Reviewer #1 (Public Review):

This well-written paper combines a novel method for assaying ubiquitin-proteasome system (UPS) activity with a yeast genetic cross to study genetic variation in this system. Many loci are mapped, and a few genes and causal polymorphism are identified. A connection between UPS variation and protein abundance is made for one gene, demonstrating that variation in this system may affect phenotypic variation.

The major strength of the study is the power of yeast genetics which makes it possible to dissect quantitative traits down to the nucleotide level. The weakness is that is not clear whether the observed UBS variation matters on any level, however, the claims are suitable to moderate, and generally supported.

The paper provides a nice example of how it is possible to genetically dissect an "endo-phenotype", and learn some new biology. It also represents a welcome attempt to put the function of a mechanism that is heavily studied in molecular cell biology in a broader context.

Reviewer #3 (Public Review):

This manuscript, "Variation in Ubiquitin System Genes Creates Substrate-Specific Effects on Proteasomal Protein Degradation" studies the genetic basis of differences in protein degradation. The authors do so by screening natural genetic variation in two yeast strains, finding several genes and often several variants within each gene that can affect protein degradation efficiency by the Ubiquitin-Proteasome system (UPS). Many of these variants have "substrate-specific effects" meaning they only affect the degradation of specific proteins (those with specific degrons). Also, many variants located within the same genes have conflicting effects, some of which are larger than others and can mask others. Overall, this study reveals a complex genetic basis for protein degradation.

Strengths: Revealing the genetic basis for any complex trait, such as protein degradation, is a major goal of biology. The results of this paper make a significant step towards the goal of mapping the genes and variants involved in this specific trait. Fine mapping methods are used to home in on the specific variants involved and to measure their effects. This is very nicely done and provides a detailed view of the genetic basis of protein degradation. Further, the GFP/RFP system used to quantify the efficiency of the protein degradation system is a very elegant system. Also, the completeness of the analysis, meaning that all 20 N-degrons were studied, is impressive and leads to very detailed findings. It is interesting that some genetic variants have larger and opposite effects on the degradation of different N-degrons.

Weaknesses: Some of the results discussed in this paper are not surprising. For example, the finding that both large effect and small effect genetic variants contribute to this complex trait is not at all surprising. This is true of many complex traits. The discussion of human disease is also a bit extensive given this study was performed on yeast. It might be more productive to use these findings to understand the UPS better on a mechanistic level. Why does the same genetic variant have opposite effects on the degradation of different degrons, even in cases where those degrons are of the same type?

Overall, this manuscript excels at mapping the genetic basis of variation in the UPS system. It demonstrates a very complex mapping from genotype to phenotype that begs for further mechanistic explanation. These results are important to the UPS field because they may help researchers interrogate this highly conserved essential system. The manuscript is weaker when it comes to the broader conclusions drawn about the relative importance of large vs. small effects variants on complex traits, the amount of heritability explained, and the effects of genetic variation on protein abundance vs transcript abundance. Though in the case of protein vs transcript, I feel the cursory examination of the trends is perhaps at an appropriate level for the study, as it is mainly meant to show these things differ rather than to show exactly how and why they differ.

Reviewer #4 (Public Review):

Overall the paper is clear and well-written. The experimental design is elegant and powerful, and it's a stimulating read. Most QTL mapping has focused on directly measurable phenotypes such as expression or drug response; I really like this paper's distinctive approach of placing bespoke functional assays for a specific molecular mechanism into the classical QTL framework.

Reviewer #1 (Public Review):

Overall this is a decently controlled clinical study with an investigation into both the humoral and cellular immune responses generated by a whole virus vaccine. The conclusions note that T cell immunity can likely be achieved quickly with a short-span dosing schedule but that an optimal humoral response may need longer exposure durations and likely boosters to increase breadth and neutralization capabilities. There are no overt weaknesses in the manuscript however, its applicability to the broader COVID field is limited as no comparison to mRNA-based vaccines was made.

Reviewer #3 (Public Review):

This paper reports the humoral (neutralizing antibody concentrations from serum) and cellular (cytopathic effect on Vero cells) immune responses of volunteers enrolled in a randomized clinical trial for the CoronaVac® SARS-CoV-2 vaccine. The findings are useful and, through solid reporting, discussion, and statistical analyses, provide context for the efficaciousness of the 0-14 day and 0-28 day dosing schedules of CoronaVac®. The results show that these two dosing schedules are similar across most metrics. Furthermore, the findings pave the way for key future work, including reporting and understanding the clinically relevant protective effects, and how long they last, of CoronaVac® against the emerging variants/subvariants.

Reviewer #1 (Public Review):

The combination of near-completion of the Drosophila brain connectome and the simultaneous development of neurogenetic tools for manipulating neurons with high temporal and spatial specificity provides a new opportunity to understand the functional relevance and underlying molecular biology of circuits within the Drosophila brain with unprecedented coverage and resolution. A major challenge to this is matching neurons in connectomic datasets to those in known driver lines. NeuronBridge is a useful online search tool that builds on previous tools developed by the community (such as Neuron Basic Local Alignment Tool (NBLAST) and Color Depth Maximum Intensity Projection (CDM)) to link images from ~74000 fly brains to themselves so it's possible to find multiple lines that express in the same neuron, and to neurons in the FlyEM hemibrain connectomics data. This is an important resource for the Drosophila neuroscience community as it provides the ability to generate tools for manipulating neurons with unparalleled resolution and link high resolution anatomy and connectivity to function. Meissner et al is a very accessible manuscript which is written to provide detail and clarity for the expert reader, and includes enough information, resources and references for amateur and novice readers to follow. The authors did an excellent job of outlining their questions and problems, how these challenges were addressed, and the performance of the NeuronBridge software.

Overall the claims in the manuscript are clearly communicated and justified by the data. However, one of the features on NeuronBridge that was mentioned in the manuscript did not work intuitively and could use more description in the manuscript. This was the feature to upload a confocal stack to search for other Gal4 lines or the appropriate neurons in the EM hemibrain. When a known Gal4 was in the database, it was easy and intuitive to go from a driver line to an EM neuron or, alternatively if an EM neuron was known it was easy to go from that neuron to find a driver line. It was, however, difficult to upload a stack and find the neuron names or a driver line. The example on Neuronbridge was somewhat helpful but an accompanying brief 'How-to' for this process in the manuscript would be very welcome. If it's a possibility, I recommend adding this in as a 'box' or Figure in the revised paper. Further, the authors may want to provide a troubleshooting guide on the website for uploading a confocal stack onto Neuronbridge.

As a relatively minor point, could the authors also provide more clarifications on the known number of neurons in the adult Drosophila brain? On line 182, the authors cite that the adult central brain has ~30,000 neurons. The approximations I'm most familiar with for the adult brain with range between 100,000-200,000 cells with ~50-67% of cells being in the optic lobes and maybe 10-15% being glia. That being said, some of those numbers don't appear to have rigorous cell counts to back up the data although Raji et al (2021) recently found the whole adult brain has ~200,000 neurons with ~100,000 in the central brain and ~100,000 in the optic lobes. The authors should rewrite that statement in the introduction to provide clarity and accuracy on their numbers of neurons in the adult brain.

Reviewer #3 (Public Review):

Meissner et al. employ stochastic Gal4 labeling with MCFO to ease the identification candidate lines for split-Gal4 line generation to genetically target neurons of interest identified in EM traces. Data basis for the approach is a novel resource of 74k MCFO images aligned to the JRC18 template allowing the matching between EM and LM traces of single neurons. The resource is released in combination with data processing and query tools. In addition, an open web-based data portal to the released data collection and data mining tools is made available. This will allow broad access to this novel resource with the potential to create high impact in the community.

Strength:

The possibility to bridge between EM neuron traces and expression patterns in LM images is a key method to achieve and accelerate genetic access to individual neurons. The proposed resource and tools contribute to this effort and provide open and easy access to it. This also includes the possibility to upload and analyze own data using the provided infrastructure, which is a great asset.

Weaknesses:

While the generation and analysis of the MCFO data is described in great detail and the overall technical approach seems feasible, the description of the technical part and its evaluation are lacking important implementation details and scientific rigor. Although this is primarily a life science paper introducing a new data resource it's the mining capability making this resource really valuable. The provided evaluation of the image mining capabilities however is currently insufficient to support the very general claims on effectivity and speed of the method.

Reviewer #1 (Public Review):

This study aimed to test the hypothesis that resident immune cells are strategically positioned along the epididymal duct to provide different immunological environments to prevent pathogens from ascending the urogenital tract. By using an epididymitis mouse model, the differential responses at different segments along the epididymis were examined at both histological and gene expression levels, and the data appeared to support their hypothesis. Furthermore, single-cell RNA-seq analyses identified the composition of resident immune cell types along the epididymal duct, and the parabiosis model further corroborated the major findings. Overall, the study was well conducted and the major conclusion seems well supported. The only caveat is the lack of elucidation on the direct or indirect impact of the resident immune cells on sperm maturation.

Reviewer #1 (Public Review):

In their paper, Noel, Angelaki and colleagues investigate neural coding in an innovative closed-loop sensorimotor task, where monkeys navigate to a "firefly" target with a joystick in a virtual reality set-up. They collect an impressive data set of hundreds of single neurons from areas MST, 7a and dlPFC. They analyse the data set by fitting spike trains to a Poisson Generalized Additive Model (P-GAM) to discern the different influences (e.g. task variables, hidden variables) have on firing rates.

The strengths of the manuscript lie in the innovative task that relies closed-loop perception-action integration, the large data-set of single cells across sensory, parietal and frontal cortices and the novel analysis approach to this complex data set.

Weaknesses lie in the complexity of the data set and analyses that make it difficult for the reader to relate the results back to the literature of single units intensively characterised with optimised stimuli and more traditional tasks. This would allow the reader to potentially distinguish neural coding that is central to the particular task performance from unrelated signals and fully assess the novelty of the results. Further information on strength of unit tuning, responsiveness, task lateralisation, visual stimulus patterns and other methodological information would be helpful.

This work is of potentially considerable impact on the field as it is trying to capture the dynamic of neural coding across many single neurons in a closed-loop sensori-motor task.

Reviewer #3 (Public Review):

Noel et al provide a neural representational account of three brain areas in a virtual, visual navigation task paradigm especially designed to achieve a closed action-perception loop closely resembling natural behaviour. The authors recorded hundreds of neurons from three monkeys while the animals were engaged in the task where latent cognitive variables like distance travelled and distance to target continuously changed. The authors build on their previous work where they robustly characterized animal behaviour on this task paradigm. Here, they aim to find neural codes of dynamic, latent variables and report a mixed and heterogeneous profile of task variable coding distributed across the two brain areas in the parietal cortex (MSTd and area 7a) and one in the prefrontal cortex (dlPFC).

Major strength: Multi-area recording and the close-loop behavioural paradigm are major strengths of this study. The robust model-based analysis of neural data strengthens the paper even more. The correlation of coupling between MSTd and dlPFC and behaviour, albeit in a coarse time scale (of sessions), is particularly interesting and makes the paper strong by quantitatively relating behaviour to neural activity.

Major weakness: The paper mainly gives a long list of what task variables the three brain areas code for along with measures of connectivity between areas. Although this is a valuable contribution to the field, the study is not designed to test predictions of specific computational hypotheses. Towards the end of the paper, the authors bring up the two alternate mechanisms: vector-coding vs distance-coding, but only as a speculation. These two hypotheses could have been developed further at the outset to make specific predictions for neural dynamics and subsequently be tested in their data. This will likely lead to richer findings going beyond representations of task variables. Nevertheless, the findings presented in the paper are surely novel and exciting.

Impact: The main impact of the paper is neurophysiology under a novel, naturalistic behavioral paradigm. The data, both behavioral and neurophysiological, is rich and has potential to test predictions of more fine-grained computational hypotheses. However, the observation that MSTd codes for latent variables is not as surprising as the authors claim. Given the recent observations of heterogeneous variables represented in brain areas traditionally thought to be highly specific (e.g. locomotion variables in V1, mixed coding in EC etc.), it is not surprising to find latent variables in a 'traditionally' sensory area, especially in a continual behavioral paradigm where many variables are changing and are correlated.

Based on their previous work and this work, the authors mention multiple times the task strategy and its embodied nature. While the authors conclusively show the involvement of eye movement in solving the task, it is difficult to imagine a concrete definition of an embodied task strategy without clear alternate hypotheses. How would the animals behave if their eye movements were prevented? Worse performance (like humans did in their previous paper) or unable to perform (akin to a bird unable to fly without wings) or a different strategy? What should we predict based on the neural observation reported here? The impact of this paper would be greater if the authors bring up these questions and provide some speculations rooted in neurophysiological observations.

Reviewer #1 (Public Review):

Using a mouse model of menstruation the authors have investigated the contribution of stromal mesenchyme cell populations to the restotation of the luminal epithelium. This work has been performed by combining the strengths of trajectory analysis in single cell RNAseq data with lineage tracking of cells using reporter constructs. This approach is an excellent example of integrating bioinformatic analysis with in vivo modelling to achieve a synergy between the two different types of data. The findings are clear and well presented with careful consideration of confounding issues. The understanding developed of the restoration of the luminal epithelium using this model system helps to define the mechanisms involved in the rapid nature of this event. This understanding is of obvious relevance to a number of related human pathologies. As yet the comparison between the mouse model data and human systems is preliminary.

Reviewer #1 (Public Review):

An osteocyte cell line exposed to oxidant stress shows enhanced translocation of connexin43 to mitochondria where it forms hemichannels that favor the ATP synthesis. Moreover, connexin43 hemichannels mediate the K+, H+, and ATP transfer across the mitochondrial inner membrane. This article provides valuable information that explains relevant steps of preconditioning. The authors used ad hoc modern cell biology techniques to unravel the interaction of Cx43 with other critical molecular elements and to demonstrate the functional role of connexin hemichannels.

In general, the manuscript is well organized and clearly written. The discussion provides the required information to easily understand the relevance of each finding.

Reviewer #3 (Public Review):

This manuscript should be of broad interest to readers not only in the field of gap junction (GJ) mediated cell-to-cell communication but also to scientists and clinicians working on the function of mitochondria and metabolism. Their data elucidates a new function of Cx43 in regulating the energy (ATP) generation of mitochondria, e.g., under oxidative stress.

The canonical function of gap junctions is in direct cell-to-cell communication by forming plasma membrane traversing channels that electrically and chemically connect the cytoplasms of adjacent cells. These channels are assembled from connexin proteins, connexin 43 (Cx43). However, more recently new, non-canonical cellular locations and functions of Cx43 have been discovered, e.g. mitochondrial Cx43 (mtCx43). However, very little is known about where Cx43 transported into mitochondria is derived from, how Cx43 is transported into mitochondria, where it is located in mitochondria, in which form Cx43 is present in mitochondria, (polypeptides, hemi-channels (HCs), complete GJ channels), and what the function of mtCx43 is. The authors addressed the latter question. The authors provide convincing evidence that mtCx43 modulates mitochondrial homeostasis and function in bone osteocytes under oxidative stress. Together, their study suggests that mtCx43 hemi-channels regulate mitochondrial ATP generation by mediating K+, H+, and ATP transfer across the mitochondrial inner membrane by directly interacting with mitochondrial ATP synthase (ATP5J2), leading to an enhanced protection of osteocytes against oxidative insult. These findings provide important information of a role of Cx43 functioning directly in mitochondria and not at the canonical location in the plasma membrane. While most of the functional assays presented in Figures 2-8 appear solid, the mitochondrial localization of Cx43, its translocation into mitochondria under oxidative stress, and its configuration as hemi-channels (Figure 1) is less convincing. I have five general comments that should be addressed:

1) This study was performed in MLO-Y4 osteocyte cells. Is the H2O2 induced increase of mitochondrial Cx43 MLO-Y4 cell type or osteocyte specific, or is Cx43 playing a more general role in mitochondrial function, e.g. under oxidative stress? Osteoblasts such as MC3T3-E1 and MG63, and many other cell types endogenously express Cx43, and oxidative stress is a general physiological stressor, not only for osteocytes and bone cells. Attending to this question would address the generality of the findings for mitochondrial function.

2) The images of MLO-Y4 cells (Figure 1A) and the primary osteocytes isolated from Csf-1+/- and control mice (Figure 8) do not show visible gap junctions. I guess this is due to the fact that slides were stained with the Cx43(E2) antibody. I feel, staining of these cells in addition with the Cx43(CT) antibody would be helpful to get a better understanding on the distribution of Cx43 in gap junctions and undocked/un-oligomerized Cx43 in these cells.

3) The images of cells presented in Figure 1A are quite fussy. No mitochondria are visible, and the Cx43 staining is hazy and does not localize to any subcellular structures. Also, it is not clear if the higher resolution image presented in Figure 1C actually represents a mitochondrion. A good DIC image, or co-staining with another mitochondrial marker such as MitoTracker (as shown in Figure 4-S1) would make the localization and translocation of Cx43 into mitochondria upon oxidative stress more convincing. This is especially important as the translocation, although statistically significant, increases only by about 10% or less (Figure 1B). Such a small difference (also represented in the Western analyses presented in Figure 1D) could easily be artefactual, depending on how the correlation coefficient was generated. Of note in this respect is that control cells in Figure 1A appear larger (compare the size of the nuclei) and are spread out more than the H2O2 treated cells. Better, more clear images would make the mitochondrial localization/translocation more convincing.

4) How pure are the mitochondria that were probed for Cx43 by Western shown in Figure 1D? The preparation method described is relatively simple, collecting the 10,000xg supernatant (here 9,000xg supernatant) as mitochondrial fraction. Is it possible that the Cx43 signal, at least in part, is derived from other, contaminating membranes, such as PM, Golgi, or ER? Testing the mitochondrial preparation by Western with marker proteins specific for these compartments would strengthen the author's results.

5) The authors rely on previous studies to postulate that Cx43 in mitochondria forms hemichannels in their system, is localized in the inner membrane, and is oriented with the Cx43 C-termini facing the inter-membrane space (as schemed in Figure 8C). The authors use lucifer yellow (LY) dye transfer and carbenoxolone, but both are not hemi-channel specific probes. They are transferred by, and block GJ channels as well. Experiments, using hemi-channel specific probes would be more convincing. This is important, as the information cited is based on only two references (Boengler et al., 2009; Miro-Casas et al., 2009), and it still is highly unclear how a membrane protein that is co-translationally inserted into the ER membrane, then traffics through the Golgi to be inserted into the plasma membrane is actually imported into mitochondria and in which state (monomeric, hexameric). Why the Cx43(CT) specific antibody traverses the outer mitochondrial membrane and reaches the Cx43CT while the Cx43(E2) specific antibody is not described and clear either. Where are these mitochondria permeabilized with Triton X-100 as described in M&M?

Reviewer #1 (Public Review):

Tang et al. in this report investigate the effects of deleting Surf4 in mouse liver by generating three different mouse models. Previously this group has shown that Surf4 functions as a cargo receptor that facilitates the secretion of PCSK9 in cultured cells. Here they have deleted the gene in hepatocytes and find that there is a significant reduction in plasma PCSK9 levels with a resulting increase in LDLR protein and lowering of plasma cholesterol levels. Surf deletion in hepatocytes using albumin-Cre had no deleterious effects in liver. What was found was a 60% reduction in plasma PCSK9 with no change in PCSK9 mRNA levels. These results were confirmed using Cas9 mice in which Surf4 was acutely deleted. Consistent with the known function of PCSK9, the reduction in plasma PCSK9 was associated with a significant increased in liver LDLR protein levels. In addition to dramatically lower plasma cholesterol levels in all lipoprotein fractions, they also find reduced plasma TG levels they show was due to a marked reduction in apoB and TG secretion. Interestingly, there was no defect in intestinal lipid absorption. Combined the studies are well done and convincing show the role of Surf4 in facilitating PCSK9 and apoB secretion from liver. Interesting remaining questions would be to address whether Sruf4 plays a similar role in intestine and whether it is required for fat absorption from the gut.

Reviewer #1 (Public Review):

This work employs a new method, namely connectivity gradient, for measuring the brain-cognition relationship. Such a method has been proposed and widely studied in large-scale connectivity. It reveals that cortical function and intrinsic connectivity change systematically along a 'principal gradient', which has primary sensory and motor cortex at one end, and transmodal regions implicated in abstract and memory-based functions at the other. Recently it has become possible to detect such gradient associations in humans using task-based fMRI. This paper provides a modelling and inference framework for detecting such gradient-related links to human semantic cognition. Specifically, the authors manipulated the degree to which ongoing semantic cognition was aligned with long-term semantic knowledge and quantified the similarity of the multivariate response to each trial along the principal gradient. Such elegant design should therefore be expected to indicate that the dimensionality of neural representations in a semantic task to decrease from unimodal to transmodal areas along the principal gradient, reflecting increasingly abstract and culturally shared representations towards the apex of the gradient. This work could be a promising flag-use for task-based fMRI brain-cognition association studies using the gradient method.

Reviewer #3 (Public Review):

With resting-state fMRI data, recent work has mapped the organisation of the cortex along a continuous gradient, and regions that share similar patterns of functional connectivity are located at similar points on the gradient (Margulies et al., 2016). In the current study, the authors investigate how this dimension of connectivity changes during conceptual retrieval with different levels of semantic association strength. Specifically, they perform gradient analysis on task-fMRI informational connectivity data and reveal a similar principal gradient to the previous study, which captures the separation of heteromodal memory regions from the unimodal cortex. More importantly, by comparing the gradient generated with data from different experimental conditions (i.e., strong vs. weak association), the authors find the separation of the regions at the two ends of the gradient can be regulated by the association strength, with more separation for stronger association. They also examine the relationships between the gradient values and dimensionality and brain-semantic alignment measures, to explore the nature of this shifting gradient as well as the corresponding brain areas.

Strengths:<br /> 1. The aim of this study is clear and the relevant background literature is covered at an appropriate level of detail. With the cortical gradient analysis approach, this study has the potential to make a contribution to the understanding of the topographical neural basis of semantics in a fine-grained manner.<br /> 2. The methodology in the current study is novel. This study validates the feasibility of performing gradient analysis on task-fMRI data, which is enlightening for future research. Using the number of PCs generated by PCA as a measure of dimensionality is also an interesting approach.<br /> 3. The authors have conducted multiple control analyses, which tested the validity of their results. Specifically, a control task without engaging semantic processing was built in the experimental design (i.e., the chevron task), and the authors conducted multiple parallel control analyses with the data from this control task as a comparison with their main results. Other control analyses were also performed to validate the robustness of their methodological choices. For example, varied thresholds were used during the calculation of dimensionality and similar results were obtained.

Weaknesses:<br /> 1. As a major manipulation in the experiment, it is not very clear how the authors split/define their stimuli into strong and weak semantic association conditions. If I understood correctly, word2vec was used to measure the association strength in each pair of words. Then the authors grouped the top 1/3 association strength trials as a "strong association" condition and the bottom 1/3 as "weak association" (Line 689), and all analyses comparing the effect of "strong vs. weak association" were conducted with data from these two subsets of stimuli. However, in multiple places, the authors indicate the association strength of their stimuli ranges from completely unrelated to weakly related to highly related (Line 612, Line 147, Line 690, and the examples in Figure 1B). This makes me wonder if the trials with bottom 1/3 association strength (i.e., those were used in the current study) are actually "unrelated/no association" trials (more like a baseline condition), instead of "weak association" trials as the authors claimed. These two situations could be different regarding how they engage semantic knowledge and control processing. Besides, I am very interested in what will the authors find if they compare all three conditions (i.e., unrelated vs. weak association vs. strong association).<br /> 2. Following the previous point, because the comparison between weak vs. strong association conditions is the key of the current study, I feel it might be better to introduce more about the stimuli in these two conditions. Specifically, the authors only suggested the word pairs fell in these two conditions varied in their association strength, but how about other psycholinguistic properties that could potentially confound their manipulation? For example, words with higher frequency and concreteness may engage more automatic/richer long-term semantic information and words with lower frequency and concreteness need more semantic control. I feel there may be a possibility that the effect of semantic association was partly driven by the differences in these measures in different conditions.<br /> 3. The dimensionality analysis in the current study is novel and interesting. In this section, the authors linked decreasing dimensionality with more abstract and less variable representations. However, most results here were built based on the comparison between the dimensionality effects for strong and weak association conditions. I wonder if these conclusions can be generalised to results within each condition and across different regions (i.e., regions having lower dimensionality are doing more abstract and cross-modal processing). If so, I am curious why the ATL (a semantic "hub") in Figure 3A has higher dimensionality than the sensory-motor cortices (quite experiences related) and AG (another semantic "hub").<br /> 4. I am not sure about the meaning/representational content underlying the semantic similarity matrix in the semantic-brain alignment analysis. According to the authors, this matrix was built based on the correlation of participants' ratings of associative strength (0, no link; 1~4, weak to strong) across trials. The authors indicate that this matrix reflects the global similarity of semantic knowledge between participants (Line 403). However, even though two participants share very similar ratings of association strength across trials, they could still interpret the meaning/knowledge underlying the associations very differently. For example, one participant may interpret the link between "man" and "car" as a man owns a car but another participant may interpret it as a man is hit by a car, although both associations could be rated as strong for this trial. This situation may be even more obvious for those pairs with weak association. Therefore, I am not confident this is a measure of similarity of semantic knowledge.

Reviewer #1 (Public Review):

The manuscript describes Mendelian Randomization (MR) analyses aimed at determining what, if any, causal effect body mass index (BMI) has on childhood emotional problems: depression, anxiety, and attention-deficit and hyperactivity disorder (ADHD) at age 8. To do this, the study leverages genetic association results on BMI to construct a genetic 'instrument', called a polygenic score, that predicts BMI. They use this score to see if the genetic predictor of BMI also predicts childhood emotional problems. What distinguishes this study from typical MR studies is that they use a large sample of 26,370 children with genotype data available for the child and both parents. This enables them to use within-family MR: within-family MR uses the parental genotypes as controls to remove confounding factors. Because offspring genotype is randomly assigned given parental genotype, controlling for parental genotype removes bias due to gene-environment correlation and assortative mating.

The authors find that 'classic MR' (i.e. without controls for parental genotypes) gives evidence that higher BMI increases depressive symptoms and ADHD symptoms in children. However, when controlling for parental genotype (within-family MR), the estimates become smaller and are no longer statistically significant. While this is consistent with 'classic MR' being confounded due to gene-environment correlation and/or assortative mating, the within family MR analysis is less powerful (i.e,. considerable uncertainty about the effect remains) so it is hard to draw any strong conclusions about whether there is or is not an effect of BMI on childhood emotional problems.

This study provides further evidence that MR analyses that do not control for parental genotypes can be biased and conclusions drawn from these analyses should not be taken at face value. However, the fact that there is still a high degree of uncertainty in the within-family MR estimates despite having a large sample of children with genotyped parents implies that, for many hypotheses, much larger samples with genotyped parents will be needed to conduct well-powered within-family MR analyses. Further studies could also interrogate what aspects of the environment explain the observed correlation between parental genotype and offspring emotional problems.

Reviewer #3 (Public Review):

Higher BMI in childhood is correlated with behavioral problems (e.g. depression and ADHD) and some studies have shown that this relationship may be causal using Mendelian Randomization (MR). However, traditional MR is susceptible to bias due to population stratification, assortative mating, and indirect effects (dynastic effects). To address this issue, Hughes et al. use within-family MR, which should be immune to the above-listed problems. They were unable to find a causal relationship between children's BMI and depression, anxiety, or ADHD. They do, however, report a causal effect of mother's BMI on depression in their children. They conclude that the causal effect of children's BMI on behavioral phenotypes such as depression and anxiety, if present, is very small, and may have been overestimated in previous studies. The analyses have been carried out carefully in a large sample and the paper is presented clearly. Overall, their assertions are justified but given that the conclusions mostly rest on an absence of an effect, I would like to see more discussion on statistical power.

1) The authors show that the estimates of within-family MR are imprecise. It would be helpful to know how much power they have for estimating effect sizes reported previously given their sample size.

2) They used the correlation between PGS and BMI to support the assertion that the former is a strong instrument. Were the reported correlations calculated across all individuals? Since we know that stratification, assortative mating, and indirect effects can inflate these correlations, perhaps a more unbiased estimate would be the proportion of childrens' BMI variance explained by their PGS conditioned on the parents' PGS. This should also be the estimate used in power calculations.

3) In testing the association of mothers' and fathers' BMI with children's symptoms, the authors used a multivariable linear regression conditioning on the child's own BMI. Was the other parent's BMI (either by itself or using the polygenic score) included as a covariate in the multivariable and MR models? This was not entirely clear from the text or from Fig. 2. I suspect that if there were assortative mating on BMI in the parent's generation, the effect of any one parent's BMI on the child's symptoms might be inflated unless the other parent's BMI was included as a covariate (assuming both mother's and father's BMI affect the child's symptoms).

4) They report no evidence of cross-trait assortative mating in the parents generation. The power to detect cross-trait assortative mating in the parents' generation using PGS would depend on the actual strength of assortative mating and the respective proportions of trait variance explained by PGS. Could the authors provide an estimate of the power for this test in their sample?

5) Are the actual phenotypes (BMI, depression or ADHD) correlated between the parents? If so, would this not suffice as evidence of cross-trait assortative mating? It is known that the genetic correlation between parents as a result of assortative mating is a function of the correlation in their phenotypes and the heritabilities underlying the two traits (e.g., see Yengo and Visscher 2018). An alternative way to estimate the genetic correlation between parents without using PGS (which is noisy and therefore underpowered) would be to use the phenotypic correlation and heritability estimated using GREML or LDSC. Perhaps this is outside the scope of the paper but I would like to hear the author's thoughts on this.

6) It would be helpful to include power calculations for the MR-Egger intercept estimates.

7) Finally, what is the correlation between PGS and genetic PCs/geography in their sample? A correlation might provide evidence to support the point that classic MR effects are inflated due to stratification.

Reviewer #1 (Public Review):

The authors have examined different pathways of B cell differentiation in patients with SARS-CoV-2 infection who did or did not have HIV-1 infection. They conclude that B cell responses to SARS-CoV-2 infection occur via an extra-follicular (EF) pathway to a greater extent in people with HIV-1 infection compared with people who do not have HIV-1 infection.

The data are important and generally robust but there are deficiencies related to presentation and interpretation of data, as indicated below:

1. There are concerns about nomenclature of cell populations defined by tSNE plots (figure 2A). For example, the population defined as "CSM/marginal zone" does not express IgD or IgM, as would be expected for class-switched memory B cells but not marginal zone B cells. In addition, while tissue homing and GC homing CSM B cells express expected amounts of CXCR4 and CXCR5, both express high amounts of CXCR3, which would be unexpected for GC homing cells. Finally, in line 144, the authors should clarify what is meant by "class switched, IgMhi B cells (highlighted in blue)". The population highlighted in blue in figure 2A, referred to as "IgM++ GC homing B cells", has the immunophenotype IgDlow, IgMhigh, CD27-. Aren't these cells at one end of a naïve B cell spectrum ranging from IgD+/IgM- to IgD+/IgM+ to IgDlow /IgMhigh? There are also other populations that have unconventional names and/or appear to be intermediary populations.

2. IgM switched memory B cells (lines 201-207) are referred to as IgM-only memory B cells by some investigators (for example, see - Bautista D et al. Front Immunol. 2020; 11:736). It would help the reader if this were indicated.

3. The authors have defined DN2 B cells based on expression of the activation marker CD95 (Fas) (see Figure 4) but the original definition of DN2 B cells in patients with SLE was based on expression of CD11c and lack of expression of CXCR5 (see - Jenks SA et al. Immunity. 2020; 52:203). These cells also express T-bet and therefore, have many characteristics in common with CD11c+/T-bet+ memory B cells (also known as age-associated B cells or atypical memory B cells). It would be informative if data on CXCR5- DN B cells were in analysed in addition to, or instead of, CD95+ DN B cells.

4. It might also be informative to discuss the extra-follicular (EF) response pathway in more detail. Recently published data from studies undertaken in mice indicate that CD11c+/T-bet+ MBCs interact with T follicular helper cells in lymphoid follicles but not in germinal centres (Song W et al. Immunity 2022; 55:290-307.e5), so it could be argued that the differentiation pathway is extra-GC rather than extra-follicular, at least in some situations. Also, in people with HIV-1 infection, HIV-1 gp140-specific B cells expressing T-bet are produced outside of GCs (Austin JW et al. Sci Transl Med. 2019; 11:eaax0904. Is the EF response pathway different to the extra-GC differentiation pathway? Where does it occur?

5. Similarly, in lines 288-290, the authors should re-consider the statement that "Both DN2 and activated naïve B cells mature via an EF pathway, independent of T cell help and in response to pro-inflammatory cytokines IFNγ, TNFa, and IL-21; and TLR 7 and 9 stimulation". There are data indicating that differentiation of DN2 B cells is T-cell-dependent (Keller B et al. Sci. Immunol. 2021; 6:eabh0891).

6. In lines 254-60 and figure 6, the investigators should consider the possibility that the CXCR3+ and DN2 SARS-CoV-2-specific MBCs that are increased in people with HIV infection are the same population of cells. CD11c+/T-bet+ MBCs (ie. DN2 B cells, age-associated B cells or atypical memory B cells) usually express high levels of CXCR3.

Reviewer #1 (Public Review):

The manuscript shows that bone is resorbed during the early steps of limb regeneration in urodeles, and osteoclasts are required for this process. In case of impaired resorption, integration of newly-formed tissue with the original bone shaft is compromised. The manuscript further shows that wound epithelium is required for bone resorption and suggests that it induces osteoclastogenesis or migration of osteoclasts. Furthermore, the authors showed that the formation of novel skeletal elements is initiated while the resorption of the old one is still actively ongoing.

The study is well designed, conclusions are relatively well supported, and data are presented in a clear way. Two new models of transgenic axolotls have been created. The strongest and most important finding is that partial bone resorption is required for tissue reintegration. My main concern is the novelty of this study, which is quite limited in my opinion. Specifically, resorption of bone stump during limb regeneration has been shown before in various model organisms. The role of osteoclasts in this process has not been well characterized in urodeles but has been shown during the regeneration of a mouse digit. It is reasonable to anticipate that similarly, osteoclasts are resorbing bone in salamanders, especially since this is the only cell type known for bone resorption. Thus, this observation, despite being nicely and thoroughly done, is of limited interest. The role of wound epithelium in bone histolysis is well demonstrated via skin flap experiments in this manuscript. However, upon skin flap surgery no limb regeneration occurs, implying wound epithelium is a key tissue triggering all the processes of limb regeneration. Accordingly, the absence of bone histolysis in such conditions can be secondary to the absence of any other part of the regenerative process, e.g., blastema formation, macrophage M1 to M2 transition, reinnervation, etc. The proposed link between wound epithelium and osteoclastogenesis (i.e., Sphk1, Ccl4, Mdka) is very superficial and very suggestive. No functional evidence was provided to confirm these connections. Finally, the authors showed that new bone formation occurs while resorption of the bone stump is still ongoing. This is a nice observation, but again, rather indirect as it is based on the dynamics of bone resorption and bone formation in different animals. Due to high variability among animals, direct evidence, like double staining for osteoclasts and blastema markers would address this point more precisely.

Reviewer #3 (Public Review):

This study outlines the role of osteoclast-mediated resorption in integrating the skeletal elements during limb regeneration, using axolotls that can regenerate the entire limb upon amputation. Using calcium-binding vital dyes (calcein and alizarin red), the authors first demonstrated that a large portion of amputated skeletal elements is resorbed prior to blastema formation. They further show that 1) inhibiting bone resorption by zoledronic acid impairs proper integration of the pre-existing and regenerating skeletal elements, 2) removing the wound epithelium using the full skin flap surgery inhibits bone resorption, and 3) bone resorption and blastema formation are correlated. The authors reached the major conclusion that bone resorption is essential for successful skeletal regeneration. Notably, this study applies a well-established and elegant axolotl limb regeneration model and transgenic reporter strains to reveal the potential roles of resorption in limb regeneration.

Strengths:<br /> 1. The authors utilized a well-established axolotl limb regeneration model and applied elegant vital mineral dyes and transgenic reporter lines for sequential in vivo imaging. The authors also provided quantitative assessment by examining multiple animals, particularly in the early sections, ensuring the rigor and the reproducibility of the study.<br /> 2. The authors further performed important interventions that can impinge upon successful limb regeneration, including inhibition of bone resorption by zoledronic acid and impairment of the wound epithelium by full skin flap surgery. These procedures gave rise to useful insights into the relationship between bone resorption and successful limb regeneration.<br /> 3. The imaging presented in this manuscript is of exceptionally high quality.

Weaknesses:<br /> 1. Despite the high quality of the work, many analyses in this study are incomplete, making it insufficient to support the major conclusion. For example, in Figure 4, the authors did not provide any quantitative assessment to show how zol affects the integration of the skeletal elements (angulation?), which seems to be essential for supporting the conclusion. Likewise in Figure 7, the analyses of EdU+ cells and Sox9 reporter expression were not included in zol-treated animals. Similarly in Figure 5, quantification of osteoclasts was not performed with the full skin flap surgery group. Analyses of only normally regenerated animals are not sufficient to support many of the conclusions.<br /> 2. The phenotype of zol-treated animals in limb regeneration is somewhat disappointing. Although zol-treated animals show decreased blastema formation and unresorbed pre-existing skeletal elements, limb regeneration still occurs and the only phenotype is a relatively minor defect in skeletal integration. It is possible that zol-induced defect in blastema formation is not directly linked to the failure of integration at a later stage.<br /> 3. As an integration failure of the newly formed skeleton still occurs in untreated animals, it is not entirely clear how the authors can attribute this defect to a lack of bone resorption. More quantitative analyses would be necessary to demonstrate the correlation between zol treatment and lack of integration.

Reviewer #1 (Public Review):

The authors are trying to show that transitions between ring-like structures and clusters are driven by the balance between 2 main forces: filament treadmilling and motor protein-driven contractility. The results obtained in computer simulations are always compared with properly set experiments, making the story very convincing. In addition, the possible microscopic picture of the mechanisms is provided, although at a more phenomenological level. But given the complexity of the system, I find it very appropriate.

One of the most important achievements of this work is that the authors clearly identified and proved the factors that lead to a very non-trivial behavior. This should stimulate more work on understanding what biological regulation mechanisms might be involved in these phenomena.

I believe that this work will have a strong impact in the field. I am especially impressed by the successful combination of advanced computational and experimental methods.

Reviewer #1 (Public Review):

The aim of the present study was to develop and validate a novel mouse model that allows to determine the proteome of defined sub-cellular compartments, and to use this model in order to elucidate the molecular processes that govern the establishment of synaptic contacts between cortical and striatal neurons in the brain. Given that knowledge of the protein composition of defined sub-cellular compartments is of key importance for the characterisation of protein machines that mediate defined cellular functionalities, the establishment of corresponding mouse models to study such issues is of major general interest. The same is true for the development and function of cortico-striatal connectivity in the brain, which plays key roles in multiple major brain processes and is perturbed in many neuropsychiatric disorders.

The major strength of the present paper is that it presents a novel mouse line that promises to serve as a very helpful tool in this context. The authors generated a KI mouse line that expresses APEX2 under the control of a Cre-activatable promoter from the ROSA26 locus, and they show convincingly that this new mouse line, upon crossing with corresponding Cre-expressing driver lines, allows the identification of cell-sub-compartment specific proteomes and phosphoproteomes - via APEX2-mediated proximity biotinylation, tissue dissection, protein affinity purification, and mass spectrometric analysis.

The biological context of the present study is less convincingly established. Focussing on neuronal connections between the cerebral cortex and the striatum, bioinformatic analyses of corresponding datasets pinpoint a selection of axon guidance systems and protein kinase cascades to play roles in the development of cortico-striatal connectivity. The corresponding data partially align with the published record, but potentially new biological insights deduced from bioinformatic analyses of proteomic data were not followed up by experimental validation.

In sum, the new APEX2 reporter mouse line reported in the present paper will likely be of substantial interest to researchers in many fields of mammalian biology, but the extent of 'new biology' provided in the present study is very limited.

Reviewer #3 (Public Review):

In this work, Dumrongprechachan et al. impressively expanded their earlier work on the identification of cell type-specific subcellular proteomes from mouse brain by APEX2 proximity labeling. Instead of using viral expression of APEX2, the authors now created a Cre-dependent APEX2 reporter mouse line using CRISPR knock-in, which can be combined with multiple Cre-driver lines for proteomic applications. Using this novel tool in combination with sophisticated mass spectrometry and elegant bioinformatics, they mapped the temporal dynamics of the axonal proteome in corticostriatal projections (instead of only identifying a static cell type- and compartment-specific proteome) together with its phosphorylation status (instead of only looking at protein abundance). The data will provide a valuable resource on developmental trajectories at the proteomic and phosphoproteomic level, and will allow for pathway- and phosphosite-centric systems-level analyses as exemplified by the identification of proline-directed protein kinases as major regulators of corticostriatal projection development.

Strengths:<br /> The key tool developed in this work is the APEX2 reporter mouse line as it enables capturing of early postnatal time points, which was not possible before due to the time window of 2-4 weeks required for viral APEX expression. Thus, this tool puts the authors into position to access the temporal dynamics of the developing axon at time points spanning from neonate (as early as P5) to young adult (P50). Within this complex experimental design, the authors even managed to introduce a crucial compartment control at least for the time point P18, in which APEX expression is restricted to nucleus and soma upon viral expression. The resulting resource will be of high value as the data are derived from advanced mass spectrometric methods and stringent data handling. Examples of this high level of scrutiny include the use of MS3 methodology for the acquisition of TMT data to address the ratio distortion issues typically seen with isobaric labeling and thereby increase the quantification accuracy and the limitation to proteins quantified in all biological replicates.

Weaknesses:<br /> As to sample preparation for mass spectrometry, the authors follow the interesting concept of first enriching the phosphopeptides from the pool of TMT-labeled tryptic peptides and then using the unbound fraction from that step for further peptide fractionation, followed by mass spectrometric protein quantification. While this strategy sounds very straightforward in principle, one would expect that the phosphopeptide enrichment comes with an unspecific loss of other peptides in general, and with a semi-specific loss of acidic peptides in particular. Was this potential issue investigated by comparison with samples that were fractionated directly without prior phosphopeptide enrichment? Or with other words: the rationale for this sequential procedure is compelling - quantification of both protein and phosphopeptide abundance from the same (limited) sample, but what is the price for it as to peptide loss?

The APEX2 reporter mouse line is a novel tool with broad applicability for proximity labeling approaches and, understandably, the authors advertise its advantages, mainly via the suitability for short temporal windows. However, the discussion on the limitations of the approach falls short. The authors should make clear that the APEX method in general is limited to ex vivo approaches such as the acute brain slices used here due to the limitation that potentially toxic reagents (i.e. low membrane-permeable biotin-phenol and H2O2) have to be delivered to the target tissue. Although treatment with H2O2 is rather short, undesired oxidative stress signaling may have to be taken into account, particularly when protein phosphorylation rather than protein abundance is assessed. It would also be interesting to discuss the pros and cons of perfusing the mice prior to preparation of brain slices; e.g., in the context of removal of catalases/endogenous peroxidases or potential for substrate delivery (like recently shown in heart, doi: 10.1038/s41586-020-1947-z). Another issue with the Discussion is that the authors do not properly reflect the involvement of proline-directed kinases in the development of corticostriatal projections, which stands in contrast to the fact that they sell this as one of their major findings throughout the manuscript, including the Abstract.

Reviewer #1 (Public Review):

The study by Tu and Zhang is very strong, from its technical implementation, the interesting question being addressed, and a clear presentation of the results. Indeed, the visual guides in the figures allow for easy navigation of the results and help the readers make his/her own inferences seamlessly. The quality of the MRI combined with electrophysiological recordings is excellent, as far as I can tell without looking at the data made available by the authors. The experiments and analysis follow a logical progression that makes sense. If any weakness is to be found, perhaps the authors overstep their inferences of respiration -> neuronal signal causality in the discussion.

Reviewer #3 (Public Review):

This study investigates the neuronal correlates of low-frequency changes in respiration volume per unit time (RVT). The authors report distributed patterns of correlations between RVT and fMRI that may represent a respiration-driven brain network. The ability to demonstrate that this pattern has neuronal origins would make an important contribution to the fMRI field, especially as physiological signals are typically treated as artifacts in fMRI analysis.

A major strength of this paper is the use of concurrent fMRI, physiological monitoring, and invasive electrophysiology (electrode in the anterior cingulate cortex; ACC) in the anesthetized rat, which allows for directly measuring local neuronal activity associated with changes in respiration. A second strength is that the authors demonstrate coherence between respiration (the raw signal as well as RVT) and gamma-band power in the ACC, and furthermore replicate prior findings of a close link between gamma-band power and the BOLD fMRI signal. The authors also take care to ensure that the pattern of correlation between RVT and fMRI is distinct from artifacts resulting from breathing-induced static field changes as well as from CO2-related effects of breathing on the BOLD signal. The findings are clearly presented throughout the paper.

I believe that additional information would help to more strongly support the main claim, i.e., that the reported RVT-fMRI correlation pattern is of neuronal origin. One analysis that supports this claim is that in the lightly anesthetized state, regressing out the gamma-band power signal considerably reduced correlations between RVT and fMRI. However, the more direct test of this possibility involves the experiment in which neural activity across the brain is silenced (isoelectric state) while respiration is artificially maintained. The resulting disappearance of correlation between RVT and fMRI data points to the neuronal nature of RVT-fMRI correlation. Yet, since the amount of temporal variation in RVT during the iso-electric state was not reported, it was not clear whether RVT itself also exhibited less temporal variation in the isoelectric state. Since respiration was maintained by a ventilator in the isoelectric state, I wondered if the respiration depth and volume was more constant compared to in the lightly anesthetized state, in which it is mentioned that spontaneous respiration occurred. Importantly, the authors do mention that the respiration patterns were visually similar between these conditions (Fig. 5C and line 219), which is very promising, but quantification of RVT properties would be important to provide as well.

Reviewer #1 (Public Review):

The paper by Campell et al., describes the isolation and characterization of Designed Ankyrin Repeat Proteins (DARP) that recognize distinct forms of gephryin. Gephyrin is a key determinant for postsynaptic accumulation of both glycine and GABAAR at synapses and thereby determines the efficacy of fast synaptic inhibition. In addition to this gephyrin regulates the synthesis of molybedum-cofactor, an essential co-factor for a number of metabolic enzymes.

The authors create DARPs that recognize specific splice forms of gephyrin and versions that discriminate between phosphorylated and dephosphorylated forms of gephyrin. These new tools reveal the differential recruitment of gephyrin isoforms to axo-axonic and somatodendritic synapses. In addition to these new tools allow the efficient one-step purification of differing gephyrin isoforms and their respective binding partners.

Reviewer #1 (Public Review):

The authors have previously reported the identification of a series of cell-cell junctional proteins as pTyr protein targets for the receptor-like PTPRK tyrosine phosphatase (PTP), including Afadin, a junctional plaque protein that links cell surface adhesion proteins to the cytoskeleton. They identified Afadin pY1230 as a target for PTPRK-mediated dephosphorylation, in keeping with the known role of tyrosine phosphorylation in regulating Afadin function in adherens junctions. They also showed that Afadin/PTPRK interaction did not require its tyrosine phosphorylation, and that the whole PTPRK cytoplasmic domain (ICD) was needed for in vitro dephosphorylation of pY1230 Afadin in vitro.

Here, they used two approaches to define a predicted 63-residue coiled-coil (CC) region (residues 1393-1455) in Afadin as being sufficient to bind the PTPRK intracellular domain (ICD). However, this region behaved as a monomer suggesting it is not a typical CC region. The CC bound the PTPRK ICD with low μM affinity and interacted selectively with the PTPRK D2 pseudophosphatase domain in vitro. Based on a predicted AlfaFold2/Multimer Afadin CC/D2 domain structure, they biochemically defined the key D2/CC interactions showing that a conserved core charged region, residues 1408-1448, in Afadin was essential, which then allowed them to refine the AlfaFold2 model. Their new model places the Afadin CC core region folded as an α-helix bound across the backside (?) of the D2 domain. They had shown previously that the ICD of the related PTPRU also bound Afadin whereas that of the PTPRM did not, and using the structural model showed that the key contact sites in PTPRK with the Afadin CC helix were conserved in PTPRU but not in PTPRM. When the residues in the G1273/L1335 "acidic" pocket of the D2 domain involved in Afadin helix binding were simultaneously mutated to His and Arg respectively, the basic residues found in PTPRM D2, both the double G1273H/L1335R mutant (DM) D2 alone and the entire PTPRK DM ICD failed to bind Afadin or to dephosphorylate (how much less that WT?) pY1230 in Afadin in lysates of pervanadate-treated cells, as assayed using a pY1230 specific antiserum they generated, even though both the WT and DM PTPRK ICD could dephosphorylate pTyr p120-catenin, another PTPRK substrate. On this basis the authors suggest that the D2 pseudophosphatase domain of PTPRK can act as a substrate recruitment domain that allows the active D1 domain to dephosphorylate a distant pTyr residue, in this case pY1230 ~150 residues away.

In this interesting study, the authors present evidence for the novel concept that the D2 pseudophosphatase domain of PTPRK can serve as a recruitment platform for a subset of PTPRK substrates, such as Afadin. Their evidence for this conclusion is strong, and by extension, their findings suggest that the D2 pseudophosphatase domains of other RPTPs may have a similar general function in substrate recruitment and selectivity.

1. While the AF2-Multimer prediction is quite compelling and supported by the properties of the RPTPK D2 DM mutant, this story would have been even more convincing if they had generated a co-crystal structure (perhaps using a PTPRK D2-Afadin aa 1393-1455 fusion with a long linker). In the absence of a true structure, some additional mutational validation of the proposed Afadin-D2 interaction would strengthen their conclusions.

2. The DM mutant data in Figure 4 show that the D2 domain interaction is important for Afadin pTyr dephosphorylation in vitro, but one would also like evidence that the DM PTPRK mutant lacks Afadin pY1230 dephosphorylating activity in cells. The authors have the PTPRK KO MCF10A cells they generated in their first paper that could be used to re-express the WT and DM PTPRK and then monitor Afadin dephosphorylation with their new anti-pY1230 antibodies.

3. If key residues in PTPRM are mutated into the equivalent PTPRK D2 residues, does this now confer on PTPRM the ability to dephosphorylate pY1230 in Afadin, i.e. a gain of function experiment?

4. It would be helpful to know whether any of the other PTPRK substrates that the authors identified previously have a similar motif that might allow them to bind to the D2 domain and be recruited for dephosphorylation.

Reviewer #3 (Public Review):

The study presents interesting new data on the role of the PTPRK D2 pseudophosphatase domain recruiting determining substrate specificity. The paper also demonstrates the utility of predicted structural models, an aspect that has been nicely integrated into this study. However, many open questions remain and additional experimental data should be provided to experimentally confirm the proposed substrate recognition model.

In particular:<br /> 1) Validation of reagents: The authors generated a pY1230 Afadin antibody claiming that (page 6) "this new antibody is specific to tyrosine phosphorylated Afadin, and that pY1230 is targeted for dephosphorylation by PTPRK, in a D2-domain dependent manner". The WB in Fig 1B shows a lot of background, two main bands are visible which both diminish in intensity in ICT WT pervanadate-treated MCF10A cell lysates. The claim that the developed peptide antibody is selective for pY1230 in Afadin would need to be substantiated, for instance by pull down studies analysed by pY-MS to substantiate a claim of antibody specificity for this site. However, for the current study it would be sufficient to demonstrate that pY1230 is indeed the dephosphorylated site. I suggest therefore including a site directed mutant (Y1230F) that would confirm dephosphorylation at this site and the ability of the pY antibody recognizing the phosphorylation state at this position.<br /> 2) The authors claim that a short, 63-residue predicted coiled coil (CC) region, is both necessary and sufficient for binding to the PTPRK-ICD. The region is predicted to have alpha-helical structure and as a consequence, a helical structure has been used in the docking model. Considering that the authors recombinantly expressed this region in bacteria, it would be experimentally simple confirming the alpha-helical structure of the segment by CD or NMR spectroscopy.<br /> 3) Only two mutants have been introduced into PTPRK-ICD to map the Afadin interaction site. One of the mutations changes a possibly structurally important residues (glycine) into a histidine. Even though this residue is present in PTPRM, it does not exclude that the D2 domain no longer functionally folds. Also the second mutation represents a large change in chemical properties and the other 2 predicted residues have not been investigated.<br /> 4) The interface on the Afadin substrate has not been investigated apart from deleting the entire CC or a central charge cluster. Based on the docking model the authors must have identified key positions of this interaction that could be mutated to confirm the proposed interaction site.<br /> 5) A minor point is that ITC experiments have not been run long enough to determine the baseline of interaction heats. In addition, as large and polar proteins were used in this experiment, a blank titration would be required to rule out that dilution heats effect the determined affinities.

Reviewer #1 (Public Review):

In this paper, the authors ask a key question in the field of adult plasticity, and in particular, amblyopia treatment: whether transient dark exposure followed by light re-introduction disrupts neural representation for basic stimulus attributes in a manner that could negatively impact vision. Prior work by Rose and colleagues using calcium imaging showed that closing one eye in adult mice leaves the responsiveness of V1 neurons unchanged but alters their orientation preference and pairwise correlations; such representational drift may require downstream areas to adjust how they readout V1 signals. The question posed here is whether binocular visual deprivation in adult mice does the same. The authors use 2-photon calcium imaging in 6 awake, head-fixed [transgenic - GCaMP6f driven by the EMX1 promoter] mice before and after transient dark exposure to record ensemble responses of layer 2/3 excitatory V1 neurons to oriented gratings of varying spatial frequencies. Data were acquired twice at baseline (allowing for an assessment of representational drift during exposure to the natural [cage] environment), once immediately after 8 days of dark exposure and once about 8 days after animals were once again exposed to their natural [cage] environment.

The study appears to be generally well designed with multiple analytical approaches trained on the same questions. Major strengths include the ability to analyze a large number of neuronal responses simultaneously in the awake-behaving state using calcium imaging in transgenic mice, and the ability to record activity in the same neurons across several weeks and following different behavioral manipulations. A relative weakness was the implication of only being able to elicit relevant visual responses from a small fraction of V1 neurons for comparison purposes. This begs the question of what may have happened to the neurons that were not tracked, and whether this in fact may have been significant. For the ~30% of V1 neurons which were tracked, the findings appear to be that dark exposure of adult mice for 8 days did not significantly corrupt their orientation or SF tuning. Instead, there were increase pairwise correlations between them, interpreted as increased stability of stimulus representation. However, when the entire neuronal pool was analyzed, a decrease in decoding accuracy was noted, attributed to decreased response reliability. Nonetheless, a recovery back to baseline was noted after mice were re-exposed to light and their natural cage environments for 8 days. The study thus provides a binocular deprivation alternative to the earlier monocular deprivation findings of Rose et al. In addition, it provides some new insights, suggesting that the early visual system (i.e. V1) of adult animals normally exhibits a flexible stimulus representation for simplistic, artificial visual stimuli such as oriented gratings, and that temporary dark exposure decreases this flexibility. Importantly for therapeutic approaches however, this can be reversed upon re-introduction of the natural, complex visual environment.

Reviewer #3 (Public Review):

This paper uses transient dark exposure to induce plasticity in the adult visual cortex. It shows that transient dark exposure in the adult mice has opposing effects at the single neuronal level versus the population level. At the population level, the stimulus representation is degraded following dark exposure but rebounds back to normal within 8 days of light re-introduction. Thus, dark exposure does not have a lasting negative impact on the visual cortex. Unexpectedly, at the single neuronal level, following dark exposure a fraction of neurons show more stable responses and higher correlations among pairs of neurons. It is inspiring to hypothesize that this fraction of neurons may form a plastic substrate for representation of complex natural scenes.

Strengths:

The paper uses a combination of single neuron and population analyses to identify the effects of transient dark exposure on visual responses in the adult mouse visual cortex. It succeeds in identifying degradation of stimulus representation at the population level following dark exposure, and stabilization of visual stimulus preference at the single neuron level as well as stabilization of stimulus correlations among pairs of neurons. This success is in part due to an impressively large set of simple visual stimuli used (180 different stimuli). This large set allows the authors to identify even small changes in stimulus preferences at the single neuronal level.<br /> This paper uses transient dark exposure to induce plasticity. An alternative and commonly used method to induce plasticity is monocular deprivation. This paper shows that at the single neuron level, the effects of transient dark exposure are different from the previously reported effects of monocular deprivation. This is an important finding for the field.

Weaknesses:

The analysis methods used are thoughtful and complementary. The statistical tests are mostly performed on visual responses pooled across 6 mice. These statistical tests support the claims of the paper. However, we are left wondering whether the effects identified would also be significant for visual responses of each individual mouse.

Reviewer #1 (Public Review):

This study demonstrates the role of the circadian clock in spatiotemporal regulation of floral development. The authors nicely illustrated floral development patterns in domesticated sunflower. In particular, during anthesis, discrete developmental zones, namely pseudowhorls, are established, and hundreds of florets simultaneously undergo maturation in each psudowhorl in a circadian-dependent manner. Consistently, the flower development follows key features of the circadian clock, such as temperature compensation and gating of plant response to environmental stimuli. Evolutionary advantages of this regulation will add more merit to this study.

Reviewer #1 (Public Review):

In addition to canonical bacterial signaling methods, two-component systems, and serine/threonine kinases, one of the most ubiquitous signal transduction modalities in M. tuberculosis is via adenylate cyclases. This study seeks to identify new adenylate cyclases of M. tuberculosis used to sense antibiotic treatment and resist its effects. To this end, authors employed cutting-edged techniques including genetic knock-out strategy, CRISPRi knock-down strategy, LC-MS-based target metabolite quantification, and various biochemical/microbiological methods. This study provides a conceptually novel strategy to kill M. tuberculosis with conventional tuberculosis chemotherapy.

Reviewer #3 (Public Review):

In a previous study, the authors screened a genome-wide CRISPRi library for sensitivity to a panel of antibiotics. One of the hits on this screen was found to be an essential adenylate cyclase, Rv3645. Rv3645 is a multidomain adenylate cyclase (AC), membrane-associated, and carries a HAMP domain (often associated with two-component signal transduction pathways). Surprisingly, Rv3645 was the only AC exhibiting this broad sensitivity to antibiotics. These observations were validated using a knock-down strategy and were also shown to be complemented by expressing a CRISPRi-resistant allele. To confirm that the sensitivity is not due to weakened cell walls or increased permeability of the cell to antibiotics, they measured the uptake of vancomycin using fluorescently conjugated vancomycin and by mass-spec. Interestingly, the essentiality and drug sensitivity of rv3645KD was found to be dependent on long-chain fatty acids. When Mtb was cultured in absence of fatty acids, rv3645 was no longer essential which allowed them to construct an rv3645 deletion strain. To determine the role of AC in lipid metabolism, the authors carried out a suppressor screen to identify mutants that reversed the fatty-acid phenotype. Mutants were identified in fatty acid transporter genes and in a cAMP phosphodiesterase gene, rv1339. The role of cAMP levels in mediating fatty acid metabolism and antibiotic resistance was further confirmed through the measurement of cAMP levels using mass spectrometry and expression of an enzymatically inactive mutant of rv3645.

Overall, this is a very elegant study that uses cutting-edge bacterial genetics to address the role of cAMP in mycobacterial pathogenesis. All the experiments have been well designed with the necessary controls and rigor. The studies clearly establish the role of cAMP, especially mediated through rv3645 in fatty acid metabolism and resistance against different classes of antibiotics. While the upstream signal is still unknown this can be for future follow-up studies.

Reviewer #1 (Public Review):

The authors have modified protocols for Phage Immunoprecipitation sequencing or PhIP-seq to allow much larger throughput and have examined value of this platform for auto-antigen discovery. Overall the manuscript is technically sound. The finding of shared auto-antigens in Kawasaki Disease and MIS-C was of interest.

Reviewer #3 (Public Review):

This paper presents a rigorously performed series of studies to improve the ability of the PhIP-seq method to discover autoantibodies against peptide antigens that span the whole peptidome at scale, and increase the ease of validation and definition of disease specificity. The paper is an extension of a recent paper from the DeRisi and Anderson groups done on APS1 patients, which defined and validated a novel series of tissue-specific autoantigens in APS1. The current studies show that the authors can find the antibodies they previously defined, and using larger numbers of disease and control samples, can expand some what they detect. They then use the new method to look at multiple additional processes in which autoimmunity has been demonstrated/postulated.

The dataset may be of use to others interested in defining novel autoantibodies. The findings really did not share significant new insights into the processes they studied,. As the authors note, they were unable to detect the antibodies (~10% of patients) recognizing type I IFNs in severe COVID-19, where these had been demonstrated effectively using ELISA previously. Unlike APS1, where their findings about uncommon tissue specific autoantibody responses across a population with known genetic deficiency and heterogeneous phenotypes could really illustrate the power of the method and approach, that elegance and powerful and novel conclusion is not as evident here.

Reviewer #1 (Public Review):

The paper has determined a considerable number of different structures and conformations by Cryo-EM, that describes the full conformational spectrum of the KdpFABC catalytic cycle. They also show by EPR that the non-phosphorylatable variant KdpBS162A variant was indeed arrested in the state observed by Cryo-EM.

Although they have been able to validate that the Cryo-EM structure of the off-cycle state is consistent with the conformational state probed by pulsed EPR, it is unclear what protein phosphorylates and then inactivates KdpFABC at higher K+ concentrations. As such, at present, it is not possible to fully comprehend the exact physiological conditions when the arrested state is formed.

Reviewer #3 (Public Review):

The authors have determined a range of conformations of the high-affinity prokaryotic K+ uptake system KdpFABC, and demonstrate at least two novel states that shed further light on the structure and function of these elusive protein complexes.

The manuscript is well-written and easy to follow. The introduction puts the work in a proper context and highlights gaps in the field. I am however missing an overview of the currently available structures/states of KdpFABC. This could also be implemented in Fig. 6 (highlighting new vs available data). This is also connected to one of my main remarks - the lack of comparisons and RMSD estimates to available structures. Similarity/resemblance to available structures is indicated several times throughout the manuscript, but this is not quantified or shown in detail, and hence it is difficult for the reader to grasp how unique or alike the structures are. Linked to this, I am somewhat surprised by the lack of considerable changes within the TM domain and the overlapping connectivity of the K indicated in Table 1 - Figure Supplement 1. According to Fig. 6 the uptake pathway should be open in early E1 states, but not in E2 states, contrasting to the Table 1 - Figure Supplement 1, which show connectivity in all structures? Furthermore, the release pathway (to the inside) should be open in the E2-P conformation, but no release pathway is shown as K ions in any of the structures in Table 1 - Figure Supplement 1. Overall, it seems as if rather small shifts in-between the shown structures (are the structures changing from closed to inward-open)? Or is it only KdpA that is shown?

My second key remark concerns the "E1-P tight is the consequence of an impaired E1-P/E2-P transition" section, and the associated discussion, which is very interesting. I am not convinced though that the nucleotide and phosphate mimic-stabilized states (such as E1-P:ADP) represent the high-energy E1P state, as I believe is indicated in the text. Supportive of this, in SERCA, the shifts from the E1:ATP to the E1P:ADP structures are modest, while the following high-energy Ca-bound E1P and E2P states remain elusive (see Fig. 1 in PMID: 32219166, from 3N8G to 3BA6). Or maybe this is not what the authors claim, or the situation is different for KdpFABC? Associated, while I agree with the statement in rows 234-237 (that the authors likely have caught an off-cycle state), I wonder if the tight E1-P configuration could relate to the elusive high-energy states (although initially counter-intuitive as it has been caught in the structure)? The claims on rows 358-360 and 420-422 are not in conflict with such an idea, and the authors touch on this subject on rows 436-450. Can it be excluded that it is the proper elusive E1P state? If the state is related to the E1P conformation it may well have bearing also on other P-type ATPases and this could be expanded upon.

Reviewer #1 (Public Review):

A novel approach is introduced for targeting Protein-RNA interactions. The approach (presented in Figure 1) integrates computational techniques with cellular assays, and is applicable, in principle, whenever the protein-RNA complex has a druggable binding pocket. It is demonstrated with the discovery of inhibitors of YB-1's interaction with its mRNA target. Of 22 putative hits, discovered based on virtual screen, 11 come out as very strong hits. Far beyond the 5-10 percent success rate that one often sees in drug discovery.

The main strength here is the proof of concept that protein-RNA interactions are targetable.

Reviewer #3 (Public Review):

The authors introduce an integrative platform for identifying small molecule ligands that can disrupt RNA-protein interactions (RPIs) in vitro and in cells. The screening assay is based on prior work establishing the MT bench assay (Boca et al. 2015) for evaluating protein-protein interactions in cells by utilizing microtubules as a platform to recruit and detect PPIs in cells. In the current manuscript, the authors adapted this methodology to evaluate small molecules targeting RNA-binding protein (RBPs) interactions with mRNA in cells. By combining the MT bench assay with computational docking/screening and ligand-binding evaluations by NMR, the authors discover inhibitors of the RBP YB-1, which included FDA-approved PARP-1 inhibitors. The impact of this work could be high given the critical roles of RNA-binding proteins in regulating the function and fate of coding and non-coding RNA. While the presented data are promising, the ability to generally apply this method beyond YB-1 and to RBPs in general remains to be addressed.

Reviewer #1 (Public Review):

The submitted manuscript describes an optimized tissue clearing protocol with some modest advantages including better preservation of tissue volume, compatibility with traditional histology methods, and simple processing steps. By combining known advantages of organic solvent-based and aqueous-based procedures the authors were able to generate a very simple, efficient, and fast tissue clearing protocol that can preserve endogenous and synthetic fluorescent signals. The manuscript is mostly written well and the fluorescent images are very striking. However, the lack of quantification throughout the manuscript makes it is difficult to assess how robust the results are across many samples and key experimental applications are missing.

1. Immunofluorescent labeling/staining is a very common procedure in whole, cleared tissues. Given that immunofluorescent labeling works well in tissue sections from EZ Cleared brains, it appears that it should work in the whole tissues after clearing. An extended version of the EZ Clear protocol with immunofluorescent labeling procedures in whole mouse brain tissue should be included along with quantification of fluorescent intensity as a function of depth. If EZ Clear provides more uniform immunofluorescent labeling relative to other protocols, this is a significant advantage.

2. The differences in tissue volume and sample processing steps between EZ Clear and Fast 3D are important, but relatively modest. Additional quantitative comparisons between EZ Clear and Fast 3D/3Disco would considerably strengthen the manuscript. The qualitative differences shown in Figure 1G-J are striking, but it is difficult to determine how robust this effect is across multiple samples without a quantitative comparison. Similar quantitative comparisons should be made for endogenous fluorescent intensity and immunofluorescent labeling as a function of tissue depth between the various protocols.

3. It would be helpful to see how the intensity and contrast of the fluorescent labeling changes as a function of depth (e.g. Lectin-649 labeling in Figures 2E and H). There is a clear improvement with EZ View relative to RIMS, but there are still noticeable changes in the signal as a function of depth. Quantification would help determine the extent of these changes, as well as reproducibility across multiple samples.

4. LSFM imaging should be performed in some of the other mouse tissues to demonstrate sufficient clearing for quantification purposes.

Reviewer #1 (Public Review):

The authors use a model system to investigate how three classes of kinesins (1, 2 and 3) interact with the dynein-dynactin-truncated BicD2 complex when coupled via a DNA scaffold. Complexes with kinesin 1 have been shown to have a plus-end bias, but unexpectedly the authors show that this is also true for kinesins 2 and 3 despite these motors having a higher load sensitivity. The authors reconcile this finding by showing via simulations that faster reattachment kinetics compensate for faster detachment rates under load. They conclude that motor kinetics is another important feature in understanding both the velocity and directionality that cargo is transported.

This is the first study directly comparing three classes of constitutively active kinesin motors versus DDB in a controlled fashion, which is a strength of this study. The caveat is that these results may require modification when dynein and kinesin are coupled via an activating adaptor rather than DNA. However, the studies in the current manuscript are a required prerequisite, as different activating adaptors would be needed for the different classes of kinesin, thus introducing another variable into how the two classes of motors interact. Moreover, results from these studies can be used as a platform for further investigation of the effect of MAPs, regulatory proteins, and PTMs of the MT on model bidirectional complexes.

Reviewer #3 (Public Review):

Gicking et al. analyze the relation between DDB (retrograde motor complex) and different members of kinesin family. The authors directly linked DDB and kinesin-1, -2 and -3 using DNA linker. Consistent with previous force measurement, kinesin-1 can dominate DDB. On the other hand, it is an unexpected and interesting observation that kinesin-2 and -3 can withstand loads by DDB because these motors are sensitive to load and easily detach from microtubules under loaded conditions in optical tweezers experiments. The authors performed computer simulations and suggested that fast detachment in kinesin-2 and -3 can be antagonized by fast reattachment. The work will impact thinking about physical properties of kinesins under loaded conditions.

Weaknesses:<br /> (1) To show DDB-kinesin-2 relation, the authors analyzed KIF3A/KIF3A homodimers. This reviewer does not think KIF3A/KIF3A homodimers represent kinesin-2. The motor domain of kinesin-2 is a heterodimer composed of KIF3A and KIF3B in the cell. The authors have previously shown that properties of KIF3A/KIF3A homodimer are different from those of KIF3A/KIF3B (Andreasson et al., Curr Biol., 2015).

(2) While these in vitro results are interesting, physiological meaning of these findings is not very clear.

Reviewer #1 (Public Review):

GCaMP indicators have become common, almost ubiquitous tools used by many neuroscientists. As calcium buffers, calcium indicators have the potential to perturb calcium dynamics and thereby alter neuronal physiology. With so many labs using GCaMPs across a variety of applications and brain regions, it's remarkable how few have documented GCaMP-related perturbations of physiology, but there are two main contexts in which perturbations have been observed: after prolonged expression of a high GCaMP concentration (common several weeks after infection with a virus using a strong promoter); and when cytoplasmic GCaMP is present during neuronal development. As a result, GCaMP studies are often designed to avoid these two conditions.

Here, Xiaodong Liu and colleagues ask whether GCaMP-X series indicators are less toxic that GCaMPs. GCaMP-X indicators are modified GCaMPs with an additional N-terminal calmodulin binding domain that reduces interactions of the calmodulin moiety of GCaMP with other cellular proteins. Xiaodong Liu and colleagues document effects of GCaMP expression on neuronal morphology in vitro, calcium oscillations in vitro, and sensory responses in vivo, in each case showing that GCaMP-X indicators are less toxic. Their results are compelling.

Unfortunately, the paper suffers two main weaknesses. Firstly, the results demonstrate that GCaMP is toxic during development, after prolonged expression via viruses in vivo, and in cell culture where maturation of the culture likely recapitulates key steps in development. GCaMPs are known to be toxic in these circumstances, such toxicity is readily circumvented by driving expression in the adult, and there are countless examples of studies in which adequate GCaMP expression was achieved without toxicity. These new results are of little relevance to the majority of GCaMP experiments. That GCaMP-X indicators are less toxic during development is a new result and may be of interest to those who wish to deploy calcium indicators during development, but this is a relatively small number of neuroscientists.

Secondly, the authors extend their claims to conclude that GCaMP indicators are toxic under other circumstances, claims supported by neither their results nor the literature. To provide one example, at the end of the introduction is the statement, 'chronic GCaMP-X imaging has been successfully implemented in vitro and in vivo, featured with long-term overexpression (free of CaM-interference), high spatiotemporal contents (multiple weeks and intact neuronal network) and subcellular resolution (cytosolic versus nuclear), all of which are nearly infeasible if using conventional GCaMP.' The statement's inaccurate: there are many chronic imaging studies in vitro and in vivo using GCaMP indicators without nuclear accumulation of GCaMP or perturbed sensory responses. There are more examples throughout the paper where the conclusions overreach the results and are inaccurate. The results are simply insufficient to support many of the strong statements in the paper.

Reviewer #1 (Public Review):

This study attempts to understand the source of problems in allocentric navigation in older adults and children compared to young adults. Using a simple and elegant Y-maze design with extensive behavioral analyses, the authors convincingly show that older adults and children are impaired with respect to the ability to use landmark cues, but not geometric cues, in order to orient in the environment. Their testing further shows that this results from a problem of remembering spatial relations between landmarks and using those to navigate, and not an issue of encoding the landmarks themselves or attending to them. The findings are important in two respects: 1) understanding the navigational problems of older adults, 2) understanding the cognitive systems underlying allocentric navigation. With regard to the first point, the authors' results from the map drawing task demonstrate that the problem is specifically with remembering the relative configuration of the landmarks with respect to one another and to the start and goal location. With regard to the second point, the paper is exciting in that it demonstrates a dissociation between two systems of allocentric navigation - landmark-based and geometry-based. As the authors point out, most papers refer to "allocentric navigation" as a process where subjects use either the geometry or landmarks interchangeably as reference points in their mental map, but these findings suggest that those systems might be dissociable. Overall, I think that the study is well-designed, the analyses are adequate, and the research questions are addressed appropriately. The authors took care to exclude other sources of difference between groups by having both physical and virtual reality mazes, using a walking VR paradigm to eliminate computer use proficiency differences, and testing visual attention and gaze as well as an array of other variables.

Reviewer #1 (Public Review):

Redox signaling is a dynamic and concerted orchestra of inter-connected cellular pathways. There is always a debate whether ROS (reactive oxygen species) could be a friend or foe. Continued research is needed to dissect out how ROS generation and progression could diverge in physiological versus pathophysiological states. Similarly, there are several paradoxical studies (both animal and human) wherein exercise health benefits were reported to be accompanied by increases in ROS generation. It is in this context, that the present manuscript deserves attention.

Utilizing the in-vitro studies as well as mice model work, this manuscript illustrates the different regulatory mechanisms of exercise and antioxidant intervention on redox balance and blood glucose level in diabetes. The manuscript does have some limitations and might need additional experiments and explanation.

The authors should consider addressing the following comments with additional experiments.

1. Although hepatic AMPK activation appears to be a central signaling element for the benefits of moderate exercise and glucose control, additional signals (on hepatic tissue) related to hepatic gluconeogenesis such as Forkhead box O1 (FoxO1), phosphoenolpyruvate carboxykinase (PEPCK), and GLUT2 needs to be profiled to present a holistic approach. Authors should consider this and revise the manuscript.<br /> 2. Very recently sestrin2 signaling is assumed significant attention in relation to exercise and antioxidant responses. Therefore, authors should profile the sestrin2 levels as it is linked to several targets such as mTOR, AMPK and Sirt1. Additionally, the levels of Nrf2 should be reported as this is the central regulator of the threshold mechanisms of oxidative stress and ROS generation.<br /> 3. Authors should discuss the exercise-associated hormesis curve. They should discuss whether moderate exercise could decrease the sensitivity to oxidative stress by altering the bell-shaped dose-response curve.<br /> 4. It would not be ideal to single-out AMPK as a sole biomarker in this manuscript. Instead, authors should consider AMPK activation and associated signaling in relation to redox balance. This should also be presented in Fig 7.

Reviewer #1 (Public Review):

Klein and colleagues have developed a new setup to artificially activate genetically targeted neurons in temporal precise correlation with specific behaviors in larva of Drosophila melanogaster. The work explores how the activation of specific sets of reward and punishment coding neurons during the execution of side-specific bending alters the occurrence of this behavior. Indeed, activating serotonergic neurons during specific bending in a training phase, biases bending direction in the test. Since altering behavior as a consequence of its rewarding or punishing outcome is considered operant learning the authors conclude that the targeted neurons mediate operant conditioning. Below I will point out the strength and my criticisms concerning the presented work.

The newly developed closed-loop set-up is impressive and will pave the way for many exciting studies on learned behavior and beyond. To validate the set up the authors induce rolling behavior by thermo- or optogenetically activating two sets of previously described neurons in individual larva. Both approaches show convincing induction of the behavior per se. However, it is worth pointing out that there seems to be an interaction of the different tools used (thermo and opto-genetic) and the targeted neurons: the authors observe different dynamics of the behavior across the three stimulation cycles depending on stimulation method and labeled neurons. These findings make it difficult to understand why the authors choose only the optogenetic activation to investigate operant conditioning. The strength of the setup is that individual animals can be targeted. Though the presented data show that behavior can be reliably induced in stimulated animals, it lacks the information about the behavior of non-targeted larva during the stimulation. Thus, it would strengthen the work if the authors could show the behavior of the non-targeted larva during the time when targeted larva receive light or heat.

The authors use their setup to investigate operant conditioning. In operant conditioning an animal learns to associate its action with the consequences. Their new setup allows the authors to artificially induce consequences, the activation of reward or punishment coding neurons, upon side-specific bending behavior. The experiments show that side specific bending in the test is slightly biased towards the side previously paired with the neuronal stimulation. Interestingly, the data suggest that this effect requires the activity of serotonergic neurons outside of the brain (in the VNC) and that it is not mediated by dopamine signaling in the brain. Though, the effects seem to be reproducible with Ddc- and the Tph-GAL4 the reported differences are small, and the origin of the relative difference between left and right bending in the paired group is not entirely clear. Thus, it will be important to strengthen the work by additional experiments and extend the analysis of the presented data. Given the novelty of the method and the differences between the tools in the proof of principle experiments the authors should repeat the key experiments (Figure 3 b and e) with the thermogenetic stimulation. Further it would strengthen the investigation on operant conditioning if the authors would explore the temporal relationship between the CS and US, especially since the effect might be a reduction of the unreinforced behavior (see below). Concerning the analysis, the authors should consider that given the small effect they observe, they want to be sure that it originates from training. Though they show the pretraining results for one of the experiments (Figure 3b, the trained group), the pretraining bending is very relevant for each of the operant learning experiments. In fact, training induced effects should not only be measured by looking at the left vs right bending in the final test but as a change between pre versus post or between a trained and a mock control group. This is done for one group (Ddc-GAL4) in Figure 3b but will be mandatory for all operant learning experiments. It would improve the accessibility of the learning induced change of behavior if the authors could show the pre vs post training results for each run (10-12 larva in a plate). Further, they should plot the numbers of reinforced behaviors in each of the training protocols and relate it to the test performance. The presented data clearly suggests a decrease of the unstimulated bending rather than a change in the reinforced behavior. Though the authors mention it, they do not explain or discuss it. It will be very important for the logic of the manuscript that the authors explain this phenomenon and how it relates to operant conditioning.

Lastly, though the manuscript discusses most of the data carefully, in my view the authors miss an important issue: it remains to be shown if fly larva are capable of operant learning using external reward or punishment. The presented evidence is based on artificial activation of neurons, which arguably is a hint but not a prove that operant conditioning is withing the repertoire of a fly larva, an issue the authors should mention and discuss.

Reviewer #3 (Public Review):

The manuscript provides evidence that larvae are capable of operant, as opposed to classical, conditioning: optogenetic activation of serotonergic neurons after a larva bends in one direction increases the likelihood that it will bend in that direction again.

Furthermore, the manuscript shows that serotonergic neurons located in the ventral nerve cord are capable of inducing this associative conditioning. While dopaminergic and serotonergic neurons, notably the dopaminergic PAM cluster in the Mushroom Bodies, have previously been implicated in classical conditioning, where different subsets apply positive or negative valence, these data suggest that specific serotonergic neurons may also contribute to learned behaviors. Although the cellular and circuit mechanisms remain unclear, and the consequences of silencing these neurons in contexts where the larva might more naturally employ operant learning are not tested, this research suggests new areas for exploring the adaptive capacity of a powerful model organism.

Peer review report

Title: Burden of HCoV infection in children hospitalized with lower respiratory infection in Cape Town, South Africa

version: 1

Referee: SOCORRO P. LUPISAN, MD MSc

email: socorrolupisan@yahoo.com

ORCID iD: 0000-0002-8916-4380

General assessment

This study reports interesting results, but the description of the methodology needs to be improved.

Essential revisions that are required to verify the manuscript

I provide below some comments/queries to strengthen the methodology, and to increase the clarity in the interpretation of the results.

1. The parent study was not described in the Methods Section. The parent study was disclosed only in the Conclusion: “While this study which is a sub-study restricted itself to the burden of human coronaviruses in children, the main respiratory pathogen under review in the parent study was Bordetella pertussis which only assessed similar risk factors in the same cohort of children. “

2. This sub study is also prospective in nature.

3. Was the Informed Consent Form prepared for the parent study only? Did the sub study investigator get a signed Informed Consent Form for the collection and laboratory analysis of samples for this HCoV study?

4. Study Population: In order for the study to reflect the whole season, recruitment was limited to a maximum of four qualifying participants per day. Did you do stratified and systematic sampling? Please describe your sampling procedures as you have done.

5. In the Discussion it was written: Although the study was sufficiently powered, it had low precision and could not demonstrate statistically significant associations. How did you calculate sample size?

Other suggestions to improve the manuscript

I also have some clarifications which need to be addressed:

1. Would you know the other viruses detected? If yes, include in the results as this will enrich you results.

2. Was ceftriaxone really given prior to admission? At home, as injection?

3. What were the clinical diagnosis of cases with HCoV and no HCoV?

Decision

Requires revisions: The manuscript contains objective errors or fundamental flaws that must be addressed and/or major revisions are suggested.

Reviewer #1 (Public Review):

The goal of the current study is to determine the impact of sleep on resilience to social stress. The research team accomplished their goals using male mice that underwent social defeat stress by a larger conspecific. The team found that sleep is necessary and sufficient for promoting stress resilience to social defeat stress. They also identified the prefrontal cortex as a major player in the link between sleep and stress resilience.

Overall, this is a well-written manuscript that is strengthened by the translational relevance and significance, the well-executed study design, and the robustness of the data.

Reviewer #3 (Public Review):

The authors demonstrate in mice that the amount of sleep is related to stress resilience, and specifically that increased sleep after stress exposure supports resilient behavior. The aims are achieved through an array of methodologies, which highly strengthens the conclusions of the work. The question of whether sleep is related to stress resilience is highly significant and in the current research, the authors tackle the questions by evaluating differences in sleep homeostasis in stress-resilient compared to stress-susceptible mice. To induce more stress-susceptibility, the authors challenge the mice with sleep restriction, and to induce more stress-resilience, the authors chemogenetically induce increased NREM sleep. Mechanistically the authors demonstrate that cortically mediated NREM sleep is sufficient to promote resilience. Despite the challenging nature of the technological approaches at hand, particularly in mice, the experiments are well-designed and the authors are commended for the execution of these studies.

It is very difficult to separate sleep loss and stress responses, as losing sleep is inevitably a stressful experience. The authors attempt to quell the notion that sleep restriction was also stressful to the animals by measuring fecal corticosterone, however, the measurements were from fecal pellets collected during an entire 24 hr period raises concerns that acute changes in HPA response may not be evident through this measurement. This is a challenging notion to tackle and deserves a bit more consideration.

Chemogenetic experiments induce a beautiful increase in NREM sleep at the expense of REM loss, yet all the animals treated with chemogenetic agents are resilient to social defeat stress. The authors conclude that because sleep restriction also reduced REM, yet opposite effects occur on social interaction, REM sleep is unlikely to be related to resilience. In this context, it would be beneficial to discuss the theories of sleeping to forget and sleeping to remember, and supporting literature that REM sleep is critical to the consolidation of memories, particularly upon stressful experiences.

Reviewer #1 (Public Review):

In this manuscript, the authors leverage novel computational tools to detect, classify and extract information underlying sharp-wave ripples, and synchronous events related to memory. They validate the applicability of their method to several datasets and compare it with a filtering method. In summary, they found that their convolutional neural network detection captures more events than the commonly used filter method. This particular capability of capturing additional events which traditional methods don't detect is very powerful and could open important new avenues worth further investigation. The manuscript in general will be very useful for the community as it will increase the attention towards new tools that can be used to solve ongoing questions in hippocampal physiology.

Additional minor points that could improve the interpretation of this work are listed below:

- Spectral methods could also be used to capture the variability of events if used properly or run several times through a dataset. I think adjusting the statements where the authors compare CNN with traditional filter detections could be useful as it can be misleading to state otherwise.

- The authors show that their novel method is able to detect "physiological relevant processes" but no further analysis is provided to show that this is indeed the case. I suggest adjusting the statement to "the method is able to detect new processes (or events)".

- In Fig.1 the authors show how they tune the parameters that work best for their CNN method and from there they compare it with a filter method. In order to offer a more fair comparison analogous tuning of the filter parameters should be tested alongside to show that filters can also be tuned to improve the detection of "ground truth" data.

- Showing a manual score of the performance of their CNN method detection with false positive and false negative flags (and plots) would be clarifying in order to get an idea of the type of events that the method is able to detect and fails to detect.

- In fig 2E the authors show the differences between CNN with different precision and the filter method, while the performance is better the trends are extremely similar and the numbers are very close for all comparisons (except for the recall where the filter clearly performs worse than CNN).

- The authors acknowledge that various forms of SWRs not consistent with their common definition could be captured by their method. But theoretically, it could also be the case that, due to the spectral continuum of the LFP signals, noisy features of the LFP could also be passed as "relevant events"? Discussing this point in the manuscript could help with the context of where the method might be applied in the future.

- In fig. 5 the authors claim that there are striking differences in firing rate and timings of pyramidal cells when comparing events detected in different layers (compare to SP layer). This is not very clear from the figure as the plots 5G and 5H show that the main differences are when compare with SO and SLM.

- Could the above differences be related to the fact that the performance of the CNN could have different percentages of false-positive when applied to different layers? Alternatively, could the variability be related to the occurrence (and detection) of similar events in neighboring spectral bands (i.e., gamma events)? Discussion of this point in the manuscript would be helpful for the readers.

Overall, I think the method is interesting and could be very useful to detect more nuance within hippocampal LFPs and offer new insights into the underlying mechanisms of hippocampal firing and how they organize in various forms of network events related to memory.

Reviewer #1 (Public Review):

The manuscript by Arnason et al. reports a careful in-depth analysis of genomic patterns of diversity of the Atlantic codfishes, sampled twice near the Icelandic coast. The manuscript is scientifically sound and provides thorough details of the statistical analysis and of the underlying models. In essence, the analysis demonstrates that recurrent selective sweeps are the most compatible scenario to explain the data. The analysis is extremely detailed, well constructed, and very convincing. It also advertises the family of Multiple-Merger Coalescents (MMCs) as good models for standard population genetics analyses. Overall, I found this article very interesting and extremely well-documented.

Reviewer #3 (Public Review):

This study addresses fundamental aspects of the eco-evolutionary dynamics of highly fecund organisms experiencing huge mortality rates during early life stages. In such species, a mechanism called "sweepstakes reproductive success" (Hedgecock, 1994) has been proposed to understand the dynamics of recruitment, in which individual reproductive success shows high variance and skewed distribution. Sweepstakes reproductive success can be either neutral due to random environmental variation influencing the recruitment of reproducing offspring, or selective because genetic variation at particular loci influences the likelihood of successful recruitment. Unfortunately, empirical tests of sweepstakes reproduction remain scarce due to the difficulty of studying individual reproductive success directly, particularly in highly fecund marine organisms.

By analysing genome-wide genetic diversity data under different coalescent models representing alternative recruitment dynamics, this pioneering study specifically tests whether random or selective sweepstakes reproduction occurs in the highly fecund Atlantic cod. Using the classical Kingman coalescent and two multiple-merger coalescent models approximating random sweepstakes (the Xi-Beta-coalescent model) and selective sweepstakes (the Durrett-Schweinsberg model), the authors show that genetic diversity in the Atlantic cod genome is most likely shaped by pervasive selective sweeps of new beneficial mutations. The best-fit selective sweepstakes model is able to reproduce the main characteristics of the allele frequency spectrum of each Atlantic cod population, while alternative models include either random sweepstakes or other biologically plausible scenarios (i.e. historical demographic changes, cryptic breeding structure, and background selection) show a much poorer fit.

These findings have a broad impact on evolutionary genomics since they provide a new and exciting perspective on the choice of appropriate coalescent models for the study of highly fecund organisms that may experience high rates of selective mortality during early life stages. The low-fecundity low-variance reproductive success model classically used in evolutionary genetics may simply not apply in highly fecund organisms with skewed offspring distribution.

By confronting different alternative models of coalescence with genome-scale genetic diversity data, this work provides a roadmap for exploring fundamental processes at the crossroads between ecology and evolution. It highlights the importance of (i) understanding the potential impact of species-specific biological characteristics when inferring demography and selection from molecular data, and (ii) being aware of the potentially significant effects of unaccounted aspects of the data (e.g. variant misorientation, past admixture) on the interpretation of results.

Reviewer #1 (Public Review):

The experiments presented in this extensive study by Ronzano et al. are a tour-de-force investigating the spatial organization of premotor interneurons in the mouse spinal cord to re-examine the fundamental question of whether there is spatial segregation of interneurons with monosynaptic connections to motoneurons innervating functionally antagonistic (flexor and extensor) pairs of limb muscles. Such segregation has been proposed from earlier studies utilizing strategies for retrograde trans-synaptic tracing of spinal premotoneurons with rabies virus (RabV) following muscle injection. This spatial organization has been suggested to provide an anatomical substrate for labeled line inputs from proprioceptive afferents to motor neurons with possibly organization advantages for motor control. The present premotor circuit mapping experiments, involving four different collaborating laboratories applying an extensive set of complementary RabV-based trans-synaptic circuit tracing techniques, convincingly demonstrate complete spatial overlap among flexor and extensor premotor interneurons, contradicting the previous mapping results that suggest spatial segregation. The present results revise our understanding of the spatial organization of spinal premotor circuits and provide an alternative view of the role of interneuron positioning in sensory input connectivity without specific spatial patterning of output connectivity to motoneurons, with fundamental implications for understanding motor circuit function.

Strengths of these studies include:

1. The investigators systematically tested and directly compared most of the available premotor circuit tracing strategies utilizing genetically modified mouse strains and viruses, as well as the previous approaches, with all tests replicating the spatial overlap of flexor and extensor premotor interneurons.

2. The authors utilized a mouse genetic strategy combining a Cre conditional allele expressing RabV glycoprotein G from the rosa locus with either the ChAT::Cre or Olig2::Cre mouse lines, which in contrast to previous RabV-based approaches, enables selective and potentially high levels of G expression in all motoneurons at the time of RabV muscle injection and likely robust transsynaptic transfer for premotor neuron labeling.

3. The authors present a very useful instructive exposition of the currently available techniques for labeling premotor interneurons outlining experimental strategies and indicating advantages and disadvantages for interpretation of results by illustrating RabV trans-synaptic transfer pathways that could confound experimental results.

4. The authors also used transgenic strategies in combination with their other approaches to differentiate inhibitory or putative excitatory premotor interneurons controlling the activity of flexor and extensor muscles and demonstrated from technically elegant spatial analyses that flexor and extensor premotor neurons were always spatially intermingled regardless of their neurotransmitter identity.

5. The authors further confirmed the lack of spatial segregation by pooling together all the results obtained with the different circuit tracing methods.

6. The authors thoroughly discuss the limitations of their mouse genetic strategy for circuit tracing including off-target G complementation in cells other than the targeted cholinergic motoneurons with the possibility of labeling disynaptic pathways via cholinergic spinal interneurons. Also considered is the problem in identifying the number of motoneurons with G complementation, which is a main determinant of reproducibility in RabV tracing experiments and a key parameter for comparing results from different circuit tracing approaches.

7. Overall the experiments are rigorously performed with a design that reduces biases associated with the various RabV-based circuit tracing methods, and the data although very extensive with numerous data source files and supplemental illustrations, are clearly presented.

Reviewer #3 (Public Review):

The manuscript by Ronzano et al presents a rigorous neuroanatomical study to convincingly demonstrate that there is no difference in the medio-lateral organization of flexor and extensor premotor interneurons. The study uses monosynaptic restricted transsynaptic tracing from ankle flexor and extensor muscles with several (4) strategies for delivery of the G protein complement and delta G Rabies virus, and additional (2) variations that consider titer and cre line. The authors went to great lengths here in attempt to replicate prior studies for which they had initial conflicting findings. Further, the experiments are performed in laboratories in four different locations. The variations on the Rabies and complement delivery, regardless of lab performing the experiment and analysis, all converge on the same conclusion. Aside from the primary conclusion, the paper can be used as a manual for anyone considering transsynaptic tracing as it details the benefits and caveats of each strategy with examples.

The initial conflicting results put the onus on the authors to demonstrate where the divergence occurred. The authors took a highly comprehensive approach, which is a clear strength of the paper. All of the data is fully and transparently presented. Standardizations and differences between experiments run or analyzed in each lab are well laid out. Figure 1 and Table 2 provide a great summary of the techniques and their limitations. These are also well thought out and discussed within each section of results.

The only thing missing is a likely explanation for the differences seen. Although the authors made several attempts to provide such explanation, the question remains - how did two groups who published independent studies using different strategies demonstrate flexor and extensor separation in the dorsal horn, when this study, using several strategies in multiple labs, show that the premotor neurons are in complete overlap? Additional small differences in methodologies could be identified which are not discussed and may provide potential explanations, but only for discrepancies in results of single techniques, not for all of the strategies used. The lack of reason for the discrepancy with prior studies despite the extensive efforts is unsatisfying, but, most importantly, the experiments were rigorously performed and the data support the conclusions presented.

Reviewer #1 (Public Review):

This project by Li et al. describes a colony morphology of P. aeruginosa that arises on agar plates and is especially pronounced in mutants lacking flagella, which were used for the majority of experiments in the paper. The paper documents the formation of large channels in the projections of swarming colonies, and within these channels, the rapid transport of fluid, cells, and extracellular vesicles. This transport is measured with great care and supported with additional support modeling.

- By and large, the project looks to have been executed with strong methodology and attention to detail in describing the channel formation effect found among colonies of P. aeruginosa flgK mutants. The authors have done very well in pushing known imaging methods to document transport within the colony channels and to make a case for how this transport is being driven physically. I think the aims of the detailed description of the physical phenomenon of colony growth in this environmental condition have been accomplished.

- A limitation here is that this colony morphology only seems to manifest strongly in mutants lacking flagella, which I don't think is common among wild P. aeruginosa isolates. To the extent that groups of P. aeruginosa cells have been imaged in situ, e.g. in the sputum of CF patients, this kind of channel formation does not occur in more realistic conditions. See DePas et al. (2015) https://journals.asm.org/doi/epub/10.1128/mBio.00796-16. I think it's more likely that this colony morphology is idiosyncratic to the agar growth substrate on which the cells are growing in this case, so the more interesting thing here is the physics of the system rather than its applications to clinical or ecological settings.

- The authors have established that flgK-null P. aeruginosa forms colonies with channels in this agar growth and incubation environment, and made a strong case for the physics underlying the spontaneous formation of this morphology. The idea that this morphology reflects a multicellular developmental program for P. aeruginosa is not strong, though, as this morphology is not found in the wild. In general, the idea that groups of microbes on agar are analogous to multicellular organisms with circulatory systems has little support from in-situ imaging experiments, or from fundamental evolutionary theory. So, I would advise shifting the introduction and discussion away from the multicellular organism focus toward a greater focus on the physics of the system and its potential for synthetic systems. See for example Yan et al. (2019) https://elifesciences.org/articles/43920

Reviewer #1 (Public Review):

The study presented by AL Seufert et al. follows the trajectory of trained immunity research in the context of sterile inflammatory diseases such as gout, cardiovascular disease and obesity. Previous studies in mice have shown that a 4 week Western-type diet is sufficient to induce systemic trained immunity, with gross reorganization of the bone marrow to support a potentiated inflammatory response [PMID: 29328911]. The current study demonstrates that mice on a Western-type diet (WD) and the more extreme Ketogenic diet (KD; where carbohydrates are essentially eliminated from the diet) for 2 weeks results in a state of increased monocyte-driven immune responsiveness when compared to standard chow diets (SC). This increased immune responsiveness after high-fat diet resulted in a deadly hyper-inflammatory in the mice in response to endotoxin (LPS) challenge in vivo. These initial findings as displayed in Figure 1 are made difficult to interpret because the authors use a mix of male and female mice coupled with very small sample sizes ( n = 5 - 9). Male and female mice are shown to have dimorphic responses to LPS exposure in vivo, with males having elevated cytokine levels (TNF, IL-6, IL-1β, and also interesting IL-10) increased rates severe outcomes to LPS challenge [PMID: 27631979]. As a reader it is impossible to discern from their methodological description what the proportion of the sexes were in each group, and therefore cannot determine if their data are skewed or biased due to sexual dimorphic responses to LPS rather than diet. Additionally due to the very small sample sizes, the authors can't perform a stratified analysis based on sex to determine whether the diets are having the greatest effects in accordance with LPS induce inflammation.

When comparing SC to the KD, the authors identify large changes in fatty acid distribution circulating in the blood. The majority of the fatty acids were shown to relate to saturated fatty acids (SFA). Although Lauric, Myristic, and Myristovaccenic acid where the most altered after KD, the authors focus their research on the more thoroughly studied palmitic acid (PA). PA was shown to increase the expression of inflammatory cytokines gene expression and protein production of TNF, IL-6 and IL-1β in bone marrow derived macrophages (BMDMs). The authors tie these effects to ceramide synthesis through a pharmacological blockade as well as the use of oleic acid, which allegedly sequesters ceramide synthesis. The author's claim that oleic acid supplementation reverses the inflammatory signaling induced by PA is invalid, as oleic acid was shown to induce a high level of cytokines in their model. When PA was added along with oleic acid, the cytokine levels returned to the levels produced by BMDM's stimulated with PA alone (see Figure 4 panels D- F).

Finally the authors test whether injection of PA into mice can recapitulate the systemic inflammatory response seen by WD and KD feeding followed by LPS exposure. They were able to demonstrate that injecting 1 mM of PA, waiting for 12h, and then exposing the mice to LPS for 24h could similarly result in a hyper-inflammatory state resulting in greater mortality. The reviewer is skeptical that 1 mM of PA truly represents post-prandial PA levels as one would expect to see after a single fatty meal, and whether this injection is generally well tolerated by mice. Looking into the paper cited by Eguchi et al. to inform their methods, it's shown that the earlier study continuously infused an emulsified ethyl palmitate solution (which contained 600 mM) at a rate of 0.2 uL/min. As far as I can read by Eguchi, they only managed to reach a serum PA concentration of 0.5 mM. This is hardly the same thing as a single i.p. injection of 1 mM PA. and reflects a single bolus injection of double the serum concentration of PA achieved by Eguchi et al.

PA is known to induce inflammation in monocytes and macrophages, therefore the findings certainly make sense in the context of previously published literature. However the authors have made some poor methodological decisions in their mouse studies, namely haphazardly switching between groups of young and old mice (4-6 weeks, 8-9 weeks, and 14-23 weeks), using different LPS injection protocols (6, 10, and 50 mg/ml of LPS), and including multiple sexes of mice. All of which are drastically alter the interpretation of the data, and preventing solid conclusions from being drawn.

Reviewer #1 (Public Review):

In this manuscript, the authors generated a zbtb14 mutant zebrafish strain via CRISPR-Cas9. In the mutant fish, they found an abnormal expansion of primitive macrophages during early development and adult macrophages in the kidney marrow. The abnormal expansion of macrophages in the mutants was confirmed to be caused by the loss of zbtb14 function, as over-expressing either zebrafish zbtb14 or human ZBTB14 could rescue the phenotype. To explore the underlying molecular mechanism, the authors performed RNA-seq analysis and found that the expression of pu.1 was up-regulation in the mutant macrophages. They further showed that the injection of mpeg1.1:pu.1-DBD construct into the mutant embryos to suppress the Pu.1 activity was able to rescue the mutant phenotype. The authors then went on to show that the SUMOylation of Zbtb14 plays an essential role in the transcriptional repression activity of the proteins. Finally, the authors documented that over-expressing the S8F mutant form of human ZBTB14, an AML associated mutation, failed to rescue the macrophage phenotype in zbtb14 mutants, suggesting that the loss of ZBTB14 function may be associated with the development of AML. Overall, the findings are interesting in developmental biology and gene regulation, especially in normal and malignant myelopoiesis.

Reviewer #1 (Public Review):

The authors have used many cleverly chosen mouse models (periodontitis models; various models that lead to an on-switch of genes) and methods (immune localizations of high quality; single cell RNA sequencing) for the quest of elucidating a role for telocytes. They describe that more telocytes are present around teeth in mice that had periodontitis. These cells proliferated, and they expressed a pattern of genes that allowed macrophages to differentiate into a different direction. In particular, they showed that telocytes in periodontitis express HGF, a molecule that steers macrophage differentiation towards a less inflammatory cell type, paving the way for recovery. As a weakness, one could state that an attempt to extrapolate to human cells is missing.

Reviewer #3 (Public Review):

Zhao and Sharpe identified telocytes in the periodontium. To address their contribution to periodontal diseases, they conducted scRNA-seq analysis and lineage tracing in mice. They demonstrated that telocytes are activated in periodontitis. The activated telocytes send HGF signals to surrounding macrophages, converting M2 to M1/M2 hybrid status. The study implies that targeting telocytes and HGF signal for the potential treatment of periodontitis.

The significance of the study could be improved by authors testing if targeting telocytes or HGF signals could ameliorate periodontitis in the mouse model. The current form of the manuscript lacks the data that demonstrate the actual contribution of telocytes in the homeostasis of periodontium or progression of periodontitis.

Major comments:

1) I see the genetic validation of the role of telocytes or HGF signals are crucial to assure the significance of this manuscript. I recommend either of two experiments. a. testing the role of HGF signals by deleting the Hgf gene in telocytes. Using Wnt11-Cre; Hgf f/f mice, the authors could address the role of HGF signals in periodontitis. CX3CR1-Cre; cMet f/f mice will delete HGF signals in monocyte-derived macrophages. This will be another verification, but not sure if the PDL macrophages are derived from yolk sac or monocytes. b. measuring the contribution of telocytes in the homeostasis or disease progression. The mouse model could be challenging though, the system if achieved will be very informative. The authors could first check the expression of telocyte enriched genes, such as Lgr5 or Foxl1 reported previously in other tissue telocytes. Delete those genes under the Wnt1-Cre driver and check if telocyte lineage is removed. The system would be very useful for next-level study. DTA model could be an alternative, but Wnt1-Cre is vastly expressed in neural crest lienage.

2) This paper points out that the M1/M2 hybrid state of macrophages appears upon periodontitis. The authors could further characterize the hybrid macrophages by the expression of more markers, production of cytokines, and morphology. Need to clarify if this means some macrophages are in M1 state and others are in M2 state, or one macrophage possesses both M1 and M2 phenotype. Please conduct either FACS or immunofluorescence to demonstrate if one macrophage expresses both markers. Please introduce more information about the M1/M2 hybrid state of macrophage based on other present literature.

3) In the introduction part, the author lists several markers that can be used for telocyte identification, such as CD34+CD31-, CD34+c-Kit+, CD34+Vim+, CD34+PDGFRα+. Could authors explain why they chose CD34 CD31, but not other markers?

4) In figure 5g, I don't think the yellow color cell shows the reduction trend in the Tivantinib treatment group compared with a control group. Please validate the observation by gene expression analysis, WB, etc. In addition, please show c-Met+ cells level in the Tivantinib treatment group and control group.

Reviewer #1 (Public Review):

It was previously shown that HGF and Met controls development of the diaphragm muscle. In particular, the signal induces delamination and migration of muscle progenitor cells that colonize the diaphragm. The present manuscript by Sefton and coworkers confirms and extends these observations using (i) conditional mouse lines in which the HGF gene was targeted by Cre/loxP recombination in the pleuroperitoneal folds (Prx1-cre) and at other sites PdgfraCreERT2, and of (ii) Met inhibitors. Overall, the technical quality of the data on diaphragm muscle development is excellent; the conceptual advance over previous work is not exceptional; the evidence for Met/HGF-dependent development of the phrenic nerve is marginal and needs to be strengthened.

The data show that fibroblasts provide HGF signals received by Met in muscle progenitor cells that is essential for diaphragm development. The PdgfraCreERT2 line was used to demonstrate that HGF produced by fibroblasts but not by muscle progenitors is essential for diaphragm development. Moreover, development of dorsal and ventral regions of diaphragm muscle requires continuous MET signaling. Thus, HGF is not only required for the delamination of progenitors, but also for proliferation and survival of those muscle progenitors that reached the anlage of the diaphragm.

My major concern is the limited data on the HGF-dependent development of the phrenic nerve (defasciculation). While it is well documented that HGF acts as a trophic factor for motor neurons in culture, its role in development of motor neurons was highly debated due to the fact that some changes observed in Met or HGF mutant mice in vivo are also present in other mutants that lack the muscle groups derived from migrating muscle progenitors. Moreover, careful genetic analyses previously demonstrated indirect mechanisms of Met during motor neuron development, i.e. a non-cell-autonomous function of Met during the recruitment of motor neurons to PEA3-positive motor pools (Helmbacher et al., Neuron 2003).

Sefton et al. provide an analysis of a single time point, one histological picture (3G, magnified in 3H) that indicate that in Met+/- animals defasciculation of the phrenic nerve does not occur correctly. This is accompanied by a quantification that barely reaches significance (Fig. 3K). Data shown in Fig. 7 using Met inhibitors show a major change in phrenic nerve branching, which is presumably due to the major change in diaphragm development, as conceded by the authors.

Despite this weakness on the experimental side, the role of HGF/Met in phrenic nerve development is strongly emphasized in abstract /intro/discussion (e.g. line 414: However, PPF-derived HGF is crucial for the defasciculation and primary branching of the nerve, independent of muscle). The data need to be strengthened in order to conclude that HGF coordinates both, diaphragm muscle and phrenic development.

Reviewer #3 (Public Review):

In this MS by Sefton et al., the authors investigate the role of HGF/MET pathway, as well as the cellular source of these molecules, during diaphragm development. In particular, the authors address the function of this pathway on muscle progenitors and phrenic nerve. They further provide evidence for the expression of HGF in pleuroperitoneal folds and for its requirement for muscle progenitor recruitment and maintenance during diaphragm muscle formation. This study is interesting and in general the results support the conclusions. The work could be improved by (1) providing appropriate controls for the role of HGF in the connective tissue and (2) linking the muscleless diaphragms and HGF to the hernia phenotype.

Reviewer #1 (Public Review):

This Methods paper explores methods of assaying the balance between muscle cell quiescence and activation. If successful, it offers a miniaturized assay that will permit systematic investigations of long-standing queries in key areas of muscle function such as regulation of adult stem cell pool size and functional heterogeneity. It could also be used to discover regulators of quiescence.

Reviewer #1 (Public Review):

This paper represents the first spatio-temporal functional parcellation derived from infant multimodal imaging data. The parcellations are generated from the longitudinally collected baby connectome project, and clearly benefit from incorporating repeat samples from individuals. Analyses demonstrate that parcellations estimated for different age groups (3, 6, 9, 12, 18 and 24 months) are fairly consistent and that repeat generation of the parcellations, using shuffled 'generating' and 'repeating' groups is robust.

In general, I think the paper does an extremely good job of robustly testing its claims and therefore I have relatively few suggestions for improvement. However, I do have some concerns that the differences in network clustering reported in Fig 6 may be due to noise and I think the comparisons against the HCP parcellation could be more robust.

Specifically, with regard to the network clustering in Fig 6. The authors use a clustering algorithm (which is not explained) to cluster the parcels into different functional networks. They achieve this by estimating the mean time series for each parcel in each individual, which they then correlate between the n regions, to generate an nxn connectivity matrix. This they then binarise, before averaging across individuals within an age group. It strikes me that binarising before averaging will artificially reduce connections for which only a subset of individuals are set to zero. Therefore averaging should really occur before binarising. Then I think the stability of these clusters should be explored by creating random repeat and generation groups (as done for the original parcells) or just by bootstrapping the process. I would be interested to see whether after all this the observation that the posterior frontoparietal expands to include the parahippocampal gryus from 3-6 months and then disappears at 9 months - remains.

Then with regard to the comparison against the HCP parcellation, this is only qualitative. The authors should see whether the comparison is quantitatively better relative to the null clusterings that they produce.

While it's clear from the results that the template achieves some good degree of spatio-temporal coherence, from the considerable benefit of the longitudinal imaging, not all individuals appear (from Fig 8) to be acquired exactly at the desired timepoints, so maybe the authors might comment on why they decided not to apply any kernel weighted or smoothing to their averaging? Pg. 8 'and parcel numbers show slight changes that follow a multi-peak fluctuation, with inflection ages of 9 and 18 months' explain - the parcels per age group vary - with age with peaks at 9 and 18 - could this be due to differences in the subject numbers, or the subjects that were scanned at that point?

I also have some residual concerns over the number of parcels reported, specifically as to whether all of this represents fine grained functional organisation, or whether some of it represents noise. The number of parcels reported is very high. While Glasser et al 2016 reports 360 as a lower bound, it seems unlikely that the number of parcels estimated by that method would greatly exceed 400. This would align with the previous work of Van Essen et al (which the authors cite as 53) which suggests a high bound of 400 regions. While accepting Eickhoff's argument that a more modular view of parcellation might be appropriate, these are infants with underdeveloped brain function. Further comparisons across different subjects based on small parcels increases the chances of downstream analyses incorporating image registration noise, since as Glasser et al 2016 noted, there are many examples of topographic variation, which diffeomorphic registration cannot match. Therefore averaging across individuals would likely lose this granularity. I'm not sure how to test this beyond showing that the networks work well for downstream analyses but I think these issues should be discussed.

Finally, I feel the methods lack clarity in some areas and that many key references are missing. In general I don't think that key methods should be described only through references to other papers. And there are many references, particular to FSL papers, that are missing.

Reviewer #1 (Public Review):

In this paper, Abadchi et al. investigate neocortical activity patterns surrounding sharp-wave ripples in awake head-fixed mice. To do so, the authors combine multiple approaches, including wide-field voltage and glutamate imaging, 2-photon single-cell calcium imaging, and electrophysiology, used to monitor the hippocampal LFP and MUA. The authors' previous findings in anaesthetized and head-fixed sleeping mice indicated that the majority of cortical areas were strongly activated by ripples. In contrast, they now show that ripple-related neocortical patterns in the awake brain show predominantly suppression of activity. Interestingly, this deactivation seems to be most pronounced and to occur earliest in the agranular retrosplenial cortex (aRSC). To gain a better understanding of the internal dynamics underlying ripple modulation in the RSC the authors perform 2-photon calcium imaging and find that similar proportions of superficial excitatory cells are activated and suppressed during ripples.

Ripple oscillations have been implicated in multiple cognitive processes including memory consolidation, memory retrieval, and planning, and there is causal evidence suggesting that awake and sleep ripples are differentially involved in those functions. Consequently, understanding the physiological mechanisms underlying hippocampal-neocortical communication during both brain states is of pivotal importance. Many studies investigated the modulation of various cortical areas by ripples during sleep and wakefulness, but the majority of those studies focused on one or few areas. The author's previous study (Abadchi et al., 2020) was an exception in this regard, as it provided a rich characterization of activity surrounding sleep ripples in multiple neocortical areas, including latency to response and direction of propagation. The present study purports to be complementary to those published results, although it lacks many of the analyses used for the sleep paper, which is a missed opportunity. The stark sleep/wake differences in cortical peri-ripple activity reported by the authors are surprising, interesting, and potentially of substantial importance for understanding the functions of ripples in the awake vs. sleep state. However, many of the results presented in the paper are insufficiently analyzed and their statistical significance is unclear, demanding further quantification and clarifications. Moreover, while the paper's major strength lies in the combination of multiple large-scale approaches, it could do better in combining those observations into a coherent conclusion.

Major points:

1) There is affluent evidence that the cortical activity in the waking brain, even in head restrained mice, is not uniform but represents a spectrum of states ranging from complete desynchronization to strong synchronization, reminiscent of the up and down states observed during sleep (Luczak et al., 2013; McGinley et al., 2015; Petersen et al., 2003). Moreover, awake synchronization can be local, affecting selective cortical areas but not others (Vyazovskiy et al., 2011). State fluctuations can be estimated using multiple criteria (e.g., pupil diameter). The authors consider reduced glutamatergic drive or long-range inhibition as potential sources of the voltage decrease but do not attempt to address this cortical state continuum, which is also likely to play a role. For example: does the voltage inactivation following ripples reflect a local downstate? The authors could start by detecting peaks and troughs in the voltage signal and investigate how ripple power is modulated around those events.

2) Ripples are known to be heterogeneous in multiple parameters (e.g., power, duration, isolated events/ ripple bursts, etc.), and this heterogeneity was shown to have functional significance on multiple occasions (e.g. Fernandez-Ruiz et al., 2019 for long-duration ripples; Nitzan et al., 2022 for ripple magnitude; Ramirez-Villegas et al., 2015 for different ripple sharp-wave alignments). It is possible that the small effect size shown here (e.g. 0.3 SD in Fig. 2a) is because ripples with different properties and downstream effects are averaged together? The authors should attempt to investigate whether ripples of different properties differ in their effects on the cortical signals.

3) The differences between the voltage and glutamate signals are puzzling, especially in light of the fact that in the sleep state they went hand in hand (Abadchi et al., 2020, Fig. 2). It is also somewhat puzzling that the aRSC is the first area to show voltage inactivation but the last area to display an increase in glutamate signal, despite its anatomical proximity to hippocampal output (two synapses away). The SVD analysis hints that the glutamate signal is potentially multiplexed (although this analysis also requires more attention, see below), but does not provide a physiologically meaningful explanation. The authors speculate that feed-forward inhibition via the gRSC could be involved, but I note that the aRSC is among the two major targets of the gRSC pyramidal cells (the other being homotypical projections) (Van Groen and Wyss, 2003), i.e., glutamatergic signals are also at play. To meaningfully interpret the results in this paper, it would be instrumental to solve this discrepancy, e.g., by adding experiments monitoring the activity of inhibitory cells.

4) I am puzzled by the ensemble-wise correlation analysis of the voltage imaging data: the authors point to a period of enhanced positive correlation between cortex and hippocampus 0-100 ms after the ripple center but here the correlation is across ripple events, not in time. This analysis hints that there is a positive relationship between CA1 MUA (an indicator for ripple power) and the respective cortical voltage (again an incentive to separate ripples by power), i.e. the stronger the ripple the less negative the cortical voltage is, but this conclusion is contradictory to the statements made by the authors about inhibition.<br /> 5) Following my previous point, it is difficult to interpret the ensemble-wise correlation analysis in the absence of rigorous significance testing. The increased correlation between the HPC and RSC following ripples is equal in magnitude to the correlation between pre-ripple HPC MUA and post-ripple cortical activity. How should those results be interpreted? The authors could, for example, use cluster-based analysis (Pernet et al., 2015) with temporal shuffling to obtain significant regions in those plots. In addition, the authors should mark the diagonal of those plots, or even better compute the asymmetry in correlation (see Steinmetz et al., 2019 Extended Fig. 8 as an example), to make it easier for the reader to discern lead/lag relationships.

6) For the single cell 2-photon responses presented in Fig. 3, how should the reader interpret a modulation that is at most 1/20 of a standard deviation? Was there any attempt to test for the significance of modulation (e.g., by comparing to shuffle)? If yes, what is the proportion of non-modulated units? In addition, it is not clear from the averages whether those cells represent bona fide distinct groups or whether, for instance, some cells can be upmodulated by some ripples but downmodulated by others. Again, separation of ripples based on objective criteria would be useful to answer this question.

7) Fig. 3: The decomposition-based analysis of glutamate imaging using SVD needs to be improved. First, it is not clear how much of the variance is captured by each component, and it seems like no attempt has been made to determine the number of significant components or to use a cross-validated approach. Second, the authors imply that reconstructing the glutamate imaging data using the 2nd-100th components 'matches' the voltage signal but this statement holds true only in the case of the aRSC and not for other regions, without providing an explanation, raising questions as to whether this similarity is genuine or merely incidental.

8) The estimation of deep pyramidal cells' glutamate activity by subtracting the Ras group (Fig. 4d) is not very convincing. First, the efficiency of transgene expression can vary substantially across different mouse lines. Second, it is not clear to what extent the wide field signal reflects deep cells' somatic vs. dendritic activity due to non-linear scattering (Ma et al., 2016), and it is questionable whether a simple linear subtraction is appropriate. The quality of the manuscript would improve substantially if the authors probe this question directly, either by using deep layer specific line/ 2-P imaging of deep cells or employing available public datasets.

Cited literature<br /> Abadchi, J.K., Nazari-Ahangarkolaee, M., Gattas, S., Bermudez-Contreras, E., Luczak, A., McNaughton, B.L., and Mohajerani, M.H. (2020). Spatiotemporal patterns of neocortical activity around hippocampal sharp-wave ripples. Elife 9, 1-26.<br /> Fernandez-Ruiz, A., Oliva, A., Oliveira, E.F. De, Rocha-Almeida, F., Tingley, D., and Buzsáki, G. (2019). Long-duration hippocampal sharp wave ripples improve memory. Science (80-. ). 364, 1082-1086.<br /> Van Groen, T., and Wyss, J.M. (2003). Connections of the Retrosplenial Granular b Cortex in the Rat. J. Comp. Neurol. 463, 249-263.<br /> Luczak, A., Bartho, P., and Harris, K.D. (2013). Gating of Sensory Input by Spontaneous Cortical Activity. J. Neurosci. 33, 1684-1695.<br /> Ma, Y., Shaik, M.A., Kim, S.H., Kozberg, M.G., Thibodeaux, D.N., Zhao, H.T., Yu, H., and Hillman, E.M.C. (2016). Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches. Philos. Trans. R. Soc. B Biol. Sci. 371.<br /> McGinley, M.J., David, S. V., and McCormick, D.A. (2015). Cortical Membrane Potential Signature of Optimal States for Sensory Signal Detection. Neuron 87, 179-192.<br /> Nitzan, N., Swanson, R., Schmitz, D., and Buzsáki, G. (2022). Brain-wide interactions during hippocampal sharp wave ripples. Proc. Natl. Acad. Sci. 119.<br /> Pernet, C.R., Latinus, M., Nichols, T.E., and Rousselet, G.A. (2015). Cluster-based computational methods for mass univariate analyses of event-related brain potentials/fields: A simulation study. J. Neurosci. Methods 250, 85-93.<br /> Petersen, C.C.H., Hahn, T.T.G., Sakmann, B., Grinvald, A., and Mehta, M. (2003). Interaction of sensory responses with spontaneous depolarization in layer 2/3 barrel cortex. Proc. Natl. Acad. Sci. 100, 13638-13643.<br /> Ramirez-Villegas, J.F., Logothetis, N.K., and Besserve, M. (2015). Diversity of sharp-wave-ripple LFP signatures reveals differentiated brain-wide dynamical events. Proc. Natl. Acad. Sci. 112, E6379-E6387.<br /> Steinmetz, N.A., Zatka-Haas, P., Carandini, M., and Harris, K.D. (2019). Distributed coding of choice, action and engagement across the mouse brain. Nature 1-8.<br /> Vyazovskiy, V. V, Olcese, U., Hanlon, E.C., Nir, Y., Cirelli, C., and Tononi, G. (2011). Local sleep in awake rats. Nature 472, 443-447.

Reviewer #3 (Public Review):

This manuscript aimed to reveal the difference and similarity of sharp-wave ripples in awake vs. sleeping mice. To do this, the authors used wide-view voltage and glutamate activity imaging in awake head-fixed mice. The two-photon Ca imaging was applied to examine the spiking activity of the retrosplenial cortex.

They showed that the mean membrane potential and glutamatergic transmission of the neocortex's superficial layers were suppressed and enhanced, respectively, just after the sharp-wave ripples in awake mice, contrary to the same authors' previous findings in urethane-anesthetized and naturally sleeping mice. The retrosplenial cortex was most strongly modulated in membrane potential and glutamatergic transmission by awake sharp-wave ripples. The authors also found two groups of retrosplenial cortical neurons, whose spiking activity, measured by Ca dynamics, was suppressed and enhanced by awake sharp-wave ripples. These findings revealed the critical difference between sharp-wave ripples during waking vs. sleep, which would impact the field of memory research.

This manuscript's strength is that it compares the dynamics of membrane potential and glutamate transmission using wide view imaging. Both experimental and analytical methods were appropriate and supported their main conclusions.

Reviewer #1 (Public Review):

The Cretaceous dinosaur Spinosaurus has recently drawn significant attention as it was hypothesized as the first aquatic dinosaur. The authors provide additional lines of evidence including the CT-based skeletal restoration of Spinosaurus and biomechanical tests to challenge the 'aquatic hypothesis'. The key claims of the manuscript are supported by the new data and the new analyses are important for the further clarification of the Spinosaurus lifestyle.

Reviewer #3 (Public Review):

The authors attempted to, and succeeded at, testing the recent hypothesis that the large theropod dinosaurs Spinosaurus was a fast and capable swimmer and diver.

The strengths of the paper are the extent of the analyses which address and test numerous aspects of the 'aquatic hypothesis' with some depth, though in places this needs a better explanation of the details of the process and organisation. The results do support the conclusions, though these should be more specific and clear and relate to the recent literature on Spinosaurus habits to say what is, and is not, possible/plausible based on their analyses.

Overall this is likely to be a major step forwards in resolving the biology of this animal (and kin) and add considerable depth to the discussion by adding new data and results.

Research on social annotation

Peer review report

Title: Angiotensin converting enzyme (ACE) expression in leukocytes of older adults

version: 1

Reviewer: Heikki Vapaatalo, MD, PhD, Emeritus professor of Pharmacology

Institution: Department of Pharmacology, Medical Faculty,University of Helsinki, Finland

email: heikki.vapaatalo@helsinki.fi

General assessment

The study is interesting and the title promises for me more than the MS finally contains.

The background, question and the aim are relevant as explained in the introduction.

The major criticism concerns the small size of the material (subjects, n=6), the small age difference (64-67 years) and the lack of younger controls.

In the following minor notes:

Title: ACE > better ACE1, or does the sophistic, elegant method include both ACE:s? The same should be explained and taken into consideration throughout the text.

Introduction: The last chapter, the Author should explain in more detail, how references 11-14 suggest that “ACE play an important role in the aging process”. ACE plays. Does this mean, that ACE is somehow regulating the aging process or in increasing age ACE -levels are changed?

Material and Methods: The N-value of the subjects should be mentioned here, as well the relation of females/males. Do the Authors really regard 64-67 “older age” nowadays? Lack of younger controls! Why first many years later the assays have been done in comparison to the collection of the blood? Are the samples still useable, not destroyed? Did the subjects have some diseases and/or drugs because the possibly were from hospital sample bank? Express the company details similarly than Amersham, cities and countries.

Results: “Table 1 shows that older adults…..” The comparison between the present data and historical studies belongs to the Discussion. Give also individual ages and gender of the subjects in the table 1. What means p-values here? Compared with which or interindividual differences in the particular variable? Should be explained The numbering of tables and the text seems to me confusing. Only three tables, but in the text mentioned four. Number 4 does not exist. It would be good to have a list of abbreviations used in the description of the cell types for an unfamiliar reader.

Discussion: A major part of the discussion deals with previous publications and not meaning or clinical significance of the present findings and comparison between the present and earlier studies. In those previous studies, also ACE2 has been reported, why not studied here? In the limitations, the Authors fairly mention the real problem: The small sample size, and I would like to say lack of younger subjects. The COVID-19 point even tempting to-day, is too far from this study and unnecessary. Linguistic checking would improve the MS.

As a summary: I recommend the acceptance of the MS for publication after the Authors careful rethinking of the message of the results and correction of the minor comments. I hope that in the future the possible age -related correlations to old age up to >80 years would be possible.

Decision

Verified with reservations: The content is scientifically sound but has shortcomings that could be improved by further studies and/or minor revisions.

Decision changed:

Verified manuscript: The content is scientifically sound, only minor amendments (if any) are suggested.

Reviewer #1 (Public Review):

Bosada et al present a study on how regulatory elements found in two atrial fibrillation-associated regions at the TBX5 locus correlate to Tbx5 expression levels and arrhythmia susceptibility. In transgenic mouse models, the investigators deleted the orthologues of these regulatory elements at the human Tbx5 locus. Tbx5 expression levels were increased in both models, and the downstream impact on epigenetic and gene expression levels was assessed. The RE(int)-/- mice had higher expression levels of Tbx5 compared to RE(down)-/- mice and this was correlated with increased atrial arrhythmia inducibility and higher numbers of transcripts impacted in the atrial gene regulatory network analysis. Multiple pathways are affected, and the authors present data on the interaction between Tbx5 and Prrx1, which encodes a cardiac transcription factor and the human ortholog harbors an atrial fibrillation-associated variant. The presented work links with the prior observation that increase in Tbx5 expression is associated with human atrial fibrillation and provides a plausible mechanistic link.

Reviewer #3 (Public Review):

In the manuscript by Bosada et al, the authors present work identifying and interrogating two cis-regulatory elements at TBX5 associated with atrial fibrillation. Mouse models lacking both copies of either element, but particularly one in the last intron of the Tbx5 gene, referred to as RE(int), results in increased Tbx5 expression, changes to cardiac electrophysiology, and downstream gene expression changes. Of interest, RE(int) induces expression of Prrx1, also associated with atrial fibrillation, and compound mutants partially rescues the RE(int) phenotype. Overall, this paper is of interest and advances our understanding of TBX5 in atrial fibrillation risk in humans. Critically, this study focuses on the impact of risk SNPs, which increase TBX5 expression in patients, while previous studies involving TBX5 in atrial fibrillation have focused on decreased expression.

The authors' work presents the following major claims:<br /> Figure 1. Identification of two, independently segregating risk regions at TBX5, which are conserved in humans and mice with predicted cis-regulatory functions termed RE(int) and RE(down).<br /> Figure 2. Homozygous RE(int) and RE(down) mutants, with a particular focus on RE(int) mutants, resulting in increased expression of Tbx5. The functional SNP appears to be rs7312625 A>G.<br /> Figure 3. Homozygous RE(int) mutants demonstrate several cardiac electrophysiological changes consistent with increased atrial fibrillation risk in humans.<br /> Figure 4. Cellular electrophysiology of RE(int) mutant cardiomyocytes demonstrates additional supportive changes to explain whole organ phenotypes presented in Figure 3.<br /> Figure 5. Transcriptional profiling of RE(int) and RE(down) homozygous mutants demonstrates many significant differences from control samples that are suggestive of specific mechanisms disrupting cardiac electrophysiology, including calcium and potassium regulators and gap junctions.<br /> Figure 6. Homozygous RE(int) and Prrx1(enh) mutant alleles genetically interact and result in partial rescue of phenotypes from RE(int) alone.

Reviewer #1 (Public Review):

The authors aim at establishing a biologically plausible learning rule for the Successor Representation (SR) to be computed by neural circuits.

The study is well designed with a strong logical flow moving from a simple example (random process on a circle) to comparison with real neural data. The manuscript is well written in all its components and figures are clear. All the results provided in the main paper are backed up by a thorough theoretical analysis outlined in the supplementary material. As it is common the theoretical analysis does not have much space in the manuscript. I would suggest summarizing with more specific statements the theoretical results that are achieved whenever there is a pointer to a supplementary note.

While the authors perform an extensive and careful review of the literature, a lot of it is confined to the Discussion. As the results of the paper strongly rely on the normalizing term in Eq.4. I would suggest potentially moving upfront part of the discussion of this term. I would suggest enlarging the paragraph that discusses the biological plausibility of this specific term. Clearly laying out, for the non-expert reader, why it is biologically plausible compared to other learning rules. And I would also consider moving the required material to establish the novelty of such term: a targeted review of the relevant literature (current lines 358-366 and 413-433). This would allow the reader to understand immediately the significance and relative novelty of such term. For example, I personally wondered while reading the paper how different was such term from the basic idea of Fiete et al. Neuron 2010 (DOI 10.1016/j.neuron.2010.02.003).

I would also suggest writing a "limitations" paragraph in the discussion clearly outlining what this learning rule couldn't achieve. For example, Stachenfeld et al Nat.Neuro. have many examples where the SR is deployed. I wonder if the learning rule suggested by the authors would always work across the board, or if there are limitations that could be highlighted where the framework suggested would not work well. I am not suggesting performing more experiments/simulations but simply sharing insight regarding the results and the capability of the proposed learning rule.

Reviewer #3 (Public Review):

Experimental and computational works have proposed that neurons in the hippocampus represent a predictive map of the environment called the successor representation. This theoretical study examines how plasticity in a model network of recurrently connected neurons can lead to such a representation. The main conclusion is that any plasticity rule that encodes transition probabilities in synaptic weights gives rise to the successor representation at the level of neural activity. This fundamental theoretical insight gives additional credibility to the idea that the hippocampus can implement the successor representation.

Strengths:<br /> - elegantly designed theoretical study<br /> - very clear writing that progressively introduces the main result and argues for its generality<br /> - comparison of the model with data in a random foraging task

Weaknesses:<br /> - certain technical choices need additional motivation

Reviewer #1 (Public Review):

This is an elegant and fascinating paper on individuality of structural covariance networks in the mouse. The core precepts are based on a series of landmark papers by the same authors that have found that individuality exists in inbred mice, and becomes entrenched when richer environments are available. Here they used structural MRI to provide whole brain analyses of differences in brain structure. They first replicated brain (mostly hippocampal) effects of enrichment. Next, they used their roaming entropy measurements to show that, after dividing their mice into two groups based on their roaming entropy, that there were no differences in brain structure between the two groups yet significant differences in brain networks as measured by structural covariance. Overall I enjoyed this paper, though am confused (and possibly concerned) about how they arrived at their two groups and have some less important methods questions.

The division of mice into two groups (down and flat) is confusing. The methods appear to suggest that k-means clustering combined with the silhouette method was used (line 380). The actual analyses used involves 2 groups of 15 mice each. The body of the manuscript suggests that 10 intermediate mice were excluded (line 100), but the methods (line 390) suggest that 8 mice were excluded, 2 for having intermediate results and 6 for having high RE slope values.

This leads to a series of questions:<br /> - How many mice were excluded and for what reasons, given the discrepancy between body and methods?<br /> - Was the k-means clustering actually used? It appears that the main division of mice was based on visual assessments.<br /> - If the clustering was used, did it result in 2 or 3 groups?<br /> - The intermediate group bothers me (if it was indeed 10 intermediate mice as indicated by the body rather than 2 as indicated in the methods): if these are indeed intermediate shouldn't they be analyzed and shown to be intermediate on the graph or other measures?<br /> - Please explain the reasoning for excluding mice for having too high of a slope (if there were indeed mice excluded for having too high of a slope).

I'd also appreciate more discussion about the structural covariance differences between flat and down mice. It is not clear what the direction of effects are - it appears that flats show mostly increases in covariance?

Reviewer #3 (Public Review):

The present study is a comparison of brain magnetic resonance imaging (MRI) of mice who developed in an enriched environment laboratory environment, in which some mice become habituated while other mice maintain active exploration of the environment over time. Between these groups, differences are shown in the pattern of correlations between brain regions of interindividual variability, which may indicate differences in brain connectivity or other shared maturational processes between regions. Because the mice are genetically inbred and have the same shared environment, these differences are attributed to individual-level differences in environment and behavior, which are extremely difficult to isolate in non-laboratory settings.

My comments are focused on aspects of the paper that overlap with my area of expertise which is human brain MRI methods. The strengths of the paper include the unique environmental paradigm that provides support for important hypotheses about individual-level variation. The imaging methods are rigorous and sound, and there is a nice convergence with human work. The application of structural covariance is interesting. The weaknesseses of the paper are that the writing could be clearer. Alternative explanations for structural covariance and alterations in "down roamers" should be more fully considered. The statistical approaches could be more rigorous in places. The areas of novelty relative to past work should be more explicitly articulated.

Reviewer #1 (Public Review):

This is a very timely and substantial advance in connectomics research that allows the fast reconstruction of selected neuronal circuits at synaptic resolution using tissue expansion and light sheet imaging. The authors describe this methodology in detail as applied to Drosophila brain, with multiple examples across different neuronal types and labeling strategies. The study is very rigorously done, methods are presented with important details, and the discussion is engaging and balanced. The paper is excellently written and very informative.

The authors begin by introducing a workflow to detect and quantify presynaptic structures of specific neuronal types. This approach takes advantage of the T-bar protein Brp ubiquitously expressed at presynapses and the widely used nc82 antibody against it, as well as the fact that presynapses are larger neurites that are readily resolvable with light microscopy. Using three distinct neuronal types, the authors show that the number of presynapses obtained with the presented light microscopy method, matches well the synapse number quantified by the gold standard, electron microscopy.

Next, the authors present two approaches to tackle a more difficult task - the quantification of the synaptic connectivity between 2 specific neuronal types. Compared to mammals, the identification of the postsynaptic site is more difficult in the Drosophila, because each presynapse contacts several different postsynaptic neurites that are right next to each other and are much smaller in size. No ubiquitous postsynaptic marker is currently available for the fly brain either. However when there is a postsynaptic marker available for specific connection, this makes the synaptic connection identification much more reliable, as shown with the example of the synaptic connections between the cholinergic SAG neurons and their postsynaptic target, the pC1 neurons, using the postsynaptic marker Drep2. Using this strategy the authors demonstrate that mated female flies have significantly less synaptic connections between SAG neurons and pC1 neurons, compared to virgin flies.

In addition to chemical synapses, this study also shows a proof of principle that electrical synapses, gap junctions, can similarly be mapped using the same approach. This is very important, because these synapses are much more difficult to identify with electron microscopy and are not currently included in the available Drosphila connectomes. Definitive mapping of gap junctions however will require further work, outside the scope of this study, because there are different gap junction proteins and individual gap junctions may be heterotypic, composed of two different proteins.

Finally, the authors extend this approach to address the important question of whether variations in behavior can be explained by differences in underlying synaptic connectivity. Using the neuronal circuit known to be responsible for the male fly courtship song, the authors show that the synaptic connectivity between pC2l and pIP10 neurons is correlated with a specific component of the optogenetically-elicited fly song.

The developed imaging and analysis pipeline includes software for visualization of multi-terabyte images, automated neuronal segmentation, detection and quantification of pre- and postsynaptic sites. As the authors point out, these tools could be useful for circuit analysis in other species as well. The different imaging and analysis pipelines are presented very well, with multiple examples that cover different scenarios, and are well validated. While with this method it is not possible to directly correlate the fluorescence signal with the underlying ultrastructure as seen with EM, and thus it cannot be confirmed that the detected synaptic connections correspond to ultrastructurally defined synapses, the authors have convincingly demonstrated that the proposed approach is precise enough to detect a similar number of synapses as EM studies of the same neurons, and that it is sensitive enough to detect changes in synapse numbers in different experimental conditions.

Reviewer #3 (Public Review):

Lillvis et al present a new method for quick targeted analysis of neural circuits through a combination of tissue expansion and (lattice) light sheet microscopy. Three color labeling is available which allows to label neurons of a molecularly specific type, presynaptic and/or post-synaptic sites.

Strengths:<br /> - The experimental technique can provide much higher throughput than EM<br /> - All source code has been made available<br /> - Manual correction of automatic segmentations has been implemented, allowing for an efficient semi-automatic workflow<br /> - Very different kinds of analyses have been demonstrated<br /> - Inclusion of electrical connections is really exciting, what a great complement to the existing EM volumes!

Weaknesses:<br /> - Limitations of the method are not really discussed. While the approach is simpler and cheaper than EM, it's still important to give the readers a clear picture of the use cases where it's not expected to work before they embark on the journey of acquiring tens of terabytes of data. Here are just a few examples of the questions I would have if I wanted to implement the method myself - I am a computational person and can easily imagine my "wet lab" colleagues would have even more to ask about the experimental side:

-- It is not very clear to me if the resolution of the method is sufficient to disentangle individual neurons of the same type. It has been demonstrated for a few examples in the paper, but is it generally the case? Are there examples of brain regions/neuron types where it wouldn't be possible? If another column was added to the table in Figure 1, e.g. "individual neuron connectivity", EM would be "+", LM "-", what would ExLLSM be?<br /> -- Similarly, the procedures for filling gaps in the signal could result in falsely merged neurons. Does it ever happen in practice?<br /> -- How long does semi-manual analysis take in person-hours/days for a new biological question similar in scope to the ones demonstrated in the paper?<br /> -- How robust are the networks for synaptic "blob" detection? The authors have shown they work for different reporters, when are they expected to break? Would you recommend to retrain for every new dataset? How would you recommend to validate the results if no EM data is available?

Reviewer #1 (Public Review):

Current generative models of protein sequences such as Potts models, Variational autoencoders, or autoregressive models must be trained on MSA data from scratch. Therefore, they cannot learn common substitution or coevolution patterns shared between families, and require a substantial number of sequences, making them less suitable for small protein families (e.g., conserved only for eukaryotes or viruses). MSA transformers are promising alternatives as they can generalize across protein families, but there is no established method to generate samples from them. Here, Sgarbossa et al. propose a simple recursive sampling procedure based on iterative masking to generate novel sequences from an input MSA. The sampling method has three hyperparameters (masking frequency, sampling temperature, and the number of iterations) which are set by rigorous benchmarking. The authors compare their approach to bmDCA, and evaluate i) single sample quality metrics ii) sample diversity and similarity to native sequences iii) similarity between original and generated sequence distribution, and iv) phylogeny/topology in sequence space of the generated distribution.

Strengths:

- The proposed sampling approach is simple.<br /> - The computational benchmarking is thorough.<br /> - The code is well organized and looks easy to use.

Weaknesses:

- There is no experimental data to back up the methodology.<br /> - It is not clear whether the sampling hyperparameter used is optimal for all protein sizes.<br /> - I am unsure that the bmDCA baseline method was trained appropriately and that the sampling method was adequate for protein design purposes (regular sampling).<br /> - Quality assessment of predicted structures is incomplete.<br /> - The proposed metrics for evaluating the diversity of generated sequences are fairly technical.

Impact assessment: The claim that MSA Transformer could be useful for protein design is supported by the computational benchmark. This work will be useful for researchers interested in applying MSA-Transformer models for protein design

Reviewer #1 (Public Review):

Our understanding of the early stages of myelination within the CNS is relatively rudimentary. In this manuscript the authors use selective cell labeling to visualize the initial interactions between individual oligodendrocytes and their target axons in the developing zebra fish with the goal of understanding the regulation of myelin sheath formation.

There are considerable strengths to the manuscript. The work extends earlier studies through the use of high spatial and temporal resolution analysis. This approach reveals a highly dynamic interaction between oligodendrocyte processes and local axons that had not previously been appreciated. The data on the initial interactions between an individual oligodendrocyte and its target axons is closely analyzed, which reveals a number of interesting traits. For example, while dorsal cells have a higher number of initial axonal interactions and ultimately myelinate more axons than ventral cells, the proportion of initial interactions that lead to a myelin sheath is similar between the two populations. To begin to examine the molecular regulation of the initial oligodendrocyte and axon interactions and subsequent formation of myelin sheaths the authors perturb selective components of the endocytic pathway and provide evidence that disruption of Rab5 selectively affects the long-term stabilization of myelin sheaths.

While there are some new advances in the current manuscript, the significance of many of the observations is unclear. For example, while the data documents extensive interactions between oligodendrocytes and axons, the nature of those interactions is not well defined. The authors describe the loss of olig/axon interactions as "ensheathment destabilization" however, it is not clear from the data that they don't represent simple oligodendrocyte process retraction.

The different interactions of dorsal and ventral cells with their target axons is interesting and may reflect different oligodendrocyte populations or environments.

Reviewer #3 (Public Review):

Almedia and Macklin sought to characterize oligodendrocyte behavior at the earliest onset of myelination in the central nervous system. By sparsely labeling oligodendrocytes with transgenic fluorescent reporters in zebrafish larvae, they show that oligodendrocytes in the dorsal and ventral spinal cord have characteristic numbers of sheaths and sheath lengths. With impressive and technically laborious time-lapse imaging, they demonstrate that oligodendrocytes repetitively sample axon segments before stabilizing a nascent sheath, with most (~90%) immature sheaths failing to stabilize. They quantify differences in dorsal and ventral oligodendrocyte sampling and convincingly show that dorsal oligodendrocytes form more sheaths due to increased sampling relative to ventral, with similar rates of sheath retraction. Finally, the authors conclude that Rab5 and Rab11 promote myelination locally and cell-autonomously in oligodendrocytes, showing specifically that Rab5 is critical for stabilization of nascent sheaths but is dispensable for sampling. Altogether, the authors provide novel and detailed visualization of early myelin sheath development by oligodendrocytes.

Strengths:<br /> This is one of the first studies to closely examine early oligodendrocyte behavior at high resolution and adds to a body of work showing how oligodendrocytes initiate and maintain myelin sheaths. The authors find that sampling is widespread while most immature sheaths destabilize. This is an intriguing finding, as sampling is likely an energetically intensive process, but its prevalence in wild-type animals suggests that it is an important part of development.

The authors' claims are substantiated by technically challenging mosaic labeling experiments that monitored individual oligodendrocyte development over the course of days. Importantly, the authors have measured the sheath accumulation and loss phase for a single oligodendrocyte over the course of several days, and can pinpoint when individual sheaths are maintained with high resolution.

The imaging acquisition and data analyses are thorough, and the labor-intensive nature of the experiments is commendable. The authors carefully use statistics to validate their conclusions, including power analyses to determine appropriate sample size.

Limitations:<br /> Prior studies suggested that the potential for each oligodendrocyte to produce myelin sheaths is at least partially dependent upon the diameter of axons enwrapped. While axons are labeled to demonstrate ensheathment, axonal diameter is not measured, and it is unclear whether dorsal and ventral oligodendrocytes behavior could be explained by regional or individual differences in axon caliber.

Other recent studies suggest that early myelination is driven by axonal factors as much as oligodendrocyte-intrinsic factors. For instance, neuronal activity stabilizes myelination for a subset of early-born neuronal types. Because of the sparse labeling techniques and focus on oligodendrocyte behavior, it is unknown how or whether axonal subtypes and activity influence early oligodendrocyte sheath sampling and stabilization.

While the authors provide a tantalizing suggestion that early oligodendrocyte sampling primes axonal segments for myelination, it is not tested directly here. Thus, the paper does not address why, or even if, repeated sampling is important in development.

Reviewer #1 (Public Review):

In this manuscript, the authors investigate the genes involved in the retention of eggs in Aedes aegypti females. They do so by identifying two candidate genes that are differentially expressed across the different reproductive phases and also show that the transcripts of those two genes are present in ovaries and in the proteome. Overall, I think this is interesting and impressive work that characterizes the function of those two specific protein-coding genes thoroughly. I also really enjoyed the figures. Although they were a bit packed, the visuals made it easy to follow the authors' arguments. I have a few concerns and suggested changes, listed below.

1. These two genes/loci are definitely rapidly evolving. However, that does not automatically imply that positive selection has occurred in these genes. Clearly, you have demonstrated that these gene sequences might be important for fitness in Aedes aegypti. However, if these happen to be disordered proteins, then they would evolve rapidly, i.e., under fewer sequence constraints. In such a scenario, dN/dS values are likely to be high. Another possibility is that as these are expressed only in one tissue and most likely not expressed constitutively, they could be under relaxed constraints relative to all other genes in the genome. For instance, we know that average expression levels of protein-coding genes are highly correlated with their rate of molecular evolution (Drummond et al., 2005). Moreover, there have clearly been genome rearrangements and/or insertion/deletions in the studied gene sequences between closely-related species (as you have nicely shown), thus again dN/dS values will naturally be high. Thus, high values of dN/dS are neither surprising nor do they directly imply positive selection in this case. If the authors really want to investigate this further, they can use the McDonald Kreitman test (McDonald and Kreitman 1991) to ask if non-synonymous divergence is higher than expected. However, this test would require population-level data. Alternatively, the authors can simply discuss adaptation as a possibility along with the others suggested above. A discussion of alternative hypotheses is extremely important and must be clearly laid out.

2. The authors show that the two genes under study are important for the retention of viable eggs. However, as these genes are close to two other conserved genes (scratch and peritrophin-like gene), it is unclear to me how it is possible to rule out the contribution of the conserved genes to the same phenotype. Is it possible that the CRISPR deletion leads to the disruption of expression of one of the other important genes nearby (i.e., in a scratch or peritrophin-like gene) as the deleted region could have included a promoter region for instance, which is causing the phenotype you observe? Since all of these genes are so close to each other, it is possible that they are co-regulated and that tweedledee and tweedledum and expressed and translated along with the scratch and peritrophin-like gene. Do we know whether their expression patterns diverge and that scratch and peritrophin-like genes do not play a role in the retention of viable eggs?

References:<br /> Drummond DA, Bloom JD, Adami C, Wilke CO, Arnold FH. 2005. Why do highly expressed proteins evolve slowly? Proc Natl Acad Sci U S A. 102:14338-14343.

McDonald JH, Kreitman M. 1991. Adaptive protein evolution at the Adh locus in Drosophila. Nature. 351:652-654. doi: 10.1038/351652a0.

Reviewer #1 (Public Review):

The rice sensor NLR protein Pik-1 carries a HMA domain to sense fungal AVR proteins. Past studies have shown that it is possible to modify the HMA domain to change new recognition specificity. However, whether this approach can generate broad-spectrum NLRs that function in rice plants remains to be shown. Prior work from the authors have shown that each of the existing Pik-1 alleles only recognizes some, but not all AVR-Pik alleles. Interestingly, they found that a natural rice target protein HIPP19 is capable of binding to all known AVR-Pik proteins. In the current study, the authors tested the idea that AVR-Pik-binding sequence in HIPP19 could be utilized to engineer Pik-1 protein with broader recognition specificity. Strikingly, the engineered Pikp-1OsHIPP19-mbl7 is capable of recognizing AVR-PikD, C, and F, whereas the original Pikp-1 is only capable of recognizing Avr-PikD. This is supported by both HR-elicitation and protein-protein interactions in N. benthamiana plants. The authors further used a structure-guided approach to identify specific amino acids responsible for expanded recognition of AVR proteins. To this end, they show that the Pikp-1SNK-EKE variant is capable of recognizing all three of the aforementioned AVR-Pik proteins. The proper interactions of the newly introduced amino acids with the Avr-Pik proteins were nicely demonstrated with structural work. Most excitingly, the Pikp-1OsHIPP19-mbl7 and Pikp-1SNK-EKE constructs were introduced in to rice plants lacking Pik-1 as stable transgenes. These lines displayed disease resistance to rice blast strains carrying any of the three AVR-Pik proteins. Overall, the study is well executed and shows how knowledge of structural and evolutionary studies can help engineering disease resistance in a major crop plant. The weakness is with the use of a strong promoter to drive the expression of the engineered Pikp-1 variants in rice and a lack of assessment of potential effects on traits.

Reviewer #1 (Public Review):

This is an awesome comprehensive manuscript. Authors start by sorting putative stromal cell-containing BM non-hematopoietic (CD235a-/CD45-) plus additional CD271+/CD235a-/CD45- populations to identify nine individual stromal identities by scRNA-seq. The dual sorting strategy is a clever trick as it enriches for rare stromal (progenitor) cell signals but may suffer a certain bias towards CD271+ stromal progenitors. The lack of readable signatures already among CD45-/CD45- sorts might argue against this fear. This reviewer would appreciate a brief discussion on number & phenotype of putative additional MSSC phenotypes in light of the fact that the majority of 'blood lineage(s)'-negative scRNA-seq signatures identified blood cell progenitor identities (glycophorin A-negative & leukocyte common antigen-negative). The nine stromal cell entities share the CXCL12, VCAN, LEPR main signature. Perhaps the authors could speculate if future studies using VCAN or LEPR-based sort strategies could identify additional stromal progenitor identities?

The authors furthermore localized CD271+, CD81+ and NCAM/CD56+ cells in BM sections in situ. Finally, referring to the strong background of the group in HSC research, in silico prediction by CellPhoneDB identified a wide range of interactions between stromal cells and hematopoietic cells. Evidence for functional interdependence of FCU-F forming cells is completing the novel and more clear bone marrow stromal cell picture.<br /> An illustrative abstract naming the top9 stromal identities in their top4 clusters by their "top10 markers" + functions would be highly appreciated.

Reviewer #1 (Public Review):

The present study used an innovative meta-analytic approach to elucidate the functional organization of the lateral prefrontal cortex (LPFC). Co-activation profiles based upon over 14,000 fMRI studies revealed a principle rostral-caudal gradient in the LPFC, as well as a secondary dorsal-ventral gradient. Rostral-ventral zones in this gradient tended to contain areas in cognitive control (Control B) and salience networks and were associated with terms involving memory and affect. Caudal-dorsal zones in the gradient tended to contain areas in cognitive control (Control A) and spatial attention networks and were associated with terms involving perception and action. Areas in-between overlapped prominently with a variety of networks including Control A and were associated with various cognitive terms associated with language, working memory, and cognitive control. Moreover, the authors found hemispheric asymmetries with the left hemisphere associated with language-related topics and the right hemisphere with response inhibition and error processing. Hemispheric differences did not show an obvious rostral-caudal topography. Collectively, the data provide quantification of the general organization of the LPFC along rostral-caudal, dorsal-ventral, and hemispheric axes. From the associations of networks and terms, the authors conclude that the rostral-caudal axis reflects an internal/external axis, with areas in the middle supporting integrative processing.

Detailing the functional organization of the LPFC has remained a challenge given the diversity of its functions and widespread involvement across various tasks. Due to the limitations of single studies in terms of what can be measured (i.e. number of tasks used), construct validity of what is measured (e.g. purity of contrasts), and the reliability and reproducibility with which things can be measured, a meta-analysis of this scale can provide a welcome synthesis.

A major challenge with meta-analyses of fMRI data is obtaining appropriate specificity. Most meta-analytic methods that have been applied to fMRI data are both spatially and functionally coarse, which hinders efforts to properly synthesize the literature. Here, the authors employ innovative techniques to maximize specificity insofar as possible. As a result, the present data can be considered our best summary to date of the functional organization of the LPFC as detailed by fMRI.

Even as the study has innovated over previous attempts, limitations of meta-analyses must still be considered. Meta-analysis will never have the spatial resolution of well-performed individual studies. Indeed, the techniques used here may cause spatial blurring given the impression of spatially ordered consistency which may not actually be present. For example, there are data to suggest that there may be multiple rostral-caudal axes along the LPFC, which can potentially be blurred together into a single axis here. So, the spatial organization detailed here may offer a gross overall picture of how the LPFC is organized, but we will naturally get more fine-grained details from carefully conducted individual studies.

Nevertheless, the approach used here is helpful not only for detailing the functional organization of the LPFC, but as a proof-of-concept that can be applied to future investigations. These techniques may be helpful for detailing the organization of other heteromodal zones of the brain such as the medial frontal wall, and parietal cortices, offering a means of distilling the thousands of fMRI studies that have been conducted into a comprehensive whole.

Reviewer #1 (Public Review):

Oppong and colleagues present a study on the association of mitochondrial DNA abundance in blood and personality traits, both of which have been linked to morbidity and mortality in aging populations. They found that mtDNAcn is negatively associated with traits related to neuroticism as well as positively with a higher personality-mortality index (PMI). The association of the PMI with mortality was attenuated by including mtDNAcn in the model, indicating that the association is mediated by mitochondrial abundance in blood.

General comments:<br /> • Previous studies have shown that mtDNAcn are potentially mediated by hormonal levels and thus menopause. Given the mean age of 57 in the SardiNIA cohort, the authors should investigate in more detail the potential confounding effects of menopause in women.<br /> • The only personality trait (out of the big five) available in the UK Biobank is neuroticism. Since the authors found that most of their associations are significant for this complex, I would strongly suggest they try to replicate their findings in patients from the UK Biobank which have both, genome-wide sequencing data as well the summary score of neuroticism (Data-Field 20127)<br /> • The amount of mtDNA varies across populations and across different haplogroups. The authors should therefore compute the major haplogroups present in Europeans and adjust/account for those variables in the correlation and mortality analyses.

Reviewer #1 (Public Review):

Liu et. al. applied an existing method to study the subtypes of CRC from a network perspective. In the proposed framework, the authors calculated the perturbation of expression-rank differences of predefined network edges in both tumor and normal samples. By clustering the derived perturbation scores in CRC tumors using publicly available gene expression datasets, they reported six subtypes (referred to as GINS 1-6) and then focused on the association of each subtype with clinical features and known molecular mechanisms and cell phenotypes. My recommendation is major revision.

Major concerns:

(1) While this study originates from the network-perspective, it is unclear to me if the new subtypes provide key novel insights into the gene regulatory mechanisms for the development of CRC. For example, the "Biological peculiarities of six subtypes" section is descriptive and lacks a punch point.

(2) To further demonstrate the novelty of the identified subtypes, the authors need to show the additional benefit of the GINS1-6 to patient stratification derived from existing methods, such as integrative clustering based on multiple genomic evidence (copy number alterations, gene expression and somatic mutations).

Reviewer #3 (Public Review):

The authors have constructed a large-scale interaction perturbation network from 2,167 CRC tissues and 308 normal tissues, deciphering six GINS subtypes with particular clinical and molecular peculiarities. In addition, the GINS taxonomy was rigorously validated in 19 external datasets (n =3,420) with distinct conditions. From an interactome perspective, this study identified and diversely validated a high-resolution classification system, which could confidently serve as an ideal tool for optimizing decision-making for CRC patients. The multifariously biological and clinical peculiarities of GINS taxonomy improve the understanding of CRC heterogeneity and facilitate clinical stratification and individuation management. Additionally, candidate specific-subtype agents provide more targeted or combined interventions for six subtypes, which also need to be validated in clinical settings.

Reviewer #1 (Public Review):

The hippo signaling pathway has emerged as a key signaling pathway in cancer and many other diseases, but there is a lack of high-quality chemical tools that would enable functional studies. The developed chemical probe targeting TEAD is therefore a much-needed chemical tool enabling more functional studies on this pathway in diverse diseases. The chemical MYF-03-69 is comprehensively characterized and it, therefore, represents a high-quality probe for future studies.

Reviewer #1 (Public Review):

The manuscript "BRCA2 BRC missense variants disrupt RAD51-dependent DNA repair" by Jimenez-Sainz et al focuses on the characterization of three BRCA2 mutants that were previously classified as Variants of Uncertain Significance (VUS) with unknown functional consequences. Mutations in the BRCA2 tumor suppressor gene predispose to breast, ovarian, pancreatic, prostate, and other cancers and are responsible for nearly half of all hereditary breast cancers and ovarian cancers. Identification of truly pathogenic BRCA2 missense mutations is a challenging but very important task for early cancer diagnostics. In this study, the authors developed a methodology for the identification of pathogenic BRCA2 mutations. They performed comprehensive analyses of three BRCA2 mutations including S1221P and T1980I, which map to conserved residues in the BRC2 and BRC7 repeats, and T1346I, located within the spacer region between BRC2 and BRC3 repeats. Using an impressive array of cellular and biochemical approaches they demonstrated that the first two BRCA2 mutants have a detrimental effect on RAD52-dependent DNA repair, and therefore likely to be pathogenic. In contrast, T1980I seems to have no effect on DNA repair in various tested assays and is likely to be a passenger mutation.

Overall, I found the presented study of high quality. The developed methodology can be applied for analyses of other potentially pathogenic mutations in BRCA1, BRCA2, or other genes involved in DNA double-strand break repair. The work may have a broad impact on the biomedical field. The presentation quality is good as well.

Reviewer #3 (Public Review):

In this report, the authors examined 3 mutations in the BRC-repeat region of BRCA2 in a series of functional assays. They found that two of the mutants showed severe defects in BRCA2 function, whereas the third mutant had no clear phenotype. The two mutants with functional defects are tested most thoroughly. The assays used here a numerous and have been validated and performed with appropriate controls and statistics. There are no concerns about the experiments themselves or the conclusions. So, the strength of the study is the number of assays performed in a rigorous manner.

However, the weakness of the study is that it is unclear why these results are impactful. Several reports over the years, including some recent studies mentioned at the end of the Discussion, have involved parallel functional analysis of hundreds of alleles of BRCA2, with a clear end goal of improving medical decision-making for carriers of these BRCA2 alleles. Certainly, these studies have usually focused on other domains of BRCA2, like the DNA binding domain, but nonetheless, since these studies have typically involved testing hundreds of BRCA2 alleles, it is unclear how this manuscript studying 3 alleles fits into a broader population science effort to categorize BRCA2 variants of unknown significance (VUS). Perhaps the authors would argue that their study involves a comprehensive analysis of the 3 alleles, whereas other studies typically involve one or two functional assays. However, if that is the case, then is the argument that multiple assays are needed for accurate characterization of VUS? If so, what is the evidence for that assertion? Are there particular assays that are more likely to be predictive of pathogenicity based on their analysis?

The mechanistic insight of the study is also unclear. These alleles are in conserved residues of the BRCA2 BRC repeats, which have been established as being important for BRCA2 function. Indeed, in the Discussion, it appears that the findings here are largely confirmatory for other mechanistic studies of the BRC repeats of BRCA2. What new information has been determined about the role of the BRC2 and BRC7 repeats from this study?

Reviewer #1 (Public Review):

In this manuscript the authors found a direct synaptic connection between inhibitory neurons in the central nucleus of the amygdala and inhibitory and other neurons in the zona incerta. They conducted a rigorous and detailed anatomical study of both the anterograde and retrograde connections between PKCdelta CeA neurons and the zona incerta. Furthermore they conducted rigorous chemogenetic investigation of the zona incerta inhibitory neurons across pain modalities. This led to the overall conclusion that PKCdelta neurons inhibit zona incerta inhibitory neurons leading to enhanced pain processing. While the results mainly support the conclusions, there is a lack of direct support for the CeA-PKCdelta-->vGAT-ZI hypothesis.

Reviewer #3 (Public Review):

This study was designed to test the hypothesis that output from a subpopulation of neurons (PKCδ neurons) in the central nucleus of the amygdala (CeA) inhibits ZI neurons in a neuropathic pain condition and this ZI inhibition results in pain-related behaviors (Fig. 5).

First, the targets of CeA-PKCδ neurons were identified using cre-dependent viral vector for anterograde labeling with red-shifted channelrhodopsin (CrimsonR-tdTomato) or mCherry, and cholera toxin B (CTB) in PKCδ-tdTomato mice for retrograde labeling. The ZI was identified as one of the targets with approximately 19% of CTB+ CeA neurons identified as PKCδ- tdTomato positive, which is significant and makes this pathway worth exploring.

Next, electrophysiological (patch-clamp) studies showed monosynaptic inhibitory transmission from CeA to both VGAT+ and VGAT- neurons of the ZI and found no significant difference between these projections (from CeA to GABAergic or non-GABAergic ZI neurons).

Finally, chemogenetics are used to activate or silence GABAergic ZI neurons and determine behavioral consequences. Inhibition of GABAergic ZI neurons induced hypersensitivity in naïve mice and activation of these neurons reversed hypersensitivity in a neuropathic pain model. Interestingly, these effects were modality specific.

The combination of tracing techniques, electrophysiology, chemogenetics and behavior is a strength of this study, and so this the impressive amount of high-quality data. The focus on CeA-PKCδ neurons in the modulation of ZI is an important novelty of the present study.

However, slice physiology and behavioral data presented here do not actually link CeA-PKCδ neurons to ZI. Electrophysiological data show inhibitory transmission from CeA to ZI, but not specifically from CeA-PKCδ neurons to ZI. Behavioral studies assess the effects of modulation of ZI neurons but not of CeA-PKCδ to ZI projections. Previous data already showed the effects of activation and inhibition of GABAergic ZI neurons on pain behaviors, including in a neuropathic pain model.

Therefore, although the proposed model of CeA-PKCδ to ZI interactions in pain (Fig. 5) is novel and significant, additional experiments focusing on CeA-PKCδ neurons and their ZI projections would be needed to fully support this concept and enhance impact of the work.

Reviewer #1 (Public Review):

The authors use both genome-wide correlations between genetic effects on metabolite pairs ('genetic correlation') and the pleiotropic effects of individual genetic variants to build an understanding of how biochemical pathways relate to global ('genetic correlation') and local (individual variant or pathway) pleiotropy. The authors look at metabolites, which are themselves interesting and predictive of metabolic health, but also serve as a useful 'model system' for understanding genetic correlation.

The authors demonstrate that genetic variants that have 'discordant' effects on a pair of metabolites, i.e. effects whose product of signs is opposite to the sign of the genome-wide genetic correlation, tend to be variants (likely) affecting pathway-relevant enzyme or transporter genes and/or affect biochemical pathways 'between' the two metabolites.

The authors attempt to extend this further to a variant associated with coronary artery disease (CAD), which they hypothesize to act by decreasing the activity of the gene PCCB. While an interesting hypothesis, establishing such a mechanism in the etiology of CAD would require further validation.

This paper represents an advance in linking statistical genetics constructs such as 'genetic correlation' to a biochemical mechanism for an important case: metabolites. While I expect their approach to be influential in showing how to dissect genetic correlation in a way that can point to the biological mechanism, extending their method to more complex phenotypes with less well-characterized biochemical pathways may be challenging.

Reviewer #3 (Public Review):

The authors have used both overall and local genetic correlations to understand how genes associated with two traits relate to those same traits. Their work focuses on understanding why in some cases local genetic correlations may disagree with overall correlation in terms of the direction of effect and exploit known biology to understand why and when this arises.

Overall the work is solid methodologically as it relies on well-established statistical methods and known biology. I don't see particular weaknesses in this work limited to the presented examples. It remains unclear how these observations will generalise to other less well-known biology or traits, but this is a matter of future work.

The work is in my opinion highly impactable as it creates a framework to be used to investigate the pleiotropic effects of genes and could help understand their biological role.

Reviewer #1 (Public Review):

In this study, the authors aim to analyze the functions of the motor subunit klc4 in nervous system development and function. This is an important question to address, as not much is known about the cellular functions of klc4 even though mutations in this gene cause early onset hereditary spastic paraplegia in human. The authors used CRISPR/Cas9 to generate a klc4 mutant in zebrafish and analyzed the development of sensory neurons in embryos as well as behavior in adults. The strengths of this study include the generation of a novel klc4 mutant in zebrafish, the use of high and super-resolution live microscopy over time coupled to a rigorous analysis to reveal unsuspected developmental defects in klc4 mutants, including the formation of aberrant projections by sensory neurons and an abnormal development of peripheral sensory axons that appear less branched and fail to repel each other. The behavioral assays conducted by the authors also yielded robust results supporting a role for klc4 in adult neural circuits regulating stress response. The data are very well quantified and support the key findings of the study. Although the study does not delineate the molecular mechanisms causing an abnormal development of sensory neurons, its findings have a high impact, as they suggest specific functions of Klcs in neuronal patterning and compartimentalization and identify klc4 as a novel gene associated with anxiety behavior.

Reviewer #3 (Public Review):

This study reports on the phenotypes of a CRISPR-engineered zebrafish mutants in kinesin light chain 4 (KLC4). KLC4 is expressed prominently in spinal cord sensory neurons, and mutants have defects in peripheral axon branching/stabilization and branch repulsion, as well as make occasional ectopic axon branches. Imaging also demonstrates that axonal microtubule growth dynamics are altered. These axonal phenotypes are nicely characterized with beautiful light sheet time-lapse microscopy and clever image analyses methods. Additionally, the growth of adult KLC4 mutants is stunted, and they exhibit a variety of behavioral defects.

The strengths of this paper are the creation of a new mutant for studying axonal transport, the impressive imaging methods, and the development of image analysis methods for characterizing axonal trajectories across a population.

The main weaknesses is the lack of a specific mechanistic explanation for how kinesin dysfunction leads to axonal defects-what kinesin cargoes play a role in branch stabilization and branch repulsion? How does kinesin-mediate transport affect microtubule growth?

Another weakness is the lack of a connection between the cellular defects characterized in larval sensory neurons, and the behavioral defects in adults. Since the adult behavioral defects likely do not involve sensory neurons, these two parts of the paper don't fit together. The authors may want to consider moving the behavior to a different paper. Additionally, the cellular basis of the adult behavioral defects is unknown, and likely involves a complex combination of defects in multiple cell types.

Reviewer #1 (Public Review):

In the manuscript "Airway Basal Cells Show Regionally Distinct Potential to Undergo Metaplastic Differentiation" by Yizhou, Yang et al., the authors take an unbiased approach to interrogate basal cell heterogeneity in the trachea. Their single-cell RNA-seq data suggests that several sub-populations of basal cells exist. Follow-up studies support the conclusion that two major basal cell populations exist corresponding to the dorsal and ventral trachea. Strikingly, their functional data also supports that the microenvironment of the dorsal or ventral trachea, being surrounded by smooth muscle or cartilage respectively, and that loss of cartilage leads to aberrant patterning of BC1 and BC2. Overall, this is an interesting study with reasonable conclusions that are supported by the data, and, the data is clear and of high quality. One point that requires further discussion pertains to the KRT13 expression following injury, and whether calling KRT13 activation "aberrant" is appropriate if it is simply a part of the natural repair process.

Reviewer #3 (Public Review):

In this manuscript, Zhou et al describe basal cell heterogeneity in the mouse trachea. They describe how dorsally vs ventrally located tracheal basal cells which are supported by different stromal cell populations show differential potential to undergo squamous metaplastic differentiation. Furthermore, they suggest that the differences in these basal cells might be epigenetically programmed as they are maintained after these basal cells have been isolated and cultured in vitro. However, it is not clear whether dorsal vs ventral supporting stromal cell populations made it into the culture medium.

https://www.rayyan.ai/

Agarwal, Pooja K., Ludmila D. Nunes, and Janell R. Blunt. “Retrieval Practice Consistently Benefits Student Learning: A Systematic Review of Applied Research in Schools and Classrooms.” Educational Psychology Review 33, no. 4 (December 1, 2021): 1409–53. https://doi.org/10.1007/s10648-021-09595-9

Yolanda Gibb: How a mindset of Ambidextrous Creativity can get you generating AND exploiting your ideas?

https://lu.ma/poo355tg

Ambidextrous creativity is having a balance between exploration and subsequent exploitation of those explorations.

Small companies and individuals are good at exploration, but often less good at exploitation.

Triple loop learning<br /> this would visually form a spiral (versus overlap)<br /> - Single loop learning: doing things right (correcting mistakes)<br /> - double loop learning: doing the right things (causality)<br /> - triple loop learning: why these systems and processes (learning to learn)

Assets<br /> Relational capital * Structural capital - pkm is part of this<br /> there's value in a well structured PKM for a particualr thing as it's been used and tested over time; this is one of the issues with LYT or Second Brain (PARA, et al.) how well-tested are these? How well designed?<br /> * Structural capital is the part that stays at the office when all the people have gone home * Human Capital

Eleanor Konik

4 Es of cognition<br /> * embodied * embedded * enacted * extended<br /> by way of extra-cranial processes

see: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7250653/

Yolanda Gibb's book<br /> Entrepreneurship, Neurodiversity & Gender: Exploring Opportunities for Enterprise and Self-employment As Pathways to Fulfilling Lives https://www.amazon.com/Entrepreneurship-Neurodiversity-Gender-Opportunities-Self-employment/dp/1800430582

Tools: - Ryyan - for literature searches - NVIVO - Obsidian - many others including getting out into one's environment

NVIVO<br /> https://www.qsrinternational.com/nvivo-qualitative-data-analysis-software/home

a software program used for qualitative and mixed-methods research. Specifically, it is used for the analysis of unstructured text, audio, video, and image data, including (but not limited to) interviews, focus groups, surveys, social media, and journal articles.

Ryyan<br /> https://www.rayyan.ai/<br /> for organizing, managing, and accelerating collaborative literature reviews

Reviewer #1 (Public Review):

The present manuscript offers valuable transcriptomic data sets of manually picked adult zebrafish photoreceptors from dissociated retinas of different transgenic lines, in which rods and cones (UV, S, L, M) were marked by the fluorescent reporter proteins. This is a very valuable approach because allows for selecting "healthy cells". Whether the approach is comparable to single-cell RNA-seq as the authors do (see page 3 and discussion) is however questionable as each of their samples is composed of 20 cells.

The authors further focused on transcription factors that are differentially expressed in the five photoreceptors cell types that they analyze, identifying a large number of them with still unidentified functions. This is very valuable information. However, the idea that this analysis will help to identify new TF involved in the specification of the photoreceptors (as stressed in the title) is at odds with the experimental setup. The authors have analyzed adult photoreceptors and thus by definition cells that had been already specified. Many of the TF involved in the specification may no longer be expressed. The analysis rather offers a list of TFs that are involved in photoreceptor homeostasis, some of which had been also involved in their specification. Proof of this is the fact that none of the four TFs of yet uncharacterized function (Skor1a, Sall1a, Lrrfip1a, and Xbp1) turned out to be involved in photoreceptor specification. The F0 screen only confirmed factors that were already known to be involved in cell specification and that in adult photoreceptors likely play a different role.

The authors further investigate the activity of the two tbx2 zebrafish paralogues in photoreceptors' specification, showing a novel role for tbx2 in the repression of different opsin in specific photoreceptor cell types. This is an interesting finding, however, it is overinterpreted by the authors. Indeed, tbx2 cannot be considered as a "master regulator of photoreceptor fate" (page 7) but, at best, a TF is required to control an appropriate proportion of the different photoreceptors' subtypes.

Overall this is an interesting and well-performed study with valuable information. The conceptual framework of the study should however be re-elaborated, further avoiding overinterpretations.

Reviewer #3 (Public Review):

Angueyra et al. tried to establish the method to identify key factors regulating fate decisions in the retinal visual photoreceptor cells by combining transcriptomic and fast genome editing approaches. First, they isolated and pooled five subtypes of photoreceptor cells from the transgenic lines in each of which a specific subtype of photoreceptor cells are labeled by fluorescence protein, and then subjected them to RNAseq analyses. Second, by comparing the transcriptome data, they extracted the list of the transcription factor genes enriched in the pooled samples. Third, they applied CRISPR-based F0 knockout to functionally identify transcription factor genes involved in cell fate decisions of photoreceptor subtypes. To benchmark this approach, they initially targeted foxq2 and nr2e3 genes, which have been previously shown to regulate S-opsin expression and S-cone cell fate (foxq2) and to regulate rhodopsin expression and rod fate (nr2e3). They then targeted other transcription factor genes in the candidate list and found that tbx2a and tbx2b are independently required for UV-cone specification. They also found that tbx2a expressed in the L-cone subtype and tbx2b expressed in L-cones inhibit M-opsin gene expression in the respective cone subtypes. From these data, the authors concluded that the transcription factors Tbx2a and Tbx2b play a central role in controlling the identity of all photoreceptor subtypes within the retina.

Overall, the contents of this manuscript are well organized and technically sound. The authors presented convincing data, and carefully analyzed and interpreted them. It includes an evaluation of the presented data on cell-type specific transcriptome by comparing it with previously published ones. I think the current transcriptomic data will be a valuable platform to identify the genes regulating cell-type specific functions, especially in combination with the fast CRISPR-based in vivo screening methods provided here. I hope that the following points would be helpful for the authors to improve the manuscript appropriately.

1) The manuscript uses the word "FØ" quite often without any proper definition. I wonder how "Ø" should be pronounced - zero or phi? This word is not common and has not been used in previous publications. I feel the phrase "F0 knockout", which was used in the paper cited by the authors (Kroll et al 2021), is more straightforward. If it is to be used in the manuscript, please define "FØ" and "CRISPR-FØ screening" appropriately, especially in the abstract.

2) Figure 1-supplement 1 shows that opn1mw4 has quite high (normalized) FPKM in one of the S-cone samples in contrast to the least (or no) expression in the M-cone samples, in which opn1mw4 is expected to be detected. The authors should address a possible origin of this inconsistent result for opn1mw4 expression as well as a technical limitation of using the Tg(opn1mw2:egfp) line for detection of opn1mw4 expression in the GFP-positive cells.

3) The manuscript lacks a description of the sampling time point. It is well known that many genes are expressed with daily (or circadian) fluctuation (cf. Doherty & Kay, 2010 Annu. Rev. Genet.). For example, the cone-specific gene list in Fig.2C includes a circadian clock gene, per3, whose expression was reported to fluctuate in a circadian manner in many tissues of zebrafish including the retina (Kaneko et al. 2006 PNAS). It appears to be cone-specific at this time point of sample collection as shown in Fig.2, but might be expressed in a different pattern at other time points (eg, rod expression). The authors should add, at least, a clear description of the sampling time points so as to make their data more informative.

Reviewer #1 (Public Review):

Kim and coauthors have performed multiple simultaneous whole cell recordings in living slices of human neocortex obtained from neurosurgical resection in order to study the properties of synaptic connections from excitatory pyramidal neurons onto various types of inhibitory interneurons. Strengths of the study include the unique ability to study biophysical properties of human synapses, and the sophisticated in situ hybridization and other approaches used to identify the class of the postsynaptic interneurons. The main finding of the study is that a key principle identified in rodent neocortex: that fast-spiking parvalbumin-positive neurons receive initially depressing synapses, whereas other categories of interneurons receive more initially facilitating synapses, is conserved in the human. The authors also make important technical contributions to our ability to study synapses in human tissue including a slice culture technique that prolongs the use of these valuable samples, and a multi-pronged approach to characterizing interneuron identity. The main weaknesses of the current version of the manuscript relate to incomplete analyses and a somewhat confusing presentation that leave in question the relative importance of interneuron identity vs. other factors in determining the degree of synaptic facilitation and depression.

Reviewer #1 (Public Review):

Ugrankar et al provide an interesting article exploring the impact of the actin network in adipocyte cell size and nutrient uptake. The manuscript is well written and presents gaps in current knowledge well. The authors use Drosophila to address their research questions, describing a specific isoform of actin, Actin 5C, as the critical mediator of lipid metabolism in the larval fat body. In support, they show that loss of a mediator of actin dynamics, twinfilin, can have similar impacts as actin 5C loss. The authors further probe for impacts of additional cytoskeletal proteins, spectrins, in this process, concluding that spectrin activity differs from Actin 5C. Last, the authors attempt to explore how actin network in the fat body impacts nutrient uptake in multiple ways. Overall, this is an interesting study that sheds light on adipocyte cytoskeletal dynamics. However, there are a number of concerns, including: a need to validate the many RNAi used, the need to add data to rule out a potential contribution from other actin isoforms, further characterization of the assays used to address nutrient uptake, and further validation of the data used to argue that actin 5C is not essential during embryogenesis.

Reviewer #1 (Public Review):

This study has some neat technological features that go a long way to reconcile contradictory data regarding functions of disease associated PTPN22 variants. These include:<br /> • Crispr/Cas9 gene editing of exon 14 of PTPN22 in primary human T cells to generate HDR for WT, and gene editing for risk and KO sequences<br /> • Use of cord blood T cells, mitigating against any variability in T cell responses that could be influenced by activation or differentiation state<br /> • Lentiviral infection of these T cells with high and low avidity TCRs that recognise the same peptide from the islet cell autoantigen IGRP, presented by HLA-DRB1*0401; the TCRs are chimeric, allowing detection of LV transgene and detection of TCRs that have not cross-paired with endogenous TCR chains<br /> • Cis-linked GFP to detect those T cells expressing TCR transgenes. Infection is undertaken using titres of virus likely to avoid high copy number TCRs and therefore variable TCR expression<br /> • Repeat experiments using multiple donors<br /> • TCR stimulations using a range of different readouts

The main findings and things to look out for are:<br /> • The HDR editing process leads to reduced expression of PTPN22 when compared to unedited/mock edited wild type T cells; thresholds of signalling are therefore different. But this is ok because expression of phosphatase in edited wild type and risk variants is equivalent, albeit at lower levels (Fig 1).<br /> • The technology inevitably leads to hemizygosity with biallelic editing events, and this needs to be born in mind when considering the homogeneity of T cell populations<br /> • The impact of the PTPN22 risk variant or phosphatase deficiency is uncovered under conditions of lower avidity/low signal strength, where loss of negative regulation leads to increased proliferation and cytokine production (IFN or IL-2)<br /> • Consistent with this PTPN22 regulates responses of T cells expressing low avidity L-TCR, but not high avidity H-TCR<br /> • Thus, the risk variant mimics the knockout, to a large extent

Additional things/experiments that might strengthen the study:<br /> • The claims of the authors might be further substantiated if they extended the range of T cell stimulatory readouts eg different cell surface markers such PD-1, OX-40, 41BB, ICOS, GPR56, whose expression is linked to TCR signalling thresholds<br /> • Additional signalling experiments such as phospho-flow using phospho-Erk specific antibodies would be a bonus; I worry a bit about only showing pS6 data<br /> • Repeat the experiments comparing wild type and ko T cells and study cytokine expression eg IFNg in non-risk edited and risk edited T cells. As it stands the only data we see comparing these genotypes is proliferation.

Reviewer #3 (Public Review):

This work is important for understanding both how immune cells are regulated and how alterations in receptor signaling can affect the balance of health and development of autoimmune diseases. The work uses CRISPR-based genetic manipulation of the autoimmunity associated PTPN22 gene in single donor human cord-derived naïve T cells to analyze T-cell receptor functions. The authors conclude that the autoimmunity associated PTPN22 variant PTPN22(620W) is a loss-of-function mutant as T cells expressing PTPN22(620W) phenocopies PTPN22 deficient T cells. The use of a single donor minimizes potential other effects that would be observed when comparison cellular functions from multiple donors.

Reviewer #1 (Public Review):

The authors aimed at explaining the origin of the persistent activity observed in neural populations recorded from larval zebrafish, its dependence on the temperature of the water the fish was immersed in, and the effects of visual stimulation. They deploy a popular data-driven model to capture the statistical structure of large neural populations, fitting a maximum entropy model (Ising model) to the average activity and pairwise correlation of recorded neurons. Using mean field methods, they reduce this high-dimensional model to two dimensions, describing the average activities of populations in the left and right hemispheres. Both the high and low dimensional models are capable of generating the long timescale of persistent activity, even though they were only trained to learn the static mean and pairwise correlation structure. The crucial theoretical insight is that this long timescale emerges from the energy landscape of the reduced model in terms of stochastic transitions between metastable attractors following the well known Arrhenius law. The height of the barriers separating the attractors is modulated by water temperature, explaining the change in transition times and persistent activity. The model can also explain the dependence of persistent activity on the water temperature.

The major strength of the present work is that, by using a simple and well motivated statistical model (maximum entropy model) based on minimal assumptions, the authors are able to quantitatively reproduce complex spatiotemporal effects of fish behavior. The authors explain why this is the case due to the emergence of metastable dynamics based on stochastic transitions between local minima of the free energy. This classic model is very easily interpretable and of wide appeal for the neuroscience and larger life science community.

In my opinion, the current manuscript has three main weaknesses. The first one is that the model fit and its comparison to the data is not cross-validated and thus likely affected by overfitting. I strongly recommend recasting all results in terms of comparison of cross-validated observables. The second weakness is the fact that it is not explained how the water temperature appears in the model, which is the central quantity whose dependence they aim to model. There is a significant confusion on issues of water temperature vs. temperature in the model Gibbs measure. The author should make sure this point gets clarified. The third weakness is that, although the authors claim that the sign of the difference between the mean population activities of left and right hemispheres is the observables that determines whether the fish is going to change swimming directions, they don't actually provide direct evidence for this, but only compare the statistical distribution of this observable with the behavioral distribution. I recommend the authors explicitly test the predictive nature of the neural observable by showing that changes in swim directions are temporally aligned to the onset of a sign change.

If the results still stand after applying cross-validation, which I believe is a quite likely outcome, I believe this manuscript will have a strong impact in the field since they demonstrated the power of a principled and well-known approach in capturing complex spatiotemporal activity of large neural populations. This work has the potential to be widely adopted and generalized to many different directions in systems neuroscience and beyond.

Reviewer #1 (Public Review):

Carlos Serpa et al., build on prior work from their laboratory showing that the rat ventrolateral orbitofrontal cortex (OFC) is not involved in goal-directed action control per se, but is involved in the updating of such actions. Here they demonstrated that noradrenergic but not dopaminergic inputs within the OFC (and not the medial PFC) are necessary for action-updating in this manner. The conclusions are well supported by the data. Overall this is an excellent manuscript with many strengths and few weaknesses.

Strengths are as follows:<br /> 1. The manuscript is written beautifully<br /> 2. The rationale for the study is clear.<br /> 3. The data are mostly very solid. All the claims are statistically supported, not only by pairwise comparison statistics but also interactions. This is very important in ensuring robustness and replicability of effects.

Weaknesses<br /> 1. There are no major weaknesses. As a minor point, a clearer demonstration of precise anatomical placements would be helpful as the function of the OFC (and the medial PFC) can differ significantly with even small alterations in placement.

I think these data will be of interest to neuroscientists and possibly psychopharmacologists. It may also be of interest to researchers in other fields, such as clinicians, although it doesn't have extremely clear health implications, so clinician interest could be limited.

Reviewer #3 (Public Review):

At the heart of this manuscript is a debate concerning the role of the orbitofrontal cortex (OFC) in goal-directed behavior. One commonly sees a paper in which Ostlund and Balleine placed large OFC lesions in behaviorally-experienced rats cited as irrefutable evidence that OFC is not involved in goal-directed behavior because these rats could perform typically in a simple devaluation task. Meanwhile, others have argued that the ventrolateral OFC (VLO) sits at a nexus between the medial PFC structures (which are attuned to reinforcer value, etc.) and the far lateral regions (which appear to be more specialized in Pavlovian associations) and may therefore play a role in goal-directed behavior (e.g., this argument is put forward in Gourley and Taylor, 2016, Nature Neuroscience). The present team published a crucial manuscript a couple of years ago showing that selective VLO lesions do indeed disrupt goal-seeking behaviors, particularly when value and contingency information needs to be integrated and/or updated (Parkes 2018). Because this sophisticated process is not tested in simple devaluation assays, it would have been missed in the older study. The Parkes 2018 paper, meanwhile, supports other investigations that also selectively manipulate the VLO and require animals to integrate new information into existing instrumental response strategies.

Here, the team first depleted NE fibers in the OFC and found that rats were unable to encode new associations in an instrumental reversal. This same deficit was not observed with parallel DA manipulation. They found that LC-OFC and not mPFC projections had the same effect. Throughout, important control experiments were conducted, and the tools being used were largely well-validated. The conclusions are sensible, and the writing is clear.

I would be curious about the authors' thoughts regarding the recent Duan ... Robbins Neuron paper (https://pubmed.ncbi.nlm.nih.gov/34171290/), in which marmosets displayed paradoxical responses to VLO inactivation and stimulation in contingency degradation tasks. Are there ways to reconcile these reports?

Reviewer #1 (Public Review):

The manuscript describes changes in single cell RNA sequencing signatures of dorsal root ganglion neurons over the development of neuropathic pain in the murine chronic constriction injury (CCI) model. Bioinformatic algorithms were employed to cluster neurons into sub-classes described previously, based on transcriptomic signatures. The authors report emergence of 4 new clusters, resulting from loss of cellular identity of neurons in known clusters and induction of inflammatory and hyperexcitability-associated genes. Moreover, they segregated neurons between injured and uninjured subclasses and observed induction of genes in both categories as well as differences between these categories. Some injured neurons maintained cellular identity. conversely, non-injured neurons were also found to show significant transcriptional plasticity in clusters with a prominent role in pain sensitivity. Sexual dimorphism was noted, particularly with respect to the c-LTMR class of sensory neurons.

The results of the current study are interesting, and the study is very well-performed. The fact that fluorescently labelled DRG neurons were employed here is an advantage since it led to lower representation of non-neuronal genes and better representation of neuronal genes expressed at low levels. However, it is largely descriptive and the level of advance beyond recent single cell transcriptomics studies on DRG neurons as well as older studies on bulk sequencing in models of neuropathic pain is debatable.

Reviewer #1 (Public Review):

This study analyzes the R-ISS-related plasma cell (PC) heterogeneity by 10X Genomics ScRNA sequencing and identified the two subsets of PCs(GZMA+ cytotoxic PCs and proliferating PCs). Three R-ISS-dependent gene modules in cytotoxic CD8+ T and NKT cells were also functionally analyzed. Potential immuno cell-cell communication such as SIRPA-CD47 and TIGIT-NECTIN3 were explored for the potential immunotargets which is an important direction for treating R/R MM. The work holds a promising way to study the drug resistance of R/R myeloma. However, the cost and complexity of the experimental method make it difficult to be widely used.

Reviewer #3 (Public Review):

The authors constructed a single-cell transcriptome atlas of bone marrow in normal and R-ISS-staged MM patients. A group of malignant PC populations with high proliferation capability (proliferating PCs) was identified. Some intercellular ligand receptors and potential immunotargets such as SIRPA-CD47 and TIGIT-NECTIN3 were discovered by cell-cell communication. A small set of GZMA+ cytotoxic PCs was reported and validated using public data.

For scRNA-seq data analysis, the authors did QC and filtering and removed low quality cells, including some doublets and followed by batch effect correction. Malignant PC populations were identified using the copy number analysis tool - "inferCNV".

The authors have done lots of analysis. But I think the results can be improved if they can do more analyses. I would recommend to 1) analyze doublets; 2) remove cell cycle effect; 3) GO and pathway analysis for genes with copy number change; 4) do cell-cell communication with more cell type/clusters.

Data analysis of public data was sufficient to prove the small set of GZMA+ cytotoxic PCs. More data analysis or wet experiment proof is required.

Reviewer #1 (Public Review):

SRSF6 is an understudied SR family member, best characterized for its role in controlling alternative splicing. Through comparative RNA-Seq analysis, the authors find that knockdown of SRSF6 results in a markedly different gene expression program than other SR proteins tested in that SRSF6 depletion leads to a dramatic increase in expression of interferon responsive genes (ISGs) and a downregulation of mitochondrial related genes. Given this correlation the authors explore the possibility that loss of SRSF6 leads to mitochondrial damage, which releases dsDNA to trigger the innate immune response through the DNA-sensor cGAS. They further propose that mitochondrial damage is due to a change in splicing of the gene BAX. The data shown in the manuscript are consistent with these conclusions, however do not rule out additional mechanisms. In particular, the mitochondrial and BAX phenotypes are much less dramatic than the interferon response. Moreover, the authors do not show that the change in BAX splicing induced by loss of SRSF6 is sufficient to lead to a change in ISG expression.

Reviewer #3 (Public Review):

The authors identified a splicing factor that regulates mitochondrial homeostasis by regulating the alternative splicing of the pro-apoptotic protein BAX, which induces basal upregulation of interferon stimulated genes and sensitizes cells to apoptotic cell death. They report that loss of Serine/Arginine Rich Splicing factor 6 (SRSF6) results in accumulation of an alternatively spliced form of BAX known as BAX-, which results in increased release of mitochondrial DNA (mtDNA). The released mtDNA is sensed by cGAS, which leads to upregulation of interferon stimulated genes via IRF3. Importantly, the increase in BAX- sensitizes macrophages to apoptosis and various pathogens decreased the expression of SRSF6 during infection, which served a protective role. Interestingly, Mycobacterium tuberculosis decreases SRSF6 expression, but this resulted in a replication advantage. Overall, these findings add new mechanistic insight into the role of alternative splicing in regulating immunity and cell death. This work can potentially open novel avenues of inquiry into the role of BAX in regulating apoptosis.

Strengths:

The paper is well written, and the major conclusions are rigorously tested by numerous experiments. The data supports the major conclusions, which are that loss of SRSF6 increases ISG and leads to accumulation of alternatively spliced BAX, sensitizing cells to death.

Weaknesses:

The authors make a very interesting discovery that SRSF6 KD sensitizes macrophages to a caspase independent death by up regulating an alternatively spliced variant of BAX, a protein that has a well-established role in mediating caspase dependent death, but they did not rigorously test whether it was truly caspase independent.

Peer review report

Title: A single measurement of fecal hemoglobin concentration outperforms polygenic risk score in colorectal cancer risk assessment

version: 1

Referee: Iris Lansdorp-Vogelaar

Institution: Erasmus MC, Rotterdam, the Netherlands

email: i.vogelaar@erasmusmc.nl

ORCID iD: 0000-0002-9438-2753

General assessment

This is a well conducted study, clearly written study. The main strengths of the study include the novelty of the topic, its large sample size and that physicians and lab analysts were blinded to each other’s outcomes. There are few weaknesses. First, FIT and SNPs in essence service different purposes. Although I agree with the authors that FIT can be used both ways, this deserves more explicit explanation in the discussion section. Second, I disagree with the exclusion of non-advanced adenomas as relevant findings. Given that the authors suggest using FIT/SNPs for risk prediction at younger ages, non-advanced adenomas are also relevant because with time they could develop into colorectal cancer.

Essential revisions that are required to verify the manuscript

1. There is an essential difference between SNPs and FIT: SNPs predict risk of developing colorectal lesions, whereas FIT signals presence of colorectal lesions. In the current manuscript, SNPs are essentially compared on their performance to detect advanced neoplasms, which is not their intention. Yet, I agree with the authors that in order to predict development of colorectal cancer, one would expect the presence of precursor lesions >10 years prior and thus the performance can be compared that way. However, this is not immediately obvious. I therefore feel very strongly that this difference in initial purpose should be more explicitly explained in the discussion section, and also the argument why this comparison is reasonable nevertheless.

2. Given the above point, I feel that non-advanced adenomas should be included as relevant findings. The purpose of SNPs/FIT in this paper is to predict colorectal cancer risk for stratified screening approaches. In that case, non-advanced adenomas are relevant for future cancer risk in 10+ years. Omitting these basically makes the tests focused on early detection rather than risk prediction and stratification.

Other suggestions to improve the manuscript

1. Genotyping was done on a random age- and sex- matched sample of participants without advanced neoplasms before applying exclusion criteria. As a consequence, there actually was an age- and sex-difference between participants with and without advanced neoplasms in the study. Would it not have been better to age- and sex- match after exclusion criteria were applied.

2. Provide statistical tests for difference in baseline characteristics between participants with and without advanced neoplasms in Table 1.

3. Have the authors evaluated a combined approach of FIT and SNPs to see if that improves risk prediction and outperforms use of either one separately.

Decision

Requires revisions: The manuscript contains objective errors or fundamental flaws that must be addressed and/or major revisions are suggested.

Reviewer #1 (Public Review):

This is an interesting study, addressing a timely question of the crosstalk between cancer, immune, and stromal cell populations in the tumor microenvironment, and the effect of therapy on the tumor microenvironment. The authors were aiming to show that the ratio between neutrophils and lymphocytes could predict treatment responses in pancreatic cancer. They indeed show that there is an association between the Neutrophil to lymphocyte ratio (NLR) and treatment outcome, suggesting that this could be a predictive marker. They go on to use a mouse model to perturb the NLR and combine this with treatment similar to that used in the clinic and find that targeting neutrophils affects tumor growth, suggesting a costive and not the only correlative role. Finally, they show that this could be mediated through the stromal compartment since this treatment affects the ratio of inflammatory to myofibroblastic CAFs.

The main strength of the paper is in tying together neutrophils, lymphocytes, and CAFs and showing how these populations affect each other. The correlations in human patients are promising and the regulation of CAF transitions is interesting.

While the correlation between NLR and survival is convincing and strong, the relevance of CAF transitions to this effect in human patients is weak, and shown only in mice and not in humans. Also in the mouse, the evidence for CAF transitions should be strengthened to support the authors' full conclusions.

Reviewer #1 (Public Review):

The manuscript by Lian et al. presents a population graph deep learning model constructed using Transformer-generated imaging features and non-imaging clinical characteristics that were proven to be effective at predicting the survival of patients with early-stage NSCLC. This study demonstrates GNN-based model significantly outperforms the TNM model and ResNet-Graph model in predicting survival in all datasets. The paper is well-written, clear for a general audience, takes nice innovations in computer vision into the medical field, and presents a usable tool for survival analysis. The strengths and limitations of the approach are brought forth in the discussion.

Reviewer #1 (Public Review):

This publication shows a strong understanding and implementation of large-scale multiprotein MD simulations. It is the first application of MD simulations to full-length membrane-bound TSHR. The authors showed that the LR is intrinsically disordered, contrasting a previously published homology model. Some simulation results are supported by cryo-EM structures. Finally, it is significant that the inclusion of TSH in the binding site altered the dynamics of the LR region, supporting a hypothesis that the LR is involved in a signaling mechanism, though the authors acknowledge this result as preliminary.

Weaknesses:<br /> The methods section lacks sufficient detail, and arbitrary choices made in the simulation setup may have biased the results. The author's finding that the LR is disordered does not provide obvious mechanistic insights, and the simulations with the bound ligand are too preliminary to make solid conclusions. Although this manuscript is technically strong, the significance of the results is often unclear.

Reviewer #1 (Public Review):

Wang et al., developed a CRISPR/Cas 9 based protocol with the aim to accurately and quickly detect bacteria in ICU patients with severe pneumonia.

The development of such a tool is important as quick and reliable identification of pathogens is extremely important. This study is innovative and aims to address an important clinical problem. The authors de novo designed an algorithm to screen species-specific . Then they used the species specific DNA tags to identify 10 pathogens.

1) It is not very clear on which epidemiological data these pathogens were selected on. Moreover, the selected pathogens are only bacteria.

2) Page 9. It is not very clear on how the primers' specificity was evaluated.

3) Page 9. Were patients on antibiotics before getting into the trial?

4) Page 10 At which timepoint the patients received different treatment based on the results of the culture or SSBD? Was this consistent?

5) Page 11. The second sentence of 3.1 section in results is not clear.

6) How were patients allocated to groups? Randomised?

7) The table describing the patient cohort is in supplementary. This shall be in the main manuscript. It seems that the control and experimental groups were not balanced.

8. The exact protocol of the study needs to be in the supplementary.

9. Were any samples poly-microbial?

10. Which was the threshold level of fluorescence (Figure 3) which was considered important?

Reviewer #3 (Public Review):

In the manuscript, the authors provided the development of a sensitive and rapid diagnostic tool for detection of pathogenic bacteria in respiratory infections given the limitations of traditional cultures in the clinical settings. Rapid identification and treatment of bacterial infections can impact the prognosis in sepsis. This work highlights how a new rapid diagnostic tool may be beneficial in the treatment of patients with bacterial pneumonia given the time-consuming nature and low sensitivity of traditional culture methods.

Strengths:

The manuscript authors created a diagnostic tool using CRISPR-Cas12 with bacterial species-specific DNA-tags to 10 epidemic bacteria at their local intensive care unit (ICU). The appendix data provided detailed reports of the reaction conditions, sample preparations and reaction incubation time.

A 2-stage validation process was used. The initial validation stage compared the use of the novel diagnostic tool to traditional cultures from bronchoalveolar lavage samples from ICU patients. Once the accuracy of the diagnostic tool was evaluated, the second validation stage was pursued in the form of a randomized controlled trial at the ICU of the study. The second validation stage demonstrated that the proposed novel diagnostic tool had faster results and correlated with improved APACHE II scores and more effective antibiotic coverage rates in the experimental group.

The use of the novel diagnostic test highlighted limitations traditional culture modalities may have in identifying polymicrobial infections which were identified more frequently in the two validation stages

Weaknesses:

Although the study has many strengths, a potential weakness could lie in the unclear use of next-generation sequence (NGS) testing where samples were reported to be sent at random. However, similar to the novel diagnostic tool proposed in this manuscript, NGS testing has been noted to have high sensitivity and specificity and both had similar results in the manuscript.

Additionally, the novel diagnostic testing demonstrated increased detection of polymicrobial infection when compared to traditional cultures; however, clinical evaluation will remain important to help decipher potential "false positive" results or identification of non-pathogenic colonization.

Based on the author's proposed aims to develop a rapid and sensitive diagnostic tool for bacterial pathogens in pneumonia; the authors demonstrated a highly sensitive and specific test when compared to gold-standard testing. Random samples were assessed against NGS testing technology with similar reported results. The development of this rapid, sensitive diagnostic tool can have wide-spread clinical implications to guide management in patient care where earlier time to effective treatment can have important impacts on prognosis.

Reviewer #1 (Public Review):

In this paper, Gao et al report that Kiaa1024L/Minar2 causes hearing loss in mice and in zebrafish. The animal studies are well executed. Mechanistically, the authors claim that Kiaa1024L/Minar2 is responsible for the enrichment of an accessible pool of cholesterol in the hair bundle membrane. Increasing cholesterol levels rescues hair cell defects whereas decreasing cholesterol aggravates the problem.

Unfortunately, the mechanistic arm of this study doesn't go beyond this correlation. The characterization of cholesterol levels and pools is not rigorous and it is unclear why cholesterol matters for hearing.

Reviewer #3 (Public Review):

In the manuscript by Gao et al, the authors were trying to achieve an understanding of how Kiaa1024L/Minar2 is necessary for hearing in vertebrates. It is known that the Kiaa1024L/Minar2 mutation causes deafness in mice but not much beyond that is known.

Strengths:<br /> - In this manuscript, they were successful in making two zebrafish mutant zebrafish strains in the Kiaa1024L/Minar2 gene using Crispr/Cas9. The mutant(s) has defects in hearing (using the C-start assay and determining thresholds) and reduced hair cell numbers in the ear (phalloidin labeling to determine hair cell density in utricle and saccule) and the lateral line (including using the AM1-43 assay). From these data, they demonstrate that hair cells are defective in these mutants.

- The authors show that Lamp1-GFP labeled lysosomes change in size in the minar2fs139 mutant. In addition, they show that GFP-Minar2 localizes to lysosomal membranes in cultured cells (human and monkey).

- They performed primary amino acid sequence analysis on Minar2 and showed that it contained a putative CSD of caveolin, which is known to interact with cholesterol. They then show that when Minar2 is expressed in cells in culture, there is an increase in cholesterol detection in the region that contained Minar2, supporting the idea that cholesterol interacts with Minar2.

The experiments in figure 5 seem to show that lowering cholesterol levels using pharmacology exacerbates hair cell defects in a minar2 mutant.

Weaknesses:<br /> 1. The authors attempt to show localization (Fig 2 A and B) of Minar2 to the stereocilia and the apical region of hair cells using GFP-MINAR2 fusion protein expression in hair cells of transgenic animals. Although this is a typical way of demonstrating localization, it is usually used to validate location after a similar pattern has been shown using an antibody (usually in mice.) So, special precautions must be taken when interpreting this kind of transgenic data. According to the authors, GFP-MINAR2 localized to the stereocilia and the apical region of hair cells. This needs to be validated by some other means. I can also see the localization of the green signal at the basolateral area of the cells in Fig 2a. Moreover, it's important to note that other mislocalized fusion proteins localize to the apical region of hair cells.

2. Figure 2C and D. The defects in the hair bundles are plausible but not convincing. Electron microscopy should be used to validate. Also, are hair bundle defects seen in the neuromast? EM would be easier to do there.

3. Fig 1A do prim 1- and prim 2-derived neuromasts express minar2? Do anterior neuromasts express minar2?

4. It's my impression that the authors don't take into account that there is much more plasma membrane in the stereocilia than in the basolateral membrane. So, this statement, "These data suggested that there are high levels of accessible cholesterol located to the stereocilia membranes, while the accessible cholesterol levels are marked lower in the basolateral membranes in the hair cells" based on Figure 4 needs to be reconsidered. The authors need to show that the little reporter that is present in the basolateral membrane is not equal to the reporter present in a single sheet of the plasma membrane in a stereocilium. I can see basolateral labeling in the lateral line hair cells.

5. It's not clear if there is a paralog of the Kiaa1024L/Minar2 gene.

Reviewer #1 (Public Review):

The authors examined the impact of pre-gravid obesity in human mothers on the monocytes of newborns by collecting umbilical cord blood. Additionally, the authors also used a non-human primate (NHP) model of diet-induced obesity to isolate fetal macrophage and assess the impact of maternal obesity on fetal macrophage function.

The comprehensive analysis of the human umbilical cord blood monocytes by studying cytokine release, bulk RNA-seq and bulk ATAC-seq, single cell RNA-seq and single cell ATAC-seq, responses to pathogen stimulation as well as metabolic studies such as glucose uptake are major strength of the work. They present convincing evidence that the monocytes of offspring with obese mothers have epigenetic and transcriptomic profiles consistent with impaired immune responses, both during baseline conditions and upon stimulation.

However, it is not clear from the data how the epigenetic data and the transcriptomic data are related to each other. The implication that the epigenetic changes drive the downstream transcriptional differences is not clearly demonstrated. Furthermore, it is not clear which of the observed attenuations of monocyte transcriptional responses overlap with chromatin accessibility differences. Such an overlap would make a stronger case for the mechanistic link.

The increased phagocytosis of E.coli in umbilical cord monocytes of newborns with obese mothers appear counter-intuitive because it implies greater host defense capacity.

One of the most remarkable aspects of the manuscript is the analysis of the fetal macrophages in a non-human primate (NHP) model of diet induced obesity because of the challenge of studying fetal macrophages in humans. The cytokine assays nicely show that the fetal macrophages in the obesity model show impaired cytokine production, consistent with what was seen in the umbilical cord blood monocytes of human newborns. This is especially important because circulating monocytes or monocyte progenitors seed the fetal tissues and give rise to fetal macrophages, thus elegantly linking the human work on circulating umbilical cord blood monocytes to the tissue macrophages in the NHP model.

However, the NHP studies do not show any additional macrophage characterization beyond the cytokine assays. Flow cytometry analysis of the macrophage phenotype and functional assays would strengthen the conclusions regarding macrophage dysregulation.

Reviewer #3 (Public Review):

The manuscript by Sureshchandra et al is a very extensive analysis of monocyte function and their molecular landscape in cord bloods from lean and obese mothers. They aimed to analyze the effects of pre-pregnancy BMI on the functioning of the innate immune system in newborns in a very extensive way. The combination of functional and molecular analyses strengthens their observations and shows many different sides of monocyte activation. I think this approach needs to be praised and should be an inspiration to many others who study monocyte function. This allows for a broad view on the matter and also shows where potential targeting will be necessary in the future. Overall, the manuscript and particularly the methods section is very well written and extensive, making it easy to study how robust the data are.

Reviewer #1 (Public Review):

The authors endeavored to determine molecular pathways that could enhance the viability and function of MSCs. The authors identified the master anti-oxidant regulator NRF2 as a direct regulator of DKK1, a Wnt pathway inhibitor. Moreover, the authors demonstrate over expression of NRF2 and DKK1 ameliorates liver regeneration in a model of acute on chronic liver failure. The strengths of this study are their multi-tier approach utilizing molecular biology, genetic interventions and in vitro and vivo models. These findings have uncovered a novel signaling loop with the potential for enhancing MSC function in vivo.

Reviewer #1 (Public Review):

Bacterial carboxysomes are compartments that enable the efficient fixation of carbon dioxide in certain types of bacteria. A focus of the current work is on two protein components that provide spatial regulation over carboxysomes. The McdA system is an ATPase that drives the positioning of carboxysomes. The McdB system is essential for maintaining carboxysome homeostasis, although how this role is achieved is unclear. Previous studies, by the lead author's lab, showed that the McdB system is a driver of phase separation in vitro and in cells. They proposed a putative connection between McdB phase separation and carboxysome homeostasis. The central premise of the current work is as follows: In order to understand if and how phase separation of McdB impacts carboxysome homeostasis, it is important to know how the driving forces for phase separation are encoded in the sequence and architecture of McdB. This is the central focus of the current work. The picture that emerges is of a protein that forms hexamers, which appears to be a trimer of dimers. The domains that drive that the dimerziation and trimerization appear to be essential for driving phase separation under the conditions interrogated by the authors. The N-terminal disordered region regulates the driving forces for phase separation - referred to as the solubility of McdB by the authors. To converge upon the molecular dissections, the authors use a combination of computational and biophysical methods. The work highlights the connection between oligomerization via specific interactions and emergent phase behavior that presumably derives from the concentration (and solution condition) dependent networking transitions of oligomerized McdB molecules.

Having failed to obtain specific structural resolution for the full-length McdB as a monomer or oligomer, the authors leverage a combination of computational tools, the primary one being iTASSER. This, in conjunction with disorder predictors, is used to identify / predict the domain structure of McdB. The domain structure predictions are tested using a limited proteolysis approach and, for the most part, the predictions stand up to scrutiny affirming the PONDR predictions. SEC-MALS data are used to pin down the oligomerization states of McdB and the consensus that emerges, through the investigations that are targeted toward a series of deletion constructs, is the picture summarized above.

Is the characterization of the oligomerization landscape complete and likely perfect? Quite possibly, the answer is no. Deletion constructs pose numerous challenges because they delete interactions and inevitably impose a modularity to the interpretation of the totality of the data. Accordingly, we are led to believe that the N-terminal IDR plays no role whatsoever in the oligomerization. Close scrutiny, driven by the puzzling choice of nomenclature and the Lys to Gln titrations in the N-terminal IDR raise certain unresolved issues. First, the central dimerization domain is referred to as being Q-rich. This does not square with the compositional biases of this region. If anything is Q/L or just L-rich. This in fact makes more sense because the region does have the architecture of canonical Leu-zippers, which do often feature Gln residues. However, there is nothing about the sequence features that mandates the designation of being Q-rich nor are there any meaningful connections to proteins with Q-rich or polyQ tracts. This aspect of the analysis and discussion is a serious and erroneous distraction. Back to the middle region that drives dimerization, the missing piece of the puzzle is the orientation of the dimers. One presumes these are canonical, antiparallel dimers. However, this issue is not addressed even though it is directly relevant to the topic of how the trimer of dimers is assembled. If the trimer is such that all binding sites are fully satisfied (with the binding sites presumably being on the C-terminal pseudo-IDR), then the hexamer should be a network terminating structure, which it does not seem to be based on the data. Instead, we find that only the full-length protein can undergo phase separation (albeit at rather high concentrations) in the absence of crowder. We also find that the driving forces for phase separation are pH dependent, with pH values above 8.5 being sufficient to dissolve condensates. Substitution of Lys to Gln in the N-terminal IDR leads to a graded weakening of the driving forces for phase separation. The totality of these data suggest a more complex interplay of the regions than is being advocated by the authors. Almost certainly, there are complementary electrostatic interactions among the N-terminal IDR and C-terminal pseudo IDR that are important and responsible for the networking transition that drives phase separation, even if these interactions do not contribute to hexamer formation. The net charge per residue of the 18-residue N-terminal IDR is +0.22 and the NCPR of the remainder is ≈ -0.1. To understand how the N-terminal IDR is essential, in the context of the full-length protein, to enable phase separation (in the absence of crowder), it is imperative that a model be constructed for the topology of the hexamer. It is also likely that the oligomer does not have a fixed stoichiometry.

Therefore, the central weakness of the current work is that it is too preliminary. A set of interesting findings are emerging but by fixating on Lys to Gln titrations within the N-terminal IDR and referring to these titrations as impacting solubility, a premature modular and confused picture emerges from the narrative that leaves too many questions unanswered.

The work itself is very important given the growing interest in bacterial condensates. However, given that the focus is on understanding the molecular interactions that govern McdB phase behavior - a necessary pre-requisite in the authors minds for understanding if and how phase separation impacts carboxysome homeostasis - it becomes imperative that the model that emerges be reasonably robust and complete. At this juncture, the model raises far too many questions. The MoRF analysis is distraction away from the central focus.

The problem, as I see it, is that the authors have gone down the wrong road in terms of how they have interpreted the preliminary set of results. Further, the methods used do not have the resolution to answer all the questions that need to be answered. Another issue is that a lot of standard tropes are erected and they become a distraction. For example, it is simply not true that in a protein featuring folded domains and IDRs it almost always is the case that the IDR is the driver of phase transitions. This depends on the context, the sequence details of the IDRs, and whether the interactions that contribute to the driving forces for phase separation are localized within the IDR or distributed throughout the sequence. In McdB it appears to be the latter, and much of the nuance is lost through the use of specific types of deletion constructs.

Overall, the work represents a good beginning but the data do not permit a clear denouement that allows one to connect the molecular and mesoscales to fully describe McdB phase behavior. Significantly more work needs to be done for such a picture to emerge.

Reviewer #3 (Public Review):

Through a series of rigorous in vitro studies, the authors determined McdB's domain architecture, its oligomerization domains, the regions required for phase separation, and how to fine-tune its phase separation activity. The SEC-MALS study provides clear evidence that the α-helical domains of McdB form a trimer-of-dimers hexamer. Through analysis of a small library of domain deletions by microscopy and SDS-PAGE gels of soluble and pellet fractions, the authors conclude that the Q-rich domain of McdB drives phase separation while the N-terminal IDR modulates solubility. A nicely executed study in Figure 4 demonstrated that McdB phase separation is highly sensitive to pH and is influenced by basic residues in the N terminal IDR. The study demonstrates that net charge, as opposed to specific residues, is critical for phase separation at 100 micromolar. In addition, the experimental design included analysis of McdB constructs that lack fluorescent proteins or organic dyes that may influence phase separation. Therefore, the observed material properties have full dependence on the McdB sequence.

Studies of proteins often neglect short, disordered segments at the N- or C- terminus due to unclear models for their potential role. This study was interesting because it revealed a short IDR as a critical regulator of phase separation. This includes experiments that remove the IDR (Fig 2 & 3) and mutate the basic residues to show their importance towards McdB phase separation. In a nice set of SDS-PAGE experiments, the authors showed that as the net charge of the IDR decreased the construct became more soluble.

One challenge is in the experimental design when mutating residues is to assess their impact on phase separation. The author's avoided substitutions to alanine, as alanine substitutions have synthetically stimulated phase separation in other systems. The authors, therefore, have a good rationale for selecting potentially milder mutations of lysine/arginine to glutamine. A potential caveat of mutation to glutamine is that stretches of glutamines have been associated with amyloid/prion formation. So, the introductions of glutamines into the IDR may also have unexpected effects on material properties. Despite these caveats, the authors show mutation of six basic residues in the short IDR abolished phase separation at 100 mM.

Computational studies (Fig 7) also suggest that this short N-IDR region may play a role as a MORF upon potential binding to a second protein McdA. The formulation of this hypothesis is strengthened by the fact that for other ParA/MinD-family ATPases, the associated partner proteins have also been shown to interact with their cognate ATPase via positively charged and disordered N-termini. This aspect of understanding McdB's N-IDR as a MORF is at a very early stage. This study lacks experimental evidence for an N-IDR: McdA interaction and experimental data showing conformational change upon McdA binding. However, the computation study sets up the future to consider whether and how the phase separation activity of McdB is related to its structural dynamics and interactions with McdA.

In summary, this study provides a strong foundation for the contribution of domains to McdB's in vitro phase separation. This knowledge will inform and impact future studies on McdB regulating carboxysomes and how the related family of ParA/MinD-family ATPases and their cognate regulatory proteins. For example, it is unknown if and how McdB's phase separation is utilized in vivo for carboxysome regulation. However, the revealed roles of the Q-rich domain and N-IDR will provide valuable knowledge in developing future research. In addition, the systematic domain analysis of McdB can be combined with a similar analysis of a broad range of other biomolecular condensates in bacteria and eukaryotes to understand the design principles of phase separating proteins.

Reviewer #1 (Public Review):

Drosophila ovarian follicle cells have been utilized as a model system to study organogenesis and tumorigenesis of epithelia. Studies have found that lack of proper cell polarity causes invasive delamination of cells and formation of multilayered epithelia, reminiscent of Epithelial-Mesenchymal Transition (EMT). Using this system, the authors analyzed the single-cell transcriptome of follicle cells and show that distinct cell populations emerge shortly after induction of polarity loss. Authors identified dynamic activation of Keap1-Nrf2 pathway Finally, subpopulation classification and analysis of regulon activity identified that Keap1-Nrf2 pathway is responsible for epithelial multilayering caused by polarity loss.

Strengths: The authors characterized the single-cell transcriptome of follicle cell subpopulations after induction of polarity loss. Using temperature-inducible driver, they can induce the polarity loss in a short period of time, which enables detection of epithelial populations in various transition stages. Detected cell-heterogeneity could be caused intrinsically or by environmental cues within in vivo tissue. Therefore, it is likely well recapitulating tumorigenesis in vivo.

Weaknesses:<br /> 1) Authors should show cells corresponding to identified key cell clusters within the tissue by immunostaining, GFP-trap, or RNA FISH.<br /> 2) Images are low magnification and difficult to see individual cells.<br /> 3) Manuscript is written weighted toward the technical aspect and more biology behind this study has to be discussed.

Reviewer #3 (Public Review):

In this manuscript, the authors aim to identify the regulators of epithelial invasiveness upon Lethal giant larvae (Lgl), a basolateral polarity protein, knockdown in the follicular epithelium of the Drosophila ovaries, which can serve as a model system to investigate cellular plasticity when apical-basal polarity is lost. Knockdown (KD) of Lgl causes a multilayered epithelium and through extensive single cell RNA-seq analyses, the authors demonstrate that Lgl-KD triggers the appearance of groups of cells exhibiting tumor-associated molecular signatures and invasive behaviour. Overall, the manuscript is technically sound and the combination of computational and experimental approaches results in a thorough characterisation of the earliest steps of epithelial de-stabilisation upon the loss of apical-basal polarity. In my view, the aims set by the authors are met and the experimental data provided support the claims. Interpretations are balanced and the display items are presented logically and informatively for even non-experts. Together, this work will set the basis for further investigations using apical-basal destabilisation of the follicle epithelium as a model of epithelial tumorigenesis.

Reviewer #1 (Public Review):

The authors' results revolutionize our understanding of the mechanism of arrestin-mediated GPCR internalization. They identified previously unknown elements on the non-receptor-binding side of arrestins participating in the process. The findings are ground-breaking and very important to the large field of GPCR signaling.

Reviewer #3 (Public Review):

Barsi-Rhyne reports a novel mode of engagement of beta arrestins as endocytic adaptors and associates this novel mode together with the previously known canonical mode to the regulation of endocytosis and signaling by class A versus class B receptors. The manuscript is very well written, very good to read, almost flawless, extremely interesting, and highly relevant to the GPCR field with very well-crafted figures and fantastic microscopy.

Reviewer #3 (Public Review):

The authors use a previously developed technology, CRISPR activation screening, in which pooled sgRNAs are used to guide an RNA-associated regulatory complex (MS2-p65-HSF1 transcriptional activators) to promoter regions resulting in increased expression of a specific target gene. The authors screen two different pooled libraries TM1 (single pass) and TM2+ (multiple pass) with 20 different recombinant biotinylated soluble ligands and identified 22 novel interactions. These interactions were further characterized by SPR and cell-based binding experiments; however, several of the interactions are low affinity and were not characterized for any activity or function beyond the relatively weak biochemical binding. Therefore, while the data provide evidence of potential novel interactions, the biological relevance remains unclear.

Reviewer #1 (Public Review):

In this manuscript, Siepe et al. developed a high-throughput screen designed to identify novel protein-protein interactions in the extracellular human proteome. Their CRISPRa-based method induced the expression of transmembrane receptors such that they could be screened for binding to proteins of interest. Major strengths of this approach include the ability to screen multiple ligands in parallel, the ability to identify low-affinity interactions, and the availability of custom single- and multi-pass transmembrane protein libraries for selective target screening. A potential weakness is that low-affinity binders and non-specific interactions can be difficult to distinguish in certain cases, and these scenarios require more complex statistical analysis. The authors also note that the CRISPRa strategy cannot induce the expression of multi-subunit receptors that may be required for some ligands. The screen was tested against a curated set of ligand candidates and identified more than twenty novel interactions with intriguing biological implications. Both the method and newly discovered interactions will be of immediate scientific interest given the growing need to identify receptors for orphan ligands. Overall, this technology should function as a powerful new tool for ligand deorphanization in the extracellular space.

Reviewer #1 (Public Review):

Previous studies have linked several lifestyle-related factors, such as body mass index and smoking, alcohol use with accelerated biological aging measured using epigenetic clocks, however, most of them focused on single lifestyle factors based on cross-sectional data from older adults. The current study has a couple of major strengths: it has a decent sample size, lifestyle was measured longitudinally during puberty and adolescence, it looked at the effect of multiple lifestyle measures collectively, it looked at multiple epigenetic clocks, and due to the data from twins, it could examine the contribution of genetic and environmental influences to the outcomes. I have a couple of comments that are mainly aimed at improving the clarity of the methods (e.g. how was multiple testing correction done, how did the association model account for the clustering of twin data, how many samples were measured on 450k vs EPIC and were raw or pre-QC'd data supplied to the online epigenetic age calculator), and interpretation of findings (why were 2 measures of Dunedin PACE of aging used, how much are results driven by BMI versus the other lifestyle factors, and the discussion on shared genetic influences should be more nuanced; it includes both pleiotropic effects and causal effects among lifestyle and biological ageing).

Reviewer #1 (Public Review):

This manuscript reports a systematic study of the cortical propagation patterns of human beta bursts (~13-35Hz) generated around simple finger movements (index and middle finger button presses).

The authors deployed a sophisticated and original methodology to measure the anatomical and dynamical characteristics of the cortical propagation of these transient events. MEG data from another study (visual discrimination task) was repurposed for the present investigation. The data sample is small (8 participants). However, beta bursts were extracted over a +/- 2s time window about each button press, from single trials, yielding the detection and analysis of hundreds of such events of interest. The main finding consists of the demonstration that the cortical activity at the source of movement related beta bursts follows two main propagation patterns: one along an anteroposterior directions (predominantly originating from pre central motor regions), and the other along a medio-lateral (i.e., dorso lateral) direction (predominantly originating from post central sensory regions). Some differences are reported, post-hoc, in terms of amplitude/cortical spread/propagation velocity between pre and post-movement beta bursts.

Several control tests are conducted to ascertain the veracity of those findings, accounting for expected variations of signal-to-noise ration across participants and sessions, cortical mesh characteristics and signal leakage expected from MEG source imaging.

One major perceived weakness is the purely descriptive nature of the reported findings: no meaningful difference was found between bursts traveling along the two different principal modes of propagation, and importantly, no relation with behavior (response time) was found. The same stands for pre vs. post motor bursts, except for the expected finding that post-motor bursts are more frequent and tend to be of greater amplitude (yielding the observation of a so-called beta rebound, on average across trials).

Overall, and despite substantial methodological explorations and the description of two modes of propagation, the study falls short of advancing our understanding of the functional role of movement related beta bursts.

For these reasons, the expected impact of the study on the field may be limited. The data is also relatively limited (simple button presses), in terms of behavioral features that could be related to the neurophysiological observations. One missed opportunity to explain the functional role of the distinct propagation patterns reports would have been, for instance, to measure the cortical "destination" of their respective trajectories.

Reviewer #3 (Public Review):

Aside from one critical reservation, I thought this paper was excellent. The figures are clear, the manuscript is well-written, the scope of the study is well-defined (i.e. it characterizes traveling beta), and the authors were circumspect in all aspects of the work, with the authors' consideration of wave propagation along different cortical meshes being but one example in a generally deft and careful approach.

However, the inverse problem remains the inverse problem, and I believe there is one thorny issue to treat regarding the 3D geometry of the central sulcus as it pertains to synchronized beta events before I can accept the authors' conclusions. After this subtle issue is treated, I believe the work will be an important step forward and generally impactful on the community interested in human brain rhythms.

The authors were gracious enough to raise the issue of spatially synchronized events themselves in their discussion: Their argument, with which I mainly agree, is that the beamformer method essentially removes synchronous components from consideration, leaving the traveling component for analysis.

However, synchronization across the sulcus introduces a further bias into event detection by means of physical source-cancellation. I will here defer to Ahlfors et al (2010), who state that "Substantial cancellation occur also for locally extended patches of simulated [cortical] activity, when the patches extended to opposite walls of sulci and gyri."

With that in mind, let's look at Figure 1, where the authors seem to show a higher density of beta events relatively deep in the sulcus compared to the sulcal walls. This is certainly an interesting result if true! But even given only the occasional synchronization of mesoscale cortical neighborhoods, it appears that events in the sulcal walls will still be systematically undersampled and those deep in the sulcus oversampled here, by vice or virtue of cortical geometry as it pertains to the magnetic field.

This spatial sampling bias could impact nearly all aspects of the event propagation analysis that follows, and so I believe it must be considered in some detail before I can fully agree with the manuscript's conclusions.

Reviewer #1 (Public Review):

The transcriptome of the cells of the human meniscus have been studied in bulk or superficially via single cell methods. In this study, the authors profile the types of cells present in the normal/healthy human meniscus as well as samples from degenerative menisci using single cell RNA seq. Using pre-existing analysis packages for single cell RNA seq data, they infer the roll of the various cell type clusters that they have identified and posit which cells interact with which cells as part of the healthy meniscus and in disease. They have developed an on-line viewer to facilitate use of these data by other research groups.

Strengths: The data has been rigorously collected and appropriate quality control steps have been implemented to ensure the veracity of the data. The result is a robust data set. This is coupled with the on line viewer portal they have created, allowing the data to be available in the public domain. Further, having this tool is a huge resource as it means that the end user does not need to have advanced programing skills to be able to use it. Some of the RNA seq results have been validated via in situ and immunofluorescence. The authors have compared their results to data already published and discuss disagreements.

Weaknesses: Some of the conclusions are very over reaching. The function of clusters, the role of cells and the interactions between cells are all inferred results based on data analyses. These results gave not been experimentally validated.

Reviewer 3 (Public Review):

This is an interesting study that describes a single cell RNAseq analysis of human menisci. The study describes cell profiling of healthy and degenerated menisci divided into two zones, inner and outer meniscus.

Reviewer #1 (Public Review):

The authors provide insight into which regions of the ribozymes are involved in pairings including some tertiary interactions. Overall, the data support known structures and give insight into the roles of bases as pairs, catalytic residues, and extensions. The epistasis analysis is novel and gives deeper insight than previous mutational analyses of ribozymes. However, more can be extracted from this data. This study will impact the field by helping classify the roles of possible bases. There are also numerous technical issues that must be addressed. The authors should consider why short and long pairings show different epistasis and discuss the robustness of pairings from an evolutionary point of view. The effect of the primer binding site on ribozyme activity needs to be discussed.

Reviewer #3 (Public Review):

This article by Roberts, Hayden and colleagues expands on an interesting high-throughput experimental approach developed by Kobori and Yokobayashi (2016; Angew Chem) by determining the relative activity for every possible single and double mutant of five known self-cleaving ribozymes. While this approach is not in itself new, the fact that the authors analyze their data by looking at epistasis (non-additive effects between pairs of mutations) provides an additional opportunity for extracting meaningful structural information that is proposed to be similar to chemical or enzymatic probing experiments obtained on these self-cleaving ribozymes. In fact, this type of high throughput mutagenesis analysis might provide data closer to comparative sequence analysis and as such, might provide even more reliable structural information than structural probing experiments, especially when a relative activity can be properly assessed for the studied RNAs.

(1) Overall, the experiments have been carefully performed and the data seem to be highly reliable.<br /> (2) The strength of this article is that it demonstrates the generality of the approach initially developed by Kobori and Yokobayashi (2016; Angew Chem) by validating its usefulness in identifying most (if not all) the structural features of the studied ribozymes. The determination of positive and negative epistasis is very useful as it can facilitate the identification of base pairs covariations that are indicative of RNA structural elements.<br /> (3) At the present time, the authors have not really discussed how their data analysis compares to comparative sequence analysis. This aspect is important.<br /> (4) It is necessary to mention more clearly that this article builds on the method of Kobori and Yokobayashi (2016). Overall, with the exception of a few experimental details, the experimental method described herein is almost identical to the one of Kobori and Yokobayashi (2016) and this should be better emphasized.<br /> (5) Most importantly, this article provides an analysis of self-cleaving ribozymes for which the three-dimensional structures are known. Considering the scope of this article, instead of mostly focusing on the 2D structural aspect, it would be absolutely necessary to provide more 3D structural information.<br /> (6) When a self-modifying enzymatic activity is associated with the studied RNA, a relative activity could potentially be derived from high throughput sequencing. Could the authors expand on the generality and requirement of their high throughput approach for the study of RNA?

Reviewer #1 (Public Review):

In the current manuscript, Bolte et al., examine how a single TBI alters the heterogeneity of dorsal meningeal immune cell responses and whether age at the time of injury affects long-term transcriptional profiles of this immune compartment of the brain. Multiple complementary approaches were undertaken to achieve high resolution of meningeal transcriptional response(s) to TBI including single-cell sequencing and bulk tissue sequencing. Several innate and adaptive immune phenotypes were quantified at the protein level, demonstrating these disease-associated responses are not solely relegated to transcriptional responses. The majority of the methods and analyses are robust, which is a notable strength of the manuscript. In its current iteration, a weakness is a lack of integration between gene sets that define meningeal immune cell subsets in the single cell data (e.g. Macrophages, Tcells, Bcells, Fibroblasts, etc.) and quantifying these DEGs (up or down-regulated) to examine whether the transcripts are altered in the chronic TBI/aging bulk sequencing data. A more thorough integration of these two datasets and their discussion would significantly bolster the main premise of the manuscript related to the resolution of inflammatory responses to TBI in the young versus the aged condition, chronically.

Reviewer #1 (Public Review):

In this study, Menjivar et al. examine the specific role of the enzyme arginase 1 (Arg1), which is expressed in immunosuppressive macrophages and catabolizes arginine to ornithine, in pancreatic cancer. They use an elegant genetic approach that leverages a dual recombinase-based genetically engineered mouse model of pancreatic cancer, which efficiently deletes Arg1 and recovers extracellular arginine in cultured macrophages. Within the pancreas, macrophage Arg1 deletion increased T cell infiltration and fewer mice developed invasive pancreatic cancer. Interestingly, when tumors did develop, the authors observed that compensatory mechanisms of arginine depletion were induced, including Arg1 overexpression in epithelial cells identified as tuft cells or Arg2 overexpression in macrophages. To overcome these compensatory mechanisms, pharmacological targeting of arginase was tested and found to increase T cell infiltration and sensitize to immune checkpoint blockade, suggesting this is a promising approach for pancreatic cancer.

Strengths:

This is a very rigorous, well-designed study and the findings are broadly interesting for the metabolism, immunometabolism, and pancreatic cancer communities. The methods are comprehensive and the experimental details in the legends are complete.

Weaknesses:

The claim that Arg1 deletion in macrophages delayed the formation of invasive disease is not completely justified by the data presented. Only a small number of mice are analyzed, and no statistics are included. Moreover, the abstract does not comprehensively summarize the findings. Many findings, including compensatory upregulation of ARG1 in tuft cells and ARG2 in myeloid cells, are not mentioned, nor was the rationale for the pharmacological approach. Finally, the claim that their data demonstrate that Arg1 is more than simply a marker of macrophage function. While this is the first time this has been examined in pancreatic cancer, a general role for Arg1 and arginine metabolism by myeloid cells in immunosuppression has already been established by multiple studies, including those cited by the authors, in multiple tumor types. This is an overstatement of the findings.

Reviewer #3 (Public Review):

Menjivar et al. present an analysis of the role of immunosuppressive Arginase 1 in myeloid cells in pancreatic cancer. They show that depletion of Arg1 in macrophages leads to attenuation in progression from PanIN to PDAC and use single cell analysis to understand underlying changes in immune activation, including an increase in cytotoxic T cells. Interestingly, the authors observed what seems to be a compensatory upregulation in Arg1 in epithelial cells and used arginase1 inhibitor to assess the therapeutic potential of targeting Arg1 systemically. This study is overall well performed and generates novel mouse models to study immunosuppression in pancreatic cancer. While the notion that Arginase1 is immunosuppressive is not novel, the observation that Arg1 is upregulated in epithelial cells is interesting. There are several instances of overstating conclusions that, if addressed in the main text (not just relegated to the discussion section), could significantly strengthen the manuscript.