Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

6) How were patients allocated to groups? Randomised?

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

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

9. Were any samples poly-microbial?

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

Reviewer #1 (Public Review):

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

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

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

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

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

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

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

Reviewer #1 (Public Review):

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

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

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Reviewer #1 (Public Review):

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

Strengths:

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

Weaknesses:

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

Reviewer #1 (Public Review):

The article by Solvi and colleagues aims to investigate what type and degree of information (either absolute, relative, or a weighted combination of both) is used by bumblebees when retrieving the value of an item. The authors reported recent evidence in humans and birds that suggest they seem to use a combination of absolute memories and remembering of subjective ranking, and an absence of relevant studies for other species, including invertebrates.

Thus, the authors conducted four different experiments to study what type of information is guiding the decision of bumblebees when facing different qualitative and quantitative comparisons.

In the first two experiments, the authors reported the use of relative ranking of stimuli instead of a memory of their absolute value. According to the authors, these results are confirmed by experiment three, where bees were presented with two equally-ranked choices which, in fact, were not treated as different by bees. In the last experiment, bumblebees showed a preference for the highest rank item.

Despite the presentation of well-designed experiments, the conclusions that bumblebees are using only memories of ordinal comparisons, thus showing a different strategy with respect to humans and birds, seems to not be fully supported by the results. The behaviour on the first two experiments, for instance, could be explained by a recency effect, where the higher item of the last comparison is better retrieved (the work of Giurfa on transitive inferences in bees was not mentioned, though is relevant here). Furthermore, in the last experiment, bumblebees could not have used an ordinal ranking; their choice for the higher-ranking item could be based on its higher absolute quantitative value in terms of sucrose solution.

The different behaviours and strategies used by bees here could be better explained by differences in the experimental task proposed, rather than supporting a general statement about the evolution of different strategies in comparison to other species.

Reviewer #1 (Public Review):

Li et al. use biochemical binding analysis combined with deletions/mutations to demonstrate that the bottom helix of the Rph3A C2B domain directly interacts with the first 10 residues (N-peptide region) on SNAP25, and this interaction is amplified by the intramolecular interaction of the C2B domain with RAB-binding domain. They establish the functional relevance of this interaction using live-cell imaging of dense-core vesicle exocytosis in neuroendocrine PC12 cells and in vitro SNARE assembly assay. They propose that the Rph3A binding to SNAP25 pre-structures the protein to efficiently assemble with Syntaxin and VAMP2, and thus, promoting the vesicle docking and priming process. This is a systematic analysis that clarifies the role of Rph3A in regulated exocytosis and provides novel insight into the underlying molecular mechanisms.

Manfred wants to be left alone

No one knows where this comically large helmet came from

The Prince of otranto has a father, manfred and the queen his mother and was preparing to get married to matilda then the day of the wedding he is killed by a comically large helmet

Reviewer #1 (Public Review):

This work focuses on the mechanisms that underlie a previous observation by the authors that the type VI secretion system (T6SS) of a Pseudomonas chlororaphis (Pchl) strain can induce sporulation in Bacillus subtilis (Bsub). The authors bioinformatically characterize the T6SS system in Pchl and identify all the core components of the T6SS, as well as 8 putative effectors and their domain structures. They then show that the Pchl T6SS, and in particular its effector Tse1, is necessary to induce sporulation in Bsub. They demonstrate that Tse1 has peptidoglycan hydrolase activity and causes cell wall and cell membrane defects in Bsub. Finally, the authors also study the signaling pathway in Bsub that leads to the induction of sporulation, and their data suggest that cell wall damage may lead to the degradation of the anti-sigma factor RsiW, leading to activation of the extracellular sigma factor σW that causes increased levels of ppGpp. Sensing of high ppGpp levels by the kinases KinA and KinB may lead to phosphorylation of Spo0F, and induction of the sporulation cascade.

The findings add to the field's understanding of how competitive bacterial interactions work mechanistically and provide a detailed example of how bacteria may antagonize their neighbors, how this antagonism may be sensed, and the resulting defensive measures initiated.

While several of the conclusions of this paper are supported by the data, additional controls would bolster some aspects of the data, and some of the final interpretations are not substantiated by the current data.

- The Bsub signaling pathway that is proposed is intricate and extensive as shown in Fig 5A. However, the data supporting that is very sparse:<br /> a) The authors show no data showing that the proteases PrsW and/or RasP, or the extracellular sigma factor σW are necessary, or that the cleavage of RsiW is needed, for induction of sporulation - this could presumably be tested using mutants of those genes.<br /> b) Similarly, they don't demonstrate that the levels of ppGpp increase in the cell upon exposure to Pchl.<br /> c) There is some data showing that kinA and kinB mutants don't induce sporulation (Fig supplement 7A), but that is lacking the 'no attacker' control that would demonstrate an induction.<br /> d) There is some data showing that RsiW may be cleaved (Fig 5C, D), but that data would benefit from a positive control showing that the lack of YFP foci is seen in a condition where RsiW is known to be cleaved, as well as from a time-course showing that the foci are present prior to the addition of Tse1, and then disappear. As it is shown now, it is possible that the addition of Tse1 just blocks the production of RsiW or its insertion into the membrane (especially given the membrane damage seen). Further, there is no data that the disappearance of the YFP loci requires the proteases PrsW and /or RasP - such data would also support the idea that the disappearance is due to cleavage of RsiW.<br /> - The entire manuscript suggests that T6SS is solely responsible for the induction of sporulation. While T6SS does appear to play a major part in explaining the sporulation induction seen, in the absence of 'no attacker' controls for Fig. 2A, it is impossible to see this. From the data shown in Fig. 2C, and figure supplement 2A, the 'no attacker' sporulation rate seems to be ~20%, while the rate is ~40% with Pchl strains lacking T6SS, suggesting that an additional factor may be playing a role.

Reviewer #1 (Public Review):

The authors have determined the structure of OmcZ cytochrome nanowires of Geobacter sulfurreducens by Cryo-EM.

OmcZ represents the third cytochrome nanowire of Geobacter to be structurally resolved. The structure reveals an octaheme cytochrome which oligomerizes to form an extended filament which scaffolds a continuous chain of hemes which serves to support long-range electron transport to terminal electron acceptors.

Previously identified nanowires which have been structurally resolved consisted of oligomers of OmcS and OmcE which, although lacking significant sequence identity, shared a common heme arrangement along the filament/nanowire.

OmcZ differs structurally from OmcS and OmcE, possessing a notably different heme chain configuration. OmcZ also differs from OmcS/OmcE in the nature of the interactions at the interface between subunits. Whilst in OmcS/OmcE a terminal heme is ligated by a histidine from the adjacent subunit of the wire, in OmcZ the terminal heme is ligated by a histidine within the same subunit, highlighting yet another difference between OmcZ and OmcS/E.

Based upon these observations, the authors suggest that OmcS and OmcE evolved from a common ancestor and that OmcZ evolved independently of OmcS/E. This is significant as it not only reveals the diversity of cytochrome nanowires which support long range electron transfer in Geobacter but also demonstrates that this mechanism of EET has potentially evolved multiple times and is likely to be exploited by other environmental microbes which utilize extracellular electron transport to support respiration.

Manuscript Strengths:<br /> The manuscript presents a solid detailed structural analysis of OmcZ providing new insight into the diverse range of electron transfer pathways utilized by Geobacter. By comparing OmcZ with other cytochrome nanowires of Geobacter (OmcS/OmcE) and with other electron transfer proteins such as the MtrABC complex, additional insight is gained into potential electron transfer properties of this cytochrome nanowire.

Manuscript Weaknesses:<br /> The manuscript compares previous characterisations of OmcZ filaments by X-ray scattering/IR nanospectroscopy prepared at pH 2 and pH 7 which indicated a higher percentage of alpha-helices and beta-sheets than what was observed by Cryo-EM from filaments prepared at pH 10.5 (this study). Due to the differences observed, it is suggested these previously utilized techniques are unreliable. Although there is a substantial difference in the proportion of beta-sheet that is observed/indicated between different methods, without a direct comparison available at the same pH it is perhaps not possible to attribute differences to the techniques alone.

Manuscript Impact:<br /> Through this work, the authors have made a significant contribution to the knowledge surrounding the electron transfer processes of Geobacter. Based on the structure obtained, they have sought to rationalise observed phenotypes associated with the different cytochrome nanowires and intriguingly propose how OmcZ may allow for more conductive biofilms through the formation of meshes of OmcZ filaments capable of exchanging electrons at solvent exposed hemes.

This manuscript will be of interest to scientists working across a range of disciplines including environmental microbiologists studying microbially driven redox processes in the subsurface, biochemists studying electron transfer proteins/pathways and in particular those working on extracellular electron transfer, and biotechnologists seeking to exploit bacterial electron transfer processes for biotechnological applications.

Reviewer #1 (Public Review):

This is an interesting paper, which has used cutting-edge approaches (DMS and ML) to probe an important phenomenon in protein function, namely allostery. The paper managed to acquire a large volume of data and to use this data efficiently to train ML models, which are then used to probe the question of why are some regions "allosteric" hot spots. The results are interesting and novel and suggest that despite structural homology, hotspot regions can differ among relatively close relatives, nevertheless, there are common mechanisms underpinning the allosteric mechanisms, likely linked to the conformational sampling of the proteins.

Strengths - To me, the strengths of the paper are predominantly in the experimental work, there's a huge amount of data generated through mutagenesis, screening, and DMS. This is likely to constitute a valuable dataset for future work. The experimental data allows mapping of the hotspots and much of the paper would be the same in terms of analysis without the ML, I think the experimental work with structural and sequence analysis would probably constitute a complete and impactful study alone, such is the quality. The ML obviously adds another layer of insight into the project. What is shown is that training on one homolog can allow the prediction of hotspots on related homologs. To some degree, this is as expected given these proteins share a common fold and function, yet the fact it is possible (albeit imperfect) despite quite a low sequence identity is notable.

Weaknesses - it is hard to describe this as a weakness, but the ML is obviously not perfect in the predictions, yet is still interesting. I don't have any major suggestions for revisions or changes - it is what it is and I think serves as a nice benchmark for follow-up studies with new methods and approaches. I think this reiterates the importance that the raw data is made available so that it can be used to benchmark alternative approaches and help advance the field. Scientifically, I think what is perhaps missing, and I don't want this to be misconstrued as a request for additional work, is a deeper analysis of the structural and dynamic molecular basis for the observations. In some ways, the ML is used to replace this and I think it doesn't do as good a job. It is clear for example that there are common mechanisms underpinning the allostery between these proteins, but they are left hanging to some degree. It should be possible to work out what these are with further biophysical analysis. To me, it is clear what we see here is likely some conservation in the dynamics of these proteins across the superfamily, and the allosteric mechanism involves modulation of the conformational sampling - which can happen through mutations/binding at different regions. Actually testing that hypothesis experimentally/computationally would be nice (rather than relying on inference from ML).

Achievement of aims: I think the aims are achieved, with the caveat as mentioned above, that the molecular basis for the observations is not really investigated or tested. The results support many of the conclusions, but without biophysical analysis, there is unavoidably some speculation in the discussion (which is reasonable and fine).

Impact: I think this will be impactful. I am sure others will love to get their hands on the data to run their own ML studies on, and the conclusions are interesting and impactful (seeing "deep" shared allostery across a fold). I think it is consistent with our understanding that protein folds have deep shared conformational tendencies, and that conformational sampling is at the core of much of what we term allostery.

Reviewer #1 (Public Review):

Pašukonis et al. sought to differentiate the explanatory power of two major hypotheses for sex differences in navigational ability: the adaptive specialization hypothesis, which links home range size and navigational ability, and the androgen spillover hypothesis, which links testosterone in males to navigational ability. To examine these alternative hypotheses, the authors quantify home range size, testosterone levels, and successful homing following translocation using three species of poison frog. Of particular interest, the authors were able to contrast species that vary in which sex has the larger home range, potentially disambiguating the relationship with androgens versus home range size, a feature that is lacking in many prior studies of sex differences in spatial ability. [While the authors cite one notable exception (Guigueno et al., 2014 on spatial ability in female cowbirds), they did not give this prior study as much weight as they probably should have.]

In many ways, this present study is a tour-de-force of field biology. Particular strengths include:

1) The combination of field-based observations with experimental intervention. Using intensive monitoring of individuals in the rainforest, the experimenters were able to delineate the size of home ranges, the maximum extent of movement, as well as specific behaviors (e.g., mating, parental transport of tadpoles) associated with different movement distances. This is particularly astonishing when extended to three different species.

2) The use of a natural navigational task. To assess navigational ability, the authors translocated individuals from their home ranges and determined the accuracy of, and success in, homing. While translocation is not exactly a natural experience (except for the rare occurrence, e.g., during an unusual flood), homing certainly is. Therefore, the author's assay tests wild animals in a real-world navigation problem. While the need for studying "cognition in nature" is widely recognized, it is often difficult to achieve.

3) The inclusion of multiple species that, while closely related, vary in sex roles. The authors include two species in which the male is predicted to have larger home ranges and one in which the female is predicted to do so. The potential strength of this feature is that it allows the authors to contrast the explanatory power of the adaptive specialization hypothesis - which would predict the sex with the larger home range will be more accurate and successful in homing - with the androgen spillover hypothesis - which would predict males (with their higher androgen levels) to be more accurate and successful in homing, regardless of home range size.

While the study offers a thorough and complex view of space-use and navigation in poison frogs, the study is held back by some weaknesses:

1) The comparison of accurate/successful homing across species is hampered by the application of discrete displacement distances that are not scaled to the species' natural movements. The three study species, chosen for their differences in reproductive sex roles, also differ considerably in their natural range of movements. Exploratory movements, whether near or far, give individuals the necessary experiences that familiarize them with areas so that later they can successfully/accurately return home from those areas. As a consequence, displacing O. sylvatica by 50 meters - a distance that may well be outside the range of prior experience - is unlikely to have the same significance as displacing A. femoralis by 50 meters - a species that regularly move tens of meters in a day. Species differences in accuracy/success in homing may simply reflect differences in experience, but not differences in spatial ability.

2) The authors' main conclusion is that their results contradict the adaptive specialization hypothesis for sex differences, but their results are more complex. Oophaga sylvatica is the one study species that provides the best test of this hypothesis, as the females have larger home range sizes and lower androgens. Yet, their results with O. sylvatica, in which males and females perform similarly in homing (i.e., there is a high p-value for the effect of sex), invite us to suspend judgement as to whether the sexes differ, rather than contradicting the adaptive specialization hypothesis. Not supporting one hypothesis does not necessarily lend strong support to the alternative hypothesis. Combined with the potential methodological shortcoming of using displacement distances that are not scaled to movement distances in O. sylvatica, caution is warranted.

The relationship between androgens and exploratory behaviors is an important addition to our understanding of the complexity of sex differences in spatial ability and these results do indeed provide indirect support for the androgen spillover hypothesis. Yet, more work needs to be done to disambiguate these two hypotheses in this group. Further, the authors may want to consider that both hypotheses are simultaneously at play, contributing to different features of navigation in the two sexes, and/or that the different species won't necessarily follow the same rules.

Reviewer #1 (Public Review):

This is an interesting manuscript that uses cell culture models to demonstrate the activation of mTORC1 by GPCR (GLP1R) PKA signaling and then goes on to use a PKA-insensitive mutant raptor-expressing mouse like to imply the importance of this PKA-dependent mTORC1 signaling for GLP1R agonist-dependent weight loss.

There are some important weaknesses in the manuscript as it currently stands, however:<br /> 1. There is no information on the mouse model, other than statements about the model expressing the mutant raptor in all cells and tissues. It is impossible to evaluate the results of this manuscript without some information on the genetics of the model, and some data showing the expression of the mutant, however.

2. The in vivo (mouse data) doesn't show the specificity of the weight-loss effects of GPCR-PKA signaling.

3. The cell culture data appear not to permit the direct comparison of results among conditions - is there no attenuation of Insulin-mediated pS6 by KT and no attenuation of Lira-mediated pS6 by MK? Relatedly, why does MK block FSK-mediated pS6?

Reviewer #1 (Public Review):

Here the authors aim to unravel the missing link between heme receptors and heme uptake into the cell and heme utilization. Previously, these authors uncovered the hemophore CSA2 and heme receptor RBT5 as the first steps in heme acquisition, but how heme is actually taken up by the cell and utilized as an Fe source was unknown. These authors identified the ferric reductase-like proteins Frp1 and Frp2 as having major roles in heme acquisition and utilization of heme as a sole Fe source. These are the first studies to demonstrate a role for members of the ferric reductase-like family in heme uptake and utilization. Although the exact mechanisms by which Frp1 and Frp2 affect the heme pathway are still unknown, these studies will inspire many new directions into microbial heme utilization at the host-pathogen interface. The paper is well written for a diverse audience, the experiments are comprehensive and the results are consistent with the conclusions.

Tracy and I would've been more interested in seeing more depictions of the negative aspects of religion which weren't addressed enough. A good example of this would've been possibly the Salem Witch Trials and the Last Judgement.

Reviewer #1 (Public Review):

Thyrring et al. provide a nice experiment testing the role of ocean acidification on the survival of two bivalve species. This novel work is fundamental in setting a more mechanistic understanding of the impacts of climate change on ocean species survival, and secondarily on their re-distribution across the globe. To me, the strength of the paper relies on the experimental setup, and on being honest about the limitations of metabolomics, fatty acids, and amino acids in explaining these results.

Reviewer #1 (Public Review):

In this collaborative and comparative modeling paper, three groups of investigators with well-validated mathematical models of the natural history of cervical cancer explored the potential impact of disruptions in screening services such as those associated with COVID-19 on cancer incidence. Given known disparities in access to regular screening in the United States, the authors were particularly interested in identifying heterogeneity of effects - would externally imposed restrictions on screening have a disproportionate effect on women already at increased risk because of access issues such as prolonged intervals between screening, or reliance on less sensitive screening tests?

Strengths:

--The authors used three existing, well-validated cervical cancer natural history to compare results. This comparative approach, used by these authors as well as other collaborators within NCI's Cancer Intervention and Surveillance Modeling Network (CISNET), improves confidence in the overall validity and robustness of the results, given qualitatively similar findings across models that differ in terms of structure and underlying assumptions.<br /> --The models have previously been used in the context of US screening policy.<br /> --The models used birth cohorts as well as screening frequency, which accounts for age-period-cohort effects on both risk of HPV and cervical cancer as well as competing risks such as other causes of mortality and hysterectomy.<br /> --Cervical cancer screening both detects pre-malignant lesions and allows prevention of cervical cancer, leading to decreased incidence, and, for those lesions which have progressed to invasive cancer, detects asymptomatic lesions, leading to decreased morbidity and improved survival. The use of "symptomatically detected cancers" as the primary outcome of interest is appropriate.<br /> --The qualitative results are consistent with previous modeling results in the context of screening program design--the effects of a short-term delay in screening are greatest for women with a longer time since the most recent screen, or for women screened with less sensitive (cytology) compared to more sensitive (HPV) modalities. These findings were true for both short- and long-term impacts.<br /> --The policy recommendation to prioritize outreach and appointment availability for catch-up when restrictions are lifted to women who do not have up-to-date screening according to guidelines is supported by the findings.

Limitations:

--The limitations are, for the most part, those inherent in any modeling exercise and are well described and discussed by the authors.<br /> --As the authors note, the models do not explicitly incorporate disparate impacts by race/ethnicity or other social determinants of health, and thus cannot explicitly highlight disparities within specific groups.<br /> --Potential effects on cervical cancer mortality are not captured. Given the high survival of stage I cervical cancer and, in most cases, the relatively slow progression of disease, it seems plausible that even an increase in symptomatically diagnosed disease will not have a detectable effect on mortality if there is not a shift in stage distribution; however, given that treatment of invasive cervical cancer has much greater risk of short- and long-term morbidity compared to treatment of preinvasive lesions, there is likely to be an impact on quality of life if not survival.<br /> --Related, if the factors affecting underscreening are ALSO associated with delays in care once symptoms develop, there is a potential for disparate effects on morbidity and mortality as well.

These results should prove useful to policy makers, clinicians, and patients, both in helping identifying women for prioritizing access to screening services when availability is constrained or restored, and for reassuring those women who do have up-to-date screening that delays are unlikely to significantly affect their risk of developing cervical cancer.

Reviewer #1 (Public Review):

This paper introduces a detailed computational model for synaptic plasticity, that is innovative in a number of ways. First, it includes the stochastic character of many of the biophysical processes. Second, it introduces a new way to readout the plasticity cascade. Third, it fits a number of experiments that previous models could not fit. It is a complicated model and presents a step forward towards a realistic model of synaptic plasticity. The readout mechanism is artificial but does the job well.

Reviewer #1 (Public Review):

The paper by Snoeck et al. addresses the evolution of the recognition of inceptin, a peptide from insect saliva, by plant immune receptor INR, a member of LRR-type receptor-like protein family. As a first step, the authors surveyed how broad inceptin recognition is among legumes and found that it likely emerged in the common ancestor of Phaseolid legumes. By considering available genomic information and supplementing it with several de novo sequenced species, the authors were able to show that all extant inceptin receptor sequences form a single phylogenetic clade, supporting a single origin for INR evolution, an event that was followed by several independent losses. The authors also describe a closely related INR-like clade that lacks inceptin recognition. By considering chimeras between INR and INR-like receptors, the authors map specificity to C1 (leucine-rich repeat) and C2 (insertion domain) regions of the protein. By testing inferred ancestral INR sequences they limit the number of amino acid residues responsible for the original ability to recognize inceptin to just a few residues.

The approach is well reasoned, the two complementary functional assays - ROS time course and ethylene accumulation time point - are qualitatively concordant, and the controls - expression level in heterologous assay - appropriate. Phylogenetic conclusions are likewise well supported. The authors have also done well to make the data on newly sequenced organisms available through NCBI.

There are two aspects of the study that could be improved. One is following up on the genomic events leading to independent INR loss events. Were there deletions, transposon insertions, point mutations leading to early stop codons, etc.? The other missing part is a structural interpretation of mutations leading to inceptin recognition. While I agree with the authors that an experimental structure of INR/peptide/co-receptor would be ideal, an AlphaFold or RoseTTaFold model of the N3/N4/N14 series might highlight where the key changes occurred leading to inceptin recognition. It could also hint at the N3 function, for example, was N3 already a likely foreign peptide receptor?

Reviewer #1 (Public Review):

Ryu V et al. performed a series of elegant studies to reveal a brain atlas for glycoprotein hormone receptors (i.e. TSHRs, LHCGRs, FSHRs) using combined coordinated methods and techniques including the RNAscope to detect mRNA at the single-transcript level. They find that these receptors and genes are differentially distributed in many brain regions, nuclei, and sub-nuclei. Generally, this is a timely and important study to reveal previously unknown but important central distributions of genes encoding anterior pituitary hormone receptors, providing a key resource for scientists to study the roles played by central anterior pituitary hormone receptor signaling in physiological and pathological conditions.

The experiments were designed and performed properly. The data were analyzed and interpreted accurately and presented logically in the manuscript. The conclusions of this paper were well supported by the data.

Reviewer #1 (Public Review):

This manuscript analyzes COVID-19 associated mortality in the pre-Omicron and Omicron eras to assess whether there is evidence of lower mortality associated with the Omicron variant in a large population spanning multiple countries. They used population-level data on variant frequency to infer the time periods when Omicron emerged in different countries. While there are weaknesses associated with this assumption which are well discussed by the authors, they provide a validation analysis with individual-level data from a smaller subsample suggesting that the categorization of pre-Omicron and Omicron periods is able to correctly discriminate between patients infected with different variants in the vast majority of cases. We can therefore have high confidence that the patients in the analysis are in most cases correctly identified as being likely to be infected with Omicron. The advantage of using the population-level definition is of course to allow using much larger sample sizes to determine the mortality risk associated with different variants.

Many of the tables presented suggest that the clinical characteristics of patients differed substantially in the pre-Omicron and Omicron periods, so that it is necessary to adjust for many of these characteristics (age, vaccination status, comorbidities) in order to compare mortality rates. The analysis also adjusts for country-level effects by including a random effect in the model, so that the odds ratios can be interpreted as being the average country-level effect on mortality of Omicron emergence. The results strongly suggest that after adjusting for country-level changes in clinical characteristics of patients, the risk of mortality was lower for patients hospitalized with COVID-19 during the Omicron era than previously.

There are reasons to be cautious about interpreting the results as being entirely due to differences in variant virulence, which I think are well discussed by the authors, including potential residual confounding, and potential increases in incidental infections in patients hospitalized for non-COVID-19 reasons, which would lead to a lower mortality rate in the Omicron era independently of changes in variant virulence. However, the consistency of the results with other sources of data suggests there is good reason to believe in my opinion that at least some of the observed differences in mortality risk can be attributed to lower virulence of Omicron.

While the analysis includes data from multiple countries, the vast majority of observations came from two countries (UK and South Africa); the study, therefore, has limited power to assess if there are differences across countries.

Reviewer #1 (Public Review):

This is a beautiful paper, which blends strong theoretical results (very well organised in the supplementary material) with intuitive descriptions of the results. The novelty of the theoretical developments in their own right is perhaps eclipsed by similar recent theoretical work in deep learning around the neural tangent kernel, but it is nevertheless great to see these ideas shed light on neural phenomena -- and this paper does this very well. We found that the study is given just the right scope: two learning tasks of increasing difficulty, both simple enough to enable mathematical analysis yet close enough to the type of tasks used in neuroscience as to enable meaningful comparisons to neural data. It is rare enough to be mentioned: the figure are beautiful and we found them of very high illustratory value (e.g. Figs 3 and 7, in particular, allowed us to understand the main results in a matter of seconds). We haven't found any issue in the analysis and the paper is in great shape already.

Reviewer #1 (Public Review):

Primordial germ cells are formed in the posterior pole of developing Drosophila embryo via taking up of maternally supplied germline determinants (a.k.a., germ plasm). PGC formation occurs approximately at the stage of 10th nuclear division cycle, located between minor and major ZGA waves which take place in somatic nuclei. Zelda and CLAMP are two key factors essential for global zygotic genome activation in soma. Since Zelda mutant retain apparently intact PGCs, Zelda has been thought to be dispensable for PGC formation. However, in this study, the authors identified slight loss of PGC number in both mutants lacking Zelda and CLAMP, which led authors propose a model in which somatic ZGA factors influence PGC specification.

The authors show that maternal or zygotic RNAi against Zelda or CLAMP caused abnormally broader distribution of germ plasm and resulted in an abnormal positioning of PGCs slightly away from posterior poles. The authors suggest that germline determinants are not efficiently captured by the cellularizing PGCs. As a result, the number of specified PGCs was slightly fewer. The Authors further show abnormal segregation of centrosomes accompanied with (and may be a cause of) an abnormal germ plasm trafficking. Moreover, authors show an aberrant pattern of gene expression both in soma and PGC, such as reduction of dpp transcript in posterior region, reduction of tll in posterior, and increased slam and sxl-pe in nascent PGCs when their global transcript is normally silent, suggesting that the germline-soma distinction is compromised in these mutants.

Strengths:

Historically, PGC specification in Drosophila has been believed to occur mainly by preformation-based mechanism. However, the authors focus on extrinsic regulations, particularly, function of centrosomes and cytoskeletons in proper transport of germ plasm components. This is a certainly important aspect to understand similarity and differences of PGC specification mechanism across species. The same group has demonstrated several mutant conditions causing aberrant extrinsic regulation of PGC specification in the past, and thus they are uniquely suited to pursue this line. The authors monitor germ plasm localization and gene expression by smFISH, which enables quantitative analyses. Detection of nascent transcript also reports zygotic transcription in a highly quantitative manner.

Weaknesses:

Overall the manuscript is descriptive and does not clearly provide functional interpretations of observed phenotypes. Specifically, the authors need to consider and discuss potential mechanism of this process.

Reviewer #1 (Public Review):

This study is a follow-up to the previous work by the authors in establishing a surprising role for the presynaptic adhesion molecules, neurexin (Nrxn) variants containing the SS4+ splice site, in differentially controlling postsynaptic NMDA and AMPA receptors by forming links through a shared system of extracellular cerebellins (Cbln) and postsynaptic GluD1. Here the authors show at CA1 to subiculum synapses, that the role for Clbn2 in mediating the effects of Nrxn1-SS4+ and Nrxn3-SS4+ in enhancing NMDAR and suppressing AMPAR, respectively, is redundant with that of Clbn1. Moreover, Clbns do not appear to play a role in synapse formation. Dai and colleagues extend their previous work also by highlighting the common function for Nrxn-Clbn signaling system across different synapses albeit with subtle differences and point to a lack of a role for Nrxn-Clbn signaling in morphological synapse development. Overall the data are solid, while the key findings are mostly incremental, and the basis for the selectivity in the observed differential regulation of AMPARs and NMDARs via the same trans-synaptic link through Clbns at various types of synapses remain to be clarified. Importantly, the authors make a definitive conclusion concerning the lack of a role for Nrxn-Cbln signaling complexes in synapse formation during development. Nevertheless, this is a contentious issue, and as such, the conclusions could be more compellingly supported with further experiments.

Equillibrium Vapor Pressure definition - rate of evaporation = rate of condensation.

The stronger the IM forces. The lower the vapor pressure.

Reviewer #1 (Public Review):

This paper considers decision-making problems when information and/or reward changes over time. It shows that the policy - the decision boundary that tells subjects when to make a decision - can have a very complicated shape; much more complicated than is typically considered. The authors use well-established techniques in reinforcement learning, but apply them in regimes where they are not normally used. Possibly the most important aspect of the paper is that it presents the relevant techniques in a reasonably accessible manner (and with a little work it could become very accessible). The paper also shows, in one non-trivial decision-making task, that normative models outperform heuristic ones by a large margin.

Reviewer #1 (Public Review):

Fibrotic change is a widespread biological phenomenon associated with both normal development and abnormal responses, often in response to pathological circumstances. In the heart, it is associated with both pump failure and arrhythmic change. This present study presents an intriguing murine genetic platform in which such processes are reduced. This used diphtheria toxin A (DTA) on a PDGFRa-CreERT2/+ mouse line. The authors report a reduction in ventricular, atrial and septal fibroblast density. However, this was surprisingly associated with relatively normal cardiac function with relatively normal histology and heart to body weight ratio, cardiomyocyte cross-sectional area, and ejection fractions, left ventricular (LV) chamber size, systolic and diastolic blood pressure, despite reduced collagen VI but not laminin and collagen IV levels. There were only minimal extracellular matrix proteomic changes. Furthermore, left anterior descending artery ligation left relatively moderated mortalities, unaltered changes in cardiac mass, measures of left-heart failure and LV chamber size, with actually better ejection fractions in fibroblast-ablated mice. Furthermore there was a reduced pathological compromise of cardiac function following profibrotic angiotensin II/phenylephrine challenge. Fibroblast ablation here did not affect cardiac mass or lung weight, sparing diastolic and slightly reducing systolic LV chamber size. Yet WT and fibroblast-ablated mice respectively showed slight decreases and fully recovered LV ejection fractions. These findings suggests the value of this platform for studies of the effect of fibrosis following normal or pathological change.

Reviewer #1 (Public Review):

The main result of the paper is a statistical dependence between the evolved size control strategy and the structure of the cell cycle, in that size control that manifests early (later) in the cell cycle tends to give adder- (weakly sizer-) like strategies. Notably, even when the final evolved network shows weak adder or weak sizer-like behaviour, they find strong sizer-like control in the evolutionary transient. Finally, they constrain the evolutionary algorithm to sense cell size only through stochastic fluctuations of protein concentrations and uncover a strategy that exhibits hallmarks of self-organised criticality.

The questions studied by the authors are both interesting and timely, and their results are intriguing and well documented. On the whole, the conclusions are convincingly argued, and the authors do an excellent job of extracting qualitative features from their evolved networks. However, the manuscript is a little difficult to read, with the figures being crowded and difficult to parse. In addition, while there is a lot of detail in some places (as in the description of one particular feedback control strategy), other results are less fleshed out (such as statistical summaries of the different simulations). The manuscript would benefit from a sharper presentation of the results.

A particularly interesting question addressed in the paper is why adders are more commonly found when sizers are believed to be better at controlling cell size. Here, the authors' simulations give two answers: first, that sizers tend to appear when cell size control is exerted later in the cycle (as in S. pombe). Second, that even when adders eventually evolve, the evolutionary transient passes through a strong sizer strategy. As the adder-vs-sizer question is repeatedly raised, it would strengthen the paper to have a longer and sharper discussion on (a) why early cell size control favours adders, and (b) why sizers appear as transients when fluctuations in cell size are large?

The final part of the paper, which describes a strategy based on sensing size through concentration fluctuations, is very interesting but brief, which is understandable given the quantity of results presented earlier in the paper. Nonetheless, it provides an excellent example of the power of the authors' approach.

Overall, the results in this paper are a compelling addition to the recent interest in cell size control.

Chadeau-Hyam, M., Wang, H., Eales, O., Haw, D., Bodinier, B., Whitaker, M., Walters, C. E., Ainslie, K. E. C., Atchison, C., Fronterre, C., Diggle, P. J., Page, A. J., Trotter, A. J., Ashby, D., Barclay, W., Taylor, G., Cooke, G., Ward, H., Darzi, A., … Elliott, P. (2022). SARS-CoV-2 infection and vaccine effectiveness in England (REACT-1): A series of cross-sectional random community surveys. The Lancet Respiratory Medicine, 0(0). https://doi.org/10.1016/S2213-2600(21)00542-7

Franklin, J., & Stein, R. (2022, February 4). 900,000 Americans have died of COVID in 2 years of the global pandemic. NPR. https://www.npr.org/sections/coronavirus-live-updates/2022/02/04/1078100069/covid19-deaths-us

Reviewer #1 (Public Review):

The cohesin ring model postulates that DNA entry and exit must occur through one of the ring's three interfaces thus leading to entrapment. The authors previously tested this model in vitro by engineering disulfide crosslinkers into the different interfaces. Here the authors further test this model by generating cohesin complexes in which the different interfaces can be covalently closed. Using these variants, the authors show that entrapment of DNA can occur through the hinge and SMC3/SCC1 interfaces. Removal of SCC2 and/or SCC3 shows that these regulatory proteins contribute to DNA entrapment through these interfaces, respectively. Sealing of the hinge interface does not prevent entrapment indicating that transport occurs through the passage between the SMC1 and SMC3 ATPase heads. Their data are consistent with the model that DNA entrapment through the SMC and kleisin compartments can lead to initial entrapment. Opening of the hinge may be required for the establishment of cohesion while an opening of the SMC3/SCC1 interface may be required for release. Overall, this information advances our understanding of the molecular basis of DNA entrapment in the cohesin complex.

Reviewer #1 (Public Review):

Mackevicius et al image CA activity in nucleus HVC of isolated singing zebra finches before and after tutor exposure. HVC is well known for its sequential activity during singing - and isolate song is known for its abnormal variability, raising two possibilities. Tutor exposure and subsequent practice may or may not be necessary for chain foundation. Because birdsong is a learned behavior but also subject to innate predispositions, the current manuscript provides a really important test of how nature vs nurture affects the development of song - at the mechanistic level. The authors discover HVC chains do exist, but they are unusually uncoupled from vocal output. More, the more immature chain formation is at the time of tutor exposure, the more copying there is. This finding that the existing HVC chain could become time-locked to new acoustic elements is an important verification of the long assumed, but never explicitly tested, idea that plasticity in the HVC-RA pathway drives phonological change during natural development. These results are really important for the songbird field - as they mechanistically link the timing of tutor exposure to HVC chain maturity to imitation quality. These results also will be useful for the general community of biologists interested in how innate predispositions for animal behavior can express at the level of signals and circuits.

Reviewer #1 (Public Review):

In this study, the authors compare computational MD simulations with functional activity data to determine if ligand activity can be predicted from simulations. As a test case, the authors use the ligand-binding domain (LBD) of an ancestral steroid receptor (AncSR2) that they and others have previously studied, providing a well-characterized system for their analyses. The studies include wild-type (WT) AncSR2 as well as four mutant proteins where a single methionine residue that contacts the steroid hormone within the pocket (Met75) was mutated (to Ala, Phe, Ile, or Leu). Computational analyses are performed to assess the stability of the complexes and determine whether the conformational ensembles generated show similarities or differences between the WT vs. mutant forms, or apo vs. ligand-bound forms (aromatic vs. 3-keto non-aromatic A-ring, EST/estrogen vs. progesterone/PROG). Simulations included conventional and accelerated methods. Clustering analysis of the accelerated simulations revealed some similarities and differences, which the authors then compare to luciferase reporter assay data (Gal4-fusion + WT vs. mutant LBDs) for the mutants where they performed dose-response experiments (up to 1 µM ligand added). One of the mutants studied did not show any activity (M75I); however, M75I and M75L both showed increased basal transcriptional activity (constitutively active) vs. WT without an exogenously added ligand. The authors developed a fluorescent ligand binding assay and showed the M75I mutant does not bind ligands (at least up to 1 µM added ligand). Next, hydrogen/deuterium exchange mass spectrometry data are provided to inform how the M75L mutant is constitutively active. The HDX results indicate that several regions display higher deuterium uptake in the M75L mutant and PROG binding has a larger destabilizing effect on WT vs. M75L. Finally, some structural snapshots from the MD simulations are shown (Fig 6A-C) that the authors claim to explain the altered transcriptional response of the M75 mutants vs. WT.

This study may be one of the first to attempt to make qualitative correlations between computational simulations of ligand-bound/free nuclear receptor LBDs and functional outcome. One could see a future where many different ligands are docked and a more quantitative, streamlined pipeline is used to predict functional outcome-this study takes the important first step in trying to determine if there are simulation-function correlations.

Reviewer #1 (Public Review):

It is a strength of the current manuscript that it provides a near-complete picture of how the metamorphosis of a higher brain centre comes about at the cellular level. The visualization of the data and analyses is a weakness.

I do not see any point where the conclusions of the authors need to be doubted, in particular as speculations are expressly defined as such whenever they are presented.

The fact that molecular or genetic analyses of how the described metamorphic processes are organized are not presented should, I think, not compromise enthusiasm about what is provided at the cellular level.

Reviewer #1 (Public Review):

In this manuscript, the authors use time-lapse microscopy in growing intestinal organdies and computational modelling to demonstrate a paradigm for the control of a pool of proliferative cells. They find strong correlations in the proliferative behaviour of sister cells. They propose a compartmentalised model, where cells in one compartment all have a high propensity to produce two proliferating daughter cells while cells in the other department produce daughter cells who both cease to proliferate.

The work establishes a previously suggested paradigm for the control of fluctuations in a pool of proliferating cells. This paradigm might be relevant for tissues other than the intestine such that this work will be of relevance to the general field of stem cell biology. I found this work to be a nice combination of modelling and the conclusions overall convincing. The authors could improve upon the precision in their wording and the discussion of the scope of their modelling results.

Reviewer #1 (Public Review):

In this study, Apiz-Saab et al. build up prior work by the Muir lab, which examined the metabolite composition in the tumor microenvironment and found that some metabolites like arginine are present in very different levels from that in our standard culture media. In this study, the authors have formulated a custom media based on the composition of the tumor interstitial fluid (TIF media or TIFM) and found that pancreatic cancer cells cultured in this media have a metabolic state more like tumors in vivo. This is primarily driven by very low levels of arginine, which induces arginine biosynthesis is the cancer cells to cope with this nutrient limited state. Using genetic and pharmacological approaches, the authors demonstrate that arginase expression within tumor-infiltrating myeloid cells drives tumor microenvironmental arginine depletion in vivo.

Strengths:

This is a very rigorous, well-designed study and the findings are broadly interesting for the metabolism, immunometabolism, and pancreatic cancer communities. The methods are comprehensive and the experimental details in the legends are complete. The discussion is particularly well developed and does an excellent job of putting the findings in the context of the field.

Weaknesses:

The claim that arginine biosynthesis is an adaptation to myeloid arginine depletion could be further supported in vivo.

Yale researchers develop RNA-based therapy that clears SARS-CoV-2 from mice. (n.d.). EurekAlert! Retrieved January 9, 2022, from https://www.eurekalert.org/news-releases/934454

Reviewer #1 (Public Review):

Gupta et al. investigate a new molecular mechanism whereby the ETS transcription factor, ETV1, is upregulated in prostate cancer. Through a series of experiments in prostate epithelial and prostate cancer cell lines, including gene knockdown, knockout and reconstitution, they demonstrated that the concomitant loss of ERF and CIC enhance malignant phenotypes such as cell viability, invasiveness and migratory capacity. Their in vitro results were supported by in vivo subcutaneous tumour xenograft assays in immunodeficient mice. Additional analyses of publicly available data and multiple in-house assays indicated that ERF and CIC target ETV1, acting as transcriptional repressors and modulating ETV1-mediated transcriptional pathways. Finally, the authors show that ETV1 chemical and genetic inhibition moderately decrease cell viability and significantly decrease invasiveness in ERF and CIC deficient prostate cancer cells.

A major strength of this paper is the range and number of analyses performed to test their hypothesis that CIC and ERF cooperate to suppress ETS target genes in prostate cancer. The authors combine both publicly available and in-house data to answer their research questions, which are logically set out in the results section. However, there are also limitations specific to these data that slightly diminish the quality of the paper and make interpretation of their results difficult for the reader.

The premise of the molecular work is based on data from the cBioPortal but it is difficult to fully grasp the results presented due to study and assay numbers being omitted and figures being hard to interpret. The significance (or lack thereof) is also not specified in the text for a number of the subsequent cell line analyses and could be made clearer, especially when the authors are describing a trend rather than significant results. A key analysis method, single-sample Gene Set Enrichment Analysis, used to answer a question central to the paper's conclusions (whether ERF and CIC regulate ETV1 transcription), is poorly explained and presented in the methods and results sections. Furthermore, the methods section does not align with the results section, there is a missing methodology (e.g., how was the PNT2 gene expression data generated?), there are instances of figures being misnumbered and/or insufficiently described/labelled, and missing supplementary data. Finally, while the authors present what appears to be very clinically relevant data showing sensitivity to ETV1 inhibition was enhanced in cells with both ERF and CIC loss, they only present experiments in a single prostate cancer cell line. Given the potential clinical relevance of these data, further in vitro and in vivo assays in the other available cell lines would have provided further evidence for their conclusions, especially given the higher metastatic potential of one of these (PC-3 cells).

Despite the limitations described above, the interpretation and overall conclusions the authors draw from their analyses are generally sound. The study represents an advance in our understanding of how ETS family transcription factors are dysregulated in prostate cancer and suggests a new sub-class of prostate cancer patients based on somatic tumour alterations. Significantly, these patients could one day benefit from targeted ETV1 inhibitors, which are currently being assessed in clinical trials for other cancers.

Reviewer #1 (Public Review):

The current study by Sakabe et al identifies an adrenergic signaling mechanism controlling cardiac regenerative capacity in mice. Using pharmacological and genetic loss-of-function studies, the authors demonstrate that inhibition of beta adrenergic signaling prolongs the cardiac regenerative window in neonatal mice. The study mechanistically connects several signaling pathways that are known to control cardiomyocyte proliferation including adrenergic signaling, G-proteins and the Hippo/Yap pathway. The results are potentially clinically significant given the widespread use of beta blockers in heart failure management.

Strengths:<br /> This is an impressive body of work that addresses an important and largely unresolved question in the field regarding signaling mechanisms controlling cardiac regeneration in the postnatal period in mammals. Through pharmacological and conditional genetic loss-of-function studies the authors provide several lines of evidence implicating the beta adrenergic signaling and the Hippo/Yap pathway in cardiomyocyte proliferation. The conditional genetic loss-of-function studies are a particular strength of the manuscript and provide strong support for the Gas/Yap-dependent nature of the cardiomyocyte proliferative response to beta adrenergic blockade.

Weaknesses:<br /> Although the study clearly implicates beta adrenergic signaling in the developmental regulation of cardiomyocyte proliferative potential, it is unclear whether the protective effects observed following myocardial infarction are due to cardiac regeneration or alternative mechanisms (e.g. immunomodulation, inhibition of cell death, angiogenesis, reduced contractile loading, improved coronary flow, etc). Induction of cardiomyocyte proliferation following administration of metoprolol in neonatal mice is fairly modest (~0.3% pH3-positive cardiomyocytes) and it seems unlikely that such a small number of proliferating cardiomyocytes could mediate such marked effects on cardiac function and fibrosis post-MI. In the absence of definitive data demonstrating that improvements in cardiac function are due to induction of cardiomyocyte proliferation (and by inference cardiac regeneration), such conclusions should be tempered. In addition, it is unclear why beta blocker studies were not conducted in adult mice (rather than P7/P14 mice) to determine whether inhibition of this pathway is sufficient to induce adult cardiomyocyte cell cycle re-entry and regeneration post-MI.

Reviewer #1 (Public Review):

This study reveals for the first time the involvement of Prdx5 in the differentiation, of osteoclast and osteoblast, which are key cellular components of bone remodelling. This novel function of Prdx5 was shown to be mediated by specific binding and regulating the function of hnRNPK, which acts as a transcription factor in bone remodelling. Moreover, Prdx5 was shown to be colocalized with hnRNPK during osteoblast differentiation. In support of this findings, the authors also reported that mice deficient for Prdx5 expression (Prdx6KO) showed osteoporosis-like phenotypes, which was associated with reduced osteoblast and increased osteoclast differentiation.

It is important to emphasise that the osteoporotic phenotypes were only demonstrated in males, but not in female mice. The observed phenotypes were not hormone-dependent, as no significant differences in examined bone parameters were observed between wild type and Prdx5KO female mice in an ovariectomy-induced osteoporosis model. However, women over 50 have a four times higher rate of osteoporosis compared with men, and the role of testosterone in the development of osteoporosis in Prdx5KO mice should be investigated. It is known that the osteoporosis is increased in men with low level of testosterone.

It is misleading for authors to state throughout the manuscript that osteoporotic phenotypes are observed in Prdx5KO mice, while it is only observed in male mice.

Reviewer #1 (Public Review):

In this manuscript, Williams et al. present a mainly bioinformatic analysis of HERV-K(HML-2) related retroviruses in Old World Monkey species. HML-2 viruses represent the youngest clade of human retroviruses and have also been shown in other primates. This manuscript is focused on identifying and characterizing HML-2-like proviruses in rhesus macaques. A majority of the identified proviruses (106/145) contain sequences that the authors determine were derived from ancient recombination with a HERV-K(HML-8)-related virus (likely after the OWM/great ape split). They further identify similar sequences in white-cheeked gibbons, which they conclude suggest interspecies transmission. Several of the viruses have deletions that disrupt the Rec-Response-Element (RcRE), which interacts with the viral Rec protein.This has previously been shown to be essential to overcome the host cell restrictions to nucleo-cytoplasmic export of unspliced/partially spliced mRNA. Export of this kind of RNA is essential for viral structural protein expression and genome packaging. The authors suggest that sequences derived from HML-8 contain a Constitutive Transport Element (CTE) that replaced the Rec-RcRE export system in the recombinant proviruses.

Strengths:<br /> This manuscript presents a comprehensive bioinformatic analysis of HML-2 like HERV-K proviruses present in rhesus macaques. Several of the authors are well-recognized experts in this kind of analysis and have published extensively in this area. They present convincing evidence (based on analysis of age, intact Open Reading Frames (ORFs), as well as insertional polymorphism) for recent and maybe even ongoing infectious activity of these viruses in rhesus macaques. The identification of the ancient recombination with HML-8 sequences is interesting and allows the authors to reasonably suggest that this event happened after the split of old world monkeys and great apes. The analysis led to the discovery of LTR deletions in recombinant proviruses. These were verified using PCR on genomic DNA and since the deletions included parts of the RcRE, this would indeed suggest that Rec/RcRE function is absent. This was also supported by the lack of function in conjunction with Rec, using a previously described reporter system, where GFP expression suggests the export of unspliced mRNA. However, when sequences from the 3' LTR (derived from HML-8) in the recombinant proviruses were tested in this reporter, GFP protein expression was observed in the absence of Rec. Based on this, the authors suggest that these sequences contain a Constitutive Transport Element (CTE). This is a potentially very interesting finding.

Weaknesses:

With the exception of the PCR analysis and the reporter assays, the manuscript does not contain any experiments or attempts to analyze current expression from any of the identified proviruses. No long-read RNASeq or other RNA analysis on cytoplasmic RNA was performed, nor any experiments to show that proteins are indeed expressed. The findings of a potential CTE are interesting, but the sequences that were appended to the reporter construct are much longer than previously identified CTEs. No data were presented to indicate whether this sequence show similarity to previously identified CTEs and no experiments to show whether this sequence functionally interacts with Nxf1, the protein shown to interact with previously identified bona fide CTEs. Also, since nucleo-cytoplasmic export was not directly analyzed, it remains possible that the sequences that were inserted into the reporter contained splice sites that would allow the RNA to be spliced "downstream" of the GFP gene, allowing the export of a "spliced" GFP mRNA.

Reviewer #1 (Public Review):

In their manuscript, the authors compared the CHC quality in around 50 different, including distantly related fruit fly species that occupy diverse habitats. Based on correlative data (produced by appropriate statistical analyses), they hypothesise that methyl-branched alkanes (mbCHC) might be decisive in resistance against desiccation in these species. They confirm previously published results that rather than the amount of CHC their quality plays an important role in desiccation resistance. Moreover, their results indicate that desiccation resistance increases with longer mbCHCs. In mbCHC coating experiments, the authors tentatively support their hypothesis.

Overall, the data are impressive, and their statistical analyses (Pearson's method, etc) are performed accurately yielding convincing results. These results, however, are not as strong as the statement in the abstract that longer mbCHCs are a "key determinant" of desiccation resistance. Admittedly, the authors' wording is very and appropriately careful about this issue.

One major weakness of this work is the coating experiments. The authors simply incubate Drosophila melanogaster flies with mbCHC and observe that they become more resistant to drought. Along with this "adding" experiment, "replacement" experiments should be carried out, ie add the mbCHC to flies without CHCs. Moreover, control experiments with CHCs with the same chain lengths but without branched methyl groups should be added. This point is crucial as the authors tempt with it to render their correlative data causative.

A second point that needs more attention regarding the discrepancies between males and females (e.g Fig. 3 & 5). These data are not discussed.

Reviewer #1 (Public Review):

According to the space-time wiring hypothesis proposed by (Kim, Greene et al. 2014), the BC-off SAC circuit mimics the structure of a Reichardt detector; BCs closer to SAC soma have slower dynamics (they can be more sustained, have a delay in activation or slower rise time), while BCs further away are more transient. Later studies confirmed the connectivity and expanded the model on SACs (Ding, Smith et al. 2016, Greene, Kim et al. 2016). However, physiological studies that used somatic recordings to assess the BC properties at different dendritic distances were inconclusive (Stincic, Smith et al. 2016, Fransen and Borghuis 2017). Here, the authors used iGluSnFR, a glutamate sensor to measure the signals impinging on SAC dendrites. Their experimental findings align with the space-time wiring hypothesis, revealing sustained responses closer to SAC soma (mediated by prolonged release from type 7 BCs, and only slightly affected by amacrine cells), which according to their simulated SAC should produce a substantial increase in direction selectivity (DS).

I find the work to be clear and well presented. However, I do have some reservations with the findings:

Main points:<br /> 1. Very low number of cells examined in the key experiment presented in the first figure. The authors used a viral approach to express flex- iGluSnFR in SACs in Chat-Cre mice. Sometimes (apparently twice) the construct was expressed in individual SACs - this is a very underpowered experiment! The low number of successes precludes adequately judging the validity of the findings.<br /> 2. The model doesn't represent key known properties of BC-SACs and the interactions within SAC dendrites. First, the authors decided to construct a ball and stick model that doesn't consider the dendritic morphology of the starburst cell. A stimulus moving over a SAC is expected to engage multiple dendrites with complex spatiotemporal patterns that are expected to have a substantial effect on the voltages recorded on the investigated dendrite (Koren, Grove et al. 2017). For example, the dendrites in the orthogonal orientation will be activated at about the same time as the proximal dendrites; how such strong input will affect dendritic integration is unclear but should be taken into account in the model. Second, the authors assume a similar peak BC drive between proximal and distal inputs. However, a recent study found an enhanced glutamate release from proximal BCs, mediated by cholinergic SAC drive ((Hellmer, Hall et al. 2021); not cited). How different release amplitude would affect the conclusions of the model?<br /> 3. Another reason for including an accurate dendritic morphology is in the differences in the number of BCs that target a cell. Because SAC dendrites cover the entire receptive field area, type 7 BCs, which occupy the proximal third of the dendrites (Ding, Smith et al. 2016, Greene, Kim et al. 2016), are expected to cover only 11% of the area covered by SAC dendrites (1/3 x 1/3 = 1/9) and correspondingly mediate just 11% of the BC drive. A non-bifurcating model presented here would dramatically overrepresent their contribution to SAC responses.<br /> 4. (Fransen and Borghuis 2017) found that off-SACs have a more pronounced distinction in the time to peak than on-SACs. I found it surprising that given the large body of work demonstrating the effectivity of the viral approach in expressing iGluSnFR in off BC (Borghuis, Marvin et al. 2013, Franke, Berens et al. 2017, Szatko, Korympidou et al. 2020, Gaynes, Budoff et al. 2021, Strauss, Korympidou et al. 2021), that the authors did not compare between on and off SAC populations.<br /> 5. Recent work (Gaynes, Budoff et al. 2021) suggests that BCs' responses to motion and to static flashes have distinct dynamics. However, the current manuscript tests responses to flashed stationary stimuli experimentally, and then combines them in a simulation modeling a moving stimulus. This potential limitation of the study should at least be discussed.

Reviewer #1 (Public Review):

The manuscript "Interplay between PML NBs and HIRA for H3.3 dynamics following type I interferon stimulus" by Kleijwegt and colleagues describes a study that's set out to explore the details of the PML-HIRA axis in H3.3 deposition at ISGs upon IFN-I stimulation. First, the authors establish that HIRA colocalized at PML NBs upon TNFa and TNFb treatment. This process is SUMO-dependent and facilitated by at least one of the identified SIM domains of HIRA. Next, the authors set out to determine whether interferon responsive genes (ISGs) are dependent on HIRA or PML. By knocking-down either HIRA or PML, only an effect on ISGs was observed when PML was knocked down. In fact, immune-FISH showed that PML NBs are in close proximity of ISGs upon TNFb treatment. To address the histone chaperone function of HIRA, the deposition of the replication-independent H3.3 on ISGs is tested. In specific, the enrichment of H3.3 across the ISG gene body. ChIP-seq data (Fig 5B) showed an enrichment around the TES, whereas qPCR (Fig 5A) showed less convincing enrichment (for details see below). When either HIRA or PML are knocked down, a mild loss of H3.3 enrichment was observed (Fig 5E). Interestingly, when HIRA is sequestered away from PML NBs by Sp100, an increased enrichment of H3.3 was observed. To understand the interplay between H3.3 deposition and HIRA's role in this process in the presence of PML NBs, H3.3 was overexpressed. Two population of cells were observed: low or high levels of H3.3. In the former, HIRA formed foci and the latter, HIRA did not form foci. Surprisingly, when HIRA is overexpressed, PML NBs form in the absence of TNFb. Finally, a two-sided model is proposed, where PML NBs is required for ISG transcription promoting H3.3 loading. The second side is that PML NBs function as a "storage center" for HIRA to regulate its availability.

Overall, it the model is intriguing, but the data presented seems insufficient to support the current claims.

Major concerns:<br /> - The suggested function of HIRA at the PML NBs as storage is interesting. Ideally, this would be tested by real-time single molecule tracking.

- The link between PML NBs containing HIRA and H3.3 deposition is very intriguing and indeed the ChIP-seq data shown in Figure 5B shows a clear increase in the H3.3 signal around the TES. This distribution is very intriguing as recent work (Fang et al 2018 Nat Comm) showed that H3.3 deposition across the gene body was diverse and dynamic. Ideally, the qPCR of some select ISGs would confirm the ChIP-seq data. Here a more complex picture emerges. Just as with the ChIP-seq, a modest decrease of H3.3 at the TSS was observed, but only in 2 of the 3 genes shown is H3.3 enriched at the TES and only in 1 gene (ISG54) is H3.3 enriched at the gene body. As qPCR is later used in the manuscript (Fig 5E and 5G), it is essential that the results of two different techniques give similar results. With regards to Fig 5E and 5G, it is unclear why certain gene regions are shown, but not others.<br /> Overall, the link between HIRA and PML in H3.3 loading is only mildly affected (Fig 5E and 5F). The conclusion that HIRA and PML are essential (Page 12, line 8) is not represented by the presented data. The authors propose that DAXX could play a role. Indeed, work on another H3 variant, CENP-A, showed that non-centromeric localization is dependent on both HIRA and DAXX (Nye et al 2018 PLoS ONE). It would be interesting to learn if a double knock-down of HIRA and DAXX can prevent the enrichment of H3.3 at TES of ISGs upon TNFb treatment.

- In Figure 6B, two versions of HIRA are overexpressed and the authors conclude that the number of PML NBs goes up. Earlier in the manuscript, the authors showed that PML NB formation upon IFNb exposure brings HIRA into the PML NBs via a SUMO-dependent mechanism. Is overexpression of HIRA and its accumulation in PML NBs also SUMO-dependent or SUMO-independent? Overexpressing the SIM mutants from Figure 3F would address this question. In addition, the link between the proposed HIRA being stored at PML NBs could be strengthened by overexpressing HIRA and see at both short and late time points whether H3.3 is enriched on ISG genes.

- BJ cells are known to senesce rather easily. Did the authors double-check what fraction of their cells were in senescence and whether this correlated with the high or low expression of ectopic H3.3?

- In Figure 6 - figure supplement D, it appears that the levels of HIRA go up upon TSA and IFNb treatment. Rather than relying on visual inspection, ideally, all Western blots should be quantified to confirm the assessment that protein levels are not affected by different experimental procedures.

Reviewer #1 (Public Review):

Neural circuits of the fruit fly mushroom body provide an interesting system to study molecular processes underlying learning and formation of memories since the input-output relationship of the circuit is quite well characterized and - importantly- genetic tools to manipulate specific circuit components are available. The current manuscript focuses on the role of different subunits of the nicotinergic Acetylcholine receptors.

The authors use a series of state-of-the-art techniques and several elegant - and partly innovative, explorative - approaches to address a specific set of neurons as models (the MBONs M4/M6), that are relevant for appetitive memories. The logic of the manuscript is overall well developed, and the experiments provided are widely in support of the model the authors propose. They first corroborate that synaptic transmission of M4/M6 is critical for appetitive memories and subsequently test different subunits of the nicotinergic Acetylcholine receptors using RNAi. Interestingly, only the alpha-5 subunit shows learning defects (acquisition or induction), while alpha-1,2, and 5 (and Dlg) show defects after 3 hours (what the authors call "memory expression"). This result indicated the differential requirement for acquisition versus that expression.

The subsequent and particularly elegant and intriguing set of experiments aims to recapitulate the processes while circumventing a direct synaptic transmission from the KCs. The authors therefore optogenetically activate DANs, while blocking KCs neurotransmitter release and measure neuronal activity in the MBONs. Only when ACh is locally applied an effect of synaptic facilitation can be observed. While this experiment is not particularly critical in the context of the current manuscript it provides a very different, complementary support for the proposed overall model.

In order to gain insight into the function of the alpha-5 and alpha-2 subunits, the authors next investigated the expression of these genes and report non-uniform patterns between the lobe systems, presumably by using GFP fusion reporters. A weakness in this section is that the technical details are not well described and thus the impact of these results remains a bit elusive. The results indicate that alpha-2 is somehow genetically "downstream" of alpha-5 and Dlg. While many parts of the manuscript are of great impact and clear, this notion - even though extremely interesting - may actually be one of the weakest parts, since no explanation for the phenomenon is provided. One would assume that dopamine signaling and coincidence detection may be involved. It is however true that the authors conceptually take this up to some degree in the discussion, particularly the point that alpha-2 may be a molecular central point to switch.

Using Calcium imaging in vivo the authors show that the physiological formation of a memory trace in M4/6 shows the expected dynamics in an alpha-2-dependent fashion and similarly that alpha-2 itself (by photobleaching) shows the expected expression/localization dynamics.

The final section is indeed an important extension and addresses the generality of the alpha-5 to alpha-2 transition by investigating familiarity rather than associative learning. The results provided are in line that this mechanism appears to be general, a point also taken up in the discussion. What I felt was especially refreshing in the discussion section is the global comparison of NMDA/AMPA as a concept and possibilities of how this task may be resolved in other systems using other transmitters, again maybe not at the molecular depth that may have added an explorative touch.

Reviewer #1 (Public Review):

This paper describes an "ERAD-like" pathway for the turnover of the SUN2 protein. In this pathway, ubiquitylation of SUN2 in the nucleoplasm by the SCFbTRCP ubiquitin ligase leads to extraction of the membrane protein by p97 for delivery to the proteasome. This process involves phosphorylation of non-canonical degrons on SUN2 by CK2, which was identified using a genome-wide crispr screening approach. The CTDNEP1 phosphatase acts to reverse phosphorylation and stabilize SUN2. Non-degradable forms of SUN2 promote altered nuclear architecture and a delay in double-strand break repair. The conclusions are based on strong biochemical and cell biological data. The paper sets the stage for further analysis of how defects in SUN2 degradation alter additional nuclear processes.

Reviewer #1 (Public Review):

In this study, the authors use a powerful mix of histone mutations, biochemistry, and proteomics to show that histones H3 and H4 are imported into the nucleus as monomers by Imp5 where they are transferred to NASP and HAT1-RBBP7 respectively. This challenges the standing paradigm that H3 and H4 are imported into the nucleus as heterodimers.

Reviewer #1 (Public Review):

Wang et al. suggested that the most prominent gene downregulated in postmenopausal osteoporosis patients is miR-27a. Data suggested that removing miR27a resulted in considerable bone loss due to disturbed remodeling. Their findings further imply that miR-27a is unnecessary for osteoblast differentiation and bone formation. This work presents good data to show that miR-27a is necessary for controlling bone resorption. The deletion of miR-27a in mice increases the number of osteoclast cells as well as key parameters for bone resorption. As a result, directing miR-27a to bone resorption surfaces using synthetic drugs such as bisphosphonates or osteoclast-targeted molecules such as acid octapeptides containing aspartic acid can be crucial therapeutics for future use and miRNAs can very well be the next wave of future therapeutics.

Reviewer #1 (Public Review):

RPG was identified as a mutant with poor nodulation in 2008, but its activity was unclear. Interest in its role was rejuvenated by a phylogenetic approach where RPG was one of only three genes that have been consistently lost in non-nodulating species in the Fagales/Fabales/Cucurbitales/Rosales families. In this careful genetic and imaging-based analysis of the role of the RPG gene in nodulation, the authors use transient and stable genetic transformation in nodulating Medicago roots to clarify the subcellular localization of RPG and its relationship to infection thread maintenance along with two other better characterized symbiosis proteins VAPYRIN (VPY) and LUMPY INFECTION (LIN). Detailed phenotypic analysis of two RPG mutants indicates that RPG is required to sustain polarization of the membrane at the advancing tip of the IT, and without RPG, the plant microtubule cytoskeleton organization, nuclear position, and localization of VPY and the cell wall modifying enzyme NODULE PECTATE LYASE all differ from normal.

The model that emerges and that is well supported by the presented data is that RPG behaves as a scaffold to convert/customize the cellular machinery that organizes cytoskeleton and membrane into something that facilitates infection thread polarity. This work established a hierarchy of "infectosome" assembly using genetics and localization of components.

The strengths are the use of new imaging modalities to define the location and functional dependencies of complex components. This paper makes numerous significant advances in the understanding of infection thread maintenance and assigning a cellular activity for RPG. It leaves open still questions about how RPG is localized to discrete puncta and how it recruits other proteins to these still symbiosis-related structures.

This is an exciting addition to the literature detailing the mechanisms by which host plant cells make environments hospitable to symbionts, the strong correlation with the presence/absence of RPG and the ability/failure to support nodulation in a variety of plant species makes RPG an attractive candidate for engineering nodulation in crop plants that currently lack it.

Reviewer #1 (Public Review):

The objective of mobile phone (mHealth) interventions in African countries is to cost-effectively increase access to care and improve health. Due to resource constraints on the healthcare systems in many African countries, inaccessibility to healthcare is more noticeable in rural areas. While there is an increase in mHealth interventions in many African countries, it is salient to examine inequity in the distribution of smartphones that enable these interventions.

Investigators used the 2017-2018 Afrobarometer data from 33 countries to estimate the percentage of the population with a mobile phone (smartphone or otherwise). The analyses were conducted at different levels: (1) among all 33 countries; (2) at the country level; and (3) at the sub-national level (within each country).

The study is well designed, and the manuscript is clearly written. The findings are important from a policy and intervention perspective. This study shows that there are substantial inequities in smartphone ownership between and within African countries. These results have important implications for designing and rolling out mHealth interventions in African countries. This study shows that people who live in rural areas are less likely to own a smartphone and less likely to live close to a healthcare center. For mHealth intervention to work, individuals who are in high need of mHealth interventions would need to own mobile phones.

Reviewer #1 (Public Review):

In this study, the authors overexpress GFP-tagged NMN-D, a prokaryotic enzyme that consumes NMN, and find that it is strongly protective in several in vivo injury paradigms in flies. This is an important finding that clarifies previously published work, which found that an untagged NMN-D construct provided only weak axon protection (Hsu et al., 2021). The authors of the current manuscript argue convincingly that the previous result stemmed from the low stability of the untagged variant. Llobet Rossell et al. also use a very nice grooming assay for synaptic connectivity following axotomy to demonstrate that NMN-D overexpression maintains synaptic connectivity. Further pointing to NMN as a crucial regulator of dSARM activation, they show that increasing NMN levels by increasing NMN synthesis through mNAMPT overexpression accelerates injury-induced axon degeneration. They provide the support that NMN-D and mNAMPT overexpression are having the expected effect on NAD+ metabolic flux via LC-MS/MS. Finally, they provide evidence that a dSARM variant that cannot bind NMN does not rescue the dSARM LOF phenotype indicating that NMN exerts its effects through dSARM.

This study is carefully done and the evidence that NMN levels are a critical determinant of axon degeneration is strong. The combination of in vivo degeneration assays, metabolomics, and behavioral assays provides confidence in the results. For the most part, the conclusions of the study are well-supported by the results. The claim that the protection afforded by low NMN levels is as strong as the loss of SARM is justified. The authors repeatedly state that protection provided by low NMN is "even stronger" than that of essential mediators of axon degeneration, which doesn't really make sense given that all their data support the hypothesis that low NMN protects because it blocks dSARM activation. However, the primary weakness of this study is that the novelty of this work comes almost entirely from showing that the NMN/NAD+ ratio is determinative for axon degeneration in Drosophila; it has already been shown both in mammalian cultured neurons and in vivo.

Reviewer #1 (Public Review):

The monogamous vole provides unique opportunities to study the neural basis of pair bonding and this study exploits that opportunity in a novel way. Focusing on the nucleus accumbens, the authors conduct RNA-Seq to characterize the transcriptome in same-sex and opposite-sex pairs when bonded, when separated for a short time and when separated for a long time at which point the literature has in the past demonstrated the willingness to form a new bond. They determine that the transcriptome of pair bonding includes a preponderance of glial-associated gene changes and that it degrades with long-term separation. To the latter point, they then conduct a neuron enriching trap schema to find those genes subject to change specifically in neurons.

The strength of the report is the clever experimental design, the unusual animal model, and the comparisons of same-sex and opposite-sex pairs and long-term and short-term separations.

The weakness is that the behavioral changes observed are not what was expected based on prior work and are relatively modest, providing a disconnect between the outcome and the more dramatic transcriptional changes. A second weakness is the focus on the nucleus accumbens which is a brain region most closely associated with reward. While pair bonding may be rewarding, that component may be independent of the memory of a partner or the willingness to partner anew. Lastly, there is no clear connection between the identified transcriptome and either the formation or degradation of the pair bond.

Reviewer #1 (Public Review):

In this paper the authors present variations in carbon oxidation state and hydration state in proteomes available in RefSeq. Then they use this information to predict community level proteomes, and their corresponding carbon oxidation states and hydration states, based on available 16S rRNA gene sequences from selected previously published datasets. When combining this with information about the environmental setting of the individual samples analyzed, the authors are able to demonstrate connections between redox conditions and proteomic carbon oxidation state and hydration state. Furthermore, they explore how individual taxonomic groups at different taxonomic levels contribute to forming these connections.

A weakness with the study is that the described environmental proteomes are inferred from 16S rRNA gene sequence data and not observed directly. However, there is good reason to believe that the conclusions drawn in the paper are valid.

The study sheds light on microbial adaptations on the genome level that so far have received relatively little attention. The paper is also interesting from an ecological perspective regarding the general question of how microbial communities are shaped by environmental settings.

Reviewer #1 (Public Review):

In this manuscript, Dodd et al. study the uptake and cytosolic release of tau fibrils. Based on a Crispr knock-out screen which identified that vacuolar H+ ATPase factors were required for tau fibril uptake, the authors focused on the role of endocytosis and endocytic acidification. Using genetic and pharmacological approaches, the authors made the surprising observation that endocytosis inhibition reduced tau fibril uptake but strongly increased fibril-induced tau seeding in the cells. Authors demonstrate that giant plasma membrane vesicles unable to undergo endocytosis still take up tau fibrils. Dodd and colleagues conclude that tau fibrils likely directly penetrate the lipid bilayer, which represents a novel entry pathway involved in tau seeding

The authors present some perplexing divergent effects of genetic or pharmacological inhibition of the endo-lysosomal system on tau fibril uptake and seeding. Surprisingly, inhibition of endo-lysosomal acidification inhibited fibril uptake but increased seeding in biosensor cells. Likewise, inhibition of Rab5a, a GTPase required for early endosome trafficking strongly impaired fibril uptake, but highly elevated tau seeding in biosensors. Low temperature during fibril incubation inhibited fibril uptake but increased seeding when cells were subsequently shifted to a normal growth temperature. Authors conclude that these results most likely show that endocytosis is not required for seeing tau. Instead, tau fibrils might directly translocate through the membrane to induce seeding.

Clearly, and rightfully stressed by the authors, the experiments demonstrate that the amount of internalized tau fibrils does not correlate with the tau seeding, arguing that minute (and potentially undetectable) amounts of tau seeds can very efficiently seed tau aggregation in biosensor cells. The massive amounts of labelled fibrils taken up by basically 100 % of cells might obscure the actual relevant tau seeds taken up by alternative routes that result in cytosolic tau seeding. This could apply to tau fibrils translocating through the membrane, as suggested by the authors, this could also apply to minute amounts of fibrils that still manage to enter the endo-lysosomal pathway even when this pathway is compromised pharmacologically or genetically. Any impairment of the endo-lysosomal system, however, likely also reduces the lysosomal degradative capacity. As a consequence, tau seeds in the endo-lysosomal system will have a higher propensity to escape to the cytosol to induce seeding. While the findings presented here are indeed very interesting and the Crispr screen is very elegant and informative, experiments are not sufficient to explain the cellular mechanisms involved.

Reviewer #1 (Public Review):

The manuscript presents an interesting study that uses the previously generated yeast strains harboring human disease-specific mutations modelled in the yeast ortholog of SEC53 (V238M & F126L variants). These variants are either controlled by a strong heterologous promoter (pACT1) or a less-efficient native promoter. In either scenario, the strains manifest growth defects. The current study uses an experimental evolution strategy to evolve the strains to identify genetic suppressors of the slow growth phenotype. The authors identify several mutations in evolved strains and find a significant number of the suppressors in phosphoglucomutase 1, PGM1 (congenital disorders of glycosylation, CDG type I human ortholog). The synthetic setup replicates the compensatory mutations, but the growth rescue did not match the primary suppressors with several other mutations suggesting synergistic effects. Furthermore, reconstituted strains harboring LOF of PGM1 also showed the growth rescue, yet none of the evolved strains possessed a LOF of PGM1. The authors identify the PGM1 suppressors to be dominant. Finally, the protein activity assays reveal that the mutations in PGM1 reduce the protein activity rather than eliminate it. Overall, the assays show the power of yeast genetics for discovering the potential therapeutic targets in human diseases such as Congenital Disorders of Glycosylation 1.

1. While the authors identify the suppressors in known genetic interactors (GIs) of the yeast SEC53, it is worth testing if the compensatory mutations are rewiring the GIs, thereby explaining the lack of comparable compensations observed in reconstituted strains. If altered GIs explain the suppression, then while yeast serves as an excellent tool to perform these assays, the human context of the disease may require a different set of genetic suppressors and, therefore, a different target than the yeast PGM1 ortholog. Also, are Sec53 and Pgm1 proteins directly interacting in yeast and whether these mutations are on the interaction interface?

2. Based on the data obtained between pACT1 and pSEC53-driven expression of the SEC53 mutant alleles, the pattern of suppressors appears to be different. Authors report that the variants expressed from strong pACT1 promoters show more suppressors than those driven by native promoters. Is this a general trend in experimental evolution that slower-growing strains tend to show lesser suppressors? For example, on Page 6, line 154, "compensating for Sec53-F126L dimerization defects are rare or not easily accessible". The statement suggests that the authors did obtain suppressors that compensate for the dimerization defect. At the same time, while rare (also, are authors suggesting suppression of dimerization defect as in better dimerization?), the rate of obtaining suppressors seems to be linked to the severity of the fitness defects of the strains. The lack of suppressors may be a limitation of the evolution experiments. Indeed later in the manuscript, the authors noticed that while PGM1 suppressors obtained in V238M can also suppress F126L alleles, the suppression was not as efficient. Could it be that evolution experiments in slower-growing strains predominantly enrich suppressors in other pathways (i.e., not in the CDG orthologs) that restore the growth better and compete out the relatively weaker suppressors in PGM1? In fact, the authors report similar effects on Page 7, lines 204-210. These two paragraphs are contradictory and should be explained further.

3. Authors report that the LOF of PGM1 compensates for the SEC53 mutations. However, the evolution experiments did not capture any LOFs in PGM1. The fitness comparisons in evolution experiments are different as many different genotypes compete in a mix. Therefore, the fitness assays in a clonal population may not represent these differences well. To test this argument, authors can try to mimic the evolution experiments by mixing two genotypes to check competitive fitness, like the co-culture of pgm1 suppressor obtained via evolution experiments with pgm1Δ.

Reviewer #1 (Public Review):

The goals of this paper were to provide structural and biochemical insight into the role that Fip1 plays as a protein interaction scaffold with other members of the cleavage and polyadenylation machinery. To that end, the authors solve two crystal structures as the featured basis for the study: FIp1 and CPSF30; Fip1 and Cst77. In both cases, subdomains of proteins were used for crystallography. These two structures are of high quality and are validated with rigorous and clear biochemistry. These points represent the technical strengths of the manuscript. One weakness of the study is the overall findings with those previously reported by the Tong laboratory. While the authors present some potentially newer information in terms of the number of PAP proteins capable of interacting with FIp1/CPSF30, there are experimental caveats that would need to be addressed first.

The novelty of the Fip1/CstF77 structure represents the strongest aspect of the paper as well as the observation that CstF77 can inhibit polyadenylation. The in vitro data support this conclusion but additional experiments would strengthen this overall model.

Reviewer #1 (Public Review):

In this work, Maxime R. and co-authors intended to investigate the consequence of dystrophin absence/alteration in myoblasts, the effector cells of muscle growth and regeneration, and the early role of such cells in the pathogenesis of the disease. They carried out a transcriptomic analysis, comparing transcripts expressed by dystrophic myoblasts isolated from two murine models of DMD (Dmdmdx and Dmdmdx-βgeo) and control healthy mice. The expression of a large number of genes, comprising key regulator of myogenic differentiation (Myod1, Myog, Pax3 etc.) resulted affected in comparison to control in both mouse lines. Authors highlighted similar gene expression modifications also in a myoblast cell line previously established from the mdx mouse. To assess the outcomes from the gene ontology analysis, which pointed on the alteration of muscle system and regulation of muscle system processes, authors evaluated the proliferative, chemotactic and differentiative capacities of dystrophic myoblasts. Myoblasts presented increased proliferation, reduced chemotaxis and quite surprisingly, improved differentiating capacity, if considering the transcriptomic data. Finally, Maxime R. and co-authors carried out a transcriptomic analysis in myoblasts from DMD human subjects. Even though the profile of altered gene expression resulted similar and the GO studies seemed to focus on the same pathway categories, a significative divergence was observed particularly at the level of gene expression.

Authors link transcriptomic abnormalities and functional changes in proliferation, chemotaxis and differentiation of the dystrophic myoblasts with the alterations (probably epigenetic changes) occurring in satellite cells of dystrophic mice, consequent to the absence of the dystrophin protein. Such modifications in gene expression are supposed to be inherited by pathological myoblasts due to the division of the SC that is no longer asymmetric as occurring in healthy tissue.

Strengths<br /> Transcriptomic data from samples of different sources are solid and rigorous statistical analyses have been carried out.<br /> Transcriptomic and functional data from primary proliferating myoblasts of the two mouse models and from the myoblast cell line are similar. This is a convincing evidence that the transcriptomic alterations observed in primary myoblasts are not influenced by the exposure to the niche environment present in the dystrophic muscle, but that are cell autonomous.<br /> Authors adopted a 3D culture for the functional analysis concerning myoblasts differentiations, in this way better mimicking the process occurring in vivo.

Weaknesses<br /> The mdx mouse phenotype is mild in comparison to the severe symptoms and the rapid disease progression experimented by most of the human DMD subjects. Mdx mice is characterized by cycle of degeneration/regeneration initiating around the age of 6 weeks and continuing for several weeks. It was expected that authors discussed this point in detail, also considering that the animals used in this study were 8 weeks old. Furthermore, transcriptomic analysis of the human DMD myoblasts highlighted many differences as well as similarities when compared to mouse samples. Why do not focus more on this aspect?<br /> According to the authors, dystrophic abnormalities in myoblasts manifest irrespective of differences in genetic backgrounds and across species. The last one is a strong statement that should have been supported at least by functional data regarding chemotaxis proliferation and differentiation of human DMD myoblasts.<br /> In the discussion, the authors suggest two possible mechanisms as responsible for alterations in the behavior of the SC that ultimately affect the functionality of myoblasts, an RNA-mediated pathological process or an alteration in epigenetic regulation. They consider the latter mechanism more likely. This is based in particular on transcriptomic data showing the downregulation of important genes involved in histone modifications, normally linked to transcriptional activation. They also reported from the literature that HDAC inhibitors upregulate MyoD, a gene that is effectively downregulated in this study. Since the authors postulate that the epigenetic dysregulation of Myod1 expression is responsible for the pathological cascade of gene downregulation, ultimately leading to the pathological phenotype, it would have been interesting to evaluate the impact of HDACi on this pathways or the overexpression of enzymes responsible for H3K4 methylation as Smid1 (downregulated in this study).

Reviewer #1 (Public Review):

The study presents the observation of the coexistence of slowly moving broad waves of high F-actin concentration and rapidly propagating planar F-actin pulses in giant Dictyostelium discoideum cells and focuses on their theoretical analysis on the basis of a 3 component activator-inhibitor reaction-diffusion model with globally conserved actin. The authors conclude that the pattern coexistence is generic in a system with mass conservation close to a primary codimension-2 T-point bifurcation. The observation of the wave patterns in Dictyostelium discoideum is interesting and adds new phenomena to intracellular self-organization and patterns. The theoretical analysis is very careful and provides deep insight into the pattern mechanism in terms of non-linear dynamics. A very interesting and careful study. Well written, excellent figures.

While the observation of the wave patterns in Dictyostelium discoideum is interesting, the focus is on the theoretical analysis - which indeed is excellent. Unfortunately, the authors did not use their experimental abilities to verify predictions of their theoretical analysis, and thus in the end the conclusions lean heavily to the theoretical side. There are little biological conclusions from the theoretical analysis. In particular, a clear discussion on whether the observations are restricted to the artificial giant cells or may also have meaning for normal-sized cells is missing.

Reviewer #1 (Public Review):

In this study, the authors use T1-weighted structural MRI and FDG-PET data from an open access cohort to estimate individual-level structural and metabolic covariance networks across the Alzheimer-continuum using well-established sites of Alzheimer's pathology as seeds, detecting clear differences between diagnostic groups. They proceed to show that the evolution of these networks along the disease continuum is associated with memory performance in a nonlinear manner, with different trajectories. The results provide insight into structural and metabolic covariance network contributions to memory performance throughout the disease course, which adds to the current knowledge about potential network-based biomarkers and might have relevance to evaluating these markers in a clinical setting.

Strengths:<br /> - The analyses were performed on a well-characterised cohort with an adequate sample size that contributes to the robustness of the results.<br /> - Taking into account the non-linearity of the association between network-based descriptors and memory performance conforms better to current hypothetical models of biomarker dynamics in Alzheimer's disease.

Weaknesses:<br /> - It is encouraging that the results were replicated in a validation dataset, however, based on the manuscript it seems it is not independent from the main analysed data. Since the individual network estimation step relies on back-projection from a group-level salience map, the generalisability of the results might be better assessed by keeping the validation dataset independent.<br /> - Along this line, the employed method estimates individual network scores that quantify the relative contribution of a certain participant to the group-level salience map. This could potentially sensitise the method to the relative imbalance of group sizes across diagnoses and/or A/T categories, or to outliers.

Reviewer #1 (Public Review):

In this well-written manuscript by Barber and colleagues from UCL in the UK, the authors seek to identify a new predictive biomarker for patients with recurrent/metastatic head and neck cancer who are treated with chemotherapy. The manuscript is clearly written. This is an impressive body of correlative research performed in the context of samples collected from patients enrolled on a phase II trial, with samples collected and analyzed for immune monitoring. There are several novel assays employed beyond the standard immune monitoring. The question is of moderate clinical significance. There are a number of critical statistical limitations.

The question is of moderate clinical significance to the field. It is correct that we have only modest predictive biomarkers for chemotherapy response in R/M HNSCC. For this study to be significant, one would want to see a marked improvement over current biomarkers, in a robust and generalizable population. Unfortunately, this study falls short in these respects. First, the authors do not adequately discuss the prior literature. Even a fairly crude and old-fashioned blood-based biomarker such as neutrophil:lymphocyte ratio has quite good predictive and prognostic capability in R/M HNSCC. It is not clear to me that there is a compelling need to do better -- given that existing predictive biomarkers based on clinical nomograms or NLR are actually used in practice.

To establish that this fairly labor-intensive and expensive assay would add value, a comparison to other existing biomarkers is necessary. It is not clear qualitatively that the biomarker presented here is an improvement beyond what is currently available. This comparison could easily be performed.

A large number (31 of 87) patients were not included due to lack of biomaterials. No analyses have been performed to examine the characteristics of these patients. It is unlikely that the collection of biomaterials has no correlation with disease characteristics, prognostic features, outcomes, or the analytes in this study. This exclusion -- akin to unequal censoring in clinical trials -- is likely to significant impact results. Given that the population enrolled in a phase II trial, and that sub-population of patients who survive long enough and are feeling well enough to submit to large volume blood draws on trial, would not necessarily represent the real world population of R/M HNSCC patients, a broader population is needed to justify conclusions about this assay having robust predictive value.

It is unclear why OS as a hard endpoint was not analyzed here. No explanation is provided, other than OS was not available, a statement that is difficult to understand, given that PFS was available, and overall survival is a component of PFS.

There is no validation set for the biomarker. The biomarker was trained and cross-validated using Bayesian techniques to reduce overfitting. This is a valid approach for training and cross-validation, but for the biomarker to be testable and interpretable, it requires assessment in an independent dataset. There is no statistical technique that I am aware of that generates informative biomarkers without an independent validation dataset, and the use of these techniques to minimize overfitting does not circumvent this limitation, if one's goal is to develop a clinically useful biomarker. The 2 articles cited to justify this approach are not germane to the question -- one is an article describing the FRET-FLIM technique, and the other article describes the effectiveness of this approach to minimize overfitting.

In the end, the degree of predictive value, as assessed by C-index and the spread in the PFS curves, is modest, and not clearly an improvement beyond currently available biomarkers. Given that this dataset is the training dataset -- with no validation dataset -- in a population that is unlikely to be representative of the R/M population, it is not clear that this expensive and labor-intensive immune monitoring approach has much to offer.

Reviewer #1 (Public Review):

Tarasov and colleagues provide data that extensively phenotypes TGAC8 mice, which exhibit a cAMP-mediated increase in cardiac workload prior to developing heart failure. The authors confirm data from prior studies, showing increased cardiac output mediated by changes in heart rate with similar ejection fraction. Interestingly, canonical markers of LV hypertrophy did not differ from wildtype mice at the time period studied. The LV demonstrated proliferation of small cardiomyocytes and a network of interstitial non-cardiac myocytes. Transcriptomic and proteomic analyses of bulk LV tissue in TGAC8 mice compared to wildtype found pathways involved in immune responses, ROS scavenging, proliferation, and apoptosis to be activated in TGAC8 mice. Similarly, metabolic profiles shifted from fatty acid oxidation to glycolysis.

The study is overall well-planned and the amount of data presented by the authors is impressive. The work nicely incorporates animal-level physiology (echocardiography data), tests for known canonical markers of hypertrophy, and then delves into an unbiased analysis of the transcriptome and proteome of LV tissue in bulk. The techniques and analyses in the study are adequately executed and within the realm of expertise of the Lakatta laboratory. This study is a necessary and crucial first step to extensively phenotype this mouse line and generate hypotheses for further work.

Reviewer #1 (Public Review):

Tilk et al investigate why cancer genomes show weak negative selection. They set out to differentiate between two scenarios whether selective pressures are relaxed during the course of tumor progression or whether selection is inefficient because of evolution without recombination thus genome-wide linkage resulting in interference among mutations referred to as Hill-Robertson interference. They calculate dN/dS for driver and passenger mutations in 50 cancer types with different levels of genome-wide mutational burden and show that passenger mutations exhibit negative selection and driver mutations show positive selection in low mutational burden tumors. The strength of selection is weakened in tumors with increasing mutational burden. The findings that the selection for passenger mutations is weak in high mutational burden tumors is novel and has not been shown before. Authors show this to be true for somatic copy number aberrations containing drivers versus passengers. Clonal mutations showed stronger selection than sub-clonal mutations. The accumulation of deleterious passenger mutations is buffered by upregulation of expression of genes encoding chaperones and the proteasome. Authors conclude that Hill-Robertson Interference can largely explain the weakened selection in drivers and passengers, which is also supported by their evolutionary model and they predict that cancer cells obtain fitness advantage from drivers by 130% and fitness cost from passengers of 40% conferring on cancer cells a net fitness advantage of 90%. This is an elegant study and the manuscript is well-written and logical. However, some aspects of the analyses require clarification.

1. Figure panels should be called out sequentially. For example, Fig. 2G is called out before Fig. 2D. This happens throughout the text, including main and supplementary figures, and should be corrected.<br /> 2. Fig. 2G shows that mean gene expression of genes encoding chaperones and the proteasome increases with increasing mutational burden. What about protein abundance? Is this in agreement with gene expression?<br /> 3. Fig. 2 mentions error bars in the figure legend, but no panel displays error bars. This is also true for Fig. S13 and other figures. Authors should display the error bars to which they are referring to make their analysis more convincing.<br /> 4. Pg. 9 line 295 describes results of the analysis across genes belonging to different GO terms. However, Fig. S13 only shows 3 categories: chromosome segregation, transcription and translation. How were these categories chosen? What about other categories? Such cherry picking doesn't convincingly support the conclusions that no specific GO functions are enriched. Also, translational regulation shows higher dN/dS in low mutation tumors suggesting that there is positive selection for passengers in this category. Authors should discuss in their manuscript why this is the case.<br /> 5. Fig. S15 shows the attenuation in selection of CNAs across cancer subtypes and broad cancer groups. However, HNSC and kidney cancer appear to be the exceptions. Authors should provide an explanation for these observations in the main text.<br /> 6. Generally, copy number variations are considered to be > 50 bp. Is there a rationale as to why authors chose 100 kb to be their cut-off in Fig. 2C? If the size of CNA is an important parameter, then authors should explain why that is.<br /> 7. Non-allelic recombination and non-homologous recombination mechanisms involving replication accidents that lead to chromosome breakage occur with some frequency in somatic cells. How does the frequency of these events impact the selection efficiency in cancer as it relates to drivers and passengers? Can this also be incorporated in their evolutionary model?<br /> 8. Authors mentioned that haploinsufficiency was not used in the model. What about loss of heterozygosity which is extensive in cancer genomes? Can this parameter be included in the evolutionary model and how would it impact the results?

Maybe cartography can be revived: https://www.reddit.com/r/interestingasfuck/comments/urp3sd/lifesize_floor_plans_for_a_better_understanding/

Reviewer #1 (Public Review):

The manuscript by Park et al. uses CLEM, cryo-milling, and cryo-ET to visualize the major morphological transitions that occur in the bacteria Coxiella burnetii as it infects mammalian cells. These bacteria move from a small cell variant (SCV) to a large cell variant (LCV) that can replicate in the host lysosome. The authors focus on the C. burnetii T4SS which is similar in composition to the legionella Dot/Icm T4SS. They generate a homology model from the sub-tomographic 3D reconstruction of a little over 7,000 T4SSs using alpha-fold and structure of the Lp T4SS. This is a very descriptive analysis of gross cellular changes that occur in this bacteria during infection. While the authors suggest models for the developmental steps they think are occurring, it doesn't appear that they have fully mined their data for a more quantitative analysis of what is happening during the transition - let alone a mechanistic model for T4SS assembly and regulation.

Major Suggestions:

1. While it seems a reasonable hypothesis that the Dot/Icm T4SS assembly is regulated during the SCV-to-LCV transition it is unclear from the data shown if this is actually the case? Can the authors quantify the number and assembly state of the T4SSs during the transition from SCV to LCV (like they quantified the number of ribosomes)? They should also show sub-tomographic averages of the various structures making clear what parts of the complexes are assembled early and late during this transition? This type of detailed analysis is essential since it is the main point of the paper.<br /> 2. "The results indicate that 38.6% of the Dot/Icm machines identified from LCV images displayed an assembled inner membrane complex. By contrast, none of the bacteria in the transitional phase displayed a Dot/Icm-associated inner membrane complex, indicating that the complete core complex assembles upon transition to the LCV form (Fig. 5)."

Related to the previous comment - Figure 5 is a cartoon model - the authors should actually show this quantification and show structures.

3. A more detailed structural comparison between the Legionella and Coxiella burnetii T4SSs should be included as a major figure.

4. The number of ribosomes is quantified between SCV and LCV cells - however, it is unclear whether the argument is that in the SCV they are poised to be transcribed or that there is no change in transcriptional activity of the ribosomes during the transition.

5. The authors should further explain how folding of the inner membrane alone would allow for rapid expansion - shouldn't the outer membrane also have to rapidly expand? Do they see any sort of protein structures within the folded membrane that explains its topology?

6. Can the authors explain more why the LCV cells appear to be further away from the lysosome membrane? I would have predicted the bacteria would be closer so that proteins translocated through the T4SS would be able to get through the lysosome membrane and into the host cell cytoplasm - otherwise wouldn't these bacterial effector proteins simply be degraded in the acidified lysosome?

7. More information about the methods used needs to be included. How was phase shift correction done? How were different symmetry mismatches dealt with in the 3D reconstructions (in methods it simply states 13-fold symmetry was applied).

Reviewer #1 (Public Review):

This paper addresses an important question: whether the conduction velocity in white matter tracts is related to individual differences in memory performance. The authors use novel MRI techniques to estimate the "g-ratio" in vivo in humans - the ratio of the inner axon relative to the inner axon plus its outer myelin sheath. They find that autobiographical recall is positively related to the g-ratio in a specific white matter tract (the parahippocampal cingulum bundle) in a population of 217 healthy adults. This main finding is extended by showing that better memory is associated with larger inner axon diameters and lower neurite dispersion, which suggests more coherently organised neurites. The authors also argue that their results show that the magnetic resonance (MR) g-ratio can reveal novel insights into individual differences in cognition and how the human brain processes information.

The study is exploratory in nature and the analyses were not pre-registered. The technique has not been used before to associate cognitive performance with MR estimates of conduction velocity in candidate white matter tracts. It is therefore unknown how strong any associations are likely to be and what sort of sample size might be needed to observe them. Nevertheless, if the technique proves to be reliable, then it certainly offers a valuable new tool to understand individual differences in cognitive abilities. However, brain structure to behavior associations are notoriously variable across studies and have been argued to require very large sample sizes to obtain reproducible results.

The authors decided to analyse performance on a single task - the Autobiographical Memory Interview - and identified three candidate white matter tracts that connect the hippocampal region with other brain regions. While it is clear why these three tracts were chosen, it is less obvious why the authors chose to investigate associations with the Autobiographical Memory Interview and not other memory tests that were part of the battery of tests administered to the participants. It is reasonable to assume that something as general as the conduction velocity of a white matter tract would have an effect on memory ability across a range of tasks, so to single out one seems an unnecessarily narrow focus.

The results of the study are interesting and highlight a key role of the parahippocampal cingulum bundle in autobiographical memory recall. The results are corrected for multiple comparisons across the three fiber tracts of interest and the recall of "external details" provides a nice control compared to the "internal details" which are the measure of interest. The main findings are extended to show that it is likely to be an increase in axon diameter and an increase in neurite coherency that characterize those individuals with better autobiographical recall. Despite these positives, it remains unclear whether memory recall, in general, is better in people with higher g-ratios in this tract (as implied in the Abstract), or if this effect is specific to scores on the Autobiographical Memory Interview.

Reviewer #1 (Public Review):

Rasicci et al. have developed a FRET biosensor that is designed to light up when cardiac myosin folds. This structure is extremely important to understand, and its link to the super-relaxed (SRX) state has not been fully shown. Their study provides a comprehensive review of the literature and provides compelling data that the 15 heptad+leucine zipper+GFP construct does function well and that the DCM mutant E525K has a similar IVM velocity despite a reduced ATPase compared with HMM. They rely on the ionic strength-dependent changes in the rate of MantATP release to argue that the E525K mutation stabilizes the 'interacting heads motif' (IHM) state, which makes logical sense.

Strengths:

Well written and comprehensive.<br /> Utilizes the appropriate fluorescence-based sensor for measuring the folding of the myosin structure.<br /> Provides a detailed range of techniques to support the premise of the study

Weaknesses:

Over-interpretation of the outcomes from this study means that the IHM and SRX are the same. Similar studies, e.g. Anderson 2018 and Chu 2021 support the opposite view that IHM and SRX are not necessarily the same, Anderson (and Rohde 2018) point out that S1 has some element of a reduced ATPase, this clearly cannot be due to folding of the molecule. Also, mavacamten was used in these studies to show that even S1 is inhibited suggesting that SRX and IHM are not connected. This is not to say that with enough supporting evidence that these observations cannot be over-ridden, it is just not clear that there is enough in this study to support this conclusion.

I felt that the authors passed over the recent Chu 2021 paper too quickly, the Thomas group used a FRET sensor as well and provides a direct comparison as a technique, but with opposite conclusions. They also have supporting data in Rohde 2018 that their constructs were less ionic strength sensitive. It would be useful to understand what the authors think about this.

Reviewer #1 (Public Review):

In their manuscript, Krug et al describe a CRISPR/Cas9 knock-out strategy for the creation of a pigment-less killifish (Nothobranchius furzeri) they term "klara". They target and inactivate three genes in parallel (mitfa, ltk, csf1ra). They employ the generated mutant offspring for studying mating preference as well as additional genome editing (knock-out of slc452) or the HDR-mediated knock-in to generate an inducible model for aging (inducible NTR mediated cell death by tagging the ORF of cdkn1a).

The authors present a valuable resource, a large bouquet of different, well-designed and described controlled experiments. The authors demonstrate the versatility of the established tool that may be of immediate use for the Noto community. Given the efficiency of the triple inactivation, the de novo inactivation may be more time and cost-efficient compared to the traditional sharing of the mutant animals.

When creating transgenic lines via HDR-mediated integration of donor sequences, the authors use the advanced protection of the donor construct by the addition of a 5'biotin. They validate integration by PCR genotyping and sequencing. However, these "proper" PCR bands can derive from in vitro recombination during the PCR (Won and Dawid, PlosOne2017), if a large number of cycles are used during PCR amplification. While PCR is often misleading, Southern Blot analysis delivers robust and unambiguous results. Here a single-copy integration is not relevant to the message of the manuscript.

Reviewer #1 (Public Review):

This pre-registration study by Kerrén et al. examined the hypothesis that the brain resolves competition between overlapping memories based on phase separation of hippocampus theta oscillations. By applying a time-resolved decoding analysis, they demonstrate that the reactivations of target and competitor memories are locked to the varied phase of theta-band oscillation after repeated recalls. Moreover, subjects with larger phase separation show less memory interference. The study provides new evidence supporting the phase-coding neural mechanism to alleviate memory interference of multiple items.

Overall, this is a very interesting report testing an influential oscillatory-phase-based hypothesis in the memory field and would bring broad impacts to other fields, such as perception, attention, and decision making, given that lessening inference of distractor to target is a fundamental challenge.

Meanwhile, several aspects of the results need more evidence to strengthen the conclusion. The major weakness is the lack of significant decoding for the target and competitor by themselves, although I understand that the main hypothesis focuses on their different phase-locking relationship. Meanwhile, less significant decoding performance, I believe, is very crucial to verify the LDA analysis and data quality. Similarly, the original decoding performance time course did not show a clear out-of-phase pattern as revealed in the phase analysis. Overall, the authors need more results to confirm that the phase separation results are based on genuine reactivations and out-of-phase relationships.

Reviewer #1 (Public Review):

In this manuscript, the authors use C. elegans as a model system to show that calcium-dependent exocytosis of synaptic vesicles is differentially coupled to two different types of calcium channels. The authors take advantage of the fact that each major calcium channel family is represented by only a single gene in C. elegans, with CaV1 corresponding to L-type, CaV2 to P/Q-type, and CaV3 to T-type calcium channels, respectively Moreover, C. elegans contains only a single ryanodine-receptor channel that is responsible for releasing calcium from intracellular stores. While it is well established that CaV2 (as in other species) is mainly responsible for exocytotic transmitter release, the role of the other channels is not clear. Here the authors use smart genetic approaches involving tissue-specific deletion of individual channels and combinations of double mutants to document that CaV1 activity is responsible for the exocytosis of a distinct class of synaptic vesicles that is farther away from the active zone, couples to a distinct short form of Unc13, and that cooperates with RyR, with the release-relevant calcium release probably mainly being derived from intracellular stores.

With the caveat that this reviewer is not an expert in C.elegans, I consider this data-rich manuscript excellent, adding important information to the role of N-type calcium channels in transmission at the neuromuscular junction in C. elegans. As far as I can judge, the data are of high quality, and even the rather tricky spatial resolution of the adjacent release sites and the selective association of RyR with CaV1 and the short form of UNC13 using superresolution fluorescence microscopy is convincing. The manuscript is well written, and the data are succinctly discussed. As discussed by the authors it remains unclear whether such a mechanism also occurs in mammalian synapses, e.g. synapses in which exocytosis is also triggered by graded potential changes rather than by action potentials.

Reviewer #1 (Public Review):

This work describes a new method, Proteinfer, which uses dilated neural networks to predict protein function, using EC terms and GO terms. The software is fast and the server-side performance is fast and reliable. The method is very clearly described. However, it is hard to judge the accuracy of this method based on the current manuscript, and some more work is needed to do so.

I would like to address the following statement by the authors: (p3, left column): "We focus on Swiss Prot to ensure that our models learn from human-curated labels, rather than labels generated by electronic annotation".

There is a subtle but important point to be made here: while SwissProt (SP) entries are human-curated, they might still have their function annotated ("labeled") electronically only. The SP entry comprises the sequence, source organism, paper(s) (if any), annotations, cross-references, etc. A validated entry does not mean that the annotation was necessarily validated manually: but rather that there is a paper backing the veracity of the sequence itself, and that it is not an automatic generation from a genome project.<br /> Example: 009L_FRG3G is a reviewed entry, and has four function annotations, all generated by BLAST, with an IEA (inferred by electronic annotation) evidence code. Most GO annotations in SwissProt are generated that way: a reviewed Swissprot entry, unlike what the authors imply, does not guarantee that the function annotation was made by non-electronic means. If the authors would like to use non-electronic annotations for functional labels, they should use those that are annotated with the GO experimental evidence codes (or, at the very least, not exclusively annotated with IEA). Therefore, most of the annotations in the authors' gold standard protein annotations are simply generated by BLAST and not reviewed by a person. Essentially the authors are comparing predictions with predictions, or at least not taking care not to do so. This is an important point that the authors need to address since there is no apparent gold standard they are using.

The above statement is relevant to GO. But since EC is mapped 1:1 to GO molecular function ontology (as a subset, there are many terms in GO MFO that are not enzymes of course), the authors can easily apply this to EC-based entries as well.

This may explain why, in Figure S8(b), BLAST retains such a high and even plateau of the precision-recall curve: BLAST hits are used throughout as gold-standard, and therefore BLAST performs so well. This is in contrast, say to CAFA assessments which use as a gold standard only those proteins which have experimental GO evidence codes, and therefore BLAST performs much poorer upon assessment.

Pooling GO DAGs together: It is unclear how the authors generate performance data over GO as a whole. GO is really 3 disjoint DAGs (molecular function ontology or MFO, Biological Process or BPO, Cellular component or CCO). Any assessment of performance should be over each DAG separately, to make biological sense. Pooling together the three GO DAGs which describe completely different aspects of the function is not informative. Interestingly enough, in the browser applications, the GO DAG results are distinctly separated into the respective DAGs.

Figure 3 and lack of baseline methods: the text refers to Figures 3A and 3B, but I could only see one figure with no panels. Is there an error here? It is not possible at this point to talk about the results in this figure as described. It looks like Figure 3A is missing, with Fmax scores. In any case, Figure 3(b?) has precision-recall curves showing the performance of predictions is the highest on Isomerases and lowest in hydrolases. It is hard to tell the Fmax values, but they seem reasonably high. However, there is no comparison with a baseline method such as BLAST or Naive, and those should be inserted. It is important to compare Proteinfer with these baseline methods to answer the following questions: (1) Does Proteinfer perform better than the go-to method of choice for most biologists? (2) does it perform better than what is expected given the frequency of these terms in the dataset? For an explanation of the Naive method which answers the latter question, see: (https://www.nature.com/articles/nmeth.2340)

Reviewer #1 (Public Review):

In the present study, Ibáñez-Solé1 et al evaluate transcriptional noise across aging and tissues in several publicly available mouse and human datasets.  Initially, the authors compare 4 generalized approaches to quantify transcriptional noise across cell types and later implement a new approach which uses iterative clustering to assess cellular noise.  Based on implementation of this approach (scallop), the authors survey noise across seven sc-seq datasets relevant for aging.  Here, the authors conclude that enhanced transcriptional noise is not a hallmark of aging, rather changes in cell identity and abundances, namely immune and endothelial cells.  The development of new tools to quantify transcriptional noise from sc-seq data presents appeal, as these datasets are increasing exponentially.  Further, the conclusion that increased transcriptional noise is not a defined aspect of aging is clearly an important contribution; however, given the provocative nature of this claim, more comprehensive and systematic analyses should be performed.  In particular, the robustness and appeal of scallop is still not sufficiently demonstrated and given the complexity  (multiple tissues, species and diverse relative age ranges) of datasets analyzed, a more thorough comparison should be performed.  I list a few thoughts below:

Initially, the authors develop Decibel, which centralizes noise quantification methods. The authors provide schematics shown in Fig 1, and compare noise estimates with aging in Fig 2 - Supplement 2.   Since the authors emphasize the necessary use of scallop as a "better" pipeline, more systematic comparisons to the other methods should be made side-by-side.  For example, scallop noise estimates (Fig 2) compared to other euclidean distance-based measures (Fig 2 supplement 2) looks fairly similar.  Are downstream observations (ex lung immune composition changes more than noise) supported from these methods as well?  If so, this would strengthen the overall conclusion on noise with age, but if not, it would be relevant to understand why.

Similarly, the 'validation of scallop seems mostly based on the ability to localize noisy vs stable cells in Fig 1 supplement 1 and relative robustness within dataset to input parameters (Fig 1 supplement 2).  A more systematic analysis should be performed to robustly establish this method.  For example, noise cell clustering comparisons across the 7 datasets used.  In addition, the Levy et all 2020 implemented a pathway-based approach to validate.  Specifically, surrogate genes were derived from GCL value where KEGG preservation was used as an output.  Similar additional types of analyses should be performed in scallop 

The conclusion that immune and endothelial cell transcriptional shifts associate more with age than noise are quite compelling, but seem entirely restricted to the mouse and human lung datasets.  It would be interesting to know if pan-tissues these same cell types enrich age-related effects or whether this phenomenon is localized

Related to these, there does not seem to be a specific rationale for why these datasets (the seven used in total or the lung for deep-dive), were selected.  Clearly, many mouse and human sc-RNA-seq datasets exist with large variations in age so expanding the datasets analyzed and/or providing sufficient rationale as to why these ones are appearing for noise analyses would be helpful. For example, querying "aging" across sc-seq datasets in Single cell portal yields 79 available datasets: https://singlecell.broadinstitute.org/single_cell?type=study&page=1&terms=aging&facets=organism_age%3A0%7C103%7Cyears

The analysis that noise is indistinguishable from cell fate shifts is compelling, but again relies on one specific example where alternative surfactant genes are used as markers.  The same question arises if this observation holds up to other cell types within other organs.  For example the human cell atlas contains over dozens of tissue with large variations in age (https://www.science.org/doi/10.1126/science.abl4290).

Reviewer #1 (Public Review):

Xian et al. systematically evaluated age and sex-dependent differences in paw skin and sciatic nerves (SCN) tissues of naïve mice, utilizing DIA-PASEF, a highly sensitive and reproducible proteomics approach. The authors demonstrated that the deep proteome profiling enabled a discovery of significant differences between male and female mice and adolescent and adult mice such as homeostasis and epidermal signaling in skin and, myelination and neuronal development in SCN that are known to be relevant to the pathophysiology. The authors claim the need for the appropriate age and sex matching in the experiment design and suggest the work as a unique systems biology proteome resource in mouse disease model. As I understand this is the first attempt to molecularly characterize the impact of mouse age and sex that would help warrant the reproducibility of the preclinical research.

Reviewer #1 (Public Review):

This manuscript reports the results of studies on the effects of an ActRIIB-Fc ligand trap inhibitor of myostatin on muscle contractures that develop when brachial plexus nerve roots are severed at 6 after birth. One component of this pathological response seems to be a failure to add sarcomeres as the skeleton grows resulting in short muscles. The authors use a carefully performed set of animal studies to test the effects of the ligand trap on denervation-induced limitations in range of motion in young mice. They also investigate several biochemical mechanisms that might contribute to contractures and be modified by the ligand trap. Finally, the test for gender discordance in the protective effect of a proteasome inhibitor against contractures. The major finding of these studies is that the ligand trap improved the range of motion at the elbow and shoulder in female mice but not in males. The major caveat to interpreting the data is that group sizes are relatively small such that the study may have been underpowered to detect smaller effects on a range of motion and biochemical endpoints.

Joint Public Review:

Tiedemann et al. evaluated the neural response to insulin before and after a 3-month caloric restriction diet compared to an active waiting group in 50 elderly persons overweight and with obesity. Peripheral insulin sensitivity and central insulin sensitivity of the mesolimbic reward circuitry predicted weight loss success and improvement after caloric restriction. This is the first longitudinal study showing an improvement in central insulin sensitivity in humans.

Strengths<br /> The major strength of the paper is the longitudinal study design in persons at high risk to develop type 2 diabetes with multiple fMRI visits, with a state-of-the-art fMRI design. Moreover, the study uses a placebo-controlled approach to evaluate insulin sensitivity in the brain. Another strength is the fact the control group is an active waiting group, which means that they received dietary counselling after the study and additionally benefited from the study by receiving training courses on stress management.

Weakness<br /> A weakness of the study is the lack of metabolic assessments of the participants. Only fasting blood samples were available. No oral glucose tolerance test or hyperinsulinemic-euglycemic clamps were acquired to quantify peripheral or whole-body insulin resistance. Whether peripheral insulin sensitivity and central insulin sensitivity are, in fact, independently involved in the success or treatment outcome of intervention still needs to be validated in future studies.<br /> Another weakness is the food cue picture set implemented in the study. The different categories of pictures were not carefully matched for psychological and physical variables (such as the complexity of a picture). This could potentially influence neural food cue reactivity.<br /> The study evaluated the regional BOLD response of the reward circuitry showing that insulin signaling in the VTA and nucleus accumbens play an important role in successful weight loss. The role of insulin signaling on projections (or connectivity) of the mesolimbic reward circuitry was not evaluated in the current study.

Reviewer #1 (Public Review):

This manuscript discusses evolutionary patterns of manipulation of others' allocation of investment in individual reproduction relative to group productivity. Three traits are considered: this investment, manipulation of others' investment, and resistance to this investment. The main result of the manuscript is that the joint evolution of these traits can lead to the maintenance of diversity through, as documented here, cyclic (or noisier) dynamics. Although there are some analytical results, this main conclusion is instead supported by individual-based simulations, which seem correctly performed (but for clonal populations, as emphasized below).

There could be material for a good paper here but the organization of the manuscript makes it difficult to fully evaluate. The narrative is highly condensed, with the drawbacks that this often entails in terms of accurately conveying the results of a study, as illustrated here by the following issue.

The population is apparently assumed to be clonal (more than just "haploid"), meaning that there is no recombination between the loci controlling the three traits. In the one case where this assumption is relaxed (quite artificially), the cyclic dynamics disappear (section 4.4 of the appendix). This is crucial information that cannot be appreciated in the main text.

The paragraph at line 368 offers a simple explanation for the joint dynamics of traits. However, this explanation would hold identically for a sexual population and a clonal population, whereas these two cases seem to have completely different dynamics. Thus, there is something essential to explain these differences, that is missing from the given explanation.

This is especially important because the finding that the joint evolution of several traits can lead to some form of diversity maintenance is not surprising. As the discussion acknowledges (but the introduction seems to downplay), it is also well understood that manipulation and counter-adaptations to it can occur in many contexts and lead to the maintenance of diversity. For this reason, similar results in the present case are not surprising, and the main outcome of the study should be to provide a deeper understanding of the forces leading to the different outcomes in the current models.

I do not see clearly what distinguishes "manipulative cheating" from other forms of manipulations that have been previously discussed in the literature (e.g, as cited lines 461). Couldn't this be clarified by some kind of mathematical criterion?

Reviewer #1 (Public Review):

The study uses public behavioral and fMRI data to study the range adaptation properties of the orbitofrontal cortex (OFC) during risky choice that requires integrating potential gains and losses. The authors demonstrate how spill-over effects from the range of gains to the sensitivity to losses, cannot be explained by simple efficient coding accounts. The authors construct an artificial neural network (ANN) and show that Hebbian plasticity between attribute-specific and integration units can account for the context-dependent effect in behavior and fMRI data.

This is an interesting study that discusses a potential mechanism for context effects often seen in decision-making. A major concern is that the manuscript focuses on Hebbian plasticity as the key mechanism, whereas the results show that the choice of activation functions (sigmoidal vs. gaussian) has a comparable contribution to explaining behavior but is not discussed. In addition, the performance of even the best model is not very convincing for extreme ranges of expected value. There are additional moderate and minor concerns with result presentation and interpretation.

Reviewer #1 (Public Review):

Lymphatic drainage of CNS antigens has received lots of attention recently due to the (re)discovery of dural meningeal lymphatics. The role of dural lymphatics in CNS antigen drainage has been shown to be important in several contexts (AD, glioma, etc.). Few studies have focused on their role in CNS infections so far. In their study, Kovacs et al. dissected the role of meningeal lymphatic drainage in T cell responses during chronic Toxoplasma gondii infection in mice. They first show that T.g. infection drives DC accumulation in the dura and CSF at 6 weeks post-infection, which matches with the replication peak of T.g. in the brain, and with T cell expansion/activation in the dCLN. This effect on T cells in the dCLN was abrogated upon surgical blockade of dural drainage. However, dural lymphatic blockade did not affect T.g. burden, nor CD4+ and CD8+ T cell number and IFNg production in the brain in the chronic phase. They finally show that during chronic infection, antigen-specific T cells are generated not only in the dCLN but also in the periphery (ILN), which could account for the presence of T cells in the brain after surgical blockade of the lymphatics.

This study is interesting and some aspects are clearly convincing, but some precisions have to be made. More importantly, with similar tools, key experiments (as explained in the last paragraph: icv infection or chronic peripheral parasite clearance, etc.) have to be generated to bring more impact to this study and could reveal a new role for dCLN T cells.

Reviewer #1 (Public Review):

In this manuscript, Soto-Feliciano et al. investigate the tumor suppressive role of MLL3 in hepatocellular carcinoma (HCC). The authors used a variety of techniques including hydrodynamic tail vain injection (HTVI), CRISPR deletion, and shRNA to disrupt MLL3 expression in mouse models. They clearly show that MLL3 acts as a tumor suppressor in the context of MYC-induced HCC. They show that MLL3 acts by activating the Cdkn2a locus. Genomic analysis showed that MLL3 binds to enhancers and promoters, and specifically interacts with the Cdkn2a promoter. When MLL3 was downregulated, Cdkn2a levels fell and this corresponded to changes in relevant histone marks targeted by MLL3. The authors were also able to show that reintroduced MLL3 expression in a dox inducible system could rescue CDKN2A locus expression, which in turn reduced colony formation and induced apoptosis. Human genomic correlation showed that MLL3 and Cdkn2a mutations are generally mutually exclusive. Overall, the conclusions of the manuscript are well supported by a logical series of experiments with good controls and orthogonal approaches. While it would be useful to examine another HCC model such a CTNNB1-driven model, the current paper is convincing in its conclusions.

Reviewer #1 (Public Review):

Mikelov et al. investigated IgH repertoires of memory B cells, plasmablasts, and plasma cells from peripheral blood collected at three time-points over the course of a year. In order to obtain deep and unbiased repertoire sequences, authors adopted uniquely developed IgH repertoire profiling technology. Based on collected peripheral blood data, authors claim that; 1) A high degree of clonal persistence in individual memory B cell subsets with inter-individual convergence in memory and ASCs. 2) ASC clonotypes are transient over time and related to memory B cells. 3) Reactivation of persisting memory B cells with new rounds of affinity maturation during proliferation and differentiation into ASCs. 4) Both positive and negative selection contribute to persisting and reactivated lineages preserving the functionality and specificity of BCRs.

The present study provides useful technical application for the analysis of longitudinal B cell repertoires, and bioinformatics and statistical data analysis are impressive. Regarding point 1), clonal persistence of memory B cells is already well known. On the other hand, inter-individual convergence between memory B cells and plasma cells might not be shown in healthy individuals even though the biological significance of circulating plasma cells is questionable.

Regarding 2), temporal stability of plasma cell clonotypes has been demonstrated already in the bone marrow with serial biopsies over time (Wu et al. DOI: 10.1038/ncomms13838). The Association of clonotypes between memory and plasma cells in the blood of healthy donors might be new, however, again its biological significance is questionable.

Regarding 3) and 4), it is hard to generalize observations from the presented data because the analysis was based on just four donor cases with different health conditions, i.e. a combination of healthy and allergic. The cell number of plasmablasts and plasma cells isolated from peripheral blood is extremely low compared to memory B cells, and in fact, the vast majority of ASCs reside in the tissues such as lymphoid organs, bone marrow, and mucosal tissues rather than in circulating blood (Mandric et al. DOI: 10.1038/s41467-020-16857-7). As the most critical problem, direct pieces of evidence to claim points, 3) and 4) are missing.

Reviewer #1 (Public Review):

This study uses the mouse calyx of Held synapse as a model to explore the presynaptic role of rac1, a regulator of actin signaling in the brain. Many of the now-classical methods and theory pioneered by Neher and colleagues are brought to bear on this problem. Additionally, the authors were able to make a cell-specific knockout of rac1 by developing a novel viral construct to express cre in the globular bushy cells of the cochlear nucleus; by doing this in a rac1 floxed mouse, they were able to KO rac1 in these neurons starting at around P14. The authors found that KO of rac1 enhanced EPSC amplitude, vesicle release probability, quantal release rates, EPSC onset time and jitter during high-frequency activity, and fast recovery rates from depression. Because the calyx synapses are the largest and most reliable of central nerve terminals, all these various effects had no effect on suprathreshold transmission during 'in vivo-like' stimulus protocols. Moreover, there was no effect morphologically on the synapse. Through some unavoidably serpentine reasoning, the authors suggest that loss of rac1 affects the so-called molecular priming of vesicles, possibly due to a restructuring of actin barriers at the active zone. The experimental analysis is at a very high level, and the work is definitely an important contribution to the field of presynaptic physiology and biophysics. It will be important to test the effects of the KO on other synapses that are not such high-performers as the calyx, and this direction might reveal significant effects on information processing by altered rac1 expression.

Major points:<br /> 1. The measurement of onset delay was used to test whether rac1-/- affects positional priming. While there is a clear effect of the KO on the latency to EPSC onset, there is no singular interpretation one can take, due to the ambiguity of the 'onset delay'. Note that in the Results authors state Lines 201-203: "The time between presynaptic AP and EPSC onset (EPSC onset delay) is determined by the distance between SVs and VGCC which defines the time it takes for Ca2+ to bind to the Ca2+ sensor and trigger SV release (Fedchyshyn and Wang, 2007)." However, in Methods "The duration between stimulus and EPSC onset was defined as EPSC onset delay." Thus the 'onset' measured is not between presynaptic spike and EPSC but from axonal stimulus and EPSC. KO of rac might also affect spike generation, spike conduction, calcium channel function, etc. Indeed some additional options are offered in the Discussion. Since the change in onset is ~100usec at most, a number of small factors all could contribute here. Moreover, the authors conclude that the KO does NOT affect positional priming since they would have expected the onset to shorten, given the other enhancements observed in earlier sections.<br /> It seems to me that all the authors can really conclude is that the onset shifted and they do not know why. If onset is driven by multiple factors, and differentially affected in the KO, then all bets are off. Thus, data in this section might be removed, or at least the authors could further qualify their interpretations given this ambiguity.

2. If the idea is that the loss of Rac1 leads to a reduced actin barrier at the active zone, is there an ultrastructural way to visualize this, labeling for actin for example? Authors conclude that new techniques are needed, but perhaps this is 'just' an EM question.

3. Authors use 1 mM kynurenic acid in the bath to avoid postsynaptic receptor saturation. But since this is a competitive antagonist and since the KO shows a large increase in release, could saturation or desensitization have been enhanced in the KO? This would affect the interpretation of recovery rates in the KO, which are quite fast.

Reviewer #1 (Public Review):

Baldazzi and coworkers propose a resource allocation model for E. coli steady-state cell growth that allows a joint description of growth rate and yield (fraction of substrate converted into biomass) and compare it with a compiled dataset based on batch growth data from different strains and two growth conditions (as well as some chemostat growth data). The model includes a description of alternative respiration and fermentation pathways with different energy efficiency. The model predicts bounds on the achievable state growth rate vs yield space that are compared with data, as well as glucose uptake and acetate secretion rates, which are compared with data.

In my view, the main merits of the model are (i) the compiled dataset of growth-yield-uptake-secretion parameters and (ii) the proposition of a resource-allocation model that includes the energy budget. Contrary to most current models in this area, the biomass includes other cellular components (DNA, RNA, metabolites, ...) in addition to proteins.

The main limitations are that the trends in the data do not emerge well and the predictions of the model are not presented in a transparent way. I believe that considerable extra work is needed in order to valorize the effort and highlight the trends in both data and model. For the data, it suffices to present more "sections" of the dataset (preferably as 2D XY plots) and more reflection on their meaning. Regarding the model, I think more effort is needed towards "breaking it open" and providing insight into why the model makes certain predictions and which ones are not trivial.

Reviewer #1 (Public Review):

The study investigated the role of oxytocin (OT) in the paraventricular hypothalamic nucleus (PVH) and oxytocin receptor (OTR) in the hypothalamus in the regulation of food intake using conditional knockout of oxytocin in adults by adreno-associated virus (AAV) approaches. Although pharmacological studies have demonstrated that oxytocin/oxytocin receptors regulate food intake behavior, constitutive knockout (KO) models are not aligned with pharmacological studies. To overcome this discrepancy between pharmacological and developmental genetic approaches, the authors used AAV to knockout oxytocin/oxytocin receptors in adults of mice, circumventing developmental compensations. They found that adult KO of OT in the PVH, but not supraoptic nucleus (SO), led to obesity due to hyperphagia. They also investigated whether OTR in the anterior or posterior side of the hypothalamus contributes to OT-mediated food intake behavior, and found that the posterior hypothalamic areas are key for that. Overall, the experiments are thoughtfully designed, and the manuscript is well written. However, there are questions that authors need to address, in particular their OT KO model.

Reviewer #1 (Public Review):

Activation of TEAD-dependent transcription by YAP/TAZ has been implicated in the development and progression of a significant number of malignancies. For example, loss of function mutations in NF2 or LATS1/2 (known upstream regulators that promote YAP phosphorylation and its retention and degradation in the cytoplasm) promote YAP nuclear entry and association with TEAD to drive oncogenic gene transcription and occurs in a significant majority of mesothelioma patients. High levels of nuclear YAP have also been reported for a number of other cancer cell types. As such, the YAP-TEAD complex represents a promising target for drug discovery and therapeutic intervention. Based on the essential functional role for TEAD palmitoylation at a conserved cysteine site, discovered by the authors of this manuscript, several groups have successfully targeted this site using both reversible binding non-covalent TEAD inhibitors (i.e., flufenamic acid (FA), MGH-CP1, compound 2 and VT101~107), as well as covalent TEAD inhibitors (i.e., TED-347, DC-TEADin02, and K-975), which have been demonstrated to inhibit YAP-TEAD function and display anti-tumor activity in cells and in vivo.

Here, Hu et al. disclose the discovery of a new class of reversible TEAD inhibitors that putatively binds across a new site within the auto-PLM pocket across the TEAD family of proteins. To date, reported inhibitors that target this site (flufenamic acid (FA), TED-347, MYF-01-037, K975, VT103, MGH-CP1) function by binding to the same hydrophobic palmitate binding pocket (PBP) which is highly conserved. The novel TEAD inhibitor is identified from a screen of 30,000 compounds using recombinant TEAD2 and TEAD4 proteins and TEAD2 and TEAD4 click-ELISA assays. A molecule termed TM2 was found to show the strongest inhibition on TEAD auto-palmitoylation (IC50= 156nM for TEAD2 and 38nM for TEAD4) and is chosen for further characterization. A co-crystal structure of TEAD2 YAP binding domain in complex with TM2 was solved and revealed that TM2 not only occupied the familiar hydrophobic PLM site but also binds within a new pocket. Notably, the charge properties of this site might be compatible with the development of more drug-like analogs with enhanced hydrophilic properties. TM2 is profiled against several malignant pleural mesothelioma (MPM) cell lines (IC50 = 26-157nM) and activity correlates well with in vitro TEAD palmitoylation inhibition. Notably, consistent with results for related inhibitor classes, TM2 is not active as a monotherapy in cells beyond NF2 deficient cell lines, although cell type selective cytotoxicity is clearly shown.

Strengths:

This newly reported chemical series is highly tractable and could provide an excellent starting point for the development of effective TEAD inhibitors. The reported ability of TM2 to bind to a new site within the conserved TEAD auto-PBP site could enable this area of drug discovery.

Weaknesses:

The authors claim that TM2 is "more specific" than existing inhibitors, with respect to its ability to regulate YAP/TAZ-TEAD target gene expression. However, this statement is based on a comparison of unrelatable RNA-Seq datasets. TM2-regulated expression is evaluated in the context of cell (mono)culture following a continuous duration of target engagement. Comparison is made to the covalent inhibitor K975 based on a published dataset involving analysis of a drug-treated NCI-H226 tumor xenograft (i.e, in vivo drug treatment). Heterogeneity in cells, time point of analysis and duration and target engagement preclude the possibility of any reasonable comparison of these datasets. The ability of TM2 to bind within a new site is a significant finding. The comparison of TM2 binding mode to other inhibitors is based on structures of non-TEAD2 co-crystal structures. It will help significantly to clarify the differences in the side chains within this site across TEAD family members (i.e., TEAD1-4). The robustness of the proposed synergistic activity of TM2 in non-responsive cell lines is unclear.

Reviewer #1 (Public Review):

This is timely and foundational work that links cellular neurophysiology with extracellular single-unit recordings used to study LC function during behavior.

The strengths of this paper include:<br /> 1. Providing an updated assessment of LC cell morphology and cell types since much of the prior work was completed in the late 1970s and early to mid-1980s.<br /> 2. Connecting LC cell morphology with membrane properties and action potential shape.<br /> 3. Showing that neurons of the same type have electrical coupling

Collectively, these findings help to link LC neuron morphology and firing properties with recent work using extracellular recordings that identify different types of LC single units by waveform shape.

Another strength of this work is that it addresses recent findings suggesting the LC neurons may release glutamate by showing that, at least within the LC, there is no local glutamatergic excitatory transmission.

Weaknesses:<br /> The authors also propose to test the role of single LC neuron activity in evoking lateral inhibition, as well as proposing that electrical coupling between LC cell pairs is organized into a train pattern. The former point is based on a weak premise and the latter point has weak support in their data given the analyses performed.

Point 1: lateral inhibition in the LC<br /> The authors write in the abstract that "chemical transmission among LC noradrenergic neurons was not detected" and this was a surprising claim given the wealth of prior evidence supporting this in vitro and in vivo (Ennis & Aston-Jones 1986. Brain Res 374, 299-305; Aghajanian, Cedarbaum & Wang 1977. Brain Res 136, 570-577; Cedarbaum & Aghajanian. 1978 Life Sci 23, 1383-1392).

Huang et al. 2007 (Huang et al. 2007. Proc National Acad Sci 104, 1401-1406) showed that local inhibition in the LC is highly dependent on the frequency of action potentials, such that local release requires multiple APs in short succession and then requires some time for the hyperpolarization to appear (even over 1 sec). This work suggests that it is not a "concentration issue" per se, rather it is just that a single AP will not cause local NE release in the LC. Although the authors did try 5APs at 50Hz this may not be enough to generate local NE release according to this prior work. A longer duration may be needed. Additionally, although the authors incubated the slices with a NET inhibitor, that will not increase volume transmission unless there is actually NE release, which may have not happened under the conditions tested. In sum, there is no reason to expect that a single AP from one neuron would cause an immediate (within the 100 msec shown in Fig 3B) hyperpolarization of a nearby neuron. Therefore, the premise of the experiment that driving one neuron to fire one AP (or even 5AP's at 50Hz in some) is not an actual test of lateral inhibition mediated by NE volume neurotransmission in the LC. Strong claims that "chemical transmission...was not detected" require substantial support and testing of a range of AP frequencies and durations. Given the wealth of evidence supporting lateral inhibition of the LC, this claim seems unwarranted.

Point 2: Train-like connection pattern<br /> Demonstrating that connected cell pairs often share a common member is an important demonstration of a connection motif in the LC. However, a "train" connection implies that you can pass from A to B to C to D (and in reverse). However, the authors do not do an analysis to test whether this occurs. Therefore, "train" is not an appropriate term to describe the interesting connection motif that they observed.

In fact, writing A↔B↔C in the paper implies a train without direct support for that form of electrical transmission. For example, in Fig. 6C, it is clear that cell 6 is coupled to cell 1 and that cell 6 is also coupled to cell 8. In both cases, the connection is bilateral. Using the author's formatting of A↔B↔C , would correspond with Cell 6 being B and cells 1 and 8 being A and C (or vice versa). However, writing A↔B↔C implies a train, whereas one can instead draw this connection pattern where B is a common source:<br /> A C<br /> . .<br /> . .<br /> B

An analysis showing that spikes in A can pass through B and later appear in C is necessary to support the use of "train". The example in Fig. 6C argues against train at least for this one example.

Although the analysis is possible to do with the authors' substantial and unique data set, it should be also noted that prior work on putative electrical coupling in extracellular recordings from rat LC showed that trains among 3 single units occurred at an almost negligible rate because out of 12 rats "Only 1 triplet out of 22,100 possible triplet patterns (0.005%) was found in one rat and 4 triplets out of 1,330 possible triplet patterns (0.301%) were found in the other rat." and moreover patterns beyond 3 units were never observed (Totah et al 2018. Neuron 99, 1055-1068.e6).

Reviewer #1 (Public Review):

The authors generated a mouse model for GEN1 and a B-cell conditional MUS81 flox allele to create B-cells devoid of both proteins using two Cre drivers. Mb1-Cre driven by the Cd79a promoter depletes MUS81 in pre-pro B cells, whereas Cd23-Cre is driven by the Fcer2a promotor to deplete MUS81 in immature, transitional and late B cells. The results show that GEN1 and MUS81 are necessary for differentiation into pro-B cells, the expansion and maintenance of pro-B cells, or both. The CD23-Cre line showed that naïve B cells can persist without MUS81 and GEN1, but they are impaired for germinal center formation. Ex vivo analysis identified a proliferation defect upon stimulation and increased cell death due to apoptosis. RNA seq analysis of such cells revealed activation of the p53 pathway and the type I interferon response. Metaphase chromosomal analysis revealed hallmarks of genomic instability including chromosomal abnormalities, including breaks, fragments, fusions, and radials. The symmetry of the breakages suggests that they arose from unresolved HR intermediates.

Strengths:<br /> This is a well-executed study, and the results support the conclusions. While the role of both nucleases has been extensively studied in cellular systems, this is the first analysis at the organismic level with a focus on B-cell development.

Weaknesses:<br /> The nature of the actual substrate(s) for MUS81 and GEN1 remains unclear and the significance of unresolved HR intermediates for the observed phenotype remains an inference from the type of chromosome aberrations observed. The DNA damage analyses presented would benefit from being clarified and extended.

Reviewer #1 (Public Review):

This paper provides a progress report on methods development that was initiated previously by the same authors to identify macromolecular complexes in cryo-EM images of cells. Whereas others have proposed to perform this task in 3D reconstructions from tomographic tilt series, the method discussed here (2DTM) uses template matching with known reference structures against individual 2D projection images. This concept was introduced in previous work. In the current paper, the authors show that 2DTM can be used to classify distinct molecular populations. They demonstrate this by distinguishing cytoplasmic mature 60S ribosome particles from a nuclear pre-60S population. They also define a maximum likelihood metric that assigns a probability for each particle belonging to each class. The paper reads a bit dense, and one could discuss how big the advance is over the previous work by the same authors. But the general topic (of being able to identify distinct particle populations in cells) is an important one.

However, I think one major concern needs to be addressed much more openly in a revised version of the paper: that of potential model bias of incorrect references. The single-particle field previously suffered the problems of Einstein from noise can cause with the debacle around an incorrect HIV trimer reconstruction that was the result of picking particles with a high-resolution reference. I realise that the problem here is a different one, but similar problems of model bias may exist. In fact, the observation on page 18 that the reconstruction from the picked particles was estimated by FSC to be 3.5A, yet the resulting map had to be filtered at 10A to limit the noise, is a strong indication that model bias does play a large role in the identification of particles. This bias must affect the measured SNR scores, and thus the metrics presented. It also suggests that part of the identified picks may in fact not be true 60S ribosomes, but false positives. This would then affect the conclusions drawn. If the authors disagree (and I suspect they do), they should set out clear arguments for their case. Also, they should discuss how potential overfitting or model bias would affect their new metrics for particle classification in the discussion. Currently, the only reference to the dangers of overfitting is on page 16, merely referring to their previous paper.

Perhaps points for additional discussion could include:<br /> 1) In the light of overfitting, I was wondering whether one could detect the 80S ribosomes also through 2DTM using the 40S subunit as a reference.<br /> 2) The authors have been wise in selecting the 60S ribosome as a test case. Probably, because of its size and RNA content, for many instances of this complex the SNR is sufficiently high for detection. However, if less careful authors would choose a smaller target, what would happen? What would be the pitfalls and how could they be avoided?

Reviewer #1 (Public Review):

In this manuscript by Chen et al., the authors use live-cell single-molecule imaging to dissect the role of DNA binding domains (DBD) and activation domains (AD) in transcription factor mobility in the nucleus. They focus on the family of Hypoxia-Inducible factors isoforms, which dimerize and bind chromatin to induce a transcriptional response. The main finding is that activation domains can be involved in DNA binding as indicated by careful observations of the diffusion/reaction kinetics of transcription factors in the nucleus. For example, different bound fractions of HIF-1beta and HIF-2alpha are observed in the presence of different binding partners and chimeras. The paradigm of interchangeable parts of transcription factors has been eroded over the years (the recent work of Naama Barkai comes to mind, cited herein), so the present observations are not unexpected per se. Yet, the measurements are rigorous and well-performed and have the important benefit of being in living cells. Enthusiasm is also dampened by the exclusive use of one technique and one analysis to reach conclusions.

Reviewer #1 (Public Review):

The authors report a public browser in which users can easily investigate associations between PRSs for a wide range of traits, and a large set of metabolites measured by the Nightingale platform in UKBB. This browser can potentially be used for identifying novel biomarkers for disease traits or, alternatively, for identifying novel causal pathways for traits of interest.

Overall I have no major technical concerns about the study, but I would encourage the authors to revisit whether they can find a more compelling example that can better showcase the work that they have done. I understand that this is partly a resource paper but I think the resource itself can have more impact if the paper provides a clearer use-case for how it can drive novel biological insight.

PRS construction: It's unclear how well the PRS work. Should the reader prefer the stringent or lenient PRS? Perhaps there could be some validation with traits that have decent sample sizes in UKBB. Was there any filtering to remove traits with few GWS hits, low sample sizes, or low SNP heritability as these are unlikely to produce useful PRSs?

Reviewer #1 (Public Review):

This manuscript sets up a well-reasoned study and capitalizes on a very impressive long-term dataset. Their methods are generally sound and well explained. The argument for paternal kin recognition here could be compelling, but at this stage, it does not seem possible to rule out a simpler cognitive mechanism, i.e. gorillas direct their aggression toward unfamiliar and/or outgroup individuals. The authors note the difficulty of indexing familiarity versus kinship because there were very few out-group dyads (two individuals from different natal groups) that were related. But were there any in-group dyads that were not related? If so, then it might be plausible to add the natal group as a co-variate to parse these mechanisms. A result in either direction could be very compelling. Another concern is dealing with age- which is incredibly difficult with data like this and the authors have offered a reasonable compromise here by settling on a single term (age difference). It makes good sense that the difference in age between two partners should contribute to shaping the interactions between a dyad, however, each of the social behaviors here is more or less common depending on age in most species (including gorillas to the best of my knowledge) with social play generally decreasing with age while social grooming and aggression increase. I understand that it is not the intent of this manuscript to describe the ontogeny of social bonds, however, as the dataset includes individuals ranging from infants through adults, is it possible that such age-related changes in social behavior are affecting the results? Whether or not the authors find strong indications that gorillas can recognize paternal kin, specifically, beyond in-group/out-group familiarity, this manuscript represents an important contribution to the field.

Reviewer #1 (Public Review):

This is a randomized controlled trial to assess the impact on the COVID-19 progression (hospitalization, oxygen supplementation need, and/or death within 14 days) of 3 different mAbs. As only one of the assessed mAbs was shown to be active in vitro against the Omicron variant, which emerged after the study onset, the trial was interrupted for potential futility. The authors compared the activity of three mAbs in patients infected with Delta and in those with Omicron variant. Symptoms duration was shorter in patients treated with sotrovimab than in those treated with the other mAbs, mainly among Omicron infected patients. No disease progression was observed in the Delta group, while two patients infected with omicron and treated with bamlanivimab/etesevimab presented progression.

The strength of this study is that it provides clinical data about the efficacy of different mAbs on COVID-19 progression against the Omicron variant assessed by a pragmatic RCT.

The limitation is the reduced sample size.

The results are useful in confirming the usefulness of Sotrovimab in the management of patients with Omicron BA 1 and BA 1.1. They cannot be applied to other Omicron sub-lineages.

Considering the availability of antiviral agents for early use in patients with asymptomatic or mild infection but with risk factors for COVID-19 progression and the longer duration of symptoms observed for casirivimab/imdevimab compared with sotrovimab, the conclusion about the potential role of this mAb against Omicron seems inappropriate.

Reviewer #1 (Public Review):

While some microbes have evolved to need an animal host for completion of the life cycle or survival, termed "obligate pathogens" (i.e. Plasmodium falciparum, viruses, Neisseria gonorrhoeae), there are many bacteria and fungi that can cause disease in insect or mammalian hosts, but can survive okay in the environment and do not need a host in order to survive, persist, and replicate. These microbes are often described as "accidental pathogens," where they evolved in the absence of a host to survive durable conditions in the environment, and only caused disease when they are accidentally exposed to a host (i.e. breathing in spores or traumatic inoculation). In this work, the authors set out to determine whether selection for Saccharomyces cerevisiae's ability to bind plastic in the absence of a host resulted in enhanced virulence when the yeast was exposed to a host. In doing so, they would be experimentally showing that adaptation to environmental conditions without a host, can "accidentally" produce pathogens. In this work, the authors indeed demonstrated that S. cerevisiae which had been selected for its ability to adhere to plastics evolved multicellular phenotypes and enhanced virulence in the Galleria mellonella wax moth host. In doing so, they effectively show experimental proof of the accidental virulence hypothesis, which can serve as the basis for future studies to better understand existing non-obligate microbes, and how new changes/exposures in the environment can cause the adaptation of microbes, which may result in the emergence of new "accidental" human pathogens. The work also investigated the evolutionary relationship between the different forms of multicellularity and uncovered that there was a strong correlation between the emergence of multiple multicellular phenotypes over cycles of plastic adhesion selection, which is a new finding compared to previous reports that these phenotypes in the environment or in laboratory/mutant strains are independent.

The conclusions drawn in this paper are well supported by the data, and the experiments are well-designed and straightforward and presented in a way that is generally able to be understood. This study is of great interest to both microbiologists who study how microbes adapt to the environment and those who study microbes in the context of infectious disease. This study experimentally proves the tenet of the accidental virulence hypothesis that adaptation/evolutionary selection to environmental factors may incidentally enhance the ability to survive within hosts.

Additionally, the authors conducted the experiments in a robust, well-controlled manner, and systematically analyzed the multicellular phenotypes. They assayed the multicellular phenotypes in a clearly defined manner and were able to characterize the traits of a large number of individual clones grown encompassing different timepoints, sexual and asexual reproduction, strains, and selection. Additionally, their virulence studies in G. mellonella show an extraordinary amount of work, which allowed them to see the increase in virulence (~30%) in the hyper-multicellular phenotype after performing infections using 40 different isolates from the experiment.

The authors also sought to find a genetic basis for the increase of multicellular phenotypes and virulence following plastic adherence selection. To do so, they studied the length of the FLO11 gene in their S. cerevisiae isolates. FLO11 length had been previously implicated in fungal adhesion and fungal virulence, which could offer a reason for the enhanced virulence phenotype following selection for plastic adherence. While their findings show the ancestral and control isolates did not have increased FLO11 length while many of the plastic-selected isolates did, there was not a definitive correlation between the multicellular phenotypes and FLO11 length. The authors did not pursue an additional investigation into the genetic basis of these adaptations.

Two aspects the reader must consider are the host and the microbe used in these virulence experiments. S. cerevisiae is an interesting choice to use because it is not considered to be a "pathogenic" microbe, although there are rare cases in which it can cause disease in humans. However, previous studies have shown S. cerevisiae has been shown to cause disease in G. mellonella, which can also be seen in the survival curves presented in this paper. Therefore, using G. mellonella in this study shows that the selection process resulted in increased virulence in the host. To strongly show the accidental virulence/pathogen hypothesis, a host-microbe pair where disease does not normally/typically occur could be used. In the context of this study, it could be done using a mouse model infected with S.cerevisiae. In doing so, it could show that environmental selection in the absence of a host has the ability to turn a "non-disease-causing microbe" into a disease-causing one, rather than a disease-causing microbe into a more disease-causing microbe. This could also make a more applicable leap to human infectious diseases.

Reviewer #1 (Public Review):

This is a very thorough biochemical work that investigated the ParABS system in pSM19035 by Volante et al. Volante et al showed convincingly that a specific architecture of the centromere (parS) of pSM19035 is required to assemble a stable/functional partition complex. Minimally, four consecutive parS are required for the formation of partition complex, and to efficiently activate the ATPase activity of ParA. The work is very interesting, and the discovery will allow the community to compare and contrast to the more widespread/more investigated canonical chromosomal ParABS system (where ParB is a sliding CTPase protein clamp, and a single parS site is often sufficient to assemble a working partition complex). All the main conclusions in the abstract are justified and supported by biochemical data with appropriate controls. A proposed multistep mechanism of partition complex assembly and disassembly (summarized in Fig 6) is reasonable. Perhaps the only shortcoming of this work is that the team does not yet get to the bottom of why four consecutive parS are needed.

Reviewer #1 (Public Review):

Dhawan et al examine the involvement of the perirhinal cortex (PRC) and ventral hippocampus (vHPC) in different forms of approach-avoidance conflict. The paper is well written, the methods used are appropriate for the question asked and, in general, the authors have succeeded in identifying the PRC and vHPC involvement. As such, the paper will eventually have an impact on thinking about the roles of the PRC and vHPC in different forms of learning and memory. However, this impact is conditional on the authors' responses to queries regarding experimental design, group allocations and statistical analyses.

Reviewer #1 (Public Review):

Ahmed et al. examine the changes in the enhancer landscape that may contribute to the transition from Barrett's oesophagus (BO) to oesophageal adenocarcinoma (OAC), building upon their past works looking at the chromatin changes within this transition. They identified a repertoire of eRNA regions that display differential expression between OAC and BO, validating their association to enhancers using H3K27ac levels, CUT&TAG, and KAS-seq. The authors look further into the target genes and regulatory TFs that may define eRNA levels, finding several TFs - AP1, KLF5, CTCF, and HNF1 - that have previously been implicated in OAC and confirming that sets of eRNA target genes were downregulated upon depletion of these TFs. Ahmed et al. also showed that eRNA target genes were relevant to OAC phenotypes, akin to that of DEGs in whole RNA-seq datasets. The authors lastly validate the activity of certain eRNAs targeting JUP, MYBL2, and CCNE1 using functional methods to confirm enhancer activity and effects on cell viability, as well as clinical features such as the age of diagnosis and survival time.

The landscape of eRNA activity seems to be well validated. However, deeper analyses to support the relevance of the function of key eRNAs, their specificity in regulating target genes, and the interaction with other OAC features would further support these findings.

Reviewer #1 (Public Review):

In this paper, Blair et al., analyze hippocampal place cell remapping in rats performing a shock avoidance task using miniscopes to image large-field-of-views. They use behavioral (barriers) and pharmacological (scopolamine) manipulations to interfere with place cell representations during the formation and extinction of aversive memories. By exploiting multi-cellular imaging they examine cell remapping dynamics during learning and extinction induced by the different manipulations and evaluate how they relate to behavioral readouts. The work is carefully planned and analyses successfully control for many potential confounds (but see below).

Major strengths of the paper include a) using large-field-of-view miniscope imaging to provide place cell data from rats thus favoring inter-species comparisons (most miniscope data is emerging from mouse and rats, especially better in memory tasks); b) an appropriate set of control analysis and experiments to exclude for potential confounds especially when it comes to comparison between groups (speed, number of trials, performance, within- and between-trials differences). Major weaknesses are a) the systemic effect of pharmacological manipulations and specificity regarding memory function; b) the lack of appropriate shuffled contrasted effects. Other inevitable methodological aspects (such as the effect of large GRIN lenses on the integrity of the dorsal, and ubiquitous expression of GCaMP) also require further consideration.

The paper may be of interest to the neuroscience community by setting new methodological standards and providing new data for across-species comparisons.

Reviewer #1 (Public Review):

ARL3 is a small GTPase that localizes to the primary cilium and plays a role in regulating the localization of some specific ciliary membrane proteins, including PDEδ and NPHP3. Mutations in this gene cause Joubert syndrome, a type of ciliopathy characterized by cerebellar malformation, and retinal degeneration. While the majority of the diseases occur in an autosomal recessive manner, two mutations in ARL3 (D67V and Y90C) have been reported to cause autosomal dominant retinal diseases. In the current paper, Travis et al. sought to understand the pathogenesis of the diseases caused by the two autosomal dominant mutations. They found that D67V acts as a constitutive active mutation, whereas Y90C is a fast-cycling mutant, which can be activated in a guanine nucleotide exchange factor (GEF) independent manner. Since the fast-cycle mutant did not bind to the effector proteins in vitro (likely because the guanine nucleotide falls off from the mutant ARL3, which has a lower affinity to GDP/GTP), they developed a method to snapshot the interaction between ARL3 and its effector. Using this method, they showed that the Y90C mutant indeed has increased interaction with the effectors, suggesting that Y90C is an overactive form of ARL3. They then addressed how photoreceptor cells are affected by these two mutations using a mouse model and found that the mutations disrupt the proper migration of the photoreceptor cells.

Strengths:<br /> • The paper is well written, and it was easy to understand what the authors did from the figure legends and the methods section.<br /> • It was easy to find out what is known or unknown, as the paper has accurate references.<br /> • The authors developed a method to analyze a snapshot of the interaction between ARL3 and its interactors.<br /> • The paper has an in vivo model and connects the biochemical characteristics of ARL3 to in vivo cellular phenotypes.

Weaknesses:<br /> (1) I understand that authors focused on nuclear migration defect as the phenotype was first described in ARL3-Q71L transgenic mice. The similar phenotype observed in RP2 knockout mice further supports the idea that the defect is caused by the hyperactivation of ARL3. Indeed, the defect is not reported in the ARL3 knockout mice, however, I feel that it does not necessarily mean that the defect is not caused by loss of function. Although it has not been assessed, ARL3 knockout mice might have the same defect. Therefore, I think analyzing both the migration defect and trafficking defect would be more informative, rather than focusing on the migration defect. The fact that the relationship between nuclear migration defect and the retinal degeneration phenotype is not entirely clear further enhances the importance of analyzing the trafficking defect.<br /> Does the expression of ARL3-Y90C also cause the trafficking defect? If it is the case, you can separate the nuclear migration phenotype from the one caused by the trafficking defect. Would the expression of lipidated cargo(s) rescue the trafficking defect as well?<br /> I think many questions can be addressed by analyzing the localization of the lipidated cargos, such as PDE and GRK1.

(2) I am not quite sure if the nuclear migration was assessed properly. Based on the pictures in Fig.1, some of the FLAG-negative cells also seem to be migrating to INL (please see Fig.1C and Fig.1D). Is this biologically normal during development? Could this analysis be affected by the thickness of OPL, the layer between ONL and INL? Also, the picture is cut out in the middle of INL. Could authors include more layers, such as IPL, of the retina in the picture, so that we can evaluate INL and OPL better? Taking this into account, I think it is worth measuring the nuclear position of FLAG-negative cells as a negative control in all the experiments.

(3) The way that the authors showed the Y90C mutant of ARL3 is a fast-cycling mutant is not very compelling. In Figure 2C, the authors showed that ARL3 Y90C can bind to PDEδ, its effector, once it is pre-loaded with GTP. The authors also showed that the mutant can bind to its effector even without EDTA as long as an excess amount of GTP is added. The authors used endogenous ARL3 as a control to compare the effects between wild-type and mutants. I see that this experiment has multiple pitfalls. First, ideally, this type of experiment needs to be done with a purified protein using fluorescent guanine nucleotide/radioactive guanine nucleotide (e.g. nucleotide loading assay or nucleotide exchange assay) to directly access the kinetics of nucleotide exchange. However, I do understand that this is out of the authors' expertise. In the authors' experimental setting, I am not sure loading the protein with GTP in the presence of the EDTA means anything more than confirming that the protein is intact. Theoretically, wild-type and a fast-cycling mutant can load GTP with similar efficiency in the presence of EDTA. Then during immuno-precipitation, GTP falls off from the Y90C mutant faster than wild-type (because a fast-cycling mutant theoretically has a lower affinity to guanine nucleotides), assuming that GTP was not added during immuno-precipitation (GTP addition was not mentioned in the method, but could authors confirm this?). But in this case, the kinetic of GTP dissociation can be affected by many factors, including the presence of GAP in the reaction, the dissociation constant of Y90C, the volume of the buffer used, and the number of washing steps. Thus, it is not very easy to estimate the difference between wild-type and Y90C. Besides, using endogenous ARL3 rather than ARL3-wild type FLAG as a control can be dangerous. I have experienced that a tagged protein is cleaved to a protein that has a similar size to endogenous protein. (I expressed GFP-protein X in knockout cells lacking protein X, and saw the band at the position where the endogenous protein is observed in wild-type cells). So, the endogenous band that the authors showed could come from the cleaved FLAG-Arl3. (Authors can easily confirm this by having wild-type not expressing FLAG-tagged ARL3, though).

An alternative experiment that I would suggest is doing immuno-precipitation in the buffer containing: 1) no guanine nucleotide, 2) 10mM GDP, or 3) 10mM GTP in the cells expressing the following protein: 1) ARL3 wild-type FLAG, 2) ARL3 Y90C FLAG, or 3) ARL3 D129N FLAG. 10mM guanine nucleotide should be added throughout the process including washing. This experiment might also be affected by many factors, but variability should be lower than the experiment presented in Fig 2C. ARL3-wild type FLAG is also a better control here than endogenous protein.

(4) In Fig.3, the authors attempted to take a snapshot of the interaction between ARL3 and multiple effector proteins. The three bands that were enriched in the Q71L cells were found as RP2, UNC119, and BART by mass spec (Fig.3B). These bands were used as a readout for the subsequent experiments. I am not quite sure why the authors used this approach rather than using the cell line that expresses both FLAG-ARL3 and GFP tagged protein of interest, just like what the authors did in Fig3G. The reasons why I prefer the latter approach are the following: FLAG bands that correspond to the three proteins (RP2, UNC119, and BART) in wild-type cells are very close to the detection limit, 2) authors failed to confirm that the lowest band actually comes from BART, 3) authors cannot access some important effector proteins, such as PDE because 293 cells might not express them. All of the problems can be solved by using the approach that was taken in Figur 3G.<br /> If the authors chose the former approach because of some specific reason, I would appreciate it if the authors could explain that in the main text of the paper.

(5) ALR3 Y90C causes nuclear migration defect. Given that Y90C is a fast-cycling mutant (hyperactive) and has a high affinity to ARL13B, the nuclear migration defect might come from either the increased activity of ARL3 or sequestration of ARL13B, which can act as a GEF for ARL3 but potentially have other functions. If my understanding is correct, the authors concluded that the defect caused by ARL3-Y90C is likely due to hyper-activation of the protein, as Y90C/T31N mutant, which cannot bind to effectors but still retains the ability to capture ARL13B, did not cause migration defect. But I am a little confused by the fact that Y90C/R149H, which is unable to bind to ARL13B (Fig.2C) but still retains the ability to interact with the effectors (Fig.3F), did not have migration defect (Fig.7B). Wouldn't this mean that the sequestration of ARL13B could contribute to the phenotype?<br /> If my understanding is correct, the authors are trying to say that both hyper-activation of cytosolic ARL3 and the defect in endogenous ARL3 activation in cilium is necessary to cause migration defect. I am not very convinced by this hypothesis, and still think that the defect could be caused by sequestration of ARL13B to the cytoplasm.<br /> Then why Y90C/T31N did not cause the defect even though they can sequester ARL13B? This might be explained by the localization of the ARL13B mutants. If Y90C can localize to the cilium while the double mutant, Y90C/T31N, does not, then only Y90C might be able to inhibit the ARL13B function in the cilium. This could explain the lack of the defect in the cells expressing Y90C/T31N.<br /> It would be helpful to understand how exactly the fast-cycling mutant causes the defect if the authors can provide more information, including localization of ARL3 (wild-type and mutants) as well as key proteins, such as ARL13B and the effector proteins. Assessing ARL13B defect seems to be particularly important to me because ARL13B deficiency has been connected to neuronal migration defect (Higginbotham et al., 2012)<br /> What I am trying to say here is that how the defect is caused is likely very complex. So, providing more information without sticking to one specific hypothesis might be important for readers/authors to accurately interpret the data.

(6) The rescue experiments that the authors presented in Fig.5-6 are striking and would build a base for future therapy of the diseases caused by ARL3 defects. However, I believe more examinations are needed to accurately interpret the data. The authors did this rescue experiment by co-injecting ARL3-FLAG and chaperons/cargos if I understand the method section correctly. But I feel we can interpret this data correctly only when ARL3-FLAG and chaperons/cargos are co-expressed in the same cells. I think a better way to analyze the data might be by comparing the nuclear migration phenotype between ARL3-FLAG only and ARL3-FLAG;chaperons/cargos double-positive cells.