Reviewer #2 (Public Review):

Hu et al. developed a new reagent to enhance single mRNA imaging in live cells and animal tissues. They combined an MS2-based RNA imaging technique and a Suntag system to further amplify the signal of single mRNA molecules. They used 8xMS2 stem-loops instead of the widely-used 24xMS2 stem-loops and then amplified the signal by fusing a 24xSuntag array to an MS2 coat protein (MCP). While a typical 24xMS2 approach can label a single mRNA with 48 GFPs, this technique can label a single mRNA with 384 GFPs, providing an 8-fold higher signal. Such high amplification allowed the authors to image endogenous mRNA in the epidermis of live C. elegans. While a similar approach combining PP7 and Suntag or Moontag has been published, this paper demonstrated imaging endogenous mRNA in live animals. Data mostly support the main conclusions of this paper, but some aspects of data analysis and interpretation need to be clarified and extended.

Strengths:<br /> Because the authors further amplified the signal of single mRNA, this technique can be beneficial for mRNA imaging in live animal tissues where light scattering and absorption significantly reduce the signal. In addition, the size of an MS2 repeat cassette can be reduced to 8, which will make it easier to insert into an endogenous gene. Also, the MCP-24xSuntag and scFv-sfGFP constructs can be expressed in previously developed 24xMS2 knock-in animal models to image single mRNAs in live tissues more easily.

The authors performed control experiments by omitting each one of the four elements of the system: MS2, MCP, 24xSuntag, and scFV. These control data confirm that the observed GFP foci are the labeled mRNAs rather than any artifacts or GFP aggregates. And the constructs were tested in two model systems: HeLa cells and the epidermis of C. elegans. These data demonstrate that the technique may be used across different species.

Weaknesses:<br /> Although the paper has strength in providing potentially useful reagents, there are some weaknesses in their approach.

Each MCP-24xSunTag is labeled with 24 GFPs, providing enough signal to be visualized as a single spot. Although the authors showed an image of a control experiment without MS2 in Figure 1B, the authors should at least mention this potential problem and discuss how to distinguish mRNA from MCP tagged with many GFPs. MCP-24xSunTag labeled with 24 GFPs may diffuse more rapidly than the labeled mRNA. Depending on the exposure time, they may appear as single particles or smeared background, but it will certainly increase the background noise. Such trade-offs should be discussed along with the advantage of this method.

Also, more quantitative image analysis would be helpful to improve the manuscript. For instance, the authors can measure the intensity of each GFP foci, show an intensity histogram, and provide some criteria to determine whether it is an MCP-24xSuntag, a single mRNA, or a transcription site. For example, it is unclear if the GFP spots in Figure 2D are transcription sites or mRNA granules.

Another concern is that the heavier labeling with 24xSuntag may alter the dynamics of single mRNA. Therefore, it would be desirable to perform a control experiment to compare the diffusion coefficient of mRNAs when they are labeled with MCP-GFP vs MCP-24xSuntag+scFv-sfGFP.

The authors could briefly explain about the genes c42d4.3 and mai-1. Why were these specific genes chosen to study gene expression upon wound healing? Did the authors find any difference in the dynamics of gene expression between these two genes?

Reviewer #2 (Public Review):

In this manuscript, Zhang et al., address the role of Polo-like kinase signaling in restricting the activity of Chk2 kinase and coordinating synapsis among homologous chromosomes with the progression of meiotic prophase in C. elegans. While individual activities of PLK-2 and CHK-2 have been demonstrated to promote chromosome pairing, and double-strand break formation necessary for homologous recombination, in this manuscript the authors attempt to link the function of these two essential kinases to assess the requirement of CHK-2 activity in controlling crossover assurance and thus chromosome segregation. The study reveals that CHK-2 acts at distinct regions of the C. elegans germline in a Polo-like kinase-dependent and independent manner.

Strengths:<br /> The study reveals distinct mechanisms through which CHK-2 functions in different spatial regions of meiosis. For example, it appears that CHK-2 activity is not inhibited by PLK's (1 and 2) in the leptotene/zygotene meiotic nuclei where pairing occurs. This suggests that either CHK-2 is not phosphorylated by PLK-2 in the distal nuclei or that it has a kinase-independent function in this spatial region of the germline. These are interesting observations that further our understanding of how the processes of meiosis are orchestrated spatially for coordinated regulation of the temporal process.

Weaknesses:<br /> While the possibilities stated above are interesting, they lack direct support from the data. A key missing element in the study is the actual role of PLK-2 signaling in controlling CHK-2 activity and thus function. I expand on this below.

Throughout the manuscript, the authors test the role of each of the kinases (CHK-2 or PLK-1, or 2) using auxin-induced degradation, which would eliminate both phosphorylated and unphosphorylated pools of proteins. This experiment thus does not test the role of PLK-2 signaling in controlling CHK-2 function or the role of CHK-2 activation. To test the role of signaling from PLK-2 or CHK-2, the authors need to generate appropriate alleles such as phospho-mutants or kinase-dead mutants. The authors do generate unphosphorylatable and phosphomimetic versions of CHK-2, however, they find that the protein level for both these alleles is lower than wild-type CHK-2 (which the authors state is already low). The authors conclude that the lower level of protein in the CHK-2 phospho-mutants is because the mutations cause destabilization of the protein. I am sympathetic with the authors since clearly these results make interpretations of actual signaling activity more challenging. But there needs to be some evidence of this activity, for example through the generation of a phosphor-specific antibody to phosphorylated CHK-2. While not functional, at least the phosphorylation status of CHK-2 would provide more information on its spatial pattern of activation and inactivation. In addition, it would still be of interest to the readership to present the data on these phosphor-mutant alleles with crossover designation and COSA-1::GFP. Is the phenotype of the WT knockin, and each of the phosphomutant knock-ins similar to auxin-induced degradation of CHK-2?

Given that the CHK-2 phosphomutants did not pan out for assessing the signaling regulation of PLK-2 on CHK-2, to directly assess whether PLK-2 activity restricts CHK-2 function in mid-pachytene but not leptotene/zygotene, the authors should generate PLK-2 kinase dead alleles. These alleles will help decouple the signaling function of PLK-2 from a structural function.

Similarly, to assess the potentially distinct roles of CHK-2 in leptotene/zygotene and mid-pachytene it would be important to assess CHK-2 kinase-dead mutant alleles. At this time, all of the analysis is based on removing both active CHK-2 and inactive CHK-2 (i.e. phosphorylated and unphosphorylated pool) using auxin-induced degradation. The kinase-dead alleles will help infer the role of the kinase more directly. The authors can then superimpose the auxin-induced degradation and assess the impact of complete removal of the protein vs only loss of its kinase function. These experiments may help clarify the role of signaling outcomes of these proteins, vs their complete loss. For example, what does kinase dead PLK-2 recruitment to the synapsed chromosomes appear like? Are their distinct activities for active and inactive PLK-2 that are spatially regulated? The same can be tested for CHK-2.

Reviewer #2 (Public Review):

This is an interesting manuscript establishing a role for Ecdysone signaling in the control of sleep. The authors show that the Ecdysone receptor EcR is required primarily in cortex glia for the control of sleep and that its target E75 is also involved in sleep regulation. This is a novel function for both cortex glia and steroid signaling in Drosophila. The authors also present evidence that Ecdysone signaling would be important for response to starvation, and that lipid droplet mobilization would mediate the effect of ecdysone on sleep. This work is certainly innovative. However, the main conclusions need to be strengthened. In particular: variability in sleep amounts in certain strains could complicate interpretation, the idea that ecdysone modulates sleep response to starvation is not sufficiently well supported, and genetic evidence for mobilization of lipid droplets being the mechanism linking steroid signaling to sleep is currently quite weak.

Major concerns:

1) I have concerns with the variability observed with the GS drivers (whether nSyb or repo). This is particularly striking in figure S3 when comparing experiments conducted with EcR-c and the Ecl RNAi. Daytime is most affected, but even nighttime looks significantly different. Definitely, nighttime quantification should be shown in addition to total sleep in figure S3. However, I feel that confirming the key results of this study with an additional driver would be reassuring. Could repo-GAL4 combined with GAL80ts be used to drive EcR RNAi, instead of repo-GS? The same combination could help determine whether glia is responsible for the 20E-mediated increase in sleep after starvation (figure S4A).<br /> 2) The idea that ecdysone might suppress the response to starvation is interesting, but the results are not convincing. First, there is an important control missing. It is important to test the effect of Ecdysone on fed flies, to ensure that Ecdysone does not simply make flies sleepy. Second, it is not clear that EcR RNAi has a specific effect on starved flies. Starvation reduces sleep, but is this reduction really exaggerated in flies expressing EcR RNAi than in control flies? It seems to me that starvation reduces sleep by the same amount when comparing results in panels 3D and E. The effect of EcRNAi and starvation might be simply additive, which would suggest that 20E impacts sleep independently of starvation.<br /> 3) The material and method section needs to be improved. In particular, it is not clear to me how the starvation/ecdysone feeding assay was done. There are some additional explanations in the figure legend, but the approach is still not clear to me. Indicate clearly when the flies were starved, and when they were exposed to Ecdysone.<br /> 4) I am not convinced that the Lsd2 results necessarily support the idea that this gene is required for the effect of 20E on sleep. Sleep is dramatically reduced during the day in the Lsd2 mutant. This is actually an interesting observation, but this strong effect on baseline sleep might be masking the ability of 20E to modulate sleep.

Reviewer #2 (Public Review):

The manuscript reports on the complex variability of expression, trafficking, assembly/stability, and peptide loading among different MHC I haplotypes. In particular by analyzing two distinct MHC I molecules as representative members of groups of allotypes, that favor canonical or non-canonical assembly modes, the PI reports on preferential cytosolic or endo-lysosomal MHC I loading. Overall, the data shed light on the intersection between MHC I conformation and subcellular sites of peptide loading and help explain MHC I immunosurveillance at a different subcellular location.

In the first series of experiments the authors report an uneven surface expression of HLA-B vs HLA-A, and C on circulating monocytes, with HLA-B being expressed 4 times higher, also they report that as compared to the TAP-dependent allotype B*08:01 the TAP-independent allotype B*35:01 has a lower surface half-life and if often present as an empty molecule. These data set the basis for the author's hypothesis that B*35:01 could traffic in Rab11+ compartment and be involved in cross-presentation, which indeed is demonstrated in a series of pulse-chase peptide experiments and using cathepsin inhibitors.

Overall, the experiments could be improved by performing subcellular fractionation and organelle purification to conclusively demonstrate the differential trafficking of B*08:01 vs B*35:01, as well as quantitative mass spectrometry to determine cytosolic vs endosomal processing for one selected epitope presented by the different haplotypes.

Reviewer #2 (Public Review):

Yeatman and colleagues used MEG in pre-literate children following a literacy intervention program to investigate changes in cortical responses to visual images of words, faces, and objects. Children who participated in a literacy intervention program showed improvements in letter knowledge and increased neural responses to words relative to an object category. The authors interpret these findings in the framework of the neuronal recycling hypothesis proposed by Dehaene and colleagues. This is important work. The opportunity to use a causal manipulation to study neural and behavioral development in humans is rare. The finding of neural changes from just 2 weeks of intervention is striking. The scope of the work extends beyond understanding brain development and has potential relevance for social and educational policies. The study appears well-designed and includes an important control group. Overall, I am enthusiastic about this work. However, it is unclear whether the results are specific to the area of interest - the visual word form area. The increased response to words from the intervention appears quite widespread cortically (Figure 5). These issues are central to the idea of neuronal recycling and the authors' proposal that training leads to increased modularization. Thus, the results currently only provide modest support for the conclusions. Additionally, aspects of the analysis need clearer motivation/justification.

Reviewer #2 (Public Review):

The molecular characteristics of OCNs in normal or ototoxic conditions are poorly understood before. The strength of this study is that it provides the first single-cell RNA-seq database of OCNs as well as surrounding facial branchial motor neurons. By thoroughly analyzing the database, they found high heterogeneities within OCN populations and identified distinct markers that are enriched in different OCN subtypes. Furthermore, a few previously unknown neuropeptides are revealed, including Npy which is more enriched in the LOC-2 located on the medial side. They also found that neuropeptide expression levels and distributions are subjected to hearing experience and noise exposure. On the other hand, the weakness of the study is that the numbers of single-cell RNA-seq are not sufficient, and may underscore the MOC heterogeneity (Figure 3A). Moreover, the physiological functions of the LOC-2 are not revealed in this study, and no specific markers in one OCN subtype are identified that can predict the morphological or projecting axon features. Those might be addressed in the following studies.

Reviewer #2 (Public Review):

This study reports interesting findings on the influence of a conserved phosphatase on mitochondrial biogenesis and function. In the absence of it, many nucleus-encoded mitochondrial proteins among which those involved in ATP generation are expressed much better than in normal cells. In addition to a better understanding of th mechanisms that regulate mitochondrial function, this work may help developing therapeutic strategies to diseases caused by mitochondrial dysfunction. However there are a number of issues that need clarification.

1) The rationale of the screening assay to identify genes required for the gene expression modifications observed in mct1 mutant is not clear. Indeed, after crossing with the gene deletion libray, the cells become heterozygote for the mct1 deletion and should no longer be deficient in mtFAS. Thank you for clarifying this and if needed adjust the figure S1D to indicate that the mated cells are heterozygous for the mct1 and xxx mutations.

2) The tests shown in Fig. S1E should be repeated on individual subclones (at least 100) obtained after plating for single colonies a glucose culture of mct1 mutant, to determine the proportion of cells with functional (rho+) mtDNA in the mct1 glucose and raffinose cultures. With for instance a 50% proportion of rho- cells, this could substantially influence the results of the analyses made with these cells (including those aiming to evaluate the MMP).

3) The mitochondria area in mct1 cells (Fig.S1G) does not seem to be consistent with the tests in Fig. 1C. that indicate a diminished mitochondrial content in mct1 cells vs wild-type yeast. A better estimate (by WB for instance) of the mitochondrial content in the analyzed strains would enable to better evaluate MMP changes monitored with Mitotracker since the amount of mitochondria in cells correlate with the intensity of the fluorescence signal.

4) Page 12: "These data demonstrate that loss of SIT4 results in a mitochondrial phenotype suggestive of an enhanced energetic state: higher membrane potential, hyper-tubulated morphology and more effective protein import." Furthermore, the sit4 mutant shows higher levels of OXPHOS complexes compared to WT yeast.

Despite these beneficial effects on mitochondria, the sit4 deletion strain fails to grow on respiratory substrates. It would be good to know whether the authors have some explanation for this apparent contradiction.

Reviewer #2 (Public Review):

Shah and colleagues tackle a significant impediment to exploiting tissue culture systems that enable prospective ex vivo experimentation in real-time. Namely, the ability to identify and track dynamic and coordinated activities of multiple composite cell types in response to experimental perturbations. They develop a clever label-free approach that collects biologically-encoded autofluorescence of epithelial cells by 2-photon imaging of mouse tracheal explant culture over 2 days. They report the ability to distinguish 7 cell types simultaneously, including rare ones, by developing a machine-learning approach using a combination of fluorescence and cytologic features. Their algorithm demonstrates high accuracy by Mathew's Correlation Coefficient when applied to a test set. Lastly, they show the ability of their approach to visualize the dynamic uptake and expulsion of fluorescently-tagged dextran by individual secretory cells. Overall, the results are intriguing and may be very useful for specific applications.

Reviewer #2 (Public Review):

The manuscript of Penha et al performs genetic correlation, Mendelian randomization (MR), and colocalization studies to determine the role of genetically determined leukocyte telomere length (LTL) and susceptibility to lung cancer. They develop an instrument from the most recent published association of LTL (Codd et al), which here is based on n=144 genetic variants, and the largest association study of lung cancer (including ~29K cases and ~56K controls). They observed no significant genetic correlation between LTL and lung cancer, in MR they observed a strong association that persisted after accounting for smoking status. They performed colocalization to identify a subset of loci where LTL and lung cancer risk coincided, mainly around TERT but also other loci. They also utilized RNA-Seq data from TCGA lung cancer adenocarcinoma, noting that a particular gene expression profile (identified by a PC analysis) seemed to correlate with LTL. This expression component was associated with some additional patient characteristics, genome stability, and telomerase activity.

In general, most of the MR analysis was performed reasonably (with some suggestions and comments below), it seems that most of this has been performed, and the major observations were made in previous work. That said, the instrument is better powered and some sub-analyses are performed, so adds further robustness to this observation. While perhaps beyond the scope here, the mechanism of why longer LTL is associated with (lung) cancer seems like one of the key observations and mechanistically interesting but nothing is added to the discussion on this point to clarify or refute previous speculations listed in the discussion mentioned here (or in other work they cite).

Some broad comments:

1. The observations that lung adenocarcinoma carries the lion's share of risk from LTL (relative to other cancer subtypes) could be interesting but is not particularly highlighted. This could potentially be explored or discussed in more detail. Are there specific aspects of the biology of the substrata that could explain this (or lead to testable hypotheses?)

2. Given that LTL is genetically correlated (and MR evidence suggests also possibly causal evidence in some cases) across a range of traits (e.g., adiposity) that may also associate with lung cancer, a larger genetic correlation analysis might be in order, followed by a larger set of multivariable MR (MVMR) beyond smoking as a risk factor. Basically, can the observed relationship be explained by another trait (beyond smoking)? For example, there is previous MR literature on adiposity measures, for example (BMI, WHR, or WHRadjBMI) and telomere length, plus literature on adiposity with lung cancer; furthermore, smoking with BMI. A bit more comprehensive set of MVMR analyses within this space would elevate the significance and interpretation compared to previous literature.

3. In the initial LTL paper, the authors constructed an IV for MR analyses, which appears different than what the authors selected here. For example, Codd et al. proposed an n=130 SNP instrument from their n=193 sentinel variants, after filtering for LD (n=193 >>> n=147) and then for multi-trait association (n=147 >> n=130). I don't think this will fundamentally change the author's result, but the authors may want to confirm robustness to slightly different instrument selection procedures or explain why they favor their approach over the previous one.

4. Colocalization analysis suggests that a /subset/ of LTL signals map onto lung cancer signals. Does this mean that the MR relationships are driven entirely by this small subset, or is there evidence (polygenic) from other loci? Rather than do a "leave one out" the authors could stratify their instrument into "coloc +ve / coloc -ve" and redo the MR analyses.

Mainly here, the goal is to interpret if the subset of signals at the top (looks like n=14, the bump of non-trivial PP4 > 0.6, say) which map predominantly to TERT, TERC, and OBFC1 explain the observed effect here. I.e., it is biology around these specific mechanisms or generally LTL (polygenicity) but exemplified by extreme examples (TERT, etc.). I appreciate that statistical power is a consideration to keep in mind with interpretation.

Reviewer #2 (Public Review):

The study is a careful investigation of the physical properties of hagfish slime and the underlying cellular framework that enables this extraordinary evolutionary innovation. I appreciate the careful and detailed measurements and images that the authors provide. The results presented here will surely be extremely important for researchers working on this particular organism and those interested in understanding the evolution, biomedical relevance, and biochemistry of mucus. However, I had difficulty contextualizing the findings in broader biological questions (e.g., the evolution of functional novelty, the adaptive processes, and the links between genetic and phenotypic evolution). I also think that the conclusions on the evolutionary origins and underlying genetics of hagfish slime based on comparative transcriptomic data may be premature.

Reviewer #2 (Public Review):

Chinnaiya et al. integrated recent scRNA transcriptomics with high-resolution multiplexing in situ hybridization, fate mapping and tissue explants to unravel the spatiotemporal development of early chick tuberal hypothalamus. They show that a wave of BMP signaling passes through anterior and posterior regions sequentially. Interestingly, they showed that neuroepithelial-intrinsic BMPs drive and maintain tuberal hypothalamus late development. Using bioinformatical and in situ profiling, the authors indicated the potential of the tuberal progenitors transferring into radial glia-like cells.

This is a remarkable piece of work and I commend the authors for their bold endeavor to decipher the complex developmental of the tuberal hypothalamus.

Reviewer #2 (Public Review):

This manuscript shows that two doses of the live attenuated Coronavac vaccine induce neutralising antibodies in the majority of individuals, though neutralisation is modest for Omicron BA.1 even after 1 month post-dose two, and substantial waning at 12 months is noted. Boosting achieves higher neutralisation than for prior doses.

Strengths of the work are the significant sample size in the cross-sectional part and a smaller prospective part which adds value to the study as a whole.

The assays used are appropriate, with PV bearing Wu-hu-1, Delta, and Omicron spike proteins.

Weakness includes the fact that the cross-sectional aspect recruits at different sites at different time points, introducing the fact that observed differences in vaccine response may be related to the underlying population differences.

In addition, the data on third-dose boosting do not appear to include VOC. This is important because data from other vaccines suggest broadening of neutralisation with the third dose.

Reviewer #2 (Public Review):

To advance the understanding of the initial events in recognition of HIV-1 genome by the viral structural protein Gag, in this study, the authors examined the involvement of the CA domain in the specific interaction between Gag and the viral genomic RNA. Previous studies including a study from the same group (Kutluay et al 2010) showed that the CA C-terminal domain plays a role in Gag binding to viral genomic RNA. In the current study, they analyzed a panel of CA mutants using a modified PAR-CLIP RNA sequencing, which allows identification of Gag binding sites in the viral genome, and a chemical crosslinking approach, which allows assessment of the multimerization status of Gag in cells. They found that substitutions of CA residues at the CA dimer, trimer, or hexamer interfaces, which reduce Gag multimerization as expected, also reduce the Ψ sequence-specific viral RNA binding, whereas substitutions elsewhere in CA have no impact. They further found that substitutions of the Lys residues important for IP6 binding, which disrupt Gag lattice formation, reduce the Ψ-specific RNA binding, whereas a second-site mutation that restores virus assembly in these Lys substitution mutants restores the RNA binding. These results strongly support the authors' conclusion that Gag lattice formation driven by CA plays an important role in NC-mediated recognition of the Ψ sequence.

The strengths of the work include the application of the modified PAR-CLIP method to the analysis of a large panel of CANC constructs. This provided the detailed information on the specific molecular features in CA required for interactions between Gag and the Ψ sequence, which was not obtainable in the previous studies. The absence of the MA domain in these constructs allowed the authors to focus on the cytoplasmic interactions. The data obtained with oligomer-forming NC constructs and CANC constructs that differ in the IP6 dependence also add support to the authors conclusion that CA-mediated lattice formation of CANC and not just NC oligomerization plays a key role in Gag-vRNA binding. Overall, the data support the conclusion that the ability to form the CANC lattice is essential for the initial NC-vRNA interaction.

The only notable weakness is that previous work by this group and others have already shown that CA and/or its interaction interfaces plays an important role in the Gag-vRNA interaction. Therefore, the current work can be regarded as a refinement of the previously presented concept rather than a conceptual breakthrough. Nonetheless, these mechanistic details are likely to help the retrovirology community gain a clearer grasp of the early steps of infectious particle formation.

Reviewer #2 (Public Review):

This interesting manuscript uses a collection of whole genome sequences of TB isolates to associate specific sequence polymorphisms with MDR/XDR strains, and having found certain mutations in DNA repair pathways, does a detailed analysis of several mutations. The evaluation of the MutY polymorphism reveals it is loss of function and TB strains carrying this mutation have a higher mutation frequency and enhanced survival in serial passage in macrophages. The strengths of the manuscript are the leveraging of a large sequence dataset to derive interesting candidate mutations in DNA repair pathway and the demonstration that at least one of these mutations has a detectable effect on mutagenicity and pathogenesis. The weaknesses of the manuscript are a lack of experimental exploration of the mechanism by which loss of a DNA repair pathway would enhance survival in vivo. The model presented is that these phenotypes are due to hypermutagenicity and thereby evolution of enhanced pathogenesis, but this is not actually directly tested or investigated. There are also some technical concerns for some of the experimental data which can be strengthened.

This paper presents the following data:

- Analyzed whole-genome sequences 2773 clinical strains: 160 000 SNPs identified<br /> - 1815 drug-susceptible/422 MDR/XDR strains: 188 mutations correlated with Drug resistance.<br /> - Novel mutations associated with the drug resistance have been found in base excision repair (BER), nucleotide excision repair (NER), and homologous recombination (HR) pathway genes (mutY, uvrA, uvrB, and recF).<br /> - Specific mutations mutY-R262Q and uvrB-A524V were studied.<br /> - mutY-R262Q and uvrB-A524V mutations behave as loss of function alleles in vivo, as measured by non-complementation of the increased mutation frequency measured by resistance to Rif and INH.<br /> - The mutY deletion and the mutY-R262Q mutation increase Mtb survival over WT in macrophages when Mtb has not been submitted to previous rounds of macrophage infection.<br /> - This advantage is exacerbated in presence of antibiotic (Rif and Cipro but not INH).<br /> - The MutY deletion and the MutY-R262Q mutation result in an enhanced survival of Mtb during guinea pig infection.

Major issues:

The finding that mutations in MutY confers an advantage during macrophage infection is convincing based on the macrophage experiments, but it is premature to conclude that the mechanism of this effect is due to hypermutagenesis and selection of fitter bacterial clones. It is described in E. coli (Foti et al., 2012) and recently in mycobacteria (Dupuy et al., 2020) that the MutY/MutM excision pathways can increase the lethality of antibiotic treatment because of double-strand breaks caused by Adenine/oxoG excisions. The higher survival of the mutY mutant during antibiotic treatment could more be due to lower Adenine/oxoG excision in the mutant rather than acquisition of advantageous mutations, or some other mechanism. The same hypothesis cannot be excluded for the Guinea pig experiments (no antibiotics, but oxidative stress mediated by host defenses could also increase oxoG) and should at least be discussed. Experiments that would support the idea that the in vivo advantage is due to hypermutagenesis would be whole genome sequencing of the output vs input populations to directly document increased mutagenesis. Similarly, is the ΔmutY survival advantage after rounds of macrophage infections dependent on macrophage environment? What happens if the ΔmutY strain is cultivated in vitro in 7H9 (same number of generations) before infecting macrophages?

- It would be useful to present more data about the strain relatedness and genome characteristics of the DNA repair mutant strains in the GWAS. For example, the model would suggest that strains carrying DNA repair mutations should have higher SNP load than control strains. Additionally, it would be helpful to know whether the identified DNA repair pathway mutations are from epidemiologically linked strains in the collection to deduce whether these events are arising repeatedly or are a founder effect of a single mutant since for each mutation, the number of strains is small.

- Some of the mutation frequency, survival and competition data could be strengthened by more experimental replicates. Data Lines 370-372 (mutation frequency), lines 387-388 (Survival of strains ex vivo), line 394 (competition experiment) : "Two biologically independent experiments were performed. Each experiment was performed in technical triplicates. Data represent one of the two biological experiments." Two biological replicates is insufficient for the phenotypes presented and all replicates should be included in the analysis. In addition, the definition of "technical triplicates" should be given, does this mean the same culture sampled in triplicate?

- MutY phenotypes. One caveat to the conclusion that the MutY R262Q mutant is nonfunctional is the lack of examination of the expression of the complementing protein. I would be informative to comment on the location of this mutation in relation to the known structures of MutY proteins. Similarly, for the UvrB polymorphism, this null strain has a clear UV sensitivity phenotype in the literature, so a fuller interrogation for UV killing would be informative re: the A524V mutation.

Public speaking was practiced long before the Greeks.Systemic the-art of public speaking, which they called "rhetoric".

Reviewer #2 (Public Review):

Wang and colleagues previously characterized the protein interactome for GABA subunits and identified HSP47 chaperone as a top interacting protein. Here, they follow up to assess the function of this HSP47-GABA interaction. Using primarily HEK293 cells, they provide evidence that the ER-resident HSP47 chaperone promotes the folding of GABA receptor subunits and the assembly of GABA subunits into multimeric ion channels. Interestingly, they demonstrate HSP47 can rescue the folding and function of a missense mutant A332D epilepsy-associated GABA subunit. They also demonstrate similar enhanced folding/function for acetylcholine receptor assembly. Overall, the experimental data are well-presented and provide insight into new ion channel clients whose folding and assembly are dependent on the HSP47 chaperone. The study also identifies HSP47 expression as a potential strategy to target and enhance the function of misfolded ion channels, and this may have broader biomedical therapeutic significance beyond GABA channels.

Reviewer #2 (Public Review):

Overall, the manuscript is clearly written and remarkably comprehensive, presenting a very large amount of data. Experimental methods are well-documented and rigorous, and I have no significant technical concerns about any of the work presented. There are some points where the presentation might be improved by modifications to the text or figures, particularly with the goal of making this important work accessible to a broad audience.

Reviewer #2 (Public Review):

This mechanistic PK/PD model simultaneous characterized several important factors, including formation of immunological synapses synapse variants, target/tumor cell densities, target CD3/tumor antigen expression levels, tumor antigen escape and the associated cancer relapse, in a unified model structure.

This model has the potential to be used in optimization dosage of T cell redirecting bispecific treatment towards best clinical outcome.

Reviewer #2 (Public Review):

This study by Yang & al. explores the mechanism of X dosage compensation in the nematode species C. briggsae; which is a close relative of C. elegans. The mechanism is well described in C. elegans, and the authors have asked whether the same condensin-like complex (DCC) is responsible for the silencing of the X and which motifs on the X are responsible for this binding specificity in C. briggsae. They discovered that although the general principle of X inactivation is conserved between these 2 species, and ortholog proteins of the pathway (xol-1, sdc-2, and the genes encoding the DCC complex) are conserved, the sequences on the X that are recognized by the DCC complex have evolved very rapidly. The motifs of C. briggsae are not recognized by the C. elegans proteins and vice versa. The authors have accumulated very solid data, both in vitro and in vivo, to support this conclusion.

Overall, the results are very convincing and extremely interesting, for the chromatin field but also from an evolutionary perspective. This finding is comparable to the discovery that centromeric sequences and centromere proteins, despite their essential function in cells, evolve extremely rapidly. The reason is that they are involved in genetic conflicts, are a perfect target to generate hybrid incompatibilities during crosses, and therefore, under such selective pressure, evolve super fast. Most examples of hybrid incompatibilities rely on chromatin conflicts, and with this study, it appears that the dosage compensation system could be one other way to generate hybrid breakdown.

Reviewer #2 (Public Review):

Briševac et al. investigate the genetic architecture of an exceptional ecological system where Clunio marinus populations have diverged in their timing of reproduction, controlled by a circalunar clock. These loci may be important in sympatric speciation and/or rapid evolution of reproductive isolation but there are some issues that need to be resolved. I outline these below:

1) The QTL mapping relies on a modest number of individuals and there are important details missing. The manuscript is missing information on heritability of the trait which is important for interpretation. While the variance explained by the QTL is hight, for the estimates of QTL effect sizes from such small samples, there is a common issue known as the Beavis effect that can inflate the effect size of individual QTL.

2) My major concern with the paper is the interpretation of divergence within the inversion as linked causally to the genes underlying ecological divergence. As the authors observe, divergence will vary within an inverted region. This can be traced to myriad factors, including variation in mutation rate, variation in constraint, patterns of ancestral polymorphism within this region, and variation in gene conversion within the inversion. Given this, I do not think it is valid to interpret the regions of high differentiation as the causal drivers of the ecological differentiation.

3) The authors imply in the discussion based on historical results that the ecotype evolved in situ in the last ~60 years. This seems substantially less likely to me than a number of alternative hypotheses including missing the phenotype in previous samples, plasticity in the phenotype causing it to be missed or migration from populations where the phenotype already existed.

Reviewer #2 (Public Review):

This study aims to describe the distribution and functional status of monocytes and dendritic cells in the blood and nasopharyngeal aspirate (NPA) after respiratory viral infection in more than 50 patients affected by influenza A, B, RSV and SARS-CoV2. The authors use flow cytometry to define HLA-DR+ lineage negative cells, and within this gate, classical, intermediate and non-classical monocytes and CD1c+, CD141+, and CD123+ dendritic cells (DC). They show a large increase in classical monocytes in NPA and an increase in intermediate monocytes in blood and NPA, with more subtle changes in non-classical monocytes. Changes in intermediate monocytes were age-dependent and resolution was seen with convalescence. While blood monocytes tended to increase in blood and NPA, DC frequency was reduced in blood but also increased in NPA. There were signs of maturation in monocytes and DC in NPA compared with blood as judged by expression of HLA-DR and CD86. Cytokine levels in NPA were increased in infection in association with enrichment of cytokine-producing cells. Various patterns were observed in different viral infections suggesting some specificity of pathogen response. The work did not fully document the diversity of human myeloid cells that have arisen from single-cell transcriptomics over the last 5 years, notably the classification of monocytes which shows only two distinct subsets (intermediate cannot be distinguished from classical), distinct populations of DC1, DC2 and DC3 (DC2 and 3 both having CD1c, but different levels of monocyte antigens), and the lack of distinction provided by CD123 which also includes a precursor population of AXL+SIGLEC6+ myeloid cells in addition to plasmacytoid DC. Furthermore, some greater precision of the gating could have been achieved for the subsets presented. Specifically, CD34+ cells were not excluded from the HLA-DR+ lineage- gate, and the threshold of CD11c may have excluded some DC1 owing to the low expression of this antigen. Overall, the work shows that interesting results can be obtained by comparing myeloid populations of blood and NPA during viral infection and that lineage, viral and age-specific patterns are observed. However, the mechanistic insights for host defense provided by these observations remain relatively modest.

Reviewer #2 (Public Review):

The paper describes a fairly complete set of experiments describing a mechanism by which 4-hour treatment with 25HC can provide reductions in plasma membrane cholesterol for up to 22 hours. The basic finding is that 25HC depletes the ER of cholesterol by stimulating esterification and that SREBP activation is also inhibited. This effect is associated with the slow loss of 25HC from the cells.

The paper describes detailed studies of the long-lasting effects of a 4-hour exposure to 25HC on the loss of plasma membrane cholesterol. The paper characterizes the effects on SREBP processing to account for this. The possible long-lasting effects of ACAT stimulation were not investigated but may play an equal role.

The paper presents data that the effects on plasma membrane cholesterol can account for the inhibitory effects on some bacterial toxins and viruses.

Reviewer #2 (Public Review):

In this article, a multi-modal strategy for live birth prediction is proposed using blastocyst images and clinical features. The CNN architecture is used for the imaging dataset, while an MLP is built for the clinical features, and the final model is developed by concatenating CNN and MLP features. 17,580 samples are used for training and testing the model. The proposed model performed significantly better than the previous ones, with an AUC of 0.77.

By creating activation maps in both scenarios: I) when imaging and clinical features were used, and II) when only imaging data was used, authors highlight the parts of images that are crucial for predictions. Their results confirm the benefits of utilizing multi-modal datasets.

However, the manuscript is currently lacking crucial methodological information that is necessary to judge the validity of various claims.<br /> Furthermore, it lacks discussion of the potential applications of the proposed model in clinical settings.

Reviewer #2 (Public Review):

There are fundamental differences in resting state with eyes open or eyes closed regardless of visual stimulation. Without visual stimulation, these differences are attributed to the switching of involuntary attention from internal (eyes closed) to external (eyes open). The authors employ a monocular deprivation paradigm by patching one eye (with it either open or closed) to induce differences in alpha amplitude that are similar to differences measured with both eyes open or closed. They then examine how these differences from monocular deprivation impact after-effects in contrast sensitivity and binocular balance.

The authors pose an interesting and well-supported hypothesis based on prior knowledge that internal oscillations (i.e. alpha waves) can be modulated with eyes open vs eyes closed. The presented experiments build well upon one another and the authors clearly describe how relevant findings from experiment 1 contribute to the design of the following monocular deprivation experiments. The authors also combine several metrics including EEG, SSVEP and contrast sensitivity to assess both neural activity and perception in tandem.

Despite these strengths, the reported data in the first experiments only shows a modest difference between conditions. In experiment one, the authors make the assumption that differences in alpha measured with binocular eyes open vs closed translates to differences in alpha noted with a patched eye open or closed. Although changes in alpha amplitude appear comparable under monocular and binocular viewing, the differences in perceptual contrast sensitivity between the patched eye open and closed condition are quite modest. The authors do not report differences in contrast sensitivity in the binocular condition, so it is difficult to assess if these are comparable (contrast sensitivity changes in binocular (both eyes open vs closed) and monocular (patched eye open vs closed). The authors also employ their results to make claims about neuroplasticity, however this may be too general a claim. It seems as though the authors are specifically using an adaptation paradigm to elicit short-term changes (within 30 minutes from deprivation). While technically, the visual system is changing, it may be slightly misleading to refer to these neuroplastic changes given there are no measured long-term effects. The authors also fail to explain differences in binocular paradigm, noting recovery of binocularity in their phase combination paradigm, but persistent changes in their rivalry assessment. The authors also may overstate the implications of this in the discussion, as they provide no direct evidence that their reported changes after monocular deprivation are attributed to GABA interactions in primary visual cortex.

This work is important to our understanding of not only endogenous modulators of visual perception, but may have implications in how this knowledge is applied in clinical practice, specifically the treatment of amblyopia with patching.

Reviewer #2 (Public Review):

The manuscript compares the chondrogenic potential of iPSCs derived from human chondrocytes isolated from healthy and osteoarthritic AC tissue. Both iPSCs derived from healthy and osteoarthritic AC tissue exhibit markers of pluripotency and were able to give rise to mesenchymal progenitors, although they had distinct differences in metabolic and chromatin modifier genes, as found by RNA seq analysis. The impact of these transcriptome signatures was functionally reflected in a lower chondrogenic potential of the MSCs derived from OA iPSCs compared to healthy donor (AC) iPSCs. This was assessed based on the reduced expression of hyaline cartilage markers and the reduced deposition of the glycoprotein-rich ECM matrix upon chondrogenic differentiation of day 21 micromass cultures from OA patients compared to healthy donors. The distinct gene expression profiles of OA chondrocytes were also found to be consistent with publicly available RNA-seq data performed on healthy and OA cartilage tissues further confirming that the newly identified differences in epigenetic and metabolic signatures are imprint from healthy and OA-chondrocytes.

Reviewer #2 (Public Review):

Tools that enable labeling and genetic manipulations of synaptic partners are important to reveal the structure and function of neural circuits. In a previous study, Barnea and colleagues developed an anterograde tracing method in Drosophila, trans-TANGO, which targets a synthetic ligand to presynaptic terminals to activate a postsynaptic receptor and trigger nuclear translocation of a transcription factor. This allows the labeling and genetic manipulation of cells postsynaptic to the ligand-expressing starter cells. Here, the same group modified trans-TANGO by targeting the ligand to the dendrites of starter cells to genetically access pre-synaptic partners of the starter cells; they call this method retro-TANGO. The authors applied retro-TANGO to various neural circuits, including those involved in escape response, navigation, and sensory circuits for sex peptides and odorants. They also compared their retro-TANGO data with synaptic connectivity derived from connectivity obtained from serial electron microscopy (EM) reconstruction and concluded that retro-TANGO can allow trans-synaptic labeling of presynaptic neurons that make ~ 17 synapses or more with the starter cells.

Overall, this study has generated and characterized a valuable retrograde transsynaptic tracing tool in Drosophila. It's simpler to use than the recently described BAcTrace (Cachero et al., 2020) and can also be adapted to other species. However, the manuscript can be substantially strengthened by providing more quantitative data and more evidence supporting retrograde specificity.

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Reviewer #2 (Public Review):

The cycling of "co-substrates" in metabolic reactions is possibly a very important but often overlooked determinant of metabolic fluxes. To better understand how the turnover dynamics of co-substrates affect metabolic fluxes the authors dissect a few metabolic reaction motifs. While these motifs are necessarily much simpler than real metabolic networks with dozens or hundreds of reactions, they still include important characteristics of the full network but allow for a deeper mathematical analysis. I found this mathematical approach of the manuscript convincing and an important contribution to the field as it provides more intuitive insights how co-substrate cycling could affect metabolic fluxes. In the manuscript, the authors stress particularly how the pool sizes of co-substrates and the enzymes involved in the cycling of those can constrain metabolic fluxes but the presented results also go substantially beyond this statement as the authors further illustrate how turnover characteristics of substrates in branches/coupled reactions can affect the ratio of produced substrates.

The authors further present an analysis of previously published experimental data (around Figure 3). This is a very nice idea as it can in principle add more direct proof that the cycling of co-substrates is indeed an important constraint shaping fluxes in real metabolic networks and (instead of being merely a theoretical phenomena which occurs only in unphysiological parameter regimes). However, the way currently presented, it remained unclear to which extent the data analysis is adding convincing support that co-cycling substantially constrains metabolic fluxes. Particularly, it remains unclear for which organisms and conditions the used experimental dataset holds, how it has been generated, and with what uncertainty different measured values come. For example, the comparison requires an estimation of v_max. How can these values determined in-vivo? Are (expected) uncertainties sufficiently low to allow for the statement that fluxes are higher than what enzyme kinetics predict? Furthermore, I am wondering to which extent the correlations between co-substrate pool levels and flux is supporting the idea that co-substrate cyling is important. The positive relation between ATP/AMP/ADP levels for example, is a nice observation. However, it remains a correlation which might occur due to many other factors beyond the limitations of co-substrate cycling and which might change with provided conditions.

Reviewer #2 (Public Review):

The authors are building on previous work by Dahlén et al testing for phenome-wide associations between ABO/RhD blood groups. This is important for identifying potential disease mechanisms related to the blood groups, and for identifying blood groups that may be at higher risk of certain diseases. As we begin to create predictive models across diseases for precision medicine approaches in clinical care, this type of information informs the inclusion of blood groups as predictors in these models.

Notably, this study looks at each subset of A, B, AB, and O versus the remaining groups as compared to other studies which focus on comparing O and non-O blood groups. This paper successfully estimates the incidence rate ratios for 1,312 phecodes for A, AB, B, O, and RhD blood groups. The authors also tested for associations between the age of diagnosis and blood groups. The study's conclusions largely summarize these associations, which are important for the community to browse and interpret. However, the conclusion that ABO/RhD groups are the result of selective pressure driven partially by robustness to disease is not well founded simply from the significant association statistics within the paper.

As in all studies, there are inherent limitations in the data. The Danish National Patient Registry (DNPR) is a population-level cohort, so findings may be generalizable to Denmark or European countries. However, ascertainment biases may exist from what subset of the DNPR also had blood group determination (patients who may need blood transfusions during their hospital stay) and from the use of diagnoses from a hospital setting (most severe diseases) rather than the primary care setting.

The statistical model used to identify these associations is sound, although additional sensitivity analyses and rationale descriptions would add clarity to the appropriateness of this model and variable selection. The authors carefully note that, based on the study design, any associations here are not to be causally interpreted. The study is well powered with nearly 500,000 patients and a median follow-up time of 40.8 years. Multiple testing burden is accounted for using FDR-adjusted p-values. The established method of phecode mapping is used for this phenome-wide approach.

Reviewer #2 (Public Review):

The HIV inflammasome sensor CARD8 senses intracellular HIV-1 protease activity through direct cleavage by HIV-1 protease between the F59 and F60 positions in the human CARD8 protein. The authors show that the F60 position is variable across non-human primate species that show varying levels of cleavage efficacy. They also posit that inflammasome induction may be dependent upon Toll-like receptor signaling.

Strengths: The authors are able to show that both HIV-1 and HIV-2 cleave and activate the human CARD8 inflammasome. The authors also demonstrate that changes to the 60th position of CARD8 cause a decrease in cleavage efficacy in vitro by HIV-1.

Weaknesses: The study is limited to the introduction of a few mutations in human CARD8 and their cleavage and activation by HIV. The physiological relevance remains unclear without direct investigation of different versions of simian CARD8 protein and SIVs in T cells and macrophages.

Reviewer #2 (Public Review):

By now, the public is aware of the peculiarities underlying the omicron variants emergence and dissemination globally. This study investigates the mutational biography underlying how mutation effects and epistasis manifest in binding to therapeutic receptors.

The study highlights how epistasis and other mutation effect measurements manifest in phenotypes associated with antibody binding with respect to spike protein in the omicron variant. It rigorously tests a large suite of mutations in the omicron receptor binding domain, highlighting differences in how mutation effects affect binding to certain therapeutic antibodies.

Interestingly, mutations of large effect drive escape from binding to certain antibodies, but not others (S309). The difference in the mutational signature is the most interesting finding, and in particular, the signature of how higher-order epistasis manifests in the partial escape in S309, but less so in the full escape of other antibodies.

The results are timely, the scope enormous, and the analyses responsible.

My only main criticisms walk the stylistic/scientific line: many of the others have pioneered discussions and methods relating to the measurement of epistasis in proteins and other biomolecules. While I recognize that the purpose of this study is focused on the public health implications, I would have appreciated more of a dive into the peculiarity of the finding with respect to epistasis. I think the authors could achieve this by doing the following:

a) Reconciling discussions around the mutation effects in light of contemporary discussions of global epistasis "vs" idiosyncratic epistasis, etc. Several of the authors of the manuscript have written other leading manuscripts of the topic. I would appreciate it if the authors couched the findings within other studies in this arena.

B)While the methods used to detect epistasis in the manuscript make sense, the authors surely realize that methods used to measure is a contentious dimension of the field. I'd appreciate an appeal/explanation as to why their methods were used relative to others. For example, the Lasso correction makes sense, but there are other such methods. Citations and some explanation would be great.

Lastly (somewhat relatedly), I found myself wanting the discussion to be bolder and more ambitious. The summary, as I read it, is on the nose and very direct (which is appropriate), but I want more: What do the findings say for greater discussions surrounding evolution in sequence space? For discussions of epistasis in proteins of a certain kind? In, my view, this data set offers fodder for fundamental discussion in evolutionary biology and evolutionary medicine. I recognize, however, the constraints: such topics may not be within the scope of a single paper, and such discussions may distract from the biomedical applications, which are more relevant for human health.

But I might say something similar about the biomedical implications: the authors do a good job outlining exactly what happened, but what does this say about patterns (the role of mutations of large effect vs. higher-order epistasis) in some traits vs others? Why might we expect certain patterns of epistasis with respect to antibody binding relative to other pathogenic virus phenotypes?

In summary: rigorous and important work, and I congratulate the authors.

Reviewer #2 (Public Review):

In the submitted manuscript under the title "NSC-derived exosomes enhance therapeutic effects of NSC transplantation on cerebral ischemia in mice", Zhang et al. applied human induced pluripotent stem cells (iPSCs) together with exosomes extracted from NSCs to treat cerebral ischemia induced by middle cerebral artery occlusion/reperfusion (MCAO/R) in mice. They reported that NSC-derived exosomes can ease the inflammatory response, alleviated oxidative stress after NSC transplantation, and facilitated NSCs differentiation in mouse brain. Using the NSC together with their exosomes can ameliorate the injury of brain tissue including cerebral infarct, neuronal death and glial scarring, and promoted the motor function recovery. Finally, they speculated that the miRNA(s) in the exosomes is the key factor to improve the treatment of the NSC transplantation for the stroke. This is an interesting study that contributes important findings which will be of interest to the researcher in the field of the NSC transplantation. However, there are some key points should be further explained.

Major points:<br /> 1). This study does not provide any evidence about the cell death of the transplanted cells. The immunostaining of the Caspase-3 or TUNEL staining should be used to address this issue.

2). The authors showed that the neurological functions (evaluated by balance beam, ladder lung, rotarod test and Modified Neurological Severity Score (mNSS) up to 8 weeks after treatment (Figure 1C)) were significantly improved in the NES+Exo group compared to their control groups. However, these cells (transplanted cells) are progenitors (Nestin+) or undifferentiated cells (Tuj1+) at this stage (Figure 3). Thus, I was curious about that how can the immature neurons play neurological functions? This point should be explained.

3). The authors used the Golgi staining to show the NES+Exo can improve dendritic density and length. How do you know these neurons are transplanted cells?

4). The cell morphology of tdTomato+ cells is fuzzy and it is difficult to distinguish the cell body. It looks like that these cells out of whack.

Reviewer #2 (Public Review):

To understand the origins of life, it is often necessary to establish synthetic molecular systems that model how primitive cells might have operated. Adopting this approach, here Le Vay et al. tackle one of the mysteries of early cells: how could primitive biomolecules have controlled the behavior of the compartments they inhabited? By forming coacervate droplets from polylysine peptides and ribozymes (catalytic RNAs), they observe changes in droplet properties driven by ribozyme activity and propose a route to form an integrated protocellular system that allows the evolution of biomolecules based on compartment behavior, modeling potential early life processes.

Polymers of opposite charge can phase-separate into coacervate droplets in equilibrium with surrounding aqueous phases. Such condensates are thought to act as subcellular compartments mediating some cellular functions. Coacervates, though, are also of interest as model compartments for biomolecules at the origins of life. A number of studies have shown how the properties and behavior of coacervates can be modulated based on external biological or physicochemical changes. There remains a key question: for coacervates to serve as a vessel for biology at the origin of life, can coacervate behavior be controlled from within? Previously this has been shown possible in some systems of membranous vesicles, an alternative model of primordial compartments.

Proteinaceous enzymes have been deployed to transform precursor compounds into potential coacervate components and induce the formation of condensed-phase microdroplets, but such enzymes are not thought to have been available at the origins of life. Instead, ribozymes are thought to have catalysed key reactions in early biology. Here, by using a ribozyme ligase to concatenate RNA molecules when together in a polylysine coacervate, the authors clearly demonstrate that coacervate properties change, showing a more rounded droplet shape and reduced fusion tendencies. Interestingly, the authors find that this distinctive behavior emerges when the reaction occurs in the coacervate phase, instead of before coacervate formation.

This influence of sequence-encoded phenotype on compartment properties has few precedents and has long been a target of origin of life research. The authors propose that it could serve as the basis for the establishment of coacervate droplets as units of selection and evolution. For this, a trio of critical challenges must be overcome and the authors begin to shed light on these.

First, the droplets must support ribozyme activity, without overly inhibiting it (or the droplet becomes an unfavorable habitat for these catalysts). Other ribozymes have often suffered inhibition due to conformation effects or substrate availability when mixed in a coacervate. The authors show here that the ligase ribozyme maintains activity (and may even be accelerated) in the coacervate. However, it appears to operate under single-turnover conditions and it is not yet clear whether multiple-turnover catalysis is possible in the coacervate.

Second, the droplet properties must be responsive to the activity of the biomolecules inside. The authors' observations of changes in coacervate behavior are robust, and they make some suggestions as to how such changes might be leveraged to establish selection pressure to drive the evolution of content molecules. In this study, though, the ribozyme comprises a substantial fraction (~1/2) of the coacervate negatively charged components, and in an evolutionary situation (with fewer molecules of RNA catalyst per compartment) it is not known whether the resulting droplet phenotype will change impactfully.

Third, the droplet must hold together its contents and avoid mixing with the contents of other droplets, to hold a molecular species together and defend against molecular parasites. Though there may still be some exchange of smaller molecules, the authors demonstrate that the lengthening of RNAs by ribozyme ligases in a coacervate can prevent fusion with other similar droplets (which otherwise occurs in the absence of RNA ligation) and preserve droplet identity. To use the coacervate as an evolutionary unit, droplets with active ribozyme will also need to be resistant to fusion with inactive droplets.

Putting such a system together based on the phenomenon observed by the authors would be a breakthrough in modeling primordial biology. A range of compartments have been proposed to act as habitats for early molecular biology, including porous rocks, mineral surfaces, ice phases, aerosols as well as membranous vesicles, and a key challenge is demonstrating how internal biological activities can influence compartment behavior. Establishing coacervates as genetically-controllable habitats for biomolecules will add to experimental models of such "life but not as we know it" and provide a new view of early biology.

Reviewer #2 (Public Review):

Gyrencephaly has been linked to the split of the subventricular zone (SVZ) and the formation of an outer subventricular zone (OSVZ) during neurogenesis. This paper proposes a convincing multizone computational model of neurogenesis allowing exploration of the role of this OSVZ in the folding dynamics. This model is a bridge between knowledge of cell proliferation and migration and the physics of growth.

Strengths<br /> • The computational model described in this paper is probably the most ambitious to date. It succeeds in translating the complexity of microscopic biological phenomena that describe cell proliferation and migration into physical phenomena from continuum mechanics. It is truly a tour de force.<br /> • The description of neurogenesis is particularly clear, within the reach of a naive reader despite its complexity. The figure illustrating the chronology of the phenomena at work is a success.<br /> • The paper builds on impressive efforts to estimate from real human brain sections some of the complex parameters of the model such as the density of cells at different stages of migration.<br /> • The physical model is able to show ripples in the deep zones of proliferation that seem induced by the folding of the cortex. This observation is consistent with feedback from folding on the organization of the migration, as these ripples are not part of the model. I do not know to what extent these ripples have been demonstrated in reality.<br /> • The model shows that significant proliferation in the OSVZ leads to a doubling of the frequency of folding, a phenomenon observed in reality in large brains, which gives rise to allometric laws between folding and brain size (see Toro et al., Germanaud et al.)<br /> • The paper includes an experiment based on heterogeneous proliferation in the OSVZ, which is difficult to model in more classical models such as Tallinen's one. This is a particularly interesting possibility for modelling spatial heterogeneity in the expression of genes that modulate neurogenesis (see Llinares-Benadero et al.).

Weaknesses<br /> • To account for the complexity of biological phenomena, the model relies on a large number of ad hoc choices whose consequences are difficult to predict.<br /> • The physical model description is highly technical and out of reach for a non-specialist.<br /> • The description of neurogenesis shows three zones of cell proliferation, each inhabited by a specific cell type. Despite its realism, the proposed model does not take into account the ISVZ where the intermediate progenitors operate.<br /> • The experiment of comparing several regimes derived from the relative importance of proliferation in the VZ and OSVZ is not very clear. It leads to the observation of the evolution of cell density maxima over time, which seems insufficient to conclude the importance of the OSVZ for folding. One wonders whether the key parameter that leads to folding is the rate of OSVZ proliferation or simply the total quantity of neurons generated by the two or even the three zones.<br /> • The experiment on the heterogeneity of proliferation in the OSVZ is a bit frustrating. I would like to see a set-up corresponding to the mosaics found in ferrets and closely associated with folding patterns.<br /> • It would be interesting to elaborate a little on the possibility of extending the model in 3D, which seems imperative to evaluate the nature of the folding pattern generated. Comparing them to reality is an essential step in gauging the credibility of the model. For instance, it would be interesting to test to which extent the model can father the type of variability observed in the general population (Mangin et al.). It will also be particularly interesting to work on the inverse model between the real folding patterns and the heterogeneous proliferation maps that can generate them.

Conclusion

The computational model of neurogenesis described in this paper is the most sophisticated model proposed to date. It is a convincing step towards a model that could one day simulate perturbations of neurogenesis that may give rise to the gyration abnormalities observed in certain developmental pathologies. A better understanding of the genesis of these anomalies could contribute to their use as a signature of hidden deleterious events occuring during neurogenesis.

References

Toro, R., Perron, M., Pike, B., Richer, L., Veillette, S., Pausova, Z., & Paus, T. (2008). Brain size and folding of the human cerebral cortex. Cerebral cortex, 18(10), 2352-2357.<br /> Germanaud, D., Lefèvre, J., Toro, R., Fischer, C., Dubois, J., Hertz-Pannier, L., & Mangin, J. F. (2012). Larger is twistier: spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism. NeuroImage, 63(3), 1257-1272.<br /> Tallinen, T., Chung, J. Y., Rousseau, F., Girard, N., Lefèvre, J., & Mahadevan, L. (2016). On the growth and form of cortical convolutions. Nature Physics, 12(6), 588-593.<br /> Llinares-Benadero, C., & Borrell, V. (2019). Deconstructing cortical folding: genetic, cellular and mechanical determinants. Nature Reviews Neuroscience, 20(3), 161-176.<br /> Mangin, J. F., Le Guen, Y., Labra, N., Grigis, A., Frouin, V., Guevara, M., ... & Sun, Z. Y. (2019). "Plis de passage" deserve a role in models of the cortical folding process. Brain topography, 32(6), 1035-1048.

Reviewer #2 (Public Review):

The authors of this paper identify a knowledge gap in our understanding of the generalizability of ecological associations of gut bacteria across hosts. Theoretically, it is possible that ecological associations between bacteria are consistent within a host organism but differ between hosts, or that they are universal across hosts and their environmental gradients. The authors utilize longitudinal data with a unique temporal resolution, on Amboseli baboons, 56 individuals who were sampled for gut microbiome hundreds of times over a decade. This data allows disentangling ecological dynamics within and across individuals in a way that as far as I know has never been done before. The authors show that ecological relationships among baboon gut bacteria, measure through a correlation based on covariation, are largely universal (similar within and across host individuals) and that the most universally covarying taxa are almost always positively associated with each other. They also compare these results with two sets of human data, finding similar patterns in one human data set but not in the other.

The main aim of this paper is to establish whether gut microbial ecologies are universal across hosts, and this the authors generally show to be true in a thorough and convincing way. However, some re-assessment or re-assurance on the solidity of their chosen method of estimating co-variation would be needed to fully assess the robustness of subsequent results. Specifically, the authors measure the correlation between microbial taxa from data on their abundance co-variation across samples. While necessary steps have been taken to validate the estimates across spurious correlations due to the compositional nature and autocorrelation structures present in the data, I worry that the sparsity of the data might influence the estimation of positive and negative correlations in a slightly different manner. There exist more microbial taxa than samples in the data and some taxa are present in as few as 20% of the samples, meaning that the covariation data will have a large amount of 0-0 pairs. I worry that the abundance of 0-0 pairs in the data might inflate the measures of positive co-variation, making taxa seem highly positively correlated in abundance when they in fact are missing from many samples. Of course, mutual absence is also a form of biologically meaningful covariation but taking the larger number of taxa than samples and the inability of sequencing technology to detect all low-abundance taxa in a sample, I am currently not convinced that all of the 0-0 pairs are modeled as a realistic and balanced way as a continuum of the other non-zero co-variation between taxa in the data. This may become problematic when positive and negative relationships are compared: The authors state that even though most associations between taxa were negative, the most universally correlated taxa pairs (taxa pairs with strongest correlations in abundance both within and between hosts) were enriched in positive associations. It may be possible that this is influenced by the fact that zero inflation in the data lends more weight to positive links than negative links. Whether these universal positive correlations are driven by positive non-zero abundance covariation or just 0-0 links in the data is currently unclear.<br /> Another additional result that would benefit from a more clear context is the result that taxa correlation patterns were more similar between phylogenetically close taxa and between genetically close host individuals. The former notion is to be expected if taxa abundances are driven by environmental (or host physiology-related) selective forces that favor bacteria with similar phenotypes. This yields more support to the idea that covariation is environmentally driven rather than driven by the ecological network of the bacteria themselves, and this could be more clearly emphasized. The latter notion of covariation being more similar in genetically related hosts is currently impossible to disentangle from the notion that covariation patterns were more similar with individuals harboring a more similar baseline microbiome composition since microbiome composition and genetic relatedness were apparently correlated. To understand if something about relatedness was actually influential over correlation pattern similarity, one would need to model that effect on top of the baseline similarity effect. Currently, it is not clear if this was done or not.

The authors also slightly overemphasize the generalizability of their results to humans, taking that only one of the human data sets they compare their results to, shows similar patterns. While they mention that the other human data set (that was not similar in patterns to theirs) was different in some key aspects (sampling frequency was much higher), the other human data set was also dissimilar to the other two (it only contained infants, not adults). Furthermore, to back up the statement that higher sampling frequency would be the reason this data set had dissimilar covariation between taxa, one would need to show that the temporal variation in this data set was different from the baboon one and show that these covariation patterns were sensitive to timescale by subsampling either data to create mock data sets with different sampling frequency and see how this would change the inference of ecological associations.

To the extent that the results are robust, particularly regarding to the main result of the universality of gut microbial ecological associations, the impact of this paper is not small. This question has never been so thoroughly and convincingly addressed, and the results as they stand have the power to strongly influence the expectations of gut microbial ecology across many different systems. Moreover, as the authors point out, evidence for universal gut microbial ecology is important for the future development of probiotics. An important point here, under-emphasized by the authors, is that universal gut microbe ecologies will allow specific interventions that use gut microbe ecology to manipulate emergent community properties of microbiomes to be more beneficial for the host, rather than just designing compositional cocktails that should fit all. In addition to the main finding of this study, the unique data set and the methods developed as part of this study (e.g. the universality score, the enrichment measures, the model of log-ratio dynamics, the assessment of covariation from time-ordered abundance trajectories) will doubtlessly be translatable to many other studies in the future.

Reviewer #2 (Public Review):

The synaptonemal complex (SC) is a ladder-like structure that is assembled between homologous chromosomes during meiotic prophase I. This structure is critical for accurate chromosome segregation as it is required for both crossover formation and regulating crossover frequency. In this study, the composition of the SC throughout meiotic prophase, SC dynamics, and its contribution to crossover formation is compared between male meiosis and female meiosis using C. elegans. Although the SC is found in both sexes, many aspects of meiosis, including recombination initiation and formation, differ between sexes. Whether sex-specific differences extend to the SC and how this influences recombination events has not been investigated. The authors use fluorescently-tagged SC central region proteins (SYP-2 and SYP-3) to quantify the amount of SC protein accumulation per nucleus. The data indicate that the composition of the SC is dynamic throughout the meiotic prophase with sexually dimorphic properties. In addition, by examining and quantifying the number of proteins that mark different recombination intermediates, the authors found that not only does the SC regulate different aspects of recombination, but the regulation is sex-specific. Overall, the assays and quantification in this manuscript are of high quality.

Overall, the manuscript is largely descriptive and doesn't test possible mechanisms behind the observed sex-specific differences. However, this study is of high interest as these sexually dimorphic phenotypes have not been previously studied. The data presented in this paper set a nice foundation for future work. The manuscript is mostly well-written and the data is presented well but lacks explanations for some of the observed phenotypes. Some minor textual revisions would provide insights into some of the male-specific phenotypes that were noted without explanation (e.g. Why might SYP-3 be more dynamic in early pachytene in spermatocytes?). In addition, the introduction could be revised to provide a more coherent flow and to highlight the significance of sexual dimorphic aspects of meiosis.

Reviewer #2 (Public Review):

The study by Rossi et al. is focused on the role of the SASP factor BAFF as a key regulator of senescent cell biology. Using both in vivo and in vitro studies, the authors show that BAFF, particularly in the monocytic cell line THP-1, is a type I interferon-induced gene. The authors further showed, using both proteomics, transcriptomics, and genetic studies that while BAFF does not play a role in the cell viability or cell cycle arrest of senescent cells, BAFF does regulate other aspects of senescent cell Biology. This includes SA-B-GAL activity and inflammatory gene expression of multiple SASP genes. Lastly, the authors demonstrate that via potential autocrine/paracrine signaling mechanisms BAFF can likely bind to multiple BAFF receptors upregulated in senescent cells, and affect both the p53 and NF-kB pathways to control inflammatory gene expression.

In summary, we find the manuscript to be both well written and organized, and a nice study on the role of BAFF as a key regulator of senescent cell biology. We believe this finding will be of significant interest to both the senescent cell field and the aging field in general.

Reviewer #2 (Public Review):

In this work, the authors present a high-resolution cryo-EM structure of mitochondrial complex I, which was isolated from the model protostomian Drosophila melanogaster. Although multiple structures of related complexes have been published earlier, this system is particularly interesting as it seems not to adopt a so-called off-pathway "deactive" (D) state in contrast to the complex from Deuterostomia (including mammals) and therefore may provide novel mechanistic insights into complex I. The work is interesting, as it provides a novel contribution to the current discussion about the assignment of structural conformations to states in the catalytic cycle and/or in the active/deactive state transition of the complex.

Reviewer #2 (Public Review):

In this study, Labuz and collaborators characterize the impact of burn injury on the T cell populations of the human skin. The authors use multiparametric flow cytometry and single-cell transcriptomics to analyze the numbers and the transcriptional profile of conventional and unconventional T cell populations in samples collected from patients with acute burn injury, late burn injury, and without burn injury. Their results show that burn injury disturbs the balance of T cell subtypes by increasing the percentage of CD4 T cells and decreasing the percentage of CD8 T cells. Both CD4 and CD8 T cells in the burn tissue presented lower expression of CD69 and higher expression of CD38, IFN-gamma, and TNF-alpha. The percentage of gamma delta T cells and MAIT cells positive for TNF-alpha and IFN-gamma also increased in the burn tissue. The authors then use single-cell RNA sequencing to gain further insights into how burn injury impacts the overall functions of skin T cells. This unbiased transcriptional profiling confirmed their previous observations that both conventional and unconventional T cells in the skin are replaced by new clusters that express lower levels of "tissue-resident" signature genes such as CD69 and higher levels of homing markers such as SELL and S1PR1. CD8 T cells of the burn skin samples show a clear reduction in the expression of cytotoxic molecules such as GZMK, GZMH, and GNLY, and this contrasts with the upregulation of cytotoxic molecules that are observed in the populations of unconventional T cell populations.

This is a relatively simple and descriptive work that will likely be an important resource for future studies investigating the role of T cell responses in skin wound healing and the maintenance of skin barrier function against pathogens following burn injury. A broader and more unbiased analysis of scRNA-seq data is necessary to better understand the biological processes and cellular responses that are being affected by the transcriptional changes observed in each T cell population as well as the possible implications of their findings.

Reviewer #2 (Public Review):

With warming, fishes are generally expected to grow faster to smaller adult body sizes, as described by the temperature-size rule and other similar theories. However, the generality of this shrinking and the patterns among age classes within a species remain major research questions made all the more urgent by the rapid warming faced by many aquatic ecosystems. In this manuscript, the authors take advantage of an artificially heated ecosystem to investigate the impacts of warming on an unharvested population of fish and investigate patterns of growth, size structure, and mortality in an unexploited fish population. Surprisingly, while faster growth rates in juveniles are demonstrated, as would be expected, adult size remains higher in the heated habitat compared to a nearby non-heated habitat. This unexpected result will be of broad interest.

Strengths

The semi-natural experiment provided by the artificial warming from the power plant is a very nice design. While it is not the only place this type of study could be conducted, this system seems to have an unusually high degree of heating, that fact and the unexpected results make for a very interesting study that should be of broad interest. The study is also presented in a clear and concise manuscript and the conclusions are well-supported.

Weaknesses

In certain sections, it seems like the paper would benefit from a more thorough consideration of alternative explanations for the higher body size in the warmed population, like the release from density dependence or altered prey availability, and how those alternative explanations do or do not fit with the result that mortality was higher for the heated population. The consideration of mortality is a strength of the paper, but this result and how it fits with the result that heated adults did not shrink could be discussed in greater depth. It is unfortunate that factors other than the heat that might influence mortality, like predation rates, remain unknown in this system, but then they are rarely well understood in real-world settings like whole ecosystems.

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.

!- David Hume : book 1 and 2 - book 1 explains what persons are - book 2 explains that persons don't have selves

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):

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).