Reviewer #2 (Public Review):

This is an interesting study. In this study, the authors have linked single-cell RNA sequencing, spatial transcriptomic, and multiplex fluorescence in situ hybridization to characterize human oral mucosa in health and oral chronic inflammatory disease. They defined highly specialized epithelial and stromal compartments and spatially mapped a rare pathogenic fibroblast population likely responsible for lymphocyte recruitment and angiogenesis. They highlighted that the most dramatic variation in transcriptional/cellular spatial variability corresponds to oral mucosal tissue depth. The comparison of the list of genes with altered expression in gingival inflammation with the ones highlighted from the GWAS analysis related to patients with periodontitis is very interesting and will help to generate new hypotheses for future studies. Together with the recent publication from Williams et al., 2021, these studies are of particular interest and a valuable resource for researchers who study oral mucosa, especially gingiva in healthy conditions and periodontal diseases.

Reviewer #2 (Public Review):

In the paper, the authors aimed to repurpose a previously developed Variational Autoencoder (VAE) trained on adult rsfMRI data to characterise the in vivo foetal-neonatal brain development. Although the attempts to understand both healthy and aberrant early functional development are becoming increasingly popular, the processing and interpretation of the foetal-neonatal rsfMRI remain challenging due to methodological difficulties and the extremely fast and complex nature of the early brain development itself. For this reason, the non-linear computational models, such as the proposed VAE, have the potential to represent the rsfMRI data and capture the early neurodevelopmental trajectories with higher accuracy compared to more prevalent linear methods such as ICA.

In this vein, the authors successfully apply the adult-trained VAE to compress the spatial representation of foetal-neonate rsfMRI cortical patterns into 256 latent features. Due to the non-linear nature of the VAE, this latent representation has the potential to yield more informative brain representations of rsfMRI data compared to other available methods making it a strength of the article.

Nevertheless, one important limitation is that the direct application of the model trained on adult data to early functional connectome and more importantly, the interpretation of the reconstructed latent space-based maps rests on a strong assumption that the adult connectome features are stable and recognisable in the very early period. Moreover, such a model trained on the adult data would also be incapable to reveal possible network structures that would be present in the developing but not in the adult brain.

The attempt to validate the method and assess its generalisability on two independent, fairly large datasets that include foetuses, and preterm- and term-born infants is commendable. However, the interpretation of the results in light of the subject, image acquisition, and processing (which is widely recognised to be very difficult, especially in foetuses) heterogeneity requires caution. For example, the VAE reconstruction error is positively correlated with the age at scan in dHCP, and DBI full-terms, but the relationship is very strong in the reverse direction in DBI foetuses. This suggests differences between the subgroups of subjects which might be driven by factors other than age. Thus, we cannot exclude the possibility that the high age-predictive power of the models based on the latent features is partly driven by those differences in addition to the age-dependant features of the infant functional connectome.

The approach for the extraction and mapping of the group-level brain resting state networks is interesting and has the potential to uncover new insights into the early connectome. However, some of the current results are rather surprising and put into question their biological plausibility. For example, the authors suggest observing the precursor of the default-mode network in the DBI but not the dHCP dataset. This is rather strange given the DBI subjects (including foetuses) were on average scanned earlier than the dHCP subjects. Also, the pattern similarity of the best matched extracted independent component ('brain network') in the full-term dHCP vs full-term DBI comparison is 0.6 which is rather low if expecting the same networks to be extracted in the age-matched comparison. Additionally, the network visualisations show large heterogeneity of the distribution of activation/deactivations within extracted independent components between the datasets (even after ordering them for pattern similarity) which contradicts the expectation that the extracted networks (if real) should be stable, if not along the whole development, then at least between the narrower age ranges within the datasets.

Overall, the interpretation of the current work is somewhat limited, and careful analysis of the latent representations derived from foetal-neonate data might be required to dissociate the effects of potential confounders from biological/developmental mechanisms. This might be difficult in the context of the highly complex and mostly black-box strategy such as VAE (this applies not only to the current method but to all novel methods proposed to study rsfMRI). Despite these limitations, the proposed approach could be very interesting methodologically with a potential impact on the future analysis of rsfMRI data. Overall, the authors achieved their aim of applying a novel VAE method to foetal-neonatal functional data and demonstrated that the extracted latent variables are predictive of brain age. However, careful evaluation of the latent representations and differences in predictive results and the mapped networks between the two datasets might be necessary to support the conclusion that the VAE-derived representations of foetal-neonatal rsfMRI carry informative neural signatures.

Reviewer #2 (Public Review):

This study combines molecular analysis of human melanoma cells with in vivo functional experiments in zebrafish. ChIP-seq analysis of A375 melanoma cells stimulated with TGFB revealed a TGFB enhancer. The human enhancer was a clone and a zebrafish transgenic line driving GFP by this enhancer (TIE:EGFP) revealed that TIE:EGFP was only expressed in late melanomas. TIE:EGFP+ cells showed downregulated IFN response but upregulation of novel chronic GHB target genes. AP-1 transcription factor is required for the activation of this enhancer. Expression of the chromatin remodeller SATB2 promoted activation of TIE:EGFP in early melanomas. Finally, in vivo imaging, flow cytometry and scRNA seq showed that macrophages preferentially phagocytosed TIE:EGFP+ melanoma cells.

The identification of this novel TGFB enhancer is important since most studies focused on acute TGFB effects in melanoma. However, the present study identified a set of chronic TGFB target genes that may be relevant in melonoma and probably other tumors. Therefore, this study paves the way for future studies aiming at revealing the importance of this enhancer in different tumor histotypes and the novel identified chronic TGFB target genes.

Most conclusions are supported by the data, with the exception of the ones related to macrophages that are not fully convincing.

Reviewer #2 (Public Review):

There is currently much discussion about the function of several viral proteins hypothesized to be "viroporins", especially specific proteins within SARS-CoV-1 and CoV-2, such as Orf3a. While some prior studies suggest that Orf3a exhibits ion channel activity, others disagree on this important topic. In the present study, compelling evidence is presented that Orf3a does not function as an ion channel, and suggestions are made as to its actual function. The study combines imaging to delineate Orf3a location in the cell, extensive functional analyses that demonstrate a lack of ion channel activity beyond endogenous currents, and compelling structural evidence that Orf3a does not take the form of an ion channel - lacking a clear conduction pathway and also having a basic aqueous vestibule that would not be predicted to support cation channel activity. Finally, co-assembly with trafficking proteins suggest, instead, functioning of Orf3a as a host cell trafficking disruptor that could contribute to immune cell evasion or even viral exit.

The authors present exhaustive, high-quality data to support their conclusions that Orf3a proteins from SARS-CoV-1 and SARS-CoV-2 do not exhibit ion channel activity. They clearly show Orf3a at the cell membrane and fail to detect ion channel activity using multiple modalities. I believe this work closes the book on the question of Orf3a as a viroporin. It is difficult to find any deficiencies in the experimental work. The parts about a role disrupting trafficking are a little more speculative but nevertheless appropriate and serve as a guidepost for future studies to fully elucidate the true role of Orf3a.

Reviewer #2 (Public Review):

The manuscript presents a very simple and clear result. It demonstrates that neither place-cell nor time-cell presence is a constant in the rat hippocampus, but that both of these modes of activity are engaged flexibly depending on task demands. This result fits into a growing body of published work showing similar examples of flexibility in hippocampal representations; the authors do a fair job in relating their results to these studies. The innovative aspect of their manuscript is that it specifically addresses place cells and time cells, which have been different, and sometimes confusing, ways of thinking about hippocampal activity. By showing that the hippocampus shifts between distance and time encoding, the authors fit place cells and time cells into a more general framework of flexible representations.

The manuscript uses somewhat unusual and not very well-motivated criteria for classifying cells as distance or time cells. To detect the timing of neural activity on each trial, the authors look at the earliest onset of firing prior to the peak. It seems that this method would be highly susceptive to noise, and it is unclear why it would be better than the more standard methods like detecting the actual peak of firing or fitting a stretchable template to the entire firing pattern on each trial. This is a minor weakness of the manuscript, since the main conclusion shouldn't depend on the exact method used to classify cells. The difference between fixed-time and fixed-distance trials reported by the manuscript appears to be large and statistically robust.

Reviewer #2 (Public Review):

In their manuscript "Growth cone advance requires EB1 as revealed by genomic replacement with a light-sensitive variant", Dema et al. showcase a CRISPR-based strategy to introduce a photo activatable EB1 variant into cultured cells in a single genome engineering step. Upon photoactivation this EB1 variant, which they term π-EB1, dissociates, thus severing the connection between the microtubule tip and +TIP proteins. They demonstrate this technique in human induced pluripotent stem cells, verifying that this genetic engineering procedure neither influences the cells beyond the EB1 gene nor hinders their ability to differentiate into neurons. Subsequently, they nicely verify that dissociation of π-EB1 leads to hindered microtubule growth, which subsequently leads to growth cone retraction. Accordingly, π-EB1 expressing axons cannot grow into an area illuminated with blue light, demonstrating the system's usefulness in circuit engineering. Finally, the authors try to specifically redirect growth cones by illuminating defined sections of the growth cone. This however leads mainly to growth cone retraction, in 70% of axons as the authors note, but succeeds in the remaining axons. Sadly, the authors do not further investigate the mechanism at the bottom of the observed axon retraction. Nevertheless, this study adds a valuable tool to the optogenetic toolbox of neurobiologists in the axon growth as well as circuit engineering fields.

Besides a few small writing and figure-editing faux pas, the study is well-written and robustly designed. The conclusions drawn by the authors are well supported by the data, which itself is technically well-prepared and controlled.

Reviewer #2 (Public Review):

Previous studies have shown that the transcription factor Emx2 controls mirror-image PCP along the line of polarity reversal (LPR) by regulating the trafficking of an orphan receptor GPR156. However, the underlying mechanism is unknown. Here, the authors provide evidence that Emx2 represses transcription of Stk32a, which, in turn, negatively regulates GPR156 surface expression, thereby coupling cell-intrinsic and tissue-level PCP in the vestibular sensory epithelia.

Overall, the data are clearly presented and largely convincing. Using RNA-seq and ISH and both loss- and gain-of-Emx2 in vivo, the authors show that Stk32a is expressed in a complementary domain to Emx2 via Emx2-mediated repression. Gain- and loss-of-Stk32a experiments demonstrate that Stk32a is required for hair cell PCP in the Emx2-negative regions and is sufficient to reorient PCP in the Emx2-positive region. Moreover, Stk32a negatively regulates GPR156 localization to apical junctions without affecting core PCP proteins or Emx2 expression. However, there are several notable weaknesses, including a) because transcripts of the Stk32a mutant allele were still present, the nature of the Stk32a mutation is unclear; b) Mechanisms by which Emx2 represses Stk32a transcription were not addressed or discussed; c) Mechanisms by which Stk32a regulates GPR156 surface expression were not addressed. Addressing these issues at least partially would provide stronger support for the proposed model and improve the paper's impact.

Reviewer #2 (Public Review):

This study combines data from different experiments to provide a detailed and conclusive mechanism of how transition metal ions are transported by a prokaryotic member of the SLC11 family. Although insight into this process was already provided in previous investigations, the novelty here concerns the presentation of X-ray structures at high resolution which, in combination with previously determined structures of the same protein, show three relevant conformations on the transport cycle in the presence and absence of substrate. For the interpretation of mechanisms, the conclusions derived from these structures are supported by complementary functional experiments from isothermal titration calorimetry and transport assays. Finally, a series of molecular dynamics simulations illustrate the stability of the investigated conformations and the interaction network that was proposed to be relevant for conformational transitions.

The strength of the manuscript lies in the thoughtful experimental design of the study and the high quality of the data. The X-ray structures are as good as they probably can get for a delicate membrane protein and the interaction with ions was confirmed by anomalous scattering experiments. Although the structure of the outward-facing conformation has relied on a mutation that stabilizes this state, the conformation is similar to known outward-facing conformations of other family members. The presented complementary ITC experiments are of high quality and the experimental design is intriguing.

A comparably smaller weakness concerns a shortage in the critical assessment of the data and their relation to previous findings in the field. This is in no way meant to question major conclusions drawn from this study, but it might help the reader to better understand the limits of the results and their interpretation. This weakness can be addressed by better documentation of the data and some revision of the text.

Reviewer #2 (Public Review):

As described in the manuscript, gaze following is a dynamic process that should be investigated with similarly dynamic stimuli (wherever possible). In this case, the authors used videos, rich with visual information, that could be deemed an appropriate example of such stimuli. By constructing scenarios where actors gazed toward 1) a target person, 2) distractor or 3) nothing, the authors were able to easily study observers' eye movements. First, they were able to determine a baseline for how observers follow gaze in each of the three aforementioned conditions which is an important reference for future studies of this nature. Further, they suggest that eye movements are affected by how gaze following interacts with peripheral information (i.e., processing gaze-related information from the actor is combined with peripheral information about the presence/absence of a target person). Second, the authors also determined that eye movement behavior is affected by gaze information (i.e., changes in the gaze of the principal actor), in an anticipatory manner. This was verified using a DNN approach (using only the gazer's head direction) and then, confirmed through human observers' ratings. Lastly, the authors noted the presence of subsequent, reverse saccades (in the direction of the gazer and then, toward the target), which were shown to play a role in correcting an initial inference based on a slow head velocity of the gazer (confirmed with an SVM approach). While these are important first inquiries related to understanding eye movement behavior elicited in response to gaze following, a few items remain to be further elucidated, including what additional, peripheral information (besides target/distractor absence and presence) drives eye movements during gaze following. Overall, the dynamic videos used by the authors, in combination with their investigations, provide an important first step toward studying gaze following in more realistic conditions.

Reviewer #2 (Public Review):

In mammalian genomes (with some exceptions), the location of recombination hotspots is driven by the PRDM9 zinc-finger protein that recognizes some specific DNA motifs and recruits the machinery inducing double-strand breaks (DSBs) initiating recombination. As DSBs are repaired with the homologous chromosome, "hot motifs" can be rapidly eroded through gene conversion occurring during the repair. This led to the "hotspot paradox" question and to the development of red queen models of hotspot evolution where the lack of enough DSB motifs can select for new PRDM9 alleles recognizing new sets of motifs, which in turn are eroded. However, this model fails to explain some observations, in particular, that the number of DSB seems not limited by PRDM9 sites. Recent findings also showed that PRDM9 played a central role in the symmetrical binding of homologous chromosomes.

In this study, the author incorporated this new finding (and more realistic assumptions compared to previous models) in a model of hotspot evolution. Their main result is that it affects the evolution dynamics and in particular the causes of selection on new PRDM9 alleles. Instead of selection pressure to increase the number of DSB targets, they showed that selection likely occurred instead to limit the number of hotspots to the hottest and symmetrical ones. These results are important as they changed our view and understanding of the evolution of mammalian hotspots and should have general implications for the study of recombination. The article focuses on complex mechanisms and can appear rather specific and technical. However, it nicely exemplifies the importance of taking molecular mechanisms into account to model genome evolution.

Overall, the model is sound with no apparent flaw and should be an important contribution to the field. The model is rather complex but the authors focused on a few key parameters while fixing others based on empirical knowledge. This allows for highlighting the novelty of the results without being lost within too many scenarios and hypotheses. However, two main issues should be addressed but they mostly concern the way the model and the results are presented and do not. First, partly due to the complexity of the mechanisms, the core of the manuscript is rather difficult to follow and would deserve a more careful and explicit presentation to guide the reader, as detailed below. Second, the implications of the model and the practical and testable predictions it makes could be developed more, in particular, to compare with previous models. The main comments are listed below.

1) The introduction reads very well and clearly explains complex mechanisms. It is a bit long and could be reduced a bit.<br /> 2) It is quite helpful to analyze the model step by step. However, the objective of each step is not clearly explained, and it is left to the reader to understand where the authors want to go. At first read, it is not clear whether the authors present an analysis of the model or simulation results and why they do that. So, the results part deserves rewriting and re-organization to guide the reader.<br /> - In the two first parts (Fitness with one heat and two heats) it should be stated more explicitly that it corresponds to an analysis of the fitness landscapes generated by the molecular mechanisms than results on the evolutionary dynamics<br /> - The part "Dynamics of the two-heat model" corresponds to simulations and it is only at this point that mutation on PRDM9 is introduced.<br /> - In the present form, the presentation of the results describes many mechanisms (which is fine). However, as the model is complex, stressing the main conclusion for each part could be useful as then making a clear link between the different steps of the reasoning.<br /> 3) The choice of key parameters is well justified with a detailed review of the literature and it is well justified to fix most of them to focus on the key unknown (or not well-known) ones. However, in a few cases, additional simulations or at least better justification would be welcome, in particular on the mutation dynamics of PRDM9.<br /> 4) The model clearly gives new insights into the evolution of recombination hotspots and appears better to explain some results. However, it is not clear what are the predictions of the model that could be properly tested with data, in particular against previous models. Some predictions are proposed but remain mainly qualitative. For example, can one quantify that this model predicts a skewer distribution of hotspots compared to previous red-queen models? How good is the model at predicting the number of PRDM9 alleles in human and mouse for example? Only the diversity at PRDM9 is given, it may be interesting to also give the number of alleles to compare to observations. The discussion on this remains a bit vague. Finally, are there additional predictions of the model that could be used to test it?<br /> 5) The Penrose stair metaphor is appealing but it seems to be dependent on the definition of hotspot, so not to represent a real biological process. Related to metaphors, it is also not very clear whether the authors suggest abandoning the red-queen metaphor for the benefit of the Penrose stair one. Actually, we can still consider that it is a red-queen dynamics but with a different underlying driver.

Reviewer #2 (Public Review):

This paper studies how relative values are encoded in a learning task, and how they are subsequently used to make a decision. This is a topic that integrates multiple disciplines (psych, neuro, economics) and has generated significant interest. The experimental setting is based on previous work from this research team that has advanced the field's understanding of value coding in learning tasks. These experiments are well-designed to distinguish some predictions of different accounts for value encoding. However there is an additional treatment that would provide an additional (strong) test of these theories: RN would make an equivalent set of predictions if the range were equivalently adjusted downward instead (for example by adding a "68" option to "50" and "86", and then comparing to WB and WT). The predictions of DN would differ however because adding a low-value alternative to the normalization would not change it much. Would the behaviour of subjects be symmetric for equivalent ranges, as RN predicts? If so this would be a compelling result, because symmetry is a very strong theoretical assumption in this setting.

Reviewer #2 (Public Review):

The manuscript by Torcal Garcia et al. shows that the mutation of a single arginine residue in a transcription factor, C/EBPα is able to accelerate the kinetics of B-cell to macrophage transdifferentiation without impacting the characteristics of the fully reprogrammed cell state. The authors delve into the mechanism underlying this phenotype and demonstrate that R35A mutation increases the affinity of C/EBPα for another transcription factor PU.1, and accelerates chromatin accessibility changes that accompany the transition from B-cell to macrophage program. The authors subsequently demonstrate that R35 is a methylation site for the arginine methyltransferase Carm1. Through Carm1 gain- and loss-of-function experiments, authors recapitulate R35me2/R35A effects on transdifferentiation. Overall, this is an interesting and well-executed study that provides one of the most striking examples of transcription factor regulation by methylation and documents the profound impact it can have on the kinetics of cell fate transition. Data are of high quality, experiments are rigorous, and deeply probe into the mechanism. Overall, the study sheds light on an under-appreciated level of transcription factor regulation.

Reviewer #2 (Public Review):

This manuscript describes several general findings that are relevant to multiple fields. First, using bioinformatic sequence analysis the authors show that RNA Recognition Motif (RRM)-containing proteins often contain a domain with a specific amino acid repeat sequence (Arg-Ser, or RS) that is enriched in proteins that form condensates. With this understanding, the authors sought to use high concentrations of Arg in buffers in an attempt to solubilize an RRM-containing protein that has a C-terminal "RS" repeat region (SRSF1) for NMR structural studies. The high salt content of these samples is not ideal for NMR studies; however, the authors found that small peptides that mimic the RS sequence within SRSF1 can enhance the solubility of SRSF1 with more favorable conditions for NMR. Using paramagnetic relaxation enhancement (PRE) NMR, the authors show that an 8 amino acid RS peptide (RS8) interacts with one of the RRM domains in SRSF1, and the addition of RS8 does not abolish inter- and intra-molecular SRSF1 interactions. PRE NMR-based structure calculations provide a visual assessment of the potential interactions between RS8 and SRSF1. Finally, the authors performed bioinformatic and structural analysis of RRM domains, which was facilitated by AlphaFold-calculated structures, and found that surface-exposed aromatic sequence features appear to be conserved among phase-separating RRM domains.

Strengths of the work include the rigorous approach and the impact that solubilizing repeat peptides could have across many different biological fields where structural data on phase-separating proteins is difficult to obtain. The finding that the RS8 peptide can increase SRSF1 solubility and enable high-resolution NMR analysis should inspire other NMR experimentalists to seek out similar peptide-stabilizing co-solutes for their systems. The bioinformatic analysis that indicates surface-exposed aromatic residues are enriched in RRM domains involved in phase separation provides reasonable hypotheses, which are not directly tested using experimental approaches here but lay the foundation for studies that could be tested in future work and should be generally informative to other researchers interested in RNA-binding proteins.

Reviewer #2 (Public Review):

In this study, the authors were seeking to determine the major antigens presented by the MHC-1 complex during the infection of human macrophages with virulent M. tuberculosis. Major strengths include rigorous and well-controlled experiments. The careful identification of mycobacterial peptides in the context of host peptides was impressive and well done. The results generally support the conclusions drawn in the study. Overall, the study is well-presented and rigorous and adds new knowledge to the field. This study provides new information regarding the mycobacterial peptides that are presented to the immune system via the MHC pathway, and the role of alternate secretion systems and known peptide processing pathways during M. tuberculosis infection of human macrophages. Importantly, adapting a protocol to identify MHC antigens in the BSL-3 pathogen will be of use to several fields. However, the study could be further strengthened by improving the discussion of prior work in the ESX and MHC fields to strengthen the context of this work and clarify its contribution to the field, as well as considering potential weaknesses of the study.

Reviewer #2 (Public Review):

In this work Lemerle et al. provide long-awaited insight into how transverse tubules develop in skeletal muscle. Together with the sarcoplasmic reticulum transverse tubules form the triad, a specialized structure required for excitation-contraction coupling in skeletal muscle. Defects in transverse tubules or the triad can lead to problems such as muscular dystrophy. Whilst the involvement of specialist membrane structures (caveolae) and the membrane-bending protein Bin1 have long been recognized the precise mechanism of how caveolae and Bin1 cause transverse tubules to form and extend has remained unknown. This work provides compelling evidence, correlating antibody labelling with electron microscopy, to support the concept that caveolae rings form underneath the cell membrane which is surrounded by the endo/sarcoplasmic reticulum. These rings contain caveolin-3 and Bin1 and the authors show Bin1 enriched tubes extend from multiple points on these rings. Their data suggest that Bin1 assembles to initially form these scaffolds that then recruit the caveolae to form the ring. In addition, tubules appear continuous with the extracellular environment which is necessary for their function of facilitating calcium release during excitation-contraction coupling. In patients with mutations in caveolin-3 the caveolin ring formation as well as Bin1 tubulation were defective which may play a role in the pathology. The elegant experiments including time-lapse work clearly support the conclusions of the authors.

The ability of the authors to combine labelling studies with advanced microscopy to show the underlying structures provides very strong evidence for the proposed mechanisms. The authors suggest that the muscle-specific isoforms of BIN1 are key to tubule extension from caveolae rings but it would be interesting for them to discuss how this fits with studies suggesting that constitutive Bin1 isoforms can also form transverse tubules. It would also be interesting to understand the authors' views on whether caveolae rings are involved in the turnover of transverse tubules in adult myotubes as well as the initial formation and, additionally, if the caveolae rings are restricted to the region just under the surface membrane.

Insight into how transverse tubules are formed sets the groundwork for future therapies. This is clearly important for skeletal muscle myopathies but should also be considered in the heart. Cardiac transverse tubule loss and disorder play an important role in dysfunction in heart failure and atrial fibrillation and as such lessons learned in skeletal muscle may be successfully applied to the heart.

Reviewer #2 (Public Review):

During Influenza virus infection, newly synthesized viral ribonucleoproteins (vRNPs) form cytosolic condensates, postulated as viral genome assembly sites and having liquid properties. vRNP accumulation in liquid viral inclusions requires its association with the cellular protein Rab11a directly via the viral polymerase subunit PB2. Etibor et al. investigate and compare the contributions of entropy, concentration, and valency/strength/type of interactions, on the properties of the vRNP condensates. For this, they subjected infected cells to the following perturbations: temperature variation (4, 37, and 42{degree sign}C), the concentration of viral inclusion drivers (vRNPs and Rab11a), and the number or strength of interactions between vRNPs using nucleozin a well-characterized vRNP sticker. Lowering the temperature (i.e. decreasing the entropic contribution) leads to a mild growth of condensates that does not significantly impact their stability. Altering the concentration of drivers of IAV inclusions impact their size but not their material properties. The most spectacular effect on condensates was observed using nucleozin. The drug dramatically stabilizes vRNP inclusions acting as a condensate hardener. Using a mouse model of influenza infection, the authors provide evidence that the activity of nucleozin is retained in vivo. Finally, using a mass spectrometry approach, they show that the drug affects vRNP solubility in a Rab11a-dependent manner without altering the host proteome profile.

The data are compelling and support the idea that drugs that affect the material properties of viral condensates could constitute a new family of antiviral molecules as already described for the respiratory syncytial virus (Risso Ballester et al. Nature. 2021).

Nevertheless, there are some limitations in the study. Several of them are mentioned in a dedicated paragraph at the end of a discussion. This includes the heterogeneity of the system (vRNP of different sizes, interactions between viral and cellular partners far from being understood), which is far from equilibrium, and the absence of minimal in vitro systems that would be useful to further characterize the thermodynamic and the material properties of the condensates.

There are other ones.<br /> 1) The concentrations are mostly evaluated using antibodies. This may be correct for Cdilute. However, measurement of Cdense should be viewed with caution as the antibodies may have some difficulty accessing the inner of the condensates (as already shown in other systems), and this access may depend on some condensate properties (which may evolve along the infection). This might induce artifactual trends in some graphs (as seen in panel 2c), which could, in turn, affect the calculation of some thermodynamic parameters.<br /> 2) Although the authors have demonstrated that vRNP condensates exhibit several key characteristics of liquid condensates (they fuse and divide, they dissolve upon hypotonic shock or upon incubation with 1,6-hexanediol, FRAP experiments are consistent with a liquid nature), their aspect ratio (with a median above 1.4) is much higher than the aspect ratio observed for other cellular or viral liquid compartments. This is intriguing and might be discussed.<br /> 3) Similarly, the fusion event presented at the bottom of figure 3I is dubious. It might as well be an aggregation of condensates without fusion.<br /> 4) The authors could have more systematically performed FRAP/FLAPh experiments on cells expressing fluorescent versions of both NP and Rab11a to investigate the influence of condensate size, time after infection, or global concentrations of Rab11a in the cell (using the total fluorescence of overexpressed GFP-Rab11a as a proxy) on condensate properties.

Reviewer #2 (Public Review):

This interesting study looks into the evolution of putative spider venom toxins, specifically disulfide-rich peptides (DRPs). The authors use published sequence data to gain new insights into the evolution of DRPs, which are the major component of most spider venoms. Through a series of sequence comparisons and phylogenetic analyses they identify a substantial number of new spider toxin superfamilies with distinct cysteine scaffolds, and they trace these back to a primitive scaffold that must have been present in the last common ancestor of mygalomorph and araneomorph spiders. Looking at the taxonomic distribution of these putative venom DRPs, they conclude that mygalomorph and araneomorph DRPs have evolved in different ways, with the former being recruited into venom at the level of genera, and the latter at the level of families. In addition, they perform selection analyses on the DRP superfamilies to uncover the surprising result that mygalomorph and araneomorph DRPs have evolved under different selective regimes, with the evolution of the former being characterised by positive selection, and the latter by purifying (negative) selection.

However, I don't think that in the current state of the manuscript these conclusions are robustly supported for several reasons. First, it seems that not all previously published data were included in the phylogenetic analyses that were used to identify new superfamilies of DRPs. Second, much of the data were obtained from whole-body transcriptome data, which leaves a degree of uncertainty that these data indeed derive from the venom glands that produce the toxins. Third, the taxonomic representation of mygalomorph and araneomorph diversity in this study is so sparse that it becomes impossible to distinguish whether toxin recruitments have happened at the level of genera, families, or even higher-level taxa. Fourth, only a selection of DRP superfamilies was used for natural selection analyses, without the authors explaining how this selection was made. Yet, they attempted to draw general conclusions about toxin evolution in mygalomorphs and araneomorphs, even though most of the striking differences they found were restricted to just two mygalomorph genera, and one family of araneomorphs.

If these concerns are addressed this study can shed important new light on venom toxin evolution in one of the most diverse venomous taxa on Earth.

Reviewer #2 (Public Review):

The manuscript nicely describes the use of a humanized NSG mice HIV model that mimics HIV infection in humans. Using this model, the Authors were able to clearly illustrate substantial evidence of inflammasome activation in HIV infection. This was done via analysis of mRNA transcripts of proteins pivotal of NLRP3, IFI16, and AIM 2 inflammasome pathway activation, and also measurement of plasma level of various inflammatory cytokines via multiplex U-PLEX Biomarker assay kit. Furthermore, they elaborated clearly on the negative correlation between inflammasome activation and some inflammatory cytokines with the percentage of CD4 T cells. From this study, the increase in inflammasome activation contributed remarkably to CD4 T cell depletion, beginning from three days post infection and reaching the climax by day 28. Interestingly, the authors were able to elucidate a decrease in inflammasome activation and CD4 T cell depletion with the use of anti-caspase 1 inhibitor VX-765.

The kinetics of viremia and CD4 T cell depletion, as well as levels of HIV RNA expression in different compartments (Figure Suppl 1 and 2) was a clever illustration of HIV dissemination in early infection. Furthermore, the evaluation of gene expression in the different compartments (lung, bone marrow, lymph node, and spleen) using qPCR at different time points of the study was supportive at the molecular level of inflammasome activation in early HIV infection (Figure 1, Figure Suppl 3) gave more credibility to the study. it was interesting to see good illustrations of different effector molecules(cytokines) of inflammasome activation at different time points of the study. The choice of using an anti-caspase 1 inhibitor VX-765 in HIV infection was a smart idea to limit the inflammatory changes and CD4 T cell death in HIV infection. The graphs supported their claim as we could see a decrease IL1B, and IL18 (Figure 4) which are key effector molecules during inflammasome activation. They also showed a decrease in CD4 T cell depletion with VX-765 compared to the negative control (Figure 5).

Despite the novelty and strengths of the study, there were some weaknesses on the design of the study. The Authors explained well in the introduction the elimination of HIV reservoirs as a key factor for HIV cure. Also, the Authors reported anti-caspase 1 inhibitor VX-765 reduces HIV reservoirs. However, in the study the Authors did not quantify the different HIV reservoirs (For example Central memory and effector memory CD4 T cells) and the effect of VX-765 on the population of these HIV reservoirs Furthermore the expression of genes associated with inflammasome activation in HIV infection was well presented. However, there was no gene expression profiling after administration of the anti-caspase 1 inhibitor VX-765, which would have been a better method to evaluate the effect of the drug on inflammasome activation

Reviewer #2 (Public Review):

This study by Liu et al. investigates the mechanism that enables the Neurospora circadian clock to maintain robust molecular and physiological rhythms under conditions of nutrient stress. The authors showed that the nutrient-sensing GCN2 signaling pathway is required to maintain robust circadian clock function and output rhythms under amino acid starvation in the filamentous fungus Neurospora. Specifically, they observed that under amino acid starvation conditions, knocking out GCN2 pathway components GCN4 (CPC-1) and GCN2 (CPC-3) severely disrupts rhythmic transcription of core clock gene frequency (frq) and clock-regulated conidiation rhythm. They provided data to indicate that the observed disruptions are due to reduced binding of the White Collar (WC) complex to the frq promoter stemming from lower histone H3 acetylation levels. This prompted the authors to propose a model in which GCN2 (CPC-3) and GCN4 (CPC-1) are activated upon sensing amino acid starvation, recruit GCN-5 containing SAGA acetyltransferase complex to maintain robust histone acetylation rhythm at the frq promoter. They then performed a battery of assays to show that both GCN-5 and ADA-2 are necessary for maintaining robust H3ac, frq mRNA, and conidiation rhythms under normal conditions. To support that low H3ac level at the frq promoter is the cause for impaired WC binding and frq transcription, they demonstrated they can partially rescue the observed rhythm defects of the knockout mutants under amino acid starvation using an HDAC inhibitor. Finally, the authors used RNA-seq to identify genes and pathways that are differentially activated by GCN4 (CPC-1) under amino acid starvation conditions. Many of these genes are involved in amino acid metabolism and they showed that 3 of them exhibit rhythmic expression in WT but low and non-rhythmic expression in the CPC-1 KO strain.

Strength: The 24-hour period length of the circadian clock is known to be stable over a range of environmental and metabolic conditions because of circadian compensation mechanisms. Whereas temperature compensation (maintenance of circadian period length over a physiological range of temperature) has been studied extensively in multiple model organisms, the phenomenon of nutritional compensation and its underlying mechanisms are poorly understood. This study provides new insights into this important yet understudied area of research in chronobiology. In addition to advancing our understanding of fundamental mechanisms governing clock compensation mechanisms, this study also adds to our understanding of metabolic regulation of rhythmic biology and the relationship between nutrition and healthy biological rhythms. Given that the GCN2 nutrient-sensing pathway is broadly conserved beyond Neurospora, findings from this study will likely be relevant to other eukaryotic systems.

The authors provided strong evidence supporting their claims that the GCN2 signaling pathway is important for maintaining the robustness of the Neurospora clock under conditions of amino acid starvation. The authors performed parallel experiments in normal (no 3-AT) vs amino acid-starved conditions (+3-AT). Their observations of relatively minor disruptions of molecular and conidiation rhythms in cpc-3 and cpc-1 KO strains in normal nutrient conditions compared to starvation conditions support their model that sensing of amino acid starvation by GCN2 pathway-induced changes at the chromatin and transcriptional level that are necessary to maintain a robust frq oscillator. Without the comparison between normal vs amino acid starved conditions, this part of their model will not be as strong.

Previously Karki et al. (2020) showed that rhythmic activation of GCN2 kinase is regulated by the clock, resulting in clock-control rhythmic translation initiation. This study uncovers an additional mechanism through which GCN2 pathway modulates circadian rhythms by regulating histone acetylation of rhythmic genes. RNA-seq as described in Figure 7 provides some potential targets.

Weakness:<br /> (1) The authors propose a model (Figure 8) in which the GCN2 pathway is activated by amino acid starvation and recruits the SAGA complex to promote histone acetylation level at the frq promoter. There is however no data in this study showing that the GCN2 pathway is activated in amino acid-starved conditions, only that it is required to maintain robust frq and conidiation rhythms. The authors should clarify how they are defining "activation of the GCN2 pathway" in this study. For example, is it recruitment of GCN-5 and SAGA complex to frq promoter?

(2) The experiments to examine the involvement of GCN-5 and ADA-2 were performed in normal conditions (no amino acid starvation). Unlike cpc-1 and cpc-3 KO strains, gcn-5 and ada-2 KO strains showed severely disrupted frq rhythms in normal nutrient conditions, suggesting they are normally required for robust circadian rhythms. If GCN-5 and the SAGA complex are normally involved in regulating H3ac rhythms in the frq loci, how does GCN2 pathway modulates the activity of GCN-5 and SAGA complex in conditions of amino acid starvation? Are the interactions between GCN2/4 with GCN-5 and SAGA complex different in normal vs amino acid starved conditions? The authors should clarify their model.

(3) Given that the GCN2 pathway is important for nutrient sensing, the authors should not disregard the alternative hypothesis that the GCN2 pathway may be important for nutrient compensation and plays a role in maintaining the robustness of rhythms in a range of nutrient conditions.

(4) The authors should use circadian statistics to compute the phase and amplitude of the mRNA, DNA binding of the WC complex, and H3Ac rhythms. This will allow them to compare between rhythms and provide statistical significance values, rather than just providing qualitative descriptions. This will be valuable when comparing rhythms between strains and between nutrient conditions.

Reviewer #2 (Public Review):

This article aims to extend human disease-related studies of PLA2G6 from fly models to iPS-neurons, mouse models, to look for drugs that suppress phenotypes and test them, and to attempt AAV whole body rescue. Generally, each of these questions/aims/experiments is excellent, but as presented, it's a bit of an underdeveloped hodgepodge of results, with each experiment somewhat underdeveloped or analyzed for the respective phenotype, in my opinion. I think the general thrust of the experiments is excellent. But the data are relatively cursory in many instances. Further development and characterization of the phenotypes would require quite a bit of work but vastly improve the paper.

Reviewer #2 (Public Review):

This study utilizes extensive molecular dynamics simulations to probe the binding of a widely-used myosin II inhibitor to several closely-related myosin isoforms. The authors focused on so called 'cryptic' drug binding site, which is not apparent in isolated 'apo' states of the proteins, but are unveiled in simulations. The probability of unveiling these sites was implicated as the factor that distinguished myosins that bind blebbistatin from those that do not. Importantly, they focus on targetting an allosteric site, which can circumvent issues with targeting the binding site of the cognate ligand that can lead to nonselective binding in other targets. These simulations were accompanied by markov state model decompositions of those trajectories to isolate states conducive to drug binding, which were assessed using molecular docking to yield aggregated drug binding free energies. To demonstrate the reliability of their model, they performed a blinded prediction for an as-of-then uncharacterized myosin variant and found strong agreement with experimentally measured affinity (micromolar). Another finding of note includes identifying the ADP/Pi-bound myosin state as the preferred conformation for blebbistatin, which is line with the drug's inhibition of myosin ATPase activity.

Strengths:<br /> This study is impactful for several reasons.  Firstly, the authors provide a molecular basis for the allosteric inhibition of myosin II by blebbistatin, through extensive GROMACS molecular dynamics simulations.   They implicate a cryptic binding site that is obscured in apo state structures of the enzyme, for differences in the ligand's affinity measured for several myosin proteins. Their simulations indicate that the binding site spontaneously opens for apo state myosin isoforms that are inhibited by blebbistatin, but remains closed for other myosins. Moreover, they discovered that the drug's apparent affinity is proportional to the probability of forming the open conformation of the cryptic binding site in the apo state structure. This knowledge is important for guiding selective drug development, because there is generally lesser conservation in allosteric binding sites, e.g. off-target binding is less likely, relative to the primary site for endogenous ligands that are shared for homologous proteins.  In addition, they used Markov State Models (MSMs) to identify protein conformational states that are conducive to ligand binding, to which they docked blebbistatin using Autodock Vina. The predicted drug affinities for each state in the MSM ensemble were weighted according to the state's probability, which yielded an aggregate estimate of drug affinity that strongly agreed with experimental data. To further establish the approach's validity, the modeler co-authors predicted the affinity for blebbistatin binding to a myosin protein that had not yet been characterized. The predicted affinity was also found to be in very good agreement with the affinity ultimately reported by the experimentalist co-authors.  Overall, this is a strong computational approach applied to a drug/target interaction that is invaluable to the research and clinical community. The researchers' claims are well-supported by the provided data.

Weaknesses<br /> A prominent limitation in the study is that the contributions of entropy in their `multi-state' ligand binding model is not apparent - at the very least I would anticipate an entropic contribution from the states identified from the MSM characterization of the apo myosin simulations. Relatedly, the docking scores likely account for changes in ligand entropy upon binding, but it is unlikely that the 3 structures selected from each MSM state would be sufficient to describe the protein disorder within the state.  This limitation does not impact the novelty of the study, but is rather an opportunity to discuss extension of the method in future applications. Additionally,  by design the myosins used for the study shared 90% or greater sequence identity. On one hand, this is a great set for testing the limits of predicting selectivity. On the other hand, it would be helpful to know how the approach might work for myosins with lower homology but very similar tertiary structures. Would there still be a cryptic site amenable to drugging, and if so, would its open probability necessarily scale with ligand binding affinity? On a related note, would this approach perform best for well-buried ligand binding domains, or could it also be expected to perform well for more surface exposed sites or those with extensive loops?

It is expected that this work will be impactful to the scientific community on two fronts. The first of which is establishing a molecular mechanism of selective myosin inhibition, which will be invaluable for drug design efforts targeting the myosin II cardiac isoform in particular. The abundance of ATPases and ATP-responsive proteins in cardiac tissues renders difficult the task of designing molecular species that competitively bind to the ATP pocket - targeting an allosteric site with lesser homology across isoforms is a compelling alternative. The use of markov state models with standard docking techniques to improve binding free energy estimates among closely related proteins has the potential to be broadly used by the computer aided drug design community. The potential for widespread adoption is tempered by the authors' use of a specialized resource, folding at home, to achieve millisecond-length simulations. Enhanced sampling techniques, however, may yield similar results with smaller simulation requirements.

Reviewer #2 (Public Review):

In this manuscript the authors explain in greater detail a recent testis snRNAseq dataset that many of these authors published earlier this year as part of the Fly Cell Atlas (FCA) Li et al. Science 2022. As part of the current effort additional collaborators were recruited and about 6,000 whole cell scRNAseq cells were added to the previous 42,000 nuclei dataset. The authors now describe 65 snRNseq clusters, each representing potential cell types or cell states, including 43 germline clusters and 22 somatic clusters. The authors state that this analysis confirms and extends previously knowledge of the testis in several important areas.

However, in areas where testis biology is well studied, such as the development of germ cells from GSC to the onset of spermatocyte differentiation, the resolution seems less than current knowledge by considerable margins. No clusters correspond to GSCs, or specific mitotic spermatogonia, and even the major stages of meiotic prophase are not resolved. Instead, the transitions between one state and the next are broad and almost continuous, which could be an intrinsic characteristic of the testis compared to other tissues, of snRNAseq compared to scRNAseq, or of the particular experimental and software analysis choices that were used in this study.

A goal of the study was to identify new rare cell types, and the hub, a small apical somatic cell region, was mentioned as a target region, since it regulates both stem cell populations, GSCs and CySCs, is capable of regeneration, and other fascinating properties. However the analysis of the hub cluster revealed more problems of specificity. 41 or 120 cells in the cluster were discordant with the remaining 79 which did express markers consistent with previous studies. Why these cells co-clustered was not explained and one can only presume that similar problems may be found in other clusters. Indeed, many other indications of specificity issues were described, including contamination of fat body with spermatocytes, the expression of germline genes such as Vasa in many somatic cell clusters like muscle, hemocytes, and male gonad epithelium, and the promiscuous expression of many genes, including 25% of somatic-specific transcription factors, in mid to late spermatocytes. The expression of only one such genes, Hml, was documented in tissue, and the authors for reasons not explained did not attempt to decisively address whether this phenomenon is biologically meaningful.

A truly interesting question mentioned by the authors is why the testis consistently ranks near the top of all tissues in the complexity of its gene expression. In the Li et al. (2022) paper it was suggested that this is due an inherently greater biological complexity of spermiogenesis than other tissues. It seems difficult to independently and rationally determine "biological complexity," but if a conserved characteristic of testis was to promiscuously express a wide range of (random?) genes, something not out of the question, this would be highly relevant and important.

Unfortunately, the most likely problems are simply technical. Drosophila cells are small and difficult to separate as intact cells. The use of nuclei was meant to overcome this inherent problem, but the effectiveness of this new approach is not yet well-documented. Support for the view that the problems are mostly technical, rather than a reflection of testis biology, comes from studies of scRNAseq in the mouse, where it has been possible to resolve a stem cell cluster, and germ cell pathways that follow known germ cell differentiation trajectories with much more discrete steps than were reported here (for example, Cao et al. 2021 cited by the authors).

The conclusions that were made by the authors seem to either be facts that are already well known, such as the problem that transcriptional changes in spermatocytes will be obscured by the large stored mRNA pool, or promises of future utility. For example, "mining the snRNA-seq data for changes in gene expression as one cluster advances to the next should identify new sub-stage-specific markers." If worthwhile new markers could be identified from these data, surely this could have been accomplished and presented in a supplemental Table. As it currently stands, the manuscript presents the dataset including a fair description of its current limitations, but very little else of novel biological interest is to be found.

In sum, this project represents an extremely worthwhile undertaking that will eventually pay off. However, some currently unappreciated technical issues, in cell/nuclear isolation, and certainly in the bioinformatic programs and procedures used that mis-clustered many different cells, has created the current difficulties. Most scRNAseq software is written to meet the needs of mammalian researchers working with cultured cells, cellular giants compared to Drosophila and of generally similar size. Such software may not be idea for much smaller cells, but which also include the much wider variation in cell size, properties and biological mechanisms that exist in the world of tissues.

Reviewer #2 (Public Review):

Summary:

This manuscript will be of interest for investigators in the field of development and the biology of pregnancy. The major strengths of the data are the detailed description of a hypoxia-induced mouse model of fetal growth restriction, where phenotypes, tissue histology, MRI images and metabolic analysis combine to characterize the experimental system. The data seem descriptive and preliminary, and the comparison to human pregnancy is neither supportive nor rigorous.

Strengths:

• The mouse pregnancy has been used by the authors and by others as a model for placental insufficiency. The manuscript provides incremental data to characterize hypoxia-induced fetal growth restriction<br /> • The 15.2T MR imaging technology is high quality and informative, even if the results did not reveal marked changes.<br /> • The detailed characterization of BPGM expression in the apical mouse placental surfaces is valuable.<br /> • The provided model may be useful for future studies by the authors.

Weaknesses<br /> • The metabolic analysis was restricted to one enzyme and metabolite. Placental analysis of 2,3-BPG and BPGM were already published (ref 29-30). At best, if the 2,3 BPG is related to the phenotype, it night be interpreted as a part of the injury in human cases, and adaptive response in the mouse models (as the authors suggested lines 286-288 and 332-336.). However, these assumptions are not tested.<br /> • The human cases are not very informative. The causes of FGR were not known, but clearly (Table 1) not analogous to that of the mouse model. Systemic hypoxia in humans might have been more informative. In its absence, the value of cross-species comparison is low.<br /> • While the provided experiments are of good quality, the approach is very descriptive and not advancing mechanistic understanding of FGR-related placental insufficiency.

Reviewer #2 (Public Review):

In this manuscript, a drug discovery pipeline was developed using a human iPSC derived organoid-based high-throughput screening platform to be used to identify drug candidates for maintaining photoreceptor survival in LCA10 retinopathies. Reserpine proved effective in patient organoids and in mutant mouse retina in vivo to improve photoreceptor survival and outer segment structure. Protein homeostasis was restored after reserpine treatment by increasing p62 levels, decreasing the 20S proteasome, and increasing proteasome activity. The manuscript is clearly written, contains a large amount of valuable and high-quality data and demonstrates that rebalancing proteostasis can stabilize photoreceptor overall homeostasis in the presence of a mutation that causes retinal degeneration.

The manuscript may lack functional in vivo data on the treatment by reserpine in RD16 mice such as ERG measurements or other functional tests (the authors also refer to it as future direction). Nevertheless, in my view, the study provides a solid and convincing set of data and substantially advances our understanding on the neuroprotective effects of reserpine beyond the scope of the retina and therefore can be expected to have widespread influence on a readership interested in the principles of neuroprotection rebalancing proteostasis.

Reviewer #2 (Public Review):

This manuscript describes the first human subject with a demonstrated recessive pathogenic variant of MCAT. Analysis of cells from this subject in general showed similar abnormalities as previously demonstrated for MCAT deficiency in the mouse. This includes combined oxidative phosphorylation deficiency. The hypothesis that MCAT deficiency causes lowering of co-factor lipoate was tested, as PDH and other enzymes require this for function. However, no evidence for this concept was observed.

Reviewer #2 (Public Review):

In this study, the authors follow up on their previous work demonstrating that NLRC4-deficient mice are susceptible to shigellosis and therefore can be used as a model to dissect immune control of infection in a tractable animal host (Mitchell & Roncaioli et al. 2020). This is therefore the first direct, mechanistic study on other immune pathways that contribute to protection of the host from Shigella in vivo. Importantly, the authors report that epithelial cell death is a critical protective mechanism against Shigella infection, and differences in the ability of the bacteria to antagonize host cell death explains in part why humans are susceptible while mice are resistant to infection.

Strengths

The authors use elegant genetic approaches to investigate the roles of distinct cell death pathways in anti-Shigella defense. The evidence presented convincingly shows that caspase-1, caspase-11, and caspase-8 mediate a hierarchy of protection against Shigella infection. The authors additionally show that the Shigella effector OspC3 drives colonization and infection by blocking caspase-11 function, which is, to this reviewer's knowledge the first demonstration that OspC3 facilitates infection in vivo. Overall, this is an important study and the work will have a large impact on the field by building a foundational understanding of the in vivo immune response against Shigella.

Weaknesses

A major limitation of the current study is absence of direct evidence that cell death within the intestinal epithelium is responsible for the loss of bacterial control. TNF is a pleiotropic cytokine that regulates cell death as well as inflammatory/antimicrobial gene expression. Similarly, caspase-8 has been found to also regulate inflammatory gene expression independent of its cell death functions. The authors propose that caspase-11 and caspase-8 contribute to protection from infection by driving epithelial cell death and extrusion. While this interpretation is supported by studies implicating cell death in eliminating the Shigella replicative niche, a formal demonstration that caspase-11 and TNF⍺/caspase-8 contribute to epithelial cell death in response to Shigella infection in vivo would strengthen the conclusions of the paper.

Furthermore, the claim that TNF⍺/caspase-8 signaling mediates protection against Shigella by driving cell death and not by NF-kB activation may be overstated, based on the evidence presented. While the work demonstrates that there is no difference in inflammatory cytokines in the Casp1/11/8/Ripk3 mice, this interpretation is less straightforward in a setting where there is substantially more CFU. Nonetheless, the study is overall very strong, and this point could be addressed experimentally or by modification to the text that would acknowledge this possibility.

Reviewer #2 (Public Review):

The aim of the present work was to find physiological mechanisms for the phenomenon of "latent inhibition" in honey bees. To achieve this goal, the authors have very successfully combined different population genetic, behavioral pharmacological, and electrophysiological methods. From my point of view, the experiments were mostly carried out accurately, but some aspects of the methods used should be described more fully and/or justified. With the identification of the tyramine receptor AmTYR1 as an important mediator of latent inhibition, the goal was achieved. In any case, the work should stimulate investigation of whether the orthologous receptor of the fruit fly Drosophila has comparable functions in this model organism. Thus, in the future, the more powerful genetic tools of this alternative model organism could be used. So far, only dopamine receptor pathways have been associated with latent inhibition in Drosophila. Comparisons with the mechanisms of latent inhibition in vertebrates are now also possible.

Reviewer #2 (Public Review):

The manuscript sets out to explain how the large micro-diversity of closely-related microbial strains might be produced and maintained. It proposes a scenario of spatiotemporal chaos, in which interactions between strains drive large changes in the relative abundances; space helps strains survive by migration between islands, and evolution produces new strains. The work presents a mathematical framework and discusses its biological relevance, and then examines its outcomes through a combination of simulations and mathematical analysis.

An important main result is that, under certain conditions, the diversity (number of extant strains) can grow continually and indefinitely. It is presented through simulations and then analyzed theoretically. Much of the work goes into understanding this increase in diversity, and the conditions required for it to happen. In particular, the effects of the distribution of mutant fitnesses, and of correlations between mutant and parent are examined.

This main result represents a significant conceptual advance on a central question in ecology. It is of broad interest in the field of ecology and evolution, likely to generate significant interest and lead to future work in a number of directions.<br /> The simulations strongly support the results. The mathematical analysis provides significant insight into phenomenology. It also develops tools that are of interest in their own right.

In tackling this difficult and general question, the authors must make simplifying assumptions in the modeling.<br /> The theoretical model does not assume the existence of niches (in the form of significant differences between inter- and intra-species interactions), or fine-tuned tradeoffs except as they may emerge from the evolutionary process. That such assumptions are not made is very appealing for microbial ecology.<br /> The interactions between species are taken to be anti-symmetric or close to that, as in predator-prey interactions. The authors motivate this assumption by bacteria-phage interactions. As the authors note, in a community with many strains of both bacteria and phage, the interactions are also expected to have a block structure, with different interactions between and within each group. This additional block structure could potentially have a significant effect on phenomenology. It is not implemented in the present work and is only briefly discussed in the Discussion section, referring to unpublished work-in-progress.

Reviewer #2 (Public Review):

The dinosaur literature from the 1970s through 1990s is rife with claims purporting to have identified sexual dimorphism in the skeletons of dinosaurs. Mallon (2017) penned a critical review of these claims and showed that nearly all of them are without statistical support. He also suggested some more appropriate methods that might be fruitfully applied to the matter. This contribution from Pintore et al. heeds Mallon's prior recommendations and, I think, fairly convincingly demonstrates the existence of sexual dimorphism in the femora of the ornithomimosaurs they investigated. Their argument is bolstered by the numerous examples they cite of similar dimorphism seen in the femora of various tetrapod groups. I believe this manuscript holds much merit.

Reviewer #2 (Public Review):

In this paper, the authors developed a new device for online decoding of position based on calcium imaging in freely moving rodents. This device could be used in the brain-computer interface to investigate neurofeedback-based therapies for neurological disorders. The technical part is properly done and gives convincing results that can be truly helpful for the scientific community using the miniscope. Nevertheless, as a methodological article, there should be more details regarding the accuracy of the decoding and of the different steps to follow if someone wants to use their methodology. Moreover, a true online real-time experiment should be performed to validate the device.

Please find below my comments:

- From what I read the authors did not perform a true real-time experiment. I think this step is crucial to ensure the quality of their device.

- There should be a validation against a classical offline Bayesian decoding.

- "To mimic these steps using the virtual sensor in our performance tests, one session of image data was collected and stored from each of the 13 rats, yielding ~7 min (8K-9K frames) of sensor and position tracking data per rat. The linear classifier was then trained on data from the first half of each session and tested on data from the second half." This sentence is not clear enough. The authors should clearly describe the exact time needed for each experimental step. What is the time needed for instance for the experimental step 2, during which the linear classifier is trained to decode behavior from the initial dataset? This is crucial information if someone wants to use this device. How the accuracy varies with the duration (or the quality) of the initial dataset? It is important that the authors provide an investigation of this to validate their device.

- For instance, what is the decrease in decoding accuracy 1) with fewer place cells? What is the approximative number of place cells to obtain reliable decoding? 2) with the duration of the initial recording session. Here it seems to be of the order of 3-4 min. What if the recording session is shorter? Is there some constraint about this recording session (in terms of speed, stops, etc...) to obtain good decoding? 3) Is there a link between the decoding accuracy and the number of place cells nearby?

- The authors specified the time delay of 2.5ms for their device. Yet, it is pointless regarding the purpose of the decoding. The important information is the precise position of the animal when the device is used to trigger a stimulation at a given location. Again, a true online experiment should be done to validate that a TTL can be triggered by the device at a precise location (with a quantification of the error made).

- There is no information on the accuracy of the decoding with respect to the location in the linear track. It is likely that the extremities of the linear track will be better identified. Figure 4C does not provide a clear description of the error made. The choice of D=2 (which seems to represent the spatial bin) is not justified. Two spatial bins seem to represent +/-40 cm which is quite large.

- The movement artefacts are not equally observed in the maze. The way they are corrected might be captured by the linear decoder. These artefacts might have a strong influence on the decoding. Please provide a quantification of the correction made during steps 1 and 2 in relation to the position of the animal on the linear track. The authors should provide a correlation between the presence of these corrections with the decoding accuracy.

- Besides the methodological part, I have some physiological questions. It is quite common in linear tracks to have bi-directional and unidirectional place cells. Is it the case here? How many? It is difficult to see this in figure C. Is there an error due to the online decoding of the position in the two directions of the linear track?

Reviewer #2 (Public Review):

Periodontal inflammation is a very common disease and constitutes a challenge for public health. Healing of periodontal tissue after an acute or chronic inflammation remains to be very difficult, if not possible. Although MSCs were known to be present and support periodontal physiological turnover, periodontal tissue hardly regenerates after the inflammation process. Therefore, learning the difference between periodontal MSCs under physiological or inflammation conditions is a fundamental issue. Due to the technical challenges, a comprehensive single-cell Seq analysis on periodontal tissue has never been performed. The current study made the first breakthrough on this issue.

Overall, the manuscript provides important information on the response of periodontal tissue towards acute inflammation.Additional experiments are needed to support their major conclusions.

Reviewer #2 (Public Review):

The work presented aims at analyzing the effect of the loss of function of WFS1, the gene responsible for Wolfram syndrome, in visual physiology. They analyzed the vision of knock-out mice and deciphered the potential altered signaling pathways using transcriptomics and proteomics approaches. Interestingly, they identified monocarboxylate transport isoform 1 and its partner Basigin as downregulated proteins. In addition, they demonstrated that excessive neuroinflammation may contribute to the observed phenotype. These data add, in an interesting way, a novel pathophysiological mechanism leading to Wolfram syndrome.

Reviewer #2 (Public Review):

This study systematically integrates multi-omics (plasma lipidomic and metabolomic, and fecal 16s microbiome) data to identify the metabolic at-risk profiles within people living with HIV on antiretroviral therapy (PLWHART). As a result, three groups of PLWHART (SNF-1 to 3) were identified, which showed distinct phenotypes. Such insights cannot be obtained by a single type of omics data or clinical data, and have implications in personalized medicine and lifestyle intervention. Connecting the findings in this study with specific medical/clinical insights is the next challenge.

Reviewer #2 (Public Review):

The major strengths of the manuscript are 1) the widely used mouse model, 2) the extensive analysis of transition metals other than iron, 3) the molecular data providing evidence for the cellular effects of excess iron accumulation on gene expression and protein levels, and 4) the phenotypic and lifespan data in animals treated with diet manipulations.

The major weakness of the manuscript is the lack of a link between the iron status of individual animals and their behaviors. The authors attempt to correlate molecular and behavioral parameters in Figure 5C, but the strength of this analysis (sample size and resolution) is modest.

The conclusions are entirely justified by the data. Moreover, this study opens several questions that, if answered, would potentially have a major impact on mitochondrial disease research. As the authors note, whether patients with different genetic defects affecting the OxPhos complexes exhibit iron excess, and whether this is detectable in the blood or other biofluid is an important question.

Reviewer #2 (Public Review):

In this manuscript by Seroussi et al, the authors describe a global analysis of Argonaute (AGO) protein biology in the model organism C. elegans. Small RNAs regulate most facets of gene expression and, therefore, play important roles in all aspects of biology, including development and health. C. elegans has been at the forefront of attempts by biologists to understand the biological roles played by AGOs and small RNAs in animals. Here, the authors make a significant contribution to this effort by epitope tagging all 21 of the elegans AGO genes. The reagents they generate allow the authors to explore at a global level the where, when, and why of C. elegans AGOs. Whenever possible the authors confirm that their tagged proteins are functional. The authors then analyze the expression patterns of elegans AGOs, sequence small RNAs that associate with these AGOs, and identify small RNA populations that change in animals lacking the AGOs.

In many cases the data presented are consistent with previously published studies, establishing that the author's approach was likely successful. In other cases, the data allow the authors to make novel observations. For instance, the authors categorize the 21 AGOs into four major categories- based on their small RNA binding profiles. They define the types of genomic loci targeted by each group of AGOs and show that these AGO groups regulate distinct classes of transposable elements, such as DNA cut-and-paste transposons, LTR retrotransposons, and Rolling transposons. This differential targeting suggests that sequence features intrinsic to each target transcript may help direct different RNAs into different silencing pathways. A metagene analysis defines differences in the 3' and 5' distribution of small RNAs across target genes for each AGO. These patterns are likely to have important implications for understanding RdRP function. The authors identify an AGO, which they name VSRA-1, which binds broadly to most classes of small RNAs. This data is likely to be an important step towards understanding how different AGOs bind different small RNAs. The authors present evidence that they have identified ten new miRNAs. The low expression levels of these miRNAs suggest that additional work is needed to ensure that these miRNAs have a biological function. The authors show that miRNAs with higher precursor duplex complementarity are preferentially loaded into the AGO RDE-1. This observation has important implications for miRNA evolution. The authors identify several hundred new candidate piRNAs as well as reclassify many mis-annotated miRNAs as piRNAs. Finally, the authors link several AGOs to interesting phenotypes, such as germ cell immortality and innate immunity.

The paper is very well written. No small accomplishment given the huge amount of data presented. As far as I can tell, experimental approaches and statistical analyses follow best practices. Alternative explanations for data are usually acknowledged. In summary, the paper provides novel insights into small RNA biology (described above), establishes high-quality reagents that will empower future studies into the myriad of ways that C. elegans use small RNAs to regulate gene expression, and demonstrate quite clearly that the C. elegans small RNA systems are intertwined and remarkably complex.

Reviewer #2 (Public Review):

This paper examined the effects of sertraline alone and with standard TB drugs in a variety of cell culture and animal models. The main finding was a reduction in CFU counts in the models. This may be of interest to the field generally.

Reviewer #2 (Public Review):

Nociception is an essential sense to detect threats to bodily integrity, and nociceptive behavior is essential to deal with such threats adaptively to minimize actual harm. Intuitively, these processes might be regarded as hard-wired, and so the choice of topic of the present paper, namely the way nociceptive behavior can be MODULATED, is a strength. Also, a strength is the most elegant use of a wide range of suitable methods.

Weaknesses are a lack of proper genetic controls for leaky transgene expression in some of the experiments, and what appears to be an incomplete discussion of results that, as the authors acknowledge, are unexpected or seemingly contradictory.

Reviewer #2 (Public Review):

This paper has huge potential for influencing the way we think about bats as foragers. But, I think that it can be improved.<br /> Specifically, there is no clearly articulated hypothesis underlying the work. Second, there should be specific testable predictions arising from the hypothesis. This change, while relatively minor, will vastly improve the focus of the work, and hence its impact on the reader.

Reviewer #2 (Public Review):

This is a highly interesting paper that provides important insights into the understanding of how HC-derived osteoblasts contribute to trabecular bone formation. Using single-cell transcriptomics, the authors found that HC descendent cells activate MMP14 and the PTH pathway as they transition to osteoblasts in neonatal and adult mice. They further demonstrate that HC lineage-specific Mmp14 null mutants (Mmp14ΔHC) produce more bone. By performing a panel of elegant in vitro studies, the authors show that MMP14 cleaves the extracellular domain of PTH1R, dampening PTH signaling. The authors provide more in vivo evidence showing that HC-derived osteogenic cells respond to PTH which is enhanced in Mmp14ΔHC. Generally, this is a very well-performed study that may contribute important novel aspects to the field.

I have the following issues for the authors to address:

1. The novel mechanism identified in this study (i.e. MMP14-induced PTH1R cleavage) is intriguing. It is unclear how specific this pathway is in the transition of HCs to osteoblasts. Are other MMPs besides MMP14 involved in the PTH1R cleavage? Is PTH1R the only substrate of MMP14?<br /> 2. Would it be possible for the authors to detect the truncated PTH1R fragment(s) from the conditioned medium prepared from either 293T or osteoblast culture?<br /> 3. The finding that HC-descendants persist and contribute to the anabolic response to PTH in aged mice is interesting. Have the authors examined the changes in MMP14 expression in bone with age and in response to PTH treatment?

Reviewer #2 (Public Review):

The human cerebellum likely has a significant but understudied contribution to cognition and behavior beyond the motor domain. Clarifying its functional relationship with the cerebral cortex is a critical detail necessary for understanding cerebellar functions. This paper addresses this challenge by testing three simple but intuitive models: winner-take-all, one-to-one model versus two converging input models. Results showed that the convergence model outperformed the one-to-one mapping model, indicating that cerebellar regions received multiple converging inputs from the different cortical regions. Overall the paper is well-written, and the results are clean and interesting. The methodological rigor of using cross-validation and generalization is also a strength of this paper.

The authors concluded that some cerebellar regions receive converging inputs from multiple cortical regions because the Ridge and Lasso models outperformed the WTA model. The WTA model has a fixed diagonal pattern, in contrast, Ridge/Lasso models included more weights in the connectivity matrix. Considering what's being estimated in this matrix, then perhaps the findings are not surprising because even after penalizing and regularization, the ridge regression models are still more complex than the WTA model (more elements are allowed to vary). In other words, Lasso/Ridge models allow more variables from the X side to explain variances in Y, similar to how throwing in more regressors can always improve the R square. I am unsure if cross-validation mitigates this issue. It would be more straightforward for the authors to compare model performance in a way that controls for the number of variables in the Ridge/Lasso models.

The authors did an excellent job reviewing the anatomical relationship between the cerebral cortex and the cerebellum. There are several issues that the authors should address in the introduction or discussion. First, if the anatomical relationship between the cerebellum and the cortex is closed-loop as suggested in the intro, then how convergence can arise from multiple cortical inputs given there is no physical cross-talk? Second, there are multiple synapses connecting a cerebellar region and the cortex, and therefore could integration occur at other sites but not the cerebellum? For example, the caudate, the thalamus, or even the cortex (integrating inputs before sending to the cerebellum)?

The dispersion metric quantifying the spread level in cortical inputs is interesting. Could the authors expand this finding and show anatomically what the physical spread is like in cortical space? The metric is novel but hard to interpret. A figure demonstrating the physical spread in the cortex should help readers interpret this result.

At the end of the discussion section, the authors discussed how results are more likely driven by cortical inputs to the cerebellum but not the other way around. This interpretation is likely overstated given the hemodynamic blurring and low temporal resolution of BOLD. Without a faster imaging sequence and accurate models that account for differences in hemodynamic properties, the more parsimonious interpretation is results are driven by bidirectional cortico-cerebellar interactions. The results are still very interesting without this added nuisance.

Reviewer #2 (Public Review):

The thrombopoietin receptor (TpoR) regulates stem cell proliferation, platelet production, and megakaryocyte differentiation. Past cell biology and biophysical studies have established that ligand-induced dimerization constitutes the mechanism of activation of TpoR. Specifically, ligands bind to the extracellular domain of TpoR and generate an allosteric response that is transmitted to the transmembrane domain, activating downstream signaling. However, up to now the molecular details of how the allosteric signals are transmitted to the intramembrane domains have been elusive. In this manuscript, Constantinescu and co-workers combined NMR, in vitro, and in vivo assays to investigate the activation and oncogenicity of TpoR. The authors concluded that the unwinding of the juxtamembrane domain is the main structural event that determines TpoR activation and regulates oncogenicity. The solid-state NMR studies were carried out in lipid membranes with polypeptides spanning the juxtamembrane and transmembrane residues. The authors show a series of spectra of 13CO resonances that encompass the juxtamembrane domain that is diagnostic of a structural transition from a helical conformation to a partially disordered state. The unwinding of the helical juxtamembrane domain was confirmed by site-specific mutations in this region. The chemical shift changes clearly indicate the transition from order to disorder (and vice versa) for selected sites. These conclusions are compounded by INEPT-type experiments that detect the most dynamic region of polypeptides. To rationalize the molecular mechanism for activation, the authors also used Ala-Ala insertions at strategic positions along the transmembrane domain. These experiments showed that the specific orientation of the transmembrane residues is central for TpoR activation, and a slight rotation of the helix is critical for activation of the receptor. Transcriptional activity assays confirm the importance of the proper orientation of the transmembrane domain for receptor activation.

Overall, I believe the data are solid, and both biophysical and cell biology studies support the conclusions of the authors. These new findings represent a significant advancement in understanding cytokine receptor activation.

Reviewer #2 (Public Review):

The acrosome is a unique sperm-specific subcellular organelle required for the fertilization process, and it is also an organelle undergoing extensive morphological and structural transformation during sperm development. The mechanism underlying the extensive acrosome morphogenesis and biogenesis remains incompletely understood. Xu et al in their manuscript entitled "The Slingshot phosphatase 2 is required for acrosome biogenesis during spermatogenesis in mice" reported that the Slingshot Phosphatase 2 is essential for acrosome biogenesis and male fertility through their characterization of spermatogenic and acrosomal defects in Ssh2 knockout mice they generated. Specifically, the authors provided molecular, genetic, and subcellular evidence supporting that Ssh2 mutation impaired the phosphorylation of an acting-binding protein, COFILIN during spermiogenesis and accordingly actin cytoskeleton remodeling, crucial for proacrosomal vesicle trafficking and acrosome biogenesis.

Strengths:<br /> Nicely written manuscript, addresses an important mechanistic question of the roles of cytoskeleton remodeling in acrosome biogenesis and provided genetic, subcellular, and molecular evidence to build up their support for their hypothesis that Ssh2 regulates actin cytoskeleton remodeling, a process essential for proacrosomal vesicle trafficking and acrosome biogenesis, through dephosphorylation actin-binding protein during spermiogenesis.

Weaknesses:<br /> For body weight, and testis weight of the mutants, the authors concluded that there is no significant difference between the mutant and wildtype (Fig 1E -1G), but they appear to use mice between 6-8 wk old, both the testis and body weight of males at 6-8 wks is still growing, with the number of mice analyzed being six, you could easily miss the significant difference of the testis size and or body weight with such a varied age and a small sample size.

Could the uniform cytoplasmic distribution of diminutive actin filaments in the wild type and disrupted actin filament remodeling be examined at the EM level on the round spermatids?

Any other defects are seen besides acrosome in the mutant testis given the important roles of actin cytoskeleton network and high expression of Ssh2 in spermatocytes, were chromatoid bodies or mitochondria affected in any way? Any other defects in the mice overall including female fertility and other organs, given the previously reported roles in the nervous system. It could be helpful information for others interested in Ssh 2 protein and actin cytoskeleton's roles in general.

Providing detailed information on the number of animals used and cells analyzed in the legend is nice, but it might be even better for the readers to include sample size and the number of cells examined in the figure/graph if possible.

Nice discussion and comparison with GOPC and GM130, how about comparison and discussion with other acrosome defective mutants like PICK1, and ATG to provide some insights into acrosome biogenesis and proacrosomal vesicle trafficking?<br /> Given the literature on Cofilin's requirement for male fertility and the increased p-Cofilin in Ssh2 mutant testis by Western and IF, the authors have a strong case for their hypothesis. But given the general role of phosphatase, it might be prudent to discuss alternative possibilities.

Reviewer #2 (Public Review):

This is a well-written manuscript in which the authors' conclusions are supported by well-established mouse genetic conditional approaches and phenotypic analyses.

Strengths:<br /> 1. The authors utilized well-established genetic tools, Adipoq-Cre to target MALPs and Prx1-Cre to globally target limb skeletal cells, and combined these drivers with Csf1 floxed alleles. This double-angled approach helps the authors determine the importance of Csf1 secreted by different skeletal cell populations in regulating bone mass.<br /> 2. The scRNA-seq analysis and the in vivo phenotypic analyses (3DmicroCT, histology, dynamic histomorphometry, serum bone resorption and formation markers) of the Csf1 CKO models are well-conducted. The authors convincingly show that cortical bone parameters are unaffected in MALP-specific Csf1 CKO mice, while serum CTX-1 is reduced in these mice. The confidence for the reported phenotypes is high.<br /> 3. The data presented in this manuscript are of very high quality. Particularly, the authors detected no changes in osteoclasts at the chondral-osseous junction and the endosteal surface, emphasizing the uniqueness of the CKO model.

Weaknesses:<br /> 1. The relevance of the LPS-induced calvarial osteolysis model is not clear. Calvaria is mostly composed of cortical bone-like structures lacking marrow space, though small marrow space exists near the suture. Osteolysis appears to occur in areas apart from where marrow is located. The authors did not show in the manuscript which cells Adipoq-Cre marks in the calvaria.<br /> 2. Although the contrast between the two Csf1 conditional deletion models (Adipoq-Cre and Prx1-Cre) is very interesting, the relationship between these two cell populations are not well described. The authors did not clarify if MALPs are also targeted by Prx1-Cre, or these two cell types are from different cell lineages. "Other mesenchymal lineage cells" in the subtitle is not extremely helpful to place this finding in context.<br /> 3. The data supporting defective bone marrow hematopoiesis in Csf1 CKO mice are not particularly strong. They observed a reduction in bone marrow cellularity, but this was only associated with an expected reduction in macrophages and a mild reduction in overall HSPC populations. More in-depth analyses might be required to define mechanisms underlying reduced bone marrow cellularity in CKO mice.<br /> 4. Some of the phenotypic analyses are still incomplete. The authors did not report whether CHet (Adipoq-Cre Csf1(flox/+)) showed any bone phenotype. Further, the authors did not report whether Csf1 mRNA or M-Csf protein is indeed expressed by MALPs, with current evidence solely reliant on scRNAseq and qPCR data of bulk-isolated cells. More specific histological methods will be helpful to support the premise of the study.

Reviewer #2 (Public Review):

The authors aim to test the hypothesis that dopamine mediates the evaluation of temporal costs in intertemporal choice in humans, with a specific goal of synthesizing the competing accounts and previous results regarding whether dopamine increases or decreases evaluation of delays in comparing differently delayed future rewards. To do this, they computationally dissect the impact of the drug amisulpride, a D2R antagonist, using a variant of a sequential sampling model, the drift-diffusion model (DDM), that is well established in decision-making literature as a cognitive process model of choice. This model allows the dissociation of starting bias from the rate at which decision evidence is integrated ('drift'), which the authors map to different accounts of the role of dopamine: the temporal proximity of an outcome is proposed to impact bias, while the cost of a delay to impact the drift rate of evidence evaluation/accumulation. Consistent with previous results, and perhaps integrating conflicting findings, the authors find that d2R blockade impacts both bias and drift rate in a cohort of 50 participants, demonstrating dopaminergic action at this receptor is implicated in dissociable components of intertemporal choice, with D2R block reducing the bias towards sooner, more temporally proximate rewards as well as enhancing the contrast between reward magnitudes irrespective of delay, effectively diminishing the effect of delay in the drug condition. These effects are consistent across a small subset of alternative models, confirming the multiple cognitive mechanisms through which D2R block impacts intertemporal choice is a robust feature of decisions on this task.

Overall, this study is a detailed dissection of the specific effects of amisulpride on a type of future-oriented, hypothetical intertemporal choice, and provides consistent evidence integrating conflicting accounts that implicate dopaminergic signaling on evaluation of the cognitive costs, such as a delay, on choice. However the specificity of the empirical intervention and the task design limits the interpretation of the broader dopaminergic mechanisms at play in intertemporal choice, especially given the complexity of receptor specificity of this drug, dopamine precursor availability and individual differences and the specifics of the intertemporal choice in this task. As it stands, the results contribute an interesting, synthesized account of how D2R manipulation can impact evaluation of delays in multiple ways, that will likely be useful for motivating future studies and more detailed computational assessments of the cognitive process-level components of intertemporal choice more generally.

The focus of this study is important, and delineating the role of DA in intertemporal choice is of high relevance given DA disfunction is prevalent in many psychiatric disorders and a key target of pharmacological treatment. While the hypotheses of the current study are framed with respect to "costs", the task used by the authors reduces these to evaluation of a hypothetical delay, one which the participants do not necessarily experience in the context of the task. In some respects this is reasonable, given the prevalence of this task paradigm in testing temporal aspects of choice in humans in an economic sense. However, humans are also notoriously subject to framing effects and the impact of instructions in cognitive tasks like these, which can limit the generality of the conclusions, and in particular the specific ways in which a delay can be interpreted as costly (for eg cost as loss of potential earnings, cost as effortful waiting, cost as computational/simulation cost in future evaluation). Given the hypothesis recruits the idea of cost in assessing the role of dopamine, testing for generality in the effects of amisulpride in related but differently framed tasks seems critical for making this link in a general sense, and in connecting it to the previous studies in the literature the authors point to as demonstrating conflicting effects.

Further, while the study aims to test the actions of dopamine broadly, the empirical manipulation is limited to the action of amisulpride, a D2R anatgonist. There is little to no discussion of, or control for, the relationship between dopaminergic action at D2 receptors (the site of amisulpride effects) and wider mechanisms of dopaminergic action at other sites eg D1-like receptors, and the interplay between activation at these two receptor types alongside baseline levels of dopamine concentration. This is necessary for a comprehensive account of dopamine effects on intertemporal choice as the authors aim to test, as opposed to a specific test of the role of the D2 receptor, which is what the study achieves. On a related note, in some preparations at least, amisulpride also acts at some of the 5-HT receptors, raising the possibility of a non-dopaminergic mechanism by which this drug might impact intertemporal decisions. This possibility, while it would not be expected to act without dopaminergic effects as well, is consistent with established effects of serotonin on waiting behaviors and patience. Granted, the limits of pharmacology in humans does not necessarily mean this can be controlled for, it should be kept in mind with a systemic manipulation such as this.

Overall the modeling methods are robust and appropriate for the specific test of decision impacts of D2R blockade, and include several prima facie variable alternative models for comparison. Some caution is warranted, since there are not many trials per subject, and some trials are discarded as well as outliers, which raises the question of power. Given the models are fit hierarchically, which gives both group-level and individual-level parameter estimates, the elements are there to probe more deeply into individual differences, and to test how reliably this approach can dissociate the dual effects of bias and drift rate at the individual level, and perhaps correlate it with other informative subject measures of either dopamine activity/capacity or other dopamine-dependent behaviors. Alternative DDMs might also capture some of this individual variation, with meaningful differences potentially in model comparison at the individual level. It should be noted that the scope of these models do not exhaust the ways in which proximity (here, temporal) of rewards and contrast between choice options might be incorporated into a cognitive process model account of choice; all alternatives here rest on the same implicit 2-alternative forced choice assumption of the DDM, and the assumptions of this model are not here tested against other accounts of choice, for example the linear ballistic accumulator (LBA) and its derivatives. Further, the concept of proximity as a global feature of a trial (on average, how soon are these options overall?) is never tested on my read of the alternative models.

Reviewer #2 (Public Review):

Richardson et al. characterize through immunophenotyping and high-throughput sequencing humanized mice versus human repertoires using many different immunological/immune repertoire metrics. They find that overall, the naïve Kymouse BCR repertoire is diverse and similar to human repertoires.

Strengths

Overall the study is carefully designed and of broad interest.<br /> - Detailed and established phenotypic and repertoire metrics are used to compare mice and human models.<br /> - Rigorous statistical analysis is mostly used to establish similarity.<br /> - Detailed description of the analyses performed.

Weaknesses

- Improvements could be made in the analyses (at times not far-reaching enough), figures (not self-explanatory enough), and text (too verbose).

Reviewer #2 (Public Review):

This manuscript presents a rather technical modelling analysis of the impact of local lockdowns on Covid-19 hospitalisations in the Netherlands. The major strength of the study is that the authors attempt to calibrate their model to a novel data source, a commercial database of mobility patterns between municipalities. The major weakness is that the model seems overly complicated, many parameters seem to have been 'guessed' without a formal uncertainty analysis, e.g. within a Bayesian framework, so that it is impossible to judge how robust the results and therefore the conclusions are.

Major points:

1) In some aspects the structure of the model presented seems overly complicated: It is not clear why the authors chose the 1:100 population scale and why they didn't go directly for modelling the full population. Artificially reducing the population size has important stochastic effects at the early phase of the epidemic. Also it is not clear what it means when 1:100 of one municipality mixes with 1:100 of another municipality? The authors should at least attempt to see what impact this has on output, i.e. conduct a sensitivity analysis.

2) On the other hand the model goes into (too) much detail regarding mixing behaviour and attempts to model processes during each hour of the day. This does not seem to be informed by actual data, but the data seems to be made up e.g. as in A.6. As an ex-student and a father of a teenager I can tell you that the susceptibility profile guessed in Table 3 does not seem to be very realistic. As it is stated in the appendix, the Mezuro data set only provides daily averages of travelling between communitities, so it is not clear why the hourly resolution is actually needed in the model.

3) It is not clear why the authors rely on only one short period of the Mezuro data set in March 2019 and not investigate the same data source during the actual lockdown in 2020, or even for the full year, as travelling is likely to be very season dependent. This would provide much better estimates of the effects of lockdown on travel patterns. The analysis presented and categorisation into frequent, regular and incidental also need further explanation. It is not clear how international travel is accounted for in the mobility data.

4) Beyond the technical points on the modelling, the main hypothesis of whether local lockdowns may work has also not been sufficiently discussed outside of the Dutch context. The authors fail to mention that this was the approach chosen in Northern Italy at the start of the epidemic (https://en.wikipedia.org/wiki/COVID-19_lockdowns_in_Italy) where it didn't work, as we all know. On the other hand, more recent local lockdowns in China appeared to be successful, albeit at a great societal cost in terms of restrictions to freedom (https://en.wikipedia.org/wiki/COVID-19_lockdown_in_China).

Reviewer #2 (Public Review):

The manuscript entitled "IL-4 and helminth infection downregulate Mincle-dependent macrophage response to mycobacteria and Th17 adjuvanticity" by Schick et al. demonstrate the inhibitory activity of IL-4 and helminth infection on mycobacteria-mediated Th17 immunity. Overall, the authors reported interesting findings with solid data that advance our understanding of CLR function in fungal-bacterial co-infection.

Reviewer #2 (Public Review):

Previous research using GWAS and population genetics approach identified a genetic haplotype on chromosome 3 derived from Neanderthals as the major risk factor for severe COVID-19. However, the specific variants that are causative of the severe COVID-19 phenotype remain unknown. Here, Jagoda et al. aim to identify the causative variants for the severe COVID-19 by leveraging eQTL analysis followed by Massively parallel reporter assays (MPRA). Their datasets and results are unique and novel. Their research is well designed, and will serve as a model strategy for future studies of functional annotation of disease-associated variants. However, there are following critical weaknesses in this manuscript that reduce the impact of this work; (1) The quantitativity of the MPRA output is questionable because of their incomplete definition of MPRA activity, which is based on absolute barcode counts without comparing negative controls. (2) Molecular mechanisms (binding transcription factors, etc.) of causative variants that underly the regulation of CCR1/5 expression and COVID19 severity are not analyzed and validated.

Reviewer #2 (Public Review):

The tongue muscles play a major role in many important behaviors including suckling, swallowing, and ensuring that the upper airway remains open during breathing. Hypoglossal motoneurons innervate tongue muscles and as such play a key role in homeostasis. Previous work has shown that heme-oxygenase-2 (HO-2) null mice have severe airway obstruction. HO-2 forms carbon monoxide, suggesting that CO contributes to hypoglossal motoneuron excitability. In addition to HO-2, the present study also shows that hypoglossal motoneurons express cystathionine ϒ-lyase (CSE), which produces H2S and is regulated by CO. Interestingly, the authors show that H2S reduced transmission of the breathing-related drive to hypoglossal motoneurons. Together these observations suggest that CO and H2S interact to maintain the excitability of hypoglossal motoneurons. An imbalance of these competing influences may underlie tongue muscle dysfunction in conditions such as obstructive sleep apnea and dysphagia. Thus, the novel observations reported here open new avenues that will lead to a better understanding of the highly complex tongue muscle motor system.

The team used brain stem slices containing hypoglossal motoneurons that were receiving rhythmic, breathing-related depolarizing drive from the pre-Botzinger complex, the putative respiratory central pattern generator. Extracellular population activity was recorded from the pre-Botzinger complex and the ipsilateral hypoglossal motor nucleus-and in some experiments-the hypoglossal premotor population located in the ipsilateral reticular formation. In these rhythmic slices, the fidelity between hypoglossal and pre-Botzinger bursts approached 100% and blocking HO-2 with drugs reduced fidelity by about 25%. In addition, HO-2 null mice showed an even larger reduction in pre-Botzinger-hypoglossal bursting fidelity of 40-45%. Since these interventions did not significantly impact the pre-Botzinger population activity, the data show convincingly that CO contributes to hypoglossal motoneuron excitability. While whole cell intracellular recordings of hypoglossal motoneurons showed that blocking HO-2 reduced the magnitude of inspiratory drive currents and the number of action potentials generated in response to the depolarizing drive, these effects were relatively modest, suggesting that the mechanisms that underlie these important observations are unsettled.

The other key part of these experiments was demonstrating that the H2S forming enzyme CSE is expressed in the hypoglossal nucleus, and that exogenous application of NaHS, an H2S donor, reduces the fidelity of pre-Botzinger-hypoglossal coupling. Interestingly, H2S activity was lower in HO-2 null mice, and HO-2-dependent uncoupling could be rescued by bath application of the CO donor CORM-3. Moreover, failed transmission between pre-Botzinger and hypoglossal population bursts was not observed in preparations from mice null for both HO-2 and CSE. These data support excitatory-inhibitory interactions that are triggered by the gases CO and H2S.

Mechanistic experiments showed that blockade of CSE with L552 propargylglycine could restore transmission fidelity, and this was accompanied by a substantial increase in the magnitude of inspiratory-related drive currents in hypoglossal motoneurons. The team also showed that blocking small-conductance potassium channels with apamin in slices where HO-2 was first blocked pharmacologically enhanced inspiratory drive currents, though this observation needs re-examination given that the effect was large in two neurons, but very small in the remaining four (Fig. 8 A3). Finally, similar experiments focused on the ATP-sensitive potassium channel (KATP), which was previously shown to be enhanced by H2S. Blockade of KATP with tolbutamide had no impact on hypoglossal motoneuron output. In conclusion, the experiments reveal a very important contribution of gas-mediated transmitters in setting the balance of excitation and inhibition of hypoglossal motoneuron excitability. More work will be needed to unravel the mechanisms behind these exciting observations.

Reviewer #2 (Public Review):

The authors performed preclinical studies to investigate the underlying mechanism of how the combination of pyrotinib, letrozole and dalpiciclib achieved satisfactory clinical outcomes in the MUKDEN 01 clinical trial (NCT04486911). Mechanistically, using anti-HER2 drugs such as pyrotinib and trastuzumab could degrade HER2 and facilitate the nuclear transportation of ER in HER2+HR+ breast cancer, which enhanced the function of ER signaling pathway. The introduction of dalpiciclib partially abrogated the nuclear transportation of ER and exerted its canonical function as cell cycle blockers, which led to the optimal cytotoxicity effect in treating HER2+HR+ breast cancer. Furthermore, using mRNA-seq analysis and in vivo drug susceptibility test, the authors succeeded in identifying CALML5 as a novel risk factor in the treatment of HER2+HR+ breast cancer.

Reviewer #2 (Public Review):

The purpose of this paper is to consider the utility of the long non-coding RNA PCA3, along with the gene PCA3 in the diagnosis of human prostate cancer. The study extends earlier findings by this group that the PRUNE2 gene product may function as a prostate tumor suppressor. The study employed two separate patient cohorts: one of 107 patients from the University of New Mexico Comprehensive Cancer Center, with organ-confined prostate cancer at their original diagnosis, and one of 497 patients with organ-confined prostate cancer from The Cancer Genome Atlas (TCGA). The authors report an overall increase in PCA levels along with a general decrease in PRUNE2 gene expression. The authors conclude that PRUNE2 functions as a prostate tumor suppressor whose levels negatively correlate with PCA3 levels. They further surmise that PCA3 in turn functions as a dominant-negative oncogene. Consequently, they expect that loss of increased PCA3 levels can lead to loss of PRUNE2 and increased prostate cancer tumor formation.

One interesting observation, consistent with earlier studies, is that PCA3 levels are highest in low-grade tumors, and then decrease as the tumors progress to a higher stage and grade. This suggests that increased PCA3 may be important for early tumor formation while possibly impeding tumor progression. The decreased PCA3 levels seen in later prostate cancer may, the authors hypothesize, be related to alterations in androgen receptor (AR) function in these higher-grade cancers. Thus, while the presence of PCA3 may be an early marker of prostate cancer formation, the results indicate that its presence in early cancers is not, by itself, predictive of future patient outcomes, as tumor progression may actually depend on the later decrease in PCA3 levels.

A strength of this study is the use of two non-redundant patient cohorts to thoroughly analyze the consequence of alterations in PRUNE2 and PCA3 by directly analyzing analyte levels in human tissue samples. The study provides important data supporting the occurrence of a loss of PRUNE2 and gain of PCA3 in organ-confined prostate cancer. The principal takeaway from this report is to highlight the role of the PRUNE2/PCA3 axis in early prostate cancer and to encourage the use of PCA3 antagonists in the prevention and treatment of early prostate cancer. It is unlikely that examination of tissue samples for alterations in PRUNE2 or PCA3 levels will be useful in prostate cancer diagnosis or prognosis as the data do not suggest that these changes in early cancers are predictive of future outcomes. It may be, however, that longitudinal analysis of PCA3 levels in patient plasma or circulating tumor cells could be a useful adjunct to follow the course of tumor progression.

Reviewer #2 (Public Review):

Dipeptide repeat (DPR) proteins produced from both sense GGGGCC (poly-GA, poly-GP and poly-GR) and antisense CCCCGG (poly-PR, poly-PG, poly-PA) repeat RNAs are found C9ORF72-linked ALS/FTD and contribute to neurodegeneration. The translation of the repeat RNA can initiate without the AUG start codon, a process known as repeat associated non-AUG (RAN) translation. In this manuscript, the authors used luciferase reporter construct to show that the translation of PR and PG from the CCCCGG repeats initiated from in-frame AUG in the C9 sequences before the repeats. After mutating candidate AUG codons, the translation can initiate from other AUG, so there is redundancy. But if mutating all the in-frame AUG codons, the luciferase was dramatically reduced, supporting the translation initiated at the AUG start codon. The translation initiation factor eIF2D has been shown to be important for CUG start codon-dependent poly-GA translation from GGGGCC repeats. Here it is shown that eIF2D is not required for poly-PG and poly-PR translation from CCCCGG repeats using both reporter and patient iPS-neurons. The data using luciferase reporter to study antisense repeat translation is solid, the translation initiates from AUG start codon as there are AUG in frame with PG and PR in the constructs containing the antisense sequences.

On the other hand, as the reporter construct includes the sequences containing the AUG codon, it is not surprising that AUG was used. This is canonical translation. Additionally, the AUG-initiated translation of antisense repeats has been reported previously. Therefore, the novelty is limited. How the antisense DPRs are translated endogenously, AUG-canonical translation or RAN translation, depends on whether the AUG is included in the antisense RNA in patients and where the transcription of the antisense starts, upstream or downstream of the AUG start codons. However, this is not considered in the manuscript.

Reviewer #2 (Public Review):

Convergence of cellular/molecular phenotypes across seemingly different types and subtypes of neurodevelopmental disorder represent an exciting frontier to identify effective drug targets. In this study, authors compared early neurodevelopmental processes, namely neurite outgrowth and migration, between a form of autism caused by copy number variation mutation in 16p11.2 (16pdel), which deletes 28 genes, to idopathic autism (I-ASD), in which genetic causes are unknown. All experiments involved neurospheres or neural precursor cells (NPCs) derived from human iPSCs. Three patients with I-ASD and their unaffected siblings as well as three patients with 16pdel were included in the study. Authors then go on to show perturbed migration and neurite length phenotypes shared between I-ASD and 16p11 NPCs. Interestingly they identified two subclasses of I-ASD patients, either with high or low levels of mTOR, and show that change in mTOR level in either direction result in similar migration and neurite extension phenotypes, either at baseline or induced by pro-migratory factors. The study design is particularly strong and communication of sample structure throughout the manuscript is commendable. This study effectively points to the potential of patient-derived in vitro models to uncover novel molecular drivers of disease. I only have a few comments below:

(1) I found that interpreting how differential EF sensitivity is connected to the rest of the story difficult at times. First, it is unclear why these extracellular factors were picked. These are seemingly different in nature (a neuropeptide, a growth factor and a neuromodulator) targeting largely different pathways. This limits the interpretation of the ASD subtype-specific rescue results. One way of reframing that could help is that these are pro-migratory factors instead of EFs broadly defined that fail to promote migration in I-ASD lines due to a shared malfunctioning of the intracellular migration machinery or cell-cell interactions (possibly through tight junction signaling, Fig S2A). Yet, this doesn't explain the migration/neurite phenotypes in 16p11 lines where EF sensitivity is not altered, overall implying that divergent EF sensitivity independent of underlying mTOR state. What is the proposed model that connects all three findings (divergent EF sensitivity based on ASD subtypes, 2 mTOR classes, convergent cellular phenotypes)?

(2) A similar bidirectional migration phenotype has been described in hiSPC-derived human cortical interneurons generated from individuals with Timothy Syndrome (Birey et al 2022, Cell Stem Cell). Here, authors show that the intracellular calcium influx that is excessive in Timothy Syndrome or pharmacologically dampened in controls results in similar migration phenotypes. Authors can consider referring to this report in support of the idea that bimodal perturbations of cardinal signaling pathways can converge upon common cellular migration deficits.

(3) Given that authors have access to 8 I-ASD hiPSC lines, it'd very informative to assay the mTOR state (e.g. pS6 westerns) in NPCs derived from all 8 lines instead of the 3 presented, even without assessing any additional cellular phenotypes, which authors have shown to be robust and consistent. This can help the readers better get a sense of the proportion of high-mTOR vs low-mTOR classes in a larger cohort.

(4) Does the mTOR modulation rescue EF-specific responses to migration as well (Figure 7)?

Reviewer #2 (Public Review):

The authors seek to determine how various species combine their effects on the growth of a species of interest when part of the same community.

To this end, the authors carry out an impressive experiment containing what I believe must be one of the largest pairwise + third-order co-culture experiments done to date, using a high-throughput co-culture system they had co-developed in previous work. The unprecedented nature of this data is a major strength of the paper. The authors also discover that species combine their effect through "dominance", i.e. the strongest effect masks the others. This is important as it calls into question the common assumption of additivity that is implicit in the choice of using Lotka-Volterra models.

A stronger claim (i.e. in the abstract) is that joint effect of multiple species on the growth of another can be derived from the effect of individual species. Unless I am misunderstanding something, this statement may have to be qualified a little, as the authors show that a model based on pairwise dominance (i.e. the strongest pairwise) does a somewhat better job (lower RMSD, though granted, not by much, 0.57 vs 0.63) than a model based on single species dominance. This is, the effect of the strongest pair predicts better the effect of a trio than the effect of the larger species.

This issue makes one wonder whether, had the authors included higher-order combinations of species (i.e. five-member consortia or higher), the strongest-effect trio would have predicted better than the strongest-effect pair, which in turn is better predictor than the strongest-effect species. This is important, as it would help one determine to what extent the strongest-effect model would work in more diverse communities, such as those one typically finds in nature. Indeed, the authors find that the predictive ability of the strongest effect species is much stronger for pairs than it is for trios (RMSD of 0.28 vs 0.63). Does the predictive ability of the single species model decline faster and faster as diversity grows beyond 4-member consortia?

While this may limit the scope of the paper somewhat, it does not subtract from its overall impressiveness. This is a very strong paper that combines state of the art methodology, of a kind that will change the field, with an important question and an intriguing finding that will surely motivate further work. Therefore, it will be of wide interest and appeal to the broad audience of microbial ecologists, and it is an important and compelling step forward in the field.

Reviewer #2 (Public Review):

I am not a specialist in cryo-EM, so cannot comment on the technicalities of the structure reconstruction or methods used. I thus focus on the conclusions and observations that the authors provide in the manuscript and their relevance to functional photosynthesis.

The authors attempt to resolve the structure of PSII from Dunaliella and noticed that three types of PSII could be identified: two conformational states, and a stacked configuration. There is no doubt that these structures add to our current knowledge of PSII and that they exist in abundance upon solubilisation of the sample. My main issue however is the relevance to in vivo conditions, and the efforts to exclude the possibility that pigment loss and conformational states and stacking are a reflection of ex-vivo manipulations.

I see a number of questions pertaining to this work. Starting from the two conformations of PSII, compact and stretched, the authors say that both are highly active based on oxygen measurements at a saturating light intensity. In the meantime, they report large variations in the chl content and positions of the chlorophyll molecules in these structures (also compared to other known PSIIs). This gives the impression that one can lose two chlorophylls, and freely modify the distance between others without losing efficiency, certainly a risky conclusion. Are the samples highly active also in light-limiting conditions? It is thought that even tiny movements and alterations in chl-chl distances alter their coupling and spectral properties, how come the variations in this report are so huge? In other words, the assay tests the charge separation activity of the PSII RC in the preps, but not the light-harvesting efficiency.

How does one ascertain that the lost chlorophyll molecules in CP29 are not a preparation error? Does slightly increasing the detergent concentration impact the proportion of stretched:compact forms?<br /> On a similar note, how do the authors exclude that a certain interaction with this type of grid impacts the distribution of these complexes? Is it identical to a biologically separate preparation of algae? In case of discoveries of this type, it is of high importance to exclude as many possibilities of non-native conditions or influences on the structure.

I would further like to encourage the authors to elaborate on the CP29 phosphorylation. What is the proportion of PSIIcomp that are phosphorylated? I assume it is not 100%, as in this case, the authors would propose that this is the effect that modulates between compact and stretched architectures.

In line 290, the authors highlight the structural heterogeneity within the two groups' PSII conformations. I would like to see how does the distribution look like for all the structures together: are the two (stretched and compact) specifically forming two heterogenous distributions? Or is it possible that the distribution between the two is quasi-continuous? In other words, if the structures are not perfectly defined, how do the authors decide that two- and not more or less subtypes exist?

Considering the stacked PSII, I also have a few concerns. Contrary to previous studies the authors do not assign a functional role to the stacking beyond the structural aspect. This could be better backed by a discussion about the closest chlorophyll a molecules across the stacked PSII, which given the rather large distance shown in fig. 4L seems to be too large for any EET across the stromal gap.<br /> There is a report that suggests the presence of some density between the stacked PSII - could the authors comment on the differences between it and their work? Are the angles and positions conserved between these types of stacks? https://doi.org/10.1038/s41598-017-10700-8

Line 387, the authors state that due to the transient nature of the interactions across the stromal gap, the stacks could be "under-detected" in cryo-ET data. This statement is in my opinion misformulated. For once, the transient interaction argument would apply the same (if not more due to changing conditions induced by the purification process) to the single particle analysis performed in this paper. Second, tomographic volumes detect hundreds of PSII in a suspended state. Any transient interaction that adds up to 25% of particle population in a steady state cell should be clearly visible, while the in situ data suggests not more than random cross-stromal-gap orientations. Of course, this can be a specificity of Chlamydomonas or a particular growth condition. The statement used by the authors could be indeed converted into: the PSII stacks are *over-detected in vitro*, and it is certainly a simpler explanation for their presence. It is also important to mention that PSII stacking alone is not the only reason for grana architecture - stacking with the antenna of larger complexes, absent in the authors' preparation could also contribute to grana maintenance; and auxiliary proteins such as CURT help with this issue as well. Here a recent demonstration of the importance of minor antenna should probably be also cited: https://doi.org/10.1101/2021.12.31.474624

Taking these last thoughts, I would like to finish by mentioning one more thing - almost philosophical. The authors are certainly at the forefront of the booming cryoEM revolution in biology which is profoundly changing the way we understand the living. There is absolutely zero doubt that this powerful technique is of the highest interest. But a growing number of structures of photosynthetic complexes remain puzzling, in particular with regard to their abundance in vivo (such as the PSII stacks) and functional relevance. How do we ascertain that these interactions are not due to in vitro preparation (isolation from cells, solubilisation)? Which ways can we use to try to exclude this (simple) hypothesis? I suggest that at least a small extent of biological replicas - experiments performed on separate batches, in different technical conditions, with slightly altered solubilization conditions, and so on - could shed light on the nature of these structures and their occurrence in vivo. Technical reps of the freezing+analysis pipeline could also be tried to see the variability. This would strongly reinforce this manuscript and its conclusions, and while not completely unequivocal (the stacked PSII, for example, could form upon each purification), a quantification of the effects would be of high interest.

Reviewer #2 (Public Review):

The central nucleus of the amygdala (CEA) has been the subject of numerous studies related to the processing of both aversive and pleasurable events; however, prior to this study a comprehensive understanding of the number of molecularly distinct neurons, their location in the CEA and their axonal projections have not been available. This paper provides a rich resource that fills this gap. The results will facilitate a more refined analysis of the roles of specific CEA neurons in mediating mouse behavior and physiology. A major strength of the paper is the application of their three-dimensional spatial profiling methodology of molecularly defined neurons to the CEA and then determining the axonal projections of those neurons to five of the most prominent target brain regions. The data are clearly presented and rigorously analyzed. The are no weaknesses in this valuable contribution.

Reviewer #2 (Public Review):

Overall this is a very interesting and important paper that demonstrates a novel synthetic interaction between nucleoporin inhibition and oncogene-driven hyperproliferation. This work is especially significant because of the paucity of effective treatments for hepatocellular carcinoma (HCC). The authors' demonstration that the Nup inhibitor Selinexor decreases larval liver size in KRAS-overexpressing zebrafish but does not cause toxicity in wild-type animals lays the groundwork for exploiting this class of drugs in HCC treatment. This paper represents an elegant demonstration of the utility of zebrafish models in cancer studies. The relevance of this work to human cancer is supported by the authors' studies using TCGA data, wherein they demonstrate that decreased NUP expression is associated with increased survival in HCC.<br /> Other major strengths of the paper include beautiful pictures demonstrating that ahctf1+/- decreases the density and volume of nuclear pores in TO(kras) larvae and increases the rate of multipolar spindle formation, misaligned chromosomes, and anaphase bridges. The experiments are very well-controlled, including detailed analysis of the effects of ahctf1 heterozygosity and Selinexor on wild-type animals. The inclusion of distinct methods for disruption nucleoporins (ranbp2 heterozygosity and drug treatment) bolsters the authors' conclusion that this represents a viable drug target in HCC.

My major concerns are as follows:

1. The authors state that "the beneficial effect of ahctf1 heterozygosity to reduce tumour burden persists in the absence of functional Tp53, due to compensatory increases in the levels of tp63 and tp73". However, tp63 and tp73 appear similarly upregulated in ahctf1 heterozygotes regardless of tp53 status. The authors do not provide enough evidence that tp63 and tp73 are compensating for tp53 loss. An alternative possibility based on the data presented is that the effects of ahctf1+/- are independent of tp53 family members, and the effects on apoptosis go through a different pathway.

2. The authors state in multiple locations that nucleoporin inhibition decreases tumor burden. In my opinion, this is not strictly correct. The TO(kras) model clearly results in HCC in adults, but it's a little unclear whether the larval liver overgrowth is truly HCC or not based on the original paper by Nguyen et al. (2012 Dis Model Mech).

Reviewer #2 (Public Review):

The goal of this study was to understand population bottlenecks during colonization in the context of different microbial communities. Capsular polysaccharide mutants, diet, and enteric infection were also used paired to short-term monitoring of overall colonization and the levels of specific strains. The major strength of this study is the innovative approach and the significance of the overall research area.

The first major limitation is the lack of clear and novel insight into the biology of B. theta or other gut bacterial species. The title is provocative, but the experiments as is do not definitively show that the microbiota controls the relative fitness of acapsular and wild-type strains or provide any mechanistic insights into why that would be the case. The data on diet and infection seem preliminary. Furthermore, many of the experiments conflict with prior literature (i.e. lack of fitness difference between acapsular and wild-type strain and lack of impact of diet) but satisfying explanations are not provided for the lack of reproducibility.

Another major limitation is the lack of data on the various background gut microbiotas used. As such, describing what microbes are in LCM, OligoMM, or SPF groups is important. The authors seem to assume that the gut microbiota will reflect prior studies without measuring it themselves. I also did not follow the logic of concluding that any differences between SPF and the two other groups are due to microbial diversity, which is presumably just one of many differences. For example, the authors acknowledge that host immunity may be distinct. It is essential to profile the gut microbiota by 16S rRNA amplicon sequencing in all these experiments and to design experiments that more explicitly test the diversity hypotheses vs. alternatives like differences in the membership of each community or other host phenotypes.

Given the prior work on the importance of capsule for phage, I was surprised that no efforts are taken to monitor phage levels in these experiments. Could B. theta phage be present in SPF mice, explaining the results? Alternatively, is the mucus layer distinct? Both could be readily monitored using established molecular/imaging methods.

The conclusion that the acapsular strain loses out due to a difference of lag phase seems highly speculative. More work would be needed to ensure that there is no difference in the initial bottleneck; for example, by monitoring the level of this strain in the proximal gut immediately after oral gavage.

Another major limitation of this paper is the reliance on short timepoints (2-3 days post colonization). Data for B. theta levels over 2 weeks or longer is essential to put these values in context. For example, I was surprised that B. theta could invade the gut microbiota of SPF mice at all and wonder if the early time points reflect transient colonization.

Finally, the number of mice/group is very low, especially given the novelty of these types of studies and uncertainty about reproducibility. Key experiments should be replicated at least once, ideally with more than n=3/group.

Reviewer #2 (Public Review):

In this study, the authors have successfully utilized and compared various supervised machine-learning techniques to identify the risk for the development of diabetic kidney disease. The study was further able to identify some potential novel risk factors for the development of diabetic kidney disease.

The heterogenous population and the identification of novel risk factors for diabetic kidney disease are some of the strengths of this study. Their definition of diabetic kidney disease, however, relies only on the decline in eGFR and is lacking in details of any other major significant events that may have impacted the decline in kidney function during the follow-up time period.

Overall it is an interesting study that advances the field of kidney disease, though its results need to be interpreted with caution due to significant limitations in the study design.

Reviewer #2 (Public Review):

This study by De Virgilio and co-workers examines the role of SNF1, the AMPK ortholog in yeast, in regulating TORC1 activity and cell growth. The authors combine the use of an analog-sensitive allele of SNF1 and SILAC to characterize the yeast phospho-proteome under nutrient-complete and glucose-starved conditions. Using this approach, in addition to confirming previously identified targets of SNF1, many potential new substrates were identified. The authors follow up on two of these: PIB2, a known upstream regulator of TORC1 linked previously to glutamine signaling; and SCH9, an important downstream target that is directly phosphorylated by TORC1. The authors use a combination of mutagenesis and in vitro and in vivo assays to demonstrate that SNF1 is a bona fide kinase for PIB2 and SCH9 and that phosphorylation of these targets impacts TORC1 kinase activity. In general, the data are thorough and convincing, and these findings will be appreciated by the wide readership of this journal.

Specific points to consider:

1. Because PIB2 is a major focus of the manuscript, I was surprised that it was not discussed in the introduction. I think it would be appropriate to discuss prior evidence linking this protein to TORC1.

2. The authors introduce mutations into PIB2 at two sites determined to be phosphorylated by SNF1, at S268 and S309. Somewhat confusing results are obtained, in that the PIB2 null and phosphomimic mutants (S268E and S309E) confer a similar TORC1 phenotype, compared to the S268A S308A mutant. These results require further explanation than simply that "TORC1 inactivation defect in SNF1-compromised cells is due to a defect in PIB1 phosphorylation". This is particularly intriguing given that the opposite results are observed with the SCH9 mutants, where the null and alanine mutants confer a similar phenotype compared to the S to E mutants.

3. The authors conclude, based on the co-IP data in Figure 4H, that interactions between KOG1 and PIB2 are direct. However, it remains possible that interactions between these proteins are mediated by other components of TORC1 or within cells. This should be addressed.

4. The authors demonstrate convincingly that the PIB2 and SCH9 SNF1-specific phospho-site mutants have a detectable effect on TORC1, primarily by examining TORC1-dependent phosphorylation of SCH9. What is unclear is whether phosphorylation at these sites has a significant physiological impact on cells. It appears that the rapamycin hyper-sensitivity displayed in Figure 6E is the only data presented to address this question. It would be appropriate for the authors to comment further on the significance of SNF1-dependent phosphorylation of these two substrates.

Reviewer #2 (Public Review):

The authors describe observations of an innovative food caching behavior attributed to two species of flying squirrels and likened the behavior to architectural joints used by humans. The discovery of nuts stored in the crook of shrub branches, facilitated by indented rings seemingly carved by squirrels, possibly represents an interesting food handling innovation that may function to prevent spoilage in a damp tropical ecosystem.

I applaud the efforts to survey the area multiple times after the initial discovery, and the use of trail cameras to try capture evidence of animal associations. For what is in essence a natural history note, the authors did a great job of trying to gather a variety of supporting evidence. The videos capturing squirrels visiting and retrieving the cached nuts were compelling, and the shaking of the shrubs demonstrating the difficulty in dislodging the nuts helps build the case that the nuts are cached effectively.

The most glaring gap in the evidence is that there is no direct observation of the squirrels actually performing this nut carving behavior, only associating with the nuts after they have been cached. There must be more documentation provided to explicitly link the causality between squirrels and this caching innovation.

The second major weakness is more to do with writing style and could be addressed with significant revisions to phrasing and development of ideas. This is namely to do with the claim that this is somehow an evolved behavior, without providing evidence that 1) it is indeed the squirrels performing this behavior, 2) that is confers some kind of fitness benefit, and 3) hard evidence that this caching method does indeed prevent decomposition/germination in comparison to the more traditional caching methods of these species. Given the limited geographic range of the observations, I wonder how much of this is actually attributable to learning and/or innovation by these individuals. These ideas are not developed fully, and sometimes the writing wanders among learning and evolution without exploring the deep links among the two concepts.

Third, the connection to architecture is attention-grabbing, but I'd like to see this fleshed out a bit more with more text description (and a visual here would help immensely).

Ultimately this work stands to potentially contribute a fascinating piece of evidence into the growing literature on animal cognition, spatial awareness, caching behavior, innovation, and adaptation, but currently, the claims are unsupported by the evidence presented.

Reviewer #2 (Public Review):

Fortier and Pritchard investigated the breadth and depth of trans-species polymorphism (TSP) within six primate classical (antigen-presenting) major histocompatibility complex (MHC) genes (three MHC class I and three MHC class II). The MHC is of wide interest because of its unique evolutionary patterns within the genomes of jawed vertebrates and for its extensive and consistent associations with disease phenotypes. The findings of the paper are:<br /> 1) Trans-species polymorphism (TSP) within major histocompatibility complex (MHC) genes, whereby some alleles are more similar between rather than within species, occurs between humans and non-human primates despite rapid allelic turnover.<br /> 2) Highly polymorphic/rapidly evolving sites are mostly involved in peptide binding.<br /> 3) The identified, rapidly-evolving sites are associated with disease.

However, because these general findings have been previously demonstrated to varying extents by numerous other studies, these are not the strength of this paper. The strength and importance of this paper are in its utilization of a large evolutionary range of species and genes and its methodological approach and the extent of analyses undertaken to characterize the depth and extent of the TSP among primates. The major contribution of this paper is showing that TSP in the MHC is widespread among diverse primate taxa, and, depending on the particular MHC gene, TSP can be detected between humans and non-human primates as distantly diverged from the human lineage as new world monkeys of the Americas, ~45 million years ago. The paper, overall, made good methodological choices to account for the fascinating but challenging nature of the MHC, which includes its extensive allelic polymorphism (much of which is only characterized for the peptide-binding domain, encoded by exons 2 and 3), the difficulty in assessing phylogenetic relationships (particularly due to recombination and/or interallelic gene conversion), and differentiating convergence from conservation. There is no single analysis that can perfectly account for all these factors. This paper used two methods to test for TSP, Bayesian evolutionary analysis and synonymous nucleotide distances (dS), each with their respective strengths and limitations articulated. TSP, to varying degrees, is supported by both analyses. The paper further identifies rapidly evolving positions within the MHC molecules (predominantly located in the MHC peptide-binding domain), quantitatively shows that they are more likely to be in proximity to the bound peptide within the peptide binding domain, and shows, via a literature review of HLA fine-mapping studies, that those positions are associated with both infectious and autoimmune disease.

The conclusions of the paper, therefore, are supported and appropriate with the most important caveats noted, but the paper would benefit from:<br /> 1) Addressing how copy number variation of MHC class I genes among primate species might have affected their analyses and results (only single representative genes of the class II MHC, which also exhibit copy number variation, were used for this study).<br /> 2) Considering the differences between class I and class II MHC roles in immune function and how those might relate to the observed patterns.

Reviewer #2 (Public Review):

Guo et al. have investigated the consequences of a frameshift mutation in the rcsD gene in the Yersinia pseudotuberculosis progenitor that is conserved in modern Y. pestis strains. Interestingly, they identify a start codon with a ribosome binding site that enables production of an Hpt-domain protein from the C-terminus in Y. pestis. Targeted deletion of this Hpt-domain increased biofilm production in Y. pestis. They find that the ancestral RcsDpstb (full length) is a positive regulator of biofilm in Y. pestis while the Hpt-domain version (RcsDYP) represses biofilm in vitro. When fleas were infected with Y. pestis expressing the ancestral RcsDPSTB protein, there was no difference in bacterial survival or rate of proventricular blockage. This strain also killed mice the same rate (in a different Y. pestis strain background). However, replacing RcsDYP with RcsYPTB dramatically increases the frequency of pgm locus deletion (containing Hms ECM and yersiniabactin genes) during flea infection. The authors predict that this would reduce the invasiveness of the bacteria in mammals and/or flea blockage in subsequent flea-rodent-flea transmission cycles. They also measured global gene expression differences between RcsDPSTB compared to the wild-type strain. They argue that the frameshift of RcsD maintaining the Hpt-domain (RcsDYP) was needed to regulate biofilm while limiting loss of the pgm locus.

Loss of the pgm locus was not tested in the Y. pestis rcsD mutant strain (lacking the entire gene or just the C-terminal Hpt domain). Therefore, the claim that maintaining the Hpt-domain protein was important lacks convincing evidence. Additionally, it is possible that the population of rcsDpe::rcsDpstb after in vitro growth for 6 days would still be proficient at infecting and blocking fleas, even though many of the bacteria would have lost the pgm locus. Production of Hms polysaccharide by pgm+ could trans-complement those that are pgm-. The nature of the pgm locus loss is assumed to be due to recombination between IS elements. This is certainly the likeliest explanation but not the only one. The authors checked for pgm loss by phenotype (CR binding) and by two sets of primers, one targeting the hmsS gene and another set that is unspecified. Loss of the entire pgm (especially yersiniabactin genes) should be clarified.

Reviewer #2 (Public Review):

In general, the authors do a thorough exploration of Drosophila larval crawling, specifically looking at where within the crawl cycle changes in speed are manifest. They find a strong correlation between changes in speed and with contraction of transverse muscles. The authors then characterize a neuron (A31c) known to be activated during the time in the crawl cycle where speed is altered. Unlike many neurons that have a wave of activity across the segments of the body during crawling, these neurons are active synchronously in the segments along the anterior-posterior axis. Also, the A31c neurons have synaptic output onto pre-motor neurons (A26f) whose output ultimately controls transverse muscles.

Experimentally, the authors use all the tools at hand to make a compelling case for their conclusions. They look at crawling in freely crawling animals. Although the data on muscle length is obtained in restrained or semi-dissected animals, it is convincing. It would be more convincing if done in intact freely moving animals, but that is a technical reach. To look at neuron morphology they use immunofluorescence and connectomic data in an effective manner. They are able to manipulate the activity of their neurons of interest in order to show that they have control over transverse muscle length and crawling speed.

Finally, the authors claim that the neurons they examine are sufficient and required to alter crawling speed. They appear to be sufficient to alter transverse muscle length and crawling speed, but the data do not support the requirement for these neurons for these processes. One way to show this would be to inhibit or ablate the neurons and find that the larvae were unable to alter the speed.

Reviewer #2 (Public Review):

One of the greatest challenges to the containment of the SARS-CoV-2 pandemic is the generalist nature of this virus and its ability to infect across non-human animal species, and successfully cycle within non-human species. It is, therefore, critical to understand the potential for transmission and evolution of the virus in non-human animal species and draw generalizations from both to help predict the occurrence of new viral variants and their associated risk for secondary spillover events back into human populations. This manuscript describes cross-species transmission between humans and non-human hosts, as well as non-human host-specific SNVs that have arisen presumably due to continued successful transmission cycles in non-human species. Using publicly available SARS-CoV-2 genomic sequences from four animal host species and humans, the study revealed that the highest number of animal-to-human transmission events have occurred between farmed mink populations and humans and that white-tailed deer have the highest number of single nucleotide variants specific to a non-human species from those included in the study. The authors are careful to point out the limitations of the dataset, as there are still too few publicly available SARS-CoV-2 whole genome sequences for non-human animal taxa, making non-human species inclusion impossible in some cases and creating unbalanced datasets that reflect sequencing and sampling effort. The authors could have offered a greater justification of statistical methods employed given this hurdle, both in terms of quantitative mitigation steps or qualitative justification of the methods used, but their methods provide a pipeline for addressing cross-species transmission and the emergence of non-human species-specific SNVs as scientists work to accumulate more genomic sequences from animal taxa. Their results are also largely congruent with another recently published manuscript using SARS-CoV-2 genomic data from the same source and aimed at understanding human-to-animal transmission solely. In addition to the two main goals, cross-species transmission, and species-specific SNVs, the authors have offered an evaluation and discussion of several species-specific SNVs that will aid the scientific community in the future in drawing connections between viral evolution, host biology, and epidemiological patterns related to SARS-CoV-2 across species.

Reviewer #2 (Public Review):

This work provides a method for extracting morphological features of cells and their neighborhoods from EM volumes in a self-supervised manner. The authors generate these MorphoFeatures using a set of neural networks, and show the usefulness of the features for cell type classification, symmetric partner identification, and the automated clustering of cells into morphologically similar groups, tissues and organs.

The main innovation of this method compared to similar studies is the separation of the input into shape, coarse, and fine texture. A combination of an auto-encoder (for texture features) and a contrastive loss (for all features) is used to obtain features without task-specific bias. The learned features are consistent with cell type when compared to manual annotations, and genetic markers. The distinction between shape, coarse, and fine features is not used beyond the development of the method.

The authors later include a descriptor of the cell's neighborhood, with the goal of automatically discovering tissues and organs. Clustering in this MorphoContextFeature space successfully delineates the different parts of the *P. dumerilii* ganglia, and shows some advantages over both manual segmentation and clustering in gene expression space. A detailed analysis of the method on finding tissues in the *P. dumerilii* foregut is given as an additional example.

Strengths

The use of an unsupervised method means that this method can be applied on data where no cell types are known a priori, and the authors have made clear that a cell type classification can be obtained from MorphoFeatures with minimal annotation. Used as a first exploratory pass, this method can help quickly guide and narrow the scope of further analysis.

By separately obtaining features at three levels of resolution, the method has the potential to pinpoint the structural features most predictive of a cell type more precisely than a single-resolution method. Most interestingly, Figure 3 indicates that the learned features are visually meaningful: this would greatly increase the impact of such a method, as it would lead to testable hypotheses.

The training method that the authors suggest for the neural network is sound, and successfully avoids the potential pitfalls of using augmentation with a contrastive loss in a situation where shape is an important signal. Similarly, the authors appropriately choose clustering methods that can discover clusters of varying sizes.

The authors make good use of prior knowledge to confirm the hypotheses generated by clustering cells in MorphoFeature space. They include specific genetic explanations for both expected and unexpected clusters found (figures 5 and 6), and provide clear indication where the gene expression atlas does not give an explanation for a MorphoFeature cluster (Figure 6D). The examples given for clustering in the MorphoContextFeature space are similarly clear and well supported by additional data (figures 8 and 9).

Weaknesses

1. In the section on "visually interpretable" features, I would have liked a more quantitative idea of how many features the authors considered meaningful, and how those can be found. For example, are the six features shown in Figure 3 particularly meaningful, or were they chosen among many? A discussion of the feature selection protocol would be useful for replicating the method on new data. Furthermore, a supplementary figure with some of the features which are not meaningful would give the reader a better idea of the range of interpretability to expect.

2. The section on MorphoContextFeatures is missing a comparison with the MorphoFeatures. This made it unclear to me whether adding the neighborhood information is necessary for the discovery of tissues and organs. This could be remedied with a supplementary figure showing the same analysis as in figures 7 and 8 on the MorphoFeatures without the additional neighborhood information. Alternatively, since the MorphoFeatures are a subset of the MorphoContextFeatures, the authors could run a post-hoc analysis of whether the MorphoFeatures or the neighborhood features best explain the inter-class variance.

3. Finally, some extra guidance is needed to replicate this work on new data. In particular the following points could use more discussion:

3.1. How to choose the size of the MorphoFeatures vector - did the authors attempt a number other than 80 and if so, what was affected by this choice?

3.2. The protocol for when and how to define sub-clusters - were the chosen thresholds based on prior knowledge such as known tissues/organs? What do the authors suggest if this kind of information is missing?

3.3. How to link the obtained clusters back to specific, potentially meaningful, MorphoFeatures. For example, does the distinctive shape of the enteric neurons in cluster 8.3 of figure 5 correspond to an extreme of the cytoplasm shape feature described in figure 3 (lower left)?

Reviewer #2 (Public Review):

Lee, Chen, Kaku, Zhuo et. al. demonstrate that a single injection of ube3a-ASO in a new mutant ube3a mouse model restores Ube3a protein expression and EEG function and sleep patterns. A key feature of these findings is the development of a new mouse model that eliminates any expression of ube3a mRNA. Moreover, they demonstrate that the impact of their treatment can last up to 6 weeks. They determine that the phenotype correction correlates with Ube3a protein level. There is an impressive amount of work that has gone into this study. It does appear, however, that much of this work is derivative of previous studies. It is less clear what is novel. While a new mouse model is introduced, it is unclear whether such a mouse model is any better defining Angelman syndrome than previous models. Several conclusions appear to be a bit too strong based on the modesty of the findings. For example, it is not clear that the current findings constitute a strong enough foundation for future drug studies.

Overall, this study describes another set of potentially interesting findings using ASO to restore Ube3a expression and phenotypic rescue. Not all phenotypes are tested, not every tested phenotype shows truly robust changes that would encourage one to move to clinical trials.

The authors did succeed in describing this new mouse line at the level of ube3a expression, EEG, sleep patterns and poly-spikes. They did so across many brain regions and multiple ages. Within these findings and approaches, there is useful information that can benefit the field. The impact of this work is that the authors may have demonstrated an approach which will have a longer lasting impact on recovery. Such an advance would be a great benefit to the population of those greatly impacted by Angelman syndrome.

Reviewer #2 (Public Review):

It is my opinion that the principle utility of this approach lies in its ability to identify the set of 'easily learnable' stimulus-response mappings from neural data which makes strong behavioral predictions that can be easily evaluated. I envision a simple experiment in which empirically obtained kernel functions are used to rank stimulus-response mappings according to their learnability which can then be plotted against measures of performance like the observed learning rate and saturated performance. Because kernel functions are empirically obtained, there is even the potential for meaningful cross-species comparisons. If behaviorally validated, one could also use this approach to label cortical populations by the set of easily learned stimulus-response mappings for that population. This allows for the identification of task-relevant neurons or regions which can be subsequently manipulated to enhance or degrade learning rates.

Of course, any theoretical approach is only as good as the underlying assumptions and so while the primary strength is the simplicity and generality of this approach, the primary weakness is its neglect of some very real and very relevant aspects of neural data in particular and statistical learning in general. In particular, the three principle limitations of this work are tied to its reliance on the assumptions that (1) neurons are noiseless, (2) decoders are linear, and (3) learned weights are unbiased.

(1) Within this framework, a realistic stimulus-dependent noise model can be easily introduced and its effects on the kernel and set of easily learned stimulus-response mappings investigated. So while the kernel would be substantially altered via the addition of a realistic noise model, the applications of the approach outlined above would not be affected. The same cannot be said for the efficient coding application described in this manuscript. There, the authors note that rotations and constant shifts of neural activity do not affect the kernel and thus do not affect the generalization error. This kernel invariance is not present when a non-trivial (i.e. non-isotropic) noise model is added. For example, suppose that neurons are independent and Poisson so that noise scales with the mean of the neural response. In this case, adding a baseline firing rate to a population of unimodal neurons representing orientation necessarily reduces the information content of the population while rotations can affect the fidelity with which certain stimulus values are represented. It is important to note, however, that while this particular efficiency result is not compelling, I believe that it is possible to perform a similar analysis that takes into account realistic noise models and focuses on a broad set of 'biologically plausible' kernels instead of particular invariant ones. For example, one could consider noise covariance structures with differential correlations (Moreno-Bote 2014). Since the magnitude of differential correlations controls the redundancy of the population code this would enable an analysis of the role of redundancy in suppressing (or enhancing) generalization error.

(2) Similarly, the linearity assumption is somewhat restrictive. Global linear decoders of neural activity are known to be highly inefficient and completely fail when decoding orientation in the primary visual cortex in the presence of contrast fluctuations. This is because contrast modulates the amplitude of the neural response and doubling the amplitude means doubling an estimate obtained from a linear decoder even when the underlying orientation has not changed. While the contrast issue could be partially addressed by simply considering normalized neural responses, it is not yet clear how to extend this approach to account for other sources of neural variability and co-variability that cause global linear decoders to fail so badly.

(3) This analysis relies on the assumption that decoder weights learned in the presence of finite data are efficient and unbiased. This assumption is problematic particularly when it comes to inductive bias and generalization error. This is because a standard way to reduce generalization error is to introduce bias into the learned decoder weights through a penalization scheme that privileges decoder weights with small magnitudes. This kind of regularization is particularly important when neurons are noisy. Fortunately, this issue could be addressed by parameterizing changes in the kernel function by the degree and type of regularization potentially leading to a more general result.

Finally, I would like to conclude by explicitly stating that while the limitations imposed by the assumptions listed above temper my enthusiasm in regards to conclusions drawn in this work, I do not believe there is some fundamental problem with the general theoretical framework. Indeed, items 1 and 3 above can be easily addressed through straightforward extensions of the authors approach and I look forward to their implementation. Item 2 is a bit more troublesome, but my intuition tells me that an information-theoretic extension based upon Fisher information may be capable of eliminating all three of these limiting assumptions by exploiting the relationship between FI(\theta) and FI(y=f(\theta)).

Reviewer #2 (Public Review):

In the present study, Liu and colleagues set out to assess the mechanisms of the therapeutic action of FGF21 on non-alcoholic steatohepatitis in the setting of obesity and dyslipidemia. They used a liver-targeted adeno-associated virus to overexpress FGF21 as a method for chronic pharmacological-type treatment of the mice. They found that FGF21 overexpression in their mouse model prevented weight gain in high-fat, high-cholesterol (HFC) diet-fed mice, compared to the control virus on the HFC diet. In addition, many of the features of obesity, insulin resistance, and NAFLD are prevented by hepatic FGF21 overexpression in their model. The authors have performed extensive phenotyping and the results leave little doubt of the efficacy of the treatment.

My main concern with the study is the distinction between a therapeutic paradigm and the preventative paradigm employed here. Based on the body-weight curves, one might expect that real liver pathology never occurred in the FGF21-overexpressing animals. In which case, it is difficult to comment on the possibility of reversing these aspects in a therapeutic setting. This point is highly relevant to the ongoing clinical trials of FGF21 analogs for NASH that the authors have referenced.

A second point raised by the authors is the aspect of FGF21 increasing thermogenic adipose tissue activity. Their results showing FGF21-induced expression of UCP1 are not in doubt, but the fact that this increase alone is responsible for the observed phenotype is not clear. For example, FGF21 has been shown to be anorexigenic in certain models (non-human primates: Talukdar, et al. Cell Metab 2016, mini-pigs: Christoffersen, et al. Diabetes Obesity Metabolism 2019, among others). Moreover, there is evidence that some effects of FGF21-driven metabolic improvements do not require UCP1 (Samms, et al. Cell Reports 2015). Given the differences in brown fat activity and physiology between mice and humans, it would be important for the authors to either moderate their comments on the UCP1 dependence of their phenotype or provide more data to clarify to what extent their findings are UCP1-dependent (e.g. food intake in the FGF21 overexpression model and/or evidence of increased energy expenditure).

Reviewer #2 (Public Review):

Optogenetic proteins are important tools for circuit neuroscience. The authors characterize five proteins, GtCCR4, KnCHR2, BeGC1, bPAC, and OaPAC with respect to their ability to suppress normal cell excitability and compare the results to those for the more established GtACR1 and CrChR2[T159]. The study makes use of expression in the zebrafish heart and hindbrain, as well as in a cell line. Electrophysiology in the cell line demonstrates that GtCCR photo-activation induces similar currents as CrChR2 activation and shows less signs of desensitization. Using a transgenic vsx2:Gal4 zebrafish line, immunohistochemistry shows that the tools are expressed. When activated, they triggered the expected behavioral responses (swimming) at short latency (<4s). This was true even for the three tools that are guanylyl or adenylyl cyclases (BeGC1, bPAC, OaPAC) and thus affect cell excitability only indirectly. At the tested light intensity, the Klebsormidium nitens channelrhodopsin (KnChR) had the shortest latency (<0.5 s) and highest (100%) probabilities of inducing locomotion. When expressing the tools in the zebrafish heart, brief illumination (100 ms) induces brief (100 ms - 1500 ms) suppression of the heartbeat. Notably, also tools that evoke depolarization induce heartbeat suppression. Heartbeat movies and calcium imaging demonstrate that this is caused by prolonged cardiomyocyte contraction. The optogenetic guanylyl and adenylyl cyclases were not effective in perturbing zebrafish heartbeat (except for bPAC over longer time scales).

Given the large number of optogenetic proteins available to date and the challenge of employing them in well-controlled neuroscience experiments, this study presents an important contribution for neuroscientists performing optogenetic research in animal models. Two light-gated cation channels, GtCCR4 and KnChR, are tested for the first time in vivo. The evidence supporting the claims regarding heartbeat and induced swimming behavior is solid. Since GtCCR4 is more Na+-selective than other channelrhodopsins, it should allow better control of experimental variables and is a valuable addition to the optogenetic tool box. The created transgenic zebrafish lines will be useful for the zebrafish neuroscience community.

The expression in zebrafish was compared using immunohistochemical staining (of a single Gal4 driver line). From this experiment alone, it is difficult to judge the expression level, the in vivo visibility of the fluorescence under the microscope, and the proportion of target cells that do express the optogenetic gene of interest.

The evidence for optogenetically induced alteration of swimming behavior is compelling. However, the associated neuronal responses and their dependence on different light intensity levels remain uncharacterized. Therefore, if anyone plans to use these tools to investigate a neural circuit in the future, the needed light levels and the specificity of the manipulation would still need to be determined.

For the optogenetic guanylyl and adenylyl cyclases, which clearly were able to alter behavioral responses, the signaling and circuit mechanisms that lead to neuronal depolarization remain unknown, but possible activation pathways are discussed.

Reviewer #2 (Public Review):

The presented study aims at deciphering the physiological function of GPCR signaling in excitable cells. To this end, the authors developed transgenic zebrafish models expressing a selection of Gq- and Gi/o-coupled bistable rhodopsins in either reticulospinal neurons or cardiomyocytes and elucidated behavioral responses (tail movements) or physiological responses (heartbeat) as well as intracellular Ca2+ dynamics following optical stimulation of rhodopsins.

One of the major strengths of the presented study is the functional comparison of five Gq- and five Gi/o-coupled rhodopsins in two major classes of excitable cells, however; the selection of rhodopsins tested remains elusive. More importantly, it is not obvious why some of the effects of rhodopsin activation were assessed in both neurons and cardiomyocytes, while others were only tested in one of the two systems without further explanation. The main chosen experimental readouts (swimming/tail bending or cardiac contractions) have limited informative value regarding GPCR signaling, as they will only report the peak of the iceberg, namely whether movements are elicited or heartbeats inhibited. No analysis on subtle changes in heart rate and contraction force was included, but such modulation of cardiac activity (e.g. positive or negative chronotropic, inotropic, dromotropic, bathmotropic, and/or lusitropic responses) would represent better the physiological modulation of the heart via GPCR and down-stream signaling events. In line, the presented data only represents behavior at one light intensity tested, whereas a light titration of observed effects could provide more meaningful insight into both rhodopsin responses and signaling mechanisms. Also, the potential promiscuity of G protein activation of selected receptors has not been addressed, neither experimentally nor in the discussion part. As a result of the above-mentioned limitations, it is difficult to follow the logic of the study and especially to interconnect the data obtained in reticulospinal neurons (where activation of jumping spider rhodopsin elicited tail bending) to myocyte data (where three Gi-coupled rhodopsins suppressed cardiac activity). Moreover, as such, the study does not provide explanations on why a certain tool might evoke an effect in one system or the other, or not, which could be the main deliverable of such a comparative analysis.

While the presented data is interesting, the graphical presentation and description of the data are insufficient. Most importantly, the current version of the text does not include a quantitative description of effects and statistical analyses (which are found in the figures and legends!). The lack of quantitative description also extends to both the introduction and discussion, which remain general without a specific dissection of observed effects.

One major concern is the selective citation of own work. While single statements in both the introduction and discussion are supported by up to ten own papers, recent studies using rhodopsins for dissecting GPCR signaling in neurons are not sufficiently discussed and new data is not compared to published results by other teams. Moreover, relevant papers on cardiomyocytes (e.g. PMID: 35579776, 35365606, 34987414, 30894542) are not cited at all, despite the use of similar rhodopsins and/or optogenetic activation of the same signaling pathways. Taking into account these published studies may help to better understand the observed responses.

Additional comment: Data were obtained from larvae zebrafish. It would be useful to include a discussion on how GPCR signaling might be different in adult fish compared to larvae, and how to test whether the observed effects are more generally applicable.

Reviewer #2 (Public Review):

The reciprocal adaptation of host immune systems and pathogens leads to complex co-evolutionary dynamics. How this dynamical process shapes host and pathogen diversity is a fundamental question in immunology and virology. To study this question experimentally, the CRISPR-Cas system which some prokaryotes use for adaptive immunity against phages has recently emerged as an important model system. In this system both host and viral adaptation can be read out by sequencing, as CRISPR-Cas immunity is guided by genomic spacers incorporated into the host genome. In this context, the current work presents a welcome deep dive into the dynamical regimes predicted by a simple phenomenological model of the co-evolution between CRISPR loci and phages. Among the notable results are the following: First, diversity primarily depends on a single scalar parameter, and does so in a sublinear manner. Second, different types of cross-reactivity are linked to different shapes of viral phylogenies. Third, comparison of spacer turnover and average immunity between theoretical and experimental timeseries data provides hints as to the operative regime in different CRISPR systems. These results together with the extensive discussion should be greatly useful in guiding further work in this field. There are many avenues for further theoretical work generalizing to less simplifying assumptions, and importantly, many concrete suggestions for future experiments.

Reviewer #2 (Public Review):

In this manuscript, Karsenty et al. describe postnatal development in the rat between P20 and P60 where crests of the cardiomyocyte lateral membranes mature. The authors previously described these crests in a Cardiovascular Res paper, where they highlighted how they facilitate interactions between cardiomyocytes in claudin-5 dependent manner. The authors previously also reported claudin-5 ephrin-b1 interactions on the cardiomyocyte lateral surface. Presently, the authors try to link together the following observations: a) crest height, mitochondrial number and area increase from postnatal day 20 to 60 in rats, and this correlates with increase claudin-5 expression, as well as gene expression accessed by microarray; b) changes in diastolic function occur in rats between days 20 and 60 postnatal life; c) cardiomyocyte-specific knockout of ephrin-b1 leads to diastolic dysfunction and a heart failure with preserved ejection fraction like phenotype.

The major strength of the paper is the detailed analysis of postnatal cardiomyocyte structure using electron microscopy and echocardiography. However, there are multiple major weaknesses of the methodology that should be clarified.

1. Most importantly, it is unclear how these mice are maintained. The authors explain the mice are in a mixed background. If this is the case, it is extremely important that littermate controls are used. Otherwise, it is very difficult to interpret the physiological data if the animals being compared are from two separate crosses.

2. The authors should clarify the echo and cath data in mice and rats. First with respect to the rat data, the end-diastolic pressure of the p60 rats reported in Figure 3 is around 9 mmHg. This is significant and abnormal, and also unexplained. More globally, the authors conclusion that "diastolic maturation" is occurring should be tempered by the fact that loading conditions at these two postnatal days are completely different, as highlighted by the blood pressures of the animals (~70/40 at p20 vs ~120/80 at P60). Third, the heart rates are significantly higher at p60 vs p20 in panel A, but not panel B. The authors report these studies were performed under isofluorane, so I imagine this reflects differences in anesthesia, which can significantly affect the heart rate and thus the diastolic parameters (particularly IVRT), so this should at least be commented on as a significant limitation.

With respect to data interpretation and whether the results are correctly interpreted, the following considerations should be taken into account:

1. The author conclusions in Figure 2d appear overstated. While the methodology of figure 2d is explained in the figure panel, it is generally looked over in the main text. Is there any precedent for utilizing human single-cell sequencing in this purpose - essentially the authors are superimposing the rat P20 and P60 data on the human UMAP plot. The authors walk back the statement in the text and clarify that these genes are expressed in the following cell types in adult human hearts.

2. The ephrin-b1 cardiomyocyte specific knockout mice are not a model of HFpEF. These mice show an accelerated death rate and clear evidence of progressive systolic impairment. Furthermore, it is completely unclear that the murine diastolic parameters are meaningfully different, and hence the overall evidence presented that this is a HFpEF phenotype is weak.

Reviewer #2 (Public Review):

The authors present a compendium of diffusion MR, dynamic contrast-enhanced MR, histological, and other results in AQP4 KO vs. WT mice which suggest that AQP4 deletion results in stagnation of interstitial fluid movement, enlargement of interstitial volume, and an increase in total brain water. The authors also provide evidence that these effects do not arise due to changes in CSF production, perfusion, or vascular density, strengthening the conclusion that AQP4 is specifically involved in modulating parenchymal resistance, rather than another aspect of glymphatic function. While the study of AQP4 deletion using various MR and histological methods is not novel per se, the breadth of concurrent methodological approaches presented here is uncommonly extensive, and thus provides a strong, self-contained case for the conclusion(s) - more so than other works on such mouse models. The key strength and utility of this work lie in the extent of corroborating evidence provided for the conclusions.

Another strength of the paper is the development of what appears to be a robust CSF space segmentation approach, which may be of interest to others aiming to quantify glymphatic function using MR. The source code, however, is not provided at this time.

I have some concerns, specifically about the discussion around transmembrane water exchange - i.e., whether the exchange is truly being measured by the diffusion MR methods - and about the validity of applying an IVIM signal model across the brain. These concerns, however, do not affect the major conclusions of the paper. Indeed, the authors have included analyses using standard ADC fitting which avoids the issues with IVIM. In summary, the paper presents a compelling body of evidence describing the effects of AQP4 deletion in mice.

Reviewer #2 (Public Review):

The manuscript by Niu and colleagues reported that ET after mastectomy did not prolong the DFS of Chinese HR+ DCIS patients, but rather increased adverse effects. For the first time, the authors analyzed the beneficial effect and safety of ET after mastectomy in Chinese patients with HR+ DCIS through the clinical case review. The conclusion of this study is of great significance to guide the choice of appropriate treatment for Chinese patients with HR+ DCIS, and it has obvious benefits to reduce the economic burden of the patient's family and improve the quality of life for patients.

Reviewer #2 (Public Review):

Although many broadly-neutralizing antibodies were discovered against virus accumulating mutations such as HIV, Influenza, and Sars-CoV-2, the methodology to induce such antibodies or design to generate them is highly demanded. The authors take the broadly-neutralizing antibody, CH65 as a model antibody and try to recapitulate the generation of the broadly-neutralizing antibody from an unmutated common ancestor over time. By performing Tite-Seq assays, Epistasis analysis, Pathway analysis, and Affinity measurement, and structural study, the authors proposed a scenario of the evolution of CH65.

Strengths<br /> Combining the models and affinity/structure data, the authors enable us to show the possible track of gaining the breadth of the CH65 antibody from the unmutated repertoire. Using the Tite-Seq assay, the authors took a forward genetics approach which is high-throughput and non-bias and mimics the situation of the evolution of a B cell repertoire in an individual over time. The data is robust, and its outcome will provide an opportunity to build a prediction model to design the antibody in silico. Especially their identification of amino acid positions important for epistasis mode in antibody evolution is valuable. Antigen selection scenarios are decisive in this study.

Weakness<br /> The proposed scenarios cannot be tested using human CH65. The readers would have great interest in how these hypothetical scenarios are fitting to the evolution occurring in vivo situation, especially in a quantitative way. The broadly neutralizing antibodies often react with self-antigens as the authors cite previous work(ref 19). How do these environmental factors affect the evolution of the antibody? These already-known facts could be mentioned and discussed in detail.

Reviewer #2 (Public Review):

Huang Mi, et al. investigated the role of MTIF3, the mitochondrial translation initiation factor 3, in the function of adipocytes. They first detected the expression of the obesity-related MTIF3 variants based on the G5Ex database and found two variants lead to an increase in MTIF3 expression. Then they knockout MTIF3 in differentiated hWAs adipocytes and characterized the mitochondrial function. They found loss of MTIF3 decrease mitochondrial respiration and fatty acid oxidation. They further treated cells with low glucose medium to mimic weight loss intervention and found MTIF3 knockout adipocytes lose fewer triglycerides than control adipocytes. This paper provides new information about MTIF3 in adipocytes and the potential functional role of MTIF3 in mitochondrial function.

1. The authors provided sufficient data to show those two genetic variants increase MTIF3 expression. Their CRISPR/Cas9 knockin cell line is also convincing. But they didn't show if the genetic variants affect adipogenesis. Adipogenesis is an important process for weight gain and fat deposition. In lines 103-107, the authors mentioned that the "allele-edited cells have some problem in differentiated state, e.g. triglyceride or mitochondrial content", so they used an inducible Cas9 system. However, the issue of differentiated allele-edited cells may be the functional effect of MTIF3 genetic variants, such as interrupting adipogenesis, decreasing triglyceride, or affecting mitochondrial number. The authors should provide that information.

2. In Figure 4, the author mentioned that MTIF3 knockout does not affect the expression of adipogenic differentiation markers. They need to provide more evidence to prove their point. Oil-red O staining is a clearer way to quantify adipocyte differentiation in cell culture. In addition, in Fig. 4B western blot, the author should include MTIF3 as a control to show the knockout efficiency. It is not clear the meaning of plus and minus in that panel. The author should also compare the total triglyceride levels in MTIF3 knockout cells and control cells.

3. MTIF3 is a translation initiation factor in mitochondria and is involved in the protein synthesis of mitochondrial DNA-encoding genes. The authors should check protein levels rather than the mRNA levels of mitochondrial DNA-encoding genes (Fig. 6E). It's interesting to see the increase of mRNA levels of ND1 and ND2, which might be feedback of lower translation. Since ND1 and ND2 are in OXPHOS complex I, the expression levels of complex I in MTIF3 KO cells would be worth checking. Additionally, the author should also check the mitochondria copy number.

4. MTIF3 knockout adipocytes retain more triglycerides under glucose restriction is interesting. It may link to the previous result of lower fatty acid oxidation in MTIF3 knockout adipocytes. However, the authors then showed there is no difference in lipolysis. The author should discuss those results in the manuscript. The authors could also check lipolysis in glucose restriction conditions. It's also necessary to include the triglyceride levels of KO cell lines at full medium.

Reviewer #2 (Public Review):

The authors present a manuscript that addresses an important topic of bacterial co-existence. Specifically modeling infection-relevant scenarios to determine how two highly antibiotic-resistant pathogens will develop over time. Understanding how such organisms can persist and tolerate therapeutic interventions has important consequences for the design of future treatment strategies.

A major strength of this paper is the methodical approach taken to assess the dynamics between the two bacterial species. Using carbon sources to regulate growth to test different community structures provides a level of control to be able to directly assess the impact of one dominant pathogen over another.

The modeling aspect of this manuscript provides a basis for testing other disturbances and/or the impact of additional incoming pathogens. This could easily be applied to other infection settings where multiple microbes are observed ( for example viral/bacterial interactions in the lung).

The authors clearly show that by altering the growth rate and metabolism of various carbon sources, population structure can be modified, with one out-competing the other. Both modeling and experimental approaches support this.

The exploration of the role of virulence factors is less clear, for example how strains unable to produce virulence factors are impacted in regard to their overall growth and whether S. aureus is able to sense virulence factors without transcriptional assays here. Although the hypothesis is strong, the experimental data does not fully support this conclusion.

Spatial disturbance has a significant impact on community structure. Although using one approach to assess this, it is not clear if the spatial structure is impacted without the comparable microscopy evaluation.

Overall this paper highlights the use of modeling approaches in combination with wet lab experiments to predict microbial interactions in changing environments.

Reviewer #2 (Public Review):

The idea that decidualization is related to or evolved from wound healing, including fibroblast activation, is old, going back all the way to Creighton 1878 who pointed to the similarity between granulation tissue and decidual tissue, and is supported by the fact that embryo implantation is a compensated form of the endometrial lesion. Nevertheless, the mechanistic connection between FB activation and decidualization is an important fact necessary for understanding decidualization, a fact that is reflected in previous work, for instance, Kim et al., 1999 (Hum Reprod 14 Suppl 2), their reference 20, and Oliver et al., 1999 (Humn Reprod 14), their reference 56 a.o.m. More specifically, a recent single-cell study of in vitro decidualization has shown that a myofibroblast-like cell state is a transient state in the process of decidualization, i.e. decidual cells themselves are not so much activated fibroblasts, but rather decidual cells differentiate after endometrial stromal fibroblasts undergo a FB activation like process, and the decidual re-programming happens from these activated FB like states (Stadtmauer et al., 2021, Biol. of Reprod. 1-18).

The above assessment of how the current study fits into the conceptual landscape of mammalian reproductive biology does not diminish the importance of the paper under consideration. The study contributes a large amount of observational and experimental facts to the understanding of how FB activation and decidualization are related. The authors suggest, in particular, that blastocyst-derived TNF activates the cLPA-producing Arachidonic acid (AA), activating PGI2 and PPARd signaling pathway (more about this later).

Other major comments:

The authors suggest that luminal epithelial cells signal through the release of arachidonic acid (AA) in response to TNF. That is interesting and supported by in vitro experiments inducing decidualization and FB activation by AA. What makes this conclusion a little problematic is that it is known that luminal epithelial cells also express COX2/PTGS2 and thus the synthesis of prostaglandins is already starting in the LE and thus LE can also signal to the stoma via PGE2, PGI2 as well as PGL2 rather than AA directly. The in vitro experiments can not exclude the possibility that the ESF is producing some prostaglandin and then having an autocrine effect.

344: here the authors report that PGE2 has no effect on FB activation marker expression, but the problem with that is, that (at least in human ESF), progesterone is causing a change in the expression of the PGE2 receptors from EP4 to EP2, and it is only the EP2 receptor that activates cAMP/PKA pathway.

The fact that the authors show an effect of PGI2 is interesting because PGI2 receptors are among the strongest expressed PTG receptors in mammalian ESF. Prostacyclin receptor is a GPCR rather than a nuclear receptor. So the question is really why the authors have not pursued the role of prostacyclin receptor and instead have focused on PPARd?

Reviewer #2 (Public Review):

The manuscript of Xu and colleagues examines in detail the regulation of the important transcription factor IRF8 in dendritic cell (DC) subsets. They identify a long noncoding RNA arises from the +32kb enhancer of IRF8 specifically in plasmacytoid DCs (pDCs)and show clearly that this lncIRF8 marks the activity of a region of this enhancer but the RNA itself does not appear to have any function. Deletion of the promoter of the lncIRF8 ablated cDC1 and pDC differentiation using an in vitro cell differentiation model. The authors propose an innovative model that the lncIRF8 promoter sequences act to limit IRF8 expression in cDC1, but are inactive in pDCs, resulting in their characteristically very high IRF8 expression.

This is a conceptually interesting study that makes excellent use of an extensive set of genomic data for the DC subsets. There has been a lot of recent research investigating the regulation of the IRF8 gene in hematopoiesis and this study provides an important new aspect to the work. The use of an in vitro model of DC differentiation is a powerful practical approach to investigating IRF8 regulation, as is the innovative use of CRISPR technology. Perhaps the biggest limitation of this study is that the authors have not conformed to the in-cell system data by creating a mouse strain lacking the lncIRF8 element. Such approaches by others, most notably the Murphy lab, have been instrumental in pushing this field forward. Nevertheless, Xu et al. significantly add to our current knowledge of the regulation of IRF8, a critical step in forming the dendritic cell network.

Reviewer #2 (Public Review):

Slusarczyk et al. investigate the functional impairment of red pulp macrophages (RPMs) during aging. When red blood cells (RBCs) become senescent, they are recycled by RPMs via erythrophagocytosis (EP). This leads to an increase in intracellular heme and iron both of which are cytotoxic. The authors hypothesize that the continuous processing of iron by RPMs could alter their functions in an age-dependent manner. The authors used a wide variety of models: in vivo model using female mice with standard (200ppm) and restricted (25ppm) iron diet, ex vivo model using EP with splenocytes, and in vitro model with EP using iRPMs. The authors found iron accumulation in organs but markers for serum iron deficiency. They show that during aging, RPMs have a higher labile iron pool (LIP), decreased lysosomal activity with a concomitant reduction in EP. Furthermore, aging RPMs undergo ferroptosis resulting in a non-bioavailable iron deposition as intra and extracellular aggregates. Aged mice fed with an iron restricted diet restore most of the iron-recycling capacity of RPMs even though the mild-anemia remains unchanged.

Overall, I find the manuscript to be of significant potential interest. But there are important discrepancies that need to be first resolved. The proposed model is that during aging both EP and HO-1 expression decreases in RPMs but iron and ferroportin levels are elevated. In their model, the authors show intracellular iron-rich proteinaceous aggregates. But if HO-1 levels decrease, intracellular heme levels should increase. If Fpn levels increase, intracellular iron levels should decrease. How does LIP stay high in RPMs under these conditions? I find these to be major conflicting questions in the model.

Reviewer #2 (Public Review):

Xie et al. investigated the medial temporal lobe (MTL) circuitry contributions to pattern separation, a neurocomputational operation to distinguish neutral representations of similar information. This presumably engages both long-term memory (LTM) and working memory (WM), bridging the gap between the working memory (WM) and long-term memory (LTM) distinction. Specifically, the authors combined an established retro-cue orientation WM task with high-resolution fMRI to test the hypothesis that the entorhinal-DG/CA3 pathway retains visual WM for a simple surface feature. They found that the anterior-lateral entorhinal cortex (aLEC) and the hippocampal DG/CA3 subfield both retained item-specific WM information that is associated with fidelity of subsequent recall. These findings highlight the contribution of MTL circuitry to item-specific WM representation, against the classic memory models.

I am a long-term memory researcher with expertise in representational similarity analysis, but not in inverted encoding modeling (IEM). Therefore, I cannot verify the correctness of these models and I will leave it to the other reviewers and editors. However, after an in-depth reading of the manuscript, I could evaluate the significance of the present findings and the strength of evidence supporting these findings. The conclusions of this paper are mostly well supported by data, but some aspects of image acquisition and data analysis need to be clarified. I would like to list several strengths and weaknesses of this manuscript:

Strengths:<br /> • Methodologically, the authors addressed uncertainty in previous research resulting from several challenges. Namely, they used a high-resolution fMRI protocol to infer signals from the MTL substructures and an established retro-cue orientation WM task to minimize the task load.<br /> • The authors selected a control ROI - amygdala - irrelevant for the experimental task, and at the same time adjacent to the other MTL ROIs, thus possibly having a similar signal-to-noise ratio. The reported effects were observed in the aLEC and DG/CA3, but not in the amygdala.<br /> • Memory performance, quantified as recall errors, was at ceiling - an average recall error of 12 degrees was only marginally away from the correct grating towards the closest incorrect grating (predefined with min. 20 degrees increments). However, the authors controlled for the effects of recall fidelity on MTL representations by comparing the IEM reconstructions between precise recall trials and imprecise recall trails (resampled to an equal number of trials). The authors found that precise recall trails have yielded better IEM reconstruction quality.<br /> • The author performed a control analysis of time-varying IEM to exclude a possibility that the mid-delay period activity in the aLEC-DG/CA3 contains item-specific information that could be attributed to perceptual processing. This analysis showed that the earlier TR in the delay period contains information for both cued and uncued items, whereas the mid-delay period activity contains the most information related to the cued, compared to uncued, item.

Weaknesses:<br /> • The authors formulate their main hypothesis building on an assumption related to the experimental task. This task requires correctly selecting the cued grating orientation while resisting the interference from internal representations of the other orientation gratings. The authors hypothesize that if this post-encoding information selection function is supported by the MTL-s entorhinal-DG/CA3 pathway, the recorded delay-period activity should contain more information about the cued item that the uncued item (even if both are similarly remembered). Thus, the assumption here is that resolving the interference would be reflected by a more distinct representation in MTL for the cued item. Could it be the opposite, namely the MTL could better represent the unresolved interference, for example by the mechanism of hippocampal repulsion (Chanales et al., 2017). It could strengthen the findings if the authors comment on the contrary hypothesis as well.<br /> • It is not clear for me why the authors chose the inverted encoding modelling approach and what is its advantage over the others multivoxel pattern analysis approaches, for example representational similarity analysis also used in this study. How are these two complementary? Since the IEM is still a relatively new approach, maybe a little comment in the manuscript could help emphasizing the strength of the paper? Especially that this paper is of interest to researchers in the fields of both working memory and long-term memory, the latter being possibly not familiar with the IEM.

Overall, this work can have a substantial impact of the field due to its theoretical and conceptual novelty. Namely, the authors leveraged an established retro-cue task to demonstrate that a neurocomputational operation of pattern separation engages both working-memory and long-term memory, both mediated by the MTL circuitry, beyond the distinction in classic memory models. Moreover, on the methodological side, using the multivariate pattern analyses (especially the IEM) to study neural computations engaged in WM and LTM seems to be a novel and promising direction for the field.

Reviewer #2 (Public Review):

This paper reports that neonatal CD43- B cells produce IL-10 upon BCR stimulation, which inhibits TNF-alpha secretion from the peritoneal macrophage. In the neonatal CD43- B cells, the BCR-mediated signal transmitted Stat5 activation and induced IL-6 production, and subsequently, the secreted IL-6 activated Stat3 finally leading to IL-10 production. The authors identified a unique signaling pathway leading to IL-10 production and revealed the different responses between CD43+ and CD43- B cells against BCR crosslinking. A weakness of this study is that the neonatal CD43- B cell subset secreting IL-10 has not been characterized and discussed as well. BCR expression levels between adult CD43- B cells and neonatal CD43- B cells have been overlooked to explain the different reactivity. Clarity on these points would substantially enhance the impact of the manuscript.

Reviewer #2 (Public Review):

The Kaiser lab has been on the forefront in understanding the mechanism of dopamine release in central mammalian neurons. assessing dopamine neuron function has been quite difficult due to the limited experimental access to these neurons. Dopamine neurons possess a number of unique functional roles and participate in several pathophysiological conditions, making them an important target of basic research. This study here has been designed to describe the proteome of the dopamine release apparatus using proximity biotin labeling via active zone protein domains fused to BirA, to test in which ways its proteome composition is similar or different to other central nerve terminals. The control experiments demonstrating proper localization as well as specificity of biotinylation are very solid, yielding in a highly enriched and well characterized proteome data base. Several new proteins were identified and the data base will very likely be a very useful resource for future analysis of the protein composition of synapse and their function at dopamine and other synapses.

Major comment:

The authors find that loss of RIM leads to major reduction in the number of synaptically enriched proteins, while they did not see this loss of number of enriched proteins in the Syt1-KO's, arguing for undisrupted synaptome. Maybe I missed this, but which fraction of proteins and synaptic proteins are than co-detected both in the Syt1 and control conditions when comparing the Venn diagrams of Fig2 and Fig 3 Suppl. 2? This analysis may provide an estimate of the reliability of the method across experimental conditions.

Reviewer #2 (Public Review):

This paper identifies the need for improved pre-clinical models for the study of human primordial germ cells (PGCs) and suggests the common marmoset (Callithrix jacchus) as a suitable primate model. In vitro gametogenesis offers an alternative method to generate germ cells from pluripotent stem cells for study and potential pre-clinical applications. Therefore, the authors aimed to take the first steps toward developing this technology for the marmoset. Here, iPSCs have been derived from the marmoset and differentiated to PGC like-cells (PGCLCs) in vitro that have similarities in gene expression with PGCs identified from single-cell studies of marmoset embryos, as demonstrated through immunofluorescence and RT-qPCR approaches, as well as RNA-sequencing.

The authors have successfully developed a protocol that produces PGCLCs from marmoset iPSCs. These are shown to express key germline gene markers and are further shown to correlate in gene expression with PGCs from the marmoset. This study uses a 2D culture system for further expansion of the PGCLCs. When cultured with mouse testicular cells in a xenogeneic reconstituted testis culture, evidence is provided that cjPGCLCs have the capacity to develop further, expressing marker genes for later germline differentiation. However, the efficiency of generating these prospermatogonia-like cells in culture is unclear. Nonetheless, with the importance of developing protocols across species for in vitro gametogenesis, this paper takes a key step towards generating a robust preclinical system for the study of germ cells in the marmoset.

The claims of the authors are generally justified by the data provided; however, some conclusions should be clarified. In particular, the authors have failed to show convincingly that cjPGCLCs are a distinct cell type to the iPSCs that generated them. cjiPSCs cultured in feeder conditions (OF) with IWR1 are reported to cluster closely with the derived cjPGCLCs using principal component analysis of RNA-Seq data. This contrasts with the cjiPSCs cultured in feeder-free (FF) conditions which maintain a more undifferentiated/less primed state, and are not capable of differentiating to the germline lineage. Therefore, the OF/IWR1 cjiPSCs could rather be an intermediate cell-state between iPSCs and cjPGCLCs.

The reasons behind improved germline competence of iPSCs in the different media conditions are unclear. The authors reject the idea that this is due to the presence of IWR1, since this condition has not affected FF iPSCs. However, the efficiency of differentiation was greatly increased in OF conditions when IWR1 was used, indicating inhibition of WNT does indeed have a positive effect on induction to the germline lineage. This area requires further clarification.

Another area requiring clarification is the reporting of RNA sequencing data as representative of a developmental trajectory, without defining which cell lines produced clusters, or defining the stages of this trajectory. The authors refer to the identification of four clusters representative of a developmental trajectory, however, they provide unclear information as to what this refers to. Importantly, detailed transcriptomic comparisons between in vivo-derived PGCs and in vitro PGCLCs are not provided.

Functional validation of iPSC lines generated in the study is not provided besides confirming that the cells express pluripotency markers OCT3/4, SOX2, and NANOG. It is important to confirm tri-lineage differentiation of iPSCs, e.g., through an embryoid body assay. Since FF cjiPSCs were unable to differentiate into cgPGCLCs, it is even more important to confirm cells are genuine iPSCs.

In summary, although there are issues surrounding clarity, this paper is generally justified in its conclusions. The authors present an optimised protocol for the derivation of PGCLCs from marmoset iPSC-like cells, with defined expansion conditions and evidence of further differentiation to prospermatogonia-like cells.

Reviewer #2 (Public Review):

Many cancers, including pancreatic tumors, host microbes that have the ability to metabolize anti-cancer drugs, thus altering cancer response to these treatments. However, many anti-cancer drugs also are quite toxic to bacteria. Thus, the authors first investigate how a model bacterium that could live pancreatic tumors can become resistant to the pancreatic chemotherapy gemcitabine. Second, they investigate how bacteria that are resistant to gemcitabine impact cancer cell response to this therapy compared to bacteria that are not resistant. By answering these two questions, the authors hope to determine how bacterial evolution to chemotherapy can impact how well chemotherapy works in pancreatic cancer.

To answer the first question, the authors perform both genetic screens and laboratory evolution experiments of E. coli bacteria exposed to gemcitabine. Both the genetic screen and laboratory evolution experiments identified mutation of the bacterial protein nupC as mediating bacterial resistance to gemcitabine. NupC is the transporter protein that bacteria use to take up gemcitabine. Thus, the authors conclude that loss of ability to take up gemcitabine would likely underlay bacterial evolution to gemcitabine in pancreatic tumors.

To answer the second question, the authors take either control of nupC mutant bacteria and expose these to gemcitabine. They then take the bacterial media with its residual gemcitabine and treat mouse colorectal cancer cells with these media. They find the amount of gemcitabine is higher in nupC mutant media and media from these mutants cause correspondingly higher killing of cancer cells.

Thus, the authors conclude that bacteria become resistant to gemcitabine by not taking it up, leaving more gemcitabine around in tumors to kill the cancer cells. The findings of the first question are a major strength of the manuscript - the complementary genetic screen and laboratory evolution experiment convincingly show that loss of nupC is likely a major genetic route for bacteria to become resistant to gemcitabine. Excellent biochemical studies delineate mechanistically how the different mutations including nupC contribute to gemcitabine resistance in the bacteria.

However, a major weakness of the manuscript is the extension to how this laboratory evolved nupC resistance to gemcitabine influences tumor response to gemcitabine. The only experiments done to assess this are performed in colorectal cell culture models in vitro. Importantly, these in vitro models do not recapitulate chemotherapy resistance observed in pancreas cancer and utilize levels of bacteria and gemcitabine that are likely not relevant to tumor physiology. Thus, additional experiments assessing in vivo if nupC mutations become prevalent in the pancreatic tumor microbiome and how much mutations affect tumor gemcitabine levels and response will be necessary to fully answer the authors second question of how bacterial evolution to gemcitabine affects tumor response to this agent.

Reviewer #2 (Public Review):

The paper provides a natural extension of 2D multiphase field models for cell monolayers to 3D, addressing cell deformations, cell-cell interaction, cell-substrate interactions and active components for the cells. As known from 2D, the cell arrangement leads to positional (hexatic) defects and if the elongation of the cells is coarse-grained to define a global nematic order also to orientational (nematic) defects. These defects are characterized, see Figure 2. However, this is done in 2D and it remains unclear if the projected basal or apical side is considered in this figure and the following statistics. The authors identify correlations between orientational defects and extrusion events. In terms of positional defects such statistics seem not to be considered and the relation between positional defects and cell extrusion events remains vague. Also in-plane and out-of-plane stresses are computed. These results confirm a mechanical origin for cell extrusions. However, these are the only 3D information provided. The final claim that the results clearly demonstrate the existence of a mechanical route related with hexatic and nematic disclinations is not clear to me. 3D vertex models for such systems e.g. showed the importance of different mechanical behavior of the apical and basal side and identified scutoids as an essential geometric 3D feature in cell monolayers. These results are not discussed at all. A comparison of the 3D multiphase field model with such results would have been nice.

Reviewer #2 (Public Review):

Skeletal muscle is the main regulator of glycemia in mammals and a major puzzle in the field of diabetes is the mechanism by which skeletal muscle (as well as other tissues) become insensitive to insulin or decrease glucose intake. the authors had proposed in a previous publication that high intracellular calcium, by means of calpain activation, could cleave and decrease the availability of GLUT4 glucose transporters. In this manuscript, the authors identify two additional targets of calpain activation. One of them is GSK3β, a specialized kinase that when cleaved, inhibits glycogen synthase and impairs glucose utilization. The second target is junctophilin 1, a protein involved in the structure of the complex responsible for E-C coupling in skeletal muscle. The authors succeeded in showing that a fragment of junctophilin1 (JPh44) moves from the triad to other cytosolic regions including the nuclei and they show changes in gene expression under these conditions, some of them linked to glucose metabolism.

Overall, the manuscript shows a novel and audacious approach with a careful treatment of the data (that was not always easy nor obvious) that allow sensible conclusions and definitively constitutes a step forward in this field.

Reviewer #2 (Public Review):

This paper investigates the maintenance and function of memory follicular helper T (Tfh) cell subsets using in vitro approaches, murine immunization models and vaccine-challenged humans. Murine Tfh cell subsets (Tfh1, Tfh2, Tfh17) were generated using in vitro polarization (iTfh1, iTfh2, iTfh17), and then tested for support of humoral response following adoptive transfer or adoptive transfer with resting in vivo for 35 days. iTfh17 cells were statistically better than iTfh1 and iTfh2 cells in promoting GC B cell and plasma cell maturation after resting in vivo, although all 3 populations were capable of B cell help. Tfh17 cells were comparatively enriched among blood borne Tfh central memory cells in humans, and were enriched at the memory phase of vaccination with hepatitis B and influenza vaccines, compared to effector phase, suggesting the possibility they are comparatively superior in Tfh cell memory formation, with greater persistence in aged individuals.

Significance<br /> The enrichment of Tfh17 cells in Tfh cell central memory compartment and the dominance of Tfh17 cell population and the Tfh17 transcriptional signature in circulating Tfh cells at the memory phase are nicely demonstrated, and may well be helpful for understanding the heterogeneity of memory Tfh cells and potentially providing clues for vaccine design. The in vitro differentiation system for mouse Tfh cells also provides a strategy for others to build upon in dissection of Tfh cell development and function.

Points to consider<br /> 1. Even though Tfh17 cells are more likely to persist at memory timepoints in mice and in humans, or produce more GC B cells or plasma cells following transfer, all subsets can do this. Is GC output otherwise distinguishable following transfer of the individual subsets, or is their effect (cytokine related perhaps) pre-GC with differential CSR? It is also not clear if the individual subsets populate the GC and assuming they do so, if their respective phenotypes persist when they become GC Tfh cells.

2. iTfh17 cells induce more GC B cells and antibodies after resting and antigen challenge (Figures 1, 2). However, it's not clear whether this effect is a consequence of comparatively enhanced iTfh17 survival during resting (as suggested by latter figures), or better expansion or differential skewing to Tfh differentiation during challenge (as suggested by Figure 1 J,K). The total number of remaining adoptively-transferred cells right before challenge and 7 days post challenge will be helpful to understand that.

3. The authors tried to address whether Tfh17 cells have better ability to survive till memory phase or Tfh17 cells with memory potential are generated at higher frequency at the effector phase of vaccination (Figure 5); however, the experiment is not conclusive. The cTfh population 7 days post vaccination is a mixed population with effector Tph cells and Tfh memory precursors. The increased frequency of Th17 cells at day 28 compared to day 7 could be a consequence of superior survival ability, or Tfh memory precursors with Tfh17 signature are better generated.

4. Experiments to confirm expansion ability of the human subsets or their B cell helper ability were not performed.

Reviewer #2 (Public Review):

This study addresses the ways in which bacteriophages antagonize or coopt the DNA restriction or recombination functions of the bacterial RecBCD helicase-nuclease.

The strength of the paper lies in the marriage of biochemistry and structural biology.

A cryo-EM structure of the RecBCD•gp5.9 complex establishes that gp5.9 is a DNA-mimetic dimer composed of an acidic parallel coiled coil that occupies the dsDNA binding site on the RecB and RecC subunits. The structure of gp5.9 is different from that of the RecBCD-inhibiting DNA mimetic protein phage λ Gam.

Cryo-EM structures of Abc2 are solved in complex with RecBCD bound to a forked DNA duplex, revealing that Abc2 interacts with the RecC subunit. A companion structure is solved containing PPI that copurifies with RecBCD•Abc2.

Whereas the gp5.9 structure fully rationalizes the effect of gp5.9 on RecBCD activity, the Abc2 structure - while illuminating the docking site on RecBCD, a clear advance - does not clarify how Abc2 impacts RecBCD function.

The authors speculate that Abc2 binding prevents RecA loading on the unwound DNA 3' strand while favoring the loading of the phage recombinase Erf.

Does the structure provide impetus and clues for further experiments to elaborate on that question and, if so, how?

Reviewer #2 (Public Review):

The molecular changes of the aged tendon are not well understood. Loiselle et al previously established a mouse model that mimics aging tendon, where they depleted Scleraxis lineage (Scxlin) cells from tendon by injecting diptheria toxin (DT) in mice expressing the DT receptor under the control of the Scx promoter (DTR mice). In this manuscript, the authors demonstrate that the tendons from DTR mice resemble tendons from aged WT mice, in that they both have decreased cellularity, altered collagen organization (via SHG imaging), and impaired biomechanical properties. Proteomic analysis of WT, DTR, and aged WT tendons show that both DTR and aged WT tendons have decreased expression of extracellular matrix proteins (ECM). Corresponding with this, single RNA seq analysis of tendons from these three groups of mice showed that while WT tendons are enriched for genes related to collagen and ECM synthesis and also inflammation, DTR tendons express genes associated with ECM organization and structure and aged tendons express genes that regulate inflammation. The authors point out that this supports designing therapies to prevent tendon cell death to prevent the changes seen in aging tendon.

These data enhances the understanding of the protein and gene changes associated with aging in the tendon and in particular characterizes the importance of Scx+ cells to tendon organization and the aging process. The conclusions are supported by the data presented.

The manuscript would be strengthened by:<br /> 1) Improved clarity of figures presented<br /> 2) More details on the methodology used for biomechanical testing<br /> 3) Clarification if the decrease in ECM protein expression is due to decreased cellularity in the tendons of the DTR and aged mice, or decreased expression per cell<br /> 4) Providing more details on genes that are downregulated in comparison between groups

Reviewer #2 (Public Review):

These discoveries are strongly supported by a large amount of clear and convincing data. Thus, the expression of seven distinct pol III-transcribed genes covering all types of promoter is shown to increase in three cell lines when STAT3 is overexpressed and to decrease when endogenous STAT3 is depleted. The proliferation of HepG2 liver cancer cells can be increased by STAT3 overexpression and decreased by STAT3 depletion. Crucially, proliferative induction by STAT3 is dependent on increased pol III activity, as it can be blocked using a pol III-specific inhibitor at a concentration that allows normal levels of pol III activity, but prevents further elevation. Growth of HepG2 xenograft tumours in mice is also slowed significantly when STAT3 is depleted. The effects of STAT3 on pol III output are indirect, mediated by miR-106a-5p. Thus, the knockdown of miR-106a-5p reverses the drop in pol III product expression following STAT3 depletion; conversely, pol III output is stimulated by a miR-106a-5p mimic. Elevated levels of miR-106a-5p correlate with significantly worse prognosis for patients with liver cancer. A key target for miR-106a-5p is a sequence in the 3'-UTR of the mRNA encoding TP73. Complementarity to this sequence allows miR-106a-5p to deplete the expression of TP73 and this is shown to be crucial for STAT3 to regulate the proliferation of HepG2 cells. Furthermore, TP73 is revealed to be a direct repressor of pol III-mediated transcription, an activity not previously known. TP73 is shown to inhibit the assembly of TFIIIB, the factor that is responsible for recruiting pol III to all of its genetic templates. A clear and convincing causal flow can therefore be traced: STAT3 induces miR-106a-5p, which depletes TP73, thereby removing a brake that limits pol III output and cell proliferation.

Reviewer #2 (Public Review):

Summary:<br /> Dominant mutations in the gene encoding LIS1 cause lissencephaly, a severe developmental brain disorder. LIS1 regulates the multisubunit microtubule motor, cytoplasmic dynein 1, which can exist in an autoinhibited (closed) form and an activatable (open) form. Dynein is only active when bound to another complex, dynactin, and one of several known cargo adaptors. Because dynactin and cargo adaptors only interact with the open form, the local ratio of open to closed dynein can potentially dictate the proportion of "activatable" motors. The current view is that LIS1 stimulates dynein by reducing the autoinhibited closed form, and by recruiting two dynein motors to the active complex, which is thought to increase speeds and run lengths. LIS1 is highly conserved across animal and fungal species. The budding yeast LIS1 ortholog, called Pac1, is around 43% identical to human LIS1. Both Pac1 and LIS1 regulate dynein but there have been intriguing differences in their effect on dynein processivity in assays with purified proteins. The authors of the current manuscript recently published high resolution cryo-EM studies of Pac1 bound to yeast dynein (Gilles 2022). Based on their models they tested several mutations predicted to impact Pac1 binding to dynein and showed these mutations disrupted the single dynein dependent process in budding yeast, translocation of the mitotic spindle. However, mutations in yeast dynein that impacted LIS1 binding apparently only modestly impacted human dynein, prompting the current study that compares cryo-EM studies of human LIS1 bound to human dynein with the previously published studies using yeast proteins. The work points to subtle differences in how yeast and human LIS1 interact with the stem and loop regions of yeast and human dynein heavy chains and reveal an intriguing difference in the residues predicted to be important for the interaction between the two LIS1 propeller structures in the LIS1 dimer. They also report map known disease causing mutations in LIS1 and dynein on the structures and find three that might impact residues involved in protein-protein interaction.

Methods:<br /> This group has been able to use innovative methods to increase the resolution of CryoEM images to 3-4 Å, allowing them to make more accurate predictions about residues involved in protein-protein interactions. They have substantial expertise in the analysis of the resultant data, as demonstrated by past peer review studies. These are very labor-intensive experiments that allow a level of detail not possible with standard biochemical or cell biological analyses.

Results:<br /> The studies revealed subtle, but potentially important, differences between the yeast and human proteins.

Based on their analyses, the authors predicted specific residues that are likely to be important for human LIS1-dynein interactions with the stem region of dynein (sitestem) and with dyneins AAA domain containing ring (sitering). They also predicted specific residues that are likely to be important for an interaction between the two LIS1 beta-propellers, which in the yeast protein is apparently critical for dynein regulation.

The prediction that K147 could be important in the interaction between beta-propellers is very intriguing, given evidence that a K147A mutation disrupts LIS1 binding to dynein, but not to NDEL1, another interacting protein.

Impact

The predictions set out in this manuscript, if they hold up, could inform the design of tools to study LIS1 in the context of human disease. It seems likely from the data that at least some of the indicated residues will be important for human LIS1/dynein interactions

Reviewer #2 (Public Review):

The authors have provided a large dataset of ribosomal RNA sequences to assist in the molecular identification of rare and unstudied medically important mosquitoes in four locations with high biodiversity and mosquito-borne virus circulation, Cambodia, French Guiana, Madagascar, and the Central African Republic. This was accomplished using a non-traditional approach, rRNA seq, which could help in the identification of novel potential vectors of disease in hotspots of transmission. Their method uses previously published insect and non-insect-specific rRNA sequences from multiple locations to perform "depletion" of interfering rRNA. This method allowed the authors to create both 28s and 18s sequences for the identification of novel species of mosquito vectors with high reliability based on phylogenetic analysis and utility where traditional cytochrome oxidase subunit I sequences are not available for systematics.

Strengths:<br /> The non-traditional approach used is well described and provides novel guidance for researchers undertaking similar studies.

The depletion method described allowed the authors to identify mosquito rRNA sequences even in the instance of non-target RNA being present.

Weaknesses:<br /> The author's approach, as with traditional approaches to molecular identification of vector species, relies on expert entomologists capable of identifying mosquitoes in the field which is rare in most places. The authors do not provide citations for the taxonomic keys used for morphological identification, which in many places are outdated or unavailable for specific locations.

While next-generation sequencing is becoming more available, it is still largely unobtainable for researchers lacking resources and infrastructure which is common in locations similar to those the authors provide these data for.

The authors give no explanation as to why they chose rRNA-seq as their method of next-generation sequencing, which is most commonly used for transcriptomics, instead of traditional DNA-based metagenomics which is more commonly used to define community relationships as would be more appropriate for this study.

Reviewer #2 (Public Review):

I agree with the authors (line 421) that their "findings provide a remarkable example of how carbohydrate metabolism dictates the relative importance of different sources of actin filaments for CAR dynamics during cellular division." The scope of the work is very broad, and the manuscript reports dozens of interesting phenotypes with high-quality experimental data. However, most points are not investigated in depth.

My main reservation is the presentation of the work. The writing style is conversational and expansive, which makes it challenging for the reader. Furthermore, long paragraphs shift from one topic to the next rather than using separate paragraphs with strong topic sentences to cover each topic. I suggested a few places to start new paragraphs, but many more paragraphs could be divided. I edited one paragraph to illustrate how the text might be cut in half.

Most of the figures are also overly complicated. I did not attempt to edit one of them, but I am sure that findings will be much clearer with about half of the panels moved to supplemental materials, so the reader can concentrate on the most important data.

Line 873: Fig 1C and many other figures. The legend says the error bars are SD's but they include far less than 2/3 of the measurements, so something is wrong. In Fig 4A and other figures, three data points are insufficient to verify a normal distribution, a prerequisite for using the Student's T-test. Furthermore, the T-test requires equal SD's.

Reviewer #2 (Public Review):

Starrett et al performed whole genome and transcriptome sequencing of bladder cancers from 43 organ transplant recipients. They found that most of these tumors contained DNA from one of four viruses (BKPyV, JCPyV, HPV, and TTV). Viral genomes are most often integrated into the genomes of these tumor cells and the authors provide evidence that the integration utilized the POL theta-mediated end joining pathway. In most cases, viral RNA was detected in tumors with viral DNA. This suggests that the viruses are actively altering the cellular environment. Frequently, this resulted in similarities for overall gene expression patterns in the tumors that were grouped by the type of virus present in the tumor. Moreover, the changes in expression linked with viral gene expression were found in genes relevant to tumorigenesis. Immunohistochemical detection of viral proteins in these tumors also demonstrated active viral gene expression. However, the presence of viral proteins was heterogenous within the tumor, with between 1 and 100% of the tumor staining positive for BKPyV large T antigen. An analysis of mutational signatures in these tumors indicate that the viruses are also shaping the tumor genome by inducing mutations. Evidence that specific viruses are contributing to tumorigenesis in organ transplant patients has fundamental implications for preventing tumorigenesis in these patients.

The conclusions of this paper are generally well supported by the data provided. Indeed, there is little doubt that viral infections are more likely in these tumors. However, there are aspects of the paper that could be improved and or clarified. Most importantly, despite the strong evidence that the viruses are altering the tumor cell environment, it is unclear if these changes are necessary for tumorigenesis or less excitingly the result of an even more immune suppressive environment within the tumor. The heterogeneity of the LT expression suggests that the presence of the viral DNA and RNA may not be enough to assess whether it is actively contributing to the tumor. Is an increased frequency of viral protein staining linked with any evidence of an active contribution to tumorigenesis (fewer tumor-suppressor/oncogene mutations). that they reduced mutations in tumor suppressors. This might be easiest to assess with the tumors that have oncogenic HPV DNA. If those tumors lacked p53 and RB mutations, it would support a causative role for the virus.

Reviewer #2 (Public Review):

Synaptic transmission is a fundamental process of communication in the brain. How and where neurotransmitter release occurs is still an open question. This study addresses an interesting question about the spatiotemporal location of neurotransmitter release in a synapse. This has important implications for postsynaptic signaling and neural excitability in general. The work provides valuable additions to recently uncovered discrepancies in the nanometer scale organization of the two primary forms of evoked vesicle fusion (synchronous and asynchronous) in the synapse from two very different methods. Essentially demonstrating convincingly that synchronous and asynchronous release sites are unshared. The study utilizes tools of super-resolution measurements of synaptic transmission that were previously developed in their lab, which help bridge the discrepancies using a convincing number of experimental paradigms. Limits in the speed of optical resolution opened a few questions of interpretation. However, this study greatly expands our knowledge of synaptic architecture and function of different forms of release. A further claim of different coupling of vesicle fusion and retrieval kinetics is made that at present seems incomplete due to temporal limitation of the super-resolution method.

Reviewer #2 (Public Review):

In this work entitled "Live imaging reveals chromatin compaction transitions and dynamic transcriptional bursting during stem cell differentiation in vivo" the authors use a combination of genetic and imaging tools to characterize dynamic changes in chromatin compaction of cells undergoing epidermal stem cell differentiation and to relate chromatin compaction to transcriptional regulation in vivo. They track this phenomenon by imaging the epithelium at the ear of live mice, thus in a physiological context. By following individual nuclei expressing H2B-GFP along time ranges of hours and up to 3 days, they develop a strategy to quantify the profile of chromatin compaction across different epidermal layers based on normalized intensity profiles of H2B-GFP. They observe that cells belonging to the basal stem cell layer display a considerable level of internuclear variability in chromatin compaction that is cell-cycle independent. Instead, intercellular variability in chromatin compaction appears more related to the differentiation status of the cells as it is stable in the hours range but dynamic in the days range. The authors show that differentiated nuclei in the spinous layer exhibit higher chromatin compaction. They also identified a subset of cells in the basal stem layer with an intermediate profile of chromatin compaction and with the dynamic expression of the early differentiation marker keratin 10. Lastly, they show that the expression of keratin-10 precedes the chromatin compaction establishing relevant temporal relationships in the process of epidermal differentiation.

This work includes a number of challenging approaches and techniques since it is carried out in living mice. Also, it provides nice tools and methods to study chromatin structure in vivo during multiple days and within a differentiation physiological system. On the other hand, the results are descriptive and, in some respect, expected in line with previous observations.

Reviewer #2 (Public Review):

This submission seeks to detect changes in the rate of selfing through pairwise comparison of haplotypes sampled from a population. It begins, as did a previous paper by a subset of the authors (Sellinger et al. 2020), with the well-known theoretical finding that partial selfing increases the rate of coalescence and decreases the rate of crossing-over events in genealogical histories.

I am supportive of pitching this contribution as primarily theoretical, with the very short discussion of the Arabidopsis data provided as a worked example. This perspective increases my enthusiasm, compared to an initial reading. My comments are intended to encourage development.

Some thematic characteristics reduce the impact of the submission. Among these are:<br /> (1) a rather less than a scholarly perspective on previous literature;<br /> (2) tendency to avoid theoretical development in favor of computation;<br /> (3) little interpretation of results of their only analysis of real data.

Reviewer #2 (Public Review):

The paper has two key messages: the discovery and the function of LncSox17. Claims of gene discovery are today untrivial, given the large number of genome-wide datasets. Of course, I understand the authors cannot check everything but I feel some more clear and deep analysis of current databases is lacking. Also, the exact coordinates of the lncRNA are not easy to find in the manuscript.

Many statistical analyses are rather lacking. In particular I did not find details of how the DEGs were identified during differentiation (FDR? How many replicates?).

The results of the smFISH are surprising, since the level of expression seems rather low in comparison to the qPCR (only 4 times less expressed than Sox17) or the RNA-seq.

Reviewer #2 (Public Review):

The X-ray crystal structure of the K. lactis Rad6-Bre1 interaction solved by Shi et al. adds an important piece to the puzzle of how H2B mono-ubiquitination is deposited. The primary strength of this work is the new structural information on the Rad6-Bre1 interaction, which reveals contacts of the E3 (Bre1) to the backside of the E2 (Rad6). Through mutagenesis and biochemical experiments, Shi et al. probe the importance of these contacts for the Rad6-Bre1 interaction, active site accessibility, and Rad6 catalytic activity. In general, the functional data support the structural model and confirm the importance of Bre1 in stimulating Rad6 catalytic activity in vitro and H2Bub1 in yeast. In comparison to the structural data, some of the functional data are not as robust and are at times over-interpreted. However, in general, the conclusions drawn by the authors about the importance of the newly revealed Rad6-Bre1 interface are appropriate and substantiated by the data.

Reviewer #2 (Public Review):

The manuscript by Sun et al., investigates the synaptic plasticity underlying visuo-auditory association. Through a series of in vivo and ex vivo electrophysiology recordings, the authors show that high-frequency stimulation (HFLS) of the cholecystokinin (CCK) positive neurons in the entorhino-auditory projection paired with an auditory stimulus can evoke long-term potentiation (LTP) of the visuo-auditory projection. However, LTP of the visuo-auditory projection could not be elicited by HFLS of the visuo-auditory projection itself or by an unpaired stimulus. They further demonstrate that auditory stimulus pairing with CCK is required to elicit LTP of the visuo-auditory projection as well as visuo-auditory association in a fear conditioning behavioral experiment. As they found elevated expression of CCK in entorhinal neurons which project to the auditory cortex, they conclude that HFLS of the entorhino-auditory projection causes CCK release.

Strengths:

The authors use an elegant approach with Chrimson and Chronos to stimulate different auditory inputs in the same mouse in vivo and also in slice and demonstrate that potentiation of the visuo-auditory projection is dependent on HFLS of the entorhino-auditory projection paired with auditory stimulus. Furthermore, they test several parameters in a systematic fashion, generating a comprehensive analysis of the plasticity changes that regulate visuo-auditory association.

Weaknesses:

In their previous publications (Chen et al., 2019; Li et al., 2014; Zhang et al., 2020), it has been established that HFLS of the entorhino-auditory projection and CKK release are important for visuo-auditory association via electrophysiology and behavioral experiments. The Chrimson and Chronos approach was applied by Zhang et al., 2020, where they already found that the visuo-auditory projection was potentiated through HFLS of entorhino-neocortical fibers. This manuscript extends those findings by testing different parameters of pairing, which may not represent a major conceptual advance. Unlike the electrophysiological recordings, drug infusion is used in behavioral manipulations to show that HFLS of the entorhino-auditory projection is important for visuo-auditory association. While the use of drugs to inhibit CKK receptors is important, it does not directly demonstrate that CCK release from the entorhino-auditory is necessary.

Reviewer #2 (Public Review):

Zhao et al., set out to investigate the molecular mechanisms controlling the timing between training tasks that leads to proactive interference (Pro-I) buildup (i.e. formation) and consequently interference in the retrieval of the newly learned memory.

During the time-dependent stabilization of newly acquired memory (i.e. memory consolidation), the memory traces are vulnerable to disruption by a variety of amnestic influences. When multiple learning events occur in rapid succession, competition occurs between consolidating memories. However, the factors that regulate what memory is remembered or forgotten are unknown. Two interference models of forgetting are proposed in the literature: events occurring prior to learning cause forgetting through proactive interference (Pro-I), or events occurring after learning cause forgetting through retroactive interference (Retro-I).

The most common explanation for Pro-I and its buildup is that this phenomenon emerges due to the competition between two differing task memories (e.g. aversive memories) for storage in overlapping brain areas. The behavioural consequence of this Pro-I buildup is that the recall of newly learned information is impaired when is preceded by a similar learning task. On the other hand, several accounts are used to describe the release from Pro-I (i.e. the reduction of proactive interference): a) having a more distinctive target task compared to the interference task (either different material or relying on different neural circuits), b) prolonging the lag between training tasks and c) contextual changes between the two learnings. Drosophila is an ideal model for the study of these questions, given the detailed knowledge base of how different types of memories are encoded, consolidated, and retrieved and the effects of context changes in these memories.

In this study, the authors use the classic aversive conditioning paradigm, where flies learn to associate an odor A with shock (in the target task), this task is preceded by a proactive task or is followed by a retroactive task, where odor X is paired with a shock. Taking advantage of the known molecular pathways for the more well-characterized model of interference (Retro-I), the authors extended the knowledge for these types of interference models. To uncover the mechanisms underlying the timing of Pro-I, the authors genetically manipulated the activity of a key phosphatase (Corkscrew) and its downstream pathway (Raf/MAPk). This phosphatase was chosen given its known role in controlling the appropriate training intervals for the induction of long-term memory in flies.

A strength of the manuscript is that the authors showed the unique and exclusive role of Corkscrew in regulating Pro-I and its temporal dynamics. Furthermore, the authors described that Corkscrew regulates Pro-I via a single subset (γ) of the intrinsic cells (i.e. Kenyon cells) of the mushroom body, which is the centre of learning and memory in Drosophila. However, the manuscript would have been improved had they characterized the Pro-I task more thoroughly. This is because behaviourally what the authors are observing might look like Pro-I buildup, but other scenarios can also explain the data (e.g. passive decay of the first memory, memory storage limitations, attentional deficits). This would be solved by applying known Pro-I release protocols and, in this way, would be more comparable to the known Pro-I literature.

Interestingly in the mammalian field, phosphatase activity is also known as a key regulator of long-term depression and memory formation. Taken together, this data implies the conserved role of phosphatase activity and its subsequent plasticity during the process of learning a new task. Furthermore, this work shows the importance of phosphatase activity in facilitating memory consolidation of newly learned information, which might occur by suppressing any potential interference from old memories in the same neuronal circuits.

Reviewer #2 (Public Review):

The authors used both pharmacological inhibition and genetic TPL2 kinase dead (KD) mice to test the hypothesis, that inhibition of TPL2 attenuates the microglia inflammatory response to stimuli such as LPS and in the context of chronic (tau mouse model) and acute (optic nerve crush/stroke) neurodegenerative models. The use of TPL2 kinase dead mice rather than KO mice is elegant and important because of the non-enzymatic role of TPL2 in stabilization of its interacting partner ABIN-2. The authors convincingly demonstrated that pharmacological and genetic inhibition of TLP2 in primary microglia reduced the production of pro-inflammatory cytokines, chemokines, and iNOS and consequently reduced neuronal cell death in neuronal-microglial cocultures. Genetic inhibition of TLP2 reduced partially the inflammatory response of microglia in the PS31 tau model. Furthermore, the authors observed reduced infiltration of T cells and dendritic cells. Notably, TLP2 inhibition rescued behavioral deficits in PS31 mice. Overall, these studies support the possibility that inhibition of TPL2 kinase may have translational potential in prevention or treatment of tau-driven neurodegeneration. One aspect of the study that merits further investigation is the alteration in the population structure of myeloid cells in the brain under the various conditions that were evaluated using single cell RNA seq. Very high representation of microglia was observed in TauP301S mice at nine months of age. These findings could reflect bias in recovery of cells for the single cell RNA sequencing assay and independent validation of microglia cellularity by immunohistochemistry would address this question.

Reviewer #2 (Public Review):

Mecp2 is the causative gene for RTT and MDS, but the Mecp2 driven pathogenesis is not clearly defined. While Mecp2 is a regulator of gene expression, identifying downstream genes that are robustly regulated by Mecp2 have been a challenge. The authors utilized computational approach to identify Mecp2 regulated genes using previously published differentially expressed genes in hippocampi of MDS mice treated with Mecp2-specific ASO (Shao et. al., 2021). Through this analysis, the authors shortlisted Gdf11, which also validated in an additional 20 transcriptional profiles for Mecp2 perturbed rat, mouse, and human brain samples.

The transcriptional regulation of Gdf11 by Mecp2 was confirmed using genetic murine models, including Mecp2 -knockout, Gdf11 mutant and Mecp2-tg1.<br /> Finally, the CUT and RUN analysis showed increased Mecp2 binding upstream of the Gdf11 TSS in Mecp2-tg1 hippocampi, which was lost in Mecp2 knockout hippocampus. Mecp2 loss increases H3K27me3, which suggested Mecp2 prevents transcriptional silencing of Gdf11. While these results provide mechanistic insight into the transcriptional control of Gdf11 by Mecp2, it remains unclear how Mecp2, which is generally a transcriptional suppressor increases Gdf11.

The author elegantly demonstrates that normalization of Gdf11 levels in Mecp2-tg1 mice crossed with Gdf11 improves several behavioral deficits in the MDS mice model. In contrast, loss of one copy of gdf11 in mice caused neurobehavioral deficits using a battery of behavioral tests, such as elevated plus maze, rotarod, anxiety tests and shock-tone conditioning.

Finally, the authors show that loss of one copy of gdf11 does not alter proliferation in the adult mouse SGZ or no gross changes in brain anatomy or volume of the dentate gyrus.

Overall, the authors demonstrate that gdf11 is robustly regulated by mecp2, which coup provide new therapeutic options for Mecp2-related diseases, such as RTT and MDS. As discussed in the paper, additional studies are needed to test whether Gdf11 can rescue behavioral deficit in symptomatic RTT murine models.

Reviewer #2 (Public Review):

This manuscript explores the importance of the plastid-hosted SUF iron-sulfur cluster synthesis pathway for plastid maintenance and for the viability of blood stages of the human parasite Plasmodium falciparum. The authors convincingly demonstrate that while most of the proteins of the SUF pathway are essential to P. falciparum survival only one, the cysteine desulfurase SufS, also leads to the loss of the plastid. The authors then explore the possibility that SufS may be providing sulfur to a plastid-localised putative tRNA modifying enzyme, MnmA. They demonstrate that, like when SufS is depleted, specific depletion of MnmA impairs parasite viability and causes plastid loss. They also elegantly complement this phenotype with bacterial MnmA expressed together with a bacterial cysteine desulfurase or even alone, suggesting that SufS from the parasite is able to directly transfer sulfur to the bacterial MnmA.

Overall, this is a well-conducted and well-controlled study, for which I do not have any major criticism, although tRNA purification, identification, and quantification in the SufS and MnmA mutants would bring more compelling evidence that tRNA thiolation is affected in these mutants.

Reviewer #2 (Public Review):

In this manuscript, Li et al. sought to identify tumor suppressor proteins in mesenchymal stem cell conditioned media in which PKA signaling was up-regulated by treatment with a small molecule, and in osteosarcoma-enriched transcripts, to provide alternative treatment strategies to combat osteosarcoma. They identified several proteins that when forcibly expressed both in vitro and in vivo, can suppress osteosarcoma viability, growth, and motility. This manuscript presents a substantial amount of data, is well organized, and provides a novel approach to addressing osteosarcomas. The data is thorough and convincing and provides an alternative approach to developing cancer therapeutics.

Reviewer #2 (Public Review):

The study by Smela et al describes the direct differentiation of human "Granulosa-like cells" via the overexpression of a limited number of transcription factors in pluripotent cells. This approach builds on other contemporary work to produce functional support cells of the mammalian gonad.

The work does succeed to establish cultured cells that retain some characteristics of these ovarian support cells, including the expression of granulosa cell markers, steroid biosynthesis in response to stimulation, and some evidence of acute germline support. The study also marks an important technological development towards the production of in vitro conditions for the production of human gametes from iPS cells. Prior efforts using human germline cells have mostly focussed on xeno-organoid approaches, and so the human-human nature of the present study represents a useful advance. Of particular note, the present study identifies a remarkably fast acquisition of DDX4 and DAZL-positive cells when both germline and support cells are both derived from a human source. This is an intriguing finding, as other groups have reported a substantial delay in acquiring this germline state when cells from mixed species are used. While these findings are of key technological importance towards ongoing efforts to create in vitro gametes, there appear to be some issues of reproducibility, and a lack of deep functional characterisation.

Several conclusions of the paper need to be described in much greater detail. For example, the regulatory effects of the over-expression of transcription factors are stated in Figures 1 and 2, but how this regulatory logic was assembled is not presented, and the methods by which this logic was experimentally probed are not presented. Second, the abstract highlights two transcription factors that are both necessary and sufficient for granulosa-like cell production. While sufficiency is tested through the overexpression of the transcription factors, necessity is not conventionally assessed through a genetic approach. The upregulation of factors in response to transcription factor overexpression does not seem appropriately described. Third, the transcriptional comparison of granulosa-like cells with cancer cell lines that do not reflect normal granulosa cells should be reconsidered.

The study contributes an important step towards the production of functional human granulosa cells from pluripotent cells, though the central conclusions would benefit from a more robust interrogation of the cell status achieved.

Reviewer #2 (Public Review):

This manuscript details the role of the rILN to the DS pathway in the onset of operant behavior that promotes the delivery of a reward and in the ultimate acquisition of that reward. The strengths of the paper are in the detailed fiber photometry study that encompasses several behavioral domains that correlate to the signal observed in the rILN to DS pathway. I am especially interested in how the "encoding" shifts across time as the animals refine their behavior both in a temporal sense and in the magnitude of the signal. Further, the authors demonstrate then that this is dependent on action, as they do not observe signals in a Pavlovian behavioral task, but do observe reward-based signals in a "free consumption" task (the strawberry milk). The examination into devaluation also enhances the understanding of this pathway, even though there were no differences between a valued and devalued task. Finally, the authors examine bi-directional optogenetic manipulation of the pathway, and its impact on how the trials are completed, omitted, or incomplete. They find that manipulation alters the % completed trials and regulates trial omission. This paper really does not have any glaring weaknesses to point out, however, the physiological assessment does seem to have a few strong trends and even though the studies are well powered, and included both sexes, sex as a biological variable was not commented on that I could find. My estimation of the data doesn't suggest strong sex differences in any metric measured. Additionally, the data that included projections to the rILN were very interesting, and future studies looking into the physiology of these neurons, and/or how the physiology of these neurons adapt after operant training may be very interesting to understand plasticity within the adaptation across the training from FR1 to FR5 with time limits.

Reviewer #2 (Public Review):

The present study from Xiaorui Shi's lab investigated the effect of pericyte depletion on spiral ganglion neurons and auditory function. Results in in vitro culture system proposed that pericyte-derived exosomes contain VEGF, and promote not just vascular stability but neuronal survival through Flk1. This study is an extension of their previous study showing pericyte depletion causes auditory dysfunction, which is ameliorated by VEGF gene therapy (Zhang et al., JCI insight 2021). Overall, the data are clear and sophisticated and promote our understanding of the biological roles of pericytes in neuronal function. Several points should be thoroughly discussed or supported by definitive experiments like analysis of neuron-specific Flk1 KO mice.

Reviewer #2 (Public Review):

In this work, Illingworth et al. investigate the effectiveness of ribavirin and favipiravir on the treatment of a paediatric patient with chronic RSV. These drugs cause mutations and the authors tested whether they could observe this effect through deep sequencing viruses from nasal aspirates over the course of treatment. They found an increase in mutations caused by ribavirin but favipiravir appeared to have no additional mutagenic effect. Despite the lack of change in viral load, the authors suggest that the ribavirin reduced viral fitness and did not lead to adaptive escape mutations. The authors modelled how generation time and fitness interacted with mutational load. They also estimated fitness for different haplotypes generated from the mutational data.

Strengths of the paper:

Using mutagenic drugs to treat viruses is generally accepted but results have been mixed with severe viral infections and specific evidence of the precise effects of the drugs is often lacking. This paper is especially valuable for demonstrating that despite in vitro evidence that favipiravir had some effect against RSV, there was no evidence for favipiravir having an effect in a patient. This differs from the authors previous work showing a clear clinical benefit to favipiravir in treating influenza. This paper also appears to be the first to sequence RSV from a patient having been exposed to ribavirin which is important for demonstrating that the drug is having a measurable effect.

Weaknesses in the paper:

I think there is a conceptual problem with the paper. Ribavirin is supposed to increase the mutational rate of the virus which would increase the mutational load. Mutational load has been calculated by summing up the frequencies of minor alleles. However, if a particular mutation rises in frequency, it does not mean that ribavirin has caused additional mutations at the same site but rather viruses containing the mutation have risen in frequency. If a subpopulation containing mutations rises through drift or selection to a relatively high percentage that will bias the mutational load. The authors provide ~75 mutations which were at significant percentages across multiple different timepoints. It seems that these mutations contribute significantly to the mutational load but changes in mutation percentages between samples do not reflect changes in mutational events but changes in viral haplotypes/subpopulations. In a previous study Lumby et al. 2020, the authors removed mutations at >5% from their analysis but there is no indication that they performed this step similarly here. Summing many small changes will give an indication of background mutational rate (though counting only a single mutation at each locus is perhaps the only method to remove the effect of viral clonal expansion).

While ribavirin appears to have shown an effect, many questions remain. Why does the mutational load only increase for 3 points before plateauing? The authors would likely argue that this is the new saturation point for mutation load but they don't test it. Sequencing points from after the cessation of treatment would be expected to show lower mutational load but this data was not collected. Furthermore, questions remain over the methodology. It is thought that Ribavirin should only increase transitions and a transition/transversion ratio for the different samples would have been helpful. The absolute numbers of many mutation classes appear to have increased including transversions e.g AU. There isn't a good reason why nucleoside analogues should have caused this effect and perhaps it is an artefact.

I don't think that the authors can reasonably determine how many haplotypes there are in the population from short read sequencing data. I think that the sequencing data very clearly shows subpopulations due to the large changes in mutation frequencies between different time points. The authors say that their analysis assumes a well-mixed population which is clearly not the case. Therefore, determining fitness of different haplotypes or mutations is likely not accurate.

The authors construct a model to estimate viral fitness and suggest that viral fitness decreased with the drug. This is somewhat problematic to me as viral load has not changed so it would be reasonable to say that viral fitness was likely unaffected by the drug. The authors define fitness in terms of the number of mutations that each virus likely has and assumes that these mutations are deleterious. The authors then use this to claim that mutagenic drugs reduce fitness. This seems very circular to me. If the drugs reduce fitness, it should be observed as a property of the virus population. As the only measure was viral load, which didn't change, it is difficult to claim ribavirin reduced viral fitness. There are other reasons why there could be an increase in the number of mutations e.g. sequencing more subpopulations which would have nothing to do with fitness.

At various points, the paper assumes that there is no selection taking place but immunoglobulin was being applied weekly and palivizumab monthly. The timing of when these drugs were given should be included. How did the palivizumab affect selection? The K272E mutation seems to go up and down but it is not clear if this was in response to drug infusion timing or if this mutation was present in a subpopulation.<br /> I think the main impact of the paper will be that favipiravir will not be used in the future to treat RSV. Given that the EC50 of favipiravir against RSC is ~100x that of influenza, favipiravir was unlikely to reach a therapeutic level in the patient. Nucleoside analogues have a mixed record at treating serious viral infections. Hopefully, this work will spur on future studies to precisely measure the effect that ribavirin has on RSV.

Reviewer #2 (Public Review):

The authors aimed to determine the mode of inhibition of the serotonin transporter SERT as a by-product of MDMA synthesis (ECSI#6). They present a thorough kinetic analysis, using different experimental techniques (binding and transport inhibition) and kinetic modelling. They also test the predicted pharmocophore effect of the compound. In my view, the authors provide compelling evidence for an uncompetitive inhibition mechanism, in which the compound most likely binds to the inward-facing and K+-bound state. Inhibitors of this type may have the potential for therapeutic use.

Reviewer #2 (Public Review):

This manuscript applied the SAXS data analysis of protein self-assembly by implementing the simultaneous fitting of intra- and inter-molecular motions/conformations against SAXS data at a series of oligomerization states/concentrations. Despite several major assumptions hinted, a diverse pool of conformational and oligomeric candidates was generated from CG simulations, and more importantly, these candidates were fitted into these SAXS data to reach a reasonable agreement, suggesting a somewhat convergence (even if the ensemble-fitting could well be at a local minimal). This is considered a technical advance, given the fairly large numbers of both the oligomer fraction phi_i (i=1, ..., N) and the conformational weight w_k (k=1, ..., n), where N is the number of oligomers and n is the number of internal conformational states.

Central is optimizing phi_i and w_k, simultaneously. The former has been illustrated in Fig. 4 and SI-Fig. 7 for the total number of 60-mers. The latter relies on an overfitting-preventing strategy, as shown in SI_Fig. 1, where an effective fraction cutoff was used from 0.1 to 1.0, as opposed to the number of conformational states. What are the numbers of conformational states for these oligomers? This should be quantifiable, e.g., defining the conformational differences by chi_2.