Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors described the litmining ecosystem that can flexibly combine automatic and manual annotation for meta-research.

Strengths:

Software development is crucial for cumulative science and of great value to the community. However, such works are often greatly under-valued in the current publish-or-perish research culture. Thus, I applaud the authors' efforts devoted to this project. All the tools and repositories are public and can be accessed or installed without difficulty. The results reported in the manuscript are also compelling that the ecosystem is relatively mature.

Weaknesses:

First and foremost, the logic flow of the current manuscript is difficult to follow.

The second issue is the results from the litmining ecosystem were not validated and the efficiency of using litmining was not quantified. To validate the results, it would be better to directly compare the results of litmining with recognized ground truth in each of the examples. To prove the efficiency of the current ecosystem, it would be better to use quantitative indices for comparing the litmining and the other two approaches (in terms of time and/or other costs in a typical meta-research).

The third family of issues is about the functionality of the litmining ecosystem. As the authors mentioned, the ecosystem can be used for multiple purposes, however, the description here is not sufficient for researchers to incorporate the litmining ecosystem into their meta-research project. Imagine that a group of researchers are interested in using the litmining ecosystem to facilitate their meta-analyses, how should they incorporate litmining into their workflow? I have this question because, in a complete meta-analysis, researchers are required to (1) search in more than one database to ensure the completeness of their literature search; (2) screen the articles from the searched articles, which requires inspection of the abstract and the pdf; (3) search all possible pdf file of included articles instead of only relying on the open-access pdf files on PMC database. That said, if researchers are interested in using litmining in a meta-analysis that follows reporting standards such as PRISMA, the following functionalities are crucial:<br /> (a) How to incorporate the literature search results from different databases;<br /> (b) After downloading the meta-data of articles from databases, how to identify whose pdf files can be downloaded from PMC and whose pdf files need to be searched from other resources;<br /> (c) Is it possible to also annotate pdf files that were not downloaded by pubget?<br /> (d) How to maintain and update the meta-data and intermediate data for a meta-analysis by using litmining? For example, after searching in a database using a specific command and conducting their meta-analysis, researchers may need to update the search results and include items after a certain period.

Reviewer #2 (Public Review):

Summary:

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 the 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:

The results are clearly and impressively supported by the experiments and data shown. During the revision, the manuscript was consistently improved and the concerns of the first reviews were resolved. All methods are described in detail, and presumably, allow good reproducibility and were suitable to address the scientific question.

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 the NaV1.7 in nociceptor excitability and the effects on drug efficacy. The data support the conclusions and clinical implications are highlighted as far as is currently justifiable due to the still limited experience in translation. This appears well-considered, not too speculative, and ultimately appropriate.

The main weaknesses of the first version were fixed during the revision:

(i) After revising the manuscript, the initial weakness that the computer model was described superficially has been fixed. Important information was added to the main text and additional information, including the full code and equations and values are deposited on ModelDB or are given in the Supplementary information (Suppl. Table 5 & 6).

(ii) The authors now comment that corresponding studies on protein levels or e.g. neuroinflammatory changes could support the characterization of the time course of membrane expression and cellular changes, but this should be addressed in future studies, as these analyses would also raise new questions, such as about membrane trafficking, post-translational modifications, etc. This is plausible and has now been appropriately addressed in the text.

(iii) During the initial review the authors were asked to discuss the promising role of NaV1.7 in the light of clinical results. In their response, the authors confidently state that they „wish to avoid speculating on which particular clinical results are better explained because our study was not designed for that." They, however, emphasize their take-home message, which is well supported "Instead, our take-home message (which is well supported; see Discussion on lines 309-321) is that NaV1.7-selective drugs may have a variable clinical effect because nociceptors' reliance on NaV1.7 is itself variable - much more than past studies would have readers believe. ... The challenge (as highlighted in the Abstract, lines 21-22) is that identifying the dominant Nav subtype to predict drug efficacy is difficult."

Against the background of this argumentation, it must be admitted that the decision not to present as yet unproven speculations is probably appropriate from a scientific point of view and that this ultimately proves the critical assessment of one's own data and the limitations of the study. This is undoubtedly acceptable and - in retrospect - probably the right way to go.

Reviewer #2 (Public Review):

Summary:

The large-conductance Ca2+ activated K+ channel (BK) has been reported to promote breast cancer progression, but it is not clear how. The present study, carried out in breast cancer cell lines, concludes that BK located in mitochondria reprograms cells towards the Warburg phenotype, one of the metabolic hallmarks of cancer.

Strengths:

The use of a wide array of modern complementary techniques, including metabolic imaging, respirometry, metabolomics and electrophysiology. On the whole experiments are astute and well designed, and appear carefully done. The use of a BK knock out cells to control for the specificity of the pharmacological tools is a major strength. The manuscript is clearly written. There are many interesting original observations that may give birth to new studies.

Weaknesses: The main conclusion regarding the role of a BK channel located in mitochondria appears is not sufficiently supported. Other perfectible aspects are the interpretation of co-localization experiments and the calibration of Ca2+ dyes. These points are discussed in more detail in the following paragraphs:

(1) May the metabolic effects be ascribed to a BK located in mitochondria? Unfortunately not, at least with the available evidence. While it is clear these cells have a BK in mitochondria (characteristic K+ currents detected in mitoplasts) and it is also well substantiated that the metabolic effects in intact cells are explained by an intracellular BK (paxilline effects absent in the BK KO), it does not follow that both observations are linked. Given that ectopic BK-DEC appeared at the surface, a confounding factor is the likely expression of BK in other intracellular locations such as ER, Golgi, endosomes, etc. To their credit authors acknowledge this limitation several times throughout the text ("...presumably mitoBK...") but not in other important places, particularly in title and abstract.

(2) mitoBK subcellular location. Pearson correlations of 0.6 and about zero were obtained between the locations of mitoGREEN on one side, and mRFP or RFP-GPI on the other (Figs. 1G and S1E). These are nice positive and negative controls. For BK-DECRFP however the Pearson correlation was about 0.2. What is the Z resolution of apotome imaging? Assuming an optimum optical section of 600 nm, as obtained a 1.4 NA objective with a confocal, that mitochondria are typically 100 nm in diameter and that BK-DECRFP appears to stain more structures that mitoGREEN, the positive correlation of 0.2 may not reflect colocalization. For instance, it could be that BK-DECRFP in not just in mitochondria but in a close underlying organelle e.g. the ER. Along the same line, why did BK-RFP also give a positive Pearson? Isn´t that unexpected? Considering that BK-DEC was found by patch clamping at the plasma membrane, the subcellular targeting of the channel is suspect. Could it be that the endogenous BK-DEC does actually reside exclusively in mitochondria (a true mitoBK), but overflows to other membranes upon overexpression? Regarding immunodetection of BK in the mitochondrial Percoll preparation (Fig. S5), absence of NKA demonstrates absence of plasma membrane contamination, but does not inform about contamination by other intracellular membranes.

(3) Calibration of fluorescent probes. The conclusion that BK blockers or BK expression affects resting Ca2+ levels should be better supported. Fluorescent sensors and dyes provide signals or ratios that need be calibrated if comparisons between different cell types or experimental conditions are to be made. This is implicitly acknowledged here when monitoring ER Ca2+, with an elaborate protocol to deplete the organelle in order to achieve a reading at zero Ca2+.

(4) Line 203. "...solely by the expression of BKCa-DECRFP in MCF-7 cells". Granted, the effect of BKCa-DECRFP on the basal FRET ratio appears stronger than that of BK-RFP, but it appears that the latter had some effect. Please provide the statistics of the latter against the control group (after calibration, see above).

The revised version of the manuscript has incorporated my suggestions to a very reasonable degree, in several cases with new experiments. The details of these improvements can be found in the correspondence.

Reviewer #2 (Public Review):

Summary:

The article entitled "Circadian regulation of endoplasmic reticulum calcium response in mouse cultured astrocytes" submitted by Ryu and colleagues describes the circadian control of astrocytic intracellular calcium levels in vitro.

Strengths:

The authors used a variety of technical approaches that are appropriate

Weaknesses:

Statistical analysis is poor and could lead to a misinterpretation of the data

Several conceptual issues have been identified.

Overinterpretation of the data should be avoided. This is a mechanistic paper done completely in vitro, all references to the in vivo situation are speculative and should be avoided.

Reviewer #2 (Public Review):

Summary:

Shahshahani and colleagues used a combination of statistical modelling and whole-brain fMRI data in an attempt to separate the contributions of cortical and cerebellar regions in different cognitive contexts.

Strengths:

* The manuscript uses a sophisticated integration of statistical methods, cognitive neuroscience, and systems neurobiology.

* The authors use multiple statistical approaches to ensure robustness in their conclusions.

* The consideration of the cerebellum as not a purely 'motor' structure is excellent and important.

Weaknesses:

* Two of the foundation assumptions of the model - that cerebellar BOLD signals reflect granule cells > purkinje neurons and that corticocerebellar connections are relatively invariant - are still open topics of investigation. It might be helpful for the reader if these ideas could be presented in a more nuanced light.

* The assumption that cortical BOLD responses in cognitive tasks should be matched irrespective of cerebellar involvement does not cohere with the idea of 'forcing functions' introduced by Houk and Wise.

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:

There are many dangers about analysing RNA-seq data at the subfamily level. Outputs may be greatly confounded by pervasive transcription, 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. The authors have tried to mitigate against some of these issues, but they have not been completely ruled out.

Reviewer #2 (Public Review):

In their manuscript entitled "DHODH inhibition enhances the efficacy of immune checkpoint blockade by increasing cancer cell antigen presentation", Mullen et al. describe an interesting mechanism of inducing antigen presentation. The manuscript includes a series of experiments that demonstrate that blockade of pyrimidine synthesis with DHODH inhibitors (i.e. brequinar (BQ)) stimulates the expression of genes involved in antigen presentation. The authors provide evidence that BQ mediated induction of MHC is independent of interferon signaling. A subsequent targeted chemical screen yielded evidence that CDK9 is the critical downstream mediator that induces RNA Pol II pause release on antigen presentation genes to increase expression. Finally, the authors demonstrate that BQ elicits strong anti-tumor activity in vivo in syngeneic models, and that combination of BQ with immune checkpoint blockade (ICB) results in significant lifespan extension in the B16-F10 melanoma model. Overall, the manuscript uncovers an interesting and unexpected mechanism that influences antigen presentation and provides an avenue for pharmacological manipulation of MHC genes, which is therapeutically relevant in many cancers. However, a few key experiments are needed to ensure that the proposed mechanism is indeed functional in vivo.

Major Points:

(1) According to the proposed model, BQ mediated induction of antigen presentation is a contributing factor to the efficacy of this therapeutic strategy. If this is true, then depletion of immune cells should reduce the therapeutic efficacy of BQ in vivo. The authors should perform the B16-F10 transplant experiments in either Rag null mice (if available) or with CD8/CD4 depletion. The expectation would be that T cell depletion (or MHC loss with genetic manipulation) should reduce the efficacy of BQ treatment. Absent this critical experiment, it is difficult to confidently conclude that induction of antigen presentation is a fundamental component of the in vivo response to DHODH inhibition.

(2) Does BQ treatment induce antigen presentation in non-malignant cells? APCs? If the induction of antigen presentation is not cancer specific and related to a pyrimidine depletion stress response, then there is a possibility that healthy tissues will also exhibit a similar phenotype, raising concerns about the specificity of a de novo immune response. The authors should examine antigen presentation genes in healthy tissues treated with BQ.

(3) In the title, the authors claim that DHODH enhances the efficacy of ICB. However, the experiment shown in Figure 5D does not demonstrate this. The Kaplan Meier curves reflect more of an additive response versus a synergistic combination. Furthermore, the concurrent treatment of BQ and ICB seems to inhibit the efficacy of ICB due to BQ toxicity in immune cells. When concurrently administered, the survival of the mice is the same as with brequinar alone, suggesting that the efficacy of ICB was diminished. However, if ICB is administered following an initial dose of BQ, there is an added survival benefit of a magnitude that is similar to ICB alone. This result seems to contradict the title. Furthermore, the authors should show the longitudinal growth curves of these tumors.

(4) Related to Point 3, the temporal separation of BQ and ICB raises the question of whether the induction of antigen presentation with BQ is persistent during the course of delayed ICB treatment. One explanation for the results is that BQ treatment reduces tumor burden, and then a subsequent course of ICB also reduces tumor burden but not that the two therapies are functioning in synergy. To address this, the authors should measure the duration of BQ mediated induction of antigen presentation after stopping treatment.

(5) In Figure 1, the authors show that DHODH inhibition induces expression of both MHC-I and MHC-II genes at the RNA level. However, they only validate MHC-I by flow cytometry. A simple experiment to evaluate the effect of BQ treatment on MHC-II surface expression would provide important additional mechanistic insight into the immunomodulatory effects of DHODH inhibition, especially given recent literature reinforcing the importance of MHC-II expression on epithelial cancers, including melanoma (Oliveira et al. Nature 2022).

Minor Points:

(1) The authors show ChIP-seq tracks from Tan et al. for HLA-B. However, given the pervasive effect of Ter treatment across many HLA genes, the authors should either show tracks at additional loci, or provide a heatmap of read density across more loci. This would substantiate the mechanistic claim that RNA Pol II occupancy and activity across antigen presentation genes is the major driver of response to DHODH inhibition as opposed to mRNA stabilization/increased translation.

(2) A compelling way to demonstrate a change in antigen presentation is through mass spectrometry based immunopeptidomics. Performing immunopeptidomic analysis of BQ treated cell lines would provide substantial mechanistic insight into the outcome of BQ treatment. While this approach may be outside the scope of the current work, the authors should speculate on how this treatment may specifically alter the antigenic landscape where future directions would include empirical immunopeptidomics measurements.

(3) While the signaling through CDK9 seems convincing, it still does not provide a mechanistic link between depleted pyrimidines and CDK9 activity. The authors should speculate on the mechanism that signals to CDK9.

(4) Related to minor point 2, the authors should consider a genetic approach to confirm the importance of CDK9. While the pharmacological approach, including multiple mechanistically distinct CDK9 inhibitors provides strong evidence, an additional experiment with genetic depletion of CDK9 (CRISPR KO, shRNA, etc) would provide compelling mechanistic confirmation.

(5) The authors should comment in the discussion on how this strategy may be particularly useful in patients harboring genetic or epigenetic loss of interferon signaling, a known mechanism of ICB resistance. Perhaps DHODH inhibition could rescue MHC expression in cells that are deficient in interferon sensing.

Overall, the paper is clearly written and presented. With the additional experiments described above, especially in vivo, this manuscript would provide a strong contribution to the field of antigen presentation in cancer. The distinct mechanisms by which DHODH inhibition induces antigen presentation will also set the stage for future exploration into alternative methods of antigen induction.

Comments on latest version:

The authors address the majority of the points raised in my previous review. However, no additional in vivo experiments were performed, which seems necessary for the major conclusions of the paper.

I disagree with the authors' assessment of Major Point 3 in my review. I have updated the text of Major Point 3 in my public review to further clarify my position.

My final assessment is that if the authors want to claim that DHODH inhibition potentiates immune checkpoint blockade, as is stated in the title, then further in vivo experimentation is needed.

Reviewer #3 (Public Review):

Summary:

In this study, Warfvinge and colleagues use CITE-seq to interrogate how CML stem cells change between diagnosis and after one year of TKI therapy. This provides important insight into why some CML patients are "optimal responders" to TKI therapy while others experience treatment failure. CITE-seq in CML patients revealed several important findings. First, substantial cellular heterogeneity was observed at diagnosis, suggesting that this is a hallmark of CML. Further, patients who experienced treatment failure demonstrated increased numbers of primitive cells at diagnosis compared to optimal responders. This finding was validated in a bulk gene expression dataset from 59 CML patients, in which it was shown that the proportion of primitive cells versus lineage-primed cells correlates to treatment outcome. Even more importantly, because CITE-seq quantifies cell surface protein in addition to gene expression data, the authors were able to identify the BCR/ABL+ and BCR/ABL- CML stem cells express distinct cell surface markers (CD26+/CD35- and CD26-/CD35+, respectively). In optimal responders, BCR/ABL- CD26-/CD35+ CML stem cells were predominant, while the opposite was true in patients with treatment failure. Together, these findings represent a critical step forward for the CML field and may allow more informed development of CML therapies, as well as the ability to predict patient outcomes prior to treatment.

Strengths:

This is an important, beautifully written, well-referenced study that represents a fundamental advance in the CML field. The data are clean and compelling, demonstrating convincingly that optimal responders and patients with treatment failure display significant differences in the proportion of primitive cells at diagnosis, and the ratio of BCR-ABL+ versus negative LSCs. The finding that BCR/ABL+ versus negative LSCs display distinct surface markers is also key and will allow for more detailed interrogation of these cell populations at a molecular level.

Weaknesses:

CITE-seq was performed in only 9 CML patient samples and 2 healthy donors. Additional samples would greatly strengthen the very interesting and notable findings.

Reviewer #2 (Public Review):

The experiments described in the manuscript are well designed and executed. Most of the data presented are of high quality, convincing, and in general support the conclusions made in the manuscript. This manuscript should be of great interest to the field of mammalian gene regulation and the approaches used here can have broader applications in studying genetic and epigenetic regulations of gene expression. The key finding reported here, the importance of 3D chromatin structure in controlling gene expression, although not unexpected, offers a better understanding of the physiological roles of TADs.

Comments on revised version:

I think the authors have substantially addressed reviewers' concerns. I have no further comments to add.

Reviewer #2 (Public Review):

In this manuscript Sangaram et al provide a systematic methodology and pipeline for benchmarking cell type deconvolution algorithms for spatial transcriptomic data analysis in a reproducible manner. They developed a tissue pattern simulator that starts from single-cell RNA-seq data to create silver standards and used spatial aggregation strategies from real in situ-based spatial technologies to obtain gold standards. By using several established metrics combined with different deconvolution challenges they systematically scored and ranked 12 different methods and assessed both functional and usability criteria. Altogether, they present a reusable and extendable platform and reach very similar conclusions to other deconvolution benchmarking paper, including that RCTD, SpatialDWLS and Cell2location typically provide the best results. Major strengths of the simulation engine include the ability to downsample and recapitulate several cell and tissue organization patterns.

More specifically, the authors of this study sought to construct a methodology for benchmarking cell type deconvolution algorithms for spatial transcriptomic data analysis in a reproducible manner. The authors leveraged publicly available scRNA-seq, seqFISH, and STARMap datasets to create synthetic spatial datasets modeled after that of the Visium platform. It should be noted that the underlying experimental techniques of seqFISH and STARMap (in situ hybridization) do not parallel that of Visium (sequencing), which could potentially bias simulated data. Furthermore, to generate the ground truth datasets cells and their corresponding count matrix are represented by simple centroids. Although this simplifies the analysis it might not necessarily accurately reflect Visium spots where cells could lie on a boundary and affect deconvolution results.

The authors thoroughly and rigorously compare methods while addressing situational discrepancies in model performance, indicative of a strong analysis. The authors make a point to address both inter- and intra- dataset reference handling, which has a significant impact on performance, as the authors note in the text and conclusions. Indeed, supplying optimal reference data is - potentially most - important to achieve the best performance and hence it's important to understand that experimental design or sample matching is at least equally important to selecting the ideal deconvolution tool.

Similarly, the authors conclude that many methods are still outperformed by bulk deconvolution methods (e.g. Music or NNLS), however, it needs to be noted that these 'bulk' methods are also among the most sensitive when using an external (inter) dataset (S10), which likely resembles the more realistic scenario for most labs.

As the authors also discuss it's important to realize that deconvolution approaches are typically part of larger exploratory data analysis (EDA) efforts and require users to change parameters and input data multiple times. Thus, running time, computing needs, and scalability are probably key factors that researchers would like to consider when looking to deconvolve their datasets.

The authors achieve their aim to benchmark different deconvolution methods and the results from their thorough analysis support the conclusions that creating cell type deconvolution algorithms that can handle both cell abundance and rarity throughout a given tissue sample are challenging.

The reproducibility of the methods described will have significant utility for researchers looking to develop cell type deconvolution algorithms, as this platform will allow simultaneous replication of the described analysis and comparison to new methods.

Reviewer #2 (Public Review):

Summary:

Preeclampsia is a disorder of pregnancy that affects 4-5% of pregnancies worldwide. Identifying this condition early is clinically relevant as it will help clinicians to make management decisions to prevent adverse outcomes. The placenta holds a key to many pregnancy-related pathologies including preeclampsia and studies have shown many differences in the placenta of women with preeclampsia as compared to controls. However as the placenta cannot be collected directly during pregnancy, the exosomes secreted by it are considered a good alternative to tissue biopsy. In this study, the authors have compared the proteins in different sizes of exosomes from the placenta of women with and without preeclampsia. The idea is to eventually use these as biomarkers for early detection of preeclampsia.

Strengths:

The novelty factor of this study is the use of two different-sized exosomes which has not been achieved earlier.

Weaknesses:

The study measured the proteins at only a single time point after the disease has already occurred. However, the placenta is an ever-changing tissue throughout pregnancy and different proteins can come up at different times in pregnancy. Thus serial measurements are necessary and a single time point measurement. The has not validated the identified biomarkers in plasma or circulating placental exosomes from women with and without preeclampsia. Thus the utility of these findings in real-life situations can not be judged from this work.

Reviewer #3 (Public Review):

The authors investigate the mechanisms by which ISG65 and C3 recognize and interact with each other. The major strength is the identification of exo-site by determining the cryoEM structure of the complex, which suggests new intervention strategies. This is a solid body of work that has an important impact in parasitology, immunology, and structural biology.

Comments on revised version:

The authors have addressed all the previous concerns.

Reviewer #3 (Public Review):

The manuscript by Bimai et al describes a structural and functional characterization of an anaerobic ribonucleotide reductase (RNR) enzyme from the human microbe, P. copri. More specifically, the authors aimed to characterize the mechanism by how (d)ATP modulates nucleotide reduction in this anaerobic RNR, using a combination of enzyme kinetics, binding thermodynamics, and cryo-EM structural determination, complemented by hydrogen-deuterium exchange (HDX). One of the principal findings of this paper is the ordering of a NxN 'flap' in the presence of ATP that promotes RNR catalysis and the disordering (or increased protein dynamics) of both this flap and the glycyl radical domain (GRD) when the inhibitory effector, dATP, binds. The latter is correlated with a loss of substrate binding, which is the likely mechanism for dATP inhibition. It is important to note that the GRD is remote (>30 Ang) from the binding site of the dATP molecule, suggesting long-range communication of the structural (dis)ordering. The authors also present evidence for a shift in oligomerization in the presence of dATP. The work does provide evidence for new insights/views into the subtle differences of nucleotide modulation (allostery) of RNR, in a class III system, through long-range interactions.

The strengths of the work are the impressive, in-depth structural analysis of the various regulated forms of PcRNR by (d)ATP using cryo-EM. The authors present seven different models in total, with striking differences in oligomerization and (dis)ordering of select structural features, including the GRD that is integral to catalysis. The authors present several, complementary biochemical experiments (ITC, MST, EPR, kinetics) aimed at resolving the binding and regulatory mechanism of the enzyme by various nucleotides. The authors present a good breadth of the literature in which the focus of allosteric regulation of RNRs has been on the aerobic orthologues.

The addition of hydrogen-deuterium exchange mass spectrometry (HDX-MS) complements the results originating from cryo-EM data. Most notably, is the observation of the enhanced exchange (albeit quite subtle) of the GRD domain in the presence of dATP that matches the loss of structural information in this region in the cryo-EM data. The most pronounced and compelling HDX results are seen in the form of dATP-induced protection of peptides immediately adjacent to the b-hairpin at the s-site, where dATP is expected to bind based on cryo-EM. It is clear that the presence of dATP increases the rigidity of this region.

Weaknesses: The discussion of the change in peptide mobility in the N-terminal region is complicated by the presence of bimodal mass spectral features and this may prevent detailed interpretation of the data, especially for select peptide region that shows opposite trends upon nucleotide association. Further, the HDX data in the NxN flap is unchanged upon nucleotide binding (ATP, dATP, or CTP), despite changes observed in the cryo-EM data.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors examine how temporal expression of the lin-4 microRNA is transcriptionally regulated.

Comments on revised version:

In the revised manuscript, the authors have suitably addressed my original concerns.

Aims achieved: The aims of the work are now achieved.

Impact: This study shows that a single transcription factor (MYRF-1) is important for the regulation of multiple microRNAs that are expressed early in development to control developmental timing.

Reviewer #3 (Public Review):

Summary:

Combining several MD simulation techniques (NMR-constrained replica-exchange metadynamics, Markov State Model, and unbiased MD) the authors identified the aC-beta4 loop of PKA kinase as a switch crucially involved in PKA nucleotide/substrate binding cooperatively. They identified a previously unreported excited conformational state of PKA (ES2), this switch controls and characterized ES2 energetics with respect to the ground state. Based on translating the simulations into chemical shits and NMR characterizing of PKA WT and an aC-beta4 mutant, the author made a convincing case in arguing that the simulation-suggested excited state is indeed an excited state observed by NMR, thus giving the excited state conformational details.

Strengths:

This work incorporates extensive simulation works, new NMR data, and in vitro biochemical analysis. It stands out in its comprehensiveness, and I think it made a great case.

Weaknesses:

The manuscript is somewhat difficult to read even for kinase experts, and even harder for the layman. The difficulty partially arises from mixing the technical description of the simulations with the structural interpretation of the results, which is more intuitive, and partially arises from the assumption that readers are familiar with kinase architecture and its key elements (the aC helix, the APE motif, etc).

Reviewer #2 (Public Review):

Summary

The goal of untargeted metabolomics is to identify differences between metabolomes of different biological samples.

Untargeted metabolomics identifies features with specific mass-to-charge-ratio (m/z) and retention time (RT). Matching those to specific metabolites based on the model compounds from databases is laborious and not always possible, which is why methods for comparing samples on the level of unmatched features are crucial.<br /> The main purpose of the GromovMatcher method presented here is to merge and compare untargeted metabolomes from different experiments. These larger datasets could then be used to advance biological analyses, for example, for identification of metabolic disease markers.

The main problem that complicates merging different experiments is that m/z and RT vary slightly for the same feature (metabolite).

The main idea behind the GromovMatcher is built on the assumption that if two features match between two datasets (that feature i from dataset 1 matches feature j from dataset 2, and feature k from dataset 1 matches feature l from dataset 2), then the correlations or distances between the two features within each of the datasets (i and k, and j and l) will be similar. The authors then use the Gromov-Wasserstein method to find the best matches matrix from these data.

The variation in m/z between the same features in different experiments is a user-defined value and it is initially set to 0.01 ppm. There is no clear limit for RT deviations, so the method estimates a non-linear deviation (drift) of RT between two studies. GromovMatcher estimates the drift between two studies, and then discards the matching pairs where the drift would deviate significantly from the estimate. It learns the drift from a weighted spline regression.

The authors validate the performance of their GromovMatcher method using a dataset of cord blood. They use 20 different splits and compare the GromovMatcher (both its GM and GMT iterations, whereby GMT version uses the deviation from estimated RT drift to filter the matching matrix) with two other matching methods: M2S and metabCombiner.

The second validation was done using a (scaled and centered) dataset of metabolics from cancer datasets from the EPIC cohort that were manually matched by an expert. This dataset was also used to show that using automated methods can identify more features that are associated with a particular group of samples than what was found by manual matching. Specifically, the authors identify additional features connected to alcohol consumption.

Strengths:

I see the main strength of this work in its combination of all levels of information (m/z, RT, and higher-order information on correlations between features) and using each of the types of information in a way that is appropriate for the measure. The most innovative aspect is using the Gromov-Wasserstein method to match the features based on distance matrices.

The authors of the paper identify two main shortcomings with previously established methods that attempt to match features from different experiments: a) all other methods require fine-tuning of user-defined parameters, and, more importantly, b) do not consider correlations between features. The main strength of the GromovMatcher is that it incorporates the information on distances between the features (in addition to also using m/z and RT).

Weaknesses:

The main weakness is that there seem not to be enough manually curated datasets that could be used for validation. It will, therefore, be important, for the authors, and the field in general to keep validating and improving their methods if more datasets become available.

The second weakness, as emphasized by the authors in the discussion is that the method as it is set up now can be directly used only to compare two datasets. I am confident that the authors will successfully implement novel algorithms to address this issue in the future.

Reviewer #2 (Public Review):

Summary:

This study explores theoretically the consequences of structural fluctuations of the endoplasmic reticulum (ER) morphology called contractions on molecular transport. Most of the manuscript consists of the construction of an interesting theoretical flow field (physical model) under various hypothetical assumptions. The computational modeling is followed by some simulations

Strengths:

The authors are focusing their attention on testing the hypothesis that a local flow in the tubule could be driven by tubular pinching. We recall that trafficking in the ER is considered to be mostly driven by diffusion at least at a spatial scale that is large enough to account for averaging of any random flow occurring from multiple directions [note that this is not the case for plants].

Weaknesses:

The manuscript extensively details the construction of the theoretical model, occupying a significant portion of the manuscript. While this section contains interesting computations, its relevance and utility could be better emphasized, perhaps warranting a reorganization of the manuscript to foreground this critical aspect.

Overall, the manuscript appears highly technical with limited conclusive insights, particularly lacking predictions confirmed by experimental validation. There is an absence of substantial conclusions regarding molecular trafficking within the ER.

Reviewer #2 (Public Review):

Summary:

This manuscript from Lee-Odegard et al reports proteomic profiling of exercise plasma in humans, leading to the discovery of CD300LG as a secreted exercise-inducible plasma protein. Correlational studies show associations of CD300LG with glycemic traits. Lastly, the authors query available public data from CD300LG-KO mice to establish a causal role for CD300LG as a potential link between exercise and glucose metabolism. However, the strengths of this manuscript were balanced by the moderate to major weaknesses. Therefore in my opinion, while this is an interesting study, the conclusions remain preliminary and are not fully supported by the experiments shown so far.

Strengths:

(1) Data from a well-phenotyped human cohort showing exercise-inducible increases in CD300LG.

(2) Associations between CD300LG and glucose and other cardiometabolic traits in humans, that have not previously been reported.

(3) Correlation to CD300LG mRNA levels in adipose provides additional evidence for exercise-inducible increases in CD300LG.

Weaknesses:

(1) CD300LG is by sequence a single-pass transmembrane protein that is exclusively localized to the plasma membrane. How CD300LG can be secreted remains a mystery. More evidence should be provided to understand the molecular nature of circulating CD300LG. Is it full-length? Is there a cleaved fragment? Where is the epitope where the o-link is binding to CD300LG? Does transfection of CD300LG to cells in vitro result in secreted CD300LG?

(2) There is a growing recognition of specificity issues with both the O-link and somalogic platforms. Therefore it is critical that the authors use antibodies, targeted mass spectrometry, or some other methods to validate that CD300LG really is increased instead of just relying on the O-link data.

(3) It is insufficient simply to query the IMPC phenotyping data for CD300LG; the authors should obtain the animals and reproduce or determine the glucose phenotypes in their own hands. In addition, this would allow the investigators to answer key questions like the phenotype of these animals after a GTT, whether glucose production or glucose uptake is affected, whether insulin secretion in response to glucose is normal, effects of high-fat diet, and other standard mouse metabolic phenotyping assays.

(4) I was unable to find the time point at which plasma was collected at the 12-week time point. Was it immediately after the last bout of exercise (an acute response) or after some time after the training protocol (trained state)?

Reviewer #2 (Public Review):

Summary:

The authors have developed marker selection and k-means (k=2) based binary clustering algorithm for the first-level supervised clustering of the CyTOF dataset. They built a seamless pipeline that offers the multiple functionalities required for CyTOF data analysis.

Strengths:

The strength of the study is the potential use of the pipeline for the CyTOF community as a wrapper for multiple functions required for the analysis. The concept of the first line of binary clustering with known markers can be practically powerful.

Weaknesses:

The weakness of the study is that there's little conceptual novelty in the algorithms suggested from the study and the benchmarking is done in limited conditions.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors start by showing that HCN loss-of-function mutation causes a decrease in spiking in bitter GRNs (bGRN) while leaving sweet GRN (sGRN) response in the same sensillum intact. They show that a perturbation of HCN channels in sweet-sensing neurons causes a similar decrease while increasing the response of sugar neurons. They were also able to rescue the response by exogenous expression. Ectopic expression of HCN in bitter neurons had no effect. Next, they measure the sensillum potential and find that sensillum potential is also affected by HCN channel perturbation. These findings lead them to speculate that HCN in sGRN increases sGRN spiking which in turn affects bGRNs. To test this idea that carried out multiple perturbations aimed at decreasing sGRN activity. They found that decreasing sGRN activity by either using receptor mutant or by expressing Kir (a K+ channel) in sGRN increased bGRN responses. These responses also increase the sensillum potential. Finally, they show that these changes are behaviorally relevant as conditions that increase sGRN activity decrease avoidance of bitter substances.

Strengths:

There is solid evidence that perturbation of sweet GRNs affects bitter GRN in the same sensillum. The measurement of transsynaptic potential and how it changes is also interesting and supports the authors' conclusion.

Weaknesses:<br /> The ionic basis of how perturbation in GRN affects the transepithelial potential which in turn affects the second neuron is not clear.

Reviewer #2 (Public Review):

The authors used a whole genome CRISPR screen to identify targetable synthetic lethalities associated with PPM1D mutations, known poor prognosis and currently undruggable factors in leukemia. The authors identified the cytosolic superoxide dismutase (SOD1, Cu/Zn SOD) as a major protective factor in PPMD1 mutant vs. wt cells, and their study investigates associated mechanisms of this protection. Using both genetic depletion and small molecule inhibitors of SOD1, the authors conclude that SOD1 loss exacerbates mitochondrial dysfunction, ROS levels and DNA damage phenotypes in PPM1D mutant cells, decreasing cell growth in AML cells. The data strongly support that PPMD1 mutant cells have high levels of total peroxides and elevated DNA breaks, and that genetic depletion of SOD1 decreases cell growth in two AML cell lines. However, the authors don't explain how superoxide radical (which is not damaging by itself) induces such damage, the on-target effects of the SOD1 inhibitors at the concentrations is not clear, the increase in total hydroperoxides is not supported by loss of SOD1, the changes in mitochondrial function are small, and there is no assessment of how the mitochondrial SOD2 expression or function, which dismutates mitochondrial superoxide, is altered. Overall these studies do not distinguish between signal vs. damaging aspects of ROS in their models and do not rule out an alternate hypothesis that loss of SOD1 increases superoxide production by cytosolic NADPH activity which would significantly alter ROS-driven regulation of kinase/phosphatase signal modulation, affecting cell growth and proliferation as well as DNA repair. Additionally, with the exception of growth defects demonstrated with sgSOD1, the majority of data are acquired using two chemical inhibitors, LCS1 and ATN-224, without supporting evidence that these inhibitors are acting in an on-target manner.

Overall, the authors address an important problem by seeking targetable vulnerabilities in PPM1D mutant AML cells, it is clear SOD1 deletion induces strong growth defects in the AML cell lines tested, most of the approaches are appropriate for the outcomes being evaluated, and the data are technically solid and well-presented. The major weakness lies in which redox pathways and ROS species are evaluated, how the resulting data are interpreted, and gaps in the follow-up experiments. Due to these omissions, as currently presented, the broader impact of these findings are unclear.

These specific concerns are outlined in detail below and I offer some suggestions regarding how to clarify the mechanisms underlying their initial observation of SOD1 synthetic lethality:

(1) Fig. 1 - SOD1 appears to be clustered with several other genes in the volcano plot (including FANC proteins). Did any other ROS-detoxifying enzymes show similar fitness scores? The effects of the SOD1 sgRNA are striking, however it would be useful to see qPCR or immunoblot data confirming robust depletion.

Does SOD1 co-expression in PPM1-mutant patient AML correspond to poorer disease outcomes? This can be evaluated in publicly available patient datasets and would support the idea of SOD1 synthetic lethality.

It would also be useful to know (given the subsequent results) whether expression of the SOD2, the mitochondrial superoxide dismutase, is altered in response to SOD1 loss.

(2) Fig. 2 - What are the relative SOD1 levels in the mutant PPM1D vs. wt. cell lines? The effects of the chemical inhibitors are stronger in MOLM-13 than the other two lines. These data could also point to whether LCS-1 and ATN-224 cytotoxicity is on-target or off-target at these concentrations, which is a key issue not currently addressed in these studies. This is a particular concern as the OCI-AML2 line shows a stronger growth defect with CRISPR SOD1 KO (in Fig 1) but the smallest effects with these chemical inhibitors.

While endogenous mitochondrial superoxide levels are elevated in PPM1D mutant lines, it is entirely unclear why SOD1 inhibition should affect mitochondrial superoxide as it detoxifies cytosolic superoxide. Also unclear why DCFDA signal (which measures total hydroperoxides) is *increased* under SOD1 inhibition - SOD1 dismutates superoxide radicals into hydrogen peroxide, therefore unless SOD2 is compensating for SOD1 loss, one might expect hydroperoxides to be lower (unless some entirely different oxidase is increasing their levels). None of these outcomes appear to be considered. Finally, it is not explained how lipid peroxidation, which requires production of hydroxyl or similarly high potency radicals, is being caused by increased superoxide or peroxides. One possibility is there is an increase in labile iron, in which case this phenotype would be rescued by the iron chelator desferal, and by the lipophilic antioxidant, ferrostatin.

Do the sgSOD1 cells also show similar increases in MitoSox green, DCFDA and BODIPY signal? These experiments would clarify whether the effects with the inhibitors are directly related directly to SOD1 loss or if they represent off-target effects from the inhibitors and/or compensatory changes in SOD2.

(3) Fig. 3 - the effects on mitochondrial respiratory parameters, while statistically significant, do not seem biologically striking. Also, these data are shown for OCI-AML2 cells which show the smallest cytotoxic effects with the SOD1 inhibitors among the 3 lines tested. They do however show the most robust growth defect with sgSOD1. This discrepancy could suggest that mitochondrial dysfunction does not underlie the observed growth defect and/or the inhibitor cytotoxicity is not on-target. Ideally mitochondrial profiling should also be carried out on this cell line with inducible SOD1 depletion. Have the authors assessed whether the mitochondrial Bcl family proteins are affected by the inhibitors?

(4) Fig. 4 - Currently the data in this figure do not support the authors claim that PPM1D-mutant cells have impaired antioxidant defense mechanisms, leading to an elevation in ROS levels and reliance on SOD1 for protection. It should be noted that oxidative stress specifically refers to adverse cellular effects of increasing ROS, not baseline levels of various redox parameters. Ideally levels of GSSG/GSH would be a better measure of potential redox stress tolerance than the total antioxidant capacity assay. Finally, oxidative stress can be assessed by challenging the wt and mutant PPM1D cell lines with oxidant stressors such as paraquat which elevates superoxide or drugs like erastin which elevate mitochondrial ROS. The immunoblot shows negligible changes in the antioxidant proteins assayed. Again, this blot should include SOD2 which is the most relevant antioxidant in the context of mitochondrial superoxide.

(5) Fig. 5 - These data support that DNA breaks are elevated in PPM1D mutant vs. wt cells. However, the data with the chemical SOD1 inhibitor again do not convince that the enhanced levels are due to on-target effects on SOD1. Use of the alkaline comet assay is appropriate for these studies and the 8-oxoguanine data do indicate contributions from oxidative DNA base damage. But these are unlikely to result directly from altered superoxide levels, as this species cannot directly oxidize DNA bases or cause DNA strand breaks.

The following points summarize my specific experimental and textual recommendations:

(1) These studies require an assessment of on-target efficacy of the inhibitors at the relevant concentration ranges. Ideally, they should have minimal effects against SOD1 knockout cell lines (acute challenge at a time point before the growth defects become apparent) and show better efficacy in SOD1-overexpressing lines. Key experiments (changes in superoxide, OCR profiling, DNA alkaline comet assay) would be more convincing if they are carried out with SOD1 knockout lines to compare against the inhibitor effects (3-4 days after introducing sgSOD1 when growth defects are not apparent).

(2) Instead of using NAC, which elevates glutathione synthesis but also has several known side-effects, the authors may want to determine whether Tempol, a SOD mimetic can rescue the effects of SOD1 knockout or inhibition. This would directly prove that SOD1 functional loss underlies the observed growth defect and cytotoxicity from genetic SOD1 knockdown or chemical inhibition.

(3) The complete lack of consideration of SOD2 in these studies is a missed opportunity as it reduces mitochondrial superoxide levels but elevates hydrogen peroxide levels. It would be very interesting to see whether SOD1 inhibition leads to compensatory increases in SOD2. SOD2 can be easily measured by immunoblot. Furthermore, measuring total superoxide via hydroethidium in a flow cytometric assay vs. mitochondrial ROS in PPM1D mut vs. wt cells and under SOD1 knockout would enable a determination of which species dominates (cytosolic or mitochondrial). These experiments are required to fill some logical gaps in interpretation of their redox data.

(4) Given the DNA breaks observed in PPM1D mutant cells, it is highly recommended the authors assess whether iron levels are elevated in mut vs. wt cells and whether desferal can rescue observed SOD1 inhibition defects.

(5) The authors may want to assess whether Rac1 or NADPH oxidase activity is altered in the SOD1 KO in wt vs. PPM1D cells. Their results may be the consequence of compromised ROS-driven survival signaling or DNA repair rather than direct ROS-induced damage, which is not caused directly by superoxide (or hydrogen peroxide).

(6) It is recommended the discussion focus more strongly on how the signaling function of superoxide vs. its reactions with other molecular entities to induce genotoxic outcomes could be contributing to the observed phenotypes. The discussion of FANC proteins, which were targets with similar fitness scores but not experimentally investigated at all, is an unwarranted digression.

Reviewer #2 (Public Review):

Boocock and colleagues present an approach whereby eQTL analysis can be carried out by scRNA-Seq alone, in a one-pot-shot experiment, due to genotypes being able to be inferred from SNPs identified in RNA-Seq reads. This approach obviates the need to isolate individual spores, genotype them separately by low-coverage sequencing, and then perform RNA-Seq on each spore separately. This is a substantial advance and opens up the possibility to straightforwardly identify eQTLs over many conditions in a cost-efficient manner. Overall, I found the paper to be well-written and well-motivated, and have no issues with either the methodological/analytical approach (though eQTL analysis is not my expertise), or with the manuscript's conclusions.

I do have several questions/comments.

393 segregant experiment:<br /> For the experiment with the 393 previously genotyped segregants, did the authors examine whether averaging the expression by genotype for single cells gave expression profiles similar to the bulk RNA-Seq data generated from those genotypes? Also, is it possible (and maybe not, due to the asynchronous nature of the cell culture) to use the expression data to aid in genotyping for those cells whose genotypes are ambiguous? I presume it might be if one has a sufficient number of cells for each genotype, though, for the subsequent one-pot experiments, this is a moot point.

Figure 1B:<br /> Is UMAP necessary to observe an ellipse/circle - I wouldn't be surprised if a simple PCA would have sufficed, and given the current discussion about whether UMAP is ever appropriate for interpreting scRNA-Seq (or ancestry) data, it seems the PCA would be a preferable approach. I would expect that the periodic elements are contained in 2 of the first 3 principal components. Also, it would be nice if there were a supplementary figure similar to Figure 4 of Macosko et al (PMID 26000488) to indeed show the cell cycle dependent expression.

Aging, growth rate, and bet-hedging:<br /> The mention of bet-hedging reminded me of Levy et al (PMID 22589700), where they saw that Tsl1 expression changed as cells aged and that this impacted a cell's ability to survive heat stress. This bet-hedging strategy meant that the older, slower-growing cells were more likely to survive, so I wondered a couple of things. It is possible from single-cell data to identify either an aging, or a growth rate signature? A number of papers from David Botstein's group culminated in a paper that showed that they could use a gene expression signature to predict instantaneous growth rate (PMID 19119411) and I wondered if a) this is possible from single-cell data, and b) whether in the slower growing cells, they see markers of aging, whether these two signatures might impact the ability to detect eQTLs, and if they are detected, whether they could in some way be accounted for to improve detection.

AIL vs. F2 segregants:<br /> I'm curious if the authors have given thought to the trade-offs of developing advanced intercross lines for scRNA-Seq eQTL analysis. My impression is that AIL provides better mapping resolution, but at the expense of having to generate the lines. It might be useful to see some discussion on that.

10x vs SPLit-Seq<br /> 10x is a well established, but fairly expensive approach for scRNA-Seq - I wondered how the cost of the 10x approach compares to the previously used approach of genotyping segregants and performing bulk RNA-Seq, and how those costs would change if one used SPLiT-Seq (see PMID 38282330).

Reviewer #2 (Public Review):

Summary:

In this manuscript, using Staphylococcus aureus as a model organism, Panda et al. aim to understand how organic acids inhibit bacterial growth. Through careful characterization and interdisciplinary collaboration, the authors present valuable evidence that acetic acid specifically inhibits the activity of Ddl enzyme that converts 2 D-alanine amino acids into D-ala-D-ala dipeptide, which is then used to generate the stem pentapeptide of peptidoglycan (PG) precursors in the cytoplasm. Thus, a high concentration of acetic acid weakens the cell wall by limiting PG-crosslinking (which requires a D-ala portion). However, S. aureus maintains a high intracellular D-ala concentration to circumvent acetate-mediated growth inhibition.

Strengths:

The authors utilized a well-established transposon mutant library to screen for mutants that struggle to grow in the presence of acetic acid. This screen allowed authors to identify that a strain lacking intact alr1, which encodes for alanine racemase (converts L-ala to D-ala), is unable to grow well in the presence of acetic acid. This phenotype is rescued by the addition of external D-ala. Next, the authors rule out the contribution of other pathways that could lead to the production of D-ala in the cell. Finally, by analyzing D-ala and D-ala-D-ala concentrations, as well as muropeptide intermediates accumulation in different mutants, the authors pinpoint Ddl as the specific target of acetic acid. In fact, the synthetic overexpression of ddl alone overcomes the toxic effects of acetic acid. Using genetics, biochemistry, and structural biology, the authors show that Ddl activity is specifically inhibited by acetic acid and likely by other biologically relevant organic acids. Interestingly, this mechanism is different from what has been reported for other organisms such as Escherichia coli (where methionine synthesis is affected). It remains to be seen if this mechanism is conserved in other organisms that are more closely related to S. aureus, such as Clostridioides difficile and Enterococcus faecalis.

Weaknesses:

Although the authors have conclusively shown that Ddl is the target of acetic acid, it appears that the acetic acid concentration used in the experiments may not truly reflect the concentration range S. aureus would experience in its environment. Moreover, Ddl is only significantly inhibited at a very high acetate concentration (>400 mM). Thus, additional experiments showing growth phenotypes at lower organic acid concentrations may be beneficial. Another aspect not adequately discussed is the presence of D-ala in the gut environment, which may be protective against acetate toxicity based on the model provided.

Reviewer #2 (Public Review):

Jarysta and colleagues set out to define how similar GNAI/O family members contribute to the shape and orientation of stereocilia bundles on auditory hair cells. Previous work demonstrated that loss of particular GNAI proteins, or inhibition of GNAIs by pertussis toxin, caused several defects in hair bundle morphogenesis, but open questions remained which the authors sought to address. Some of these questions include whether all phenotypes resulting from expression of pertussis toxin stemmed from GNAI inhibition; which GNAI family members are most critical for directing bundle development; whether GNAI proteins are needed for basal body movements that contribute to bundle patterning. These questions are important for understanding how tissue is patterned in response to planar cell polarity cues.

To address questions related to the GNAI family in auditory hair cell development, the authors assembled an impressive and nearly comprehensive collection of mouse models. This approach allowed for each Gnai and Gnao gene to be knocked out individually or in combination with each other. Notably, a new floxed allele was generated for Gnai3 because loss of this gene in combination with Gnai2 deletion was known to be embryonic lethal. Besides these lines, a new knockin mouse was made to conditionally express untagged pertussis toxin following cre induction from a strong promoter. The breadth and complexity involved in generating and collecting these strains makes this study unique, and likely the authoritative last word on which GNAI proteins are needed for which aspect of auditory hair bundle development.

Appropriate methods were employed by the authors to characterize auditory hair bundle morphology in each mouse line. Conclusions were carefully drawn from the data and largely based on excellent quantitative analysis. The main conclusions are that GNAI3 has the largest effect on hair bundle development. GNAI2 can compensate for GNAI3 loss in early development but incompletely in late development. The Gnai2 Gnai3 double mutant recapitulates nearly all the phenotypic effects associated with pertussis toxin expression and also reveals a role for GNAIs in early movement of the basal body. This comprehensive study builds on earlier reports, both uncovering new functions and putting previously putative functions on solid ground.

Reviewer #3 (Public Review):

Summary: Through a rigorous methodology, the authors demonstrated that within 11 different primates, the shape of the brain followed a universal scaling law with fractal properties. They enhanced the universality of this result by showing the concordance of their results with a previous study investigating 70 mammalian brains, and the discordance of their results with other folded objects that are not brains. They incidentally illustrated potential applications of this fractal property of the brain by observing a scale-dependant effect of aging on the human brain.

Strengths:<br /> - New hierarchical way of expressing cortical shapes at different scales derived from previous report through implementation of a coarse-graining procedure<br /> - Investigation of 11 primate brains and contextualisation with other mammals based on prior literature<br /> - Proposition of tool to analyse cortical morphology requiring no fine tuning and computationally achievable<br /> - Positioning of results in comparison to previous works reinforcing the validity of the observation.<br /> - Illustration of scale-dependance of effects of brain aging in the human.

Weaknesses:<br /> - The notion of cortical shape, while being central to the article, is not really defined, leaving some interpretation to the reader<br /> - The organization of the manuscript is unconventional, leading to mixed contents in different sections (sections mixing introduction and method, methods and results, results and discussion...). As a result, the reader discovers the content of the article along the way, it is not obvious at what stages the methods are introduced, and the results are sometimes presented and argued in the same section, hindering objectivity.<br /> To improve the document, I would suggest a modification and restructuring of the article such that: 1) by the end of the introduction the reader understands clearly what question is addressed and the value it holds for the community, 2) by the end of the methods the reader understands clearly all the tools that will be used to answer that question (not just the new method), 3) by the end of the results the reader holds the objective results obtained by applying these tools on the available data (without subjective interpretations and justifications), and 4) by the end of the discussion the reader understands the interpretation and contextualisation of the study, and clearly grasps the potential of the method depicted for the better understanding of brain folding mechanisms and properties.

Reviewer #2 (Public Review):

Summary:

Carabalona and colleagues investigated the role of the membrane-deforming cytoskeletal regulator protein Abba (MTSS1L/MTSS2) in cortical development to better understand the mechanisms of abnormal neural stem cell mitosis. The authors used short hairpin RNA targeting Abba20 with a fluorescent reporter coupled with in-utero electroporation of E14 mice to show changes to neural progenitors. They performed flow cytometry for in-depth cell cycle analysis of Abba-shRNA impact on neural progenitors and determined an accumulation in the S phase. Using culture rat glioma cells and live imaging from cortical organotypic slides from mice in utero electroporated with Abba-shRNA, the authors found Abba played a prominent role in cytokinesis. They then used a yeast-two-hybrid screen to identify three high-confidence interactors: Beta-Trcp2, Nedd9, and Otx2. They used immunoprecipitation experiments from E18 cortical tissue coupled with C6 cells to show Abba's requirement for Nedd9 localization to the cleavage furrow/cytokinetic bridge. The authors performed a shRNA knockdown of Nedd9 by in-utero electroporation of E14 mice and observed similar results as with the Abba-shRNA. They tested a human variant of Abba using in-utero electroporation of cDNA and found disorganized radial glial fibers and misplaced, multipolar neurons, but lacked the impact of cell division seen in the shRNA-Abba model.

Strengths:

A fundamental question in biology about the mechanics of neural stem cell division.

Directly connecting effects in Abba protein to downstream regulation of RhoA via Nedd9.

Incorporation of human mutation in ABBA gene.

Use of novel technologies in neurodevelopment and imaging.

Weaknesses:

Unexplored components of the pathway (such as what neurogenic populations are impacted by Abba mutation) and unleveraged aspects of their data (such as the live imaging) limit the scope of their findings and leave significant questions about the effect of ABBA on radial glia development.

(1) The claim of disorganized radial glial fibers lacks quantifications.<br /> On page 11, the authors claim that knockdown of Abba leads to changes in radial glial morphology observed with vimentin staining. Here they claim misoriented apical processes, detached end feet, and decreased number of RGP cells in the VZ. However, they do not provide quantification of process orientation to better support their first claim. Measurements of radial glia fiber morphology (directionality, length) and angle of division would be metrics that can be applied to data. Some of these analyses could be done in their time-lapse microscopy images, such as to quantify the number of cell divisions during their period of analysis (though that is short-15 hours).

(2) It is unclear where the effect is:

-In RG or neuroblasts? Is it in cell cleavage that results in the accumulation of cells at VZ (as sometimes indicated by their data like in Figure 2A or 4D)? Interrogation of cell death (such as by cleaved caspase 3) would also help. Given their time-lapse, can they identify what is happening to the RG fiber? The authors describe a change in "migration" but do not show evidence for this for either progenitor or neuroblast populations. Given they have nice time-lapse imaging data, could they visualize progenitor versus young neuron migration? Analysis of neuroblasts (such as with doublecortin expression in the tissue) would also help understand any issues in migration (of neurons v stem cells).

-At cleavage furrow? In abscission? There is high-resolution data that highlights the cleavage furrow as the location of interest (Figure 3A), however, there is also data (Figure 3B) to suggest Abba is expressed elsewhere as well and there is an overall soma decrease. More detail of the localization of Abba during the division process would be helpful for example, could cleavage furrow proteins, such as Aurora B, co-localization (and potentially co-IP) help delineate subpopulations of Abba protein? Furthermore, the FRET imaging is a unique way to connect their mutation with function - could they measure/quantify differences at furrow compared to the rest of soma to further corroborate that the Abba-associated RhoA effect was furrow-enriched?

-The data highlights nicely that a furrow doesn't clearly form when ABBA expression and subsequent RhoA activity are decreased (in Figure 3 or 5A). Does this lead to cells that can't divide because of poor abscission, especially since "rounding" still occurs? Or abnormal progenitors (with loss of fiber or inability to support neuroblast migration)? Or abnormal progression of progenitors to neuroblasts?

(3) Limited to a singular time point of mouse cortical development

On page 13, the authors outline the results of their Y2H screen with the identification of three high-confidence interactors. Notably, they used an E10.5-E12.5 mouse brain embryo library rather than one that includes E14, the age of their in-utero electroporation mice. Many of the authors' claims focus on in-utero electroporation of shRNA-Abba of E14 mice that are then evaluated at E16-18. Justification for the focus on this age range should be included to support that their findings can then be applied to all mouse corticogenesis.

(4) Detail of the effect of the human variant of the ABBA mutation in mice is lacking.

Their identification of the R671W mutation is interesting and the IUE model warrants more characterization, as they did with their original KD experiments.

-Could they show that Abba protein levels are decreased (in either cell lines or electroporated tissue)?

-While time-lapse morphology might not have been performed, more analysis on cell division phenotype (such as plane of division and radial glia morphology) would be helpful.

Reviewer #2 (Public Review):

The manuscript details an investigation aimed at developing a protocol to render centimeter-scale formalin-fixed paraffin-embedded specimens optically transparent and suitable for deep immunolabeling. The authors evaluate various detergents and conditions for epitope retrieval such as acidic or basic buffers combined with high temperatures in entire mouse brains that had been paraffin-embedded for months. They use various protein targets to test active immunolabeling and light-sheet microscopy registration of such preparations to validate their protocol. The final procedure, called MOCAT pipeline, briefly involves 1% Tween 20 in citrate buffer, heated in a pressure cooker at 121 {degree sign}C for 10 minutes. The authors also note that part of the delipidation is achieved by the regular procedure.

Major Strengths<br /> - The simplicity and ease of implementation of the proposed procedure using common laboratory reagents distinguish it favorably from more complex methods.

- Direct comparisons with existing protocols and exploration of alternative conditions enhance the robustness and practicality of the methodology.

Final considerations<br /> The evidence presented supports the effectiveness of the proposed method in rendering thick FFPE samples transparent and facilitating repeated rounds of immunolabeling.

The developed procedure holds promise for advancing tissue and 3D-specific determination of proteins of interest in various settings, including hospitals, basic research, and clinical labs, particularly benefiting neuroscience research.

The methodological findings suggest that MOCAT could have broader applications beyond FFPE samples, differentiating it from other tissue-clearing approaches in that the equipment and chemicals needed are broadly accessible.

Reviewer #2 (Public Review):

In this manuscript, Yang et al. present a modeling framework to understand the pattern of response biases and variance observed in delayed-response orientation estimation tasks. They combine a series of modeling approaches to show that coupled sensory-memory networks are in a better position than single-area models to support experimentally observed delay-dependent response bias and variance in cardinal compared to oblique orientations. These errors can emerge from a population-code approach that implements efficient coding and Bayesian inference principles and is coupled to a memory module that introduces random maintenance errors. A biological implementation of such operation is found when coupling two neural network modules, a sensory module with connectivity inhomogeneities that reflect environment priors, and a memory module with strong homogeneous connectivity that sustains continuous ring attractor function. Comparison with single-network solutions that combine both connectivity inhomogeneities and memory attractors shows that two-area models can more easily reproduce the patterns of errors observed experimentally. This, the authors take as evidence that a sensory-memory network is necessary, but I am not convinced about the evidence in support of this "necessity" condition. A more in-depth understanding of the mechanisms operating in these models would be necessary to make this point clear.

Strengths:

The model provides an integration of two modeling approaches to the computational bases of behavioral biases: one based on Bayesian and efficient coding principles, and one based on attractor dynamics. These two perspectives are not usually integrated consistently in existing studies, which this manuscript beautifully achieves. This is a conceptual advancement, especially because it brings together the perceptual and memory components of common laboratory tasks.

The proposed two-area model provides a biologically plausible implementation of efficient coding and Bayesian inference principles, which interact seamlessly with a memory buffer to produce a complex pattern of delay-dependent response errors. No previous model had achieved this.

Weaknesses:

The correspondence between the various computational models is not fully disclosed. It is not easy to see this correspondence because the network function is illustrated with different representations for different models and the correspondence between components of the various models is not specified. For instance, Figure 1 shows that a specific pattern of noise is required in the low-dimensional attractor model, but in the next model in Figure 2, the memory noise is uniform for all stimuli. How do these two models integrate? What element in the population-code model of Figure 2 plays the role of the inhomogeneous noise of Figure 1? Also, the Bayesian model of Figure 2 is illustrated with population responses for different stimuli and delays, while the attractor models of Figures 3 and 4 are illustrated with neuronal tuning curves but not population activity. In addition, error variance in the Bayesian model appears to be already higher for oblique orientations in the first iteration whereas it is only first shown one second into the delay for the attractor model in Figure 4. It is thus unclear whether variance inhomogeneities appear already at the perceptual stage in the attractor model, as it does in the population-code model. Of course, correspondences do not need to be perfect, but the reader does not know right now how far the correspondence between these models goes.

The manuscript does not identify the mechanistic origin in the model of Figure 4 of the specific noise pattern that is required for appropriate network function (with higher noise variance at oblique orientations). This mechanism appears critical, so it would be important to know what it is and how it can be regulated. In particular, it would be interesting to know if the specific choice of Poisson noise in Equation (3) is important. Tuning curves in Figure 4 indicate that population activity for oblique stimuli will have higher rates than for cardinal stimuli and thus induce a larger variance of injected noise in oblique orientations, based on this Poisson-noise assumption. If this explanation holds, one wonders if network inhomogeneities could be included (for instance in neural excitability) to induce higher firing rates in the cardinal/oblique orientations so as to change noise inhomogeneities independently of the bias and thus control more closely the specific pattern of errors observed, possibly within a single memory network.

The main conclusion of the manuscript, that the observed patterns of errors "require network interaction between two distinct modules" is not convincingly shown. The analyses show that there is a quantitative but not a qualitative difference between the dynamics of the single memory area compared to the sensory-memory two-area network, for specific implementations of these models (Figure 7 - Figure Supplement 1). There is no principled reasoning that demonstrates that the required patterns of response errors cannot be obtained from a different memory model on its own. Also, since the necessity of the two-area configuration is highlighted as the main conclusion of the manuscript, it is inconvenient that the figure that carefully compares these conditions is in the Supplementary Material.

The proposed model has stronger feedback than feedforward connections between the sensory and memory modules. This is not a common assumption when thinking about hierarchical processing in the brain, and it is not discussed in the manuscript.

Reviewer #2 (Public Review):

The authors have studied subpopulations of individual neurons recorded in the thalamus and subthalamic nucleus (STN) of awake humans performing a simple cognitive task. They have carefully designed their task structure to eliminate motor components that could confound their analyses in these subcortical structures, given that the data was recorded in patients with Parkinson's Disease (PD) and diagnosed with an Essential Tremor (ET). The recorded data represents a promising addition to the field. The analyses that the authors have applied can serve as a strong starting point for exploring the kinds of complex signals that can emerge within a single neuron's activity. Pereira et. al conclude that their results from single neurons indicate that task-related activity occurs, purportedly separate from previously identified sensory signals. These conclusions are a promising and novel perspective for how the field thinks about the emergence of decisions and sensory perception across the entire brain as a unit.

Despite the strength of the data that was obtained and the relevant nature of the conclusions that were drawn, there are certain limitations that must be taken into consideration:

(1) The authors make several claims that their findings are direct representations of consciousness identifiable in subcortical structures. The current context for consciousness does not sufficiently define how the consciousness is related to the perceptual task.

(2) The current work would benefit greatly from a description and clarification of what all the neurons that have been recorded are doing. The authors' criteria for selecting subpopulations with task-relevant activity are appropriate, but understanding the heterogeneity in a population of single neurons is important for broader considerations that are being studied within the field.

(3) The authors have omitted a proper set of controls for comparison against the active trials, for example, where a response was not necessary. Please explain why this choice was made and what implications are necessary to consider.

Reviewer #2 (Public Review):

Summary:

Here the authors describe a model for tracking time-varying coupling between neurons from multi-electrode spike recordings. Their approach extends a GLM with static coupling between neurons to include dynamic weights, learned by a long-short-term-memory (LSTM) model. Each connection has a corresponding LSTM embedding and is read out by a multi-layer perceptron to predict the time-varying weight.

Strengths:

This is an interesting approach to an open problem in neural data analysis. I think, in general, the method would be interesting to computational neuroscientists.

Weaknesses:

It is somewhat difficult to interpret what the model is doing. I think it would be worthwhile to add some additional results that make it more clear what types of patterns are being described and how.

Major Issues:

Simulation for dynamic connectivity. It certainly seems doable to simulate a recurrent spiking network whose weights change over time, and I think this would be a worthwhile validation for this DyNetCP model. In particular, I think it would be valuable to understand how much the model overfits, and how accurately it can track known changes in coupling strength. If the only goal is "smoothing" time-varying CCGs, there are much easier statistical methods to do this (c.f. McKenzie et al. Neuron, 2021. Ren, Wei, Ghanbari, Stevenson. J Neurosci, 2022), and simulations could be useful to illustrate what the model adds beyond smoothing.

Stimulus vs noise correlations. For studying correlations between neurons in sensory systems that are strongly driven by stimuli, it's common to use shuffling over trials to distinguish between stimulus correlations and "noise" correlations or putative synaptic connections. This would be a valuable comparison for Figure 5 to show if these are dynamic stimulus correlations or noise correlations. I would also suggest just plotting the CCGs calculated with a moving window to better illustrate how (and if) the dynamic weights differ from the data.

Reviewer #2 (Public Review):

In this paper, Boi et al. thoroughly classified the electrophysiological and morphological characteristics of serotonergic and dopaminergic neurons in the DRN and examined the alterations of these neurons in the 6-OHDA-induced mouse PD model. Using whole-cell patch clamp recording, they found that 5-HT and dopamine (DA) neurons in the DRN are electrophysiologically well-distinguished from each other. In addition, they characterized distinct morphological features of 5-HT and DA neurons in the DRN. Notably, these specific features of 5-HT and DA neurons in the DRN exhibited different changes in the 6-OHDA-induced PD model. Then the authors utilized desipramine (DMI) to separate the effects of nigrostriatal DA depletion and noradrenalin (NA) depletion which are induced by 6-OHDA. Interestingly, protection from NA depletion by DMI pretreatment reversed the changes in 5-HT neurons, while having a minor impact on the changes in DA neurons in the DRN. These data indicate that the role of NA lesion in the altered properties of DRN 5-HT neurons by 6-OHDA is more critical than the one of DA lesion.

Overall, this study provides foundational data on the 5-HT and DA neurons in the DRN and their potential involvement in PD symptoms. Given the defects of the DRN in PD, this paper may offer insights into the cellular mechanisms that may underlie non-motor symptoms associated with PD. Despite the importance of the primary claim proposed by the authors, however, the interpretation of the authors on some DMI experiments is not explained well.

Reviewer #2 (Public Review):

The authors examine the impact of optogenetic inhibition of hippocampal axon terminals in the retrosplenial cortex (RSP) during the performance of a working memory T-maze task. Performance on a delayed non-match-to-place task was impaired by such inhibition. The authors also report that inhibition is associated with faster decision-making and that the effects of inhibition can be observed over several subsequent trials. The work seems reasonably well done and the role of hippocampal projections to retrosplenial cortex in memory and decision-making is very relevant to multiple fields. However, the work should be expanded in several ways before one can make firm conclusions on the role of this projection in memory and behavior.

(1) The work is very singular in its message and the experimentation. Further, the impact of the inhibition on behavior is very moderate. In this sense, the results do not support the conclusion that the hippocampal projection to retrosplenial cortex is key to working memory in a navigational setting.

(2) There are no experiments examining other types of behavior or working memory. Given that the animals used in the studies could be put through a large number of different tasks, this is surprising. There is no control navigational task. There is no working memory test that is non-spatial. Such results should be presented in order to put the main finding in context.

(3) The actual impact of the inhibition on activity in RSP is not provided. While this may not be strictly necessary, it is relevant that the hippocampal projection to RSP includes, and is perhaps dominated by inhibitory inputs. I wonder why the authors chose to manipulate hippocampal inputs to RSP when the subiculum stands as a much stronger source of afferents to RSP and has been shown to exhibit spatial and directional tuning of activity. The points here are that we cannot be sure what the manipulation is really accomplishing in terms of inhibiting RSP activity (perhaps this explains the moderate impact on behavior) and that the effect of inhibiting hippocampal inputs is not an effective means by which to study how RSP is responsive to inputs that reflect environmental locations.

(4) The impact of inhibition on trials subsequent to the trial during which optical stimulation was actually supplied seems trivial. The authors themselves point to evidence that activation of the hyperpolarizing proton pump is rather long-lasting in its action. Further, each sample-test trial pairing is independent of the prior or subsequent trials. This finding is presented as a major finding of the work, but would normally be relegated to supplemental data as an expected outcome given the dynamics of the pump when activated.

(5) In the middle of the first paragraph of the discussion, the authors make reference to work showing RSP responses to "contextual information in egocentric and allocentric reference frames". The citations here are clearly deficient. How is the Nitzan 2020 paper at all relevant here?

(6) The manuscript is deficient in referencing and discussing data from the Smith laboratory that is similar. The discussion reads mainly like a repeat of the results section.

Reviewer #3 (Public Review):

The manuscript by Yang et al. investigated in mice how hypobaric hypoxia can modify the RBC clearance function of the spleen, a concept that is of interest. Via interpretation of their data, the authors proposed a model that hypoxia causes an increase in cellular iron levels, possibly in RPMs, leading to ferroptosis, and downregulates their erythrophagocytic capacity.

Comments on revised version:

The manuscript has now improved with all the new data, supporting the model proposed by the authors. However, it remains not very easy to follow for the conclusions and experimental details. Some of the most important remaining comments are listed below:

(1) Lines 401-406 - The conclusions in this new fragment sound a bit overstated - the authors do not directly measure erytrophagocytosis capacity, only the total RBC parameters in the circulation. The increase is also very mild biologically between sham and splenectomized mice in HH conditions.

(2) scRNA seq data are still presented in a way that is very difficult to understand. The readers could not see from the graphics that macrophages are depleted. The clusters are not labelled - some clusters in the bin 'macrophahes+DC' seem actually to be more represented in Fig. 3E; Fig. 3F does not correspond to Fig. 3D. It would be maybe more informative to present like in Figure D side by side NN versus HH? The authors could consider moving the data from supplements that relate to RPMs to the main figure and making it consistent for the Clusters - eg, the authors show data for Cluster 0 in the supplement, and the same Cluster is not marked as macrophages in the main figure. This is quite difficult to follow.

(3) Figure 3G has likely mislabeled axis for F4/80 and CD11b - such mistakes should be avoided in a second revised version of the manuscript, and this data is now redundant with the data shown as new Figure 5A.

(4) The data from new Figure 4 should be better mentioned in the main body of the manuscript - all panels are mentioned twice in the text, first speaking about the decline of labelled RBCs and second referring to phagocytic capacity, whereas this figure only illustrates the decline of labelled RBCs, not directly phagocytic capacity of RPMs. What is lacking, as opposed to typical RBC life span assay, is the time '0' ('starting point') - this is particularly important as we can observe a big drop in labelled RBCs for eg 7 days between NN and HH group, actually implying increased removal of labelled RBCs within the first days of hypoxia exposure. What should be better labelled in this figure is that the proportion of RBCs are labelled RBCs not all RBCs (Y axis in individual panels). Overall, the new Figure 4 brings new data to the study, but how it is presented and discussed is not at the 'state-of-the-art' level (eg, missing the time '0') and is not very straightforward to the reader.

(5) In Figure 7, the experiments with Tuftsin are not very easy to follow, especially for the major conclusions. In panels A and B, the focus is the drug itself under NN conditions, with RBC removal as a readout. Then, in the next panels, the authors introduce HH, and then look at the F4/80 and iron staining. What was exactly the major point the authors wanted to make here?

(6) The data from Figure 8 are informative but do not address the individual cell types - eg, a drop in HO1 or FT may be due to the depletion of RPMs. An increase of TFR1 could be due to the retention of RBCs, the same as maybe labile iron. The data from PBMC are only very loosely linked to these phenotypes observed in the total spleen, and the reason for the regulation of the same proteins in PBMC might be different. It goes back to the data in Figure 3A-C, where also total splenocytes are investigated for their viability.

(7) Can the authors provide the data for the purity (eg cell surface markers) of their primary splenic macrophage cultures? Only ensuring that these are macrophages or addressing the readouts from Figure 8 in RPMs could link ferroptosis to RPMs under HH conditions.

(8) All the data are not presented as individual data points which is not widely applied in papers.

(9) No gating strategies are nicely illustrated or described.

Reviewer #3 (Public Review):

Previously, it has been shown the essential role of IDA peptide and HAESA receptor families in driving various cell separation processes such as abscission of flowers as a natural developmental process, of leaves as a defense mechanism when plants are under pathogenic attack or at the lateral root emergence and root tip cell sloughing. In this work, Olsson et al. show for the first time the possible role of IDA peptide in triggering plant innate immunity after the cell separation process occurred. Such an event has been previously proposed to take place in order to seal open remaining tissue after cell separation to avoid creating an entry point for opportunistic pathogens. The elegant experiments in this work demonstrate that IDA peptide is triggering the defense-associated marker genes together with immune specific responses including release of ROS and intracellular CA2+. Thus, the work highlights an intriguing direct link between endogenous cell wall remodeling and plant immunity. Moreover, the upregulation of IDA in response to abiotic and especially biotic stimuli are providing a valuable indication for potential involvement of HAE/IDA signalling in other processes than plant development.

Comments on revised version:

We thank the authors for addressing our previous comments. Overall, we are satisfied with the improvements and appreciate the hard work that has gone into this manuscript. We wish you all the best on the further publication pathway.

Reviewer #2 (Public Review):

This manuscript explores the interplay between Legionella Dot/Icm effectors that modulate ubiquitination of the host GTPase Rab10. Rab10 undergoes phosphoribosyl-ubiquitination (PR-Ub) by the SidE family of effectors which is required for its recruitment to the Legionella containing vacuole (LCV). Through a series of elegant experiments using effector gene knockouts, co-transfection studies and careful biochemistry, Kubori et al further demonstrate that:

(1) The SidC family member SdcB contributes to the polyubiquitination (poly-Ub) of Rab10 and its retention at the LCV membrane.

(2) The transglutaminase effector, MavC acts as an inhibitor of SdcB by crosslinking ubiquitin at Gln41 to lysine residues in SdcB.

Reviewer #2 (Public Review):

Summary:

This study focuses on the 5-HT3 serotonin receptor, a pentameric ligand-gated ion channel important in chemical neurotransmission. There are many cryo-EM structures of this receptor with diverse ligands bound, however assignment of functional states to the structures remains incomplete. The team applies voltage-clamp fluorometry to measure, at once, both changes in ion channel activity, and changes in fluorescence. Four cysteine mutants were selected for fluorophore labeling, two near the neurotransmitter site, one in the ECD vestibule, and one at the ECD-TMD junction. Agonists, partial agonists, and antagonists were all found to yield similar changes in fluorescence, a proxy for conformational change, near the neurotransmitter site. The strength of the agonist correlated to a degree with propagation of this fluorescence change beyond the local site of neurotransmitter binding. Antagonists failed to elicit a change in fluorescence in the vestibular of the ECD-TMD junction sites. The VCF results further turned up evidence supporting intermediate (likely pre-active) states.

Strengths:

The experiments appear rigorous, the problem the team tackles is timely and important, the writing and the figures are for the most part very clear. We sorely need approaches orthogonal to structural biology to annotate conformational states and observe conformational transitions in real membranes- this approach, and this study, get right to the heart of what is missing.

Weaknesses:

The weaknesses in the study itself are overall minor, I only suggest improvements geared toward clarity. What we are still missing is application of an approach like this to annotate the conformation of the part of the receptor buried in the membrane; there is an important debate about which structure represents which state, and that is not addressed in the current study.

Reviewer #2 (Public Review):

Summary:

In this manuscript, the authors describe a mechanism, by which fluorescently-labelled Collagen type I is taken up by cells via endocytosis and then incorporated into newly synthesized fibers via an ITGA11 and VPS33B-dependent mechanism. The authors claim the existence of this collagen recycling mechanism and link it to fibrotic diseases such as IPF and chronic wounds.

Strengths:

The manuscript is well-written, and experimentally contains a broad variation of assays to support their conclusions. Also, the authors added data of IPF patient-derived fibroblasts, patient-derived lung samples, and patient-derived samples of chronic wounds that highlight a potential in vivo disease correlation of their findings.

The authors were also analyzing the membrane topology of VPS33B and could unravel a likely 'hairpin' like conformation in the ER membrane.

Weaknesses:

Experimental evidence is missing that supports the non-degradative endocytosis of the labeled collagen.

The authors show and mention in the text that the endocytosis inhibitor Dyngo®4a shows an effect on collagen secretion. It is not clear to me how specific this readout is if the inhibitor affects more than endocytosis. This issue was unfortunately not further discussed. The authors use commercial rat tail collagen, it is unclear to me which state the collagen is in when it's endocytosed. Is it fully assembled as collagen fiber or are those single heterotrimers or homotrimers?

The Cy-labeled collagen is clearly incorporated into new fibers, but I'm not sure whether the collagen is needed to be endocytosed to be incorporated into the fibers or if that is happening in the extracellular space mediated by the cells.

In general for the collagen blots, due to the lack of molecular weight markers, what chain/form of collagen type I are you showing here?

Besides the VPS33B siRNA transfected cells the authors also use CRISPR/Cas9-generated KO. The KO cells do not seem to be a clean system, as there is still a lot of mRNA produced. Were the clones sequenced to verify the KO on a genomic level? For the siRNA transfection, a control blot for efficiency would be great to estimate the effect size. To me it is not clear where the endocytosed collagen and VPS33B eventually meet in the cells and whether they interact. Or is ITGA11 required to mediate this process, in case VPS33B is not reaching the lumen?

The authors show an upregulation of ITGA11 and VPS33B in IPF patients-derived fibroblasts, which can be correlated to an increased level of ColI uptake, however, it is not clear whether this increased uptake in those cells is due to the elevated levels of VPS33B and/or ITGA11.

Reviewer #2 (Public Review):

Summary:

This manuscript uses FRET, 19F-NMR, and DEER/EPR solution measurements to examine the allosteric effects of a panel of BRAF inhibitors (BRAFi). These include first-generation aC-out BRAFi, and more recent Type I and Type II aC-in inhibitors. Intermolecular FRET measurements quantify Kd for BRAF dimerization and inhibitor binding to the first and second subunits. Distinct patterns are found between aC-in BRAFi, where Type I BRAFi binds equally well to the first and second subunits within dimeric BRAF. In contrast, Type II BRAFi shows stronger affinity for the first subunit and weaker affinity for the second subunit, an effect named "allosteric asymmetry". Allosteric asymmetry has the potential for Type II inhibitors to promote dimerization while favoring occupancy of only one subunit (BBD form), leading to the enrichment of an active dimer.

Measurements of in vitro BRAF kinase activity correlate amazingly well with the calculated amounts of the half-site-inhibited BBD forms with Type II inhibitors. This suggests that the allosteric asymmetry mechanism explains paradoxical activation by this class of inhibitors. DEER/EPR measurements further examine the positioning of helix aC. They show systematic outward movement of aC with Type II inhibitors, relative to the aC-in state with Type I inhibitors, and further show that helix aC adopts multiple states and is therefore dynamic in apo BRAF. This makes a strong case that negative cooperativity between sites in the BRAF dimer can account for paradoxical kinase activation by Type II inhibitors by creating a half-site-occupied homodimer, BBD. In contrast, Type I inhibitors and aC-out inhibitors do not fit this model, and are therefore proposed to be explained by previously proposed models involving negative allostery between subunits in BRAF-CRAF heterodimers, RAS priming, and transactivation.

Strengths:

This study integrates orthogonal spectroscopic and kinetic strategies to characterize BRAF dynamics and determine how it impacts inhibitor allostery. The unique combination of approaches presented in this study represents a road map for future work in the important area of protein kinase dynamics. The work represents a worthy contribution not only to the field of BRAF regulation but to protein kinases in general.

Weaknesses:

Some questions remain regarding the proposed model for Type II inhibitors and its comparison to Type I and aC-out inhibitors that would be useful to clarify. Specifically, it would be helpful to address whether the activation of BRAF by Type II inhibitors, while strongly correlated with BBD model predictions in vitro, also depends on CRAF via BRAF-CRAF in cells and therefore overlaps with the mechanisms of paradoxical activation by Type I and aC-out inhibitors.

Reviewer #2 (Public Review):

Summary:

A dominant hypothesis concerning the origin of life is that, before the appearance of the first enzymes, RNA replicated non-enzymatically by templating. However, this replication was probably not very efficient, due to the propensity of single strands to bind to each other, thus inhibiting template replication. This phenomenon, known as product inhibition, has been shown to lead to parabolic growth instead of exponential growth. Previous works have shown that this situation limits competition between alternative replicators and therefore promotes RNA population diversity. The present work examines this scenario in an agent-based model of RNA replication, taking into account finite population size, mutations and differences in GC content. The main results are (1) confirmation that parabolic growth promotes diversity, but that when the population size is small enough, sequences least efficient at replicating may nevertheless go extinct; (2) the observation that fitness is not only controlled by the replicability of sequences, but also by their GC content ; (3) the observation that parabolic growth attenuates the impact of mutations and, in particular, that the error threshold to which exponentially growing sequences are subject can be exceeded, enabling sequence identity to be maintained at higher mutation rates.

Strengths:

The analyses are sound and the observations intriguing. Indeed, while it has been noted previously that parabolic growth promotes coexistence, this is the first work to show that it can also mitigate the error threshold catastrophe, which is often presented as a major obstacle to our understanding of the origin of life.

Weaknesses:

A general weakness, which can however be seen as inherent in an agent-based model that aims to be more realistic than earlier, more phenomenological models, is the proliferation of parameters. The choice and values of these parameters are generally justified and, in many cases, several values are tested to assess the robustness of the results, but it can be difficult for the reader to identify the modeling choices that are truly critical from those that are less so.

Reviewer #2 (Public Review):

Maurer et al investigated the contribution of GAD2+ neurons in the preoptic area (POA), projecting to the tuberomammillary nucleus (TMN), to REM sleep regulation. They applied an elegant design to monitor and manipulate activity of this specific group of neurons: a GAD2-Cre mouse, injected with retrograde AAV constructs in the TMN, thereby presumably only targeting GAD2+ cells projecting to the TMN. Using this set-up in combination with technically challenging techniques including EEG with photometry and REM sleep deprivation, the authors found that this cell-type studied becomes active shortly (≈40sec) prior to entering REM sleep and remains active during REM sleep. Moreover, optogenetic inhibition of GAD2+ cells inhibits REM sleep by a third, and also impairs the rebound in REM sleep in the following hour. Thus, the data makes a convincing case for a role of GAD2+ neurons in the POA projecting to the TMN in REM sleep regulation.

Reviewer #3 (Public Review):

Summary:

The work by Masala and colleagues highlights a striking artifact that can result from a particular viral method for expressing genetically encoded calcium indicators (GECIs) in neurons. In a cross-institutional collaboration, the authors find that viral transduction of GECIs in the hippocampus can result in aberrant slow-traveling calcium (Ca2+) micro-waves. These Ca2+ micro-waves are distinct from previously described ictal activity but nevertheless are likely a pathological consequence of overexpression of virally transduced proteins. Ca2+ micro-waves will most-likely obscure the physiology that most researchers are interested in studying with GECIs, and their presence indicates that the neural circuit is in an unintended pathological state. Interestingly this pathology was not observed using the same viral transduction methods in other brain regions. The authors recommend several approaches that may help other experimenters avoid this confound in their own data such as reducing the titer of viral injections or using recombinase-dependent expression. The intent of this manuscript is to raise awareness of the potential unintended consequences of viral overexpression, particularly for GECIs. A rigorous investigation into the exact causes of Ca2+ micro-waves or the mechanisms supporting them are beyond the authors' intended scope.

Strengths:

The authors clearly demonstrate that Ca2+ micro-waves occur in the CA1 and CA3 regions of the hippocampus following large volume, high titer injections of adeno-associated viruses (AAV1 and AAV9) encoding GECIs. The supplementary videos provide undeniable proof of their existence.

By forming an inter-institutional collaboration, the authors demonstrate that this phenomenon is robust to changes in surgical techniques or imaging conditions.

Weaknesses:

I believe that the weaknesses of the manuscript are appropriately highlighted by the authors themselves in the discussion. The manuscript does not attempt to exhaustively characterize the conditions under which calcium micro-waves occur. Rather, the authors raise awareness of this problem.

Reviewer #2 (Public Review):

Summary:

Roy et al. investigated the role of non-canonical DNA structures called G-quadruplexes (G4s) in long-range chromatin interactions and gene regulation. Introducing a G4 array into chromatin significantly increased the number of long-range interactions, both within the same chromosome (cis) and between different chromosomes (trans). G4s functioned as enhancer elements, recruiting p300 and boosting gene expression even 5 megabases away. The study proposes a mechanism where G4s directly influence 3D chromatin organization, facilitating communication between regulatory elements and genes.

Strength:

The findings are valuable for understanding the role of G4-DNA in 3D genome organization and gene transcription.

Weaknesses:

The study would benefit from more robust and comprehensive data, which would add depth and clarity.

(1) Lack of G4 Structure Confirmation: The absence of direct evidence for G4 formation within cells undermines the study's foundation. Relying solely on in vitro data and successful gene insertion is insufficient.

(2) Alternative Explanations: The study does not sufficiently address alternative explanations for the observed results. The inserted sequences may not form G4s or other factors like G4-RNA hybrids may be involved.

(3) Limited Data Depth and Clarity: ChIP-qPCR offers limited scope and considerable variation in some data makes conclusions difficult.

(4) Statistical Significance and Interpretation: The study could be more careful in evaluating the statistical significance and magnitude of the effects to avoid overinterpreting the results.

Reviewer #3 (Public Review):

Summary:

The manuscript uses a combination of evolutionary approaches and structural/dynamics observations to provide mechanistic insights in the adaptation of the Spike protein during the evolution of SARS-COV-2 variants. The conclusion that CAP sites should be taken in particular account when considering the impact of the emergence of new strains and mutations is warranted.

Strengths:

The results presented in this work are very well outlined with well-written text, pleasant and well-described pictures, didactical and clear description of the methods, e.g. the discussion of how the MD equilibration procedure is applied and evaluated is clear and well argument.<br /> The citation of relevant similar results with different approaches strengthens the reasoning; in particular, comparing the calculated scores with previous experimentally obtained data is one of the strongest points of the manuscript.

Weaknesses:

There are no replicas of the molecular dynamics (MD) simulations, understandable since it's not a MD-focused paper. However, the comparison of multiple replicas could enhance the reliability of the findings.

Reviewer #2 (Public Review):

Summary:

This paper by Olah et al. uncovers a previously unknown role of HCN channels in shaping synaptic inputs to L2/3 cortical neurons. The authors demonstrate using slice electrophysiology and computational modeling that, unlike layer 5 pyramidal neurons, L2/3 neurons have an enrichment of HCN channels in the proximal dendrites. This location provides a locus of neuromodulation for inputs onto the proximal dendrites from L4 without an influence on distal inputs from L1. The authors use pharmacology to demonstrate the effect of HCN channels on NMDA-mediated synaptic inputs from L4. The authors further demonstrate the developmental time course of HCN function in L2/3 pyramidal neurons. Taken together, this a well-constructed investigation of HCN channel function and the consequences of these channels on synaptic integration in L2/3 pyramidal neurons.

Strengths:

The authors use careful, well-constrained experiments using multiple pharmacological agents to asses HCN channel contributions to synaptic integrations. The authors also use a voltage clamp to directly measure the current through HCN channels across developmental ages. The authors also provide supplemental data showing that their observation is consistent across multiple areas of the cerebral cortex.

Weaknesses:

The gradient of the HCN channel function is based almost exclusively on changes in EPSP width measured at the soma. While providing strong evidence for the presence of HCN current in L2/3 neurons, there are space clamp issues related to the use of somatic whole-cell voltage clamps that should be considered in the discussion.

Reviewer #2 (Public Review):

The present study aims to investigate brain white matter predictors of back pain chronicity. To this end, a discovery cohort of 28 patients with subacute back pain (SBP) was studied using white matter diffusion imaging. The cohort was investigated at baseline and one-year follow-up when 16 patients had recovered (SBPr) and 12 had persistent back pain (SBPp). A comparison of baseline scans revealed that SBPr patients had higher fractional anisotropy values in the right superior longitudinal fasciculus SLF) than SBPp patients and that FA values predicted changes in pain severity. Moreover, the FA values of SBPr patients were larger than those of healthy participants, suggesting a role of FA of the SLF in resilience to chronic pain. These findings were replicated in two other independent datasets. The authors conclude that the right SLF might be a robust predictive biomarker of CBP development with the potential for clinical translation.

Developing predictive biomarkers for pain chronicity is an interesting, timely, and potentially clinically relevant topic. The paradigm and the analysis are sound, the results are convincing, and the interpretation is adequate. A particular strength of the study is the discovery-replication approach with replications of the findings in two independent datasets.

The following revisions might help to improve the manuscript further.

- Definition of recovery. In the New Haven and Chicago datasets, SBPr and SBPp patients are distinguished by reductions of >30% in pain intensity. In contrast, in the Mannheim dataset, both groups are distinguished by reductions of >20%. This should be harmonized. Moreover, as there is no established definition of recovery (reference 79 does not provide a clear criterion), it would be interesting to know whether the results hold for different definitions of recovery. Control analyses for different thresholds could strengthen the robustness of the findings.

- Analysis of the Chicago dataset. The manuscript includes results on FA values and their association with pain severity for the New Haven and Mannheim datasets but not for the Chicago dataset. It would be straightforward to show figures like Figures 1 - 4 for the Chicago dataset, as well.

- Data sharing. The discovery-replication approach of the present study distinguishes the present from previous approaches. This approach enhances the belief in the robustness of the findings. This belief would be further enhanced by making the data openly available. It would be extremely valuable for the community if other researchers could reproduce and replicate the findings without restrictions. It is not clear why the fact that the studies are ongoing prevents the unrestricted sharing of the data used in the present study.

Reviewer #2 (Public Review):

Summary:

Galanti et al investigate genetic variation in plant pest resistance using non-target reads from whole-genome sequencing of 207 field lines spontaneously colonized by aphids and mildew. They calculate significant differences in pest DNA load between populations and lines, with heritability and correlation with climate and glucosinolate content. By genome-wide association analyses they identify known defence genes and novel regions potentially associated with pest load variation. Additionally, they suggest that differential methylation at transposons and some genes are involved in responses to pathogen pressure. The authors present in this study the potential of leveraging non-target sequencing reads to estimate plant biotic interactions, in general for GWAS, and provide insights into the defence mechanisms of Thlaspi arvense.

Strengths:

The authors ask an interesting and important question. Overall, I found the manuscript very well-written, with a very concrete and clear question, a well-structured experimental design, and clear differences from previous work. Their important results could potentially have implications and utility for many systems in phenotype-genotype prediction. In particular, I think the use of unmapped reads for GWAS is intriguing.

Weaknesses:

I found that several of the conclusions are incomplete, not well supposed by the data and/or some methods/results require additional details to be able to be judged. I believe these analyses and/or additional clarifications should be considered.

Reviewer #2 (Public Review):

Summary:

To investigate the evolutionary relationship between the RNAi pathway and innate immunity, this study uses biochemistry and structural biology to investigate the trimeric complex of Dicer-1, DRH-1 (a RIGI homologue) and RDE-4 , which exists in C. elegans. The three subunits were co-expressed to promote stable purification of the complex. This complex promoted ATP-dependent cleavage of blunt-ended dsRNAs. A detailed kinetic analysis was also carried out to determine the role of each subunit of the trimeric complex in both the specificity and efficiency of cleavage. These studies indicate that RDE-4 is critical for cleavage while DRC-1 is primarily involved in the specificity of the reaction, and DRH-1 promotes ATP hydrolysis. Finally, a moderate density (6-7 angstrom) cryo-EM structure of the trimeric complex is provided.

Strengths:

(1) Newly described methods for studying the C. elegans DICER complex<br /> (2) New structure, albeit only moderate resolution<br /> (3) Kinetic study of the complex in the presence and absence of individual subunits and mutations, provide detailed insight into the contribution of each subunit

Weaknesses:

(1) Limited insight due to limited structural resolution.

Reviewer #2 (Public Review):

Summary:

The authors noticed that there was an enhanced ability to detect nuclear pore proteins in trypanosomes using a streptavidin-biotin-based detection approach in comparison to conventional antibody-based detection, and this seemed particularly acute for phase-separated proteins. They explored this in detail for both standard imaging but also expansion microscopy and CLEM, testing resolution, signal strength, and sensitivity. An additional innovative approach exploits the proximity element of biotin labelling to identify where interacting proteins have been as well as where they are.

Strengths:

The data is high quality and convincing and will have obvious application, not just in the trypanosome field but also more broadly where proteins are tricky to detect or inaccessible due to phase separation (or some other steric limitations). It will be of wide utility and value in many cell biological studies and is timely due to the focus of interest on phase separation, CLEM, and expansion microscopy.

Reviewer #2 (Public Review):

Wang, Liu, et al. identified Rnf220 and Wdr5 as novel regulators of Hox gene expression during pons development. Phenotypic characterization of Rnf220 deficient mice with single-cell transcriptomics, qRT-PCR, and axonal tracing methods show that Rnf220 knockdown causes de-repression of Hox gene expression at multiple stages of pons development to regulate the final formation of the pontine nuclei neural circuit. Additionally, they also perform exhaustive expression analysis of multiple genes in the Hox family cluster to identify specific gene groups that are targeted by Rnf220. Furthermore, they also demonstrate that Rnf220 modulates Hox gene expression by directly binding to Wdr5, thus targeting it for ubiquitination and subsequent degradation. To elucidate the molecular mechanism of this interaction, they perform detailed immunoprecipitation assays and identify the precise Wdr5 amino acid residues that are targeted by Rnf220. Intriguingly, they show that inhibition of Wdr5 in Rnf220 deficient mice reverses the de-repression of Hox gene expression suggesting the direct involvement of Rnf220-Wdr5 interaction in modulating Hox gene expression during pons development. These data highlight the role of a new form of Hox gene regulation via the ubiquitination of epigenetic modulator Wdr5.

The conclusions of this paper are mostly supported by the data provided, but the downstream molecular and tissue-level effects of Wdr5 knockdown/inhibition need to be further characterized to establish its definitive role in pons development.

(1) Figure 1E shows that Rnf220 knockdown alone could not induce an increase in Hox expression without RA, which indicates that Rnf220 might endogenously upregulate Retinoic acid signaling. The authors should test if RA signaling is downstream of Rnf220 by looking at differences in the expression of Retinaldehyde dehydrogenase genes (as a proxy for RA synthesis) upon Rnf220 knockdown.

(2) In Figure 2C-D further explanation is required to describe what criteria were used to segment the tissue into Rostral, middle, and caudal regions. Additionally, it is unclear whether the observed change in axonal projection pattern is caused due to physical deformation and rearrangement of the entire Pons tissue or due to disruption of Hox3-5 expression levels. Labeling of the tissue with DAPI or brightfield image to show the structural differences and similarities between the brain regions of WT and Rnf220 +/- will be helpful.

(3) Line 192-195. These roles of PcG and trxG complexes are inconsistent with their initial descriptions in the text - lines 73-74.

(4) In Figure 4D, the band in the gel seems unclear and erased. Please provide a different one. These data show that neither Rnf220 nor wdr5 directly regulates Hox gene expressions. The effect of double knockdown in the presence of RA suggests that they work together to suppress Hox gene expression via a different downstream target. This point should be addressed in the text and discussion section of the paper. example for the same data which shows a full band with lower intensity.

(5) In Figure 4G the authors could provide some form of quantitation for changes in ubiquitination levels to make it easier for the reader. They should also describe the experimental procedures and conditions used for each of the pull-down and ubiquitination assays in greater detail in the methods section.

(6) Figure 5 shows that neither Rnf220 nor wdr5 directly regulate Hox gene expressions. The effect of double knockdown in the presence of RA suggests that they work together to suppress Hox gene expression via a different downstream target. This point should be addressed in the text and discussion section of the paper.

(7) In Figure 6, while the reversal of changes in Hox gene expression upon concurrent Rnf220; Wdr5 inhibition highlights the importance of Wdr5 in this regulatory process, the mechanistic role of wdr5 and its functional consequences are unclear. To answer these questions, the authors need to: (i) Assay for activated and repressive epigenetic modifications upon double knockdown of Rnf220 and Wdr5 similar to that shown in Figure 4- supplement 1. This will reveal if wdr5 functions according to its intended role as part of the TrxG complex. (ii) The authors need to assay for changes in axon projection patterns in the double knockdown condition to see if Wdr5 inhibition rescues the neural circuit defects in Rnf220 +/- mice.

Reviewer #2 (Public Review):

Summary:

Bolamperti S. et al. 2023 investigates whether expression of TG-interacting factor (Tgif1) is essential for osteoblastic cellular activity regarding morphology, adherence, migration/recruitment, and repair. Towards this end, germ-line Tgif1 deletion (Tgif1-/-) mice or male mice lacking expression of Tgif1 in mature osteoblastic and osteocytic cells (Dmp1-Cre+; Tgif1fl/fl) and corresponding controls were studied in physiological, bone anabolic, and bone fracture-repair conditions. Both Tgif1-/- and Dmp1-Cre+; Tgif1fl/fl exhibited decreased osteoblasts on cancellous bone surfaces and adherent to collagen I-coated plates. Tgif1-/- mice exhibit impaired healing in the tibial midshaft fracture model, as indicated by decreased bone volume (BV/Cal.V), osteoid (OS/BS), and low osteoblasts (number and surface). Likewise, both Tgif1-/- and Dmp1-Cre+; Tgif1fl/fl show impaired PTH 1-34, (100 µg/kg, 5x/wk for 3 wks) osteoblast activation in vivo, as detected by increases in quiescent bone surfaces. Mechanistic in vitro studies then utilized primary osteoblasts isolated from Tgif1-/- mice and siRNA Tgif1 knockdown OCY454 cells to further investigate and identify the downstream Tgif1 target driving these osteoblastic impairments. In vitro, Tgif1-/- osteoblastic and Tgif1 knockdown OCY454 cells exhibit decreased migration, abnormal morphology, and decreased focal adhesions/cell. Unexpectantly though, localization assays revealed Tgif1 to primarily concentrate in the nucleus and not to co-localize with focal adhesions (paxillin, talin). Also, expression of major focal adhesion components (paxillin, talin, FAK, Src etc.) or the Cdc42 family was not altered by loss of Tgif1 expression. In contrast, PAK3 expression is markedly upregulated by loss of Tgif1. In silico analysis followed by mechanistic molecular assays involving ChIP, siRNA (Tgif1, PAK3), and transfection (rat PAK3 promoter) techniques show that Tgif1 physically binds to a specific site in the PAK3 promoter region. Further, the knockdown of PAK3 rescues the Tgif1-deficient abnormal morphology in OCY454 cells. This is the first study to identify the novel transcriptional repression of PAK3 by Tgif1 as well as the specific Tgif1 binding site within the PAK3 promoter.

Strengths:

This work has a plethora of strengths. The co-authors achieved their aim in eliciting the role of Tgif1 expression to osteoblastic cellular functions (morphology, spreading/attachment, migration). Further, this work is the first to depict the novel mechanism of Tgif1 transcriptional repression of PAK3 by a through usage of mechanistic molecular assays (In silico analysis, ChIP, siRNA, transfection etc.). The conclusions are well supported and justified by these findings, as the appropriate controls, sample sizes (statistical power), statistics, and assays were fully utilized.

Claims and conclusions justified by data? Yes. absolutely

Weaknesses:

None. All reviewer comments were fully addressed.

Reviewer #3 (Public Review):

Summary:

Nakai-Futatsugi et al. present a novel method to analyze the correlation between the degree of pigmentation and the gene expression profile of human-induced pluripotent stem cell-derived RPE (iPSC-RPE) cells at the single cell level. This was achieved with the use of ALPS (Automated Live imaging and cell Picking system), an invention developed by the same authors. Briefly, it allows one to choose and photograph a specific cell from a culture dish and proceed to single cell digital RNA-seq. The authors identify clusters of cells that present differential gene expression, but this showed no association with the degree of pigmentation of the cells. Further data analysis allowed the authors to correlate the degree of pigmentation to some degree with the expression of complement and lysosome-related genes.

Strengths:

An important amount of data related to gene expression and heterogeneity of the iPSC-RPE population has been generated in this work.

Weaknesses:

However, the justification of the analysis, and the physiological relevance of the hypothesis and the findings could be strengthened.

Importantly, I fail to grasp from the introduction what is the previous evidence that leads to the hypothesis. Why would color intensity be related to the quality of cell transplantation? In fact, cell transplantation is not evaluated at all in this work. The authors mention "quality metrics for clinical use", but this concept is not further explained. Neither is the concept of "sufficient degree of pigmentation" explained.<br /> On the other hand, the positive correlation of cluster formation with complement and lysosome-related genes is not discussed.

As a consequence it is very difficult to evaluate the impact of these findings on the field.

Reviewer #2 (Public Review):

Summary:

The authors conducted research on the role of SerpinE2 and HtrA1 in neural crest migration using Xenopus embryos. The data presented in this study was of high quality and supported the authors' conclusions. The discovery of the potential molecular connection between SerpinE2 and HtrA1 in neural crest cell migration in vivo is significant, as understanding this pathway could potentially lead to treatments for aggressive cancers and pregnancy-related disorders.

Strengths:

Previous research has shown that SerpinE2 and HtrA1 can have both positive and negative effects on cell migration, but their molecular interplay and role in neural crest migration are not well-established. This study is the first to reveal a potential connection between these two proteins in neural crest cell migration in vivo. The authors found that SerpinE2 promotes neural crest migration by inhibiting HtrA1. Additionally, overexpression of Sdc4 partly alleviates neural crest migration issues caused by SerpinE2 knockdown or HtrA1 overexpression. These findings suggest that the SeprinE2-HtrA1-Sdc4 pathway is crucial for neural crest migration.

Weaknesses:

To further increase the study's credibility, it may be helpful to use techniques like western blotting, qRT-PCR, or in situ hybridization to verify the efficiency of SerpinE2 and HtrA1 knockdown and/or overexpression.

Reviewer #2 (Public Review):

Summary:

The manuscript expands the current bulk sequencing data deconvolution toolkit to include ATAC-seq. The EPIC-ATAC tool successfully predicts accurate proportions of immune cells in bulk tumour samples and EPIC-ATAC seems to perform well in benchmarking analyses. The authors achieve their aim of developing a new bulk ATAC-seq deconvolution tool.

Strengths:

The manuscript describes simple and understandable experiments to demonstrate the accuracy of EPIC-ATAC. They have also been incredibly thorough with their reference dataset collections. The authors have been robust in their benchmarking endeavours and measured EPIC-ATAC against multiple datasets and tools.

Weaknesses:

Currently, the tool has a narrow applicability in that it estimates the percentage of immune cells in a bulk ATAC-seq experiment.

Comments:

(1) Has any benchmarking been done on the runtime of the tool? Although EPIC-ATAC seems to "win" in benchmarking metrics, sometimes the differences are quite small. If EPIC-ATAC takes forever to run, compared to another tool that is a lot quicker, might some people prefer to sacrifice 0.01 in correlation for a quicker running tool?

(2) In Figure 3B the data points look a bit squashed in the bottom-left corner. Could the plot be replotted with the data point spread out? There also seems to be some inter-patient variability. Could the authors comment on that?

(3) Could the authors comment on the possibility of expanding EPIC-ATAC into more than a percentage prediction tool? Perhaps EPIC-ATAC could remove the immune cell signal from the bulk ATAC-seq data to "purify" the uncharacterised cells in silico, or generate pseudo-ATAC-seq tracks of the identified cell types.

Reviewer #2 (Public Review):

Summary:

In their manuscript entitled "In vitro function, assembly and interaction of primary cell wall cellulose synthase homotrimers" Purushotham et al. purify and functionally and structurally characterize the primary cell wall cellulose synthase isoforms from soybeans. Overall, the manuscript is well-written and contributes several important observations.

Strengths:

The structural and functional characterization of all three primary cell wall CesA isoforms contributes significantly to important problems in plant biochemistry.

The demonstration that the isolated CesA monomers and homotrimers are catalytically active in vitro, interact with each other, and show catalytic cooperativity between the homotrimers.

Weaknesses:

The paper could be further strengthened by addressing the following:

Are the interactions between the homotrimers observed via the pull-down assays stable enough to co-elute on the sizing column or are they transient interactions?

The authors show that the monomeric CesA isoforms can interact with each other using pull-down assays (Figure Supplement 4e). Are these interactions stable or transient? Have the authors tried running the mixed monomers over a sizing column? If you mix all three isoform monomers can you form heterotrimers?

The authors demonstrate via truncation that the N-terminus of the CesA is not involved in the interactions between the isoforms and propose that the CSR hook-like extensions are the primary mediator of trimer-trimer interactions. This argument would be strengthened by equivalent truncation experiments in which the CSR region is removed.

The statement on page 6 that "All CesA isoforms show greatest catalytic activity at neutral pH" seems to contradict the data in Figure 1e and the subsequent statements.

Reviewer #2 (Public Review):

In the manuscript entitled "Noncaloric monosaccharides induce excessive sprouting angiogenesis in zebrafish via foxo1a-marcksl1a signal". Liu et al. observed that glucose and noncaloric monosaccharides can prompt an excessive formation of blood vessels, particularly intersegmental vessels (ISVs). They propose that these branched vessels arise from the ectopic activation of quiescent endothelial cells (ECs) into tip cells. Moreover, through single-cell transcriptome sequencing analysis of embryonic endothelial cells exposed to glucose, they noted an increased proportion of arterial and capillary endothelial cells, proliferative endothelial cells, along with a series of upregulated genes in categories of blood vessel morphogenesis, development, and pro-angiogenesis. The authors provide evidence suggesting that caloric and noncaloric monosaccharides (NMS) induce excessive angiogenesis via the foxo1a-Marcksl1a pathway.

The authors address an important problem about the effects of artificially sweetened beverages such as noncaloric monosaccharides on blood vessels. However, the study lacks adequate experimental data and comprehensive analyses to support the mechanistic conclusions, which require extensive revisions.

Reviewer #2 (Public Review):

This study investigates the excitability of neurons in the peri-infarct cortex during recovery from ischemic stroke. The excitability of neurons in the peri-infarct cortex during stroke recovery has produced contradictory findings: some studies suggest hyper-excitability to direct-brain stimulation, while others indicate diminished responsiveness to physical stimuli. However, most studies have used anesthetized animals, which can disrupt cortical activity and functional connectivity. The present study used two-photon Ca2+ imaging after focal photothrombotic stroke to examine neural activity patterns in awake mice. The authors found reduced neuronal spiking in the peri-infarct cortex that was strongly correlated with motor performance deficits. Additionally, the authors found disruptions in neural activation, functional connectivity, and assembly architecture in the immediate peri-infarct region but not in the distal cortex regions.

The findings of this study are very important as they show that there is no measurable change in terms of neuronal activation and reorganization in distal regions of remapped cortical response areas after stroke.

Reviewer #2 (Public Review):

Summary:

This study provides an important overview of infectious etiology for neurodevelopment delay.

Strengths:

Strong RNA evaluation.

Weaknesses:

The study lacks an overview of other infectious agents. The study should address the epigenetic contributors (PMID: 36507115) and the role of supplements in improving outcomes (PMID: 27705610).<br /> Addressing the above - with references included - is recommended.

Reviewer #2 (Public Review):

Summary:

This is an important and very interesting report on a change in newborns' neural abilities to distinguish auditory signals as a function of the gestational age (GA) of the infant at birth (from 35 weeks GA to 40 weeks GA). The authors tested neural discrimination of sounds that were labeled 'happy' vs 'neutral' by listeners that represent two categories of sound, either human voices or auditory signals that mimic only certain properties of the human vocal signals. The finding is that a change occurs in neural discrimination of the happy and neutral auditory signals for infants born at or after 37 weeks of gestation, and not prior (at 35 or 36 weeks of gestation), and only for discrimination of the human vocal signals; no change occurs in discrimination of the nonhuman signals over the 35- to 40-week gestational ages tested. The neural evidence of discrimination of the vocal happy-neutral distinction and the absence of the discrimination of the control signals is convincing. The authors interpret this as a 'landmark' in infants' ability to detect changes in emotional vocal signals, and remark on the potential value of the test as a marker of the infants' interest in emotional signals, underscoring the fact that children at risk for autism spectrum disorder may not show the discrimination. Although the finding is novel and interesting, additional discussion is essential so that readers understand two potential caveats affecting this interpretation.

Strengths:

The event-related potential (ERP) method and results are clear, well-described, and convincing.

Weaknesses/ Information needed:

First, readers need to see spectrograms that show the 0-4000 Hz in more detail, rather than what is now shown (0-10,000 Hz). The vocal signals in clearer spectrograms will show I believe the initial consonant burst and formant frequencies that are unique to human speech and give rise to the perception of the consonant sounds in the vocal signals like 'dada' and 'tutu' that were tested. The control signals will presumably not show these abrupt acoustic changes at their onset, even though they appear (from the oscillograms) to approximate the amplitude envelope. The primary cue distinguishing the happy and neutral signals in both the vocal and control signals is the pitch of the signals (high vs low), but the burst of energy representing the consonants is only contained in the vocal signals; it has no comparable match in the control signals. It is possible that the presence of a sharp acoustic onset (a unique characteristic of consonants in human speech) is especially alerting to the infants, and that this acoustic cue, in the context of the pitch change, enhances discrimination in the vocal case. One way to test this would be to use only vowel sounds to represent the vocal signals, without consonants. Another critical detail that the authors need to include about the signals is an explanation of how the control signals were generated. The text states that the Fo and amplitude envelope of the vocal signals were mimicked in the control signals, but what was the signal used for the controls? Was a pure tone complex modulated, or was pink noise used to generate the control signals? Or were the original vocal signals simply filtered in some way to create the controls, which would preserve the Fo and amplitude envelope? If merely filtered, the control signals still may be perceived as 'vocal' signals, rather than as nonspeech (the Supplement contains the sounds, and some of the control sounds can be perceived, to my ear, as 'vocal' signals).

Second, there is no information in the manuscript or supplement about the auditory environment of the participants, nor discussion of the fetus' ability to hear in the womb. In the womb, infants are listening to the mothers' bone-conducted speech (which is full of consonant sounds), and we know from published studies that infants can discern differences not only in the prosody of the speech they hear in the womb, but the phonetic characteristics of the mother's speech. The ability at 37 weeks GA or beyond to discriminate the pitch changes in the vocal, but not control signals, could thus be due to additional experience in utero to speech. Another experiential explanation is that the infants born at 37 weeks GA and beyond may be exposed to greater amounts of speech after birth, when compared to those born at 35 and 36 weeks GA, from the attending nurses and from their caregivers, and this speech is also full of consonant sounds. What these infants hear is likely to be 'infant-directed speech,' which is significantly higher in pitch, mirroring the signals tested here. At 37 weeks GA, infants are likely more robust, may sleep less, and are likely more alert. If infants' exposure to speech, either after birth, or their auditory ability to discern differences in speech in utero, is enhanced at 37 weeks GA and beyond, then an 'experience-related' explanation is a viable alternative to a maturational explanation, and should be discussed. Perhaps both are playing a role. As the authors state, many more signals need to be tested to discern how the effect should be interpreted, and other viable interpretations of the current results discussed.

Reviewer #2 (Public Review):

Summary:

The authors develop a highly detailed pipeline to analyze hemodynamic signals from in vivo two-photon fluorescence microscopy. This includes motion correction, segmentation of the vascular network, diameter measurements across time, mapping neuronal position relative to the vascular network, and analyzing vascular network properties (interactions between different vascular segments). For the segmentation, the authors use a Convolution Neural Network to identify vessel (or neural) and background pixels and train it using ground truth images based on semi-automated mapping followed by human correction/annotation. Considerable processing was done on the segmented images to improve accuracy, extract vessel center lines, and compute frame-by-frame diameters. The model was tested with artificial diameter increases and Gaussian noise and proved robust to these manipulations.

Network-level properties include Assortativity - a measure of how similar a vessel's response is to nearby vessels - and Efficiency - the ease of flow through the network (essentially, the combined resistance of a path based on diameter and vessel length between two points).

Strengths:

This is a very powerful tool for cerebral vascular biologists as many of these tasks are labor intensive, prone to subjectivity, and often not performed due to the complexity of collecting and managing volumes of vascular signals. Modelling is not my specialty so I cannot speak too specifically, but the model appears to be well-designed and robust to perturbations. It has many clever features for processing the data.

The authors rightly point out that there is a real lack in the field of knowledge of vascular network activity at single-vessel resolution. Network anatomy has been studied, but hemodynamics are typically studied either with coarse resolution or in only one or a few vessels at a time. This pipeline has the potential to change that.

Weaknesses:

The authors apply their method to in vivo data. However, there are some weaknesses in the design that make it hard to accept many of the conclusions and even to see that the method could yield much useful data with this type of application. Primarily, the acquisition of a large volume of tissue is very slow. In order to obtain a network of vascular activity, large volumes are imaged with high resolution. However, the volumes are scanned once every 42 seconds following stimulation. Most vascular responses to neuronal activation have come and gone in 42 seconds so each vessel segment is only being sampled at a single time point in the vascular response. So all of the data on diameter changes are impossible to compare since some vessels are sampled during the initial phase of the vascular response, some during the decay, and many probably after it has already returned to baseline. The authors attempt to overcome this by alternating the direction of the scan (from surface to deep and vice versa). But this only provides two sample points along the vascular response curve and so the problem still remains.

A second problem is the use of optogenetic stimulation to activate the tissue. First, it has been shown that blue light itself can increase blood flow (Rungta et al 2017). The authors note the concern about temperature increases but that is not the same issue. The discussion mentions that non-transgenic mice were used to control for this with "data not shown". This is very important data given these earlier reports that have found such effects and so should be included. Secondly, there doesn't seem to be any monitoring of neural activity following the photo-stimulation. The authors repeatedly mention "activated" neurons and claim that vessel properties change based on distance from "activated" neurons. But I can't find anything to suggest that they know which neurons were active versus just labeled. Third, the stimulation laser is focused at a single depth plane. Since it is single-photon excitation, there is likely a large volume of activated neurons. But there is no way of knowing the spatial arrangement of neural activity and so again, including this as a factor in the analysis of vascular responses seems unjustified.

The study could also benefit from more clear illustration of the quality of the model's output. It is hard to tell from static images of 3-D volumes how accurate the vessel segmentation is. Perhaps some videos going through the volume with the masks overlaid would provide some clarity. Also, a comparison to commercial vessel segmentation programs would be useful in addition to benchmarking to the ground truth manual data.

Another useful metric for the model's success would be the reproducibility of the vessel responses. Seeing such a large number of vessels showing constrictions raises some flags and so showing that the model pulled out the same response from the same vessels across multiple repetitions would make such data easier to accept.

A number of findings are questionable, at least in part due to these design properties.

There are unrealistically large dilations and constrictions indicated. These are likely due to artifacts of the automated platform. Inspection of these results by eye would help understand what is going on.

In Figure 6, there doesn't seem to be much correlation between vessels with large baseline level changes and vessels with large stimulus-evoked changes. It would be expected that large arteries would have a lot of variability in both conditions and veins much less. There is also not much within-vessel consistency. For instance, the third row shows what looks like a surface vessel constricting to stimulation but a branch coming off of it dilating - this seems biologically unrealistic.

As mentioned, the large proportion of constricting capillaries is not something found in the literature. Do these happen at a certain time point following the stimulation? Did the same vessel segments show dilation at times and constriction at other times? In fact, the overall proportion of dilators and constrictors is not given. Are they spatially clustered? The assortativity result implies that there is some clustering, and the theory of blood stealing by active tissue from inactive tissue is cited. However, this theory would imply a region where virtually all vessels are dilating and another region away from the active tissue with constrictions. Was anything that dramatic seen?

As mentioned, the claims about distance to active neurons are not meaningful if there is no measure of which neurons were active and which weren't. But even still, the claim is overly strong as the average distance to the nearest neuron for dilators was ~17 microns and for constrictors it was ~22 microns - about a half a neuronal soma difference.

The distance to the nearest neuron likely will depend on depth as well - neurons are quite sparse superficially and very dense in layer 4. The capillary network varies much less (see Blinder et al 2016 Nature Neuroscience). So the distance of a neuron to the nearest capillary may not vary much with depth, but the distance from the capillary to the nearest neuron might vary quite a lot.<br /> Why were nearly all vessels > 5um diameter not responding >2SD above baseline? Did they have highly variable baselines or small responses? Usually, bigger vessels respond strongly to local neural activity.

Reviewer #2 (Public Review):

Summary:

The research conducted by Yaning Cui and colleagues delves into understanding FLS2-mediated immunity. This is achieved by comparing the spatiotemporal dynamics of a FLS2-S938A mutant and FLS2-WT, especially in relation to their association with the remorin protein. To delineate the differences between the FLS2-S938A mutant and FLS2-WT, they utilized a plethora of advanced fluorescent imaging techniques. By analyzing surface dynamics and interactions involving the receptor signal co-receptor BAK1 and remorin proteins, the authors propose a model of how FLS2 and BAK1 are assembled and positioned within a remorin-specific nano-enviroment during FLS2 ligand-induced immune responses.

Strengths:

These techniques offer direct visualizations of molecular dynamics and interactions, helping us understand their spatial relationships and interactions during innate immune responses.

Advanced cell biology imaging techniques are crucial for obtaining high-resolution insights into the intracellular dynamics of biomolecules. The demonstrated imaging systems are excellent examples to be used in studying plant immunity by integrating other functional assays.

Weaknesses:

It's essential to acknowledge that every fluorescence-based method, just like biochemical assays, comes with its unique limitations. These often pertain to spatial and temporal resolutions, as well as the sensitivity of the cameras employed in each setup. Meticulous interpretation is pivotal to guarantee an accurate depiction and to steer clear of potential misunderstandings when employing specific imaging systems to analyze molecular attributes. Moreover, a discerning interpretation and accurate image analysis can offer invaluable guidance for future studies on plant signaling molecules using these nice cell imaging techniques.

For instance, although single-particle analysis couldn't conclusively link FLS2 and remorin, FLIM-FRET effectively highlighted their ligand-triggered association and the disengagement brought on by mutations. While these methodologies seemed to present differing outcomes, they were described in the manuscript as harmonious. In reality, these differences could highlight distinct protein populations active in immune responses, each accentuated differently by the respective imaging techniques due to their individual spatial and temporal limitations. Addressing these variations is imperative, especially when designing future imaging explorations of immune complexes.

Reviewer #2 (Public Review):

Summary:

The authors present a framework for exploiting shotgun metagenomics and metabolomics data along with constraint-based analysis (CBA) to study, in their case, the dynamics and interactions between the apple rootstock and rhizosphere's microbial community. This study should be considered as a follow-up of Berihu et al. (2022) where the shotgun data were first introduced. A set of 395 Metagenome-Assembled Genomes (MAGs) was derived from those reads and from the latter, using an automatic Genome-scale Metabolic Model (GSMM) reconstruction tool (CarveMe), 243 GSMMs. Metabolomics data from a set of studies were gathered to describe/represent root exudates. Flux Variability Analysis (FVA), a type of constraint-based analysis, was conducted iteratively. Three distinct in silico media were used (optimal, poor, and realistic, with the latter informed by metabolomics data) to examine the potential impact of root exudates on bacterial growth. Additionally, the study investigated the extent to which compounds secreted by bacteria could support the growth of other community members. Further, an exchange network representing all potential metabolic exchanges within the rhizosphere community was built and motifs on it were classified with healthy and/or symptomized soil.

Strengths:

The study provides a great starting point for how one can bring together shotgun metagenomics and other omics technologies such as metabolomics with metabolic modelling approaches. MAGs and the automatic reconstruction of corresponding GSMMs become more and more a common practice and frameworks for their analysis and interpretation are more than needed. The usage of FVA instead of the Flux Balance Analysis allows the authors to get all the range of potentially produced metabolites. The iterative approach can highlight what species are supported by the plant and which need the first to join the community while correlating microbial metabolic interactions with soil performance through differential abundance can bring up valid hypotheses to examine further. On top of that, avoiding modelling approaches that require community objective functions and optimization of that makes the simulation more realistic.

Weaknesses:

There are two main drawback approaches like the one described here, both related only partially to the authors' work yet with great impact in the presented framework. First, the usage of automatic GSMM reconstruction requires great caution. It is indicative of how the semi-curated AGORA models are still considered reconstructions and expect the user to parameterize those in a model. In this study, CarveMe was used. CarveMe is a well-known tool with several pros [1]. Yet, several challenges need to be considered when using it [2]. For example, the biomass function used might lead to an overestimation of auxotrophies. Also, as its authors admit in their reply paper, CarveMe does gap fill in a way [3]; models are constructed to ensure no gaps and also secure a minimum growth. However, curation of such a high number of GSMMs is probably not an option. Further, even if FVA is way more useful than FBA for the authors' aim, it does not yet ensure that when a species secretes one compound (let's say metabolite A), the same flux vector, i.e. the same metabolic functioning profile, secretes another compound (metabolite B) at the same time, even if the FVA solution suggests that metabolite B could be secreted in general.

Besides those challenges, the suggested framework is promising and such approaches can work as the starting point for the next step in microbial ecology studies in general; from soil to marine and host ecosystems. The authors highlight perfectly this angle stating that this framework is currently conceptual and that it can be only used to formulate new hypotheses. Unbiased constraint-based approaches that focus on metabolite exchanges would benefit such approaches.

[1] Mendoza, Sebastián N., et al. "A systematic assessment of current genome-scale metabolic reconstruction tools." Genome biology 20.1 (2019): 1-20.<br /> [2] Price, Morgan. "Erroneous predictions of auxotrophies by CarveMe." Nature Ecology & Evolution 7.2 (2023): 194-195.<br /> [3] Machado, Daniel, and Kiran R. Patil. "Reply to: Erroneous predictions of auxotrophies by CarveMe." Nature Ecology & Evolution 7.2 (2023): 196-197.<br /> [4] Ylva Katarina Wedmark, Jon Olav Vik, Ove Øyås bioRxiv 2023.09.05.556413; doi: https://doi.org/10.1101/2023.09.05.556413

Reviewer #2 (Public Review):

In this manuscript, Chen et al. reported that the core binding factor beta (Cbfβ), a heterodimeric subunit of the RUNX family transcription factors (TFs), is crucial in maintaining cartilage homeostasis and counteracting traumatic OA pathology. Using mouse models in which Cbfβ is conditionally inactivated in the Col2a1+ and Acan+ cells, the authors claimed that Cbfβ ablation led to articular cartilage (AC) degeneration, which is associated with aberrant cartilage gene expression and chondrocyte signaling, particularly the elevated Wnt/Catenin and the decreased Hippo/YAP and TGFβ signaling. The authors further showed that Cbfβ transcripts are decreased in human OA cartilage, and sustaining Cbfβ expression in mouse knee joints mitigated the severity of surgery-evoked OA.

On the whole, the work reported is interesting and exciting. Genetic and biochemical data support key statements. Both in vivo and in vitro experiments were well designed with proper controls; semiquantitative data were digitalized and processed for statistical significance. Furthermore, new findings were adequately discussed in contrast to the current available knowledge. However, the conceptual novelty of this study is slightly compromised by recent publications showing that Cbfβ reduction is associated with OA (Che et al. 2023; Li et al. 2021). Also, the authors claimed that multiple signaling pathways were affected by Cbfβ ablation in cartilage cells; many of them, however, are indirect effects given the nature of Cbfβ as a TF. The authors also showed that pSMAD2/3 and active βCatenin decreased and increased upon Cbfβ depletion in the mouse AC cartilage. However, how the deficiency of Cbfβ, a widely expressed TF, affected the posttranslational modification of SMAD2/3 and βCatenin is unclear and needs further discussion. Overall, Cbfβ's role in cartilage and OA pathology is an emerging area of study; the authors provided a set of genetic evidences showing that Cbfβ is indispensable for cartilage homeostasis.

Reviewer #2 (Public Review):

The manuscript expands on the previous work from the lab where novel interactors of Rac1 GTPase (CYRI-A and B) provide localized inhibition by sequestration of activated Rac1. These novel regulators are fascinating as they complement the functions of the classical negative modulators of GTPases, GAPs and GDIs. The current manuscript focuses on the in vivo role of CYRI-B in pancreatic cancer progression, and distinct CYRI-B functions are shown for early and later stages. The in vivo data following CYRI-B depletion (no change in proliferation, reduced metastatic potential) is substantiated with in vitro analyses of receptor uptake, temporal recruitment of CYRI-B on macropinosomes and reduced chemotaxis.

The authors describe in detail the role of CYRI-B in pancreatic adenocarcinoma, building from their prior studies mapping CYRI-B function in the regulation of polarity, motility and chemotaxis. The experiments are well-designed and performed, and the text was clearly written. However, the results partially support some of their conclusions. The interpretation of the data and the discussion in the context of human pancreatic tumours would help the understanding and impact of the work.

The hypothesis is that depletion of CYRI-B would promote localized Rac1 activation at the membrane. However, the authors show that CYRI-B is found overexpressed in PDAC, consistent with other papers where its high expression correlates with poor outcome of many cancers. The prediction is that Rac1 functions modulated by CYRI-B would be inhibited in those tumours where CYRI-B is overexpressed. Is this the case and has it been formally demonstrated?

Most experiments use the depletion of CYRI-B to probe its function. It would be useful to readers and important to elaborate on how the specific CYRI-B functions shown upon depletion would fit with the in vivo observation of CYRI-B overexpressed in tumours. For example, loss of CYRI-B reduces chemotaxis potential. How this result can be conciliated with the predicted increase in Rac1activation in the absence of CYRI-B? Conversely, a prediction of CYRI-B overexpression in human tumours would imply the inactivation of Rac1 whereas chemotaxis is promoted. The discussion could be improved with the addition of the authors' views and further explanations in this context.

Similarly, it is confusing to extrapolate a proposed increase in LPAR1 internalization by macropinocytosis with CYRI-B overexpression in PDAC. It is predicted that Rac1 would be locally inhibited in this scenario, and thus micropinocytosis would be compromised. It will be good to spell out what the authors envisage happens. For example, uptake could be switched to another receptor uptake process that would not involve CYRI-B sequestration of Rac1. Discussion of the potential alternatives will strengthen the manuscript.

"..LPAR1 is a cargo of CYRI-B dependent macropinocytosis" (page 21). This statement reads as an overinterpretation of the specificity of the process. It may suggest that there is a cargo selectivity by CYRI-B, which has not been formally demonstrated or is well accepted. Macropinocytosis is thought to occur as a bulk engulfment of the membrane and thus any receptor at the cell surface would be internalised non-specifically. The demonstrated reduction in LPAR1 uptake could be proportional to the interference with micropinocytosis rate by CYRI-B depletion for example

Furthermore, the readers would benefit from more clear explanations of the differences and similarities between CYRI-A and CYRI-B. It will be important to clarify the specificity of the proposed functions of each protein. Both localize at the macropinosomes, modulate engulfment and regulate integrin a5b1 trafficking. It will be informative to specify if CYRI-A is also upregulated in human tumours, has a similar outcome as CYRI-B in vivo and also regulates LPAR1 uptake.

Upon depletion of CYRI-B in pancreatic tumour cells in vivo, the presence of similar levels of jaundice is confusing. Less metastasis is detected in the mesentery. Are liver metastasis affected in the absence of CYRI-B?

Reviewer #2 (Public Review):

Schwann cells actively repair and regenerate peripheral nerves following tissue injury. Central to this process is the collective cell migration of 'cords' of Schwann cells, which guide the regenerating axons across an injury site. Previously published research from the Lloyd lab shows that at the injury site, Schwann cell cords are maintained via N-cadherin-based cell-cell adhesions; however, when cultured under low density conditions, Schwann cells display cell repulsion and contact inhibition of locomotion (CIL) phenotypes, suggesting Schwann cell behaviour is plastic. In this study, Hoving, Lloyd and colleagues build upon their previous work to show that Slit2/3/Robo signalling triggers cell repulsion between Schwann cells in an N-cadherin-dependent manner. This in turn induces contact inhibition of locomotion to propel Schwann cells to migrate collectively and with direction. The authors show that N-cadherin has a dual function in Schwann cell migration: to keep migrating Schwann cells together as a group, and concomitantly present Slit2/3 repulsive cues to cells to trigger cell repulsion locally. Their data also show that extracellular N-cadherin is required for cell repulsion, independent of cell-cell adhesion functions. The authors use a combination of in vitro Schwann cell cultures and live cell imaging, with an ex vivo precision cut tissue slice system to show that Slit2/3-dependent CIL underpins proper Schwann cell migration in an injury model.

This is a very well executed and important study, which provides new insights into mechanisms of CIL and places CIL in the context of tissue repair and regeneration in adult tissues. The experiments are well designed, and the main findings and conclusions are based on robust and convincing data.

Reviewer #2 (Public Review):

It is well-known that repeated exposure to perceptual stimuli improves discrimination performance, but less is known about the effects on perceptual appearance. In the present work, the authors tackle this question and focus on one particular effect on perceptual appearance termed boundary avoidance, i.e. the tendency to perceive (or report) a stimulus as biased away from a discrimination boundary.

In the study, participants performed either a motion discrimination task (clockwise or counterclockwise with respect to a reference axis) or an estimation task (reproducing the orientation of the motion stimulus). Participants were divided in three groups which either i) trained on the discrimination task, ii) trained on the estimation task or iii) received no training (control group). Performance in both tasks was assessed prior and after training. The main behavioral finding is that training (which did not involve feedback) improved discrimination performance and increased estimation precision, but at the same time appeared to increase the boundary avoidance effect. Thus, the authors conclude that perceptual learning improved performance at the cost of appearance.

To explain these effects, the authors created a computational model in which performance improvements were implemented as a gain increase of neurons sensitive to the trained motion directions. Repulsive biases away from the reference orientation were implemented by a combination of two modeling choices: i) Even during estimation, participants perform an implicit categorization such that they assume that their percept was created by a stimulus in line with their categorization (clockwise or counterclockwise). This effectively biases their response away from the boundary. ii) There is an abundance of neurons tuned to the horizontal reference axis (the "boundary") which likewise leads to a repulsive bias. Overall, the authors conclude that the model was able to explain the major behavioral effects, including the a priori presence of repulsive biases, the increase in performance, the increase in estimation precision and the increase of the repulsive bias.

It is well-known that repeated exposure to perceptual stimuli improves discrimination performance, but less is known about the effects on perceptual appearance. In the present work, the authors tackle this question and focus on one particular effect on perceptual appearance termed boundary avoidance, i.e. the tendency to perceive (or report) a stimulus as biased away from a discrimination boundary. On first glance, it was a pleasure reading this paper due to a number of aspects the authors got quite right in my opinion:<br /> - A clear and well-explained research question.<br /> - The results are generally well-presented. Much effort and expertise was put into the Figures and many helpful auxiliary Figures are included as a Supplement.<br /> - The writing was concise and clear.

However, as outlined below, I'm afraid that the main conclusion of the study and the main motivation for computational modeling are not backed up by the data.

(1) No evidence for a change in overestimation<br /> Overestimation is (rightly) defined by the authors as a bias of the perceived orientations towards more extreme values (visualized also in Fig. 2F). However, as acknowledged by the authors, there is nearly no evidence for such an effect. The modal estimation response (correct trials) doesn't change significantly between the sessions. The mean, which is the primary measure used by the authors, is not an appropriate measure for an overestimation, as it is severely biased by accuracy. It was unclear to me why it was chosen as the primary measure for nearly all figures and analyses, given that the authors were aware of (and reported) a more suited measure.

In my opinion, the mode of the correct responses would be the best way to quantify the overestimation bias. An alternative would be looking at the average absolute (unsigned) distance from the boundary, possibly including both correct and incorrect responses. However, such a "mean of absolute differences" approach would be affected by lucky guessing trials, which could manifest in a probability mass close to the boundary (and the proportion of which changes with overall accuracy). Therefore I see the mode as the strongest and least confounded measure.

(2) Nature of the biases<br /> Although, as outlined in 1), there might actually be no evidence for a *change* in overestimation bias, there clearly was a baseline overestimation bias. However, the reported biases appear extremely large. For instance, for the 2{degree sign} orientation the modal estimation is close to 20{degree sign}. To me this raises the question whether we're really dealing with a pure perceptual effect (18{degree sign} misperception seems quite suboptimal) or whether there are some other psychological effects at work that could be rather classified as a response bias.

In particular, I wondered whether the baseline bias is partly explained by participants "wanting to make sure" they indicate the correct category in estimation and therefore bias their estimation response away from the ambiguous proximity of the cardinal axes? Does it require more effort to set estimation orientation close to a cardinal axis while still making sure that it has the correct categorical orientation. I guess there was no horizontal reference line on the screen which would help with this?

The overall discrimination-focused task design might have contributed to this bias. First, because the participants trained on estimation also performed a discrimination task (pre/post) which very likely could have affected their response style. Second, the presented orientations during estimation were likewise 50:50 around the horizontal reference which could shift the focus towards "getting the sign right" rather than "getting the precise orientation right".

(3) The mechanism of the model<br /> As a disclaimer a priori, I am not very familiar with this particular modeling literature (but this may be the case for other readers as well). For this reason I could have used a bit more guidance about how the model works. My understanding is that there a three key mechanisms: 1) Gain modulation which explains the improvement in discrimination; 2) Warping which partly explains boundary avoidance; 3) Implicit categorization which likewise partly explains boundary avoidance. In addition, there are two levels of analysis: 1) the pre-training state (a priori presence of a repulsive bias) and 2) learning effects (bias and performance increase through training). If the models were to be kept as part of a revised manuscript, my suggestion would be to structure the corresponding section in the Results ("Observer Model") a bit more along these anchors. I suggest also providing a bit more explanation already at this point. For instance, I consider the fact that implicit categorization effectively works through Bayes rule by assuming a uniform(?) prior over either the negative or positive orientation axis, as very relevant. I assume that other priors would have been conceivable for conditioning on the response, e.g. taking into account the actual (objective or subjective) distribution of orientations for the particular choice category, so this is a non-trivial modeling choice.<br /> Intuitively, I would have also thought that if more resources are devoted to the cardinal directions (and the decoder is unaware of this), this would lead to a bias *towards* the cardinal directions. If more neurons fire particularly strong to near-cardinal orientations (such as the +-4{degree sign} in training), why would the decoder be repulsed *away* from the cardinal orientation? I trust the authors that the presentation is correct, but to me, this was not obvious and I would have wished for some guidance.

Reviewer #2 (Public Review):

This manuscript describes a new algorithm for clonal family inference based on V and J gene identity, sequence divergence in the CDR3 region, and shared mutations outside the CDR3. Specifically, the algorithm starts by grouping sequences that have the same V and J genes and the same CDR3 length. It then performs single-linkage clustering on these groups based on CDR3 Hamming distance, then further refines these groups based on shared mutations.

Although there are a number of algorithms that use a similar overall strategy, a couple of aspects make this work unique. First, a persistent challenge for algorithms such as this one is how to set a cutoff for single-linkage clustering: if it is too low, then one separates clusters that should be together, and if too high one joins together clusters that should be separate. Here the authors leverage a rich collection of probabilistic tools to make an optimal choice. Specifically, they model the probability distributions of within- and between-cluster CDR3 Hamming distances, with parameters depending on CDR3 length and the "prevalence" of clonal sequence pairs (i.e. family size distribution). This allows the algorithm to make optimal choices for separating clusters, given the particular chosen distance metric, and assuming the sample in question has been accurately modeled. Second, the algorithm uses a highly efficient means of doing single-linkage clustering on nucleotide sequences.

This leads to a fast and highly performant algorithm on data meant to replicate the original sample used in algorithm design. The ideas are new and beautifully developed. The application to real data is interesting, especially the point about dN/dS.

However, the paper leaves open the question of how this inference algorithm works on samples other than the one used for simulation and as a template for validation. If I understand the simulation procedure correctly - that one takes a collection of inferred trees from the real data, then re-draws the root sequence and the identity of the mutations on the branches - then the simulated data should be very close to the data used to develop the methods in the paper. This consideration seems especially important given that key methods in this paper use mutation counts and overall mutation counts are preserved.

Repertoires come in all shapes and sizes: infants to adults, healthy to cancerous, and naive to memory to plasma-cell-just-after-vaccination. If this is being proposed as a general-purpose clonal inference algorithm rather than one just for this sample, then a more diverse set of validations are needed.

It is unclear how to run the code. The software repo has a nice readme explaining the file layout, dependencies, and input file format, but the repo seems to be lacking an `inference.ipynb` mentioned there which runs an analysis. Perhaps this is a typo and refers to `inference.py`, which in addition to the documented cdr3 clustering, seems to have functions to run both clustering methods. However, it does not seem to have any documentation or help messages about how to run these functions.

The results are not currently reproducible, because the simulated data is not available. The data availability statement says that no data have been generated for this manuscript, however simulated data has been generated, and that is a key aspect of the analysis in the paper.

More detail is needed to understand the timing comparisons. The new software is clearly written to use many threads. Were the other software packages run using multiple threads? What type of machine was used for the benchmarks?

Reviewer #2 (Public Review):

I completely agree with the basic thrust of this study. Yes, of course, machine learning is FAR better than any variant of PCA for the paleosciences. I agree with the authors' critique early on that this point is not new per se - it is familiar to most of the founders of the field of GMM, including this reviewer. A crucial aspect is the dependence of ALL of GMM, PCA or otherwise, on the completely unexamined, unformalized praxis by which a landmark configuration is designed in the first place. I must admit that I am stunned by the authors' estimate of over 32K papers that have used PCA with GMM.

But beating a dead horse is not a good way of designing a motor vehicle. I think the manuscript needs to begin with a higher-level view of the pathology of its target disciplines, paleontology and paleoanthropology, along the lines that David Hull demonstrated for numerical taxonomy some decades ago. That many thousands of bad methodologies require some sort of explanation all of their own in terms of (a) the fears of<br /> biologists about advanced mathematics, (b) the need for publications and tenure, (c) the desirability of covers of Nature and Science, and (d) the even greater glory of getting to name a new "species." This cumulative pathology of science results in paleoanthro turning into a branch of the humanities, where no single conclusion is treated as stable beyond the next dig, the next year or so of applied genomics, and the next chemical trace analysis. In short, the field is not cumulative.

It is not obvious that the authors' suggestion of supervised machine learning will remedy this situation, since (a) that field itself is undergoing massive changes month by month with the advent of applications AI, and even more relevant (b) the best ML algorithms, those based on deep neural nets, are (literally) unpublishable - we cannot see how their decisions have actually been computed. Instead, to stabilize, the field will need to figure out how to base its inferences on some syntheses of actual empirical theories.

It's not that this reviewer is cynical, but it is fair to suggest a revision conveying a concern for the truly striking lack of organized skepticism in the literature that is being critiqued here. A revision along those lines would serve as a flagship example of exactly the deeper argument that reference (17) was trying to seed, that the applied literature obviously needs a hundred times more of. Such a review would do the most good if it appeared in one of the same journals - AJBA, Evolution, Journal of Human Evolution, Paleobiology - where the bulk of the most highly cited misuses of PCA themselves have appeared.

Reviewer #2 (Public Review):

Summary:

Wang and collaborators have evaluated the impact of inflammation on bone loss induced by Doxorubicin, which is commonly used in chemotherapy to treat various cancers. In mice, they show that a single injection of Doxorubicin induces systemic inflammation, leukopenia, and a significant bone loss associated with increased bone-resorbing osteoclast numbers. In vitro, the authors show that Doxorubicin activates the AIM2 and NLRP3 inflammasomes in macrophages and neutrophils. Importantly, they show that the full knockouts (germline deletions) of AIM2 (Aim2-/-) and NLRP3 (Nlrp3-/-) and Caspase 1 (Casp1-/-) limit (but do not completely abolish) bone loss induced 4 weeks after a single injection of Doxorubicin in mice. From these results, they conclude that Doxorubicin activates inflammasomes to cause inflammation-associated bone loss.

Strength:

This manuscript provides functional experiments demonstrating that NRLP3 and/or AIM2 loss-of-functions (and thus the systemic impairment of the inflammatory response) prevent bone-loss induced by Doxorubicin in mice.

Weaknesses:

Numerous studies have reported that Doxorubicin induces systemic inflammation and activates the inflammasome in myeloid cells and various other cell types. It is also known that systemic inflammation and Doxorubicin treatment lead to bone loss. Hence, the key conclusions drawn from this work have been known already or were very much expected. Therefore, the novelty appears somewhat limited. One important limitation is the lack of experiments that could determine which cell lineages are involved in bone loss induced by Doxorubicin in vivo, while the tools to do so exist. The characterization of the bone phenotype is incomplete, and unfortunately does not tell us whether the inflammasome is activated in some of the cell lineages present in bones in vivo. Another limitation is that the relative importance of the inflammasomes compared to cell senescence and autophagy, which are also induced by Doxorubicin, has not been evaluated. Hence the main molecular mechanisms responsible for bone loss induced by Doxorubicin in vivo remains unknown. Lastly, it would have been interesting, on a more clinical point of view, to compare the few relevant treatments that could limit the deleterious effect of Doxorubicin on bone loss while preserving the toxicity on tumor cells.

Reviewer #2 (Public Review):

Summary:

The authors previously generated renal Glut2 knockout mice, which have high levels of glycosuria but normal fasting glucose. They use this as an opportunity to investigate how compensatory mechanisms are engaged in response to glycosuria. They show that renal and hepatic glucose production, but not metabolism, is elevated in renal Glut2 male mice. They show that renal Glut2 male mice have elevated Crh mRNA in the hypothalamus, and elevated plasma levels of ACTH and corticosterone. They also show that temporary denervation of renal nerves leads to a decrease in fasting and fed blood glucose levels in female renal Glut2 mice, but not control mice. Finally, they perform plasma proteomics in male mice to identify plasma proteins with a greater than 25% (up or down) between the knockouts and controls.

Strengths:

The question that is trying to be addressed is clinically important: enhancing glycosuria is a current treatment for diabetes, but is limited in efficacy because of compensatory increases in glucose production.

Weaknesses:

(1) Although I appreciate that the initial characterization of the mice in another publication showed that both males and females have glycosuria, this does not mean that both sexes have the same mechanisms giving rise to glycosuria. There are many examples of sex differences in HPA activation in response to threat, for example. There is an unfounded assumption here that males and females have the same underlying mechanisms of glycosuria that undermines the significance of the findings.

(2) The authors state that they induced the Glut2 knockout with taxomifen as in their previous publication. The methods of that publication indicate that all experiments were completed within 14 days of inducing the Glut2 knockout. This means that the last dose of tamoxifen was delivered 14 days prior to the experimental endpoint of each experiment. This seems like an important experimental constraint that should be discussed in this manuscript. Is the glycosuria that follows Glut2 knockout only a temporary change? If so, then the long-term change in glycosuria that follows SGLT2 inhibition in humans might not be best modelled by this knockout. Please specify when the surgeries to implant a jugular catheter or ablate the renal nerves performed relative to the Glut2 knockout in the Methods.

(3) I am still unclear what group was used for controls. Are these wild-type mice who receive tamoxifen? Are they KspCadCreERT2;Glut2loxP/loxP mice who do not receive tamoxifen? This is important and needs to be specified.

(4) The authors should report some additional control measures for the renal denervation that could also impact blood glucose and perhaps some of their other measures. The control measures, which one would like to see unimpacted by renal denervation, include body weights, food consumption and water intake, and glycosuria itself.

(5) The graphical abstract shows a causal link between the hypothalamus and the liver that is unsupported by any of the current findings. That arrow should be removed or a question mark should be added next to the arrow.

(6) Though the authors have toned down their language implying a causal link between the HPA measures and compensatory elevation of blood glucose in the face of glycosuria, the title still implies this causal link. It is still the case that their data do not support causation. There are many potential ways to establish a causal link but those experiments are not performed here. The renal afferents are correlated with Crh content of the PVN, but nothing has been done to show that the Crh content is important for elevating blood glucose. In light of this, the title should be toned down. Perhaps something like "Renal nerves maintain blood glucose production and elevated HPA activity in response to glycosuria". The link between HPA and glucose is not shown in this paper.

Reviewer #2 (Public Review):

Summary:

The authors identify the root cap as an important key region for establishing microbial symbioses with roots. By highlighting for the first time the crucial importance of tight regulation of a specific form of programmed cell death of root cap cells and the clearance of their cell corpses, they start unraveling the molecular mechanisms and its regulation at the root cap (e.g. by identifying an important transcription factor) for the establishment of symbioses with fungi (and potentially also bacterial microbiomes).

Strengths:

It is often believed that the recruitment of plant microbiomes occurs from bulk soil to rhizosphere to endosphere. These authors demonstrate that we have to re-think microbiome assembly as a process starting and regulated at the root tip and proceeding along the root axis.

Weaknesses:

The study is a first crucial starting point to investigate the spatial recruitment of beneficial microorganisms along the root axis of plants. It identifies e.g. an important transcription factor for programmed cell death, but more detailed investigations along the root axis are now needed to better understand - spatially and temporally - the orchestration of microbiome recruitment.

Reviewer #2 (Public Review):

Summary:

This manuscript answers an important question about the transmission of Plasmodium parasites resistant to apicoplast inhibitors, specifically azithromycin. This study builds on previous work showing the inability to transmit parasites resistant to mitochondrial inhibitor, atovaquone, based on fitness defects in transmission stages in the mosquito. The transmissibility of drug-resistant parasites is grounded in the basic biology of the Plasmodium lifecycle and has implications for the selection of drug regimens for clinical treatment, so these questions are highly significant. The authors clearly demonstrate severe defects in mosquito stages of azithromycin-resistant (AZR) P. berghei (rodent species) inhibiting transmission of AZR parasites. However, surprisingly AZR P. falciparum (human species) is unaffected in mosquito stages, rather defects are observed in liver-stage development suggesting AZR P. falciparum can transmit but may not mount a productive blood infection. The differences in the observed defects in the 2 species are important and well demonstrated in the results but are obscured in the title/summary of the manuscript. The results demonstrate that AZR parasites are unlikely to spread.

Strengths:

The authors performed experiments with both P. berghei (rodent species) and P. falciparum (human species). P. falciparum is the more relevant species from a clinical standpoint, however, there are limitations to studying the full lifecycle of P. falciparum which only infects humans and some primates, for example requiring humanized mice without intact immune systems. Pberghei is commonly used in lifecycle analyses as a proxy for experimental tractability, however, there are cases where the biology of P. berghei does not reflect that in P. falciparum. So the use of both species is complementary and most informative. Specific modification of the apicoplast genome, where AZR mutations are located, is not currently possible so matched genotypes could not be produced but multiple AZR mutants were analyzed for each species. Acknowledging these limitations in the experimental systems available, the authors perform a thorough set of experiments to pinpoint the specific defects in AZR Pb vs Pf during mosquito and liver developmental stages. The results show phenotypic differences between AZR Pb and Pf in mosquito stages which was not expected but in line with differences in apicoplast biology of Pb vs Pf that are important to document and be aware of when using P. berghei as a model for P. falciparum development.

Weaknesses:

The claim that human AZR malaria parasites (P. falciparum) is not readily transmitted to mosquitoes is incorrect, as stated in the title and abstract. Strictly speaking, transmission refers to the infection of a human host by another via mosquitos. The evidence that AZR Pf is unaffected in mosquito development indicates that transmission is not reduced compared to WT Pf. Rather transmitted AZR Pf has disrupted liver stage development and may not mount a productive blood infection. This distinction between the phenotypes of AZR Pb vs Pf is surprising, significant (suggesting differences between Pb and Pf and/or specific mutations in Rpl4), and should be more accurately represented in the title/abstract. To their credit, the authors performed thorough experiments to pinpoint the specific defects in AZR Pb vs Pf, but the current claim about AZR Pf is misleading.

Additional context:

Clinical trials (MORDOR studies) in several African countries have shown that biannual administration of azithromycin reduces childhood mortality (PMID: 31167050). The mechanism of this survival benefit is unknown and may be multifactorial. The findings in this manuscript can also be considered in the context that azithromycin is a commonly used antibiotic and may be administered for purposes other than malaria treatment. In theory, AZR-resistant parasites could be selected in asymptomatic patients not receiving malaria treatment but receiving azithromycin. This study indicates that mass distribution of azithromycin for other clinical applications would not result in adverse effects on malaria transmissions in the same population.

Reviewer #2 (Public Review):

In the manuscript "Modulation of α-Synuclein Aggregation Amid Diverse Environmental Perturbation", Wasim et al describe coarse-grained molecular dynamics (cgMD) simulations of α-Synuclein (aSyn) at several concentrations and in the presence of molecular crowding agents or high salt. They begin by bench-marking their cgMD against all-atom simulations by Shaw. They then carry 2.4-4.3 µs cgMD simulations under the above-noted conditions and analyze the data in terms of protein structure, interaction network analysis, and extrapolated fluid mechanics properties. This is an interesting study because a molecular scale understanding of protein droplets is currently lacking, but I have a number of concerns about how it is currently executed and presented.

(1) It is not clear whether the simulations have reached a steady state. If they have not, it invalidates many of their analysis methods and conclusions.

(2) The benchmarking used to validate their cgMD methods is very minimal and fails to utilize a large amount of available all-atom simulation and experimental data.

(3) They also miss opportunities to compare their simulations to experimental data on aSyn protein droplets.

(4) Aspects such as network analysis are not contextualized by comparison to other protein condensed phases.

(5) Data are not made available, which is an emerging standard in the field.

Reviewer #2 (Public Review):

Summary:

The authors had previously identified that a colorectal cancer cell line generates small extracellular vesicles (sEVs) via a mechanism where a larger intracellular compartment containing these sEVs is secreted from the surface of the cell and then tears to release its contents. Previous studies have suggested that intraluminal vesicles (ILVs) inside endosomal multivesicular bodies and amphisomes can be secreted by the fusion of the compartment with the plasma membrane. The 'torn bag mechanism' considered in this manuscript is distinctly different because it involves initial budding off of a plasma membrane-enclosed compartment (called the amphiectosome in this manuscript, or MV-lEV). The authors successfully set out to investigate whether this mechanism is common to many cell types and to determine some of the subcellular processes involved.

The strengths of the study are:

(1) The high-quality imaging approaches used, seem to show good examples of the proposed mechanism.

(2) They screen several cell lines for these structures, also search for similar structures in vivo, and show the tearing process by real-time imaging.

(3) Regarding the intracellular mechanisms of ILV production, the authors also try to demonstrate the different stages of amphiectosome production and differently labelled ILVs using immuno-EM.<br /> Several of these techniques are technically challenging to do well, and so these are critical strengths of the manuscript.

The weaknesses are:

(1) Most of the analysis is undertaken with cell lines. In fact, all of the analysis involving the assessment of specific proteins associated with amphiectosomes and ILVs are performed in vitro, so it is unclear whether these processes are really mirrored in vivo. The images shown in vivo only demonstrate putative amphiectosomes in the circulation, which is perhaps surprising if they normally have a short half-life and would need to pass through an endothelium to reach the vessel lumen unless they were secreted by the endothelial cells themselves.

(2) The analysis of the intracellular formation of compartments involved in the secretion process (Figure 2_S5) relies on immuno-EM, which is generally less convincing than high-/super-resolution fluorescence microscopy because the immuno-labelling is inevitably very sporadic and patchy. High-quality EM is challenging for many labs (and seems to be done very well here), but high-/super-resolution fluorescence microscopy techniques are more commonly employed, and the study already shows that these techniques should be applicable to studying the intracellular trafficking processes.

(3) One aspect of the mechanism, which needs some consideration, is what happens to the amphisome membrane, once it has budded off inside the amphiectosome. In the fluorescence images, it seems to be disrupted, but presumably, this must happen after separation from the cell to avoid the release of ILVs inside the cell. There is an additional part of Figure 1 (Figure 1Y onwards), which does not seem to be discussed in the text (and should be), that alludes to amphiectosomes often having a double membrane.

(4) The real-time analysis of the amphiectosome tearing mechanism seemed relatively slow to me (over three minutes), and if this has been observed multiple times, it would be helpful to know if this is typical or whether there is considerable variation.

Overall, I think the authors have been successful in identifying amphiectosomes secreted from multiple cell lines and demonstrating that the ILVs inside them have at least two origins (autophagosome membrane and late endosomal multivesicular body) based on the markers that they carry. The analysis of intracellular compartments producing these structures is rather less convincing and it remains unclear what cells release these structures in vivo.

I think there could be a significant impact on the EV field and consequently on our understanding of cell-cell signalling based on these findings. It will flag the importance of investigating the release of amphiectosomes in other studies, and although the authors do not discuss it, the molecular mechanisms involved in this type of 'ectosomal-style' release will be different from multivesicular compartment fusion to the plasma membrane and should be possible to be manipulated independently. Any experiments that demonstrate this would greatly strengthen the manuscript.

In general, the EV field has struggled to link up analysis of the subcellular biology of sEV secretion and the biochemical/physical analysis of the sEVs themselves, so from that perspective, the manuscript provides a novel angle on this problem.

Reviewer #2 (Public Review):

Summary:

Overall, this study provides a thorough description of the formation of syncytia following wounding of the proliferation-competent diploid epithelium of the pupal notum. While this phenomenon has already been described briefly for this particular tissue by the Galko lab in Wang et al 2015, the authors provide a much more detailed description and characterisation of the process providing some novel insights (radial versus tangential border breakdown, cell shrinkage, timings, syncytia outcompeting mononucleated cells, etc.).

Strengths:

This paper provides an elegant, thorough, descriptive characterisation of syncytia-driven wound closure using state-of-the-art confocal live imaging of the pupal notum. The authors show that laser-induced wounding of this diploid, proliferation-competent epithelium results in the formation of syncytia of various sizes in the first few cell rows around the wound edge, which progressively become bigger as healing proceeds. This results in ~50% of cells becoming part of these syncytia. The cell fusion events were convincingly demonstrated by showing the disappearance of p120ctnRFP and E-Cadherin-GFP from cell-cell borders as well as cytoplasmic GFP mixing of GFP-positive cells with a GFP-negative cell.

Apart from cell-cell fusion by border breakdown that mostly happens in the first 2h following wounding, the authors also found that at later stages of wound healing cell shrinkage following cytoplasmic mixing contributed to sycytia formation.

Next, the authors provided some convincing evidence that syncytia outcompete mononuclear cells for being positioned in the first cell row around the wound.

The authors then show that radial border breakdown occurs much less frequently than tangential border breakdown. They suggest that radial border breakdown reduces the requirement for cell-cell intercalations. They also hypothesise that tangential border breakdown might allow fused cells to share resources and provide more resources to be used near the wound edge, e.g. for actomyosin cable formation. To test this, the authors generate single-cell clones that overexpress Actin-GFP. They then show convincingly how a single Actin-GFP-positive cell in the second cell row fuses with one GFP-negative cell in the first cell row. The Actin-GFP signal then spreads in the fused cell and labels some previously unlabelled actin-rich structure near the wound edge which most likely is the actomyosin cable. This provides some evidence for resource sharing by cytoplasmic mixing following fusion.

Weaknesses:

The authors provide some convincing evidence that syncytia outcompete mononuclear cells for being positioned in the first cell row around the wound. The authors suggest that the syncytial cells might be better able to close the wound. However, some genetic studies would need to be done to establish this more convincingly. E.g. Could the authors genetically block syncytia formation and then show that these wounds now heal slower?

The authors suggest that radial border breakdown reduces the requirement for cell intercalation. While this might be true it also raises the question of how the various syncytia facing the wound border change shape to allow the shrinkage of the first cell row over time to allow wound closure. None of the four movies included in the study shows the whole wound healing process until the later stages, making it hard to assess this. It would be good to include one such movie showing the syncytia in the whole wound and comment on this point.

The authors hypothesise that tangential border breakdown might allow fused cells to share resources and provide more resources to be used near the wound edge, e.g. for actomyosin cable formation. They show convincingly through the fusion of a single Actin-GFP-positive cell in the second cell row with a GFP-negative cell in the first cell row that Actin-GFP spreads in the fused cell and labels the previously unlabelled actomyosin cable. While the hypothesis of resource sharing to improve healing is intriguing and makes sense, this experiment doesn't necessarily prove the benefit of resource sharing. It does show cytoplasmic mixing following fusion, now allowing the GFP-labelled actin to diffuse and be incorporated into the actomyosin cable. In a wild-type condition, fusion would not increase the total concentration of resources, although it would increase the total amount of resources within this bigger fused cell. The question is whether resource sharing without increasing the protein concentration is beneficial and increases the efficiency of certain wound healing mechanisms. There might be a benefit of cell fusion, if for example certain resources were only present in limited amounts or if protein transport could increase the concentration locally. To provide better evidence for the hypothesis that resource sharing improves wound healing, maybe the authors could look at the actomyosin cable in a wounded epithelium (such as in Figure 4E, F), in which all cells express MyoII-GFP. The authors could compare the average intensity of the actomyosin cable at the wound edge in mononucleated cells versus in syncytia. If resource sharing is indeed beneficial, it might be that the actomyosin cable is stronger/brighter in syncytia or it forms quicker.

The biggest limitation of this study is that the authors don't address how the formation of these syncytia is regulated. While the manuscript in its current form provides some valuable new insights into syncytial-driven wound closure, it would be much more informative if it also provided some mechanistic details. The authors could test if some of the mechanisms shown to regulate syncytial formation in other types of syncytia-driven wound healing are also involved here. E.g. Yorkie was shown to negatively regulate cell fusion in adult syncytial-driven wound closure (Losick et al 2013). The authors could test for the effect of Yorkie-RNAi in the epithelium on wound closure and syncytia formation. Expression of the dominant negative RacN17 also blocked cell fusion in adult syncytial-driven wound closure (Losick et al 2013).

Moreover, JNK activation was shown to be needed in larval syncytial-driven wound closure (Galko and Krasnow 2004). The authors could test JNK pathway reporters to assess pathway activation or test if the JNK pathway is needed for syncytial-driven wound closure by expressing a dominant-negative form of Basket JNK in the epithelium.

Or could syncytia formation be regulated by changes in Integrin-mediated adhesion as shown by the Galko lab in Wang et al 2015? They show that wounding provoked a striking relocalization of PINCH and ILK, indicating the disassembly of functional FA complexes concomitant with syncytium formation. Maybe the authors could investigate some of these.

Another general question that the authors raise but don't address enough is whether syncytia-driven wound closure in proliferation-competent epithelia is any different from the one in post-mitotic, polyploid epithelia. Since the mechanism regulating the former is not known, this remains unclear.

Finally, it is not clear, whether syncytia in these proliferation-competent epithelia get resolved after wound healing. Do they get removed and replaced by mononucleated proliferation-competent cells or do the syncytia stay in the epithelium like a scar? The authors should provide some images of wound areas a few hours after wound closure is complete and comment on this.

Minor points:

Figure 3: It would be better to have the microcopy images alongside the quantifications.

Figure 4A: The syncytium at the wound edge here doesn't look straight but wavy. Does it not form an actomyosin cable that straightens the front? Or are there lamellipodia/filopodia?

248: The authors suggest an interesting hypothesis that mitochondria or ER could be pooled in fused cells. It would be nice to see some evidence: e.g. by labeling mitochondria and assessing where they are in syncytia versus mononucleated cells and whether they are concentrated around the wound edge.

141-145 (Figure 4B and C) This example is not completely convincing. First, it is hard to see where the wound edge is. Second, it would be good to include an even later time point when the cell is clearly no longer at the wound edge.

Reviewer #2 (Public Review):

The authors investigated the role of inflammatory molecules in diastolic dysfunction and screened antiviral and cardioprotective pharmacological agents for their potential to reverse inflammation-mediated diastolic dysfunction. This study focuses on heart failure with preserved ejection fraction (HFpEF) in people living with HIV (PLWH), a condition often challenging to study due to the lack of suitable animal models. Using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), researchers simulated HFpEF in vitro. They observed that inflammatory cytokines impaired cardiomyocyte relaxation, mimicking HFpEF, while SGLT2 inhibitors and mitochondrial antioxidants reversed this effect. Exposure to serum from HIV patients did not induce dysfunction in hiPSC-CMs. These findings suggest hiPSC-CMs as a promising model for understanding HFpEF mechanisms and testing potential treatments.

Comments to improve the study:

The manuscript is well-written, and the results are well-illustrated. However, there are some topics that are not well-connected, and the rationale and hypothesis are not clearly defined beforehand, such as mitochondrial membrane potential, mitochondrial ROS, and angiogenic potential.

As the hiPSC cardiomyocytes are treated with various reagents to measure diastolic dysfunction, it is important to confirm whether the treatment time and dose used were sufficient to exert a functional effect. Dose and time-dependent experiments are essential, or at least sufficient citations should be provided for selecting the dose for IFN and TNF.

After IFN and TNF treatment, determining the expression levels of molecular markers of DD/HFpEF is crucial. Again, if sufficient evidence is available, it can be cited.

The Methods section describes TMRE colocalization and immunofluorescence, but no images are provided.

The concentration of TNF and IFN in patients is critical, which was acknowledged and discussed as a limitation of the study by the authors. Authors should consider this aspect, and if not feasible, clinical reports should be cited to provide a rough estimation of their concentration.

Reviewer #2 (Public Review):

Summary:

Sterols, including desmosterol and cholesterol, play critical roles in male fertility including membrane rearrangements associated with sperm capacitation, steroidogenesis, and germ cell development. Relovska, Sona, et al. investigated the effects of global overexpression of classic cholesterol biosynthesis enzyme DHCR24 in a mouse model, focusing on the impacts on sperm function and male fertility. While mice were viable and did not exhibit altered plasma cholesterol levels or obesity, the authors demonstrated that concentrations of relevant sterols in sperm from transgenic mice were altered compared to WT mouse sperm, including the expected depletion of desmosterol. The transgenic males exhibited several indicators of reduced sperm function and fertility. Mitochondrial dysfunction was indicated by a noted depletion of localization in the distal middle-piece of up to approximately 20-25% of transgenic sperm flagella, and alterations in mitochondrial membrane potential and oxygen consumption rates in transgenic sperm were noted.

Strengths:

The authors demonstrate that DHCR24 overexpression was achieved and that sperm sterol levels are altered. The conclusions that global DHCR24 overexpression impacts mitochondrial localization and male fertility parameters are supported by the number of different supporting assessments utilized to reach these conclusions and this is a strength. Overall, the authors achieve their aim of demonstrating DHCR24 overexpression impacts on indicators of sperm function and fertility including reduced sperm counts and sperm motility, reduced fertility in mating trials with aged males, and reduced IVF success when sperm were capacitated in conditions of higher sperm concentrations in vitro. The authors further investigate sperm mitochondrial localization and function. While a mitochondrial sheath can form in sperm from transgenic mice, 25% of the sperm exhibit a shortened mitochondrial sheath where a distal portion of the middle piece of the sperm flagella lacks mitochondria and instead exhibits exposed outer dense fibers.

Weaknesses:

In the current study, the authors conclude that desmosterol may not act as an LXR activator in testicular cells based on assessment of relevant mRNA levels in whole testis that indicated the relevant transcripts were not altered in transgenic testes. However, caution should be taken in utilizing whole testis transcriptomics to rule out a role in specific cell populations within the testis with minor relative representation, such as macrophages or undifferentiated spermatogonia. This is an important distinction for a few reasons. The authors reveal through single-cell assessments of DHCR24 expression in WT testis that it is most highly expressed in undifferentiated spermatogonia. Further, the authors previously reported that DHCR24 over-expression in myeloid/macrophage populations did impact LXR activation impacting atherosclerosis. Taken together with emerging evidence that testis macrophages may impact spermatogonial fate decisions, the potential for DHCR24 to impact these minor testicular cell populations should not yet be ruled out. The significance of individual observations needs to be clarified through improved reporting of methodologies, specific biological and technical replicates, and statistical significance for each individual assessment. The lack of these details obfuscates the ability of the reader to interpret or replicate several reported observations which is a weakness.

(1) The fertility trials indicate a reduced number of pups/litter in aged but not younger transgenic males. However, the data for the aged males includes three data points of 0 pups, which brings to question if the data points each represent the average pups/litter for individual males or individual litters with multiple litters separately included for fertile males. Clarification could help in interpreting whether litter sizes were reduced, or if litter frequency and/or fertility of individual males was reduced. In the latter case, behavioral infertility would not be excluded from consideration.

(2) The statistical significance is not clear for altered acrosome reaction data, hyperactivated motility data, waveform analysis, mitochondrial membrane potential, and some of the sperm morphology assessments. In many assessments, the biological and technical replicates assessed need to be clarified.

(3) Methods utilized for image assessment of waveform analysis and mitochondrial membrane potential are lacking detail sufficient for replication of the assessments or for reader interpretation of how conclusions were reached.

Summary of impact:

Overall, the novel observations in this study are consistent with a role for controlled sterol concentrations being important for male fertility and indicate that this model will be useful to further investigate sterol biosynthesis contributions to testis function including steroidogenesis, spermatogenesis, and sperm function including capacitation.

Reviewer #2 (Public Review):

Summary:

This manuscript uses cell lines representative of germ line cells, somatic cells, and pluripotent cells to address the question of how the endocrine-disrupting compound BPS affects these various cells with respect to gene expression and DNA methylation. They find a relationship between the presence of estrogen receptor gene expression and the number of DNA methylation and gene expression changes. Notably, PGCLCs do not express estrogen receptors and although they do have fewer changes, changes are nevertheless detected, suggesting a nonconical pathway for BPS-induced perturbations. Additionally, there was a significant increase in the occurrence of BPS-induced epimutations near EREs in somatic and pluripotent cell types compared to germ cells. Epimutations in the somatic and pluripotent cell types were predominantly in enhancer regions whereas that in the germ cell type was predominantly in gene promoters.

Strengths:

The strengths of the paper include the use of various cell types to address the sensitivity of the lineages to BPS as well as the observed relationship between the presence of estrogen receptors and changes in gene expression and DNA methylation.

Weaknesses:

The weaknesses include the lack of reporting of replicates, superficial bioinformatic analysis, and the fact that exposures are more complicated in a whole organism than in an isolated cell line.

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors conducted a comprehensive study of the X-linked miR-506 family miRNAs in mice on its origin, evolution, expression, and function. They demonstrate that the X-linked miR-506 family, predominantly expressed in the testis, may be derived from MER91C DNA transposons and further expanded by retrotransposition. By genetic deletion of different combinations of 5 major clusters of this miRNA family in mice, they found these miRNAs are not required for spermatogenesis. However, by further examination, the mutant mice show mild fertility problem and inferior sperm competitiveness. The authors conclude that the X-linked miR-506 miRNAs finetune spermatogenesis to enhance sperm competition.

Strengths:

This is a comprehensive study with extensive computational and genetic dissection of the X-linked miR-506 family providing a holistic view of its evolution and function in mice. The finding that this family miRNAs could enhance sperm competition is interesting and could explain their roles in finetuning germ cell gene expression to regulate reproductive fitness.

Comments on revised version:

The authors have addressed the concerns raised.

Reviewer #2 (Public Review):

How organism physiological state modulates establishment and perdurance of memories is a timely question that the authors aimed at addressing by studying the interplay between energy homeostasis and food-related conditioning in Drosophila. Specifically, they studied how starvation modulates the establishment of short-term vs long-term memories and clarified the role of the monoamine Octopamine in food-related conditioning, showing that it is not per se involved in formation of appetitive short-term memories but rather gates memory formation by suppressing LTM when energy levels are high. This work clarifies previously described phenotypes and provides insight about interconnections between energy levels, feeding and formation of short-term and long-term food-related memories.

Strengths<br /> - Previous studies have documented the impact of Octopamine on different aspects of food-related behaviors (regulation of energy homeostasis, feeding, sugar sensing, appetitive memory...), but we currently lack a clear understanding of how these different functions are interconnected. The authors have used a variety of experimental approaches to systematically test the impact of internal energy levels in establishment of different forms of appetitive memory and the role of Octopamine in this process.

- The authors have used a range of approaches, performed carefully controlled experiments and produced high quality data.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Mahapatra and Takahashi report on the physiological consequences of pharmacologically blocking either clathrin and dynamin function during compensatory endocytosis or of the cortical actin scaffold both in the calyx of Held synapse and hippocampal boutons in acute slice preparations

Strengths:

Although many aspects of these pharmacological interventions have been studied in detail during the past decades, this is a nice comprehensive and comparative study, which reveals some interesting differences between a fast synapse (Calyx of Held) tuned to reliably transmit at several 100 Hz and a more slow hippocampal CA1 synapse. In particular the authors find that acute disturbance of the synaptic actin network leads to a marked frequency-dependent enhancement of synaptic depression in the Calyx, but not in the hippocampal synapse This striking difference between both preparations is the most interesting and novel finding.

Weaknesses:

Unfortunately, however, these findings concerning the different consequences of actin depolymerization are not sufficiently discussed in comparison to the literature. My only criticism concerns the interpretation of the ML 141 and Lat B data. With respect to the Calyx data, I am missing a detailed discussion of the effects observed here in light of the different RRP subpools SRP and FRP. This is very important since Lee at al. (2012, PNAS 109 (13) E765-E774) showed earlier that disruption of actin inhibits the rapid transition of SRP SVs to the FRP at the AZ. The whole literature on this important concept is missing. Likewise, the role of actin for the replacement pool at a cerebellar synapse (Miki et al., 2016) is only mentioned in half a sentence. There is quite some evidence that actin is important both at the AZ (SRP to FRP transition, activation of replacement pool) and at the peri-active zone for compensatory endocytosis and release site clearance. Both possible underlying mechanisms (SRP to FRP transition or release site clearance) should be better dissected.

Reviewer #3 (Public Review):

Summary:

This study implements an innovative neurofeedback procedure in rats, providing food reward upon detection of a sharp wave-ripple event (SWR) in the hippocampus. The elegant experimental design enables a within-animal comparison of the effects of this neurofeedback procedure as compared to a control condition in which equivalent reward is provided in a non-contingent manner. The neurofeedback procedure was found to increase SWR rate, followed by a compensatory reduction in SWR rate. These changes in SWR rate were not accompanied by any changes in memory performance on the memory-guided task.

Strengths:

The scientific premise for the study is outstanding. It addresses an issue of high importance, of developing ways to not merely describe correlations between SWRs (and their content) and memory performance, but to manipulate them. The authors argue clearly and convincingly that even studies that have performed causal manipulations of SWRs have important confounds and limitations, and most importantly for translational purposes, they are all invasive. So, the idea of developing a potentially non-invasive neurofeedback procedure for modulating SWRs is compelling both as an innovative new experimental manipulation in studies of SWRs, and as a potentially impactful therapeutic avenue.

In addition to addressing an important issue with an innovative approach, the study has many other strengths. The data unambiguously show that the method is effective at increasing SWR rate in each individual subject. The experimental design allows within-subject comparison of neurofeedback and control trials, where the subjects wait an equivalent amount of time. The careful analyses of SWR properties and their content establish that neurofeedback SWRs are comparable to control SWRs. The data add further evidence to the notion that SWR rate is subject to homeostatic control. The paper is also exceptionally well written, and was a pleasure to read. So, there is a clear technical advance, in that there is now a method for increasing SWR rate non-invasively, which is rigorously established and characterized.

Weaknesses:

The one overall limitation I find with this study is that it is unclear to what extent the same (or better) results could have been obtained using behavior-feedback instead of neuro-feedback. Because SWR rates are generally higher during states of quiescence compared to active movement or task engagement, it is possible that reinforcing behaviorally detected quiescent states (e.g. low movement) would indirectly increase SWR rates. The authors include an important control analysis showing higher SWR rates in the neurofeedback condition even when movement speed is controlled for by subsetting the data, demonstrating that changes in movement speed cannot be the only explanation of the results. At the same time, the observation that all 4 subjects had lower movement speeds during neurofeedback compared to control trials suggests that neurofeedback is likely reinforcing both overt (behavior) and covert (SWR) processes. Understanding the relative contributions of each to the observed SWR increase would help clarify whether the neurofeedback approach is worth the additional effort and expense compared to behavioral feedback.

Reviewer #2 (Public Review):

This MEG study used co-registered eye-tracking and Rapid Invisible Frequency Tagging (RIFT) to track the effects of semantic parafoveal preview during natural sentence reading. Unpredictable target words could either be congruent or incongruent with sentence context. This modulated the RIFT response already while participants were fixating the preceding word. This indicates that the semantic congruency of the upcoming word modulates visual attention demands already in parfoveal preview.<br /> The quest for semantic parafoveal preview in natural reading has attracted a lot of attention in recent years, especially with the development of co-registered eye-tracking and EEG/MEG. Evidence from dynamic neuroimaging methods using innovative paradigms as in this study is important for this debate.

Major points:

(1) The authors frame their study in terms of "congruency with sentence context". However, it is the congruency between adjective-noun pairs that determines congruency (e.g. "blue brother" vs "blue jacket", and examples p. 16 and appendix). This is confirmed by Suppl Figure 1, which shows a significantly larger likelihood of refixations to the pre-target word for incongruent sentences, probably because the pre-target word is most diagnostic for the congruency of the target word. The authors discuss some possibilities why there is variability in parafoveal preview effects in the literature. It is more likely to see effects for this simple and local congruency, rather than congruency that requires and integration and comprehension of the full sentence. Future studies should investigate whether the observed effects depend on sentence context or local congruency.

(2) The authors used MEG and provided a source estimate for the tagging response (Figure 2), which unsurprisingly is in visual cortex. The most important results are presented at the sensor level. This does not add information about the brain sources of the congruency affect, as the RIFT response probably reflects top-down effects on visual attention etc. The RIFT response can test for preview effects on visual brain responses but does not allow the localisation of context processing effects that cause them.

(3) The earliest semantic preview effects occurred around 100ms after fixating the pre-target word (discussed around l. 323). This means that at this stage the brain must have processed the pre-target and the target word and integrated their meanings (at some level). Even in the single-word literature, semantic effects at 100 ms are provocatively early. Future studies should aim at reconciling these different findings.

(4) As in previous EEG/MEG studies, the authors found a neural but no behavioural preview effect. As before, this raises the question whether the observed effect is really "critical" for sentence comprehension. If interpreted in terms of "information" and "attention", then one would expect a positive effect on behaviour, either reading speed or accuracy. The authors provide a correlation analysis with reading speed, but this does not allow causal conclusions: Some people may simply read slowly and therefore pay more attention and get a larger preview response. Some readers may hurry and therefore not pay attention and not get a preview response. In order to address this, one would have to control for reading speed and show an effect of RIFT response on comprehension performance (or vice versa, with a task that is not close to ceiling performance).

Reviewer #3 (Public Review):

Summary:

Here the authors show global synchronization of cerebral blood flow (CBF) induced by oscillating visual stimuli in the mouse brain. The study validates the use of endogenous autofluorescence to quantify the vessel "shadow" to assess the magnitude of frequency-locked cerebral blood flow changes. This approach enables straightforward estimation of artery diameter fluctuations in wild-type mice, employing either low magnification wide-field microscopy or deep-brain fibre photometry. For the visual stimuli, awake mice were exposed to vertically oscillating stripes at a low temporal frequency (0.25 Hz), resulting in oscillatory changes in artery diameter synchronized to the visual stimulation frequency. This phenomenon occurred not only in the primary visual cortex but also across a broad cortical and cerebellar surface. The induced CBF changes adapted to various stimulation parameters, and interestingly, repeated trials led to plastic entrainment. The authors control for different artefacts that may have confounded the measurements such as light contamination and eye movements but found no influence of these variables. The study also tested horizontally oscillating visual stimuli, which induce the horizontal optokinetic response (HOKR). The amplitude of eye movement, known to increase with repeated training sessions, showed a strong correlation with CBF entrainment magnitude in the cerebellar flocculus. The authors suggest that parallel plasticity in CBF and neuronal circuits is occurring. Overall, the study proposes that entrained "vasomotion" contributes to meeting the increased energy demand associated with coordinated neuronal activity and subsequent neuronal circuit reorganization.

Strengths:

-The paper describes a simple and useful method for tracking vasomotion in awake mice through an intact skull.<br /> -The work controls for artefacts in their primary measurements.<br /> -There are some interesting observations, including the nearly brain-wide synchronization of cerebral blood flow oscillations to visual stimuli and that this process only occurs after mice are trained in a visual task.<br /> -This topic is interesting to many in the CBF, functional imaging, and dementia fields.

Reviewer #2 (Public Review):

Summary:

This is a paper about the segmentation of visual stimuli based on speed cues. The experimental stimuli are random dot fields in which each dot moves at one of two velocities. By varying the difference between the two speeds, as well as the mean of the two speeds, the authors estimate the capacity of observers (human and non-human primates) to segment overlapping motion stimuli. Consistent with previous work, perceptual segmentation ability depends on the mean of the two speeds. Recordings from area MT in monkeys show that the neuronal population to compound stimuli often shows a bias towards the faster-speed stimuli. This bias can be accounted for with a computational model that modulates single-neuron firing rates by the speed preferences of the population. The authors also test the capacity of a linear classifier to produce the psychophysical results from the MT data.

Strengths:

Overall, this is a thorough treatment of the question of visual segmentation with speed cues. Previous work has mostly focused on other kinds of cues (direction, disparity, color), so the neurophysiological results are novel. The connection between MT activity and perceptual segmentation is potentially interesting, particularly as it relates to existing hypotheses about population coding.

Weaknesses:

Page 10: The relationship between (R-Rs) and (Rf-Rs) is described as "remarkably linear". I don't actually find this surprising, as the same term (Rs) appears on both the x- and y-axes. The R^2 values are a bit misleading for this reason.

Figure 9: I'm confused about the linear classifier section of the paper. The idea makes sense - the goal is to relate the neuronal recordings to the psychophysical data. However the results generally provide a poor quantitative match to the psychophysical data. There is mention of a "different paper" (page 26) involving a separate decoding study, as well as a preprint by Huang et al. (2023) that has better decoding results. But the Huang et al. preprint appears to be identical to the current manuscript, in that neither has a Figure 12, 13, or 14. The text also says (page 26) that the current paper is not really a decoding study, but the linear classifier (Figure 9F) is a decoder, as noted on page 10. It sounds like something got mixed up in the production of two or more papers from the same dataset. In any case, I think that some kind of decoding analysis would really strengthen the current paper by linking the physiology to the psychophysics, but given the limitations of the linear classifier, a more sophisticated approach might be necessary -- see for example Zemel, Dayan, and Pouget, 1998. The authors might also want to check out closely related work by Treue et al. (Nature Neuroscience 2000) and Watamaniuk and Duchon (1992).

What do we learn from the normalization model? Its formulation is mostly a restatement of the results - that the faster and slower speeds differentially affect the combined response. This hypothesis is stated quantitatively in equation 8, which seems to provide a perfectly adequate account of the data. The normalization model in equation 10 is effectively the same hypothesis, with the mean population response interposed - it's not clear how much the actual tuning curve in Figure 10A even matters, since the main effect of the model is to flatten it out by averaging the functions in Figure 10B. Although the fit to the data is reasonable, the model uses 4 parameters to fit 5 data points and is likely underconstrained; the parameters other than alpha should at least be reported, as it would seem that sigma is actually the most important one. And I think it would help to examine how robust the statistical results are to different assumptions about the normalization pool.

Reviewer #2 (Public Review):

Summary:

The study investigates the representation of irrelevant stimuli in neural circuits using neural recordings from the primate prefrontal cortex during a passive object association task. They find a significant decrease in the linear decodability of irrelevant stimuli over the course of learning (in the time window in which the stimuli are irrelevant). They then compare these trends to RNNs trained with varying levels of noise and firing rate regularization and find agreement when these levels are at an intermediate value. In a complementary analysis, they found (in both RNNs and PFC) that the magnitude of relevant and irrelevant stimuli increased and decreased, respectively, during learning. These findings were interpreted in terms of a minimization of metabolic cost in the cortex.

To understand how stimuli can be dynamically suppressed at times when they are irrelevant, the authors constructed and analyzed a reduced two-neuron model of the task. They found a mechanism in which firing rate regularization increased the probability of negative weights in the input, pushing the neural activities below the threshold. A similar mechanism was observed in RNNs.

Strengths:

The article is well-written and the figures are easily understood. The analyses are well explained and motivated. The article provides a valuable analysis of the effect of two parameters on representations of irrelevant stimuli in trained RNNs.

Weaknesses:

(1) The mechanism for suppressing dynamically relevant stimuli appears to be incomplete and does not explain clearly enough how representations of 'color' which are suppressed through negative input weights become un-suppressed in the presence of the second variable 'shape'.

(2) Interpretation of results in terms of the effect of metabolic cost on cortical dynamics is not backed up by the presented data/analyses. The change in dynamics of 'color' representations in the prefrontal cortex only qualitatively matches RNN dynamics and may arise from other causes.

Reviewer #2 (Public Review):

Summary:

The manuscript by Hike et al. entitled 'High-resolution awake mouse fMRI at 14 Tesla' describes the implementation of awake mouse BOLD-fMRI at high field. This work is timely as the field of mouse fMRI is working toward collecting high-quality data from awake animals. Imaging awake subjects offers opportunities to study brain function that are otherwise not possible under the more common anesthetized conditions. Not to mention the confounding effects that anesthesia has on neurovascular coupling. What has made progress in this area slow (relative to other imaging approaches like optical imaging) is the environment within the MRI scanner (high acoustic noise) - as well as the intolerance of head and body motion. This work adds to a relatively small, but quickly growing literature on awake mouse fMRI. The findings in the study include testing of an implanted head-coil (for MRI data reception). Two designs are described and the SNR of these units at 9.4T and 14T are reported. Further, responses to visual as well as whisker stimulation recorded in acclimated awake mice are shown. The most interesting finding, and most novel, is the observation that mice seem to learn to anticipate the presentation of the stimulus - as demonstrated by activations evident ~6 seconds prior to the presentation of the stimulus when stimuli are delivered at regular intervals (but not when stimuli are presented at random intervals). These kinds of studies are very challenging to do. The surgical preparation and length of time invested into training animals are grueling. I also see this work as a step in the right direction and evidence of the foundations for lots of interesting future work. However, I also found a few shortcomings listed below.

Weaknesses:

(1) The surface coil, although offering a great SNR boost at the surface, ultimately comes at a cost of lower SNR in deeper more removed brain regions in comparison to commercially available Bruker coils (at room temperature). This should be quantified. A rough comparison in SNR is drawn between the implanted coils and the Bruker Cryoprobe - this should be a quantitative comparison (if possible) - including any differences in SNR in deeper brain structures. There are drawbacks to the Cryoprobe, which can be discussed, but a more thorough comparison between the implanted coils, and other existing options should be provided (the Cryoprobe has been used previously in awake mouse experiments). Further, the details of how to build the implanted coils should be provided (shared) - this should include a parts list as well as detailed instructions on how to build the units. Also, how expensive are they? And can they be reused?

(2) In the introduction, the authors state that "Awake mouse fMRI has been well investigated". I disagree with this statement and others in the manuscript that give the reader the impression that awake experiments are not a challenging and unresolved approach to fMRI experiments in mice (or rodents). Although there are multiple labs (maybe 15 worldwide) that have conducted awake mouse experiments (with varying degrees of success/thoroughness), we are far from a standardized approach. This is a strength of the current work and should be highlighted as such. I encourage the authors to read the recent systematic review that was published on this topic in Cerebral Cortex by Mandino et al. There are several elements in there that should influence the tone of this piece including awake mouse implementations with the Bruker Cryoprobe, prevalence of surgical preparations, and evaluations of stress.

(3) The authors also comment on implanted coils reducing animal stress - I don't know where this comment is coming from, as this has not been reported in the literature (to my knowledge) and the authors don't appear to have evaluated stress in their mice.

(4) Following on the above point, measures of motion, stress, and more details on the acclimation procedure that was implemented in this study should be included.

(5) It wasn't clear to me at what times the loop versus "Figure 8" coil was being used, nor how many mice (or how much data) were included in each experiment/plot. There is also no mention of biological sex.

(6) Building on the points above, the manuscript overall lacks experimental detail (especially since the format has the results prior to the methods).

(7) An observation is made in the manuscript that there is an appreciable amount of negative BOLD signal. The authors speculate that this may come from astrocyte-mediated BOLD during brain state changes (and cite anesthetized rat and non-human primate experiments). This is very strange to me. First, the negative BOLD signal is not plotted (please do this), further, there are studies in awake mice that measure astrocyte activation eliciting positive BOLD responses (see Takata et al. in Glia, 2017).

Reviewer #2 (Public Review):

Weng et al. perform a comprehensive study of gene expression changes in young and old animals, in wild-type and daf-2 insulin receptor mutants, in the whole animal, and specifically in the nervous system. Using this data, they identify gene families that are correlated with neuronal ageing, as well as a distinct set of genes that are upregulated in neurons of aged daf-2 mutants. This is particularly interesting as daf-2 mutants show both extended lifespans and healthier neurons in aged animals, reflected by better learning/memory in older animals compared with wild-type controls. Indeed, the knockdown of several of these upregulated genes resulted in poorer learning and memory. In addition, the authors showed that several genes upregulated during ageing in wild-type neurons also contribute to learning and memory; specifically knockdown of these genes in young animals resulted in improved memory. This indicates that (at least in this small number of cases), genes that show increased transcript levels with age in the nervous system somehow suppress memory, potentially by having damaging effects on neuronal health.

Finally, from a resource perspective, the neuronal transcriptome provided here will be very useful for C. elegans researchers as it adds to other existing datasets by providing the transcriptome of older animals (animals at day 8 of adulthood) and demonstrating the benefits of performing tissue-specific RNAseq instead of whole-animal sequencing.

The work presented here is of high quality and the authors present convincing evidence supporting their conclusions. I only have a few comments/suggestions:

(1) Do the genes identified to decrease learning/memory capacity in daf-2 animals (Figure 4d/e) also impact neuronal health? daf-2 mutant worms show delayed onset of age-related changes to neuron structure (Tank et al., 2011, J Neurosci). Does knockdown of the genes shown to affect learning also affect neuron structure during ageing, potentially one mechanism through which they modulate learning/memory?

(2) The learning and memory assay data presented in this study uses the butanone olfactory learning paradigm, which is well established by the same group. Have the authors tried other learning assays when testing for learning/memory changes after the knockdown of candidate genes? Depending on the expression pattern of these genes, they may have more or less of an effect on olfactory learning versus for example gustatory or mechanosensory-based learning.

(3) I have a comment on the 'compensatory vs dysregulatory' model as stated by the authors on page 7. I understand that this model presents the two main options, but perhaps this is slightly too simplistic: the gene expression that rises during ageing may be detrimental for memory (= dysregulatory), but at the same time may also be beneficial for other physiological roles in other tissues (=compensatory).

Reviewer #2 (Public Review):

The manuscript describes a new framework for thinking about the place and grid cell system in the hippocampus and entorhinal cortex in which these cells are fundamentally involved in supporting non-spatial information coding. If this framework were shown to be correct, it could have high impact because it would suggest a completely new way of thinking about the mammalian memory system in which this system is non-spatial. Although this idea is intriguing and thought-provoking, a very significant caveat is that the paper does not provide evidence that specifically supports its framework and rules out the alternate interpretations. Thus, although the work provides interesting new ideas, it leaves the reader with more questions than answers because it does not rule out any earlier ideas.

Basically, the strongest claim in the paper, that grid cells are inherently non-spatial, cannot be specifically evaluated versus existing frameworks on the basis of the evidence that is shown here. If, for example, the author had provided behavioral experiments showing that human memory encoding/retrieval performance shifts in relation to the predictions of the model following changes in the environment, it would have been potentially exciting because it could potentially support the author's reconceptualization of this system. But in its current form, the paper merely shows that a new type of model is capable of explaining the existing findings. There is not adequate data or results to show that the new model is a significantly better fit to the data compared to earlier models, which limits the impact of the work. In fact, there are some key data points in which the earlier models seem to better fit the data.

Overall, I would be more convinced that the findings from the paper are impactful if the author showed specific animal memory behavioral results that were only supported by their memory model but not by a purely spatial model. Perhaps the author could run new experiments to show that there are specific patterns of human or animal behavior that are only explained by their memory model and not by earlier models. But in its current form, I cannot rule out the existing frameworks and I believe some of the claims in this regard are overstated.

In addition to the broader concerns noted above regarding the absence of any specific behavioral data that are explained by their model and not by existing spatial models, I am additionally concerned that this manuscript does not explain a number of important key empirical results in the rodent grid cell literature.

* The paper does not fully take into account all the findings regarding grid cells, some of which very clearly show spatial processing in this system. For example, findings on grid-by-direction cells (e.g., Sargolini et al. 2006) would seem to suggest that the entorhinal grid system is very specifically spatial and related to path integration. Why would grid-by-direction cells be present and intertwined with grid cells in the author's memory-related reconceptualization? It seems to me that the existence of grid-by-direction cells is strong evidence that at least part of this network is specifically spatial.

* I am also concerned that the paper does not do enough to address findings regarding how the elliptical shape of grid fields shifts when boundaries of an environment compress in one direction or change shape/angles (Lever et al., & Krupic et al). Those studies show compression in grid fields based on boundary position, and I don't see how the authors' model would explain these findings.

* Are findings regarding speed modulation of grid cells problematic for the paper's memory results?

* A further issue is that the paper does not seem to adequately address developmental findings related to the timecourses of the emergence of different cell types. In their simulation, researchers demonstrate the immediate emergence of grid fields in a novel environment, while noting that the stabilization of place cell positions takes time. However, these simulation findings contradict previous empirical developmental studies (Langston et al., 2010). Those studies showed that head direction cells show the earliest development of spatial response, followed by the appearance of place cells at a similar developmental stage. In contrast, grid cells emerge later in this developmental sequence. The gradual improvement in spatial stability in firing patterns likely plays a crucial role in the developmental trajectory of grid cells. Contrary to the model simulation, grid cells emerge later than place cells and head direction cells, yet they also hold significance in spatial mapping.

* The model simulations suggest that certain grid patterns are acquired more gradually than others. For instance, egocentric grid cells require the stabilization of place cell memories amidst ongoing consolidation, while allocentric grid cells tend to reflect average place field positions. However, these findings seemingly conflict with empirical studies, particularly those on the conjunctive representation of distance and direction in the earliest grid cells. Previous studies show no significant differences were found in grid cells and grid cells with directional correlates across these age groups, relative to adults (Wills et al., 2012). This indicates that the combined representation of distance and direction in single mEC cells is present from the earliest ages at which grid cells emerge.

Reviewer #2 (Public Review):

Summary:

This valuable study investigates how statistical learning may facilitate a target detection task and whether the facilitation effect is related to statistical learning of word boundaries. Solid evidence is provided that target detection and word segmentation rely on different statistical learning mechanisms.

Strengths:

The study is well designed, using the contrast between the learning of words of uniform length and words of variable length to dissociate general statistical learning effects and effects related to word segmentation.

Weaknesses:

The study relies on the contrast between word length effects on target detection and word learning. However, the study only tested the target detection condition and did not attempt to replicate the word segmentation effect. It is true that the word segmentation effect has been replicated before but it is still worth reviewing the effect size of previous studies.

The paper seems to distinguish prediction, anticipation, and statistical learning, but it is not entirely clear what each term refers to.

Reviewer #2 (Public Review):

Summary:

The authors present a comprehensive technical overview of the challenging acquisition of large-scale cortical activity, including surgical procedures and custom 3D-printed headbar designs to obtain neural activity from large parts of the dorsal or lateral neocortex. They then describe technical adjustments for stable head fixation, light shielding, and noise insulation in a 2-photon mesoscope and provide a workflow for multisensory mapping and alignment of the obtained large-scale neural data sets in the Allen CCF framework. Lastly, they show different analytical approaches to relate single-cell activity from various cortical areas to spontaneous activity by using visualization and clustering tools, such as Rastermap, PCA-based cell sorting, and B-SOID behavioral motif detection.

The study contains a lot of useful technical information that should be of interest to the field. It tackles a timely problem that an increasing number of labs will be facing as recent technical advances allow the activity measurement of an increasing number of neurons across multiple areas in awake mice. Since the acquisition of cortical data with a large field of view in awake animals poses unique experimental challenges, the provided information could be very helpful to promote standard workflows for data acquisition and analysis and push the field forward.

Strengths:

The proposed methodology is technically sound and the authors provide convincing data to suggest that they successfully solved various challenging problems, such as motion artifacts of large imaging preparations or high-frequency noise emissions, during 2-photon imaging. Overall, the authors achieved their goal of demonstrating a comprehensive approach for imaging neural data across many cortical areas and providing several examples that demonstrate the validity of their methods and recapitulate and further extend some recent findings in the field. A particular focus of the results is to emphasize the need for imaging large population activity across cortical areas to identify cross-area information processing during active behaviors.

Weaknesses:

The manuscript contains a lot of technical details and might be challenging for readers without previous experimental experience. However, the different paragraphs illuminate a large range of technical aspects and challenges of large-scale functional imaging. Therefore, the work should be a valuable source of solutions for a diverse audience.

Reviewer #2 (Public Review):

Summary:

The aim of this paper was to elucidate the role of the dorsal HP and intermediate HP (dHP and iHP) in value-based spatial navigation through behavioral and pharmacological experiments using a newly developed VR apparatus. The authors inactivated dHP and iHP by muscimol injection and analyzed the differences in behavior. The results showed that dHP was important for spatial navigation, while iHP was critical for both value judgments and spatial navigation. The present study developed a new sophisticated behavioral experimental apparatus and proposed a behavioral paradigm that is useful for studying value-dependent spatial navigation. In addition, the present study provides important results that support previous findings of differential function along the dorsoventral axis of the hippocampus.

Strengths:

The authors developed a VR-based value-based spatial navigation task that allowed separate evaluation of "high-value target selection" and "spatial navigation to the target." They were also able to quantify behavioral parameters, allowing detailed analysis of the rats' behavioral patterns before and after learning or pharmacological inactivation.

Weaknesses:

Although differences in function along the dorsoventral axis of the hippocampus is an important topic that has received considerable attention, differences in value coding have been shown in previous studies, including the work of the authors; the present paper is an important study that supports previous studies, but the novelty of the findings is not that high, as the results are from pharmacological and behavioral experiments only.

Reviewer #2 (Public Review):

Summary:

Developing a mechanical model of C. elegans is difficult to do from basic principles because it moves at low (but not very small) Reynolds number, is itself visco-elastic, and often is measured moving at a solid/liquid interface. The ElegansBot is a good first step at a kinetic model that reproduces a wide range of C. elegans motility behavior.

Strengths:

The model is general due to its simplicity and likely useful for various undulatory movements. The model reproduces experimental movement data using realistic physical parameters (e.g. drags, forces, etc). The model is predictive (semi?) as shown in the liquid to solid gait transition. The model is straightforward in implementation and so likely is adaptable to modification and addition of control circuits.

Comments on revised version:

This is a revised manuscript. I'm happy with the changes made, including the specific responses to my previous concerns.

Reviewer #3 (Public Review):

Laham et al. present a manuscript investigating the function of adult-born granule cells (abGCs) projecting to the CA2 region of the hippocampus during social memory. It should be noted that no function for the general DG to CA2 projection has been proposed yet. The authors use targeted ablation, chemogenetic silencing and in vivo ephys to demonstrate that the abGCs to CA2 projection is necessary for the retrieval of a remote social memories such as the memory of one's mother. They also use in vivo ephys to show that abGCs are necessary for differential CA2 network activity, including theta-gamma coupling and sharp wave-ripples, in response to novel versus familiar social stimuli.

The question investigated is important since the function of DG to CA2 projection remained elusive a decade after its discovery. Overall, the results are interesting but focused to the social memory of the mother and their description in the manuscript and figures is too cursory. For example, raw interaction times must be shown before their difference. The assumption that mice exhibit social preference between familiar or novel individuals such as mother and non-mother based on social memory formation, consolidation and retrieval should be better explained throughout the manuscript. Thus, when describing the results, the authors should comment on changes in preference and how this can be interpreted as a change in social memory retrieval. Several critical experimental details such as the total time of presentation to the mother and non-mother stimulus mice are also lacking from the manuscript. The in vivo e-phys results are interesting as well but even more succinct with no proposed mechanism as to how abGCs could regulate SWR and PAC in CA2.

The manuscript is well-written with the appropriate references. The choice of behavioral test is somewhat debatable however. It is surprising the authors chose to use a direct presentation test (presentation of the mother and non-mother in alternance) instead of the classical 3-chamber test which is particularly appropriate to investigate social preference. Since the authors focused exclusively on this preference, the 3-chamber test would have been more adequate in my opinion. It would greatly strengthened the results if the authors could repeat a key experiment from their investigation using such test. In addition, the authors only impaired the mother's memory. An additional experiment showing that disruption of the abGCs to CA2 circuit impairs social memory retrieval in general would allow to generalize the findings to social memories in general. As the manuscript stands, the authors can only conclude as to the importance of this circuit for the memory of the mother. Developmental memory implies the memory of familiar kin as well.

The in vivo ephys section (Figure 3) is interesting but even more minimalistic and it is unclear how abGCs projection to CA2 can contribute to SWR and theta-gamma PAC. In figure 1, the authors suggest that abGCs project preferentially to PV+ neurons in CA2. At minima, the authors should discuss how the abGCs to PV+ neurons to CA2 pyramidal neurons circuit can facilitate SWR and theta-gamma PAC.

Finally, proposing a function for 4-6-week-old abGCs projecting to CA2 begs two questions: What are abGCs doing once they mature further and more generally, what is the function of the DG to CA2 projection? It would be interesting for the authors to comment on these questions in the discussion.

Revision:

The authors have followed my recommendations except for the ones suggesting new experiments. As a result, the clarity of the manuscript and the links between evidence and claims have improved by the message is quite reduced. Many important questions remain open such as: What makes mother's memories so special they require the abGC projection to CA2 unlike other types of social memories? Do abGCs truly connect CA2 PV+ interneurons and how does this connection shape sharp-wave ripples in CA2?

Reviewer #2 (Public Review):

Summary:

Methods to infer action potentials from fluorescence-based measurements of intracellular calcium dynamics are important for optical measurements of activity across large populations of neurons. The variety of existing methods can be separated into two broad classes: a) model-independent approaches that are trained on ground truth datasets (e.g., deep networks), and b) approaches based on a model of the processes that link action potentials to calcium signals. Models usually contain parameters describing biophysical variables, such as rate constants of the calcium dynamics and features of the calcium indicator. The method presented here, PGBAR, is model-based and uses a Bayesian approach. A novelty of PGBAR is that static parameters and state variables are jointly estimated using particle Gibbs sampling, a sequential Monte Carlo technique that can efficiently sample the latent embedding space.

Strengths:

A main strength of PGBAR is that it provides probability distributions rather than point estimates of spike times. This is different from most other methods and may be an important feature in cases when estimates of uncertainty are desired. Another important feature of PGBAR is that it estimates not only the state variable representing spiking activity but also other variables such as baseline fluctuations and stationary model variables, in a joint process. PGBAR can therefore provide more information than various other methods. The information in the GitHub repository is well-organized.

Weaknesses:

On the other hand, the accuracy of spike train reconstructions is not higher than that of other model-based approaches, and clearly lower than the accuracy of a model-independent approach based on a deep network. The authors demonstrate convincingly that PGBAR can resolve inter-spike intervals in the range of 5 ms using fluorescence data obtained with a very fast genetically encoded calcium indicator at very high sampling rates (line scans at >= 1 kHz). It would be interesting to more systematically compare the performance of PGBAR to other methods in this regime of high temporal resolution, which has not been explored much.

Reviewer #2 (Public Review):

Summary:

The authors have diligently addressed most of the points raised during the review process (except the important point of "additional in vitro experiments [...] needed to investigate the implication of circHIPK3 in bladder cancer cell phenotype" for which no additional experiments were performed), resulting in an improvement in the study. The data are now described with clarity and conciseness, enhancing the overall quality of the manuscript.

Strengths:

New, well-defined molecular mechanism of circRNAs involvement in bladder cancer.

Weaknesses:

Lack of solid translational significance data.

Reviewer #2 (Public Review):

The manuscript has been revised according to Reviewer's suggestions. Recommendations for the Authors have been almost entirely followed. However, there are some points where the authors state that they have made changes, but the text does not show this. The revised version would have gained in clarity if it was with track changes and numbered rows. In particular, I cannot see the following changes:

Lines 104-105: Did you mean: "We confirmed that optogenetic stimulation of PiCo neurons in ChATcre:Vglut2FlpO:ChR2 mice exposed to CIH triggers swallow and laryngeal activation similar to the control mice exposed to room air (Huff et al., 2023)." Otherwise, the sentence is not clear.<br /> Thank you, this has been changed

Lines 228-232: "PiCo-triggered swallows are characterized by a significant decrease in duration compared to swallows evoked by water in ChATcre:Ai32 mice (265 {plus minus} 132ms vs 144 {plus minus} 101ms; paired t-test: p= 0.0001, t= 5.21, df= 8), Vglut2cre:Ai32 mice (308 {plus minus} 184ms vs 125 {plus minus} 44ms; paired t-test: p= 0.0003, t= 6.46, df= 7), and ChATcre:Vglut2FlpO:ChR2 mice (230 {plus minus} 67ms vs 130 {plus minus} 35ms; paired t-test: p= 0.0005, t= 5.62, df= 8) exposed to CIH (Table S1).".<br /> Thank you, this has been changed

Lines 283-290: "Thus, CIH does not alter PiCo's ability to coordinate the timing for swallowing and breathing. Rather, our data reveals that CIH disrupts the swallow motor sequence likely due to changes in the interaction between PiCo and the SPG, presumably the cNTS.

While it has previously been demonstrated that PiCo is an important region in swallow-breathing coordination (Huff et al., 2023), previous studies did not demonstrate that PiCo is involved in swallow pattern generation itself. Thus, here we show for the first time that CIH resulted in the instability of the swallow motor pattern activated by stimulating PiCo, suggesting PiCo plays a role in its modulation.".<br /> Thank you, this has been changed

Line 437: Mice of the ChATcre:Ai32, Vglut2cre:Ai32 and ChATcre:Vglut2FlpO:ChR2 lines were kept in collective cages with food and water ad libitum placed inside custom-built chambers.<br /> Thank you, this has been changed.

Overall, the manuscript has been improved.

Reviewer #2 (Public Review):

Summary:

In the present study, the authors investigated the neural coding mechanisms for D1- and D2-expressing striatal direct and indirect pathway MSNs in interval timing by using multiple strategies. They concluded that D2-MSNs and D1-MSNs have opposing temporal dynamics yet disrupting either type produced similar effects on behavior, indicating the complementary roles of D1- and D2- MSNs in cognitive processing. However, the data was incomplete to fully support this major finding. One major reason is the heterogenetic responses within the D1-or D2-MSN populations. In addition, there are additional concerns about the statistical methods used. For example, the majority of the statistical tests are based on the number of neurons, but not the number of mice. It appears that the statistical difference was due to the large sample size they used (n=32 D2-MSNs and n=41 D1-MSNs), but different neurons recorded in the same mouse cannot be treated as independent samples; they should use independent mouse-based statistical analysis.

Strengths:

The authors used multiple approaches including awake mice behavior training, optogenetic-assistant cell-type specific recording, optogenetic or pharmacological manipulation, neural computation, and modeling to study neuronal coding for interval timing.

Weaknesses:

(1) More detailed behavior results should be shown, including the rate of the success switches, and how long it takes to wait in the second nose poke to get a reward. For line 512 and the Figure 1 legend, the reviewer is not clear about the reward delivery. The methods appear to state that the mouse had to wait for 18s, then make nose pokes at the second port to get the reward. What happens if the mouse made the second nose poke before 18 seconds, but then exited? Would the mouse still get the reward at 18 seconds? Similarly, what happens if the mice made the third or more nosepokes within 18 seconds? It is important to clarify because, according to the method described, if the mice made a second nose poke before 18 seconds, this already counted as the mouse making the "switch." Lastly, what if the mice exited before 6s in the first nosepoke?

(2) There are a lot of time parameters in this behavior task, the description of those time parameters is mentioned in several parts, in the figure legend, supplementary figure legend, and methods, but was not defined clearly in the main text. It is inconvenient, sometimes, confusing for the readers. The authors should make a schematic diagram to illustrate the major parameters and describe them clearly in the main text.

(3) In Line 508, the reviewer suggests the authors pay attention to those trials without "switch". It would be valuable to compare the MSN activity between those trials with or without a "switch".

(4) The definition of interval is not very clear. It appears that the authors used a 6-second interval in analyzing the data in Figure 2 and Figure 3. But from my understanding, the interval should be the time from time "0" to the "switch", when the mice start to exit from the first nose poke.

(5) For Figure 2 C-F, the authors only recorded 32 D2-MSNs in 4 mice, and 41 D1-MSNs in 5 mice. The sample size is too small compared to the sample size usually used in the field. In addition to the small sample size, the single-cell activity exhibited heterogeneity, which created potential issues. For both D1 and D2 MSNs, the authors tried to make conclusions on the "trend" of increasing in D2-MSNs and decreasing in D1-MSNs populations, respectively, during the interval. However, such a conclusion is not sufficiently supported by the data presented. It looks like the single-cell activity patterns can be separated into groups: one is a decreasing activity group, one is an increasing activity group and a small group for on and off response. Because of the small sample size, the author should pay attention to the variance across different mice (which needs to be clearly presented in the manuscript), instead of pooling data together and analyzing the mean activity.

(6) For Figure 2, from the activity in E and F, it seems that the activity already rose before the trial started, the authors should add some longer baseline data before time zero for clarification and comparison, and show the timing of the actual start of the activity with the corresponding behavior. What behavior states are the mice in when initiating the activity?

(7) The authors were focused on the "switch " behavior in the task, but they used an arbitrary 6s time window to analyze the activity, and tried to correlate the decreasing or increasing activities of MSNs to the neural coding for time. A better way to analyze is to sort the activity according to the "switch" time, from short to long intervals. This way, the authors could see and analyze whether the activity of D1 or D2 MSNs really codes for the different length of interval, instead of finding a correlation between average activity trends and the arbitrary 6s time window.

Reviewer #2 (Public Review):

Summary:

In this study, the authors find that the deletion of a sulfate transporter in yeast, Sul1, leads to the extension of replicative lifespan. They investigate mechanisms underlying this extension and claim that the effects on longevity can be separated from sulfate transport, and are instead linked to a previously proposed transceptor function of the Sul1 transporter. Through RNA sequencing analysis, the authors find that Sul1 loss triggers activation of several stress response pathways, and conclude that deletion of two pathways, autophagy or Msn2/4, partially prevents lifespan extension in cells lacking Sul1. Overall, while it is well-appreciated that activation of Msn2/4 or autophagy is beneficial for lifespan extension in yeast, the results of this study would add an important new mechanism by which this could achieved, through perceived sulfate starvation. However, as described below, several of the experiments utilized to support the authors' conclusion are not experimentally sound, and significant additional experimentation is required to support the authors' claims throughout the manuscript.

Strengths:

The major strength of the study is the robust RNA-seq data that identified differentially expressed genes in cells lacking Sul1. This facilitated the authors' focus on two of these pathways, autophagy and the Msn2/4 stress response pathway.

Weaknesses:

Several critical experimental flaws need to be addressed by the authors to more rigorously test their hypothesis.

(1) The lifespan assays throughout the manuscript contain inconsistencies in the mean lifespan of the wild-type strain, BY4741. For example, in Figure 1A, the lifespan of BY4741 is 24.3, and the extended lifespan of the sul1 mutant is 31. However, although all mutants tested in Figure 1B also have lifespans close to 30 cell divisions, the wild-type control is also at 30 divisions in those experiments as well. This is problematic, as it makes it impossible to conclude anything about the lifespan extension of various mutants with inconsistencies in the wild-type lifespan. Additionally, the mutants analyzed in 1B are what the authors use to claim that loss of the transporter does not extend lifespan through sulfate limitation, but instead through a signaling function. Thus, it remains unclear whether loss of sul1 extends lifespan at all, and if it does, whether this is separable from cellular sulfate levels.

(2) While the authors use mutants in Figure 1 that should have differential effects on sulfate levels in cells, the authors need to include experiments to measure sulfate levels in their various mutant cells to draw any conclusions about their data.

3) Similar to point 2, the authors focused their RNA sequencing analysis on the deletion of sul1 and did not include important RNA seq analysis of the specific Sul1 mutation or other mutants in Figure 1B that do not exhibit lifespan extension. The prediction is that they should not see the activation of stress response pathways in these mutants as they do not see lifespan extension, but this needs to be tested.

(4) While the RNA-seq data is robust in Figure 2 as well as the follow-up quantitative PCR and trehalose/glycogen assays in 2A-B, the follow-up imaging assays for Msn2/4 localization in Figure 2 are not robust and are difficult to interpret. The authors need to include more high-resolution imaging or at least a close-up of the cells in Figure 3C.

(5) The autophagy assays utilized in Figure 4 appear to all be done with a C-terminal GFP-tagged Atg8 protein. As C-terminal GFP is removed from Atg8 prior to conjugation to phosphatidylethanolamine, microscopy assays of this reporter cannot be utilized to report on autophagy activity or flux. Instead, the authors need to utilize N-terminally tagged Atg8, which they can monitor for vacuole uptake as an appropriate readout of autophagy levels. As it stands, the authors cannot draw any conclusions about autophagy activity in their studies.

Reviewer #2 (Public Review):

Summary:

Bestry et al. investigated the effects of prenatal alcohol exposure (PAE) and high methyl donor diet (HMD) on offspring DNA methylation and behavioral outcomes using a mouse model that mimics common patterns of alcohol consumption in pregnancy in humans. The researchers employed whole-genome bisulfite sequencing (WGBS) for unbiased assessment of the epigenome in the newborn brain and liver, two organs affected by ethanol, to explore tissue-specific effects and to determine any "tissue-agnostic" effects that may have arisen prior to the germ-layer commitment during early gastrulation. The authors found that PAE induces measurable changes in offspring DNA methylation. DNA methylation changes induced by PAE coincide with non-coding regions, including enhancers and promoters, with the potential to regulate gene expression. Though the majority of the alcohol-sensitive differentially methylated regions (DMRs) were not conserved in humans, the ones that were conserved were associated with clinically relevant traits such as facial morphology, educational attainment, intelligence, autism, and schizophrenia Finally, the study provides evidence that maternal dietary support with methyl donors alleviates the effects of PAE on DNA methylation, suggesting a potential prenatal care option.

Strengths:

The strengths of the study include the use of a mouse model where confounding factors such as genetic background and diet can be well controlled. The study performed whole-genome bisulfite sequencing, which allows a comprehensive analysis of the effects of PAE on DNA methylation.

Weaknesses:

Transcriptome analysis to test if the identified DMRs indeed affect gene expression would help determine the potential function of the identified methylation changes.

Reviewer #2 (Public Review):

This work started with transcriptomic profiling of ductal cells to identify the upregulation of calcineurin in the zebrafish after beta-cell ablation. By suppressing calcineurin with its chemical inhibitor cyclosporin A and expressing a constitutively active form of calcineurin ubiquitously or specifically in ductal cells, the authors found that inhibited calcineurin activity promoted beta-cell regeneration transiently while ectopic calcineurin activity hindered beta-cell regeneration in the pancreatic tail. They also showed similar effects in the basal state but only when it was within a particular permissive window of Notch activity. To further investigate the roles of calcineurin in the ductal cells, the authors demonstrated that calcineurin inhibition additionally induced the proliferation of the ductal cells in the regenerative context or under a limited level of Notch activity. Interestingly, the enhanced proliferation was followed by a depletion of ductal cells, suggesting that calcineurin inhibition would exhaust the ductal cells. Based on the data, the authors proposed a very attractive and intriguing model of the role of calcineurin in maintaining the balance of the progenitor proliferation and the endocrine differentiation. However, the conclusions of this paper are only partially supported by the data as some evidence of the lineage between ductal cells and beta cells remains suggestive.

Reviewer #2 (Public Review):

Summary:

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 gained insights into how cytokinesis occurs.

Strengths:

(i) Human iPSC cells are used

Weaknesses:

(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:

The manuscript by Kokinovic et al. presents evidence that a significant portion of striatal projection neurons (SPNs) are spontaneously active early in development. This spontaneous activity (as measured in ex vivo brain slices) is due to intrinsic mechanisms, and subsides over the course of the first few postnatal weeks in a cell-type specific way: striosome direct and indirect pathway SPNs (dSPNs and iSPNs, respectively) remain spontaneously active until postnatal days 10-14, by which time matrix dSPNs and iSPNs have become entirely silent. The authors suggest that this early spontaneous activity may be in part due to M1 muscarinic receptor signaling. Through chemogenetic inhibition of striosome SPNs (of which dSPNs target dopaminergic neurons of the SNc), the authors present evidence that critical postnatal windows of SPN activity shape the strength of GABAergic innervation of the SNc (measured in adults). This study provides a useful and solid characterization of the functional, postnatal compartmental development of the striatum. However, some weaknesses in the experimental design should be addressed before definitively concluding that postnatal striosome SPN activity determines its functional innervation of dopaminergic SNc neurons.

Specific Comments:

(1) While certainly interesting and possibly true, evidence for the necessity of early striosome dSPN activity in shaping their functional innervation of dopaminergic SNc neurons is not entirely convincing. The functional measure of GABAergic innervation of dopamine neurons is inferred from mIPSCs. As the authors state, dopaminergic neurons have numerous other sources of GABAergic inputs in addition to striosome dSPNs. So while manipulating striosome activity may ultimately alter the overall GABAergic innervation of SNc dopamine neurons, the specificity of this to striosome dSPN inputs is not known. Optogenetic stimulation of striosome->SNc neurons after chemogenetic silencing would help support the authors' interpretation. Related to this point, while striatonigral projections form embryonically, is there evidence that striosome->SNc synapses are indeed functional by P6-14 when CNO is delivered?

(2) One big caveat that needs to be addressed is that all measures of early postnatal spontaneous SPN activity were performed in ex vivo slices. Are SPNs active (in pathway/compartmental specific ways) in vivo during this time? If it is unknown, is there other evidence (e.g. immediate early gene expression, etc...) that may suggest this is indeed the case in vivo?

(3) It appears that 8mM KCl (external) was only used while measuring spontaneous calcium oscillations, not spontaneous spiking (Figure 2). Was there any evidence of spontaneous calcium activity in the lower KCl concentration (3mM?) used for cell-attached recordings? One caveat is that experiments demonstrating that SPNs fire spontaneously in the presence of AMPA receptor blockers (Figure S1) were presumably performed in 3mM KCl. Does elevated KCl increases spontaneous EPSPs during the ages examined? If so, are the calcium oscillations shown in Figure 2 synaptically driven or intrinsically generated? Somewhat related, speculation on why M1 receptor blockade reduces calcium oscillations but not spontaneous spikes in striosome dSPNs would be useful.

(4) Several statements in the introduction could use references.

Reviewer #2 (Public Review):

The authors sought to establish the role played by N343 glycosylation on the SARS-CoV-2 S receptor binding domain structure and binding affinity to the human host receptor ACE2 across several variants of concern. The work includes both computational analysis in the form of molecular dynamics simulations and experimental binding assays between the RBD and ganglioside receptors.

The work extensively samples the conformational space of the RBD beginning with atomic coordinates representing both the bound and unbound states and computes molecular dynamics trajectories until equilibrium is achieved with and without removing N343 glycosylation. Through comparison of these simulated structures, the authors are able to demonstrate that N343 glycosylation stabilizes the RBD. Prior work had demonstrated that glycosylation at this site plays an important role in shielding the RBD core and in this work, the authors demonstrate that removal of this glycan can trigger a conformational change to reduce water access to the core without it. This response is variant-dependent and variants containing interface substitutions that increase RBD stability, including Delta substitution L452R, do not experience the same conformational change when the glycan is removed. The authors also explore structures corresponding to Alpha and Beta in which no structure-reinforcing substitutions were identified and two Omicron variants in which other substitutions with an analogous effect to L452R are present.

The authors experimentally assessed these inferred structural changes by measuring the binding affinity of the RBD for the oligosaccharides of the mono-sialylated gangliosides GM1os and GM2os with and without the glycan at N343. While GM1os and GM2os binding is influenced by additional factors in the Beta and Omicron variants, the comparison between Delta and Wuhan-hu-1 is clear: removal of the glycan abrogated binding for Wuhan-hu-1 and minimally affected Delta as predicted by structural simulations.

In summary, these findings suggest, in the words of the authors, that SARS-CoV-2 has evolved to render the N-glycosylation site at N343 "structurally dispensable". This study emphasizes how glycosylation impacts both viral immune evasion and structural stability which may in turn impact receptor binding affinity and infectivity. Mutations that stabilize the antigen may relax the structural constraints on glycosylation opening up avenues for subsequent mutations that remove glycans and improve immune evasion. This interplay between immune evasion and receptor stability may support complex epistatic interactions which may in turn substantially expand the predicted mutational repertoire of the virus relative to expectations that do not take into account glycosylation.

Reviewer #2 (Public Review):

Summary:

Using K562 (Leukemia) cells as an experimental model, Van Vracken et. al. use Thermal Proteome Profiling (TPP) to investigate changes in protein stability after exposing either live cells or crude cell lysates to a library of anti-cancer drugs. This was a large-scale and highly ambitious study, involving thousands of hours of mass spectrometry instrument time. The authors used an innovative combination of TPP together with Proteome Integral Solubility Alternation (PISA) assays to reduce the amount of instrument time needed, without compromising on the amount of data obtained.

The paper is very well written, the relevance of this work is immediately apparent, and the results are well-explained and easy to follow even for a non-expert. The figures are well-presented. The methods appear to be explained in sufficient detail to allow others to reproduce the work.

Strengths:

Using CDK4/6 inhibitors, the authors observe strong changes in protein stability upon exposure to the drug. This is expected and shows their methodology is robust. Further, it adds confidence when the authors report changes in protein stability for drugs whose targets are not well-known. Many of the drugs used in this study - even those whose protein targets are already known - display numerous off-target effects. Although many of these are not rigorously followed up in this current study, the authors rightly highlight this point as a focus for future work.

Weaknesses:

While the off-target effects of several drugs could've been more rigorously investigated, it is clear the authors have already put a tremendous amount of time and effort into this study. The authors have made their entire dataset available to the scientific community - this will be a valuable resource to others working in the fields of cancer biology/drug discovery.

Reviewer #2 (Public Review):

Summary:

This paper examines the recruitment of the inflammasome seeding pattern recognition receptor NLRP3 to the Golgi. Previously, electrostatic interactions between the polybasic region of NLRP3 and negatively charged lipids were implicated in membrane association. The current study reports that reversible S-acylation of the conserved Cys-130 residue, in conjunction with upstream hydrophobic residues plus the polybasic region, act together to promote Golgi localization of NLRP3, although additional parts of the protein are needed for full Golgi localization. Treatment with the bacterial ionophore nigericin inhibits membrane traffic and prevents Golgi-associated thioesterases from removing the acyl chain, causing NLRP3 to become immobilized at the Golgi. This mechanism is put forth as an explanation for how NLRP3 is activated in response to nigericin.

Strengths:

The experiments are generally well presented. It seems likely that Cys-130 does indeed play a previously unappreciated role in the membrane association of NLRP3.

Weaknesses:

The interpretations about the effects of nigericin are less convincing. Specific comments follow.

(1) The experiments of Figure 4 bring into question whether Cys-130 is S-acylated. For Cys-130, S-acylation was seen only upon expression of a severely truncated piece of the protein in conjunction with overexpression of ZDHHC3. How do the authors reconcile this result with the rest of the story?

(2) Nigericin seems to cause fragmentation and vesiculation of the Golgi. That effect complicates the interpretations. For example, the FRAP experiment of Figure 5 is problematic because the authors neglected to show that the FRAP recovery kinetics of non-acylated resident Golgi proteins are unaffected by nigericin. Similarly, the colocalization analysis in Figure 6 is less than persuasive when considering that nigericin significantly alters Golgi structure and could indirectly affect colocalization.