Reviewer #2 (Public Review):

Tejeda Muñoz et al. investigate the intersection of Wnt signaling, macropinocytosis, lysosomes, focal adhesions and membrane trafficking in embryogenesis and cancer. Following up on their previous papers, the authors present evidence that PMA enhances Wnt signaling and embryonic patterning through macropinocytosis. Strikingly, PMA and Wnt ligand act synergistically to trigger macropinocytosis in fibroblasts. Proteins that are associated with the endo-lysosomal pathway and Wnt signaling are co-increased in colorectal cancer samples, consistent with their pro-tumorigenic action. The function of macropinocytosis is not well understood in most physiological contexts, and its role in Wnt signaling is intriguing. The authors use a wide range of models - Xenopus embryos, cancer cells in culture and in xenografts and patient samples to investigate several endolysosomal processes that appear to act upstream or downstream of Wnt. This broad approach has the downside that results are often validated only in a subset of biological systems and that experiments tend to lack of mechanistic depth. The connections between PMA, Wnt signaling, Rac stabilization, FAK signaling and macropinocytosis remain unclear. Nevertheless, the results provide intriguing insights into a novel connection of the tumor promoting agent PMA and Wnt signaling in development and cancer.

The authors demonstrate striking, additive effects of Wnt3a and PMA in inducing macropinocytosis in 3T3 cells (Fig. 1 K-P). In the APC-mutant colorectal cancer line SW480, the authors show that PMA treatment increases macropinocytosis (Fig. S1). While these data provide additional confirmation that PMA can trigger macropinocytosis, they do not address the role of Wnt signaling directly. This could be done by restoring APC function in SW480 cells, or by ectopically activating Wnt signaling in a CRC cell line that lacks activating mutations in the Wnt pathway. These experiments would help to strengthen the cancer angle and validate the connection between Wnt signaling and PMA in macropinocytosis induction in additional cell lines.

The authors conclude that PMA enhances Wnt signaling based on experiments in Xenopus embryos where co-treatment with PMA and the Wnt activator LiCl increases Wnt target gene expression. This is an interesting observation, but large parts of the paper focus on mammalian cells / cancer cells. It would be important to demonstrate the ability of PMA to enhance Wnt signaling in these contexts as well.

Reviewer #2 (Public Review):

Members of the EphB family of tyrosine kinase receptors are involved in a multitude of diverse cellular functions, ranging from the control of axon growth to angiogenesis and synaptic plasticity. In order to provide these diverse functions, it is expected that these receptors interact in a cell-type specific manner with a diverse variety of downstream signalling molecules.

The authors have used proteomics approaches to characterise some of these molecules in further detail. This molecule, myc-binding protein 2 (MYCBP2) is also known as highwire, has been identified in the context of establishment of neural connectivity. Another molecule coming up on this screen was identified as FBXO45.

The authors use classical methods of co-IP to show a kinase-independent binding of MYCBP2 to EphB2. They further showed that FBXO45 within a ternary complex increased the stability of the EphB2/MYCBP2 complex.

To define the interacting domains, they used clearly designed swapping experiments to show that the extracellular and transmembrane domains are necessary and sufficient for the formation of the ternary complex.

Using a cellular contraction assay, the authors showed the necessity of MYCBP2 in mediating the cytoskeletal response of EphB2 forward signalling. Furthermore, they used the technically challenging stripe assay of alternating lanes of ephrinB-Fc and Fc to show that also in this migration-based essay MYCBP2 is required for EphB mediated differential migration pattern.

MYCBP2 in addition is necessary to stabilize EphB2, that is in the absence of MYCBP2, EphB2 is degraded in the lysosomal pathway.

Interestingly, the third protein in this complex, Fbxo45, was further characterized by overexpression of the domain of MYCBP2, known to interact with Fbxo45. Here the authors showed that this approach led to the disruption of the EphB2 / MYCBP2 complex, and also abolished the ephrinB mediated activation of EphB2 receptors and their differential outgrowth on ephrinB2-Fc / Fc stripes.

Finally, the authors demonstrated an in vivo function of this complex using another model system, C elegans where they were able to show a genetic interaction.

Data show in a nice set of experiments a novel level of EphB2 forward signalling where a ternary complex of this receptor with multifunctional MYCBP2 and Fbxo45 controls the activity of EphB2, allowing a further complex regulation of this important receptors. Additionally, the authors challenge pre-existing concepts of the function of MYCBP2 which might open up novel ways to think about this protein.<br /> Of interest is this work also in terms of development of the retinotectal projection in zebrafish where MYCBP2/highwire plays a crucial role, and thus might lead to a better understanding of patterning along the DV axis, for which it is known that EphB family members are crucial.

Overall, the experiments are classical experiments of co-immunoprecipitations, swapping experiments, collapse assays, and stripe assays which all are well carried out and are convincing.

Reviewer #2 (Public Review):

This manuscript presents a comprehensive investigation into the role of condensin complexes in telomere segregation in fission yeast. The authors employ chromatin immunoprecipitation analysis to demonstrate the enrichment of condensin at telomeres during anaphase. They then use condensin conditional mutants to confirm that this complex plays a crucial role in sister telomere disjunction. Interestingly, they show that condensin role in telomere disjunction is unlikely related to catenation removal but rather related to the organization of telomeres in cis and/or the elimination of structural constraints or proteins that hinder separation.

The authors also investigate the regulation of condensin localization to telomeres and reveal the involvement of the shelterin subunit Taz1 in promoting condensin's association with telomeres while demonstrating that the chromatin remodeler Mit1 prevents excessive loading of condensin onto telomeres. Finally, they show that cohesin acts as a negative regulator of telomere separation, counteracting the positive effects of condensin.

Overall, the manuscript is well-executed, and the authors provide sufficient supporting evidence for their claims. There are a couple of aspects that arise from this study that when fully elucidated will lead to mechanistic understanding of important biological processes. For instance, the exact mechanism by which Taz1 affects condensin loading or the mechanistic link between cohesin and condensin, especially in the context of their opposing roles, are exciting prospects for the future and it is possible that future work within the context of telomeres might provide valuable insights to these questions .

Reviewer #2 (Public Review):

Summary: Maksimova, Ojavee, and colleagues extend two of their methods, BayesW and BayesRR-RC to be used as mixed-model association methods by combining them with a similar approach as in step 2 of REGENIE. BayesW handles time-to-event data whereas BayesRR-RC works for case-control phenotypes. They provide UKBB results for 11 cancers and replicate findings and assess predictions in the Estonian biobank.

Strengths: Age-of-onset is becoming more and more available, and developing methods that make the best use of this additional information is valuable.

Weaknesses: In this work, there is (for now) limited validation of results and comparison with other existing methods.

Reviewer #2 (Public Review):

Summary:<br /> The authors characterized the antigenicity of N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 using ferret and mice immune sera. Four antigenic groups were identified, which correlated with their respective phylogenic/ genetic groups. Among 102 amino acids differed by the 44 selected N2 proteins, the authors identified residues that differentiate the antigenicity of the four groups and constructed a machine-learning model that provides antigenic distance estimation. Three recent A(H3N2) vaccine strains were tested in the model but there was no experimental data to confirm the model prediction results.

Strengths:<br /> This study used N2 protein of 44 selected A(H3N2) influenza A viruses isolated from 2009-2017 and generated corresponding panels of ferret and mouse sera to react with the selected strains. The amount of experimental data for N2 antigenicity characterization is large enough for model building.

Weaknesses:<br /> The main weakness is that the strategy of selecting 44 A(H3N2) viruses from 2009-2017 was not explained. It is not clear if they represent the overall genetic diversity of human A(H3N2) viruses circulating during this time. A comprehensive N2 phylogenetic tree of human A(H3N2) viruses from 2009-2017, with the selected 44 strains labeled in the tree, would be helpful to assess the representativeness of the strains included in the study. The second weakness is the use of double-immune ferret sera (post-infection plus immunization with recombinant NA protein) or mouse sera (immunized twice with recombinant NA protein) to characterize the antigenicity of the selected A(H3N2) viruses. Conventionally, NA antigenicity is characterized using ferret sera after a single infection. Repeated influenza exposure in ferrets has been shown to enhance antibody binding affinity and may affect the cross-reactivity to heterologous strains (PMID: 29672713). The increased cross-reactivity is supported by the NAI titers shown in Table S3, as many of the double immune ferret sera showed the highest reactivity not against its own homologous virus but to heterologous strains. Although the authors used the post-infection ferret sera to characterize 5 viruses (Figure 2, Figure Supplement 4), the patterns did not correlate well. If the authors repeat the NA antigenic analysis using the post-infection ferret sera with lower cross-reactivity, will the authors be able to identify more antigenic groups instead of 4 groups? Another weakness is that the authors used the newly constructed model to predict the antigenic distance of three recent A(H3N2) viruses but there is no experimental data to validate their prediction (eg. if these viruses are indeed antigenically deviating from group 2 strains as concluded by the authors).

Reviewer #2 (Public Review):

Summary:<br /> The authors in this study previously reported that BYL719, an inhibitor of PI3Kα, suppressed heterotopic ossification in mice model of a human genetic disease, fibrodysplasia ossificans progressive, which is caused by the activation of mutant ACVR1/R206H by Activin A. The aim of this study is to identify the mechanism of BYL719 for the inhibition of heterotopic ossification. They found that BYL719 suppressed heterotopic ossification in two ways: one is to inhibit the specification of precursor cells for chondrogenic and osteogenic differentiation and the other is to suppress the activation of inflammatory cells.

Strengths:<br /> This study is based on the authors' previous reports and the experimental procedures including the animal model are established. In addition, to confirm the role of PI3Kα, the authors used the conditional knock-out mice of the subunit of PI3Kα. They clearly demonstrated the evidence indicating that the targets of PI3Kα are not members of TGFBR by a newly established experimental method.

Weaknesses:<br /> Overall, the presented data were closely related to those previously published by the authors' group or others, and there were very few new findings.<br /> Heterotopic ossification in the mice model was not stable and was inappropriate for scientific evaluation.<br /> The method for chondrogenic differentiation was not appropriate, and the scientific evidence of successful differentiation was lacking.<br /> The design of the gene expression profile comparison was not appropriate and failed to obtain the data for the main aim of this study.<br /> The experiments of inflammatory cells were performed in cell lines without ACVR1/R206H mutation, and therefore the obtained data were not precisely related to the inflammation in FOP.

Reviewer #2 (Public Review):

Summary: The authors aimed to describe the effect of different temperature and precipitation regimes on microbial growth responses in an alpine grassland ecosystem using quantitative 18O stable isotope probing. It was found that all climate manipulations had negative effects on microbial growth, and that single-factor manipulations exerted larger negative effects as compared to combined-factor manipulations. The degree of antagonism between factors was analyzed in detail, as well as the differential effect of these divergent antagonistic responses on microbial taxa that incorporated the isotope. Finally, a hypothetical functional profiling was performed based on taxonomic affiliations. This work gives additional evidence that altered warming and precipitation regimes negatively impact microbial growth.

Strengths: A long term experiment with a thorough experimental design in apparently field conditions is a plus for this work, making the results potentially generalisable to the alpine grassland ecosystem. Also, the implementation of a qSIP approach to determine microbial growth ensures that only active members of the community are assessed. Finally, particular attention was given to the interaction between factors and a robust approach was implemented to quantify the weight of the combined-factor manipulations on microbial growth.

Weaknesses: The methodology does not mention whether the samples taken for the incubations were rhizosphere soil, bulk soil or a mix between both type of soils. If the samples were taken from rhizosphere soil, I wonder how the plants were affected by the infrared heaters and if the resulting shadow (also in the controls with dummy heaters) had an effect on the plants and the root exudates of the parcels as compared to plants outside the blocks? If the samples were bulk soil, are the results generalisable for a grassland ecosystem? In my opinion, it is needed to add more info on the origin of the soil samples and how these were taken.

The qSIP calculations reported in the methodology for this work are rather superficial and the reader must be experienced in this technique to understand how the incorporators were identified and their growth quantified. For instance, the GC content of taxa was calculated for reads clustered in OTUs, and it is not discussed in the text the validity of such approach working at genus level.

The selection of V4-V5 region over V3-V4 region to quantify the number of copies of the 16S rRNA gene should be substantiated in the text. Classic works determined one decade ago that primer pairs that amplify V3-V4 are most suitable to assess soil bacterial communities. Hungate et al. (2015), worked with the V3-V4 region when establishing the qSIP method. Maybe the number of unassigned OTUs is related with the selection of this region.

Report of preprocessing and processing of the sequences does not comply state of the art standards. More info on how the sequences were handled is needed, taking into account that a significant part of the manuscript relies on taxonomic classification of such sequences. Also, an OTU approach for an almost species-dependent analysis (GC contents) should be replaced or complemented with an ASV or subOTUs approach, using denoisers such as DADA2 or deblur. Usage of functional prediction tools underestimates gene frequencies, including those related with biogeochemical significance for soil-carbon and nitrogen cycling.

Reviewer #2 (Public Review):

This study connects prior findings on MicroRNA15/16 and Malat1 to demonstrate a functional interaction that is consequential for T cell activation and cell fate.

The study uses mice (Malat1scr/scr) with a precise genetic modification of Malat1 to specifically excise the sites of interaction with the microRNA, but sparing all other sequences, and mice with T-cell specific deletion of miR-15/16. The effects of genetic modification on in vivo T-cell responses are detected using specific mutations and shown to be T-cell intrinsic.

It is not known where in the cell the consequential interactions between MicroRNA15/16 and Malat1 take place. The authors depict in the graphical abstract Malat1 to be a nuclear lncRNA. Malat 1 is very abundant, but it is unclear if it can shuttle between the nucleus and cytoplasm. As the authors discuss future work defining where in the cell the relevant interactions take place will be important.

In addition to showing physiological phenotypic effects, the mouse models prove to be very helpful when the effects measured are small and sometimes hard to quantitate in the context of considerable variation between biological replicates (for example the results in Figure 4D).

The impact of the genetic modification on the CD28-IL2- Bcl2 axis is quantitatively small at the level of expression of individual proteins and there are likely to be additional components to this circuitry.

Reviewer #2 (Public Review):

Summary:<br /> Bian et al studied creatine (Cr) in the context of central nervous system (CNS) function. They detected Cr in synaptic vesicles purified from mouse brains with anti-Synaptophysin using capillary electrophoresis-mass spectrometry. Cr levels in the synaptic vesicle fraction was reduced in mice lacking the Cr synthetase AGAT, or the Cr transporter SLC6A8. They provide evidence for Cr release within several minutes after treating brain slices with KCl. This KCl-induced Cr release was partially calcium dependent and was attenuated in slices obtained from AGAT and SLC6A8 mutant mice. Cr application also decreased the excitability of cortical pyramidal cells in one third of the cells tested. Finally, they provide evidence for SLC6A8-dependent Cr uptake into synaptosomes, and ATP-dependent Cr loading into synaptic vesicles. Based on these data, the authors propose that Cr may act as neurotransmitter in the CNS.

Strengths:<br /> 1. A major strength of the paper is the broad spectrum of tools used to investigate Cr.<br /> 2. The study provides evidence that Cr is present in/loaded into synaptic vesicles.

Weaknesses:<br /> 1. There is no significant decrease in Cr content pulled down by anti-Syp in AGAT-/- mice when normalized to IgG controls. Hence, blocking AGAT activity/Cr synthesis does not affect Cr levels in the synaptic vesicle fraction, arguing against a Cr enrichment.<br /> 2. There is no difference in KCl-induced Cr release between SLC6A8-/Y and SLC6A8+/Y when normalizing the data to the respective controls. Thus, the data are not consistent with the idea that depolarization-induced Cr release requires SLC6A8.<br /> 3. The rationale of grouping the excitability data into responders and non-responders is not convincing because the threshold of 10% decrease in AP rate is arbitrary. The data do therefore not support the conclusion that Cr reduces neuronal excitability.

DOI: 10.1016/j.cub.2023.08.037

Resource: (ZFIN Cat# ZDB-ALT-141023-2,RRID:ZFIN_ZDB-ALT-141023-2)

Curator: @scibot

SciCrunch record: RRID:ZFIN_ZDB-ALT-141023-2

What is this?

Is that really true? Can dependency refer to a person or thing which depends on something/someone else?? I'm only used to it the other way.

"demands context" :)

Reviewer #2 (Public Review):

Summary:

This study takes a new approach to studying the role of corticofugal projections from auditory cortex to inferior colliculus. The authors performed two-photon imaging of cortico-recipient IC neurons during a click detection task in mice with and without lesions of auditory cortex. In both groups of animals, they observed similar task performance and relatively small differences in the encoding of task-response variables in the IC population. They conclude that non-cortical inputs to the IC provide can substantial task-related modulation, at least when AC is absent.

Strengths:

This study provides valuable new insight into big and challenging questions around top-down modulation of activity in the IC. The approach here is novel and appears to have been executed thoughtfully. Thus, it should be of interest to the community.

Weaknesses:

There are, however, substantial concerns about the interpretation of the findings and limitations to the current analysis. In particular, Analysis of single unit activity is absent, making interpretation of population clusters and decoding less interpretable. These concerns should be addressed to make sure that the results can be interpreted clearly in an active field that already contains a number of confusing and possibly contradictory findings.

Reviewer #2 (Public Review):

Extracellular vesicles have recently gained significant attention across a wide variety of fields, and they have therefore been implicated in numerous physiological and pathophysiological processes. When such a discovery and an explosion of interest occur in science, there is often much excitement and hope for answers to mechanisms that have remained elusive and poorly understood. Unfortunately, there is an equal amount of hype and overstatement that may also be put forth in the name of "impact", but this temptation must be avoided so that scientists and the broader public are not misled by overreaching interpretations and statements that lack rigorous and fully convincing evidence.

The study presented by Kapustin et al. is certainly intriguing and timely, and it offers an interesting working hypothesis for the fields of extracellular vesicles and vascular biology to consider. The authors do a reasonable job at detecting these small extracellular vesicles, though some aspects of data presentation are missing such as full Western blots with accompanying size markers for the viewer to more fully appreciate that data and comparisons being made (see Figures 1 and 7).

Much of the imaging data from cell-based experiments is strong and conducted with many cutting-edge tools and approaches. That said, the static images and the dynamic imaging fall short of being fully convincing that the small extracellular vesicles found in the neighboring extracellular matrix are indeed being deposited there via the smooth muscle cell filopodia. Many of the lines of evidence presented suggest that this could occur, but alternative hypotheses also exist that were not fully ruled out, such as the ECM-deposited vesicles were secreted more from the soma and/or the lamellipodia that are also emitted and retracted from the cells. In particular, the authors show very nice dynamic imaging (Supplementary Figure S2A and Supplemental Video S1) that is interpreted as "extracellular vesicles being released from the cell" and these are seen as "bursts" of fluorescent signal; however, none of these appear to occur in filopodia as they appear within the cell proper (a "burst" of signal vs. a more intense "streak" of signal), which would be a stronger and more consistent observation predicted by the working model proposed by the authors.

Imaging of related human samples is certainly a strength of the paper, and the authors are commended for attempting to connect the findings from their cell culture experiments to an important clinical scenario. However, the marker selected for marking extracellular vesicles is CD81, which has been described as present on the endothelium of atherosclerotic plaques with a proposed role in the recruitment of monocytes into diseased arteries (Rohlena et al. Cardiovasc Res 2009). More data should address this potentially confounding interpretation of the signals presented in images within Figure 4.

On a conceptual level, the idea that the small extracellular vesicles contain Type VI Collagen, and this element of their cargo is modulating smooth muscle cell migration, is an intriguing aspect of the authors' working model. Nevertheless, the evidence supporting this potential mechanism does not quite fit together as presented. It is not entirely clear how the collagen VI within the vesicles is somehow accessed by the smooth muscle cell filopodia during migration. Are the vesicles lysed open once on the extracellular matrix? If so, what is the proposed mechanism for that to occur? If not, how are the adhesion molecules on the smooth muscle cell surface engaging the collagen VI fibers that are contained within the vesicles? This aspect of the model does not quite fit together with the proposed mechanism and may be an interesting speculative interpretation, warranting further investigation, but it should not be considered a strong conclusion with sufficient convincing data supporting this idea.

On a technical level, some of the statistical analysis is not readily understood from the data presented. It is very much appreciated that the authors show many of the graphs with technical and biological replicate values in addition to the means and standard deviations (though this is not clearly stated in all figure legends). However, in figures such as Figure 5, there are bars shown and indicated to be different by statistical comparison (see panel B in Figure 5). It is not clear how the values for Group 1 (no FN, no 3-OMS, no sEV) are statistically different (denoted by three asterisks but no p value provided in the legend) than Group 3 (no FN, 3-OMS added, no sEV), when their means and standard deviations appear almost identical. If this is an oversight, this needs to be corrected. If this is truly the outcome, further explanation is warranted. A higher level of transparency in such instances would certainly go a long way in helping address the current crisis of mistrust within the scientific community and at the interface with society at-large.

Reviewer #2 (Public Review):

Summary:<br /> In this work, Hu and colleagues investigate telomerase-independent survival in Saccharomyces cerevisiae strains engineered to have different chromosome numbers. The authors describe the molecular patterns of survival that change with fewer chromosomes and that differ from the well-described canonical Type I and Type II, including chromosome circularization and other atypical outcomes. They then take advantage of the strain with 3 chromosomes to examine the effect of deleting all the subtelomeric elements, called X and Y'. For most of the tested phenotypes, they find no significant effect of the absence of X- and Y'-element, and show that they are not essential for survivor formation. They speculate that X- and Y'-elements are remnants of ancient telomere maintenance mechanisms.

Strengths:<br /> This work advances our understanding of the telomerase-independent strategies available to the cell by altering the structure of the genome and of the subtelomeres, a feat that was enabled by the set of strains they engineered previously. By using strains with non-standard genome structures, several alternative survival mechanisms are uncovered, revealing the diversity and plasticity of telomere maintenance mechanisms. Overall, the conclusions are well supported by the data, with adequate sample sizes for investigating survivors. The molecular analyses mostly based on Southern blots are also very well-conducted.

Weaknesses:<br /> The qualification of survivor types mostly relies on molecular patterns in Southern blots. While this is a valid method for a standard strain, it might be more difficult to apply to the strains used in this study. For example, in SY8, SY11 and SY12, the telomere signal at 1-1.2 kb can be very faint due to the small number of terminal Y' elements left. As another example, for the Y'-less strain, it might seem obvious that no Type I survivor can emerge given that Y' amplification is a signature of Type I, but maybe Type-I-specific molecular mechanisms might still be used. To reinforce the characterization of survivor types, an analysis of the genetic requirements for Type I and Type II survivors (e.g. RAD51, RAD54, RAD59, RAD50) could complement the molecular characterization in specific result sections.

In the title, the abstract and throughout the discussion, the authors chose to focus on the effect of X- and Y'-element deletion on different phenotypes and on survivor formation, as the main message to convey. While it is a legitimate and interesting message, other important results of this work might benefit from more spotlight. Namely, the observation that strains with different chromosome numbers show different survivor patterns and that several survival strategies beyond Type I and II exist and can reach substantial frequencies depending on the chromosomal context.

In SY12 strain, while X- and Y'-elements are not essential for survivor emergence, they do modulate the frequency of each type of survivors, with more chromosome circularization events observed for SY12Y∆, SY12XY∆ and SY12XY∆+Y strains. This result should be stated and discussed, maybe alongside the change in survivor patterns in the other SY strains, to more accurately assess the roles of these subtelomeric elements.

Reviewer #2 (Public Review):

Summary:<br /> This paper further investigates the role of self-assembly of ice-binding bacterial proteins in promoting ice-nucleation. For the P. borealis Ice Nucleating Protein (PbINP) studied here, earlier work had already determined clearly distinct roles for different subdomains of the protein in determining activity. Key players are the water-organizing loops (WO-loops) of the central beta-solenoid structure and a set of non-water-organizing C-terminal loops, called the R-loops in view of characteristically located arginines. Previous mutation studies (using nucleation activity as a read-out) had already suggested the R-loops interact with the WO loops, to cause self-assembly of PbINP, which in turn was thought to lead to enhanced ice-nucleating activity. In this paper, the activities of additional mutants are studied, and a bioinformatics analysis on the statistics of the number of WO- and R-loops is presented for a wide range of bacterial ice-nucleating proteins, and additional electron-microscopy results are presented on fibrils formed by the non-mutated PbINP in E coli lysates.

Strengths:<br /> -A very complete set of additional mutants is investigated to further strengthen the earlier hypothesis.<br /> -A nice bioinformatics analysis that underscores that the hypothesis should apply not only to PbINP but to a wide range of (related) bacterial ice-nucleating proteins.<br /> -Convincing data that PbINP overexpressed in E coli forms fibrils (electron microscopy on E coli lysates).

Weaknesses:<br /> -The new data is interesting and further strengthens the hypotheses put forward in the earlier work. However, just as in the earlier work, the proof for the link between self-assembly and ice-nucleation remains indirect. Assembly into fibrils is shown for E coli lysates expressing non-mutated pbINP, hence it is indeed clear that pbINP self-associates. It is not shown however that the mutations that lead to loss of ice-nucleating activity also lead to loss of self-assembly. A more quantitative or additional self-assembly assay could shine light on this, either in the present or in future studies.

-Also the "working model" for the self-assembly of the fibers remains not more than that, just as in the earlier papers, since the mutation-activity relationship does not contain enough information to build a good structural model. Again, a better model would require different kinds of experiments, that yield more detailed structural data on the fibrils.

Reviewer #2 (Public Review):

This study aims to investigate the mediatory role of intestinal ILC3-derived IL-22 in intermittent fasting-elicited metabolic benefits.

Strengths:<br /> The observation of induction of IL-22 production by intestinal ILC3 is significant, and the scRNAseq provides new information into intestine-resident immune cell profiling in response to repeated fasting and refeeding.

Weaknesses:<br /> The experimental design for some studies needs to be improved to enhance the rigor of the overall study. There is a lack of direct evidence showing that the metabolically beneficial effects of IF are mediated by intestinal ILC3 and their derived IL-22. The mechanism by which IL-22 induces a thermogenic program is unknown. The browning effect induced by IF may involve constitutive activation of lipolysis, which was not considered.

Reviewer #2 (Public Review):

In this manuscript, the authors used an original empirical design to test if somatic mutation rates are different depending on the plant growth rates. They detected somatic mutations along the growth axes of four trees - two individuals per species for two dipterocarp tree species growing at different rates. They found here that plant somatic mutations are accumulated are a relatively constant rate per year in the two species, suggesting that somatic mutation rates correlate with time rather than with growth, i.e. the number of cell divisions. The authors then suggest that this result is consistent with a low relative contribution of DNA replication errors (referred to as α in the manuscript) to the somatic mutation rates as compared to the other sources of mutations (β). Given that plants - in particular, trees - are generally assumed to deviate from the August Weismann's theory (a part of the somatic variation is expected to be transmitted to the next generation), this work could be of interest for a large readership interested by mutation rates as a whole, since it has implications also for heritable mutation rates too. In addition, even if this is not discussed, the putatively low contribution of DNA replication errors could help to understand the apparent paradox associated to trees. Indeed, trees exhibit clear signatures of lower molecular evolution (Lanfear et al. 2013), therefore suggesting lower mutation rates per unit of time. Trees could partly keep somatic mutations under control thanks to a long-term evolution towards low α values, resulting in low α/β ratios as compared to short-lived species. I therefore consider that the paper tackles a fundamental albeit complex question in the field.

Overall, I consider that the authors should clearly indicate the weaknesses of the studies. For instance, because of the bioinformatic tools used, they have reasonably detected a small part of the somatic mutations, those that have reached a high allele frequency in tissues. Mutation counts are known to be highly dependent on the experimental design and the methods used. Consequently, (i) this should be explicit and (ii) a particular effort should be made to demonstrate that the observed differences in mutation counts are robust to the potential experimental biases. This is important since, empirically, we know how mutation counts can vary depending on the experimental designs. For instance, a difference of an order of magnitude has been observed between the two papers focusing on oaks (Schmid-Siegert et al. 2017 and Plomion et al. 2018) and this difference is now known to be due to the differences in the experimental designs, in particular the sequencing effort (Schmitt et al. 2022).

Having said that, my overall opinion is that (i) the authors have worked on an interesting design and generated unique data, (ii) the results are probably robust to some biases and therefore strong enough (but see my comments regarding possible improvements), (iii) the interpretations are reasonable and (iv) the discussion regarding the source of somatic mutations is valuable (even if I also made some suggestions here also).

Reviewer #2 (Public Review):

The authors of this paper use a "digital twin" computational model of electrophysiology to investigate the pathology of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) in several patients undergoing Electro-Physiological Studies (EPS) to treat Ventricular Tachycardias (VTs). The digital twin computational models are customised to the individual patient in two ways. Firstly, information on the patient's heart geometry and muscle/fibrous structure is extracted from Late Gadolium-Enhanced Magnetic Resonance Image (LGE-MRI) scans. Secondly, information from the patient's genotype is used to decide the particular electrophysiological cell model to use in the computational model. The two patient genotypes investigated include a Gene Ellusive (GE) group characterised by abnormal fibrous but normal cell electrical physiology and a palakophilin-2 (PKP2) group in which patients have abnormal fibrotic remodelling and distorted electrical conduction. The computational model predicts the locations and pathways of re-entrant circuits that cause VT. The model results are compared to previous recordings of induced VTs obtained from EPS studies.

The paper is very well written, and the modelling study is well thought out and thorough and represents an exemplar in the field. The major strengths of the paper are the use of a personalised patient model (geometry, fibrous structure and genotype) in a clinically relevant setting. Such a comprehensive personal model puts this paper at the forefront of such models in the field. The main weaknesses of the paper are more of a reflection on what is required for creating such models than on the study itself. As the authors acknowledge, the number of patients in each group is small. Additional patients would allow for statistical significance to be investigated.

The paper's authors set out to demonstrate the use of a "digital twin" computational model in the clinical setting of ARVC. The main findings of the paper were threefold. Firstly, the locations of VTs could be accurately predicted. There was a difference in the abnormal fibrous structure between the two genotype groups. Finally, there was an interplay between the fibrous structure of the heart and the cellular electrophysiology in that the fibrous remodelling was responsible for VTs in the GE group, but in the PKP2 group VTs were caused by slowed electrical conduction and altered restitution. The study successfully met the aims of the paper.

The major impact of the paper will be in demonstrating that a personalised computational model can a) be developed from available measurements (albeit at the high end of what would normally be measured clinically) and b) generate accurate results that may prove helpful in a clinical setting. Another impact is the finding in the paper that the cause of VTs may be different for the two genotypes investigated. The different interplay between fibrous and electrophysiology suggested by the modelling results may provide insights into different treatments for the different genotypes of the pathology. The authors use open-source software and have deposited all non-confidential data in publically available repositories.

Reviewer #2 (Public Review):

In the article "Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli" the authors discovered that the aging process correlates with lower cellular levels of ribosomes in Escherichia coli. The article is well-written and easy to follow and understand. The experiments are conducted rigorously with the appropriate controls. However, it is not novel and exhaustive enough. In particular, the causes and effects of this spatial and temporal distribution of ribosomes have not been investigated. What happens when this distribution is perturbed? Does stress influence this distribution? What is the biological significance of this distribution? These are examples of questions that should be addressed in order to broaden the interest of the paper.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Gewering and coworkers is an elegant mechanistic investigation of the mammalian multidrug transporter Pgp. I will not elaborate on the significance of this protein except to point out its clinical involvement in cancer resistance to chemotherapy.

Strengths:<br /> The strengths of the investigation are partly in the combination of sophisticated chemical synthesis, state-of-the-art cryoEM in a well-established biochemical context. What is more exciting is the tackling of a long-standing question in the field: namely how do drugs make their way through the structure to be exported across the membrane? Unfortunately, the field has been stuck in hand waving model based on structures that in the outward-facing conformations are devoid of substrates. The work challenges the dogma that emerged from this hand-waving model and presents an alternative model that appears to be supported by the data.

Weaknesses:<br /> There is much to like about the experimental work here but I am less sanguine on the interpretation. The main idea is to covalently link via disulfide bonds a model tripeptide substrate under different conditions that mimic transport and then image the resulting conformations. The choice of the Pgp cysteine mutants here is critical but also poses questions regarding the interpretation. What seems to be missing, or not reported, is a series of control experiments for further cysteine mutations.

Reviewer #2 (Public Review):

In this paper, Phan et al. investigate the properties of human HP1 paralogs, their interactions and abilities to undergo liquid-liquid phase separation. For this, they use a coarse-grained computational approach (validated with additional all-atom simulations) which allows to explore complex mixtures. Matching (wet-lab) experimental results, HP1 beta (HP1b) exhibits different properties from HP1 alpha and gamma (HP1a,g), in that it does not phase separate. Using domain switch experiments, the authors determine that the more negatively charged hinge in HP1b, compared to HP1a and HP1g, is mainly responsible for this effect. Exploring heterotypic complexes, mixtures between HP1 subtypes and DNA, the authors further show that HP1a can serve as a scaffold for HP1b to enter into condensed phases and that DNA can further stabilize phase separated compartments. Most interestingly, they show that a multicomponent mixture containing DNA, and HP1a and HP1b generates spatial separation between the HP1 paralogs: due to increased negative charge of DNA within the condensates, HP1b is pushed out and accumulates at the phase boundary. This represents an example how complex assemblies could form in the cell.<br /> Overall, this is purely computational work, which however builds on extensive experimental results (including from the authors). The methods showcase how coarse-grained models can be employed to generate and test hypotheses how proteins can condense. Applied to HP1 proteins, the results from this tour-de-force study are consistent and convincing, within the experimental constraints. Moreover, they generate further models to test experimentally, in particular in light of multicomponent mixtures.

There are, of course, some limitations to these models.

First, the CG models employed probably will not be able to pick up more complex structure-driven interactions (i.e. specific binding of a peptide in a protein cleft, including defined H-bonds, or induced structural elements). Some of those interactions (i.e. beyond charge-charge or hydrophobics) may also play a role in HP1, and might be ignored here. There is also the question of specificity, i.e. how can diverse phases coexist in cells, when the only parameters are charge and hydrophobicity? Does the arrangement of charges in the NTD, hinges and CTDs matter or are only the average properties important?

Second, the authors fix CSD-CSD dimers, whereas these interactions are expected to be quite dynamic. In the particular example of HP1 proteins, having dimerization equilibria may change the behavior of complex mixtures significantly, e.g. in view of the proposed accumulation of HP1b at a phase boundary. This point would warrant more discussion in the paper. Moreover, the biological plausibility of such a behavior would be interesting. Is there any experimental data supporting such assemblies?

Reviewer #2 (Public Review):

Summary:<br /> The existence of hox gene complexes conserved in animals with bilateral symmetry and in which the genes are arranged along the chromosome in the same order as the structures they specify along the anteroposterior axis of organisms is one of the most spectacular discoveries of recent developmental biology. In brief, homeotic mutations lead to the transformation of a given body segment of the fly into a copy of the next adjacent segment. For the sake of understanding the main observation of this work, it is important to know that in loss-of-function (LOF) alleles, a given segment develops like a copy of the segment immediately anterior to it, and in gain-of-function mutations (GOF), the affected segment develops like a copy of the immediately posterior segment. Over the last 30 years the molecular lesions associated with GOF alleles led to a model where the sequential activation of the hox genes along the chromosome result from the sequential opening of chromosomal domains. Most of these GOF alleles turned out to be deletions of boundary elements (BE) that define the extent of the segment-specific regulatory domains. The fruit fly Drosophila is a highly specialized insect with a very rapid mode of segmentation. Furthermore, the hox clusters in this lineage have split. Given these specificities it is legitimate to question whether the regulatory landscape of the BX-C we know of in D.melanogaster is the result of very high specialization in this lineage, or whether it reflects a more ancestral organization. In this article, the authors address this question by analyzing the continuous hox cluster in butterflies. They focus on the intergenic region between the Antennapedia and the Ubx gene, where the split occurred in D.melanogaster. Hi-C and ATAC-seq data suggest the existence of a boundary element between 2 Topologically-Associated-Domain (TAD) which is also characterized by the presence of CTCF binding sites. Butterflies have 2 pairs of wings originating from T2 (forewing) specified by Antp and T3 specified by Ubx (hindwing). Remarkably, CRISPR mutational perturbation of this boundary leads to the hatching of butterflies with homeotic clones of cells with hindwings identities in the forewing (a posteriorly oriented homeotic transformation). In agreement with this phenotype, the authors observe ectopic expression of Ubx in these clones of cells. In other words, CRISPR mutagenesis of this BE region identified by molecular tool give rise to homeotic transformations directed towards more posterior segment as the boundary mutations that had been 1st identified on the basis of their posterior oriented homeotic transformation in Drosophila. None of the mutant clones they observed affect the hindwing, indicating that their scheme did not affect the nearby Ubx transcription unit. This is reassuring and important first evidence that some of the regulatory paradigms that have been proposed in fruit flies are also at work in the common ancestor to Drosophilae and Lepideptora.

Given the large size of the Ubx transcription unit and its associated regulatory regions it is not surprising that the authors have identified ncRNA that are conserved in 4 species of Nymphalinae butterflies, some of which also present in D.melanogaster. Attempts to target the promoters by CRISPR give rise to clones of cells in both forewings and hindwings, suggesting the generation of regulatory mutations associated with both LOF and GOF transformations. The presence of clones with dual homeosis suggests the targeting of Ubx activator and repression CRMs. Unfortunately, these experiments do not allow us to make further conclusions on the role of these ncRNA or in the identification of specific regulatory elements. To the opinion of this reviewer, some recent papers addressing the role that these ncRNA may play in boundary function should be taken with caution, and evidence that ncRNA(s) regulate boundaries in the BX-C in a WT context is still lacking.

Strengths:<br /> The convincing GOF phenotype resulting from the targeting of the Antp-Ubx_BE.

Weaknesses:<br /> The lack of comparisons with the equivalent phenotypes obtained in D.melanogaster with for example the Fub mutation.

Reviewer #2 (Public Review):

Summary:<br /> Y., Tao E., et al. used multiscale MD simulations to show that PI(4,5)P2 binds stably to an inactivated state of Nav channels at a conserved site within the DIV S4-S5 linker, which couples the voltage sensing domain (VSD) to the pore. The authors hypothesized that PI(4,5)P2 prolongs inactivation by binding to the same site where the C-terminal tail is proposed to bind during recovery from inactivation. They convincingly showed that PI(4,5)P2 reduces the mobility of both the DIV S4-S5 linker and the DIII-IV linker, thus slowing the conformational changes required for the channel to recover to the resting state. They also conducted MD simulations to show that phosphoinositides bind to VSD gating charges in the resting state of Nav channels. These interactions may anchor VDS at the resting state and impede its activation. Their results provide a mechanism by which phosphoinositides alter the voltage dependence of activation and the recovery rate from inactivation, an important step for developing novel therapies to treat Nav-related diseases. However, the study is incomplete and lacks the expected confirmatory studies which are relevant to such proposals.

Strengths:<br /> The authors identified a novel binding between phosphoinositides and the VSD of Nav and showed that the strength of this interaction is state-dependent. Based on their work, the affinity of PIPs to the inactivated state is higher than the resting state. This work will help pave the way for designing novel therapeutics that may help relieve pain or treat diseases like arrhythmia, which may result from a leftward shift of the channel's activation.

Weaknesses:<br /> However, the study lacks the expected confirmatory studies which are relevant to such proposals. For example, one would expect that the authors would mutate the positive residues that they claim to make interactions with phosphoinositides to show that there are much fewer interactions once they make these mutations. Another point is that the authors found that the main interaction site of PIPs with Nav1.4 is the VSD-DIV and DIII-DIV linker, an interaction that is expected to delay fast inactivation if it happens at the resting state. The authors should make a resting state model of the Nav1.4 channel to explain the recent experimental data showing that PIP2 delays the activation of Nav1.4, with almost no effect on the voltage dependence of fast inactivation.

Major concern:<br /> 1- Lack of confirmatory experiments, e.g., mutating the positive residues that show a high affinity towards PIPs to a neutral and negative residue and assessing the effect of mutagenesis on binding.<br /> 2- Nav1.4 is the only channel that has been studied in terms of the effect of PIPs on it, therefore the authors should build a resting state model of Nav1.4 and study the effect of PIPs on it.<br /> Minor points:

There are a lot of incorrect statements in many areas, e.g., "These diseases 335 are associated with accelerated rates of channel recovery from inactivation, consistent with our observations that an interaction between PI(4,5)P2 and the residue corresponding to R1469 in other Nav 337 subtypes could be important for prolonging the fast-inactivated state." Prolonging the fast inactivated state would actually reduce recovery from inactivation and not accelerate it.

Reviewer #2 (Public Review):

In this study the authors investigate functional associations made by transcription factor ZMYM2 with chromatin regulators, and the impact of perturbing these complexes on the transcriptome of the U2OS cell line. They focus on validating two novel chromatin-templated interactions: with TRIM28/KAP1 and with ADNP, concluding that via these distinct chromatin regulators, ZMYM2 contributes to transcriptional control of LTR and SINE retrotransposons, respectively.

Strengths of the study:

-The co-localization of ZMYM2 with ADNP and TRIM28 is validated through RIME, ChIP-seq and co-IP. Since TRIM28 is a highly abundant nuclear protein, the use of multiple methods is important to add confidence in particular for the novel (SUMO-dependent interaction identified between ZMYM2 and TRIM28. That TRIM28 pulls down less of the ZMYM2-SIM mutant is reassuring.

-It is good that uniquely-mapped reads are used in the ChIP-seq analysis given the interest in repetitive elements. Likewise, though the RT-qPCR data in Fig 6 should be complemented by analysis of the RNA-seq data that the authors already have, it seems that the primers are carefully designed such that a single retrotransposon copy is amplified.

-The paper is generally written very clearly, the experiments well done and the different datasets appear to be robust.

Weaknesses of the study:

-The transcriptional response using bulk RNA-seq in ZMYM2-depleted cells remains gene-centric despite the title of the paper being about TE transcription. In fact, the only panels about TE transcription are the RT-qPCR data in Fig 6D, F. During the revision the authors said that their RNA-seq data is unfortunately too shallow to retrieve TEs. Fair enough - however, it remains the case that the central claim is control of TE transcription by ZMYM2. Thus, without additional transcriptomic analysis we are left with only a few qPCRs, even if they are nicely done! Perhaps the title could be modified a bit in that case?

-The mechanism by which ZMYM2 and TRIM28 work together does remain a mystery. Following review the authors performed TRIM28 ChIP on ZMYM2-depleted cells, but identified no changes over three transposons. It remains unclear if H3K9me3 levels are altered.

Reviewer #2 (Public Review):

The authors aimed to investigate the microbiota present in the fallopian tubes (FT) and its potential association with ovarian cancer (OC). They collected swabs intraoperatively from the FT and other surgical sites as controls to profile the FT microbiota and assess its relationship with OC.<br /> They observed a clear shift in the FT microbiota of OC patients compared to non-cancer patients. Specifically, the FT of OC patients had more types of bacteria typically found in the gastrointestinal tract and the mouth. In contrast, vaginal bacterial species were more prevalent in non-cancer patients. Serous carcinoma, the most common OC subtype, showed a higher prevalence of almost all FT bacterial species compared to other OC subtypes.

The strengths of the study include its large sample size, rigorous collection methods, and use of controls to identify the possible contaminants. Additionally, the study employed advanced sequencing techniques for microbiota analysis. However, there are some weaknesses to consider. The study relied on swabs collected intraoperatively, which may not fully represent the microbiota in the FT during normal physiological conditions. The study also did not establish causality between the identified bacteria and OC but rather demonstrated an association. Regardless, the findings are important and these questions need to be addressed by future studies. A few additions in data representation and analysis are instead recommended.

Overall, the authors achieved their aims of identifying the FT microbiota and assessing its relationship with OC. The results support the conclusion that there is a clear shift in the FT microbiota in OC patients, paving the way for further investigations into the role of these bacteria in the pathogenesis of ovarian cancer.

The identification of specific bacterial species associated with OC could contribute to the development of novel diagnostic and therapeutic approaches. The study design and the data generated here can be valuable to the research community studying the microbiota and its impact on cancer development. However, further research is needed to validate these findings and elucidate the underlying mechanisms linking the FT microbiota shift and OC.

Reviewer #2 (Public Review):

The pear psylla Cacopsylla chinensis has two morphologically different forms, winter- and summer-forms depending on the temperatures. The authors provided solid data showing that the cold sensor CcTRPM is responsible for switching summer- to winter forms, which is in turn regulated by the miRNA miR-252. This finding is interesting and novel.

Reviewer #2 (Public Review):

Summary:

Anil Verma et al. have performed prime-boost HIV vaccination to enhance HIV-1 Env antibodies in the rhesus macaques model. The authors used two different adjuvants, a cationic liposome-based adjuvant (CAF01) and a monophosphoryl lipid A (MPLA)+QS-21 adjuvant. They demonstrated that these two adjuvants promote different transcriptomes in the GC-TFH subsets. The MPLA+QS-21 adjuvant induces abundant GC TFH1 cells expressing CXCR3 at first priming, while the CAF01 adjuvant predominantly induced GC TFH1/17 cells co-expressing CXCR3 and CCR6. Both adjuvants initiate comparable Env antibody responses. However, MPLA+QS-21 shows more significant IgG1 antibodies binding to gp140 even after 30 weeks.

The enhancement of memory responses by MPLA+QS-21 consistently associates with the emergence of GC TFH1 cells that preferentially produce IFN-γ.

Strengths:

The strength of this manuscript is that all experiments have been done in the rhesus macaque model with great care. This manuscript beautifully indicated that MPLA+QS-21 would be a promising adjuvant to induce the memory B cell response in the HIV vaccine.

Weaknesses:

The authors did not provide clear evidence to indicate the functional relevance of GC TFH1 in IgG1 class-switch and B cell memory responses.

Reviewer #2 (Public Review):

In this manuscript, the authors use a number of approaches to show that a posterior subset of cholinergic neurons located in the nucleus basalis of myenert (NBV) and substantia innominata (SIp) region of the basal forebrain, and projecting to the basolateral nucleus of the amygdala (BLA), are part of the conditioned threat-memory engram that is associated with the defensive freezing response. The paper clearly demonstrates that NBM/SIp inputs to the BLA are selectively activated during cued-associative learning which is then reactivated upon cued memory retrieval, leading to cholinergic release in the BLA. Likewise, the authors also use in-vitro recordings of cue-activated vs inactivated cholinergic cells to demonstrate that activated neurons are more excitable (firing more action potentials) and with a lower rheobase. Collectively, these data support the notion that NBM/SIp is part of the memory engram for the learned association. To better characterize the importance of the cholinergic input to the amygdala for behavior, the authors delineate the segregation of function in cholinergic input to the BLA along the rostrocaudal axis. They show that inputs to the BLA originating from the more anterior NBM/SIa region mediate innate anxiety behavior whereas the more posterior cholinergic inputs are involved in associative fear conditioning.

Overall, these findings make a significant contribution to our understanding of how the cholinergic system partakes in mediating cue-specific and non-specific emotional behavior. There are several group comparisons and statistical analyses that could strengthen the claims made in the paper.

1) Throughout the paper, the authors use comparisons of cell activity between groups to address questions about projection-specific and cue-specific cell activation and reactivation. However, statistical comparisons are sometimes done between biological replicates (e.g. Fig. 5A), whereas a lot of them are done between technical replicates (e.g. Fig. 2B, 5B, 7B). Adding statistics that compare biological replicates would help increase confidence in the results.

2) To demonstrate engram-like specificity, in figure 4C the authors show fold change in cholinergic reactivation in low and high responders (animals that show low and high defensive freezing upon cue presentation) as normalized by cell activity while sitting in the home cage. However, the authors also collected a better control for this comparison, which is shown in figure S4, where the animals were exposed to an unconditioned tone cue. Comparing fold change to this tone-alone condition would provide stronger evidence for the authors' point, as this would directly compare the specificity of cholinergic reactivation to a conditioned vs an unconditioned cue. A discussion of the same comparison is relevant for figure 2 (and is shown in figure S4) but is not mentioned in the text.

3) The significant correlation between cue-evoked percent change in defensive freezing from pretone and fold change in cholinergic cell activity relative to the home cage that is shown in figure 4D is somewhat confusing. Is the correlation considering all the points shown (high and low responders as depicted by black and grey points)? It's first reported as one correlation but then is discussed as two populations that have different results. Further, is the average amount of reactivation for the home-cage controls used here the same denominator for each reported animal? Similarly to the point above, a correlation looking at fold change from tone-alone would also be helpful to determine the degree to which cholinergic reactivation is specific to threat-association learning versus the more general attentional component that this system is known for.

4) The compelling argument of this paper is that the authors are separating out the general attention role typically attributed to the cholinergic system from a more specific, engram-based role. Given the importance of untangling this, it would useful to see the recorded traces and behavioral scoring for the data shown in figure S2B. For example, was the higher slope in the recorded cholinergic response during unconditioned tone 1 also accompanied by an increase in freezing, which later went away with additional non-reinforced tones? Given that the animals were not habituated to tones (according to the Methods), this activity could be related to a habituation/general attention response, which may then be weaker than the learned response.

Reviewer #2 (Public Review):

The manuscript by Gubensak et al describes the structure of the periplasmic domains of the Vibrio cholerae proteins ToxR and ToxS. These proteins control virulence in V. cholerae, however they are conserved throughout the Vibrionaceae and are important for controlling outermembrane porin expression, as well as other factors. ToxR specifically has been the focus of intense study for several decades, and this work is a nice contribution to a deeper understanding of exactly how this protein works. The authors show by a variety of biochemical techniques, including Xray crystallography, that the ToxR and ToxS periplasmic domains fold into a structure that forms a binding pocket in ToxS to allow binding of bile salts, a known modulator of ToxR activity. The detailed structural studies show how the interaction between the two proteins is critical to alter the co-structure of the two proteins and form the binding pocket.

The study was very straightforward, and the biochemical techniques were extensive and convincing. These studies add a nice rigorous insight into bile modulation of signal transduction in the Vibrios.

Reviewer #2 (Public Review):

This paper is an attempt to extend or augment muscle synergy and motor primitive ideas with task measures. The authors idea is to use information metrics (mutual information, co-information) in 'synergy' constraint creation that includes task information directly. By using task related information and muscle information sources and then sparsification, the methods construct task relevant network communities among muscles, together with task redundant communities, and task irrelevant communities. This process of creating network communities may then constrain and help to guide subsequent synergy identification using the authors published sNM3F algorithm to detect spatial and temporal synergies.

The revised paper is much clearer and examples are helpful in various ways. However, figure 2 as presented does not convincingly show why task muscle mutual information helps in separating synergies, though it is helpful in defining the various network communities used in the toy example.

The impact of the information theoretic constraints developed as network communities on subsequent synergy separation are posited to be benign and to improve over other methods (e.g., NNMF). However, not fully addressed are the possible impacts of the methods on compositionality links with physiological bases, and the possibility remains of the methods sometimes instead leading to modules that represent more descriptive ML frameworks that may not support physiological work easily. Accordingly, there is a caveat. This is recognized and acknowledged by the authors in their rebuttal of the prior review. It will remain for other work to explore this issue, likely through testing on detailed high degree of freedom artificial neuromechanical models and tasks. This possible issue with the strategy here likely needs to be fully acknowledged in the paper.

The approach of the methods seeks to identify task relevant coordinative couplings. This is a meta problem for more classical synergy analyses. Classical analyses seek compositional elements stable across tasks. These elements may then be explored in causal experiments and generative simulations of coupling and control strategies. However, task-based understanding of synergy roles and functional uses is significant and is clearly likely to be aided by methods in this study.

Information based separation has been used in muscle synergy analyses using infomax ICA, which is information based at core. Though linear mixing of sources is assumed in ICA, minimized mutual information among source (synergy) drives is the basis of the separation and detects low variance synergy contributions (e.g., see Yang, Logan, Giszter, 2019). In the work in this paper, instead, mutual information approaches are used to cluster muscles and task features into network communities preceding the SNM3F algorithm use for separation, rather than using minimized information in separation. This contrast of an accretive or agglomerative mutual information strategy here used to cluster into networks, versus a minimizing mutual information source separation used in infomax ICA epitomizes a key difference in approach here.

Physiological causal testing of synergy ideas is neglected in the literature reviews in the paper. Although these are only in animal work (Hart and Giszter, 2010; Takei and Seki, 2017), the clear connection of muscle synergy analysis choices to physiology is important, and eventually these issues need to be better managed and understood in relation to the new methods proposed here, even if not in this paper.

Analyses of synergies using the methods the paper has proposed will likely be very much dependent on the number and quality of task variables included and how these are managed, and the impacts of these on the ensuing sparsification and network communities used prior to SNM3F. The authors acknowledge this in their response. This caveat should likely be made very explicit in the paper.

It would be useful in the future to explore the approach described with a range of simulated data to better understand the caveats, and optimizations for best practices in this approach.

Reviewer #2 (Public Review):

Summary:<br /> The objective of this study was to further our understanding of the brain mechanisms associated with facial expressions of pain. To achieve this, participants' facial expressions and brain activity were recorded while they received noxious heat stimulation. The authors then used a decoding approach to predict facial expressions from functional magnetic resonance imaging (fMRI) data. They found a distinctive brain signature for pain facial expressions. This signature had minimal overlap with brain signatures reflecting other components of pain phenomenology, such as signatures reflecting subjective pain intensity or negative effects.

Strength:<br /> The manuscript is clearly written. The authors used a rigorous approach involving multivariate brain decoding to predict the occurrence and intensity of pain facial expressions during noxious heat stimulation. The analyses seem solid and well-conducted. I think that this is an important study of fundamental and clinical relevance.

Weaknesses:<br /> Despite those major strengths, I felt that the authors did not suffciently explain their own interpretation of the significance of the findings. What does it mean, according to them, that the brain signature associated with facial expressions of pain shows a minimal overlap with other pain-related brain signatures?

A few questions also arose during my reading.

Question 1: Is the FEPS really specific to pain expressions? Is it possible that the signature includes a facial expression signal that would be shared with facial expressions of other emotions, especially since it involves socio-affective regulation processes? Perhaps this question should be discussed as a limit of the study?

Question 2: All AUs are combined together in a composite score for the regression. Given that the authors have other work showing that different AUs may be associated with different components of pain (affective vs. sensory), is it possible that combining all AUs together has decreased the correlation with other pain signatures? Or that the FEPS actually reflects multiple independent signatures?

Question 3: Is facial expressivity constant throughout the experiment? Is it possible that the expressivity changes between the beginning and the end of the experiment? For instance, if there is a habituation, or if the participant is less surprised by the pain, or in contrast if they get tired by the end of the experiment and do not inhibit their expression as much as they did at the beginning. If facial expressivity changes, this could perhaps affect the correlation with the pain ratings and/or with the brain signatures; perhaps time (trial number) could be added as one of the variables in the model to address this question.

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors use the tractable Drosophila embryonic/larval motor circuit to determine how manipulations of activity during a critical period (CP) modify the circuit in ways that persist into later developmental stages. Previously, this group demonstrated that manipulations to the aCC/MN-Ib neuron in embryonic stages enhance (or can rescue) susceptibility to seizures at later larval stages. Here, the authors demonstrate that following enhanced excitatory drive (by PTX feeding), the aCC neuron acquires increased sensitivity to cholinergic excitatory transmission, presumably due to increased postsynaptic receptor abundance and/or sensitivity, although this is not clarified. Although locomotion is not altered at later developmental larval stages, the authors suggest there is reduced "robustness" to induced seizures. The second part of the study then goes on to enhance inhibition during the CP in an attempt to counteract the enhanced excitation, and show that many aspects of the CP plasticity are rescued. The authors conclude that "average" E/I activity is integrated during the CP to determine the excitability of the mature locomotor network.

Overall, this study provides compelling mechanistic insight into how a final motor output neuron changes in response to enhanced excitatory drive during a CP to change the functionality of the circuit at later mature developmental stages. The first part of this study is strong, clearly showing the changes in the aCC neuron that result from enhanced excitatory input. This includes very nice electrophysiology and imaging data that assess synaptic function and structure onto aCC neurons from pre-motor inputs resulting from PTX exposure during development. However, the later experiments in Figures 6 and 7 designed to counteract the CP plasticity are somewhat difficult to interpret. In particular, the specificity of the manipulations of the ch neuron intended to counteract the CP plasticity is unclear, given the complexities of how these changes impact the excitability of all neurons during development. It is clear that CP plasticity is largely rescued in later stages, but it is hard to know if downstream or secondary adaptations may be masking the PTX-induced plasticity normally observed. Nonetheless, this study provides an important advance in our understanding of what parameters change during CPs to calibrate network dynamics at later developmental stages.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Jain et al explore whether increasing adult neurogenesis is protective against status epilepticus (SE) and the development of spontaneous recurrent seizures (chronic epilepsy) in a mouse pilocarpine model of TLE. The authors increase adult neurogenesis via conditional deletion of Bax, a pro-apoptotic gene, in Nestin-CreERT2Baxfl/fl mice. Cre- littermates are used as controls for comparisons. In addition to characterizing seizure phenotypes, the authors also compare the abundance of hilar ectopic granule cells, mossy cells, hilar SOM interneurons, and the degree of neuronal damage between mice with increased neurogenesis (Cre+) vs Cre- controls. The authors find less severe SE and a reduction in chronic seizures in female mice with pre-insult increased adult-born neurons. Immunolabeling experiments show these females also have preservation of hilar mossy cells and somatostatin interneurons, suggesting the pre-insult increase in adult neurogenesis is protective.

Strengths:<br /> 1. The finding that female mice with increased neurogenesis at the time of pilocarpine exposure have fewer seizures despite having increased hilar ectopic granule cells is very interesting.<br /> 2. The work builds nicely on the group's prior studies.<br /> 3. Apparent sex differences are a potentially important finding.<br /> 4, The immunohistochemistry data are compelling.<br /> 5. Good controls for EEG electrode implantation effects.<br /> 6. Nice analysis of most of the SE EEG data.

Weaknesses:<br /> 1. In addition to the Cre- littermate controls, a no Tamoxifen treatment group is necessary to control for both insertional effects and leaky expression of the Nestin-CreERT2 transgene.

2. The authors suggest sex differences; however, experimental procedures differed between male and female mice (as the authors note). Female mice received diazepam 40 minutes after the first pilocarpine-induced seizure onset, whereas male mice did not receive diazepam until 2 hours post-onset. The former would likely lessen the effects of SE on the female mice. Therefore, sex differences cannot be accurately assessed by comparing these two groups, and instead, should be compared between mice with matching diazepam time courses. Additionally, the authors state that female mice that received diazepam 2 hours post-onset had severe brain damage. This is concerning as it would suggest that SE is more severe in the female than in the male mice.

3. Some sample sizes are low, particularly when sex and genotypes are split (n=3-5), which could cause a type II statistical error.

4. Several figures show a datapoint in the sex and genotype-separated graphs that is missing from the corresponding male and female pooled graphs (Figs. 2C, 2D, 4B).

5. In Suppl Figs. 1B & 1C, subsections 1c and 2c, the EEG trace recording is described as the end of SE; however, SE appears to still be ongoing in these traces in the form of periodic discharges in the EEG.

6. In Results section II.D and associated Fig.3, what the authors refer to as "postictal EEG depression" is more appropriately termed "postictal EEG suppression". Also, postictal EEG suppression has established criteria to define it that should be used. The example traces in Fig. 3A and B should also be expanded to better show this potential phenomenon.

7. In Fig.5D, the area fraction of DCX in Cre+ female mice is comparable to that of Cre- and Cre+ male mice. Is it possible that there is a ceiling effect in DCX expression that may explain why male Cre+ mice do not have a significant increase compared to male Cre- mice?

8. In Suppl. Fig 6, the authors should include DCX immunolabeling quantification from conditional Cre+ male mice used in this study, rather than showing data from a previous publication.

9. In Fig 8, please also include Fluorojade-C staining and quantification for male mice.

10. Page 13: Please specify in the first paragraph of the discussion that findings were specific to female mice with pre-insult increases in adult-born neurogenesis.

Minor:<br /> 11. In Fig. 1 and suppl. figure 1, please clarify whether traces are from male or female mice.

12. Please be consistent with indicating whether immunolabeling images are from female or male mice.

a. Fig 5B images labeled as from "Cre- Females" and "Cre+ Females".

b. Suppl. Fig 8: Images labeled as "Cre- F" and "Cre+ F".

c. Fig 6: sex not specified.

d. Fig. 7: sex only specified in the figure legend.

e. Fig 8: only female mice were included in these experiments, but this is not clear from the figure title or legend.

13. Page 4: the last paragraph of the introduction belongs within the discussion section.

14. Page 6: The sentence "The data are consistent with prior studies..." is unnecessary.

15. Suppl. Fig 6A: Please include representative images of normal condition DCX immunolabeling.

16. In Suppl. Fig 7C, I believe the authors mean "no loss of hilar mossy and SOM cells" instead of "loss of hilar mossy and SOM cells".

Reviewer #2 (Public Review):

Summary:<br /> The present study aims to investigate whether learning about temporal regularities of painful events, i.e. statistical learning can influence pain perception. To this end, sequences of heat pain stimuli with fluctuating intensity are applied to 27 healthy human participants. The participants are asked to provide ratings of perceived as well as predicted pain intensity. Using an advanced modelling strategy, the results reveal that statistical expectations and confidence scale the judgment of pain in sequences of noxious stimuli as predicted by hierarchical Bayesian inference theory.

Strengths:<br /> This is a highly interesting and novel finding with potential implications for the understanding and treatment of chronic pain where pain regulation is deficient. The paradigm is clear, the analysis is state-of-the-art, the results are convincing, and the interpretation is adequate.

Reviewer #2 (Public Review):

Summary:

The goal of this study is to provide a deeper understanding of the roles of syt7 and Doc2 in synaptic vesicle fusion. Depending on the system studied, and the nature of the preparation, it appears that syt7 functions as a sensor for asynchronous release, synaptic facilitation, both processes, or neither. The perspective offered by Chapman, Watanabe, and colleagues varies from those previously published and is therefore novel and interesting. However, the study is also burdened by some weaknesses which should be acknowledged and addressed.

Strengths:

The strengths of the study include the complementary imaging and electrophysiology approaches for assessing the function of syt7, and the use of appropriate knockout lines.

Weaknesses:

First, the manuscript strongly overstates the significance of the EM data which is interesting but not as definitive as the authors would suggest. As a consequence, the conclusion offered by the authors of syt7 "feeding" vesicles to Doc2 for asynchronous release is weakened. Second, it is not clear to this reviewer that the mathematical model is necessary or justified.

Reviewer #2 (Public Review):

The paper nicely demonstrates the extent of the issue with the unreliability of commercial antibodies and describes a highly significant initiative for the robust validation of antibodies and recording this data so that others can benefit. It is a great idea to have all individual antibody characterisation reports available on Zenodo - these reports are comprehensive, clear and available to everyone.

A significant proportion of all life science research conclusions are based on data obtained through the use of antibodies. The quality and specificity of antibodies vary significantly. Until now there has been no uniform generally recognised approach to how to systematically assess and rate antibody specificity and quality. Furthermore, the applications that a particular antibody can be used in including western blot, immunofluorescence or immunoprecipitation are frequently not known. This paper provides important guidelines for how the quality of an antibody should be assessed and recorded and data made freely available via a Zenodo repository. This study will ensure that researchers only use well-validated antibodies for their work. A worrying aspect of this paper is that many poor-quality antibodies that failed validation are reportedly being widely used in the literature. More than 60% of all antibodies recommended for immunofluorescence failed QC. This study will have broad interest. I would recommend that all researchers select their antibodies using the database described in the paper and follow its recommendations for how antibodies should be thoroughly validated before being used in research. Hopefully, other researchers can contribute to this database in the future all widely used antibodies will eventually be well characterized. This should improve the quality and reproducibility of life science research.

Reviewer #2 (Public Review):

Summary:<br /> This work by Cloarec-Ung et al. sets out to uncover strategies that would allow for the efficient and precision editing of primitive human hematopoietic stem and progenitor cells (HSPCs). Such effective editing of HSPCs via homology directed repair has implications for the development of tractable gene therapy approaches for monogenic hematopoietic disorders as well as precise engineering of these cells for clinical regenerative and/or cell therapy strategies. In the setting of experimental hematology, precision introduction of disease relevant mutations would also open the door to more robust disease modeling approaches. It has been recognized that to encourage HDR, NHEJ as the dominant mode of repair in quiescent HSPCs must be inhibited. Testing editing of human cord blood HSPCs the authors first incorporate a prestimulation phase then identify optimal RNP amounts and donor types/amounts using standard editing culture conditions identifying optimal concentrations of AAV and short single-stranded oligonucleotide donors (ssODNs) that yield minimal impacts to cell viability while still enabling heightened integration efficiency. They then demonstrate the superiority of AZD7648, an inhibitor of NHEJ-promoting DNA-PK, in allowing for much increased HDR with toxicities imparted by this compound reduced substantially by siRNAs against p53 (mean targeting efficiencies at 57 and 80% for two different loci). Although AAV offered the highest HDR frequencies, differing from ssODN by a factor by ~2-fold, the authors show that spacer breaking sequence mutations introduced into the ssODN to better mimic the disruption of the spacer sequence provided by the synthetic intron in the AAV backbone yielded ssODN HDR frequencies equal to that attained by AAV. By examining editing efficiency across specific immunophenotypically identified subpopulations they further suggest that editing efficiency with their improved strategy is consistent across stem and early progenitors and use colony assays to quantify an approximate 4-fold drop in total colony numbers but no skewing in the potentiality of progenitors in the edited HSPC pool. Finally, the authors provide a strategy using mutation-introducing AAV mixed with different ratios of silent ssODN repair templates to enable tuning of zygosity in edited CD34+ cells.

Strengths:<br /> The methods are clearly described and the experiments for the most part also appropriately powered. In addition to using state of the art approaches the authors also provided useful insights into optimizing the practicalities of the experimental procedures that will aid bench scientists in effectively carrying out these editing approaches, for example avoiding longer handling times inherent when scaling up to editing over multiple conditions.

The sum of the adjustments to the editing procedure have yielded important advances towards minimizing editing toxicity while maximizing editing efficiency in HSPCs. In particular, the significant increase in HDR facilitated by the authors' described application of AZD7648 and the preservation of a pool of targeted progenitors is encouraging that functionally valuable cell types can be effectively edited.

The discovery of the effectiveness of spacer breaking changes in ssODNs allowing for substantially increased targeting efficiency is a promising advance towards democratizing these editing strategies given the ease of designing and synthesizing ssODNs relative to the production of viral donors.

The ability to zygosity tune was convincingly presented and provides a valuable strategy to modify this HDR procedure towards more accurate disease modelling.

Weaknesses:<br /> Despite providing convincing evidence that functional progenitors can be successfully edited by their procedure, as the authors acknowledge it remains to be verified to what degree the self-renewal capacity and in vivo regenerative potential of the more primitive fractions is maintained with their strategy.

Assessments of the potential for off-target effects via the authors' approach was somewhat cursory and would have benefitted from a more thorough evaluation.

Viability was assessed by live cell counting however given the short-term nature of the editing assay, more sensitive readouts of potentially compromised cell health could have provided a more stringent assessment of how the editing methodology impacted cell fitness.

Reviewer #2 (Public Review):

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

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

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

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Fig. 1/S1. Authors selected a mutant for further study, npr-15, which showed resistance to various pathogens, and less colonization. Data are convincing. Data also suggest that in response to S. aureus, where wt animals exhibit avoidance behavior measured as numbers of animals that move off a focal spot of bugs, the npr-15 mutants do not. The effect was abrogated when a full lawn was used, at least for S. aureus, where there was no place to run. The conclusion is that the NPR-15 mediates behavioral changes resulting in pathogen avoidance.

Comments: There is some variance in lawn occupancy of wt strains between the different trials in WT animals (e.g. in Fig. 1: 25 for wt vs 60% for npr mutant; S1c 5% for wt and 60% for npr mutant). Does this reflect rates of migration or re-occupancy in WT? Does pathogen avoidance persist and/or the rate of avoidance differ in npr mutant worms, and if animals were exposed then re-exposed, could the authors to determine whether a learned avoidance was similarly affected by this mutation by assessing rate changes?

Fig. 2/S2. NPR inhibits expression of immune and aversion pathway genes (ELT-2, HLH-30, PMK-1, and DAF-2/DAF-16). No concerns.

Comment: Is there any difference in gene expression of animals that have migrated off the lawn to those remaining on the lawn (e.g. in partial lawn expts?)

Fig. 3/S3. Let-2RNAi or hlh-30 RNAi abrogates immunity in both WT and npr mutants. Similar effects with mutants. pmk and daf-16 inactivation were without effect.

Comment. No concerns but the P values in the legends are a pain to read. Why not put them in figures as in the above figures.

Fig. 4. Using neuronal and gut specific RNAi, the authors implicate the ASJ neurons in NPR-15 effects (ie in WT animals npr15 RNAi resulted in a pathogen resistance phenotype similar to that of the mutant animals. Specific expression of NPR-15 in the enhanced survival of the npr-15 mutants, an effect rescued by neuronal expression of NPR-15. Using strains lacking particular neurons, they found that strains lacking ASJ- strains phenocopies the npr mutant. Finally, sealing things nicely, they rescued NPR-15 in the mutant on an ASJ-specific Ptrx promoter.

Fig. 5. explores the dependence of pathogen avoidance on ASJ neurons and gut effects. Fig 5 shows that mutation of NPR in ASJ neuron alone phenocopies pathogen avoidance of the global npr mutant, indicating NPR expression in this and only this neurons is required. Fig. 5 also demonstrates that the loss of the ion channel GON-2 phenocopies the npr-15 mutant.

Comments: The authors suggest that the ASJ/NPR15 effect to limit avoidance acts via inhibition of GON-2 in the intestine. The observation that GON-2 inhibition effects on pathogen avoidance occur independently of neurons could suggest that it is a redundant way of accomplishing the same thing, which then makes one ask what the connection exists between the neuron and the gut. The effect of ASJ via NPR on pathogen avoidance is not neuropeptide dependent, which they show. So how does the neuronal-gut communication works. Specific Transmitters... perhaps. Since ASJ neurons control entry into dauer, perhaps isn't surprising that DAF-16 showed up as an NPR-15. induced factor (and dauer worms are resistant to a lot of stressors); that said dauer hormones might be involved as well. Is there any evidence that DAF-16 down-regulates GON-2 expression (see Murphy, Kenyon et al. 2005), and along these lines would GON-2 RNAi work in a DAF-16 mutant? I think addressing these issues are in my view the subject of future studies.

Weaknesses: The paper is solid and elegantly defines the genetic basis of behavioral avoidance via neurons and gut. The neuronal gut connection is shown, but how they are connected remains unsolved. I wouldn't suggest this is a weakness as much as an invitation for future work.

Reviewer #2 (Public Review):

Summary<br /> In this study, single author Jeroen Verharen investigates 500 publicly available peer review documents from 200 neuroscience papers. He uses ChatGPT to examine the sentiment and politeness of each review and performs a series of analyses including scores across reviewers, by field, institution ranking, and author gender. This is an impressive amount of analysis for a single author and uncovers an interesting pattern where female first authors receive consistently less polite reviews compared with male first authors. It is well known that women scientists face systematic discrimination across the field, and consistently in peer review. Using ChatGPT to examine these with a predefined scoring and metric system is novel and an accessible way for others in the future to evaluate these.<br /> Strengths include:<br /> 1) Given the variability in responses from ChatGPT, he pooled two scores for each review and demonstrated significant correlation between these two iterations. He confirmed also reasonable scoring by manipulating reviews. Finally, he compared a small subset (7 papers) to human scorers and again demonstrated correlation with sentiment and politeness.<br /> 2) The figures are consistently well presented and informative. Figure 2C nicely plots the scores with example reviews. The supplementary data are also thoughtful and include combination of first/last author genders. It is interesting that first author female last author male has the lowest score.<br /> 3) A series of detailed analysis including breaking down reviews by subfield (interesting to see the wide range of reviewer sentiment/politeness scores in Computational papers), institution, and author's name and inferred gender using Genderize. The author suggests that peer review to blind the reviewers to authors' gender may be helpful to mitigating the impoliteness seen.<br /> 4) The author has strengthened the analysis in this revision by comparing it to lexicon- and rule-based algorithms TextBlob and VADER.

Weaknesses:<br /> The weaknesses listed in my Public Review of the previous version have been adequately addressed in this revised version, and the article now acknowledges its limitations (ie, it is a pilot, proof-of-concept study, limited to articles about neuroscience). The author proposes further studies and it will be interesting to see the results of these.

Reviewer #2 (Public Review):

Summary:

The goal of the authors in this study is to develop a more reliable approach for quantifying codon usage such that it is more comparable across species. Specifically, the authors wish to estimate the degree of adaptive codon usage, which is potentially a general proxy for the strength of selection at the molecular level. To this end, the authors created the Codon Adaptation Index for Species (CAIS) that controls for differences in amino acid usage and GC% across species. Using their new metric, the authors find a previously unobserved negative correlation between the overall adaptiveness of codon usage and body size across 118 vertebrates. As body size is negatively correlated with effective population size and thus the general strength of natural selection, the negative correlation between CAIS and body size is expected. The authors argue this was previously unobserved due to failures of other popular metrics such as Codon Adaptation Index (CAI) and the Effective Number of Codons (ENC) to adequately control for differences in amino acid usage and GC content across species. Most surprisingly, the authors also find a positive relationship between CAIS and the overall "disorderedness" of a species protein domains. As some of these results are unexpected, which is acknowledged by the authors, I think it would be particularly beneficial to work with some simulated datasets. I think CAIS has the potential to be a valuable tool for those interested in comparing codon adaptation across species in certain situations. However, I have certain theoretical concerns about CAIS as a direct proxy for the efficiency of selection when the mutation bias changes across species.

Strengths:

(1) I appreciate that the authors recognize the potential issues of comparing CAI when amino acid usage varies and correct for this in CAIS. I think this is sometimes an under-appreciated point in the codon usage literature, as CAI is a relative measure of codon usage bias (i.e. only considers synonyms). However, the strength of natural selection on codon usage can potentially vary across amino acids, such that comparing mean CAI between protein regions with different amino acid biases may result in spurious signals of statistical significance (see Cope et al. Biochemica et Biophysica Acta - Biomembranes 2018 for a clear example of this).

(2) The authors present numerous analysis using both ENC and mean CAI as a comparison to CAIS, helping given a sense of how CAIS corrects for some of the issues with these other metrics. I also enjoyed that they examined the previously unobserved relationship between codon usage bias and body size, which has bugged me ever since I saw Kessler and Dean 2014. The result comparing protein disorder to CAIS was particularly interesting and unexpected.

(3) The CAIS metric presented here is generally applicable to any species that has an annotated genome with protein-coding sequences.

Weaknesses:

(1) The main weakness of this work is that it lacks simulated data to confirm that it works as expected. This would be particularly useful for assessing the relationship between CAIS and the overall effect of protein structure disorder, which the authors acknowledge is an unexpected result. I think simulations could also allow the authors to assess how their metric performs in situations where mutation bias and natural selection act in the same direction vs. opposite directions. Additionally, although I appreciate their comparisons to ENC and mean CAI, the lack of comparison to other popular codon metrics for calculating the overall adaptiveness of a genome (e.g. dos Reis et al.'s statistic, which is a function of tRNA Adaptation Index (tAI) and ENC) may be more appropriate. Even if results are similar to , CAIS has a noted advantage that it doesn't require identifying tRNA gene copy numbers or abundances, which I think are generally less readily available than genomic GC% and protein-coding sequences.

The authors mention the selection-mutation-drift equilibrium model, which underlies the basic ideas of this work (e.g. higher results in stronger selection on codon usage), but a more in-depth framing of CAIS in terms of this model is not given. I think this could be valuable, particularly in addressing the question "are we really estimating what we think we're estimating?"

Let's take a closer look at the formulation for RSCUS. From here on out, subscripts will only be used to denote the codon and it will be assumed that we are only considering the case of for some species

I think what the authors are attempting to do is "divide out" the effects of mutation bias (as given by , such that only the effects of natural selection remain, i.e. deviations from the expected frequency based on mutation bias alone represent adaptive codon usage. Consider Gilchrist et al. MBE 2015, which says that the expected frequency of codon at selection-mutation-drift equilibrium in gene for an amino acid with synonymous codons is

where is the mutation bias, is the strength of selection scaled by the strength of drift, and is the gene expression level of gene \(g\). In this case, \ and reflect the strength and direction of mutation bias and natural selection relative to a reference codon, for which . Assuming the selection-mutation-drift equilibrium model is generally adequate to model the true codon usage patterns in a genome (as I do and I think the authors do, too), the could be considered the expected observed frequency codon in gene .

Let's re-write the in the form of Gilchrist et al., such that it is a function of mutation bias . For simplicity, we will consider just the two-codon case and assume the amino acid sequence is fixed. Assuming GC% is at equilibrium, the term and can be written as

where is the mutation rate from nucleotides to. As described in Gilchrist et al. MBE 2015 and Shah and Gilchrist PNAS 2011, the mutation bias . This can be expressed in terms of the equilibrium GC content by recognizing that

As we are assuming the amino acid sequence is fixed, the probability of observing a synonymous codon at an amino acid becomes just a Bernoulli process.

If we do this, then

Recall that in the Gilchrist et al. framework, the reference codon has . Thus, we have recovered the Gilchrist et al. model from the formulation of under the assumption that natural selection has no impact on codon usage and codon NNG is the pre-defined reference codon. To see this, plug in 0 for in equation (1).

We can then calculate the expected RSCUS using equation (1) (using notation and equation (6) for the two codon case. For simplicity assume, we are only considering a gene of average expression (defined as . Assume in this case that NNG is the reference codon .

This shows that the expected value of RSCUS for a two-codon amino acid is expected to increase as the strength of selection increases, which is desired. Note that in Gilchrist et al. is formulated in terms of selection against a codon relative to the reference, such that a negative value represents that a codon is favored relative to the reference. If (i.e. selection does not favor either codon), then . Also note that the expected RSCUS does not remain independent of the mutation bias. This means that even if (i.e. the strength of natural selection) does not change between species, changes to the strength and direction of mutation bias across species could impact RSCUS. Assuming my math is right, I think one needs to be cautious when interpreting CAIS as representative of the differences in the efficiency of selection across species except under very particular circumstances. One such case could be when it is known that mutation bias varies little across the species of interest. Looking at the species used in this manuscript, most of them have a GC content ranging around 0.41, so I suspect their results are okay.

Although I have not done so, I am sure this could be extended to the 4 and 6 codon amino acids.

Another minor weakness of this work is that although the method is generally applicable to any species with an annotated genome and the code is publicly available, the code itself contains hard-coded values for GC% and amino acid frequencies across the 118 vertebrates. The lack of a more flexible tool may make it difficult for less computationally-experienced researchers to take advantage of this method.

Reviewer #2 (Public Review):

The manuscript by Escobedo et al. is an interesting investigation addressing the involvement of a lesser-studied brain region/neuron population (SUM glutamate neurons that project to the POA and other places) in active coping and locomotor behavior. The authors present data that this small population of glutamate neurons is an important circuit hub recruited for active coping but not overall locomotion by employing several behavioral tests. The manuscript is straightforward and potentially interesting, but the strength of the evidence and the significance of the paper as a whole is limited due to some lack of rigor with regards to 1) validation and quantification of anatomical tracing data that serve as a basis for the behavioral testing, 2) the use of statistics, 3) sex as a biological variable, 4) genotype differences between experimental and control groups in behavioral tests, and other concerns laid out below.

1) These are very difficult, small brain regions to hit, and it is commendable to take on the circuit under investigation here. However, there is no evidence throughout the manuscript that the authors are reliably hitting the targets and the spread is comparable across experiments, groups, etc., decreasing the significance of the current findings. There are no hit/virus spread maps presented for any data, and the representative images are cropped to avoid showing the brain regions lateral and dorsal to the target regions. In images where you can see the adjacent regions, there appears expression of cell bodies (such as Supp 6B), suggesting a lack of SuM specificity to the injections.

2) In addition, the whole brain tracing is very valuable, but there is very little quantification of the tracing. As the tracing is the first several figures and supp figure and the basis for the interpretation of the behavior results, it is important to understand things including how robust the POA projection is compared to the collateral regions, etc. Just a rep image for each of the first two figures is insufficient, especially given the above issue raised. the combination of validation of the restricted expression of viruses, rep images, and quantified tracing would add rigor that made the behavioral effects have more significance.

For example, in Fig 2, how can one be sure that the nature of the difference between the nonspecific anterograde glutamate neuron tracing and the Sum-POA glutamate neuron tracing is real when there is no quantification or validation of the hits and expression, nor any quantification showing the effects replicate across mice? It could be due to many factors, such as the spread up the tract of the injection in the nonspecific experiment resulting in the labeling of additional regions, etc.

Relatedly, in Supp 4, why isn't C normalized to DAPI, which they show, or area? Similar for G -what is the mcherry coverage/expression, and why isn't Fos normalized to that?

3) The authors state that they use male and female mice, but they do not describe the n's for each experiment or address sex as a biological variable in the design here. As there are baseline sex differences in locomotion, stress responses, etc., these could easily factor into behavioral effects observed here.

4) In a similar vein as the above, the authors appear to use mice of different genotypes (however the exact genotypes and breeding strategy are not described) for their circuit manipulation studies without first validating that baseline behavioral expression, habituation, stress responses are not different. Therefore, it is unclear how to interpret the behavioral effects of circuit manipulation. For example in 7H, what would the VGLUT2-Cre mouse with control virus look like over time? Time is a confound for these behaviors, as mice often habituate to the task, and this varies from genotype to genotype. In Fig 8H, it looks like there may be some baseline differences between genotypes- what is normal food consumption like in these mice compared to each other? Do Cre+ mice just locomote and/or eat less? This issue exists across the figures and is related to issues of statistics, potential genotype differences, and other experimental design issues as described, as well as the question about the possibility of a general locomotor difference (vs only stress-induced). In addition, the authors use a control virus for the control groups in VGAT-Cre manipulation studies but do not explain the reasoning for the difference in approach.

5) The statistics used throughout are inappropriate. The authors use serial Mann-Whitney U tests without a description of data distributions within and across groups. Further, they do not use any overall F tests even though most of the data are presented with more than two bars on the same graph. Stats should be employed according to how the data are presented together on a graph. For example, stats for pre-stim, stim, and post-stim behavior X between Cre+ and Cre- groups should employ something like a two-way repeated measures ANOVA, with post-hoc comparisons following up on those effects and interactions. There are many instances in which one group changes over time or there could be overall main effects of genotype. Not only is serially using Mann-Whitney tests within the same panel misleading and statistically inaccurate, but it cherry-picks the comparisons to be made to avoid more complex results. It is difficult to comprehend the effects of the manipulations presented without more careful consideration of the appropriate options for statistical analysis.

Conceptual:<br /> 6) What does the signal look like at the terminals in the POA? Any suggestion from the data that the projection to the POA is important?

7) Is this distinguishing active coping behavior without a locomotor phenotype? For example, Fig. 5I and other figure panels show a distance effect of stimulation (but see issues raised about the genotype of comparison groups). In addition, locomotor behavior is not included for many behaviors, so it is hard to completely buy the interpretation presented.

8) What is the role of GABA neurons in the SuM and how does this relate to their function and interaction with glutamate neurons? In Supp 8, GABA neuron activation also modulates locomotion and in Fig 7 there is an effect on immobility, so this seems pretty important for the overall interpretation and should probably be mentioned in the abstract.

Questions about figure presentation:<br /> 9) In Fig 3, why are heat maps shown as a single animal for the first couple and a group average for the others? Why is the temporal resolution for J and K different even though the time scale shown is the same? What is the evidence that these signal changes are not due to movement per se?

10) In Fig 4, the authors carefully code various behaviors in mice. While they pick a few and show them as bars, they do not show the distribution of behaviors in Cre- vs Cre+ mice before manipulation (to show they have similar behaviors) or how these behaviors shift categories in each group with stimulation. Which behaviors in each group are shifting to others across the stim and post-stim periods compared to pre-stim?<br /> Of note, issues of statistics, genotype, and SABV are important here. For example, the hint that treading/digging may have a slightly different pre-stim basal expression, it seems important to first evaluate strain and sex differences before interpreting these data.

11) Why do the authors use 10 Hz stimulation primarily? is this a physiologically relevant stim frequency? They show that they get effects with 1 Hz, which can be quite different in terms of plasticity compared to 10 Hz.

12) In Fig 5A-F, it is unclear whether locomotion differences are playing a role. Entrances (which are low for both groups) are shown but distance traveled or velocity are not.

In B, there is no color in the lower left panel. where are these mice spending their time? How is the entirety of the upper left panel brighter than the lower left? If the heat map is based on time distribution during the session, there should be more color in between blue and red in the lower left when you start to lose the red hot spots in the upper left, for example. That is, the mice have to be somewhere in apparatus. If the heat map is based on distance, it would seem the Cre- mice move less during the stim.

13) By starting with 1 hz, are the experimenters inducing LTD in the circuit? what would happen if you stop stimming after the first epoch? Would the behavioral effect continue? What does the heat map for the 1 hz stim look like?

Relatedly, it is a lot of consistent stimulation over time and you likely would get glutamate depletion without a break in the stim for that long.

14) In Fig 6, the authors show that the Cre- mice just don't do the task, so it is unclear what the utility of the rest of the figure is (such as the PR part). Relatedly, the pause is dependent on the activation, so isn't C just the same as D? In G and H, why is a subset of Cre+ mice shown? Why not all mice, including Cre- mice?

15) In Fig 7, what does the GCaMP signal look like if aligned to the onset of immobility? It looks like since the hindpaw swimming is short and seems to precede immobility, and the increase in the signal is ramping up at the onset of hindpaw swimming, it may be that the calcium signal is aligned with the onset of immobility. What does it look like for swimming onset? In I, what is the temporal resolution for the decrease in immobility? Does it start prior to the termination of the stim, or does it require some elapsed time after the termination, etc?

Reviewer #2 (Public Review):

Having previously solved the X-ray crystallographic structure of the polymer adhesin domain (PAD) of PrgB from E. faecalis, the authors looked to build on that work by crystallizing a nearly full-length construct of PrgB. Though they were successful in their crystallization endeavors, the crystal contained only what was previously thought to be two domains with RGD motifs. The authors' high-resolution structure shows that in fact the C-terminal portion of PrgB is made up of four immunoglobulin-like domains. The authors then set out to collect single-particle cryoEM data in a bid to obtain a full-length structure of PrgB, both in the presence and absence of ssDNA. The authors were only able to obtain quite low-resolution data, which they fit their crystal structures into. The authors then used these structures to inform the design of novel deletion mutants and point mutations, as well as to rationalize years of phenotypic data from other published mutants.

The X-ray crystallographic structure is beautiful and in combination with their in vivo data allowed them to propose a model where PrgB positions cells at an appropriate distance for conjugation. The in vivo experiments appear to be done well and the authors' discovery that the Ser-Asn-Glu is not important for generalized aggregation but has an additional yet unknown role in conjugation and biofilm formation is exciting and well supported by their data.

[Editors' note: In response to reviews of a previous version of this manuscript, the authors have carried out additional experiments that have strengthened the already convincing aspects of the work. We commend the authors for responding to questions raised by the reviewers about the inference of interactions of in vivo importance inferred from low-resolution cryo-EM studies by carrying out and reporting on additional experiments that fail to confirm their initial speculative model. The current work is stronger and more convincing as a result.]

Reviewer #2 (Public Review):

This manuscript discusses the posttranscriptional regulation of flagella synthesis in Escherichia coli. The bacterial flagellum is a complex structure that consists of three major domains, and its synthesis is an energy-intensive process that requires extensive use of ribosomes. The flagellar regulon encompasses more than 50 genes, and the genes are activated in a sequential manner to ensure that flagellar components are made in the order in which they are needed. Transcription of the genes is regulated by various factors in response to environmental signals. However, little is known about the posttranscriptional regulation of flagella synthesis. The manuscript describes four UTR-derived sRNAs (UhpU, MotR, FliX, and FlgO) that are controlled by the flagella sigma factor σ28 (fliA) in Escherichia coli. The sRNAs have varied effects on flagellin protein levels, flagella number, and cell motility, and they regulate different aspects of flagella synthesis.<br /> UhpU corresponds to the 3´ UTR of uhpT.

UhpU is transcribed from its own promoter inside the coding sequence of uhpT.

MotR originates from the 5´ UTR of motA. The promoter for motR is within the flhC CDS and is also the promoter of the downstream motAB-cheAW operon.

FliX originates from the 3´ UTR of fliC. Probably processed from parental mRNA.

FlgO originates from the 3´ UTR of flgL. Probably processed from parental mRNA.

This is a very interesting study that shows how sRNA-mediated regulation can create a complex network regulating flagella synthesis. The information is new and gives a fresh outlook at cellular mechanisms of flagellar synthesis.

Reviewer #2 (Public Review):

Summary:<br /> In this paper, the authors induced large doxorubicin-resistant (L-DOXR) cells by generating DOX gradients using their Cancer Drug Resistance Accelerator (CDRA) chip. The L-DOXR cells showed enhanced proliferation rates, migration capacity, and carcinogenesis. Then the authors identified that the chemoresistance of L-DOXR cells is caused by failed epigenetic control of NUPR1/HDAC11 axis.

Strengths:

- Chemoresistant cancer cells were generated using a novel technique and their oncogenic properties were clearly demonstrated using both in vivo and in vitro analysis.<br /> - The mechanisms of chemoresistance of the L-DOXR cells could be elucidated using in vivo chemoresistant xenograft models, an unbiased genome-wide transcriptome analysis, and a patient data/tissue analysis.<br /> - This technique has great capability to be used for understanding the chemoresistant mechanisms of tumor cells.

Reviewer #2 (Public Review):

Summary:

This is a fine work on the development of computational approaches to detect cancer through exosomes. Exosomes are an emerging biomarker resource and have attracted considerable interests in the biomedical field. Kalluri and co-workers collected a large sample pool and used random forest to identify a group of protein markers that are universal to exosomes and to cancer exosomes. The results are very exciting and not only added new knowledge in cancer research but also a new and advanced method to detect cancer. Data was presented very nicely and the manuscript was well written.

Strengths:

Identified new biomarkers for cancer diagnosis via exosomes.<br /> Developed a new method to detect cancer non-invasively.<br /> Results were presented nicely and manuscript were well written.

Weaknesses:

N/A.

Reviewer #2 (Public Review):

Any stimulus that enters the human mind is in one way or another other compressed. A drawing with hundreds of lines might be turned into "picture of a seescape", a complex set of harmonically overlapping sine waves might be turned into "sad piano chord", and a weird set of utterances incomprehensible to most animals could be turned into "someone reading a review aloud" if prior experience permits. Understanding this process is essential to understanding the human mind. Understanding compression is even more critical to understanding working memory that - in its limited capacity - can most profit from compression, abstraction, or chunking.

Here, the authors provide some insight into how a sequence of binary pitch might be compressed during encoding into memory. They use a previously developed method to encapsulate sequences of 16 high and low pitches using a math-like description scheme (Planton et al., 2021). One can think of this scheme as a "language", "a categorization model", or "a process of segmenting patterns", but its central role in the experiment is to derive a 'rough' measure of complexity that is shown to covary with behavioral data, here and in prior work (Planton et al., 2021).

This language seems to be particularly useful in the context of this highly regularized task, where the set of possible sequences is limited to 20 (out of an overall number of 65.536 imaginable sequences). Instead of finding structures in random sequences, subjects can be expected to quickly learn that their task is to detect which particular structure (of a fairly limited class) is to be found in the given sequence. It is unclear whether such a language would also be useful for sequences of more natural stimuli that motivate the authors' research (e.g. syllables, tones, or shapes). What both more natural compression and the compression used in this task have in common is that long-term memory might play an instrumental role during the compression.

Thus, the authors provide clear evidence that these sequences are being compressed and some evidence that the compression used shares some features with the compression model employed, here. The neural data are consistent with this interpretation.

Regardless of our disagreement with the interpretation of the results the authors put forward, we find the research presented here elegantly designed, well grounded in a series of prior work, and inspiring. There is little known about the representation of sequences in memory and during perception and we believe that this work is a notable and helpful addition to our understanding of this question.

Reviewer #2 (Public Review):

Indeed, ENKTL is a rather deadly tumor with unmet medical needs. The work is novel in the sense that they designed and identified a very potent inhibitor homing at CRM1 via a deep-reinforcement learning model to suppress the overactivation of NF-κB signaling, an underlying mechanism of ENKTL pathogenesis. The authors demonstrated that LFS-1107 binds more strongly with CRM1 (approximately 40-fold) as compared to KPT-330, an existing CRM1 inhibitor. Another merit of the small-molecule inhibitor is that LFS-1107 can selectively eliminate ENKTL cells while sparing normal blood cells. Their animal results clearly demonstrated that the small-molecule inhibitor was able to extend mouse survival and eliminate tumor cells considerably. Overall, the manuscript may provide a possible therapeutic strategy to treat ENKTL with a good safety profile. The manuscript is also well-written. The weakness of the manuscript is that some details for the design and evaluation of the small-molecular inhibitor are missing.

Reviewer #2 (Public Review):

Chehade and Gharbawie investigated motor and premotor cortex in macaque monkeys performing grasping and reaching tasks. They used intrinsic signal optical imaging (ISOI) covering an exceedingly large field-of-view extending from the IPS to the PS. They compared reaching and fine/power-grip grasping ISOI maps with "motor" maps which they obtained using extensive intracranial microstimulation. The grasping/reaching-induced activity activated relatively isolated portions of M1 and PMd, and did not cover the entire ICM-induced 'motor' maps of the upper limbs. The authors suggest that small subzones exist in M1 and PMd that are preferentially activated by different types of forelimb actions. In general, the authors address an important topic. The results are not only highly relevant for increasing our basic understanding of the functional architecture of the motor-premotor cortex and how it represents different types of forelimb actions, but also for the development of brain-machine interfaces. These are challenging experiments to perform and add to the existing yet complementary electrophysiology, fMRI, and optical imaging experiments that have been performed on this topic - due to the high sensitivity and large coverage of the particular IOSI methods employed by the authors. The manuscript is generally well written and the analyses seem overall adequate - but see below for some additional analyses that should be done. Although I'm generally enthusiastic about this manuscript, there are two major issues that should be clarified. These major questions relate mainly to potential thresholding issues and clustering issues.

Major:

1) The main claim of the authors is that specific forelimb actions activate only a small fraction of what they call the motor map (i.e., those parts of M1/PMd that evoke muscle contractions upon ICM). The action-related activity is measured by ISOI. When looking a the 'raw' reflectance maps, it is rather clear that relatively wide portions of the exposed cortex are activated by grasping/reaching, especially at later time points after the action. In fact, another reading of the results may be that there are two zones of 'deactivation' that split a large swath of motor-premotor cortex being activated by the grasping/reaching actions. (e.g. at 6 seconds after the cue in Fig 3A, 5A). At first sight, the 'deactivated' regions seem to be located in the cortex representing the trunk/shoulder/face - hence regions not necessarily activated (or only weakly) during the grasping/reaching actions. If true, this means that most of the relevant M1/PMd cortex IS activated during the latter actions - opposing the 'clustering' claims of the authors. This raises the question of whether the 'granularity' claimed by the authors is<br /> a. threshold dependent. In this context, the authors should provide an analysis whereby 'granularity' is shown independent of statistical thresholds of the ISOI maps.<br /> b. dependent on the time-point one assesses the maps. Given the sluggish hemodynamic responses, it is unclear which part of the ISOI maps conveys the most information relative to the cue and arm/hand movements. I suspect that timepoints > 6 s will reveal even larger 'homogeneous' activations compared to the maps < 6s.<br /> In fact, Fig 5F (which is highly thresholded) shows a surprisingly good match between the different forelimb actions, which argues against the existence of small subzones that are preferentially activated by different types of forelimb actions -the main claim of the authors.

2) Related to the previous point, the ROI selections/definitions for the time course analyses seem highly arbitrary. As indicated in the introduction, the clustering hypothesis dictates that "an arm function would be concentrated in subzones of the motor arm zones. Neural activity in adjacent subzones would be tuned for other arm functions." To test this hypothesis directly in a straightforward manner, the authors could use the results from the ICM experiment to construct independent ROIs and to evaluate the ISOI responses for the different actions. In that case, the authors could do a straightforward ANOVA (if the data permits parametric analyses) with ROI, action, and time point (and possibly subject) as factors.

Reviewer #2 (Public Review):

In this article, Daniels et al evaluate the function of Cst7, a gene previously shown to be strongly expressed when microglia respond to Alzheimer's-like pathology. The reported findings include evidence for a sexually dimorphic role of Cst7 in microglia, including differences in lysosomal activity and ability to phagocytose. Some questions remain as to how many of these effects are 1) disease-independent, 2) age-dependent, and 3) ultimately affecting cognition

Strengths:<br /> -The approach taken here is sound, knocking out Cst7 in an animal model of Alzheimer's-like pathology, and analysing a range of variables associated with the pathology.<br /> -The authors have made good use of existing datasets, evidencing the advantages of data sharing and open data mining.<br /> -Data reporting is also excellent, as we can see the individual data points, and also observe how optimal group numbers were used. This adds solidity to the study.<br /> -The results are very well connected, with experiments focusing on the in vivo and in vitro lysosomal/phagocytic function<br /> -Exploring the effect of sex, as an independent variable, is a refreshing approach and clearly an important one by looking at the findings reported here.

Weaknesses:<br /> -The basis for the hypothesis of Cst7 displaying sexual dymorphism is not as strong as indicated by the text. Data presented in Figure 1 supports 1/2 models have statistically significant differences in expression of Cst7 between males and females.<br /> -As presented, it is hard to disentangle the differential impact of sex, in isolation, compared to the accelerated pathology/ageing observed in females. In other words, Cst7 could be playing a differential role in females not because that particular gene has sexually dimorphic roles, but because female microglia are generally more advanced in their phenotype and prone to Cst7-dependent effects that their younger counterparts (or male microglia) would not suffer. We also lack context when it comes to baseline effects of Cst7-/- compared to disease-related effects, since a crucial control (non-AD Cst7-/-) is missing from analyses, key in Figure 2 for example.<br /> -It is unclear how the knockout of Cst7 would selectively affect microglia. The expression of Cst7 is definitely very high in microglia in AD, but it's less clear whether other cells express this gene as well. If so, the effects of Cst7-/- could be microglia-independent in part.<br /> -Considering the large number of mice used in these studies, and the effort that very likely went into these, it is disappointing that we do not have any measure of cognition or any other behavioural task associated with the molecular data. Ultimately, changes in amyloid, for example, could or could not correlate with real pathology in APP models.

Reviewer #2 (Public Review):

Gating of the CFTR chloride channel is controlled by its nucleotide binding domains (NBDs) where ATP binding-induced dimerization leads to channel opening and ATP hydrolysis in the catalytic ATP binding site terminates CFTR's opening burst. Mutations that diminish ATP hydrolysis, including Walker A mutation K1250A, Walker B mutation D1370N, and catalytic glutamate mutations E1371Q and E1371S, have been used extensively to trap the channel in the open state by researchers studying CFTR function. The E1371Q human CFTR (hCFTR) has an extremely longer burst duration than all the other hydrolysis-deficient mutants, including E1371S hCFTR. An unexpected finding that the E-to-Q and E-to-S mutants of zebrafish CFTR (zCFTR) have similar non-hydrolytic closing rates inspired Simon et al to investigate the underlying mechanism for this discrepancy between the human and zebrafish CFTR orthologs, and examine how hydrolysis deficient mutations have differential effects on the CFTR's burst duration. Their data support the idea that all the above mutations completely abolish ATP hydrolysis. The closing rate of K1250A and E1371S CFTR represents the true non-hydrolytic closing rate of wildtype CFTR, while the closing rate of D1370N is accelerated presumably due to the lack of interaction between the negatively charged aspartate and magnesium ion in the ATP binding site. On the other hand, an artificial H-bond between the G576-Q1371 of hCFTR, which is absent in zCFTR, stabilizes the NBD dimer and slowers non-hydrolytic closure.

The conclusions of this paper are mostly well supported by the data, but some additional experiments will strengthen the claim on the role of the artificial inter-NBD hydrogen bond (point 1 below). Some aspects of data interpretation need to be further clarified (point 2-5 below).

1) The author hypothesized that in hCFTR an artificial H-bond between the side-chain of glutamine at position 1371 (i.e., in E1371Q mutant) and the backbone carbonyl at G576 of the D-loop stabilizes the NBD dimer. Such H-bond is absent in E1372Q zCFTR. The authors employed mutant cycle analysis on the G576Δ-E1371S mutation pair to demonstrate an energetic coupling between the hG576 and hE1371Q. However, how the deletion of G576 might alter the local structure is unpredictable. The result does not directly address the discrepancy between zCFTR and hCFTR, either. The D-loop is highly conserved across species with a consensus sequence PFGYLD (residue 574-579 in hCFTR), but in zCFTR the analogous sequence is PFTHLD. The backbone carbonyl oxygen could therefore be harder to access in zCFTR. A simple yet critical experiment would have strengthened the authors' claim that the interaction between Q1371 and G576 stabilizes the dimer: introducing mutation in the D-loop of zCFTR to match the sequence of hCFTR (and vice versa). The authors' hypothesis would predict that zCFTR with hCFTR's D-loop sequence should recapitulate hCFTR's phenotype: the E-to-Q mutation on the catalytic glutamate would further lengthen the burst duration compared to the E-to-S mutation.

2) The authors speculated that the reason for D1370N's relatively fast closing rate compared to other non-hydrolytic mutants is the loss of interaction between Mg2+ and the negatively charged aspartate. However, this reasoning fails to explain why non-hydrolytic closure of wildtype CFTR in the absence of Mg2+ (e.g., Levring et al. 2023 Extended Data Fig. 7g) is even slower than the non-hydrolytic closure of D1370N CFTR opened by MgATP, where at least the Mg2+ is present. The authors should caution the readers that so far no definitive experimental evidence can explain the destabilizing effect of D1370N.

3) Based on the results that the double mutant E1371S/K1250A hCFTR has similar burst duration as single mutant E1371S and K1250A, the authors made a strong claim that both mutations completely abolish ATP hydrolysis. Similar reasoning was applied to D1370N. The limitations in such interpretations should be discussed. The authors made the assumption that the termination of a burst is solely controlled by site 2 (Figure 1C). However, when hydrolysis is significantly diminished, binding of ATP in site 2 is very stable, and thus dissociation of ATP from site 2 versus site 1 becomes hard to distinguish. Whether all hydrolysis-deficient mutants share the same open-to-close transition by releasing ATP from site 2 but retaining ATP in site 1 is still a question. As the authors have elaborated in the text, it is known that mutations in the degenerate site 1 can affect non-hydrolytic closing. When mutations are introduced to site 2, they might as well result in allosteric effects on the stability of ATP binding in site 1, which could subsequently alter the channel's closing rate. The authors might want to make the readers aware of the complicated relationship between channel closure and CFTR's two ATP binding sites, and that the estimation of the "true non-hydrolytic closing rate" is based on an oversimplified gating scheme shown in Figure 1C.

4) It is known that non-hydrolytic closing rate of CFTR is phosphorylation dependent, which the authors briefly mentioned in the Discussion. Vergani et al. (2003) documented that τburst of K1250A and D1370N in PKA is ~80 s and ~4 s respectively, but both are reduced by roughly twofold when PKA was removed. In this study the burst durations of K1250A (~30 s, Figure 4C) and D1370N (~2 s, Figure 4E) indicate that these channels are not strongly phosphorylated. Similarly, the τburst of E1371S in PKA is over 100 s (Bompadre et al. 2005), significantly longer than that in the current study. Although it is unclear how a different degree of R domain phosphorylation affects non-hydrolytic closing, the fact that it does again suggests that the simplified scheme used as the base for data interpretation may have its limitation. The Discussion would benefit from a more cautionary note on the oversimplification of the IB1↔B1 transition, and clarify that channels are not strongly phosphorylated in the current experimental condition.

5) The τburst of E1371Q CFTR is over 400 second while the τburst of K1250A-E1371Q double mutant is shortened to ~200 second (Figure 3B, black vs Figure 4C, black). The K1250A-E1371S CFTR also seems to have a shorter τburst than E1371S CFTR (Figure 4C, blue vs Figure 3B, blue). Although the effect of the K1250A mutation on shortening τburst of E1371Q and E1371S CFTR is not as dramatic as the D1370N mutation, the authors might want to clearly state if there is indeed a significant difference and address how K1250A mutation has such destabilizing effect.

Reference:<br /> Bompadre, S. G., Cho, J. H., Wang, X., Zou, X., Sohma, Y., Li, M., and Hwang, T. C. (2005) CFTRgating II: Effects of nucleotide binding on the stability of open states. J Gen Physiol 125, 377-394

Levring,J., Terry,D.S., Kilic,Z., Fitzgerald,G., Blanchard,S.C., and Chen,J. (2023). CFTR function,<br /> pathology and pharmacology at single-molecule resolution. Nature 616, 606-614.

Vergani,P., Nairn,A.C., and Gadsby,D.C. (2003). On the mechanism of MgATP-dependent gating of CFTR Cl- channels. J. Gen. Physiol 121, 17-36.

Reviewer #2 (Public Review):

Antonio, Weiss, Gao, Sawyer, et al. provide new ancient DNA (aDNA) data for 200 individuals from Europe and the Mediterranean from the historical period, including Iron Age, Late Antiquity, Middle Ages, and early modernity. These data are used to characterize population structure in Europe across time and identify first-generation immigrants (roughly speaking, those who present genetic ancestry that is significantly different from others in the same archaeological site). Authors provide an estimate of an average across regions of >8% of individuals being first-generation immigrants. This observation, coupled with the observed genetic heterogeneity across regions, suggests high mobility of individuals during the historical period in Europe. In spite of that, Principal Component Analysis (PCA) indicates that the overall population structure in Europe has been rather stable in the last 3,000 years, i.e., the levels of genetic differentiation across space have been relatively stable. To understand whether population structure stability is compatible with a large number (>8%) of long-distance immigrants, authors use spatially-explicit Wright-Fisher simulations. They conclude these phenomena are incompatible and provide a thoughtful and convincing explanation for that.

Overall I think this manuscript is very well written and provides an exciting take-home message. The dataset with 200+ novel ancient human genomes will be a great resource for population genetics and paleogenomic studies. Methods are robust and well-detailed. Although the methods used are well-known and standard in the field of paleogenomics, the way the authors use these methods is very creative, insightful, and refreshing. Results provide a comprehensive and novel assessment of historical population genetic structure in Europe, including characterizing genetic heterogeneity within populations and interactions/migration across regions. Conclusions are fully supported by the data.

A few of the strengths of this manuscript are its dataset containing a large number of ancient human genomes, the novel insights about human migration provided by the results, the creative approach to characterize migration and population structure across time using aDNA, and the excellent figures describing research results. I see no major issues with this paper.

Reviewer #2 (Public Review):

The manuscript aims at understanding how the fatty acid ligand MYR inhibits the activity of Abl kinase. Despite a wealth of structural and biochemical data, a key mechanistic understanding of how MYR binding could inactive Abl was missing.

The authors used equilibrium and enhanced molecular dynamics (MD) simulations to masterfully answer open questions left by extensive experimental data in the mechanistic understanding of this system. The authors took advantage of several state-of-the-art simulation techniques and carefully planned simulations to extract a coherent understanding from a wealth of experimental facts.

The manuscript convincingly identifies an allosteric regulation by MYR. Allostery is often a source of confusion and sometimes is used as a magic catch-it-all explanation for poorly understood phenomena. Here, the authors show very compelling evidence of the existence of an allosteric mechanism. Also, they identify the physical origin of the allosteric pathway, providing a clear mechanistic understanding at the residue-level resolution. This is an impressive achievement.

By leaving a pocket in the protein, MYR enables the protein's activation. But MYR is a highly hydrophobic molecule surrounded by water. Where could it go rather than quickly binding back to the protein pocket? By asking this reasonable question, the authors propose an exciting mechanistic hypothesis. The physical proximity of Abl kinase to a cellular membrane could lead to a competition between the protein and the membrane for MYR, leading to a novel layer of regulation for this kinase. Free energy calculations performed by the authors show that this hypothesis is reasonable from the thermodynamic point of view.

From a broader perspective, this manuscript is an important contribution to the discussion of four outstanding topics. 1) myristoylation is an example of lipidation, a post-translational modification where an acyl chain is covalently linked to a protein. The role of post-translational modifications has been greatly underappreciated and investigated in the MD community. However, as all the work on Sars-Cov2 and this contribution show, post-translational modifications can be crucial to understanding function. Ignoring them could lead to severely biased results. 2) the debate on the nature of allostery is still on the rage. Some authors claim that looking for a residue-level mechanistic chain of events that explains the allosteric action does not make sense and that the only way of thinking about allostery is as a sudden global change of the conformational landscape. Here, the authors show that instead, it is possible and leads to an essential understanding. 3) The authors hypothesize a novel crosstalk between the Abl and cellular membranes mediated by MYR. This exciting and far-reaching hypothesis opens the door to new complex layers of regulation. I suspect that these crosstalks between cytosolic proteins, or the soluble domain of membrane-tethered proteins and membranes, are much more ubiquitous than what has been appreciated so far. 4) From a methodological point of view, this manuscript represents a masterful use of simulations to put existing experimental data in a coherent picture. It is an example of the use of MD simulations at its best, where the simulations make sense of experiments, integrate existing data into a unified picture, and lead to new hypotheses that can be tested in future experiments.

It would be superb if the authors could propose precise predictions that could inspire future experiments. Now that they present a residue-resolution allosteric pathway, can they suggest point mutations that would interrupt it?

Reviewer #2 (Public Review):

Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.

Reviewer #2 (Public Review):

Bilgic et al first explored cellular diversity in the developing cerebral cortex of ferret, honing in on progenitor cell diversity by employing FACS sorting of HES5-positive cells. They have generated a novel single cell transcriptomic dataset capturing the diversity of cells in the developing ferret cerebral cortex, including diverse radial glial and excitatory neuron populations. Unexpectedly, this analysis revealed the presence of CRYAB-positive truncated radial glia previously described only in humans. Using bioinformatic analyses, the investigators proposed that truncated radial glia produce ependymal cells, astrocytes, and to a lesser degree, neurons. Of particular interest to the field, they identify enriched expression of FOXJ1 in late truncated radial glia strongly indicating that towards the end of neurogenesis, these cells likely give rise to ependymal cells. This study represents a major advancement in the field of cortical development and a valuable dataset for future studies of ferret cortical development.

Reviewer #2 (Public Review):

Summary:<br /> This study aims to test auditory confounds during transcranial ultrasound stimulation (TUS) protocols that rely on audible frequencies. In several experiments, the authors show that a commonly observed suppression of motor-evoked potentials (MEP) during TUS can be explained by acoustic stimulation. For instance, not only target TUS, but also stimulation of a control site and acoustic stimulation led to suppressed MEP.

Strengths:<br /> A clear strength of the study is the multitude of control conditions (control sites, acoustic masking, acoustic stimulation etc) that makes results very convincing.<br /> Indeed, I do not have much to criticise. The paper follows a clear structure and is easy to follow, the research question is clearly relevant, and analyses are sound. Figures are of high quality.<br /> Although auditory confounds during TUS have been demonstrated before, the thorough design of the study will lead to a strong impact in the field.

Weaknesses:<br /> I cannot see major weaknesses. A few minor ones are that (1) the overview of previous related work, and how frequent audible TUS protocols are in the field, could be a bit clearer/more detailed; (2) the acoustic control stimulus can be described in more detail; and (3) the finding that remaining motor inhibition is observed during acoustically masked trials deserves further discussion.

Reviewer #2 (Public Review):

Segas et al motivate their work by indicating that none of the existing myoelectric solution for people with trans-humeral limb difference offer four active degrees of freedom, namely forearm flexion/extension, forearm supination/pronation, wrist flexion/extension, and wrist radial/ulnar deviation. These degrees of freedom are essential for positioning the prosthesis in the correct plan in the space before a grasp can be selected. They offer a controller based on the movement of the stump.

The proposed solution is elegant for what it is trying to achieve in a laboratory setting. Using a simple neural network to estimate the arm position is an interesting approach, despite the limitations/challenges that the approach suffers from, namely, the availability of prosthetic hardware that offers such functionality, information about the target and the noise in estimation if computer vision methods are used. Segas et al indicate these challenges in the manuscript, although they could also briefly discuss how they foresee the method could be expanded to enable a grasp command beyond the proximity between the end-point and the target. Indeed, it would be interesting to see how these methods can be generalise to more than one grasp.

One bit of the results that is missing in the paper is the results during the familiarisation block. If the methods in "intuitive" I would have thought no familiarisation would be needed. Do participants show any sign of motor adaptation during the familiarisation block?

In Supplementary Videos 3 and 4, how would the authors explain the jerky movement of the virtual arm while the stump is stationary? How would be possible to distinguish the relative importance of the target information versus body posture in the estimation of the arm position? This does not seem to be easy/clear to address beyond looking at the weights in the neural network.

I am intrigued by how the Generic ANN model has been trained, i.e. with the use of the forward kinematics to remap the measurement. I would have taught an easier approach would have been to create an Own model with the native arm of the person with the limb loss, as all your participants are unilateral (as per Table 1). Alternatively, one would have assumed that your common model from all participants would just need to be 'recalibrated' to a few examples of the data from people with limb difference, i.e. few shot calibration methods.

Reviewer #2 (Public Review):

Summary:<br /> The authors describe a deep mutational scanning (DMS) study of the kinase domain of the c-MET receptor tyrosine kinase. The screen is conducted with a highly activated fusion oncoprotein - Tpr-MET - in which the MET kinase domain is fused to the Tpr dimerization element. The mutagenized region includes the entire kinase domain and an alpha-helix in the juxtamembrane region that is essentially part of the MET kinase domain. The DMS screen is carried out in two contexts, one containing the entire cytoplasmic region of MET, and the other with an "exon 14 deletion" which removes a large portion of the juxtamembrane region (but retains the aforementioned alpha-helix). The work provides a robust and essentially exhaustive catalog of the effect of mutations (within the kinase domain) on the ability of the Tpr-MET fusion oncoproteins to drive IL3-independent growth of Ba/F3 cells. Every residue in the kinase is mutated to every natural amino acid. Given the design of the screen, one would expect it to be a powerful tool for identifying mutations that impair catalytic activity and therefore impair IL3-independent proliferation, but not the right tool for identifying gain-of-function mutations that operate by shifting the kinase from an inactive to active state (because the Tpr-Met fusion construct is already very highly activated). This is borne out by the data, which reveal many many deleterious mutations and few "gain-of-function" mutations (which are of uncertain significance, as discussed below).

Strengths:<br /> The authors take a very scholarly and thorough approach to interpreting the effect of mutations in light of available information for the structure and regulation of MET and other kinases. They examine the effect of mutations in the so-called catalytic (C) and regulatory (R) spines, the interface between the JM alpha-helix and the C-helix, the glycine-rich loop, and other key elements of the kinase, providing a structural rationale for the deleterious effect of mutations. Comparison of the panoply of deleterious mutations in the TPR-met versus TPR- exon14del-MET DMS screens reveals an interesting difference - the exon14 deletion MET is much more tolerant of mutations in the JM alpha-helix/C-helix interface. The reason for this is unclear, however.

Weaknesses:<br /> Because the screens were conducted with highly active Tpr-MET fusions, they have limited power to reveal gain-of-function mutations. Indeed, to the extent that Tpr-MET is as active or even more active than ligand-activated WT MET, one could argue that it is "fully" activated and that any additional gain of fitness would be "super-physiologic". I would expect such mutations to be rare (assuming that they could be detected at all in the Ba/F3 proliferation assay). Consistent with this, the authors note that gain-of-function mutations are rare in their screen (as judged by being more fit than the average of synonymous mutations). In their discussion of cancer-associated mutations, they highlight several "strong GOF variants in the DMS". It is unclear what the authors mean by "strong GOF", indeed it is unclear to this reviewer whether the screen has revealed any true gain of function mutations at all. A few points in this regard:

1) more active than the average of synonymous mutations (nucleotide changes that have no effect on the sequence of the expressed protein) seems to be an awfully low bar for GOF - by that measure, several synonymous mutations would presumably be classified as GOF.

2) In the +IL3 heatmap in supplemental Figure 1A, there is as much or more "blue" indicating GOF as in the -IL3 heatmap, which could suggest that the observed level of gain in fitness is noise, not signal.

3) And finally, consistent with this interpretation, in Supplemental Figure 1C, comparing the synonymous and missense panels in the IL3 withdrawal condition suggests that the most active missense mutations (characterized here as strong GOF) are no more active than the most active synonymous mutations.

My other major concern with the work as presented is that the authors conflate "activity" and "activation" in discussing the effects of mutations. "Activation" implies a role in regulation - affecting a switch between inactive and active conformations or states - at least in this reviewer's mind. As discussed above, the screen per se does not probe activation, only activity. To the extent that the residues discussed are important for activation/regulation of the kinase, that information is coming from prior structural/functional studies of MET and other kinases, not from the DMS screen conducted here. Of course, it is appropriate and interesting for the authors to consider residues that are known to form important structural/regulatory elements, but they should be careful with the use of activity vs. activation and make it clear to the reader that the screen probes the former. One example - in the abstract, the authors rightly note that their approach has revealed a critical hydrophobic interaction between the JM segment and the C-helix, but then they go on to assert that this points to differences in the regulation of MET and other RTKs. There is no evidence that this is a regulatory interaction, as opposed to simply a structural element present in MET (and indeed the authors' examination of prior crystal structures shows that the interaction is present in both active and inactive states.

Reviewer #2 (Public Review):

Summary:<br /> One of the greatest challenges for the spliceosome is to be able to repress the many cryptic splice sites that can occur in both the intronic and exotic sequences of genes. Although many studies have focused on cryptic signals in introns (because of their common involvement in disease) the question still remained open as to the factors that repress cryptic exons in exons. Because exons are normally much shorter than introns, in many cases the problem does not exist. However, in human genes, a significant proportion of exons can be considerably longer than the average 150 nt length and this raises the question of how cryptic splicing can be prevented in long exons. To address this question, the authors have focused on the possible role played by an ancient mammalian RBD protein called RBMX. Using a combination of high-throughput and classic splicing methodologies, they have shown that there is a class of RBMX-dependent ultra-long exons connected where the RBMX, RBMXL2, and RBMY paralogs have closely related functional activity in repressing cryptic splice site selection.

Strengths:<br /> In general, the present work sheds light on what has been a rather understudied process in splicing research. The use of iCLIP and RNA-seq data has not only allowed us to identify the long exons where cryptic splicing is prevented by the RBMX proteins but has also allowed us to identify a network of genes mostly involved in genome stability and transcriptional control where these proteins seem to play a prominent role. This can therefore also shed additional information on the way splicing has shaped evolutionary processes in the mammalian lineage and will therefore be of interest to many researchers in this field.

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

Reviewer #2 (Public Review):

Summary:<br /> In this work, Boor and colleagues explored the role of microbial food cues in the regulation of neuroendocrine-controlled foraging behavior. Consistent with previous reports, the authors find that C. elegans foraging behavior is regulated by the neuroendocrine TGFβ ligand encoded by daf-7. In addition to its known role in the neuroendocrine/sensory ASI neurons, Boot and colleagues show that daf-7 expression is dynamically regulated in the ASJ sensory neurons by microbial food cues - and that this regulation is important for exploration/exploitation balance during foraging. They identify at least two independent pathways by which microbial cues regulate daf-7 expression in ASJ: a likely gustatory pathway that promotes daf-7 expression and an opposing interoceptive pathway, also likely chemosensory in nature but which requires microbial ingestion to inhibit daf-7 expression. Two neuroendocrine pathways known to regulate foraging (serotonin and PDF-1) appear to act at least in part via daf-7 induction. They further identify a novel role for the C. elegans ALK orthologue encoded by scd-2, which acts in interneurons to regulate daf-7 expression and foraging behavior. These results together imply that distinct cues from microbial food are used to regulate the balance between exploration and exploitation via conserved signaling pathways.

Strengths:<br /> The findings that gustatory and interoceptive inputs into foraging behavior are separable and opposing are novel and interesting, which they have shown clearly in Figure 1. It is also clear from their results that removal of the interoceptive cue (via transfer to non-digestible food) results in rapid induction of daf-7::gfp in ASJ, and that ASJ plays an important role in the regulation of foraging behavior.

The role of the hen-1/scd-2 pathway in mediating the effects of ingested food is also compelling and well-interpreted. The use of precise gain-of-function alleles further supports their conclusions. This implies that important elements of this food-sensing pathway may be conserved in mammals.

Weaknesses:<br /> What is less clear to me from the work at this stage is how the gustatory input fits into this picture and to what extent can it be strongly concluded that the daf-7-regulating pathways that they have identified (del-3/7, 5-HT, PDFR-1, scd-2) act via the interoceptive pathway as opposed to the gustatory pathway. It follows from the work of the Flavell lab that del-3/7 likely acts via the interoceptive pathway in this context as well but this isn't shown directly - e.g. comparing the effects of aztreonam-treated bacteria and complete food removal to controls. The roles of 5-HT and PDFR-1 are even a bit less clear. Are the authors proposing that these are entirely parallel pathways? This could be explained in better detail.

It would also be helpful to elaborate more on why the identified transcriptional positive feedback loop is predicted to extend roaming state duration - as opposed to some other mechanism of increasing roaming such as increased probability of roaming state initiation. This doesn't seem self-evident to me. Related to this point is the somewhat confusing conclusion that the effects of tph-1 and pdfr-1 mutations on daf-7 expression are due to changes in ingestion during roaming/dwelling. From my understanding (e.g. Cermak et al., 2020), pharyngeal pumping rate does not reliably decrease during roaming - so is it clear that there are in fact lower rates of ingestion during roaming in their experiments? If so, why does increased roaming (via tph-1 mutation) result in further increases in daf-7 expression in animals fed aztreonam-treated food (Fig 3B)? Alternatively, there could be a direct signaling connection between the 5-HT/PDFR-1 pathways and daf-7 expression which could be acknowledged or explained.

Reviewer #2 (Public Review):

Clarkson et al investigated the impact of in vivo ESR1 gene disruption selectively in preoptic area GABA neurons on the estrogen regulation of LH secretion. The hypothalamic pathways by which estradiol controls the secretion of gonadotrophins are incompletely understood and relevant to a better understanding of the mechanisms driving fertility and reproduction. Using CRISPR-Cas9 methodology, the authors were able to effectively reduce the expression of estrogen receptor (ER)-alpha in GABA neurons located in the preoptic area of adult female mice. The results obtained were rather variable except in the animals with concomitant suppression of kisspeptin in the rostral periventricular region of the third ventricle (RP3V), which displayed interruption of ovarian cyclicity and an altered estradiol-induced LH surge. The experimental approach used allowed for a cell-selective, temporally-controlled suppression of ER-alpha expression, providing further evidence of the critical role of RP3V kisspeptin neurons in the estrogen positive-feedback effect. Nevertheless, the assessment of the estradiol-induced LH surge was limited to only one terminal blood collection. The preovulatory LH surge is a variable phenomenon and would require serial blood sampling for a conclusive evaluation of the surge occurrence or alteration, such as in shape, amplitude, or timing. The animals were not assessed for ovulation either, which might be a functional readout for the effectiveness of the LH surge. Thus, the actual effect on the preovulatory LH surge was not fully characterized. Finally, the study leaves unanswered the role of GABA itself. As there was no evident phenotype for the ESR1 knockdown in GABA neurons that do not coexpress kisspeptin, this suggests that GABA neurotransmission in the preoptic area is not involved in the estrogen regulation of LH secretion.

Reviewer #2 (Public Review):

Summary:

In this work, the authors explore how Notch activity acts together with Bsh homeodomain transcription factors to establish L4 and L5 fates in the lamina of the visual system of Drosophila. They propose a model in which differential Notch activity generates different chromatin landscapes in presumptive L4 and L5, allowing the differential binding of the primary homeodomain TF Bsh (as described in the co-submitted paper), which in turn activates downstream genes specific to either neuronal type. The requirement of Notch for L4 vs. L5 fate is well supported, and complete transformation from one cell type into the other is observed when altering Notch activity. However, the role of Notch in creating differential chromatin landscapes is not directly demonstrated. It is only based on correlation, but it remains a plausible and intriguing hypothesis.

Strengths:

The authors are successful in characterizing the role of Notch to distinguish between L4 and L5 cell fates. They show that the Notch pathway is active in L4 but not in L5. They identify L1, the neuron adjacent to L4 as expressing the Delta ligand, therefore being the potential source for Notch activation in L4. Moreover, the manuscript shows molecular and morphological/connectivity transformations from one cell type into the other when Notch activity is manipulated.

Using DamID, the authors characterize the chromatin landscape of L4 and L5 neurons. They show that Bsh occupies distinct loci in each cell type. This supports their model that Bsh acts as a primary selector gene in L4/L5 that activates different target genes in L4 vs L5 based on the differential availability of open chromatin loci.

Overall, the manuscript presents an interesting example of how Notch activity cooperates with TF expression to generate diverging cell fates. Together with the accompanying paper, it helps thoroughly describe how lamina cell types L4 and L5 are specified and provides an interesting hypothesis for the role of Notch and Bsh in increasing neuronal diversity in the lamina during evolution.

Weaknesses:

Differential Notch activity in L4 and L5:<br /> ● The manuscript focuses its attention on describing Notch activity in L4 vs L5 neurons. However, from the data presented, it is very likely that the pool of progenitors (LPCs) is already subdivided into at least two types of progenitors that will rise to L4 and L5, respectively. Evidence to support this is the activity of E(spl)-mɣ-GFP and the Dl puncta observed in the LPC region. Discussion should naturally follow that Notch-induced differences in L4/L5 might preexist L1-expressed Dl that affect newborn L4/L5. Therefore, the differences between L4 and L5 fates might be established earlier than discussed in the paper. The authors should acknowledge this possibility and discuss it in their model.<br /> ● The authors claim that Notch activation is caused by L1-expressed Delta. However, they use an LPC driver to knock down Dl. Dl-KD should be performed exclusively in L1, and the fate of L4 should be assessed.<br /> ● To test whether L4 neurons are derived from NotchON LPCs, I suggest performing MARCM clones in early pupa with an E(spl)-mɣ-GFP reporter.<br /> ● The expression of different Notch targets in LPCs and L4 neurons may be further explored. I suggest using different Notch-activity reporters (i.e., E(spl)-GFP reporters) to further characterize these differences. What cause the switch in Notch target expression from LPCs to L4 neurons should be a topic of discussion.

Notch role in establishing L4 vs L5 fates:<br /> ● The authors describe that 27G05-Gal4 causes a partial Notch Gain of Function caused by its genomic location between Notch target genes. However, this is not further elaborated. The use of this driver is especially problematic when performing Notch KD, as many of the resulting neurons express Ap, and therefore have some features of L4 neurons. Therefore, Pdm3+/Ap+ cells should always be counted as intermediate L4/L5 fate (i.e., Fig3 E-J, Fig3-Sup2), irrespective of what the mechanistic explanation for Ap activation might be. It's not accurate to assume their L5 identity. In Fig4 intermediate-fate cells are correctly counted as such.<br /> ● Lines 170-173: The temporal requirement for Notch activity in L5-to-L4 transformation is not clearly delineated. In Fig4-figure supplement 1D-E, it is not stated if the shift to 29{degree sign}C is performed as in Fig4-figure supplement 1A-C.<br /> ● Additionally, using the same approach, it would be interesting to explore the window of competence for Notch-induced L5-to-L4 transformation: at which point in L5 maturation can fate no longer be changed by Notch GoF?

L4-to-L3 conversion in the absence of Bsh<br /> ● Although interesting, the L4-to-L3 conversion in the absence of Bsh is never shown to be dependent on Notch activity. Importantly, L3 NotchON status is assumed based on their position next to Dl-expressing L1, but it is not empirically tested. Perhaps screening Notch target reporter expression in the lamina, as suggested above, could inform this issue.<br /> ● Otherwise, the analysis of Bsh Loss of Function in L4 might be better suited to be included in the accompanying manuscript that specifically deals with the role of Bsh as a selector gene for L4 and L5.

Different chromatin landscape in L4 and L5 neurons<br /> ● A major concern is that, although L4 and L5 neurons are shown to present different chromatin landscapes (as expected for different neuronal types), it is not demonstrated that this is caused by Notch activity. The paper proves unambiguously that Notch activity, in concert with Bsh, causes the fate choice between L4 and L5. However, that this is caused by Notch creating a differential chromatin landscape is based only in correlation (NotchON cells having a different profile than NotchOFF). Although the authors are careful not to claim that differential chromatin opening is caused directly by Notch, this is heavily suggested throughout the text and must be toned down.<br /> e.g.: Line 294: "With Notch signaling, L4 neurons generate distinct open chromatin landscape" and Line 298: "Our findings propose a model that the unique combination of HDTF and open chromatin landscape (e.g. by Notch signaling)" . These claims are not supported well enough, and alternative hypotheses should be provided in the discussion. An alternative hypothesis could be that LPCs are already specified towards L4 and L5 fates. In this context, different early Bsh targets in each cell type could play a pioneer role generating a differential chromatin landscape.

● The correlation between open chromatin and Bsh loci with Differentially Expressed genes is much higher for L4 than L5. It is not clear why this is the case, and should be discussed further by the authors.

Reviewer #2 (Public Review):

Summary:<br /> In this paper, the authors explore the role of the Homeodomain Transcription Factor Bsh in the specification of Lamina neuronal types in the optic lobe of Drosophila. Using the framework of terminal selector genes and compelling data, they investigate whether the same factor that establishes early cell identity is responsible for the acquisition of terminal features of the neuron (i.e., cell connectivity and synaptogenesis).

The authors convincingly describe the sequential expression and activity of Bsh, termed here as 'primary HDTF', and of Ap in L4 or Pdm3 in L5 as 'secondary HDTFs' during the specification of these two neurons. The study demonstrates the requirement of Bsh to activate either Ap and Pdm3, and therefore to generate the L4 and L5 fates. Moreover, the authors show that in the absence of Bsh, L4 and L5 fates are transformed into a L1 or L3-like fates.

Finally, the authors used DamID and Bsh:DamID to profile the open chromatin signature and the Bsh binding sites in L4 neurons at the synaptogenesis stage. This allows the identification of putative Bsh target genes in L4, many of which were also found to be upregulated in L4 in a previous single-cell transcriptomic analysis. Among these genes, the paper focuses on Dip-β, a known regulator of L4 connectivity. They demonstrate that both Bsh and Ap are required for Dip-β, forming a feed-forward loop. Indeed, the loss of Bsh causes abnormal L4 synaptogenesis and therefore defects in several visual behaviors.

The authors also propose the intriguing hypothesis that the expression of Bsh expanded the diversity of Lamina neurons from a 3 cell-type state to the current 5 cell-type state in the optic lobe.

Strengths:

Overall, this work presents a beautiful practical example of the framework of terminal selectors: Bsh acts hierarchically with Ap or Pdm3 to establish the L4 or L5 cell fates and, at least in L4, participates in the expression of terminal features of the neuron (i.e., synaptogenesis through Dip-β regulation).

The hierarchical interactions among Bsh and the activation of Ap and Pdm3 expression in L4 and L5, respectively, are well established experimentally. Using different genetic drivers, the authors show a window of competence during L4 neuron specification during which Bsh activates Ap expression. Later, as the neuron matures, Ap becomes independent of Bsh. This allows the authors to propose a coherent and well-supported model in which Bsh acts as a 'primary' selector that activates the expression of L4-specific (Ap) and L5-specific (Pdm3) 'secondary' selector genes, that together establish neuronal fate.

Importantly, the authors describe a striking cell fate change when Bsh is knocked down from L4/L5 progenitor cells. In such cases, L1 and L3 neurons are generated at the expense of L4 and L5. The paper demonstrates that Bsh in L4/L5 represses Zfh1, which in turn acts as the primary selector for L1/L3 fates. These results point to a model where the acquisition of Bsh during evolution might have provided the grounds for the generation of new cell types, L4 and L5, expanding lamina neuronal diversity for a more refined visual behaviors in flies. This is an intriguing and novel hypothesis that should be tested from an evo-devo standpoint, for instance by identifying a species when L4 and L5 do not exist and/or Bsh is not expressed in L neurons.

To gain insight into how Bsh regulates neuronal fate and terminal features, the authors have profiled the open chromatin landscape and Bsh binding sites in L4 neurons at mid-pupation using the DamID technique. The paper describes a number of genes that have Bsh binding peaks in their regulatory regions and that are differentially expressed in L4 neurons, based on available scRNAseq data. Although the manuscript does not explore this candidate list in depth, many of these genes belong to classes that might explain terminal features of L4 neurons, such as neurotransmitter identity, neuropeptides or cytoskeletal regulators. Interestingly, one of these upregulated genes with a Bsh peak is Dip-β, an immunoglobulin superfamily protein that has been described by previous work from the author's lab to be relevant to establish L4 proper connectivity. This work proves that Bsh and Ap work in a feed-forward loop to regulate Dip-β expression, and therefore to establish normal L4 synapses. Furthermore, Bsh loss of function in L4 causes impairs visual behaviors.

Weaknesses:

● The last paragraph of the introduction is written using rhetorical questions and does not read well. I suggest rewriting it in a more conventional direct style to improve readability.

● A significant concern is the way in which information is conveyed in the Figures. Throughout the paper, understanding of the experimental results is hindered by the lack of information in the Figure headers. Specifically, the genetic driver used for each panel should be adequately noted, together with the age of the brain and the experimental condition. For example, R27G05-Gal4 drives early expression in LPCs and L4/L5, while the 31C06-AD, 34G07-DBD Split-Gal4 combination drives expression in older L4 neurons, and the use of one or the other to drive Bsh-KD has dramatic differences in Ap expression. The indication of the driver used in each panel will facilitate the reader's grasp of the experimental results.

● Bsh role in L4/L5 cell fate:<br /> o It is not clear whether Tll+/Bsh+ LPCs are the precursors of L4/L5. Morphologically, these cells sit very close to L5, but are much more distant from L4.<br /> o Somatic CRISPR knockout of Bsh seems to have a weaker phenotype than the knockdown using RNAi. However, in several experiments down the line, the authors use CRISPR-KO rather than RNAi to knock down Bsh activity: it should be explained why the authors made this decision. Alternatively, a null mutant could be used to consolidate the loss of function phenotype, although this is not strictly necessary given that the RNAi is highly efficient and almost completely abolishes Bsh protein.<br /> o Line 102: Rephrase "R27G05-Gal4 is expressed in all LPCs and turned off in lamina neurons" to "is turned off as lamina neurons mature", as it is kept on for a significant amount of time after the neurons have already been specified.<br /> o Line 121: "(a) that all known lamina neuron markers become independent of Bsh regulation in neurons" is not an accurate statement, as the markers tested were not shown to be dependent on Bsh in the first place.<br /> o Lines 129-134: Make explicit that the LPC-Gal4 was used in this experiment. This is especially important here, as these results are opposite to the Bsh Loss of Function in L4 neurons described in the previous section. This will help clarify the window of competence in which Bsh establishes L4/L5 neuronal identities through ap/pdm3 expression.

● DamID and Bsh binding profile:<br /> ○ Figure 5 - figure supplement 1C-E: The genotype of the Control in (C) has to be described within the panel. As it is, it can be confused with a wild type brain, when it is in fact a Bsh-KO mutant.<br /> ○ It Is not clear how L4-specific Differentially Expressed Genes were found. Are these genes DEG between Lamina neurons types, or are they upregulated genes with respect to all neuronal clusters? If the latter is the case, it could explain the discrepancy between scRNAseq DEGs and Bsh peaks in L4 neurons.

● Dip-β regulation:<br /> ○ Line 234: It is not clear why CRISPR KO is used in this case, when Bsh-RNAi presents a stronger phenotype.<br /> ○ Figure 6N-R shows results using LPC-Gal4. It is not clear why this driver was used, as it makes a less accurate comparison with the other panels in the figure, which use L4-Split-Gal4. This discrepancy should be acknowledged and explained, or the experiment repeated with L4-Split-Gal4>Ap-RNAi.<br /> ○ Line 271: It is also possible that L4 activity is dispensable for motion detection and only L5 is required.

● Discussion: It is necessary to de-emphasize the relevance of HDTFs, or at least acknowledge that other, non-homeodomain TFs, can act as selector genes to determine neuronal identity. By restricting the discussion to HDTFs, it is not mentioned that other classes of TFs could follow the same Primary-Secondary selector activation logic.

Reviewer #2 (Public Review):

Summary:<br /> Desiderio and colleagues investigated the role of the TALE (three amino acid loop extension) homeodomain transcription factor Meis2 during maturation and target innervation of mechanoreceptors and their sensation to touch. They start with a series of careful in situ hybridizations to examine Meis2 transcript expression in mouse and chick DRGs of different embryonic stages. By this approach, they identify Meis2+ neurons as slowly- and rapidly adapting A-beta LTMRs, respectively. Retrograde tracing experiments in newborn mice confirmed that Meis2-expressing sensory neurons project to the skin, while unilateral limb bud ablations in chick embryos in Ovo showed that these neurons require target-derived signals for survival. The authors further generated a conditional knock-out (cKO) mouse model in which Meis2 is selectively lost in Islet1-expressing, postmitotic neurons in the DRG (IsletCre/+::Meis2flox/flox, abbreviated below as cKO). WT and Islet1Cre/+ littermates served as controls. cKO mice did not exhibit any obvious alteration in volume or cellular composition of the DRGs but showed significantly reduced sensitivity to touch stimuli and various innervation defects to different end-organ targets. RNA-sequencing experiments of E18.5 DRGs taken from WT, Islet1Cre/+, and cKO mice reveal extensive gene expression differences between cKO cells and the two controls, including synaptic proteins and components of the GABAergic signaling system. Gene expression also differed considerably between WT and heterozygous Islet1Cre/+ mice while several of the other parameters tested did not. These findings suggest that Islet1 heterozygosity affects gene expression in sensory neurons but not sensory neuron functionality. However, only some of the parameters tested were assessed for all three genotypes. Histological analysis and electrophysiological recordings shed light on the physiological defects resulting from the loss of Meis2. By immunohistochemical approaches, the authors describe distinct innervation defects in glabrous and hairy skin (reduced innervation of Merkel cells by SA1-LTMRs in glabrous but not hairy skin, reduced complexity of A-beta RA1-LTMs innervating Meissner's corpuscles in glabrous skin, reduced branching and innervation of A-betA RA1-LTMRs in hairy skin). Electrophysiological recordings from ex vivo skin nerve preparations found that several, but not all of these histological defects are matched by altered responses to external stimuli, indicating that compensation may play a considerable role in this system.

Strengths:<br /> This is a well-conducted study that combines different experimental approaches to convincingly show that the transcription factor Meis2 plays an important role in the perception of light touch. The authors describe a new mouse model for compromised touch sensation and identify a number of genes whose expression depends on Meis2 in mouse DRGs. Given that dysbalanced MEIS2 expression in humans has been linked to autism and that autism seems to involve an inappropriate response to light touch, the present study makes a novel and important link between this gene and ASD.

Weaknesses:<br /> The authors make use of different experimental approaches to investigate the role of Meis2 in touch sensation, but the results obtained by these techniques could be connected better. For instance, the authors identify several genes involved in synapse formation, synaptic transmission, neuronal projections, or axon and dendrite maturation that are up- or downregulated upon targeted Meis2 deletion, but it is unresolved whether these chances can in any way explain the histological, electrophysiological, or behavioral deficits observed in cKO animals. The use of two different controls (WT and Islet1Cre/+) is unsatisfactory and it is not clear why some parameters were studied in all three genotypes (WT, Islet1Cre/+ and cKO) and others only in WT and cKO. In addition, Meis2 mutant mice apparently are less responsive to touch, whereas in humans, mutation or genomic deletion involving the MEIS2 gene locus is associated with ASD, a condition that, if anything, is associated with an elevated sensitivity to touch. It would be interesting to know how the authors reconcile these two findings. A minor weakness, the first manuscript suffers from some ambiguities and errors, but these can be easily corrected.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by David et al. describes a novel image segmentation method, implementing Local Moran's method, which determines whether the value of a datapoint or a pixel is randomly distributed among all values, in differentiating pixel clusters from the background noise. The study includes several proof-of-concept analyses to validate the power of the new approach, revealing that implementation of Local Moran's method in image segmentation is superior to threshold-based segmentation methods commonly used in analyzing confocal images in neuroanatomical studies.

Strengths:<br /> Several proof-of-concept experiments are performed to confirm the sensitivity and validity of the proposed method. Using composed images with varying levels of background noise and analyzing them in parallel with the Local Moran's or a Threshold-Based Method (TBM), the study is able to compare these approaches directly and reveal their relative power in isolating clustered pixels.

Similarly, dual immuno-electron microscopy was used to test the biological relevance of a colocalization that was revealed by Local Moran's segmentation approach on dual-fluorescent labeled tissue using immuno-markers of the axon terminal and a membrane-protein (Figure 5). The EM revealed that the two markers were present in terminals and their post-synaptic partners, respectively. This is a strong approach to verify the validity of the new approach for determining object-based colocalization in fluorescent microscopy.

The methods section is clear in explaining the rationale and the steps of the new method (however, see the weaknesses section). Figures are appropriate and effective in illustrating the methods and the results of the study. The writing is clear; the references are appropriate and useful.

Weaknesses:<br /> While the steps of the mathematical calculations to implement Local Moran's principles for analyzing high-resolution images are clearly written, the manuscript currently does not provide a computation tool that could facilitate easy implementation of the method by other researchers. Without a user-friendly tool, such as an ImageJ plugin or a code, the use of the method developed by David et al by other investigators may remain limited.

Reviewer #2 (Public Review):

This manuscript by Muñoz-Reyes et al. presents studies on the molecular mechanisms by which NCS-1 regulates Ric-8A and its interaction with Ga. They have investigated how calcium ions and phosphorylation of Ric-8A affect these interactions. They found that NCS-1 induces a conformational change in Ric-8A that prevents its phosphorylation and subsequent interaction with Ga, and this can be reversed by increasing calcium ion concentration. Using structural biology methods, they determined the interaction surfaces between NCS-1 and Ric-8A. These mechanistic analyses are needed in the field and beneficial to helping us understand specificity in the regulation of G protein signaling.

Overall, this manuscript presents an abundance of data that supports the authors' conclusions. The introduction is thorough and well-written. The structure figures are beautiful and clear - well done. Most of the biochemical and biophysical experiments are convincing. In some cases, further elaborations and explanations of data interpretation are needed. The crystallographic data is solid. However, I have major concerns with the cryo-EM data presented due to its low quality and the conclusions drawn from it.

Reviewer #2 (Public Review):

Summary:<br /> The authors set out to determine which lipid transfer proteins impact the lipids of Golgi apparatus, and they identified a reasonable number of "hits" where the lack of one lipid transfer protein affected a particular Golgi lipid or class of lipids. They then carried out something close to a "proof of concept" for one lipid (sphingomyelin) and two closely related lipid transfer proteins (ORP9/ORP11). They looked into that example in great detail and found a previously unknown relationship between the level of phosphatidylserine in the Golgi (presumably trans-Golgi, trans-Golgi Network) and the function of the sphingomyelin synthase enzyme. This was all convincingly done - results support their conclusions - showing that the authors achieved their aims.

Impact:<br /> There are likely to be 2 types of impact:<br /> (I) cell biology: sphoingomyelin synthase, ORP9/11 will be studied in the future in more informed ways to understand (a) the role of different Golgi lipids - this work opens that out and produces more questions than answers (b) the role of different ORPs: what distinguishes ORP11 from its paralogy ORP10?<br /> (ii) molecular biochemistry: combining knockdown miniscreen with organelle lipidomics must be time-consuming, but here it is shown to be quite a powerful way to discover new aspects of lipid-based regulation of protein function. This will be useful to others as an example, and if this kind of workflow could be automated, then the possible power of the method could be widely applied.

Strengths:<br /> Nicely controlled data;<br /> Wide-ranging lipidomics dataset with repeats and SDs - all data easily viewed.<br /> Simple take-home message that PS traffic to the TGN by ORP9/11 is required for some aspect of SMS1 function.

Weaknesses:<br /> Model and Discussion:<br /> No idea about the aspect of SMS1 function that is being affected. Even if no further experiments were carried out, the authors could discuss possibilities. One might speculate what the PS is being used for. For example, is it a co-factor for integral membrane proteins, such as flippases? Is it a co-factor for peripheral membrane proteins, such as yet more LTPs? The model could include the work of Peretti et al (2008), which linked Nir2 activity exchanging PI:PA (Yadav et al, 2015) to the eventual function of CERT. Could the PS have a role in removing/reducing DAG produced by CERT?

Reviewer #2 (Public Review):

Summary: The study demonstrates that deletion of a small cytoplasmic membrane protein, Tmem263, caused severe impairment of longitudinal bone growth and that the impaired bone growth was caused by suppression of expression and/or protein levels of growth hormone receptors in the liver.

Strengths: The experimental design of the study is sound and the results are in general supportive of the conclusions.

Weaknesses: The study lacks mechanistic investigation into how the deletion of a gene corresponding to a small cytoplasmic membrane protein would lead to a substantial reduction in the gene expression of growth hormone receptor, which takes place in the nuclei. Accordingly, the manuscript is of a largely descriptive nature.

Reviewer #2 (Public Review):

Summary:

The authors provide strong evidence that bacteria, such as E. coli, compete with tumor cells for iron resources and consequently reduce tumor growth. When sequestration between LCN2 and bacterobactin is blocked by upregulating CDG(DGC-E. coli) or salmochelin(IroA-E.coli), E. coli increase iron uptake from the tumor microenvironment (TME) and restrict iron availability for tumor cells. Long-term remission in IroA-E.coli treated mice is associated with enhanced CD8+ T cell activity. Additionally, systemic delivery of IroA-E.coli shows a synergistic effect with chemotherapy reagent oxaliplatin to reduce tumor growth.

Strengths:

It is important to identify the iron-related crosstalk between E. coli and TME. Blocking lcn2-bacterobactin sequestration by different strategies consistently reduces tumor growth.

Weaknesses:

As engineered E.coli upregulate their function to uptake iron, they may increase the likelihood of escaping from nutritional immunity (LCN2 becomes insensitive to sequester iron from the bacteria). Would this raise the chance of developing sepsis? Do authors think that it is safe to administrate these engineered bacteria in mice or humans?

Reviewer #2 (Public Review):

Summary:<br /> The authors embarked on a journey to understand the mechanisms and intensity-dependency of ultrasound (US)-induced extracellular vesicle (EV) release from myotubes and the potential anti-inflammatory effects of these EVs on macrophages. This study builds on their prior work from 2021 that initially reported US-induced EV secretion.

Strengths:<br /> 1. The finding that US-treated myotube EVs can suppress macrophage inflammatory responses is particularly intriguing, hinting at potential therapeutic avenues in inflammation modulation.

Weaknesses:<br /> 1. The exploration of output parameters for US induction appears limited, with only three different output powers (intensities) tested, thus narrowing the scope of their findings.<br /> 2. Their claim of elucidating mechanisms seems to be only partially met, with a predominant focus on the correlation between calcium responses and EV release.<br /> 3. While the intracellular calcium response is a dynamic activity, the method used to measure it could risk a loss of kinetic information.<br /> 4. The inclusion of miRNA sequencing is commendable; however, the interpretation of this data fails to draw clear conclusions, diminishing the impact of this segment.

While the authors have shown the anti-inflammatory effects of US-induced EVs on macrophages, there are gaps in the comprehensive understanding of the mechanisms underlying US-induced EV release. Certain aspects, like the calcium response and the utility of miRNA sequencing, were not fully explored to their potential. Therefore, while the study establishes some findings, it leaves other aspects only partially substantiated.

Reviewer #2 (Public Review):

The manuscript of Akter et al is an important study that investigates the role of astrocytic Gi signaling in the anterior cingulate cortex in the modulation of extracellular L-lactate level and consequently impairment in flavor-place associates (PA) learning. However, whereas some of the behavioral observations and signaling mechanism data are compelling, the conclusions about the effect on memory are inadequate as they rely on an experimental design that does not allow to differentiate acute or learning effect from the effect outlasting pharmacological treatments, i.e. effect on memory retention. With the addition of a few experiments, this paper would be of interest to the larger group of researchers interested in neuron-glia interactions during complex behavior.<br /> • Largely, I agree with the authors' conclusion that activating Gi signaling in astrocytes impairs PA learning, however, the effect on memory retrieval is not that obvious. All behavioral and molecular signaling effects described in this study are obtained with the continuous presence of CNO, therefore it is not possible to exclude the acute effect of Gi pathway activation in astrocytes. What will happen with memory on retrieval test when CNO is omitted selectively during early, middle, or late session blocks of PA learning?<br /> • I found it truly exciting that the administration of exogenous L-lactate is capable to rescue CNO-induced PA learning impairment, when co-applied. Would it be possible that this treatment has a sensitivity to a particular stage of learning (acquisition, consolidation, or memory retrieval) when L-lactate administration would be the most efficacious?<br /> • The hypothesis that observed learning impairments could be associated with diminished mitochondrial biogenesis caused by decreased l-lactate in the result of astrocytic Gi-DREADDS stimulation is very appealing, but a few key pieces of evidence are missing. So far, the hypothesis is supported by experiments demonstrating reduced expression of several components of mitochondrial membrane ATP synthase and a decrease in relative mtDNA copy numbers in ACC of rats injected with Gi-DREADDs. L-lactate injections into ACC restored and even further increased the expression of the above-mentioned markers. Co-administration of NMDAR antagonist D-APV or MCT-2 (mostly neuronal) blocker 4-CIN with L-lactate, prevented L-lactate-induced increase in relative mtDNA copy. I am wondering how the interference with mitochondrial biogenesis is affecting neuronal physiology and if it would result in impaired PA learning or schema memory.

Reviewer #2 (Public Review):

Summary:

The manuscript by Wohlwend et al. investigates the implications of inhibiting ceramide synthase Cers1 on skeletal muscle function during aging. The authors propose a role for Cers1 in muscle myogenesis and aging sarcopenia. Both pharmacological and AAV-driven genetic inhibition of Cers1 in 18-month-old mice lead to reduced C18 ceramides in skeletal muscle, exacerbating age-dependent features such as muscle atrophy, fibrosis, and center-nucleated fibers. Similarly, inhibition of the Cers1 orthologue in C. elegans reduces motility and causes alterations in muscle morphology.

Strengths:

The study is well-designed, carefully executed, and provides highly informative and novel findings that are relevant to the field.

Weaknesses:

The following points should be addressed to support the conclusions of the manuscript.

1) It would be essential to investigate whether P053 treatment of young mice induces age-dependent features besides muscle loss, such as muscle fibrosis or regeneration. This would help determine whether the exacerbation of age-dependent features solely depends on Cers1 inhibition or is associated with other factors related to age-dependent decline in cell function. Additionally, considering the reported role of Cers1 in whole-body adiposity, it is necessary to present data on mice body weight and fat mass in P053-treated aged-mice.

2) As grip and exercise performance tests evaluate muscle function across several muscles, it is not evident how intramuscular AAV-mediated Cers1 inhibition solely in the gastrocnemius muscle can have a systemic effect or impact different muscles. This point requires clarification.

3) To further substantiate the role of Cers1 in myogenesis, it would be crucial to investigate the consequences of Cers1 inhibition under conditions of muscle damage, such as cardiotoxin treatment or eccentric exercise.

4) It would be informative to determine whether the muscle defects are primarily dependent on the reduction of C18-ceramides or the compensatory increase of C24-ceramides or C24-dihydroceramides.

5) Previous studies from the research group (PMID 37118545) have shown that inhibiting the de novo sphingolipid pathway by blocking SPLC1-3 with myriocin counteracts muscle loss and that C18-ceramides increase during aging. In light of the current findings, certain issues need clarification and discussion. For instance, how would myriocin treatment, which reduces Cers1 activity because of the upstream inhibition of the pathway, have a positive effect on muscle? Additionally, it is essential to explain the association between the reduction of Cers1 gene expression with aging (Fig. 1B) and the age-dependent increase in C18-ceramides (PMID 37118545).

Addressing these points will strengthen the manuscript's conclusions and provide a more comprehensive understanding of the role of Cers1 in skeletal muscle function during aging.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, Nie et al investigate the effect of PARG KO and PARG inhibition (PARGi) on pADPR, DNA damage, cell viability, and synthetic lethal interactions in HEK293A and Hela cells. Surprisingly, the authors report that PARG KO cells are sensitive to PARGi and show higher pADPR levels than PARG KO cells, which are abrogated upon deletion or inhibition of PARP1/PARP2. The authors explain the sensitivity of PARG KO to PARGi through incomplete PARG depletion and demonstrate complete loss of PARG activity when incomplete PARG KO cells are transfected with additional gRNAs in the presence of PARPi. Furthermore, the authors show that the sensitivity of PARG KO cells to PARGi is not caused by NAD depletion but by S-phase accumulation of pADPR on chromatin coming from unligated Okazaki fragments, which are recognized and bound by PARP1. Consistently, PARG KO or PARG inhibition shows synthetic lethality with Pol beta, which is required for Okazaki fragment maturation. PARG expression levels in ovarian cancer cell lines correlate negatively with their sensitivity to PARGi.

Strengths:<br /> The authors show that PARG is essential for removing ADP-ribosylation in S-phase.

Weaknesses:<br /> 1) This begs the question as to the relevant substrates of PARG in S-phase, which could be addressed, for example, by analysing PARylated proteins associated with replication forks in PARG-depleted cells (EdU pulldown and Af1521 enrichment followed by mass spectrometry).<br /> 2) The results showing the generation of a full PARG KO should be moved to the beginning of the Results section, right after the first Results chapter (PARG depletion leads to drastic sensitivity to PARGi), otherwise, the reader is left to wonder how PARG KO cells can be sensitive to PARGi when there should be presumably no PARG present.<br /> 3) Please indicate in the first figure which isoforms were targeted with gRNAs, given that there are 5 PARG isoforms. You should also highlight that the PARG antibody only recognizes the largest isoform, which is clearly absent in your PARG KO, but other isoforms may still be produced, depending on where the cleavage sites were located.<br /> 4) FACS data need to be quantified. Scatter plots can be moved to Supplementary while quantification histograms with statistical analysis should be placed in the main figures.<br /> 5) All colony formation assays should be quantified and sensitivity plots should be shown next to example plates.<br /> 6) Please indicate how many times each experiment was performed independently and include statistical analysis.

Reviewer #2 (Public Review):

This paper explores how minimal active matter simulations can model tissue rheology, with applications to the in vivo situation of zebrafish morphogenesis. The authors explore the idea of active noise, particle softness and size heterogeneity cooperating to give rise to surprising features of experimental tissue rheologies (in particular an increase and then a plateau in viscosity with fluid fraction). In general, the paper is interesting from a theoretical standpoint, by providing a bridge between concepts from jamming of particulate systems and experiments in developmental biology. The idea of exploring a free space picture in this context is also interesting. However, I'm still unsure right now though of how much it can be applied to the specific system that the authors refer to - which could be fixed either by doing theoretical checks or considering other experimental systems/models reported in the recent literature.

Reviewer #2 (Public Review):

The authors investigate the origin of asexual reproduction through hybridization between species. In loaches, diploid, polyploid, and asexual forms have been described in natural populations. The authors experimentally cross multiple species of loaches and conduct an impressively detailed characterization of gametogenesis using molecular cytogenetics to show that although meiosis arrests early in male hybrids, a subset of cells in females undergo endoreplication before meiosis, producing diploid eggs. This only occurred in hybrids of parental species that were of intermediate divergence. This work supports an expanding view of speciation where asexuality could emerge during a narrow evolutionary window where genomic divergence between species is not too high to cause hybrid inviability, but high enough to disrupt normal meiotic processes.

I enjoyed reading this study and I was impressed by the rigorous experiments. The authors provide strong evidence that premeiotic genome endoreplication is the mechanism behind asexually-reproducing females. In addition, I found the evidence convincing that this phenomenon is a consequence of combining two divergent genomes in an F1 hybrid female. The authors did not observe a single incidence of genome duplication in any of the parental species among a large number of surveyed oocytes.

Reviewer #2 (Public Review):

Summary:<br /> The authors study through theory and simulations the diffusion of microscopic particles and aim to account for the effects of inhomogeneous viscosity and diffusion - in particular regarding the intracellular environment. They propose a mechanism, termed "Diffusive lensing", by which particles are attracted towards high-viscosity regions where they remain trapped. To obtain these results, the authors rely on agent-based simulations using custom rules performed with the Ito stochastic calculus convention, without spurious drift. They acknowledge the fact that this convention does not describe equilibrium systems, and that their results would not hold at equilibrium - and discard these facts by invoking the fact that cells are out-of-equilibrium. Finally, they show some applications of their findings, in particular enhanced clustering in the high-viscosity regions. The authors conclude that as inhomogeneous diffusion is ubiquitous in life, so must their mechanism be, and hence it must be important.

Strengths:<br /> The article is well-written, and clearly intelligible, its hypotheses are stated relatively clearly and the models and mathematical derivations are compatible with these hypotheses.

Weaknesses:<br /> The main problem of the paper is these hypotheses. Indeed, it all relies on the Ito interpretation of the stochastic integrals. Stochastic conventions are a notoriously tricky business, but they are both mathematically and physically well-understood and do not result in any "dilemma" [some citations in the article, such as (Lau and Lubensky) and (Volpe and Wehr), make an unambiguous resolution of these]. Conventions are not an intrinsic, fixed property of a system, but a choice of writing; however, whenever going from one to another, one must include a "spurious drift" that compensates for the effect of this change - a mathematical subtlety that is entirely omitted in the article: if the drift is zero in one convention, it will thus be non-zero in another in the presence of diffusive gradients. It is well established that for equilibrium systems obeying fluctuation-dissipation, the spurious drift vanishes in the anti-Ito stochastic convention (which is not "anticipatory", contrarily to claims in the article, are the "steps" are local and infinitesimal). This ensures that the diffusion gradients do not induce currents and probability gradients, and thus that the steady-state PDF is the Gibbs measure. This equilibrium case should be seen as the default: a thermal system NOT obeying this law should warrant a strong justification (for instance in the Volpe and Wehr review this can occur through memory effects in robotic dynamics, or through strong fluctuation-dissipation breakdown). In near-equilibrium thermal systems such as the intracellular medium (where, although out-of-equilibrium, temperature remains a relevant and mostly homogeneous quantity), deviations from this behavior must be physically justified and go to zero when going towards equilibrium.

Here, drifts are arbitrarily set to zero in the Ito convention (the exact opposite of the equilibrium anti-Ito), which is the equilibrium equivalent to adding a force (with drift $- grad D$) exactly compensating the spurious drift. If we were to interpret this as a breakdown of detailed balance with inhomogeneous temperature, the "hot" region would be effectively at 4x higher temperature than the cold region (i.e. 1200K) in Fig 1A.

It is the effects of this arbitrary force (exactly compensating the Ito spurious drift) that are studied in the article. The fact that it results in probability gradients is trivial once formulated this way (and in no way is this new - many of the references, for instance, Volpe and Wehr, mention this). Enhanced clustering is also a trivial effect of this probability gradient (the local concentration is increased by this force field, so phase separation can occur). As a side note the "neighbor sensing" scheme to describe interactions is very peculiar and not physically motivated - it violates stochastic thermodynamics laws too, as the detailed balance is apparently not respected. Finally, the "anomalous diffusion" discussion is at odds with what the literature on this subject considers anomalous (the exponent does not appear anomalous).

The authors make no further justification of their choice of convention than the fact that cells are out-of-equilibrium, leaving the feeling that this is a detail. They make mentions of systems (eg glycogen, prebiotic environment) for which (near-)equilibrium physics should mostly prevail, and of fluctuation-dissipation ("Diffusivity varies inversely with viscosity", in the introduction). Yet the "phenomenon" they discuss is entirely reliant on an undiscussed mechanism by which these assumptions would be completely violated (the citations they make for this - Gnesotto '18 and Phillips '12 - are simply discussions of the fact that cells are out-of-equilibrium, not on any consequences on the convention).

Finally, while inhomogeneous diffusion is ubiquitous, the strength of this effect in realistic conditions is not discussed (this would be a significant problem if the effect were real, which it isn't). Gravitational attraction is also an ubiquitous effect, but it is not important for intracellular compartmentalization.

To conclude, the "diffusive lensing" effect presented here is not a deep physical discovery, but a well-known effect of sticking to the wrong stochastic convention.

Reviewer #2 (Public Review):

Summary:<br /> In the manuscript by Luo et al, the authors investigated the nature and function of TRAIL-HS binding for the regulation of TRAIL-mediated apoptosis in cancer cells. The authors discovered that TRAIL binds to 12mer HS and identified the amino acid residues critical for the binding. The authors further nicely showed that 12mer HS binds to TRAIL homotrimer and larger HS can further promote the formation of larger TRAIL oligomers. Structural analyses were conducted to characterize the binding of TRAIL/HS complexes. At functional level, the authors demonstrated that HS promotes the cell surface binding of TRAIL to enhance TRAIL-mediated apoptosis in a variety of cancer cells. Moreover, the ability of TRAIL to induce apoptosis is correlated with cell surface HS level. Lastly, the authors showed that HS forms complex with TRAIL and its receptor DR5 and promotes DR5 internalization.

Strengths:<br /> Overall, this is a nicely executed study providing both mechanistic and functional insight for TRAIL-mediated apoptosis. It conducted detailed characterization on the direct binding between HS and TRAIL and provided solid evidence supporting the role of such interaction for the regulation of TRAIL-induced apoptosis. The experiments were well-designed with proper controls included. The data interpretation is accurate. The manuscript was clearly written and easy to follow by general readers.

Weaknesses:<br /> There is no major weakness identified from this study. However, the role of HS for the formation of TRAIL homotrimer needs to be further clarified. In addition, the current relationship between cell surface HS level and sensitivity to TRAIL-mediated apoptosis is still correlative, as the authors indicated. Additional evidence to support the regulatory function of HS would further strengthen the significance of the study.

Reviewer #2 (Public Review):

Summary:<br /> In the manuscript by Chiu et al., "Structure and dynamics of cholesterol-mediated aquaporin-0 arrays and implications for lipid rafts," the authors address the effect of cholesterol on array formation by AQP0. Using a combination of electron crystallography and molecular dynamics simulations, the authors show binding of a "deep" cholesterol molecule between AQP0 tetramers. Each AQP0 tetramers binds four deep cholesterols to form a crystallographic array of AQP0.

Strengths:<br /> The combined approaches of electron crystallography and MD simulations under different lipid conditions (different sphingomyelin and cholesterol concentrations) are a strength of the study. The authors provide a thorough and convincing assessment of cholesterol binding, protein-protein interactions, and array formation by AQP0. The MD simulations allow the authors to consider the propensity of cholesterol to occupy the observed binding sites in the absence of crystal contacts. The combined methods and the breadth of analyses set a high standard in the field of membrane protein structural biology.

The findings of the authors fit nicely into a growing body of literature on cholesterol binding sites that mediate membrane protein-protein interactions. Cholesterol interacts with a variety of membrane proteins via its smooth alpha face of rough beta face. AQP0 is somewhat unique in that it binds the rough face of cholesterol in a "deep" binding site that places cholesterol in the middle of the membrane bilayer. So-called "deep" cholesterol binding sites have been described for GPCRs and docking studies suggest they may exist on other ion channels and transporters. In the case of AQP0, the deep cholesterol acts as a glue that holds two tetramers together. Since each tetramer has four binding sites for deep cholesterol, the assembly and mechanical stability of an extended two-dimensional array of AQP0 tetramers is a natural consequence in lens membranes.

Weaknesses:<br /> The authors report that the findings generally apply to raft formation in membranes. However, this point is less clear as the lens membrane in which AQP0 resides is rather unique in lipid and protein content and density. Nonetheless, the authors achieve the overall goal of evaluating cholesterol binding to AQP0, and there are many valuable and informative figures in the main manuscript and supplement that provide convincing results and interpretations.

Reviewer #2 (Public Review):

Summary:<br /> Pulfer A. et al. developed a deep learning-based apoptosis detection system named ADeS, which outperforms the currently available computational tools for in vitro automatic detection. Furthermore, ADeS can automatically identify apoptotic cells in vivo in intravital microscopy time-lapses, preventing manual labeling with potential biases. The authors trained and successfully evaluated ADeS in packed epithelial monolayers and T cells distributed in 3D collagen hydrogels. Moreover, in vivo, training and evaluation were performed on polymorphonucleated leukocytes in lymph nodes and spleen.

Strengths:<br /> Pulfer A. et colleagues convincingly presented their results, thoroughly evaluated ADeS for potential toxicity assay, and compared its performance with available state-of-the-art tools.

Weaknesses:<br /> The use of ADeS is still restricted to samples where cells are fluorescently labeled either in the cytoplasm or in the nucleus, which limits its use for in vitro toxicity assays that are performed on primary cells or organoids (e.g., iPSCs-derived systems) that are normally harder to transfect. In conclusion, ADeS will be a useful tool to improve output quality and accelerate the evaluation of assays in several research areas with basic and applied aims.

Reviewer #2 (Public Review):

Summary:<br /> The objective of authors using metabolomics analysis of primary angle closure glaucoma (PACG) is to demonstrate that serum androstenedione is a novel biomarker that can be used to diagnose PACG and predict visual field progression.

Strengths:<br /> Use of widely targeted and untargeted metabolite detection conditions. Use of liquid chromatography-tandem mass spectrometry and a chemiluminescence method for confirmation of androstenedione.

Weaknesses:<br /> The "predict" part is on much less solid ground. The visual field progression and association with serum androstenedione within the current experimental design eludes to a correlation. It truly cannot be stated as predictive. To predict one needs to put the substance when nothing is there and demonstrate that the desired endpoint is reached. Conversely, the substance (androstenedione) can be removed, and show that the condition regresses. None of these are possible without model system experiments, which have not been done. The authors could put some additional details in the methods, such as: 1) how much sample was collected, 2) whether equal serum volume for analysis had equal serum proteins (or cells). They have used a LC-MS/MS and a Chemiluminescence method, but another independent method such as GC-MS/MS or NMR to detect androstenedione for a subset of patients with different stages of visual field defect would be desirable.

Reviewer #2 (Public Review):

Summary:<br /> Zhao et al. aimed to explore an important question - how to overcome the resistance of hepatocellular carcinoma cells to radiotherapy? Given that the immune-suppressive microenvironment is a major mechanism underlying resistance to radiotherapy, they reasoned that a drug that blocks the PD-1/PD-L1 pathway could improve the efficacy of radiation therapy and chose to investigate the effect of Nifuroxazide, an inhibitor of stat3 activation, on radiotherapy efficacy in treating hepatocellular carcinoma cells. From in vitro experiments, they find combination treatment (Nifuroxazide+ radiotherapy) increases apoptosis and reduces proliferation and migration, in comparison to radiotherapy alone. From in vivo experiments, they demonstrate that combined treatment reduces the size and weight of tumors in vivo and enhances mice survival. These data indicate a better efficacy of combination therapy compared to radiotherapy alone. Moreover, they also determined the effect of combination therapy on tumor microenvironment as well as peripheral immune response. They find that combination therapy increases infiltration of CD4+ and CD8+ cells as well as M1 macrophages in the tumor microenvironment. Interestingly, they find that the ratio of Treg cells in spleen is increased by radiotherapy but decreased by Nifuroxazide. Considering the immune-suppressive role of Treg cells, this finding is consistent with reduced tumor growth by combination therapy. However, it is unclear whether the combined therapy affects the ratio of Treg cells in the tumors or not. The most intriguing part of the study is the determination of the effect of Nifuroxazide on PD-L1 expression in the context of radiotherapy. Considering Nifuroxazide is a stat3 activation inhibitor and stat3 inhibition leads to reduced expression of PD-L1, one would expect Nifuroxazide decreases PD-L1 expression through stat3. However, they found that the effect of Nifuroxazide on PD-L1 is dependent on GSK3 mediated Proteasome pathways and independent of stat3, in the given experimental context. To determine the relevance to human hepatocellular carcinoma, they also measured the PD-L1 expression in human tumor tissues of HCC patients pre- and post-radiotherapy. The increased PD-L1 expression level in HCC after radiotherapy is impressive. However, it is unclear whether the patients being selected in the study had resistant disease to radiotherapy or not.

Overall, the data are convincing and supportive to the conclusions.

Strengths:<br /> 1) Novel finding: Identified novel mechanism underlying the effect of Nifuroxazide on PD-L1 expression in hepatocellular carcinoma cells in the context of radiotherapy.<br /> 2) Comprehensive experimental approaches: using different approaches to prove the same finding. For example, in Fig 4, both IHC and WB were used. In Fig 5, both IF and WB were used.<br /> 3) Human disease relevance: Compared observations in mice with human tumor samples.

Weaknesses:<br /> 1. It is hard to tell whether the observed phenotype and mechanism are generic or specific to the limited cell lines used in the study. The in vitro experiments were performed in one human cell line and the in vivo experiments were performed in one mouse cell line.<br /> 2. The study did not distinguish the effect of increased radiosensitivity by nifuroxazide from combined anti-tumor effects by two different treatments.

Reviewer #2 (Public Review):

Summary:<br /> The authors have taken their previous finding that arpin is important for epithelial junctions and extended this to endothelial cells. They find that the positive effects of arpin on endothelial junctions are not dependent on Arp2/3 activity but instead on suppression of actinomyosin contractility.

Strengths:<br /> The study uses standard approaches to test each of the components in the model. The quality of the experimental work is good and the amount of experimental evidence is sufficient to support this straightforward story.

Weaknesses:<br /> The major weakness is that the story is a simple extension of the previous work on arpin and junctions in epithelial cells. The additional information is that the effects are not via Arp2/3 directly, but instead through an increase in actinomyosin contractility. However, the connection between arpin and increased ROCK activity is not revealed.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript by Hadebe and colleagues describes a striking reduction in airway hyperresponsiveness in Igm-deficient mice in response to HDM, OVA and papain across the B6 and BALB-c backgrounds. The authors suggest that the deficit is not due to improper type 2 immune responses, nor an aberrant B cell response, despite a lack of class switching in these mice. Through RNA-Seq approaches, the authors identify few differences between the lungs of WT and Igm-deficient mice, but see that two genes involved in actin regulation are greatly reduced in IgM-deficient mice. The authors target these genes by CRISPR-Cas9 in in vitro assays of smooth muscle cells to show that these may regulate cell contraction. While the study is conceptually interesting, there are a number of limitations, which stop us from drawing meaningful conclusions.

Strengths:<br /> Fig. 1. The authors clearly show that IgMKO mice have striking reduced AHR in the HDM model, despite the presence of a good cellular B cell response.

Weaknesses:<br /> Fig. 2.<br /> The authors characterize the cd4 t cell response to HDM in IGMKO mice.<br /> They have restimulated medLN cells with antiCD3 for 5 days to look for IL-4 and IL-13, and find no discernible difference between WT and KO mice. The absence of PBS-treated WT and KO mice in this analysis means it is unclear if HDM-challenged mice are showing IL-4 or IL-13 levels above that seen at baseline in this assay. The choice of 5 days is strange, given that the response the authors want to see is in already primed cells. A 1-2 day assay would have been better. It is concerning that the authors state that HDM restimulation did not induce cytokine production from medLN cells, since countless studies have shown that restimulation of medLN would induce IL-13, IL-5 and IL-10 production from medLN. This indicates that the sensitization and challenge model used by the authors is not working as it should. The IL-13 staining shown in panel c is also not definitive. One should be able to optimize their assays to achieve a better level of staining, to my mind.

In d-f, the authors perform a serum transfer, but they only do this once. The half life of IgM is quite short. The authors should perform multiple naïve serum transfers to see if this is enough to induce FULL AHR.

The presence of negative values of total IgE in panel F would indicate some errors in calculation of serum IgE concentrations.

Overall, it is hard to be convinced that IgM-deficiency does not lead to a reduction in Th2 inflammation, since the assays appear suboptimal.

Fig. 3. Gene expression differences between WT and KO mice in PBS and HDM challenged settings are shown. PCA analysis does not show clear differences between all four groups, but genes are certainly up and downregulated, in particular when comparing PBS to HDM challenged mice. In both PBS and HDM challenged settings, three genes stand out as being upregulated in WT v KO mice. these are Baiap2l1, erdr1 and Chil1.

Fig. 4. The authors attempt to quantify BAIAP2L1 in mouse lungs. It is difficult to know if the antibody used really detects the correct protein. A BAIAP2L1-KO is not used as a control for staining, and I am not sure if competitive assays for BAIAP2L1 can be set up. The flow data is not convincing. The immunohistochemistry shows BAIAP2L1 (in red) in many, many cells, essentially throughout the section. There is also no discernible difference between WT and KO mice, which one might have expected based on the RNA-Seq data. So, from my perspective, it is hard to say if/where this protein is located, and whether there truly exists a difference in expression between wt and ko mice.

Fig. 5 and 6. The authors use a single cell contractility assay to measure whether BAIAP2L1 and ERDR1 impact on bronchial smooth muscle cell contractility. I am not familiar with the assay, but it looks like an interesting way of analysing contractility at the single cell level.<br /> The authors state that targeting these two genes with Cas9gRNA reduces smooth muscle cell contractility, and the data presented for contractility supports this observation. However, the efficiency of Cas9-mediated deletion is very unclear. The authors present a PCR in supp fig 9c as evidence of gene deletion, but it is entirely unclear with what efficiency the gene has been deleted. One should use sequencing to confirm deletion. Moreover, if the antibody was truly working, one should be able to use the antibody used in Fig 4 to detect BAIAP2L1 levels in these cells. The authors do not appear to have tried this.

Other impressions:<br /> The paper is lacking a link between the deficiency of IgM and the effects on smooth muscle cell contraction.<br /> The levels of IL-13 and TNF in lavage of WT and IGMKO mice could be analysed.

Moreover, what is the impact of IgM itself on smooth muscle cells? In the Fig. 7 schematic, are the authors proposing a direct role for IgM on smooth muscle cells? Does IgM in cell culture media induce contraction of SMC? This could be tested and would be interesting, to my mind.

Reviewer #2 (Public Review):

In this study by Jing, Fooksman, and colleagues, a Blimp1-CreERT2-based genetic tracing study is employed to label plasma cells. Over the course of several months post-tamoxifen treatment, the only remaining labeled cells are long-lived plasma cells. This system provides a way to sort live long-lived plasma cells and compare them to unlabeled plasma cells, which contain a range of short-to-long-lived cells. From this analysis, several observations are made: 1) the turnover rate of plasma cells is greater in the spleen than in the bone marrow; 2) the turnover rate is highest early in life; 3) subtle transcriptional and cell surface marker differences distinguish long- from shorter-lived plasma cells; 4) long-lived plasma cells in the bone marrow are sessile and localize in clusters with each other; 5) CXCR4 is required for plasma cell retention in these clusters and in the bone marrow; 6) Repertoire analysis hints that the selection of long-lived plasma cells is not random for any cell that lands in the bone marrow.

Strengths:

1) The genetic timestamping approach is a clever and functional way to separate plasma cells of differing longevities.

2) This approach led to the identification of several markers that could help prospective separation of long-lived plasma cells from others.

3) Functional labeling of long-lived plasma cells allowed for a higher resolution analysis of transcriptomes and motility than was previously possible.

4) The genetic system allowed for a revisitation of the importance of CXCR4 in plasma cell retention and survival.

Weaknesses:

1) Most of the labeling studies, likely for practical reasons, were done on polyclonal rather than antigen-specific plasma cells. The triggers of these responses could vary based on age at the time of exposure, anatomical sites, etc. How these differences might influence markers and transcriptomes, independently of longevity, is not completely known.

2) The fraction of long-lived plasma cells in the unlabeled fraction varies with age, potentially diluting differences between long- and short-lived plasma cells.

3) The authors suggest their data favors a model by which plasma cells compete for niche space. Yet there is no evidence presented here that these niches are limiting.

4) The functional importance of the observed transcriptome differences between long- and shorter-lived plasma cells is unknown. An assessment as to whether these differences are conserved in human long- and short-lived bone marrow plasma cells might provide circumstantial supporting evidence that these changes are important for longevity.

Reviewer #2 (Public Review):

This study investigates T-cell repertoire responses in a mouse model with a transgenic beta chain, such that all T-cells in all mice share a fixed beta chain, and repertoire diversity is determined solely by alpha chain rearrangements. Each mouse is exposed to one of a few distinct immune challenges, sacrificed, and T-cells are sampled from multiple tissues. FACS is used to sort CD4 and Treg cell populations from each sample, and TCR repertoire sequencing from UMI-tagged cDNA is done.

Various analyses using repertoire diversity, overlap, and clustering are presented to support several principal findings: 1) TCR repertoires in this fixed beta system have highly distinct clonal compositions for each immune challenge and each cell type, 2) these are highly consistent across mice, so that mice with shared challenges have shared clones, and 3) induction of CD4-to-Treg cell type transitions is challenge-specific.

The beta chain used for this mouse model was previously isolated based on specificity for Ovalbumin. Because the beta chain is essential for determining TCR antigen specificity, and is highly diverse in wildtype mice, I found it surprising that these mice are reported to have robust and consistently focused clonal responses to very diverse immune challenges, for which a fixed OVA-specific beta chain is unlikely to be useful. The authors don't comment on this aspect of their findings, but I would think it is not expected *a priori* that this would work. If this does work as reported, it is a valuable model system: due to massively reduced diversity, the TCR repertoire response is much more stereotyped across individual samples, and it is much easier to detect challenge-specific TCRs via the statistics of convergent responses.

While the data and analyses present interesting signals, they are flawed in several ways that undermine the reported findings. I summarize below what I think are the most substantive data and analysis issues.

1. There may be systematic inconsistencies in repertoire sampling depth that are not described in the manuscript. Looking at the supplementary tables (and making some plots), I found that the control samples (mice with mock challenge) have consistently much shallower sampling-in terms of both read count and UMI count-compared with the other challenge samples. There is also a strong pattern of lower counts for Treg vs CD4 cell samples within each challenge.

2. FACS data are not reported. Although the graphical abstract shows a schematic FACS plot, there are no such plots in the manuscript. Related to the issue above, it would be important to know the FACS cell counts for each sample.

3. For diversity estimation, UMI-wise downsampling was performed to normalize samples to 1000 random UMIs, but this procedure is not validated (the optimal normalization would require downsampling cells). What is the influence of possible sampling depth discrepancies mentioned above on diversity estimation? All of the Treg control samples have fewer than 1000 total UMIs-doesn't that pose a problem for sampling 1000 random UMIs? Indeed, I simulated this procedure and found systematic effects on diversity estimates when taking samples of different numbers of cells (each with a simulated UMI count) from the same underlying repertoire, even after normalizing to 1000 random UMIs. I don't think UMI downsampling corrects for cell sampling depth differences in diversity estimation, so it's not clear that the trends in Fig 1A are not artifactual-they would seem to show higher diversity for control samples, but these are the very same samples with an apparent systematic sampling depth bias.

4. The Figures may be inconsistent with the data. I downloaded the Supplementary Table corresponding to Fig 1 and made my own version of panels A-C. This looked quite different from the diversity estimations depicted in the manuscript. The data does not match the scale or trends shown in the manuscript figure.

5. For the overlap analysis, a different kind of normalization was performed, but also not validated. Instead of sampling 1000 UMIs, the repertoires were reduced to their top 1000 most frequent clones. It is not made clear why a different normalization would be needed here. There are several samples (including all Treg control samples) with only a couple hundred clones. It's also likely that the noted systematic sampling depth differences may drive the separation seen in MDS1 between Treg and CD4 cell types. I also simulated this alternative downsampling procedure and found strong effects on MDS clustering due to sampling effects alone.

It is not made clear how the overlap scores were converted to distances for MDS. It's hard to interpret this without seeing the overlap matrix.

6. The cluster analysis is superficial, and appears to have been cherry-picked. The clusters reported in the main text have illegibly small logo plots, and no information about V/J gene enrichments. More importantly, as the caption states they were chosen from the columns of a large (and messier-looking) cluster matrix in the supplementary figure based on association with each specific challenge. There's no detail about how this association was calculated, or how it controlled for multiple tests. I don't think it is legitimate to simply display a set of clusters that visually correlate; in a sufficiently wide random matrix you will find columns that seem to correlate with any given pattern across rows.

7. The findings on differential plasticity and CD4 to Treg conversion are not supported. If CD4 cells are converting to Tregs, we expect more nucleotide-level overlap of clones. This intuition makes sense. But it seems that this section affirms the consequent: variation in nucleotide-level clone overlap is a readout of variation in CD4 to Treg conversion. It is claimed, based on elevated nucleotide-level overlap, that the LLC and PYMT challenges induce conversion more readily than the other challenges. It is not noted in the textual interpretations, but Fig 4 also shows that the control samples had a substantially elevated nucleotide-level overlap. There is no mention of a null hypothesis for what we'd expect if there was no induced conversion going on at all. This is a reduced-diversity mouse model, so convergent recombination is more likely than usual, and the challenges could be expected to differ in the parts of TCR sequence space they induce focus on. They use the top 100 clones for normalization in this case, but don't say why (this is the 3rd distinct normalization procedure).

Although interpretations of the reported findings are limited due to the issues above, this is an interesting model system in which to explore convergent responses. Follow-up experimental work could validate some of the reported signals, and the data set may also be useful for other specific questions.

Reviewer #2 (Public Review):

Summary:<br /> The authors have developed a Myoscreen platform, which is a scalable and physiologically relevant system for generating and characterizing patient-derived myotubes. The platform can be used to accurately predict the DMD disease phenotype in a disease-relevant cell type and has wide applications in the drug development process.

Strengths:<br /> The Myoscreen platform is scalable, meaning that it can be used to generate and characterize a large number of patient-derived myotubes. This is important for drug discovery, as it allows researchers to test a wider range of potential treatments. The Myoscreen platform also uses a physiologically relevant system for generating and characterizing myotubes. This means that the results obtained from the platform are more likely to be relevant to the human disease. This compared for example to using C2C12 myotubes. The Myoscreen platform has been shown to be effective in predicting the DMD disease phenotype. This means that it can be used to identify potential treatments that are likely to be effective in patients with DMD.

Weaknesses:<br /> The study has several limitations. The method and material section could be improved. The authors rely heavily on UMAP to identify differences between non-DMD and DMD donor myotubes. They do not validate their findings using pharmacological small drugs. Additionally, the biological replicates used are extremely low, which raises concerns about the reproducibility of the findings.

Reviewer #2 (Public Review):

Summary:<br /> The paper by Kuhn and colleagues follows upon a 2022 paper in which they identified residues in CD4 constrained by evolutionary purifying selection in placental mammals and then performed functional analyses of these conserved sequences. They showed that sequences distinct from the CXC "clamp" involved in recruitment of Lck have critical roles in TCR signaling, and these include a glycine-rich motif in the transmembrane (TM) domain and the cys-containing juxtamembrane (JM) motif that undergoes palmitoylation, both of which promote TCR signaling, and a cytoplasmic domain helical motif, also involved in Lck binding, that constrains signaling. Mutations in the transmembrane and juxtamembrane sequences led to reduced proximal signaling and IL-2 production in a hybridoma's response to antigen presentation, despite retention of abundant CD4 association with Lck in the detergent-soluble membrane fraction, presumably mislocalized outside of lipid rafts and distal to the TCR. A major conclusion of that study was that CD4 sequences required for Lck association, including the CXC "clasp" motif, are not as consequential for CD4 co-receptor function in TCR signaling as the conserved TM and JM motifs. However, the experiments did not determine whether the functions of the TM and JM motifs are dependent on the Lck-binding properties of CD4 - the mutations in those motifs could result in free Lck redistributing to associate with CD4 in signaling-incompetent membrane domains or could function independently of CD4-Lck association. The current study addresses this specific question.

Using the same model system as in the earlier paper (the entire methods section is a citation to the earlier paper), the authors show that truncation of the Lck-binding intracellular domain resulted in a moderate reduction in IL-2 response, as previously shown, but there was no apparent effect on proximal phosphorylation events (CD3z, Lck, ZAP70, PLCg1). They then evaluated a series of TM and JM motif mutations in the context of the truncated Lck-nonbinding molecule, and showed that these had substantially impaired co-receptor function in the IL-2 assay and reduced proximal signaling. The proximal signaling could be observed at high ligand density even with a MHC non-binding mutation in CD4, although there was still impaired IL-2 production. This result additionally illustrates that phosphorylation of the proximal signaling molecules is not sufficient to activate IL-2 expression in the context of antigen presentation.

Strengths:<br /> The strength of the paper is the further clear demonstration that the classical model of CD4 co-receptor function (MHCII-binding CD4 bringing Lck to the TCR complex, for phosphorylation of the CD3 chain ITAMs and of the ZAP70 kinase) is not sufficient to explain TCR activation. The data, combined with the earlier paper, further implicate the gly-rich TM sequence and the palmitoylation targets in the JM region as having critical roles in productive co-receptor-dependent TCR activation.

Weaknesses:<br /> The major weakness of the paper is the lack of mechanistic insight into how the TM and JM motifs function. The new results are largely incremental in light of the earlier paper from this group as well as other literature, cited by the authors, that implicates "free" Lck, not associated with co-receptors, as having the major role in TCR activation. It is clear that the two motifs are important for CD4 function at low pMHCII ligand density. The proposal that they modulate interactions of TCR complex with cholesterol or other membrane lipids is an interesting one, and it would be worth further exploring by employing approaches that alter membrane lipid composition. The JM sequence presumably dictates localization within the membrane, by way of palmitoylation, which may be critical to regulate avidity of the TCR:CD4 complex for pMHCII or TCR complex allosteric effects that influence the activation threshold. Experiments that explore the basis of the mutant phenotype could substantially enhance the impact of this study.

Reviewer #2 (Public Review):

Summary: This paper investigates the role of motor practice and sensory feedback when a motor action returns to a learned or established baseline. Adult male zebra finches perform a stereotyped, learned vocalization (song). It is possible to shift the pitch of particular syllables away from the learned baseline pitch using contingent white noise reinforcement. When the reinforcement is stopped, birds will return to their baseline over time. During the return, they often sing hundreds of renditions of the song. However, whether motor action, sensory feedback, or both during singing is necessary to return to baseline is unknown.

Previous work has shown that there is covert learning of the pitch shift. If the output of a song plasticity pathway is blocked during learning, there is no change in pitch during the training. However, as soon as the pathway is unblocked, the pitch immediately shifts to the target location, implying that there is learning of the shift even without performance. Here, they ask whether the return to baseline from such a pitch shift also involves covert or overt learning processes. They perform a series of studies to address these questions, using muting and deafening of birds at different time points. learning.

Strengths: The overall premise is interesting and the use of muting and deafening to manipulate different aspects of motor practice vs. sensory feedback is a solid approach.

Weaknesses: One of the main conclusions, which stems primarily from birds deafened after being pitch-shifted using white noise (WNd) birds in comparison to birds deafened before being pitch-shifted with light as a reinforcer (LOd), is that recent auditory experience can drive motor plasticity even when an individual is deprived of such experience. While the lack of shift back to baseline pitch in the LOd birds is convincing, the main conclusion hinges on the responses of just a few WNd individuals who are closer to baseline in the early period. Moreover, only 2 WNd individuals reached baseline in the late period, though neither of these were individuals who were closer to baseline in the early phase. Most individuals remain or return toward the reinforced pitch. These data highlight that while it may be possible for previous auditory experience during reinforcement to drive motor plasticity, the effect is very limited. Importantly, it's not clear if there are other explanations for the changes in these birds, for example, whether there are differences in the number of renditions performed or changes to other aspects of syllable structure that could influence measurements of pitch.

While there are examples where the authors perform direct comparisons between particular manipulations and the controls, many of the statistical analyses test whether each group is above or below a threshold (e.g. baseline) separately and then make qualitative comparisons between those groups. Given the variation within the manipulated groups, it seems especially important to determine not just whether these are different from the threshold, but how they compare to the controls. In particular, a full model with time (early, late), treatment (deafened, muted, etc), and individual ID (random variable) would substantially strengthen the analysis.

The muted birds seem to take longer to return to baseline than controls even after they are unmuted. Presumably, there is some time required to recover from surgery, however, it's unclear whether muting has longer-term effects on syrinx function or the ability to pass air. In particular, it's possible that the birds still haven't recovered by 4 days after unmuting as a consequence of the muting and unmuting procedure or that the lack of recovery is indicative of an additional effect that muting has on pitch recovery. For example, the methods state that muted birds perform some quiet vocalizations. However, if birds also attempt to sing, but just do so silently, perhaps the aberrant somatosensory or other input from singing while muted has additional effects on the ability to regain pitch. It would also be useful to know if there is a relationship between how long they are muted and how quickly they return to baseline.

Reviewer #2 (Public Review):

Erk2 is an essential element of the MAP kinase signaling cascade and directly controls cell proliferation, migration, and survival. Therefore, it is one of the most important drug targets for cancer therapy. The catalytic subunit of Erk2 has a bilobal architecture, with the small lobe harboring the nucleotide-binding pocket and the large lobe harboring the substrate-binding cleft. Several studies by the Ahn group revealed that the catalytic domain hops between (at least) two conformational states: active (R) and inactive (L), which exchange in the millisecond time scale based on the chemical shift mapping. The R state is a signature of the double phosphorylated Erk2 (2P-Erk2), while the L state has been associated with the unphosphorylated kinase (0P-Erk2). Interestingly, the X-ray structures reveal only minimal differences between these two states, a feature that led to the conclusion that active and inactive states are structurally similar but dynamically very different. The Ahn group also found that ATP-competitive inhibitors can steer the populations of Erk2 either toward the R or the L state, depending on their chemical nature. The latter opens up the possibility of modulating the activity of this kinase by changing the chemistry of the ATP-competitive inhibitor. To prove this point, the authors present a set of nineteen compounds with diverse chemical substituents. From their combined NMR and HDX-Mass Spec analyses, fourteen inhibitors drive the kinase toward the R state, while four compounds keep the kinase hopping between the R and L states. Based on these data, the authors rationalize the effects of these inhibitors and the importance of the nature of the substituents on the central scaffold to steer the kinase activity. While all these inhibitors target the ATP binding pocket, they display diverse structural and dynamic effects on the kinase, selecting a specific structural state. Although the inhibited kinase is no longer able to phosphorylate substrates, it can initiate signaling events functioning as scaffolds for other proteins. Therefore, by changing the chemistry of the inhibitors it may be possible to affect the MAP cascade in a predictable manner. This concept, recently introduced as proof of principle, finds here its significance and practical implications. The design of the next-generation inhibitors must be taken into account for these design principles. The research is well executed, and the data support the author's conclusions.

Reviewer #2 (Public Review):

Summary:

Artificial intelligence (AI) could be useful in some applications and could help humankind. Some forms of AI work on the platform of artificial neural networks (ANN). ANNs are inspired by real brains and real neurons. Therefore understanding the repertoire and logic of real neurons could potentially improve AANs. Cell bodies of real neurons, and axons of real neurons, fire nerve impulses (nerve impulses are very brief ~2 ms, and very tall ~100 mV). Dendrites, which comprise ~80% of the total neuronal membrane (80% of the total neuronal apparatus) typically generate smaller (~50 mV amplitude) but much longer (~100 ms duration) electrical transients, called glutamate-mediated dendritic plateau potentials. The authors have built artificial neurons capable of generating such dendritic plateau potentials, and through computer simulations the authors concluded that long-lasting dendritic signals (plateau potentials) reduce negative impact of temporal jitter occurring in real brain, or in AANs. The authors showed that in AANs equipped with neurons whose dendrites are capable of generating local dendritic plateau potentials, the sparse, yet reliable spiking computations may not require precisely synchronized inputs. That means, the real world can impose notable fluctuations in the network activity and yet neurons could still recognize and pair the related network events. In the AANs equipped with dendritic plateaus, the computations are very robust even when inputs are only partially synchronized. In summary, dendritic plateau potentials endow neurons with ability to hold information longer and connect two events which did not happen at the same moment of time. Dendritic plateaus circumvent the negative impact, which the short membrane time constants arduously inflict on the action potential generation (in both real neurons and model neurons). Interestingly, one of the indirect conclusions of the current study is that neurons equipped with dendritic plateau potentials may reduce the total number of cells (nodes, units) required to perform robust computations.

Strengths:<br /> The majority of published studies are descriptive in nature. Researchers report what they see or measure. A smaller number of studies embark on a more difficult task, which is to explain the logic and rationale of a particular natural design. The current study falls into that second category. The authors first recognize that conduction delays and noise make asynchrony unavoidable in communication between circuits in the real brain. This poses a fundamental problem for the integration of related inputs in real (noisy) world. Neurons with short membrane time constants can only integrate coincident inputs that arrive simultaneously within 2-3 ms of one another. Then the authors considered the role for dendritic plateau potentials. Glutamate-mediated depolarization events within individual dendritic branches, can remedy the situation by widening the integration time window of neurons. In summary, the authors recognized that one important feature of neurons, their dendrites, are built-in to solve the major problems of rapid signal processing: [1] temporal jitter, [2] variation, [3] stochasticity, and [4] reliability of computation. In one word, the dendritic plateau potentials have evolved in the central nervous systems to make rapid CNS computations robust.

Weaknesses:<br /> The authors made some unsupported statements, which should either be deleted, or thoroughly defended in the manuscript. But first of all, the authors failed to bring this study to the readers who are not experts in computational modeling or Artificial Neural Networks. Critical terms (syntax) and ideas have not been explained. For example: [1] binary feature space? [2] 13 dimensions binary vectors? [3] the binary network could still cope with the loss of information due to the binarization of the continuous coordinates? [4] accurate summation?

Reviewer #2 (Public Review):

Summary: The authors aim to learn about retinal cell-specific metabolic pathways, which could substantially improve the way retinal diseases are understood and treated. They culture ex vivo mouse retinas for 6 days with 2 - 4 days of various drug treatments targeting different metabolic pathways or by removing the RPE/choroid tissue from the neural retina. They then look at photoreceptor survival, stain for various metabolic enzymes, and quantify a broad panel of metabolites. While this is an important question to address, the results are not sufficient to support the conclusions.

Strengths: The questions the authors are exploring at extremely valuable and I commend the authors and working to learn more about retina metabolism. The different sensitivity of the cones to various drugs is interesting and may suggest key differences between rods and cones. The authors also provide a thoughtful discussion of various metabolic pathways in the context of previous publications.

Weaknesses: As the authors point out, ex vivo culture models allow for control over multiple aspects of the environment (such as drug delivery) not available in vivo. Ex vivo cultures can provide good hints as to what pathways are available between interacting tissues. However, there are many limitations to ex vivo cultures, including shifting to a very artificial culture media condition that is extremely different than the native environment of the retina. It is well appreciated that cells have flexible metabolism and will adapt to the conditions provided. Therefore, observations of metabolic responses obtained under culture conditions need to be interpreted with caution, they indicate what the tissue is doing under those specific conditions (which include cells adapting and dying).

Chen et al use pharmacological interventions to the impact of various metabolic pathways on photoreceptor survival and "long term" metabolic changes. The dose and timing of these drug treatments are not examined though. It is also hard to know how these drugs penetrate the tissue and it needs to be validated that the intended targets are being accurately hit. These relatively long-term treatments should be causing numerous downstream changes to metabolism, cell function, and survival, which makes looking at a snapshot of metabolite levels hard to interpret. It would be more valuable to look at multiple time points after drug treatment, especially easy time points (closer to 1 hr). The authors use metabolite ratios to make conclusions about pathway activity. It would be more valuable to directly measure pathway activity by looking a metabolite production rates in the media and/or with metabolic tracers again in time scales closer to minutes and hours instead of days.

It is not clear from the text if the ex vivo samples with RPE/choroid intact are analyzed for metabolomics with the RPE/choroid still intact or if this is removed. If it is not removed, the comparison to the retina without RPE/choroid needs to be re-interpreted for the contribution of metabolites from the added tissue. The composition of the tissue is different and cannot be disentangled from the changes to the neural retina specifically.

While the data is interesting and may give insights into some rod and cone-specific metabolic susceptibility, more work is needed to validate these conclusions. Given the limitations of the model the authors have over-interpreted their findings and the conclusions are not supported by the results. They need to either dramatically limit the scope of their conclusions or validate these hypotheses with additional models and tools.

Reviewer #2 (Public Review):

Summary:<br /> This study aims to address existing differences in the literature regarding the extent of reward versus aversive dopamine signaling in the prefrontal cortex. To do so, the authors chose to present mice with both a reward and an aversive stimulus during different trials each day. The authors used high spatial resolution two-photon calcium imaging of individual dopaminergic axons in the medial PFC to characterize the response of these axons to determine the selectivity of responses in unique axons. They also paired the reward (water) and an aversive stimulus (tail shock) with auditory tones and recorded across 12 days of associative learning.

The authors find that some axons respond to both reward and aversive unconditioned stimuli, but overall, there is a strong preference to respond to aversive stimuli consistent with expectations from prior studies that used other recording methods. The authors find that both of their two auditory stimuli initially drive responses in axons, but that with training axons develop more selective responses for the shock associated tone indicating that associative learning led to changes in these axon's responses. Finally, the authors use anticipatory behaviors during the conditioned stimuli and facial expressions to determine stimulus discrimination and relate dopamine axons signals with this behavioral evidence of discrimination. This study takes advantage of cutting-edge imaging approaches to resolve the extent to which dopamine axons in PFC respond appetitive or aversive stimuli. They conclude that there is a strong bias to respond to the aversive tail shock in most axons and weaker more sparse representation of water reward.

Strengths:<br /> The strength of this study is the imaging approach that allows for investigation of the heterogeneity of response across individual dopamine axons, unlike other common approaches such as fiber photometry which provide a measure of the average population activity. The use of appetitive and aversive stimuli to probe responses across individual axons is another strength.

Weaknesses:<br /> A weakness of this study is the design of the associative conditioning paradigm. The use of only a single reward and single aversive stimulus makes it difficult to know whether these results are specific to the valence of the stimuli versus the specific identity of the stimuli. Further, the reward presentations are more numerous than the aversive trials making it unclear how much novelty and habituation account for results. Moreover, the training seems somewhat limited by the low number of trials and did not result in strong associative conditioning. The lack of omission responses reported may reflect weak associative conditioning. Finally, the study provides a small advance in our understanding of dopamine signaling in the PFC and lacks evidence for if and what might be the consequence of these axonal responses on PFC dopamine concentrations and PFC neuron activity.

Reviewer #2 (Public Review):

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

Nevertheless, I would suggest that the authors consider the following recommendations to strengthen the message further. First, I believe that the relation between individual motor neuron behavioral characteristics (delta F, brace height etc.) and the motor neuron input properties can be illustrated more clearly. Although this is explained in the text, I believe that this is not optimally supported by figures. Figure 6 to some extent shows this, but figures 8 and 9 as well as Table 1 shows primarily the goodness of fit rather than the actual fit. Second, I would have expected the discussion to have addressed specifically the question of which of the two primary schemes (push-pull, balanced) is the most prevalent. This is the main research question of the study, but it is to some degree left unanswered. Now that the authors have identified the relation between the characteristics of motor neuron behaviors (which has been reported in many previous studies), why not exploit this finding by summarizing the results of previous studies (at least a few representative ones) and discuss the most likely underlying input scheme? Is there a consistent trend towards one of the schemes, or are both strategies commonly used?

In addition, it seems striking to me that highly non-linear excitation profiles are necessary to obtain a linear CST ramp in many model configurations. Although somewhat speculative, one may expect that an approximately linear relation is desired for robust and intuitive motor control. It seems to me that humans generally have a good ability to accurately grade the magnitude of the motor output, which implies that either a non-linear relation has been learnt (complex task), or that the central nervous system can generally rely on a somewhat linear relation between the neural drive to the muscle and the output (simpler task). Following this reasoning, it could be interesting to report also for which input scheme, the excitation profile is most linear. I understand that this is not the primary aim of the study, but it may be an interesting way to elaborate on the finding that in many cases non-linear excitation profiles were needed to produce the linear ramp.

Reviewer #2 (Public Review):

In this manuscript, Parrotta et al. tested whether it is possible to modulate pain perception and heart rate by providing false HR acoustic feedback before administering electrical cutaneous shocks. To this end, they performed two experiments. The first experiment tested whether false HR acoustic feedback alters pain perception and the cardiac anticipatory response. The second experiment tested whether the same perceptual and physiological changes are observed when participants are exposed to a non-interoceptive feedback. The main results of the first experiment showed a modulatory effect for faster HR acoustic feedback on pain intensity, unpleasantness, and cardiac anticipatory response compared to a control (acoustic feedback congruent to the participant's actual HR). However, the results of the second experiment also showed an increase in pain ratings for the faster non-interoceptive acoustic feedback compared to the control condition, with no differences in pain unpleasantness or cardiac response.

The main strengths of the manuscript are the clarity with which it was written, and its solid theoretical and conceptual framework. The researchers make an in-depth review of predictive processing models to account for the complex experience of pain, and how these models are updated by perceptual and active inference. They follow with an account of how pain expectations modulate physiological responses and draw attention to the fact that most previous studies focus on exteroceptive cues. At this point, they make the link between pain experience and heart rate changes, and introduce their own previous work showing that people may illusorily perceive a higher cardiac frequency when expecting painful stimulation, even though anticipating pain typically goes along with a decrease in HR. From here, they hypothesize that false HR acoustic feedback evokes more intense and unpleasant pain perception, although the actual HR actually decreases due to the orienting cardiac response. Furthermore, they also test the hypothesis that an exteroceptive cue will lead to no (or less) changes in those variables. The discussion of their results is also well-rooted in the existing bibliography, and for the most part, provides a credible account of the findings.

The main weaknesses of the manuscript lies in a few choices in methodology and data analysis that hinder the interpretation of the results and the conclusions as they stand. The first peculiar choice is the convoluted definition of the outcomes. Specifically, pain intensity and unpleasantness are first normalized and then transformed into variation rates (sic) or deltas, which makes the interpretation of the results unnecessarily complicated. This is also linked to the definitions of the smallest effect of interest (SESOI) in terms of these outcomes, which is crucial to determining the sample size and gauging the differences between conditions. However, the choice of SESOI is not properly justified, and strangely, it changes from the first experiment to the second.

Furthermore, the researchers propose the comparison of faster vs. slower delta HR acoustic feedback throughout the manuscript when the natural comparison is the incongruent vs. the congruent feedback. This could be influenced by the fact that the faster HR exteroceptive cue in experiment 2 also shows a significant modulatory effect on pain intensity compared to congruent HR feedback, which puts into question the hypothesized differences between interoceptive vs. exteroceptive cues. These results could also be influenced by the specific choice of exteroceptive cue: the researchers imply that the main driver of the effect is the nature of the cue (interoceptive vs. exteroceptive) and not its frequency. However, they attempt to generalize their findings using knocking wood sounds to all possible sounds, but it is possible that some features of these sounds (e.g., auditory roughness or loomingness) could be the drivers behind the observed effects. Finally, it is noteworthy that the researchers divided the study into two experiments when it would have been optimal to test all the conditions with the same subjects in a randomized order in a single cross-over experiment to reduce between-subject variability.

Taking this into consideration, I believe that the conclusions are only partially supported by the evidence. Despite of the outcome transformations, a clear effect of faster HR acoustic feedback can be observed in the first experiment, which is larger than the proposed exteroceptive counterpart. This work could be of broad interest to pain researchers, particularly those working on predictive coding of pain.

Reviewer #2 (Public Review):

Summary:<br /> This work explores the implication of astrocytes in the regulation of long-term potentiation of excitatory synapses onto inhibitory neurons in CA1 hippocampus. They found that astrocytes of a sub-region of CA1 regulate this plasticity through their activation of endocannabinoids that lead to the release of the NMDA receptor co-agonist, D-serine.

Strengths:<br /> The experiments are well considered and conceptualized, and use appropriate tools to explore the role of astrocytes in the tripartite synapse. The results highlight a novel role of astrocytes in an important aspect of the synaptic regulation of the hippocampal circuit. There are extensive levels of analysis for each experimental group of evidence.

Weaknesses:<br /> The authors underscore and used an oversimplified view of the heterogeneity of interneuron populations and their selective roles in the hippocampal network. Also, there is an uneven level of astrocyte-selective tools used in the different experiments which creates an uneven strength of arguments and conclusions regarding the role of glial cells. Finally, the wording used by the authors often lead to some confusion or sense of overinterpretation.

Reviewer #2 (Public Review):

Summary:<br /> Through a set of experiments and model simulations, the authors tested whether the commonly assumed world model of gravity was a faithful replica of the physical world. They found that participants did not model gravity as a single, fixed vector for gravity but instead as a distribution of possible vectors. Surprisingly, the width of this distribution was quite large (~20 degrees). While previous accounts had suggested that this uncertainty was due to perceptual noise or an inferred external perturbation, the authors suggest that this uncertainty simply arises from a noisy distribution of the representation of gravity's direction. A reinforcement learning model with an initial uniform distribution for gravity's direction ultimately converged to a precision in the same order as the human participants, which lends support to the authors' conclusion and suggests that this distribution is learned through experience. What's more, further simulations suggest that representing gravity with such a wide distribution may balance speed and accuracy, providing a potentially normative explanation for the world model with gravity as a distribution.

Strengths:<br /> The authors present surprising findings in a relatively straightforward way in a now classic experimental task. They provide a normative explanation based on a resource-rational framework for why people may have a stochastic world model instead of a deterministic world model.

Weaknesses:<br /> Support for gravity being represented as a Gaussian distribution (stochastic world model), as opposed to perceptual uncertainty or (inferred) external perturbations, is from an RL model simulation. It would be more convincing if the authors could experimentally demonstrate that potential external perturbations did not affect the distribution of gravity.

Reviewer #2 (Public Review):

Summary and strengths:<br /> The authors have developed a helpful resource for the community regarding hippocampal cell types and their interactions from many perspectives. There have been many updates to hippocampome v1.0 to v1.12, that are nicely summarized and explained (e.g., Table 1). The content and impact are also presented (Fig. 4).

Weaknesses:<br /> My main comment is that it is not completely clear and/or it is a bit buried as to what makes this v2.0 (rather than v1.13). The title would seem to encompass it ('... enabling data-driven spiking neural network simulations...), but in the introduction, the authors seem to emphasize "50 newly identified neuron types...". Is it the case that launching network simulations (using CARLsim) was not possible up to v1.12? I don't think so? I think that this research advance is to announce and summarize the various updates and to demonstrate how network simulations can be easily done? If so, this should and could be made more clear so that the reader does not necessarily have to go through all the previous versions to understand what is 'special' or different about v2.0. This could perhaps be achieved by situating their tool and its goals relative to other efforts (e.g., blue brain project) that are mentioned in the Discussion?

Reviewer #2 (Public Review):

Summary:<br /> Chromosome organization in E. coli and related species ('transversal') deviates starkly from the pattern more commonly found in bacteria ('longitudinal'). The underlying mechanisms and the physiological roles, however, are not well understood. This manuscript by Seba et al. investigates the activity and regulation of MukBEF in chromosome folding in E. coli. Using a construct for inducible expression of MukBEF, the authors first demonstrate that the initiation of long-range chromosome contacts (likely by loop extrusion) is not restricted to few positions on the chromosome and rather widely distributed but excluding the replication terminus region. Using ChIP-Seq, the authors show that the distribution of MukBEF over the chromosome is consistent with widely distributed loading and moreover indicate a connection of chromosome folding and DNA replication with newly replicated DNA shower an increased tendency for MukBEF binding. To dissect this further, they then redistribute matS sites on the chromosome by a clever strategy based on large-scale transpositions. The results reveal that matS-free DNA segments undergo MukBEF dependent folding regardless of their position relative to the origin of replication, being consistent with a broad distributed loading of MukBEF. By fine-mapping with smaller transposition events, they show that few matS sites are sufficient to impede MukBEF activity. Surprisingly, however, E. coli and most related genomes harbor many matS sites, which are particularly highly concentrated near the chromosome dimer resolution dif site (Fig. 5).

Strengths:<br /> This is a well-executed and well-presented study. The findings show that the MatP/matS system acts locally and independently of DNA replication to restrict MukBEF in the replication terminus region. Few of the many matS sites are sufficient for MukBEF restriction. The main conclusions of the work are clear and well supported by the data.

Weaknesses:<br /> The biological relevance of MukBEF restriction from the replication terminus region remains unresolved. The authors could speculate on possible functions.

Reviewer #2 (Public Review):

Studying the weakly electric brown ghost knifefish, the authors provide evidence that 'chirps' (brief modulations in the frequency and amplitude of the ongoing electric signal) function in active sensing (specifically homeoactive sensing) rather than communication. This is a behavior that has been very well studied, including numerous studies on the sensory coding of chirps and the neural mechanisms for chirp generation. Chirps are largely thought to function in communication behavior, so this alternative function is a very exciting possibility that could have a great impact on the field. The authors do provide convincing evidence that chirps may function in homeoactive sensing. However, their evidence arguing against a role for chirps in communication is not as strong, and neglects a large body of research. Ultimately, the manuscript has great potential but suffers from framing these two possibilities as mutually exclusive and dismissing evidence in favor of a communicative function.

(1) The specific underlying question of this study is not made clear in the abstract or introduction. It becomes apparent in reading through the manuscript that the authors seek to test the hypothesis that chirps function in active sensing (specifically homeoactive sensing). This should be made explicitly clear in both the abstract and introduction, along with the rationale for this hypothesis.

(2) My biggest issue with this manuscript is that it is much too strong in dismissing evidence that chirping correlates with context. This is captured in this sentence in the introduction, "We first show that the choice of different chirp types does not significantly correlate with any particular behavioral or social context." This very strong conclusion comes up repeatedly, and I disagree with it, for the following reasons:

In your behavioral observations, you found sex differences in chirping as well as differences between freely interacting and physically separated fish. Your model of chirp variability found that environmental experience, social experience, and beat frequency (DF) are the most important factors explaining chirp variability. Are these not all considered "behavioral or social context"? Beat frequency (DF) in particular is heavily downplayed as being a part of "context" but it is a crucial part of the context, as it provides information about the identity of the fish you're interacting with.

In your playback experiments, fish responded differently to small vs. large DFs, males chirped more than females, type 2 chirps became more frequent throughout a playback, and rises tended to occur at the end of a playback. These are all examples of context-dependent behavior.

Further, you only considered the identity of interacting fish or stimulated fish, not their behavior during the interaction or during playback. Such an analysis is likely beyond the scope of this study, but several other studies have shown correlations between social behavior and chirping. In the absence of such data here, it is too strong to claim that chirping is unrelated to context.

In summary, it is simply too strong to say that chirping does not correlate with context. Importantly, however, this does not detract from your hypothesis that chirping functions in homeoactive sensing. A given EOD behavior could serve both communication and homeoactive sensing. I actually suspect that this is quite common in electric fish. The two are not mutually exclusive, and there is no reason for you to present them as such. I recommend focusing more on the positive evidence for a homeoactive function and less on the negative evidence against a communication function.

(3) The results were generally challenging to follow. In the first 4 sections, it is not made clear what the specific question is, what the approach to addressing that question is, and what specific experiment was carried out (the last two sections of the results were much clearer). The independent variables (contexts) are not clearly established before presenting the results. Instead they are often mentioned in passing when describing the results. They come across as an unbalanced hodgepodge of multiple factors, and it is not made clear why they were chosen. This makes it challenging to understand why you did what you did, the results, and their implications. For each set of major results, I recommend: First, pose a clear question. Then, describe the general approach to answering that question. Next, describe the specifics of the experimental design, with a rationale that appeals to the general approach described. Finally, describe the specific results.

(4) Results: "We thus predicted that, if behavioral meaning can be attributed to different types of chirps, as posed by the prevailing view (e.g., Hagedorn and Heiligenberg, 1985; Larimer and MacDonald, 1968; Rose, 2004)..." It should be made clear why this is the prevailing view, and this description should likely be moved to the introduction. There is a large body of evidence supporting this view and it is important to be complete in describing it, especially since the authors seem to seek to refute it.

(5) I am not convinced of the conclusion drawn by the analysis of chirp transitions. The transition matrices show plenty of 1-2 and 2-1 transitions occurring. Further, the cross-correlation analysis only shows that chirp timing between individuals is not phase-locked at these small timescales. It is entirely possible that chirp rates are correlated between interacting individuals, even if their precise timing is not.

Reviewer #2 (Public Review):

Kandola et al. explore the important and difficult question regarding the initiating event that triggers (nucleates) amyloid fibril growth in glutamine-rich domains. The researchers use a fluorescence technique that they developed, dAMFRET, in a yeast system where they can manipulate the expression level over several orders of magnitude, and they can control the length of the polyglutamine domain as well as the insertion of interfering non-glutamine residues. Using flow cytometry, they can interrogate each of these yeast 'reactors' to test for self-assembly.

In the introduction, the authors provide a fairly thorough yet succinct review of the relevant literature into the mechanisms of polyglutamine-mediated aggregation over the last two decades, as well as a fairly clear description of the experimental techniques they developed.

Their assay shows that the fraction of cells with AmFRET signal increases strongly with an increase in polyQ length, with a threshold around 35-40 glutamines. This roughly correlates with the Q-length dependence of disease. The experiments in which asparagine or other amino acids are inserted at variable positions in the glutamine repeat are creative and thorough, and the data along with the simulations provide compelling support for the proposed Q zipper model. The experiments are strongly supportive of a model where formation of the beta-sheet nucleus is within a monomer. This is a potentially important result, as there are conflicting data in the literature as to whether the nucleus in polyQ is monomer.

The authors present convincing data that there are differences in the structural stability of their "QU" versus "QB" aggregates. However, the conclusion that "QB" must have multilamellar architecture versus "QU" was feasible but less compelling.

The authors present intriguing data showing that amyloid formation does not monotonically increase with increasing concentration, and their conclusion that high concentrations of polyQ can 'self-poison' amyloid growth is supported by the experimental data. The discussion surrounding the mechanism by which 'self-poisoning' occurs is confusing. The authors variously discuss that soluble oligomers must be the inhibitory species, that dead-end products of Q zipper nuclei are the inhibitory species, or that self-poisoning occurs because conformational conversion at the templating surface is slow relative to the rate of arrival of new molecules to the surface. The data seem consistent with an argument that, at high concentrations, non-structured polyQ oligomers form which interfere with elongation into structured amyloid assemblies - but it is not clear why such oligomers would be zippers.

Overall, this is a very valuable and thorough exploration of the fundamental question as to the nature and identity of the nucleating species in polyglutamine aggregation.

Reviewer #2 (Public Review):

Summary:<br /> The EAG family of ion channels is associated with many pathological conditions and are considered a target for the treatment of disease such as cancer. In this study, Abdelaziz et. al. examine the role of interaction between PAS domain and CNBHD in voltage-dependent gating of EAG channels. Based on their data, the authors conclude that they have identified a hidden open state that is only accessible in the mutant channels but not in the wild type. This hidden open state O1 can distinguished from the canonical open state O2 because it exhibits very different voltage-dependence. Although it is clear that the kinetics of these two open states are different, I have concerns about whether the data presented in this manuscript rule out alternate explanations. The idea that PAS domain deletions uncover a hidden open state is an extraordinary claim and if established, it has the potential to open a completely new approach to studying early gating transitions of these channels.

Strengths:<br /> 1. The study has identified a number of potentially interesting mutants that modulate voltage-dependent gating.<br /> 2. The discovery of a hidden open state due to mutations in the cytosolic domains is quite astonishing.

Weaknesses:<br /> 1. WT EAG currents are far right shifted compared to previously published data. It is not clear whether it is the recording conditions but at 0 mV very few channels are open. Compare this with recordings reported previously of the same channel hEAG1 by Gail Robertson's lab ( Zhao et. al. (2017) JGP). In that case, most of the channels are open at 0 mV. There must be at least 25 mV shift in voltage-dependence. These differences are unusually large.

2. In most of the mutants, O2 state becomes more prevalent at potentials above +50 mV. At these potentials, endogenous voltage-dependent currents are often observed in xenopus oocytes. The observed differences between the various mutants might simply be a function of the expression level of the channel versus endogenous currents.

3. Voltage-dependence of the kinetics of WT currents appears a bit strange. Why is the voltage-dependence saturated at 0 mV even though very few channels have activated at that point? I cannot imagine any kinetic model that can lead to such unusual voltage-dependence of kinetics.

4. One of the other concerns I have is that in many cases, it is clear that the pulse is too short to measure steady-state voltage-dependence. For instance, the currents in -160 mV and -100 mV in Figure 6A and 6B are not saturated.

Reviewer #2 (Public Review):

The manuscript starts with a demonstration of pantoate binding to ASBTnm using a thermostability assay and ITC, and follows with structure determinations of ASBTnm with or without pantoate. The structure of ASBTnm in the presence of pantoate pinpoints the binding site of pantoate to the "crossover" region formed by partially unwinded helices TMs 4 and 9. Binding of pantoate induces modest movements of side chain and backbone atoms at the crossover region that are consistent with providing coordination of the substrate. The structures also show movement of TM1 that opens the substrate binding site to the cytosol and mobility of loops between the TMs. MD simulations of the ASBT structure embedded in lipid bilayer suggests a stabilizing effect of the two sodium ions that are known to co-transport with the substrate. Binding study on pantoate analogs further demonstrate the specificity of pantoate as a substrate.

Overall, the structural, functional and computational studies are solid and rigorous, and the conclusions are well justified. In addition, the authors discussed the significance of the current study in a broader perspective relevant to recent structures of mammalian BASS members.

Reviewer #2 (Public Review):

Summary:<br /> The paper sought to determine the number of myosin 10 molecules per cell and localized to filopodia, where they are known to be involved in formation, transport within, and dynamics of these important actin-based protrusions. The authors used a novel method to determine the number of molecules per cell. First, they expressed HALO tagged Myo10 in U20S cells and generated cell lysates of a certain number of cells and detected Myo10 after SDS-PAGE, with fluorescence and a stained free method. They used a purified HALO tagged standard protein to generate a standard curve which allowed for determining Myo10 concentration in cell lysates and thus an estimate of the number of Myo10 molecules per cell. They also examined the fluorescence intensity in fixed cell images to determine the average fluorescence intensity per Myo10 molecule, which allowed the number of Myo10 molecules per region of the cell to be determined. They found a relatively small fraction of Myo10 (6%) localizes to filopodia. There are hundreds of Myo10 in each filopodia, which suggests some filopodia have more Myo10 than actin binding sites. Thus, there may be crowding of Myo10 at the tips, which could impact transport, the morphology at the tips, and dynamics of the protrusions themselves. Overall, the study forms the basis for a novel technique to estimate the number of molecules per cell and their localization to actin-based structures. The implications are broad also for being able to understand the role of myosins in actin protrusions, which is important for cancer metastasis and wound healing.

Strengths:<br /> The paper addresses an important fundamental biological question about how many molecular motors are localized to a specific cellular compartment and how that may relate to other aspects of the compartment such as the actin cytoskeleton and the membrane. The paper demonstrates a method of estimating the number of myosin molecules per cell using the fluorescently labeled HALO tag and SDS-PAGE analysis. There are several important conclusions from this work in that it estimates the number of Myo10 molecules localized to different regions of the filopodia and the minimum number required for filopodia formation. The authors also establish a correlation between number of Myo10 molecules filopodia localized and the number of filopodia in the cell. There is only a small % of Myo10 that tip localized relative to the total amount in the cell, suggesting Myo10 have to be activated to enter the filopodia compartment. The localization of Myo10 is log-normal, which suggest a clustering of Myo10 is a feature of this motor.

Weaknesses:<br /> One main critique of this work is that the Myo10 was overexpressed. Thus, the amount in the cell body compared to the filopodia is difficult to compare to physiological conditions. The amount in the filopodia was relatively small - 100s of molecules per filopodia so this result is still interesting regardless of the overexpression. However, the overexpression should be addressed in the limitations.<br /> The authors have not addressed the potential for variability in transfection efficiency. The authors could examine the average fluorescence intensity per cell and if similar this may address this concern.<br /> The SDS PAGE method of estimating the number of molecules is quite interesting. I really like this idea. However, I feel there are a few more things to consider. The fraction of HALO tag standard and Myo10 labeled with the HALO tagged ligand is not determined directly. It is suggested that since excess HALO tagged ligand was added we can assume nearly 100% labeling. If the HALO tag standard protein is purified it should be feasible to determine the fraction of HALO tagged standard that is labeled by examining the absorbance of the protein at 280 and fluorophore at its appropriate wavelength. The fraction of HALO tagged Myo10 labeled may be more challenging to determine, since it is in a cell lysate, but there may be some potential approaches (e.g. mass spec, HPLC).<br /> In Figure 1B, the stain free gel bands look relatively clean. The Myo10 is from cell lysates so it is surprising that there are not more bands. I am not surprised that the bands in the TMR fluorescence gel are clean, and I agree the fluorescence is the best way to quantitate.<br /> In Figure 3C, the number of Myo10 molecules needed to initiate a filopodium was estimated. I wonder if the authors could have looked at live cell movies to determine that these events started with a puncta of Myo10 at the edge of the cell, and then went on to form a filopodia that elongated from the cell. How was the number of Myo10 molecules that were involved in the initiation determined? Please clarify the assumptions in making this conclusion.<br /> It is stated in the discussion that the amount of Myo10 in the filopodia exceeds the number of actin binding sites. However, since Myo10 contains membrane binding motifs and has been shown to interact with the membrane it should be pointed that the excess Myo10 at the tips may be interacting with the membrane and not actin, which may prevent traffic jams.

Reviewer #2 (Public Review):

The authors suggest that the African trypanosome endomembrane system has unusual organisation, in that the entire system is a single reticulated structure. It is not clear if this is thought to extend to the lysosome or MVB. There is also a suggestion that this unusual morphology serves as a trans-(post)Golgi network rather than the more canonical arrangement.

The work is based around very high-quality light and electron microscopy, as well as utilising several marker proteins, Rab5A, 11 and 7. These are deemed as markers for early endosomes, recycling endosomes and late or pre-lysosomes. The images are mostly of high quality but some inconsistencies in the interpretation, appearance of structures and some rather sweeping assumptions make this less easy to accept. Two perhaps major issues are claims to label the entire endosomal apparatus with a single marker protein, which is hard to accept as certainly this reviewer does not really even know where the limits to the endosomal network reside and where these interface with other structures. There are several additional compartments that have been defined by Rob proteins as well, and which are not even mentioned. Overall I am unconvinced that the authors have demonstrated the main things they claim.

The approaches taken are state-of-the-art but not novel, and because of the difficulty in fully addressing the central tenet, I am not sure how much of an impact this will have beyond the trypanosome field. For certain this is limited to workers in the direct area and is not a generalisable finding.

Reviewer #2 (Public Review):

The authors use Xenopus embryos to study feedback interactions between the planar cell polarity (PCP) proteins in the context of convergence and extension. They show that binding of the cytoplasmic polarity protein Pk2 to Vangl2 is needed for them to synergistically suppress defects in convergence and extension caused by Dvl overexpression. They then examine protein localizations in animal cap cells, and show that Wnt11-induced accumulation of Fzd7, Ror2 and Dvl into plasma membrane patches is disrupted by the functional Vangl2/Pk complex. This disperses Fzd and causes its endocytosis, while Dvl remains at the plasma membrane.

This is a potentially interesting paper, showing mechanisms by which Vangl2/Pk can functionally antagonize Fzd/Dvl during planar cell polarity.

The protein localization experiments in animal cap assays are for the most part convincing, but with the caveat that the authors assume that the proteins are acting within the same cell. As Fzd and Vangl2 are thought to localize to opposite cell ends in many contexts, can the authors be sure that the effects they observe are not due to trans interactions?

The authors propose a model whereby Vangl2 acts as an adaptor between Dvl and Ror, to first prevent ectopic activation of signaling, and then to relay Dvl to Fzd upon Wnt stimulation. This is based on the observation that Ror2 can be co-IPed with Vangl2 but not Dvl; and secondly that the distribution of Ror2 in membrane patches after Wnt11 stimulation is broader than that of Fzd7/Dvl, while Vangl2 localizes to the edges of these patches. The data for both these points is not wholly convincing. The co-IP of Ror2 and Vangl2 is very weak, and the input of Dvl into the same experiment is very low, so any direct interaction could have been missed. Secondly, the broader distribution of Ror2 in membrane patches is very subtle, and further analysis would be needed to firm up this conclusion.

A final caveat to these experiments is that in the animal cap assays, loss of function and gain of function both cause convergence and extension defects, so any genetic interactions need to be treated with caution i.e. two injected factors enhancing a phenotype does not imply they act in the same direction in a pathway, in particular as there are both cis/trans and positive/negative feedbacks between the PCP proteins.

Reviewer #2 (Public Review):

Where this study is interesting is that the authors do a meta-analysis of studies in which metabolic rate was experimentally manipulated and both this rate and glucocorticoid levels were simultaneously measured. Unsurprisingly, there are relatively few such studies and many are from a single lab. More studies are needed. While the results of the analysis are compelling, they are not surprising. That said, this work is important.

Reviewer #2 (Public Review):

Prime editing is a major gene editing technique because it allows for the introduction of all possible substitutions, as well as small insertions and deletions, without causing double strand breaks. However, its efficiency is often limited. In a previous study, the authors showed that prime editing could be performed in zebrafish using recombinant PE2 protein and pegRNAs generated by in vitro transcription, but at many of the sites tested, gene editing efficiency remained relatively low.

In this current paper, the authors find that when pegRNAs were combined with Cas9, many induced much less indels than their corresponding guide RNAs and propose that this is due to the complementarity between the 5' and 3' regions of pegRNAs. Two methods aiming to reduce the resulting circularization of pegRNAs were next shown to increase the efficiency of prime editing: a slow refolding protocol (which was previously shown to be useful for inefficient guide RNAs), and the introduction of a substitution at position +2 of the reverse transcriptase template sequence. The data obtained and analyzed is solid and convincing.

These methods are remarkably straightforward and proved beneficial for most of the pegRNAs tested. Consequently, they represent important advances for the prime editing technique.

It should be noted, however, that despite these advances, prime editing activity remained relatively low for a significant proportion of pegRNAs tested (with less than 2% sequencing reads exhibiting the expected sequence change). This shows that further improvements are still needed for this important gene editing technique.

Reviewer #2 (Public Review):

Summary:<br /> This is a solid study that dissects the thermodynamics of lipopolysaccharide (LPS) transporter MsbA and LPS. Native ESI-MS and the novel strategies developed by the authors were employed to quantify the affinities of LPS-MsbA interactions and its temperature dependence. Here, the equilibrium of lipid-protein interactions occurs in the micellar phase. The double-/triple-mutant cycle analysis and van't Hoff analysis allowed a full thermodynamic description of the lipid-protein interactions and the analysis of thermodynamic coupling between LPS binding sites. The most notable result would be that LPS-MsbA interaction is largely driven by entropy involving the negative heat capacity, a signature of the solvent reorganization effect (here authors attribute the solvent effect to "water" reorganization). The entropy driven lipid binding has been previously reported by the same authors for Kir1,2-PIP2 interactions.

Strengths:

1) This is overall a very thorough and rigorous study providing the detailed thermodynamic principles of LPS-MsbA interaction.

2) The double and triple-mutant cycle approaches are newly applied to lipid-protein interactions, enabling detailed thermodynamics between LPS binding sites.

3) The entropy-driven protein-lipid interaction is surprising. The binding seems to be mainly mediated by the electrostatic interaction between the positively charged residues on the protein and the negatively charged or polar headgroup of LPS, which could be thought of as "enthalpic" (making of a strong bond relative to that with solvent).

Weaknesses:

1. This study is a good contribution to the field, but it was difficult to find novel biological insights or methodological novelty from this study.

1a) Thermodynamic analysis of lipid-protein interactions, an example of entropy-driven lipid-protein interactions, and the cooperativity between lipid binding sites have been reported by the author's group. Also, the cooperativity between binding sites in general have been reported from numerous studies of biomolecular interactions.

1b) It is not clear how this study provides new insights into the understanding of LPS transport mechanisms. Probably, authors could strengthen the Discussion by providing biological insights-how the residue coupling.

2) One to three LPS molecules bind to MsbA, but it is unclear whether bound KDL occupies inner or outer cavities, or both and how a specific mutation affects the affinity of specific LPS (i.e., to inner or to outer cavities). Based on the known structures, the maximal number of LPS is three. It is possible that the inner and outer cavities have different LPS affinities. Also, there can be multiple one-LPS-bound states, two-LPS-bound states if LPS strictly binds to the binding sites indicated by the structures. This aspect is beyond the scope of this study and difficult to address, but without this information, it seems hard to tell what is going on in the system.

3) If a single mutation is introduced to the inner cavity, its effect will be "doubled" because the inner cavity is shared by two identical subunits. This effect needs to be clarified in the result section.

4) In the result section, "Mutant cycle analysis of KDL binding to vanadate-trapped MsbA.":

4a) It seems necessary to show the mass spectra for Msb-ADP-vanadate complex as well as its lipid bound forms.

4b) The rationale of this section (i.e., what mechanistic insights can be obtained from this study) is unclear. For example, it is not sure what meaningful information can be obtained from a single type (ADP/vanadate) of the bound state regarding the ATP-driven function of MsbA.

Reviewer #2 (Public Review):

Previously, using bioinformatics study, authors have identified potential sequence motifs that are common to a large subset of beta-barrel outer membrane proteins in gram negative bacteria. Interestingly, in that study, some of those motifs are located in the internal strands of barrels (not near the termini), in addition to the well-known "beta-signal" motif in the C-terminal region.

Here, the authors carried out rigorous biochemical, biophysical, and genetic studies to prove that the newly identified internal motifs are critical to the assembly of outer membrane proteins and the interaction with the BAM complex. The author's approaches are rigorous and comprehensive, whose results reasonably well support the conclusions. While overall enthusiastic, I have some scientific concerns with the rationale of the neutron refractory study, and the distinction between "the intrinsic impairment of the barrel" vs "the impairment of interaction with BAM" that the internal signal may play a role in. I hope that the authors will be able to address this.

Strengths:

1. It is impressive that the authors took multi-faceted approaches using the assays on reconstituted, cell-based, and population-level (growth) systems.

2. Assessing the role of the internal motifs in the assembly of model OMPs in the absence and presence of BAM machinery was a nice approach for a precise definition of the role.

Weaknesses:

1. The result section employing the neutron refractory (NR) needs to be clarified and strengthened in the main text (from line 226). In the current form, the NR result seems not so convincing.

What is the rationale of the approach using NR?<br /> What is the molecular event (readout) that the method detects?<br /> What are "R"-y axis and "Q"-x axis and their physical meanings (Fig. 5b)?<br /> How are the "layers" defined from the plot (Fig. 5b)?<br /> What are the meanings of "thickness" and "roughness" (Fig. 5c)?<br /> What are the meanings of the increases in thickness and roughness?<br /> What does "SLD" stand for?

2. In the result section, "The internal signal is necessary for insertion step of assembly into OM"

This section presents an important result that the internal beta-signal is critical to the intrinsic propensity of barrel formation, distinct from the recognition by BAM complex. However, this point is not elaborated in this section. For example, what is the role of these critical residues in the barrel structure formation? That is, are they involved in any special tertiary contacts in the structure or in membrane anchoring of the nascent polypeptide chains?