Reviewer #2 (Public Review):

This manuscript by Xu et al. explores the potential joint storage/retrieval of associated signals in learning/memory and how that is encoded by some associative memory neurons using a mouse model. The authors examined mouse associative learning by pairing multimodal mouse learning including olfactory, tactile, gustatory, and pain/tail heating signals. The key finding is that after associative learning, barrel neurons respond to other multi-model stimulations. They found these barrel cortical neurons interconnect with other structures including piriform cortex, S1-Tr and gustatory cortical neurons. Further studies showed that Neuroligin 3 mediated the recruitment of associative memory neurons during paired stimulation group. The authors found that knockdown Neuroligin 3 in the barrel cortex suppressed the associative memory cell recruitment in the paired stimulation learning. Overall, this is an interesting study that reveals novel modalities associative learning involving multiple functionally connective cortical regions. Data presented are in general supporting their conclusions after revision.

Reviewer #2 (Public Review):

In this study the authors sought to understand the extent of similarity among species in intraspecific adaptation to environmental heterogeneity at the phenotypic and genetic levels. A particular focus was to evaluate if regions that were associated with adaptation within putative inversions in one species were also candidates for adaptation in another species that lacked those inversions. This study is timely for the field of evolutionary genomics, due to recent interest surrounding how inversions arise and become established in adaptation.

Major strengths-

Their study system was well suited to addressing the aims, given that the different species of sunflower all had GWAS data on the same phenotypes from common garden experiments as well as landscape genomic data, and orthologous SNPs could be identified. Organizing a dataset of this magnitude is no small feat. The authors integrate many state-of-the-art statistical methods that they have developed in previous research into a framework for correlating genomic Windows of Repeated Association (WRA, also amalgamated into Clusters of Repeated Association based on LD among windows) with Similarity In Phenotype-Environment Correlation (SIPEC). The WRA/CRA methods are very useful and the authors do an excellent job at outlining the rationale for these methods.

Weaknesses-

The authors did an excellent job responding to the first set of reviews and overall I found the manuscript more streamlined and easier to read. The main weakness in the manuscript is that correlations among environmental variables were not controlled for in their results, and is a source of potential pseudoreplication. The authors are clear about the results that are affected by pseudoreplication.

The manuscript shows how to integrate many recent methods to study the repeatability of adaptation, and the methods and data are likely to be used in similar studies.

Reviewer #2 (Public Review):

Davidsen and Sullivan present an improved method for quantifying tRNA aminoacylation levels by deep sequencing. By combining recent advances in tRNA sequencing with lysine-based chemistry that is more gentle on RNA, splint oligo-based adapter ligation, and full alignment of tRNA reads, they generate an interesting new protocol. The lab protocol is complemented by a software tool that is openly available on Github. Many of the points highlighted in this protocol are not new but have been used in recent protocols such as Behrens et al. (2021) or McGlincy and Ingolia (2017). Nevertheless, a strength of this study is that the authors carefully test different conditions to optimize their protocol using a set of well-designed controls.

The conclusions of the manuscript appear to be well supported by the data presented. However, there are a few points that need to be clarified.

1) One point that remains unsatisfactory is a better benchmarking against the state of the art. It is currently impossible to estimate how much the results of this new protocol differ from alternative methods and in particular from Behrens et al. (2021). Here it will be helpful to perform experiments with samples similar to those used in the mim-tRNAseq study and not with H1299 cells.

2) While the protocol aims to implement an improved method for quantification of tRNA aminoacylation, it can also be used for tRNA quantification and analysis of tRNA modifications. It will increase the impact of this study if the authors benchmark the outcomes of their protocol with other tRNA sequencing protocols with samples similar to these papers, which will be important for certain research teams that are unlikely to implement two different tRNA sequencing methods. Are there any possible adaptations that would allow the analysis of tRNA fragments?

3) Like Behrens et al. (2021), Davidsen and Sullivan use TGIRT-III RT for their analyses. The enzyme is not currently available in a form suitable for tRNA-seq. It would be very helpful to test different new RT enzymes that are commercially available. The example of Maxima RT - Figure 2 Supp 6 - shows significantly lower performance than the presented TGIRT-III RT data. In lines 296-298, the authors mention improvements to the protocol by using ornithine. Why are these improvements not included?

4) A technical concern: The samples are purified multiple times using a specific RNA purification kit. Did the authors test different methods to purify the RNA and does this influence the result of the method?

5) The study would benefit from an explicit step-by-step protocol, including the choice of adapters that are shown to work best in the protocol.

Reviewer #2 (Public Review):

Summary:<br /> This study provided a neural network emulator of the human ventricular cardiomyocyte action potential. The inputs are the corresponding maximum conductances and the output is the action potential (AP). It used the forward and inverse problems to evaluate the model. The forward problem was solved for synthetic data, while the inverse problem was solved for both synthetic and experimental data. The NN emulator tool enables the acceleration of simulations, maintains high accuracy in modeling APs, effectively handles experimental data, and enhances the overall efficiency of pharmacological studies. This, in turn, has the potential to advance drug development and safety assessment in the field of cardiac electrophysiology.

Strengths:<br /> (1) Low computational cost: The NN emulator demonstrated a massive speed-up of more than 10,000 times compared to the simulator. This substantial increase in computational speed has the potential to expedite research and drug development processes

(2) High accuracy in the forward problem: The NN emulator exhibited high accuracy in solving the forward problem when tested with synthetic data. It accurately predicted normal APs and, to a large extent, abnormal APs with early afterdepolarizations (EADs). High accuracy is a notable advantage over existing emulation methods, as it ensures reliable modeling and prediction of AP behavior

Weaknesses:<br /> (1) Input space constraints: The emulator relies on maximum conductances as inputs, which explain a significant portion of the AP variability between cardiomyocytes. Expanding the input space to include channel kinetics parameters might be challenging when solving the inverse problem with only AP data available.

(2) Simplified drug-target interaction: In reality, drug interactions can be time-, voltage-, and channel state-dependent, requiring more complex models with multiple parameters compared to the oversimplified model that represents the drug-target interactions by scaling the maximum conductance at control. The complex model could also pose challenges when solving the inverse problem using only AP data.

(3) Limited data variety: The inverse problem was solved using AP data obtained from a single stimulation protocol, potentially limiting the accuracy of parameter estimates. Including AP data from various stimulation protocols and incorporating pacing cycle length as an additional input could improve parameter identifiability and the accuracy of predictions.

(4) Larger inaccuracies in the inverse problem using experimental data: The reasons for this result are not quite clear. Hypotheses suggest that it may be attributed to the low parameter identifiability or the training data set were collected in small tissue preparation.

Reviewer #2 (Public Review):

Bhanja et al have examined how actin polymerization switch B-cell receptor (BCR) signaling from amplification to attenuation. The authors have examined B cell spreading and contraction using lipid bilayers to assess the molecular regulation of BCR signalling during the contraction phase. Their data provide evidence for that N-WASP activated Arp2/3 generates centripetally moving actin foci and contractile actomyosin from lamellipodia actin networks. This generates BCR dense foci that pushes out both stimulatory kinases and inhibitory phosphatases. The study provides novel insight into how B cells upon activation attenuate BCR signalling by contraction of the actin cytoskeleton and clustering of BCR foci and this dynamic response is mediated by N-WASP and Arp2/3.

Strengths: The manuscript is well written and results, methods, figures and legends described in detail making it easy to follow the experimental setup, analysis, and conclusions. The authors achieved their aims, and the results support their conclusions.

Weaknesses: Minor. The working hypothesis of molecular crowding as a way to push out signalling molecules from the BCR dense foci is interesting. The authors provide evidence for that this is an active process mediated by N-WASP - Arp2/3 induced actin foci. Another possibility discussed in the revised version is that BCR dense foci formation is an indirect consequence of lamellipodia retraction. Future works should define the specific role of N-WASP, Arp2/3 and actin in the process to form BCR dense foci, especially as the BCR continue to signal in the cytoplasm.

Reviewer #2 (Public Review):

Summary:

Tissue-resident macrophages are more and more thought to exert key homeostatic functions and contribute to physiological responses. In the report of O'Brien and Colleagues, the idea that the macrophage-expressed scavenger receptor MARCO could regulate adrenal corticosteroid output at steady-state was explored. The authors found that male MARCO-deficient mice exhibited higher plasma aldosterone levels and higher lung ACE expression as compared to wild-type mice, while the availability of cholesterol and the machinery required to produce aldosterone in the adrenal gland were not affected by MARCO deficiency. The authors take these data to conclude that MARCO in alveolar macrophages can negatively regulate ACE expression and aldosterone production at steady-state and that MARCO-deficient mice suffer from secondary hyperaldosteronism.

Strengths:

If properly demonstrated and validated, the fact that tissue-resident macrophages can exert physiological functions and influence endocrine systems would be highly significant and could be amenable to novel therapies.

Weaknesses:

The data provided by the authors currently do not support the major claim of the authors that alveolar macrophages, via MARCO, are involved in the regulation of a hormonal output in vivo at steady-state. At this point, there are two interesting but descriptive observations in male, but not female, MARCO-deficient animals, and overall, the study lacks key controls and validation experiments, as detailed below.

Major weaknesses:

1) According to the reviewer's own experience, the comparison between C57BL/6J wild-type mice and knock-out mice for which precise information about the genetic background and the history of breedings and crossings is lacking, can lead to misinterpretations of the results obtained. Hence, MARCO-deficient mice should be compared with true littermate controls.

2) The use of mice globally deficient for MARCO combined with the fact that alveolar macrophages produce high levels of MARCO is not sufficient to prove that the phenotype observed is linked to alveolar macrophage-expressed MARCO (see below for suggestions of experiments).

3) If the hypothesis of the authors is correct, then additional read-outs could be performed to reinforce their claims: levels of Angiotensin I would be lower in MARCO-deficient mice, levels of Antiotensin II would be higher in MARCO-deficient mice, Arterial blood pressure would be higher in MARCO-deficient mice, natremia would be higher in MARCO-deficient mice, while kaliemia would be lower in MARCO-deficient mice. In addition, co-culture experiments between MARCO-sufficient or deficient alveolar macrophages and lung endothelial cells, combined with the assessment of ACE expression, would allow the authors to evaluate whether the AM-expressed MARCO can directly regulate ACE expression.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Trautman et al. set out to test the hypothesis that increased intake of dietary protein is deleterious to health when uncoupled from resistance training.

Strengths:

The experimental design is well crafted and the experiments provide useful information supporting the hypothesis. The authors take into account the limitations of their study in the discussion, and guide the reader through their results and the interpretation in a fair and measured way, without overstating claims.

Weaknesses:

As acknowledged by the authors in the discussion section, this study only features a small sample of male mice from a single strain. Thus the results may not hold when female mice and diverse genetic backgrounds are analyzed. The lack of repeated measures of physiological parameters is also a limitation of the study. Measurements of body weight, body composition, food (calorie) consumption, and locomotor/strength assays could have been provided throughout the study and compared to a baseline value for each animal.

Reviewer #2 (Public Review):

The authors introduce "HAMA", a new automated pipeline for architectural analysis of the bacterial cell wall. Using MS/MS fragmentation and a computational pipeline, they validate the approach using well-characterized model organisms and then apply the platform to elucidate the PG architecture of several members of the human gut microbiota. They discover differences in the length of peptide crossbridges between two species of the genus Bifidobacterium and then show that these species also differ in cell envelope stiffness, resulting in the conclusion that PG "compactness" determines stiffness.

The pipeline is solid and revealing the poorly characterized PG architecture of the human gut microbiota is worthwhile and significant. However, it is unclear if or how their pipeline is superior to other existing techniques - PG architecture analysis is routinely done by many other labs; the only difference here seems to be that the authors chose gut microbes to interrogate.

I do not agree with their conclusions about the correlation between compactness and cell envelope stiffness. These experiments are done on two different species of bacteria and their experimental setup therefore does not allow them to isolate crossbridge length (which they propose indicates more or less compact PG) as the only differential property that can influence stiffness. These two species likely also differ in other ways that could modulate stiffness, e.g. turgor pressure, overall PG architecture (not just crossbridge length), membrane properties, teichoic acid composition etc.

Reviewer #2 (Public Review):

Unconventional secretion refers to the release of cargoes without a signal peptide and is performed independent of ER-Golgi trafficking. One essential type of unconventional secretion is type I, in which a cargo can translocate directly across the plasma membrane. FGF2 is one excellent mode to study type I translocation and the authors have focused on FGF2 secretion for decades. Many beautiful works have been performed to reveal the mechanism of FGF2 translocation step by step. And the picture is getting clearer which time a new work from the lab is published. In the current work, the authors characterized the importance of disulfate bond formation on C95 of FGF2 in lipid binding and translocation. In addition, they clearified the role of another C77 which is require for binding to the Na/K -ATPase that regulates the early step of FGF2 binding to the membrane. The authors also employed structural approaches and MD to provide mechanistic insights into the translocation process. In general it is an important advance regarding the translocation of FGF2 and data provided are brief, clear and convincing.

Reviewer #2 (Public Review):

The authors have done a number of additional experiments and textual changes to address referee comments from the first round of review that have improved some aspects of the manuscript. However, they did not fully address two major issues brought up in my previous public review, reiterated below.

1) What is the specific role for HSP90a/b in regulating protein translation during chronic stress through the ISR or related pathways? The authors indicate that the induction of the eIF2a phosphatase GADD34 is not impacted in HSP90-deficient cells, so what role does HSP90 have in this process. Is HSP90 required for proper folding of GADD34? Would you see similar effects in protein translation recovery if other ISR activators are used in HSP90-deficient cells?

2) Are similar effects observed in non-dividing cells?' Does chronic stress lead to increases of size and regulation of protein translation in primary cell models that are not undergoing division.

This leaves the study as an interesting observational study that correlates increases in cell size and protein translation. However, it doesn't really answer some of the most important questions related to mechanisms defining this correlation. Regardless, this remains an interesting jumping off point to continue exploring this interesting finding correlating cell size and stress signaling that will be further pursued in subsequent manuscripts, which will likely continue to reveal the importance and mechanistic basis of this 'rewiring stress response' during stress and in disease.

Reviewer #2 (Public Review):

An important paper that confirms the validity of the initial findings of Chretien et al regarding the hot temperatures at which the mitochondrion is operating. The authors responded adequately to the reviewers' concerns.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript titled 'Proteolytic cleavage and inactivation of the TRMT1 tRNA modification enzyme by SARS-CoV-2 main protease' from K. Zhang et al. demonstrates that several RNA modifications are downregulated during SARS-CoV-2 infection including the widespread m2,2G methylation, which potentially contributes to changes in host translation. To understand the molecular basis behind this global hypomodification of RNA during infection, the authors focused on the human methyltransferase TRMT1 that catalyzes the m2,2G modification. They reveal that TRMT1 not only interacts with the main SARS-CoV-2 protease (Nsp5) in human cells but is also cleaved by Nsp5. To establish if TRMT1 cleavage by Nsp5 contributes to the reduction in m2,2G levels, the authors show compelling evidence that the TRMT1 fragments are incapable of methylating the RNA substrates due to loss of RNA binding by the catalytic domain. They further determine that expression of full-length TRMT1 is required for optimal SARS-CoV-2 replication in 293T cells. Nevertheless, the cleavage of TRMT1 was dispensable for SARS-CoV-2 replication hinting at the possibility that TRMT1 could be an off-target or fortuitous substrate of Nsp5. Overall, this study will be of interest to virologists and biologists studying the role of RNA modification and RNA modifying enzymes in viral infection.

Strengths:<br /> • The authors use a state-of-the-art mass spectrometry approach to quantify RNA modifications in human cells infected with SARS-CoV-2.<br /> • The authors go to great length to demonstrate that SARS-CoV-2 main protease, Nsp5, interacts, and cleaves TRMT1 in cells and perform important controls when needed. They use a series of overexpression with strategically placed tags on both TRMT1 and Nsp5 to strengthen their observations.<br /> • The use of an inactive Nsp5 mutant (C145A) strongly supports the claim of the authors that Nsp5 is solely responsible for TRMT1 cleavage in cells.<br /> • Although the direct cleavage was not experimentally determined, the authors convincingly show that TRMT1 Q530N is not cleaved by Nsp5 suggesting that the predicted cleavage site at this position is most likely the bona fide region processed by Nsp5 in cells.<br /> • To understand the impact of TRMT1 cleavage on its RNA methylation activity, the authors rigorously test four protein constructs for their capacity not only to bind RNA but also to introduce the m2,2G modification. They demonstrate that the fragments resulting from TRMT1 cleavage are inactive and cannot methylate RNA. They further establish that the C-terminal region of TRMT1 (containing a zinc-finger domain) is the main binding site for RNA.<br /> • While 293T cells are unlikely an ideal model system to study SARS-CoV-2 infection, the authors use two cell lines and well-designed rescue experiments to uncover that TRMT1 is required for optimal SARS-CoV-2 replication.

Weaknesses:<br /> • Immunoblotting is extensively used to probe for TRMT1 degradation by Nsp5 in this study. Regretfully, the polyclonal antibody used by the authors shows strong non-specific binding to other epitopes. This complicates the data interpretation and quantification since the cleaved TRMT1 band migrates very closely to a main non-specific band detected by the antibody (for instance Fig 3A). While this reviewer is concerned about the cross-contamination during quantification of the N-TRMT1, the loss of this faint cleaved band with the TRMT1 Q530N mutant is reassuring. Nevertheless, the poor behavior of this antibody for TRMT1 detection was already reported and the authors should have taken better precautions or designed a different strategy to circumvent the limitation of this antibody by relying on additional tags.

• While 293T cells are convenient to use, it is not a well-suited model system to study SARS-CoV-2 infection and replication. Therefore, some of the conclusions from this study might not apply to better-suited cell systems such as Vero E6 cells or might not be observed in patient-infected cells.

• The reduction of bulk TRMT1 levels is minor during infection of MRC5 cells with SARS-CoV-2 (Fig 1). This does not seem to agree with the more dramatic reduction in m2,2G modification levels. Cellular Localization experiments of TRMT1 would help clarify this. While TRMT1 is found in the cytoplasm and nucleus, it is possible that TRMT1 is more dramatically degraded in the cytoplasm due to easier access by Nsp5.

• In Fig 6, the authors show that TRMT1 is required for optimal SARS-CoV-2 replication. This can be rescued by expressing TRMT1 (Fig 7). Nevertheless, it is unknown if the methylation activity of TRMT1 is required. The authors could have expressed an inactive TRMT1 mutant (by disrupting the SAM binding site) to establish if the RNA modification by TRMT1 is important for SARS-CoV-2 replication or if it is the protein backbone that might contribute to other processes.

• Fig 7, the authors used the Q530N variant to rescue SARS-CoV-2 replication in TRMT1 KO cells. This is an important experiment and unexpectedly reveals that TRMT1 cleavage by Nsp5 is not required for viral replication. To strengthen the claim of the authors that TRMT1 is required to promote viral replication and that its cleavage inhibits RNA methylation, the authors could express the TRMT1 N-terminal construct in the TRMT1 KO cells to assess if viral replication is restored or not to similar levels as WT TRMT1. This will further validate the potential biological importance of TRMT1 cleavage by Nsp5.

• Fig 7 shows that the TRMT1 Q530N variant rescues SARS-CoV-2 replication to greater levels then WT TRMT1. The authors should discuss this in greater detail and its possible implications with their proposed statement. For instance, are m2,2G levels higher in Q530N compared to WT? Does Q530N co-elute with Nsp5 or is the interaction disrupted in cells?

Reviewer #2 (Public Review):

Summary:<br /> The manuscript focuses on the comparison of two PLP-dependent enzyme classes that perform amino acyl decarboxylations. The goal of the work is to understand the substrate specificity and factors that influence the catalytic rate in an enzyme linked to theanine production in tea plants.

Strengths:<br /> The work includes x-ray crystal structures of modest resolution of the enzymes of interest. These structures provide the basis for the design of mutagenesis experiments to test hypotheses about substrate specificity and the factors that control catalytic rate. These ideas are tested via mutagenesis and activity assays, in some cases both in vitro and in plants.

Weaknesses:<br /> The manuscript could be more clear in explaining the contents of the x-ray structures and how the complexes studied relate to the reactant and product complexes. The structure and mechanism section would also be strengthened by including a diagram of the reaction mechanism and including context about reactivity. As it stands, much of the structural results section consists of lists of amino acids interacting with certain ligands without any explanation of why these interactions are important or the role they play in catalysis. The experiments testing the function of a novel Zn(II)-binding domain also have serious flaws. I don't think anything can be said at this point about the function of the Zn(II) due to a lack of key controls and problems with experimental design.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript 'Recognition and Cleavage of Human tRNA Methyltransferase TRMT1 by the SARS-CoV-2 Main Protease' from Angel D'Oliviera et al., uncovers that TRMT1 can be cleaved by SARS-CoV-2 main protease (Mpro) and defines the structural basis of TRMT1 recognition by Mpro. They use both recombinant TRMT1 and Mpro as well as endogenous TRMT1 from HEK293T cell lysates to convincingly show cleavage of TRMT1 by the SARS-CoV-2 protease. To understand how Mpro recognizes TRMT1, they solved a co-crystal structure of Mpro bound to a peptide derived from the predicted cleavage site of TRMT1. This structure revealed important protein-protein interfaces and highlights the importance of the conserved Q530 for cleavage by Mpro. They then compared their structure with previous X-ray crystal structures of Mpro bound to substrate peptides derived from the viral polyprotein and proposed the concept of two distinct binding conformations to Mpro: P3´-out and P3´-in conformations (here P3´ stands for the third residue downstream of the cleavage site). It remains unknown what is the physiological role of these two binding conformations on Mpro function, but the authors established that Mpro has dramatically different cleavage efficiencies for three distinct substrates. In an effort to rationalize this observation, a series of mutations in Mpro's active site and the substrate peptide were tested but unexpectedly had no significant impact on cleavage efficiency. While molecular dynamic simulations further confirmed the propensity of certain substrates to adopt the P3´-out or P3´-in conformation, they did not provide additional insights into the dramatic differences in cleavage efficiencies between substrates. This led the authors to propose that the discrimination of Mpro for preferred substrates might occur at a later stage of catalysis after binding of the peptide. Overall, this work will be of interest to biologists studying proteases and substrate recognition by enzymes as well as help efforts to target Mpro with peptide-like drugs.

Strengths:<br /> • The authors' statements are well supported by their data, and they used relevant controls when needed. Indeed, they used the Mpro C145A inactive variant to unambiguously show that the TRMT1 cleavage detected in vitro is solely due to Mpro's activity. Moreover, they used two distinct polyclonal antibodies to probe TRMT1 cleavage.

• Their 1.9 Å crystal structure is of high quality and increases the confidence in the reported protein-protein contacts seen between TRMT1-derived peptide and Mpro.

• Their extensive in vitro kinetic assay was performed in ideal conditions although it is unclear how many replicates were performed.

• The authors test multiple hypotheses to rationalize the preference of Mpro for certain substrates.

• While this reviewer is not able to comment on the rigor of the MD simulations, the interpretations made by the authors seem reasonable and convincing.

• The concept of two binding conformations (P3´-out or P3´-in) for the substrate in the active site of Mpro is significant and can guide drug design.

Weaknesses:<br /> • While the authors convincingly show that TRMT1 is cleaved by Mpro, the exact cleavage site was never confirmed experimentally. It is most likely that the predicted site is the main cleavage site as proposed by the authors (region 527-534). Nevertheless, in Fig 1C (first lane from the right) there are two bands clearly observed for the cleavage product containing the MT Domain. If the predicted site was the only cleavage site recognized by Mpro, then a single band for the MT domain would be expected. This observation suggests that there might be two cleavage sites for Mpro in TRMT1. Indeed, residues RFQANP (550-555) in TRMT1 might be a secondary weaker cleavage site for Mpro, which would explain the two observed bands in Fig 1C. A mass spectrometry analysis of the cleaved products would clarify this.

• A control is missing in Fig 1D. Since the authors use western blots to show the gradual degradation of endogenous TRMT1, a control with a protein that does not change in abundance over the course of the measurement is important. This is required to show that the differences in intensity of TRMT1 by western blotting are not due to loading differences etc.

• The two polyclonal antibodies used by the authors seem to have strong non-specific binding to proteins other than TRMT1 but did not impact the author's conclusions. This is a limitation of the commercially available antibodies for TRMT1, and unless the authors select a new monoclonal antibody specific to TRMT1 (costly and lengthy process), this limitation seems out of their control.

• The recombinantly purified TRMT1 seems to have some non-negligible impurities (extra bands in Fig 1C). This does not impact the conclusions of the authors but might be relevant to readers interested in working with TRMT1 for biochemical, structural, or other purposes.

• Despite the reasonable efforts of the authors, it remains unknown why Mpro shows higher cleavage efficiency for the nsp4/5 sequence compared to TRMT1 or nsp8/9 sequences.

• The peptide cleavage kinetic assay used by the authors relies on a peptide labelled with a fluorophore (MCA) on the N-terminus and a quencher (Dpn) on the C-terminus. This design allows high-throughput measurements compatible with plate readers and is a robust and convenient tool. Nevertheless, the authors did not control for the impact of the labels (MCA and Dpn) on the activity of Mpro. It is possible that the differences in cleavage efficiencies between peptides are due to unexpected conformational changes in the peptide upon labelling. Moreover, the TRMT1 peptide has an E at the N-terminus and an R at the C-terminus (while the nsp4/5 peptide has an S and M, respectively). It is possible that these two terminal residues form a salt bridge in the TRMT1 peptide that might constrain the conformation of the peptide and thus reduce its accessibility and cleavage by Mpro. Enzymatic assays in the absence of labels and MD simulations with the bona fide peptides (including the labels) used in the kinetic measurements are needed to prove that the cleavage efficiencies are not biased by the fluorescence assay.

• The authors used A431S variant in TRMT1-derived peptide to disrupt the P3´-in conformation. While this reviewer agrees with the rationale behind A431S design, it is important to confirm experimentally that the mutation disrupted the P3´-in conformation in favor of the P3´-out conformer. The authors could use their MD simulations to determine if the TRMT1 A431S variant favors the P3´-out conformation.

• An unanswered question not addressed by the authors is if the peptides undergo conformational changes upon Mpro binding or if they are pre-organized to adopt the P3´-out and P3´-in conformations.

• While the authors describe at great length the hydrogen bonds involved in the substrate recognition by Mpro, they occluded to highlight important stacking interactions in this interface. For instance, Phe533 from TRMT1 stacks with Met49 while L529 from TRMT1 packs against His41 of Mpro. Both hydrogen bonding and stacking interactions seem important for TRMT1-derived peptide recognition by Mpro.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors extend their previous studies on trans-activation, cis-inhibition (PMID: 25255098), and cis-activation (PMID: 30628888) of the Notch pathway. Here they create a large number of cell lines using CHO-K1 and C2C12 cells expressing either Notch1-Gal4 or Notch2-Gal4 receptors which express a fluorescent protein upon receptor activation (receiver cells). For cis-inhibition and cis-activation assays, these cells were engineered to express one of the four canonical Notch ligands (Dll1, Dll4, Jag1, Jag2) under tetracycline control. Some of the receiver cells were also transfected with a Lunatic fringe (Lfng) plasmid to produce cells with a range of Lfng expression levels. Sender cells expressing all of the canonical ligands were also produced. Cells were mixed in a variety of co-culture assays to highlight trans-activation, cis-activation, and cis-inhibition. All four ligands were able to trans-activate Notch1 and Notch 2, except Jag1 did not transactivate Notch1. Lfng enhanced trans-activation of both Notch receptors by Dll1 and Dll2, and inhibited Notch1 activation by Jag2 and Notch2 activation by both Jag 1 and Jag2. Cis-expression of all four ligands was predominantly inhibitory, but Dll1 and Dll4 showed strong cis-activation of Notch2. Interestingly, cis-ligands preferentially inhibited trans-activation by the same ligand, with varying effects on other trans-ligands.

Strengths:<br /> This represents the most comprehensive and rigorous analysis of the effects of canonical ligands on cis- and trans-activation, and cis-inhibition, of Notch1 and Notch2 in the presence or absence of Lfng so far. Studying cis-inhibition and cis-activation is difficult in vivo due to the presence of multiple Notch ligands and receptors (and Fringes) that often occur in single cells. The methods described here are a step towards generating cells expressing more complex arrays of ligands, receptors, and Fringes to better mimic in vivo effects on Notch function.

In addition, the fact that their transactivation results with most ligands on Notch1 and 2 in the presence or absence of Lfng were largely consistent with previous publications provides confidence that the author's assays are working properly.

Weaknesses:<br /> It was unusual that the engineered CHO cells expressing Notch1-Gal4 were not activated at all by co-culture with Jag1-expressing CHO cells. Many previous reports have shown that Jag1 can activate Notch1 in co-culture assays, including when Notch1 was expressed in CHO cells. Interestingly, when the authors used Jag1-Fc in a plate coating assay, it did activate Notch1 and could be inhibited by the expression of Lfng.

The cell surface level of the ligands was determined by flow cytometry of a co-translated fluorescent protein. Some calibration of the actual cell surface levels with the fluorescent protein would strengthen the results.

Reviewer #2 (Public Review):

The manuscript by Okholm and colleagues identified an interesting new instance of ceRNA involving a circular RNA. The data are clearly presented and support the conclusions. Quantification of the copy number of circRNA and quantification of the protein were performed, and this is important to support the ceRNA mechanism.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript addresses the role of the extracellular matrix in olfactory development. Despite the importance of these extracellular structures, the specific roles and activities of matrix molecules are still poorly understood. Here, the authors combine live imaging and genetics to examine the role of laminin gamma 1 in multiple steps of olfactory development. The work comprises a descriptive but carefully executed, quantitative assessment of the olfactory phenotypes resulting from loss of laminin gamma. Overall, this is a constructive advance in our understanding of extracellular matrix contributions to olfactory development, with a well-written Discussion with relevance to many other systems.

Strengths:<br /> The strengths of the manuscript are in the approaches: the authors have combined live imaging, careful quantitative analyses, and molecular genetics. The work presented takes advantage of many zebrafish tools including mutants and transgenics to directly visualize the laminin extracellular matrix in living embryos during the developmental process.

Weaknesses:<br /> The weaknesses are primarily in the presentation of some of the imaging data. In certain cases, it was not straightforward to evaluate the authors' interpretations and conclusions based on the single confocal sections included in the manuscript. For example, it was difficult to assess the authors' interpretation of when and how laminin openings arise around the olfactory placode and brain during olfactory axon guidance.

Reviewer #2 (Public Review):

Summary:<br /> The manuscript "A multi-hierarchical approach reveals D-1 serine as a hidden substrate of sodium-coupled monocarboxylate transporters" by Wiriyasermkul et al. is a resubmission of a manuscript, which focused first on the proteomic analysis of apical membrane isolated from mouse kidney with early Ischemia-Reperfusion Injury (IRI), a well-known acute kidney injury (AKI) model. In the second part, the transport of D-serine by Asct2, Smct1, and Smct2 has been characterized in detail in different model systems, such as transfected cells and proteoliposomes.

Strengths:<br /> A major problem with the first submission was the explanation of the link between the two parts of the manuscript: it was not very clear why the focus on Asct2, Smct1, and Smct2 was a consequence of the proteomic analysis. In the present version of the manuscript, the authors have focused on the expression of membrane transporters in the proteome analysis, thus making the reason for studying Asct2, Smct1, and Smct2 transporters more clear. In addition, the authors used 2D-HPLC to measure plasma and urinary enantiomers of 20 amino acids in plasma and urine samples from sham and Ischemia-Reperfusion Injury (IRI) mice. The results of this analysis demonstrated the value of D-serine as a potential marker of renal injury. These changes have greatly improved the manuscript and made it more convincing.

Reviewer #2 (Public Review):

Patel et al perform the analysis of neurons in a somatosensory network involved in responses to noxious cold in Drosophila larvae. Using a combination of behavioral experiments, Calcium imaging, optogenetics, and synaptic connectivity analysis in the Drosophila larval they assess the function of circuit elements in the somatosensory network downstream of multimodal somatosensory neurons involved in innocuous and noxious stimuli sensing and probe their function in noxious cold processing, Consistent with their previous findings they find the multidendritic class III neurons, to be the key cold sensing neurons that are both required and sufficient for the CT behaviors response (shown to evoked by noxious cold). They further investigate the downstream neurons identified based on literature and connectivity from EM at different stages of sensory processing characterize the different phenotypes upon activating/silencing those neurons and monitor their responses to noxious cold. The work reveals diverse phenotypes for the different neurons studied and provides the groundwork for understanding how information is processed in the nervous system from sensory input to motor output and how information from different modalities is processed by neuronal networks. However, at times the writing could be clearer and some results interpretations more rigorous.

Specific comments

1) In Figure 1 -supplement 6D-F (Cho co-activation)

The authors find that Ch neurons are cold sensitive and required for cold nociceptive behavior but do not facilitate behavioral responses induced but CIII neurons

The authors show that coactivating mdIII and cho inhibits the CT (a typically observed cold-induced behavioral response) in the second part of the stimulation period, while Cho was required for cold-induced CT. Different levels of activation of md III and Cho (different light intensities) could bring some insights into the observed phenotypes upon Cho manipulation as different levels activate different downstream networks that could correspond to different stimuli. Also, it would be interesting to activate chordotonal during exposure to cold to determine how a behavioral response to cold is affected by the activation of chordotonal sensory neurons.

2) Throughout the paper the co-activation experiments investigate whether co-activating the different candidate neurons and md III neurons facilitates the md III-induced CT response. However, the cold noxious stimuli will presumably activate different neurons downstream than optogenetic activation of MdIII and thus can reveal more accurately the role of the different candidate neurons in facilitating cold nociception.

3) Use of blue lights in behavioral and imaging experiments

Strong Blue and UV have been shown to activate MDIV neurons (Xiang, Y., Yuan, Q., Vogt, N. et al. Light-avoidance-mediating photoreceptors tile the Drosophila larval body wall. Nature 468, 921-926 (2010). https://doi.org/10.1038/nature09576) and some of the neurons tested receive input from MdIV. In their experiments, the authors used blue light to optogenetically activate CDIII neurons and then monitored Calcium responses in Basin neurons, premotor neurons, and ascending neurons and UV light is necessary for photoconversion in Campari Experiments. Therefore, some of the neurons monitored could be activated by blue light and not cdIII activation. Indeed, responses of Basin-4 neurons can be observed in the no ATR condition (Fig 3HI) and quite strong responses of DnB neurons. (Figure 6E) How do authors discern that the effects they see on the different neurons are indeed due to cold nociception and not the synergy of cold and blue light responses could especially be the case for DNB that could have in facilitating the response to cold in a multisensory context (where mdIV are activated by light). In addition, the silencing of DNB neurons during cold stimulation does not seem to give very robust phenotypes (no significant CT decrease compared to empty GAL4 control).

It would be important to for example show that even in the absence of blue light the DNB facilitates the mdIII activation or cold-induced CT by using red light and Chrimson for example or TrpA activation (for coactivation with md III)

Alternatively, in some other cases, the phenotype upon co-activation could be inhibited by blue light (e.g. chair-1 (Figure 5 H-I))

More generally, given the multimodal nature of stimuli activating mdIV , MdIII (and Cho) and their shared downstream circuitry it is important to either control for using the blue light in these stimuli or take into account the presence of the stimulus in interpreting the results as the coactivation of for example Cho and mdIII using blue lights also could activate mdIV (and downstream neurons, alter the state of the network that could inhibit the md III induced CT responses

Assessing the differences in behavioral phenotypes in the different conditions could give an idea of the influence of combining different modalities in these assays. For example, did the authors observe any other behaviors upon co-activation of MDIII and Cho (at the expense of CT in the second part of the stimulation) or did the larvae resume crawling? Blue light typically induces reorientation behavior. What about when co-activating mdIII and Basin-4?

Using Chrimson and red light or TrpA in some key experiments e.g. with Cho, Basin-4, and DNB would clarify the implication of these neurons in cold nociception

4) Basins<br /> - Page 17 line 442-3 "Neural silencing of all Basin (1-4) neurons, using two independent driver lines (R72F11GAL4 and R57F07GAL4)<br /> Did the authors check the expression profile of the R57F07 line that they use to probe "all basins"? The expression profile published previously (Ohyama et al, 2015, extended data) shows one basin neuron (identified as basin-4 ) and some neurons in the brain lobes. Also, the split GAL4 that labels Basin-4 (SS00740) is the intersection between R72F11 and R57F07 neurons. Thus the R57F07 likely labels Basin-4 and if that is the case the data in Figure 2 9 and supplement) and Figure 3 related to this driver line, should be annotated as Basin-4, and the results and their interpretation modified to take into account the different phenotypes for all basins and Basin-4 neurons

Page 19 l. 521-525 I am confused by these sentences as the authors claim that Basin-4 showed reduced Calcium responses upon repetitive activation of CDIII md neurons but then they say they exhibit sensitization. Looking at the plots in FIG 3 F-I the Basin-4 responses upon repeated activation seem indeed to decrease on the second repetition compared to the first. What is the sensitization the authors refer to?

On Page 47-In this section of the discussion, the authors emit an interesting hypothesis that the Basin-1 neuron could modulate the gain of behavioral responses. While this is an interesting idea, I wonder what would be the explanation for the finding that co-activation of Cho and MDIII does not facilitate cold nociceptive responses. Would activation of Basin-1 facilitate the cold response in different contexts (in addition to CH0-mediated stimuli?

Page 48 Thus the implication of the inhibitory network in cold processing should be better contextualized

The authors explain the difference in the lower basin-2 Ca- response to Cold/ mdIII activation (compared to Basin-4) despite stronger connectivity, due a stronger inputs from inhibitory neurons to Basin-2 (compared to Basin-4). The previously described inhibitory neurons that synapse onto Basin-2 receive rather a small fraction of inputs from the class III sensory neurons. The differences in response to cold could be potentially assigned to the activation of the inhibitory neurons by the cold-sensing cho- neurons. However, that cannot explain the differences in responses induced by class III neurons. Do the authors refer to additional inhibitory neurons that would receive significant input from MdIII?

Alternative explanations could exist for this difference in activation: electrical synapses from mdII I onto Basin-4, and by stronger inputs from mdIV (compared to Basin-2 in the case of responses to Cold stimulus (Cold induces responses in md IV sensory neurons). Different subtypes of CD III may differentially respond to cold and the cold-sensing ones could synapse preferentially on basin-4 etc.

5) A00c<br /> Page 26 Figure 4F-I line While Goro may not be involved in cold nociception the A00c (and A05q) seems to be.<br /> A00c could convey information to other neurons other than Goro and thus be part of a pathway for cold-induced CT.

6) Page 31 766-768 the conclusion that "premotor function is required for and can facilitate cold nociception" seems odd to stress as one would assume that some premotor neurons would be involved in controlling the behavioral responses to a stimulus. It would be more pertinent in the summary to specify which premotor neurons are involved and what is their function

7) There are several Split GAL4 used in the study (with transgenes inserted in attP40 et attP2 site). A recent study points to a mutation related toattP40 that can have an effect on muscle function: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9750024/. The controls used in behavioral experiments do not contain the attP40 site. It would be important to check a control genotype bearing an attP40 site and characterize the different parameters of the CT behavior to cold and take this into account in interpreting the results of the experiments using the Split-GAL4 lines

Reviewer #2 (Public Review):

Summary:

This paper nicely introduces WormPsyQi, an imaging analysis pipeline that effectively quantifies synaptically localized fluorescent signals in C. elegans through high-throughput automation. This toolkit is particularly valuable for the analysis of densely packed regions in 3D space, such as the nerve ring. The authors applied WormPsyQi to various aspects, including the examination of sexually dimorphic synaptic connectivity, presynaptic markers in eight head neurons, five GRASP reporters, electrical synapses, the enteric nervous system, and developmental synapse comparisons. Furthermore, they validated WormPsyQi's accuracy by comparing its results to manual analysis.

Strengths:

Overall, the experiments are well done, and their toolkit demonstrates significant potential and offers a valuable resource to the C. elegans community. This will expand the range of possibilities for studying synapses in the central nervous system in C. elegans.

Weaknesses:

1. The authors effectively validated sexually dimorphic synaptic connectivity by comparing the synapse puncta numbers of PHB>AVA, PHA>AVG, PHB>AVG, and ADL>AVA. However, these differences appear to be quite robust. Knowing how well WormPsyQi can detect more subtle changes at the synapses, such as 10-20% changes in puncta number and fluorescence intensity, will require further study.

2. The authors mentioned that having a cytoplasmic reporter in the background of the synaptic reporter enhanced performance. However, comparative results with and without cytoplasmic reporters, particularly for scenarios involving dim signals or densely distributed signals, are not provided, making it difficult to rigorously assess the importance of this step.

3. In some cases, the authors note discrepancies between WormPsyQi and human quantification. While they provide some potential explanations for these, the areas of discrepancy are not always highlighted in the images. This may make it difficult for users to know which types of signals are or are not well-suited for analysis by WormPsyQi.

Reviewer #2 (Public Review):

Summary:<br /> During C. elegans development, embryos undergo elongation of their body axis in the absence of cell proliferation or growth. This process relies in an essential way on periodic contractions of two pairs of muscles that extend along the embryo's main axis. How contraction can lead to extension along the same direction is unknown.

To address this question, the authors use a continuum description of a multicomponent elastic solid. The various components are the interior of the animal, the muscles, and the epidermis. The different components form separate compartments and are described as hyperelastic solids with different shear moduli. For simplicity, a cylindrical geometry is adopted. The authors consider first the early elongation phase, which is driven by contraction of the epidermis, and then late elongation, where contraction of the muscles injects elastic energy into the system, which is then released by elongation. The authors get elongation that can be successfully fitted to the elongation dynamics of wild-type worms and two mutant strains.

Strengths:<br /> The work proposes a physical mechanism underlying a puzzling biological phenomenon. The framework developed by the authors could be used to explain phenomena in other organisms and could be exploited in the design of soft robots.

Weaknesses:<br /> 1) This reviewer considers that the quality of the writing is poor. Because of this the main result of this work, how elongation is achieved by contraction, remains unclear to me. In the opinion of this reviewer, the work is not accessible to a biologist. This is a real pity because the findings are potentially of great interest to developmental biologists and engineers alike.

2) The authors assume that the embryo is elastic throughout all stages of development. Is this assumption appropriate? In my opinion, the authors need to critically discuss this assumption and provide justification. Would this still be true for the adult? If so could the adult relax back to the state prior to elongation? The embryo should be able to do that, if the contractility of the epidermis were sufficiently reduced, right?

3) The authors impose strains rather than stress. Since they want to understand the final deformation, I find this surprising. Maybe imposing strain or stress is equivalent, but then you should discuss this.

4) Does your mechanism need 4 muscle strands or would 2 be sufficient?

5) It is sometimes hard to understand, whether the authors are talking about the model or the worm.

Reviewer #2 (Public Review):

This paper by Lucas et al follows on from earlier work by the same group. They use high-resolution 2D template matching (2DTM) to find particles of a given target structure in 2D cryo-EM images, either of in vitro single-particle samples or of more complicated samples, such as FIB-milled cells (which would otherwise perhaps be used for 3D electron tomography). One major concern for high-resolution template matching has been the amount of model bias that gets introduced into a reconstruction that is calculated straight from the orientations and positions identified by the projection matching algorithm. This paper assesses the amount of model bias that gets introduced in high-resolution features of such maps.

For a high-signal-to-noise in vitro single-particle cryo-EM data set, the authors show that their approach does not yield much model bias. This is probably not very surprising, as their method is basically a low false-positive particle picker, which works very well on such data. Still, I guess that is the whole point of it, and it is good to see that they can reconstruct density for a small-molecule compound that was not present in the original template.

For FIB-milled lamella of yeast cells with stalled ribosomes, the SNR is much lower and the dangers of model bias will be higher. This is also evidenced by the observation that further refinement of initial 2DTM identified orientations and positions worsens the map. This is obviously a more relevant SNR regime to assess their method. Still, they show convincing density for the GHX compound that was not present in the template, but was there in the reconstruction from the identified particles.

Quantification of the amount of model bias is then performed using omit maps, where every 20th residue in removed from the template and corresponding reconstructions are compared (for those residues) with the full-template reconstructions. As expected, model bias increases with lower thresholds for the picking. Some model bias (Omega=8%) remains even for very high thresholds. The authors state this may be due to overfitting of noise when template-matching true particles, instead of introducing false positive. Probably, that still represents some sort of problem. Especially because the authors then go on to show that their expectations of number of false positives do not always match the correct number of false positive, probably due to inaccuracies in the noise model for more complicated images, this may warrant further in-depth discussion in a revised manuscript.

Overall, I think this paper is well written and it has made me think differently (again) about the 2DTM technique and its usefulness in various applications, as outlined in the Discussion. Therefore, it will be a constructive contribution to the field.

After the first round of review, the authors addressed most points raised in a satisfying manner, which has led to a further (relatively minor) improvement of the manuscript.

Reviewer #2 (Public Review):

Summary:<br /> ECM components are prominent constituents of the pericellular environment of CNS cells and form complex and dynamic interactomes in the pericellular spaces. Based on bioinformatic analysis, more than 300 genes have been attributed to the so-called matrisome, many of which are detectable in the CNS. Yet, not much is known about their functions while increasing evidence suggests important contributions to developmental processes, neural plasticity, and inhibition of regeneration in the CNS. In this respect, the present work offers new insights and adds interesting aspects to the facets of ECM contributions to neural development. This is even more relevant in view of the fact that neurocan has recently been identified as a potential risk gene for neuropsychiatric diseases. Because ECM components occur in the interstitial space and are linked in interactomes their study is very difficult. A strength of the manuscript is that the authors used several approaches to shed light on ECM function, including proteome studies, the generation of knockout mouse lines, and the analysis of in vivo labeled neural progenitors. This multi-perspective approach permitted to reveal hitherto unknown properties of the ECM and highlighted its importance for the overall organization of the CNS.

Strengths:<br /> Systematic analysis of the ternary complex between neurone, TNC, and hyaluronic acid; establishment of KO mouse lines to study the function of the complex, use of in utero electroporation to investigate the impact on neuronal migration;

Weaknesses:<br /> The analysis is focused on neuronal progenitors, however, the potential impact of the molecules of interest, in particular, their removal on differentiation and /or survival of neural stem/progenitor cells is not addressed. The potential receptors involved are not considered. It also seems that rather the passage to the outer areas of the forming cortex is compromised, which is not the same as the migration process. The movement of the cells is not included in the analysis.

Reviewer #2 (Public Review):

Brunner et al. present a new and promising application of functional ultrasound (fUS) imaging to follow the evolution of perfusion and haemodynamics upon thrombotic stroke in awake rats. The authors leveraged a chemically induced occlusion of the rat Medial Cerebral Artery (MCA) with ferric chloride in awake rats, while imaging with fUS cerebral perfusion with high spatial and temporal resolution (100µm x 110µm x 300µm x 0.8s). The authors also measured evoked haemodynamic responses at different timepoints following whisker stimulation.

As the fUS setup of the authors is limited to 2D imaging, Brunner and colleagues focused on a single coronal slice where they identified the primary Somatosensory Barrel Field of the Cortex (S1BF), directly perfused by the MCA and relay nuclei of the Thalamus: the Posterior (Po) and the Ventroposterior Medial (VPM) nuclei of the Thalamus. All these regions are involved in the sensory processing of whisker stimulation. By investigating these regions the authors present the hyper-acute effect of the stroke with these main results:

- MCA occlusion results in a fast and important loss of perfusion in the ipsilesional cortex.<br /> - Thrombolysis is followed by Spreading Depolarisation measured in the Retrosplenial cortex.<br /> - Stroke-induced hypo-perfusion is associated with a significant drop in ipsilesional cortical response to whisker stimulation, and a milder one in ipsilesional subcortical relays.<br /> - Contralesional hemisphere is almost not affected by stroke with the exception of the cortex which presents a mildly reduced response to the stimulation.

In addition, the authors demonstrate that their protocol allows to follow up stroke evolution up to five days postinduction. They further show that fUS can estimate the size of the infarcted volume with brilliance mode (Bmode), confirming the presence of the identified lesional tissue with post-mortem cresyl violet staining.

Upon measuring functional response to whisker stimulation 5 days after stroke induction, the authors report that:

- The ipsilesional cortex presents no response to the stimulation<br /> - The ipsilesional thalamic relays are less activated than hyper acutely

These observations mainly validate a new method to chronically image the longitudinal sequelae of stroke in awake animals. However, the potentially more intriguing results the authors describe in terms of functional reorganization of functional activity following stroke will require additional data to be validated. While highly preliminary, the research model proposed by the author (where the loss of the infarcted cortex induces reduces activity in connected regions, whether by cortico-thalamic or cortico-cortical loss of excitatory drive), is interesting. This hypothesis would require a greatly expanded, sufficiently powered study to be validated (or disproven)."

Reviewer #2 (Public Review):

Summary:<br /> In this study, the authors investigated the role of a medullary region, named Postinspiratory Complex (PiCo), in the mediation of swallow/laryngeal behaviours, their coordination with breathing, and the possible impact on the reflex exerted by chronic intermittent hypoxia (CIH). This region is characterized by the presence of glutamatergic/cholinergic interneurons. Thus, experiments have been performed in single allelic and intersectional allelic recombinase transgenic mice to specifically excite cholinergic/glutamatergic neurons using optogenetic techniques, while recording from relevant muscles involved in swallowing and laryngeal activation. The data indicate that in anaesthetized transgenic mice exposed to CIH, the optogenetic activation of PiCo neurons triggers swallow activity characterized by variable motor patterns. In addition, these animals show an increased probability of triggering a swallow when stimulation is applied during the first part of the respiratory cycle.

They conclude that the PiCo region may be involved in the occurrence of swallow and other laryngeal behaviours. These data interestingly improve the ongoing discussion on neural pathways involved in swallow-breathing coordination, with specific attention to factors leading to disruption that may contribute to dysphagia under some pathological conditions.

The Authors' conclusions are partially justified by their data. However, it should be acknowledged that the impact of the study is to a certain extent limited by the lack of knowledge on the source of excitatory inputs to PiCo during swallowing under physiological conditions, i.e. during water-evoked swallowing. Also the connectivity between this region and the swallowing CPG, a structure not well defined, or other brain regions involved in the reflex is not known.

Strengths:<br /> Major strengths of the manuscript:

- The methodological approach is refined and well-suited for the experimental question. The in vivo mouse preparation developed for this study takes advantage of selective optogenetic stimulation of specific cell types with the simultaneous EMG recordings from upper airway muscles involved in respiration and swallowing to assess their motor patterns. The animal model and the chronic intermittent hypoxia protocol have already been published in previous papers (Huff et al. 2022, 2023).

- The choice of the topic. Swallow disruption may contribute to the dysphagia under some pathological conditions, such as obstructive sleep apnea. Investigations aimed at exploring and clarifying neural structures involved in this behaviour as well as the connectivity underpinning muscle coordination are needed.

- This study fits in with previous works. This work is a logical extension of previous studies from this group on swallowing-breathing coordination with further advances using a mouse model for obstructive sleep apnea.

Weaknesses:<br /> Major weaknesses of the manuscript:

- The Authors should be more cautious in concluding that the PiCo is critical for the generation of swallowing itself. It remains to demonstrate that PiCo is necessary for swallowing and laryngeal function in a more physiological situation, i.e. swallow of a bolus of water or food. It should be interesting to investigate the effects of silencing PiCo cholinergic/glutamatergic neurons on normal swallowing. In this perspective, the title should be slightly modified to avoid "swallow pattern generation" (e.g. Chronic Intermittent Hypoxia reveals the role of the Postinspiratory Complex in the mediation of normal swallow production).

- The duration of swallows evoked by optogenetic stimulation of PiCo is considerably shorter in comparison with the duration of swallows evoked by a physiological stimulus (water). This makes it hard to compare the timing and the pattern of motor response in CIH-exposed mice. In Figure 1, the trace time scale should be the same for water-triggered and PiCo-triggered swallows. In addition, it is not clear if exposure to CIH alters the ongoing respiratory activity. Is the respiratory rhythm altered by hypoxia? If a disturbed or irregular pattern of breathing is already present in CIH-exposed mice, could this alteration interfere with the swallowing behaviour?

Reviewer #2 (Public Review):

In this paper, the authors presented a compelling rationale for investigating the role of UBCs in prolonging and diversifying signals. Based on the two types of UBCs known as ON and OFF UBC subtypes, they have highlighted the existing gaps in understanding UBCs connectivity and the need to investigate whether UBCs target UBCs of the same subtype, different subtypes, or both. The importance of this knowledge is for understanding how sensory signals are extended and diversified in the granule cell layer.

The authors designed very interesting approaches to study UBCs connectivity by utilizing transgenic mice expressing GFP and RFP in UBCs, Brainbow approach, immunohistochemical and electrophysiological analysis, and computational models to understand how the feed-forward circuits of interconnected UBCs transform their inputs.

This study provided evidence for the existence of distinct ON and OFF UBC subtypes based on their electrophysiological properties, anatomical characteristics, and expression patterns of mGluR1 and calretinin in the cerebellum. The findings support the classification of GRP UBCs as ON UBCs and P079 UBCs as OFF UBCs and suggest the presence of synaptic connections between the ON and OFF UBC subtypes. In addition, they found that GRP and P079 UBCs form parallel and convergent pathways and have different membrane capacitance and excitability. Furthermore, they showed that UBCs of the same subtype provide input to one another and modify the input to granule cells, which could provide a circuit mechanism to diversify and extend the pattern of spiking produced by mossy fiber input. Accordingly, they suggested that these transformations could provide a circuit mechanism for maintaining a sensory representation of movement for seconds.

Overall, the article is well written in a sound detailed format, very interesting with excellent discovery and suggested model.

I believe the authors have provided appropriate responses and have consequently revised the manuscript in a convincing manner. Although I am not an expert in physiology, I find the explanations and clarifications to be acceptable.

Reviewer #2 (Public Review):

Summary:<br /> The authors use previously characterised FRET methods to measure distances between intracellular segments of ASIC and with the membrane. The distances are measured across different conditions and at multiple positions in a very complete study. The picture that emerges is that the N- and C-termini do not associate.

Strengths:<br /> Good controls, good range of measurements, advanced, well-chosen and carefully performed FRET measurements. The paper is a technical triumph. Particularly, given the weak fluorescence of ANAP, the extent of measurements and the combination with TETAC is noteworthy.

The distance measurements are largely coherent and favour the interpretation that the N and C terminus are not close together as previously claimed.

Weaknesses:<br /> One difficulty, which admittedly is hard to address, is that we do not have a positive control for what binding of something to either N- or C-terminus would look like (either in FRET or otherwise).

One limitation is unroofing. The concept of interaction with intracellular domains is being examined. But the authors use unroofing to measure the positions, fully disrupting the cytoplasm. Thus it is not excluded that the unroofing disrupts that interaction. But this limitation is discussed adequately in the text.

Reviewer #2 (Public Review):

The proper expression and organization of CaV channels at the presynaptic release sites are subject to coordinative and redundant control of many active zone-specific molecules including RIM-BPs. Previous studies have demonstrated that ablation of RIM-BPs in various mammalian synapses causes significant impairment of synaptic transmission, either by reducing CaV expression or decoupling CaV from synaptic vesicles. The mechanisms remain unknown.

In the manuscript, Sakaba and colleagues aimed to examine the specific role of RIM-BP2 at the hippocampal mossy fiber-CA3 pyramidal cell synapse, which is well-characterized by low initial release probability and strong facilitation during repetitive stimulation. By directly recording Ca2+ currents and capacitance jumps from the MF boutons, which is very challenging but feasible, they showed that depolarization-evoked Ca2+ influx was reduced significantly (~39%) by KO of RIM-BP2, but no impacts on Ca-induced exocytosis and RRP (measured by capacitance change). They used STED microscopy to image the spatial distribution of the CaV2.1 cluster but found no change in the cluster number with a slight decrease in cluster intensity (~20%). They concluded that RIM-BP2 functions in tonic synapses by reducing CaV expression and thus differentially from phasic synapses by decoupling CaV-SV.

In general, they provide solid data showing that RIM-BP2 KO reduces Ca influx at MF-CA3 synapse, but the phenotype is not new as Moser and colleagues have also used presynaptic recording and capacitance measurement and shown that RIM-BP2 KO reduces Ca2+ influx at hair cell active zone (Krinner et al., 2017), although at different synapse model expressing CaV1.3 instead of CaV2.1. Further, the concept that RIM-BP2 plays diverse functions in transmitter release at different central synapses has also been proposed with solid evidence (Brockmann et al., 2019).

Reviewer #2 (Public Review):

This paper addresses the empirical demonstration of "distractor effects" in multi-attribute decision-making. It continues a debate in the literature on the presence (or not) of these effects, which domains they arise in, and their heterogeneity across subjects. The domain of the study is a particular type of multi-attribute decision-making: choices over risky lotteries. The paper reports a re-analysis of lottery data from multiple experiments run previously by the authors and other laboratories involved in the debate.

Methodologically, the analysis assumes a number of simple forms for how attributes are aggregated (adaptively, multiplicatively, or both) and then applies a "reduced form" logistic regression to the choices with a number of interaction terms intended to control for various features of the choice set. One of these interactions, modulated by ternary/binary treatment, is interpreted as a "distractor effect."

The claimed contribution of the re-analysis is to demonstrate a correlation in the strength/sign of this treatment effect with another estimated parameter: the relative mixture of additive/multiplicative preferences.

Major Issues

1) How to Interpret GLM 1 and 2

This paper, and others before it, have used a binary logistic regression with a number of interaction terms to attempt to control for various features of the choice set and how they influence choice. It is important to recognize that this modelling approach is not derived from a theoretical claim about the form of the computational model that guides decision-making in this task, nor an explicit test for a distractor effect. This can be seen most clearly in the equations after line 321 and its corresponding log-likelihood after 354, which contain no parameter or test for "distractor effects". Rather the computational model assumes a binary choice probability and then shoehorns the test for distractor effects via a binary/ternary treatment interaction in a separate regression (GLM 1 and 2). This approach has already led to multiple misinterpretations in the literature (see Cao & Tsetsos, 2022; Webb et al., 2020). One of these misinterpretations occurred in the datasets the authors studied, in which the lottery stimuli contained a confound with the interaction that Chau et al., (2014) were interpreting as a distractor effect (GLM 1). Cao & Tsetsos (2022) demonstrated that the interaction was significant in binary choice data from the study, therefore it can not be caused by a third alternative. This paper attempts to address this issue with a further interaction with the binary/ternary treatment (GLM 2). Therefore the difference in the interaction across the two conditions is claimed to now be the distractor effect. The validity of this claim brings us to what exactly is meant by a "distractor effect."

The paper begins by noting that "Rationally, choices ought to be unaffected by distractors" (line 33). This is not true. There are many normative models that allow for the value of alternatives (even low-valued "distractors") to influence choices, including a simple random utility model. Since Luce (1959), it has been known that the axiom of "Independence of Irrelevant Alternatives" (that the probability ratio between any two alternatives does not depend on a third) is an extremely strong axiom, and only a sufficiency axiom for a random utility representation (Block and Marschak, 1959). It is not a necessary condition of a utility representation, and if this is our definition of rational (which is highly debatable), not necessary for it either. Countless empirical studies have demonstrated that IIA is falsified, and a large number of models can address it, including a simple random utility model with independent normal errors (i.e. a multivariate Probit model). In fact, it is only the multinomial Logit model that imposes IIA. It is also why so much attention is paid to the asymmetric dominance effect, which is a violation of a necessary condition for random utility (the Regularity axiom).

So what do the authors even mean by a "distractor effect." It is true that the form of IIA violations (i.e. their path through the probability simplex as the low-option varies) tells us something about the computational model underlying choice (after all, different models will predict different patterns). However we do not know how the interaction terms in the binary logit regression relate to the pattern of the violations because there is no formal theory that relates them. Any test for relative value coding is a joint test of the computational model and the form of the stochastic component (Webb et al, 2020). These interaction terms may simply be picking up substitution patterns that can be easily reconciled with some form of random utility. While we can not check all forms of random utility in these datasets (because the class of such models is large), this paper doesn't even rule any of these models out.

2) How to Interpret the Composite (Mixture) model?

On the other side of the correlation are the results from the mixture model for how decision-makers aggregate attributes. The authors report that most subjects are best represented by a mixture of additive and multiplicative aggregation models. The authors justify this with the proposal that these values are computed in different brain regions and then aggregated (which is reasonable, though raises the question of "where" if not the mPFC). However, an equally reasonable interpretation is that the improved fit of the mixture model simply reflects a misspecification of two extreme aggregation processes (additive and EV), so the log-likelihood is maximized at some point in between them.

One possibility is a model with utility curvature. How much of this result is just due to curvature in valuation? There are many reasonable theories for why we should expect curvature in utility for human subjects (for example, limited perception: Robson, 2001, Khaw, Li Woodford, 2019; Netzer et al., 2022) and of course many empirical demonstrations of risk aversion for small stakes lotteries. The mixture model, on the other hand, has parametric flexibility.

There is also a large literature on testing expected utility jointly with stochastic choice, and the impact of these assumptions on parameter interpretation (Loomes & Sugden, 1998; Apesteguia & Ballester, 2018; Webb, 2019). This relates back to the point above: the mixture may reflect the joint assumption of how choice departs from deterministic EV.

3) So then how should we interpret the correlation that the authors report?

On one side we have the impact of the binary/ternary treatment which demonstrates some impact of the low value alternative on a binary choice probability. This may reflect some deep flaws in existing theories of choice, or it may simply reflect some departure from purely deterministic expected value maximization that existing theories can address. We have no theory to connect it to, so we cannot tell. On the other side of the correlation, we have a mixture between additive and multiplicative preferences over risk. This result may reflect two distinct neural processes at work, or it may simply reflect a misspecification of the manner in which humans perceive and aggregate attributes of a lottery (or even just the stimuli in this experiment) by these two extreme candidates (additive vs. EV). Again, this would entail some departure from purely deterministic expected value maximization that existing theories can address.

It is entirely possible that the authors are reporting a result that points to the more exciting of these two possibilities. But it is also possible (and perhaps more likely) that the correlation is more mundane. The paper does not guide us to theories that predict such a correlation, nor reject any existing ones. In my opinion, we should be striving for theoretically-driven analyses of datasets, where the interpretation of results is clearer.

4) Finally, the results from these experiments might not have external validity for two reasons. First, the normative criterion for multi-attribute decision-making differs depending on whether the attributes are lotteries or not (i.e. multiplicative vs additive). Whether it does so for humans is a matter of debate. Therefore if the result is unique to lotteries, it might not be robust for multi-attribute choice more generally. The paper largely glosses over this difference and mixes literature from both domains. Second, the lottery information was presented visually and there is literature suggesting this form of presentation might differ from numerical attributes. Which is more ecologically valid is also a matter of debate.

Minor Issues:<br /> The definition of EV as a normative choice baseline is problematic. The analysis requires that EV is the normative choice model (this is why the HV-LV gap is analyzed and the distractor effect defined in relation to it). But if the binary/ternary interaction effect can be accounted for by curvature of a value function, this should also change the definition of which lottery is HV or LV for that subject!

References<br /> Apesteguia, J. & Ballester, M. Monotone stochastic choice models: The case of risk and time preferences. Journal of Political Economy (2018).

Block, H. D. & Marschak, J. Random Orderings and Stochastic Theories of Responses. Cowles Foundation Discussion Papers (1959).

Khaw, M. W., Li, Z. & Woodford, M. Cognitive Imprecision and Small-Stakes Risk Aversion. Rev. Econ. Stud. 88, 1979-2013 (2020).

Loomes, G. & Sugden, R. Testing Different Stochastic Specificationsof Risky Choice. Economica 65, 581-598 (1998).

Luce, R. D. Indvidual Choice Behaviour. (John Wiley and Sons, Inc., 1959).

Netzer, N., Robson, A. J., Steiner, J. & Kocourek, P. Endogenous Risk Attitudes. SSRN Electron. J. (2022) doi:10.2139/ssrn.4024773.

Robson, A. J. Why would nature give individuals utility functions? Journal of Political Economy 109, 900-914 (2001).

Webb, R. The (Neural) Dynamics of Stochastic Choice. Manage Sci 65, 230-255 (2019).

Reviewer #2 (Public Review):

Summary:<br /> In this study, Ghafari et al. explored the correlation between hemispheric asymmetry in the volume of various subcortical regions and lateralization of posterior alpha-band oscillations in a spatial attention task with varying cognitive demands. To this end, they combined structural MRI and task MEG to investigate the relationship between hemispheric differences in the volume of basal ganglia, thalamus, hippocampus, and amygdala and hemisphere-specific modulation of alpha-band power. The authors report that differences in the thalamus, caudate nucleus, and globus pallidus volume are linked to the attention-related changes in alpha band oscillations with differential correlations for different regions in different conditions of the design (depending on the salience of the distractor and/or the target).

Strengths:<br /> The manuscript contributes to filling an important gap in current research on attention allocation which commonly focuses exclusively on cortical structures. Because it is not possible to reliably measure subcortical activity with non-invasive electrophysiological methods, they correlate volumetric measurements of the relevant subcortical regions with cortical measurements of alpha band power. Specifically, they build on their own previous finding showing a correlation between hemispheric asymmetry of basal ganglia volumes and alpha lateralization by assessing a task without an explicit reward component. Furthermore, the authors use differences in saliency and perceptual load to disentangle the individual contributions of the subcortical regions.

Weaknesses:<br /> The theoretical bases of several aspects of the design and analyses remain unclear. Specifically, we missed statements in the introduction about why it is reasonable, from a theoretical perspective, to expect:<br /> (i) a link between volumetric measurements and task activity;<br /> (ii) a specific link with hemispheric asymmetry in subcortical structures (While focusing on hemispheric lateralization might circumvent the problem of differences in head size, it would be better to justify this focus theoretically, which requires for example a short review of evidence showing ipsilateral vs contralateral connections between the relevant subcortical and cortical structures);<br /> (iii) effects not only in basal ganglia and thalamus, but also hippocampus and amygdala (a justification of selection of all ROIs);<br /> (iv) effects that depend on distractor versus target salience (a rationale for the specific two-factor design is missing);<br /> (v) effects in the absence of reward (why it is important to show that the effect seen previously in a task with reward is seen also in a task without reward);<br /> (vi) effects on rapid frequency tagging.

Second, the results are not fully reported. The model space and the results from the model comparison are omitted. Behavioral data and rapid frequency tagging results are not shown. Without having access to the data or the results of the analyses, the reader cannot evaluate whether the null effect corresponds to the absence of evidence or (as claimed in the discussion) evidence of absence.

Third, it remains unclear whether the MMS is the best approach to analyzing effects as a function of target and distractor salience. To address the question of whether the effects of subcortical volumes on alpha lateralization vary with task demands (which we assume is the primary research question of interest, given the factorial design), we would like to evaluate some sort of omnibus interaction effect, e.g., by having target and distractor saliency interact with the subcortical volume factors to predict alpha lateralization. Without such analyses, the results are very hard to interpret. What are the implications of finding the differential effects of the different volumes for the different task conditions without directly assessing the effect of the task manipulation? Moreover, the report would benefit from a further breakdown of the effects into simple effects on unattended and attended alpha, to evaluate whether effects as a function of distractor (vs target) salience are indeed accompanied by effects on unattended (vs attended) alpha.

The fourth concern is that the discussion section is not quite ready to help the reader appreciate the implications of key aspects of the findings. What are the implications for our understanding of the roles of different subcortical structures in the various psychological component processes of spatial attention? Why does the volumetric asymmetry of different subcortical structures have diametrically opposite effects on alpha lateralization? Instead, the discussion section highlights that the different subcortical structures are connected in circuits: "Globus pallidus also has wide projections to the thalamus and can thereby impact the dorsal attentional networks by modulating prefrontal activities." If this is true, then why does the effect of the GP dissociate from that of the thalamus? Also, what is it about the current behavioural paradigm that makes the behavioral readout insensitive to variation in subcortical volume (or alpha lateralization?)?

Reviewer #2 (Public Review):

Richevaux et al investigate how anterior thalamic (AD) and retrosplenial (RSC) inputs are integrated by single presubicular (PrS) layer 3 neurons. They show that these two inputs converge onto single PrS layer 3 principal cells. By performing dual-wavelength photostimulation of these two inputs in horizontal slices, the authors show that in most layer 3 cells, these inputs summate supra-linearly. They extend the experiments by focusing on putative layer 4 PrS neurons, and show that they do not receive direct anterior thalamic nor retrosplenial inputs; rather, they are (indirectly) driven to burst firing in response to strong activation of the PrS network.

This is a valuable study, that investigates an important question - how visual landmark information (possibly mediated by retrosplenial inputs) converges and integrates with HD information (conveyed by the AD nucleus of the thalamus) within PrS circuitry. The data indicate that near-coincident activation of retrosplenial and thalamic inputs leads to non-linear integration in target layer 3 neurons, thereby offering a potential biological basis for landmark + HD binding.

The main limitations relate to the anatomical annotation of 'putative' PrS L4 neurons, and to the presentation of retrosplenial/thalamic input modularity. Specifically, more evidence should be provided to convincingly demonstrate that the 'putative L4 neurons' of the PrS are not distal subicular neurons (as the authors' anatomy and physiology experiments seem to indicate). The modularity of thalamic and retrosplenial inputs could be better clarified in relation to the known PrS modularity.

Reviewer #2 (Public Review):

Summary:<br /> The authors have developed a comprehensive set of tools to describe dynamics within a single time-series or across multiple time-series. The motivation is to better understand interacting networks within the human brain. The time-series used here are from direct estimates of the brain's electrical activity; however, the tools have been used with other metrics of brain function and would be applicable to many other fields.

Strengths:<br /> The methods described are principled, and based on generative probabilistic models.<br /> This makes them compact descriptors of the complex time-frequency data.<br /> Few initial assumptions are necessary in order to reveal this compact description.<br /> The methods are well described and demonstrated within multiple peer-reviewed articles.<br /> This toolbox will be a great asset to the brain imaging community.

Weaknesses:<br /> The only question I had was how to objectively/quantitatively compare different network models. This is possibly easily addressed by the authors.

Reviewer #2 (Public Review):

Summary:<br /> Interest in using nanobodies for therapeutic interventions in infectious diseases is growing due to their ability to bind hidden or cryptic epitopes that are inaccessible to conventional immunoglobulins. In the present study, the authors were posed to characterize nanobodies derived from the library produced earlier with the Wuhan strain of SARS-CoV-2, map their epitopes on SARS-CoV-2 spike protein, and demonstrate that some nanobodies retain binding and even neutralization against antigenically distant Variants of Concern (VOCs) that are currently circulating.

Strengths:<br /> The authors demonstrate that some nanobodies - despite being obtained against the ancestral virus strain - retain high affinity binding to antigenically distant SARS-CoV-2 strains. This is despite the majority of the repertoire losing binding. Although limited to only two nanobody combinations, the demonstration of synergy in virus neutralization between nanobodies targeting different epitopes is compelling.

Weaknesses:<br /> The authors imply that nanobodies that retain binding/neutralization of early Omicron sublineages will be active against currently circulating and future virus strains. Unfortunately, no reasoning for such a conclusion nor data supporting this prediction are provided.

Reviewer #2 (Public Review):

Summary:<br /> Dr. Sheyn and colleagues report the step-wise induction of syndetome-like cells from human induced pluripotent stem cells (iPSCs), following a previously published protocol which they adjusted. The progression of the cells through each stage, i.e. presomitic mesoderm (PSM), somitic mesoderm (SM), sclerotome (SCL), and syndetome (SYN)) is characterized using FACS, RT-qPCR and immunofluorescence staining (IF). The authors also performed single-cell RNA sequencing (scRNAseq) analysis of their step-wise induced cells and identified signaling pathways which are potentially involved in and possibly necessary for syndetome induction. They then optimized their protocol by simultaneous inhibition of BMP and Wnt signaling pathways, which led to an increase in syndetome induction while inhibiting off-target differentiation into neural lineages.

Strengths:<br /> The authors conducted scRNAseq analysis of each step of their protocol from iPSCs to syndetome-like cells and employed pathway analysis to uncover further insights into somitic mesoderm (SM) and syndetome (SYN) differentiation. They found that BMP inhibition, in conjunction with the inhibition of WNT signaling, plays a role in driving syndetome differentiation. Analyzing their scRNAseq results, they could improve the syndetome induction efficiency of their protocol from 47.6% to 67%-78% while off-target differentiation into neural lineages could be reduced.

Weaknesses:<br /> The authors demonstrated the efficiency of syndetome induction solely by scRNA-seq data analysis before and after pathway inhibition, without using e.g. FACS analysis or immunofluorescence (IF)-staining based assessment. A functional assessment and validation of the induced cells is also completely missing.

The following points are not clear and need to be addressed by the authors:<br /> 1. Notably, in Figure 1D, certain PSM markers (TBXT, MSGN1, WNT3A) show higher expression on day 3. If the authors initiate SM induction on day 3 instead of day 4, could this potentially enhance the efficiency of syndetome-like cell induction?

2. In the third paragraph of the result section the authors note, "Interestingly, SCX, a prominent tenogenic transcription factor, was significantly downregulated at the SCL stage compared to iPSC, but upregulated during the differentiation from SCL to SYN." Despite this increase, the expression level of SCX in SYN remains lower than that in iPSCs in Fig.1G and Fig.3C. Can the authors provide an explanation for this? Can the authors provide IF data using iPSCs and compare it with in vitro-induced SYN cells? Can the authors provide e.g. additional scRNAseq data which could support this statement?

3. In the fourth paragraph of the result section the authors state, "SM markers (MEOX1, PAX3) and SCL markers (PAX1, PAX9, NKX3.2, SOX9) were upregulated in a stepwise manner." However, the data for MEOX1 and NKX3.2 seems to be missing from Figure 3B-C. The authors should provide this data and/or additional support for their claim.

4. In Figures 2B and 2E, the background of the red channel seems extremely high. Are there better images available, particularly for MEOX1? Given the expected high expression of MEOX1 in SM cells, the authors should observe a strong signal in the nucleus of the stained somitic mesoderm-like cells, but that is not the case in the shown figure. The authors should provide separate channel images instead of merged ones for clarity. The antibody which the authors used might not be specific. Can the authors provide images using an antibody which has been shown to work previously e.g. antibody by ATLAS (Cat#: HPA045214)?

5. In Fig. 2C and Supplementary Fig. 1, the authors present data from immunofluorescence (IF) staining and FACS analysis using a DLL1 antibody. While FACS analysis indicates an efficiency of 96.2% for DLL1+ cells, this was not clearly observed in their IF data. How can the authors explain this discrepancy? Could the authors quantify their IF data and compare it with the corresponding FACS data?

6. In Fig. 2G, PAX9 is expected to be expressed in the nucleus, but the shown IF staining does not appear to be localized to the nucleus. Could the authors provide improved or alternative images to clarify this? The authors should use antibodies shown to work with high specificity as already reported by other groups.

7. Why did the authors choose to display day 10 data for SYN induction in Fig. 4A? Could they provide information about the endpoint of their culture at day 21?

8. In Supplementary Fig. 5, the authors depicted the expression level of SCX, a SYN marker, which peaked at day 14 and then decreased. By day 21, it reached a level comparable to that of iPSCs. Given this observation, could the authors provide a characterization of the cells at day 21 during SYN induction using IF? What was the rationale behind selecting 21 days for SYN induction? The authors also need to show 'n numbers'; how many times were the experiments repeated independently (independent experiments)?<br /> 9. Overall the shown immunofluorescence (IF) data does not appear convincing. Could the authors please provide clearer images, including separate channel images, a bright field image, and magnified views of each staining?

10. As stated by the authors in the manuscript, another research group performed FACS analysis to assess the efficiency of syndetome induction using SCX antibody, and/or quantification of immunofluorescence (IF) with SCX, MKX, COL1A1, or COL2A1 antibodies. Could the authors conduct a comparative analysis of syndetome induction efficiency both before and after protocol optimization, utilizing FACS analysis in conjunction with an SCX reporter line or antibody staining, e.g. quantifying induction efficiency via immunofluorescence (IF) staining with syndetome-specific marker genes?

11. To enhance the paper's significance, the authors should conduct functional validation experiments and proper assessment of their induced syndetome-like cells. They could perform e.g. xeno-transplantation experiments with syndetome cells into SCID-mice or injury models. They could also assess whether the in vitro induced cells could be applied for in vitro tendon/ligament formation.

12. The authors should also compare their scRNA-seq data with actual human embryo data sets, something which could be done given the recent increase in available human embryo scRNA-seq data sets.

Reviewer #2 (Public Review):

In the presented manuscript, the authors first use structured microfluidic devices with gliding filamentous cyanobacteria inside in combination with micropipette force measurements to measure the bending rigidity of the filaments.

Next, they use triangular structures to trap the bacteria with the front against an obstacle. Depending on the length and rigidity, the filaments buckle under the propulsive force of the cells. The authors use theoretical expressions for the buckling threshold to infer propulsive force, given the measured length and stiffnesses. They find nearly identical values for both species, 𝑓 ∼ (1.0 {plus minus} 0.6) nN∕µm, nearly independent of the velocity.

Finally, they measure the shape of the filament dynamically to infer friction coefficients via Kirchhoff theory. This last part seems a bit inconsistent with the previous inference of propulsive force. Before, they assumed the same propulsive force for all bacteria and showed only a very weak correlation between buckling and propulsive velocity. In this section, they report a strong correlation with velocity, and report propulsive forces that vary over two orders of magnitude. I might be misunderstanding something, but I think this discrepancy should have been discussed or explained.

From a theoretical perspective, not many new results are presented. The authors repeat the well-known calculation for filaments buckling under propulsive load and arrive at the literature result of buckling when the dimensionless number (f L^3/B) is larger than 30.6 as previously derived by Sekimoto et al in 1995 [1] (see [2] for a clamped boundary condition and simulations). Other theoretical predictions for pushed semi-flexible filaments [1-4] are not discussed or compared with the experiments.<br /> Finally, the Authors use molecular dynamics type simulations similar to [2-4] to reproduce the buckling dynamics from the experiments. Unfortunately, no systematic comparison is performed.

[1] K. Sekimoto, N. Mori, K. Tawada and Y. Toyoshima, Phys. Rev. Lett., 1995, 75, 172-175<br /> [2] R. Chelakkot, A. Gopinath, L. Mahadevan and M. F. Hagan, J. R. Soc., Interface, 2014, 11, 20130884.<br /> [3] R. E. Isele-Holder, J. Elgeti and G. Gompper, Soft Matter, 2015, 11, 7181-7190.<br /> [4] R. E. Isele-Holder, J. Jager, G. Saggiorato, J. Elgeti and G. Gompper, Soft Matter, 2016, 12, 8495

Reviewer #2 (Public Review):

Here, the authors use quantitative behavioral analyses to describe in unprecedented detail the various behavioral choices animals make when encountering the lawn edge. They report that leaving the lawn is a rare outcome compared to other choices such as pausing or reversing back into the lawn. It occurs predominantly out of the roaming state and has a characteristic preceding fast crawling profile. They developed a refined analysis method, the result of which suggests that the arousal state of animals on food can be described by a 4-state behavior (as opposed to the 2-state roaming - dwelling classification); leaving the lawn occurs predominantly from "state 3", which corresponds to the highest level of arousal during roaming. They further show that various manipulations, such as optogenetic inhibition of feeding, stimulation of RIB neurons, or mutations of neuromodulator pathways, all of which have previously been reported to affect crawling speed and/or roaming/dwelling, maintain the coupling between roaming states and leaving, suggesting a dedicated mechanism for coupling leaving to the roaming state. Finally, they use genetics to implicate chemosensory neurons as neuronal circuit elements mediating this coupling.

How arousal states affect decision making is an active area of neuroscience research; therefore, the current manuscript will impact the field beyond the small community of C. elegans researchers. Also, in the past, roaming/dwelling and leaving have been treated as independent behaviors; the current manuscript is very intriguing, demonstrating both the interconnectedness of different behavioral programs and the importance of the animal's behavioral context for specific decisions.

In this current revision and, the authors have made a good effort at addressing most of my previous comments, especially to clarify the sample sizes and how independent assays were performed.

My major concern, however, remains: when leaving animals apparently accelerate their locomotion speed starting about 30s prior to the leaving events (Fig. 2A, D, G). By the authors' analysis, these episodes are assigned to roaming or 'state 3'. Note, that even within these states the behavior seems to be distinctively faster than baseline roaming- or 'state 3'- speed (Fig. 2A, D, G). If leaving is indeed preceded by a stereotypic acceleration phase, this phase should be assigned to the leaving event, not to roaming or 'state 3'. If this is done, the distribution of roaming dwelling states prior to acceleration-leaving could get closer to 50/50 (draw a vertical line at 30s onto Figure 2C, and then count the fraction of prior roaming-dwelling states). I would conclude that the probability of leaving is also high out of the dwelling-state. This interpretation challenges the major conclusion of the study, which is that the roaming behavioral state is a major determinant of the leaving decision. The analysis in Figure 2 S1E shows interesting results hinting that leaving is indeed not fully independent of the roaming history, but does not directly address the issue described above.

I think that the work is otherwise overall very well done and the results are extremely interesting. But I would interpret the results differently unless the authors provide a more tailored analysis that rules out my concern.

Reviewer #2 (Public Review):

Summary: Kelly et al. strategically leverage the unique strengths of the zebrafish larval model and scRNA-seq to uncover genes that determine the stereotypic output of different neuronal circuits. The results lead to the identification of ion channel and synapse associated genes that distinguish a fast reliable neuronal circuit.

Strengths:<br /> - Well-established neuronal markers allow the transcriptomic analyses to match a majority of the transcriptomic clusters to specific spinal neuron subtypes.<br /> - One transcriptomic cluster reveals the presence in zebrafish of a spinal neuron subtype previously identified in mammals.<br /> - The primary motor neuron and specific interneurons of the circuit mediating strong and fast swimming share expression of cassettes of ion channel and synapse-related gene cassette that sculpt fast and strong synaptic transmission.<br /> - Results are optimally placed in the context of the rich background and literature regarding zebrafish spinal neuron physiology.

Weaknesses:<br /> -The revised version has addressed previous concerns.

Likely Impact:<br /> - The ion channel and synapse-related gene cassettes that distinguish the primary motor neuron circuit are shared with some mammalian circuits that also generate fast, reliable synaptic transmission.<br /> - The transcriptomic data have been deposited in the publicly accessible Gene Expression Omnibus allowing others to mine the rich data set that also included glial cells that were not the focus of this study.

Reviewer #2 (Public Review):

In this publication, the authors provide a comprehensive trajectory of transcriptional changes in Müller glia cells (MG) in the regenerating retina of zebrafish. These resident glia cells of the retina can differentiate into all neural cell classes following injury, providing full regenerative capabilities of the zebrafish retina. The authors achieved this by using single-cell RNA sequencing of Müller glia, progenitors, and regenerated progeny, comparing uninjured and light-lesioned retinae.

The isolation strategy involves using two transgenic strains, one labelling dividing cells and their immediate progeny, and the other Müller glia cells. This allowed them to separate injury-induced proliferating and non-reactive Müller glia cells. Subsequent single-cell transcriptomics showed that MG could be non-reactive under both uninjured and lesioned conditions and reactive MG gives rise to a cell population that both replenishes the pool of MG and replenishes neurogenic retinal precursor cells. These precursor cells produce regenerated neurons in a developmental time series with ganglion cells being born first and bipolar cells being born last. Interestingly hybrid populations have been detected that co-share characteristics of photoreceptor precursors and reactive glia.

This is the first study of its kind following the dynamic changes of transcriptional changes during retinal regeneration, providing a rich data source of genes involved in regeneration. Their finding of transcriptionally separable MG populations is intriguing.

This study focuses on the light-lesioned retina and leaves open the question if the observed transcriptional trajectories of regenerating neurons are generalizable to other lesion models (e.g. chemical or mutational lesions) or are specific to the light-damaged retina.

Reviewer #2 (Public Review):

Summary:<br /> DAVID syndrome is a rare autosomal dominant disorder characterized by variable immune dysfunction and variable ACTH deficiency. Nine different families have been reported, and all have heterozygous mutations in NFKB2. The mechanism of NFKB2 action in the immune systems has been well-studied, but nothing is known about its role in the pituitary gland.

The DAVID mutations cluster in the C-terminus of the NFKB2 and interfere with cleavage and nuclear translocation. The mutations are likely dominant negative, by affecting dimer function. ACTH deficiency can be life-threatening in neonates and adults, thus, understanding the mechanism of NFKB2 action in pituitary development and/or function is important.

The authors use CRISPR/Cas gene editing of human iPSC-derived pituitary-hypothalamic organoids to assess the function of NFKB2 and TBX19 in pituitary development. Mutations in TBX19 are the most common, known cause of pituitary ACTH deficiency, and the mechanism of action has been studied in mice, which phenocopy the human condition. Thus, the TBX19 organoids can serve as a positive control. The Nfkb2 mouse model has a p.Y868* mutation that impairs cleavage of NFKB2 p100, and the immune phenotype mimics the patients with DAVID mutations, but no pituitary phenotype was evident. Thus, a human organoid model might be the only approach suitable to discover the etiology of the pituitary phenotype.

Overall, the authors have selected an important problem, and the results suggest that the pituitary insufficiency in DAVID syndrome is caused by a developmental defect rather than an autoimmune hypophysitis condition. The use of gene editing in human iPSC-derived hypothalamic-pituitary organoids is significant, as there is only one example of this previously, namely studies on OTX2. Only a few laboratories have demonstrated the ability to differentiate iPSC or ES cells to these organoids, and the authors have improved the efficiency of differentiation, which is also significant.

The strength of the evidence is excellent. However, the two ACTH-deficient organoid models use a single genetically engineered clone, and the potential for variability amongst clones makes the conclusions less compelling. Since the authors obtained two independent clones for NFKB2 it is not clear why only one clone was studied. Finally, the effect of TBX19 on early pituitary fate markers is somewhat surprising given the phenotype of the knockout mice and patients with mutations. Thus, the use of a single clone for that study is also worrisome.

Strengths:<br /> The authors make mutations in TBX19 and NFKB2 that exist in affected patients. The TBX19 p.K146R mutation is recessive and causes isolated ACTH deficiency. Mutations in this gene account for 2/3 of isolated ACTH deficiency cases. The NFKB2 p.D865G mutation is heterozygous in a patient with recurrent infections and isolated ACTH deficiency. NFKB2 mutations are a rare cause of ACTH deficiency, and they can be associated with the loss of other pituitary hormones in some cases. However, all reported cases are heterozygous.

The developmental studies of organoid differentiation seem rigorous in that 200 organoids were generated for each hiPSC line, and 3-10 organoids were analyzed for each time point and genotype. Differentiation analysis relied on both RNA transcript measurements and immunohistochemistry of cleared organoids using light sheet microscopy. Multiple time points were examined, including seven times for gene expression at the RNA level and two times in the later stages of differentiation for IHC.<br /> TBX19 deficient organoids exhibit reduced levels of PITX1, LHX3, and POMC (ACTH precursor) expression at the RNA and IHC level, and there are fewer corticotropes in the organoids, as ascertained by POMC IHC.

The NFKB2 deficient organoids have a normal expression of the early pituitary transcription factor HESX1, but reduced expression of PITX2, LHX3, and POMC. Because there is no immune component in the organoid, this shows that NFKB2 mutations can affect corticotrope differentiation to produce POMC. RNA sequencing analysis of the organoids reveals potential downstream targets of NFKB2 action, including a potential effect on epithelial-to-mesenchymal-like transition and selected pituitary and hypothalamic transcription factors and signaling pathways.

Weaknesses:<br /> There could be variation between individual iPSC lines that is unrelated to the genetically engineered change. While the authors check for off-target effects of the guide RNA at predicted sites using WGS, a better control would be to have independently engineered clones or to correct the engineered clone to wild type and show that the phenotypic effects are reversed.

All NFKB2 patients are heterozygous for what appear to be dominant negative mutations that affect protein cleavage and nuclear localization of processed protein as homo or heterdimers. The organoids are homozygous for this mutation. Supplemental Figure 4 indicates that one heterozygous clone and two homozygous mutant clones were obtained. Analysis of these additional clones would give more strength to the conclusions, showing reproducibility and the effect of mutant gene dosage.

Reviewer #2 (Public Review):

Summary:

To identify sugar receptors and assess the capacity of these genes the authors first set out to identify behavioral responses in larvae and adults as well as physiological response. They used phylogenetics and gene expression (RNAseq) to identify candidates for sugar reception. Using first an in vitro oocyte system they assess the responses to distinct sugars. A subsequent genetic analysis shows that the Gr10 and Gr6 genes provide stage specific functions in sugar perception.

Strengths:

A clear strength of the manuscript is the breadth of techniques employed allowing a comprehensive study in a non-canonical model species.

Weaknesses:

There are no major weaknesses in the study for the current state of knowledge in this species. Since it is much basic work to establish a broader knowledge, context with other modalities remains unknown. It might have been possible to probe certain contexts known from the fruit fly, which would have strengthened the manuscript.

Reviewer #2 (Public Review):

Summary:

In this article, the authors provide a method of evaluating safety of orthopedic implants in relation to Radiofrequency induced heating issues. The authors provide an open source computational heterogeneous human model and explain computational techniques in a finite element method solver to predict the RF induced temperature increase due to an orthopedic implant while being exposed to MRI RF fields at 1.5 T.

Strengths:

The open access computational human model along with their semiautomatic algorithm to position the implant can help realistically model the implant RF exposure in patient avoiding over- or under-estimation of RF heating measured using rectangular box phantoms such as ASTM phantom. Additionally, using numerical simulation to predict radiofrequency induced heating will be much easier compared to the experimental measurements in MRI scanner, especially when the scanner availability is limited.

Weaknesses:

The proposed method only used radiofrequency (RF) field exposure to evaluate the heating around the implant. However, in the case of bulky implants the rapidly changing gradient field can also produce significant heating due to large eddy currents. So the gradient induced heating still remains an issue to be evaluated to decide on the safety of the patient. Moreover, the method is limited to a single human model and might not be representative of patients with different age, sex and body weights.

Reviewer #2 (Public Review):

Summary:<br /> Sang-Hyeon et al. laid out a compelling rationale to explore the role of the SMN protein in mesenchymal cells, to determine whether SMN deficiency there could be a pathologic mechanism of SMA. They crossed Smnf7/f7 mice with Prrx1Cre mice to produce SmnΔMPC mice where exon 7 was specifically deleted and thus SMN protein was eliminated in limb mesenchymal progenitor cells (MPCs). To demonstrate gene dosage-dependence of phenotypes, SmnΔMPC mice were crossed with transgenic mice expressing human SMN2 to produce SmnΔMPC mice with different copies of SMN2 (0, 1, or 2). The paper provides genetic evidence that SMN in mesenchymal cells regulates the development of bones and neuromuscular junctions. Genetic data were convincing and revealed novel functions of SMN.

Strengths:<br /> Overall, the paper provided genetic evidence that SMN deficiency in mesenchymal cells caused abnormalities in bones and NMJs, revealing novel functions of SMN and leading to future experiments. As far as genetics is concerned, the data were convincing (except for the rescue experiment, see below); the conclusions are important.

Weaknesses:<br /> The paper seemed to be descriptive in nature and could be improved with more experiments to investigate underlying mechanisms. In addition, some data appeared to be contradicting or difficult to explain. The rescue data were not convincing.

Reviewer #2 (Public Review):

Summary:<br /> In this study, Zhang and colleagues characterise the behaviour of mouse hematopoietic stem cells when cultured in PVA conditions, a recently published method for HSC expansion (Wilkinson et al., Nature, 2019), using multiome analysis (scRNA-seq and scATACseq in the same single cell) and extensive transplantation experiments. The latter are performed in several settings including barcoding and avoiding recipient conditioning. Collectively the authors identify several interesting properties of these cultures namely: 1) only very few cells within these cultures have long-term repopulation capacity, many others, however, have progenitor properties that can rescue mice from lethal myeloablation; 2) single-cell characterisation by combined scRNAseq and scATACseq is not sufficient to identify cells with repopulation capacity; 3) expanded HSCs can be engrafted in unconditioned host and return to quiescence.<br /> The authors also confirm previous studies that EPCRhigh HSCs have better reconstitution capability than EPCRlow HSCs when transplanted.

Strengths:<br /> The major strength of this manuscript is that it describes how functional HSCs are expanded in PVA cultures to a deeper extent than what has been done in the original publication. The authors are also mindful of considering the complexities of interpreting transplantation data. As these PVA cultures become more widely used by the HSC community, this manuscript is valuable as it provides a better understanding of the model and its limitations.

Novelty aspects include:<br /> • The authors determined that small numbers of expanded HSCs enable transplantation into non-conditioned syngeneic recipients.<br /> • This is to my knowledge the first report characterising the output of PVA cultures by multiome. This could be a very useful resource for the field.<br /> • They are also the first to my knowledge to use barcoding to quantify HSC repopulation capacity at the clonal level after PVA culture.<br /> • It is also useful to report that HSCs isolated from fetal livers do expand less than their adult counterparts in these PVA cultures.

Weaknesses:<br /> • The analysis of the multiome experiment is limited. The authors do not discuss what cell types, other than functional or phenotypic HSCs are present in these cultures (are they mostly progenitors or bona fide mature cells?) and no quantifications are provided.<br /> • Barcoding experiments are technically elegant but do not bring particularly novel insights.<br /> • The number of mice analysed in certain experiments is fairly low (Figures 1 and 5).<br /> • The manuscript remains largely descriptive. While the data can be used to make useful recommendations to future users working with PVA cultures and in general with HSCs, those recommendations could be more clearly spelled out in the discussion.<br /> • The authors should also provide a discussion of the other publications that have used these methods to date.

Overall, the authors succeeded in providing a useful set of experiments to better interpret what type of HSCs are expanded in PVA cultures. More in-depth mining of their bioinformatic data (by the authors or other groups) is likely to highlight other interesting/relevant aspects of HSC biology in relation to this expansion methodology.

Reviewer #2 (Public Review):

Summary:<br /> Numerous studies by the authors and other groups have demonstrated an important role for HIV gene expression kidney cells in promoting progressive chronic kidney disease, especially HIV-associated nephropathy. The authors had previously demonstrated a role for protein kinase R (PKR) in a non-HIV transgenic model of kidney disease (Okamoto, Commun Bio, 2021). In this study, the authors used innovative techniques including bulk and single nuclear RNAseq to demonstrate that mice expressing a replication-incompetent HIV transgene have prominent dysregulation of mitochondrial gene expression and activation of PKR and that treatment of these mice with a small molecule PKR inhibitor ameliorated the kidney disease phenotype in HIV-transgenic mice. They also identified STAT3 as a key upstream regulator of kidney injury in this model, which is consistent with previously published studies. Other important advances include identifying the kidney cell types that express the HIV transgene and have dysregulation of cellular pathways.

Strengths:<br /> Major strengths of the study include the use of a wide variety of state-of-the-art molecular techniques to generate important new data on the pathogenesis of kidney injury in this commonly used model of kidney disease and the identification of PKR as a potential druggable target for the treatment of HIV-induced kidney disease. The authors also identify a potential novel cell type within the kidney characterized by high expression of mitochondrial genes.

Weaknesses:<br /> Though the HIV-transgenic model used in these studies results in a phenotype that is very similar to HIV-associated nephropathy in humans, the model has several limitations that may prevent direct translation to human disease, including the fact that mice lack several genetic factors that are important contributors to HIV and kidney pathogenesis in humans. Additional studies are therefore needed to confirm these findings in human kidney disease.

Reviewer #2 (Public Review):

Summary:<br /> The authors examined the hypothesis that eugenol enhances the metabolic profiles of skeletal muscles by activating the TRPV1-Ca2+-calcineurin-NFATc1-IL-15 signalling pathway. They first show that eugenol promotes skeletal muscle transformation and metabolic functions in mitochondria and adipose tissues by analysing changes in the expression of mRNA and proteins of relevant representative protein markers. With similar methodologies, they further found that eugenol increases the expression of mRNA and/or proteins of TRPV1, CaN, NFATC1, and IL-15. These processes were, however, prevented by inhibiting TRPV1 and CaN. Similar expression changes were also triggered by increasing intracellular Ca2+ with A23187, suggesting a Ca2+-dependent process.

Strengths:<br /> Different protein markers were used as a readout of the functions of skeletal muscles, mitochondria, and adipose tissues and analysed at both mRNA and protein levels. The results are mostly consistent though it is not always the case. Although the signaling pathway of TRPV1-Ca2+-CaN-NFAT is not new and well documented, they identified IL-15 as a new downstream target of this pathway,

Weaknesses:<br /> Apart from Fig.2A and 2B, they mostly utilised protein expression changes as an index of tissue functional changes. Most of the data supporting the conclusions are thus rather indirect. More direct functional evidence would be more compelling. For example, a lipolysis assay could be used to measure the metabolic function of adipocytes after eugenol treatment in Fig.3. Functional activation of NFAT can be demonstrated by examining the nuclear translocation of NFAT.

To further demonstrate the role of TRPV1 channels in the effects of eugenol, TRPV1-deficient mice and tissues could also be used. Will the improved swimming test in Fig. 2B and increased CaN, NFAT, and IL-15 triggered by eugenol be all prevented in TRPV1-lacking mice and tissues?

Direct evidence of eugenol activation of TRPV1 channels in skeletal muscles is also lacking. The flow cytometry assay was used to measure Ca2+ changes in the C2C12 cell line in Fig. 5A. But this assay is rather indirect. It would be more convincing to monitor real-time activation of TRPV1 channels in skeletal muscles not in cell lines using Ca2+ imaging or electrophysiology.

Reviewer #2 (Public Review):

Summary:<br /> The authors conducted the first warm autopsy of prostate cancer in China with clear and repeatable standard workflow, documented the transcriptional/genomic/epigenetic profiles across primary tumors and metastases, and highlighted CDKN1B mutation as a key driver mutation for prostate cancer metastases. They provided sufficient details and convincing evidence of multi-omics in their study to define a potential clonal evolution map for the metastatic progression of prostate cancer. The study will also stimulate the development of warm autopsy programs beneficial to patients in Asian populations.

Strengths:<br /> Although the overall incidence of prostate cancer is lower in Asian men compared to men in Western countries, the incidence is increasing in China recently. Therefore the autopsy program will have an important significance in boosting the understanding of molecular mechanism and drug development in prostate cancer for Asian population.<br /> 1. Clear illustration on the warm autopsy workflow and detailed documentation of patient clinical course, sample sites, and downstream analyses. This established a great standard for future expansion of similar autopsy programs and may help boost the consent of more cases.<br /> 2. Systematic and in-depth multi-omic analyses based on limited samples resulted in an impressive atlas for the intratumoral heterogeneity and clonal evolution across primary tumors and metastases. Key driver mutations were thus highlighted.

Weaknesses:<br /> 1. Although the authors highlighted TP53, CDK12, and CDKN1B mutations in the results, not much new knowledge on mechanisms is added to the field since these are already documented in previous studies. Both the unique/private and representative patterns in the single patient, compared to the publicly documented Chinese populations and other ethnical populations will add more significance to this study.

2. The authors claimed that CDKN1B mutation may be the driver event for prostate cancer metastases, but the mutation was absent in the initial bone metastases according to the evolution map created. Although the authors acknowledged this gap and mentioned an FUS mutation in the bone metastases, this compromised the strength in demonstrating the driving significance of this gene mutation. The shRNA experiments on migration<br /> and invasion were impressive but did not necessarily support the initiating potential of CDKN1B mutation in metastases to bone, which is the predominant site of metastases in prostate cancer. It might be a passenger mutation enriched in soft organ metastases or a driver mutation for the secondary metastases from bone metastases.

3. The epigenetic regulation highlighted in the study was not closely correlated to the genetic pattern highlighted (CDK12, CDKN1B, etc.).

Reviewer #2 (Public Review):

Summary:<br /> In the paper from Hartman, Vandenberg, and Hill entitled "assessing drug safety, by identifying the access of arrhythmia and cardio, myocytes, electro physiology", the authors, define a new metric, the axis of arrhythmia" that essentially describes the parameter space of ion channel conductance combinations, where early after depolarization can be observed.

Strengths:<br /> There is an elegance to the way the authors have communicated the scoring system. The method is potentially useful because of its simplicity, accessibility, and ease of use. I do think it adds to the field for this reason - a number of existing methods are overly complex and unwieldy and not necessarily better than the simple parameter regime scan presented here.

Weaknesses:<br /> The method described in the manuscript suffers from a number of weaknesses that plague current screening methods. Included in these are the data quality and selection used to inform the drug-blocking profile. It's well known that drug measurements vary widely, depending on the measurement conditions.

There doesn't seem to be any consideration of pacing frequency, which is an important consideration for arrhythmia triggers, resulting from repolarization abnormalities, but also depolarization abnormalities. Extremely high doses of drugs are used to assess the population risk. But does the method yield important information when realistic drug concentrations are used? In the discussion, the comparison to conventional approaches suggests that the presented method isn't necessarily better than conventional methods.

In conclusion, I have struggled to grasp the exceptional novelty of the new metric as presented, especially when considering that the badly needed future state must include a component of precision medicine.

Reviewer #2 (Public Review):

Summary: The study showed the impact of cancer treatment on new onset of diabetes among patients with colorectal cancer using the national database. Findings reported that individuals with rectal cancer without chemotherapy were less likely to develop diabetes but among other groups, treatment didn't show any impact on the development of diabetes. BMI still played a significant role in developing diabetes regardless of treatment types.

Strengths:<br /> One of the strengths of this study is innovative findings about the prognosis of colorectal cancer treatment stratified by treatment types. Especially, as it examined the impact of treatment on the risk of new chronic disease after diagnosis, it became significant evidence that suggests practical insights in developing a proper monitoring system for patients with colorectal cancer and their outcomes after treatment and diagnosis. It is imperative for providers to guide patients and caregivers to prevent adverse outcomes like new onset of chronic disease based on BMI and types of treatment. The next strength is the national database. As the study used the national database, the generalizability is validated.

Weaknesses: Even though the study attempted to examine the impact of each treatment option, the dosage of chemotherapy and the types of chemotherapy were not able to be examined due to the data source.

Reviewer #2 (Public Review):

In this manuscript, Touray et al investigate the mechanisms by which PIP5Pase and RAP1 control VSG expression in T. brucei and demonstrate an important role for this enzyme in a signalling pathway that likely plays a role in antigenic variation in T. brucei. While these data do not definitively show a role for this pathway in antigenic variation, the data are critical for establishing this pathway as a potential way the parasite could control antigenic variation and thus represent a fundamental discovery.

The methods used in the study are generally well-controlled. The authors provide evidence that RAP1 binds to PI(3,4,5)P3 through its N-terminus and that this binding regulates RAP1 binding to VSG expression sites, which in turn regulates VSG silencing. Overall their results support the conclusions made in the manuscript. Readers should take into consideration that the epitope tags on RAP1 could alter its function, however.

There are a few small caveats that are worth noting. First, the analysis of VSG derepression and switching in Figure 1 relies on a genome which does not contain minichromosomal (MC) VSG sequences. This means that MC VSGs could theoretically be mis-assigned as coming from another genomic location in the absence of an MC reference. As the origin of the VSGs in these clones isn't a major point in the paper, I do not think this is a major concern, but I would not over-interpret the particular details of switching outcomes in these experiments.

Another aspect of this work that is perhaps important, but not discussed much by the authors, is the fact that signalling is extremely poorly understood in T. brucei. In Figure 1B, the RNA-seq data show many genes upregulated after expression of the Mut PIP5Pase (not just VSGs). The authors rightly avoid claiming that this pathway is exclusive to VSGs, but I wonder if these data could provide insight into the other biological processes that might be controlled by this signaling pathway in T. brucei.

Overall, this is an excellent study which represents an important step forward in understanding how antigenic variation is controlled in T. brucei. The possibility that this process could be controlled via a signalling pathway has been speculated for a long time, and this study provides the first mechanistic evidence for that possibility.

Reviewer #2 (Public Review):

Summary:<br /> Birzu et al. describe two sympatric hotspring cyanobacterial species ("alpha" and "beta") and infer recombination across the genome, including inter-species recombination events (hybridization) based on single-cell genome sequencing. The evidence for hybridization is strong and the authors took care to control for artefacts such as contamination during sequencing library preparation. Despite hybridization, the species remain genetically distinct from each other. The authors also present evidence for selective sweeps of genes across both species - a phenomenon which is widely observed for antibiotic resistance genes in pathogens, but rarely documented in environmental bacteria.

Strengths:<br /> This manuscript describes some of the most thorough and convincing evidence to date of recombination happening within and between cohabitating bacteria in nature. Their single-cell sequencing approach allows them to sample the genetic diversity from two dominant species. Although single-cell genome sequences are incomplete, they contain much more information about genetic linkage than typical short-read shotgun metagenomes, enabling a reliable analysis of recombination. The authors also go to great lengths to quality-filter the single-cell sequencing data and to exclude contamination and read mismapping as major drivers of the signal of recombination.

Weaknesses:<br /> Despite the very thorough and extensive analyses, many of the methods are bespoke and rely on reasonable but often arbitrary cutoffs (e.g. for defining gene sequence clusters etc.). Much of this is warranted, given the unique challenges of working with single-cell genome sequences, which are often quite fragmented and incomplete (30-70% of the genome covered). I think the challenges of working with this single-cell data should be addressed up-front in the main text, which would help justify the choices made for the analysis. The conclusions could also be strengthened by an analysis restricted to only a subset of the highest quality (>70% complete) genomes. Even if this results in a much smaller sample size, it could enable more standard phylogenetic methods to be applied, which could give meaningful support to the conclusions even if applied to just ~10 genomes or so from each species. By building phylogenetic trees, recombination events could be supported using bootstraps, which would add confidence to the gene sequence clustering-based analyses which rely on arbitrary cutoffs without explicit measures of support.

The manuscript closes without a cartoon (Figure 4) which outlines the broad evolutionary scenario supported by the data and analysis. I agree with the overall picture, but I do think that some of the temporal ordering of events, especially the timing of recombination events could be better supported by data. In particular, is there evidence that inter-species recombination events are increasing or decreasing over time? Are they currently at steady-state? This would help clarify whether a newly arrived species into the caldera experiences an initial burst of accepting DNA from already-present species (perhaps involving locally adaptive alleles), or whether recombination events are relatively constant over time. These questions could be answered by counting recombination events that occur deeper or more recently in a phylogenetic tree. The cartoon also shows a 'purple' species that is initially present, then donates some DNA to the 'blue' species before going extinct. In this model, 'purple' DNA should also be donated to the more recently arrived 'orange' species, in proportion to its frequency in the 'blue' genome. This is a relatively subtle detail, but it could be tested in the real data, and this may actually help discern the order of the inferred recombination events.

The abstract also makes a bold claim that is not well-supported by the data: "This widespread mixing is contrary to the prevailing view that ecological barriers can maintain cohesive bacterial species..." In fact, the two species are cohesive in the sense that they are identifiable based on clustering of genome-wide genetic diversity (as shown in Fig 1A). I agree that the mixing is 'widespread' in the sense that it occurs across the genome (as shown in Figure 2A) but it is clearly not sufficient to erode species boundaries. So I believe the data is consistent with a Biological Species Concept (sensu Bobay & Ochman, Genome Biology & Evolution 2017) that remains 'fuzzy' - such that there are still inter-species recombination events, just not sufficient to erode the cohesion of genomic clusters. Therefore, I think the data supports the emerging picture of most bacteria abiding by some version of a BSC, and is not particularly 'contrary' to the prevailing view.

The final Results paragraph begins by posing a question about epistatic interactions, but fails to provide a definitive answer to the extent of epistasis in these genomes. Quantifying epistatic effects in bacterial genomes is certainly of interest, but might be beyond the scope of this paper. This could be a Discussion point rather than an underdeveloped section of the Results.

Reviewer #2 (Public Review):

Summary:<br /> This research demonstrates the breadth of IgA response as determined by isolating individual antigen-specific B cells and generating mAbs in mice following intranasal immunization of mice with SARS-CoV2 Spike protein. The findings show that some IgA mAb can neutralize the virus, but many do not. Notable immunization with Wuhan S protein generates a weak response to the omicron variant.

Strengths:<br /> Detailed analysis characterizing individual B cells with the generation of mAbs demonstrates the response's breadth and diversity of IgA responses and the ability to generate systemic immune responses.

Weaknesses:<br /> The data presentation needs clarity, and results show mAb ability to inhibit SARS-CoV2 in vitro. How IgA functions in vivo is uncertain.

Reviewer #2 (Public Review):

Many studies have found that self-generated tactile contact is perceived as weaker than the same contact with an external source. A recent high-profile study found that a force that was predictable based on a participant's own movement but was not caused by contact was perceived as stronger than the same force in an interleaved no-go condition without movement. By combining methods from this and older studies within a single design, the present study resolves the apparent contradiction by showing that the predictable force is enhanced only relative to the no-go reference, and that forces are attenuated when self-contact occurs or is predicted.

The key strength of this work lies in the robust application of pre-registered methods to reproduce and compare findings within a single experimental setting that have been separately interpreted as enhancement or attenuation in previous work. The results are admirably clear and decisive.

I feel there is room for some conceptual clarification when it comes to the discussion of appropriate baselines. The paper tends (as does the preceding work by Thomas et al.) towards claims of the absolute kind, such as "self-generated sensation is attenuated" (or "enhanced"), that are not meaningful because the scales of sensation and stimulus are incommensurate (e.g. there is no sensation that is objectively equal to 2N of force on the finger). Rather, the only claims that can or should be made are relative ones, e.g. "self-generated sensation is attenuated *compared to* externally-generated sensation". The present results provide a strong confirmation of this existing claim while clarifying that the recent findings of Thomas et al.'s Exp 1 could be better summarized as "predictable sensations are enhanced in trials with a GO signal compared to a NOGO signal". So it is not that one study chose the "right" baseline and the other the "wrong" one, but rather that Thomas et al. extrapolated their results to comparisons other than the one they had tested.

The paper does not directly address Thomas et al.'s Exp 2, in which they observed enhanced sensation of force in an expected compared to an unexpected finger. Because there was never any (real or virtual) contact between the fingers in that experiment, the authors would probably argue that it is irrelevant to the classical "predictive attenuation" hypothesis, but the results nonetheless suggest the existence of another factor influencing force perception that is not explained by NOGO inhibition.

Reviewer #2 (Public Review):

The manuscript by Mishra et al. examines the modulation of the nervous system by different bacterial food to influence reproductive phenotypes-specifically onset of oogenesis, fertilization rate, and progeny production. Defining how animal reproduction could be modulated by bacterial food cues through neuroendocrine signaling is a fascinating subject of study for which C. elegans is well-suited. However, the overall scope of the current study is limited, and some of the central data do not provide compelling evidence for the authors' underlying hypothesis and model.

1. Two strains of E. coli are examined, the standard C. elegans bacterial food strain OP50 and an E. coli strain that Alcedo and colleagues have previously characterized to influence aging and longevity through nervous system modulation. While the authors determine that differences in LPS structure present between the strains does not account for the food-dependent effects, there is little further insight regarding the bacterial features that contribute to the observed differences in reproductive physiology. Moreover, at least two of the phenotypes examined-total progeny and fertilization rate-are known to be affected by bacterial food quality and may be affected by bacteria in many ways, so the description of these phenotypes is somewhat less compelling than the study of the onset of oogenesis.

2. The onset of oogenesis phenotype, using the lin-41::GFP reporter, seems more specific and tractable, and the authors nicely decouple this phenotype from the total progeny and fertilization rate phenotypes through experiments that shift animals to different bacterial food at specific developmental stages. However, as it stands, the data regarding the role of ins-6 and ASJ in modulating this phenotype, and the model that exposure to CS180 bacterial food causes a change in the ASJ expression of ins-6, which is sufficient to promote the earlier onset of oogenesis at the mid-L4 stage, seems somewhat incomplete and have some inconsistencies to be addressed.

a. The ins-6 mutant phenotype is rescued by genome ins-6 and partially rescued by ins-6 expressed under and ASJ-specific promoter. The lack of rescue from an ASI promoter is puzzling given the secreted nature of ins-6.

b. The ins-6 mutant phenotype with regard to delaying the early expression of lin-41::GFP on CS180 appears weaker than the daf-2 mutant phenotype. This is difficult to reconcile with what is known about the relative strength of the daf-2 mutant alleles relative to ins-6 for a wide range of phenotypes.

c. The daf-16 loss-of-function phenotype and suppression of daf-2 and ins-6 mutant phenotypes are not shown for the lin-41::GFP expression phenotype.

d. The modest difference in ins-6p::mCherry expression in the ASJ neurons (Figure 5D) make the idea that this difference causes onset of oogenesis somewhat implausible.

e. The strain carrying an genetic ablation of ASJ appears to have a markedly different baseline of kinetics of lin-41::GFP expression (even at lethargus, less than half of the animals appear to express lin-41::GFP). Given this phenotype, it seems difficult to draw conclusions about bacterial food-dependent effects on expression of lin-41::GFP. Additional characterization corroborating timing of oogenesis independent of the lin-41::GFP marker may be helpful, but something seems amiss.

Reviewer #2 (Public Review):

Based on their results the authors make the following statements:<br /> 1) Apoptotic pathways and efferocytosis receptors are elevated in fibroblasts and immune cells in mouse skin wounds. Based on the analysis of the scRNASeq data this is a valid conclusion.

I suggest to repeat the quantification of cells containing active caspase-3 with an anti-cleaved caspase-3 antibody. Here the authors use an antibody recognizing phospho S150 antibody, which is far from generally accepted to be a marker for active caspase-3.

It would also be good to quantify the apoptotic cells observed in the sections (Fig 1 I and J) and compare to control treatment on sections. It is not clear from the data presented whether the number of apoptotic cells increases or not in the time frame analyzed since the controls are lacking. In a FACS analysis (Fig S1 H), the authors show that there is no increase in dead cells in a time frame of 48 hrs. Could it be that the majority of the cells that may have died in vivo, were lost during the procedure of tissue digestions. Dead cells tend to aggregate.

On line 104 the authors refer to the apoptosis-inducing activity of G0s2. Please, realize that there is little or no in vivo evidence for a role of G0s2 in apoptosis.

The authors state that Axl is uniquely expressed in DC and fibroblasts (Fig 2). Are the Axl-cells positive in panel G (red, Fig 2) that do not stain for the Pdgfra marker (green) then all DCs? Please clarify or show with a triple staining that these cells are indeed DCs. In addition, it is not clear to me to what reference level exactly the expression levels are compared in Fig 2A. Is this between the 24 and 48h time points after wounding (as mentioned in the legend)? If so, the analysis may indicate up or down regulation but not necessarily expression or no expression.

2) Human diabetic wounds display increased and altered efferocytosis signaling via Axl.<br /> This conclusion is solely based on CellChat analysis and should be tuned down or validated. Tools like CellChat or NicheNet generate data that are suggestive and help scientist to build hypothesis. However, these data do not hold formal proof, but should be experimentally validated. Alternatively, the statement should be downtuned.

3) Axl expression is regulated via an TLR3-independent mechanism during wounding. This statement is supported by analysis in a genetic mouse model.

4) In mice, Axl signaling is required for wound repair but is dispensable for efferocytosis.<br /> This was concluded based on an in vivo experiment in which the authors treat the mice during wound healing with neutralizing anti-Axl antibodies that were validated in literature. The effectivity of the treatment is checked by analyzing the Axl mRNA levels since Axl activation upregulates its own mRNA expression levels. Anti-Axl therapy resulted in a downregulation of the Axl mRNA levels, while IFN-beta levels (an inducer of Axl expression) were upregulated by the treatment.<br /> The authors conclude that anti-Axl treatment leads to healing defects based on lack of granulation tissue and larger scabs, a reduction of fibroblast repopulation and revascularization. The differences in the last two parameters mentioned above are obvious, however the other parameters, as granulation tissue and scabs are less clear to me. Is this quantified in any way? In Fig S4 D there is also a large scab visible in the control treatment image. Therefore, it would be good if these parameters could be better substantiated. In view of the lack of revascularization, are there differences in the mRNA expression levels of angiogenic factors such as VEGF and others at this time point? Does revascularization occur at later stages?.<br /> Based on the FACS analysis the authors claim that there are no differences at the level of DCs. However, the plots shown in Fig 5C do not convincingly show the detection of DC (as boxed in the lower panel). Based on the density plots one would presume this is just the continuation of the CD11b+ population and not a separate CD11c+ population. To get a better view on that, it would be better to show dot plots instead of density plots.<br /> Finally, the authors state (line 265-266) that anti-Axl treatment leads to non-significantly increased expression of IL1alpha and IL6 after one day of injury (Fig S4C). If the difference between the control-treated and the anti-Axl-treated group is statistically not significant I would not conclude there is an increase. Please adapt phrasing or include more mice in the experiment (now only 4) to substantiate the observation and clarify whether it is increased or not.

5) Inhibition of the efferocytosis receptor Timd4 decreases efferocytosis and abrogates wound repair.<br /> The reason to study the effect of Timd4 was based on the fact that the authors find it upregulated on DCs during wound healing.<br /> The contribution of Timd4 in wound healing was investigated in vivo, under conditions in which the mice were treated with an anti-Timd4 antibody.<br /> The authors conclude that overall healing was not affected but that the wound beds appeared more fragile. What is meant with 'appeared more fragile' is not clear. In addition, this seems to me a quite subjective interpretation. What are the objective parameters to come this conclusion?<br /> Similar to inhibition of Axl, inhibition of Timd4 led to a defect in revascularization as witnessed by the absence of CD31 staining. Also in this experiment one can raise similar questions as in the anti-Axl experiment: 1) does revascularization occur at a later timepoint; 2) what about the expression of angiogenic factors?<br /> In the anti-Timd4 treated wounds the authors observe more TUNEL-positive cells and conclude that this is due to a defect in efferocytosis. However, the formal experimental proof for this in the current model is lacking. How do the authors exclude the possibility that anti-Timd4 treatment attracts more infiltrating cells that then undergo treatment, or that the treatment with anti-Timd4 leads to more apoptosis of certain cells in the wound bed. What is the nature of these apoptotic cells (neutrophils, T cells, others)? It has been shown that Timd4 can have stimulatory effects on other cells, such as T cells. Could deprivation of Timd4 signaling in certain conditions lead to more dying cells in this model?

Based on the comments and concerns raised above, this study appears premature at this stage.

Reviewer #2 (Public Review):

The communication between mitochondria and the nucleus is crucial for maintaining cellular homeostasis and coordinating various cellular processes. The work by Sriram and colleagues discovers a potentially novel messenger molecule between mitochondrial-nuclear crosstalk through the widespread association of mitochondrial RNAs with nuclear chromatin. They termed this as mt-caRNAs that establishes a direct connection between mtRNA and the epigenome. These mt-caRNAs were found to preferentially attach to promoter regions, which led them to investigate how mt-caRNAs may regulate nuclear-encoded transcripts. Using an endothelial cell model, depletion/ overexpression of a specific mt-caRNA altered stress-induced transcription of nuclear genes encoding for innate inflammation and endothelial activation. Overall, these findings are interesting and warrant further investigation of the role of mt-caRNA-mediated nuclear transcription in controlling cellular processes.

Reviewer #2 (Public Review):

Casp11 is a cytosolic sensor for LPS in mice (orthologue of Casp4/5 in human). It is an important innate sensor of intracellular infection. Casp11 activity results in cleavage and activation of the pore-forming protein Gasdemin D (GSDMD) leading to lytic death (pyroptosis), of an infected cell. How exactly Casp11 signals upon LPS detection is beginning to be understood, but the picture is incomplete. Previous reports suggested that upon LPS detection, Casp11 dimerizes and undergoes auto-processing to form a pyroptosis-competent enzyme. The prediction from these studies was that the formation of a fully functional Casp11 signalling complex involves two steps: inducible dimerization and auto-processing.

In this study, authors used fluorescently tagged Casp11 reporter fusions, to report that detection of cytosolic LPS induces Casp11 assembly into a large perinuclear speck to form a signalling complex, where GSDMD can be processed. Such signalling complex resembles signalling specks formed upon the activation of other canonical inflammasomes.

Strengths:

Results are clean, experiments well controlled, and support the conclusions. Overall conclusions fit nicely in the general principle of innate signalling, whereby activation of many innate sensors results in their inducible assembly into higher-order oligomeric signalling complexes, called supra-molecular organizing centers (SMOCs).

A surprising finding from this work was that catalytically inactive Casp11 (C254A mutant) did not form signalling specks, despite being able to bind LPS and dimerise. This model is proposed where LPS binding to the CARD domain of Casp11 and Casp11 dimerization is necessary but not sufficient to mediate Casp11 speck formation within cells. The Casp11 catalytic activity is needed to facilitate the assembly of the higher-order, pyroptosis-competent Casp11 signalling platform. The model is further supported by experimental evidence that auto-processing of Casp11, by an exogenous protease TEV, (i.e. in the absence of LPS), is sufficient to mediate speck assembly in cells expressing wild type, but not catalytically inactive Casp11 mutant.

Possible technical improvements:

In general, the authors achieved their aims, and the results support the conclusions.

For technical robustness, it would be nice to consider a few controls:<br /> (a) Visualise Casp11 specks using constructs with smaller tags, and test whether tag placement on N or C terminus matters for speck formation; or<br /> (b) Biochemically crosslink and isolate endogenous, untagged Casp11 specks upon LPS transfection of primed macrophages (e.g. after priming through IFNs or TLRs). This would mimic the natural upregulation and activation of endogenous Casp11.<br /> (c) Test what happens after actual intracellular pathogen detection when the pathogen itself serves as a signalling platform? Are specks stills formed (or even needed)?

The broad impact of the work, implication, and questions for future work:

Results of this study would suggest that the enzymatic activity of Casp11 in macrophages may be highly restricted to the speck location, similar to what was described for Casp1. This may explain the very restricted substrate repertoire of Casp11 in cells, likely controlled by the substrate recruitment to the speck. This also opens avenues for follow-up work to answer several emerging questions:

1. After LPS binding and dimerization, why Casp11 must undergo intra-molecular processing to induce the formation of a pyroptosis-competent speck? Is there any substrate for LPS-bound, uncleaved Casp11 (beyond Casp11 itself), before Casp11 forms a full speck for GSDMD processing? The only currently known targets of Casp11 activity are itself, and GSDMD. Also, after intradomain linker cleavage of Casp11, what additional substrate must the cleaved Casp11 process to allow full speck formation?

2. Can activity probes be designed to detect the location of the active Casp11, and if so, would the activity of Casp11 be restricted to the speck? Is there a second cleavage event that would eventually dissociate Casp11 from the speck, to terminate its signalling? If not, how is speck activity terminated? If specks are released by lysis, are they capable of seeding new speck formation in neighbouring phagocytes, in prion-like behaviour previously described for canonical ASC speck?

3. What is the role of macrophage priming in speck formation, and what roles, if any GBPs play in speck formation?

4. Does this model apply to human orthologues, Casp4/5?

Reviewer #2 (Public Review):

Biphasic responses are widely observed in biological systems and the determination of general design principles underlying biphasic responses is an important problem. The authors attempt to study this problem using a range of biochemical signaling models ranging from simple enzymatic modification and de-modification of a single substrate to systems with multiple enzymes and substrates. The authors used analytical and computational calculations to determine conditions such as network topology, range of concentrations, and rate parameters that could give rise to biphasic responses. I think the approach and the result of their investigation are interesting and can be potentially useful. However, the conditions for biphasic responses are described in terms of parameter ranges or relationships in particular biochemical models, and these parameters have not been connected to the values of concentrations or rates in real biological systems. This makes it difficult to evaluate how these findings would be applicable in nature or in experiments. It might also help if some general mechanisms in terms of competition/cooperation of time scales/processes are gleaned which potentially can be used to analyze biphasic responses in real biological systems.

Reviewer #2 (Public Review):

This paper uses the mouse mesoscale connectome, combined with data on the number and fraction of PV-type interneurons, to build a large-scale model of working memory activity in response to inputs from various sensory modalities. The key claims of the paper are two-fold. First, previous work has shown that there does not appear to be an increase in the number of excitatory inputs (spines) per pyramidal neuron along the cortical hierarchy (and this increase was previously suggested to underlie working memory activity occurring preferentially in higher areas along the cortical hierarchy). Thus, the claim is that a key alternative mechanism in the mouse is the heterogeneity in the fraction of PV interneurons. Second, the authors claim to develop novel cell type-specific graph theory.

I liked seeing the authors put all of the mouse connectomic information into a model to see how it behaved and expect that this will be useful to the community at large as a starting point for other researchers wishing to use and build upon such large-scale models. However, I have significant concerns about both primary scientific claims. With regard to the PV fraction, this does not look like a particularly robust result. First, it's a fairly weak result to start, much smaller than the simple effect of the location of an area along the cortical hierarchy (compare Figs. 2D, 2E; 3C, 3D). Second, the result seems to be heavily dependent upon having subdivided the somatosensory cortex into many separate points and focusing the main figures of the paper (and the only ones showing rates as a function of PV cell fraction) solely on simulations in which the sensory input is provided to the visual cortex. With regards to the claim of novel cell type-specific graph theory, there doesn't appear to be anything particularly novel. The authors simply make sure to assign negative rather than positive weights to inhibitory connections in their graph-theoretic analyses.

Major issues:<br /> 1) Weakness of result on effect of PV cell fraction. Comparing Figures 2D and 2E, or 3C and 3D, there is a very clear effect of cortical hierarchy on firing rate during the delay period in Figures 2D and 3C. However, in Figure 2E relating delay period firing rate to PV cell fraction, the result looks far weaker. (And similarly for Figs. 3C, 3D, with the latter result not even significant). Moreover, the PV cell fraction results are dominated by the zero firing rate brain regions (as opposed to being a nice graded set of rates, both for zeros and non-zeros, as with the cortical hierarchy results of Figures 2D), and these zeros are particularly contributed to by subdividing somatosensory (SS) into many subregions, thus contributing many points at the lower right of the graph.<br /> Further, it should be noted that Figure 2E is for visual inputs. In the supplementary Figure 2 - supplement 1, the authors do apply sensory inputs to auditory and somatosensory cortex...but then only show the result that the delay period firing rate increases along the cortical hierarchy (as in Figure 2D for the visual input), but strikingly omit the plots of firing rate versus PV cell fraction. This omission suggests that the result is even weaker for inputs to other sensory modalities, and thus difficult to justify as a defining principle.

2) Graph theoretic analyses. The main comparison made is between graph-theoretic quantities when the quantities account for or do not account for, PV cells contributing negative connection strengths. This did not seem particularly novel.

3) It was not clear to me how much the cell-type specific loop strength results were a result of having inhibitory cell types, versus were a result of the assumption ('counter-stream inhibitory bias') that there is a different ratio of excitation to inhibition in top-down versus bottom-up connections. It seems like the main results were more a function of this assumed asymmetry in top-down vs. bottom-up than it was a function of just using cell-type per se. That is, if one ignored inhibitory neurons but put in the top-down vs. bottom-up asymmetry, would one get the same basic results? And, likewise, if one didn't assume asymmetry in the excitatory vs. inhibitory connectivity in top-down versus bottom-up connections, but kept the Pyramidal and PV cell fraction data, would the basic result go away?

4) In the Discussion, there is a third 'main finding' claimed: "when local recurrent excitation is not sufficient to sustain persistent activity...distributed working memory must emerge from long-range interactions between parcellated areas". Isn't this essentially true by definition?

5) I don't know if it's even "CIB" that's important or just "any asymmetry (excitatory or inhibitory) between top-down vs. bottom-up directions along the hierarchy". This is worth clarifying and thinking more about, as assigning this to inhibition may be over-attributing a more basic need for asymmetry to a particular mechanism.

Other questions:<br /> 1) Is it really true that less than 2% of neurons are PV neurons for some areas? Are there higher fractions of other inhibitory interneuron types for these areas, and does this provide a confound for interpreting model results that don't include these other types?<br /> Maybe related to the above, the authors write in the Results that local excitation in the model is proportional to PV interneuron density. However, in the methods, it looks like there are two terms: a constant inhibition term and a term proportional to density. Maybe this former term was used to account for other cell types. Also, is local excitation in the model likewise proportional to pyramidal interneuron density (and, if not, why not?)?

2) Non-essential areas. The categorization of areas as 'non-essential' as opposed to, e.g. "inputs" is confusing. It seems like the main point is that, since the delay period activity as a whole is bistable, certain areas' contributions may be small enough that, alone, they can't flip the network between its bistable down and up states. However, this does not mean that such areas (such as the purple 'non-essential' area in Figure 5a) are 'non-essential' in the more common sense of the word. Rather, it seems that the purple area is just a 'weaker input' area, and it's confusing to thus label it as 'non-essential' (especially since I'd guess that, whether or not an area flips on/off the bistability may also depend on the assumed strength of the external input signal, i.e. if one made the labeled 'input area' a bit too weak to alone trigger the bistability, then the purple area might become 'essential' to cross the threshold for triggering a bistable-up state).

3) Relation between 'core areas' and loop strength. The measure underlying 'prediction accuracy = 0.93' in Figure 6D and the associated results seems incomplete by being unidirectional. It captures the direction: 'given high cell-type specific loop strength, then core area' but it does not capture the other direction: 'given a cell is part of a core area, is its predicted cell-type specific loop strength strong?'. It would be good to report statistics for both directions of association between loop strength and core area.

4) More justification would be useful on the assumption that the reticular nucleus provides tonic inhibition across the entire thalamus.

5) Is NMDA/AMPA ratio constant across areas and is this another difference between mice and monkeys? I am aware of early work in the mouse (Myme et al., J. Neurophys., 2003) suggesting no changes at least in comparing two brain regions' layer 2/3, but has more work been performed related to this?

6) Are bilateral connections between the left and right sides of a given area omitted and could those be important?

Reviewer #2 (Public Review):

This is a potentially important finding regarding the roles of O-GlcNAc cycling and one-carbon metabolism in nerve regeneration. In a previous paper (Taub et al. 2018) they showed that both ogt-1 and oga-1 mutants show strong activation of a neuronal regeneration phenotype. However, the different biological processes used for the neural regeneration phenotype differed between the ogt-1 and oga-1 mutants. Several small issues emerge in the present paper which will increase the interest in the findings presented.

In summary, this paper under review is a potentially important finding which upon further documentation will be an excellent contribution.

Reviewer #2 (Public Review):

This manuscript introduces an integrative framework for modelling and analysis in neuroscience called BrainPy. It describes the many tools and utilities for building a wide range of models with an accessible and extensible unified interface written in Python. Several illustrative examples are provided for common use cases, including how to extend the existing classes to incorporate new features, demonstrating its ease of use and adherence to Python's programming conventions for integrative modelling across multiple scales and paradigms. The provided benchmarks also demonstrate that despite the convenience of presenting a high-level interpreted language to the user, it provides orders of magnitude of computational speed-up relative to three popular alternative frameworks on the chosen simulations through the extensive use of several Just In Time compilers. Computational benchmarks are also provided to illustrate the speed-up gained from running the models on massively parallel processing hardware, including GPUs, suggesting leading computational performance across a wide range of use cases.

While the results presented are impressive, publishing further details of the benchmarks in an appendix would be helpful for evaluating the claims and the overall conclusion would be more convincing if the performance benefits were demonstrated on a wider selection of test cases. Unsatisfyingly, the authors gave up on making a direct comparison to Brian running on GPUs with GeNN which would have been a fairer comparison than CPU-based simulations. The code for the chosen benchmarks is also likely to be highly optimised by the authors for running on BrainPy but less so for the other platforms - a fairer test would be to invite the authors of the other simulators to optimise the same models and re-evaluate the benchmarks. Furthermore, the manuscript reads like an advertisement for the platform with very little discussion of its limitations, weaknesses, or directions for further improvement. A more frank and balanced perspective would strengthen the manuscript and give the reader greater confidence in the platform.

Since simulators wax and wane in popularity, it would be reassuring to see a roadmap for development with a proposed release cadence and a sustainable governance policy for the project. This would serve to both clearly indicate the areas of active development where community contributions would be most valuable and also to reassure potential users that the project is unlikely to be abandoned in the near future, ensuring that their time investment in learning to use the framework will not be wasted. Similarly, a complex set of dependencies, which need to be modified for BrainPy, will likely make the project hard to maintain and so a similar plan to those given for the CI pipeline and documentation generation for automation of these modifications would be a good addition. It is also important to periodically reflect on whether it still makes sense to combine all the disparate tools into one framework as the codebase grows and starts to strain under modifications required to maintain its unification.

Finally, a live demonstration would be a very useful addition to the project. For example, a Jupyter notebook hosted on mybinder.org or similar, and a fully configured Docker image, would each enable potential users to quickly experiment with BrainPy without having to install a stack of dependencies and troubleshoot version conflicts with their pre-existing setup. This would greatly lower the barrier to adoption and help to convince a larger base of modellers of the potential merits of BrainPy, which could be major, both in terms of the computational speed-up and ease of development for a wide range of modelling paradigms.

Reviewer #2 (Public Review):

Guo and her colleagues develop a new approach to map the category-selective functional topographies in individual participants based on their movie-viewing fMRI data and functional localizer data from a normative sample. The connectivity hyperalignment are used to derived the transformation matrices between the participants according to their functional connectomes during movies watching. The transformation matrices are then used to project the localizer data from the normative sample into the new participant and create the idiosyncratic cortical topography for the participant. The authors demonstrate that a target participant's individualized category-selective topography can be accurately estimated using connectivity hyperalignment, regardless of whether different movies are used to calculate the connectome and regardless of other data collection parameters. The new approach allows researchers to estimate a broad range of functional topographies based on naturalistic movies and a normative database, making it possible to integrate datasets from laboratories worldwide to map functional areas for individuals. The topic is of broad interest for neuroimaging community; the rationale of the study is straightforward and the experiments were well designed; the results are comprehensive. I have some concerns that the authors may want to address, particularly on the details of the pipeline used to map individual category-selective functional topographies.

1. How does the length of the scan-length of movie-viewing fMRI affect the accuracy in predicting the idiosyncratic cortical topography? Similarly, how does the number of participants in the normative database affect the prediction of the category-selective topography? This information is important for the researchers who are interested in using the approach in their studies.<br /> 2. The data show that category-selective topography can be accurately estimated using connectivity hyperalignment, regardless of whether different movies are used to calculate the connectome and regardless of other data collection parameters. I'm wondering whether the functional connectome from resting state fMRI can do the same job as the movie-watching fMRI. If it is yes, it will expand the approach to broader data.<br /> 3. The authors averaged the hyper-aligned functional localizer data from all of subjects to predict individual category-selective topographies. As there are large spatial variability in the functional areas across subjects, averaging the data from many subjects may blur boundaries of the functional areas. A better solution might be to average those subjects who show highly similar connectome to the target subjects.<br /> 4. It is good to see that predictions made with hyperalignment were close to and sometimes even exceeded the reliability values measured by Cronbach's alpha. But, please clarify how the Cronbach's alpha is calculated.<br /> 5. Which algorithm was used to perform surface-based anatomical alignment? Can the state-of-the-art Multimodal Surface Matching (MSM) algorithm from HCP achieve better performance?<br /> 6. Is it necessary to project to the time course of the functional localizer from the normative sample into the new participants? Does it work if we just project the contrast maps from the normative samples to the new subjects?<br /> 7. Saygin and her colleagues have demonstrated that structural connectivity fingerprints can predict cortical selectivity for multiple visual categories across cortex (Osher DE et al, 2016, Cerebral Cortex; Saygin et al, 2011, Nat. Neurosci). I think there's a connection between those studies and the current study. If the author can discuss the connection between them, it may help us understand why CHA work so well.

Reviewer #2 (Public Review):

Relative simplicity and genetic accessibility of the fly brain makes it a premier model system for studying the function of genes linked to various diseases in humans. Here, Pan et al. show that human UBA5, whose mutations cause developmental and epileptic encephalopathy, can functionally replace the fly homolog Uba5. The authors then systematically express in flies the different versions of the gene carrying clinically relevant SNPs and perform extensive phenotypic characterization such as survival rate, developmental timing, lifespan, locomotor and seizure activity, as well as in vitro biochemical characterization (stability, ATP binding, UFM-1 activation) of the corresponding recombinant proteins. The biochemical effects are well predicted by (or at least consistent with) the location of affected amino acids in the previously described Uba5 protein structure. Most strikingly, the severity of biochemical defects appears to closely track the severity of phenotypic defects observed in vivo in flies. While the paper does not provide many novel insights into the function of Uba5, it convincingly establishes the fly nervous system as a powerful model for future mechanistic studies.

One potential limitation is the design of the expression system in this work. Even though the authors state (ln. 127-128) that "human cDNA is expressed under the control of the endogenous Uba5 enhancer and promoter", it is in fact the Gal4 gene that is expressed from the endogenous locus (which authors also note in the same paragraph 138-139), meaning that the cDNA expression level would inevitably be amplified in comparison. While I do not think this weakens the conclusions of this paper, it may impact the interpretation of future experiments that use these tools. Especially considering the authors argue that most disease variants of UBA5 are partial loss-of-functions, the amplification effect could potentially mask the phenotypes of milder hypomorphic alleles. Temperature sensitivity of Gal4 expression may allow calibrating levels to reduce the impact of this amplification, but the revised manuscript still does not openly acknowledge or discuss this potential caveat.

Reviewer #2 (Public Review):

More than 80 million people live at high altitude. This impacts health outcomes, including those related to pregnancy. Longer-lived populations at high altitudes, such as the Tibetan and Andean populations show partial protection against the negative health effects of high altitude. The paper by Yue sought to determine the mechanisms by which the placenta of Tibetans may have adapted to minimise the negative effect of high altitude on fetal growth outcomes. It compared placentas from pregnancies from Tibetans to those from the Han Chinese. It employed RNAseq profiling of different regions of the placenta and fetal membranes, with some follow-up of histological changes in umbilical cord structure and placental structure. The study also explored the contribution of fetal sex in these phenotypic outcomes.

A key strength of the study is the large sample sizes for the RNAseq analysis, the analysis of different parts of the placenta and fetal membranes, and the assessment of fetal sex differences.

A main weakness is that this study, and its conclusions, largely rely on transcriptomic changes informed by RNAseq. Changes in genes and pathways identified through bioinformatic analysis were not verified by alternate methods, such as by western blotting, which would add weight to the strength of the data and its interpretations. There is also a lack of description of patient characteristics, so the reader is unable to make their own judgments on how placental changes may link to pregnancy outcomes. Another weakness is that the histological analyses were performed on n=5 per group and were rudimentary in nature.

Reviewer #2 (Public Review):

Summary:<br /> This study addresses the factors affecting the loss of independent control of finger forces after stroke. As central and peripheral factors contribute to this impairment, the authors used a novel apparatus and task to rigorously quantify the specific features of loss of finger individuation across all digits. The analyses ruled out the role of biomechanical constraints and revealed that the loss of independent control of finger forces is primarily driven by the interaction of two factors: loss of complexity in finger control (shape of enslavement patterns) and involuntary coactivations of task-irrelevant fingers (flexion bias).

Strengths:<br /> 1. The device and 3D finger individuation task are major strengths of the study, setting this work apart from previous work and enabling novel insights.<br /> 2. The analyses are thorough and well-designed. Of particular value is the analysis of finger force control in 3D Cartesian space and the use of Representational Similarity Analysis of finger enslavement pattern magnitude and shape.<br /> 3. A major contribution of this work is the teasing out of the effects of top-down factors versus biomechanical constraints affecting impairment of finger force control.<br /> 4. I found the discussion about complexity of finger control (lines 541-553) very interesting. The topic of adaptability of finger coactivation patterns in the context of dexterous manipulation is a key topic in robotics and neuroscience. In robotics, finger forces are decomposed into a grasp and manipulation component. In human motor control studies, this approach has identified their temporal coordination (work by Latash and Zatsiorsky, e.g., Gao et al., 2005) and potentially distinct sensorimotor control mechanisms (Wu and Santello, 2023). The authors might wish to discuss how coactivation patterns might contribute to the coordination of grasp and manipulation forces.

Weaknesses:<br /> None (only minor clarifications, e.g., the term biomechanical constraints should be defined earlier in the paper).

Reviewer #2 (Public Review):

Summary:

In recent years, Auxin treatment has been frequently used for inducing targeted protein degradation in Drosophila and various other organisms. This approach provides a way to acutely alter the levels of specific proteins. In this manuscript, the authors examine the impact of Auxin treatment and provide strong evidence that Auxin treatment elicits alterations in feeding activity, survival rates, lipid metabolism, and gene expression patterns. Researchers should carefully consider these effects to design experiments and interpret their data.

Strengths:

Regarding the widespread usage of Auxin mediated gene manipulation method, it is important to address whether the application of Auxin itself causes any physiological changes. The authors provide evidence of several Auxin effects. Experiments are suitably designed with appropriate sample size and data analysis methods.

Weaknesses:

The provided information is limited and not very helpful for many applications. For example, although authors briefly mentioned aging research, feeding behavior, and lipid data, RNA seq data are provided only for short-term (48 hours) treatment. Especially, since ovary phenotype was examined with long-term treatment (15 days), authors should also show other data for long-term treatment as well.

Although the authors show that Auxin causes a change in gene expression patterns and suggests the possible alteration of Gal4 expression levels, no cell-type-specific data is provided. It would be informative if the authors could examine the expression level of major Gal4 drivers.<br /> Authors should discuss how severe these changes are by comparing them with other treatments or conditions, such as starvation or mutant data (ideally, comparing with reported data or their own data if any?).

Reviewer #2 (Public Review):

Summary:<br /> The work is potentially interesting as it outlines the role of satellite cells in supporting the functional decline of skeletal muscle due to the denervation process. In this context the authors analyze the functional and molecular characteristics of satellite cells in different muscle types differently affected by the degenerative process in the ALS model.

Strengths:<br /> The work illustrates a relevant aspect of the differences in stem cell potential in different skeletal muscles in a mouse model of the disease through a considerable amount of data and experimental models.

Weaknesses:<br /> However, there are some criticisms of the structuring of the results:

It is not clear how many animals were used in each experimental group (Figs 1 and 2, Fig. 2-9). In particular, it is unclear whether the dots in the histograms represent biological or technical replicates. Furthermore, the gender used in experimental groups is never specified. This last point appears to be important considering the gender differences observed in the SOD1G93A mouse model.

The first paragraph of the results lacks a functional analysis of the motor decline of the animals after the administration of sodium butyrate. The authors, in fact, administered NaBu around 90 days of age while in previous work the drug had been administered at a pre-symptomatic age. It would therefore be useful, to make the message more effective, to characterize the locomotor functions of the treated animals in parallel with the histological evidence of the integrity of the NMJ.

Figure 5 should be completed with the administration of NaBu also to the satellite cells isolated from the WT mouse, the same for figure 9 where AAV-CMV-Cxcl12 transduction of WT myotubes is missing.

In the experiment illustrated in Figure 8, treatment of cell cultures with NaBu would improve the outcome as well as the interference of Cxcl12 expression in myotubes derived from G93A EOM SC (Fig.9) would strengthen the specificity of this protein in axon guidance in this NMJ typical of a spared muscle in ALS.

In the "materials and methods" section the paragraph relating to the methods used for statistical analysis is missing.

Reviewer #2 (Public Review):

It is well known that as seasonal day length increases, molecular cascades in the brain are triggered to ready an individual for reproduction. Some of these changes, however, can begin to occur before the day length threshold is reached, suggesting that short days similarly have the capacity to alter aspects of phenotype. This study seeks to understand the mechanisms by which short days can accomplish this task, which is an interesting and important question in the field of organismal biology and endocrinology.

The set of studies that this manuscript presents is comprehensive and well-controlled. Many of the effects are also strong and thus offer tantalizing hints about the endo-molecular basis by which short days might stimulate major changes in body condition. Another strength is that the authors put together a compelling model for how different facets of an animal's reproductive state come "on line" as day length increases and spring approaches. In this way, I think the authors broadly fulfill their aims.

Reviewer #2 (Public Review):

As I indicated in the initial review, the experiments are well conceived and executed, and the data are clear. I also agree with the authors that this work represents a key first step toward understanding how Notch signaling contributes to temporal control of fly neuroblasts. It is my opinion that the authors fall short of demonstrating how Notch signaling and temporal identity genes at the chromatin levels. I find this disappointing given the availability of various tools for looking at dynamic regulation of gene activity at high resolution. Given these weaknesses, my opinion is that the study is descriptive and lacks mechanistic explanation.

Reviewer #2 (Public Review):

The phenotypic instability of in vitro-induced Treg cells (iTregs) has been discussed for a long time, mainly in the context of the epigenetic landscape of Treg-signature genes; e.g. Treg-specifically CpG-hypomethylated Foxp3 CNS2 enhancer region. However, it has been insufficiently understood the upstream molecular mechanisms, the particularity of intracellular signaling of natural Treg cells, and how they connect to stable/unstable suppressive function.

Huiyun Lv et al. addressed the issue of phenotypic instability of in vitro-induced regulatory T cells (iTregs), which is a different point from the physiological natural Treg cells and an obstacle to the therapeutic use of iTreg cells. The authors focused on the difference between iTreg and nTreg cells from the perspective of their control of store-operated calcium entry (SOCE)-mediated cellular signaling, and they clearly showed that the sustained SOCE signaling in iTreg and nTreg cells led to phenotypic instability. Moreover, the authors pointed out the correlation between the incomplete conversion of chromatin configuration and the NFAT-mediated control of effector-type gene expression profile in iTreg cells. These findings potentially cultivate our understanding of the cellular identity of regulatory T cells and may shed light on the therapeutic use of Treg cells in many clinical contexts.

The authors demonstrated the biological contribution of Ca2+ signaling with the variable methods, which ensure the reliability of the results and the claims of the authors. iTreg cells sustained SOCE-signaling upon stimulation while natural Treg cells had lower strength and shorter duration of SOCE-signaling. The result was consistent with the previously proposed concept; a certain range of optimal strength and duration of TCR-signaling shape the Treg generation and maintenance, and it provides us with further in-depth mechanistic understanding.

In the later section, authors found the incomplete installment of Treg-type open chromatin landscape in some effector/helper function-related gene loci in iTreg cells. These findings propose the significance of focusing on not only the "Treg"-associated gene loci but also "Teffector-ness"-associated regions to determine the Treg conversion at the epigenetic level.

Limitations;<br /> ・NFAT regulation did not explain all of the differences between iTregs and nTregs, as the authors mentioned as a limitation.<br /> ・Also, it is still an open question whether NFAT can directly modulate the chromatin configuration on the effector-type gene loci, or whether NFAT exploits pre-existing open chromatin due to the incomplete conversion of Treg-type chromatin landscape in iTreg cells. The authors did not fully demonstrate that the distinct pattern of chromatin regional accessibility found in iTreg cells is the direct cause of an effector-type gene expression.

Reviewer #2 (Public Review):

Summary:

Chew et al describe interaction of the flavivirus protein NS1 with HDL using primarily cryoEM and mass spec. The NS1 was secreted from dengue virus infected Vero cells, and the HDL were derived from the 3% FBS in the culture media. NS1 is a virulence factor/toxin and is a biomarker for dengue infection in patients. The mechanisms of its various activities in the host are incompletely understood. NS1 has been seen in dimer, tetramer and hexamer forms. It is well established to interact with membrane surfaces, presumably through a hydrophobic surface of the dimer form, and the recombinant protein has been shown to bind HDL. In this study, cryoEM and crosslinking-mass spec are used to examine NS1 secreted from virus-infected cells, with the conclusion that the sNS1 is predominantly/exclusively HDL-associated through specific contacts with the ApoA1 protein.

Strengths:

The experimental results are consistent with previously published data.

Weaknesses:

CryoEM:

Some of the neg-stain 2D class averages for sNS1 in Fig S1 clearly show 1 or 2 NS1 dimers on the surface of a spherical object, presumably HDL, and indicate the possibility of high-quality cryoEM results. However, the cryoEM results are disappointing. The cryo 2D class averages and refined EM map in Fig S4 are of poor quality, indicating sub-optimal grid preparation or some other sample problem. Some of the FSC curves (2 in Fig S7 and 1 in Fig S6) have extremely peculiar shapes, suggesting something amiss in the map refinement. The sharp drop in the "corrected" FSC curves in Figs S5c and S6c (upper) indicate severe problems. The stated resolutions (3.42 & 3.82 Å) for the sNS1ts-Fab56.2 are wildly incompatible with the images of the refined maps in Figs 3 & S7. At those resolutions, clear secondary structural elements should be visible throughout the map. From the 2D averages and 3D maps shown in the figures this does not seem to be the case. Local resolution maps should be shown for each structure.

The samples were clearly challenging for cryoEM, leading to poor quality maps that were difficult to interpret. None of the figures are convincing that NS1, Ab56.2 or Fab56.2 are correctly fit into EM maps. There is no indication of ApoA1 helices. Details of the fit of models to density for key regions of the higher-resolution EM maps should be shown and the models should be deposited in the PDB. An example of modeling difficulty is clear in the sNS1ts dimer with bound Fab56.2 (figs 3c & S7e). For this complex, the orientation of the Fab56.2 relative to the sNS1ts dimer in this submission (Fig 3c) is substantially different than in the bioRxiv preprint (Fig 3c). Regions of empty density in Fig 3c also illustrate the challenge of building a model into this map.

Mass spec:

Crosslinking-mass spec was used to detect contacts between NS1 and ApoA1, providing strong validation of the sNS1-HDL association. As the crosslinks were detected in a bulk sample, they show that NS1 is near ApoA1 in many/most HDL particles, but they do not indicate a specific protein-protein complex. Thus, the data do not support the model of an NS1-ApoA1 complex in Fig 4d. Further, a specific NS1-ApoA1 interaction should have evidence in the EM maps (helical density for ApoA1), but none is shown or mentioned. If such exists, it could perhaps be visualized after focused refinement of the map for sNS1ts-HDL with Fab56.2 (Fig S7d). The finding that sNS1-ApoA1 crosslinks involved residues on the hydrophobic surface of the NS1 dimer confirms previous data that this NS1 surface engages with membranes and lipids.

Sample quality:

The paper lacks any validation that the purified sNS1 retains established functions, for example the ability to enhance virus infectivity or to promote endothelial dysfunction. Peculiarities include the gel filtration profiles (Fig 2a), which indicate identical elution volumes (apparent MWs) for sNS1wt-HDL bound to Ab562 (~150 kDa) and to the ~3X smaller Fab56.2 (~50 kDa). There should also be some indication of sNS1wt-HDL pairs crosslinked by the full-length Ab, as can be seen in the raw cryoEM micrograph (Fig S5b).

Obtaining high quality structures is often more demanding of sample integrity than are activity assays. Given the low quality of the cryoEM maps, it's possible that the acidification step in immunoaffinity purification damaged the HDL complex. No validation of HDL integrity, for example with acid-treated HDL, is reported. Acid treatment is perhaps discounted by a statement (line 464) that another group also used immunoaffinity purification in a recent study (ref 20) reporting sNS1 bound to HDL. However the statement is incorrect; the cited study used affinity purification via a strep-tag on recombinant sNS1.

Discussion:

The Discussion reflects a view that the NS1 secreted from virus-infected cells is a 1:1 sNS1dimer:HDL complex with the specific NS1-ApoA1 contacts detected by crosslinking mass spec. This is inconsistent with both the neg-stain 2D class average with 2 sNS1 dimers on an HDL (Fig S1c) and with the recent study of Flamand & co-workers showing 1-3 NS1 dimers per HDL (ref 20). It is also ignores the propensity of NS1 to associate with membranes and lipids. It is far more likely that NS1 association with HDL is driven by these hydrophobic interactions than by specific protein-protein contacts. A lengthy Discussion section (lines 461-522) includes several chemically dubious or inconsistent statements, all based on the assumption that specific ApoA1 contacts are essential to NS1 association with HDL and that sNS1 oligomers higher than the dimer necessarily involve ApoA1 interaction, conclusions that are not established by the data in this paper.

Reviewer #2 (Public Review):

Summary: Larouche et al show that TEs are broadly expressed in thymic cells, especially in mTECs and pDCs. Their data suggest a possible involvement of TEs in thymic gene regulation and IFN-alpha secretion. They also show that at least some TE-derived peptides are presented by MHC-I in the thymus.

Strengths: The idea of high/broad TE expression in the thymus as a mechanism for preventing TE-mediated autoimmunity is certainly an attractive one, as is their involvement in IFN-alpha secretion therein. The analyses and experiments presented here are therefore a very useful primer for more in-depth experiments, as the authors point out towards the end of the discussion.

Weaknesses: Throughout the manuscript, most conclusions are presented as proven causal relationships that the current data do not demonstrate. In the abstract, results, and discussion, the following conclusions are drawn that are not supported by the data: a) TEs interact with multiple transcription factors in thymic cells, b) TE expression leads to dsRNA formation, activation of RIG-I/MDA5 and secretion of IFN-alpha, c) TEs are regulated by cell proliferation and expression of KZFPs in the thymus. All these statements derive from correlations. Only one TF has ChIP-seq data associated with it, dsRNA formation and/or IFN-alpha secretion could be independent of TE expression, and whilst KZFPs most likely regulate TEs in the thymus, the data do not demonstrate it. The authors also seem to suggest that AIRE, FEZF2, and CHD4 regulate TEs directly, but binding is not shown. The manuscript needs a thorough revision to be absolutely clear about the correlative nature of the described associations.

On the technical side, there are many dangers about analysing RNA-seq data at the subfamily level and without stringent quality control checks. Outputs may be greatly confounded by pervasive transcription (see PMID 31425522), DNA contamination, and overlap of TEs with highly expressed genes. Whether TE transcripts are independent units or part of a gene also has important implications for the conclusions drawn. I would say that for most purposes of this work, an analysis restricted to independent TE transcripts, with appropriate controls for DNA contamination, would provide great reassurances that the results from subfamily-level analyses are sound. Showing examples from the genome browser throughout would also help.

Reviewer #2 (Public Review):

Summary:

In this work, Mohamed Y. El-Naggar and co-workers present a detailed electronic characterization of cable bacteria from Southern California freshwater sediments. The cable bacteria could be reliably enriched in laboratory incubations, and subsequent TEM characterization and 16S rRNA gene phylogeny demonstrated their belonging to the genus Candidatus Electronema. Atomic force microscopy and two-point probe resistance measurements were then used to map out the characteristics of the conductive nature, followed by microelectrode four-probe measurements to quantify the conductivity.

Interestingly, the authors observe that some freshwater cable bacteria filaments displayed a higher degree of robustness upon oxygen exposure than what was previously reported for marine cable bacteria. Finally, a single nanofiber conductivity on the order of 0.1 S/cm is calculated, which matches the expected electron current densities linking electrogenic sulphur oxidation to oxygen reduction in sediment. This is consistent with hopping transport.

Strengths and weaknesses:

A comprehensive study is applied to characterise the conductive properties of the sampled freshwater cable bacteria. Electrostatic force microscopy and conductive atomic force microscopy provide direct evidence of the location of conductive structures. Four-probe microelectrode devices are used to quantify the filament resistance, which presents a significant advantage over commonly used two-probe measurements that include contributions from contact resistances. While the methodology is convincing, I find that some of the conclusions seem to be drawn on very limited sample sizes, which display widely different behaviour. In particular:

The authors observe that the conductivity of freshwater filaments may be less sensitive to oxygen exposure than previously observed for marine filaments. This is indeed the case for an interdigitated array microelectrode experiment (presented in Figure 5) and for a conductive atomic force microscopy experiment (described in line 391), but the opposite is observed in another experiment (Figure S1). It is therefore difficult to assess the validity of the conclusion until sufficient experimental replications are presented.

The calculation of a single nanofiber conductivity is based on experiment and calculation with significant uncertainty. E.g. for the number of nanofibres in a single filament that varies depending on the filament size (Frontiers in microbiology, 2018, 9: 3044.), and the measured CB resistance, which does not scale well with inner probe separation (Figure 5). A more rigorous consideration of these uncertainties is required.

Reviewer #2 (Public Review):

The authors set out to identify CAPs (Candidate Adaptive Polymorphyisms), i.e., simply put mutations that carry a potential functional advantage, and utilize computational methods based on the perturbation of C-alpha positions with an Elastic Network Model to determine if dynamics of CAP residues are different in any way.

In my opinion this manuscript *may* suffer from fundamental flaws in the detection of CAPs, and does not provide enough analysis and discussion to determine if the methodology is applicable. A highly expanded and rewritten manuscript may help clarify the results. Lastly, the authors severely ignore the vast literature and results already in the public domain, not only with respect to the use of normal-mode analysis methods as well as the detection of functionally relevant mutations in general and to understand the evolution of the SARS-CoV-2 Spike protein in particular.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript uses an interesting abstraction of epigenetic inheritance systems as partially stable states in biological networks. This follows on previous review/commentary articles by the author. Most of the molecular epigenetic inheritance literature in multicellular organisms implies some kind of templating or copying mechanisms (DNA or histone methylation, small RNA amplification) and does not focus on stability from a systems biology perspective. By contrast, theoretical and experimental work on the stability of biological networks has focused on unicellular systems (bacteria), and neglects development. The larger part of the present manuscript (Figures 1-4) deals with such networks that could exist in bacteria. The author classifies and simulates networks of interacting entities, and (unsurprisingly) concludes that positive feedback is important for stability. This part is an interesting exercise but would need to be assessed by another reviewer for comprehensiveness and for originality in the systems biology literature. There is much literature on "epigenetic" memory in networks, with several stable states and I do not see here anything strikingly new.

An interesting part is then to discuss such networks in the framework of a multicellular organism rather than dividing unicellular organisms, and Figure 5 includes development in the picture. Finally, Figure 6 makes a model of the feedback loops in small RNA inheritance in C. elegans to explain differences in the length of inheritance of silencing in different contexts and for different genes and their sensitivity to perturbations. The proposed model for the memory length is distinct from a previously published model by Karin et al. (ref 49).

Strengths:<br /> A key strength of the manuscript is to reflect on conditions for epigenetic inheritance and its variable duration from the perspective of network stability.

Weaknesses:<br /> - I found confusing the distinction between the architecture of the network and the state in which it is. Many network components (proteins and RNAs) are coded in the genome, so a node may not disappear forever.

- From the Supplementary methods, the relationship between two nodes seems to be all in the form of dx/dt = Kxy . Y, which is just one way to model biological reactions. The generality of the results on network architectures that are heritable and robust/sensitive to change is unclear. Other interactions can have sigmoidal effects, for example. Is there no systems biology study that has addressed (meta)stability of networks before in a more general manner?

- Why is auto-regulation neglected? As this is a clear cause of metastable states that can be inherited, I was surprised not to find this among the networks.

- I did not understand the point of using the term "entity-sensor-property". Are they the same networks as above, now simulated in a computer environment step by step (thus allowing delays)?

- The final part applies the network modeling framework from above to small RNA inheritance in C. elegans. Given the positive feedback, what requires explanation is how fast the system STOPs small RNA inheritance. A previous model (Karin et al., ref. 49) builds on the fact that factors involved in inheritance are in finite quantity hence the different small RNAs "compete" for amplification and those targeting a given gene may eventually become extinct.

The present model relies on a simple positive feedback that in principle can be modulated, and this modulation remains outside the model. A possibility is to add negative regulation by factors such as HERI-1, that are known to limit the duration of the silencing.

The duration of silencing differs between genes. To explain this, the author introduces again outside the model the possibility of piRNAs acting on the mRNA, which may provide a difference in the stability of the system for different transcripts.<br /> At the end, I do not understand the point of modeling the positive feedback.

- From the initial analysis of abstract networks that do not rely on templating, I expected a discussion of possible examples from non-templated systems and was a little surprised by the end of the manuscript on small RNAs.

Reviewer #2 (Public Review):

The manuscript presents a valuable investigation of genetic associations related to plant resistance against the turnip mosaic virus (TuMV) using Arabidopsis thaliana as a model. The study infects over 1,000 A. thaliana inbred lines with both ancestral and evolved TuMV and assesses four disease-related traits: infectivity, disease progress, symptom severity, and necrosis. The findings reveal that plants infected with the evolved TuMV strain generally exhibited more severe disease symptoms than those infected with the ancestral strain. However, there was considerable variation among plant lines, highlighting the complexity of plant-virus interactions.

A major genetic locus on chromosome 2 was identified, strongly associated with symptom severity and necrosis. This region contained several candidate genes involved in plant defense against viruses. The study also identified additional genetic loci associated with necrosis, some common to both viral isolates and others specific to individual isolates. Structural variations, including transposable element insertions, were observed in the genomic region linked to disease traits.

Surprisingly, the minor allele associated with increased disease symptoms was geographically widespread among the studied plant lines, contrary to typical expectations of natural selection limiting the spread of deleterious alleles. Overall, this research provides valuable insights into the genetic basis of plant responses to TuMV, highlighting the complexity of these interactions and suggesting potential avenues for improving crop resilience against viral infections.

Overall, the manuscript is well-written, and the data are generally high-quality. The study is generally well-executed and contributes to our understanding of plant-virus interactions. I suggest that the authors consider the following points in future versions of this manuscript:

1. Major allele and minor allele definition: When these two concepts are mentioned in the figure, there is no clear definition of the two words in the text. Especially for major alleles, there is no clear definition in the whole text. It is recommended that the author further elaborate on these two concepts so that readers can more easily understand the text and figures.

2. Possible confusion caused by three words (Major focus / Major association and major allele): Because there is no explanation of the major allele in the text, it may cause readers to be confused with these two places in the text when trying to interpret the meaning of major allele: major locus (line 149)/ the major association with disease phenotypes (line 183).

3. Discussion: The authors could provide a more detailed discussion of how the research findings might inform crop protection strategies or breeding programs.

Reviewer #2 (Public Review):

Faress et al. ask the question of how synaptic plasticity (i.e. long-term potentiation, LTP) induced at different time points and different synapses in relationship to learning can transform memories supported by these circuits. The authors adopted an experimental design developed by Nabavi et al, 2014 and used male mice to optogenetically induce a weak fear memory in thalamo-LA circuits by pairing an optical conditioned stimulus (CS) at thalamo-LA synapses with a footshock unconditioned stimulus (US), or subjected the mice to an unpairing of the opto-CS and the footshock US. They then investigated how homosynaptic (thalamo-LA)- or heterosynaptic (cortico-LA) high-frequency stimulation (HFS) -that would induce LTP- delivered at different time points before and after learning can transform the opto-fear memory by using state of the art in vivo dual-wavelength optogenetics. They find that homosynaptic HFS delivered before or after learning transforms weak memories into stronger ones, whereas heterosynaptic HFS can do so when delivered immediately after learning. Both homo- and hetero-HFS delivered after unpairing produce a 24 h fear memory for the opto-CS. Lastly, they show that synaptic potentiation accompanies the strengthening of fear memory induced by hetero HFS in freely moving mice.

The significance of the study lies in showing in vivo that plasticity induced at different times or different synapses than those engaged during learning can modify memory and the synaptic strength in a synaptic pathway related to that memory. While heterosynaptic and timing-dependent effects in synaptic plasticity have been described largely ex vivo on shorter time scales, the discovery of lasting behavioral effects on memory is novel.

A strength of the study is that it uses well-defined and elegant optogenetic manipulations of distinct neural pathways in awake-behaving mice combined with in vivo recordings, which allows the authors to directly manipulate and monitor synaptic strength and memory.

The conclusions of this paper are mostly well supported by the data, but there are some aspects that should be resolved:

1. The experimental design for assessing the effects of applying HFS 24 h after conditioning should be clarified, and it should be re-evaluated which experimental groups can be compared and how. The experimental schemes in Figs. 1 and 3 (and Fig. 4e and extended data 4a,b) show that one group of animals was subjected to retrieval in the test context at 24 h, then received HFS, which was then followed by a second retrieval session. With this design, it remains unclear what the HFS impacts when it is delivered between these two 24 h memory retrieval sessions. It would be nice to see these data parsed out in a clean experimental design for all experiments (in Figs 1, 3, and 4), that means 4 groups with different treatments that are all tested only once at 24 h, and the appropriate statistical tests (ANOVA). This would also avoid repeating data in different panels for different pairwise comparisons (Fig 1, Fig 3, Fig 4, and extended Fig 4).

2. The final experiment (Fig. 5a-c, extended data 5c) combines behavioral assessments with in vivo LFP recordings before and 24 h after hetero-HFS. While this experiment is demanding, it seems a bit underpowered and not well-controlled. It would be critical to know if LFPs change over 24 h in animals in which memory is not altered by HFS, and to see correlations between memory performance and LFP changes, as two animals displayed low freezing levels. Also, the slice experiments (Fig. 5d-f) are not well aligned with the in vivo experiments (juvenile animals, electrical vs. opto stimulation, different HFS protocols, timescale of hours). They would suggest that thalamo-LA potentiation occurs directly after learning+HFS (which could be tested) and is maintained over 24 h.

3. The statistical analyses need to be clarified. All statements should be supported with statistical testing (e.g. extended data 5c, pg 7 stats are missing). The specific tests should be clearly stated throughout. For ANOVAs, the post-hoc tests and their outcomes should be stated. In some cases, 2-way ANOVAs were performed, but it seems there is only one independent variable, calling for one-way ANOVA.

4. There are a number of details in the methods and procedures that need to be elaborated on and clarified for the reader. All of them will be listed in the recommendations to the authors.

Reviewer #2 (Public Review):

A number of previous reports have demonstrated that theta synchrony between the hippocampus (HPC) and prefrontal cortex (PFC) is associated with correct performance on spatial working memory tasks. The main goal of the current study is to examine this relationship by initiating trials either randomly (as is typically done) or during periods of high or low PFC-HPC coherence. To this end, they develop a 'brain-machine interface' (BMI) that provides real-time estimates of PFC-HPC theta coherence, which are then used to control trial onset using an automated figure-eight maze. Their main finding is that choice accuracy is significantly higher on trials initiated when theta coherence is high whereas performance on low coherence trials does not differ from randomly initiated control trials. They also observe a similar result using a non-working memory task in the same maze.

Overall the main experiments (Figures 1-4) are well designed and the BMI approach is convincingly validated. There are also appropriate controls and analyses to rule out behavioral confounds and the results clearly presented. The idea of triggering trial onset based on brain activity is an interesting idea and helps to examine how extremes in the distribution of brain states are associated with behavior, something that might be more difficult to examine if trials are initiated randomly. As such, the BMI is an interesting approach for studying the neuronal basis of behavior that could potentially be applied beyond the particular field of the study, something the authors could perhaps have elaborated on more.

That being said, although the authors have elegantly revealed an association between PFC-HPC theta synchrony and behavior using their BMI approach, it is not apparent whether these results add substantially to previous reports of similar associations, including from the author's own work. The authors sometimes seem to claim that they do; for example, in the discussion, after describing previous studies that reported an association between PFC-HPC theta synchrony and behavior, they raise the reasonable question "did mPFC-hippocampal theta coherence lead to, or coincide with, correct choice outcomes?" What they subsequently write gives the impression that their study has somehow addressed the question, whereas in fact their results still leave this question open. For example, it is entirely possible that during high-coherence trials an unobserved neural process is influencing both coherence and task performance. The authors could have made a more convincing case as to why their correlative results go beyond similar findings from previous studies, perhaps by including additional analysis to strengthen their case.

Sometimes, the authors also seem to suggest that their results establish a causal relationship between synchrony and behavior, for example when they say that they have "demonstrated for the first time that strong mPFC-hippocampal theta coherence ENHANCES memory-guided choice" (line 557, my emphasis). However, causal manipulations of PFC-HPC synchrony would be required to make such claims. I am not suggesting that the lack of such data is necessarily a weakness of the study, only that causal claims are not supported by the author's results.

In addition to the behavioral results described above, the authors also examine how HPC-PFC synchrony modulates synchrony with the ventromedial thalamus (VMT; Figure 5) and how optogenetic modulation of the VMT influences PFC-HPC synchrony (Figure 6). However, these results feel somewhat more preliminary and their relationship to the other findings in the manuscript is not always clear. For example, given that the authors demonstrate that "Prefrontal-hippocampal theta synchronization modulates prefrontal-thalamic interactions" (Figure 5) I would rather have expected the authors to manipulate HPC and/or PFC and see how this affects VMT in Figure 6. It is also difficult to draw strong conclusions about the effects of optogenetic VMT stimulation since the results presented by the authors come from only 2 rats (Figure 6D-K) and therefore feel somewhat anecdotal. I could also not find any statistical test supporting the increase in the proportion of phase-locked neurons during high theta states shown in Figure 5K.

Reviewer #2 (Public Review):

This interesting research commendably revealed irregular sleep-wake patterns are associated with higher mortality risk. However, as authors acknowledged, the analysis can not to accurately identify the cause and effect. In my opinion, the causality is important for this topic, cuz, sleep regularity and health (e.g. chronic disease) were long-term simultaneous status. especially given the participants are older. I suggest that the author could utilize MR analysis to find out for more evidence.

Reviewer #2 (Public Review):

Hage et al examine how the foraging behavior of marmoset monkeys in a laboratory setting systematically takes into account the reward value and anticipated effort cost associated with the acquisition and consumption of food. In an interesting comprehensive framework, the authors study how experimental and natural variation of these factors affect both the decisions and actions necessary to gather and accumulate food, as well as the actions necessary to consume the food.

The manuscript proposes a computational model of how the monkeys may guide all these aspects of behavior, by maximizing a food capture rate that trades off the food that can be gathered with the effort and duration of the underlying actions. They use this model to derive qualitative predictions for how monkeys should react to an increase in the effort associated with food consumption: Monkeys should work longer before deciding to consume the accumulated food, but should move more slowly. The model also predicts that monkeys should show a different reaction to an increase in reward value of the food, also working longer but moving faster. The authors test these predictions in an interesting experimental setup that requires monkeys to collect small increments of food rewards for successful eye movements to targets. The monkeys can decide freely when to interrupt work and consume the accumulated food, and the authors measure the speed of the eye movements involved in the food acquisition as well as the tongue movements involved in the food consumption.

By and large, the behavioral findings fall in line with the qualitative model predictions: When the effort involved in food consumption increases, monkeys collect more food before deciding to consume it, and they move slower both during food acquisition and food consumption. In a second test, the authors approximate the effects of reward value of the food at stake, by comparing monkey behavior during different days with natural variations in body weight. These quasi-experimental increases in the reward value of food also lead to longer work times before consumption, but to faster movements during food consumption. Finally, the authors show that these effects correlate with pupil size, with pupils dilating more for low-effort foraging actions with increased saccade speed and decreased work duration. The authors conclude that the effort associated with anticipated actions can lead to changes in global brain state that simultaneously affect decisions and action vigor.

The paper proposes an interesting model for how one unified action policy may simultaneously affect multiple types of decisions and movements involved in foraging. The methods employed to measure behavior and test these predictions are generally sound, and the paper is well written.

Reviewer #2 (Public Review):

Summary:<br /> This research shows compelling and detailed evidence showing that aging influences intrinsic membrane properties of peripheral sympathetic motor neurons such that they become more excitable. Furthermore, the authors present convincing evidence that the oral administration of the anti-aging drug Rapamycin partially reversed hyperexcitability in aged neurons. This study also investigates the molecular mechanisms underlying age-associated hyperexcitability in mouse sympathetic motor neurons. In that regard, the authors found an age-associated reduction of an outward current having properties similar to KCNQ2/Q3 potassium current. They suggested a reduction of KCNQ2/Q3 current density in aged neurons as a potential mechanism behind their overactivity.

Strengths:<br /> Detailed and rigorous analysis of electrical responses of peripheral sympathetic motor neurons using electrophysiology (perforated patch and whole-cell recordings). Most of the conclusions of this paper are well supported by the data.

Weaknesses:<br /> 1) The identity of the age-associated reduced current as KCNQ2/Q3 is not corroborated by pharmacology (blocking the current with the specific blocker XE-991).<br /> 2) The manuscript does not include a direct test of the reduction of KCNQ current as the mechanism behind age-induced hyperexcitability.

Reviewer #2 (Public Review):

Summary<br /> This work investigates how multiple regulatory elements combine to regulate gene expression. The authors use an episomal reporter assay which measures the transcriptional output of the reporter under the regulation of an enhancer-enhancer-promoter triple. The authors test all combinations of 8 promoters and 59 enhancers in this assay. The main finding is that enhancer pairs generally combine additively on reporter output. The authors also find that the extent to which enhancers increase reporter output is inversely related to the intrinsic strength of the promoter.

This manuscript presents a compact experiment that investigates an important open question in gene regulation. The results and data will be of interest to researchers studying enhancers. Given that my expertise is in modeling and computation, I will take the experimental results at face value and focus my review on the interpretation of the results and the computational methodology. I find the result of additivity between enhancers to be well supported. The findings on differential responsiveness between promoters are very interesting but the interpretation of such responses as 'non-linear' or 'following a power-law' may be misleading. More broadly, I think a more rigorous description of the mathematical methodology would increase the clarity and accessibility of this manuscript. A major unanswered question is whether the findings in this study apply to enhancers in their native genomic context. Regardless, investigating such questions in an episomal reporter assay is valuable.

Main comments<br /> Applicability to native genomic context: The applicability of the results in this paper to enhancers in their native genomic context is unclear. As the authors state in the discussion section, the reporter gene is not integrated into the genome, the spacing between enhancers does not match their native context etc. It is thus unclear whether this experimental design is able to detect the non-additivity between enhancers which is known to be present in the genome. This could be investigated by testing the enhancer-enhancer-promoter tuples for which non-additivity has been observed in the genome (references are given in the introduction) in this assay.

Interpretation of promoter responses as non-linear and following a power-law: In Fig 5, the authors demonstrate that enhancer-enhancer pairs boost reporter output more for weak promoters as opposed to strong promoters. I agree the data supports this finding, but I find the interpretation of such data as promoters scaling enhancers according to a power-law (as stated in the abstract) to be misleading. As mentioned on line 297, it is not possible to define an intrinsic measure of enhancer strength, thus the authors assign the base of the power-law to be the average boost index of the enhancer-enhancer pair across the 8 promoters. But this measure incorporates some aspect of a promoter and is not solely a property of enhancers. It would also be useful to know whether the results in Fig 5 apply to only enhancer-enhancer-promoter triples or also to enhancer-promoter pairs.

Enhancer-promoter selectivity: As a follow-up to a previous study (Martinez-Ara et al, Molecular Cell 2022) the authors mention that the data in this study also shows that enhancers show selectivity for certain promoters. The authors mention that both studies use the same statistical methodology and the data in this study is consistent with the data from the 2022 paper. However, I think the statistical methodology in both studies needs further exposition. This section of the review is thus meant to ensure that I understand the author's methodology, to guide the reader in understanding how the authors define 'selectivity', and to probe certain assumptions underlying the methodology.

My understanding of the approach is as follows: The authors consider an enhancer to be not selective if its 'boost index' is the same across a set of promoters. 'Boost index' is defined to be the ratio of the reporter output with the enhancer and promoter divided by the reporter output with just the promoter. Conceptually, I think that considering the boost index is a reasonable way to quantify selectivity.

The authors use a frequentist approach to classify each enhancer as selective or not selective. The null hypothesis is that the boost index of the enhancer is equal across a set of promoters. This can be visualized in Fig. 2C where the null hypothesis is that the mean of each vertical distribution is equal. Note that in Figure S4 of this paper (and in Figure 4B of their 2022 paper) the within-group variance is not plotted. Statistical significance is assessed using a Welch F-test. This is a parametric test that assumes that the observations within each vertical distribution in Fig 2C are normally distributed (this test does allow for heteroskedasticity - which means that the variance may differ within each vertical distribution). Does the normality assumption hold? This analysis should be reported. If this assumption does not hold, is the Welch test well calibrated?

Reviewer #2 (Public Review):

Human STEAPs form a family of transmembrane heme-bound proteins. They are implicated in cancer given their high expression levels in tumor cells. Previous work has revealed that STEAPs 1-4 are iron and copper reductases. The recent structure determination of STEAP1 and STEAP4 unveiled their trimeric arrangement. STEAP1 is an outlier because it lacks the cytosolic reductase domain present in STEAPs 2-5. The present work adds to our knowledge of the family. It reports on the cryoEM structure of STEAP2 that is similar to the known structures of STEAP4 and STEAP1. The structural analysis provides additional support to a FAD-dependent heme-reduction mechanism whereby FAD oscillates between two conformations. The excellent kinetics experiments show that STEAP1 can be promiscuous regarding the source of electron donors that it can use. Indeed, cytochrome b5 can directly reduce the heme prosthetic group of STEAP1 thereby establishing an electron transfer chain that conveys electrons from NADP(P)H to the extracellular iron. Remarkably, STEAP1 can also accept electrons from free reduced FAD. Most interestingly, the manuscript demonstrates that STEAP2 can be a source of reduced FAD so that STEAP2 can create the reducing power needed for its own activity and the activity of STEAP1. This work further convincingly shows that STEAP1 can reduce iron whereas STEAP2 is less effective in iron reduction. The manuscript indicates that STEAP2 might accept other substrates providing a hint about the distinct biochemical and physiological roles of the STEAP paralogs. The manuscript does not address this point that remains open for further investigations. Aside from this minor weakness, the manuscript will advance the fields of STEAP and iron biochemistry. It has benefited from the advice given by the Reviewers leading to a high-quality presentation and data analysis.

Reviewer #2 (Public Review):

Summary:<br /> Deng et al. investigate, for the first time to my knowledge, the role that hippocampal dentate gyrus mossy cells play in Fragile X Syndrome. They provide strong evidence that, in slice preparations from Fmr1 knockout mice, mossy cells are hypoactive due to increased Kv7 function whereas granule cells are hyperactive compared to slices from wild-type mice. They provide indirect evidence that the weakness of mossy cell-interneuron connections contributes to granule cell hyperexcitability, despite converse adaptations to mossy cell inputs. The authors show that application of the Kv7 inhibitor XE991 is able to rescue granule cell hyperexcitability back to wild-type baseline, supporting the overall conclusion that inhibition of Kv7 in the dentate may be a potential therapeutic approach for Fragile X Syndrome. However, any claims regarding specific circuit-based intervention or analysis are limited by the exclusively pharmacological approach of the manipulations.

Strengths:<br /> Thorough electrophysiological characterization of mossy cells in Fmr1 knockout mice, a novel finding.

Their electrophysiological approach is quite rigorous: patched different neuron types (GC, MC, INs) one at a time within the dentate gyrus in FMR1 KO and WT, with and without 'circuit blockade' by pharmacologically inhibiting neurotransmission. This allows the most detailed characterization possible of passive membrane/intrinsic cell differences in the dentate gyrus of Fmr1 knockout mice.

Provide several examples showing the use of Kv7 inhibitor XE991 is able to rescue excitability of granule cell circuit in Fmr1 knockout mice (AP firing in the intact circuit, postsynaptic current recordings, theta-gamma coupling stimulation).

Weaknesses:<br /> The implications for these findings and the applicability of the potential treatment for the disorder in a whole animal are limited due to the fact that all experiments were done in slices.

The authors' interpretation of the word 'circuit-based' is problematic - there are no truly circuit-specific manipulations in this study due to the reliance on pharmacology for their manipulations. While the application of the Kv7 inhibitor may have a predominant effect on the circuit through changes to mossy cell excitability, this manipulation would affect many other cells within the dentate and adjacent brain regions that connect to the dentate that express Kv7 as well.

Reviewer #2 (Public Review):

Summary:<br /> In this paper, the authors investigated the relationship between menopause (including status, type, and age of onset) with measures of brain health, including cognition, Alzheimer's disease (including age of onset), and structural brain imaging.

Strengths:<br /> A key strength is the use of propensity matching to address the confound of age. However, further clarification and justification regarding the study design, methodology, reporting, and discussion of the results is required.

Weaknesses:<br /> Overall, the strength of evidence is uncertain/incomplete, given the methodological limitations present in the design, analyses, and reporting of results. The findings are useful, however, much of the relevant literature in this area is missing and the findings have therefore not been appropriately contextualised nor compared with previous results, including those using the same dataset.

Reviewer #2 (Public Review):

Summary:

The work of Poudel et al. identified potential causal mutations related to the successful emergence of the virulent USA300 community-associated MRSA clone within clonal complex 8. To achieve this, the authors employed a methodology that combines the genome-wide association studies (GWAS) with the inference of a transcriptional regulatory network (TRN) through the independent component analysis (ICA) method from publicly available transcriptomic data. Thus, they identified genes with altered expression in the iModulons calculated by ICA and enriched mutations obtained from the De Bruijn graph genome-wide association study (DBGWAS) in the USA300 strains versus non-USA300 strains. The results revealed a deletion of 38 base pairs, containing a binding site for the Fur repressor, and an A→T mutation, both occurring in the upstream region of the isdH gene, whose expression level in USA300 strains exhibited a general increase compared to the other group. IsdH encodes the iron-regulated surface determinant protein H, which plays a crucial role in iron acquisition from heme and immune system evasion - two essential processes for the pathogenicity of S. aureus.

Strengths:

The clonal complex 8 (CC8), one of the most prevalent among S. aureus, encompasses strains responsible for both community-associated MRSA infections (CA-MRSA) and healthcare-associated (HA) infections (HA-MRSA and HA-MSSA). Within the CC8, one of the most prominent lineages is USA300, which emerged in the early 2000s and has since become a leading cause of CA-MRSA infections in the United States. The key genetic traits that characterize USA300 strains include the presence of the Panton-Valentine leukocidin (PVL) encoded by the genes lukF-PV and lukS-PV, the staphylococcal chromosomal cassette mec IVa (SCCmecIVa), and the arginine catabolic mobile element (ACME). Investigating the phenotypic impact of individual mutations on the success of epidemic strains through GWAS poses a challenge due to two main confounding factors: genome-wide linkage disequilibrium (LD) and population structure. The genome-wide LD is associated with false positives, where linked non-causal mutations are mistakenly identified as causal due to the same genomic backgrounds. Therefore, the strength of this work lies in the use of publicly available transcriptomic data to construct a TRN based on ICA. This approach validates the mutations enriched by GWAS and reduces the occurrence of false positives attributed to high genome-wide LD. By integrating various 'omics' data sources, this method enhances the reliability of the results and has successfully identified new potential genetic markers specific to USA300 strains. Furthermore, it revealed mutations within core genes and intergenic regulatory regions, findings that can be validated through experimental data.

Weaknesses:

GWAS aims to identify statistically significant associations that suggest a causal link between genotype and the specific phenotype of interest while simultaneously filtering out spurious associations caused by confounding factors. While the method described in this study minimizes the impact of genome-wide linkage disequilibrium (LD), it does not extend to addressing population structure. This is because the objective was precisely to identify mutations associated with the emergence of the USA300 clone. In this context, the confounding element arising from shared ancestry becomes the subject of analysis rather than an issue to be corrected. Therefore, it is essential to highlight that the method proposed in this work can not be applied to genome-wide association studies, where correction for population structure is critical for distinguishing genuine causal associations from spurious ones. This correction is crucial and necessary to most of the studied phenotypes of interest.

Another limitation is that, although the authors emphasize the mutation in the isdH gene, the analyses conducted in this study do not provide insight into any potential adaptive function associated with it. Similarly, like the other genes exhibiting distinct expression patterns associated with enriched mutations from DBGWAS in USA300 strains, isdH is among the potential markers related to the success of the clone. This group includes well-established markers, such as ACME, which carries relevant genes like the arc operon and the speG gene that contribute to virulence and survival at infection sites.

Finally, despite the availability of the codes on GitHub, the analysis itself is not easily reproducible or adaptable to other datasets.

Reviewer #2 (Public Review):

In this study, Torcq and colleagues make careful observations of the cellular morphology of haemogenic endothelium undergoing endothelial to haematopoietic transition (EHT) to become stem cells, using the zebrafish model. To achieve this, they used an extensive array of transgenic lines driving fluorescent markers, markers of apico-basal polarity (podocalixin-FP fusions), or tight junction markers (jamb-FP fusions). The use of the runx truncation to block native Runx1 only in endothelial cells is an elegant tool to achieve something akin to tissue-specific deletion of Runx1. Overall, the imaging data is of excellent quality. They demonstrate that differences in apico-basal polarity are strongly associated with different cellular morphologies of cells undergoing EHT from HE (EHT pol- and EHT pol+) which raises the exciting possibility that these morphological differences reflect the heterogeneity of HE (and therefore HSCs) at a very early stage. They then overexpress a truncated form of Runx1 (just the runt domain) to block Runx1 function and show that more HE cells abort EHT and remain associated with the embryonic dorsal aorta. They identify pard3aa and pard3ab as potential regulators of cell polarity. However, despite showing that loss of runx1 function leads to (late) decreases in the expression of these genes, no evidence for their role in EHT is presented. The FRAP experiments and the 2d-cartography, albeit very elegant, are difficult to interpret and not very clearly described throughout the text, making interpretation difficult for someone less familiar with the techniques. Finally, while it is clear that ArhGEF11 is playing an important role in defining cell shapes and junctions between cells during EHT, there is very little statistical evidence to support the limited data presented in the (very beautiful) images.

There is a sense that this work is both overwhelming in terms of the sheer amount of imaging data, and the work behind it to generate all the lines they required, and at the same time that there is very little evidence supporting the assertion that pard3 (and even ArhGEF11) are important mediators of cell morphology and cell fate in the context of EHT. For instance, the pard3 expression data, and levels after blocking runx1 (part of Figure 3 and Figure 4) don't particularly add to the manuscript beyond indicating that the pard3 genes are regulated by Runx1.

Weaknesses<br /> The writing style is quite convoluted and could be simplified for clarity. For example, there is plenty of discussion and speculation throughout the presentation of the results. A clearer separation of the results from this speculation/discussion would help with understanding. Figures are frequently presented out of order in the text; modifying the figures to accommodate the flow of the text (or the other way around) - would make it much easier to follow the narrative. While the evidence for the different cellular morphologies of cells undergoing EHT is strong, the main claim (or at least the title of the manuscript) that tuning apico-basal polarity and junctional recycling orchestrate stem cell emergence complexity is not well supported by the data.

Reviewer #2 (Public Review):

Summary:<br /> The paper by Kim et al. investigates the potential of stimulating the dopaminergic A13 region to promote locomotor restoration in a Parkinson's mouse model. Using wild-type mice, 6-OHDA injection depletes dopaminergic neurons in the substantia nigra pars compacta, without impairing those of the A13 region and the ventral tegmentum area, as previously reported in humans. Moreover, photostimulation of presumably excitatory (CAMKIIa) neurons in the vicinity of the A13 region improves bradykinesia and akinetic symptoms after 6-OHDA injection. Whole-brain imaging with retrograde and anterograde tracers reveals that the A13 region undergoes substantial changes in the distribution of its afferents and projections after 6-OHDA injection. The study suggests that if the remodeling of the A13 region connectome does not promote recovery following chronic dopaminergic depletion, photostimulation of the A13 region restores locomotor functions.

Strengths:<br /> Photostimulation of presumably excitatory (CAMKIIa) neurons in the vicinity of the A13 region promotes locomotion and locomotor recovery of wild-type mice 1 month after 6-OHDA injection in the medial forebrain bundle, thus identifying a new potential target for restoring motor functions in Parkinson's disease patients.

Weaknesses:<br /> Electrical stimulation of the medial Zona Incerta, in which the A13 region is located, has been previously reported to promote locomotion (Grossman et al., 1958). Recent mouse studies have shown that if optogenetic or chemogenetic stimulation of GABAergic neurons of the Zona Incerta promotes and restores locomotor functions after 6-OHDA injection (Chen et al., 2023), stimulation of glutamatergic ZI neurons worsens motor symptoms after 6-OHDA (Lie et al., 2022).

Although CAMKIIa is a marker of presumably excitatory neurons and can be used as an alternative marker of dopaminergic neurons, behavioral results of this study raise questions about the neuronal population targeted in the vicinity of the A13 region. Moreover, if YFP and CHR2-YFP neurons express dopamine (TH) within the A13 region (Fig. 2), there is also a large population of transduced neurons within and outside of the A13 region that do not, thus suggesting the recruitment of other neuronal cell types that could be GABAergic or glutamatergic.

Regarding the analysis of interregional connectivity of the A13 region, there is a lack of specificity (the viral approach did not specifically target the A13 region), the number of mice is low for such correlation analyses (2 sham and 3 6-OHDA mice), and there are no statistics comparing 6-OHDA versus sham (Fig. 4) or contra- versus ipsilesional sides (Fig. 5). Moreover, the data are too processed, and the color matrices (Fig. 4) are too packed in the current format to enable proper visualization of the data. The A13 afferents/efferents analysis is based on normalized relative values; absolute values should also be presented to support the claim about their upregulation or downregulation.

In the absence of changes in the number of dopaminergic A13 neurons after 6-OHDA injection, results from this correlation analysis are difficult to interpret as they might reflect changes from various impaired brain regions independently of the A13 region. There is no causal link between anatomical and behavioral data, which raises questions about the relevance of the anatomical data.

Overall, the study does not take advantage of genetic tools accessible in the mouse to address the direct or indirect behavioral and anatomical contributions of the A13 region to motor control and recovery after 6-OHDA injection.

Reviewer #2 (Public Review):

In this paper, Paladini and colleagues investigate the concerted motions within the Abl kinase that control its conformational transition between the active (disassembled) and inactive (assembled state). This work follows their previously published findings that binding of the type II inhibitor, imatinib to the active site of Abl, leads to kinase core disassembly via the force imposed by the P-loop and other regions of the N-lobe on the SH3 domain. Interestingly, imatinib-induced disassembly is prevented when an allosteric inhibitor, asciminib, binds to the myristate-binding pocket. Key to asciminib and myristate binding are motions of helix I, located in the C-lobe, and thus, helix I is hypothesized to be the sensor of the imatinib-induced changes. Specifically, bending of helix I upon engagement of myristate or asciminib was postulated to be important for re-assembly of the autoinhibited Abl core, and thus, reducing the "force" with which kinase N-lobe pushes against the SH2 domain upon binding imatinib.

The authors use NMR to measure conformational transitions in the several 15N-labeled Abl kinase constructs that display different degrees of helix I truncations. This analysis is slightly limited by the instability of the constructs that carry truncations beyond the helix I "bend". Nevertheless, it is sufficient to establish that truncation of helix I that removes its fragment, which is in contact with myristate or asciminib ligands, results in loss of the ability of helix I to impose "force" on the SH2 domain that results in kinase core disassembly, even in the presence of imatinib binding. In the absence of this force, the allosteric coupling between the helix I/SH2 and KD/SH3 interfaces is compromised. Principle component analysis is used to analyze the NMR data, and it is very clear and convincing.

A compelling evidence in support of the proposed allosteric mechanism comes from the analysis of the E528K disease mutation, identified in the Abl1 malformation syndrome. The authors show that this mutant, poised to break a salt bridge formed between E528 in the C-terminal portion of helix I and R479 on the kinase domain, increases helix I outward motions resulting in core disassembly and higher Abl kinase activity. Together, these results reinforce that helix I motions are central to the mechanism of kinase activation via core disassembly. I find that all authors' claims are supported by the experimental data. A couple of suggestions on how to expand and improve the discussion of the data are listed in specific feedback to the authors.

Reviewer #2 (Public Review):

In this manuscript, the authors present a novel interactome focused on human and fly alpha-arrestin family proteins and demonstrate its application in understanding the functions of these proteins. Initially, the authors employed AP/MS analysis, a popular method for mapping protein-protein interactions (PPIs) by isolating protein complexes. Through rigorous statistical and manual quality control procedures, they established two robust interactomes, consisting of 6 baits and 307 prey proteins for humans, and 12 baits and 467 prey proteins for flies. To gain insights into the gene function, the authors investigated the interactors of alpha-arrestin proteins through various functional analyses, such as gene set enrichment. Furthermore, by comparing the interactors between humans and flies, the authors described both conserved and species-specific functions of the alpha-arrestin proteins. To validate their findings, the authors performed several experimental validations for TXNIP and ARRDC5 using ATAC-seq, siRNA knockdown, and tissue staining assays. The experimental results strongly support the predicted functions of the alpha-arrestin proteins and underscore their importance.

Reviewer #2 (Public Review):

Summary:<br /> Previous work has shown subjects can use a form of short-term sensory memory, known as 'iconic memory', to accurately remember stimuli over short periods of time (several hundred milliseconds). Working memory maintains representations for longer periods of time but is strictly limited in its capacity. While it has long been assumed that sensory information acts as the input to working memory, a process model of this transfer has been missing. To address this, Tomic and Bays present the Dynamic Neural Resource (DyNR) model. The DyNR model captures the dynamics of processing sensory stimuli, transferring that representation into working memory, the diffusion of representations within working memory, and the selection of memory for report.

The DyNR model captures many of the effects observed in behavior. Most importantly, psychophysical experiments found the greater the delay between stimulus presentation and the selection of an item from working memory, the greater the error. This effect also depended on working memory load. In the model, these effects are captured by the exponential decay of sensory representations (i.e., iconic memory) following the offset of the stimulus. Once the selection cue is presented, residual information in iconic memory can be integrated into working memory, improving the strength of the representation and reducing error. This selection process takes time, and is slower for larger memory loads, explaining the observation that memory seems to decay instantly. The authors compare the DyNR model to several variants, demonstrating the importance of the persistence of sensory information in iconic memory, normalization of representations with increasing memory load, and diffusion of memories over time.

Strengths:<br /> The manuscript provides a convincing argument for the interaction of iconic memory and working memory, as captured by the DyNR model. The analyses are cutting-edge and the results are well captured by the DyNR model. In particular, a strength of the manuscript is the comparison of the DyNR model to several alternative variants.

The results provide a process model for interactions between iconic memory and working memory. This will be of interest to neuroscientists and psychologists studying working memory. I see this work as providing a foundation for understanding behavior in continuous working memory tasks, from either a mechanistic, neuroscience, perspective or as a high-water mark for comparison to other psychological process models.

Finally, the manuscript is well written. The DyNR model is nicely described and an intuition for the dynamics of the model is clearly shown in Figures 2 and 4.

Weaknesses:<br /> Despite its strengths, the paper does have some (relatively minor) weaknesses. In particular, the authors could consider the role of sensory processing, and its limitations, and variability in selecting an item from working memory as other factors affecting memory accuracy.

Reviewer #2 (Public Review):

The contribution of glial cells to the pathogenesis of amyotrophic lateral sclerosis (ALS) is of substantial interest and the investigators have contributed significantly to this emerging field via prior publications. In the present study, authors use a SOD1G93A mouse model to elucidate the role of astrocyte ephrinB2 signaling in ALS disease progression. Erythropoietin-producing human hepatocellular receptors (Ephs) and the Eph receptor-interacting proteins (ephrins) signaling is an important mediators of signaling between neurons and non-neuronal cells in the nervous system. Recent evidence suggests that dysregulated Eph-ephrin signaling in the mature CNS is a feature of neurodegenerative diseases. In the ALS model, upregulated Eph4A expression in motor neurons has been linked to disease pathogenesis. In the present study, authors extend previous findings to a new class of ephrinB2 ligands. Urban et al. hypothesize that upregulated ephrinB2 signaling contributes to disease pathogenesis in ALS mice. The authors successfully test this hypothesis and their results generally support their conclusion.

Major strengths of this work include a robust study design, a well-defined translational model, and complementary biochemical and experimental methods such that correlated findings are followed up by interventional studies. Authors show that ephrinB2 ligand expression is progressively upregulated in the ventral horn of the cervical and lumbar spinal cord through pre-symptomatic to end stages of the disease. This novel association was also observed in lumbar spinal cord samples from post-mortem samples of human ALS donors with a SOD1 mutation. Further, they use a lentiviral approach to drive knock-down of ephrinB2 in the central cervical region of SOD1G93A mice at the pre-symptomatic stage. Interestingly, in spite of using a non-specific promoter, authors note that the lentiviral expression was preferentially driven in astrocytes.

Since respiratory compromise is a leading cause of morbidity in the ALS population, the authors proceed to characterize the impact of ephrinB2 knockdown on diaphragm muscle output. In mice approaching the end stage of the disease, electrophysiological recordings from the diaphragm muscle show that animals in the knock-down group exhibited a ~60% larger amplitude. This functional preservation of diaphragm function was also accompanied with the preservation of diaphragm neuromuscular innervation. However, it must be noted that this cervical ephrinB2 knockdown approach had no impact on disease onset, disease duration, or animal survival. Furthermore, there was no impact of ephrinB2 knockdown on forelimb or hindlimb function. This is an expected result, given the fairly focal approach of ephrinB2 knockdown in C3-C5 spinal segments.

The major limitation of the study is the conclusion that the preservation of diaphragm output following ephrinB2 knockdown in SOD1 mice is mediated primarily (if not entirely) by astrocytes. The authors present convincing evidence that a reduction in ephrinB2 is observed in local astrocytes (~56% transduction) following the intraspinal injection of the lentivirus. However, the proportion of cell types assessed for transduction with the lentivirus in the spinal cord was limited to neurons, astrocytes, and oligodendrocyte lineage cells. Microglia comprise a large proportion of the glial population in the spinal grey matter and have been shown to associate closely with respiratory motor pools. This cell type, amongst the many other that comprise the ventral gray matter, have not been investigated in this study. Nonetheless, there is convincing evidence to suggest astrocytes play a significant role, as compared to oligodendrocytes in promoting ALS pathogenesis.

In summary, this study by Urban et al. provides a valuable framework for Eph-Ephrin signaling mechanisms imposing pathological changes in an ALS mouse model. The role of glial cells in ALS pathology is a very exciting and upcoming field of investigation. The current study proposes a novel astrocyte-mediated mechanism for the propagation of disease that may eventually help to identify potential therapeutic targets.

Reviewer #2 (Public Review):

Summary:

Using in vitro and in vivo approaches, the authors first demonstrate that BEST4 inhibits intestinal tumor cell growth and reduces their metastatic potential, possibly via downstream regulation of TWIST1.

They further show that HES4 positively upregulates BEST4 expression, with direct interaction with BEST4 promoter region and protein. The authors further expand on this with results showing that negative regulation of TWIST1 by HES4 requires BEST4 protein, with BEST4 required for TWIST1 association with HES4. Reduction of BEST1 expression was shown in CRC tumor samples, with correlation of BEST4 mRNA levels with different clinicopathological factors such as sex, tumor stage, and lymph node metastasis, suggesting a tumor-suppressive role of BEST4 for intestinal cancer.

Strengths:

• Good quality western blot data.<br /> • Multiple approaches were used to validate the findings.<br /> • Logical experimental progression for readability.<br /> • Human patient data / In vivo murine model / Multiple cell lines were used, which supports translatability / reproducibility of findings.

Weaknesses:

• Interpretation of figures and data (unsubstantiated conclusions).<br /> • Figure quality.<br /> • Figure legends lack information.<br /> • Lacking/shallow discussion.<br /> • Requires more information for reproducibility regarding materials and methods.

Reviewer #2 (Public Review):

Summary:<br /> This manuscript examines the expression of orexin receptors in the midbrain - with a focus on dopamine neurons - and uses several fairly sophisticated manipulation techniques to explore the role of this peptide neurotransmitter in reward-related behaviors. Specifically, in situ hybridization is used to show that dopamine neurons predominantly express the orexin receptor 1 subtype and then go on to delete this receptor in dopamine neurons using a transgenic strategy. Ex vivo calcium imaging of midbrain neurons is used to show that in the absence of this receptor orexin is no longer able to excite dopamine neurons of the substantia nigra.

The authors proceed to use this same model to study the effect of orexin receptor 1 deletion on a series of behavioral tests, namely, novelty-induced locomotion and exploration, anxiety-related behavior, preference for sweet solutions, cocaine-induced conditioned place preference, and energy metabolism. Of these, the most consistent effects are seen in the tests of novelty-induced locomotion and exploration in which the mice with orexin 1 receptor deletion are observed to show greater levels of exploration, relative to wild-type, when placed in a novel environment, an effect that is augmented after icv administration of orexin.

In the final part of the paper, the authors use PET imaging to compare brain-wide activity patterns in the mutant mice compared to wildtype. They find differences in several areas both under control conditions (i.e., after injection of saline) as well as after injection of orexin. They focus on changes in the dorsal bed nucleus of stria terminalis (dBNST) and the lateral paragigantocellular nucleus (LPGi) and perform analysis of the dopaminergic projections to these areas. They provide anatomical evidence that these regions are innervated by dopamine fibers from the midbrain, are activated by orexin in control, but not mutant mice, and that dopamine receptors are present. Thus, they argue these anatomical data support the hypothesis that behavioral effects of orexin receptor 1 deletion in dopamine neurons are due to changes in dopamine signaling in these areas.

Strengths:<br /> Understanding how orexin interacts with the dopamine system is an important question and this paper contains several novel findings along these lines. Specifically:<br /> (1) The distribution of orexin receptor subtypes in VTA and SN is explored thoroughly.<br /> (2) Use of the genetic model that knocks out a specific orexin receptor subtype from only dopamine neurons is a useful model and helps to narrow down the behavioral significance of this interaction.<br /> (3) PET studies showing how central administration of orexin evokes dopamine release across the brain is intriguing, especially since two key areas are pursued - BNST and LPGi - where the dopamine projection is not as well described/understood.

Weaknesses:<br /> The role of the orexin-dopamine interaction is not explored in enough detail. The manuscript presents several related findings, but the combination of anatomy and manipulation studies does not quite tell a cogent story. Ideally, one would like to see the authors focus on a specific behavioral parameter and show that one of their final target areas (dBNST or LPGi) was responsible or at least correlated with this behavioral readout. In addition, some more discussion on what the results tell us about orexin signaling to dopamine neurons under normal physiological conditions would be very useful. For example, what is the relevance of the orexin-dopamine interaction blunting novelty-induced locomotion under wildtype conditions?

In some places in the Results, insufficient explanation and reporting is provided. For example, when reporting the behavioral effects of the Ox1 deletion in two bottle preference, it is stated that "[mutant] mice showed significant changes..." without stating the direction in which preference was affected.

The cocaine CPP results are difficult to interpret because it is unclear whether any of the control mice developed a CPP preference. Therefore, it is difficult to conclude that the knockout animals were unaffected by drug reward learning. Similarly, the sucrose/sucralose preference scores are also difficult to interpret because no test of preference vs. water is performed (although the data appear to show that there is a preference at least at higher concentrations, it has not been tested).

Reviewer #2 (Public Review):

Summary:<br /> Mouse models are widely used to determine key molecular mechanisms of atherosclerosis, the underlying pathology that leads to coronary artery disease. The authors use various systems biology approaches, namely co-expression and Bayesian Network analysis, as well as key driver analysis, to identify co-regulated genes and pathways involved in human and mouse atherosclerosis in artery and liver tissues. They identify species-specific and tissue-specific pathways enriched for the genetic association signals obtained in genome-wide association studies of human and mouse cohorts.

Strengths:<br /> The manuscript is well executed with appropriate analysis methods. It also provides a compelling series of results regarding mouse and human atherosclerosis.

Reviewer #2 (Public Review):

Summary:

In the manuscript 'Auditory cortical error signals retune during songbird courtship', Jones and Goldberg study auditory cortex in male zebra finches. They explore song-related responses in two different contexts, when the male is either alone or in the presence of a female. Social-context related responses are hypothesized based on previous results on downstream VTA neurons where such modulation is found. They play jamming stimuli through a loudspeaker to probe sensitivity of song-related neural responses to these external stimuli. They find a heterogeneity of responses, in line with auditory cortical neurons computing the social modulation of responses found in VTA.

Strengths:

In general, the work is interesting and sheds light onto auditory processing and self-perception mechanisms in songbirds.

Weaknesses:

Stability of responses has not been studied: some neurons seem to have responses that slowly drift in time, which could lead to observed differences between alone and with-female conditions. Also, possible motor confounds and sound-of-audience confounds should be addressed. The language is often imprecise.

Stability and Reversal: It is a bit unfortunate that stability of effects seemingly has not been studied by reversing experimental conditions. The work would be much stronger if authors could show that audience-dependent tuning is robust in individual cells. Did they record from some neurons during reversal back to the alone condition? Ideally, the responses should be identical before and after recording with an audience. This would control for possible non-stationarities in their neuron recordings/spike-sorting/circadian trends. If authors do not have such data, it would be worth wile to even just try to divide the dataset for each neuron and condition (either the audience or isolate condition) into two parts to verify that the response is the same in either part (provided sufficient song renditions are recorded). See also my comment below about Fig. 2A.

Motor responses: Does DAF playback change song? If so, especially if it applies only in one of the two conditions (audience/no audience), then the observed response differences could be motor-related rather than auditory responses. Analyses of song spectrograms right after DAF would presumably provide the answer.

Similarly, motif-aligned spiking activity was time warped to the median duration of undirected or directed motifs. Could the shorter motifs during directed song (as has been reported in other studies) lead to alignment differences that would account for the different error responses in alone/wfemale conditions? In other words, could increased error responses be due to the fixed 100 ms analysis window of the audience condition that extends into a song region beyond the 100 ms region of the no-audience condition where there is increased firing? And vice versa for observed decreases in error responses, i.e. is there a firing pause just after the offset of the 100 ms window in the no-audience condition that causes audience dependence of responses? A simple compensation of song tempo differences by shortening/stretching the analysis window in one of the two conditions would allow to test for this.

Audience versus sound of audience: In the first sentence of the discussion authors write: we discovered that auditory representations of an animal's own vocalizations change with an audience. Is it truly the audience that causes the difference in error responses or is it the sounds the audience makes? To control for that would be to play back stimuli that simulate a non-silent audience through a loudspeaker to see whether error responses depend on the soundscape created by a typical audience (either present or absent). Authors probably do not have such data and to record it would go beyond the scope of this study, but it would be important to discuss this possibility or perform some analysis in that vein.

Reviewer #2 (Public Review):

Summary:<br /> Hwang, Ran-Der et al utilized a CRISPR-Cas9 knockout in human retinal pigment epithelium (RPE1) cells to evaluate for suppressors of toxicity by the proteasome inhibitor MG132 and identified that knockout of dihydrolipoamide branched chain transacylase E2 (DBT) suppressed cell death. They show that DBT knockout in RPE1 cells does not alter proteasome or autophagy function at baseline. However, with MG132 treatment, they show a reduction in ubiquitinated proteins but with no change in proteasome function. Instead, they show that DBT knockout cells treated with MG132 have improved autophagy flux compared to wildtype cells treated with MG132. They show that MG132 treatment decreases ATP/ADP ratios to a greater extent in DBT knockout cells, and in accordance causes activation of AMPK. They then show downstream altered autophagy signaling in DBT knockout cells treated with MG132 compared to wild-type cells treated with MG132. Then they express the ALS mutant TDP43 M337 or expanded polyglutamine repeats to model Huntington's disease and show that knockdown of DBT improves cell survival in RPE1 cells with improved autophagic flux. They also utilize a Drosophila model and show that utilizing either a RNAi or CRISPR-Cas9 knockout of DBT improves eye pigment in TDP43M337V and polyglutamine repeat-expressing transgenic flies. Finally, they show evidence for increased DBT in postmortem spinal cord tissue from patients with ALS via both immunoblotting and immunofluorescence.

Strengths:<br /> This is a mechanistic and well-designed paper that identifies DBT as a novel regulator of proteotoxicity via activating autophagy in the setting of proteasome inhibition. Major strengths include careful delineation of a mechanistic pathway to define how DBT is protective. These conclusions are largely justified, but additional experiments and information would be useful to clarify and extend these conclusions.

Weaknesses:<br /> The large majority of the experiments are evaluating suppression of drug (MG132) toxicity in an in vitro epithelial cell line, so the generalizability to disease is unclear. Indeed, MG132 itself has been shown to modulate autophagy, and off-target effects of MG132 are not addressed. While this paper is strengthened by the inclusion of mouse-induced motor neurons, Drosophila models, and postmortem tissue, the putative mechanisms are minimally evaluated in these models.

Also, this effect is only seen with MG132 treatment, at a dose that causes markedly impaired cell survival. In this setting, it is certainly plausible that changes in autophagy could be the result of differences in cell survival, as opposed to an underlying mechanism for cell survival. Additional controls would be useful to increase confidence that DBT knockdown is protective via modulation of autophagy.

While the authors report increased DBT in postmortem ALS tissue as suggestive that DBT may modulate proteotoxicity in neurodegeneration, this point would be better supported with the evaluation of overexpression of DBT in their model.

Reviewer #2 (Public Review):

Summary:<br /> The authors have noted in preliminary work that tetrodotoxin (TTX), which inhibits NaV1.7 and several other TTX-sensitive sodium channels, has differential effects on nociceptors, dramatically reducing their excitability under certain conditions but not under others. Partly because of this coincidental observation, the aim of the present work was to re-examine or characterize the role of NaV1.7 in nociceptor excitability and its effects on drug efficacy. The manuscript demonstrates that a NaV1.7-selective inhibitor produces analgesia only when nociceptor excitability is based on NaV1.7. More generally and comprehensively, the results show that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and NaV expression of different NaV subtypes (NaV 1.3/1.7 and 1.8). This can cause widespread changes in the role of a particular subtype over time. The degenerate nature of nociceptor excitability shows functional implications that make the assignment of pathological changes to a particular NaV subtype difficult or even impossible.

Thus, the analgesic efficacy of NaV1.7- or NaV1.8-selective agents depends essentially on which NaV subtype controls excitability at a given time point. These results explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

Strengths:<br /> The above results are clearly and impressively supported by the experiments and data shown. All methods are described in detail, presumably allow good reproducibility, and were suitable to address the corresponding question. The only exception is the description of the computer model, which should be described in more detail.

The results showing that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and expression of different NaV subtypes are of great importance in the fields of basic and clinical pain research and sodium channel physiology and pharmacology, but also for a broad readership and community. The degenerate nature of nociceptor excitability, which is clearly shown and well supported by data has large functional implications. The results are of great importance because they may explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have major implications for the future development of Nav-selective analgesics.

In summary, the authors achieved their overall aim to enlighten the role of NaV1.7 in nociceptor excitability and the effects on drug efficacy. The data support the conclusions, although the clinical implications could be highlighted in a more detailed manner.

Weaknesses:<br /> As mentioned before, the results that nociceptors can achieve equivalent excitability through changes in differential NaV inactivation and NaV expression of different NaV subtypes are impressive. However, there is some "gap" between the DRG culture experiments and acutely dissociated DRGs from mice after CFA injection. In the extensive experiments with cultured DRG neurons, different time points after dissociation were compared. Although it would have been difficult for functional testing to examine additional time points (besides DIV0 and DIV4-7), at least mRNA and protein levels should have been determined at additional time points (DIV) to examine the time course or whether gene expression (mRNA) or membrane expression (protein) changes slowly and gradually or rapidly and more abruptly. It would also be interesting to clarify whether the changes that occur in culture (DIV0 vs. DIV4-7) are accompanied by (pro-)inflammatory changes in gene and protein expression, such as those known for nociceptors after CFA injection. This would better link the following data demonstrating that in acutely dissociated nociceptors after CFA injection, the inflammation-induced increase in NaV1.7 membrane expression enhances the effect of (or more neurons respond to) the NaV1.7 inhibitor PF-71, whereas fewer CFA neurons respond to the NaV1.8 inhibitor PF-24.

The results shown explain, at least in part, the poor clinical outcomes with the use of subtype-selective NaV inhibitors and therefore have important implications for the future development of Nav-selective analgesics. However, this point, which is also evident from the title of the manuscript, is discussed only superficially with respect to clinical outcomes. In particular, the promising role of NaV1.7, which plays a role in nociceptor hyperexcitability but not in "normal" neurons, should be discussed in light of clinical results and not just covered with a citation of a review. Which clinical results of NaV1.7-selective drugs can now be better explained and how?

Another point directly related to the previous one, which should at least be discussed, is that all the data are from rodents, or in this case from mice, and this should explain the clinical data in humans. Even if "impediment to translation" is briefly mentioned in a slightly different context, one could (as mentioned above) discuss in more detail which human clinical data support the existence of "equivalent excitability through different sodium channels" also in humans.

Although speculative, it would be interesting for readers to know whether a treatment regimen based on "time since injury" with NaV1.7 and NaV1.8 inhibitors might offer benefits. Based on the data, could one hypothesize that NaV1.7 inhibitors are more likely to benefit (albeit in the short term) in patients with neuropathic pain with better patient selection (e.g., defined interval between injury and treatment)?

Reviewer #2 (Public Review):

Summary<br /> This paper expands on the literature on spatial metamers, evaluating different aspects of spatial metamers including the effect of different models and initialization conditions, as well as the relationship between metamers of the human visual system and metamers for a model. The authors conduct psychophysics experiments testing variations of metamer synthesis parameters including type of target image, scaling factor, and initialization parameters, and also compare two different metamer models (luminance vs energy). An additional contribution is doing this for a field of view larger than has been explored previously.

General Comments<br /> Overall, this paper addresses some important outstanding questions regarding comparing original to synthesized images in metamer experiments and begins to explore the effect of noise vs image seed on the resulting syntheses. While the paper tests some model classes that could be better motivated, and the results are not particularly groundbreaking, the contributions are convincing and undoubtedly important to the field. The paper includes an interesting Voronoi-like schematic of how to think about perceptual metamers, which I found helpful, but for which I do have some questions and suggestions. I also have some major concerns regarding incomplete psychophysical methodology including lack of eye-tracking, results inferred from a single subject, and a huge number of trials. I have only minor typographical criticisms and suggestions to improve clarity. The authors also use very good data reproducibility practices.

Specific Comments

Experimental Setup<br /> Firstly, the experiments do not appear to utilize an eye tracker to monitor fixation. Without eye tracking or another manipulation to ensure fixation, we cannot ensure the subjects were fixating the center of the image, and viewing the metamer as intended. While the short stimulus time (200ms) can help minimize eye movements, this does not guarantee that subjects began the trial with correct fixation, especially in such a long experiment. While Covid-19 did at one point limit in-person eye-tracked experiments, the paper reports no such restrictions that would have made the addition of eye-tracking impossible. While such a large-scale experiment may be difficult to repeat with the addition of eye tracking, the paper would be greatly improved with, at a minimum, an explanation as to why eye tracking was not included.

Secondly, many of the comparisons later in the paper (Figures 9,10) are made from a single subject. N=1 is not typically accepted as sufficient to draw conclusions in such a psychophysics experiment. Again, if there were restrictions limiting this it should be discussed. Also (P11) Is subject sub-00 is this an author? Other expert? A naive subject? The subject's expertise in viewing metamers will likely affect their performance.

Finally, the number of trials per subject is quite large. 13,000 over 9 sessions is much larger than most human experiments in this area. The reason for this should be justified.

Model<br /> For the main experiment, the authors compare the results of two models: a 'luminance model' that spatially pools mean luminance values, and an 'energy model' that spatially pools energy calculated from a multi-scale pyramid decomposition. They show that these models create metamers that result in different thresholds for human performance, and therefore different critical scaling parameters, with the basic luminance pooling model producing a scaling factor 1/4 that of the energy model. While this is certain to be true, due to the luminance model being so much simpler, the motivation for the simple luminance-based model as a comparison is unclear.

The authors claim that this luminance model captures the response of retinal ganglion cells, often modeled as a center-surround operation (Rodieck, 1964). I am unclear in what aspect(s) the authors claim these center-surround neurons mimic a simple mean luminance, especially in the context of evidence supporting a much more complex role of RGCs in vision (Atick & Redlich, 1992). Why do the authors not compare the energy model to a model that captures center-surround responses instead? Do the authors mean to claim that the luminance model captures only the pooling aspects of an RGC model? This is particularly confusing as Figures 6 and 9 show the luminance and energy models for original vs synth aligning with the scaling of Midget and Parasol RGCs, respectively. These claims should be more clearly stated, and citations included to motivate this. Similarly, with the energy model, the physiological evidence is very loosely connected to the model discussed.

Prior Work:<br /> While the explorations in this paper clearly have value, it does not present any particularly groundbreaking results, and those reported are consistent with previous literature. The explorations around critical eccentricity measurement have been done for texture models (Figure 11) in multiple papers (Freeman 2011, Wallis, 2019, Balas 2009). In particular, Freeman 20111 demonstrated that simpler models, representing measurements presumed to occur earlier in visual processing need smaller pooling regions to achieve metamerism. This work's measurements for the simpler models tested here are consistent with those results, though the model details are different. In addition, Brown, 2023 (which is miscited) also used an extended field of view (though not as large as in this work). Both Brown 2023, and Wallis 2019 performed an exploration of the effect of the target image. Also, much of the more recent previous work uses color images, while the author's exploration is only done for greyscale.

Discussion of Prior Work:<br /> The prior work on testing metamerism between original vs. synthesized and synthesized vs. synthesized images is presented in a misleading way. Wallis et al.'s prior work on this should not be a minor remark in the post-experiment discussion. Rather, it was surely a motivation for the experiment. The text should make this clear; a discussion of Wallis et al. should appear at the start of that section. The authors similarly cite much of the most relevant literature in this area as a minor remark at the end of the introduction (P3L72).

White Noise:<br /> The authors make an analogy to the inability of humans to distinguish samples of white noise. It is unclear however that human difficulty distinguishing samples of white noise is a perceptual issue- It could instead perhaps be due to cognitive/memory limitations. If one concentrates on an individual patch one can usually tell apart two samples. Support for these difficulties emerging from perceptual limitations, or a discussion of the possibility of these limitations being more cognitive should be discussed, or a different analogy employed.

Relatedly, in Figure 14, the authors do not explain why the white noise seeds would be more likely to produce syntheses that end up in different human equivalence classes.

It would be nice to see the effect of pink noise seeds, which mirror the power spectrum of natural images, but do not contain the same structure as natural images - this may address the artifacts noted in Figure 9b.

Finally, the authors note high-frequency artifacts in Figure 4 & P5L135, that remain after syntheses from the luminance model. They hypothesize that this is due to a lack of constraints on frequencies above that defined by the pooling region size. Could these be addressed with a white noise image seed that is pre-blurred with a low pass filter removing the frequencies above the spatial frequency constrained at the given eccentricity?

Schematic of metamerism:<br /> Figures 1,2,12, and 13 show a visual schematic of the state space of images, and their relationship to both model and human metamers. This is depicted as a Voronoi diagram, with individual images near the center of each shape, and other images that fall at different locations within the same cell producing the same human visual system response. I felt this conceptualization was helpful. However, implicitly it seems to make a distinction between metamerism and JND (just noticeable difference). I felt this would be better made explicit. In the case of JND, neighboring points, despite having different visual system responses, might not be distinguishable to a human observer.

In these diagrams and throughout the paper, the phrase 'visual stimulus' rather than 'image' would improve clarity, because the location of the stimulus in relation to the fovea matters whereas the image can be interpreted as the pixels displayed on the computer.

Other<br /> The authors show good reproducibility practices with links to relevant code, datasets, and figures.

Reviewer #2 (Public Review):

This is a very nice study showing how partial loss of vestibular function leads to long term alterations in behavioural responses of mice. Specifically, the authors show that VOR involving both canal and otolith afferents are strongly attenuated following treatment and partially recover. The main result is that loss of VOR is partially "compensated" by increased OKR in treated animals. Finally, the authors show that treatment primarily affects type I hair cells as opposed to type II hair cells. Overall, these results have important implications for our understanding of how the VOR Is generated using input from both type I and type II hair cells.

The major strength of the study lies in the use of partial inactivation of hair cells to look at the effects on behaviors such as VOR and OKR. Some weaknesses stem from the fact that the effects of inactivation are highly variable across specimens and that there is no recovery of behavioral function.

Reviewer #2 Public Review:

Summary:<br /> In this manuscript, the authors ran a dual task. Subjects monitored a peripheral location for a target onset (to generate a saccade to), and they also monitored a foveal location for a foveal probe. The foveal probe could be congruent or incongruent with the orientation of the peripheral target. In this study, the authors manipulated the conspicuity of the peripheral target, and they saw changes in performance in the foveal task. However, the changes were somewhat counterintuitive.

Strengths:<br /> The authors use solid analysis methods and careful experimental design.

Weaknesses:<br /> I have some issues with the interpretation of the results, as explained below. In general, I feel that a lot of effects are being explained by attention and target-probe onset asynchrony etc, but this seems to be against the idea put forth by the authors of "foveal prediction for visual continuity across saccades". Why would foveal prediction be so dependent on such other processes? This needs to be better clarified and justified.

Specifics:<br /> The explanation of decreased hit rates with increased peripheral target opacity is not convincing. The authors suggest that higher contrast stimuli in the periphery attract attention. But, then, why are the foveal results occurring earlier (as per the later descriptions in the manuscript)? And, more importantly, why would foveal prediction need to be weaker with stronger pre-saccadic attention to the periphery? What is the function of foveal prediction? What of the other interpretation that could be invoked in general for this type of task used by the authors: that the dual task is challenging and that subjects somehow misattribute what they saw in the peripheral task when planning the saccade. i.e. foveal hit rates are misperceptions of the peripheral target. When the peripheral target is easier to see, then the foveal hit rate drops.

The analyses of Fig. 3C appear to be overly convoluted. They also imply an acknowledgment by the authors that target-probe temporal difference matters. Doesn't this already negate the idea that the foveal effects are associated with the saccade generation process itself? If the effect is related to target onset, how is it interpreted as related to a foveal prediction that is associated with the saccade itself? Also, the oscillatory nature of the effect in Fig. 3C for 59% and 90% opacity is quite confusing and not addressed. The authors simply state that enhancement occurs earlier before the saccade for higher contrasts. But, this is not entirely true. The enhancement emerges then disappears and then emerges again leading up to the saccade. Why would foveal prediction do that?

The interpretation of Fig. 4 is also confusing. Doesn't the longer latency already account for the lapse in attention, such that visual continuity can proceed normally now that the saccade is actually eventually made? In all results, it seems that the effects are all related to the dual nature of the task and/or attention, rather than to the act of making the saccade itself. Why should visual continuity (when a saccade is actually made, whether with short or long latency) have different "fidelity"? And, isn't this disruptive to the whole idea of visual continuity in the first place?

Small question: is it just me or does the data in general seem to be too excessively smoothed?

Reviewer #2 (Public Review):

Summary:<br /> The authors have generated human iPSC cells constitutively expressing the mNG21-10 and tested them by endogenous tagging multiple genes with mNG211 (several tagged iPS cell lines clones were isolated). With this tool, they have explored several weakly expressed cytokinesis genes and gained insights into how cytokinesis occurs.

Strengths:<br /> Human iPSC cells are used.

Weaknesses:<br /> i) The manuscript is extremely incremental, no improvements are present in the split-fluorescent (split-FP) protein variant used nor in the approach for endogenous tagging with split-FPs (both of them are already very well established and used in literature as well as in different cell types).

ii) The fluorescence intensity of the split mNeonGreen appears rather low, for example in Figure 2C the H2BC11, ANLN, SOX2, and TUBB3 signals are very noisy (differences between the structures observed are almost absent). For low-expression targets, this is an important limitation. This is also stated by the authors but image restoration could not be the best solution since a lot of biologically relevant information will be lost anyway.

iii) There is no comparison with other existing split-FP variants, methods, or imaging and it is unclear what the advantages of the system are.

Reviewer #2 (Public Review):

Summary:<br /> The authors here develop a novel Ovalbumin model peptide that can be labeled with a site-specific FlAsH dye to track agonist peptides both in vitro and in vivo. The utility of this tool could allow better tracking of activated polyclonal T cells particularly in novel systems. The authors have provided solid evidence that peptides are functional, capable of activating OTII T cells, and that these peptides can undergo trogocytosis by cognate T cells only.

Strengths:<br /> -An array of in vitro and in vivo studies are used to assess peptide functionality.<br /> -Nice use of cutting-edge intravital imaging.<br /> -Internal controls such as non-cogate T cells to improve the robustness of the results (such as Fig 5A-D).<br /> -One of the strengths is the direct labeling of the peptide and the potential utility in other systems.

Weaknesses:<br /> 1. What is the background signal from FlAsH?<br /> The baselines for Figure 1 flow plots are all quite different. Hard to follow. What does the background signal look like without FLASH (how much fluorescence shift is unlabeled cells to No antigen+FLASH?). How much of the FlAsH in cells is actually conjugated to the peptide? In Figure 2E, it doesn't look like it's very specific to pMHC complexes. Maybe you could double-stain with Ab for MHCII. Figure 4e suggests there is no background without MHCII but I'm not fully convinced. Potentially some MassSpec for FLASH-containing peptides.

2. On the flip side, how much of the variant peptides are getting conjugated in cells? I'd like to see some quantification (HPLC or MassSpec). If it's ~10% of peptides that get labeled, this could explain the low shifts in fluorescence and the similar T cell activation to native peptides if FlasH has any deleterious effects on TCR recognition. But if it's a high rate of labeling, then it adds confidence to this system.

3. Conceptually, what is the value of labeling peptides after loading with DCs? Why not preconjugate peptides with dye, before loading, so you have a cleaner, potentially higher fluorescence signal? If there is a potential utility, I do not see it being well exploited in this paper. There are some hints in the discussion of additional use cases, but it was not clear exactly how they would work. One mention was that the dye could be added in real-time in vivo to label complexes, but I believe this was not done here. Is that feasible to show?

4. Figure 5D-F the imaging data isn't fully convincing. For example, in 5F and 2G, the speeds for T cells with no Ag should be much higher (10-15micron/min or 0.16-0.25micron/sec). The fact that yours are much lower speeds suggests technical or biological issues, that might need to be acknowledged or use other readouts like the flow cytometry.

Reviewer #2 (Public Review):

Summary:<br /> This paper examined whether circulating platelets regulate oligodendrocyte progenitor cell (OPC) differentiation for the link with multiple sclerosis (MS). They identified that the interaction with platelets enhances OPC differentiation although persistent contact inhibits the process in the long-term. The mouse model with increased platelet levels in the blood reduced mature oligodendrocytes, while how platelets might regulate OPC differentiation is not clear yet.

Strengths:<br /> The use of both partial platelet depletion and thrombocytosis mouse models gives in vivo evidence. The presentation of platelet accumulation in a time-course manner is rigorous. The in vitro co-culture model tested the role of platelets in OPC differentiation, which was supportive of in vivo observations.

Weaknesses:<br /> How platelets regulate OPC differentiation is not clear. What the significance of platelets is in MS progression is not clear.

Reviewer #2 (Public Review):

Summary:<br /> In this manuscript, the authors reported a study to uncover that β-catenin inhibition disrupting the homeostasis of osteogenic/adipogenic differentiation contributes to the development of Glucocorticoid-induced osteonecrosis of the femoral head (GONFH). In this study, they first observed abnormal osteogenesis and adipogenesis associated with decreased β-catenin in the necrotic femoral head of GONFH patients, but the exact pathological mechanisms of GONFH remain unknown. They then performed in vivo and in vitro studies to further reveal that glucocorticoid exposure disrupted osteogenic/adipogenic differentiation bone marrow stromal cells (BMSCs) by inhibiting β-catenin signaling in glucocorticoid-induced GONFH rats, and specific deletion of β-catenin in Col2+ cells shifted BMSCs commitment from osteoblasts to adipocytes, leading to a full spectrum of disease phenotype of GONFH in adult mice.

Strengths:<br /> This innovative study provides strong evidence supporting that β-catenin inhibition disrupts the homeostasis of osteogenic/adipogenic differentiation that contributes to the development of GONFH. This study also identifies an ideal genetically modified mouse model of GONFH. Overall, the experiment is logically designed, the figures are clear, and the data generated from humans and animals is abundant supporting their conclusions.

Weaknesses:<br /> There is a lack of discussion to explain how the Wnt agonist 1 works. There are several types of Wnt ligands. It is not clear if this agonist only targets Wnt1 or other Wnts as well. Also, why Wnt agonist 1 couldn't rescue the GONFH-like phenotype in β-cateninCol2ER mice needs to be discussed.

Reviewer #2 (Public Review):

Summary: In the manuscript, the authors summarized and introduced the correlation between the non-core regions of RAG1 and RAG2 in BCR-ABL1+acute B lymphoblastic leukemia and off-target recombination which has certain innovative and clinical significance.

Reviewer #2 (Public Review):

Summary:

Jablonowski and colleagues studied key characteristics of MYC-driven cancers: dysregulated pre-mRNA splicing and altered metabolism. This is an important field of study as it remains largely unclear as to how these processes are coordinated in response to malignant transformation and how they are exploitable for future treatments. In the present study, the authors attempt to show that Jumonji Domain Containing 6, Arginine Demethylase And Lysine Hydroxylase (JMJD6) plays a central role in connecting pre-mRNA splicing and metabolism in MYC-driven neuroblastoma. JMJD6 collaborates with the MYC protein in driving cellular transformation by physically interacting with RNA-binding proteins involved in pre-mRNA splicing and protein regulation. In cell line experiments, JMJD6 affected the alternative splicing of two forms of glutaminase (GLS), an essential enzyme in the glutaminolysis process within the central carbon metabolism of neuroblastoma cells. Additionally, the study provides in vitro (and in silico) evidence for JMJD6 being associated with the anti-proliferation effects of a compound called indisulam, which degrades the splicing factor RBM39, known to interact with JMJD6.

Overall, the findings presented by Jabolonowski et al. begin to illuminate a cancer-promoting metabolic, and potentially, a protein synthesis suppression program that may be linked to alternative pre-mRNA splicing through the action of JMJD6 - downstream of MYC. This discovery can provide further evidence for considering JMJD6 as a potential therapeutic target for the treatment of MYC-driven cancers.

Strengths:

Alternative Splicing Induced by JMJD6 Knockdown: the study presents evidence for the role of JMJD6 in alternative splicing in neuroblastoma cells. Specifically, the RNA immunoprecipitation experiments demonstrated a significant shift from the GAC to the KGA GLS isoform upon JMJD6 knockdown. Moreover, a significant correlation between JMJD6 levels and GAC/KGA isoform expression was identified in two distinct neuroblastoma cohorts. This suggests a causative link between JMJD6 activity and isoform prevalence.

Physical Interaction of JMJD6 in Neuroblastoma Cells: The paper provides preliminary insight into the physical interactome of JMJD6 in neuroblastoma cells. This offers a potential mechanistic avenue for the observed effects on metabolism and protein synthesis and could be exploited for a deeper investigation into the exact nature, and implications of neuroblastoma-specific JMJD6 protein-protein interactions.

Weaknesses:

There are several areas that would benefit from improvements with regard to the current data supporting the claims of the paper (i.e., the conclusion presented in Figure 8).

Neuroblastoma Modelling Strategy: The study heavily relies on cell lines without incorporating patient-derived cells/biomaterials. Using databases to fill gaps in the experimental design can only fortify the observations to a certain extent. A critical oversight is the absence of non-cancerous control cells in many figures, and the rationale for selecting specific cell lines for assays/approaches remains somewhat unclear. A foundational control for such experiments should involve the non-transformed neural crest cell line, which the authors have readily available. Are the observed splicing and metabolic effects of JMJD6 specific to neuroblastoma? Is there a neuroblastoma-specific JMJD6 interactome? Is MYC function essential?

In Vivo Modelling: The inclusion of a genetic mouse model combined with an inducible JMJD6 knockdown, would enhance the study by allowing examination of JMJD6's role during both tumor initiation and growth in vivo. For instance, the TH-MYCN mice overexpressing MYCN in neural crest cells, could be a promising choice.

Dependence on Colony Formation Assay: The study leans on 2D and semi-quantitative colony formation assays to assess malignant growth. To validate the link between the mechanistic insights discussed (e.g., reduced protein synthesis) and JMJD6-mediated malignant growth as a potential therapeutic target, evidence from in vivo or representative 3D models would be crucial.

Data Presentation and Rigor: The presented data is predominantly qualitative and necessitates quantification. For instance, Western blots should be quantified. The RNAseq, metabolism, and pull-down data should be transparently and numerically presented. The figure legends seem elusive and their lack of transparency (often with regards to biological repeats, error bars, cell line used etc.) is concerning. Adequate citation and identification of all data sources, including online resources, are imperative. The manuscript would also benefit from a more rigorous depiction and quantification of RNA interference of both stable and transient knockdowns with quantitative validation at mRNA and protein levels.

Novelty Concerns: The emphasis on JMJD6 as a novel neuroblastoma target is contingent on the new mechanistic revelations about the JMJD6-centered link between splicing, metabolism, and protein synthesis. Given that JMJD6 has been previously linked to neuroblastoma biology, the rationale (particularly in Figure 1) for concentrating on JMJD6 may stem more from bias rather than data-driven reasoning.

Depth of Mechanistic Investigation: Current evidence lacks depth in key areas such as JMJD6-RNA binding. A more thorough approach would involve pinpointing specific JMJD6 binding sites on endogenous RNAs using techniques such as cross-linking and immunoprecipitation, paired with complementary proximity-based methodologies. Regarding the presented metabolism data, diving deeper into metabolic flux via isotope labeling experiments could shed light on dynamic processes like TCA and glutaminolysis. As it stands, the 'pathway cartoon' in Figure 6d appears overly qualitative.

Reviewer #2 (Public Review):

Summary:

In this work, the authors report a role for the well-studied GTPase Rab7 in gut homeostasis. The study combines cell culture experiments with mouse models and human ulcerative colitis patient tissues to propose a model where, Rab7 by delivering a key mucous component CLCA1 to lysosomes, regulates its secretion in the goblet cells. This is important for the maintenance of mucous permeability and gut microbiota composition. In the absence of Rab7, CLCA1 protein levels are higher in tissues as well as the mucus layer, corroborating with the anti-correlation of Rab7 (reduced) and CLCA1 (increased) from ulcerative colitis patients. The authors conclude that Rab7 maintains CLCA1 level by controlling its lysosomal degradation, thereby playing a vital role in mucous composition, colon integrity, and gut homeostasis.

Strengths:

The biggest strength of this manuscript is the combination of cell culture, mouse model, and human tissues. The experiments are largely well done and in most cases, the results support their conclusions. The authors go to substantial lengths to find a link, such as alteration in microbiota, or mucus proteomics.

Weaknesses:

There are also some weaknesses that need to be addressed. The association of Rab7 with UC in both mice and humans is clear, however, claims on the underlying mechanisms are less clear. Does Rab7 regulate specifically CLCA1 delivery to lysosomes, or is it an outcome of a generic trafficking defect? CLCA1 is a secretory protein, how does it get routed to lysosomes, i.e. through Golgi-derived vesicles, or by endocytosis of mucous components? Mechanistic details on how CLCA1 is routed to lysosomes will add substantial value.

Why does the level of Rab7 fluctuate during DSS treatment (Fig 1B)? Does the reduction seen in Rab7 levels (by WB) also reflect in reduced Rab7 endosome numbers? Are other late endosomal (and lysosomal) populations also reduced upon DSS treatment and UC? Is there a general defect in lysosomal function?

The evidence for lysosomal delivery of CLCA1 (Fig 7 I, J) is weak. Although used sometimes in combination with antibodies, lysotracker red is not well compatible with permeabilization and immunofluorescence staining. The authors can substantiate this result further using lysosomal antibodies such as Lamp1 and Lamp2. For Fig 7J, it will be good to see a reduction in Rab7 levels upon KD in the same cell. In this connection, Fig S3D is somewhat confusing. While it is clear that the pattern of Muc2 in WT and Rab7-/- cells are different, how this corroborates with the in vivo data on alterations in mucus layer permeability -- as claimed -- is not clear.

Overall, the work shows a role for a well-studied GTPase, Rab7, in gut homeostasis. This is an important finding and could provide scope and testable hypotheses for future studies aimed at understanding in detail the mechanisms involved.

Reviewer #2 (Public Review):

Despite the fact that CTLA-4 is a critical molecule for inhibiting the immune response, surprisingly individuals with heterozygous CTLA-4 mutations exhibit immunodeficiency, presenting with antibody deficiency secondary to B cell loss. Why the loss of a molecule that regulates T cell activation should lead to B cell loss has remained unclear. In this study, Muthana and colleagues use an anti-CTLA-4 antibody drug conjugate (aCTLA-4 ADC) to delete cells expressing high levels of CTLA-4, and show that this leads to a reduction in B cells. The aCTLA-4 ADC is found to delete a subset of Tregs, leading to hyperactivation of T cells that is associated with B cell depletion. Using blocking antibodies, the authors implicate TNFa in the observed B cell loss.

The reciprocal regulation of T and B cell homeostasis is an important research area. While it has been shown that Treg defects are associated with B cell loss, the mechanisms at play are incompletely understood. CTLA-4 is not normally expressed in B cells so an indirect mechanism of action is assumed. The authors show that the decrease in Treg following aCTLA-4 ADC treatment is associated with activation of T cells, and that B cell loss is blunted if T cells are depleted. A role for both CD4 and CD8 T cells is identified by selective CD4/CD8 depletion. T cells appear to require CD28 costimulation in order to mediate B cell loss, since the response is partially inhibited in the presence of the costimulation blockade drug belatacept (CTLA-4-Ig). Finally, experiments using the anti-TNFa antibody adalimumab suggest a potential role for TNFa in the depletion of B cells.

While the manuscript makes a useful contribution, a number of limitations remain. Perhaps most important is the extent to which this model mimics the natural situation in individuals with CTLA-4 mutations (or following CTLA-4-based clinical interventions). aCTLA-4 ADC treatment permits acute deletion of Treg expressing high levels of CTLA-4, whereas in patients the Treg population remains but is specifically impaired in CTLA-4 function. Secondly, although the requirement for T cells to mediate B cell loss is convincingly demonstrated, the incomplete reversal by TNFa blockade suggests additional unidentified factors contribute to this effect. Finally, although the manuscript favours peripheral killing of mature B cells over alterations to B cell lymphopoiesis, one concern is that this may simply reflect the model employed: the short-term (6 day) treatment used here may be too acute to alter B cell development, but this may nevertheless be a feature of prolonged immune dysregulation in humans.

Reviewer #2 (Public Review):

Summary: The authors present a technique for fitting diffusion magnetic resonance images (dMRI) to a sub-diffusion model of the diffusion process within brain imaging. The authors suggest that their technique provides robust and accurate calculation of diffusional kurtosis imaging parameters from which high quality images can be calculated from short dMRI data acquisitions at two diffusion times.

Strengths: If the authors can show that the dMRI signal in brain tissue follows a sub-diffusion model decay curve then their technique for accurately and robustly calculating diffusional kurtosis parameters from multiple diffusion times would be of benefit for tissue microstructural imaging in research and clinical arenas.

Weaknesses: The applied sub-diffusion model has two parameters that are invariant to diffusion time, D_β and β which are used to calculate the diffusional kurtosis measures of a diffusion time dependent D* and a diffusion time invariant K*. However, the authors do not demonstrate that the D_β, β and K* parameters are invariant to diffusion time in brain tissue. The authors' results visually show that there is time dependence of the K* measure (in Figure 6) that is more apparent in white matter with K* values being higher for diffusion times of ∆=49 ms than ∆ = 19 ms. The diffusion time dependence of K* indicates there is also diffusion time dependence of β. Furthermore, Figure 7 shows that there is a tissue specific root mean squared error in model fitting over the two diffusion times which indicates greater deviation from the model fit in white matter than grey matter. To show that the sub-diffusion model is robust and accurate (and consequently that K* is robust and accurate) the authors would have to demonstrate that there is no diffusion time-dependence in both D_β and β in application to brain imaging data for each diffusion time separately. Simulated data should not be used to demonstrate the robustness and accuracy of the sub-diffusion model or to determine optimization of dMRI acquisition parameters without first demonstrating that D_β and β are invariant to diffusion time. This is because simulated signals calculated by using the sub-diffusion charateristic equation of dMRI signal decay will necessarily have diffusion time invariant D_β and β parameters.

Without further information demonstrating diffusion time invariance of D_β, β and K* it is not possible to determine whether the authors have achieved their aims or that their results support their conclusions.

Ungenerous to take Alter to task for context which he might not have the background to comment upon.

Does Alter call it a "platitude" from it's historical context, or with respect to the modern context of Donald J. Trump and a wide variety of Republican Party members who are anything but Christian?