Reviewer #2 (Public Review):

Summary:

The paper investigates the role of astrocyte-specific aquaporin-4 (AQP4) water channel in mediating water transport within the mouse brain and the impact of the channel on astrocyte and neuron signaling. Throughout various experiments including epifluorescence and light sheet microscopy in mouse brain slices, and fiber photometry or diffusion-weighted MRI in vivo, the researchers observe that acute inhibition of AQP4 leads to intracellular water accumulation and swelling in astrocytes. This swelling alters astrocyte calcium signaling and affects neighboring neuron populations. Furthermore, the study demonstrates that AQP4 regulates astrocyte volume, influencing mainly the dynamics of water efflux in response to osmotic challenges or associated with cortical spreading depolarization. The findings suggest that AQP4-mediated water efflux plays a crucial role in maintaining brain homeostasis, and indicates the main role of AQP4 in this mechanism. However authors highlight that the report sheds light on the mechanisms by which astrocyte aquaporin contributes to the water environment in the brain parenchyma, the mechanism underlying these effects remains unclear and not investigated. The manuscript requires revision.

Strengths:

The paper elucidates the role of the astrocytic aquaporin-4 (AQP4) channel in brain water transport, its impact on water homeostasis, and signaling in the brain parenchyma. In its idea, the paper follows a set of complimentary experiments combining various ex vivo and in vivo techniques from microscopy to magnetic resonance imaging. The research is valuable, confirms previous findings, and provides novel insights into the effect of acute blockage of the AQP4 channel using TGN-020.

Weaknesses:

Despite the employed interdisciplinary approach, the quality of the manuscript provides doubts regarding the significance of the findings and hinders the novelty claimed by the authors. The paper lacks a comprehensive exploration or mention of the underlying molecular mechanisms driving the observed effects of astrocytic aquaporin-4 (AQP4) channel inhibition on brain water transport and brain signaling dynamics. The scientific background is not very well prepared in the introduction and discussion sections. The important or latest reports from the field are missing or incompletely cited and missconcluded. There are several citations to original works missing, which would clarify certain conclusions. This especially refers to the basis of the glymphatic system concept and recently published reports of similar content. The usage of TGN-020, instead of i.e. available AER-270(271) AQP4 blocker, is not explained. While employing various experimental techniques adds depth to the findings, some reasoning behind the employed techniques - especially regarding MRI - is not clear or seemingly inaccurate. Most of the time the number of subjects examined is lacking or mentioned only roughly within the figure captions, and there are lacking or wrongly applied statistical tests, that limit assessment and reproducibility of the results. In some cases, it seems that two different statistical tests were used for the same or linked type of data, so the results are contradictory even though appear as not likely - based on the figures. Addressing these limitations could strengthen the paper's impact and utility within the field of neuroscience, however, it also seems that supplementary experiments are required to improve the report.

Reviewer #2 (Public Review):

The work by Yun et al. explores an important question related to post-copulatory sexual selection and sperm competition: Can females actively influence the outcome of insemination by a particular male by modulating the storage and ejection of transferred sperm in response to contextual sensory stimuli? The present work is exemplary for how the Drosophila model can give detailed insight into the basic mechanism of sexual plasticity, addressing the underlying neuronal circuits on a genetic, molecular, and cellular level.

Using the Drosophila model, the authors show that the presence of other males or mated females after mating shortens the ejaculate-holding period (EHP) of a female, i.e. the time she takes until she ejects the mating plug and unstored sperm. Through a series of thorough and systematic experiments involving the manipulation of olfactory and chemo-gustatory neurons and genes in combination with exposure to defined pheromones, they uncover two pheromones and their sensory cells for this behavior. Exposure to the male-specific pheromone 2MC shortens EHP via female Or47b olfactory neurons, and the contact pheromone 7-T, present in males and on mated females, does so via ppk23 expressing gustatory foreleg neurons. Both compounds increase cAMP levels in a specific subset of central brain receptivity circuit neurons, the pC1b,c neurons. By employing an optogenetically controlled adenyl cyclase, the authors show that increased cAMP levels in pC1b and c neurons increase their excitability upon male pheromone exposure, decrease female EHP, and increase the remating rate. This provides convincing evidence for the role of pC1b,c neurons in integrating information about the social environment and mediating not only virgin but also mated female post-copulatory mate choice.

Understanding context and state-dependent sexual behavior is of fundamental interest. Mate behavior is highly context-dependent. In animals subjected to sperm competition, the complexities of optimal mate choice have attracted a long history of sophisticated modelling in the framework of game theory. These models are in stark contrast to how little we understand so far about the biological and neurophysiological mechanisms of how females implement post-copulatory or so-called "cryptic" mate choice and bias sperm usage when mating multiple times.

The strength of the paper is decrypting "cryptic" mate choice, i.e. the clear identification of physiological mechanisms and proximal causes for female post-copulatory mate choice. The discovery of peripheral chemosensory nodes and neurophysiological mechanisms in central circuit nodes will provide a fruitful starting point to fully map the circuits for female receptivity and mate choice during the whole gamut of female life history.

Reviewer #2 (Public Review):

In their paper entitled "In mice, discrete odors can selectively promote the neurogenesis of sensory neuron subtypes that they stimulate" Hossain et al. address lifelong neurogenesis in the mouse main olfactory epithelium. The authors hypothesize that specific odorants act as neurogenic stimuli that selectively promote biased OR gene choice (and thus olfactory sensory neuron (OSN) identity). Hossain et al. employ RNA-seq and scRNA-seq analyses for subtype-specific OSN birthdating. The authors find that exposure to male and musk odors accelerates the birthrates of the respective responsive OSNs. Therefore, Hossain et al. suggest that odor experience promotes selective neurogenesis and, accordingly, OSN neurogenesis may act as a mechanism for long-term olfactory adaptation.

The authors follow a clear experimental logic, based on sensory deprivation by unilateral naris occlusion, EdU labeling of newborn neurons, and histological analysis via OR-specific RNA-FISH. The results reveal robust effects of deprivation on newborn OSN identity. However, the major weakness of the approach is that the results could, in (possibly large) parts, depend on "downregulation" of OR subtype-specific neurogenesis, rather than (only) "upregulation" based on odor exposure. While, in Figure 6, the authors show that the observed effects are, in part, mediated by odor stimulation, it remains unclear whether deprivation plays an "active" role as well. Moreover, as shown in Figure 1C, unilateral naris occlusion has both positive and negative effects in a random subtype sample.

Another weakness is that the authors build their model (Figure 8), specifically the concept of selectivity, on a receptor-ligand pair (Olfr912 that has been shown to respond, among other odors, to the male-specific non-musk odors 2-sec-butyl-4,5-dihydrothiazole (SBT)) that would require at least some independent experimental corroboration. At least, a control experiment that uses SBT instead of muscone exposure should be performed. In this context, it is somewhat concerning that some results, which appear counterintuitive (e.g., lower representation and/or transcript levels of Olfr912 and Olfr1295 in mice exposed to male odors) are brushed off as "reflecting reduced survival due to overstimulation." The notion of "reduced survival" could be tested by, for example, a caspase3 assay.<br /> Important analyses that need to be done to better be able to interpret the findings are to present (i) the OR+/EdU+ population of olfactory sensory neurons not just as a count per hemisection, but rather as the ratio of OR+/EdU+ cells among all EdU+ cells; and (ii) to the ratio of EdU+ cells among all nuclei (UNO versus open naris). This way, data would be normalized to (i) the overall rate of neurogenesis and (ii) any broad deprivation-dependent epithelial degeneration.

Finally, the paper will benefit from improved data presentation and adequate statistical testing. Images in Figures 2 - 7, showing both EdU labeling of newborn neurons and OR-specific RNA-FISH, are hard to interpret. Moreover, t-tests should not be employed when data is not normally distributed (as is the case for most of their samples).

Reviewer #2 (Public Review):

The authors tried to characterize the function of the SWI/SNF remodeler family, BAF, in spermatogenesis. The authors focused on ARID1A, a BAF-specific putative DNA binding subunit, based on gene expression profiles.

The authors disagreed with my previous assessments. I disagree with their response.

Reviewer #2 (Public Review):

The study by Diffendall et al. set out to establish a link between the activity of RNA polymerase III (Pol III) and its inhibitor Maf1 and the virulence of Plasmodium falciparum in vivo. Having previously found that knockdown of the ncRNA ruf6 gene family reduces var gene expression in vitro, they now present experimental evidence for the regulation of ruf6 and subsequently, var gene expression by Pol III using a commercially available inhibitor. They confirm their findings with samples from a previously published Gambian cohort study using asymptomatic dry season and mildly symptomatic wet season samples, showing that higher levels of Pol III-dependent transcripts and var transcripts as well as lower MgCl2 plasma concentrations are present in wet season samples. From this, they hypothesize that the external stimuli heat, reduced glucose and essential amino acid supply, and increased MgCl2 levels are sensed by the parasite through the only known Pol III inhibitor Maf1 and result in lower Pol III activity and fewer ruf6 transcripts, which in turn reduces var gene expression, leading to reduced cytoadherence and virulence of P. falciparum. In their in vitro experiments they focus on investigating higher MgCl2 levels and their impact on Pol III and Maf1 activity as well as var gene expression and parasites adherence to purified CD36, thereby successfully confirming their hypothesis for MgCl2. Nicely, MgCl2-induced down-regulation of Pol III activity was shown to be dependent on Maf1 using a knock-down cell line. Additionally, they show that the Maf1-KD cell line displays a slower growth rate with fewer merozoites per schizonts and Maf1 interacts with RNA pol III subunits and some kinases/phosphatases.

Comments on latest version:

It is understandable that the RNA samples from the Gambian cohort were limited, but for all in vitro analyses a larger panel of qPCR primers or RNAseq would have been feasible. I also understand the rationale for using the general var primer pair (DBLa) for field isolates, but since the authors were working with a clonal parasite line (3D7) in vitro, qPCR with specific 3D7/NF54 primer pairs or RNAseq, which would also allow inferences about ruf6 regulation of specific (neighboring?) var genes and other Pol III-regulated genes, would have been a far better option.

As far as I could see from the resubmitted manuscript, the authors did not correct the statistical analyses. For example, they continue to apply a t-test to fold-change values (which must be transformed to log2), many t-test based analyses rely on only 2-3 replicates (a non-parametric test would be more appropriate), they have not corrected for multiple testing, and it is unclear how the authors handle technical and biological replicates in their plots. Therefore, I still suspect that more appropriate statistical analyses might have an impact on the significance of their results.

I agree that CD36 binding is associated with mild malaria, but since the authors only make a link between Pol III and CD36 binding in vitro, I think it is an overstatement to claim something like "Our study reveals a regulatory mechanism in P. falciparum involving RNA Polymerase III, which plays a pivotal role in the parasite's virulence."

Finally, if the authors have checked all the relevant literature on MgCl2, it should be easy for them to give a brief explanation why they included only one study and ignored all the other contradictory results.

Reviewer #2 (Public Review):

Bian et al. calculated Phenotypic Age Acceleration (PhenoAgeAccel) via a linear model regressing Phenotypic Age on chronological age. They examined the associations between PhenoAgeAccel and cancer incidence using 374,463 individuals from the UK Biobank and found that older PhenoAge was consistently related to an increased risk of incident cancer, even among each risk group defined by genetics.

The study is well-designed, and uses a large sample size from the UK biobank.

Comments on revised version:

The authors have addressed all my concerns.

Reviewer #2 (Public Review):

In the present manuscript, Huang et.al. revealed the significant roles of the DNA methylome in regulating virulence and metabolism within Pseudomonas syringae, with a particular focus on the HsdMSR system in this model strain. The authors used SMRT-seq to profile the DNA methylation patterns (6mA, 5mC, and 4mC) in three P. syringae strains (Psph, Pss, and Psa) and displayed the conservation among them. They further identified the type I restriction-modification system (HsdMSR) in P. syringae, including its specific motif sequence. The HsdMAR participated in the process of metabolism and virulence (T3SS & Biofilm formation), as demonstrated through RNA-seq analyses. Additionally, the authors revealed the mechanisms of the transcriptional regulation by 6mA. Strictly from the point of view of the interest of the question and the work carried out, this is a worthy and timely study that uses third-generation sequencing technology to characterize the DNA methylation in P. syringae. The experimental approaches were solid, and the results obtained were interesting and provided new information on how epigenetics influences the transcription in P. syringae. The conclusions of this paper are mostly well supported by data, but some aspects of data analysis and discussion need to be clarified and extended.

Reviewer #2 (Public Review):

Summary:

Although an oversimplification of the biological complexities, this modeling work does add, in a limited way, to the current knowledge on the theoretical difficulties of detecting mosaicism in human blastocysts from a single trophectoderm biopsy in PGT. However, many of the premises that the modeling was built on are theoretical and based on unproven biological and clinical assumptions that could yet lead to be untrue. Therefore, the work should be considered only as a simplified model that could assist in further understanding of the complexities of preimplantation embryo mosaicism, but assumptions of real-world application are, at this stage, premature and should not be considered as evidence in favour of any clinical strategies.

Strengths:

The work has presented an intriguing theoretical model for elaborating on the interpretation of complex and still unclear biological phenomena such as chromosomal mosaicism in preimplantation embryos.

Weaknesses:

Lines 134-138: The spatial modeling of mitotic errors in the embryo was oversimplified in this manuscript. There is only limited (and non-comprehensive) evidence that meiotic errors leading to chromosome mosaicism arise from chromosome loss or gain only (e.g. anaphase lag). This work did not take into account the (more recognised) possibility of mitotic nondisjunction where following the event there would be clones of cells with either one more or one less of the same chromosome. Although addressed in the discussion (lines 572-574), not including this in the most basic of modeling is a significant oversight that, based on the simple likelihood, could significantly affect results.

General comment: the premise of the manuscript is that an embryologist (embryology laboratory) is aware of and can accurately quantify the number of cells in a blastocyst or TE biopsy. The reality is that it is not possible to accurately do this without the destruction of the sample which is obviously not clinically applicable. Based on many assumptions the findings show that taking small biopsies poorly classifies mosaic embryos, which is not disputed. However, extrapolating this to the clinic and making suggestions to biopsy a certain amount of cells (lines 539-540) is careless and potentially harmful by suggesting the introduction of potential change in clinical practice without validation. Additionally, no embryologist in the field can tell how many cells are present in a clinical TE biopsy, making this suggestion even more impractical.

On a more general clinical consideration, the authors should acknowledge that when reporting findings of unproven clinical utility and unknown predictive values this inevitably results in negative consequences for infertile couples undergoing IVF. It is proven and established that when couples face the decision on how to manage a putative mosaicism finding, the vast majority decide on embryo disposal. It was recently reported in an ESHRE survey that about 75% of practitioners in the field consider discarding or donating to research embryos with reported mosaicism. A prospective clinical trial showed that about 30% live birth rate reduction can be expected if mosaic embryos are not considered (Capalbo et al., AJHG 2021). The real-world experience is that when mosaicism is reported, embryos with almost normal reproductive potential are discarded. The authors should be more careful with the clinical interpretation and translation of these theoretical findings.

There is a robust consensus within the field of clinical genetics and genomics regarding the necessity to exclusively report findings that possess well-established clinical validity and utility. This consensus is grounded in the imperative to mitigate misinterpretation and ineffective actions in patient care. However, the clinical framework delineated in this manuscript diverges from the prevailing consensus in clinical genetics. Clinical genetics and genomics prioritize the dissemination of findings that have undergone rigorous validation processes and have demonstrated clear clinical relevance and utility. This emphasis is crucial for ensuring accurate diagnosis, prognosis, and therapeutic decision-making in patient care. By adhering to established standards of evidence and clinical utility, healthcare providers can minimize the potential for misinterpretation and inappropriate interventions. The framework proposed in this manuscript appears to deviate from the established principles guiding clinical genetics practice. It is imperative for clinical frameworks to align closely with the consensus guidelines and recommendations set forth by professional organizations and regulatory bodies in the field. This alignment not only upholds the integrity and reliability of genetic testing and interpretation but also safeguards patient well-being and clinical outcomes.

References:<br /> ACMG Board of Directors. (2015). Clinical utility of genetic and genomic services: a position statement of the American College of Medical Genetics and Genomics. Genetics in Medicine, 17(6), 505-507. https://doi.org/10.1038/gim.2014.194.<br /> Richards, S., Aziz, N., Bale, S., Bick, D., Das, S., Gastier-Foster, J., ... ACMG Laboratory Quality Assurance Committee. (2015). Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine, 17(5), 405-424. https://doi.org/10.1038/gim.2015.30

Line 61: "Self correction" - This terminology is unfortunately indiscriminately used in the field for PGT when referring to mosaicism and implies that the embryo can actively correct itself from a state of inherent abnormality. Apart from there being no evidence to suggest that there is an active process by which the embryo itself can correct chromosomal errors, most presumed euploid/aneuploid mosaic embryos will have been euploid zygotes and therefore "self-harm" may be a better explanation. True self-correction in the form of meiotic trisomy/monosomy rescue is of course theoretically possible but not at all clinically significant. The concept being conveyed in this part of the manuscript is not disputed but it is strongly suggested that the term "self correction" is not used in this context, nor in the rest of the manuscript, to prevent the perpetuation of misinformation in the field and instead use a better description.

Lines 69-73: The ability to quantify aneuploidy in known admixtures of aneuploid cells is indeed well established. However, the authors claim that the translation of this to embryo biopsy samples is inferred with some confidence and that if a biopsy shows an intermediate chromosome copy number (ICN), that the biopsy and the embryo are mosaic. There are no references provided here and indeed the only evidence in the literature relating to this is to the contrary. Multifocal biopsy studies have shown that an ICN result in a single biopsy is often not seen in other biopsies from the same embryo (Capalbo et al 2021; Kim et al., 2022; Girardi et al., 2023; Marin, Xu, and Treff 2021). Multifocal biopsies showing reciprocal gain and loss which would provide stronger validation for the presence of true mosaicism are also rare. In this work, the entire manuscript is based on the accuracy of ICN in a biopsy being reflective of mosaicism in the embryo. The evidence however points to a large proportion of ICN detected in embryo biopsy potentially being technical artifacts (misdiagnosing both constitutionally normal and abnormal (meiotic aneuploid) embryos as mosaic. Therefore, although results from the modelling provide insight into theoretical results, these can not be used to inform clinical decision-making at all.

Lines 87-89: The authors make the claim that emerging evidence is suggestive that the majority of embryos are mosaic to some degree. If in fact, mosaicism is the norm, the clinical importance may be limited.

Line 102-103: The statement that data shows that the live birth rate per ET is generally lower in mosaic embryos than euploid embryos is from retrospective cohort studies that suffer from significant selection bias. The authors have ignored non-selection study results (Capalbo et al, ajhg 2021) that suggest that putative mosaicism has limited predictive value when assessed prospectively and blinded.

Lines 94-98: The authors have misrepresented the works they have presented as evidence for biopsy result accuracy (Kim et al., 2023; Victor et al 2019; Capalbo et al., 2021; Girardi et al., 2023, and any others). These studies show that a mosaic biopsy is not representative of the whole embryo and can actually be from embryos where the remainder of the embryo shows no evidence of mosaicism. There is also a missing key reference of Capalbo et al, AJHG 2021, and Girardi et al., HR 2023 where multifocal biopsies were taken.

Lines 371-372: "Selecting the embryo with the lowest number of aneuploid cells in the biopsy for transfer is still the most sensible decision". Where is the evidence for this other than the modeling which is affected by oversimplification and unproven assumptions? Although the statement seems logical at face value, there is no concrete evidence that the proportion of aneuploid cells within a biopsy is valuable for clinical outcomes, especially when co-evaluated with other more relevant clinical information.

Lines 431-463: In this section, the authors discuss clinical outcome data from the transfer of putative mosaic embryos and make conclusions about the relationship between ICN level in biopsy and successful pregnancy outcomes. The retrospective and selective nature of the data used in forming the results has the potential to lead to incorrect conclusions when applied to prospective unselected data.

Reviewer #2 (Public Review):

Summary:

This study argues it has found that it has stratified viral kinetics for saliva specimens into three groups by the duration of "viral shedding"; the authors could not identify clinical data or microRNAs that correlate with these three groups.

Strengths:

The question of whether there is a stratification of viral kinetics is interesting.

Weaknesses:

The data underlying this work are not treated rigorously. The work in this manuscript is based on PCR data from two studies, with most of the data coming from a trial of nelfinavir (NFV) that showed no effect on the duration of SARS-CoV-2 PCR positivity. This study had no PCR data before symptom onset, and thus exclusively evaluated viral kinetics at or after peak viral loads. The second study is from the University of Illinois; this data set had sampling prior to infection, so has some ability to report the rate of "upswing." Problems in the analysis here include:

-- The PCR Ct data from each study is treated as equivalent and referred to as viral load, without any reports of calibration of platforms or across platforms. Can the authors provide calibration data and justify the direct comparison as well as the use of "viral load" rather than "Ct value"? Can the authors also explain on what basis they treat Ct values in the two studies as identical?

-- The limit of detection for the NFV PCR data was unclear, so the authors assumed it was the same as the University of Illinois study. This seems a big assumption, as PCR platforms can differ substantially. Could the authors do sensitivity analyses around this assumption?

-- The authors refer to PCR positivity as viral shedding, but it is viral RNA detection (very different from shedding live/culturable virus, as shown in the Ke et al. paper). I suggest updating the language throughout the manuscript to be precise on this point.

-- Eyeballing extended data in Figure 1, a number of the putative long-duration infections appear to be likely cases of viral RNA rebound (for examples, see S01-16 and S01-27). What happens if all the samples that look like rebound are reanalyzed to exclude the late PCR detectable time points that appear after negative PCRs?

-- There's no report of uncertainty in the model fits. Given the paucity of data for the upslope, there must be large uncertainty in the up-slope and likely in the peak, too, for the NFV data. This uncertainty is ignored in the subsequent analyses. This calls into question the efforts to stratify by the components of the viral kinetics. Could the authors please include analyses of uncertainty in their model fits and propagate this uncertainty through their analyses?

-- The clinical data are reported as a mean across the course of an infection; presumably vital signs and blood test results vary substantially, too, over this duration, so taking a mean without considering the timing of the tests or the dynamics of their results is perplexing. I'm not sure what to recommend here, as the timing and variation in the acquisition of these clinical data are not clear, and I do not have a strong understanding of the basis for the hypothesis the authors are testing.

It's unclear why microRNAs matter. It would be helpful if the authors could provide more support for their claims that (1) microRNAs play such a substantial role in determining the kinetics of other viruses and (2) they play such an important role in modulating COVID-19 that it's worth exploring the impact of microRNAs on SARS-CoV-2 kinetics. A link to a single review paper seems insufficient justification. What strong experimental evidence is there to support this line of research?

Reviewer #2 (Public Review):

Summary:

This work identifies two variants in CAPSL in two-generation familial exudative vitreoretinopathy (FEVR) pedigrees, and using a knockout mouse model, they link CAPSL to retinal vascular development and endothelial proliferation. Together, these findings suggest that the identified variants may be causative and that CAPSL is a new FEVR-associated gene.

Strengths:

The authors' data provides compelling evidence that loss of the poorly understood protein CAPSL can lead to reduced endothelial proliferation in mouse retina and suppression of MYC signaling in vitro, consistent with the disease seen in FEVR patients. The study is important, providing new potential targets and mechanisms for this poorly understood disease. The paper is clearly written, and the data generally support the author's hypotheses.

Weaknesses:

(1) Both pedigrees described appear to suggest that heterozygosity is sufficient to cause disease, but authors have not explored the phenotype of Capsl heterozygous mice. Do these animals have reduced angiogenesis similar to KOs? Furthermore, while the p.R30X variant protein does not appear to be expressed in vitro, a substantial amount of p.L83F was detectable by western blot and appeared to be at the normal molecular weight. Given that the full knockout mouse phenotype is comparatively mild, it is unclear whether this modest reduction in protein expression would be sufficient to cause FEVR - especially as the affected individuals still have one healthy copy of the gene. Additional studies are needed to determine if these variants alter protein trafficking or localization in addition to expression, and if they can act in a dominant negative fashion.

(2) The manuscript nicely shows that loss of CAPSL leads to suppressed MYC signaling in vitro. However, given that endothelial MYC is regulated by numerous pathways and proteins, including FOXO1, VEGFR2, ERK, and Notch, and reduced MYC signaling is generally associated with reduced endothelial proliferation, this finding provides little insight into the mechanism of CAPSL in regulating endothelial proliferation. It would be helpful to explore the status of these other pathways in knockdown cells but as the authors provide only GSEA results and not the underlying data behind their RNA seq results, it is difficult for the reader to understand the full phenotype. Volcano plots or similar representations of the underlying expression data in Figures 6 and 7 as well as supplemental datasets showing the differentially regulated genes should be included. In addition, while the paper beautifully characterizes the delayed retinal angiogenesis phenotype in CAPSL knockout mice, the authors do not return to that model to confirm their in vitro findings.

(3) In Figure S2D, the result of this vascular leak experiment is unconvincing as no dye can be seen in the vessels. What are the kinetics for biocytin tracers to enter the bloodstream after IP injection? Why did the authors choose the IP instead of the IV route for this experiment? Differences in the uptake of the eye after IP injection could confound the results, especially in the context of a model with vascular dysfunction as here.

(4) In Figure 5, it is unclear how filipodia and tip cells were identified and selected for quantification. The panels do not include nuclear or tip cell-specific markers that would allow quantification of individual tip cells, and in Figure 5C it appears that some filipodia are not highlighted in the mutant panel.

Reviewer #2 (Public Review):

Summary:<br /> In this report the authors used solution-based single-molecule FRET and low resolution cryo-EM to investigate the interactions between the substrate-binding domains of the ABC-importer OpuA from Lactococcus lactis. Based on their results, the authors suggest that the SBDs interact in an ionic strength-dependent manner.

Strengths:<br /> The strength of this manuscript is the uniqueness and importance of the scientific question, the adequacy of the experimental system (OpuA), and the combination of two very powerful and demanding experimental approaches.

Weaknesses:<br /> A demonstration that the SBDs physically interact with one another, and that this interaction is important for the transport mechanism will greatly strengthen the claims of the authors. The relation to cooperativity is also unclear.

Reviewer #2 (Public Review):

Summary:

The manuscript by Howard et al reports the development of high affinity WDR5-interaction site inhibitors (WINi) that engage the protein to block the arginine-dependent engagement with its partners. Treatment of MLL-rearranged leukemia cells with high-affinity WINi (C16) decreases the expression of genes encoding most ribosomal proteins and other proteins required for translation. Notably, although these targets are enriched for WDR5-ChIP-seq peaks, such peaks are not universally present in the target genes. High concordance was founded between the alterations in gene expression due to C16 treatment and the changes resulting from treatment with an earlier, lower affinity WINi (C6). Besides protein synthesis, genes involved in DNA replication or MYC responses are downregulated, while p53 targets and apoptosis genes are upregulated. Ribosome profiling reveals a global decrease in translational efficiency due to WINi with overall ribosome occupancies of mRNAs ~50% of control samples. The magnitude in the decrements of translation for most individual mRNAs exceeds the respective changes in mRNA levels genome-wide. From these results and other considerations, the authors hypothesize that WINi results in ribosome depletion. Quantitative mass spec documents the decrement in ribosomal proteins following WINi treatment along with increases in p53 targets and proteins involved in apoptosis occurring over 3 days. Notably RPL22L1 is essentially completely lost upon WINi treatment. The investigators next conduct a CRISPR screen to find moderators and cooperators with WINi. They identify components of p53 and DNA repair pathways as mediators of WINi inflicted cell death (so gRNAs against these genes permit cell survival). Next, WINi are tested in combination with a variety of other agents to explore synergistic killing to improve their expected therapeutic efficacy. The authors document loss of the p53 antagonist MDM4 (in combination with splicing alterations of RPL22L1), an observation that supports the notion that WINi killing is p53-mediated.

This is a scientifically very strong and well-written manuscript that applies a variety of state-of-the art molecular approaches to interrogate the role of the WDR5 interaction site and WINi. They reveal that the effects of WINi seem to be focused on the overall synthesis of protein components of the translation apparatus, especially ribosomal proteins-even those that do not bind WDR5 by ChIP (a question left unanswered is how such the WDR5-less genes are nevertheless WINi targeted). They convincingly show that disruption of the synthesis of these proteins occurs upon activation of p53 dependent apoptosis, likely driven by unbalanced ribosomal protein synthesis leading to MDM2 inhibition. This apoptosis is subsequently followed, as expected by ɣH2AX-activation. Pathways of possible WINi resistance and synergies with other anti-neoplastic approaches are explored. These experiments are all well-executed and strongly invite more extensive pre-clinical and translational studies of WINi in animal studies. The studies also may anticipate the use of WINi as probes of nucleolar function and ribosome synthesis though this was not really explored in the current manuscript. The current version of the manuscript documents ribosomal stress revealed by leakage of NPM1 into the nucleoplasm while nucleolar integrity is preserved. A progressive loss of rRNA synthesis occurs upon drug treatment that is presumably secondary to the decrement in ribosomal protein production.

Comments on revised version:

(1) The authors to my mind, have quite nicely and professionally addressed the comments of the reviewers and are to be congratulated on an important contribution to the elucidation of WDR5 biology and pathology.

Reviewer #2 (Public Review):

Summary:

HCN-4 isoform is found primarily in sino-atrial node where it contributes to the pacemaking activity. LRMP is an accessory subunit which prevents cAMP-dependent potentiation of HCN4 isoform but does not have any effect on HCN2 regulation. In this study, the authors combine electrophysiology, FRET with standard molecular genetics to determine the molecular mechanism of LRMP action on HCN4 activity. Their study shows parts of N- and C-termini along with specific residues in C-linker and S5 of HCN4 are crucial for mediating LRMP action on these channels. Furthermore, they show that the initial 224 residues of LRMP are sufficient to account for most of the activity. In my view, the highlight of this study is Fig. 7 which recapitulates LRMP modulation on HCN2-HCN4 chimera. Overall, this study is an excellent example of using time-tested methods to probe the molecular mechanisms of regulation of channel function by an accessory subunit.

The authors adequately addressed my earlier concerns.

Reviewer #2 (Public Review):

Summary:

This manuscript examined the underlying mechanisms between senescent osteoclasts (SnOCs) and lumbar spine instability (LSI) or aging. They first showed that greater numbers of SnOCs are observed in mouse models of LSI or aging, and these SnOCs are associated with induced sensory nerve innervation, as well as the growth of H-type vessels, in the porous endplate. Then, the deletion of senescent cells by administration of the senolytic drug Navitoclax (ABT263) results in significantly less spinal hypersensitivity, spinal degeneration, porosity of the endplate, sensory nerve innervation, and H-type vessel growth in the endplate. Finally, they also found that there is greater SnOC-mediated secretion of Netrin-1 and NGF, two well-established sensory nerve growth factors, compared to non-senescent OCs. The study is well conducted and data strongly support the idea.

Reviewer #2 (Public Review):

Summary:

This paper investigates a rare and severe brain disease called Hereditary Diffuse Leukoencephalopathy with Axonal Spheroids (HDLS). The authors aimed to understand how mutations in the gene CSF-1R affect microglia, the resident immune cells in the brain, and which alterations and factors lead to the specific pathophysiology. To model the human brain with the pathophysiology of HDLS, they used the human-specific model system of induced pluripotent stem cell (iPSC)-derived forebrain organoids with integrated iPSC-derived microglia (iMicro) from patients with the HDLS-causing mutation and an isogenic cell line with the corrected genome. They found that iPSC-derived macrophages (iMac) with HDLS mutations showed changes in their response, including increased inflammation and altered metabolism. Additionally, they studied these iMacs in forebrain organoids, where they differentiate into iMicro, and showed transcriptional differences in isolated iMicro when carrying the HDLS mutation. In addition, the authors described the influence of the mutation within iMicro on the transcriptional level of neurons and neural progenitor cells (NPCs) in the organoid. They observed that the one mutation showed implications for impaired development of neurons, possibly contributing to the progression of the disease.

Overall, this study provides valuable insights into the mechanisms underlying HDLS and emphasizes the importance of studying diseases like these with a suitable model system. These findings, while promising, represent only an initial step towards understanding HDLS and similar neurodegenerative diseases, and thus, their direct translation into new treatment options remains uncertain.

Strengths:

The strength of the work lies in the successful reprogramming of two HDLS patient-derived induced pluripotent stem cells (iPSCs) with different mutations, which is crucial for the study of HDLS using human forebrain organoid models. The use of corrected isogenic iPSC lines as controls increases the validity of the mutation-specific observations. In addition, the model effectively mimics HDLS, particularly concerning deficits in the frontal lobe, mirroring observations in the human brain. Obtaining iPSCs from patients with different CSF1R mutations is particularly valuable given the limitations of rodent and zebrafish models when studying adult-onset neurodegenerative diseases. The study also highlights significant metabolic changes associated with the CSF1R mutation, particularly in the HD2 mutant line, which is confirmed by the HD1 line. In addition, the work shows transcriptional upregulation of the proinflammatory cytokine IL-1beta in cells carrying the mutation, particularly when they phagocytose apoptotic cells, providing further insight into disease mechanisms.

Weaknesses:

The authors have not elucidated the significance of the increased CSF1 dosage in Figure 2F, aside from its effect on cell viability, lacking a thorough discussion of this result. Additionally, while transcriptomic and metabolic alterations related to the mutation were demonstrated in iMac models, similar investigations in iMicros are absent, necessitating further experiments to validate the findings across cell models. The conclusion drawn regarding cytokine levels lacks robust support from the data, particularly considering the varied responses observed in different mutant lines. Further analysis of the secretome (e.g. via ELISA) could provide additional insights. Moreover, the characterization of iMicros is incomplete, with limited protein-level analysis (e.g. validate RNA-seq via flow cytometry). Additionally, the claim of microglial-like morphology lacks adequate evidence, as the provided image is insufficient for such an assessment. RNA-seq experiments should be represented better, it is not possible to read the legends or gene names in the figures. Maybe the data sets can be combined into PCAone and one overall analysis, e.g. via WGCNA-like analyses? This would make it easier for the reader to compare the two cell lines side by side. Furthermore, inaccuracies and omissions in the figure legends compromise the clarity of data representation. Statistical test information is missing. Finally, inconsistent terminology usage throughout the paper may confuse readers (iMac versus iMicros).

Reviewer #3 (Public Review):

Summary:

Sperm-egg fusion is a critical step in successful fertilization. Although several proteins have been identified in mammals that are required for sperm-egg adhesion and fusion, it is still unclear whether there are other proteins involved in this process and how the reported proteins complex co-operate to complete the fusion process. In this study, the authors first identified TMEM81 as a structural homologue of IZUMO1 and SPACA6, and predicted the interactions with a pool of human proteins associated with gamete fusion, using AlphaFold-Multimer, a recent advance in protein complex structure prediction. The prediction is compelling and well discussed, and the experimental evidence to verify this interaction is lacking in this study but supported by a complementary and independent study by another group.

Strengths:

The authors present a pentameric complex formation of four previously reported proteins involved in egg/sperm interaction together with TMEM181 using a deep learning tool, AlphaFold-Multimer.

Weaknesses:

It is intriguing to see that some of the proteins involved in sperm-egg interaction are successfully predicted to be assembled into a single multimeric structure by AlphaFold-Multimer. The experimental validation of the interactions is not directly supported in this study. As there are more candidate proteins in the process, testing other possible protein interactions more comprehensively will provide more rationale for the current 3D multi-protein modeling.

Reviewer #2 (Public Review):

Summary:

In this manuscript, Cai et al use a combination of mouse transgenic lines to re-examine the question of the embryonic origin of telencephalic oligodendrocytes (OLs). Their tools include a novel Flp mouse for labelling mature oligodendrocytes and a number of pre-existing lines (some previously generated by the last author in Josh Huang's lab) that allowed combinatorial or subtractive labelling of oligodendrocytes with different origins. The conclusion is that cortically-derived OLs are the predominant OL population in the motor and somatosensory cortex and underlying corpus callosum, while the LGE/CGE generates OLs for the piriform cortex and anterior commissure rather than the cerebral cortex. Small numbers of MGE-derived OLs persist long-term in the motor, somatosensory and piriform cortex.

Strengths:

The strength and novelty of the manuscript lies in the elegant tools generated and used and which have the potential to elegantly and accurately resolve the issue of the contribution of different progenitor zones to telencephalic regions.

Weaknesses:

(1) Throughout the manuscript (with one exception, lines 76-78), the authors quantified OL densities instead of contributions to the total OL population (as a % of ASPA for example). This means that the reader is left with only a rough estimation of the different contributions.

(2) All images and quantifications have been confined to one level of the cortex and the potential of the MGE and the LGE/CGE to produce oligodendrocytes for more anterior and more posterior cortical regions remains unexplored.

(3) Hence, the statement that "In summary, our findings significantly revised the canonical model of forebrain OL origins (Figure 4A) and provided a new and more comprehensive view (Figure 4B )." (lines 111, 112) is not really accurate as the findings are neither new nor comprehensive. Published manuscripts have already shown that (a) cortical OLs are mostly generated from the cortex [Tripathi et al 2011 (https://doi.org/10.1523/JNEUROSCI.6474-10.2011), Winker et al 2018 (https://doi.org/10.1523/JNEUROSCI.3392-17.2018) and Li et al (https://doi.org/10.1101/2023.12.01.569674)] and (b) MGE-derived OLs persist in the cortex [Orduz et al 2019 (https://doi.org/10.1038/s41467-019-11904-4) and Li et al 2024 (https://doi.org/10.1101/2023.12.01.569674)]. Extending the current study to different rostro-caudal regions of the cortex would greatly improve the manuscript.

Reviewer #2 (Public Review):

Summary:

Latham A.P. et al. apply simulations and FLIM to analyse several di-block elastin-like polypetides and connect their sequence to the micro-structure of coacervates resulting from their phase-separation.

Strengths:

Understanding the molecular grammar of phase separating proteins and the connection with mesoscale properties of the coacervates is highly relevant. This work provides insights into micro-structures of coacervates resulting from di-block polypetides.

Weaknesses:

The results apply to a very specific architecture (di-block polypetides) with specific sequences.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

More than weakness I would speak of discussion points: I have a few suggestions that may help to make the paper more accessible to a general audience.<br /> (1) In the Introduction, when the authors introduce the term "micromolecules", it would be beneficial to provide a precise definition or clarification of what they mean by this term. Adding a brief explanation may help the reader to better understand the context.<br /> (2) In line 91, I suggest specifying that this is a renal IRI model.<br /> (3) Lines 167-168 state that Asct2 is localised to the apical side of the renal proximal tubules. Is there any expression of Asct2 in other nephron segments?<br /> (4) Lines 225-226: Have the authors expressed the candidate genes in HEK293 cells with ASCT2 knockdown?<br /> (5) lines 254-255: why was D-serine transport enhanced by ASCT2 knockdown in FlpInTR-SMCT1 or 2 cells?<br /> (6) line 265: The low affinity of SMCT1 for D-serine alone makes it an unlikely transporter for urinary D-serine.<br /> (7) line 316: The authors state that there is a high tubular D-serine reabsorption in IRI and in line 424 that there is an inactivation of DAAO during the pathology. This suggests that there is a reabsorption of D-serine mediated by a transport system in the basolateral membrane domain of proximal tubular cells. Do the authors have any information about this transporter?<br /> (8) in lines 462-463, the authors state: "It is suggested that PAT1 is less active at the apical membrane where the luminal pH is neutral". However, the pH of urine in the proximal tubules is normally acidic due to the high activity of NH3. I suggest rewording this sentence.

Reviewer #2 (Public Review):

Taken as a whole, the data in the manuscript show that BDNF can regulate PD-associated kinase LRRK2 and that LRRK2 modifies the BDNF response. The chief strength is that the data provide a potential focal point for multiple observations across many labs. Since LRRK2 has emerged as a protein that is likely to be part of the pathology in both sporadic and LRRK2 PD, the findings will be of broad interest. At the same time, the data used to imply a causal throughline from BDNF to LRRK2 to synaptic function and actin cytoskeleton (as in the title) are mostly correlative and the presentation often extends beyond the data. This introduces unnecessary confusion. There are also many methodological details that are lacking or difficult to find. These issues can be addressed.

(1) The writing/interpretation gets ahead of the data in places and this was confusing. For example, the abstract highlights prior work showing that Ser935 LRRK2 phosphorylation changes LRRK2 localization, and Figure 1 shows that BDNF rapidly increases LRRK2 phosphorylation at this site. Subsequent figures highlight effects at synapses or with synaptic proteins. So is the assumption that LRRK2 is recruited to (or away from) synapses in response to BDNF? Figure 2H shows that LRRK2-drebrin interactions are enhanced in response to BDNF in retinoic acid-treated SH-SY5Y cells, but are synapses generated in these preps? How similar are these preps to the mouse and human cortical or mouse striatal neurons discussed in other parts of the paper (would it be anticipated that BDNF act similarly?) and how valid are SH-SY5Y cells as a model for identifying synaptic proteins? Is drebrin localization to synapses (or its presence in synaptosomes) modified by BDNF treatment +/- LRRK2? Or do LRRK2 levels in synaptosomes change in response to BDNF? The presentation requires re-writing to stay within the constraints of the data or additional data should be added to more completely back up the logic.

(2) The experiments make use of multiple different kinds of preps. This makes it difficult at times to follow and interpret some of the experiments, and it would be of great benefit to more assertively insert "mouse" or "human" and cell type (cortical, glutamatergic, striatal, gabaergic) etc.

(3) Although BDNF induces quantitatively lower levels of ERK or Akt phosphorylation in LRRK2KO preps based on the graphs (Figure 4B, D), the western blot data in Figure 4C make clear that BDNF does not need LRRK2 to mediate either ERK or Akt activation in mouse cortical neurons and in 4A, ERK in SH-SY5Y cells. The presentation of the data in the results (and echoed in the discussion) writes of a "remarkably weaker response". The data in the blots demand more nuance. It seems that LRRK2 may potentiate a response to BDNF that in neurons is independent of LRRK2 kinase activity (as noted). This is more of a point of interpretation, but the words do not match the images.

(4) Figure 4F/G shows an increase in PSD95 puncta per unit length in response to BDNF in mouse cortical neurons. The data do not show spine induction/dendritic spine density/or spine morphogenesis as suggested in the accompanying text (page 8). Since the neurons are filled/express gfp, spine density could be added or spines having PSD95 puncta. However, the data as reported would be expected to reflect spine and shaft PSDs and could also include some nonsynaptic sites.

(5) Experimental details are missing that are needed to fully interpret the data. There are no electron microscopy methods outside of the figure legend. And for this and most other microscopy-based data, there are few to no descriptions of what cells/sites were sampled, how many sites were sampled, and how regions/cells were chosen. For some experiments (like Figure 5D), some detail is provided in the legend (20 segments from each mouse), but it is not clear how many neurons this represents, where in the striatum these neurons reside, etc. For confocal z-stacks, how thick are the optical sections and how thick is the stack? The methods suggest that data were analyzed as collapsed projections, but they cite Imaris, which usually uses volumes, so this is confusing. The guide (sgRNA) sequences that were used should be included. There is no mention of sex as a biological variable.

(6) For Figures 1F, G, and E, how many experimental replicates are represented by blots that are shown? Graphs/statistics could be added to the supplement. For 1C and 1I, the ANOVA p-value should be added in the legend (in addition to the post hoc value provided).

(7) Why choose 15 minutes of BDNF exposure for the mass spec experiments when the kinetics in Figure 1 show a peak at 5 mins?

(8) The schematic in Figure 6A suggests that iPSCs were plated, differentiated, and cultured until about day 70 when they were used for recordings. But the methods suggest they were differentiated and then cryopreserved at day 30, and then replated and cultured for 40 more days. Please clarify if day 70 reflects time after re-plating (30+70) or total time in culture (70). If the latter, please add some notes about re-differentiation, etc.

(9) When Figures 6B and 6C are compared it appears that mEPSC frequency may increase earlier in the LRRK2KO preps than in the WT preps since the values appear to be similar to WT + BDNF. In this light, BDNF treatment may have reached a ceiling in the LRRK2KO neurons.

(10) Schematic data in Figures 5A and C and Figures 5B and E are too small to read/see the data.

Reviewer #2 (Public Review):

Summary:

In this study, Amason et al employ spatial transcriptomics and intervention studies to probe the spatial and temporal dynamics of chemokines and their receptors and their influence on cellular dynamics in C. violaceum granulomas. As a result of their spatial transcriptomic analysis, the authors narrow in on the contribution of neutrophil- and monocyte-recruiting pathways to host response. This results in the observation that monocyte recruitment is critical for granuloma formation and infection control, while neutrophil recruitment via CXCR2 may be dispensable.

Strengths:

Since C. violaceum is a self-limiting granulomatous infection, it makes an excellent case study for 'successful' granulomatous inflammation. This stands in contrast to chronic, unproductive granulomas that can occur during M. tuberculosis infection, sarcoidosis, and other granulomatous conditions, infectious or otherwise. Given the short duration of C. violaceum infection, this study specifically highlights the importance of innate immune responses in granulomas.

Another strength of this study is the temporal analysis. This proves to be important when considering the spatial distribution and timing of cellular recruitment. For example, the authors observe that the intensity and distribution of neutrophil- and monocyte-recruiting chemokines vary substantially across infection time and correlate well with their previous study of cellular dynamics in C. violaceum granulomas.

The intervention studies done in the last part of the paper bolster the relevance of the authors' focus on chemokines. The authors provide important negative data demonstrating the null effect of CXCR1/2 inhibition on neutrophil recruitment during C. violaceum infection. That said, the authors' difficulty with solubilizing reparixin in PBS is an important technical consideration given the negative result. On the other hand, monocyte recruitment via CCR2 proves to be indispensable for granuloma formation and infection control. I would hesitate to agree with the authors' interpretation that their data proves macrophages are serving as a physical barrier from the uninvolved liver. It is possible and likely that they are contributing to bacterial control through direct immunological activity and not simply as a structural barrier.

Weaknesses:

There are several shortcomings that limit the impact of this study. The first is that the cohort size is very limited. While the transcriptomic data is rich, the authors analyze just one tissue from one animal per time point. This assumes that the selected individual will have a representative lesion and prevents any analysis of inter-individual variability. Granulomas in other infectious diseases, such as schistosomiasis and tuberculosis, are very heterogeneous, both between and within individuals. It will be difficult to assert how broadly generalizable the transcriptomic features are to other C. violaceum granulomas. Furthermore, this undermines any opportunity for statistical testing of features between time points, limiting the potential value of the temporal data.

Another caveat to these data is the limited or incompletely informative data analysis. The authors use Visium in a more targeted manner to interrogate certain chemokines and cytokines. While this is a great biological avenue, it would be beneficial to see more general analyses considering Visum captures the entire transcriptome. Some important questions that are left unanswered from this study are:

What major genes defined each spatial cluster?

What were the top differentially expressed genes across time points of infection?

Did the authors choose to focus on chemokines/receptors purely from a hypothesis perspective or did chemokines represent a major signature in the transcriptomic differences across time points?

In addition to the absence of deep characterization of the spatial transcriptomic data, the study lacks sufficient quantitative analysis to back up the authors' qualitative assessments. Furthermore, the authors are underutilizing the spatial information provided by Visium with no spatial analysis conducted to quantify the patterning of expression patterns or spatial correlation between factors.

Impact:

The author's analysis helps highlight the chemokine profiles of protective, yet host protective granulomas. As the authors comment on in their discussion, these findings have important similarities and differences with other notable granulomatous conditions, such as tuberculosis. Beyond the relevance to C. violaceum infection, these data can help inform studies of other types of granulomas and hone candidate strategies for host-directed therapy strategies.

Reviewer #2 (Public Review):

Summary:

This article takes an expansive look at the potential role of DUX4 in cancer treatment and prognosis, including its correlation with other key biomarkers, the potential for cancer to be resistant to treatment, and risk prediction.

Strengths:

The primary strength of this work is the breadth of the analyses. The authors have linked DUX4 to not just one but multiple points in the trajectory of cancer, which increases the face validity of their conclusion that DUX4 is meaningfully related to the course of a cancer as well as the prognosis for a patient.

Statistically, the authors have taken care to properly validate their findings using appropriate bootstrapping and testing strategies.

Weaknesses:

Several weaknesses are noted. First, there is little-to-no description of the underlying sample population. It is only stated that "several large cohorts of patients with different metastatic cancers" were analyzed, and that a cohort of patients with advanced urothelial cancer was used for estimating associations with clinical outcomes. Lacking is information on the sampling mechanism, inclusion/exclusion criteria, treatment modalities, the definition of 'time = 0', the number of events observed, or even the sample size. Knowledge about the underlying study design would help explain some counterintuitive results, e.g. that the hazard of death among patients with Stage IV cancer is half that of those with Stage I cancer (Table 1); presumably this is not because Stage IV is actually protective but rather an artifact of the sampling scheme for these data. Second, the definition of negative versus positive DUX4 expression varies throughout the paper. In Figure 2B, Figure 3A, and Figure 3C, it is defined as >1 TPM vs. <= 1 TPM; in Figure 4A and Figure 5A, it is defined as >1 TPM vs. < 0.25 TPM; in Figure S1C it is partitioned into four groups, with boundaries defined at 0.25 TPM, 1 TPM, and 5 TPM. If categorization is needed, a rationale should be provided (ideally prospectively and not based upon the observed data, so as to avoid the perception of forking paths analyses), and it should be consistently applied. Third and finally, data seem to be occasionally excluded without rationale. For example, as mentioned above, the Cox model presented in Figure 4A seems to exclude all patients with DUX4 TPM between 0.25 and 1. Figure 3C excludes patients with TMB in the lowest quartile (although the decision was ostensibly to control for TMB confounding, there are more appropriate ways to do so that don't result in loss of data, e.g. a stratified KM plot). Excluding patients based upon a particular region of the covariate space makes interpreting the resulting model awkward.

Reviewer #2 (Public Review):

Summary:

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

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

Strengths:

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

Weaknesses:

(1) The manuscript is hard to read without being very familiar with continuum descriptions of elastic media. This might make the work difficult to access for biologists. This is a real pity because the findings are potentially of great interest to developmental biologists and engineers alike.

(2) The discussion of the worm's mechanical properties could go deeper. The authors hardly justify their assumptions.

Reviewer #2 (Public Review):

As discussed in the original review, this manuscript is an important contribution to a mechanistic understanding of LRRK2 kinase. Kinetic parameters for the GTPase activity of the ROC domain have been determined in the absence/presence of kinase activity. A feedback mechanism from the kinase domain to GTP/GDP hydrolysis by the ROC domain is convincingly demonstrated through these kinetic analyses. However, a regulatory mechanism directly linking the T1343 phospho-site and a monomer/dimer equilibrium is not fully supported. The T1343A mutant has reduced catalytic activity and can form similar levels of dimer as WT. The revised manuscript does point out that other regulatory mechanisms can also play a role in kinase activity and GTP/GDP hydrolysis (Discussion section). The environmental context in cells cannot be captured from the kinetic assays performed in this manuscript, and the introduction contains some citations regarding these regulatory factors. This is not a criticism, the detailed kinetics here are rigorous, but it is simply a limitation of the approach. Caveats concerning effects of membrane localization, Rab/14-3-3 proteins, WD40 domain oligomers, etc... should be given more prominence than a brief (and vague) allusion to 'allosteric targeting' near the end of the Discussion.

Specific comments

(1) The revised version is better organized with respect to the significance of monomer/dimer equilibrium and the relevance of the GTP-binding region of ROC domain that encompasses the T1343 phospho-site. The relevance of monomers/dimers of LRRK2 from previous studies is better articulated and readers are able to follow the reasoning for the various mutations.

(2) As a suggestion I would change the following on page 6 to clarify for readers:<br /> "...would show no change in kcat and KM values upon in vitro ATP treatment" to:<br /> "...would show no change in kcat and KM values for GTP hydrolysis upon in vitro ATP treatment"

(3) The levels of dimer in WT (+ATP) and T1343A (+/- ATP) are the same, about 40-45%. These data are cited when the authors state that ATP-induced monomerization is 'abolished' (page 6). My suggestion is to re-phrase this conclusion for consistency with data (Fig 5). For example, one can state that 'ATP incubation does not affect the percentage of dimer for the T1343A variant of LRRK2'. This would be similar to the authors' description of these data on page 8 - 'no difference in dimer formation upon ATP treatment'.

Reviewer #2 (Public Review):

Zhao et al., focus on mechanisms through which cells convert from epithelium to mesenchyme and become migratory. This phenomenon of epithelial-to-mesenchymal transition (EMT) occurs during both embryonic development and cancer progression. During cancer progression, EMT seemingly includes cells at intermediate states as defined by the combinatorial expression of epithelial and mesenchymal markers. But the importance of these markers and the role of these intermediate states remains unclear. Moreover, whether EMT during development also involves equivalent intermediate cell states is not known. To address this gap in knowledge, the authors devise a strategy to identify and characterize changes that an embryonic population of cells called the cranial neural crest undergo as they delaminate from the neuroepithelium and become a highly migratory population of mesenchymal cells that ultimately give rise to a broad range of derivatives.

To isolate and study the neural crest, the authors use embryos collected at E8.5 from two transgenic mouse lines. Wnt1-Cre;RosaeYFP labels Wnt1-positive neuroepithelial cells in the dorsolateral neural plate, which includes pre-migratory neural crest that reside in the dorsal neuroectoderm and neural plate border before induction (as well as some other lineages). Mef2c-F10N-LacZ leverages a neural crest cell-specific enhancer of Mef2c to control LacZ expression in predominantly migratory neural crest. This dual genetic approach that allows the authors to distinguish and compare pre-migratory and migratory neural crest cells is a strength of the work.

To assay for the differential expression of genes involved in the EMT and migration of cranial neural crest, the authors perform single cell RNA sequencing (scRNA-seq) using current methods. A strength is a large sample size per mouse line, and relatively high numbers of single cells analyzed. The authors identify six major cell/tissue types present in mouse E8.5 cranial tissues using known markers, which they then segregate into a cranial neural crest cluster using a well-reasoned bioinformatic strategy. The cranial neural crest cluster contains pre-migratory and migratory cells that they partition further into five subclusters and then characterize using the differential expression and combinatorial patterns of neural crest specifier genes, markers of pre-migratory neural crest, markers of early versus late migratory neural crest, markers of undifferentiated versus differentiated neural crest, tissue-specific markers, and region-specific markers. One weakness is that there is little attempt to map potential novel genes and/or pathways that also distinguish these clusters.

The authors then go on to subdivide the five cranial neural crest subclusters into almost two dozen smaller subclusters, again using the combinatorial expression of known markers (e.g., neural crest genes, cell junction genes, and cell cycle genes). A weakness is that the marker analysis and accompanying interpretation of the results relies heavily on the purported roles of different genes as described in the published work of others, which potentially introduces some untested assumptions and a bit of hand-waving into the study. Moreover, the limited correlation between mRNA and protein abundance for cell cycle markers is well documented in the literature but the authors rely heavily on gene expression to determine cell cycle status. Even though the authors add a compelling Edu/pHH3 double-labeling experiment and cell cycle inhibition studies, the work would be strengthened by including some analysis of protein expression to see if the cell cycle correlations hold up. Nonetheless, the subcluster and cell cycle analyses lead the authors to conclude that there are a series of intermediate cell states between neural crest EMT and delamination, and that cell cycle regulation is a defining feature and necessary component of those states. These novel findings are generally well supported by the data.

To test if there are spatiotemporal differences in the localization of neural crest cells during EMT in vivo, the authors apply a cutting-edge technique called signal amplification by exchange reaction for multiplexed fluorescent in situ hybridization (SABER-FISH), which they validate using standard in situ hybridization. The authors select specific marker genes that seem justified based on their scRNA-seq dataset, and they generate a series of convincing images and quantitative data that add valuable depth to the story.

As a functional test of their hypothesis that one of the genes indicative of an EMT intermediate stage (i.e., Dlc1) is essential for neural crest migration, the authors use a lentivirus-mediated knockdown strategy. A strength is that the authors include appropriate scramble and cell death controls as part of their experimental design.

The authors use Sox10 as a marker to count neural crest cells, but Sox10 may only label a subset of neural crest cells and thus some unaffected lineages may not have been counted. Although the data are persuasive, a second marker for counting neural crest cells following knockdown would make the analysis more robust.

Overall, this is a first-rate study with many more strengths than weaknesses. The authors generate high quality data, and their interpretations are reasonable and balanced. Another strength is the writing, which is clear and well organized, and the figures (including supplemental), which are excellent and provide unambiguous visualization of some very complex data sets. The methods are state-of the art and are effectively executed, and they will be useful to the broader cell and developmental biology community. The work contains well-substantiated findings and supports the conclusion that EMT is a highly dynamic, multi-step process, which was previously thought to be more-or-less binary. Such findings will alter the way the field thinks about EMT in neural crest and the work will likely serve as an important example alongside cancer metastasis.

Reviewer #2 (Public Review):

Summary:

Syntaxin17 (STX17) is a SNARE protein that is recruited to mature (i.e., closed) autophagosomes, but not to immature (i.e., unclosed) ones, and mediates the autophagosome-lysosome fusion. How STX17 recognizes the mature autophagosome is an unresolved interesting question in the autophagy field. Shinoda and colleagues set out to answer this question by focusing on the C-terminal domain of STX17 and found that PI4P is a strong candidate that causes the STX17 recruitment to the autophagosome.

Strengths:

The main findings are: 1) Rich positive charges in the C-terminal domain of STX17 are sufficient for the recruitment to the mature autophagosome; 2) Fluorescence charge sensors of different strengths suggest that autophagic membranes have negative charges and the charge increases as they mature; 3) Among a battery of fluorescence biosensors, only PI4P-binding biosensors distribute to the mature autophagosome; 4) STX17 bound to isolated autophagosomes is released by treatment with Sac1 phosphatase; 5) By dynamic molecular simulation, STX17 TM is shown to be inserted to a membrane containing PI4P but not to a membrane without it. These results indicate that PI4P is a strong candidate that STX17 binds to in the autophagosome.

Weaknesses:

• It was not answered whether PI4P is crucial for the STX17 recruitment in cells because manipulation of the PI4P content in autophagic membranes was not successful for unknown reasons.<br /> • The question that the authors posed in the beginning, i.e., why is STX17 recruited to the mature (closed) autophagosome but not to immature autophagic membranes, was not answered. The authors speculate that the seemingly gradual increase of negative charges in autophagic membranes is caused by an increase in PI4P. However, this was not supported by the PI4P fluorescence biosensor experiment that showed their distribution to the mature autophagosome only. Here, there are at least two possibilities: 1) The increase of negative charges in immature autophagic membranes is derived from PI4P. However the fluorescence biosensors do not bind there for some reason; for example, they are not sensitive enough to recognize PI4P until it reaches a certain level, or simply, their binding does not occur in a quantitative manner. 2) The negative charge in immature membranes is not derived from PI4P, and PI4P is generated abundantly only after autophagosomes are closed. In either case, it is not easy to explain why STX17 is recruited to the mature autophagosome only. For the first scenario, it is not clear how the PI4P synthesis is regulated so that it reaches a sufficient level only after the membrane closure. In the second case, the mechanism that produces PI4P only after the autophagosome closure needs to be elucidated (so, in this case, the question of the temporal regulation issue remains the same).

Reviewer #2 (Public Review):

This useful investigation of learning-driven dynamics of cortical and some subcortical structures combines a novel in-scanner learning paradigm with interesting analysis approaches. The new task for reward-based motor learning is highly compelling and goes beyond the current state-of-the-art, but it is incomplete with respect to examining different signatures of learning, clarifying probed learning processes, and investigating changes in all relevant subcortical structures is incomplete and would benefit from more rigorous approaches. With the rationale and data presentation strengthened this paper would be of interest to neuroscientists working on motor control and reward-based learning.

Reviewer #3 (Public Review):

In this study, authors used the Drosophila model to characterize molecular details underlying traumatic brain injury (TBI). Authors used the transcriptomic analysis of astrocytes collected by FACS sorting of cells derived from Drosophila heads following brain injury and identified upregulation of multiple genes, such as Pvr receptor, Jun, Fos, and MMP1. Additional studies identified that Pvr positively activates AP-1 transciption factor (TF) complex consisting of Jun and Fos, of which activation leads to the induction of MMP1. Finally, authors found that disruption of endocytosis and endocytotic trafficking facilitates Pvr signaling and subsequently leads to induction of AP-1 and MMP1.

Overall, this study provides important clues to understanding molecular mechanisms underlying TBI. The identified molecules linked to TBI in astrocytes could be potential targets for developing effective therapeutics. The obtained data from transcriptional profiling of astrocytes will be useful for future follow-up studies. The manuscript is well-organized and easy to read.

However, the connection suggested by the authors between Pvr and AP-1, potentially mediated through the JNK pathway, lacks strong experimental support in my view. It's important to recognize that AP-1 activity is influenced by multiple upstream signaling pathways, not just the JNK pathway, which is the most well-characterized among them. Therefore, assuming that AP-1 transcriptional activity solely reflects the activity of the JNK pathway without additional direct evidence is unwarranted. To strengthen their argument, the study could benefit from direct evidence implicating the JNK pathway in linking Pvr to AP-1. This could be achieved through genetic studies involving mutants or transgenes targeting key components of the JNK pathway, such as Bsk and Hep, the Drosophila homologues of JNK and JNKK, respectively. Alternatively, employing p-JNK antibody-based techniques like Western blotting, while considering the potential challenges associated with p-JNK immunohistochemistry, could provide further validation. This important criticism regarding the molecular link between Pvr and AP-1 has been overlooked.

Reviewer #2 (Public Review):

In this work, Dasgupta et al. investigates the role of Sema7a in the formation of peripheral sensory circuit in the lateral line system of zebrafish. They show that Sema7a protein is present during neuromast maturation and localized, in part, to the base of hair cells (HCs). This would be consistent with pre-synaptic Sema7a mediating formation and/or stabilization of the synapse. They use sema7a loss-of-function strain to show that lateral line sensory terminals display abnormal arborization. They provide highly quantitative analysis of the lateral line terminal arborization to show that a number of specific topological parameters are affected in mutants. Next, they ectopically express a secreted form of Sema7a to show that lateral line terminals can be ectopically attracted to the source. Finally, they also demonstrate that the synaptic assembly is impaired in the sema7a mutant. Overall, the data are of high quality and properly controlled. The availability of Sema7a antibody is a big plus, as it allows to address the endogenous protein localization as well to show the signal absence in the sema7a mutant. The quantification of the arbor topology should be useful to people in the field who are looking at the lateral line as well as other axonal terminals. I think some results are overinterpreted though. The authors state: "Our findings demonstrate that Sema7A functions both as a juxtracrine and as a secreted cue to pattern neural circuitry during sensory organ development." However, they have not actually demonstrated which isoform functions in HCs (also see comments below). In addition, they have to be careful in interpreting their topology analysis, as they cannot separate individual axons. Thus, such analysis can generate artifacts. They can perform additional experiments to address these issues or adjust their interpretations.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

This is a mechanistic and well-designed paper that identifies DBT as a novel regulator of proteotoxicity via activating autophagy in the setting of proteasome inhibition. Major strengths include careful delineation of a mechanistic pathway to define how DBT is protective. These conclusions are well-justified.

Weaknesses:

None

Reviewer #2 (Public Review):

The application of rabies virus (RabV)-mediated transsynaptic tracing has been widely utilized for mapping cell-type-specific neural connectivities and examining potential modifications in response to biological phenomena or pharmacological interventions. Despite the predominant focus of studies on quantifying and analyzing labeling patterns within individual brain regions based on labeling abundance, such an approach may inadvertently overlook systemic alterations. There exists a considerable opportunity to integrate RabV tracing data with the global connectivity patterns and the transcriptomic signatures of labeled brain regions. In the present study, the authors take an important step towards achieving these objectives.

Specifically, the authors conducted an intensive reanalysis of a previously generated large dataset of RabV tracing to the ventral tegmental area (VTA) using dimension reduction methods such as PCA and UMPA. This reaffirmed the authors's earlier conclusion that different cell types in the VTA, namely dopamine neurons (DA) and GABAergic neurons, exhibit quantitatively distinct input patterns, and a single dose of addictive drugs, such as cocaine and morphine, induced altered labeling patterns. Additionally, the authors illustrate that distinct axes of PCA can discriminate experimental variations, such as minor differences in the injection site of viral tracers, from bona fide alternations in labeling patterns caused by drugs of abuse. While the specific mechanisms underlying altered labeling in most brain regions remain unclear, whether involving synaptic strength, synaptic numbers, pre-synaptic activities, or other factors, the present study underscores the efficacy of an informatics approach in extracting more comprehensive information from the RabV-based circuit mapping data.

Moreover, the authors showcased the utility of their previously devised bulk gene expression patterns inferred by the Allen Gene Expression Atlas (AGEA) and "projection portrait" derived from bulk axon mapping data sourced from the Allen Mouse Brain Connectivity Atlas. The utilization of such bulk data rests upon several limitations. For instance, the collection of axon mapping data involves an arbitrary selection of both cell type-specific and non-specific data, which might overlook crucial presynaptic partners, and often includes contamination from neighboring undesired brain regions. Concerns arise regarding the quantitativeness of AGEA, which may also include the potential oversight of key presynaptic partners. Nevertheless, the authors conscientiously acknowledged these potential limitations associated with the dataset.

Notably, building on the observation of a positive correlation between the basal expression levels of Ca2+ channels and the extent of drug-induced changes in RabV labeling patterns, the authors conducted a CRISPRi-based knockdown of a single Ca2+ channel gene. This intervention resulted in a reduction of RabV labeling, supporting that the observed gene expression patterns have causality in RabV labeling efficiency. While a more nuanced discussion is necessary for interpreting this result (see below), overall I commend the authors for their efforts to leverage the existing dataset in a more meaningful way. This endeavor has the potential to contribute significantly to our understanding of the mechanisms underlying alterations in RabV labeling induced by drugs of abuse.

Finally, drawing upon the aforementioned reanalysis of previous data, the authors underscored that a single administration of ketamine/xylazine anesthesia could induce enduring modifications in RabV labeling patterns for VTA DA neurons, specifically those projecting to the nucleus accumbens and amygdala. Given the potential impact of such alterations on motivational behaviors at a broader level, I fully agree that prudent consideration is warranted when employing ketamine/xylazine for the investigation of motivational behaviors in mice.

Specific Points:

(1) Beyond advancements in bioinformatics, readers may find it insightful to explore whether the PCA/UMPA-based approach yields novel biological insights. For example, the authors are encouraged to discuss more functional implications of PBN and LH in the context of drugs of abuse, as their labeling abundance could elucidate the PC2 axis in Fig. 2M.

2) While I appreciate the experimental data on Cacna1e knockdown, I am unclear about the rationale behind specifically focusing on Cacna1e. The logic behind the statement, "This means that expression of this gene is not inhibitory towards RABV transmission," is also unclear. Loss-of-function experiments only signify the necessity or permissive functions of a gene. In this context, Cacna1e expression levels are required for efficient RabV labeling, but this neither supports nor excludes the possibility that this gene expression instructively suppresses RabV labeling/transmission, which could be assessed through gain-of-function experiments.

Reviewer #3 (Public Review):

The work proposes a model of neural information processing based on a 'synergistic global workspace,' which processes information in three principal steps: a gatekeeping step (information gathering), an information integration step, and finally, a broadcasting step. They provided an interpretation of the reduced human consciousness states in terms of the proposed model of brain information processing, which could be helpful to be implemented in other states of consciousness. The manuscript is well-organized, and the results are important and could be interesting for a broad range of literature, suggesting interesting new ideas for the field to explore.

Comments on revised version:

The authors have addressed all my comments made in the previous revision.

Reviewer #3 (Public Review):

Strengths:<br /> There are many reports on the effect of chemical properties of foods on feeding in fruit flies, but only limited studies reported how physical properties of food affect feeding especially pharyngeal mechanosensory neurons. First, they found that mechanosensory mutants, including nompC, Tmc, and Piezo, showed impaired swallowing, mainly the emptying process. Next, they identified cibarium multidendritic mechanosensory neurons (md-C) are responsible for controlling swallowing by regulating motor neuron (MN) 12 and 11, which control filling and emptying, respectively.

Weaknesses:<br /> While the involvement of md-C and mechanosensory channels in controlling swallowing is convincing, it is not yet clear which stimuli activate md-C. Can it be an expansion of cibarium or food viscosity, or both? In addition, if rhythmic and coordinated contraction of muscles 11 and 12 is essential for swallowing, how can simultaneous activation of MN 11 and 12 by md-C achieve this? Finally, previous reports showed that food viscosity mainly affects the filling rather than the emptying process, which seems different from their finding.

Reviewer #2 (Public Review):

Summary:

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

Strengths:

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

Weaknesses:

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

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

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

Reviewer #2 (Public Review):

Summary:

Canonically cerebellar neurons are derived from 2 primary germinal zones within the anterior hindbrain (dorsal rhombomere 1). This manuscript identifies an important, previously underappreciated origin for a subset of early cerebellar nuclei neurons - the dorsal mesencephalon. This is an exciting finding. While the conclusions are generally supported, several of the figure panels are of inferior quality and do not readily convey the results the authors assert.

Strengths:

The authors have identified a novel early population of cerebellar neurons with likely novel origin in the midbrain. They have used multiple assays to support their conclusions, including immunohistochemistry and in situ analyses of a number of markers of this population which appear to stream from the midbrain into the dorsal anterior cerebellar anlage.

The inclusion of Otx2-GFP short-term lineage analyses and analysis of Atoh1 -/- animals also provide considerable support for the midbrain origin of these neurons as streams of cells seem to emanate from the midbrain. However, without live imaging, there remains the possibility that these streams of cells are not actually migrating, and rather, gene expression is changing in static cells. Hence the authors have conducted midbrain diI labelling experiments of short-term and long-term cultured embryos showing di-labelled cells in the developing cerebellum. These studies confirm the migration of cells from the midbrain into the early cerebellum.

Reviewer #2 (Public Review):

Summary:

Disruption of the excitatory/inhibitory (E/I) balance has been reported in Autism Spectrum Disorders (ASD), with which PTEN mutations have been associated. Giunti et al choose to explore the impact of PTEN mutations on the balance between E/I signaling using as a platform the C. elegans neuromuscular system where both cholinergic (E) and GABAergic (I) motor neurons regulate muscle contraction and relaxation. Mutations in daf-18/PTEN specifically affect morphologically and functionally the GABAergic (I) system, while leaving the cholinergic (E) system unaffected. The study further reveals that the observed defects in the GABAergic system in daf-18/PTEN mutants are attributed to reduced activity of DAF-16/FOXO during development.

Moreover, ketogenic diets (KGDs), known for their effectiveness in disorders associated with E/I imbalances such as epilepsy and ASD, are found to induce DAF-16/FOXO during early development. Supplementation with β-hydroxybutyrate in the nematode at early developmental stages proves to be both necessary and sufficient to correct the effects on GABAergic signaling in daf-18/PTEN mutants.

Strengths:

The authors combined pharmacological, behavioral, and optogenetic experiments to show the GABAergic signaling impairment at the C. elegans neuromuscular junction in DAF-18/PTEN and DAF-16/FOXO mutants. Moreover, by studying the neuron morphology, they point towards neurodevelopmental defects in the GABAergic motoneurons involved in locomotion. Using the same set of experiments, they demonstrate that a ketogenic diet can rescue the inhibitory defect in the daf-18/PTEN mutant at an early stage.

Weaknesses:

The morphological experiments hint towards a pre-synaptic defect to explain the GABAergic signaling impairment, but it would have also been interesting to check the post-synaptic part of the inhibitory neuromuscular junctions such as the GABA receptor clusters to assess if the impairment is only presynaptic or both post and presynaptic.

Moreover, all observations done at the L4 stage and /or adult stage don't discriminate between the different GABAergic neurons of the ventral nerve cord, ie the DDs which are born embryonically and undergo remodeling at the late L1 stage, and VDs which are born post-embryonically at the end of the L1 stage. Those additional elements would provide information on the mechanism of action of the FOXO pathway and the ketone bodies.

Conclusion:

Giunti et al provide fundamental insights into the connection between PTEN mutations and neurodevelopmental defects through DAF-16/FOXO and shed light on the mechanisms through which ketogenic diets positively impact neuronal disorders characterized by E/I imbalances.

Reviewer #2 (Public Review):

Summary:<br /> In this work, the authors combine diffusion MRI and high-resolution x-ray synchrotron phase-contrast imaging in monkey and mouse brains to investigate the 3D organization of brain white matter across different scales and species. The work is at the forefront of the anatomical investigation of the human connectome and aligns with several current efforts to bridge the resolution gap between what we can see in vivo at the millimeter scale and the complexity of the human brain at the sub-micron scale. The authors compare the 3D white matter organization across modalities within 2 small regions in one monkey brain (body of the corpus callosum, centrum semiovale) and within one region (splenium of the corpus callosum) in healthy mice and in one murine model of focal demyelination. The study compares measures of tissue anisotropy and fiber orientations across modalities, performs a qualitative comparison of fasciculi trajectories across brain regions and tissue conditions using streamlined tractography based on the structure tensor, and attempts to quantify the shape of fasciculi trajectories by measuring the tortuosity index and the maximum deviation for each reconstructed streamline. Results show measures of anisotropy and fiber orientations largely agree across modalities, especially for larger FOV data. The high-resolution data allows us to explore the fiber trajectories in relation to tissue complexity and pathology. The authors claim the study reveals new common organization principles of white matter fibers across species and scales, for which axonal fasciculi arrange into sheet-like laminar structures.

Strengths:

The aim of the study is of central importance within present efforts to bridge the gap between macroscopic structures observable in vivo in humans using conventional diffusion MRI and the microscopic organization of white matter tissue. Results obtained from this type of study are important to interpret data obtained in vivo, inform the development of novel methodologies, and expand our knowledge of the structural and thus functional organization of brain circuits.

Multi-scale data acquired across modalities within the same sample constitute extremely valuable data that is often hard to acquire and represent a precious resource for validation of both diffusion MRI tractography and microstructure methods.

The inclusion of multi-species data adds value to the study, allowing the exploration of common organization principles across species.

The addition of data from a murine cuprizone model of focal demyelination adds interesting opportunities to study the underlying biological changes that follow demyelination and how these impact tissue anisotropy and fiber trajectories. These data can inform the interpretation and development of diffusion MRI microstructure models.

Weaknesses:

The main claim of a newly discovered laminar organization principle that is consistent across scales and species is not supported strongly enough by the data. The main evidence in support of the claim comes from the larger FOV data obtained from the body of the corpus callosum in the monkey brain. A laminar organization principle is partially shown in the centrum semiovale in the monkey brain and it is not shown in mice data. Additionally, the methods lack details to help the correct interpretation of these findings (e.g., how were these fasciculi defined?; how well do they represent different axonal populations?; what is the effect of blood vessels on the structure tensor reconstruction?; how was laminar separation quantified?) and the discussion does not provide a biological background for this organization. The corpus callosum sample suggests axons within a bundle of fibers are organized in a sheet-like fashion, while data from the centrum semiovale suggest fibers belonging to different fiber bundles are organized in a sheet-like arrangement. While I acknowledge the challenges in acquiring such high-resolution data, additional samples from different regions in the same animals and from different animals would help strengthen this claim.

The main goal of the study is to bridge the organization of white matter across anatomical length scales and species. However, given the substantial difference in FOVs between the two imaging modalities used, and the absence of intermediate-resolution data, it remains difficult to effectively understand how these results can be used to inform conventional diffusion MRI. In this sense, the introduction does not do a good enough job of building a strong motivation for the scientific questions the authors are trying to answer with these experiments and for the specific methodology used.

The cuprizone data represent a unique opportunity to explore the effect of demyelination on white matter tissue. However, this specific part of the study is not well motivated in the introduction and seems to represent a missed opportunity for further exploration of the qualitative and quantitative relationship between diffusion MRI and sub-micron tissue information (although unfortunately not within the same brain sample). This is especially true considering the diffusion MRI protocol for mice would allow extrapolation of advanced measures from different tissue compartments.

Reviewer #2 (Public Review):

Summary:

The submitted manuscript by Michaud and Francavilla et al., is a very interesting study describing early disruptions in the disinhibitory modulation exerted by VIP+ interneurons in CA1, in a triple transgenic model of Alzheimer's disease. They provide a comprehensive analysis at the cellular, synaptic, network, and behavioral level on how these changes correlate and might be related to behavioral impairments during these early stages of the disease.

Main findings:

- 3xTg mice show early Aß accumulation in VIP-positive interneurons.

- 3xTg mice show deficits in a spatially modified version of the novel object recognition test.

- 3xTg mice VIP cells present slower action potentials and diminished firing frequency upon current injection.

- 3xTg mice show diminished spontaneous IPSC frequency with slower kinetics in Oriens / Alveus interneurons.

- 3xTg mice show increased O/A interneuron activity during specific behavioral conditions.

- 3xTg mice show decreased pyramidal cell activity during specific behavioral conditions.

Strengths:

This study is very important for understanding the pathophysiology of Alzheimer´s disease and the crucial role of interneurons in the hippocampus in healthy and pathological conditions.

Weaknesses:

Although results nicely suggest that deficits in VIP physiological properties are related to the differences in network activity, there is no demonstration of causality.

Reviewer #2 (Public Review):

Original Review:

In this study Mao and co-workers deliver a substantial suite of genetic tools in support of the senior author's recent proposal to create a "chemoconnectomic" tool kit for the expression mapping and conditional disruption of specific neurotransmitter systems with fly neurons of interest. Specifically, they describe the creation of two toolsets for recombination-based and CRISPR/Cas9-based conditional knockouts of genes supporting neurotransmitter and neuromodulator function and Flp-Out and Split-LexA toolkit for the examination of gene expression within defined subsets of neurons. The authors report the creation of conditional genetic tools for the disruption/mapping of approximately 200 chemoconnectomic gene products, an examination of the general effectiveness of these tools in the fly brain and apply them to the circadian clock network in an attempt to reveal new information regarding the transmitter/modulator systems involved in daily behavioral timing. The authors provide clear evidence of the effectiveness of the new methods along with a transparent assessment of the variability of the tools. In addition, they present evidence that the neuro peptide CNMa influences the morning peak of daily activity in the fly by regulating the timing of activity increases in anticipation of dawn.

A major strength of the study is the transparent assessment of the effectiveness and variability of the conditional genetic approaches developed by the authors. The authors have largely achieved their aims and the study therefore represents a major delivery on the promise of chemoconnectomics made by the senior author in 2019 (Neuron, Vol. 101, p. 876). Though there are some concerns about the variability of knockout effectiveness, off target effects of the knockout strategies, and (especially) the accuracy of the gene expression approach, the tools created for this study will almost certainly be useful for the field and support a great deal of future work.

Comments on revised version:

The authors have responded to each of my concerns. Most importantly, they have made the discrepancies within the study and between the study and previously published work clearer to the reader. they have also corrected statements that are not consistent with the current state of the field. The issue regarding opposing effects of PDF signaling and CNMa, which was also raised by Reviewer One still stands, notwithstanding the edits made to the text.

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):

This useful investigation of learning-driven dynamics of cortical and some subcortical structures combines a novel in-scanner learning paradigm with interesting analysis approaches. The new task for reward-based motor learning is compelling and goes beyond the current state of the art. The results are of interest to neuroscientists working on motor control and reward-based learning.

Comments on revised version:

The revision has produced a stronger manuscript. Thank you for your thorough responses to the comments and concerns.

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:

The manuscript by Gao et al. described a study identifying the role of FAK in fine-tuning the activation levels of ERK signaling in BRAF-V600E-driven colorectal cancer. The authors generated new mouse models combining Vill-Cre mediated BRAF-V600E expression with FAK deletion. Analyses of intestinal tumor phenotypes revealed that FAK-loss promotes BRAF-V600E-induced tumor formation, specifically in the cecum. Interestingly, these tumors closely resemble human sessile serrated adenoma/polyps. Using bioinformatics analysis, the authors found that FAK deletion upregulates the intestinal stem cell and fetal-type transcriptomic signatures compared to mice expressing BRAF-V600E alone. In addition, FAK-loss decreases the phosphorylation of ERK whereas it increases the expression of Lgr4 at both mRNA and protein levels. To mechanistically connect FAK-mediated downregulation of ERK and upregulation of Lgr4 in the context of BRAF-V600E mutation, results from biochemical experiments showed that MEK inhibitor treatment decreases the expression of NEDD4, a previously identified ubiquitin E3 ligase of Lgr4, which coincides with increased Lgr4 protein expression both in cells and in vivo. Moreover, the FAK-dependent modulation of ERK signaling is specific to BRAF-V600E-driven tumorigenesis only as knockout of FAK has no effect in Vill-Cre/KRAS-G12D mice. Collectively, the authors proposed a "just right" model in that a tunable FAK expression controls the optimal level of ERK pathway output needed for BRAF-V600E-induced cecal tumor formation.

Strengths:

This study provides new insights into the mechanisms underlying the serrated pathway-driven tumorigenesis in colorectal cancer. The newly established mouse model with compound mutations of BRAF and FAK offers a useful resource for future studies of the serrated pathway. The conclusions of this paper are mostly supported by data.

Weaknesses:

However, some aspects of the paper can be strengthened with additional mechanistically focused experiments.

(1) Some of the conclusions of the paper mainly rely on bioinformatic analyses of RNA-seq data. For example, it has been noted in several places in the paper that the knockout of FAK in Vill-Cre/BRAF-V600E mice does not affect the transcriptional outcome downstream of ERK while ERK phosphorylation levels are decreased. This statement is based on the lack of significant difference in the MAPK signature according to GSEA. However, whereas a significant enrichment of certain pathways can be used as support evidence, the lack of enrichment does not necessarily indicate those pathways are not involved. Other experiments are needed to examine the expression of ERK target genes to confirm. Similarly, the upregulation of fetal stem cell signature in FAK knockout mice needs to be verified using other methods besides GSEA.

(2) According to Figure 5i, the half-life of Lgr4 is around 48 hours in HT29 cells. However, it has been reported by at least two other publications cited in this paper (Ref. 44 and 45) that the half-life of Lgr4 is much shorter. This discrepancy is not explained.

(3) The effect of decreased ERK signaling on NEDD4 expression has only been briefly explored in Figure 6. The mechanisms by which FAK-loss and/or inhibition of MEK/ERK activity regulate NEDD4 expression are currently unclear. Moreover, the levels of NEDD4 expression are only analyzed in one mouse per group in Figure 6a. Quantitative analysis of NEDD4 as well as Lgr4 expression in additional numbers of mice will provide more solid support for the inverse correlation between NEDD4 and Lgr4 proteins. Since MEK inhibitor treatment also increases Lgr4 mRNA expression as shown in Figure 5f-g, the relative contribution of this altered mRNA expression vs. NEDD4L-mediated ubiquitination has not been investigated.

(4) It is an interesting finding that knockout FAK has no effect on KRAS-G12D-driven hyperplasia as shown in Figure 7. However, additional studies are needed to further explore the potential mechanisms by which FAK-loss specifically decreases EGFR/ERK signaling in the context of BRAF-V600E mutation.

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.