inhibition and homeostatic conditions. Their conclusions are that during proliferation HSCs rely more on glycolysis (as other cell types) while HSCs in homeostatic conditions are mostly dependent on mitochondrial metabolism. Mitochondrial inhibition is used to demonstrate that blocking mitochondrial metabolism results in similar features of proliferative conditions.

The authors used state-of-the-art technologies that allow metabolic readout in a limited number of cells like rare HSCs. These applications could be of help in the field since one of the major issues in studying HSCs metabolism is the limited sensitivity of the "standard" assays, which make them not suitable for HSC studies.

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.

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.

Reviewer #2 (Public Review):

Summary:<br /> The work by Varadharajan et. al. explored a previously known genetic variant and its pathophysiology in the development of alcohol-associated liver injury. It provides a plausible mechanism for how varying levels of MBOAT7 could impact the lipid metabolomics of the cell, leading to a deleterious phenotype in MBOAT7 knockout. The authors further characterized the impact of the lipidomic changes and raised lysosomal biogenesis and autophagic flux as mechanisms of how MBOAT7 deletion causes the progression of ALD.

Strengths:<br /> Connecting the GWAS data on MBOAT7 variants with plausible pathophysiology greatly enhances the translational relevance of these findings. The global lipidomic profiling of ALD mice is also very informative and may lead to other discoveries related to lipid handling pathways.

Weaknesses:<br /> The rationale of why MBOAT7 metabolites are lower in heavy drinkers than in normal individuals is not well explained. MBOAT7 loss of function drives ALD, but unclear if MBOAT7 deletion also drives preference for alcohol or if alcohol inhibits MBOAT7 function. Presuming most individuals studied here were WT and expressed an appropriate level of MBOAT7?<br /> Also, the discussion of mechanisms of MBOAT7-induced dysregulation of lysosomal biogenesis/autophagy, while very interesting, seems incomplete. It is not clear how MBOAT7 an enzyme involved in membrane phospholipid remodeling increases mTOR which leads to decreased TFEB target gene transcription. Furthermore, given the significant disturbances of global lipidomic profiling in MBOAT7 knockout, many pathways are potentially affected by this deletion. Further in vivo modeling that specifically addresses these pathways (TFEB targeting, mTOR inhibitor) would help strengthen the conclusions of this paper.

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?

Reviewer #2 (Public Review):

Id proteins are thought to function by binding and antagonizing basic helix-loop-helix (bHLH) transcription factors but new findings demonstrate roles for emc including in tissues where no proneural (Drosophila bHLH) genes are known to function. The authors propose a new mechanism for developmental regulation that entails restraining new/novel non-apoptotic functions of apoptotic caspases.

Specifically, the data suggest that loss of emc leads to reduced expression of diap1 and increased apoptotic caspase activity, which does not induce apoptosis but elevates Delta expression to increase N activity and cause developmental defects. Indeed, many of the phenotypes of emc mutant clones can be rescued by a chromosomal deficiency that reduces caspase activation or by mutations in the initiator caspase Dronc. A related manuscript that shows that loss of emc results in increased da, linked previously to diap1 expression, provides supporting data. There is increasing appreciation that apoptotic caspases have non-apoptotic roles. This study adds to the emerging field and should be of interest to readers.

The data, for the most part, support the conclusions but I do have concerns about some of the data and the interpretations that should be addressed.

Reviewer #3 (Public Review):

The work extends earlier studies on the Drosophila Id protein EMC to uncover a potential pathway that explains several tissue-scale developmental abnormalities in emc mutants. It also describes a non-apoptotic role for caspases in cell biology.

Strengths:<br /> The work adds to an emerging new set of functions for caspases beyond their canonical roles as cell death mediators. This novelty is a major strength as well as its reliance on genetic-based in vivo study. The study will be of interest to those who are curious about caspases in general.

Weaknesses:<br /> The manuscript relies on imaging experiments using genetic mosaic imaginal discs. It is for the most part a qualitative analysis, showing representative samples with a small number of mutant clones in each. Although the senior author has a long track record of using experiments like this to rigorously discover regulatory mechanisms in this system, it is straightforward in 2023 to use Fiji and other image analysis tools to measure fluorescence. Such measurements could be done for all replicate clones of a given genotype as well as genetic control sampling. These could be presented in plots that would not only provide quantitative and statistical measurements, but will be more reader-friendly to those who are not fly people.

Likewise, more details are needed to describe how clone areas were measured in Figure 1. Did they measure each clone and its twin spot, and then calculate the area ratio for each clone and its paired twin spot? This would be the correct way to analyze the data, yielding many independent measurements of the ratio. And doing so would obviate the need to log transform the data which is inexplicable unless they were averaging clones and twins within a disc and making replicates. More explanation is needed and if they indeed averaged, then they need to calculate the ratios pairwise for each clone and twin.

‘It’s totally unhinged’: is the book world turning against Goodreads? by David Smith in The Guardinan 2023-12-18

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.

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.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

The only minor weakness I found was that I still don't have a better sense into (a) intuition and (b) mathematical derivation of Equation 1, which is so central to the work. I would recommend that the authors provide this early on in the main text.

Reviewer #3 (Public Review):

Summary:

Allosteric regulations are complicated in multi-domain proteins and many large-scale mutational data cannot be explained by current theoretical models,, especially for those that are neither in the functional/allosteric sites nor on the allosteric pathways. This work provides a statistical thermodynamic model for a two-domain protein, in which one domain contains an effector binding site and the other domain contains a functional site. The authors build the model to explain the mutational experimental data of TetR, a transcriptional repress protein that contains a ligand and a DNA-binding domain. They incorporate three basic parameters, the energy change of the ligand and DNA binding domains before and after binding, and the coupling between the two domains to explain the free energy landscape of TetR's conformational and binding states. They go further to quantitatively explain the in vivo expression level of the TetR-regulated gene by fitting into the induction curves of TetR mutants. The effects of most of the mutants studied could be well explained by the model. This approach can be extended to understand the allosteric regulation of other two-domain proteins, especially to explain the effects of widespread mutants not on the allosteric pathways.

Strengths:

The effects of mutations that are neither in the functional or allosteric sites nor in the allosteric pathways are difficult to explain and quantify. This work develops a statistical thermodynamic model to explain these complicated effects. For simple two-domain proteins, the model is quite clean and theoretically solid. For the real TetR protein that forms a dimeric structure containing two chains with each of them composed of two domains, the model can explain many of the experimental observations. The model separates intra and inter-domain influences that provide a novel angle to analyse allosteric effects in multi-domain proteins.

Weaknesses:

As mentioned above, the TetR protein is not a simple two-main protein, but forms a dimeric structure in which the DNA binding domain in each chain forms contacts with the ligand-binding domain in the other chain. In addition, the two ligand-binding domains have strong interactions. Without considering these interactions, especially those mutants that are on these interfaces, the model may be oversimplified for TetR.

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.

Reviewer #3 (Public Review):

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

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

Weaknesses<br /> This reviewer's concerns were convincingly addressed by the revisions.

Overall Impact<br /> The authors present a convincing argument for the use of SLM as a better non-interacting null model for macroecological quantities and relationships.

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

Reviewer #2 (Public Review):

Summary:

In this study, the authors investigate the effect of ACh on neuronal responses in the auditory cortex of anesthetized rats during an auditory oddball task. The paradigm consisted of two pure tones (selected from the frequency responses at each recording site) presented in a pseudo-random sequence. One tone was presented frequently (the "standard" tone) and the other infrequently (the "deviant" tone). The authors found that ACh enhances the detection of unexpected stimuli in the auditory environment by increasing or decreasing the neuronal responses to deviant and standard tones.

Strengths:

The study includes the use of appropriate and validated methodology in line with the current state-of-the-art, rigorous statistical analysis and the demonstration of the effects of acetylcholine on auditory processing.

Weaknesses:

The study was conducted in anesthetized rats, and further research is needed to determine the behavioral relevance of these findings.

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.

Reviewer #2 (Public Review):

Summary:

This interesting study addresses the ability of Ym1 protein crystals to promote pulmonary type 2 inflammation in vivo, in mice.

Strengths:

The data are extremely high quality, clearly presented, significantly extending previous work from this group on the type 2 immunogenicity of protein crystals.

Weaknesses:

There are no major weaknesses in this study. It would be interesting to see if Ym2 crystals behave similarly to Ym1 crystals in vivo. Some additional text in the Introduction and Discussion would enrich those sections.

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.

Reviewer #2 (Public Review):

Summary:<br /> The work fruitfully adds to the tools to study cannabinoid action and pharmacology specifically, but also this method is applicable to other drugs, in particular, if lipophilic in nature.

Strengths:<br /> The addition of chocolate flavor overcomes aversive reactions which are often experienced in pharmacological treatments, leading to possible caveats in the interpretation of the behavioral outcomes.

Weaknesses:<br /> Certainly, more THC mediated behavioral outcomes could have been tested, but the work presents a proof-of-concept study to investigate acute THC treatment.<br /> It would have been interesting if this application form is also possible for chronic treatment regimen.

Reviewer #3 (Public Review):

Summary: This manuscript explores the development of a rodent voluntary oral THC consumption model. The authors use the model to demonstrate that similar effect levels of THC can be observed to what has previously been described for i.p. THC administration.

Strengths: Overall this is an interesting study with compelling data presented. There is a growing need within the field of cannabinoid research to explore more 'realistic' routes of cannabinoid administration, such as oral consumption or inhalation. The evidence presented here shows the utility of this oral administration model.

Weaknesses: The main weaknesses of the manuscript revolve around clarification of the Methods section. All of these weaknesses are described in the "Recommendations to authors" section. Revising the manuscript would account for many of these weaknesses.

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.

Reviewer #3 (Public Review):

Summary: This paper presents evidence of recursive self-embedding in the vocalization structure of orangutans, using fine-grained acoustical analysis. It proves the existence of isochrony nested in isochrony in the motifs produced by a nonhuman vocal system.

Strengths: Very clear written, clear analysis, excellent responses to the Reviewers.

Weaknesses: Jargonous language may be reduced. A video showing the sound as it unfolds and the spectrogram (as in Fig 1A) of the long call could be useful to best exemplify the results.

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.

Reviewer #2 (Public Review):

Summary:<br /> Morucci et al. tested the influence of linguistic prosody long-term priors in forming predictions about simple acoustic rhythmic tone sequences composed of alternating tone duration, by violating context-dependent short-term priors formed during sequence listening. Spanish and Basque participants were selected due to the different rhythmic prosody of the two languages (functor-initial vs. Functor final, respectively), despite a common cultural background. The authors found that neuromagnetic responses to casual tone omissions reflected the linguistic prosody pattern of the participant's dominant language: in Spanish speakers, omission responses were larger to short tones, whereas in Basque speakers, omission responses were larger to long tones. Source localization of these responses revealed this interaction pattern in the left auditory cortex, which the authors interpret as reflecting a perceptual bias due to acoustic cues (inherent linguistic rhythms, rather than linguistic content). Importantly, this pattern was not found when the rhythmic sequence entailed pitch, rather than duration, cues. To my knowledge, this is the first study providing neural signatures of a known behavioral effect linking ambiguous rhythmic tone sequence perceptual organization to linguistic experience.

The conclusions of the study are well supported by the data, albeit weakly by the source analysis, but I have the impression that the rationale of the study and the analyses performed may be missing an important aspect of rhythmic sequence perception, namely the involvement of entrained oscillatory activity to the perceived rhythm, particularly phase alignment to pattern onsets. This view would not change the impact of the results but add depth to their interpretation.

Strengths:<br /> 1) The choice of participants. The bilingual population of the Basque country is perfect for performing studies that need to control for cultural and socio-economic background while having profound linguistic differences. In this sense, having dominant Basque speakers as a sample equates that in Molnar et al. (2016), and thus overcomes the lack of direct behavioral evidence for a difference in rhythmic grouping across linguistic groups. Molnar et al. (2016)'s evidence on the behavioral effect is compelling, and the evidence on neural signatures provided by the present study aligns with it.

2) The experimental paradigm. It is a well-designed acoustic sequence, that considers aspects such as gap length insertion, to be able to analyze omission responses free from subsequent stimulus-driven responses, and which includes a control sequence that uses pitch instead of duration as a cue to rhythmic grouping, which provides a stronger case for the differences found between groups to be due to prosodic duration cues.

3) Data analyses. Sound, state-of-the-art methodology in the event-related field analyses at the sensor level.

Weaknesses:<br /> 1) Despite the evidence provided on neural responses, the main conclusion of the study reflects a known behavioral effect on rhythmic sequence perceptual organization driven by linguistic background (Molnar et al. 2016, particularly). Also, the authors themselves provide a good review of the literature that evidences the influence of long-term priors in neural responses related to predictive activity. Thus, in my opinion, the strength of the statements the authors make on the novelty of the findings may be a bit far-fetched in some instances.

2) Albeit the paradigm is well designed, I fail to see the grounding of the hypotheses laid by the authors as framed under the predictive coding perspective. The study assumes that responses to an omission at the beginning of a perceptual rhythmic pattern will be stronger than at the end. I feel this is unjustified. If anything, omission responses should be larger when the gap occurs at the end of the pattern, as that would be where stronger expectations are placed: if in my language a short sound occurs after a long one, and I perceptually group tone sequences of alternating tone duration accordingly, when I hear a short sound I will expect a long one following; but after a long one, I don't necessarily need to expect a short one, as something else might occur.

3) In this regard, it is my opinion that what is reflected in the data may be better accounted for (or at least, additionally) by a different neural response to an omission depending on the phase of an underlying attentional rhythm (in terms of Large and Jones rhythmic attention theory, for instance) and putative underlying entrained oscillatory neural activity (in terms of Lakatos' studies, for instance). Certainly, the fact that the aligned phase may differ depending on linguistic background is very interesting and would reflect the known behavioral effect.

4) Source localization is performed on sensor-level significant data. The lack of source-level statistics weakens the conclusions that can be extracted. Furthermore, only the source reflecting the interaction pattern is taken into account in detail as supporting their hypotheses, overlooking other sources. Also, the right IFG source activity is not depicted, but looking at whole brain maps seems even stronger than the left. To sum up, source localization data, as informative as it could be, does not strongly support the author's claims in its current state.

Reviewer #3 (Public Review):

Summary:<br /> The paper investigates the effects of long-term linguistic experience on early auditory processing, a subject that has been relatively less studied compared to short-term influences. Using MEG, the study examines brain responses to auditory stimuli in speakers of Spanish and Basque, whose syntactic rules provide different degrees of exposure to durational patterns (long-short vs short-long). The findings suggest that both long-term language experience, as well as short-term transitional probabilities, can shape auditory predictive coding for non-linguistic sound sequences, evidenced by differences in mismatch negativity amplitudes localised to the left auditory cortex.

Strengths:<br /> The study integrates linguistics and auditory neuroscience in an interesting interdisciplinary way that may interest linguists as well as neuroscientists. The fact that long-term language experience affects early auditory predictive coding is important for understanding group and individual differences in domain-general auditory perception. It has importance for neurocognitive models of auditory perception (e.g. inclusion of long-term priors), and will be of interest to researchers in linguistics, auditory neuroscience, and the relationship between language and perception. The inclusion of a control condition based on pitch is also a strength.

Weaknesses:<br /> The main weaknesses are the strength of the effects and generalisability. The sample size is also relatively small by today's standards, with N=20 in each group. Furthermore, the crucial effects are all mostly in the .01>P<.05 range, such as the crucial interaction P=.03. It would be nice to see it replicated in the future, with more participants and other languages. It would also have been nice to see behavioural data that could be correlated with neural data to better understand the real-world consequences of the effect.

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.

Reviewer #2 (Public Review):

Summary:<br /> In this study, Hauser et al investigate the role of amphibian (Xenopus laevis) mast cells in cutaneous immune responses to the ecologically important pathogen Batrachochytrium dendrobatidis (Bd) using novel methods of in vitro differentiation of bone marrow-derived mast cells and in vivo expansion of skin mast cell populations. They find that bone marrow-derived myeloid precursors cultured in the presence of recombinant X. laevis Stem Cell Factor (rSCF) differentiate into cells that display hallmark characteristics of mast cells. They inject their novel (r)SCF reagent into the skin of X. laevis and find that this stimulates the expansion of cutaneous mast cell populations in vivo. They then apply this model of cutaneous mast cell expansion in the setting of Bd infection and find that mast cell expansion attenuates the skin burden of Bd zoospores and pathologic features including epithelial thickness and improves protective mucus production and transcriptional markers of barrier function. Utilizing their prior expertise with expanding neutrophil populations in X. laevis, the authors compare mast cell expansion using (r)SCF to neutrophil expansion using recombinant colony-stimulating factor 3 (rCSF3) and find that neutrophil expansion in Bd infection leads to greater burden of zoospores and worse skin pathology.

Strengths:<br /> The authors report a novel method of expanding amphibian mast cells utilizing their custom-made rSCF reagent. They rigorously characterize expanded mast cells in vitro and in vivo using histologic, morphologic, transcriptional, and functional assays. This establishes solid footing with which to then study the role of rSCF-stimulated mast cell expansion in the Bd infection model. This appears to be the first demonstration of the exogenous use of rSCF in amphibians to expand mast cell populations and may set a foundation for future mechanistic studies of mast cells in the X. laevis model organism.

Weaknesses:<br /> The conclusions regarding the role of mast cell expansion in controlling Bd infection would be stronger with a more rigorous evaluation of the model, as there are some key gaps and remaining questions regarding the data. For example:

1. Granulocyte expansion is carefully quantified in the initial time courses of rSCF and rCSF3 injections, but similar quantification is not provided in the disease models (Figures 3E, 4G, 5D-G). A key implication of the opposing effects of mast cell vs neutrophil expansion is that mast cells may suppress neutrophil recruitment or function. Alternatively, mast cells also express notable levels of csfr3 (Figure 2) and previous work from this group (Hauser et al, Facets 2020) showed rG-CSF-stimulated peritoneal granulocytes express mast cell markers including kit and tpsab1, raising the question of what effect rCSF3 might have on mast cell populations in the skin. Considering these points, it would be helpful if both mast cells and neutrophils were quantified histologically (based on Figure 1, they can be readily distinguished by SE or Giemsa stain) in the Bd infection models.

2. Epithelial thickness and inflammation in Bd infection are reported to be reduced by rSCF treatment (Figure 3E, 5A-B) or increased by rCSF3 treatment (Figure 4G) but quantification of these critical readouts is not shown.

3. Critical time points in the Bd model are incompletely characterized. Mast cell expansion decreases zoospore burden at 21 dpi, while there is no difference at 7 dpi (Figure 3E). Conversely, neutrophil expansion increases zoospore burden at 7 dpi, but no corresponding 21 dpi data is shown for comparison (Figure 4G). Microbiota analysis is performed at a third time point,10 dpi (Figure 5D-G), making it difficult to compare with the data from the 7 dpi and 21 dpi time points. Reporting consistent readouts at these three time points is important to draw solid conclusions about the relationship of mast cell expansion to Bd infection and shifts in microbiota.

4. Although the effect of rSCF treatment on Bd zoospores is significant at 21 dpi (Figure 3E), bacterial microbiota changes at 21 dpi are not (Figure S3B-C). This discrepancy, how it relates to the bacterial microbiota changes at 10 dpi, and why 7, 10, and 21 dpi time points were chosen for these different readouts (Figure 5F-G), is not discussed.

5. The time course of rSCF or rCSF3 treatments relative to Bd infection in the experiments is not clear. Were the treatments given 12 hours prior to the final analysis point to maximize the effect? For example, in Figure 3E, were rSCF injections given at 6.5 dpi and 20.5 dpi? Or were treatments administered on day 0 of the infection model? If the latter, how do the authors explain the effects at 7 dpi or 21 dpi given mast cell and neutrophil numbers return to baseline within 24 hours after rSCF or rCSF3 treatment, respectively?

The title of the manuscript may be mildly overstated. Although Bd infection can indeed be deadly, mortality was not a readout in this study, and it is not clear from the data reported that expanding skin mast cells would ultimately prevent progression to death in Bd infections.

Reviewer #3 (Public Review):

Summary:<br /> Hauser et al. provide an exceptional study describing the role of resident mast cells in amphibian epidermis that produce anti-inflammatory cytokines that prevent Batrachochytrium dendrobatidis (Bd) infection from causing harmful inflammation, and also protect frogs from changes in skin microbiomes and loss of mucin in glands and loss of mucus integrity that otherwise cause changes to their skin microbiomes. Neutrophils, in contrast, were not protective against Bd infection. Beyond the beautiful cytology and transcriptional profiling, the authors utilized elegant cell enrichment experiments to enrich mast cells by recombinant stem cell factor, or to enrich neutrophils by recombinant colony-stimulating factor-3, and examined respective infection outcomes in Xenopus.

Strengths:<br /> Through the use of recombinant IL4, the authors were able to test and eliminate the hypothesis that mast cell production of IL4 was the mechanism of host protection from Bd infection. Instead, impacts on the mucus glands and interaction with the skin microbiome are implicated as the protective mechanism. These results will press disease ecologists to examine the relative importance of this immune defense among species, the influence of mast cells on the skin microbiome and mucosal function, and open the potential for modulating mucosal defense.

Weaknesses:<br /> A reduction of bacterial diversity upon infection, as described at the end of the results section, may not always be an "adverse effect," particularly given that anti-Bd function of the microbiome increased. Some authors (see Letourneau et al. 2022 ISME, or Woodhams et al. 2023 DCI) consider these short-term alterations as encoding ecological memory, such that continued exposure to a pathogen would encounter an enriched microbial defense. Regardless, mast cell-initiated protection of the mucus layer may negate the need for this microbial memory defense.

While the description of the mast cell location in the epidermal skin layer in amphibians is novel, it is not known how representative these results are across species ranging in chytridiomycosis susceptibility. No management applications are provided such as methods to increase this defense without the use of recombinant stem cell factor, and more discussion is needed on how the mast cell component (abundance, distribution in the skin) of the epidermis develops or is regulated.

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.

Reviewer #2 (Public Review):

Summary:<br /> This study focuses on the 5-HT3 serotonin receptor, a pentameric ligand-gated ion channel important in chemical neurotransmission. There are many cryo-EM structures of this receptor with diverse ligands bound, however assignment of functional states to the structures remains incomplete. The team applies voltage-clamp fluorometry to measure, at once, both changes in ion channel activity, and changes in fluorescence. Four cysteine mutants were selected for fluorophore labeling, two near the neurotransmitter site, one in the ECD vestibule, and one at the ECD-TMD junction. Agonists, partial agonists, and antagonists were all found to yield similar changes in fluorescence, a proxy for conformational change, near the neurotransmitter site. The strength of the agonist correlated to a degree with propagation of this fluorescence change beyond the local site of neurotransmitter binding. Antagonists failed to elicit a change in fluorescence in the vestibular the ECD-TMD junction sites. The VCF results further turned up evidence supporting intermediate (likely pre-active) states.

Strengths:<br /> The experiments appear rigorous, the problem the team tackles is timely and important, the writing and the figures are for the most part very clear. We sorely need approaches orthogonal to structural biology to annotate conformational states and observe conformational transitions in real membranes- this approach, and this study, get right to the heart of what is missing.

Weaknesses:<br /> The weaknesses in the study itself are overall minor, I only suggest improvements geared toward clarity. What we are still missing is application of an approach like this to annotate the conformation of the part of the receptor buried in the membrane; there is important debate about which structure represents which state, and that is not addressed in the current study.

Reviewer #3 (Public Review):

Summary:<br /> The authors have examined the 5-HT3 receptor using voltage clamp fluorometry, which enables them to detect structural changes at the same time as the state of receptor activation. These are ensemble measurements, but they enable a picture of the action of different agonists and antagonists to be built up.

Strengths:<br /> The combination of rigorously tested fluorescence reporters with oocyte electrophysiology is a solid development for this receptor class.

Weaknesses:<br /> The interpretation of the data is solid but relevant foundational work is ignored. Although the data represent a new way of examining the 5-HT3 receptor, nothing that is found is original in the context of the superfamily. Quantitative information is discussed but not presented.

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.

Reviewer #2 (Public Review):

Summary:<br /> The authors have developed a comprehensive set of tools to describe dynamics within a single time-series or across multiple time-series. The motivation is to better understand interacting networks within the human brain. The time-series used here are from direct estimates of the brain's electrical activity; however the tools have been used with other metrics of brain function and would be applicable to many other fields.

Strengths:<br /> The methods described are principled, based on generative probabilistic models.<br /> This makes them compact descriptors of the complex time-frequency data.<br /> Few initial assumptions are necessary in order to reveal this compact description.<br /> The methods are well described and demonstrated within multiple peer reviewed articles.<br /> This toolbox will be a great asset to the brain imaging community.

Weaknesses:<br /> The only question I had (originally) was how to objectively/quantitatively compare different network models. This has now been addressed by the authors in the latest revision.

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.

Reviewer #2 (Public Review):

Summary:<br /> The authors build a gene expression model based on histone post-translational modifications and find that H3K27ac is correlated with gene expression. They proceed to perturb H3K27ac at 8 gene promoters, and measure gene expression changes to test their model.

Strengths:<br /> The combination of multiple methods to model expression, along with utilizing 6 histone datasets in 13 cell types allowed the authors to build a model that correlates between 0.7-0.79 with gene expression. This group also utilized a tool they are experts in, dCas9-p300 fusions to perturb H3K27ac and monitor gene expression to test their model. Ranked correlations showed some support for the predictions after the perturbation of H3K27ac.

Weaknesses:<br /> The perturbation of only 8 genes, and the only readout being qPCR-based gene expression, as opposed to including H3K27ac, weakened their validation of the computational model. Likewise, the use of six genes that were not expressed being most activated by dCas9-p300 might weaken the correlations vs. looking at a broad range of different gene expressions as the original model was trained on.

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?

Reviewer #2 (Public Review):

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

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

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

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

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.

Reviewer #2 (Public Review):

Greve et al. investigated the effects of a disease-associated gamma-actin mutation (E334Q) on actin filament polymerization, association of selected actin-binding proteins, and myosin activity. Recombinant wildtype and mutant proteins expressed in sf9 cells were found to be folded and stable, and the presence of the mutation altered a number of activities. Given the location of the mutation, it is not surprising that there are changes in polymerization and interactions with actin binding proteins. Nevertheless, it is important to quantify the effects of the mutation to better understand disease etiology. Some weaknesses were identified in the paper as discussed below.

Throughout the paper, the authors report average values and the standard-error-of-the-mean (SEM) for groups of three experiments. Reporting the SEM is not appropriate or useful for so few points, as it does not reflect the distribution of the data points. When only three points are available, it would be better to just show the three different points. Otherwise, plot the average and the range of the three points.

The description and characterization of the recombinant actin is incomplete. Please show gels of purified proteins. This is especially important with this preparation since the chymotrypsin step could result in internally cleaved proteins and altered properties, as shown by Ceron et al (2022). The authors should also comment on N-terminal acetylation of actin.

The authors do not use the best technique to assess actin polymerization parameters. Although the TIRF assay is excellent for some measurements, it is not as good as the standard pyrene-actin assays that provide critical concentration, nucleation, and polymerization parameters. The authors use pyrene-actin in other parts of the paper, so it is not clear why they don't do the assays that are the standard in the actin field.

The authors' data suggest that, while the binding of cofilin-1 to both the WT and mutant actins remains similar, the major defect of the E334Q actin is that it is not as readily severed/disassembled by cofilin. What is missing is a direct measurement of the severing rate (number of breaks per second) as measured in TIRF.

Figure 4 shows that the E334Q mutation increases rather than decreases the number of filaments that spontaneously assemble in the TIRF assay, but it is unclear how reduced severing would lead to increased filament numbers, rather, the opposite would be expected. A more straightforward approach would be to perform experiments where severing leads to more nuclei and therefore enhances the net bulk assembly rate.

Figure 5 A: in the pyrene disassembly assay, where actin is diluted below its critical concentration, cofilin enhances the rate of depolymerization by generating more free ends. The E334Q mutation leads to decreased cofilin-induced severing and therefore lower depolymerization. While these data seem convincing, it would be better to present them as an XY plot and fit the data to lines for comparison of the slopes.

Figure 5 B and C: the cosedimentation data do not seem to help elucidate the underlying mechanism. While the authors report statistical significance, differences are small, especially for gel densitometry measurements where the error is high, which suggests that there may be little biological significance. Importantly, example gels from these experiments should be shown, if not the complete set included in the supplement. In B, the higher cofilin concentrations would be expected to stabilize the filaments and thus the curve should be U-shaped.

Figure 5 D: these data show that the binding of cofilin to WT and E334Q actin is approximately the same, with the mutant binding slightly more weakly. It would be clearer if the two plots were normalized to their respective plateaus since the difference in arbitrary units distracts from the conclusion of the figure. If the difference in the plateaus is meaningful, please explain.

Figure 6: It is assumed that the authors are trying to show in this figure that cofilin binds both actins approximately the same but does not sever as readily for E334Q actin. The numerous parameters measured do not directly address what the authors are actually trying to show, which presumably is that the rate of severing is lower for E334Q than WT. It is therefore puzzling why no measurement of severing events per second per micron of actin in TIRF is made, which would give a more precise account of the underlying mechanism.

Actin-activated steady-state ATPase data of the NM2A with mutant and WT actin would have been extremely useful and informative. The authors show the ability to make these types of measurements in the paper (NADH assay), and it is surprising that they are not included for assessing the myosin activity. It may be because of limited actin quantities. If this is the case, it should be indicated.

(line 310) The authors state that they "noticed increased rapid dissociation and association events for E334Q filaments" in the motility assay. This observation motivates the authors to assess actin affinities of NM2A-HMM. Although differences in rigor and AM.ADP affinities are found between mutant and wt actins, the actin attachment lifetimes (many minutes) are unlikely to be related to the rapid association and dissociation event seen in the motility assay. Rather, this jiggling is more likely to be related to a lower duty ratio of the myosins, which appears to be the conclusion reached for the myosin-V data. These points should be clarified in the text.

(line 327) The authors report that the 1/K1 value is unchanged. There are no descriptions of this experiment in the paper. I am assuming the authors measured the ATP-induced dissociation of actomyosin and determined ATP affinity (K1) from this experiment. If this is the case, they should describe the experiment and show the data, provide a second-order rate constate for ATP binding, and report the max rate of dissociation (k2). This is a kinetic experiment done frequently by this group, so the absence of these details is surprising.

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.

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?

Reviewer #2 (Public Review):

Summary:<br /> In this new paper, the authors used biochemical, structural, and biophysical methods to elucidate the mechanisms by which IP4, the PIP3 headgroup, can induce an autoinhibit form of P-Rex1 and propose a model of how PIP3 can trigger long-range conformational changes of P-Rex1 to relieve this autoinhibition. The main findings of this study are that a new P-Rex1 autoinhibition is driven by an IP4-induced binding of the PH domain to the DH domain active site and that this autoinhibited form is stabilized by two key interactions between DEP1 and DH and between PH and IP4P 4-helix bundle (4HB) subdomain. Moreover, they found that the binding of phospholipid PIP3 to the PH domain can disrupt these interactions to relieve P-Rex1 autoinhibition.

Strengths:<br /> The study provides good evidence that binding of IP4 to the P-Rex1 PH domain can make the two long-range interactions between the catalytic DH domain and the first DEP domain and between the PH domain and the C-terminal IP4P 4HB subdomain that generate a novel P-Rex1 autoinhibition mechanism. This valuable finding adds an extra layer of P-Rex1 regulation (perhaps in the cytoplasm) to the synergistic activation by phospholipid PIP3 and the heterotrimeric Gbeta/gamma subunits at the plasma membrane. Overall, this manuscript's goal sounds interesting, the experimental data were carried out carefully and reliably.

Reviewer #3 (Public Review):

Summary:<br /> In this report, Ravala et al demonstrate that IP4, the soluble head-group of phosphatiylinositol 3,4,5 - trisphosphate (PIP3), is an inhibitor of pREX-1, a guanine nucleotide exchange factor (GEF) for Rac1 and related small G proteins that regulate cell migration. This finding is perhaps unexpected since pREX-1 activity is PIP3-dependent. By way of Cryo-EM (revealing the structure of the p-REX-1/IP4 complex at 4.2Å resolution), hydrogen-deuterium mass spectrometry, and small angle X-ray scattering, they deduce a mechanism for IP4 activation, and conduct mutagenic and cell-based signaling assays that support it. The major finding is that IP4 stabilizes two interdomain interfaces that block access to the DH domain, which conveys GEF activity towards small G protein substrates. One of these is the interface between the PH domain that binds to IP4 and a 4-helix bundle extension of the IP4 Phosphatase domain and the DEP1 domain. The two interfaces are connected by a long helix that extends from PH to DEP1. Although the structure of fully activated pREX-1 has not been determined, the authors propose a "jackknife" mechanism, similar to that described earlier by Chang et al (2022) (referenced in the author's manuscript) in which binding of IP3 relieves a kink in a helix that links the PH/DH modules and allows the DH-PH-DEP triad to assume an extended conformation in which the DH domain is accessible. While the structure of the activated pREX-1 has not been determined, cysteine mutagenesis that enforces the proposed kink is consistent with this hypothesis. SAXS and HDX-MS experiments suggest that IP4 acts by stiffening the inhibitory interfaces, rather than by reorganizing them. Indeed, the cryo-EM structure of ligand-free pREX-1 shows that interdomain contacts are largely retained in the absence of IP4.

Strengths:<br /> The manuscript thus describes a novel regulatory role for IP4 and is thus of considerable significance to our understanding of regulatory mechanisms that control cell migration, particularly in immune cell populations. Specifically, they show how the inositol polyphosphate IP4 controls the activity of pREX-1, a guanine nucleotide exchange factor that controls the activity of small G proteins Rac and CDC42 . In their clearly written discussion, the authors explain how PIP3, the cell membrane, and the Gbeta-gamma subunits of heterotrimeric membranes together localize pREX-1 at the membrane and induce activation. The quality of experimental data is high and both in vitro and cell-based assays of site-directed mutants designed to test the author's hypotheses are confirmatory. The results strongly support the conclusions. The combination of cryo-EM data, that describe the static (if heterogeneous) structures with experiments (small angle x-ray scattering and hydrogen-deuterium exchange-mass spectrometry) that report on dynamics are well employed by the authors

Weaknesses:<br /> There are a few weaknesses. While the resolution of the cryo-EM structure is modest, it is sufficient to identify the domain-domain interactions that are mechanistically important, since higher-resolution structures of various pREX-1 modules are available.

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.

Reviewer #2 (Public Review):

Summary:<br /> The study by Yeo and co-authors addresses a long-lasting issue about botulinum neurotoxin (BoNT) intoxication. The current view is that the toxin binds to its receptors at the axon terminus by its HCc domain and is internalized in recycled neuromediator vesicles just after the release of the neuromediators. Then, the HCn domain assists the translocation of the catalytic light chain (LC) of the toxin through the membrane of these endocytic vesicles into the cytosol of the axon terminus. There, the LC cleaves its SNARE substrate and blocks neurosecretion. However, other views involving kinetic aspects of intoxication suggest that the toxin follows the retrograde axonal transport up to the nerve cell body and then back to the nerve terminus before cleaving its substrate.

In the current study, the authors claim that the BoNT/A (isotype A of BoNT) not only progresses to the cell body but once there, follows the retrograde transport trafficking pathway in a retromer-dependent fashion, through the Golgi apparatus, until reaching the endoplasmic reticulum. Next, the LC dissociates from the HC (a process not studied here) and uses the translocon Sec61 machinery to retro-translocate into the cytosol. Only then, does the LC traffic back to the nerve terminus following the anterograde axonal transport. Once there, LC cleaves its SNARE substrate (SNAP25 in the case of BoTN/A) and blocks neurosecretion.

To reach their conclusion, Yeo and co-authors use a combination of engineered tools: a cell line able to differentiate into neurons (ReNcell VN), a reporter dual fluorescent protein derived from SNAP25, the substrate of BoNT/A (called SNAPR), the use of either native BoNT/A or a toxin to which three fragment 11 of the reporter fluorescent protein Neon Green (mNG) are fused to the N-terminus of the LC (BoNT/A-mNG11x3), and finally ReNcell VN transfected with mNG1-10 (a protein consisting of the first 10 beta strands of the mNG).

SNAPR is stably expressed all over in the ReNcell VN. SNAPR is yellow (red and green) when intact and becomes red only when cleaved by BoNT/A LC, the green tip being degraded by the cell. When the LC of BoNT/A-mNG11x3 reaches the cytosol in ReNcell VN transfected by mNG1-10, the complete mNG is reconstituted and emits a green fluorescence.

In the first experiment, the authors show that the catalytic activity of the LC appears first in the cell body of neurons where SNAPR is cleaved first. This phenomenon starts 24 hours after intoxication and progresses along the axon towards the nerve terminus during an additional 24 hours. In a second experiment, the authors intoxicate the ReNcell VN transfected by mNG1-10 using the BoNT/A-mNG11x3. The fluorescence appears also first in the soma of neurons, then diffuses in the neurites in 48 hours. The conclusion of these two experiments is that translocation occurs first in the cell body and that the LC diffuses in the cytosol of the axon in an anterograde fashion.

In the second part of the study, the authors perform a siRNA screen to identify regulators of BoNT/A intoxication. Their aim is to identify genes involved in intracellular trafficking of the toxin and translocation of the LC. Interestingly, they found positive and negative regulators of intoxication. Regulators could be regrouped according to the sequential events of intoxication. Genes affecting binding to the cell-surface receptor (SV2) and internalization. Genes involved in intracellular trafficking. Genes involved in translocation such as reduction of the disulfide bond linking the LC to the HC and refolding in the cytosol. Genes involved in signaling such as tyrosine kinases and phosphatases. All these groups of genes may be consistent with the current view of BoNT intoxication within the nerve terminus. However, two sets of genes were particularly significant to reach the main conclusion of the work and definitely constitute an original finding important to the field. One set of genes consists of those of the retromer, and the other relates to the Sec61 translocon. This should indicate that once endocytosed, the BoNT traffics from the endosomes to the Golgi apparatus, and then to the ER. Ultimately, the LC should translocate from the ER lumen to the cytosol using the Sec61 translocon. The authors further control that the SV2 receptor for the BoNT/A traffics along the axon in a retromer-dependent fashion and that BoNT/A-mNG11x3 traverses the Golgi apparatus by fusing the mNG1-10 to a Golgi resident protein.

Strengths:<br /> The findings in this work are convincing. The experiments are carefully done and are properly controlled. In the first part of the study, both the activity of the LC is monitored together with the physical presence of the toxin. In the second part of the work, the most relevant genes that came out of the siRNA screen are checked individually in the ReNcell VN / BoNT/A reporter system to confirm their role in BoNT/A trafficking and retro-translocation.

These findings are important to the fields of toxinology and medical treatment of neuromuscular diseases by BoNTs. They may explain some aspects of intoxication such as slow symptom onset, aggravation, and appearance of central effects.

Weaknesses:<br /> The findings antagonize the current view of the intoxication pathway that is sustained by a vast amount of observations. The findings are certainly valid, but their generalization as the sole mechanism of BoNT intoxication should be tempered. These observations are restricted to one particular neuronal model and engineered protein tools. Other models such as isolated nerve/muscle preparations display nerve terminus paralysis within minutes rather than days. Also, the tetanus neurotoxin (TeNT), whose mechanism of action involving axonal transport to the posterior ganglia in the spinal cord is well described, takes between 5 and 15 days. It is thus possible that different intoxication mechanisms co-exist for BoNTs or even vary depending on the type of neurons.

Although the siRNA experiments are convincing, it would be nice to reach the same observations with drugs affecting the endocytic to Golgi to ER transport (such as Retro-2, golgicide or brefeldin A) and the Sec61 retrotranslocation (such as mycolactone). Then, it would be nice to check other neuronal systems for the same observations.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Yao et al. investigates the intracellular trafficking of Botulinum neurotoxin A (BoNT/A), a potent toxin used in clinical and cosmetic applications. Contrary to the prevailing understanding of BoNT/A translocation into the cytosol, the study suggests a retrograde migration from the synapse to the soma-localized Golgi in neurons. Using a genome-wide siRNA screen in genetically engineered neurons, the researchers identified over three hundred genes involved in this process. The study employs organelle-specific split-mNG complementation, revealing that BoNT/A traffics through the Golgi in a retromer-dependent manner before moving to the endoplasmic reticulum (ER). The Sec61 complex is implicated in the retro-translocation of BoNT/A from the ER to the cytosol. Overall, the research challenges the conventional model of BoNT/A translocation, uncovering a complex route from synapse to cytosol for efficient intoxication. The findings are based on a comprehensive approach, including the introduction of a fluorescent reporter for BoNT/A catalytic activity and genetic manipulations in neuronal cell lines. The conclusions highlight the importance of retrograde trafficking and the involvement of specific genes and cellular processes in BoNT/A intoxication.

Strengths:<br /> The major part of the experiments are convincing. They are well-controlled and the interpretation of their results is balanced and sensitive.

Weaknesses:<br /> To my opinion, the main weakness of the paper is in the interpretation of the data equating loss of tGFP signal (when using the Red SNAPR assay) with proteolytic cleavage by the toxin. Indeed, the first step for loss of tGFP signal by degradation of the cleaved part is the actual cleavage. However, this needs to be degraded (by the proteasome, I presume), a process that could in principle be affected (in speed or extent) by the toxin.

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.

Reviewer #2 (Public Review):

Summary:<br /> This study analyses camera trapping information on the occurrence of forest mammals along a gradient of human modification of the environment. The key hypotheses are that human disturbance squeezes wildlife into a smaller area or their activity into only part of the day, leading to increased co-occurrence under modification. The method used is joint species distribution modelling (JSDM).

Strengths:<br /> The data source seems to be very nice, although since very little information is presented, this is hard to be sure of. Also, the JSDM approach is, in principle, a nice way of simultaneously analysing the data.

Weaknesses:<br /> The manuscript suffers from a mismatch of hypotheses and methods at two different levels.

1) At the lower level, we first need to understand what the individual species do and "like" (their environmental niche). That information is not presented, and the methods suggest that the representation of each species in the JSDM is likely to be extremely poor.

2) The hypothesis clearly asks for an analysis of the statistical interaction between human disturbance and co-occurrence. Yet, the model is not set up this way, and the authors thus do a lot of indirect exploration, rather than direct hypothesis testing.

Even when the focus is not the individual species, but rather their association, we need to formulate what the expectation is. The hypotheses point towards presenting the spatial and the temporal niche, and how it changes, species for species, under human disturbance. To this, one can then add the layer of interspecific associations.

The change in activity and space use can be analysed much simpler, by looking at the activity times and spatial distribution directly. It remains unclear what the contribution of the JSDM is, unless it is able to represent this activity and spatial information, and put it in a testable interaction with human disturbance.

The topic is actually rather complicated. If biotic interactions change along the disturbance gradient, then observed data are already the outcome of such changed interactions. We thus cannot use the data to infer them! But we can show, for each species, that the habitat preferences change along the disturbance gradient - or not, as the case may be.

Then, in the next step, one would have to formulate specific hypotheses about which species are likely to change their associations more, and which less (based e.g. on predator-prey or competitive interactions). The data and analyses presented do not answer any of these issues.

Another more substantial point is that, according to my understanding of the methods, the per-species models are very inappropriate: the predictors are only linear, and there are no statistical interactions (L374). There is no conceivable species in the world whose niche would be described by such an oversimplified model.

We have no idea of even the most basic characteristics of the per-species models: prevalences, coefficient estimates, D2 of the model, and analysis of the temporal and spatial autocorrelation of the residuals, although they form the basis for the association analysis! Why are times of day and day of the year not included as predictors IN INTERACTION with niche predictors and human disturbance, since they represent the temporal dimension on which niches are hypothesised to change?

Also, all correlations among species should be shown for the raw data and for the model residuals: how much does that actually change and can thus be explained by the niche models?

The discussion has little to add to the results. The complexity of the challenge (understanding a community-level response after accounting for species-level responses) is not met, and instead substantial room is given to general statements of how important this line of research is. I failed to see any advance in ecological understanding at the community level.

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.

Reviewer #2 (Public Review):

Allison Coté et al. investigated the ordering and spatial distribution of nascent transcripts in several cells using smFISH, expansion microscopy, and live-cell imaging. They find that pre-mRNA splicing occurs post-transcriptionally at the clouds around the transcription start site, termed the transcription site proximal zone. They show that pre-mRNA may undergo continuous splicing when they pass through the zone after transcription. These data suggest a unifying model for explaining previously reported co-transcriptional splicing events and provide a direction for further study of the nature of the slow-moving zone around the transcription start site.

This paper is well-written. The findings are very important, and the data supports the conclusions well. However, some aspects of the image and description need to be clarified and revised.

1) The sentence "By distinguishing the separate fluorescent signals from probes bound to exons and introns, we could visualize splicing intermediates (represented by colocalized intron and exon spots) relative to the site of transcription (represented by bright colocalized intron and exon spots) and fully spliced products (represented by exon spots alone)." is accidentally repeated twice, one of them should be deleted.<br /> 2) The authors describe Figure 4E and 4F results in the main text as that "we performed RNA FISH simultaneously with immunofluorescence for SC35, a component of speckles, and saw that these compartmentalized pre-mRNA did indeed appear near nuclear speckles both before (Supplementary Figure 6C) and after (Figure 4E) splicing inhibition." However, no SC35 staining is shown in the Figure 4E. A similar situation happened in describing Figure 4F.

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.

Reviewer #2 (Public Review):

Lin et al attempt to examine the role of lncRNAs in human evolution in this manuscript. They apply a suite of population genetics and functional genomics analyses that leverage existing data sets and public tools, some of which were previously built by the authors, who clearly have experience with lncRNA binding prediction. However, I worry that there is a lack of suitable methods and/or relevant controls at many points and that the interpretation is too quick to infer selection. While I don't doubt that lnc RNAs contribute to the evolution of modern humans, and certainly agree that this is a question worth asking, I think this paper would benefit from a more rigorous approach to tackling it.

I thank the authors for their revisions to the manuscript; however, I find that the bulk of my comments have not been addressed to my satisfaction. As such, I am afraid I cannot say much more than what I said last time, emphasising some of my concerns with regards to the robustness of some of the analyses presented. I appreciate the new data generated to address some questions, but think it could be better incorporated into the text - not in the discussion, but in the results.

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.

Reviewer #2 (Public Review):

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

Reviewer #3 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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.

Reviewer #2 (Public Review):

Summary:<br /> The authors describe a novel ML approach to predict binding between MHC-bound peptides and T-Cell receptors. Such approaches are particularly useful for predicting the binding of peptide sequences with low similarity when compared to existing data sets. The authors focus on improving dataset quality and optimizing model architecture to achieve a pan-specific predictive model in hopes of achieving a high-precision model for novel peptide sequences.

Strengths:<br /> Since assuring the quality of training datasets is the first major step in any ML training project, the extensive human curation, computational analysis, and enhancements made in this manuscript represent a major contribution to the field. Moreover, the systematic approach to testing redundancy reduction and data augmentation is exemplary, and will significantly help future research in the field.

The authors also highlight how their model can identify outliers and how that can be used to improve the model around known sequences, which can help the creation and optimization of future datasets for peptide binding.

The new models presented here are novel and built using paired α/β TCR sequence data to predict peptide-specific TCR binding, and have been extensively and rigorously tested.

Weaknesses:<br /> Achieving an accurate pan-specific model is an ambitious goal, and the authors have significant difficulties when trying to achieve non-random performance for the prediction of TCR binding to novel peptides. This is the most challenging task for this kind of model, but also the most desirable when applying such models to biotechnological and bioengineering projects.

The manuscript is a highly technical and extremely detailed computational work, which can make the achievements and impact of the work hard to parse for application-oriented researchers.<br /> The authors briefly mention real-world use cases for TCR specificity predictions, but do not contextualize the work into possible applications.

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).

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.

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.

Reviewer #2 (Public Review):

Summary:

This paper nicely introduces WormPsyQi, an imaging analysis pipeline that effectively quantifies synaptically localized fluorescent signals in C. elegans through high-throughput automation. This toolkit is particularly valuable for the analysis of densely packed regions in 3D space, such as the nerve ring. The authors applied WormPsyQi to various aspects, including the examination of sexually dimorphic synaptic connectivity, presynaptic markers in eight head neurons, five GRASP reporters, electrical synapses, the enteric nervous system, and developmental synapse comparisons. Furthermore, they validated WormPsyQi's accuracy by comparing its results to manual analysis.

Strengths:

Overall, the experiments are well done, and their toolkit demonstrates significant potential and offers a valuable resource to the C. elegans community. This will expand the range of possibilities for studying synapses in C. elegans.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors present a new automated image analysis pipeline named WormPsyQi which allows researchers to quantify various parameters of synapses in C. elegans. Using a collection of newly generated transgenic strains in which synaptic proteins are tagged with fluorescent proteins, the authors showed that WormPsyQi can reliably detect puncta of synaptic proteins, and measure several parameters, including puncta number, location, and size.

Strengths:

The image analysis of fluorescently labeled synaptic (or other types of) puncta pattern requires extensive experience such that one can tell which puncta likely represent bona fide synapse or background noise. The authors showed that WormPsyQi nicely reproduced the quantifications done manually for most of the marker strains they tested. Many researchers conducting such types of quantifications would receive significant benefits in saving their time by utilizing the pipeline developed by the authors. The collection of new markers would also help researchers examine synapse patterning in different neuron types which may have unique mechanisms in synapse assembly and specificity. The authors describe the limitations of the use of toolkits and potential solutions users can take.

Reviewer #2 (Public Review):

Summary:<br /> Developing a mechanical model of C. elegans is difficult to do from basic principles because it moves at a low (but not very small) Reynolds number, is itself visco-elastic, and often is measured moving at a solid/liquid interface. The ElegansBot is a good first step at a kinetic model that reproduces a wide range of C. elegans motiliy behavior.

Strengths:<br /> The model is general due to its simplicity and likely useful for various undulatory movements. The model reproduces experimental movement data using realistic physical parameters (e.g. drags, forces, etc). The model is predictive (semi?) as shown in the liquid-to-solid gait transition. The model is straightforward in implementation and so likely is adaptable to modification and addition of control circuits.

Weaknesses:<br /> Since the inputs to the model are the actual shape changes in time, parameterized as angles (or curvature), the ability of the model to reproduce a realistic facsimile of C. elegans motion is not really a huge surprise.

The authors do not include some important physical parameters in the model and should explain in the text these assumptions. 1) The cuticle stiffness is significant and has been measured [1]. 2) The body of C. elegans is under high hydrostatic pressure which adds an additional stiffness [2]. 3) The visco-elasticity of C. elegans body has been measured. [3]

There is only a very brief mention of proprioception. The lack of inclusion of proprioception in the model should be mentioned and referenced in more detail in my opinion.

These are just suggested references. There may be more relevant ones available.

1. Rahimi M, Sohrabi S, Murphy CT. Novel elasticity measurements reveal C. elegans cuticle stiffens with age and in a long-lived mutant. Biophys J. 2022 Feb 15;121(4):515-524. doi: 10.1016/j.bpj.2022.01.013. Epub 2022 Jan 19. PMID: 35065051; PMCID: PMC8874029.

2. Park SJ, Goodman MB, Pruitt BL. Analysis of nematode mechanics by piezoresistive displacement clamp. Proc Natl Acad Sci U S A. 2007 Oct 30;104(44):17376-81. doi: 10.1073/pnas.0702138104. Epub 2007 Oct 25. PMID: 17962419; PMCID: PMC2077264.

3. Backholm M, Ryu WS, Dalnoki-Veress K. Viscoelastic properties of the nematode Caenorhabditis elegans, a self-similar, shear-thinning worm. Proc Natl Acad Sci U S A. 2013 Mar 19;110(12):4528-33. doi: 10.1073/pnas.1219965110. Epub 2013 Mar 4. PMID: 23460699; PMCID: PMC3607018.

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.

Reviewer #3 (Public Review):

Summary:<br /> A mechanical model is used with input force patterns to generate output curvature patterns, corresponding to a number of different locomotion behaviors in C. elegans

Strengths:<br /> The use of a mechanical model to study a variety of locomotor sequences and the grounding in empirical data are strengths. The matching of speeds (though qualitative and shown only on agar) is a strength.

Weaknesses:<br /> What is the relation between input and output data? How does the input-output relation depend on the parameters of the model? What biological questions are addressed and can significant model predictions be made?

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.

Reviewer #2 (Public Review):

In this study, Hernandez-Hernandez et al developed a gender-dependent mathematical model of arterial myocytes based on a previous model and new experimental data. The ionic currents of the model and its sex difference were formulated based on patch clamp experimental data, and the model properties were compared with single cell and tissue scale experimental results. This is a study that is of importance for the modeling field as well as for experimental physiology.

Reviewer #3 (Public Review):

Summary:

This hybrid experimental/computational study by Hernandez-Hernandez sheds new light on sex-specific differences between male and female arterial myocytes from resistance arteries. The authors conduct careful experiments in isolated myocytes from male and female mice to obtain the data needed to parameterized sex-specific models of two important ionic currents (i.e., those mediated by CaV1.2 and KV2.1). Available experimental data suggest that KV1.5 channel currents from male and female myocytes are similar, but simulations conducted in the novel Hernandez-Hernandez sex-specific models provide a more nuanced view. This gives rise to the first of the authors' three key scientific claims: (1) In males, KV1.5 is the dominant current regulating membrane potential; whereas, in females, KV2.1 plays a primary role in voltage regulation. They further show that this (2) the latter distinction drives drive sex-specific differences in intracellular Ca2+ and cellular excitability. Finally, working with one-dimensional models comprising several copies of the male/female myocyte models linked by resistive junctions, they use simulations to (3) predict that sensitivity of arterial smooth muscle to Ca2+ channel-blocking drugs commonly used to treat hypertension is heightened in female compared to male cells.

In my opinion, the following strengths of the work are particularly notable:

• The Methodology is described in exquisite detail in straightforward language that will be easy to understand for most if not all peer groups working in computational physiology. The authors have deployed standard protocols (e.g., parameter fitting as described by Kernik et al., sensitivity analysis as described by Sobie et al.) and appropriate brief explanations of these techniques are provided. The manoeuvre used to represent stochastic effects on voltage dynamics is particularly clever and something I have not personally encountered before. Collectively, these strengthen the credibility of the model and greatly enrich the manuscript.<br /> • The Results section describes findings that robustly support the three key scientific claims outlined in my Summary. It is evident these experiments were carefully designed and carried out with care and intentionality. Several figures show experimental data side-by-side with outputs from the corresponding models. These are an excellent illustration of the power of the authors' novel sex-specific computational simulation platform.

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.

Reviewer #2 (Public Review):

Summary:<br /> The authors are studying the behavioral response to pathogen exposure. They and others have previously describe the role that the G-protein coupled receptors in the nervous system plays in detecting pathogens, and initiating behavioral patterns (e.g. avoidance/learned avoidance) that minimize contact. The authors study this problem in C. elegans, which is amenable to genetic and cellular manipulations and allow the authors to define cellular and signaling mechanisms. This paper extends the original idea to now implicate signaling and transcriptional pathways within a particular neuron (ASJ) and the gut in mediating avoidance behaviour.

Strengths:<br /> The work is rigorous and elegant and the data are convincing. The authors make superb use of mutant strains in C. elegans, as well tissue specific gene inactivation and expression and genetic methods of cell ablation. to demonstrate how a gene, NPR15 controls behavioral changes in pathogen infection. The results suggest that ASJ neurons and the gut mediate such effects. I expect the paper will constitute an important contribution to our understanding of how the nervous system coordinates immune and behavioral responses to infection.

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.

Reviewer #2 (Public Review):

This is a nice story about auricular chondrocyte maintenance, its molecular mechanism, and the role of the BMP 1 receptor in microtia disease conditions. A detailed analysis of different parts of the ear, their proliferation, and their differentiation condition with histological and immunofluorescence analysis strengthens the evidence. Further validation with patient sample RNA-Seq also helps the study end with an informative story.

From the public point of view, I want to say that the authors want to explain how auricular chondrocytes differ from growth plates or other chondrocytes. The authors show that Prxx1 is a good marker to differentiate auricular chondrocytes from different types of chondrocytes, which I doubt because other chondrocytes have an expression of Prxx1 at a lower level.

Another thing the authors mention is that microtia conditions develop through reduced size without affecting proliferation and apoptosis. The authors never provide any evidence about how the ablation of Bmpr1a affects the size, protein trafficking, and ECM organization.

Crosstalk between BMP-PKA in auricular chondrocytes and switching the chondrocytes' cell fate in osteoblast cells are not entirely stable by these studies for physiological functions.

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.

Reviewer #3 (Public Review):

Summary:<br /> The authors set out to characterize the anatomical connectivity profile and the functional responses of chandelier cells (ChCs) in the mouse primary visual cortex. Using retrograde rabies tracing, optogenetics, and in vitro electrophysiology, they found that the primary source of input to ChCs are local layer 5 pyramidal cells, as well as long-range thalamic and cortical connections. ChCs provided input to local layer 2/3 pyramidal neurons, but did not receive reciprocal connections.

With two-photon calcium imaging recordings during passive viewing of drifting gratings, the authors showed that ChCs exhibit weakly selective visual responses, high correlations within their own population, and strong responses during periods of arousal (assessed by locomotion and pupil size). These results were replicated and extended in experiments with natural images and prediction of receptive field structure using a convolutional neural network.

Furthermore, the authors employed a learned visuomotor task in a virtual corridor to show that ChCs exhibit strong responses to mismatches between visual flow and locomotion, locomotion-related activation (similar to what was shown above), and visually-evoked suppression. They also showed the existence of two clusters of pyramidal neurons with functionally different responses - a cluster with "classically visual" responses and a cluster with locomotion- and mismatch-driven responses (the latter more correlated with ChCs). Comparing naive and trained mice, the authors found that visual responses of ChCs are suppressed following task learning, accompanied by a shortening of the axon initial segment (AIS) of pyramidal cells and an increase in the proportion of AIS contacted by ChCs. However, additional controls would be required to identify which component(s) of the experimental paradigm led to the functional and anatomical changes observed.

Strengths:<br /> The authors bring a comprehensive, state-of-the-art methodology to bear, including rabies tracing, in vivo two-photon calcium imaging, in vitro electrophysiology, optogenetics and chemogenetics, and deep neural networks. Their analyses and statistical tests are sound and for the most part, support their claims. Their results are in line with previous findings and extend them to the primary visual cortex.

Weaknesses:<br /> - Some of the results (e.g. arousal-related responses) are not entirely surprising given that similar results exist in other cortical areas.

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.

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.

Reviewer #2 (Public Review):

Summary:<br /> Nakai-Futatsugi et al. present a novel method to analyze the correlation between the degree of pigmentation and the gene expression profile of human-induced pluripotent stem cell-derived RPE (iPSC-RPE) cells at the single cell level. This was achieved with the use of ALPS (Automated Live imaging and cell Picking System), an invention developed by the same authors. Briefly, it allows one to choose and photograph a specific cell from a culture dish and proceed to single-cell digital RNA-seq. The authors identify clusters of cells that present differential gene expression, but this shows no association with the degree of pigmentation of the cells. Further data analysis allowed the authors to correlate the degree of pigmentation to some degree with the expression of complement and lysosome-related genes.

Strengths:<br /> An important amount of data related to gene expression and heterogeneity of the iPSC-RPE population has been generated in this work.

Weaknesses:<br /> However, the justification of the analysis, and the physiological relevance of the hypothesis and the findings could be strengthened.

Importantly, I fail to grasp from the introduction what is the previous evidence that leads to the hypothesis. Why would color intensity be related to the quality of cell transplantation? In fact, cell transplantation is not evaluated at all in this work. The authors mention "quality metrics for clinical use", but this concept is not further explained. Neither is the concept of "sufficient degree of pigmentation" explained.

On the other hand, the positive correlation of cluster formation with complement and lysosome-related genes is not discussed.

As a consequence, it is very difficult to evaluate the impact of these findings on the field.

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).

Reviewer #2 (Public Review):

This paper introduces a new model that aims to explain the generators of temporal decoding matrices (TGMs) in terms of underlying signal properties. This is important because TGMs are regularly used to investigate neural mechanisms underlying cognitive processes, but their interpretation in terms of underlying signals often remains unclear. Furthermore, neural signals are often variant over different instances of stimulation despite behaviour being relatively stable. The author aims to tackle these concerns by developing a generative model of electrophysiological data and then showing how different parameterizations can explain different features of TGMs. The developed technique is able to capture empirical observations in terms of fundamental signal properties. Specifically, the model shows that complexity is necessary in terms of spatial configuration, frequencies and latencies to obtain a TGM that is comparable to empirical data.

The major strength of the paper is that the novel technique has the potential to further our understanding of the generators of electrophysiological signals which are an important way to understand brain function. The paper clearly outlines how the method can be used to capture empirical data. Furthermore, the used techniques are state-of-the-art and the developed model is publicly shared in open source code.

On the other hand, there is no unambiguous mapping between neurobiological mechanisms and different signal generators, making it hard to draw firm conclusions about neural underpinnings based on this analysis.

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

Reviewer #2 (Public Review):

This manuscript by Petersen and colleagues investigates the mechanistic underpinnings of activation of the ion channel TREK-1 by mechanical inputs (fluid shear or membrane stretch) applied to cells. Using a combination of super-resolution microscopy, pair correlation analysis and electrophysiology, the authors convincingly show that the application of shear to a cell can lead to changes in the distribution of TREK-1 and the enzyme PhospholipaseD2 (PLD2), relative to lipid domains defined by either GM1 or PIP2. The activation of TREK-1 by mechanical stimuli was shown to be sensitized by the presence of PLD2, but not a catalytically inactive xPLD2 mutant. In addition, the activity of PLD2 is increased when the molecule is more associated with PIP2, rather than GM1 defined lipid domains. The presented data do not exclude direct mechanical activation of TREK-1, rather suggest a modulation of TREK-1 activity, increasing sensitivity to mechanical inputs, through an inherent mechanosensitivity of PLD2 activity. The authors additionally demonstrate that cellular uptake of cholesterol inhibits TREK-1 activation and, in ex vivo studies, that depletion of cholesterol from astrocytes reduces correlation of TREK-1 and G1 lipids in mouse brain slices. In vivo studies, using Drosophila melanogaster behavioural assays, were used to demonstrate that disrupting PLD2 altered behavioural responses to mechanical and electrical inputs. These data demonstrate that manipulation of PLD2 analogue in the fly can alter sensory transduction, suggesting that PLD functions to regulate sensitivity to mechanical force. However, as the authors note, there is no TREK-1 homologue in this organism: thus the identity of the downstream effectors of PLD in D. melanogaster remain unknown. This work will be of interest to the growing community of scientists investigating the myriad mechanisms that can tune mechanical sensitivity of cells, providing valuable insight into the role of functional PLD2 in sensitizing TREK-1 activation in response to mechanical inputs, in some cellular systems.

The authors convincingly demonstrate that, post application of shear, an alteration in the distribution of TREK-1 and mPLD2 (in HEK293T cells) from being correlated with GM1 defined domains (no shear) to increased correlation with PIP2 defined membrane domains (post shear). The association of TREK-1 with PIP2 required functional mPLD2. These data were generated using super-resolution microscopy to visualise, at sub diffraction resolution, the localisation of labelled protein, compared to labelled lipids. The use of super-resolution imaging enabled the authors to visualise changes in cluster association that would not have been achievable with diffraction limited microscopy.

This work provides further evidence of the astounding flexibility of mechanical sensing in cells. By outlining how mechanical activation of TREK-1 can be sensitised by mechanical regulation of PLD2 activity, the authors highlight a mechanism by which TREK-1 sensitivity could be regulated under distinct physiological conditions.

Reviewer #3 (Public Review):

The manuscript "Mechanical activation of TWIK-related potassium channel by nanoscopic movement and second messenger signaling" presents a new mechanism for the activation of TREK-1 channel. The mechanism suggests that TREK1 is activated by phosphatidic acids that are produced via a mechanosensitive motion of PLD2 to PIP2-enriched domains. Overall, I found the topic interesting but several typos and unclarities reduced the readability of the manuscript. Additionally, I have several major concerns on the interpretation of the results. Therefore, the proposed mechanism is not fully supported by the presented data. Lastly, the mechanism is based on several previous studies from the Hansen lab, however, the novelty of the current manuscript is not clearly stated. For example, in the 2nd result section, the authors stated, "fluid shear causes PLD2 to move from cholesterol dependent GM1 clusters to PIP2 clusters and this activated the enzyme". However, this is also presented as a new finding in section 3 "Mechanism of PLD2 activation by shear."<br /> In the revised manuscript, the authors addressed most of my concerns. I still have the following suggestions/confusions.<br /> 1. the reviewer would highly appreciate verification of the cholesterol assay, either by additional experiment or by citations of independent work.

2. The claim on "shear thinning" is still very confusing. First, asymmetric insertion of molecules to one monolayer of the membrane is a main mechanism for membrane bending and curvature formation. Second, why is "shear thinning" equivalent to entropy/order?

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.

Reviewer #2 (Public Review):

In their submitted manuscript, Blin et al. describe differences in the olfactory-driven behaviors of river-dwelling surface forms and cave-dwelling blind forms of the Mexican tetra, Astyanax mexicanus. They provide a dataset of unprecedented detail, that compares not only the behaviors of the two morphs but also that of a significant number of F2 hybrids, therefore also demonstrating that many of the differences observed between the two populations have a clear (and probably relatively simple) genetic underpinning.

To complete the monumental task of behaviorally testing 425 six-week-old Astyanax larvae, the authors created a setup that allows for the simultaneous behavioral monitoring of multiple larvae and the infusion of different odorants without introducing physical perturbations into the system, thus biasing the responses of cavefish that are particularly fine-tuned for this sensory modality. During the optimization of their protocol, the authors also found that for cave-dwelling forms one hour of habituation was insufficient and a full 24 hours were necessary to allow them to revert to their natural behavior. It is also noteworthy that this extremely large dataset can help us see that population averages of different morphs can mask quite significant variations in individual behaviors.

Testing with different amino-acids (applied as relevant food-related odorant cues) shows that cavefish are alanine- and histidine-specialists, while surface fish elicit the strongest behavioral responses to cysteine. It is interesting that the two forms also react differently after odor detection: while cave-dwelling fish decrease their locomotory activity, surface fish increase it. These differences are probably related to different foraging strategies used by the two populations, although, as the observations were made in the dark, it would be also interesting to see if surface fish elicit the same changes in light as well.

Further work will be needed to pinpoint the exact nature of the genetic changes that underlie the differences between the two forms. Such experimental work will also reveal how natural selection acted on existing behavioral variations already present in the SF population.

It will be equally interesting, however, to understand what lies behind the large individual variation of behaviors observed both in the case surface and cave populations. Are these differences purely genetic, or perhaps environmental cues also contribute to their development? Does stochasticity provided by the developmental process has also a role in this? Answering these questions will reveal if the evolvability of Astyanax behavior was an important factor in the repeated successful colonization of underground caves.

Reviewer #3 (Public Review):

Summary:<br /> The paper explores chemosensory behaviour in surface and cave morphs and F2 hybrids in the Mexican cavefish Astyanax mexicanus. The authors develop a new behavioural assay for the long-term imaging of individual fish in a parallel high-throughput setup. The authors first demonstrate that the different morphs show different basal exploratory swimming patterns and that these patterns are stable for individual fish. Next, the authors test the attraction of fish to various concentrations of alanine and other amino acids. They find that the cave morph is a lot more sensitive to chemicals and shows directional chemotaxis along a diffusion gradient of amino acids. For surface fish, although they can detect the chemicals, they do not show marked chemotaxis behaviour and have an overall lower sensitivity. These differences have been reported previously but the authors report longer-term observations on many individual fish of both morphs and their F2 hybrids. The data also indicate that the observed behavior is a quantitative genetic trait. The approach presented will allow the mapping of genes' contribution to these traits. The work will be of general interest to behavioural neuroscientists and those interested in olfactory behaviours and the individual variability in behavioural patterns.

Strengths:<br /> A particular strength of this paper is the development of a new and improved setup for the behavioural imaging of individual fish for extended periods and under chemosensory stimulation. The authors show that cavefish need up to 24 h of habituation to display a behavioural pattern that is consistent and unlikely to be due to the stressed state of the animals. The setup also uses relatively large tanks that allow the build-up of chemical gradients that are apparently present for at least 30 min.

The paper is well written, and the presentation of the data and the analyses are clear and to a high standard.

Weaknesses:<br /> One point that would benefit from some clarification or additional experiments is the diffusion of chemicals within the behavioural chamber. The behavioural data suggest that the chemical gradient is stable for up to 30 min, which is quite surprising. It would be great if the authors could quantify e.g. by the use of a dye the diffusion and stability of chemical gradients.

The paper starts with a statement that reflects a simplified input-output (sensory-motor) view of the organisation of nervous systems. "Their brains perceive the external world via their sensory systems, compute information and generate appropriate behavioral outputs." The authors' data also clearly show that this is a biased perspective. There is a lot of spontaneous organised activity even in fish that are not exposed to sensory stimulation. This sentence should be reworded, e.g. "The nervous system generates autonomous activity that is modified by sensory systems to adapt the behavioural pattern to the external world." or something along these lines.

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.

Reviewer #2 (Public Review):

The mechanisms that mediate female aggression remain poorly understood. Chiu, Schretter, and colleagues, employed circuit dissection techniques to tease apart the specific roles of particular doublesex and fruitless expressing neurons in the fly Drosophila in generating a persistent aggressive state. They find that activating the fruitless positive alPg neurons, generated an aggressive state that persisted for >10min after the stimulation ended. Similarly, activating the doublesex positive pC1de neurons also generated a peristent state. Activating pC1d or pC1e individually did not induce a persistent state. Interestingly, while neural activation of alPGs and pC1d+e neurons induced a persistent behavioural states it did not induce persistent activity in the neurons being activated.

The authors have revised the manuscript in accordance with comments of the reviewers. The conclusions of this paper are by and large well supported by the data. These data will be a useful addition to the literature on the circuit basis of female aggression, and open up intriguing avenues for further studies to explore.

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.

Reviewer #2 (Public Review):

In this study, the authors describe a pipeline to sequence expressed var genes from RNA sequencing that improves on a previous one that they had developed. Importantly, they use this approach to determine how var gene expression changes with short-term culture. Their finding of shifts in the expression of particular var genes is compelling and casts some doubt on the comparability of gene expression in short-term culture versus var expression at the time of participant sampling.

Other studies have relied on short-term culture to understand var gene expression in clinical malaria studies. This study indicates the need for caution in over-interpreting findings from these studies.

We appreciate the careful attention of the authors to our comments and the edits that have been made. One additional suggestion that would be helpful to readers is to include in Table S1 the new approach described in the manuscript. This will provide the reader a direct means of comparing what the authors have done to past work.

Reviewer #3 (Public Review):

This research addresses a critical challenge in malaria research, specifically how to effectively access the highly polymorphic var gene family using short-read sequence data. The authors successfully tackled this issue by introducing an optimization of their original de novo assembler, which notably more than doubled the N50 metric and greatly improved the assembly of var genes.

The most intriguing aspect of this study lies in its methodologies, particularly the longitudinal analysis of assembled var transcripts within subjects. This approach allows for the construction of an unbiased var repertoire for each individual, free from the influence of a reference genome or other samples. These sample-specific var gene repertoires are then tracked over time in culture to evaluate the reliability of using cultured samples for inferences about in vivo expression patterns. The findings from this analysis are thought-provoking. While the authors conclude that culturing parasites can lead to unpredictable transcriptional changes, they also observe that the overall ranking of each var gene remains relatively robust over time. This resilience in the var gene ranking within individuals raises intriguing questions about the mechanisms behind var gene switching and adaptation during short-term culture.

In addition to the var gene-specific analysis, the study also delves into a comparison of ex vivo samples with generation 1 and generation 2 cultured parasites across the core genome. This analysis reveals substantial shifts in expression due to culture adaptation, shedding light on broader changes in the parasite transcriptome during short-term culture.

In summary, this research contributes to our understanding of var gene expression and potentially associations with disease. It emphasizes the importance of improved assembly techniques to access var genes and underscores the challenges of using short-term cultured parasites to infer in vivo characteristics. The longitudinal analysis approach offers a fresh perspective on var gene dynamics within individuals and highlights the need for further investigations into var gene switching and adaptation during culture.

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.

Reviewer #2 (Public Review):

In this study, a minimalist setup was used to investigate the selectivity of the nuclear pore complex as a function of its diameter. To this end, a series of solid-state pores in a free-standing palladium membrane were designed and attached to a PDMS-based fluid cell that could be mounted on a confocal microscope. In this way, the frequency of translocation events could be measured in an unbiased manner. Furthermore, the pores were designed to exhibit the key properties of the nuclear pore complex: (i) the size of the pore, (ii) disordered FG Nups specifically located in the central channel; (ii) transport receptors that can shuttle through the central channel by binding to the FG-Nups. Additionally, such system offered the advantage of monitoring the translocation of multiple fluorescently labeled molecules (e.g. Kap95 and BSA) simultaneously and under well-controlled conditions.

The authors were able to demonstrate convincingly that the pore selectivity depends on the pore diameter, the FG Nup layer organization within the pore and the transport receptors concentration that can specifically interact with FG Nups. It was shown that the pores coated with FG Nups (e.g. Nsp1 in this case) and smaller than 50-60 nm are highly selective and such selectivity is increasing with the decrease of the pore diameter. Also, it was shown that the pore selectivity moderately enhances at the high Kap95 concentration (1 µM). Importantly, it was also shown that the selectivity is becoming negligible for the pores, which are larger than 60-75 nm.

The experimental data are well supported by coarse-grained modelling of Nsp1-coated pores, and the theoretical prediction correlates qualitatively with the experimentally obtained data.

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.

Reviewer #2 (Public Review):

This study explores the breadth of effects of one important metabolite, azelaic acid, on marine microbes, and reveals in-depth its pathway of uptake and catabolism in one model bacterial strain. This compound is known to be widely produced by phytoplankton and plants, and to have complex effects on associated microbiomes.

This work uses transcriptomics to assay the response of two strains that show contrasting responses to the metabolite: one catabolizes the compound and assimilates the carbon, while the other shows growth inhibition and stress response. A highly induced TRAP transporter, adjacent to a previously identified regulator, is inferred to be the specific uptake system for azelaic acid, though this function was not directly tested via genetic or biochemical methods. Nevertheless, this is a significant finding that will be useful for exploring the distribution of azelaic acid uptake capability across metagenomes and other bacteria.

The authors use pulse-chase style metabolomics experiments to beautifully demonstrate the fate of azelaic acid through catabolic pathways. They also measure an assimilation rate per cell, though it remains unclear how this measured rate relates to natural systems. The metabolomics approach is an elegant way to show carbon flux through cells, and could serve as a model for future studies.

The study seeks to extend the results from two model strains to complex communities, using seawater mesocosm experiments and soil/Arabidopsis experiments. The seawater experiments show a community shift in mesocosms with added azelaic acid. The mechanisms for the shift were not determined in this study; further work is necessary to demonstrate which community members are directly assimilating the compound, benefitting indirectly, or experiencing inhibition. The authors also took the unusual and creative step of performing similar experiments in a soil - Arabidopsis system. I admire the authors' desire to identify unifying themes across ecosystems. The parallels are intriguing, and future experiments could determine the different modes of action in aquatic vs terrestrial microbial communities.

This work is a nice illustration of how we can begin to tease apart the effects of chemical currencies on marine ecosystems. A key strength of this work is the combination of transcriptomics and metabolomics methods, along with assaying the impacts of the metabolite on model strains of bacteria and whole communities. Given the sheer number of compounds that probably play critical roles in community interactions, a key challenge for the field will be navigating the tradeoffs between breadth and depth in future studies of metabolite impacts. This study offers a good compromise and will be a useful model for future studies.

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.

Reviewer #2 (Public Review):

In this study, the authors utilize a compendium of public genomic data to identify transcription factors (TF) that can identify their DNA binding motifs in the presence of nuclosome-wrapped chromatin and convert the chromatin to open chromatin. This class of TFs are termed Pioneer TFs (PTFs). A major strength of the study is the concept, whose premise is that motifs bound by PTFs (assessed by ChIP-seq for the respective TFs) should be present in both "closed" nucleosome wrapped DNA regions (measured by MNase-seq) as well as open regions (measured by DNAseI-seq) because the PTFs are able to open the chromatin. Use of multiple ENCODE cell lines, including the H1 stem cell line, enabled the authors to assess if binding at motifs changes from closed to open. Typical, non-PTF TFs are expected to only bind motifs in open chromatin regions (measured by DNaseI-seq) and not in regions closed in any cell type. This study contributes to the field a validation of PTFs that are already known to have pioneering activity and presents an interesting approach to quantify PTF activity.

For this reviewer, there were a few notable limitations. One was the uncertainty regarding whether expression of the respective TFs across cell types was taken into account. This would help inform if a TF would be able to open chromatin. Another limitation was the cell types used. While understandable that these cell types were used, because of their deep epigenetic phenotyping and public availability, they are mostly transformed and do not bear close similarity to lineages in a healthy organism. Next, the methods used to identify PTFs were not made available in an easy-to-use tool for other researchers who may seek to identify PTFs in their cell type(s) of interest. Lastly, some terms used were not defined explicitly (e.g., meaning of dyads) and the language in the manuscript was often difficult to follow and contained improper English grammar.

Reviewer #3 (Public Review):

Peng et al. designed a computational framework for identifying pioneer factors using epigenomic data from five cell types. The identification of pioneer factors is important for our understanding of the epigenetic and transcriptional regulation of cells. A computational approach toward this goal can significantly reduce the burden of labor-intensive experimental validation.

The authors have addressed my previous comments.

The main issue identified in this re-review is based on the authors' additional experiments to investigate the reproducibility of the pioneer factors identified in the previous analysis that anchored on H1 ESCs.

The additional analysis that uses the other four cell types (HepG2, HeLa-S3, MCF-7, and K562) as anchors reveals the low reproducibility/concordance and high dependence on the selection of anchor cell type in the computational framework. In particular, now several stem cell related TFs (e.g. ESRRB, POU5F1) are ranked markedly higher when H1 ESC is not used as the anchor cell type as shown in Supplementary Figure 5.

Of note, the authors have now removed the shape labels that denote Yamanaka factors in Figure 2c (revised manuscript) that was presented in the main Figure 2a in the initial submission. The NFYs and ESRRB labels in Supplementary 4a are also removed and the boxplot comparing NFYs and ESRRB with other TF are also removed in this figure. Removing these results effectively hides the issues of the computational framework we identified in this revision. Please justify why this was done.

In summary, these new results reveal significant limitations of the proposed computational framework for identifying pioneer factors. The current identifications appear to be highly dependent on the choice of cell types.

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.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Yu and colleagues sought to identify new susceptibility genes for adolescent idiopathic scoliosis (AIS). The significance of this work is high, especially given the still large knowledge gap of the mechanistic underpinnings for AIS. In this multidisciplinary body of work, the authors first performed a genetic association study of AIS case-control cohorts (combined 9,161 cases and 80,731 controls) which leveraged common SNPs in 1027 previously defined matrisome genes. Two nonsynonymous variants were found to be significantly associated with AIS: MMP14 p.Asp273Asn and COL11A1 p.Pro1153Leu, the latter of which had the more robust association and remained significant when females were tested independent of males. Next, the authors followed a series of functional validation experiments to support biological involvement of COL11A1 p.Pro1153Leu in AIS through expression, biochemical, and histological studies in physiologically relevant cell and mouse models. Together, the authors propose a hitherto unreported model for AIS that involves the interplay of the COL11A1 susceptibility locus with estrogen signaling to alter a Pax1-Col11a1-Mmp3 signaling axis at the growth plate.

Strengths:

The manuscript is clearly written and follows a series of logical steps toward connecting multiple matrisome genes and putative AIS effectors in a new framework of pathomechanism. The multidisciplinary nature of the work makes it a strong body of work wherein multiple models offer multiple lines of supportive data. Thus, this manuscript remains an important multidisciplinary study of the genetic and functional basis of adolescent idiopathic scoliosis (AIS). To the benefit of the overall manuscript quality, the reviewers have addressed most concerns to satisfaction. Please include the list of three rare missense variants mentioned in the response to reviewers as a supplementary table. Please also include methods for the SKATO rare variant burden analysis.

Reviewer #3 (Public Review):

Summary:

This article demonstrates a Pax1-Col11a1-Mmp3 signaling axis associated with adolescent idiopathic scoliosis and finds that estrogen affects this signaling axis. In addition, the authors have identified a new COL11A1 mutation and verified its effect on the Pax1-Col11a1-Mmp3 axis.

Strengths:

1. Col11a1P1335L is verified in multicenter cohorts with high confidence.

2. The article identified a potential pathogenesis of AIS.

Weaknesses:

The SV40-immortalized cell line established from Col11a1fl/fl mouse rib cartilage was applied in the study, and overexpression system was used to confirm that P1335L variant in COL11A1 perturbs its regulation of MMP3. However, due to the absence of P1335L point mutant mice, it cannot be confirmed whether P1335L can actually cause AIS, and the pathogenicity of this mutation cannot be directly verified.

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.

Reviewer #2 (Public Review):

Summary:<br /> In Ferrareti et al. they identify adaptively introgressed genes using VolcanoFinder and then identify pathways enriched for adaptively introgressed genes. They also use a signet to identify pathways that are enriched for Denisovan alleles. The authors find that angiogenesis and nitric oxide induction are enriched for archaic introgression.

Strengths:<br /> Most papers that have studied the genetic basis of high altitude (HA) adaptation in Tibet have highly emphasized the role of a few genes (e.g. EPAS1, EGLN1), and in this paper, the authors look for more subtle signals in other genes (e.g EP300, NOS 2) to investigate how archaic introgression may be enriched at the pathway level.

Looking into the biological functions enriched for Denisovan introgression in Tibetans is important for characterizing the impact of Denisovan introgression.

Weaknesses:<br /> The manuscript lacks details or justification about how/why some of the analyses were performed. Below are some examples where the authors could provide additional details.

The authors made specific choices in their window analysis. These choices are not justified or there is no comment as to how results might change if these choices were perturbed. For example, in the methods, the authors write "Then, the genome was divided into 200 kb windows with an overlap of 50 kb and for each of them we calculated the ratio between the number of significant SNVs and the total number of variants."

Additional information is needed for clarity. For example, "we considered only protein-protein interactions showing confidence scores {greater than or equal to} 0.7 and the obtained protein frameworks were integrated using information available in the literature regarding the functional role of the related genes and their possible involvement in high-altitude adaptation." What do the confidence scores mean? Why 0.7?

In the method section (Identifying gene networks enriched for Denisovan-like derived alleles), the authors write "To validate VolcanoFinder results by using an independent approach". Does this mean that for signet the authors do not use the regions identified as adaptively introgressed using volcanofinder? I thought in the original signet paper, the authors used a summary describing the amount of introgression of a given region.

Later, the authors write "To do so, we first compared the Tibetan and Denisovan genomes to assess which SNVs were present in both modern and archaic sequences. These loci were further compared with the ancestral reconstructed reference human genome sequence (1000 Genomes Project Consortium et al., 2015) to discard those presenting an ancestral state (i.e., that we have in common with several primate species)." It is not clear why the authors are citing the 1000 genomes project. Are they comparing with the reference human genome reference or with all populations in the 1000 genomes project? Also, are the authors allowing derived alleles that are shared with Africans? Typically, populations from Africa are used as controls since the Denisovan introgression occurred in Eurasia.

The methods section for Figures 4B, 4C, and 4D is a little hard to understand. What is the x-axis on these plots? Is it the number of pairwise differences to Denisovan? The caption is not clear here. The authors mention that "Conversely, for non-introgressed loci (e.g., EGLN1), we might expect a remarkably different pattern of haplotypes distribution, with almost all haplotype classes presenting a larger proportion of non-Tibetan haplotypes rather than Tibetan ones." There is clearly structure in EGLN1. There is a group of non-Tibetan haplotypes that are closer to Denisovan and a group of Tibetan haplotypes that are distant from Denisovan...How do the authors interpret this?

In the original signet paper (Guoy and Excoffier 2017), they apply signet to data from Tibetans. Zhang et al. PNAS (2021) also applied it to Tibetans. It would be helpful to highlight how the approach here is different.

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.

Reviewer #2 (Public Review):

In the manuscript by Rajan et al., the authors have highlighted the direct interaction between Dbp5 and tRNA, wherein Dbp5 serves as a mediator for tRNA export. This export process is subject to spatial regulation, as Dbp5 ATPase activation occurs specifically at nuclear pore complexes. Notably, this regulation is independent of the Los1-mediated pre-tRNA export route and instead relies on Gle1. The manuscript is well constructed and nicely written.

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).

Reviewer #2 (Public Review):

In their study, Stajich and co-authors present a new 1.03 Gb genome assembly for an isolate of the fungal insect parasite Entomophthora muscae (Entomophthoromycota phylum, isolated from Drosophila hydei). Many species of the Entomophthoromycota phylum are specialised insect pathogens with relatively large genomes for fungi, with interesting yet largely unexplored biology. The authors compare their new E. muscae assembly to those of other species in the Entomophthorales order and also more generally to other fungi. For that, they first focus on repetitive DNA (transposons) and show that Ty3 LTRs are highly abundant in the E. muscae genome and contribute to ~40% of the species' genome, a feature that is shared by closely related species in the Entomophthorales. Next, the authors describe the major differences in protein content between species in the genus, focusing on functional domains, namely protein families (pfam), carbohydrate-active enzymes, and peptidases. They highlight several protein families that are overrepresented/underrepresented in the E. muscae genome and other Entomophthorales genomes. The authors also highlight differences in components of the circadian rhythm, which might be relevant to the biology of these insect-infecting fungi. To gain further insights into E. muscae specificities, the authors identify orthologous proteins among four Entomophthorales species. Consistently with a larger genome and protein set in E. muscae, they find that 21% of the 17,111 orthogroups are specific to the species. To finish, the authors examine the consistency between methods for species delineation in the genus using molecular (ITS + 28S) or morphological data (# of nuclei per conidia + conidia size) and highlight major incongruences between the two.

Although most of the methods applied in the frame of this study are appropriate with the scripts made available, I believe there are some major discrepancies in the datasets that are compared which could undermine most of the results/conclusions. More precisely, most of the results are based on the comparison of protein family content between four Entomophthorales species. As the authors mention on page 5, genome (transcriptome) assembly and further annotation procedures can strongly influence gene discovery. Here, the authors re-annotated two assemblies using their own methods and recovered between 30 and 60% more genes than in the original dataset, but if I understand it correctly, they perform all downstream comparative analyses using the original annotations. Given the focus on E. muscae and the small sample size (four genomes compared), I believe performing the comparisons on the newly annotated assemblies would be more rigorous for making any claim on gene family variation.

The authors also investigate the putative impact of repeat-induced point mutation on the architecture of the large Entomophthorales genomes (for three of the eight species in Figure 1) and report low RIP-like dinucleotide signatures despite the presence of RID1 (a gene involved in the RIP process in Neurospora crassa) and RNAi machinery. They base their analysis on the presence of specific PFAM domains across the proteome of the three Entomophthorales species. In the case of RID1, the authors searched for a DNA methyltransferase domain (PF00145), however other proteins than RID1 bear such functional domain (DNMT family) so that in the current analysis it is impossible to say if the authors are actually looking at RID1 homologs (probably not, RID1 is monophyletic to the Ascomycota I believe). Similar comments apply to the analysis of components of the RNAi machinery. A more reliable alternative to the PFAM analysis would be to work with full protein sequences in addition to the functional domains.

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.

Reviewer #2 (Public Review):

Summary:<br /> The study by Toth et al. investigates the role of RIN4, a key immune regulator, in the symbiotic nitrogen fixation process between soybean and rhizobium. The authors found that SymRK can interact with and phosphorylate GmRIN4. This phosphorylation occurs within a 15 amino acid motif that is highly conserved in N-fixation clades. Genetic studies indicate that GmRIN4a/b play a role in root nodule symbiosis. Based on their data, the authors suggest that RIN4 may function as a key regulator connecting symbiotic and immune signaling pathways.

Overall, the conclusions of this paper are well supported by the data, although there are a few areas that need clarification.

Strengths:<br /> • This study provides important insights by demonstrating that RIN4, a key immune regulator, is also required for symbiotic nitrogen fixation.<br /> • The findings suggest that GmRIN4a/b could mediate appropriate responses during infection, whether it is by friendly or hostile organisms.

Weaknesses:<br /> • The study did not explore the immune response in the rin4 mutant. Therefore, it remains unknown how GmRIN4a/b distinguishes between friend and foe.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript by Toth et al reveals a conserved phosphorylation site within the RIN4 (RPM1-interacting protein 4) R protein that is exclusive to two of the four nodulating clades, Fabales and Rosales. The authors present persuasive genetic and biochemical evidence that phosphorylation at the serine residue 143 of GmRIN4b, located within a 15-aa conserved motif with a core five amino acids 'GRDSP' region, by SymRK, is essential for optimal nodulation in soybean. While the experimental design and results are robust, the manuscript's discussion fails to clearly articulate the significance of these findings. Results described here are important to understand how the symbiosis signaling pathway prioritizes associations with beneficial rhizobia, while repressing immunity-related signals.

Strengths:<br /> The manuscript asks an important question in plant-microbe interaction studies with interesting findings.

Overall, the experiments are detailed, thorough, and very well-designed. The findings appear to be robust.

The authors provide results that are not overinterpreted and are instead measured and logical.

Weaknesses:<br /> No major weaknesses. However, a well-thought-out discussion integrating all the findings and interpreting them is lacking; in its current form, the discussion lacks 'boldness'. The primary question of the study - how plants differentiate between pathogens and symbionts - is not discussed in light of the findings. The concluding remark, "Taken together, our results indicate that successful development of the root nodule symbiosis requires cross-talk between NF-triggered symbiotic signaling and plant immune signaling mediated by RIN4," though accurate, fails to capture the novelty or significance of the findings, and left me wondering how this adds to what is already known. A clear conclusion, for eg, the phosphorylation of RIN4 isoforms by SYMRK at S143 modulates immune responses during symbiotic interactions with rhizobia, or similar, is needed.

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.

Reviewer #2 (Public Review):

This manuscript proposed a new link between the formation of chloroplast budding vesicles (Rubisco-containing bodies [RCBs]) and the development of chloroplast-associated autophagosomes. The authors' previous work demonstrated two types of autophagy pathways involved in chloroplast degradation, including piecemeal degradation of partial chloroplast and whole chloroplast degradation. However, the mechanisms underlying piecemeal degradation are largely unknown, particularly regarding the initiation and release of the budding structures. Here, the authors investigated the progression of piecemeal-type chloroplast trafficking by visualizing it with a high-resolution time-lapse microscope. They provide evidence that autophagosome formation is required for the initiation of chloroplast budding, and that stromule formation is not correlated with this process. In addition, the authors also demonstrated that the release of chloroplast-associated autophagosome is independent of a chloroplast division factor, DRP5b.

Overall, the findings are interesting, and in general, the experiments are very well executed. Although the mechanism of how Rubisco-containing bodies are processed is still unclear, this study suggests that a novel chloroplast division machinery exists to facilitate chloroplast autophagy, which will be valuable to investigate in the future.

Reviewer #3 (Public Review):

Summary:<br /> Regulated chloroplast breakdown allows plants to modulate these energy-producing organelles, for example during leaf aging, or during changing light conditions. This manuscript investigates how chloroplasts are broken down during light-limiting conditions.

The authors present very nice time-lapse imaging of multiple proteins as buds form on the surface of chloroplasts and pinch away, then associate with the vacuole. They use mutant analysis and autophagy markers to demonstrate that this process requires the ATG machinery, but not dynamin-related proteins that are required for chloroplast division. The manuscript concludes with a discussion of an internally-consistent model that summarizes the results.

Strengths:<br /> The main strength of the manuscript is the high-quality microscopy data. The authors use multiple markers and high-resolution time-lapse imaging to track chloroplast dynamics under light-limiting conditions.

Weaknesses:<br /> The main weakness of the manuscript is the lack of quantitative data. Quantification of multiple events is required to support the authors' claims, for example, claims about which parts of the plastid bud, about the dynamics of the events, about the colocalization between ATG8 and the plastid stroma buds, and the dynamics of this association. Without understanding how often these events occur and how frequently events follow the manner observed by the authors (in the 1 or 2 examples presented in each figure) it is difficult to appreciate the significance of these findings.